Metabolic syndrome （MS） is a clinical syndrome characterized by obesity， insulin resistance， and dyslipidemia， and chronic inflammation is closely associated with its pathogenesis. The imbalance between pro-inflammatory and anti-inflammatory macrophage polarization， as one of the core pathological mechanisms of chronic inflammation， is a crucial driver of MS progression. According to Essential Questions in Yellow Emperor's Inner Canon： Distinctive Theory on Meridians and Diseased Pulses， "the spleen Qi dispersing essence... along all the meridians and collaterals". When the spleen fails in transportation and transformation， the distribution of refined essence becomes disordered， leading to internal accumulation of phlegm-dampness， forming a dynamic pathological state of "root deficiency with branch excess". Accordingly， the core traditional Chinese medicine （TCM） pathogenesis of MS is closely related to "spleen failing in transportation and transformation coupled with the internal accumulation of phlegm-dampness"； however， its modern biological basis remains elusive. Therefore， based on the theory of "spleen Qi dispersing essence" and recent advances in immunometabolism， this paper explored the modern scientific connotation of the TCM pathogenesis of MS from the perspective of macrophage polarization driven by glucose metabolic reprogramming. Through theoretical analysis and literature integration， it was proposed that mitochondrial oxidative phosphorylation participates in the energy metabolism process of "spleen Qi dispersing essence". The dysfunction of the spleen's transportation and transformation prompts macrophage metabolism to shift toward glycolysis， resulting in the accumulation of lactate and succinate， which represents the microscopic manifestation of "refined essence deviating from proper transformation" and can be defined as "microscopic phlegm-dampness". These metabolites subsequently drive M1 macrophage polarization via the hypoxia-inducible factor-1α （HIF-1α）/nuclear factor-κB （NF-κB） signaling pathway， triggering the release of pro-inflammatory cytokines and inducing systemic chronic low-grade inflammation， ultimately manifesting as insulin resistance， lipid metabolic disorders， and other core components of MS， thus achieving immune amplification from local "microscopic phlegm-dampness" to systemic "internal accumulation of phlegm-dampness". Therefore， macrophage polarization driven by glucose metabolic reprogramming constitutes an important biological link connecting the TCM concept of "spleen failing to disperse essence" with the pathology of MS. Furthermore， this paper reviewed the potential mechanisms by which TCM herbal formulas and their monomeric components that "restore spleen transportation and resolve phlegm-dampness" ameliorate MS by modulating macrophage metabolic remodeling， thereby providing novel biological connotations for the modern interpretation of the theory of "spleen Qi dispersing essence". Future research should integrate multi-omics technologies with disease-syndrome animal models to elucidate the regulatory network of formulas that "restore spleen transportation and resolve phlegm-dampness". Additionally， the feasibility of utilizing macrophage metabolic phenotypes as objective diagnostic biomarkers for the phlegm-dampness syndrome in MS warrants further investigation.

Metabolic syndrome （MS） is a clinical syndrome characterized by obesity， insulin resistance， and dyslipidemia， and chronic inflammation is closely associated with its pathogenesis. The imbalance between pro-inflammatory and anti-inflammatory macrophage polarization， as one of the core pathological mechanisms of chronic inflammation， is a crucial driver of MS progression. According to Essential Questions in Yellow Emperor's Inner Canon： Distinctive Theory on Meridians and Diseased Pulses， "the spleen Qi dispersing essence... along all the meridians and collaterals". When the spleen fails in transportation and transformation， the distribution of refined essence becomes disordered， leading to internal accumulation of phlegm-dampness， forming a dynamic pathological state of "root deficiency with branch excess". Accordingly， the core traditional Chinese medicine （TCM） pathogenesis of MS is closely related to "spleen failing in transportation and transformation coupled with the internal accumulation of phlegm-dampness"； however， its modern biological basis remains elusive. Therefore， based on the theory of "spleen Qi dispersing essence" and recent advances in immunometabolism， this paper explored the modern scientific connotation of the TCM pathogenesis of MS from the perspective of macrophage polarization driven by glucose metabolic reprogramming. Through theoretical analysis and literature integration， it was proposed that mitochondrial oxidative phosphorylation participates in the energy metabolism process of "spleen Qi dispersing essence". The dysfunction of the spleen's transportation and transformation prompts macrophage metabolism to shift toward glycolysis， resulting in the accumulation of lactate and succinate， which represents the microscopic manifestation of "refined essence deviating from proper transformation" and can be defined as "microscopic phlegm-dampness". These metabolites subsequently drive M1 macrophage polarization via the hypoxia-inducible factor-1α （HIF-1α）/nuclear factor-κB （NF-κB） signaling pathway， triggering the release of pro-inflammatory cytokines and inducing systemic chronic low-grade inflammation， ultimately manifesting as insulin resistance， lipid metabolic disorders， and other core components of MS， thus achieving immune amplification from local "microscopic phlegm-dampness" to systemic "internal accumulation of phlegm-dampness". Therefore， macrophage polarization driven by glucose metabolic reprogramming constitutes an important biological link connecting the TCM concept of "spleen failing to disperse essence" with the pathology of MS. Furthermore， this paper reviewed the potential mechanisms by which TCM herbal formulas and their monomeric components that "restore spleen transportation and resolve phlegm-dampness" ameliorate MS by modulating macrophage metabolic remodeling， thereby providing novel biological connotations for the modern interpretation of the theory of "spleen Qi dispersing essence". Future research should integrate multi-omics technologies with disease-syndrome animal models to elucidate the regulatory network of formulas that "restore spleen transportation and resolve phlegm-dampness". Additionally， the feasibility of utilizing macrophage metabolic phenotypes as objective diagnostic biomarkers for the phlegm-dampness syndrome in MS warrants further investigation.

