DNA polymerase delta governs parental histone transfer to DNA replication lagging strand.

Chromatin replication is intricately intertwined with the recycling of parental histones to the newly duplicated DNA strands for faithful genetic and epigenetic inheritance. The transfer of parental histones occurs through two distinct pathways: leading strand deposition, mediated by the DNA polymerase ε subunits Dpb3/Dpb4, and lagging strand deposition, facilitated by the MCM helicase subunit Mcm2. However, the mechanism of the facilitation of Mcm2 transferring parental histones to the lagging strand while moving along the leading strand remains unclear. Here, we show that the deletion of Pol32, a nonessential subunit of major lagging-strand DNA polymerase δ, results in a predominant transfer of parental histone H3-H4 to the leading strand during replication. Biochemical analyses further demonstrate that Pol32 can bind histone H3-H4 both in vivo and in vitro. The interaction of Pol32 with parental histone H3-H4 is disrupted through the mutation of the histone H3-H4 binding domain within Mcm2. Our findings identify the DNA polymerase δ subunit Pol32 as a critical histone chaperone downstream of Mcm2, mediating the transfer of parental histones to the lagging strand during DNA replication.

Defective transfer of parental histone decreases frequency of homologous recombination by increasing free histone pools in budding yeast.

Recycling of parental histones is an important step in epigenetic inheritance. During DNA replication, DNA polymerase epsilon subunit DPB3/DPB4 and DNA replication helicase subunit MCM2 are involved in the transfer of parental histones to the leading and lagging strands, respectively. Single Dpb3 deletion (dpb3Δ) or Mcm2 mutation (mcm2-3A), which each disrupts one parental histone transfer pathway, leads to the other's predominance. However, the biological impact of the two histone transfer pathways on chromatin structure and DNA repair remains elusive. In this study, we used budding yeast Saccharomyces cerevisiae to determine the genetic and epigenetic outcomes from disruption of parental histone H3-H4 tetramer transfer. We found that a dpb3Δ mcm2-3A double mutant did not exhibit the asymmetric parental histone patterns caused by a single dpb3Δ or mcm2-3A mutation, suggesting that the processes by which parental histones are transferred to the leading and lagging strands are independent. Surprisingly, the frequency of homologous recombination was significantly lower in dpb3Δ, mcm2-3A and dpb3Δ mcm2-3A mutants, likely due to the elevated levels of free histones detected in the mutant cells. Together, these findings indicate that proper transfer of parental histones during DNA replication is essential for maintaining chromatin structure and that lower homologous recombination activity due to parental histone transfer defects is detrimental to cells.

Challenges of COVID-19 Case Forecasting in the US, 2020-2021.

During the COVID-19 pandemic, forecasting COVID-19 trends to support planning and response was a priority for scientists and decision makers alike. In the United States, COVID-19 forecasting was coordinated by a large group of universities, companies, and government entities led by the Centers for Disease Control and Prevention and the US COVID-19 Forecast Hub (https://covid19forecasthub.org). We evaluated approximately 9.7 million forecasts of weekly state-level COVID-19 cases for predictions 1-4 weeks into the future submitted by 24 teams from August 2020 to December 2021. We assessed coverage of central prediction intervals and weighted interval scores (WIS), adjusting for missing forecasts relative to a baseline forecast, and used a Gaussian generalized estimating equation (GEE) model to evaluate differences in skill across epidemic phases that were defined by the effective reproduction number. Overall, we found high variation in skill across individual models, with ensemble-based forecasts outperforming other approaches. Forecast skill relative to the baseline was generally higher for larger jurisdictions (e.g., states compared to counties). Over time, forecasts generally performed worst in periods of rapid changes in reported cases (either in increasing or decreasing epidemic phases) with 95% prediction interval coverage dropping below 50% during the growth phases of the winter 2020, Delta, and Omicron waves. Ideally, case forecasts could serve as a leading indicator of changes in transmission dynamics. However, while most COVID-19 case forecasts outperformed a naïve baseline model, even the most accurate case forecasts were unreliable in key phases. Further research could improve forecasts of leading indicators, like COVID-19 cases, by leveraging additional real-time data, addressing performance across phases, improving the characterization of forecast confidence, and ensuring that forecasts were coherent across spatial scales. In the meantime, it is critical for forecast users to appreciate current limitations and use a broad set of indicators to inform pandemic-related decision making.

