SARS-CoV-2 infections before, during, and after the Omicron wave: a 2-year Indian community cohort study.

Background: We measured the incidence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections and re-infections in an adult community-based cohort in southern India. Methods: We conducted a 2-year follow-up on 1229 participants enrolled between May and October 2021. Participants provided vaccination histories, weekly saliva samples, and blood samples at 0, 6, 12, and 24 months. Salivary reverse transcription polymerase chain reaction (RT-PCR) and Meso-Scale Discovery panels were used for SARS-CoV-2 detection and anti-spike, anti-nucleocapsid immunoglobulin G quantification. Whole genome sequencing was performed on a subset of positive samples. SARS-CoV-2 infection incidence was measured across Pre-Omicron (May-December 2021), Omicron-I (December 2021-June 2022), and Omicron-II (July 2022-October 2023) periods. Findings: In total, 1166 (95%) participants with 83% seropositivity at baseline completed the follow-up, providing 2205 person-years of observation. Utilizing both RT-PCR and serology we identified 1306 infections and yielded an incidence rate of 591.3 per 1000 person-years (95% confidence interval, 559.6-624.3), which peaked during Omicron-I at 1418.1 per 1000 person-years (95% confidence interval, 1307.4-1535.6). During Omicron-I and II, neither prior infection nor vaccination conferred protection against infection. Overall, 74% of infections were asymptomatic. Interpretation: Integrated RT-PCR and serology revealed significant SARS-CoV-2 infection frequency, highlighting the prevalence of asymptomatic cases among previously infected or vaccinated individuals. This underscores the effectiveness of combining surveillance strategies when monitoring pandemic trends and confirms the role of non-invasive sampling in ensuring participant compliance, reflecting national transmission patterns. Funding: The study was funded by the Bill and Melinda Gates Foundation.

AMLdb: a comprehensive multi-omics platform to identify biomarkers and drug targets for acute myeloid leukemia.

Acute myeloid leukemia (AML) is one of the leading leukemic malignancies in adults. The heterogeneity of the disease makes the diagnosis and treatment extremely difficult. With the advent of next-generation sequencing (NGS) technologies, exploration at the molecular level for the identification of biomarkers and drug targets has been the focus for the researchers to come up with novel therapies for better prognosis and survival outcomes of AML patients. However, the huge amount of data from NGS platforms requires a comprehensive AML platform to streamline literature mining efforts and save time. To facilitate this, we developed AMLdb, an interactive multi-omics platform that allows users to query, visualize, retrieve, and analyse AML related multi-omics data. AMLdb contains 86 datasets for gene expression profiles, 15 datasets for methylation profiles, CRISPR-Cas9 knockout screens of 26 AML cell lines, sensitivity of 26 AML cell lines to 288 drugs, mutations in 41 unique genes in 23 AML cell lines, and information on 41 experimentally validated biomarkers. In this study, we have reported five genes, i.e. CBFB, ENO1, IMPDH2, SEPHS2, and MYH9 identified via our analysis using AMLdb. ENO1 is uniquely identified gene which requires further investigation as a novel potential target while other reported genes have been previously confirmed as targets through experimental studies. Top of form we believe that these findings utilizing AMLdb can make it an invaluable resource to accelerate the development of effective therapies for AML and assisting the research community in advancing their understanding of AML pathogenesis. AMLdb is freely available at https://project.iith.ac.in/cgntlab/amldb.

AagingBase: a comprehensive database of anti-aging peptides.

The process of aging is an intrinsic and inevitable aspect of life that impacts every living organism. As biotechnological advancements continue to shape our understanding of medicine, peptide therapeutics have emerged as a promising strategy for anti-aging interventions. This is primarily due to their favorable attributes, such as low immunogenicity and cost-effective production. Peptide-based treatments have garnered widespread acceptance and interest in aging research, particularly in the context of age-related therapies. To effectively develop anti-aging treatments, a comprehensive understanding of the physicochemical characteristics of anti-aging peptides is essential. Factors such as amino acid composition, instability index, hydrophobic areas and other relevant properties significantly determine their efficacy as potential therapeutic agents. Consequently, the creation of 'AagingBase', a comprehensive database for anti-aging peptides, aims to facilitate research on aging by leveraging the potential of peptide therapies. AagingBase houses experimentally validated 282 anti-aging peptides collected from 54 research articles and 236 patents. Employing state-of-the-art computational techniques, the acquired sequences have undergone rigorous physicochemical calculations. Furthermore, AagingBase presents users with various informative analyses highlighting atomic compositions, secondary structure fractions, tertiary structure, amino acid compositions and frequencies. The database also offers advanced search and filtering options and similarity search, thereby aiding researchers in understanding their biological functions. Hence, the database enables efficient identification and prioritization of potential peptide candidates in geriatric medicine and holds immense potential for advancing geriatric medicine research and innovations. AagingBase can be accessed without any restriction. Database URL: https://project.iith.ac.in/cgntlab/aagingbase/.

