Development of a multivariable risk model integrating urinary cell DNA methylation and cell-free RNA data for the detection of significant prostate cancer.

BACKGROUND: Prostate cancer exhibits severe clinical heterogeneity and there is a critical need for clinically implementable tools able to precisely and noninvasively identify patients that can either be safely removed from treatment pathways or those requiring further follow up. Our objectives were to develop a multivariable risk prediction model through the integration of clinical, urine-derived cell-free messenger RNA (cf-RNA) and urine cell DNA methylation data capable of noninvasively detecting significant prostate cancer in biopsy naïve patients. METHODS: Post-digital rectal examination urine samples previously analyzed separately for both cellular methylation and cf-RNA expression within the Movember GAP1 urine biomarker cohort were selected for a fully integrated analysis (n = 207). A robust feature selection framework, based on bootstrap resampling and permutation, was utilized to find the optimal combination of clinical and urinary markers in a random forest model, deemed ExoMeth. Out-of-bag predictions from ExoMeth were used for diagnostic evaluation in men with a clinical suspicion of prostate cancer (PSA ≥ 4 ng/mL, adverse digital rectal examination, age, or lower urinary tract symptoms). RESULTS: As ExoMeth risk score (range, 0-1) increased, the likelihood of high-grade disease being detected on biopsy was significantly greater (odds ratio = 2.04 per 0.1 ExoMeth increase, 95% confidence interval [CI]: 1.78-2.35). On an initial TRUS biopsy, ExoMeth accurately predicted the presence of Gleason score ≥3 + 4, area under the receiver-operator characteristic curve (AUC) = 0.89 (95% CI: 0.84-0.93) and was additionally capable of detecting any cancer on biopsy, AUC = 0.91 (95% CI: 0.87-0.95). Application of ExoMeth provided a net benefit over current standards of care and has the potential to reduce unnecessary biopsies by 66% when a risk threshold of 0.25 is accepted. CONCLUSION: Integration of urinary biomarkers across multiple assay methods has greater diagnostic ability than either method in isolation, providing superior predictive ability of biopsy outcomes. ExoMeth represents a more holistic view of urinary biomarkers and has the potential to result in substantial changes to how patients suspected of harboring prostate cancer are diagnosed.

A four-group urine risk classifier for predicting outcomes in patients with prostate cancer.

OBJECTIVES: To develop a risk classifier using urine-derived extracellular vesicle (EV)-RNA capable of providing diagnostic information on disease status prior to biopsy, and prognostic information for men on active surveillance (AS). PATIENTS AND METHODS: Post-digital rectal examination urine-derived EV-RNA expression profiles (n = 535, multiple centres) were interrogated with a curated NanoString panel. A LASSO-based continuation ratio model was built to generate four prostate urine risk (PUR) signatures for predicting the probability of normal tissue (PUR-1), D'Amico low-risk (PUR-2), intermediate-risk (PUR-3), and high-risk (PUR-4) prostate cancer. This model was applied to a test cohort (n = 177) for diagnostic evaluation, and to an AS sub-cohort (n = 87) for prognostic evaluation. RESULTS: Each PUR signature was significantly associated with its corresponding clinical category (P < 0.001). PUR-4 status predicted the presence of clinically significant intermediate- or high-risk disease (area under the curve = 0.77, 95% confidence interval [CI] 0.70-0.84). Application of PUR provided a net benefit over current clinical practice. In an AS sub-cohort (n = 87), groups defined by PUR status and proportion of PUR-4 had a significant association with time to progression (interquartile range hazard ratio [HR] 2.86, 95% CI 1.83-4.47; P < 0.001). PUR-4, when used continuously, dichotomized patient groups with differential progression rates of 10% and 60% 5 years after urine collection (HR 8.23, 95% CI 3.26-20.81; P < 0.001). CONCLUSION: Urine-derived EV-RNA can provide diagnostic information on aggressive prostate cancer prior to biopsy, and prognostic information for men on AS. PUR represents a new and versatile biomarker that could result in substantial alterations to current treatment of patients with prostate cancer.

Dietary mineral supplies in Africa.

