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In-app service
PMC9034646
42979_2022_1092_Fig3_HTML.jpg
0.412309
904d50083c3842fb86282b49bb5151d4
Weekly survey
PMC9034646
42979_2022_1092_Fig4_HTML.jpg
0.437473
758e007481b14f52a64e7090ff2a2e8d
Predicted compliance ratio for a subject
PMC9034646
42979_2022_1092_Fig5_HTML.jpg
0.375821
1f2a3782913f4b9c82e73adc6bd2fcbb
Observed compliance ratio for a subject
PMC9034646
42979_2022_1092_Fig6_HTML.jpg
0.523548
92c6fdb4d6c04b03bca2716f59fe101e
Average predicted vs observed CR
PMC9034646
42979_2022_1092_Fig7_HTML.jpg
0.448057
fd15511c2c9448ffb99ca8725ed02abd
Aggregated ER w(/o) personalization
PMC9034646
42979_2022_1092_Fig8_HTML.jpg
0.418301
a3f99e87131f49c7a4d8b0145672325c
Individual ER average (over 11 weeks)
PMC9034646
42979_2022_1092_Fig9_HTML.jpg
0.385544
ae8d1fa31fa542b4946da4f00d909760
Histogram of days since ICU admission until the first candidemia episode between COVID-19 positive and negative patients (combined pandemic and pre-pandemic period).
PMC9035354
gr1.jpg
0.451642
7017c4b6cc4e4f3da8fe2a9b8a4a4568
(A) Production network among various C1 and C2 feedstocks. CO2 and lignocellulosic biomass serve as the two ultimate carbon sources for all the liquid feedstocks. H2 is used for the reduction of CO2 and CO. O2 is required for the oxidization of methane to produce methanol and formate. Gaseous feedstocks (CO2, CO, H2) are in circles, while liquid feedstocks (methanol, formate) are in boxes. The formats of below figures are the same in colour and shapes. (B) Free energy and the oxidation state of C1 and C2 species (Aresta et al., 2014). Synonyms: g, gas; l, liquid, s, solid; aq, aqueous.
PMC9035589
fbioe-10-874612-g001.jpg
0.425749
4449e2ee0be74b02913d091634eb0e7b
The Calvin-Benson-Bassham (CBB) cycle and its application in metabolic engineering. (A) The simplified CBB cycle. (B) Autotrophic E. coli harnessing the CBB cycle. (C) The CBB-enabled synthetic autotrophic P. pastoris. Enzymes: RuBisCO, ribulose-1,5-bisphosphate carboxylase/oxygenase; PrkA or Prk, phosphoribulokinase; FDH, formate dehydrogenase; CA, carbonic anhydrase; PfkA/B, 6-phosphofructokinase; Zwf, glucose-6-phosphate dehydrogenase; Aox1/2, alcohol oxidase; DAS1/2, dihydroxyacetone synthase; Fld1, formaldehyde dehydrogenase; Fgh, S-formylglutathione hydrolase; PGK1, phosphoglycerate kinase; TDH3, glyceraldehyde-3-phosphate dehydrogenase; TPI1, triosephosphate isomerase; TKL1, transketolose. Metabolites: RuBP, ribulose-1,5-bisphosphate; Ru5P, ribulose-5-phosphate; 3PG, 3-phosphoglycerate; 1,3BPG, 1,3-diphosphoglycerate; GAP, glyceraldehyde-3-phosphate; DHAP, dihydroxyacetone phosphate; FBP, fructose 1,6-bisphosphatase; R5P, ribose 5-phosphate. Reduced feedstocks (methanol, formate, xylose) and cofactors (ATP, NAD(P)H) are in blue. Genes/enzymes are in red.
PMC9035589
fbioe-10-874612-g002.jpg
0.472519
ad0bc3fa7c444c40b575bdf0afeb78a3
The Wood-Ljungdahl pathway (WLP). Enzymes: ACS, acetyl-CoA synthase; CODH, carbon monoxide dehydrogenase; FDH, ormatedehydrogenase; PFOR, pyruvate:ferredoxin oxidoreductase. Metabolites/cofactors: THF, tetrahydrofolate; FDred, reduced ferredoxins. Reduced cofactors (ATP, NAD(P)H, FDred) are in blue. Genes/enzymes are in red.
PMC9035589
fbioe-10-874612-g003.jpg
0.413168
aa4e95b277ce493cb96ed0cefa179051
The reductive tricarboxylic acid (rTCA) cycle. Enzymes: PyrS, pyruvate synthase; PEPC, PEP carboxylase; KGS, α-ketoglutarate synthase; ICDH, isocitrate dehydrogenase. Metabolites: PEP, phosphoenolpyruvate. Dashed arrows are multiple enzymatic reactions.
PMC9035589
fbioe-10-874612-g004.jpg
0.431017
6341bd71f442488b9cfe3450edab2ad8
The 3-hydroxypropionate–4-hydroxybutyrate (3HP-4HB) cycle and the dicarboxylate–4-hydroxybutyrate (DC–4HB) cycle. Enzymes: AcC, acetyl-CoA carboxylase; PrC, propionyl-CoA carboxylase; PyrS, pyruvate synthase; PEPC, PEP carboxylase.
PMC9035589
fbioe-10-874612-g005.jpg
0.41385
cfac0b6ce239467293bc97ed434925a4
The reductive glycine pathway (rGlyP). The rGlyP has two variants: serine deaminase pathway (in orange) and glycine reductase pathway (in black). Enzymes: FDH, ormatedehydrogenase; GCS, glycine cleavage/synthase system; GlyA, serine hydroxymethyltransferase; Sda, serine deaminase; GRC, Glycine reductase complex. Metabolites: THF, tetrahydrofolate.
PMC9035589
fbioe-10-874612-g006.jpg
0.407069
8b5e7db1f84b4c209511cafcebe41e48
Methane and methanol assimilation routes. In nature, three main routes were identified: ribulose monophosphate (RuMP) cycle, xylose monophosphate (XuMP) cycle or dihydroxyacetone (DHA) cycle and Serine cycle. Enzymes: HPS, 3-hexulose-6-phosphate synthase; PHI, 6-phosphate-3-hexuloisomerase; PGDH, 6-phosphogluconate dehydrogenase; MMO, methane monooxygenase; MDH, methanol dehydrogenase; AOX, alcohol oxidase; FADH, formaldehyde dehydrogenase; FDH, formate dehydrogenase. Metabolites: H6P, hexulose 6-phosphate; F6P, fructose-6-phosphate; FBP, fructose 1,6-bisphosphatase; G6P, glucose-6-phosphate; 6PG, 6-phosphogluconate; GAP, glyceraldehyde-3-phosphate; DHAP, dihydroxyacetone phosphate; R5P, ribose 5-phosphate; DHA, dihydroxyacetone; Xu5P, xylulose-5-phosphate; PEP, phosphoenolpyruvate; OAA, oxaloacetate.
PMC9035589
fbioe-10-874612-g007.jpg
0.539004
f66b66cd91684e5f89890e9bd3c3bcd2
Synthetic routes for C1-feedstock assimilation. (A) Synthetic routes of the formyl-CoA elongation (FORCE) pathways. (B) Two strain co-culture system using the FORCE pathways. (C) A synthetic CO2 fixation pathway, the POAP cycle. Enzymes: HACL, 2-hydroxyacyl-CoA lyase; PYC, pyruvate carboxylase; OAH, oxaloacetate acetylhydrolase; ACS, acetate-CoA ligase, and PFOR, pyruvate synthase. Cofactors: FDred, reduced ferredoxins.
