Global Sex Disparity Of Covid-19: A Descriptive Review Of Sex Hormones And Consideration For The Potential Therapeutic Use Of Hormone Replacement Therapy In Older Adults

The 2019-2020 SARS-related coronavirus-2 (SARS-CoV-2) pandemic has brought unprecedented challenges to healthcare sectors around the world. As of November 2020, there have been over 64 million confirmed cases and approaching 2 million deaths globally. Despite the large number of positive cases, there are very limited established standards of care and therapeutic options available. To date, there is still no Food and Drug Administration (FDA) approved vaccine for COVID-19, although there are several options in various clinical trial stages. Herein, we have performed a global review evaluating the roles of age and sex on COVID-19 hospitalizations, ICU admissions, deaths in hospitals, and deaths in nursing homes. We have identified a trend in which elderly and male patients are significantly affected by adverse outcomes. There is evidence suggesting that sex hormone levels can influence immune system function against SARS-CoV-2 infection, thus reducing the adverse effects of COVID-19. Since older adults have lower levels of these sex hormones, we therefore speculate, within rational scientific context, that sex steroids, such as estrogen and progesterone, needs further consideration for use as alternative therapeutic option for treating COVID-19 elderly patients. To our knowledge, this is the first comprehensive article evaluating the significance of sex hormones in COVID-19 outcomes in older adults

Attenuated Superoxide Dismutase 2 Activity Induces Atherosclerotic Plaque Instability During Aging in Hyperlipidemic Mice

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142527/1/jah32679-sup-0001-SupInfo.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/142527/2/jah32679_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/142527/3/jah32679.pd

Synthesis, antitubercular activity and mechanism of resistance of highly effective thiacetazone analogues

Defining the pharmacological target(s) of currently used drugs and developing new analogues with greater potency are both important aspects of the search for agents that are effective against drug-sensitive and drug-resistant Mycobacterium tuberculosis. Thiacetazone (TAC) is an anti-tubercular drug that was formerly used in conjunction with isoniazid, but removed from the antitubercular chemotherapeutic arsenal due to toxic side effects. However, several recent studies have linked the mechanisms of action of TAC to mycolic acid metabolism and TAC-derived analogues have shown increased potency against M. tuberculosis. To obtain new insights into the molecular mechanisms of TAC resistance, we isolated and analyzed 10 mutants of M. tuberculosis that were highly resistant to TAC. One strain was found to be mutated in the methyltransferase MmaA4 at Gly101, consistent with its lack of oxygenated mycolic acids. All remaining strains harbored missense mutations in either HadA (at Cys61) or HadC (at Val85, Lys157 or Thr123), which are components of the bhydroxyacyl-ACP dehydratase complex that participates in the mycolic acid elongation step. Separately, a library of 31 new TAC analogues was synthesized and evaluated against M. tuberculosis. Two of these compounds, 15 and 16, exhibited minimal inhibitory concentrations 10-fold lower than the parental molecule, and inhibited mycolic acid biosynthesis in a dose-dependent manner. Moreover, overexpression of HadAB HadBC or HadABC in M. tuberculosis led to high level resistance to these compounds, demonstrating that their mode of action is similar to that of TAC. In summary, this study uncovered new mutations associated with TAC resistance and also demonstrated that simple structural optimization of the TAC scaffold was possible and may lead to a new generation of TAC-derived drug candidates for the potential treatment of tuberculosis as mycolic acid inhibitors

Arginine at positions 13 or 70-71 in pocket 4 of HLA-DRB1 alleles is associated with susceptibility to tuberculoid leprosy

Evaluation of human histocompatibility leukocyte antigen (HLA) class II genes in 54 cases of tuberculoid leprosy (TL) and 44 controls has shown a positive association with HLA-DRB1 alleles that contain Arg13 or Arg70-Arg71. Among TL patients, 87% carry specific alleles of DRB1 Arg13 or Arg70-Arg71 as compared to 43% among controls (p = 5 x 10(-6)) conferring a relative risk of 8.8. Thus, susceptibility to TL involves three critical amino acid positions of the beta chain, the side chains of which, when modeled on the DR1 crystal structure, line a pocket (pocket 4) accommodating the side chain of a bound peptide. This study suggests that disease susceptibility may be determined by the independent contribution of polymorphic residues participating in the formation of a functional arrangement (i.e., pocket) within the binding cleft of an HLA molecule

