BACKGROUND: Generalized pustular psoriasis (GPP), a rare and recurrent autoinflammatory disease, imposes a substantial burden on patients and society. Awareness of GPP in China remains limited. METHODS: This cross-sectional survey, conducted between September 2021 and May 2023 across 14 hospitals in China, included GPP patients of all ages and disease phases. Data collected encompassed demographics, clinical characteristics, economic impact, disease severity, quality of life, and treatment-related complications. Risk factors for GPP recurrence were analyzed. RESULTS: Among 127 patients (female/male ratio = 1.35:1), the mean age of disease onset was 25 years (1st quartile [Q1]-3rd quartile [Q3]: 11-44 years); 29.2% had experienced GPP for more than 10 years. Recurrence occurred in 75.6% of patients, and nearly half reported no identifiable triggers. Younger age at disease onset ( P  = 0.021) and transitioning to plaque psoriasis ( P  = 0.022) were associated with higher recurrence rates. The median diagnostic delay was 8 months (Q1-Q3: 2-41 months), and 32.3% of patients reported misdiagnoses. Comorbidities were present in 53.5% of patients, whereas 51.1% experienced systemic complications during treatment. Depression and anxiety affected 84.5% and 95.6% of patients, respectively. During GPP flares, the median Dermatology Life Quality Index score was 19.0 (Q1-Q3: 13.0-23.5). This score showed significant differences between patients with and without systemic symptoms; it demonstrated correlations with both depression and anxiety scores. Treatment costs caused financial hardship in 55.9% of patients, underscoring the burden associated with GPP. CONCLUSIONS The substantial disease and economic burdens among Chinese GPP patients warrant increased attention. Patients with early onset disease and those transitioning to plaque psoriasis require targeted interventions to mitigate the high recurrence risk.
Humans ; Male ; Female ; Psoriasis/pathology* ; Adult ; Cross-Sectional Studies ; Adolescent ; Child ; Young Adult ; Quality of Life ; Middle Aged ; China/epidemiology* ; Recurrence ; Risk Factors ; Surveys and Questionnaires ; East Asian People

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 minimize variations in treatment outcomes of L5/S1 percutaneous intervertebral radiofrequency thermocoagulation(PIRFT)arising from physician proficiency and achieve precise quantitative risk assessment of the puncture paths.Methods We used a self-developed deep neural network DWT-UNet for automatic segmentation of the magnetic resonance(MR)images of the L5/S1 segments into 7 key structures:L5,S1,Ilium,Disc,N5,Dura mater,and Skin,based on which a needle insertion path planning environment was modeled.Six hard constraints and 6 soft constraints were proposed based on clinical criteria for needle insertion,and the physician's experience was quantified into weights using the analytic hierarchy process and incorporated into the risk function for needle insertion paths to enhance individual case adaptability.By leveraging the proposed skin entry point sampling sub-algorithm and Kambin's triangle projection area sub-algorithm in conjunction with the analytic hierarchy process,and employing various technologies such as ray tracing,CPU multi-threading,and GPU parallel computing,a puncture path was calculated that not only met clinical hard constraints but also optimized the overall soft constraints.Results A surgical team conducted a subjective evaluation of the 21 needle puncture paths planned by the algorithm,and all the paths met the clinical requirements,with 95.24%of them rated excellent or good.Compared with the physician's planning results,the plans generated by the algorithm showed inferior DIlium,DS1,and Depth(P<0.05)but much better DDura,DL5,DN5,and AKambin(P<0.05).In the 21 cases,the planning time of the algorithm averaged 7.97±3.73 s,much shorter than that by the physicians(typically beyond 10 min).Conclusion The multi-constraint optimal puncture path planning algorithm offers an efficient automated solution for PIRFT of the L5/S1 segments with great potentials for clinical application.

Objective:To review and analyze the clinical diagnosis and treatment of renal Ewing's sar-coma with venous tumor embolus,to follow up the survival and prognosis of the patients,and to provide help for the diagnosis and treatment of the disease.Methods:Clinical data(including general data,sur-gical data and postoperative pathological data)of patients diagnosed with renal Ewing's sarcoma with ve-nous tumor embolus in Peking University Third Hospital from June 2016 to June 2022 were collected,and the prognosis of the patients was followed up to analyze the influence of diagnosis and treatment process on the prognosis of the disease.Results:There were 6 patients,including 1 male and 5 females.There were 4 cases of left renal tumor and 2 cases of right renal tumor.The median age at diagnosis was 28 years(16-52 years).The imaging findings were all exogenous tumors with internal necrotic tissue and hemorrhage.The mean maximum tumor diameter was 12.6 cm,and the mean tumor thrombus length was 7.8 cm.Four patients underwent open surgery and 2 patients underwent laparoscopic surgery.The post-operative pathological results were renal Ewing sarcoma.Immunohistochemical results showed 3 cases of CD99(+),2 cases of FLI-1(+),and 1 case of CD99,FLI-1(-).3 patients received chemothera-py(cyclophosphamide,doxorubicin,vincristine/ifosfamide,etoposide),1 case received chemotherapy combined with radiotherapy,and 2 cases received no adjuvant therapy.The mean overall survival(OS)of the 6 patients was 37 months,and the mean OS of the 4 patients(47 months)who received chemo-therapy was significantly higher than that of the 2 patients(16 months)who did not receive chemotherapy(P=0.031).Conclusion:Renal Ewing's sarcoma with venous tumor embolus is rare in clinic,and it is common in young female patients.The operation is difficult and the prognosis is poor.Surgical resection,adjuvant radiotherapy and chemotherapy can improve the overall survival rate of the patients.

