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Traumatic central nervous system injury, including traumatic brain injury and spinal cord injury, has extremely high disability and mortality rates. The huge medical expenses and sequelae further aggravate the economic and psychological burden of patients and their families. Current treatments for traumatic central nervous system injury include surgical therapy, physical therapy, medication and post-rehabilitation treatment, but none of them can achieve ideal efficacy, and more effective treatment is urgently needed. Ferroptosis, as one of the newly discovered modes of programmed cell death, has been shown to play a crucial role in secondary injury to the traumatic central nervous system, but its clinical transformation is limited. This article summarizes the research results of ferroptosis inhibitors, points out the types and effects of them, to provide new ideas for clinical treatment of traumatic central nervous system injury and drug development.

Infertility is a prevalent problem among 10% of people within their reproductive years. Sometimes, even advanced treatment options like assisted reproduction technology have the potential to result in failed implantation. Because of the expected changes in gene expression during both in vitro and in vivo fertilization processes, these methods of assisting fertility have also been associated with undesirable pregnancy outcomes related to infertility. In this aspect, Circular RNAs (circRNAs) play a crucial role as epigenetic modifiers in a wide range of biological and pathological activities, including problems with fertility. CircRNAs are integral pieces in multiple cellular functions, including moving substances within the nucleus, silencing one X chromosome, cell death, the ability of stem cells to differentiate into different cell types, and the process of gene expression inherited from parental genes. Due to the progress made in high-speed gene sequencing, a large amount of circRNA molecules have been detected, revealing their significant functions in diverse biological functions like enhancing testicular development, preserving the differentiation and renewal of spermatogonial cells, and controlling spermatocyte meiosis. Moreover, these non-coding RNAs contribute in different aspects of female reproductive system including pregnancy-related diseases, gynecologic cancers, and endometriosis. In conclusion, there is no denying that circRNAs have immense potential to be used as biomarkers and treatments for reproductive disorders in males and females. In this research, we provide a comprehensive analysis of the multiple circRNAs associated with women's infertility. [ABSTRACT FROM AUTHOR]

Relay strip intercropping (RSI) increases soybean nodule number and nitrogen fixation activity at the reproductive stage more than monocropping (M), but the effect of changes in the environment, especially light, on nodules during the coexistence duration and vegetative stage, is unclear. To determine the impact of shading on nodule development at the seedling stage, nodule traits, distribution, and physiological function were compared between M and RSI in a potting experiment in a field environment. Compared with M, nodule number and weight decreased significantly (an average of 81.77% and 93.16%, respectively); thus, the exponential relationship between them changed because of the smaller nodule in RSI. Nodules were clustered on the tap roots, but there was no effect on the distribution of nodule weight on the tap or lateral root. The nodule density of the tap root notably decreased by an average of 56.00%, whereas that of the lateral root showed no difference. Dry weight-specific nodulation (DW-specific), and the ratio of nodule weight to root or whole plant weight decreased (61.33%, 85.46%, and 88.50%, respectively). Nodule leghemoglobin and sucrose content decreased in RSI by 94.29% and 95.17% at the plant level, and nodule nitrogenase activity was suppressed, especially at the plant level. The nodule growth and nitrogen fixation ability of ND showed the strongest adaptability to shading among the varieties. [ABSTRACT FROM AUTHOR]

Objective The aim of this study is to evaluate performance of aldosterone-to-renin ratio (ARR) before washout of antihypertensive drugs as a screening test for primary aldosteronism (PA). Methods This retrospective analysis included consecutive patients screening for secondary hypertension during a period from January 2017 to May 2022 at the authors' institute. For inclusion in the final analysis, ARR had to be available prior to as well as after discontinuation of antihypertensives. Patients with ARR ≥2.4(ng/dL)/(μIU/mL) after washout proceeded to confirmatory tests. Diagnosis of PA was established based on a positive result of the confirmatory test. The diagnostic accuracy of ARR prior to the washout in predicting PA is shown as sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Results The analysis included a total of 1306 patients [median age of 50.2 (41.0-59.0) years, 64.0% male]. Confirmatory tests showed PA in 215(16.5%) patients and essential hypertension (EH) in the remaining 1091(83.5%) patients. In comparison to the second screening test, the first screening test (before washout of antihypertensives) yielded lower plasma aldosterone and higher renin and consequently lower ARR in both the PA and EH groups. At a cutoff of.7(ng/dL)/(μIU/mL), ARR before washout had 96.3% sensitivity, 61.2% specificity,.33 PPV, and.99 NPV. At a lower cutoff of.5(ng/dL)/(μIU/mL), the sensitivity, specificity, PPV, and NPV were 97.7%, 52.0%,.29, and.99, respectively. Conclusion ARR prior to washout of antihypertensives is a sensitive screening test for PA. Washout of antihypertensives could be omitted and further investigation for PA is not warranted if ARR is ≤.7(ng/dL)/(μIU/mL) before washout. [ABSTRACT FROM AUTHOR]

