dedup-isc-ft-v107-score
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0.501913 |
30dacd6fe75b4083a86e70181e1a28fc
|
Resolution enhancement results for in vivo imaging of rat ear blood vessels. AR-PAM images: (a) raw PA image, (b) by R-L-10, (c) by FDUNet, (d) by EDSR, (e) by RRDBNet, and (f) by FFANet. (g,h) 1D profiles along the lines #6 (g) and #7 (h), respectively, in (a)–(f). The blue arrow indicates the representative area with small vessels. Scale bar: 1 mm.
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PMC9095893
|
gr8.jpg
|
0.442976 |
82ddde5c39a844589291b5605e254b61
|
Prognostic value of alanine aminotransferase (ALT) in pediatric patients with DCM. ROC curves showing ALT levels in patients with DCM predicting the cardiac death. AUC, area under the curve; DCM, dilated cardiomyopathy; ROC, receiver operating characteristic.
|
PMC9096786
|
fped-10-833434-g001.jpg
|
0.533317 |
5ce469fef2b64acbbe06ec94e221f0ff
|
The comparison of mortality according the follow-up time after diagnosis of DCM.
|
PMC9096786
|
fped-10-833434-g002.jpg
|
0.487216 |
096839cdad1d447db881d7efc6bb2424
|
Survival rates from Kaplan–Meier estimates among the study population by sex (A) and age at diagnosis (B).
|
PMC9096786
|
fped-10-833434-g003.jpg
|
0.440858 |
fd46d22541eb479cb498cc947f914cf7
|
Representation of genes and loci in syndromic and non syndromic syndactyly analyzed in this review. These variants are further characterized according to involvement in documented syndactyly pathogenesis interactions. WNT Wingless‐type integration site family, BMP Bone Morphogenic Protein, FGF Fibroblast Growth Factor, RA Retinoic Acid
|
PMC9097448
|
13023_2022_2339_Fig1_HTML.jpg
|
0.499503 |
8ae0b186357c44dfa3dd30342f41e08b
|
Mean compliance scores of the conservative and the liberal participants in the disgust and the non-disgust conditions of study 1.(Note: Error bars show standard errors).
|
PMC9098091
|
pone.0267735.g001.jpg
|
0.400017 |
10bb5b8346e54fabadc1922d0951b2d3
|
Mean compliance scores of the unvaccinated conservative and the liberal participants in the disgust, non-disgust, and the vaccine-perks conditions in study 2.(Note: Error bars show standard errors).
|
PMC9098091
|
pone.0267735.g002.jpg
|
0.390957 |
ce0f991f05534d9eb462c619ae4748d5
|
Mean Likelihood ratings of receiving COVID-19 vaccine by the unvaccinated conservative and the liberal participants in the disgust, non-disgust, and the vaccine-perks conditions in study 2.(Note: Error bars show standard errors).
|
PMC9098091
|
pone.0267735.g003.jpg
|
0.400145 |
0d095a95666b4508bfeaff1d1a0c6048
|
Clinical presentations in the right eye (OD) and left eye (OS) of the patient. (A) Manifestation of Kayser-Fleischer (K-F) ring and sunflower-like cataract. (B) Fundus images of osteocyte-like pigmentation (white arrows) in bilateral retina. (C) Optical coherence tomography (OCT) showing outer retina atrophy and cystoid macular edema. (D) Vision detection featuring binocular tunnel vision.
|
PMC9098211
|
fmed-09-877752-g0001.jpg
|
0.466316 |
e8e146b6d9234c3290b7fda3201d6018
|
Pedigree of the patient's family. (A)
CNGA1 variant family pedigree. Circles represent females and the square represents the male. The filled circle represents the patient with RP. The proband is indicated by a black arrow, while A represents a mutation. (B) Partial sequence of ATP7B gene locus of the proband (II-2) and the unaffected family members (I-1 and I-2). The columnar graphics indicate the site of the variant. (C) Partial sequence of the family's CNGA1 gene locus. (D) Partial sequence of the family's RP2 gene locus. (E) Partial sequence of the family's SNRNP200 gene locus.
|
PMC9098211
|
fmed-09-877752-g0002.jpg
|
0.460686 |
80d18ce0ba084bb0b3c94e47e0d5b7dd
|
Prediction of the protein structure of the ATP7B(R778L) mutant expression product.
|
PMC9098211
|
fmed-09-877752-g0003.jpg
|
0.494604 |
64a2bd058cad448e990a139e6edc77c4
|
Logical mapping illustrates the possible pathogenesis of Wilson disease and retinitis pigmentosa in this patient.
|
PMC9098211
|
fmed-09-877752-g0004.jpg
|
0.373636 |
78a79b4bfe6743d3b9eca05c21ff92b7
|
hPSC-derived neurons express markers of MSNs. (A) hPSCs are differentiated into hMSN-like cells following an Activin A induction protocol (Arber et al., 2015 [17]), (B) immunostained for MAP2+ (red), DARPP32 (green), and DAPI (blue) and quantified for DARPP32+ percentage. GFP-transfected hMSN-like cells were imaged to better highlight cell morphology. Scale bar = 50 µm. (C) QRT-PCR of RNA isolated from H1 (blue) and H9 (orange) hPSCs and hPSCs differentiated into hMSN-like cells at DIV 16 (D16) and DIV 45 (D45), for genes of interest. Values were normalized to HPRT1 mRNA levels in the same samples and expressed as normalized fold changes in hMSN-like versus hPSC cells. Values normalized to GUSB are provided in Figure S1. Gene categories are labeled in red. n = 3–4 independent replicates & 2 technical replicates. Error bars = Standard error.
|
PMC9100557
|
cells-11-01411-g001.jpg
|
0.444966 |
c946110141b44ab58ab20b09a4a5fcda
|
hMSN-like cells exhibit dose and time-dependent responses to dopamine. (A) QRT-PCR of RNA isolated from DIV45 H1 and H9 hMSN-like cells 1 h after exposure to different dopamine concentrations (1 µM to 10 mM) and analyzed for FOSB and FOS. (B) QRT-PCR of RNA isolated from DIV 45 H1 and H9 hMSN-like cells 0 to 120 min after exposure to 1 mM dopamine and analyzed for FOSB and FOS. (A,B) For QRT-PCR, values were normalized to GUSB mRNA levels in the same samples and expressed as a fold change in dopamine versus PBS control cultures. * = p < 0.05; One-way ANOVA. n = 3–4 independent replicates and 2 technical replicates. (C) Venn Diagram showing the number of shared differentially expressed genes (DEG) between DIV45 hMSN-like cells quantified by RNA-seq 1 hour after acute 1 μM and 1 mM dopamine. (D) Functional enrichment analysis of RNA-seq data for KEGG pathways of DEGs unique to DIV45 1 μM dopamine dosed (left) and 1 mM dosed (right) hMSN-like cells. Significance is represented by Log10-transformed p-values. Dotted red line indicates p-value of 0.05. (C,D) DEGs were identified by max group mean ≥ 0.75, FDR p-value < 0.05, and Log2(Fold Change) > |1|. Differential expression was performed against PBS control group using the Wald test. n = 3 independent replicates.
