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Abstract Objectives This study aimed to assess the predictive value of radiomics derived from intratumoral and peritumoral regions and to develop a radiomics nomogram to predict preoperative nuclear grade and overall survival (OS) in patients with clear cell renal cell carcinoma (ccRCC). Methods The study included 395 patients with ccRCC from our institution. The patients in Center A (anonymous) institution were randomly divided into a training cohort (n = 284) and an internal validation cohort (n = 71). An external validation cohort comprising 40 patients from Center B also was included. Computed tomography (CT) radiomics features were extracted from the internal area of the tumor (IAT) and IAT combined peritumoral areas of the tumor at 3 mm (PAT 3 mm) and 5 mm (PAT 5 mm). Independent predictors from both clinical and radiomics scores (Radscore) were used to construct a radiomics nomogram. Kaplan–Meier analysis with a log-rank test was performed to evaluate the correlation between factors and OS. Results The PAT 5-mm radiomics model (RM) exhibited exceptional predictive capability for grading, achieving an area under the curves of 0.80, 0.80, and 0.90 in the training, internal validation, and external validation cohorts. The nomogram and RM gained from the PAT 5-mm region were more clinically useful than the clinical model. The association between OS and predicted nuclear grade derived from the PAT 5-mm Radscore and the nomogram-predicted score was statistically significant (p

Abstract Background Esophageal carcinoma (EC) and gastric cardiac adenocarcinoma (GCA) have high incidence rates in the Chaoshan region of South China. Multifocal esophageal and cardiac cancer (MECC) is commonly observed in this region in clinical practice. However, the genomic characteristics of MECC remains unclear. Materials and methods In this study, a total of 2123 clinical samples of EC and GCA were analyzed to determine the frequency of multifocal tumors, as well as their occurrence sites and pathological types. Cox proportional hazards regression was used to model the relationship between age, sex, and tumor state concerning survival in our analysis of the cohort of 541 patients with available follow-up data. We performed whole-genome sequencing on 20 tumor foci and 10 normal samples from 10 MECC patients to infer clonal structure on 6 MECC patients to explore genome characteristics. Result The MECC rate of EC and GCA was 5.65% (121 of 2123). Age and sex were potential factors that may influence the risk of MECC (p

The association between the exposure of organochlorine pesticides (OCPs) and serum uric acid (UA) levels remained uncertain. In this study, to investigate the combined effects of OCP mixtures on hyperuricemia, we analyzed serum OCPs and UA levels in adults from the National Health and Nutrition Examination Survey (2005–2016). Four statistical models including weighted logistic regression, weighted quantile sum (WQS), quantile g-computation (QGC), and bayesian kernel machine regression (BKMR) were used to assess the relationship between mixed chemical exposures and hyperuricemia. Subgroup analyses were conducted to explore potential modifiers. Among 6,529 participants, the prevalence of hyperuricemia was 21.15%. Logistic regression revealed a significant association between both hexachlorobenzene (HCB) and trans-nonachlor and hyperuricemia in the fifth quintile (OR: 1.54, 95% CI: 1.08–2.19; OR: 1.58, 95% CI: 1.05–2.39, respectively), utilizing the first quintile as a reference. WQS and QGC analyses showed significant overall effects of OCPs on hyperuricemia, with an OR of 1.25 (95% CI: 1.09–1.44) and 1.20 (95% CI: 1.06–1.37), respectively. BKMR indicated a positive trend between mixed OCPs and hyperuricemia, with HCB having the largest weight in all three mixture analyses. Subgroup analyses revealed that females, individuals aged 50 years and above, and those with a low income were more vulnerable to mixed OCP exposure. These results highlight the urgent need to protect vulnerable populations from OCPs and to properly evaluate the health effects of multiple exposures on hyperuricemia using mutual validation approaches.

Abstract Background Impaired functional capacity is a common symptom in patients with heart failure. Standard measures of left ventricular (LV) function, such as ejection fraction (EF) and LV diastolic parameters, do not correlate with measures of functional capacity. The aim of this study is to determine if measures of global and regional LV strain better correlate with 6-minute walk distance than does EF or measures of LV diastolic function. Methods 120 patients referred to a cardiology clinic for evaluation of known or suspected heart failure were approached for enrollment. Of those 120 patients, 58 had an echocardiogram within 3 months of enrollment with images adequate for regional and global strain assessment, had no contra-indication to exercise testing, and had no previously documented non-cardiac explanation for dyspnea on exertion. In those 58 patients, 6-minute walk distance was measured, LV EF was determined with Simpson’s biplane method, and global and regional longitudinal strain were measured with TomTec Image Arena 4.5.1 software. Results LV EF had no correlation with 6-minute walk distance (r = 0.22, p = 0.09) even when controlling for age, gender, and BMI (p = 0.07). No measures of LV diastolic function (including E velocity, Deceleration Time, e’ annular velocities, or E/e’) had a correlation with 6-minute walk distance. Multiple measures of global and regional LV longitudinal systolic function had a correlation with 6-minute walk distance. Longitudinal strain of the basal LV segments had the strongest correlation with 6-minute walk distance (r= -0.36, p = 0.005), and correlation persisted after controlling for age, gender, BMI, and systolic blood pressure (p = 0.004). Conclusions Longitudinal strain correlates with a measure of functional capacity, but LVEF and traditional measures of LV diastolic dysfunction do not. Measures of longitudinal strain, especially in basal LV segments, will likely be an important marker of clinically relevant LV function. Graphical Abstract

The accurate fenestration, screw implantation and assisting stabilizing‐plate placement in surgery of benign tumors in the proximal femur needs be defined easily. The aim of this study was to investigate the value of 3D printed multifunctional guides plate (3D‐MGP) based on computer aided design. Between January 2020 and June 2022, 17 patients (nine females and eight males) with benign proximal femoral tumor had lesion curettage and allograft combined with internal plate fixation using 3D‐MGP. In this study, the patients had CT scans and a technician reconstructed the 3D images of tumor and the femur, a doctor designed the location and margin of the fenestration and screws, and integrated different functions into MGP for benign proximal femoral lesions, which assisted in precise localization, fenestration and screw drilling. Musculoskeletal Tumor Society (MSTS) scoring was used to evaluate lower extremity function. Bone healing and the screws location was assessed with the radiographs. All patients underwent successful surgery with complete resection of the tumor and internal fixation with using the 3D‐MGP. The mean follow‐up was 16.4 months. The operative time was 126.47 ± 18.44 min, intraoperative bleeding was 198.23 ± 67.94 mL, intraoperative fluoroscopy was 6.47 ± 0.62, postoperative drainage was 223.82 ± 119.51 mL, and MSTS score was 27.29 ± 1.31 points. There were no unplanned fenestration and improper screw fixation. The 3D‐MGP enabled personalized and accurate location of tumor, fenestration, screw placement and assisted stabilizing‐plate placement for the treatment of benign tumor of the proximal femur. This technique has the potential to shorten operative times, decrease intraoperative bleeding, and reduce radiation exposure to patients.

