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Self-directed learning (SDL) is a basic individual ability in modern society. It is of great value to explore SDL and its relationship to learners’ online learning effectiveness. This study explored the relationships among online learners’ personality traits (neuroticism and extraversion), SDL (SDL-approach and SDL-attitude), and perceived online learning ineffectiveness (POLI). A total of 668 high school students who had received online learning completed the survey. Results revealed that neuroticism negatively predicted SDL-approach and SDL-attitude, whereas extraversion was positively correlated with SDL-approach and SDL-attitude, and SDL-approach and SDL-attitude were negatively correlated with POLI. In addition, the correlation between personality traits and POLI was significantly mediated by the two types of SDL. The findings provide educators with empirical evidence and insights about improving students’ SDL and understanding the importance of personality traits in online learning.

Abstract Amino acid metabolism plays a pivotal role in tumor microenvironment, influencing various aspects of cancer progression. The metabolic reprogramming of amino acids in tumor cells is intricately linked to protein synthesis, nucleotide synthesis, modulation of signaling pathways, regulation of tumor cell metabolism, maintenance of oxidative stress homeostasis, and epigenetic modifications. Furthermore, the dysregulation of amino acid metabolism also impacts tumor microenvironment and tumor immunity. Amino acids can act as signaling molecules that modulate immune cell function and immune tolerance within the tumor microenvironment, reshaping the anti-tumor immune response and promoting immune evasion by cancer cells. Moreover, amino acid metabolism can influence the behavior of stromal cells, such as cancer-associated fibroblasts, regulate ECM remodeling and promote angiogenesis, thereby facilitating tumor growth and metastasis. Understanding the intricate interplay between amino acid metabolism and the tumor microenvironment is of crucial significance. Expanding our knowledge of the multifaceted roles of amino acid metabolism in tumor microenvironment holds significant promise for the development of more effective cancer therapies aimed at disrupting the metabolic dependencies of cancer cells and modulating the tumor microenvironment to enhance anti-tumor immune responses and inhibit tumor progression.

Abstract Friction as a fundamental physical phenomenon dominates nature and human civilization, among which the achievement of molecular rolling lubrication is desired to bring another breakthrough, like the macroscale design of wheel. Herein, an edge self-curling nanodeformation phenomenon of graphite nanosheets (GNSs) at cryogenic temperature is found, which is then used to promote the formation of graphite nanorollers in friction process towards molecular rolling lubrication. The observation of parallel nanorollers at the friction interface give the experimental evidence for the occurrence of molecular rolling lubrication, and the graphite exhibits abnormal lubrication performance in vacuum with ultra-low friction and wear at macroscale. The molecular rolling lubrication mechanism is elucidated from the electronic interaction perspective. Experiments and theoretical simulations indicate that the driving force of the self-curling is the uneven atomic shrinkage induced stress, and then the shear force promotes the intact nanoroller formation, while the constraint of atomic vibration decreases the dissipation of driving stress and favors the nanoroller formation therein. It will open up a new pathway for controlling friction at microscale and nanostructural manipulation.

Single-cell RNA sequencing (scRNA-seq) is a high-throughput sequencing technology that quantifies gene expression profiles of specific cell populations at the single-cell level, providing a foundation for studying cellular heterogeneity and patient pathological characteristics. It is effective for developmental, fertility, and disease studies. However, the cell-gene expression matrix of single-cell sequencing data is often sparse and contains numerous zero values. Some of the zero values derive from noise, where dropout noise has a large impact on downstream analysis. In this paper, we propose a method named scIALM for imputation recovery of sparse single-cell RNA data expression matrices, which employs the Inexact Augmented Lagrange Multiplier method to use sparse but clean (accurate) data to recover unknown entries in the matrix. We perform experimental analysis on four datasets, calling the expression matrix after Quality Control (QC) as the original matrix, and comparing the performance of scIALM with six other methods using mean squared error (MSE), mean absolute error (MAE), Pearson correlation coefficient (PCC), and cosine similarity (CS). Our results demonstrate that scIALM accurately recovers the original data of the matrix with an error of 10e-4, and the mean value of the four metrics reaches 4.5072 (MSE), 0.765 (MAE), 0.8701 (PCC), 0.8896 (CS). In addition, at 10%-50% random masking noise, scIALM is the least sensitive to the masking ratio. For downstream analysis, this study uses adjusted rand index (ARI) and normalized mutual information (NMI) to evaluate the clustering effect, and the results are improved on three datasets containing real cluster labels.

Abstract Background Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy with high probability of recurrence and distant metastasis. Liver metastasis is the predominant metastatic mode developed in most pancreatic cancer cases, which seriously affects the overall survival rate of patients. Abnormally activated endoplasmic reticulum stress and lipid metabolism reprogramming are closely related to tumor growth and metastasis. This study aims to construct a prognostic model based on endoplasmic reticulum stress and lipid metabolism for pancreatic cancer, and further explore its correlation with tumor immunity and the possibility of immunotherapy. Methods Transcriptomic and clinical data are acquired from TCGA, ICGC, and GEO databases. Potential prognostic genes were screened by consistent clustering and WGCNA methods, and the whole cohort was randomly divided into training and testing groups. The prognostic model was constructed by machine learning method in the training cohort and verified in the test, TCGA and ICGC cohorts. The clinical application of this model and its relationship with tumor immunity were analyzed, and the relationship between endoplasmic reticulum stress and intercellular communication was further explored. Results A total of 92 characteristic genes related to endoplasmic reticulum stress, lipid metabolism and liver metastasis were identified in pancreatic cancer. We established and validated a prognostic model for pancreatic cancer with 7 signatures, including ADH1C, APOE, RAP1GAP, NPC1L1, P4HB, SOD2, and TNFSF10. This model is considered to be an independent prognosticator and is a more accurate predictor of overall survival than age, gender, and stage. TIDE score was increased in high-risk group, while the infiltration levels of CD8+ T cells and M1 macrophages were decreased. The number and intensity of intercellular communication were increased in the high ER stress group. Conclusions We constructed and validated a novel prognostic model for pancreatic cancer, which can also be used as an instrumental variable to predict the prognosis and immune microenvironment. In addition, this study revealed the effect of ER stress on cell–cell communication in the tumor microenvironment.

The ecological relationships between tree growth and climate factors are important for the adaptation, growth prediction, and forest management of tree species against a background of global warming. Yet how these relationships for drought-sensitive conifer trees are changed and affected by elevation remains unclear. To investigate the effect of elevation on spruce tree growth–climate interactions, we collected a total of 1886 tree-ring cores (two cores per tree) from four spruce species, including Picea crassifolia Kom., Picea meyeri Rehd. et Wils., Picea schrenkiana Fisch. et Mey., and Picea wilsonii Mast., in 10 pure forests at a pair of high- and low-elevation alpine sites with the same slope across two aridity zones in China. We then constructed 20 stand tree-ring chronologies for the low- and high-elevation sites. Overall, the growth of spruce trees was more sensitive to drought variability at sites in the semi-arid zone whereas it was weakly limited by drought in the semi-humid zone. Further, spruce trees growing at high-elevation sites were sensitive to temperature unlike the stronger positive drought responses of those at low-elevation sites. In the latter half of the 20th century, the positive drought–growth relationships of spruce were enhanced at both high and low elevation across both aridity zones due to warming and increased drought intensity. Our dendrochronology-based findings suggest that spruce trees’ radial growth in stands at high elevation may have faced drought stress during three recent decades. Nevertheless, the low-elevation trees incurred stronger drought stress compared to the first half of the 20th century.

