Chronic eczema has a high prevalence in China， significantly impacting patients’ quality of life. Leveraging the unique advantages of pattern identification/syndrome differentiation and treatment， along with a holistic approach， traditional Chinese medicine （TCM）， which integrates internal and external therapies， has been widely applied in the management of chronic eczema. It has demonstrated significant efficacy and distinctive strengths in alleviating symptoms， reducing recurrence rates， maintaining disease stability， and enhancing patients’ quality of life. Oral administration of TCM（e.g. modified Longdan xiegan decoction） can improve patients’ clinical symptoms through systemic regulation. External use of TCM can directly act on the skin lesion with the help of steaming and washing， hydropathic compress， ointment and other forms. At the same time， it can effectively relieve the clinical symptoms of chronic eczema by combining with non-drug therapies such as acupuncture， moxibustion， acupoint catgut embedding， blood-letting puncture and cupping. In addition， characteristic therapies such as oral administration of TCM combined with external treatment， a combination of various external treatments and a combination of Chinese and Western medicine have also demonstrated certain advantages in regulating immune function， alleviating skin lesions， and relieving itching symptoms. These therapies cooperate with each other， creating a synergistic effect that treats both the symptoms and the root cause simultaneously. It is suggested that more high-quality， large-scale clinical research should be conducted in the future to systematically confirm the therapeutic advantages of TCM and further explore the specific molecular mechanism of action.

Cancer remains a leading cause of global mortality, necessitating the development of advanced therapeutic strategies with enhanced efficacy and reduced systemic toxicity. Among promising bioactive agents, lactoferrin (LF)—a multifunctional iron-binding glycoprotein abundantly found in mammalian milk and exocrine secretions—has garnered significant interest for its potent and multifaceted anti-cancer properties. This review provides a comprehensive analysis of the current understanding of LF’s role in oncology, encompassing its structural biology, diverse mechanisms of action, and groundbreaking advancements in its application through nano-engineering. LF exerts anti-tumor effects through multiple pathways, including extracellular action, intracellular action, and immune regulation. It demonstrates a remarkable affinity for cancer cell membranes, binding to overexpressed anionic components such as glycosaminoglycans and sialic acids, as well as to specific receptors including the low-density lipoprotein receptor-related protein-1 (LRP-1). This selective binding facilitates targeted uptake. Upon internalization, LF orchestrates a direct assault by inducing cell-cycle arrest in phases such as G0/G1 or S phase through the modulation of key regulators including cyclins, CDKs, and p53. Furthermore, it promotes programmed cell death via apoptotic pathways, involving caspase activation and downregulation of anti-apoptotic proteins such as survivin. A more recently elucidated mechanism is the induction of ferroptosis, an iron-dependent form of cell death characterized by overwhelming lipid peroxidation. Beyond direct cytotoxicity, LF acts as a potent immunomodulator. It enhances natural killer (NK) cell activity, modulates T-lymphocyte populations, and crucially reprograms tumor-associated macrophages (TAMs) from a pro-tumor M2 state to an anti-tumor M1 state, thereby reversing the immunosuppressive tumor microenvironment (TME). The translation of LF’s potential has been significantly accelerated by nanotechnology. The inherent biocompatibility and natural tumor-targeting capabilities of LF make it an ideal platform for sophisticated drug-delivery systems. This review details various fabrication strategies for LF-based nanoparticles (NPs), including self-assembly, sol-in-oil emulsion, and electrostatic nanocomplexes, among others. Research demonstrates that nano-formulations not only protect LF from degradation but also enhance its bioactivity and anti-cancer potency. More importantly, LF NPs serve as versatile carriers for a wide array of therapeutic agents, including conventional chemotherapeutics, natural compounds, and imaging agents. These engineered systems enable synergistic therapy and facilitate site-specific delivery. Notably, the ability of LF to bind to receptors on the blood-brain barrier (BBB) has been leveraged to develop nano-systems for glioblastoma treatment. Other innovative designs utilize LF to modulate the TME—for instance, by alleviating tumor hypoxia to sensitize cells to radiotherapy and chemotherapy. Despite compelling pre-clinical evidence, the clinical translation of LF and its nano-formulations remains nascent. While early-phase trials have established a favorable safety profile for recombinant human LF, larger Phase III studies have yielded mixed results, underscoring the complexity of its action in humans. Key challenges include enhancing drug targeting, optimizing loading efficiency, ensuring batch-to-batch reproducibility, and achieving deep tumor penetration. Future research must focus on the rational design of next-generation LF-NPs. This entails developing standardized manufacturing protocols, engineering “smart” stimuli-responsive systems for targeted drug release in the TME, and constructing multi-targeting platforms. A concerted interdisciplinary effort is paramount to bridge the gap between bench and bedside. In conclusion, LF, particularly in its nano-engineered forms, represents a highly promising and versatile agent in the oncological arsenal, holding immense potential for precise and effective cancer therapy.

