Classification of coronary artery disease using radial artery pulse wave analysis via machine learning.

BACKGROUND: Coronary artery disease (CAD) is a major global cardiovascular health threat and the leading cause of death in many countries. The disease has a significant impact in China, where it has become the leading cause of death. There is an urgent need to develop non-invasive, rapid, cost-effective, and reliable techniques for the early detection of CAD using machine learning (ML). METHODS: Six hundred eight participants were divided into three groups: healthy, hypertensive, and CAD. The raw data of pulse wave from those participants was collected. The data were de-noised, normalized, and analyzed using several applications. Seven ML classifiers were used to model the processed data, including Decision Tree (DT), Random Forest (RF), Gradient Boosting Decision Tree (GBDT), Extra Trees (ET), Extreme Gradient Boosting (XGBoost), Light Gradient Boosting (LightGBM), and Unbiased Boosting with Categorical Features (CatBoost). RESULTS: The Extra Trees classifier demonstrated the best classification performance. After tunning, the results performance evaluation on test set are: 0.8579 accuracy, 0.9361 AUC, 0.8561 recall, 0.8581 precision, 0.8571 F1 score, 0.7859 kappa coefficient, and 0.7867 MCC. The top 10 feature importances of ET model are w/t1, t3/tmax, tmax, t3/t1, As, hf/3, tf/3/tmax, tf/5, w and tf/3/t1. CONCLUSION: Radial artery pulse wave can be used to identify healthy, hypertensive and CAD participants by using Extra Trees Classifier. This method provides a potential pathway to recognize CAD patients by using a simple, non-invasive, and cost-effective technique.

Status and prospect of international standardization of TCM diagnosis.

The present study aimed to review the current status and development of international standards in the domain of traditional Chinese medicine (TCM) diagnosis. Moreover, the roles and relevant work of different organizations in developing such standards were explored, and the difficulties and challenges encountered were analyzed. The study further elaborated on the approaches to establish a complete set of international standards on TCM diagnosis. It also provided a promising solution for the development of international standards on TCM diagnosis.

[Material basis and molecular mechanism of Dachengqi Decoction in treatment of acute pancreatitis based on network pharmacology].

The network pharmacology was used to investigate the material basis and molecular mechanism of Dachengqi Decoction(DCQD) in the treatment of acute pancreatitis(AP). Potential targets of components from DCQD and relevant pathogenic genes of AP were identified through database retrieval. Then, crucial targets were verified with relevant active chemical components via molecular docking. DAVID database was used to explore the functions and pathways involved in the treatment of AP. A total of 108 components were correlated with 28 targets. Molecular docking showed a strong binding ability of key targets and their corresponding compounds. DAVID enrichment analysis showed 438 biological process, 31 molecular functions, 17 cellular components and 96 KEGG pathways. DCQD may achieve its pharmacological effects through anti-inflammatory and anti-oxidative effects, negative regulation of apoptosis and regulation of pancreatic secretion, involving multiple signals, such as IL-17, TNF and NF-κB signaling pathway. In this study, it is the first time to use the method of network pharmacology to reveal the molecular mechanism of DCQD in the treatment of AP by multiple components and multi-signaling pathways, which provides a basis for further biological experiments of AP.

Ethylene responses in rice roots and coleoptiles are differentially regulated by a carotenoid isomerase-mediated abscisic acid pathway.

