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Abstract Background In recent years, several giant pandas have suffered from testicular tumor, which has seriously affected giant panda health. However, the pathogenesis of testicular tumor in giant panda is still unclear. Studies have shown that miRNAs are involved in the occurrence and development of a variety of cancers. However, the effect of miRNAs on giant panda testicular tumor has been little studied. Therefore, this study explored the pathogenesis of giant panda testicular tumor through miRNA and mRNA sequencing, and screened out diagnostic markers of testicular tumor. Results Combined with phenotypic symptoms and pathological section results, three giant pandas were diagnosed with testicular tumor and divided into tumor group, and three other giant pandas were divided into normal group. A total of 29 differentially expressed miRNAs (DEmiRNAs) were screened by blood miRNA-seq, and 3149 target gene candidates were predicted. Functional enrichment analysis showed that the target genes were mainly involved in intermembrane lipid transfer and ATP-dependent chromatin remodeling. However, only 5 DEmiRNAs were screened by miRNA-seq of blood-derived exosomes and 364 target genes were predicted, which were mainly involved in antigen processing and presentation. In addition, 216 differentially expressed genes (DEGs) were screened by RNA-seq, and functional enrichment analysis showed that tumor-specific DEGs significantly enriched to protein phosphorylation. Spearman correlation analysis of miRNA-mRNA showed that the expressions of miR-331-3p and PKIG were significantly positively correlated (spearman = 0.943, p

Abstract Pullorum disease and fowl typhoid are caused by the Salmonella serovars Gallinarum biovars Pullorum and Gallinarum, respectively. The prevalence of these diseases varies across regions and is affected by different risk factors that remain insufficiently documented. To fill this knowledge gap, we have compiled a global dataset for its prevalence, drawing upon a collection of literature from the last seven decades obtained from bilingual databases. However, a more interactive and dynamic platform is still needed for both academics and policymakers to improve biosecurity measures, limit disease transmission, and prevent future outbreaks at the global and local levels. Here, we developed an advanced visualization platform to depict the prevalence of Salmonella Pullorum and Gallinarum, especially in China, which is categorized by geographical region and temporal span. The platform offers a user-friendly, efficient, and visually engaging tool to explore the prevalence of pullorum disease and fowl typhoid between 1945 and 2021 in different regions. Additionally, this platform allows users to understand the influence of various factors, such as breed, farm mode, economic usage and even the sex of the primary host, chickens, on the prevalence of this disease. We further provided a detailed overview of individual province within China. In particular, by selecting two different provinces on the interface, users can quickly visualize and grasp the disparities in disease prevalence between the chosen regions. This interactive toolkit enables a dynamic exploration of the patterns and factors contributing to the prevalence of Salmonella Pullorum and Gallinarum. This interactive platform is freely available open source at http://139.9.85.208/ .

Abstract Background Application of data-driven strategies may support veterinarians’ decision-making, benefitting pig disease prevention and control. However, little is known about veterinarians’ need for data utilisation to support their decision-making process. The current study used qualitative methods, specifically focus group discussions, to explore veterinarians’ views on data utilisation and their need for data tools in relation to pig health and welfare management in Spain, the Netherlands, and Ireland. Results Generally, veterinarians pointed out the potential benefits of using technology for pig health and welfare management, but data is not yet structurally available to support their decision-making. Veterinarians pointed out the challenge of collecting, recording, and accessing data in a consistent and timely manner. Besides, the reliability, standardisation, and the context of data were identified as important factors affecting the efficiency and effectiveness of data utilisation by veterinarians. A user-friendly, adaptable, and integrated data tool was regarded as potentially helpful for veterinarians’ daily work and supporting their decision-making. Specifically, veterinarians, particularly independent veterinary practitioners, noted a need for easy access to pig information. Veterinarians such as those working for integrated companies, corporate veterinarians, and independent veterinary practitioners expressed their need for data tools that provide useful information to monitor pig health and welfare in real-time, to visualise the prevalence of endemic disease based on a shared report between farmers, veterinarians, and other professional parties, to support decision-making, and to receive early warnings for disease prevention and control. Conclusions It is concluded that the management of pig health and welfare may benefit from data utilisation if the quality of data can be assured, the data tools can meet veterinarians’ needs for decision-making, and the collaboration of sharing data and using data between farmers, veterinarians, and other professional parties can be enhanced. Nevertheless, several notable technical and institutional barriers still exist, which need to be overcome.

Vitamin A is a micronutrient critical for versatile biological functions and has been widely used in the food, cosmetics, pharmaceutical, and nutraceutical industries. Synthetic biology and metabolic engineering enable microbes, especially the model organism Saccharomyces cerevisiae (generally recognised as safe) to possess great potential for the production of vitamin A. Herein, we first generated a vitamin A-producing strain by mining β-carotene 15,15′-mono(di)oxygenase from different sources and identified two isoenzymes Mbblh and Ssbco with comparable catalytic properties but different catalytic mechanisms. Combinational expression of isoenzymes increased the flux from β-carotene to vitamin A metabolism. To modulate the vitamin A components, retinol dehydrogenase 12 from Homo sapiens was introduced to achieve more than 90 % retinol purity using shake flask fermentation. Overexpressing POS5Δ17 enhanced the reduced nicotinamide adenine dinucleotide phosphate pool, and the titer of vitamin A was elevated by almost 46 %. Multi-copy integration of the key rate-limiting step gene Mbblh further improved the synthesis of vitamin A. Consequently, the titer of vitamin A in the strain harbouring the Ura3 marker was increased to 588 mg/L at the shake-flask level. Eventually, the highest reported titer of 5.21 g/L vitamin A in S. cerevisiae was achieved in a 1-L bioreactor. This study unlocked the potential of S. cerevisiae for synthesising vitamin A in a sustainable and economical way, laying the foundation for the commercial-scale production of bio-based vitamin A.

Background: Tongue inspection, an essential diagnostic method in Traditional Chinese Medicine (TCM), has the potential for early-stage disease screening. This study aimed to evaluate the effectiveness of deep learning-based analysis of tongue images for hepatic fibrosis screening. Methods: A total of 1083 tongue images were collected from 741 patients and divided into training, validation, and test sets. DenseNet-201, a convolutional neural network, was employed to train the AI model using these tongue images. The predictive performance of AI was assessed and compared with that of FIB-4, using real-time two-dimensional shear wave elastography as the reference standard. Results: The proposed AI model achieved an accuracy of 0.845 (95% CI: 0.79–0.90) and 0.814 (95% CI: 0.76–0.87) in the validation and test sets, respectively, with negative predictive values (NPVs) exceeding 90% in both sets. The AI model outperformed FIB-4 in all aspects, and when combined with FIB-4, the NPV reached 94.4%. Conclusion: Tongue inspection, with the assistance of AI, could serve as a first-line screening method for hepatic fibrosis.

