Humans ; Amyloidosis ; Amyloid ; Cardiomyopathies

Objective To study changes in immune cells and cytokines during the reactivation stage of varicella-zoster virus(VZV)in patients with herpes zoster.Methods A total of 50 patients with herpes zoster and 30 healthy individuals were selected from Xi'an Ninth Hospital between May 2022 and October 2022.Flow cytometry was used to detect the proportion of peripheral blood CD3+cells,CD4+cells,CD8+T cells,B cells and NK cells,as well as levels of cytokines IL-2,IFN-γ,IL-10 and IL-6.We analyzed the immune mechanism of VZV reactivation stage in herpes zoster patients.Results Compared with the healthy control group,the proportion of CD3+cells and CD4+T cells in herpes zoster patients decreased significantly;the proportion of NK cells significantly increased;the levels of IFN-γ,IL-10 and IL-6 significantly increased;the proportion of CD8+T cells,B cells and IL-2 content showed an increasing trend,but there was no significant difference.In addition,the severity of neurological involvement in herpes zoster patients might affect changes in cytokine levels.Conclusion During the reactivation period of VZV,changes in the proportion of immune cells and cytokine expression levels are closely related to the occurrence and development of herpes zoster.

Objective:To build a medical consumables demand prediction model to predict the demand for medical consumables,and to reduce the occurrence of emergency replenishment and shortage of medical consumables.Methods:The medical consumables demand prediction model was established using support vector regression(SVR)algorithm,the replenishment strategy and inventory control strategy optimization model was established using multiple population genetic algorithm(MPGA)to build a medical consumables demand forecasting model,and the replenishment strategy and inventory control strategy were automatically generated.The relevant data of supply-processing-distribution(SPD)mode introduced by Benxi Central Hospital for medical consumables management from January 2019 to May 2023 were selected for model training,model validation test(test set)and model application prediction(application set),respectively.The average absolute prediction error,peak prediction error and trough of prediction error of the model were evaluated,and the average ratio of consumption per day to inventory cost,the average number of urgent orders per month,the average number of out of stock per month,the average number of non-urgent orders per month and the decreasing range of the index weekly average were compared.Results:There was no statistically significant difference in the average absolute prediction error between the model test set and the application set(P＞0.05).The average absolute prediction error of the model was 0.033 5±0.024 5,the peak prediction error was 0.071 7 and the trough of prediction error was-0.0090.After the application of the model,the ratio of average daily consumption to inventory cost,the average number of monthly emergency order frequency,the average number of shortage of stock,and the average number of monthly non-emergency orders were(0.457 5±0.060 3),(23.95±6.04),(5.58±2.17),and(20.68±2.77),respectively.The ratio of daily average consumption to inventory cost was higher than that before the application,the average number of monthly emergency order,shortage of stock,and monthly non-emergency order were lower than those before the application,the difference was statistically significant(F=371.912,88.486,124.472,142.138,P＜0.000).After the application of the model,the weekly average inventory amount decreased by 43.66%,and the average number of emergency replenishment decreased by 53.76%,the average number of shortages of stock decreased by 76.95%,and the average shortage of stock normal replenishments decreased by 34.41%.Conclusion:The medical consumables demand prediction model can predict the demand for medical consumables,optimize replenishment and inventory control strategies,reduce the cost of medical consumables inventory,reduce occurrence of emergency replenishment and shortages of stock,and reduce the number of normal replenishment.

Ulcerative colitis(UC)is characterized by chronic relapsing intestinal inflammation.Currently,there is no effective treatment for the disease.According to our preliminary data,1,8-cineole,which is the main active compound of Amomum compactum Sol.ex Maton volatile oil and an effective drug for the treat-ment of pneumonia,showed remarkable anti-inflammatory effects on colitis pathogenesis.However,its mechanism of action and direct targets remain unclear.This study investigated the direct targets and mechanism through which 1,8-cineole exerts its anti-inflammatory effects using a dextran sulfate so-dium salt-induced colitis mouse model.The effects of 1,8-cineole on macrophage polarization were investigated using activated bone marrow-derived macrophages and RAW264.7 cells.In addition,1,8-cineole targets were revealed by drug affinity responsive target stability,thermal shift assay,cellular thermal shift assay,and heat shock protein 90(HSP90)adenosine triphosphatases(ATPase)activity assays.The results showed that 1,8-cineole exhibited powerful anti-inflammatory properties in vitro and in vivo by inhibiting the macrophage M1 polarization and protecting intestinal barrier function.Mech-anistically,1,8-cineole directly interacted with HSP90 and decreased its ATPase activity,also inhibited nucleotide-binding and oligomerization domain-,leucine rich repeat-,and pyrin domain-containing 3(NLRP3)binding to HSP90 and suppressor of G-two allele of SKP1(SGT1)and suppressed NLRP3 inflammasome activation in macrophages.These results demonstrated that 1,8-cineole is a potential drug candidate for UC treatment.

