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The collision and friction between the rock masses during the caving of the gob roof has become an important hidden danger to induce the gas explosion accident in the gob. In order to study the mechanism of gas explosion induced by sandstone friction by friction velocity, friction force, gas concentration, SiO2 content and other factors, the rock friction effect igniting gas test system was used to conduct quantitative test research on each factor. The results show that when the gas concentration is 7.0%-11.5%, the gas explosion time induced by sandstone friction first decreases and then increases with the increase of gas concentration. The high friction and hot surface of sandstone is the main cause of gas explosion. Gas explosion induced by friction can be divided into two stages: gas burning on sandstone friction surface and gas explosion diffusion. The time of gas explosion induced by friction decreases with the increase of friction and the increase of SiO2 content in sandstone. When the friction is lower than the minimum critical velocity, the gas explosion will not be induced. When the friction is higher than the minimum critical velocity and lower than the maximum critical velocity, the maximum friction velocity is negatively correlated with the gas explosion time.

Abstract Background Diffusion kurtosis imaging (DKI) and neurite orientation dispersion and density imaging (NODDI) provide more comprehensive and informative perspective on microstructural alterations of cerebral white matter (WM) than single-shell diffusion tensor imaging (DTI), especially in the detection of crossing fiber. However, studies on systemic lupus erythematosus patients without neuropsychiatric symptoms (non-NPSLE patients) using multi-shell diffusion imaging remain scarce. Methods Totally 49 non-NPSLE patients and 41 age-, sex-, and education-matched healthy controls underwent multi-shell diffusion magnetic resonance imaging. Totally 10 diffusion metrics based on DKI (fractional anisotropy, mean diffusivity, axial diffusivity, radial diffusivity, mean kurtosis, axial kurtosis and radial kurtosis) and NODDI (neurite density index, orientation dispersion index and volume fraction of the isotropic diffusion compartment) were evaluated. Tract-based spatial statistics (TBSS) and atlas-based region-of-interest (ROI) analyses were performed to determine group differences in brain WM microstructure. The associations of multi-shell diffusion metrics with clinical indicators were determined for further investigation. Results TBSS analysis revealed reduced FA, AD and RK and increased ODI in the WM of non-NPSLE patients (P

Abstract Background Balloon pulmonary angioplasty (BPA) improves the prognosis of chronic thromboembolic pulmonary hypertension (CTEPH). Right ventricle (RV) is an important predictor of prognosis in CTEPH patients. 2D-speckle tracking echocardiography (2D-STE) can evaluate RV function. This study aimed to evaluate the effectiveness of BPA in CTEPH patients and to assess the value of 2D-STE in predicting outcomes of BPA. Methods A total of 76 patients with CTEPH underwent 354 BPA sessions from January 2017 to October 2022. Responders were defined as those with mean pulmonary artery pressure (mPAP) ≤ 30 mmHg or those showing ≥ 30% decrease in pulmonary vascular resistance (PVR) after the last BPA session, compared to baseline. Logistic regression analysis was performed to identify predictors of BPA efficacy. Results BPA resulted in a significant decrease in mPAP (from 50.8 ± 10.4 mmHg to 35.5 ± 11.9 mmHg, p

BackgroundCardiovascular complications are the leading cause of death among individuals with Duchenne muscular dystrophy (DMD). However, due to the difficulty in evaluating individuals with inactive DMD, acute myocardial injury may be overlooked.Case presentationAn 11-year-old boy with DMD presented to the emergency department with a 5-day history of persistent nasal congestion, runny nose, and cough. He was regularly taking prednisolone acetate, angiotensin-converting enzyme (ACE) inhibitors, and β-blockers for suspected DMD-associated cardiomyopathy. Upon presentation, a substantially elevated cardiac troponin I (cTnI) level of 19.8 μg/L and abnormal electrocardiogram (ECG) results were detected. Further cardiac magnetic resonance imaging (CMR) showed myocardial inflammation with localized T2 hyperintensity from the basal to middle lateral and inferior walls, as well as late gadolinium enhancement (LGE) from the basal to apical inferior lateral walls, supporting a diagnosis of acute myocarditis. Subsequently, the patient showed clinical improvement in response to combination treatment with intravenous immunoglobulin, oral prednisolone acetate, potassium chloride sustained-release tablets, anti-heart failure medication, and broad-spectrum antibiotics.ConclusionsWe report a rare case of acute myocarditis in a patient with DMD, potentially due to upper respiratory tract infection. This case highlights the importance of early myocarditis recognition and treatment in patients with DMD.

BackgroundPrevious study has indicated a potential link between gut microbiota and maternal pregnancy outcomes. However, the causal relationship between gut microbiota and premature rupture of membranes (PROM) remains a topic of ongoing debate.MethodsA two-sample Mendelian Randomization (MR) study was used to investigate the relationship between gut microbiota and PROM. Genetic data on gut microbiota was obtained from the MiBioGen consortium’s largest genome-wide association study (GWAS) (n=14,306). Genetic data on PROM (3011 cases and 104247 controls) were sourced from publicly available GWAS data from the Finnish National Biobank FinnGen consortium. Various methods including Inverse variance weighted (IVW), MR-Egger, simple mode, weighted median, and weighted mode were utilized to assess the causal relationship by calculating the odd ratio (OR) value and confidence interval (CI). Sensitivity analyses for quality control were performed using MR-Egger intercept tests, Cochran’s Q tests, and leave-one-out analyses.ResultsThe IVW method revealed that class Mollicutes (IVW, OR=0.773, 95%CI: 0.61-0.981, pval = 0.034), genus Marvinbryantia (IVW, OR=00.736, 95%CI: 0.555-0.977, pval = 0.034), genus Ruminooccaceae UCG003 (IVW, OR=0.734, 95%CI: 0.568-0.947, pval = 0.017) and phylum Tenericutes (IVW, OR=0.773, 95%CI: 0.566-1.067, pval = 0.034) were associated with a reduced risk of PROM, while genus Collinsella (IVW, OR=1.444, 95%CI: 1.028-2.026, pval = 0.034), genus Intestinibacter (IVW, OR=1.304, 95%CI: 1.047-1.623, pval = 0.018) and genus Turicibacter (IVW, OR=1.282, 95%CI: 1.02-1.611, pval = 0.033) increased the risk of PROM. Based on the other four supplementary methods, six gut microbiota may have a potential effect on PROM. Due to the presence of pleiotropy (pval=0.045), genus Lachnoclostridium should be ruled out. No evidence of horizontal pleiotropy or heterogeneity was found in other microbiota (pval >0.05).ConclusionsIn this study, we have discovered a causal relationship between the presence of specific probiotics and pathogens in the host and the risk of PROM. The identification of specific gut microbiota associated with PROM through MR studies offers a novel approach to diagnosing and treating this condition, thereby providing a new strategy for clinically preventing PROM.

Background: Yinqiaosan decoction (YQSD), a traditional Chinese medicinal recipe, has been employed to treat influenza in China for approximately 300 years. Objective: Our study aimed to explore the mechanisms of YQSD against influenza via in vivo and in vitro experimental studies. Study design: and methods UHPLC-Q-TOF-MS/MS was utilized to examine the substances of the YQSD. The chemical components of YQSD detected by UHPLC-Q-TOF-MS/MS were used for network pharmacology analysis. The antiviral effect of YQSD in vivo was investigated. The potential mechanisms of YQSD in combating influenza, which were predicted from network pharmacology analysis, were validated in vitro. Results: By use of UHPLC-Q-TOF-MS/MS, 97 compounds were identified from YQSD. Network pharmacology analysis revealed that the therapeutic effect of YQSD against influenza may be associated with the regulation of T cell receptors (TCR) and Phosphoinositide 3-Kinase (PI3K)- protein kinase B (Akt) signaling pathways. Treatment with YQSD significantly prolonged the mean survival time of the mice and reduced lung injury due to the influenza A virus in vivo. It was discovered that YQSD efficiently inhibited the expression of inflammation-related cytokines. Moreover, YQSD has been found to significantly reduce the expression levels of cluster of differentiation 3 (CD3), monocyte chemoattractant protein-1 (MCP-1), and H1N1 virus nucleoprotein (NP), and prevent the decrease of epithelial cadherin (E-cadherin) protein. In addition, YQSD can inhibit the phosphorylation of the zeta chain of T cell receptor-associated protein kinase 70 (ZAP70) and PI3K proteins in vitro. Conclusion: The capacity of YQSD to suppress viral multiplication and inflammatory response by modulating T cell immunity may explain its effect against influenza viral pneumonia, which may involve the regulation of TCR and PI3K signaling pathways.

