Databases, Bibliographic ; Evidence-based Practice ; Health Services Needs And Demand

The present study aimed to explore the main active components and underlying mechanisms of Marsdenia tenacissima in the treatment of ovarian cancer(OC) through network pharmacology, molecular docking, and in vitro cell experiments. The active components of M. tenacissima were obtained from the literature search, and their potential targets were obtained from SwissTargetPrediction. The OC-related targets were retrieved from Therapeutic Target Database(TTD), Online Mendelian Inheritance in Man(OMIM), GeneCards, and PharmGKB. The common targets of the drug and the disease were screened out by Venn diagram. Cytoscape was used to construct an "active component-target-disease" network, and the core components were screened out according to the node degree. The protein-protein interaction(PPI) network of the common targets was constructed by STRING and Cytoscape, and the core targets were screened out according to the node degree. GO and KEGG enrichment analyses of potential therapeutic targets were carried out with DAVID database. Molecular docking was used to determine the binding activity of some active components to key targets by AutoDock. Finally, the anti-OC activity of M. tenacissima extract was verified based on SKOV3 cells in vitro. The PI3K/AKT signaling pathway was selected for in vitro experimental verification according to the results of GO function and KEGG pathway analyses. Network pharmacology results showed that 39 active components, such as kaempferol, 11α-O-benzoyl-12β-O-acetyltenacigenin B, and drevogenin Q, were screened out, involving 25 core targets such as AKT1, VEGFA, and EGFR, and the PI3K-AKT signaling pathway was the main pathway of target protein enrichment. The results of molecular docking also showed that the top ten core components showed good binding affinity to the top ten core targets. The results of in vitro experiments showed that M. tenacissima extract could significantly inhibit the proliferation of OC cells, induce apoptosis of OC cells through the mitochondrial pathway, and down-regulate the expression of proteins related to the PI3K/AKT signaling pathway. This study shows that M. tenacissima has the characteristics of multi-component, multi-target, and multi-pathway synergistic effect in the treatment of OC, which provides a theoretical basis for in-depth research on the material basis, mechanism, and clinical application.
Humans ; Female ; Marsdenia ; Molecular Docking Simulation ; Network Pharmacology ; Phosphatidylinositol 3-Kinases ; Proto-Oncogene Proteins c-akt ; Ovarian Neoplasms/genetics* ; Databases, Genetic ; Plant Extracts ; Drugs, Chinese Herbal/pharmacology*

Sleep staging is the basis for solving sleep problems. There's an upper limit for the classification accuracy of sleep staging models based on single-channel electroencephalogram (EEG) data and features. To address this problem, this paper proposed an automatic sleep staging model that mixes deep convolutional neural network (DCNN) and bi-directional long short-term memory network (BiLSTM). The model used DCNN to automatically learn the time-frequency domain features of EEG signals, and used BiLSTM to extract the temporal features between the data, fully exploiting the feature information contained in the data to improve the accuracy of automatic sleep staging. At the same time, noise reduction techniques and adaptive synthetic sampling were used to reduce the impact of signal noise and unbalanced data sets on model performance. In this paper, experiments were conducted using the Sleep-European Data Format Database Expanded and the Shanghai Mental Health Center Sleep Database, and achieved an overall accuracy rate of 86.9% and 88.9% respectively. When compared with the basic network model, all the experimental results outperformed the basic network, further demonstrating the validity of this paper's model, which can provide a reference for the construction of a home sleep monitoring system based on single-channel EEG signals.
China ; Sleep Stages ; Sleep ; Electroencephalography ; Databases, Factual

Arrhythmia is a significant cardiovascular disease that poses a threat to human health, and its primary diagnosis relies on electrocardiogram (ECG). Implementing computer technology to achieve automatic classification of arrhythmia can effectively avoid human error, improve diagnostic efficiency, and reduce costs. However, most automatic arrhythmia classification algorithms focus on one-dimensional temporal signals, which lack robustness. Therefore, this study proposed an arrhythmia image classification method based on Gramian angular summation field (GASF) and an improved Inception-ResNet-v2 network. Firstly, the data was preprocessed using variational mode decomposition, and data augmentation was performed using a deep convolutional generative adversarial network. Then, GASF was used to transform one-dimensional ECG signals into two-dimensional images, and an improved Inception-ResNet-v2 network was utilized to implement the five arrhythmia classifications recommended by the AAMI (N, V, S, F, and Q). The experimental results on the MIT-BIH Arrhythmia Database showed that the proposed method achieved an overall classification accuracy of 99.52% and 95.48% under the intra-patient and inter-patient paradigms, respectively. The arrhythmia classification performance of the improved Inception-ResNet-v2 network in this study outperforms other methods, providing a new approach for deep learning-based automatic arrhythmia classification.
Humans ; Arrhythmias, Cardiac/diagnostic imaging* ; Cardiovascular Diseases ; Algorithms ; Databases, Factual ; Electrocardiography

