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Abstract In surgical medicine, suturing is the standard treatment for large incisions, yet traditional sutures are limited in functionality. Electrical stimulation is a non-pharmacological therapy that promotes wound healing. In this context, we designed a passive and biodegradable mechanoelectric suture. The suture consists of multi-layer coaxial structure composed of (poly(lactic-co-glycolic acid), polycaprolactone) and magnesium to allow safe degradation. In addition to the excellent mechanical properties, the mechanoelectrical nature of the suture grants the generation of electric fields in response to movement and stretching. This is shown to speed up wound healing by 50% and reduce the risk of infection. This work presents an evolution of the conventional wound closure procedures, using a safe and degradable device ready to be translated into clinical practice.

Abstract Maintaining stillness is essential for accurate bioelectrical signal acquisition, but dynamic noise from breathing remains unavoidable. Isotropic adhesives are often used as bioelectronic interfaces to ensure signal fidelity, but they can leave irreversible residues, compromising device accuracy. We propose a hydrogel with selective frequency damping and asymmetric adhesion as a bioelectronic interface. This hydrogel mitigates dynamic noise from breathing, with a damping effect in the breathing frequency range 60 times greater than at other frequencies. It also exhibits an asymmetric adhesion difference of up to 537 times, preventing residues. By homogenizing ion distribution, extending Debye length, and densifying the electric field, the hydrogel ensures stable signal transmission over 10,000 cycles. Additionally, it can non-invasively diagnose otitis media with higher sensitivity than invasive probes and has been effective in clinical polysomnography monitoring, aiding in the diagnosis of obstructive sleep apnea.

Abstract Purpose This study aimed to use propensity score matching (PSM) to explore the long-term outcomes and failure patterns in locally advanced rectal cancer (LARC) patients with positive versus negative lateral pelvic lymph node (LPLN). Materials and methods Patients with LARC were retrospectively divided into LPLN-positive and LPLN-negative groups. Clinical characteristics were compared between the groups using the chi-square test. PSM was applied to balance these differences. Progression-free survival (PFS) and overall survival (OS), and local–regional recurrence (LRR) and distant metastasis (DM) rates were compared between the groups using the Kaplan–Meier method and log-rank tests. Results A total of 651 LARC patients were included, 160 (24.6%) of whom had positive LPLN and 491 (75.4%) had negative LPLN. Before PSM, the LPLN-positive group had higher rates of lower location (53.1% vs. 43.0%, P = 0.025), T4 stage (37.5% vs. 23.2%, P = 0.002), mesorectal fascia (MRF)-positive (53.9% vs. 35.4%, P

Abstract Background To achieve Universal Health Coverage (UHC), China have implemented health system reform to expend health coverage and improve health equity. Scholars have explored the implementing effect of this health reform, but gaps remained in health care received by elderly. This study aims to assess the effect of implementing health insurance payment reform on health care received by elderly, as well as to evaluate its effect on cost sharing to identify whether improve financial protection of elderly under this reform. Methods We identified hospitalization of 46,714 elderly with cerebral infarction from 2013 to 2023. To examine the determinant role played by DRGs payment reform in healthcare for elderly and their financial protection, this study employs the OLS linear regression model for analysis. In the robustness checks, we validated the baseline results through several methods, including excluding the data from the initial implementation of the reform (2021), reducing the impact of the pandemic, and exploring the group effects of different demographic characteristics. Results The findings proposed that implementing DRGs payment reduces drug expenses but increases treatment expense of chronic disease for elderly in China. This exacerbates healthcare costs for elderly patients and seems to be contrary to the original purpose of health care reform. Additionally, the implementation of DRGs payment reduced the spending of medical insurance fund, while increased the out-of-pocket of patients, revealing a shift in health care expenses from health insurance fund to out-of-pocket. Conclusions This study shares the lessons from China’s health reform and provides enlightenment on how to effective implement health reform to improve health equity and achieve UHC in such low- and middle-income countries facing challenges in health financing.

Abstract The work numerically investigated laminar natural convection heat transfer from the single sphere with a constant heat flux surface in air over the wide range of Grashof number ( $$10 \le Gr \le 10^{7}$$ 10 ≤ G r ≤ 10 7 ). The more efficient and precise numerical method based on Bejan et al. was employed here, the accuracy of which has been confirmed through validation against a single sphere case. The heat transfer characteristics were systemically analyzed in terms of isothermal contours and streamlines around the sphere, dimensionless temperature and velocity profiles. Additionally, local Nusselt number as well as local pressure and friction drag coefficients were studied with different Grashof number. In comparison to the sphere with uniform heat flux surface, the heat transfer from the isothermal sphere was found to be enhanced attributable to a more robust buoyancy force and a steeper temperature gradient. Moreover, the average Nusselt number for the sphere with a constant heat flux between 60.4 and 98.6% of the isothermal sphere’s value, this range being contingent upon the specific Grashof number. What’s more, the proposed correlation addresses a notable void in the predictive understanding of heat transfer from the sphere with uniform heat flux, which is scenario prevalent in various engineering applications, particularly for the cooling of electrical and nuclear systems, and offer values for academic research.

Background: Education level significantly impacts individual health outcomes. This research investigates the correlation between education level and the prevalence of overactive bladder (OAB). Methods: This study employed data from the National Health and Nutrition Examination Survey (NHANES) spanning 2005 to 2020 to conduct a thorough investigation of the association between educational level and OAB using multivariable logistic regression, smooth curve fitting, and generalized additive model. Results: Out of 37,423 surveyed participants from the United States, 8,033 were identified with OAB. The comprehensive adjusted model revealed a notable inverse correlation between education level and OAB prevalence (odds ratio [OR] = 0.86, 95 % confidence interval [CI] = 0.83–0.89, P < 0.001). When education level was categorized, participants with the highest educational qualification (college graduates or higher) had a 44 % lower likelihood of having OAB compared to those with the lowest education (below 9th grade) (OR = 0.56, 95 % CI = 0.47–0.66, P < 0.001). Conclusion: The findings underscore a substantial inverse correlation between education level and OAB prevalence. Although continued research is required to confirm these findings, educational attainment may guide the development of preventative and therapeutic strategies for OAB.

ABSTRACT Background Prostate cancer (PCa) is the most common urinary tumor with the highest incidence rate and the second among the leading causes of death worldwide for adult males. In the worldwide cancer incidence rate, PCa is on the increase. The cancerous cells in the prostate and cells in the microenvironment surrounding the tumor communicate through signal transduction, which is crucial for the development and spread of PCa. Recent findings Exosomes are nanoscale vesicles released into body fluids by various cells that can aid intercellular communication by releasing nucleic acids and proteins. Exosomes published by different types of cells in the tumor microenvironment can have varying impacts on the proliferation and growth of tumor cells via various signaling pathways, modes of action, and secreted cytokines. Conclusion The main purpose of this review is to describe the effects of different cell‐derived exosomes in the tumor microenvironment of PCa on the progression of tumor cells, as well as to summarize and discuss the prospects for the application of exosomes in the treatment and diagnosis of PCa.