|
PMC9100557
|
cells-11-01411-g002.jpg
|
0.467486 |
2436e5b0985c4da1abf13df7abeee1d1
|
Chronic administration of dopamine leads to desensitization of genes implicated in cocaine and dopamine responses. (A) Schematic for isolation of RNA from H9 hMSN-like cells dosed acutely (DIV45) and chronically (DIV50) with dopamine. (B) Total number of DEGs from RNA-seq of H9 hMSN-like cells dosed with 1 μM and 1 mM dopamine. (C) Venn diagrams showing shared number of DEGs 1 hour after dosage between hMSN-like cells dosed with DIV45 acute and DIV50 chronic dopamine. (D) Heatmaps of top 20 desensitized genes for hMSN-like cells exposed to acute and chronic dopamine. Desensitized genes are defined as the ratio of Acute 1 h Log2(Fold Change)/Chronic 1 h Log2(Fold Change) > |1.1|. Overlapping genes highlighted by tan-colored bars. (E) IPA upstream regulators and gProfiler transcription factor regulatory motifs of desensitized genes common between 1 μM and 1 mM dopamine conditions. (F) Gene ontology biological processes for highly desensitized genes after chronic 1 mM dopamine, defined when the ratio Acute 1 h Log2(Fold Change)/Chronic 1 h Log2(Fold Change) > |2|. (E,F) Significance is represented by Log10-transformed p-values with dotted red line indicating p-value of 0.05. In all cases, data were obtained from RNA-seq of H9 hMSN-like cells. DEGs were identified by max group mean ≥ 0.75, FDR p-value < 0.05, and Log2(Fold Change) > |1|. Differential expression was performed against PBS control group using the Wald test. n = 3 independent replicates.
|
PMC9100557
|
cells-11-01411-g003.jpg
|
0.473682 |
bfc19af5c92e44808854e5d7c92c2ac0
|
Time course of chronic dopamine administration reveals peak in DEGs at day 3 and desensitization at day 5. (A) Total number of DEGs from RNA-seq of DIV50 hMSN-like cells 1 h after 2, 3, 4, or 5 days of daily dosing of 1 mM dopamine. (B) Venn diagrams showing shared (white) and unique (red) numbers of DEGs between hMSN-like cells dosed with dopamine for 2–5 days. (C) Gene ontology biological processes and KEGG pathways for shared and unique genes from hMSN-like cells dosed with dopamine for 2–5 days. Significance is represented by Log10-transformed p-values with dotted red line indicating p-value of 0.05. In all cases, data were obtained from RNA-seq of H9 hMSN-like cells. DEGs were identified by FDR p-value < 0.05. Differential expression was performed against ascorbic acid vehicle control group using the Wald test. n = 2–3 independent replicates.
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PMC9100557
|
cells-11-01411-g004.jpg
|
0.422874 |
a59d38675ab04faea3e47b034d35b588
|
hMSN-like cells capture some features of dopamine receptor cross-interactions. (A) Total number of DEGs from RNA-seq of DIV45 hMSN-like cells dosed with receptor agonists. (B) Gene ontology molecular functions and reactome pathways for DEGs from hMSN-like cells dosed with ADORA2A agonist CGS21680 and D2-like receptor agonist quinpirole. Dotted red line indicates p-value of 0.05. (C) Venn diagram showing shared and unique numbers of DEGs for DIV45 hMSN-like cells dosed with agonists. In all cases, data were obtained from RNA-seq of DIV45 H9 hMSN-like cells. DEGs were identified by FDR p-value < 0.05. Differential expression was performed against a water (vehicle) control group using the Wald test. n = 3 independent replicates.
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PMC9100557
|
cells-11-01411-g005.jpg
|
0.507057 |
f9c4e0b8a1524b81b707235c17fef06b
|
Fibrous composite materials with metal matrices disposal methods.
|
PMC9100760
|
materials-15-03207-g001.jpg
|
0.430439 |
f057ca2eaef14d06951b7fd2d10eac30
|
Fragments of (B-W/fibrous composite materials with metal matrices): prepregs from W-B fibres with subsequent aluminium sputtering (a); tubes after hot pressing of prepregs (diameter 20–100 mm (b); also—in section (c); multilayer plate of B-W fibres in a matrix of aluminium alloy (c) thickness—4 mm (d).
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PMC9100760
|
materials-15-03207-g002.jpg
|
0.468046 |
7f0cf16061f54588992b3dfb6606ec24
|
Al-W-B microstructure (a,b): 1—tungsten wire rod 10–12 µm, 2—boron coating with a diameter of 70–100 µm; 3—matrix material aluminium.
|
PMC9100760
|
materials-15-03207-g003.jpg
|
0.463634 |
a6ff4abd1def428f8b4dd68b64f86786
|
Stages of Al-W-B waste shredding: breaking (a) and cutting the plates (b); shredding and milling the material (c,d).
|
PMC9100760
|
materials-15-03207-g004.jpg
|
0.440937 |
2f401a5dd6aa4ac98021776437e78a64
|
Microstructure of Al-W-B composite after grinding in a vibrating mill (a–c).
|
PMC9100760
|
materials-15-03207-g005.jpg
|
0.445817 |
9db2ae13b40b4599ac9ae3cb75bda1e5
|
Grinding diagram Al-W-B waste into powder material at various stages.
|
PMC9100760
|
materials-15-03207-g006.jpg
|
0.399333 |
7540e6ccaf52407c891fd4b89612c078
|
Microstructure of Al-W-B composite powders after grinding in disintegrator (a,b).
|
PMC9100760
|
materials-15-03207-g007.jpg
|
0.421461 |
2b940fa640714ebc980b5e15ed22c70a
|
Elements for grinding and polishing devices: honing stones 6 × 10 × 120 mm (a,b); ring drill Ø 45 mm (c).
