Search

ABSTRACT: Background: As healthcare moves from a one-size-fits-all approach towards precision care, individual risk prediction is an important step in disease prevention and early detection. Biobank-linked healthcare systems can generate knowledge about genomic risk and test the impact of implementing that knowledge in care. Risk-stratified prostate cancer screening is one clinical application that might benefit from such an approach. Methods: We developed a clinical translation pipeline for genomics-informed prostate cancer screening in a national healthcare system. We used data from 585,418 male participants of the Veterans Affairs (VA) Million Veteran Program (MVP), among whom 101,920 self-identify as Black/African-American, to develop and validate the Prostate CAncer integrated Risk Evaluation (P-CARE) model, a prostate cancer risk prediction model based on a polygenic score, family history, and genetic principal components. The model was externally validated in data from 18,457 PRACTICAL Consortium participants. A novel blended genome-exome (BGE) platform was used to develop a clinical laboratory assay for both the P-CARE model and rare variants in prostate cancer-associated genes, including additional validation in 74,331 samples from the All of Us Research Program. Results: In overall and ancestry-stratified analyses, the polygenic score of 601 variants was associated with any, metastatic, and fatal prostate cancer in MVP and PRACTICAL. Values of the P-CARE model at ≥80th percentile in the multiancestry cohort overall were associated with hazard ratios (HR) of 2.75 (95% CI 2.66-2.84), 2.78 (95% CI 2.54-2.99), and 2.59 (95% CI 2.22-2.97) for any, metastatic, and fatal prostate cancer in MVP, respectively, compared to the median. When high– and low-risk groups were defined as P-CARE HR>1.5 and HR

Objectives Four intrinsic molecular subsets (inflammatory, fibroproliferative, limited, normal-like) have previously been identified in SSc and are characterized by unique gene expression signatures and pathways. The intrinsic subsets have been linked to improvement with specific therapies. Here, we investigated associations between baseline demographics and intrinsic molecular subsets in a meta-analysis of published datasets. Methods Publicly available gene expression data from skin biopsies of 311 SSc patients measured by DNA microarray were classified into the intrinsic molecular subsets. RNA-sequencing data from 84 participants from the ASSET trial were used as a validation cohort. Baseline clinical demographics and intrinsic molecular subsets were tested for statistically significant associations. Results Males were more likely to be classified in the fibroproliferative subset (P  = 0.0046). SSc patients who identified as African American/Black were 2.5 times more likely to be classified as fibroproliferative compared with White/Caucasian patients (P  = 0.0378). ASSET participants sera positive for anti-RNA pol I and RNA pol III autoantibodies were enriched in the inflammatory subset (P  = 5.8 × 10−5, P  = 9.3 × 10−5, respectively), while anti-Scl-70 was enriched in the fibroproliferative subset. Mean modified Rodnan Skin Score (mRSS) was statistically higher in the inflammatory and fibroproliferative subsets compared with normal-like (P  = 0.0027). The average disease duration for inflammatory subset was less than fibroproliferative and normal-like intrinsic subsets (P  = 8.8 × 10−4). Conclusions We identified multiple statistically significant differences in baseline demographics between the intrinsic subsets that may represent underlying features of disease pathogenesis (e.g. chronological stages of fibrosis) and have implications for treatments that are more likely to work in certain SSc populations. [ABSTRACT FROM AUTHOR]

Knowledge about the impact of agricultural practices on soil quality is very important to plan the use and sustainable management of productive lands. Citrus cropping has recently acquired a significant economic importance in Misiones, Argentina. It is cultivated in different types of soils sensitive to crosion, like Oxisoles. The aim of this work was to determine the effect of citrus cropping on some chemical and biological soil quality indicators. The Field experiment consisted of 2 treatments: subtropical rainforest (Sv) and citrus (Ci). In 0-10 cm samples the following parameters were measured: pH, organic carbon (OC), particulate organic matter (POM), total nitrogen (TN), available phosporous (P), acid phosphatase activity (APA), respiration (RES), and potentially mineralizable nitrogen (PMN). The comparisons of the mean treatments were carried out through Duncan's Multiple Range Test (P < 0.05). The average OC content was higher in Sv (4.03%) than in Ci (2.35). In spite of N addition to Citrus, TN and PMN were higher in Sv than in Ci. Sv showed the highest values (statistically different from Ci) in POM and its fractions. Nt accounted for 69% of the APA variance and the OC a 61%: APA = 1775 TN 153.7 (r2 = 0.69). APA = 221 CO - 230 (r2 = 0.61). Obtained results showed that citrus cultivation decreases OC, TN, APA, PMN, POM and soil respiration, which accelerated soil degradation. These soil attributes should be considered as indicators to assess soil quality. [ABSTRACT FROM AUTHOR]

The objective of this work was to select indicators and develop indices to evaluate soil quality and thus be able to determine the effects of replacing natural pastures with forest systems in vulnerable environments. The experiment was carried out in Inceptisols of Corrientes, a province located in the northeast of Argentina. In order to obtain indicators and develop indices, we used both natural systems (natural pasture, M) and systems cultivated with exotic species (Pinus sp.). A completely randomized design was established at the department of Ituzaingó (Corrientes). The methodological approach consisted in determining a reference level against which changes in soil quality were compared and quantified. Climax vegetation (natural pastures) soils were taken as high-quality reference soils. The cultivated system included a forest plantation with 17-year-old Pinus sp. In each case, composite samples were collected at random to the 0-0.10 m depth. The following edaphic variables were determined: bulk density (Da), texture, silt (Li) and clay proportion (Arc), pH, total organic carbon (COT), potentially mineralizable nitrogen (NPM), and soil respiration (RES). On the other hand, the indices for COT/Li+Arc, NPM/RES, NPM/MO and IRC (index of carbon reserve) were determined by calculation. All data were analyzed through ANOVA, and the means were reckoned by the LSD Test (p<0.05). The RES, NPM and COT indicators, and all soil quality indices obtained were sensitive to anthropic disturbances and effective enough to quantify soil quality and to assess the effects of land-use changes. Replacing the natural vegetation with Pinus sp. plantations increased soil acidity, decreased respiration rate (23%) and NPM content (70%) and affected organic matter turnover. Forest land-use, hence, resulted in soil degradation and poorer soil quality. [ABSTRACT FROM AUTHOR]

