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Abstract Dominant species occupy a pivotal role in plant community, influencing the structure and function of the ecosystem. The spatial distributions of dominant species can react to the effect of different grazing intensities, thereby reflecting their tolerance and adaptive strategies toward grazing. In this study, geostatistical methods were mainly used to study the spatial distribution characteristics of Stipa krylovii Roshev. and Leymus chinensis (Trin.) Tzvel. species at two interval scales (quadrat size 5 m × 5 m, 10 m × 10 m) and two treatments (free grazing, FG, 1.66 sheep·ha− 1·a− 1; control, CK, 0 sheep·ha− 1·a− 1) in typical steppe of Inner Mongolia. A systematic sampling method was used in each 100 m × 100 m representative sample plots to obtain the height, coverage, and density of all species in the community. The results showed that grazing altered the concentrated distribution of S. krylovii and the spatial mosaic distribution pattern of S. krylovii and L. chinensis while having no effect on the spatial clumped distribution of L. chinensis. It also found that the spatial distributions of dominant species are primarily affected by structural factors, and random factors such as long-term grazing led to a transition of S. krylovii from a concentrated distribution to a small patchy random pattern should not be overlooked. Our findings suggest that long-term grazing alters the spatial distribution pattern of dominant species and that adaptive strategies may be the key for maintaining the dominant role of structural factors.

Triboelectrification, a process that transforms mechanical energy into electrical energy through friction, holds promise for eco-friendly wastewater treatment. This study delves into the enhancement of tribocatalytic dye degradation using SrTiO3, a material notable for its non-piezoelectric and centrosymmetric properties. The synthesis of uni- and bi-doped SrTiO3 particles, achieved through a solid-state reaction at 1000 °C, results in a high-purity cubic perovskite structure. Doping with rhodium (Rh) and carbon (C) causes crystal lattice contraction, internal stress, and significant oxygen vacancies. These changes notably improve tribocatalytic efficiency under solar irradiation, with Rh-doped SrTiO3 demonstrating an impressive degradation rate of approximately 88% for Rhodamine B (RhB), along with reaction rate constants near 0.9 h−1 at 554 nm and a noticeable blueshift. This study highlights that defects introduced by doping are integral to this process, boosting catalytic activity through energy state modification and enhancing surface redox radical production. Additionally, these defects are instrumental in generating a flexoelectric field, which markedly influences the separation of electron–hole pairs under solar irradiation. Our findings illuminate the complex interplay between material composition, defect states, and environmental conditions, paving the way for advanced strategies in environmental remediation through optimized tribocatalytic activity.

Owing to their limited accuracy and narrow applicability, current antimicrobial peptide (AMP) prediction models face obstacles in industrial application. To address these limitations, we developed and improved an AMP prediction model using Comparing and Optimizing Multiple DEep Learning (COMDEL) algorithms, coupled with high-throughput AMP screening method, finally reaching an accuracy of 94.8% in test and 88% in experiment verification, surpassing other state-of-the-art models. In conjunction with COMDEL, we employed the phage-assisted evolution method to screen Sortase in vivo and developed a cell-free AMP synthesis system in vitro, ultimately increasing AMPs yields to a range of 0.5–2.1 g/L within hours. Moreover, by multi-omics analysis using COMDEL, we identified Lactobacillus plantarum as the most promising candidate for AMP generation among 35 edible probiotics. Following this, we developed a microdroplet sorting approach and successfully screened three L. plantarum mutants, each showing a twofold increase in antimicrobial ability, underscoring their substantial industrial application values.

Abstract The negative effects of obesity and excess body fat on bone mineral density (BMD) have been widely reported. As opposed to waist circumference (WC) or body mass index (BMI), weight-adjusted waist index (WWI) is a superior method for assessing obesity. WWI also indicates centripetal obesity independently of the weight of the individual. An investigation of WWI and adolescents’ BMD was conducted in this study. The National Health and Nutrition Examination Survey (NHANES) 2011–2018 provided the data for this cross-sectional investigation. In this study, weighted multivariate logit models were employed to assess the correlation between teenage BMD and WWI. Additionally, we conducted interaction tests and subgroup analysis. Through multivariate linear regression, we discovered that WWI was negatively linked with lumbar, trunk, and total BMD but not pelvis BMD in this study, which included 6828 subjects. We found that each unit increase in WWI resulted in a lumbar BMD decline of 0.04 g/cm2 (95%CI −0.04, −0.04), a trunk BMD decrease of 0.03 g/cm2 (95%CI −0.03, −0.02), and a total BMD decrease of 0.02 g/cm2 (95%CI −0.02, −0.02). In conclusion, in US teenagers, there were negative connections discovered between WWI and lumbar, trunk, and total BMD, but not pelvis BMD.

Gastrochilus is an orchid genus containing 73 species of mainly epiphytic on trees or rocks in mountain forests of tropical and subtropical Asia. Previous phylogenetic analyses and morphological assessments have failed to produce a well-resolved phylogeny at the infrageneric level. In the present study, a new infrageneric classification of Gastrochilus is proposed based on thoroughly morphological and phylogenetic analyses based on 52 species. Our phylogenetic analysis divided the genus into six sections including three new sections, G. sect. Pseudodistichi, G. sect. Brachycaules and G. sect. Acinacifolii. We also reinstate G. suavis to the specific rank. Furthermore, two new species, G. armeniacus Jun Y. Zhang, B. Xu & Yue H. Cheng and G. minjiangensis Jun Y. Zhang, B. Xu & Yue H. Cheng, are described and illustrated. A key to six sections of the genus is presented.

Abstract Hydraulic systems play a pivotal and extensive role in mechanics and energy. However, the performance of intelligent fault diagnosis models for multiple components is often hindered by the complexity, variability, strong hermeticity, intricate structures, and fault concealment in real-world conditions. This study proposes a new approach for hydraulic fault diagnosis that leverages 2D temporal modeling and attention mechanisms for decoupling compound faults and extracting features from multisample rate sensor data. Initially, to address the issue of oversampling in some high-frequency sensors within the dataset, variable frequency data sampling is employed during the data preprocessing stage to resample redundant data. Subsequently, two-dimensional convolution simultaneously captures both the instantaneous and long-term features of the sensor signals for the coupling signals of hydraulic system sensors. Lastly, to address the challenge of feature fusion with multisample rate sensor data, where direct merging of features through maximum or average pooling might dilute crucial information, a feature fusion and decoupling method based on a probabilistic sparse self-attention mechanism is designed, avoiding the issue of long-tail distribution in multisample rate sensor data. Experimental validation showed that the proposed model can effectively utilize samples to achieve accurate fault decoupling and classification for different components, achieving a diagnostic accuracy exceeding 97% and demonstrating robust performance in hydraulic system fault diagnosis under noise conditions.

Abstract Objective To evaluate sanitary techniques for radical thyroid cancer surgery via the transaxillary approach without inflation single-port endoscopic surgery (TAWISES) and the conventional open anterior cervical approach (COACAS) in a controlled manner. Methods This work was a retrospective analysis of the clinical data of 60 patients admitted to our hospital for unilateral radical thyroid cancer surgery between 01/2021 and 12/2022. The control group underwent COACAS (30 patients), and the experimental group underwent TAWISES (30 patients). The patients’ operative time, intraoperative bleeding volume, 24-h postoperative pain index, drainage tube carrying time, hospitalization duration and complication rate were compared and analyzed. The patients were followed up for 3, 6 and 12 months postoperatively and evaluated based on numbness, muscular tightness, pain and other discomfort in the neck, as well as satisfaction with social adaptation and cosmetic incisions. The recurrence status was assessed for 1 year in both groups of patients. A questionnaire survey was conducted to assess patient acceptance of the two surgical approaches. The economic characteristics (cost-effectiveness and cost-utility) of the different approaches in our region were evaluated comprehensively. Results The length of the incision, drainage tube carrying time and hospitalization duration were greater in the experimental group than in the control group (P 0.05). Neck discomfort was greater in the control group, and the difference was statistically significant at the 3-month postoperative follow-up (P 0.05). However, mild discomfort was significantly more common in the experimental group (63.33% > 36.67%, 80% > 53.33%, P

Abstract Introduction Although there has been abundant evidence of the association between dyslipidemia as a single factor and osteoporosis, the non-linear relationship between osteoporosis and the Atherogenic Index of Plasma (AIP) has not yet been thoroughly investigated. This study aimed to investigate the complex relationship between AIP and bone mineral density (BMD) to elucidate their interrelationship. Methods An analysis of 2007–2018 National Health and Nutrition Survey (NHANES) data was conducted for this study. The study enrolled 5,019 participants. Logarithmically multiplying triglycerides and high-density lipoprotein cholesterol yields the AIP (base 10). The measured variables consisted of BMD in the total femur (TF), femoral neck (FN), and lumbar spine (LS). The association between AIP and BMD was examined using a range of statistical models, such as weighted multivariable logistic regression, generalized additive model, etc. Results It was found that AIP was positively associated with BMD after adjusting for age, gender, race, socioeconomic status, degree of education, income, Consuming alcoholic beverages, osteoporosis status (Yes or No), ALT, AST, serum creatinine, and total calcium levels. Further studies supported the association link between elevated BMD and AIP. Furthermore, compared to men, females had a higher positive connection between AIP and BMD. In general, there was a curve in the reverse L-shape seen, with a point of change around 0.877, indicating a relationship between AIP and TF BMD. Moreover, a curve exhibiting an L-formed pattern, with a point of inflection at around 0.702, was seen between AIP and FN BMD. In addition, a J-shaped curve was seen, with a point of inflection at 0.092, which demonstrates the association between AIP and LS BMD. Conclusion The AIP and TF BMD curves resemble inverted L shapes, as do the AIP and FN BMD curves. The relationship between AIP and LS BMD was further demonstrated by a J-shaped curve. The results indicate a possible association between AIP and bone mineral density, which should be explored in more detail.

