With the rapid development of sequencing technologies, the detection of alternative polyadenylation (APA) in mammals has become more precise. APA precisely regulates gene expression by altering the length and position of the poly(A) tail, and is involved in various biological processes such as disease occurrence and embryonic development. The research on APA in mammals mainly focuses on the following aspects:(1) identifying APA based on transcriptome data and elucidating their characteristics; (2) investigating the relationship between APA and gene expression regulation to reveal its important role in life regulation;(3) exploring the intrinsic connections between APA and disease occurrence, embryonic development, differentiation, and other life processes to provide new perspectives and methods for disease diagnosis and treatment, as well as uncovering embryonic development regulatory mechanisms. In this review, the classification, mechanisms and functions of APA were elaborated in detail and the methods for APA identifying and APA data resources based on various transcriptome data were systematically summarized. Moreover, we epitomized and provided an outlook on research on APA, emphasizing the role of sequencing technologies in driving studies on APA in mammals. In the future, with the further development of sequencing technology, the regulatory mechanisms of APA in mammals will become clearer.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

The concept of'harmony'is the soul of traditional Chinese culture,which has a profound impact on the formation and development of traditional Chinese medicine(TCM).TCM is rooted in traditional Chinese culture,and the mode of thinking in TCM is in line with traditional Chinese culture.Based on the harmony culture,TCM has developed a unique view of health,disease and therapeutics.From the view of the harmony culture and by combining with years of clinical experience in treating dermatosis,Chinese medical master XUAN Guo-Wei has applied the concept of'harmony'in the TCM syndrome differentiation and treatment system in clinic,and has developed the academic thoughts of harmonizing therapy for removing toxins for the diagnosis and treatment of dermatosis.The thoughts of harmonizing therapy for removing toxins includes four aspects,namely harmonizing yin and yang,harmonizing healthy qi and pathogenic qi,harmonizing water and fire(i.e.,clod and hot),and harmonizing the administration of formula and drugs,aiming to remove toxins and expel pathogens and value the harmony.The thoughts of harmonizing therapy for removing toxins will beneficial to the comprehensive understanding of the unique health-disease-therapeutics concept in TCM,and will be helpful for managing the doctor-patient relationship,which is of enlightening significance to the modern clinical practice with TCM.

Objective: We aimed to investigate whether 2-[ 18F]fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (2-[ 18F]FDG PET/CT) can aid in evaluating the risk of malignancy in ampullary tumors detected by endoscopy. Materials and Methods: This single-center retrospective cohort study analyzed 155 patients (79 male, 76 female; mean age, 65.7 ± 12.7 years) receiving 2-[ 18F]FDG PET/CT for endoscopy-detected ampullary tumors 5–87 days (median, 7 days) after the diagnostic endoscopy between June 2007 and December 2020. The final diagnosis was made based on histopathological findings. The PET imaging parameters were compared with clinical data and endoscopic features. A model to predict the risk of malignancy, based on PET, endoscopy, and clinical findings, was generated and validated using multivariable logistic regression analysis and an additional bootstrapping method. The final model was compared with standard endoscopy for the diagnosis of ampullary cancer using the DeLong test. Results: The mean tumor size was 17.1 ± 7.7 mm. Sixty-four (41.3%) tumors were benign, and 91 (58.7%) were malignant. Univariable analysis found that ampullary neoplasms with a blood-pool corrected peak standardized uptake value in earlyphase scan (SUVe) ≥ 1.7 were more likely to be malignant (odds ratio [OR], 16.06; 95% confidence interval [CI], 7.13–36.18;P < 0.001). Multivariable analysis identified the presence of jaundice (adjusted OR [aOR], 4.89; 95% CI, 1.80–13.33; P = 0.002), malignant traits in endoscopy (aOR, 6.80; 95% CI, 2.41–19.20; P < 0.001), SUVe ≥ 1.7 in PET (aOR, 5.43; 95% CI, 2.00–14.72; P < 0.001), and PET-detected nodal disease (aOR, 5.03; 95% CI, 1.16–21.86; P = 0.041) as independent predictors of malignancy. The model combining these four factors predicted ampullary cancers better than endoscopic diagnosis alone (area under the curve [AUC] and 95% CI: 0.925 [0.874–0.956] vs. 0.815 [0.732–0.873], P < 0.001). The model demonstrated an AUC of 0.921 (95% CI, 0.816–0.967) in candidates for endoscopic papillectomy. Conclusion Adding 2-[ 18F]FDG PET/CT to endoscopy can improve the diagnosis of ampullary cancer and may help refine therapeutic decision-making, particularly when contemplating endoscopic papillectomy.

