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Abstract Breast cancer diagnosis and treatment have been revolutionized by multiparametric Magnetic Resonance Imaging (mpMRI), encompassing T2-weighted imaging (T2WI), Diffusion-weighted imaging (DWI), and Dynamic Contrast-Enhanced MRI (DCE-MRI). We conducted a retrospective analysis of mpMRI data from 194 breast cancer patients (September 2019 to October 2023). Using ‘pyradiomics’ for radiomics feature extraction and MOVICS for unsupervised clustering. Interestingly, we identified two distinct patient clusters associated with significant differences in molecular subtypes, particularly in Luminal A subtype distribution (p = 0.03), estrogen receptor (ER) (p = 0.01), progesterone receptor (PR) (p = 0.04), mean tumor size (p

Abstract Background Glycerophospholipids (GPLs) are essential for cell membrane structure and function. Sphingomyelin and its metabolites regulate cell growth, apoptosis, and stress responses. This study aimed to investigate lipid metabolism in patients experiencing sudden sensorineural hearing loss across all frequencies (AF-SSNHL). Methods The study included 60 patients diagnosed with unilateral AF-SSNHL, among whom 30 patients had a level of hearing improvement ≥ 15 dB after 6 months of follow-up. A propensity score-matched (2:1) control group was used. Liquid chromatography‒mass spectrometry based untargeted lipidomics analysis combined with multivariate statistics was performed to investigate the lipids change. The “lipidome” R package and weighted gene co-expression network analysis (WGCNA) were utilised to assess the lipids’ structural features and the association between lipids and hearing. Results Lipidomics successfully differentiated the AF-SSNHL group from the control group, identifying 17 risk factors, mainly including phosphatidylcholine (PC), phosphatidylethanolamine (PE), and related metabolites. The ratios of lysophosphatidylcholine/PC, lysophosphatidylethanolamine/PE, and lysodimethylphosphatidylethanolamine/PE were upregulated, while some glycerophospholipid (GPL)-plasmalogens were downregulated in the AF-SSNHL group, indicating abnormal metabolism of GPLs. Trihexosylceramide (d34:1), PE (18:1e_22:5), and sphingomyelin (d40:3) were significantly different between responders and nonresponders, and positively correlated with hearing improvement. Additionally, the results of the WGCNA also suggested that partial GPL-plasmalogens were positively associated with hearing improvement. Conclusion AF-SSNHL patients exhibited abnormally high blood lipids and pronounced GPLs metabolic abnormalities. Sphingolipids and GPL-plasmalogens had an association with the level of hearing improvement. By understanding the lipid changes, clinicians may be able to predict the prognosis of hearing recovery and personalize treatment approaches.

Abstract Background The effects on bone mineral density (BMD)/fracture between type 1 (T1D) and type 2 (T2D) diabetes are unknown. Therefore, we aimed to investigate the causal relationship between the two types of diabetes and BMD/fracture using a Mendelian randomization (MR) design. Methods A two-sample MR study was conducted to examine the causal relationship between diabetes and BMD/fracture, with three phenotypes (T1D, T2D, and glycosylated hemoglobin [HbA1c]) of diabetes as exposures and five phenotypes (femoral neck BMD [FN-BMD], lumbar spine BMD [LS-BMD], heel-BMD, total body BMD [TB-BMD], and fracture) as outcomes, combining MR-Egger, weighted median, simple mode, and inverse variance weighted (IVW) sensitivity assessments. Additionally, horizontal pleiotropy was evaluated and corrected using the residual sum and outlier approaches. Results The IVW method showed that genetically predicted T1D was negatively associated with TB-BMD (β = -0.018, 95% CI: -0.030, -0.006), while T2D was positively associated with FN-BMD (β = 0.033, 95% CI: 0.003, 0.062), heel-BMD (β = 0.018, 95% CI: 0.006, 0.031), and TB-BMD (β = 0.050, 95% CI: 0.022, 0.079). Further, HbA1c was not associated with the five outcomes (β ranged from − 0.012 to 0.075). Conclusions Our results showed that T1D and T2D have different effects on BMD at the genetic level. BMD decreased in patients with T1D and increased in those with T2D. These findings highlight the complex interplay between diabetes and bone health, suggesting potential age-specific effects and genetic influences. To better understand the mechanisms of bone metabolism in patients with diabetes, further longitudinal studies are required to explain BMD changes in different types of diabetes.