MyeloDB: a multi-omics resource for multiple myeloma.

Multiple myeloma (MM) is a common type of blood cancer affecting plasma cells originating from the lymphoid B-cell lineage. It accounts for about 10% of all hematological malignancies and can cause significant end-organ damage. The emergence of genomic technologies such as next-generation sequencing and gene expression analysis has opened new possibilities for early detection of multiple myeloma and identification of personalized treatment options. However, there remain significant challenges to overcome in MM research, including integrating multi-omics data, achieving a comprehensive understanding of the disease, and developing targeted therapies and biomarkers. The extensive data generated by these technologies presents another challenge for data analysis and interpretation. To bridge this gap, we have developed a multi-omics open-access database called MyeloDB. It includes gene expression profiling, high-throughput CRISPR-Cas9 screens, drug sensitivity resources profile, and biomarkers. MyeloDB contains 47 expression profiles, 3 methylation profiles comprising a total of 5630 patient samples and 25 biomarkers which were reported in previous studies. In addition to this, MyeloDB can provide significant insight of gene mutations in MM on drug sensitivity. Furthermore, users can download the datasets and conduct their own analyses. Utilizing this database, we have identified five novel genes, i.e., CBFB, MANF, MBNL1, SEPHS2, and UFM1 as potential drug targets for MM. We hope MyeloDB will serve as a comprehensive platform for researchers and foster novel discoveries in MM. MyeloDB Database URL: https://project.iith.ac.in/cgntlab/myelodb/ .

Deep learning-based classifier of diffuse large B-cell lymphoma cell-of-origin with clinical outcome.

Diffuse large B-cell lymphoma (DLBCL) is an aggressive form of non-Hodgkin lymphoma with poor response to R-CHOP therapy due to remarkable heterogeneity. Based on gene expression, DLBCL cases were divided into two subtypes, i.e. ABC and GCB, where ABC subtype is associated with poor outcomes. Due to its association with clinical outcome, this classification, also known as cell-of-origin (COO), is an efficient way to predict the response to R-CHOP therapy. Previous COO classification methods have some shortcomings, e.g. limited number of samples in the training dataset. These shortcomings challenge the robustness of methods and make it difficult to implicate these methods at clinical level. To overcome the shortcomings of previous methods, we developed a deep learning-based classifier model on a cohort of 381 DLBCL patients using expression data of 20 genes. We implemented multilayer perceptron (MLP) to train deep learning-based classifier, named MLP-COO. MLP-COO achieved accuracy of 99.70% and 94.70% on training and testing datasets, respectively, with 10-fold cross-validation. We also assessed its performance on an independent dataset of 294 DLBCL patients. On independent dataset, we achieved an accuracy of 95.90% with MCC of 0.917. To show its broader applicability, we used this classifier to predict the clinical outcome using survival data from two large cohorts of DLBCL patients. In survival analysis, MLP-COO recapitulates the survival probabilities of DLBCL patients based on their COO in both cohorts. We anticipate that MLP-COO model developed in this study will benefit in the accurate COO prediction of DLBCL patients and their clinical outcomes.

Botanicals and Oral Stem Cell Mediated Regeneration: A Paradigm Shift from Artificial to Biological Replacement.

Stem cells are a well-known autologous pluripotent cell source, having excellent potential to develop into specialized cells, such as brain, skin, and bone marrow cells. The oral cavity is reported to be a rich source of multiple types of oral stem cells, including the dental pulp, mucosal soft tissues, periodontal ligament, and apical papilla. Oral stem cells were useful for both the regeneration of soft tissue components in the dental pulp and mineralized structure regeneration, such as bone or dentin, and can be a viable substitute for traditionally used bone marrow stem cells. In recent years, several studies have reported that plant extracts or compounds promoted the proliferation, differentiation, and survival of different oral stem cells. This review is carried out by following the PRISMA guidelines and focusing mainly on the effects of bioactive compounds on oral stem cell-mediated dental, bone, and neural regeneration. It is observed that in recent years studies were mainly focused on the utilization of oral stem cell-mediated regeneration of bone or dental mesenchymal cells, however, the utility of bioactive compounds on oral stem cell-mediated regeneration requires additional assessment beyond in vitro and in vivo studies, and requires more randomized clinical trials and case studies.

