The therapeutic effect of human umbilical cord mesenchymal stem cells (hUCMSCs) combined with intestinal probiotics on the wound healing of diabetic mice and its potential mechanism were explored. A diabetic wound mouse model was established, and 25 male C57BL/6J mice were randomly divided into five groups: blank control group, model group, hUCMSCs treatment group, probiotics treatment group, and hUCMSCs combined with probiotics treatment group. The wound healing conditions were photographed and recorded on days 0, 3, 6, 9, and 12 after modeling, and the differences in wound healing rates among the groups were analyzed. HE and Masson staining were used to observe the histopathological changes and collagen deposition. CD31 immunofluorescence was used to detect angiogenesis. Collagen I immunohistochemistry was used to evaluate the formation of type I collagen. ELISA was used to detect the expression levels of anti-inflammatory factors (Arg1) and pro-inflammatory factors (IL-6, IL-1β, TNF-α) in wounded skin tissue and serum. The results showed that on day 12 after modeling, compared with the other groups, the combined treatment group had the most significant wound contraction and the fastest healing rate. HE and Masson staining showed that the combined treatment group had the fastest epithelialization and the most collagen deposition. Immunofluorescence and immunohistochemistry showed that the combined treatment group had the highest expression levels of CD31 and Collagen I. ELISA results indicated that the combined treatment group had higher expression levels of Arg1 in wound skin tissue and serum than the other groups, while the expression levels of IL-6, IL-1β, and TNF-α were significantly lower. These results suggest that the combined treatment of hUCMSCs and intestinal probiotics can accelerate wound healing in diabetic mice through mechanisms such as promoting angiogenesis, enhancing collagen deposition, and regulating the inflammatory microenvironment. The therapeutic effect was significantly better than that of single treatment, providing a new potential strategy for the clinical treatment of diabetic foot.

Objective To analyze the epidemiological characteristics and incidence trend of mumps in Nantong City from 2016 to 2023, and to provide a basis for scientific prevention and control. Methods Descriptive statistical analysis was conducted on monthly mumps incidence data in Nantong City from 2016 to 2023, and a SARIMA model was constructed to predict the incidence trend. Results A total of 3 928 mumps cases were reported in Nantong City from 2016 to 2023, with an average annual incidence rate of 6.36/100 000. Cases predominantly occurred during April–July and September–December, showing seasonal peaks. The male-to-female ratio was 1.43:1. The cases were concentrated in individuals aged ≤15 years (85.57%), primarily students, children in childcare settings, and scattered children (88.31%). The optimal model constructed by the SPSS Expert Modeler was SARIMA(1,0,0)(0,1,1)₁₂, predicting an epidemic peak of mumps in Nantong City from September to November in the second half of 2024. Conclusion From 2016 to 2023, mumps incidence in Nantong City has shown an overall downward trend with a seasonal bimodal distribution. Males had higher incidence rates than females, and cases were predominantly students, kindergartens and scattered children, highlighting the need to strengthen mumps prevention in schools and childcare institutions. The SARIMA model is suitable for short to medium term prediction of mumps in Nantong City. A minor peak is predicted to occur in the second half of 2024 (September–November). It is necessary to strengthen the epidemic surveillance of mumps and vaccination of age-eligible children.

A 53-year-old female patient was diagnosed as allergic bronchopulmonary aspergillosis in March 2015. The patient was treated with oral glucocorticoid (methylprednisolone 6-20 mg/d for 4.5 years and prednisone 5-20 mg/d over 2 years) for 6.5 years. And patient’s condition was not well controlled. In June 2019, itraconazole was taken for more than one month, and it was discontinued due to adverse reactions such as edema of ankle, face, shoulder and skin pigmentation. The patient suffered from acute ABPA exacerbation repeatedly and disease progression. The levels of serum total immunoglobulin E (TIgE) and Aspergillus fumigatus specific immunoglobulin E (Af-sIgE) were higher. The biological agents were used after full evaluation and informed consent. Omalizumab was given off-label use (600 mg, q4w) in September 2021. After treatment, the patient gradually improved, the acute exacerbation was reduced, the condition was evaluated to be stable, and the dose of prednisone was gradually reduced to 5 mg/d.

Objective:To determine the prevalence of self-reported food allergies among children in the grasslands of North China and to analyze its associated risk factors.Methods:In this study, a cross-sectional epidemiological survey method was used to select children under 14 years old by multi-stage, stratified and random cluster sampling in the grassland ecological area of Zhangbei County, Hebei Province, China from May to July 2018. Face-to-face questionnaires were administered to gather food allergy-related information from the participants. Multivariate logistic regression analysis was used to analyze the risk factors associated with self-reported food allergy.Results:A total of 2 086 children completed the survey. The prevalence of self-reported food allergies was 22.0%(459/2 086). The prevalence of multiple food allergies (≥3 types) was 3.1%(64/2 086) versus 16.3% (341/2 086) for a single food allergy among all children. Mango allergy (6.1%, 127/2 086) was the most common, followed by peach allergy (4.1%, 85/2 086). Children who reported food allergies had a significantly higher prevalence of all 4 atopic disorders (eczema, asthma, allergic rhinitis, and allergic conjunctivitis than those without food allergies(35.73% vs. 20.65%, 5.88% vs. 2.77%, 17.86% vs. 7.38%, 16.78% vs. 10.45%, χ2 =44.663 1, 10.434 3, 45.038 3, 13.728 4, all P<0.001).Significantly associated risk factors of food allergy were found to be pollen allergy ( OR: 2.29; 95% CI: 1.80-2.92) and drug allergy ( OR: 1.53; 95% CI: 1.12-2.09). Conclusions:The prevalence of self-reported food allergies among children in the Zhangbei County area of the North China Grassland was relatively high. Pollen allergy and drug allergy are major risk factors.