PMC9035589
fbioe-10-874612-g008.jpg
0.428166
e4965918231a415f8a40abf55a35f34f
Metabolic pathway for C2 feedstock. Dotted lines indicate multiple steps; letters in empty boxes indicate the single letter codes for amino acids; orange lines indicate potential routes for C2 feedstock utilization; AAC, ADP/ATP carrier protein; ACC, acetyl-CoA carboxylase; ACAT, acetyl-CoA acetyltransferase; ADH, alcohol dehydrogenase; ALD, aldehyde dehydrogenase; ALDH, Acetaldehyde dehydrogenase (EC 1.2.1.10); ACO, aconitase; ACS, acetyl-CoA synthetase; ACL, ATP-citrate lyase; AS, ATP synthase; ASCT, acetate:succinate CoA-transferase; CA, carbonic anhydrase; CAT, carnitine acetyltransferase; CRC, carnitine carrier; CTP, mitochondria citrate transporter; CS, citrate synthase, FAS, fatty acid synthase; FUM, fumarase; HK, hexokinase; IDH, isocitrate dehydrogenase; ICL, isocitrate lyase; KDG, α-ketoglutarate dehydrogenase complex; MAE, malic enzyme; MDH, malate dehydrogenase; MPC, mitochondrial pyruvate carrier; MS, malate synthase; NADK, NAD+ kinase; NADPP, NADPH phosphatase; SCS, succinyl-CoA synthetase; SDH, succinate dehydrogenase; PDC, pyruvate dehydrogenase complex; PEPCK, Phosphoenolpyruvate carboxykinase; PYC, pyruvate carboxylase; PYK, pyruvate kinase; MPC, mitochondrial pyruvate carrier; MCT, monocarboxylate transporters. The feeding point to photosynthetic product in plants and algae is shown in green.
PMC9035589
fbioe-10-874612-g009.jpg
0.414855
676335e9f52148f8925b3bdb0a2baf58
The overview of the bioeconomy using C1 and C2 feedstocks. Gaseous feedstocks (CO2, CO, H2) are in circles, liquid feedstocks (methanol, formate, ethanol and acetate) are in boxes. Green and red dots refer as intermediate metabolites and by-products. Metabolic engineering strategies include deleting the competing pathways to eliminate/minimize by-products. Elution engineering refers that the mutant strains with higher fitness (rings in red) will gradually dominate in the fermentation medium supplemented with unfavorable NGFs.
PMC9035589
fbioe-10-874612-g010.jpg
0.452918
87b74447c3804494a9066d20955a252c
Optical, morphological properties of PTB7-Th:Y6 layers, and device structure(A) Chemical structures of PTB7-Th and Y6, (B) UV-Vis-NIR absorption spectra of PTB7-Th, Y6, and PTB7-Th:Y6 films, (C) device structure of fabricated NIR OPD (D) energy levels of materials used in the devices (Pan et al., 2019) (Tang et al., 2019), and (E) topographic surface images of PTB7-Th:Y6 films with different additives measured by AFM (scales: one um).
PMC9035714
gr1.jpg
0.426812
a020adbe08f64997a20de5b3e36787f1
Electrical properties of NIR OPDs based on PTB7-Th:Y6 BHJ layers(A) J-V curves for PTB7-Th:Y6-based NIR OPDs (black dot line: dark current density of PM6:Y6-BHJ-based OPDs), (B) external quantum efficiency and responsivity spectra, (C) specific detectivity based on shot noise, (D) noise spectral density, (E) 3-dimensinal specific detectivity plot based on noise spectral density, (F) linear dynamic range, and (G) cut-off frequency plot of NIR OPDs based on PTB7-Th:Y6 layers.
PMC9035714
gr2.jpg
0.477947
71f9c546bd3e4b1f8ddb3ff54a45c420
Mechanical and optical properties of ultra-thin OPDs(A) Photograph of the OPD device after delamination from the supporting glass substrate.(B) J-V characteristics of the OPD under solar illumination (1000 W/m2) and dark condition before/after peeling-off.(C) Image of an ultra-thin device laminated into a pre-stretched acrylic elastomer (200%) and compressed condition with 50% of tensile strain steps.(D) 3D confocal microscope image of the sample at 50% of tensile strain.(E) Top-view SEM image (left) of device surface at 50% tensile strain and enlarged image (right) indicating that the bending radius is below 7 μm. Photodiode parameters under mechanical deformation: (F) JSC, JD, under forward (compression, blue) and backward (tensile, red) (G) Specific detectivity (D∗), under mechanical deformation.(H) Normalized response of the OPDs at blue (430 nm), green (565 nm), red (700 nm), and IR (851 nm) wavelength.
PMC9035714
gr3.jpg
0.478881
c28e42e671614e5ea8777027601ddecc
Skin-compatible NIR photoplethysmography sensors(A) Photograph of the ultra-flexible organic photodiode attached to a bottom surface of fingertip.(B) Conformal attachment with fingerprint (left) and position of skin-conformal photodetector under finger (right top) and enlarged image of (B) (right bottom).(C) PPG signal detection from ultra-flexible NIR responsive organic photodiodes for 10s.(D) Power spectrum analyzed by fast Fourier transform (FFT) signal processing. The evaluated heart rate (HR) from measured output signals exhibits 61 BPM.
PMC9035714
gr4.jpg
0.390961
ad63fe2c4af846788ce2b9a7ca2ac577
Restaging of disease with PET scan showing partial response.
PMC9035949
cro-0015-0305-g01.jpg
0.535253
048ff7f0de504c4d96bc6a8932d35232
Mapping of reads to various ncRNAs in FC, HIP, and CER of male and female rats. The Y-axis shows the mapping out of 1.0, representing 100%. The X-axis shows various types of ncRNAs.
PMC9036230
epigenomes-06-00011-g001.jpg
0.528537
8956354d723b4457a6bdffa589111a37
Size distribution of reads mapping to different ncRNAs in brain regions of male and female rats. (A) “FC_Male”—frontal cortex of male rats; (B) “HIP_Male”—hippocampus of male; (C) “CER_Male”—cerebellum of male; (D) “FC_Female”—frontal cortex of female rats; (E) “HIP_Female”—hippocampus of female; (F) “CER_Female”—cerebellum of female. The Y-axis shows the size of the reads, while the X-axis shows various types of ncRNAs. The bottom and top of the rectangle indicate the first and third quartiles, respectively. The lower and upper ends of the vertical line extending outside the rectangle represent the minimum and maximum, respectively. The thick horizontal line inside the rectangle is the median, and the circle beyond the rectangle displays an outlier.
PMC9036230
epigenomes-06-00011-g002.jpg
0.451582
d9018def1c8445e1bdab8de1c4e09c62
Comparison of tRF read number for tRFs of various sizes. Comparison of read number between different brain regions in male (A) and female (B). Since 18 nt reads were predominant, we generated another figure omitting 18 nt reads—see the inserts. Comparison of read number between male and female for all nt distributions (C) and for all but the 18 nt fraction (D). The Y-axis shows the number of reads for each specific group. The X-axis shows the size of reads.
PMC9036230
epigenomes-06-00011-g003.jpg
0.398969
84144c11a44547889cc65c4b2f2746ed
Analysis of tRF by their mapping to different tRNAs. Comparison of percentage of reads mapping to different tRNAs between different brain regions in male (A) and female (B). Since reads mapping to Gly were predominant, we generated another figure omitting Gly reads—see the inserts. (C–E) show male to female comparison for FC, CER and HIP brain regions, respectively. The Y-axis shows the percentage of reads for each specific group. The X-axis shows the tRNA the reads mapped to.
PMC9036230
epigenomes-06-00011-g004.jpg
0.410492
694edd39164e4732a81e039656cf8953
Enrichment of tRFs produced from tRNAs in various brain regions. (A) “FC_Male”—frontal cortex of male rats; (B) “HIP_Male”—hippocampus of male; (C) “CER_Male”—cerebellum of male; (D) “FC_Female”—frontal cortex of female rats; (E) “HIP_Female”—hippocampus of female; (F) “CER_Female”—cerebellum of female. The Y-axis shows specific tRNA and tRF-5 ratios for specific tRNAs and t-RFs relative to all. When the t-RF peak is larger than the tRNA peak, there is an enrichment, while when it is lower, there is underrepresentation.