Cancer remains a leading cause of global mortality, necessitating the development of advanced therapeutic strategies with enhanced efficacy and reduced systemic toxicity. Among promising bioactive agents, lactoferrin (LF)—a multifunctional iron-binding glycoprotein abundantly found in mammalian milk and exocrine secretions—has garnered significant interest for its potent and multifaceted anti-cancer properties. This review provides a comprehensive analysis of the current understanding of LF’s role in oncology, encompassing its structural biology, diverse mechanisms of action, and groundbreaking advancements in its application through nano-engineering. LF exerts anti-tumor effects through multiple pathways, including extracellular action, intracellular action, and immune regulation. It demonstrates a remarkable affinity for cancer cell membranes, binding to overexpressed anionic components such as glycosaminoglycans and sialic acids, as well as to specific receptors including the low-density lipoprotein receptor-related protein-1 (LRP-1). This selective binding facilitates targeted uptake. Upon internalization, LF orchestrates a direct assault by inducing cell-cycle arrest in phases such as G0/G1 or S phase through the modulation of key regulators including cyclins, CDKs, and p53. Furthermore, it promotes programmed cell death via apoptotic pathways, involving caspase activation and downregulation of anti-apoptotic proteins such as survivin. A more recently elucidated mechanism is the induction of ferroptosis, an iron-dependent form of cell death characterized by overwhelming lipid peroxidation. Beyond direct cytotoxicity, LF acts as a potent immunomodulator. It enhances natural killer (NK) cell activity, modulates T-lymphocyte populations, and crucially reprograms tumor-associated macrophages (TAMs) from a pro-tumor M2 state to an anti-tumor M1 state, thereby reversing the immunosuppressive tumor microenvironment (TME). The translation of LF’s potential has been significantly accelerated by nanotechnology. The inherent biocompatibility and natural tumor-targeting capabilities of LF make it an ideal platform for sophisticated drug-delivery systems. This review details various fabrication strategies for LF-based nanoparticles (NPs), including self-assembly, sol-in-oil emulsion, and electrostatic nanocomplexes, among others. Research demonstrates that nano-formulations not only protect LF from degradation but also enhance its bioactivity and anti-cancer potency. More importantly, LF NPs serve as versatile carriers for a wide array of therapeutic agents, including conventional chemotherapeutics, natural compounds, and imaging agents. These engineered systems enable synergistic therapy and facilitate site-specific delivery. Notably, the ability of LF to bind to receptors on the blood-brain barrier (BBB) has been leveraged to develop nano-systems for glioblastoma treatment. Other innovative designs utilize LF to modulate the TME—for instance, by alleviating tumor hypoxia to sensitize cells to radiotherapy and chemotherapy. Despite compelling pre-clinical evidence, the clinical translation of LF and its nano-formulations remains nascent. While early-phase trials have established a favorable safety profile for recombinant human LF, larger Phase III studies have yielded mixed results, underscoring the complexity of its action in humans. Key challenges include enhancing drug targeting, optimizing loading efficiency, ensuring batch-to-batch reproducibility, and achieving deep tumor penetration. Future research must focus on the rational design of next-generation LF-NPs. This entails developing standardized manufacturing protocols, engineering “smart” stimuli-responsive systems for targeted drug release in the TME, and constructing multi-targeting platforms. A concerted interdisciplinary effort is paramount to bridge the gap between bench and bedside. In conclusion, LF, particularly in its nano-engineered forms, represents a highly promising and versatile agent in the oncological arsenal, holding immense potential for precise and effective cancer therapy.

