Transcriptomics and chromatin accessibility in multiple African population samples.

Mapping the functional human genome and impact of genetic variants is often limited to European-descendent population samples. To aid in overcoming this limitation, we measured gene expression using RNA sequencing in lymphoblastoid cell lines (LCLs) from 599 individuals from six African populations to identify novel transcripts including those not represented in the hg38 reference genome. We used whole genomes from the 1000 Genomes Project and 164 Maasai individuals to identify 8,881 expression and 6,949 splicing quantitative trait loci (eQTLs/sQTLs), and 2,611 structural variants associated with gene expression (SV-eQTLs). We further profiled chromatin accessibility using ATAC-Seq in a subset of 100 representative individuals, to identity chromatin accessibility quantitative trait loci (caQTLs) and allele-specific chromatin accessibility, and provide predictions for the functional effect of 78.9 million variants on chromatin accessibility. Using this map of eQTLs and caQTLs we fine-mapped GWAS signals for a range of complex diseases. Combined, this work expands global functional genomic data to identify novel transcripts, functional elements and variants, understand population genetic history of molecular quantitative trait loci, and further resolve the genetic basis of multiple human traits and disease.

Transgenic mouse models support a protective role of type I IFN response in SARS-CoV-2 infection-related lung immunopathology and neuroinvasion.

Type I interferon (IFN-I) response is the first line of host defense against invading viruses. In the absence of definite mouse models, the role of IFN-I in SARS-CoV-2 infection remains perplexing. Here, we develop two mouse models, one with constitutively high IFN-I response (hACE2; Irgm1-/-) and the other with dampened IFN-I response (hACE2; Ifnar1-/-), to comprehend the role of IFN-I response. We report that hACE2; Irgm1-/- mice are resistant to lethal SARS-CoV-2 infection. In contrast, a severe SARS-CoV-2 infection along with immune cell infiltration, cytokine storm, and enhanced pathology is observed in the lungs and brain of hACE2; Ifnar1-/- mice. The hACE2; Irgm1-/-Ifnar1-/- double-knockout mice display loss of the protective phenotype observed in hACE2; Irgm1-/- mice, suggesting that heightened IFN-I response accounts for the observed immunity. Taking the results together, we demonstrate that IFN-I protects from lethal SARS-CoV-2 infection, and Irgm1 (IRGM) could be an excellent therapeutic target against SARS-CoV-2.

High-Throughput Exploration of Triple-Cation Perovskites via All-in-One Compositionally-Graded Films.

Many devices heavily rely on combinatorial material optimization. However, new material alloys are classically developed by studying only a fraction of giant chemical space, while many intermediate compositions remain unmade in light of the lack of methods to synthesize gapless material libraries. Here report a high-throughput all-in-one material platform to obtain and study compositionally-tunable alloys from solution is reported. This strategy is applied to make all Csx MAy FAz PbI3 perovskite alloys (MA and FA stand for methylammonium and formamidinium, respectively), in less than 10 min, on a single film, on which 520 unique alloys are then studied. Through stability mapping of all these alloys in air supersaturated with moisture, a range of targeted perovskites are found, which are then chosen to make efficient and stable solar cells in relaxed fabrication conditions, in ambient air. This all-in-one platform provides access to an unprecedented library of compositional space with no unmade alloys, and hence aids in a comprehensive accelerated discovery of efficient energy materials.

Ferroelectricity in Hybrid Perovskites.

Ferroelectric ceramics such as PbZrxTi1-xO3 (PZT) are widely applied in many fields, from medical to aerospace, because of their dielectric, piezoelectric, and pyroelectric properties. In the past few years, hybrid organic-inorganic halide perovskites have gradually attracted attention for their optical and electronic properties, including ferroelectricity, and for their low fabrication costs. In this Review, we first describe techniques that are used to quantify ferroelectric figures of merit of a material. We then discuss ferroelectricity in hybrid perovskites, starting from controversies in methylammonium iodoplumbate perovskites and then focusing on low-dimensional perovskites that offer an unambiguous platform to obtain ferroelectricity. Finally, we provide examples of the application of perovskite ferroelectrics in solar cells, LEDs, and X-ray detectors. We conclude that the vast structure-property tunability makes low-dimensional hybrid perovskites promising, but they have yet to offer ferroelectric figures of merit (e.g., saturated polarization) and thermal stability (e.g., Curie temperature) competitive with those of conventional oxide perovskite ferroelectric materials.