Abstract Objective The purpose of this study was to evaluate the efficacy and clinical value of US, FNAC,FNA-Tg and FNAC + FNA-Tg, as well as the cutoff values of FNA-Tg to evaluate LN metastasis. Methods We analyzed the diagnostic value of different US signs, the efficiency of US, FNAC, FNA-Tg and FNAC + FNA-Tg among the LN- and LN + groups, and the cutoff value of FNA-Tg to evaluate LN metastasis. We punctured LNs multiple times and measured the levels of FNA-Tg. Furthermore, the LNs were marked with immunohistochemical Tg and LCA to distinguish the presence of Tg in the para-cancerous tissue of the LNs. Results The s-Tg and FNA-Tg of the LN + group were higher than those of the LN- group (P = 0.018, ≤ 0.001). The LN + group had more abnormal US signs than the LN- group. The cutoff value of FNA-Tg was 3.2 ng/mL. US had a high sensitivity (92.42), but the specificity was not satisfactory (55.1). FNA-Tg had a higher sensitivity (92.42 vs. 89.39), specificity (100 vs. 93.88), and accuracy (92.42 vs. 83.27) than FNAC. However, the sensitivity of FNAC + FNA-Tg increased further, while the specificity and accuracy decreased slightly. The presence of Tg in the normal lymphocytes adjacent to the cancer was confirmed. Conclusion Ultrasonography provides a noninvasive, dynamic, multidimensional assessment of LNs. With a cutoff value of 3.2 ng/mL, FNA-Tg has higher accuracy and a lower false-negative rate than various single diagnoses. However, FNAC combined with FNA-Tg does not cause additional pain to patients and offers a higher diagnostic efficacy and clinical value.

Abstract By mimicking the neurons and synapses of the human brain and employing spiking neural networks on neuromorphic chips, neuromorphic computing offers a promising energy-efficient machine intelligence. How to borrow high-level brain dynamic mechanisms to help neuromorphic computing achieve energy advantages is a fundamental issue. This work presents an application-oriented algorithm-software-hardware co-designed neuromorphic system for this issue. First, we design and fabricate an asynchronous chip called “Speck”, a sensing-computing neuromorphic system on chip. With the low processor resting power of 0.42mW, Speck can satisfy the hardware requirements of dynamic computing: no-input consumes no energy. Second, we uncover the “dynamic imbalance” in spiking neural networks and develop an attention-based framework for achieving the algorithmic requirements of dynamic computing: varied inputs consume energy with large variance. Together, we demonstrate a neuromorphic system with real-time power as low as 0.70mW. This work exhibits the promising potentials of neuromorphic computing with its asynchronous event-driven, sparse, and dynamic nature.

Abstract Background Studies have shown that RASGRP1 was potently associated with the onset of type 2 diabetes mellitus (T2DM), and RASGRP1 rs7403531 was significantly correlated with islet function in T2DM patients. However, the effect of RASGRP1 polymorphism on blood glucose and blood pressure in T2DM patients after continuous treatment has yet to be fully elucidated. Objective This study aimed to explore the association between RASGRP1 genetic polymorphism and cardiovascular complications in T2DM patients, so as to provide more evidence for the individualized treatment of T2DM patients. Methods We retrospectively analyzed a large-scale multicenter drug clinical study cohort that based on a 2 × 2 factorial (glucose control axis and blood pressure lowering axis) randomized controlled design, with follow-up for 5 years. The major vascular endpoint events included cardiovascular death, non-fatal stroke, coronary heart disease, new-onset or worsening renal disease, and diabetic retinopathy. RASGRP1 rs12593201, rs56254815 and rs7403531 were finally selected as candidate single nucleotide polymorphisms. Mixed linear model and Cox hazard ratio (HR) model were used for data analysis with IBM SPSS (version 20.0 for windows; Chicago, IL). Results Our study enrolled 1357 patients with high-risk diabetes, with a mean follow-up duration of 4.8 years. RASGRP1 rs7403531 was associated with vascular events in hypoglycemic and antihypertensive therapy. Specifically, compared with CC carriers, patients with CT/TT genotype had fewer major microvascular events (HR = 0.41, 95% confidence interval (CI) 0.21–0.80, P = 0.009), and reduced the risk of major eye disease events (HR = 0.44, 95% CI 0.20–0.94, P = 0.03). For glucose lowering axis, CT/TT carriers had a lower risk of secondary nephropathy (HR = 0.48, 95% CI 0.25–0.92, P = 0.03) in patients with standard glycemic control. For blood pressure lowering axis, all cerebrovascular events (HR = 2.24, 95% CI 1.11–4.51, P = 0.025) and stroke events (HR = 2.07, 95% CI 1.03–4.15, P = 0.04) were increased in patients with CC genotype compared to those with CT/TT genotype in the placebo group, respectively. Furthermore, patients with CC genotype showed a reduced risk of major cerebrovascular events in antihypertensive group (HR = 0.36, 95% CI 0.15–0.86, P = 0.021). For RASGRP1 rs56254815, compared with the AA genotype carriers, the systolic blood pressure of AG/GG carriers in the antihypertensive group decreased by 1.5mmhg on average (P = 0.04). In the placebo group, the blood pressure of AG/GG carriers was 1.7mmHg higher than that of AA carriers (P = 0.02). Conclusion We found that patients with G allele of RASGRP1 (rs56254815) showed a better antihypertensive therapy efficacy in T2DM patients. The rs7403531 T allele could reduce the risk of major microvascular events and major eye diseases in T2DM patients receiving either hypoglycemic or antihypertensive therapy. Our findings suggest that RASGRP1 genetic polymorphism might predict the cardiovascular complications in T2DM patients.

Objective In the process of shield construction under-passing the existing metro line in water-rich pebble stratum, irregular settlement of the overlying soil mass beyond control range may occur, potentially leading to issues such as underground water gushing and ground collapse. Therefore, it is necessary to research the construction technology for shield under-passing in proximity to operation metro tunnel in water-rich pebble stratum. Method Taking the case of shield under-passing existing Chengdu Metro Line 4 at the newly-built Fengxi Avenue Station on Chengdu Metro Line 17, on the basis of introducing project overview, four land subsidence monitoring points and four deep soil mass settlement monitoring points are selected to analyze the stratum settlement variation law during shield excavation process. A three-dimensional finite element model is created using MIDAS GTS, simulating the reinforcement construction with a combination of 38 m super-long pipe shed and oblique angle grouting. The pre-reinforcement effect on Line 4 tunnel is analyzed. Based on this, the timing for ground tracking grouting is determined, and its effectiveness is further analyzed. Result & Conclusion The reinforcement measures effectively enhance the overall integrity of structure bottom soil mass, improve the structural loading conditions, and successfully control the structural settlement of Line 4.

Purpose: Polypharmacy presents many challenges to patient medication self-management. This study aims to explore the self-management processes of medication in polypharmacy from the perspectives of both patients and healthcare providers, which can help identify barriers and facilitators to effective management.Methods: A systematic review of qualitative studies was performed by searching seven databases: PubMed, Web of Science, Cochrane Library, Embase, CINAHL, PsycINFO, and MEDLINE, from their establishment until August 2024. The Critical Appraisal Skills Programme (CASP) tool was employed to evaluate the quality of the studies included. The extracted data were then analysed thematically and integrated into The Taxonomy of Everyday Self-management Strategies (TEDSS) framework.Results: A total of 16 studies were included, involving 403 patients and 119 healthcare providers. Patient management measures were mapped into TEDSS framework, including categories such as medical management, support-oriented domains and emotional and role management.Conclusion: Enhancing patients’ proactive health awareness, improving medication literacy, balancing lifestyle adjustments with medication therapy, dynamically reviewing and optimizing medications, strengthening patients’ social support networks, and helping patients integrate medication management into their daily life are the key elements that can effectively assist patients in self-managing their medications. Future interventions to improve patient medication self-management ability should be designed for these issues.Systematic Review Registration:https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42024524742.