Metabolomics assisted by transcriptomics analysis to reveal metabolic characteristics and potential biomarkers associated with treatment response of neoadjuvant therapy with TCbHP regimen in HER2 + breast cancer.

BACKGROUND: This study aimed to explore potential indicators associated with the neoadjuvant efficacy of TCbHP regimen (taxane, carboplatin, trastuzumab, and pertuzumab) in HER2 + breast cancer (BrCa) patients. METHODS: A total of 120 plasma samples from 40 patients with HER2 + BrCa were prospectively collected at three treatment times of neoadjuvant therapy (NAT) with TCbHP regimen. Serum metabolites were analyzed based on LC-MS and GC-MS data. Random forest was used to establish predictive models based on pre-therapeutic differentially expressed metabolites. Time series analysis was used to obtain potential monitors for treatment response. Transcriptome analysis was performed in nine available pre­therapeutic specimens of core needle biopsies. Integrated analyses of metabolomics and transcriptomics were also performed in these nine patients. qRT-PCR was used to detect altered genes in trastuzumab-sensitive and trastuzumab-resistant cell lines. RESULTS: Twenty-one patients achieved pCR, and 19 patients achieved non-pCR. There were significant differences in plasma metabolic profiles before and during treatment. A total of 100 differential metabolites were identified between pCR patients and non-pCR patients at baseline; these metabolites were markedly enriched in 40 metabolic pathways. The area under the curve (AUC) values for discriminating the pCR and non-PCR groups from the NAT of the single potential metabolite [sophorose, N-(2-acetamido) iminodiacetic acid, taurine and 6-hydroxy-2-aminohexanoic acid] or combined panel of these metabolites were greater than 0.910. Eighteen metabolites exhibited potential for monitoring efficacy. Several validated genes might be associated with trastuzumab resistance. Thirty-nine altered pathways were found to be abnormally expressed at both the transcriptional and metabolic levels. CONCLUSION: Serum-metabolomics could be used as a powerful tool for exploring informative biomarkers for predicting or monitoring treatment efficacy. Metabolomics integrated with transcriptomics analysis could assist in obtaining new insights into biochemical pathophysiology and might facilitate the development of new treatment targets for insensitive patients.

Psychological stress induces hair regenerative disorders through corticotropin-releasing hormone-mediated autophagy inhibition.

Psychosocial stress is increasing, causing a growing number of people to suffer from hair loss. Stress-related corticotropin-releasing hormone (CRH) is associated with hair loss, but the mechanism by which hair follicles respond to stress and CRH remain poorly understood. The aim of the study is to elucidate the association between CRH and stress-related hair regenerative disorders, and reveal the potential pathological mechanisms. A chronic unpredictable stress mouse model and a chronic social defeat stress mouse model were used to examine the role of CRH and stress-related hair regrowth. Chronic unpredictable stress and chronic social defeat stress increased the expression of CRH and CRH receptors (CRHRs), and contributed to the onset of hair-cycle abnormalities. Psychoemotional stress and stress-related CRH blocked hair follicle regrowth, which could be restored by astressin, a CRHR antagonist. Long-term exposure to either chronic unpredictable stress or CRH induced a decrease in autophagy, which could be partially rescued by astressin. Activating CRHR, by stress or CRH administration, decreased autophagy via the mTOR-ULK1 signaling pathway to mediate hair regenerative disorders, which could be partially reversed through enhancing autophagy by administration of brefeldin A. These findings indicate that CRH-mediated autophagy inhibition play an important role in stress-induced hair regenerative disorders. CRH regulates the local hypothalamic-pituitary-adrenal axis of hair follicles, but also plays an independent pathogenic role in stress-related hair regenerative disorders through CRH-mediated autophagy inhibition. This work contributes to the present understanding of hair loss and suggests that enhancing autophagy may have a therapeutic effect on stress-induced hair loss.