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PMC9100760
|
materials-15-03207-g008.jpg
|
0.461658 |
64e9a291772e4b90b3993f204acfdd54
|
Coefficient of friction versus time, cycles, distance.
|
PMC9100760
|
materials-15-03207-g009.jpg
|
0.484427 |
fd2783a6e84f4a15a21730930dbaccf9
|
Wear images of the counterparty and the body under study (a) spherical counterpart made of steel 100 Cr 6; (b) the body being examined.
|
PMC9100760
|
materials-15-03207-g010.jpg
|
0.397899 |
5a50800e54434f0098ab570f22885560
|
Sample of concrete containing boron 40 × 40 × 160 mm3.
|
PMC9100760
|
materials-15-03207-g011.jpg
|
0.40941 |
770a923be5c548f7b57e713e2fb0a10f
|
Boron-containing material: in an aluminium matrix (a); (W-B) fibres after chemical cleaning from aluminium matrix material: general view (b); W-B fibre powder (c).
|
PMC9100760
|
materials-15-03207-g012.jpg
|
0.409997 |
80bf4e56d436444d886d9c321dd6cc91
|
Elements filled with W-B (30–50%) based on copper (a,b) and iron (c) powder after pressing and sintering.
|
PMC9100760
|
materials-15-03207-g013.jpg
|
0.444345 |
82f75b20d9f64f79ae4499138627f4f9
|
Microstructure of elements based on copper with the inclusion of W-B fibers in a copper matrix (a,b).
|
PMC9100760
|
materials-15-03207-g014.jpg
|
0.451176 |
08c3759869984bf593c1718e5378d72e
|
Distribution of examined lymph nodes.
|
PMC9101477
|
fsurg-09-864593-g001.jpg
|
0.445954 |
0c50cc55df824e649567605d6a4c04d4
|
The fitting curves for the OR of nodal stage migration were smoothed using the LOWESS technique, and the corresponding cutoff point of the ELNs was calculated by the Chow test. ELN, examined lymph node. OR, odds ratio.
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PMC9101477
|
fsurg-09-864593-g002.jpg
|
0.487048 |
409cb7c742bc4095bd03fee6f02337a4
|
Overall survival rates among patients with node-negative EC at the cutoff point of 16 ELNs. ELN, examined lymph node. EC, esophageal cancer.
|
PMC9101477
|
fsurg-09-864593-g003.jpg
|
0.497385 |
277db3864a5a4805a7492ad4de382865
|
Overall survival rates among patients with node-positive EC at the cutoff point of 16 ELNs. ELN, examined lymph node. EC, esophageal cancer.
|
PMC9101477
|
fsurg-09-864593-g004.jpg
|
0.474152 |
2c07d592d0924dbd97327bb2bfd13341
|
The fitting curves for the HR of each ELN count (>16 nodes) compared with 16 ELNs (as a reference) among patients with node-negative EC were smoothed using the LOWESS technique. ELN, examined lymph node. EC, esophageal cancer. OR, odds ratio.
|
PMC9101477
|
fsurg-09-864593-g005.jpg
|
0.413003 |
b323c14743c84e3c8dcedcc93f07ffa6
|
The fitting curves for the HR of each ELN count (>16 nodes) compared with 16 ELNs (as a reference) among patients with node-positive EC were smoothed using the LOWESS technique. ELN, examined lymph node. EC, esophageal cancer. OR, odds ratio.
|
PMC9101477
|
fsurg-09-864593-g006.jpg
|
0.446835 |
171171d28b294d6cbaf74fe89f563fde
|
Response surface plots of the interaction of alcohol insoluble residue from potato peel byproduct (AIR-PPB) and particle size (PS) on (A) total dietary fibers (TDF) (g/100 g FEP), (B) insoluble dietary fibers (IDF) (g/100 g FEP), and (C) soluble dietary fibers (SDF) (g/100 g FEP) of FEP samples as compared to control pasta (CP) (0 AIR-PPB, 0 PS). FEP, fiber-enriched pasta.
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PMC9101751
|
molecules-27-02868-g001.jpg
|
0.497084 |
1dea681c4a674d35973b95ccd4a8b63f
|
Response surface plots of the interaction of alcohol insoluble residue from potato peel byproduct (AIR-PPB) and Particle size (PS) on (A) optimum cooking time (OCT) (min), (B) cooking loss (Cl) (%), (C) mass increase index (MII) (kg cooked pasta/kg uncooked pasta), (D) Firmness (N), and (E) Stickiness (N) of fiber-enriched pasta (FEP) samples.
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PMC9101751
|
molecules-27-02868-g002.jpg
|
0.438685 |
a0af700ae7794ed08ea3bf454d617c39
|
Response surface plots of the interaction of alcohol insoluble residue from potato peel byproduct (AIR-PPB) and particle size (PS) on (A) onset temperature (To) (°C), (B) melting temperature (Tp) (°C), (C) conclusion temperature (Tc) (°C), and (D) ∆H (J/g) of fiber-enriched pasta (FEP) samples.
|
PMC9101751
|
molecules-27-02868-g003.jpg
|
0.460536 |
b613ad1d5d6c4d2ab764e9639d5c730a
|
Survival analyses. Kaplan–Meier analyses of cumulative liver graft survival (a) and overall survival (b) in patients with no intensive care unit discharge delay (ICUDD) and patients with ICUDD.
|
PMC9101850
|
jcm-11-02561-g001.jpg
|
0.453777 |
3f28191c7ae54d60a3abfcfde7ce101a
|
Survival analyses. Kaplan–Meier analyses of cumulative liver graft survival (a) and overall survival (b) in patients who did not become newly colonized with a multi-resistant organism infection and patients who did become colonized.
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PMC9101850
|
jcm-11-02561-g002.jpg
|
0.47841 |
00bf3bd35e2949fdbfd6038dd43058ce
|
(A–C): 3D-Response surface plots demonstrating the influence of independent variables i.e., amount of span 60 (X1), amount of cholesterol (X2) and amount of drug (X3) on VZ (nm) of EZL-PNs.
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PMC9101870
|
molecules-27-02748-g001.jpg
|
0.509143 |
a673ef650977428fa2dc795af5f58105
|
(A–C): 3D-Response surface plots demonstrating the influence of independent variables i.e., amount of span 60 (X1), amount of cholesterol (X2) and amount of drug (X3) on EE (%).
