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BackgroundArsenic, cobalt, barium, and other individual metal exposure have been confirmed to be associated with the incidence of kidney stones. However, there are few studies on the association between mixed metal exposure and kidney stones, especially in occupational groups. ObjectiveTo investigate the association between mixed metal exposure and kidney stones in an occupational population from a metal smelting plant. MethodsA questionnaire survey was conducted to collect sociodemographic characteristics, medical history, and lifestyle information of 1158 mixed metal-exposed workers in a metal smelting plant in Guangdong Province from July 2021 to January 2022. Midstream morning urine samples were collected from the workers, the concentrations of 18 metals including lithium, vanadium, chromium, manganese, cobalt, nickel, copper, zinc, arsenic, selenium, strontium, molybdenum, cadmium, cesium, barium, tungsten, titanium, and lead were measured by inductively coupled plasma mass spectrometry, and the urinary mercury levels were measured by cold atomic absorption spectroscopy. Based on predetermined inclusion criteria, a total of 919 mixed metal-exposed workers were included in the study, including 117 workers in the kidney stone group and 802 workers in the non-kidney stone group. With a detection rate of urinary metals greater than 80% as entry criterion, 16 eligible metals were finally included for further analysis. Parametric or non-parametric methods were used to compare the differences between continuous or categorical variables of the non-kidney stone group and the kidney stone group. Logistic regression models were constructed to explore the association between individual metal exposures and kidney stones. Weighted quantile sum (WQS) regression models were used to evaluate the association between mixed metal exposure and kidney stones, as well as the weights of each metal on kidney stones. Then Bayesian kernel machine regression (BKMR) models were used to explore the overall effect of mixed metal exposure on renal calculi and the potential interactions between metals. ResultsWe found that there were significant differences in sex, age, length of service, and body mass Index (BMI) between the non-kidney stone group and the kidney stone group (P

Abstract Background The ultrasonic scalpel is widely used during surgery. It is safe and effective to close the pulmonary artery branch vessels of 7 mm or below with an ultrasonic energy device as reported. However, there have been no multicenter randomized clinical trial to assess the safety and effectiveness of using ultrasonic scalpel to coagulate 5–7 mm blood vessels in thoracic surgery. Methods This is a prospective, multicenter, randomized, parallel controlled, non-inferiority clinical trial. A total of 144 eligible patients planning to undergo lung or esophageal surgery will be randomly allocated to the experimental group and the control group. The investigational product (Disposable Ultrasonic Shears manufactured by Reach Surgical, Inc.) and the control product (Harmonic Ace + 7, 5 mm Diameter Shears with Advanced Hemostasis) will be used in each group. The primary endpoint is the success rate of coagulating target blood vessels during surgery. Secondary endpoints include postoperative rebleeding, intraoperative bleeding volume, drainage volume, surgical duration, etc. Postoperative follow-up before and after discharge will be performed. Discussion This clinical trial aims to evaluate the safety and effectiveness of using the investigational product (Disposable Ultrasonic Shears manufactured by Reach Surgical, Inc.) and that of the control product (Harmonic Ace + 7, 5 mm Diameter Shears with Advanced Hemostasis) to coagulate 5–7 mm blood vessels in thoracic surgery. Trial registration ClinicalTrials.gov: NCT06002737. The trial was prospectively registered on 16 August 2023, https://www.clinicaltrials.gov/study/NCT06002737 .