Simultaneous Efficient Photocatalytic Hydrogen Evolution and Degradation of Dye Wastewater without Cocatalysts and Sacrificial Agents Based on g-C3N5 and Hybridized Ni-MOF Derivative-CdS-DETA.

Inspired by energy conversion and waste reuse, hybridized Ni-MOF derivative-CdS-DETA/g-C3N5, a type-II heterojunction photocatalyst, is synthesized by a hydrothermal method for simultaneous and highly efficient photocatalytic degradation and hydrogen evolution in dye wastewater. Without the addition of cocatalysts and sacrificial agents, the optimal MOF-CD(2)/CN5 (i.e. Ni-MOF derivative-CdS-DETA (20 wt.%)/g-C3N5) exhibit good bifunctional catalytic activity, with a H2 evolution rate of 2974.4 µmol g-1 h-1 during the degradation of rhodamine B (RhB), and a removal rate of 99.97% for RhB. In the process of H2-evolution-only, triethanolamine is used as a sacrificial agent, exhibiting a high H2 evolution rate (19663.1 µmol g-1 h-1) in the absence of a cocatalyst, and outperforming most similar related materials (such as MOF/g-C3N5, MOF-CdS, CdS/g-C3N5). With the help of type-II heterojunction, holes are scavenged for the oxidative degradation of RhB, and electrons are used in the decomposition of water for H2 evolution during illumination. This work opens a new path for photocatalysts with dual functions of simultaneous efficient degradation and hydrogen evolution.

Design and Realization of Visual and Contact-Type Fast Charging Power Source.

Charging power supplies with both fast and visualization functions have a wide range of applications in the information and new energy industries. In this paper, the visualized and contact-type fast charging power supply based on WO3 film and Zn sheet is presented, and the prototype devices are fabricated. Different with the charging method of conventional batteries, charging is achieved by a Zn sheet contacting with a WO3 film moistened with water, resulting in a rapid discoloration of WO3. Theoretical investigation indicates that the interaction between Zn sheet and water molecules is the primary cause of the color change in the WO3 film. The WO3 film completes the colouring state within 10 s in the presence of Zn sheet and water, and the open-circuit voltage of the device is 0.7 V, which can be used to drive various electronics by series-parallel connection. This research introduces a novel method to induce colouring of WO3 films and proposes a fast charging mode different from traditional power sources. It provides valuable insights for the future development of fast charging in the field of electrical energy.

Self-amplified activatable nanoprodrugs for enhanced chemodynamic/chemo combination therapy.

Chemodynamic therapy (CDT) has gained increasing attention by virtue of its high tumor specificity and low side effect. However, the low concentration of hydrogen peroxide (H2O2) in the tumor site suppresses the therapeutic efficacy of CDT. To improve the efficacy, introducing other kind of therapeutic modality is a feasible choice. Herein, we develop a self-amplified activatable nanomedicine (PCPTH NP) for chemodynamic/chemo combination therapy. PCPTH NP is composed of a H2O2-activatable amphiphilic prodrug PEG-PCPT and hemin. Upon addition of H2O2, the oxalate linkers within PCPTH NP are cleaved, which makes the simultaneous release of CPT and hemin. The released CPT can not only kill cancer cells but also upregulate the intracellular reactive oxygen species (ROS) level. The elevated ROS level may accelerate the release of drugs and enhance the CDT efficacy. PCPTH NP shows a H2O2concentration dependent release profile, and can effectively catalyze H2O2into hydroxyl radical (·OH) under acidic condition. Compared with PCPT NP without hemin, PCPTH NP has better anticancer efficacy bothin vitroandin vivowith high biosafety. Thus, our study provides an effective approach to improve the CDT efficacy with high tumor specificity.

