ObjectiveTo establish the multi-technique characteristic profiles of Alumen by X-ray diffraction（XRD）， Fourier-transform infrared spectroscopy（FTIR） and thermogravimetric-differential thermal analysis（TG-DTA）， and to explore the spectral characteristics for rapid identification of Alumen and its potential adulterant， Ammonium alum. MethodsA total of 27 batches of Alumen samples from 8 production regions were collected for preliminary identification based on visual characteristics. The PDF standard cards of XRD were used to differentiate Alumen from A. alum， and the XRD characteristic profiles of Alumen were established， and then the common peaks were screened. Based on hierarchical clustering analysis（HCA） and orthogonal partial least squares-discriminant analysis（OPLS-DA）， the characteristic information that could be used for identification of Alumen was selected with variable importance in the projection（VIP） value>1. FTIR characteristic profiles of Alumen were established， and key wavenumbers for identification were screened by HCA and OPLS-DA with VIP value>1. Meanwhile， the thermogravimetric differences between Alumen and A. alum were analyzed by TG-DTA， and the thermogravimetric traits that could be used for identification were screened. ResultsAlumen and A. alum could not be effectively distinguished by traits alone. However， by comparing the PDF standard cards of XRD， 15 batches of Alumen and 12 batches of A. alum could be distinguished. In the XRD profiles， 10 characteristic peaks were confirmed， corresponding to diffraction angles of 14.560°， 24.316°， 12.620°， 32.122°， 17.898°， 34.642°， 27.496°， 46.048°， 40.697° and 21.973°. In the FTIR profiles， 4 wavenumber ranges（399.193-403.050， 1 186.010-1 471.420， 1 801.190-2 620.790， 3 612.020-3 997.710 cm^-1） and 12 characteristic wavenumbers（1 428.994， 1 430.922， 1 432.851， 1 434.779， 1 436.708， 1 438.636， 1 440.565， 1 442.493， 1 444.422， 1 446.350， 1 448.279， 1 450.207 cm^-1） were identified. In the TG-DTA profiles， there were characteristic decomposition peaks of ammonium ion and mass reduction features near 555.34 ℃ for A. alum. These characteristics could serve as important criteria for distinguishing the authenticity of Alumen. ConclusionXRD， FTIR and TG-DTA can be used to rapidly detect Alumen and A. alum， and combined with the discriminant features selected through chemometrics， the rapid and accurate identification of Alumen and A. alum can be achieved. The research findings provide new approaches for the rapid identification of Alumen.

ObjectiveTo establish the multi-technique characteristic profiles of Alumen by X-ray diffraction（XRD）， Fourier-transform infrared spectroscopy（FTIR） and thermogravimetric-differential thermal analysis（TG-DTA）， and to explore the spectral characteristics for rapid identification of Alumen and its potential adulterant， Ammonium alum. MethodsA total of 27 batches of Alumen samples from 8 production regions were collected for preliminary identification based on visual characteristics. The PDF standard cards of XRD were used to differentiate Alumen from A. alum， and the XRD characteristic profiles of Alumen were established， and then the common peaks were screened. Based on hierarchical clustering analysis（HCA） and orthogonal partial least squares-discriminant analysis（OPLS-DA）， the characteristic information that could be used for identification of Alumen was selected with variable importance in the projection（VIP） value>1. FTIR characteristic profiles of Alumen were established， and key wavenumbers for identification were screened by HCA and OPLS-DA with VIP value>1. Meanwhile， the thermogravimetric differences between Alumen and A. alum were analyzed by TG-DTA， and the thermogravimetric traits that could be used for identification were screened. ResultsAlumen and A. alum could not be effectively distinguished by traits alone. However， by comparing the PDF standard cards of XRD， 15 batches of Alumen and 12 batches of A. alum could be distinguished. In the XRD profiles， 10 characteristic peaks were confirmed， corresponding to diffraction angles of 14.560°， 24.316°， 12.620°， 32.122°， 17.898°， 34.642°， 27.496°， 46.048°， 40.697° and 21.973°. In the FTIR profiles， 4 wavenumber ranges（399.193-403.050， 1 186.010-1 471.420， 1 801.190-2 620.790， 3 612.020-3 997.710 cm^-1） and 12 characteristic wavenumbers（1 428.994， 1 430.922， 1 432.851， 1 434.779， 1 436.708， 1 438.636， 1 440.565， 1 442.493， 1 444.422， 1 446.350， 1 448.279， 1 450.207 cm^-1） were identified. In the TG-DTA profiles， there were characteristic decomposition peaks of ammonium ion and mass reduction features near 555.34 ℃ for A. alum. These characteristics could serve as important criteria for distinguishing the authenticity of Alumen. ConclusionXRD， FTIR and TG-DTA can be used to rapidly detect Alumen and A. alum， and combined with the discriminant features selected through chemometrics， the rapid and accurate identification of Alumen and A. alum can be achieved. The research findings provide new approaches for the rapid identification of Alumen.