Prostate cancer (PCa) is a significant health concern globally, necessitating effective treatment options. Typical treatment methods for early stage, particularly localized PCa, encompass radical procedures, such as radical prostatectomy (RP) and radiotherapy (RT), and nonradical focal therapy (FT). FT is a focused approach mainly used for treating small lesions limited to a specific zone of the prostate. Its objective is to achieve cancer control when minimizing damage to benign tissue. High-intensity focused ultrasound (HIFU) is one of the most used modalities in FT for the management of PCa. The progress in HIFU technology showcases continuous advancements, offering clinicians a variety of strategies to cater to diverse patient requirements. The advancements include the development of transrectal and transurethral HIFU machines that offer enhanced treatment distances, magnetic resonance imaging (MRI) fusion capabilities, real-time monitoring, and precise ablation. These improvements contribute to increased treatment effectiveness and better outcomes for patients. This narrative review aims to summarize the use of HIFU technology and its evolution, offering diverse options to clinicians, and explores the safety, effectiveness, and quality of different HIFU strategies, such as whole-gland ablation, hemigland ablation, and focal ablation. We conclude that nonwhole-gland HIFU offers similar cancer control with better short-term functional outcomes and fewer complications compared to whole-gland ablation. Combining HIFU with transurethral resection of the prostate (TURP) improves urinary function and reduces catheterization time. Focal ablation and hemigland ablation show promise in achieving cancer control when preserving continence and potency.
Humans ; Male ; Prostatic Neoplasms/surgery* ; High-Intensity Focused Ultrasound Ablation/methods* ; Ultrasound, High-Intensity Focused, Transrectal/methods* ; Magnetic Resonance Imaging ; Treatment Outcome

Objective:To develop a short-term prognostic model of spontaneous cerebral hemorrhage based on eXtreme Gradient Boosting (XGBoost) machine learning, and to compare its predictive performance with a Logistic regression model.Methods:Patients with sICH admitted to Department of Neurology, Second People's Hospital of Hefei from January 2018 to March 2022 were chosen; their general demographic characteristics, medical history, laboratory indices and cranial imaging data were retrospectively collected. The prognoses of patients 90 d after discharge were evaluated according to modified Rankin Scale (mRS) scores (good prognosis: mRS scores<3; poor prognosis: mRS scores≥3). XGboost and multiple Logistic regression models were used to screen out the factors for prognoses of patients 90 d after discharge, and area under receiver operating characteristic (ROC) curves, sensitivity, specificity and prediction accuracy of the 2 models were analyzed and compared.Results:A total of 413 patients with sICH were included; 180 patients(43.6 %) had poor prognosis and 233 (56.4%) had good prognosis 90 d after discharge. Multivariate Logistic regression results showed that age≥65 years, hemorrhage into the ventricle, hematoma volume of 20-40 mL, hematoma volume>40 mL and National Institutes of Health Stroke Scale (NIHSS) scores were independent influencing factors for short-term prognoses of sICH ( P<0.05). The variables in the XGBoost model were ranked in order of importance: NIHSS scores, systolic blood pressure at admission, Glasgow coma scale (GCS) scores, age≥65 years, hemorrhage into the ventricle, hematoma volume of 20-40 mL, and hematoma volume>40 mL. AUC of XGBoost model in predicting the prognosis was 0.895 (95% CI: 0.820-0.947), enjoying sensitivity of 68.89%, specificity of 94.83%, and prediction accuracy of 83.5%. AUC of Logistic regression model in predicting the prognosis was 0.894 (95% CI: 0.818-0.946), enjoying sensitivity of 93.33%, specificity of 70.69%, and prediction accuracy of 80.58%. Conclusion:The short-term prognostic model based on XGboost for sICH patients has high predictive efficacy, whose predictive accuracy is better than traditional Logistic regression.

Early diagnosis of rheumatoid arthritis with the initiation of disease-modifying antirheumatic drugs is important to prevent future disability. Seronegative rheumatoid arthritis lacks the classical immunological markers, thus imposing clinical diagnostic difficulty. In this case, we reported 68 Ga-FAPI PET/CT findings of seronegative rheumatoid arthritis in a 60-year-old lady. This case illustrates how 68  Ga-FAPI PET/CT aids in the diagnosis of seronegative rheumatoid arthritis.