Objective The diagnosis of nasal fractures poses challenges in forensic clinical evaluation.This study aims to develop and enhance an artificial intelligence-based model for nasal fracture recognition,evaluate its performance,and provide assistance and support for forensic clinical identification.Methods Multi-center nasal CT images were selected and screened according to the consensus standards set by Chinese experts in nasal CT examination and diagnosis.A recognition model was constructed,followed by external verification and evaluation.Additionally,the diagnostic capabilities of qualified appraisers/doctors with different professional titles(primary,intermediate,and senior)were compared with the performance of the intelligent recognition model.The accuracy,sensitivity,specificity),and negative predictive value(NP)of the intelligent recognition model were comprehensively evaluated.Results The intelligent recognition model exhibited high diagnostic efficiency and stability.It improved the diagnostic accuracy of radiologists and appraisers in detecting nasal fractures while effectively bridging the gap between inexperienced doctors/appraisers and experienced ones.Conclusion The intelligent recognition model for nasal fractures can assist appraisers in enhancing their ability to locate such fractures on CT images and improve work efficiency while enhancing appraisal opinions'accuracy and scientificity.

Objective To conduct a comprehensive visual analysis of the application of Artificial Intelligence(AI)in forensic medicine using bibliometric tools so as to create knowledge maps of cooperation network,research hotspots,important findings,and potential future trends in this field.Methods The Web of Science(WoSCC)was utilized as the primary data source,search formula incorporating AI and forensic medicine as core subject words was constructed,resulting in a dataset comprising 2 287 literature records.Vosviewer,Citespace,and Bibliometrix were employed for analyzing various aspects such as cooperation network,keyword co-occurrence networks,clustering dynamics,clusters,centrality degree and thematic strategic coordinate charts.These analyses facilitated the creation of corresponding visual maps.Results The collaboration among authors still requires further strengthening;however significant groups have emerged among institutions and countries.Research hotspots and important findings predominantly revolve around algorithmic applications.Furthermore,"identification"related research appears to become a prominent future research trend.Conclusion By employing bibliometric analysis techniques on the application of artificial intelligence in forensic medicine domain,this study successfully elucidats cooperation networks,research hotspots,important findings,future research directions,and provides objective support through empirical evidence for related studies.

Objective:To investigate the clinical and cardiac magnetic resonance (CMR) characteristics of heart involvement in patients with Fabry disease (AFD).Methods:From January 2018 to March 2021, eight AFD patients [3 males and 5 females, mean age (50±11) years old, range 26-60 years old] confirmed by genetic testing or pathology in Fuwai Hospital were retrospectively included in this study. At the same time, sixteen patients with hypertrophic cardiomyopathy (HCM) [6 males and 10 females, mean age (46±15) years old] and 16 healthy individuals [6 males and 10 females, mean age (51±11) years old] were included as controls. The clinical baseline data and CMR data of the patients were collected and analyzed. The CMR data were analyzed using the software CVI42, with the corresponding parameters automatically generated. One-way ANOVA or Kruskal-Wallis test was used to compare the differences in the parameters among the three groups. Independent-samples t test, Fisher precise test or Mann-Whitney U test were used for the comparison between each two groups. Results:Statistically significant difference was found in renal insufficiency between the HCM group and the AFD group; No other significant difference was found in other clinical factors and ECG results (all P>0.05). CMR results showed that in the AFD group, there were 5 cases with symmetric or roughly symmetric hypertrophy, and 3 with asymmetric hypertrophy. The late gadolinium enhancement (LGE) showed myocardial enhancement in 5 patients, mainly presenting as multiple intermural enhancement, and partially as local subendocardial enhancement. In the HCM group, fourteen cases suffered mainly asymmetric ventricular septal thickening, with or without thickening of other parts of left ventricular wall; and 2 cases had thickening of middle and distal part of the left ventricle. The LGE showed myocardial enhancement in 14 patients, which manifested as focal or patchy enhancement in hypertrophic myocardium, including focal enhancement in the right ventricular insertion of ventricular septum (more common) and subendocardial enhancement in the middle and far segments of left ventricle. Statistically significant difference was found in the differences between the left atrial anterior posterior diameter, the maximum wall thickness of left ventricular, the left ventricular myocardial mass index (LVMI) and the native T 1 value among the three groups (all P<0.001). However, there was no statistically significant difference in the left atrial anterior posterior diameter and the maximum wall thickness of left ventricular between AFD group and HCM group ( P>0.05). The LVMI in AFD group was higher than that in healthy group and HCM group (all P<0.05). Significant difference was found in the native T 1 value among the three groups, with the native T 1 value of the AFD group [(1 177.4±46.0) ms] was significantly lower than that of the healthy group [(1 244.5±34.3) ms] and the HCM group [(1 278.8±41.6) ms], with ( F=13.10, P<0.001). Conclusions:The clinical characteristics of AFD and HCM are quite similar. When AFD is suspected, CMR imaging should be the first choice for imaging examination. Especially, T 1 mapping imaging can provide important information for the diagnosis of AFD.