Background::Limited information exists regarding the impact of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) infection on psoriasis patients. The objective of this study was to identify clinical factors associated with the prognosis of psoriasis following SARS-CoV-2 infection.Methods::A retrospective, multicenter study was conducted between March and May 2023. Univariable and multivariable logistic regression analyses were employed to identify factors associated with coronavirus disease 2019 (COVID-19)-related psoriasis outcomes. The study included 2371 psoriasis patients from 12 clinical centers, with 2049 of them having been infected with SARS-CoV-2.Results::Among the infected groups, lower exacerbation rates were observed in individuals treated with biologics compared to those receiving traditional systemic or nonsystemic treatments (22.3% [236/1058] vs. 39.8% [92/231] vs. 37.5% [140/373], P <0.001). Psoriasis progression with lesions (adjusted odds ratio [OR] = 8.197, 95% confidence interval [95% CI] = 5.685–11.820, compared to no lesions), hypertension (adjusted OR = 1.582, 95% CI = 1.068–2.343), traditional systemic (adjusted OR = 1.887, 95% CI= 1.263–2.818), and nonsystemic treatment (adjusted OR= 1.602, 95% CI= 1.117–2.297) were found to be associated with exacerbation of psoriasis after SARS-CoV-2 infection, but not biologics (adjusted OR = 0.931, 95% CI = 0.680–1.274, compared to no treatment), according to multivariable logistic regression analysis. Conclusions::A reduced risk of psoriasis exacerbation after SARS-CoV-2 infection was observed with biologics compared to traditional systemic and nonsystemic treatments. Significant risk factors for exacerbation after infection were identified as existing psoriatic lesions and hypertension.

Objective To propose a random forest(RF)algorithm-based prediction method for diabetic retinopathy(DR)to solve the problems due to multi feature dimension for detecting diabetes follow-up data and outliers and noises in the values of some indicators in the disease samples.Methods Firstly,the feature selection of the follow-up dataset of diabetic patients from the endocrinology and metabolism departments of Shanghai Jiao Tong University Affiliated Sixth People's Hospital and Kobe University Hospital in Japan was carried out using the Weka tool to screen out the features or subsets that were hightly correlated with DR;secondly,a model for assisting clinical diagnosis of DR was constructed based on feature subsets and RF algorithm;finally,model comparison experiments and ablation experiments were performed to validate the model performance and to determine which feature contributed the most to the model.Results The feature subset containing disease duration,glycosylated hemoglobin(HbA1c),thyroid stimulating hormone(TSH),total bilirubin(T-bilirubin),low density lipoprotein(LDL),serum creatinine(sCr)and albumin(ALB)correlated the most with RF.A model was constructed based on the above findings with RF algorithm,which behaved better than other models in terms of precision(0.92),accuracy(0.91),F1 score(0.91)and AUC(0.95).The results of ablation experiments showed that the disease duration contributed the most to the model,followed by albumin and serum creatinine,and then by LDL,total bilirubin,glycosylated hemoglobin and thyroid stimulating hormone.Conclusion The RF algorithm-based prediction method with high accuracy can be used for assisted diagnosis of DR.[Chinese Medical Equipment Journal,2024,45(11):8-14]

Objective To investigate the risk factors for bronchopulmonary dysplasia(BPD)in twin preterm infants with a gestational age of<34 weeks,and to provide a basis for early identification of BPD in twin preterm infants in clinical practice.Methods A retrospective analysis was performed for the twin preterm infants with a gestational age of<34 weeks who were admitted to 22 hospitals nationwide from January 2018 to December 2020.According to their conditions,they were divided into group A(both twins had BPD),group B(only one twin had BPD),and group C(neither twin had BPD).The risk factors for BPD in twin preterm infants were analyzed.Further analysis was conducted on group B to investigate the postnatal risk factors for BPD within twins.Results A total of 904 pairs of twins with a gestational age of<34 weeks were included in this study.The multivariate logistic regression analysis showed that compared with group C,birth weight discordance of>25%between the twins was an independent risk factor for BPD in one of the twins(OR=3.370,95%CI:1.500-7.568,P<0.05),and high gestational age at birth was a protective factor against BPD(P<0.05).The conditional logistic regression analysis of group B showed that small-for-gestational-age(SGA)birth was an independent risk factor for BPD in individual twins(OR=5.017,95%CI:1.040-24.190,P<0.05).Conclusions The development of BPD in twin preterm infants is associated with gestational age,birth weight discordance between the twins,and SGA birth.

Objective To explore the clinical characteristics and treatment strategies of infective endocarditis caused by Bartonella vinsonii subsp.berkhoffii(Bvb).Methods Clinical diagnosis and treatment of a 25-year-old male patient with infective endocarditis caused by Bvb in China was reported,combined with literatures about three similar cases reported abroad were summarized and analyzed.Results All 4 patients were young and middle-aged males with a history of close contact with canines in the past one year.The main symptoms were chest pain,fa-tigue,and dyspnea,accompanied by cerebrovascular accidents and severe anemia,as well as the formation of heart valve vegetations and valve function impairment.Multiple blood cultures were negative,2 and 3 cases were con-firmed to be infected with Bvb through metagenomic next-generation sequencing(mNGS)of pathogenic microorga-nisms and polymerase chain reaction respectively.All patients underwent surgical treatment due to heart failure,and all survived after surgery and targeted anti-infective treatment.Conclusion This case report is the first case of Bvb infective endocarditis in China.Patient's diagnosis is confirmed by serum indirect immunofluorescence assay and mNGS,combination of surgery and anti-infective treatment has achieved ideal effect.

