Role of gut microbiota in the pathogenesis of castration-resistant prostate cancer: a comprehensive study using sequencing and animal models.

CRPC remains a significant challenge in prostate cancer research. We aimed to elucidate the role of gut microbiota and its specific mechanisms in CRPC using a multidisciplinary approach. We analyzed 16S rRNA sequencing data from mouse fecal samples, revealing substantial differences in gut microbiota composition between CRPC and castration-sensitive prostate cancer mice, particularly in Firmicutes and Bacteroidetes. Functional analysis suggested different bacteria may influence CRPC via the α-linolenic acid metabolism pathway. In vivo, experiments utilizing mouse models and fecal microbiota transplantation (FMT) demonstrated that FMT from healthy control mice could decelerate tumor growth in CRPC mice, reduce TNF-α levels, and inhibit the activation of the TLR4/MyD88/NF-κB signaling pathway. Transcriptome sequencing identified crucial genes and pathways, with rescue experiments confirming the gut microbiota's role in modulating CRPC progression through the TLR4/MyD88/NF-κB pathway. The activation of this pathway by TNF-α has been corroborated by in vitro cell experiments, indicating its role in promoting prostate cancer cell proliferation, migration, and invasion while inhibiting apoptosis. Gut microbiota dysbiosis may promote CRPC development through TNF-α activation of the TLR4/MyD88/NF-κB signaling pathway, potentially linked to α-linolenic acid metabolism.

Real-world effectiveness and safety of goserelin 10.8-mg depot in Chinese patients with localized or locally advanced prostate cancer.

OBJECTIVE: Real-word data on long-acting luteinizing hormone-releasing hormone (LHRH) agonists in Chinese patients with prostate cancer are limited. This study aimed to determine the real-world effectiveness and safety of the LHRH agonist, goserelin, particularly the long-acting 10.8-mg depot formulation, and the follow-up patterns among Chinese prostate cancer patients. METHODS: This was a multicenter, prospective, observational study in hormone treatment-naïve patients with localized or locally advanced prostate cancer who were prescribed goserelin 10.8-mg depot every 12 weeks or 3.6-mg depot every 4 weeks with or without an anti-androgen. The patients had follow-up evaluations for 26 weeks. The primary outcome was the effectiveness of goserelin in reducing serum testosterone and prostate-specific antigen (PSA) levels. The secondary outcomes included testosterone and PSA levels, attainment of chemical castration (serum testosterone <50 ng/dL), and goserelin safety. The exploratory outcome was the monitoring pattern for serum testosterone and PSA. All analyses were descriptive. RESULTS: Between September 2017 and December 2019, a total of 294 eligible patients received ≥ 1 dose of goserelin; 287 patients (97.6%) were treated with goserelin 10.8-mg depot. At week 24 ± 2, the changes from baseline [standard deviation (95% confidence interval)] in serum testosterone (n = 99) and PSA (n = 131) were -401.0 ng/dL [308.4 ng/dL (-462.5, -339.5 ng/dL)] and -35.4 ng/mL [104.4 ng/mL (-53.5, -17.4 ng/mL)], respectively. Of 112 evaluable patients, 100 (90.2%) achieved a serum testosterone level < 50 ng/dL. Treatment-emergent adverse events (TEAEs) and severe TEAEs occurred in 37.1% and 10.2% of patients, respectively. The mean testing frequency (standard deviation) was 1.6 (1.5) for testosterone and 2.2 (1.6) for PSA. CONCLUSIONS: Goserelin 10.8-mg depot effectively achieved and maintained castration and was well-tolerated in Chinese patients with localized and locally advanced prostate cancer.

FV-MViT: Mobile Vision Transformer for Finger Vein Recognition.

In addressing challenges related to high parameter counts and limited training samples for finger vein recognition, we present the FV-MViT model. It serves as a lightweight deep learning solution, emphasizing high accuracy, portable design, and low latency. The FV-MViT introduces two key components. The Mul-MV2 Block utilizes a dual-path inverted residual connection structure for multi-scale convolutions, extracting additional local features. Simultaneously, the Enhanced MobileViT Block eliminates the large-scale convolution block at the beginning of the original MobileViT Block. It converts the Transformer's self-attention into separable self-attention with linear complexity, optimizing the back end of the original MobileViT Block with depth-wise separable convolutions. This aims to extract global features and effectively reduce parameter counts and feature extraction times. Additionally, we introduce a soft target center cross-entropy loss function to enhance generalization and increase accuracy. Experimental results indicate that the FV-MViT achieves a recognition accuracy of 99.53% and 100.00% on the Shandong University (SDU) and Universiti Teknologi Malaysia (USM) datasets, with equal error rates of 0.47% and 0.02%, respectively. The model has a parameter count of 5.26 million and exhibits a latency of 10.00 milliseconds from the sample input to the recognition output. Comparison with state-of-the-art (SOTA) methods reveals competitive performance for FV-MViT.

Antibiotic Resistance and Genetic Profiles of Vibrio parahaemolyticus Isolated from Farmed Pacific White Shrimp (Litopenaeus vannamei) in Ningde Regions.

To better understand the antibiotic resistance, virulence genes, and some related drug-resistance genes of Vibrio parahaemolyticus in farmed pacific white shrimp (Litopenaeus vannamei) in Ningde regions, Fujian province, we collected and isolated a total of 102 strains of V. parahaemolyticus from farmed pacific white shrimp in three different areas of Ningde in 2022. The Kirby-Bauer disk method was used to detect V. parahaemolyticus resistance to 22 antibiotics, and resistant genes (such as quinolones (qnrVC136, qnrVC457, qnrA), tetracyclines (tet A, tetM, tetB), sulfonamides (sulI, sulII, sulIII), aminoglycosides (strA, strB), phenicols (cat, optrA, floR, cfr), ß-lactams (carB), and macrolides (erm)) were detected by using PCR. The findings in this study revealed that V. parahaemolyticus was most resistant to sulfamoxazole, rifampicin, and erythromycin, with resistance rates of 56.9%, 36.3%, and 33.3%, respectively. Flufenicol, chloramphenicol, and ofloxacin susceptibility rates were 97.1%, 94.1%, and 92.2%, respectively. In all, 46% of the bacteria tested positive for multi-drug resistance. The virulence gene test revealed that all bacteria lacked the tdh and trh genes. Furthermore, 91.84% and 52.04% of the isolates were largely mediated by cat and sulII, respectively, with less than 5% resistance to aminoglycosides and macrolides. There was a clear mismatch between the antimicrobial resistance phenotypes and genotypes, indicating the complexities of V. parahaemolyticus resistance.