nopperl/pmc-image-text · Datasets at Hugging Face

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0.466279	6de0f4c0020644b5b0be3ea29ec2a030	Receiver operating characteristic (ROC) curves for predictors of mortality in the COVID-19 cohort (n=74). CRP, C reactive protein; LDH, lactate dehydrogenase; gbCR, glass-bead test Clot Rate; gbPA, glass-bead test Peak Amplitude.	PMC9062462	bmjopen-2021-051971f04.jpg
0.394458	99b43645f4bb4d7693af857ff606281b	FE-SEM images of pLys-HAp composites: (a) α-pLys-HAp (20 mg), (b) α-pLys-HAp (30 mg), (c) α-pLys-HAp (40 mg), (d) ε-pLys-HAp (20 mg), (e) ε-pLys-HAp (30 mg) and (f) ε-pLys-HAp (40 mg). The insets in (a–f) show TEM images of each sample.	PMC9062467	c9ra01764j-f1.jpg
0.48906	f9baa4fd2fbf491e8095d2ac45ef2bbe	(A) X-ray diffraction patterns of (a) α-pLys-HAp (20 mg), (b) α-pLys-HAp (30 mg), (c) α-pLys-HAp (40 mg), (d) ε-pLys-HAp (20 mg), (e) ε-pLys-HAp (30 mg) and (f) ε-pLys-HAp (40 mg), respectively (JCPDS card no. 09-0432). (B) FT-IR spectra of (a) α-pLys-HAp (20 mg), (b) α-pLys-HAp (30 mg), (c) α-pLys-HAp (40 mg), (d) pure α-pLys, (e) ε-pLys-HAp (20 mg), (f) ε-pLys-HAp (30 mg), (g) ε-pLys-HAp (40 mg) and (h) pure ε-pLys, respectively.	PMC9062467	c9ra01764j-f2.jpg
0.392276	12caa311ae9043e9bb659cf8f0f37133	STEM images and EDX maps of elements of (A) α-pLys-HAp (40 mg) and (B) ε-pLys-HAp (40 mg). Yellow, green and red colours display nitrogen, calcium and phosphorus elements, respectively.	PMC9062467	c9ra01764j-f3.jpg
0.545375	9675ca4c68824910b2b8a1681861c5d8	Adsorption isotherm curves for GOX on α-pLys-HAp (40 mg) and ε-pLys-HAp (40 mg).	PMC9062467	c9ra01764j-f4.jpg
0.404961	ec17d88bd3c5458095b834ec4bf467b7	(A) Fluorescence spectra of free and immobilised GOX. (B) The three-dimensional structure of GOX was obtained from Protein Data Bank; ID: 1CF3. Hydrophobic amino residues in GOX were emphasised using red colour.	PMC9062467	c9ra01764j-f5.jpg
0.4578	a295e7a954294781a99ea11f1c3feb16	The Lineweaver–Burk plots of free and immobilised GOX.	PMC9062467	c9ra01764j-f6.jpg
0.521998	f7d7b7c09c944cb39558a199990cc267	Remaining activity of GOX immobilised on pLys-HAp in cycling test.	PMC9062467	c9ra01764j-f7.jpg
0.521671	57c45088931d4b0cb7bf71cb8c630f9d	The glucose-sensitivity using GOX (free and immobilised on pLys-HAp). The inset shows the plot in the range of 4–80 μM of glucose.	PMC9062467	c9ra01764j-f8.jpg
0.497781	2994f7add3fb4b53ab6a01a96092fd15	Cyclic voltammograms of (A) graphene/imogolite/GOX/α-pLys-HAp (40 mg)-modified GCE and (B) graphene/imogolite/GOX/ε-pLys-HAp (40 mg)-modified GCE for the addition of 0–2.0 mM glucose in O2-saturated Dulbecco's PBS (pH 7.3) at a scan rate of 100 mV s−1. The insets in (A) and (B) show the linear plots for the concentration of glucose vs. peak current.	PMC9062467	c9ra01764j-f9.jpg
0.46558	653b98f0a74a45feb399cc4e0d9b237f	Aneurysm wall pathophysiology and progression. (a) The normal arterial vessel wall consists of an inner endothelial layer (tunica intima) followed by the two strength layers: internal elastic lamina and the smooth-muscle of the tunica media. Dotted line represents the region of the cross-sectional image displayed on the left (b) Regions of high WSS (blue arrow) (e.g., vessel bifurcations and outer wall of curved vessels) trigger an inflammatory cascade, increased protease activity, and breakdown of the tunica media and internal elastic lamina. Loss of integrity of the strength layers of the vessel wall cause outpouching of the vessel wall and formation of an early aneurysm bulge. (c) Enlargement of the aneurysm sac alters the flow dynamics, leading to areas of low WSS and high WSS (blue arrows). Areas of low WSS can develop thrombus, which trigger further inflammation and wall breakdown. Areas of persistent high WSS continue to experience protease activity and inflammation leading to continues degradation of the tunica media and internal elastic lamina.	PMC9062958	SNI-13-182-g001.jpg
0.441664	d2abe0ec2a784d859ffccd61aa27e0ab	High-risk aneurysm morphologies. (a) Standard saccular aneurysm morphology. (b) Aneurysm with daughter sac. (c) Aneurysm with high aspect ratio. (d) Aneurysm with high size ratio.	PMC9062958	SNI-13-182-g002.jpg
0.407504	de3b70d59d234f59b607240f74e49018	The total length stacked bar chart of 26 Ligusticum plastomes composed of four regions (LSC, IRb, SSC, and IRa). The numbers on the bar represent the length of the four regions. A–K Represents the genes at IR/SC borders. A ycf2; B petB; C rpl22; D rps19; E ycf1/ndhF; F ycf1; G trnN-GUU-ndhF; H trnL-CAA-trnH-GUG; I petB-trnH-GUG; J rps19-trnH-GUG; K rpl2-trnH-GUG. All the SSC/IRa borders are ycf1, which is indicated by asterisks	PMC9063207	12862_2022_2010_Fig1_HTML.jpg
0.543402	fba8fa4f62e94f9dad939fbb6fb0a371	Comparison of the GC content (GC%) of 26 Ligusticum plastomes using a radar-plot. From inside to out: SSC GC%, LSC GC%, Total GC%, IR GC%, and rRNA GC%. The background colors of purple, green, blue, and pink represent Selineae, Sinodielsia Clade, Acronema Clade, and East-Asia Clade, respectively	PMC9063207	12862_2022_2010_Fig2_HTML.jpg
0.424184	4fe0cf129fc343e1b38612ab9747db57	The RSCU values of 53 merged protein-coding sequences for 26 Ligusticum plastomes. Color key: the red values indicate higher RSCU values and the blue values indicate lower RSCU values	PMC9063207	12862_2022_2010_Fig3_HTML.jpg
0.389253	e1276ce301a94e1d812f5cdc27247e10	The dN/dS (ω) and nucleotide diversity (Pi) of the 79 protein-coding sequences within 26 Ligusticum plastomes	PMC9063207	12862_2022_2010_Fig4_HTML.jpg
0.476195	85f8bb8e3b2c4802b29629ceba6905bb	Phylogenetic relationships inferred from Maximum likelihood (ML) and Bayesian inference (BI) analyses based on 66 complete plastomes within Apiaceae. The bootstrap support values (BS) and posterior probabilities (PP) are listed at each node	PMC9063207	12862_2022_2010_Fig5_HTML.jpg
0.442818	ecc365fec3294bf38b3bd7b5f8168a48	Phylogenetic relationships of 66 Apiaceae species inferred from 76 common protein-coding sequences based on the coalescent-based approach using ASTRAL. The local posterior probabilities (LPP) are listed at each node	PMC9063207	12862_2022_2010_Fig6_HTML.jpg
0.433789	69aa5f9afa5946dba1c812dda3a35124	UV-vis absorption spectra of P(O-DBND-2T), P(N,O-DBND-2T) and P(N-DBND-2T) in diluted o-DCB (a) and as the thin film (b).	PMC9063523	c9ra01545k-f1.jpg
0.405163	37422eea578c44829ecbb238f0e013b1	Photovoltaic characteristics: J–V curves (a) and EQE (b) plots of polymer : PC71BM (1 : 2 w/w) optimal solar cells under the illumination of AM 1.5 G 100 mW cm−2.	PMC9063523	c9ra01545k-f2.jpg
0.456152	422396f7326a4e389f81d2a9a9358176	GIWAXS curves of polymer neat films (a) and TEM images of active layers containing P(N,O-DBND-2T) : PC71BM (b), P(O-DBND-2T) : PC71BM (c) and P(N-DBND-2T) : PC71BM (d) in weight ratio of 1 : 2.	PMC9063523	c9ra01545k-f3.jpg
0.446769	694e511aa61545a28e2f9e95d46029d0	Chromatograms (distribution of n-alkanes for the test oils).	PMC9064330	c9ra02775k-f1.jpg
0.429916	56fdbc764ede45ecadaf029aab91d789	Submerged oils formed observed by UV epi-fluorescence. Fluorescing green indicates the oil droplets.	PMC9064330	c9ra02775k-f2.jpg
0.477304	40babe3e3bb043c8ac805c5ff7f3a513	Adsorption isotherms of the three test oils. Note: the dash lines are the fitted line using the Langmuir isotherm.	PMC9064330	c9ra02775k-f3.jpg
0.466554	3a3382365fc84070a5a7e2d46fce8f3b	The kinetics of submerged oil formation for the three test oils. Note: the dashed lines are fitted by eqn (4).	PMC9064330	c9ra02775k-f4.jpg
0.450702	994bdf1c6a484ccb9435a302c9ffe5c7	Modeling of predicting the submerged oils formation as a function of sediment concentrations. The dash lines represent the model results computed using eqn (7) based on Kd = 0.5 and 1.5 mL mg−1. Note: The use of chemical dispersant and change of salinity lead to deviate from model results.	PMC9064330	c9ra02775k-f5.jpg
0.445267	0de5b0dabbeb4056876821eb75124976	Cell viability of ATP and UTP-treated cells. TNBC MDA-MB 231, Hs 578t and MDA-MB 468 cell lines and non-tumorigenic immortal mammary epithelial MCF-10A cells were treated for 48 hours with increasing concentrations of ATP or UTP, and cell viability was measured with the PrestoBlue HS assay. Error bars represent standard deviations calculated from three independent experiments performed in triplicate. The student’s t-test was applied to the to ascertain significance. * represents p < 0.05 and ** represents p < 0.01 when comparing ATP to UTP.	PMC9065442	fonc-12-855032-g001.jpg
0.397869	4bd33f59abce4da0915850e75dff551b	Cell viability of ATP-treated cells in the presence of P2RX inhibitors. TNBC cell lines and MCF-10A cells were treated for 48 hours with increasing concentrations of ATP in the presence of the P2RX inhibitor Iso-PPADS (20 µmol/L), the P2RX7 inhibitor A438079 (20 µmol/L) or the P2RX4 inhibitor 5-BDBD (20 µmol/L) or vehicle addition, and cell viability was measured using the PrestoBlue HS assay. Error bars represent standard deviations calculated from three independent experiments performed in triplicate. One way ANOVA with Tukey’s HSD was applied to ascertain significance. * represents p < 0.05 and ** represents p < 0.01 when comparing vehicle addition to Iso-PPADS, A438079 or 5-BDBD.	PMC9065442	fonc-12-855032-g002.jpg
0.549365	0bc4a7c8d8524dfe821ac99ff76e3b30	Comparing eATP release from paclitaxel-treated cells in the presence of inhibitors or vehicle addition. (A) TNBC and MCF-10A cells were treated with increasing concentrations of paclitaxel and the nucleoside phosphohydrolase inhibitors POM-1 (E-NTPDase inhibitor, 10 µmol/L), PSB 069 (E-NTPDase inhibitor, 10 µmol/L), ENNP1 inhibitor C (ENPP1 inhibitor, 10 µmol/L) or vehicle addition for six hours, and cell viability was measured using the PrestoBlue HS assay. Standard deviation was calculated from three independent experiments performed in triplicate. (B) eATP concentrations were measured in the supernatants of TNBC and MCF-10A cells after six hours of treatment with increasing concentrations of paclitaxel and nucleoside phosphohydrolase inhibitors or vehicle addition. Standard deviation was calculated from three independent experiments performed in triplicate. One way ANOVA with Tukey’s HSD was applied to ascertain significance. * represents p < 0.05 and ** represents p < 0.01 when comparing vehicle addition to PSB 069. We highlighted just the significance in the presence of PSB 069 because the cell viability results were consistently significant.	PMC9065442	fonc-12-855032-g003.jpg
0.509328	820bbffae5e44d80b266e6253a38b387	Examining the influence of P2RX inhibitors in combination with E-NTPDase inhibitor on cell viability and eATP release in paclitaxel-treated cells. (A) Paclitaxel-treated breast cancer MDA-MB 468 cell lines were treated for six hours with P2RX7 inhibitor A438079 (20 µmol/L) or P2RX4 inhibitor 5-BDBD (20 µmol/L) in the presence or absence of PSB 069 (10 µmol/L), and cell viability was measured by applying PrestoBlue HS assay. Standard deviation was calculated from three independent experiments performed in triplicate. We used the same values for both graphs for vehicle addition and PSB 069. (B) eATP concentrations were measured in the supernatants of paclitaxel-treated MDA-MB 468 cells after six hours of treatment. Standard deviation was calculated from three independent experiments performed in triplicate. We used the to the same values for both graphs for vehicle addition and PSB 069. The student’s t-test was applied to the applicable assays to ascertain significance. * represents p < 0.05 and ** represents p < 0.01 for A438079 and PSB 069 or 5-BDBD and PSB 069 when compared to PSB 069 alone.	PMC9065442	fonc-12-855032-g004.jpg
0.440819	f1044067a9764cc4b70cf2127f531256	Determining relative eATP content and cell viability in paclitaxel-treated cells in the presence of ivermectin or vehicle addition. (A) The graphs represent cell viability as measured using the Presto Blue HS assay +/- standard deviation from three independent experiments performed in triplicate in TNBC and MCF-10A cells after six hours of treatment with increasing concentrations of paclitaxel and the P2RX4 and P2RX7 activator ivermectin (10 µmol/L) or vehicle addition. (B) eATP content was measured in the supernatants of paclitaxel-treated TNBC and MCF-10A cell lines in the presence of the P2RX4 and P2RX7 activator ivermectin (10 µmol/L) or vehicle addition. The student’s t-test was applied to the applicable assays to ascertain significance. * represents p < 0.05 and ** represents p < 0.01 when comparing ivermectin to vehicle addition.	PMC9065442	fonc-12-855032-g005.jpg
0.428031	9426325427304cc4b3b60e348472132d	mRNA and protein expression analysis of P2RX4 and P2RX7 for all cell lines. (A) qRT-PCR was performed on mRNA of TNBC cell lines and MCF-10A cells using specific primers for P2RX4 and P2RX7. * represents p < 0.05 and ** represents p < 0.01. TNBC cell lines, MCF-10A cells, and HEK 293T cells transfected with P2RX4 or P2RX7 as positive controls were probed for (B) P2RX4 and (C) P2RX7, and GADPH was used as a loading control for western blot analysis repeated twice. HEK 293T cells transfected with P2RX7 were loaded at increasing protein concentrations of 1.0 µg, 2.5 µg, and 5.0 µg combined with lysates of control vector-transfected cells to keep the total loaded protein the same in each lane. Densitometry analysis was performed using Image Studio on the 75 kDa P2RX7 band. The student’s t-test was applied to the applicable assays to ascertain significance. * represents p<0.05 and ** represents p < 0.01 relative to MCF-10A; + represents p < 0.05 and ++ represents p < 0.01 relative to HEK293-empty vector transfected. (D) The calculated difference in mean fluorescence intensity (MFI) values between TNBC cell lines, MCF-10A cells, and HEK 293T cells transfected with P2RX4 or P2RX7 as positive controls stained with P2RX4 or P2RX7 specific antibody and the isotype control for the different cell lines examined. * represents p < 0.05 and ** represents p < 0.01 relative to MFI difference in MCF-10A cells; + represents p < 0.05 and ++ represents p < 0.01 relative to MFI difference in HEK293-empty vector transfected. O/E represents overexpressed.	PMC9065442	fonc-12-855032-g006.jpg
