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0.446291 | 54c0479daa734a64911fe5caf5e41f35 | Principal component analysis (A) and cluster analysis (B) of the comprehensive quality of the 34 edible flower samples. In (A), 4 corresponding colors for A, C, G and R represent flower samples of Asteraceae, Caryophyllaceae, Gentianaceae and Rosaceae, respectively. (B) shows the cluster analysis conducted using the parameter of “Manhattan distance 2.5” in the tool of “heat map with Dendrogram” provided by the software Origin 2021. These 34 edible flower samples were classified into 2 major categories, Ⅰ and II. | PMC10343634 | molecules-28-05260-g006.jpg |
0.447672 | 5d2502d4bd284d7395d0c6e330f6ce4d | The 34 edible flower samples used in this study. | PMC10343634 | molecules-28-05260-g007.jpg |
0.454642 | a9550acc86114604aec5f00a234c4398 | (a) Unit cell and coordination environment of ZnEu-MOF, solvent water molecules were omitted. (b) Coordination modes of Zn1 and Eu1. (c) Staking diagram of ZnEu-MOF along b axis. (d) Staking diagram of ZnEu-MOF along an axis. (e–g) Coordination modes of H2L. (h) Powder XRD pattern of ZnEu-MOF and the simulated pattern. Infrared spectrum of ZnEu-MOF and H2L ligand. (i) Infrared spectrum of ZnEu-MOF and H2L ligand. (j) The TG and DTG curves of ZnEu-MOF. | PMC10343636 | nanomaterials-13-01904-g001.jpg |
0.43603 | 3f42d80ddd024726a655543fa91e33cf | Synthesis process of graft copolymer (GCL). | PMC10343636 | nanomaterials-13-01904-g002.jpg |
0.45592 | a18dc14591ee4ef584a0b3e35a2a1f53 | Coordination insertion mechanism of ROP of ε-caprolactone (‡: Transition state). | PMC10343636 | nanomaterials-13-01904-g003.jpg |
0.389414 | 63d5e2dee6cb41b0a2d0c1fcd6bfa2cd | Macroscopic mechanical properties, morphology of the pure PCL and composite films: (a) tensile strength, (b) elastic modulus, (c) elongation at break and (d) stress–strain diagrams of pure PCL film and composite films; (e–j) micromorphology of (e) pure PCL and LCF composite films with different GCL ratios: (f) 2 wt%, (g) 4 wt%, (h) 6 wt%, (i) 8 wt%, and (j) 10 wt%. | PMC10343636 | nanomaterials-13-01904-g004.jpg |
0.406261 | 34588c2b3fe640a7abb69d0c47e02b08 | Physical-chemical properties of PCL and composite films: (a) powder XRD pattern; (b) TG and DTG curves; (c) DSC curves of secondary heating; (d) DSC curves of primary cooling; (e) contact angles. | PMC10343636 | nanomaterials-13-01904-g005.jpg |
0.459454 | 894db5d36a964068ad17406c6435e205 | Fluorescent properties of composite films: (a) fluorescence of ZnEu-MOF and GCL; (b) fluorescence of composite films; (c) the calculated UV–vis spectrum of ZnEu-MOF; (d–g) molecular frontier orbitals of ZnEu-MOF. | PMC10343636 | nanomaterials-13-01904-g006.jpg |
0.453093 | bbbf518a92914b14a877b8cca05e0f7c | Cytotoxicity studies of GCL-D/PCL and 4 wt% LCF to HEK293T cells. (a) Cell viability at 24 h after treatment; (b) Cell viability 48 h after treatment. | PMC10343636 | nanomaterials-13-01904-g007.jpg |
0.461708 | 42e73e64e9e746e0bab0464d32381a87 | A plot of the contact angle (θ) on the PTFE surface vs. the logarithm of fraction concentration (log m ). Curves 1–5 correspond the fractions E0, E1, E2, E3 and E4, respectively. | PMC10343909 | molecules-28-04943-g001.jpg |
0.473524 | 0d2c1bb4d2b148f8927732a5b10a92b4 | A plot of the contact angle (θ) on the PMMA surface vs. the logarithm of fraction concentration (log m ). Curves 1–5 correspond the fractions E0, E1, E2, E3 and E4, respectively. | PMC10343909 | molecules-28-04943-g002.jpg |
0.465628 | 059e54dd1f604fd285fe13d69e6499af | A plot of the contact angle (θ) on the glass surface vs. the logarithm of fraction concentration (log m ). Curves 1–5 correspond the fractions E0, E1, E2, E3 and E4, respectively. | PMC10343909 | molecules-28-04943-g003.jpg |
0.409187 | a2ac8b95621e4fe9be6f9237add4961b | Pearson correlation coefficients. | PMC10344755 | gr1.jpg |
0.482871 | d8f1970ea33e4bb18e6ec076d5044909 | Principal component versus Eigen value (left) and the principal component versus the proportion (cumulative) (right). | PMC10344755 | gr2.jpg |