Abstract Purpose We aimed to evaluate the efficiency of computed tomography (CT) radiomic features extracted from gross tumor volume (GTV) and peritumoral volumes (PTV) of 5, 10, and 15 mm to identify the tumor grades corresponding to the new histological grading system proposed in 2020 by the Pathology Committee of the International Association for the Study of Lung Cancer (IASLC). Methods A total of 151 lung adenocarcinomas manifesting as pure ground-glass lung nodules (pGGNs) were included in this randomized multicenter retrospective study. Four radiomic models were constructed from GTV and GTV + 5/10/15-mm PTV, respectively, and compared. The diagnostic performance of the different models was evaluated using receiver operating characteristic curve analysis Results The pGGNs were classified into grade 1 (117), 2 (34), and 3 (0), according to the IASLC grading system. In all four radiomic models, pGGNs of grade 2 had significantly higher radiomic scores than those of grade 1 (P

Background Continuous glucose monitoring (CGM) is rarely applied to outpatient treatments. The impact of CGM-based diabetes education to change unhealthy living and eating habits on the blood glucose profile is still unclear. Objective Based on the retrospective results of CGM, outpatient education such as diet and exercise was applied to outpatients with type 2 diabetes mellitus (T2DM) who were managed by oral hypoglycemic drugs. This study aims to evaluate the effects on blood glucose profiles. Methods A total of 88 outpatient T2DM patients medicated with oral hypoglycemic drugs in the Department of Endocrinology, Nanjing First Hospital in 2021 were included and managed by CGM, involving 60 male and 28 female patients. The enrolled patients maintained the original hypoglycemic treatment regimen and lifestyle habits on the 1st to 3rd day. On the 4th day, we downloaded and analyzed CGM data and provided outpatient education based on individualized eating habit and exercise. On the 6th day, the CGM sensor and recorder were removed. CGM data on the 2nd day versus 5th day were compared for dynamic blood glucose profiles, including the 24 h mean blood glucose (MBG), mean amplitude of glycemic excursion (MAGE) and time in target glucose range (TIR) . Results Based on the CGM results, MBG in outpatients with T2DM on the 5th day after outpatient education was significantly reduced from (8.34±1.97) mmol/L to (7.85±1.65) mmol/L (P

Alzheimer’s disease (AD) is a neurodegenerative disorder marked by cognitive decline, primarily affecting memory and executive function. This review highlights recent advancements in single-cell sequencing and spatial transcriptomics, which provide detailed insights into the cellular heterogeneity and neuroimmune mechanisms of AD. The review addresses the need for understanding complex cellular interactions to identify novel therapeutic targets and biomarkers. Single-cell sequencing has revolutionized our understanding by mapping gene expression at the individual cell level, revealing distinct microglial and astrocytic states that contribute to neuroinflammation and neurodegeneration. These technologies have uncovered disease-associated microglial subpopulations and gene expression changes linked to AD risk genes, essential for developing targeted therapies. In conclusion, the integration of single-cell and spatial transcriptomics with other omics data is crucial for a comprehensive understanding of AD, paving the way for personalized medicine. Continued interdisciplinary collaboration will be vital in translating these findings into effective treatments, improving patient outcomes.

This study introduces an innovative system for combined cycle power plants that significantly enhances efficiency and sustainability through advanced heat recovery techniques. By integrating various cycles and units, including the Brayton, Rankine, and Kalina cycles, along with a thermoelectric generator, proton exchange membrane electrolysis hydrogen production unit, and RO desalination unit, the proposed system optimizes performance across multiple dimensions. Multi-objective optimization, employing a genetic algorithm, ensures optimal system performance in terms of energy, exergy, economics, and environmental impact. The novelty of this research lies in its comprehensive approach to combining power generation with water desalination and hydrogen production, thereby addressing multiple energy and environmental challenges simultaneously. The thermodynamic analysis confirms the system's capability to deliver 1.45 MW of electrical power and produce 3.24 kg/h of hydrogen, with a unit cost of production (UCOP) of 10.24 cents/kWh. Key findings highlight the significant impact of gas turbine inlet temperature on system cost and efficiency, and the trade-offs involved in optimizing pressure ratios for peak performance. The optimized system demonstrates an exergy efficiency of 37. 6 % at a cost rate of 57. 2 $/h. The integrated approach not only increases power generation capacity but also enables the production of hydrogen fuel and fresh water, showcasing technological advancements with significant practical applications. The potential prospects of this research include its application in various industrial sectors, contributing to sustainable energy solutions and environmental conservation.

Data missing and anomalies in monitoring equipment have become critical barriers to developing intelligent Water Supply Systems (WSS). The valid data preceding and after the missing segments can be utilized to impute missing values. However, traditional imputation methods, such as linear interpolation and prediction-based methods, have limited capacity to use data relationships or can only utilize information before the missing values. Therefore, existing methods still need to work on efficiently and conveniently achieving high-accuracy imputation. According to the continuity and periodicity of WSS data, missing values often exhibit multi-level correlations with valid data. This paper innovatively employs graph structures to analyze the multi-level correlations at different timestamps and applies graph signal sampling algorithms to extract low-frequency features for imputation. A novel Graph-based Data Imputation (GDI) method has been developed, which leverages multi-level correlations to propagate information and completes imputation tasks without requiring complex feature engineering and pre-training processes. Results indicate that GDI outperforms Holt-Winters, Support Vector Regression, and Gated Recurrent Unit in the task of imputing continuous missing data. It can still achieve R2>0.8 even when the proportion of missing values reaches 80 %. These results demonstrate that GDI ensures a more streamlined and efficient imputation with high robustness and accuracy.

ABSTRACTThe United Nations has proposed Sustainable Development Goals (SDGs), of which SDG11 aims to “make cities and human settlements inclusive, safe, resilient and sustainable”. This is in line with Urban Vitality's objectives. This study proposes a quantitative framework to evaluate the impact of urban morphology on urban vitality. In this framework, a proxy that is more reflective of economic and human activities is proposed for depicting urban vitality based on geographic big data; then we use a Multi–scale Geographically Weighted Regression (MGWR) regression considering spatial heterogeneity to analyze the different effects of urban form on urban vitality. Taking the Beijing Sixth Ring Road area as the study region, the results indicate that tall, large–area, multi–functional buildings have a significantly positive impact on urban vitality. These areas exhibit single–function buildings and high levels of greenery, leading to inefficient space utilization. Increasing road network density, as well as the density of transportation and public facilities, also positively influences urban vitality. However, commercial density has a negative impact on workday vitality. Furthermore, excessive green space density, a high proportion of the largest green patches, and complex green space borders all contribute to a reduction in urban vitality.

