Mental fatigue recognition study based on 1D convolutional neural network and short-term ECG signals.

BACKGROUND: Mental fatigue has become a non-negligible health problem in modern life, as well as one of the important causes of social transportation, production and life accidents. OBJECTIVE: Fatigue detection based on traditional machine learning requires manual and tedious feature extraction and feature selection engineering, which is inefficient, poor in real-time, and the recognition accuracy needs to be improved. In order to recognize daily mental fatigue level more accurately and in real time, this paper proposes a mental fatigue recognition model based on 1D Convolutional Neural Network (1D-CNN), which inputs 1D raw ECG sequences of 5 s duration into the model, and can directly output the predicted fatigue level labels. METHODS: The fatigue dataset was constructed by collecting the ECG signals of 22 subjects at three time periods: 9:00-11:00 a.m., 14:00-16:00 p.m., and 19:00-21:00 p.m., and then inputted into the 19-layer 1D-CNN model constructed in the present study for the classification of mental fatigue in three grades. RESULTS: The results showed that the model was able to recognize the fatigue levels effectively, and its accuracy, precision, recall, and F1 score reached 98.44%, 98.47%, 98.41%, and 98.44%, respectively. CONCLUSION: This study further improves the accuracy and real-time performance of recognizing multi-level mental fatigue based on electrocardiography, and provides theoretical support for real-time fatigue monitoring in daily life.

[Design and Development of ECG Monitoring Cloud Platform Based on the Internet of Things Electrocardiograph].

The design and development of electrocardiogram（ECG） monitoring cloud platform based on the Internet of Things（IoT） electrocardiograph is introduced. The platform is mainly composed of ECG acquisition module, algorithm module, diagnostic model comparison module, warning module, positioning module and medical aid system. The ECG acquisition module collects ECG signals of patients and displays them in real time on the mobile terminals. Then they are uploaded to the ECG monitoring cloud platform through the IoT. The algorithm module and the diagnostic model comparison module mark, process, analyze and diagnose the ECG. Meanwhile, the ECG diagnosis and warning results are pushed to patients and 120 emergency centers through the IoT. Furthermore, the cloud platform will guide patients to self-rescue and the emergency platform will open the green channel to save patients in time.The platform realizes from the onset to diagnosis and treatment in one step, and saves lives against time.

[Early Warning System of Sudden Cardiac Death Based on Internet Electrocardiograph and Intelligent Platform].

An early warning system of sudden cardiac death based on the Internet electrocardiograph and intelligent platform is designed to detect the signal of sudden cardiac death in time and save lives. The system is mainly composed of four parts: Internet electrocardiograph, mobile terminal, intelligent platform and 120 emergency center. It has been verified that the sudden cardiac death early warning system is reliable, suitable for remote electrocardiogram monitoring, and can provide diagnosis and early warning for people at risk of sudden cardiac death. The system realizes the miniaturization of ECG monitoring equipment, and has the advantages of intelligent diagnosis and rapid warning, and can be applied to the pre-hospital monitoring of high-risk groups of sudden cardiac death and has a good application value.

[Design and Application of Home Wireless Electrocardiograph Machine Based on Internet].

This study introduces the design and application of home wireless electrocardiograph(ECG) machine based on Internet. The world's first three-lead dry electrode mobile electrocardiograph machine has been developed, on the basis of the successful development of dry electrodes. Moreover, it is not only chips filtering, but also wireless, as a result it is applied to ECG monitoring and diagnosis of patients. Compared with traditional electrocardiograph machine, the machine is very convenient and comes into the home, ECG Machines is connected to mobile phones by Bluetooth, wireless upload, therefore we recommend to achieve remote monitoring and early warning and reduce sudden death, to achieve Internet medical by using Internet technology, people can be self-test. It is playing an increasingly important role and it is an inevitable machine to improve the success rate of diagnosis, monitoring and first aid.

A clinical prediction nomogram to assess risk of colorectal cancer among patients with type 2 diabetes.

