Aromatic Chinese medicinal essential oils are volatile oils extracted from aromatic Chinese herbs， which can prevent and treat respiratory infectious diseases through multiple synergistic mechanisms including pathogen inhibition， immune regulation， and inflammatory response regulation. Essential oils are primarily used externally on the body to prevent infections and alleviate symptoms through methods like inhalation， smearing， topical application， bathing， gargling or as a suppository. They can also be utilized in the environment for disinfection and air purification， through methods like diffusion， vaporization， or spraying. The external application of essential oils extracted from Chinese aromatic herbs has the advantages of convenience， quick absorption， and simultaneous influence on both the body and mind. However， there are still challenges and deficiencies in aspects such as the positioning of functions， indications， safety， and the research on the mechanism of action. It has been proposed to combine the theory of aromatic Chinese medicinals with the characteristics of essential oils， and formulate prescriptions of Chinese medicinal essential oils under the principles of traditional Chinese medicine syndrome differentiation， and prevent and treat respiratory infectious diseases efficiently， accurately， and safely， thereby expanding the clinical application of aromatic Chinese medicinals and the preventive theory of traditional Chinese medicine.

Objective:To investigate the current situation of nursing information ability of head nurses in different grades of hospitals in Jiaozuo City, and analyze its influencing variables based on the random forest model, so as to provide evidence-based basis for the construction of nursing information ability improvement strategies and training programs for head nurses.Methods:From August to September 2024, the head nurses of 20 hospitals of different grades were selected by cluster sampling method in Jiaozuo City as the research subjects. General Data Questionnaire and Nursing Information Ability Scale of Head Nurses were used to conduct a cross-sectional survey. Random forest model was used to evaluate the importance of variables, lasso regression analysis was applied to complete the variable screening, and the influencing factors of nursing information ability of head nurses were explored through stepwise multiple linear regression analysis.Results:A total of 305 questionnaires were ultimately collected, of which 297 were valid, the effective rate was 97.38%. Out of 297 head nurses, 6 were male and 291 were female; 49 individuals aged 20-29 years old, 127 individuals aged 30-39 years old, 92 individuals aged 40-49 years old, and 29 individuals aged ≥ 50 years old. The total score of nursing information ability was (139.06 ± 24.62). Random forest model and lasso regression analysis showed that the top 6 variables in terms of importance were the number of years serving as head nurses, participation in information function development, number of academic conferences in the past three years, hospital grade, participating in information training, and chairing or participating in scientific research in the past three years. Stepwise multiple linear regression analysis showed that the number of years serving as head nurses, participating in information training, participating in information function development and number of academic conferences in the past three years had significant effects on nursing information ability of head nurses (t values were -4.66 to 3.81, all P<0.05). Conclusions:The nursing information ability of head nurses in Jiaozuo city is in the middle level, and the nursing information ability of head nurses in different grades of hospitals is different. It is suggested to construct a stepped information ability continuing education framework and a research-information ability coupling development mechanism, and incorporate nursing information ability into the necessary conditions for the appointment of nursing management posts, so as to realize the balanced development of nursing information management ability and the continuous iteration of nursing manager information ability.

