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INTRODUCTIONMillions of people have received genome and exome sequencing to date, a collective effort that has illuminated for the first time the vast catalog of small genetic differences that distinguish us as individuals within our species. However, the effects of most of these genetic variants remain unknown, limiting their clinical utility and actionability. New approaches that can accurately discern disease-causing from benign mutations and interpret genetic variants on a genome-wide scale would constitute a meaningful initial step towards realizing the potential of personalized genomic medicine.RATIONALEAs a result of the short evolutionary distance between humans and nonhuman primates, our proteins share near-perfect amino acid sequence identity. Hence, the effects of a protein-altering mutation found in one species are likely to be concordant in the other species. By systematically cataloging common variants of nonhuman primates, we aimed to annotate these variants as being unlikely to cause human disease as they are tolerated by natural selection in a closely related species. Once collected, the resulting resource may be applied to infer the effects of unobserved variants across the genome using machine learning.RESULTSFollowing the strategy outlined above we obtained whole-genome sequencing data for 809 individuals from 233 primate species and cataloged 4.3 million common missense variants. We confirmed that human missense variants seen in at least one nonhuman primate species were annotated as benign in the ClinVar clinical variant database in 99% of cases. By contrast, common variants from mammals and vertebrates outside the primate lineage were substantially less likely to be benign in the ClinVar database (71 to 87% benign), restricting this strategy to nonhuman primates. Overall, we reclassified more than 4 million human missense variants of previously unknown consequence as likely benign, resulting in a greater than 50-fold increase in the number of annotated missense variants compared to existing clinical databases.To infer the pathogenicity of the remaining missense variants in the human genome, we constructed PrimateAI-3D, a semisupervised 3D-convolutional neural network that operates on voxelized protein structures. We trained PrimateAI-3D to separate common primate variants from matched control variants in 3D space as a semisupervised learning task. We evaluated the trained PrimateAI-3D model alongside 15 other published machine learning methods on their ability to distinguish between benign and pathogenic variants in six different clinical benchmarks and demonstrated that PrimateAI-3D outperformed all other classifiers in each of the tasks.CONCLUSIONOur study addresses one of the key challenges in the variant interpretation field, namely, the lack of sufficient labeled data to effectively train large machine learning models. By generating the most comprehensive primate sequencing dataset to date and pairing this resource with a deep learning architecture that leverages 3D protein structures, we were able to achieve meaningful improvements in variant effect prediction across multiple clinical benchmarks. Personalized genome sequencing has revealed millions of genetic differences between individuals, but our understanding of their clinical relevance remains largely incomplete. To systematically decipher the effects of human genetic variants, we obtained whole-genome sequencing data for 809 individuals from 233 primate species and identified 4.3 million common protein-altering variants with orthologs in humans. We show that these variants can be inferred to have nondeleterious effects in humans based on their presence at high allele frequencies in other primate populations. We use this resource to classify 6% of all possible human protein-altering variants as likely benign and impute the pathogenicity of the remaining 94% of variants with deep learning, achieving state-of-the-art accuracy for diagnosing pathogenic variants in patients with genetic diseases.

The rich diversity of morphology and behavior displayed across primate species provides an informative context in which to study the impact of genomic diversity on fundamental biological processes. Analysis of that diversity provides insight into long-standing questions in evolutionary and conservation biology, and is urgent given severe threats these species are facing. Here, we present high coverage whole-genome data from 233 primate species representing 86% of genera and all 16 families. This dataset was used, together with fossil calibration, to create a nuclear DNA phylogeny and to reassess evolutionary divergence times among primate clades. We found within-species genetic diversity across families and geographic regions to be associated with climate and sociality, but not with extinction risk. Furthermore, mutation rates differ across species, potentially influenced by effective population sizes. Lastly, we identified extensive recurrence of missense mutations previously thought to be human-specific. This study will open a wide range of research avenues for future primate genomic research.One-Sentence SummaryThe whole genome sequences of 233 primate species provide insight into the determinants of genetic diversity, phylogenomics, and human uniqueness.

ObjectivesTo ascertain the effect of historical demography and past climate change as the drivers of diversity in northeast India.Materials and methodsWe took the variant called whole genome files of nine species present in the northeast India from Primate genome sequencing consortium work and assessed each species historic effective population size by using Multiple Sequentially Markovian Coalescent (MSMC) tool. We also constructed species distribution models on past (Pliocene and Pleistocene) and present climate with Maxent, by utilizing publicly available distribution data for each species.ResultsWe got the effective population sizes for 10 million years ago at most, though we considered the data only till 3.3 million years. All species showed rise and decline at various time periods. The species distribution models showed disparate distribution at all three time points with a genera-wise pattern emerging.DiscussionWe found that the evolutionary trajectories of all the four genera into consideration,Macaca, Trachypithecus, HoolockandNycticebusare different from each other. Species inMacacalooks to be evolved in northeast as well as come from southeast Asia. Some species ofTrachypithecusseems to radiated in the northeast India. Similarly,Hoolockhas evolved in the region andNycticebusis predicted have arrived from Indochina in the region. Hence, this study provides unique insights to the evolutionary dynamics for primate species in the northeast India.

