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Abstract To examine the association and modifiable risk factors between grip strength (GS) and Parkinson’s disease (PD) incidence considering genetic factors, a total of 411,648 individuals without PD at baseline from the UK Biobank were included. GS was measured by a hydraulic dynamometer. The polygenic risk score assessed the genetic predisposition. Multivariable Cox regression models were performed. During a median follow-up of 12.3 years, 2409 individuals developed PD. Compared with those with high GS, low-GS individuals had a 58.5% increased risk of PD (42.7%–76.1%), and 16.3% of this excess risk could be explained by adjusted risk factors. Low GS and high genetic predisposition contribute to the highest PD risk in an additive interaction. We observed that low GS was associated with higher PD incidence, particularly among individuals with high genetic predisposition. In addition to enhancing GS, interventions targeting risk factors (e.g., unhealthy lifestyles) might also reduce the excess risk.

Food bioactive compounds, such as polyphenols, carotenoids, functional proteins and unsaturated fatty acids, have been used as important ingredients of functional foods due to their diverse biological activities. However, the low aqueous solubility, poor stability and limited bioavailability of these compounds limit their applications in the food industry. The preparation of delivery carriers from natural food macromolecules offers a promising approach to enhance the solubility, stability, and bioavailability of bioactive compounds. As a novel delivery system, intelligent responsive delivery carriers enable precise targeted and controlled release of bioactive compounds, thus improving their bioavailability. In addition, the delivery carriers have the capacity to effectively improve the added nutritional value, enhance the sensory properties, and extend the shelf life of functional foods. This review summarizes the functional properties of food bioactive compounds, the challenges in their application and their steady-state delivery strategies, with a particular emphasis on the common intelligent responsive delivery carriers and their mechanisms of action. Finally, this article discusses the application of these delivery carriers in functional foods, and provides an outlook on future research on bioactive compound delivery systems.

Abstract Background In the management of complex diseases, the strategic adoption of combination therapy has gained considerable prominence. Combination therapy not only holds the potential to enhance treatment efficacy but also to alleviate the side effects caused by excessive use of a single drug. Presently, the exploration of combination therapy encounters significant challenges due to the vast spectrum of potential drug combinations, necessitating the development of efficient screening strategies. Methods In this study, we propose a prediction scoring method that integrates heterogeneous data using a weighted Bayesian method for drug combination prediction. Heterogeneous data refers to different types of data related to drugs, such as chemical, pharmacological, and target profiles. By constructing a multiplex drug similarity network, we formulate new features for drug pairs and propose a novel Bayesian-based integration scheme with the introduction of weights to integrate information from various sources. This method yields support strength scores for drug combinations to assess their potential effectiveness. Results Upon comprehensive comparison with other methods, our method shows superior performance across multiple metrics, including the Area Under the Receiver Operating Characteristic Curve, accuracy, precision, and recall. Furthermore, literature validation shows that many top-ranked drug combinations based on the support strength score, such as goserelin and letrozole, have been experimentally or clinically validated for their effectiveness. Conclusions Our findings have significant clinical and practical implications. This new method enhances the performance of drug combination predictions, enabling effective pre-screening for trials and, thereby, benefiting clinical treatments. Future research should focus on developing new methods for application in various scenarios and for integrating diverse data sources.

Abstract Suppressor of Mek1 (Smek1) is a regulatory subunit of protein phosphatase 4. Genome‐wide association studies have shown the protective effect of SMEK1 in Alzheimer's disease (AD). However, the physiological and pathological roles of Smek1 in AD and other tauopathies are largely unclear. Here, the role of Smek1 in preventing neurodegeneration is investigated in tauopathy. Smek1 is downregulated in the aged human brain. Through single‐cell sequencing, a novel neuronal cluster is identified that possesses neurodegenerative characteristics in Smek1−/− mice. Smek1 deficiency caused markedly more severe motor and cognitive impairments in mice, as well as neuronal loss, gliosis, and tau hyperphosphorylation at major glycogen synthase kinase 3β (Gsk3β) sites. Protein‐protein interaction analysis revealed that the Ran‐binding domain (RanBD) in the N‐terminus of Smek1 facilitated binding with kinesin family member 2A (Kif2a). Depletion of Smek1 resulted in cytoplasmic aggregation of Kif2a, axon outgrowth defects, and impaired mitochondrial axonal trafficking. Downregulation of Kif2a markedly attenuated tau hyperphosphorylation and axon outgrowth defects in shSmek1 cells. For the first time, this study demonstrates that Smek1 deficiency progressively induces neurodegeneration by exacerbating tau pathology and mitochondrial dysfunction in an age‐dependent manner.