Background: Highly heterogeneity and inconsistency in terms of prognosis are widely identified for early‐stage cervical cancer (esCC). Herein, we aim to investigate for an intuitional risk stratification model for better prognostication and decision‐making in combination with clinical and pathological variables. Methods: We enrolled 2071 CC patients with preoperative biopsy‐confirmed and clinically diagnosed with FIGO stage IA‐IIA who received radical hysterectomy from 2013 to 2018. Patients were randomly assigned to the training set (n = 1450) and internal validation set (n = 621), in a ratio of 7:3. We used recursive partitioning analysis (RPA) to develop a risk stratification model and assessed the ability of discrimination and calibration of the RPA‐derived model. The performances of the model were compared with the conventional FIGO 2018 and 9th edition T or N stage classifications. Results: RPA divided patients into four risk groups with distinct survival: 5‐year OS for RPA I to IV were 98%, 95%, 85.5%, and 64.2%, respectively, in training cohort; and 99.5%, 93.2%, 85%, and 68.3% in internal validation cohort (log‐rank p < 0.001). Calibration curves confirmed that the RPA‐predicted survivals were in good agreement with the actual survivals. The RPA model outperformed the existing staging systems, with highest AUC for OS (training: 0.778 vs. 0.6–0.717; internal validation: 0.772 vs. 0.595–0.704; all p < 0.05), and C‐index for OS (training: 0.768 vs. 0.598–0.707; internal validation: 0.741 vs. 0.583–0.676; all p < 0.05). Importantly, there were associations between RPA groups and the efficacy of treatment regimens. No obvious discrepancy was observed among different treatment modalities in RPA I (p = 0.922), whereas significant survival improvements were identified in patients who received adjuvant chemoradiotherapy in RPA II–IV (p value were 0.028, 0.036, and 0.024, respectively). Conclusion: We presented a validated novel clinicopathological risk stratification signature for robust prognostication of esCC, which may be used for streamlining treatment strategies. [ABSTRACT FROM AUTHOR]

It has been 3 years since the first appearance of COVID-19 in China. During this time, social isolation was widely used as an important method to fight it. However, this measure had many negative effects on the mental health of college students. To better understand this issue, this study aims to explore the impact of social isolation and COVID-19-related stress on psychological distress among Chinese college students. Additionally, resilience has been evaluated as a key component of stress resistance in this situation. Coronavirus Stress Measure (CSM), the Connor-Davidson Resilience Scale (CD-RISC) and the Brief Symptom Inventory (BSI) were used in this study. A total of 388 Chinese college students participated in the survey via the Internet. Two groups (isolated group vs. non-isolated group) were divided according to whether they have been isolated from their classmates and families. Data analysis adopts t-test, F test and mediate effect analysis by SPSS21.0. (1) All factors, except resilience, were found to have lower scores in the isolated group; (2) significant correlations were found between all factors; (3) resilience partially mitigated the impact of COVID-19 stress on psychological symptoms. Social isolation has been found to be a significant factor contributing to negative psychological distress in Chinese college students. The COVID-19-related stress may increase the likelihood of psychological suffering among isolated group. Resilience can help reduce the negative effects of COVID-19 stress on college students. Therefore, providing appropriate psychological support tailored to different isolation situations is crucial. [ABSTRACT FROM AUTHOR]