Ethylene and abscisic acid (ABA) act synergistically or antagonistically to regulate plant growth and development. ABA is derived from the carotenoid biosynthesis pathway. Here, we analyzed the interplay among ethylene, carotenoid biogenesis, and ABA in rice (Oryza sativa) using the rice ethylene response mutant mhz5, which displays a reduced ethylene response in roots but an enhanced ethylene response in coleoptiles. We found that MHZ5 encodes a carotenoid isomerase and that the mutation in mhz5 blocks carotenoid biosynthesis, reduces ABA accumulation, and promotes ethylene production in etiolated seedlings. ABA can largely rescue the ethylene response of the mhz5 mutant. Ethylene induces MHZ5 expression, the production of neoxanthin, an ABA biosynthesis precursor, and ABA accumulation in roots. MHZ5 overexpression results in enhanced ethylene sensitivity in roots and reduced ethylene sensitivity in coleoptiles. Mutation or overexpression of MHZ5 also alters the expression of ethylene-responsive genes. Genetic studies revealed that the MHZ5-mediated ABA pathway acts downstream of ethylene signaling to inhibit root growth. The MHZ5-mediated ABA pathway likely acts upstream but negatively regulates ethylene signaling to control coleoptile growth. Our study reveals novel interactions among ethylene, carotenogenesis, and ABA and provides insight into improvements in agronomic traits and adaptive growth through the manipulation of these pathways in rice.

Immune-related long noncoding RNA zinc finger protein 710-AS1-201 promotes the metastasis and invasion of gastric cancer cells.

BACKGROUND: Gastric cancer (GC) is a prevalent malignant tumor of the gastrointestinal system. ZNF710 is a transcription factor (TF), and zinc finger protein 710 (ZNF710)-AS1-201 is an immune-related long noncoding RNA (lncRNA) that is upregulated in GC cells. AIM: To assess the correlation between ZNF710-AS1-201 and immune microenvironment features and to investigate the roles of ZNF710-AS1-201 in the invasion and metastasis processes of GC cells. METHODS: We obtained data from The Cancer Genome Atlas and Wujin Hospital. We assessed cell growth, migration, invasion, and programmed cell death using cell counting kit-8, EdU, scratch, Transwell, and flow cytometry assays. Quantitative real-time polymerase chain reaction (qRT-PCR) was used to identify the potential downstream targets of ZNF710-AS1-201. RESULTS: In GC tissues with low ZNF710-AS1-201 expression, immunoassays detected significant infiltration of various antitumor immune cells, such as memory CD8 T cells and activated CD4 T cells. In the low-expression group, the half-maximal inhibitory concentrations (IC50s) of 5-fluorouracil, cisplatin, gemcitabine, and trametinib were lower, whereas the IC50s of dasatinib and vorinostat were higher. The malignant degree of GC was higher and the stage was later in the high-expression group. Additionally, patients with high expression of ZNF710-AS1-201 had lower overall survival and disease-free survival rates. In vitro, the overexpression of ZNF710-AS1-201 greatly enhanced growth, metastasis, and infiltration while suppressing cell death in HGC-27 cells. In contrast, the reduced expression of ZNF710-AS1-201 greatly hindered cell growth, enhanced apoptosis, and suppressed the metastasis and invasion of MKN-45 cells. The expression changes in ZNF710 were significant, but the corresponding changes in isocitrate dehydrogenase-2, Semaphorin 4B, ARHGAP10, RGMB, hsa-miR-93-5p, and ZNF710-AS1-202 were not consistent or statistically significant after overexpression or knockdown of ZNF710-AS1-201, as determined by qRT-PCR. CONCLUSION: Immune-related lncRNA ZNF710-AS1-201 facilitates the metastasis and invasion of GC cells. It appears that ZNF710-AS1-201 and ZNF710 have potential as effective targets for therapeutic intervention in GC. Nevertheless, it is still necessary to determine the specific targets of the ZNF710 TF.

Metabolic markers and microecological characteristics of tongue coating in patients with chronic gastritis.