Summary: Adjuvant radiation therapy is a common treatment for breast cancer, yet its effectiveness is often limited by radioresistance in patients. Identifying novel targets to combat this radioresistance is imperative. Recent investigations show that gp78 is upregulated in drug-resistant breast cancer cells. Our study reveals that gp78 markedly increased the phosphorylation of KAP1 and promoted DNA damage repair caused by ionizing radiation. Mechanistically, gp78 degrades phosphatases (PPP1CC/PPP2CA) in a ubiquitination-dependent manner. PPP1CC and PPP2CA are crucial regulators of KAP1 phosphorylation in response to DNA damage. Therefore, gp78 leads to a notable elevation in the phosphorylation of KAP1 by degrading phosphatases, thereby promoting the DNA damage repair process and increasing the radioresistance of tumor cells. The identification of gp78 as a pivotal regulator in radioresistance suggests a promising avenue for intervention. Combining blockade strategies targeting gp78 holds a signification potential for reversing radioresistance and improving the efficacy of breast cancer radiotherapy.

BackgroundArtificial intelligence (AI) is transforming healthcare, yet little is known about Chinese oncologists’ attitudes towards AI. This study investigated oncologists’ knowledge, perceptions, and acceptance of AI in China.MethodsA cross-sectional online survey was conducted among 228 oncologists across China. The survey examined demographics, AI exposure, knowledge and attitudes using 5-point Likert scales, and factors influencing AI adoption. Data were analyzed using descriptive statistics and chi-square tests.ResultsRespondents showed moderate understanding of AI concepts (mean 3.39/5), with higher knowledge among younger oncologists. Only 12.8% used ChatGPT. Most (74.13%) agreed AI is beneficial and could innovate healthcare, 52.19% respondents expressed trust in AI technology. Acceptance was cautiously optimistic (mean 3.57/5). Younger respondents (∼30) show significantly higher trust (p = 0.004) and acceptance (p = 0.009) of AI compared to older respondents, while trust is significantly higher among those with master’s or doctorate vs. bachelor’s degrees (p = 0.032), and acceptance is higher for those with prior IT experience (p = 0.035).Key drivers for AI adoption were improving efficiency (85.09%), quality (85.53%), reducing errors (84.65%), and enabling new approaches (73.25%).ConclusionsChinese oncologists are open to healthcare AI but remain prudently optimistic given limitations. Targeted education, especially for older oncologists, can facilitate AI implementation. AI is largely welcomed for its potential to augment human roles in enhancing efficiency, quality, safety, and innovations in oncology practice.

ObjectivesHip involvement is an important reason of disability in patients with ankylosing spondylitis (AS). Unveiling the potential phenotype of hip involvement in AS remains an unmet need to understand its biological mechanisms and improve clinical decision-making. Radiomics, a promising quantitative image analysis method that had been successfully used to describe the phenotype of a wide variety of diseases, while it was less reported in AS. The objective of this study was to investigate the feasibility of radiomics-based approach to profile hip involvement in AS.MethodsA total of 167 patients with AS was included. Radiomic features were extracted from pelvis MRI after image preprocessing and feature engineering. Then, we performed unsupervised machine learning method to derive radiomics-based phenotypes. The validation and interpretation of derived phenotypes were conducted from the perspectives of clinical backgrounds and MRI characteristics. The association between derived phenotypes and radiographic outcomes was evaluated by multivariable analysis.Results1321 robust radiomic features were extracted and four biologically distinct phenotypes were derived. According to patient clinical backgrounds, phenotype I (38, 22.8%) and II (34, 20.4%) were labelled as high-risk while phenotype III (24, 14.4%) and IV (71, 42.5%) were at low risk for hip involvement. Consistently, the high-risk phenotypes were associated with higher prevalence of MRI-detected lesion than the low-risk. Moreover, phenotype I had significant acute inflammation signs than phenotype II, while phenotype IV was enthesitis-predominant. Importantly, the derived phenotypes were highly predictive of radiographic outcomes of patients, as the high-risk phenotypes were 3 times more likely to have radiological hip lesion than the low-risk [27 (58.7%) vs 16 (28.6%); adjusted odds ratio (OR) 2.95 (95% CI 1.10, 7.92)].ConclusionWe confirmed for the first time, the clinical actionability of profiling hip involvement in AS by radiomics method. Four distinct phenotypes of hip involvement in AS were identified and importantly, the high-risk phenotypes could predict structural damage of hip involvement in AS.

Abstract Two‐dimensional (2D) non‐layered materials, along with their unique surface properties, offer intriguing prospects for sensing applications. Introducing mechanical degrees of freedom is expected to enrich the sensing performances of 2D non‐layered devices, such as high frequency, high tunability, and large dynamic range, which could lead to new types of high performance nanosensors. Here, we demonstrate 2D non‐layered nanomechanical resonant sensors based on β‐In2S3, where the devices exhibit robust nanomechanical vibrations up to the very high frequency (VHF) band. We show that such device can operate as pressure sensor with broad range (from 10−3 Torr to atmospheric pressure), high linearity (with a nonlinearity factor as low as 0.0071), and fast response (with an intrinsic response time less than 1 μs). We further unveil the frequency scaling law in these β‐In2S3 nanomechanical sensors and successfully extract both the Young's modulus and pretension for the crystal. Our work paves the way towards future wafer‐scale design and integrated sensors based on 2D non‐layered materials.

Background: Zhiqiao Gancao decoction (ZQGCD) was created by Professor Gong Zhengfeng, a renowned Chinese medicine expert. Clinical studies have shown its efficacy in alleviating pain and enhancing lumbar function in intervertebral disc degeneration (IDD) patients. However, the precise mechanism of ZQGCD in treating IDD remains unclear. Methods: The active components of ZQGCD were identified using Liquid chromatography-tandem mass spectrometry (LC-MS/MS). A rat model of intervertebral disc degeneration was established, and rats in each group received ZQGCD for three weeks. Assessment parameters included hyperalgesia status, observation of intervertebral disc tissue degeneration and macrophage infiltration, and analysis of JAK2/STAT3 pathway protein expression in the intervertebral disc. Primary macrophage M1 polarization was induced using LPS, with cells treated using the JAK2 inhibitor (AZD1480) and ZQGCD to evaluate macrophage polarization, cellular supernatant inflammatory factors, and JAK2/STAT3 pathway expression. Macrophage supernatant served as a conditioned medium to observe its effects on the proliferation of nucleus pulposus cells (NPCs) and the expression of collagen II and MMP3 proteins. Results: A total of 81 active components were identified in ZQGCD. Following ZQGCD treatment, infiltrating macrophages in intervertebral disc tissues of model rats decreased, the content of M1 macrophages decreased, while the content of M2 macrophages increased, the expression of proinflammatory factors and pain-inducing factors in serum decreased, and the expression of substance P in intervertebral disc tissue decreased. Consequently, the intervertebral disc degeneration and hyperalgesia of rats were improved. In vitro studies revealed that LPS induced M1 macrophage polarization. By inhibiting the JAK2/STAT3 pathway, both JAK2 inhibitors and ZQGCD effectively suppressed M1 polarization, resulting in decreased levels of IL-1β, IL-6, TNF-α, and various other inflammatory factors. Consequently, this inhibition led to a delay in the degeneration of NPCs. Conclusion: There is macrophage infiltration in the intervertebral disc tissue of IDD rats, and JAK2/STAT3 pathway is activated, macrophages are polarized to M1 type, resulting in inflammatory microenvironment, leading to intervertebral disc degeneration and hyperalgesia. ZQGCD exhibited a delaying effect on IDD and improved hyperalgesia by inhibiting the JAK2/STAT3/macrophage M1 polarization pathway.

In recent years, with the continuous development of molecular immunology, immune checkpoint inhibitors (ICIs) have also been widely used in the treatment of gastric cancer, but they still face some challenges: The first is that only some people can benefit, the second is the treatment-related adverse events (TRAEs) that occur during treatment, and the third is the emergence of varying degrees of drug resistance with long-term use. How to overcome these challenges, combined therapy based on ICIs has become one of the important strategies. This article summarizes the clinical application of ICIs combined with chemotherapy, targeted therapy, radiotherapy, photodynamic therapy, thermotherapy, immune adjuvant, and dual immunotherapy and discusses the mechanism, and also summarizes the advantages and disadvantages of the current combination modalities and the potential research value. The aim of this study is to provide more and more optimized combination regimen for ICI combined therapy in patients with advanced gastric cancer and to provide reference for clinical and scientific research.