Artificial intelligence for graph‐structured data has achieved remarkable success in applications such as recommendation systems, social networks, drug discovery, and circuit annotation. Graph convolutional networks (GCNs) are an effective way to learn representations of various graphs. The increasing size and complexity of graphs call for in‐memory computing (IMC) accelerators for GCN to alleviate massive data transmission between off‐chip memory and processing units. However, GCN implementation with IMC is challenging because of the large memory consumption, irregular memory access, and device nonidealities. Herein, a fully binarized GCN (BGCN) accelerator based on computational resistive random‐access memory (RRAM) through software–hardware codesign is presented. The essential operations including aggregation and combination in GCN are implemented on the RRAM crossbar arrays with cooperation between multiply‐and‐accumulation and content‐addressable memory operations. By leveraging the model quantization and IMC on the RRAM, the BGCN accelerator demonstrates less RRAM usage, high robustness to the device variations, high energy efficiency, and comparable classification accuracy compared to the current state‐of‐the‐art GCN accelerators on both graph classification task using the MUTAG and PTC datasets and node classification task using the Cora and CiteSeer datasets. These results provide a promising approach for edge intelligent systems to efficiently process graph‐structured data.

Abstract Combinatorial optimization (CO) has a broad range of applications in various fields, including operations research, computer science, and artificial intelligence. However, many of these problems are classified as nondeterministic polynomial‐time (NP)‐complete or NP‐hard problems, which are known for their computational complexity and cannot be solved in polynomial time on traditional digital computers. To address this challenge, continuous‐time Ising machine solvers have been developed, utilizing different physical principles to map CO problems to ground state finding. However, most Ising machine prototypes operate at speeds comparable to digital hardware and rely on binarizing node states, resulting in increased system complexity and further limiting operating speed. To tackle these issues, a novel device‐algorithm co‐design method is proposed for fast sub‐optimal solution finding with low hardware complexity. On the device side, a piezoelectric lithium niobate (LiNbO3) microelectromechanical system (MEMS) oscillator network‐based Ising machine without second‐harmonic injection locking (SHIL) is devised to solve Max‐cut and graph coloring problems. The LiNbO3 oscillator operates at speeds greater than 9 GHz, making it one of the fastest oscillatory Ising machines. System‐wise, an innovative grouping method is used that achieves a performance guarantee of 0.878 for Max‐cut and 0.658 for graph coloring problems, which is comparable to Ising machines that utilize binarization.

Endoscopic tattooing plays a pivotal role in modern endoscopic localization of gastrointestinal lesions, facilitating further surgical intervention and aiding in the postoperative identification and repositioning of lesions. However, traditional endoscopic tattoo dyes often suffer from drawbacks such as side effects, short tattoo duration, and high overall costs. In this study, we developed polyvinylpyrrolidone (PVP)-modified polypyrrole (PPy) nanoparticles by oxidizing pyrrole in a PVP aqueous solution to create a PPy/PVP nanoparticle solution. This innovation aims to enhance endoscopic tattooing efficiency and mitigate the limitations associated with current tattooing methods. Both in vitro and in vivo evaluations confirmed the biosafety of PPy/PVP nanoparticles. Endoscopic tattooing experiments conducted in a pig model demonstrated the dye’s stability within the digestive tract. Similarly, subcutaneous tissue tattooing experiments performed in a mouse model revealed the sustained stability of the PPy/PVP tattoo dye for at least 180 days. With its robust stability, safety, and longevity, PPy/PVP nanoparticles hold promise as novel tattoo dyes for marking intestinal lesion sites. This advancement has the potential to enhance the accuracy of lesion localization and long-term tracking.

Background: High mobility group box 2 (HMGB2) is considered as a biomarker of poor prognosis in various cancers.This study aims to investigate the effect and mechanism of HMGB2 in gliomas. Methods: With the glioma related on-line and our local hospital databases, the expression differences of HMGB2,Kaplan-Meier survival analysis and COX regression analysis were performed.The correlation analysis between the clinicopathological features and imaging parameters with the HMGB2 expression had been done. Then GSEA and PPI networks were carried out to find out the most significant pathway. The pathway inhibitor was applied to verify HMGB2’s participation. CCK8,EDU assays,γ-H2AX immunofluorescence staining and colony formation assay were conducted to observe effects on glioma cells. Results: Available datasets showed that HMGB2 was highly expressed in glioma and patients with high expression of HMGB2 had poorer prognosis and molecular characteristics. Protein level evidence of western blot and immunohistochemistry from our center supported the conclusions above. Analysis on imaging features suggested that HMGB2 expression level had an inverse association with ADCmean but positively with the thickness of enhancing margin. Results from GSEA and PPI network analysis exhibited that HMGB2 was involved in base excision repair (BER) signaling pathway. Experimental evidence demonstrated that the overexpression of HMGB2 promoted the proliferation of glioma cells and enhanced the radio-resistance. Conclusions: HMGB2 could promote glioma development and enhance the radioresistance of glioma cells, potentially related to the BER pathway, suggesting it may serve as an underlying biomarker for patients with glioma.

Abstract Background In this era of big data, data harmonization is an important step to ensure reproducible, scalable, and collaborative research. Thus, terminology mapping is a necessary step to harmonize heterogeneous data. Take the Medical Dictionary for Regulatory Activities (MedDRA) and International Classification of Diseases (ICD) for example, the mapping between them is essential for drug safety and pharmacovigilance research. Our main objective is to provide a quantitative and qualitative analysis of the mapping status between MedDRA and ICD. We focus on evaluating the current mapping status between MedDRA and ICD through the Unified Medical Language System (UMLS) and Observational Medical Outcomes Partnership Common Data Model (OMOP CDM). We summarized the current mapping statistics and evaluated the quality of the current MedDRA-ICD mapping; for unmapped terms, we used our self-developed algorithm to rank the best possible mapping candidates for additional mapping coverage. Results The identified MedDRA-ICD mapped pairs cover 27.23% of the overall MedDRA preferred terms (PT). The systematic quality analysis demonstrated that, among the mapped pairs provided by UMLS, only 51.44% are considered an exact match. For the 2400 sampled unmapped terms, 56 of the 2400 MedDRA Preferred Terms (PT) could have exact match terms from ICD. Conclusion Some of the mapped pairs between MedDRA and ICD are not exact matches due to differences in granularity and focus. For 72% of the unmapped PT terms, the identified exact match pairs illustrate the possibility of identifying additional mapped pairs. Referring to its own mapping standard, some of the unmapped terms should qualify for the expansion of MedDRA to ICD mapping in UMLS.

Oxidative stress and metabolic disorders are involved in the pathogenesis of polycystic ovary syndrome (PCOS). Heme oxygenase 2 (HMOX2) plays a critical role in preserving heme metabolism as well as in modulating glycolipid metabolism, oxidative stress, and inflammation. This study examined the correlation between HMOX2 G554A (rs1051308) and A-42G (rs2270363) genetic variants with the risk of PCOS and assessed the effects of these genotypes on clinical, hormonal, metabolic, and oxidative stress indices using a case–control design that included 1014 patients with PCOS and 806 control participants. We found that the allelic and genotypic frequencies of the HMOX2 G554A and A-42G polymorphisms were comparable between the PCOS and control groups in Chinese women (P > 0.05). Nevertheless, it was discovered that patients with the AA or AG genotype of A-42G polymorphism had notably elevated levels of estradiol (E2), follicle-stimulating hormone (FSH), luteinizing hormone (LH), LH/FSH ratio, high-density lipoprotein cholesterol (HDL-C), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), apolipoprotein (apo)B, and/or apoB/apoA1 ratio than those with the GG genotypes (P < 0.05). Patients with the GG or AG genotype of G554A polymorphism had elevated serum levels of LH, FSH, E2, LH/FSH ratio, TC, HDL-C, LDL-C, apoB, and/or apoB/apoA1 ratio and lower 2-h glucose concentration compared with those with the AA genotype (P < 0.05). Our findings indicate a potential association between the genetic variants and endocrine abnormalities in the reproductive system and metabolic irregularities in glycolipid levels in patients, thus suggesting their potential role in the pathogenesis of PCOS.

