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The combination of no-till farming and green manure is key to nourishing the soil and increasing crop yields. However, it remains unclear how to enhance the efficiency of green manure under no-till conditions. We conducted a two-factor field trial of silage maize rotated with hairy vetch to test the effects of tillage methods and returning. Factor 1 is the type of tillage, which is divided into conventional ploughing and no-tillage; factor 2 is the different ways of returning hairy vetch as green manure, which were also compared: no return (NM), stubble return (H), mulching (HM), turnover (HR, for CT only), and live coverage (LM, for NT only). Our findings indicate that different methods of returning hairy vetch to the field will improve maize yield and quality. The best results were obtained in CT and NT in HM and LM, respectively. Specifically, HM resulted in the highest dry matter quality and yield, with improvements of 35.4% and 31.9% over NM under CT, respectively. It also demonstrated the best economic and net energy performance. However, other treatments had no significant effect on the beneficial utilization and return of nutrients. The LM improved yields under NT by boosting soil enzyme activity, promoting nitrogen transformation and accumulation, and increasing nitrogen use efficiency for better kernel development. Overall, NTLM is best at utilizing and distributing soil nutrients and increasing silage maize yield. This finding supports the eco-efficient cultivation approach in silage maize production in the region.

Background: Diabetic nephropathy (DN) is a common microvascular complication of diabetes mellitus (DM). Ferroptosis is an atypical form of iron-dependent, modulated cell death that has been shown to occur in human umbilical vein endothelial cells (HUVECs). Leonurine (LEO) is a single active ingredient extracted from Leonurus japonicus Houtt. It has various biological activities, including anti-inflammatory and anti-cancer effects. However, whether LEO affects ferroptosis in DN has yet to be investigated. Methods: An animal model of DN was established by subjecting C57/BL6 mice to a high-fat diet (HFD) while being induced with Streptozotocin (STZ). A cellular model of DN was established by exposing HUVECs to a high glucose (HG) concentration of 30 mM. Results: LEO was found to improve DN and to attenuate the degree of glomerulosclerosis and tubular atrophy in the mouse model. Additionally, it markedly decreased the levels of ferroptosis markers. Molecular analyses revealed that LEO inhibited HG-induced oxidative stress in HUVECs, thereby decreasing endothelial cell (EC) dysfunction. Furthermore, LEO was found to reduce ferroptosis and reverse EC dysfunction by increasing the expression of glutathione peroxidase 4 (GPX4) and nuclear factor erythroid 2-related factor 2 (Nrf2). The suppression of Nrf2 in HG-induced HUVECs inhibited LEO-GPX4 axis-mediated ferroptosis and increased EC dysfunction. Conclusions: LEO exerts anti-DN effects both in vivo and in vitro by suppressing GPX4-mediated EC ferroptosis. Mechanistically, LEO appears to induce Nrf2-mediated GPX4 expression to inhibit ferroptosis, thereby reducing EC dysfunction. This study provides a new perspective on the treatment of diseases using natural medicines. It involves a novel form of cell death that could potentially lead to better treatment of DN.

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal disease with poor survival rates, primarily due to the limited effectiveness of gemcitabine (Gem)-based chemotherapy, as well as the acquisition of chemotherapeutic resistance. Aronia berry extracts (ABEs), abundant in phenolic constituents, have been recently recognized for their anticancer properties as well as their encouraging potential to help overcome chemoresistance in various cancers. In the present study, we explored ABE’s potential to overcome Gem resistance in PDAC and identify specific growth regulatory pathways responsible for its anticancer activity. Through a series of in vitro experiments in gemcitabine-resistant (Gem-R) cells, we elucidated the synergistic interactions between Gem and ABE treatments. Using advanced transcriptomic analysis and network pharmacology, we revealed key molecular pathways linked to chemoresistance and potential therapeutic targets of ABE in Gem-R PDAC cells. Subsequently, the findings from cell culture studies were validated in patient-derived 3D tumor organoids (PDOs). The combination treatment of ABE and Gem demonstrated significant synergism and anticancer effects on cell viability, proliferation, migration, and invasion in Gem-R cells. Transcriptomic analysis revealed a correlation between the NF-Κb signaling pathway and Gem-R (p < 0.05), exhibiting a marked upregulation of MYD88. Additionally, MYD88 exhibited a significant correlation with the overall survival rates in patients with PDAC patients in the TCGA cohort (HR = 1.58, p < 0.05). The MYD88/NF-Κb pathway contributes to chemoresistance by potentially upregulating efflux transporters like P-glycoprotein (P-gp). Our findings revealed that the combined treatment with ABE suppressed the NF-Κb pathway by targeting MYD88 and reducing P-gp expression to overcome Gem resistance. Lastly, the combination therapy proved highly effective in PDOs in reducing both their number and size (p < 0.05). Our study offers previously unrecognized insights into the ability of ABE to overcome Gem resistance in PDAC cells through its targeting of the MYD88/NF-κb/P-gp axis, hence providing a safe and cost-effective adjunctive therapeutic strategy to improve treatment outcomes in PDAC.

The deteriorating soil health under continuous monoculture is commonly found across various cropping systems. This study evaluated the effects of different tillage practices (conventional tillage and no till) and species mixtures (legumes and grasses) on arbuscular mycorrhizal fungi (AMF) community properties, soil nutrients, and enzyme activity in a 3-year experiment. Compared with traditional tillage, the number of AMF species under no-till conditions was increased, with the Glomus group being dominant. Under different tillage conditions, TN (total N) and AN (available N) contents under no till were significantly higher than those under conventional tillage, while no significant differences among other nutrients were found. The activities of soil acid phosphatase (S-ACP), soil dehydrogenase (S-DHA), and soil sucrose (S-SC) under conventional tillage were significantly higher than those under no till, and the cover crop mixtures also had an exclusive advantage in yield. Soil organic matter (SOM) indicated a significant negative correlation with glomalin-related soil protein (GRSP). The increase in diversity associated with the AMF species community was strongly correlated with the increase in three enzyme activities, and AN was negatively correlated with all species. Tillage did not significantly change soil chemistry, except for AN, and the high concentration of AN led to a decrease in AMF species. The results of this study showed that no till was an effective measure for enriching soil micro-organism population. Additionally, soil AMF diversity was improved by cover crop mixtures, and microbial diversity was higher than that under monoculture cover crops. Different AMF groups responded differently to tillage and cover crop mixtures. Across all mixtures, the combination of hairy vetch (Vicia villosa R.) and ryegrass (Lolium perenne L.) performed the best.

Deep neural networks have played a crucial role in the field of deep learning, achieving significant success in practical applications. The architecture of neural networks is key to their performance. In the past few years, these architectures have been manually designed by experts with rich domain knowledge. Additionally, the optimal neural network architecture can vary depending on specific tasks and data distributions. Neural Architecture Search (NAS) is a class of techniques aimed at automatically searching for and designing neural network architectures according to the given tasks and data. Specifically, evolutionary-computation-based NAS methods are known for their strong global search capability and have aroused widespread interest in recent years. Although evolutionary-computation-based NAS has achieved success in a wide range of research and applications, it still faces bottlenecks in training and evaluating a large number of individuals during optimization. In this study, we first devise a multi-objective evolutionary NAS framework based on a weight-sharing supernet to improve the search efficiency of traditional evolutionary-computation-based NAS. This framework combines the population optimization characteristic of evolutionary algorithms with the weight-sharing ideas in one-shot models. We then design a bi-population MOEA/D algorithm based on the proposed framework to effectively solve the NAS problem. By constructing two sub-populations with different optimization objectives, the algorithm can effectively explore network architectures of various sizes in complex search spaces. An inter-population communication mechanism further enhances the algorithm’s exploratory capability, enabling it to find network architectures with uniform distribution and high diversity. Finally, we conduct performance comparison experiments on image classification datasets of different scales and complexities. Experimental results demonstrate the effectiveness of the proposed multi-objective evolutionary NAS framework and the practicality and transferability of the introduced bi-population MOEA/D-based NAS method compared to existing state-of-the-art NAS methods.

