Targeting cellular plasticity: esculetin-driven reversion of stem cell-like characteristics and EMT phenotype in transforming cells with sequential p53/p73 knockdowns.

The intricate interplay of cancer stem cell plasticity, along with the bidirectional transformation between epithelial-mesenchymal states, introduces further intricacy to offer insights into newer therapeutic approaches. Differentiation therapy, while successful in targeting leukemic stem cells, has shown limited overall success, with only a few promising instances. Using colon carcinoma cell strains with sequential p53/p73 knockdowns, our study underscores the association between p53/p73 and the maintenance of cellular plasticity. Morphological alterations corresponding with cell surface marker expressions, transcriptome analysis and functional assays were performed to access stemness and EMT (Epithelial-Mesenchymal Transition) characteristics in the spectrum of cells exhibiting sequential p53 and p73 knockdowns. Notably, our investigation explores the effectiveness of esculetin in reversing the shift from an epithelial to a mesenchymal phenotype, characterized by stem cell-like traits. Esculetin significantly induces enterocyte differentiation and promotes epithelial cell polarity by altering Wnt axes in Cancer Stem Cell-like cells characterized by high mesenchymal features. These results align with our previous findings in leukemic blast cells, establishing esculetin as an effective differentiating agent in both Acute Myeloid Leukemia (AML) and solid tumor cells.

Exploring serine-arginine rich splicing factors: potential predictive markers for dysregulation in oral cancer.

BACKGROUND: Dysregulated splicing events are a common phenomenon in cancer with the Serine-arginine-rich splicing factor (SRSF) family emerging as pivotal regulators of gene expression, exerting influence over constitutive and alternative splicing processes. Although aberrations in a few SRSF family members have been implicated in various cancers, the comprehensive roles of other family constituents remain underexplored. METHODS: This study delves into the expression profile of the entire SRSF family (SRSF1-SRSF12) in 23 cancerous cell lines originating from diverse tissues using quantitative Real-Time PCR. Further, the transcript levels of the SRSF family were examined in oral cancer patient samples stratified into Pre-cancer (n = 15), Early cancer (n = 11), Late cancer (n = 14), and adjacent non-tumor tissues (n = 26) as controls. The results were corroborated by a parallel investigation utilizing the transcriptomics data of oral squamous cell carcinoma (OSCC) patients (n = 319) and controls (n = 35) available in The Cancer Genome Atlas (TCGA) database. RESULTS: Our investigation reveals a notable upregulation in the expression levels of key splicing factors, namely SRSF3, SRSF9, and SRSF10 in all oral cancer cell lines (SCC-4, UM-SCC-84, CAL33, SAS-H1). Conversely, no significant associations between SRSF family members and other cancer cell lines were discerned. Further, the expression profile of the SRSF family in oral cancer patient samples revealed significant upregulation of SRSF1, SRSF3, SRSF7, SRSF9, SRSF10, and SRSF11 in patients with late-stage oral cancer compared to controls. Transcriptomics data from TCGA database demonstrated remarkable upregulation of SRSF1, SRSF4, SRSF9, SRSF10, and SRSF11 in OSCC patients. CONCLUSION: Collectively our results underscore the critical involvement of SRSF family members in the context of oral cancer, highlighting their potential as key players in the altered splicing dynamics associated with cancer progression.

Artificial intelligence-driven reverse vaccinology for Neisseria gonorrhoeae vaccine: Prioritizing epitope-based candidates.