Active physiotherapy (APT) embraces a patient-centered approach, prioritizing self-management within the biopsychosocial model and involving active patient movements. Beyond structured exercise, APT incorporates pain neuroscience education, Mulligan Mobilization (MWM), and active myofascial release techniques to integrate sensory-motor information for functional recovery and pain relief. This study aims to rigorously compare the effectiveness of APT versus conventional physical therapy (CPT) on pain and functional outcomes in patients with chronic knee pain. Eighty-seven patients with symptomatic and radiographically confirmed knee pain were included in this 12-month follow-up of a randomized controlled trial, conducted at a national institute and a rehabilitation clinic. Patients were randomized to either APT (n = 44) or CPT (n = 43). The APT protocol integrated pain neuroscience education, MWM, active myofascial release techniques, and structured exercises focusing on flexibility, stability, neuromuscular control, and coordination. The CPT protocol included health education, laser therapy, ultrasound therapy, and exercise. Both interventions were performed for 60 min twice a week for 3 months. The primary outcome was the Knee Injury and Osteoarthritis Outcome Score-4 domain version (KOOS4). Secondary outcomes included pain intensity (VAS), KOOS-pain, activities of daily living (ADL), function in sport and recreation (Sports/Rec), knee-related quality of life, global rating of change (GROC), quality of life (SF-36), Tampa Scale for Kinesiophobia (TSK), and functional performances measured at different intervals. Intention-to-treat analyses were performed. Of the 87 patients, 70 (80.5%) completed the 12-month follow-up. KOOS4 improved more in the APT group (16.13; 95% CI, 10.39–21.88) than in the CPT group (11.23; 95% CI, 5.42–17.04). APT showed additional improvement in KOOS4 compared to CPT (2.94; 95% CI: 0.04 to 5.85, p = 0.047). The VAS difference was −3.41 mm (95% CI: −6.40 to −0.43, p = 0.025), favoring APT. APT also showed more improvements in KOOS-pain, KOOS-ADL, KOOS-Sports/Rec, and TSK (p < 0.05). No differences between groups were observed in GROC and SF-36. APT significantly improved most functional performance variables compared to CPT (p < 0.05). Active Physiotherapy outshines conventional physical therapy by delivering more substantial reductions in pain intensity and marked enhancements in function among patients with knee pain. This distinctive efficacy underscores the invaluable role of APT in the management of chronic knee pain. By actively involving patients in their recovery journey, APT not only fosters superior results but also emphasizes the critical need to integrate these advanced therapeutic strategies into everyday clinical practices.

BackgroundGallstones are among the most common complications of hereditary spherocytosis (HS). In previous treatments, gallbladder-preserving cholelithotomy (GPC) has remained a subject of significant debate due primarily to potential risks of stone recurrence. However, past studies have often overlooked the impact of specific disease conditions on GPC. In this study, we reviewed the clinical data of GPC in HS pediatric patients with concurrent gallstones over a period of seven years in a single center.MethodsFrom December 2016 to April 2024, 32 pediatric patients with HS who underwent splenectomy and GPC surgery based on our inclusion criteria. Clinical pathological, and follow-up data of these patients were collected.ResultsIn terms of short-term complications, there were there were no cases of postoperative bleeding, bile duct injury. 3 cases (9.3%) experienced varying degrees of bile peritonitis. During long-term follow-up, only 2 cases (6.2%) showed recurrence of gallstones. One case of bile leakage occurred.ConclusionGPC demonstrates significant efficacy for pediatric patients with hereditary spherocytosis (HS) complicated by gallstones, showing a a low recurrence rate and high safety profile.

Microplastic pollution from everyday plastic items has increased tremendously worldwide. Pyrolysis gas chromatography coupled to mass spectrometry (Py-GC/MS) has been widely investigated for the qualitative and quantitative analysis of microplastics in environmental samples. However, there are several pitfalls to consider when developing an appropriate protocol for their analysis. This study aimed at the development of an in-house database of primary (single) polymers, binary (two) polymers and tertiary (three) polymer mixtures. In this context the potential occurrence of gas phase reactions during pyrolysis of binary and tertiary polymers were investigated. Further, different diluters were tested for the accurate preparation of calibration standards for quantification purposes.Seven different polymers were included in this study, which were chosen due to their prevalence in daily plastic appliances. For each single polymer specific peaks could be identified and recommendation for quantifier analytes given. The analysis of binary polymer mixtures revealed gas phase reactions for PET with PVC, PVC with MDI-PU and PE with PVC. For these binary polymers, several different novel pyrolysis products, specific for the according binary polymer mixture, could be identified. These results confirmed that especially PVC exhibits strong interactions during co-pyrolysis with ester- and ether-based polymers. Similar results were obtained for tertiary polymers.For accurate preparation of calibration standards different diluters (silica, deactivated silica, calcium carbonate, THF and HFIP) were tested. It was observed that deactivated silica had only an influence on the pyrolysis of PET. Whereas, dilution with silica affected PA-6/66, PE, PET and MDI-PU. Only PVC was not influenced by dilution with silica.In conclusion, our results highlight the necessity of an international standard of reference material as well as a standardized analytical protocol for the analysis and quantification of polymers in environmental samples. It is crucial to use diluters suitable for the specific polymer, to exclude potential interactions of diluters with the polymer. The present work has to be seen as a foundation, but future work is needed to adequately address the quantification of polymers in environmental samples.

BackgroundDifficulty in achieving complete resection leads to a poor prognosis for retroperitoneal soft tissue sarcoma, hence emphasizing the significance of adjuvant treatment. The benefit of preoperative radiotherapy for retroperitoneal liposarcoma was initially demonstrated by the STRASS trial. However, the impact of intraoperative radiotherapy (IORT) on retroperitoneal liposarcoma remains unexplored.MethodPatients with retroperitoneal liposarcoma were identified in the Surveillance, Epidemiology, and End Results (SEER) database, treated between 2000 and 2019. Subsequently, a 1:1 propensity score-matched (PSM) analysis was conducted based on variables identified from a multivariate analysis. T-tests were used to assess differences in normally distributed continuous variables, while the rank-sum test was applied to variables that did not follow a normal distribution. The chi-squared test was utilized to evaluate differences in categorical variables. Ultimately, survival analysis was performed using SPSS to evaluate patient prognosis.ResultA total of 2129 patients with retroperitoneal liposarcoma were included in our study. Age, sex, histology, grading, chemotherapy, and tumor size as independent prognostic risk factors for these patients through multivariate Cox regression analysis. Subsequently, 66 patients were included in the survival analysis through PSM, with 33 patients receiving IORT. Finally, the survival analysis revealed that there was no difference in overall survival among patients with retroperitoneal liposarcoma, regardless of whether they received IORT or not (p= 0.711).ConclusionAs an exploratory study, our findings suggest that patients may not derive benefit from intraoperative radiotherapy. These observations are intended to lay the groundwork for future prospective clinical studies.

ObjectiveThis study investigates the impact of transvascular antitumor interventional therapies on immune cell dynamics and its correlation with disease control and progression-free survival (PFS) in hepatocellular carcinoma (HCC) patients.MethodsA single-center observational case-control study was conducted with 119 HCC patients. Transvascular antitumor interventional therapy were administered based on patient-specific evaluations. Peripheral blood samples were collected before and within 28 days after the first treatment to analyze lymphocyte subsets and other immune cells.ResultsHigher counts of total white blood cells (WBCs), lymphocytes, monocytes, and basophils were significantly associated with disease control rate. Subgroup analysis revealed that abnormal BMI, diabetes, infection, and multiple lesions were significantly associated with T cell abnormalities. Age, abnormal BMI, hypertension, and abnormal AFP were linked to total T cell abnormalities. NK cells, B cells, Th cells, Tc/Ts cells, and CD4/CD8 ratios did not show significant differences in PFS probabilities.ConclusionHigher counts of WBCs, lymphocytes, monocytes, and basophils, play a crucial role in the effectiveness of HCC interventional therapy.