Dietary micronutrient deficiencies (MNDs) are widespread, yet their prevalence can be difficult to assess. Here, we estimate MND risks due to inadequate intakes for seven minerals in Africa using food supply and composition data, and consider the potential of food-based and agricultural interventions. Food Balance Sheets (FBSs) for 46 countries were integrated with food composition data to estimate per capita supply of calcium (Ca), copper (Cu), iron (Fe), iodine (I), magnesium (Mg), selenium (Se) and zinc (Zn), and also phytate. Deficiency risks were quantified using an estimated average requirement (EAR) 'cut-point' approach. Deficiency risks are highest for Ca (54% of the population), followed by Zn (40%), Se (28%) and I (19%, after accounting for iodized salt consumption). The risk of Cu (1%) and Mg (<1%) deficiency are low. Deficiency risks are generally lower in the north and west of Africa. Multiple MND risks are high in many countries. The population-weighted mean phytate supply is 2770 mg capita(-1) day(-1). Deficiency risks for Fe are lower than expected (5%). However, 'cut-point' approaches for Fe are sensitive to assumptions regarding requirements; e.g. estimates of Fe deficiency risks are 43% under very low bioavailability scenarios consistent with high-phytate, low-animal protein diets. Fertilization and breeding strategies could greatly reduce certain MNDs. For example, meeting HarvestPlus breeding targets for Zn would reduce dietary Zn deficiency risk by 90% based on supply data. Dietary diversification or direct fortification is likely to be needed to address Ca deficiency risks.

Applications of Urinary Extracellular Vesicles in the Diagnosis and Active Surveillance of Prostate Cancer.

Prostate cancer is the most common non-cutaneous cancer among men in the UK, causing significant health and economic burdens. Diagnosis and risk prognostication can be challenging due to the genetic and clinical heterogeneity of prostate cancer as well as uncertainties in our knowledge of the underlying biology and natural history of disease development. Urinary extracellular vesicles (EVs) are microscopic, lipid bilayer defined particles released by cells that carry a variety of molecular cargoes including nucleic acids, proteins and other molecules. Urine is a plentiful source of prostate-derived EVs. In this narrative review, we summarise the evidence on the function of urinary EVs and their applications in the evolving field of prostate cancer diagnostics and active surveillance. EVs are implicated in the development of all hallmarks of prostate cancer, and this knowledge has been applied to the development of multiple diagnostic tests, which are largely based on RNA and miRNA. Common gene probes included in multi-probe tests include PCA3 and ERG, and the miRNAs miR-21 and miR-141. The next decade will likely bring further improvements in the diagnostic accuracy of biomarkers as well as insights into molecular biological mechanisms of action that can be translated into opportunities in precision uro-oncology.

Cancer invasion and anaerobic bacteria: new insights into mechanisms.

There is growing evidence that altered microbiota abundance of a range of specific anaerobic bacteria are associated with cancer, including Peptoniphilus spp., Porphyromonas spp., Fusobacterium spp., Fenollaria spp., Prevotella spp., Sneathia spp., Veillonella spp. and Anaerococcus spp. linked to multiple cancer types. In this review we explore these pathogenic associations. The mechanisms by which bacteria are known or predicted to interact with human cells are reviewed and we present an overview of the interlinked mechanisms and hypotheses of how multiple intracellular anaerobic bacterial pathogens may act together to cause host cell and tissue microenvironment changes associated with carcinogenesis and cancer cell invasion. These include combined effects on changes in cell signalling, DNA damage, cellular metabolism and immune evasion. Strategies for early detection and eradication of anaerobic cancer-associated bacterial pathogens that may prevent cancer progression are proposed.

EURRECA-Estimating selenium requirements for deriving dietary reference values.

Current reference values for selenium, an essential micronutrient, are based on the intake of selenium that is required to achieve maximal glutathione peroxidase activity in plasma or erythrocytes. In order to assess the evidence of relevance to setting dietary reference values for selenium, the EURRECA Network of Excellence focused on systematic searches, review, and evaluation of (i) selenium status biomarkers and evidence for relationships between intake and status biomarkers, (ii) selenium and health (including the effect of intake and/or status biomarkers on cancer risk, immune function, HIV, cognition, and fertility), (iii) bioavailability of selenium from the diet, and (iv) impact of genotype/single nucleotide polymorphisms on status or health outcomes associated with selenium. The main research outputs for selenium and future research priorities are discussed further in this review.