0.484331 | e6e4517821944a55a4c10e0bd08fe6df | IsoQuant pipeline outline and characteristics of novel transcripts generated from mouse simulated data.a, Outline of the IsoQuant pipeline. When a reference gene annotation is provided, reads are assigned to annotated isoforms and alignment artifacts are corrected (top). The intron graph is constructed from read alignments (middle) and transcripts are discovered via path construction (bottom). b, F1-score for novel transcripts reported by different tools on simulated ONT (left) and PacBio data (right). c, Precision and recall for novel transcripts reported by different tools on simulated ONT data broken up by expression levels in TPM. TPM bins are presented by dot sizes. d, Precision (left) and recall (right) for novel transcripts reported by different tools on simulated ONT data. e, Same as d, but for simulated PacBio data.Source Data | PMC10344776 | 41587_2022_1565_Fig1_HTML.jpg |
0.406246 | 36895323c6bf4b20a6b63ba8693035fe | Characteristics of transcripts obtained from real sequencing data.a, Precision, recall and F1-score for novel transcripts generated on real SIRV ONT cDNA sequencing data. b, Consistency of predictions made by different methods on real human ONT cDNA, ONT dRNA and PacBio data.Source Data | PMC10344776 | 41587_2022_1565_Fig2_HTML.jpg |
0.470922 | e74a0374318d43e4b54eb8f2446e88ad | BiLMP-coated fiber.a Schematic illustration of BiLMP-coated fiber. The BiLMP-coated fiber consists of two layers: PaLMP (polymer-attached LMP) and CaLMP (carbon nanotube-attached LMP) b Initial conductivity and gauge factor of the BiLMP-coated fibers in comparison to previously reported conductive filler-based fibers. c Images demonstrating the stretchable operation of LEDs attached to the BiLMP-coated fiber before (left) and during (right) stretching. d Images demonstrating the durability of BiLMP-coated fibers upon scrubbing. e Images of various mechanical interactions enabled with BiLMP-coated fibers for 1D bioelectronics (top) and schematic illustration (bottom) demonstrating recording and stimulation interfaces for implantable bioelectronics. Figure 1e was created with BioRender.com. | PMC10345103 | 41467_2023_39928_Fig1_HTML.jpg |
0.464223 | cd7022aee1bf40adb768b15060c99e05 | Deposition of particle-assembled LMP on 1D substrate with suspension shearing.a Schematic illustration of the incompatibility of LMPs with the dip-coating on fiber. b Schematic illustration of suspension shearing-based coating of LMP on fiber. c Film coverage ratio according to inks with different combinations of additives with suspension shearing. d, Comparison of fill ratio according to the coating technique. Scale bar: 50 µm. e Photograph and SEM image of PaLMP-coated fiber through suspension shearing. Reproducibility: Suspension shearing was conducted six times, and on each occasion, it resulted in a compact coating. Scale bar: 40 µm. Values in c–d represent the mean and the 1.5 IQR (n = 6). | PMC10345103 | 41467_2023_39928_Fig2_HTML.jpg |
0.501548 | 3ad5973c3cfc4df293dfad711492deb5 | Stretchability and mechanical durability of BiLMP-coated fibers.a Initial electrical conductivity comparison of CaLMP, PaLMP, and BiLMP. b, Relative resistance of conductive fibers under strain with respect to the type of coated film (CaLMP, PaLMP, and BiLMP). c Relative resistance of BiLMP-coated fibers under 10,000 strain cycles. d Peel test of each film with commercialized scotch tape. There is no notable peel-off and residue with CaLMP and BaLMP films. e Resistance variation of BiLMP-coated fibers under repeated attachment and detachment of tape. f Electrical current passing through an attached LED and the resistance of the connected BiLMP-coated fiber interconnect under strain. g Photograph of a sewn electrical circuit with a BiLMP-coated fiber. Scale bar: 2 cm. h Image of large-area integration of BiLMP-coated fibers on commercial cloth. i Image of BiLMP fiber-integrated smart clothes. | PMC10345103 | 41467_2023_39928_Fig3_HTML.jpg |
0.492562 | 4cfd33c3a17840caa857f49ac04e0ad0 | Neural recording and stimulation with BiLMP-coated fibers for multifunctional 1D bioelectronics.a Image and illustration of BiLMP-coated recording fiber (BiLMP-R-fiber) for electrophysiological recording. b Electrophysiology recordings of spontaneous activity from CA1 regions with BiLMP-R-fiber before stretching. c Electrophysiology recordings of spontaneous activity from CA1 regions with BiLMP-R-fiber after stretching (20% strain). d Overlapped spike waveforms recorded from the BiLMP-R-fiber before (green) and after (red, 20% strain) stretching. e PCA clustering of spikes recorded from BiLMP-R-fiber before and after stretching. f Cross-sectional image of BiLMP-multifunctional (extracellular recording, optical stimulation, and drug delivery) fiber device (BiLMP-M-fibers). Reproducibility: Suspension shearing was conducted six times, and on each occasion, it resulted in a compact coating. Scale bar represent 100 μm. g Electrophysiology