We proposed a novel method for predicting the service life of optical cables based on the Autoformer model combined with the calculation method. Leveraging historical weather data from Guangzhou and employing specific cable length calculation techniques, our study comprehensively considers factors impacting cable lifespan. Moreover, through comparative analysis with alternative deep learning models and parameter assessments, our method validates the superiority and stability of the Autoformer model in predicting cable lifespan, which can offer a more reliable approach for ensuring cable technology reliability and the management of associated industries.

With the development of natural gas pipelines, the proportion of aged pipelines in service has been increasing, and corrosion remains a primary cause of pipeline failure. Regular inspections and reliability assessments are crucial to ensure the safe operation of pipelines. This study investigated an efficient reliability assessment method for corroded pipelines that considers in-line inspection intervals. First, this study compared the commonly used limit state equations for corrosion defects to select one suitable for X80-grade steel pipelines. Additionally, a Tail-Fit Monte Carlo Simulation (TF-MCS) algorithm was proposed to improve the computational speed by 30 times compared to traditional Monte Carlo simulations. Then, this study explored the inspection intervals used for reliability assessments of corroded pipelines. Finally, the parameter sensitivity was analyzed considering the yield strength, maximum operating pressure, and pipe diameter. This study ensures the reliable operation of corroded gas pipelines.

Alkaline coal mine drainage represents one of the most critical issues in the coal industry, driven by complex hydro-biogeochemical processes. However, the interplay of hydrogeochemical and biogeochemical interactions in alkaline coal mine drainage is still poorly understood. To this end, water samples were systematically collected from alkaline coal mine drainage sites from five coal mining areas in Chongqing coal mining district, located in southwestern China. Hydrogeochemical analyses showed that the main water type of the coal mine drainage sample was HCO3-SO4~K-Na, which primarily originated from local meteoric water. The microbial community compositions in the studied alkaline coal drainage were critically associated with sulfate, bicarbonate, DOC, nitrate, and pH, and linked to three putative keystone genera via network analysis (Thiothrix, Methylophilaceae_MM1, and an unclassified genus from Comamonadaceae family). Functional predictions from FAPROTAX suggested a high abundance of metabolic pathways involving the oxidation of sulfide and sulfur compounds, potentially underscoring their importance in controlling sulfate enrichment in alkaline coal mine drainage. Interestingly, members of the Methylomonadaceae family (methanotrophs) and the Methylotenera genus (methylotrophs) had positive Spearman correlations with both ammonium and sulfate, potentially inferring that the enhanced activities of methanotrophs might help capture methane in the alkaline coal mine drainage. This study further enhances our comprehension of the intricate interplay between hydrogeochemical and biogeochemical interactions in alkaline coal mine drainage, contributing to the carbon budget.

Microbial and enzymatic stoichiometry have been widely used to reflect microbial nutrient limitations. However, the dominant drivers of microbial and enzymatic C:N:P ratios are not well known, which hinders our understanding of whether microbial and enzymatic stoichiometry can accurately reflect microbial resource limitation. Here, we studied vertical patterns (0–100 cm) of factors influencing microbial and enzymatic C:N:P ratios in five forest ecosystems (one tropical, two subtropical, and two temperate) in southwestern China. Our results showed that microbial and enzymatic C:P were not regulated by soil C:P, while N: P followed the same pattern. This suggests microbial resource status is weakly related to microbial and enzymatic C:N:P ratios and that understanding stoichiometry may be inadequate to disentangle nutritional limitations. Soil C:N affected microbial and enzymatic C:N:P ratios likely by altering microbial community structure in all soil horizons. Overall, our study highlighted the important role of soil C:N in regulating C, N, and P cycles, and challenged current methods for modeling microbial nutrient limitations.

Background The number of newly reported older (≥50 years old) people living with HIV/AIDS in China has been steadily increasing, and heterosexual transmission has been identified as the major route.Methods In this study, based on biopsychosocial model, a case–control study (74 cases vs 296 controls) was applied to find out predictors (21 potential ones) of HIV infection among older men from rural China. Binary logistic regression with backward selection was applied.Results Out of 21 potential predictors of HIV infection, 4 were confirmed: receiving HIV-related health education (HRHE) (OR 0.449, 95% CI 0.238 to 0.848), self-reported homosexual identity (16.517 (95% CI 1.073 to 254.182)), visiting female sex workers (FSW) (58.427 (95% CI 7.895 to 432.403)), complete non-overlap of intimate social network and sexual network (2.912 (95% CI 1.372 to 6.177)), partial overlap (3.334 (95% CI 1.536 to 7.236)).Discussion Findings from this study suggest current comprehensive prevention and control services need to be strengthened to provide effective HRHE including condom use to older men and help them to improve condom use, especially during visiting FSW and among self-reported homosexual older men. Moreover, increasing intimacy in their sexual relationships is necessary.

Background: In general, the identification of cholesterol-depleted lipid particles can be inferred from non-high-density lipoprotein cholesterol (non-HDL-C) concentration to apolipoprotein B (apoB) concentration ratio, which serves as a reliable indicator for assessing the risk of cardiovascular disease. However, the ability of non-HDL-C/apoB ratio to predict the risk of long-term mortality among the general population remains uncertain. The aim of this study is to explore the association of non-HDL-C/apoB ratio with long-term all-cause and cardiovascular mortality in adults of the United States. Methods: This retrospective cohort study was a further analysis of existing information from the National Health and Nutrition Examination Survey (NHANES). In the ultimate analysis, 12,697 participants from 2005 to 2014 were included. Kaplan-Meier (K-M) curves and the log-rank test were applied to visualize survival differences between groups. Multivariate Cox regression and restricted cubic spline (RCS) models were applied to evaluate the association of non-HDL-C/apoB ratio with all-cause and cardiovascular mortality. Subgroup analysis was conducted for the variables of age, sex, presence of coronary artery disease, diabetes and hypertriglyceridemia and usage of lipid-lowering drugs. Results: The average age of the cohort was 46.8 ± 18.6 years, with 6215 (48.9%) participants being male. During a median follow-up lasting 68.0 months, 891 (7.0%) deaths were documented and 156 (1.2%) patients died of cardiovascular disease. Individuals who experienced all-cause and cardiovascular deaths had a lower non-HDL-C/apoB ratio compared with those without events (1.45 ± 0.16 vs. 1.50 ± 0.17 and 1.43 ± 0.17 vs. 1.50 ± 0.17, both P values

IntroductionUltrasound has become a routine method for endometrial receptivity (ER) evaluation. However, there is controversy over the independent evaluation values of various ultrasound indicators. Some researchers have designed multi-indicator prediction systems, but their prediction values are uneven. To further our understanding of ER, we conducted this prospective cohort study to estimate ER noninvasively and effectively.MethodsWomen who underwent the first frozen–thawed embryo transfer (FET) cycle from April 2019 to July 2021 were included in the study. On the day of transfer, transvaginal three-dimensional ultrasound examination was performed to evaluate ER, including endometrial thickness, morphology, volume, movement, blood flow and flow index. The clinical pregnancy rate was the primary outcome. Based on whether clinical pregnancy was achieved, enrolled patients were divided into pregnant and nonpregnant groups.ResultsThis study analyzed 197 FET patients (139 pregnancies in total, 70.5%). The protective factors for clinical pregnancy included primary infertility [adjusted odds ratio (aOR), 1.98; 95% confidence interval (CI), 1.01–3.882; p = 0.047] and more frequent endometrial peristalsis (aOR, 1.33; 95% CI, 1.028–1.722; p = 0.03). Scores of 1–2 were assigned according to the relationship between different ultrasound indicators and the clinical pregnancy rate (CPR). The ER score of the patient was the sum of the scores of the 6 items. The ER score of the pregnant group was significantly higher than that of the nonpregnant group (7.40 ± 1.73 vs. 6.33 ± 1.99, p = 0.001). The CPR increased with an increasing ER score. The CPR in the ER 6 group (45.5% vs. 75.6%, p = 0.001).ConclusionA noninvasive ultrasound scoring system for ER was proposed. This system may provide a non-invasive guidance perspective, in conjunction with invasive assessments currently used in clinical practice, to achieve more effective embryo transfer.