Abstract Background Gliomas are recognized as the most frequent type of malignancies in the central nervous system, and efficacious prognostic indicators are essential to treat patients with gliomas and improve their clinical outcomes. The chemokine (C‐C motif) ligand 2 (CCL2) is a promising predictor for glioma malignancy and progression. However, at present, the methods to evaluate CCL2 expression level are invasive and operator‐dependent. Objective It was expected to noninvasively predict CCL2 expression levels in malignant glioma tissues by magnetic resonance imaging (MRI)‐based radiomics and assess the association between the developed radiomics model and prognostic indicators and related genes. Methods MRI‐based radiomics was used to predict CCL2 expression level using data obtained from The Cancer Imaging Archive (TCIA) and The Cancer Genome Atlas (TCGA) databases. A support vector machine (SVM)‐based radiomics model and a logistic regression (LR)‐based radiomics model were used to predict the radiomics score, and its correlation with CCL2 expression level was analyzed. Results The results revealed that there was an association between CCL2 expression level and the overall survival of cases with gliomas, and bioinformatics correlation analysis showed that CCL2 expression level was highly correlated with disease‐related pathways, such as mTOR signaling pathway, cGMP‐PKG signaling pathway, and MAPK signaling pathway. Both SVM‐ and LR‐based radiomics data robustly predicted CCL2 expression level, and radiomics scores could also be used to predict the overall survival of patients. Moreover, the high/low radiomics scores were highly correlated with the known glioma‐related genes, including CD70, CD27, and PDCD1. Conclusion An MRI‐based radiomics model was successfully developed, and its clinical benefits were confirmed, including the prediction of CCL2 expression level and patients' prognosis.

In recent years, the consortium, composed of the design enterprise, construction enterprise, and supplier, has witnessed rapid development in implementing the EPC project model in China. However, there are conflicts of interest and ambiguous safety management among EPC consortium members, leading to accidents. This study aims to explore the decision-making process regarding different safety behavior strategies among EPC consortium members. Given the uncertainty of the EPC project environment, consortium members show risk preferences and perceptual biases. Prospect theory reveals the irrational elements in the decision-making process. Therefore, this study incorporates prospect theory, constructs a safety behavior perception payoff matrix and an evolutionary game model involving design enterprise, construction enterprise, and supplier as the primary stakeholders, analyzes the interactive mechanisms of safety behavior among the three parties, and uses MATLAB simulation to explain the evolutionary path of behavioral strategies under varying parameters. The consequence indicates that the optimal strategy’s stable state in the safety behavior evolution system of EPC consortium members is affected by the players’ cognitive biases and risk preferences, and the costs of safety input, punishment intensity, and accident losses. This study mainly provides theoretical evidence and decision support for safety control activities among EPC consortium members.

Abstract As museums continue to play an increasingly significant role in the preservation, innovation, and dissemination of cultural heritages, the products sold in their souvenir shops have become a vital carrier of cultural and creative industries. The creativity of these products has drawn intensive attention from various industries. However, the evaluation of museum products’ creativity still lacks objectivity, scientific rigour, and systematisation. This study aims to construct a contextual and comprehensive measurement model to evaluate the creativity of products purchased in souvenir shops affiliated with urban historical museums in China. Based on the literature, ten related hypotheses were introduced, and a conceptual model was illustrated. Six relevant dimensions and 28 corresponding indicators were identified, and then a 7-point Likert-styled questionnaire was developed. An online survey was conducted, which invited 931 participants to take part. Among them, 708 responses are valid (rate 76.05%). The overall reliability of the survey is 0.96 (Cronbach’s α). Then, exploratory factor analysis, confirmatory factor analysis and a structural equation modelling analysis using SPSS and SmartPLS were conducted. The results supported most hypotheses proposed by this study and confirmed the validity of the museum product creativity measurement (MPCM). The validated instrument comprises five dimensions: Affect, Usefulness, Aesthetics, Cultural Values and Novelty, with a total of 21 indicators. Additionally, the findings revealed that Aesthetics mediates Affect, and Cultural Values mediate Usefulness. Moreover, a negative moderating effect of Educational Level on the perception of Cultural Values was detected.

