Search

Abstract Obstructive hypertrophic cardiomyopathy (oHCM) is a subtype of HCM characterized by left ventricular outflow tract obstruction resulting from cardiac muscle hypertrophy and anatomic alterations in the mitral valve and apparatus. Mavacamten, a cardiac myosin inhibitor metabolized primarily by CYP2C19 in the liver, is the first and only targeted medication approved for the treatment of symptomatic New York Heart Association (NYHA) class II–III oHCM. Previous pharmacokinetic (PK) results of mavacamten in healthy Caucasian, Japanese, and Asian participants demonstrated that mavacamten exposure was affected by CYP2C19 metabolism status. This open‐label, parallel‐group, phase I trial aimed to determine the PK and safety of mavacamten in healthy Chinese participants with different CYP2C19 genotypes. The primary outcome was to define the PK of mavacamten in healthy Chinese participants; the secondary outcome was to examine safety and tolerability. After a single oral dose of 15 or 25 mg mavacamten in fasted healthy adult Chinese individuals, Cmax was reached within a median Tmax of 0.6–1.5 h, indicating rapid absorption. Inter‐individual variability was moderate, and individuals carrying non‐functional CYP2C19 alleles (*2/*2, *3/*3, or *2/*3) exhibited longer half‐life and increased total exposure. After stratification of CYP2C19 genotypes, total mavacamten exposures were similar among different ethnic groups when compared with prior PK studies. No significant adverse events were observed in this study. Single oral administration of mavacamten at 15 mg was well tolerated across all CYP2C19 genotypes, and 25 mg dose was well tolerated in healthy participants with CYP2C19 genotypes UM/RM/NM. The PK profile of mavacamten in the healthy Chinese population was consistent with that in other healthy populations.

IntroductionHerpes simplex keratitis (HSK) is a blinding disease caused by corneal infection of Herpes simplex virus type 1 (HSV-1). Effective clearance of HSV-1 from the infected cornea is crucial for HSK management. Macrophages play an important part in the innate immune defense against viral infections. This study investigates the immunomodulatory role of NLRP12 in macrophage immune response during HSV-1 infection.MethodsNLRP12 expression post-infection was assessed in various macrophage cell lines. Overexpression of NLRP12 was achieved by lentiviral transfection, and its effect on HSV-1 replication and immune responses were examined. Mechanistic insights into the role of NLRP12 were explored using immunofluorescence and Western Blot. For in vivo studies, ocular adoptive transfer of NLRP12-overexpressing bone marrow derived macrophages (BMDMs) was performed. HSV-1 viral loads, HSK symptoms, and macrophage-mediated immune responses were investigated.ResultsA significant decrease in NLRP12 expression post-infection was observed in various macrophage cell lines. Overexpression of NLRP12 in macrophages reduced HSV-1 replication. Mechanistically, overexpression of NLRP12 triggered early and robust pyroptosis in response to HSV-1 infection, inducing interleukin (IL)-18 production and activating downstream antiviral responses through the JAK-STAT signaling pathway. In vivo, ocular adoptive transfer of NLRP12-overexpressing BMDMs to mouse corneas alleviated HSK damage and reduced HSV-1 viral loads. NLRP12-overexpressing BMDMs improved antiviral responses in the cornea and promoted the maturation of corneal-infiltrating macrophages and dendritic cells. Additionally, NLRP12-overexpressing BMDMs amplified the adaptive immune response in the submandibular draining lymph nodes.DiscussionThese findings highlight the role of NLRP12 in macrophage-mediated immune response against HSV-1 infection and suggest its potential for possible immunotherapy for HSK.

Alzheimer’s disease (AD) has an increasing prevalence, complicated pathogenesis and no effective cure. Emerging evidences show that flavonoid compounds such as xanthohumol (Xn) could play an important role as a dietary supplement or traditional Chinese herbal medicine in the management of diseases such as AD. This study aims to analyze the target molecules of Xn in the prevention and treatment of AD, and its potential mechanism from the perspective of metabolites. APP/PS1 mice 2- and 6-months old were treated with Xn for 3 months, respectively, the younger animals to test for AD-like brain disease prevention and the older animals to address therapeutic effects on the disease. Memantine (Mem) was selected as positive control. Behavioral tests were performed to assess the course of cognitive function. Urine samples were collected and analyzed by high-performance liquid chromatography (HPLC) with tandem mass spectrometry (MS/MS) coupled with online Compound Discoverer software. Morris Water Maze (MWM) tests showed that Xn, like Mem, had a therapeutic but not a preventive effect on cognitive impairment. The expression levels of urinary metabolites appeared to show an opposite trend at different stages of Xn treatment, downregulated in the prevention phase while upregulated in the therapy phase. In addition, the metabolic mechanisms of Xn during preventive treatment were also different from that during therapeutic treatment. The signaling pathways metabolites nordiazepam and genistein were specifically regulated by Xn but not by Mem in the disease prevention stage. The signaling pathway metabolite ascorbic acid was specifically regulated by Xn in the therapeutic stage. In conclusion, dietary treatment with Xn altered the urinary metabolite profile at different stages of administration in APP/PS1 mice. The identified potential endogenous metabolic biomarkers and signal pathways open new avenues to investigate the pathogenesis and treatment of AD.

BackgroundCarotid atherosclerosis (CAS) is a significant risk factor for cardio-cerebrovascular events. The objective of this study is to employ stacking ensemble machine learning techniques to enhance the prediction of CAS occurrence, incorporating a wide range of predictors, including endocrine-related markers.MethodsBased on data from a routine health check-up cohort, five individual prediction models for CAS were established based on logistic regression (LR), random forest (RF), support vector machine (SVM), extreme gradient boosting (XGBoost) and gradient boosting decision tree (GBDT) methods. Then, a stacking ensemble algorithm was used to integrate the base models to improve the prediction ability and address overfitting problems. Finally, the SHAP value method was applied for an in-depth analysis of variable importance at both the overall and individual levels, with a focus on elucidating the impact of endocrine-related variables.ResultsA total of 441 of the 1669 subjects in the cohort were finally diagnosed with CAS. Seventeen variables were selected as predictors. The ensemble model outperformed the individual models, with AUCs of 0.893 in the testing set and 0.861 in the validation set. The ensemble model has the optimal accuracy, precision, recall and F1 score in the validation set, with considerable performance in the testing set. Carotid stenosis and age emerged as the most significant predictors, alongside notable contributions from endocrine-related factors.ConclusionThe ensemble model shows enhanced accuracy and generalizability in predicting CAS risk, underscoring its utility in identifying individuals at high risk. This approach integrates a comprehensive analysis of predictors, including endocrine markers, affirming the critical role of endocrine dysfunctions in CAS development. It represents a promising tool in identifying high-risk individuals for the prevention of CAS and cardio-cerebrovascular diseases.