Abstract According to statistics, the incidence of liver cancer is increasing yearly, and effective treatment of liver cancer is imminent. For early liver cancer, resection surgery is currently the most effective treatment. However, resection does not treat the disease in advanced patients, so finding a method with a better prognosis is necessary. In recent years, ferroptosis and cuproptosis have been gradually defined, and related studies have proved that they show excellent results in the therapy of liver cancer. Cuproptosis is a new form of cell death, and the use of cuproptosis combined with ferroptosis to inhibit the production of hepatocellular carcinoma cells has good development prospects and is worthy of in-depth discussion by researchers. In this review, we summarize the research progress on cuproptosis combined with ferroptosis in treating liver cancer, analyze the value of cuproptosis and ferroptosis in the immune of liver cancer, and propose potential pathways in oncotherapy with the combination of cuproptosis and ferroptosis, which can provide background knowledge for subsequent related research.

ObjectiveTo analyze the HIV infection characteristics and influencing factors among the spouses of HIV/AIDS patients in Shanghai.MethodsA cross-sectional survey was conducted to collect demographic， behavioral， epidemiological and spousal HIV detection information of newly reported and married patients with HIV/AIDS in Shanghai from January 2018 to July 2022 in the comprehensive HIV prevention and control information system of Chinese Center for Disease Prevention and Control. Descriptive analysis was used to analyze the HIV positivity rate of the spouses of HIV patients and the influencing factors were analyzed by univariate and multivariate logistic regression models.ResultsA total of 1 233 subjects were investigated， and the first HIV-testing positivity rate of the spouses of HIV/AIDS patients was 29.3% （361/1 233）. There were statistically significant differences in the HIV-testing positivity rate among spouses of HIV/AIDS patients by different age， gender， education level， occupation， transmission route， quantity of non-marital sexual activities， quantity of homo-sexual activities， and baseline CD4 cell count level （P

Probiotics offer numerous health benefits for human beings. However, it is difficult to achieve the expected beneficial effects of oral probiotics due to the viability loss during processing, storage and digestion. Oral delivery systems are effective ways to improve the processing and storage stability, gastric acid and bile salt tolerance, and intestinal adhesion and colonization ability of probiotics. This review focuses on the state of the art of oral delivery of probiotics, and summarizes the types of probiotics commonly used in probiotic products and their functional characteristics. Specifically, this review analyzes the effects of external environmental factors such as humidity, temperature, pH and oxygen, and internal environments such as the mouth, stomach, and small intestine on the survival rate of probiotics. Furthermore, the characteristics and applications of different oral delivery systems including microcapsule, hydrogel, oleogel, nanocoating, emulsion, and nanofiber are compared. Finally, this review proposes future prospects for cost reduction, intelligent packaging, co-packaging and population experiments of probiotic delivery systems, with the aim of providing technical support for the development of probiotic formulations with high storage stability and high viability suitable for intestinal targeted delivery.