Colorectal cancer remains a major health burden worldwide and is closely related to type 2 diabetes. This study aimed to develop and validate a colorectal cancer risk prediction model to identify high-risk individuals with type 2 diabetes. Records of 930 patients with type 2 diabetes were reviewed and data were collected from 1 November 2013 to 31 December 2019. Clinical and demographic parameters were analyzed using univariable and multivariable logistic regression analysis. The nomogram to assess the risk of colorectal cancer was constructed and validated by bootstrap resampling. Predictors in the prediction nomogram included age, sex, other blood-glucose-lowering drugs and thiazolidinediones. The nomogram demonstrated moderate discrimination in estimating the risk of colorectal cancer, with Hosmer-Lemeshow test P = 0.837, an unadjusted C-index of 0.713 (95% CI 0.670-0.757) and a bootstrap-corrected C index of 0.708. In addition, the decision curve analysis demonstrated that the nomogram would be clinically useful. We have developed a nomogram that can predict the risk of colorectal cancer in patients with type 2 diabetes. The nomogram showed favorable calibration and discrimination values, which may help clinicians in making recommendations about colorectal cancer screening for patients with type 2 diabetes.

Nomogram for Predicting Risk of Digestive Carcinoma Among Patients with Type 2 Diabetes.

PURPOSE: Digestive carcinomas remain a major health burden worldwide and are closely related to type 2 diabetes. The aim of this study was to develop and validate a digestive carcinoma risk prediction model to identify high-risk individuals among those with type 2 diabetes. PATIENTS AND METHODS: The prediction model was developed in a primary cohort that consisted of 655 patients with type 2 diabetes. Data were collected from November 2013 to December 2018. Clinical parameters and demographic characteristics were analyzed by logistic regression to develop a model to predict the risk of digestive carcinomas; then, a nomogram was constructed. The performance of the nomogram was assessed with respect to calibration, discrimination, and clinical usefulness. The results were internally validated by a bootstrapping procedure. The independent validation cohort consisted of 275 patients from January 2019 to December 2019. RESULTS: Predictors in the prediction nomogram included sex, age, insulin use, and body mass index. The model showed good discrimination (C-index 0.747 [95% CI, 0.718-0.791]) and calibration (Hosmer-Lemeshow test P=0.541). The nomogram showed similar discrimination in the validation cohort (C-index 0.706 [95% CI, 0.682-0.755]) and good calibration (Hosmer-Lemeshow test P=0.418). Decision curve analysis demonstrated that the nomogram would be clinically useful. CONCLUSION: We developed a low-cost and low-risk model based on clinical and demographic parameters to help identify patients with type 2 diabetes who might benefit from digestive cancer screening.

Experimental study of thymidine kinase gene therapy of neuroblastoma in vitro and in vivo.

Neuroblastoma arises as a direct result of genetic disorder; therefore, it should be well treated and conquered by gene therapy in future. In this study, neuroblastoma cell line SH-SY5Y experiments, in vitro and in nude mice in vivo, were subjected to research thymidine kinase suicide gene to treat neuroblastoma. The plasmid LXpsp-hytk and a plasmid LXSH were transduced separately by lipofectin into human neuroblastoma cell line SH-SY5Y. SH-SY5Y-hy and SH-SY5Y-hytk were selected by hygromycin B. Different ganciclovir (GCV) concentration was given to SH-SY5Y-hytk to determine optimal GCV concentration. The cytotoxic effect of GCV on SH-SY5Y-hytk, SH-SY5Y-hy, and SH-SY5Y cells was determined. Scapular subcutaneous tumors were established in nude mice by inoculating 2.5 x 10(6) SH-SY5Y-hytk on their left sides and 2.5 x 10(6) SH-SY5Y-hy cells on their right sides for every mouse of treatment group and control group, respectively. After 1 week, mass grew in both sides of all the mice, and from the eighth day on, every mouse in treatment group received daily intraperitoneal injection of GCV 50 mg/kg body weight for 14 days; every mouse in control group received daily intraperitoneal injection of 1 ml saline for 14 days. On day 22 tumors were excised and weighed on the left and right sides, respectively, and apoptosis was detected by TUNEL method. Apoptotic index was calculated on the left and on the right sides, respectively, for every mouse in treatment group and control group. The lowest concentration of hygromycin B was 60 microg/ml. The cytotoxic effect of GCV on SH-SY5Y-hytk cells was obvious (IC(50)=0.03 microM), whereas GCV showed almost no cytotoxic effect on SH-SY5Y and SH-SY5Y-hy cells (IC(50)>400 microM). SH-SY5Y-hytk was killed by concentrations of 30 microM GCV effectively and it obviously showed the bystander effect, when SH-SY5Y-hytk remained at least 18% in the mixture culture cells. The tumor on the left side was much smaller than that of the right side in control group (p<0.05), and apoptotic index of the left was higher than that of the right in control group (p<0.01). SH-SY5Y-hytk has the bystander effect over 18% SH-SY5Y-hytk of the mixture culture cells at the concentration of 30 microM GCV. The HSV-tk/GCV system was effective in treating SH-SY5Y neuroblastoma cell line in vivo as well. Our findings suggest that thymidine kinase gene therapy could be a potential method for treating neuroblastoma in the future.

