ObjectiveTo develop a community-family management model for older adults with mild cognitive impairment (MCI) and to formulate detailed application specifications, and to fully leverage the initiative of communities and families under limited resource conditions, for achieving community-based early detection and early intervention for older adults with MCI. MethodsA systematic literature review was conducted to identify pertinent publications. Corpus-based research methodologies were employed to extract, refine, integrate and synthesize management elements, thereby establishing the specific content and service processes for each stage of the management model. Utilizing the 5W2H analytical framework, essential elements such as management stakeholders, target populations, content and methods for each stage were delineated. The model and its application guidelines were finalized through expert consultation and demonstration. ResultsAn expert evaluation of the management model yielded mean scores of 4.84, 4.32 and 4.84 for acceptability, feasibility and systematicity, respectively. By integrating the identified core elements with expert ratings and feedback, the final iteration of the community-family management model for older adults with MCI was formulated. This model comprised of five stages: screening and identification, comprehensive assessment, intervention planning, monitoring and referral pathways to ensure implementation, and enhanced support for communities, family members and caregivers. Additionally, it included 18 specific application guidelines. ConclusionThe proposed management model may theoretically help delay cognitive decline, improve cognitive function and potentially promote reversal from MCI to normal cognition. It may also enhance the awareness and coping capacity of older adults and their families, strengthen community healthcare professionals' ability to early identify and manage MCI.

With the emergence of deep learning techniques based on convolutional neural networks, artificial intelligence (AI) has driven transformative developments in the field of medical image analysis. Recently, large language models (LLMs) such as ChatGPT have also started to achieve distinction in this domain. Increasing research shows the undeniable role of AI in reshaping various aspects of medical image analysis, including processes such as image enhancement, segmentation, detection in image preprocessing, and postprocessing related to medical diagnosis and prognosis in clinical settings. However, despite the significant progress in AI research, studies investigating the recent advances in AI technology in the aforementioned aspects, the changes in research hotspot trajectories, and the performance of studies in addressing key clinical challenges in this field are limited. This article provides an overview of recent advances in AI for medical image analysis and discusses the methodological profiles, advantages, disadvantages, and future trends of AI technologies.
Artificial Intelligence ; Humans ; Image Processing, Computer-Assisted/methods* ; Neural Networks, Computer ; Deep Learning ; Diagnostic Imaging/methods*

Objective: To investigate the protective effects of morusin on lipopolysaccharide (LPS)-induced acute liver injury in mice and its underlying mechanisms. Methods: Thirty-two male specific pathogen-free (SPF) C57BL/6J mice were randomly divided into four groups (n = 8 per group): control, LPS, low-dose morusin (morusin-L, 10 mg/kg), and high-dose morusin (morusin-H, 20 mg/kg) groups. The mice in each group were administered the corresponding drugs or normal saline via continuous gavage daily for 16 consecutive days. Except for control group, which received an equal volume of normal saline, other groups were intraperitoneally injected with LPS (5 mg/kg) 2 h after the last gavage to establish the acute liver injury model. Serum and liver tissues were collected for subsequent analysis 6 h after LPS injection. The activities of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) in serum were detected with biochemical methods. The levels of tumor necrosis factor (TNF)-α, interleukin (IL)-6, and IL-1β in serum were measured by enzyme-linked immunosorbent assay (ELISA). Hepatic pathological changes were evaluated by hematoxylin-eosin (HE) staining. The 16S ribosomal RNA (16S rRNA) sequencing was performed to assess the composition of intestinal flora, linear discriminant analysis effect size (LEfSe) was applied for multi-level species discrimination, and Spearman’s correlation analysis was performed. The liver tissues of mice with acute liver injury were analyzed by RNA sequencing (RNA-seq) technology to identify differentially expressed genes (DEGs), and then enrichment analysis of the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway was conducted. The expression levels of selected genes was validated by quantitative reverse transcription polymerase chain reaction (qRT-PCR), while immunohistochemistry (IHC) was performed to examine the expression levels of IL-6, myeloid differentiation primary response 88 (MYD88), and toll-like receptor 2 (TLR2). Results: Morusin significantly reduced the serum levels of ALT, AST, and inflammatory factors (TNF-α, IL-6, and IL-1β) (P < 0.05, P < 0.01, or P < 0.001), while alleviating the hepatic pathological damage in mice. Based on efficacy comparisons, morusin-H group was selected for subsequent microbiome and transcriptome analyses. Microbiome analysis revealed that morusin-H effectively mitigated LPS-induced gut dysbiosis and restored the Firmicutes/Bacteroidota balance (P < 0.01). At the genus level, morusin-H significantly reduced the abundances of norank_f_Muribaculaceae, Desulfovibrio, Parabacteroides, and Muribaculum (P < 0.05, P < 0.01, or P < 0.001). At the phylum, family, and genus levels, our findings indicated that morusin-H treatment caused a significant decrease in the abundance of Desulfobacterota, Desulfovibrionaceae, and Desulfovibrio (P < 0.01). Importantly, the abundance of Desulfovibrio was positively correlated with the levels of ALT, AST, TNF-α, IL-1β, and IL-6. Transcriptomic and molecular analyses showed that the therapeutic mechanism of morusin-H involved suppression of the IL-17/TNF signaling pathways and downregulating the mRNA levels of Tlr2, Tlr3, Myd88, Il6, and Cxcl10 (P < 0.05 or P < 0.001), as well as the protein levels of key inflammatory mediators (IL-6, MYD88, and TLR2) (P < 0.001). Conclusion Morusin demonstrates protective effects against LPS-induced acute liver injury, likely through modulation of gut microbiota and suppression of pro-inflammatory factor expression. These findings indicate that morusin exerts its effects through the "microbiota-inflammation-liver" axis, providing a theoretical basis for its use as a multi-target plant-based drug in the treatment of metabolic inflammation-related liver diseases.

