Symptom-based drug prediction of lifestyle-related chronic diseases using unsupervised machine learning techniques.

BACKGROUND AND OBJECTIVES: Lifestyle-related diseases (LSDs) impose a substantial economic burden on patients and health care services. LSDs are chronic in nature and can directly affect the heart and lungs. Therapeutic interventions only based on symptoms can be crucial for prompt treatment initiation in LSDs, as symptoms are the first information available to clinicians. So, this work aims to apply unsupervised machine learning (ML) techniques for developing models to predict drugs from symptoms for LSDs, with a specific focus on pulmonary and heart diseases. METHODS: The drug-disease and disease-symptom associations of 143 LSDs, 1271 drugs, and 305 symptoms were used to compute direct associations between drugs and symptoms. ML models with four different algorithms - K-Means, Bisecting K-Means, Mean Shift, and Balanced Iterative Reducing and Clustering using Hierarchies (BIRCH) - were developed to cluster the drugs using symptoms as features. The optimal model was saved in a server for the development of a web application. A web application was developed to perform the prediction based on the optimal model. RESULTS: The Bisecting K-means model showed the best performance with a silhouette coefficient of 0.647 and generated 138 drug clusters. The drugs within the optimal clusters showed good similarity based on i) gene ontology annotations of the gene targets, ii) chemical ontology annotations, and iii) maximum common substructure of the drugs. In the web application, the model also provides a confidence score for each predicted drug while predicting from a new set of input symptoms. CONCLUSION: In summary, direct associations between drugs and symptoms were computed, and those were used to develop a symptom-based drug prediction tool for LSDs with unsupervised ML models. The ML-based prediction can provide a second opinion to clinicians to aid their decision-making for early treatment of LSD patients. The web application (URL - http://bicresources.jcbose.ac.in/ssaha4/sdldpred) can provide a simple interface for all end-users to perform the ML-based prediction.

RegX3-dependent transcriptional activation of kdpDE and repression of rv0500A are linked to potassium homeostasis in Mycobacterium tuberculosis.

Ionic homeostasis is essential for the survival and replication of Mycobacterium tuberculosis within its host. Low potassium ion concentrations trigger a transition of M. tuberculosis into dormancy. Our current knowledge of the transcriptional regulation mechanisms governing genes involved in potassium homeostasis remains limited. Potassium transport is regulated by the constitutive Trk system and the inducible Kdp system in M. tuberculosis. The two-component system KdpDE (also known as KdpD/KdpE) activates expression of the kdpFABC operon, encoding the four protein subunits of the Kdp potassium uptake system (KdpFABC). We show that, under potassium deficiency, expression of the two-component system senX3/regX3 is upregulated, and bacterial survival is compromised in a regX3-inactivated mutant, ΔregX3. Electrophoretic mobility shift assays (EMSAs), promoter reporter assays and chromatin immunoprecipitation (ChIP) show that RegX3 binds to the kdpDE promoter and activates it under potassium deficiency, whereas RegX3 (K204A), a DNA binding-deficient mutant, fails to bind to the promoter. Mutation of the RegX3 binding motifs on the kdpDE promoter abrogates RegX3 binding. In addition, EMSAs and ChIP assays show that RegX3 represses Rv0500A, a repressor of kdpFABC, by binding to consensus RegX3 binding motifs on the rv0500A promoter. Our findings provide important insight into two converging pathways regulated by RegX3; one in which it activates an activator of kdpFABC, and the other in which it represses a repressor of kdpFABC, during potassium insufficiency. This culminates in increased expression of the potassium uptake system encoded by kdpFABC, enabling bacterial survival. These results further expand the growing transcriptional network in which RegX3 serves as a central node to enable bacterial survival under stress.

4-(Benzyloxy)phenol-induced p53 exhibits antimycobacterial response triggering phagosome-lysosome fusion through ROS-dependent intracellular Ca2+ pathway in THP-1 cells.

