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Abstract Background The North American opioid crisis is driven by opioid-related mortality and morbidity, including opioid use-associated infections (OUAIs), resulting in a substantial burden for society. Users of legal and illegal opioids are at an increased risk of OUAIs compared to individuals not using opioids. As reported for hepatitis C virus (HCV), human immunodeficiency virus (HIV), bacterial, fungal, and other infections, OUAIs transmission and acquisition risks may be modifiable. Several systematic reviews (SRs) synthetized data regarding interventions to prevent infections in persons using drugs (e.g., opioid substitution therapy, needle and syringes exchange programs, psycho-social interventions); however, their conclusions varied. Therefore, SR of published SRs is needed to synthesize the highest level of evidence on the scope and effectiveness of interventions to prevent OUAIs in people using opioids legally or illegally. Methods We will comprehensively search for SRs in the PubMed, Embase, PsycINFO, Cochrane Database of Systematic Reviews, Epistemonikos, and Google Scholar databases from inception to November 2020. Data selection and extraction for each SR will be performed independently by two researchers, with disagreements resolved by consensus. All SRs regarding interventions with evaluated effectiveness to prevent OUAI in legal and/or illegal opioid users will be eligible. Risk of bias assessment will be performed using the AMSTAR2 tool. The results will be qualitatively synthesized, and a typology of interventions��� effectiveness with a statement on the strength of evidence for each category will be created. Discussion Our pilot search of PubMed resulted in 379 SRs analyzing the effectiveness of interventions to prevent HCV and HIV in persons who inject different types of drugs, including opioids. Of these 379 SRs, 8 evaluated primary studies where participants used opioids and would therefore be eligible for inclusion. The search results thus justify the application of SR of SRs approach. Comprehensive data on the scope and effectiveness of existing interventions to prevent OUAIs will help policy-makers to plan and implement preventive interventions and will assist clinicians in the guidance for their patients using opioids. Systematic review registration Registered in PROSPERO on 30 July 2020 ( #195929 ).

Abstract Background B7-H3 and B7-H4 are highly expressed by many human malignancies making them attractive immunotherapeutic targets. However, their expression patterns and immune contexts in epithelial ovarian cancer have not been well characterized. Methods We used flow cytometry, immunohistochemistry, and genomic analyses to determine the patterns of B7-H3, B7-H4, and PD-L1 expression by tumor, stromal, and immune cells in the ovarian tumor microenvironment (TME). We analyzed immune cell frequency and expression of PD-1, TIM3, LAG3, ICOS, TIA-1, granzyme B, 2B4, CD107a, and GITR on T cells; CD20, CD22, IgD, BTLA, and CD27 on B cells; CD16 on monocytes; and B7-H3, B7-H4, PD-L1, PD-L2, ICOSL, CD40, CD86, and CLEC9a on antigen-presenting cells by flow cytometry. We determined intratumoral cellular location of immune cells using immunohistochemistry. We compared differences in immune infiltration in tumors with low or high tumor-to-stroma ratio and in tumors from the same or unrelated patients. Results On non-immune cells, B7-H4 expression was restricted to tumor cells whereas B7-H3 was expressed by both tumor and stromal cells. Stromal cells of the ovarian TME expressed high levels of B7-H3 compared to tumor cells. We used this differential expression to assess the tumor-to-stroma ratio of ovarian tumors and found that high tumor-to-stroma ratio was associated with increased expression of CD16 by monocytes, increased frequencies of PD-1high CD8+ T cells, increased PD-L1 expression by APCs, and decreased CLEC9a expression by APCs. We found that expression of PD-L1 or CD86 on APCs and the proportion of PD-1high CD4+ T cells were strongly correlated on immune cells from tumors within the same patient, whereas expression of CD40 and ICOSL on APCs and the proportion of PD-1high CD8+ T cells were not. Conclusions This study provides insight into the expression patterns of B7-H3 and B7-H4 in the ovarian TME. Further, we demonstrate an association between the tumor-to-stroma ratio and the phenotype of tumor-infiltrating immune cells. We also find that some but not all immune parameters show consistency between peritoneal metastatic sites. These data have implications for the design of immunotherapies targeting these B7 molecules in epithelial ovarian cancer.

Spreadsheet of analyte concentrations and metabolite/parent ratios for tamoxifen and its metabolites. (XLSX 10 kb)

Additional file 2: Figure S2. Simulated degree used as the generating distribution for the simulated networked populations. The full range of reported degrees is shown in A, and a reduced range of degree

Additional file 5: Table S4. EGFR information on LGSC cell lines.

