Expression of lipid biosynthetic genes is decreased with polyamine depletion. by Yazmin E. Cruz-Pulido (20285238)

Map of Pakistan with marked Punjab province. by Sumaira Sumaira (21453523)

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>…”

<b>Supporting data for manuscript</b> "<b>Voluntary locomotion induces an early and remote hemodynamic decrease in the large cerebral veins</b>" by Kira Shaw (18796168)

“…The MATLAB file 'dvpaper_tstraces_meningeal.mat' contains the individual hemodynamic traces across all included locomotion events (N=1224) where a meningeal vessel was detectable in the thin cranial window. …”

Group-level narrow- and broad-band spectral changes after hemispherotomy reveal a marked EEG slowing of the isolated cortex, robust across patients. by Michele Angelo Colombo (22446342)

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

Cinacalcet administered early in the inactive phase markedly decrease parathyroid Ki-67 index. by Søren Egstrand (10906087)

Narrow- and broad-band spectral changes after hemispherotomy in an awake representative patient, displaying marked electroencephalography (EEG) slowing of the isolated cortex. by Michele Angelo Colombo (22446342)

Tornado diagram showing the results of a one-way sensitivity analysis conducted for the scenario with vaccination. by Albertus Constantijn Sloof (20405090)

Tornado diagram showing the results of a one-way sensitivity analysis conducted for the scenario without vaccination. by Albertus Constantijn Sloof (20405090)

Mean values and 95% confidence intervals for recovery time, Average NN Interval (AVNN); Standard Deviation of NN Intervals (SDNN), Low Frequency/ High Frequency Ratio (LF/HF); and... by Robert Trybulski (10998702)

Correlation between HRV and cognitive performance variables (n = 45). by Min Wang (21070)

Survival of soft-shell clams with MarBTN compared to control clams. by Rachael M. Giersch (22331947)

“…(<i>B</i>) Analysis of long-term non-progressing clams (n = 11, light red line), along with their respective paired controls (blue line), shows no difference in survival with maintained low-level infection. (C) A sub-analysis of low-positive clams in which MarBTN progressed and did not regress (n = 9, dark red line), with survival starting at the time the clam was detected with >10% cancer, compared with their paired control clams starting at the same date (blue line), shows a significant decrease in time-to death. “+” marks the dates at which two negative control animals were culled before natural death (these events were censored in the survival analysis).…”

MarBTN-specific eDNA detection in each clam that was followed for MarBTN in hemolymph and eDNA. by Rachael M. Giersch (22331947)

“…The animal with clear regression is FFM-21A1. In a second clam (FFM-22H11), the cancer decreased but it did not survive more than 8 weeks after this drop, so under our conservative criteria, we consider it to be progression. …”

Spatiotemporal variables of sprint running (n = 22). by Shinnosuke Hase (20917896)

The comparison of the Spectral Exponent in hemispherotomy with a reference pediatric sample across wakefulness and NREM Sleep reveal values compatible with deep sleep in the isolat... by Michele Angelo Colombo (22446342)

Cells lacking Cbf11 and/or Mga2 display nutrient-responsive decrease in lipid droplet (LD) content. by Anna Marešová (14375187)

Baseline sociodemographic data and disease-related variables of two groups (n = 105). by Nan Tang (642590)

Bootstrapped spearman correlations from a randomly selected subset of male sample donor originating samples (n = 493). by Arttu Autio-Kimura (20454681)

The parameters of gas exchange markedly decreased in maize <i>zmstomagen1/2</i> mutant compared with in wild type (WT). by Juan-Juan Xu (18590868)