With the increasing prevalence of overweight and obesity among children and adolescents in China, pediatric metabolic syndrome has emerged as a significant public health challenge. The Developmental Origins of Health and Disease (DOHaD) theory underscores the critical influence of early environmental factors on lifelong metabolic health. Consequently, maternal nutritional status and physical activity during pregnancy have become key modifiable factors that have attracted considerable attention in recent years. Research indicates exposure to a maternal high-fat diet (HFD) during pregnancy has long-term effects on offspring health, which may be transmitted through placental transit disorder, inflammation, and oxidative stress. Similarly, a high-protein diet (HPD) during pregnancy exhibits a dose- and time-dependent biphasic effect: excessive intake may lead to fetal growth restriction and an increased risk of preterm birth, whereas moderate supplementation may instead reduce the susceptibility of offspring to obesity. Interestingly, caloric restriction (CR) during pregnancy presents a double-edged sword: while it may impair the development of metabolic organs in offspring, moderate CR in metabolically compromised mothers can ameliorate maternal metabolic dysfunction and reprogram oocyte DNA methylation, significantly lowering the risk of metabolic disorders in offspring. Notably, metabolic abnormalities induced by a low-protein diet (LPD) during pregnancy demonstrate lifecycle-accumulative effects and transgenerational inheritance, with offspring exhibiting obesity phenotypes during weaning, insulin resistance in adulthood, and hepatic decompensation in old age, mediated through oocyte epigenetic reprogramming. Additionally, maintaining an optimal micronutrient balance is crucial for the metabolic homeostasis of offspring, as both deficiency and excess can lead to detrimental outcomes. Maternal exercise has been established as a safe and effective non-pharmacological intervention that confers multigenerational metabolic benefits through diverse biological pathways. Maternal metabolic dysregulation represents a critical determinant of offspring metabolic disorders. Regular exercise during gestation exerts protective effects by attenuating maternal systemic inflammation and reducing the incidence of pregnancy-related complications, thereby effectively mitigating fetal overgrowth and metabolic dysfunction. This dual benefit for both mother and offspring underscores the pivotal role of gestational physical activity in promoting long-term metabolic health. The placenta, serving as the exclusive interface for maternal-fetal communication, mediates exercise-induced metabolic programming through enhanced secretion of key regulatory factors (including SOD3, Apelin, ADPN, and Irisin) and promotes the development of vascular networks, collectively optimizing nutrient transport efficiency. The intrauterine period represents a crucial window for epigenetic reprogramming, during which maternal exercise modulates DNA methylation patterns of critical metabolic genes (e.g., Ppargc-1α, Prdm16, Klf4, and Slc23a2) in offspring, thereby enhancing their capacity to resist metabolic disorders. Notably, the regulatory effects of maternal exercise extend beyond the gestational period. Postnatally, exercise-induced modifications in the bioactive components of breast milk and gut microbiota composition contribute to the sustained maintenance of metabolic homeostasis in offspring, establishing a continuum of metabolic protection from prenatal to postnatal stages. This review explores the potential of maternal combined nutrition-exercise interventions, suggesting that such strategies may synergistically enhance transgenerational health benefits through interactions within the metabolic-epigenetic network, thereby outperforming single interventions. Additionally, it examines current research limitations, including controversies surrounding transgenerational mechanisms, sex-specific responses, and undefined dynamic thresholds, while providing directions for future investigations. These findings pave the way for a theoretical foundation for early-life health interventions, potentially offering a more effective strategy for combatting intergenerational metabolic disorders.

AIM To analyze the dynamic change patterns of aflatoxin B1,aflatoxin B2,aflatoxin G1,aflatoxin G2,T-2 toxin and deoxynivalenol contents during the fermentation of Massa Medicata Fermentata.METHODS The analysis was performed on a 40 ℃ thermostatic Waters ACQUITY UPLC HSS T3 column(100 mm×2.1 mm,1.8 μm),with the mobile phase comprising of 0.01％formic acid-[acetonitrile-methanol(1∶1)]flowing at 0.3 mL/min,and electron spray ionization source was adopted in positive ion scanning with multiple reaction monitoring mode.RESULTS Six mycotoxins showed good linear relationships within their own ranges(R2＞0.998 0),whose average recoveries were 76.1％-119.3％with the RSDs of 0.49％-9.27％,and except for deoxynivalenol,their contents demonstrated the trends of growing out of nothing and gradually increasing.CONCLUSION The risk of mycotoxin infection exists in the fermentation of Massa Medicata Fermentata.This simple,efficient,rapid and sensitive method can provide a reference for whole-process monitoring the fermentation process for Massa Medicata Fermentata.

