Parkinson's disease （PD） is a neurodegenerative disorder primarily characterized by motor dysfunction. Traditionally， its main clinical features include resting tremor， muscular rigidity， bradykinesia， and postural balance disorders. However， an increasing number of studies have shown that its non-motor symptoms （NMS） exert an even greater impact on patients' quality of life than motor symptoms， severely affecting daily functioning and increasing the burden on families and society. Among these， depression is one of the most common and most debilitating NMS， with statistics indicating that the incidence of depression among PD patients reaches as high as 40%-50%. The pathological mechanisms are complex， involving the interplay between degenerative changes in dopaminergic neurons and disruptions in emotional regulatory circuits， which poses a substantial challenge to clinical treatment. Traditional Chinese medicine （TCM）， characterized by holistic regulation and multi-target intervention， has demonstrated significant advantages in the treatment of PD and depression， offering new insights for managing PD-depression comorbidity. This study integrates research extracted from multiple databases， including PubMed， Web of Science， Google Scholar， and China National Knowledge Infrastructure （CNKI）， that investigates the potential mechanisms of PD and depression as well as TCM-based treatments for these conditions. The aim is to elucidate the shared pathological mechanisms underlying PD and depression and to explore the therapeutic potential of TCM in effectively combating PD-depression comorbidity through these shared mechanisms， thereby providing valuable insights for the development of targeted therapies.

Objective To analyze the efficacy of CT-guided alcohol ablation of splanchnic nerve block(SNB)in the treatment of pain in patients with pancreatic cancer,and to discuss the related factors influencing the effectiveness in treating pancreatic cancer pain.Methods The clinical data of patients with pancreatic cancer pain,who was unable to receive surgery and underwent CT-guided SNB at Hai'an People's Hospital from June 2018 to September 2023,were retrospectively analyzed.According to postoperative one-month VAS pain score and the used dosage of opioids,the improvement of pain was assessed.Logistic regression analysis was used to evaluate the demographic characteristics,tumor features,and pain-related factors so as to determine the predictive factors for effective analgesia after SNB,and the survival outcomes were compared between the patients with effective SNB analgesia and the patients with ineffective SNB analgesia.Results A total of 133 patients were included in this analysis.One week after SNB,74.4％of patients achieved effective pain relief,and one month after the procedure,54.9％of patients experienced effective pain relief.One month after treatment,multivariate logistic regression analysis showed that the diabetes(OR=0.637,95％CI=0.397-0.876,P=0.034),serum CA199(OR=1.531,95％CI=1.030-2.370,P=0.042),serum MMP-1(OR=0.703,95％CI=0.457-0.983,P=0.038),preoperative ECOG score(OR=2.693,95％CI=1.234-6.609,P=0.021),and preoperative daily morphine consumption(OR=2.797,95％CI=1.148-6.695,P=0.019)were the independent predictive factors for achieving a good analgesic efficacy after SNB.Patients with poor analgesic outcomes after SNB had a significantly lower median survival time when compared to patients with good analgesic outcomes(82 days vs 149 days,P＜0.05).No serious SNB-related adverse events occurred.Conclusion For the treatment of refractory pancreatic cancer pain,CT-guided SNB is clinically safe and effective.The diabetes,ECOG score,serum MMP-1 level,CA199 level,and preoperative daily used dosage of opioids are the independent predictive factors for the efficacy of CT-guided SNB in treating pancreatic cancer pain.