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PMC9101870
|
molecules-27-02748-g002.jpg
|
0.460086 |
058b07829bea41f0bdb8b42af4ea7047
|
(A–C): 3D-Response surface plots demonstrating the influence of independent variables i.e., amount of span 60 (X1), amount of cholesterol (X2) and amount of drug (X3) on drug release.
|
PMC9101870
|
molecules-27-02748-g003.jpg
|
0.458147 |
422534c243e2406aa3397715fd9d1f25
|
(A) Vesicle size and (B) Zeta potential graph of EZL-PNsopt.
|
PMC9101870
|
molecules-27-02748-g004.jpg
|
0.469083 |
dc38ec8671454f9a86826bbe4887ebb2
|
SEM photograph of EZL-PNsopt.
|
PMC9101870
|
molecules-27-02748-g005.jpg
|
0.401023 |
a52824810c28482487d372ec6db2ac7a
|
Thermal transition analysis of (A) pure EZL, (B) maltodextrin and (C) EZL-PNsopt.
|
PMC9101870
|
molecules-27-02748-g006.jpg
|
0.461083 |
117516503a624225ae0135fd2151f227
|
X-ray diffraction spectra of (A) pure EZL, (B) maltodextrin and (C) EZL-PNsopt.
|
PMC9101870
|
molecules-27-02748-g007.jpg
|
0.45568 |
01c3777c34dc40efb880a828cc59c19a
|
In vitro drug release profile of EZL-PNopt and pure EZL.
|
PMC9101870
|
molecules-27-02748-g008.jpg
|
0.438568 |
aac3da2a16bc4abfabcdd8c05856bb02
|
In vitro release kinetic model for EZL-PNsopt.
|
PMC9101870
|
molecules-27-02748-g009.jpg
|
0.40736 |
4d27f9a01d1d41e78088ec5df1059ea4
|
Ex-vivo gut EZL permeation profile from pure EZL and EZL-PNsopt.
|
PMC9101870
|
molecules-27-02748-g010.jpg
|
0.412486 |
d4a3b95272e948bbaf8f7c7aff8dd137
|
EZL plasma concentration vesicle size time profile of pure EZL and EZL-PNsopt.
|
PMC9101870
|
molecules-27-02748-g011.jpg
|
0.485495 |
0d34867d81304972a8c3724f89e8c9ba
|
Photographs of (A) non-ulcer induce stomach (Group-I), (B) indomethacin induced (Group-II), (C) Pure EZL (Group III) (D) EZL-PNopt (Group IV).
|
PMC9101870
|
molecules-27-02748-g012.jpg
|
0.431049 |
d799be6b96e347d9973b3af4e81e7454
|
PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flow diagram of study selection process.
|
PMC9102382
|
fpsyg-13-882389-g001.jpg
|
0.444263 |
4406380d82c54311ad8208d1d6e4db4e
|
Diagram representing included studies on the three levels of evidence for dyadic interdependence.
|
PMC9102382
|
fpsyg-13-882389-g002.jpg
|
0.429929 |
7853aa8a8efa4a4ba31448a6af306228
|
Schematic illustrating the 2 × 2 crossover experimental design used in this study. Participants followed a home-based balance and coordination training program for 12 weeks split into two six-week blocks. Following an initial laboratory-based performance assessment (A1), participants were split into two groups. Group 1 performed home-based training with vibrotactile SA for the first six weeks then trained without vibrotactile SA for the following six weeks. Group 2 performed home-based training without vibrotactile SA for the first six weeks then trained with vibrotactile SA for the following six weeks. After each block of six weeks, participants’ balance and coordination were assessed halfway through (A2) and at the end (A3) of the 12-week intervention.
|
PMC9103288
|
sensors-22-03512-g001.jpg
|
0.429088 |
fbe988df9c5048aeb6a62a535a5eaf4d
|
The smartphone-based balance trainer included a user interface unit (Apple iPod) and sensing unit (elastic band with a sensing Apple iPod and four tactors to provide vibrotactile SA). Participants were instructed to wear the user interface unit on a lanyard while performing exercises. The user interface unit allowed participants to select exercises and acted as a timer that instructed participants to start and stop exercises. The sensing unit used (1) the tri-axial gyroscopes embedded in the Apple iPod to measure ML and AP angular velocities, (2) both the tri-axial accelerometers and gyroscopes embedded in the Apple iPod to estimate tilt with respect to gravitational acceleration, and (3) an audio signal to trigger the four tactors to provide vibrotactile feedback. Participants were instructed to make a postural correction in the opposite direction (“move away from the vibration”) when they perceived a vibration.
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PMC9103288
|
sensors-22-03512-g002.jpg
|
0.491758 |
658397d342ea4dd1940e2fb4f2c2e951
|
Schematic demonstrating the architecture of the vibrotactile feedback algorithm used in the smartphone-based balance trainer. For each exercise, tilt angles and angular velocities extracted from the Core Motion SDK were used to determine when the vibrating actuators (tactors) should be activated. A control signal (trunk tilt plus one half of the angular rate of tilt [42]) was used for static standing, compliant standing, and arm-raise exercises. However, the control signal only considered trunk tilt for the weight shifting exercises. When a participant’s control signal exceeded a pre-defined threshold in a particular direction (Table 2), the tactor bud in the direction of movement was activated via an audio signal to provide a vibrotactile cue to the participant.
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PMC9103288
|
sensors-22-03512-g003.jpg
|
0.416552 |
0d2db4c5684545d5a64406cba1484f6c
|
Screenshots showcasing the prompts participants responded to during home-based balance and coordination training sessions. After each repetition of a home-based exercise, participants were prompted (a) to report whether they stepped out during the exercise, and (b) to indicate a self-rating on the VAS 1–5 scale.
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PMC9103288
|
sensors-22-03512-g004.jpg
|
0.449196 |
219778470d5d4c9abac4090db50f5c34
|
SARAposture&gait scores measured during assessments performed in the laboratory immediately before (initial assessment A1), halfway through (intermediate assessment A2), and immediately after (final assessment A3) home-based balance and coordination training for each group. No statistically significant changes in the SARAposture&gait scores were observed after 12 weeks of training (between A1 and A3), but all participants’ scores improved (Participants 3, 6, 9, and 10) or remained the same as baseline at assessment A1 (Participants 1, 2, and 8). Group 1 received vibrotactile SA during the first six weeks of training (between A1 and A2). Group 2 received vibrotactile SA during the second six weeks of training (between A2 and A3).
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PMC9103288
|
sensors-22-03512-g005.jpg
|
0.476571 |
6ee49e1118ab42fca9d17d21cc5e141b
|
DGI scores measured during assessments performed in the laboratory before (pre−SA) and after training at home without vibrotactile SA (post−SA). Participants scored significantly higher on the DGI assessment after training with vibrotactile SA. The main plot shows individual trends for the participants’ DGI scores, and the inset shows the average DGI scores. Error bars on the bar plot indicate standard error (SEM) values. DGI scores from Participant 2 are not included due to missing data. (*) indicates statistically significant changes (p < 0.05).
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PMC9103288
|
sensors-22-03512-g006.jpg
|
0.442514 |
4636c6fdb32b4eb28117281a68b8711d
|
SARAposture&gait scores measured during assessments performed in the laboratory before (pre+SA) and after (post+SA) training at home with vibrotactile SA. Participants scored significantly lower on the SARAposture&gait after training with vibrotactile SA. The main plot shows individual trends for the participants’ SARAposture&gait scores and the inset shows the average SARAposture&gait scores. Error bars on the bar plot indicate SEM values. (*) indicates statistically significant changes (p < 0.05).
|
PMC9103288
|
sensors-22-03512-g007.jpg
|
0.460442 |
bd29c47e9cb342169af9bb8e2cda936c
|
RMS ML Sway measured while participants were standing on foam with eyes open before pre+SA,pre−SA and after post+SA,post−SA each of the six-week training blocks. No statistically significant differences in postural sway measures were captured through IMU-based kinematic features (p > 0.05). The main plots show individual trends for the participants’ RMS ML Sway values, and the inset shows average RMS ML Sway values before and after training for each training block. Error bars on the bar plot indicate SEM values. Participants 1 and 6 were excluded due to missing data.
