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This dataset supports the study “Eco-efficiency of Room Air Conditioner Units in a Dengue-Prone Climate: A Comprehensive Life Cycle Analysis Integrating Epidemiological Perspectives.” It contains the inputs, calculations, and model outputs used to investigate the relationship between indoor thermal conditions, room air-conditioner energy consumption, environmental impacts, household costs, and dengue transmission risk. The dataset covers eight dengue-endemic cities in South and Southeast Asia: Bangkok, Cebu, Chennai, Colombo, Dhaka, Ho Chi Minh City, Jakarta, and Yangon. It includes climate and dengue observations used for model development, physics-informed machine-learning predictions of the indoor basic reproduction number, estimated hospitalized secondary dengue cases per household, Variable Cooling Degree Day energy calculations, life-cycle assessment results, environmental externality and consumer-cost estimates, and integrated eco-efficiency indicators. Scenarios span air-conditioned and non-air-conditioned living spaces, indoor temperatures of approximately 18–30 °C, different mosquito densities, vector-control interventions, and national-grid and decentralized-solar electricity supplies. Uncertainty ranges generated through Monte Carlo analysis are also provided where applicable. These data enable reproduction and further analysis of the climate–cooling–dengue nexus and can support research on climate-resilient cooling, household energy policy, environmental sustainability, and vector-borne disease prevention in tropical regions.

This dataset contains the experimental, analytical, and bioinformatic data supporting the study "Living commensal biofilms for corrosion prevention." It provides a comprehensive, multimodal evaluation of microbiome engineering as a sustainable strategy to mitigate microbiologically influenced corrosion (MIC) on copper surfaces. Specifically, the data demonstrates the efficacy of the commensal bacterium Citrobacter sp. strain MICI21 in outcompeting the highly corrosive sulfate-reducing bacterium (SRB) Oleidesulfovibrio alaskensis G20. The repository encompasses the four-part ecological framework of microbioclaim, including competitive surface occupation, biological passivation, and commensal antagonism. Data contained in this repository includes: Electrochemical Data: Open Circuit Potential (OCP), Electrochemical Impedance Spectroscopy (EIS) Nyquist/Bode plots, and potentiodynamic polarization curves demonstrating 3- to 15-fold higher corrosion resistance. Surface & Structural Characterization: Scanning Electron Microscopy (SEM) micrographs, Confocal Laser Scanning Microscopy (CLSM) surface coverage profiles, nanoindentation metrics (stiffness/elasticity), and pit-depth quantifications. Physicochemical Analysis: Gravimetric (weight-loss) assay results, Extracellular Polymeric Substance (EPS) characterization, Energy-Dispersive Spectroscopy (EDS), X-ray Diffraction (XRD), and reactor H₂S quantification. Genomic & Bioinformatic Context: 16S rRNA analysis data and outputs from comparative genomic analysis (STRING-DB protein-protein interaction networks) of publicly available Citrobacter strains highlighting putative Type VI secretion system (T6SS) antagonism features. (Note: KBase Narratives #182783 and #182791 are hosted externally). Keywords: Microbiologically Influenced Corrosion (MIC), Biofilm Engineering, Living Coatings, Citrobacter, Sulfate-Reducing Bacteria (SRB), Electrochemical Impedance Spectroscopy (EIS), Biological Passivation, Type VI Secretion System (T6SS), Copper Corrosion

This dataset supports the manuscript **“Post-diffusion cooling effects on Hall-derived active lithium donor profiles in high-purity germanium.”** It contains the measured cooling histories, the raw and processed 77 K Hall-profile data, and the Jupyter notebooks used for the reported profile fits and figures. Eight HPGe coupons were studied: four nominal Li-diffusion temperatures (240, 260, 280, and 310 °C) and two post-diffusion cooling protocols (short and long cooling), with one coupon per condition (`n = 1`). Every diffusion hold was 30 min. Figures 1 and 2 in the manuscript are photographs/schematics of the samples and apparatus and therefore have no numerical data file in this dataset.

Supplemental material associated with a small real-world case series evaluating remibrutinib in patients with inadequately controlled cholinergic urticaria.

Western blot

This dataset contains the source data underlying the main and supplemental figures in the article “PHYHD1-mediated translational control regulates renal cell carcinoma progression.” Ribo-seq and RNA-seq data have been deposited in GEO under accession number GSE282151 and are publicly available as of the date of publication. The code and scripts used to reproduce the analyses are available at https://github.com/FakeEnd/pan_cancer_alpha_KG_dependent_analysis.