ObjectiveThis study aims to explore the neurotoxicity mechanism of Dictamni Cortex by integrating network toxicology and metabolomics techniques. MethodsThe neurotoxicity targets induced by Dictamni Cortex were screened by the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform （TCMSP）， Traditional Chinese Medicine Information Database （TCM-ID）， and Comparative Toxicogenomics Database （CTD）. The target predictions of the components were performed by the Swiss Target Prediction tool. Neurotoxicity-related targets were collected from the Pharmacophore Mapping and Potential Target Identification Platform （PharmMapper）， GeneCards Human Gene Database （GeneCards）， DisGeNET Disease Gene Network （DisGeNET）， and Online Mendelian Inheritance in Man （OMIM）， and the intersection targets were identified. Protein-protein interaction （PPI） analysis， Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway analysis， and Gene Ontology （GO） enrichment analysis were conducted. A "drug-compound-toxicity target-pathway" network was constructed via Cytoscape software to display the core regulatory network. Based on the prediction results， the neurotoxicity mechanism of Dictamni Cortex in mice was verified by using hematoxylin-eosin （HE） staining， Nissl staining， enzyme-linked immunosorbent assay （ELISA）， quantitative real-time fluorescence polymerase chain reaction （Real-time PCR）， and Western blot. The effects of Dictamni Cortex on the metabolic profile of mouse brain tissue were further explored by non-targeted metabolomics. ResultsNetwork toxicology screening identified 13 compounds and 175 targets in Dictamni Cortex that were related to neurotoxicity. PPI network analysis revealed that serine/threonine-protein kinase （Akt1） and tumor protein 53 （TP53） were the core targets. Additionally， GO/KEGG enrichment analysis indicated that Dictamni Cortex may regulate the phosphatidylinositol 3-kinase （PI3K）/Akt pathway and affect oxidative stress and cell apoptosis， thereby inducing neural damage. The "Dictamni Cortex-compound-toxicity target-pathway-neural damage" network showed that dictamnine， phellodendrine， and fraxinellone may be the toxic compounds. Animal experiments showed that compared with those in the blank group， the hippocampal neurons in the brain tissue of mice treated with Dictamni Cortex were damaged. The level of superoxide dismutase （SOD） and acetylcholine （ACh） in the brain tissue was significantly reduced， while the content of malondialdehyde （MDA） was significantly increased. The level of Akt1 and p-Akt1 mRNAs and proteins in the brain tissue was significantly decreased， while the level of TP53 was significantly increased. Non-targeted metabolomics results showed that Dictamni Cortex could disrupt the level of 40 metabolites in mouse brain tissue， thereby regulating the homeostasis of 13 metabolism pathways， including phenylalanine， glycerophospholipid， and retinol. Combined analysis revealed that Akt1， p-Akt1， and TP53 were significantly correlated with phenylalanine， glycerophospholipid， and retinol metabolites. This suggested that Dictamni Cortex induced neurotoxicity in mice by regulating Akt1， p-Akt1， and TP53 and further modulating the phenylalanine， glycerophospholipid， and retinol metabolism pathways. ConclusionDictamni Cortex can induce neurotoxicity in mice， and its potential mechanism may be closely related to the activation of oxidative stress， inhibition of the PI3K/Akt signaling pathway， and regulation of phenylalanine， glycerophospholipid， and retinol metabolism pathways.

ObjectiveThis study aims to investigate the effect of Dictamni Cortex on intestinal barrier damage in rats and its mechanism by untargeted metabolomics and targeted metabolomics for short-chain fatty acids （SCFAs）. MethodsRats were randomly divided into a control group， a high-dose group of Dictamni Cortex （8.1 g·kg^-1）， a medium-dose group （2.7 g·kg^-1）， and a low-dose group （0.9 g·kg^-1）. Except for the control group， the other groups were administered different doses of Dictamni Cortex by gavage for eight consecutive weeks. Hematoxylin-eosin （HE） staining was used to observe the pathological changes in the ileal tissue. Enzyme-linked immunosorbent assay （ELISA） was employed to detect the level of cytokines， including tumor necrosis factor-α （TNF-α）， interleukin-6 （IL-6）， and interleukin-1β （IL-1β）， in the ileal tissue of rats. Quantitative real-time fluorescence polymerase chain reaction （Real-time PCR） technology was used to detect the expression level of tight junction proteins， including zonula occludens-1 （ZO-1）， Occludin， and Claudin-1 mRNAs， in the ileal tissue of rats to preliminarily explore the effects of Dictamni Cortex on intestinal damage. The dose with the most significant toxic phenotype was selected to further reveal the effects of Dictamni Cortex on the metabolic profile of ileal tissue in rats by non-targeted metabolomics combined with targeted metabolomics for SCFAs. ResultsCompared with the control group， all doses of Dictamni Cortex induced varying degrees of pathological damage in the ileum， increased TNF-α （P<0.01）， IL-6 （P<0.01）， and IL-1β （P<0.01） levels in the ileal tissue， and decreased the expression level of ZO-1 （P<0.05， P<0.01）， Occludin （P<0.01）， and Claudin-1 （P<0.05） in the ileal tissue， with the high-dose group showing the most significant toxic phenotypes. The damage mechanisms of the high-dose group of Dictamni Cortex on the ileal tissue were further explored by integrating non-targeted metabolomics and targeted metabolomics for SCFAs. The non-targeted metabolomics results showed that 21 differential metabolites were identified in the control group and the high-dose group. Compared with that in the control group， after Dictamni Cortex intervention， the level of 14 metabolites was significantly increased （P<0.05， P<0.01）， and the level of seven metabolites was significantly decreased （P<0.05， P<0.01） in the ileal contents. These metabolites collectively acted on 10 related metabolic pathways， including glycerophospholipids and primary bile acid biosynthesis. The quantitative data of targeted metabolomics for SCFAs showed that Dictamni Cortex intervention disrupted the level of propionic acid， butyric acid， acetic acid， caproic acid， isobutyric acid， isovaleric acid， valeric acid， and isocaproic acid in the ileal contents of rats. Compared with those in the control group， the level of isobutyric acid， isovaleric acid， and valeric acid were significantly increased， while the level of propionic acid， butyric acid， and acetic acid were significantly decreased in the ileal contents of rats after Dictamni Cortex intervention （P<0.05， P<0.01）. ConclusionDictamni Cortex can induce intestinal damage by regulating glycerophospholipid metabolism， primary bile acid biosynthesis， and metabolic pathways for SCFAs.