RIPosomes are targets of IRGM-SQSTM1-dependent autophagy.

The NOD1-NOD2-RIPK2-NFKB/NF-κB pro-inflammatory axis plays a significant role in regulating the immune response to bacterial infection. However, an excess of NFKB-dependent cytokine response can be detrimental and, thus, should be kept under control to maintain the innate immune balance. In our recent study, first, we showed that bacterial infection induces the biogenesis of RIPK2 oligomers (RIPosomes) that are recruited around the bacteria to enhance an NFKB-dependent pro-inflammatory response. Next, we showed that SQSTM1- and IRGM-dependent selective macroautophagy/autophagy degrades RIPosomes and their components to limit NOD1-NOD2-RIPK2-NFKB pro-inflammatory signaling. Consistently, depletion of IRGM results in an augmented RIPK2-dependent pro-inflammatory cytokine response induced by Shigella flexneri and Salmonella typhimurium. Further, bacterial infection- and DSS-induced gut inflammation in irgm1KO mice is dampened upon therapeutic inhibition of RIPK2. Taken together, we showed that autophagy selectively degrades RIPosomes to suppress inflammation and maintain innate immune homeostasis.

Biomass using tribal women exhibited respiratory symptoms, hypertensive risks and abnormal pulmonary function.

In rural areas of developing countries, solid fuels are still widely used for cooking, heating, and lighting purposes. This study investigates the effects of household air pollutants (HAPs) exposure on the occurrence of respiratory symptoms, blood pressure, and lung function. In this study, we randomly selected 123 (83 biomass and 40 clean fuel user) subjects to assess the impact of smoke generated from solid biomass fuel by assessing their health status along with the ventilation pattern of the kitchens and living rooms. HAPs (PM10, PM2.5, and CO) and different health parameters were measured along with monitoring of self-reported health symptoms for a consecutive period of eight months. Results revealed that the concentration of CO, PM2.5, and PM10 were found highest in biomass using households. Higher odds of the upper respiratory symptoms, runny nose (OR: 4.08, 95% CI: 1.22-22.14, p < 0.03), nasal congestion (OR: 9.07, 95% CI: 1.39-97.89, p < 0.01) and the odds of the lower respiratory symptoms like wheezing (OR: 1.62, 95% CI: 1.23-10.94, p < 0.01), breathlessness (OR: 4.44, 95% CI: 1.3-14.75, p < 0.01), chest tightness (OR: 4.89, 95% CI: 1.23-22.14, p < 0.03) and dry cough (OR: 3.661, 95% CI: 1.05-12.25, p < 0.04) were significantly higher in biomass fuel user. Similarly higher systolic (+11.41 mmHg), higher diastolic pressure (+3.3 mmHg), higher pulse pressure (+8.11 mmHg), and a 6 mmHg higher mean arterial pressure among biomass fuel using tribal women. The risk of hypertension was significantly (p < 0.03) higher (OR: 3.04; 95% CI: 1.18-7.89) among solid biomass fuel users. The lung abnormality was recorded 28.91% (OR: 5.02, 95% CI: 1.50 to 16.56, p < 0.01) among biomass fuel user. Finally, it is suggested that the use of efficient cookstoves, increase in cross ventilation, and cleaner fuel are urgently needed to curb the pollution load.

Bisphenol A-induced neurobehavioral transformation is associated with augmented monoamine oxidase activity and neurodegeneration in zebrafish brain.