Objective To systematically evaluate the risk factors for postoperative delirium (POD) in patients undergoing pneumonectomy. Methods PubMed, Web of Science, Cochrane Library, CNKI, Wanfang, and VIP databases were searched from the inception to November 7, 2024 for cross-sectional studies, case-control studies, and cohort studies on POD in patients undergoing pneumonectomy. Two researchers independently screened the literature, extracted data, and evaluated the quality of the literature. RevMan 5.4.1 software was used for meta-analysis. The Newcastle-Ottawa Scale (NOS) was used to evaluate the quality of the literature. Results A total of 12 studies were included, with 5 574 patients. The NOS scores of the literature were all≥6 points. Meta-analysis results showed that age (≥60 years) [OR=2.43, 95%CI (2.01, 2.93), P<0.01], American Society of Anesthesiologists (ASA) classification (Ⅳ) [OR=8.74, 95%CI (5.23, 14.61), P<0.01], history of diabetes [OR=12.81, 95%CI (10.45, 15.71), P<0.01], history of cerebrovascular disease [OR=3.00, 95%CI (2.46, 3.67), P<0.01], depression [OR=7.27, 95%CI (5.46, 9.67), P<0.01], squamous cell carcinoma [OR=4.79, 95%CI (1.83, 12.51), P<0.01], malnutrition [OR=5.25, 95%CI (3.35, 8.25), P<0.01], sleep disorders [OR=2.79, 95%CI (2.28, 3.42), P<0.01], and duration of one-lung ventilation during surgery [OR=1.32, 95%CI (1.11, 1.57), P<0.01] were all risk factors for POD, while high body mass index (BMI) [OR=0.96, 95%CI (0.95, 0.97), P<0.01] was a protective factor for POD. Conclusion Age (≥60 years), ASA classification (Ⅳ), history of diabetes, history of cerebrovascular disease, depression, squamous cell carcinoma, malnutrition, sleep disorders, and duration of one-lung ventilation during surgery are independent risk factors for POD, while high BMI is a protective factor.

ObjectiveTo establish a high-performance liquid chromatography（HPLC） for the quantitative analysis of multiple components in Gegen Qinlian tablets， and to comprehensively evaluate the quality of samples from different manufacturers by integrating chemical pattern recognition and technique for order preference by similarity to ideal solution（TOPSIS）， in order to provide a reference basis for quality evaluation and control of Gegen Qinlian tablets. MethodsHPLC was employed to determine the contents of 10 components in 28 batches of Gegen Qinlian tablets collected from 6 manufacturers， and taking the detection results as variables， SIMCA 14.1 and SPSS 26.0 were employed for cluster analysis（CA）， principal component analysis（PCA）， and orthogonal partial least squares-discriminant analysis（OPLS-DA） to identify key components affecting the quality. Then， TOPSIS analysis was employed to rank the quality of Gegen Qinlian tablets from the 6 manufacturers and establish a comprehensive quality evaluation method. ResultsA quantitative method for Gegen Qinlian tablets was established. After methodological validation， the method was found to be stable and reliable， and could be used for the quantitative analysis of this preparation. The contents of 3′-hydroxy puerarin， puerarin， 3′-methoxy puerarin， daidzein， coptisine hydrochloride， epiberberine， jatrorrhizine hydrochloride， berberine hydrochloride， palmatine hydrochloride and baicalin in 28 batches of samples were 3.58-7.35， 24.88-42.32， 4.20-9.36， 4.33-7.60， 2.52-6.44， 0.93-4.10， 0.58-3.05， 10.68-22.92， 0.82-4.82， 11.73-60.16 mg·g^-1， respectively. Among them， puerarin， berberine hydrochloride and baicalin all met the limit requirements for this preparation specified in the 2025 edition of the Pharmacopoeia of the People's Republic of China. CA and PCA clustered the 28 batches of samples into 5 categories， PCA extracted 2 principal components with a cumulative variance contribution rate of 90.588%， and OPLS-DA screened out 4 differential markers with variable importance in the projection（VIP） values>1.0， namely baicalin， 3′-hydroxy puerarin， coptisine hydrochloride and palmatine hydrochloride， which might be the main components affecting the quality of Gegen Qinlian tablets. TOPSIS analysis showed that the comprehensive score of each evaluation index（C_i） values of different manufacturers were different. Among them， the C_i of manufacturer B was ranked higher， indicating potentially superior quality， while the C_i of manufacturer A was ranked lower， suggesting potentially inferior quality. ConclusionThis study establishes a quantitative method for Gegen Qinlian tablets， and the content uniformity of the same manufacturer is good， while there are differences in the contents of active components among different manufacturers. Through the chemical pattern recognition analysis， it is found that the content differences of Gegen Qinlian tablets may be related to baicalin， 3′-hydroxy puerarin， coptisine hydrochloride and palmatine hydrochloride.

