Hepcidin contributes to largemouth bass (Micropterus salmoides) against bacterial infections.

The increasing emergence and dissemination of bacterial pathogens in largemouth bass culture accelerate the desire for new treatment measures. Antimicrobial peptides as the host's antimicrobial source dominate the preferred molecules for discovering antibacterial agents. Here, the potential of Hepcidin-1 from largemouth bass (Micropterus salmoides) (MsHep-1) against bacterial infection is demonstrated. MsHep-1 not only improved the survival rate in infection experiments involving Nocardia seriolae (12 %) and Aeromonas hydrophila (18 %) but also coped with iron overload conditions in vivo. Moreover, the antibacterial activity of MsHep-1 in vitro was identified against both gram-negative and gram-positive bacteria. Mechanistic studies show MsHep-1 leads to bacterial death by changing the bacterial membrane potential and disrupting the bacterial membrane structure. These findings demonstrate that MsHep-1 may play an important role in the host response to bacterial infection. It provides promising strategies in the application of immunosuppression prevention and control in fish. AMPs may be a promising and available reservoir for treating the current bacterial diseases.

IFN-γ enhances protective efficacy against Nocardia seriolae infection in largemouth bass (Micropterus salmoides).

Introduction: Nocardia seriolae adversely impacts a diverse range of fish species, exhibiting significant pathogenic characteristics that substantially impede the progress of aquaculture. N. seriolae infects in fish has a long incubation period, and clinical symptoms are not obvious in the early stages. There is presently no viable and eco-friendly approach to combat the spread of the disease. According to reports, N. seriolae primarily targets macrophages in tissues after infecting fish and can proliferate massively, leading to the death of fish. Interferon-gamma (IFN-γ) is a crucial molecule that regulates macrophage activation, but little is known about its role in the N. seriolae prevention. Methods: IFN-γ was first defined as largemouth bass (Micropterus salmoides, MsIFN-γ), which has a highly conserved IFN-γ characteristic sequence through homology analysis. The recombinant proteins (rMsIFN-γ) were obtained in Escherichia coli (E. coli) strain BL21 (DE3). The inflammatory response-inducing ability of rMsIFN-γ was assessed in vitro using monocytes/macrophages. Meanwhile, the protective effect of MsIFN-γ in vivo was evaluated by N. seriolae infection largemouth bass model. Results: In the inflammatory response of the monocytes/macrophages activated by rMsIFN-γ, various cytokines were significantly increased. Interestingly, interleukin 1ß (IL-1ß) and tumor necrosis factor alpha (TNF-a) increased by 183- and 12-fold, respectively, after rMsIFN-γ stimulation. rMsIFN-γ improved survival by 42.1% compared with the control. The bacterial load in the liver, spleen and head kidney significantly decreased. rMsIFN-γ was also shown to better induce increased expression of IL-1ß, TNF-α, hepcidin-1(Hep-1), major histocompatibility complex I (MHCI), and MHC II in head kidney, spleen and liver. The histopathological examination demonstrated the transformation of granuloma status from an early necrotic foci to fibrosis in the infection period. Unexpectedly, the development of granulomas was successfully slowed in the rMsIFN-γ group. Discussion: This work paves the way for further research into IFN-γ of largemouth bass and identifies a potential therapeutic target for the prevention of N. seriolae.

Anticipating interpersonal sensitivity: A predictive model for early intervention in psychological disorders in college students.

Psychological disorders, notably social anxiety and depression, exert detrimental effects on university students, impeding academic achievement and overall development. Timely identification of interpersonal sensitivity becomes imperative to implement targeted support and interventions. This study selected 958 freshmen from higher education institutions in Zhejiang province as the research sample. Utilizing the runge-kutta search and elite levy spreading enhanced moth-flame optimization (MFO) in conjunction with the kernel extreme learning machine (KELM), we propose an efficient intelligent prediction model, namely bREMFO-KELM, for predicting the interpersonal sensitivity of college students. IEEE CEC 2017 benchmark functions and the interpersonal sensitivity dataset were employed as the basis for detailed comparisons with peer-reviewed studies and well-known machine learning models. The experimental results demonstrate the outstanding performance of the bREMFO-KELM model in predicting the sensitivity of interpersonal relationships in college students, achieving an impressive accuracy rate of 97.186%. In-depth analysis reveals that the prediction of interpersonal sensitivity in college students is closely associated with multiple features, including easily hurt in relationships, shy and uneasy with the opposite sex, feeling inferior to others, discomfort when observed or discussed, and blame and criticize others. These features are not only crucial for the accuracy of the prediction model but also provide valuable information for a deeper understanding of the sensitivity of college students' interpersonal relationships. In conclusion, the bREMFO-KELM model excels not only in performance but also possesses a high degree of interpretability, providing robust support for predicting the sensitivity of interpersonal relationships in college students.