EURRECA-Estimating iron requirements for deriving dietary reference values.

Currently, a factorial approach is used to derive reference values for iron. Calculations include the use of a bioavailability factor to convert the physiological requirement, derived from obligatory losses and requirements for growth and development, into a dietary intake value. A series of systematic reviews undertaken by the EURRECA Network of Excellence aimed to identify data that may increase the accuracy of factorial calculations across all population groups. The selection of robust data was guided by the use of standardized review methodology and the evidence-based selection of status biomarkers and dietary intake assessment techniques. Results corroborated the dearth of relevant factorial data, including whole-diet bioavailability data, and confirmed the need to continue extrapolating physiological requirements across population groups. Data were also unavailable that would allow reference values to be based on selected health outcomes associated with iron intake or status. Ideally, a series of observational and randomized controlled trial (RCT) studies need to be undertaken across all population groups and life stages to generate robust data for setting dietary reference values for iron. It will also be essential to include information on polymorphisms that potentially influence iron absorption and status in the derivation process.

EURRECA-Evidence-based methodology for deriving micronutrient recommendations.

The EURopean micronutrient RECommendations Aligned (EURRECA) Network of Excellence explored the process of setting micronutrient recommendations to address the variance in recommendations across Europe. Work centered upon the transparent assessment of nutritional requirements via a series of systematic literature reviews and meta-analyses. In addition, the necessity of assessing nutritional requirements and the policy context of setting micronutrient recommendations was investigated. Findings have been presented in a framework that covers nine activities clustered into four stages: stage one "Defining the problem" describes Activities 1 and 2: "Identifying the nutrition-related health problem" and "Defining the process"; stage two "Monitoring and evaluating" describes Activities 3 and 7: "Establishing appropriate methods," and "Nutrient intake and status of population groups"; stage three "Deriving dietary reference values" describes Activities 4, 5, and 6: "Collating sources of evidence," "Appraisal of the evidence," and "Integrating the evidence"; stage four "Using dietary reference values in policy making" describes Activities 8 and 9: "Identifying policy options," and "Evaluating policy implementation." These activities provide guidance on how to resolve various issues when deriving micronutrient requirements and address the methodological and policy decisions, which may explain the current variation in recommendations across Europe. [Supplementary materials are available for this article. Go to the publisher's online edition of Critical Reviews in Food Science and Nutrition for the following free supplemental files: Additional text, tables, and figures.].

A high prevalence of zinc- but not iron-deficiency among women in rural Malawi: a cross-sectional study.

BACKGROUND: Zinc deficiency is often associated with nutritional iron deficiency (ID), and may be exacerbated by low selenium status. AIM: To investigate risk of iron and zinc deficiency in women with contrasting selenium status. METHODS: In a cross-sectional study, 1-day diet composites and blood samples were collected from self-selected Malawian women aged 18-50 years from low- (Zombwe) (n=60) and high-plant-available soil selenium (Mikalango) (n=60) districts. Diets were analyzed for trace elements and blood for biomarkers. RESULTS: Zinc deficiency (>90 %) was greater than ID anemia (6 %), or ID (5 %), attributed to diets low in zinc (median 5.7 mg/day) with high phytate:zinc molar ratios (20.0), but high in iron (21.0 mg/day) from soil contaminant iron. Zombwe compared to Mikalango women had lower (p<0.05) intakes of selenium (6.5 vs. 55.3 µg/day), zinc (4.8 vs. 6.4 mg/day), iron (16.6 vs. 29.6 mg/day), lower plasma selenium (0.72 vs. 1.60 µmol/L), and higher body iron (5.3 vs. 3.8 mg/kg), although plasma zinc was similar (8.60 vs. 8.87 µmol/L). Body iron and plasma zinc were positive determinants of hemoglobin. CONCLUSION: Risk of zinc deficiency was higher than ID and was shown not to be associated with selenium status. Plasma zinc was almost as important as body iron as a hemoglobin determinant.