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 therapeutic effect of precise disconnection of pargastric varices guided by endoscopic ultrasound in the treatment of esophagogastric variceal bleeding.Method A retrospective analysis was conducted on 20 patients with cirrhosis esophagogastric variceal bleeding treated with endoscopic ultrasound-guided precise disconnection of pargastric varices from January 1,2024 to December 31,2024.The efficacy was analyzed.Result All 20 patients successfully completed the precise disconnection of pargastric varices under the guidance of endoscopic ultrasound.The injection of tissue gel combined with the placement of spring coils(14 cases)and the injection of tissue gel alone(4 cases)successfully blocked the pargastric varices.All patients did not experience perforation,esophageal and cardia stenosis,massive bleeding,septicemia,or ectopic embolization.One patient who received tissue gel alone had slight bleeding from the pargastric varices after surgery and improved after 3 days of treatment to reduce portal vein pressure.Another one patient who received tissue gel alone had a low-grade fever and normal body temperature after 3 days of anti-infection treatment.Conclusion Precise disconnection of pargastric varices under the guidance of endoscopic ultrasound has a good therapeutic effect on esophagogastric variceal bleeding,with fewer complications such as ectopic embolization,massive bleeding,infection,and perforation.However,close follow-up observation is still needed to address the issue of pargastric varices.

Objective To analyze the risk factors for increased drainage volume after open transforaminal lumbar interbody fusion(TLIF),and to establish a predictive model and then validate it.Methods The clinical data of 680 patients who underwent open TLIF at the General Hospital of Northern Theater Command from January 2016 to December 2019 were collected and the patients were randomly divided into the training group(n=476)and the validation group(n=204).Taking the predictive factors screened out by LASSO regression analysis as independent variables,a multivariate Logistic regression predictive model was constructed.The model was internally validated through the receiver operating characteristic(ROC)curve,Hosmer-Lemeshow goodness-of-fit test,and calibration curve,and its clinical utility was assessed via decision curve analysis(DCA).Results LASSO regression analysis screened out four predictive variables:age,number of surgical segments,operative duration,and intraoperative blood loss.The multivariate Logistic regression predictive model demonstrated that age≥60 years,number of surgical segments≥4,operative duration≥2 hours,and intraoperative blood loss≥200 mL were independent influencing factors for the increased postoperative drainage volume in patients undergoing TLIF(P<0.05).ROC curve analysis revealed an area under the curve(AUC)of 0.816(95%CI:0.798 to 0.867)in the training group and 0.783(95%CI:0.685 to 0.823)in the validation group,indicating that the predictive model had good discriminatory ability.Additionally,the Hosmer-Lemeshow goodness-of-fit test and calibration curve indicated that the predictive model had a good degree of fit,and the predicted probability was basically consistent with the actual probability,demonstrating a good calibration.The DCA results confirmed that this predictive model could be applied in clinical practice.Conclusion The risk factors for increased drainage volume after open TLIF include age,number of surgical segments,operative duration,and intraoperative blood loss.The predictive model established based on these factors demonstrates good performance,and it can be applied in clinical guidance for the selection of drainage tube removal time after TLIF.

The Expert Consensus on Clinical Application of Qinbaohong Zhike Oral Liquid in Treatment of Acute Bronchitis and Acute Attack of Chronic Bronchitis （GS/CACM 337-2023） was released by the China Association of Chinese Medicine on December 13^th， 2023. This expert consensus was developed by experts in methodology， pharmacy， and Chinese medicine in strict accordance with the development requirements of the China Association of Chinese Medicine （CACM） and based on the latest medical evidence and the clinical medication experience of well-known experts in the fields of respiratory medicine （pulmonary diseases） and pediatrics. This expert consensus defines the application of Qinbaohong Zhike oral liquid in the treatment of cough and excessive sputum caused by phlegm-heat obstructing lung， acute bronchitis， and acute attack of chronic bronchitis from the aspects of applicable populations， efficacy evaluation， usage， dosage， drug combination， and safety. It is expected to guide the rational drug use in medical and health institutions， give full play to the unique value of Qinbaohong Zhike oral liquid， and vigorously promote the inheritance and innovation of Chinese patent medicines.

ObjectiveINF2 is a member of the formins family. Abnormal expression and regulation of INF2 have been associated with the progression of various tumors, but the expression and role of INF2 in hepatocellular carcinoma (HCC) remain unclear. HCC is a highly lethal malignant tumor. Given the limitations of traditional treatments, this study explored the expression level, clinical value and potential mechanism of INF2 in HCC in order to seek new therapeutic targets. MethodsIn this study, we used public databases to analyze the expression of INF2 in pan-cancer and HCC, as well as the impact of INF2 expression levels on HCC prognosis. Quantitative real time polymerase chain reaction (RT-qPCR), Western blot, and immunohistochemistry were used to detect the expression level of INF2 in liver cancer cells and human HCC tissues. The correlation between INF2 expression and clinical pathological features was analyzed using public databases and clinical data of human HCC samples. Subsequently, the effects of INF2 expression on the biological function and Drp1 phosphorylation of liver cancer cells were elucidated through in vitro and in vivo experiments. Finally, the predictive value and potential mechanism of INF2 in HCC were further analyzed through database and immunohistochemical experiments. ResultsINF2 is aberrantly high expression in HCC samples and the high expression of INF2 is correlated with overall survival, liver cirrhosis and pathological differentiation of HCC patients. The expression level of INF2 has certain diagnostic value in predicting the prognosis and pathological differentiation of HCC. In vivo and in vitro HCC models, upregulated expression of INF2 triggers the proliferation and migration of the HCC cell, while knockdown of INF2 could counteract this effect. INF2 in liver cancer cells may affect mitochondrial division by inducing Drp1 phosphorylation and mediate immune escape by up-regulating PD-L1 expression, thus promoting tumor progression. ConclusionINF2 is highly expressed in HCC and is associated with poor prognosis. High expression of INF2 may promote HCC progression by inducing Drp1 phosphorylation and up-regulation of PD-L1 expression, and targeting INF2 may be beneficial for HCC patients with high expression of INF2.

