Table 1_Distinct lipidomic profiles but similar improvements in aerobic capacity following sprint interval training versus moderate-intensity continuous training in male adolescent... by Wantang Su (15442988)

“…</p>Results<p>VO₂peak significantly improved from 39.05 ± 8.17 to 47.52 ± 8.51 [F (1, 44) = 14.75, p < 0.05] for MICT and from 40.13 ± 6.37 to 48.42 ± 7.01 [F (1, 44) = 14.75, p < 0.05] for SIT. …”

PPFIA4 Knockdown Suppresses Expression, Proliferation, and Migration in Colorectal Cancer Cells. by Wenliang Yuan (7842908)

Supplementary file 2_Quantile regression application to identify key determinants of malnutrition in five West African countries of Gabon, Gambia, Liberia, Mauritania, and Nigeria.... by Reshav Beni (21422981)

“…</p>Method<p>This study employed a quantile regression model to examine the determinants of malnutrition at various quantiles of interest across the Western African countries under consideration to facilitate focused policy measures and intervention strategies aimed at decreasing the prevalence.</p>Results<p>For the lower quantiles (0.1 and 0.25), which indicate severe malnutrition, significant variables included the child’s weight [quantile = 0.1, 95% CI(0.0063, 0.0103), quantile = 0.25, 95% CI(0.0054, 0.0107)], mother’s education level [No education: quantile = 0.1, 95% CI(−49.7471, −32.1376), quantile = 0.25, 95% CI(−38.1513, −22.4438) Primary: quantile = 0.1, 95% CI(−24.8095, −5.7693), quantile = 0.25, 95% CI(−19.5273, −6.3424) Higher: quantile = 0.1, 95% CI(5.6499, 40.3274), quantile = 0.25, 95% CI(21.8158, 40.278)], drinking water source [Natural Sources: quantile = 0.1, 95% CI(0.6877, 24.384),Piped: quantile = 0.1, 95% CI(25.578, 45.2368), quantile = 0.25, 95% CI(22.2782, 34.8212), Bottle/Sachet: quantile = 0.25, 95% CI(3.438, 98.1675)], toilet type [Flush: quantile = 0.25, 95% CI(2.2598, 18.3457),Other: quantile = 0.1, 95% CI(8.7863, 24.504), quantile = 0.25, 95% CI(7.0995, 20.1119)], household wealth index [Poorest: quantile = 0.1, 95% CI(−52.5112, −16.9197), quantile = 0.25, 95% CI(−48.3804, −23.0633),Poorer: quantile = 0.1, 95% CI(−38.8744, −4.7586), quantile = 0.25, 95% CI(−34.6993, −9.1766), Middle: quantile = 0.25, 95% CI(−28.9491, −6.5834)], health care visits [No: quantile = 0.1, 95% CI(−19.293, −3.6393), quantile = 0.25, 95% CI(−17.2342, −5.6411)], consumption of fortified foods and tubers [No: quantile = 0.1, 95% CI(−36.3898, −12.0378), quantile = 0.25, 95% CI(−17.8127, −1.2374)], anemia status [Anemic: quantile = 0.1, 95% CI(−15.9326, −1.1929), quantile = 0.25, 95% CI(−12.3361, −1.5516)], mosquito net usage [No: quantile = 0.1, 95% CI(−22.0323, −0.8033), quantile = 0.25, 95% CI(−13.8107, 1.1366)], child’s age [0 to 12 months: quantile = 0.1, 95% CI(81.6424, 105.7155), quantile = 0.25, 95% CI(61.4817, 78.5194),12 to 24 months: quantile = 0.1, 95% CI(0.5592, 24.933), 24 to 36 months: quantile = 0.1, 95% CI(7.9128, 40.2828)] and gender [Female: quantile = 0.1, 95% CI(4.5351, 17.9783), quantile = 0.25, 95% CI(5.0076, 15.4735)], and recent fever [No: quantile = 0.1, 95% CI(11.5663, 29.5984), quantile = 0.25, 95% CI(7.0313, 20.8918)]. …”

Supplementary file 1_Quantile regression application to identify key determinants of malnutrition in five West African countries of Gabon, Gambia, Liberia, Mauritania, and Nigeria.... by Reshav Beni (21422981)