Abstract Ecosystem‐scale photosynthetic efficiency (EPE) is proposed as an effective indicator to quantify gross primary productivity (GPP), but how the coupling between EPE and GPP varies as vegetation resilience decreases has not been evaluated. Here, we quantified forest resilience with optimized Bayesian models. With the use of multisource satellite and modeling data, our study revealed that forests on the Loess Plateau and in the Qinba Mountains in China are experiencing rapid resilience loss and are already facing mortality warnings after 2010. Reductions in resilience also drove the marked decoupling of GPP from EPE. Notably, the decline in resilience was accompanied by a decrease in EPE in about 74% of the forests while GPP increased. The mechanism underlying this decoupling could be attributed to enhanced atmospheric water demand and soil water constraints. The dynamic relationships found here could help to improve forest mortality models and enhance photosynthesis‐based GPP evaluation.

Abstract Brown carbon (BrC) in China is of great interest to the regional and global climate due to its strong absorption of sunlight. However, the contribution of BrC to total carbonaceous aerosol light absorption and its direct radiative effects (DRE) in China remains largely uncertain. To better assess its climate impact in China, we develop an explicit BrC scheme and implement it in a global climate model, which includes optical parameters of primary BrC derived from local measurements, secondary BrC absorption, and a photobleaching parameterization of BrC. By comparing with multi‐type observational data, we find that with the implementation of this scheme, the model captures the seasonal variations of BrC light absorption well in China. The model estimates that BrC contributes 19% and 12% to the total light absorption of carbonaceous aerosol in China in winter and summer, resulting in 0.110 and 0.205 W m−2 of DRE, respectively.

Abstract Numerous Earth system models exhibit excessive aerosol effective forcing at the top of the atmosphere (TOA), including the Department of Energy's Energy Exascale Earth System Model (E3SM). Here, in the context of the E3SM version 3 effort, the predicted particle property (P3) stratiform cloud microphysics scheme and an enhanced deep convection parameterization suite (ZM_plus) are implemented into E3SM. The ZM_plus includes a convective cloud microphysics scheme, a multi‐scale coherent structure parameterization for mesoscale convective systems, and a revised cloud base mass flux formulation considering impacts of the large‐scale environment. The P3 scheme improved cloud and radiation particularly over the Northern Hemisphere and the frequency of heavy precipitation over the tropics, and the ZM_plus improved clouds in the tropics. P3 decreases aerosol effective forcing by 0.15 W m−2, while the ZM_plus increases it by 0.27 W m−2, resulting from excessive direct (0.31 W m−2) and indirect forcing (−1.79 W m−2). The excessive aerosol forcings are due to aerosol overestimation associated with insufficient aerosol wet removal. By improving the physical treatments in the aerosol wet removal, we effectively mitigate anthropogenic aerosol overestimation and thus attenuate direct (0.09 W m−2) and indirect aerosol forcing (−1.52 W m−2). Adjustment to primary organic matter hygroscopicity reduces direct and indirect forcing to more reasonable values: −0.13 W m−2 and −1.31 W m−2, respectively. On climatology, improved aerosol treatments mitigate overestimation of aerosol optical depth.

Small-molecule prodrug nanoassembly technology with a unique advantage in off-target toxicity reduction has been widely used for antitumor drug delivery. However, prodrug activation remains a rate-limiting step for exerting therapeutic actions, which requires to quickly reach the minimum valid concentrations of free drugs. Fortunately, we find that a natural compound (BL-193) selectively improves the chemotherapy sensitivity of breast cancer cells to podophyllotoxin (PPT) at ineffective dose concentrations. Based on this, we propose to combine prodrug nanoassembly with chemotherapy sensitization to fully unleash the chemotherapeutic potential of PPT. Specifically, a redox-sensitive prodrug (PSSF) of PPT is synthesized by coupling 9-fluorenyl-methanol (Fmoc-OH) with PPT linked via disulfide bond. Intriguingly, PSSF with a π-conjugated structure readily co-assembles with BL-193 into stable nanoassembly. Significantly, BL-193 serves as an excellent chemosensitizer that creates an ultra-low-dose chemotherapeutic window for PPT. Moreover, prodrug design and precise hybrid nanoassembly well manage off-target toxicity. As expected, such a BL-193-empowered prodrug nanoassembly elicits potent antitumor responses. This study offers a novel paradigm to magnify chemotherapy efficacy-toxicity benefits.

Background: This research aimed to create a predictive model and an innovative risk classification system for patients with gallbladder cancer who undergo radical surgery. Methods: A cohort of 1387 patients diagnosed with gallbladder cancer was selected from the SEER database. The researchers devised a prognostic tool known as a nomogram, which was subjected to assessment and fine-tuning using various statistical measures such as the concordance index (C-index), receiver operating characteristic (ROC) curve, and calibration curve, decision curve analysis (DCA), and risk stratification were included in the catalog of comparisons. An external validation set comprising 93 patients from Nanchong Central Hospital was gathered for evaluation purposes. Results: The nomogram effectively incorporated seven variables and demonstrated satisfactory discriminatory ability, as evidenced by the C-index (training cohort: 0.737, validation cohort: 0.730) and time-dependent AUC (>0.7). Additionally, calibration plots confirmed the excellent alignment between the nomogram and actual observations. Our investigation unveiled NRI scores of 0.79, 0.81, and 0.81 in the training group, while the validation group exhibited NRI values of 0.82, 0.77, and 0.78. Additionally, when evaluating CSS at three-, six-, and nine-year intervals using DCA curves, our established nomograms demonstrated significantly improved performance compared to the old model (P

IntroductionFusarium wilt (FW) caused by Fusarium oxysporum f. sp. cucumerinum (Foc) is a destructive soil-borne disease in cucumber (Cucumis sativus. L). However, there remains limited knowledge on the molecular mechanisms underlying FW resistance-mediated defense responses in cucumber.MethodsIn this study, metabolome and transcriptome profiling were carried out for two FW resistant (NR) and susceptible (NS), near isogenic lines (NILs) before and after Foc inoculation. NILs have shown consistent and stable resistance in multiple resistance tests conducted in the greenhouse and in the laboratory. A widely targeted metabolomic analysis identified differentially accumulated metabolites (DAMs) with significantly greater NR accumulation in response to Foc infection, including many phenolic acid and flavonoid compounds from the flavonoid biosynthesis pathway.ResultsTranscriptome analysis identified differentially expressed genes (DEGs) between the NILs upon Foc inoculation including genes for secondary metabolite biosynthesis and transcription factor genes regulating the flavonoid biosynthesis pathway. Joint analysis of the metabolomic and transcriptomic data identified DAMs and DEGs closely associated with the biosynthesis of phenolic acid and flavonoid DAMs. The association of these compounds with NR-conferred FW resistance was exemplified by in vivo assays. These assays found two phenolic acid compounds, bis (2-ethylhexyl) phthalate and diisooctyl phthalate, as well as the flavonoid compound gallocatechin 3-O-gallate to have significant inhibitory effects on Foc growth. The antifungal effects of these three compounds represent a novel finding.DiscussionTherefore, phenolic acids and flavonoids play important roles in NR mediated FW resistance breeding in cucumber.

Analcime plays a significant role in sandstone reservoirs as an authigenic diagenetic mineral in the Junggar Basin (northwestern China). However, the origin and controls on the reservoirs have received remarkably little attention. This study investigates the formation mechanism of analcime in the Middle Permian strata in the Jinan sag (southern Junggar Basin) through petrography and geochemistry. The results show that analcime is formed through early alkaline hydrolysis of volcanic materials under specific temperature and pressure conditions. The reservoir rocks primarily consist of various lithic sandstones, including volcanic debris such as basalt, andesite, and tuff. Analcime is characterized as rich in aluminium and poor in sodium, classified as low-silica analcime with a low Si-Al ratio (1.98–2.38). Furthermore, various other diagenetic minerals, such as glauconite, chlorite, albite, and calcite have been identified. The primary reservoir space chiefly consists of intragranular dissolved pores of analcime, while secondary pores are formed by intragranular pores of feldspar and lithic, along with some remaining intergranular pores. Cementation of analcime during early diagenesis changes primary pore structures and reduces reservoir properties. The low-silica analcime dissolves due to acidic pore fluids associated with three stages of oil and gas charging, transforming into albite and creating numerous secondary pores, thereby enhancing reservoir quality.

