A sinus of Valsalva aneurysm (SOVA) is usually a silent entity until one of its complications arises, such as heart failure. SOVA itself is uncommon, but it is more frequently associated with a supracristal ventricular septal defect (SVSD). We present a 67-year-old man with a history of an asymptomatic SVSD who presented to the emergency department with signs and symptoms of heart failure. He was subsequently found to have a ruptured SOVA and underwent urgent surgical repair.

Abstract Introduction Supratentorial primitive neuroectodermal tumors predominantly occur in children, and are rare in the adult population. Less than 100 cases of supratentorial primitive neuroectodermal tumor have been reported in adults internationally. Our case study reports this rare incident. Case presentation A 22-year-old Hispanic man presented with headaches, blurry vision, diplopia, intermittent vomiting, and grossly decreased vision. A magnetic resonance image showed a left posterior parietal heterogeneously enhancing mass measuring 4.2cm × 7.2cm × 7.0cm. After craniotomy for resection and decompression, the mass was histologically revealed to be a supratentorial primitive neuroectodermal tumor. Standardized immunohistochemical studies for this mass were carried out. Conclusion We have concluded that immunohistochemical and genetic workup should be included in the standardized pathological workup for primitive neuroectodermal tumors in order to provide more prognostic information. Based on our current literature review, we propose an immunohistochemical panel.

Tobacco usage is a known risk factor associated with development of oral cancer. It is mainly consumed in two different forms (smoking and chewing) that vary in their composition and methods of intake. Despite being the leading cause of oral cancer, molecular alterations induced by tobacco are poorly understood. We therefore sought to investigate the adverse effects of cigarette smoke/chewing tobacco exposure in oral keratinocytes (OKF6/TERT1). OKF6/TERT1 cells acquired oncogenic phenotype after treating with cigarette smoke/chewing tobacco for a period of 8 months. We employed whole exome sequencing (WES) and quantitative proteomics to investigate the molecular alterations in oral keratinocytes chronically exposed to smoke/ chewing tobacco. Exome sequencing revealed distinct mutational spectrum and copy number alterations in smoke/ chewing tobacco treated cells. We also observed differences in proteomic alterations. Proteins downstream of MAPK1 and EGFR were dysregulated in smoke and chewing tobacco exposed cells, respectively. This study can serve as a reference for fundamental damages on oral cells as a consequence of exposure to different forms of tobacco.

Deregulated HER2 is a target of many approved cancer drugs. We analyzed 111,176 patient tumors and identified recurrent mutations in HER2 transmembrane domain (TMD) and juxtamembrane domain (JMD) that include G660D, R678Q, E693K, and Q709L. Using a saturation mutagenesis screen and testing of patient-derived mutations we found several activating TMD and JMD mutations. Structural modeling and analysis showed that the TMD/JMD mutations function by improving the active dimer interface or stabilizing an activating conformation. Further, we found that HER2 G660D employed asymmetric kinase dimerization for activation and signaling. Importantly, anti-HER2 antibodies and small-molecule kinase inhibitors blocked the activity of TMD/JMD mutants. Consistent with this, a G660D germline mutant lung cancer patient showed remarkable clinical response to HER2 blockade.

COVID-19 is a respiratory illness caused by a novel coronavirus called SARS-CoV-2. The viral spike (S) protein engages the human angiotensin-converting enzyme 2 (ACE2) receptor to invade host cells with ~10-15-fold higher affinity compared to SARS-CoV S-protein, making it highly infectious. Here, we assessed if ACE2 polymorphisms can alter host susceptibility to SARS-CoV-2 by affecting this interaction. We analyzed over 290,000 samples representing >400 population groups from public genomic datasets and identified multiple ACE2 protein-altering variants. Using reported structural data, we identified natural ACE2 variants that could potentially affect virus-host interaction and thereby alter host susceptibility. These include variants S19P, I21V, E23K, K26R, T27A, N64K, T92I, Q102P and H378R that were predicted to increase susceptibility, while variants K31R, N33I, H34R, E35K, E37K, D38V, Y50F, N51S, M62V, K68E, F72V, Y83H, G326E, G352V, D355N, Q388L and D509Y were predicted to be protective variants that show decreased binding to S-protein. Using biochemical assays, we confirmed that K31R and E37K had decreased affinity, and K26R and T92I variants showed increased affinity for S-protein when compared to wildtype ACE2. Consistent with this, soluble ACE2 K26R and T92I were more effective in blocking entry of S-protein pseudotyped virus suggesting that ACE2 variants can modulate susceptibility to SARS-CoV-2.