BackgroundAcute appendicitis (AA) is one of the most prevalent acute abdominal diseases and appendectomy is the definitive treatment of appendicitis. However, whether appendicitis and appendectomy cause colorectal cancer (CRC) is controversial. The results of observational studies are contradictory, but randomized controlled trials (RCT) cannot be conducted.MethodsData of appendectomy, AA, and CRC were obtained from the IEU Open GWAS project. We selected several Genome-wide association studies (GWAS) summary statistics for CRC: statistics for colon cancer (CC) were obtained from MRC-IEU and Neale lab, respectively; statistics for rectum cancer (RC) were obtained from MRC-IEU and FinnGen, respectively; statistics for CRC were provided by Sakaue S et al. Mendelian randomization (MR) was used to evaluate the causal relationships between exposure and outcomes. Inverse variance weighting (IVW) was the most important analysis method. Meta-analysis was used to summarize the results of IVW to increase the reliability and sensitivity analysis was used to evaluate the robustness of the results.ResultsAccording to the results of IVW, appendectomy did not increase risk of CC: MRC-IEU (OR:1.009, 95%CI:0.984-1.035, P=0.494), Neale lab (OR:1.016, 95%CI:0.993-1.040, P=0.174); Appendectomy also did not increase risk of RC: MRC-IEU(OR:0.994, 95%CI:0.974-1.014, P=0.538), FinnGen(OR:2.791, 95%CI:0.013-580.763, P=0.706); Appendectomy also did not increase risk of CRC: Sakaue S(OR:1.382, 95%CI:0.301-6.352, P=0.678). Appendicitis did not increase risk of CC: MRC-IEU(OR:1.000, 95%CI:0.999-1.001, P=0.641), Neale lab(OR:1.000, 95%CI:1.000-1.001, P=0.319); Appendicitis also did not increase risk of RC: MRC-IEU(OR:1.000, 95%CI:0.999-1.000, P=0.361), FinnGen(OR:0.903, 95%CI:0.737-1.105, P=0.321); Appendicitis also did not increase risk of CRC: Sakaue S (OR:1.018, 95%CI:0.950-1.091, P=0.609). The results of Meta-analysis also showed appendectomy (P=0.459) and appendicitis (P=0.999) did not increase the risk of CRC.ConclusionsAppendectomy and appendicitis do not increase the risk of colorectal cancer. More clinical trials are needed in the future to verify the causal relationships.

BackgroundUnderstanding and mapping the distribution of sandflies and sandfly-associated pathogens (SAPs) is crucial for guiding the surveillance and control effort. However, their distribution and the related risk burden in China remain poorly understood.MethodsWe mapped the distribution of sandflies and SAPs using literature data from 1940 to 2022. We also mapped the human visceral leishmaniasis (VL) cases using surveillance data from 2014 to 2018. The ecological drivers of 12 main sandfly species and VL were identified by applying machine learning, and their distribution and risk were predicted in three time periods (2021-2040, 2041-2060, and 2061-2080) under three scenarios of climate and socioeconomic changes.ResultsIn the mainland of China, a total of 47 sandfly species have been reported, with the main 12 species classified into three clusters according to their ecological niches. Additionally, 6 SAPs have been identified, which include two protozoa, two bacteria, and two viruses. The incidence risk of different VL subtypes was closely associated with the distribution risk of specific vectors. The model predictions also revealed a substantial underestimation of the current sandfly distribution and VL risk. The predicted areas affected by the 12 major species of sandflies and the high-risk areas for VL were found to be 37.9-1121.0% and 136.6% larger, respectively, than the observed range in the areas. The future global changes were projected to decrease the risk of mountain-type zoonotic VL (MT-ZVL), but anthroponotic VL (AVL) and desert-type zoonotic VL (DT-ZVL) could remain stable or slightly increase.ConclusionsCurrent field observations underestimate the spatial distributions of main sandfly species and VL in China. More active surveillance and field investigations are needed where high risks are predicted, especially in areas where the future risk of VL is projected to remain high or increase.

Background: Non-alcoholic steatohepatitis (NASH), an escalating global health concern, is a primary factor behind cirrhosis, liver transplantation, and hepatocellular carcinoma. Effective treatments remain elusive. Danggui-Shaoyao-San (DGSY), a classic famous prescription employed in treating NASH, could hold promise, although its molecular underpinnings are still under investigation. This study undertakes an exploration of the impacts of DGSY on NASH and seeks to illuminate the mechanisms at play. Methods: UHPLC-Q-Orbitrap HRMS was employed to identify compounds within DGSY. Mice underwent a 25-week regimen of HFHC diet and high-sugar water, with 4 weeks of DGSY treatment for efficacy and pathogenic mechanism exploration in vivo. L02 cells were cultured with 0.2 mM FFA for 24 h, exposed to DGSY at 1 mg/ml and 2 mg/ml for efficacy and pathogenic mechanism exploration in vitro. Using online databases, we sought potential targets for NASH treatment, and through PPI networks, identified key targets. Expression levels of genes and proteins were examined by western blotting, RT-PCR, and immunofluorescence staining. Results: Thirty-four compounds were identified within DGSY. DGSY brought about marked reductions in biochemical indicators and yielded significant improvements in NASH mice histological features. Additionally, it mitigated hepatic steatosis and inflammation both in vivo and in vitro. The top 10 targets from two network pharmacology analyses, one focusing on structural prediction and the other on literature mining, identified APOE and APP as potential therapeutic targets for DGSY in NASH treatment. PCR validation confirmed that DGSY reduced APP expression after treatment, and further investigation revealed that DGSY significantly suppressed hepatic APP and Aβ expression, indicating its effectiveness in treating NASH. Furthermore, it inhibited Aβ-induced Cathepsin B lysosomal release, reducing hepatic inflammation. Conclusion: Danggui-Shaoyao-San has anti-steatohepatitis effects in ameliorating hepatic APP protein expression, reducing hepatic lysosomal CTSB release, and suppressing hepatic NF-κB activation. The study provided a more theoretical basis for the future clinical application of DGSY.

Summary: The oxidative-stress-related protein Kelch-like ECH-associated protein 1 (KEAP1) is a substrate articulator of E3 ubiquitin ligase, which plays an important role in the ubiquitination modification of proteins. However, the function of KEAP1 in breast cancer and its impact on the survival of patients with breast cancer remain unclear. Our study demonstrates that KEAP1, a positive prognostic factor, plays a crucial role in regulating cell proliferation, apoptosis, and cell cycle transition in breast cancer. We investigate the underlying mechanism using human tumor tissues, high-throughput detection technology, and a mouse xenograft tumor model. KEAP1 serves as a key regulator of cellular metabolism, the reprogramming of which is one of the hallmarks of tumorigenesis. KEAP1 has a significant effect on mitochondrial biogenesis and oxidative phosphorylation by regulating HSPA9 ubiquitination and degradation. These results suggest that KEAP1 could serve as a potential biomarker and therapeutic target in the treatment of breast cancer.

To explore the spatiotemporal evolution characteristics of heat vulnerability in the Pearl River Delta urban agglomeration during heatwave disasters, this research employs the Entropy Weight Method (EWM) to calculate the heat vulnerability assessment results for nine cities in the region spanning from 2001 to 2022. Through the application of kernel density estimation, Moran's I, and the Geographically and Temporally Weighted Regression (GTWR) model, which is proven to be superior to traditional model such as OLS, this study analyzes the dynamic distribution patterns of heat vulnerability in the study area and dissect the trends of influencing factors. The results reveal that from 2001 to 2022, the overall heat vulnerability index in the study area demonstrates a fluctuating downward trend. Key contributors to heat vulnerability include high-frequency and long-duration heatwaves, population sensitivity, and changes in residents' consumption levels. Throughout this period of development, the disparity in heat vulnerability among cities has gradually widened, indicating an overall pattern of uneven development in the region. Future attention should be focused on formulating heat adaptation strategies in areas with high vulnerability to enhance the overall sustainability of the study area.

Light‐emitting diodes (LEDs) are widely used in lighting and display applications. Carbon quantum dots (CQDs), which have high biocompatibility, high resistance to photobleaching, and full‐spectrum luminescence, have inherent advantages as fluorescent materials for LED devices. Herein, multicolor CQDs are prepared by a new reagent engineering strategy due to the difference of effective conjugate length and the surface electron‐withdrawing groups of CQDs. White CQDs are realized by mixing blue, green, and red CQDs proportionally. Then, the aggregation‐caused quenching phenomenon of CQDs is suppressed through the hydrogen‐bonding network of cellulose nanofibrils (CNFs). Multicolor fluorescent films are prepared from CQDs and CNFs by simple mixing and casting methods. Finally, thin‐film encapsulation based on the photosensitive resin ABPE‐10 coating can be realized and rapidly assembles into fluorescent films with different light‐emitting colors into LED devices, leading to have superior thermal performance compared with conventional LEDs. White LEDs have excellent white‐light illumination performance, with Commission Internationale de L’Eclairage color coordinates of (0.33, 0.37), a correlated color temperature of 5688 K, and a color rendering index of 86. This strategy provides a convenient and scalable pathway for low‐cost, environmentally friendly, and high‐performance CQDs‐based LEDs.