Dopaminergic treatment has proved effective to Parkinson’s disease (PD), but the conventional treatment assessment is human-administered and prone to intra- and inter-assessor variability. In this paper, we propose a knowledge-driven framework and discover that brain ACtivation-Transition-Spectrum (ACTS) features achieve effective quantified assessments of dopaminergic therapy in PD. Firstly, brain activities of fifty-one PD patients during clinical walking tests under the OFF and ON states (without and with dopaminergic medication) were measured with functional near-infrared spectroscopy (fNIRS). Then, brain ACTS features were formulated based on the medication-induced variations in temporal features of brain regional activation, transition features of brain hemodynamic states, and graph spectrum of brain functional connectivity. Afterwards, a prior selection algorithm was constructed based on recursive feature elimination and graph spectrum analysis for the selection of principal discriminative features. Further, linear discriminant analysis was conducted to predict the treatment-induced improvements. The results demonstrated that the proposed method decreased the misclassification probability from 42% to 16% in the evaluations of dopaminergic treatment and outperformed existing fNIRS-based methods. Therefore, the proposed method promises a quantified and objective approach for dopaminergic treatment assessment, and our brain ACTS features may serve as promising functional biomarkers for treatment evaluation.

Deep brain stimulation (DBS) is establishing itself as a promising treatment for disorders of consciousness (DOC). Measuring consciousness changes is crucial in the optimization of DBS therapy for DOC patients. However, conventional measures use subjective metrics that limit the investigations of treatment-induced neural improvements. The focus of this study is to analyze the regulatory effects of DBS and explain the regulatory mechanism at the brain functional level for DOC patients. Specifically, this paper proposed a dynamic brain temporal-spectral analysis method to quantify DBS-induced brain functional variations in DOC patients. Functional near-infrared spectroscopy (fNIRS) that promised to evaluate consciousness levels was used to monitor brain variations of DOC patients. Specifically, a fNIRS-based experimental procedure with auditory stimuli was developed, and the brain activities during the procedure from thirteen DOC patients before and after the DBS treatment were recorded. Then, dynamic brain functional networks were formulated with a sliding-window correlation analysis of phase lag index. Afterwards, with respect to the temporal variations of global and regional networks, the variability of global efficiency, local efficiency, and clustering coefficient were extracted. Further, dynamic networks were converted into spectral representations by graph Fourier transform, and graph energy and diversity were formulated to assess the spectral global and regional variability. The results showed that DOC patients under DBS treatment exhibited increased global and regional functional variability that was significantly associated with consciousness improvements. Moreover, the functional variability in the right brain regions had a stronger correlation with consciousness enhancements than that in the left brain regions. Therefore, the proposed method well signifies DBS-induced brain functional variations in DOC patients, and the functional variability may serve as promising biomarkers for consciousness evaluations in DOC patients.

ABSTRACTPersistent human papillomavirus HPV infection is a necessary but insufficient condition for cervical cancer. Microorganisms are crucial environmental factors in cancers susceptibility and progression, recently attracting considerable attention. This study aimed to determine the infection status and relationship between high-risk HPV (HR-HPV) and lower genital tract infectious pathogens in cervical cancer and its precursors. From a retrospective and a prospective cohort analysis, Escherichia coli (E. coli) dominated the pathogens isolated from cervical discharges, and an isolation rate uptrend has been shown recently. HPV16 and E. coli’s coinfection rate gradually increased with the severity of cervical intraepithelial neoplasia. The adhesion and invasion abilities of the isolated E. coli to HPV16-positive SiHa cells were evaluated in vitro. The TCGA database and cervical tissues samples analysis showed that IL-10 was upregulated in cervical cancer. IL-10 expression levels increased in tissue samples with the severity of cervical cancer and its precursors with HPV16 and E. coli coinfection. Although no significant changes in IL-10 production were observed in the co-culture supernatant, we hypothesized that Treg immune cells in the tumour microenvironment might be responsible for the local IL-10 upregulation, according to our data showing Foxp3 upregulation and an upward trend with the cervical intraepithelial neoplasia grading to cancer and tumours with E. coli and HPV16 coinfection. Our data provide insights into the possible role of E. coli in cervical cancer progression and suggest that the application of HPV and E. coli screening programs may be an effective strategy to relieve the burden of cervical cancer and its precursor lesions.

AimsThis study aims to investigate the effects of coronary collateral circulation (CCC) on the prognosis of chronic total occlusion (CTO) patients with or without metabolic syndrome (MetS).MethodsThe study included 342 CTO patients who underwent successful percutaneous coronary intervention at the People's Hospital of Liaoning Province between 1 February 2021 and 30 September 2023. The Rentrop score was used to assess the status of CCC. The outcome was major adverse cardiovascular and cerebrovascular events (MACCEs), defined as a composite of all-cause mortality, cardiac death, non-fatal myocardial infarction (MI), target vessel revascularization (TVR), and non-fatal stroke. Univariate and multivariate logistic analyses were used to investigate the association of CCC, MetS, and MACCEs with odds ratios (ORs) and 95% confidence intervals (CIs). The effect of CCC was further investigated in different MetS, diabetes mellitus (DM), and Syntax score groups.ResultsMACCEs were more common in patients with poor CCC compared to those with good CCC (38.74% vs. 16.56%). Statistical differences were found in MACCEs (OR = 3.33, 95% CI: 1.93–5.72), MI (OR = 3.11, 95% CI: 1.73–5.58), TVR (OR = 3.06, 95% CI: 1.70–5.53), and stent thrombosis (OR = 6.14, 95% CI: 2.76–13.65) between the good and poor CCC groups. Poor CCC patients with MetS had a higher incidence of MACCEs (OR = 4.21, 95% CI: 2.05–8.65), non-fatal MI (OR = 4.44, 95% CI: 2.01–9.83), TVR (OR = 3.28, 95% CI: 1.51–7.11), and stent thrombosis (OR = 10.80, 95% CI: 3.11–37.54). Similar findings were also observed in CTO patients with DM and a Syntax score ≥23.ConclusionPoor CCC could increase the risk of MACCEs in CTO patients, particularly those with MetS, DM, and a Syntax score ≥23. Further prospective, multicenter studies are needed to validate our findings and to explore potential therapeutic interventions.

Background: Balloon pulmonary angioplasty (BPA) is an established treatment for inoperable chronic thromboembolic pulmonary hypertension (CTEPH), but its efficacy in CTEPH patients with a pulmonary comorbidity has not been well-studied. Here, we compared post-BPA outcomes between CTEPH patients with and without chronic pulmonary disease at baseline and analyzed predictors of BPA success. Methods: From August 2017 to October 2022, 62 patients with inoperable CTEPH who underwent BPA were consecutively enrolled and grouped based on the presence of a pulmonary comorbidity at baseline. All patients underwent transthoracic echocardiography, pulmonary function tests, and right heart catheterization. Pre- and post-BPA data were evaluated to identify factors that influence the success of BPA. Results: Among the 62 CTEPH patients, BPA was considered successful in 50 patients and unsuccessful in 12 patients. Responders to BPA had better exercise capacity and right heart function at baseline, but no differences in hemodynamic or respiratory function were detected between the groups. In CTEPH patients with chronic pulmonary disease (n = 14), BPA significantly improved mean pulmonary arterial pressure, pulmonary vascular resistance and right heart function parameters. Only CTEPH patients without chronic pulmonary disease (n = 48) exhibited significant improvement in 6-minute walk distance and respiratory function. Multivariate logistic regression analysis showed that pulmonary comorbidity at baseline was independently associated with the efficacy of BPA. Conclusions: BPA provided significantly improvements in hemodynamics and right heart function in CTEPH patients, independent of pulmonary comorbidity at baseline. However, pulmonary comorbidity can negatively impact post-BPA outcomes.

