Numerous studies have shown that depression is main-ly associated with the abnormal expression of connexin 43(Cx43)in astrocytes(Astro)and its mediated dysfunction of gap junction(GJ).However,the molecular mechanism of post-translational modifications targeting Cx43 to regulate neuroin-flammation-associated depression is still unclear.Post-transla-tional modifications of Cx43 mainly include phosphorylation of specific amino acid sites by PKC,PKA,PKG,MAPK and PTK,and protein degradation of Cx43 through the K48/K63 polyubiq-uitylation and deubiquitination pathways,which ultimately lead to protein degradation through K48/K63 polyubiquitination and deubiquitination.These modifications are ultimately involved in the regulation of neuroinflammatory responses through the associ-ation of GJ function.In this paper,we systematically review the role of Cx43 post-translational modifications in neuroinflamma-tion,with the aim of further exploring the potential application of targeting these modifications to modulate the inflammatory re-sponse mechanism in improving depressive symptoms.

AIM To investigate the effects of Liangxue Heying Formula-medicated serum(LXHY-MS)on human umbilical vein endothelial cells(HUVECs)induced by lipopolysaccharide(LPS).METHODS CCK-8,DCFH-DA fluorescence probe and Western blot method were used to screen the LPS concentration in modeling and the serum LXHY concentration for treatment.The HUVECs divided into the normal group,the model group and the LXHY-MS group had their SOD activity detected by automatic biochemical analyzer;their MDA level detected by colorimetry;their protein expressions of ICAM-1,VCAM-1,IL-6,TNF-α,p-JAK2 and p-STAT3 detected by Western blot;and their mROS expression and recruitment effect on THP-1 photographed with high connotation.With the use of JAK2/STAT3 pathway inhibitor(AG490),the HUVECs divided into the normal group,the AG490 group,the LPS group,the LPS+AG490 group,the LPS+LXHY-MS group,and LPS+LXHY-MS+AG490 group were subjected to the corresponding treatment,followed by the detection of their protein expressions of ICAM-1,VCAM-1,IL-6,TNF-α,p-JAK2 and p-STAT3 by Western blot.RESULTS Compared with the normal group,the model group displayed decreased SOD activity(P＜0.01),increased MDA level(P＜0.05),increased ICAM-1,VCAM-1,IL-6,TNF-α,p-JAK2,p-STAT3 protein expressions(P＜0.05,P＜0.01),and increased mROS expression and THP-1 cells recruitment.Compared with the model group,the LXHY-MS group shared increased SOD activity(P＜0.05),decreased MDA level(P＜0.01),decreased ICAM-1,VCAM-1,IL-6,TNF-α,p-JAK2,p-STAT3 protein expressions(P＜0.05,P＜0.01),reduced mROS expression and THP-1 cells recruitment.Given the use of AG490,the model group displayed increased protein expressions of ICAM-1,VCAM-1,IL-6,TNF-α,p-JAK2 and p-STAT3 in contrast to the normal group(P＜0.05,P＜0.01);each intervened group showed decreased expressions of related proteins in contrast to the model group(P＜0.05,P＜0.01).CONCLUSION LXHY-MS may protect the injury due to the activation of HUVECs by inhibiting the JAK2/STAT3 signaling pathway.