The triglyceride-glucose index (TyGI) is a novel indicator of insulin resistance, which has been associated with an increased risk of cardiovascular diseases. The aim of this meta-analysis was to determine the association between TyGI and the prognosis of patients with heart failure (HF). Cohort studies relevant to the aim of the meta-analysis were retrieved by searching electronic databases, including PubMed, Web of Science, and Embase. A random-effects model was used to combine the data, incorporating the influence of between-study heterogeneity. Twelve studies involving 20,639 patients with HF were included. Pooled results showed that compared to patients with the lowest category of TyGI at baseline, those with the highest TyGI index were associated with a higher risk of all-cause mortality during follow-up (relative risk [RR] 1.71, 95% confidence interval [CI] 1.46 - 2.00; P < 0.001; I² = 55%). Sensitivity analyses limited to studies after adjustment for confounding factors showed similar results (RR 1.89, 95% CI 1.67 - 2.21; P < 0.001; I² = 13%). Subsequent meta-analyses also showed that a high TyGI at baseline was related to the incidence of cardiovascular death (RR 1.87, 95% CI 1.42 - 2.47; P < 0.001; I² = 57%), HF rehospitalization (RR 1.33, 95% CI 1.04 - 1.69; P < 0.02; I² = 46%), and major adverse cardiovascular events (RR 1.69, 95% CI 1.39 - 2.06; P < 0.001; I² = 17%) during follow-up. In conclusion, a high TyGI may be associated with a poor clinical prognosis for patients with HF.

Summary: This study investigated host responses to long COVID by following up with 89 of the original 144 cohorts for 1-year (N = 73) and 2-year visits (N = 57). Pulmonary long COVID, characterized by fibrous stripes, was observed in 8.7% and 17.8% of patients at the 1-year and 2-year revisits, respectively, while renal long COVID was present in 15.2% and 23.9% of patients, respectively. Pulmonary and renal long COVID at 1-year revisit was predicted using a machine learning model based on clinical and multi-omics data collected during the first month of the disease with an accuracy of 87.5%. Proteomics revealed that lung fibrous stripes were associated with consistent down-regulation of surfactant-associated protein B in the sera, while renal long COVID could be linked to the inhibition of urinary protein expression. This study provides a longitudinal view of the clinical and molecular landscape of COVID-19 and presents a predictive model for pulmonary and renal long COVID.

PurposeThe purpose of this study is to investigate the impact of negative urgency on implicit mobile phone addiction tendency among college freshmen, and to observe whether social exclusion situations affect the relationship between negative urgency and implicit mobile phone addiction tendency.MethodsThe UPPS-P Impulsive Behavior Scale was used to screen 575 freshmen from a certain university. The experiment utilized a GO/NO-GO paradigm. Experiment 1 employed a 2 (negative urgency group: high negative urgency group, low negative urgency group) × 2 (word type: phone related words, phone non-related words) two-factor mixed experimental design. Experiment 2 employed a 2 (negative urgency group: high negative urgency group, low negative urgency group) × 2 (social exclusion type: priming group, non-priming group) × 2 (word type: phone related words, phone non-related words) three-factor mixed experimental design.ResultsExperiment 1 results showed a significant main effect of negative urgency group and a significant interaction effect between negative urgency group and word type. Experiment 2 results demonstrated a significant main effect of negative urgency group and a significant main effect of social exclusion type. There was a significant interaction effect between word type and social exclusion type, as well as between word type and negative urgency group. The three-way interaction effect among negative urgency group, word type, and social exclusion type was significant.ConclusionCollege freshmen with high negative urgency exhibit a higher tendency toward implicit mobile phone addiction. In social exclusion situations, college freshmen show a higher tendency toward implicit smartphone addiction. Social exclusion situations and negative urgency jointly influence the implicit mobile phone addiction tendency of college freshmen.

Accurate wheat ear counting is one of the key indicators for wheat phenotyping. Convolutional neural network (CNN) algorithms for counting wheat have evolved into sophisticated tools, however because of the limitations of sensory fields, CNN is unable to simulate global context information, which has an impact on counting performance. In this study, we present a hybrid attention network (CTHNet) for wheat ear counting from RGB images that combines local features and global context information. On the one hand, to extract multi-scale local features, a convolutional neural network is built using the Cross Stage Partial framework. On the other hand, to acquire better global context information, tokenized image patches from convolutional neural network feature maps are encoded as input sequences using Pyramid Pooling Transformer. Then, the feature fusion module merges the local features with the global context information to significantly enhance the feature representation. The Global Wheat Head Detection Dataset and Wheat Ear Detection Dataset are used to assess the proposed model. There were 3.40 and 5.21 average absolute errors, respectively. The performance of the proposed model was significantly better than previous studies.

To investigate the parameter characteristics of permanent magnet synchronous motor (PMSM) speed sensorless vector control system and capture the noise matrices quickly and accurately in the speed estimation process of the extended Kalman filter for PMSM, The recursive least square method with forgetting factor is proposed to determine the actual parameters of the system, and then a new variable-scale chaotic particle swarm optimization (VCPSO) algorithm is put forward to accurately obtain the system noise matrix and the measurement noise matrix. The simulation results show that noise matrix optimization of extended Kalman filter by employing VCPSO algorithm under actual motor parameters is better than those employing standard PSO or chaotic PSO algorithms with faster speed and higher accuracy.

Aortic graft infection is an uncommon but highly fatal complication. Correct diagnosis and timely treatment are somewhat challenging. This study presents a case report of successful recognition and treatment of this complication.

In contemporary times, tumors have emerged as the primary cause of mortality in the global population. Ongoing research has shed light on the significance of neurotransmitters in the regulation of tumors. It has been established that neurotransmitters play a pivotal role in tumor cell angiogenesis by triggering the transformation of stromal cells into tumor cells, modulating receptors on tumor stem cells, and even inducing immunosuppression. These actions ultimately foster the proliferation and metastasis of tumor cells. Several major neurotransmitters have been found to exert modulatory effects on tumor cells, including the ability to restrict emergency hematopoiesis and bind to receptors on the postsynaptic membrane, thereby inhibiting malignant progression. The abnormal secretion of neurotransmitters is closely associated with tumor progression, suggesting that focusing on neurotransmitters may yield unexpected breakthroughs in tumor therapy. This article presents an analysis and outlook on the potential of targeting neurotransmitters in tumor therapy.

Organophosphorus compounds (OPs) are widely used as flame retardants (FRs) and plasticizers, yet strategies for comprehensively screening of suspect OPs in environmental samples are still lacking. In this work, a neoteric, robust, and general suspect screening technique was developed to identify novel chemical exposures by use of ultra-high performance liquid chromatography-Q Exactive hybrid quadrupole-Orbitrap high resolution mass spectrometry (UHPLC-Q-Orbitrap HRMS). We firstly established a suspect chemical database which had 7,922 OPs with 4,686 molecular formulas, and then conducted suspect screening in n = 50 indoor dust samples, n = 76 sediment samples, and n = 111 water samples. By use of scoring criteria such as retention time prediction models, we successfully confirmed five compounds by comparison with their authentic standards, and prioritized three OPs candidates including a nitrogen/fluorine-containing compound, that is dimethyl {1H-indol-3-yl[3-(trifluoromethyl)anilino]methyl} phosphonate (DMITFMAMP). Given that the biodegradation half-life values in water (t1/2,w) of DMITFMAMP calculated by EPI Suite is 180 d, it is considered to be potentially persistent. This strategy shows promising potential in environmental pollution assessment, and can be expected to be widely used in future research.

