Share your research data

This repository contains a graphical figure for a functional Hemin-Binding Site Competition Assay and an LDH Cytotoxicity Assay. The functional assay assesses how the addition of exogenous hemin modulates the suppression of kynurenine (Kyn) production by our Apo-IDO1 inhibitor (i.e., 1g), confirming a competitive mechanism of action. The LDH cytotoxicity assay serves as an experimental control, demonstrating that the concentrations of hemin used in the competition study do not compromise cell viability. These experiments provide further validation of the molecular hypothesis reported in our paper in the European Journal of Pharmaceutical Sciences (DOI: 10.1016/j.ejps.2026.107605).

Anesthesia _ Neurology _ Chronic Pain

Data package for manuscript "Mineral-specific ligand and redox dynamics of adsorbed platinum: Pathway-dependent mobility during terrestrial weathering" by Emily G. Wright, Fernanda M. Loza, Elaine D. Flynn, and Jeffrey G. Catalano. The manuscript will be submitted to Geochimica et Cosmochimica Acta. This dataset contains results from adsorption experiments exploring the effect of chloride, ammonia, initial Pt speciation, pH, and aging time on Pt adsorption to hematite and goethite. This includes lab experiments reacting mineral suspensions and characterization of adsorbed Pt with X-ray absorption fine structure spectroscopy. The file "Wright2026_pHEdge_data.csv" contains the aqueous Pt and associated error (in uM), calculated adsorbed Pt and associated error (in umol/m2), target chloride (mM), target ammonia (mM), mineral concentration/loading (in g/L), and the final pH. Associated mineral-free controls at all pH values (mineral loading = 0 g/L) were used to determine the initial Pt in reactors and are included; the aqueous Pt error was not calculated. All reaction times were 24 hours. These data appear in Figures 2 and S4. The files "Wright2026_ShortKinetic_data.csv" and "Wright2026_LongKinetic_data.csv" contains the aqueous Pt and associated error (in uM), calculated adsorbed Pt and associated error (in umol/m2), target chloride (mM), target ammonia (mM), mineral concentration/loading (in g/L), pH, and reaction time for kinetic reactors prepared at pH 6 that were subsampled for 3 days ("Short") or 4 months ("Long"). Associated mineral-free controls (mineral loading = 0 g/L) are included. These data appear in Figures 3, S5, and S6. The file "Wright2026_MineralBatches_data.csv" contains the mineral identity and BET specific surface area (in m2/g) for every mineral batch used in experiments. These data appear in Table S1. The file "Wright2026_XRD_data.csv" contains the powder X-ray diffraction patterns of synthesized batches of hematite and goethite. Note that the data were collected under variable conditions that are detailed in the manuscript. These data appear in Figure S1. The file "Wright2026_XAFSSamples_data.csv" contains the specific mineral batch, measured final aqueous Pt (in uM), pH, estimated adsorbed Pt (umol/g), target chloride (mM), and target ammonia (mM) of all experimental XAFS samples. These data appear in Table S2. The file "Wright2026_EXAFS_data.csv" and "Wright2026_XANES_data.csv" contains the normalized XAFS spectra of samples of Pt adsorbed to hematite and goethite as well as reference materials PtCl2, PtO2, PtCl4(NH4)2, PtCl6(NH4)2, and Pt(O2C5H7)2 used for EXAFS and XANES fitting. See "Wright2026_XAFSSamples_data.csv" for a guide to sample names for experimental samples. These data appear in Figures 4, 6, S2, S3, S7, and S10.

Table A: Selected Studies on Metaverse-Enabled English Language Learning (30 Studies) Table B: Comprehensive Matrix of Included Studies

This repository contains the data and analysis code supporting "Words That Price: How Listing Language Encodes Audiences and Shapes Market Value" (submitted to the Journal of Business Research). The dataset comprises 12,682 anonymized rental listings collected from Meqasa, a major Ghanaian online real estate marketplace, covering Greater Accra between 2013 and 2026. Each record includes structured property attributes (rent, bedrooms, bathrooms, floor area, property type, amenities, locality, listing date) alongside an anonymized free-text description. The repository also includes the corpus-driven term-discovery output and thematic-coding materials used to classify listing language into seven registers (including a Western-Standard Signaling register and a Domestic-Reference register), along with inter-rater reliability data from two independent professional coders (Cohen's kappa = 0.875). Python code reproduces all reported pricing models and robustness checks, including coarsened exact matching, within-agent and cell fixed-effects comparisons, repeat-listing analysis, Oster (2019) and Cinelli-Hazlett (2020) sensitivity bounds, quantile regression, and the seasonal audience-tracking test, plus all figures. A step-by-step analysis protocol and full variable-level documentation are included. All platform-identifying information (URLs, agent names, internal IDs) has been removed from the data; agent identity is preserved only as an anonymized integer code, to support agent fixed-effects estimation.