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PMC9103288
|
sensors-22-03512-g008.jpg
|
0.402873 |
389cfeab861b4c39a58dccd7fb955fda
|
Flow chart of the study participants describing their participation and allocation.
|
PMC9103307
|
nutrients-14-01759-g001.jpg
|
0.427789 |
751c275d6cd74225bd1d8e88b81f197b
|
SEM micrographs of MC powder (a) ×1500 and (b) ×4000.
|
PMC9103540
|
polymers-14-01794-g001.jpg
|
0.413231 |
c2d7bc6c771f43e69047bbd3c967a82b
|
OM images of (a) LDPE/MC-0, (b) LDPE/MC-0.5, (c) LDPE/MC-1, (d) LDPE/MC-3, and (e) LDPE/MC-5.
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PMC9103540
|
polymers-14-01794-g002.jpg
|
0.455753 |
b651196ed86a43b2a6c84b8626b60c91
|
SEM micrographs of (a) LDPE/MC-0, (b) LDPE/MC-0.5, (c) LDPE/MC-1, (d) LDPE/MC-3, and (e) LDPE/MC-5.
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PMC9103540
|
polymers-14-01794-g003.jpg
|
0.532888 |
5353c6d4ef5f4c6ea8d479c17f9675ea
|
TGA thermograms of LDPE/MC composites films at various MC concentrations.
|
PMC9103540
|
polymers-14-01794-g004.jpg
|
0.486673 |
378fa512bf464680a782338c9290f8ef
|
Tensile strength and elongation at break of the LDPE/MC composite films at various MC powder concentrations.
|
PMC9103540
|
polymers-14-01794-g005.jpg
|
0.452854 |
15610830801a4c65ada85b67d0c39d42
|
FIR emission spectra of the LDPE/MC composite films at various MC powder concentrations.
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PMC9103540
|
polymers-14-01794-g006.jpg
|
0.456998 |
0bc89389021447529ade2015d615bc77
|
The oxygen transmission rate (OTR) and water vapor transmission rate (WVTR) as the barrier properties of various LDPE/MC composite films.
|
PMC9103540
|
polymers-14-01794-g007.jpg
|
0.54872 |
a10b1ce3192b4bf2a04c869aa1ae0541
|
Light transmission and opacity of various LDPE/MC composite films.
|
PMC9103540
|
polymers-14-01794-g008.jpg
|
0.446781 |
1c68f36618074e9ab96de2c7a9e2d60d
|
Photographs of lettuces packed with various LDPE/MC composite films for 3/5/7 days at 28 °C.
|
PMC9103540
|
polymers-14-01794-g009.jpg
|
0.546139 |
ce624bdbb8dc4f46add73e62c22fcd39
|
Photographs of strawberries packed with various LDPE/MC composite films for 3/5/7 days at 28 °C.
|
PMC9103540
|
polymers-14-01794-g010.jpg
|
0.423332 |
cdfc36ee2bd54ca69fd5dc1d26246ffb
|
FTIR spectra for Ex, ExAh, and ExHp. Absorption bands at 3401, 2941, 1621, 1421, 1230, 1055, 837, 620, and 580 cm−1 are indicated.
|
PMC9103907
|
polymers-14-01812-g001.jpg
|
0.52674 |
bc19349c60c54147a21bc3e5efde9488
|
NMR spectra for Ex, ExAh, and ExHp. (A) 1H-NMR of Ex, ExAh, and ExHp and (B) 13C-NMR of Ex, ExAh, and ExHp. The characteristic peaks are indicated in each graph.
|
PMC9103907
|
polymers-14-01812-g002a.jpg
|
0.612687 |
3d58428bd21f4eddb62a0e4119f0fa21
|
Effects of various concentrations of Ex, ExAh, and ExHp on cell viability, NO production, TNF-α production, IL-1β production, IL-6 production, and IL-10 production in RAW 264.7 macrophages. (A) cell viability, (B) NO production, (C) TNF-α production, (D) IL-1β production, (E) IL-6 production, and (F) IL-10 production. Values are mean ± SD (n = 3); values in the same graph with different letters (in a, b, c, d, e, f, g, h, and i) are significantly different (p < 0.05).
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PMC9103907
|
polymers-14-01812-g003a.jpg
|
0.431919 |
ccc5e49df9354826bf6b84c5aec87d94
|
Uniformly distributed-slit array coded spectral imaging system.
|
PMC9103919
|
sensors-22-03206-g001.jpg
|
0.419769 |
f97a2c94ce694aab994bbeef81093707
|
Data flow chart of the uniformly distributed-slit array coded spectral imaging system. (a) L times of a whole detector data acquisition during the movement of the uniformly distributed-slit array. (b) The L positions of the uniformly distributed-slit array corresponding to one period of detection. (c) The dispersion of the ith slit located in the aperture diaphragm. (d) A single slit moving within one sample period, taking the row distribution to obtain the full rank unit matrix M′. (e) The dispersion of the ith slit at the kth exposure measurement.
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PMC9103919
|
sensors-22-03206-g002.jpg
|
0.464075 |
3cde7c428ba244a6ba9910cc7954283c
|
Optical system of uniformly distributed-slit array coded spectral imaging system.
|
PMC9103919
|
sensors-22-03206-g003.jpg
|
0.424943 |
64737437426b4ed59c02a0bd67e5148f
|
System design model.
|
PMC9103919
|
sensors-22-03206-g004.jpg
|
0.388397 |
39bf1f8caa1a470f9fa9ceac279528c9
|
Prototype system.
|
PMC9103919
|
sensors-22-03206-g005.jpg
|
0.458702 |
2e9105e6387546deab59578f8c4e7d2d
|
System spectral calibration schematic (a) and physical diagram (b).
|
PMC9103919
|
sensors-22-03206-g006.jpg
|
0.385205 |
409e965aa1f849a5b52b43231fba539c
|
Spectral resolution test results of the hyperspectral imager. (a) For spectral channels 1–38 and (b) for spectral channels 39–60.
|
PMC9103919
|
sensors-22-03206-g007.jpg
|
0.394232 |
22489cd2c8f045e482ddcccc428df997
|
Spectral restoration image and spectral reconstruction curve.
|
PMC9103919
|
sensors-22-03206-g008.jpg
|
0.428363 |
138c1a7e0d064e2298885f4ff67af8cd
|
The 10 Hz frame rate for the spectral data recovery results of moving targets. (a–z) are the spectral data cubes acquired over a continuous period of 2.6 s. Reconstructed spectral data cubes are displayed by ENVI (The Environment for Visualizing Images).