BACKGROUND: In Traditional Chinese Medicine (TCM), tongue diagnosis has been an important diagnostic method for the last 3000 years. Tongue diagnosis is a non-invasive, simple and valuable diagnostic tool. TCM treats the tongue coating on a very sensitive scale that reflects physiological and pathological changes in the organs, especially the spleen and stomach. Tongue coating can diagnose disease severity and determine the TCM syndrome ("Zheng" in Chinese). The biological bases of different tongue coating appearances are still poorly understood and lack systematic investigation at the molecular level. METHODS: Tongue coating samples were collected from 70 chronic gastritis patients and 20 normal controls. 16S rRNA denatured gradient gel electrophoresis (16S rRNA-DGGE) and liquid chromatography and mass spectrometry (LC-MS) were designed to profile tongue coatings. The statistical techniques used were principal component analysis and partial least squares-discriminate analysis. RESULTS: Ten potential metabolites or markers were found in chronic gastritis patients, including UDP-D-galactose, 3-ketolactose, and vitamin D2, based on LC-MS. Eight significantly different strips were observed in samples from chronic gastritis patients based on 16S rRNA-DGGE. Two strips, Strips 8 and 10, were selected for gene sequencing. Strip 10 sequencing showed a 100% similarity to Rothia mucilaginosa. Strip 8 sequencing showed a 96.2% similarity to Moraxella catarrhalis. CONCLUSIONS: Changes in glucose metabolism could possibly form the basis of tongue coating conformation in chronic gastritis patients. The study revealed important connections between metabolic components, microecological components and tongue coating in chronic gastritis patients. Compared with other diagnostic regimens, such as blood tests or tissue biopsies, tongue coating is more amenable to, and more convenient for, both patients and doctors.

A novel method for assessing cardiac function in patients with coronary heart disease based on wrist pulse analysis.

BACKGROUND: The timely assessment of B-type natriuretic peptide (BNP) marking chronic heart failure risk in patients with coronary heart disease (CHD) helps to reduce patients' mortality. OBJECTIVE: To evaluate the potential of wrist pulse signals for use in the cardiac monitoring of patients with CHD. METHODS: A total of 419 patients with CHD were assigned to Group 1 (BNP < 95 pg/mL, n = 249), 2 (95 < BNP < 221 pg/mL, n = 85), and 3 (BNP > 221 pg/mL, n = 85) according to BNP levels. Wrist pulse signals were measured noninvasively. Both the time-domain method and multiscale entropy (MSE) method were used to extract pulse features. Decision tree (DT) and random forest (RF) algorithms were employed to construct models for classifying three groups, and the models' performance metrics were compared. RESULTS: The pulse features of the three groups differed significantly, suggesting different pathological states of the cardiovascular system in patients with CHD. Moreover, the RF models outperformed the DT models in performance metrics. Furthermore, the optimal RF model was that based on a dataset comprising both time-domain and MSE features, achieving accuracy, average precision, average recall, and average F1-score of 90.900%, 91.048%, 90.900%, and 90.897%, respectively. CONCLUSIONS: The wrist pulse detection technology employed in this study is useful for assessing the cardiac function of patients with CHD.

Association study of ACE polymorphisms and systemic lupus erythematosus in Northern Chinese Han population.

Systemic lupus erythematosus (SLE) is an autoimmune disease, with multiple genetic and environmental factors involving in its etiology. Angiotensin converting enzyme (ACE) gene was reported to have important roles in the development and progression of SLE. In this study, a case-control study was carried out to investigate the effects of seven SNPs and I/D in ACE gene in the development of SLE in Northern China. Seven SNPs including A5466C, T3892C, A240T, C1237T, G2215A, A2350G and C3409T were genotyped by PCR-RFLP method, and I/D was examined by agarose gel electrophoresis followed PCR directly. 314 SLE patients were compared to 320 normal controls in the study. Data were analyzed by SPSS 13.0 and HaploView software. The frequency distribution of SNP A2350G and Alu I/D and five haplotypes (AAAACCCI, AGAACCTD, AAAATCTI, TAAATTTI and TAAATCTI) were demonstrated to be different between case and control groups significantly. Whereas other SNPs and haplotypes had no differences in two cohorts. The results revealed that variations of ACE gene had association with SLE, which indicated ACE gene may play an important role in pathogenesis of SLE in Northern Chinese Han population.

CpG oligodeoxynucleotides discriminately enhance binding capacity of human naïve B cells to Hepatitis B virus epitopes.