This paper describes a weekly economic index (WEI) developed to track the rapid economic developments associated with the onset of and policy response to the novel coronavirus in the United States. The WEI is a weekly composite index of real economic activity, with eight of 10 series available the Thursday after the end of the reference week. In addition to being a weekly real activity index, the WEI has strong predictive power for output measures and provided an accurate nowcast of current-quarter GDP growth in the first half of 2020, with weaker performance in the second half. We document how the WEI responded to key events and data releases during the first 10 months of the pandemic.

This paper describes a weekly economic index (WEI) developed to track the rapid economic developments associated with the onset of and policy response to the novel coronavirus in the United States. The WEI, with its ten component series, tracks the overall economy. Comparing the contributions of the WEI's components in the 2008 and 2020 recessions reveals differences in how the two events played out at a high frequency. During the 2020 collapse and recovery, it provides a benchmark to interpret similarities and differences of novel indicators with shorter samples and/or nonstationary coverage, such as mobility indexes or credit card spending.

Information about the taxonomy and geographical distribution of a species is essential to understand its evolution and for conservation efforts. The phylogeny of the Hylobatidae remains unclear. India is reported to have one species of Hoolock gibbon (Hoolock hoolock) but a recent study based on pelage colour suggested that another species, H. leuconedys, occurs in the Mishmi Hills between the Dibang and Nao Dehing rivers in Arunachal Pradesh. We examined whether H. leuconedys occurs in India and its evolutionary relationships with other Hylobatidae species. We collected blood, tissue, and fecal samples from various populations of H. hoolock (N = 17) and the Mishmi Hills gibbons (N = 14) from their distribution in Northeast India, zoos, and rescues centers. We isolated DNA from these samples and constructed phylogenetic trees using partial D-loop and COI markers. We also performed whole mitochondrial analysis to study the phylogenetics of the Hylobatidae family. Our genetic analysis showed that none of the samples from India were H. leuconedys, and that all samples from the Mishmi Hills could be assigned to H. hoolock. Our mitogenome analysis supported this conclusion. We estimate that gibbon divergence from a common ancestor occurred 8.38 mya and that the split between H. hoolock and H. leuconedys occurred 1.49 mya. These findings will facilitate exchange of individuals from different zoos for captive breeding programs and conservation and management of wild populations of these gibbons.

AimsTo determine the prevalence and predictors of myopic macular degeneration (MMD) in a consortium of Asian studies.MethodsIndividual-level data from 19 885 participants from four population-based studies, and 1379 highly myopic participants (defined as axial length (AL) >26.0 mm) from three clinic-based/school-based studies of the Asian Eye Epidemiology Consortium were pooled. MMD was graded from fundus photographs following the meta-analysis for pathologic myopia classification and defined as the presence of diffuse choroidal atrophy, patchy chorioretinal atrophy, macular atrophy, with or without ‘plus’ lesion (lacquer crack, choroidal neovascularisation or Fuchs’ spot). Area under the curve (AUC) evaluation for predictors was performed for the population-based studies.ResultsThe prevalence of MMD was 0.4%, 0.5%, 1.5% and 5.2% among Asians in rural India, Beijing, Russia and Singapore, respectively. In the population-based studies, older age (per year; OR=1.13), female (OR=2.0), spherical equivalent (SE; per negative diopter; OR=1.7), longer AL (per mm; OR=3.1) and lower education (OR=1.9) were associated with MMD after multivariable adjustment (all pConclusionIn this pooled analysis of multiple Asian studies, older age, female, lower education, greater myopia severity and longer AL were risk factors of MMD, and myopic SE was the strongest single predictor of MMD.

