While collaboration with industry is paramount to innovation, the recent emphasis on industrial relationship transparency has sparked new guidelines, research studies, and standardizations focused on re-defining conflict of interest. There is limited data on defining the specific financial amount wherein a conflict of interest is relevant. This study is the first to assess the potential financial effects on high-quality clinical data, or the “indirect sponsorship”.
Criss CN, MacEachern MP, Matusko N, Dimick JB, Maggard-Gibbons M, Gadepalli SK. The Impact of Corporate Payments on Robotic Surgery Research: A Systematic Review. Ann Surg. 2019 Mar; 269 (3): 389-396. doi: 10.1097/SLA.0000000000003000. PMID: 30067545. https://doi.org/10.1097/SLA.0000000000003000
The dataset includes the reproducible search strategies for all literature databases searched during the review, the key articles used to generate relevant search terms and test the effectiveness of the searches, the Endnote library that has all citations considered for inclusion, a flow chart describing the screening process, and the screening forms used for inclusion and exclusion.
Bennett K, Berlin N, MacEachern MP, Buchman S, Vercler C. (2018). The ethical and professional use of social media in surgery - A systematic review of the literature. Plastic and Reconstructive Surgery, 142(3), 388e-398e. PMID: 30148789. https://doi.org/10.1097/prs.0000000000004692
The dataset includes all citations considered for inclusion in the systematic review. The citations are accessible in Endnote (enlx), as well as through the primary citation export files from each database. The literature search strategies are included for reproducibility and transparency purposes. See the published methods for more information.
DeLong MR, Tandon VJ, Farajzadeh M, Berlin NL, MacEachern MP, Rudkin GH, Da Lio AL, Cederna PS. (2019). Systematic review of the impact of acellular dermal matrix on aesthetics and patient satisfaction in tissue expander-to-implant breast reconstructions. Plastic and Reconstructive Surgery. and https://doi.org/10.1097/PRS.0000000000006212
This data is part of a large program to translate detection and interpretation of HFOs into clinical use. A zip file is included which contains hfo detections, metadata, and Matlab scripts. The matlab scripts analyze this input data and produce figures as in the referenced paper (note: the blind source separation method is stochastic, and so the figures may not be exactly the same). A file "README.txt" provides more detail about each individual file within the zip file.
This data repository includes the quantitative features of high frequency, intracranial EEG along with all necessary scripts to reproduce the figures of the accompanying manuscript.
Supplementary Figure 1. Example gating scheme for bone marrow mature leukocytes and hematopoietic progenitors. To stain for mature leukocytes antibodies used were against CD45, Ly6G, CD11b, CD115, CD19, and CD3e. All CD45+ cells were gated first. Neutrophils were defined as Ly6G+CD11b+, monocytes were defined as Ly6G-CD11b+CD115+ (17,18), B cells were defined as Ly6G-CD11b-CD19+, and T cells were defined as Ly6G-CD11b-CD3e+. To stain for hematopoietic stem and progenitor cells antibodies used were against lineage panel (B220, Gr1, TER119, CD11b, CD4, CD8), cKit, Sca1, CD48, CD150, CD16/32, and CD105. HSCs were defined as Lin-Sca1+cKit+CD48-CD150+, MPPs were defined as Lin-Sca1+cKit+CD48-CD150-, HPC1 were defined as Lin-Sca1+cKit+CD48+CD150-, HPC2 were defined as Lin-Sca1+cKit+CD48+CD150+, GMP were defined as Lin-Sca1-cKit+CD150-CD16/32+, PreGM were defined as Lin-Sca1+cKit+CD150-CD105-, preMegE were defined as Lin-Sca1+cKit+CD150+CD105-, and PreCFUe were defined as Lin-Sca1+cKit+CD150+CD105+. , Supplementary Figure 2. Hematopoietic stem and progenitor cell frequency by flow cytometry as a percentage of CD45 bone marrow cells in male and female Ctrl and HFD PN offspring. Hematopoietic stem cells (HSC), multipotent progenitor cells (MPP), Pre-Granulocyte Macrophage (Pre-GM), granulocyte monocyte precursors (GMP), Pre-Megakaryocyte-Erythroid Precursors (Pre-MegE) and erythroid precursors (Pre-CFUE). Analyses were Student’s t-test ang gating per Supplementary Figure 1., Supplementary Table 1. Differential gene expression between Ctrl and HFD PN male gonadal white adipose tissue (GWAT) from postnatal day 16. The significant gene expression differences were determined by the DESeq2 package for R Studio. Sequencing The RNA was extracted from adipose tissue using Trizol LS (Life Technologies) by Qiagen RNeasy Mini Kit (74106) according to the manual. The RNA was sent to the University of Michigan Advanced Genomics Core for RNA-sequencing. For RNAseq studies, gonadal white adipose tissue 3’ QuantSeq single-end poly-A mRNA libraries were generated (Lexogen). These were sequenced to a depth of 10-20M reads on Illumina NovaSeq platform. Data are available from GEO at accession number GSE227337., and Supplementary Table 2. Differentially expressed genes between Ctrl and HFD PN male gonadal white adipose tissue (GWAT) from postnatal day 16 that are significant after correction for false discovery rate were determined by the DESeq2 package for R Studio.
Citation to related publication:
Kim K, Varghese M, Sun H, Abrishami S, Bowers E, Bridges D, Meijer JL, Singer K* and Gregg B*. The influence of maternal high fat diet during lactation on offspring hematopoietic priming. Endocrinology. https://doi.org/10.1210/endocr/bqad182 PMID 38048597.
The main goal of this research was to identify potential molecular pathways that contribute to memory dysregulation and decline that persists long after illness or inflammation. We have previously established a subchronic immune challenge model that results in memory impairments months after the inflammatory challenge. This project aimed to determine whether memory impairments were accompanied by transcriptional dysregulation in memory related brain region (the hippocampus).
These data show the differential gene expression as log2fold change (and p-value) in males and females 3 months after immune challenge (Supp Tables 1 and 2); after a subsequent immune challenge (Supp Tables 3 and 4); the differential regulation of genes in males and females (Supp Table 5); genes differentially expressed in the hippocampus of males and females at baseline (Supp Table 6) and the differential regulation of those genes in males and females after immune challenge (Supp Tables 7,8).
Tchessalova, D., & Tronson, N. C. (2019). Enduring and sex-specific changes in hippocampal gene expression after a subchronic immune challenge. BioRxiv, 566570. https://doi.org/10.1101/566570
The dataset includes all citations considered for inclusion in the scoping review. The citations are accessible in Endnote (enlx) and Microsoft Excel (xlsx), as well as the primary citation export files from each database. The literature search strategies are included for reproducibility and transparency purposes. See the published methods for more information.
Muzyk A, Smothers ZPW, Akrobetu D, Ruiz Veve J, MacEachern M, Tetrault JM, Grupen L. (2019). Substance use disorder education in medical schools: A scoping review of the literature. Academic Medicine. PMID: 31348067. and https://doi.org/10.1097/ACM.0000000000002883
The dataset includes most citations considered for inclusion in the scoping review. The citations are accessible in the Endnote file, as well as the primary citation export files from each database. The literature search strategies are included for reproducibility and transparency purposes.
Tan MH, Iyengar R, Mizokami-Stout K, et al. Spectrum of immune checkpoint inhibitors-induced endocrinopathies in cancer patients: a scoping review of case reports. Clin Diabetes Endocrinol. 2019;5:1. Published 2019 Jan 22. https://doi.org/10.1186/s40842-018-0073-4