Objective To minimize variations in treatment outcomes of L5/S1 percutaneous intervertebral radiofrequency thermocoagulation(PIRFT)arising from physician proficiency and achieve precise quantitative risk assessment of the puncture paths.Methods We used a self-developed deep neural network DWT-UNet for automatic segmentation of the magnetic resonance(MR)images of the L5/S1 segments into 7 key structures:L5,S1,Ilium,Disc,N5,Dura mater,and Skin,based on which a needle insertion path planning environment was modeled.Six hard constraints and 6 soft constraints were proposed based on clinical criteria for needle insertion,and the physician's experience was quantified into weights using the analytic hierarchy process and incorporated into the risk function for needle insertion paths to enhance individual case adaptability.By leveraging the proposed skin entry point sampling sub-algorithm and Kambin's triangle projection area sub-algorithm in conjunction with the analytic hierarchy process,and employing various technologies such as ray tracing,CPU multi-threading,and GPU parallel computing,a puncture path was calculated that not only met clinical hard constraints but also optimized the overall soft constraints.Results A surgical team conducted a subjective evaluation of the 21 needle puncture paths planned by the algorithm,and all the paths met the clinical requirements,with 95.24%of them rated excellent or good.Compared with the physician's planning results,the plans generated by the algorithm showed inferior DIlium,DS1,and Depth(P<0.05)but much better DDura,DL5,DN5,and AKambin(P<0.05).In the 21 cases,the planning time of the algorithm averaged 7.97±3.73 s,much shorter than that by the physicians(typically beyond 10 min).Conclusion The multi-constraint optimal puncture path planning algorithm offers an efficient automated solution for PIRFT of the L5/S1 segments with great potentials for clinical application.

Objective To studyexplore the reversal effect of S-adenosylmethionine(SAM)on chemotherapy resistancechemoresis-tance of pancreatic cancer and explore its related mechanisms.Methods After treatment of human pancreatic cancer resistant cell lines PANC-1/GEM with SAM,the cell proliferation activity of PANC-1/GEM cells and their resistance to gemcitabine(GEM)were ana-lyzed by MTT assay;The the effect of SAM on apoptosis rate of PANC-1/GEM cells was detected by flow cytometry;the change of SAM on the migration activity of drug-resistant cell lines was detected by cell scratch assay;the expression of NEDD4-1 protein in drug-re-sistant cell lines and the changes of NEDD4-1,p-JAK2,p-STAT3 and P-gp protein levels after SAM treatment were detected by Western blot.Results SAM could inhibit the activity of pancreatic cancer PANC-1/GEM resistant cell lines and significantly decreased its resistance to GEM chemotherapy.The IC50 value decreased from 1557.50±201.10nmol/L to 218.39±20.61 nmol/L(P＜0.01);SAM can obviously induced the apoptosis of drug-resistant cell lines and inhibited their migration activity;the expression of NEDD4-1 protein was up-regulated in drug-resistant cell lines,and SAM could inhibit the activation levels of NEDD4-1,p-JAK2,p-STAT3 and P-gp proteins.Conclusion SAM can reduce the chemotherapy resistance of PANC-1/GEM cells to GEM by regulating NEDD4-1 to inhibit the activity of JAK2/STAT3 pathway and regulate the activity of P-gp protein,which provides some experimental evidence for the clinical application of SAM in the treatment of chemotherapy resistance in tumor patients.

METHODS: We retrospectively collected CT scan data from 276 patients with pathologically confirmed primary bone tumors from 4 medical centers in Guangdong Province between January, 2010 and August, 2021. A convolutional neural network (CNN) was employed as the deep learning architecture. The optimal baseline deep learning model (R-Net) was determined through transfer learning, and an optimized model (S-Net) was obtained through algorithmic improvements. Multivariate logistic regression analysis was used to screen the clinical features such as sex, age, mineralization location, and pathological fractures, which were then connected with the imaging features to construct the deep learning fusion model (SC-Net). The diagnostic performance of the SC-Net model and machine learning models were compared with radiologists' diagnoses, and their classification performance was evaluated using the area under the receiver operating characteristic curve (AUC) and F1 score. RESULTS: In the external test set, the fusion model (SC-Net) achieved the best performance with an AUC of 0.901 (95% CI: 0.803-1.00), an accuracy of 83.7% (95% CI: 69.3%-93.2%) and an F1 score of 0.857, and outperformed the S-Net model with an AUC of 0.818 (95% CI: 0.694-0.942), an accuracy of 76.7% (95% CI: 61.4%-88.2%), and an F1 score of 0.828. The overall classification performance of the fusion model (SC-Net) exceeded that of radiologists' diagnoses. CONCLUSIONS The deep learning fusion model based on multi-center CT images and clinical features is capable of accurate classification of osseous and chondroid matrix mineralization and may potentially improve the accuracy of clinical diagnoses of osteogenic versus chondrogenic primary bone tumors.
Humans ; Deep Learning ; Bone Neoplasms/diagnostic imaging* ; Retrospective Studies ; Tomography, X-Ray Computed/methods* ; Neural Networks, Computer ; Male ; Female ; ROC Curve ; Algorithms