Due to its high sensitivity and non-destructive nature, Raman spectroscopy has become an essential analytical tool in biopharmaceutical analysis and drug development. Despite of the computational demands, data requirements, or ethical considerations, artificial intelligence (AI) and particularly deep learning algorithms has further advanced Raman spectroscopy by enhancing data processing, feature extraction, and model optimization, which not only improves the accuracy and efficiency of Raman spectroscopy detection, but also greatly expands its range of application. AI-guided Raman spectroscopy has numerous applications in biomedicine, including characterizing drug structures, analyzing drug forms, controlling drug quality, identifying components, and studying drug-biomolecule interactions. AI-guided Raman spectroscopy has also revolutionized biomedical research and clinical diagnostics, particularly in disease early diagnosis and treatment optimization. Therefore, AI methods are crucial to advancing Raman spectroscopy in biopharmaceutical research and clinical diagnostics, offering new perspectives and tools for disease treatment and pharmaceutical process control. In summary, integrating AI and Raman spectroscopy in biomedicine has significantly improved analytical capabilities, offering innovative approaches for research and clinical applications.

Objective:To retrospectively analyze the pathogenic factors of retrograde peri-implantitis (RPI) and assess the effectiveness of treatment, and to provide clinicians evidence for the prevention and treatment of RPI.Methods:A total of 2 731 patients with missing teeth (4 016 implants) who underwent implant restoration in the Department of Stomatology, The First Affiliated Hospital of Wenzhou Medical University between January 2004 and December 2022 were included in the study. According to the diagnostic criteria of RPI, a total of 20 cases (23 implants) of RPI were collected, including 4 female (5 implants) and 16 male (18 implants), and the treatment medical records, intraoral photos and cone beam CT or oral panoramic radiographs records of each patient were collected. Each patient with RPI was treated accordingly and followed up regularly to evaluate its efficacy.Results:After treatment, the follow-up time for 20 patients with clinical symptoms of RPI was 13 (6, 40) months (1 month to 13 years), and the survival rate of the treated implants was 91% (21/23). There were 7 patients (8 implants) with inactive RPI, no clinical symptoms, no loosening of the implant, with normal occlusal load, and the disease was at the inactive stage and was not treated. The pulp vitality of the natural tooth adjacent to the implant was normal, and the implant could function normally. There were 13 patients (15 implants) with infected RPI, 1 patient (1 implant) had no loosening of the implant, and the periapical radiolucency of the implant disappeared after endodontic treatment of the natural tooth adjacent to the implant; 12 patients (14 implants) had clinical symptoms such as implant loosening, pus discharge, etc. Among them, 10 patients (12 implants) were successfully implanted in situ or in adjacent sites after removing the implants, and were successfully implanted after 3 to 20 months. Two patients(2 implants) were removed and no further implants were placed. Among them, 2 implants with infected RPI had cystic lesions, which was similar to natural root apex cysts.Conclusions:The etiology of RPI is related to inflammation of adjacent tooth root tips or bacterial residues from inflammatory lesions in the alveolar bone and bone augmentation. RPI can be treated by perfect root canal treatment of adjacent teeth, removal of inflammatory tissue, or simultaneous guided bone regeneration techniques.

Dyslipidemia refers to the increased level of TG and total cholesterol in plasma, and also generally refers to other forms of dyslipidemia, which is characterized by non-obvious symptoms in the early stage of the disease, and the first episode is cardiovascular disease. The prevalence of dyslipidemia varies with country, region and population, and the prevalence of dyslipidemia in China is in increase, which is influenced by various risk factors. This paper summarizes the prevalence and risk factors of dyslipidemia and introduces the emerging risk factors of dyslipidemia, such as HIV infection, systemic lupus erythematosus, sarcopenia and environmental problem.