Geriatric Mental Healthcare Training: A Mini-Fellowship Approach to Interprofessional Assessment and Management of Geriatric Mental Health Issues.

INTRODUCTION: The population in United States aged 65 and older has rapidly grown and is projected to grow faster than any other segment of the population. Despite this demographic shift, the nation's geriatric workforce is shrinking. AIM: The primary goal of the fellowship was to form a learning collaborative that would help trainees in medicine, nursing, social work, pharmacy and occupational/physical therapy understand the roles of each discipline involved in the provision of geriatric mental healthcare and to enhance basic knowledge of common geriatric syndromes. METHODS: Faculty from the University of Pittsburgh developed a format for the mini-fellowship. Trainees from five disciplines were recruited for participation in the mini-fellowship. This was offered annually over four-year period, hosted by the John A. Hartford Foundation Centers of Excellence in Geriatric Psychiatry at the University of Pittsburgh and University of California at San Diego. RESULTS: Eighty-one participants across five schools of the health sciences completed the mini-fellowship. Feedback was positive: most participants appreciated learning from other team members, endorsed appreciation of the contributions of other disciplines to patient care, and reported improved understanding of three major geriatric syndromes. CONCLUSION: Conducting an interdisciplinary mini-fellowship in geriatric mental health was feasible and well received by trainees. The fellowship enabled better appreciation for the provision of geriatric mental health care within the context of an interprofessional team. However, decanal and faculty leadership across the schools needs to place greater emphasis on the importance of interprofessional team-based learning and to free up time for such activity.

Malignant Hyperthermia.

Malignant Hyperthermia (MH) is a life-threatening pharmacogenetic disorder which results from exposure to volatile anesthetic agents and depolarizing muscle relaxants. It manifests as a hypermetabolic response resulting in tachycardia, tachypnea, hyperthermia, hypercapnia, acidosis, muscle rigidity and rhabdomyolysis. An increase in the end-tidal carbon dioxide is one of the earliest diagnostic signs. Dantrolene sodium is effective in the management of MH, and should be available whenever general anesthesia is administered. This review also aims to highlight the genetics and pathology of MH, along with its association with various inherited myopathy syndromes like central core disease, multi-mini core disease, Native-American myopathy, and King-Denborough syndrome.

Cerebral Fat Embolism: Neuroprotective Goals in an Unusual Cause of Altered Mental Status.

Cerebral fat embolism syndrome is a rare, but potentially lethal, complication that may arise from long bone fractures and/or orthopaedic surgery. Neurological symptoms are variable, and clinical diagnosis is difficult. We report the case of a 75-year-old woman who developed cerebral fat embolism four days after a right hip arthroplasty. Maintenance of intracranial pressure monitoring (ICP) within normal limits and cerebral tissue oxygenation monitoring (PbtO2) over 20 mmHg prevented secondary brain injury and resulted in a gradual improvement of the patient's sensorium. This case demonstrates that the use of ICP and PbtO2 monitoring defines optimal neuroprotective goals.

Glia Maturation Factor and Mast Cell-Dependent Expression of Inflammatory Mediators and Proteinase Activated Receptor-2 in Neuroinflammation.

Parkinson's disease (PD) is characterized by the presence of inflammation-mediated dopaminergic neurodegeneration in the substantia nigra. Inflammatory mediators from activated microglia, astrocytes, neurons, T-cells and mast cells mediate neuroinflammation and neurodegeneration. Administration of neurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induces PD like motor deficits in rodents. 1-methyl-4-phenylpyridinium (MPP+), a toxic metabolite of MPTP activates glial cells, neurons and mast cells to release neuroinflammatory mediators. Glia maturation factor (GMF), mast cells and proteinase activated receptor-2 (PAR-2) are implicated in neuroinflammation. Alpha-synuclein which induces neurodegeneration increases PAR-2 expression in the brain. However, the exact mechanisms are not yet understood. In this study, we quantified inflammatory mediators in the brains of MPTP-administered wild type (Wt), GMF-knockout (GMF-KO), and mast cell knockout (MC-KO) mice. Additionally, we analyzed the effect of MPP+, GMF, and mast cell proteases on PAR-2 expression in astrocytes and neurons in vitro. Results show that the levels of interleukin-1beta (IL-1ß), tumor necrosis factor-alpha (TNF-α), and the chemokine (C-C motif) ligand 2 (CCL2) were lesser in the brains of GMF-KO mice and MC-KO mice when compared to Wt mice brain after MPTP administration. Incubation of astrocytes and neurons with MPP+, GMF, and mouse mast cell protease-6 (MMCP-6) and MMCP-7 increased the expression of PAR-2. Our studies show that the absence of mast cells and GMF reduce the expression of neuroinflammatory mediators in the brain. We conclude that GMF along with mast cell interactions with glial cells and neurons during neuroinflammation can be explored as a new therapeutic target for PD and other neuroinflammatory disorders.