Objective: To systematically evaluate the performance of machine learning (ML) models in predicting non suicidal self injury (NSSI) behavior among adolescents, providing an evidence based foundation for the development of clinically applicable risk assessment tools. Methods: A comprehensive search was conducted in PubMed, Embase, Web of Science, CNKI, and Wanfang databases for relevant studies from their inception to July 21, 2025. The Prediction Model Risk of Bias Assessment Tool (PROBAST) was used to evaluate the methodological quality of the included studies. Stata 18 software was used to calculate the area under the receiver operating characteristic curve (AUC) of the models, and publication bias assessment, sensitivity analysis, and Egger s test were performed. Results: The total of 12 studies (42 prediction models) involving 58 070 adolescents were included. There were 15 machine learning algorithms in total, among which Random Forest, Logistic Regression, XGBoost, and Support Vector Machines were the most frequently utilized. The most common predictors were gender (female), family function, depression, emotion regulation, and age. All 12 included studies exhibited a high risk of bias. The pooled AUC was 0.80 (95% CI =0.78-0.82), although heterogeneity was substantial ( I 2=95.8%, P <0.01). Sensitivity analysis confirmed the robustness of these findings (no overlap in 95% CI ), while Egger s test indicated the presence of publication bias ( P <0.05). Conclusions Machine learning demonstrates potential in the risk prediction of adolescent NSSI, but existing models have a high risk of bias. Future research should focus on improving methodological quality and optimizing model reliability through rigorous external validation.

BACKGROUND: Atrial fibrillation (AF) is a common cardiac arrhythmia in the elderly. This study aimed to evaluate urban-rural disparities in its prevalence and management in elderly Chinese. METHODS: Consecutive participants aged ≥ 65 years attending outpatient clinics were enrolled for AF screening using handheld single-lead electrocardiogram (ECG) from April 2017 to December 2022. Each ECG rhythm strip was reviewed from the research team. AF or uninterpretable single-lead ECGs were referred for 12-lead ECG. Primary study outcome comparison was between rural and urban areas for the prevalence of AF. The Student's t-test was used to compare mean values of clinical characteristics between rural and urban participants, while the Pearson's chi-square test was used to compare between-group proportions. Multivariate stepwise logistic regression analysis was performed to estimate the association between AF and various patient characteristics. RESULTS: The 29,166 study participants included 13,253 men (45.4%) and had a mean age of 72.2 years. The 7073 rural participants differed significantly (P ≤ 0.02) from the 22,093 urban participants in several major characteristics, such as older age, greater body mass index, and so on. The overall prevalence of AF was 4.6% (n = 1347). AF was more prevalent in 7073 rural participants than 22,093 urban participants (5.6% vs. 4.3%, P < 0.01), before and after adjustment for age, body mass index, blood pressure, pulse rate, cigarette smoking, alcohol consumption and prior medical history. Multivariate logistic regression analysis identified overweight/obesity (OR = 1.35, 95% CI: 1.17-1.54) in urban areas and cigarette smoking (OR = 1.62, 95% CI: 1.20-2.17) and alcohol consumption (OR = 1.42, 95% CI: 1.04-1.93) in rural areas as specific risk factors for prevalent AF. In patients with known AF in urban areas (n = 781) and rural areas (n = 338), 60.6% and 45.9%, respectively, received AF treatment (P < 0.01), and only 22.4% and 17.2%, respectively, received anticoagulation therapy (P = 0.05). CONCLUSIONS In China, there are urban-rural disparities in AF in the elderly, with a higher prevalence and worse management in rural areas than urban areas. Our study findings provide insight for health policymakers to consider urban-rural disparity in the prevention and treatment of AF.