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PMC9103919
|
sensors-22-03206-g009.jpg
|
0.455668 |
667d680062354edb9dc69389e50865ed
|
The optical flow method identifies the motion information between adjacent frames with a time difference of 0.1 s.
|
PMC9103919
|
sensors-22-03206-g010.jpg
|
0.426666 |
ef781140f30440f89c66d3f742f1198a
|
Changes to bacterial family communities.Changes to bacterial communities with different liquid supplements. The relative abundance (family) present in caecal contents collected from individual rats (n = 50) are shown. Two control groups received water with either casein diet (Casein water) or amino acid diet (AA water). Treatment groups received AA diet with either bovine milk (AA milk), soy beverage (AA soy), or almond beverage (AA almond). Diets and treatments were supplied over 4 weeks from weaning to 7 weeks old. The colours represent different families as indicated in the figure legend.
|
PMC9104089
|
peerj-10-13415-g001.jpg
|
0.504434 |
af39b073930d46efb004efe20f216a64
|
Relative abundance (%) of Actinobacteria for the five groups.Two control groups received water with either casein diet (Casein water) or amino acid diet (AA water). Treatment groups received AA diet with either bovine milk (AA milk), soy beverage (AA soy), or almond beverage (AA almond). Differences between individual taxa among the different treatments were assessed for significance using permutation analysis of variance. Dissimilar letters denote significant differences (P < 0.05). Midline shows median, the upper and lower limits of the box showing the third and first quartile (i.e., 75th and 25th percentile), respectively and the whiskers represent 1.5 times the interquartile range. Open circles represent outliers (i.e., >1.5 × IQR). n = 10 per group.
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PMC9104089
|
peerj-10-13415-g002.jpg
|
0.456409 |
25d840222238473793a0b548a1ce94e4
|
Relative abundance (%) of Bacteriodetes in the five groups.Two control groups received water with either casein diet (Casein water) or amino acid diet (AA water). Treatment groups received AA diet with either bovine milk (AA milk), soy beverage (AA soy), or almond beverage (AA almond). Differences between individual taxa among the different treatments were assessed for significance using permutation analysis of variance. Dissimilar letters denote significant differences (P < 0.05). Midline shows median, the upper and lower limits of the box showing the third and first quartile (i.e., 75th and 25th percentile), respectively and the whiskers represent 1.5 times the interquartile range. Open circles represent outliers (i.e., >1.5 × IQR) n = 10 per group.
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PMC9104089
|
peerj-10-13415-g003.jpg
|
0.526487 |
fc1af63598524b5bad645fb002bc5df5
|
Relative abundance (%) of Firmicutes in the five groups.Two control groups received water with either casein diet (Casein water) or amino acid diet (AA water). Treatment groups received AA diet with either bovine milk (AA milk), soy beverage (AA soy), or almond beverage (AA almond). Differences between individual taxa among the different treatments were assessed for significance using permutation analysis of variance. Dissimilar letters denote significant differences (P < 0.05). Midline shows median, the upper and lower limits of the box showing the third and first quartile (i.e., 75th and 25th percentile), respectively and the whiskers represent 1.5 times the interquartile range. Open circles represent outliers (i.e., >1.5 × IQR) n = 10 per group.
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PMC9104089
|
peerj-10-13415-g004.jpg
|
0.431263 |
c62e1b28f8384864977988bcbca8f727
|
Relative abundance (%) of Proteobacteria in the five groups.Two control groups received water with either casein diet (Casein water) or amino acid diet (AA water). Treatment groups received AA diet with either bovine milk (AA milk), soy beverage (AA soy), or almond beverage (AA almond). Differences between individual taxa among the different treatments were assessed for significance using permutation analysis of variance. Dissimilar letters denote significant differences (P < 0.05). Midline shows median, the upper and lower limits of the box showing the third and first quartile (i.e., 75th and 25th percentile), respectively and the whiskers represent 1.5 times the interquartile range. Open circles represent outliers (i.e., >1.5 × IQR). n = 10 per group.
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PMC9104089
|
peerj-10-13415-g005.jpg
|
0.419248 |
7ba632fd26204f60b1afb5ef705ef695
|
Overview of RNA crosslink-ligation experiments and analysis pipeline. (A) Outline of a typical crosslink-ligation experiment leading to FASTQ output files. The proximity ligation of crosslinked duplexes can produce both forward and backward arrangements. Circularized RNAs are rare and lost during library preparation because they cannot be ligated to adaptors. Similarly, concurrent crosslinking at multiple locations and subsequent ligation of them produce multigapped reads (gapm in panel B). (B) Several different types of crosslinking methods, such as psoralen, UV, and formaldehyde, together with proximity ligation produces noncontinuous reads that can be used to determine RNA structures. Newly developed computational tools and optimized parameters are listed on the right in nine steps (steps 1–9). Sequencing data that include both continuous and noncontinuous reads are demultiplexed, and the adapter/primer sequences are removed using published tools, for example, FASTX and Trimmomatic (step 1). The processed reads are mapped to genome references using optimized STAR parameters (permissive parameters, step 2). After the first round of STAR mapping, continuous alignments with softclips (indicating unmapped segments) are rearranged for a second round of STAR mapping (step 3). All alignments from the two rounds of STAR mapping are combined and filtered based on the gap penalty and a database of gapped alignments with longer segments, and then classified into six alignment types, including continuous (cont.sam in SAM format), one-gap (gap1), multigap (gapm), trans interactions (trans), homotypic interactions (homodimers, or homo), and miscellaneous bad alignments (bad) (step 4, using the gaptypes.py script) (see details in Fig. 3A–D; Supplemental Fig. S4). Data quality is checked using seglendist.py and gaplendist.py scripts, which calculate segment and gap length distributions (step 5). After removal of splicing events and reverse transcription artifacts, for example, short 1- to 2-nt gaps (step 6, using gapfilter.py), each of these alignment types is further processed to extract information for duplexes (step 7) (see Fig. 4 for details), high-level structures (step 8) (see Fig. 5 for details), and RNA homodimers (step 9, homo.sam) (see Fig. 6 for details). In step 7, two types of alignments, gap1filter.sam and trans.sam, are used to generate duplex groups and non-overlapping groups (DGs and NGs). In step 8, gapmfilter.sam alignments and the precomputed DGs and NGs are used to build trisegment groups (TGs). In step 9, overlapping chimeras are used to build potential homodimers. Detailed descriptions of these steps are in the Methods section and Supplemental Material.