An understanding of recombinant adeno-associated virus (AAV) biodistribution profiles is an important element of a preclinical development program. Here, we have developed a radiolabeling strategy utilizing the co-delivery of 125I (non-residualizing) and 111In (residualizing) radionuclide-conjugated AAVs to provide a detailed distribution quantification at tissue level delineating between the cellular internalized AAV (degraded, 111In-125I) and AAV remaining in the extracellular matrix (intact, 125I). This labeling method has been successfully applied to AAV9 and AAV-PHP.eB as tool molecules without altering the physical properties and biological activities of the AAVs. Upon labeling with either of the radioactive probes, these molecules were systemically injected into C57BL/6 mice. The biodistribution results indicate that AAVs, with a fast distribution profile, were mainly located in the extracellular matrix of highly perfused organs such as liver and spleen at early time points, leading to a difference between capsid quantification and vector genome quantification. The results suggest that the 125I-AAV/111In-AAV co-delivery approach offers a robust and efficient analytical strategy to investigate the detailed tissue distribution of AAV vectors, including both vector genome and protein capsids. This novel method has the potential to be applied to capsid optimization, selection, and lead candidate development.

With the explosive growth of data, the digital economy, where data serves as a crucial element, continues to advance.In the context of data markets, establishing a fair and efficient pricing and trading system becomes paramount.Addressing fairness within data markets, this study introduces a data market model based on data quality.Firstly, aiming at user demands, a comprehensive pricing strategy based on data quality is formulated.Secondly, to mitigate malicious fraudulent behaviors from users, a market mechanism ensuring fair data transactions is designed.Lastly, building upon primary data transactions, data cleaning services related to data quality are discussed.A multi-user value allocation mechanism for cleaning is designed using principles from game theory.Experimental results demonstrate that constructing systems according to this model ensures both efficiency and fairness within data markets.

Abstract Developing fiber electronics presents a practical approach for establishing multi-node distributed networks within the human body, particularly concerning triboelectric fibers. However, realizing fiber electronics for monitoring micro-physiological activities remains challenging due to the intrinsic variability and subtle amplitude of physiological signals, which differ among individuals and scenarios. Here, we propose a technical approach based on a dynamic stability model of sheath-core fibers, integrating a micro-flexure-sensitive fiber enabled by nanofiber buckling and an ion conduction mechanism. This scheme enhances the accuracy of the signal transmission process, resulting in improved sensitivity (detectable signal at ultra-low curvature of 0.1 mm−1; flexure factor >21.8% within a bending range of 10°.) and robustness of fiber under micro flexure. In addition, we also developed a scalable manufacturing process and ensured compatibility with modern weaving techniques. By combining precise micro-curvature detection, micro-flexure-sensitive fibers unlock their full potential for various subtle physiological diagnoses, particularly in monitoring fiber upper limb muscle strength for rehabilitation and training.

Abstract Thin films of organic mixed ionic electronic conductors (OMIECs) constitute the functional layer in organic electrochemical transistors (OECTs), organic bioelectronic transducers and other ionic‐electronic devices. The thin‐film configuration constrains devices to be fabricated on impermeable substrates in the form of 2D microstructures with lateral electrodes to drive an electronic current through the thin film. In order to alleviate such constraints, novel OMIEC deposition methods are needed that produce alternatives to thin‐film devices and that are compatible with permeable substrates and electronic transport in the vertical direction. Here OMIECs filled nanoporous membranes are introduced as functional layer in devices with mixed ionic electronic transport. Electropolymerization of ethylenedioxythiophene (EDOT) monomers is used to fabricate OMIEC filled nanochannels. Electronic and ionic transport through such nanochannels are investigated and modulation of electronic as well as ionic carrier density by action of a third gate electrode is demonstrated. The novel OMIEC nanochannels enable the fabrication of vertical OECTs with high transconductance and organic ionic transistors using only additive fabrication methods.

Summary: Platinum-based chemo-resistance is the major issue for the treatment of small cell lung cancer (SCLC). The integrative analysis of multi-omics data is a reliable approach for discovering novel biomarkers associated with chemo-resistance. Here, multi-omics integrative analysis and Cox regression found that higher expression of PCDHB4 was associated with poorer survival of SCLC patients who received chemotherapy. PCDHB4 gene was hypomethylated and upregulated in SCLC, which was validated in the levels of promoter methylation, mRNA, and protein expression. Mechanistically, using bulk RNA-seq data, functional enrichment analysis indicated that higher PCDHB4 expression was associated with lower immune infiltration. The analysis of single-cell RNA-seq (scRNA-seq) found that SCLC cells with PCDHB4 expression exhibited the characteristics of stemness and EMT. In addition, the high expression and hypomethylation of PCDHB4 were also significantly associated with poor survival in lung squamous cell carcinoma. In summary, PCDHB4 is a potential prognostic biomarker of platinum-based chemotherapy in SCLC.

ABSTRACT: Migratory wild birds can carry various pathogens, such as influenza A virus, which can spread to globally and cause disease outbreaks and epidemics. Continuous epidemiological surveillance of migratory wild birds is of great significance for the early warning, prevention, and control of epidemics. To investigate the pathogen infection status of migratory wild birds in eastern China, fecal samples were collected from wetlands to conduct pathogen surveillance. The results showed that duck orthoreovirus (DRV) and goose parvovirus (GPV) nucleic acid were detected positive in the fecal samples collected from wild ducks, egrets, and swan. Phylogenetic analysis of the amplified viral genes reveals that the isolates were closely related to the prevalent strains in the regions involved in East Asian-Australasian (EAA) migratory flyway. Phylogenetic analysis of the amplified viral genes confirmed that they were closely related to circulating strains in the regions involved in the EAA migration pathway. The findings of this study have expanded the host range of the orthoreovirus and parvovirus, and revealed possible virus transmission between wild migratory birds and poultry.

