Mendeley Data Showcase

This work demonstrates a rapid and responsive pipeline for T-cell-specific multi-target vaccine development that leverages epitope identification, protein folding, and docking to render a collection of viral proteomes into a ranked list of peptide candidates scored for immunogenicity, allele coverage, solubility, and epitope stability in cleavage and processing. After epitope reactiveness was evaluated by microarrays, molecular dynamics simulations were used to assess the epitope's correct binding to the target host MHC. Finally, flow cytometry evaluated T-cell antigen-specific immunogenicity on mice and human peripheral blood mononuclear cells (PBMCs). Most final epitopes could elicit strong T-cell activation with the secretion of IFN-ɣ, TNF-α, or IL-2 – varying by host species and HLA allele. Final candidates were selected by overall scores in a string-of-beads design. This furthers the specific aim of developing vaccines for alphaviruses and the general aim of establishing efficient and tunable processes for vaccine development in a global setting. Data here was organized by the figure panel on the original manuscript to allow straightforward interpretation. Each folder contains the raw data for each independent experiment and the analysis datasheet for the human PBMC experiments presented in the manuscript, including the original workspace on the statistical software used for data plot. Each folder also contains a plate map or sample ID to allow interpretation of the raw data.

This work demonstrates a rapid and responsive pipeline for T-cell-specific multi-target vaccine development that leverages epitope identification, protein folding, and docking to render a collection of viral proteomes into a ranked list of peptide candidates scored for immunogenicity, allele coverage, solubility, and epitope stability in cleavage and processing. After epitope reactiveness was evaluated by microarrays, molecular dynamics simulations were used to assess the epitope's correct binding to the target host MHC. Finally, flow cytometry evaluated T-cell antigen-specific immunogenicity on mice and human peripheral blood mononuclear cells (PBMCs). Most final epitopes could elicit strong T-cell activation with the secretion of IFN-ɣ, TNF-α, or IL-2 – varying by host species and HLA allele. Final candidates were selected by overall scores in a string-of-beads design. This furthers the specific aim of developing vaccines for alphaviruses and the general aim of establishing efficient and tunable processes for vaccine development in a global setting. Data here was organized by the figure panel on the original manuscript to allow straightforward interpretation. Each folder contains the raw data and the analysis datasheet for the alphavirus pre-exposed (vaccinees) human PBMC experiments presented in the manuscript, including the original workspace on the statistical software used for data plot. Each folder also contains a plate map or sample ID to allow interpretation of the raw data.

This work demonstrates a rapid and responsive pipeline for T-cell-specific multi-target vaccine development that leverages epitope identification, protein folding, and docking to render a collection of viral proteomes into a ranked list of peptide candidates scored for immunogenicity, allele coverage, solubility, and epitope stability in cleavage and processing. After epitope reactiveness was evaluated by microarrays, molecular dynamics simulations were used to assess the epitope's correct binding to the target host MHC. Finally, flow cytometry evaluated T-cell antigen-specific immunogenicity on mice and human peripheral blood mononuclear cells (PBMCs). Most final epitopes could elicit strong T-cell activation with the secretion of IFN-ɣ, TNF-α, or IL-2 – varying by host species and HLA allele. Final candidates were selected by overall scores in a string-of-beads design. This furthers the specific aim of developing vaccines for alphaviruses and the general aim of establishing efficient and tunable processes for vaccine development in a global setting. Data here was organized by the figure panel on the original manuscript to allow straightforward interpretation. Each folder contains the raw data and the analysis datasheet for serology and mouse experiments, including the original workspace on the statistical software used for data plots. Each folder also contains a plate map or sample ID to allow interpretation of the raw data.

Height, diameter and age of sampled trees affected by snow avalanches in Piatra Craiului Mountains (Southern Carpathians).

These data were generated by a full-wave model that has been referenced in the paper. Data are saved in text format in various files which are listed in the readme document. The columns of data used in the figures are provided in the readme document. The figures (below) based on data (also below) are published in Journal of Geophysical Research: Atmospheres, in our paper The Dynamics and Energetics of Fast Waves from the Earth's Surface to the Lower Thermosphere.