Objective To explore the predictive efficacy of several multimodal MRI-based machine learning models for the promoter methylation states of O6-methylguanine-DNA methyltransferase(MGMT)of glioblastoma muliforme(GBM)patients in terms of the GBM heterogeneity and the complexity of the tumor microenvironment.Methods Firstly,the multimodal MRI images of 317 GBM patients from The University of Pennsylvania Glioblastoma(UPENN-GBM)dataset were pre-processed,with four sequences involved in including T1-weighted imaging(T1WI)sequence,T1-weighted contrast-enhanced imaging(T1CE)sequence,T2-weighted imaging(T2WI)sequence and fluid-attenuated inversion recovery(FLAIR)sequence,and the radiomics features were extracted for two regions of interest(ROIs)such as the tumor core region and the tumor edema region.Secondly,the data of the 317 GBM patients were randomly divided into a training set(254 cases)and a test set(63 cases),which underwent normalization with Z-scores and feature selection and dimensionality reduction with Lasso regression.Finally,three models were established respectively with particle swarm optimization-support vector machine(PSO-SVM),C-support vector classification(C-SVC)and adaptive boosting(adaptive boosting(Adaboost)algorithms,and the predictive efficacy of the three models for glioblastoma multiforme MGMT promoter methylation states were evaluated in terms of accuracy and AUC.Results The Adaboost model based on T2WI sequence and radiomics features of the tumor core region had the highest predictive efficacy with accuracy and AUC values of 67％and 0.74,respectively,higher than those of other combinations of sequences,models and regions of interest.Conclusion The multimodal MRI-based machine learning models can be used for the prediction of glioblastoma multiforme MGMT promoter methylation states,which provides powerful support for personalized treatment and prognostic assessment of GBM.[Chinese Medical Equipment Journal,2025,46(6):7-13]

Objective To explore the clinical effect of 3D-printed interbody fusion cage applied in anterior cervical decompression and bone graft fusion for the treatment of cervical spondylotic myelopathy.Methods A total of 100 patients with cervical spondylotic myelopathy who underwent anterior cervical fusion surgery in our hospital from June 2020 to June 2023 were selected as the research subjects,they were randomly divided into the 3D group and the control group according to the random number table method,with 50 cases in each group.Patients in the 3D group were implanted with a 3D-printed interbody fusion cage which was made of microporous metal materials,while patients in the control group were implanted with intervertebral fusion cage which was made of polyetheretherketone material.The surgery-related indicators,cervical imaging parameters,cervical spinal cord function,cervical axial function and surgical complications of patients between the two groups were compared.Results There was no statistically significant difference in the operation time,intraoperative blood loss or length of hospital stay of patients between the two groups(P>0.05).The height of the cervical fusion segments and the Cobb angle of the fusion segments of patients in both groups at each time point after the operation were significantly increased compared with those before the operation(P<0.05).The height of the cervical fusion segments and the Cobb angle of the fusion segments of patients 1 month,3 months,and 6 months after the operation in the 3D group were all greater than those in the control group(P>0.05).The subjective symptom score and the total score of the Japanese orthopaedic association(JOA)of patients 6 months after the operation in the 3D group were higher than those in the control group(P<0.05).The cervical axial function of patients 6 months after the operation in the 3D group was better than that in the control group(P<0.05).The incidence of surgical complications in the 3D group was lower than that in the control group(P<0.05).Conclusion The use of 3D-printed interbody fusion cage during the anterior cervical decompression and bone graft fusion for patients with cervical spondylotic myelopathy can significantly improve the clinical symptoms of patients,achieve better cervical axial function,and have fewer complications.

Numerous studies have shown that depression is main-ly associated with the abnormal expression of connexin 43(Cx43)in astrocytes(Astro)and its mediated dysfunction of gap junction(GJ).However,the molecular mechanism of post-translational modifications targeting Cx43 to regulate neuroin-flammation-associated depression is still unclear.Post-transla-tional modifications of Cx43 mainly include phosphorylation of specific amino acid sites by PKC,PKA,PKG,MAPK and PTK,and protein degradation of Cx43 through the K48/K63 polyubiq-uitylation and deubiquitination pathways,which ultimately lead to protein degradation through K48/K63 polyubiquitination and deubiquitination.These modifications are ultimately involved in the regulation of neuroinflammatory responses through the associ-ation of GJ function.In this paper,we systematically review the role of Cx43 post-translational modifications in neuroinflamma-tion,with the aim of further exploring the potential application of targeting these modifications to modulate the inflammatory re-sponse mechanism in improving depressive symptoms.