Background: Inflammation and immune factors are the core of intervertebral disc degeneration (IDD), but the immune environment and epigenetic regulation process of IDD remain unclear. This study aims to identify immune-related diagnostic candidate genes for IDD, and search for potential pathogenesis and therapeutic targets for IDD. Methods: Gene expression datasets were obtained from the Gene Expression Omnibus (GEO). Differential expression immune genes (Imm-DEGs) were identified through weighted gene correlation network analysis (WGCNA) and linear models for microarray data analysis (Limma). LASSO algorithm was used to identify feature genes related to IDD, which were compared with core node genes in PPI network to obtain hub genes. Based on the coefficients of hub genes, a risk model was constructed, and the diagnostic value of hub genes was further evaluated through receiver operating characteristic (ROC) analysis. Xcell, an immunocyte analysis tool, was used to estimate the infiltration of immune cells. Finally, nucleus pulposus cells were co-cultured with macrophages to create an M1 macrophage immune inflammatory environment, and the changes of hub genes were verified. Results: Combined with the results of WGCNA and Limma gene differential analysis, a total of 30 Imm-DEGs were identified. Imm-DEGs enriched in multiple pathways related to immunity and inflammation. LASSO algorithm identified 10 feature genes from Imm-DEGs that significantly affected IDD, and after comparison with core node genes in the PPI network of Imm-DEGs, 6 hub genes (NR1H3, SORT1, PTGDS, AGT, IRF1, TGFB2) were determined. Results of ROC curves and external dataset validation showed that the risk model constructed with the 6 hub genes had high diagnostic value for IDD. Immunocyte infiltration analysis showed the presence of various dysregulated immune cells in the degenerative nucleus pulposus tissue. In vitro experimental results showed that the gene expression of NR1H3, SORT1, PTGDS, IRF1, and TGFB2 in nucleus pulposus cells in the immune inflammatory environment was up-regulated, but the change of AGT was not significant. Conclusions: The hub genes NR1H3, SORT1, PTGDS, IRF1, and TGFB2 can be used as immunorelated biomarkers for IDD, and may be potential targets for immune regulation therapy for IDD.

Coronavirus disease 2019 (COVID-19) has been reported to decrease semen quality in reproductive-age men. Semen quality in vaccinated men after SARS-CoV-2 infection remains unclear. We recruited reproductive-age Chinese men scheduled for COVID-19 vaccination from December 2022 to March 2023. Among 1,639 vaccinated participants, an upward trend was found in sperm concentration ( p < .001), progressive motility ( p < .001), total motility ( p < .001), total motile sperm count (TMSC) ( p < .001), and normal morphology ( p = .01) over time following COVID-19 recovery. Among men with an SARS-CoV-2 infection that lasted less than 30 days, men who received an inactivated vaccine booster had higher sperm progressive ( p = .006) and total motility ( p = .005) as well as TMSC ( p = .008) than those without a booster vaccine, whereas no difference was found in semen parameters among men who received a recombinant protein vaccine. Similarly, an upward trend in semen quality was found among 122 men who provided semen samples before and after COVID-19. Higher risks of asthenozoospermia (odds ratio [ OR ] = 2.23, p < .001) and teratozoospermia (OR = 2.09, p = .03) were found among men who had an SARS-CoV-2 infection that lasted less than 30 days than among those without COVID-19. Collectively, after receiving SARS-CoV-2 vaccination, adverse but reversible semen parameters were observed in men recovering from COVID-19 over time. Recombinant protein vaccines and inactivated vaccine boosters should be recommended to all reproductive-age men.

Gastric cancer is highly prevalent in China, yet early diagnosis and overall survival rates are low. The primary treatment strategy is comprehensive therapy centered on surgery. Studies indicate that neoadjuvant chemotherapy can enhance radical resection rates and extend survival in locally advanced gastric cancer. Combining VEGFR inhibitors with chemotherapy improves efficacy in digestive system tumors, while PD-1/PD-L1 inhibitors combined with anti-angiogenesis agents or chemotherapy show synergistic effects. This report presents a case of gastric adenocarcinoma (cT3N1M0) treated with SOX, apatinib mesylate, and camrelizumab as neoadjuvant therapy, followed by D2 distal gastrectomy and postoperative adjuvant therapy with the same regimen. The patient completed all treatment cycles successfully. Post-neoadjuvant therapy, only focal residual cancer cells were found in the lamina propria (pT1a). During postoperative adjuvant therapy follow-up, gastroscopic biopsy indicated a pathological complete response with no recurrence or metastasis. The patient primarily experienced dyspepsia, oropharyngeal pain, capillary proliferation, mild bone marrow suppression, nausea, and vomiting as side effects. Therefore, SOX combined with apatinib mesylate and camrelizumab shows promise for treating resectable locally advanced gastric cancer.

The main objectives of this study are to estimate the biased technical progress in China considering heterogeneity in human capital and labor force, examine how this heterogeneity quantitatively impacts the elasticity of substitution and biased technical progress compared to homogeneous labor assumptions, and compare the growth rates of human capital-augmenting and labor-augmenting technical progress. The estimation procedure involves a constrained Seemingly Unrelated Regression (SUR) using provincial-level panel data from 1985 to 2021. By comparing results with and without accounting for labor force heterogeneity and human capital, the analysis quantifies their impact on the estimated elasticity of substitution between factors and the magnitude and direction of technical bias. Results found that the elasticity of capital-labor (human capital) substitution is between 0.7 and 0.8, and the elements are generally complementary. Although it does not affect the overall trend of elasticity of substitution and biased technical progress, the heterogeneity of human capital and labor force has a quantitative impact on them. It means that the elasticity of substitution increased, and the biased technological progress decreased. Moreover, the growth rate of human capital-augmenting technical progress was significantly lower than that of labor-augmenting technological progress. This study estimates the biased technical progress in China, where the human capital and labor force are heterogeneous. The findings suggest that policymakers should prioritize human capital investments and technological upgrades in industries to rebalance China's technical progress and boost productivity growth.

Abstract The applications of self-assembled InAs/GaAs quantum dots (QDs) for lasers and single photon sources strongly rely on their density and quality. Establishing the process parameters in molecular beam epitaxy (MBE) for a specific density of QDs is a multidimensional optimization challenge, usually addressed through time-consuming and iterative trial-and-error. Here, we report a real-time feedback control method to realize the growth of QDs with arbitrary density, which is fully automated and intelligent. We develop a machine learning (ML) model named 3D ResNet 50 trained using reflection high-energy electron diffraction (RHEED) videos as input instead of static images and providing real-time feedback on surface morphologies for process control. As a result, we demonstrate that ML from previous growth could predict the post-growth density of QDs, by successfully tuning the QD densities in near-real time from 1.5 × 1010 cm−2 down to 3.8 × 108 cm−2 or up to 1.4 × 1011 cm−2. Compared to traditional methods, our approach can dramatically expedite the optimization process and improve the reproducibility of MBE. The concepts and methodologies proved feasible in this work are promising to be applied to a variety of material growth processes, which will revolutionize semiconductor manufacturing for optoelectronic and microelectronic industries.

Abstract Background Anorectal malformations (ARMs) are the most common congenital anomaly of the digestive tract. And colostomy should be performed as the first-stage procedure in neonates diagnosed with intermediate- or high-type ARMs. However, the most classic Pe˜na’s colostomy still has some disadvantages such as complicated operation procedure, susceptibility to infection, a greater possibility of postoperative incision dehiscence, difficulty of nursing and large surgical trauma and incision scarring when closing the stoma. We aimed to explore the effectiveness of middle descending colon-double lumen ostomy (MDCDLO) in the treatment of high and intermediate types of anorectal malformations. Methods We retrospectively reviewed the data of patients who underwent MDCDLO for high or intermediate types of ARMs between June 2016 and December 2021 in our hospital. The basic characteristics were recorded. All patients were followed up monthly to determine if any complication happen. Results There were 17 boys and 6 girls diagnosed with high or intermediate types of ARMs in our hospital between June 2016 and December 2021. All 23 patients were cured without complications such as abdominal incision infection, stoma stenosis, incisional hernia, and urinary tract infection in the postoperative follow-up time of 6 months to 6 years except one case of proximal intestinal prolapse was restored under anesthesia. Conclusion MDCDLO offers the advantages of simplicity, efficiency, safety, mild trauma, and small scarring in the treatment of high and intermediate types of anorectal malformations.