Neisseria gonorrhoeae is the causative agent of the sexually transmitted disease gonorrhea. The increasing prevalence of this disease worldwide, the rise of antibiotic-resistant strains, and the difficulties in treatment necessitate the development of a vaccine, highlighting the significance of preventative measures to control and eradicate the infection. Currently, there is no widely available vaccine, partly due to the bacterium's ability to evade natural immunity and the limited research investment in gonorrhea compared to other diseases. To identify distinct vaccine candidates, we chose to focus on the uncharacterized, hypothetical proteins (HPs) as our initial approach. Using the in silico method, we first carried out a comprehensive assessment of hypothetical proteins of Neisseria gonorrhoeae, encompassing assessments of physicochemical properties, cellular localization, secretary pathways, transmembrane regions, antigenicity, toxicity, and prediction of B-cell and T-cell epitopes, among other analyses. Detailed analysis of all HPs resulted in the functional annotation of twenty proteins with a great degree of confidence. Further, using the immuno-informatics approach, the prediction pipeline identified one CD8+ restricted T-cell epitope, seven linear B-cell epitopes, and seven conformational B-cell epitopes as putative epitope-based peptide vaccine candidates which certainly require further validation in laboratory settings. The study accentuates the promise of functional annotation and immuno-informatics in the systematic design of epitope-based peptide vaccines targeting Neisseria gonorrhoeae.

Critical insights from recent outbreaks of Mycoplasma pneumoniae: decoding the challenges and effective interventions strategies.

OBJECTIVES: Mycoplasma pneumoniae (M. pneumoniae) continues to pose a significant disease burden on global public health as a respiratory pathogen. The antimicrobial resistance among M. pneumoniae strains has complicated the outbreak control efforts, emphasizing the need for robust surveillance systems and effective antimicrobial stewardship programs. DESIGN: This review comprehensively investigates studies stemming from previous outbreaks to emphasize the multifaceted nature of M. pneumoniae infections, encompassing epidemiological dynamics, diagnostic innovations, antibiotic resistance, and therapeutic challenges. RESULTS: We explored the spectrum of clinical manifestations associated with M. pneumoniae infections, emphasizing the continuum of disease severity and the challenges in gradating it accurately. Artificial intelligence and machine learning have emerged as promising tools in M. pneumoniae diagnostics, offering enhanced accuracy and efficiency in identifying infections. However, their integration into clinical practice presents hurdles that need to be addressed. Further, we elucidate the pivotal role of pharmacological interventions in controlling and treating M. pneumoniae infections as the efficacy of existing therapies is jeopardized by evolving resistance mechanisms. CONCLUSION: Lessons learned from previous outbreaks underscore the importance of adaptive treatment strategies and proactive management approaches. Addressing these complexities demands a holistic approach integrating advanced technologies, genomic surveillance, and adaptive clinical strategies to effectively combat this pathogen.

Unveiling parental perspectives: COVID-19 vaccination for children in India.

Background: Irrespective of the availability of a safe and effective COVID-19 vaccine and its success rate in adults, administering vaccines to children remains a challenge for healthcare workers. Children's vaccine hesitancy among parents remains substantial and is exacerbated due to misleading information. In the present study, we aimed to investigate the hesitancy of parents and their concern about the vaccination and clinical characteristics of COVID-19 in their children. Methods: A cross-sectional web-based and offline survey comprised of questions about the demographic of children, the status of COVID-19 infection, its severity, vaccination status, sources of information, willingness, concerns and attitude of parents to vaccinate their children against the COVID-19 virus, was conducted. Overall, 846 responses from parents fulfilling the inclusion criteria were analysed by GraphPad Prism 5. Results: Out of the 846 responses, 51.2% (n = 433) of children were vaccinated against COVID-19. Out of vaccinated children (51.2%), 60.3% (n = 261) had experienced adverse events. Around 21% (n = 98) of children had a history of exposure to the SARS-CoV-2 virus. Among the infected children, 14.3% were asymptomatic and 85.7% had symptoms. Approximately 8% of children had comorbidities, with chronic lung diseases and asthma being the most common. Among the 846 participating parents, 59.5% were mothers and the remaining 40.5% were fathers. A total of 2.7% and 22.2% of parents were found hesitant to administer the COVID-19 vaccine to their children aged 15-18 years and below 15 years, respectively. Among hesitant parents, mothers were found slightly more hesitant as compared to fathers. Also, 35.5% of parents were found hesitant about their own COVID-19 vaccination. Furthermore, the concern for COVID-19 vaccine unwillingness among parents is that a child has already achieved natural immunity after COVID-19 infections (76.8%) followed by vaccine safety and its side effects. The motivating factors to convince parents for their children's COVID-19 vaccination were if their doctors recommend it, followed by detailed information on vaccine side effects and efficacy in children. The most trusted source of information for the parents was found to be the healthcare workers. Conclusion: These results suggest that data and reviews regarding the safety and efficacy of the COVID-19 vaccine readily available in the public domain could serve as a highly effective strategy for promoting and implementing widespread vaccination among children. By providing easily accessible and comprehensive information, public health authorities can address parental concerns, dispel misconceptions and foster a greater sense of trust in the vaccination process.