Porcine reproductive and respiratory syndrome virus (PRRSV) continues to cause significant economic losses to the global swine industry, yet effective prevention and control measures remain elusive. The development of novel antivirals is thus urgently needed. Rifampicin (RFP), a semisynthetic derivative of rifamycin, has been previously reported to inhibit the replication of certain mammalian DNA viruses as well as RNA viruses. In this study, we unveil RFP as a potent inhibitor of PRRSV both in Marc-145 cells (half-maximal inhibitory concentration 61.26 μM) and porcine alveolar macrophages (half-maximal inhibitory concentration 53.09 μM). The inhibitory effect of RFP occurred during viral replication rather than binding, internalization and release. We also demonstrated that RFP inhibits PRRSV proteins production in the early stage of infection, without inhibiting host protein synthesis. Moreover, RFP effectively restricted porcine epidemic diarrhea virus (PEDV) and porcine enteric alphacoronavirus (PEAV) infection in Vero cells. In summary, these findings indicate the promising potential of RFP as a therapeutic agent for PRRSV, PEDV and PEAV infection in pig farms.

Abstract Purpose The pathways underpinning suicide ideation (SI) and certain physical and psychological factors in patients with advanced breast cancer remain unclear. This study develops and validates a mediation model that delineates the associations between several multidimensional variables and SI in Chinese patients with advanced breast cancer. Methods Patients with advanced breast cancer (n = 509) were recruited as study participants from 10 regional cancer centers across China from August 2019 to December 2020. Participants were required to complete five questionnaires using an electronic patient-reported outcomes (ePRO) system: 9 item- Patient Health Questionnaire (PHQ-9), Hospital Anxiety and Depression Scale (HADS), Insomnia Severity Index (ISI), 5-level EQ-5D (EQ-5D-5L), and MD Anderson Symptom Inventory (MDASI). Risk factors for SI were identified using multivariable logistic regression, and inputted into serial multiple mediation models to elucidate the pathways linking the risk factors to SI. Results SI prevalence was 22.8% (116/509). After adjusting for covariates, depression (odds ratio [OR] = 1.384), emotional distress (OR = 1.107), upset (OR = 0.842), and forgetfulness (OR = 1.236) were identified as significant independent risk factors (all p

There are two sets of thermal reservoirs with different rock types in the Gucheng geothermal field of Hebei Province, namely the Ordovician fractured carbonate thermal reservoir and the Neogene Guantao sandstone thermal reservoir, each developed using independent well networks. The energy demand per unit area in the region is high, and the existing geothermal development methods cannot meet the regional energy demand. For this type of block, combined with the development characteristics of different types of thermal reservoirs, numerical simulation methods were used to study the geothermal development trends of Ordovician fractured carbonate reservoirs and Neogene Guantao Formation sandstone reservoirs. When simulating sandstone thermal storage, priority should be given to demonstrating the optimal recharge flow rate, while in simulating carbonate thermal storage, the focus should be on considering the influence of fracture development direction on development trends. Through numerical simulation of thermal storage development and combined with well network design, the optimal well spacing, production reinjection flow rate, and reinjection temperature for two sets of thermal reservoirs developed using the same well network were determined. It is predicted that the average heat flow in the study can increase by 47.8 %. This study presents reasonable development technical countermeasures to maximize the heating capacity of the geothermal development zone and provides an effective reference for the efficient development of similar geothermal resources in the Bohai Bay Basin.

Abstract Objective Calcific aortic valve disease (CAVD) is the leading cause of angina, heart failure, and death from aortic stenosis. However, the molecular mechanisms of its progression, especially the complex disease-related transcriptional regulatory mechanisms, remain to be further elucidated. Methods This study used porcine valvular interstitial cells (PVIC) as a model. We used osteogenic induced medium (OIM) to induce calcium deposition in PVICs to calcify them, followed by basic fibroblast growth factor (bFGF) treatment to inhibit calcium deposition. Transcriptome sequencing was used to study the mRNA expression profile of PVICs and its related transcriptional regulation. We used DaPars to further examine alternative polyadenylation (APA) between different treatment groups. Results We successfully induced calcium deposition of PVICs through OIM. Subsequently, mRNA-seq was used to identify differentially expressed mRNAs for three different treatments: control, OIM-induced and OIM-induced bFGF treatment. Global APA events were identified in the OIM and bFGF treatment groups by bioinformatics analysis. Finally, it was discovered and proven that catalase (CAT) is one of the potential targets of bFGF-induced APA regulation. Conclusion We described a global APA change in a calcium deposition model related to CAVD. We revealed that transcriptional regulation of the CAT gene may contribute to bFGF-induced calcium deposition inhibition.

Abstract Airway epithelial transcriptome analysis of asthma patients with different severity was used to disentangle the immune infiltration mechanisms affecting asthma exacerbation, which may be advantageous to asthma treatment. Here we introduce various bioinformatics methods and develop two models: an OVA/CFA-induced neutrophil asthma mouse model and an LPS-induced human bronchial epithelial cell damage model. Our objective is to investigate the molecular mechanisms, potential targets, and therapeutic strategies associated with asthma severity. Multiple bioinformatics methods identify meaningful differences in the degree of neutrophil infiltration in asthma patients with different severity. Then, PTPRC, TLR2, MMP9, FCGR3B, TYROBP, CXCR1, S100A12, FPR1, CCR1 and CXCR2 are identified as the hub genes. Furthermore, the mRNA expression of 10 hub genes is determined in vivo and in vitro models. Reperixin is identified as a pivotal drug targeting CXCR1, CXCR2 and MMP9. We further test the potential efficiency of Reperixin in 16HBE cells, and conclude that Reperixin can attenuate LPS-induced cellular damage and inhibit the expression of them. In this study, we successfully identify and validate several neutrophilic signatures and targets associated with asthma severity. Notably, Reperixin displays the ability to target CXCR1, CXCR2, and MMP9, suggesting its potential therapeutic value for managing deteriorating asthma.