PMC9036230
epigenomes-06-00011-g005.jpg
0.441816
1b9caee68d4e43c099d9a5e0613d4699
snoRF-3 and snoRF-5 enrichment from snoRFs in various brain regions. The Y-axis shows reads mapping to snoRFs or snoRF-3 and snoRF-5. When the snoRFs peak is larger than snoRNA peak, there is an enrichment, while when it is lower, there is underrepresentation.
PMC9036230
epigenomes-06-00011-g006.jpg
0.399332
8e1a6de81a59430d8fba7f36dea25119
rRF and snRF enrichment from rRNA and snRNA in various brain regions. (A) rRNA and rRF ratios for female hippocampus; (B) rRNA and rRF ratios for male hippocampus; (C) snRNA and snRF ratios for female hippocampus; (D) snRNA and snRF ratios for male hippocampus. The Y-axis shows reads mapping to rRFs and snRFs or rRF-5 and snRF-3. When the rRFs and snRFs peaks are larger than rRNA and snRNA peaks, there is an enrichment, while when it is lower, there is underrepresentation.
PMC9036230
epigenomes-06-00011-g007.jpg
0.539616
ab3d0912107e467199af25a503fabd5a
Venn diagrams of overlapping target genes (as analyzed by miRDB) of tRFs in male and female brain regions. The upper panel shows the overlap between different brain regions in male (left part) and female (right part), while the lower panel shows the overlap between male and female groups for each brain region.
PMC9036230
epigenomes-06-00011-g008.jpg
0.505325
ab941d58270446f8aaeacec1b76cac2b
Venn diagrams of overlapping target genes (as analyzed by miRDB) of snoRFs in male and female brain regions. The upper panel shows the overlap between different brain regions in male (left part) and female (right part), while the lower panel shows the overlap between male and female groups for each brain region.
PMC9036230
epigenomes-06-00011-g009.jpg
0.502695
a510867c298e4e9b96fca07f6dd59803
Venn diagrams of overlapping target pathways (as analyzed by DAVID) for tRFs in male and female brain regions. The upper panel shows the overlap between different brain regions in male (left part) and female (right part), while the lower panel shows the overlap between male and female groups for each brain region.
PMC9036230
epigenomes-06-00011-g010.jpg
0.40553
37990b854f9f45b7a61529fe376c8858
The nutritional status of children classified by child’s sex.
PMC9036463
bmjopen-2021-058504f01.jpg
0.385268
60248f6b396e4cc5bd915f279d46cf04
The receiver operating characteristic (ROC) curve analysis for the multivariate logistic regression model.
PMC9036463
bmjopen-2021-058504f02.jpg
0.415823
24194295e44c4ae39a90a50d41b8cac9
Schematic diagram of epitaxy InGaN film with different method (a) two-step method, (b) one-step method. (c) The schematic structures for the PDs. (d) Photograph of the chip on wafer.
PMC9037029
d1ra04739f-f1.jpg
0.465718
356d87c7e89344548888d63155e6f84f
The optical microscopy images of InGaN with different method (a) sample 1, (b) sample 2. The AFM images of InGaN with different method (c) sample 1, (d) sample 2.
PMC9037029
d1ra04739f-f2.jpg
0.447594
7c2c5bdcde974b99b6a74d678b1a3235
(a) InGaN(0002) and (b) InGaN(101̄2) XRCs for sample 1 and 2. HRTEM image for (c) sample 1 and (d) sample 2.
PMC9037029
d1ra04739f-f3.jpg
0.436216
74a50b2168cc455e8681173863667397
Photoelectric performance of InGaN-based blue-light photodetectors. (a) I–V characteristic curve for different photodetectors; (b, c) and (e, f) time response curve; (d) responsivity curves for different photodetectors.
PMC9037029
d1ra04739f-f4.jpg
0.512275
d6c4c4725f5347b2ba30caee22b2689e
Experimental design showing model adopted to investigate effects of rat bone marrow mesenchymal stem cells (rMSCs) and agathisflavone (FAB) treatments in a model of spinal cord injury (SCI). Days in vitro (DIV).
PMC9037239
fphar-13-858190-g001.jpg
0.491432
c946d36956cd4c108e9806b39f5edea7
(A) Morphological aspect of 30 days in vitro (DIV) of rMSCs of cultures in control conditions (0.01% DMSO) and 72 h after treatment with FAB (0.1, 0.5 and 1 µM); Rosenfeld staining; obj. x40, scale bar 50 µm. After treatment with 0.1 and 0.5 µM FAB, the cells presented a flat polygonal morphology similar to that of the control (DMSO). However, after treatment with 1 µM FAB, the cells presented Y-shaped extensions. (B) Analysis of viable rMSCs of cultures in control conditions (0.01% DMSO) and 24 and 72 h after treatment with FAB (0.1, 1, 5 and 10 µM), showing no toxicity in 24 h and toxicity only for FAB 10 µM 72 h after treatment; MTT test; Each graph is representative of three independent experiments and the data are expressed as means ± standard deviation. An ANOVA one-way test followed by Turkey’s test for multiple comparisons was performed.
PMC9037239
fphar-13-858190-g002.jpg
0.406149
4002c9d6f79549aab1b61a218b487ca7
Analysis of the expression of neural markers GFAP (red) and β-tubulin III (β-tub, green) in rat bone marrow-derived mesenchymal stem cells (rMSCs). (A) Photomicrographies of cultures in control conditions (0.01% DMSO) and 72 h after treatment with agathisflavone (0.1, 1 µM FAB); immunocytochemistry; scale bar 100 µm. Note that there is an discret increase compare to control in the proportion of GFAP + cells distributed in the cell body of flat polygonal cells in cultures exposed to 0.1 µM FAB, with some polygonal cells co-expressing β-tub, typical of neural progenitor cells. Such effect was not observed at the extension in cultures exposed to 1 µM FAB. (B) Quantification of the proportion of GFAP + cells and β-tub + cells related to the total of cell nuclei counted by DAPI-stained nucleus (blue); the results are expressed as the percentage of means ± SD related to control, considered as 100%, in three independent experiments and were analyzed by Kruskal–Wallis ANOVA, followed by Turkey’s test for multiple comparisons (*) representing p ≤ 0.05 compared to control; (C) Morphological analysis of rMSCs maintained 21 days in control conditions (0.01% DMSO) or treated with a single dose of 1 µM FAB; obj. x20, scale bar 100 µm. In the inserts of image at obj. 40x, one can see some cells with neuronal morphology, presenting cellular process similar to neurites and interacting with other cells. (D) Photomicrographies of cultures in control conditions (0.01% DMSO) and 72 h after treatment with agathisflavone (1 µM FAB); immunocytochemistry, obj. x20, scale bar 100 µm. Note that there is an increase in the proportion of cells co-expressing GFAP and β-tub compared to control cultures, which is confirmed in (E) by quantifying the proportion of GFAP+/β-tub + cells, related to the total of cell nuclei; the results are expressed as the means of percentage in three independent experiments and analyzed by Kruskal–Wallis ANOVA followed by Turkey’s test for multiple comparisons (*) representing p ≤ 0.05 compared to control.
PMC9037239
fphar-13-858190-g003.jpg
0.475721
68b5371dc57d49a2b6de39fb9c22e5e3
Behavioral outcomes in animals subjected to spinal cord injury (SCI). (A) Motor function assessment based on the Basso, Beattie, Bresnahan scale (BBB) on day zero (before SCI), day 1, day 3 and day 7 after SCI. Adult male Wistar rats (n = 6/group) underwent acute SCI and after 4 h were treated with a single application of 1 × 106 control rMSCs or 1 × 106 rMSCs pretreated with agathisflavone (+FABrMSCs), treated with one single dose of methylprednisolone (60 mg/kg i.p., MP), or treated daily with agathisflavone (10 mg/kg i. p., FAB) (#) p ≤ 0.05 vs. SCI rats. Data are the means ± SD (B) Weight variations of animals with SCI and different treatments.