Understanding Longevity: SIN-3 and DAF-16 Revealed as Independent Players in Lifespan Regulation.

Aging is the process of gradual physio-biochemical deterioration. Although aging is inevitable, healthy aging is the key to individual and communal well-being. Therefore, it is essential to understand the regulation of aging. SIN-3/Sin-3 is a unique regulatory protein that regulates aging without DNA-binding activity. It functions by establishing multiple protein interactions. To understand the functional mechanism of this transcriptional regulator, the Caenorhabditis elegans protein interactome was assessed for SIN-3 interactions. DAF-16/FOXO emerged as one of the leading contenders for SIN-3-mediated regulation of aging. This study looks at the concerted role of SIN-3 and DAF-16 proteins in lifespan regulation. Phenotypic profiling for the mutants of these genes shows the functional accord between these 2 proteins with similar functions in stress response and vital biological processes. However, there were no significant physical interactions when checked for protein-protein interaction between SIN-3 and DAF-16 proteins. C. elegans genomics and transcriptomics data also indicated the possibilities of concerted gene regulation. This genetic regulation is more likely related to SIN-3 dominance on DAF-16 function. Overall, SIN-3 and DAF-16 proteins have strong functional interactions that ensure healthy aging. The influence of SIN-3 on DAF-16-mediated stress response is one of their convergence points in longevity regulation.

Identification and clinicopathological analysis of potential p73-regulated biomarkers in colorectal cancer via integrative bioinformatics.

This study aims to decipher crucial biomarkers regulated by p73 for the early detection of colorectal cancer (CRC) by employing a combination of integrative bioinformatics and expression profiling techniques. The transcriptome profile of HCT116 cell line p53 - / - p73 + / + and p53 - / - p73 knockdown was performed to identify differentially expressed genes (DEGs). This was corroborated with three CRC tissue expression datasets available in Gene Expression Omnibus. Further analysis involved KEGG and Gene ontology to elucidate the functional roles of DEGs. The protein-protein interaction (PPI) network was constructed using Cytoscape to identify hub genes. Kaplan-Meier (KM) plots along with GEPIA and UALCAN database analysis provided the insights into the prognostic and diagnostic significance of these hub genes. Machine/deep learning algorithms were employed to perform TNM-stage classification. Transcriptome profiling revealed 1289 upregulated and 1897 downregulated genes. When intersected with employed CRC datasets, 284 DEGs were obtained. Comprehensive analysis using gene ontology and KEGG revealed enrichment of the DEGs in metabolic process, fatty acid biosynthesis, etc. The PPI network constructed using these 284 genes assisted in identifying 20 hub genes. Kaplan-Meier, GEPIA, and UALCAN analyses uncovered the clinicopathological relevance of these hub genes. Conclusively, the deep learning model achieved TNM-stage classification accuracy of 0.78 and 0.75 using 284 DEGs and 20 hub genes, respectively. The study represents a pioneer endeavor amalgamating transcriptomics, publicly available tissue datasets, and machine learning to unveil key CRC-associated genes. These genes are found relevant regarding the patients' prognosis and diagnosis. The unveiled biomarkers exhibit robustness in TNM-stage prediction, thereby laying the foundation for future clinical applications and therapeutic interventions in CRC management.