Abstract Anaplasma and Ehrlichia are tick-borne bacterial pathogens that cause anaplasmoses and ehrlichioses in humans and animals. In this study, we examined the prevalence of Anaplasma and Ehrlichia species in ticks and domesticated animals in Suizhou County, Hubei Province in the central China. We used PCR amplification and DNA sequencing of the 16S rRNA, groEL, and gltA genes to analyze. We collected 1900 ticks, including 1981 Haemaphysalis longicornis and 9 Rhipicephalus microplus, 159 blood samples of goats (n = 152), cattle (n = 4), and dogs (n = 3) from May to August of 2023. PCR products demonstrated that Anaplasma bovis, Anaplasma capra, and an Ehrlichia species were detected in the H. longicornis with the minimum infection rates (MIR) of 1.11%, 1.32%, and 0.05%, respectively; A. bovis, A. capra, and unnamed Anaplasma sp. were detected in goats with an infection rate of 26.31%, 1.31% and 1.97%, respectively. Anaplasma and Ehrlichia species were not detected from cattle, dogs and R. microplus ticks. The genetic differences in the groEL gene sequences of the Anaplasma in the current study were large, whereas the 16S rRNA and gltA gene sequences were less disparate. This study shows that ticks and goats in Suizhou County, Hubei Province carry multiple Anaplasma species and an Ehrlichia species, with relatively higher infection rate of A. bovis in goats. Our study indicates that multiple Anaplasma and Ehrlichia species exist in ticks and goats in the central China with potential to cause human infection.

Abstract Seasonal variability could have an impact on the incidence and outcome of stroke. However, little is known about the correlation between seasonal variability and location of acute cerebral infarction. This study aimed to explore the relationship between onset season and the lesions distribution of acute ischemic stroke (AIS). We retrospectively analysis data from 1488 AIS patients admitted to the Second Hospital of Tianjin Medical University from 2018 to 2022. All subjects completed head magnetic resonance imaging examination (MRI) and were divided into four groups according to the onset seasons. The lesions distribution of AIS was evaluated for anterior/posterior/double circulation infarction (DCI), unilateral/bilateral infarctions, and single/multiple cerebral infarctions based on MRI. Logistic regression models were employed to assess the association of season with lesions distribution of AIS. Subgroup analysis was performed in different stroke subtypes. Of 1488 patients, 387 (26.0%) AIS occurred in spring, 425 (28.6%) in summer, 331 (22.2%) in autumn and 345 (23.2%) in winter. Multivariate logistic regression demonstrated that the winter group had 2.15 times (95% CI:1.44–3.21) risk of multiple infarctions, 2.69 times (95% CI:1.80–4.02) of bilateral infarctions and 1.54 times (95% CI:1.05–2.26) of DCI compared with summer group, respectively. Subgroup analysis showed an increased risk of multiple (p

AIM: To observe the effect of ghrelin, a growth hormone-releasing peptide, on retinal angiogenesis in vitro under high glucose (HG) stress and to explore the possible mechanism of autophagy. METHODS: Human retinal microvascular endothelial cells (HRMECs) were treated with high concentration of glucose alone or in combination with ghrelin. The cell migration, tube formation and the expression of the autophagy-related proteins LC3-II/I, Beclin-1, p62, phosphorylated AKT (p-AKT)/AKT and phosphorylated mammalian target of rapamycin (p-mTOR)/mTOR were detected. Then, to clarify the correlation between ghrelin effect and autophagy, AKT inhibitor VIII was adopted to treat HRMECs, and cell migration, tube formation as well as the protein expressions of LC3-II/I, Beclin-1 and p62 were observed. RESULTS: Under HG stress, ghrelin inhibited migration and tube formation of HRMECs. Ghrelin inhibited the increases in the protein levels of LC3-II/I, Beclin-1 and the decreases in the protein levels of p62, p-AKT/AKT and p-mTOR/mTOR induced by HG stress. Moreover, under the action of AKT/mTOR pathway inhibitors, the effects of ghrelin on migration and tube formation were both reduced. In addition, the expression of LC3-II/I and Beclin-1 were significantly up-regulated and the expression of p62 was down-regulated. CONCLUSION: Retinal angiogenesis under in vitro HG stress can be inhibited by ghrelin through activating AKT/mTOR pathway to inhibit autophagy.

Abstract Background Healthcare staff in China, especially females, work in a high-pressure, high-load, and high-risk environment, which affects the physical and mental health, the efficiency and quality of work, and increases turnover intention. The present study investigated the relationship between perceived stress and turnover intention in female healthcare staff, and the effects of future-oriented coping and work-family balance on this relationship. Methods Four hundred thirty-five female medical workers were recruited to perform a perceived stress scale, future-oriented coping inventory, work-family balance scale and turnover intention scale. Meanwhile, serial multiple mediation analysis was performed using PROCESS. Results 1) Perceived stress positively predicted the level of turnover intention in female healthcare staff; 2) Preventive coping and proactive coping showed mediation effects on the relationship between perceived stress and turnover intention, and preventive coping positively related to proactive coping; 3) The work-family balance also showed mediation effects on the relationship between perceived stress and turnover intention; 4) Preventive coping, proactive coping and work-family balance showed a serial multiple mediation on the relationship between perceived stress and turnover intention in female healthcare workers. Conclusions Perceived stress affects the level of turnover intention in female healthcare staff through preventive coping, proactive coping, and work-family balance. In addition, the sequential model of future-oriented coping was validated among female healthcare staff.

Abstract Background Extrachromosomal circular DNAs (eccDNAs) have been reported to play a key role in the occurrence and development of various diseases. However, the characterization and role of eccDNAs in pulmonary arterial hypertension (PAH) remain unclear. Methods In the discovery cohort, we first explored eccDNA expression profiles by Circle-sequencing analysis. The candidate eccDNAs were validated by routine polymerase chain reaction (PCR), TOPO-TA cloning and Sanger sequencing. In the validation cohort, 30 patients with PAH and 10 healthy controls were recruited for qPCR amplification to detect the candidate eccDNAs. Datas at the baseline were collected, including clinical background, biochemical variables, echocardiography and hemodynamic factors. Receiver operating characteristic curve was used to investigate the diagnostic effect of the eccDNA. Results We identified a total of 21,741 eccDNAs in plasma samples of 3 IPAH patients and 3 individuals in good health, and the expression frequency, GC content, length distribution, and genome distribution of the eccDNAs were thoroughly characterized and analyzed. In the validation cohort, 687 eccDNAs were differentially expressed in patients with IPAH compared with healthy controls (screening threshold: |FC|≥2 and P

BackgroudHuman epithelial growth factor receptor 2 (HER2) amplification is an important mechanism of acquired resistance to anti-epidermal growth factor receptor (EGFR) therapy in non-small cell lung cancer (NSCLC) patients. For patients with both EGFR mutation and HER2 amplification, there is currently no unified standard treatment, and further exploration is needed on how to choose the therapy.Methods and resultsA female NSCLC patient developed bone and brain metastases 14 and 42 months after radical surgery, respectively. The second genetic sequencing detected EGFR L858R mutation and HER2 amplification, and therefore initiated treatment with almonertinib and pyrotinib. The patient achieved partial remission and did not show any further progression during the follow-up period.ConclusionFor NSCLC patients with both EGFR mutation and HER2 amplification, the combination of almonertinib and pyrotinib is a valuable therapy that can continuously reduce tumor burden and achieve long-term survival.