As bisphenol A (BPA) effortlessly crosses the blood-brain barrier, its serious impacts on the neuronal microenvironment towards precocious induction of oxidative stress and neuromorphological alteration can't be ignored. Incidentally, a symmetric study establishing the possible link of transformed neurobehavior with heightened monoamine oxidase (MAO) activity and neuromorphological alteration in zebrafish brain subsequent to BPA-exposure is limiting in the literature. The study was conducted to delineate the role of BPA towards the genesis of aggressive behaviour in zebrafish and its correlation with brain MAO activity. Mirror biting test and open field test were conducted to evaluate the aggressive and explorative behaviour respectively. Biochemical studies were performed to delineate the modulation of the antioxidant defence system. Cresyl violet staining and Hoechst staining in the periventricular grey zone of the zebrafish brain were conducted to evaluate neuronal pyknosis and chromatin condensation. Our study showed that BPA exposure is associated with the genesis of aggressive neurobehavioral response. Moreover, the brain MAO activity, oxidative stress and chromatin condensation were increased with increase in exposure duration. The results of the present study gave conclusive evidence that BPA act as a potent neurotoxicant in transforming the native neurobehavioral response of zebrafish through heightened oxidative stress, MAO activity and altered neuromorphology.

Integrative single-cell analysis of cardiogenesis identifies developmental trajectories and non-coding mutations in congenital heart disease.

To define the multi-cellular epigenomic and transcriptional landscape of cardiac cellular development, we generated single-cell chromatin accessibility maps of human fetal heart tissues. We identified eight major differentiation trajectories involving primary cardiac cell types, each associated with dynamic transcription factor (TF) activity signatures. We contrasted regulatory landscapes of iPSC-derived cardiac cell types and their in vivo counterparts, which enabled optimization of in vitro differentiation of epicardial cells. Further, we interpreted sequence based deep learning models of cell-type-resolved chromatin accessibility profiles to decipher underlying TF motif lexicons. De novo mutations predicted to affect chromatin accessibility in arterial endothelium were enriched in congenital heart disease (CHD) cases vs. controls. In vitro studies in iPSCs validated the functional impact of identified variation on the predicted developmental cell types. This work thus defines the cell-type-resolved cis-regulatory sequence determinants of heart development and identifies disruption of cell type-specific regulatory elements in CHD.

Hierarchical, Grid-Aware, and Economically Optimal Coordination of Distributed Energy Resources in Realistic Distribution Systems.

Renewable portfolio standards are targeting high levels of variable solar photovoltaics (PV) in electric distribution systems, which makes reliability more challenging to maintain for distribution system operators (DSOs). Distributed energy resources (DERs), including smart, connected appliances and PV inverters, represent responsive grid resources that can provide flexibility to support the DSO in actively managing their networks to facilitate reliability under extreme levels of solar PV. This flexibility can also be used to optimize system operations with respect to economic signals from wholesale energy and ancillary service markets. Here, we present a novel hierarchical scheme that actively controls behind-the-meter DERs to reliably manage each unbalanced distribution feeder and exploits the available flexibility to ensure reliable operation and economically optimizes the entire distribution network. Each layer of the scheme employs advanced optimization methods at different timescales to ensure that the system operates within both grid and device limits. The hierarchy is validated in a large-scale realistic simulation based on data from the industry. Simulation results show that coordination of flexibility improves both system reliability and economics, and enables greater penetration of solar PV. Discussion is also provided on the practical viability of the required communications and controls to implement the presented scheme within a large DSO.

A lightweight asymmetric U-Net framework for acute ischemic stroke lesion segmentation in CT and CTP images.

BACKGROUND AND OBJECTIVES: This paper has introduced a patch-based, residual, asymmetric, encoder-decoder CNN that solves two major problems in acute ischemic stroke lesion segmentation from CT and CT perfusion data using deep neural networks. First, the class imbalance is encountered since the lesion core size covers less than 5% of the volume of the entire brain. Second, deeper neural networks face the drawback of vanishing gradients, and this degrades the learning ability of the network. METHODS: The neural network architecture has been designed for better convergence and faster inference time without compromising performance to address these difficulties. It uses a training strategy combining Focal Tversky and Binary cross-entropy loss functions to overcome the class imbalance issue. The model comprises only four resolution steps with a total of 11 convolutional layers. A base filter of 8, used for the residual connection with two convolutional blocks at the encoder side, is doubled after each resolution step. Simultaneously, the decoder consists of residual blocks with one convolutional layer and a constant number of 8 filters in each resolution step. This proposition allows for a lighter build with fewer trainable parameters as well as aids in avoiding overfitting by allowing the decoder to decode only necessary information. RESULTS: The presented method has been evaluated through submission on the publicly accessible platform of the Ischemic Stroke Lesion Segmentation (ISLES) 2018 medical image segmentation challenge achieving the second-highest testing dice similarity coefficient (DSC). The experimental results demonstrate that the proposed model achieves comparable performance to other submitted strategies in terms of DSC Precision, Recall, and Absolute Volume Difference (AVD). CONCLUSIONS: Through the proposed approach, the two major research gaps are coherently addressed while achieving high challenge scores by solving the mentioned problems. Our model can serve as a tool for clinicians and radiologists to hasten decision-making and detect strokes efficiently.