The Expression of B7-H3 Molecule in Periodontal Disease.

STATEMENT OF THE PROBLEM: T cells have been shown to play a role in the etiopathogenesis of periodontal disease. B7-H3, a costimulatory molecule, is found to be associated with regulation of T cell function in some tumoral tissues, as well as autoimmune and inflammatory diseases. PURPOSE: The aim of this study was to investigate the expression of B7-H3 molecule in healthy and diseased gingival tissue samples. MATERIALS AND METHOD: Gingival samples were taken from 2 groups (A and B) representing periodontal health and periodontal disease, respectively. These were paraffinized and processed to carry out immunostaining to identify B7-H3 expression. The slides were then examined under light microscope to assess the positive staining in epithelium and connective tissue. The intensity of positive staining in epithelium and the number of positive cells in the connective tissue were evaluated. Statistical analysis was done using kappa analysis and independent t-test. RESULTS: Kappa analysis revealed good inter-examiner agreement for both the groups (group A: 0.718; group B: 0.797). Intensity of staining in the epithelium ranged from intense to moderate for both the groups. In the connective tissue, there was a statistically insignificant decrease (p value= 0.415) in the number of positive cells from group A (mean labeling index: 50.28±26.09) to group B (mean labeling index= 41.37±25.29). CONCLUSION: B7-H3 molecule has been found to be expressed in gingival tissue samples; however, it showed a statistically insignificant decrease in periodontal disease group compared to healthy group.

Ultra-large alignments using phylogeny-aware profiles.

Many biological questions, including the estimation of deep evolutionary histories and the detection of remote homology between protein sequences, rely upon multiple sequence alignments and phylogenetic trees of large datasets. However, accurate large-scale multiple sequence alignment is very difficult, especially when the dataset contains fragmentary sequences. We present UPP, a multiple sequence alignment method that uses a new machine learning technique, the ensemble of hidden Markov models, which we propose here. UPP produces highly accurate alignments for both nucleotide and amino acid sequences, even on ultra-large datasets or datasets containing fragmentary sequences. UPP is available at https://github.com/smirarab/sepp .

Comprehensive, structurally-informed alignment and phylogeny of vertebrate biogenic amine receptors.

Biogenic amine receptors play critical roles in regulating behavior and physiology in both vertebrates and invertebrates, particularly within the central nervous system. Members of the G-protein coupled receptor (GPCR) family, these receptors interact with endogenous bioamine ligands such as dopamine, serotonin, and epinephrine, and are targeted by a wide array of pharmaceuticals. Despite the clear clinical and biological importance of these receptors, their evolutionary history remains poorly characterized. In particular, the relationships among biogenic amine receptors and any specific evolutionary constraints acting within distinct receptor subtypes are largely unknown. To advance and facilitate studies in this receptor family, we have constructed a comprehensive, high-quality sequence alignment of vertebrate biogenic amine receptors. In particular, we have integrated a traditional multiple sequence approach with robust structural domain predictions to ensure that alignment columns accurately capture the highly-conserved GPCR structural domains, and we demonstrate how ignoring structural information produces spurious inferences of homology. Using this alignment, we have constructed a structurally-partitioned maximum-likelihood phylogeny from which we deduce novel biogenic amine receptor relationships and uncover previously unrecognized lineage-specific receptor clades. Moreover, we find that roughly 1% of the 3039 sequences in our final alignment are either misannotated or unclassified, and we propose updated classifications for these receptors. We release our comprehensive alignment and its corresponding phylogeny as a resource for future research into the evolution and diversification of biogenic amine receptors.