Drug-resistant tuberculosis (TB) outbreak has emerged as a global public health crisis. Therefore, new and innovative therapeutic options like host-directed therapies (HDTs) through novel modulators are urgently required to overcome the challenges associated with TB. In the present study, we have investigated the anti-mycobacterial effect of 4-(Benzyloxy)phenol. Cell-viability assay asserted that 50 µM of 4-(Benzyloxy)phenol was not cytotoxic to phorbol 12-myristate 13-acetate (PMA) differentiated THP-1 (dTHP-1) cells. It was observed that 4-(Benzyloxy)phenol activates p53 expression by hindering its association with KDM1A. Increased ROS, intracellular Ca2+ and phagosome-lysosome fusion, were also observed upon 4-(Benzyloxy)phenol treatment. 4-(Benzyloxy)phenol mediated killing of intracellular mycobacteria was abrogated in the presence of specific inhibitors of ROS, Ca2+ and phagosome-lysosome fusion like NAC, BAPTA-AM, and W7, respectively. We further demonstrate that 4-(Benzyloxy)phenol mediated enhanced ROS production is mediated by acetylation of p53. Blocking of p53 acetylation by Pifithrin-α (PFT- α) enhanced intracellular mycobacterial growth by blocking the mycobactericidal effect of 4-(Benzyloxy)phenol. Altogether, the results showed that 4-(Benzyloxy)phenol executed its anti-mycobacterial effect by modulating p53-mediated ROS production to regulate phagosome-lysosome fusion through Ca2+ production.

Fog caused distinct diversity of airborne bacterial communities enriched with pathogens over central Indo-Gangetic plain in India.

Fog causes enhancement of bacterial loading in the atmosphere. Current study represents the impact of occurrences of fog on the alteration of diversity of airborne bacteria and their network computed from metagenomic data of airborne samples collected at Arthauli (25.95°N, 85.10°E) situated at central Indo-Gangetic Plain (IGP) during 1-14 January 2021. A distinct bacterial diversity with a complex network is identified in foggy condition due to the enrichment of unique types of bacteria. Present investigation highlights a statistically significant enrichment of airborne pathogenic bacteria found in a unique ecosystem within air evolved due to the occurrences of fog over central IGP. In the foggy network, Cutibacterium, an opportunistic pathogen, is identified to be interacting maximum (21 edges) with other bacteria with statistically significant copresence relation, which are responsible for various infections for human beings. A 40-60% increase (p < 0.01) in the abundance of pathogenic bacteria for respiratory and skin diseases is noticed in fog period. Among the fog-enriched bacteria, Cutibacterium, Herbaspirillum, Paenibacillus, and Tsukamurella are examples of opportunistic bacteria causing various respiratory diseases, while Paenibacillus can even cause skin cancer and acute lymphoblastic leukemia.

Application of singular value decomposition analysis: Insights into the complex mechanisms of amyloidogenesis.

Amyloidogenesis, with its multifaceted nature spanning from peptide self-assembly to membrane-mediated structural transitions, presents a significant challenge for the interdisciplinary scientific community. Here, we emphasize on how Singular Value Decomposition (SVD) can be employed to reveal hidden patterns and dominant modes of interaction that govern the complex process of amyloidogenesis. We first utilize SVD analysis on Circular Dichroism (CD) spectral datasets to identify the intermediate structural species emerging during peptide-membrane interactions and to determine binding constants more precisely than conventional methods. We investigate the monomer loss kinetics associated with peptide self-assembly using Nuclear Magnetic Resonance (NMR) dataset and determine the global kinetic parameters through SVD. Furthermore, we explore the seeded growth of amyloid fibrils by analyzing a time-dependent NMR dataset, shedding light on the kinetic intricacies of this process. Our analysis uncovers two distinct states in the aggregation of Aß40 and pinpoints key residues responsible for this seeded growth. To strengthen our findings and enhance their robustness, we validate those using simulated data, thereby highlighting the physical interpretations derived from SVD. Overall, SVD analysis offers a model-free, global kinetic perspective, enabling the selection of optimal kinetic models. This study not only contributes valuable insights into the dynamics but also highlights the versatility of SVD in unravelling complex processes of amyloidogenesis.

Genome-wide identification and annotation of SNPs for economically important traits in Frieswal™, newly evolved crossbred cattle of India.

