The chemical constituents from leaves of Cyclocarya paliurus were isolated and purified by chromatography on silica gel, C_(18) reverse-phase silica gel, and Sephadex LH-20 gel, as well as semi-preparative high-performance liquid chromatography. Six compounds were identified by UV, IR, NMR, MS, calculated ECD, and comparison with literature data as cyclopaloside D(1), boscialin(2),(5R,6S)-6-hydroxy-6-[(E)-3-hydroxybut-1-enyl]-1,1,5-trimethylcyclohexanone(3), 3S,5R-dihydroxy-6R,7-megastigmadien-9-one(4), 3S,5R-dihydroxy-6S,7-megastigmadien-9-one(5), and gingerglycolipid A(6), respectively. Among them, compound 1 was identified as a new tetralone glycoside, and compounds 2-6 were isolated from leaves of C. paliurus for the first time. Furthermore, compound 1 exhibited strong antioxidant activity, with the IC_(50) of(454.20±31.81)μmol·L~(-1) and(881.82±42.31)μmol·L~(-1) in scavenging DPPH and ABTS free radicals, respectively.
Plant Leaves/chemistry* ; Glycosides/isolation & purification* ; Juglandaceae/chemistry* ; Tetralones/isolation & purification* ; Drugs, Chinese Herbal/isolation & purification*

Medical institutions, with their clinical practice foundation and abundant human use experience data, have become important carriers for the inheritance and innovation of traditional Chinese medicine(TCM) and the "cradles" of the preparation of new TCM. To effectively promote the transformation of new TCM originating from the TCM clinical practice in medical institutions and establish an effective evaluation index system for the transformation of new TCM conforming to the characteristics of TCM, consensus experts adopted the literature research, questionnaire survey, Delphi method, etc. By focusing on the policy and technical evaluation of new TCM originating from the TCM clinical practice in medical institutions, a comprehensive evaluation from the dimensions of drug safety, efficacy, feasibility, and characteristic advantages was conducted, thus forming a comprehensive evaluation system with four primary indicators and 37 secondary indicators. The expert consensus reached aims to encourage medical institutions at all levels to continuously improve the high-quality research and development and transformation of new TCM originating from the TCM clinical practice in medical institutions and targeted at clinical needs, so as to provide a decision-making basis for the preparation, selection, cultivation, and transformation of new TCM for medical institutions, improve the development efficiency of new TCM, and precisely respond to the public medication needs.
Medicine, Chinese Traditional/standards* ; Humans ; Consensus ; Drugs, Chinese Herbal/therapeutic use* ; Surveys and Questionnaires

OBJECTIVES: To report the development, validation, and findings of the Multi-dimensional Attention Rating Scale (MARS), a self-report tool crafted to evaluate six-dimension attention levels. METHODS: The MARS was developed based on Classical Test Theory (CTT). Totally 202 highly educated healthy adult participants were recruited for reliability and validity tests. Reliability was measured using Cronbach's alpha and test-retest reliability. Structural validity was explored using principal component analysis. Criterion validity was analyzed by correlating MARS scores with the Toronto Hospital Alertness Test (THAT), the Attentional Control Scale (ACS), and the Attention Network Test (ANT). RESULTS: The MARS comprises 12 items spanning six distinct dimensions of attention: focused attention, sustained attention, shifting attention, selective attention, divided attention, and response inhibition.As assessed by six experts, the content validation index (CVI) was 0.95, the Cronbach's alpha for the MARS was 0.78, and the test-retest reliability was 0.81. Four factors were identified (cumulative variance contribution rate 68.79%). The total score of MARS was correlated positively with THAT (r = 0.60, P < 0.01) and ACS (r = 0.78, P < 0.01) and negatively with ANT's reaction time for alerting (r = -0.31, P = 0.049). CONCLUSIONS The MARS can reliably and validly assess six-dimension attention levels in real-world settings and is expected to be a new tool for assessing multi-dimensional attention impairments in different mental disorders.
Humans ; Adult ; Male ; Attention/physiology* ; Female ; Middle Aged ; Reproducibility of Results ; Young Adult ; Psychometrics

