Enterococci are troublesome nosocomial, opportunistic Gram-positive cocci bacteria showing enhanced resistance to many commonly used antibiotics. This study aims to investigate the prevalence and genetic basis of antibiotic resistance to macrolides, lincosamides, and streptogramins (MLS) in Enterococci, as well as the correlation between MLS resistance and biocide resistance. From 913 clinical isolates collected from King Khalid Hospital, Hail, Saudi Arabia, 131 isolates were identified as Enterococci spp. The susceptibility of the clinical enterococcal isolates to several MLS antibiotics was determined, and the resistance phenotype was detected by the triple disk method. The MLS-involved resistance genes were screened in the resistant isolates. The current results showed high resistance rates to MLS antibiotics, and the constitutive resistance to all MLS (cMLS) was the most prevalent phenotype, observed in 76.8% of resistant isolates. By screening the MLS resistance-encoding genes in the resistant isolates, the erythromycin ribosome methylase (erm) genes that are responsible for methylation of bacterial 23S rRNA were the most detected genes, in particular, ermB. The ereA esterase-encoding gene was the most detected MLS modifying-encoding genes, more than lnuA (adenylation) and mphC (phosphorylation). The minimum inhibitory concentrations (MICs) of commonly used biocides were detected in resistant isolates and correlated with the MICs of MLS antibiotics. The present findings showed a significant correlation between MLS resistance and reduced susceptibility to biocides. In compliance with the high incidence of the efflux-encoding genes, especially mefA and mefE genes in the tolerant isolates with higher MICs to both MLS antibiotics and biocides, the efflux of resistant isolates was quantified, and there was a significant increase in the efflux of resistant isolates with higher MICs as compared to those with lower MICs. This could explain the crucial role of efflux in developing cross-resistance to both MLS antibiotics and biocides.

Numerical simulation of mass transfer in membrane contactors for water purification was carried out in this study. The models were developed to estimate permeate volume, a critical performance variable in membrane desalination. We analyzed and compared the accuracy of models: Multilayer Perceptron (MLP), Extreme Gradient Boosting (XGBoost), and a Stacking ensemble method combining MLP and XGBoost. Data preprocessing techniques were applied to improve model performance, including outlier detection using Z-scores and log transformation for normalization. A distinctive contribution of this work is the innovative application of the Jellyfish Optimizer (JO) for hyperparameter tuning, which enhanced model robustness and set it apart from conventional optimization approaches. Unlike conventional optimization algorithms, JO’s biologically inspired dynamics offers a novel balance between exploration and exploitation, leading to superior tuning of model hyperparameters. The models’ predictive accuracy was evaluated using R², RMSE, and MAE with an 85%–15% train–test split. The Stacking model outperformed single models, achieving R² values of 0.99060 (training), 0.97627 (cross-validation), and 0.99043 (testing), along with the lowest test errors (RMSE = 6.17921), confirming its efficiency in predicting permeate volume. The results show that stacking significantly improves prediction accuracy in complex tasks like membrane desalination.

Breast cancer represents the most frequently occurring cancer globally among women. As per the recent report of the World Health Organization (WHO), it was documented that by the end of the year 2020, approximately 7.8 million females were positively diagnosed with breast cancer and in 2020 alone, 685,000 casualties were documented due to breast cancer. The use of standard chemotherapeutics includes the frontline treatment option for patients; however, the concomitant side effects represent a major obstacle for their usage. Carbazole alkaloids are one such group of naturally-occurring bioactive compounds belonging to the Rutaceae family. Among the various carbazole alkaloids, 3-Methoxy carbazole or C₁₃H₁₁NO (MHC) is obtained from Clausena heptaphylla as well as from Clausena indica. In this study, MHC was investigated for its anti-breast cancer activity based on molecular interactions with specific proteins related to breast cancer, where the MHC had predicted binding affinities for NF-κB with −8.3 kcal/mol. Furthermore, to evaluate the biological activity of MHC, we studied its in vitro cytotoxic effects on MCF-7 cells. This alkaloid showed significant inhibitory effects and induced apoptosis, as evidenced by enhanced caspase activities and the cellular generation of ROS. It was observed that a treatment with MHC inhibited the gene expression of NF-kB in MCF-7 breast cancer cells. These results suggest that MHC could be a promising medical plant for breast cancer treatment. Further studies are needed to understand the molecular mechanisms behind the anticancer action of MHC.