Proteomic Biomarkers of Intrahepatic Cholestasis of Pregnancy.

Intrahepatic cholestasis of pregnancy (ICP) is a pregnancy-specific liver disease, which can lead to adverse fetal outcomes, including preterm labor and intrauterine death. The pathogenesis of ICP is still unclear. We hypothesized that pathological index leads to abnormal placenta changes in ICP. Investigation of these differences in protein expression in parallel profiling is essential to understand the comprehensive pathophysiological mechanism underlying ICP. The present study screened differentially expressed proteins (DEPs) as novel diagnostic markers for ICP. Proteomic profiles of placental tissues from 32 ICP patients and 24 healthy volunteers (controls) were analyzed. Our founding was valid by following western blotting and immunohistochemistry staining, respectively. The association of the key protein expression with clinicopathological features of ICP was further analyzed. A total of 178 DEPs were identified between the ICP and control groups. Functional enrichment analysis showed these proteins were significantly enriched in the PPAR singling pathway by KEGG and PPARα/RXRα activation by IPA. Apolipoprotein A2 (APOA2) was the only upregulated protein, which uniquely identified in ICP groups and related to both pathways. Validation of western blotting and immunohistochemical staining analysis showed significantly higher APOA2 expression in the ICP group than in the control group. Furthermore, the expression of APOA2 is associated with clinicopathological features in ICP groups. Receiver operating characteristic (ROC) curve analyses showed that the AUC of APOA2 was 0.8984 (95% confidence interval (CI): 0.772-1.000). This study has identified up-regulated APOA2 associated with PPAR singling pathway and PPARα/RXRα activation in ICP. Thus, APOA2 may be involved in ICP pathogenesis, serving as a novel biomarker for its diagnosis.

A hybrid quantum-classical classification model based on branching multi-scale entanglement renormalization ansatz.

Tensor networks are emerging architectures for implementing quantum classification models. The branching multi-scale entanglement renormalization ansatz (BMERA) is a tensor network known for its enhanced entanglement properties. This paper introduces a hybrid quantum-classical classification model based on BMERA and explores the correlation between circuit layout, expressiveness, and classification accuracy. Additionally, we present an autodifferentiation method for computing the cost function gradient, which serves as a viable option for other hybrid quantum-classical models. Through numerical experiments, we demonstrate the accuracy and robustness of our classification model in tasks such as image recognition and cluster excitation discrimination, offering a novel approach for designing quantum classification models.

A hybrid effectiveness-implementation trial of application-based tiered care (Mom's Good Mood) in treating perinatal anxiety within a primary health care system in China.

INTRODUCTION: Perinatal anxiety (PNA) is a major public health concern. METHODS: A hybrid effectiveness-implementation trial was conducted in two antenatal clinics in Hefei, China, to assess the effectiveness and cost-effectiveness of application-based tiered care (Mom's Good Mood, MGM) in treating PNA and to understand how well it fits into routine practices. Pregnant women who scored at least 5 points on the 7-Item Generalised Anxiety Disorder Scale (GAD-7) scale were successively assigned to the control group or the intervention group, which were given the usual care and MGM on usual care, respectively. At 6 months post partum, anxiety, depression and life satisfaction were assessed. Intention-to-treat analysis and the Reach, Effectiveness, Adoption, Implementation and Maintenance framework were adopted. RESULTS: A total of 214 women were assigned to the control group and 341 to the intervention group. The mean changes in GAD-7 scores (Least-squares means, LSM, -1.42, 95% CI -2.18 to -0.66) and the risk of anxiety (adjusted odds ratio, aOR 0.30, 95% CI 0.18 to 0.51) were decreased, and the anxiety remission rate (aOR 2.72, 95% CI 1.69 to 4.40) were improved in the intervention group. Similar findings were observed regarding the change in Edinburgh Postnatal Depression Scale scores (LS -1.92, 95% CI -2.85 to -0.99), depression remission rate (aOR 2.24, 95% CI 1.39 to 3.63) and the risk of depression (aOR 0.57, 95% CI 0.33 to 0.98). MGM only costs ¥1.88 (US$0.27) per pregnant woman to boost the postpartum anxiety remission rate by 1% and was revealed to have a high reach rate of 78.3%, an adoption rate of 51.3%-80.8%. CONCLUSION: MGM is a cost-effective and accessible tool in coping with PNA. TRIAL REGISTRATION NUMBER: ChiCTR2100053419.

Epidemiological Characteristics and Spatiotemporal Patterns of Visceral Leishmaniasis in Xinjiang, China, during 2004-2021.

The spread of visceral leishmaniasis (VL), a serious global zoonotic parasitic disease, is mostly under control; however, several cases have been reported in recent decades in Xinjiang, China. This study aimed to analyze the epidemiological status and spatiotemporal clustering characteristics of VL in Xinjiang, China, between 2004 and 2021 to provide a basis for the development and implementation of surveillance and response measures. Data on VL incidence during 2004-2021 were collected from the National Diseases Reporting Information System of China. Global spatial autocorrelation analysis, identification of local indicators of spatial association, and spatial-temporal clustering analysis were conducted to identify the distribution and high-risk areas. A total of 2034 VL cases were reported, with a mean annual incidence of 0.50 per 100,000. There was a general decreasing trend in the incidence of VL during our study period. The majority of the cases were reported from October to February of the following year, and fewer cases were reported from April to July. Spatial autocorrelation analysis revealed that the incidence of VL was spatially clustered within a few counties. Significant differences were observed during the study period (Moran's I = 0.74, Z = 4.900, p < 0.05). The male-to-female ratio was 1.37:1, and most patients were in the age group 0-3 years. Cases were primarily distributed in seven regions and two autonomous prefectures, and Kashgar reported the highest number of cases (1688, 82.98%). Spatial analysis revealed that the aggregation of VL was predominantly observed in southwest Xinjiang. This was in alignment with the high-risk areas identified by spatiotemporal clustering analysis. The H-H clustering region was primarily observed in Gashi, Atushi, Shufu, Injisha, Kashgar, Yepuhu, and Bachu. These findings indicate that integrated control measures must be taken in different endemic areas to strengthen the VL control program in Xinjiang, China.