Thrombocytosis is a common condition in children, classified into primary and secondary types. Secondary thrombocytosis is mainly caused by factors such as infection, anemia, iron deficiency, trauma, or surgical intervention, and it typically occurs without severe thrombosis or bleeding events. Platelet counts can return to normal after control of the primary factors, with favorable clinical outcomes. Primary thrombocytosis is mainly caused by myeloproliferative neoplasms such as polycythemia vera, essential thrombocythemia, and myelofibrosis, often accompanied by gene mutations in hematopoietic cells. In children, clinical manifestations are atypical compared to adults, with few thromboembolic or bleeding events. No special treatment is required for patients who are asymptomatic or have mild symptoms, and it is recommended to regularly monitor platelet counts. Antiplatelet therapy with aspirin can be considered for patients at risk of thrombosis or those with extreme thrombocytosis, and cytoreductive therapy can be performed when necessary, but the toxicities and side effects of drugs should be closely monitored. At present, hydroxyurea, interferon-alpha, and anagrelide are commonly used for cytoreductive therapy. This article provides an overview of the etiology, classification, clinical manifestations, diagnosis, and treatment of childhood thrombocytosis to guide healthcare professionals in treatment decisions.
Humans ; Thrombocytosis/therapy* ; Child

OBJECTIVE: To study the clinical and laboratory characteristics of monoclonal gammopathy anemia and explore the risk factors associated with anemia in monoclonal gammopathy. METHODS: A retrospective analysis was conducted on 5 539 patients who underwent immunofixation electrophoresis at the First Affiliated Hospital of Chengdu Medical College from January 2016 to February 2024. A total of 351 newly diagnosed M protein positive patients were selected as the study subjects, including 270 in the anemia group and 81 in the non-anemia group. Laboratory test results were compared between the two groups, and logistic regression models were used to analyze the risk factors for anemia. ROC curve analysis was performed to evaluate the predictive value of risk factors for anemia in monoclonal gammopathy. RESULTS: The proportion of non-anemic patients was 23.1% (81/351), with a median age of 67(60-75) years; the proportion of anemic patients was 76.9% (270/351), with a median age of 70(63-75) years. The total protein, globulin, urea, creatinine, uric acid, β₂-microglobulin, and ceruloplasmin levels in the anemia group were higher than those in the non-anemia group ( P < 0.05), while albumin, neutrophil count, lymphocyte count, monocyte count, complement C3, complement C4, haptoglobin, and transferrin levels were lower in the non-anemia group ( P < 0.05). After adjustment, multivariate logistic regression analysis shows that elevated GLB, increased β₂-MG, decreased ANC, and reduced complement C3 were independent risk factors for anemia in monoclonal gammopathy ( P < 0.05). ROC curve analysis demonstrates that GLB, β₂-MG, ANC, and complement C3 had good predictive value for anemia associated with monoclonal gammopathy. CONCLUSION Elevated GLB, increased β₂-MG, decreased ANC, and reduced complement C3 are independent risk factors for anemia in monoclonal gammopathy (P < 0.05). The combined assessment of these four factors has good predictive value for anemia in monoclonal gammopathy.
Humans ; Retrospective Studies ; Anemia/complications* ; Aged ; Middle Aged ; Paraproteinemias/diagnosis* ; Risk Factors ; Male ; Female ; Logistic Models ; ROC Curve ; Complement C3

With the change of infectious disease incidence pattern and the development of related technologies, progresses have been made in the research of infectious disease epidemiology. In recent years, due to the change in the requirements of infectious disease prevention and control, the research focus has expanded from common infectious diseases to diseases which have been eliminated or might be eliminated, as well as emerging and re-emerging infectious diseases. Infectious disease data has been characterized by multiple sources and modalities. Along with the rapid development of pathogen detection methods, infectious disease surveillance has shifted from a single disease-targted one to a comprehensive one. Moreover, novel technologies such as multi-omics and artificial intelligence have been applied in infectious disease epidemiology research. The international cooperation in this field has become increasingly crucial, and the revision of the International Health Regulations and the negotiation of pandemic agreement will have a profound impact. In the future, infectious disease epidemiology research will develop with more powerful tools to improve its capabilities.