Abstract Background Single-cell RNA sequencing (scRNA-seq) is a powerful tool for studying complex biological systems, such as tumor heterogeneity and tissue microenvironments. However, the sources of technical and biological variation in primary solid tumor tissues and patient-derived mouse xenografts for scRNA-seq are not well understood. Results We use low temperature (6 °C) protease and collagenase (37 °C) to identify the transcriptional signatures associated with tissue dissociation across a diverse scRNA-seq dataset comprising 155,165 cells from patient cancer tissues, patient-derived breast cancer xenografts, and cancer cell lines. We observe substantial variation in standard quality control metrics of cell viability across conditions and tissues. From the contrast between tissue protease dissociation at 37 °C or 6 °C, we observe that collagenase digestion results in a stress response. We derive a core gene set of 512 heat shock and stress response genes, including FOS and JUN, induced by collagenase (37 °C), which are minimized by dissociation with a cold active protease (6 °C). While induction of these genes was highly conserved across all cell types, cell type-specific responses to collagenase digestion were observed in patient tissues. Conclusions The method and conditions of tumor dissociation influence cell yield and transcriptome state and are both tissue- and cell-type dependent. Interpretation of stress pathway expression differences in cancer single-cell studies, including components of surface immune recognition such as MHC class I, may be especially confounded. We define a core set of 512 genes that can assist with the identification of such effects in dissociated scRNA-seq experiments.

Continuing professional development is an important means of improving access to effective patient care. Although pain content has increased significantly in prelicensure programs, little is known about how postlicensure health professionals advance or maintain competence in pain management. The aim of this study was to investigate Canadian health professionals’ continuing professional development needs, activities, and preferred modalities for pain management. This study employed a cross-sectional self-report web survey. The survey response rate was 57% (230/400). Respondents were primarily nurses (48%), university educated (95%), employed in academic hospital settings (62%), and had ≥11 years postlicensure experience (70%). Most patients (>50%) cared for in an average week presented with pain. Compared to those working in nonacademic settings, clinicians in academic settings reported significantly higher acute pain assessment competence (mean 7.8/10 versus 6.9/10; P < 0.002) and greater access to pain specialist consultants (73% versus 29%; P < 0.0001). Chronic pain assessment competence was not different between groups. Top learning needs included neuropathic pain, musculoskeletal pain, and chronic pain. Recently completed and preferred learning modalities respectively were informal and work-based: reading journal articles (56%, 54%), online independent learning (44%, 53%), and attending hospital rounds (43%, 42%); 17% had not completed any pain learning activities in the past 12 months. Respondents employed in nonacademic settings and nonphysicians were more likely to use pocket cards, mobile apps, and e-mail summaries to improve pain management. Canadian postlicensure health professionals require greater access to and participation in interactive and multimodal methods of continuing professional development to facilitate competency in evidence-based pain management.

Table S1A. All hydrogen deuterium exchange (HDX) peptide data for experiments examining the global exchange of PI4KIIIA, TTC7B, and FAM126A. The charge state (Z), residue start, residue end number, retention time (RT) and sequence are displayed for every peptide. In the Raw Data column, the two time points (0.3s and full) are labelled, and the relative level of HDX is coloured according to the amount of deuterium incorporated, on a blue to red continuum. The data listed for the 0.3s time point are the average of three independent experiments, with SD shown next to all HDX values. In the Normalized to Full Deuteration column, the 0.3s data has been normalised to the full deuteration measurements with the exception of those data (surrounded by black lines) where the full deuteration measurement was lower than 20% deuterium incorporation. The third column denotes the corresponding peptide centroid. Table S1B. All HDX peptide data for experiments examining the complex dynamics of PI4KIIIA, TTC7B, and FAM126A. The charge state (Z), residue start, residue end number, retention time (RT) and sequence are displayed for every peptide. The two columns represent each state examined (+/- PI4KIIIA) and contain the data for five time points. The data listed are the average of three independent experiments, with SD shown next to all HDX values. Table S1C. All HDX peptide data for experiments examining the dynamics of inhibitor specificity of PI4KIIIA, TTC7B, and FAM126A. The charge state (Z), residue start, residue end number, retention time (RT) and sequence are displayed for every peptide. The three columns represent each state examined (+/- inhibitor) and contain the data for four time points. The data listed are the average of three independent experiments, with SD shown next to all HDX values.