ObjectiveTo address the key challenges in breast electrical impedance tomography (EIT) reconstruction including the severe ill‑posedness of the inverse problem, limited measurement information from the electrodes, low contrast of small lesions, as well as the common drawbacks of traditional reconstruction methods such as boundary blurring, low spatial resolution, and weak small-target detection capability, and to overcome the limitations of existing deep learning approaches namely low training efficiency, insufficient physical consistency, and substantial information loss during the low‑to‑high dimensional mapping process, this study proposes a multi‑scale attention and dynamic sparse mask fusion network (MADS‑Net). The proposed method aims to enhance high‑resolution reconstruction accuracy, small-lesion detectability, noise robustness, and computational efficiency in breast‑screening-oriented EIT, thereby providing a feasible solution for the application of EIT in breast functional imaging. MethodsThe proposed network adopts a strategy of “locate first, reconstruct later”. It realizes adaptive allocation of computational resources through a dynamic mask module, alleviates information loss in the low-to-high dimensional mapping process via a multi-scale attention mechanism, and embeds physical constraints to improve the physical rationality of reconstruction results. The performance of the proposed method was validated through systematic numerical simulations, agar phantom experiments, and porcine tissue experiments. Comparisons were made with mainstream methods including the Gauss-Newton algorithm, convolutional neural networks, U-Net, and Deep D-Bar. The image correlation coefficient (ICC), root mean square error (RMSE), and peak signal-to-noise ratio (PSNR) were adopted as quantitative evaluation metrics. Furthermore, lesion‑level evaluation metrics were introduced to assess the capability of different methods in reconstructing abnormal target boundaries and small‑sized target regions. ResultsExperimental results demonstrate that MADS-Net outperforms all comparison methods across all test scenarios. In numerical simulations, it achieves higher accuracy in target morphology and spatial location recovery as well as better background suppression. In agar phantom experiments, its detection and imaging reliability for small targets is significantly superior to the comparison methods. In porcine tissue experiments, the model maintains good generalization performance and can adapt to complex biological tissue imaging scenarios. Quantitative results show that MADS-Net achieves an average ICC of 0.917 6±0.048 8, an RMSE as low as0.060 6±0.031 6, and a PSNR of (23.893 9±2.685 3) dB. It successfully detects tiny targets as small as 5 mm within a 100 mm diameter sensing field, reduces the total training duration by 23.5% compared with the baseline method, and maintains stable reconstruction performance even under strong noise interference. ConclusionThe results demonstrate that MADS-Net achieves favorable EIT reconstruction performance in numerical simulations, agar phantom experiments, and porcine tissue experiments, even under common practical imaging challenges including low signal-to-noise ratio and blurred tissue boundaries. This study provides a methodological reference for further research on EIT in breast-screening-related scenarios and other medical functional imaging tasks, and also offers a low-cost, radiation-free alternative for breast lesion screening that aligns with the clinical demand for non-invasive diagnostic tools. It should be noted that real clinical breast data have not yet been used for validation in this study, and the clinical applicability of the proposed method requires further investigation. Future work will prioritize collecting multi-center real clinical breast datasets, and further optimize the model’s generalization ability to adapt to individual differences in breast tissue composition to promote its clinical application.

With the change of infectious disease incidence pattern and the development of related technologies, progresses have been made in the research of infectious disease epidemiology. In recent years, due to the change in the requirements of infectious disease prevention and control, the research focus has expanded from common infectious diseases to diseases which have been eliminated or might be eliminated, as well as emerging and re-emerging infectious diseases. Infectious disease data has been characterized by multiple sources and modalities. Along with the rapid development of pathogen detection methods, infectious disease surveillance has shifted from a single disease-targted one to a comprehensive one. Moreover, novel technologies such as multi-omics and artificial intelligence have been applied in infectious disease epidemiology research. The international cooperation in this field has become increasingly crucial, and the revision of the International Health Regulations and the negotiation of pandemic agreement will have a profound impact. In the future, infectious disease epidemiology research will develop with more powerful tools to improve its capabilities.