Abstract Background Simulation is widely utilized in medical education. Exploring the effectiveness of high-fidelity simulation of clinical research within medical education may inform its integration into clinical research training curricula, finally cultivating physician-scientist development. Methods Standard teaching scripts for both clinical trial and cross-sectional study simulation were designed. We recruited undergraduates majoring in clinical medicine at 3th grade into a pre-post intervention study. Additionally, a cross-sectional survey randomly selected medical undergraduates at 4th or 5th grade, medical students in master and doctor degree as external controls. Self-assessment scores of knowledge and practice were collected using a 5-point Likert scale. Changes in scores were tested by Wilcoxon signed-rank test and group comparisons were conducted by Dunn’s tests with multiple corrections. Multivariable quantile regressions were used to explore factors influencing the changes from baseline. Results Seventy-eight undergraduates involved the clinical trial simulation and reported improvement of 1.60 (95% CI, 1.48, 1.80, P

Abstract Learning with noisy labels aims to train neural networks with noisy labels. Current models handle instance-independent label noise (IIN) well; however, they fall short with real-world noise. In medical image classification, atypical samples frequently receive incorrect labels, rendering instance-dependent label noise (IDN) an accurate representation of real-world scenarios. However, the current IDN approaches fail to consider the typicality of samples, which hampers their ability to address real-world label noise effectively. To alleviate the issues, we introduce typicality- and instance-dependent label noise (TIDN) to simulate real-world noise and establish a TIDN-combating framework to combat label noise. Specifically, we use the sample’s distance to decision boundaries in the feature space to represent typicality. The TIDN is then generated according to typicality. We establish a TIDN-attention module to combat label noise and learn the transition matrix from latent ground truth to the observed noisy labels. A recursive algorithm that enables the network to make correct predictions with corrections from the learned transition matrix is proposed. Our experiments demonstrate that the TIDN simulates real-world noise more closely than the existing IIN and IDN. Furthermore, the TIDN-combating framework demonstrates superior classification performance when training with simulated TIDN and actual real-world noise.

Abstract The IPv6 extension header mechanism, a new feature of the IPv6 protocol, enhances flexibility and scalability but introduces numerous security threats like firewall evasion and covert channels. Existing threat detection methods face limitations in detection types, universality, and speed. Hence, an adaptive detection model for IPv6 extension header threats (ADM-DDA6) is proposed. Firstly, standard rule sets are designed for common IPv6 extension headers, successfully detecting 70 types of threats from THC-IPv6 and ExtHdr tools using only 20 rules. Secondly, by parsing IPv6 extension headers, matching rules, establishing transition relationships, and deciding packet threat status based on final states (Normal or Abnormal), complex threats like header disorder and header repetition can be detected. Finally, an adaptive rule matching method is introduced, which dynamically selects rule sets based on IPv6 extension header types, effectively reducing rule matching time. Experimental results show that under different threat magnitudes, ADM-DDA6 is 32% faster than Suricata v6.0.12 and 21.2% faster than Snort v3.1.61.0 in detection speed. Additionally, as the number of threats increases, on commodity hardware, ADM-DDA6 incurs only a 0.7% increase in CPU overhead with no significant memory consumption increase, maintains maximum throughput, and exhibits minor performance changes under low and moderate network load conditions.

Abstract Interstitial lung disease (ILD) can lead to lung cancer, which brings great challenges to differential diagnosis and comprehensive treatment. However, the clinical features of lung-dominant connective tissue disease (LD-CTD) related ILD combined with lung cancer has not been validated. We report the case of an 80-year-old woman with LD-CTD treated regularly with nintedanib who presented progressive dyspnoea and hypoxemia after recurrent viral infections. Her chest computed tomography (CT) showed aggravated interstitial fibrosis in both lower lungs with moderate right pleural effusion. Clinicians should be alert to lung cancer in patients who are experiencing poor responsiveness to treatment or acute progression of ILD. The available literatures about the differential diagnosis of clinical manifestations, imaging, treatment and prognosis of LD-CTD are reviewed and discussed in this study.

Abstract Electroencephalography (EEG) microstate analysis is a neuroimaging analytical method that has received considerable attention in recent years and is widely used for analysing EEG signals. EEG is easily influenced by internal and external factors, which can affect the repeatability and stability of EEG microstate analysis. However, there have been few reports and publicly available datasets on the repeatability of EEG microstate analysis. In the current study, a 39-year-old healthy male underwent a total of 60 simultaneous electroencephalography and electrocardiogram measurements over a period of three months. After the EEG recording was completed, magnetic resonance imaging (MRI) was also conducted. To date, this EEG dataset has the highest number of repeated measurements for one individual. The dataset can be used to assess the stability and repeatability of EEG microstates and other analytical methods, to decode resting EEG states among subjects with open eyes, and to explore the stability and repeatability of cortical spatiotemporal dynamics through source analysis with individual MRI.

Abstract Objectives We aim to analyse the effects of government subsidies on residents’ health and healthcare expenditure from the perspectives of supply and demand. Data and methods According to the regional division adopted in the data query system of the National Bureau of Statistics, this study divides 31 provinces and cities into three regions: eastern, central, and western. The data used are from public databases, such as the “China Statistical Yearbook,” “China Health Statistical Yearbook,” and “Government Final Account Report”. In this study, mathematical model derivation is used to construct a fixed effects model, and an empirical study based on cross-sectional data and general linear regression is conducted. To prevent endogeneity issues, this study introduces instrumental variables and uses 2SLS regression to further analyse the output results. Results For every 1% increase in supplementary funding on the supply side, the perinatal mortality rate decreases by 1.765%, while for every 1% increase in financial compensation on the demand side, per capita outpatient expenses increase by 0.225% and per capita hospitalization expenses increase by 0.196%. Regarding medical resources, for every 1% increase in the number of beds per 1,000 people, per capita hospitalization expenses decrease by 0.099%. In the central and eastern regions, where economic levels are higher, supply-side government funding is more effective than demand-side funding. In contrast, demand-side funding is more effective in the western region. Conclusions The roles of multiple influencing factors and significant regional heterogeneity are clarified. Increasing financial compensation to providers positively impacts perinatal mortality but leads to higher per capita outpatient and hospital expenditures. Finally, this study provides targeted policy recommendations and solid theoretical support for policymakers.

Abstract Background Quitting support from smokers’ partners can predict quit attempts and smoking abstinence but research on factors that predict such support has been limited. To add more evidence for partner support and the improved interventions for smoking cessation, we analyzed some new potential predictors of quitting support from smokers’ spouses. Method This cross-sectional study was conducted in in 2022 and 2023, selecting the students’ families in which fathers smoked and mothers didn’t smoke from grade 1–5 of 13 primary schools in Qingdao, China. Parents who met the criteria completed the online questionnaires and 1018 families were included in the analysis. We measured personal information related to smokers and their spouses such as age, education and nicotine dependence, and variables related to family and marital relationship such as family functioning, perceived responsiveness and power in decision-making of quitting smoking. Quitting support from smokers’ spouses was measured by Partner Interaction Questionnaire and generalized linear model was used to explore the potential predictors of partner support. Results In this study, the mean age of smokers was 39.97(SD = 5.57) and the mean age of smokers’ spouses was 38.24(SD = 4.59). The regression analysis showed that for smokers and their spouses, the older age groups showed the lower ratio of positive/negative support(P

Abstract Tea is an indispensable beverage in people’s daily life. However, the relationship between tea intake and dental caries and periodontitis is controversial. We extracted datasets for tea intake and oral diseases from genome-wide association studies (GWASs) conducted by the UK Biobank and the Gene Lifestyle Interactions in Dental Endpoints consortium. We selected 38 single-nucleotide polymorphisms (SNPs) significantly associated with tea intake as instrumental variables (IVs) (P