Lung diseases have become a major threat to human health worldwide. Despite advances in treatment and intervention in recent years, effective drugs are still lacking for many lung diseases. As a traditional natural medicine, Tibetan medicine has had a long history of medicinal use in ethnic minority areas, and from ancient times to the present, it has a good effect on the treatment of lung diseases and has attracted more and more attention. In this review, a total of 586 Tibetan medicines were compiled through literature research of 25 classical works on Tibetan medicine, drug standards, and some Chinese and English databases. Among them, 33 Tibetan medicines have been studied to show their effectiveness in treating lung diseases. To investigate the uses of these Tibetan medicines in greater depth, we have reviewed the ethnomedicinal, phytochemical and pharmacological properties of the four commonly used Tibetan medicines for lung diseases (rhodiola, gentian, sea buckthorn, liexiang dujuan) and the five most frequently used Tibetan medicines (safflower, licorice, sandalwood, costus, myrobalan). It is expected to provide some reference for the development of new drugs of lung diseases in the future.

ABSTRACTCRISPR-Cas technology has widely been applied to detect single-nucleotide mutation and is considered as the next generation of molecular diagnostics. We previously reported the combination of nucleic acid amplification (NAA) and CRISPR-Cas12a system to distinguish major severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants. However, the mixture of NAA and CRISPR-Cas12a reagents in one tube could interfere with the efficiency of NAA and CRISPR-Cas12a cleavage, which in turn affects the detection sensitivity. In the current study, we employed a novel photoactivated CRISPR-Cas12a strategy integrated with recombinase polymerase amplification (RPA) to develop one-pot RPA/CRISPR-Cas12a genotyping assay for detecting SARS-CoV-2 Omicron sub-lineages. The new system overcomes the potential inhibition of RPA due to early CRISPR-Cas12a activation and cleavage of the target template in traditional one-pot assay using photocleavable p-RNA, a complementary single-stranded RNA to specifically bind crRNA and precisely block Cas12a activation. The detection can be finished in one tube at 39℃ within 1 h and exhibits a low limit of detection of 30 copies per reaction. Our results demonstrated that the photocontrolled one-pot RPA/CRISPR-Cas12a assay could effectively identify three signature mutations in the spike gene of SARS-CoV-2 Omicron variant, namely, R346T, F486V, and 49X, and distinguish Omicron BA.1, BA.5.2, and BF.7 sub-lineages. Furthermore, the assay achieved a sensitivity of 97.3% and a specificity of 100.0% and showed a concordance of 98.3% with Sanger sequencing results.IMPORTANCEWe successfully developed one-pot recombinase polymerase amplification/CRISPR-Cas12a genotyping assay by adapting photocontrolled CRISPR-Cas technology to optimize the conditions of nucleic acid amplification and CRISPR-Cas12a-mediated detection. This innovative approach was able to quickly distinguish severe acute respiratory syndrome coronavirus 2 Omicron variants and can be readily modified for detecting any nucleic acid mutations. The assay system demonstrates excellent clinical performance, including rapid detection, user-friendly operations, and minimized risk of contamination, which highlights its promising potential as a point-of-care testing for wide applications in resource-limiting settings.

Due to its advantages of having a high power-to-weight ratio and being energy-efficient, the electro-hydraulic servo pump control system (abbreviated as EHSPCS) is frequently employed in the industrial field, such as the electro-hydraulic servo pump control (EHSPC) servomotor for steam turbine valve regulation control. However, the EHSPCS has strong nonlinearity and time-varying features, and the factors that cause system performance degradation are complex. Once a system failure occurs, it may lead to serious accidents, causing serious casualties and economic losses. To address the above issues, a system health assessment method based on LSTM-GRNN-ANN (LGA) deep neural network is proposed in this paper. Firstly, with oil volume gas content, servo motor air-gap flux density, and system leakage coefficient as the health assessment performance indicators, a health assessment performance index system for the EHSPCS is built, Furthermore, the system performance index threshold is set. Secondly, an LGA deep neural network is constructed by combining LSTM, GRNN and ANN, and a deep neural network based on the LGA is used to create an EHSPCS health assessment model. Subsequently, system feature parameter extraction, algorithm design, and parameter debugging are carried out. Finally, an EHSPCS experimental platform is established, typical system failure simulation experiments are designed, and comparative experimental analysis is conducted. The experimental findings demonstrate that the average accuracy of the system health assessment model based on the LGA deep neural network suggested in this paper is 96.37%, compared to 89.84%, 87.99% for LSTM and GRNN, which validates the accuracy of the system health assessment model based on the LGA deep neural network.

Background: Contrast retention (CR) is an important predictor of left atrial appendage thrombus (LAAT) and stroke in patients with non-valvular atrial fibrillation (AF). We sought to explore the underlying mechanisms of CR using computational fluid dynamic (CFD) simulations. Methods: A total of 12 patients with AF who underwent both cardiac computed tomography angiography (CTA) and transesophageal echocardiography (TEE) before left atrial appendage occlusion (LAAO) were included in the study. The patients were allocated into the CR group or non-CR group based on left atrial appendage (LAA) angiography. Patient-specific models were reconstructed to evaluate time-averaged wall shear stress (TAWSS), oscillatory shear index (OSI), relative residence time (RRT), and endothelial cell activation potential (ECAP). Additionally, the incidence of thrombosis was predicted using residence time (RT) at different time-points. Results: TAWSS was lower [median (Interquartile Range) 0.27 (0.19–0.47) vs 1.35 (0.92–1.79), p

Yellow tea is a lightly fermented tea with unique sensory qualities and health benefits. However, chemical composition and sensory quality of yellow tea products have rarely been studied. 12 representative yellow teas, which were basically covered the main products of yellow tea, were chosen in this study. Combined analysis of non-targeted/targeted metabolomics and electronic sensor technologies (E-eye, E-nose, E-tongue) revealed the chemical and sensor variation. The results showed that yellow big tea differed greatly from yellow bud teas and yellow little teas, but yellow bud teas could not be effectively distinguished from yellow little teas based on chemical constituents and electronic sensory characteristics. Sensor variation of yellow teas might be attributed to some compounds related to bitterness and aftertaste-bitterness (4′-dehydroxylated gallocatechin-3-O-gallate, dehydrotheasinensin C, myricitin 3-O-galactoside, phloroglucinol), aftertaste-astringency (methyl gallate, 1,5-digalloylglucose, 2,6-digalloylglucose), and sweetness (maltotriose). This study provided a comprehensive understanding of yellow tea on chemical composition and sensory quality.

As the economy continues to develop and technology advances, there is an increasing societal need for an environmentally friendly ecosystem. Consequently, natural gas, known for its minimal greenhouse gas emissions, has been widely adopted as a clean energy alternative. The accurate prediction of short-term natural gas demand poses a significant challenge within this context, as precise forecasts have important implications for gas dispatch and pipeline safety. The incorporation of intelligent algorithms into prediction methodologies has resulted in notable progress in recent times. Nevertheless, certain limitations persist. However, there exist certain limitations, including the tendency to easily fall into local optimization and inadequate search capability. To address the challenge of accurately predicting daily natural gas loads, we propose a novel methodology that integrates the adaptive particle swarm optimization algorithm, attention mechanism, and bidirectional long short-term memory (BiLSTM) neural networks. The initial step involves utilizing the BiLSTM network to conduct bidirectional data learning. Following this, the attention mechanism is employed to calculate the weights of the hidden layer in the BiLSTM, with a specific focus on weight distribution. Lastly, the adaptive particle swarm optimization algorithm is utilized to comprehensively optimize and design the network structure, initial learning rate, and learning rounds of the BiLSTM network model, thereby enhancing the accuracy of the model. The findings revealed that the combined model achieved a mean absolute percentage error (MAPE) of 0.90% and a coefficient of determination (R2) of 0.99. These results surpassed those of the other comparative models, demonstrating superior prediction accuracy, as well as exhibiting favorable generalization and prediction stability.