High-Throughput Synthesis of Thin Films for the Discovery of Energy Materials: A Perspective.

Thin films are an integral part of many electronic and optoelectronic devices. They also provide an excellent platform for material characterization. Therefore, strategies for the fabrication of thin films are constantly developed and have significantly benefited from the advent of high-throughput synthesis (HTS) platforms. This perspective summarizes recent advances in HTS of thin films from experimentalists' point of view. The work analyzes general strategies of HTS and then discusses their use in developing new energy materials for applications that rely on thin films, such as solar cells, light-emitting diodes, batteries, superconductors, and thermoelectrics. The perspective also summarizes some key challenges and opportunities in the HTS of thin films.

Single-nucleus chromatin accessibility profiling highlights regulatory mechanisms of coronary artery disease risk.

Coronary artery disease (CAD) is a complex inflammatory disease involving genetic influences across cell types. Genome-wide association studies have identified over 200 loci associated with CAD, where the majority of risk variants reside in noncoding DNA sequences impacting cis-regulatory elements. Here, we applied single-nucleus assay for transposase-accessible chromatin with sequencing to profile 28,316 nuclei across coronary artery segments from 41 patients with varying stages of CAD, which revealed 14 distinct cellular clusters. We mapped ~320,000 accessible sites across all cells, identified cell-type-specific elements and transcription factors, and prioritized functional CAD risk variants. We identified elements in smooth muscle cell transition states (for example, fibromyocytes) and functional variants predicted to alter smooth muscle cell- and macrophage-specific regulation of MRAS (3q22) and LIPA (10q23), respectively. We further nominated key driver transcription factors such as PRDM16 and TBX2. Together, this single-nucleus atlas provides a critical step towards interpreting regulatory mechanisms across the continuum of CAD risk.

Radiological Analysis of COVID-19 Using Computational Intelligence: A Broad Gauge Study.

Pulmonary medical image analysis using image processing and deep learning approaches has made remarkable achievements in the diagnosis, prognosis, and severity check of lung diseases. The epidemic of COVID-19 brought out by the novel coronavirus has triggered a critical need for artificial intelligence assistance in diagnosing and controlling the disease to reduce its effects on people and global economies. This study aimed at identifying the various COVID-19 medical imaging analysis models proposed by different researchers and featured their merits and demerits. It gives a detailed discussion on the existing COVID-19 detection methodologies (diagnosis, prognosis, and severity/risk detection) and the challenges encountered for the same. It also highlights the various preprocessing and post-processing methods involved to enhance the detection mechanism. This work also tries to bring out the different unexplored research areas that are available for medical image analysis and how the vast research done for COVID-19 can advance the field. Despite deep learning methods presenting high levels of efficiency, some limitations have been briefly described in the study. Hence, this review can help understand the utilization and pros and cons of deep learning in analyzing medical images.

DJ-1-Nrf2 axis is activated upon murine ß-coronavirus infection in the CNS.

