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Simple Summary: Although the anticancer effects of metformin are well studied, its effect on energy metabolism of cancer cells remains elusive. Metformin can alter the metabolism of cells either by activating AMPK or inhibiting the mitochondrial respiratory chain complex. The aim of the study was to explore the distinct metabolic profiles of ovarian cancer cell lines post-metformin treatment and to understand metformin's metabolism-based anti-growth effect on ovarian cancer cell lines. In this study, using the untargeted metabolomics approach, we found that metformin treatment promoted omega-3 fatty acid metabolism in three different ovarian cancer cell lines, and treating ovarian xenografts with specific omega-3 fatty acids, especially EPA, reduced ovarian tumor growth. Thus, our study adds an additional potential therapeutic mechanism to the multi-potent anticancer effects of metformin. Metformin is being actively repurposed for the treatment of gynecologic malignancies including ovarian cancer. We investigated if metformin induces analogous metabolic changes across ovarian cancer cells. Functional metabolic analysis showed metformin caused an immediate and sustained decrease in oxygen consumption while increasing glycolysis across A2780, C200, and SKOV3ip cell lines. Untargeted metabolomics showed metformin to have differential effects on glycolysis and TCA cycle metabolites, while consistent increased fatty acid oxidation intermediates were observed across the three cell lines. Metabolite set enrichment analysis showed alpha-linolenic/linoleic acid metabolism as being most upregulated. Downstream mediators of the alpha-linolenic/linoleic acid metabolism, eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), were abundant in all three cell lines. EPA was more effective in inhibiting SKOV3 and CaOV3 xenografts, which correlated with inhibition of inflammatory markers and indicated a role for EPA-derived specialized pro-resolving mediators such as Resolvin E1. Thus, modulation of the metabolism of omega-3 fatty acids and their anti-inflammatory signaling molecules appears to be one of the common mechanisms of metformin's antitumor activity. The distinct metabolic signature of the tumors may indicate metformin response and aid the preclinical and clinical interpretation of metformin therapy in ovarian and other cancers. [ABSTRACT FROM AUTHOR]

We performed untargeted metabolomics in plasma of B6 mice with experimental autoimmune encephalitis (EAE) at the chronic phase of the disease in search of an altered metabolic pathway(s). Of 324 metabolites measured, 100 metabolites that mapped to various pathways (mainly lipids) linked to mitochondrial function, inflammation, and membrane stability were observed to be significantly altered between EAE and control (p < 0.05, false discovery rate <0.10). Bioinformatics analysis revealed six metabolic pathways being impacted and altered in EAE, including α-linolenic acid and linoleic acid metabolism (PUFA). The metabolites of PUFAs, includingω-3 andω-6 fatty acids, are commonly decreased in mouse models of multiple sclerosis (MS) and in patients with MS. Daily oral administration of resolvin D1, a downstream metabolite ofω-3, decreased disease progression by suppressing autoreactive T cells and inducing an M2 phenotype of monocytes/macrophages and resident brain microglial cells. This study provides a proof of principle for the application of metabolomics to identify an endogenous metabolite(s) possessing drug-like properties, which is assessed for therapy in preclinical mouse models of MS. [ABSTRACT FROM AUTHOR]

Background: Acquisition of metabolic alterations has been shown to be essential for the unremitting growth of cancer, yet the relation of such alterations to chemosensitivity has not been investigated. In the present study our aim was to identify the metabolic alterations that are specifically associated with platinum resistance in ovarian cancer. A global metabolic analysis of the A2780 platinum-sensitive and its platinum-resistant derivative C200 ovarian cancer cell line was performed utilizing ultra-high performance liquid chromatography/mass spectroscopy and gas chromatography/mass spectroscopy. Per-metabolite comparisons were made between cell lines and an interpretive analysis was carried out using the Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic library and the Ingenuity exogenous molecule library. Results: We observed 288 identified metabolites, of which 179 were found to be significantly different (t-test p < 0.05) between A2780 and C200 cells. Of these, 70 had increased and 109 had decreased levels in platinum resistant C200 cells. The top altered KEGG pathways based on number or impact of alterations involved the cysteine and methionine metabolism. An Ingenuity Pathway Analysis also revealed that the methionine degradation super-pathway and cysteine biosynthesis are the top two canonical pathways affected. The highest scoring network of altered metabolites was related to carbohydrate metabolism, energy production, and small molecule biochemistry. Compilation of KEGG analysis and the common network molecules revealed methionine and associated pathways of glutathione synthesis and polyamine biosynthesis to be most significantly altered. Conclusion: Our findings disclose that the chemoresistant C200 ovarian cancer cells have distinct metabolic alterations that may contribute to its platinum resistance. This distinct metabolic profile of platinum resistance is a first step towards biomarker development for the detection of chemoresistant disease and metabolism-based drug targets specific for chemoresistant tumors. [ABSTRACT FROM AUTHOR]