ERA5 reanalysis data, precipitation data from China, and National Oceanic and Atmospheric Administration (NOAA) monthly sea surface temperature (SST) data are used to analyse the impact of the meridional position of the East Asian subtropical jet (EASJ) on summer precipitation in China and its correlation with Atlantic SST. The results indicate that when the EASJ significantly shifts northward, the western North Pacific subtropical high (WNPSH) weakens with an eastward displacement. Upper‐level convergence and moisture divergence, corresponding to descending motion, lead to decreased precipitation in the Yangtze River Valley (YRV). Meanwhile, upper‐level divergence occurs over South China (SC), the Hexi Corridor (HC), and Northeast China (NEC), where moisture converges and ascends, favouring an increase in precipitation. Conversely, when the EASJ undergoes a significant southward shift, the WNPSH strengthens and expands westward. Opposing atmospheric circulation patterns in these four regions result in reversed precipitation anomalies compared with those observed when the jet shifts northward. The meridional position of the EASJ is closely related to the summer subtropical Atlantic SST. The positive (negative) SST anomaly (SSTA) over the subtropical Atlantic induces negative (positive) geopotential height anomaly in the upper troposphere over the North Atlantic by modulating the atmospheric meridional circulation. Geopotential height anomalies trigger eastward‐propagating Rossby waves, generating anomalous cyclones and anticyclones over East Asia. These anomalous cyclones and anticyclones lead to zonal wind anomalies, which alter the strength of the westerlies on both sides of the climatological jet axis, thereby changing the jet's meridional position. Additionally, the difference in the propagation direction of wave activity flux between positive and negative SSTA alters the distribution of wave energy convergence and divergence in the EASJ region, further affecting the intensity of the average westerly winds on both sides of the climatological jet axis, ultimately producing the changes in the meridional position of the EASJ. [ABSTRACT FROM AUTHOR]

Oyster peptide (OP) and Pfaffia glomerata extract (PGE) were used as raw materials. The optimal formulation of the pressed candy (PC) was optimized by one‐way experiment and D‐optimal mixture experiment design, and animal experiment was used to evaluate the effect of PC on male sexual dysfunction. The results showed that PC intervention significantly improved the sexual behavior of male mice with sexual dysfunction, including a significant shortening of the mount latency (ML) and intromission latency, and a significant increase in the mount frequency (MF) and intromission frequency (IF). At the same time, the concentrations of serum testosterone (T) and luteinizing hormone (LH) in mice were restored, and the erectile parameters and pathological changes of penile tissue were improved. Further studies found that PC intervention increased the activities of superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GSH‐Px) and reduced the content of malondialdehyde (MDA) in testicular tissue. In addition, PC intervention improved testicular tissue morphology. In conclusion, the obtained PC has good taste quality, and the relevant quality indicators are qualified. It has a good ameliorative effect on male sexual dysfunction and may be a potential dietary supplement. [ABSTRACT FROM AUTHOR]

Early and differential diagnosis of sepsis is essential to avoid unnecessary antibiotic use and further reduce patient morbidity and mortality. Here, we aimed to identify predictors of sepsis and advance a machine-learning strategy to predict sepsis-induced respiratory tract infection (RTI). Patients with sepsis and RTI were selected via retrospective analysis, and essential population characteristics and laboratory parameters were recorded. To improve the performance of the primary model and avoid over-fitting, a recursive feature elimination with cross-validation (RFECV) strategy was used to screen the optimal subset of biomarkers and construct nine machine-learning models based on this subset; the average accuracy, precision, recall, and F1-score were used for evaluation of the models. We identified 430 patients with sepsis and 686 patients with RTI. A total of 39 features were collected, with 23 features identified for initial model construction. Using the RFECV algorithm, we found that the XGBoost classifier, which only needed to include seven biomarkers, demonstrated the best performance among all prediction models, with an average accuracy of 89.24 ± 2.28, while the Ridge classifier, which included 11 biomarkers, had an average accuracy of only 83.87 ± 4.69. The remaining models had prediction accuracies greater than 88%. We developed nine models for predicting sepsis using a strategy that combined RFECV with machine learning. Among these models, the XGBoost classifier, which included seven biomarkers, showed the best performance and highest accuracy for predicting sepsis and may be a promising tool for the timely identification of sepsis. [ABSTRACT FROM AUTHOR]