This study focuses on developing a water-in-oil-in-water (W1/O/W2) double emulsion system using high-intensity ultrasound (HIU)-treated pea protein isolate (HIU-PPI) and pectin to encapsulate Lactobacillus plantarum (L. plantarum). The effects of ultrasound treatment on pea protein isolate (PPI) characteristics such as solubility, particle size, emulsification, surface hydrophobicity, and surface free sulfhydryl group were examined, determining optimal HIU processing conditions was 400 W for 10 min. The developed W1/O/W2 double emulsion system based on HIU-PPI demonstrated effective encapsulation and protection of L. plantarum, especially at the HIU-PPI concentration of 4 %, achieving an encapsulation efficiency of 52.65 %. Incorporating both HIU-PPI and pectin as emulsifiers increased the particle size and significantly enhanced the emulsion’s viscosity. The highest bacterial encapsulation efficiency of the emulsion, 59.94 %, was attained at a HIU to pectin concentration ratio of 3:1. These emulsions effectively encapsulate and protect L. plantarum, with the concentration of HIU-PPI being a critical factor in enhancing probiotic survival under simulated gastrointestinal digestion. However, the concurrent utilization of pectin and HIU-PPI as emulsifiers did not provide a notable advantage compared to the exclusive use of HIU-PPI in enhancing probiotic viability during in vitro simulated digestion. This research offers valuable perspectives for the food industry on harnessing environmentally friendly, plant-based proteins as emulsifiers in probiotic delivery systems. It underscores the potential of HIU-modified pea protein and pectin in developing functional food products that promote the health benefits of probiotics.

Copper (Cu) contamination represents a persistent and significant form of heavy metal pollution in agricultural ecosystems, posing serious threats to organisms in current society. Spiders serve as crucial biological indicators for assessing the impact of heavy metals-induced toxicity. However, the specific molecular responses of spiders to Cu exposure and the mechanisms involved are not well understood. In our study, the wolf pond spiders, Pirata subpiraticus, were exposed to Cu for 21 d, resulting in a notable decline in survival rates compared with the control (n = 50, p < 0.05). We observed an increased expression of enzymes like glutathione peroxidase and superoxide dismutase (p < 0.05), signaling a strong oxidative stress response crucial for counteracting the harmful effects of reactive oxygen species. This response was corroborated by a rise in malondialdehyde levels (p < 0.05), a marker of lipid peroxidation and oxidative damage. Transcriptomic and metabolomic analyses revealed 2004 differentially expressed genes (DEGs) and 220 metabolites (DEMs). A significant number of these DEGs were involved in the glutathione biosynthetic process and antioxidant activity. A conjoint analysis revealed that under the Cu stress, several important enzymes and metabolites were altered (e.g., cathepsin A, legumain, and lysosomal acid lipase), affecting the activities of key biological processes and components, such as lysosome and insect hormone biosynthesis. Additionally, the protein interaction network analysis showed an up-regulation of processes like the apoptotic process, glutamate synthase activity, and peroxisome, suggesting that spiders activate cellular protective strategies to cope with stress and maintain homeostasis. This study not only deepens our understanding of spider biology in the context of environmental stress but also makes a significant contribution to the field of environmental stress biology.

Developing an efficient photocatalytic system for hydrogen peroxide (H2O2) activation in Fenton-like processes holds significant promise for advancing water purification technologies. However, challenges such as high carrier recombination rates, limited active sites, and suboptimal H2O2 activation efficiency impede optimal performance. Here we show that single-iron-atom dispersed Bi2WO6 monolayers (SIAD-BWOM), designed through a facile hydrothermal approach, can offer abundant active sites for H2O2 activation. The SIAD-BWOM catalyst demonstrates superior photo-Fenton degradation capabilities, particularly for the persistent pesticide dinotefuran (DNF), showcasing its potential in addressing recalcitrant organic pollutants. We reveal that the incorporation of iron atoms in place of tungsten within the electron-rich [WO4]2− layers significantly facilitates electron transfer processes and boosts the Fe(II)/Fe(III) cycle efficiency. Complementary experimental investigations and theoretical analyses further elucidate how the atomically dispersed iron induces lattice strain in the Bi2WO6 monolayer, thereby modulating the d-band center of iron to improve H2O2 adsorption and activation. Our research provides a practical framework for developing advanced photo-Fenton catalysts, which can be used to treat emerging and refractory organic pollutants more effectively.

Objective Machine learning has been widely applied in the fields of collapse, landslide and debris flow susceptibility analysis. The selection of nonhazard samples is a key issue in landslide susceptibility analysis. Traditional random sampling and manual labelling methods may involve randomness and subjectivity. Methods In view of the potential randomness and representativeness of noncollapse samples, this paper considered soil collapse susceptibility evaluation a positive-unlabelled (PU) learning problem and proposes a two-step convolutional neural network framework (ISpy-CNN) that combines an information value model and the Spy technique. First, 15 collapse-related factors were selected for modelling based on the geomorphological, geological, hydrological, and artificial environmental conditions of the study area. Low-information-value samples that were able to map the distribution structure of noncollapsing samples were screened by the information value model. Then, through the Spy technique and training the CNN model, negative samples with high confidence were identified from low-information-value samples that were classified as noncollapsed samples. Finally, based on the framework and traditional random sampling, we used support vector machine (SVM) and random forest (RF) models to compare and verify the reliability, prediction accuracy and data sensitivity of the proposed learning framework and other models. Results The results illustrate that the proposed ISpy-CNN method can improve the accuracy, F1 value, sensitivity and specificity on the validation set by 6.82%, 6.82%, 6.82%, 8.23%, respectively compared to random sampling and 2.86%, 2.89%, 2.86%, 2.31%, respectively compared to the traditional Spy technique. The prediction accuracy of step 2 in PU learning using the CNN model is higher than that of the RF and SVM models. The sample set screened by the ISpy-CNN framework exhibited greater stability, prediction accuracy and growth rate than those screened by the traditional Spy technique by adding the same number of training samples. Conclusion The ISpy-CNN framework proposed in this paper can better assist in the selection of nonhazard samples and real collapse spatial distribution maps, and the results of the framework are more consistent with the actual collapse distributions.

In order to explore the fracturing characteristics of coalbed methane wells in the Tunlan block, the No.2 coal seam in the Tunlan block, Xishan, Taiyuan was taken as the research object. The fracturing characteristics of the coal seams from multiple scales was studied through geological cataloguing, macroscopic characterization of coal samples and CT (Computed Tomography) analysis for four coal bed methane wells of XST-167, XST-168, XST-176 and XST-177, which were exposed at the coal mining face. The results shown that, the coal seam near the wells in the study area were mainly distributed with “X” type fractured fractures consisting of diagonally intersecting fractures, and there were “T” type fractured fractures near the XST-177 coalbed methane well. Collision and friction of quartz sand with fractured fracture walls produced pulverized coal, which filled in the fracture and hindered the output of coalbed methane. By comparing the drill holes exposed by the two coalbed methane wells of XST-168 and XST-177, it was found that the fracturing effect of the XST-177 coalbed methane well was better and more conductive to the output of coalbed methane. Most of the coals near coalbed methane wells were fragmented and crushed coal, and hydraulic fracturing destroyed the original structure of coal, which reduced the hardness of coal and significantly increased the cracks. Embedded quartz sand can be observed on some of the coal samples, which was mainly concentrated on the bedding surface, indicating that the quartz sand, after being pressed into the coal seam, mainly extended into the seam along the horizontal fracture, which was consistent with the direction of the maximum principal stress. By CT scanning technology, the coal samples affected by fracturing (fractured coal) and not affected by fracturing (normal coal) were scanned. It was found that, the fractures with a width greater than 100 μm in the fractured coals of T1 and T2 accounted for 58.8% and 48.5% of the total fracture volume, and the numbers of the fractures was 23407 and 19679, respectively. In normal coal T3, the fractures with width greater than 100 μm only accounted for 1.7% of the total fracture volume, and the number of fractures was only 3504. The width of the fractures in T1 and T2 was wider and the number of fractures was more than that in T3, which indicated that the width and number of fractures in the coal sample were significantly increased by the fracturing action, and the pores and fractures in the fractured coal were more developed.