CpG oligodeoxynucleotides (CpG ODN) have the potential to enhance the antigen-presenting cells function of human naïve B cells. In this study, we aim to define the effect of CpG ODNs on the binding capacity of human naïve B cells for different Hepatitis B virus (HBV) epitopes. Three HLA-A2 restricted epitopes were selected to incubate with CpG ODN-primed human naïve B cells. Binding capacity for each epitope and expression of CD80, CD86, class I major histocompatibility complex (MHC), and class II MHC of naïve B cells was tested, respectively, by flow cytometry. CpG ODNs, especially ODN 2216, enhanced the binding capacity of human naïve B cells for HBV epitopes (p < 0.01), and induced markedly higher expression of CD80, CD86, class I MHC, and class II MHC. The binding capacity of CpG-treated naive B cells for each epitope was significantly different. In all the 3 subjects, CpG ODN 2216-primed naïve B cells showed the highest binding ability for Env172-180 compared with the other epitopes with a high expression of co-stimulatory and MHC molecules. CpG ODN showed the potential to selectively enhance the binding capacity of human naïve B cells for HBV epitopes. These results suggest new strategies for development of vaccine design.

Application of multilabel learning using the relevant feature for each label in chronic gastritis syndrome diagnosis.

Background. In Traditional Chinese Medicine (TCM), most of the algorithms are used to solve problems of syndrome diagnosis that only focus on one syndrome, that is, single label learning. However, in clinical practice, patients may simultaneously have more than one syndrome, which has its own symptoms (signs). Methods. We employed a multilabel learning using the relevant feature for each label (REAL) algorithm to construct a syndrome diagnostic model for chronic gastritis (CG) in TCM. REAL combines feature selection methods to select the significant symptoms (signs) of CG. The method was tested on 919 patients using the standard scale. Results. The highest prediction accuracy was achieved when 20 features were selected. The features selected with the information gain were more consistent with the TCM theory. The lowest average accuracy was 54% using multi-label neural networks (BP-MLL), whereas the highest was 82% using REAL for constructing the diagnostic model. For coverage, hamming loss, and ranking loss, the values obtained using the REAL algorithm were the lowest at 0.160, 0.142, and 0.177, respectively. Conclusion. REAL extracts the relevant symptoms (signs) for each syndrome and improves its recognition accuracy. Moreover, the studies will provide a reference for constructing syndrome diagnostic models and guide clinical practice.

Nonlinear Analysis of Auscultation Signals in TCM Using the Combination of Wavelet Packet Transform and Sample Entropy.

Auscultation signals are nonstationary in nature. Wavelet packet transform (WPT) has currently become a very useful tool in analyzing nonstationary signals. Sample entropy (SampEn) has recently been proposed to act as a measurement for quantifying regularity and complexity of time series data. WPT and SampEn were combined in this paper to analyze auscultation signals in traditional Chinese medicine (TCM). SampEns for WPT coefficients were computed to quantify the signals from qi- and yin-deficient, as well as healthy, subjects. The complexity of the signal can be evaluated with this scheme in different time-frequency resolutions. First, the voice signals were decomposed into approximated and detailed WPT coefficients. Then, SampEn values for approximated and detailed coefficients were calculated. Finally, SampEn values with significant differences in the three kinds of samples were chosen as the feature parameters for the support vector machine to identify the three types of auscultation signals. The recognition accuracy rates were higher than 90%.

[Metabolite changes in the greasy tongue coating of patients with chronic gastritis].