Objective To develop the Ego Depletion Scale for Type 2 Diabetes Patients and evaluate its reliability and validity,and to provide a specific assessment tool for evaluating ego-depletion in self-management.Methods Guided by the self-control strength model,the initial scale was constructed through literature review,semi-structured interviews,2 rounds of expert consultation,and a pilot survey.A convenience sampling method was employed to recruit 460 patients with Type 2 Diabetes from the endocrinology department of a tertiary hospital in Wuhan,Hubei Province,between April and July 2024.They were randomly divided into 2 subsets for exploratory factor analysis and confirmatory factor analysis.Results A total of 451 valid questionnaires were collected.Exploratory factor analysis extracted 6 common factors,with a cumulative variance contribution of 73.231％.In confirmatory factor analysis,an item was deleted due to failing to meet the standardized loading value criterion.The revised Ego Depletion Scale for Type 2 Diabetes Patients comprised 6 dimensions and 22 items.The total Cronbach's α coefficient was 0.911;split-half reliability was 0.744;the content validity index was 0.860.Correlation coefficients between the total score and scores of each dimension of the scale and the total score of the Self-Regulatory Fatigue Scale ranged from 0.558 to 0.946(P＜0.001).Conclusion The scale exhibits robust reliability and validity,serving as a scientifically instrument for assessing ego depletion in patients with Type 2 Diabetes.

Objective:To explore the neurophysiological features of the prefrontal-limbic-striatal circuit in patients with early-stage bipolar disorder without manic or hypomanic episodes, and its role in identifying early-stage bipolar disorder.Methods:From 2009 to 2019, a total of 155 hospitalized patients with major depressive disorder (MDD) from Nanjing Brain Hospital were selected after at least 5 years of follow-up, 31 patients with depression transitioned to bipolar disorder(ctBD group) and 76 patients remained the diagnosis of MDD(MDD group) were recruited.Sixty-two healthy controls matched for age, gender, and education years were selected as control group(HC group). Resting-state magnetoencephalography (MEG) data in eyes-open state of all subjects were collected.Data were analyzed based on the fieldtrip toolkit on the MATLAB platform. The key brain area of the prefrontal-limbic-striatal circuit were selected. Inter-group statistical analysis were conducted on the spectral energy and power-correlated functional connectivity at the theta, alpha, beta, and gamma frequency bands in the brain area of interest. In addition, the prediction model was constructed to early recognize bipolar disorder.Results:(1)There were statistically significant differences in the spectral energy of theta and alpha frequency bands in the prefrontal-limbic-striatal circuit among the 3 groups (cluster- F=120.50, 112.39, both P<0.05). The spectral energy of theta and alpha frequency bands in interest brain regions of prefrontal-limbic-striatal circuit in MDD group was lower than that in HC group (cluster- t=89.52, P<0.05). The spectral energy of theta band in prefrontal-limbic-striatal circuit in ctBD group was lower than that in HC group(cluster- t=105.82, P<0.05), and the spectral energy of alpha band in inferior frontal gyrus, orbitofrontal gyrus and caudate nucleus was lower than that in HC group (cluster- t=75.78, P<0.05), while there was no significant difference between the MDD group and the ctBD group ( P>0.05).(2)After FDR correction, there were statistically significant differences in functional connectivity between the left orbitofrontal gyrus and the right ventral striatum among the three groups (0.26 (0.13, 0.34), 0.12 (0.09, 0.24), 0.27 (0.20, 0.37), H=13.51, P<0.05, FDR correction). The strength of functional connectivity between the left orbitofrontal gyrus and the right ventral striatum in the MDD group was weaker than that in the HC group and the ctBD group (all P<0.05).(3)Binary Logistic regression analysis showed that the functional connectivity of beta frequency band between the left orbitofrontal gyrus and the right ventral striatum ( B=1.50, OR=4.50, 95% CI=1.73-11.70), the functional connectivity between the right orbitofrontal gyrus and the right amygdala( B=0.98, OR=2.68, 95% CI=1.18-6.13), the total HAMD score ( B=0.80, OR=2.28, 95% CI=1.36-3.67), the body weight factor score ( B=-1.99, OR=0.14, 95% CI=0.04-0.45), the anxiety factor score ( B=-0.99, OR=0.37, 95% CI=0.19-0.71), and sleep factor score( B=-1.14, OR=0.32, 95% CI=0.16-0.65)were the influencing factors for depression transitioned to bipolar disorder. Conclusion:The decreased resting low-frequency energy in the prefrontal-limbic-striatal circuit may be the common neural basis for the onset of unipolar and bipolar depression, and enhanced functional connectivity may be a potential neural circuit mechanism for depression transitioned to bipolar disorder. Functional connectivity combined with clinical manifestations is helpful for early recognition of bipolar disorder.