Green space and its types can attenuate the associations of PM2.5 and its components with prediabetes and diabetes-- a multicenter cross-sectional study from eastern China.

BACKGROUND: The effect of fine particulate matter (PM2.5) components on prediabetes and diabetes is of concern, but the evidence is limited and the specific role of different green space types remains unclear. This study aims to investigate the relationship of PM2.5 and its components with prediabetes and diabetes as well as the potential health benefits of different types and combinations of green spaces. METHODS: A multicenter cross-sectional study was conducted in eastern China by using a multi-stage random sampling method. Health screening and questionnaires for 98,091 participants were performed during 2017-2020. PM2.5 and its five components were estimated by the inverse distance weighted method, and green space was reflected by the Normalized Difference Vegetation Index (NDVI), percentages of tree or grass cover. Multivariate logistic regression and quantile g-computing were used to explore the associations of PM2.5 and five components with prediabetes and diabetes and to elucidate the potential moderating role of green space and corresponding type combinations in these associations. RESULTS: Each interquartile range (IQR) increment of PM2.5 was associated with both prediabetes (odds ratio [OR]: 1.15, 95%CI [confidence interval]: 1.10-1.20) and diabetes (OR: 1.18, 95% CI: 1.11-1.25), respectively. All five components of PM2.5 were related to prediabetes and diabetes. The ORs of PM2.5 on diabetes were 1.49 (1.35-1.63) in the low tree group and 0.90 (0.82-0.98) in the high tree group, respectively. In the high tree-high grass group, the harmful impacts of PM2.5 and five components were significantly lower than in the other groups. CONCLUSION: Our study suggested that PM2.5 and its components were associated with the increased risk of prediabetes and diabetes, which could be diminished by green space. Furthermore, the coexistence of high levels of tree and grass cover provided greater benefits. These findings had critical implications for diabetes prevention and green space-based planning for healthy city.

Desipramine ameliorates fine particulate matter-induced hepatic insulin resistance by modulating the ceramide metabolism in mice.

Recent research has highlighted a correlation between exposure to ambient fine particulate matter (PM2.5) and the development of systemic insulin resistance (IR) along with an elevated risk of diabetes. Ceramide has emerged as one of the pathogenic mechanisms contributing to IR. The inhibition of acid sphingomyelinase (ASMase) activity by desipramine (DES) has been shown to effectively reduce ceramide levels. In the present study, 24 female C57BL/6 N mice were randomized into one of the four groups: the filtered air exposure (FA) group, the concentrated PM2.5 exposure (PM) group, the concentrated PM2.5 treated with low-dose DES (DL) group, and the concentrated PM2.5 treated with high-dose DES (DH) group. The PM, DL and DH groups were exposed to PM2.5 for an 8-week period within a whole-body exposure system. The study encompassed extensive examinations of glucose homeostasis, liver lipid profile, ceramide pathway, and insulin signaling pathway. Our results demonstrated that PM2.5 exposure caused impaired glucose tolerance, elevated ceramide levels, increased phosphorylation PP2A, reduced Akt phosphorylation, and hindered GLUT2 expression. Remarkably, DES administration mitigated PM2.5-induced IR by effectively lowering ceramide levels. In conclusion, the reduction of ceramide levels by DES may be a promising therapeutic strategy for coping PM2.5-induced IR.

An intelligent grasper to provide real-time force feedback to shorten the learning curve in laparoscopic training.