This study introduces an innovative thermal management system tailored for cylindrical Lithium-ion batteries. It integrates a tubular thermoelectric generator (TTEG) to handle both battery thermal management and the utilization of waste heat for power generation. The main focus lies in evaluating the waste heat recovery capabilities of the TTEG to enhance effective thermal management. The research investigates key geometric and operational parameters such as battery discharge rate (C-rate), thermocouple count (NTC), heat transfer coefficient (HTC), and thermoelectric leg height (HL) to comprehensively assess the overall system performance. The results highlight that integrating the TTEG improves thermal management and waste heat recovery in lithium-ion batteries. It demonstrates temperature reductions of up to 21 °C at a discharge rate of 3C compared to batteries without the TTEG thermal management system. Additionally, increasing the NTC leads to a rise in the maximum battery temperature, thereby enhancing waste heat recovery performance. For instance, increasing the number of thermocouples from 100 to 144 results in a substantial up to 70 % increase in TTEG voltage.Furthermore, enhancing HTC and HL positively impacts thermal performance, showing a significant decrease in the maximum battery temperature. Elevated HTC and HL also contribute to improving thermoelectric voltage, power, and conversion efficiency, highlighting their dual role in enhancing waste heat recovery. For instance, at peak conditions, there is a notable reduction of 2.66 °C in the maximum battery temperature with an HL of 12 mm compared to 4 mm. Additionally, increasing HTC from 10 to 20, particularly at maximum discharge, leads to a surge of 15.87 % in voltage and a substantial 34.28 % increase in output power.

Background Addressing current health challenges requires the integrated and continuous health care services. The collaboration between primary care providers (PCPs) and medical specialists other than general practice is the most common means of achieving this objective. The patterns and effect of collaborative working between different disciplines has a direct impact on the quality of integrated service delivery, which is critical to improving patient health outcomes. Objective To systematically review the characteristics of studies related to collaboration patterns between PCPs and medical specialists, contents of collaboration patterns and effects reported by the authors by using scoping review methods. Methods On September 3 in 2022, PubMed, EmBase, Web of Science, CNKI, and Wanfang Data Knowledge Service Platform were searched for literature related to collaboration between PCPs and medical specialists from inception to the date of search. The characteristics of literature, collaboration patterns and effects were extracted. The elemental decomposition of collaboration patterns was performed based on Mulave 'Gearing Up' model and the contents of collaboration patterns were integrated and demonstrated using content analysis method. Results A total of 420 relevant papers were included, of which 214 (51.0%) were committed to evaluating the effects of collaboration patterns, but specific contents of collaboration patterns could be extracted from 82 (19.5%) papers. The distinctive characteristics revealed by the extraction of limited information on the details of collaboration patterns included clear and formalized collaboration patterns, evidence-based guidelines/norms support for collaborative service contents, information systems and dedicated coordinators support for the collaboration between PCPs and specialists. Among the 82 papers, a total of 54 (65.9%) papers clearly reported indicators of effect, of which 90.7% (49/54) reported positive impact on service delivery and outcomes, ranging from service provision process, service utilization and health-related outcome indicators, however, higher proportion (90.7%, 49/54) of studies reporting positive effects could not exclude the presence of publication bias. Conclusion When collaboration patterns between PCPs and medical specialists other than general practice are implemented in integrated health services, it is necessary to ensure that approaches and contents of collaboration are specified, as well as the focus on the support of information systems and coordinators. Intervention studies related to health system and policy should emphasize describing the details of intervention design and implementation processes. Methodological quality assessment and meta-analysis are necessary to conduct in future studies on this topic.

Abstract Infectious disease outbreaks transcend the medical and public health realms, triggering widespread panic and impeding socio-economic development. Considering that self-limiting diarrhoea of sporadic cases is usually underreported, the Salmonella outbreak (SO) study offers a unique opportunity for source tracing, spatiotemporal correlation, and outbreak prediction. To summarize the pattern of SO and estimate observational epidemiological indicators, 1,134 qualitative reports screened from 1949 to 2023 were included in the systematic review dataset, which contained a 506-study meta-analysis dataset. In addition to the dataset comprising over 50 columns with a total of 46,494 entries eligible for inclusion in systematic reviews or input into prediction models, we also provide initial literature collection datasets and datasets containing socio-economic and climate information for relevant regions. This study has a broad impact on advancing knowledge regarding epidemic trends and prevention priorities in diverse salmonellosis outbreaks and guiding rational policy-making or predictive modeling to mitigate the infringement upon the right to life imposed by significant epidemics.

Objective To explore the expression of triggering receptor expressed on myeloid cells 2 (TREM2) in high-glucose microglia and to investigate the role of TREM2 in the proliferation, migration and phagocytosis of high-glucose microglia. Methods Microglia cells were divided into control group and high-glucose treatment group(67.5 mmol/L glucose, 24 h). The microglia cells were counted and the expression of Iba1 and TREM2 was detected. TREM2 siRNA was transfected to detect the proliferation and migration of microglia. The amyloid β-peptide (Aβ) with a fluorescent tag was added to observe the phagocytosis of Aβ by microglia. Results Compared to normal microglia, the number of microglia significantly decreased after high-glucose treatment (P＜0.001), while the expression of TREM2 and Iba1 markedly increased (P＜0.001). High glucose and TREM2 did not affect the proliferation of microglia. Compared to the normal group, the migration of microglia significantly decreased after high-glucose treatment (P＜0.05) and TREM2 did not affect the migration ability of high-glucose microglia. Compared to the normal group, the phagocytosis of Aβ by microglia significantly decreased in the high-glucose treated group(P＜0.001). Furthermore, TREM2 knockdown further decreased the phagocytosis of Aβ by high-glucose microglia (P＜0.001). Conclusions The expression of TREM2 in microglia significantly increases after high-glucose treatment, which significantly affects phagocytosis of Aβ by microglia.