Cilia,as cellular sensory organelles,actively partici-pate in and regulate cellular processes such as autophagy and metabolic breakdown during their generation and transportation.Autophagy,on the other hand,is a cell self-protection mecha-nism that maintains cellular homeostasis by clearing aggregates and damaged organelles.Combining recent research findings,this review comprehensively elucidates the bidirectional crosstalk between primary cilia and autophagy.Specifically,it highlights the crucial role of cilia-dependent signaling pathways in activa-ting cellular autophagy and how autophagy regulates cilia genera-tion and length by degrading specific ciliary proteins.Moreover,the dysregulation of primary cilia and autophagy is closely asso-ciated with the clinical manifestations and pathogenesis of vari-ous ciliopathy-related diseases such as polycystic kidney disease and tuberous sclerosis.In terms of pharmacotherapy,this review provides a comprehensive and in-depth overview of small mole-cule inhibitors targeting ciliogenesis,including cytoskeletal drugs and Hedgehog signaling pathway inhibitors.Despite the current limitations in clinical use,these drugs lay the groundw-ork for developing highly specific targeted small molecule inhibi-tors of ciliogenesis and for the treatment of ciliopathies and canc-ers.By systematically discussing ciliogenesis,autophagy,disea-ses and drugs,this review offers new insights for further elucida-ting the crosstalk between ciliogenesis and autophagy,exploring their pathological mechanisms in disease development,and de-veloping therapeutic strategies in the future.

OBJECTIVE: As an age-related neurodegenerative disease, the prevalence of mild cognitive impairment (MCI) increases with age. Within the framework of traditional Chinese medicine, spleen-kidney deficiency syndrome (SKDS) is recognized as the most frequent MCI subtype. Due to the covert and gradual onset of MCI, in community settings it poses a significant challenge for patients and their families to discern between typical aging and pathological changes. There exists an urgent need to devise a preliminary diagnostic tool designed for community-residing older adults with MCI attributed to SKDS (MCI-SKDS). METHODS: This investigation enrolled 312 elderly individuals diagnosed with MCI, who were randomly distributed into training and test datasets at a 3:1 ratio. Five machine learning methods, including logistic regression (LR), decision tree (DT), naive Bayes (NB), support vector machine (SVM), and gradient boosting (GB), were used to build a diagnostic prediction model for MCI-SKDS. Accuracy, sensitivity, specificity, precision, F1 score, and area under the curve were used to evaluate model performance. Furthermore, the clinical applicability of the model was evaluated through decision curve analysis (DCA). RESULTS: The accuracy, precision, specificity and F1 score of the DT model performed best in the training set (test set), with scores of 0.904 (0.845), 0.875 (0.795), 0.973 (0.875) and 0.973 (0.875). The sensitivity of the training set (test set) of the SVM model performed best among the five models with a score of 0.865 (0.821). The area under the curve of all five models was greater than 0.9 for the training dataset and greater than 0.8 for the test dataset. The DCA of all models showed good clinical application value. The study identified ten indicators that were significant predictors of MCI-SKDS. CONCLUSION The risk prediction index derived from machine learning for the MCI-SKDS prediction model is simple and practical; the model demonstrates good predictive value and clinical applicability, and the DT model had the best performance. Please cite this article as: Ai YT, Zhou S, Wang M, Zheng TY, Hu H, Wang YC, Li YC, Wang XT, Zhou PJ. Development of a machine learning-based risk prediction model for mild cognitive impairment with spleen-kidney deficiency syndrome in the elderly. J Integr Med. 2025; 23(4): 390-397.
Humans ; Cognitive Dysfunction/diagnosis* ; Aged ; Male ; Female ; Machine Learning ; Spleen ; Aged, 80 and over ; Kidney ; Medicine, Chinese Traditional