Abstract Background Emerging evidences suggest that aberrant metabolites contributes to the immunosuppressive microenvironment that leads to cancer immune evasion. Among tumor immunosuppressive cells, myeloid-derived suppressor cells (MDSCs) are pathologically activated and extremely immunosuppressive, which are closely associated with poor clinical outcomes of cancer patients. However, the correlation between MDSCs mediated immunosuppression and particular cancer metabolism remained elusive. Methods Spontaneous lung adenocarcinoma and subcutaneous mouse tumor models, gas chromatography–mass spectrometry (GC–MS) and immunofluorescence assay of patient-derived lung adenocarcinoma tissues, and flow cytometry, RNA sequencing and Western blotting of immune cells, were utilized. Results Metabolite profiling revealed a significant accumulation of acetic acids in tumor tissues from both patients and mouse model, which contribute to immune suppression and cancer progression significantly through free fatty acid receptor 2 (FFAR2). Furthermore, FFAR2 is highly expressed in the myeloid-derived suppressor cells (MDSCs) from the tumor of lung adenocarcinoma (LUAD) patients which is greatly associated with poor prognosis. Surprisingly, whole or myeloid Ffar2 gene deletion markedly inhibited urethane-induced lung carcinogenesis and syngeneic tumor growth with reduced MDSCs and increased CD8+ T cell infiltration. Mechanistically, FFAR2 deficiency in MDSCs significantly reduced the expression of Arg1 through Gαq/Calcium/PPAR-γ axis, which eliminated T cell dysfunction through relieving L-Arginine consumption in tumor microenvironment. Therefore, replenishment of L-Arginine or inhibition to PPAR-γ restored acetic acids/FFAR2 mediated suppression to T cells significantly. Finally, FFAR2 inhibition overcame resistance to immune checkpoint blockade through enhancing the recruitment and cytotoxicity of tumor-infiltrating T cells. Conclusion Altogether, our results demonstrate that the acetic acids/FFAR2 axis enhances MDSCs mediated immunosuppression through Gαq/calcium/PPAR-γ/Arg1 signaling pathway, thus contributing to cancer progression. Therefore, FFAR2 may serve as a potential new target to eliminate pathologically activated MDSCs and reverse immunosuppressive tumor microenvironment, which has great potential in improving clinical outcomes of cancer immunotherapy.

Abstract Background Little is understood about the association between psychosomatic symptoms and advanced cancer among older Chinese patients. Methods This secondary analysis was part of a multicenter cross-sectional study based on an electronic patient-reported outcome platform. Patients with advanced cancer were included between August 2019 and December 2020 in China. Participants (over 60 years) completed the MD Anderson Symptom Inventory (MDASI) and Hospital Anxiety and Depression Scale (HADS) to measure symptom burden. Network analysis was also conducted to investigate the network structure, centrality indices (strength, closeness, and betweenness) and network stability. Results A total of 1022 patients with a mean age of 66 (60–88) years were included; 727 (71.1%) were males, and 295 (28.9%) were females. A total of 64.9% of older patients with advanced cancer had one or more symptoms, and up to 80% had anxiety and depression. The generated network indicated that the physical symptoms, anxiety and depression symptom communities were well connected with each other. Based on an evaluation of the centrality indices, ‘distress/feeling upset’ (MDASI 5) appears to be a structurally important node in all three networks, and ‘I lost interest in my own appearance’ (HADS-D4) had the lowest centrality indices. The network stability was relatively high (> 0.7). Conclusion The symptom burden remains high in older patients with advanced cancer in China. Psychosomatic symptoms are highly interactive and often present as comorbidities. This network can be used to provide targeted interventions to optimize symptom management in older patients with advanced cancer in China. Trial registration Chinese Clinical Trial Registry (ChiCTR1900024957), registered on 06/12/2020.

To analyze the episodic alteration of Middle Permian carbonate reservoirs by complex hydrothermal fluid in southwestern Sichuan Basin, petrology, geochemistry, fluid inclusion and U-Pb dating researches are conducted. The fractures and vugs of Middle Permian Qixia–Maokou formations are filled with multi-stage medium−coarse saddle dolomites and associated hydrothermal minerals, which indicates that the early limestone/dolomite episodic alteration was caused by the large-scale, high-temperature, deep magnesium-rich brine along flowing channels such as basement faults or associated fractures under the tectonic compression and napping during the Indosinian. The time of magnesium-rich hydrothermal activity was from the Middle Triassic to the Late Triassic. The siliceous and calcite fillings were triggered by hydrothermal alteration in the Middle and Late Yanshanian Movement and Himalayan Movement. Hydrothermal dolomitization is controlled by fault, hydrothermal property, flowing channel and surrounding rock lithology, which occur as equilibrium effect of porosity and permeability. The thick massive grainstone/dolomites were mainly altered by modification such as hydrothermal dolomitization/recrystallization, brecciation and fracture-vugs filling. Early thin–medium packstones were mainly altered by dissolution and infilling of fracturing, bedding dolomitization, dissolution and associated mineral fillings. The dissolved vugs and fractures are the main reservoir space under hydrothermal conditions, and the connection of dissolved vugs and network fractures is favorable for forming high-quality dolomite reservoir. Hydrothermal dolomite reservoirs are developed within a range of 1 km near faults, with a thickness of 30–60 m. Hydrothermal dolomite reservoirs with local connected pore/vugs and fractures have exploration potential.

Aldehyde oxidase (AOX) is a molybdoenzyme that is primarily expressed in the liver and is involved in the metabolism of drugs and other xenobiotics. AOX-mediated metabolism can result in unexpected outcomes, such as the production of toxic metabolites and high metabolic clearance, which can lead to the clinical failure of novel therapeutic agents. Computational models can assist medicinal chemists in rapidly evaluating the AOX metabolic risk of compounds during the early phases of drug discovery and provide valuable clues for manipulating AOX-mediated metabolism liability. In this study, we developed a novel graph neural network called AOMP for predicting AOX-mediated metabolism. AOMP integrated the tasks of metabolic substrate/non-substrate classification and metabolic site prediction, while utilizing transfer learning from 13C nuclear magnetic resonance data to enhance its performance on both tasks. AOMP significantly outperformed the benchmark methods in both cross-validation and external testing. Using AOMP, we systematically assessed the AOX-mediated metabolism of common fragments in kinase inhibitors and successfully identified four new scaffolds with AOX metabolism liability, which were validated through in vitro experiments. Furthermore, for the convenience of the community, we established the first online service for AOX metabolism prediction based on AOMP, which is freely available at https://aomp.alphama.com.cn.

This study presents a novel method to assess the learning effectiveness using Electroencephalography (EEG)-based deep learning model. It is difficult to assess the learning effectiveness of professional courses in cultivating students’ ability objectively by questionnaire or other assessment methods. Research in the field of brain has shown that innovation ability can be reflected from cognitive ability which can be embodied by EEG signal features. Three navigation tasks of increasing cognitive difficulty were designed and a total of 41 subjects participated in the experiment. For the classification and tracking of the subjects’ EEG signals, a convolutional neural network (CNN)-based Multi-Time Scale Spatiotemporal Compound Model (MTSC) is proposed in this paper to extract and classify the features of the subjects’ EEG signals. Furthermore, Spiking neural networks (SNN) -based NeuCube is used to assess the learning effectiveness and demonstrate cognitive processes, acknowledging that NeuCube is an excellent method to display the spatiotemporal differences between spikes emitted by neurons. The results of the classification experiment show that the cognitive training traces of different students in solving three navigational problems can be effectively distinguished. More importantly, new information about navigation is revealed through the analysis of feature vector visualization and model dynamics. This work provides a foundation for future research on cognitive navigation and the training of students’ navigational skills.

Pancreatic cancer, a highly fatal malignancy, is predicted to rank as the second leading cause of cancer-related death in the next decade. This highlights the urgent need for new insights into personalized diagnosis and treatment. Although molecular subtypes of pancreatic cancer were well established in genomics and transcriptomics, few known molecular classifications are translated to guide clinical strategies and require a paradigm shift. Notably, chronically developing and continuously improving high-throughput technologies and systems serve as an important driving force to further portray the molecular landscape of pancreatic cancer in terms of epigenomics, proteomics, metabonomics, and metagenomics. Therefore, a more comprehensive understanding of molecular classifications at multiple levels using an integrated multi-omics approach holds great promise to exploit more potential therapeutic options. In this review, we recapitulated the molecular spectrum from different omics levels, discussed various subtypes on multi-omics means to move one step forward towards bench-to-beside translation of pancreatic cancer with clinical impact, and proposed some methodological and scientific challenges in store.

