Biomedical researchers are generating high-throughput, high-dimensional single-cell 5 data at a staggering rate. As costs of data generation decrease, experimental design is mov-6 ing towards measurement of many different single-cell samples in the same dataset. These 7 samples can correspond to different patients, conditions, or treatments. While scalability of 8 methods to datasets of these sizes is a challenge on its own, dealing with large-scale exper-9 imental design presents a whole new set of problems, including batch effects and sample 10 1 .

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Healthy donors exposed to Japanese encephalitis (JE) virus show a CD8+ T cell response that cross reacts with other flaviviruses. Patients that recovered from JE show a CD4+ T cell response that targets structural proteins of JE virus.

Handling the vast amounts of single-cell RNA-sequencing and CyTOF data, which are now being generated in patient cohorts, presents a computational challenge due to the noise, complexity, sparsity and batch effects present. Here, we propose a unified deep neural network-based approach to automatically process and extract structure from these massive datasets. Our unsupervised architecture, called SAUCIE (Sparse Autoencoder for Unsupervised Clustering, Imputation, and Embedding), simultaneously performs several key tasks for single-cell data analysis including 1) clustering, 2) batch correction, 3) visualization, and 4) denoising/imputation. SAUCIE is trained to recreate its own input after reducing its dimensionality in a 2-D embedding layer which can be used to visualize the data. Additionally, it uses two novel regularizations: (1) an information dimension regularization to penalize entropy as computed on normalized activation values of the layer, and thereby encourage binary-like encodings that are amenable to clustering and (2) a Maximal Mean Discrepancy penalty to correct batch effects. Thus SAUCIE has a single architecture that denoises, batch-corrects, visualizes and clusters data using a unified 1 . CC-BY 4.0 International license peer-reviewed) is the author/funder. It is made available under a

Japanese encephalitis virus (JEV) envelope (E) protein has been shown to play a critical role in attachment to cells. However, the receptor interacting with envelope protein has not been conclusively identified. Using mouse neuroblastoma (Neuro2a) cells and purified JEV-E protein in 'Virus Overlay Protein Binding Assay' followed by MALDI-TOF analysis, we identified 'heat shock protein 70' (Hsp70) as a possible receptor for JEV. Indirect immunofluorescence and flow-cytometry analysis demonstrated localization of Hsp70 on Neuro2a cell surface. Co-immunoprecipitation followed by Western blot analysis reconfirmed the interaction between Hsp70 and JEV-E protein. Further, anti-Hsp70 polyclonal-antibodies were able to block JEV entry into Neuro2a cells. Additionally, using the bioinformatic tool - FTDOCK, docking between the proteins was performed. Amongst six interacting structural poses studied one pose involving RGD motif on JEV-E and leucine(539) on Hsp70 displayed stable interaction. These observations indicate that Hsp70 serves as putative receptor for JEV in Neuro2A cells.

Most studies of cognitive functioning in human immunodeficiency virus type 1 (HIV-1)-seropositive (HIV-1+) subjects have been done in the United States and Europe, where clade B infections predominate. However, in other parts of the world such as South India, where clade C HIV is most common, the prevalence of HIV-1 is increasing. Standardized neuropsychological tests were used to assess cognitive functioning in a sample of 119 adults infected with clade C HIV-1 who were not on antiretroviral medications. The subjects did not have neurological or psychiatric illness and were functioning adequately. Neuropsychological test performance was compared with gender-, age-, and education-matched normative data derived from a sample of 540 healthy volunteers and a matched cohort of 126 healthy, HIV-1-seronegative individuals. Among the seropositive subjects, 60.5% had mild to moderate cognitive deficits characterized by deficits in the domains of fluency, working memory, and learning and memory. None of the subjects had severe cognitive deficits. The HIV-1+ sample was classified into groups according to the level of immune suppression as defined by CD4 count (< 200, 201-499, and > 500 cells/mm3) and viral load (< 5000, 5001-30,000, 30,001-99,999, 100,000-1,000,000, and > 1,000,001 copies). Although the most immunosuppressed group (CD4 count < 200 cells/mm3 or viral load > 1,000,001 copies) was small, their rate of impairment in visual working memory was greater when compared to groups with better immune functioning. Mild to moderate cognitive deficits can be identified on standardized neuropsychological tests in clade C-infected HIV-1+ adults who do not have any clinically identifiable functional impairment. The prevalence of cognitive deficits is similar to that reported in antiretroviral treatment-naïve individuals infected with clade B virus in the western world.

Late in 2020, two genetically-distinct clusters of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with mutations of biological concern were reported, one in the United Kingdom and one in South Africa. Using a combination of data from routine surveillance, genomic sequencing and international travel we track the international dispersal of lineages B.1.1.7 and B.1.351 (variant 501Y-V2). We account for potential biases in genomic surveillance efforts by including passenger volumes from location of where the lineage was first reported, London and South Africa respectively. Using the software tool grinch (global report investigating novel coronavirus haplotypes), we track the international spread of lineages of concern with automated daily reports, Further, we have built a custom tracking website (cov-lineages.org/global_report.html) which hosts this daily report and will continue to include novel SARS-CoV-2 lineages of concern as they are detected.

To investigate whether uncharacterized infectious agents were associated with neurologic disease, we analyzed cerebrospinal fluid specimens from 12 children with acute central nervous system infection. A high-throughput pyrosequencing screen detected human parvovirus 4 DNA in cerebrospinal fluid of 2 children with encephalitis of unknown etiology.