Abstract Background Individual patients with ovarian cancer show remarkably different prognosis. Present prognostic models for ovarian cancer mainly focus on clinico-pathological parameters, so quantifiable prognostic markers at molecular level are urgently needed. Platelets contribute to ovarian cancer progression, but have not been considered as biomarkers likely due to their instability. Here, we aimed to search for a stable prognostic marker from platelet-treated ovarian cancer cells, and explore its functions and mechanisms. Methods Microarrays analysis was done with platelet-treated SKOV-3 ovarian cancer cells. Relevant studies were searched in the Gene Expression Omnibus (GEO) database. The candidate genes were determined by differentially expressed genes (DEGs), Venn diagram drawing, protein-protein interaction (PPI) network, Cox proportional hazards model and Kaplan-Meier analysis. The expression of TGFBI in clinical samples was assessed by immunehistochemical staining (IHC), and the association of TGFBI levels with the clinic-pathological characteristics and prognosis in ovarian cancer patients was evaluated by univariate and multivariate analysis. The functions of TGFBI were predicted using data from TCGA, and validated by in vitro and in vivo experiments. The mechanism exploration was performed based on proteomic analysis, molecular docking and intervention study. Results TGFBI was significantly higher expressed in the platelet-treated ovarian cancer cells. An analysis of bioinformatics data revealed that increased expression of TGFBI led to significant decrease of overall survival (OS), progression-free survival (PFS) and post-progression survival (PPS) in ovarian cancer patients. Tissue microarray results showed that TGFBI was an independent factor for ovarian cancer, and TGFBI expression predict poor prognosis. Functionally, TGFBI affected the migration and invasion of ovarian cancer cells by regulation of epithelial mesenchymal transition (EMT) markers (CDH1 and CDH2) and extracellular matrix (ECM) degradation proteins (MMP-2). Mechanistically, TGFBI phosphorylated PI3K and Akt by combining integrin αvβ3. Conclusions We found out TGFBI as a novel prognostic indicator for ovarian cancer patients. TGFBI could promote metastasis in ovarian cancer by EMT induction and ECM remodeling, which might be associated with the activation of integrin αvβ3-PI3K-Akt signaling pathway.

Abstract Alzheimer’s disease (AD) is a neurodegenerative disease with insidious onset and progressive development. It is clinically characterized by cognitive impairment, memory impairment and behavioral change. Chinese herbal medicine and acupuncture are important components of traditional Chinese medicine (TCM), and are commonly used in clinical treatment of AD. This paper systematically summarizes the research progress of traditional Chinese medicine natural products and acupuncture treatment of AD, which combined with existing clinical and preclinical evidence, based on a comprehensive review of neuroinflammation, and discusses the efficacy and potential mechanisms of traditional Chinese medicine natural products and acupuncture treatment of AD. Resveratrol, curcumin, kaempferol and other Chinese herbal medicine components can significantly inhibit the neuroinflammation of AD in vivo and in vitro, and are candidates for the treatment of AD. Acupuncture can alleviate the memory and cognitive impairment of AD by improving neuroinflammation, synaptic plasticity, nerve cell apoptosis and reducing the production and aggregation of amyloid β protein (Aβ) in the brain. It has the characteristics of early, safe, effective and benign bidirectional adjustment. The purpose of this paper is to provide a basis for improving the clinical strategies of TCM for the treatment of AD. Graphical Abstract

Abstract This paper studies the rating lives of wind turbine main bearings, as determined by the IEC 61400‐1 and ISO 281 standards. A critical review of relevant bearing life theory and turbine design requirements is provided, including discussion on possible shortcomings such as the existence (or not) of the bearing fatigue load limit and the validity of assuming linear damage accumulation. A detailed exploratory case study is then undertaken to determine rating lives for two models of main bearing in a 1.5 MW wind turbine. Rating life assessment is carried out under different conditions, including various combinations of main bearing temperature, wind field characteristics, lubricant viscosity, and contamination levels. Rating lives are found to be sufficiently above the desired 20‐year design life for both bearing models under expected operating conditions. For the larger bearing, operational loads are shown to be below or close to the bearing fatigue load limit a vast majority of the time. Key sensitivities for rating life values are temperature and contamination. Overall, the results of this study suggest that an ISO 281 rating life assessment does not account for reported rates of main bearing failures in 1 to 3 MW wind turbines. It is recommended that a similar analysis be undertaken for ISO/TS 16281 rating lives, along with further efforts to identify principal root causes of main bearing failures in future work, possibly leading to a new application standard specific to this component. It is also recommended that the impacts of partial wake impingement on main bearing rating lives are investigated.

Objectives: The aim of this research was to investigate the functions of Piezo channels in dentin defect, including mechanical signalling and odontoblast responses. Methods: Rat dentin-defect models were constructed, and spatiotemporal expression of Piezo proteins was detected in the pulpo-dentinal complex. Real-time polymerase chain reaction (rtPCR) was used to investigate the functional expression pattern of Piezo channels in odontoblasts. Moreover, RNA interference technology was employed to uncover the underlying mechanisms of the Piezo-driven inflammatory response and repair under fluid shear stress (FSS) conditions in vitro. Results: Piezo1 and Piezo2 were found to be widely expressed in the odontoblast layer and dental pulp in the rat dentin-defect model during the end stage of reparative dentin formation. The expression levels of the Piezo1 and Piezo2 genes in MDPC-23 cells were high in the initial stage under FSS loading and then decreased over time. Moreover, the expression trends of inflammatory, odontogenic, and mineralisation genes were generally contrary to those of Piezo1 and Piezo2 over time. After silencing of Piezo1/Piezo2, FSS stimulation resulted in significantly higher expression of inflammatory, odontogenesis, and mineralisation genes in MDPC-23 cells. Finally, the expression of genes involved in the integrin β1/ERK1 and Wnt5b/β-catenin signalling pathways was changed in response to RNA silencing of Piezo1 and Piezo2. Conclusions: Piezo1 and Piezo2 may be involved in regulating the expression of inflammatory and odontogenic genes in odontoblasts stimulated by FSS.

Background: Organophosphate esters (OPEs) and Per- and polyfluoroalkyl substances (PFAS) are ubiquitous environmental contaminants with common exposure sources, leading to their widespread presence in human body. However, evidence on co-exposure to OPEs and PFAS and its impact on cardiovascular-kidney-liver-metabolic biomarkers remains limited. Methods: In this cross-sectional study, 467 adults were enrolled from January to May 2022 during physical visits in Shijiazhuang, Hebei province. Eleven types of OPEs and twelves types of PFAS were detected, among which eight OPEs and six PFAS contaminants were detected in more than 60% of plasma samples. Seventeen biomarkers were assessed to comprehensively evaluate the cardiovascular-kidney-liver-metabolic function. Multiple linear regression, multipollutant models with sparse partial least squares, and Bayesian kernel machine regression (BKMR) models were applied to examine the associations of individual OPEs and PFAS and their mixtures with organ function and metabolism, respectively. Results: Of the over 400 exposure–outcome associations tested when modelling, we observed robust results across three models that perfluorohexanoic acid (PFHxS) was significantly positively associated with alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin (TBIL), and indirect bilirubin (IBIL). Perfluorononanoic acid was significantly associated with decreased AST/ALT and increased very-low-density lipoprotein cholesterol levels. Besides, perfluorodecanoic acid was correlated with increased high lipoprotein cholesterol and perfluoroundecanoic acid was consistently associated with lower glucose level. BKMR analysis showed that OPEs and PFAS mixtures were positively associated with IBIL and TBIL, among which PFHxS was the main toxic chemicals. Conclusions: Our findings suggest that exposure to OPEs and PFAS, especially PFHxS and PFNA, may disrupt organ function and metabolism in the general population, providing insight into the potential pathophysiological mechanisms of OPEs and PFAS co-exposure and chronic diseases.