Diagnostic potential of SORT1 gene in coronary artery disease.

BACKGROUND: Genome-wide association studies identify SORT1 gene associated with risk of coronary artery disease (CAD). Sortilin protein enhances LDL absorption, form cell development, and atherosclerosis in macrophages. AIM: We therefore explored SORT1 expression in CAD patients and its gene expression's predictive usefulness for the severity of the disease. METHODOLOGY: This is a case control study and Quantitative real-time PCR; Sandwich ELISA and western blotting were used to determine the expression of SORT1 gene at the mRNA and protein level in two hundred healthy controls and two hundred patients with various CAD syndromes. RESULTS: CAD patients exhibit higher SORT1 gene expression in CAD patients, a higher concentration of sortilin in their plasma, and distinct expression patterns in various CAD syndromes. The study reveals a positive correlation between gene expression and the severity of coronary artery stenosis, the number of diseased vessels, and the presence of diabetes. ROC curve analysis of SORT1 gene expression both at mRNA and protein level showed strong discrimination between significant CAD and control subjects. CONCLUSION: Therefore, elevated SORT1 gene expression in various CAD syndromes may be a potential biomarker for the disease.

Functional annotation of Candida albicans hypothetical proteins: a bioinformatics approach.

Candida albicans is a member of the ascomycetes class of fungi and it is an opportunistic pathogen species responsible for a wide range of fungal infections in humans. Bioinformatics and sequencing analysis of Candida proteomics has disclosed that around 69% proteome is still uncharacterized which needs to be annotated with functions. The NCBI-Genome has termed them as hypothetical proteins (HPs) in the whole proteome of Candida. Interpretation of this substantial portion of the proteome can reveal novel pharmacological targets for markers, drug development, and other therapeutics and so on. In this article, we have assigned functional annotation to these hypothetical proteins using bioinformatics methodologies. The advanced and robust computational models have been used to assign the preliminary functions to these putative HPs with high level of confidence. The findings of this study unveil some novel pharmacological targets for drug therapy and vaccines and it would help to identify novel molecular mechanisms underlying the fungal pathogenesis.

Structure-based drug discovery to identify SARS-CoV2 spike protein-ACE2 interaction inhibitors.

After the emergence of the COVID-19 pandemic in late 2019, the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has undergone a dynamic evolution driven by the acquisition of genetic modifications, resulting in several variants that are further classified as variants of interest (VOIs), variants under monitoring (VUM) and variants of concern (VOC) by World Health Organization (WHO). Currently, there are five SARS-CoV-2 VOCs (Alpha, Beta, Delta, Gamma and Omicron), two VOIs (Lambda and Mu) and several other VOIs that have been reported globally. In this study, we report a natural compound, Curcumin, as the potential inhibitor to the interactions between receptor binding domain (RBD(S1)) and human angiotensin-converting enzyme 2 (hACE2) domains and showcased its inhibitory potential for the Delta and Omicron variants through a computational approach by implementing state of the art methods. The study for the first time revealed a higher efficiency of Curcumin, especially for hindering the interaction between RBD(S1) and hACE-2 domains of Delta and Omicron variants as compared to other lead compounds. We investigated that the mutations in the RBD(S1) of VOC especially Delta and Omicron variants affect its structure compared to that of the wild type and other variants and therefore altered its binding to the hACE2 receptor. Molecular docking and molecular dynamics (MD) simulation analyses substantially supported the findings in terms of the stability of the docked complexes. This study offers compelling evidence, warranting a more in-depth exploration into the impact of these alterations on the binding of identified drug molecules with the Spike protein. Further investigation into their potential therapeutic effects in vivo is highly recommended.Communicated by Ramaswamy H. Sarma.

Bactericidal activity of esculetin is associated with impaired cell wall synthesis by targeting glutamate racemase of Neisseria gonorrhoeae.

