m⁶A modification compares PK-15 cells transfected with siCtrl or siMETTL14 by MeRIP-seq. by Jing Chen (4762)

“…(B) m⁶A peaks distribution in 5’UTR, stop codon, and 3’UTR region by MeRIP-seq. …”

Table_5_Decreased Functional Connectivities of Low-Degree Level Rich Club Organization and Caudate in Post-stroke Cognitive Impairment Based on Resting-State fMRI and Radiomics Fea... by Guofu Miao (11271528)

Nucleotide sequence changes in E6, L1 (MY), and LCR regions from A1/2, D2 and D3 HPV16 variants. by Ana Alfaro (280118)

A complete set of mathematical model equations utilized in ILYCM software to develop S. <i>frugiperda</i> phenology for each life stage. by Marian Adan (16641634)

Thymus regeneration promotes naïve T-cell recovery in iMycTg aging-E mice and a partial decrease in Treg frequencies. by Abigail Morales-Sánchez (21799582)

Data_Sheet_1_Non-invasive Vagus Nerve Stimulation for COVID-19: Results From a Randomized Controlled Trial (SAVIOR I).docx by Carlos Tornero (9946163)

“…C-reactive protein (CRP) levels decreased from baseline to a significantly greater degree in the nVNS group than in the SoC group at day 5 and overall (i.e., all postbaseline data points collected through day 5, combined). …”

Data Sheet 3_Global, regional, and national epilepsy of unknown cause incidence and mortality, 1990–2036: cross-national health inequalities and predictive analytics.pdf by Lijun Wang (176511)

“…We excluded countries or regions with a total number of age-group cases <5 (42 cases in total) because of potential problems with the sparsity of age-group data in countries with very small populations, resulting in the non-convergence of the BAPC model.…”

Data Sheet 4_Global, regional, and national epilepsy of unknown cause incidence and mortality, 1990–2036: cross-national health inequalities and predictive analytics.pdf by Lijun Wang (176511)

“…We excluded countries or regions with a total number of age-group cases <5 (42 cases in total) because of potential problems with the sparsity of age-group data in countries with very small populations, resulting in the non-convergence of the BAPC model.…”

Table 4_Global, regional, and national epilepsy of unknown cause incidence and mortality, 1990–2036: cross-national health inequalities and predictive analytics.xlsx by Lijun Wang (176511)

“…We excluded countries or regions with a total number of age-group cases <5 (42 cases in total) because of potential problems with the sparsity of age-group data in countries with very small populations, resulting in the non-convergence of the BAPC model.…”

Data Sheet 1_Global, regional, and national epilepsy of unknown cause incidence and mortality, 1990–2036: cross-national health inequalities and predictive analytics.pdf by Lijun Wang (176511)

“…We excluded countries or regions with a total number of age-group cases <5 (42 cases in total) because of potential problems with the sparsity of age-group data in countries with very small populations, resulting in the non-convergence of the BAPC model.…”

Table 2_Global, regional, and national epilepsy of unknown cause incidence and mortality, 1990–2036: cross-national health inequalities and predictive analytics.xlsx by Lijun Wang (176511)

“…We excluded countries or regions with a total number of age-group cases <5 (42 cases in total) because of potential problems with the sparsity of age-group data in countries with very small populations, resulting in the non-convergence of the BAPC model.…”

Data Sheet 2_Global, regional, and national epilepsy of unknown cause incidence and mortality, 1990–2036: cross-national health inequalities and predictive analytics.pdf by Lijun Wang (176511)

“…We excluded countries or regions with a total number of age-group cases <5 (42 cases in total) because of potential problems with the sparsity of age-group data in countries with very small populations, resulting in the non-convergence of the BAPC model.…”

Table 3_Global, regional, and national epilepsy of unknown cause incidence and mortality, 1990–2036: cross-national health inequalities and predictive analytics.xlsx by Lijun Wang (176511)

“…We excluded countries or regions with a total number of age-group cases <5 (42 cases in total) because of potential problems with the sparsity of age-group data in countries with very small populations, resulting in the non-convergence of the BAPC model.…”

Table 1_Global, regional, and national epilepsy of unknown cause incidence and mortality, 1990–2036: cross-national health inequalities and predictive analytics.xlsx by Lijun Wang (176511)

“…We excluded countries or regions with a total number of age-group cases <5 (42 cases in total) because of potential problems with the sparsity of age-group data in countries with very small populations, resulting in the non-convergence of the BAPC model.…”

Growth of cell monolayers and 3D spheroids under different serum concentration in growth media. by Sreerupa Sarkar (9628788)

ApoE, MMP-9, Claudin-5, and Occludin Protein Expression. by Lu Xu (386491)

Intestinal Intraepithelial Lymphocyte Cytometric Pattern Is More Accurate than Subepithelial Deposits of Anti-Tissue Transglutaminase IgA for the Diagnosis of Celiac Disease in Lym... by Fernando Fernández-Bañares (596205)

“…<div><p>Background & Aims</p><p>An increase in CD3+TCRγδ+ and a decrease in CD3− intraepithelial lymphocytes (IEL) is a characteristic flow cytometric pattern of celiac disease (CD) with atrophy. …”

A flowchart describes the stepwise analysis of missense SNPs in the human PC and illustrates the computational tools used in the study. by Mahvash Farajzadeh-Dehkordi (17468232)

Forest plots comparing demographic factors within SARS-CoV-2 variant waves. by Rebecca M. Cantu (19787070)

DataSheet_5_RNA Demethylase ALKBH5 Prevents Lung Cancer Progression by Regulating EMT and Stemness via Regulating p53.zip by Xiangli Liu (507857)

“…Knockdown of ALKBH5 increased global m⁶A level, and also increased E-cadherin, decreased stem hallmarkers, Nanog and Oct4, and inhibited stemness of CSCs. …”