Decoding Fujian’s cervical HPV landscape: unmasking dominance of non-16/18 HR-HPV and tailoring prevention strategies at a large scale

BackgroundPersistent HR-HPV causes cervical cancer, exhibiting geographic variance. Europe/Americas have higher HPV16/18 rates, while Asia/Africa predominantly have non-16/18 HR-HPV. This study in Fujian, Asia, explores non-16/18 HR-HPV infections, assessing their epidemiology and cervical lesion association for targeted prevention.MethodsA total of 101,621 women undergoing HPV screening at a hospital in Fujian Province from 2013 to 2019 were included. HPV genotyping was performed. A subset of 11,666 HPV-positive women with available histopathology results were analyzed to characterize HPV genotype distribution across cervical diagnoses.ResultsIn 101,621 samples, 24.5% tested positive for HPV. Among these samples, 17.3% exhibited single infections, while 7.2% showed evidence of multiple infections. The predominant non-16/18 high-risk HPV types identified were HPV 52, 58, 53, 51, and 81. Single HPV infections accounted for 64.1% of all HPV-positive cases, with 71.4% of these being non-16/18 high-risk HPV infections. Age-related variations were observed in 11,666 HPV-positive patients with pathological results. Cancer patients were older. In the cancer group, HPV52 (21.8%) and HPV58 (18.6%) were the predominant types, followed by HPV33, HPV31, and HPV53. Compared to single HPV16/18 infection, non-16/18 HPV predominated in LSIL. Adjusted odds ratios (OR) for LSIL were elevated: multiple HPV16/18 (OR 2.18), multiple non-16/18 HR-HPV (OR 2.53), and multiple LR-HPV (OR 2.38). Notably, solitary HPV16/18 conferred higher odds for HSIL and cancer.ConclusionOur large-scale analysis in Fujian Province highlights HPV 52, 58, 53, 51, and 81 as predominant non-16/18 HR-HPV types. Multiple HPV poses increased LSIL risks, while solitary HPV16/18 elevates HSIL and cancer odds. These findings stress tailored cervical cancer prevention, highlighting specific HPV impacts on lesion severity and guiding region-specific strategies for optimal screening in Asia, emphasizing ongoing surveillance in the vaccination era

YY1 directly interacts with myocardin to repress the triad myocardin/SRF/CArG box-mediated smooth muscle gene transcription during smooth muscle phenotypic modulation

Yin Yang 1 (YY1) regulates gene transcription in a variety of biological processes. In this study, we aim to determine the role of YY1 in vascular smooth muscle cell (VSMC) phenotypic modulation both in vivo and in vitro. Here we show that vascular injury in rodent carotid arteries induces YY1 expression along with reduced expression of smooth muscle differentiation markers in the carotids. Consistent with this finding, YY1 expression is induced in differentiated VSMCs in response to serum stimulation. To determine the underlying molecular mechanisms, we found that YY1 suppresses the transcription of CArG box-dependent SMC-specific genes including SM22α, SMα-actin and SMMHC. Interestingly, YY1 suppresses the transcriptional activity of the SM22α promoter by hindering the binding of serum response factor (SRF) to the proximal CArG box. YY1 also suppresses the transcription and the transactivation of myocardin (MYOCD), a master regulator for SMC-specific gene transcription by binding to SRF to form the MYOCD/SRF/CArG box triad (known as the ternary complex). Mechanistically, YY1 directly interacts with MYOCD to competitively displace MYOCD from SRF. This is the first evidence showing that YY1 inhibits SMC differentiation by directly targeting MYOCD. These findings provide new mechanistic insights into the regulatory mechanisms that govern SMC phenotypic modulation in the pathogenesis of vascular diseases

Analysis of the risk factors of negative emotions in patients undergoing microwave ablation of thyroid nodules during the perioperative period and its impact on prognosis: a prospective cohort study.

BackgroundThyroid nodule (TN) is one or more abnormal lump structures in the thyroid gland parenchyma caused by genetic, environmental, and other factors. It is the most common thyroid disease in clinics. Microwave ablation (MWA) can significantly reduce the nodule volume and effectively reduce the symptoms caused by nodules. However, the patient's negative emotions during the perioperative period may affect the postoperative recovery. This study explored the risk factors of negative emotions in patients during the perioperative period and its impact on patient prognosis. This data provides a basis for clinical psychological interventions before MWA, so as to improve the quality of life of patients with TN.MethodsA total of 238 patients who were hospitalized for TNs in The First Affiliated Hospital of Soochow University from January 2017 to January 2022, and who received MWA therapy were enrolled in this study. The patients were evaluated with a general situation questionnaire, a Self-rating Anxiety Scale (SAS), and a Self-rating Depression Scale (SDS). The TN volume was followed up to evaluate the prognosis of patients. Binary logistic regression was used to analyze the risk factors of perioperative negative emotions and the impact of negative emotions on the prognosis.ResultsThe results of binary logistic regression analysis showed that education, income, hypertension, hyperglycemia, and solid nodule volume were independent influencing factors of anxiety (P<0.05). Age, income, hypertension, hyperglycemia, and solid nodule volume were independent influencing factors of depression (P<0.05). The prognosis of patients with no negative emotions at the first, third, and sixth months after surgery was significantly better than that of patients with negative emotions (P<0.05).ConclusionsNegative emotions have a significant impact on the prognosis of TNs. According to individual differences, targeted nursing intervention should be supplemented to stabilize a patient's emotions, improve compliance, and enhance quality of life

Physical activity level of urban pregnant women in Tianjin, China: a cross-sectional study.