OBJECTIVE: To explore the changes in metabolites in the greasy tongue coating in patients with chronic gastritis. METHODS: Forty chronic gastritis patients presenting with greasy tongue coating, 30 chronic gastritis patients presenting with non-greasy tongue coating, and 20 healthy control persons presenting with light red tongues and thin white coating were enrolled, and the tongue coating was detected by combining artificial diagnosis and the Z-BOX Tongue Digital Analyzer's diagnosis. Samples of all the tongue coatings were collected before treatment. The metabolic fingerprinting of the tongue coating samples was obtained using ultra-performance liquid chromatography and mass spectrometry (UPLC-MS), and the metabolic components in the tongue coating samples were detected. After this, principal component analysis, partial least squares discriminant analysis and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to identify potential metabolic markers. Finally, the components were identified using the Chemspider and HMDB searching. RESULTS: UPLC-MS results were analyzed by OPLS-DA and showed that the metabolites among the three groups were distributed in different regions. The different potential metabolic markers between the patients with or without greasy coating were 3-ketolactose, 2-deoxy-D-ribose, UDP-D-galactose metarhodopsin, ascorbate, picolinate and histidine. The different potential metabolic markers between the greasy coating group and the normal group were 3-ketolactose, UDP-D-galactose, leukotriene A4 and vitamin D(2). CONCLUSION: The metabolites of the greasy coating group, the non-greasy coating group and the normal group show significant differences in energy metabolism, mainly of glucose metabolism. This demonstrated that glucose metabolism may be one of the mechanisms leading to the formation of greasy coating.

Current status and advances of immunotherapy in nasopharyngeal carcinoma.

The general immune landscape of nasopharyngeal carcinoma (NPC) renders immunotherapy suitable for patients with NPC. Immune checkpoint inhibitors (ICIs) based on programmed death-1/programmed death ligand-1 (PD-1/PD-L1) blockade have made a breakthrough with the approval of PD-1 inhibitor for refractory recurrence and/or metastatic (R/M NPC) and the approval of PD-1 inhibitor in combination with gemcitabine and cisplatin as first line for R/M NPC in 2021 in China. The incorporation of ICIs into the treatment paradigms of NPC has become a clinical hot spot and many prospective clinical studies are ongoing. In this review, we provide a comprehensive overview of the rationale for immunotherapy in NPC and current status, advances and challenges of immunotherapy in NPC based on published clinical data, and ongoing trials. We focus on the clinical application and advances of PD-1 inhibitor monotherapy and its combination with chemotherapy and summarize the clinical explorations of other immunotherapy approaches, for example, combination of PD-1/PD-L1 inhibitors with antiangiogenic inhibitor with molecular targeted agents, cancer vaccines, adaptive immunotherapy, and new ICI agents beyond PD-1/PD-L1 inhibitors in R/M NPC. We also describe the clinical studies' status and challenges of ICIs-based immunomodulatory strategies in local advanced NPC and pay attention to the biomarker application for personalized immunotherapy of NPC in the hope to provide insights for clinical practice and future clinical studies.

Characteristics of Pulse Parameters in Patients with Polycystic Ovary Syndrome Varied at Different Body Mass Index Levels.

Objective: To analyze the characteristics of pulse graph parameters in patients with polycystic ovary syndrome (PCOS) varied at different body mass index (BMI) levels and to provide pulse diagnosis basis for syndrome differentiation and treatment of PCOS. Methods: Pulse graph parameters of 152 patients with PCOS (26 lean patients, 63 patients with moderate weight, and 63 overweight patients) were measured by a Z-BOX pulse meter, and the pulse graph parameters of patients with PCOS varied at different BMI levels were analyzed. Results: Fine pulse, slippery pulse, and string-like pulse were the most common pulse conditions in patients with PCOS. The common pulse conditions of patients with PCOS varied at different BMI levels. The order of pulse conditions was as follows: lean group: fine pulse > string-like pulse > slippery pulse; moderate group: fine pulse > slippery pulse > string-like pulse; and overweight group: slippery pulse > fine pulse > sunken pulse. Compared to the overweight group, the pulse graph parameters h1, h3, h4, h5, h4/h1, As, and Ad increased in the moderate group (P < 0.05), and the parameters h1, h3, and Ad increased (P < 0.05) and the parameter t1 decreased (P < 0.05) in the lean group. Conclusion: Pulse graph parameters among patients with PCOS varied at different BMI levels, which can probably provide pulse diagnosis basis for syndrome differentiation and treatment of PCOS by traditional Chinese medicine (TCM).

