End-stage liver disease (ESLD) covers the end-stage of acute and chronic liver diseases, mainly involving decompensated cirrhosis, various types of liver failure, and advanced liver cancer. Hepatocyte transplantation has shown promise in treating ESLD, but its clinical application is hampered by the shortage of donor hepatocytes. Cell therapy, an emerging effective treatment for ESLD, faces the same limitation due to scarce hepatocyte availability. Hepatocyte-like cells (HLCs), which are terminally differentiated cells, can be induced from both stem cells and somatic cells. As HLCs exhibit the morphology and function of primary hepatocytes, they offer a promising supplementary source of hepatocytes for cell therapy. First, we provide a background for the differentiation and maturation of primary hepatocytes. Subsequently, based on the current insights into the molecular pathways that regulate hepatocyte differentiation in vivo, we describe a strategy for establishing HLC derived from either stem cells or somatic cells. The key characteristics of these HLCs are also detailed. Furthermore, HLC offers therapeutic potential for liver failure, and HLC-based liver organoids and bioartificial liver systems have demonstrated the ability to provide liver functions, offering an innovative approach to treating various types of ESLD. Despite their promise, challenges such as efficiency in differentiation and functional maturation need to be addressed to improve the clinical application of HLCs. This review discusses these advancements and outlines the therapeutic potential and current challenges of HLC therapy for ESLD.

Objective: To analyze the disease burden and trends of oral diseases among China’s elderly population (1990-2021) and provide evidence for developing targeted intervention strategies Methods : Using data from the Global Burden of Disease (GBD) 2021 study, we extracted prevalence, incidence, and disability-adjusted life years (DALYs) for oral conditions (permanent dental caries, edentulism, periodontal diseases, and other oral disorders) in individuals aged ≥60 years in China. Due to data limitations, other oral diseases only included DALYs and prevalence. Age-standardized rates (ASR)—including age-standardized prevalence rate (ASPR), age-standardized incidence rate (ASIR), and age-standardized DALYs rate (ASDR)--were calculated. Trends were assessed via Joinpoint regression using average annual percentage change (AAPC), stratified by sex and age groups (60-64, 65-69, 70-74, 75-79, 80-84, 85-89, 90-94, 95+ years). Results: From 1990 to 2021, China’s elderly population exhibited distinct trends in oral disease burden. Overall oral diseases showed declining ASDR and ASPR, yet ASIR slightly increased. Permanent dental caries demonstrated significant rises across ASDR, ASIR, and ASPR. Edentulism showed declining ASDR and ASPR alongside stable ASIR. 95+ age group saw rising rates. Periodontal diseases remained largely stable in ASDR and ASPR but experienced a slight ASIR decline. Other oral disorders showed mild ASDR decline and stable ASPR. Notably, sex and age disparities persisted. Women consistently bore higher burdens for overall oral diseases, caries, edentulism, and other oral diseases but lower periodontal disease rates compared to men. 85-89, 90-95, 95+ age group faced rising DALYs and prevalence for overall oral diseases, while all other age groups demonstrated declining trends in both DALYs and prevalence; for permanent caries, the 60-64 age group showed the largest increases in DALY rate, incidence, and prevalence; edentulism demonstrated the most pronounced and sustained rises in DALY rate and prevalence in the 95+ group, while declining most rapidly in the 60-64 age group; for periodontal disease, both DALY rates and prevalence declined in the 90-94 and 95+ age groups, but increased across all measures (DALY rate, incidence, and prevalence) in the 70-74 and 75-79 age group; other oral conditions exhibited relatively stable burden distributions or minor changes, with no significant age-specific shifting trends observed. Conclusion From 1990 to 2021, China’s elderly oral disease burden declined overall, but caries surged, edentulism improved, periodontal diseases stabilized, and other oral diseases slightly declined. Prioritizing older women and the adults aged 85+ is critical to addressing evolving oral health needs.