Wastewater-based surveillance (WBS) can track the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in communities. Laboratory methods for this testing involve labor-intensive, multi-step processes. This study assessed the feasibility of performing WBS with an off-label use of an automated commercial SARS-CoV-2 assay that had received Emergency Use Authorization for human diagnostic testing from the United States Food and Drug Administration (FDA EUA). Twenty-four-hour composite samples of primary influent wastewater from seven municipalities in New Hampshire and Vermont were collected between September 2020 and February 2021, and were centrifuged upon receipt. An aliquot of fresh supernatant was immediately tested with the Abbott m 2000 RealTi m e SARS-CoV-2 assay (Abbott Molecular, Des Plaines, IL, USA). Corresponding aliquots were then stored at -80°C until they were thawed, polyethylene glycol (PEG) concentrated, and tested by two PCR-based laboratory-developed tests (LDTs). Wastewater samples (103) were tested with successful detection of SARS-CoV-2 viral RNA by all three methods. Bland-Altman analysis showed overall concordant results with a bias of -0.13 and -0.42 log copies/mL detected by the FDA EUA assay compared to the LDTs. Specimen stability assessment demonstrated a decrease of 33.9% measurable viral RNA after three freeze-thaw cycles. SARS-CoV-2 detection in wastewater using an FDA EUA assay on an automated commercial testing platform performed comparably but with more efficient workflow when compared to two LDTs. This sample-to-answer automated method could save time and labor for surveillance testing, but further validation of its ability to quantitate SARS-CoV-2 viral RNA is necessary.IMPORTANCEThis proof-of-principle study evaluates an off-label use of an automated United States Food and Drug Administration (FDA) Emergency Use Authorization (EUA) severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) human diagnostic assay for wastewater surveillance. Compared to standard, labor-intensive, multi-step methods currently in use for wastewater surveillance testing, an off-label use of an FDA EUA assay on an automated platform offers a sample-to-answer testing requiring less labor and a faster turnaround time.

Wastewater - based epidemiology (WBE) can be used to monitor the community presence of infectious disease pathogens of public health concern such as the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Viral nucleic acid has been detected in the stool of SARS-CoV-2-infected individuals. Asymptomatic SARS-CoV-2 infections make community monitoring difficult without extensive and continuous population screening. In this study, we validated a procedure that includes manual pre-processing, automated SARS-CoV-2 RNA extraction and detection workflows using both reverse-transcriptase quantitative polymerase chain reaction (RT-qPCR) and reverse transcriptase droplet digital PCR (RT-ddPCR). Genomic RNA and calibration materials were used to create known concentrations of viral material to determine the linearity, accuracy, and precision of the wastewater extraction and SARS-CoV-2 RNA detection. Both RT-qPCR and RT-ddPCR perform similarly in all the validation experiments, with a limit of detection of 50 copies/mL. A wastewater sample from a care facility with a known outbreak was assessed for viral content in replicate, and we showed consistent results across both assays. Finally, in a 2-week survey of two New Hampshire cities, we assessed the suitability of our methods for daily surveillance. This paper describes the technical validation of a molecular assay that can be used for long-term monitoring of SARS-CoV-2 in wastewater as a potential tool for community surveillance to assist with public health efforts.IMPORTANCEThis paper describes the technical validation of a molecular assay that can be used for the long-term monitoring of SARS-CoV-2 in wastewater as a potential tool for community surveillance to assist with public health efforts., Competing Interests: J.A.L. is an advisor for Bio-Rad and owns publicly traded stock in Bio-Rad and Thermo Fisher.

Systemic sclerosis (SSc) is an autoimmune disease characterized by skin fibrosis, internal organ involvement and vascular dropout. We previously developed and phenotypically characterized an in vitro 3D skin-like tissue model of SSc, and now analyze the transcriptomic (scRNA-seq) and epigenetic (scATAC-seq) characteristics of this model at single-cell resolution. SSc 3D skin-like tissues were fabricated using autologous fibroblasts, macrophages, and plasma from SSc patients or healthy control (HC) donors. SSc tissues displayed increased dermal thickness and contractility, as well as increased α-SMA staining. Single-cell transcriptomic and epigenomic analyses identified keratinocytes, macrophages, and five populations of fibroblasts (labeled FB1 - 5). Notably, FB1 APOE-expressing fibroblasts were 12-fold enriched in SSc tissues and were characterized by high EGR1 motif accessibility. Pseudotime analysis suggests that FB1 fibroblasts differentiate from a TGF-β1-responsive fibroblast population and ligand-receptor analysis indicates that the FB1 fibroblasts are active in macrophage crosstalk via soluble ligands including FGF2 and APP. These findings provide characterization of the 3D skin-like model at single cell resolution and establish that it recapitulates subsets of fibroblasts and macrophage phenotypes observed in skin biopsies.