This article investigates the safety risks associated with sea ice along the Arctic Route by using polar sea ice images obtained by Gaofen-3 (GF3) Synthetic Aperture Radar (SAR) satellites. We collected three SAR datasets, representative of GF3 satellites' operational modes, and constructed semantic segmentation datasets through meticulous annotation using concurrent optical satellite imagery obtained by Landsat satellites to ensure precision. We propose SI-CTFNet, an innovative sea ice semantic segmentation model that integrates convolutional neural networks (CNNs) and vision transformers (ViTs) for enhanced multiscale feature extraction. SI-CTFNet features a dual-pathway architecture designed to optimize feature extraction, complemented by the BiAFusion module, which effectively merges local and global features to improve decoding accuracy. In addition, we introduce the MSDAM module to facilitate a comprehensive multiscale contextual analysis, addressing the diverse distribution of ice types in the imagery. The model incorporates advanced decoding techniques, including a progressive upsampling approach for the CNN-fusion branch and an efficient All-MLP module for the Transformer branch. Performance evaluations across three distinct datasets reveal that SI-CTFNet significantly outperforms existing methods in key metrics and maintains efficacy with supplementary Sentinel1A C-band satellite data. Furthermore, we present a streamlined variant of SI-CTFNet, which achieves a threefold increase in inference speed with minimal reduction in classification accuracy. The ultimate objective of this work is to advance a precise sea ice forecasting and navigation system for polar regions, aimed at automating sea ice classification within a smart polar shipping framework.

Abstract Direct electrosynthesis of hydrogen peroxide (H2O2) via the two-electron oxygen reduction reaction presents a burgeoning alternative to the conventional energy-intensive anthraquinone process for on-site applications. Nevertheless, its adoption is currently hindered by inferior H2O2 selectivity and diminished H2O2 yield induced by consecutive H2O2 reduction or Fenton reactions. Herein, guided by theoretical calculations, we endeavor to overcome this challenge by activating a main-group Pb single-atom catalyst via a local micro-environment engineering strategy employing a sulfur and oxygen super-coordinated structure. The main-group catalyst, synthesized using a carbon dot-assisted pyrolysis technique, displays an industrial current density reaching 400 mA cm−2 and elevated accumulated H2O2 concentrations (1358 mM) with remarkable Faradaic efficiencies. Both experimental results and theoretical simulations elucidate that S and O super-coordination directs a fraction of electrons from the main-group Pb sites to the coordinated oxygen atoms, consequently optimizing the *OOH binding energy and augmenting the 2e− oxygen reduction activity. This work unveils novel avenues for mitigating the production-depletion challenge in H2O2 electrosynthesis through the rational design of main-group catalysts.

Abstract Palm leaf manuscripts (PLMs) are of great importance in recording Buddhist Scriptures, medicine, history, philosophy, etc. Some damages occur during the use, spread, and preservation procedure. The comprehensive investigation of Sanskrit PLMs is a prerequisite for further conservation and restoration. However, current damage identification and investigation are carried out manually. They require strong professional skills and are extraordinarily time-consuming. In this study, PLM-SegFormer is developed to provide an automated damage segmentation for Sanskrit PLMs based on the SegFormer architecture. Firstly, a digital image dataset of Sanskrit PLMs (the PLM dataset) was obtained from the Potala Palace in Tibet. Then, the hyperparameters for pre-processing, model training, prediction, and post-processing phases were fully optimized to make the SegFormer model more suitable for the PLM damage segmentation task. The optimized segmentation model reaches 70.1% mHit and 51.2% mIoU. The proposed framework automates the damage segmentation of 10,064 folios of PLMs within 12 h. The PLM-SegFormer framework will facilitate the preservation state survey and record of the Palm-leaf manuscript and be of great value to the subsequent preservation and restoration. The source code is available at https://github.com/Ryan21wy/PLM_SegFormer .

Game theory-inspired deep learning using a generative adversarial network provides an environment to competitively interact and accomplish a goal. In the context of medical imaging, most work has focused on achieving single tasks such as improving image resolution, segmenting images, and correcting motion artifacts. We developed a dual-objective adversarial learning framework that simultaneously 1) reconstructs higher quality brain magnetic resonance images (MRIs) that 2) retain disease-specific imaging features critical for predicting progression from mild cognitive impairment (MCI) to Alzheimer’s disease (AD). We obtained 3-Tesla, T1-weighted brain MRIs of participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI, N=342) and the National Alzheimer’s Coordinating Center (NACC, N =190) datasets. We simulated MRIs with missing data by removing 50% of sagittal slices from the original scans (i.e., diced scans). The generator was trained to reconstruct brain MRIs using the diced scans as input. We introduced a classifier into the GAN architecture to discriminate between stable (i.e., sMCI) and progressive MCI (i.e., pMCI) based on the generated images to facilitate encoding of disease-related information during reconstruction. The framework was trained using ADNI data and externally validated on NACC data. In the NACC cohort, generated images had better image quality than the diced scans (Structural similarity (SSIM) index: $0.553 \pm 0.116$ versus $0.348 \pm 0.108$ ). Furthermore, a classifier utilizing the generated images distinguished pMCI from sMCI more accurately than with the diced scans (F1-score: $0.634 \pm 0.019$ versus $0.573 \pm 0.028$ ). Competitive deep learning has potential to facilitate disease-oriented image reconstruction in those at risk of developing Alzheimer’s disease.

Radar echo image sequence prediction is a spatial-temporal forecasting problem, which is one of the main challenges in precipitation nowcasting. In response to issues such as poor extraction of spatiotemporal features and blurred prediction of image sequence in previous models, this paper proposes a spatial-temporal dual discriminator precipitation nowcasting method using SNGAN with InceptionGRU (STD-SNGAN-InceptionGRU). The design of temporal and spatial dual discriminators constrains the generator’s prediction samples, effectively enhancing the spatiotemporal prediction capability of the generator through adversarial training. The generator utilizes multiscale convolution (Inception) and multiscale gate recurrent unit (InceptionGRU) to enhance its ability to extract spatiotemporal features, thereby improving its learning capability for the evolution of radar echo sequences. The comparative experimental results demonstrate that the proposed STD-SNGAN-InceptionGRU model outperforms other algorithms in terms of critical success index (CSI) and probability of detection (POD) at different echo intensities, especially in areas with long time series and high echo intensity. Furthermore, through ablation experiments, this paper proves that the temporal discriminator, spatial discriminator, and InceptionGRU all effectively improve the model’s prediction capability for radar echo images.

