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large decrease » marked decrease (Expand Search), large increases (Expand Search), large degree (Expand Search)
i levels » _ levels (Expand Search), 1 levels (Expand Search), 6 levels (Expand Search)
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Deletion of murine <i>Rhoh</i> leads to de-repression of <i>Bcl-6</i> via decreased KAISO levels and accelerates a malignancy phenotype in a murine model of lymphoma
Published 2022“…The loss of Rhoh in Bcl-6<sup>Tg</sup> mice led to a more rapid disease progression. Mechanistically, we demonstrated that deletion of Rhoh in these murine lymphoma cells was associated with decreased levels of the RhoH binding partner KAISO, a dual-specific Zinc finger transcription factor, de-repression of KAISO target Bcl-6, and downregulation of the BCL-6 target Blimp-1. …”
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Foldases and holdases each decrease the level of unfolded protein.
Published 2020“…The benefit of a large spare foldase capacity can be seen from the rapid rise of the unfolded level [<i>U</i>], up 4-fold for only a 2-fold increase in unfolding load (thin black lines). …”
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(a) Molds; (b) Samples; (c)(d) Test devices.
Published 2025“…Although increasing SHMP content improved the early strength, it led to a decrease in later strength, with the maximum late strength observed at 2% SHMP. …”
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Supplementary data: In vitro amplification of whole large plasmids via transposon-mediated oriC insertion
Published 2021“…Amplification of a small plasmid contaminant in isothermal RCR.</b> The indicated amount of pRpoABCDZ was subjected into the Tn-oriC insertion reaction, followed by RCR at 30˚C for 16 h. …”
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Table 1_Association of dynamic changes in metabolic syndrome components with clinical outcomes in diffuse large B-cell lymphoma.docx
Published 2025“…High baseline high-density lipoprotein cholesterol (HDL-C) was associated with reduced progression risk (HR = 0.27, 95% CI: 0.10-0.78), while high baseline low-density lipoprotein cholesterol (LDL-C) was linked to decreased CR rate (OR = 0.65, 95% CI: 0.44-0.97) and increased progression risk (HR = 1.78, 95% CI: 1.14-2.79). …”
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Data from: Colony losses of stingless bees increase in agricultural areas, but decrease in forested areas
Published 2025“…</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>…”
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(a) Cement; (b) SHMP; (c) Water glass; (d) PG.
Published 2025“…Although increasing SHMP content improved the early strength, it led to a decrease in later strength, with the maximum late strength observed at 2% SHMP. …”
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Supplementary Material for: High-sensitivity Troponin I Measurement in a Large Contemporary Cohort: Implications for Clinical Care
Published 2025“…Male sex, higher HDL-C, higher Hgb A1c, decreasing eGFR, and increasing systolic blood pressure were significant predictors of increased hsTnI. …”
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Table 1_Cholesterol metabolic reprogramming drives the onset of DLBCL and represents a promising therapeutic target.docx
Published 2025“…</p>Methods<p>We retrospectively analyzed clinical data from 200 DLBCL patients and 185 healthy controls, focusing on lipid and lipoprotein levels, including triglycerides (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), apolipoprotein A1 (ApoA1), apolipoprotein B (ApoB), and apolipoprotein E (ApoE). …”
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