Antibiotic resistance genes prevalence prediction and interpretation in beaches affected by urban wastewater discharge.

Background: The annual death toll of over 1.2 million worldwide is attributed to infections caused by resistant bacteria, driven by the significant impact of antibiotic misuse and overuse in spreading these bacteria and their associated antibiotic resistance genes (ARGs). While limited data suggest the presence of ARGs in beach environments, efficient prediction tools are needed for monitoring and detecting ARGs to ensure public health safety. This study aims to develop interpretable machine learning methods for predicting ARGs in beach waters, addressing the challenge of black-box models and enhancing our understanding of their internal mechanisms. Methods: In this study, we systematically collected beach water samples and subsequently isolated bacteria from these samples using various differential and selective media supplemented with different antibiotics. Resistance profiles of bacteria were determined by using Kirby-Bauer disk diffusion method. Further, ARGs were enumerated by using the quantitative polymerase chain reaction (qPCR) to detect and quantify ARGs. The obtained qPCR data and hydro-meteorological were used to create an ML model with high prediction performance and we further used two explainable artificial intelligence (xAI) model-agnostic interpretation methods to describe the internal behavior of ML model. Results: Using qPCR, we detected blaCTX-M, blaNDM, blaCMY, blaOXA, blatetX, blasul1, and blaaac(6'-Ib-cr) in the beach waters. Further, we developed ML prediction models for blaaac(6'-Ib-cr), blasul1, and blatetX using the hydro-metrological and qPCR-derived data and the models demonstrated strong performance, with R2 values of 0.957, 0.997, and 0.976, respectively. Conclusions: Our findings show that environmental factors, such as water temperature, precipitation, and tide, are among the important predictors of the abundance of resistance genes at beaches.

Synthesis, characterization and biological investigation of zinc nanoparticles using Acacia modesta Wall. leaves.

The study aimed to synthesize zinc nanoparticles (Zn-NPs) using an aqueous extract derived from Acacia modesta Wall. leaves. Several characterization techniques were employed to confirm the successful formation of zinc nanoparticles. UV-visible spectrophotometry indicated a peak at 374 nm, validating the bioreduction process. Scanning electron microscopy (SEM) was utilized to analyze the morphology, transmission electron microscopy (TEM) to determine particle size and shape, X-ray diffraction (XRD) for crystalline structure analysis, energy-dispersive X-ray spectroscopy (EDX) for elemental composition and Fourier-transform infrared spectroscopy (FTIR) to identify functional groups. The synthesized Zn-NPs demonstrated remarkable antibacterial activity against Escherichia coli (95% inhibition) and moderate antifungal activity against Candida albicans (70% inhibition). In phytotoxicity tests, the Zn-NPs exhibited a 55% reduction in the growth of Lamina minor at the highest dilution (1000 µl). Based on these findings, the study concluded that the green-synthesized Zn-NPs hold great potential as effective antibiotics against pathogenic bacteria and could be utilized in various industrial and agricultural applications.

Biallelic ZNF407 mutations in a neurodevelopmental disorder with ID, short stature and variable microcephaly, hypotonia, ocular anomalies and facial dysmorphism.

We describe five members of a consanguineous Pakistani family (Family I) plus two affected children from families of different ethnic origins presenting with neurodevelopmental disorders with overlapping features. All affected individuals from families have intellectual disability (ID), ranging from mild to profound, and reduced motor and cognitive skills plus variable features including short stature, microcephaly, developmental delay, hypotonia, dysarthria, deafness, visual problems, enuresis, encopresis, behavioural anomalies, delayed pubertal onset and facial dysmorphism. We first mapped the disease locus in the large family (Family I), and by exome sequencing identified homozygous ZNF407 c.2814_2816dup (p.Val939dup) in four affected members where DNA samples were available. By exome sequencing we detected homozygous c.2405G>T (p.Gly802Val) in the affected member of Family II and compound heterozygous variants c.2884C>G (p.Arg962Gly) and c.3642G>C (p.Lys1214Asn) in the affected member of Family III. Homozygous c.5054C>G (p.Ser1685Trp) has been reported in two brothers with an ID syndrome. Affected individuals we present did not exhibit synophrys, midface hypoplasia, kyphosis, 5th finger camptodactyly, short 4th metatarsals or limited knee mobility observed in the reported family.