The ionic compressor is an advanced and prospective compression technology for hydrogen storage. However, a complex wave phenomenon was observed inside the compression chamber due to the fluid flow vortex. This complex gas-fluid interaction can be intervened by a new mechanical design of the motion piston. In this paper, the thermodynamic performance of a novel homocentric two-piston ionic compressor was carried out by mathematical modelling of one compression cycle. The optimisation of the design parameters of the compressor proposed was conducted by the Taguchi method. This study found that the piston diameter ratio was the dominating factor accounting for more than 80 % of the contribution to the mass delivered, power consumption and specific energy consumption. The optimal design parameters were obtained as 0.7 for the piston diameter ratio, 0.5 for the stroke diameter ratio of Piston A and 0.1 for the trajectory parameter. Under the optimal design parameters, the specific energy consumption was obtained as 1563.38 kJ/kg.

Deep brain stimulation (DBS) is an established safe neurosurgical symptomatic therapy for Parkinson's disease (PD) in whom medical treatment fails to provide adequate symptom control. Skin-related complications, particularly skin erosion, may lead to exposure of the DBS device, compromising the effectiveness of the DBS device. We presented a patient who suffered from skin erosion over bilateral burr hole site. A Multidisciplinary Team (MDT) approach was used to provide staged surgical treatment for scalp reconstruction. Without the removal of the DBS system. No alteration of DBS system efficacy was observed and the bilateral wounds healed well during the follow-up period.

Background: Polycystic ovary syndrome (PCOS) is characterized by excess androgens, ovulatory dysfunction, and polycystic ovaries. The mechanisms underlying ovulatory and metabolic disorders in PCOS remain elusive, hampering therapeutic development. Enhanced metabolic health correlates with increased microbiota gene content and microbial diversity. We aimed to explore the impact of gut microbiota and serum steroids on PCOS regulation associated with androgen excess.Methods: The fecal samples of patients with hyperandrogenic PCOS (n = 14) and control group with PCOS (n = 14) were analyzed by 16S rRNA gene sequencing. The peripheral venous blood of all subjects was collected to detect serum hormones. The association between gut microbiota and serum hormones was analyzed with the R language.Results: Our findings reveal that the hyperandrogenic PCOS group exhibits lower richness and diversity of gut microbiota compared to the control group. Characteristic genera in PCOS patients with hyperandrogenism include Bifidobacterium, Enterobacteriaceae_unclassified, Streptococcus, Saccharimonadaceae, Enterococcus, and Eubacterium_nodatum_group. Five hormones, including 5β-androsterone, deoxycorticosterone, corticosterone, 11-dehydrocorticosterone, and cortexolone, emerge as potential serum biomarkers for identifying patients with hyperandrogenic-PCOS (HA-PCOS). Furthermore, a lower vitamin D3 level may act as a susceptibility factor, suggesting that vitamin D3 supplementation could serve as a potential intervention for PCOS with hyperandrogenism.Conclusion: Specific fecal microbiota and serum steroids may be used as characteristic markers for clinical diagnosis of hyperandrogenic-PCOS. This research enhances our understanding of the intricate interplay among hormones, gut microbiota, and hyperandrogenemia in patients with PCOS.

Abstract Background Human dermal fibroblasts (HDFs) are essential in the processes of skin ageing and wound healing. However, the underlying mechanism of HDFs in skin healing of the elderly has not been well defined. This study aims to elucidate the mechanisms of HDFs senescence and how senescent HDFs affect wound healing in aged skin. Methods The expression and function of sperm equatorial segment protein 1 (SPESP1) in skin ageing were evaluated via in vivo and in vitro experiments. To delve into the potential molecular mechanisms by which SPESP1 influences skin ageing, a combination of techniques was employed, including proteomics, RNA sequencing, immunoprecipitation, chromatin immunoprecipitation and liquid chromatography‐mass spectrometry analyses. Clearance of senescent cells by dasatinib plus quercetin (D+Q) was investigated to explore the role of SPESP1‐induced senescent HDFs in wound healing. Results Here, we define the critical role of SPESP1 in ameliorating HDFs senescence and retarding the skin ageing process. Mechanistic studies demonstrate that SPESP1 directly binds to methyl‐binding protein, leading to Decorin demethylation and subsequently upregulation of its expression. Moreover, SPESP1 knockdown delays wound healing in young mice and SPESP1 overexpression induces wound healing in old mice. Notably, pharmacogenetic clearance of senescent cells by D+Q improved wound healing in SPESP1 knockdown skin. Conclusions Taken together, these findings reveal the critical role of SPESP1 in skin ageing and wound healing, expecting to facilitate the development of anti‐ageing strategies and improve wound healing in the elderly.

Knowledge representation is increasingly recognized as an effective method for information extraction. Nevertheless, numerous studies have disregarded its potential applications in the zero-shot setting. In this article, a novel framework, called knowledge-based prompt tuning for zero-shot relation triplet extraction (KBPT), was developed, founded on external ontology knowledge. This framework serves as a catalyst for exploring relation triplet extraction (RTE) methods within low-resource scenarios, warranting further scrutiny. Zero-shot setting RTE aims to extract multiple triplets that consist of head entities, tail entities, and relation labels from an input sentence, where the extracted relation labels are those that do not exist in the training set. To address the data scarcity problem in zero-shot RTE, a technique was introduced to synthesize training samples by prompting language models to generate structured texts. Specifically, this involves integrating language model prompts with structured text methodologies to create a structured prompt template. This template draws upon relation labels and ontology knowledge to generate synthetic training examples. The incorporation of external ontological knowledge enriches the semantic representation within the prompt template, enhancing its effectiveness. Further, a multiple triplets decoding (MTD) algorithm was developed to overcome the challenge of extracting multiple relation triplets from a sentence. To bridge the gap between knowledge and text, a collective training method was established to jointly optimize embedding representations. The proposed model is model-agnostic and can be applied to various PLMs. Exhaustive experiments on four public datasets with zero-shot settings were conducted to demonstrate the effectiveness of the proposed method. Compared to the baseline models, KBPT demonstrated enhancements of up to 14.65% and 24.19% in F1 score on the Wiki-ZSL and TACRED-Revisit datasets, respectively. Moreover, the proposed model achieved better performance compared with the current state-of-the-art (SOTA) model in terms of F1 score, precision-recall (P–R) curves and AUC. The code is available at https://Github.com/Phevos75/KBPT.