Quality Control in Metagenomics Data.

Experiments involving metagenomics data are become increasingly commonplace. Processing such data requires a unique set of considerations. Quality control of metagenomics data is critical to extracting pertinent insights. In this chapter, we outline some considerations in terms of study design and other confounding factors that can often only be realized at the point of data analysis.In this chapter, we outline some basic principles of quality control in metagenomics, including overall reproducibility and some good practices to follow. The general quality control of sequencing data is then outlined, and we introduce ways to process this data by using bash scripts and developing pipelines in Snakemake (Python).A significant part of quality control in metagenomics is in analyzing the data to ensure you can spot relationships between variables and to identify when they might be confounded. This chapter provides a walkthrough of analyzing some microbiome data (in the R statistical language) and demonstrates a few days to identify overall differences and similarities in microbiome data. The chapter is concluded by discussing remarks about considering taxonomic results in the context of the study and interrogating sequence alignments using the command line.

Time Spent at Well-Child Care Visits for English- and Spanish-Speaking Parents.

OBJECTIVE: To measure duration of well-child care (WCC) visits at 2 federally qualified health centers (FQHCs), across 10 clinic sites, and determine if differences exist in visit duration for English- and Spanish-speaking parents. METHODS: Upon arrival to their child's 2- to 24-month well visit, a research team member followed families throughout their visit noting start and end times for a series of 5 WCC visit tasks. The average time to complete each visit task for the entire sample was then calculated. Mann-Whitney U tests were run to determine if task completion time differed significantly between English- and Spanish-speaking parents. RESULTS: The total sample included 199 parents of infants and children between 2 and 24 months old. Over one third of the sample spoke Spanish as their primary language (37%). The average visit time was 77 minutes (standard deviation [SD] = 48). Median time spent with the clinician was 14 minutes (SD = 5). Clinician visit time was significantly different U = 2608, P < .001, r = 0.38 between English- (median = 15 minutes) and Spanish (median = 11 minutes)-speaking parents. No other significant differences were identified. DISCUSSION: Our findings align with previous studies showing the average time spent with a clinician during a WCC visit was 15 minutes. Further, the average time with a clinician was less for Spanish-speaking parents. With limited visit length to address child and family concerns, re-designing the structure and duration of WCC visits is critical to best meet the needs of families living in poverty, and may ensure that Spanish-speaking parents receive appropriate guidance and support without time limitations.

Gene-Transcript Expression in Urine Supernatant and Urine Cell-Sediment Are Different but Equally Useful for Detecting Prostate Cancer.

There is considerable interest in urine as a non-invasive liquid biopsy to detect prostate cancer (PCa). PCa-specific transcripts such as the TMPRSS2:ERG fusion gene can be found in both urine extracellular vesicles (EVs) and urine cell-sediment (Cell) but the relative usefulness of these and other genes in each fraction in PCa detection has not been fully elucidated. Urine samples from 76 men (PCa n = 40, non-cancer n = 36) were analysed by NanoString for 154 PCa-associated genes-probes, 11 tissue-specific, and six housekeeping. Comparison to qRT-PCR data for four genes (PCA3, OR51E2, FOLH1, and RPLP2) was strong (r = 0.51-0.95, Spearman p < 0.00001). Comparing EV to Cells, differential gene expression analysis found 57 gene-probes significantly more highly expressed in 100 ng of amplified cDNA products from the EV fraction, and 26 in Cells (p < 0.05; edgeR). Expression levels of prostate-specific genes (KLK2, KLK3) measured were ~20× higher in EVs, while PTPRC (white-blood Cells) was ~1000× higher in Cells. Boruta analysis identified 11 gene-probes as useful in detecting PCa: two were useful in both fractions (PCA3, HOXC6), five in EVs alone (GJB1, RPS10, TMPRSS2:ERG, ERG_Exons_4-5, HPN) and four from Cell (ERG_Exons_6-7, OR51E2, SPINK1, IMPDH2), suggesting that it is beneficial to fractionate whole urine prior to analysis. The five housekeeping genes were not significantly differentially expressed between PCa and non-cancer samples. Expression signatures from Cell, EV and combined data did not show evidence for one fraction providing superior information over the other.