OBJECTIVE: To prepare clinical-grade human umbilical cord-derived mesenchymal stem cells (hUC-MSC) with high expression of hematopoietic supporting factors and evaluate their stem cell characteristics. METHODS: Fetal umbilical cord tissues were collected from healthy postpartum women during full-term cesarean section. Wharton's jelly was mechanically separated and hUC-MSCs were obtained by explant culture method and enzyme digestion method in an animal serum-free culture system with addition of human platelet lysate. The phenotypic characteristics of hUC-MSCs obtained by two methods were detected by flow cytometry. The differences in proliferation ability between the two groups of hUC-MSCs were identified through CCK-8 assay and colony forming unit-fibroblast (CFU-F) assay. The differences in multilineage differentiation potential between the two groups of hUC-MSCs were identified through induction of adipogenic, osteogenic, and chondrogenic differentiation. The mRNA expression levels of hematopoietic supporting factors such as SCF, IL-3, CXCL12, VCAM1 and ANGPT1 in the two groups of hUC-MSCs were identified by real-time fluorescence quantiative PCR(RT-qPCR). RESULTS: The results of flow cytometry showed that hUC-MSCs obtained by the two methods both expressed high levels of CD73, CD90 and CD105, while lowly expressed CD31, CD45 and HLA-DR. The results of CCK-8 and CFU-F assay showed that the proliferation ability of hUC-MSCs obtained by explant culture method was better than those obtained by enzyme digestion method. The results of the triple lineage differentiation experiment showed that there was no significant difference in multilineage differentiation potential between the two grous of hUC-MSCs. The results of RT-qPCR showed that the mRNA expression levels of hematopoietic supporting factors SCF, IL-3, CXCL12, VCAM1 and ANGPT1 in hUC-MSCs obtained by explant cultrue method were higher than those obtained by enzyme digestion method. CONCLUSION Clinical-grade hUC-MSCs with high expression levels of hematopoietic supporting factors were successfully cultured in an animal serum-free culture system.
Humans ; Mesenchymal Stem Cells/metabolism* ; Umbilical Cord/cytology* ; Cell Differentiation ; Female ; Cell Proliferation ; Cells, Cultured ; Chemokine CXCL12/metabolism* ; Angiopoietin-1/metabolism* ; Vascular Cell Adhesion Molecule-1/metabolism* ; Stem Cell Factor/metabolism* ; Flow Cytometry ; Pregnancy

With the change of infectious disease incidence pattern and the development of related technologies, progresses have been made in the research of infectious disease epidemiology. In recent years, due to the change in the requirements of infectious disease prevention and control, the research focus has expanded from common infectious diseases to diseases which have been eliminated or might be eliminated, as well as emerging and re-emerging infectious diseases. Infectious disease data has been characterized by multiple sources and modalities. Along with the rapid development of pathogen detection methods, infectious disease surveillance has shifted from a single disease-targted one to a comprehensive one. Moreover, novel technologies such as multi-omics and artificial intelligence have been applied in infectious disease epidemiology research. The international cooperation in this field has become increasingly crucial, and the revision of the International Health Regulations and the negotiation of pandemic agreement will have a profound impact. In the future, infectious disease epidemiology research will develop with more powerful tools to improve its capabilities.

This study explored the potential therapeutic targets and mechanisms of Danggui Shaoyao San(DSS) in the prevention and treatment of Alzheimer's disease(AD) through transcriptomics and metabolomics, combined with animal experiments. Fifty male C57BL/6J mice, aged seven weeks, were randomly divided into the following five groups: control, model, positive drug, low-dose DSS, and high-dose DSS groups. After the intervention, the Morris water maze was used to assess learning and memory abilities of mice, and Nissl staining and hematoxylin-eosin(HE) staining were performed to observe pathological changes in the hippocampal tissue. Transcriptomics and metabolomics were employed to sequence brain tissue and identify differential metabolites, analyzing key genes and metabolites related to disease progression. Reverse transcription-quantitative polymerase chain reaction(RT-qPCR) was employed to validate the expression of key genes. The Morris water maze results indicated that DSS significantly improved learning and cognitive function in scopolamine(SCOP)-induced model mice, with the high-dose DSS group showing the best results. Pathological staining showed that DSS effectively reduced hippocampal neuronal damage, increased Nissl body numbers, and reduced nuclear pyknosis and neuronal loss. Transcriptomics identified seven key genes, including neurexin 1(Nrxn1) and sodium voltage-gated channel α subunit 1(Scn1a), and metabolomics revealed 113 differential metabolites, all of which were closely associated with synaptic function, oxidative stress, and metabolic regulation. RT-qPCR experiments confirmed that the expression of these seven key genes was consistent with the transcriptomics results. This study suggests that DSS significantly improves learning and memory in SCOP model mice and alleviates hippocampal neuronal pathological damage. The mechanisms likely involve the modulation of synaptic function, reduction of oxidative stress, and metabolic balance, with these seven key genes serving as important targets for DSS in the treatment of AD.
Animals ; Alzheimer Disease/genetics* ; Male ; Drugs, Chinese Herbal/administration & dosage* ; Mice ; Mice, Inbred C57BL ; Metabolomics ; Transcriptome/drug effects* ; Maze Learning/drug effects* ; Hippocampus/metabolism* ; Humans ; Disease Models, Animal ; Memory/drug effects*

