This study utilized data from the non-communicable diseases (NCDs) Progress Monitor Reports (2015, 2017, 2020, 2022) released by World Health Organization (WHO) to analyze the implementation of NCDs prevention and control policies in China from 2014 to 2021 through descriptive statistical method, aiming to provide evidence for strengthening national NCDs strategies. The analysis focuses on WHO-recommended ‘best buys’ policies for NCDs prevention and control, covering 10 categories (18 interventions): national NCDs targets, mortality data, risk factor surveys, national integrated NCDs policies/strategies/action plans, tobacco demand-reduction measures, harmful use of alcohol reduction measures, unhealthy diet reduction policies, physical activity campaigns, national clinical guidelines for cancer/CVD/diabetes/CRD management, and drug therapy/counselling for cardiovascular diseases. In accordance with the WHO′s NCDs progress monitor scoring methodology, policies are assigned 1.0 point for full implementation, 0.5 points for partial implementation, and 0 points for non-implementation or missing data, with a maximum total score of 18.0 points. The analytical metrics encompass the policy implementation score, implementation rate, and period-on-period implementation growth rate. The results showed that China′s total policy implementation scores for NCDs prevention and control in 2014, 2016, 2019, and 2021 were consistently higher than the global average (8.5, 10.5, 9.5, 9.5 vs 6.7, 8.3, 8.6, 8.6). From 2014 to 2021, the total score increased by 1.0 point, and the implementation rate improved by 8.9%. From 2014 to 2016, China′s total policy implementation score rose from 8.5 to 10.5, primarily driven by improvements in tobacco tax increases and unhealthy diet reduction measures (salt reduction, restrictions on high-fat foods, and regulation of breast-milk substitute sales). However, this progress was partially offset by a decline in scores for physical activity campaigns. From 2016 to 2019, the total score decreased to 9.5, largely due to lower scores in harmful use of alcohol reduction measures (alcohol taxation and advertising bans). From 2019 to 2021, the total score remained stable, with increases in marketing to children restrictions balanced by declines in scores for drug therapy/counselling for cardiovascular diseases. In 2021, China′s total policy implementation score (9.5) exceeded the global average (8.6) but fell below the G20 average (11.2). Significant gaps remained compared to top-performing G20 countries such as Turkey (16.5), particularly in tobacco control and restrictions on harmful alcohol use. In conclusion, from 2014 to 2021, China′s total policy implementation score for NCDs prevention and control consistently exceeded the global average, demonstrating an upward trend, and various NCDs prevention and control policies have been continuously improved.

The phenomenon of adolescent suicide has become a serious challenge to global public health, and suicidal behavior can directly threatening the lives of adolescents.Attempted suicide during adolescence has long-term negative impacts on their health in adulthood.With the continuous development of artificial intelligence technology, machine learning has demonstrated markedly superior performance compared to traditional assessment tools in predicting the risk of suicide among adolescents.Therefore, this article reviews the application and significance of machine learning in predicting suicidal behavior among adolescents.It mainly focuses on machine learning-related concepts, the utilization of multimodal data such as text and voice, as well as the in-depth analysis of algorithmic performance.However, this learning technology continues to encounter challenges pertaining to data quality, overfitting, model interpretability as well as ethical considerations.In future practical applications, various factors, including data characteristics, problem requirements, time costs and algorithm performance, should be comprehensively considered to develop a more accurate predictive model for adolescent suicidal behavior, thereby safeguarding the mental health of adolescents.