0.525798	c7accb745a4e4ff29fab1284f56a9a3c	Schematic displaying our proposed model for ATP release. Our proposed model suggests that ivermectin activates P2RX4 and P2RX7 leading to the release of ATP and the more ATP that accumulates extracellular can promote cell death especially in the presence of paclitaxel. In addition, the breakdown of ATP can be prevented in the presence of E-NTPDase inhibitors POM-1 or PSB 069. However, the release of ATP can be prevented in the presence of P2RX4 inhibitors 5-BDBD or Iso-PPADS or P2RX7 inhibitors A438079 or Iso-PPADS.	PMC9065442	fonc-12-855032-g007.jpg
0.411999	6c4b0d2dbf51406d833299e7969b9eb1	XRD analysis of vanadium-bearing titanomagnetite concentrates.	PMC9065754	c9ra03271a-f1.jpg
0.42295	229139b078274d83b64db7e623257c2d	Worn surface and wear debris of sintered samples. (a) and (b) without rare-earth oxide, (c) (d) La-0.2 wt%, and (e) and (f) Ce-0.4.	PMC9065754	c9ra03271a-f10.jpg
0.520469	a80b5c9dc0ad4068a1f8eb8088c7519e	XPS spectrum of the worn surface of sintered sample with different rare-earth addition: (a) carbon, (b) Fe on the worn surface of Re-0, (c) Fe on the worn surface of La-0.2, (d) Fe on the worn surface of Ce-0.4.	PMC9065754	c9ra03271a-f11.jpg
0.376181	aa44216db6744fa1890c89def179a580	XRD analysis of the pre-reduced powders.	PMC9065754	c9ra03271a-f2.jpg
0.577574	ae521a5b8b8f406fb8aa3e2b8b4b949f	Diagram of block-on ring tester (a) grinding wheel, (b) specimen, and (c) load.	PMC9065754	c9ra03271a-f3.jpg
0.438372	354d73a128b14454a2a0b1ad794f22bb	Microstructure of sintered sample (a) and EDS analysis of area A (b), B (c) and D (d).	PMC9065754	c9ra03271a-f4.jpg
0.36366	989af5fd0a7042c789bdfd1d42da03ee	XRD pattern of the sintered sample without rare-earth oxide.	PMC9065754	c9ra03271a-f5.jpg
0.431699	1a0e538021de42e4ab939800f010da8b	SEM micrographs of powders (a) without and with (b) 0.2 wt% La2O3, (c) 0.4 wt% La2O3, (d) 0.4 wt% CeO2 and (e) 0.6 wt% CeO2.	PMC9065754	c9ra03271a-f6.jpg
0.404877	38e19f5e8bea40c0a18d33029cee053d	Microstructure of the sintered specimens with (a) 0.2 wt% La2O3, (b) 0.2 wt% CeO2, (c) 0.4 wt% La2O3, (d) 0.4 wt% CeO2, (e) 0.6 wt% La2O3, (f) 0.6 wt% CeO2.	PMC9065754	c9ra03271a-f7.jpg
0.412863	ddc6af94931c4d14a3c1d310cf26407f	Hardness and relative density of Fe-based friction material with different rare earth.	PMC9065754	c9ra03271a-f8.jpg
0.402829	eb4a9abe0550420dbd42bc37d6315e1e	Wear rate and friction coefficient of Fe-based friction material with different rare earth addition.	PMC9065754	c9ra03271a-f9.jpg
0.420233	9e80b30cdb2d4630ab8e77a2f734ae01	Identification of cofilin-rich regions at the base of neuronal growth cone filopodia.a–c Immunofluorescence images of phalloidin (Alexa Fluor 488) alone (a), cofilin (Alexa Fluor 594) alone (b), and a merge of the two (c). Most of the cofilin signal emanates from linear aggregates near the base of filopodia. The white dashed line in c marks the position of the lamellipodial veil. d Merged immunofluorescence image of a growth cone with fascin (Alexa Fluor 488-green) and cofilin (Alexa Fluor 594-red) labeled, showing cofilin-rich regions at the base of filopodia as in c. Bottom-left inset: Split view of the boxed-out region. The white arrow points to the same location in each image and shows the point at which the fascin signal drops off and the cofilin signal intensifies. e Representative line scan intensity profile of a single filopodium showing the distribution of fascin and cofilin. The image above the graph shows a close-up view of the measured filopodium and the location where the line profile was drawn. The transition region is marked by two dashed lines. The images in a–c are representative images, but two independent experiments showed similar localization of cofilin and actin. d is a representative image from one of three independent experiments. Scale bars: (c) 5 µm (this also corresponds to a and b), d 5 µm. Source data are provided as a Source Data file.	PMC9068697	41467_2022_30116_Fig1_HTML.jpg
0.416944	b29faa2b41624e7b913720228450684d	Structural features of neuronal growth cone filopodia and their associated cofilactin bundles.a Overview image of a cryo-preserved growth cone on a Quantifoil EM grid. The green and red boxes represent growth cone regions similar to where the tomograms in b and c were imaged, respectively. b, c 5 nm-thick slices of tomograms from the tip (b) and base (c) of growth cone filopodia. In b, a bundle of actin filaments fills the entire cytoplasm. In c, branched networks of individual actin filaments can be seen surrounding a central bundle of hyper-twisted cofilactin filaments. White arrows point to the bundle. Lower-left insets: 68 nm-thick transverse cross-sections through each bundle, illustrating the hexagonal packing of filaments. The blue line in the main images show the plane from which the insets were taken. Bottom insets: Subtomogram averages of filament pairs in filopodial tips (below b) or in cofilactin bundles at the filopodial bases (below c). Cofilactin filaments have a shorter helical twist than F-actin and are out of phase with adjacent filaments. d EM map (blue) resulting from the subtomogram averaging of actin filaments in filopodial tips, and rigid body fitting of a previously reported atomic structure for F-actin (PDB ID: 6T1Y; green). e EM map (blue) resulting from the subtomogram averaging of cofilactin filaments near the base of filopodia, and rigid body fitting of a previously reported atomic structure of cofilactin (PDB ID: 3J0S; actin is green and cofilin is red). f Segmented filopodial protrusion with a schematic of filament centerlines overlaid (red). These lines are comprised of a series of points that were used for nearest neighbor analysis. g Nearest neighbor histograms showing the cumulative total of three normal actin filopodial bundles (green) and three cofilactin bundles (red). Scale bars: (a) 5 µm, (b) 200 nm (this also corresponds to the image in c), f 100 nm.	PMC9068697	41467_2022_30116_Fig2_HTML.jpg
0.459147	fa5d3a1a29b444e9b8f99f456af67748	Higher-order structure of filopodial bundle types.a Schematic model of the higher-order structure of actin (fascin-linked) and cofilactin bundles in growth cone filopodia (as they appear looking down the long axis of the bundle). Filaments in both bundle types are organized in layers and hexagonally packed (blue hexagons). Filaments in the actin bundle are all twisting in phase with one another, but in the cofilactin bundle filaments are rotated 90° with respect to their neighbors in the same layer. This creates columns of filaments that are oriented similarly to one another. The yellow dots on filaments in the hexagon correspond to filaments in b. b 17 nm-thick slices through tomograms of a filopodial tip (top) and a cofilactin bundle (bottom). In the cofilactin bundle, brackets show the wide portion of the helical twist while red arrows show the thin portion. The yellow dots correspond to the dots in a. For instance, the bracketed filament in layer two is directly between the two filaments in layers 1 and 3, only on a different Z-plane. Scale bars in b are 20 nm.	PMC9068697	41467_2022_30116_Fig3_HTML.jpg
0.4784	d256bdc063b14fdebca310516b361aad	Potential conflict between fascin and cofilin, and potential cofilactin interactions.a, b Top-down views of fascin-linked actin (a) and cofilactin (b) filaments. Both pairs of filaments are shown at interfaces where they are in phase with one another. In a, fascin (blue) is shown in its actin-binding pockets (22), two sites that are sterically blocked by the presence of cofilin in our model of cofilactin bundles (b). F-actin is green, and cofilin monomers are red. c Sideview of model cofilactin hexagonal unit. Dashed regions labeled 1 and 2 illustrate cross-sections shown in d and e, respectively. F-actin is green and cofilin is red. d, e Cross-sections through different regions of the hexagonal unit shown in c. Arrows point to the place where cofilin monomers on neighboring filaments are closest to each other (~2 nm apart at their closest residues). f Zoomed-in view of neighboring cofilins like those in the boxed-out region in e. Cys39 and Cys147 are displayed on each (cyan).	PMC9068697	41467_2022_30116_Fig4_HTML.jpg
0.52466	6e5b30cf550548de9dd1db082cdc4531	Tomography of cofilactin within filopodia.In all images, red arrows signify cofilactin and green arrows show normal F-actin. The top-right corner of each image shows their distance from the lamellipodial veil (positive values are distal from the veil and negative values are proximal from it). a A 13.3 nm-thick tomographic slice where individual cofilactin filaments are scattered throughout a fascin-linked actin bundle. b 13.3 nm-thick tomographic slice through a prospective transition region where a clear boundary (represented by the dashed line) exists between the F-actin on top and the cofilactin on bottom. c 13.3 nm-thick tomographic slice showing a pure cofilactin bundle). Scale bars: 50 nm.	PMC9068697	41467_2022_30116_Fig5_HTML.jpg
0.447194	c7ff18d3280148aeabf6c95a8d27753c	Cofilactin bundles facilitate bending and breaking of filopodial protrusions.a Single image of a whole-cell expressing tdTomato-Lifeact (pseudocolored green) and EGFP-cofilin (pseudocolored red). b, c Maximum intensity projections (MIP) of lower and upper boxed regions in a, respectively. MIPs include 40 images at 3 s intervals for 2 min total. Filopodia in b are examples of “resting” filopodia and (c) shows a “searching” filopodium. Dashed arrows indicate the direction of actin retrograde flow, and arrowheads indicate inflection points seen along the flexing filopodial bundles. The white dashed line marks the position of the lamellipodial veil. d–f 2-min movie montages showing behaviors exhibited by the cofilin-rich filopodia designated with the corresponding label in a. Arrowheads follow either a kink/breaking point (d), a cofilactin bundle “wave” (e), or an inflection point in a bending filopodium (f). In e, the wave is caused by the filopodial tip moving from left to right, which drags the attached base behind it in a flexible, wave-like motion. The localization of EGFP-cofilin and tdTomato-Lifeact shown in a was replicated in multiple cells from two independent experiments, and similar results were also seen using other fluorescent protein combinations (Supplementary Fig. 5). Scale bars: (a, b) 5 µm (scale bar in b also corresponds to image in c), (d) 500 nm (also corresponds to (e) and (f)).	PMC9068697	41467_2022_30116_Fig6_HTML.jpg
0.434371	1478987d4ff34e8281fb9ebb3de9d68d	Tomograms of growth cone filopodia in different dynamic states.In all images, red arrows signify cofilactin and green arrows show normal F-actin. a 13.3 nm-thick tomographic slice showing a ~90° kink in a growth cone filopodium. This filopodium is likely in the process of severing, like in Fig. 6d and Supplementary Movie 7. Cofilactin filaments can be seen near the apex of the kink in the bundle. b 13.3 nm-thick tomographic slice where the proximal portion of a filopodium appears to be moving from right to left in a wave-like motion. This is similar to the motion exhibited by the filopodium shown in Fig. 6e and Supplementary Movie 8. The dashed boxes on top and bottom represent the regions shown in the top and bottom zoomed-in insets (white boxes), respectively. The top zoomed-in view shows a cofilactin filament forming an S-curve through the fascin cross-linked bundle. The cofilactin filament is moving through the Z-axis, so the middle of the S-curve is not visible in this image. The bottom zoomed-in view shows, similar to the kink from (a), cofilactin filaments near the crest of the wave. c 13.3 nm-thick tomographic slice of a bend in a distal filopodial region. Here, cofilactin and actin coexist as separate bundles wrapping around one another. This tomogram resembles that shown in the movie from Fig. 6f and Supplementary Movie 9. Inset: TEM overview image showing the location of the tomogram in the main panel. Scale bars: a, b, and c represent 100 nm.	PMC9068697	41467_2022_30116_Fig7_HTML.jpg
0.42792	33b083be14ba4143b3b8d84d12396ab4	Current model.Schematic of filopodial actin bundle in a rigid (a) and flexible (b) state. As cofilactin filaments permeate the fascin-linked region of the filament, they competitively dislodge fascin cross-linkers and increase the flexibility of filopodial bundles. In the proximal region of the bundles, cofilactin filaments prevail and are cross-linked through either cofilin oligomers/self-association or by some, as of yet, unknown cross-linker.	PMC9068697	41467_2022_30116_Fig8_HTML.jpg