“…</p>Method<p>This study employed a quantile regression model to examine the determinants of malnutrition at various quantiles of interest across the Western African countries under consideration to facilitate focused policy measures and intervention strategies aimed at decreasing the prevalence.</p>Results<p>For the lower quantiles (0.1 and 0.25), which indicate severe malnutrition, significant variables included the child’s weight [quantile = 0.1, 95% CI(0.0063, 0.0103), quantile = 0.25, 95% CI(0.0054, 0.0107)], mother’s education level [No education: quantile = 0.1, 95% CI(−49.7471, −32.1376), quantile = 0.25, 95% CI(−38.1513, −22.4438) Primary: quantile = 0.1, 95% CI(−24.8095, −5.7693), quantile = 0.25, 95% CI(−19.5273, −6.3424) Higher: quantile = 0.1, 95% CI(5.6499, 40.3274), quantile = 0.25, 95% CI(21.8158, 40.278)], drinking water source [Natural Sources: quantile = 0.1, 95% CI(0.6877, 24.384),Piped: quantile = 0.1, 95% CI(25.578, 45.2368), quantile = 0.25, 95% CI(22.2782, 34.8212), Bottle/Sachet: quantile = 0.25, 95% CI(3.438, 98.1675)], toilet type [Flush: quantile = 0.25, 95% CI(2.2598, 18.3457),Other: quantile = 0.1, 95% CI(8.7863, 24.504), quantile = 0.25, 95% CI(7.0995, 20.1119)], household wealth index [Poorest: quantile = 0.1, 95% CI(−52.5112, −16.9197), quantile = 0.25, 95% CI(−48.3804, −23.0633),Poorer: quantile = 0.1, 95% CI(−38.8744, −4.7586), quantile = 0.25, 95% CI(−34.6993, −9.1766), Middle: quantile = 0.25, 95% CI(−28.9491, −6.5834)], health care visits [No: quantile = 0.1, 95% CI(−19.293, −3.6393), quantile = 0.25, 95% CI(−17.2342, −5.6411)], consumption of fortified foods and tubers [No: quantile = 0.1, 95% CI(−36.3898, −12.0378), quantile = 0.25, 95% CI(−17.8127, −1.2374)], anemia status [Anemic: quantile = 0.1, 95% CI(−15.9326, −1.1929), quantile = 0.25, 95% CI(−12.3361, −1.5516)], mosquito net usage [No: quantile = 0.1, 95% CI(−22.0323, −0.8033), quantile = 0.25, 95% CI(−13.8107, 1.1366)], child’s age [0 to 12 months: quantile = 0.1, 95% CI(81.6424, 105.7155), quantile = 0.25, 95% CI(61.4817, 78.5194),12 to 24 months: quantile = 0.1, 95% CI(0.5592, 24.933), 24 to 36 months: quantile = 0.1, 95% CI(7.9128, 40.2828)] and gender [Female: quantile = 0.1, 95% CI(4.5351, 17.9783), quantile = 0.25, 95% CI(5.0076, 15.4735)], and recent fever [No: quantile = 0.1, 95% CI(11.5663, 29.5984), quantile = 0.25, 95% CI(7.0313, 20.8918)]. …”

Shift in the Microbial Community Composition in Lake Wetland Sediments in the Source Region of the Yellow River Linked to Environmental Factors by Hexing Qi (20730615)

“…Meanwhile, the abundance of the fungal phylum Rozellomycota decreased (17.6–3.0%) as the elevation increased. The redundancy analysis suggested that the structures of the bacterial and fungal communities were influenced by environmental factors including elevation, organic matter content, hydrolyzed nitrogen, total phosphorus, total potassium, and pH. …”

Supplementary Material for: Exploring associations between cannabis prices, stores, and usage after recreational legalization by figshare admin karger (2628495)

Over-expression of Fas2 in the wing imaginal disc causes an EGFR-dependent reduction in organ size. by Luis Garcia-Alonso (152388)

Data Sheet 1_Characteristics of gut microbiota in Penaeus vannamei shifted with elevated salinity.docx by Bo Wang (86769)

Table 1_Urinary and oral microbiota in Polish women: a pilot case-control study of breast cancer.docx by Anna Marciniak (12354534)

“…</p>Results<p>BC case urine microbiota contained an increased abundance of Corynebacterium (5.2-fold, but not significant) and Gammaproteobacteria including unknown genus and Pseudomonas (1.7- and 1.8-fold) and decreased abundance of Family XI (0.3-fold) and Bifidobacteriaceae (0.4-fold) compared to HCs. …”

Supplementary file 1_The efficacy and safety of endoscopic surgery combined with platelet-rich plasma for lumbar disk herniation: a systematic review and meta-analysis.pdf by Guimei Guo (4127074)

“…For back pain, VAS scores decreased significantly at 3 months (MD = −0.58, 95% CI: −0.84 to −0.31, p < 0.0001), 6 months (MD = −0.32, 95% CI: −0.48 to −0.16, p = 0.0001), ≥12 months (MD = −0.40, 95% CI: −0.51 to −0.28, p < 0.00001) and at last follow-up (MD = −0.23, 95% CI: −0.36 to −0.10, p = 0.0005; very low certainty). …”

Data Sheet 1_Burn inhalation injury and intubation with dexamethasone-eluting endotracheal tubes modulate local microbiome and alter airway inflammation.xlsx by Gabriela Gonzales (19756103)

Results for the EPIC bowel subscale and the EORTC QLQ PR25 bowel symptoms scale. by John N. Staffurth (20636565)

Discriminatory learning preferentially enhances reward associated input. by Rahul Garg (3064578)

Table 1_Burn inhalation injury and intubation with dexamethasone-eluting endotracheal tubes modulate local microbiome and alter airway inflammation.xlsx by Gabriela Gonzales (19756103)

Video 1_The contribution of personalized video feedback to robotic partial nephrectomy training in realistic 3D tumor kidney models: design, production and implementation.mp4 by Ahmet Furkan Sarıkaya (21731246)

Differences between patients and controls. by Jolanda Malamud (19727472)

Photomicrograph of the gastric mucosa colored with an anti-caspase-3 antibody. by Rehab F. Taher (20478600)

Data Sheet 1_Invasive treatment strategy for older patients with non-ST-elevation acute coronary syndrome: a systematic review and meta-analysis of randomized controlled trials.pdf by Vaibhav Vats (18702889)

“…Invasive management significantly decreased the risk of MI (RR 0.70, 95% CI: 0.55, 0.89) and revascularization (RR 0.29, 95% CI: 0.21, 0.40). …”

Efficient Optimization of Plasma Radiation Detector Configurations using Imperfect Inference Models by Difan Song (15209755)

Initial transport rate of [³H]-hypoxanthine of PhZ mutants (V%). by Mariana Barraco-Vega (19996318)