Fibroblast-like synoviocytes (FLS) are important components of the synovial membrane. They can contribute to joint damage through crosstalk with inflammatory cells and direct actions on tissue damage pathways in rheumatoid arthritis (RA). Recent evidence suggests that, compared with FLS in normal synovial tissue, FLS in RA synovial tissue exhibits significant differences in metabolism. Recent metabolomic studies have demonstrated that metabolic changes, including those in glucose, lipid, and amino acid metabolism, exist before synovitis onset. These changes may be a result of increased biosynthesis and energy requirements during the early phases of the disease. Activated T cells and some cytokines contribute to the conversion of FLS into cells with metabolic abnormalities and pro-inflammatory phenotypes. This conversion may be one of the potential mechanisms behind altered FLS metabolism. Targeting metabolism can inhibit FLS proliferation, providing relief to patients with RA. In this review, we aimed to summarize the evidence of metabolic changes in FLS in RA, analyze the mechanisms of these metabolic alterations, and assess their effect on RA phenotype. Finally, we aimed to summarize the advances and challenges faced in targeting FLS metabolism as a promising therapeutic strategy for RA in the future.

Abstract Organic donor‐acceptor semiconductors exhibit great potential in photothermal conversion. However, it is still challenging to achieve pure organic materials with broad absorption comparable with inorganic materials such as graphene. Herein, two D‐A‐D type DPA‐BT‐O4 and NDI‐TPA‐O4 and three D‐A‐π‐A‐D type Th‐O4, Th2‐O4, and IDT‐O4 were readily prepared via two high‐yield steps and simple air oxidization. The stability can be attributed to their multiple resonance structures based on the aromatic nitric acid radical mechanism. Compared with the D‐A‐D radicals, the conjugation extension of the D‐A‐π‐A‐D radicals endows them with a narrowed band gap and broad absorption in powder. Interestingly, the IDT‐O4 powder with aggregation‐induced radical effect exhibits broad absorption between 300 and 2500 nm, which is comparable with graphene and other inorganic materials. Under irradiation of 0.9 W/cm2 (808 nm), the temperature of IDT‐O4 powder rises to 250°C within 60 s. The water evaporation conversion efficiency of 94.38 % and an evaporation rate of 1.365 kg/m2 h−1 under one sun illumination were achieved. IDT‐O4 stands as one of the most efficient photothermal conversion materials among pure organic materials via a rational design strategy.

Introduction: Pre-diabetes, a high-risk metabolic state, is situated between normal glucose homeostasis and diabetes. Early identification of pre-diabetes offers opportunities for intervention and diabetes reversal, highlighting the crucial need to investigate reliable biomarkers for this condition.Methods: We conducted an in-depth bioinformatics analysis of clinical samples from non-diabetic (ND), impaired glucose tolerance (IGT), and type 2 diabetes mellitus (T2DM) categories within the GSE164416 dataset. Thereafter the HFD and STZ treated mice were used for validation.Results: This analysis identified several codifferentially expressed genes (Co-DEGs) for IGT and T2DM, including CFB, TSHR, VNN2, APOC1, CLDN2, SLPI, LCN2, CXCL17, FAIM2, and REG3A. Validation of these genes and the determination of ROC curves were performed using the GSE76895 dataset. Thereafter, CLDN2 was selected for further verification. Gene expression analysis and immunofluorescence analysis revealed a significant upregulation of CLDN2 expression in the pancreas islets of mice in the high-fat diet and T2DM groups compared to the control group. Similarly, serum level of CLDN2 in patients with IGT and T2DM were significantly higher than those in the healthy group.Discussion: These results suggest that CLDN2 can serve as a novel biomarker for pre-diabetes, providing a new direction for future research in the prevention of type 2 diabetes.

ObjectiveTo investigate the diagnostic efficiency and prognostic value of 68Ga-Pentixafor PET/CT in comparison with adrenal vein sampling (AVS) for functional lateralization in primary aldosteronism (PA). Histology and long-term clinical follow-up normally serve as the gold standard for such diagnosis.MethodsWe prospectively recruited 26 patients diagnosed with PA. All patients underwent 68Ga-Pentixafor PET/CT and AVS. Postsurgical biochemical and clinical outcomes of patients with unilateral primary aldosteronism (UPA), as diagnosed by PET/CT or AVS, were assessed by applying standardized Primary Aldosteronism Surgical Outcome (PASO) criteria. Immunohistochemistry (IHC) was performed to detect the expression of aldosterone synthase (CYP11B2) and CXCR4.ResultsOn total, 19 patients were diagnosed with UPA; of these, 13 patients were lateralized by both PET/CT and AVS, four patients were lateralized by PET-only, and two by AVS-only. Seven subjects with no lateralization on AVS and PET received medical therapy. All patients achieved complete biochemical success except one with nodular hyperplasia lateralized by AVS alone. The consistency between PET/CT and AVS outcomes was 77% (20/26). Moreover, CYP11B2-positive nodules were all CXCR4-positive and showed positive findings on PET. Patients who achieved complete biochemical and clinical success had a higher uptake on PET as well as stronger expression levels of CXCR4 and CYP11B2.ConclusionOur analysis showed that 68Ga-Pentixafor PET/CT could enable non-invasive diagnosis in most patients with PA and identify additional cases of unilateral and surgically curable PA which could not be classified by AVS. 68Ga-Pentixafor PET/CT should be considered as a first-line test for the future classification of PA.

ObjectiveThis research aims to investigate whether peripheral biomarkers might differentiate individuals with Tourette syndrome (TS) from those without the condition.MethodsA broad range of databases was searched through November 2022. This study employed a systematic literature review and subsequent meta-analysis of case-control studies that assessed the aberration of biomarkers of patients with TS and controls.ResultsA total of 81 studies were identified, out of which 60 met the eligibility criteria for inclusion in the meta-analysis. Following a meticulous screening procedure to determine the feasibility of incorporating case–control studies into the meta-analysis, 13 comparisons were statistically significant [CD3+ T cell, CD4+ T cell, CD4+ T cell to CD8+ T cell ratio, NK-cell, anti-streptolysin O antibodies, anti-DNase antibodies, glutamic acid (Glu), aspartic acid (Asp), ferritin (Fe), zinc (Zn), lead (Pb), vitamin D, and brain-derived neurotrophic factor (BDNF)]. Publication bias was found for anti-streptolysin O antibodies. Suggestive associations were evidenced for norsalsolinol (NSAL), neuron-specific enolase (NSE), and S100B.ConclusionIn this study, we present empirical evidence substantiating the link between several peripheral biomarkers and the early diagnosis of TS. Larger and more standardized studies are necessary to replicate the observed results, elucidate the specificity of the biomarkers for TS, and evaluate their precision for use in clinical settings.

Background: Collagen represents a prominent constituent of the tumor’s extracellular matrix (ECM). Nonetheless, its correlation with the molecular subtype attributes of clear cell renal cell carcinoma (ccRCC) remains elusive. Our objective is to delineate collagen-associated molecular subtypes and further construct diagnostic model, offering insights conducive to the precise selection of ccRCC patients for immunotherapeutic interventions.Methods: We performed unsupervised non-negative matrix factorization (NMF) analysis on TCGA-KIRC samples, utilizing a set of 33 collagen-related differentially expressed genes (33CRDs) for clustering. Our analysis encompassed evaluations of subtype-associated differences in pathways, immune profiles, and somatic mutations. Through weighted gene co-expression network analysis (WGCNA) and four machine learning algorithms, two core genes were found and a diagnostic model was constructed. This was subsequently validated in a clinical immunotherapy cohort. Single cell sequencing analysis and experiments demonstrated the role of core genes in ccRCC. Finally, we also analyzed the roles of MMP9 and SCGN in pan-cancer.Results: We described two novel collagen related molecular subtypes in ccRCC, designated subtype 1 and subtype 2. Compared with subtype 1, subtype 2 showed more infiltration of immune components, but had a higher TIDE (tumor immunedysfunctionandexclusion) score and increased levels of immune checkpoint molecules. Furthermore, reduced prognosis for subtype 2 was a consistent finding in both high and low mutation load subgroups. MMP9 and SCGN were identified as key genes for distinguishing subtype 1 and subtype 2. The diagnostic model based on them could better distinguish the subtype of patients, and the differentiated patients had different progression free survival (PFS) in the clinical immunotherapy cohort. MMP9 was predominantly expressed in macrophages and has been extensively documented in the literature. Meanwhile, SCGN, which was overexpressed in tumor cells, underwent experimental validation, emphasizing its role in ccRCC. In various cancers, MMP9 and SCGN were associated with immune-related molecules and immune cells.Conclusion: Our study identifies two collagen-related molecular subtypes of ccRCC and constructs a diagnostic model to help select appropriate patients for immunotherapy.