Neisseria gonorrhoeae (NG), the causative organism of gonorrhea, has been classified by the World Health Organization as 'Priority' two organism owing to its increased resistance to antibiotics and even failure of recommended dual therapy with ceftriaxone and azithromycin. As a result, the general and reproductive health of infected individuals is severely compromised. The imminent public health catastrophe of antimicrobial-resistant gonococci cannot be understated, as t he of severe complications and sequelae of infection are not only increasing but their treatment has also become more expensive. Tenacious attempts are underway to discover novel drug targets as well as new drugs to fight against NG. Therefore, a considerable number of phytochemicals have been tested for their remedial intercession via targeting bacterial proteins. The MurI gene encodes for an enzyme called glutamate racemase (MurI) that is primarily involved in peptidoglycan (PG) biosynthesis and is specific to the bacterial kingdom and hence can be exploited as a potential drug target for the treatment of bacterial diseases. Accordingly, diverse families of phytochemicals were screened in silico for their binding affinity with N. Gonorrhoeae MurI (NG-MurI) protein. Esculetin, one of the shortlisted compounds, was evaluated for its functional, structural, and anti-bacterial activity. Treatment with esculetin resulted in growth inhibition, cell wall damage, and altered permeability as revealed by fluorescence and electron microscopy. Furthermore, esculetin inhibited the racemization activity of recombinant, purified NG-MurI protein, one of the enzymes required for peptidoglycan biosynthesis. Our results suggest that esculetin could be further explored as a lead compound for developing new drug molecules against multidrug-resistant strains.

Navigating bioactivity space in anti-tubercular drug discovery through the deployment of advanced machine learning models and cheminformatics tools: a molecular modeling based retrospective study.

Mycobacterium tuberculosis is the bacterial strain that causes tuberculosis (TB). However, multidrug-resistant and extensively drug-resistant tuberculosis are significant obstacles to effective treatment. As a result, novel therapies against various strains of M. tuberculosis have been developed. Drug development is a lengthy procedure that includes identifying target protein and isolation, preclinical testing of the drug, and various phases of a clinical trial, etc., can take decades for a molecule to reach the market. Computational approaches such as QSAR, molecular docking techniques, and pharmacophore modeling have aided drug development. In this review article, we have discussed the various techniques in tuberculosis drug discovery by briefly introducing them and their importance. Also, the different databases, methods, approaches, and software used in conducting QSAR, pharmacophore modeling, and molecular docking have been discussed. The other targets targeted by these techniques in tuberculosis drug discovery have also been discussed, with important molecules discovered using these computational approaches. This review article also presents the list of drugs in a clinical trial for tuberculosis found drugs. Finally, we concluded with the challenges and future perspectives of these techniques in drug discovery.

Esculetin releases maturation arrest and induces terminal differentiation in leukemic blast cells by altering the Wnt signaling axes.

BACKGROUND: The "Differentiation therapy" has been emerging as a promising and more effective strategy against acute leukemia relapses. OBJECTIVE: In extension to the revolutionising therapeutic outcomes of All Trans Retinoic Acid (ATRA) to induce terminal differentiation of Acute Promyelocytic Leukemic (APL) blast cells, we decipher the potential effect of a natural compound "Esculetin" to serve as a differentiating agent in Acute Myeloid Leukemia (AML). Underlaying role of Wnt signaling pathways in esculetin mediated blast cell differentiation was also evaluated. METHODS: Human acute myeloid leukemic cells (Kasumi-1) with t(8;21/AML-ETO) translocation were used as a model system. Growth inhibitory and cytotoxic activity of esculetin were analysed using growth kinetics and MTT assay. Morphological alterations, cell scatter characteristics, NBT reduction assay and cell surface marker expression patterns were analysed to detect terminally differentiated phenotypes. We employed RT2profiler PCR array system for the analysis of transcriptome profile of Wnt signaling components. Calcium inhibitors (TMB8 and Amlodipine) and Transforming growth factor beta (TGF-ß) were used to modulate the Wnt signaling axes. RESULTS: We illustrate cytotoxic as well as blast cell differentiation potential of esculetin on Kasumi-1 cells. Morphological alterations akin to neutrophilic differentiation as well as the corresponding acquisition of myeloid lineage markers indicate terminal differentiation potential of esculetin in leukemic blast cells. Exposure to esculetin also resulted in downregulation of canonical Wnt axis while upto ~ 21 fold upregulation of non-canonical axis associated genes. CONCLUSIONS: Our study highlights the importance of selective use of calcium pools as well as "axis shift" of the canonical to non-canonical Wnt signaling upon esculetin treatment which might abrogate the inherent proliferation to release maturation arrest and induce the differentiation in leukemic blast cells. The current findings provide further therapeutic interventions to consider esculetin as a potent differentiating agent to counteract AML relapses.