Dietary requirements for magnesium, but not calcium, are likely to be met in Malawi based on national food supply data.

Mineral malnutrition is widespread in sub-Saharan Africa but its extent is difficult to quantify. Using Malawi as a case study, the aim of this work was to investigate the adequacy of calcium (Ca) and magnesium (Mg) nutrition by combining national food supply and food composition data with a new spatial survey of maize grain. Non-maize dietary sources of Ca and Mg were estimated using existing food supply and composition data. Calcium and Mg concentrations in maize grain were determined at 88 field sites, representing > 75 % of Malawi’s land area in terms of soil classification. Median maize grain concentrations from the survey were 34 and 845 mg kg(-1), representing a per capita supply of 12 and 299 mg d(-1) of Ca and Mg, respectively. Combining these data with food supply and composition data reveals that average Ca nutrition is likely to be inadequate for many individuals, whereas average Mg nutrition appears adequate. Optimal supply of Ca per capita depends critically on balanced food availability and choice. Since maize grain sourced from highly calcareous soils is still unlikely to deliver > 5 % of estimated average requirements, agronomic solutions to rectify Ca malnutrition via maize are limited, in comparison with strategies for dietary diversification.

Microbiomes of Urine and the Prostate Are Linked to Human Prostate Cancer Risk Groups.

BACKGROUND: Bacteria play a suspected role in the development of several cancer types, and associations between the presence of particular bacteria and prostate cancer have been reported. OBJECTIVE: To provide improved characterisation of the prostate and urine microbiome and to investigate the prognostic potential of the bacteria present. DESIGN, SETTING, AND PARTICIPANTS: Microbiome profiles were interrogated in sample collections of patient urine (sediment microscopy: n = 318, 16S ribosomal amplicon sequencing: n = 46; and extracellular vesicle RNA-seq: n = 40) and cancer tissue (n = 204). OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Microbiomes were assessed using anaerobic culture, population-level 16S analysis, RNA-seq, and whole genome DNA sequencing. RESULTS AND LIMITATIONS: We demonstrate an association between the presence of bacteria in urine sediments and higher D'Amico risk prostate cancer (discovery, n = 215 patients, p < 0.001; validation, n = 103, p < 0.001, χ2 test for trend). Characterisation of the bacterial community led to the (1) identification of four novel bacteria (Porphyromonas sp. nov., Varibaculum sp. nov., Peptoniphilus sp. nov., and Fenollaria sp. nov.) that were frequently found in patient urine, and (2) definition of a patient subgroup associated with metastasis development (p = 0.015, log-rank test). The presence of five specific anaerobic genera, which includes three of the novel isolates, was associated with cancer risk group, in urine sediment (p = 0.045, log-rank test), urine extracellular vesicles (p = 0.039), and cancer tissue (p = 0.035), with a meta-analysis hazard ratio for disease progression of 2.60 (95% confidence interval: 1.39-4.85; p = 0.003; Cox regression). A limitation is that functional links to cancer development are not yet established. CONCLUSIONS: This study characterises prostate and urine microbiomes, and indicates that specific anaerobic bacteria genera have prognostic potential. PATIENT SUMMARY: In this study, we investigated the presence of bacteria in patient urine and the prostate. We identified four novel bacteria and suggest a potential prognostic utility for the microbiome in prostate cancer.

A Parent Coach-Led Model of Well-Child Care for Young Children in Low-Income Communities: Protocol for a Cluster Randomized Controlled Trial.