Objective:To explore the application value of machine learning prediction model for neural invasion in gallbladder cancer based on enhanced computed tomography (CT) and clinical characteristics.Methods:The retrospective cohort study was conducted. The clinical and imaging data of 502 patients with gallbladder cancer who were admitted to The First Affiliated Hospital of Xinxiang Medical University from January 2010 to June 2024 were collected. There were 171 males and 331 females, aged 65(range, 35?91)years. All patients underwent preoperative abdominal enhanced CT and radical resection. The 502 patients were randomly divided into a training set of 351 cases and a test set of 151 cases at a 7:3 ratio. The training set was used to construct prediction model, and the test set was used to validate prediction model. Observation indicators: (1)neural invasion in gallbladder cancer and influencing factor analysis; (2) construction and validation of machine learning prediction models for neural invasion in gallbladder cancer. Comparison of count data between groups was conducted using the chi-square test. Comparison of ordinal data between groups was conducted using the Mann-Whitney U test. Logistic regression model was performed for univariate and multivariate analyses. Independent influencing factors were incor-porated to construct machine learning models using the standard library modules based on Python 3.9. Receiver operating characteristic (ROC) curves were plotted, and the accuracy, sensitivity, specificity, area under the curve (AUC), precision, F1 score, positive predictive value, negative predic-tive value, and Kappa value were calculated to evaluate the predictive performance of the models. The Delong test was used to assess the differences in AUC among different models in the test set. The Hosmer-Lemeshow test and Brier score were used to evaluate the calibration of the models. Results:(1) Neural invasion in gallbladder cancer and influencing factor analysis. Of the 502 patients with gallbladder cancer, 131 cases had neural invasion, and 371 cases had no neural invasion. Results of multivariate analysis showed that total bilirubin, carcinoembryonic antigen, CA199, CA125, neutrophil-lymphocyte ratio, liver invasion detected by CT, vascular invasion detected by CT, hilar or retroperi-toneal lymph node metastasis detected by CT, and tumor stages T3 and T4 were independent influencing factors for neural invasion in patients with gallbladder cancer [ odds ratios=3.747, 2.395, 3.917, 3.596, 2.805, 2.377, 3.523, 2.774, 5.080, 6.809, 95% confidence interval ( CI) as 1.890?7.430, 1.154?4.971, 2.054?7.472, 1.807?7.155, 1.506?5.225, 1.241?4.553, 1.666?7.449, 1.483?5.189, 2.050?12.589, 2.552?18.168, P<0.05]. (2) Construction and validation of machine learning predic-tion models for neural invasion in gallbladder cancer. Based on the independent influencing factors, seven machine learning models were constructed, including logistic regression, K-nearest neighbors, support vector machine, random forest, decision tree, back-propagation neural network, and gradient boosting machine. The ROC curves of seven machine learning models in the test set were plotted, and the AUC were 0.900(95% CI as 0.851?0.948), 0.741(95% CI as 0.646?0.829), 0.836(95% CI as 0.762?0.895), 0.782(95% CI as 0.701?0.855), 0.839(95% CI as 0.770?0.901), 0.817(95% CI as 0.738?0.887), 0.843(95% CI as 0.770?0.909), respectively. Results of Delong test showed that the logistic regression model had the highest AUC. The sensitivity and specificity of the logistic regression model were 0.868 and 0.805 respectively, indicating the best balance. Results of Hosmer-Lemeshow test showed that the logistic regression model had a good goodness-of-fit ( χ2=5.320, P>0.05). The Brier score of the logistic regression model was relatively low, as 0.168, which verified its calibration advantage. Conclusion:Total bilirubin, carcinoembryonic antigen, CA199, CA125, neutrophil-to-lymphocyte ratio, liver invasion detected by enhanced CT, vascular invasion detected by enhanced CT, hilar or retroperitoneal lymph node metastasis detected by enhanced CT, and tumor stages T3 and T4 are independent influencing factors for nerve invasion in patients with gallbladder cancer. Seven machine learning models are constructed based on enhanced CT and clinical characteristics to predict neural invasion in gallbladder cancer, of which the logistic regression model demonstrates good predictive performance.

Lung cancer poses a serious threat to global public health security.Chemotherapy,as the main strategy for cancer treatment,faces challenges such as high toxicity and drug resistance.Anticancer peptides have the potential of being developed into new anticancer drugs due to their advantages of broad-spectrum anticancer activity,rapid action,and difficulty in generating drug resistance,but they also face shortcomings such as weak activity and strong toxic side effects.The weakly acidic microenvironment of tumors(pH 6.5-6.8)provides a good idea for the design of anticancer peptides of high-efficiency and low-toxicity.Previously,we designed the acid-sensitive antibacterial peptide pHly-1 using the wolf spider(Lycosa singoriensis)toxin Lycosin-Ⅰ as a template.In this study,we found that pHly-1 also had acid-sensitive anticancer activity.Further alanine scanning analysis of pHly-1 was carried out,and we ob-tained a mutant pHTP-2 with better acid sensitivity,whose IC50(half maximal inhibitory concentration)against A549 cells was 15.68 μmol/L at pH 6.6 and was greater than 100 μmol/L at pH 7.4.At pH 6.6,pHTP-2 could act on various lung cancer cell lines and induce the death of A549 cells by rapid ly-sis;at pH 7.4,500 μmol/L pHTP-2 had weak toxicity to red blood cells(the hemolysis rate was ap-proximately 38％)and primary myocardial cells(the inhibition rate was 49.7％,with P＜0.05).Analy-sis of its charge,particle size,morphology,and secondary structure showed that at pH 6.6,the histidine in the sequence of pHTP-2 was protonated,increasing the positive charge(P＜0.01),decreasing the hy-drated particle size(P＜0.05)and forming an α-helical structure to induce membrane lysis of A549 cells.At pH 7.4,it was deprotonated,the positive charge decreases,a β-sheet structure was formed and self-aggregation occurred,limiting its effect on the A549 cell membrane and showing weak activity.In summary,pHTP-2 could respond to the weakly acidic microenvironment of tumors to exert selective cyto-toxic activity,effectively overcoming the shortcomings of anticancer peptides such as low efficiency and high toxicity.Our findings suggest that it is a high-quality lead molecule for anticancer drugs.