The phenomenon of adolescent suicide has become a serious challenge to global public health, and suicidal behavior can directly threatening the lives of adolescents.Attempted suicide during adolescence has long-term negative impacts on their health in adulthood.With the continuous development of artificial intelligence technology, machine learning has demonstrated markedly superior performance compared to traditional assessment tools in predicting the risk of suicide among adolescents.Therefore, this article reviews the application and significance of machine learning in predicting suicidal behavior among adolescents.It mainly focuses on machine learning-related concepts, the utilization of multimodal data such as text and voice, as well as the in-depth analysis of algorithmic performance.However, this learning technology continues to encounter challenges pertaining to data quality, overfitting, model interpretability as well as ethical considerations.In future practical applications, various factors, including data characteristics, problem requirements, time costs and algorithm performance, should be comprehensively considered to develop a more accurate predictive model for adolescent suicidal behavior, thereby safeguarding the mental health of adolescents.

This study utilized data from the non-communicable diseases (NCDs) Progress Monitor Reports (2015, 2017, 2020, 2022) released by World Health Organization (WHO) to analyze the implementation of NCDs prevention and control policies in China from 2014 to 2021 through descriptive statistical method, aiming to provide evidence for strengthening national NCDs strategies. The analysis focuses on WHO-recommended ‘best buys’ policies for NCDs prevention and control, covering 10 categories (18 interventions): national NCDs targets, mortality data, risk factor surveys, national integrated NCDs policies/strategies/action plans, tobacco demand-reduction measures, harmful use of alcohol reduction measures, unhealthy diet reduction policies, physical activity campaigns, national clinical guidelines for cancer/CVD/diabetes/CRD management, and drug therapy/counselling for cardiovascular diseases. In accordance with the WHO′s NCDs progress monitor scoring methodology, policies are assigned 1.0 point for full implementation, 0.5 points for partial implementation, and 0 points for non-implementation or missing data, with a maximum total score of 18.0 points. The analytical metrics encompass the policy implementation score, implementation rate, and period-on-period implementation growth rate. The results showed that China′s total policy implementation scores for NCDs prevention and control in 2014, 2016, 2019, and 2021 were consistently higher than the global average (8.5, 10.5, 9.5, 9.5 vs 6.7, 8.3, 8.6, 8.6). From 2014 to 2021, the total score increased by 1.0 point, and the implementation rate improved by 8.9%. From 2014 to 2016, China′s total policy implementation score rose from 8.5 to 10.5, primarily driven by improvements in tobacco tax increases and unhealthy diet reduction measures (salt reduction, restrictions on high-fat foods, and regulation of breast-milk substitute sales). However, this progress was partially offset by a decline in scores for physical activity campaigns. From 2016 to 2019, the total score decreased to 9.5, largely due to lower scores in harmful use of alcohol reduction measures (alcohol taxation and advertising bans). From 2019 to 2021, the total score remained stable, with increases in marketing to children restrictions balanced by declines in scores for drug therapy/counselling for cardiovascular diseases. In 2021, China′s total policy implementation score (9.5) exceeded the global average (8.6) but fell below the G20 average (11.2). Significant gaps remained compared to top-performing G20 countries such as Turkey (16.5), particularly in tobacco control and restrictions on harmful alcohol use. In conclusion, from 2014 to 2021, China′s total policy implementation score for NCDs prevention and control consistently exceeded the global average, demonstrating an upward trend, and various NCDs prevention and control policies have been continuously improved.

