Histopathological examination is currently the gold standard for the diagnosis of metabolic associated fatty liver disease （MAFLD）； however， due to its invasiveness， high risks， and low feasibility， application of noninvasive indicators in the staging and classification of MAFLD has become a research hotspot. This article systematically reviews the efficacy of dynamic changes in various noninvasive markers in reflecting histological changes and clinical outcome events in MAFLD patients， in order to provide theoretical support for dynamic monitoring and individualized management of the disease.

ObjectiveTo delineate imaging findings using an imaging platform and investigate the correlation between MRI characteristics of spinal cord atrophy and clinical diagnosis in children with spinal cord injury (SCI). MethodsImaging data of 150 children with SCI admitted to Beijing Bo'ai Hospital, China Rehabilitation Research Center, from January, 2002 to March, 2024 were collected and imported into the imaging platform. The anteroposterior and transverse diameters of the middle part of the spinal cord at the cross-section with the most severe atrophy were measured, and the relevant indicators of the previous normal spinal cord segment were measured as controls; the radiomic features were extracted. Clinical data of the children including gender, age, cause of injury, sensory level, motor level, spinal cord injury level, injury severity and disease course were collected. ResultsSpinal cord atrophy was identified in 81 cases (54%), among which 78 cases (96%) were American Spinal Injury Association Impairment Scale (AIS) grade A and 3 cases (4%) were AIS grade C. The upper boundary of the spinal cord atrophy site strongly correlated with the injury level, motor level and sensory level (r > 0.8, P < 0.001). ConclusionMore than half of children with SCI may develop secondary spinal cord atrophy, the vast majority of whom suffer from complete spinal cord injury; the upper boundary of spinal cord atrophy is correlated with the injury level.

Periodontitis is a chronic inflammatory disease triggered by periodontal pathogens and mediated by immune responses. Traditionally, gingival fibroblasts (GFs) were considered to be primarily responsible for maintaining periodontal matrix homeostasis. However, recent studies reveal that GFs play a significant immunoregulatory role in periodontitis. Through signaling pathways, such as the Toll-like receptor 4 (TLR4) pathway, GFs recognize virulence factors from pathogens, such as Porphyromonas gingivalis, and secrete various inflammatory mediators, thus driving extracellular matrix degradation and osteoclast differentiation. Simultaneously, GFs modulate immune cells, including neutrophils and macrophages, amplifying inflammatory responses and fostering a chronic inflammatory microenvironment. Risk factors, such as hyperglycemia and smoking, exacerbate GFs dysfunction via oxidative stress-mediated activation of the nuclear factor kappa B (NF-κB) pathway and other mechanisms, while inflammation and cellular senescence form a vicious cycle. Senescent GFs further aggravate alveolar bone destruction by activating the mechanistic target of the rapamycin (mTOR) pathway. Therapeutic strategies targeting GFs, such as suppressing NF-κB signaling or modulating mTOR-mediated senescence, may disrupt the link between inflammation and tissue destruction, showing promising therapeutic potential. Future studies should employ advanced technologies such as spatial multi-omics and single-cell proteomics to elucidate the spatial distribution, functional interactomes, and heterogeneity of GFs subsets, in order to deepen our understanding of their roles in periodontitis progression. This review summarizes the multifaceted mechanisms of GFs in periodontitis and explores potential therapeutic strategies targeting GFs, offering novel insights for periodontitis prevention and treatment.

Objective To analyze the status quo and related factors of treatment compliance in elderly patients with advanced gastric cancer complicated with cancer pain. Methods Three hundred and ten elderly patients with advanced gastric cancer from January 2021 to June 2024 were selected, and their general data were collected. Hospital Anxiety and Depression Scale (HADS), Beliefs about Medicines Questionnaire (BMQ), Numerical Rating Scale (NRS) and 8-item Morisky Medication Adherence Scale (MMAS-8) were adopted to investigate the psychological status, necessity of medication belief, degree of cancer pain and treatment compliance. Univariate analysis, correlation analysis and multivariate logistic regression analysis were used to describe and analyze the treatment compliance status and related factors in elderly advanced gastric cancer with cancer pain. Results A total of 310 patients were divided into group A (good compliance, 93 cases), group B (moderate compliance ,102 cases) and group C (poor compliance , 115 cases) by means of compliance degree. There were significant differences in education level , pain duration and intensity and analgesic category (P<0.05). Treatment compliance was associated with education level, analgesic category, psychological status, medication belief and pain degree (P<0.05). The necessity of medication belief and pain duration and degree were influencing factors of treatment compliance. Conclusion The treatment compliance in advanced gastric cancer with cancer pain is poor, and can be affected by the necessity of medication belief and duration and degree of pain.