OBJECTIVE: Circadian rhythm disruption (CRD) is a risk factor that correlates with poor prognosis across multiple tumor types, including hepatocellular carcinoma (HCC). However, its mechanism remains unclear. This study aimed to define HCC subtypes based on CRD and explore their individual heterogeneity. METHODS: To quantify CRD, the HCC CRD score (HCCcrds) was developed. Using machine learning algorithms, we identified CRD module genes and defined CRD-related HCC subtypes in The Cancer Genome Atlas liver HCC cohort (n = 369), and the robustness of this method was validated. Furthermore, we used bioinformatics tools to investigate the cellular heterogeneity across these CRD subtypes. RESULTS: We defined three distinct HCC subtypes that exhibit significant heterogeneity in prognosis. The CRD-related subtype with high HCCcrds was significantly correlated with worse prognosis, higher pathological grade, and advanced clinical stages, while the CRD-related subtype with low HCCcrds had better clinical outcomes. We also identified novel biomarkers for each subtype, such as nicotinamide n-methyltransferase and myristoylated alanine-rich protein kinase C substrate-like 1. CONCLUSION We classify the HCC patients into three distinct groups based on circadian rhythm and identify their specific biomarkers. Within these groups greater HCCcrds was associated with worse prognosis. This approach has the potential to improve prediction of an individual's prognosis, guide precision treatments, and assist clinical decision making for HCC patients. Please cite this article as: Li XJ, Chang L, Mi Y, Zhang G, Zhu SS, Zhang YX, et al. Integrated-omics analysis defines subtypes of hepatocellular carcinoma based on circadian rhythm. J Integr Med. 2025; 23(4): 445-456.
Humans ; Carcinoma, Hepatocellular/pathology* ; Liver Neoplasms/pathology* ; Circadian Rhythm/genetics* ; Prognosis ; Male ; Female ; Biomarkers, Tumor/genetics* ; Middle Aged ; Machine Learning ; Computational Biology

OBJECTIVE: This cross-sectional study assessed the methodological quality of systematic reviews (SRs) of Chinese herbal medicine (CHM) published in Chinese between Jan 2021 and Sep 2022. METHODS: Chinese language CHM SRs were identified through literature searches across 3 international and 4 Chinese databases. Methodological quality was appraised using A MeaSurement Tool to Assess systematic Reviews 2. Logistic regressions were used to explore associations between bibliographical characteristics and quality. RESULTS: Analyses of methodological quality found that among the 213 sampled SRs, 69.5% were of critically low quality, 30.5% were of low quality, and none achieved high or moderate quality. Common shortcomings included the failure to identify the studies excluded from the analysis, failure to disclose funding sources, and limited evaluation of the potential impact of bias on conclusions. Logistic regressions revealed that SRs led by corresponding authors affiliated with universities or academic institutions tended to be of lower quality than SRs led by authors affiliated with hospitals or clinical facilities. CONCLUSION Recent Chinese language CHM SRs exhibited limited methodological quality, making them unlikely to support the development of clinical practice guidelines. Urgent initiatives are needed to enhance training for researchers, peer-reviewers and editors involved in the preparation and publication of SRs. Adoption of Preferred Reporting Items for Systematic Reviews and Meta-Analyses reporting guidelines in Chinese language journals is crucial to improve the relevance of SRs for Chinese medicine development. Addressing deficiencies in methodology and reporting is essential for promoting evidence-based practices and informed clinical decisions in Chinese medicine. Please cite this article as: Jiang Y, Zhong CC, Wang BH, Xu SS, Ho FF, Kwong MH, Ho L, Zhou JHS, Lam KC, Liu JP, Zhang BT, Chung VCH. Methodological quality of systematic reviews on orally administered Chinese herbal medicine published in Chinese between 2021 and 2022: A cross-sectional study. J Integr Med. 2025; 23(5):492-501.
Cross-Sectional Studies ; Drugs, Chinese Herbal/administration & dosage* ; Systematic Reviews as Topic/standards* ; Humans ; China ; Administration, Oral ; Medicine, Chinese Traditional