PMC9037239
fphar-13-858190-g004.jpg
0.453708
2120a249a8324ef89bc03878503b1927
General histopathology of the spinal cord of animals 8 days after being subjected to spinal cord injury (SCI) and different treatments. (A) Representative longitudinal section of a normal spinal cord (sham animals), and from animals treated with a single application of 1 × 106 control rMSCs or 1 × 106 rMSCs pretreated with agathisflavone (+FABrMSCs), treated with one single dose of methylprednisolone (60 mg/kg i.p., MP), or treated daily with agathisflavone (10 mg/kg i.p., FAB); hematoxylin and eosin (H&E), x40; details x100. Abundant foamy macrophages and extensive area of liquefactive necrosis with strong macrophage reaction are observed in the spinal cord of animals with SCI (spotlight), also observed in the spinal cord of animals that received implant of control rMSC (spotlight), and in less expansion of animals treated daily with FAB. However, in the spinal cord of animals that received implant of +FABrMSCs, isolated vacuolization by demyelization and walerian degeneration (arrow) are observed. In the spinal cord of animals treated with MP, diffuse and mild vacuolization by demyelination of white matter is observed. (B) Quantification of foamy macrophages in injured spinal cord tissue. The results are expressed as the media of percentage in three independent experiments and were analyzed by Kruskal–Wallis ANOVA followed by Dunn’s post-test (*) p ≤ 0.05 compared to SCI group. (C–E): Expression of neurotrophic factors and arginase in the spinal cord of animals 8 days after being subjected to spinal cord injury (SCI) and different treatments. Expression of mRNA for neurotrophic factors NGF and GFDN, and for enzyme arginase, was analyzed with RT-qPCR; Sham = Non-lesioned; SCI and other groups = Lesioned; values expressed as mean ± standard deviation; significant differences are expressed as *p ≤ 0.05 when compared to the control NL; #p ≤ 0.05 when compared to FAB 0.1 μM NL treatment; and p ≤ 0.05 when compared to the control L; and &p ≤ 0.05 when compared to FAB 0.1 μM treatment. Kruskal–Wallis and one-way ANOVA followed by Dunn’s post-hoc were used.
PMC9037239
fphar-13-858190-g005.jpg
0.479328
c2b84a0481314dccb77cf2983012c429
- Schematic representation of how to develop a teleneurology program.1
PMC9037570
Neurosciences-27-1-4_page_3_1.jpg
0.525157
a6d7baa556cc49679b634fd4caf28308
Packaged Idli powder
PMC9037875
IJNM-37-12-g001.jpg
0.464397
8ed57c151cc34a079d4b19c910e0917e
Gastric emptying scintigraphy image analysis by geometric mean method for global gastric emptying parameters in a 23-year-old healthy male subject
PMC9037875
IJNM-37-12-g002.jpg
0.494644
d84e2bb1f3284fb19bbc638d58f2a341
Gastric emptying scintigraphy image analysis by geometric mean method for proximal gastric emptying parameters in a 23-year-old healthy male subject
PMC9037875
IJNM-37-12-g003.jpg
0.470142
f703233fe26f4b12933f2fa7a3877b77
Scatter plots between intragastric meal distribution at time t = 0 (IMD0) and retention index in different camera view methods
PMC9037875
IJNM-37-12-g004.jpg
0.420191
a2784fe0017d45658253ea8fd106acf9
Financial Performance at 0%, 25%, 50%, 75%,100% disruption levels analysing (a) Production cost (b) Inventory carrying cost (c) Profit (d) Revenue (e) Total cost (f) Transportation CostFinancial performance indicates the effect caused by the disruption of the supply chain and its various performance indicators. Figure 10a gives the trend of reduction in production cost which indicates the reduction in the supply of raw materials at every production unit. Hence it can be inferred that increased disruption level causes the number of finished goods to decrease. From 10b it can be inferred that increased disruption level causes inventory to reduce, and inventory cost is directly indicating that loss in inventory as disruption stops the flow of copper from the lower level of the supply chain to the higher levels. Figure 10c, d infers the loss of Profit and Revenue (Sales) in the entire supply chain is due to the disruption. From Fig. 10c it can be observed that there is an approximate loss of 12.1% between 0% disruption and 100% disruption. Thus, the higher the disruption leads to increased loss of profit and revenue. Figure 10e indicates that the loss is evenly distributed based on the linearly decreasing graph, on all the other financial parameters as it agrees with the trend which is shown by the other performance indicators thus showing us the ripple effect on each node of the supply chain. Figure 10f helps to understand the loss in the movement of copper further up the supply chain as transportation cost decreases due to the lack of products and it also shows the loss of revenue to the transportation companies
PMC9038444
12063_2021_231_Fig10_HTML.jpg
0.40718
e7541d41193642b6812094cc4eb62364
Supply chain dashboard for project management activities
PMC9038444
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0.397222
17490526ae0c4945bf363c5c8a8c825e
Flowchart representing the case study
PMC9038444
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0.473458
44b0d07eef184676b9d85631d347f79e
The supply chain of copper from its ore to the customers
PMC9038444
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0.397118
d9edccf33a614677b39710da09af5af4
The supply chain on world map plotted in anyLogistix
PMC9038444
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0.445421
a2624591861440f89daaa4f0355eaeb6
The supply chain Zoom View over Indian sub-continent
PMC9038444
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0.431522
e063f949ace34c748cf9ec899e701bec
ELT service level by product at 0%, 25%, 50%, 75%, 100% disruption levels with ration values ranging from 0 to 2
PMC9038444
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0.466648
da36fa9a004f462f931e182666ed7519
Peak capacity at 0%, 25%, 50%, 75%, 100% disruption levels with average maximum value of 5.69E6 to minimum value of 0
PMC9038444
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0.454835
9fe1a71ffddb4ea884a2fc557f6ff4bd
Fulfilment received analyzed at 0%, 25%, 50%, 75%, 100% disruption levels for Cu Alloys, Cu Wire and Pipes
PMC9038444
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0.41939
47eb988606c945399ea20558b67151ee
Available inventory at 0%, 25%, 50%, 75%, 100% disruption levels with values ranging from 0 to 99,000
PMC9038444
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0.444028
65bcd75a759441a6a8df9e667ce3a6ef
Products produced at 0%, 25%, 50%, 75%, 100% disruption levels. Refined Cu, Cu Alloys, Cu Wire, and Cu pipes are included in the analysis
PMC9038444
12063_2021_231_Fig9_HTML.jpg
0.455278
fe0f7852ff9d43aab647502c65789de9
PRISMA flow diagram
PMC9038879
408_2022_527_Fig1_HTML.jpg
0.435133
11577a5f33f44c20800700730f6032ce
Gut microbial diversity and community composition in the ECB larvae fed with an artificial diet (ECB-D) or maize plants (ECB-M). (A) Relative abundance of microbiota in both strains at the phylum level. The number of x-axis indicates individual gut sample. (B) Linear discriminant analysis effect sizes (LEFSe) for the top 10 bacterial genus that differed significantly in relative abundance between ECB-D and ECB-M. (C) α-diversity comparison based on the Shannon diversity index, using a t-test to determine significant differences (**P < 0.01). Horizontal lines indicate the mean (± SE) of biological replicates. (D) Principal coordinate analysis (PCoA) plot generated using OTU metrics based on Bray-Curtis distance. The variation explained by the PCoA axes is given in parentheses. (E) Heatmap showing the main function of microbiota present in the larval gut of ECB-D and ECB-M with different abundance.