Pancreatic fat is associated with obesity and type 2 diabetes mellitus (T2DM); however, the relationship between different types of pancreatic fat and diabetes status remains unclear. Therefore, we aimed to determine the potential of different types of pancreatic fat accumulation as a risk factor for T2DM in overweight or obese patients. In total, 104 overweight or obese patients were recruited from January 2020 to December 2022. The patients were divided into three groups: normal glucose tolerance (NGT), impaired fasting glucose or glucose tolerance (IFG/IGT), and T2DM. mDixon magnetic resonance imaging (MRI) was used to detect pancreatic fat in all three groups of patients. The pancreatic head fat (PHF), body fat (PBF), and tail fat (PTF) in the IFG/IGT group were 21, 20, and 31% more than those in the NGT group, respectively. PHF, PBF, and PTF were positively associated with glucose metabolic dysfunction markers in the NGT group, and inter-lobular fat volume (IFV) was positively associated with these markers in the IFG/IGT group. The areas under the receiver operating characteristic curves for PHF, PBF, and PTF (used to evaluate their diagnostic potential for glucose metabolic dysfunction) were 0.73, 0.73, and 0.78, respectively, while those for total pancreatic volume (TPV), pancreatic parenchymal volume, IFV, and IFV/TPV were 0.67, 0.67, 0.66, and 0.66, respectively. These results indicate that intra-lobular pancreatic fat, including PHF, PTF, and PBF, may be a potential independent risk factor for the development of T2DM. Additionally, IFV exacerbates glucose metabolic dysfunction. Intra-lobular pancreatic fat indices were better than IFV for the diagnosis of glucose metabolic dysfunction.

Artificial optoelectronic synaptic transistors have attracted extensive research interest as an essential component for neuromorphic computing systems and brain emulation applications. However, performance challenges still remain for synaptic devices, including low energy consumption, high integration density, and flexible modulation. Employing trapping and detrapping relaxation, a novel optically stimulated synaptic transistor enabled by the AlGaN/GaN hetero-structure metal-oxide semiconductor high-electron-mobility transistor has been successfully demonstrated in this study. Synaptic functions, including excitatory postsynaptic current (EPSC), paired-pulse facilitation index, and transition from short-term memory to long-term memory, are well mimicked and explicitly investigated. In a single EPSC event, the AlGaN/GaN synaptic transistor shows the characteristics of low energy consumption and a high signal-to-noise ratio. The EPSC of the synaptic transistor can be synergistically modulated by both optical stimulation and gate/drain bias. Moreover, utilizing a convolution neural network, hand-written digit images were used to verify the data preprocessing capability for neuromorphic computing applications.

Abstract Background Tumor mutational burden (TMB) is one of the most significant predictive biomarkers of immunotherapy efficacy in non-small cell lung cancer (NSCLC). Radiomics allows high-throughput extraction and analysis of advanced and quantitative medical imaging features. This study develops and validates a radiomic model for predicting TMB level and the response to immunotherapy based on CT features in NSCLC. Method Pre-operative chest CT images of 127 patients with NSCLC were retrospectively studied. The 3D-Slicer software was used to outline the region of interest and extract features from the CT images. Radiomics prediction model was constructed by LASSO and multiple logistic regression in a training dataset. The model was validated by receiver operating characteristic (ROC) curves and calibration curves using external datasets. Decision curve analysis was used to assess the value of the model for clinical application. Results A total of 1037 radiomic features were extracted from the CT images of NSCLC patients from TCGA. LASSO regression selected three radiomics features (Flatness, Autocorrelation and Minimum), which were associated with TMB level in NSCLC. A TMB prediction model consisting of 3 radiomic features was constructed by multiple logistic regression. The area under the curve (AUC) value in the TCGA training dataset was 0.816 (95% CI: 0.7109–0.9203) for predicting TMB level in NSCLC. The AUC value in external validation dataset I was 0.775 (95% CI: 0.5528–0.9972) for predicting TMB level in NSCLC, and the AUC value in external validation dataset II was 0.762 (95% CI: 0.5669–0.9569) for predicting the efficacy of immunotherapy in NSCLC. Conclusion The model based on CT radiomic features helps to achieve cost effective improvement in TMB classification and precise immunotherapy treatment of NSCLC patients.

Abstract Background Hospital chief financial officer (CFO) contributes to improving health system performance. However, how to become an excellent hospital CFO has rarely been considered from a holistic perspective. This paper aims to identify competencies required by hospital CFO to fulfil the position’s responsibilities and explore effective implementation pathways to generate high performance and improve healthcare service. Methods We conducted 61 semi-structured interviews with individuals in key leadership positions in China’s hospitals and researchers focusing on healthcare system management to identify core competencies necessary for hospital CFO. Interviews were analysed through a multi-stage review process and modified via expert vetting using a national panel of 23 professors. Subsequently, interviews were conducted with 32 hospital CFOs from 14 provinces throughout September 2021 to May 2022. We scored the performance of 32 hospital CFOs in various aspects of competency and used the fuzzy-set qualitative comparative analysis to explore the competency configurations of excellent CFOs. Results We identify seven core competencies necessary for a hospital CFO to fulfil management practices, including personal morality, resource management, strategy management, learning ability, negotiating skill, leadership skill, and financial management. The findings indicate that a single competency factor is not a necessary condition to become an excellent hospital CFO. The results of qualitative comparative analysis then make it possible to propose four configurational paths, namely, supportive, interpersonal, all-around development, and technical, to become an excellent hospital CFO and achieve effective managerial performance. Conclusions The responsibilities of hospital CFOs are complex and varied, hence, a better understanding of competencies required by CFO is essential to implement their responsibilities effectively. The identification in this study of the four effective implementation pathways to becoming an excellent hospital CFO enriches the literature on hospital management and provides implications for China’s hospitals and their CFOs.

Abstract To investigate the occurrence and 90-day mortality of cancer patients following unplanned admission to the intensive care unit (ICU), as well as to develop a risk prediction model for their 90-day prognosis. We prospectively analyzed data from cancer patients who were admitted to the ICU without prior planning within the past 7 days, specifically between May 12, 2021, and July 12, 2021. The patients were grouped based on their 90-day survival status, and the aim was to identify the risk factors influencing their survival status. A total of 1488 cases were included in the study, with an average age of 63.2 ± 12.4 years. The most common reason for ICU admission was sepsis (n = 940, 63.2%). During their ICU stay, 29.7% of patients required vasoactive drug support (n = 442), 39.8% needed invasive mechanical ventilation support (n = 592), and 82 patients (5.5%) received renal replacement therapy. We conducted a multivariate COX proportional hazards model analysis, which revealed that BMI and a history of hypertension were protective factors. On the other hand, antitumor treatment within the 3 months prior to admission, transfer from the emergency department, general ward, or external hospital, high APACHE score, diagnosis of shock and respiratory failure, receiving invasive ventilation, and experiencing acute kidney injury (AKI) were identified as risk factors for poor prognosis within 90 days after ICU admission. The average length of stay in the ICU was 4 days, while the hospital stay duration was 18 days. A total of 415 patients died within 90 days after ICU admission, resulting in a mortality rate of 27.9%. We selected 8 indicators to construct the predictive model, which demonstrated good discrimination and calibration. The prognosis of cancer patients who are unplanned transferred to the ICU is generally poor. Assessing the risk factors and developing a risk prediction model for these patients can play a significant role in evaluating their prognosis.