AIM To establish a UPLC-MS/MS method for the simultaneous content determination of alisol A,23-acetyl alisol B,alisol A-24-acetate,alisol B,alisol C,23-acetyl alisol C,alisol F,alisol G,atractylenolideⅠ,atractylenolide Ⅱ,atractylenolide Ⅲ,atractylon and ferulic acid in Zexie Decoction.METHODS The analysis was performed on a 30 ℃ thermostatic Waters ACQUITY UPLC HSS C18 column(100 mm×2.1 mm,1.8μm),with the mobile phase comprising of water(containing 0.1％formic acid)-acetonitrile(containing 0.1％formic acid)flowing at 0.3 mL/min in a gradient elution manner,and electron spray ionization source was adopted in positive and negative ion scanning with multiple reaction monitoring mode.RESULTS Thirteen constituents showed good linear relationships within their own ranges(r＞0.999 1),whose average recoveries were 95.05％-103.8％with the RSDs of 1.4％-6.7％.CONCLUSION This simple,rapid and accurate method can provide experimental basis for the quality control of Zexie Decoction.

ObjectiveThe nucleolar protein PES1 (Pescadillo homolog 1) plays critical roles in ribosome biogenesis and cell cycle regulation, yet its involvement in cellular senescence remains poorly understood. This study aimed to comprehensively investigate the functional consequences of PES1 suppression in cellular senescence and elucidate the molecular mechanisms underlying its regulatory role. MethodsInitially, we assessed PES1 expression patterns in two distinct senescence models: replicative senescent mouse embryonic fibroblasts (MEFs) and doxorubicin-induced senescent human hepatocellular carcinoma HepG2 cells. Subsequently, PES1 expression was specifically downregulated using siRNA-mediated knockdown in these cell lines as well as additional relevant cell types. Cellular proliferation and senescence were assessed by EdU incorporation and SA-β-gal staining assays, respectively. The expression of senescence-associated proteins (p53, p21, and Rb) and SASP factors (IL-6, IL-1β, and IL-8) were analyzed by Western blot or qPCR. Furthermore, Northern blot and immunofluorescence were employed to evaluate pre-rRNA processing and nucleolar morphology. ResultsPES1 expression was significantly downregulated in senescent MEFs and HepG2 cells. PES1 knockdown resulted in decreased EdU-positive cells and increased SA‑β‑gal-positive cells, indicating proliferation inhibition and senescence induction. Mechanistically, PES1 suppression activated the p53-p21 pathway without affecting Rb expression, while upregulating IL-6, IL-1β, and IL-8 production. Notably, PES1 depletion impaired pre-rRNA maturation and induced nucleolar stress, as evidenced by aberrant nucleolar morphology. ConclusionOur findings demonstrate that PES1 deficiency triggers nucleolar stress and promotes p53-dependent (but Rb-independent) cellular senescence, highlighting its crucial role in maintaining nucleolar homeostasis and regulating senescence-associated pathways.

ObjectiveIn the realm of forensic science, dust is a valuable type of trace evidence with immense potential for intricate investigations. With the development of DNA sequencing technologies, there is a heightened interest among researchers in unraveling the complex tapestry of microbial communities found within dust samples. Furthermore, striking disparities in the microbial community composition have been noted among dust samples from diverse geographical regions, heralding new possibilities for geographical inference based on microbial DNA analysis. The pivotal role of microbial community data from dust in geographical inference is significant, underscoring its critical importance within the field of forensic science. This study aims to delve deeply into the nuances of fungal community composition across the urban landscapes of Beijing, Fuzhou, Kunming, and Urumqi in China. It evaluates the accuracy of biogeographic inference facilitated by the internal transcribed spacer 2 (ITS2) fungal sequencing while concurrently laying a robust foundation for the operational integration of environmental DNA into geographical inference mechanisms. MethodsITS2 region of the fungal genomes was amplified using universal primers known as 5.8S-Fun/ITS4-Fun, and the resulting DNA fragments were sequenced on the Illumina MiSeq FGx platform. Non-metric multidimensional scaling analysis (NMDS) was employed to visually represent the differences between samples, while analysis of similarities (ANOSIM) and permutational multivariate analysis of variance (PERMANOVA) were utilized to statistically evaluate the dissimilarities in community composition across samples. Furthermore, using Linear Discriminant Analysis Effect Size (LEfSe) analysis to identify and filter out species that exhibit significant differences between various cities. In addition, we leveraged SourceTracker to predict the geographic origins of the dust samples. ResultsAmong the four cities of Beijing, Fuzhou, Kunming and Urumqi, Beijing has the highest species richness. The results of species annotation showed that there were significant differences in the species composition and relative abundance of fungal communities in the four cities. NMDS analysis revealed distinct clustering patterns of samples based on their biogeographic origins in multidimensional space. Samples from the same city exhibited clear clustering, while samples from different cities showed separation along the first axis. The results from ANOSIM and PERMANOVA confirmed the significant differences in fungal community composition between the four cities, with the most pronounced distinctions observed between Fuzhou and Urumqi. Notably, the biogeographic origins of all known dust samples were successfully predicted. ConclusionSignificant differences are observed in the fungal species composition and relative abundance among the cities of Beijing, Fuzhou, Kunming, and Urumqi. Employing fungal ITS2 sequencing on dust samples from these urban areas enables accurate inference of biogeographical locations. The high feasibility of utilizing fungal community data in dust for biogeographical inferences holds particular promise in the field of forensic science.