The gradual transition from a traditional transportation system to an intelligent transportation system (ITS) has paved the way to preserve green environments in metro cities. Moreover, electric vehicles (EVs) seem to be beneficial choices for traveling purposes due to their low charging costs, low energy consumption, and reduced greenhouse gas emission. However, a single failure in an EV’s intrinsic components can worsen travel experiences due to poor charging infrastructure. As a result, we propose a deep learning and blockchain-based EV fault detection framework to identify various types of faults, such as air tire pressure, temperature, and battery faults in vehicles. Furthermore, we employed a 5G wireless network with an interplanetary file system (IPFS) protocol to execute the fault detection data transactions with high scalability and reliability for EVs. Initially, we utilized a convolutional neural network (CNN) and a long-short term memory (LSTM) model to deal with air tire pressure fault, anomaly detection for temperature fault, and battery fault detection for EVs to predict the presence of faulty data, which ensure safer journeys for users. Furthermore, the incorporated IPFS and blockchain network ensure highly secure, cost-efficient, and reliable EV fault detection. Finally, the performance evaluation for EV fault detection has been simulated, considering several performance metrics, such as accuracy, loss, and the state-of-health (SoH) prediction curve for various types of identified faults. The simulation results of EV fault detection have been estimated at an accuracy of 70% for air tire pressure fault, anomaly detection of the temperature fault, and battery fault detection, with R2 scores of 0.874 and 0.9375.

We postulate that the trends for infective endocarditis (IE) are different for patients admitted for this condition compared with those admitted for a different reason with IE as a secondary diagnosis. Using the Myocardial Infarction Data Acquisition System (MIDAS) database, we analyzed 21,443 records of patients hospitalized with diagnosis of IE from 1994 to 2015. There were 9,191 patients hospitalized with IE as the primary diagnosis, and 12,252 patients with IE as a secondary diagnosis. Piecewise linear models were used to detect changes in trends. A bootstrap method was used to assess the statistical significance of the slopes and break point of each model. Differences in co-morbidities and microbiological patterns were analyzed. Trend analysis showed a significant decrease in IE as the primary diagnosis starting in the year 2004 (p0.01). Hospitalizations with IE as a secondary diagnosis showed a linear increase in incidence (p0.001), without any change points. In primary diagnosis IE, the proportion of streptococci as a causative microorganism was higher compared with staphylococci (p0.001). On the contrary, in secondary diagnosis IE, the proportion of staphylococci was higher than streptococci (p0.001). The proportion of gram-negative and other organism IE was similar in both groups. In conclusion, this study showed 2 divergent temporal trends in hospitalizations for IE as a primary or secondary diagnosis starting in 2004. The profile of the microorganisms reveals a steady higher proportion of staphylococcal infection in secondary diagnosis IE compared with streptococcal infection. Different strategies are needed for the prevention of IE.

Purpose: There has been considerable debate on the extent to which the decline in coronary heart disease (CHD) mortality has been caused by better control of coronary risk factors in the general population or is the result of invasive coronary interventions in symptomatic individuals. Methods Using the Myocardial Infarction Data Acquisition System, a statewide database of all cardiovascular hospital admissions in New Jersey, we examined time trends in incidence of death from CHD in the Years 2000–2014 in persons with a history of hospitalization for CHD in the previous 10 years and those without such a history. Results Over the 10-year study period, there was a marked decline in CHD-related mortality in both persons with a history of CHD and persons without a history of CHD. The decline occurred across all gender, racial, and age groups and was higher in those without a prior history of CHD. Conclusions This adds more evidence that the decline in CHD was not only because of advanced invasive medical and surgical treatments but also equally because of improved lifestyle, pharmacologic treatment of risk factors for CHD, and public health interventions.

This paper describes a weekly economic index (WEI) developed to track the rapid economic developments associated with the onset of and policy response to the novel coronavirus in the United States. The WEI, with its ten component series, tracks the overall economy. Comparing the contributions of the WEI’s components in the 2008 and 2020 recessions reveals differences in how the two events played out at a high frequency. During the 2020 collapse and recovery, it provides a benchmark to interpret similarities and differences of novel indicators with shorter samples and/or nonstationary coverage, such as mobility indexes or credit card spending.

This paper describes a weekly economic index (WEI) developed to track the rapid economic developments associated with the onset of and policy response to the novel coronavirus in the United States. The WEI is a weekly composite index of real economic activity, with eight of 10 series available the Thursday after the end of the reference week. In addition to being a weekly real activity index, the WEI has strong predictive power for output measures and provided an accurate nowcast of current-quarter GDP growth in the first half of 2020, with weaker performance in the second half. We document how the WEI responded to key events and data releases during the first 10 months of the pandemic.