To determine the physical activity level and factors influencing physical activity among pregnant urban Chinese women.This prospective cross-sectional study enrolled 1056 pregnant women (18-44 years of age) in Tianjin, China. Their socio-demographic characteristics were recorded, and the Pregnancy Physical Activity Questionnaire was used to assess their physical activity during pregnancy. The data were analyzed by multinomial logistic regression with adjustment for potential confounders.Median total energy expenditure of pregnant women in each of the three trimesters ranged from 18.50 to 21.90 metabolic equivalents of task (METs) h/day. They expended 1.76-1.85 MET h/day on moderate and vigorous activities and 0.11 MET h/day on exercise. Only 117 of the women (11.1%) met the international guideline for physical activity in pregnancy (≥150 min moderate intensity exercise per week). The most frequent reason given for not being more physically active was the fear of miscarriage. Higher education level (OR: 4.11, 95% CI: 1.59-10.62), habitual exercise before pregnancy (OR: 2.14, 95% CI: 1.39-3.28), and husbands who exercised regularly (OR: 2.21, 95% CI: 1.33-3.67) significantly increased the odds of meeting the guideline (p<0.001). A low pre gravid body mass index (OR: 0.42, 95% CI: 0.20-0.87) significantly decreased the odds (p<0.001).Few urban Chinese pregnant women met the recommended physical activity guideline. They also expended little energy exercising. Future interventions should be based on the clinic environment and targeting family members as well as the subjects. All pregnant women should be targeted, not just those in high-risk groups

Realized Jump Risk and Equity Return in China

National Science Foundation of China [71071132]We utilize the realized jump components to explore a new jump (including nonsystematic jump and systematic jump) risk factor model. After estimating daily realized jumps from high-frequency transaction data of the Chinese A-share stocks, we calculate monthly jump size, monthly jump standard deviation, and monthly jump arrival rate and then use those monthly jump factors to explain the return of the following month. Our empirical results show that the jump tail risk can explain the equity return. For the large capital-size stocks, large cap stock portfolios, and index, one-month lagged jump risk factor significantly explains the asset return variation. Our results remain the same even when we add the size and value factors in the robustness tests

Assessment of Sentinel-2 MSI Spectral Band Reflectances for Estimating Fractional Vegetation Cover

Fractional vegetation cover (FVC) is an essential parameter for characterizing the land surface vegetation conditions and plays an important role in earth surface process simulations and global change studies. The Sentinel-2 missions carrying multi-spectral instrument (MSI) sensors with 13 multispectral bands are potentially useful for estimating FVC. However, the performance of these bands for FVC estimation is unclear. Therefore, the objective of this study was to assess the performance of Sentinel-2 MSI spectral band reflectances on FVC estimation. The samples, including the Sentinel-2 MSI canopy reflectances and corresponding FVC values, were simulated using the PROSPECT + SAIL radiative transfer model under different conditions, and random forest regression (RFR) method was then used to develop FVC estimation models and assess the performance of various band reflectances for FVC estimation. These models were finally evaluated using field survey data. The results indicate that the three most important bands of Sentinel-2 MSI data for FVC estimation are band 4 (Red), band 12 (SWIR2) and band 8a (NIR2). FVC estimation using these bands has a comparable accuracy (root mean square error (RMSE) = 0.085) with that using all bands (RMSE = 0.090). The results also demonstrate that band 12 had a better performance for FVC estimation than the green band (RMSE = 0.097). However, the newly added red-edge bands, with low scores in the RFR model, have little significance for improving FVC estimation accuracy compared with the Red, NIR2 and SWIR2 bands

Generating High Spatio-Temporal Resolution Fractional Vegetation Cover by Fusing GF-1 WFV and MODIS Data

As an important indicator to characterize the surface vegetation, fractional vegetation cover (FVC) with high spatio-temporal resolution is essential for earth surface process simulation. However, due to technical limitations and the influence of weather, it is difficult to generate temporally continuous FVC with high spatio-temporal resolution based on a single remote-sensing data source. Therefore, the objective of this study is to explore the feasibility of generating high spatio-temporal resolution FVC based on the fusion of GaoFen-1 Wide Field View (GF-1 WFV) data and Moderate-resolution Imaging Spectroradiometer (MODIS) data. Two fusion strategies were employed to identify a suitable fusion method: (i) fusing reflectance data from GF-1 WFV and MODIS firstly and then estimating FVC from the reflectance fusion result (strategy FC, Fusion_then_FVC). (ii) fusing the FVC estimated from GF-1 WFV and MODIS reflectance data directly (strategy CF, FVC_then_Fusion). The FVC generated using strategies FC and CF were evaluated based on FVC estimated from the real GF-1 WFV data and the field survey FVC, respectively. The results indicated that strategy CF achieved higher accuracies with less computational cost than those of strategy FC both in the comparisons with FVC estimated from the real GF-1 WFV (CF:R2 = 0.9580, RMSE = 0.0576; FC: R2 = 0.9345, RMSE = 0.0719) and the field survey FVC data (CF: R2 = 0.8138, RMSE = 0.0985; FC: R2 = 0.7173, RMSE = 0.1214). Strategy CF preserved spatial details more accurately than strategy FC and had a lower probability of generating abnormal values. It could be concluded that fusing GF-1 WFV and MODIS data for generating high spatio-temporal resolution FVC with good quality was feasible, and strategy CF was more suitable for generating FVC given its advantages in estimation accuracy and computational efficiency

Association between participants' characteristics and the odds of meeting the guideline.

<p>Association between participants' characteristics and the odds of meeting the guideline.</p

Physical activities during pregnancy.

a<p> MET-hours/day.</p>b<p> Kruskal–Wallis test of differences in ranks.</p><p>Physical activities during pregnancy.</p