The Frieswal™ is a crossbred cattle evolved by ICAR-Central Institute for Research on Cattle utilizing more than 15,000 cattle maintained at more than 37 military farms spread all over the agro-climatic regions of the country. The ddRAD sequencing method was used to identify and annotate the SNPs and INDELs. The results of variant calling revealed 1,487,851 SNPs and 128,175 INDELs at a read depth of 10. A total of 3,775,079 effects were identified, and majority (66.41%) of the effects were in the intron region of the genome followed by intergenic (21.87%). Majority (99.18%) of the variants had the modifier effect. The results revealed a higher magnitude of transitions as compared to the transversion. The classification of SNPs by functional class revealed a majority of missense (43%) and silent (56%) effects. Out of 26,278 genes identified, 1841 SNPs were annotated in 207 candidate genes responsible for various milk production and reproduction traits. The observed heterozygosity was 0.2804 against the expected heterozygosity value of 0.2978. The overall average inbreeding coefficient (FIS) was 0.0604. The pathway analysis revealed that the prolactin signaling pathway (GO:0038161) was significant biological process complete for both milk production and reproduction traits. The SNP variations can be effectively used as markers for early and accurate identification of the QTLs and for formulating an efficient and effective breed improvement program in Frieswal™ cattle. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-023-03701-0.

Updates on Databases of Allergens and Allergen-Epitopes.

The increasing prevalence of allergic diseases is of great public health concern. Environmental and food allergens are the major triggers of allergic diseases via respiratory or gastrointestinal routes, respectively. A major setback in the clinical management of allergies is the unavailability of purified allergens required for diagnostic purposes. Furthermore, manipulation of allergen sequences and structures by employing protein-engineering approaches is needed to design immunotherapeutic vaccines. All these approaches rely upon the sequence, structure, and epitope location of allergens. A number of databases have therefore been developed that serve as repositories of molecular information of allergens. In this chapter, we discuss the five most important widely used allergen databases that might be helpful for the research community working on molecular allergology.

Computational Vaccine Design for Common Allergens.

In this chapter, the steps of designing candidate vaccine molecules for allergen-specific immunotherapy (AIT) using immunoinformatics are described. The most modern approach of AIT deals with carrier-bound B cell epitope and multi-epitope vaccine molecules. The strategy for designing these molecules and the bioinformatics tools and servers used for that are discussed in detail here.

Tumor-Associated CD19+CD39- B Regulatory Cells Deregulate Class-Switch Recombination to Suppress Antibody Responses.

B cells are an essential component of humoral immunity. Their primary function is to mount antigen-specific antibody responses to eliminate pathogens. Despite an increase in B-cell number, we found that serum-IgG levels were low in patients with breast cancer. To solve this conundrum, we used high-dimensional flow cytometry to analyze the heterogeneity of B-cell populations and identified a tumor-specific CD19+CD24hiCD38hi IL10-producing B regulatory (Breg)-cell subset. Although IL10 is a Breg-cell marker, being an intracellular protein, it is of limited value for Breg-cell isolation. Highly expressed Breg-cell surface proteins CD24 and CD38 also impede the isolation of viable Breg cells. These are hurdles that limit understanding of Breg-cell functions. Our transcriptomic analysis identified, CD39-negativity as an exclusive, sorting-friendly surface marker for tumor-associated Breg cells. We found that the identified CD19+CD39‒IL10+ B-cell population was suppressive in nature as it limited T helper-cell proliferation, type-1 cytokine production, and T effector-cell survival, and augmented CD4+FOXP3+ regulatory T-cell generation. These tumor-associated Breg cells were also found to restrict autologous T follicular helper-cell expansion and IL21 secretion, thereby inhibiting germinal transcript formation and activation-induced cytidine deaminase expression involved in H-chain class-switch recombination (CSR). This isotype-switching abnormality was shown to hinder B-cell differentiation into class-switched memory B cells and subsequent high-affinity antibody-producing plasma B cells, which collectively led to the dampening of IgG-mediated antibody responses in patients with cancer. As low IgG is associated with poor prognosis in patients with cancer, Breg-cell depletion could be a promising future therapy for boosting plasma B cell-mediated antibody responses.