ObjectivesTo investigate the risk of atrial fibrillation (AF) with sodium-glucose cotransporter-2 inhibitors (SGLT2is) compared to dipeptidyl peptidase-4 inhibitor (DPP4i) use in older US adults and across diverse subgroups.MethodsWe conducted a retrospective cohort analysis using claims data from 15% random samples of Medicare fee-for-service beneficiaries. Patients were adults with type 2 diabetes (T2D), no preexisting AF, and were newly initiated on SGLT2i or DPP4i. The outcome was the first incident AF. Inverse probability treatment weighting (IPTW) was used to balance the baseline covariates between the treatment groups including sociodemographics, comorbidities, and co-medications. Cox regression models were used to assess the effect of SGLT2i compared to DPP4i on incident AF.ResultsOf the 97,436 eligible individuals (mean age 71.2 ± 9.8 years, 54.6% women), 1.01% (n = 983) had incident AF over a median follow-up of 361 days. The adjusted incidence rate was 8.39 (95% CI: 6.67–9.99) and 11.70 (95% CI: 10.9–12.55) per 1,000 person-years in the SGLT2i and DPP4i groups, respectively. SGLT2is were associated with a significantly lower risk of incident AF (HR 0.73; 95% CI, 0.57 to 0.91; p = 0.01) than DPP4is. The risk reduction of incident AF was significant in non-Hispanic White individuals and subgroups with existing atherosclerotic cardiovascular diseases and chronic kidney disease.ConclusionCompared to the use of DPP4i, that of SGLT2i was associated with a lower risk of AF in patients with T2D. Our findings contribute to the real-world evidence regarding the effectiveness of SGLT2i in preventing AF and support a tailored therapeutic approach to optimize treatment selection based on individual characteristics.

Epilepsy can be defined as a dysfunction of the brain network, and each type of epilepsy involves different brain-network changes that are implicated differently in the control and propagation of interictal or ictal discharges. Gaining more detailed information on brain network alterations can help us to further understand the mechanisms of epilepsy and pave the way for brain network-based precise therapeutic approaches in clinical practice. An increasing number of advanced neuroimaging techniques and electrophysiological techniques such as diffusion tensor imaging-based fiber tractography, diffusion kurtosis imaging-based fiber tractography, fiber ball imaging-based tractography, electroencephalography, functional magnetic resonance imaging, magnetoencephalography, positron emission tomography, molecular imaging, and functional ultrasound imaging have been extensively used to delineate epileptic networks. In this review, we summarize the relevant neuroimaging and neuroelectrophysiological techniques for assessing structural and functional brain networks in patients with epilepsy, and extensively analyze the imaging mechanisms, advantages, limitations, and clinical application ranges of each technique. A greater focus on emerging advanced technologies, new data analysis software, a combination of multiple techniques, and the construction of personalized virtual epilepsy models can provide a theoretical basis to better understand the brain network mechanisms of epilepsy and make surgical decisions.

AbstractArtabotrys hexapetalus (L.f.) Bhandari, 1965, an evergreen climbing shrub of significant value, is prominent in Chinese history and culture. The whole-gene sequencing of its chloroplast genome using Illumina pair-end sequencing data is conducted during this research. The complete chloroplast genome was determined to be 178,457 bp in size, separated by a large single copy (LSC) and a small single copy (SSC) region of 90,803 and 3,066 bp, respectively. A total of 134 genes were identified, including 90 protein-coding genes, 36 tRNA, and eight rRNA genes. Phylogenetic analysis revealed a close relationship between A. hexapetalus and Artabotrys pilosus, forming a sister branch with 100% support. The study suggests that the chloroplast genome of A. hexapetalus provides valuable insights into its evolutionary history and will contribute to the conservation efforts of this species.

Abstract Background In recent years, the impact of diet on Alzheimer's disease (AD) as a modifiable lifestyle has attracted widespread attention. We aimed to elucidate the current research status, frontiers, and research trends regarding the role of diet in AD over the past two decades through CiteSpace. Methods Studies related to AD and diet that were published from January 1, 2003, to June 30, 2023, were retrieved via the Web of Science Core Collection. We imported the study data into CiteSpace for visual analysis of countries, institutions, co-authors, and co-occurring keywords. Results A total of 922 relevant studies were included in our analysis, which found Nikolaos Scarmeas was the most prolific author (13 studies, 1.41%). The results also indicated that USA and Columbia University were the country and institution with the highest number of publications, with 209 (22.67%) and 23 (2.49%), respectively. The keywords that had a burst in the past four years were neuroinflammation, AD, tau, association, and beta. Conclusion Talent exchange and regional cooperation are recommended in this study field. The results indicate that the effectiveness of various dietary patterns and mechanisms of dietary interventions using biomarkers and supplementation with refined nutrients will be the main research trends in the future.

Accurate and reliable segmentation of rectal cancer in Magnetic Resonance Imaging holds crucial significance in preoperative prediction, tumor staging, and neoadjuvant therapy. Currently, the automated segmentation methods for rectal tumor have predominantly relied on Convolutional Neural Networks (CNNs), which lean heavily on discerning the contrast disparities among locally neighboring MRI voxels. However, these methods tend to exhibit segmentation inaccuracies when confronted with rectal cancer instances characterized by indistinct contrasts and markedly diverse shapes. Here, we propose a FCTformer who Fuses Convolutional operations and Transformer modules for accurate rectal tumor segmentation in 3D MRI. Specifically, first, FCTformer integrates a transformer-based global feature extraction mechanism and a CNN-based local feature extraction approach to obtain a dual-faceted multiscale feature representation. This representation enhances the model’s capability to capture both the comprehensive semantic features and intricate details of rectal cancer instances, especially in challenging situations such as low-contrast imaging and substantial shape variations. Second, to capitalize on features captured across different scales, thereby enhancing segmentation accuracy, we have incorporated a Dual-Attention decoder. Third, to enhance the tumor’s edges and contours, the Prediction Aggregation Unit is designed to capture sharper tumor boundaries and retain fine details that could be lost during repetitive down-sampling stages. Experimental results involving 362 instances of rectal tumor segmentation demonstrate that our proposed method achieves a Dice Similarity Coefficient of 0.827, surpassing existing methods. The satisfactory results obtained from evaluating our approach on a publicly available prostate dataset validate its generalizability.

Abstract There are enormous enthusiasm and concerns in applying large language models (LLMs) to healthcare. Yet current assumptions are based on general-purpose LLMs such as ChatGPT, which are not developed for medical use. This study develops a generative clinical LLM, GatorTronGPT, using 277 billion words of text including (1) 82 billion words of clinical text from 126 clinical departments and approximately 2 million patients at the University of Florida Health and (2) 195 billion words of diverse general English text. We train GatorTronGPT using a GPT-3 architecture with up to 20 billion parameters and evaluate its utility for biomedical natural language processing (NLP) and healthcare text generation. GatorTronGPT improves biomedical natural language processing. We apply GatorTronGPT to generate 20 billion words of synthetic text. Synthetic NLP models trained using synthetic text generated by GatorTronGPT outperform models trained using real-world clinical text. Physicians’ Turing test using 1 (worst) to 9 (best) scale shows that there are no significant differences in linguistic readability (p = 0.22; 6.57 of GatorTronGPT compared with 6.93 of human) and clinical relevance (p = 0.91; 7.0 of GatorTronGPT compared with 6.97 of human) and that physicians cannot differentiate them (p

Synovial sarcoma, a rare malignant neoplasm with a poor prognosis, accounts for approximately 5%-10% of all primary soft-tissue malignancies worldwide. Typically affecting adolescents and young adults, it primarily manifests near the joints of the lower extremities. This study aimed to demonstrate that this tumor can also affect the prevertebral space. A 32-year-old male patient presented at our outpatient clinic with a 2-month history of upper limb numbness and a 1-month complaint of palpable neck mass. Imaging studies revealed a bulky, lobulated, and heterogeneous mass exhibiting heterogeneous enhancement. Furthermore, the mass caused expansion of the neuroforamen in the neck, initially suggesting a diagnosis of malignant schwannoma. However, a histopathologic examination suggested synovial sarcoma. The article provided a comprehensive review of the clinical, pathological, and radiological features of this condition. Additionally, it explored current treatment options and prognoses by referencing relevant literature.