Spectral efficiency (SE) and energy efficiency (EE) are two main metrics for the transmit design in Visible Light Communications (VLC). However, the SE-optimal and EE-optimal strategies may be in conflict with each other to some extent. In this paper, we investigate the the tradeoff between EE and SE in rate splitting multiple access (RSMA)-aided VLC systems to maximize the system resource efficiency (RE) taking both perfect and imperfect channel state information (CSI) into consideration. For the scenarios with perfect CSI, we explore the joint precoding design and common rate allocation to maximize the RE of RSMA-aided VLC systems under the constraints of quality of service (QoS) and linear operation region (LoR) of LED, and propose a primal-dual-gradient-based precoding strategy. Furthermore, in the presence of CSI estimation errors, we propose a worst-case robust precoding design by exploiting quadratic transform and $\mathcal {S}$-Procedure. Numerical results indicate that the proposed resource efficient RSMA algorithm achieves the tradeoff between EE and SE.

Abstract Background Single nucleotide polymorphisms (SNPs) in the nucleotide-binding domain leucine-rich repeat protein-3 (NLRP3) gene are reported to be linked to many inflammatory disorders. However, uncertainty persists over the associations between these SNPs and susceptibilities to chronic osteomyelitis (COM). This study aimed to investigate potential relationships between NLRP3 gene SNPs and the risks of developing COM in a Chinese Han cohort. Methods The four tag SNPs of the NLRP3 gene were genotyped in a total of 428 COM patients and 368 healthy controlsusing the SNapShot technique. The genotype distribution, mutant allele frequency, and the four genetic models (dominant, recessive, homozygous, and heterozygous) of the four SNPs were compared between the two groups. Results A significant association was found between rs10754558 polymorphism and the probability of COM occurence by the heterozygous model (P = 0.037, odds ratio [OR] = 1.541, 95% confidence interval [CI] = 1.025–2.319), indicating that rs10754558 may be associated with a higher risk of developing COM.In addition, possible relationship was found between rs7525979 polymorphism and the risk of COM development by the outcomes of homozygous (P = 0.073, OR = 0.453, 95% CI = 0.187–1.097) and recessive (P = 0.093, OR = 0.478, 95% CI = 0.198–1.151) models, though no statistical differences were obtained. Conclusions Outcomes of the present study showed, for the first time, that rs10754558 polymorphism of the NLRP3 gene may increase the risk of COM development in this Chinese Han population, with genotype CG as a risk factor. Nonetheless, this conclusion requires verification from further studies with a larger sample size.

IntroductionPathogens causing diabetic foot infections (DFIs) vary by region globally; however, knowledge of the causative organism is essential for effective empirical treatment. We aimed to determine the incidence and antibiotic susceptibility of DFI pathogens worldwide, focusing on Asia and China.MethodsThrough a comprehensive literature search, we identified published studies on organisms isolated from DFI wounds from January 2000 to December 2020.ResultsBased on our inclusion criteria, we analyzed 245 studies that cumulatively reported 38,744 patients and 41,427 isolated microorganisms. DFI pathogens varied according to time and region. Over time, the incidence of Gram-positive and Gram-negative aerobic bacteria have decreased and increased, respectively. America and Asia have the highest (62.74%) and lowest (44.82%) incidence of Gram-negative bacteria, respectively. Africa has the highest incidence (26.90%) of methicillin-resistant Staphylococcus aureus. Asia has the highest incidence (49.36%) of Gram-negative aerobic bacteria with species infection rates as follows: Escherichia coli, 10.77%; Enterobacter spp., 3.95%; and Pseudomonas aeruginosa, 11.08%, with higher local rates in China and Southeast Asia. Linezolid, vancomycin, and teicoplanin were the most active agents against Gram-positive aerobes, while imipenem and cefoperazone-sulbactam were the most active agents against Gram-negative aerobes.DiscussionThis systematic review showed that over 20 years, the pathogens causing DFIs varied considerably over time and region. This data may inform local clinical guidelines on empirical antibiotic therapy for DFI in China and globally. Regular large-scale epidemiological studies are necessary to identify trends in DFI pathogenic bacteria.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/, identifier CRD42023447645.