Objective:To develop the Nurse Parenting Stress Scale and evaluate its reliability and validity.Methods:Based on Abidin's Parenting Stress Theory, scale items were generated through literature review and semi-structured interviews. The initial version was constructed via Delphi expert consultation. Using a convenience sampling method, nurses from six hospitals in Shandong Province were surveyed between August and October 2024. The first survey collected 314 questionnaires (308 valid, effective recovery rate 98.1%) for item analysis and exploratory factor analysis (EFA). The second survey collected 458 questionnaires (447 valid, effective recovery rate 97.6%) for confirmatory factor analysis (CFA) .Results:The Nurse Parenting Stress Scale consists of 4 dimensions and 31 items. The Cronbach's α coefficient of the total scale was 0.951, split-half reliability was 0.782, and test-retest reliability was 0.926. EFA extracted four common factors explaining 70.241% of the cumulative variance. CFA demonstrated a good model fit. The item-level content validity index ( I- CVI) ranged from 0.889 to 1.000, the scale-level universal agreement content validity index ( S- CVI/ UA) was 0.903, and the scale-level average content validity index ( S- CVI/ Ave) was 0.989. Conclusions:The Nurse Parenting Stress Scale shows strong reliability and validity and can serve as an effective tool for assessing parenting stress among nurses.

Objective To construct a quality control model for cervical liquid-based thin cell smears using two different artificial intelligence(AI)techniques and to compare the total use of the two methods to improve the level of quality control of cervical liquid-based thin cell smears through the assistance of hybrid AI.Methods In this study,105 cervical liquid-based thin cell smear samples were used.Convolutional neural network(CNN)algorithm and Transformer network algorithm were used as specific AI algorithms in the AI model.The labeled features included the number of cells in the slice,excessive red blood cells,excessive inflammatory cells,and air bubbles.The smear samples were pre-processed and digitized by smear,followed by image segmentation and feature extraction.Using the labeled feature data,machine learning models were trained and optimized.Statistical AI and physician QC results were analyzed by calculating KAPPA index,sensitivity,specificity,area under the curve(AUC),and other indexes for AI QC results.Results CNN algorithm QC results in normal smear,inflammatory background and bloody background were significantly different from the expert review QC results(P＜0.001).Transformer algorithm QC results were similar to the expert review results,with no statistical difference(P＞0.05).General practitioner QC results were statistically different from the expert review QC results in normal smear detection rate and bloody background(P＜0.001).CNN algorithm Kappa value was 0.567,which had medium consistency with expert review results.Transformer algorithm Kappa value was 0.890,with the best consistency with expert review results.General practitioner Kappa value was 0.675,which had better consistency with expert review results.Using the expert review results as a reference standard,the predictive efficacy of the Transformer algorithm and the general practitioners' QC results was evaluated,and the predictive efficacy of the Transformer algorithm was higher than that of the general practitioners in detecting hemorrhagic backgrounds and normal smears(inflammatory backgrounds:AUC=1.000;normal smears:AUC=0.768)(hemorrhagic backgrounds:AUC=0.849;normal smears:AUC=0.849;normal smear:AUC=0.500).Conclusion In this study,we found that the Transformer algorithm was effective in improving the quality control of cervical liquid-based thin-layer cell smears by assisting doctors to perform smear quality control scoring and improving the efficiency and accuracy of smear sample quality control.It can be used as a new quality control method for cervical cancer cytological screening and has potential clinical applications.

Electrical impedance tomography (EIT) is a new non-invasive functional imaging technology, which has the advantages of non-invasion, non-radiation, low cost, fast response, portability and visualization. In recent years, more and more studies have shown that EIT has great potential in the detection of lung diseases and has been applied to early diagnosis and treatment of some diseases. This paper introduced the basic principle of EIT, discussed the research and clinical application of EIT in the detection of acute respiratory distress syndrome, chronic obstructive pulmonary disease, pneumothorax and pulmonary embolism, and focused on the summary and introduction of indicators and functional images of EIT related to the detection of lung diseases. This review will help medical workers understand and use EIT, and promote the further development of EIT in lung diseases as well as other fields.
Humans ; Electric Impedance ; Tomography/methods* ; Lung Diseases/diagnosis* ; Pulmonary Disease, Chronic Obstructive/diagnosis* ; Pulmonary Embolism/diagnosis* ; Respiratory Distress Syndrome/diagnosis*