Artificial intelligence (AI), particularly deep learning, has demonstrated remarkable performance in medical imaging across a variety of modalities, including X-ray, computed tomography (CT), magnetic resonance imaging (MRI), ultrasound, positron emission tomography (PET), and pathological imaging. However, most existing state-of-the-art AI techniques are task-specific and focus on a limited range of imaging modalities. Compared to these task-specific models, emerging foundation models represent a significant milestone in AI development. These models can learn generalized representations of medical images and apply them to downstream tasks through zero-shot or few-shot fine-tuning. Foundation models have the potential to address the comprehensive and multifactorial challenges encountered in clinical practice. This article reviews the clinical applications of both task-specific and foundation models, highlighting their differences, complementarities, and clinical relevance. We also examine their future research directions and potential challenges. Unlike the replacement relationship seen between deep learning and traditional machine learning, task-specific and foundation models are complementary, despite inherent differences. While foundation models primarily focus on segmentation and classification, task-specific models are integrated into nearly all medical image analyses. However, with further advancements, foundation models could be applied to other clinical scenarios. In conclusion, all indications suggest that task-specific and foundation models, especially the latter, have the potential to drive breakthroughs in medical imaging, from image processing to clinical workflows.
Humans ; Artificial Intelligence ; Deep Learning ; Diagnostic Imaging/methods* ; Magnetic Resonance Imaging ; Tomography, X-Ray Computed ; Positron-Emission Tomography

Nonunion of osteoporotic vertebral fractures (OVF), predominantly affecting the elderly, can lead to intractable pain, vertebral collapse, progressive kyphotic deformity, and neurological impairment, significantly compromising patients′ quality of life. There exists considerable debate on diagnosis and management of OVF, encompassing key issues such as clinical diagnosis and staging criteria for nonunion, surgical indications and procedure selection, and postoperative rehabilitation planning. Currently, there lacks standardized clinical guideline and expert consensus on the diagnosis and management of OVF nonunion in China. To address this gap, Minimally Invasive Surgery Group of Chinese Orthopedic Association, Osteoporosis Committee of Chinese Association of Orthopedic Surgeons, Prevention and Rehabilitation Committee for Osteoporosis of Chinese Association of Rehabilitation Medicine and Minimally Invasive Orthopedic Surgery Branch of China Association for Geriatric Care jointly organized domestic experts in spinal surgery, endocrinology, and rehabilitation to formulate the Clinical guideline for the diagnosis and treatment for nonunion of osteoporotic vertebral fractures ( version 2025), based on existing literature and clinical experience and adhering to principles of scientific rigor and practicality. The guideline provided 13 evidence-based recommendations encompassing diagnosis and treatment of OVF nonunion, aiming to standardize its clinical management.

Objective:To identify the relevant factors for the first-course remission of acute myeloid leukemia (AML) and to develop a predictive model as well as assess its predictive capability.Methods:Clinical data of 749 patients newly diagnosed with AML admitted to the Department of Hematology, the First Affiliated Hospital, Zhejiang University, School of Medicine from January 1, 2019, to April 30, 2023, were collected and randomly divided into training and validation sets. Multivariate logistic regression analysis was conducted to determine variables associated with complete remission in the first course of induction therapy, and a predictive model was established based on these variables. The receiver operating characteristic (ROC) curve of the predictive model was plotted, and the area under the curve (AUC) was calculated.Results:The indicators predicting the first remission course included peripheral blood white blood cell count during onset, CBF::MYH11 fusion gene, CEBPA bZIP region mutation, myelodysplastic syndrome-related gene mutation, and induction chemotherapy regimen selection as independent factors for the first remission course. The model’s area under the training and validation curves was 0.738 (95% CI: 0.696-0.780) and 0.726 (95% CI: 0.650-0.801), respectively. The Hosmer-Lemeshow test results yielded P-values of 0.993 and 0.335, respectively. Conclusion:In this study, the developed model demonstrates a strong predictive capability for the efficacy of the first course of patients with AML, providing valuable guidance to clinicians in assessing patient prognosis and selecting appropriate treatment strategies.