Emerging research suggests a potential association of progression of Alzheimer's disease (AD) with alterations in synaptic currents and mitochondrial dynamics. However, the specific associations between these pathological changes remain unclear. In this study, we utilized Aβ42-induced AD rats and primary neural cells as in vivo and in vitro models. The investigations included behavioural tests, brain magnetic resonance imaging (MRI), liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) analysis, Nissl staining, thioflavin-S staining, enzyme-linked immunosorbent assay, Golgi-Cox staining, transmission electron microscopy (TEM), immunofluorescence staining, proteomics, adenosine triphosphate (ATP) detection, mitochondrial membrane potential (MMP) and reactive oxygen species (ROS) assessment, mitochondrial morphology analysis, electrophysiological studies, Western blotting, and molecular docking. The results revealed changes in synaptic currents, mitophagy, and mitochondrial dynamics in the AD models. Remarkably, intervention with Dengzhan Shengmai (DZSM) capsules emerged as a pivotal element in this investigation. Aβ42-induced synaptic dysfunction was significantly mitigated by DZSM intervention, which notably amplified the frequency and amplitude of synaptic transmission. The cognitive impairment observed in AD rats was ameliorated and accompanied by robust protection against structural damage in key brain regions, including the hippocampal CA3, primary cingular cortex, prelimbic system, and dysgranular insular cortex. DZSM intervention led to increased IDE levels, augmented long-term potential (LTP) amplitude, and enhanced dendritic spine density and length. Moreover, DZSM intervention led to favourable changes in mitochondrial parameters, including ROS expression, MMP and ATP contents, and mitochondrial morphology. In conclusion, our findings delved into the realm of altered synaptic currents, mitophagy, and mitochondrial dynamics in AD, concurrently highlighting the therapeutic potential of DZSM intervention.

Abstract Objective To evaluate the early and mid-term outcomes of open repair in patients with thoracoabdominal aortic aneurysm (TAAA) after thoracic endovascular aortic repair (TEVAR). Methods This was a retrospective single center study. Data were retrospectively collected and analyzed for consecutive patients undergoing open TAAA repair (TAAAR) after TEVAR from November 2016 to June 2021. Indications for TAAAR included aneurysm progression due to endoleak, persisted false lumen perfusion, proximal/distal disease progression, and aorta rupture. The risk factor of operative mortality was analyzed by multivariable logistic regression model and the survival was evaluated by Kaplan–Meier. Results Sixty-three patients who met the inclusion criteria for the study were identified. The mean age at TAAAR was 41 ± 12 years and 43 (68.3%) were male. Marfan syndrome (MFS) was presented in 39 patients (61.9%). 60 (95.2%) patients presented with post-dissection aneurysm and 3 (4.8%) patients with degenerative aneurysm. The extent of TAAA was Crawford I in 9 (14.3%), II in 22 (34.9%), III in 23 (36.5%), and IV in 9 (14.3%). Emergent TAAAR was done in 10 (15.9%) patients, and deep hypothermic circulatory arrest was used in 22 (34.6%). Endograft was explanted in 31 (49.2%). Operative mortality was 11 (17.5%). Stroke, paraplegia, and acute kidney failure occurred in 5 (7.9%), 7 (11.1%), and 6 (9.5%) patients, respectively. Pulmonary complications occurred in 19 (30.2%) patients. The estimated survival was 74.8 ± 4.9% at 5 years. Late reoperations were performed in 2 patients at 2.5 years and 1.3 years, respectively. Conclusions In this series of TAAA after TEVAR, TAAAR was related with a high risk of operative mortality and morbidity and the midterm outcomes represented a durable treatment and were respectable.

Abstract Bronchopulmonary dysplasia (BPD) is a chronic lung disease characterized by retarded alveolarization. Tenascin-C (TN-C), an extracellular matrix glycoprotein and soluble molecule, is involved in tissue morphogenesis. In the present study, we demonstrated that the level of TN-C in lung tissues was greater in a mouse model of BPD induced by 85% oxygen. TN-C deficiency, however, impaired alveolarization in the hyperoxia-induced BPD model. In contrast, a functional TN-C blocking antibody ameliorated alveolar dysplasia in BPD-like mice. Mechanistically, hyperoxia increased the soluble TN-C (sTN-C) released from respiratory epithelial cells. On one hand, low-dose sTN-C promoted lung epithelial cell proliferation and migration, which was mediated by ICAM-1. On the other hand, high-dose sTN-C hindered the proliferation and migration of epithelial cells. Overall, this study revealed that TN-C plays a dual role in lung alveolarization and that TN-C may be a target in BPD therapy.

Abstract Background Small RNAs are essential for germ cell development and fertilization. However, fundamental questions remain, such as the level of conservation in small RNA composition between species and whether small RNAs control transposable elements in mammalian oocytes. Results Here, we use high-throughput sequencing to profile small RNAs and poly(A)-bearing long RNAs in oocytes of 12 representative vertebrate species (including 11 mammals). The results show that miRNAs are generally expressed in the oocytes of each representative species (although at low levels), whereas endo-siRNAs are specific to mice. Notably, piRNAs are predominant in oocytes of all species (except mice) and vary widely in length. We find PIWIL3-associated piRNAs are widespread in mammals and generally lack 3′-2′-O-methylation. Additionally, sequence identity is low between homologous piRNAs in different species, even among those present in syntenic piRNA clusters. Despite the species-specific divergence, piRNAs retain the capacity to silence younger TE subfamilies in oocytes. Conclusions Collectively, our findings illustrate a high level of diversity in the small RNA populations of mammalian oocytes. Furthermore, we identify sequence features related to conserved roles of small RNAs in silencing TEs, providing a large-scale reference for future in-depth study of small RNA functions in oocytes.

Abstract Homologous protein search is one of the most commonly used methods for protein annotation and analysis. Compared to structure search, detecting distant evolutionary relationships from sequences alone remains challenging. Here we propose PLMSearch (Protein Language Model), a homologous protein search method with only sequences as input. PLMSearch uses deep representations from a pre-trained protein language model and trains the similarity prediction model with a large number of real structure similarity. This enables PLMSearch to capture the remote homology information concealed behind the sequences. Extensive experimental results show that PLMSearch can search millions of query-target protein pairs in seconds like MMseqs2 while increasing the sensitivity by more than threefold, and is comparable to state-of-the-art structure search methods. In particular, unlike traditional sequence search methods, PLMSearch can recall most remote homology pairs with dissimilar sequences but similar structures. PLMSearch is freely available at https://dmiip.sjtu.edu.cn/PLMSearch .

Abstract Background Metarhizium rileyi is an important entomopathogenic fungus which has a wide range of host pests. In this work, the virulence of M. rileyi EFNL-08 against 3rd instar larvae of the fall armyworm, Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae), was quantified. Additionally, the infection process and aspects of the host immunological response were described in the laboratory. Results Bioassay results proved that M. rileyi was highly virulent to 3rd instar S. frugiperda larvae with 98.33% mortality at 1 × 108 conidia/ml. Scanning electron microscopy was used to monitor morphological aspects of the infection process. When hyphal bodies (Hbs) of M. rileyi were injected into the hemocoel of host, they were not recognized by the host’s immune system as invaders. There were nonsignificant differences in the hemocytes and phenoloxidase activity between the infected and control larvae at the initial 30 h, indicating that fungus successfully avoids the attack from the immune system. However, it inhibited the enzyme activity at the latest stage when Hbs reached a high density. After infection with M. rileyi, the activity of glutathione-S-transferase (GST) of S. frugiperda larvae presented a significant upward trend, while the activity of acetylcholinesterase (AchE) initially increased, followed by a decrease, and eventually stabilized. However, the activity of both detoxification enzymes in the control group showed slight fluctuations in the initial stage, and then stabilized at a low level. Conclusion Obtained results provided new insights into the virulence and potential physiological responses of M. rileyi. This provides ideas for further development of novel and efficient entomopathogenic fungi (EPF) for pest control.