Rosae Radix et Rhizoma is a herbal medicine in a variety of famous Chinese patent medicines, while the quality standard for this medicine remains to be developed due to the insufficient research on the quality of Rosae Radix et Rhizoma from different sources. Therefore, this study comprehensively analyzed the components in Rosae Radix et Rhizoma of different sources from the aspects of extract, component category content, identification based on thin-lay chromatography, active component content determination, and fingerprint, so as to improve the quality control. The results showed that the content of chemical components varied in the samples of different sources, while there was little difference in the chemical composition among the samples. The content of components in the roots of Rosa laevigata was higher than that in the other two species, and the content of components in the roots was higher than that in the stems. The fingerprints of triterpenoids and non-triterpenoids were established, and the content of five main triterpenoids including multiflorin, rosamultin, myrianthic acid, rosolic acid, and tormentic acid in Rosae Radix et Rhizoma was determined. The results were consistent with those of major component categories. In conclusion, the quality of Rosae Radix et Rhizoma is associated with the plant species, producing area, and medicinal parts. The method established in this study lays a foundation for improving the quality standard of Rosae Radix et Rhizoma and provides data support for the rational use of the stem.
Drugs, Chinese Herbal/chemistry* ; Rhizome/chemistry* ; Plant Roots/chemistry* ; Plants, Medicinal ; Quality Control

Pulmonary blast injury has become the main type of trauma in modern warfare, characterized by externally mild injuries but internally severe injuries, rapid disease progression, and a high rate of early death. The injury is complicated in clinical practice, often with multiple and compound injuries. Currently, there is a lack of effective protective materials, accurate injury detection instrument and portable monitoring and transportation equipment, standardized clinical treatment guidelines in various medical centers, and evidence-based guidelines at home and abroad, resulting in a high mortality in clinlcal practice. Therefore, the Trauma Branch of Chinese Medical Association and the Editorial Committee of Chinese Journal of Trauma organized military and civilian experts in related fields such as thoracic surgery and traumatic surgery to jointly develop the Clinical treatment guideline for pulmonary blast injury ( version 2023) by combining evidence for effectiveness and clinical first-line treatment experience. This guideline provided 16 recommended opinions surrounding definition, characteristics, pre-hospital diagnosis and treatment, and in-hospital treatment of pulmonary blast injury, hoping to provide a basis for the clinical treatment in hospitals at different levels.

In this study, a new ileal orthotopic bladder (Urumqi Bladder) modified by our center based on the ileal "W" type orthotopic bladder and Studer bladder was used on 8 patients with invasive bladder cancer. All of patients were male and aged between 54 and 66 years. The history of disease ranged from 1 month to 3 years, including 5 patients with initial onset, 3 patients with ≥2 TURBT history. 6 patients had multiple tumors, tumor size from 0.5 cm to 2.5cm. There were 2 patients with single tumor. Preoperative PET-CT examination showed no distant metastasis and pelvic lymph node enlargement, no urinary tract hydronephrosis, and cystoscopy showed no suspected tumor in the urethra. Preoperative pathological results: high-grade invasive urothelial carcinoma was found in 6 cases and muscular invasive urothelial carcinoma in 2 cases. In 8 patients, 50cm ileum was taken from 15cm away from ileocecum after radical cystectomy, which was crimped clockwise inward from the right end into a nearly circular shape, with 10cm left at the left end. The remaining 40cm ileum was formed into 3 sections of about 13cm each, which were decanted to form a storage capsule. The last 10cm intestinal tube was crossed from the front of sigmoid colon. The end of intestine was anastomosed with the left ureter. The right ureter was anastomosed with the top of the right intestine pouch, and the urethra was anastomosed with the pouch to complete the diversion of urine flow. During 3-12 months of postoperative follow-up, 4 patients had short-term mild urinary incontinence. All had complete urinary control at 12 months. 1 patient still had mild left ureter reflux 12 months after surgery, and the other 7 patients had no ureter reflux. In this group of 8 patients, postoperative excretory cystography showed satisfactory effect of bladder voiding, residual, and bladder capacity. Follow-up review of chest CT, urinary CT and abdominal ultrasound showed no hydronephrosis, and no tumor recurrence or distant metastasis.