Ydj1 interaction at nucleotide-binding-domain of yeast Ssa1 impacts Hsp90 collaboration and client maturation.

Hsp90 constitutes one of the major chaperone machinery in the cell. The Hsp70 assists Hsp90 in its client maturation though the underlying basis of the Hsp70 role remains to be explored. In the present study, using S. cerevisiae strain expressing Ssa1 as sole Ssa Hsp70, we identified novel mutations in the nucleotide-binding domain of yeast Ssa1 Hsp70 (Ssa1-T175N and Ssa1-D158N) that adversely affect the maturation of Hsp90 clients v-Src and Ste11. The identified Ssa1 amino acids critical for Hsp90 function were also found to be conserved across species such as in E.coli DnaK and the constitutive Hsp70 isoform (HspA8) in humans. These mutations are distal to the C-terminus of Hsp70, that primarily mediates Hsp90 interaction through the bridge protein Sti1, and proximal to Ydj1 (Hsp40 co-chaperone of Hsp70 family) binding region. Intriguingly, we found that the bridge protein Sti1 is critical for cellular viability in cells expressing Ssa1-T175N (A1-T175N) or Ssa1-D158N (A1-D158N) as sole Ssa Hsp70. The growth defect was specific for sti1Δ, as deletion of none of the other Hsp90 co-chaperones showed lethality in A1-T175N or A1-D158N. Mass-spectrometry based whole proteome analysis of A1-T175N cells lacking Sti1 showed an altered abundance of various kinases and transcription factors suggesting compromised Hsp90 activity. Further proteomic analysis showed that pathways involved in signaling, signal transduction, and protein phosphorylation are markedly downregulated in the A1-T175N upon repressing Sti1 expression using doxycycline regulatable promoter. In contrast to Ssa1, the homologous mutations in Ssa4 (Ssa4-T175N/D158N), the stress inducible Hsp70 isoform, supported cell growth even in the absence of Sti1. Overall, our data suggest that Ydj1 competes with Hsp90 for binding to Hsp70, and thus regulates Hsp90 interaction with the nucleotide-binding domain of Hsp70. The study thus provides new insight into the Hsp70-mediated regulation of Hsp90 and broadens our understanding of the intricate complexities of the Hsp70-Hsp90 network.

BCSCdb: a database of biomarkers of cancer stem cells.

Cancer stem cells (CSCs) are a small heterogeneous population present within the tumor cells exhibiting self-renewal properties. CSCs have been demonstrated to elicit an important role in cancer recurrence, metastasis and drug resistance. CSCs are distinguished from cancer cell populations based on their molecular profiling or expression of distinct CSC biomarker(s). Recently, a huge amount of omics data have been generated for the characterization of CSCs, which enables distinguishing CSCs in different cancers. Here, we report biomarkers of the Cancer Stem Cells database (BCSCdb), a repository of information about CSC biomarkers. BCSCdb comprises CSC biomarkers collected from PubMed literature where these are identified using high-throughput and low-throughput methods. Each biomarker is provided with two different scores: the first is a confidence score to give confidence to reported CSC biomarkers based on the experimental method of detection in CSCs. The second is the global score to identify the global CSC biomarkers across 10 different types of cancer. This database contains three tables containing information about experimentally validated CSC biomarkers or genes, therapeutic target genes of CSCs and CSC biomarkers interactions. It contains information on three types of markers: high-throughput marker (HTM-8307), high-throughput marker validated by the low-throughput method (283) and low-throughput marker (LTM-525). A total of 171 low-throughput biomarkers were identified in primary tissue referred to as clinical biomarkers. Moreover, it contains 445 target genes for CSC therapeutics, 10 biomarkers targeted by clinical trial drugs in CSCs and 5 different types of interaction data for CSC biomarkers. BCSCdb is an online resource for CSC biomarkers, which will be immensely helpful in the cancer research community and is freely available. Database URL: http://dibresources.jcbose.ac.in/ssaha4/bcscdb.