Abstract BackgroundThe traditional clinical trial data collection process requires a clinical research coordinator who is authorized by the investigators to read from the hospital’s electronic medical record. Using electronic source data opens a new path to extract patients’ data from electronic health records (EHRs) and transfer them directly to an electronic data capture (EDC) system; this method is often referred to as eSource. eSource technology in a clinical trial data flow can improve data quality without compromising timeliness. At the same time, improved data collection efficiency reduces clinical trial costs. ObjectiveThis study aims to explore how to extract clinical trial–related data from hospital EHR systems, transform the data into a format required by the EDC system, and transfer it into sponsors’ environments, and to evaluate the transferred data sets to validate the availability, completeness, and accuracy of building an eSource dataflow. MethodsA prospective clinical trial study registered on the Drug Clinical Trial Registration and Information Disclosure Platform was selected, and the following data modules were extracted from the structured data of 4 case report forms: demographics, vital signs, local laboratory data, and concomitant medications. The extracted data was mapped and transformed, deidentified, and transferred to the sponsor’s environment. Data validation was performed based on availability, completeness, and accuracy. ResultsIn a secure and controlled data environment, clinical trial data was successfully transferred from a hospital EHR to the sponsor’s environment with 100% transcriptional accuracy, but the availability and completeness of the data could be improved. ConclusionsData availability was low due to some required fields in the EDC system not being available directly in the EHR. Some data is also still in an unstructured or paper-based format. The top-level design of the eSource technology and the construction of hospital electronic data standards should help lay a foundation for a full electronic data flow from EHRs to EDC systems in the future.

Abstract Background Patients diagnosed with advanced stage cancer face an elevated risk of suicide. We aimed to develop a suicidal ideation (SI) risk prediction model in patients with advanced cancer for early warning of their SI and facilitate suicide prevention in this population. Patients and Methods We consecutively enrolled patients with multiple types of advanced cancers from 10 cancer institutes in China from August 2019 to December 2020. Demographic characteristics, clinicopathological data, and clinical treatment history were extracted from medical records. Symptom burden, psychological status, and SI were assessed using the MD Anderson Symptom Inventory (MDASI), Hospital Anxiety and Depression Scale (HADS), and Patient Health Questionnaire‐9 (PHQ‐9), respectively. A multivariable logistic regression model was employed to establish the model structure. Results In total, 2814 participants were included in the final analysis. Nine predictors including age, sex, number of household members, history of previous chemotherapy, history of previous surgery, MDASI score, HADS‐A score, HADS‐D score, and life satisfaction were retained in the final SI prediction model. The model achieved an area under the curve (AUC) of 0.85 (95% confidential interval: 0.82–0.87), with AUCs ranging from 0.75 to 0.95 across 10 hospitals and higher than 0.83 for all cancer types. Conclusion This study built an easy‐to‐use, good‐performance predictive model for SI. Implementation of this model could facilitate the incorporation of psychosocial support for suicide prevention into the standard care of patients with advanced cancer.

Distant hybridization is a well-established technique in genetic breeding for cultivation of superior traits. Previous studies have shown that, hybrids derived from the cross between Schizothorax wangchiachii (♀) and Percocypris pingi (♂) are significantly different from their parents in terms of growth performance, feeding behavior and disease resistance. Both cellular and plasma components of blood are integral to immune system, and erythrocytes serve as the sole cells for transporting oxygen which makes energy available for the growth, development, immune responses and all other physiological activities. In order to understand ecological adaptive strategies and also the underlying physiological and biochemical mechanisms of fish with different characteristics, the present study used offsprings and hybrids produced by artificial reproduction of the same batch of domesticated S. wangchiachii, P. pingi broodstock as the experimental fish, and analyses of biochemical indexes, differential leucocytes counts and histological examination of liver sections were performed. Results showed that the proportions of lymphocytes and thrombocytes in P. pingi were significantly higher than those in S. wangchiachii (P

Abstract Objectives Patients with advanced colorectal cancer (CRC) have multiple concurrent physical and psychological symptoms. This study aimed to explore the relationship between anxiety, depression, and symptom burden in advanced CRC. Methods A multicenter cross‐sectional study was conducted in 10 cancer centers from geographically and economically diverse sites in China. A total of 454 patients with advanced CRC completed the Hospital Anxiety and Depression Scale and the MD Anderson Symptom Inventory. Multiple regression analysis was applied to explore the relationship between anxiety, depression and symptom burden. Results About one‐third of the patients showed symptoms of anxiety or depression. Patients with anxiety or depression reported significantly higher symptom burden than those without (p

Abstract The dust direct radiative effect (DRE) depends strongly on the dust particle size distribution (PSD) and complex refractive index (CRI). Although recent studies constrained the dust PSD in the models, its CRI uncertainties are still large. As a result, whether dust warms or cools the climate system remains unclear. Here, we estimate the dust DRE by employing the regionally‐dependent dust CRI based on global measurements. We find that new dust CRI significantly enhances the scattering of dust in the shortwave while reduces its absorption in the longwave, which is opposite to that caused by increasing the coarse and giant dust fraction via constraining the PSD. Constraining both PSD and CRI ultimately leads to a net dust DRE of −0.68 W m−2, a cooling stronger than current model estimates.

African swine fever (ASF) is an acute, hemorrhagic, and severe infectious disease caused by the ASF virus (ASFV). ASFV has evolved multiple strategies to escape host antiviral immune responses. Here, we reported that ASFV pB318L, a trans-geranylgeranyl-diphosphate synthase, reduced the expression of type I interferon (IFN-I) and IFN-stimulated genes (ISGs). Mechanically, pB318L not only interacted with STING to reduce the translocation of STING from the endoplasmic reticulum to the Golgi apparatus but also interacted with IFN receptors to reduce the interaction of IFNAR1/TYK2 and IFNAR2/JAK1. Of note, ASFV with interruption of B318L gene (ASFV-intB318L) infected PAMs produces more IFN-I and ISGs than that in PAMs infected with its parental ASFV HLJ/18 at the late stage of infection. Consistently, the pathogenicity of ASFV-intB318L is attenuated in piglets compared with its parental virus. Taken together, our data reveal that B318L gene may partially affect ASFV pathogenicity by reducing the production of IFN-I and ISGs. This study provides a clue to design antiviral agents or live attenuated vaccines to prevent and control ASF.

Allogeneic hematopoietic cell transplantation (HCT) is used to treat many blood-based disorders and malignancies, however it can also result in serious adverse events, such as the development of acute graft-versus-host disease (aGVHD). This study aimed to develop a donor-specific epigenetic classifier to reduce incidence of aGVHD by improving donor selection. Genome-wide DNA methylation was assessed in a discovery cohort of 288 HCT donors selected based on recipient aGVHD outcome; this cohort consisted of 144 cases with aGVHD grades III-IV and 144 controls with no aGVHD. We applied a machine learning algorithm to identify CpG sites predictive of aGVHD. Receiver operating characteristic (ROC) curve analysis of these sites resulted in a classifier with an encouraging area under the ROC curve (AUC) of 0.91. To test this classifier, we used an independent validation cohort (n = 288) selected using the same criteria as the discovery cohort. Attempts to validate the classifier failed with the AUC falling to 0.51. These results indicate that donor DNA methylation may not be a suitable predictor of aGVHD in an HCT setting involving unrelated donors, despite the initial promising results in the discovery cohort. Our work highlights the importance of independent validation of machine learning classifiers, particularly when developing classifiers intended for clinical use.