Anxiety disorder is a major symptom of autism spectrum disorder (ASD) with a comorbidity rate of ~40%. However, the neural mechanisms of the emergence of anxiety in ASD remain unclear. In our study, we found that hyperactivity of basolateral amygdala (BLA) pyramidal neurons (PNs) in Shank3 InsG3680 knock-in (InsG3680^+/+) mice is involved in the development of anxiety. Electrophysiological results also showed increased excitatory input and decreased inhibitory input in BLA PNs. Chemogenetic inhibition of the excitability of PNs in the BLA rescued the anxiety phenotype of InsG3680^+/+ mice. Further study found that the diminished control of the BLA by medial prefrontal cortex (mPFC) and optogenetic activation of the mPFC-BLA pathway also had a rescue effect, which increased the feedforward inhibition of the BLA. Taken together, our results suggest that hyperactivity of the BLA and alteration of the mPFC-BLA circuitry are involved in anxiety in InsG3680^+/+ mice.
Animals ; Prefrontal Cortex/metabolism* ; Basolateral Nuclear Complex/metabolism* ; Mice ; Anxiety/metabolism* ; Nerve Tissue Proteins/genetics* ; Male ; Gene Knock-In Techniques ; Pyramidal Cells/physiology* ; Mice, Transgenic ; Neural Pathways/physiopathology* ; Mice, Inbred C57BL ; Microfilament Proteins

Patients suffering from nerve injury often experience exacerbated pain responses and complain of memory deficits. The dorsal hippocampus (dHPC), a well-defined region responsible for learning and memory, displays maladaptive plasticity upon injury, which is assumed to underlie pain hypersensitivity and cognitive deficits. However, much attention has thus far been paid to intracellular mechanisms of plasticity rather than extracellular alterations that might trigger and facilitate intracellular changes. Emerging evidence has shown that nerve injury alters the microarchitecture of the extracellular matrix (ECM) and decreases ECM rigidity in the dHPC. Despite this, it remains elusive which element of the ECM in the dHPC is affected and how it contributes to neuropathic pain and comorbid cognitive deficits. Laminin, a key element of the ECM, consists of α-, β-, and γ-chains and has been implicated in several pathophysiological processes. Here, we showed that peripheral nerve injury downregulates laminin β1 (LAMB1) in the dHPC. Silencing of hippocampal LAMB1 exacerbates pain sensitivity and induces cognitive dysfunction. Further mechanistic analysis revealed that loss of hippocampal LAMB1 causes dysregulated Src/NR2A signaling cascades via interaction with integrin β1, leading to decreased Ca²⁺ levels in pyramidal neurons, which in turn orchestrates structural and functional plasticity and eventually results in exaggerated pain responses and cognitive deficits. In this study, we shed new light on the functional capability of hippocampal ECM LAMB1 in the modulation of neuropathic pain and comorbid cognitive deficits, and reveal a mechanism that conveys extracellular alterations to intracellular plasticity. Moreover, we identified hippocampal LAMB1/integrin β1 signaling as a potential therapeutic target for the treatment of neuropathic pain and related memory loss.
Animals ; Laminin/genetics* ; Hippocampus/metabolism* ; Neuralgia/metabolism* ; Cognitive Dysfunction/etiology* ; Male ; Peripheral Nerve Injuries/metabolism* ; Extracellular Matrix/metabolism* ; Integrin beta1/metabolism* ; Pyramidal Cells/metabolism* ; Signal Transduction

In-depth study of the components of polymyxins is the key to controlling the quality of this class of antibiotics. Similarities and variations of components present significant analytical challenges. A two-dimensional (2D) liquid chromatography-mass spectrometr (LC-MS) method was established for screening and comprehensive profiling of compositions of the antibiotic colistimethate sodium (CMS). A high concentration of phosphate buffer mobile phase was used in the first-dimensional LC system to get the components well separated. For efficient and high-accuracy screening of CMS, a targeted method based on a self-constructed high resolution (HR) mass spectrum database of CMS components was established. The database was built based on the commercial MassHunter Personal Compound Database and Library (PCDL) software and its accuracy of the compound matching result was verified with six known components before being applied to genuine sample screening. On this basis, the unknown peaks in the CMS chromatograms were deduced and assigned. The molecular formula, group composition, and origins of a total of 99 compounds, of which the combined area percentage accounted for more than 95% of CMS components, were deduced by this 2D-LC-MS method combined with the MassHunter PCDL. This profiling method was highly efficient and could distinguish hundreds of components within 3 h, providing reliable results for quality control of this kind of complex drugs.