A systems approach to decipher a role of transcription factor RegX3 in the adaptation of Mycobacterium tuberculosis to hypoxic stress.

Two-component systems (TCSs) are required for the ability of Mycobacterium tuberculosis to respond to stress. The paired TCS, SenX3-RegX3 is known to respond to phosphate starvation and acid stress. The other stress conditions under which RegX3 is required for M. tuberculosis to mount an appropriate response, remain incompletely understood. Here we have employed genome-wide microarray profiling to compare gene expression in a ΔregX3 mutant with the wild-type under phosphate stress, in order to gain information on the probable RegX3 regulon. We pulled out a set of 128 hypoxia-associated genes, which could potentially be regulated by RegX3, by overlapping the gene set downregulated at least twofold in ΔregX3 with the gene set reported in the literature to be associated with the response to hypoxia. We identified potential RegX3 binding inverted repeats at the loci of 41 of these genes, in silico. We also observed that ΔregX3 was attenuated in terms of its ability to withstand hypoxia, and this was reversed upon complementation with regX3, corroborating a role of RegX3 in the response of M. tuberculosis to hypoxia. We validated the binding of RegX3 at the upstream regions of a selected set of these genes. Electrophoretic mobility shift assays (EMSAs) confirmed that RegX3 binds to the upstream regions of the hypoxia-associated genes Rv3334, whiB7, Rv0195, Rv0196 and Rv1960c. Gene expression analyses showed that the expression of these genes is regulated by RegX3 under hypoxia. We also show that the expression of whiB7, Rv3334 and Rv0195 in macrophage-grown M. tuberculosis, is dependent on RegX3. Finally, we show that attenuation of survival of ΔregX3 under hypoxia is partly reversed upon overexpression of either Rv0195 or Rv3334, suggesting that the RegX3-Rv0195 and the RegX3-Rv3334 axis are involved in the adaptation of M. tuberculosis to a hypoxic environment.

Identification of small molecules targeting homoserine acetyl transferase from Mycobacterium tuberculosis and Staphylococcus aureus.

There is an urgent need to validate new drug targets and identify small molecules that possess activity against both drug-resistant and drug-sensitive bacteria. The enzymes belonging to amino acid biosynthesis have been shown to be essential for growth in vitro, in vivo and have not been exploited much for the development of anti-tubercular agents. Here, we have identified small molecule inhibitors targeting homoserine acetyl transferase (HSAT, MetX, Rv3341) from M. tuberculosis. MetX catalyses the first committed step in L-methionine and S-adenosyl methionine biosynthesis resulting in the formation of O-acetyl-homoserine. Using CRISPRi approach, we demonstrate that conditional repression of metX resulted in inhibition of M. tuberculosis growth in vitro. We have determined steady state kinetic parameters for the acetylation of L-homoserine by Rv3341. We show that the recombinant enzyme followed Michaelis-Menten kinetics and utilizes both acetyl-CoA and propionyl-CoA as acyl-donors. High-throughput screening of a 2443 compound library resulted in identification of small molecule inhibitors against MetX enzyme from M. tuberculosis. The identified lead compounds inhibited Rv3341 enzymatic activity in a dose dependent manner and were also active against HSAT homolog from S. aureus. Molecular docking of the identified primary hits predicted residues that are essential for their binding in HSAT homologs from M. tuberculosis and S. aureus. ThermoFluor assay demonstrated direct binding of the identified primary hits with HSAT proteins. Few of the identified small molecules were able to inhibit growth of M. tuberculosis and S. aureus in liquid cultures. Taken together, our findings validated HSAT as an attractive target for development of new broad-spectrum anti-bacterial agents that should be effective against drug-resistant bacteria.

Designing Next-Generation Vaccines Against Common Pan-Allergens Using In Silico Approaches.

