<b>Addition root exudates increase microbial biomass but decreases diversity and richness.</b> by Xiaochong Zhang (21179348)

Data Sheet 1_Decreased neuronal excitability in hypertriglyceridemia hamsters with acute seizures.docx by Qiuyue Shen (20373266)

“…Following seizure induction, free palmitic acid levels in the frontal cortex dialysate significantly decreased, while the expression of palmitoyl acyltransferase 14 (ZDHHC14) in the frontal cortex tissue was higher in Apoc2^−/− hamsters than in wild-type hamsters. …”

Brain regions with significantly decreased activations for the Raven task are shown in blue. by Morteza Fattahi (15892028)

(Related to Fig 6): NPF in LNd and NPFR in LPN are not required to high-temperature-induced evening sleep decrease. by Xin Yuan (174619)

nsP4-C483Y or Q192L mutations decrease sensitivity to 4′-FlU. by Peiqi Yin (6533747)

Percent Decrease in FGM between Oldest (45-49 years) and Youngest (15-19 years) Cohorts of Women over the years in Egypt. by Shatha Elnakib (8901764)

Training-induced changes in bipedal stance. by Cristina Dolciotti (16317330)

Subjects:

Suggestive significant associations in the candidate gene approach. by Dai Nogimura (21445649)

Subjects:

Decreased synthesis of VCAM-1, tubulin and dynein proteins in the heart of mice stimulated with EVs (green) or ICs (blue). by Alberto Cornet-Gomez (10676133)

“…The values represent the mean ± SEM, with significance set at p < 0.05 (*).</p>…”

Summary of significant treatment × time effect. by Wensheng Xiao (16557866)

Intracellular retention, but not shedding of NKp65 molecules containing threonine at amino acid position 131 causes decreased surface expression. by Julian Leonard Lino Heller (22049674)

Inhibition of LDHA leads to decreased ATP, reduced AKT phosphorylation, and enhanced chemotherapy sensitivity to LBP in A549 and NCL-H1975 cells. by Siyu Yuan (7425719)

Subjects:

Introgression decreases allelic shuffling. by Enrique J. Schwarzkopf (6579275)

Image 1_Chromosome 1 variants associated with decreased HIV set-point viral load correlate with PRKAB2 expression changes.png by Riley H. Tough (14432838)

Supplementary Material for: Longitudinal Decrease in Left Ventricular Size with Age: Impact on Mortality and Cardiovascular Hospitalization by figshare admin karger (2628495)

“…Results: A decrease in LVEDD was observed in 24% of participants (mean change -9±3 mm) and was significantly associated with older age, female sex, decreased volumes, concentric remodeling and diastolic dysfunction. …”

Summary of post-treatment CAPS score changes from MDMA-AT publications. by Filip Stanicic (17808254)

Subjects:

Comparison of knowledge retention among different socio-demographic factors using independent t-test (n = 422). by Chikondi Maluwa (20660522)

Subjects:

Data from: Colony losses of stingless bees increase in agricultural areas, but decrease in forested areas by Malena Sibaja Leyton (18400983)

“…</p><p><br></p><p dir="ltr">#METADATA</p><p dir="ltr">#'data.frame': 472 obs. of 28 variables:</p><p dir="ltr"> #$ ID: Factor variable; a unique identity for the response to the survey</p><p dir="ltr"> #$ Year: Factor variable; six factors available (2016, 2017, 2018, 2019, 2020, 2021) representing the year for the response to the survey</p><p dir="ltr"> #$ N_dead_annual: Numeric variable; representing the number of colonies annually lost</p><p dir="ltr">#$ N_alive_annual: Numeric variable; representing the number of colonies annually alive</p><p dir="ltr"> #$ N_dead_dry: Numeric variable; representing the number of colonies lost during the dry season</p><p dir="ltr">#$ N_alive_dry: Numeric variable; representing the number of colonies alive during the dry season</p><p dir="ltr"> #$ N_dead_rainy: Numeric variable; representing the number of colonies lost during the rainy season</p><p dir="ltr">#$ N_alive_rainy: Numeric variable; representing the number of colonies alive during the rainy season</p><p dir="ltr"> #$ Education: Factor variable; four factors are available ("Self-taught","Learned from another melip","Intro training","Formal tech training"), representing the training level in meliponiculture</p><p dir="ltr"> #$ Operation_Size: Numeric variable; representing the number of colonies managed by the participant (in n)</p><p dir="ltr"> #$ propAgri: Numeric variable; representing the percentage of agricultural area surrounding the meliponary (in %)</p><p dir="ltr"> #$ propForest: Numeric variable; representing the percentage of forested area surrounding the meliponary (in %)</p><p dir="ltr">#$ temp.avg_annual: Numeric variable; representing the average annual temperature (in ºC)</p><p dir="ltr">#$ precip_annual_sum: Numeric variable; representing the total accumulated precipitation (in mm)</p><p dir="ltr">#$ precip_Oct_March_sum: Numeric variable; representing the total accumulated precipitation between October to March (in mm)</p><p dir="ltr">#$ precip_Apri_Sept_sum: Numeric variable; representing the total accumulated precipitation between April to September (in mm)</p><p dir="ltr">#$ temp.avg_Oct_March: Numeric variable; representing the total accumulated precipitation between October to March (in ºC)</p><p dir="ltr">#$ temp.avg_Apri_Sept: Numeric variable; representing the total accumulated precipitation between April to September (in ºC)</p><p dir="ltr"> #$ Importance_dead: Factor variable; three factors are available Normal","High","Very high"), representing the perception of the significance of annual colony losses</p><p dir="ltr"> #$ Climatic_environmental: Binary variable; representing if the participant considered climatic and environmental problems as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr"> #$ Contamination: Binary variable; representing if the participant considered contamination problems as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr"> #$ Nutritional: Binary variable; representing if the participant considered nutritional problems as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr">#$ Sanitary: Binary variable; representing if the participant considered sanitary problems as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr">#$ Queen: Binary variable; representing if the participant considered queen problems as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr">#$ Time: Binary variable; representing if the participant considered time problems as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr">#$ Economic: Binary variable; representing if the participant considered economic problems as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr">#$ Attacks: Binary variable; representing if the participant considered time attacks as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr">#$ Swarming: Binary variable; representing if the participant considered swarming problems as a potential driver (1) or not (0) of their annual colony losses</p><p><br></p>…”

Correlations between significantly different microbiota and metabolites. by Bhuripit Saraphol (20855573)

Subjects:

Correlation between protein abundances and R_5-20 z-score among cases at baseline. Protein abundances, normalized to mean 0 and variance 1, are displayed on the y-axis. (... by Spela Kokelj (8356644)

Subjects: