Regulation of spermatogonial stem cell differentiation by Sertoli cells-derived exosomes through paracrine and autocrine signaling.

In the orchestrated environment of the testicular niche, the equilibrium between self-renewal and differentiation of spermatogonial stem cells (SSCs) is meticulously maintained, ensuring a stable stem cell reserve and robust spermatogenesis. Within this milieu, extracellular vesicles, specifically exosomes, have emerged as critical conveyors of intercellular communication. Despite their recognized significance, the implications of testicular exosomes in modulating SSC fate remain incompletely characterized. Given the fundamental support and regulatory influence of Sertoli cells (SCs) on SSCs, we were compelled to explore the role of SC-derived exosomes (SC-EXOs) in the SSC-testicular niche. Our investigation hinged on the hypothesis that SC-EXOs, secreted by SCs from the testes of 5-day-old mice-a developmental juncture marking the onset of SSC differentiation-participate in the regulation of this process. We discovered that exposure to SC-EXOs resulted in an upsurge of PLZF, MVH, and STRA8 expression in SSC cultures, concomitant with a diminution of ID4 and GFRA1 levels. Intriguingly, obstructing exosomal communication in a SC-SSC coculture system with the exosome inhibitor GW4869 attenuated SSC differentiation, suggesting that SC-EXOs may modulate this process via paracrine signaling. Further scrutiny revealed the presence of miR-493-5p within SC-EXOs, which suppresses Gdnf mRNA in SCs to indirectly restrain SSC differentiation through the modulation of GDNF expression-an indication of autocrine regulation. Collectively, our findings illuminate the complex regulatory schema by which SC-EXOs affect SSC differentiation, offering novel perspectives and laying the groundwork for future preclinical and clinical investigations.

A novel hybrid model based on two-stage data processing and machine learning for forecasting chlorophyll-a concentration in reservoirs.

The accurate and efficient prediction of chlorophyll-a (Chl-a) concentration is crucial for the early detection of algal blooms in reservoirs. Nevertheless, predicting Chl-a concentration in multivariate time series poses a significant challenge due to the complex interrelationships within the aquatic environment and the discrete and non-stationary nature of online monitoring of water quality data. To address the aforementioned issue, this paper proposes a novel prediction model named SGMD-KPCA-BiLSTM (SKB) for predicting Chl-a concentration. The model combines two-stage data processing and machine learning (ML). To capture nonlinear relationships in multivariate time series data, the optimal data subset is determined by combining symplectic geometry mode decomposition (SGMD) and kernel principal component analysis (KPCA). This subset is then input into a bidirectional long short-term memory (BiLSTM) model, and the model's hyperparameters are optimized using the sparrow search algorithm (SSA) to improve the accuracy of predictions. The performance of the model was evaluated at Qiaodian Reservoir in Shandong, China. To assess its superiority, the evaluation criteria included the root mean square error (RMSE), mean absolute percentage error (MAPE), mean absolute error (MAE), coefficient of determination (R2), frequency histograms of the prediction error, and the Taylor diagram. The prediction performance of five single models, namely the back-propagation (BP) neural network, support vector regression (SVR), long short-term memory (LSTM), convolutional neural network with long short-term memory (CNN-LSTM), and BiLSTM, as well as three hybrid models, namely SGMD-LSTM, SGMD-KPCA-LSTM, and SGMD-BiLSTM, were compared against the SKB model. The results demonstrated that the SKB model performs best in predicting Chl-a concentration (R2 = 96.19%, RMSE = 1.05, MAE = 0.65, MAPE = 0.08). It significantly reduced the prediction error compared to other models for comparison. Furthermore, the multi-step predictive capabilities of the SKB model are also discussed. The analysis shows a decline in predictive performance with larger prediction time steps, and the SKB model exhibits slightly superior performance compared to the other model at corresponding prediction intervals. The model has significant advantages in terms of its ability to accurately predict the non-smooth and nonlinear Chl-a sequences observed by the online monitoring system. This study presents a potential solution for controlling and preventing reservoir eutrophication, as well as an innovative approach for predicting water quality.

Calculation of Short-Term Creep of Concrete Using Fractional Viscoelastic Model.