0.420134	9b02e2d755f449399fd10eb3b00db19e	Histidine levels were significantly higher in the hypersensitivity group. (A) Heatmap and cluster analysis of significant differential metabolites between the normal group (group 1) and the hypersensitivity group (group 2). (B) Z-score graph of significant differential metabolites. l-Histidine levels in the normal group were significantly higher than those in the hypersensitivity group. (C–F) Four significant differential metabolites levels between the normal and hypersensitivity groups included l-histidine, urocanic acid, myristicin, and d-aldose. (G) Pathway enrichment analysis. Histidine metabolism showed a high impact on hypersensitivity (p < 0.05, *p < 0.01).	PMC9068896	fphar-13-827446-g001.jpg
0.389697	9e6c0d34e45e457a8d1b4b30ff31c223	Receiver operating characteristic (ROC) curves and content level of 30 differential metabolites.	PMC9068896	fphar-13-827446-g002.jpg
0.436613	ef857c786e5b48d6bc96b1a00226a019	Histidine supplement-enhanced PLD-induced HSR in rat model. (A) H&E staining (100x). PLD injection could induce pulmonary edema. Histidine supplement-aggravated pulmonary edema, but this phenomenon could be alleviated by histidine decarboxylase inhibitor: bromo-3-hydroxybenzoic acid (BHBA). (B) Toluidine blue staining (mast cell staining) (200x). Histidine could increase mastocyte infiltration in the trachea and lungs and significantly increase mastocyte degranulation in the trachea and larynx after PLD injection. (C) Degranulation and undegranulation mast cell counting. (D) Histidine supplement group showed significantly increased IgE levels. BHBA treatment could decrease IgE levels significantly (PLD, PEGylated liposomal doxorubicin; HSR, hypersensitivity reaction; p < 0.05, p < 0.01, **p < 0.001).	PMC9068896	fphar-13-827446-g003.jpg
0.492023	d2252878f3ca49a3bfd0da03ba1b8dcf	Corona virus binds to Lung Epithelial Cells which causes the activation of inflammatory cells and cytokine storms	PMC9069147	IJPVM-13-45-g001.jpg
0.503843	a01b8204cad047d882e988124f40658c	Schematic representation of the multimodal X-ray microscopy experimental setup. KB mirrors focus X-rays down to a focal spot of about 70 nm and with a 1.2 mrad divergence. The sample is mounted on a motor stack enabling xyz translation and θ, φ rotation, i.e. around the x and y axes, respectively. The sample can be translated in and out of the X-ray beam focus via translation along z (total travel range 46 mm), effectively tuning the X-ray beam size. An ion chamber is positioned downstream of the KB chamber to monitor the incoming X-ray photon flux. An optical in-line microscope provides a view onto the sample along the optical z axis. A fluorescence detector is positioned 15 mm away from focus, with a 15° orientation with respect to the focal plane. An in-line area detector is positioned 1.12 m downstream of the focus to collect holograms.	PMC9070709	s-29-00807-fig1.jpg
0.490743	991d191b7afe4bb083da3c076e2b4174	Preliminary reconstructions from a 5 × 5 holography scan covering a potential ROI of a section of an Os-stained human peripheral sural nerve biopsy from a healthy male. These qualitative results were used to delimit a ROI on which to perform a nanoscale X-ray fluorescence scan, as more conveniently annotated in Fig. 3 ▸. Further processing followed. The frame number is annotated on each frame, revealing the scanning sequence.	PMC9070709	s-29-00807-fig2.jpg
0.476043	e3222abd6f904fe1ab842ceb8a0d4d6a	Quantitative result obtained from processing the images from Fig. 2 ▸. The ROI on which a nanoscale X-ray fluorescence scan was performed is highlighted by the white rectangle. A blood vessel (blue arrow) as well as myelin layers surrounding several axons (red arrows) can be identified. The intensity scale represents relative electron density variations and for convenience was converted into units of Å−3.	PMC9070709	s-29-00807-fig3.jpg
0.496383	9b0bff561368482e9b4479a1af7d7b96	(a)–(c) Area mass density maps obtained via nanoscale X-ray fluorescence emission spectroscopy for (a) Cl, (b) Fe and (c) Os within a ROI of a section of an Os-stained human peripheral sural nerve biopsy from a healthy male. Linear intensity scales are shown in units of ng mm−2. (d) RGB representation of the same region including electron density information from the holography scan: red, green and blue channels represent electron density, Fe and Os area mass densities, respectively. A 10 µm scale bar for all images is given in (a).	PMC9070709	s-29-00807-fig4.jpg
0.489397	55d3bd280c2b4912bd0bc4ea90bb5d21	Postprandial 1,2-dicarbonyl compound concentrations in older (25 months) and younger (5 months) male mice. Data are shown as Violin plots; dotted lines represent median and quartiles. Student’s t-test for normally distributed data and Mann–Whitney U test for nonnormally distributed data were used to assess differences between age groups. 25 months old (n = 11), 5 months old (n = 14). 3-DG = 3-deoxyglucosone; GO = glyoxal; MGO = methylglyoxal; 25 M = 25 months old; 5 M = 5 months old; p < .05.	PMC9071428	glab331_fig1.jpg
0.456125	d58d26f7c0a44d7eaa2da5280acedc4b	Fasting 1,2-dicarbonyl compound concentrations in older and younger women (A) and men (B). Data are shown as Violin plots; dotted lines represent median and quartiles. Student’s t-test for normally distributed data and Mann–Whitney U test for nonnormally distributed data were used to assess differences between age groups. YW (n = 19), OW (n = 19), YM (n = 15), OM (n = 15). 3-DG = 3-deoxyglucosone; GO = glyoxal; MGO = methylglyoxal; YW = younger women; OW = older women; YM = younger men; OM = older men; p < .05.	PMC9071428	glab331_fig2.jpg
0.476952	62f927fad4ab49faabb5e8d6b86b39f1	Postprandial 1,2-dicarbonyl concentrations and response (iAUC) to a dextrose challenge in older and younger women and men. Data are shown as mean ± SD. Repeated measures analysis of variance was used to examine changes over time and differences between age groups, and Mann–Whitney U test was used to assess age differences of the postprandial response (iAUC). *Significantly different between age groups. YW (n = 19), OW (n = 19), YM (n = 15), OM (n = 15). iAUC = incremental area under the curve; 3-DG = 3-deoxyglucosone; GO = glyoxal; MGO = methylglyoxal; YW = younger women; OW = older women; YM = younger men; OM = older men; p < .05.	PMC9071428	glab331_fig3.jpg
0.405949	61457424ace84c04a9025d6761df8c9c	Associations of glucose response with 3-DG (A) and GO (B) response as well as insulin response with MGO response (C) to a dextrose challenge. (A) No significant correlation in women, men: r = 0.782, p = .008. (B) No significant correlation in women, men: r = 0.707, p = .022. (C) No significant correlation in women, men: r = 0.784, p = .007. YW (n = 19), OW (n = 19), YM (n = 15), OM (n = 15). iAUC = incremental area under the curve; 3-DG = 3-deoxyglucosone; GO = glyoxal; MGO = methylglyoxal; YW = younger women; OW = older women; YM = younger men; OM = older men; p < .05.	PMC9071428	glab331_fig4.jpg
0.457334	fe5311e4dd2c4323a6754a6d5e03aae0	Flow diagram of the simulation, benchmarking, and experimental data evaluation strategy presented in the manuscript. Briefly, SplattDR was developed to simulate dose–response scRNAseq data and validated based on experimental dose–response data. Simulated datasets were generated varying diverse parameters 10 times and then used to assess the performance of each test method. Each test method was also assessed using experimental data from the hepatic snRNAseq dose response dataset obtained from male mice gavage every 4 days for 28 days with 0.01, 0.03, 0.1, 0.3, 1, 3, 10 or 30 μg/kg TCDD. Related figures for each analysis from the main body are noted.	PMC9071439	gkac019fig1.jpg
0.42975	52a53f4cf5254c458e0a1d49a611aca5	Comparison of simulated and real dose–response data. (A) Relationship between gene-wise mean expression and percent zeroes for simulated and real dose–response data. Simulation data consisted of 10 000 genes and nine dose groups based on parameters derived from experimental dose–response snRNAseq data. Black line represents a fitted model to the experimental data from which the normalized root mean square deviation (NRMSD) of simulated data was determined. (B) Relationship between gene-wise mean expression and variance for simulated and experimental data. NMRSD was calculated for simulated data from the fitted model represented as a black line. (C) Distribution of log(fold-changes) in experimental and simulated data showing the median and minimum and maximum values. (D) Principal components analysis of simulated data colored according to simulated dose groups. (E) NMRSD estimated relative to fitted model in A,B for simulated data generated from initial parameters derived from published hepatic scRNAseq (two dose; GSE148339), hepatic whole cell (whole cell; GSE129516), and peripheral blood mononuclear cell (PBMC; GSE108313) datasets. (F) NMRSD estimated relative to model fitted to cell-type specific experimental dose–response data when simulated from initial parameters estimated from that same cell type. Box and whisker plots show median NMRSD, 25th and 75th percentiles, and minimum and maximum values.	PMC9071439	gkac019fig2.jpg
0.40547	9393420bace24831bf038a4622e7fc70	Classification performed of DE analysis tests. (A) ROCs estimated from simulated dose–response scRNAseq data for nine DE test methods including all genes expressed in at least one cell (unfiltered). (B) ROCs for nine DE test methods after filtering simulated dose–response scRNAseq data for genes expressed in only ≥5% of cells (low levels) in at least one dose group. (C) Precision-recall curves (PRCs) for nine DE test methods on unfiltered simulated dose–response scRNAseq data. (D) PRCs for nine DE test methods on filtered simulated dose–response scRNAseq data. Lines represent the mean values and shaded region reflects the standard deviation for 10 independent simulations. (E) Precision of DE test methods. (F) FPR of DE test methods. (G) MCC for test methods. (E–G) Box and whisker plots median values, 25th and 75th percentiles, and minimum and maximum values for 10 independent simulations. Points reflects values for each independent simulation. Panels display comparisons of unfiltered and filtered datasets.	PMC9071439	gkac019fig3.jpg
0.433991	07e550188fbf4a399430f9c372ce5640	Evaluation of Type I and II error control. (A) False positive rate (FPR) of 9 differential expression test methods estimated from negative control (0% DE genes) simulated dose–response scRNAseq data including all genes expressed in at least 1 cell (unfiltered) and genes expressed in only ≥ 5% of cells in at least one dose group (filtered). (B, C) Logistic regression models were fitted to negative control data to predict the probability of false positive identification using percent zeroes and mean expression as covariates. Lines represent the predicted probability of false positive classification with the shaded region representing the 95% confidence interval. (D) False negative rate (FNR) of nine differential expression test methods estimated from positive control (100% DE genes) simulated dose–response scRNAseq data including unfiltered and filtered datasets. (E, F) Logistic regression models were fit to positive control data. Lines represent predicted probability of false negative classification with shaded region representing the 95% confidence interval.	PMC9071439	gkac019fig4.jpg
0.496533	df576553fcc34d4585990e8a9d5f80c9	Matthews correlation coefficient (MCC) from sensitivity analyses of differential expression test methods. (A) MCC for nine DGEA test methods determined from simulated dose response data with varying number of cells per dose group. Simulations consisted of 5,000 genes with a probability of differential expression of 10% and 9 dose groups. (B) MCC for simulated data varying the cells numbers by dose group. The number of cells in each of the nine doses groups is shown on the right. (C) MCC for varying proportion of differentially expressed genes. (D) MCC when varying the mean fold-change (location) of repressed differentially expressed genes. (E) MCC for varying distribution of fold-change (scale) of differentially expressed genes. (F) MCC for varying dropout rates calculated as in Supplementary Table S3. Points represent median and error bars represent minimum to maximum values. Boxplots represent median, 25th to 75th percentile, and minimum to maximum values. Each analysis consisted of 10 replicate datasets including all genes expressed in at least one cell (unfiltered) and genes expressed in ≥5% of cells in at least one dose group (filtered).	PMC9071439	gkac019fig5.jpg