Summary: Background: The long-term survival and perioperative outcomes of robotic-assisted lobectomy (RAL) and video-assisted lobectomy (VAL) in resectable non-small-cell lung cancer (NSCLC) were found to be comparable in retrospective studies, but they have not been investigated in a randomized trial setting. We conducted the RVlob trial to investigate if RAL was non-inferior to VAL in patients with resectable NSCLC. Methods: In this single-center, open-label, and parallel-arm randomized controlled trial conducted in Ruijin Hospital (Shanghai, China) between May 2017 and May 2020, we randomly assigned patients with resectable NSCLC in a 1:1 ratio to receive either RAL or VAL. One of the primary endpoints was 3-year overall survival. Secondary endpoints included 3-year disease-free survival. The Kaplan–Meier approach was used to calculate overall survival and disease-free survival at 3 years. This study was registered with ClinicalTrials.gov, NCT03134534. Findings: A total of 320 patients were randomized to receive RAL (n = 157) or VAL (n = 163). The baseline characteristics of patients were well balanced between the two groups. After a median follow-up of 58.0 months, the 3-year overall survival was 94.6% (95% confidence interval [CI], 91.0–98.3) in the RAL group and 91.5% (95% CI, 87.2–96.0) in the VAL group (hazard ratio [HR] for death, 0.65; 95% CI, 0.33–1.28; P = 0.21); noninferiority of RAL was confirmed according to the predefined margin of −5% (absolute difference, 2.96%; a one-sided 90% CI, −1.39% to ∞; P = 0.0029 for noninferiority). The 3-year disease-free survival was 88.7% (95% CI, 83.6–94.1) in the RAL group and 85.4% (95% CI, 80.0–91.2) in the VAL group (HR for disease recurrence or death, 0.87; 95% CI, 0.50–1.52; P = 0.62). Interpretation: This study is the first randomized trial to show that RAL resulted in non-inferior overall survival compared with VAL in patients with resectable NSCLC. Based on our results, RAL is an equally oncologically effective treatment and can be considered as an alternative to VAL for resectable NSCLC. Funding: National Natural Science Foundation of China (82072557), National Key Research and Development Program of China (2021YFC2500900), Shanghai Municipal Education Commission-Gaofeng Clinical Medicine Grant (20172005, the 2nd round of disbursement), program of Shanghai Academic Research Leader from Science and Technology Commission of Shanghai Municipality (20XD1402300), Novel Interdisciplinary Research Project from Shanghai Municipal Health Commission (2022JC023), and Interdisciplinary Program of Shanghai Jiao Tong University (YG2023ZD04).

Abstract Background The presence of lymph node (LN) metastasis directly affects the treatment strategy for lung adenocarcinoma (LUAD). Next‐generation sequencing (NGS) has been widely used in patients with advanced LUAD to identify targeted genes, while early detection of pathologic LN metastasis using NGS has not been assessed. Methods Clinicopathologic features and molecular characteristics of 224 patients from Ruijin Hospital were analyzed to detect factors associated with LN metastases. Another 140 patients from Huashan Hospital were set as a test cohort. Results Twenty‐four out of 224 patients were found to have lymph node metastases (10.7%). Pathologic LN‐positive tumors showed higher mutant allele tumor heterogeneity (p

Arbitrage trading is a common quantitative trading strategy that leverages the long-term cointegration relationships between multiple related assets to conduct spread trading for profit. Specifically, when the cointegration relationship between two or more related series holds, it utilizes the stability and mean-reverting characteristics of their cointegration relationship for spread trading. However, in real quantitative trading, determining the cointegration relationship based on the Engle-Granger two-step method imposes stringent conditions for the cointegration to hold, which can easily be disrupted by price fluctuations or trend characteristics presented by the linear combination, leading to the failure of the arbitrage strategy and significant losses. To address this issue, this article proposes an optimized strategy based on long-short-term memory (LSTM), termed Dynamic-LSTM Arb (DLA), which can classify the trend movements of linear combinations between multiple assets. It assists the Engle-Granger two-step method in determining cointegration relationships when clear upward or downward non-stationary trend characteristics emerge, avoiding frequent strategy switches that lead to losses and the invalidation of arbitrage strategies due to obvious trend characteristics. Additionally, in mean-reversion arbitrage trading, to determine the optimal trading boundary, we have designed an optimized algorithm that dynamically updates the trading boundaries. Training results indicate that our proposed optimization model can successfully filter out unprofitable trades. Through trading tests on a backtesting platform, a theoretical return of 23% was achieved over a 10-day futures trading period at a 1-min level, significantly outperforming the benchmark strategy and the returns of the CSI 300 Index during the same period.

Objective This study aimed to develop and validate robust predictive models for patients with oesophageal cancer who achieved a pathological complete response (pCR) and those who did not (non-pCR) after neoadjuvant therapy and oesophagectomy.Design Clinicopathological data of 6517 primary oesophageal cancer patients who underwent neoadjuvant therapy and oesophagectomy were obtained from the National Cancer Database for the training cohort. An independent cohort of 444 Chinese patients served as the validation set. Two distinct multivariable Cox models of overall survival (OS) were constructed for pCR and non-pCR patients, respectively, and were presented using web-based dynamic nomograms (graphical representation of predicted OS based on the clinical characteristics that a patient could input into the website). The calibration plot, concordance index and decision curve analysis were employed to assess calibration, discrimination and clinical usefulness of the predictive models.Results In total, 13 and 15 variables were used to predict OS for pCR and non-pCR patients undergoing neoadjuvant therapy followed by oesophagectomy, respectively. Key predictors included demographic characteristics, pretreatment clinical stage, surgical approach, pathological information and postoperative treatments. The predictive models for pCR and non-pCR patients demonstrated good calibration and clinical utility, with acceptable discrimination that surpassed that of the current tumour, node, metastases staging system.Conclusions The web-based dynamic nomograms for pCR (https://predict-survival.shinyapps.io/pCR-eso/) and non-pCR patients (https://predict-survival.shinyapps.io/non-pCR-eso/) developed in this study can facilitate the calculation of OS probability for individual patients undergoing neoadjuvant therapy and radical oesophagectomy, aiding clinicians and patients in making personalised treatment decisions.