OBJECTIVE To explore the mechanism of Huayu jiedu formula in regulating inflammatory injury in chronic kidney disease （CKD）. METHODS Fifty male SD rats were randomly divided into a sham surgery group （10 rats） and a modeling group （40 rats）. The CKD model was replicated in the modeling group by unilateral ureteral obstruction surgery. After successful modeling， the rats were randomly divided into model group， esaxerenone group （positive control）， and TCM low- and high-dose groups， with 10 rats in each group. The Esaxerenone group was given 1 mg/kg of esaxerenone， while the TCM low- and high-dose groups were given 13.7 and 27.4 g/kg of Huayu jiedu formula respectively， the sham surgery group and model group were given an equal volume of physiological saline， all groups were intervened continuously for 14 days. Hematoxylin eosin and Masson staining were used to observe the pathological changes in rat kidney tissue. Conventional biochemical methods were used to detect serum urea （SUr）， serum creatinine （SCr）， malondialdehyde （MDA）， and superoxide dismutase （SOD） levels； enzyme-linked immunosorbent assay was used to detect the levels of serum interleukin-1β （IL-1β）， IL-6， and tumor necrosis factor-α（TNF-α）； immunohistochemistry and Western blot were used to detect the protein expression of peroxisome proliferator-activated receptor γ coactivator-1α（PGC-1α） ， mitochondrial transcription factor A （TFAM）， absent in melanoma 2（AIM2）， caspase-1， gasdermin D （GSDMD）， IL-1β and IL-18 in renal tissue； real-time fluorescence quantitative PCR was used to detect the mRNA expression of AIM2. RESULTS Compared with the sham surgery group， the renal tissue of the model group showed pathological changes such as glomerular deformation and destruction， severe tubular dilation， and increased deposition of blue fibrin； the levels of SUr， SCr， MDA， IL-1β， IL-6， TNF-α，the protein expression of AIM2， GSDMD， caspase-1， IL-1β， IL-18 ， and the mRNA expression of AIM2 were significantly increased or up-regulated （P＜0.01）； the levels of SOD， the protein expression of PGC-1α， TFAM were significantly reduced or down-regulated （P＜0.01）. Compared with the model group， all treatment groups showed improvement in the above symptoms and most indicators in rats. CONCLUSIONS Huayu jiedu formula may improve renal function， alleviate renal inflammatory damage and pyroptosis， and exert renal protective effects by regulating the AIM2 pyroptosis pathway.

Buyang Huanwu Decoction(BYHWD), as one of the classic formulas in traditional Chinese medicine(TCM) for the treatment of cerebral ischemic stroke(CIS), has demonstrated definite effects in clinical practice. However, the material basis and mechanism of treatment have not been systematically elucidated. This study employed network pharmacology and molecular docking to analyze the potential targets and mechanisms of blood-and brain-penetrating active components of BYHWD in reducing cell apoptosis in CIS. Cell experiments were then carried out to validate the prediction results. In the experiments, five active components including hydroxysafflor yellow A( HSYA), tetramethylpyrazine( TMP), astragaloside Ⅳ( AS-Ⅳ), amygdalin( AMY), and paeoniflorin(PF) were selected to explore the pharmacological effects of BYHWD. HT22 cells were treated with BYHWD, and the cell counting kit-8(CCK-8) method was employed to examine the toxic and side effects of BYHWD. A cell model of oxygen-glucose deprivation/reoxygenation( OGD/R) was constructed, with apoptosis and pyroptosis as the main screening indicators. The levels of lactate dehydrogenase(LDH) and glutathione(GSH) were measured to assess the cell membrane integrity. Flow cytometry was employed to detect apoptosis, and the activities of caspase-3 and caspase-1 were measured to clarify the status of apoptosis and pyroptosis. ELISA was employed to determine the levels of interleukin(IL)-1β and IL-18 to confirm pyroptosis. HSYA and AMY were identified in this study as the active components regulating apoptosis and pyroptosis. TUNEL was employed to detect the apoptosis rate, and Western blot was employed to determine the expression levels of apoptosis-related proteins B-cell lymphoma-2(Bcl-2), Bcl-2-associated X protein(Bax), and caspase-3, which confirmed that the anti-apoptotic effect of the combined component group was superior to that of the single component groups. The molecular docking results revealed strong binding affinity of HSYA and AMY with SDF-1α and CXCR4.AMD3100, a selective antagonist of CXCR4, was then used for intervention. The results of Western blot showed alterations in the expression levels of apoptosis-associated proteins, SDF-1α, and CXCR4. In conclusion, HSYA and AMY influence cellular apoptosis by modulating the SDF-1α/CXCR4 signaling cascade.
Drugs, Chinese Herbal/chemistry* ; Apoptosis/drug effects* ; Animals ; Neurons/cytology* ; Mice ; Molecular Docking Simulation ; Cell Line ; Glucose/metabolism* ; Humans ; Neuroprotective Agents/pharmacology*