recordings of optically evoked potentials (OEP) with 10 Hz (top), 100 Hz (bottom) optical simulation, simultaneously recorded through BiLMP-M-fibers. h Inhibition of OEP peak potentials with time, after injection of synaptic blocker (CNQX) using BiLMP-M-fibers. Inset: peak-to-peak amplitude of OEP at before/after CNQX injection. Data are presented as mean values +/- SD. Each 180 peaks are used in sampling. i Illustration (left) and image (right) of sciatic nerve electrical stimulation using BiLMP-based stimulation thread devices (BiLMP-S-threads) with simultaneous EMG recording. Scale bar represent 10 mm. j Correlation between peak amplitude of evoked EMG signal and injected charge density from the BiLMP-S-thread. Data are presented as mean values +/- SD. Each 50 peaks are used in sampling. Inset: raw data of EMG signal. Error band is presented as mean values +/- SD. Scale bar represent 300μV (vertical) and 0.01 s (horizontal). The arrow indicates the onset of a biphasic electrical stimulation pulse of 0.1 A/cm2. k Recorded charge injection capacity waveform of the BiLMP-S-thread. Figure 4a, i were created with BioRender.com. | PMC10345103 | 41467_2023_39928_Fig4_HTML.jpg |
0.447831 | b0e511f441294a8c81140c3f34f8f7ec | Hierarchy form of the proposed HHAOA optimization algorithm. | PMC10346496 | sensors-23-06224-g001.jpg |
0.453783 | c137b50fd22e48bb902f9f11c533896c | Flowchart of the proposed HHAOA technique. | PMC10346496 | sensors-23-06224-g002.jpg |
0.452287 | 851aca0f3c604ad4afc03b8bdd1eb1b2 | Real-time schematic of the pressure process plant. | PMC10346496 | sensors-23-06224-g003.jpg |
0.471123 | e43851b9d22b46e49b24fa9dbc7abc08 | P&I diagram of the pressure process plant. | PMC10346496 | sensors-23-06224-g004.jpg |
0.47252 | ef550c8f0b914fb580df53229ac42e86 | FOPPI controller tuning using HHAOA. | PMC10346496 | sensors-23-06224-g005.jpg |
0.444208 | 2d146f0ccfa24fe285d861d7778a82b3 | Benchmark functions search space plots. | PMC10346496 | sensors-23-06224-g006.jpg |
0.481853 | fe8f5b9325594056b0056e4d4cd5963f | Convergence performance of all the benchmark functions. | PMC10346496 | sensors-23-06224-g007.jpg |
0.446375 | ea5b9bf9dcdc466c95d2d1f0478bc305 | WMN convergence for different algorithms. | PMC10346496 | sensors-23-06224-g008.jpg |
0.501198 | 1502afc6dd0e4fd7a409e3f6b8a9848a | WMN network connectivity and its coverage area for various algorithms. (a) Initial Network; (b) AOA Optimized WMN; (c) MFO Optimized WMN; (d) SCA Optimized WMN; (e) GWO Optimized WMN; (f) WOA Optimized WMN; (g) HHO Optimized WMN; (h) HHAOA Optimized WMN. | PMC10346496 | sensors-23-06224-g009.jpg |
0.455615 | e3a0e1ff28d6479194e8bdeaf724b534 | Set-point tracking and disturbance rejection analysis for optimal FOPPI controller. | PMC10346496 | sensors-23-06224-g010.jpg |
0.439331 | 2260966b9df6433a976416e44c7301ae | Zoomed view of Figure 10 (A) Initial set-point tracking (B) Disturbance rejection performance (C) Control signal during initial set-point (D) Control signal during disturbance rejection. | PMC10346496 | sensors-23-06224-g011.jpg |
0.469147 | 81f4d799134040dcaaabbd25aca38cb9 | The main function diagram of the delay generator. | PMC10346596 | sensors-23-06144-g001.jpg |
0.421082 | 271458e1e4544a1eba8fc1cd6e40acf0 | The carry delay chain structure diagram. | PMC10346596 | sensors-23-06144-g002.jpg |
0.510298 | a0c41629b5184feb9841d11c057d0460 | The tap signal waveform. | PMC10346596 | sensors-23-06144-g003.jpg |
0.456092 | 90d57470f23c4c619ebc358dac94cff7 | The structure of the CARRY4 unit and the carry delay chain. | PMC10346596 | sensors-23-06144-g004.jpg |
0.509466 | 035e436855414eeeacd68b7a99f80c5b | The structure diagram of the whole device. | PMC10346596 | sensors-23-06144-g005.jpg |
0.452716 | fa3b0b3fe44248759bc8295705b29ee7 | The structure diagram of the delay chain function module. | PMC10346596 | sensors-23-06144-g006.jpg |
0.477137 | c3c78f3ff3634e01b14a429612e58fb6 | The structure diagram of the register array. | PMC10346596 | sensors-23-06144-g007.jpg |
0.522351 | cb6f184c5eb3464cbf4dca04c2cd060d | The overall working principle diagram. | PMC10346596 | sensors-23-06144-g008.jpg |
0.499109 | 261b651ce710488c91bc228d5f3d7c40 | The function of the delay compensation module. | PMC10346596 | sensors-23-06144-g009.jpg |
0.442983 | d94e7eb4281a41f183e08f4dcb4a3d3b | The placement of delay chain 1 and delay chain 2. | PMC10346596 | sensors-23-06144-g010.jpg |
0.404635 | 066c0ad8dc8d450390416b0b49e4e3bb | The timing simulation waveform of the carry delay chain. | PMC10346596 | sensors-23-06144-g011.jpg |