Coronaviruses have emerged as alarming pathogens owing to their inherent ability of genetic variation and cross-species transmission. Coronavirus infection burdens the endoplasmic reticulum (ER.), causes reactive oxygen species production and induces host stress responses, including unfolded protein response (UPR) and antioxidant system. In this study, we have employed a neurotropic murine ß-coronavirus (M-CoV) infection in the Central Nervous System (CNS) of experimental mice model to study the role of host stress responses mediated by interplay of DJ-1 and XBP1. DJ-1 is an antioxidant molecule with established functions in neurodegeneration. However, its regulation in virus-induced cellular stress response is less explored. Our study showed that M-CoV infection activated the glial cells and induced antioxidant and UPR genes during the acute stage when the viral titer peaks. As the virus particles decreased and acute neuroinflammation diminished at day ten p.i., a significant up-regulation in UPR responsive XBP1, antioxidant DJ-1, and downstream signaling molecules, including Nrf2, was recorded in the brain tissues. Additionally, preliminary in silico analysis of the binding between the DJ-1 promoter and a positively charged groove of XBP1 is also investigated, thus hinting at a mechanism behind the upregulation of DJ-1 during MHV-infection. The current study thus attempts to elucidate a novel interplay between the antioxidant system and UPR in the outcome of coronavirus infection.

Ifit2 deficiency restricts microglial activation and leukocyte migration following murine coronavirus (m-CoV) CNS infection.

The interferon-induced tetratricopeptide repeat protein (Ifit2) protects mice from lethal neurotropic viruses. Neurotropic coronavirus MHV-RSA59 infection of Ifit2-/- mice caused pronounced morbidity and mortality accompanied by rampant virus replication and spread throughout the brain. In spite of the higher virus load, induction of many cytokines and chemokines in the brains of infected Ifit2-/- mice were similar to that in wild-type mice. In contrast, infected Ifit2-/- mice revealed significantly impaired microglial activation as well as reduced recruitment of NK1.1 T cells and CD4 T cells to the brain, possibly contributing to the lack of viral clearance. These two deficiencies were associated with a lower level of microglial expression of CX3CR1, the receptor of the CX3CL1 (Fractalkine) chemokine, which plays a critical role in both microglial activation and leukocyte recruitment. The above results uncovered a new potential role of an interferon-induced protein in immune protection.

Single-cell epigenomic analyses implicate candidate causal variants at inherited risk loci for Alzheimer's and Parkinson's diseases.

Genome-wide association studies of neurological diseases have identified thousands of variants associated with disease phenotypes. However, most of these variants do not alter coding sequences, making it difficult to assign their function. Here, we present a multi-omic epigenetic atlas of the adult human brain through profiling of single-cell chromatin accessibility landscapes and three-dimensional chromatin interactions of diverse adult brain regions across a cohort of cognitively healthy individuals. We developed a machine-learning classifier to integrate this multi-omic framework and predict dozens of functional SNPs for Alzheimer's and Parkinson's diseases, nominating target genes and cell types for previously orphaned loci from genome-wide association studies. Moreover, we dissected the complex inverted haplotype of the MAPT (encoding tau) Parkinson's disease risk locus, identifying putative ectopic regulatory interactions in neurons that may mediate this disease association. This work expands understanding of inherited variation and provides a roadmap for the epigenomic dissection of causal regulatory variation in disease.

CD4 Deficiency Causes Poliomyelitis and Axonal Blebbing in Murine Coronavirus-Induced Neuroinflammation.