Objective To investigate the current status of home medicine cabinet management and unmet needs for home-based pharmaceutical services among elderly hypertensive patients in Hubei Province,and to provide evidence for optimizing home pharmaceutical care models.Methods From July 2022 to March 2023,310 elderly hypertension patients across Hubei Province were enrolled.Pharmacists conducted home visits to administer structured questionnaires capturing demographics and blood pressure control rates,perform medication categorization and quality assessments of home medicine cabinets and document cabinet management issues in real-time.Results Among 290 valid questionnaires,binary logistic regression revealed better blood pressure control in non-working and non-smoking individuals.Medicine cabinet audits identified three critical issues:failure to separate Chinese and chemical medicines,duplicate medications with similar ingredients and missing original packaging.Post-intervention,all cabinets demonstrated proper medication categorization and storage compliance.Conclusions Significant medication safety hazards exist in elderly hypertensive patients'home medicine cabinets.Pharmacist-led home interventions effectively cleared substandard medications and improved medication safety.Future home pharmaceutical services should focus on optimizing cabinet management protocols,enhancing medication safety awareness and personalizing pharmaceutical care to ensure precise and effective home-based medication management.

Organophosphorus nerve agents are the most threatening chemical warfare agents and terrorist agents.The number of nerve agents and their related chemicals involved in the verification of Chemical Weapon Convention(CWC)exceeds ten million,with the majority being isomers.Accurate structural identification of these chemicals has always been one of the challenges in CWC related verification analysis.In this work,a total of 17 kinds of alkyl phosphonate isomers and structural analogs from 5 groups were designed and synthesized,and then analyzed by gas chromatography-mass spectrometry(GC-MS)and gas chromatography-infrared spectroscopy(GC-FTIR).The spectra of isomers or structural analogs obtained from two techniques as well as the structural information provided therein were compared and analyzed.The results showed that for isomers or structural analogs with similar MS spectra,FTIR spectra could provided more structural fingerprint information of compounds and had advantages in confirming structures.Combined with the excellent separation ability of GC,GC-FTIR can be used to assist GC-MS in the structural confirmation of alkyl phosphates,achieving rapid and accurate identification of isomers or structural analogues.

Based on the core collection retrieval of the Web of Science database,researches related to the medicinal field of plant-derived vesicles(PDVs)were retrieved.The research hotspots and their changes in the pharmaceutical field of PDVs are visually analyzed by using bibliometric software VOSviewer and CiteSpace.A detailed discussion is held around the author,institution,country,key research hotspots and annual develop-ment hotspots,revealing the current research status of PDVs in the pharmaceutical field and predicting future trends,which provides valuable perspectives for researchers to understand the current research status of PDVs in the pharmaceutical field and discover possible unexplored areas in this field.

