Objective To reveal the differences in gene expression levels between Th2-driven classical asthma (CA) and Th2-driven cough variant asthma (CVA) in order to investigate the pathogenesis of asthma further. Methods Clinical data were collected from asthmatic patients in the Department of Respiratory and Critical Care of Sichuan Provincial People's Hospital from June 1, 2018, to December 31, 2019. The healthy control (HC) group was healthy adults from the physical examination center. Gene expression of peripheral blood mononuclear cells (PBMCs) in the CA group, CVA group, and HC group was determined by full-length transcriptome sequencing. Differential genes were screened by GO, KEGG analysis, and protein-protein interaction (PPI) network analysis. The results of interaction network analysis were visualized by Cytoscape. Finally, the candidate genes were verified by real-time quantitative polymerase chain reaction (RT-PCR). ResultsA total of 31 patients with asthma were included in the study, including 20 patients in the CA group and 11 patients in the CVA group. According to serum total IgE > 60 IU/mL and fractional exhaled nitric oxide (FeNO) > 40 ppb as the screening condition, 9 cases of Th2-driven CA and 5 cases of Th2-driven CVA were screened for analysis. Gene expression analysis showed 300 differentially expressed genes between the Th2-driven CA group and the Th2-driven CVA group, among which 155 genes were up-regulated, and 145 were down-regulated. GO enrichment analysis showed that differential genes were mainly enriched in drug response, nitrogen compound biosynthesis, cytoplasmic matrix, protein binding, ATP binding, etc. KEGG pathway analysis showed that differential genes were mainly concentrated in 2-oxy-carboxylic acid metabolism and cytotoxic signaling pathways mediated by natural killer cells. PPI analysis revealed extensive protein interactions between different genes. Ten candidate genes were screened for RT-PCR verification and finally found that CLU, GZMB, PPBP, PRF1, PTGS1, and TMSB4X were significantly differentially expressed between the Th2-driven CA group and the Th2-driven CVA group. Conclusions Asthma's occurrence results from the interaction of many genes and pathways. CLU, GZMB, PPBP, PRF1, PTGS1, and TMSB4X genes may be essential in developing Th2-driven CVA to Th2-driven CA.
Lorenz plot (LP) method which gives a global view of long-time electrocardiogram signals, is an efficient simple visualization tool to analyze cardiac arrhythmias, and the morphologies and positions of the extracted attractors may reveal the underlying mechanisms of the onset and termination of arrhythmias. But automatic diagnosis is still impossible because it is lack of the method of extracting attractors by now. We presented here a methodology of attractor extraction and recognition based upon homogeneously statistical properties of the location parameters of scatter points in three dimensional LP (3DLP), which was constructed by three successive RR intervals as X, Y and Z axis in Cartesian coordinate system. Validation experiments were tested in a group of RR-interval time series and tags data with frequent unifocal premature complexes exported from a 24-hour Holter system. The results showed that this method had excellent effective not only on extraction of attractors, but also on automatic recognition of attractors by the location parameters such as the azimuth of the points peak frequency (APF) of eccentric attractors once stereographic projection of 3DLP along the space diagonal. Besides, APF was still a powerful index of differential diagnosis of atrial and ventricular extrasystole. Additional experiments proved that this method was also available on several other arrhythmias. Moreover, there were extremely relevant relationships between 3DLP and two dimensional LPs which indicate any conventional achievement of LPs could be implanted into 3DLP. It would have a broad application prospect to integrate this method into conventional long-time electrocardiogram monitoring and analysis system.
Heart rate variability (HRV) is the difference between the successive changes in the heartbeat cycle, and it is produced in the autonomic nervous system modulation of the sinus node of the heart. The HRV is a valuable indicator in predicting the sudden cardiac death and arrhythmic events. Traditional analysis of HRV is based on a multi-electrocardiogram (ECG), but the ECG signal acquisition is complex, so we have designed an HRV analysis system based on photoplethysmography (PPG). PPG signal is collected by a microcontroller from human’s finger, and it is sent to the terminal via USB-Serial module. The terminal software not only collects the data and plot waveforms, but also stores the data for future HRV analysis. The system is small in size, low in power consumption, and easy for operation. It is suitable for daily care no matter whether it is used at home or in a hospital.
On the basis of Poincare scatter plot and first order difference scatter plot, a novel heart rate variability (HRV) analysis method based on scatter plots of RR intervals and first order difference of RR intervals (namely, RdR) was proposed. The abscissa of the RdR scatter plot, the x-axis, is RR intervals and the ordinate, y-axis, is the difference between successive RR intervals. The RdR scatter plot includes the information of RR intervals and the difference between successive RR intervals, which captures more HRV information. By RdR scatter plot analysis of some records of MIT-BIH arrhythmias database, we found that the scatter plot of uncoupled premature ventricular contraction (PVC), coupled ventricular bigeminy and ventricular trigeminy PVC had specific graphic characteristics. The RdR scatter plot method has higher detecting performance than the Poincare scatter plot method, and simpler and more intuitive than the first order difference method.