Abstract Background The repair of bone defects caused by periodontal diseases is a difficult challenge in clinical treatment. Dental pulp stem cells (DPSCs) are widely studied for alveolar bone repair. The current investigation aimed to examine the specific mechanisms underlying the role of Zinc finger DHHC-type palmitoyl transferases 16 (ZDHHC16) in the process of osteogenic differentiation (OD) of DPSCs. Methods The lentiviral vectors ZDHHC16 or si-ZDHHC16 were introduced in the DPSCs and then the cells were induced by an odontogenic medium for 21 days. Subsequently, Quantitate Polymerase Chain Reaction (PCR), immunofluorescent staining, proliferation assay, ethynyl deoxyuridine (EdU) staining, and western blot analysis were used to investigate the specific details of ZDHHC16 contribution in OD of DPSCs. Results Our findings indicate that ZDHHC16 exhibited a suppressive effect on cellular proliferation and oxidative phosphorylation, while concurrently inducing ferroptosis in DPSCs. Moreover, the inhibition of ZDHHC16 promoted cell development and OD and reduced ferroptosis of DPSCs. The expression of p-CREB was suppressed by ZDHHC16, and immunoprecipitation (IP) analysis revealed that ZDHHC16 protein exhibited interconnection with cAMP-response element binding protein (CREB) of DPSCs. The CREB suppression reduced the impacts of ZDHHC16 on OD and ferroptosis of DPSCs. The activation of CREB also reduced the influences of si-ZDHHC16 on OD and ferroptosis of DPSCs. Conclusions These findings provide evidences to support a negative association between ZDHHC16 and OD of DPSCs, which might be mediated by ferroptosis of DPSCs via CREB.

In the context of plant factories relying on artificial light sources, energy consumption stands out as a significant cost factor. Implementing early seedling removal and replacement operations has the potential to enhance the yield per unit area and the per-energy consumption. Nevertheless, conventional transplanting machines are limited to handling older seedlings with well-established roots. This study addresses these constraints by introducing a transplanting workstation based on the UR5 industrial robot tailored to early plug tray seedlings in plant factories. A diagonal oblique insertion end effector was employed, ensuring stable grasping even in loose substrate conditions. Robotic vision technology was utilized for the recognition of nongerminating holes and inferior seedlings. The integrated robotic system seamlessly managed the entire process of removing and replanting the plug tray seedlings. The experimental findings revealed that the diagonal oblique-insertion end effector achieved a cleaning rate exceeding 65% for substrates with a moisture content exceeding 70%. Moreover, the threshold-segmentation-based method for identifying empty holes and inferior seedlings demonstrated a recognition accuracy surpassing 97.68%. The success rate for removal and replanting in transplanting process reached an impressive 95%. This transplanting robot system serves as a reference for the transplantation of early seedlings with loose substrate in plant factories, holding significant implications for improving yield in plant factory settings.

Abstract Background The causality of the relationship between bronchiectasis and chronic obstructive pulmonary disease (COPD) remains unclear. This study aims to investigate the potential causal relationship between them, with a specific focus on the role of airway inflammation, infections, smoking as the mediators in the development of COPD. Methods We conducted a two-sample Mendelian randomization (MR) analysis to assess: (1) the causal impact of bronchiectasis on COPD, sex, smoking status, infections, eosinophil and neutrophil counts, as well as the causal impact of COPD on bronchiectasis; (2) the causal effect of smoking status, infections and neutrophil counts on COPD; and (3) the extent to which the smoking status, infections and neutrophil counts might mediate any influence of bronchiectasis on the development of COPD. Results COPD was associated with a higher risk of bronchiectasis (OR 1.28 [95% CI 1.05, 1.56]). Bronchiectasis was associated with a higher risk of COPD (OR 1.08 [95% CI 1.04, 1.13]), higher levels of neutrophil (OR 1.01 [95% CI 1.00, 1.01]), higher risk of respiratory infections (OR 1.04 [95% CI 1.02, 1.06]) and lower risk of smoking. The causal associations of higher neutrophil cells, respiratory infections and smoking with higher COPD risk remained after performing sensitivity analyses that considered different models of horizontal pleiotropy, with OR 1.17, 1.69 and 95.13, respectively. The bronchiectasis–COPD effect was 0.99, 0.85 and 122.79 with genetic adjustment for neutrophils, respiratory infections and smoking. Conclusion COPD and bronchiectasis are mutually causal. And increased neutrophil cell count and respiratory infections appears to mediate much of the effect of bronchiectasis on COPD.

Abstract Background Body weight and size are important economic traits in chickens. While many growth-related quantitative trait loci (QTLs) and candidate genes have been identified, further research is needed to confirm and characterize these findings. In this study, we investigate genetic and genomic markers associated with chicken body weight and size. This study provides new insights into potential markers for genomic selection and breeding strategies to improve meat production in chickens. Methods We performed whole-genome resequencing of and Wenshang Barred (WB) chickens (n = 596) and three additional breeds with varying body sizes (Recessive White (RW), WB, and Luxi Mini (LM) chickens; (n = 50)). We then used selective sweeps of mutations coupled with genome-wide association study (GWAS) to identify genomic markers associated with body weight and size. Results We identified over 9.4 million high-quality single nucleotide polymorphisms (SNPs) among three chicken breeds/lines. Among these breeds, 287 protein-coding genes exhibited positive selection in the RW and WB populations, while 241 protein-coding genes showed positive selection in the LM and WB populations. Genomic heritability estimates were calculated for 26 body weight and size traits, including body weight, chest breadth, chest depth, thoracic horn, body oblique length, keel length, pelvic width, shank length, and shank circumference in the WB breed. The estimates ranged from 0.04 to 0.67. Our analysis also identified a total of 2,522 genome-wide significant SNPs, with 2,474 SNPs clustered around two genomic regions. The first region, located on chromosome 4 (7.41-7.64 Mb), was linked to body weight after ten weeks and body size traits. LCORL, LDB2, and PPARGC1A were identified as candidate genes in this region. The other region, located on chromosome 1 (170.46-171.53 Mb), was associated with body weight from four to eighteen weeks and body size traits. This region contained CAB39L and WDFY2 as candidate genes. Notably, LCORL, LDB2, and PPARGC1A showed highly selective signatures among the three breeds of chicken with varying body sizes. Conclusion Overall this study provides a comprehensive map of genomic variants associated with body weight and size in chickens. We propose two genomic regions, one on chromosome 1 and the other on chromosome 4, that could helpful for developing genome selection breeding strategies to enhance meat yield in chickens.

Abstract This study intended to evaluate the diagnostic accuracy of the prostate imaging reporting and data system (PI-RADS) and prostate-specific antigen density (PSAD) for clinically significant prostate cancer (csPCa) with PSA levels of 4–10 ng/ml. Between July 2018 and June 2022, a total of 453 patients with PSA levels of 4–10 ng/ml were retrospectively included, which were randomly assigned to the training group (323 patients) and validation group (130 patients). Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) with their 95% CI were calculated. The overall diagnostic performance was determined with area under the receiver operating characteristic curve (AUC), and an integrated nomogram combining PI-RADS score and PSAD was constructed and tested in a validation cohort. In the training group, the AUC for PI-RADS 2.1 and PSAD alone were 0.875 (95% CI 0.834–0.916) and 0.712 (95% CI 0.648–0.775). At the cutoff PI-RADS score ≥ 4, the sensitivity and specificity were 86.2% (95% CI 77.4–1.9%) and 84.7% (95% CI 79.6–88.8%), respectively. For PSAD, the sensitivity and specificity were 73.3% (95% CI 63.0–82.4%) and 62.1% (95% CI 55.8–68.5%) at the cutoff 0.162 ng/ml/ml. While combining PI-RADS with PSAD, the diagnostic performance was improved significantly, with AUC of 0.893 (95% CI 0.853–0.933). In the validation group, the nomogram yielded a AUC of 0.871 (95% CI 0.807–0.934), which is significantly higher than PI-RADS alone (0.829, 95% CI 0.759–0.899, P = 0.02). For patients with PSA levels of 4–10 ng/ml, PSAD demonstrated moderate diagnostic accuracy whereas PI-RADS showed high performance. By combination of PSAD and PI-RADS together, the diagnostic performance could be improved significantly.