Identification of thrombin inhibiting antithrombin-III like protein from Punica granatum using in silico approach and in vitro validation of thrombin inhibition activity in crude protein.

Thrombosis is characterized by the formation of clots in the blood vessels. Antithrombin-III deficiency in the blood causes thrombus formation. Supplementing antithrombin-III may serve as anticoagulant therapy. In the present studies, an antithrombin like Protein from Punica granatum has been identified and characterized using in silico approach. Based on sequence homology, an ALPP was selected depending upon its highest binding affinity of -41.28 kcal/mol with thrombin. Thrombin structure complexed with ALPP was docked with TAME using AutoDock Vina. No binding was observed for TAME at Ser195 of thrombin. MD simulation (50 ns) was performed to evaluate the flexibility and stability of docked complexes. In vitro assays with crude protein showed 78% thrombin inhibition at 5 µg and calculated IC50 value was 0.188 µg. The presence of thrombin inhibitors in crude protein was also confirmed by reverse zymography. Thus, it is very likely that the protein identified from P. granatum may act as thrombin inhibitor.

Structure-guided pharmacophore based virtual screening, docking, and molecular dynamics to discover repurposed drugs as novel inhibitors against endoribonuclease Nsp15 of SARS-CoV-2.

COVID-19 (Corona Virus Disease of 2019) caused by the novel 'Severe Acute Respiratory Syndrome Coronavirus-2' (SARS-CoV-2) has wreaked havoc on human health and the global economy. As a result, for new medication development, it's critical to investigate possible therapeutic targets against the novel virus. 'Non-structural protein 15' (Nsp15) endonuclease is one of the crucial targets which helps in the replication of virus and virulence in the host immune system. Here, in the current study, we developed the structure-based pharmacophore model based on Nsp15-UMP interactions and virtually screened several databases against the selected model. To validate the screening process, we docked the top hits obtained after secondary filtering (Lipinski's rule of five, ADMET & Topkat) followed by 100 ns molecular dynamics (MD) simulations. Next, to revalidate the MD simulation studies, we have calculated the binding free energy of each complex using the MM-PBSA procedure. The discovered repurposed drugs can aid the rational design of novel inhibitors for Nsp15 of the SARS-CoV-2 enzyme and may be considered for immediate drug development.

Identification of novel inhibitors of Neisseria gonorrhoeae MurI using homology modeling, structure-based pharmacophore, molecular docking, and molecular dynamics simulation-based approach.

MurI is one of the most significant role players in the biosynthesis of the peptidoglycan layer in Neisseria gonorrhoeae (Ng). We attempted to highlight the structural and functional relationship between Ng-MurI and D-glutamate to design novel molecules targeting this interaction. The three-dimensional (3D) model of the protein was constructed by homology modeling and the quality and consistency of generated model were assessed. The binding site of the protein was identified by molecular docking studies and a pharmacophore was identified using the interactions of the control ligand. The structure-based pharmacophore model was validated and employed for high-throughput virtual screening and molecular docking to identify novel Ng-MurI inhibitors. Finally, the model was optimized by molecular dynamics (MD) simulations and the optimized model complex with the substrate glutamate and novel molecules facilitated us to confirm the stability of the protein-ligand docked complexes. The 100 ns MD simulations of the potential lead compounds with protein confirmed that the modeled complexes were stable. This study identifies novel potential compounds with good fitness and docking scores, which made the interactions of biological significance within the protein active site. Hence, the identified compounds may act as new leads to design and develop Ng-MurI inhibitors.Communicated by Ramaswamy H. Sarma.

