Diallyl Trisulfide, an Active Substance from Garlic, Inhibits Female Oviposition by Decreasing the Expression of the <i>OCT</i> Gene, which is Highly Expressed in the Spermathecal... by Wen-Han Yan (20539256)

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Diallyl Trisulfide, an Active Substance from Garlic, Inhibits Female Oviposition by Decreasing the Expression of the <i>OCT</i> Gene, which is Highly Expressed in the Spermathecal... by Wen-Han Yan (20539256)

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

Summary of significance levels for comparison of surgical segment ROM between different test groups. by Jia Zhu (135506)

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Analysis of the Nugent score before (T=0) and after (T=1) the use of the vaginal gel. Number of participants and respective percentages of Nugent scores before and after the intervention. A statistically significant decrease in Nugent scores was observed after the intervention (p value =0.0047). by Adriana Bittencourt Campaner (21175462)

“…Number of participants and respective percentages of Nugent scores before and after the intervention. A statistically significant decrease in Nugent scores was observed after the intervention (p value =0.0047).…”

Multiple comparison analysis of principal effects. by Hui Zhang (7197)

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National (A) Medicare prescription rates per thousand Part D enrollees and (B) Medicare spending for clozapine gradually decreased for 2015-2020. by Luke R. Cavanah (19022435)

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Decreased childhood asthma hospitalizations linked to hotter, drier climate with lower wind speed in drylands by Klézio Silva Monte (20579829)

“…<p>Climate change poses a significant threat to human health. Long-term climate effects on childhood asthma hospitalizations depend on the population’s geographic region. …”

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>…”

The impact of health knowledge and obesity status on the effectiveness of a warning label. by Yulian Ding (5984591)

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

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<i>Porphyromonas gingivalis</i> LPS pretreated by ozone ultrafine bubble water induces decreased TLR2 activation. by Mana Endo (22430706)

The effect of CWI on blood levels of (A) creatine kinase (CK); (B) CK-muscle brain (CK-MB) and (C) lactate dehydrogenase (LDH) in young healthy males. by Aneta Teległów (9570190)

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RTA408 significantly reduces RGCs loss in glaucoma. by Hongmei Qian (538647)

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PAP I point mutations lead to a decrease in pYV PCN, plasmid stability, and T3SS activity. by Katherine Schubert (5452712)

Y-27632 collaborated with BA to attenuate the increase in the integrity and decrease in the permeability of epithelial barrier injury induced by LPS in Caco2 monolayers. by Luqiong Liu (11537092)

“…(<b>B)</b> Y-27632 collaborated with BA to attenuate the effect of LPS on TEER in Caco2 cells on day 22. (<b>C</b>) Y-27632 collaborated with BA to alleviate the decrease in FD-4 flux in LPS-induced Caco2 cells on day 22. …”

Y-27632 synergized with BA to alleviate the decrease in the expression of and abnormal localization of ZO-1 and Occludin in LPS-induced Caco2 cells. by Luqiong Liu (11537092)

Everolimus decreased CD89 deposits in α1^KICD89^Tg mice. by Alexandra Cambier (22307216)

Significant inter-relationships between baseline variables and MSCC or MCS. by Harshit Arora (22008280)

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The effectiveness of a warning label on carbonated beverage consumption for consumers with different habit strengths. by Yulian Ding (5984591)

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