The high-mobility group-box transcription factor sex-determining region Y-box 2 (Sox2) is essential for the maintenance of stem cells from early development to adult tissues. Sox2 can reprogram differentiated cells into pluripotent cells in concert with other factors and is overexpressed in various cancers. In glioblastoma (GBM), Sox2 is a marker of cancer stemlike cells (CSCs) in neurosphere cultures and is associated with the proneural molecular subtype. Here, we report that Sox2 expression pattern in GBM tumors and patient-derived mouse xenografts is not restricted to a small percentage of cells and is coexpressed with various lineage markers, suggesting that its expression extends beyond CSCs to encompass more differentiated neoplastic cells across molecular subtypes. Employing a CSC derived from a patient with GBM and isogenic differentiated cell model, we show that Sox2 knockdown in the differentiated state abolished dedifferentiation and acquisition of CSC phenotype. Furthermore, Sox2 deficiency specifically impaired the astrocytic component of a biphasic gliosarcoma xenograft model while allowing the formation of tumors with sarcomatous phenotype. The expression of genes associated with stem cells and malignancy were commonly downregulated in both CSCs and serum-differentiated cells on Sox2 knockdown. Genes previously shown to be associated with pluripontency and CSCs were only affected in the CSC state, whereas embryonic stem cell self-renewal genes and cytokine signaling were downregulated, and the Wnt pathway activated in differentiated Sox2-deficient cells. Our results indicate that Sox2 regulates the expression of key genes and pathways involved in GBM malignancy, in both cancer stemlike and differentiated cells, and maintains plasticity for bidirectional conversion between the two states, with significant clinical implications. [ABSTRACT FROM AUTHOR]

There is increasing interest in using the heterogeneity of tissue properties in a bone for predicting its fracture risk. Heterogeneity of volumetric bone mineral density (BMD) as measured from quantitative computed tomography (QCT) is of particular interest as these measurements are clinically feasible. Previous examinations of the relationship between the BMD heterogeneity and the mechanical behavior of human vertebrae only considered quasistatic strength and were with limited number of samples. McCubbrey et al. (1995) studied the value of regional BMDs for predicting vertebral fatigue life, determined from short-cycle tests at force levels scaled with the estimated strength of the vertebra, but the focus of that work was in best predictor subsets without a specific focus on the heterogeneity of BMD or the positive vs negative direction of the relationships. The previous analysis also did not take into account the censored nature of the fatigue life data. As such, whether BMD heterogeneity is positively or negatively associated with fatigue life and whether this is independent of the average or minimum BMD are not clear. In the present work, we revisited the McCubbrey data for a preliminary examination of the relationship between BMD heterogeneity and fatigue life using survival analysis. The analysis suggests that BMD heterogeneity measured as the intra-vertebral standard deviation of BMDs in a vertebra is negatively associated with short cycle (high-amplitude) fatigue life independent of the average BMD. The results motivate further studies on the role of BMD heterogeneity in fatigue failure and clinical fracture risk of human vertebrae. [ABSTRACT FROM AUTHOR]