Abstract There are several overlapping clinical practice guidelines in acute pancreatitis (AP), however, none of them contains suggestions on patient discharge. The Hungarian Pancreatic Study Group (HPSG) has recently developed a laboratory data and symptom-based discharge protocol which needs to be validated. (1) A survey was conducted involving all members of the International Association of Pancreatology (IAP) to understand the characteristics of international discharge protocols. (2) We investigated the safety and effectiveness of the HPSG-discharge protocol. According to our international survey, 87.5% (49/56) of the centres had no discharge protocol. Patients discharged based on protocols have a significantly shorter median length of hospitalization (LOH) (7 (5;10) days vs. 8 (5;12) days) p

Abstract This paper presents a linear-nonlinear switching control strategy, called Switching Active Disturbance Rejection Control (SADRC), to enhance the disturbance rejection capability of the speed controller in a servo system. SADRC combines the advantages of Linear Active Disturbance Rejection Control (LADRC) and Nonlinear Active Disturbance Rejection Control (NLADRC), and introduces a parameter to switch between nonlinear and linear control, thereby improving the robustness of the servo system. Firstly, the mathematical model of the motor is analyzed as the starting point of the paper. Then, the basic principles of Active Disturbance Rejection Control (ADRC) are analyzed, and improvements are made to address its limitations, resulting in the design of SADRC. The parameters introduced in SADRC are analyzed to determine their appropriate ranges. Finally, the performance of SADRC is validated by comparing the rotational effects of Permanent Magnet Synchronous Motor (PMSM).

Reservoirs are a hotspot for methane emissions, a potent greenhouse gas. However, the microbial basis for methane production in the Qinghai Plateau reservoirs remains unclear. To explore the characteristics of methanogenic communities in reservoir sediments on the northeastern Qinghai Plateau, sediment samples were collected from 18 reservoirs in the Yellow River basin during May 2023 (dry season) and August 2023 (wet season). High-throughput sequencing technology was employed to analyze the community composition, diversity, and co-occurrence network of methanogens. Furthermore, FAPROTAX and Mantel analysis were used to assess the metabolic functions of methanogens and their influencing factors. The results showed that (1) the predominant genera of methanogens were Methanobacterium (28.87%) and Methanosarcina (21.67%). Hydrogenotrophic methanogenesis was the main pathway in the sediments. (2) Significant spatiotemporal differences were observed in the diversity of methanogenic communities (p < 0.05). The composition and diversity of these communities were found to be significantly influenced by temperature, pH, altitude, organic carbon, and total nitrogen (p < 0.05). (3) Methanosarcina, Methanobacterium, and Methanospirillum play crucial roles in maintaining the stability of methanogenic community networks. The co-occurrence network nodes are predominantly positively correlated (99.82%). These results provide data for further studies on carbon cycling in the Qinghai Plateau reservoirs.

PurposeTo develop and validate a deep learning radiomics (DLR) model that uses X-ray images to predict the classification of osteoporotic vertebral fractures (OVFs).Material and methodsThe study encompassed a cohort of 942 patients, involving examinations of 1076 vertebrae through X-ray, CT, and MRI across three distinct hospitals. The OVFs were categorized as class 0, 1, or 2 based on the Assessment System of Thoracolumbar Osteoporotic Fracture. The dataset was divided randomly into four distinct subsets: a training set comprising 712 samples, an internal validation set with 178 samples, an external validation set containing 111 samples, and a prospective validation set consisting of 75 samples. The ResNet-50 architectural model was used to implement deep transfer learning (DTL), undergoing -pre-training separately on the RadImageNet and ImageNet datasets. Features from DTL and radiomics were extracted and integrated using X-ray images. The optimal fusion feature model was identified through least absolute shrinkage and selection operator logistic regression. Evaluation of the predictive capabilities for OVFs classification involved eight machine learning models, assessed through receiver operating characteristic curves employing the “One-vs-Rest” strategy. The Delong test was applied to compare the predictive performance of the superior RadImageNet model against the ImageNet model.ResultsFollowing pre-training separately on RadImageNet and ImageNet datasets, feature selection and fusion yielded 17 and 12 fusion features, respectively. Logistic regression emerged as the optimal machine learning algorithm for both DLR models. Across the training set, internal validation set, external validation set, and prospective validation set, the macro-average Area Under the Curve (AUC) based on the RadImageNet dataset surpassed those based on the ImageNet dataset, with statistically significant differences observed (P