OBJECTIVE: We aimed to investigate the patterns of fasting blood glucose (FBG) trajectories and analyze the relationship between various occupational hazard factors and FBG trajectories in male steelworkers. METHODS: The study cohort included 3,728 workers who met the selection criteria for the Tanggang Occupational Cohort (TGOC) between 2017 and 2022. A group-based trajectory model was used to identify the FBG trajectories. Environmental risk scores (ERS) were constructed using regression coefficients from the occupational hazard model as weights. Univariate and multivariate logistic regression analyses were performed to explore the effects of occupational hazard factors using the ERS on FBG trajectories. RESULTS: FBG trajectories were categorized into three groups. An association was observed between high temperature, noise exposure, and FBG trajectory ( P < 0.05). Using the first quartile group of ERS1 as a reference, the fourth quartile group of ERS1 had an increased risk of medium and high FBG by 1.90 and 2.21 times, respectively (odds ratio [ OR] = 1.90, 95% confidence interval [ CI]: 1.17-3.10; OR = 2.21, 95% CI: 1.09-4.45). CONCLUSION An association was observed between occupational hazards based on ERS and FBG trajectories. The risk of FBG trajectory levels increase with an increase in ERS.
Humans ; Male ; Adult ; Blood Glucose/analysis* ; China ; Prospective Studies ; Occupational Exposure/adverse effects* ; Risk Factors ; Middle Aged ; Steel ; Fasting/blood* ; Metal Workers ; East Asian People

Ferritin, a ubiquitous protein in living organisms, plays a crucial role in storing and converting iron, as well as maintaining cellular iron metabolism balance. Due to the ability of self-assembling into unique nanocage-like structures in vitro and the special physicochemical properties, ferritin has garnered extensive attention in the biomedical field. This paper provides a brief overview of the structure and cargo loading strategies of ferritin, with a specific focus on its applications in various biological fields such as nanomedicine, bioimaging, and nanoparticle vaccine carriers. The aim is to offer a valuable reference for the future research involving ferritin nanoparticles.
Ferritins/chemistry* ; Nanoparticles/chemistry* ; Humans ; Nanomedicine/methods* ; Animals

Objective:To observe the early efficacy of intense pulsed light(IPL)combined with non-ablative fractional laser(NAFL)in preventing postoperative pathological scar formation and intervention of inflammatory factors.Methods:93 patients with postoperative pathological scar formation who were admitted to our hospital from March 2022 to September 2024 were selected,they were divided into control group A(silicone gel treatment,n=31),control group B(NAFL on the basis of control group A,n=31)and study group(IPL on the basis of control group B,n=31)using the random number table method.The clinical efficacy,simple quality of life scale(SF-36),vancouver scar scale(VSS),inflammatory factors[interleukin-6(IL-6),tumor necrosis factor-α(TNF-α),C-reactive protein(CRP)],and adverse reactions among three groups were compared.Results:The clinical total effective rate in the study group were higher than those in the control group A and control group B(P＜0.05).SF-36 increased sequentially and VSS decreased sequentially in control group A,control group B,and study group after treatment(P＜0.05).CRP,IL-6,and TNF-α decreased sequentially in control group A,control group B,and study group after treatment(P＜0.05).There was no significant difference in the incidence of adverse reactions among the three groups(P＞0.05).Conclusion:IPL combined with NAFL in preventing postoperative pathological scar formation,can effectively reduce scar formation,reduce inflammatory factors levels,improve patients' quality of life,and be safe and reliable.

Objective:To investigate the clinical management,complications,and prognostic prediction model of bronchopulmonary dysplasia(BPD)in preterm infants.Methods:A total of 854 very preterm infants(gestational age ≤ 32 weeks)admitted to the Neonatal Intensive Care Unit(NICU)of Shanghai Children's Hospital from January 2018 to December 2022 were retrospectively enrolled.After applying inclusion and exclusion criteria,713 infants were included.Based on the 2018 National Institute of Child Health and Human Development(NICHD)diagnostic criteria for BPD,the cohort was divided into a BPD group(n=164)and a non-BPD group(n=549).Clinical data of infants and maternal characteristics were compared between groups.Univariate and stepwise multivariate logistic regression analyses were performed to identify independent risk factors for BPD and evaluate clinical management.A nomogram model was subsequently developed to predict BPD prognosis.Results:Gestational age,duration of non-invasive ventilation,total oxygen therapy time,total hospital stay,hemodynamically significant patent ductus arteriosus(hsPDA),maximum diameter of patent ductus arteriosus(PDA),fetal growth restriction(FGR),use of vasoactive agents,and proportion of pulmonary surfactant administration were identified as independent risk factors for BPD(all P＜0.05,OR＞0).The nomogram model demonstrated excellent predictive performance,with an area under the receiver operating characteristic curve(AUC)of 0.93 and a calibration curve slope approaching 1.The Hosmer-Lemeshow goodness-of-fit test indicated satisfactory model calibration(x2=8.2865,P=0.406).Conclusion:Gestational age,non-invasive ventilation duration,total oxygen therapy time,total hospital stay,hsPDA,PDA maximum diameter,FGR,vasoactive agents,and pulmonary surfactant use are critical predictors of BPD in preterm infants.The prognostic models for BPD incidence and severity,constructed based on these factors,exhibit strong predictive accuracy and may serve as a valuable clinical tool for risk stratification and early intervention.