BackgroundChronic excessive exposure to fluoride can cause damage to the central nervous system and a certain degree of learning and memory impairment. However, the associated mechanism is not yet clear and further exploration is needed. ObjectiveUsing 4D unlabelled quantitative proteomics techniques to explore differentially expressed proteins and their potential mechanisms of action in chronic excessive fluoride exposure induced brain injury. MethodsTwenty-four SPF-grade adult SD rats, half male and half male, were selected and divided into a control group and a fluoride group by random number table method, with 12 rats in each group. Among them, the control group drank tap water (fluorine content

In response to the shortcomings of current spatiotemporal prediction models, which frequently encounter difficulties in temporal feature extraction and the forecasting of medium to high echo intensity regions over extended sequences, this study presents a novel model for radar echo extrapolation that combines a translator encoder-decoder architecture with a spatiotemporal dual-discriminator conditional generative adversarial network (STD-TranslatorNet). Initially, an image reconstruction network is established as the generator, employing a combination of a temporal attention unit (TAU) and an encoder–decoder framework. Within this architecture, both intra-frame static attention and inter-frame dynamic attention mechanisms are utilized to derive attention weights across image channels, thereby effectively capturing the temporal evolution of time series images. This approach enhances the network’s capacity to comprehend local spatial features alongside global temporal dynamics. The encoder–decoder configuration further bolsters the network’s proficiency in feature extraction through image reconstruction. Subsequently, the spatiotemporal dual discriminator is crafted to encapsulate both temporal correlations and spatial attributes within the generated image sequences. This design serves to effectively steer the generator’s output, thereby augmenting the realism of the produced images. Lastly, a composite multi-loss function is proposed to enhance the network’s capability to model intricate spatiotemporal evolving radar echo data, facilitating a more comprehensive assessment of the quality of the generated images, which in turn fortifies the network’s robustness. Experimental findings derived from the standard radar echo dataset (SRAD) reveal that the proposed radar echo extrapolation technique exhibits superior performance, with average critical success index (CSI) and probability of detection (POD) metrics per frame increasing by 6.9% and 7.6%, respectively, in comparison to prior methodologies.

As to the problems in current tourism recommendation, this paper proposes a tourism recommendation algorithm based on the mobile ICV service platform. Firstly, the ICV service system for the Point of Interest (POI) searching and route recommendation is designed. Secondly, the recommendation service model is set up from two aspects, namely the tourism POI clustering algorithm and the tourism POI searching and route recommendation algorithm. In the aspect of symmetrical-based matching features, the clustered POIs are matched with the tourists’ interests, and the POIs in the neighborhood of the ICV dynamic locations are searched. Then, a POI recommendation algorithm based on the tourists’ interests is constructed, and the POIs that best match the symmetrical interests of the tourists within the dynamic buffer zones of ICV are confirmed. Based on the recommended POIs, the ICV guidance route algorithm is constructed. The experiment verifies the advantages of the proposed algorithm on the aspect of the POI matching tourists’ interests, algorithm stability, traveling time cost, traveling distance cost and computational complexity. As to the iterative sum and the iterative sum average of the POI matching function values, the proposed algorithm has a performance improvement of at least 20.2% and a stability improvement of at least 20.5% compared to the randomly selected POIs in matching tourists’ interests. As to the cost of the guidance routes, the proposed algorithm reduces the average cost by 19.6% compared to the other suboptimal routes. Compared with the control group algorithms, the proposed algorithm is superior in terms of route cost, with an average cost reduction of 13.8% for the output routes compared to the control group. Also, the proposed algorithm is superior in terms of route cost compared to the control group recommendation algorithms, with an average cost reduction of 11.2%.

A focused crawler automatically retrieves, organizes, and extracts specific topic-related information from the internet for analysis and application. Currently, most focused crawlers assess the relevance of web pages to a given topic through methods such as keyword matching, semantic analysis, and link structures. However, these existing focused crawlers suffer from issues such as misleading directions and reduced accuracy due to the lack of semantic analysis of topic terms, as well as biased computation of topic relevance caused by the absence of effective weighting factors. To solve the above-mentioned problems, this study proposes a semantic and optimized focused crawler based on Semantic Graph and Genetic Algorithm. The proposed crawler eliminates ambiguous terms by constructing a semantic graph, optimizes the weighting factors of topic relevance with asymmetry by using a genetic algorithm, and combines both above two points to predict the priority of each unvisited hyperlink. The experiment results indicate that the proposed SG-GA Crawler improves the evaluation indicators compared with the other three focused crawlers, including VSM Crawler, SSRM Crawler, and SG Crawler. More specifically, the percentage improvement achieved by the proposed method exceeds 19%, 19%, and 13% in terms of three evaluation indicators, including the number of relevant web pages, acquisition rate, and average relevance, respectively. In conclusion, the proposed focused crawler can grab more quantity and higher quality topic-related web pages from the Internet.

Small intestinal lipomatosis is a rare condition that presents a diagnostic challenge due to the absence of identifiable clinical symptoms and limitations of small intestine examination methods. Consequently, preoperative diagnosis is difficult and only a limited number of cases have been documented in the scientific literature. Here, we report a rare case of volvulus caused by small intestinal lipomatosis. A 58-year-old female patient was tentatively diagnosed with acute ileus. The whirl sign was detected using abdominal three-dimensional enhanced computed tomography, along with marked local intestinal dilation and multiple irregular fat-like containing lesions. During surgery, abnormal dilation of the small intestine between 80 and 220 cm from the ileocecal valve was detected and the affected intestine displayed a folded and twisted configuration. Examination of the resected intestine showed that the inner wall of the diseased intestinal lumen was covered with more than 100 lipomas of different sizes, the largest of which measured ~8.0 cm in diameter. Based on clinical symptoms alone, it was difficult to identify the cause of intestinal volvulus before surgery. Complete resection of the affected small intestine and subsequent pathological analysis yielded a definitive diagnosis of small intestinal lipomatosis. While small intestinal lipomatosis is a rare condition, prognosis is favorable if diagnosed early and treated appropriately. The application of three-dimensional enhanced computed tomography imaging can aid in accurate diagnosis, while complete resection of the affected small intestine is crucial to improve patient prognosis.

Fluorescence-activated cell sorting (FACS) holds great promise for the separation of single cells or cell populations according to specific light scattering and fluorescent characteristics. Here, we present a new perspective on microfluidic FACS (μFACS) with predictable geometry, which meets the requirements of high-throughput analysis and sorting. Instead of the widely applied elastic polydimethylsiloxane (PDMS), a rigid epoxy resin chip was rapidly fabricated and irreversibly encapsulated to eliminate channel deformation (tenfold reduction) and enhance performance while meeting high pressure (>600 kPa) and high flow rate application scenarios. Fluorescence discrimination and particle differentiation were additionally validated in a self-contained μFACS system using calibration microspheres and mammalian cells. The μFACS chip and system were integrally optimized to achieve a minimum interval (0.58 ms) with a mean flow rate of 1.5 m/s. Ultimately, event recording and automated sorting were accomplished in real time while achieving a sorting efficiency of 87% at cell throughput of 8,000 events/s. This rigid chip for high-throughput μFACS, which is independent of the physical properties of cells could pave the way for cell screening in plasma samples for personalized medicine.

Although serum albumin and neuroticism have revealed a strong association with suicidal ideation in individuals with depression, the causal relationship between them is uncertain. This study analyzed the causal association of serum albumin, neuroticism and suicidal ideation using large-scale GWAS data and Univariable Mendelian Randomization (UVMR) methods. The Multivariable MR (MVMR) analysis was used to explore the causal pathways. UVMR analysis revealed that genetically determined serum albumin is causally associated with neuroticism (β = −0.006 S.D.; 95 % CI: 0.009, −0.002; p = 0.003) and suicidal ideation (β = 0.009 S.D.; 95 % CI: 0.001, 0.016; p = 0.037); and that neuroticism mediates 100 % of the causal association between serum albumin and suicidal ideation in individuals with depression. These findings suggest genetic evidence for the causal effect of serum albumin on suicidal ideation in depressed patients and the significant mediation effect of neuroticism on this causal association. This study proves the protective role of serum albumin for neuroticism and the riskiness of personality traits for suicidal ideation in individuals with depression.

