Psoriasis is a chronic, recurrent, inflammatory systemic disease that is not only characterized by skin manifestations but may also be accompanied by various comorbidities, imposing a heavy burden on patients’ physical and mental health and affecting their quality of life. Although the continuous approval of various biological agents for clinical use has provided more effective treatment options to patients with psoriasis, no consensus on the evaluation of comprehensive treatment goals has yet been established. The treat-to-target (T2T) strategy requires consideration of multiple dimensions of treatment outcomes, the development of long-term management goals, and regular assessments of treatment conditions, which are often used in the management of chronic diseases. Therefore, based on the latest consensuses and guidelines, research data, and clinical experience as well as the combination of survey results and expert group discussions, the present consensus focuses on 4 dimensions of short- and long-term integrated management goals for biological agents: alleviating skin lesions, improving quality of life, screening and managing psoriasis comorbidities, and ensuring drug safety. The implementation methods, evaluation time, treatment monitoring, and program adjustments are also herein described to achieve comprehensive management of psoriasis to the maximum extent. This consensus provides a reference for clinical practice.

Lupus erythematosus (LE) is a heterogeneous, antibody-mediated autoimmune disease. Isolate discoid LE (IDLE) and systematic LE (SLE) are traditionally regarded as the two ends of the spectrum, ranging from skin-limited damage to life-threatening multi-organ involvement. Both belong to LE, but IDLE and SLE differ in appearance of skin lesions, autoantibody panels, pathological changes, treatments, and immunopathogenesis. Is discoid lupus truly a form of LE or is it a completely separate entity? This question has not been fully elucidated. We compared the clinical data of IDLE and SLE from our center, applied multi-omics technology, such as immune repertoire sequencing, high-resolution HLA alleles sequencing and multi-spectrum pathological system to explore cellular and molecular phenotypes in skin and peripheral blood from LE patients. Based on the data from 136 LE patients from 8 hospitals in China, we observed higher damage scores and fewer LE specific autoantibodies in IDLE than SLE patients, more uCDR3 sharing between PBMCs and skin lesion from SLE than IDLE patients, elevated diversity of V-J recombination in IDLE skin lesion and SLE PBMCs, increased SHM frequency and class switch ratio in IDLE skin lesion, decreased SHM frequency but increased class switch ratio in SLE PBMCs, HLA-DRB1*03:01:01:01, HLA-B*58:01:01:01, HLA-C*03:02:02:01, and HLA-DQB1*02:01:01:01 positively associated with SLE patients, and expanded Tfh-like cells with ectopic germinal center structures in IDLE skin lesions. These findings suggest a significant difference in the immunopathogenesis of skin lesions between SLE and IDLE patients. SLE is a B cell-predominate systemic immune disorder, while IDLE appears limited to the skin. Our findings provide novel insights into the pathogenesis of IDLE and other types of LE, which may direct more accurate diagnosis and novel therapeutic strategies.

IntroductionWith the rapid development of artificial intelligence technology, machine learning algorithms have been widely applied at various stages of stroke diagnosis, treatment, and prognosis, demonstrating significant potential. A correlation between stroke and cytokine levels in the human body has recently been reported. Our study aimed to establish machine-learning models based on cytokine features to enhance the decision-making capabilities of clinical physicians.MethodsThis study recruited 2346 stroke patients and 2128 healthy control subjects from Chongqing University Central Hospital. A predictive model was established through clinical experiments and collection of clinical laboratory tests and demographic variables at admission. Three classification algorithms, namely Random Forest, Gradient Boosting, and Support Vector Machine, were employed. The models were evaluated using methods such as ROC curves, AUC values, and calibration curves.ResultsThrough univariate feature selection, we selected 14 features and constructed three machine-learning models: Support Vector Machine (SVM), Random Forest (RF), and Gradient Boosting Machine (GBM). Our results indicated that in the training set, the RF model outperformed the GBM and SVM models in terms of both the AUC value and sensitivity. We ranked the features using the RF algorithm, and the results showed that IL-6, IL-5, IL-10, and IL-2 had high importance scores and ranked at the top. In the test set, the stroke model demonstrated a good generalization ability, as evidenced by the ROC curve, confusion matrix, and calibration curve, confirming its reliability as a predictive model for stroke.DiscussionWe focused on utilizing cytokines as features to establish stroke prediction models. Analyses of the ROC curve, confusion matrix, and calibration curve of the test set demonstrated that our models exhibited a strong generalization ability, which could be applied in stroke prediction.

Background: Most respiratory viruses can cause serious lower respiratory diseases at any age. Therefore, timely and accurate identification of respiratory viruses has become even more important. This study focused on the development of rapid nucleic acid testing techniques for common respiratory infectious diseases in the Chinese population.Methods: Multiplex fluorescent quantitative polymerase chain reaction (PCR) assays were developed and validated for the detection of respiratory pathogens including the novel coronavirus (SARS-CoV-2), influenza A virus (FluA), parainfluenza virus (PIV), and respiratory syncytial virus (RSV).Results: The assays demonstrated high specificity and sensitivity, allowing for the simultaneous detection of multiple pathogens in a single reaction. These techniques offer a rapid and reliable method for screening, diagnosis, and monitoring of respiratory pathogens.Conclusion: The implementation of these techniques might contribute to effective control and prevention measures, leading to improved patient care and public health outcomes in China. Further research and validation are needed to optimize and expand the application of these techniques to a wider range of respiratory pathogens and to enhance their utility in clinical and public health settings.

Background: Urticaria is a common skin disease characterized by episodes of wheals, and it has a negative effect on patients' quality of life. Large-scale population-based epidemiological studies of urticaria are scarce in China. The aim of this survey was to determine the prevalence, clinical forms, and risk factors of urticaria in the Chinese population. Methods: This survey was conducted in 35 cities from 31 provinces, autonomous regions, and municipalities of China. Two to three communities in each city were selected in this investigation. Participants completed questionnaires and received dermatological examinations. We analyzed the prevalence, clinical forms, and risk factors of urticaria. Results: In total, 44,875 questionnaires were distributed and 41,041 valid questionnaires were collected (17,563 male and 23,478 female participants). The lifetime prevalence of urticaria was 7.30%, with 8.26% in female and 6.34% in male individuals (P < 0.05). The point prevalence of urticaria was 0.75%, with 0.79% in female and 0.71% in male individuals (P < 0.05). Concomitant angioedema was found in 6.16% of patients. Adults had a higher prevalence of urticaria than adolescents and children. Living in urban areas, exposure to pollutants, an anxious or depressed psychological status, a personal and family history of allergy, thyroid diseases, and Helicobacter pylori infection were associated with a higher prevalence of urticaria. Smoking was correlated with a reduced risk of urticaria. Conclusion: This study demonstrated that the lifetime prevalence of urticaria was 7.30% and the point prevalence was 0.75% in the Chinese population; women had a higher prevalence of urticaria than men. Various factors were correlated with urticaria.