Data Sheet 3_Effects of aging on otolith morphology and functions in mice.xlsx by Keita Ueda (19855536)

“…Background<p>Increased fall risk caused by vestibular system impairment is a significant problem associated with aging. A vestibule is composed of linear acceleration-sensing otoliths and rotation-sensing semicircular canals. …”

Data Sheet 8_Effects of aging on otolith morphology and functions in mice.xlsx by Keita Ueda (19855536)

“…Background<p>Increased fall risk caused by vestibular system impairment is a significant problem associated with aging. A vestibule is composed of linear acceleration-sensing otoliths and rotation-sensing semicircular canals. …”

Data Sheet 1_Effects of aging on otolith morphology and functions in mice.docx by Keita Ueda (19855536)

“…Background<p>Increased fall risk caused by vestibular system impairment is a significant problem associated with aging. A vestibule is composed of linear acceleration-sensing otoliths and rotation-sensing semicircular canals. …”

The relationship between longer TV watching time and risk of cognitive impairment. by Hattapark Dejakaisaya (22238613)

Table 1_Body mass index influences Antimüllerian Hormone and inhibin B in adult males.xls by Wen Zhou (49050)

“…However, due to the low effect size of BMI/AMH, caution is needed in interpreting its clinical significance. Although we found a non-linear relationship and key thresholds between these variables, further studies with larger sample sizes are needed to confirm these findings.…”

Gender-specific incidence trends of HFMD in Guangzhou from 2013 to 2023. by Haipeng Luo (5322419)

The clinical characteristic of patients. by Hai-bo Ai (20790405)

The results of threshold effect analysis. by Hai-bo Ai (20790405)

The forest plot of subgroup analysis. by Hai-bo Ai (20790405)

Tuning curve sharpening and familiarity suppression. by Weifan Wang (4669081)

The results of curve fitting analysis. by Hai-bo Ai (20790405)

Pathological changes in lung tissue of mice exposed to continuous inhalation of CS. by Yue He (385239)

Image 2_Changes in the gut microbiome due to diarrhea in neonatal Korean indigenous calves.jpeg by Ji-Yeong Ku (20832209)

“…However, Proteobacteria increased and Bacteroidetes and Actinobacteria decreased in calves with diarrhea. In addition, calves with diarrhea showed a significant decrease in the diversity of the gut microbiome, especially for anaerobic microorganisms Faecalibacterium prausnitzii, Gemmiger formicilis, and Collinsella aerofaciens. …”

Image 1_Changes in the gut microbiome due to diarrhea in neonatal Korean indigenous calves.jpeg by Ji-Yeong Ku (20832209)

“…However, Proteobacteria increased and Bacteroidetes and Actinobacteria decreased in calves with diarrhea. In addition, calves with diarrhea showed a significant decrease in the diversity of the gut microbiome, especially for anaerobic microorganisms Faecalibacterium prausnitzii, Gemmiger formicilis, and Collinsella aerofaciens. …”

Plots summarising the fixed effect coefficient estimates from fitting the generalised linear mixed effects models to contact matrices calculated at a resolution of 10 kb. by Tze Yee Lim (22057822)

Supplementary file 1_Monitoring the dual-season hydrological dynamics of the Pong reservoir in Himachal Pradesh, India.docx by Rajesh Sarda (13162317)

“…The study employed a spatial linear trend modelling approach to identify trends in relative water depth, revealing a decreasing trend and a quantifiable reduction in the reservoir’s depth for both seasons. …”

BMI groups by SES. by Krystal Hunter (6820052)

“…For every increase in BMI, there was a decrease in the probability of PTB (OR = 0.923, 95% CI 0.915–0.931, P < 0.001). …”

BMISES_Data_Part2. by Krystal Hunter (6820052)

“…For every increase in BMI, there was a decrease in the probability of PTB (OR = 0.923, 95% CI 0.915–0.931, P < 0.001). …”

Logistic regression for LSES population. by Krystal Hunter (6820052)

“…For every increase in BMI, there was a decrease in the probability of PTB (OR = 0.923, 95% CI 0.915–0.931, P < 0.001). …”

Logistic regression for HSES population. by Krystal Hunter (6820052)

“…For every increase in BMI, there was a decrease in the probability of PTB (OR = 0.923, 95% CI 0.915–0.931, P < 0.001). …”