A novel MED12 pathogenic variant in a female fetus with facial cleft and cardiac defects identified in the first trimester.

Trio exome sequencing was performed on a female fetus with an increased nuchal translucency, along with nasal bone hypoplasia, suspected cleft palate and abnormal outflow tract of the heart. A de novo heterozygous variant c.5500_5507del, p.(Tyr1834Argfs × 58) in the MED12 gene was detected. Loss-of-function variants in MED12 in females are associated with Hardikar syndrome (HS). A follow-up ultrasound at 15+5 weeks of gestation identified multiple fetal anomalies including bilateral cleft lip and palate, diaphragmatic hernia, atrioventricular septal defect, persistent truncus arteriosus, and bilateral renal pelvis dilation. Fetal autopsy confirmed the prenatal sonographic findings, and the MED12 variant was discussed by our multidisciplinary team to be the cause of fetal anomalies. Our case is the first prenatal one in which HS was diagnosed due to first trimester structural malformations. This case report presents another example of early identification of a major anomaly which allows earlier genetic diagnosis and more time for clinical management.

High-Accuracy Tomato Leaf Disease Image-Text Retrieval Method Utilizing LAFANet.

Tomato leaf disease control in the field of smart agriculture urgently requires attention and reinforcement. This paper proposes a method called LAFANet for image-text retrieval, which integrates image and text information for joint analysis of multimodal data, helping agricultural practitioners to provide more comprehensive and in-depth diagnostic evidence to ensure the quality and yield of tomatoes. First, we focus on six common tomato leaf disease images and text descriptions, creating a Tomato Leaf Disease Image-Text Retrieval Dataset (TLDITRD), introducing image-text retrieval into the field of tomato leaf disease retrieval. Then, utilizing ViT and BERT models, we extract detailed image features and sequences of textual features, incorporating contextual information from image-text pairs. To address errors in image-text retrieval caused by complex backgrounds, we propose Learnable Fusion Attention (LFA) to amplify the fusion of textual and image features, thereby extracting substantial semantic insights from both modalities. To delve further into the semantic connections across various modalities, we propose a False Negative Elimination-Adversarial Negative Selection (FNE-ANS) approach. This method aims to identify adversarial negative instances that specifically target false negatives within the triplet function, thereby imposing constraints on the model. To bolster the model's capacity for generalization and precision, we propose Adversarial Regularization (AR). This approach involves incorporating adversarial perturbations during model training, thereby fortifying its resilience and adaptability to slight variations in input data. Experimental results show that, compared with existing ultramodern models, LAFANet outperformed existing models on TLDITRD dataset, with top1, top5, and top10 reaching 83.3% and 90.0%, and top1, top5, and top10 reaching 80.3%, 93.7%, and 96.3%. LAFANet offers fresh technical backing and algorithmic insights for the retrieval of tomato leaf disease through image-text correlation.

Mutations in the MepRAB efflux system contribute to the in vitro development of tigecycline resistance in Staphylococcus aureus.

OBJECTIVE: To characterize the evolutionary pathways of tigecycline (TGC) resistance and alterations in the biological characteristics of hospital-derived Staphylococcus aureus isolates under selective pressure. METHODS: Three clinical S. aureus strains and one standard S. aureus strain, ATCC 29213, were used for the in vitro selection of TGC-resistant S. aureus variants with gradient concentrations of TGC. Changes in drug resistance and genetic alterations in resistance-related genes (operon mepRAB and rpsJ) in mutant strains were determined. The efflux inhibitor assay for MepA and the fitness cost, determined by comparing the growth and virulence of parental and mutant strains, were also investigated. RESULTS: Mutants induced in vitro showed a 64- to 128-fold increase in the minimum inhibitory concentration (MIC) of TGC. Substitution mutations were detected in the transcriptional repressor mepR and the efflux pump gene mepA. A K57M amino acid substitution occurred in the ribosomal S10 protein-encoding gene rpsJ. The MICs of TGC in the final mutants were significantly decreased in the presence of efflux pump inhibitors. It was worth noting that growth was unaffected by TGC resistance selection in vitro, with the exception of one strain, and the MICs of other antibiotics and virulence were also unaffected. CONCLUSIONS: The evolution of TGC resistance in S. aureus in vitro is associated with a loss-of-function mutation in the efflux pump transcriptional repressor mepR and a missense mutation in the efflux pump-encoding gene mepA. Our work further validated the resistance mechanisms of S. aureus to TGC and reported previously undiscovered mutations.