Abstract The molecular profiles and tumor immune microenvironment (TIME) of multiple primary lung cancers (MPLCs) presenting as concurrent lung adenocarcinoma (ADC) and squamous cell carcinoma (SQCC) remain unknown. We aimed to clarify these factors. We performed whole-exome sequencing (WES), RNA sequencing (RNA-Seq), and multiplex immunohistochemistry (mIHC) for five patients with concurrent ADC and SQCC. We found the genetic mutations were similar between ADC and SQCC groups. RNA-Seq revealed that the gene expression and pathways enriched in ADC and SQCC groups were quite different. Gene set enrichment analysis (GSVA) showed that nine gene sets were significantly differentially expressed between the ADC and SQCC groups (p

Dynamic multi-objective optimization problems have been popular because of its extensive application. The difficulty of solving the problem focuses on the moving PS as well as PF dynamically. A large number of efficient strategies have been put forward to deal with such problems by speeding up convergence and keeping diversity. Prediction strategy is a common method which is widely used in dynamic optimization environment. However, how to increase the efficiency of prediction is always a key but difficult issue. In this paper, a new prediction model is designed by using the rank sums of individuals, and the position difference of individuals in the previous two adjacent environments is defined to identify the present change type. The proposed prediction strategy depends on environment change types. In order to show the effectiveness of the proposed algorithm, the comparison is carried out with five state-of-the–art approaches on 20 benchmark instances of dynamic multi-objective problems. The experimental results indicate the proposed algorithm can get good convergence and distribution in dynamic environments.

Abstract Targeting tumor-infiltrating regulatory T cells (Tregs) is an efficient way to evoke an anti-tumor immune response. However, how Tregs maintain their fragility and stability remains largely unknown. IFITM3 and STAT1 are interferon-induced genes that play a positive role in the progression of tumors. Here, we showed that IFITM3-deficient Tregs blunted tumor growth by strengthening the tumor-killing response and displayed the Th1-like Treg phenotype with higher secretion of IFNγ. Mechanistically, depletion of IFITM3 enhances the translation and phosphorylation of STAT1. On the contrary, the decreased IFITM3 expression in STAT1-deficient Tregs indicates that STAT1 conversely regulates the expression of IFITM3 to form a feedback loop. Blocking the inflammatory cytokine IFNγ or directly depleting STAT1-IFITM3 axis phenocopies the restored suppressive function of tumor-infiltrating Tregs in the tumor model. Overall, our study demonstrates that the perturbation of tumor-infiltrating Tregs through the IFNγ-IFITM3-STAT1 feedback loop is essential for anti-tumor immunity and constitutes a targetable vulnerability of cancer immunotherapy.

The multi-point dynamic aggregation problem (MPDAP) that arises in practical applications is characterized by a group of robots that have to cooperate in executing a set of tasks distributed over multiple locations, in which the demand for each task grows over time. To minimize the completion time of all tasks, one needs to schedule the robots and plan the routes. Hence, the problem is essentially a combinatorial optimization problem. The manuscript presented a new MPDAP in which the priority of the task was considered that is to say, some tasks must be first completed before others begin to be executed. When the tasks were located at different priority levels, some additional constraints were added to express the priorities of tasks. Since route selection of robots depends on the priorities of tasks, these additional constraints caused the presented MPDAP to be more complex than ever. To efficiently solve this problem, an improved optimization algorithm, called the multi-strategy genetic algorithm (MSGA), was developed. First of all, a two-stage hybrid matrix coding scheme was proposed based on the priorities of tasks, then to generate more route combinations, a hybrid crossover operator based on 0-1 matrix operations was proposed. Furthermore, to improve the feasibility of individuals, a repair schedule was designed based on constraints. Meanwhile, a $ q $-tournament selection operator was adopted so that better individuals can be kept into the next generation. Finally, experimental results showed that the proposed algorithm is feasible and effective for solving the MPDAP.