BACKGROUND: The Parent-focused Redesign for Encounters, Newborns to Toddlers (PARENT) intervention was created as a team-based approach to well-child care (WCC) that relies on a health educator (Parent Coach) to provide the bulk of WCC services, address specific needs faced by families in low-income communities, and decrease reliance on the clinician as the primary provider of WCC services. OBJECTIVE: This study aims to evaluate the impact of PARENT using a cluster randomized controlled trial. METHODS: This study tested the effectiveness of PARENT at 10 clinical sites in 2 federally qualified health centers in Tacoma, Washington, and Los Angeles, California. We conducted a cluster randomized controlled trial that included 916 families with children aged ≤12 months at the time of the baseline survey. Parents will be followed up at 6 and 12 months after enrollment. The Parent Coach, the main element of PARENT, provides anticipatory guidance, psychosocial screening and referral, developmental and behavioral surveillance, screening, and guidance at each WCC visit. The coach is supported by parent-focused previsit screening and visit prioritization, a brief, problem-focused clinician encounter for a physical examination and any concerns that require a clinician's attention, and an automated text message parent reminder and education service for periodic, age-specific messages to reinforce key health-related information recommended by Bright Futures national guidelines. We will examine parent-reported quality of care (receipt of nationally recommended WCC services, family-centeredness of care, and parental experiences of care), and health care use (WCC, urgent care, emergency department, and hospitalizations), conduct a cost analysis, and conduct a separate time-motion study of clinician time allocation to assess efficiency. We will also collect data on exploratory measures of parent-and parenting-focused outcomes. Our primary outcomes were receipt of anticipatory guidance and emergency department use. RESULTS: Participant recruitment began in March 2019. After recruitment, 6- and 12-month follow-up surveys will be completed. As of August 30, 2021, we enrolled a total of 916 participants. CONCLUSIONS: This large pragmatic trial of PARENT in partnership with federally qualified health centers will assess its utility as an evidence-based and financially sustainable model for the delivery of preventive care services to children in low-income communities. TRIAL REGISTRATION: ClinicalTrials.gov: NCT03797898; https://clinicaltrials.gov/ct2/show/NCT03797898. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/27054.

The Urine Biomarker PUR-4 Is Positively Associated with the Amount of Gleason 4 in Human Prostate Cancers.

The Prostate Urine Risk (PUR) biomarker is a four-group classifier for predicting outcome in patients prior to biopsy and for men on active surveillance. The four categories correspond to the probabilities of the presence of normal tissue (PUR-1), D'Amico low-risk (PUR-2), intermediate-risk (PUR-3), and high-risk (PUR-4) prostate cancer. In the current study we investigate how the PUR-4 status is linked to Gleason grade, prostate volume, and tumor volume as assessed from biopsy (n = 215) and prostatectomy (n = 9) samples. For biopsy data PUR-4 status alone was linked to Gleason Grade group (GG) (Spearman's, ρ = 0.58, p < 0.001 trend). To assess the impact of tumor volume each GG was dichotomized into Small and Large volume cancers relative to median volume. For GG1 (Gleason Pattern 3 + 3) cancers volume had no impact on PUR-4 status. In contrast for GG2 (3 + 4) and GG3 (4 + 3) cancers PUR-4 levels increased in large volume cancers with statistical significance observed for GG2 (p = 0.005; Games-Howell). These data indicated that PUR-4 status is linked to the presence of Gleason Pattern 4. To test this observation tumor burden and Gleason Pattern were assessed in nine surgically removed and sectioned prostates allowing reconstruction of 3D maps. PUR-4 was not correlated with Gleason Pattern 3 amount, total tumor volume or prostate size. A strong correlation was observed between amount of Gleason Pattern 4 tumor and PUR-4 signature (r = 0.71, p = 0.034, Pearson's). These observations shed light on the biological significance of the PUR biomarker and support its use as a non-invasive means of assessing the presence of clinically significant prostate cancer.

Methodology for the at-home collection of urine samples for prostate cancer detection.

Urine from patients with prostate cancer (PCa) contains gene transcripts that have been used for PCa diagnosis and prognosis. Historically, patient urine samples have been collected after a digital rectal examination of the prostate, which was thought necessary to boost the levels of prostatic secretions in the urine. We herein describe methodology that allows urine to be collected by patients at home and then posted to a laboratory for analysis. RNA yields and quality were comparable to those for post digital rectal examination urine, and there was improved sensitivity for the detection of TMPRSS2:ERG transcripts by RT-PCR. The At-Home collection protocol has opened up the potential to perform large-scale PCa studies without the inconvenience, cost, discomfort and expense of patients having to visit the clinic.