OBJECTIVE To investigate the potential mechanism of epigallocatechin gallate （EGCG） enhancing the sensitivity of hepatocellular carcinoma （HCC） cells to lenvatinib based on the phosphoinositide 3-kinase （PI3K）/protein kinase B （Akt） signaling pathway. METHODS Five human HCC cell lines （HepG2， Huh-7， SMMC-7721， SNU-368 and SNU-739） were used to evaluate the effects of lenvatinib alone and in combination with EGCG on survival rates， clone number， proliferation rate， invasion number and the expressions of mRNAs and proteins related to the PI3K/Akt signaling pathway. The PI3K activator insulin-like growth factor-1 （IGF-1） was introduced to investigate the effect of activating the PI3K/Akt signaling pathway on the sensitization effect of EGCG. RESULTS Compared with the control group， lenvatinib （10 μmol/L） and different concentrations of EGCG+ lenvatinib （1， 5 and 10 μg/mL EGCG+10 μmol/L lenvatinib） significantly reduced the survival rates and clone numbers of all five HCC cell lines in a dose-dependent manner （P＜0.05）. Lenvatinib （10 μmol/L） and EGCG+lenvatinib （10 μg/mL EGCG+10 μmol/L lenvatinib） also markedly inhibited the proliferation rate and invasion numbers of these cells， and decreased the mRNA expressions of PI3K， Akt， mammalian target of rapamycin （mTOR）， P70S6K and 4EBP， and the phosphorylation levels of PI3K and Akt， as well as the protein expressions of mTOR and B cell lymphoma-2 （Bcl-2） in HepG2 cells or all five HCC cells； conversely， the mRNA and protein expressions of phosphatase and tensin homologue deleted on chromosome 10（PTEN）， and the protein expressions of caspase-3 and cleaved caspase-3 were significantly upregulated， with more pronounced effects observed in the EGCG+lenvatinib group than in the lenvatinib group （P＜0.05）. Compared with the lenvatinib group and the EGCG+lenvatinib group， the clone number， proliferation rate and invasion number of HepG2 cells in the EGCG+lenvatinib+IGF-1 group （10 μg/mL EGCG+10 μmol/L lenvatinib+50 ng/mL IGF-1） were significantly increased （P＜0.05）. CONCLUSIONS EGCG can enhance the sensitivity of HCC cells to lenvatinib， and its underlying mechanism may be related to the inhibition of the activation of PI3K/Akt signaling pathway activation.

Objective To investigate the distribution and antimicrobial resistance profiles of common pathogens isolated from cerebrospinal fluid(CSF)in CHINET program from 2015 to 2021.Methods The bacterial strains isolated from CSF were identified in accordance with clinical microbiology practice standards.Antimicrobial susceptibility test was conducted using Kirby-Bauer method and automated systems per the unified CHINET protocol.Results A total of 14 014 bacterial strains were isolated from CSF samples from 2015 to 2021,including the strains isolated from inpatients(95.3％)and from outpatient and emergency care patients(4.7％).Overall,19.6％of the isolates were from children and 80.4％were from adults.Gram-positive and Gram-negative bacteria accounted for 68.0％and 32.0％,respectively.Coagulase negative Staphylococcus accounted for 73.0％of the total Gram-positive bacterial isolates.The prevalence of MRSA was 38.2％in children and 45.6％in adults.The prevalence of MRCNS was 67.6％in adults and 69.5％in children.A small number of vancomycin-resistant Enterococcus faecium(2.2％)and linezolid-resistant Enterococcus faecalis(3.1％)were isolated from adult patients.The resistance rates of Escherichia coli and Klebsiella pneumoniae to ceftriaxone were 52.2％and 76.4％in children,70.5％and 63.5％in adults.The prevalence of carbapenem-resistant E.coli and K.pneumoniae(CRKP)was 1.3％and 47.7％in children,6.4％and 47.9％in adults.The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)and Pseudomonas aeruginosa(CRPA)was 74.0％and 37.1％in children,81.7％and 39.9％in adults.Conclusions The data derived from antimicrobial resistance surveillance are crucial for clinicians to make evidence-based decisions regarding antibiotic therapy.Attention should be paid to the Gram-negative bacteria,especially CRKP and CRAB in central nervous system(CNS)infections.Ongoing antimicrobial resistance surveillance is helpful for optimizing antibiotic use in CNS infections.