ICAM-1 expression is upregulated in reflux nephropathy.

Reflux nephropathy (RN) is a major cause of end-stage renal failure in children and young adults. Intercellular adhesion molecule-1 (ICAM-1), a cell surface glycoprotein, has a role in the regulation of interaction among immune cells. It has been demonstrated that increased levels of tubular ICAM-1 correlate with an extent of tubular damage in diabetic nephropathy. We hypothesized that ICAM-1 local synthesis is altered in reflux nephropathy and therefore designated this study to investigate ICAM-1 expression in RN. The kidney specimens from six patients with severe reflux nephropathy secondary to primary vesicoureteral reflux were obtained at the time of nephrectomy. Control materials included normal kidney specimens obtained from three adult patients during partial nephrectomy for an incidentaloma. Fluorescent immunohistochemistry was carried out using monoclonal antibodies to ICAM-1 utilizing confocal laser scanning microscopy. Reverse transcriptase polymerase chain reaction (RT-PCR) was performed to evaluate the relative amount of ICAM-1. In the control kidneys, there was lack of ICAM-1 immunoreactivity in the interstitium and proximal tubules and moderate immunoreactivity in the glomerulus. In the refluxing kidney there was strong ICAM-1 immunoreactivity in the glomerulus, interstitium and proximal tubules. The RT-PCR showed strong ICAM-1 mRNA expression in the refluxing kidneys and absent or weak ICAM-1 expression in the controls. Our findings of increased expression of ICAM-1 in the severe reflux nephropathy kidney suggests that ICAM-1 may play a role in the pathogenesis of renal parenchymal damage associated with RN.

The prevalence of metabolic syndrome in Han and Zhuang Chinese in Guangxi / 中华内分泌代谢杂志

Objective To investigate the prevalence of metabolic syndrome(MS)and its components among people aged over 15 years in Guangxi Zhuang Autonomous Region and to compare the difference between Zhuang and Han populations.Methods Adopting cluster sampling,a survey of diabetes mellitus was conducted in Guangxi from 2003 to 2005.A total of 27 240 subjects aged over 15 years with complete data,including background information of each individual,blood pressure,lipid profile,plasma glucose,blood uric acid and fasting insulin were analyzed in this study.The prevalence of MS and its components were analysed in Han and Zhuang Chinese in Guangxi.The criteria of International Diabetes Federation(IDF)in 2005 and the China Diabetes Society(CDS)in 2004 were applied for diagnosis.Results(1)The crude prevalence rates of MS according to IDF definition were 13.15%in total,12.41%in male and 14.11%in female respectively.The age- standardized prevalence rates of MS(according to the population composition in China in 2000)were 7.66%in total,7.26%in male and 8.81%in female.The crude prevalence rates of MS according to CDS definition were 10.75%in total,13.45%in male and 7.28%in female respectively and the age-standar-dized prevalence rates of MS were 5.9%in total,7.21%in male and 4.31%in female.The prevalence of MS in total,male and female was increasing with age(P