With the advantages of eco-friendliness, low cost, and low density, Mg2(Si,Sn) solid solutions are promising candidates for thermoelectric applications. In this work, Sb-doped Mg2Si0.4Sn0.6 bulks were prepared with a combined method of solid-state reaction and high pressure synthesis, followed by spark plasma sintering. Our investigations show that Sb doping optimizes the carrier concentration, while Si/Sn alloying effectively suppresses the lattice thermal conductivity and induces a convergence of the two lowest-lying conduction bands. Additionally, numerous coherent Sn-rich nanoprecipitates are formed within micron-sized grains. All these factors contribute synergistically to improving the thermoelectric properties of Mg2Si0.4Sn0.6. The optimal Mg2(Si0.4Sn0.6)0.985Sb0.015 exhibits a power factor higher than 4 000 μW·m−1·K−2 and a lattice thermal conductivity less than 0.8 W·m−1·K−1 at temperatures higher than 600 K, leading to the highest ZT of 1.61 at 823 K. Current work demonstrates an effective approach to enhancing the thermoelectric performance of n-type Mg2X solid solutions through doping, alloying, and microstructure modification.

Abstract The metastasis of non-small cell lung cancer (NSCLC) is the leading death cause of NSCLC patients, which requires new biomarkers for precise diagnosis and treatment. Circular RNAs (circRNAs), the novel noncoding RNA, participate in the progression of various cancers as microRNA or protein sponges. We revealed the mechanism by which circEPB41L2 (hsa_circ_0077837) blocks the aerobic glycolysis, progression and metastasis of NSCLC through modulating protein metabolism of PTBP1 by the E3 ubiquitin ligase TRIP12. With ribosomal RNA-depleted RNA seq, 57 upregulated and 327 downregulated circRNAs were identified in LUAD tissues. circEPB41L2 was selected due to its dramatically reduced levels in NSCLC tissues and NSCLC cells. Interestingly, circEPB41L2 blocked glucose uptake, lactate production, NSCLC cell proliferation, migration and invasion in vitro and in vivo. Mechanistically, acting as a scaffold, circEPB41L2 bound to the RRM1 domain of the PTBP1 and the E3 ubiquitin ligase TRIP12 to promote TRIP12-mediated PTBP1 polyubiquitylation and degradation, which could be reversed by the HECT domain mutation of TRIP12 and circEPB41L2 depletion. As a result, circEPB41L2-induced PTBP1 inhibition led to PTBP1-induced PKM2 and Vimentin activation but PKM1 and E-cadherin inactivation. These findings highlight the circEPB41L2-dependent mechanism that modulates the “Warburg Effect” and EMT to inhibit NSCLC development and metastasis, offering an inhibitory target for NSCLC treatment.

Abstract Background Acephalic spermatozoa syndrome is a rare type of teratozoospermia causing male infertility due to detachment of the sperm head and flagellum, which precludes fertilization potential. Although loss-of-function variations in several genes, including TSGA10, have been associated with acephalic spermatozoa syndrome, the genetic cause of many cases remains unclear. Results We recruited a Pakistani family with two infertile brothers who suffered from acephalic spermatozoa syndrome. Through whole-exome sequencing (WES) followed by Sanger sequencing, we identified a novel missense variant in TSGA10 (c.1112T > C, p. Leu371Pro), which recessively co-segregated with the acephalic spermatozoa syndrome within this family. Ultrastructural analyses of spermatozoa from the patient revealed that 98% of flagellar cross-sections displayed abnormal axonemal ultrastructure, in addition to the head-flagellum detachment. Real-time quantitative PCR analysis revealed almost no detectable TSAG10 mRNA and western blot analysis also failed to detect TSAG10 protein in patient's sperm samples while TSGA10 expression was clearly detected in control samples. Consistently, immunofluorescence analysis demonstrated the presence of TSGA10 signal in the midpiece of sperm from the control but a complete absence of TSGA10 signal in sperm from the patient. Conclusion Altogether, our study identifies a novel TSGA10 pathogenic variant as a cause of acephalic spermatozoa syndrome in this family and provides information regarding the clinical manifestations associated with TSGA10 variants in human.

Abstract Rationale Cancer of unknown primary (CUP) is a group of rare malignancies with poor prognosis and unidentifiable tissue-of-origin. Distinct DNA methylation patterns in different tissues and cancer types enable the identification of the tissue of origin in CUP patients, which could help risk assessment and guide site-directed therapy. Methods Using genome-wide DNA methylation profile datasets from The Cancer Genome Atlas (TCGA) and machine learning methods, we developed a 200-CpG methylation feature classifier for CUP tissue of origin prediction (MFCUP). MFCUP was further validated with public-available methylation array data of 2977 specimens and targeted methylation sequencing of 78 Formalin‐fixed paraffin‐embedded (FFPE) samples from a single center. Results MFCUP achieved an accuracy of 97.2% in a validation cohort (n = 5923) representing 25 cancer types. When applied to an Infinium 450 K array dataset (n = 1052) and an Infinium EPIC (850 K) array dataset (n = 1925), MFCUP achieved an overall accuracy of 93.4% and 84.8%, respectively. Based on MFCUP, we established a targeted bisulfite sequencing panel and validated it with FFPE sections from 78 patients of 20 cancer types. This methylation sequencing panel correctly identified tissue of origin in 88.5% (69/78) of samples. We also found that the methylation levels of specific CpGs can distinguish one cancer type from others, indicating their potential as biomarkers for cancer diagnosis and screening. Conclusion Our methylation-based cancer classifier and targeted methylation sequencing panel can predict tissue of origin in diverse cancer types with high accuracy.

Hydrangea xinfeniae W.B.Ju & J.Ru, a new species of Hydrangeaceae from Sichuan Province, China, is described and illustrated. The new species belongs to Hydrangea sect. Dichroa (Lour.) Y.De Smet & Samain, with its distinctive characteristic being the nearly superior ovary. It shares morphological similarities with H. yaoshanensis (Y.C.Wu) Y.De Smet & C.Granados, but can be distinguished by its hirsute trichomes densely covered on the branchlets, leaves, peduncles and pedicels, broadly elliptic to rectangular-elliptic leaf blade with nearly rounded base, coarse teeth leaf margins, 3–4 pairs of lateral veins, corymbose cyme with few and loose branches, lanceolate bract, the calyx tube and lobes margin with sparsely hirsute trichomes, adaxially glabrous and abaxially sparsely hirsute petal, outer whorl filaments are linear, inner ones are awl-shaped, glabrous styles, and the nearly superior ovary. H. xinfeniae sp. nov. currently known from only three relatively small populations of the type locality, and its conservation status is assessed as Data Deficient (DD).

High-frequency quantitative trading in the emerging digital currency market poses unique challenges due to the lack of established methods for extracting trading information. This paper proposes a deep evolutionary reinforcement learning (DERL) model that combines deep reinforcement learning with evolutionary strategies to address these challenges. Reinforcement learning is applied to data cleaning and factor extraction from a high-frequency, microscopic viewpoint to quantitatively explain the supply and demand imbalance and to create trading strategies. In order to determine whether the algorithm can successfully extract the significant hidden features in the factors when faced with large and complex high-frequency factors, this paper trains the agent in reinforcement learning using three different learning algorithms, including Q-learning, evolutionary strategies, and policy gradient. The experimental dataset, which contains data on sharp up, sharp down, and continuous oscillation situations, was chosen to test Bitcoin in January-February, September, and November of 2022. According to the experimental results, the evolutionary strategies algorithm achieved returns of 59.18%, 25.14%, and 22.72%, respectively. The results demonstrate that deep reinforcement learning based on the evolutionary strategies outperforms Q-learning and policy gradient concerning risk resistance and return capability. The proposed approach offers a robust and adaptive solution for high-frequency trading in the digital currency market, contributing to the development of effective quantitative trading strategies.

Genetic risk factors have been shown to contribute to the development of sexual dysfunction. However, the role of methylenetetrahydrofolate reductase (MTHFR) gene variants in the risk of erectile dysfunction (ED) remains unclear. In this study, we recruited 1254 participants who underwent ED assessed by the International Index of Erectile Function-5. The MTHFR c.677C>T variant was also measured by fluorescence polymerase chain reaction (PCR). No significant difference in the genotypic frequency of the MTHFR C677T polymorphism (CC, CT, and TT) was observed between men from the ED and non-ED groups. In addition, on binary logistic regression analysis, both crude and adjusted models showed that the risk of ED was not significantly associated with the C677T polymorphism. Interestingly, a significantly higher frequency of the 677TT polymorphism was found in severe and moderate ED (P = 0.02). The positive correlation between the MTHFR 677TT polymorphism and severe ED was confirmed by logistic regression analysis, even after adjusting for potential confounders (odds ratio [OR] = 2.46, 95% confidence interval [CI]: 1.15–5.50, P = 0.02). These findings suggest a positive correlation between the MTHFR 677TT polymorphism and the risk of severe ED. Identification of MTHFR gene polymorphisms may provide complementary information for ED patients during routine clinical diagnosis.