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PMC9104705
|
968f01.jpg
|
0.454591 |
6878879fced746628f38d708e4727ec5
|
Optimization of short-read mapping from crosslink-ligation experiments. (A,B) RNA stems were extracted from the human cytoplasmic and mitochondrial ribosome and spliceosome crystal or cryo-EM structures. The following RNAs are included: 12S, 16S, 5S, 5.8S, 18S, 28S, U1, U2, U4, U6, U5, U11, U12, U4atac, and U6atac. (C) List of critical STAR parameters that are optimized to map noncontinuous reads. The default value for chimSegmentMin is unset, whereas setting this value to any positive integer triggers chimeric alignments. The recommended value of 15 is used here as the “default.” (D) Strategy for the two-round STAR mapping. After the first round of optimized STAR mapping, continuous alignments with softclips (“S” in CIGAR) are rearranged and then mapped again using the optimized STAR parameters. (E,F) Strategies for filtering alignments after STAR mapping. (E) Confident alignments: all segments or arms are uniquely mapped to the genome. Alignments with shorter segments that cannot be mapped uniquely are to be tested against confident ones. (F) Filtering method for the less confident alignments: all arms of the confident alignments are built into a database of connections between segments, in five nucleotide intervals (dots shown at the bottom). The connection database consists of reference name (RNAME), strand (STRAND), and coordinates between start and end (START, END). Then, the less confident alignments are tested against this database. (G–J) Benchmarking four mapping strategies on simulated reads for the human ACTB gene. Alignments are quantified on the following four aspects: (G) % mapped reads, that is, reads that are mappable to hg38 primary genome; (H) % correct alignments, that is, alignments with the same mapped positions and gap lengths as the simulated values, allowing 10-nt differences in positions or lengths due to ambiguities at the ends of reads; (I) Suboptimal alignments per read, defined as alignments that are not mapped to the correct locations; (J) % forward or backward chimera. In theory, both forward and backward chimera should be ∼50% (randomly assigned during simulation, so they are not precisely 50%). Here, only STAR alignments are calculated. (K) Gap1 (one gap, i.e., two segments) alignments in PARIS and hiCLIP data were recovered by various mapping methods and segment-length selections. Fractions for the highest-performing method (STAR_optimized) are set to 1. For STAR analysis, sequencing reads were mapped to the genome (hg38 primary); then alignments were filtered and classified into six categories using gaptypes.py. The gap1 alignments were filtered to remove short gaps and splicing alignments (gapfilter.py). Primary alignments were extracted from all alignments and used for analysis. For Bowtie 2 mapping, previously reported parameters (hyb and Aligater) were used. Unique alignments with deletions (D in SAM CIGAR string) were extracted and alignments were converted to join the multiple segments (bowtie2chim.py). Then, the alignments were classified using gaptypes.py. The gap1 alignments were filtered to remove short gaps and splicing alignments (gapfilter.py). The selection of alignments with both arms > 15 nt or 20 nt mimics the mapping and chaining strategy in previous studies that employ Bowtie 2 (hyb and Aligater). (L,M) Alignments in the ACTB mRNA from PARIS data in HEK cells were separated into ones where both arms (or segments) are at least 20 nt (L), or at least one arm is shorter than 20 nt (M). The inset boxes show DGs that support the same duplex regardless of segment length.
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PMC9104705
|
968f02.jpg
|
0.423095 |
357ef89331fc4027af7eaae753e67914
|
Classification and processing of alignments from crosslink-ligation experiments. (A) Types of alignments and classification after processing. This diagram presents a unified model for data from all types of crosslink-ligation experiments, and the terms are defined as follows. A read: one piece of sequence from the sequencing machine, and it may have one or multiple alignments to the reference; segment or arm: part of an alignment with no “N” in the CIGAR substring; continuous alignments: type 1, with only one segment or arm, either from non-crosslinked or crosslinked but not ligated RNA; gapped: forward arrangement, with one or more gaps, including gap1 and gapm (types 2 and some of type 8); chimeric: noncontinuous alignments similar to the definition from the STAR method, including types 3–7 and some of type 8; noncontinuous: including both gapped and chimeric alignments; homotypic: chimeric alignments where the arms overlap, suggesting RNA homodimers; trans: segments mapped to different chromosomes or strands (types 6–7 and some of type 8). In SAM files, each record describes one alignment, and it is represented by one CIGAR string. For example, a CIGAR string of “20M25N21M” (M for match, N for gap) has two segments or arms, 20 nt and 21 nt, separated by a 25-nt gap. In type 1, these two segments are from two different reads, and therefore represented by two records in SAM files (two CIGAR strings, e.g., “20M” and “21M”). Type 1 alignments are output to cont.sam. In type 2, these two segments are from the same read and therefore represented by one record in SAM files (one CIGAR string, e.g., “20M25N21M”). This alignment is either output to gap1.sam, or cont.sam if it does not pass the filtering (e.g., the gap corresponds to a splice junction). In type 3, the two segments are from the same read but still represented by two records in SAM files because they are mapped beyond the alignment window in STAR (two CIGAR strings, e.g., “20M” and “21M”). Type 3 alignments are rearranged and output to gap1.sam, or cont.sam if it does not pass the filtering. In type 4, the two segments are from the same read but mapped in reverse order and cannot be represented by one record because reverse order is not allowed in the CIGAR string (therefore represented by two records). Type 4 alignments are rearranged and output to gap1.sam, or cont.sam if it does not pass the filtering. In type 5, the two segments are from one read but overlap each other, which cannot be represented by one CIGAR string and therefore must be represented by two records in SAM files. Type 5 alignments are rearranged and output to homo.sam. In types 6 and 7, the two segments are from the same read but mapped to opposite strands of the same chromosome (type 6) or different chromosomes regardless of strand (type 7), and therefore must be represented by two records in SAM files. Type 6 and 7 alignments are output to trans.sam, or cont.sam if they do not pass filtering. In type 8, the multiple segments are from the same read but are mapped either to the same strand or to different strands or chromosomes. These arrangements are represented either by one record or multiple records in SAM files. Type 8 alignments are rearranged and output to gapm.sam, gap1.sam, or trans.sam, depending on their relative mapping locations. (B) Diagram for joining collinear distant segments into gapped alignments. The two segments are connected so that the two arms are represented by one record in SAM format, where xM and zM are the two arms, and yN is the gap. (C) Diagram for rearranging backward chimeric alignments to normal gapped alignments. The 5′ and 3′ arms are switched so that the two segments can be represented by one record in SAM format, where xM and zM are the two arms, and yN is the gap. (D) Diagram for rearranging overlapped chimera. The two arms are converted to three segments: left overhang, overlap, and right overhang. The new alignment can be represented by one record in SAM format, where y(2I1D) represents the overlapped region. (E) Classification of alignments from previously published crosslink-ligation experiments, in which the low abundance categories are magnified on the right.