ObjectiveThe proteome of biological evidence contains rich genetic information, namely single amino acid polymorphisms (SAPs) in protein sequences. However, due to the lack of efficient and convenient analysis tools, the application of SAP in public security still faces many challenges. This paper aims to meet the application requirements of SAP analysis for forensic biological evidence’s proteome data. MethodsThe software is divided into three modules. First, based on a built-in database of common non-synonymous single nucleotide polymorphisms (nsSNPs) and SAPs in East Asian populations, the software integrates and annotates newly identified exonic nsSNPs as SAPs, thereby constructing a customized SAP protein sequence database. It then utilizes a pre-installed search engine—either pFind or MaxQuant—to perform analysis and output SAP typing results, identifying both reference and variant types, along with their corresponding imputed nsSNPs. Finally, SAPTyper compares the proteome-based typing results with the individual’s exome-derived nsSNP profile and outputs the comparison report. ResultsSAPTyper accepts proteomic DDA mass spectrometry raw data (DDA acquisition mode) and exome sequencing results of nsSNPs as input and outputs the report of SAPs result. The pFind and Maxquant search engines were used to test the proteome data of 2 hair shafts of2 individuals, and both obtained SAP results. It was found that the results of the Maxquant search engine were slightly less than those of pFind. This result shows that SAPTyper can achieve SAP fingding function. Moreover, the pFind search engine was used to test the proteome data of 3 hair shafts from 1 European person and 1 African person in the literature. Among the sites fully matched by the literature method, sites detected by SAPTyper are also included; for semi-matching sites, that is, nsSNPs are heterozygous, both literature method and SAPTyper method had the risk of missing detection for one type of the allele. Comparing the analysis results of SAPTyper with the SAP test results reported in the literature, it was found that some imputed nsSNP sites identified by the literature method but not detected by SAPTyper had a MAF of less than 0.1% in East Asian populations, and therefore they were not included in the common nsSNP database of East Asian populations constructed by this software. Since the database construction of this software is based on the genetic variation information of East Asian populations, it is currently unable to effectively identify representative unique common variation sites in European or African populations, but it can still identify SAP sites shared by these populations and East Asian populations. ConclusionAn automated SAP analysis algorithm was developed for East Asian populations, and the software named SAPTyper was developed. This software provides a convenient and efficient analysis tool for the research and application of forensic proteomic SAP and has important application prospects in individual identification and phenotypic inference based on SAP.

Traditional Chinese Medicine (TCM), as a treasure of the Chinese nation, plays a significant role in maintaining public health. In 2019, the Central Committee of the Communist Party of China and the State Council proposed for the first time the establishment of a TCM registration and evaluation evidence system that integrates TCM theory, "personal experience" and clinical trials (referred to as the "Three-in-One" System) to promote the inheritance and innovation of TCM. Subsequently, the National Medical Products Administration issued several guiding principles to advance the improvement and implementation of this system. Owing to the complexity of its implementation, there are still differing understandings within the TCM industry regarding the positioning of the "Three-in-One" Registration and Evaluation Evidence System, as well as the connotation and value orientation of the "personal experience." To address this, Academician WANG Qi, President of the TCM Association, China International Exchange and Promotion Association for Medical and Healthcare and TCM master, led a group of academicians, TCM masters, TCM pharmacology experts and clinical TCM experts to convene a "Seminar on Promoting the Implementation of the ′Three-in-One′ Registration and Evaluation Evidence System for Chinese Medicinals." Through extensive discussions, an expert consensus was formed, clarifying the different roles of the TCM theory, "personal experience" and clinical trials within the system. It was further emphasized that the "personal experience" is the core of this system, and its data should be derived from clinical practice scenarios. In the future, the improvement of this system will require collaborative efforts across multiple fields to promote the high-quality development of the Chinese medicinal industry.