0.434207 | 34f06138c52344ee8668378a3ae1bf5b | Delay chain 1 and the related hardware resource placement. | PMC10346596 | sensors-23-06144-g012.jpg |
0.499153 | d9bec6f90d2945c5b92af1b2b2735eac | A diagram of the input and output of the tri_flag register. | PMC10346596 | sensors-23-06144-g013.jpg |
0.472313 | 939b904f59454adba8b5b47e90afc09f | Diagram of the correction of the measurement results of delay chain 1. | PMC10346596 | sensors-23-06144-g014.jpg |
0.365404 | 0abd94995abd4339a37dd3abbfeca529 | Placement of delay chain 2 and the input registers. | PMC10346596 | sensors-23-06144-g015.jpg |
0.451906 | e12d9b3a500f470083017797f6b90d80 | A structure diagram of system clock of the FPGA. | PMC10346596 | sensors-23-06144-g016.jpg |
0.439718 | 3e2cf021c6734d6ab71bab682386b6f4 | (a) FPGA hardware resource distribution. (b) System clock signal wire placement diagram. | PMC10346596 | sensors-23-06144-g017.jpg |
0.493027 | dc839a8f3aeb4cf487a45eef0e1b5a0a | A diagram of the input data correction of delay chain 2. | PMC10346596 | sensors-23-06144-g018.jpg |
0.374011 | c83667b9bb1a4ff584a7baa0a339f0b0 | The first group of experimental data. | PMC10346596 | sensors-23-06144-g019.jpg |
0.38082 | b1abf24d2b4f412783cf57cfba7484cc | The second group of experimental data. | PMC10346596 | sensors-23-06144-g020.jpg |
0.469902 | c8882a28c8dc41dcaf83dbf3f53574d5 | An error histogram of the experimental data. | PMC10346596 | sensors-23-06144-g021.jpg |
0.367586 | c46dd0643fb440d89e867de98f430e65 | The resource occupancy rate of the FPGA. | PMC10346596 | sensors-23-06144-g022.jpg |
0.558845 | 433017bf78d6416e97b7b412bab15aa9 | Composite materials fabrication process. | PMC10346752 | polymers-15-02870-g001.jpg |
0.487234 | dadc7d41245141929eb7f416c7077cdc | (a) Methodology for the prototype development and (b) development of a tendon-driven actuator with an integrated triboelectric sensor. | PMC10346752 | polymers-15-02870-g002a.jpg |
0.458512 | 6ae9acb8eb6044a5a20ccf82cb277b39 | Characterisation of the viscosity of the PU thermoset over time. The viscosity was analysed for pure PU and PU composites. | PMC10346752 | polymers-15-02870-g003.jpg |
0.471227 | cb52d3959b5f4792a61dba98570bd857 | SQUID analysis of the MWCNT and magnetite particles. (a) From −50,000 to 50,000 Oe. (b) From −120 to 120 Oe. | PMC10346752 | polymers-15-02870-g004.jpg |
0.417353 | 0be9c49b3b4447bfaab9e5d0ed90de88 | OM analysis of the organisation of the particles over time under a static magnetic field. (a) Composite with 1 wt.% of MWCNT and (b) 1 wt.% MWCNT + 1 wt.% of magnetite. The images on the left were acquired before cross-linking and on the right 20 min after the cross-linking process started, under the applied magnetic field. | PMC10346752 | polymers-15-02870-g005.jpg |
0.453824 | 0781d9e378bd405ba67f22120e03a38e | Magnetic characterisation of the permanent magnets used for the magnetic patterning of the electrodes. (a) Permanent magnets with a magnetic film. (b) Three-dimensional north pole and south pole distribution in the Z axis. (c) Three-dimensional symmetry analysis for the north and south poles in the Z axis. | PMC10346752 | polymers-15-02870-g006.jpg |
0.42214 | 497ffb3eb74447f2a1cfcda5b2bfb8d7 | Longitudinal images of the magnetic patterns created on the composite samples produced. (a) Composite with 1 wt.% MWCNT/PU, (b) 1 wt.% magnetite/PU and (c) (1 wt.% MWCNT + 1 wt.% magnetite)/PU. (OM, transmission). | PMC10346752 | polymers-15-02870-g007.jpg |
0.445273 | 635633516ef84e648e13d47f61294e9c | Cross-section images of the electrodes obtained by OM in transmission: (a) 1 wt.% MWCNT/PU, (b) 1 wt.% magnetite/PU and (c) (1 wt.% MWCNT + 1 wt.% magnetite)/PU. | PMC10346752 | polymers-15-02870-g008a.jpg |
0.494693 | e89a834e12354e68bd94e59ea7ff13bc | Micro CT analysis of the particle distribution inside the PU matrix for (a) 1 wt.% MWCNT/PU, (b) 1 wt.% magnetite/PU and (c) (1 wt.% MWCNT + 1 wt.% magnetite)/PU. The images on the left present the polymeric matrix and the particles, and the images on the right present just the particles. | PMC10346752 | polymers-15-02870-g009.jpg |
0.505404 | 7f341e22ef454201907cd4e44a9293e4 | Electrical resistance of each electrode for composites with different ratios of magnetite added to 1 wt.% of MWCNT/PU. | PMC10346752 | polymers-15-02870-g010.jpg |
0.407325 | e657cde081f745c18755380bddffab86 | Triboelectric sensor characterisation with (a) a PU layer on top, compared with (b) an SR layer on top. | PMC10346752 | polymers-15-02870-g011.jpg |