Mouse hepatitis virus (MHV) is a murine betacoronavirus (m-CoV) that causes a wide range of diseases in mice and rats, including hepatitis, enteritis, respiratory diseases, and encephalomyelitis in the central nervous system (CNS). MHV infection in mice provides an efficient cause-effect experimental model to understand the mechanisms of direct virus-induced neural-cell damage leading to demyelination and axonal loss, which are pathological features of multiple sclerosis (MS), the most common disabling neurological disease in young adults. Infiltration of T lymphocytes, activation of microglia, and their interplay are the primary pathophysiological events leading to disruption of the myelin sheath in MS. However, there is emerging evidence supporting gray matter involvement and degeneration in MS. The investigation of T cell function in the pathogenesis of deep gray matter damage is necessary. Here, we employed RSA59 (an isogenic recombinant strain of MHV-A59)-induced experimental neuroinflammation model to compare the disease in CD4-/- mice with that in CD4+/+ mice at days 5, 10, 15, and 30 postinfection (p.i.). Viral titer estimation, nucleocapsid gene amplification, and viral antinucleocapsid staining confirmed enhanced replication of the virions in the absence of functional CD4+ T cells in the brain. Histopathological analyses showed elevated susceptibility of CD4-/- mice to axonal degeneration in the CNS, with augmented progression of acute poliomyelitis and dorsal root ganglionic inflammation rarely observed in CD4+/+ mice. Depletion of CD4+ T cells showed unique pathological bulbar vacuolation in the brain parenchyma of infected mice with persistent CD11b+ microglia/macrophages in the inflamed regions on day 30 p.i. In summary, the current study suggests that CD4+ T cells are critical for controlling acute-stage poliomyelitis (gray matter inflammation), chronic axonal degeneration, and inflammatory demyelination due to loss of protective antiviral host immunity.IMPORTANCE The current trend in CNS disease biology is to attempt to understand the neural-cell-immune interaction to investigate the underlying mechanism of neuroinflammation, rather than focusing on peripheral immune activation. Most studies in MS are targeted toward understanding the involvement of CNS white matter. However, the importance of gray matter damage has become critical in understanding the long-term progressive neurological disorder. Our study highlights the importance of CD4+ T cells in safeguarding neurons against axonal blebbing and poliomyelitis from murine betacoronavirus-induced neuroinflammation. Current knowledge of the mechanisms that lead to gray matter damage in MS is limited, because the most widely used animal model, experimental autoimmune encephalomyelitis (EAE), does not present this aspect of the disease. Our results, therefore, add to the existing limited knowledge in the field. We also show that the microglia, though important for the initiation of neuroinflammation, cannot establish a protective host immune response without the help of CD4+ T cells.

Assessing the accuracy of phylogenetic rooting methods on prokaryotic gene families.

Almost all standard phylogenetic methods for reconstructing gene trees result in unrooted trees; yet, many of the most useful applications of gene trees require that the gene trees be correctly rooted. As a result, several computational methods have been developed for inferring the root of unrooted gene trees. However, the accuracy of such methods has never been systematically evaluated on prokaryotic gene families, where horizontal gene transfer is often one of the dominant evolutionary events driving gene family evolution. In this work, we address this gap by conducting a thorough comparative evaluation of five different rooting methods using large collections of both simulated and empirical prokaryotic gene trees. Our simulation study is based on 6000 true and reconstructed gene trees on 100 species and characterizes the rooting accuracy of the four methods under 36 different evolutionary conditions and 3 levels of gene tree reconstruction error. The empirical study is based on a large, carefully designed data set of 3098 gene trees from 504 bacterial species (406 Alphaproteobacteria and 98 Cyanobacteria) and reveals insights that supplement those gleaned from the simulation study. Overall, this work provides several valuable insights into the accuracy of the considered methods that will help inform the choice of rooting methods to use when studying microbial gene family evolution. Among other findings, this study identifies parsimonious Duplication-Transfer-Loss (DTL) rooting and Minimal Ancestor Deviation (MAD) rooting as two of the most accurate gene tree rooting methods for prokaryotes and specifies the evolutionary conditions under which these methods are most accurate, demonstrates that DTL rooting is highly sensitive to high evolutionary rates and gene tree error, and that rooting methods based on branch-lengths are generally robust to gene tree reconstruction error.

SaGePhy: an improved phylogenetic simulation framework for gene and subgene evolution.

SUMMARY: SaGePhy is a software package for improved phylogenetic simulation of gene and subgene evolution. SaGePhy can be used to generate species trees, gene trees and subgene or (protein) domain trees using a probabilistic birth-death process that allows for gene and subgene duplication, horizontal gene and subgene transfer and gene and subgene loss. SaGePhy implements a range of important features not found in other phylogenetic simulation frameworks/software. These include (i) simulation of subgene or domain level evolution inside one or more gene trees, (ii) simultaneous simulation of both additive and replacing horizontal gene/subgene transfers and (iii) probabilistic sampling of species tree and gene tree nodes, respectively, for gene- and domain-family birth. SaGePhy is open-source, platform independent and written in Java and Python. AVAILABILITY AND IMPLEMENTATION: Executables, source code (open-source under the revised BSD license) and a detailed manual are freely available from http://compbio.engr.uconn.edu/software/sagephy/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.