Abstract Background Mutated KRAS may indicate an invasive nature and predict prognosis in locally advanced rectal cancer (LARC). We aimed to establish a radiomic model using pretreatment T2W MRIs to predict KRAS status and explore the association between the KRAS status or model predictions and lung metastasis. Methods In this retrospective multicentre study, LARC patients from two institutions between January 2012 and January 2019 were randomly divided into training and testing cohorts. Least absolute shrinkage and selection operator (LASSO) regression and the support vector machine (SVM) classifier were utilized to select significant radiomic features and establish a prediction model, which was validated by radiomic score distribution and decision curve analysis. The association between the model stratification and lung metastasis was investigated by Cox regression and Kaplan‒Meier survival analysis; the results were compared by the log-rank test. Results Overall, 103 patients were enrolled (73 and 30 in the training and testing cohorts, respectively). The median follow-up was 38.1 months (interquartile range: 26.9, 49.4). The radiomic model had an area under the curve (AUC) of 0.983 in the training cohort and 0.814 in the testing cohort. Using a cut-off of 0.679 defined by the receiver operating characteristic (ROC) curve, patients with a high radiomic score (RS) had a higher risk for lung metastasis (HR 3.565, 95% CI 1.337, 9.505, p = 0.011), showing similar predictive performances for the mutant and wild-type KRAS groups (HR 3.225, 95% CI 1.249, 8.323, p = 0.016, IDI: 1.08%, p = 0.687; NRI 2.23%, p = 0.766). Conclusions We established and validated a radiomic model for predicting KRAS status in LARC. Patients with high RS experienced more lung metastases. The model could noninvasively detect KRAS status and may help individualize clinical decision-making.

China's central state-owned enterprises (SOEs) are politically and economically significant, and executives play a crucial role in determining their performance. In a competitive business environment, the selection and competencies of central SOE executives are crucial. This study aims to identify the competencies required to operate central SOEs and develops a competency framework for their executives. Through qualitative studies (face-to-face interviews and Delphi method) and two quantitative studies, we identify four dimensions—self-development, interpersonal, positional and organizational development—comprising 12 factors and 45 competencies, and use these to construct a competency framework. The competencies identified include some previously identified, but also unique competencies that are specific to the Chinese context. The proposed framework is valuable for understanding and improving managerial practices in central SOEs, and will help in the selection and development of executives. It also provides insights for central SOEs, and for individuals considering career and competency development.

IntroductionDue to the problems of greenhouse gas emissions, noise pollution, and vegetable waste pollution during the transportation of vegetables, it is not conducive to the sustainable development of the environment. To mitigate the pollution of the environment during transportation, vegetable green logistics plays a pivotal role in promoting both environmental sustainability and high-quality economic development. Therefore, it is crucial to evaluate the development of vegetable green logistics.MethodsThis research builds a DEMATEL-ANP-FCE model to scientifically assess the development of vegetable green logistics in Lanling County. In the first place, the model uses DEMATEL to verify the relationship and degree of influence between the primary indexes. In the second place, the ANP approach with Super Decisions software to determine the weights of the indexes at each level. Lastly, evaluating and scoring vegetable green logistics in Lanling County based on FCE.Results and discussionThe results of the study show that there is an interaction relationship between the primary evaluation indexes, and its evaluation score is low, the vegetable logistics in Lanling County has not reached the degree of greening. Accordingly, the evaluation results obtained by the DEMATEL-ANP-FCE model in this work are in line with the actual situation of vegetable green logistics in Lanling County, which verifies that the model has good applicability. Moreover, managerial contributions for promoting the development of vegetable green logistics in Lanling County are put forward in response to the evaluation situation. Expecting to enhance the greening level of vegetable logistical development and advance agricultural sustainability. Finally, all four questions raised in this paper are well addressed. This study also provides a new perspective and evaluation model for future related research.

This study evaluated the feasibilities and outcomes following four-dimensional magnetic resonance imaging (4D-MRI) assisted stereotactic body radiation therapy (SBRT) for unresectable colorectal liver metastases (CRLMs). From March 2018 to January 2022, we identified 76 unresectable CRLMs patients with 123 lesions who received 4D-MRI guided SBRT in our institution. 4D-MRI simulation with or without abdominal compression was conducted for all patients. The prescription dose was 50–65 Gy in 5–12 fractions. The image quality of computed tomography (CT) and MRI were compared using the Clarity Score. Clinical outcomes and toxicity profiles were evaluated. 4D-MRI improved the image quality compared with CT images (mean Clarity Score: 1.67 vs 2.88, P

The chemokine 20 (CCL20) is a member of the CC chemokine family and plays a role in tumor immunity and autoimmune disease. This work investigated the value of CCL20 as a serum diagnostic marker for primary hepatocellular carcinoma (HCC). Based on the data of hepatocellular carcinoma patients in the TCGA database, the up-regulated genes encoding secretory proteins were analyzed in each pathological stage, and the candidate marker CCL20 gene was selected. Serum concentrations of CCL20 in patients with primary HCC, benign liver disease, and healthy subjects were analyzed by enzyme-linked immunosorbent assay (ELISA). The ROC curve evaluated the efficacy of CCL20 alone or in combination with AFP in the diagnosis of HCC. It was found the expression of CCL20 in HCC patients was significantly higher than that in the benign liver disease group and healthy controls (P

The main limitation of wireless sensor networks (WSNs) lies in their reliance on battery power. Therefore, the primary focus of the current research is to determine how to transmit data in a rational and efficient way while simultaneously extending the network’s lifespan. In this paper, a hybrid of a fuzzy logic system and a quantum annealing algorithm-based clustering and routing protocol (FQA) is proposed to improve the stability of the network and minimize energy consumption. The protocol uses a fuzzy inference system (FIS) to select appropriate cluster heads (CHs). In the routing phase, we used the quantum annealing algorithm to select the optimal route from the CHs and the base station (BS). Furthermore, we defined an energy threshold to filter candidate CHs in order to save computation time. Unlike with periodic clustering, we adopted an on-demand re-clustering mechanism to perform global maintenance of the network, thereby effectively reducing the computation and overhead. The FQA was compared with FRNSEER, BOA-ACO, OAFS-IMFO, and FC-RBAT in different scenarios from the perspective of energy consumption, alive nodes, network lifetime, and throughput. According to the simulation results, the FQA outperformed all the other methods in all scenarios.

The advancement of data collection technology has led to a rapid increase in the size of datasets.Due to the big scale and high complexity of the data volume, serious data quality issues arise.Therefore, data cleaning is a necessary and important step in data activities.To effectively reduce human annotation costs while ensuring the accuracy of cleaning, an iterative data cleaning method (IDCHI) with human participation was proposed.This method proposed a data selection optimization method in the detection module, which enables the classifier to have high accuracy in the initial stage; and further proposed a method for selecting data to be manually annotated, effectively reducing the amount of data to be manually annotated.The experimental results show that the proposed method is effective and efficient in cleaning erroneous data.