Background In early adolescence, youth are highly prone to suicidal behaviours. Identifying modifiable risk factors during this critical phase is a priority to inform effective suicide prevention strategies.Aims To explore the risk and protective factors of suicidal behaviours (ie, suicidal ideation, plans and attempts) in early adolescence in China using a social-ecological perspective.Methods Using data from the cross-sectional project ‘Healthy and Risky Behaviours Among Middle School Students in Anhui Province, China’, stratified random cluster sampling was used to select 5724 middle school students who had completed self-report questionnaires in November 2020. Network analysis was employed to examine the correlates of suicidal ideation, plans and attempts at four levels, namely individual (sex, academic performance, serious physical illness/disability, history of self-harm, depression, impulsivity, sleep problems, resilience), family (family economic status, relationship with mother, relationship with father, family violence, childhood abuse, parental mental illness), school (relationship with teachers, relationship with classmates, school-bullying victimisation and perpetration) and social (social support, satisfaction with society).Results In total, 37.9%, 19.0% and 5.5% of the students reported suicidal ideation, plans and attempts in the past 6 months, respectively. The estimated network revealed that suicidal ideation, plans and attempts were collectively associated with a history of self-harm, sleep problems, childhood abuse, school bullying and victimisation. Centrality analysis indicated that the most influential nodes in the network were history of self-harm and childhood abuse. Notably, the network also showed unique correlates of suicidal ideation (sex, weight=0.60; impulsivity, weight=0.24; family violence, weight=0.17; relationship with teachers, weight=−0.03; school-bullying perpetration, weight=0.22), suicidal plans (social support, weight=−0.15) and suicidal attempts (relationship with mother, weight=−0.10; parental mental illness, weight=0.61).Conclusions This study identified the correlates of suicidal ideation, plans and attempts, and provided practical implications for suicide prevention for young adolescents in China. Firstly, this study highlighted the importance of joint interventions across multiple departments. Secondly, the common risk factors of suicidal ideation, plans and attempts were elucidated. Thirdly, this study proposed target interventions to address the unique influencing factors of suicidal ideation, plans and attempts.

Summary: n-3 polyunsaturated fatty acids (PUFAs) are closely related to the progression of numerous chronic inflammatory diseases, but the role of n-3 PUFAs in the intervertebral disc degeneration (IVDD) remains unclear. In this study, male C57BL/6 wildtype mice (WT group, n = 30) and fat-1 transgenic mice (TG group, n = 30) were randomly selected to construct the IVDD model. The results demonstrated that the optimized composition of PUFAs in the TG mice had a significant impact on delaying IVDD and cellular senescence of intervertebral disc (IVD). Mechanismly, n-3 PUFAs inhibited IVD senescence by alleviating NCOA4-mediated iron overload. NCOA4 overexpression promoted iron overload and weakened the pro-proliferation and anti-senescence effect of DHA on the IVD cells. Furthermore, this study futher revealed n-3 PUFAs downregulated NCOA4 expression by inactiviting the LGR5/β-catenin signaling pathway. This study provides an important theoretical basis for preventing and treating IVDD and low back pain.

Summary: As a primary target of severe acute respiratory syndrome coronavirus 2, lung exhibits heterogeneous histopathological changes following infection. However, comprehensive insight into their protein basis with spatial resolution remains deficient, which hinders further understanding of coronavirus disease 2019 (COVID-19)-related pulmonary injury. Here, we generate a region-resolved proteomic atlas of hallmark pathological pulmonary structures by integrating histological examination, laser microdissection, and ultrasensitive proteomics. Over 10,000 proteins are quantified across 71 post-mortem specimens. We identify a spectrum of pathway dysregulations in alveolar epithelium, bronchial epithelium, and blood vessels compared with non-COVID-19 controls, providing evidence for transitional-state pneumocyte hyperplasia. Additionally, our data reveal the region-specific enrichment of functional markers in bronchiole mucus plugs, pulmonary fibrosis, airspace inflammation, and alveolar type 2 cells, uncovering their distinctive features. Furthermore, we detect increased protein expression associated with viral entry and inflammatory response across multiple regions, suggesting potential therapeutic targets. Collectively, this study provides a distinct perspective for deciphering COVID-19-caused pulmonary dysfunction by spatial proteomics.

IntroductionRice (Oryza sativa L.) is a pivotal cereal crop worldwide. It relies heavily on the presence of iron plaque on its root surfaces for optimal growth and enhanced stress resistance across diverse environmental conditions.MethodTo study the crystallographic aspects of iron plaque formation on rice roots, the concentrations of Fe2+ and PO43- were controlled in this study. The effects of these treatments were assessed through comprehensive analyzes encompassing root growth status, root surface iron concentration, root vitality, enzyme activities, and microstructural characteristics using advanced techniques such as root analysis, scanning electron microscopy (SEM), and ultrathin section transmission electron microscopy (TEM).ResultsThe results demonstrated that an increase in the Fe2+ concentration or a decrease in the PO43- concentration in the nutrient solution led to improvements in various root growth indicators. There was an elevation in the DCB (dithionite-citrate–bicarbonate) iron content within the roots, enhanced root vitality, and a significant increase in the activities of the superoxide dismutase (SOD), peroxidase (POD) and catalase (CAT) enzymes. Moreover, as the Fe2+ concentration increased, amorphous iron oxide minerals on the root surface were gradually transformed into ferrihydrite particles with sizes of approximately 200 nm and goethite particles with sizes of approximately 5 μm. This study showed that an increase in the Fe2+ concentration and a decrease in the PO43- concentration led to the formation of substantial iron plaque on the root surfaces. It is noteworthy that there was a distinct gap ranging from 0.5 to 3 μm between the iron plaque formed through PO43- treatment and the cellular layer of the root surface.DiscussionThis study elucidated the impacts of Fe2+ and PO43- treatments on the formation, structure, and morphology of the iron plaque while discerning variations in the spatial proximity between the iron plaque and root surface under different treatment conditions.

With the development of industrial demand, precise identification of system models is currently required in the field of industrial control, which limits the whale search algorithm. In response to the fact that whale optimization algorithms are prone to falling into local optima and the identification of important Hammerstein models ignores the issue of noise outliers in actual industrial environments, this study improves the whale algorithm and constructs a Hammerstein model identification strategy for nonlinear systems under heavy-tailed noise using the improved whale algorithm. Results showed that it had a lower rank average and an average success rate of 95.65%. It found the global optimum when the number of iterations reached around 150 and had faster convergence speed and accuracy. In identifying Hammerstein model under heavy-tailed noise, the average prediction recognition accuracy of the improved whale algorithm was 92.38%, the determination coefficient was 0.89, the percentage fitting error was 0.03, and the system error was 0.02. This research achievement has certain value in the field of industrial control and can serve as a technical reference.

Digital reading has changed the traditional reading pattern, and it is popular among college students because of its portability, fast content update and rich presentation, but the phenomenon of shallow reading such as lack of concentration, lack of thinking and superficiality in the process of reading is also becoming more and more obvious. In this paper, we construct the model of college students’ reading ability based on RoBTANet model, construct the index system of college students’ reading ability evaluation based on the relationship structure between the main categories derived from the rooted coding, and finally design the model of college students’ reading ability evaluation to achieve the purpose of analyzing the results of college students’ reading ability evaluation. The scoring results correspond to the data of 59 initial concepts, 27 valid indicators, and 5 main categories of a student, which can be mapped to the reading ability of students through the various scores and provide effective countermeasures for the digital reading mode of college students. This paper effectively evaluates the reading ability of college students, broadens the application value and research field of RoBTANet model, actively explores the digital reading mode of college students, provides development ideas, and is important to promote the innovation and application of digital reading mode of college students.