Abstract Over the last 20 years, industry interest in copper has increased. Its application in the petrochemical, automotive, and nuclear power industries highlights the need for new research directions especially in the joining of copper to other metals. In this work, lap joint of 304 stainless steel and T2 copper precoated with Cu–Mn–Ni filler metal was performed by laser brazing. The aim of this study is to characterize the influence of laser beam incidence angle on the welded joint forming mode, microstructure, elements diffusion and corrosion resistance. According to the findings, the joint is classified as a welded joint when the laser beam incidence angle is 80°, and as a welded-brazed joint when it’s 90°, 70°, or 60°. The microstructure is mainly composed of Cu-rich and Fe-rich phases, Mn in the Cu-rich phase aggregation and Cr in the Fe-rich phase aggregation. In the fusion zone (FZ) the content of less than 50% of the liquid will be in the form of supersaturated droplets in the matrix of the other side. The local corrosion pair that the copper steel matrix and liquid drop produce in the FZ speeds up the dissolution of the Cu-rich phase, which effected corrosion resistance of the joint.

Abstract Photonic quantum computation plays an important role and offers unique advantages. Two decades after the milestone work of Knill-Laflamme-Milburn, various architectures of photonic processors have been proposed, and quantum advantage over classical computers has also been demonstrated. It is now the opportune time to apply this technology to real-world applications. However, at current technology level, this aim is restricted by either programmability in bulk optics or loss in integrated optics for the existing architectures of processors, for which the resource cost is also a problem. Here we present a von-Neumann-like architecture based on temporal-mode encoding and looped structure on table, which is capable of multimode-universal programmability, resource-efficiency, phase-stability and software-scalability. In order to illustrate these merits, we execute two different programs with varying resource requirements on the same processor, to investigate quantum signature of chaos from two aspects: the signature behaviors exhibited in phase space (13 modes), and the Fermi golden rule which has not been experimentally studied in quantitative way before (26 modes). The maximal program contains an optical interferometer network with 1694 freely-adjustable phases. Considering current state-of-the-art, our architecture stands as the most promising candidate for real-world applications.

In the present study, in-situ TiN ceramic particles were introduced into Ti–V–Al based shape memory alloys to optimize mechanical properties and friction resistance. The results revealed that increasing the TiN content resulted in the transition from α'' to β phase, and led to a reduction in the martensitic transformation temperature. Additionally, the TiN ceramic particles were found to significantly reduced the grain size of the Ti–V–Al based shape memory alloys. Compared to other Ti–V–Al-X shape memory alloys, the introduction of TiN ceramic particles enhanced the mechanical and wear properties of the Ti–V–Al shape memory alloy. These improvements can be attributed to a combination of solid solution strengthening, grain refinement and precipitation strengthening. Notably, the (Ti–V–Al)100-xNx shape memory alloy exhibited a maximum yield strength of 568 MPa and a fracture strength of 788 MPa. Furthermore, the micro-hardness of the Ti–V–Al based shape memory alloy increased monotonously from 355HV to 393HV, while the wear coefficient steadily decreased from 0.53 to 0.48. In conclusion, by adjusting content of TiN ceramic particles, it is possible to obtain a lightweight Ti–V–Al shape memory alloy with tailored martensitic transformation temperatures, enhanced strength and hardness, as well as excellent friction properties.

Abstract As a typical sub-deep reservoir in the upper reaches of the Yangtze River in the southwest region, Zhangjiayan Reservoir is also an important source of drinking water. Exploring the role of microorganisms in the material cycle of water bodies is of great significance for preventing the exacerbation of eutrophication in the reservoir. In this study, water samples from the overlying water of five points in the reservoir were collected four times in spring (April), summer (July), autumn (November), and winter (January) of 2022–2023 using a gas-tight water sampler. Physicochemical factors were measured, and the microbial community structure was analyzed by high-throughput MiSeq sequencing of the V3–V4 hypervariable region of 16S rRNA gene in order to explore the relationship between physicochemical factors and microbial community structure and the dominant microbial populations that affect eutrophication of the reservoir. The following results were obtained through analysis. Among the 20 overlying water samples from Zhangjiayan Reservoir, a total of 66 phyla, 202 classes, 499 orders, 835 families, 1716 genera, and 27,904 ASVs of the bacterial domain were detected. The phyla Proteobacteria and Actinobacteria were dominant in the microbial community of the overlying water in Zhangjiayan Reservoir. At the genus level, hgcI_clade and Actinobacteria had the highest abundance and was the dominant population. The microbial community in the water of Zhangjiayan Reservoir has a high level of diversity. The diversity index ranked by numerical order was winter > autumn > summer > spring. Significant differences were found in the composition and structure of the microbial community between the spring/summer and autumn/winter seasons (p

Abstract In this study, we present a sophisticated multi-label deep learning framework for the prediction of RNA-RBP (RNA-binding protein) interactions, a critical aspect in understanding RNA functionality modulation and its implications in disease pathogenesis. Our approach leverages machine learning to develop a rapid and cost-efficient predictive model for these interactions. The proposed model captures the complex characteristics of RNA and recognizes corresponding RBPs through its dual-module architecture. The first module employs convolutional neural networks (CNNs) for intricate feature extraction from RNA sequences, enabling the model to discern nuanced patterns and attributes. The second module is a multi-view multi-label classification system incorporating a feature attention mechanism. The second module is a multi-view multi-label classification system that utilizes a feature attention mechanism. This mechanism is designed to intricately analyze and distinguish between common and unique deep features derived from the diverse RNA characteristics. To evaluate the model's efficacy, extensive experiments were conducted on a comprehensive RNA-RBP interaction dataset. The results emphasize substantial improvements in the model's ability to predict RNA-RBP interactions compared to existing methodologies. This advancement emphasizes the model's potential in contributing to the understanding of RNA-mediated biological processes and disease etiology.

Abstract Background Safely implementing transbronchial lung cryobiopsy (TBLC) in patients with interstitial lung disease (ILD) requires accurate navigation. Traditional fluoroscopy falls short in reducing the risk of post-procedure pneumothorax. The potential of electromagnetic navigation bronchoscopy (ENB) as a more precise navigation method warrants further exploration. Methods A prospective cohort study was conducted on ILD patients undergoing TBLC. Patients were assigned either fluoroscopy or ENB for cryoprobe positioning. Navigation accuracy was evaluated using cone beam computed tomography (CBCT) images as the standard. Safety and diagnostic yield were also observed. Results Seventeen patients underwent TBLC, with 10 guided by fluoroscopy and seven by ENB. Fluoroscopy-guided cryoprobe navigation required more adjustments [9/15 (60%) v.s. 1/9 (11%), p = 0.018] for subsequent TBLC compared to ENB, as confirmed by CBCT images. Clinical characteristics, post-procedure complications, and biopsy specimen size showed no significant differences between the groups. Fourteen patients obtained a pathological diagnosis, and 15 received a multidisciplinary discussion (MDD) diagnosis. In the fluoroscopy group, three patients failed to obtain a pathological diagnosis, and two failed to obtain an MDD diagnosis. Conclusions ENB demonstrates significantly superior accuracy in TBLC navigation compared to traditional fluoroscopy when CBCT images are used as a reference. Further studies are necessary to determine the value of ENB in TBLC navigation for ILD patients.