Introduction The multicenter CHAMPION study aimed to assess the impact of smoking cessation on post-operative complications (PCs) and smoking cessation patterns in Chinese patients undergoing lung surgery. Methods Patients undergoing elective lung surgery were prospectively enrolled from three major tertiary centers in China. Patients were categorized as smokers or quitters before surgery. Baseline characteristics and smoking status were analyzed. The incidence of PCs and pulmonary PCs (PPCs), smoking relapse rate, and causes within six months post-operatively were investigated. The questionnaire was conducted in all patients and 30 healthcare professionals (HCPs), regarding the awareness and effectiveness of smoking cessation methods. Results Of the 276 enrolled patients, 213 (77.2%) were smokers and 63 (22.8%) were quitters; 76.4% were diagnosed with primary lung cancer. PCs occurred in 13.8% of patients, with similar proportions in smokers (14.1%) and quitters (12.7%). PPCs occurred in 9.8% of patients with no significant differences between smokers and quitters (9.4% vs 11.1%, p=0.70). At six months, 9.2% of patients relapsed, with a lower rate in quitters compared to smokers (3.3% vs 11.0%, p=0.01). HCPs exhibited higher awareness of smoking cessation methods than patients. Perceived effectiveness of smoking cessation methods from the patients were low. Conclusions In patients undergoing lung surgery with a low risk of PCs, active smoking does not significantly increase the risk of PCs or PPCs relative to quitters, suggesting that there is likely no need to postpone lung surgery for those who have not yet quit smoking. However, further large-scale studies are necessary to confirm these findings.

Abstract Background METTL3 plays a significant role as a catalytic enzyme in mediating N6-methyladenosine (m6A) modification, and its importance in tumour progression has been extensively studied in recent years. However, the precise involvement of METTL3 in the regulation of translation in non-small cell lung cancer (NSCLC) remains unclear. Results Here we discovered by clinical investigation that METTL3 expression is correlated with NSCLC metastasis. Ablation of METTL3 in NSCLC cells inhibits invasion and metastasis in vitro and in vivo. Subsequently, through translatomics data mining and experimental validation, we demonstrated that METTL3 enhances the translation of aromatase (CYP19A1), a key enzyme in oestrogen synthesis, thereby promoting oestrogen production and mediating the invasion and metastasis of NSCLC. Mechanistically, METTL3 interacts with translation initiation factors and binds to CYP19A1 mRNA, thus enhancing the translation efficiency of CYP19A1 in an m6A-dependent manner. Pharmacological inhibition of METTL3 enzymatic activity or translation initiation factor eIF4E abolishes CYP19A1 protein synthesis. Conclusions Our findings indicate the crucial role of METTL3-mediated translation regulation in NSCLC and reveal the significance of METTL3/eIF4E/CYP19A1 signaling as a promising therapeutic target for anti-metastatic strategies against NSCLC. Graphical abstract

BackgroundHeavy metal exposure is an important cause of reduced bone mineral density (BMD). Epidemiological studies focusing on the effects of mixed heavy metal exposure on BMD in middle-aged and older people are scarce. In single-metal studies, men and women have shown distinct responses of BMD to environmental metal exposure. This study therefore aimed to elucidate the association between mixed heavy metal exposure and BMD and to investigate whether it is sex-specific.MethodsData from the 2017–2020 National Health and Nutrition Examination Survey were selected for this cross-sectional study. The study used three statistical methods, i.e., linear regression, Bayesian kernel machine regression (BKMR) modeling, and weighted quartiles (WQS) regression, to explore the association between the urinary concentrations of 11 metals (barium, cadmium, cobalt, cesium, manganese, molybdenum, lead, antimony, tin, thallium, and Tungsten), either individually or as a mixture, and total femoral BMD.ResultsA total of 1,031 participants were included in this study. Femoral BMD was found to be higher in men than women. A significant negative correlation between the urinary concentrations of the 10 metals and femoral BMD was found in the overall cohort. Further gender sub-stratified analyses showed that in men, urinary metal concentrations were negatively correlated with femoral BMD, with cobalt and barium playing a significant and non-linear role in this effect. In women, although urinary metal concentrations negatively modulated femoral BMD, none of the correlations was statistically significant. Antimony showed sex-specific differences in its effect.ConclusionThe urinary concentrations of 10 mixed heavy metals were negatively correlated with femoral BMD in middle-aged and older participants, and this effect showed gender differences. These findings emphasize the differing role of mixed metal exposure in the process of BMD reduction between the sexes but require further validation by prospective studies.