Abstract The study aims to evaluate and compare the performance of various machine learning (ML) classifiers in the context of detecting cyber-trolling behaviors. With the rising prevalence of online harassment, developing effective automated tools for aggression detection in digital communications has become imperative. This research assesses the efficacy of Random Forest, Light Gradient Boosting Machine (LightGBM), Logistic Regression, Support Vector Machine (SVM), and Naive Bayes classifiers in identifying cyber troll posts within a publicly available dataset. Each ML classifier was trained and tested on a dataset curated for the detection of cyber trolls. The performance of the classifiers was gauged using confusion matrices, which provide detailed counts of true positives, true negatives, false positives, and false negatives. These metrics were then utilized to calculate the accuracy, precision, recall, and F1 scores to better understand each model’s predictive capabilities. The Random Forest classifier outperformed other models, exhibiting the highest accuracy and balanced precision-recall trade-off, as indicated by the highest true positive and true negative rates, alongside the lowest false positive and false negative rates. LightGBM, while effective, showed a tendency towards higher false predictions. Logistic Regression, SVM, and Naive Bayes displayed identical confusion matrix results, an anomaly suggesting potential data handling or model application issues that warrant further investigation. The findings underscore the effectiveness of ensemble methods, with Random Forest leading in the cyber troll detection task. The study highlights the importance of selecting appropriate ML algorithms for text classification tasks in social media contexts and emphasizes the need for further scrutiny into the anomaly observed among the Logistic Regression, SVM, and Naive Bayes results. Future work will focus on exploring the reasons behind this occurrence and the potential of deep learning techniques in enhancing detection performance.

Abstract Background Coronary artery calcification (CAC) is a highly specific marker of atherosclerosis. Niemann-Pick C1-like 1 (NPC1L1) and 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR) are the therapeutic targets of ezetimibe and statins, respectively, which are important for the progression of atherosclerosis. However, CAC’s genetic susceptibility with above targets is still unknown. We aimed to investigate the association of NPC1L1 and HMGCR gene polymorphisms with CAC in patients with premature triple-vessel disease (PTVD). Methods Four single nucleotide polymorphisms (SNPs) (rs11763759, rs4720470, rs2072183, rs2073547) of NPC1L1, and three SNPs (rs12916, rs2303151, rs4629571) of HMGCR were genotyped in 872 PTVD patients. According to the coronary angiography results, patients were divided into low-degree CAC group and high-degree CAC group. Results A total of 872 PTVD patients (mean age, 47.71 ± 6.12; male, 72.8%) were finally included for analysis. Multivariate logistic regression analysis showed no significant association between the SNPs of NPC1L1 and HMGCR genes and high-degree CAC in the total population (P > 0.05). Subgroup analysis by gender revealed that the variant genotype (TT/CT) of rs4720470 on NPC1L1 gene was associated with increased risk for high-degree CAC in male patients only (OR = 1.505, 95% CI: 1.008–2.249, P = 0.046) in dominant model, but no significant association was found in female population, other SNPs of NPC1L1 and HMGCR genes (all P > 0.05). Conclusions We reported for the first time that the rs4720470 on NPC1L1 gene was associated with high-degree CAC in male patients with PTVD. In the future, whether therapies related to this target could reduce CAC and cardiovascular events deserves further investigation.

Hierarchical heterostructures have emerged as promising candidates for the efficient photocatalytic degradation of antibiotics owing to their matched energy levels and tunable absorption bands. Herein, we report the facile synthesis of a heterojunction photocatalyst composed of basic bismuth nitrate (BiON) and BiOCl0.9I0.1 using a simple room-temperature hydrolysis method. Our results demonstrate that the BiON/BiOCl0.9I0.1 composite exhibits superior photodegradation performance compared to pure-phase materials owing to the catalytic enhancement at the heterointerface and the effective separation of the photogenerated carriers. Moreover, the unique three-dimensional microsphere morphology of the synthesized composite enhances its specific surface area and light absorption, further enhancing its photocatalytic activity. In the tetracycline (TC) photodegradation reaction as a model reaction, the catalyst could degrade 88% of TC in just 25 min. Overall, this work provides a promising strategy for the facile and low-cost synthesis of heterogeneous photocatalytic degradation materials.

AbstractGastrochilus sinensis is a beautiful epiphytic orchid with high ornamental value. In this study, the first complete chloroplast genome sequence of G. sinensis was determined using next-generation sequencing (NGS). The de novo assembled chloroplast genome was 148,020 bp in length, including a pair of inverted repeat regions (IRs; 25,987 bp), a small single-copy region (SSC; 11,045 bp), and a large single-copy region (LSC; 85,001 bp). The chloroplast genome encodes 109 unique genes, including 75 protein-coding genes (PCGs), 30 tRNA genes, and four rRNA genes. The total GC content of the chloroplast genome was 36.8%. The phylogenetic analysis showed a close relationship between G. sinensis and G. formosanus species. The complete chloroplast genome provides fundamental information for genetic diversity and phylogenetic relationships in Gastrochilus.

Abstract With the development of artificial intelligence technology and edge computing technology, deep learning-based automatic modulation classification (AI-based AMC) deployed at edge devices using centralised or distributed learning methods for optimisation has emerged in recent years, and has made great progress in the recognition accuracy and recognisable range of wireless signals. However, the lack of sufficient explanation of these models leads to low accuracy and training efficiency of model training, and their applications and further improvements are limited. Researchers have started to propose interpretable methods for technical analysis of deep learning-based AMC. In this paper, based on the research and application development of interpretable methods in recent years, we review the applicable methods and existing research challenges of interpretable automatic modulation classification. And an interpretable AI-based automatic modulation classification framework is proposed to map the interpretability of automatic modulation classification results by obtaining the contribution of wireless signal features to deep learning network training. Experimental results show that the proposed method possesses the ability to explore the classification mechanism of non-transparent auto-modulated classification networks and has the potential to help edge devices train networks with lower energy consumption and higher accuracy.

Background The status of BRCA1/2 genes plays a crucial role in the treatment decision-making process for multiple cancer types. However, due to high costs and limited resources, a demand for BRCA1/2 genetic testing among patients is currently unmet. Notably, not all patients with BRCA1/2 mutations achieve favorable outcomes with poly (ADP-ribose) polymerase inhibitors (PARPi), indicating the necessity for risk stratification. In this study, we aimed to develop and validate a multimodal model for predicting BRCA1/2 gene status and prognosis with PARPi treatment.Methods We included 1695 slides from 1417 patients with ovarian, breast, prostate, and pancreatic cancers across three independent cohorts. Using a self-attention mechanism, we constructed a multi-instance attention model (MIAM) to detect BRCA1/2 gene status from hematoxylin and eosin (H&E) pathological images. We further combined tissue features from the MIAM model, cell features, and clinical factors (the MIAM-C model) to predict BRCA1/2 mutations and progression-free survival (PFS) with PARPi therapy. Model performance was evaluated using area under the curve (AUC) and Kaplan-Meier analysis. Morphological features contributing to MIAM-C were analyzed for interpretability.Results Across the four cancer types, MIAM-C outperformed the deep learning-based MIAM in identifying the BRCA1/2 genotype. Interpretability analysis revealed that high-attention regions included high-grade tumors and lymphocytic infiltration, which correlated with BRCA1/2 mutations. Notably, high lymphocyte ratios appeared characteristic of BRCA1/2 mutations. Furthermore, MIAM-C predicted PARPi therapy response (log-rank p

Inhibiting the death receptor 3 (DR3) signaling pathway in group 3 innate lymphoid cells (ILC3s) presents a promising approach for promoting mucosal repair in individuals with ulcerative colitis (UC). Paeoniflorin, a prominent component of Paeonia lactiflora Pall., has demonstrated the ability to restore barrier function in UC mice, but the precise mechanism remains unclear. In this study, we aimed to delve into whether paeoniflorin may promote intestinal mucosal repair in chronic colitis by inhibiting DR3 signaling in ILC3s. C57BL/6 mice were subjected to random allocation into 7 distinct groups, namely the control group, the 2 % dextran sodium sulfate (DSS) group, the paeoniflorin groups (25, 50, and 100 mg/kg), the anti-tumor necrosis factor-like ligand 1A (anti-TL1A) antibody group, and the IgG group. We detected the expression of DR3 signaling pathway proteins and the proportion of ILC3s in the mouse colon using Western blot and flow cytometry, respectively. Meanwhile, DR3-overexpressing MNK-3 cells and 2 % DSS-induced Rag1−/− mice were used for verification. The results showed that paeoniflorin alleviated DSS-induced chronic colitis and repaired the intestinal mucosal barrier. Simultaneously, paeoniflorin inhibited the DR3 signaling pathway in ILC3s and regulated the content of cytokines (Interleukin-17A, Granulocyte-macrophage colony stimulating factor, and Interleukin-22). Alternatively, paeoniflorin directly inhibited the DR3 signaling pathway in ILC3s to repair mucosal damage independently of the adaptive immune system. We additionally confirmed that paeoniflorin-conditioned medium (CM) restored the expression of tight junctions in Caco-2 cells via coculture. In conclusion, paeoniflorin ameliorates chronic colitis by enhancing the intestinal barrier in an ILC3-dependent manner, and its mechanism is associated with the inhibition of the DR3 signaling pathway.