PMC9039043
fmicb-13-816954-g001.jpg
0.373208
b843579759984c02a3738ec9703d3a12
Draft genomes of two microbial consortia from the gut of ECB larvae fed with an artificial diet (BI-D) and maize plants (BI-M) respectively. Panel (A) and panel (B) represent the relative abundance of the dominant bacteria in BI-D and BI-M respectively. (C) The number of CAZyme genes defined in the draft genomes of BI-D and BI-M.
PMC9039043
fmicb-13-816954-g002.jpg
0.409291
30e874dfc8404984b9e368a0f89e908f
FISH analysis of the localization of (A) Streptococcus (green), (B) Klebsiella (purple), (C) Enterococcus (blue), and (D) three bacteria in the larval midgut of ECB-M, and (E) Bacillus (green), (F) Enterobacter (purple), (G) Enterococcus (blue), and (H) three bacteria in the larval midgut of ECB-D.
PMC9039043
fmicb-13-816954-g003.jpg
0.46994
e1305f0fff37441c87c413f772386bce
In vitro maize cellulose degradation by microbial consortia BI-D and BI-M. Scanning electron micrographs of (A) untreated maize particles, (B) maize particles treated by BI-D for 9 days, and (C) maize particles treated by BI-M for 9 days. The content of (D) lignin, (E) cellulose and (F) hemicellulose in maize particles after treated for 9 days. The cellulose-associated enzyme activity of (G) endoglucanase, (H) exoglucanase, and (I) β-glucosidase in the culture medium of maize particles treated with BI-D and BI-M for 9 days. Horizontal lines in the boxes represent group medians, and whiskers represent the 10th–90th percentiles. Superscripts (a, b) indicate significant differences between different groups (P < 0.05).
PMC9039043
fmicb-13-816954-g004.jpg
0.439418
3c43ff9c14254d4d9eba53da8eb58374
Metabolomic analysis of in vitro degradation of maize particles by two microbial consortia. PCA score plot of metabolic profiles in (A) positive and (B) negative ionization modes. Colored circles represent the metabolic profiles of individual samples. Ellipses indicate 95% confidence region for each group. Relative metabolite levels of maize cellulolytic degradation by two bacterial isolates in (C) positive and (D) negative ionization modes. The color scale shows levels for each metabolite relative to the average abundance. Asterisks indicate significant differences (P < 0.05) between each group. Summary statistics are provided in Supplementary Table 7.
PMC9039043
fmicb-13-816954-g005.jpg
0.493912
c2734b48fd434966afcb60a6d3109d01
Graphical summary of the main results. Diet shapes the gut bacterial community of ECB larvae. Two bacterial isolates from the guts of ECB larvae exhibited the ability to degrade maize cellulose to varying degrees in vitro and produced distinctive metabolomic profiles, including reduced sugars and amino acids.
PMC9039043
fmicb-13-816954-g006.jpg
0.489409
757fc9a0905445ab8f963c1d3553f04d
BBR effectively decreases blood lipids in hyperlipidemic patients. Eighty-three hyperlipidemic patients were treated with BBR (42 subjects, 1 g/day) or placebo (41 subjects) for 3 months. The lipids changes at each time point compared to the baseline levels were analyzed.
PMC9039652
gr1.jpg
0.419671
1ec5ca19aebc4346a95b41e178ef94ae
The cholesterol-lowering efficiency of BBR is closely related with its modulation on gut microbiota. A-B. The principal coordinate analysis (PCoA) (A) and non-metric multi-dimensional scaling (NMDS) analysis (B) of gut microbiota. (C) The Bray-Curtis distance-based clustering analysis. (D) The changes of alpha diversity indices compared to the baseline values. We obtained the initial (week0) and final (week12) fecal samples from 51 patients (28 in BBR group and 23 in placebo group) and analyzed their gut microbiota composition by shotgun sequencing metagenomics. *P < 0.05.
PMC9039652
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0.46383
3d0033cd65b845e28358ca24e6c51296
The baseline abundance of Alistipes and Blautia spp. are effective to predict the cholesterol-lowering efficiency of BBR in hyperlipidemic patients. (A) The genus profile of responsive (PS) and non-responsive (NPS) patients, and Alistipes is the only dominant genus whose baseline abundance is significantly different between PS and NPS patients. (B) The species profile of PS and NPS patients, and three Alistipes spp. are significantly different between PS and NPS patients at the baseline level. (C) Co-occurrence network established by SparCC analysis. The area of each node indicates the accumulated abundance of the species, and the portion of each group was displayed in different colours. The connecting edges indicate positive (orange) or negative (blue) correlations between species. (D) The top 15 species that discriminate the PS and NPS patients based on random forest analysis. (E) Receiver operating characteristic curve (ROC) for the combination of Alistipes and Blautia spp. Area under curve (AUC) and the 95% confidence interval are also shown.
PMC9039652
gr3.jpg
0.476716
9d6df57ed2cd4fb5a8a87bcdd132f22b
Parenteral administration or antibiotic treatment largely weakens BBR’s lipid-lowering effect. (A) Serum lipids and glucose levels in each treatment group; error bars denote standard error in measurements. (B) Oral glucose tolerance test (OGTT) and insulin tolerance test (ITT) in each group. (C) Hematoxylin and eosin (H&E) staining of the liver (bar = 10 μm). (D) Steatosis score of different treatment groups; each dot represents a liver sample wherein steatosis was diagnosed. (0–3) was evaluated as follows: 0, no involvement; 1, mild involvement; 2, moderate involvement; and 3, severe involvement. E-F Liver total cholesterol (TC) (E) and triglyceride (F) measurements in different treatment groups. *P < 0.05, **P < 0.01, ***P < 0.001, N.S. = non-significant.
PMC9039652
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0.456348
a9627b5d60814573806e9fd4bc58345e
Fecal material transplantation after BBR treatment prevents HFD-induced hyperlipidemia as effectively as BBR. (A–D) Bodyweight (A), bodyweight gain (B) and the weights of liver (C), subcutaneous fat (D) and epididymal fat (E) of different treatment groups, respectively. (F) Serum levels of TC, TG, LDL-c, and glucose. (G) Oral glucose tolerance test (OGTT) and insulin tolerance test (ITT). (H–J) H&E staining of liver (bar = 10 μm) (H) and hepatic levels of total cholesterol (TC)(I), and triglycerides (TG) (J) from different treatment groups, respectively. (K) HPLC for BBR in BBR soup (bottom panel) and the collected fecal material after BBR administration (top panel), indicating the absence of BBR in fecal materials used for the transplant. *P < 0.05, **P < 0.01, ***P < 0.001, N.S. = non-significant.
PMC9039652
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0.507294
f6705b44d48c418e82396a265fd7fa0c
Dysregulation of Blautia downregulates the cholesterol-lowering action of BBR. (A) Bodyweight curve. (B) Bodyweight change. (C) Serum lipids levels. (D) Relative abundance of key genera that were confirmed to be closely related to BBR’s lipid-lowering effects. Data are expressed as mean ± s.e.m. N = 8 for each group. #P < 0.05, HFD group vs Chow group; *P < 0.05, **P < 0.01, ***P < 0.001. N.S. = non-significant.
PMC9039652
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0.444375
3a1a5637d71f4206ba38b74fb1c46ac3
Multiple Box-and-Whisker plots for the content of the elements studied in mg/L.
PMC9039940
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0.441522
ca5acdcf59df4804aee73e2c80ba47f2
Principal component analysis (PCA). a) Loading plot of elements data in wine samples. b) Scores of the wine samples on the first two PCs.
PMC9039940
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0.509482
4ace62d7ecb746bfb32c3e46ac25894b
Dendrogram obtained by hierarchical cluster analysis based on the Euclidean distance between samples for the metals determined by TXRF. For the abbreviations of the samples’ names, see Table S2.