Protocols for Personal Protective Equipment in a COVID-19 Medical Shelter.

The coronavirus disease 2019 (COVID-19) has greatly impacted health-care systems worldwide, leading to an unprecedented rise in demand for health-care resources. In anticipation of an acute strain on established medical facilities in Dallas, Texas, federal officials worked in conjunction with local medical personnel to convert a convention center into a Federal Medical Station capable of caring for patients affected by COVID-19. A 200,000 square foot event space was designated as a direct patient care area, with surrounding spaces repurposed to house ancillary services. Given the highly transmissible nature of the novel coronavirus, the donning and doffing of personal protective equipment (PPE) was of particular importance for personnel staffing the facility. Furthermore, nationwide shortages in the availability of PPE necessitated the reuse of certain protective materials. This article seeks to delineate the procedures implemented regarding PPE in the setting of a COVID-19 disaster response shelter, including workspace flow, donning and doffing procedures, PPE conservation, and exposure event protocols.

Cytotoxicity testing of multipurpose contact lens solutions using monolayer and stratified cultures of human corneal epithelial cells.

OBJECTIVE: To investigate in vitro cytotoxicity of five marketed multipurpose contact lens solutions (MPS) on the morphology, viability, and barrier function of monolayer and stratified human corneal-limbal epithelial cells. METHODS: Cells were exposed to MPS for 10, 20, or 60 minutes. In monolayer cultures, effects of the MPS on cell morphology were observed using Hoffman modulation contrast microscopy. Cell proliferation after exposure to MPS was evaluated and cytotoxicity of the MPS was determined using a live/dead cell assay and flow cytometry. In stratified cultures, multilayer corneal epithelial constructs were established on membrane inserts. Effects of the MPS on the morphology and barrier function of stratified cultures were determined using microscopy, a fluorescein permeability test, and measurement of trans-epithelial resistance. RESULTS: In monolayer cultures, none of the MPS damaged cells during a 10-min exposure. All of the MPS had varying time-dependent adverse effects on cell morphology, viability, and proliferation during 20- and 60-min exposures. In stratified cultures, none of the MPS had an adverse effect on the structure or barrier function of stratified cultures. CONCLUSIONS: Monolayer cultures are highly sensitive to damage by MPS. In contrast, because stratified human corneal-limbal epithelial cultures are resistant to adverse effects of MPS, it is suggested that models that simulate the stratified structure of the corneal epithelium should be used for in vitro toxicologic testing. Caution should be used when interpreting such studies, because in vitro tests may not be predictive of clinical responses to contact lens products that are known to be safe when used as directed.

SEPATH: benchmarking the search for pathogens in human tissue whole genome sequence data leads to template pipelines.

BACKGROUND: Human tissue is increasingly being whole genome sequenced as we transition into an era of genomic medicine. With this arises the potential to detect sequences originating from microorganisms, including pathogens amid the plethora of human sequencing reads. In cancer research, the tumorigenic ability of pathogens is being recognized, for example, Helicobacter pylori and human papillomavirus in the cases of gastric non-cardia and cervical carcinomas, respectively. As of yet, no benchmark has been carried out on the performance of computational approaches for bacterial and viral detection within host-dominated sequence data. RESULTS: We present the results of benchmarking over 70 distinct combinations of tools and parameters on 100 simulated cancer datasets spiked with realistic proportions of bacteria. mOTUs2 and Kraken are the highest performing individual tools achieving median genus-level F1 scores of 0.90 and 0.91, respectively. mOTUs2 demonstrates a high performance in estimating bacterial proportions. Employing Kraken on unassembled sequencing reads produces a good but variable performance depending on post-classification filtering parameters. These approaches are investigated on a selection of cervical and gastric cancer whole genome sequences where Alphapapillomavirus and Helicobacter are detected in addition to a variety of other interesting genera. CONCLUSIONS: We provide the top-performing pipelines from this benchmark in a unifying tool called SEPATH, which is amenable to high throughput sequencing studies across a range of high-performance computing clusters. SEPATH provides a benchmarked and convenient approach to detect pathogens in tissue sequence data helping to determine the relationship between metagenomics and disease.