Next-generation allergy vaccines refer to allergen-derived attenuated molecules that can boost allergen-blocking IgG response. These IgG antibodies are specifically directed toward the IgE epitope of allergens and interfere in allergen-IgE interaction. Our study is a computational approach to design such vaccines against four widespread pan-allergens families. Pan-allergens display extensive immunological cross-reactivity due to the presence of conserved IgE epitope and T cell epitope. In this study, the vaccine design is based on hapten-carrier concept in which the carrier protein is an immunogenic component providing T cell help. Either PreS protein of hepatitis B or cholera enterotoxin B (CTB) fused with three tetanus toxoid fragments (TTFrC) was used here as the carrier. The hapten components are nonanaphylactic peptides (NAPs) derived from experimentally determined antigenic regions of the allergens. The charged residues of NAPs are selectively modified to obliterate IgE, as well as T cell reaction, and hence, are safe to apply in allergy patients. Various combinations of vaccine constructs (PreS/CTB+TTFrC and NAPs) were designed with intermediate linker motifs. Screening of constructs was performed through a three-step method such as physicochemical parameters, secondary structures, and tertiary structures using various bioinformatic tools. The final construct with best quality and stability was selected for each allergen family. Suitability of these constructs for being expressed in recombinant form was checked at DNA, RNA, and protein level. Presence of putative epitopes inducing tolerogenic interleukin-10 was also predicted for these constructs. The present work led to the design of putative vaccines with immunotherapeutic potential and broad applicability for allergic diseases caused by a wide array of cross-reactive allergens.

LHSPred: A web based application for predicting lung health severity.

Background and objectives: The computed tomography (CT) scan facilities are crucial for diagnosis of pulmonary diseases and are overburdened during the current pandemic of novel coronavirus disease 2019 (COVID-19). LHSPred (Lung Health Severity Prediction) is a web based tool that enables users to determine a score that evaluates CT scans, without radiologist intervention, and predict risk of pneumonia with features of blood examination and age of patient. It can help in early assessment of lung health severity of patients without CT-scan results and also enable monitoring of post-COVID lung health for recovered patients. Methods: This tool uses Support Vector Regression (SVR) and Multi-Layer Perceptron Regression (MLPR), trained on COVID-19 patient data reported in the literature. It allows to compute a score (CT severity score) that evaluates the involvement of lesions in lung lobes and to predict risk of pneumonia. A web application was implemented that uses the trained regression models. Results: The application has proven to be effective and user friendly in a clinical setting for pulmonary disease treatment. The SVR model achieved Pearson correlation coefficient (PCC) of 0.77 and mean absolute error (MAE) of 2.239 while determining the computed tomography (CT) severity score. The MLPR model achieved PCC of 0.77 and MAE of 2.309. Thus, it can be applied as a useful tool in predicting pneumonia in the post COVID-19 era. Conclusion: LHSPred can be used as a decision support system by the clinicians and as a tool for self-assessment by the patients with only six blood test input features.

Meta-analysis of sputum microbiome studies identifies airway disease-specific taxonomic and functional signatures.

Introduction. Studying taxonomic and functional signatures of respiratory microbiomes provide a better understanding of airway diseases.Gap Statement. Several human airway metagenomics studies have identified taxonomic and functional features restricted to a single disease condition and the findings are not comparable across airway diseases due to use of different samples, NGS platforms, and bioinformatics databases and tools.Aim. To study the microbial taxonomic and functional components of sputum microbiome across airway diseases and healthy smokers.Methodology. Here, 57 whole metagenome shotgun sequencing (WMSS) runs coming from the sputum of five airway diseases: asthma, bronchiectasis, chronic obstructive pulmonary diseases (COPD), cystic fibrosis (CF), tuberculosis (TB), and healthy smokers as the control were reanalysed using a common WMSS analysis pipeline.Results. Shannon's index (alpha diversity) of the healthy smoker group was the highest among all. The beta diversity showed that the sputum microbiome is distinct in major airway diseases such as asthma, COPD and cystic fibrosis. The microbial composition based on differential analysis showed that there are specific markers for each airway disease like Acinetobacter bereziniae as a marker for COPD and Achromobacter xylosoxidans as a marker of cystic fibrosis. Pathways and metabolites identified from the sputum microbiome of these five diseases and healthy smokers also show specific markers. 'ppGpp biosynthesis' and 'purine ribonucleosides degradation' pathways were identified as differential markers for bronchiectasis and COPD. In this meta-analysis, besides bacteria kingdom, Aspergillus fumigatus was detected in asthma and COPD, and Roseolovirus human betaherpesvirus 7 was detected in COPD. Our analysis showed that the majority of the gene families specific to the drug-resistant associated genes were detected from opportunistic pathogens across all the groups.Conclusion. In summary, the specific species in the sputum of airway diseases along with the microbial features like specific gene families, pathways, and metabolites were identified which can be explored for better diagnosis and therapy.

