Environmentally relevant estrogens impaired spermatogenesis and sexual behaviors in male and female zebrafish.

Environmental estrogens (EEs) are found extensively in natural waters and negatively affect fish reproduction. Research on the reproductive toxicity of EEs mixtures in fish at environmentally relevant concentrations is scarce. In this study, adult male zebrafish were exposed for 60 days to EES (a mixture of EEs), EE2-low (5.55 ng/L, with an estrogenic potency equal to EES), and EE2-high (11.1 ng/L). After exposure, the expression levels of vtg1, vtg3, and esr1 in the livers in EES-treated fish remained unaltered, whereas they were significantly increased in EE2-treated fish. Both EE2-high and EES exposures notably reduced the gonad somatic index and sperm count. A disrupted spermatogenesis was also observed in the testes of EE2-high- and EES-exposed fish, along with an alteration in the expression of genes associated with spermatogonial proliferation (pcna, nanog), cell cycle transition (cyclinb1, cyclind1), and meiosis (aldh1a2, cyp26a1, sycp3). Both EE2 and EES significantly lowered plasma 11-ketotestosterone levels in males, likely by inhibiting the expression level of genes for its synthesis (scc, cyp17a1 and cyp11b2), and increased 17ß-estradiol (E2) levels, possibly through upregulating the expression of cyp19a1a. A significant increase in tnfrsf1a expression and the tnfrsf1a/tnfrsf1b ratio in EE2-high and EES-treated males also suggests increased apoptosis via the extrinsic pathway. Further investigation showed that both EE2-high and EES diminished the sexual behavior of male fish, accompanied with reduced E2 levels in the brain and the expression of genes in the kisspeptin/gonadotropin-releasing hormone system. Interestingly, the sexual behavior of unexposed females paired with treated males was also reduced, indicating a synergistic effect. This study suggests that EES have a more severe impact on reproduction than EE2-low, and EEs could interfere not only with spermatogenesis in fish, but also with the sexual behaviors of both exposed males and their female partners, thereby leading to a more significant disruption in fish reproduction.

eDNA reveals spatial homogenization of fish diversity in a mountain river affected by a reservoir cascade.

One of the main reasons for the decline in global freshwater biodiversity can be attributed to alterations in hydrological conditions resulting from dam construction. However, the majority of current research has focused on single or limited numbers of dams. Here, we carried out a seasonal fish survey, using environmental DNA (eDNA) method, on the Wujiang River mainstream (Tributaries of the Yangtze River, China) to investigate the impact of large-scale cascade hydropower development on changes in fish diversity patterns. eDNA survey revealed that native fish species have decreased in contrast to alien fish. There was also a shift in fish community structure, with declines of the dominant rheophilic fish species, an increase of the small-size fish species, and homogenization of species composition across reservoirs. Additionally, environmental factors, such as temperature, dissolved oxygen and reservoir age, had a significant effect on fish community diversity. This study provides basic information for the evaluation of the impact of cascade developments on fish diversity patterns.

Developing Deep LSTMs With Later Temporal Attention for Predicting COVID-19 Severity, Clinical Outcome, and Antibody Level by Screening Serological Indicators Over Time.

OBJECTIVE: The clinical course of COVID-19, as well as the immunological reaction, is notable for its extreme variability. Identifying the main associated factors might help understand the disease progression and physiological status of COVID-19 patients. The dynamic changes of the antibody against Spike protein are crucial for understanding the immune response. This work explores a temporal attention (TA) mechanism of deep learning to predict COVID-19 disease severity, clinical outcomes, and Spike antibody levels by screening serological indicators over time. METHODS: We use feature selection techniques to filter feature subsets that are highly correlated with the target. The specific deep Long Short-Term Memory (LSTM) models are employed to capture the dynamic changes of disease severity, clinical outcome, and Spike antibody level. We also propose deep LSTMs with a TA mechanism to emphasize the later blood test records because later records often attract more attention from doctors. RESULTS: Risk factors highly correlated with COVID-19 are revealed. LSTM achieves the highest classification accuracy for disease severity prediction. Temporal Attention Long Short-Term Memory (TA-LSTM) achieves the best performance for clinical outcome prediction. For Spike antibody level prediction, LSTM achieves the best permanence. CONCLUSION: The experimental results demonstrate the effectiveness of the proposed models. The proposed models can provide a computer-aided medical diagnostics system by simply using time series of serological indicators.

α-synuclein regulates Cyclin D1 to promote abnormal initiation of the cell cycle and induce apoptosis in dopamine neurons.