In the contemporary context marked by globalization and the growing prominence of sustainable development, assessing urban tourism competitiveness has emerged as a crucial research domain. This paper aims to develop a comprehensive model for evaluating city tourism competitiveness, grounded in the principles of sustainable development. The model incorporates factors such as city tourism resources, environmental considerations, economic aspects, and societal factors. This holistic approach seeks to offer valuable insights for the city tourism industry. The study conducts a thorough analysis of current research both domestically and internationally, highlighting gaps and articulating the objectives and significance of the research. Employing a machine learning-based empowerment method, the paper determines the significance of evaluation indices and utilizes the Topsis method for assessing urban tourism competitiveness. Distinguishing itself from traditional evaluation methods, this model integrates the principles of sustainable development throughout the evaluation process, with environmental, social, and economic sustainability serving as pivotal evaluation indicators. Empirical analysis involves the evaluation of tourism competitiveness for select cities, facilitating inter-city comparisons. Results from empirical studies demonstrate the model’s effectiveness in evaluating urban tourism competitiveness, providing targeted developmental recommendations for urban tourism.

BackgroundThe rapid development of artificial intelligence (AI) has brought significant interest to its potential applications in oncology. Although AI-powered tools are already being implemented in some Chinese hospitals, their integration into clinical practice raises several concerns for Chinese oncologists. ObjectiveThis study aims to explore the concerns of Chinese oncologists regarding the integration of AI into clinical practice and to identify the factors influencing these concerns. MethodsA total of 228 Chinese oncologists participated in a cross-sectional web-based survey from April to June in 2023 in mainland China. The survey gauged their worries about AI with multiple-choice questions. The survey evaluated their views on the statements of “The impact of AI on the doctor-patient relationship” and “AI will replace doctors.” The data were analyzed using descriptive statistics, and variate analyses were used to find correlations between the oncologists’ backgrounds and their concerns. ResultsThe study revealed that the most prominent concerns were the potential for AI to mislead diagnosis and treatment (163/228, 71.5%); an overreliance on AI (162/228, 71%); data and algorithm bias (123/228, 54%); issues with data security and patient privacy (123/228, 54%); and a lag in the adaptation of laws, regulations, and policies in keeping up with AI’s development (115/228, 50.4%). Oncologists with a bachelor’s degree expressed heightened concerns related to data and algorithm bias (34/49, 69%; P=.03) and the lagging nature of legal, regulatory, and policy issues (32/49, 65%; P=.046). Regarding AI’s impact on doctor-patient relationships, 53.1% (121/228) saw a positive impact, whereas 35.5% (81/228) found it difficult to judge, 9.2% (21/228) feared increased disputes, and 2.2% (5/228) believed that there is no impact. Although sex differences were not significant (P=.08), perceptions varied—male oncologists tended to be more positive than female oncologists (74/135, 54.8% vs 47/93, 50%). Oncologists with a bachelor’s degree (26/49, 53%; P=.03) and experienced clinicians (≥21 years; 28/56, 50%; P=.054). found it the hardest to judge. Those with IT experience were significantly more positive (25/35, 71%) than those without (96/193, 49.7%; P=.02). Opinions regarding the possibility of AI replacing doctors were diverse, with 23.2% (53/228) strongly disagreeing, 14% (32/228) disagreeing, 29.8% (68/228) being neutral, 16.2% (37/228) agreeing, and 16.7% (38/228) strongly agreeing. There were no significant correlations with demographic and professional factors (all P>.05). ConclusionsAddressing oncologists’ concerns about AI requires collaborative efforts from policy makers, developers, health care professionals, and legal experts. Emphasizing transparency, human-centered design, bias mitigation, and education about AI’s potential and limitations is crucial. Through close collaboration and a multidisciplinary strategy, AI can be effectively integrated into oncology, balancing benefits with ethical considerations and enhancing patient care.

Inkjet-printed quantum dot light-emitting diodes (QLEDs) are emerging as a promising technology for next-generation displays. However, the progress in fabricating QLEDs using inkjet printing technique has been slower compared to spin-coated devices, particularly in terms of efficiency and stability. The key to achieving high performance QLEDs lies in creating a highly ordered and uniform inkjet-printed quantum dot (QD) thin film. In this study, we present a highly effective strategy to significantly improve the quality of inkjet-printed CdZnSe/CdZnS/ZnS QD thin films through a pressure-assisted thermal annealing (PTA) approach. Benefiting from this PTA process, a high quality QD thin film with ordered packing, low surface roughness, high photoluminescence and excellent electrical property is obtained. The mechanism behind the PTA process and its profound impact on device performance have been thoroughly investigated and understood. Consequently, a record high external quantum efficiency (EQE) of 23.08% with an impressive operational lifetime (T50) of up to 343,342 ​h@100 ​cd ​m−2, and a record EQE of 22.43% with T50 exceeding to 1,500,463 ​h@100 ​cd ​m−2 are achieved in inkjet-printed red and green CdZnSe-based QLEDs, respectively. This work highlights the PTA process as an important approach to realize highly efficient and stable inkjet-printed QLEDs, thus advancing QLED technology to practical applications.

Abstract Campylotropis xinfeniae, a new species from the dry‐hot valley of the Jinsha River in the Yunnan province, China, is described and illustrated. It is morphologically similar to C. wilsonii and C. brevifolia in having glabrescent old branches, absent stipels, 3‐foliolate leaves, and adaxially puberulent leaflets, while it differs from the latter two in having often paniculate inflorescences, obviously white standard, not incurved sickle keel, larger narrowly oblique legumes, and longer legume beak. The complete chloroplast genome of this new species is 149,073 bp in length and exhibits a typical quadripartite structure. Phylogenetic analyses based on the complete chloroplast genome also supported C. xinfeniae as a new species located at the basal distinct clade of the genus Campylotropis, clearly separated from the remaining members of the genus and its allied genera. A conservation assessment of data deficient (DD) is recommended for the new species without extensive exploring of similar habitats according to the IUCN Categories and Criteria.

ObjectiveTo examine the impact of tobacco smoking on seminal parameters in men with both primary and secondary infertility.MethodsThis cross-sectional study analyzed 1938 infertile men from China who were categorized as nonsmokers (n=1,067) and smokers (n=871), with the latter group further divided into moderate smokers (1-10 cigarettes per day) (n=568) and heavy smokers (>10 cigarettes per day) (n=303). We assessed semen volume, concentration, total sperm count, progressive motility, and normal morphology following World Health Organization (WHO 2010) guidelines. A logistic regression model was used to analyze the relationships between smoking and seminal parameters while also controlling for lifestyle factors.ResultsThe analysis demonstrated a statistically significant correlation between smoking and adverse seminal parameters in both primary and secondary infertility patients. Specifically, primary infertile men who smoked had a lower semen concentration, with heavy smokers showing a median sperm concentration of 59.2×10^6/ml compared to 68.6×10^6/ml in nonsmokers (P=0.01). The secondary infertile men who smoked exhibited reduced forward sperm motility, with heavy smokers demonstrating a median progressive motility of 44.7%, which was significantly lower than the 48.1% observed in nonsmokers (P=0.04).ConclusionSmoking is significantly associated with detrimental effects on seminal parameters in infertile men, thus highlighting the need for cessation programs as part of fertility treatment protocols. Encouraging smoking cessation could substantially improve semen quality and fertility outcomes in this population.