Mutations in UMOD, encoding uromodulin, lead to Autosomal Dominant Tubulointerstitial Kidney Disease (ADTKD), a genetic cause of kidney failure. UMOD mutations have a common gain-of-toxic-function effect, causing mutant uromodulin retention in the endoplasmic reticulum (ER). This leads to ER stress, alteration of protein homeostasis and mitochondrial dynamics, defective autophagy and increased cell death. Calorie restriction exerts a beneficial role in diseases characterized by accumulation of pathogenic protein and inflammation, by modulating several pathways, including autophagy induction and suppression of inflammation and fibrosis. Given the relevance of these features in ADTKD, we investigated the effect of calorie restriction on disease onset and progression. Transgenic mice expressing C147W uromodulin (TgUmodC147W) were subjected to a moderate (30%) calorie restriction regimen for 15 or 24 weeks, starting at different stages of disease progression. Calorie restriction restored autophagy, as shown by decreased P62 punctae and quenched mTOR activation specifically in mutant uromodulin expressing cells, and it recovered expression of key ER-phagy receptor genes, with a concomitant, striking reduction of mutant uromodulin ER retention. In pre-symptomatic TgUmodC147W mice, calorie restriction alleviated epithelial cell stress. This, likely along with a direct anti-inflammatory effect of calorie restriction, prevented inflammation and progressive decline of kidney function. At this early disease stage, calorie restriction ameliorated the already established kidney damage and reduced fibrosis, suggesting reversal of ADTKD phenotype. Calorie restriction was also effective in significantly delaying disease progression in TgUmodC147W mice with advanced disease and already compromised kidney function. Calorie restriction enhanced autophagy and uromodulin degradation, counteracting the primary effect of UMOD mutations, and significantly ameliorated kidney disease onset and progression. Complete data files relative to the manuscript "Cratere MG, Perrone B, Canciani B, Schaeffer C, Rampoldi L. Calorie Restriction Leads to Degradation of Mutant Uromodulin and Ameliorates Inflammation and Fibrosis in UMOD-Related Kidney Disease. J Am Soc Nephrol. 2026 Feb 3. doi: 10.1681/ASN.0000001032. Epub ahead of print. PMID: 41632531".

Data associated with the manuscript "Petrogenesis of Permian A-type and I-type felsic rocks in the southern Beishan Orogenic Collage and geodynamic implications"

Abstract Teachers' leadership style is a critical determinant of instructional effectiveness, particularly in English as a Foreign Language (EFL) contexts where student engagement is essential. This study aims to identify the dominant leadership styles applied by English teachers and to evaluate the level and characteristics of students' learning motivation in junior high schools on Bangka Island. Employing a quantitative survey design, data were collected from 20 English teachers and 20 seventh-grade students. The Leader Behavior Description Questionnaire (LBDQ) and a multi-dimensional motivation scale were utilized. Data analysis involved descriptive statistics and mapping into the Ohio State leadership quadrants. Findings reveal that teachers predominantly exhibit a "High Initiating Structure and High Consideration" style (Quadrant III), indicating an effective balance between task-oriented and relationship-oriented behaviors. Students' motivation was generally high, driven by strong internal factors such as sense of agency (84%) and need for action (76%). However, external support from "significant others" showed significant variability. The study suggests that teacher leadership is not a fixed trait but a situational capability to synchronize instructional structure with students' psychological needs, thereby fostering an optimal EFL learning environment. Keywords: Teacher leadership style, Learning motivation, English Foreign Language (EFL), Ohio State Model, Junior high school

The data that support the findings of this study were derived from the following resources available in the public domain: Precipitation: https://www.scidb.cn/en/file?fid=62386fd82032a703ca4c3697&mode=front; Snowmelt: https://www.ncdc.ac.cn/portal/metadata/22711754-dbff-439d-a0e5-afb3d4cdad74; Soil moisture: https://cds.climate.copernicus.eu/datasets/reanalysis-era5-land-monthly-means?tab=overview; NDVI: https://zenodo.org/records/8253971.

This study introduces a self-constructed loofah pest and disease dataset comprising 2,929 images collected from real agricultural environments in Guangdong, China. The dataset covers five distinct categories: Downy Mildew (475 images), Diaphania Indica (550 images), Healthy Loofah (732 images), Liromyza (496 images), and Needle Peak (676 images). Collected under diverse lighting conditions and complex field backgrounds using various imaging devices including digital cameras and smartphones, the dataset presents substantial challenges for recognition tasks due to uneven illumination, varied disease severity, and complex environmental contexts. This dataset serves as a valuable benchmark for evaluating lightweight models in real-world agricultural scenarios and supports the development of efficient crop disease diagnosis systems for UAV edge devices.