Abstract Background Noninvasive and precise methods to estimate treatment response and identify hepatocellular carcinoma (HCC) patients who could benefit from transarterial chemoembolization (TACE) are urgently required. The present study aimed to investigate the ability of intratumoral and peritumoral radiomics based on contrast-enhanced magnetic resonance imaging (CE-MRI) to preoperatively predict tumor response to TACE in HCC patients. Methods A total of 138 patients with HCC who received TACE were retrospectively included and randomly divided into training and validation cohorts at a ratio of 7:3. Total 1206 radiomics features were extracted from arterial, venous, and delayed phases images. The inter- and intraclass correlation coefficients, the spearman’s rank correlation test, and the gradient boosting decision tree algorithm were used for radiomics feature selection. Radiomics models on intratumoral region (TR) and peritumoral region (PTR) (3 mm, 5 mm, and 10 mm) were established using logistic regression. Three integrated radiomics models, including intratumoral and peritumoral region (T-PTR) (3 mm), T-PTR (5 mm), and T-PTR (10 mm) models, were constructed using TR and PTR radiomics scores. A clinical-radiological model and a combined model incorporating the optimal radiomics score and selected clinical-radiological predictors were constructed, and the combined model was presented as a nomogram. The discrimination, calibration, and clinical utilities were evaluated by receiver operating characteristic curve, calibration curve, and decision curve analysis, respectively. Results The T-PTR radiomics models performed better than the TR and PTR models, and the T-PTR (3 mm) radiomics model demonstrated preferable performance with the AUCs of 0.884 (95%CI, 0.821–0.936) and 0.911 (95%CI, 0.825–0.975) in both training and validation cohorts. The T-PTR (3 mm) radiomics score, alkaline phosphatase, tumor size, and satellite nodule were fused to construct a combined nomogram. The combined nomogram [AUC: 0.910 (95%CI, 0.854–0.958) and 0.918 (95%CI, 0.831–0.986)] outperformed the clinical-radiological model [AUC: 0.789 (95%CI, 0.709–0.863) and 0.782 (95%CI, 0.660–0.902)] in the both cohorts and achieved good calibration capability and clinical utility. Conclusions CE-MRI-based intratumoral and peritumoral radiomics approach can provide an effective tool for the precise and individualized estimation of treatment response for HCC patients treated with TACE.

Microbial flocculants (MBFs), a class of eco-friendly and biodegradable biopolymers produced by various microorganisms, have gained increasing attention as promising alternatives to conventional chemical flocculants in wastewater treatment and pollutant removal. This review presents a comprehensive overview of the current state of MBF research, encompassing their diverse sources (bacteria, fungi, and algae), major categories (polysaccharides, proteins, and glycoproteins), production processes, and flocculation performance and mechanisms. The wide-ranging applications of MBFs in removing suspended solids, heavy metals, dyes, and other pollutants from industrial and municipal wastewater are critically examined, highlighting their superior efficiency, selectivity, and environmental compatibility compared to traditional flocculants. Nonetheless, bioflocculants face significant challenges including high substrate costs, low production yields, and intricate purification methodologies, factors that impede their industrial scalability. Moreover, the risk of microbial contamination and the attendant health implications associated with the use of microbial flocculants (MBFs) necessitate thorough evaluation. To address the challenges of high production costs and variable product quality, strategies such as waste valorization, strain improvement, process optimization, and biosafety evaluation are discussed. Moreover, the development of multifunctional MBF-based flocculants and their synergistic use with other treatment technologies are identified as emerging trends for enhanced wastewater treatment and resource recovery. Future research directions are outlined, emphasizing the need for in-depth mechanistic studies, advanced characterization techniques, pilot-scale demonstrations to accelerate the industrial adoption of MBF, and moreover, integration with novel wastewater treatment processes, such as partial nitrification and the anammox process. This review is intended to inspire and guide further research and development efforts aimed at unlocking the full potential of MBFs as sustainable, high-performance, and cost-effective bioflocculants for addressing the escalating challenges in wastewater management and environmental conservation.

Introduction: High concentrations of nonesterified fatty acids (NEFA) is the key of characteristic of fatty liver in dairy cows. Therefore, the aim of this study was to investigate the effect of high concentration of NEFA on lipid metabolism in hepatocytes through the lipidomic approach and molecular biology techniques.Methods: Stimulate AML-12 cells with different concentrations of NEFA, observe the cellular lipid accumulation, and select 0.6 mM NEFA stimulation concentration for subsequent experiments. Collect cells for lipidomics analysis.Results: High concentration of NEFA (0.6–2.4 mM) significantly reduced the cell viability in a concentration-dependent manner, indicating that high concentrations of NEFA have lipotoxicity on hepatocytes. In addition, NEFA promoted triglycerides (TAG) accumulation, increased the mRNA expression of the lipogenic molecules SREBP1c and FASN, and decreased the mRNA expression of lipolytic molecules CPT1A and HSL in hepatocytes. Mechanistically, high concentration of NEFA induced lipid metabolism disorders in hepatocytes by regulating metabolic pathways such as glycerol phospholipid metabolism, glycosyl phosphatidylinositol anchored biosynthesis, triglyceride metabolism, sphingolipid metabolism, and inositol phosphate metabolism.Discussion: High concentration of NEFA is lipotoxic to cells, promoting lipid accumulation. LPE (18:2), LPE (18:3), LPE (18:1) via glycerophospholipid metabolism, glycosylphosphatidylinositol (GPI)-anchor biosynthesis, glycerolipid metabolism, sphingolipid metabolism, and inositol phosphate metabolism, indicating their potential regulation role in the pathogenesis of fatty liver.

Background The rapid evolution of artificial intelligence (AI) in conjunction with recent updates in dual antiplatelet therapy (DAPT) management guidelines emphasizes the necessity for innovative models to predict ischemic or bleeding events after drug‐eluting stent implantation. Leveraging AI for dynamic prediction has the potential to revolutionize risk stratification and provide personalized decision support for DAPT management. Methods and Results We developed and validated a new AI‐based pipeline using retrospective data of drug‐eluting stent‐treated patients, sourced from the Cerner Health Facts data set (n=98 236) and Optum's de‐identified Clinformatics Data Mart Database (n=9978). The 36 months following drug‐eluting stent implantation were designated as our primary forecasting interval, further segmented into 6 sequential prediction windows. We evaluated 5 distinct AI algorithms for their precision in predicting ischemic and bleeding risks. Model discriminative accuracy was assessed using the area under the receiver operating characteristic curve, among other metrics. The weighted light gradient boosting machine stood out as the preeminent model, thus earning its place as our AI‐DAPT model. The AI‐DAPT demonstrated peak accuracy in the 30 to 36 months window, charting an area under the receiver operating characteristic curve of 90% [95% CI, 88%–92%] for ischemia and 84% [95% CI, 82%–87%] for bleeding predictions. Conclusions Our AI‐DAPT excels in formulating iterative, refined dynamic predictions by assimilating ongoing updates from patients' clinical profiles, holding value as a novel smart clinical tool to facilitate optimal DAPT duration management with high accuracy and adaptability.

Typically developing (TD) individuals can readily orient attention according to others’ eye-gaze direction, an ability known as social attention, which involves both innate and acquired components. To distinguish between these two components, we used a critical flicker fusion technique to render gaze cues invisible to participants, thereby largely reducing influences from consciously acquired strategies. Results revealed that both visible and invisible gaze cues could trigger attentional orienting in TD adults (aged 20 to 30 years) and children (aged 6 to 12 years). Intriguingly, only the ability to involuntarily respond to invisible gaze cues was negatively correlated with autistic traits among all TD participants. This ability was substantially impaired in adults with autism spectrum disorder (ASD) and in children with high autistic traits. No such association or reduction was observed with visible gaze cues. These findings provide compelling evidence for the functional demarcation of conscious and unconscious gaze-triggered attentional orienting that emerges early in life and develops into adulthood, shedding new light on the differentiation of the innate and acquired aspects of social attention. Moreover, they contribute to a comprehensive understanding of social endophenotypes of ASD.