Abstract Background Ferroptosis is an iron-related form of programmed cell death. Accumulating evidence has identified the pathogenic role of ferroptosis in multiple orthopedic disorders. However, the relationship between ferroptosis and SONFH is still unclear. In addition, despite being a common disease in orthopedics, there is still no effective treatment for SONFH. Therefore, clarifying the pathogenic mechanism of SONFH and investigating pharmacologic inhibitors from approved clinical drugs for SONFH is an effective strategy for clinical translation. Melatonin (MT), an endocrine hormone that has become a popular dietary supplement because of its excellent antioxidation, was supplemented from an external source to treat glucocorticoid-induced damage in this study. Methods Methylprednisolone, a commonly used glucocorticoid in the clinic, was selected to simulate glucocorticoid-induced injury in the current study. Ferroptosis was observed through the detection of ferroptosis-associated genes, lipid peroxidation and mitochondrial function. Bioinformatics analysis was performed to explore the mechanism of SONFH. In addition, a melatonin receptor antagonist and shGDF15 were applied to block the therapeutic effect of MT to further confirm the mechanism. Finally, cell experiments and the SONFH rat model were used to detect the therapeutic effects of MT. Results MT alleviated bone loss in SONFH rats by maintaining BMSC activity through suppression of ferroptosis. The results are further verified by the melatonin MT2 receptor antagonist that can block the therapeutic effects of MT. In addition, bioinformatic analysis and subsequent experiments confirmed that growth differentiation factor 15 (GDF15), a stress response cytokine, was downregulated in the process of SONFH. On the contrary, MT treatment increased the expression of GDF15 in bone marrow mesenchymal stem cells. Lastly, rescue experiments performed with shGDF15 confirmed that GDF15 plays a key role in the therapeutic effects of melatonin. Conclusions We proposed that MT attenuated SONFH by inhibiting ferroptosis through the regulation of GDF15, and supplementation with exogenous MT might be a promising method for the treatment of SONFH. Graphical Abstract

Abstract Background Hospital chief financial officer (CFO) plays a vital role in supporting the effective management of organization. Understanding their competencies is essential to improve hospital development and health care services in China. This paper aims to explore competencies necessary for hospital CFOs to fulfil their management responsibilities and develop a competency framework for hospital CFOs in China. Methods A qualitative study was applied by conducting in-depth interviews with 151 participants from 15 Chinese provinces, comprising 89 individuals from 67 hospitals, and 62 individuals from 39 medical universities. Interviews were anonymised, recorded and transcribed. Qualitative thematic analysis was applied through a multi-stage review process and modified via the Delphi process using a national panel of 36 experts. Results Using content analysis, we identified 17 competencies organized into three themes (personal attitudes, leadership competencies and managerial competencies) to conduct a competency framework for hospital CFO to fulfil their management practices. Those competencies emphasized the integration of different competencies required by the hospital CFO. Conclusions This paper identified the detailed expertise, abilities and personal traits required by hospital CFOs in China, expanding the insights and perspectives of hospital CFOs currently working in China to literature. The proposed framework will help hospitals establish selection criteria, coaching tools, and development plans for CFOs.

Abstract Flexible thin‐film thermoelectric devices (TEDs) can generate electricity from the heat emitted by the human body, which holds great promise for use in energy supply and biomonitoring technologies. The p‐type Sb2Te3 hexagon nanosheets are prepared by the hydrothermal synthesis method and compounded with Ti3C2Tx to make composite films, and the results show that the Ti3C2Tx content has a significant impact on the thermoelectric properties of the composite films. When the Ti3C2Tx content is 2 wt%, the power factor of the composite film reaches ≈59 µW m−1 K−2. Due to the outstanding electrical conductivity, high specific surface area, and excellent flexibility of Ti3C2Tx, the composite films also exhibit excellent thermoelectric and mechanical properties. Moreover, the small addition of Ti3C2Tx has a negligible effect on the phase composition of Sb2Te3 films. The TED consists of seven legs with an output voltage of 45 mV at ΔT = 30 K. The potential of highly flexible thin film TEDs for wearable energy collecting and sensing is great.

BackgroundThe aim of this article was to establish the clinical prognostic models and identify the predictive radiation dosimetric parameters for thrombocytopenia during concurrent chemoradiotherapy for rectal cancer.MethodsIn this retrospective cohort study, patients with rectal adenocarcinoma undergoing concurrent long-term chemoradiotherapy were included. The primary outcome of interest was grade 2 or higher (2+) thrombocytopenia (platelet(PLT) count

Abstract Although hard carbon (HC) demonstrates superior initial Coulombic efficiency, cycling durability, and rate capability in ether‐based electrolytes compared to ester‐based electrolytes for sodium‐ion batteries (SIBs), the underlying mechanisms responsible for these disparities remain largely unexplored. Herein, ex situ electron paramagnetic resonance (EPR) spectra and in situ Raman spectroscopy are combined to investigate the Na storage mechanism of HC under different electrolytes. Through deconvolving the EPR signals of Na in HC, quasi‐metallic‐Na is successfully differentiated from adsorbed‐Na. By monitoring the evolution of different Na species during the charging/discharging process, it is found that the initial adsorbed‐Na in HC with ether‐based electrolytes can be effectively transformed into intercalated‐Na in the plateau region. However, this transformation is obstructed in ester‐based electrolytes, leading to the predominant storage of Na in HC as adsorbed‐Na and pore‐filled‐Na. Furthermore, the intercalated‐Na in HC within the ether‐based electrolytes contributes to the formation of a uniform, dense, and stable solid–electrolyte interphase (SEI) film and eventually enhances the electrochemical performance of HC. This work successfully deciphers the electrolyte‐dominated Na+ storage mechanisms in HC and provides fundamental insights into the industrialization of HC in SIBs.

With the widespread adoption of ultrasound guidance, Seldinger puncture techniques, and intracardiac electrical positioning technology for the placement of peripherally inserted central catheters in recent years, an increasing number of medical staff and patients now accept peripheral placement of totally implantable venous access devices (TIVADs) in the upper arm. This approach has the advantage of completely avoiding the risks of hemothorax, pneumothorax, and neck and chest scarring. Medical specialties presently engaged in this study in China include internal medicine, surgery, anesthesiology, and interventional departments. However, command over implantation techniques, treatment of complications, and proper use and maintenance of TIVAD remain uneven among different medical units. Moreover, currently, there are no established quality control standards for implantation techniques or specifications for handling complications. Thus, this expert consensus is proposed to improve the success rate of TIVAD implantation via the upper-arm approach, reduce complication rates, and ensure patient safety. This consensus elaborates on the technical indications and contraindications, procedures and technical points, treatment of complications, and the use and maintenance of upper-arm TIVAD, thus providing a practical reference for medical staff.