Background::The conversion of adenosine (A) to inosine (I) through deamination is the prevailing form of RNA editing, impacting numerous nuclear and cytoplasmic transcripts across various eukaryotic species. Millions of high-confidence RNA editing sites have been identified and integrated into various RNA databases, providing a convenient platform for the rapid identification of key drivers of cancer and potential therapeutic targets. However, the available database for integration of RNA editing in hematopoietic cells and hematopoietic malignancies is still lacking.Methods::We downloaded RNA sequencing (RNA-seq) data of 29 leukemia patients and 19 healthy donors from National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) database, and RNA-seq data of 12 mouse hematopoietic cell populations obtained from our previous research were also used. We performed sequence alignment, identified RNA editing sites, and obtained characteristic editing sites related to normal hematopoietic development and abnormal editing sites associated with hematologic diseases.Results::We established a new database, "REDH", represents RNA editome in hematopoietic differentiation and malignancy. REDH is a curated database of associations between RNA editome and hematopoiesis. REDH integrates 30,796 editing sites from 12 murine adult hematopoietic cell populations and systematically characterizes more than 400,000 edited events in malignant hematopoietic samples from 48 cohorts (human). Through the Differentiation, Disease, Enrichment, and knowledge modules, each A-to-I editing site is systematically integrated, including its distribution throughout the genome, its clinical information (human sample), and functional editing sites under physiological and pathological conditions. Furthermore, REDH compares the similarities and differences of editing sites between different hematologic malignancies and healthy control.Conclusions::REDH is accessible at http://www.redhdatabase.com/. This user-friendly database would aid in understanding the mechanisms of RNA editing in hematopoietic differentiation and malignancies. It provides a set of data related to the maintenance of hematopoietic homeostasis and identifying potential therapeutic targets in malignancies.

Antiviral therapy is an effective means of curing chronic hepatitis C (CHC) and a key focus of preventing the spread of hepatitis C. By analyzing domestic and foreign literature, this paper provides an overview of the estimation of the antiviral treatment rate for CHC, the current situation of antiviral treatment for CHC both domestically and internationally, and the factors that affect acceptance of antiviral treatment. At present, the antiviral treatment rate for CHC cases is relatively low both domestically and internationally. The treatment status of CHC cases is related to factors such as the general situation of the case, knowing their HCV status or self-perceived condition, concurrent presence of other diseases or conditions, knowledge of hepatitis C prevention and treatment, and social interaction and behavioral guidance. In response to the relevant difficulties, in-depth research or more support is needed to improve the antiviral treatment rate of CHC cases and achieve the goal of eliminating hepatitis C by 2030. Efforts should be made to strengthen policy support, improve the diagnosis of hepatitis C, prevent and control multiple diseases together, conduct targeted publicity and education, and enhance social support.

Antiviral therapy is an effective means of curing chronic hepatitis C (CHC) and a key focus of preventing the spread of hepatitis C. By analyzing domestic and foreign literature, this paper provides an overview of the estimation of the antiviral treatment rate for CHC, the current situation of antiviral treatment for CHC both domestically and internationally, and the factors that affect acceptance of antiviral treatment. At present, the antiviral treatment rate for CHC cases is relatively low both domestically and internationally. The treatment status of CHC cases is related to factors such as the general situation of the case, knowing their HCV status or self-perceived condition, concurrent presence of other diseases or conditions, knowledge of hepatitis C prevention and treatment, and social interaction and behavioral guidance. In response to the relevant difficulties, in-depth research or more support is needed to improve the antiviral treatment rate of CHC cases and achieve the goal of eliminating hepatitis C by 2030. Efforts should be made to strengthen policy support, improve the diagnosis of hepatitis C, prevent and control multiple diseases together, conduct targeted publicity and education, and enhance social support.