BACKGROUND: The relationship between glycated hemoglobin (HbA1c) and cognitive impairment in older adults with coronary heart disease (CHD) remains unclear. METHODS: The present study used a prospective cohort study design and included 3244 participants aged ≥ 65 years in Beijing, China. The Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) were used to assess cognitive function. Serum HbA1c was detected at admission. All patients were divided into high HbA1c group (≥ 6.5 mmol/L) and low HbA1c group (< 6.5 mmol/L) based on their HbA1c levels. Logistic regression analyses were used to evaluate the association between HbA1c and cognitive impairment. RESULTS: In this study of 3244 participants, 1201 (37.0%) patients were in high HbA1c group and 2045 (63.0%) patients were in a state of cognitive impairment. Logistic regression analyses demonstrated that HbA1c was an independent risk factor for cognitive impairment regardless of whether the HbA1c was a continuous or categorical variable (OR = 1.27, 95% CI: 1.15-1.40, P < 0.001; OR = 1.79, 95% CI: 1.41-2.26, P ≤ 0.001, respectively). The restricted cubic spline curve exhibited that the relationship between the HbA1c and cognitive impairment was linear (p for non-linear = 0.323, P < 0.001). CONCLUSION Elevated levels of HbA1c were associated with an increased risk of cognitive impairment in older patients with CHD. These insights could be used to improve the accuracy and sensitivity of cognitive screening in these patient populations.

Gut microbial communities are likely remodeled in tandem with accumulated physiological decline during aging, yet there is limited understanding of gut microbiome variation in advanced age. Here, we performed a metagenomics-based enterotype analysis in a geographically homogeneous cohort of 367 enrolled Chinese individuals between the ages of 60 and 94 years, with the goal of characterizing the gut microbiome of elderly individuals and identifying factors linked to enterotype variations. In addition to two adult-like enterotypes dominated by Bacteroides (ET-Bacteroides) and Prevotella (ET-Prevotella), we identified a novel enterotype dominated by Escherichia (ET-Escherichia), whose prevalence increased in advanced age. Our data demonstrated that age explained more of the variance in the gut microbiome than previously identified factors such as type 2 diabetes mellitus (T2DM) or diet. We characterized the distinct taxonomic and functional profiles of ET-Escherichia, and found the strongest cohesion and highest robustness of the microbial co-occurrence network in this enterotype, as well as the lowest species diversity. In addition, we carried out a series of correlation analyses and co-abundance network analyses, which showed that several factors were likely linked to the overabundance of Escherichia members, including advanced age, vegetable intake, and fruit intake. Overall, our data revealed an enterotype variation characterized by Escherichia enrichment in the elderly population. Considering the different age distribution of each enterotype, these findings provide new insights into the changes that occur in the gut microbiome with age and highlight the importance of microbiome-based stratification of elderly individuals.
Aged ; Aged, 80 and over ; Female ; Humans ; Male ; Middle Aged ; Bacteroides ; China ; Diabetes Mellitus, Type 2/microbiology* ; Escherichia coli/classification* ; Gastrointestinal Microbiome/genetics* ; Metagenomics ; East Asian People

Hearing loss is the most prevalent disabling disease. Cochlear implantation（CI） serves as the primary intervention for severe to profound hearing loss. This consensus systematically explores the value of genetic diagnosis in the pre-operative assessment and efficacy prognosis for CI. Drawing upon domestic and international research and clinical experience, it proposes an evidence-based medicine three-tiered prognostic classification system（Favorable, Marginal, Poor）. The consensus focuses on common hereditary non-syndromic hearing loss（such as that caused by mutations in genes like GJB2, SLC26A4, OTOF, LOXHD1） and syndromic hereditary hearing loss（such as Jervell & Lange-Nielsen syndrome and Waardenburg syndrome）, which are closely associated with congenital hearing loss, analyzing the impact of their pathological mechanisms on CI outcomes. The consensus provides recommendations based on multiple round of expert discussion and voting. It emphasizes that genetic diagnosis can optimize patient selection, predict prognosis, guide post-operative rehabilitation, offer stratified management strategies for patients with different genotypes, and advance the application of precision medicine in the field of CI.
Humans ; Cochlear Implantation ; Prognosis ; Hearing Loss/surgery* ; Consensus ; Connexin 26 ; Mutation ; Sulfate Transporters ; Connexins/genetics*