Feeding the increasing global population and reducing the carbon footprint of agricultural activities are two critical challenges of our century. Growing crops under protected horticulture and precise crop monitoring have emerged to address these challenges. Crop monitoring in commercial protected facilities remains mostly manual and labour intensive. Using computer vision to solve specific problems in image-based crop monitoring in these compact and complex growth environments is currently hindered by the scarcity of available data. We collected an RGBD dataset for vertically supported, hydroponically-grown capsicum plants in a commercial-scale glasshouse facility to fill this gap. Data were collected weekly using a single top-angled stereo camera mounted on a mobile platform running between the hydroponic gutters. The RGBD streams covered 80 % of the crop growing season in three different light conditions. The metadata include camera configurations and light condition information. Manually measured plant heights of ten selected plants per gutter are provided as ground truth. The images covered the whole plants and focused on the top third. This dataset will support research on plant height estimation, plant organ identification, object segmentation, organ measurements, 3D reconstruction, 3D data processing, and depth noise reduction. The usability of the dataset has been successfully demonstrated in a previously published study on plant height estimation using machine learning and 3D point cloud.

Given its high morbidity, disability, and mortality rates, ischemic stroke (IS) is a severe disease posing a substantial public health threat. Although early thrombolytic therapy is effective in IS treatment, the limited time frame for its administration presents a formidable challenge. Upon occurrence, IS triggers an ischemic cascade response, inducing the brain to generate endogenous protective mechanisms against excitotoxicity and inflammation, among other pathological processes. Stroke patients often experience limited recovery stages. As a result, activating their innate self-protective capacity [endogenous brain protection (EBP)] is essential for neurological function recovery. Acupuncture has exhibited clinical efficacy in cerebral ischemic stroke (CIS) treatment by promoting the human body's self-preservation and “Zheng Qi” (a term in traditional Chinese medicine (TCM) describing positive capabilities such as self-immunity, self-recovery, and disease prevention). According to research, acupuncture can modulate astrocyte activity, decrease oxidative stress (OS), and protect neurons by inhibiting excitotoxicity, inflammation, and apoptosis via activating endogenous protective mechanisms within the brain. Furthermore, acupuncture was found to modulate microglia transformation, thereby reducing inflammation and autoimmune responses, as well as promoting blood flow restoration by regulating the vasculature or the blood–brain barrier (BBB). However, the precise mechanism underlying these processes remains unclear. Consequently, this review aims to shed light on the potential acupuncture-induced endogenous neuroprotective mechanisms by critically examining experimental evidence on the preventive and therapeutic effects exerted by acupuncture on CIS. This review offers a theoretical foundation for acupuncture-based stroke treatment.

Summary: In the brain, the role of matrilin-3, an extracellular matrix component in cartilage, is unknown. Here, we identify that matrilin-3 decreased in reactive astrocytes but was unchanged in neurons after ischemic stroke in animals. Importantly, it declined in serum of patients with acute ischemic stroke. Genetic or pharmacological inhibition or supplementation of matrilin-3 aggravates or reduces brain injury, astrocytic cell death, and glial scar, respectively, but has no direct effect on neuronal cell death. RNA sequencing demonstrates that Matn3−/− mice display an increased inflammatory response profile in the ischemic brain, including the nuclear factor κB (NF-κB) signaling pathway. Both endogenous and exogenous matrilin-3 reduce inflammatory mediators. Mechanistically, extracellular matrilin-3 enters astrocytes via caveolin-1-mediated endocytosis. Cytoplasmic matrilin-3 translocates into the nucleus by binding to NF-κB p65, suppressing inflammatory cytokine transcription. Extracellular matrilin-3 binds to BMP-2, blocking the BMP-2/Smads pathway. Thus, matrilin-3 is required for astrocytes to exert neuroprotection, at least partially, by suppressing astrocyte-mediated neuroinflammation.

IntroductionThe presence of brackish water resources is significant in addressing the scarcity of freshwater resources, particularly in the Xinjiang region. Studies focused on reducing adverse effect of brackish water irrigation based on using ionized brackish water, as well as on investigating its effects on fibre and oil plant production processes, remain incipient in the literature. Some benefits of this technique are the optimization of the quality and quantity of irrigation water, economy of water absorbed by the plants, improvement in the vegetative growth and productivity compared to irrigation using conventional brackish water. Thus, the aim of the current study is to assess the effect of different nitrogen application rates on soil water and salinity, cotton growth and water and nitrogen use efficiency.MethodsThe experimental design consisted of completely randomized design with two water types (ionized and non-ionized) and six nitrogen application rates with four replications.ResultsIrrigation conducted with ionized brackish water and different nitrogen application rates had significant effect on the plant height, leaf area index, shoot dry matter, boll number per plant and chlorophyll content. The study also demonstrated significant effects of ionized brackish water on soil water content and soil salinity accumulation. The highest cotton production was achieved with the use of 350 kg·ha-1 of ionized brackish water for irrigation, resulting in an average increase of 11.5% compared to the use of non-ionized brackish water. The nitrogen application exhibits a quadratic relationship with nitrogen agronomic use efficiency and apparent nitrogen use efficiency, while it shows a liner relationship with nitrogen physiological use efficiency and nitrogen partial productivity. After taking into account soil salinity, cotton yield, water and nitrogen use efficiency, the optimal nitrogen application rate for ionized brackish water was determined to be 300 kg·ha-1.DiscussionIt is hoped that this study can contribute to improving water management, reducing the environmental impact without implying great costs for the producer.

BackgroundTo investigate the clinical efficacy of Castor integrated branched aortic stent graft for the treatment of Stanford type B aortic dissection with insufficient anchoring area.MethodsRetrospective analysis of clinical data of 26 patients with Stanford type B aortic dissection with insufficient anchoring region (

BackgroundEsophageal cancer is the seventh most frequently diagnosed cancer with a high mortality rate and the sixth leading cause of cancer deaths in the world. Early detection of esophageal cancer is very vital for the patients. Traditionally, contrast computed tomography (CT) was used to detect esophageal carcinomas, but with the development of deep learning (DL) technology, it may now be possible for non-contrast CT to detect esophageal carcinomas. In this study, we aimed to establish a DL-based diagnostic system to stage esophageal cancer from non-contrast chest CT images.MethodsIn this retrospective dual-center study, we included 397 primary esophageal cancer patients with pathologically confirmed non-contrast chest CT images, as well as 250 healthy individuals without esophageal tumors, confirmed through endoscopic examination. The images of these participants were treated as the training data. Additionally, images from 100 esophageal cancer patients and 100 healthy individuals were enrolled for model validation. The esophagus segmentation was performed using the no-new-Net (nnU-Net) model; based on the segmentation result and feature extraction, a decision tree was employed to classify whether cancer is present or not. We compared the diagnostic efficacy of the DL-based method with the performance of radiologists with various levels of experience. Meanwhile, a diagnostic performance comparison of radiologists with and without the aid of the DL-based method was also conducted.ResultsIn this study, the DL-based method demonstrated a high level of diagnostic efficacy in the detection of esophageal cancer, with a performance of AUC of 0.890, sensitivity of 0.900, specificity of 0.880, accuracy of 0.882, and F-score of 0.891. Furthermore, the incorporation of the DL-based method resulted in a significant improvement of the AUC values w.r.t. of three radiologists from 0.855/0.820/0.930 to 0.910/0.955/0.965 (p = 0.0004/