This paper utilizes an improved undesirable output DEA model to measure the eco-efficiency of cities in five major urban agglomerations in China during 2006-2020. It employs the Theil Index and Geodetector to investigate the spatial-temporal distribution differentiation characteristics and driving factors of urban eco-efficiency. The main findings are as follows. Firstly, the eco-efficiency of all urban agglomerations showed a fluctuating upward trend, but the eco-efficiency performance of different urban agglomerations in China shows a stratification characteristic. Specifically, the Pearl River Delta urban agglomeration consistently ranks first in China, while the mean values of the Yangtze River Delta urban agglomeration, Beijing-Tianjin-Hebei urban agglomeration, and Chengdu-Chongqing urban agglomeration are lower than the national average. Secondly, the overall differences in the urban eco-efficiency of all sample cities show a consistently fluctuating downward trend. The factor that affects the level differences of eco-efficiency in different cities is the intra-regional differences. Last but not least, the top three factors affecting the spatial distribution difference of urban eco-efficiency in the whole sample are environmental pollution control investments, innovation level, and environmental infrastructure investments. In the end, this paper proposes that reducing the intra-regional differences is the primary task to achieve the coordinated improvement of urban eco-efficiency in urban agglomerations, and then puts forward some policy suggestions to improve eco-efficiency for the five major urban agglomerations.

In order to better understand the formation of thrust fault in coal measures and how it makes a difference on mining-induced disasters, a simulation system for the formation process of a new type of thrust fault in coal measures has been improved, which adopts hydraulic servo control to realize the double precise control of displacement and stress. During the coal seam mining test, only part of the transparent plate at the mining position behind the coal seam is removed to keep the internal structural stress from being released. The system is used to carry out the experimental research on the formation of thrust fault in coal measures and coal winning operation. The results indicate that the displacement of each rock stratum can be divided into three regions during the formation of thrust fault: displacement region, compression region and stability region. The maximum displacement of the measuring point is in the displacement region and the relative displacement in various measuring points is small, its extents increase with the decrease of the burial depth of rock stratum. The displacement of measuring points in the compression region gradually decreases from hanging wall to footwall, and the displacement and relative displacement in the stability region are both the smallest, and their extents decrease with the burial depth of the rock stratum. The displacement angle of hanging wall measuring point increases gradually as the measuring point approaches the fault plane, reaching a maximum of 87.5°. In the formation of thrust fault, the horizontal stress on the roof and floor increases and then decreases, and the horizontal stress on the hanging wall is greater than that at the foot wall. The vertical stress of the coal roof in the foot wall of the fault tends to increase, while the vertical stress of the coal seam roof in the hanging wall of the fault tends to present the change of increase−decrease – increase. When comparing and analyzing the in-situ stress measurements of 22 domestic thrust faults in coal measures, it suggests that the ratio of maximum horizontal principal stress to vertical principal stress is in the range of 1−4 in the tectonic zones of thrust fault. After the thrust fault is stabilized in the test, the k of the hanging wall and foot wall is stable between 2−3. After the formation of thrust fault in coal measures, in the footwall coal seam mining process, the vertical and horizontal stresses in the coal seam roof both tend to increase and then decrease. Under the superposition of tectonic stress and mining-induced stress, the rock stratum near the fault produces stress aggregation, and its peak stress is greater. The conditions mentioned above lead to more violent movement of the overlying strata after coal winning. The coal winning can be divided into the cyclic evolution stage of rock pressure and the dynamic disaster stage. In the cyclic evolution stage of rock pressure, the vertical stress of wall and working face increases significantly periodically, and the high stress area migrates to the footwall structure coal. In the dynamic disaster stage, the working face is already in high stress area, which is easy to cause coal mine dynamic disasters such as rock burst.

Abstract Background The utilization of dermoscopic analysis is becoming increasingly critical for diagnosing skin diseases by physicians and even artificial intelligence. With the expansion of dermoscopy, its vocabulary has proliferated, but the rapid evolution of the vocabulary of dermoscopy without standardized control is counterproductive. We aimed to develop a domain-specific ontology to formally represent knowledge for certain dermoscopic features. Methods The first phase involved creating a fundamental-level ontology that covers the fundamental aspects and elements in describing visualizations, such as shapes and colors. The second phase involved creating a domain ontology that harnesses the fundamental-level ontology to formalize the definitions of dermoscopic metaphorical terms. Results The Dermoscopy Elements of Visuals Ontology (DEVO) contains 1047 classes, 47 object properties, and 16 data properties. It has a better semiotic score compared to similar ontologies of the same domain. Three human annotators also examined the consistency, complexity, and future application of the ontology. Conclusions The proposed ontology was able to harness the definitions of metaphoric terms by decomposing them into their visual elements. Future applications include providing education for trainees and diagnostic support for dermatologists, with the goal of generating responses to queries about dermoscopic features and integrating these features to diagnose skin diseases.

Abstract Central serous chorioretinopathy (CSCR), first described by Albrecht von Graefe in 1866, is characterized by focal serous detachment of the neural retina and/or retinal pigment epithelium (RPE) in the posterior pole. CSCR is the first ever described pachychoroid disease. Most recently, hypothetical venous overload choroidopathy is also proposed due to its distinguished morphological and pathological characteristics, including choroidal thickening, choriocapillaris hyperpermeability, remodelling, and intervortex venous anastomoses. Identification of genetic variants is necessary to comprehend the pathophysiology of CSCR. The novel multimodality imaging platforms, including the ultra-widefield imaging system, flavoprotein fluorescence, fluorescence lifetime imaging ophthalmoscopy, and multispectral imaging system, have been used for diagnosing and managing CSCR. Half-dose photodynamic therapy (PDT) remains the mainstay of clinical practice, with about 95% of patients with chronic CSCR improving to visual acuity (VA) of 20/30 or better. The use of oral eplerenone for routine clinical care remains controversial, and long-term randomized clinical trials are warranted to investigate its efficacy in acute and chronic CSCR. While CSCR has generally been recognized as a self-limiting disease with good prognosis, the underlying pathogenesis is still not fully understood, and treatments are often not fully effective. With new evidence emerging about pachydrusen being a disease precursor in both CSCR and polypoidal choroidal vasculopathy (PCV), it would be interesting to investigate whether CSCR can be a precursor to PCV. In this review, we highlighted the currently available evidence on the pathogenesis, diagnosis, multimodality imaging features, and management strategies, including recent findings related to CSCR.

Palmitoylethanolamide (PEA) exhibits multiple skincare functions such as anti-nociceptive and anti-inflammatory effects. However, its topical application is limited due to its difficulty in bypassing the stratum corneum barrier, relatively low bioavailability, and low stability. Herein, elastic nano-liposomes (ENLs) with excellent deformability and elasticity were utilized as a novel drug delivery system to encapsulate PEA to overcome the abovementioned issues and enhance the biological effects on the skin. ENL was prepared with phosphatidylcholine, cholesterol, and cetyl-PG hydroxyethyl palmitamide with a molar ratio mimicking skin epidermal lipids, and PEA was loaded. The PEA-loaded ENL (PEA-ENL) demonstrated efficient transdermal delivery and enhanced skin retention, with negligible cytotoxicity toward HaCaT cells and no allergic reaction in the human skin patch test. Notably, PEA-ENL treatment increased cell migration and induced significant regulation in the expression of genes associated with anti-nociceptive, anti-inflammatory, and skin barrier repair. The mechanism of the anti-nociceptive and anti-inflammatory effects of PEA was further investigated and explained by molecular docking site analysis. This novel PEA-ENL, with efficient transdermal delivery efficiency and multiple skincare functionalities, is promising for topical application.

Chinese sour bamboo shoot is a traditionally, spontaneous fermented food that is particularly popular due to its complex and distinctive flavor. The volatile compounds of sour bamboo shoot originate mainly from the raw materials and the microbial fermentation. To reveal the correlation between microorganisms and flavor, third-generation sequencing and Gas Chromatography-Ion Mobility Spectrometry were applied to analyze the dynamics of microbial communities at the species level and volatile compounds during sour bamboo shoot fermentation. The abundance of Lactobacillus acetotolerans and Lactobacillus fermentum increased during the fermentation, while Lactobacillus amyloliquefaciens decreased at first but then began to rise. At the end of fermentation, Lactobacillus amyloliquefaciens and Lactobacillus acetotolerans became the predominant species. A total of sixty-seven volatile compounds, which included twenty-three esters, nineteen alcohols, eight ketones, six aldehydes, six aromatic hydrocarbons, four acids and one ether, were identified. These compounds constituted the primary flavor of sour bamboo, which created a complex flavor of sour bamboo shoot. Among them, the contents of acetic acid, propionic acid, and isoamyl alcohol gradually increased during the fermentation process, and they became the main volatile compounds. Furthermore, the correlation between microorganisms and volatile compounds was investigated through two-way Orthogonal Partial Least Squares (O2PLS), which revealed a positive correlation between Lactobacillus amylolyticus and ethyl propanoate. Additionally, the abundance of Lactobacillus acetotolerans and Lactobacillus fermentum was found to be positively correlated with 2-heptenal. These findings provide a theoretical basis for understanding the formation mechanism of sour bamboo shoot flavor and the standardized production of high-quality sour bamboo shoots.