Abstract Background Small cell lung cancer (SCLC) is a very malignant tumor with rapid growth and early metastasis. Platinum-based chemo-resistance is the major issue for SCLC treatment failure. Identifying a new prognostic model will help to make an accurate treatment decision for SCLC patients. Methods Using the genomics of drug sensitivity in cancer (GDSC) database, we identified cisplatin resistance-related lncRNAs in SCLC cells. Based on the competing endogenous RNA (ceRNA) network, we identified the mRNAs correlated with the lncRNAs. Using Cox and LASSO regression analysis, a prognostic model was established. The survival prediction accuracy was evaluated by receiver operating characteristic (ROC) curve and Kaplan–Meier analysis. GSEA, GO, KEGG and CIBERSORT tools were used for functional enrichment and immune cells infiltration analysis. Results We first screened out 10 differentially expressed lncRNAs between cisplatin resistant and sensitive SCLC cells from GDSC database. Based on ceRNA network, 31 mRNAs were identified with a correlation with the 10 lncRNAs. Furthermore, two genes (LIMK2 and PI4K2B) were identified by Cox and LASSO regression analysis to construct a prognostic model. Kaplan–Meier analysis indicated that the high-risk group had a poor overall survival compared with the low-risk group. The predicted area under the ROC curve (AUC) was 0.853 in the training set, and the AUC was 0.671 in the validation set. In the meanwhile, the low expression of LIMK2 or the high expression of PI4K2B in SCLC tumors was also significantly associated with poor overall survival in both training and validation sets. Functional enrichment analysis showed that the low-risk group was enriched in the apoptosis pathway and high immune infiltration of T cells. Finally, an apoptosis-related gene Cathepsin D (CTSD) was identified to be up-regulated in the low-risk group, and its higher expression correlated with better overall survival in SCLC. Conclusion We established a prognostic model and potential biomarkers (LIMK2, PI4K2B and CTSD), which could help to improve the risk stratification of SCLC patients.

Abstract The emergence of ionic-junction devices has attracted growing interests due to the potential of serving as signal transmission and translation media between electronic devices and biological systems using ions. Among them, fiber-shaped iontronics possesses a great advantage in implantable applications owing to the unique one-dimensional geometry. However, fabricating stable ionic-junction on curved surfaces remains a challenge. Here, we developed a polyelectrolyte based ionic-junction fiber via an integrated opposite charge grafting method capable of large-scale continuous fabrication. The ionic-junction fibers can be integrated into functions such as ionic diodes and ionic bipolar junction transistors, where rectification and switching of input signals are implemented. Moreover, synaptic functionality has also been demonstrated by utilizing the fiber memory capacitance. The connection between the ionic-junction fiber and sciatic nerves of the mouse simulating end-to-side anastomosis is further performed to realize effective nerve signal conduction, verifying the capability for next-generation artificial neural pathways in implantable bioelectronics.

With the continuous development of automotive intelligence, vehicle occupant detection technology has received increasing attention. Despite various types of research in this field, a simple, reliable, and highly private detection method is lacking. This paper proposes a method for vehicle occupant detection using millimeter-wave radar. Specifically, the paper outlines the system design for vehicle occupant detection using millimeter-wave radar. By collecting the raw signals of FMCW radar and applying Range-FFT and DoA estimation algorithms, a range–azimuth heatmap was generated, visually depicting the current status of people inside the vehicle. Furthermore, utilizing the collected range–azimuth heatmap of passengers, this paper integrates the Faster R-CNN deep learning networks with radar signal processing to identify passenger information. Finally, to test the performance of the detection method proposed in this article, an experimental verification was conducted in a car and the results were compared with those of traditional machine learning algorithms. The findings indicated that the method employed in this experiment achieves higher accuracy, reaching approximately 99%.

Dysarthria is common in movement disorders, such as Wilson's disease (WD), Parkinson's disease, or Huntington's disease. Dysarthria severity assessment is often indispensable for the management of these diseases. However, such assessment is usually labor‐intensive, time‐consuming, and expensive. To seek efficient and cost‐effective solutions for dysarthria assessment, an artificial intelligence (AI)‐powered acoustic analysis system is proposed and its performance in a valuable sample of WD, an ideal disease model with mainly mixed dysarthria, is verified. A test‐retest reliability analysis yields excellent reproducibility in the acoustic measures (mean intraclass correlation coefficient [ICC] = 0.81). Then, a system for dysarthria assessment is trained with WD patients (n = 65) and sex‐matched healthy controls (n = 65) using a machine learning approach. The system achieves reasonable performance in evaluating dysarthria severity with either stepwise classification or regression (all areas under the curve >80%; mean absolute error = 6.25, r = 0.79, p

Abstract Background The optimal duration and choice of anticoagulant for the treatment of Peripherally inserted central catheters (PICC)-related upper extremity deep vein thrombosis (UEDVT) in cancer patients are still undetermined. Objectives The aim of this study was to assess the efficacy and safety of rivaroxaban for the treatment of PICC-related UEDVT in cancer patients. Methods We conducted a retrospective cohort study including consecutive cancer patients for the management of acute symptomatic PICC-related UEDVT. The efficacy outcome of the study was the 180-day recurrence of any venous thromboembolism (VTE), while the safety outcome was the 180-day incidence of all bleeding events. The Kaplan‒Meier method was used to estimate the overall incidence. Hazard ratios (HRs) were obtained with a Cox proportional hazards model to estimate the risk of the outcome events. Results A total of 217 patients were included in the final analysis with a median age of 56 years old, 41.5% of whom had metastases. After the initial 3–5 days of nadroparin, patients received sequential anticoagulation, either with nadroparin (118 patients) or with rivaroxaban (99 patients). Four patients with recurrent VTE were observed (nadroparin, n = 2; rivaroxaban, n = 2). The 180-day cumulative VTE recurrence rates were 1.7% and 2.0% (p = 0.777) in patients receiving nadroparin and rivaroxaban, respectively. The overall bleeding rate at 180 days was 8.8%. Although no major bleeding events were observed, nineteen patients with clinically relevant nonmajor bleeding (CRNMB) were observed. The 180-day cumulative rate of CRNMB was 5.1% for nadroparin and 13.1% for rivaroxaban (HR = 3.303, 95% CI 1.149–9.497, p = 0.027). Conclusion Our study supported the efficacy of rivaroxaban for treating PICC-related UEDVT in cancer patients. However, data on anticoagulation therapy for PICC-related UEDVT presented with a low risk of VTE recurrence and a relatively high risk of CRNMB bleeding events. Considering the risk–benefit ratio, further well-designed trials are required to optimize the drug selection and duration for the treatment of PICC-related UEDVT in cancer patients.