Ocular manifestations of central insulin resistance.

Central insulin resistance, the diminished cellular sensitivity to insulin in the brain, has been implicated in diabetes mellitus, Alzheimer's disease and other neurological disorders. However, whether and how central insulin resistance plays a role in the eye remains unclear. Here, we performed intracerebroventricular injection of S961, a potent and specific blocker of insulin receptor in adult Wistar rats to test if central insulin resistance leads to pathological changes in ocular structures. 80 mg of S961 was stereotaxically injected into the lateral ventricle of the experimental group twice at 7 days apart, whereas buffer solution was injected to the sham control group. Blood samples, intraocular pressure, trabecular meshwork morphology, ciliary body markers, retinal and optic nerve integrity, and whole genome expression patterns were then evaluated. While neither blood glucose nor serum insulin level was significantly altered in the experimental or control group, we found that injection of S961 but not buffer solution significantly increased intraocular pressure at 14 and 24 days after first injection, along with reduced porosity and aquaporin 4 expression in the trabecular meshwork, and increased tumor necrosis factor α and aquaporin 4 expression in the ciliary body. In the retina, cell density and insulin receptor expression decreased in the retinal ganglion cell layer upon S961 injection. Fundus photography revealed peripapillary atrophy with vascular dysregulation in the experimental group. These retinal changes were accompanied by upregulation of pro-inflammatory and pro-apoptotic genes, downregulation of anti-inflammatory, anti-apoptotic, and neurotrophic genes, as well as dysregulation of genes involved in insulin signaling. Optic nerve histology indicated microglial activation and changes in the expression of glial fibrillary acidic protein, tumor necrosis factor α, and aquaporin 4. Molecular pathway architecture of the retina revealed the three most significant pathways involved being inflammation/cell stress, insulin signaling, and extracellular matrix regulation relevant to neurodegeneration. There was also a multimodal crosstalk between insulin signaling derangement and inflammation-related genes. Taken together, our results indicate that blocking insulin receptor signaling in the central nervous system can lead to trabecular meshwork and ciliary body dysfunction, intraocular pressure elevation, as well as inflammation, glial activation, and apoptosis in the retina and optic nerve. Given that central insulin resistance may lead to neurodegenerative phenotype in the visual system, targeting insulin signaling may hold promise for vision disorders involving the retina and optic nerve.

Corrigendum: Navigating bioactivity space in anti-tubercular drug discovery through the deployment of advanced machine learning models and cheminformatics tools: a molecular modeling based retrospective study.

[This corrects the article DOI: 10.3389/fphar.2023.1265573.].

Multiple sexually transmitted co-infections are associated with adverse reproductive outcomes in asymptomatic adolescent pregnant women; A Prospective cohort study.

Background: A prospective cohort was conducted to assess the prevalence of seven RTIs/STIs in adolescent asymptomatic pregnant women to find a significant correlation between infection and pregnancy. Methods: The study was restricted to 18-19 years of asymptomatic adolescent pregnant women attending Ante-Natal Care and the health status of the pregnant women were followed up to parturition. The health status of the infant was followed till 6 months post-delivery. The prevalence of the concerning pathogens and the significance of their association with adverse outcomes of pregnancy were determined. Results: Among 279 subjects, the most significant co-infections were observed for M. hominis with U. parvum (9.31%; p-value-0.0071/OR-2.6421) and U. urealyticum (7.88%; p-value-0.0119/OR-2.6455). Statistically significant associations were found between C. trachomatis [(p-value-0.0439); OR-2.9902] and M. genitalium [(p-value-0.0284); OR-3.442] with PTB, N. gonorrhoeae with LBW <2.5 kg [(p-value-0.0052);OR-4.9017], U. urealyticum with VLBW <2 kg [(p-value-0.0262);OR-3.0207], M. genitalium [(p-value-0.0184); OR-11.7976] and T. vaginalis with PROM [(p-value 0.0063); OR-19.4275] while M. genitalium [(p-value 0.0190); OR-12.9230] and U. urealyticum [(p-value 0.0063); OR-14.5149] with PPROM with 95% CI respectively. Conclusions: Asymptomatic adolescents are at high risk of adverse pregnancy outcomes if infected with the concerned pathogens.