Extra energy consumption, inefficient nitrogen removal, and excessive sludge production are major challenges faced by wastewater treatment plants (WWTPs) that rely on the traditional activated sludge process. Fermentation of wasted activated sludge (WAS) and novel nitrogen removal technologies based on partial nitrification (PN) have emerged as promising solutions to these issues. Recent studies have revealed an innovative strategy that integrates these two processes by supplementing fermentation liquid into activated sludge to induce PN. This review summarizes the research progress on PN establishment induced by the fermentation process. The microbiology and establishment methods of PN are briefly introduced, followed by a detailed discussion on the process, influencing factors, and product characteristics of WAS fermentation. The core section focuses on the side-stream and main-stream approaches of fermentation-induced PN, comparing their performance and application prospects. The potential mechanisms are explored, with an emphasis on the roles of free ammonia for the side-stream approach and the high tolerance of ammonium oxidizers to in-site fermentation stress for the main-stream approach. Finally, the limitations of the current research and future perspectives are discussed, highlighting the need for further investigation into microbial ecology, process optimization, and long-term stability. This review aims to provide insights into the synergistic integration of WAS fermentation and PN for sustainable and energy-efficient wastewater treatment.

Rheumatoid arthritis (RA) is a chronic autoimmune disease that leads to deformities and disabilities in patients. Conventional treatment focuses on delaying progression; therefore, new treatments are necessary. The present study reported a novel ionic liquid transdermal platform for efficient RA treatment, and the underlying mechanism was elucidated using FTIR, 1H-NMR, Raman, XPS, and molecular simulations. The results showed that the reversibility of the semi-ionic hydrogen bonding facilitated high drug loading and enhanced drug permeability. Actarit’s drug loading had an approximately 11.34-times increase. The in vitro permeability of actarit and ketoprofen was improved by 5.46 and 2.39 times, respectively. And they had the same significant effect in vivo. Furthermore, through the integration of network pharmacology, Western blotting (WB), and radiology analyses, the significant osteoprotective effects of SIHDD-PSA (semi-ionic H-bond double-drug pressure-sensitive adhesive transdermal patch) were revealed through the modulation of the JAK-STAT pathway. The SIHDD-PSA significantly reduced paw swelling and inflammation in the rat model, and stimulatory properties evaluation confirmed the safety of SIHDD-PSA. In conclusion, these findings provide a novel approach for the effective treatment of RA, and the semi-ionic hydrogen bonding strategy contributes a new theoretical basis for developing TDDS.

Abstract Chimeric antigen receptor T-cell (CAR-T) therapy has demonstrated potent clinical efficacy in the treatment of hematopoietic malignancies. However, the application of CAR-T in solid tumors has been limited due in part to the expression of inhibitory molecules in the tumor microenvironment, leading to T-cell exhaustion. To overcome this limitation, we have developed a synthetic T-cell receptor (TCR) that targets programmed death-ligand 1 (PD-L1), a molecule that is widely expressed in various solid tumors and plays a pivotal role in T-cell exhaustion. Our novel TCR platform is based on antibody-based binding domain, which is typically a single-chain variable fragment (scFv), fused to the γδ TCRs (TCRγδ). We have utilized the T-cell receptor alpha constant (TRAC) locus editing approach to express cell surface scFv of anti-PD-L1, which is fused to the constant region of the TCRγ or TCRδ chain in activated T cells derived from peripheral blood mononuclear cells (PBMCs). Our results indicate that these reconfigured receptors, both γ-TCRγδ and δ-TCRγδ, have the capability to transduce signals, produce inflammatory cytokines, degranulate and exert tumor killing activity upon engagement with PD-L1 antigen in vitro. Additionally, we have also shown that γ-TCRγδ exerted superior efficacy than δ-TCRγδ in in vivo xenograft model.

Abstract The motivation for analyzing the impact of deep neural networks on enterprise performance is mainly due to the continuous deepening of enterprise information construction, shifting from traditional paper-based data acquisition methods to electronic data management. The data generated by the sales, production, logistics and other links of enterprises is also becoming increasingly large. How to scientifically and effectively process these massive amounts of data and extract valuable information has become an important issue that enterprises need to solve. The continuous and stable growth of China's economy has promoted the development and growth of enterprises, however, it has also made enterprises face a more complex competitive environment. The question of how to improve the performance of enterprises to enhance their competitiveness in the market has become a major issue to be addressed in the face of fierce competition and to ensure the long-term development of enterprises. In this paper, based on the research of firm performance evaluation, deep neural network is introduced to analyse the influence of ambidextrous innovation and social network on firm performance, and the theories of social network, ambidextrous innovation and deep neural network are sorted out and analysed, and a deep neural network-based firm performance evaluation model is established, and finally the sample data is obtained using crawler technology, and then the response values are analysed. Innovation and the improvement of the mean value of social networks are helpful to firm performance.

Purpose – Evaluating the economic effects of climate change is a pivotal step for planning adaptation in developing countries. For Bangladesh, global warming has put it among the most vulnerable countries in the world to climate change, with increasing temperatures and sea-level rise. Hence, the purpose of this paper is to examine how climate change impacts the economy in Bangladesh in the case of climate scenarios. Design/methodology/approach – Using a dynamic computable general equilibrium (CGE) model and three climate change scenarios, this paper assesses the economy-wide implications of climate change on Bangladesh’s economy and agriculture. It is clear from the examination of the CGE model that the impacts of climate change on agricultural sectors were felt more sharply, reducing output by −3.25% and −3.70%, respectively, and increasing imports by 1.22% and 1.53% in 2030 and 2050, compared to the baseline. Findings – The findings reveal that, relative to baseline, agricultural output will decline by a range of −3.1% to −3.6% under the high climate scenario (higher temperatures and lower yields). A decrease in agricultural output results in declines in agricultural labor and household income. Household income falls in all categories, although it drops the most in urban less educated households with a range of −3.1% to −3.4%. On the other hand, consumption of commodities will fall by −0.11% to −0.13%, according to the findings. Although climate change impacts had a relatively small effect on gross domestic product, reducing it by −0.059% and −0.098% in 2030 and 2050, respectively. Practical implications – As agricultural output, household consumption and income decline, it will impact the majority of the population’s health in Bangladesh by increasing malnutrition, hidden hunger, poverty, changing food environment, changing physical and mental health status and a changing health-care environment. Therefore, population health and food security will be a top socioeconomic and political concern for Bangladesh Government. Originality/value – The examination of the dynamic CGE model is its originality. In conclusion, the evidence generated here can provide important information to policymakers and guide government policies that contribute to national development and the achievement of food security targets. It is also necessary to put more emphasis on climate change issues and address potential risks in the following years.