Code and data that reproduce the empirical results, tables and figures of “Measuring the Inflation Anchor” by Fabio Gómez-Rodríguez. The paper measures the inflation anchor as the most persistent component of the term structure of market-based inflation expectations. The package estimates a Bayesian factor VAR on the Federal Reserve Bank of Cleveland’s 1–10 year expected inflation curve, identifies an anchor shock and a transitory shock by maximum forecast-error-variance shares, and uses the two shocks as external instruments in a macroeconomic Bayesian VAR. It also runs every robustness check, historical decomposition and test reported in the paper, the curve-level unit-root tests (PANIC and the functional test of Chang, Kim and Park), and the calibration of the paper’s theoretical model. The code is in Python 3.13, and run_all.sh reproduces everything in about 45 minutes on one core. The folder paper_outputs holds the outputs used in the paper, and compare_outputs.py checks a fresh run against them. The README lists every data source with its provider, retrieval date and citation, and maps the paper’s tables, figures and numbers to the programs that produce them.

This dataset supports the research article titled Social Visibility and Peer Networks in PrEP Use Among Female Sex Workers in Peri-Urban Kenya: A Mixed-Methods Study. The dataset comprises quantitative and qualitative data collected between September and October 2026 in Turbo and Kapseret sub-counties, Uasin Gishu County, Kenya. The quantitative component contains interviewer-administered survey responses from 368 HIV-negative female sex workers aged 18 years and above. It captures socio-demographic characteristics, PrEP awareness and knowledge, attitudes towards HIV prevention, perceived HIV risk, peer influence, partner relationships, alcohol and substance use, stigma, social visibility, confidentiality, health-service experiences, and PrEP initiation, current use and discontinuation. The qualitative component comprises eight key informant interview records from healthcare providers, HIV testing and counselling personnel, and programme staff involved in PrEP service delivery, together with one focus group discussion record involving 12 peer educators, outreach workers and peer leaders. These records provide additional insights into peer networks, community perceptions, confidentiality, barriers to PrEP access, service delivery experiences and recommendations for improving PrEP uptake and continuation. The three datasets are provided in Microsoft Excel format and collectively support the quantitative analyses, qualitative thematic findings and mixed-methods interpretation presented in the associated research article.

This study explores psychometrically sound measures of preschoolers’ scientific interest. By evaluating seven measures adapted from work in other domains or with older children, we aim to identify reliable and valid measures that can contribute to understanding how scientific interest develops in early childhood and to evaluating interventions designed to foster it. The dataset includes de-identified scores on each measure, participant demographic information, and R-scripts used for data analysis.

Data to generate figures from Chambers, Kimchi et al, PLoS Biology

Este conjunto de dados reúne dados de pacientes diagnosticados com tuberculose disponibilizados pelo Ministério da Saúde através do SINAN (Sistema de Informação de Agravos de Notificação). O conjunto abrange notificações de pacientes com tuberculose no Brasil entre 2001 e 2024, com informações de dados clínicos, laboratoriais e sociodemográficos, totalizando 2.188.471 registros e 108 atributos. O notebook incluído realiza todo o pré-processamento e a análise: conversão dos códigos com base no dicionário de dados do SINAN, tratamento dos dados faltantes e remoção de 428 registros duplicados e de atributos com mais de 70% de dados faltantes, de identificação e de datas, entre outros, resultando em 2.188.043 registros e 49 atributos. O desfecho foi definido pela variável SITUA_ENCE e analisado em dois desfechos separados, ambos comparados à cura: abandono do tratamento e óbito por tuberculose. A análise de associação considera os 855.182 casos diagnosticados entre 2014 e 2024 e encerrados por cura, abandono ou óbito por tuberculose, sendo 149.237 abandonos (18,2% do desfecho abandono) e 36.215 óbitos (5,1% do desfecho óbito), por meio da razão de chances (OR) bruta e ajustada por regressão logística. Para reproduzir a análise, extraia o arquivo SINANTB_01a24.csv em uma pasta chamada dados, coloque o notebook na mesma pasta que contém dados (ou em uma subpasta dela), instale as bibliotecas do requirements.txt (Python 3.13) e execute o notebook de cima para baixo. As tabelas e figuras são gravadas em saidas/desfechos_ajustada. Os dados desse repositório incluem: • Base de dados de tuberculose do SINAN, 2001 a 2024 (SINANTB_01a24.zip) • Notebook de pré-processamento e análise (notebook.ipynb) • Versões das bibliotecas utilizadas (requirements.txt) • Dicionário de dados do SINAN