Objective:To analyze the genetic etiology and prognosis in fetuses with increased nuchal translucency (NT) in order to assist in the clinical prenatal genetic counseling and diagnosis.Methods:This study retrospectively enrolled 1 658 cases of singleton pregnancy (<35 years old) receiving invasive prenatal diagnosis, including karyotype analysis and/or chromosome microarray analysis or copy number variation (CNV) sequencing, due to NT value ≥2.5 mm in the first trimester in Henan Provincial People's Hospital from August 2014 to December 2021. They were divided into different groups according to the thickness of NT (≥2.5-<3.0, ≥3.0-<3.5, ≥3.5-<4.5, ≥4.5-<5.5, ≥5.5-<6.5 and ≥6.5 mm groups) and abnormal ultrasound findings (isolated increased NT group, increased NT complicated by soft markers/non-severe structural abnormality group and increased NT complicated by severe structural abnormality group). The results of invasive prenatal diagnosis and pregnancy outcomes were compared between different groups using Chi-square test and trend Chi-square test. Results:The detection rates of numerical abnormalities of chromosomes were 15.8% (262/1 658) and 17.6% (252/1 431) when the NT thickness cut-off value were 2.5 mm or 3.0 mm, respectively. Overall, the detection rate of numerical abnormalities of chromosomes increased with thickness of NT ( χ2trend=180.75, P<0.001), ranging from 6.6% (44/671) in the NT≥2.5-<3.5 mm group to 45.6% (113/248) in the NT≥5.5 mm group. The incidence of pathogenic/likely pathogenic CNV(P/LP CNV) did not increased with NT thickness ( χ2trend=3.26, P=0.071), and the highest detection rate was observed in the NT≥4.5-<5.5 mm group (9.0%, 19/211). The detection rate of numerical abnormalities of chromosomes plus P/LP CNV in the isolated NT≥2.5-<3.0 mm group and NT≥3.0-<3.5 mm group were 5.3% (10/188) and 9.6% (36/375), respectively, however, the difference was not statistically significant ( χ2=3.06, P=0.080). The detection rates of numerical abnormalities of chromosomes plus P/LP CNV in the isolated NT≥3.5-<4.5 mm group and NT≥2.5-<3.0 mm complicated by soft markers/ non-severe structural abnormality group were 12.7% (52/410) and 24.1% (7/29), respectively, and the risk were 2.6 times (95% CI: 1.3-5.2) and 5.7 times (95% CI: 2.0-16.4) of the isolated NT≥2.5-<3.0 mm group, respectively. The pregnancy termination rate increased with the NT thickness ( χ2trend=304.42, P<0.001), ranging from 10.8% (23/212) in the NT≥2.5-<3.0 mm group to 90.7% (117/129) in the NT≥6.5 mm group. After exclusion of the pregnancies terminated due to numerical abnormalities of chromosomes and P/LP CNV, 87.6% (862/984) of the fetus with increased NT were born alive. Conclusions:The detection rate of numerical abnormalities of chromosomes increases with the thickness of NT. Invasive prenatal diagnosis is required for non-advance aged singleton pregnant women when fetuses present with isolated NT≥2.5 mm with or without soft markers/structural abnormalities.

Increasing evidence suggests that atrial fibrillation is associated with an increased risk of cognitive impairment and dementia beyond its association with stroke and mortality. The association is independent of stroke. However, the association between atrial fibrillation and cognitive function has often been overlooked in the management and treatment in clinical practice. There is a lack of consensus on the relationship and its mechanisms between atrial fibrillation and brain dysfunction. Whether treatments targeted atrial fibrillation are effective for brain function remains unknown. Through reviewing relevant literatures, this article analyzed the association between atrial fibrillation and its underlying mechanisms. Furthermore, this article further discussed the effectiveness of atrial fibrillation treatments to cognitive function and brain health.

Objective:To establish a standardized training assessment index system for newly recruited nurses in the Hematology Department, so as to provide reference for the quality evaluation of standardized training for newly recruited nurses in the Hematology Department.Methods:Taking the Kirkpatrick four-level model as the theoretical framework, combined with literature review, group discussion, and Delphi expert consultation, indicators were screened and weights were determined to ultimately determine the index system.Results:Around two rounds of consultation, the positivity coefficients of experts were 100% (15/15), and the authoritative coefficients of experts were 0.850 and 0.875, respectively. The Kendall's coordination coefficients of indicators at all levels for two rounds of consultation were 0.379 to 0.685 and 0.235 to 0.307, respectively. The final standardized training assessment index system for newly recruited nurses in the Hematology Department included four first-level indicators, 15 second-level indicators, and 57 third-level indicators.Conclusions:The standardized training assessment index system is scientific and standardized, with relatively reasonable content settings, which can provide reference for the standardized training assessment of newly recruited nurses in the Hematology Department.