0.469303 | 571dc3e7fb5546878bef0a1caed6d0d7 | Soft robotics prototype using a triboelectric sensor (a) catching, (b) holding and (c) releasing an object when pulled away. (d) Output voltage signal at the three different stages (a) catching, (b) holding and (c) releasing an object when pulled away. | PMC10346752 | polymers-15-02870-g012.jpg |
0.440767 | d23d09051c6a47dbac77ce109baf3b06 | Flow chart of literature selection. EMA, ecological momentary assessment. | PMC10347474 | bmjopen-2022-069523f01.jpg |
0.438461 | b0dbfff5092840beb37be0d86c964196 | Forest plot of eligible studies. Weights are from random-effects model. ES, effect size. | PMC10347474 | bmjopen-2022-069523f02.jpg |
0.40977 | 73deeddf2dbc47c494eada745201f3c6 | Sensitivity analysis estimating heterogeneity. | PMC10347474 | bmjopen-2022-069523f03.jpg |
0.38746 | 2fabb04b163a47efbe0a991384ddce2b | Flow chart for patient selection | PMC10347709 | 12882_2023_3262_Fig1_HTML.jpg |
0.407155 | 7b4d6097b0954f05a7f99b6e81b51346 | Relationship between urinary N-acetyl-beta-D-glucosaminidase (uNAG) level and patient histology. (A-E) Association between uNAG level and Oxford classification. *P < 0.05, ***P < 0.001. (F) Correlation between uNAG level and global glomerulosclerosis. (G) Correlation between uNAG level and segmental glomerulosclerosis. (H) Correlation between uNAG level and MEST-C score. (I) Correlation between uNAG level and interstitial score; each dot represents a value from an individual patient. Coefficients of correlation (r for Pearson analysis and ρ for Spearman analysis, respectively) and p values are shown | PMC10347709 | 12882_2023_3262_Fig2_HTML.jpg |
0.399934 | 93377873739645ceb57e389ade64afe8 | ROC analysis for models predicting IgAN remission status. (A) In the whole cohort (n = 213). (B) In patients with baseline eGFR ≥ 60 ml/min/1.73 m2 (n = 142). (C) In patients with baseline eGFR < 60 ml/min/1.73 m2 (n = 71). The blue line represents the model based on clinical data at biopsy alone; the red line represents the model based on the combination of clinical data and uNAG level at biopsy; the yellow line represents the model using baseline clinical data, uNAG level and MEST-C score. Clinical data were MAP, 24-hour proteinuria and eGFR | PMC10347709 | 12882_2023_3262_Fig3_HTML.jpg |
0.479795 | 25c674ac72094f918b4595ed3f729544 | Workflow to deform planning computed tomography (pCT) structure-set to cone-beam computed tomography (CBCT) and to generate CBCT_REF structure set | PMC10348325 | rpor-28-2-224f1.jpg |
0.42547 | 39b1ddca11db4d9bb082be01eccd6a2c | Original treatment plan dose distribution for planning target volume (PTV): PTV-60 and PTV-54 on (A) axial computed tomography (CT) image and (B) coronal CT image, and recalculated dose distribution with rotational error for PTV-60 and PTV-54 on (C) axial cone-beam computed tomography (CBCT) image and (D) coronal CBCT image, for a single fraction. | PMC10348325 | rpor-28-2-224f2.jpg |
0.380611 | 57e1f0a50c774af6b6dd396c6e8817cb | Dose volume histogram comparison for a single fraction of patient-1 for (A) reference plan (Ref) and rotational error plan (R), (B) reference plan (Ref) and translational error plan (T), and (c) reference plan (Ref) and translational plus rotational error plan (T+R). DVH color: clinical target volume (CTV): CTV-60 (dark blue), CTV-54 (cyan), planning target volume (PTV): PTV-60 (pink),PTV-54 (orange), parotid-right, and parotid-left (yellow), brainstem (brown), spinalcord (cyan), mandible and larynx (dark brown). Dose volume histogram (DVH) marker: reference plan (triangle) and setup error plan (square) | PMC10348325 | rpor-28-2-224f3.jpg |
0.411212 | ab5cfcb0110943ca9f7aa27de6c71513 | Box and whisker plot for percentage dose variation ΔD (%) in rotational error (R), translational error (T), and translational plus rotational error (T+R) plans with no correction (NC) and moderate correction (MC) of setup errors for D98%, D95%, D2%, and D0.035cc in clinical target volume (CTV): (A) CTV-60, (B) CTV-54, and planning target volume (PTV) (C) PTV-60, and (D) PTV-54. The cross represents the mean, the line inside the box represents the median, the bottom of the box represents the 25% quartile, the top of the box represents the 75% quartile, the bottom whisker represents the minimum value, the top whisker represents the maximum value, and the dots represent the outlier | PMC10348325 | rpor-28-2-224f4.jpg |