Objective To develop the Ego Depletion Scale for Type 2 Diabetes Patients and evaluate its reliability and validity,and to provide a specific assessment tool for evaluating ego-depletion in self-management.Methods Guided by the self-control strength model,the initial scale was constructed through literature review,semi-structured interviews,2 rounds of expert consultation,and a pilot survey.A convenience sampling method was employed to recruit 460 patients with Type 2 Diabetes from the endocrinology department of a tertiary hospital in Wuhan,Hubei Province,between April and July 2024.They were randomly divided into 2 subsets for exploratory factor analysis and confirmatory factor analysis.Results A total of 451 valid questionnaires were collected.Exploratory factor analysis extracted 6 common factors,with a cumulative variance contribution of 73.231％.In confirmatory factor analysis,an item was deleted due to failing to meet the standardized loading value criterion.The revised Ego Depletion Scale for Type 2 Diabetes Patients comprised 6 dimensions and 22 items.The total Cronbach's α coefficient was 0.911;split-half reliability was 0.744;the content validity index was 0.860.Correlation coefficients between the total score and scores of each dimension of the scale and the total score of the Self-Regulatory Fatigue Scale ranged from 0.558 to 0.946(P＜0.001).Conclusion The scale exhibits robust reliability and validity,serving as a scientifically instrument for assessing ego depletion in patients with Type 2 Diabetes.

With the growing emphasis on maternal and child oral health, the significance of managing oral health across preconception, pregnancy, and infancy stages has become increasingly apparent. Oral health challenges extend beyond affecting maternal well-being, exerting profound influences on fetal and neonatal oral development as well as immune system maturation. This expert consensus paper, developed using a modified Delphi method, reviews current research and provides recommendations on maternal and child oral health management. It underscores the critical role of comprehensive oral assessments prior to conception, diligent oral health management throughout pregnancy, and meticulous oral hygiene practices during infancy. Effective strategies should be seamlessly integrated across the life course, encompassing preconception oral assessments, systematic dental care during pregnancy, and routine infant oral hygiene. Collaborative efforts among pediatric dentists, maternal and child health workers, and obstetricians are crucial to improving outcomes and fostering clinical research, contributing to evidence-based health management strategies.
Humans ; Pregnancy ; Female ; Infant ; Consensus ; Mouth Diseases/therapy* ; Pregnancy Complications/therapy* ; Oral Health ; Infant, Newborn ; Delphi Technique ; Oral Hygiene

BACKGROUND: Postoperative pulmonary complications (PPCs) are major adverse events in neurosurgical patients. This study aimed to develop and validate machine learning models predicting PPCs after neurosurgery. METHODS: PPCs were defined according to the European Perioperative Clinical Outcome standards as occurring within 7 postoperative days. Data of cases meeting inclusion/exclusion criteria were extracted from the anesthesia information management system to create three datasets: The development (data of Huashan Hospital, Fudan University from 2018 to 2020), temporal validation (data of Huashan Hospital, Fudan University in 2021) and external validation (data of other three hospitals in 2023) datasets. Machine learning models of six algorithms were trained using either 35 retrievable and plausible features or the 11 features selected by Lasso regression. Temporal validation was conducted for all models and the 11-feature models were also externally validated. Independent risk factors were identified and feature importance in top models was analyzed. RESULTS: PPCs occurred in 712 of 7533 (9.5%), 258 of 2824 (9.1%), and 207 of 2300 (9.0%) patients in the development, temporal validation and external validation datasets, respectively. During cross-validation training, all models except Bayes demonstrated good discrimination with an area under the receiver operating characteristic curve (AUC) of 0.840. In temporal validation of full-feature models, deep neural network (DNN) performed the best with an AUC of 0.835 (95% confidence interval [CI]: 0.805-0.858) and a Brier score of 0.069, followed by Logistic regression (LR), random forest and XGBoost. The 11-feature models performed comparable to full-feature models with very close but statistically significantly lower AUCs, with the top models of DNN and LR in temporal and external validations. An 11-feature nomogram was drawn based on the LR algorithm and it outperformed the minimally modified Assess respiratory RIsk in Surgical patients in CATalonia (ARISCAT) and Laparoscopic Surgery Video Educational Guidelines (LAS VEGAS) scores with a higher AUC (LR: 0.824, ARISCAT: 0.672, LAS: 0.663). Independent risk factors based on multivariate LR mostly overlapped with Lasso-selected features, but lacked consistency with the important features using the Shapley additive explanation (SHAP) method of the LR model. CONCLUSIONS: The developed models, especially the DNN model and the nomogram, had good discrimination and calibration, and could be used for predicting PPCs in neurosurgical patients. The establishment of machine learning models and the ascertainment of risk factors might assist clinical decision support for improving surgical outcomes. TRIAL REGISTRATION ChiCTR 2100047474; https://www.chictr.org.cn/showproj.html?proj=128279 .
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Algorithms ; Lung Diseases/etiology* ; Machine Learning ; Neurosurgical Procedures/adverse effects* ; Postoperative Complications/diagnosis* ; Risk Factors ; ROC Curve