Anti-tumor angiogenesis therapy, targeting the suppression of blood vessel growth in tumors, presents a potent approach in the battle against cancer. Traditional therapies have primarily concentrated on single-target techniques, with a specific emphasis on targeting the vascular endothelial growth factor, but have not reached ideal therapeutic efficacy. In response to this issue, our study introduced a novel nanoparticle system known as CS-siRNA/PEITC&L-cRGD NPs. These chitosan-based nanoparticles have been recognized for their excellent biocompatibility and ability to deliver genes. To enhance their targeted delivery capability, they were combined with a cyclic RGD peptide (cRGD). Targeted co-delivery of gene and chemotherapeutic agents was achieved through the use of a negatively charged lipid shell and cRGD, which possesses high affinity for integrin αvβ3 overexpressed in tumor cells and neovasculature. In this multifaceted approach, co-delivery of VEGF siRNA and phenethyl isothiocyanate (PEITC) was employed to target both tumor vascular endothelial cells and tumor cells simultaneously. The co-delivery of VEGF siRNA and PEITC could achieve precise silencing of VEGF, inhibit the accumulation of HIF-1α under hypoxic conditions, and induce apoptosis in tumor cells. In summary, we have successfully developed a nanoparticle delivery platform that utilizes a dual mechanism of action of anti-tumor angiogenesis and pro-tumor apoptosis, which provides a robust and potent strategy for the delivery of anti-cancer therapeutics.

ARPC1B encodes the protein known as actin-related protein 2/3 complex subunit 1 B (ARPC1B), which controls actin polymerization in the human body. Although ARPC1B has been linked to several human malignancies, its function in these cancers remains unclear. TCGA, GTEx, CCLE, Xena, CellMiner, TISIDB, and molecular signature databases were used to analyze ARPC1B expression in cancers. Visualization of data was primarily achieved using R language, version 4.0. Nineteen tumors exhibited high levels of ARPC1B expression, which were associated with different tumor stages and significantly affected the prognosis of various cancers. The level of ARPC1B expression substantially connected the narrative of ARPC1B expression with several TMB cancers and showed significant changes in MSI. Additionally, tolerance to numerous anticancer medications has been linked to high ARPC1B gene expression. Using Gene Set Variation Analysis/Gene Set Enrichment Analysisanalysis and concentrating on Rectum adenocarcinoma (READ), we thoroughly examined the molecular processes of the ARPC1B gene in pan-cancer. Using WGCNA, we examined the co-expression network of READ and ARPC1B. Meanwhile, ten specimens were selected for immunohistochemical examination, which showed high expression of ARPC1B in READ. Human pan-cancer samples show higher ARPC1B expression than healthy tissues. In many malignancies, particularly READ, ARPC1B overexpression is associated with immune cell infiltration and a poor prognosis. These results imply that the molecular biomarker ARPC1B may be used to assess the prognosis and immune infiltration of patients with READ.

Epithelial growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) have significantly enhanced the treatment outcomes in non-small cell lung cancer (NSCLC) patients harboring EGFR mutations. However, the occurrence of acquired resistance to EGFR-TKIs is an unavoidable outcome observed in these patients. Disruption of the PI3K/AKT/mTOR signaling pathway can contribute to the emergence of resistance to EGFR TKIs in lung cancer. The emergence of PIK3CA mutations following treatment with EGFR-TKIs can lead to resistance against EGFR-TKIs. This review provides an overview of the current perspectives regarding the involvement of PI3K/AKT/mTOR signaling in the development of lung cancer. Furthermore, we outline the state-of-the-art therapeutic strategies targeting the PI3K/AKT/mTOR signaling pathway in lung cancer. We highlight the role of PIK3CA mutation as an acquired resistance mechanism against EGFR-TKIs in EGFR-mutant NSCLC. Crucially, we explore therapeutic strategies targeting PIK3CA-mediated resistance to EGFR TKIs in lung cancer, aiming to optimize the effectiveness of treatment.

Abstract Background Chinese indigenous pigs in Yunnan exhibit considerable phenotypic diversity, but their population structure and the biological interpretation of signatures of artificial selection require further investigation. To uncover population genetic diversity, migration events, and artificial selection signatures in Chinese domestic pigs, we sampled 111 Yunnan pigs from four breeds in Yunnan which is considered to be one of the centres of livestock domestication in China, and genotyped them using Illumina Porcine SNP60K BeadChip. We then leveraged multiple bioinformatics database tools to further investigate the signatures and associated complex traits. Results Population structure and migration analyses showed that Diannanxiaoer pigs had different genetic backgrounds from other Yunnan pigs, and Gaoligongshan may undergone the migration events from Baoshan and Saba pigs. Intriguingly, we identified a possible common target of sharing artificial selection on a 265.09 kb region on chromosome 5 in Yunnan indigenous pigs, and the genes on this region were associated with cardiovascular and immune systems. We also detected several candidate genes correlated with dietary adaptation, body size (e.g., PASCIN1, GRM4, ITPR2), and reproductive performance. In addition, the breed-sharing gene MMP16 was identified to be a human-mediated gene. Multiple lines of evidence at the mammalian genome, transcriptome, and phenome levels further supported the evidence for the causality between MMP16 variants and the metabolic diseases, brain development, and cartilage tissues in Chinese pigs. Our results suggested that the suppression of MMP16 would directly lead to inactivity and insensitivity of neuronal activity and skeletal development in Chinese indigenous pigs. Conclusion In this study, the population genetic analyses and identification of artificial selection signatures of Yunnan indigenous pigs help to build an understanding of the effect of human-mediated selection mechanisms on phenotypic traits in Chinese indigenous pigs. Further studies are needed to fully characterize the process of human-mediated genes and biological mechanisms.

AbstractPancreatic ductal adenocarcinoma (PDAC) is one of the leading causes of cancer-related death. Therefore, we intend to explore novel strategies against PDAC. The exosomes-based biomimetic nanoparticle is an appealing candidate served as a drug carrier in cancer treatment, due to its inherit abilities. In the present study, we designed dasatinib-loaded hybrid exosomes by fusing human pancreatic cancer cells derived exosomes with dasatinib-loaded liposomes, followed by characterization for particle size (119.9 ± 6.10 nm) and zeta potential (−11.45 ± 2.24 mV). Major protein analysis from western blot techniques reveal the presence of exosome marker proteins CD9 and CD81. PEGylated hybrid exosomes showed pH-sensitive drug release in acidic condition, benefiting drug delivery to acidic cancer environment. Dasatinib-loaded hybrid exosomes exhibited significantly higher uptake rates and cytotoxicity to parent PDAC cells by two-sample t-test or by one-way ANOVA analysis of variance, as compared to free drug or liposomal formulations. The results from our computational analysis demonstrated that the drug-likeness, ADMET, and protein-ligand binding affinity of dasatinib are verified successfully. Cancer derived hybrid exosomes may serve as a potential therapeutic candidate for pancreatic cancer treatment.

This study highlights the significance of high-quality development of energy (EHQD) in achieving carbon neutrality. Researchers have explored how to successfully achieve carbon neutrality, but few studies have examined the impact of the EHQD on carbon neutrality. Accordingly, while considering the high-quality development of China’s economy, this study constructs a comprehensive evaluation index system for China’s EHQD using the technique for order preference by similarity to an ideal solution (TOPSIS) method based on entropy weight to measure the EHQD level of energy in 30 provinces in China from 2004 to 2019. Considering the possibility of endogeneities, the two-stage least squares (2SLS) regression is applied to empirically analyze the impact of the EHQD on carbon neutrality. Cointegration tests show a long-term cointegration relationship between the EHQD, real GDP per capita, urbanization, traffic pressure, industrial structure, and CO2 emissions (CE). The 2SLS method empirically shows that the EHQD has a significant negative impact on CE. The EHQD can significantly reduce CE, which is conducive for China to achieve the goal of carbon neutrality. The results of this study indicate that to reduce CE and enable China to successfully achieve its goal of carbon neutrality by 2060, policymakers should take effective measures to promote the EHQD.