0.40413 | 96f7c5112b5f4ba1a7e384a7f7909727 | Box and whisker plot for percentage dose variation ΔD (%) in rotational error (R), translational error (T), and translational plus rotational error (T+R) plans with no correction (NC) and moderate correction (MC) of setup errors (A) for D1cc and D0.035cc, in the spinalcord (SC) and brainstem (BS), (B) for Dmean and D50% in the parotid-left (PL) and parotid-right (PR), and (C) for Dmean and D50% in the larynx (LAR), and for D1cc and D0.035cc in the mandible (MAN). The cross represents the mean, the line inside the box represents the median, the bottom of the box represents the 25% quartile, the top of the box represents the 75% quartile, the bottom whisker represents the minimum value, the top whisker represents the maximum value, and the dots represent the outlier | PMC10348325 | rpor-28-2-224f5.jpg |
0.437678 | 0734c0e8d6aa49e3a45995e1e1588ce5 | Aperture block and range shifter configurations at our institution and aperture block w/and w/o range shifter configurations used in the water phantom validation. (a) Aperture block and range shifter configurations in PBSPT-based SRS. (b) Configurations of the aperture block without range shifters in ConfigA. (c) Configurations of the aperture block with a range shifter in ConfigB. | PMC10350098 | nihpp-2307.01416v1-f0001.jpg |
0.427301 | 1e543d0f33c5429db0471f861bb25791 | Results of the energy layer validation in homogenous water phantoms with ConfigA. Row (a) are the IDD curves, (b) log PDD curves, and (c) contours of iso-dose contours (20% and 80% of the maximum dose) in the transverse planes. From left to right, columns display the results calculated with aperture openings from 1cm to 4cm, respectively. Blue lines are the results calculated by MCsquare, while orange lines are the results calculated by VPMC. | PMC10350098 | nihpp-2307.01416v1-f0002.jpg |
0.374326 | fe25669c46194facbcc5e163f75246bf | Dose distributions on a transverse plane of patient 5 ((a)-(c)) and patient 7 ((d)-(f)) calculated by VPMC. Red contours are CTVs. Dose profiles are compared in (b) (e) longitudinal direction (horizontal x arrows in (a) and (d)) and (c) (f) lateral direction (vertical y arrows in (a) and (d)). Results with the aperture block from RayStation MC, VPMC, and MCsquare are in green, blue and purple, respectively. | PMC10350098 | nihpp-2307.01416v1-f0003.jpg |
0.423464 | a8b7511701f443c8a326fe500bf44781 | Experimental workflow and MS processing. A) Overview of cohort and sample processing. B) Distribution of duplicate CV before (red) and after (blue) filtering of robustly measured peptides; dotted lines indicate median. C) Principal component analyses before and after ComBat batch correction of the data. Dots represent individual samples and are colored by their corresponding batch. | PMC10350182 | nihpp-rs3073597v1-f0001.jpg |
0.429601 | 0eab71e272a64fe4a134f6ce1353cae0 | Overview of differentially abundant peptides in CSF in AD. A) Overview of differentially expressed peptides between DEM-AD and any non-AD group. B) MS-intensity levels of 4 peptides differentially expressed in an AD specific pattern (ALDOA: Aldolase-A, BASP1: Brain acid soluble protein 1, PKM: Pyruvate kinase muscle). Red lines indicate mean. C) STRING-DB cluster highlighting the enrichment of proteins involved in energy metabolism in AD CSF. Blue indicates proteins from the GO-term “canonical glycolysis”. | PMC10350182 | nihpp-rs3073597v1-f0002.jpg |
0.441635 | f1e48863d8ef43ee8367b21ecb41c54c | Immunoblotting of ALDOA and PKM indicate the presence of full-length proteins in CSF. A) Normalized band intensities of ALDOA and PKM follow similar intensity pattern across groups as their tryptic peptides (*: p < 0.05). B) MS-intensity of tryptic peptides of both ALDOA and PKM are correlated with the normalized band intensity indicating presence of full-length proteins in CSF. | PMC10350182 | nihpp-rs3073597v1-f0003.jpg |
0.444129 | 7e1502a0e20b4816955f574fd2da8db1 | Measures of metabolites in CSF. A) Levels of glucose and lactate in CSF across groups. (*: p < 0.05) B) MS intensities for ALDOA and PKM peptides correlate negatively with the CSF glucose and lactate levels. C) Peripheral glucose metabolism marker HbA1c did not show a strong correlation with MS intensities for ALDOA and PKM peptides. | PMC10350182 | nihpp-rs3073597v1-f0004.jpg |
0.404657 | 642aecfd1c7f4a6787fa2d5bf1c3124b | Levels of glycolytic enzymes are generally elevated in AD in CSF and brain tissue. Colors represent scaled peptide or protein abundance across all proteins for each individual dataset.†: DEx compared to MCI-AD, *: DEx compared to DEM-AD, #: DEx compared to AD in tissue. | PMC10350182 | nihpp-rs3073597v1-f0005.jpg |