PMC9039940
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0.435496
5899148ce6a4419aa10e16483a9c56df
Discriminant scatter plot of wine samples.
PMC9039940
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0.401031
7067fb1a51764d2e8e5bb527ff9909ad
Overview of the primary experimental design and the B and T cell responses induced by WT-LNP-mRNA vaccination against SARS-CoV-2 WT, B.1.351, and B.1.617 spikes in mice(A) Schematic of the designs of three variant-specific LNP-mRNA vaccine candidates. Functional elements are shown in the spike mRNA and translated protein of SARS-CoV-2 WT, B.1.351, and B.1.617 spikes, including protein domains, HexaPro, and variant-specific mutations.(B) 3D structure highlighting certain variant-specific mutations in B.1.351 and B.1.617 spikes. Distribution of mutations of B.1.351 and B.1.617 are shown in the structure of SARS-CoV-2 (PDB: 6VSB). Mutations of B.1.351 and B.1.617 are shown as spheres, except for those in the unstructured loop regions. Certain mutations are not visible in the structure, as they fall into floppy regions of spike.(C) Graphical representation of B.1.351-LNP-mRNA complex and B.1.617-LNP-mRNA complex formation. The spike mRNAs of B.1.351 and B.1.617 are encapsulated by LNP via NanoAssemblr Ignite. The size and encapsulation rate of the mRNA-LNP complex were measured by dynamic light scatter (DLS) and Ribogreen assay, respectively.(D) After electroporated into 293FT cells, in vitro expression of B.1.351-spike or B.1.617-spike mRNA were detected by flow cytometry using the human ACE2-Fc fusion protein and PE-anti-Fc antibody.(E and F) DLS (E) and TEM (F) of size and monodispersity characterization of LNP-mRNAs.(G) Schematic of overall design of primary experiments. Six- to 8-week-old C57BL/6Ncr mice (B.1.351-LNP-mRNA (top) and B.1.617-LNP-mRNA, n = 6 mice per group; WT-LNP-mRNA, n = 4 mice; PBS, n = 9) received 1 or 10 μg of WT-LNP mRNA, B.1.351-LNP-mRNA, or B.1.617-LNP-mRNA via the intramuscular route on day 0 (Prime) and day 21 (Boost). Blood was collected twice, 2 weeks post-prime and -boost. The binding and pseudovirus-neutralizing antibody responses induced by LNP-mRNA were evaluated by ELISA and neutralization assay. Mice were euthanized at day 40. The spleen, lymph node, and blood samples were collected to analyze immune responses by flow cytometry, bulk BCR, and TCR profiling and single-cell profiling.(H and I) Serum ELISA titers of WT-LNP mRNA-vaccinated animals (n = 4). Serum antibody titer as area under curve (AUC) of log10-transformed curve (1og10 AUC) to spike RBDs (H) and ECDs (I) of SARS-CoV-2 WT, B.1.351, and B.1.617. Two-way ANOVA with Tukey’s multiple comparisons test was used to assess statistical significance.(J) Serum neutralization titers of WT-LNP mRNA-vaccinated animals (n = 4). Cross neutralization of SARS-CoV-2 WT, B.1.351, or B.1.617 pseudovirus infection of ACE2-overexpressed 293T cells. Two-way ANOVA with Tukey’s multiple comparisons test was used to assess statistical significance.(K and L) T cell response of WT-LNP mRNA-vaccinated animals (n = 4). CD8+ (K) and CD4+ (L) T cell responses were measured by intracellular cytokine staining 6 h after addition of BFA. The unpaired parametric t test was used to evaluate the statistical significance. Note that in this figure each dot represents data from one mouse. Data are shown as mean ± SEM plus individual data points in dot plots. Statistical significance labels: n.s., not significant; ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001. Source data and additional statistics for experiments are provided in a supplemental excel file. See also Figures S1 and S2.
PMC9040489
gr1.jpg
0.428085
31c831870124411e8be42ca39a5c24fb
B.1.351-LNP-mRNA and B.1.617-LNP-mRNA elicit robust binding and pseudovirus-neutralizing antibody response against all three variants in mice(A) Serum ELISA titers of animals vaccinated with B.1.351-LNP-mRNA (top) and B.1.617-LNP-mRNA (bottom) against RBD from three different spikes (WT, B.1.351, and B.1.617) of SARS-CoV-2 (n = 6).(B) Serum ELISA titers of animals vaccinated with B.1.351-LNP-mRNA (top) and B.1.617-LNP-mRNA (bottom) against ECD from three different spikes (WT, B.1.351, and B.1.617) of SARS-CoV-2 (n = 6).(C) Serum neutralization titers of animals vaccinated with B.1.351-LNP-mRNA (top) and B.1.617-LNP-mRNA (bottom) against three pseudoviruses (WT, B.1.351, and B.1.617) of SARS-CoV-2 (n = 6).(D and E) Direct comparison of serum ELISA (D) and neutralization (E) titers of animals boosted by WT, B.1.351-LNP-mRNA, and B.1.617-LNP-mRNA against WT, B.1.351, and B.1.617 spikes or pseudoviruses of SARS-CoV-2.F.Heatmap of neutralization titers of animals vaccinated with all three LNP-mRNAs, against three pseudoviruses (WT, B.1.351, and B.1.617) of SARS-CoV-2. G, correlation X-Y scatterplots of ELISA and neutralization titers between ELISA ECD log10 AUC versus neutralization log10 IC50 for all vaccine groups. Note that in this figure, each dot represents data from one mouse. Data are shown as mean ± SEM plus individual data points in dot plots. Statistical significance labels: n.s., not significant; ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001. Source data and additional statistics for experiments are provided in a supplemental excel file. See also Figure S1.
PMC9040489
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0.428014
f9dfc17dbbe3470bbf5c8f92cf53778d
B.1.351-LNP-mRNA and B.1.617-LNP-mRNA induced S protein-specific T cell response(A–C) Percentage of CD8+ T cells expressing IFN-γ (A), TNF-α (B), and IL-2 (C) in response to stimulation of S-peptide pools (n = 3). Left: representative flow plots; right: dot-bar plots for statistics on the left.(D) Percentage of CD4+ T cells expressing IFN-γ in response to stimulation of S-peptide pools (n = 3). Left: representative flow plots; right: dot-bar plots for statistics on the left.B.1.351-LNP-mRNA and B.1.617-LNP-mRNA induced S protein-specific polyfunctional CD8 and CD4 T cells. (E-H) Percentage of CD8+ T cells expressing both IFN-γ and TNFα (E), both IFN-γ and IL-2 (F), TNFα and IL-2 (G), in response to stimulation of S peptide pools (n = 3). Percentage of CD4+ T cells expressing both IFN-γ and TNFα in response to stimulation of S peptide pools (H). Left panels, representative flow plots; right panels, dot-bar plots for statistics of the left panels.(H) Percentage of CD4+ T cells expressing both IFN-γ and TNF-α in response to stimulation of S-peptide pools (n = 3). Left: representative flow plots; right: dot-bar plots for statistics on the left. Note that in this figure, each dot represents data from one mouse. Data are shown as mean ± SEM plus individual data points in dot plots. Statistical significance labels: n.s., not significant; ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001. Source data and additional statistics for experiments are provided in a supplemental excel file. See also Figure S2.