Abstract: We explore the utility of p-value weighting for enhancing the power to detect differential metabolites in a two-sample setting. Related gene expression information is used to assign an a priori importance level to each metabolite being tested. We map the gene expression to a metabolite through pathways and then gene expression information is summarized per-pathway using gene set enrichment tests. Through simulation we explore four styles of enrichment tests and four weight functions to convert the gene information into a meaningful p-value weight. We implement the p-value weighting on a prostate cancer metabolomic dataset. Gene expression on matched samples is used to construct the weights. Under certain regulatory conditions, the use of weighted p-values does not inflate the type I error above what we see for the un-weighted tests except in high correlation situations. The power to detect differential metabolites is notably increased in situations with disjoint pathways and shows moderate improvement, relative to the proportion of enriched pathways, when pathway membership overlaps. [Copyright &y& Elsevier]

Multiple, complex molecular events characterize cancer development and progression. Deciphering the molecular networks that distinguish organ-confined disease from metastatic disease may lead to the identification of critical biomarkers for cancer invasion and disease aggressiveness. Although gene and protein expression have been extensively profiled in human tumours, little is known about the global metabolomic alterations that characterize neoplastic progression. Using a combination of high-throughput liquid-and-gas-chromatography-based mass spectrometry, we profiled more than 1,126 metabolites across 262 clinical samples related to prostate cancer (42 tissues and 110 each of urine and plasma). These unbiased metabolomic profiles were able to distinguish benign prostate, clinically localized prostate cancer and metastatic disease. Sarcosine, an N-methyl derivative of the amino acid glycine, was identified as a differential metabolite that was highly increased during prostate cancer progression to metastasis and can be detected non-invasively in urine. Sarcosine levels were also increased in invasive prostate cancer cell lines relative to benign prostate epithelial cells. Knockdown of glycine-N-methyl transferase, the enzyme that generates sarcosine from glycine, attenuated prostate cancer invasion. Addition of exogenous sarcosine or knockdown of the enzyme that leads to sarcosine degradation, sarcosine dehydrogenase, induced an invasive phenotype in benign prostate epithelial cells. Androgen receptor and the ERG gene fusion product coordinately regulate components of the sarcosine pathway. Here, by profiling the metabolomic alterations of prostate cancer progression, we reveal sarcosine as a potentially important metabolic intermediary of cancer cell invasion and aggressivity. [ABSTRACT FROM AUTHOR]

Abstract: With the development of new technologies for assaying biological activity on a global basis in experimental samples, various new “-omics” signatures have been developed to predict disease progression. Such signatures hold the potential to alter the nature of clinical management of human disease. In this article, we describe some necessary statistical considerations needed to take these signatures from the discovery phase to a clinically useful assay. Much of the work discussed is in the area of cancer. [Copyright &y& Elsevier]

Background: Family-based association testing is an important part of genetic epidemiology. Tests are available to include multiple siblings, unaffected offspring, and to adjust for environmental covariates. We explore a susceptibility residual method of adjustment for covariates. Results: Through simulation, we show that environmental adjustments that down-weight persons who are "destined" to be affected decrease the power to detect genetic association. We used the residual adjusted method on the Framingham Heart Study offspring data, provided for Genetic Analysis Workshop 13, and got mixed results. Conclusion: When the genetic effect and environmental effects are independent, a susceptibility residual method of adjustment for environmental covariates reduces the power of the association test. Further study is necessary to determine if residual adjustment is appropriate in more complex disease models. [ABSTRACT FROM AUTHOR]

Background: Gene × environment models are widely used to assess genetic and environmental risks and their association with a phenotype of interest for many complex diseases. Mixed generalized linear models were used to assess gene ×environment interactions with respect to systolic blood pressure on sibships adjusting for repeated measures and hierarchical nesting structures. A data set containing 410 sibships from the Framingham Heart Study offspring cohort (part of the Genetic Analysis Workshop 13 data) was used for all analyses. Three mixed gene × environment models, all adjusting for repeated measurement and varying levels of nesting, were compared for precision of estimates: 1) all sibships with adjustment for two levels of nesting (sibs within sibships and sibs within pedigrees), 2) all sibships with adjustment for one level of nesting (sibs within sibships), and 3) 100 data sets containing random draws of one sibship per extended pedigree adjusting for one level of nesting. Results: The main effects were: gender, baseline age, body mass index (BMI), hypertensive treatment, cigarettes per day, grams of alcohol per day, and marker GATA48G07A. The interaction fixed effects were: baseline age by gender, baseline age by cigarettes per day, baseline age by hypertensive treatment, baseline age by BMI, hypertensive treatment by BMI, and baseline age by marker GATA48G07A. The estimates for all three nesting techniques were not widely discrepant, but precision of estimates and determination of significant effects did change with the change in adjustment for nesting. Conclusion: Our results show the importance of the adjustment for all levels of hierarchical nesting of sibs in the presence of repeated measures. [ABSTRACT FROM AUTHOR]