Osteopontin (OPN) is a secreted extracellular matrix glycoprotein that exists in body fluids and mediates multiple biological functions. The expression of OPN is particularly critical and active after ischemic stroke, and has dual significance for the body. The rapid increase of OPN has certain protective effects on the body, such as anti-inflammatory and promoting wound healing; if the rate of increase is relatively slower, it will have adverse effects on the body, such as promoting thrombosis and inducing inflammatory reactions. This article reviews the research progress of OPN in ischemic stroke.

ObjectiveTo identify the prototypical components and metabolites absorbed into blood and cerebrospinal fluid of Schisandrae Chinensis Fructus（SCF） based on sequential metabolism combined with liquid chromatography-mass spectrometry. MethodBlood and cerebrospinal fluid samples of integrated metabolism， intestinal metabolism and hepatic metabolism were collected from male SD rats after gavage and in situ intestinal perfusion administration， and ultra-performance liquid chromatography-quadrupole/electrostatic field orbitrap high-resolution mass spectrometry（UPLC Q-Exactive Orbitrap MS） was used to analyze and compare the differences in the spectra of SCF extract， blank plasma， administered plasma， blank cerebrospinal fluid and administered cerebrospinal fluid with ACQUITY UPLC BEH Shield RP18 column（2.1 mm×100 mm， 1.7 µm）， the mobile phase was acetonitrile（A）-0.1% formic acid aqueous solution（B） for gradient elution（0-7 min， 95%B； 7-12 min， 95%-35%B； 12-17 min， 35%-15%B； 17-20 min， 15%-12%B； 20-22 min， 12%-5%B； 22-23 min， 5%B； 23-25 min， 5%-95%B； 25-28 min， 95%B）. And heated electrospray ionization（HESI） was used with positive and negative ion modes， the scanning range was m/z 100-1 500. The prototypical constituents and their metabolites absorbed into blood and cerebrospinal fluid of SCF were identified according to the retention time， characteristic fragments， molecular formulae and the information of reference substances. ResultA total of 42 chemical components were identified in the extract of SCF， including lignans， flavonoids， amino acids， tannins， and others， of which lignans were the main ones. A total of 27 prototypical components and 14 metabolites were identified in plasma samples from different sites. A total of 15 prototypical components and 9 metabolites were identified in cerebrospinal fluid. The main metabolic reactions involved in the formation of metabolites were mainly demethylation， methylation， demethoxylation and hydroxylation. ConclusionThrough the systematic identification of the prototypical components and metabolites of SCF in rats， it provides data support for further better exploring the material basis of SCF in the treatment of central nervous system diseases.