Objective Explore the effect of remote ischemic preconditioning (RIPC) on preoperative heart rate variability in patients with heart valves. Methods From January 2022 to July 2022, screening was conducted among 118 patients based on inclusion/exclusion criteria. Fifty-eight patients were excluded, and 60 patients participated in this trial with informed consent and were randomly divided into a RIPC group (n=30) and a control group (n=30). Due to the cancellation of surgery, HRV data was missing. 7 patients in the control group were excluded, and 5 patients in the RIPC group were excluded, 23 patients in the final control group and 25 patients in the RIPC group were included in the analysis. Comparison of relevant indicators of heart rate variability (standard deviation of NN interval (SDNN), standard deviation of mean value of NN interval in every five minutes (SDANN), mean square root of difference between consecutive NN intervals (RMSSD), percentage of adjacent RR interval>50 ms (PNN50), low frequency component (LF), high frequency component (HF) and LF/HF) at 8 hours in the morning on the surgical day between two groups of patients. Results There was no statistical difference in baseline characteristics between the two groups, and there was no significant difference in heart rate variability 24 hours before intervention (P>0.05). After the intervention measures were taken, the comparison of the results of heart rate variability at 8 hours on the day of operation showed that SDNN and SDANN of patients in the RIPC group were higher than those in the control group, with statistical differences (P<0.05). Conclusion RIPC can stabilize the preoperative heart rate variability of patients undergoing cardiac valve surgery.
目的：观察卡介菌多糖核酸注射液在小儿咳嗽变异性哮喘治疗应用的疗效。方法：将本科40例咳嗽变异性哮喘患儿，随机分为治疗组和对照组(各20例)。治疗组给予BCG-PSN+必可酮气雾剂，对照组：给予单用必可酮气雾剂吸入，连续吸入6周，观察疗效，并进行统计学处理。结果：治疗组总有效率为95%，对照组总有效率为70%，统计学处理总有效率有显著差异(Plt;0.01)。结论：卡介菌多糖核酸(polysaccharide nucleic acidfraction of BCG，BCG-PSN)能有效地控制咳嗽变异性哮喘(CVA)的呼吸道的反复感染，提高免疫功能；与必可酮配合，能有效地控制CVA的复发。
Blood pressure variability (BPV) refers to the fluctuations of blood pressure in a certain period of time. In recent years, BPV is becoming a predictive marker for cardiovascular events. Given the hemodynamic and internal environmental change brought by hemodialysis as well as the complex complications, hemodialysis patients always have complex BPV. Nowadays there is no consensus on an optimal standard to evaluate BPV in hemodialysis population. Metrics usually used are as follows: blood pressure change during a certain period of time, standard deviation, coefficient of variation, variation independent of mean, average real variability, weighted mean of daytime and night-time standard deviation, residual derived from generalized linear models, and residual standard deviation. Impact factors of BPV in hemodialysis patients include age, ultrafitration volume, hemodialysis frequency and time length, peripheral vascular disease, serum calcium, antihypertensive drugs and so on. Recent studies showed significant associations between both long-term and short-term BPV with prognosis of hemodialysis patients. This review focuses on the evaluation methods, the influencing factors and the impact on prognosis of BPV.
【摘要】 目的 探讨急性脑梗死对心脏自主神经活性的影响。 方法 Wistar大鼠32只随机分为正常组、假手术组和脑梗死组，脑梗死组用线栓法行右侧大脑中动脉阻塞。脑梗死组和假手术组于术前及术后24 h作心率变异性（HRV）检测，同时检测正常组HRV，将3组的HRV指标进行比较。实验终点取各组心肌组织检测儿茶酚胺和神经肽Y（NPY），进行组间比较。 结果 术后24 h脑梗死组和正常组、假手术组相比，窦性心搏间期标准差、均方根，总功率谱、高频功率谱（HF）、低频功率谱（LF）降低，差异有统计学意义。3组比较LF/HF和分数维无明显差异。脑梗死组心肌组织去甲肾上腺素（NA）和NPY高于正常组和假手术组。 结论 脑梗死引起心脏自主神经总活性降低、自主神经功能受损，自主神经末梢去甲肾上腺素和NPY的异常分泌可能是重要的原因。【Abstract】 Objective To investigate the effect of acute cerebral infarction on cardiac autonomic nervous activity. Methods A total of 32 Wistar rats were divided into normal group, sham operation group and infarction group by random. Experimental cerebral infarction in Wistar rats was induced by intraluminal occlusion of middle cerebral artery. About 24 hours after the occlusion or 24 hours after sham operation, the heart rate variability (HRV) sequences were measured, and the HRV values in the three groups were compared. The levels of catecholamine and neuropeptide (NPY) in myocardium were measured. Results At the 24th hour after the occlusion, the standard deviation and root mean square standard deviation of R-R interval, the total power, high frequency (HF) and low frequency (LF) in infarction group were lower than those in normal and sham operation group. LF/HF and fractal dimension did not differ much among the three groups. The levels of noradrenaline and NPY in myocardium in infarction group were higher than those in the other groups. Conclusion It is suggested that acute cerebral infarction may cause the decrease of autonomic nervous activity and damage of the autonomic nervous function; the abnormal secretion of noradrenalin in autonomic nerve ending and NPY may be the important reasons.
The peak period of cardiovascular disease (CVD) is around the time of awakening in the morning, which may be related to the surge of sympathetic activity at the end of nocturnal sleep. This paper chose 140 participants as study object, 70 of which had occurred CVD events while the rest hadn’t during a two-year follow-up period. A two-layer model was proposed to investigate whether hypnopompic heart rate variability (HRV) was informative to distinguish these two types of participants. In the proposed model, the extreme gradient boosting algorithm (XGBoost) was used to construct a classifier in the first layer. By evaluating the feature importance of the classifier, those features with larger importance were fed into the second layer to construct the final classifier. Three machine learning algorithms, i.e., XGBoost, random forest and support vector machine were employed and compared in the second layer to find out which one can achieve the highest performance. The results showed that, with the analysis of hypnopompic HRV, the XGBoost+XGBoost model achieved the best performance with an accuracy of 84.3%. Compared with conventional time-domain and frequency-domain features, those features derived from nonlinear dynamic analysis were more important to the model. Especially, modified permutation entropy at scale 1 and sample entropy at scale 3 were relatively important. This study might have significance for the prevention and diagnosis of CVD, as well as for the design of CVD-risk assessment system.