Data‐intensive research continues to expand with the goal of improving healthcare delivery, clinical decision‐making, and patient outcomes. Quantitative scientists, such as biostatisticians, epidemiologists, and informaticists, are tasked with turning data into health knowledge. In academic health centres, quantitative scientists are critical to the missions of biomedical discovery and improvement of health. Many academic health centres have developed centralized Quantitative Science Units which foster dual goals of professional development of quantitative scientists and producing high quality, reproducible domain research. Such units then develop teams of quantitative scientists who can collaborate with researchers. However, existing literature does not provide guidance on how such teams are formed or how to manage and sustain them. Leaders of Quantitative Science Units across six institutions formed a working group to examine common practices and tools that can serve as best practices for Quantitative Science Units that wish to achieve these dual goals through building long‐term partnerships with researchers. The results of this working group are presented to provide tools and guidance for Quantitative Science Units challenged with developing, managing, and evaluating Quantitative Science Teams. This guidance aims to help Quantitative Science Units effectively participate in and enhance the research that is conducted throughout the academic health centre—shaping their resources to fit evolving research needs. [ABSTRACT FROM AUTHOR]

A correction to the article "Metabolomic profiles delineate potential role for sarcosine in prostate cancer progression" that was published in a 2009 issue of the periodical is presented.

Metabolic aberrations impact the pathogenesis of multiple sclerosis (MS) and possibly can provide clues for new treatment strategies. Using untargeted metabolomics, we measured serum metabolites from 35 patients with relapsing-remitting multiple sclerosis (RRMS) and 14 healthy age-matched controls. Of 632 known metabolites detected, 60 were significantly altered in RRMS. Bioinformatics analysis identified an altered metabotype in patients with RRMS, represented by four changed metabolic pathways of glycerophospholipid, citrate cycle, sphingolipid, and pyruvate metabolism. Interestingly, the common upstream metabolic pathway feeding these four pathways is the glycolysis pathway. Real-time bioenergetic analysis of the patient-derived peripheral blood mononuclear cells showed enhanced glycolysis, supporting the altered metabolic state of immune cells. Experimental autoimmune encephalomyelitis mice treated with the glycolytic inhibitor 2-deoxy-D-glucose ameliorated the disease progression and inhibited the disease pathology significantly by promoting the antiinflammatory phenotype of monocytes/macrophage in the central nervous system. Our study provided a proof of principle for how a blood-based metabolomic approach using patient samples could lead to the identification of a therapeutic target for developing potential therapy. [ABSTRACT FROM AUTHOR]

Objective: Examine the effect of a universal facemask policy for healthcare workers (HCW) and incidence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positivity. Methods: Daily number of symptomatic HCW tested, SARS-CoV-2 positivity rates, and HCW job-descriptions were collected pre and post Universal HCW facemask policy (March 26, 2020). Multiple change point regression was used to model positive-test-rate data. SARS-CoV-2 testing and positivity rates were compared for pre-intervention, transition, post-intervention, and follow-up periods. Results: Between March 12 and August 10, 2020, 19.2% of HCW were symptomatic for COVID-19 and underwent SARS-CoV-2 testing. A single change point was identified-March 28-30 (95% probability). Before the change point, the odds of a tested HCW having a positive result doubled every 4.5 to 7.5 days. Post-change-point, the odds of a tested HCW having a positive result halved every 10.5 to 13.5 days. Conclusions: Universal facemasks were associated with reducing HCW's risk of acquiring COVID-19. [ABSTRACT FROM AUTHOR]