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PMC9104705
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968f03.jpg
|
0.440473 |
0510902287e145f59dfeb56d4548cd93
|
Network/graph-based method for automatic assembly of duplex groups underlying RNA structures and interactions (CRSSANT). (A) Overlap and span calculation for a pair of alignments. Two alignments r1 and r2 each comprising a left and right arm (solid blue bars), share left and right overlaps ol, or, respectively, and left and right spans sl, sr, respectively. The arm start and stop positions of read/alignment i are represented by the 4-tuple (ai,l,0, ai,l,1, ai,r,0, ai,r,1). The two arms can be on the same chromosome and strand (gap1.sam), or different ones (trans.sam). (B) Diagram for network/graph-based clustering. All alignments with a single gap (gap1 and trans) are represented as a graph where each alignment is a vertex and the relative overlap ratio between the arms is the edge. Highly connected vertices cluster together forming subgraphs, corresponding to individual DGs. (C) Diagram for the DG tag information. The string after DG:Z includes the names of the two genes that the DG connects (gene1 and gene2). gene1 and gene2 are identical when the DG describes intramolecular structures or homodimers. DGID is a number based on assembly order. covfrac (coverage fraction) is defined as the number of alignments in this DG divided by the geometric mean of the coverages at the two arms. (D) Diagram for NG assembly. Non-overlapping DGs (e.g., DG1 and DG3, DG2 and DG4) are combined into NGs for visualization in genome browers like IGV. (E,F) Benchmarking CRSSANT clustering on 100 simulated DGs. All alignments map to Chr 1: 1–1000 and consist of cores 5, 10, or 15 nt (corelen = 5, 10 or 15), and random extensions on each side between 5 and 15 nt. Gaps between the two cores are at least 50 nt and at most the length of the Chr 1: 1–1000. Each DG contains between 10 and 100 alignments. The alignments were clustered using cliques or spectral algorithms. For cliques, overlap threshold to was varied between 0.1 and 0.9. For spectral clustering, to was varied between 0.1 and 0.9 when the eigenratio threshold was set at teig = 5. Alternatively, for spectral clustering, teig was varied between 1 and 10 when to was set at 0.5. The fraction of assigned alignments (out of 5335 input) was plotted in panel E. The fraction of assembled DGs (against 100 input) was plotted in panel F. (G) For each simulated DG data set and clustering parameter combination, the sensitivity and specificity of DG assembly was calculated for each of the top 100 DGs. The sensitivity of DG assembly is defined as the fraction of remaining alignments in each DG after CRSSANT assembly. The specificity is defined as the fraction of alignments from the dominant simulated DG. (H) Human U2 snRNA structure model based on previous studies. (I,J) Human HEK and mouse ES PARIS data were clustered using CRSSANT. The DGs were labeled corresponding to the secondary structure models in panel H. Alignments are grouped in IGV using the NG tag. “?” is a new duplex not in the known structure model. (K) Human HeLa SHARC data were clustered using CRSSANT, and the DGs were labeled as above. (L) The duplex SLIId is conserved from human down to yeast based on multiple sequence alignment of 208 seed sequences (Rfam: RF00004, in WebLogo format). (M) SLIId model; top strand is the 5′ arm, and the bottom is the 3′. Black letters, GUAUGA, indicate the BPRS masked by SLIId. (N) The alternative SLIII + SLIV structure models.
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PMC9104705
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968f04.jpg
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0.452786 |
93b6be665c9746e3b09fecb893ce5f03
|
Multisegment alignments support higher level structures and interactions. (A) Distributions of the numbers of arms/segments in gapm alignments. (B) Numbers of RNAs involved in each gapm alignment. Gapm alignments with three arms are shown. R1, R2, and R3 represent three different RNAs. (C) Gapm alignments with three arms indicate the coexistence of two helical regions. Sequential helices joined by gapm alignments indicate two separate stem–loops (left). Interlocked helices joined by gapm alignments indicate pseudoknots (middle). Overlapping helices joined by gapm alignments indicate triplexes. (D) Strategy to cluster gapm alignments, assuming that all TGs should be combinations of DGs. Alignments with more than two gaps are ignored for now. The DGs were produced by CRSSANT using gap1.sam and trans.sam alignments. The boundaries for each arm are the medians for the DGs. For the TGs, the merged middle arm is the redefined as boundaries of both DGs. Alignments from gapm.sam are then matched to the TGs so that each arm is overlapped. (E) Gapm alignment number distribution for TGs on the human 28S rRNA. PARIS2 HEK293 gapm alignments were assembled directly on the DGs (blue) or shuffled randomly across the 28S rRNA before assembly (red). The shuffling preserves the distances among the segments in each gapm read (i.e., the same CIGAR string). The crossing point (242, 14) indicates that the first 242 TGs each contain at least 14 gapm alignments. (F) Coverage of reads along the 28S rRNA for (1) all DGs, (2) only DGs that support the TGs, (3) TGs from original PARIS2 gapm alignments, and (4) TGs from shuffled gapm alignments. Coverage depth is indicated in the brackets. (G) For the top ranked 242 TGs either from the original gapm alignments (left) or the shuffled gapm alignments (right), the numbers of alignments (x-axis) were plotted against the geometric means of the numbers of alignments in the two DGs that support each TG (y-axis). Alignment numbers are log10-transformed before plotting and calculation of Pearson's correlation. (H) gapm alignments mapped to the human 5.8S rRNA. Top track: base-pairing secondary structure model in arc format. (I) Mapping the three segments to the secondary structure model. The three segments are color-coded in panels H,I.
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PMC9104705
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968f05.jpg
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0.385783 |
e110cdbbc07648de88a5a081be92ded9
|
Identification of potential RNA homodimers using homotypic alignments. (A) The same base-pairing interactions can mediate intramolecular stem–loops (top) and homotypic interactions between two (middle) or more (bottom) copies of the same molecule. (B) Diagram showing alignments with gapped or overlapped arms, suggesting RNA stem–loops or homodimers. (C) Coverage of five different types of alignments on U1. The overlapped part of homo alignments is shown individually at the bottom. (D) Heat map of U1 snRNA homo alignments in three data sets. (E) PARIS2 data showing overlapped regions and corresponding local stem–loop (SLII). DGs were assembled from 1000 total alignments. (F) Secondary structure of U1homo interaction, with the SLII in bold letters. (G) Secondary structure model for the SLII homodimer.
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PMC9104705
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968f06.jpg
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0.436462 |
862241222f754a2e984d4e6be2e80ca4
|
Progression-free survival in both groups. Kaplan–Meier estimates. log Rank: 0.011.
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PMC9105143
|
cancers-14-02108-g001.jpg
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