BACKGROUND: A lack of force feedback in laparoscopic surgery often leads to a steep learning curve to the novices and traditional training system equipped with force feedback need a high educational cost. This study aimed to use a laparoscopic grasper providing force feedback in laparoscopic training which can assist in controlling of gripping forces and improve the learning processing of the novices. METHODS: Firstly, we conducted a pre-experiment to verify the role of force feedback in gripping operations and establish the safe gripping force threshold for the tasks. Following this, we proceeded with a four-week training program. Unlike the novices without feedback (Group A2), the novices receiving feedback (Group B2) underwent training that included force feedback. Finally, we completed a follow-up period without providing force feedback to assess the training effect under different conditions. Real-time force parameters were recorded and compared. RESULTS: In the pre-experiment, we set the gripping force threshold for the tasks based on the experienced surgeons' performance. This is reasonable as the experienced surgeons have obtained adequate skill of handling grasper. The thresholds for task 1, 2, and 3 were set as 0.731 N, 1.203 N and 0.938 N, respectively. With force feedback, the gripping force applied by the novices with feedback (Group B1) was lower than that of the novices without feedback (Group A1) (p < 0.005). During the training period, the Group B2 takes 6 trails to achieve gripping force of 0.635 N, which is lower than the threshold line, whereas the Group A2 needs 11 trails, meaning that the learning curve of Group B2 was significantly shorter than that of Group A2. Additionally, during the follow-up period, there was no significant decline in force learning, and Group B2 demonstrated better control of gripping operations. The training with force feedback received positive evaluations. CONCLUSION: Our study shows that using a grasper providing force feedback in laparoscopic training can help to control the gripping force and shorten the learning curve. It is anticipated that the laparoscopic grasper equipped with FBG sensor is promising to provide force feedback during laparoscopic training, which ultimately shows great potential in laparoscopic surgery.

Gas Outburst Warning Method in Driving Faces: Enhanced Methodology through Optuna Optimization, Adaptive Normalization, and Transformer Framework.

Addressing common challenges such as limited indicators, poor adaptability, and imprecise modeling in gas pre-warning systems for driving faces, this study proposes a hybrid predictive and pre-warning model grounded in time-series analysis. The aim is to tackle the effects of broad application across diverse mines and insufficient data on warning accuracy. Firstly, we introduce an adaptive normalization (AN) model for standardizing gas sequence data, prioritizing recent information to better capture the time-series characteristics of gas readings. Coupled with the Gated Recurrent Unit (GRU) model, AN demonstrates superior forecasting performance compared to other standardization techniques. Next, Ensemble Empirical Mode Decomposition (EEMD) is used for feature extraction, guiding the selection of the Variational Mode Decomposition (VMD) order. Minimal decomposition errors validate the efficacy of this approach. Furthermore, enhancements to the transformer framework are made to manage non-linearities, overcome gradient vanishing, and effectively analyze long time-series sequences. To boost versatility across different mining scenarios, the Optuna framework facilitates multiparameter optimization, with xgbRegressor employed for accurate error assessment. Predictive outputs are benchmarked against Recurrent Neural Networks (RNN), GRU, Long Short-Term Memory (LSTM), and Bidirectional LSTM (BiLSTM), where the hybrid model achieves an R-squared value of 0.980975 and a Mean Absolute Error (MAE) of 0.000149, highlighting its top performance. To cope with data scarcity, bootstrapping is applied to estimate the confidence intervals of the hybrid model. Dimensional analysis aids in creating real-time, relative gas emission metrics, while persistent anomaly detection monitors sudden time-series spikes, enabling unsupervised early alerts for gas bursts. This model demonstrates strong predictive prowess and effective pre-warning capabilities, offering technological reinforcement for advancing intelligent coal mine operations.

CRISPR Screen Identifies the RNA-Binding Protein Eef1a1 as a Key Regulator of Myogenesis.

