Rhizomes of Drynaria quercifolia have long been traditionally used to manage rheumatic pain. However, there is limited research supporting this traditional practice and insufficient evidence demonstrating the molecular mechanisms of action of plant-derived bioactives in rheumatoid arthritis (RA). The current study aims to identify the effective components in Drynaria quercifolia methanol rhizome extract (DME) and their probable pharmacological mechanisms in alleviating Rheumatoid Arthritis (RA) using network-pharmacology, molecular docking, molecular-dynamics simulations, and gene expression-based validation. Gas chromatography–mass spectrometry (GC-MS) based screening identified 41 volatile phytocomponents from DME having drug-like potentiality. Network pharmacology-based screening revealed 117 therapeutic targets for RA of which 11 have been identified as core targets. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis indicated that key target genes were mostly enriched in the inflammatory response associated with multiple signalling pathways. Molecular docking and molecular dynamics studies revealed that key target proteins like serine/threonine-protein kinase (AKT1), peroxisome proliferator-activated receptor alpha (PPARA), and peroxisome proliferator-activated receptor gamma (PPARG), exhibited strong binding affinity and stable interactions with multiple phytocomponents present in DME. For experimental verification FCA (Freund’s complete adjuvant)-induced chronic arthritis model employed for further molecular investigation. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) results validated that DME significantly (p ≤ 0.05) regulate the expression of key identified target genes AKT and PPARG in experimental RA model. Moreover, this study further confirmed that DME significantly (p ≤ 0.05) downregulated pro-inflammatory mediators like COX-2, IL-6 and TNF-α at gene and protein levels and also normalized (p ≤ 0.05) different oxidative stress parameters in both the low and high dose groups of DME-treated arthritic animals. In conclusion, the network-based in silico approach indicated that the phytocomponents present in DME probably act in a synergistic way to modulate key identified targets associated with RA, which was further validated by experimental studies. Therefore, DME could be a potential alternative in immunomodulatory therapies to combat RA and related chronic inflammatory conditions.

Dengue cases are increasing every year in the sub-Himalayan part of West Bengal, where Aedes albopictus (Skuse 1894) has emerged as a predominant dengue vector. Dengue management heavily relies on the recurrent application of chemical insecticides such as temephos (larvicide) and deltamethrin (adulticide). However Ae. albopictus can quickly develop resistance which complicates their management. Thus, detailed population-specific studies on resistance status and mechanism of resistance are useful for designing an effective dengue management strategy. In this study, wild mosquitoes were collected and bioassays with temephos and deltamethrin, including synergist assays, were conducted to investigate the probable mechanism of resistance. Furthermore, carboxylesterase activity and level of monooxygenase were measured followed by real-time polymerase chain reaction analysis to assess expression patterns of CCE and CYP genes. Bioassays confirmed temephos and deltamethrin resistance in Ae. albopictus population is driven by metabolic detoxification. Biochemical assay recorded significantly elevated carboxylesterase activity and monooxygenase levels compared to a susceptible laboratory strain. This is further supported by the elevated relative expression of CCE and CYP genes with consistent expression of CYP6A8 and CCEae3a in these populations. A molecular docking study suggested that the conformation of the binding site for temephos and deltamethrin may enhance their potential metabolism. These findings align with the global trend of insecticide resistance development and highlight the urgent need for more sustainable and informed approaches to dengue vector management.

Kanchnar Guggulu (KG) is a potent Ayurvedic remedy for hormonal imbalances, PCOS, ulcers, cystic swelling, and tumors

Background Bulk tumour-versus-normal breast transcriptomic classifiers commonly show high internal discrimination, but a high area under the curve may reflect the biology of tissue contrast, cohort construction or technical separation as much as a portable malignant-cell program. We asked whether a pre-specified, interpretable score trained in one public cohort could retain rank discrimination in a locked cohort while its underlying biology was examined in parallel. Methods Processed Affymetrix GPL570 data from GSE42568 were used for discovery and nested model development. GSE7904 was held as an external cohort. Within-study normalization, probe-to-gene collapse and gene intersection produced 22,737 shared genes. Differential expression and enrichment were conducted. The elastic-net logistic score was the primary model; feature selection and tuning were contained in discovery-cohort nested cross-validation. Results The discovery cohort had 1,213 upregulated and 1,369 downregulated genes at false-discovery rate < 0.05 and log2 fold change ≥ 1. Of 2,582 discovery differentially expressed genes, 1,729 (67.0%) had a concordant external direction; 563 met the stringent criterion with the same direction in both cohorts. Cell-cycle/mitotic programmes dominated the upregulated signal, while PPAR, lipid-metabolism and adipocyte-lipolysis terms dominated the downregulated signal. The 20-feature elastic-net score produced a nested discovery AUC of 0.933 (95% CI 0.830–0.997) and a locked external AUC of 0.970 (95% CI 0.900-1.000). External basal-like and non-BLC AUCs were 0.968 and 0.986, respectively; the BRCA1-associated subgroup was too small for credible estimation. Conclusion The score transports as a rank discriminator, but its uniformly negative coefficients and lipid/adipose-associated features indicate that it likely captures loss of normal breast-tissue programmes in addition to tumour biology. The evidence supports a contrast-aware transportability signal. Prospective cohorts with representative benign controls, unified preprocessing and formal calibration assessment are required in future works.