Organ transplantation is the gold standard therapy for end-stage organ failure. However, the shortage of available grafts and long-term graft dysfunction remain the primary barriers to organ transplantation. Exploring approaches to solve these issues is urgent, and CRISPR/Cas9-based transcriptome editing provides one potential solution. Furthermore, combining CRISPR/Cas9-based gene editing with an ex vivo organ perfusion system would enable pre-implantation transcriptome editing of grafts. How to determine effective intervention targets becomes a new problem. Fortunately, the advent of high-throughput CRISPR screening has dramatically accelerated the effective targets. This review summarizes the current advancements, utilization, and workflow of CRISPR screening in various immune and non-immune cells. It also discusses the ongoing applications of CRISPR/Cas-based gene editing in transplantation and the prospective applications of CRISPR screening in solid organ transplantation.

The Monocyte chemoattractant protein-1 (MCP-1), also referred to as chemokine ligand 2 (CCL2), belongs to the extensive chemokine family and serves as a crucial mediator of innate immunity and tissue inflammation. It has a notable impact on inflammatory conditions affecting the kidneys. Upon binding to its receptor, MCP-1 can induce lymphocytes and NK cells’ homing, migration, activation, differentiation, and development while promoting monocytes’ and macrophages’ infiltration, thereby facilitating kidney disease-related inflammation. As a biomarker for kidney disease, MCP-1 has made notable advancements in primary kidney diseases such as crescentic glomerulonephritis, chronic glomerulonephritis, primary glomerulopathy, idiopathic proteinuria glomerulopathy, acute kidney injury; secondary kidney diseases like diabetic nephropathy and lupus nephritis; hereditary kidney diseases including autosomal dominant polycystic kidney disease and sickle cell kidney disease. MCP-1 not only predicts the occurrence, progression, prognosis of the disease but is also closely associated with the severity and stage of nephropathy. When renal tissue is stimulated or experiences significant damage, the expression of MCP-1 increases, demonstrating a direct correlation with the severity of renal injury.

In recent decades, climate change has significantly affected water quality and algal blooms in lakes worldwide. Studying the temporal dynamics patterns of algal production efficiency and its drivers in individual lakes is useful for analyzing the evolutionary trajectory of Chla-TP changes, and identifying the main controlling factors of eutrophication to guide lake management. In this study, we used a dataset for the Lake Gehu (1986–2020) to analyze the drivers of the ETP variability on interannual and seasonal time scales and to quantify the relative impacts and contributions of nutrient and climatic factors on the ETP. The results showed a negative correlation of the Chla-TP relationship appeared in years with very high ETP. The effects of nutritional and climatic factors on the ETP at different time scales were quantified using a generalized additive model. The results showed that the total phosphorus (TP) concentration had a significant effect on the interannual ETP variation, explaining up to 28.9 %. At the intra-annual scale, climatic variables had a much greater effect on the ETP than the nutrient concentration, and the explanatory effect was ranked as temperature > wind speed > rainfall > total nitrogen (TN). Based on the characteristics of seasonal ETP variations, the TPa of Lake Gehu were 50 μg/L, 33 μg/L, 20 μg/L with ETP levels of 0.2, 0.3, 0.5, respectively. This research highlights the significance of nutrient and climatic factors in interannual and seasonal scale, respectively. In addition, ETP influenced by the coupling of nutrient and climate provides a criterion for establishing the seasonal nutrient threshold of lakes.

Abstract The influence maximization problem is one of the most fundamental topics in social networks. However, most existing studies have focused on non-attributed networks, neglecting the consideration of users’ properties during information propagation. Additionally, specific scenarios may involve external queries that target a particular subset of users, which has not been adequately addressed in prior research. To address these limitations, this study first formulates the customized influence maximization (CIM) problem in the context of attributed social networks. The node score and influence probability are derived by fully considering the user’s attributes and the external queries. Then, we develop two algorithms to identify a group of most influential nodes in CIM. The first is a heuristic algorithm based on discounted degree, which is able to find relatively high-quality solutions in a short time. The second is a meta-heuristic algorithm, which makes several adjustments to the original ant colony algorithm to make it efficient to the CIM problem. Specifically, multiple CIM-related heuristics are derived, and a heuristic adaptation strategy is designed to automatically assign the heuristic information to ants according to the search environments and stages. Extensive experiments show the promising performance of our proposed algorithms in terms of accuracy, efficiency, and robustness.

Abstract Multimodal epigenetic characterization of cell-free DNA (cfDNA) could improve the performance of blood-based early cancer detection. However, integrative profiling of cfDNA methylome and fragmentome has been technologically challenging. Here, we adapt an enzyme-mediated methylation sequencing method for comprehensive analysis of genome-wide cfDNA methylation, fragmentation, and copy number alteration (CNA) characteristics for enhanced cancer detection. We apply this method to plasma samples of 497 healthy controls and 780 patients of seven cancer types and develop an ensemble classifier by incorporating methylation, fragmentation, and CNA features. In the test cohort, our approach achieves an area under the curve value of 0.966 for overall cancer detection. Detection sensitivity for early-stage patients achieves 73% at 99% specificity. Finally, we demonstrate the feasibility to accurately localize the origin of cancer signals with combined methylation and fragmentation profiling of tissue-specific accessible chromatin regions. Overall, this proof-of-concept study provides a technical platform to utilize multimodal cfDNA features for improved cancer detection.

Abstract Background Delayed healing of diabetic cutaneous wounds is one of the most common complications of type 2 diabetes mellitus (T2DM), which can bring great distress to patients. In diabetic patients, macrophages accumulate around skin wounds and produce NLRP3 (NOD-, LRR-, and pyrin domain-containing protein 3) inflammasomes, which in turn undergo pyroptosis and produce inflammatory factors such as interleukin-1β that affect wound healing. Although our previous study revealed that apoptotic extracellular vesicles (ApoEVs) produced from mesenchymal stem cells (MSCs) improve cutaneous wound healing in normal C57BL/6 mice, whether ApoEVs can also improve diabetic wound healing remains unclear. Methods Umbilical cord mesenchymal stem cells (UCMSCs) were cultured in vitro and apoptosis was induced. ApoEVs were extracted and identified and used in a T2DM mouse cutaneous wound model to evaluate the efficacy. The inhibitory effect of ApoEVs on macrophage pyroptosis was verified in vivo and in vitro, and the level of oxidative stress in macrophages was assessed to explore the mechanism by which ApoEVs play a role. Results UCMSC-derived ApoEVs improved skin defect healing in T2DM mice. Moreover, UCMSC-derived ApoEVs inhibited macrophage pyroptosis in T2DM mice in vivo as well as in vitro under high-glucose culture conditions. In addition, we demonstrated that ApoEVs reduce oxidative stress levels, which is a possible mechanism by which they inhibit macrophage pyroptosis. Conclusions Our study confirmed that local application of UCMSC-derived ApoEVs improved cutaneous wound healing in T2DM mice. ApoEVs, as products of MSC apoptosis, can inhibit macrophage pyroptosis and regulate the death process by decreasing the level of oxidative stress.

Abstract Architectural heritage is vulnerable to disasters. Digital technologies can fight destruction and can ensure integrity by monitoring, managing and protecting architectural heritage from disasters. In this paper, we clarify the relationship between disasters, digitalization and architectural heritage conservation for the sustainability of cultural heritage. This study used the PRISMA process, and bibliometric tools VOSviewer and Citespace to explore the potential of digital technologies in the protection of architectural heritage—especially during disaster cycles, from the perspectives of both universal and typicality; the results revealed that digital twins, deep learning, and preventive conservation are currently hot topics in digital preservation research (especially that research which relates to disaster cycles). On this basis, this paper summarizes the relevant technologies involved in architectural heritage preservation from the perspective of the disaster cycle and the digital phase, and proposes three future research directions: accurate prediction of multi-disasters, automatic early warning of structural damages, and intelligent monitoring of human–computer interaction. This paper constructs a new research frame for digital preservation of architectural heritage during disasters, providing theoretical reference and practical guidance for architectural heritage conversation.

