Objective:To explore the clinical profile and prognostic features of relapsing polychondritis (RP) with nervous system involvement.Methods:The clinical data of 28 RP patients with nervous system involvement admitted to Peking Union Medical College Hospital from December 2005 to November 2019 were collected and analyzed.Results:The median age of the patients was 50 years and 57.1% (16/28) were men. Patients with central nervous system involvement accounted for 92.9% (26/28) of the total. Common manifestations included headache (69.2%, 18/26), cognitive impairment (38.5%, 10/26), and mental disorders (38.5%, 10/26); only two cases had peripheral nervous system damage. Brain magnetic resonance imaging revealed that subcortical (13/18) and cortical (8/18) tissues were most affected. Cerebrospinal fluid tests showed that the median white blood cell count was 55×10 6/L, while the protein level was also slighted elevated ((0.54±0.17) g/L). All patients were treated with glucocorticoids, and 85.7% (24/28) of patients with immunosuppressants; 27 patients showed optimistic responses to the treatment, while 24 had recurrent courses. Cognitive dysfunction was the most common residual symptom. Follow-up data of 16 patients were available with an average follow-up time of 3.3 years. Ten of the patients were in stable condition and three patients died. Conclusions:Nervous system damage, especially limbic encephalitis and meningitis may present in course of RP. However, it is a challenge to diagnose for the non-specific clinical manifestations. Treatment with corticosteroids and immunosuppressants can lead to a favorable response.

Circular RNA (circRNA) is involved in tumor progression. CircPVT1 is an oncogene that is abnormally expressed and correlated with a variety of tumors. It can regulate tumors' malignant behavior and affect the survival and prognosis of patients. This article reviews research on the regulatory roles of circPVT1 in tumors to provide references for accurate treatment.

BackgroundAt least 77.0% of breast cancer patients will experience cancer-related fatigue. Hope level and resilience play as two important factors that have influence on cancer-related fatigue. Currently， most studies involve one single factor， either the level of hope or resilience， and explore its relationship with the cancer-related fatigue. Only limited studies explore the action mechanism behind with all three factors put together. ObjectiveTo investigate the mediating role of resilience between hope and cancer-related fatigue in patients with breast cancer， and to provide references for finding intervention targets for cancer-related fatigue in breast cancer patients. MethodsFrom March to October 2022， this study was conducted on the sample size of 324 hospitalized patients from three Grade-A tertiary hospitals in Shaanxi Province. These patients were over 18 years old and pathologically diagnosed as breast cancer. Hope level， resilience and cancer-related fatigue were assessed， respectively， using Adult Dispositional Hope Scale （ADHS）， Connor-Davidson Resilience Scale （CD-RISC-10） and Cancer Fatigue Scale （CFS）. Pearson Correlation Analysis was used to analyze the relationship between ADHS score， CD-RISC-10 score and CFS score. AMOS 22.0 was used to analyze the mediating effect of resilience between hope level and cancer-related fatigue in breast cancer patients. ResultsThe detection rate of cancer-related fatigue in patients with breast cancer was 88.58%. Scores of ADHS and CD-RISC-10 were negatively correlated with CFS score （r=-0.750， -0.809， P<0.01）. ADHS score was positively correlated with CD-RISC-10 score （r=0.901， P<0.01）. Resilience had a mediating effect between the hope level and cancer-related fatigue. The mediating effect value was -0.676（95% CI： -1.005~-0.347）， accounting for 81.90% of the total effect. ConclusionThe hope level of breast cancer patients can affect cancer-related fatigue directly as well as indirectly through resilience. Resilience plays a partial mediating role between hope level and cancer-related fatigue .

Objective:To investigate the diagnostic accuracy of serological indicators and evaluate the diagnostic value of a new established combined serological model on identifying the minimal hepatic encephalopathy (MHE) in patients with compensated cirrhosis.Methods:This prospective multicenter study enrolled 263 compensated cirrhotic patients from 23 hospitals in 15 provinces, autonomous regions and municipalities of China between October 2021 and August 2022. Clinical data and laboratory test results were collected, and the model for end-stage liver disease (MELD) score was calculated. Ammonia level was corrected to the upper limit of normal (AMM-ULN) by the baseline blood ammonia measurements/upper limit of the normal reference value. MHE was diagnosed by combined abnormal number connection test-A and abnormal digit symbol test as suggested by Guidelines on the management of hepatic encephalopathy in cirrhosis. The patients were randomly divided (7∶3) into training set ( n=185) and validation set ( n=78) based on caret package of R language. Logistic regression was used to establish a combined model of MHE diagnosis. The diagnostic performance was evaluated by the area under the curve (AUC) of receiver operating characteristic curve, Hosmer-Lemeshow test and calibration curve. The internal verification was carried out by the Bootstrap method ( n=200). AUC comparisons were achieved using the Delong test. Results:In the training set, prevalence of MHE was 37.8% (70/185). There were statistically significant differences in AMM-ULN, albumin, platelet, alkaline phosphatase, international normalized ratio, MELD score and education between non-MHE group and MHE group (all P<0.05). Multivariate Logistic regression analysis showed that AMM-ULN [odds ratio ( OR)=1.78, 95% confidence interval ( CI) 1.05-3.14, P=0.038] and MELD score ( OR=1.11, 95% CI 1.04-1.20, P=0.002) were independent risk factors for MHE, and the AUC for predicting MHE were 0.663, 0.625, respectively. Compared with the use of blood AMM-ULN and MELD score alone, the AUC of the combined model of AMM-ULN, MELD score and education exhibited better predictive performance in determining the presence of MHE was 0.755, the specificity and sensitivity was 85.2% and 55.7%, respectively. Hosmer-Lemeshow test and calibration curve showed that the model had good calibration ( P=0.733). The AUC for internal validation of the combined model for diagnosing MHE was 0.752. In the validation set, the AUC of the combined model for diagnosing MHE was 0.794, and Hosmer-Lemeshow test showed good calibration ( P=0.841). Conclusion:Use of the combined model including AMM-ULN, MELD score and education could improve the predictive efficiency of MHE among patients with compensated cirrhosis.