0.440178	3773fa32a7084a4e892b195a546cd6bc	Agreement of differential expression test methods on experimental dose–response data. (A) Upset plot showing the intersection size of genes identified as differentially expressed by nine different test methods in hepatocytes from the portal region of the liver lobule. (B) Intersect of differentially expressed genes in portal fibroblasts. (C) Intersect size in hepatic stellate cells. Vertical bars represent the intersect size for test methods denoted by a black dot. Horizontal bars show the total number of differentially expressed genes identified within each test (set sizes). Only intersects for which genes were identified are shown. Genes were considered differentially expressed when (i) expressed in >5% of cells within any given dose group and (ii) exhibit a \|fold-change\| ≥ 1.5. A heatmap in the upper left corner of each panel shows the pairwise AUCC comparisons for the 500 lowest P-values. (D) Relative proportion of cell types identified in each dose group of the real dataset for the cell types in (A–C). Experimental snRNAseq data was obtained from male mice gavaged with sesame oil vehicle (vehicle control) or 0.01–30 μg/kg TCDD every 4 days for 28 days. (E) Graph metrics for gene set enrichment analysis of portal fibroblasts grouped by similarity in gene membership. Violin plots show distribution of node-wise values for each test method. (F) Network visualization of significantly enriched (adjusted P-value ≤ 0.05) gene sets using the Bayes factor ranked genes of portal fibroblasts. Groups of ≥2 nodes were manually annotated following commonality in the gene set names. Each node represents a gene set with the size of the node representing the number of genes in a gene set, and edges connect nodes with ≥50% overlap.	PMC9071439	gkac019fig6.jpg
0.465634	992c09a99bbc4a58978ca6436e9a339f	Median ranking of differential expression test methods across all simulations. The median rank of each test method was calculated for AUPRC, AUROC, MCC, FNR and FPR. Tests were grouped according to intended application including fit-for-purpose tests developed for the analysis of dose–response datasets, multiple group tests, and two group tests. The overall rank represents the median value for the five key metrics presented here.	PMC9071439	gkac019fig7.jpg
0.393916	2ab64ca0949a48fa89c4d64172480268	The pattern classification of tumor microenvironment (TME). (a) Optimal number of clusters: K value calculated by the elbow method and gap statics algorithm. The ordinate axis represents total within sum of square; the abscissa axis represents the number of clusters K. (b) Consensus matrix heat map (K = 3): ConsensusClusterPlus was used for unsupervised class discovery (1000 iterations, k = 1 : 10). The optimal k value of 3 was determined using the elbow method and gap statics, combined with the correlation between the final classification and survival. (c) The distribution ratio of all kinds of immune cells in different TME clusters. (d) Clustering heat map of the distribution ratio of all kinds of immune cells in different TME clusters. (e) Survival analysis for different TME clusters: the red curve represents the TME cluster 1, the blue curve represents the TME cluster 2, and the yellow curve represents the TME cluster 3. The ordinate axis represents the probability of survival, and the abscissa axis represents the survival days.	PMC9071896	BMRI2022-5673810.001.jpg
0.456703	32d746738c974c51a9c41fcb1716fa75	Evaluation of TMEscore model and analysis of its correlation with mutation load. (a) The meta-analysis results of TMEscore model in different datasets: training set, testing set, TCGA, TCGA different stages, metastatic breast cancer, and prognosis evaluation of drug treatment. (b) Correlation analysis between TMEscore and mutation loads in different subtypes (basal, Her 2, Lum A, Lum B, and normal): the ordinate axis represents total mutations, and the abscissa axis represents TMEscore. (c) TMEscore box plots in different subtypes (basal, Her 2, Lum A, and Lum B). (d) Survival analysis results in four different subtypes of breast cancer (basal, Her 2, Lum A, and Lum B): the ordinate axis represents the probability of survival, and the abscissa axis represents the survival days. Different colors represent different subtypes. (e) Survival analysis of luminal A subtype after grouping according to TMEscore: the ordinate axis represents the probability of survival, and the abscissa axis represents the survival days. Different colors represent different TMEscore subgroups (high TMEscore and low). (f) Survival analysis of luminal B subtype after grouping according to TMEscore: the ordinate axis represents the probability of survival, and the abscissa axis represents the survival days. Different colors represent different TMEscore subgroups (high TMEscore and low).	PMC9071896	BMRI2022-5673810.002.jpg
0.425939	d27306a1ab2c43d4b12a7ecc0a8f1e47	Overview of mutations in 1039 TCGA-BRCA samples. (a) Tumor mutation profile. A1: variant classification of 1039 tumor samples. Missense mutations were the main mutation type in BRCA. A2: variant type of 1039 tumor samples. The source of mutations was mainly SNPs (mostly C>T) followed by indels. A3: SNV class of 1039 tumor samples. A4: variants per sample among 1039 tumor samples. A5: variant classification summary of 1039 tumor samples. A6: top 10 mutated genes in 1039 tumor samples. MUC4 was the most common mutated gene, followed by TTN. (b) Gene mutation distribution and phenotype in different TMEscore groups. B1: the distribution of mutations and mutation annotations of 24 genes in TMEscore high group. B2: the distribution of mutations and mutation annotations of 24 genes in TMEscore low group. (c) The frequency distribution of common gene mutations. Among them, the mutation rates of PIK3CA, TP53, KMT2C, GATA3, and MUC4 in the two subgroups have statistically significant differences.	PMC9071896	BMRI2022-5673810.003.jpg
0.451255	97b6d41d020c4b26be46b9c3c0d7938c	The analysis results of CNV. (a) The occurrence of chromosome arm-level amplification and deletion in different TMEscore groups: the abscissa axis represents the chromosome locus, and the ordinate axis represents the frequency of copy number alterations. Red represents the high TMEscore group, and the other one represents the low TMEscore group. ∗ represents statistical differences in frequency between the two groups. (b) Distribution of copy number amplification and deletion regions in high TMEscore group: 11q13.3 was the most significant in the amplified region, and 11q23.1 was the most significant in the deletion region. (c) Distribution of copy number amplification and deletion regions in TMEscore_low group: the most significant amplification region was located at 8q24.21, and the most significant deletion region was located at 8p23.2. (d) Ploidy analysis results in high and low TMEscore groups: ∗ represents statistical differences in frequency between the two groups. (e) Purity analysis results in high and low TMEscore groups: ∗∗ represents statistical differences in frequency between the two groups.	PMC9071896	BMRI2022-5673810.004.jpg
0.438062	bdbea8658c344e9f9cb116970067413e	The analysis results of miRNA and mRNA. (a) Functional annotation of differentially expressed miRNA: the ordinate axis represents different miRNAs, and the abscissa axis represents the functional annotations of miRNAs. (b) Volcano map of differentially expressed genes (DEG): the red part on the right shows the upregulated TOP 9 genes, and the blue on the left shows the downregulated top 2 genes. (c) Heat map of differentially expressed genes (DEG). (d) GO enrichment analysis of differentially expressed genes (DEG): the abscissa axis represents the number of genes, and the ordinate axis represents the results of CC (cellular component), BP (biological process), and MF (molecular function). (e) KEGG enrichment analysis of differentially expressed genes (DEG): the abscissa axis represents the number of genes, and the ordinate axis represents the corresponding pathways.	PMC9071896	BMRI2022-5673810.005.jpg
0.427068	1e225930a169458b96183c12b7784ab0	Comprehensive analysis results of tumor samples. (a) Volcano map of differentially methylated sites: 217 significantly different methylation sites were detected, and 67 methylation sites related to survival were obtained. (b) The survival analysis results of hsa-mic-1307 in different subgroups: the abscissa axis represents the survival time, and the ordinate axis represents the survival probability. The red curve represents high expression, and the blue curve represents low expression. (c) The survival analysis results of LRRC48 in different subgroups: the abscissa axis represents the survival time, and the ordinate axis represents the survival probability. The red curve represents high expression, and the blue curve represents low expression. (d) The survival analysis results of cg25726128 in different subgroups: the abscissa axis represents the survival time, and the ordinate axis represents the survival probability. The red curve represents high expression, and the blue curve represents low expression. (e) Immunotherapy efficacy score calculated by TMEscore group: the abscissa axis represents the TMEscore subgroup, and the ordinate axis represents TIDE. ∗∗ represents that the analysis result is statistically significant. (f) Using ROC analysis to evaluate the predictive ability of TMB, TMEgroup, and TMB+TME group on the effect of immunotherapy. (g) The relationship between MSI and TMEscore: the abscissa axis represents different MSI subgroups, and the ordinate axis represents TMEscore. ∗∗ represents that the analysis result is statistically significant. (h) Comprehensive genome landscape of BRCA (47 survival-related genes, P < 0.01).	PMC9071896	BMRI2022-5673810.006.jpg
0.435716	5a232d636ab149738c37e168fb740006	1H NMR spectra of the monomer.	PMC9071944	c9ra04828f-f1.jpg
0.424406	cacfa72d94d4496388863b788b8c8279	Results from nanoindentation tests for the cured resin.	PMC9071944	c9ra04828f-f10.jpg
0.527658	e84c6d2f30f14a2fabd5abf62eae3336	DMA curves of the cured resin.	PMC9071944	c9ra04828f-f11.jpg
0.514916	feebf9bcfcf641afbba37c0d7f1a1858	FT-IR spectra of the monomer and resin.	PMC9071944	c9ra04828f-f2.jpg
0.522294	33bd4cabe51a416b971b872b861a875e	DSC curve of Monomer 3 at a heating rate of 10 °C min−1 in N2.	PMC9071944	c9ra04828f-f3.jpg
0.52205	5f211f51f19f4808910ea1257465a1df	TG curve of the cured resin in N2 with a heating rate of 10 °C min−1.	PMC9071944	c9ra04828f-f4.jpg
0.517435	68ff41b5cfce4019883a85573d73aae0	DTG curve of the cured resin in N2 with a heating rate of 10 °C min−1.	PMC9071944	c9ra04828f-f5.jpg
0.447709	34656cadaf45438e9bf2cb2df0514582	Contact angle of water on the cured resin.	PMC9071944	c9ra04828f-f6.jpg
0.470885	89bb001c057c4a5987bd38d57a378962	AFM images of the cured resin film: (a) planar graph and (b) stereogram.	PMC9071944	c9ra04828f-f7.jpg
0.507214	b37ea1564a034505943e7a7c2842a42a	Dielectric constant and dielectric loss of the cured resin.	PMC9071944	c9ra04828f-f8.jpg
0.45041	1d3c36c63c7847ccb13a80562311ed43	X-ray diffraction (XRD) patterns of the cured resin (powder).	PMC9071944	c9ra04828f-f9.jpg
0.415888	9be29a28cef6468c9ec6b2217afd5b47	Reagents and conditions: (i) NaNO2, concentrated HCl, 0 °C, 1 h; HNO3 : H2O (3 : 2), 17 °C, 75 min; (ii) EtOH, reflux, 24 h; (iii) pyridine, 50 °C, 30 min.	PMC9072087	c9ra05712a-f1.jpg
0.428227	afa554f4fc7249d2b6d146aba4575d51	Optical microscope and scanning electron micrographs of the hyphae of S. sclerotiorum grown on PDA medium with DMSO or compounds 2, 5c at 25 °C. Optical microscope: (A) untreated control, 0.5% DMSO, ×400; (B) compound 2 at 0.0016 mM (EC50) treatment, ×400; (C) compound 5c at 0.0030 mM (EC50) treatment, ×400; scanning electron microscopy: (D) untreated control, 0.5% DMSO, ×1500; (E) after 72 h compound 2 at 0.0016 mM (EC50) treatment, ×1500; (F) after 72 h compound 5c at 0.0030 mM (EC50) treatment, ×1500.	PMC9072087	c9ra05712a-f2.jpg
0.371974	cf1a1aa5ec81441cab1d4491eb08cab7	In vivo protective efficacy of compounds 2, 5c and azoxystrobin against S. sclerotiorum on rape leaves.	PMC9072087	c9ra05712a-f3.jpg
0.536259	34d674f0972a42cab215f027ca7845bf	DSC of perdecanoic acid at a heating rate of 10 °C min−1.	PMC9072111	c9ra06087a-f1.jpg
0.448481	c1849a434a0c40049efaab6c878cf5ff	The activity of peracids in the model oxidation of 2-adamantanone. Reaction conditions: 2-adamantanone (0.100 g, 0.67 mmol), peracid (1.34 mmol), toluene (2 mL), 25 °C, 1200 rpm.	PMC9072111	c9ra06087a-f2.jpg
0.523724	baf7c9d370074904bcb40d09734d2605	The influence of the solvent for the model oxidation of 2-adamantanone. Reaction conditions: 2-adamantanone (0.100 g, 0.67 mmol), perdecanoic acid (1.34 mmol), solvent (2 mL), 25 °C, 1200 rpm.	PMC9072111	c9ra06087a-f3.jpg
0.443058	fa075fe9534e4f3abf528bd3be6f5133	The influence of the temperature for the model oxidation of 2-adamantanone. Reaction conditions: 2-adamantanone (0.100 g, 0.67 mmol), perdecanoic acid (1.34 mmol), toluene (2 mL), 1200 rpm.	PMC9072111	c9ra06087a-f4.jpg
0.476406	f9228813f2784f4f80d4f438bc8cd89c	The influence of molar ratio ketone : oxidant for the model oxidation of 2-adamantanone. Reaction conditions: 2-adamantanone (0.100 g, 0.67 mmol), perdecanoic acid, toluene (2 mL), 35 °C, 1200 rpm.	PMC9072111	c9ra06087a-f5.jpg
0.468649	a3e5042b9d8e40da86d95a1661248c76	(a) XRD pattern, TEM image (inset), (b) XPS spectrum and (c) proton longitudinal r1 and transverse r2 relaxivities (measured at 1.41 T and 37 °C) of pristine Fe3O4/γ-Fe2O3 nanoparticles.	PMC9072193	c9ra07227f-f1.jpg
0.486335	5cb2f938e59e42ac97ead1144f8f1451	Proton longitudinal r1 and transverse r2 relaxivities (measured at 1.41 T and 37 °C) of (a) Ca2+, (b) Fe3+, (c) Na+, (d) Mg2+, (e) Zn2+, (f) Ni2+, (g) Co2+, and (h) Cd2+ adsorbed Fe3O4/γ-Fe2O3 nanoparticles.	PMC9072193	c9ra07227f-f2.jpg
0.454902	15cc2705f2eb4d70b8d41e42ac8bbdaa	Dependence of (a) r1 and (b) r2 values on Xr/Z with regard to various cation-adsorbed Fe3O4/γ-Fe2O3 nanoparticles. The experimental data are plotted as solid squares, and the solid lines are fitting results according to eqn (1).	PMC9072193	c9ra07227f-f3.jpg
0.388584	88c5312fb369479fb1a7e6a7c902d54e	Dependence of (Xr/Z − xc)/w values for various cation-adsorbed Fe3O4/γ-Fe2O3 nanoparticles.	PMC9072193	c9ra07227f-f4.jpg