Abstract Background Chinese indigenous pigs are popular with consumers for their juiciness, flavour and meat quality, but they have lower meat production. Insulin-like growth factor 2 (IGF2) is a maternally imprinted growth factor that promotes skeletal muscle growth by regulating cell proliferation and differentiation. A single nucleotide polymorphism (SNP) within intron 3 of porcine IGF2 disrupts a binding site for the repressor, zinc finger BED-type containing 6 (ZBED6), leading to up-regulation of IGF2 and causing major effects on muscle growth, heart size, and backfat thickness. This favorable mutation is common in Western commercial pig populations, but absent in most Chinese indigenous pig breeds. To improve meat production of Chinese indigenous pigs, we used cytosine base editor 3 (CBE3) to introduce IGF2-intron3-C3071T mutation into porcine embryonic fibroblasts (PEFs) isolated from a male Liang Guang Small Spotted pig (LGSS), and single-cell clones harboring the desired mutation were selected for somatic cell nuclear transfer (SCNT) to generate the founder line of IGF2 T/T pigs. Results We found the heterozygous progeny IGF2 C/T pigs exhibited enhanced expression of IGF2, increased lean meat by 18%–36%, enlarged loin muscle area by 3%–17%, improved intramuscular fat (IMF) content by 18%–39%, marbling score by 0.75–1, meat color score by 0.53–1.25, and reduced backfat thickness by 5%–16%. The enhanced accumulation of intramuscular fat in IGF2 C/T pigs was identified to be regulated by the PI3K-AKT/AMPK pathway, which activated SREBP1 to promote adipogenesis. Conclusions We demonstrated the introduction of IGF2-intron3-C3071T in Chinese LGSS can improve both meat production and quality, and first identified the regulation of IMF deposition by IGF2 through SREBP1 via the PI3K-AKT/AMPK signaling pathways. Our study provides a further understanding of the biological functions of IGF2 and an example for improving porcine economic traits through precise base editing.

【Objective】The mutations in the VRTN gene g.20311_20312ins291 and g.19034A>C have been found to influence the number of thoracic vertebrae in lean meat pigs. These mutations can increase the number of thoracic vertebrae. This study aims to investigate the frequency of VRTN gene mutations in the Liang Guang Small Spotted pig populations and their impact on carcass and meat quality traits, providing reference for molecular breeding of Liang Guang Small Spotted pigs.【Method】Genomic DNA of 69 Liang Guang Small Spotted pigs was extracted and subjected to PCR amplification. Gel electrophoresis and TA cloning were used to detect the mutations at the g.20311_20312ins291 and g.19034A>C loci of the VRTN gene. Carcass and meat quality traits of the population were recorded, and the animals were grouped based on their mutation status. Statistical analysis was performed using t-tests.【Result】Among the population, 5 individuals were identified as carrying heterozygous mutations at both loci, indicating that the two mutations may be closely linked, with a frequency of 3.62% for both mutations. Statistical analysis indicated that the VRTN linked mutation allele did not significantly affect the number of ribs in Liang Guang Small Spotted pigs. However, they did affect carcass and meat quality traits. In terms of carcass traits, the VRTN gene heterozygous mutations significantly increased body length by 4.6% (P < 0.05) and body weight by 9.6% (P < 0.01), increased body slant length by 3.5%, but the difference was not significant. The backfat thickness and skin thickness were increased by 6.5% and decreased by 3.7%, respectively, but without significant differences. In terms of meat quality traits, the brightness L, chromaticity index a and b values of the heterozygous mutants increased by 0.01%, 14.7%, and 8.4%, respectively. The water loss rate significantly increased by 51.2% (P < 0.05). The difference in changes of shear force and pH value are not significant.【Conclusion】The VRTN gene mutations g.20311_20312ins291 and g.19034A > C are detected in the Liang Guang Small Spotted pig populations, but their frequencies are relatively low. These two mutations may be tightly linked. The VRTN gene heterozygous mutations will not increase the number of thoracic vertebrae in Liang Guang Small Spotted pigs, but they improve carcass traits to some extent while also have adverse effects on meat quality traits. Future breeding of Liang Guang Small Spotted pigs needs to balance the impact of VRTN gene mutations on carcass traits and meat quality traits.

Abstract The present study explored the potential role of cold-regulated plasma membrane protein COR413PM1 isolated from Saussurea involucrata (Matsum. & Koidz)(SikCOR413PM1), in enhancing cotton (Gossypium hirsutum) tolerance to cold and drought stresses through transgenic methods. Under cold and drought stresses, the survival rate and the fresh and dry weights of the SikCOR413PM1-overexpressing lines were higher than those of the wild-type plants, and the degree of leaf withering was much lower. Besides, overexpressing SikCOR413PM1 overexpression increased the relative water content, reduced malondialdehyde content and relative conductivity, and elevated proline and soluble sugar levels in cotton seedlings. These findings suggest that SikCOR413PM1 minimizes cell membrane damage and boosts plant stability under challenging conditions. Additionally, overexpression of this gene upregulated antioxidant enzyme-related genes in cotton seedlings, resulting in enhanced antioxidant enzyme activity, lowered peroxide content, and reduced oxidative stress. SikCOR413PM1 overexpression also modulated the expression of stress-related genes (GhDREB1A, GhDREB1B, GhDREB1C, GhERF2, GhNAC3, and GhRD22). In field trials, the transgenic cotton plants overexpressing SikCOR413PM1 displayed high yields and increased environmental tolerance. Our study thus demonstrates the role of SikCOR413PM1 in regulating stress-related genes, osmotic adjustment factors, and peroxide content while preserving cell membrane stability and improving cold and drought tolerance in cotton.

The complete mitochondrial genome of Pyricularia oryzae Cavara 1892 strain Guy11 is 34,865 bp in length (GenBank accession number OP095391), containing 29 tRNA genes, 2 rRNA genes, and 15 protein-coding genes (PCGs). The gene order and orientation are novel compared to other Sordariomycetes species with sequenced mitogenomes in the GenBank database. Phylogenetic analysis suggests that P. oryzae Guy11 and 19 other Sordariomycetes species form a monophyletic group. The complete mitochondrial sequence of P. oryzae Guy11 will be a valuable resource for species identification, population genetics, phylogenetics, and comparative genomics studies in Sordariomycetes and Magnaporthales.

In this work, β-NiS nanoparticles (NPs) were efficiently prepared by a straightforward hydrothermal process. The difference in morphology between these NiS NPs was produced by adding different amounts of thiourea, and the corresponding products were denoted as NiS-15 and NiS-5. Through electrochemical tests, the specific capacity (Cs) of NiS-15 was determined to be 638.34 C g−1 at 1 A g−1, compared to 558.17 C g−1 for NiS-5. To explore the practical application potential of such β-NiS NPs in supercapacitors, a hybrid supercapacitor (HSC) device was assembled with activated carbon (AC) as an anode. Benefitting from the high capacity of the NiS cathode and the large voltage window of the device, the NiS-15//AC HSC showed a high energy density (Ed) of 43.57 W h kg−1 at 936.92 W kg−1, and the NiS-5//AC HSC provided an inferior Ed of 37.89 W h kg−1 at 954.79 W kg−1. Both HSCs showed excellent cycling performance over 6000 cycles at 10 A g−1. The experimental findings suggest that both NiS-15 and NiS-5 in this study can serve as potential cathodes for high-performance supercapacitors. This current synthesis method is simple and can be extended to the preparation of other transition metal sulfide (TMS)-based electrode materials with exceptional electrochemical properties.