PMC9040489
gr3.jpg
0.441411
d5e802d39a4245d387cc96d2f7652012
B.1.351-LNP-mRNA and B.1.617-LNP-mRNA shown in vivo to protect efficacy against the challenge of replication competent authentic SARS-CoV-2 and variant viruses(A) Schematic of authentic virus challenge experiments on mRNA-LNP-vaccinated mice. hACE2-K18 mice were separated randomly and received 10 μg of WT-LNP mRNA, B.1.351-LNP-mRNA, or B.1.617-LNP-mRNA via the intramuscular route on day 0 (Prime) and day 21 (Boost). One week after boost (day 28), the mRNA-LNP-vaccinated, and control mice were distributed into three groups and challenged with WA-1, Beta, and Delta authentic live virus. Survival, body conditions, and weights of mice were monitored daily for 10 consecutive days.(B) A numeric summary of the number of hACE2-K18 mice vaccinated with WT-LNP mRNA, B.1.351-LNP-mRNA, or B.1.617-LNP-mRNA and challenged with three different authentic virus WA01, Beta (B.1.351), and Delta (B.1.617.2).(C) Body weight curves of WT-LNP mRNA-, B.1.351-LNP-mRNA-, B.1.617-LNP-mRNA-vaccinated, and control hACE2 transgenic mice under lethal challenges with different authentic virus WA-01 (left), Beta (middle), and Delta (right).(D) Survival curves of WT-LNP mRNA-, B.1.351-LNP-mRNA-, or B.1.617-LNP-mRNA-vaccinated, and control hACE2 transgenic mice under lethal challenges with different authentic virus WA-01 (left), Beta (middle), and Delta (right). Note that in this figure, each dot represents data from one mouse. Data are shown as mean ± SEM plus individual data points in dot plots. Statistical significance labels: n.s., not significant; ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001. Source data and additional statistics for experiments are provided in a supplemental excel file.
PMC9040489
gr4.jpg
0.394
f0fc6aa24ee44505a9a3f3686e863998
Single-cell transcriptomics of variant-specific LNP-mRNA-vaccinated animals(A) UMAP visualizations of all 141,729 cells pooled across samples and conditions. Cells are color labeled by vaccine, concentration, and unsupervised clustering in each panel, top to bottom. Clusters are labeled by cell types that were assigned based on the expression of cell type-specific markers.(B) UMAP heatmaps of the expression of major cell type-specific markers across all cells.(C) Heatmap of differentially expressed genes (DEGs) across indicated cell types. Differential expression analyses were performed using Wilcoxon rank-sum test for each cell type versus all other cells, and the heatmap includes the 10 DEGs from each analysis (absolute log2-FC > 4, q < 0.01).(D) Boxplots of overall cell type proportions compared across vaccine groups (n = 6 for each). Comparisons were performed using a two-way ANOVA, accounting for vaccine and cell type as covariates, with Dunnet’s post hoc analysis for multiple comparisons against PBS as the control. Data were analyzed together but are displayed separately for clarity.(E) Stacked bar chart of cell proportions between different vaccination groups (n = 6 for each).(F) UMAP visualization of T cell and B cell subpopulations across all samples and conditions. Subclusters are labeled by cell types, assigned by the expression of cell type-specific markers.(G) Boxplots of B and T subset proportions compared across vaccine groups (n = 6 for each). Comparisons were performed using a two-way ANOVA, accounting for vaccine and cell type as covariates, with Dunnet’s post hoc analysis for multiple comparisons against PBS as the control. Data were analyzed together but are displayed separately for clarity. Note that in this (D) and (G), each dot represents data from one mouse. The high-dose (n = 3 each) and low-dose (n = 3 each) groups for each vaccine were merged (n = 6 total) in single-cell data analysis, the same thereafter. Statistical significance labels: n.s., not significant; ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001. See also Figures S3–S6.
PMC9040489
gr5.jpg
0.425573
6d9aacc7f7964d5688802d0527e4360d
Single-cell analysis of activated B cell and CD8 T cell populations with gene expression signatures of variant-specific LNP-mRNA-vaccinated animals(A) Volcano plots of differential expression (DE) analyses for each vaccination group versus PBS in B cells. Analyses were performed using quasi-likelihood F tests of scRNA-seq data fitted with gamma-Poisson generalized linear models.(B) Network plots of clustered terms from pathway analyses of upregulated genes in the indicated B cell DE analysis. Pathway enrichment analyses were performed by gProfiler2, and significantly enriched pathways were clustered with Leiden algorithm. Pathway clusters (supra-pathways) are labeled by their most significant member term along with its enrichment q value. The top five supra-pathways are shown for each plot.(C) Expression heatmaps of DE genes from selected upregulated supra-pathways in B cell DE analysis. Single-cell expression values were scaled and then averaged across vaccination groups.(D) Volcano plots of DE analyses for each vaccination group versus PBS in CD8 T cells. Analyses were performed using quasi-likelihood F tests of scRNA-seq data fitted with gamma-Poisson generalized linear models.(E) Network plots of clustered terms from pathway analyses of upregulated genes in the indicated in CD8 T cell DE analysis. Pathway enrichment analyses were performed by gProfiler2, and significantly enriched pathways were clustered with Leiden algorithm. Pathway clusters (supra-pathways) are labeled by their most significant member term along with its enrichment q value. The top five supra-pathways are shown for each plot.(F) Expression heatmaps of DE genes from selected upregulated supra-pathways in CD8 T cell DE analysis. Single-cell expression values were scaled and then averaged across vaccination groups. See also Figures S7–S9.
PMC9040489
gr6.jpg
0.467577
18237679dfbe42e594e2ca820ecc1c10
VDJ repertoire and clonal analyses of B cell and T cell populations from variant-specific LNP-mRNA-vaccinated animals(A) Clonal composition bar plot depicting proportion of the BCR repertoire occupied by the clones of a given size for all samples in the single-cell BCR-seq dataset.(B) Bar plot of Chao1 indices for each condition for repertoires in the single cell BCR-seq dataset (n = 6 for each group).(C) Clonal composition bar plot depicting proportion of the TCR repertoire occupied by the clones of a given size for all samples in the single-cell TCR-seq dataset.(D) Bar plot of unique clonotypes for each for repertoires in the single-cell TCR-seq.(E) Circos plots of V-J clonotype distribution for single-cell BCR-seq dataset (left) and single cell TCR-seq dataset (right). The 20 most abundant V-J combinations are shown for pooled vaccination group.(F) Clonal composition bar plot depicting proportion of the BCR repertoire occupied by the clones of a given size for all samples in the bulk BCR-seq dataset (left) and bulk TCR-seq dataset (right).(G) Bar plots depicting relative abundances of IGH, IGK, IGL, TRA, TRB, and TRD clonotypes within specific frequency ranges in the bulk BCR/TCR-seq data from different tissues of different vaccination groups. Relative abundances are presented for individual and grouped samples in (E) and (F), respectively.(H) Bar plots of the effective clone numbers (true-diversity estimates) for selected BCR and TCR chain repertoires in the bulk TCR-seq dataset across vaccination and tissue groups. Note that for the single-cell BCR/TCR-seq datasets, n = 6 samples for the PBS and n = 3 for WA-1 1 μg, WA-1 10 μg, B.1.351 1 μg, B.1.351, B.1.617 1 μg, and B.1.617 10 μg groups. For the bulk BCR/TCR-seq datasets, n = 4 PBS samples, and n = 3 for B.1.351 1 μg, B.1.351, B.1.617 1 μg, and B.1.617 10 μg groups. Statistics for (F) and (G) were performed using two-way ANOVA with Dunnet’s multiple comparison test. Statistical significance labels: n.s., not significant; ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001. See also Figures S10–S12.
PMC9040489
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0.424559
5a4378268e0f429eb87f8399a6cb8381
Viruses identified in the IBS and corresponding healthy controls. (A) Workflow of the analysis in this paper. (B) Viral composition in family level of each sample.