0.466279

6de0f4c0020644b5b0be3ea29ec2a030

Receiver operating characteristic (ROC) curves for predictors of mortality in the COVID-19 cohort (n=74). CRP, C reactive protein; LDH, lactate dehydrogenase; gbCR, glass-bead test Clot Rate; gbPA, glass-bead test Peak Amplitude.

PMC9062462

bmjopen-2021-051971f04.jpg

0.394458

99b43645f4bb4d7693af857ff606281b

FE-SEM images of pLys-HAp composites: (a) α-pLys-HAp (20 mg), (b) α-pLys-HAp (30 mg), (c) α-pLys-HAp (40 mg), (d) ε-pLys-HAp (20 mg), (e) ε-pLys-HAp (30 mg) and (f) ε-pLys-HAp (40 mg). The insets in (a–f) show TEM images of each sample.

PMC9062467

c9ra01764j-f1.jpg

0.48906

f9baa4fd2fbf491e8095d2ac45ef2bbe

(A) X-ray diffraction patterns of (a) α-pLys-HAp (20 mg), (b) α-pLys-HAp (30 mg), (c) α-pLys-HAp (40 mg), (d) ε-pLys-HAp (20 mg), (e) ε-pLys-HAp (30 mg) and (f) ε-pLys-HAp (40 mg), respectively (JCPDS card no. 09-0432). (B) FT-IR spectra of (a) α-pLys-HAp (20 mg), (b) α-pLys-HAp (30 mg), (c) α-pLys-HAp (40 mg), (d) pure α-pLys, (e) ε-pLys-HAp (20 mg), (f) ε-pLys-HAp (30 mg), (g) ε-pLys-HAp (40 mg) and (h) pure ε-pLys, respectively.

PMC9062467

c9ra01764j-f2.jpg

0.392276

12caa311ae9043e9bb659cf8f0f37133

STEM images and EDX maps of elements of (A) α-pLys-HAp (40 mg) and (B) ε-pLys-HAp (40 mg). Yellow, green and red colours display nitrogen, calcium and phosphorus elements, respectively.

PMC9062467

c9ra01764j-f3.jpg

0.545375

9675ca4c68824910b2b8a1681861c5d8

Adsorption isotherm curves for GOX on α-pLys-HAp (40 mg) and ε-pLys-HAp (40 mg).

PMC9062467

c9ra01764j-f4.jpg

0.404961

ec17d88bd3c5458095b834ec4bf467b7

(A) Fluorescence spectra of free and immobilised GOX. (B) The three-dimensional structure of GOX was obtained from Protein Data Bank; ID: 1CF3. Hydrophobic amino residues in GOX were emphasised using red colour.

PMC9062467

c9ra01764j-f5.jpg

0.4578

a295e7a954294781a99ea11f1c3feb16

The Lineweaver–Burk plots of free and immobilised GOX.

PMC9062467

c9ra01764j-f6.jpg

0.521998

f7d7b7c09c944cb39558a199990cc267

Remaining activity of GOX immobilised on pLys-HAp in cycling test.

PMC9062467

c9ra01764j-f7.jpg

0.521671

57c45088931d4b0cb7bf71cb8c630f9d

The glucose-sensitivity using GOX (free and immobilised on pLys-HAp). The inset shows the plot in the range of 4–80 μM of glucose.

PMC9062467

c9ra01764j-f8.jpg

0.497781

2994f7add3fb4b53ab6a01a96092fd15

Cyclic voltammograms of (A) graphene/imogolite/GOX/α-pLys-HAp (40 mg)-modified GCE and (B) graphene/imogolite/GOX/ε-pLys-HAp (40 mg)-modified GCE for the addition of 0–2.0 mM glucose in O2-saturated Dulbecco's PBS (pH 7.3) at a scan rate of 100 mV s−1. The insets in (A) and (B) show the linear plots for the concentration of glucose vs. peak current.

PMC9062467

c9ra01764j-f9.jpg

0.46558

653b98f0a74a45feb399cc4e0d9b237f

Aneurysm wall pathophysiology and progression. (a) The normal arterial vessel wall consists of an inner endothelial layer (tunica intima) followed by the two strength layers: internal elastic lamina and the smooth-muscle of the tunica media. Dotted line represents the region of the cross-sectional image displayed on the left (b) Regions of high WSS (blue arrow) (e.g., vessel bifurcations and outer wall of curved vessels) trigger an inflammatory cascade, increased protease activity, and breakdown of the tunica media and internal elastic lamina. Loss of integrity of the strength layers of the vessel wall cause outpouching of the vessel wall and formation of an early aneurysm bulge. (c) Enlargement of the aneurysm sac alters the flow dynamics, leading to areas of low WSS and high WSS (blue arrows). Areas of low WSS can develop thrombus, which trigger further inflammation and wall breakdown. Areas of persistent high WSS continue to experience protease activity and inflammation leading to continues degradation of the tunica media and internal elastic lamina.

PMC9062958

SNI-13-182-g001.jpg

0.441664

d2abe0ec2a784d859ffccd61aa27e0ab

High-risk aneurysm morphologies. (a) Standard saccular aneurysm morphology. (b) Aneurysm with daughter sac. (c) Aneurysm with high aspect ratio. (d) Aneurysm with high size ratio.

PMC9062958

SNI-13-182-g002.jpg

0.407504

de3b70d59d234f59b607240f74e49018

The total length stacked bar chart of 26 Ligusticum plastomes composed of four regions (LSC, IRb, SSC, and IRa). The numbers on the bar represent the length of the four regions. A–K Represents the genes at IR/SC borders. A ycf2; B petB; C rpl22; D rps19; E ycf1/ndhF; F ycf1; G trnN-GUU-ndhF; H trnL-CAA-trnH-GUG; I petB-trnH-GUG; J rps19-trnH-GUG; K rpl2-trnH-GUG. All the SSC/IRa borders are ycf1, which is indicated by asterisks

PMC9063207

12862_2022_2010_Fig1_HTML.jpg

0.543402

fba8fa4f62e94f9dad939fbb6fb0a371

Comparison of the GC content (GC%) of 26 Ligusticum plastomes using a radar-plot. From inside to out: SSC GC%, LSC GC%, Total GC%, IR GC%, and rRNA GC%. The background colors of purple, green, blue, and pink represent Selineae, Sinodielsia Clade, Acronema Clade, and East-Asia Clade, respectively

PMC9063207

12862_2022_2010_Fig2_HTML.jpg

0.424184

4fe0cf129fc343e1b38612ab9747db57

The RSCU values of 53 merged protein-coding sequences for 26 Ligusticum plastomes. Color key: the red values indicate higher RSCU values and the blue values indicate lower RSCU values

PMC9063207

12862_2022_2010_Fig3_HTML.jpg

0.389253

e1276ce301a94e1d812f5cdc27247e10

The dN/dS (ω) and nucleotide diversity (Pi) of the 79 protein-coding sequences within 26 Ligusticum plastomes

PMC9063207

12862_2022_2010_Fig4_HTML.jpg

0.476195

85f8bb8e3b2c4802b29629ceba6905bb

Phylogenetic relationships inferred from Maximum likelihood (ML) and Bayesian inference (BI) analyses based on 66 complete plastomes within Apiaceae. The bootstrap support values (BS) and posterior probabilities (PP) are listed at each node

PMC9063207

12862_2022_2010_Fig5_HTML.jpg

0.442818

ecc365fec3294bf38b3bd7b5f8168a48

Phylogenetic relationships of 66 Apiaceae species inferred from 76 common protein-coding sequences based on the coalescent-based approach using ASTRAL. The local posterior probabilities (LPP) are listed at each node

PMC9063207

12862_2022_2010_Fig6_HTML.jpg

0.433789

69aa5f9afa5946dba1c812dda3a35124

UV-vis absorption spectra of P(O-DBND-2T), P(N,O-DBND-2T) and P(N-DBND-2T) in diluted o-DCB (a) and as the thin film (b).

PMC9063523

c9ra01545k-f1.jpg

0.405163

37422eea578c44829ecbb238f0e013b1

Photovoltaic characteristics: J–V curves (a) and EQE (b) plots of polymer : PC71BM (1 : 2 w/w) optimal solar cells under the illumination of AM 1.5 G 100 mW cm−2.

PMC9063523

c9ra01545k-f2.jpg

0.456152

422396f7326a4e389f81d2a9a9358176

GIWAXS curves of polymer neat films (a) and TEM images of active layers containing P(N,O-DBND-2T) : PC71BM (b), P(O-DBND-2T) : PC71BM (c) and P(N-DBND-2T) : PC71BM (d) in weight ratio of 1 : 2.

PMC9063523

c9ra01545k-f3.jpg

0.446769

694e511aa61545a28e2f9e95d46029d0

Chromatograms (distribution of n-alkanes for the test oils).

PMC9064330

c9ra02775k-f1.jpg

0.429916

56fdbc764ede45ecadaf029aab91d789

Submerged oils formed observed by UV epi-fluorescence. Fluorescing green indicates the oil droplets.

PMC9064330

c9ra02775k-f2.jpg

0.477304

40babe3e3bb043c8ac805c5ff7f3a513

Adsorption isotherms of the three test oils. Note: the dash lines are the fitted line using the Langmuir isotherm.

PMC9064330

c9ra02775k-f3.jpg

0.466554

3a3382365fc84070a5a7e2d46fce8f3b

The kinetics of submerged oil formation for the three test oils. Note: the dashed lines are fitted by eqn (4).

PMC9064330

c9ra02775k-f4.jpg

0.450702

994bdf1c6a484ccb9435a302c9ffe5c7

Modeling of predicting the submerged oils formation as a function of sediment concentrations. The dash lines represent the model results computed using eqn (7) based on Kd = 0.5 and 1.5 mL mg−1. Note: The use of chemical dispersant and change of salinity lead to deviate from model results.

PMC9064330

c9ra02775k-f5.jpg

0.445267

0de5b0dabbeb4056876821eb75124976

Cell viability of ATP and UTP-treated cells. TNBC MDA-MB 231, Hs 578t and MDA-MB 468 cell lines and non-tumorigenic immortal mammary epithelial MCF-10A cells were treated for 48 hours with increasing concentrations of ATP or UTP, and cell viability was measured with the PrestoBlue HS assay. Error bars represent standard deviations calculated from three independent experiments performed in triplicate. The student’s t-test was applied to the to ascertain significance. * represents p < 0.05 and ** represents p < 0.01 when comparing ATP to UTP.

PMC9065442

fonc-12-855032-g001.jpg

0.397869

4bd33f59abce4da0915850e75dff551b

Cell viability of ATP-treated cells in the presence of P2RX inhibitors. TNBC cell lines and MCF-10A cells were treated for 48 hours with increasing concentrations of ATP in the presence of the P2RX inhibitor Iso-PPADS (20 µmol/L), the P2RX7 inhibitor A438079 (20 µmol/L) or the P2RX4 inhibitor 5-BDBD (20 µmol/L) or vehicle addition, and cell viability was measured using the PrestoBlue HS assay. Error bars represent standard deviations calculated from three independent experiments performed in triplicate. One way ANOVA with Tukey’s HSD was applied to ascertain significance. * represents p < 0.05 and ** represents p < 0.01 when comparing vehicle addition to Iso-PPADS, A438079 or 5-BDBD.

PMC9065442

fonc-12-855032-g002.jpg

0.549365

0bc4a7c8d8524dfe821ac99ff76e3b30

Comparing eATP release from paclitaxel-treated cells in the presence of inhibitors or vehicle addition. (A) TNBC and MCF-10A cells were treated with increasing concentrations of paclitaxel and the nucleoside phosphohydrolase inhibitors POM-1 (E-NTPDase inhibitor, 10 µmol/L), PSB 069 (E-NTPDase inhibitor, 10 µmol/L), ENNP1 inhibitor C (ENPP1 inhibitor, 10 µmol/L) or vehicle addition for six hours, and cell viability was measured using the PrestoBlue HS assay. Standard deviation was calculated from three independent experiments performed in triplicate. (B) eATP concentrations were measured in the supernatants of TNBC and MCF-10A cells after six hours of treatment with increasing concentrations of paclitaxel and nucleoside phosphohydrolase inhibitors or vehicle addition. Standard deviation was calculated from three independent experiments performed in triplicate. One way ANOVA with Tukey’s HSD was applied to ascertain significance. * represents p < 0.05 and ** represents p < 0.01 when comparing vehicle addition to PSB 069. We highlighted just the significance in the presence of PSB 069 because the cell viability results were consistently significant.

PMC9065442

fonc-12-855032-g003.jpg

0.509328

820bbffae5e44d80b266e6253a38b387

Examining the influence of P2RX inhibitors in combination with E-NTPDase inhibitor on cell viability and eATP release in paclitaxel-treated cells. (A) Paclitaxel-treated breast cancer MDA-MB 468 cell lines were treated for six hours with P2RX7 inhibitor A438079 (20 µmol/L) or P2RX4 inhibitor 5-BDBD (20 µmol/L) in the presence or absence of PSB 069 (10 µmol/L), and cell viability was measured by applying PrestoBlue HS assay. Standard deviation was calculated from three independent experiments performed in triplicate. We used the same values for both graphs for vehicle addition and PSB 069. (B) eATP concentrations were measured in the supernatants of paclitaxel-treated MDA-MB 468 cells after six hours of treatment. Standard deviation was calculated from three independent experiments performed in triplicate. We used the to the same values for both graphs for vehicle addition and PSB 069. The student’s t-test was applied to the applicable assays to ascertain significance. * represents p < 0.05 and ** represents p < 0.01 for A438079 and PSB 069 or 5-BDBD and PSB 069 when compared to PSB 069 alone.

