All data points from Fig 8. by Sara Hijazi (21656615)

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All data points from Fig 3. by Sara Hijazi (21656615)

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Comparison between juvenile and adult demyelination. by Sara Hijazi (21656615)

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Effect of AUT00201 (1 µM) on PV properties after juvenile demyelination. by Sara Hijazi (21656615)

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Effect of KV3 modulation on PV interneuron firing frequency and on autaptic release. by Sara Hijazi (21656615)

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All data points from Fig 1. by Sara Hijazi (21656615)

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Effect of AUT00201 (1 µM) on PV properties after adult demyelination. by Sara Hijazi (21656615)

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All data points from Fig 4. by Sara Hijazi (21656615)

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Juvenile demyelination impairs the maturation of PV interneurons in the PFC. by Sara Hijazi (21656615)

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All data points from Fig 9. by Sara Hijazi (21656615)

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Juvenile demyelination impairs autaptic plasticity. by Sara Hijazi (21656615)

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AUT00201 (1 µM) can rescue AP width in cuprizone mice. by Sara Hijazi (21656615)

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All data points from Fig 7. by Sara Hijazi (21656615)

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All data points from Fig 6. by Sara Hijazi (21656615)

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Adult demyelination has no effect on PV interneuron’s firing rate or failures in autaptic responses. by Sara Hijazi (21656615)

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Autapses play a crucial role in PV interneuron’s sustained firing at high frequencies. by Sara Hijazi (21656615)

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Expression of proteins significantly correlated with stereotypy severity in CD1 Mice (n = 28). by Kendall M. Coden (18516237)

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>…”

Age-standardized rates of PUD in 204 countries globally by SDI in 2021. by Wende Hao (10315597)

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Age-standardized rates of PUD globally and for 21 GBD regions by SDI, 1990–2021. by Wende Hao (10315597)

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