ObjectiveTo examine the inhibitory effects of berberine compounds， including columbamine， on acetylcholinesterase from the perspectives of drug-target binding affinity and kinetics and explore the blood-brain barrier （BBB） permeability of these compounds in different multi-component backgrounds. MethodThe median inhibitory concentration （IC₅₀） of acetylcholinesterase by berberine compounds including columbamine was measured using the Ellman-modified spectrophotometric method. The binding kinetic parameters （K_off） of these compounds with acetylcholinesterase were determined using the enzyme activity recovery method. A qualitative analysis of the ability of these components to penetrate the BBB and arrive at the brain tissue in diverse multi-component backgrounds （including medicinal herbs and compound formulas） was conducted using ultra performance liquid chromatography-high resolution mass spectrometry （UPLC-HRMS）. ResultBerberine compounds， including columbamine， exhibited strong inhibition of acetylcholinesterase， with IC₅₀ values in the nanomolar range. Moreover， they displayed better drug-target binding kinetics characteristics （with smaller K_off values） than the positive control of donepezil hydrochloride （P<0.01）， indicating a longer inhibition duration of acetylcholinesterase. Berberine components such as columbamine could penetrate the BBB to arrive at brain tissue in the form of a monomer， as well as in the multi-component backgrounds of Coptis and Phellodendri Chinensis Cortex medicinal extracts and the compound formula Huanglian Jiedutang. ConclusionThese berberine compounds such as columbamine exhibit a strong inhibitory effect on acetylcholinesterase and can arrive at brain tissue in multi-component backgrounds. In the level of pharmacological substance， this supports the clinical efficacy of compound Huanglian Jiedutang in improving Alzheimer's disease， providing data support for elucidating the pharmacological basis of compound Huanglian Jiedutang.

Objective:To analyze the variations of serum lymphocyte subsets, immunoglobulins, and complement levels in patients with cheilitis, and to explore the associations between the changes in serum immune levels and the onset of cheilitis.Methods:A retrospective analysis was conducted on 153 patients with cheilitis who visited the Department of Stomatology, The First Affiliated Hospital of Zhengzhou University from January 2017 to December 2023. They were compared with 50 healthy individuals who visited the physical examination department during the same period. The changes of serum lymphocyte subsets, immunoglobulins, and complement levels in patients with cheilitis were analyzed. Main detection indicators as the percentage of total T lymphocytes (T%), helper/inducer T lymphocytes (CD4 +T%), absolute numbers of total T lymphocytes (T#), absolute numbers of helper/inducer T lymphocytes (CD4 +T#), percentage of natural killer cells (NK%), absolute numbers of B lymphocytes (B#), immunoglobulins IgG, IgM and complement C3, C4 were included. Multivariate logistic regression was used to explore the relationship between serum lymphocyte subsets, immunoglobulins, complement levels and cheilitis. Subgroup analysis was further conducted on patients with cheilitis based on gender, age, cheilitis type and severity. Results:The levels of T% [69.54% (64.41%, 75.14%)], CD4 +T% [(35.09±7.10)%], T# [1 328.00 (1 054.00, 1 560.50)], and CD4 +T# [653.00 (505.00, 831.50)] in the cheilitis group were significantly lower than those in the control group respectively [72.33% (69.41%, 75.47%), (39.07±5.84)%, 1 483.50 (1 245.75, 1 805.25), 769.00 (687.25, 933.00), with the corresponding statistical test results of Z=-2.64, P=0.008; t=3.58, P<0.001; Z=-2.80, P=0.005; Z=-3.80, P<0.001]. The level of NK% [16.21% (12.16%, 21.29%)] was significantly higher in the cheilitis group compared to the control group [14.61% (10.97%, 17.87%)] ( Z=-2.28, P=0.023). IgG [12.29 (10.77, 13.73) g/L] and IgM levels [1.18 (0.86, 1.58) g/L] were significantly higher in the cheilitis group than in the control group respectively [11.52 (10.16, 12.91) g/L, 0.99 (0.77, 1.26) g/L] ( Z=-2.24, P=0.025; Z=-2.10, P=0.036), while complement C3 [(1.09±0.17) g/L] and C4 levels [0.23 (0.19, 0.28) g/L] were significantly lower in the cheilitis group compared to the control [(1.18±0.17) g/L, 0.31(0.24, 0.35) g/L] ( t=3.10, P=0.002; Z=-4.79, P<0.001). Logistic regression analysis showed that elevated IgG ( P=0.021), decreased C4 ( P<0.001), decreased CD4 +T% ( P=0.003), and decreased T# ( P=0.035) were independent influencing factors for the occurrence of cheilitis. The rate of abnormal lymphocyte immune analysis in the cheilitis group [68.0% (104/153)] was significantly higher than that in the control group [24.0% (12/50)] (χ 2=29.76, P<0.001). The rate of abnormal immunoglobulin and complement detection in the cheilitis group [41.8% (64/153)] was significantly higher than that in the control group [4.0% (2/50)] (χ 2=24.58, P<0.001). The rate of detection abnormalities in female patients with cheilitis [51.5% (53/103)] was significantly higher than in male ones [22.0% (11/50)] (χ 2=12.00, P=0.001). Patients with granulomatous cheilitis had significantly lower levels of T# [1 136.50 (663.75, 1 310.50)] and B# [162.50 (104.00, 225.50)] compared to those with chronic cheilitis [1 366.00 (1 063.03, 1 602.00), 202.48 (148.00, 298.00)] ( Z=-2.35, P=0.019; Z=-2.16, P=0.031). Conclusions:Patients with cheilitis exhibit a certain degree of imbalance on cellular immunity, humoral immunity, and innate immunity, which may be related to the onset of cheilitis.