Temporomandibular disorder (TMD) and fibromyalgia syndrome (FMS) may present as comorbid conditions, but treatment options are ineffective. The purpose of this study was to investigate whether valproate (VPA) attenuates somatic hyperalgesia induced by orofacial inflammation combined with stress, which represents a model of pain associated with TMD and FMS comorbidity, and to explore the potential mechanisms. The results showed that VPA inhibited somatic hyperalgesia induced by orofacial inflammation combined with stress, and down-regulated the interleukin-6 (IL-6) expression in the L4-L5 spinal dorsal horn of female rats. The anti-nociceptive effect of VPA was blocked by single or 5 consecutive day intrathecal administration of recombinant rat IL-6. Orofacial inflammation combined with stress up-regulated the ratio of phosphorylated signal transducer and activator of transcription 1 (p-STAT1) to STAT1 (p-STAT1/STAT1) in the spinal cord. VPA did not affect the STAT1 expression, while it down-regulated the ratio of p-STAT1/STAT1. The expression of STAT3 and the ratio of p-STAT3/STAT3 were not affected by orofacial inflammation combined with stress and VPA treatment. Intrathecal administration of exogenous IL-6 up-regulated the ratio of p-STAT1/STAT1. These data indicate that VPA attenuated somatic hyperalgesia induced by orofacial inflammation combined with stress via inhibiting spinal IL-6 in female rats, and the mechanism may involve the alteration of activation status of spinal STAT1. Thus, VPA may be a new candidate analgesic that targets IL-6 and STAT1 for the treatment of pain associated with the comorbidity of TMD and FMS.

Abstract Background Cervical cancer (CC) has become the fourth most common cancer worldwide and it is mainly caused by the infection of human papillomavirus (HPV), especially high‐risk HPV16. Aberrant miRNA expression in CC is closely related to HPV16 infection, and the regulation of HPV16 E6 expression can affect a variety of miRNA expression. This study aims to exploring the miRNAs involved in E6 regulation in CC. Methods Our study screened differentially expressed miRNAs in cervical cells of HPV16 infected and uninfected cervical cancer patients by analyzing the GSE81137 dataset of the gene expression omnibus database (GEO), and identified miR‐320a that plays an anti‐tumor role and is associated with good prognosis of cervical cancer. Explore the effect of HPV16 E6 on the expression of miR‐320a in cervical cancer, and verify whether HPV16 E6 regulates the downstream target gene TOP2A expression through miR‐320a, thereby affecting cervical cancer cell proliferation, apoptosis, migration, invasion, and EMT in vitro and in vivo. Results The bioinformatic methods selected the miR‐320a, which was differentially expressed in cervical cells from HPV16‐infected patients compared to uninfected patients. We further demonstrated that miR‐320a level was regulated by HPV16 E6, which promoted the CC cell proliferation, migration, invasion, and inhibited apoptosis. In addition, we predicted the downstream target genes of miR‐320a and confirmed that TOP2A was one of its targeting proteins. Moreover, HPV16 E6 promoted the TOP2A expression in CC cells through down‐regulating miR‐320a, leading to promoting CC development. Conclusions We confirmed that HPV16 E6 promoted the TOP2A expression through down‐regulation of miR‐320a, thus promoting CC development, and the HPV16 E6/miR‐320a/TOP2A axis may perform as a potential target for CC treatment.

IntroductionA potential association between periodontitis and endometriosis has been indicated in previous observational studies. Nevertheless, the causal link between these two disorders has not been clarified.MethodsBased on publicly available genome-wide association study (GWAS) summary datasets, we conducted a bidirectional Mendelian randomization (MR) study to investigate the relationship between periodontitis and endometriosis and its subtypes. Single nucleotide polymorphisms (SNPs) strongly associated with candidate exposures at the genome-wide significance level (P < 5 × 10−8) were selected as instrumental variables (IVs). The inverse variance-weighted regression (IVW) was performed to estimate the causal effect of periodontitis on endometriosis. We further conducted two sensitivity analyses, MR-Egger and weighted median, to test the validity of our findings. The main results were replicated via data from the UK Biobank. Finally, a reverse MR analysis was performed to evaluate the possibility of reverse causality.ResultsThe IVW method suggested that periodontitis was positively associated with endometriosis of the pelvic peritoneum (OR = 1.079, 95% CI = 1.016 to 1.146, P = 0.014). No causal association was indicated between periodontitis and other subtypes of endometriosis. In reversed analyses, no causal association between endometriosis or its subtypes and periodontitis was found.ConclusionsOur study provided genetic evidence on the causal relationship between periodontitis and endometriosis of the pelvic peritoneum. More studies are necessary to explore the underlying mechanisms.

BackgroundTetanus is a rare surgical infectious disease with a high reported relevant mortality. It still remains a serious problem in public health, particularly in low-income and middle-income countries. The purpose of this study was to investigate the management and prognosis of adult generalized tetanus in our hospital.MethodsA total of 20 adult generalized tetanus patients were recruited in this retrospective observational study. Patients were retrieved from the hospital data base via discharge diagnosis. Patients were divided into two groups (Severe or Non-severe tetanus group) based on the severity of tetanus by using the Ablett classification. The differences between the two groups were compared.ResultsThe study included 11 males (55%) and 9 females (45%). All tetanus patients recovered. The median age was 53.5 years [IQR: 19–78]. There were 1 mild (Grade 1) case (5%),5 moderate (Grade 2) cases (25%), 2 severe (Grade 3) cases (10%), and 12 very severe (Grade 4) cases (60%). Nineteen patients (95%) did not have tetanus immunization before. The majority of patients were farmers (60%), and came from rural areas (60%). Thirteen (65%) patients had a history of puncture injury. The rate of wound debridement after admission was 60% overall. Thirteen (65%) patients required mechanical ventilation for a median of 21 [IQR:12–41] days. Autonomic instability occurred in 13 (65%) patients. Pulmonary infections occurred in 12 (60%) patients. Median duration of hospital stay was 29.5 [IQR:12–68] days. More patients in the Severe group needed ICU admission, wound debridement, mechanical ventilation and heavy sedation combined with muscle relaxants (p