Osteoarthritis (OA) is a degenerative joint disease in which early mitochondrial dysfunction and cuproptosis blunt endogenous repair. Because these two processes demand intervention at different times, we asked whether a “microenvironment preconditioning” strategy could meet both, and built a double-barrier hydrogel (CFG@M/E) that releases OLA1 early and Cytl1 late. OLA1, a protein we identified by proteomic profiling of synovial fibroblast-derived exosomes, is delivered rapidly under ROS-enriched conditions to suppress cuproptosis, whereas Cytl1, identified by single-cell RNA sequencing, is released slowly and in a pH-dependent manner to drive matrix synthesis. In vitro, early OLA1 suppressed Elesclomol-induced cuproptosis, restored mitochondrial membrane potential, and lowered ROS, and the subsequent Cytl1 exposure then promoted anabolism (COL2A1/SOX9 up, MMP13 down). In a DMM mouse model, intra-articular CFG@M/E reduced OARSI scores, preserved cartilage, and restored locomotion without systemic toxicity. The double-barrier design thus matches the bioavailability of OLA1 and Cytl1 to the distinct pathological windows of OA—a more rational approach than co-delivering two drugs at once.

This dataset studies whether gum arabic (GA), a low-cost and sustainable biopolymer, can improve the wear resistance of epoxy coatings on steel. The main idea is that adding GA to epoxy may change the wear behavior and surface damage during reciprocating sliding compared with pure epoxy. The dataset contains 273 high-resolution optical microscopy images (.tif) of wear scars formed on EN8 steel substrates coated with epoxy (Araldite LY556), with and without GA. Two Taguchi L16 tests were used. The EP group (pure epoxy) contains 135 images and was tested by changing the normal load (5–20 N), sliding frequency (1–2.5 Hz), and temperature (40–70 °C). The EPGA group (epoxy with GA) contains 138 images and was tested using the same three parameters along with different GA contents (0.25–3 wt.%). A total of 32 test conditions were studied, and each condition was tested three times using a reciprocating ball-on-flat tribometer against an EN31 steel counter-ball. The wear scars were taken at up to three locations (center, edge, and overview) using 50× magnification. The images are arranged by coating group, test condition, and replicate number. They are listed in the accompanying Metadata_Manifest.csv file. The file contains the test conditions, image information, and the observed wear mechanisms. The wear mechanisms include micro-cracking, ploughing, adhesive pitting, plastic deformation, transfer-film formation, and Schallamach-like waves. Some conditions have fewer images than expected because of actual test results and not because of missing data. In EP conditions C2, C8, and C12, coating peeling occurred in one replicate. In EPGA condition G3, no visible wear scar was produced. These results are included because they provide useful information about the coating behavior under those test conditions. The images can be used to study changes in wear-scar shape and surface damage between pure epoxy and GA-reinforced epoxy. The average coefficient of friction and specific wear rate from the related publication are also provided in the metadata for reference. The images and their wear-mechanism labels are the main data in this dataset. This dataset can be used for studying wear mechanisms, comparing bio-based gum arabic reinforced epoxy and pure epoxy coatings, image analysis, and developing machine-learning methods for wear classification. The condition numbers C1–C16 and G1–G16 follow the Taguchi test order used in the related study.

This dataset contains raw soil physical, chemical, and biological collected across three contrasting landscapes in the Central Highlands of Madagascar. The dataset includes the geographic location of sampling sites, topographic position, geological type, local site (fokontany), landscape type, land cover, soil depth, and replicates. Soil properties include bulk density, soil moisture, pH, total nitrogen, soil organic carbon, Olsen phosphorus, microbial phosphorus, resin phosphorus, and soil texture (clay, silt, and sand). Macrofauna variables include total density, total biomass, taxonomic richness, and Shannon diversity index. Soil samples were collected at three depths (0–10, 10–20, and 20–30 cm), with up to four replicates per sampling site. The dataset is provided as raw observations and includes the original measurements used for the analyses presented in the associated study. All soil samples were collected in the Itasy Region in may/june 2023, in the central highlands of Madagascar. The study area is located approximately between 46°10′– 47°00′ E and 19°25′–19°39′ S. The precise geographic coordinates of individual sampling plots are not provided in the publicly available dataset.

This dataset contains the source data underlying the figures in the manuscript entitled “A Bacteroides ovatus-lysophosphatidylcholine axis supports neural repair after spinal cord injury.” The Excel workbook is organized by figure and panel and contains the individual values used for quantitative analyses and graph generation. Experimental procedures and statistical analyses are described in the accompanying manuscript.