Objective To investigate the antimicrobial resistance of clinical isolates from elderly patients(≥65 years)in major medical institutions across China.Methods Bacterial strains were isolated from elderly patients in 52 hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program during the period from 2015 to 2021.Antimicrobial susceptibility test was carried out by disk diffusion method and automated systems according to the same CHINET protocol.The data were interpreted in accordance with the breakpoints recommended by the Clinical and Laboratory Standards Institute(CLSI)in 2021.Results A total of 514 715 nonduplicate clinical isolates were collected from elderly patients in 52 hospitals from January 1,2015 to December 31,2021.The number of isolates accounted for 34.3％of the total number of clinical isolates from all patients.Overall,21.8％of the 514 715 strains were gram-positive bacteria,and 78.2％were gram-negative bacteria.Majority(90.9％)of the strains were isolated from inpatients.About 42.9％of the strains were isolated from respiratory specimens,and 22.9％were isolated from urine.More than half(60.7％)of the strains were isolated from male patients,and 39.3％isolated from females.About 51.1％of the strains were isolated from patients aged 65-＜75 years.The prevalence of methicillin-resistant strains(MRSA)was 38.8％in 32 190 strains of Staphylococcus aureus.No vancomycin-or linezolid-resistant strains were found.The resistance rate of E.faecalis to most antibiotics was significantly lower than that of Enterococcus faecium,but a few vancomycin-resistant strains(0.2％,1.5％)and linezolid-resistant strains(3.4％,0.3％)were found in E.faecalis and E.faecium.The prevalence of penicillin-susceptible S.pneumoniae(PSSP),penicillin-intermediate S.pneumoniae(PISP),and penicillin-resistant S.pneumoniae(PRSP)was 94.3％,4.0％,and 1.7％in nonmeningitis S.pneumoniae isolates.The resistance rates of Klebsiella spp.(Klebsiella pneumoniae 93.2％)to imipenem and meropenem were 20.9％and 22.3％,respectively.Other Enterobacterales species were highly sensitive to carbapenem antibiotics.Only 1.7％-7.8％of other Enterobacterales strains were resistant to carbapenems.The resistance rates of Acinetobacter spp.(Acinetobacter baumannii 90.6％)to imipenem and meropenem were 68.4％and 70.6％respectively,while 28.5％and 24.3％of P.aeruginosa strains were resistant to imipenem and meropenem,respectively.Conclusions The number of clinical isolates from elderly patients is increasing year by year,especially in the 65-＜75 age group.Respiratory tract isolates were more prevalent in male elderly patients,and urinary tract isolates were more prevalent in female elderly patients.Klebsiella isolates were increasingly resistant to multiple antimicrobial agents,especially carbapenems.Antimicrobial resistance surveillance is helpful for accurate empirical antimicrobial therapy in elderly patients.