AbstractPopulation-scale genetic studies can identify drug targets and allow disease risk to be predicted with resulting benefit for management of individual health risks and system-wide allocation of health care delivery resources. Although population-scale projects are underway in many parts of the world, genetic variation between population groups means that additional projects are warranted. South Asia has a population whose genetics is the least characterized of any of the world’s major populations. Here we describe GenomeAsia studies that characterize population structure in South Asia and that create tools for economical and accurate genotyping at population-scale. Prior work on population structure characterized isolated population groups, the relevance of which to large-scale studies of disease genetics is unclear. For our studies we used whole genome sequence information from 4,807 individuals recruited in the health care delivery systems of Pakistan, India and Bangladesh to ensure relevance to population-scale studies of disease genetics. We combined this with WGS data from 927 individuals from isolated South Asian population groups, and developed a custom SNP array (called SARGAM) that is optimized for future human genetic studies in South Asia. We find evidence for high rates of reproductive isolation, endogamy and consanguinity that vary across the subcontinent and that lead to levels of homozygosity that approach 100 times that seen in outbred populations. We describe founder effects that increase the power to associate functional variants with disease processes and that make South Asia a uniquely powerful place for population-scale genetic studies.

Host galaxy identification is a crucial step for modern supernova (SN) surveys such as the Dark Energy Survey and the Large Synoptic Survey Telescope, which will discover SNe by the thousands. Spectroscopic resources are limited, and so in the absence of real-time SN spectra these surveys must rely on host galaxy spectra to obtain accurate redshifts for the Hubble diagram and to improve photometric classification of SNe. In addition, SN luminosities are known to correlate with host-galaxy properties. Therefore, reliable identification of host galaxies is essential for cosmology and SN science. We simulate SN events and their locations within their host galaxies to develop and test methods for matching SNe to their hosts. We use both real and simulated galaxy catalog data from the Advanced Camera for Surveys General Catalog and MICECATv2.0, respectively. We also incorporate "hostless" SNe residing in undetected faint hosts into our analysis, with an assumed hostless rate of 5%. Our fully automated algorithm is run on catalog data and matches SNe to their hosts with 91% accuracy. We find that including a machine learning component, run after the initial matching algorithm, improves the accuracy (purity) of the matching to 97% with a 2% cost in efficiency (true positive rate). Although the exact results are dependent on the details of the survey and the galaxy catalogs used, the method of identifying host galaxies we outline here can be applied to any transient survey.

The See Change survey was designed to make z > 1 cosmological measurements by efficiently discovering high-redshift Type Ia supernovae (SNe Ia) and improving cluster mass measurements through weak lensing. This survey observed twelve galaxy clusters with the Hubble Space Telescope (HST) spanning the redshift range z = 1.13-1.75, discovering 57 likely transients and 27 likely SNe Ia at z ∼ 0.8-2.3. As in similar previous surveys, this proved to be a highly efficient use of HST for supernova observations; the See Change survey additionally tested the feasibility of maintaining, or further increasing, the efficiency at yet higher redshifts, where we have less detailed information on the expected cluster masses and star formation rates. We find that the resulting number of SNe Ia per orbit is a factor of ∼8 higher than for a field search, and 45% of our orbits contained an active SN Ia within 22 rest-frame days of peak, with one of the clusters by itself yielding 6 of the SNe Ia. We present the survey design, pipeline, and supernova discoveries. Novel features include fully blinded supernova searches, the first random forest candidate classifier for undersampled IR data (with a 50% detection threshold within 0.05 mag of human searchers), real-time forward-modeling photometry of candidates, and semi-automated photometric classifications and follow-up forecasts. We also describe the spectroscopic follow-up, instrumental in measuring host galaxy redshifts. The cosmology analysis of our sample will be presented in a companion paper.

The benefits of large-scale genetic studies for healthcare of the populations studied are well documented, but these genetic studies have traditionally ignored people from some parts of the world, such as South Asia. Here we describe whole genome sequence (WGS) data from 4806 individuals recruited from the healthcare delivery systems of Pakistan, India and Bangladesh, combined with WGS from 927 individuals from isolated South Asian populations. We characterize population structure in South Asia and describe a genotyping array (SARGAM) and imputation reference panel that are optimized for South Asian genomes. We find evidence for high rates of reproductive isolation, endogamy and consanguinity that vary across the subcontinent and that lead to levels of rare homozygotes that reach 100 times that seen in outbred populations. Founder effects increase the power to associate functional variants with disease processes and make South Asia a uniquely powerful place for population-scale genetic studies.