Eight compounds were isolated and purified from the ethyl acetate part of 70% acetone extract of Rehmannia glutinosa by various chromatographic techniques such as silica gel, MCI gel CHP-20, ODS, Toyopearl HW-40C, combined with TLC and semi-preparative HPLC. Their structures were elucidated by modern spectroscopy techniques (NMR, MS, UV, IR), and identified as neomartynoside A (1), osmanthuside B₆ (2), martynoside (3), isomartynoside (4), (E)-p-hydroxycinnamic acid (5), caffeic acid (6), ferulic acid (7), and methyl caffeate (8). Compound 1 is a new phenylethanol glycoside, which was identified as neomartynoside A. Compound 2 was isolated from Rehmannia glutinosa for the first time. In addition, compounds 2, 6 and 7 significantly increased relative glucose consumption, showing potential hypoglycemic activity.

ObjectiveThe rapid advancement of bioanalytical technologies has heightened the demand for high-throughput, label-free, and real-time cellular analysis. Electrochemical impedance spectroscopy (EIS) operating in the GHz frequency range (GHz-EIS) has emerged as a promising tool for characterizing cell suspensions due to its ability to rapidly and non-invasively capture the dielectric properties of cells and their microenvironment. Although GHz-EIS enables rapid and label-free detection of cell suspensions, significant challenges remain in interpreting GHz impedance data for complex samples, limiting the broader application of this technique in cellular research. To address these challenges, this study presents a novel method that integrates GHz-EIS with deep learning algorithms, aiming to improve the precision of cell suspension concentration identification and quantification. This method provides a more efficient and accurate solution for the analysis of GHz impedance data. MethodsThe proposed method comprises two key components: dielectric property dataset construction and backpropagation (BP) neural network modeling. Yeast cell suspensions at varying concentrations were prepared and separately introduced into a coaxial sensor for impedance measurement. The dielectric properties of these suspensions were extracted using a GHz-EIS dielectric property extraction method applied to the measured impedance data. A dielectric properties dataset incorporating concentration labels was subsequently established and divided into training and testing subsets. A BP neural network model employing specific activation functions (ReLU and Leaky ReLU) was then designed. The model was trained and tested using the constructed dataset, and optimal model parameters were obtained through this process. This BP neural network enables automated extraction and analytical processing of dielectric properties, facilitating precise recognition of cell suspension concentrations through data-driven training. ResultsThrough comparative analysis with conventional centrifugal methods, the recognized concentration values of cell suspensions showed high consistency, with relative errors consistently below 5%. Notably, high-concentration samples exhibited even smaller deviations, further validating the precision and reliability of the proposed methodology. To benchmark the recognition performance against different algorithms, two typical approaches—support vector machines (SVM) and K-nearest neighbor (KNN)—were selected for comparison. The proposed method demonstrated superior performance in quantifying cell concentrations. Specifically, the BP neural network achieved a mean absolute percentage error (MAPE) of 2.06% and an R² value of 0.997 across the entire concentration range, demonstrating both high predictive accuracy and excellent model fit. ConclusionThis study demonstrates that the proposed method enables accurate and rapid determination of unknown sample concentrations. By combining GHz-EIS with BP neural network algorithms, efficient identification of cell concentrations is achieved, laying the foundation for the development of a convenient online cell analysis platform and showing significant application prospects. Compared to typical recognition approaches, the proposed method exhibits superior capabilities in recognizing cell suspension concentrations. Furthermore, this methodology not only accelerates research in cell biology and precision medicine but also paves the way for future EIS biosensors capable of intelligent, adaptive analysis in dynamic biological research.