Abstract Antibiotic resistance and the ability to form biofilms of Enterococcus faecalis have compromised the choice of therapeutic options, which triggered the search for new therapeutic strategies, such as the use of phage endolysins and antimicrobial peptides. However, few studies have addressed the synergistic relationship between these two promising options. Here, we investigated the combination of the phage endolysin Ply2660 and the antimicrobial peptide LL-37 to target drug-resistant biofilm-producing E. faecalis. In vitro bactericidal assays were used to demonstrate the efficacy of the Ply2660–LL-37 combination against E. faecalis. Larger reductions in viable cell counts were observed when Ply2660 and LL-37 were applied together than after individual treatment with either substance. Transmission electron microscopy revealed that the Ply2660–LL-37 combination could lead to severe cell lysis of E. faecalis. The mode of action of the Ply2660–LL-37 combination against E. faecalis was that Ply2660 degrades cell wall peptidoglycan, and subsequently, LL-37 destroys the cytoplasmic membrane. Furthermore, Ply2660 and LL-37 act synergistically to inhibit the biofilm formation of E. faecalis. The Ply2660–LL-37 combination also showed a synergistic effect for the treatment of established biofilm, as biofilm killing with this combination was superior to each substance alone. In a murine peritoneal septicemia model, the Ply2660–LL-37 combination distinctly suppressed the dissemination of E. faecalis isolates and attenuated organ injury, being more effective than each treatment alone. Altogether, our findings indicate that the combination of a phage endolysin and an antimicrobial peptide may be a potential antimicrobial strategy for combating E. faecalis.

Naringenin, a citrus-derived flavonoid, has been reported to positively exert skeletal muscle function. The study designed to explore the potential role and mechanisms of naringenin on regulating the expression of oxidized myofibrils in mice and C2C12 myotubes. In this study, we found that naringenin supplementation significantly improved exercise endurance and oxygen consumption of mice, and also increased aerobic enzyme activity and oxidative myofibers expression in skeletal muscle and C2C12 cells. Meanwhile, naringenin activated the expression of p-PKA/PKA, p-LKB1/LKB1, p-AMPK/AMPK and PGC-1α in skeletal muscle. Furthermore, in vitro studies shown that inhibition of PKA, LKB1 and AMPK could attenuate naringenin-regulated increase in slow muscle fiber proteins. This study suggests that naringenin supplementation can enhance slow myofiber expression by activating the PKA signaling pathway in C57BL/6J mice and C2C12 myotubes. These findings provide a new application of naringenin as a natural candidate to regulate oxidized fiber types and endurance of skeletal muscle.

Background and objectives: The heterogeneity of pulmonary fibroblasts, a critical aspect of both murine and human models under physiological and pathological conditions, is well-documented. Yet, consensus remains elusive on the subtypes, lineage, biological attributes, signal transduction pathways, and plasticity of these fibroblasts. This ambiguity significantly impedes our understanding of the fibrotic processes that transpire in lung tissue during aging. This study aims to elucidate the transcriptional profiles, differentiation pathways, and potential roles of fibroblasts within aging pulmonary tissue.Methods: We employed single-cell transcriptomic sequencing via the 10x Genomics platform. The downstream data were processed and analyzed using R packages, including Seurat. Trajectory and stemness of differentiation analyses were conducted using the Monocle2 and CytoTRACE R packages, respectively. Cell interactions were deciphered using the CellChat R package, and the formation of collagen and muscle fibers was identified through Masson and Van Geison staining techniques.Results: Our analysis captured a total of 22,826 cells, leading to the identification of fibroblasts and various immune cells. We observed a shift in fibroblasts from lipogenic and immune-competent to fibrotic and myofibroblast-like phenotype during the aging process. In the aged stage, fibroblasts exhibited a diminished capacity to express chemokines for immune cells. Experimental validation confirmed an increase of collagen and muscle fiber in the aged compared to young lung tissues. Furthermore, we showed that TGFβ treatment induced a fibrotic, immunodeficient and lipodystrophic transcriptional phenotype in young pulmonary fibroblasts.Conclusion: We present a comprehensive single-cell transcriptomic landscape of lung tissue from aging mice at various stages, revealing the differentiation trajectory of fibroblasts during aging. Our findings underscore the pivotal role of fibroblasts in the regulation of immune cells, and provide insights into why age increases the risk of pulmonary fibrosis.

IntroductionSmall colony variant (SCV) is a bacterial phenotype closely related to persistent and recurrent infections. SCVs are mutations that occur within bacterial populations, resulting in a change in bacterial morphology and the formation of small colonies. This morphological change may enhance bacterial resistance to antibiotics and contribute to persistent and recurrent infections.MethodsWe isolated Klebsiella pneumoniae (KPN) and its SCV from a child with recurrent respiratory tract infections. KPN and SCV were treated with subinhibitory concentrations of antibiotics. growth curves, serum resistance experiments, macrophage phagocytosis experiments and whole genome sequencing were used to characterize KPN and SCV.ResultsAfter treating KPN and SCV with subinhibitory concentrations of antibiotics, we found that ciprofloxacin induced the SCV transition to the mucoid phenotype. We found that the growth of mucoid Klebsiella pneumoniae was significantly slower than maternal strain and SCV though growth curves. Serum resistance experiments showed that mucoid strains had significantly higher serum resistance compared to maternal strain and SCV. Macrophage phagocytosis experiments revealed that SCV had significantly higher intracellular survival rates compared to maternal strain and mucoid strains. Differential gene analysis of three strains revealed that the mucoid strain contained DNA polymerase V subunit UmuC gene on the plasmid, while the SCV strain had an additional IcmK family IV secretion protein on its plasmid.DiscussionOur study showed the SCV of KPN changed to a mucoid colony when exposed to subinhibitory concentrations of ciprofloxacin. The higher resistance of serum of mucoid colonies was possibly related to the UmuC gene, while the increased intracellular survival of SCV may be related to the IcmK family type IV secretion proteins.

At present, energy shortages are becoming increasingly severe, and the concept of park level multi energy complementary systems (MECS) has provided direction for sustainable energy development. In recent years, how to improve the economy and reliability of multi energy complementary systems has become a research hotspot in this field. In this paper, a two-layer optimal scheduling strategy is proposed to allocate the capacity of various energy equipment in the park, considering the comprehensive energy self-sufficiency rate, comprehensive energy utilization rate and energy shortage expectation. The proposed capacity allocation scheme can effectively improve the economy of MECS in the park. Finally, the effectiveness and practicability of the algorithm are verified by simulation analysis.

BackgroundThis study aims to investigate the association between an elevated bilateral pulse wave velocity difference (BPWVD) and cardiovascular diseases (CVDs) and all-cause mortality.MethodsThis study included a total of 38,356 participants. A multivariable Cox proportional hazards regression was used to assess the association between high BPWVD and the increased risk of CVDs and all-cause mortality by calculating hazard ratios (HRs) with 95% confidence intervals.ResultsA total of 1,213 cases of CVDs were identified over a mean duration of 6.19 years, including 886 cases of cerebral infarction (CI), 105 cases of intracerebral hemorrhage (ICH), and 222 cases of myocardial infarction (MI), along with 1,182 cases of all-cause mortality. The median BPWVD was 42 cm/s (19–80 cm/s). After adjusting for all confounders and baseline brachial-ankle PWV (baPWV), our analysis revealed a significant correlation between a higher risk of CVDs, MI, and all-cause mortality with an increase in BPWVD per standard deviation. HRs (95% confidence interval) were found to be 1.06 (1.01–1.11), 1.11 (1.02–1.21), and 1.07 (1.04–1.10), respectively. Among the participants with higher baPWV on the left side, the HRs (95% confidence interval) were 1.08 (1.02–1.14) for CVDs, 1.27 (1.10–1.46) for incident ICH, 1.16 (1.00–1.24) for incident MI, and 1.10 (1.07–1.15) for all-cause mortality, for per standard deviation increase in BPWVD.ConclusionsOur findings reveal a significant correlation between elevated BPWVD and the risks of developing CVDs and all-cause mortality. This highlights the importance of thoroughly evaluating BPWVD as a means of detecting individuals at risk for CVDs and mortality.

Abstract Reflective tomography Lidar is long‐range, high‐resolution imaging Lidar. Because the angular resolution is independent of detection range, it enjoys promising application prospects in imaging of small space targets, estimation of barycentre range of space debris, and many other fields. In practice, images generated by reflective tomography Lidar generally contain a large number of artefacts and noise that need to be removed to obtain the target profile. To improve the quality of the target profile, an algorithm is proposed for the extraction and segmentation of the target region in reflective tomography Lidar images. According to the experimental results, the algorithm can achieve better segmentation results than the traditional threshold segmentation algorithms. In particular, the algorithm can maintain good segmentation results for those images with noticeable ring artefacts, strip artefacts, and noise while avoiding under‐segmentation or over‐segmentation. It also guarantees the integrity of the target segmentation, preserves the outer contour and detailed structure information of the target as much as possible, and improves the accuracy of the target segmentation. Compared with conventional threshold segmentation algorithms, the algorithm improves the quality of image segmentation, and can improve the quality factor by more than 3%.