With the increasing number of users in the metaverse, the data also increases accordingly, which brings challenges to the data management of the metaverse.Big data management techniques are essential to realizing the metaverse.Therefore, data management technology in the metaverse was discussed.The metaverse was decomposed into three levels cloud, edge, and end.The massive data in the metaverse was analyzed.The four challenges of data management in the metaverse were discussed, and the corresponding research routes were put forward from four aspects of data synchronization, data access, data model, and query optimization.

When traditional proportional integral and differential controllers are applied to speed control in permanent magnet synchronous motors (PMSM), their coefficients are basically determined based on experience, which inevitably leads to unsatisfactory results when using this parameter to control the speed stability of permanent magnet synchronous motors. Therefore, this paper proposes an improved quantum genetic algorithm using quantum states as the basic unit. Utilizing quantum properties for global optimization to optimize the coefficients of proportional integral and differential control, improving the rotation angle of quantum state particles through the idea of velocity changes in particle swarm optimization (PSO), introducing adaptive weight changes, using Hadamard gates to replace traditional algorithm mutation strategies, and incorporating disaster mechanisms. In addition, this paper uses four test functions to find the minimum value, thereby verifying that our algorithm has better performance in optimization iteration compared to other algorithms, providing the initial basis for the next step of application in PID parameter optimization. Prove that this method can solve the problem of traditional genetic algorithms falling into local optima due to improper selection, crossover, and mutation methods, which cannot effectively control the stability of motor speed. Finally, this paper uses Matlab2018a simulation to compare with the other four algorithms, and the results show that this algorithm can find better PID parameter values to achieve better results in motor oscillation, overshoot, and faster target speed.

Three common Apolipoprotein E isoforms, ApoE2, ApoE3, and ApoE4, are key regulators of lipid homeostasis, among other functions. Apolipoprotein E can interact with amyloid proteins. The isoforms differ by one or two residues at positions 112 and 158, and possess distinct structural conformations and functions, leading to isoform-specific roles in amyloid-based neurodegenerative diseases. Over 30 different amyloid proteins have been found to share similar characteristics of structure and toxicity, suggesting a common interactome. The molecular and genetic interactions of ApoE with amyloid proteins have been extensively studied in neurodegenerative diseases, but have not yet been well connected and clarified. Here we summarize essential features of the interactions between ApoE and different amyloid proteins, identify gaps in the understanding of the interactome and propose the general interaction mechanism between ApoE isoforms and amyloid proteins. Perhaps more importantly, this review outlines what we can learn from the interactome of ApoE and amyloid proteins; that is the need to see both ApoE and amyloid proteins as a basis to understand neurodegenerative diseases.

Background and purpose: Predicting tumour response would be useful for selecting patients with locally advanced rectal cancer (LARC) for organ preservation strategies. We aimed to develop and validate a prediction model for T downstaging (ypT0-2) in LARC patients after neoadjuvant chemoradiotherapy and to identify those who may benefit from consolidation chemotherapy. Materials and methods: cT3-4 LARC patients at three tertiary medical centers from January 2012 to January 2019 were retrospectively included, while a prospective cohort was recruited from June 2021 to March 2022. Eight filter (principal component analysis, least absolute shrinkage and selection operator, partial least-squares discriminant analysis, random forest)-classifier (support vector machine, logistic regression) models were established to select radiomic features. A nomogram combining radiomics and significant clinical features was developed and validated by calibration curve and decision curve analysis. Interaction test was conducted to investigate the consolidation chemotherapy benefits. Results: A total of 634 patients were included (426 in training cohort, 174 in testing cohort and 34 in prospective cohort). A radiomic prediction model using partial least-squares discriminant analysis and a support vector machine showed the best performance (AUC: 0.832 [training]; 0.763 [testing]). A nomogram combining radiomics and clinical features showed significantly better prognostic performance (AUC: 0.842 [training]; 0.809 [testing]) than the radiomic model. The model was also tested in the prospective cohort with AUC 0.727. High-probability group (score > 81.82) may have potential benefits from ≥ 4 cycles consolidation chemotherapy (OR: 4.173, 95 % CI: 0.953–18.276, p = 0.058, pinteraction = 0.021). Conclusion: We identified and validated a model based on multicenter pre-treatment radiomics to predict ypT0-2 in cT3-4 LARC patients, which may facilitate individualised treatment decision-making for organ-preservation strategies and consolidation chemotherapy.

Data cleaning is considered as an effective approach of improving data quality in order to help practitioners and researchers be devoted to downstream analysis and decision-making without worrying about data trustworthiness. This paper provides a systematic summary of the two main stages of data cleaning for Internet of Things (IoT) data with time series characteristics, including error data detection and data repairing. In respect to error data detection techniques, it categorizes an overview of quantitative data error detection methods for detecting single-point errors, continuous errors, and multidimensional time series data errors and qualitative data error detection methods for detecting rule-violating errors. Besides, it provides a detailed description of error data repairing techniques, involving statistics-based repairing, rule-based repairing, and human-involved repairing. We review the strengths and the limitations of the current data cleaning techniques under IoT data applications and conclude with an outlook on the future of IoT data cleaning.

Several essential brain micro-environments like pH, salt, and metal ions play a vital role in modulating the amyloid-ß fibrillation, however, the cooperative modulation of these variables remains poorly understood. Here, the authors investigate multivariate effects of pH, ionic strength, and Zn2+ ions on Aß40 peptide fibrillation.

Abstract Background While an important surgical landmark of the dentate line has been established for locally advanced lower rectal cancer (LALRC), the prognostic significance of dentate line invasion (DLI) has not been well defined. This study aimed to explore the impact of DLI on prognosis in LALRC patients with anal sphincter involvement after neoadjuvant chemoradiotherapy followed by surgery. Methods We analyzed 210 LALRC patients and classified them into DLI group (n = 45) or non-DLI group (n = 165). The exact role of DLI in survival and failure patterns was assessed before and after propensity-score matching(PSM). Finally, 50 patients were matched. Results Before matching, patients in the DLI group had poorer 5-year distant relapse-free survival (DRFS) (P

Abstract Background Venous thromboembolism (VTE) is a threat to the prognosis of tumor patients, especially for critically ill patients. No uniform standard model of VTE risk for critically ill patients with tumors was formatted by now. We thus analyzed risk factors of VTE from the perspectives of patient, tumor, and treatment and assessed the predictive value of the ICU-VTE score, which consisted of six independent risk factors (central venous catheterization, 5 points; immobilization ≥ 4 days, 4 points; prior VTE, 4 points; mechanical ventilation, 2 points; lowest hemoglobin during hospitalization ≥ 90 g/L, 2 points; and baseline platelet count > 250,000/μL, 1 points). Methods We evaluated the data of tumor patients admitted to the intensive care unit of the Peking University Cancer Hospital between November 2011 and January 2022; 560 cases who received VTE-related screening during hospitalization were chosen for this retrospective study. Results The inhospital VTE occurrence rate in our cohort was 55.7% (312/560), with a median interval from ICU admission to VTE diagnosis of 8.0 days. After the multivariate logistic regression analysis, several factors were proved to be significantly associated with inhospital VTE: age ≥ 65 years, high tumor grade (G3–4), medical diseases, fresh frozen plasma transfusion, and anticoagulant prophylaxis. The medium-high risk group according to the ICU-VTE score was positively correlated with VTE when compared with the low-risk group (9–18 points vs. 0–8 points; OR, 3.13; 95% CI, 2.01–4.85, P < 0.001). The AUC of the ICU-VTE scores according to the ROC curve was 0.714 (95% CI, 0.67–0.75, P < 0.001). Conclusions The ICU-VTE score, as well as tumor grade, might assist in the assessment of inhospital VTE risk for critically ill patients with tumors. The predictive accuracy might be improved when combining two of them; further follow-up researches are needed to confirm it.