Skeletal muscle myogenesis hinges on gene regulation, meticulously orchestrated by molecular mechanisms. While the roles of transcription factors and non-coding RNAs in myogenesis are widely known, the contribution of RNA-binding proteins (RBPs) has remained unclear until now. Therefore, to investigate the functions of post-transcriptional regulators in myogenesis and uncover new functional RBPs regulating myogenesis, we employed CRISPR high-throughput RBP-KO (RBP-wide knockout) library screening. Through this approach, we successfully identified Eef1a1 as a novel regulatory factor in myogenesis. Using CRISPR knockout (CRISPRko) and CRISPR interference (CRISPRi) technologies, we successfully established cellular models for both CRISPRko and CRISPRi. Our findings demonstrated that Eef1a1 plays a crucial role in promoting proliferation in C2C12 myoblasts. Through siRNA inhibition and overexpression methods, we further elucidated the involvement of Eef1a1 in promoting proliferation and suppressing differentiation processes. RIP (RNA immunoprecipitation), miRNA pull-down, and Dual-luciferase reporter assays confirmed that miR-133a-3p targets Eef1a1. Co-transfection experiments indicated that miR-133a-3p can rescue the effect of Eef1a1 on C2C12 myoblasts. In summary, our study utilized CRISPR library high-throughput screening to unveil a novel RBP, Eef1a1, involved in regulating myogenesis. Eef1a1 promotes the proliferation of myoblasts while inhibiting the differentiation process. Additionally, it acts as an antagonist to miR-133a-3p, thus modulating the process of myogenesis.

Metabolic Profile and Lipid Metabolism Phenotype in Mice with Conditional Deletion of Hepatic BMAL1.

The disruption of circadian rhythms (CRs) has been linked to metabolic disorders, yet the role of hepatic BMAL1, a key circadian regulator, in the whole-body metabolism and the associated lipid metabolic phenotype in the liver remains unclear. Bmal1 floxed (Bmal1f/f) and hepatocyte-specific Bmal1 knockout (Bmal1hep-/-) C57BL/6J mice underwent a regular feeding regimen. Hepatic CR, lipid content, mitochondrial function, and systemic metabolism were assessed at zeitgeber time (ZT) 0 and ZT12. Relevant molecules were examined to elucidate the metabolic phenotype. Hepatocyte-specific knockout of Bmal1 disrupted the expression of rhythmic genes in the liver. Bmal1hep-/- mice exhibited decreased hepatic TG content at ZT0, primarily due to enhanced lipolysis, reduced lipogenesis, and diminished lipid uptake. The ß-oxidation function of liver mitochondria decreased at both ZT0 and ZT12. Our findings on the metabolic profile and associated hepatic lipid metabolism in the absence of Bmal1 in hepatocytes provides new insights into metabolic syndromes from the perspective of liver CR disturbances.

Effects of Cascade Reservoirs on Spatiotemporal Dynamics of the Sedimentary Bacterial Community: Co-occurrence Patterns, Assembly Mechanisms, and Potential Functions.

Dam construction as an important anthropogenic activity significantly influences ecological processes in altered freshwater bodies. However, the effects of multiple cascade dams on microbial communities have been largely overlooked. In this study, the spatiotemporal distribution, co-occurrence relationships, assembly mechanisms, and functional profiles of sedimentary bacterial communities were systematically investigated in 12 cascade reservoirs across two typical karst basins in southwest China over four seasons. A significant spatiotemporal heterogeneity was observed in bacterial abundance and diversity. Co-occurrence patterns in the Wujiang Basin exhibited greater edge counts, graph density, average degree, robustness, and reduced modularity, suggesting more intimate and stronger ecological interactions among species than in the Pearl River Basin. Furthermore, Armatimonadota and Desulfobacterota, identified as keystone species, occupied a more prominent niche than the dominant species. A notable distance-decay relationship between geographical distance and community dissimilarities was identified in the Pearl River Basin. Importantly, in the Wujiang Basin, water temperature emerged as the primary seasonal variable steering the deterministic process of bacterial communities, whereas 58.5% of the explained community variance in the neutral community model (NCM) indicated that stochastic processes governed community assembly in the Pearl River Basin. Additionally, principal component analysis (PCA) revealed more pronounced seasonal dynamics in nitrogen functional compositions than spatial variation in the Wujiang Basin. Redundancy analysis (RDA) results indicated that in the Wujiang Basin, environmental factors and in Pearl River Basin, geographical distance, reservoir age, and hydraulic retention time (HRT), respectively, influenced the abundance of nitrogen-related genes. Notably, these findings offer novel insights: building multiple cascade reservoirs could lead to a cascading decrease in biodiversity and resilience in the river-reservoir ecosystem.