Primary ciliary dyskinesia (PCD) is a clinically rare, genetically and phenotypically heterogeneous condition characterized by chronic respiratory tract infections, male infertility, tympanitis, and laterality abnormalities. PCD is typically resulted from variants in genes encoding assembly or structural proteins that are indispensable for the movement of motile cilia. Here, we identified a novel nonsense mutation, c.466G>T, in cilia- and flagella-associated protein 300 ( CFAP300 ) resulting in a stop codon (p.Glu156*) through whole-exome sequencing (WES). The proband had a PCD phenotype with laterality defects and immotile sperm flagella displaying a combined loss of the inner dynein arm (IDA) and outer dynein arm (ODA). Bioinformatic programs predicted that the mutation is deleterious. Successful pregnancy was achieved through intracytoplasmic sperm injection (ICSI). Our results expand the spectrum of CFAP300 variants in PCD and provide reproductive guidance for infertile couples suffering from PCD caused by them.
Adult ; Female ; Humans ; Male ; Pregnancy ; China ; Ciliary Motility Disorders/genetics* ; Codon, Nonsense ; East Asian People/genetics* ; Exome Sequencing ; Homozygote ; Infertility, Male/genetics* ; Kartagener Syndrome/genetics* ; Pedigree ; Sperm Injections, Intracytoplasmic ; Cytoskeletal Proteins/genetics*

OBJECTIVE: This study aimed to explore the association between body mass index (BMI) and mortality based on the 10-year population-based multicenter prospective study. METHODS: A general population-based multicenter prospective study was conducted at four sites in rural China between 2013 and 2023. Multivariate Cox proportional hazards models and restricted cubic spline analyses were used to assess the association between BMI and mortality. Stratified analyses were performed based on the individual characteristics of the participants. RESULTS: Overall, 19,107 participants with a sum of 163,095 person-years were included and 1,910 participants died. The underweight (< 18.5 kg/m ²) presented an increase in all-cause mortality (adjusted hazards ratio [ aHR] = 2.00, 95% confidence interval [ CI]: 1.66-2.41), while overweight (≥ 24.0 to < 28.0 kg/m ²) and obesity (≥ 28.0 kg/m ²) presented a decrease with an aHR of 0.61 (95% CI: 0.52-0.73) and 0.51 (95% CI: 0.37-0.70), respectively. Overweight ( aHR = 0.76, 95% CI: 0.67-0.86) and mild obesity ( aHR = 0.72, 95% CI: 0.59-0.87) had a positive impact on mortality in people older than 60 years. All-cause mortality decreased rapidly until reaching a BMI of 25.7 kg/m ² ( aHR = 0.95, 95% CI: 0.92-0.98) and increased slightly above that value, indicating a U-shaped association. The beneficial impact of being overweight on mortality was robust in most subgroups and sensitivity analyses. CONCLUSION This study provides additional evidence that overweight and mild obesity may be inversely related to the risk of death in individuals older than 60 years. Therefore, it is essential to consider age differences when formulating health and weight management strategies.
Humans ; Body Mass Index ; China/epidemiology* ; Male ; Female ; Middle Aged ; Prospective Studies ; Rural Population/statistics & numerical data* ; Aged ; Follow-Up Studies ; Adult ; Mortality ; Cause of Death ; Obesity/mortality* ; Overweight/mortality*

Acute pancreatitis(AP)is a common digestive disorder associated with moderate to high nutritional risks,necessitating timely nutritional support.Over the past five decades,medical nutrition therapy for AP has undergone a paradigm shift,transitioning from traditional fasting based on the"pancreatic rest theory"to the current emphasis on early enteral feeding to"awaken the gut."Currently,nutritional treatment has become a cornerstone of comprehensive AP management.The European Society for Clinical Nutrition and Metabolism(ESPEN),founded in 1980,is a leading professional organization dedicated to advancing research,clinical practice,and education in clinical nutrition and metabolism.To date,ESPEN has published five evidence-based guidelines on nutritional management in pancreatic diseases.This article reviews the evolution of AP nutritional therapy as outlined in these ESPEN guidelines,highlighting key recommendations and their clinical implications.