Background: The study of tumor metabolism is of great value to elucidate the mechanism of tumorigenesis and predict the prognosis of patients. However, the prognostic role of metabolism-related genes (MRGs) in gastric adenocarcinoma (GAD) remains poorly understood. Methods: We downloaded the gene chip dataset GSE79973 (n = 20) of GAD from the Gene Expression Omnibus (GEO) database to compare differentially expressed genes (DEGs) between normal and tumor tissues. We then extracted MRGs from these DEGs and systematically investigated the prognostic value of these differential MRGs for predicting patients' overall survival by univariable and multivariable Cox regression analysis. Six metabolic genes (ACOX3, APOE, DIO2, HSD17B4, NUAK1, and WHSC1L1) were identified as prognosis-associated hub genes, which were used to build a prognostic model in the training dataset GSE15459 (n = 200), and then validated in the dataset GSE62254 (n = 300). Results: Patients were divided into high-risk and low-risk subgroups based on the model's risk score, and it was found that patients in the high-risk subgroup had shorter overall survival than those in the low-risk subgroup, both in the training and testing datasets. In addition, for the training and testing cohorts, the area under the ROC curve of the prognostic model for one-year survival prediction was 0.723 and 0.667, respectively, indicating that the model has good predictive performance. Furthermore, we established a nomogram based on tumor stage and risk score to effectively predict the overall survival (OS) of GAD patients. The expression of 6 MRGs at the protein level was confirmed by immunohistochemistry (IHC). Kaplan-Meier survival analysis further confirmed that their expression influenced OS in GAD patients. Conclusion: Collectively, the 6 MRGs signature might be a reliable tool for assessing OS in GAD patients, with potential application value in clinical decision-making and individualized therapy.

To study the normal section crack resistance of pre-stressed steel-reinforced concrete simply supported composite beams, the specific parameters such as the component steel content, the reinforcement ratio of non-pre-stressed and pre-stressed bars, and the section size of simply supported beams, are designed with different sections and reinforcement. Given the relatively poor bond property between steel and concrete, by introducing the bond property reduction coefficient, the formula for calculating the average crack spacing of pre-stressed steel-concrete simply supported composite beams is modified. Through the analysis of test data, the influence coefficient of concrete self-elongation between cracks on crack width is obtained, and the formula for calculating average crack width reflecting the characteristics of pre-stressed steel-concrete simply supported composite beams is obtained. The value of the expansion coefficient considering the uneven distribution of cracks is obtained by the crack distribution curve and the formula for calculating the crack width of pre-stressed steel concrete composite beams is given. The actual average crack spacing of the 5 pre-stressed steel-concrete simply supported beams in this test is 106.04 mm, which is calculated according to the above formula. The average value of the ratio between the calculated value and the measured value is 0.916, the standard deviation is 0.059, and the coefficient of variation is 0.064. The average value of calculated and measured crack widths of the beams is 0.927, the standard deviation is 0.194, and the coefficient of variation is 0.209.

Abstract Background Pyroptosis is a programmed cell death mediated by the gasdermin superfamily, accompanied by inflammatory and immune responses. Exogenously activated pyroptosis is still not well characterized in the tumor microenvironment. Furthermore, whether pyroptosis-related genes (PRGs) in lower-grade glioma (LGG) may be used as a biomarker remains unknown. Methods The RNA-Sequencing and clinical data of LGG patients were downloaded from publicly available databases. Bioinformatics approaches were used to analyze the relationship between PRGs and LGG patients’ prognosis, clinicopathological features, and immune status. The NMF algorithm was used to differentiate phenotypes, the LASSO regression model was used to construct prognostic signature, and GSEA was used to analyze biological functions and pathways. The expression of the signature genes was verified using qRT-PCR. In addition, the L1000FWD and CMap tools were utilized to screen potential therapeutic drugs or small molecule compounds and validate their effects in glioma cell lines using CCK-8 and colony formation assays. Results Based on PRGs, we defined two phenotypes with different prognoses. Stepwise regression analysis was carried out to identify the 3 signature genes to construct a pyroptosis-related signature. After that, samples from the training and test cohorts were incorporated into the signature and divided by the median RiskScore value (namely, Risk-H and Risk-L). The signature shows excellent predictive LGG prognostic power in the training and validation cohorts. The prognostic signature accurately stratifies patients according to prognostic differences and has predictive value for immune cell infiltration and immune checkpoint expression. Finally, the inhibitory effect of the small molecule inhibitor fedratinib on the viability and proliferation of various glioma cells was verified using cell biology-related experiments. Conclusion This study developed and validated a novel pyroptosis-related signature, which may assist instruct clinicians to predict the prognosis and immunological status of LGG patients more precisely. Fedratinib was found to be a small molecule inhibitor that significantly inhibits glioma cell viability and proliferation, which provides a new therapeutic strategy for gliomas.

Abstract In order to enhance the speed control performance of the brushless DC motor (BLDCM), a novel proportion integration differentiation (PID) is proposed in this paper by using dual fuzzy logic systems (FLSs) with harmony search algorithm (HSA) optimization, which is called DFPID-HSA. Firstly, the FLS1 in DFPID-HSA locks the three coefficients of the PID controller in an extensive range on the basis of the system error and error change rate. Then, the FLS2 is optimized by HSA (HSA-F2) to obtain the precise correction of the three coefficients. To get the optimal global harmony better, the improved dynamic adjustment mode is used for the pitch adjustment rate (PAR) and distance bandwidth (BW) in HSA, and the triple selection method is adopted in the composition harmony section to realize the global search. Finally, DFPID-HSA provides the optimal supply control signal to BLDCM so that it can control the speed effectively. Moreover, the stability of the system is analyzed by the pole, Lyapunov, and Nyquist determination methods. And the sensitivity analysis of DFPID-HSA is carried out under the condition of different motor’s mechanical parameters to check its robustness. In addition, the superiority of DFPID-HSA is verified by MATLAB simulation and experiment platform.