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Zulfia S, A.

Publications and source records attributed to Zulfia S, A..

2 recordsLinked to original sources

Tracking vaginal microbiome transitions in bacterial vaginosis for cues of antibiotic resilience

BackgroundBacterial vaginosis (BV) is a common and difficult-to-treat vaginal disorder, with significant implications for reproductive health, particularly in low and middle-income countries. Clinical cure based on symptom resolution or Nugent scores often do not correspond to restoration of healthy vaginal microbiome. Factors underlying treatment failure remain poorly defined, warranting the need for understanding post-treatment microbiome dynamics to improve long-term outcomes. ObjectivesTo delineate longitudinal vaginal bacteriome dynamics, integrating microbial composition, transition patterns, and clinical symptoms in a closely followed cohort of women with BV based on treatment outcome. MethodsVaginal swabs from reproductive-age women (18-45 years) were collected and classified as BV-positive ([≥]7) or healthy ([≤]3) using Nugent scoring. BV cases were treated using single-dose secnidazole and followed for three months. Sociodemographic, clinical, and behavioral data were statistically analyzed across groups. Vaginal microbiome composition was assessed using 16S rRNA sequencing, evaluating taxonomic profiles, alpha and beta diversity, differential abundance, and co-occurrence networks. ResultsAntibiotic treatment reduced overall microbial diversity and shifted community composition toward healthy controls, though relapse samples retained higher diversity of BV-associated taxa such as Sneathia, Dialister, and Gardnerella, while no-relapse and control groups showed higher Lactobacillus abundance. Corynebacterium amycolatum appeared protective, while Mycoplasma and Fusobacterium played symptom-specific roles. Microbial network analysis showed denser and more persistent associations in baseline and relapse groups, with Sneathia remaining a central node. ConclusionShort-term symptom resolution in BV does not correspond to full microbial recovery; necessary for long-term remission. Functional traits of resilient taxa like Sneathia, Fannyhessea and Dialister may confer resilience and enable recolonization, undermining long term treatment efficacy.

microbiology↗

LCLNCRdb: A Comprehensive Resource for Investigating long non-coding RNAs in Lung Cancer

Lung cancer is a primary cause of death worldwide, accounting for a substantial number of mortalities. It involves several molecular mechanisms that are influenced by long non-coding RNAs (lncRNAs), a specific types of RNA molecules that do not code for proteins. Several research have revealed the importance of long non-coding RNAs (lncRNAs) in the initiation, progression, and development of resistance to lung cancer therapy. However, there are no centralized web resources or databases that collect and integrate information regarding lung cancer associated lncRNAs. This led to the development of the LCLNCRdb, a manually curated database that includes data from various sources, such as published research articles, and The Cancer Genome Atlas (TCGA) data portal. This database contains detailed information on 1102 lncRNAs that have differential expression patterns in lung cancer patients, such as lncRNA name, entrez ID, Ensemble ID, HGNC ID, NONCODE ID, lung cancer type, source, lncRNA expression pattern, experimental techniques, network analysis, and survival analysis details. The database offers a user-friendly platform for browsing, retrieving, and downloading data, and it features a dedicated submission page for researchers to share newly identified lncRNAs related to lung cancer. LCLNCRdb aims to enhance our knowledge of lncRNA deregulation in lung cancer and provides a valuable and timely resource for lncRNA research. The database is freely accessible at (https://dbtcmi.in/tools/lclncrdb/main.html).

bioinformatics↗