Objective To construct a model for predicting the risk of essential hypertension accompanied by left ventricular hypertrophy using machine learning algorithms based on pulse diagram parameters;To explore its clinical application value.Methods A total of 295 patients with essential hypertension who were hospitalized in Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine,Shanghai Hospital of Traditional Chinese Medicine and Shanghai Hospital of Integrated Traditional Chinese and Western Medicine were selected from July 2020 to May 2021 and July 2023 to July 2024.According to the echocardiographic results,the selected research subjects were divided into the essential hypertension with left ventricular hypertrophy group(referred to as the"LVH group")and the essential hypertension without left ventricular hypertrophy group(referred to as the"non-LVH group").The general data and clinical biochemical indicators were collected,and the pulse diagram parameters of the patients were detected using the SMART-I type TCM digital pulse analyzer.A clinical prediction model was constructed based on decision tree,support vector machine and extreme gradient boosting model algorithms.The predictive performance of the model was evaluated in terms of discrimination,calibration and clinical prediction ability by using the receiver operating characteristic(ROC)curve,calibration curve and decision curve analysis respectively.The influence of each predictive factor on the risk of LVH in essential hypertension was explained based on the SHAP algorithm.Results Compared with the non-LVH group,the BMI,the proportion of males,drinkers and smokers was lower in the LVH group,with statistical significance(P<0.05);the thickened ventricular wall,left ventricular internal dimension enlargement,left common carotid artery intima-media thickness and high density lipoprotein cholesterol were higher in the LVH group than in the non-LVH group(P<0.05);the left common carotid peak systolic velocity,left common carotid resistance index,serum uric acid and serum creatinine were lower in the LVH group than in the non-LVH group(P<0.05).The pulse diagram parameters T4,T,W1,W2,H3/H1 and H4/H1 were higher in the LVH group than in the non-LVH group(P<0.05).The areas of the ROC curves of the models constructed by the three types of machine learning algorithms were 0.887,0.962 and 0.873 respectively,indicating that the model had good discrimination and certain diagnostic efficacy.The calibration curve suggested that the prediction accuracy of the model was average;the clinical decision curve showed that XGBoost model has a higher net benefit.Conclusion The interpretable model constructed based on pulse diagram parameters and machine learning algorithms can be used as a reliable tool for predicting the risk of essential hypertension with LVH.

Central nervous system(CNS)degenerative disorders refer to a spectrum of pathological alterations triggered by struc-tural damage to cerebral neural tissues,clinically manifested as diverse neurological dysfunction syndromes,including multiple sclerosis(MS),neurodegenerative diseases(NDs),and ische-mic stroke.The hallmark pathological features of these disorders involve irreversible neuronal damage and decompensation of functional neural networks,ultimately leading to progressive neurological deficits.Notably,with the accelerating global popu-lation aging,the incidence of these diseases has surged signifi-cantly.According to WHO statistics,they now rank among the top three global causes of disability and mortality.Current re-search has confirmed that the pathogenesis of CNS degenerative disorders exhibits high heterogeneity,encompassing multifaceted pathophysiological processes such as genetic predisposition,oxi-dative stress,protein misfolding,and metabolic dysregulation.This intricate pathogenic network not only complicates clinical differential diagnosis but also poses substantial challenges to the development of precision therapeutic strategies.Importantly,re-cent studies have revealed that mitochondrial homeostasis disrup-tion-induced inflammatory cascades(termed mitochondrial in-flammation)play a pivotal regulatory role in neurodegenerative progression.Key molecular mechanisms include impaired mito-phagy,aberrant mitochondrial DNA(mtDNA)release and NL-RP3 inflammasome activation.This review systematically deci-phers the molecular regulatory network of mitochondrial inflam-mation,with a focus on its biological effects in critical pathologi-cal events such as blood-brain barrier disruption,microglial hy-peractivation and neuronal apoptosis.The overarching aim is to provide a theoretical foundation for developing innovative thera-peutic strategies targeting mitochondrial homeostasis restoration.

Drynaria fortunei,commonly known as"bone setting herb",has been widely included in various traditional Chinese herb-al classics for treating bone injuries.It is used medicinally from its rhizome,which has a bitter taste and warm property.It is known to nourish the kidneys,strengthen bones,and alleviate pain from injuries.The chemical constituents mainly include flavonoids,phenylpro-panoids,triterpenoids,phenolic acids,lignans,and sterols.Modern medical research indicates that Drynaria fortunei has anti-osteoporo-sis effects,promotes fracture healing,has anti-inflammatory properties,and benefits dental health.This article reviews the historical use of Drynaria fortunei and recent research on its chemical composition and pharmacological effects,summarizing some of the mechanisms of action.The aim is to provide a reference for further research on this medicinal herb.