In the diagnosis of cardiovascular diseases, the analysis of electrocardiogram (ECG) signals has always played a crucial role. At present, how to effectively identify abnormal heart beats by algorithms is still a difficult task in the field of ECG signal analysis. Based on this, a classification model that automatically identifies abnormal heartbeats based on deep residual network (ResNet) and self-attention mechanism was proposed. Firstly, this paper designed an 18-layer convolutional neural network (CNN) based on the residual structure, which helped model fully extract the local features. Then, the bi-directional gated recurrent unit (BiGRU) was used to explore the temporal correlation for further obtaining the temporal features. Finally, the self-attention mechanism was built to weight important information and enhance model's ability to extract important features, which helped model achieve higher classification accuracy. In addition, in order to mitigate the interference on classification performance due to data imbalance, the study utilized multiple approaches for data augmentation. The experimental data in this study came from the arrhythmia database constructed by MIT and Beth Israel Hospital (MIT-BIH), and the final results showed that the proposed model achieved an overall accuracy of 98.33% on the original dataset and 99.12% on the optimized dataset, which demonstrated that the proposed model can achieve good performance in ECG signal classification, and possessed potential value for application to portable ECG detection devices.
Humans ; Electrocardiography ; Algorithms ; Cardiovascular Diseases ; Databases, Factual ; Neural Networks, Computer

Objective: To analyze the global epidemiology of renal cell carcinoma (RCC) in 2020. Methods: The incidence and mortality data of RCC in the cooperative database GLOBOCAN 2020 of International Agency for Research on Cancer of WHO and the human development index (HDI) published by the United Nations Development Programme in 2020 were collated. The crude incidence rate (CIR), age-standardized incidence rate (ASIR), crude mortality rate (CMR), age-standardized mortality rate (ASMR) and mortality/incidence ratio (M/I) of RCC were calculated. Kruskale-Wallis test was used to analyze the differences in ASIR or ASMR among HDI countries. Results: In 2020, the global ASIR of RCC was 4.6/100 000, of which 6.1/100 000 for males and 3.2/100 000 for females and ASIR was higher in very high and high HDI countries than that in medium and low HDI countries. With the rapid increase of age after the age of 20, the growth rate of ASIR in males was faster than that in females, and slowed down at the age of 70 to 75. The truncation incidence rate of 35-64 years old was 7.5/100 000 and the cumulative incidence risk of 0-74 years old was 0.52%. The global ASMR of RCC was 1.8/100 000, 2.5/100 000 for males and 1.2/100 000 for females. The ASMR of males in very high and high HDI countries (2.4/100 000-3.7/100 000) was about twice that of males (1.1/100 000-1.4/100 000) in medium and low HDI countries, while the ASMR of female (0.6/100 000-1.5/100 000) did not show significant difference. ASMR continued to increase rapidly with age after the age of 40, and the growth rate of males was faster than that of females. The truncation mortality rate of 35-64 years old was 2.1/100 000, and the cumulative mortality risk of 0-74 years old was 0.20%. M/I decreases with the increase of HDI, with M/I as 0.58 in China, which was higher than the global average of 0.39 and the United States' 0.17. Conclusion: The ASIR and ASMR of RCC presented significant regional and gender disparities globally, and the heaviest burden was in very high HDI countries.
Male ; Humans ; Female ; Adult ; Middle Aged ; Infant, Newborn ; Infant ; Child, Preschool ; Child ; Adolescent ; Young Adult ; Aged ; Carcinoma, Renal Cell/epidemiology* ; Incidence ; Databases, Factual ; China ; Kidney Neoplasms/epidemiology* ; Global Health

Addressing weight stigma is essential to obesity management as it causes inequalities in healthcare and impacts the outcomes of health. This narrative review summarises systematic review findings about the presence of weight bias in healthcare professionals, and interventions to reduce weight bias or stigma in these professionals. Two databases (PubMed and Cumulative Index to Nursing and Allied Health Literature [CINAHL]) were searched. Seven eligible reviews were identified from 872 search results. Four reviews identified the presence of weight bias, and three investigated trials to reduce weight bias or stigma in healthcare professionals. The findings may help further research and the treatment, health and well-being of individuals with overweight or obesity in Singapore. Weight bias was prevalent among qualified and student healthcare professionals globally, and there is a lack of clear guidance for effective interventions to reduce it, particularly in Asia. Future research is essential to identify the issues and inform initiatives to reduce weight bias and stigma among healthcare professionals in Singapore.
Humans ; Weight Prejudice ; Singapore ; Asia ; Databases, Factual ; Health Facilities