Abstract Background Lung adenocarcinoma (LUAD) is a fatal form of lung cancer with a poor prognosis. Coagulation system had been confirmed closely related to tumor progression and the hypercoagulable state encouraged the immune infiltration and development of tumor cells, leading to a poor prognosis in cancer patients. However, the use of the coagulation‐related genes (CRGs) for prognosis in LUAD has yet to be determined. In this study, we constructed an immune‐related signature (CRRS) and identified a potential coagulation‐related biomarker (P2RX1). Methods We obtained a total of 209 CRGs based on two coagulation‐related KEGG pathways, then developed the CRRS signature by using the TCGA‐LUAD RNA‐seq data via the procedure of LASSO‐Cox regression, stepwise‐Cox regression, univariate and multivariate Cox regression. Grouped by the CRRS, Kaplan–Meier survival curves and receiver operating characteristic curves were drawn for the training and validation sets, respectively. In addition, single‐sample gene set enrichment analysis was exploited to explore immune infiltration level. Moreover, immunophenotypes and immunotherapy grouped by CRRS were further analyzed. Results We developed an immune‐related signature (CRRS) composed of COL1A2, F2, PLAUR, C4BPA, and P2RX1 in LUAD. CRRS was an independent risk factor for overall survival and displayed stable and powerful performance. Additionally, CRRS possessed distinctly superior accuracy than traditional clinical variables and molecular features. Functional analysis indicated that the differentially high expressed genes in the low‐risk group significantly enriched in T cell and B cell receptor signaling pathways. The low‐risk group was sensitive to anti‐PD‐1/PD‐L1 immunotherapy and displayed abundant immune infiltration and immune checkpoint gene expression. Finally, we identified an independent prognostic gene P2RX1. Low expression of P2RX1 associated with poor overall survival and decreased immune infiltration. Conclusions Our study revealed a significant correlation between CRRS and immune infiltration. CRRS could serve as a promising tool to improve the clinical outcomes for individual LUAD patients.

Low-carbon development of the iron and steel industry is critical to China’s goal of carbon neutrality and emission peaking. The carbon emissions of China’s iron and steel industry are calculated using the emission factor method in this paper, and the influencing factors of emission growth are investigated using the two-stage logarithmic mean divisia index (LMDI). The results show that carbon emissions from the steel industry continue to rise, reaching a stage peak of 1.848 billion tons in 2014 before declining. Carbon emissions fall by 52.4% during this period, energy intensity decreases by 52.9% per ton of steel; the decline in energy intensity will be much smaller in the future. The scale effect is the most important factor in the growth of carbon emission, accounting for 178.17% of the total, whereas energy intensity is the most important restraining factor, accounting for 76.02% of the total. However, the impact of energy structure and emission factors remains unclear. This is due to the small change in the energy mix and emission factors. The scale effect, which is a major contributor to rising carbon emissions, is broken down once more. Capital stock and total factor productivity drive carbon emission growth, whereas labor factors reflect the transition of the industrial population to low-carbon industries. The STIRPAT model predicts future carbon emissions from the iron and steel industry. The results of the scenario analysis show that carbon emissions will peak in 2025 under the baseline scenario, with carbon emissions totaling 1.904 billion tons. The peak time for carbon emissions in the low carbon scenario is 2021, and the peak is lower, with carbon emissions of 1.867 billion tons. Carbon emissions have already peaked in 2020 in the strong low-carbon scenario and will further decline to 1.439 billion tons in 2030, which is equivalent to 2010 carbon emissions. However, the rapid development scenario will not be able to reach a peak in carbon dioxide emissions before 2030. The forecast results show that both social and economic factors, as well as steel production factors, can have a significant impact on the overall industry’s carbon emission, implying that both the supply and demand sides must contribute to emission reductions. Controlling new capacity, transforming process structure, reducing fossil energy consumption, and promoting the use of hydrogen energy in the smelting process will be critical in the future for the industry’s low-carbon development.

Accurate prediction of shock wave position of hypersonic aircrafts can effectively improve the accuracy and efficiency of computational fluid dynamics (CFD) simulation. On the one hand, orthogonalization and densification of the grid near the shock wave of the hypersonic vehicle can effectively improve the numerical accuracy. On the other hand, using the shock wave position of the hypersonic vehicle to correct the computational grid can speed up the CFD convergence process. A shock wave intelligent prediction method for hypersonic vehicles based on machine learning was proposed, which could efficiently and accurately predict the shock position of the typical hypersonic aircraft shape. Firstly, for the typical hypersonic vehicle shape and typical flight state, numerical methods were used to obtain a convergent flow field. Secondly, the shock wave extraction method based on Mach number contour was used to identify the shock wave surface from the flow field and extract the key points that constitute the shock wave to form training data. After that, the supervised learning method was used to predict the positions of these key points and the quadratic curve was used to fit these key points along the flow direction to form a preliminary shock line family. Finally, based on the typical pressure profile, an image-based neural network was constructed to correct the preliminary shock line family and obtain the three-dimensional shock surface. A large number of experimental results show that the shock wave prediction model can effectively predict the shock wave position of the hypersonic vehicle, and the error between the reconstructed shock wave surface and the extracted shock surface from the CFD results is in the order of 10-4.