Histological transformation is a phenomenon that is well described as one of the causes of tyrosine kinase inhibitor resistance in oncogene-driven non-small-cell lung cancer (NSCLC). The use of immune checkpoint inhibitors (ICIs) as a potential mechanism of acquired resistance to immunotherapy in NSCLC to small-cell lung cancer was also recently found. Here, we report the histological transformation of sarcomatoid carcinoma and metastasis in a lung adenocarcinoma patient without targetable genetic alterations who experienced long-term disease remission after nivolumab therapy. The patient subsequently developed rapid progression in the mediastinal and retroperitoneal lymph nodes, bones, and small intestine. Surgical resection of the small intestine lesion due to acute small intestine bleeding revealed the transformation of NSCLC to sarcomatoid carcinoma. The patient died 3 months after sarcomatoid carcinoma transformation and extensive disease progression, although he was rechallenged with immunotherapy. Genomic and immunohistochemical analyses revealed a comparable abundance of gene mutations and a limited number of immune cells in the tumor microenvironment, with low infiltration of CD8 + T cells, CD4 + T cells, regulatory T cells, and PD-L1 + macrophages in metastatic tumors, revealing a noninflamed immune microenvironment for ICI-resistant tumors.

Abstract Epigenetic modifications are defined as heritable changes in gene activity that do not involve changes in the underlying DNA sequence. The oncogenic process is driven by the accumulation of alterations that impact genome's structure and function. Genetic mutations, which directly disrupt the DNA sequence, are complemented by epigenetic modifications that modulate gene expression, thereby facilitating the acquisition of malignant characteristics. Principals among these epigenetic changes are shifts in DNA methylation and histone mark patterns, which promote tumor development and metastasis. Notably, the reversible nature of epigenetic alterations, as opposed to the permanence of genetic changes, positions the epigenetic machinery as a prime target in the discovery of novel therapeutics. Our review delves into the complexities of epigenetic regulation, exploring its profound effects on tumor initiation, metastatic behavior, metabolic pathways, and the tumor microenvironment. We place a particular emphasis on the dysregulation at each level of epigenetic modulation, including but not limited to, the aberrations in enzymes responsible for DNA methylation and histone modification, subunit loss or fusions in chromatin remodeling complexes, and the disturbances in higher‐order chromatin structure. Finally, we also evaluate therapeutic approaches that leverage the growing understanding of chromatin dysregulation, offering new avenues for cancer treatment.

IntroductionPeanut allergy is an immunoglobulin E (IgE) mediated food allergy. Rubia cordifolia L. (R. cordifolia), a Chinese herbal medicine, protects against peanut-induced anaphylaxis by suppressing IgE production in vivo. This study aims to identify IgE-inhibitory compounds from the water extract of R. cordifolia and investigate the underlying mechanisms using in vitro and in vivo models.MethodsCompounds were isolated from R. cordifolia water extract and their bioactivity on IgE production was assessed using a human myeloma U266 cell line. The purified active compound, xanthopurpurin (XPP), was identified by LC-MS and NMR. Peanut-allergic C3H/HeJ mice were orally administered with or without XPP at 200µg or 400µg per mouse per day for 4 weeks. Serum peanut-specific IgE levels, symptom scores, body temperatures, and plasma histamine levels were measured at challenge. Cytokines in splenocyte cultures were determined by ELISA, and IgE + B cells were analyzed by flow cytometry. Acute and sub-chronic toxicity were evaluated. IL-4 promoter DNA methylation, RNA-Seq, and qPCR analysis were performed to determine the regulatory mechanisms of XPP.ResultsXPP significantly and dose-dependently suppressed the IgE production in U266 cells. XPP significantly reduced peanut-specific IgE (>80%, p

Pre-training and fine-tuning have emerged as a promising paradigm across various natural language processing (NLP) tasks. The effectiveness of pretrained large language models (LLM) has witnessed further enhancement, holding potential for applications in the field of medicine, particularly in the context of Traditional Chinese Medicine (TCM). However, the application of these general models to specific domains often yields suboptimal results, primarily due to challenges like lack of domain knowledge, unique objectives, and computational efficiency. Furthermore, their effectiveness in specialized domains, such as Traditional Chinese Medicine, requires comprehensive evaluation.To address the above issues, we propose a novel domain specific TCMDA (TCM Domain Adaptation) approach, efficient pre-training with domain-specific corpus. Specifically, we first construct a large TCM-specific corpus, TCM-Corpus-1B, by identifying domain keywords and retrieving from general corpus. Then, our TCMDA leverages the LoRA which freezes the pretrained model’s weights and uses rank decomposition matrices to efficiently train specific dense layers for pre-training and fine-tuning, efficiently aligning the model with TCM-related tasks, namely TCM-GPT-7B. We further conducted extensive experiments on two TCM tasks, including TCM examination and TCM diagnosis. TCM-GPT-7B archived the best performance across both datasets, outperforming other models by relative increments of 17% and 12% in accuracy, respectively. To the best of our knowledge, our study represents the pioneering validation of domain adaptation of a large language model with 7 billion parameters in TCM domain. We will release both TCM-Corpus-1B and TCM-GPT-7B model once accepted to facilitate interdisciplinary development in TCM and NLP, serving as the foundation for further study.

In civil engineering, stability analysis of slope is one of the main content of design. By using the finite element limit analysis software OptumG2, a landslide geological model is established to simulate the failure process of the landslide in Huadu District, Guangzhou City, China. The analysis focused on the deformation and failure characteristics, as well as the mechanical mechanism of landslide; the landslide mode of homogeneous soil is circular sliding. Additionally, investigating the influencing factors affecting slope stability is crucial in engineering implementation; in which the five influencing factors are considered as follow: slope height, slope gradient, soil cohesion, soil internal friction angle, and soil unit weight, respectively. A stability calculation model for a soil slope is established under 25 working conditions based on strength reduction method and orthogonal experimental design, in which the relationship between the safety factor and slope height, slope gradient, soil cohesion, soil internal friction angle, and soil unit weight is obtained. As the slope height increases from 5m to 45m, the safety factor of soil slope gradually decreases from 2.21 to 0.94; As the slope gradient increases from 20° to 60°, the safety factor of soil slope decreases approximately linearly from 1.80 to 0.95; As the cohesion of soil increases from 10kpa to 30kpa, the safety factor of soil slope increases approximately linearly from 1.04 to 1.60; As the internal friction angle of soil increases from 10° to 30°, the safety factor of soil slope increases approximately linearly from 1.00 to 1.81; As the unit weight of soil increases from 13kN/m3 to 21kN/m3, the safety factor of soil slope decreases approximately linearly from 1.50 to 1.21. The influencing factors affecting the safety factor of soil slope in descending order are slope height, slope angle, soil internal friction angle, soil cohesion, and soil unit weight. The research has reference significance for studying the stability and failure laws of soil slopes and conducting landslide control on soil slopes.

Abstract Previous studies have noticed that the Coupled Model Intercomparison Project Phase 6 (CMIP6) models with a stronger cooling from aerosol‐cloud interactions (ACI) also have an enhanced warming from positive cloud feedback, and these two opposing effects are counter‐balanced in simulations of the historical period. However, reasons for this anti‐correlation are less explored. In this study, we perturb the cloud ice microphysical processes to obtain cloud liquid of varying amounts in two Earth System Models (ESMs). We find that the model simulations with a larger liquid water path (LWP) tend to have a stronger cooling from ACI and a stronger positive cloud feedback. More liquid clouds in the mean‐state present more opportunities for anthropogenic aerosol perturbations and also weaken the negative cloud feedback at middle to high latitudes. This work, from a cloud state perspective, emphasizes the influence of the mean‐state LWP on effective radiative forcing due to ACI (ERFACI).