Background: Clinically relevant glioma subtypes, such as the glioma-CpG island methylator phenotype (G-CIMP), have been defined by epigenetics. In this study, the role of long non-coding RNAs in association with the poor-prognosis G-CMIP-low phenotype and the good-prognosis G-CMIP-high phenotype was investigated. Functional associations of lncRNAs with mRNAs and miRNAs were examined to hypothesize influencing factors of the aggressive phenotype.Methods: RNA-seq data on 250 samples from TCGA's Pan-Glioma study, quantified for lncRNA and mRNAs (GENCODE v28), were analyzed for differential expression between G-CIMP-low and G-CIMP-high phenotypes. Functional interpretation of the differential lncRNAs was performed by Ingenuity Pathway Analysis. Spearman rank order correlation estimates between lncRNA, miRNA, and mRNA nominated differential lncRNA with a likely miRNA sponge function.Results: We identified 4371 differentially expressed features (mRNA = 3705; lncRNA = 666; FDR ≤ 5%). From these, the protein-coding gene TP53 was identified as an upstream regulator of differential lncRNAs PANDAR and PVT1 (p = 0.0237) and enrichment was detected in the "development of carcinoma" (p = 0.0176). Two lncRNAs (HCG11, PART1) were positively correlated with 342 mRNAs, and their correlation estimates diminish after adjusting for either of the target miRNAs: hsa-miR-490-3p, hsa-miR-129-5p. This suggests a likely sponge function for HCG11 and PART1.Conclusions: These findings identify differential lncRNAs with oncogenic features that are associated with G-CIMP phenotypes. Further investigation with controlled experiments is needed to confirm the molecular relationships. [ABSTRACT FROM AUTHOR]

Background: Public Health policies related to social distancing efforts during the COVID-19 pandemic helped slow the infection rate. However, individual-level factors associated with social distancing are largely unknown. We sought to examine social distancing during the COVID-19 pandemic in Michigan, an infection "hotspot" state in the United States early in the pandemic.Methods: Two surveys were distributed to Michigan residents via email lists and social media following COVID-19 related state mandates in March; 45,691 adults responded to the first survey and 8512 to the second. Staying home ≥ 3 out of 5 previous days defined having more social distancing. Logistic regression models were used to examine potential factors associated with more social distancing.Results: Most respondents were women (86% in Survey 1, 87% in Survey 2). In Survey 1, 63% reported more social distancing, increasing to 78% in Survey 2. Female sex and having someone (or self) sick in the home were consistently associated with higher social distancing, while increasing age was positively associated in Survey 1 but negatively associated in Survey 2. Most respondents felt social distancing policies were important (88% in Survey 1; 91% in Survey 2).Conclusions: Michiganders responding to the surveys were both practicing and supportive of social distancing. State-level executive orders positively impacted behaviors early in the COVID-19 pandemic in Michigan. Additional supports are needed to help vulnerable populations practice social distancing, including older individuals. [ABSTRACT FROM AUTHOR]

Purpose: There is variability in survival within IDH mutant gliomas determined by chromosomal events. Copy number variation (CNV) abundance associated with survival in low-grade and IDH mutant astrocytoma has been reported. Our purpose was to correlate the extent of genome-wide CNV abundance in IDH mutant astrocytomas with MRI features. Methods: Presurgical MRI and CNV plots derived from Illumina 850k EPIC DNA methylation arrays of 18 cases of WHO grade II–IV IDH mutant astrocytomas were reviewed. IDH mutant astrocytomas were divided into CNV stable group (CNV-S) with ≤ 3 chromosomal gains or losses and lack of focal gene amplifications and CNV unstable group (CNV-U) with > 3 large chromosomal gains/losses and/or focal amplifications. The associations between MR features, relative cerebral blood volume (rCBV), CNV abundance, and time to progression were assessed. Tumor rCBV estimates were obtained using DSC T2* perfusion analysis. Results: There were nine (50%) CNV-S and nine (50%) CNV-U IDH mutant astrocytomas. CNV-U tumors showed larger mean tumor size (P = 0.004) and maximum diameter on FLAIR (P = 0.004) and also demonstrated significantly higher median rCBV than CNV-S tumors (2.62 vs 0.78, P = 0.019). CNV-U tumors tended to have shorter time to progression although without statistical significance (P = 0.393). Conclusions: Larger size/diameter and higher rCBVs were seen associated CNV-U astrocytomas, suggesting a correlation of aggressive imaging phenotype with unstable and aggressive genotype in IDH mutant astrocytomas. [ABSTRACT FROM AUTHOR]