We consider a single-machine scheduling problem with due-date assignment and stochastic processing times, where only the mean and support (i.e. an interval bounded with lower and upper values) of processing times are known to the decision maker. The objective is to jointly determine a scheduling policy and a set of due dates for all jobs, so as to minimise the total expected individually weighted costs of earliness, tardiness and due-date assignment. By identifying an upper bound with the robust optimisation approach and a lower bound, and using a linear function of them to approximate the studied objective function, we establish an approximated problem. Then, a branch-and-bound algorithm is proposed to find an optimal solution for the approximated problem. Finally, a series of computational experiments are conducted to examine the performance of problem approximation and two developed heuristic algorithms. HIGHLIGHTS Study due-date assignment scheduling problem with stochastic processing times. Apply the mean and support (interval data) to model stochastic processing times. Use a linear function of identified lower and upper bounds to make an approximation. Derive optimal due-date assignment and develop branch-and-bound algorithms. Evaluate the efficiency of branch-and-bound algorithm and heuristic algorithms. [ABSTRACT FROM AUTHOR]

Plant intraspecific diversity genetic diversity could affect also other trophic levels. This meta-analysis shows that increasing plant genetic diversity improves the performance of plants and natural enemies of herbivores, while decreasing the performance of plant antagonists.

ObjectiveTo explore the effect of esketamine nasal drops on pain in children after tonsillectomy using low-temperature plasma ablation.Methods76 children who underwent tonsillectomy between May 2020 and July 2021, were randomly divided into two groups of 38 cases each. Patients in the control group were treated with conventional medication, while those in the study group were treated with esketamine nasal drops, along with the routine drug treatment. Pain levels of children in the two groups were compared within 1–3 days post-surgery, and the pseudomembrane formation and shedding-off time and recovery time were statistically analyzed.ResultsThe pain level of children in the study group was lower than that of the control group 1–3 days post-surgery. The pseudomembrane formation and shedding-off time and recovery time in the study group were shorter than in the control group (P 0.05).ConclusionIt is safe to use esketamine nasal drops in children after tonsillectomy using low temperature plasma ablation, and this is found to reduce pain and shorten the recovery time.

Abstract Background To compare the effectiveness of intraoperative cell salvage (IOCS) combined with a modified leucocyte depletion filter (MLDF) with IOCS combined with a regular leucocyte depletion filter (RLDF) in eliminating tumour cells from blood salvage during metastatic spine tumour surgery (MSTS). Methods Patients with a known primary epithelial tumour who underwent MSTS were recruited for this study. Blood samples were collected in 5 stages: from the patients’ vein before anaesthesia induction (S1), from the operative field at the time of maximum tumour manipulation (S2), and from the operative blood after IOCS processing (S3) and after IOCS+RLDF (S4) and IOCS+MLDF (S5) processing. The polyploids of tumour cells in the blood samples were collected and counted with immunomagnetic separation enrichment and fluorescence in situ hybridization. Results We recruited 20 patients. Tumour cells were detected in 14 patients (70%) in S1, 16 patients (80%) in S2, 13 patients (65%) in S3, and 12 patients (60%) in S4. MLDF was added in 8 patients. Tumour cells were detected in only 1 of 8 patients in S5 (12.5%). There were significantly fewer tumour cells in the samples collected after MLDF processing (S5) than in the samples collected after RLDF (S4) and around the tumour (S2) (P = 0.016 and P = 0.039, respectively). Although no significant difference was observed between S4 and S1, a downward trend was observed after IOCS+RLDF processing. Conclusions Tumour cells could be removed by IOCS combined with RLDF from blood salvaged during MSTS, but residual tumour cells remained. The findings support the notion that MLDF eliminates tumour cells more effectively than RLDF. Hence, this technique can be applied to MSTS. Trial registration ChiCTR1800016162 Chinese Clinical Trial Registry.