17β-estradiol promotes extracellular vesicle release and selective miRNA loading in ERα-positive breast cancer

The causes and consequences of abnormal biogenesis of extracellular vesicles (EVs) are not yet well understood in malignancies, including in breast cancers (BCs). Given the hormonal signaling dependence of estrogen receptor–positive (ER+) BC, we hypothesized that 17β-estradiol (estrogen) might influence EV production and microRNA (miRNA) loading. We report that physiological doses of 17β-estradiol promote EV secretion specifically from ER+ BC cells via inhibition of miR-149-5p, hindering its regulatory activity on SP1, a transcription factor that regulates the EV biogenesis factor nSMase2. Additionally, miR-149-5p downregulation promotes hnRNPA1 expression, responsible for the loading of let-7’s miRNAs into EVs. In multiple patient cohorts, we observed increased levels of let-7a-5p and let-7d-5p in EVs derived from the blood of premenopausal ER+ BC patients, and elevated EV levels in patients with high BMI, both conditions associated with higher levels of 17β-estradiol. In brief, we identified a unique estrogen-driven mechanism by which ER+ BC cells eliminate tumor suppressor miRNAs in EVs, with effects on modulating tumor-associated macrophages in the microenvironment

A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems

International audienceSzeliski et al. published an influential study in 2006 on energy minimization methods for Markov Random Fields (MRF). This study provided valuable insights in choosing the best optimization technique for certain classes of problems. While these insights remain generally useful today, the phenomenal success of random field models means that the kinds of inference problems that have to be solved changed significantly. Specifically , the models today often include higher order interactions, flexible connectivity structures, large label-spaces of different car-dinalities, or learned energy tables. To reflect these changes, we provide a modernized and enlarged study. We present an empirical comparison of more than 27 state-of-the-art optimization techniques on a corpus of 2,453 energy minimization instances from diverse applications in computer vision. To ensure reproducibility, we evaluate all methods in the OpenGM 2 framework and report extensive results regarding runtime and solution quality. Key insights from our study agree with the results of Szeliski et al. for the types of models they studied. However, on new and challenging types of models our findings disagree and suggest that polyhedral methods and integer programming solvers are competitive in terms of runtime and solution quality over a large range of model types

Data mining of high density genomic variant data for prediction of Alzheimer's disease risk

<p>Abstract</p> <p>Background</p> <p>The discovery of genetic associations is an important factor in the understanding of human illness to derive disease pathways. Identifying multiple interacting genetic mutations associated with disease remains challenging in studying the etiology of complex diseases. And although recently new single nucleotide polymorphisms (SNPs) at genes implicated in immune response, cholesterol/lipid metabolism, and cell membrane processes have been confirmed by genome-wide association studies (GWAS) to be associated with late-onset Alzheimer's disease (LOAD), a percentage of AD heritability continues to be unexplained. We try to find other genetic variants that may influence LOAD risk utilizing data mining methods.</p> <p>Methods</p> <p>Two different approaches were devised to select SNPs associated with LOAD in a publicly available GWAS data set consisting of three cohorts. In both approaches, single-locus analysis (logistic regression) was conducted to filter the data with a less conservative p-value than the Bonferroni threshold; this resulted in a subset of SNPs used next in multi-locus analysis (random forest (RF)). In the second approach, we took into account prior biological knowledge, and performed sample stratification and linkage disequilibrium (LD) in addition to logistic regression analysis to preselect loci to input into the RF classifier construction step.</p> <p>Results</p> <p>The first approach gave 199 SNPs mostly associated with genes in calcium signaling, cell adhesion, endocytosis, immune response, and synaptic function. These SNPs together with <it>APOE and GAB2 </it>SNPs formed a predictive subset for LOAD status with an average error of 9.8% using 10-fold cross validation (CV) in RF modeling. Nineteen variants in LD with <it>ST5, TRPC1, ATG10, ANO3, NDUFA12, and NISCH </it>respectively, genes linked directly or indirectly with neurobiology, were identified with the second approach. These variants were part of a model that included <it>APOE </it>and <it>GAB2 </it>SNPs to predict LOAD risk which produced a 10-fold CV average error of 17.5% in the classification modeling.</p> <p>Conclusions</p> <p>With the two proposed approaches, we identified a large subset of SNPs in genes mostly clustered around specific pathways/functions and a smaller set of SNPs, within or in proximity to five genes not previously reported, that may be relevant for the prediction/understanding of AD.</p