Constrained multi-objective optimization problems (CMOPs) are commonly encountered in engineering practice. The key to effectively solving these problems lies in achieving a timely balance between convergence, diversity, and feasibility during iterations. Furthermore, the appropriate utilization of infeasible solutions is crucial for identifying potential feasible regions. In order to accomplish this comprehensive objective, we propose a novel dual-stage constrained multi-objective evolutionary algorithm (CMOEA) called NACMOEA in this paper. It can be characterized by the following features: 1) Introducing a novel niche-based individual selection and infeasible solution utilization strategy to enhance convergence, diversity, and feasibility. 2) Presenting a cooperative search strategy assisted by dual archives to approximate the constrained Pareto front (CPF) from both feasible and infeasible perspectives, thereby improving the efficiency of obtaining the complete CPF. 3) Designing a new stage switch method based on non-dominant coverage rate to ensure proper completion of search stage switching. Extensive experiments demonstrate that NACMOEA exhibits competitive comprehensive performance when compared with other advanced CMOEAs.

Gene delivery therapy has emerged as a popular approach for the treatment of various diseases. However, it still poses the challenges of accumulation in target sites and reducing off-target effects. Aerosol gene delivery for the treatment of pulmonary diseases has the advantages of high lung accumulation, specific targeting and fewer systemic side effects. However, the key challenge is selecting the appropriate formulation for aerosol gene delivery that can overcome physiological barriers. There are numerous existing gene carriers under study, including viral vectors and non-viral vectors. With the development of biomaterials, more biocompatible substances have applied gene delivery via inhalation. Furthermore, many types of genes can be delivered through aerosol inhalation, such as DNA, mRNA, siRNA and CRISPR/Cas9. Aerosol delivery of different types of genes has proven to be efficient in the treatment of many diseases such as SARS-CoV-2, cystic fibrosis and lung cancer. In this paper, we provide a comprehensive review of the ongoing research on aerosol gene delivery therapy, including the basic respiratory system, different types of gene carriers, different types of carried genes and clinical applications.

Background: New clinically important postoperative atrial fibrillation (POAF) is the most common arrhythmia after thoracoscopic anatomical lung cancer surgery and is associated with increased morbidity and mortality. The full spectrum of predictors remains unclear, and effective assessment tools are lacking. This study aimed to develop and externally validate a novel model for predicting new clinically important POAF. Methods: This retrospective study included 14 074 consecutive patients who received thoracoscopic anatomical lung cancer surgery from January 2016 to December 2018 in Shanghai Chest Hospital. Based on the split date of 1 January 2018, we selected 8717 participants for the training cohort and 5357 participants for the testing cohort. For external validation, we pooled 2941 consecutive patients who received this surgical treatment from July 2016 to July 2021 in Shanghai Ruijin Hospital. Independent predictors were used to develop a model and internally validated using a bootstrap-resampling approach. The area under the receiver operating characteristic curves (AUROCs) and Brier score were performed to assess the model discrimination and calibration. The decision curve analysis (DCA) was used to evaluate clinical validity and net benefit. New clinically important POAF was defined as a new-onset of POAF that causes symptoms or requires treatment. Results: Multivariate analysis suggested that age, hypertension, preoperative treatment, clinical tumor stage, intraoperative arrhythmia and transfusion, and operative time were independent predictors of new clinically important POAF. These seven candidate predictors were used to develop a nomogram, which showed a concordance statistic (C-statistic) value of 0.740 and good calibration (Brier score; 0.025). Internal validation revealed similarly good discrimination (C-statistic, 0.736; 95% CI: 0.705-0.768) and calibration. The decision curve analysis showed positive net benefits with the threshold risk range of 0-100%. C-statistic value and Brier score were 0.717 and 0.028 in the testing cohort, and 0.768 and 0.012 in the external validation cohort, respectively. Conclusions: This study identified seven predictors of new clinically important POAF, among which preoperative treatment, intraoperative arrhythmia, and operative time were rarely reported. The established and externally validated model has good performance and clinical usefulness, which may promote the application of prevention and treatment in high-risk patients, and reduce the development and related adverse outcomes of this event. [ABSTRACT FROM AUTHOR]