Abstract Background Novel and effective immunotherapies are required for refractory or recurrent sarcomas. Transforming growth factor-beta (TGF-β) is a diverse regulatory and fibrogenic protein expressed in multiple sarcoma tumors that promotes epithelial-mesenchymal transition and excessive deposition of extracellular matrix. This study evaluated the efficacy and safety of the anti-PD-L1/TGF-β antibody TQB2858 in patients with refractory osteosarcoma and alveolar soft part sarcoma (ASPS). Methods This single-arm phase 1b exploratory study included patients with refractory osteosarcoma or ASPS who had previously undergone at least two lines of systemic therapy. Patients were administered 1200 mg of TQB2858 once every 3 weeks. The primary endpoint was objective response rate (ORR), with null and alternative hypotheses of ORR ≤5% and ≥20%, respectively. Exploratory biomarker analyses using immunohistochemistry (IHC) staining (for PD-L1 and TGF-β) were performed on pre-treatment tumor samples. Results Eleven eligible patients were included in this study. TQB2858 did not demonstrate evidence of efficacy as 0/5 osteosarcomas had any objective response, while 2/6 ASPS showed a partial response. The median progression-free survivals were 1.51 (1.38, Not Evaluable) and 2.86 (1.38, Not Evaluable) months for the osteosarcoma and ASPS groups, respectively. None of the administered cycles met the criteria for unacceptable toxicity. Other Grade 3 toxicities included abnormal liver function and elevation of γ-glutamyl transferase. IHC analysis revealed that functional enrichment in the TGF-β pathway or PD-L1 was not associated with treatment outcomes. Conclusions The combination of PD-L1 and TQB2858 did not significantly improve the ORR in patients with recurrent osteosarcoma. However, it improved immunogenic responses in ASPS, even after progression upon anti-PD-1/PD-L1 therapy, with an acceptable safety profile. IHC profiling with pathway enrichment analysis may not have any predictive value for survival outcomes. Trial registration Prospectively registered in the Ethical Review Committee of Peking University People’s Hospital. The trial registration number is 2021PHA105-001 and 2021PHA140-001 and the registration date was March 2, 2022. ClinicalTrials.gov Identifier CTR20213001 and CTR20220390

Abstract Highly-efficient molecular photoswitching occurs ex-situ but not to-date inside electronic devices due to quenching of excited states by background interactions. Here we achieve fully reversible in-situ mechano-optoelectronic switching in self-assembled monolayers (SAMs) of tetraphenylethylene molecules by bending their supporting electrodes to maximize aggregation-induced emission (AIE). We obtain stable, reversible switching across >1600 on/off cycles with large on/off ratio of (3.8 ± 0.1) × 103 and 140 ± 10 ms switching time which is 10-100× faster than other approaches. Multimodal characterization shows mechanically-controlled emission with UV-light enhancing the Coulomb interaction between the electrons and holes resulting in giant enhancement of molecular conductance. The best mechano-optoelectronic switching occurs in the most concave architecture that reduces ambient single-molecule conformational entropy creating artificially-tightened supramolecular assemblies. The performance can be further improved to achieve ultra-high switching ratio on the order of 105 using tetraphenylethylene derivatives with more AIE-active sites. Our results promise new applications from optimized interplay between mechanical force and optics in soft electronics.

Abstract Malignant pleural mesothelioma (MPM) is a malignant tumor originating from the pleura, and its incidence has been increasing in recent years. Due to the insidious onset and strong local invasiveness of MPM, most patients are diagnosed in the late stage and early screening and treatment for high‐risk populations are crucial. The treatment of MPM mainly includes surgery, chemotherapy, and radiotherapy. Immunotherapy and electric field therapy have also been applied, leading to further improvements in patient survival. The Mesothelioma Group of the Yangtze River Delta Lung Cancer Cooperation Group (East China LUng caNcer Group, ECLUNG; Youth Committee) developed a national consensus on the clinical diagnosis and treatment of MPM based on existing clinical research evidence and the opinions of national experts. This consensus aims to promote the homogenization and standardization of MPM diagnosis and treatment in China, covering epidemiology, diagnosis, treatment, and follow‐up.

Abstract Adenosine N1 methylation (m1A) of RNA, a type of post-transcriptional modification, has been shown to play a significant role in the progression of cancer. The objective of the current research was to analyze the genetic alteration and prognostic significance of m1A regulators in kidney renal clear cell carcinoma (KIRC). Genomic and clinicopathological characteristics were obtained from 558 KIRC patients in the Cancer Genome Atlas (TCGA) and Gene Omnibus Expression (GEO) databases. Alterations in the gene expression of ten m1A-regulators were analyzed and survival analysis was performed using the Cox regression method. We also identified three clusters of patients based on their distinct m1A alteration patterns, using integrated analysis of the ten m1A-related regulators, which were significantly related to overall survival (OS), disease-free survival (DFS) and tumor microenvironment (TME) immune cell infiltration cells in KIRC. Our findings showed that m1A alteration patterns have critical roles in determining TME complexity and its immune cell composition. Furthermore, different m1A expression patterns were significantly associated with DFS and OS rates in KIRC patients. In conclusion, the identified m1A RNA modification patterns offer a potentially effective way to classify KIRC patients based on their TME immune cell infiltration, enabling the development of more personalized and successful treatment strategies for these patients.

Objective Mechanical stress is an important risk factor for intervertebral disc degeneration (IVDD). Angiopoietin‐2 (ANG‐2) is regulated by mechanical stress and is widely involved in the regulation of extracellular matrix metabolism. In addition, the signaling cascade between HIF‐1α and NF‐κB is critical in matrix degradation. This study aims to investigate the role and molecular mechanism of ANG‐2 in regulating the degeneration of annulus fibrosus (AF) through the HIF‐1α/NF‐κB signaling pathway. Methods The bipedal standing mice IVDD model was constructed, and histological experiments were used to evaluate the degree of IVDD and the expression of ANG‐2 in the AF. Mouse primary AF cells were extracted in vitro and subjected to mechanical stretching experiments. Western blot assay was used to detect the effect of mechanical stress on ANG‐2, and the role of the ANG‐2‐mediated HIF‐1α/NF‐κB pathway in matrix degradation. In addition, the effect of inhibiting ANG‐2 expression by siRNA or monoclonal antibody on delaying IVDD was investigated at in vitro and in vivo levels. One‐way ANOVA with the least significant difference method was used for pairwise comparison of the groups with homogeneous variance, and Dunnett's method was used to compare the groups with heterogeneous variance. Results In IVDD, the expressions of catabolic biomarkers (mmp‐13, ADAMTS‐4) and ANG‐2 were significantly increased in AF. In addition, p65 expression was increased while HIF‐1α expression was significantly decreased. The results of western blot assay showed mechanical stress significantly up‐regulated the expression of ANG‐2 in AF cells, and promoted matrix degradation by regulating the activity of HIF‐1α/NF‐κB pathway. Exogenous addition of Bay117082 and CoCl2 inhibited matrix degradation caused by mechanical stress. Moreover, injection of neutralizing antibody or treatment with siRNA to inhibit the expression of ANG‐2 improved the matrix metabolism of AF and inhibited IVDD progression by regulating the HIF‐1α/NF‐κB signaling pathway. Conclusion In IVDD, mechanical stress could regulate the HIF‐1α/NF‐κB signaling pathway and matrix degradation by mediating ANG‐2 expression in AF degeneration.

Hydrogen storage is a key link in hydrogen economy, where solid-state hydrogen storage is considered as the most promising approach because it can meet the requirement of high density and safety. Thereinto, magnesium-based materials (MgH2) are currently deemed as an attractive candidate due to the potentially high hydrogen storage density (7.6 wt%), however, the stable thermodynamics and slow kinetics limit the practical application. In this study, we design a ternary transition metal sulfide FeNi2S4 with a hollow balloon structure as a catalyst of MgH2 to address the above issues by constructing a MgH2/Mg2NiH4-MgS/Fe system. Notably, the dehydrogenation/hydrogenation of MgH2 has been significantly improved due to the synergistic catalysis of active species of Mg2Ni/Mg2NiH4, MgS and Fe originated from the MgH2-FeNi2S4 composite. The hydrogen absorption capacity of the MgH2-FeNi2S4 composite reaches to 4.02 wt% at 373 K for 1 h, a sharp contrast to the milled-MgH2 (0.67 wt%). In terms of dehydrogenation process, the initial dehydrogenation temperature of the composite is 80 K lower than that of the milled-MgH2, and the dehydrogenation activation energy decreases by 95.7 kJ·mol–1 compared with the milled-MgH2 (161.2 kJ·mol–1). This method provides a new strategy for improving the dehydrogenation/hydrogenation performance of the MgH2 material.