PMC9065442

fonc-12-855032-g004.jpg

0.440819

f1044067a9764cc4b70cf2127f531256

Determining relative eATP content and cell viability in paclitaxel-treated cells in the presence of ivermectin or vehicle addition. (A) The graphs represent cell viability as measured using the Presto Blue HS assay +/- standard deviation from three independent experiments performed in triplicate in TNBC and MCF-10A cells after six hours of treatment with increasing concentrations of paclitaxel and the P2RX4 and P2RX7 activator ivermectin (10 µmol/L) or vehicle addition. (B) eATP content was measured in the supernatants of paclitaxel-treated TNBC and MCF-10A cell lines in the presence of the P2RX4 and P2RX7 activator ivermectin (10 µmol/L) or vehicle addition. The student’s t-test was applied to the applicable assays to ascertain significance. * represents p < 0.05 and ** represents p < 0.01 when comparing ivermectin to vehicle addition.

PMC9065442

fonc-12-855032-g005.jpg

0.428031

9426325427304cc4b3b60e348472132d

mRNA and protein expression analysis of P2RX4 and P2RX7 for all cell lines. (A) qRT-PCR was performed on mRNA of TNBC cell lines and MCF-10A cells using specific primers for P2RX4 and P2RX7. * represents p < 0.05 and ** represents p < 0.01. TNBC cell lines, MCF-10A cells, and HEK 293T cells transfected with P2RX4 or P2RX7 as positive controls were probed for (B) P2RX4 and (C) P2RX7, and GADPH was used as a loading control for western blot analysis repeated twice. HEK 293T cells transfected with P2RX7 were loaded at increasing protein concentrations of 1.0 µg, 2.5 µg, and 5.0 µg combined with lysates of control vector-transfected cells to keep the total loaded protein the same in each lane. Densitometry analysis was performed using Image Studio on the 75 kDa P2RX7 band. The student’s t-test was applied to the applicable assays to ascertain significance. * represents p<0.05 and ** represents p < 0.01 relative to MCF-10A; + represents p < 0.05 and ++ represents p < 0.01 relative to HEK293-empty vector transfected. (D) The calculated difference in mean fluorescence intensity (MFI) values between TNBC cell lines, MCF-10A cells, and HEK 293T cells transfected with P2RX4 or P2RX7 as positive controls stained with P2RX4 or P2RX7 specific antibody and the isotype control for the different cell lines examined. * represents p < 0.05 and ** represents p < 0.01 relative to MFI difference in MCF-10A cells; + represents p < 0.05 and ++ represents p < 0.01 relative to MFI difference in HEK293-empty vector transfected. O/E represents overexpressed.

PMC9065442

fonc-12-855032-g006.jpg

0.525798

c7accb745a4e4ff29fab1284f56a9a3c

Schematic displaying our proposed model for ATP release. Our proposed model suggests that ivermectin activates P2RX4 and P2RX7 leading to the release of ATP and the more ATP that accumulates extracellular can promote cell death especially in the presence of paclitaxel. In addition, the breakdown of ATP can be prevented in the presence of E-NTPDase inhibitors POM-1 or PSB 069. However, the release of ATP can be prevented in the presence of P2RX4 inhibitors 5-BDBD or Iso-PPADS or P2RX7 inhibitors A438079 or Iso-PPADS.

PMC9065442

fonc-12-855032-g007.jpg

0.411999

6c4b0d2dbf51406d833299e7969b9eb1

XRD analysis of vanadium-bearing titanomagnetite concentrates.

PMC9065754

c9ra03271a-f1.jpg

0.42295

229139b078274d83b64db7e623257c2d

Worn surface and wear debris of sintered samples. (a) and (b) without rare-earth oxide, (c) (d) La-0.2 wt%, and (e) and (f) Ce-0.4.

PMC9065754

c9ra03271a-f10.jpg

0.520469

a80b5c9dc0ad4068a1f8eb8088c7519e

XPS spectrum of the worn surface of sintered sample with different rare-earth addition: (a) carbon, (b) Fe on the worn surface of Re-0, (c) Fe on the worn surface of La-0.2, (d) Fe on the worn surface of Ce-0.4.

PMC9065754

c9ra03271a-f11.jpg

0.376181

aa44216db6744fa1890c89def179a580

XRD analysis of the pre-reduced powders.

PMC9065754

c9ra03271a-f2.jpg

0.577574

ae521a5b8b8f406fb8aa3e2b8b4b949f

Diagram of block-on ring tester (a) grinding wheel, (b) specimen, and (c) load.

PMC9065754

c9ra03271a-f3.jpg

0.438372

354d73a128b14454a2a0b1ad794f22bb

Microstructure of sintered sample (a) and EDS analysis of area A (b), B (c) and D (d).

PMC9065754

c9ra03271a-f4.jpg

0.36366

989af5fd0a7042c789bdfd1d42da03ee

XRD pattern of the sintered sample without rare-earth oxide.

PMC9065754

c9ra03271a-f5.jpg

0.431699

1a0e538021de42e4ab939800f010da8b

SEM micrographs of powders (a) without and with (b) 0.2 wt% La2O3, (c) 0.4 wt% La2O3, (d) 0.4 wt% CeO2 and (e) 0.6 wt% CeO2.

PMC9065754

c9ra03271a-f6.jpg

0.404877

38e19f5e8bea40c0a18d33029cee053d

Microstructure of the sintered specimens with (a) 0.2 wt% La2O3, (b) 0.2 wt% CeO2, (c) 0.4 wt% La2O3, (d) 0.4 wt% CeO2, (e) 0.6 wt% La2O3, (f) 0.6 wt% CeO2.

PMC9065754

c9ra03271a-f7.jpg

0.412863

ddc6af94931c4d14a3c1d310cf26407f

Hardness and relative density of Fe-based friction material with different rare earth.

PMC9065754

c9ra03271a-f8.jpg

0.402829

eb4a9abe0550420dbd42bc37d6315e1e

Wear rate and friction coefficient of Fe-based friction material with different rare earth addition.

PMC9065754

c9ra03271a-f9.jpg

0.420233

9e80b30cdb2d4630ab8e77a2f734ae01

Identification of cofilin-rich regions at the base of neuronal growth cone filopodia.a–c Immunofluorescence images of phalloidin (Alexa Fluor 488) alone (a), cofilin (Alexa Fluor 594) alone (b), and a merge of the two (c). Most of the cofilin signal emanates from linear aggregates near the base of filopodia. The white dashed line in c marks the position of the lamellipodial veil. d Merged immunofluorescence image of a growth cone with fascin (Alexa Fluor 488-green) and cofilin (Alexa Fluor 594-red) labeled, showing cofilin-rich regions at the base of filopodia as in c. Bottom-left inset: Split view of the boxed-out region. The white arrow points to the same location in each image and shows the point at which the fascin signal drops off and the cofilin signal intensifies. e Representative line scan intensity profile of a single filopodium showing the distribution of fascin and cofilin. The image above the graph shows a close-up view of the measured filopodium and the location where the line profile was drawn. The transition region is marked by two dashed lines. The images in a–c are representative images, but two independent experiments showed similar localization of cofilin and actin. d is a representative image from one of three independent experiments. Scale bars: (c) 5 µm (this also corresponds to a and b), d 5 µm. Source data are provided as a Source Data file.

PMC9068697

41467_2022_30116_Fig1_HTML.jpg

0.416944

b29faa2b41624e7b913720228450684d

Structural features of neuronal growth cone filopodia and their associated cofilactin bundles.a Overview image of a cryo-preserved growth cone on a Quantifoil EM grid. The green and red boxes represent growth cone regions similar to where the tomograms in b and c were imaged, respectively. b, c 5 nm-thick slices of tomograms from the tip (b) and base (c) of growth cone filopodia. In b, a bundle of actin filaments fills the entire cytoplasm. In c, branched networks of individual actin filaments can be seen surrounding a central bundle of hyper-twisted cofilactin filaments. White arrows point to the bundle. Lower-left insets: 68 nm-thick transverse cross-sections through each bundle, illustrating the hexagonal packing of filaments. The blue line in the main images show the plane from which the insets were taken. Bottom insets: Subtomogram averages of filament pairs in filopodial tips (below b) or in cofilactin bundles at the filopodial bases (below c). Cofilactin filaments have a shorter helical twist than F-actin and are out of phase with adjacent filaments. d EM map (blue) resulting from the subtomogram averaging of actin filaments in filopodial tips, and rigid body fitting of a previously reported atomic structure for F-actin (PDB ID: 6T1Y; green). e EM map (blue) resulting from the subtomogram averaging of cofilactin filaments near the base of filopodia, and rigid body fitting of a previously reported atomic structure of cofilactin (PDB ID: 3J0S; actin is green and cofilin is red). f Segmented filopodial protrusion with a schematic of filament centerlines overlaid (red). These lines are comprised of a series of points that were used for nearest neighbor analysis. g Nearest neighbor histograms showing the cumulative total of three normal actin filopodial bundles (green) and three cofilactin bundles (red). Scale bars: (a) 5 µm, (b) 200 nm (this also corresponds to the image in c), f 100 nm.

PMC9068697

41467_2022_30116_Fig2_HTML.jpg

0.459147

fa5d3a1a29b444e9b8f99f456af67748

Higher-order structure of filopodial bundle types.a Schematic model of the higher-order structure of actin (fascin-linked) and cofilactin bundles in growth cone filopodia (as they appear looking down the long axis of the bundle). Filaments in both bundle types are organized in layers and hexagonally packed (blue hexagons). Filaments in the actin bundle are all twisting in phase with one another, but in the cofilactin bundle filaments are rotated 90° with respect to their neighbors in the same layer. This creates columns of filaments that are oriented similarly to one another. The yellow dots on filaments in the hexagon correspond to filaments in b. b 17 nm-thick slices through tomograms of a filopodial tip (top) and a cofilactin bundle (bottom). In the cofilactin bundle, brackets show the wide portion of the helical twist while red arrows show the thin portion. The yellow dots correspond to the dots in a. For instance, the bracketed filament in layer two is directly between the two filaments in layers 1 and 3, only on a different Z-plane. Scale bars in b are 20 nm.

PMC9068697

41467_2022_30116_Fig3_HTML.jpg

0.4784

d256bdc063b14fdebca310516b361aad

Potential conflict between fascin and cofilin, and potential cofilactin interactions.a, b Top-down views of fascin-linked actin (a) and cofilactin (b) filaments. Both pairs of filaments are shown at interfaces where they are in phase with one another. In a, fascin (blue) is shown in its actin-binding pockets (22), two sites that are sterically blocked by the presence of cofilin in our model of cofilactin bundles (b). F-actin is green, and cofilin monomers are red. c Sideview of model cofilactin hexagonal unit. Dashed regions labeled 1 and 2 illustrate cross-sections shown in d and e, respectively. F-actin is green and cofilin is red. d, e Cross-sections through different regions of the hexagonal unit shown in c. Arrows point to the place where cofilin monomers on neighboring filaments are closest to each other (~2 nm apart at their closest residues). f Zoomed-in view of neighboring cofilins like those in the boxed-out region in e. Cys39 and Cys147 are displayed on each (cyan).

PMC9068697

41467_2022_30116_Fig4_HTML.jpg

0.52466

6e5b30cf550548de9dd1db082cdc4531

Tomography of cofilactin within filopodia.In all images, red arrows signify cofilactin and green arrows show normal F-actin. The top-right corner of each image shows their distance from the lamellipodial veil (positive values are distal from the veil and negative values are proximal from it). a A 13.3 nm-thick tomographic slice where individual cofilactin filaments are scattered throughout a fascin-linked actin bundle. b 13.3 nm-thick tomographic slice through a prospective transition region where a clear boundary (represented by the dashed line) exists between the F-actin on top and the cofilactin on bottom. c 13.3 nm-thick tomographic slice showing a pure cofilactin bundle). Scale bars: 50 nm.

PMC9068697

41467_2022_30116_Fig5_HTML.jpg

0.447194

c7ff18d3280148aeabf6c95a8d27753c

Cofilactin bundles facilitate bending and breaking of filopodial protrusions.a Single image of a whole-cell expressing tdTomato-Lifeact (pseudocolored green) and EGFP-cofilin (pseudocolored red). b, c Maximum intensity projections (MIP) of lower and upper boxed regions in a, respectively. MIPs include 40 images at 3 s intervals for 2 min total. Filopodia in b are examples of “resting” filopodia and (c) shows a “searching” filopodium. Dashed arrows indicate the direction of actin retrograde flow, and arrowheads indicate inflection points seen along the flexing filopodial bundles. The white dashed line marks the position of the lamellipodial veil. d–f 2-min movie montages showing behaviors exhibited by the cofilin-rich filopodia designated with the corresponding label in a. Arrowheads follow either a kink/breaking point (d), a cofilactin bundle “wave” (e), or an inflection point in a bending filopodium (f). In e, the wave is caused by the filopodial tip moving from left to right, which drags the attached base behind it in a flexible, wave-like motion. The localization of EGFP-cofilin and tdTomato-Lifeact shown in a was replicated in multiple cells from two independent experiments, and similar results were also seen using other fluorescent protein combinations (Supplementary Fig. 5). Scale bars: (a, b) 5 µm (scale bar in b also corresponds to image in c), (d) 500 nm (also corresponds to (e) and (f)).

PMC9068697

41467_2022_30116_Fig6_HTML.jpg

0.434371

1478987d4ff34e8281fb9ebb3de9d68d

Tomograms of growth cone filopodia in different dynamic states.In all images, red arrows signify cofilactin and green arrows show normal F-actin. a 13.3 nm-thick tomographic slice showing a ~90° kink in a growth cone filopodium. This filopodium is likely in the process of severing, like in Fig. 6d and Supplementary Movie 7. Cofilactin filaments can be seen near the apex of the kink in the bundle. b 13.3 nm-thick tomographic slice where the proximal portion of a filopodium appears to be moving from right to left in a wave-like motion. This is similar to the motion exhibited by the filopodium shown in Fig. 6e and Supplementary Movie 8. The dashed boxes on top and bottom represent the regions shown in the top and bottom zoomed-in insets (white boxes), respectively. The top zoomed-in view shows a cofilactin filament forming an S-curve through the fascin cross-linked bundle. The cofilactin filament is moving through the Z-axis, so the middle of the S-curve is not visible in this image. The bottom zoomed-in view shows, similar to the kink from (a), cofilactin filaments near the crest of the wave. c 13.3 nm-thick tomographic slice of a bend in a distal filopodial region. Here, cofilactin and actin coexist as separate bundles wrapping around one another. This tomogram resembles that shown in the movie from Fig. 6f and Supplementary Movie 9. Inset: TEM overview image showing the location of the tomogram in the main panel. Scale bars: a, b, and c represent 100 nm.