Objective To analyze the risk factors influencing the occurrence of atherosclerosis in patients with type 2 diabetes, and to construct and evaluate a nomogram prediction model. Methods Multivariate logistic regression was used to analyze the risk factors of atherosclerosis in type 2 diabetes mellitus, and R software was used to build a nomogram prediction model. The accuracy and clinical validity of the model were verified by using H-L fit curve, area under ROC curve and calibration curve. Results The prevalence rate of atherosclerosis was 56.37%. Independent risk factors for atherosclerosis in type 2 diabetes mellitus (P<0.05) were body weight (OR=1.42，P<0.05), glycated serum protein (OR=1.35, P<0.05), lactate dehydrogenase (OR=1.17, P<0.05), alkaline phosphatase (OR=0.79, P<0.05), hyperlipidemia (OR=2.30, P<0.05), stroke (OR=4.20, P<0.05), coronary heart disease (OR=64.54, P<0.05), lower extremity artery disease (OR=24.52, P<0.05), and other endocrine diseases (OR=1.65 , P<0.05). The area under ROC curve was 0.91, the slope of the calibration curve was close to 1, and the H-L fit curve χ²=3.11. The internal verification result of the constructed nomogram prediction model was P=0.93. External verification of patients in the test set showed that the area under ROC curve was 0.91, indicating good differentiation and accuracy of the model. Conclusion The prediction model established by using the risk factors screened in this study has a high accuracy and differentiation, and medical staff can take effective prevention measures according to the individual factors of patients.

Objective To explore the status quo of treatment adherence and its influencing factors in community management of patients with chronic diseases in Nanjing. Methods A total of 673 patients with chronic diseases managed by community health service centers in Nanjing were selected. The general data of the study subjects were collected. MMAS-8 Scale, the Chinese version of WHQOL-BREF and PSS-Fa were used to evaluate the treatment adherence, quality of life and family support level. Pearson correlation was used to analyze the correlation between MMAS-8 score and WHQOL-BREF Chinese version and PSS-Fa score, and logistic regression analysis was used to investigate the influencing factors of treatment adherence. Results The MMAS-8 score was positively correlated with WHQOL-BREF Chinese version psychological and social management domain score and PSS-Fa score , logistic regression analysis results suggested that > 65 years of age (OR =1.723) was a risk factor for poor treatment adherence, undergraduate and above education level (OR = 0.582), annual family income > 80 000 yuan (OR = 0.603), comorbidity of chronic diseases (OR = 0.718), better overall evaluation of their own quality of life (OR = 0.547) , and high family support level (OR = 0.619) were protective factors for poor treatment adherence, and the above differences were statistically significant (P < 0.05) . Conclusion There is still room to improve the treatment adherence of patients with chronic diseases in community management in Nanjing . It is necessary to focus on elderly patients, strengthen the education of patients with single chronic diseases and improve the quality of life and family support level of patients.

Objective To quantitatively analyze and evaluate the content of rehabilitation policy for people with disabilities in China. Methods This study focused on ten national policies of disability rehabilitation issued from 2021 to 2023.It employed text mining techniques to process policy texts and constructed a policy modeling consistency index model for dis-ability rehabilitation policies in China.The relevant policies were evaluated and analyzed quantitatively. Results The disability rehabilitation policies in China were relatively comprehensive in terms of policy transparency,op-erational mechanisms and policy nature.However,there was still a need for optimization in terms of policy per-spectives,target groups,incentive mechanisms,and other aspects. Conclusion The overall quality of disability rehabilitation policy texts at the national level in China is relatively good.There is a need to further enhance the predictability of policy objectives,clarify the responsibilities and division of labor among various departments,and improve policy incentive mechanisms in future policy formulation,which will further refine China's disability rehabilitation policy system and contribute to high-quality develop-ment of the disability cause.