MAP3K4 kinase action and dual role in cancer.

It is commonly known that the MAPK pathway is involved in translating environmental inputs, regulating downstream reactions, and maintaining the intrinsic dynamic balance. Numerous essential elements and regulatory processes are included in this pathway, which are essential to its functionality. Among these, MAP3K4, a member of the serine/threonine kinases family, plays vital roles throughout the organism's life cycle, including the regulation of apoptosis and autophagy. Moreover, MAP3K4 can interact with key partners like GADD45, which affects organism's growth and development. Notably, MAP3K4 functions as both a tumor promotor and suppressor, being activated by a variety of factors and triggering diverse downstream pathways that differently influence cancer progression. The aim of this study is to provide a brief overview of physiological functions of MAP3K4 and shed light on its contradictory roles in tumorigenesis.

Facilitating the coping and development of college students with mental disorders: a positive clinical psychology approach.

In serving college students with mental disorders, on-campus mental health professionals have been lacking integrative theoretical frameworks to guide their missions of prevention, remedy, and development facilitation. In the current paper, we propose the positive clinical psychology as a theoretically and practically valuable framework for these missions by narratively reviewing the preventive, remedial, and developmental mechanisms derived from the theory and summarizing the most recent empirical evidence that supports each mechanism. We further discuss why and how these mechanisms and findings can be applied to on-campus mental health services to facilitate the resilience and optimal development of college students with mental disorders. Particularly, the use of resilience-focused and strength-based intervention strategies are promoted for services.

A two-stage fine-tuning method for low-resource cross-lingual summarization.

Cross-lingual summarization (CLS) is the task of condensing lengthy source language text into a concise summary in a target language. This presents a dual challenge, demanding both cross-language semantic understanding (i.e., semantic alignment) and effective information compression capabilities. Traditionally, researchers have tackled these challenges using two types of methods: pipeline methods (e.g., translate-then-summarize) and end-to-end methods. The former is intuitive but prone to error propagation, particularly for low-resource languages. The later has shown an impressive performance, due to multilingual pre-trained models (mPTMs). However, mPTMs (e.g., mBART) are primarily trained on resource-rich languages, thereby limiting their semantic alignment capabilities for low-resource languages. To address these issues, this paper integrates the intuitiveness of pipeline methods and the effectiveness of mPTMs, and then proposes a two-stage fine-tuning method for low-resource cross-lingual summarization (TFLCLS). In the first stage, by recognizing the deficiency in the semantic alignment for low-resource languages in mPTMs, a semantic alignment fine-tuning method is employed to enhance the mPTMs' understanding of such languages. In the second stage, while considering that mPTMs are not originally tailored for information compression and CLS demands the model to simultaneously align and compress, an adaptive joint fine-tuning method is introduced. This method further enhances the semantic alignment and information compression abilities of mPTMs that were trained in the first stage. To evaluate the performance of TFLCLS, a low-resource CLS dataset, named Vi2ZhLow, is constructed from scratch; moreover, two additional low-resource CLS datasets, En2ZhLow and Zh2EnLow, are synthesized from widely used large-scale CLS datasets. Experimental results show that TFCLS outperforms state-of-the-art methods by 18.88%, 12.71% and 16.91% in ROUGE-2 on the three datasets, respectively, even when limited with only 5,000 training samples.

Pan-cancer prognostic model and immune microenvironment analysis of natural killer cell-related genes.