0.426121 | ca838dde9a1645e0a9566cd6ba348579 | CONSORT flow diagram | PMC10350277 | 40364_2023_494_Fig1_HTML.jpg |
0.445462 | 5ad9248e5550434a8565169a485b8866 | Type of magnetic resonance images acquired for the study: (A) T1-weighted image; (B) T2-weighted image. The segmented region of interest is also displayed | PMC10350277 | 40364_2023_494_Fig2_HTML.jpg |
0.447534 | 0955ba29a4ba4e15afd5ddb5f11dd085 | Features selection process | PMC10350277 | 40364_2023_494_Fig3_HTML.jpg |
0.413648 | 1c5daf80887645c2a2e6fbe6a5094ee2 | Radiomic model. (A) Kaplan-Meier curves for the retrospective dataset (n = 123 patients, used for model training). (B) Kaplan-Meier curves for the prospective dataset (n = 108 patients, used for model testing). For comparison, a follow-up time of 36 months was displayed. Shadows represent 95% confidence interval | PMC10350277 | 40364_2023_494_Fig4_HTML.jpg |
0.470558 | 4ae78cd83fb4421d8a95d641a873691b | Comparison of the prognostic performance of the radiomic model with the clinical tumor-node-metastasis (cTNM) stage and pathological tumor-node-metastasis (pTNM) stage on the prospective subset 1 (n = 75 prospective patients). (A/B) Kaplan-Meier curves for the cTNM/pTNM, with low-risk corresponding to cTNM/pTNM stage = III and high-risk corresponding to cTNM/pTNM stage = IV. Shadows represent 95% confidence interval. (C) Kaplan-Meier curves for the radiomic signature. Shadows represent 95% confidence interval. (D) Concordance indexes (C-index) for the cTNM, pTNM and radiomic signatures. *p < 0.05 (Kruskal-Wallis with Tukey-Kramer correction) | PMC10350277 | 40364_2023_494_Fig5_HTML.jpg |
0.388788 | 02a45399ef0941038344c8d900f9b4a8 | Comparison of the prognostic performance of the radiomic model with 7 prognostic genomic signatures and the clinical tumor-node-metastasis stage (cTNM) in terms of concordance index (C-index), on the prospective subset 2 (n = 90 prospective patients). Grey boxplots: C-index of the 7 genomic signatures; blue boxplot: C-index of the cTNM staging; red boxplot: C-index of the radiomic signature (Rad). The C-index of the radiomic model was significantly different (Kruskal-Wallis p < 0.001, with Tukey-Kramer correction) from that of the cTNM staging and of 6 over 7 genomic signatures (G-1, G-2, G-4, G-5, G-6 and G-7). No statistical difference was found between the C-index of the radiomic signature and G-3 | PMC10350277 | 40364_2023_494_Fig6_HTML.jpg |
0.439553 | ff3c74a6bfbd401297ad4c8e9ec927a5 | Radiomic signature distributions in patients classified according to the pathologic tumor-node-metastasis stage (pTNM = III – IVa – IVb). *p < 0.05 (Kruskal-Wallis, with Tukey-Kramer correction). n = 37 patients presented pTNM = III; n = 76 patients presented pTNM = IVa; n = 64 patients presented pTNM = IVb. | PMC10350277 | 40364_2023_494_Fig7_HTML.jpg |
0.418309 | 9541c221ad6a4c3d855c26ed30b40f49 | Maximum likelihood phylogenetic reconstruction of Methanobacterium metagenome assembled genomes based on 76 archaeal marker genes (Lee, 2019). The well and depth from which each MAG was collected is denoted in the sample name, along with the MAG ID. The MAGs are color-coded based on their population designation: blue = type II, green = mixed, yellow = type I. Bootstrap values ≥ 90% out of 1,000 bootstraps are denoted with black circles. Methanosarcina barkeri representatives were chosen as the outgroup. | PMC10350532 | fmicb-14-1205558-g001.jpg |
0.480133 | c3d9b3a8ec2e400299753a93ca7a5f4a | Visual depiction of the pangenome of Methanobacterium-affiliated metagenome assembled genomes (MAGs) recovered from subsurface fracture fluids from the Samail Ophiolite, Oman. The inner radial dendrogram shows the 3,125 protein-encoding genes homologs in the pangenome, clustered by presence/absence across MAGs. The 8 MAGs of the three different population “types” are plotted on the innermost 8 layers (270° arcs), ordered and spaced to reflect groupings based on genomic composition. The presence of gene clusters are indicated by filled and colored bars; unshaded bars indicate the lack of a gene cluster in a MAG. Gene clusters belonging to the core genome shared across all MAGs and environmental accessory genomes are binned and labeled with the according specificity on the outside of the outermost layer. The top right portion above the pangenome contains relevant information for each MAG, with the y-axis limits contained within the parentheses. The relative abundance is representative of each Methanobacterium MAG’s percentage of overall reads within its corresponding metagenome. | PMC10350532 | fmicb-14-1205558-g002.jpg |