PMC9068697

41467_2022_30116_Fig7_HTML.jpg

0.42792

33b083be14ba4143b3b8d84d12396ab4

Current model.Schematic of filopodial actin bundle in a rigid (a) and flexible (b) state. As cofilactin filaments permeate the fascin-linked region of the filament, they competitively dislodge fascin cross-linkers and increase the flexibility of filopodial bundles. In the proximal region of the bundles, cofilactin filaments prevail and are cross-linked through either cofilin oligomers/self-association or by some, as of yet, unknown cross-linker.

PMC9068697

41467_2022_30116_Fig8_HTML.jpg

0.420134

9b02e2d755f449399fd10eb3b00db19e

Histidine levels were significantly higher in the hypersensitivity group. (A) Heatmap and cluster analysis of significant differential metabolites between the normal group (group 1) and the hypersensitivity group (group 2). (B) Z-score graph of significant differential metabolites. l-Histidine levels in the normal group were significantly higher than those in the hypersensitivity group. (C–F) Four significant differential metabolites levels between the normal and hypersensitivity groups included l-histidine, urocanic acid, myristicin, and d-aldose. (G) Pathway enrichment analysis. Histidine metabolism showed a high impact on hypersensitivity (*p < 0.05, **p < 0.01).

PMC9068896

fphar-13-827446-g001.jpg

0.389697

9e6c0d34e45e457a8d1b4b30ff31c223

Receiver operating characteristic (ROC) curves and content level of 30 differential metabolites.

PMC9068896

fphar-13-827446-g002.jpg

0.436613

ef857c786e5b48d6bc96b1a00226a019

Histidine supplement-enhanced PLD-induced HSR in rat model. (A) H&E staining (100x). PLD injection could induce pulmonary edema. Histidine supplement-aggravated pulmonary edema, but this phenomenon could be alleviated by histidine decarboxylase inhibitor: bromo-3-hydroxybenzoic acid (BHBA). (B) Toluidine blue staining (mast cell staining) (200x). Histidine could increase mastocyte infiltration in the trachea and lungs and significantly increase mastocyte degranulation in the trachea and larynx after PLD injection. (C) Degranulation and undegranulation mast cell counting. (D) Histidine supplement group showed significantly increased IgE levels. BHBA treatment could decrease IgE levels significantly (PLD, PEGylated liposomal doxorubicin; HSR, hypersensitivity reaction; *p < 0.05, **p < 0.01, ***p < 0.001).

PMC9068896

fphar-13-827446-g003.jpg

0.492023

d2252878f3ca49a3bfd0da03ba1b8dcf

Corona virus binds to Lung Epithelial Cells which causes the activation of inflammatory cells and cytokine storms

PMC9069147

IJPVM-13-45-g001.jpg

0.503843

a01b8204cad047d882e988124f40658c

Schematic representation of the multimodal X-ray microscopy experimental setup. KB mirrors focus X-rays down to a focal spot of about 70 nm and with a 1.2 mrad divergence. The sample is mounted on a motor stack enabling xyz translation and θ, φ rotation, i.e. around the x and y axes, respectively. The sample can be translated in and out of the X-ray beam focus via translation along z (total travel range 46 mm), effectively tuning the X-ray beam size. An ion chamber is positioned downstream of the KB chamber to monitor the incoming X-ray photon flux. An optical in-line microscope provides a view onto the sample along the optical z axis. A fluorescence detector is positioned 15 mm away from focus, with a 15° orientation with respect to the focal plane. An in-line area detector is positioned 1.12 m downstream of the focus to collect holograms.

PMC9070709

s-29-00807-fig1.jpg

0.490743

991d191b7afe4bb083da3c076e2b4174

Preliminary reconstructions from a 5 × 5 holography scan covering a potential ROI of a section of an Os-stained human peripheral sural nerve biopsy from a healthy male. These qualitative results were used to delimit a ROI on which to perform a nanoscale X-ray fluorescence scan, as more conveniently annotated in Fig. 3 ▸. Further processing followed. The frame number is annotated on each frame, revealing the scanning sequence.

PMC9070709

s-29-00807-fig2.jpg

0.476043

e3222abd6f904fe1ab842ceb8a0d4d6a

Quantitative result obtained from processing the images from Fig. 2 ▸. The ROI on which a nanoscale X-ray fluorescence scan was performed is highlighted by the white rectangle. A blood vessel (blue arrow) as well as myelin layers surrounding several axons (red arrows) can be identified. The intensity scale represents relative electron density variations and for convenience was converted into units of Å−3.

PMC9070709

s-29-00807-fig3.jpg

0.496383

9b0bff561368482e9b4479a1af7d7b96

(a)–(c) Area mass density maps obtained via nanoscale X-ray fluorescence emission spectroscopy for (a) Cl, (b) Fe and (c) Os within a ROI of a section of an Os-stained human peripheral sural nerve biopsy from a healthy male. Linear intensity scales are shown in units of ng mm−2. (d) RGB representation of the same region including electron density information from the holography scan: red, green and blue channels represent electron density, Fe and Os area mass densities, respectively. A 10 µm scale bar for all images is given in (a).

PMC9070709

s-29-00807-fig4.jpg

0.489397

55d3bd280c2b4912bd0bc4ea90bb5d21

Postprandial 1,2-dicarbonyl compound concentrations in older (25 months) and younger (5 months) male mice. Data are shown as Violin plots; dotted lines represent median and quartiles. Student’s t-test for normally distributed data and Mann–Whitney U test for nonnormally distributed data were used to assess differences between age groups. 25 months old (n = 11), 5 months old (n = 14). 3-DG = 3-deoxyglucosone; GO = glyoxal; MGO = methylglyoxal; 25 M = 25 months old; 5 M = 5 months old; p < .05.

PMC9071428

glab331_fig1.jpg

0.456125

d58d26f7c0a44d7eaa2da5280acedc4b

Fasting 1,2-dicarbonyl compound concentrations in older and younger women (A) and men (B). Data are shown as Violin plots; dotted lines represent median and quartiles. Student’s t-test for normally distributed data and Mann–Whitney U test for nonnormally distributed data were used to assess differences between age groups. YW (n = 19), OW (n = 19), YM (n = 15), OM (n = 15). 3-DG = 3-deoxyglucosone; GO = glyoxal; MGO = methylglyoxal; YW = younger women; OW = older women; YM = younger men; OM = older men; p < .05.

PMC9071428

glab331_fig2.jpg

0.476952

62f927fad4ab49faabb5e8d6b86b39f1

Postprandial 1,2-dicarbonyl concentrations and response (iAUC) to a dextrose challenge in older and younger women and men. Data are shown as mean ± SD. Repeated measures analysis of variance was used to examine changes over time and differences between age groups, and Mann–Whitney U test was used to assess age differences of the postprandial response (iAUC). *Significantly different between age groups. YW (n = 19), OW (n = 19), YM (n = 15), OM (n = 15). iAUC = incremental area under the curve; 3-DG = 3-deoxyglucosone; GO = glyoxal; MGO = methylglyoxal; YW = younger women; OW = older women; YM = younger men; OM = older men; p < .05.

PMC9071428

glab331_fig3.jpg

0.405949

61457424ace84c04a9025d6761df8c9c

Associations of glucose response with 3-DG (A) and GO (B) response as well as insulin response with MGO response (C) to a dextrose challenge. (A) No significant correlation in women, men: r = 0.782, p = .008. (B) No significant correlation in women, men: r = 0.707, p = .022. (C) No significant correlation in women, men: r = 0.784, p = .007. YW (n = 19), OW (n = 19), YM (n = 15), OM (n = 15). iAUC = incremental area under the curve; 3-DG = 3-deoxyglucosone; GO = glyoxal; MGO = methylglyoxal; YW = younger women; OW = older women; YM = younger men; OM = older men; p < .05.

PMC9071428

glab331_fig4.jpg

0.457334

fe5311e4dd2c4323a6754a6d5e03aae0

Flow diagram of the simulation, benchmarking, and experimental data evaluation strategy presented in the manuscript. Briefly, SplattDR was developed to simulate dose–response scRNAseq data and validated based on experimental dose–response data. Simulated datasets were generated varying diverse parameters 10 times and then used to assess the performance of each test method. Each test method was also assessed using experimental data from the hepatic snRNAseq dose response dataset obtained from male mice gavage every 4 days for 28 days with 0.01, 0.03, 0.1, 0.3, 1, 3, 10 or 30 μg/kg TCDD. Related figures for each analysis from the main body are noted.

PMC9071439

gkac019fig1.jpg

0.42975

52a53f4cf5254c458e0a1d49a611aca5

Comparison of simulated and real dose–response data. (A) Relationship between gene-wise mean expression and percent zeroes for simulated and real dose–response data. Simulation data consisted of 10 000 genes and nine dose groups based on parameters derived from experimental dose–response snRNAseq data. Black line represents a fitted model to the experimental data from which the normalized root mean square deviation (NRMSD) of simulated data was determined. (B) Relationship between gene-wise mean expression and variance for simulated and experimental data. NMRSD was calculated for simulated data from the fitted model represented as a black line. (C) Distribution of log(fold-changes) in experimental and simulated data showing the median and minimum and maximum values. (D) Principal components analysis of simulated data colored according to simulated dose groups. (E) NMRSD estimated relative to fitted model in A,B for simulated data generated from initial parameters derived from published hepatic scRNAseq (two dose; GSE148339), hepatic whole cell (whole cell; GSE129516), and peripheral blood mononuclear cell (PBMC; GSE108313) datasets. (F) NMRSD estimated relative to model fitted to cell-type specific experimental dose–response data when simulated from initial parameters estimated from that same cell type. Box and whisker plots show median NMRSD, 25th and 75th percentiles, and minimum and maximum values.

PMC9071439

gkac019fig2.jpg

0.40547

9393420bace24831bf038a4622e7fc70

Classification performed of DE analysis tests. (A) ROCs estimated from simulated dose–response scRNAseq data for nine DE test methods including all genes expressed in at least one cell (unfiltered). (B) ROCs for nine DE test methods after filtering simulated dose–response scRNAseq data for genes expressed in only ≥5% of cells (low levels) in at least one dose group. (C) Precision-recall curves (PRCs) for nine DE test methods on unfiltered simulated dose–response scRNAseq data. (D) PRCs for nine DE test methods on filtered simulated dose–response scRNAseq data. Lines represent the mean values and shaded region reflects the standard deviation for 10 independent simulations. (E) Precision of DE test methods. (F) FPR of DE test methods. (G) MCC for test methods. (E–G) Box and whisker plots median values, 25th and 75th percentiles, and minimum and maximum values for 10 independent simulations. Points reflects values for each independent simulation. Panels display comparisons of unfiltered and filtered datasets.

PMC9071439

gkac019fig3.jpg

0.433991

07e550188fbf4a399430f9c372ce5640

Evaluation of Type I and II error control. (A) False positive rate (FPR) of 9 differential expression test methods estimated from negative control (0% DE genes) simulated dose–response scRNAseq data including all genes expressed in at least 1 cell (unfiltered) and genes expressed in only ≥ 5% of cells in at least one dose group (filtered). (B, C) Logistic regression models were fitted to negative control data to predict the probability of false positive identification using percent zeroes and mean expression as covariates. Lines represent the predicted probability of false positive classification with the shaded region representing the 95% confidence interval. (D) False negative rate (FNR) of nine differential expression test methods estimated from positive control (100% DE genes) simulated dose–response scRNAseq data including unfiltered and filtered datasets. (E, F) Logistic regression models were fit to positive control data. Lines represent predicted probability of false negative classification with shaded region representing the 95% confidence interval.

PMC9071439

gkac019fig4.jpg

0.496533

df576553fcc34d4585990e8a9d5f80c9

Matthews correlation coefficient (MCC) from sensitivity analyses of differential expression test methods. (A) MCC for nine DGEA test methods determined from simulated dose response data with varying number of cells per dose group. Simulations consisted of 5,000 genes with a probability of differential expression of 10% and 9 dose groups. (B) MCC for simulated data varying the cells numbers by dose group. The number of cells in each of the nine doses groups is shown on the right. (C) MCC for varying proportion of differentially expressed genes. (D) MCC when varying the mean fold-change (location) of repressed differentially expressed genes. (E) MCC for varying distribution of fold-change (scale) of differentially expressed genes. (F) MCC for varying dropout rates calculated as in Supplementary Table S3. Points represent median and error bars represent minimum to maximum values. Boxplots represent median, 25th to 75th percentile, and minimum to maximum values. Each analysis consisted of 10 replicate datasets including all genes expressed in at least one cell (unfiltered) and genes expressed in ≥5% of cells in at least one dose group (filtered).

PMC9071439

gkac019fig5.jpg

0.440178

3773fa32a7084a4e892b195a546cd6bc

Agreement of differential expression test methods on experimental dose–response data. (A) Upset plot showing the intersection size of genes identified as differentially expressed by nine different test methods in hepatocytes from the portal region of the liver lobule. (B) Intersect of differentially expressed genes in portal fibroblasts. (C) Intersect size in hepatic stellate cells. Vertical bars represent the intersect size for test methods denoted by a black dot. Horizontal bars show the total number of differentially expressed genes identified within each test (set sizes). Only intersects for which genes were identified are shown. Genes were considered differentially expressed when (i) expressed in >5% of cells within any given dose group and (ii) exhibit a |fold-change| ≥ 1.5. A heatmap in the upper left corner of each panel shows the pairwise AUCC comparisons for the 500 lowest P-values. (D) Relative proportion of cell types identified in each dose group of the real dataset for the cell types in (A–C). Experimental snRNAseq data was obtained from male mice gavaged with sesame oil vehicle (vehicle control) or 0.01–30 μg/kg TCDD every 4 days for 28 days. (E) Graph metrics for gene set enrichment analysis of portal fibroblasts grouped by similarity in gene membership. Violin plots show distribution of node-wise values for each test method. (F) Network visualization of significantly enriched (adjusted P-value ≤ 0.05) gene sets using the Bayes factor ranked genes of portal fibroblasts. Groups of ≥2 nodes were manually annotated following commonality in the gene set names. Each node represents a gene set with the size of the node representing the number of genes in a gene set, and edges connect nodes with ≥50% overlap.