Abstract Mutation-induced malfunction of ten-eleven translocation methylcytosine dioxygenase 2 (TET2) is widely reported in haematological malignancies. However, the role of TET2 in solid cancers, including colorectal cancer (CRC), is unclear. Here, we found that TET2 malfunction in CRC is mostly due to decreased nuclear localization and that nuclear localization of TET2 is correlated with better survival of patients. To explore the underlying mechanisms, 14 immortalized solid tumour cell lines and 12 primary CRC cell lines were used. TET2 was mostly detected in the nucleus, and it induced significant DNA demethylation and suppressed cell growth by demethylating RORA and SPARC in cell lines like SW480. While in cell lines like SW620, TET2 was observed in the cytosol and did not affect DNA methylation or cell growth. Further examination with immunoprecipitation–mass spectrometry illustrated that β-catenin activation was indispensable for the nuclear localization and tumour suppression effects of TET2. In addition, the β-catenin pathway activator IM12 and the TET2 activator vitamin C were used simultaneously to enhance the effects of TET2 under low-expression conditions, and synergistic inhibitory effects on the growth of cancer were observed both in vitro and in vivo. Collectively, these data suggest that β-catenin-mediated nuclear localization of TET2 is an important therapeutic target for solid tumours.

Abstract Background Insulin is commonly used in type 2 diabetes mellitus (T2DM) to achieve glycemic control. However, recent evidence showed that insulin use is associated with poor outcomes in the context of heart failure (HF). Since heart failure with reduced ejection fraction (HFrEF) accounts for approximately 50% of cases in the general HF population, we aimed to evaluate the effect of insulin treatment on left ventricular (LV) remodeling and contractility abnormalities in a HFrEF cohort and assess whether insulin was a predictor of adverse outcomes in this entity. Methods A total of 377 HFrEF patients who underwent cardiac MRI were included and divided according to diabetes status and the need for insulin treatment. LV structural and functional indices, as well as systolic strains, were measured. The determinants of impaired myocardial strains were assessed using linear regression analysis. The associated endpoints were determined using a multivariable Cox proportional hazards model. Results T2DM patients on insulin displayed a higher indexed LV end-diastolic volume and LV mass than those with T2DM not on insulin or those without T2DM, despite similar LV ejection fractions, accompanied by a higher three-dimensional spherical index (P

Abstract Background Recent insights suggest that remnant cholesterol (RC) plays a role in cellular senescence, yet its specific contribution to frailty remains indeterminate. Through the integration of observational and mendelian randomization (MR) studies, this research explores the impact of elevated serum RC levels on frailty susceptibility. Methods A dual-method approach, combining an observational study with an MR study, was employed to investigate the connection between RC and frailty. The observational study included 11,838 participants from the National Health and Nutrition Examination Survey. Multivariable logistic regression and propensity score matching were employed to control for potential confounders. The non-linear relationship was assessed using restricted cubic splines. To circumvent observational study limitations, a two-sample MR analysis was conducted using the inverse-variance weighted method, leveraging genome-wide association studies (GWAS) data. Results After adjusting for potential confounding variables, the observational study identified a significant association between high serum RC levels and frailty in middle-aged and older adults (odds ratio [OR] = 1.67, 95% confidence interval [CI] = 1.20 to 2.33, P = 0.003), exhibiting a non-linear dose–response correlation (non-linear P = 0.011). This association persisted after propensity score matching (OR = 1.53, 95% CI = 1.14 to 2.06, P = 0.005). The MR study echoed these results, demonstrating a causal association of RC with the frailty index (β = 0.059, 95% CI = 0.033 to 0.085, P = 1.05E-05), consistent with the observational findings (β = 0.017, 95% CI = 0.008 to 0.026, P = 4.51E-04). Conclusion This study provides evidence that higher RC levels amplify frailty risk in middle-aged and older adults, implying that the reduction of RC levels may present a promising strategy for frailty prevention and management.

Introduction: Oesophageal cancer is a prevalent and deadly cancer around the world. Objectives: We aimed to present a comprehensive analysis of the global geographic patterns and temporal trends in the mortality and incidence of oesophageal cancer. Methods: The mortality and incidence data of oesophageal cancer in 2020 were obtained from the GLOBOCAN database. Based on World Health Organization (WHO) mortality database and the Cancer Incidence in Five Continents (CI5), we also retrieved the mortality and incidence age-standardized rates (ASRs) of oesophageal cancer. The average annual percentage changes (AAPCs) of mortality and incidence were calculated using the joinpoint regression analysis. Results: Globally, 0.54 million deaths and 0.6 million new cases were identified in 2020. In the majority of countries of South America and Asia, the mortality and incidence trends have substantially decreased, but trends in European countries have varied. The prevalence in European nations varied, but the incidence in most other continents decreased dramatically. In terms of mortality, the global average rate was 5.6 per 100000, ranging from 16.7 (Malawi) to 0.28 (Belize). European countries varied in mortality, such as Norway (AAPC, male: 0.68; female: 0.89) and Ireland (AAPC, male: −0.96; female: −1.52). Most non-European countries saw large decreases in mortality, such as Singapore (AAPC, male: −4.78; female: −6.89). The elderly had more noticeable trends in mortality and incidence in most countries. Conclusions: We have identified different trends in mortality and incidence among European countries, whereas declining trends were identified in most non-European countries. However, increasing trends were identified in specific subgroups of some countries, such as men in Thailand. For populations with rising mortality and incidence trends, more preventative efforts are required.

Primary cilia are formed in nearly all growth-arrested cells and are essential for mammalian development and tissue homeostasis. Defects in primary cilia result in a range of disorders in humans, named ciliopathies. The spatiotemporal localization of RABIN8 on the pericentrosome is an early step in ciliogenesis. Here, we show that CENTLEIN depletion causes the persistent accumulation of RABIN8 on the pericentrosome and primary cilium loss in hTERT-immortalized retinal pigment epithelial cells and murine embryonic fibroblasts. CENTLEIN interacts with RABIN8 directly. A stretch of a 31-amino acid sequence located in the 200‒230 region of the RABIN8 GEF domain is responsible for its physical interaction with CENTLEIN, while expression of the full-length but not the internal deletion lacking the RABIN8-binding site of CENTLEIN largely rescues the ciliogenesis defect provoked by CENTLEIN depletion. Expression of activated RAB8A partially reverses cilium loss in CENTLEIN-null RPE1 cells, so the functional importance of the CENTLEIN-RABIN8 interaction is defined.

To establish a method for the determination of morpholine guanidine residues in lettuce, ultra performance liquid chromatography-tandem mass spectrometry and uncertainty evaluation of the established method were studied. After samples were extracted and purified, the morpholine guanidine was quantified by scanning with positive ions from an electrospray ionization source in multiple reaction monitoring mode. The uncertainty was synthesized by building a mathematical model to analyze the sources of measurement uncertainty and quantify each uncertainty component. The morpholinoguanidine showed a good line in the range of 0.1~20 mg/L with a correlation coefficient R2 of 0.999 3. The spiked recoveries at the three levels of 0.5, 5.0 and 10.0 μg/kg ranged from 84.08% to 98.06% (n=6) with the relative standard deviations of 3.58% to 5.26% (n=6), and the extended uncertainty was 2.84 μg/kg (k=2) at 95% confidence interval for the determination of morpholine guanidine in the sample at 17.5 μg/kg. The method was rapid and efficient, highly accurate and reproducible, and the recovery and precision can meet the test requirements. The uncertainty was mainly caused by the standard solution, the establishment of the standard curve and the recovery of the sample spiking. The experimental results could provide a reference for the determination of morpholine guanidine residues in lettuce by UPLC-MS/MS and the uncertainty evaluation.