Sound diffusion performance is considered as an important issue in building acoustics. A well-diffused sound field can effectively enhance the human listening experience. In this context, inspired by Fresnel lenses in optics, we design a sub-wavelength acoustic metasurface (termed “Fresnel acoustic reflector”) to achieve broadband uniform diffuse reflections. To this end, an optimization strategy that combines Monte-Carlo search and other derivative-free algorithms is proposed to ensure, as far as possible, a global optimum for the objective function when dealing with the multi-peak problem encountered in complex sound fields. Numerical simulations show that the average normalized diffusion coefficient of the designed Fresnel reflector can reach up to 0.6 in the sub-wavelength frequency range 500–3400 Hz, which exhibits a better broadband diffusion performance compared to the traditional Schroeder diffusers. The simulated sound pressure field is also verified by experimental measurements. From a general perspective, the proposed optimization strategy and simulation framework can benefit the design of interior components in building acoustics.

Abstract Background The impact of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) infection on postoperative recovery of non‐small cell lung cancer (NSCLC) is need to be understood, thereby informing the optimal timing of surgical decision‐making during the COVID‐19 pandemic for NSCLC patients. This study reports the postoperative outcomes of surgical NSCLC patients with preoperative SARS‐CoV‐2 infection. Method This single‐center retrospective cohort study included 241 NSCLC patients who underwent lobectomy or sub‐lobectomy between December 1, 2022 and February 14, 2023. Surgical outcomes of patients with preoperative SARS‐CoV‐2 infection (stratified by the time from diagnosis of SARS‐CoV‐2 infection to surgery) were compared with those without preoperative SARS‐CoV‐2 infection. The primary outcomes were total postoperative complications and postoperative pulmonary complications (PPCs), the secondary outcomes included operation time, total postoperative drainage and time, length of hospital stay (LOS), 30‐day and 90‐day postoperative symptoms. Results This study included 153 (63.5%) patients with preoperative SARS‐CoV‐2 infection and 88 (36.5%) patients without previous SARS‐CoV‐2 infection. In patients with a preoperative SARS‐CoV‐2 diagnosis, the incidence of total postoperative complications (OR, 3.00; 95% CI, 1.12–8.01; p = 0.028) and PPCs (OR, 4.20; 95% CI, 1.11–15.91; p = 0.035) both increased in patients infected having surgery within 2 weeks compared with non‐infection before surgery. However, patients who underwent lung resection more than 2 weeks after SARS‐CoV‐2 diagnosis had a similar risk of postoperative complications and surgical outcomes with those non‐infection before surgery. Conclusion This is the first study to provide evidence regarding the optimum timing of lung resection surgery and assessing early outcomes after surgery in NSCLC patients with SARS‐CoV‐2 infection. Our study documents that the SARS‐CoV‐2 infection did not complicate surgical procedures for lung cancer, and suggest that lung surgery should be postponed at least 2 weeks after SARS‐CoV‐2 infection for NSCLC patients.

Diffuse midline glioma with H3K27 M alteration is a primary malignant tumor located along the linear structure of the brain, predominantly manifesting in children and adolescents. The mortality rate is exceptionally high, with a mere 1 % 5-year survival rate for newly diagnosed patients. Beyond conventional surgery, radiotherapy, and chemotherapy, novel approaches are imperative to enhance patient prognosis. This article comprehensively reviews current innovative treatment modalities and provides updates on the latest research advancements in preclinical studies and clinical trials focusing on H3K27M-altered diffuse midline glioma. The goal is to contribute positively to clinical treatment strategies.