Ankylosing spondylitis (AS) combined with lower cervical fracture is often categorized into unstable fracture, with a high incidence of neurological injury and a high rate of disability and morbidity. As factors such as shoulder occlusion may affect the accuracy of X-ray imaging diagnosis, it is often easily misdiagnosed at the primary diagnosis. Non-operative treatment has complications such as bone nonunion and the possibility of secondary neurological damage, while the timing, access and choice of surgical treatment are still controversial. Currently, there are no clinical practice guidelines for the treatment of AS combined with lower cervical fracture with or without dislocation. To this end, the Spinal Trauma Group of Orthopedics Branch of Chinese Medical Doctor Association organized experts to formulate Clinical guidelines for the treatment of ankylosing spondylitis combined with lower cervical fracture in adults ( version 2024) in accordance with the principles of evidence-based medicine, scientificity and practicality, in which 11 recommendations were put forward in terms of the diagnosis, imaging evaluation, typing and treatment, etc, to provide guidance for the diagnosis and treatment of AS combined with lower cervical fracture.

At present, brain disease has become a "killer" in the field of general health, and the existence of blood-brain barrier has become one of the challenges in drug delivery into the brain. According to studies, cell membrane coating technique can endow nanoparticles with the characteristics of immune escape, long circulation, targeted delivery, and so on. Therefore, membrane biomimetic nanoparticles have been widely used in the field of disease treatment. Among them, the cell membrane derived from immune cells, tumor cells, and stem cells can cross the blood-brain barrier through the transcellular pathway and cell bypass pathway, which is used to prepare biomimetic membrane nanoparticles to break through the blood-brain barrier to achieve the treatment of brain diseases. What's more, the brain targeted ability of biomimetic nanoparticles would be further enhanced by modifying the cell membrane with peptides. This paper introduces the preparation methods of membrane biomimetic nanoparticles, expounds in detail the way that cell membrane coated nanoparticles break through the blood-brain barrier and achieve efficient intracerebral drug delivery. It also summarizes the prospects and challenges of this novel drug delivery system in the treatment of brain diseases, providing a reference for the research of membrane biomimetic nanoparticles in the treatment of brain diseases.

Background: Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease is associated with coronary artery lesion development.Purpose: This study aimed to explore the factors associated with IVIG-resistance and construct and validate an interpretable machine learning (ML) prediction model in clinical practice. Methods: Between December 2014 and November 2022, 602 patients were screened and risk factors for IVIG-resistance investigated. Five ML models are used to establish an optimal prediction model. The SHapley Additive exPlanations (SHAP) method was used to interpret the ML model. Results: Na+, hemoglobin (Hb), C-reactive protein (CRP), and globulin were independent risk factors for IVIG-resistance. A nonlinear relationship was identified between globulin level and IVIG-resistance. The XGBoost model exhibited excellent performance, with an area under the receiver operating characteristic curve of 0.821, accuracy of 0.748, sensitivity of 0.889, and specificity of 0.683 in the testing set. The XGBoost model was interpreted globally and locally using the SHAP method. Conclusion Na+, Hb, CRP, and globulin levels were independently associated with IVIG-resistance. Our findings demonstrate that ML models can reliably predict IVIG-resistance. Moreover, use of the SHAP method to interpret the established XGBoost model's findings would provide evidence of IVIG-resistance and guide the individualized treatment of Kawasaki disease.

Background: Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease is associated with coronary artery lesion development.Purpose: This study aimed to explore the factors associated with IVIG-resistance and construct and validate an interpretable machine learning (ML) prediction model in clinical practice. Methods: Between December 2014 and November 2022, 602 patients were screened and risk factors for IVIG-resistance investigated. Five ML models are used to establish an optimal prediction model. The SHapley Additive exPlanations (SHAP) method was used to interpret the ML model. Results: Na+, hemoglobin (Hb), C-reactive protein (CRP), and globulin were independent risk factors for IVIG-resistance. A nonlinear relationship was identified between globulin level and IVIG-resistance. The XGBoost model exhibited excellent performance, with an area under the receiver operating characteristic curve of 0.821, accuracy of 0.748, sensitivity of 0.889, and specificity of 0.683 in the testing set. The XGBoost model was interpreted globally and locally using the SHAP method. Conclusion Na+, Hb, CRP, and globulin levels were independently associated with IVIG-resistance. Our findings demonstrate that ML models can reliably predict IVIG-resistance. Moreover, use of the SHAP method to interpret the established XGBoost model's findings would provide evidence of IVIG-resistance and guide the individualized treatment of Kawasaki disease.