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)

Box plots showing baseline prevalence and mean egg count at pre-MDA1 in districts that were responders compared to those that were persistent hotspots of decreasing praziquantel ef... by Takafira Mduluza (39754)

Changes in inflammatory cytokine levels compared with baseline values in all patients over time. by Jia Song (495396)

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

Schematic representation of the experimental protocol over time. by Vanessa Wellauer (18408477)

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S2 File - Factors influencing effective decrease of controlled attenuation parameters in metabolic-associated steatotic liver disease: A multilevel linear regression analysis at Va... by Sonsawan Sangprasert (22772538)

No significant diurnal rhythmicity of short chain fatty acids in the blood was observed. by Weiran Shan (16969688)

Changes in the UACR and urinary β2-MG levels compared with baseline values over time. by Jia Song (495396)

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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>…”

Changes in the eGFRs and serum potassium levels compared with baseline values in all patients over time. by Jia Song (495396)

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Path analysis diagram illustrating the associations between alexithymia, social support, anticipated stigma and patient satisfaction, with their respective correlation coefficients... by Keya Bibikar (22386306)

Arctigenin decreased proliferation in colorectal cancer cells with no significant effect on normal cells. by Xiang-Fan Chen (13932983)

Descriptive statistics of alcohol consumption in G7 countries (in litres/capita). by Luis Alberiko Gil-Alana (14659817)

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Data for the G7 countries in 2022. by Luis Alberiko Gil-Alana (14659817)

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Estimates of the differencing parameter, d, in Eq (1). by Luis Alberiko Gil-Alana (14659817)

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Estimates of the differencing parameter, d, in Eq (1). by Luis Alberiko Gil-Alana (14659817)

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Estimated coefficients based on the selected model in Table 4. by Luis Alberiko Gil-Alana (14659817)

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Estimated coefficients based on the selected model in Table 3. by Luis Alberiko Gil-Alana (14659817)

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Pairwise comparisons of the intervention effects by time point for physiological parameters. by Vanessa Wellauer (18408477)

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Pairwise comparisons of the intervention effects by time point for recovery parameter. by Vanessa Wellauer (18408477)

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