0.459604 | b6f5fa1b471c4c7aae0604ce2c44509a | The number of genes within each Methanobacterium population’s accessory metagenome assembled genome. The COG20 Category is listed on the y-axis and the x-axis denotes the number of genes that make up the category. The full list of genes found in the top categories of each population can be found in Supplementary Table 4. | PMC10350532 | fmicb-14-1205558-g003.jpg |
0.398771 | a5f57a9095ed4dfe822e2d3407fcf42d | The gene copy number of genes (rfaB and wcaA) encoding glycosyltransferase in the accessory metagenome assembled genomes of each Methanobacterium population. The full list of genes within the accessory genome of each population can be found in Supplementary Table 4. | PMC10350532 | fmicb-14-1205558-g004.jpg |
0.459207 | 23ee72fe738d4fb0802426280693cff2 | (A) The gene copy number of genes involved in transport mechanisms for various metabolites. The x-axis denotes the gene and are faceted (above) into custom transporter categories. The y-axis represents each MAG at the depth in which it was collected and is faceted (on the right) from the borehole in which it was sampled and the Methanobacterium population it belongs to. Each dot is also sized by the gene copy number. (B) The presence or absence of additional transporter genes across each population type. The presence of a gene is indicated by a filled in dot and represents all MAGs within the population containing the presence of the gene. The x-axis represents the transporter genes and are faceted (above) into custom categories. The y-axis represents the Methanobacterium population. | PMC10350532 | fmicb-14-1205558-g005.jpg |
0.390638 | fcd196a4510b497f87d09a7aa60c0cc7 | The different enzymatic pathways for the core methanogenesis pathway (gray), hydrogenetrophic (tan), acetoclastic (purple), formatotrophic (red) or steps involving conversion of bicarbonate into CO2 for methanogenesis (black). Carbon substrates, intermediates, and products appear in rectangular boxes, while enzymes are in black lettering next to arrows that point in the direction of their end product. Dashed arrows indicate the potential use for the pathway to allow for intracellular CO2 to be generated and subsequently reduced to CH4. The enzymatic component of heterodisulfide reductase (hdr) is included in both formatotrophic and hydrogenetrophic pathways because each due to its similar function, but does not represent a different gene. The bottom of the figure contains a presence/absence diagram, where circles are filled in to represent the presence of a gene in the respective pathway and a white, unfilled circle indicates the absence of a gene. The rows of the presence/absence diagram are representative of each Methanobacterium population. Figure inspired by Carr et al. (2018). Genes: fwd, formylmethanofuran dehydrogenase; ftr, formylmethanofuran:H4SPT formyltransferase; mch, methenyl-H4SPT cyclohydrolase; mtd, F420-dependent methylene H4SPT dehydrogenase; mer, F420-dependent methylene-H4SPT reductase; mtr, methyl-H4SPT:coenzyme M methyltransferase; mcr, methyl-coenzyme M reductase; ack, acetate kinase; pta, phosphate acetyltransferase; acs, acetyl-CoA synthetase; cdh, carbon monoxide dehydrogenase; fdh, formate dehydrogenase; hdr, heterodisulfide reductase; mvh, methyl viologen-reducing [NiFe]-hydrogenase; frh, coenzyme F420 [NiFe]-hydrogenase; F420, coenzyme F420. Carbon compounds: CO2, carbon dioxide; formyl-MFR, formyl-methanofuran; formyl-H4SPT, formyl-tetrahydrosarcinapterin; methenyl-H4SPT, methenyl-tetrahydrosarcinapterin; methylene-H4SPT, methylene-tetrahydrosarcinapterin; methyl-H4SPT, methylene-tetrahydrosarcinapterin; methylene-S-CoM, 2-(Methylthio)ethanesulfonate; Acetyl-CoA, acetyl-Coenzyme A; Acetyl-PO4, acetylphosphate; CH3COO−, acetate; HCOO−, formate. | PMC10350532 | fmicb-14-1205558-g006.jpg |
0.403284 | e5dd655548554b1b9b923f4bc9a9dcbf | Child/adolescent vaccination coverage (≥ 1 dose) and parental intent to get children vaccinated, by child age/adolescent group, United States, household Pulse Survey, September 14–November 14, 2022. | PMC10351440 | IANN_A_2232818_F0001_C.jpg |
0.40275 | bfc4c5e2c1d9478fa274b8a36b749a90 | TLR signaling pathways. | PMC10351979 | fendo-14-1124334-g001.jpg |
0.438918 | f60cb7a32fbe40e387812b114618af6e | NLRP3 inflammasome pathway. | PMC10351979 | fendo-14-1124334-g002.jpg |
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