Klebsiella pneumoniae,as a clinically prevalent opportunistic pathogen,ranks as the second most com-monly detected pathogen in clinical isolates in China.The extensive clinical use of carbapenem antibiotics has led to a high global detection rate of carbapenem-resistant K.pneumoniae(CRKP).Characterized by complex resist-ance mechanisms and diverse evolutionary pathways,CRKP infections pose significant challenges in prevention and treatment,with high associated mortality rates,creating substantial obstacles for clinical anti-infective therapy.In recent years,the emergence and global spread of carbapenem-resistant hypervirulent K.pneumoniae(CR-hvKP)have escalated into a major public health threat.Notably,hypervirulent K.pneumoniae isolates carry-ing carbapenem resistance genes are rapidly disseminating worldwide,causing fatal infections even in immunocom-petent individuals.This article systematically reviews the latest research advances on the resistance mechanisms,evolutionary pathways,adaptive changes,and clinical management strategies of CR-hvKP,aiming to deepen un-derstanding of this"superbug"and provide a theoretical foundation for clinical prevention and control.

Klebsiella pneumoniae,as a clinically prevalent opportunistic pathogen,ranks as the second most com-monly detected pathogen in clinical isolates in China.The extensive clinical use of carbapenem antibiotics has led to a high global detection rate of carbapenem-resistant K.pneumoniae(CRKP).Characterized by complex resist-ance mechanisms and diverse evolutionary pathways,CRKP infections pose significant challenges in prevention and treatment,with high associated mortality rates,creating substantial obstacles for clinical anti-infective therapy.In recent years,the emergence and global spread of carbapenem-resistant hypervirulent K.pneumoniae(CR-hvKP)have escalated into a major public health threat.Notably,hypervirulent K.pneumoniae isolates carry-ing carbapenem resistance genes are rapidly disseminating worldwide,causing fatal infections even in immunocom-petent individuals.This article systematically reviews the latest research advances on the resistance mechanisms,evolutionary pathways,adaptive changes,and clinical management strategies of CR-hvKP,aiming to deepen un-derstanding of this"superbug"and provide a theoretical foundation for clinical prevention and control.

Objective:To investigate the effects of sarcopenia on therapeutic response and prognosis of newly diagnosed acute myeloid leukemia(AML)patients,and reveal its predictive value for the clinical outcomes of AML patients.Methods:A total of 122 AML patients who were initially diagnosed and treated with induction chemotherapy at the Department of Hematology in the Affiliated Hospital of Nantong University from January 2017 to December 2020 were included in this study.The sarcopenia was diagnosed by measuring body composition parameters with multifrequency bioelectrical impedance analyzer,and all AML patients were divided into sarcopenia and non-sarcopenia groups.Kaplan-Meier curves and log-rank test were used to compare the survival difference between the two groups.The relationship between sarcopenia and overall survival(OS)of AML patients was further determined by the univariate and multivariate Cox regression analysis.Results:Among 122 AML patients,46(37.7％)were diagnosed with sarcopenia before induction chemotherapy.The body mass index(BMI)of patients with sarcopenia was significantly lower than that of non-sarcopenia patients(t=4.258,P＜0.001),and the complete response(CR)and partial response(PR)rates of sarcopenia patients after induction chemotherapy were significantly lower than those of non-sarcopenia patients(x2=6.348,P=0.042).Kaplan-Meier curves showed that sarcopenic patients had a shorter OS than non-sarcopenic patients,and the median OS of the two groups were 20.7(95％CI:12.6-27.8)months and 27.8(95％CI:22.3-31.9)months,respectively(x2=5.659,P=0.017).Subgroup analysis indicated that the median OS of sarcopenic and non-sarcopenic AML patients who received standard induction chemotherapy were 12.2(95％CI:5.4-24.7)months and 26.1(95％CI:16.7-35.4)months,respectively(x2=3.949,P=0.047).The multivariate Cox regression analysis revealed that sarcopenia(HR=1.671,95％CI:1.034-2.701,P=0.036)was an independent predictor for poor prognosis in AML patients.Conclusion:Sarcopenia is significantly associated with low response rate of induction chemotherapy and poor prognosis in AML patients,and it might be an useful tool for predicting the clinical outcome of AML patients.