In the past few decades, the use of acupuncture analgesia in clinical practice has increased worldwide. This is due to its various benefits, including natural alleviation of pain without causing various adverse effects associated with non-steroidal anti-inflammatory drugs (NSAID) and opioids. The acupoint represents the initial site of acupuncture stimulation, where diverse types of nerve fibers located at the acupoint hold significant roles in the generation and transmission of acupuncture-related information. In this study, we analyzed the patterns and mechanisms of acupuncture analgesic mediated by acupoint afferent fibers, and found that acupuncture stimulates acupoints which rapidly and directly induces activation of high-density primary afferent fibers under the acupoints, including myelinated A fibers and unmyelinated C fibers. During acupuncture stimulation at the muscle layer, the analgesic effects can be induced by stimulation of A fiber threshold intensity. At the skin layer, the analgesic effects can only be produced by stimulation of C fiber threshold intensity. Electroacupuncture (EA) activates A fibers, while manual acupuncture (MA) activates both A and C fibers. Furthermore, acupuncture alters acupoint microenvironments, which positively modulates afferent fibers, enhancing the transmission of analgesic signals. In addition to local activation and conduction at acupoints, nerve fibers mediate the transmission of acupuncture information to pain centers. In the spinal cord, acupuncture activates neurons by inducing afferent fiber depolarization, modulating pain gating, inhibiting long-term potentiation (LTP) of the spinal dorsal horn and wide dynamic range (WDR) neuronal activities. At higher nerve centers, acupuncture inhibits neuronal activation in pain-related brain regions. In summary, acupuncture inhibits pain signal transmission at peripheral and central systems by activating different patterns of afferent fibers located on various layers of acupoints. This study provides ideas for enhancing the precise application and clinical translation of acupuncture.

Esophageal cancer (EC) is a leading cause of cancer-related death in the west 1. Esophageal squamous cell carcinoma (SCC) is the most common type of EC worldwide. However, in Western countries, including the United States, esophageal adenocarcinoma (EAC) is the most common 2. EAC is most common in the lower esophagus whereas SCC is most common in the middle and upper esophagus 3. The incidence of EAC has increased dramatically in western countries over the past few decades. 2 3 The exact reason for this rise in EAC has not been clearly understood. However, an increase in the prevalence of EAC risk factors is postulated as a potential explanation 4. Although there are many identifiable EAC risk factors, including gastroesophageal reflux disease (GERD), obesity, male sex, White race, and smoking 5 6 7, Barrett’s esophagus (BE) remains the major precursor lesion of esophageal adenocarcinoma. BE develops when there is a change in the normal squamous lining of the esophageal mucosa into intestinal metaplasia 8 9. The incidence has also increased in the population over the past few decades 10 11. There is a well-described progression within BE from non-dysplastic BE (NDBE), low-grade dysplasia (LGD), high-grade dysplasia (HGD), intramucosal carcinoma (IMC), to invasive EAC 12 13. Recent data suggest that the increased incidence of EAC may have plateaued 1. However, we questioned whether the prevalence of EAC is still increasing, especially at younger ages in lieu of recent trends showing an increase in the prevalence of colorectal cancer in younger patients. These findings resulted in a lowering of the colorectal cancer screening age cutoff to 45 years from 50 years 14 15 16. Therefore, we aimed to assess the time trends in the prevalence and incidence of EAC and some of its risk factors in a large population of patients in Florida and to assess these trends based on age categories. We hypothesized that the prevalence of EAC and BE has increased over time at younger age groups.

Abstract Background Hepatocyte growth factor (HGF) is a peptide-containing multifunctional cytokine, which is overexpressed and/or activated in multiple malignancies and is reported to be associated with tumor development and inferior survival. At present, the role of HGF in small cell lung cancer (SCLC) has not been fully explored yet. Materials and methods The expression of HGF and its value in predicting survival in SCLC were explored from GEO database and in pan-cancer analysis. Furthermore, we detected the expression of HGF using tumor tissue and paired plasma samples from a validation cohort of 71 SCLC patients at our institute. Correlation between tumor and plasma HGF expression and the prognostic values were analyzed. Results GEO database analysis revealed that tumor tissue had lower HGF expression than paired normal tissue in SCLC. At our institute, immunohistochemical staining showed negative expression of HGF in tumor tissue of SCLC at our institute (47/47, 100%). The average baseline plasma HGF was 1.28 (range,0.42–4.35) ng/ml. However, plasma HGF was higher in SCLC patients with patients with N3, M1, liver metastasis (LM) and bone metastasis (BM) disease compared with those N0 − 2 (1.25 vs. 1.75 ng/mL, P = 0.000), M0 (1.26 vs. 1.63 ng/mL, P = 0.003), non-LM (1.32 vs. 2.06 ng/mL, P = 0.009), and non-BM (1.35 vs. 1.77 ng/mL, P = 0.047), respectively. Multivariate analysis revealed plasma HGF was an independent predictor for LM and prognostic factor of OS. Conclusion Our results revealed that plasma HGF rather than tumor HGF exhibited a potential role in predicting metastasis and survival in SCLC. Plasma HGF might be used as a non-invasive detecting and monitoring tool for SCLC.

Abstract Autonomous robotics working in the uncertain environment have drawn increasing interests from researchers. Here, an issue of online motion optimization under unknown environment is considered while preserving the safety and improving the flexible manoeuvrability of robot–environment interaction. This problem is addressed by improving the conventional dynamic movement primitives (DMPs) framework with force tracking constraints. First, an initial motion is learned through the DMPs. At the stage of skill generalization, a temporal coupling term combining with force constraints scheme which is inspired by the barrier Lyapunov function and finite‐time prescribed performance is deduced and adds to the original DMPs, so as to remain the contacting force staying within a predefined limit while aligning the motion along with surface of unknown environment adaptively. In this way, not only the contacting force can be guaranteed within a safe margin, but the shape of generalizing motion is preserved. Then the convergence and stability of the proposed DMPs are proved which is grounded on Laplace transformation‐based stability analysis to ensure the performance and safety. Finally, the proposed method is instantiated combined with conventional PID controller through the compared simulations to verify its effectiveness.

Promoting the opening and sharing of large scientific research facilities is a development strategy for China to in-depth implement the innovation-driving, and an important measure to continuously support innovation. The ocean test field is an important platform for marine scientific and technological innovation, industrial development and business system construction. It holds the principles of public welfare, opening and sharing, and contribute to the high-quality development of the ocean economy. The opening and sharing of ocean test field will be a "booster" for the innovation-driven development of the maritime power. This paper compared the policies and status of sharing large scientific research facilities at home and abroad, and analyzed the national and market requirements of sharing. It also discussed the sharing content, sharing mode and sharing mechanism of the ocean test field, based on the test capability of ocean test field. Some suggestions on the sharing mechanism of ocean test field were put forwards.

Carbon tax is important to achieve carbon peaking and carbon neutrality goal. In this paper, we study the impact of carbon tax on energy sector segmentation in China under different closures. First, the social accounting matrix (SAM) of year 2017 is constructed. Second, the electric sector is subdivided into five power generation sectors. Third, by building a static computable general equilibrium (CGE) model, carbon tax is simulated under Neoclassical closure (NC) and Keynesian closure (KC) respectively. The results validate that carbon tax is efficacious in reducing CO2 emission. Specific findings include the following. (1) Carbon tax on three fossil fuels (i.e., coal, oil and natural gas) will increase with the improved emission reduction goal. (2) Reducing the usage of coal and thermal power plant in the electric power sector will significantly contribute to CO2 emission reduction. (3) Carbon tax can produce double dividend effect under KC scenario to increase the income of households and government. (4) The 30% emission reduction goal can be achieved under KC with the carbon tax at 84.19 yuan/ton, which is 3.3 yuan/ton less than that under NC. In the meantime, the carbon emission density will reduce to 116.93 t/million yuan.