In order to find an additional quantitative way to estimate the petrographic type of unequilibrated ordinary chondrites (UOC), and one that can be used remotely in the study of asteroids, we have analyzed the near-infrared spectra of a suite of UOC observed falls. We obtained spectra from the RELAB database at Brown University and applied several methods for determining the amount of clinopyroxene (CPX) as a percentage of the total pyroxene in the meteorites. The presence of low-Ca CPX has long been known to be characteristic of little-metamorphosed ordinary chondrites. The methods we used were (1) naked-eye determination of the wavelength of the absorption features at ~1 μm and ~2 μm, (2) determination of the wavelengths of these features by fitting polynomial equations, and (3) determining the relative intensities of the CPX and OPX features after isolation by a curve fitting procedure. The measurements were then “calibrated” using data from the literature to obtain values for the amount of CPX in the total pyroxene. We find that there is an empirical relationship between the amount of CPX detected by these methods of spectrum analysis and the petrologic type. Petrologic type = + 4.402 – 0.019 × CPX % We explain this empirical relationship (1) as evidence that in pyroxene bearing rocks the spectrum of pyroxene dominates (this has been known in the 1970s), (2) that low-Ca CPX is so abundant in these meteorites (up to 40 vol%) that it is easily detected by reflectance spectroscopy, and (3) compositional effects caused by Ca and Fe in the pyroxenes partially cancel out or are small. We thus have a new method of quantitatively measuring the level of metamorphic alteration experienced by these important meteorites and of assigning them a petrologic type of 3.0 to 3.9. More importantly, unlike existing methods, this can be applied remotely so that chondritic asteroid surfaces (i.e. those of Q and S asteroids) can also be characterized in terms of their metamorphic history. As an example, (433) Eros and (25143) Itokawa were found to be types ~3.5 and ~3.4, respectively. We briefly discuss the implications of this for understanding the history of meteorites and asteroids.

Due to increasing power demand in the recent scenario, intensely integrated penetration of distributed generation (DG) has become need of the day. Grid-tied inverter based DG is becoming popular due to its effective controllability. However, voltage unbalance is observed sometime at the Point of Common Coupling (PCC) due to fluctuating demands of injection of active-reactive power by the DG into the Grid. This paper presents realization of two different topologies of grid tied inverter - conventional two-level three-phase four-wire, and three-level T-type Neutral Point Clamped (T-NPC) based DG, both controlled by three-phase damping control strategy. Simulation studies presented indicate effective operational control for DG based on both these topologies of inverter under various operating conditions. The primary function of DG, which is to inject power into the grid and decrease the burden on the conventional generation system is analyzed. Effective behavior of the proposed two-level as-well-as three-level DG without giving rise to voltage unbalance issue is presented in this paper. Detailed analysis of unbalance index and total harmonic distortion (THD) for PCC voltages and currents is presented. Also, performance of both the proposed DGs for fulfilling load requirement during operation in islanding mode are presented. Satisfactory voltage compensation capability of DGs is depicted from the presented results for single-phase asymmetric fault and three-phase symmetric faults. Low voltage ride through capability, reduction in unbalance index, and THD within the standard limits are the main features of the presented DG systems.

There is a gap in knowledge about the clinical course of patients admitted with non-specific chest pain (NSCP) and discharged after finding no evidence of cardiovascular disease. The MIDAS database, a statewide repository for all cardiovascular discharges in New Jersey was used to study 107,692

none 17 si Although the MYC oncogene has been implicated in cancer, a systematic assessment of alterations of MYC, related transcription factors, and co-regulatory proteins, forming the proximal MYC network (PMN), across human cancers is lacking. Using computational approaches, we define genomic and proteomic features associated with MYC and the PMN across the 33 cancers of The Cancer Genome Atlas. Pan-cancer, 28% of all samples had at least one of the MYC paralogs amplified. In contrast, the MYC antagonists MGA and MNT were the most frequently mutated or deleted members, proposing a role as tumor suppressors. MYC alterations were mutually exclusive with PIK3CA, PTEN, APC, or BRAF alterations, suggesting that MYC is a distinct oncogenic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such as immune response and growth factor signaling; chromatin, translation, and DNA replication/repair were conserved pan-cancer. This analysis reveals insights into MYC biology and is a reference for biomarkers and therapeutics for cancers with alterations of MYC or the PMN. none Schaub, Franz X; Dhankani, Varsha; Berger, Ashton C; Trivedi, Mihir; Richardson, Anne B; Shaw, Reid; Zhao, Wei; Zhang, Xiaoyang; Ventura, Andrea; Liu, Yuexin; Ayer, Donald E; Hurlin, Peter J; Cherniack, Andrew D; Eisenman, Robert N; Bernard, Brady; Grandori, Carla; Grazi GL Schaub, Franz X; Dhankani, Varsha; Berger, Ashton C; Trivedi, Mihir; Richardson, Anne B; Shaw, Reid; Zhao, Wei; Zhang, Xiaoyang; Ventura, Andrea; Liu, Yuexin; Ayer, Donald E; Hurlin, Peter J; Cherniack, Andrew D; Eisenman, Robert N; Bernard, Brady; Grandori, Carla; Grazi GL

Background: The incidence of myocardial infarction (MI) has been decreasing for several decades. However, scant data are available on whether this decline has been magnified, diminished, or remained stable over the recent 15 year period. Methods: Using the Myocardial Infarction Data Acquisition