The study of short-term creep is essential for understanding the concrete creep process and deformation under alternating stress. Researchers are concentrating on the nano- and micron-scale creep of cement pastes. In the latest RILEM creep database, short-term concrete creep data at hourly or minutely levels are still rare and scarce. In order to describe the short-term creep and creep-recovery behavior of concrete specimens more accurately, the short-term creep and creep-recovery experiments were carried out firstly. The load-holding time varied from 60 s to 1800 s. Secondly, the accuracy of current creep models (B4, B4s, MC2010, and ACI209) in predicting the short-term creep of concrete was compared. It was discovered that the B4, B4s, and MC2010 models all overestimate concrete's short-term creep, and the ACI model does the opposite. Thirdly, the applicability of the fractional-order-derivative viscoelastic model (with a derivative order between 0 and 1) in the calculation of the short-term creep and creep recovery of concrete is investigated. The calculation results show that the fractional-order derivatives are more suitable for analyzing the static viscoelastic deformation of concrete while the classical viscoelastic model requires a large number of parameters. Therefore, a modified fractional-order viscoelastic model is proposed considering the residual deformation characteristics of concrete after unloading, and the values of the model parameters under different conditions are given with the experimental data.

Black Soldier Fly (Hermetia illucens) Larvae Meal Modulates Intestinal Morphology and Microbiota in Xuefeng Black-Bone Chickens.

The addition of Hermetia illucens larvae meal (HILM) to the feed could contribute to particular antimicrobial and intestinal health in animal husbandry. This study was conducted to investigate the effects of HILM on intestinal morphology and microbial diversity in different intestinal segments of Xuefeng black-bone chickens. All of 432 birds (45 weeks old) were randomly assigned to four equal groups with six replicates and 18 hens in each replicate: (A) basal diet, (B) basal diet with 1% HILM, (C) basal diet with 3% HILM, and (D) basal diet with 5% HILM. The results showed that, compared with the basal diet group, the HILM supplement significantly increased the abundance-based coverage estimator (ACE) and Chao index in cecum (p < 0.05). Diet with 1% HILM significantly increased the villus height (VH) of the duodenum (p < 0.05) and cecum microbial diversity as represented by the Simpson index (p < 0.05). In particular, 1% HILM displayed a markedly increase in the genus unclassified Bacteroidales (cecum, p < 0.05). A basal diet with 3% HILM markedly increased the beneficial genus Romboutsia (jejunum, p < 0.05). Also, principal component analysis (PCA) cluster analysis showed that 3% of HILM was more individual than other groups (p < 0.05). However, 5% HILM decreased the VH and the ratio of villus height to crypt depth (VH/CD) of the jejunum and increased beneficial bacteria such as Staphylococcus (p < 0.05), which was regarded as pathogenetic genera. In conclusion, we found that HILM improved intestinal morphology and increased microbiological diversity and species abundance. Together, dietary supplementation of 1 or 3% HILM might benefit the intestinal morphology and intestinal microbiota of Xuefeng black-bone chicken. However, the addition of 5% HILM could decrease VH and the ratio of VH/CD of the jejunum and increased pathogenetic genera. HILM was an excellent protein substitute for Xuefeng black-bone chickens, which could meet the nutritional requirements under the condition of less feed. These results provide information for HILM meal as an alternative source of soybean meal in Xuefeng black-bone chickens' feed.

Improved grain yield and lowered arsenic accumulation in rice plants by inoculation with arsenite-oxidizing Achromobacter xylosoxidans GD03.

Arsenite is the predominant arsenic species in flooded paddy soil, and arsenite bioaccumulation in rice grains has been identified as a major problem in many Asian countries. Lowering arsenite level in rice plants and grain via accelerating arsenite oxidation is a potential strategy to help populations, who depended on rice consumption, to reduce the internal exposure level of arsenic. We herein isolated a strain, Achromobacter xylosoxidans GD03, with the high arsenite-oxidizing ability and plant growth-promoting traits. We observed that arsenite exposure could promote A. xylosoxidans GD03 to excrete indole-3-acetic acid and thus promoted rice growth. The pot culture experiments of Indica rice cultivar Guang You Ming 118 (GYM118) demonstrated that A. xylosoxidans GD03 inoculation of paddy soil (4.5-180 × 108 CFU GD03/kg soil) significantly accelerated arsenite oxidation in flooded soil. The daily arsenic oxidation rate with GD03 inoculation was 1.5-3.3 times as that without strain GD03 inoculation within the whole growth period of Indica GYM118 in the presence of the native microflora. It thus led to a 34-69%, 43-74%, 24-76% and 35-57% decrease in arsenite concentration of the stems, leaves, bran and grain of Indica GYM118 respectively and a 59-96% increase in rice grain yield. The paddy soil inoculated with 40.0 mL/kg of A. xylosoxidans GD03 resulted in a lowest As(III) concentrations in all rice organs of Indica GYM118, which equivalent to only 24-50% of the As(III) concentrations in the group without GD03 inoculation. The results highlight that a highly arsenite-oxidizing bacterium could accelerate arsenite oxidation of paddy soil when facing competition with the native microflora, thus decrease arsenic toxicity and bioavailable soil arsenic.