Both the induction of SPARC expression and the loss of the p53 tumor suppressor gene are changes that occur early in glioma development. Both SPARC and p53 regulate glioma cell survival by inverse effects on apoptotic signaling. Therefore, during glioma formation, the upregulation of SPARC may cooperate with the loss of p53 to enhance cell survival. This study determined whether the loss of Sparc in astrocytes that are null for p53 would result in reduced cell survival and tumor formation and increased tumor immunogenicity in an in vivo xenograft brain tumor model. In vitro, the loss of S parc in p53-null astrocytes resulted in an increase in cell proliferation, but a loss of tumorigenicity. At 7 days after intracranial implantation, Sparc-null tumors had decreased tumor cell survival, proliferation and reduced tumor size. The loss of Sparc promoted microglia/macrophage activation and phagocytosis of tumor cells. Our results indicate that the loss of p53 by deletion/mutation in the early stages of glioma formation may cooperate with the induction of SPARC to potentiate cancer cell survival and escape from immune surveillance. [ABSTRACT FROM AUTHOR]

Objective: Glioblastoma (GBM) is a heterogeneous neoplasm with a small percentage of long-term survivors. Despite aggressive surgical resection and advances in radiotherapy and chemotherapy, the median survival for patients with GBM is 12-14 months. Factors associated with a favorable prognosis include young age, high performance status, gross resection >98%, non-eloquent tumor location and O6-methylguanine methyltransferase (MGMT) promoter methylation. We retrospectively analyzed the relationship of clinical, epidemiologic, genetic and molecular characteristics with survival in patients with GBM. Methods: This retrospective analysis of overall survival looked at the outcomes of 480 patients diagnosed with GBM over 14 years at a single institution. Multivariate analysis was performed examining multiple patient characteristics. Results: Median survival time improved from 11.8 months in patients diagnosed from 1995 to 1999 to 15.9 months in those diagnosed from 2005 to 2008. Factors associated with survivor groups were age, KPS, tumor resection, treatment received and early progression. 18 cancer-related genes were upregulated in short-term survivors and five genes were downregulated in short-term survivors. Conclusions: Epidemiologic, clinical, and molecular characteristics all contribute to GBM prognosis. Identifying factors associated with survival is important for treatment strategies as well as research for novel therapeutics and technologies. This study demonstrated improved survival for patients over time as well as significant differences among survivor groups. [ABSTRACT FROM AUTHOR]

Glioblastomas (GBM), the most common and aggressive type of malignant glioma, are characterized by increased invasion into the surrounding brain tissues. Despite intensive therapeutic strategies, the median survival of GBM patients has remained dismal over the last decades. In this study we examined the expression of miR-145 in glial tumors and its function in glioma cells. Using TCGA analysis and real-time PCR we found that the expression of miR-145/143 cluster was downregulated in astrocytic tumors compared to normal brain specimens and in glioma cells and glioma stem cells (GSCs) compared to normal astrocytes and neural stem cells. Moreover, the low expression of both miR-145 and miR-143 in GBM was correlated with poor patient prognosis. Transfection of glioma cells with miR-145 mimic or transduction with a lentivirus vector expressing pre-miR 145 significantly decreased the migration and invasion of glioma cells. We identified connective tissue growth factor (CTGF) as a novel target of miR-145 in glioma cells; transfection of the cells with this miRNA decreased the expression of CTGF as determined by Western blot analysis and the expression of its 3′-UTR fused to luciferase. Overexpression of a CTGF plasmid lacking the 3′-UTR and administration of recombinant CTGF protein abrogated the inhibitory effect of miR-145 on glioma cell migration. Similarly, we found that silencing of CTGF decreased the migration of glioma cells. CTGF silencing also decreased the expression of SPARC, phospho-FAK and FAK and overexpression of SPARC abrogated the inhibitory effect of CTGF silencing on cell migration. These results demonstrate that miR-145 is downregulated in glial tumors and its low expression in GBM predicts poor patient prognosis. In addition miR-145 regulates glioma cell migration by targeting CTGF which downregulates SPARC expression. Therefore, miR-145 is an attractive therapeutic target for anti-invasive treatment of astrocytic tumors. [ABSTRACT FROM AUTHOR]