IntroductionPsoriasis is a chronic skin disease characterized by unique scaling plaques. However, during the acute phase, psoriatic lesions exhibit eczematous changes, making them difficult to distinguish from atopic dermatitis, which poses challenges for the selection of biological agents. This study aimed to identify potential diagnostic genes in psoriatic lesions and investigate their clinical significance.MethodsGSE182740 datasets from the GEO database were analyzed for differential analysis; machine learning algorithms (SVM-RFE and LASSO regression models) are used to screen for diagnostic markers; CIBERSORTx is used to determine the dynamic changes of 22 different immune cell components in normal skin lesions, psoriatic non-lesional skin, and psoriatic lesional skin, as well as the expression of the diagnostic genes in 10 major immune cells, and real-time quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry are used to validate results.ResultsWe obtained 580 differentially expressed genes (DEGs) in the skin lesion and non-lesion of psoriasis patients, 813 DEGs in mixed patients between non-lesions and lesions, and 96 DEGs in the skin lesion and non-lesion of atopic dermatitis, respectively. Then 144 specific DEGs in psoriasis via a Veen diagram were identified. Ultimately, UGGT1, CCNE1, MMP9 and ARHGEF28 are identified for potential diagnostic genes from these 144 specific DEGs. The value of the selected diagnostic genes was verified by receiver operating characteristic (ROC) curves with expanded samples. The the area under the ROC curve (AUC) exceeded 0.7 for the four diagnosis genes. RT-qPCR results showed that compared to normal human epidermis, the expression of UGGT1, CCNE1, and MMP9 was significantly increased in patients with psoriasis, while ARHGEF28 expression was significantly decreased. Notably, the results of CIBERSORTx showed that CCNE1 was highly expressed in CD4+ T cells and neutrophils, ARHGEF28 was also expressed in mast cells. Additionally, CCNE1 was strongly correlated with IL-17/CXCL8/9/10 and CCL20. Immunohistochemical results showed increased nuclear expression of CCNE1 in psoriatic epidermal cells relative to normal.ConclusionBased on the performance of the four genes in ROC curves and their expression in immune cells from patients with psoriasis, we suggest that CCNE1 possess higher diagnostic value.

Ageing is an inevitable process that affects various tissues and organs of the human body, leading to a series of physiological and pathological changes. Mechanisms such as telomere depletion, stem cell depletion, macrophage dysfunction, and cellular senescence gradually manifest in the body, significantly increasing the incidence of diseases in elderly individuals. These mechanisms interact with each other, profoundly impacting the quality of life of older adults. As the ageing population continues to grow, the burden on the public health system is expected to intensify. Globally, the prevalence of musculoskeletal system diseases in elderly individuals is increasing, resulting in reduced limb mobility and prolonged suffering. This review aims to elucidate the mechanisms of ageing and their interplay while exploring their impact on diseases such as osteoarthritis, osteoporosis, and sarcopenia. By delving into the mechanisms of ageing, further research can be conducted to prevent and mitigate its effects, with the ultimate goal of alleviating the suffering of elderly patients in the future.

Purpose:Sacroiliac joint dysfunction (SIJD), while being the primary contributor to low back pain, is still disregarded and treated as low back pain. Mulligan’s Mobilization with Movement (MWM) Techniques and Core Stability Exercises (CSE) are often used to treat low back pain. There is not much evidence that it is effective in SIJD. To evaluate the effectiveness of CSE coupled with MWM (CSE + MWM) in the treatment of SIJD.Methods:39 patients with SIJD were recruited and randomly divided into distinct groups as follows: control group (n = 13), CSE group (n = 13) and CSE + MWM group (n = 13). The Numerical Pain Rating Scale (NPRS), the Roland Morris Disability Questionnaire (RMDQ), the Range of Motion (ROM), the Pressure Pain Threshold (PPT) and the pelvic tilt angle asymmetry ratio in the sagittal plane (PTAR) were used to gauge the intervention’s success both before (M0) and after (M1) it. All experimental data were statistically analyzed.Results:The SIJ-related pain metric significantly decreased in both the CSE + MWM group and the CSE group between M0 and M1, as determined by the NPRS and RMDQ. Between M0 and M1, The CSE group’s left axial rotation ROM and lumbar flexion ROM were significantly decreased. The CSE + MWM group’s extension ROM and left lateral flexion ROM both significantly increased between M0 and M1. In the difference variable (M1-M0), the CSE + MWM group substantially outperformed control group in the left lateral flexion ROM and outperformed the CSE group in the left axial rotation ROM.Conclusion:In individuals with SIJD, CSE + MWM is beneficial in lowering pain, disability, and function. Treatment with CSE and MWM approaches for SIJ appears to boost this efficacy.

BackgroundResident physicians at the standardized training stage had undergone significant physical and mental stress during the release of the COVID-19 pandemic restrictions at the end of 2022 in China. This study aimed to investigate the psychological status (including anxiety, depression, somatic symptoms, job burnout, and vicarious trauma) of resident physicians and identify its influencing factors under these special periods.MethodsSurvey was conducted one month after the release of the COVID-19 pandemic restrictions on resident training physicians from a tertiary first-class hospital in Zhejiang, China. Resident physicians completed the psychological status questionnaire. Chi-square tests, Mann–Whitney U tests, and logistic regression analyses were used to estimate the group differences and variable associations.ResultsThe prevalence of anxiety, depression, and somatic discomfort in this study was 20.88, 28.53, and 41.47%, respectively. Female resident physicians were more likely to experience somatic symptoms [adjusted odds ratio (OR) = 2.36, 95% confidence interval (CI): 1.33–4.18]. Resident physicians with problem-focused coping styles were less prone to psychological health issues [depression (adjusted OR = 0.92, 95% CI: 0.88–0.96), anxiety (adjusted OR = 0.94, 95% CI: 0.90–0.98), somatic symptoms (adjusted OR = 0.93, 95% CI: 0.89–0.97), job burnout (adjusted OR = 0.91, 95% CI: 0.87–0.96) and vicarious trauma (adjusted OR = 0.94, 95% CI: 0.90–0.98)]. Inversely, resident physicians with emotion-focused coping styles and experienced negative life events were more prone to psychological health issues.ConclusionResident training physicians had a high risk of anxiety, depression, and somatic symptoms under the special COVID-19 pandemic restriction release period. Females, with lower training stages, degrees, negative life events, and emotion-focused coping styles had a disadvantaged effect on psychological status. The medical teaching management department needs to monitor and reduce the workload and working hours of resident physicians, ensure sufficient sleep time, and pay attention to the psychological status of resident physicians. By strengthening regular communication and mental health education or intervention, which can help them improve their ability to cope with complex tasks.