Cloning and immunobiochemical analyses on recombinant chymopapain allergen Cari p 2 showing pollen-fruit cross-reaction.

Papaya is reported to trigger food and respiratory allergy. Here, we identified chymopapain Cari p 2 as an allergen that can sensitize atopic individuals through fruit consumption followed by respiratory hazards through pollen exposure. Recombinant Cari p 2 displayed IgE-reactivity with 78% of papaya allergic sera. rCari p 2 also displayed allergenic activity through basophil degranulation. rCari p 2 is correctly folded and showed irreversible denaturation in the melting curve. rCari p 2 displayed IgE-cross-reactivity with homologous cysteine proteases from kiwi and pineapple. Cari p 2 transcript was also detected in papaya pulps. rCari p 2 was resistant to pepsin digestion and retained IgE-reactivity after 60 minutes of pepsin digestion. In mouse model, rCari p 2 was found to elicit inflammatory responses in the lung and gastrointestinal epithelium. Hence, Cari p 2 is a newly characterized allergen with diagnostic and immunotherapeutic potential for managing allergic disorders in papaya sensitized individuals.

Disruption of redox homeostasis with synchronized activation of apoptosis highlights the antifilarial efficacy of novel piperine derivatives: An in vitro mechanistic approach.

A series of novel piperine derivatives were synthesized with high yield and were evaluated for its antifilarial potential against the bovine filarial parasite Setaria cervi. Among 21 (3a-3u) compounds screened, three of them (3k, 3l, 3s) showed significant potential against all the developmental stages (oocytes, microfilariae and adult) of the filarial worm in time and dose dependent manner. 3l showed the highest efficacy among the selected three compounds. These three compounds were further evaluated for both in vitro and in vivo toxicity analyses which further fortified the benign nature of the selected compounds. The antifilarial activities they exhibited were clearly fuelled through disparity of the internal redox homeostasis as evidenced from the alterations in the enzymatic and non-enzymatic antioxidants level which ultimately shifted towards activation of pro-apoptotic signaling cascade eventually leading to the death of the parasites. The ability of the compound 3l to bind thioredoxin reductase and CED-3 protein are the key findings of this study. The present study supported with several biological experiments is therefore a maiden report on the antifilarial effectiveness of these novel piperine derivatives.

Perspectives About Modulating Host Immune System in Targeting SARS-CoV-2 in India.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the causative agent of coronavirus induced disease-2019 (COVID-19), is a type of common cold virus responsible for a global pandemic which requires immediate measures for its containment. India has the world's largest population aged between 10 and 40 years. At the same time, India has a large number of individuals with diabetes, hypertension and kidney diseases, who are at a high risk of developing COVID-19. A vaccine against the SARS-CoV-2, may offer immediate protection from the causative agent of COVID-19, however, the protective memory may be short-lived. Even if vaccination is broadly successful in the world, India has a large and diverse population with over one-third being below the poverty line. Therefore, the success of a vaccine, even when one becomes available, is uncertain, making it necessary to focus on alternate approaches of tackling the disease. In this review, we discuss the differences in COVID-19 death/infection ratio between urban and rural India; and the probable role of the immune system, co-morbidities and associated nutritional status in dictating the death rate of COVID-19 patients in rural and urban India. Also, we focus on strategies for developing masks, vaccines, diagnostics and the role of drugs targeting host-virus protein-protein interactions in enhancing host immunity. We also discuss India's strengths including the resources of medicinal plants, good food habits and the role of information technology in combating COVID-19. We focus on the Government of India's measures and strategies for creating awareness in the containment of COVID-19 infection across the country.