Objective:To explore the clinical value of T 1 mapping/indexed extracellular volume fraction (iECV) quantified with cardiac MR (CMR) parameters, and its correlation with traditional indicators of myocardial dysfunction in aortic insufficiency (AI) patients. Methods:A total of 36 patients clinically and radiologically diagnosed with chronic AI in our hospital between May 2012 and February 2016 were retrospectively selected. All AI patients underwent conventional CMR protocol, native and post T 1 mapping. CMR parameters, such as aortic regurgitant fraction (RF), late gadolinium enhancement (LGE) mass fraction, myocardial extracellular volume fraction (ECV) and iECV. Based on the values of aortic RF, AI patients were divided into mild AI group (9 cases), moderate AI group (14 cases) and severe AI group (13 cases). The clinical characteristics were teased from the patients′ electronic medical records. Univariate analysis of variance was used to compare the measurement data of native T 1 mapping, post-contrast T 1 mapping, ECV, and iECV. LSD test was used for pair wise comparison between the mild AI, moderate AI and severe AI groups. Data about cardiovascular history, New York Heart Association (NYHA) heart function classification, and LGE were compared by chi-square test or Fisher exact test. The correlation between left ventricle ejection fraction (LVEF) and iECV was evaluated by Spearman correlation analysis. Results:There was no difference in age, sex, cardiovascular history among the three groups. Comparison of patients with different severity of AI in the three groups: (1) There was statistically significant difference in the LGE positive rate among the three groups ( P=0.023), while the myocardial replacement of fibrosis increased with the grade of aortic regurgitation. (2) There was no statistically significant difference in the measurement data of native T 1 mapping, post-contrast T 1 mapping, ECV among the three groups ( H=1.815, 0.929, 2.496, all P values>0.05), while the diffuse myocardial fibrosis tended to increase with the degree of aortic regurgitation. There was statistically significant difference in iECV among the three groups ( H=16.725, P<0.001). The measurement data of iECV in the severe AI group was significantly higher than those in the other two groups ( P<0.05). LVEF value was inversely correlated with iECV ( r=-0.649, P<0.001). Conclusions:Quantitative T 1 mapping/iECV can serve as a parameter to noninvasively identify diffuse myocardial fibrosis in AI patients of different severities. It changes with LVEF and can manifest the reversible stage of left ventricular decompensation.

Endogenously eliminating the hematoma is a favorable strategy in addressing intracerebral hemorrhage (ICH). This study sought to determine the role of retinoid X receptor-α (RXR-α) in the context of hematoma absorption after ICH. Our results showed that pharmacologically activating RXR-α with bexarotene significantly accelerated hematoma clearance and alleviated neurological dysfunction after ICH. RXR-α was expressed in microglia/macrophages, neurons, and astrocytes. Mechanistically, bexarotene promoted the nuclear translocation of RXR-α and PPAR-γ, as well as reducing neuroinflammation by modulating microglia/macrophage reprograming from the M1 into the M2 phenotype. Furthermore, all the beneficial effects of RXR-α in ICH were reversed by the PPAR-γ inhibitor GW9662. In conclusion, the pharmacological activation of RXR-α confers robust neuroprotection against ICH by accelerating hematoma clearance and repolarizing microglia/macrophages towards the M2 phenotype through PPAR-γ-related mechanisms. Our data support the notion that RXR-α might be a promising therapeutic target for ICH.
Anilides/pharmacology* ; Cerebral Hemorrhage/drug therapy* ; Hematoma/drug therapy* ; Humans ; Macrophages ; Microglia ; Neuroprotection ; PPAR gamma ; Retinoid X Receptor alpha

Endogenously eliminating the hematoma is a favorable strategy in addressing intracerebral hemorrhage (ICH). This study sought to determine the role of retinoid X receptor-α (RXR-α) in the context of hematoma absorption after ICH. Our results showed that pharmacologically activating RXR-α with bexarotene significantly accelerated hematoma clearance and alleviated neurological dysfunction after ICH. RXR-α was expressed in microglia/macrophages, neurons, and astrocytes. Mechanistically, bexarotene promoted the nuclear translocation of RXR-α and PPAR-γ, as well as reducing neuroinflammation by modulating microglia/macrophage reprograming from the M1 into the M2 phenotype. Furthermore, all the beneficial effects of RXR-α in ICH were reversed by the PPAR-γ inhibitor GW9662. In conclusion, the pharmacological activation of RXR-α confers robust neuroprotection against ICH by accelerating hematoma clearance and repolarizing microglia/macrophages towards the M2 phenotype through PPAR-γ-related mechanisms. Our data support the notion that RXR-α might be a promising therapeutic target for ICH.