Improved management can be achieved by introducing additional parameters in the syndromic diagnosis of nonviral sexually transmitted infections at low-resource settings.

BACKGROUND: The syndromic approach is a simple and affordable strategy for the management of sexually transmitted infections in countries with low-resource settings. However, because of the lack of specificity and accuracy, the risk of overuse and misuse of antibiotics is very high. Here, we proposed a more specific and accurate algorithm compared with the current algorithm used for syndromic case management of 3 common sexually transmitted pathogens and compared its precision with laboratory-based tests. OBJECTIVE: This study aimed to report a comparative account of the accuracy of existing syndromic case management guidelines followed in mainstream hospitals, for taking care of patients with nonviral sexually transmitted infections, concerning an approach involving an alternative algorithm formulated in our laboratory followed by polymerase chain reaction testing. STUDY DESIGN: This was an observational study that compared the data between 2 categories based on diagnostics accuracy and treatment. In category I, symptoms of infection were scored on the basis of the existing National AIDS Control Organization and National AIDS Control Programme guidelines, and patients were treated before testing by polymerase chain reaction. In category II, patients were recruited on the basis of the National AIDS Control Organization and National AIDS Control Programme guidelines with additional alternative syndromic case management parameters. All samples were tested by polymerase chain reaction for Chlamydia trachomatis, Neisseria gonorrhoeae, and Trichomonas vaginalis and clinically correlated before giving the treatment. RESULTS: In category I, among 646 women with symptomatic infection, only 46 (7.82%) tested positive by polymerase chain reaction assay for at least 1 of the pathogens, and 600 (92.87%) tested negative for infection by any of the 3 pathogens. The total estimated percentages of the overuse and misuse of antibiotics were 92.87% and 8.69%, respectively. Correct and complete treatment based on laboratory outcome compared with National AIDS Control Programme guidelines was 42 of 46 (91.30%). The estimated overuse of azithromycin and cefixime (Gray Kit) was 29.69%, the estimated overuse of a combination of doxycycline, cefixime, and metronidazole (Yellow Kit) was 29.87%, and the estimated overuse of a combination of doxycycline, cefixime, metronidazole, and azithromycin (Gray with Yellow Kit) was 11.45%. In category II, wherein patients were treated using an alternative syndromic approach and polymerase chain reaction diagnostics, 243 of 319 patients (76.15%) were infected with either of the pathogens (Chlamydia trachomatis, Neisseria gonorrhoeae, and Trichomonas vaginalis), whereas 76 of 319 patients (23.82%) were negative for any of the 3 pathogens. Among 243 patients with infection, 99 of 243 (40.74%) were infected with a single pathogen, whereas 144 of 243 (59.20%) were coinfected. Of 144 coinfected patients, the percentage of Chlamydia trachomatis + Neisseria gonorrhoeae infection was the highest (51.38%), followed by coinfection with all 3 pathogens (30%). Coinfection with Chlamydia trachomatis + Trichomonas vaginalis was 9.72%, and coinfection with Neisseria gonorrhoeae + Trichomonas vaginalis was 9.03%. The estimated overuse of antibiotics was found to be 23.82% only. CONCLUSION: The proposed alternative strategies of syndromic case management can reduce the percentage of misuse and overuse of antibiotics from 92.87% to 23.82%. Moreover, syndromic case management alone was insufficient for disease management.