Geometric effect analysis of highway-rail grade crossing safety performance.

Highway-rail grade crossings (HRGCs) are where a roadway and railway intersect at the same level. Safety at HRGCs has been identified as a high-priority concern among transportation agencies, but there has been little research on the effects of HRGC geometric parameters on their safety performance. This paper evaluates the effects of HRGC geometric parameters on crash occurrence and severity likelihoods. The competing risk algorithm is selected to simultaneously analyze crash occurrence and severities. Four main HRGC geometric factors, along with other contributors, are investigated at 3,194 public HRGCs in North Dakota. This study focuses primarily on four geometric features of an HRGC: (1) acute crossing angle, (2) number of tracks (indicator of crossing width), (3) the roadway distance between the HRGC and the signalized intersection, and (4) number of highway lanes. Distance to the nearest roadway intersections and highway-railway crossing angles are map-based calculations drawn from geographic information systems (GIS). The findings are: (1) all contributors tested in this study, including highway characteristics, traffic exposures from both railway and highway, and the four geometric features, significantly affect at least one crash severity level; (2) all contributors significantly impact crash frequency except for the distance between crossings and the nearest roadway intersection; and (3) geometric parameters' long-term effects on cumulative probability of crash severity and occurrence over 30 years is also evaluated. Crossings with three main tracks contribute the highest long-term crash probabilities.

Clinical and epidemiological characteristics of adult hand, foot, and mouth disease in northern Zhejiang, China, May 2008-November 2013.

BACKGROUND: Hand, foot, and mouth disease (HFMD) is an infectious disease typically caused by enterovirus 71 (EV71) and Coxsackievirus A16. The incidence of HFMD appears to be increasing across the Asia Pacific region, with deaths occurring predominantly among children. Therefore, most HFMD reports focus on children and few have studied HFMD in adults. However, more adult HFMD cases may be seen in the foreseeable future as a result of global warming, continued viral evolution, and an increase in traveling. Thus, this study investigated the clinical and epidemiological characteristics of adult HFMD. METHODS: Case data of 49 adult HFMD patients who attended The First Affiliated Hospital of Jiaxing College, China from May 2008 to November 2013 were obtained. Socio-demographic data were collected through follow-up phone calls. Throat swab specimens were tested for enterovirus by quantitative reverse transcription-polymerase chain reaction and further confirmed by virus isolation assay. For 10 patients infected with EV71, the gene encoding the EV71 VP1 protein was sequenced and analyzed. Data from 8,354 child HFMD patients and 49 adult patients in the fever clinic of The First Affiliated Hospital of Jiaxing College during the same period were collected for comparison. RESULTS: This study revealed that close contact with HFMD patients and poor personal hygiene consciousness were risk factors for adult HFMD. This study also found that EV71 subgenotype C4a was the most common pathogen associated with adult HFMD in this area. Furthermore, this study demonstrated several unique epidemiological characteristics of adult HFMD compared to child HFMD, such as the geographic and gender distribution of adult HFMD patients and HFMD seasonality. CONCLUSIONS: The findings in this study showed the potential threat of adult HFMD.

[Qualitative research of self-management behavior in patients with advanced schistosomiasis].

OBJECTIVE: To explore the self-management behavior of patients with advanced schistosomiasis, so as to provide the evidence for improving clinical nursing. METHODS: A total of 18 patients with advanced schistosomiasis were interviewed in depth by using a semi structured interview method. The results were analyzed with Miles and Huberman content analysis method. RESULTS: Most of the patients with advanced schistosomiasis had self-management control behavior and were cooperated with medical assistance because of their seriously illness. Based on data analysis, the symptom management, follow-up management, a healthy lifestyle, medication awareness, and emotional management were obtained. CONCLUSION: The patients with advanced schistosomiasis have self management control behavior. Health care workers should promote the patients, their families and social people to participate in the self-management behavior of advanced schistosomiasis patients.