PMC9071439

gkac019fig6.jpg

0.465634

992c09a99bbc4a58978ca6436e9a339f

Median ranking of differential expression test methods across all simulations. The median rank of each test method was calculated for AUPRC, AUROC, MCC, FNR and FPR. Tests were grouped according to intended application including fit-for-purpose tests developed for the analysis of dose–response datasets, multiple group tests, and two group tests. The overall rank represents the median value for the five key metrics presented here.

PMC9071439

gkac019fig7.jpg

0.393916

2ab64ca0949a48fa89c4d64172480268

The pattern classification of tumor microenvironment (TME). (a) Optimal number of clusters: K value calculated by the elbow method and gap statics algorithm. The ordinate axis represents total within sum of square; the abscissa axis represents the number of clusters K. (b) Consensus matrix heat map (K = 3): ConsensusClusterPlus was used for unsupervised class discovery (1000 iterations, k = 1 : 10). The optimal k value of 3 was determined using the elbow method and gap statics, combined with the correlation between the final classification and survival. (c) The distribution ratio of all kinds of immune cells in different TME clusters. (d) Clustering heat map of the distribution ratio of all kinds of immune cells in different TME clusters. (e) Survival analysis for different TME clusters: the red curve represents the TME cluster 1, the blue curve represents the TME cluster 2, and the yellow curve represents the TME cluster 3. The ordinate axis represents the probability of survival, and the abscissa axis represents the survival days.

PMC9071896

BMRI2022-5673810.001.jpg

0.456703

32d746738c974c51a9c41fcb1716fa75

Evaluation of TMEscore model and analysis of its correlation with mutation load. (a) The meta-analysis results of TMEscore model in different datasets: training set, testing set, TCGA, TCGA different stages, metastatic breast cancer, and prognosis evaluation of drug treatment. (b) Correlation analysis between TMEscore and mutation loads in different subtypes (basal, Her 2, Lum A, Lum B, and normal): the ordinate axis represents total mutations, and the abscissa axis represents TMEscore. (c) TMEscore box plots in different subtypes (basal, Her 2, Lum A, and Lum B). (d) Survival analysis results in four different subtypes of breast cancer (basal, Her 2, Lum A, and Lum B): the ordinate axis represents the probability of survival, and the abscissa axis represents the survival days. Different colors represent different subtypes. (e) Survival analysis of luminal A subtype after grouping according to TMEscore: the ordinate axis represents the probability of survival, and the abscissa axis represents the survival days. Different colors represent different TMEscore subgroups (high TMEscore and low). (f) Survival analysis of luminal B subtype after grouping according to TMEscore: the ordinate axis represents the probability of survival, and the abscissa axis represents the survival days. Different colors represent different TMEscore subgroups (high TMEscore and low).

PMC9071896

BMRI2022-5673810.002.jpg

0.425939

d27306a1ab2c43d4b12a7ecc0a8f1e47

Overview of mutations in 1039 TCGA-BRCA samples. (a) Tumor mutation profile. A1: variant classification of 1039 tumor samples. Missense mutations were the main mutation type in BRCA. A2: variant type of 1039 tumor samples. The source of mutations was mainly SNPs (mostly C>T) followed by indels. A3: SNV class of 1039 tumor samples. A4: variants per sample among 1039 tumor samples. A5: variant classification summary of 1039 tumor samples. A6: top 10 mutated genes in 1039 tumor samples. MUC4 was the most common mutated gene, followed by TTN. (b) Gene mutation distribution and phenotype in different TMEscore groups. B1: the distribution of mutations and mutation annotations of 24 genes in TMEscore high group. B2: the distribution of mutations and mutation annotations of 24 genes in TMEscore low group. (c) The frequency distribution of common gene mutations. Among them, the mutation rates of PIK3CA, TP53, KMT2C, GATA3, and MUC4 in the two subgroups have statistically significant differences.

PMC9071896

BMRI2022-5673810.003.jpg

0.451255

97b6d41d020c4b26be46b9c3c0d7938c

The analysis results of CNV. (a) The occurrence of chromosome arm-level amplification and deletion in different TMEscore groups: the abscissa axis represents the chromosome locus, and the ordinate axis represents the frequency of copy number alterations. Red represents the high TMEscore group, and the other one represents the low TMEscore group. ∗ represents statistical differences in frequency between the two groups. (b) Distribution of copy number amplification and deletion regions in high TMEscore group: 11q13.3 was the most significant in the amplified region, and 11q23.1 was the most significant in the deletion region. (c) Distribution of copy number amplification and deletion regions in TMEscore_low group: the most significant amplification region was located at 8q24.21, and the most significant deletion region was located at 8p23.2. (d) Ploidy analysis results in high and low TMEscore groups: ∗ represents statistical differences in frequency between the two groups. (e) Purity analysis results in high and low TMEscore groups: ∗∗ represents statistical differences in frequency between the two groups.

PMC9071896

BMRI2022-5673810.004.jpg

0.438062

bdbea8658c344e9f9cb116970067413e

The analysis results of miRNA and mRNA. (a) Functional annotation of differentially expressed miRNA: the ordinate axis represents different miRNAs, and the abscissa axis represents the functional annotations of miRNAs. (b) Volcano map of differentially expressed genes (DEG): the red part on the right shows the upregulated TOP 9 genes, and the blue on the left shows the downregulated top 2 genes. (c) Heat map of differentially expressed genes (DEG). (d) GO enrichment analysis of differentially expressed genes (DEG): the abscissa axis represents the number of genes, and the ordinate axis represents the results of CC (cellular component), BP (biological process), and MF (molecular function). (e) KEGG enrichment analysis of differentially expressed genes (DEG): the abscissa axis represents the number of genes, and the ordinate axis represents the corresponding pathways.

PMC9071896

BMRI2022-5673810.005.jpg

0.427068

1e225930a169458b96183c12b7784ab0

Comprehensive analysis results of tumor samples. (a) Volcano map of differentially methylated sites: 217 significantly different methylation sites were detected, and 67 methylation sites related to survival were obtained. (b) The survival analysis results of hsa-mic-1307 in different subgroups: the abscissa axis represents the survival time, and the ordinate axis represents the survival probability. The red curve represents high expression, and the blue curve represents low expression. (c) The survival analysis results of LRRC48 in different subgroups: the abscissa axis represents the survival time, and the ordinate axis represents the survival probability. The red curve represents high expression, and the blue curve represents low expression. (d) The survival analysis results of cg25726128 in different subgroups: the abscissa axis represents the survival time, and the ordinate axis represents the survival probability. The red curve represents high expression, and the blue curve represents low expression. (e) Immunotherapy efficacy score calculated by TMEscore group: the abscissa axis represents the TMEscore subgroup, and the ordinate axis represents TIDE. ∗∗ represents that the analysis result is statistically significant. (f) Using ROC analysis to evaluate the predictive ability of TMB, TMEgroup, and TMB+TME group on the effect of immunotherapy. (g) The relationship between MSI and TMEscore: the abscissa axis represents different MSI subgroups, and the ordinate axis represents TMEscore. ∗∗ represents that the analysis result is statistically significant. (h) Comprehensive genome landscape of BRCA (47 survival-related genes, P < 0.01).

PMC9071896

BMRI2022-5673810.006.jpg

0.435716

5a232d636ab149738c37e168fb740006

1H NMR spectra of the monomer.

PMC9071944

c9ra04828f-f1.jpg

0.424406

cacfa72d94d4496388863b788b8c8279

Results from nanoindentation tests for the cured resin.

PMC9071944

c9ra04828f-f10.jpg

0.527658

e84c6d2f30f14a2fabd5abf62eae3336

DMA curves of the cured resin.

PMC9071944

c9ra04828f-f11.jpg

0.514916

feebf9bcfcf641afbba37c0d7f1a1858

FT-IR spectra of the monomer and resin.

PMC9071944

c9ra04828f-f2.jpg

0.522294

33bd4cabe51a416b971b872b861a875e

DSC curve of Monomer 3 at a heating rate of 10 °C min−1 in N2.

PMC9071944

c9ra04828f-f3.jpg

0.52205

5f211f51f19f4808910ea1257465a1df

TG curve of the cured resin in N2 with a heating rate of 10 °C min−1.

PMC9071944

c9ra04828f-f4.jpg

0.517435

68ff41b5cfce4019883a85573d73aae0

DTG curve of the cured resin in N2 with a heating rate of 10 °C min−1.

PMC9071944

c9ra04828f-f5.jpg

0.447709

34656cadaf45438e9bf2cb2df0514582

Contact angle of water on the cured resin.

PMC9071944

c9ra04828f-f6.jpg

0.470885

89bb001c057c4a5987bd38d57a378962

AFM images of the cured resin film: (a) planar graph and (b) stereogram.

PMC9071944

c9ra04828f-f7.jpg

0.507214

b37ea1564a034505943e7a7c2842a42a

Dielectric constant and dielectric loss of the cured resin.

PMC9071944

c9ra04828f-f8.jpg

0.45041

1d3c36c63c7847ccb13a80562311ed43

X-ray diffraction (XRD) patterns of the cured resin (powder).

PMC9071944

c9ra04828f-f9.jpg

0.415888

9be29a28cef6468c9ec6b2217afd5b47

Reagents and conditions: (i) NaNO2, concentrated HCl, 0 °C, 1 h; HNO3 : H2O (3 : 2), 17 °C, 75 min; (ii) EtOH, reflux, 24 h; (iii) pyridine, 50 °C, 30 min.

PMC9072087

c9ra05712a-f1.jpg

0.428227

afa554f4fc7249d2b6d146aba4575d51

Optical microscope and scanning electron micrographs of the hyphae of S. sclerotiorum grown on PDA medium with DMSO or compounds 2, 5c at 25 °C. Optical microscope: (A) untreated control, 0.5% DMSO, ×400; (B) compound 2 at 0.0016 mM (EC50) treatment, ×400; (C) compound 5c at 0.0030 mM (EC50) treatment, ×400; scanning electron microscopy: (D) untreated control, 0.5% DMSO, ×1500; (E) after 72 h compound 2 at 0.0016 mM (EC50) treatment, ×1500; (F) after 72 h compound 5c at 0.0030 mM (EC50) treatment, ×1500.

PMC9072087

c9ra05712a-f2.jpg

0.371974

cf1a1aa5ec81441cab1d4491eb08cab7

In vivo protective efficacy of compounds 2, 5c and azoxystrobin against S. sclerotiorum on rape leaves.

PMC9072087

c9ra05712a-f3.jpg

0.536259

34d674f0972a42cab215f027ca7845bf

DSC of perdecanoic acid at a heating rate of 10 °C min−1.

PMC9072111

c9ra06087a-f1.jpg

0.448481

c1849a434a0c40049efaab6c878cf5ff

The activity of peracids in the model oxidation of 2-adamantanone. Reaction conditions: 2-adamantanone (0.100 g, 0.67 mmol), peracid (1.34 mmol), toluene (2 mL), 25 °C, 1200 rpm.

PMC9072111

c9ra06087a-f2.jpg

0.523724

baf7c9d370074904bcb40d09734d2605

The influence of the solvent for the model oxidation of 2-adamantanone. Reaction conditions: 2-adamantanone (0.100 g, 0.67 mmol), perdecanoic acid (1.34 mmol), solvent (2 mL), 25 °C, 1200 rpm.

PMC9072111

c9ra06087a-f3.jpg

0.443058

fa075fe9534e4f3abf528bd3be6f5133

The influence of the temperature for the model oxidation of 2-adamantanone. Reaction conditions: 2-adamantanone (0.100 g, 0.67 mmol), perdecanoic acid (1.34 mmol), toluene (2 mL), 1200 rpm.

PMC9072111

c9ra06087a-f4.jpg

0.476406

f9228813f2784f4f80d4f438bc8cd89c

The influence of molar ratio ketone : oxidant for the model oxidation of 2-adamantanone. Reaction conditions: 2-adamantanone (0.100 g, 0.67 mmol), perdecanoic acid, toluene (2 mL), 35 °C, 1200 rpm.

PMC9072111

c9ra06087a-f5.jpg

0.468649

a3e5042b9d8e40da86d95a1661248c76

(a) XRD pattern, TEM image (inset), (b) XPS spectrum and (c) proton longitudinal r1 and transverse r2 relaxivities (measured at 1.41 T and 37 °C) of pristine Fe3O4/γ-Fe2O3 nanoparticles.

PMC9072193

c9ra07227f-f1.jpg

0.486335

5cb2f938e59e42ac97ead1144f8f1451

Proton longitudinal r1 and transverse r2 relaxivities (measured at 1.41 T and 37 °C) of (a) Ca2+, (b) Fe3+, (c) Na+, (d) Mg2+, (e) Zn2+, (f) Ni2+, (g) Co2+, and (h) Cd2+ adsorbed Fe3O4/γ-Fe2O3 nanoparticles.

PMC9072193

c9ra07227f-f2.jpg

0.454902

15cc2705f2eb4d70b8d41e42ac8bbdaa

Dependence of (a) r1 and (b) r2 values on Xr/Z with regard to various cation-adsorbed Fe3O4/γ-Fe2O3 nanoparticles. The experimental data are plotted as solid squares, and the solid lines are fitting results according to eqn (1).

PMC9072193

c9ra07227f-f3.jpg

0.388584

88c5312fb369479fb1a7e6a7c902d54e

Dependence of (Xr/Z − xc)/w values for various cation-adsorbed Fe3O4/γ-Fe2O3 nanoparticles.

PMC9072193

c9ra07227f-f4.jpg