Based on data mining technology, the acupoints compatibility rules of acupuncture for depression diseases were explored. The randomized controlled trial (RCT) articles regarding acupuncture for depression diseases published from establishment of database to September 2nd, 2022 were searched in CNKI database, Wangfang database, VIP database, SinoMed database, PubMed, EMbase, Web of Science and Cochrane Library. The use frequency of acupoints, meridian tropism, selection of special acupoints and acupoint association rules for five common depression diseases, including primary depression, post-stroke depression, menopausal syndrome, psychoneurosis and anxiety disorder, were analyzed by Python programming language. Cytoscape software was used to analyze the acupoint association and the disease-acupoint co-occurrence network. As a result, totally 387 articles were included, and 319 acupoints prescriptions for the above five common depression diseases were extracted, involving 159 acupoints. The use frequency of acupoints was 2 574 times in total. The frequently-used acupoints were Baihui (GV 20), Sanyinjiao (SP 6), Taichong (LR 3), Neiguan (PC 6), Shenmen (HT 7), Yintang (GV 24⁺), Zusanli (ST 36), Hegu (LI 4), Sishencong (EX-HN 1) and Taixi (KI 3), etc. The frequently involved meridians were the governor vessel, foot-taiyang bladder meridian, foot-taiyin spleen meridian, and foot-jueyin liver meridian. The frequency of the special acupoints from high to low was crossing points, five-shu points, yuan-primary points, back-shu points, luo-connecting points, and eight confluent points, etc, which were often used in combination with "Baihui (GV 20)-Yintang (GV 24⁺)" (the highest degree of association). At the same time, the analysis of the co-occurrence network of depression diseases and acupoints showed that the core acupoints group of acupuncture for depression diseases were Baihui (GV 20), Taichong (LR 3), Shenmen (HT 7), Zusanli (ST 36), Neiguan (PC 6) and Sanyinjiao (SP 6). In conclusion, acupuncture treatment for depression diseases has gradually formed a rule of acupoint compatibility, with special acupoint as the main body and "unblocking the governor vessel, and regulating the spirit and qi " as the main therapeutic principle.
Acupuncture Points ; Acupuncture Therapy ; Data Mining ; Depression ; Meridians ; Randomized Controlled Trials as Topic

The patents of acupuncture and moxibustion in China and abroad was analyzed, aiming to provide support for the innovative development of acupuncture industry. With the China Think Tank of Patent of Traditional Chinese Medicine and the PatSnap database as data sources, based on the mathematical statistics method, the application trend, legal status, patent types, transformation and distribution of major technical fields of acupuncture patents in China and abroad were analyzed. As a result, a total of 53,422 acupuncture patents were screened, involving 49 countries and 4 organizations. The patent types were mainly utility model patents. Although the application number of acupuncture patent had increased rapidly, the average patent conversion rate was generally low, approximately 4%. In the context of global economic integration, the acupuncture industry is developing at a high speed. It is suggested to take advantage of the "Belt and Road Initiative" to improve the international acceptance of acupuncture and moxibustion, adhere to the principle of attaching equal importance to the number and quality of patents, promote the in-depth cooperation of industry-university-research, and promote high-quality development of acupuncture and moxibustion.
Humans ; Moxibustion ; Acupuncture Therapy ; China ; Medicine, Chinese Traditional ; Databases, Factual

INTRODUCTION: To compare epidemiological features and clinical presentations of deep infiltrating endometriosis with endometrioma and adenomyosis, as well as to identify risk factors for the respective histologically confirmed conditions. METHOD: Patients undergoing index surgery at the National University Hospital, Singapore for endometriosis or adenomyosis over a 7-year period-from 2015 to 2021-were identified from hospital databases using the Table of Surgical Procedures coding. Social and epidemiological features of cases with histologically confirmed diagnoses of endometrioma only, adenomyosis only, and deep infiltrating endometriosis were compared. Significant variables from univariate analysis were entered into 3 binary multivariate logistic regression models to obtain independent risk factors for: deep infiltrating endometriosis versus endometrioma only, deep infiltrating endometriosis versus adenomyosis only, and adenomyosis only versus endometrioma only. RESULTS: A total of 258 patients were included with 59 ovarian endometrioma only, 47 adenomyosis only, and 152 deep infiltrating endometrioses. Compared to endometrioma only, deep infiltrating endometriosis was associated with higher rates of severe dysmenorrhoea (odds ratio [OR] 2.80, 95% confidence interval [CI] 1.02-7.70) and out-of-pocket private surgical care (OR 4.72, 95% CI 1.85-12.04). Compared to adenomyosis only, deep infiltrating endometriosis was associated with a higher fertility desire (OR 13.47, 95% CI 1.01-180.59) and a lower body mass index (OR 0.89, 95% CI 0.79-0.99). In contrast, heavy menstrual bleeding was the hallmark of adenomyosis, being less common in patients with endometriosis. CONCLUSION Deep infiltrating endometriosis is associated with severe dysmenorrhoea, pain related to urinary and gastrointestinal tracts, higher fertility desire and infertility rate. Patients with pain symptomatology and subfertility should be referred early to a tertiary centre with the capability to diagnose and manage deep infiltrating endometriosis.
Female ; Humans ; Endometriosis/surgery* ; Adenomyosis/surgery* ; Dysmenorrhea/etiology* ; Risk Factors ; Databases, Factual