Abstract A drug conjugate consists of a cytotoxic drug bound via a linker to a targeted ligand, allowing the targeted delivery of the drug to one or more tumor sites. This approach simultaneously reduces drug toxicity and increases efficacy, with a powerful combination of efficient killing and precise targeting. Antibody‒drug conjugates (ADCs) are the best-known type of drug conjugate, combining the specificity of antibodies with the cytotoxicity of chemotherapeutic drugs to reduce adverse reactions by preferentially targeting the payload to the tumor. The structure of ADCs has also provided inspiration for the development of additional drug conjugates. In recent years, drug conjugates such as ADCs, peptide‒drug conjugates (PDCs) and radionuclide drug conjugates (RDCs) have been approved by the Food and Drug Administration (FDA). The scope and application of drug conjugates have been expanding, including combination therapy and precise drug delivery, and a variety of new conjugation technology concepts have emerged. Additionally, new conjugation technology-based drugs have been developed in industry. In addition to chemotherapy, targeted therapy and immunotherapy, drug conjugate therapy has undergone continuous development and made significant progress in treating lung cancer in recent years, offering a promising strategy for the treatment of this disease. In this review, we discuss recent advances in the use of drug conjugates for lung cancer treatment, including structure-based drug design, mechanisms of action, clinical trials, and side effects. Furthermore, challenges, potential approaches and future prospects are presented.

Abstract The ocean’s major circulation system, the Atlantic Meridional Overturning Circulation (AMOC), is slowing down. Such weakening is consistent with warming associated with increasing greenhouse gases, as well as with recent decreases in industrial aerosol pollution. The impact of biomass burning aerosols on the AMOC, however, remains unexplored. Here, we use the Community Earth System Model version 1 Large Ensemble to quantify the impact of both aerosol types on the AMOC. Despite relatively small changes in North Atlantic biomass burning aerosols, significant AMOC evolution occurs, including weakening from 1920 to ~1970 followed by AMOC strengthening. These changes are largely out of phase relative to the corresponding AMOC evolution under industrial aerosols. AMOC responses are initiated by thermal changes in sea surface density flux due to altered shortwave radiation. An additional dynamical mechanism involving the North Atlantic sea-level pressure gradient is important under biomass-burning aerosols. AMOC-induced ocean salinity flux convergence acts as a positive feedback. Our results show that biomass-burning aerosols reinforce early 20th-century AMOC weakening associated with greenhouse gases and also partially mute industrial aerosol impacts on the AMOC. Recent increases in wildfires suggest biomass-burning aerosols may be an important driver of future AMOC variability.

Abstract Seawater electrolysis offers a renewable, scalable, and economic means for green hydrogen production. However, anode corrosion by Cl- pose great challenges for its commercialization. Herein, different from conventional catalysts designed to repel Cl- adsorption, we develop an atomic Ir catalyst on cobalt iron layered double hydroxide (Ir/CoFe-LDH) to tailor Cl- adsorption and modulate the electronic structure of the Ir active center, thereby establishing a unique Ir-OH/Cl coordination for alkaline seawater electrolysis. Operando characterizations and theoretical calculations unveil the pivotal role of this coordination state to lower OER activation energy by a factor of 1.93. The Ir/CoFe-LDH exhibits a remarkable oxygen evolution reaction activity (202 mV overpotential and TOF = 7.46 O2 s−1) in 6 M NaOH+2.8 M NaCl, superior over Cl--free 6 M NaOH electrolyte (236 mV overpotential and TOF = 1.05 O2 s−1), with 100% catalytic selectivity and stability at high current densities (400-800 mA cm−2) for more than 1,000 h.

Abstract Background Patients with colorectal cancer (CRC) with liver metastasis or drug resistance have a poor prognosis. Previous research has demonstrated that PPP2R1B inactivation results in the development of CRC. However, the role of PPP2R1B in CRC metastasis and drug resistance is unclear. Methods Venny 2.1 was used to determine the intersection between survival-related differentially expressed genes (DEGs) and liver metastasis-related DEGs according to RNA-seq data from The Cancer Genome Atlas (TCGA) and the GEO database (GSE179979). LC‒MS/MS and coimmunoprecipitation were performed to predict and verify the substrate protein of PPP2R1B. Gene Set Variation Analysis (GSVA) was subsequently utilized to assess pathway enrichment levels. The predictive performance of PPP2R1B was assessed by regression analysis, Kaplan–Meier (KM) survival analysis and drug sensitivity analysis. Immunohistochemistry (IHC), qRT-PCR and western blotting were performed to measure the expression levels of related mRNAs or proteins. Biological features were evaluated by wound healing, cell migration and invasion assays and CCK-8 assays. A mouse spleen infection liver metastasis model was generated to confirm the role of PPP2R1B in the progression of liver metastasis in vivo. Results According to bioinformatics analysis, PPP2R1B is significantly associated with liver metastasis and survival in CRC patients, and these findings were further verified via immunohistochemistry (IHC), qPCR and Western blotting. Pathway enrichment and LC‒MS/MS analysis revealed that PPP2R1B is negatively associated with the MAPK/ERK signalling pathway. Additionally, PD98059, a MAPK/ERK pathway inhibitor, inhibited EMT in vitro by reversing the changes in key proteins involved in EMT signalling (ZEB1, E-cadherin and Snail) and ERK/MAPK signalling (p-ERK) mediated by PPP2R1B. Oxaliplatin sensitivity prediction and validation revealed that PPP2R1B silencing decreased Oxaliplatin chemosensitivity, and these effects were reversed by PD98059 treatment. Moreover, PPP2R1B was coimmunoprecipitated with p-ERK in vitro. A negative correlation between PPP2R1B and p-ERK expression was also observed in clinical CRC samples, and the low PPP2R1B/high p-ERK coexpression pattern indicated a poor prognosis in CRC patients. In vivo, PPP2R1B silencing significantly promoted liver metastasis. Conclusions This study revealed that PPP2R1B induces dephosphorylation of the p-ERK protein, inhibits liver metastasis and increases Oxaliplatin sensitivity in CRC patients and could be a potential candidate for therapeutic application in CRC.

Background and Aim: Xuefu Zhuyu decoction (XZD), a traditional Chinese medicinal formula, was firstly recorded in the Qing dynasty of ancient China and previously demonstrated to ameliorate hepatic steatosis. In the present study, the effects of XZD on non-alcoholic fatty liver disease (NAFLD) induced by high-fat diet (HFD) were evaluated in mice and the hepatic transcriptome was detected to disclose the potential mechanisms of XZD. Experimental procedure: The effects of XZD (low- and high-dosage) on NAFLD induced by HFD for 16 weeks were evaluated. Obeticholic acid was used as control drug. Body weight, food intake and index of homeostatic model assessment for insulin resistance (HOMA-IR) were analyzed. Hepatic histology were observed in haematoxylin and eosin stained sections and quantified with NAFLD activity score (NAS). Lipid in hepatocytes was visualized by Oil red staining. Alanine aminotransferase (ALT) and hepatic triglyceride (TG) was measured. The hepatic transcriptom was detected with RNA-sequencing and validated with real-time polymerase chain reaction, western-blotting and hepatic quantitative metabolomics. Results: XZD ameliorated hepatic histology of NAFLD mice, accompanied with decreasing fasting insulin, HOMA-IR, NAS, ALT and hepatic TG. The hepatic transcriptom of NAFLD was significantly reversed by XZD treatment, especially the genes enriched in the pathways of arachidonic acid metabolism, fatty acid degradation, cytokine-cytokine receptor interaction and extracellular matrix (ECM) -receptor interaction. The hepatic quantitative metabolomics analysis confirmed fatty acid degradation as the key targeting pathway of XZD. Conclusions: XZD ameliorated NAFLD induced by HFD, which probably correlated closely to the pathways of fatty acid degradation.