Abstract Background Mixed payment schemes have become one of the effective measures to balance medical costs and quality of medical services. However, altruism as an intrinsic motivation may influence the effect of switching from a pure payment system to mixed payment schemes. This study aimed to quantify physicians’ altruism and analyze the effect of changes of payment system on physicians’ altruism and thus proposed references for the reform of payment system. Methods We simulated an exogenous payment system in a controlled laboratory with five experimental groups and 150 medical student subjects. Physicians’ altruism was measured by estimating altruistic parameter and marginal rate of substitution. The non-parametric test and the least square regression analysis were used to analyze the differences of altruistic parameters between pure payment systems and mixed payment schemes. Finally, we analyzed the effect of changes in payment system accompanied by changes in trade-off range on physicians’ altruism. Results We find that the mean value of individual altruistic parameter is 0.78 and the marginal rate of substitution is 1.078. Their estimates at the individual level were significantly positively correlated (Spearman’s ρ = 0.715, p

Parkinson’s disease (PD) is a prevalent brain disorder, and PD diagnosis is crucial for treatment. Existing methods for PD diagnosis are mainly focused on behavior analysis, while the functional neurodegeneration of PD has not been well investigated. This paper proposes a method to signify functional neurodegeneration of PD with dynamic functional connectivity analysis. A functional near-infrared spectroscopy (fNIRS)-based experimental paradigm was designed to capture brain activation from 50 PD patients and 41 age-matched healthy controls in clinical walking tests. Dynamic functional connectivity was constructed with sliding-window correlation analysis, and k-means clustering was applied to generate the key brain connectivity states. Dynamic state features including state occurrence probability, state transition percentage and state statistical features were extracted to quantify the variations of brain functional networks. A support vector machine was trained to classify PD patients and healthy controls. Statistical analysis was conducted to investigate the difference between PD patients and healthy controls as well as the relationship between dynamic state features and the MDS-UPDRS sub-score of gait. The results showed that PD patients had a higher probability of transiting to brain connectivity states with high levels of information transmission compared with healthy controls. The MDS-UPDRS sub-score of gait and the dynamics state features showed a significant correlation. Moreover, the proposed method had better classification performances than the available fNIRS-based methods in terms of accuracy and F1 score. Thus, the proposed method well signified functional neurodegeneration of PD, and the dynamic state features may serve as promising functional biomarkers for PD diagnosis.

Abstract The prognostic value of albumin-to-alkaline phosphatase ratio (AAPR) in patients with hepatocellular carcinoma (HCC) remains controversial. This meta-analysis aims to evaluate the prognostic role of AAPR in patients with HCC. The databases of Web of Science, Embase, Cochrane Library and PubMed were comprehensively searched from inception to April 25, 2022. Pooled hazard ratio (HR) and 95% confidence interval (CI) were calculated with Stata 16.0 software for the assessment of the relationship between AAPR and overall survival (OS) as well as recurrence-free survival (RFS) in patients with HCC. A total of 2634 patients from 12 cohorts were included in this meta-analysis. The pooled results showed that lower AAPR predicted poorer OS (HR 2.02, 95% CI 1.78–2.30). Similarly, pooled results demonstrated that lower AAPR also predicted poorer RFS (HR 1.88, 95% CI 1.37–2.57). The heterogeneity for RFS by multivariate analytic results and the publication bias for OS existed, however, the subgroup analysis, meta-regression analysis as well as adjustment using trim-and-fill analysis confirmed an association between AAPR and OS as well as RFS. This meta-analysis proves that lower AAPR in patients with HCC predicted inferior survival outcomes, and AAPR might be a promising indicator for the prognosis of HCC.

Time-based prospective memory (TBPM) refers to the ability of an individual to successfully execute an expected plan in the future at a certain time point or after a definite period of time. This study investigated the potential developmental mechanism of school-age children’s TBPM ability from the perspective of time monitoring. Experiment 1 used a between-subjects design of three ages (7, 9, 11) × two TBPM types (time point, time period) to investigate the trends and characteristics of two types of TBPM in children aged 7–11 years old. Experiment 2 used a between-subjects design of three ages (7, 9, 11) × two monitoring conditions (free monitoring, fixed monitoring) to investigate differences in two types of TBPM and monitoring behavior among school-age children under different monitoring conditions. These results showed that the age effect of TBPM was affected by the type of prospective memory (PM) and that time-point PM performance was significantly better than time-period PM performance among school-age children. These findings indicate that clear and definite external cues are helpful for school-age children in performing TBPM tasks. Moreover, there were significant differences found in the TBPM performance of school-age children under different time monitoring conditions. The performance of older children was significantly better than that of younger children. This indicates that older children can better allocate their attentional resources and use time monitoring strategies to improve their performance in PM tasks. Accordingly, this study showed that the TBPM ability of 7- to 11-year-old children is in continuous development and that the time monitoring behavior in the TBPM task is affected by task type and monitoring conditions.

Voltage sags resulting from symmetrical or asymmetrical faults pose a significant threat to power quality. In response to this challenge, a voltage sag loss assessment method based on a two-stage Taguchi quality perspective approach is proposed to address the quantitative analysis of voltage sag economic losses. Initially, using the Taguchi quality perspective method, single-index quality loss functions are separately established for voltage sag magnitude and fault duration. Subsequently, by introducing a comprehensive load tolerance curve, sensitivity parameters within the quality loss function are accurately calculated. This yields a deterministic model for voltage sag assessment. Building upon this, the relative impact of the two indices on voltage sag loss is evaluated using the quality loss function. Consequently, a comprehensive loss model under the influence of multiple indices is formed by integrating two single-index evaluation models. The simulation results indicate that this method can effectively assess the economic losses of voltage sags under the combined influence of multiple factors. Compared to the original economic loss assessment method, it improves quantitative accuracy by approximately 3.72%. Moreover, the method reduces the computational complexity of loss assessment through the consolidation of intervals with similar sensitivity parameters.

The Multi-Point Relay (MPR) is one of the core technologies for Optimizing Link State Routing (OLSR) protocols, offering significant advantages in reducing network overhead, enhancing throughput, maintaining network scalability, and adaptability. However, due to the restriction that only MPR nodes can forward control messages in the network, the current evaluation criteria for selecting MPR nodes are relatively limited, making it challenging to flexibly choose MPR nodes based on current link states in dynamic networks. Therefore, the selection of MPR nodes is crucial in dynamic networks. To address issues such as unstable links, poor transmission accuracy, and lack of real-time performance caused by mobility in dynamic networks, we propose a comprehensive evaluation algorithm of MPR based on link-state awareness. This algorithm defines five state evaluation parameters from the perspectives of node mobility and load. Subsequently, we use the entropy weight method to determine weight coefficients and employing the method of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for comprehensive evaluation to select MPR nodes. Finally, the Comprehensive Evaluation based on Link-state awareness of OLSR (CEL-OLSR) protocol is proposed, and simulated experiments are conducted using NS-3. The results indicate that, compared to PM-OLSR, ML-OLSR, LD-OLSR, and OLSR, CEL-OLSR significantly improves network performance in terms of packet delivery rate, average end-to-end delay, network throughput, and control overhead.

The periosteum is known as the thin connective tissue covering most bone surfaces. Its extrusive bone regeneration capacity was confirmed from the very first century-old studies. Recently, pluripotent stem cells in the periosteum with unique physiological properties were unveiled. Existing in dynamic contexts and regulated by complex molecular networks, periosteal stem cells emerge as having strong capabilities of proliferation and multipotential differentiation. Through continuous exploration of studies, we are now starting to acquire more insight into the great potential of the periosteum in bone formation and repair in situ or ectopically. It is undeniable that the periosteum is developing further into a more promising strategy to be harnessed in bone tissue regeneration. Here, we summarized the development and structure of the periosteum, cell markers, and the biological features of periosteal stem cells. Then, we reviewed their pivotal role in bone repair and the underlying molecular regulation. The understanding of periosteum-related cellular and molecular content will help enhance future research efforts and application transformation of the periosteum.