PMC9040671
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0.411817
100fc438c5f2488d88fedbffde53154b
Correlations among viruses, bacteria, and metabolites. (A) Heatmap of the Spearman correlations between significantly different viruses (column) and significantly different bacteria (row). There were 22 viruses in genus level depleted and six enriched in the IBS group (Mann–Whitney U test, p ≤ 0.05), 97 bacteria in genus level depleted, and nine enriched in the IBS group (Mann–Whitney U test, p ≤ 0.05). The significances of correlations were labeled with “*” (FDR p < 0.05) and “**” (FDR p < 0.01). The same color-labeled names of bacteria or viruses indicate the pairs of infective phages and their bacteria hosts. (B) Heatmap of the Spearman correlations between significantly different viral gene families (column) and significantly different metabolic ions (row). There were 51 metabolic ions depleted and 85 enriched in the IBS group (t-test, p ≤ 0.05). The significances of correlations were labelled with “*” (FDR p < 0.05) and “**” (FDR p < 0.01).
PMC9040671
fcimb-12-846063-g002.jpg
0.45212
7162e48c603a4a0480078b0afb6d43d5
Abundance and composition of the gut virome in different groups. (A) Viral gene abundance in different samples. The blue part of each bar is the viral gene abundance relative to all the predicted genes in that sample and represents the portion of reads from the detected viral genes to reads from all genes in a sample. (B) Composition of viruses in family and order level. Inner pie chart, viral families. Outer circle, corresponding orders to the families. Microviridae, Inoviridae, Bicaudaviridae, and families that belong to Caudovirales are bacteriophages. Phycodnaviridae, Mimiviridae, Poxviridae, Marseilleviridae, Iridoviridae, and Ascoviridae are Megavirales known as nucleocytoplasmic large DNA viruses (eukaryotic viruses). Pithoviridae, Baculoviridae, and Nudiviridae are also eukaryotic viruses.
PMC9040671
fcimb-12-846063-g003.jpg
0.3861
7ed45846762343e9a6d228bcdd970bda
Characterization of disease-specific co-abundance relationships of viruses. (A) IBS-specific network. (B) Pan-network of five disease-specific networks in family level. (A, B) The co-abundance networks of the gut microbiome, including bacteria, phages, and eukaryotic viruses. The two ends of each edge represent two nodes (genus) that have interaction. Three types of annotations are outside the nodes: the outermost circles of the ribbon indicate three classes of the node; the two circles of the heatmap represent the node importance centrality and the node degree, which is defined as the number of nodes that link to each node. (C) Histogram of negative correlation ratios within and between three classes of nodes: bacteria, phages, and eukaryotic viruses in each disease-specific network (“*”; FDR p < 0.05, “**”; FDR p < 0.01, “***”; FDR p < 0.001, “****”; FDR p < 0.0001). (D) Proportion of four bacterial phyla that link to viruses. (E) Ratio of negative correlations of four bacterial phyla that link to viruses. Points with label “1” denote FDR p > 0.05. The p-values were calculated two-sided, so the negative correlation ratio close to 0 or 1 and FDR p < 0.05 means the positive correlation ratio or the negative correlation ratio (respectively) was enriched in the relationships between that bacteria and viruses. The negative link ratio in Proteobacteria and Bacteroidetes and the positive link ratio in Firmicutes and Actinobacteria were significantly higher than the random ratio (permutation test, FDR p is shown in the figure).
PMC9040671
fcimb-12-846063-g004.jpg
0.370916
30b00a342e314ccfadfd62b07bda5ffe
Structural indices of disease-specific networks. (A) Heatmap showing the modularity of the IBS-specific co-abundance network. (B) Heatmap showing the modularity of the IBS-specific co-abundance network after removing viral nodes. (C) Log2-transformed node degree distribution. Node degree is the number of direct links of a node. Degree distribution of a scale-free network follows a power-law distribution, and after log–log transformation, the distribution should fit a linear relationship. The r-square of each line is defined as the scale-free index. In each subgraph, R1 represents the line of all the nodes, R2 represents the line of nodes excluding eukaryotic viruses, R3 represents the line of nodes excluding phages, and R4 represents the line of nodes excluding all viruses. (D) Average path lengths of the pan-disease-specific network in family level. Viruses were added to the bacteria network in the decreasing order of betweenness centrality.
PMC9040671
fcimb-12-846063-g005.jpg
0.468502
67da243e2a0f477297bf0923714857da
Composition of 16 categories of viral gene functions based on the VirGenFunD functional annotations. Samples from the same data source were grouped, and the label “H” stands for healthy controls. Not surprisingly, some conserved backbone functions such as phage integration and transpositional recombination, DNA/RNA replication, and repair occupied a substantial part of the whole viral functions. Phage lysis, metabolic enzymes, transporter activity, and signal transduction-related function were also active in viral gene functions. At the same time, accessory gene functions such as toxins and detoxification were also detected.
PMC9040671
fcimb-12-846063-g006.jpg
0.390612
e105c18dd1fb4a9fac719f1249d99be8
Optical images of water droplet on ZrO2 surface. (a) Native oxide (b) bare ZrNTs (c) ZrNTs after attaching OPA SAM. Inset shows SEM top and cross-section of ∼100 nm ZrNTs.
PMC9040732
d1ra04751e-f1.jpg
0.419682
590983f4ff634a18a321d32545b3087b
Adsorption (atomic percentage (at%)) of organic molecules to ZrO2 (C 1s–ZrO2 signal) and TiO2 (C 1s–TiO2 signal) and substrate signals respectively (Zr 3d and Ti 2p) measured using XPS for 18-C carbohydrate molecules with different anchoring groups (OPA – octadecylphosphonic acid, ODMS – octadecyltrimethoxysilane, ODA – stearic acid, ODAM – octadecylamine).
PMC9040732
d1ra04751e-f2.jpg
0.362699
772cfda97b13465cafd537e86d83dd80
ToF-SIMS spectra of ZrNTs before and after coverage with octadecylphosphonic acid SAMs; (a) Zr+ isotopic pattern; (b) OPA–H− molecular signal.
PMC9040732
d1ra04751e-f3.jpg
0.465554
0c1ff53b83a442359716f89ccf0c0126
Optical images of water droplets on SAM modified ZrNT structures of different porosity and corresponding SEM images (scale bar – 500 nm) of the surfaces. Diameters, (a) d ≤ 20 nm, (b) d = 40 nm, (c) thick walled d = 100 nm, (d) thin walled d = 100 nm and (e) compact anodic oxide (droplet image – scale bar = 1 mm).
PMC9040732
d1ra04751e-f4.jpg
0.413804
65ee485639ed4790bb1f59278e84da6a
Optical images of water droplets on SAM modified ZrNT structures of different oxide-layer thickness and corresponding SEM images of the cross-sections. Length (a) ∼3 μm, (b) ∼4.5 μm and (c) ∼9 μm.
PMC9040732
d1ra04751e-f5.jpg
0.456596
b98b73a0ca264581ae85f0ba55207880
CAD rendering of bench top double pendulum with emphasized key components.
PMC9041261
gr1.jpg
0.406768
fd94bff26c604aa995ff76d09168f601
Rendering of encoder housing assembly process.
PMC9041261
gr10.jpg
0.465037
0bad9ca71f674e4e94bd29e20edda3c4
Marker design and assembly process. (a) Markers attached to double pendulum (see Section 3 for mechanical drawings), (b) physical setup with tape applied to reflective surfaces of double pendulum, and (c) initial frame of video data showing high contrast between markers and the pendulum and background.
PMC9041261
gr11.jpg
0.418383
d5e5ba53e2134ec1a7d834df5cb5c4dd
Marker locations. (a) Relative distances between markers and (b) web of relative position vectors for each rigid link.
PMC9041261
gr12.jpg
0.387571
4ed086fb02a241a8a468d4b02876348e
Comparison between synchronized encoder and video data of θ1 for validation of video data. (left) entire time series of recorded data from both encoder and video data, (top right) zoomed-in section of time series at t∈[21,24], and (bottom right) zoomed-in section of time series t∈[60,63] inclusding one standard deviation error bounds on θ1 which was computed using the video data.
PMC9041261
gr13.jpg