Alzheimer’s disease (AD) is a chronic neurodegenerative disorder that severely affects the health of the elderly, marked by its incurability, high prevalence, and extended latency period. The current approach to AD prevention and treatment emphasizes early detection and intervention, particularly during the pre-AD stage of mild cognitive impairment (MCI), which provides an optimal “window of opportunity” for intervention. Clinical detection methods for MCI, such as cerebrospinal fluid monitoring, genetic testing, and imaging diagnostics, are invasive and costly, limiting their broad clinical application. Speech, as a vital cognitive output, offers a new perspective and tool for computer-assisted analysis and screening of cognitive decline. This is because elderly individuals with cognitive decline exhibit distinct characteristics in semantic and audio information, such as reduced lexical richness, decreased speech coherence and conciseness, and declines in speech rate, voice rhythm, and hesitation rates. The objective presence of these semantic and audio characteristics lays the groundwork for computer-based screening of cognitive decline. Speech information is primarily sourced from databases or collected through tasks involving spontaneous speech, semantic fluency, and reading, followed by analysis using computer models. Spontaneous language tasks include dialogues/interviews, event descriptions, narrative recall, and picture descriptions. Semantic fluency tasks assess controlled retrieval of vocabulary items, requiring participants to extract information at the word level during lexical search. Reading tasks involve participants reading a passage aloud. Summarizing past research, the speech characteristics of the elderly can be divided into two major categories: semantic information and audio information. Semantic information focuses on the meaning of speech across different tasks, highlighting differences in vocabulary and text content in cognitive impairment. Overall, discourse pragmatic disorders in AD can be studied along three dimensions: cohesion, coherence, and conciseness. Cohesion mainly examines the use of vocabulary by participants, with a reduction in the use of nouns, pronouns, verbs, and adjectives in AD patients. Coherence assesses the ability of participants to maintain topics, with a decrease in the number of subordinate clauses in AD patients. Conciseness evaluates the information density of participants, with AD patients producing shorter texts with less information compared to normal elderly individuals. Audio information focuses on acoustic features that are difficult for the human ear to detect. There is a significant degradation in temporal parameters in the later stages of cognitive impairment; AD patients require more time to read the same paragraph, have longer vocalization times, and produce more pauses or silent parts in their spontaneous speech signals compared to normal individuals. Researchers have extracted audio and speech features, developing independent systems for each set of features, achieving an accuracy rate of 82% for both, which increases to 86% when both types of features are combined, demonstrating the advantage of integrating audio and speech information. Currently, deep learning and machine learning are the main methods used for information analysis. The overall diagnostic accuracy rate for AD exceeds 80%, and the diagnostic accuracy rate for MCI also exceeds 80%, indicating significant potential. Deep learning techniques require substantial data support, necessitating future expansion of database scale and continuous algorithm upgrades to transition from laboratory research to practical product implementation.