BackgroundDefinitive concurrent chemoradiotherapy (CCRT) followed by maintenance therapy with immune checkpoint inhibitors offers the best chance of cure for patients with stage III non-small cell lung cancer (NSCLC). A significant challenge in this regimen is the occurrence of acute severe lymphopenia (ASL), which can compromise treatment efficacy. Currently, there are no effective strategies for preventing and treating ASL. Shenglin decoction (SLD), a traditional Chinese herbal medicine formulation, has demonstrated preliminary efficacy in mitigating ASL. However, robust evidence from clinical trials and a clear understanding of its mechanism of action are still needed. This study aims to comprehensively assess the efficacy, safety, and underlying mechanisms of SLD in the prevention of ASL.MethodsThis prospective, dual-center, open-label, randomized controlled trial will enroll 140 stage III NSCLC patients. Participants will be randomly allocated in a 1:1 ratio to a control group or an experimental group. Both groups will undergo definitive CCRT. Alongside the commencement of CCRT, the experimental group will receive an additional oral SLD intervention for a duration of three months. The primary outcome is the incidence rate of ASL, defined as the proportion of patients who experience at least one instance of a total lymphocyte count falling below 0.5 × 10^9 cells/L within 3 months of initiating CCRT treatment. Additionally, 16S rRNA gene sequencing analysis of fecal samples to assess gut microbiota, as well as metabolomic analysis of fecal/blood samples, will be conducted to explore potential mechanisms.DiscussionThis study protocol aims to rigorously evaluate the efficacy and safety of SLD, as well as elucidate its mechanism of action in preventing ASL. Successful outcomes could establish SLD as an evidence-based intervention for ASL prevention in NSCLC patients undergoing CCRT.Trial RegistrationThe trial was registered at the Chinese Clinical Trials Registry (ChiCTR2300071788, https://www.chictr.org.cn/).

Di-hexyl phthalate (2-ethylhexyl) (DEHP) has been confirmed to cause female reproductive toxicity in humans and model animals by affecting the survival of ovarian granulosa cells (GCs), but the interrelationships between DEHP's on autophagy, apoptosis, and inflammation in GCs are not clear. Our previous study demonstrated that DEHP exposure resulted in the disturbance of intestinal flora associated with serum LPS release, which in turn led to impaired ovarian function. LPS has also been shown to determine cell fate by modulating cellular autophagy, apoptosis, and inflammation. Therefore, this study investigated the role and link between LPS and autophagy, apoptosis, and inflammation of GCs in DEHP-induced ovarian injury. Here, we constructed an in vivo injury model by continuous gavage of 0–1500 mg/kg of DEHP in female mice for 30 days and an in vitro injury model by treatment of human ovarian granulosa cells (KGN) cells with mono-2- ethylhexyl ester (MEHP, an active metabolite of DEHP in vivo). In addition, the expression of relevant pathway molecules was detected by immunohistochemistry, immunofluorescence, qRT-PCR, and Western blotting after the addition of the autophagy inhibitor 3-methyladenine (3-MA), the apoptosis inhibitor Z-VAD- FMK and the NF-κB inhibitor BAY11-7082. The current study found that autophagy and apoptosis were significantly activated in GCs of DEHP-induced atretic follicles in vivo and found that MEHP-induced KGN cells autophagy and apoptosis were independent and potentially cytotoxic of each other in vitro. Further studies confirmed that DEHP exposure resulted in LPS release from the intestinal tract and entering the ovary, thereby participating in DEHP-induced inflammation of GCs. In addition, we found that exogenous LPS synergized with MEHP could activate the NF-κB signaling pathway to induce inflammation and apoptosis of GCs in a relatively prolonged exposure condition. Meanwhile, inhibition of inflammatory activation could rescue apoptosis and estrogen secretion function of GCs induced by MEHP combined with LPS. These results indicated that the increased LPS influenced by DEHP might cooperate with MEHP to induce inflammatory apoptosis of GCs, an important cause of ovarian injury in mice.

Particulate nitrate, a key component of fine particles, forms through the intricate gas-to-particle conversion process. This process is regulated by the gas-to-particle conversion coefficient of nitrate (ε(NO3−)). The mechanism between ε(NO3−) and its drivers is highly complex and nonlinear, and can be characterized by machine learning methods. However, conventional machine learning often yields results that lack clear physical meaning and may even contradict established physical/chemical mechanisms due to the influence of ambient factors. It urgently needs an alternative approach that possesses transparent physical interpretations and provides deeper insights into the impact of ε(NO3−). Here we introduce a supervised machine learning approach—the multilevel nested random forest guided by theory approaches. Our approach robustly identifies NH4+, SO42−, and temperature as pivotal drivers for ε(NO3−). Notably, substantial disparities exist between the outcomes of traditional random forest analysis and the anticipated actual results. Furthermore, our approach underscores the significance of NH4+ during both daytime (30%) and nighttime (40%) periods, while appropriately downplaying the influence of some less relevant drivers in comparison to conventional random forest analysis. This research underscores the transformative potential of integrating domain knowledge with machine learning in atmospheric studies.

Excessive cadmium (Cd) in rice, caused by Cd pollution of farmlands, poses a serious threat to human health. In this study, a pot experiment was conducted to investigate the effects of two doses of CaCO3 (Ca1: 2 g kg-1, Ca2: 10g kg-1), two types of Fe(II) (EDTA-Fe(II) and FeSO4; 0.14 g Fe kg-1), and their combined application on the uptake and accumulation of Cd in rice plants grown in Cd-contaminated acidic soil. The results revealed that FeSO4 significantly increased rice grain biomass, whereas the other treatments had no significant effects. Further, the addition of EDTA-Fe(II) or FeSO4 significantly enhanced iron plaque formation on the root surface and increased the Fe content in the rice plants and porewater. Compared to the control, CaCO3 addition weakened the formation of iron plaque and reduced the Fe concentration in the porewater and root tissue, stems and leaves, whereas the Fe concentration in brown rice and the husks remained unaffected. Combined application of CaCO3 and Fe(II) significantly promoted the formation of iron plaque and increased the Fe concentration in brown rice. However, the Cd concentration in the iron plaque was reduced by CaCO3 addition but increased by Fe(II) treatment. Notably, all treatments reduced the Cd concentration in all rice plant tissues. The application of Ca1, Ca2, EDTA-Fe(II), FeSO4, Ca1+EDTA-Fe(II), Ca1+FeSO4, Ca2+EDTA-Fe(II) and Ca2+FeSO4 significantly reduced the Cd concentration in brown rice by 69%, 63%, 51%, 60%, 46%, 39%, 38%, and 29%, respectively. These results indicate that the application of CaCO3, EDTA-Fe(II)/FeSO4, or their combination can effectively reduce Cd accumulation and translocation in rice plants.

The brain topology highly reflects the complex cognitive functions of the biological brain after million-years of evolution. Learning from these biological topologies is a smarter and easier way to achieve brain-like intelligence with features of efficiency, robustness, and flexibility. Here we proposed a brain topology-improved spiking neural network (BT-SNN) for efficient reinforcement learning. First, hundreds of biological topologies are generated and selected as subsets of the Allen mouse brain topology with the help of the Tanimoto hierarchical clustering algorithm, which has been widely used in analyzing key features of the brain connectome. Second, a few biological constraints are used to filter out three key topology candidates, including but not limited to the proportion of node functions (e.g., sensation, memory, and motor types) and network sparsity. Third, the network topology is integrated with the hybrid numerical solver-improved leaky-integrated and fire neurons. Fourth, the algorithm is then tuned with an evolutionary algorithm named adaptive random search instead of backpropagation to guide synaptic modifications without affecting raw key features of the topology. Fifth, under the test of four animal-survival-like RL tasks (i.e., dynamic controlling in Mujoco), the BT-SNN can achieve higher scores than not only counterpart SNN using random topology but also some classical ANNs (i.e., long-short-term memory and multi-layer perception). This result indicates that the research effort of incorporating biological topology and evolutionary learning rules has much in store for the future.

While nanocrystals in group II-IV semiconductors have been extensively studied as photosensitizers in quantum dot-sensitized solar cells (QDSCs), their practical use is severely hampered by the high toxicity of the heavy metals, like Cd, Pb, and Hg, present in these semiconductors. Our present work is based on a proposition to use a “green” alternative to the currently used sensitizers, namely CuInS2 which is a low-toxic semiconductor. However, as for many other types of QDs, surface defects limit also their photovoltaic performance. Therefore, in order to passivate the surface defects and improve the performance of CuInS2 QDs we explore in this work two strategies - ZnS shell coating and hybrid passivation. The results show that although ZnS shell coating can effectively passivate the surface defects, the electron injection from QDs to TiO2 nanoparticle is also hampered. Moreover, the size of CuInS2 QDs is increased after the shell coating, which also is unfavorable for the enhancement of the solar cells efficiency. In contrast, hybrid passivation can passivate the surface defects on the CuInS2 QDs without size changing, and can increase the loading efficiency of the QDs simultaneously. Consequently, the efficiency of the solar cells is improved to 4.7%, which is a promising result for the green CuInS2 based QDSCs. Therefore, in addition to the most used shell coatings of CuInS2 QDs, hybrid passivation may be an effective way for improving their photovoltaic performance. This study employs two strategies “hybrid passivation and ZnS shell coating” and discuss about their effect in solar cell efficiency.