MicroRNAs (miRNAs) are recently discovered small non-coding RNAs and can serve as serum biomarkers for disease diagnosis and prognoses. Lack of reliable serum miRNA endogenous references for normalization in miRNA gene expression makes single miRNA assays inaccurate. Using TaqMan® real-time PCR miRNA arrays with a global gene expression normalization strategy, we have analyzed serum miRNA expression profiles of 20 female mice of NOD/ShiLtJ (n = 8), NOR/LtJ (n = 6), and C57BL/6J (n = 6) at different ages and disease conditions. We identified five miRNAs, miR-146a, miR-16, miR-195, miR-30e and miR-744, to be stably expressed in all strains, which could serve as mouse serum miRNA endogenous references for single assay experiments. [ABSTRACT FROM AUTHOR]

(1) Background: Outcomes with coronavirus disease 2019 (COVID-19) have been worse in those with comorbidities and amongst minorities. In our study, we describe outcomes amongst cancer patients in Detroit, a major COVID-19 hotspot with a predominant inner-city population. (2) Methods: We retrospectively analyzed 85 patients with active invasive cancers who were infected with COVID-19. The primary outcome was death or transition to hospice. (3) Results: The majority were males (55.3%, n = 47), ≤70 years old (58.5%, n = 50), and African Americans (65.5%, n = 55). The most common primary site was prostate (18.8%, n = 16). Inpatient admission was documented in 85.5% (n = 73), ICU admission in 35.3% (n = 30), and primary outcome in 43.8% (n = 32) of hospitalized patients. On a multivariate analysis, factors associated with increased odds of a primary outcome included an age of >70 years versus ≤70 years (OR 4.7, p = 0.012) and of male gender (OR 4.8, p = 0.008). Recent cancer-directed therapy was administered in 66.7% (n = 20) of ICU admissions versus 39.5% (n = 17) of general floor admissions (Chi-square p-value of 0.023). (4) Conclusions: High rates of mortality/transition to hospice and ICU utilization were noted amongst our patients with active invasive cancer, following a COVID-19 infection. Men and those of >70 years of age had a greater than four-fold increase in odds of death or transition to hospice. [ABSTRACT FROM AUTHOR]

To quantify and compare diagnoses according to race in pediatric Health Maintenance Organization (HMO) health plan patients seen in a general dermatology clinic over a 10-year period. Retrospective cohort of health plan pediatric patients seen in the dermatology clinic between 1997 and 2007 was established using an electronic medical record database. Diagnoses and diagnostic codes were recorded according to International Classification of Diseases, Ninth Revision (ICD-9) diagnostic codes grouped on their first three digits. The proportion of patients with each diagnosis was determined according to race and sex, and the 10 most common diagnoses were determined. The most common diagnoses observed in all pediatric patients were acne (28.6%), dermatitis (19.4%), and warts (16.2%), accounting for more than 60% of dermatologic visits by children. Although acne (29.9%), warts (22.6%), and dermatitis (13.1%) were also the most common diagnoses for Caucasian children, African American pediatric patients were most commonly seen for dermatitis (29.0%), acne (27.5%), and dermatophytosis (10.2%). The three most common diagnoses for Asian patients were dermatitis (29.1%), acne (22.2%), and warts (12.6%). Acne remains one of the most common dermatologic diagnoses in children of all races. Differences in frequency of office visits for dermatitis, warts, and dermatophytosis were seen when comparing children of other races with Caucasian children. [ABSTRACT FROM AUTHOR]