Background: Natural killer (NK) cells play a significant role in antitumor immunity and are closely related to tumor prognosis and recurrence. NK cell-based tumor immunotherapy, including immune checkpoint inhibition and CAR-engineered NK cells, is a promising area of research. However, there is a need for better NK cell-related models and associated biomarkers. Methods: The sequences of NK cell-related genes were obtained from the published NK cell CRISPR/Cas9 library data, and the common genes were selected as NK cell-related genes. The RNA sequencing (RNA-seq) and clinical data of 32 solid tumors from The Cancer Genome Atlas (TCGA) were downloaded from the UCSC Xena database, and the RNA-seq data of normal samples were downloaded from the Genotype-Tissue Expression (GTEx) database. The differentially expressed NK cell-related genes (DENKGs) between the tumor and normal samples were analyzed. The DENKGs related to the prognosis of solid tumors were selected via univariate Cox analysis, and 32 kinds of solid tumor prognostic models were constructed using least absolute shrinkage and selection operator (LASSO) and multivariate Cox analysis. Survival, receiver operating characteristic (ROC), and independent prognostic analyses were employed to test the effectiveness of the model, along with a nomogram model and prediction curve. Differences in the immune pathways and microenvironment cells were analyzed between the high- and low-risk groups identified by the model. Results: We constructed a pan-cancer prognostic model with 63 NK cell-related genes and further identified DEPDC1 and ASPM as potentially offering new directions in tumor research by literature screening. Conclusions: In this study, 63 prognostic solid tumor markers were investigated using NK cell-related genes, and for the first time, a pan-cancer prognostic model was constructed to analyze their role in the immune microenvironment, which may contribute new insights into tumor research.

Psychological health status of Chinese university students: based on Psychological Resilience Dynamic System Model.

Introduction: The mental health of unverisity students is influenced by diverse factorsis multifaceted, requiring further investigation to evaluate its current status and determinants. The present study aims to address this gap by targeting Chinese university students and employing the Psychological Resilience Dynamic System model. Through a questionnaire survey, this research endeavors to explore the mental health status and influencing factors. Ultimately, the findings of this study aim to provide a theoretical basis and tailored practical guidance for the development of mental health intervention strategies for university students. Methods: Based on the Psychological Resilience Dynamic System Model, the mental health status of 3,390 Chinese university students from 15 universities was empirically investigated with the principle of stratified sampling and the geographical distribution and disciplinary diversity of universities. The questionnaires used included Kessler psychological distress scale, psychological resilience scale,positive psychological capital scale, family hardiness index and social support scale. Among the participants, 47.85% were male and 52.15% were female. Regarding the origin, 42.89% of the students were from rural areas, while 57.11% were from urban areas. Results: Key findings unveil: (1) A prevalence of 24.54% in students has suboptimal mental health, with 18.70 and 5.84%, respectively, representing those with poor and relatively poor mental health conditions; (2) A noteworthy negative correlation (p < 0.01) between mental health scores of university students and nine pivotal factors, including psychological resilience, self-efficacy, optimism, hope, resilience, family resilience, objective support, subjective support, and support utilization; (3) Eight factors, including grade, family economic status, psychological resilience, self-efficacy, optimism, family resilience, objective support, and support utilization, emerge as significant predictors of university students' mental health (p <0.001), collectively elucidating 57.9% of the total variance in mental health. Discussion: The aforementioned research results, indicate that the influencing factors on the mental health of university students encompass four main aspects. These include individual demographic factors such as grade and family economic status, positive psychological capital factors such as psychological resilience, self-efficacy, optimism, hope, and resilience, family resilience factors including responsibility, control, and challenge, and societal support factors including objective support, subjective support, and support utilization. Based on this, this paper focuses on four recommendations: giving full play to the leading role of universities in mental health education and stress intervention, strengthening the educational power of positive family ideals and role modeling, building a support system for positive social atmosphere and psychological counseling, and improving the self-shaping ability of university students' psychological resilience and positive psychological capital. These recommendations aspire to better promote the mental health of university students and provide a strength reserve for psychological problem intervention.