Aim To explore the effect of hydroxysafflor yellow A(HSYA)on lipocalin 2(LCN2)-induced fer-roptosis in HT22 cells and the related mechanism.Methods Thirty male Sprague-Dawley(SD)rats were used to establish the middle cerebral artery occlu-sion/reperfusion(MCAO/R)model by the suture method.The rats were randomly divided into the Sham group,the MCAO/R group,and the MCAO/R+HSYA group.The infarct area was measured by TTC staining,and the degree of neurological deficit was evaluated by the Z-Longa scoring method.The expressions of LCN2 and 24P3R in brain tissues were detected by Western blot.LCN2 protein was added to HT-22 cells,and the cells were divided into the normal group,the LCN2 group,and the LCN2+HSYA group.The optimal con-centration of LCN2-induced neuronal ferroptosis was screened by LDH assay and Western blot,and the ex-pression levels of ferritin,FPN1,GPX4,SLC7A11,COX2,and 24P3R were detected.LCN2 was knocked down by siRNA transfection,and the expressions of GPX4 and ferritin were detected.The contents of glu-tathione(GSH),malondialdehyde(MDA),GPX4,and Fe2+were determined by colorimetry,and the expres-sion of GPX4 was detected by immunofluorescence.The binding force between HSYA and LCN2 was ana-lyzed by molecular docking technology.Results Ani-mal experiments showed that HSYA could reduce the cerebral infarction area and decrease the neurological function score of MCAO/R rats.Compared with the sham group,the levels of LCN2 and 24P3R increased in the MCAO/R group,while HSYA inhibited their ex-pressions.Cell experiments showed that the optimal concentration of LCN2 to induce ferroptosis in HT22 cells was 2 μmol·L-1.After knocking down LCN2 by siRNA transfection,compared with the LCN2 group,the expression levels of GPX4 and ferritin in the siLCN2 group increased significantly.Compared with the nor-mal group,the expressions of SLC7A11,GPX4,FPN1,ferritin,and GSH in the LCN2 group decreased signifi-cantly,while the concentration of Fe2+,and the expres-sions of MDA,COX2,and 24P3R increased.HSYA could increase the expressions of SLC7A11,GPX4,FPN1,ferritin,and GSH,reduce the contents of Fe2+and MDA,and inhibit the expressions of COX2 and 24P3R.Molecular docking showed that the binding en-ergy between HSYA and LCN2 was-8.0 kJ·mol-1.Conclusion HSYA can inhibit LCN2-induced ferrop-tosis in HT22 cells through the SLC7A11/GPX4 signa-ling pathway.

To review the current knowledge and beliefs of patients with metabolic dysfunction-associated fatty liver disease (MAFLD) about disease management, including knowledge belief and practice, to find out and analyze the factors that may affect the level of knowledge and beliefs of the patients, including age, occupation, cultural level, family income and social support. We also summarize and propose possible effective interventions for patients with MAFLD from the perspectives of personalized health education and multi-disciplinary team, with the aim of providing references to improve the patients' knowledge, adherence to treatment and quality of life.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

Aim To systematically investigate the ac-tive components,targets,and regulatory pathways of Po-lygonum capitatum in intervening atherosclerosis(AS)through network pharmacology,molecular docking and animal experiments.Methods Active components of Polygonum capitatum and AS-related targets were screened and identified through database searches.Protein-protein interaction(PPI)network analysis was performed using the STRING database,followed by GO and KEGG enrichment analyses via the David plat-form.Molecular docking validation was conducted with AutoDock.An AS model was established in Syrian golden hamsters fed a high-fat diet.Predicted pathways and targets were validated using qPCR,ELISA,and histopathological assessment of aortic and hepatic tis-sues via HE staining.Results Network pharmacology identified 27 potential active components of Polygonum capitatum(primarily flavonoids such as quercetin and luteolin)and 110 drug-disease intersection targets,in-cluding core targets MMP-9,ALB,and AKT1.GO and KEGG analyses enriched 593 and 125 pathways,re-spectively,with the NF-κB inflammatory pathway,TNF signaling pathway and lipid metabolism/atherosclerosis pathways highlighted as key mechanisms.Animal ex-periments demonstrated that Polygonum capitatum im-proved serum lipid profiles(reduced TC,TG,LDL-C)in AS hamsters,suppressed the MMP-9/NF-κB signa-ling pathway(downregulated MMP-9,p65 phosphoryla-tion,TNF-α,and IL-6),and inhibited VSMC synthetic phenotypic transformation(upregulated α-SMA and myocardin)by downregulating MCPIP1.Additionally,Polygonum capitatum ameliorated aortic lesions and he-patic lipid deposition in AS hamsters.Conclusions Polygonum capitatum alleviates AS by synergistically regulating the MMP-9/NF-κB/MCPIP1 axis through flavonoid components,suppressing vascular inflammato-ry cascades and maintaining VSMC contractile pheno-types.This reflects Polygonum capitatum's multi-com-ponent,multi-pathway,and multi-target characteristics in combating AS.