The etiology of Parkinson's disease (PD) is characterized by the death of dopamine neurons in the substantia nigra pars compacta, while misfolding and abnormal aggregation of α-synuclein (α-syn) are core pathological features. Previous studies have suggested that damage to dopamine neurons may be related to cell cycle dysregulation, but the specific mechanisms remain unclear. In this study, a PD mouse model was induced by stereotactic injection of α-syn into the nucleus, and treated with the cell cycle inhibitor, roscovitine (Rosc). The results demonstrated that Rosc improved behavioral disorders caused by α-syn, increased TH protein expression, inhibited α-syn and p-α-syn protein expression, and reduced the expression levels of G1/S phase cell cycle genes Cyclin D1, Cyclin E, CDK2, CDK4, E2F and pRB. Additionally, Rosc decreased Bax and Caspase-3 expression caused by α-syn, while increasing Bcl-2 protein expression. Meanwhile, we observed that α-syn can influence neuronal cell autophagy by decreasing the expression level of Beclin 1 and increasing the expression level of P62. However, Rosc can improve this phenomenon. In a cell model induced by α-syn in dopamine neuron injury cells, knockdown of Cyclin D1 led to similar results as those observed in animal experiments: Knocking down Cyclin D1 improved the abnormal initiation of the cell cycle caused by α-syn and regulated cellular autophagy, resulting in a reduction of apoptosis in dopamine neurons. In summary, exogenous α-syn can lead to the accumulation of α-syn and phosphorylated α-syn in dopamine neurons, increase key factors of the G1/S phase cell cycle such as Cyclin D1, and regulate downstream related indicators, causing the cell cycle to restart and leading to apoptosis of dopamine neurons. This exacerbates PD symptoms. However, knockdown of Cyclin D1 inhibits the progression of the cell cycle and can reverse this situation. These findings suggest that a Cyclin D inhibitor may be a novel therapeutic target for treating PD.

Identification and preliminary validation of differently expressed genes as candidate biomarkers associated with atherosclerosis.

OBJECTIVE: Atherosclerosis (AS) is the primary cause of deadly cardio-cerebro vascular diseases globally. This study aims to explore the key differentially expressed genes (DEGs), potentially serving as predictive biomarkers for AS. METHODS: Microarray datasets were retrieved from the GEO database for DEGs and DE-miRNAs identification. Then biological function of DEGs were elucidated based on gene ontology (GO) and KEGG pathway enrichment analysis. The protein-protein interaction (PPI) network and DEGs-DE-miRNAs network were constructed, with emphasis on hub DEGs selection and their interconnections. Additionally, receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic precision of hub DEGs for AS. More importantly, an AS Syrian Golden hamster model was established to validate the expression levels of hub DEGs in AS. RESULTS: A total of 203 DEGs and 10 DE-miRNAs were screened, with six genes were chosen as hub DEGs. These DEGs were significantly enriched in AS-related biological processes and pathways, such as immune and inflammatory response, cellular response to IL-1 and TNF, positive regulation of angiogenesis, Type I diabetes mellitus, Cytokine-cytokine receptor interaction, TLR signaling pathway. Also, these DEGs and DE-miRNAs formed a closely-interacted DE-miRNAs - DEGs - KEGG pathway network. Besides, hub DEGs presented promising diagnostic potential for AS (AUC: 0.781 âˆ¼ 0.887). In addition, the protein expression levels of TNF-α, CXCL8, CCL4, IL-1ß, CCL3 and CCR8 were significantly increased in AS group Syrian Golden hamsters. CONCLUSION: The identified candidate genes TNF, CXCL8, CCL4, IL1B, CCL3 and CCR8 may have the potential to serve as prognostic biomarker in diagnosing AS.

Multidirectional associations between the gut microbiota and Parkinson's disease, updated information from the perspectives of humoral pathway, cellular immune pathway and neuronal pathway.

The human gastrointestinal tract is inhabited by a diverse range of microorganisms, collectively known as the gut microbiota, which form a vast and complex ecosystem. It has been reported that the microbiota-gut-brain axis plays a crucial role in regulating host neuroprotective function. Studies have shown that patients with Parkinson's disease (PD) have dysbiosis of the gut microbiota, and experiments involving germ-free mice and fecal microbiota transplantation from PD patients have revealed the pathogenic role of the gut microbiota in PD. Interventions targeting the gut microbiota in PD, including the use of prebiotics, probiotics, and fecal microbiota transplantation, have also shown efficacy in treating PD. However, the causal relationship between the gut microbiota and Parkinson's disease remains intricate. This study reviewed the association between the microbiota-gut-brain axis and PD from the perspectives of humoral pathway, cellular immune pathway and neuronal pathway. We found that the interactions among gut microbiota and PD are very complex, which should be "multidirectional", rather than conventionally regarded "bidirectional". To realize application of the gut microbiota-related mechanisms in the clinical setting, we propose several problems which should be addressed in the future study.

Exploring a novel therapeutic strategy: the interplay between gut microbiota and high-fat diet in the pathogenesis of metabolic disorders.

In the past two decades, the rapid increase in the incidence of metabolic diseases, including obesity, diabetes, dyslipidemia, non-alcoholic fatty liver disease, hypertension, and hyperuricemia, has been attributed to high-fat diets (HFD) and decreased physical activity levels. Although the phenotypes and pathologies of these metabolic diseases vary, patients with these diseases exhibit disease-specific alterations in the composition and function of their gut microbiota. Studies in germ-free mice have shown that both HFD and gut microbiota can promote the development of metabolic diseases, and HFD can disrupt the balance of gut microbiota. Therefore, investigating the interaction between gut microbiota and HFD in the pathogenesis of metabolic diseases is crucial for identifying novel therapeutic strategies for these diseases. This review takes HFD as the starting point, providing a detailed analysis of the pivotal role of HFD in the development of metabolic disorders. It comprehensively elucidates the impact of HFD on the balance of intestinal microbiota, analyzes the mechanisms underlying gut microbiota dysbiosis leading to metabolic disruptions, and explores the associated genetic factors. Finally, the potential of targeting the gut microbiota as a means to address metabolic disturbances induced by HFD is discussed. In summary, this review offers theoretical support and proposes new research avenues for investigating the role of nutrition-related factors in the pathogenesis of metabolic disorders in the organism.