Association of Plasma Epstein-Barr Virus DNA With Outcomes for Patients With Recurrent or Metastatic Nasopharyngeal Carcinoma Receiving Anti-Programmed Cell Death 1 Immunotherapy.

IMPORTANCE: Anti-programmed cell death 1 (anti-PD-1) immunotherapy features a durable response and improved survival in a small subset of patients with recurrent or metastatic nasopharyngeal carcinoma (RM-NPC). The association between plasma Epstein-Barr virus (EBV) DNA titer dynamics and efficacy of anti-PD-1 monotherapy has been reported, while its value in predicting long-term outcomes and monitoring disease progression is unclear for patients with RM-NPC who are receiving anti-PD-1 monotherapy. OBJECTIVE: To evaluate the role of plasma EBV DNA titers in prognosis prediction and surveillance of disease progression for patients with RM-NPC who are receiving anti-PD-1 monotherapy. DESIGN, SETTING, AND PARTICIPANTS: Patients with RM-NPC from the POLARIS-02 prospective clinical trial, the largest cohort to receive anti-PD-1 monotherapy, were included in this study. From December 22, 2016, to February 19, 2019, 17 participating centers in China screened 279 patients with RM-NPC; 190 patients were enrolled and followed up until February 19, 2020. Plasma EBV DNA was detected before treatment and every 4 weeks until disease progression. MAIN OUTCOMES AND MEASURES: Plasma EBV DNA as a predictor for progression-free survival (PFS), overall survival (OS), durable clinical benefit (defined as PFS of ≥6 months), and disease progression. RESULTS: Of 179 patients with RM-NPC receiving anti-PD-1 therapy, 148 (82.7%) were men, and the median age was 46 years (range, 22-71 years). A higher baseline EBV DNA titer was associated with shorter median OS (hazard ratio, 1.88; 95% CI, 1.22-2.89; P = .004). Patients with a ratio of the EBV DNA titer at week 4 to that at baseline (W4 to baseline ratio) greater than 0.5 had shorter median OS (hazard ratio, 2.18; 95% CI, 1.30-3.65; P < .001) than those with a W4 to baseline ratio of 0.5 or less. Patients with higher baseline EBV DNA titers had a lower durable clinical benefit rate than those with lower baseline EBV DNA titers (19 of 97 [19.6%] vs 27 of 71 [38.0%]; P = .01). Similarly, patients with a W4 to baseline ratio greater than 0.5 had a lower durable clinical benefit rate than those with a W4 to baseline ratio of 0.5 or less (9 of 86 [10.5%] vs 32 of 54 [59.3%]; P < .001). In addition, a significant EBV DNA titer increase was present at a median of 2.6 months (IQR, 0.9-4.5 months) prior to radiographic progression. CONCLUSIONS AND RELEVANCE: This study of plasma EBV DNA in patients with RM-NPC who are receiving anti-PD-1 monotherapy suggests that plasma EBV DNA could be a useful biomarker for outcomes and monitoring disease progression.

[Study of traditional Chinese medicine pulse signals in patients with coronary heart disease based on recurrence quantification analysis].

OBJECTIVE: By using recurrence quantification analysis (RQA) to analyze traditional Chinese medicine pulse signals of patients with coronary heart disease (CHD), this study aims to find nonlinear dynamic parameters of pulses to distinguish patients with CHD from normal subjects. METHODS: First, pulse signals were collected using ZBOX-I pulse digitization gathering analyzer from October 2007 to June 2008. RQA was used to analyze RQA parameters of pulses of 63 patients with CHD and 61 normal subjects. RQA parameters included recurrence rate (RR), determinism (DET), averaged diagonal length (L), entropy of diagonal length (ENTR), length of longest diagonal line (L(max)), laminarity (LAM), trapping time (TT) and length of longest vertical line (V(max)). Then, rank-sum test and BoxPlot were employed to find significant difference and distribution of RQA parameters. Lastly, receiver operating characteristic (ROC) curves were used to assess the diagnostic value of the measurements with significant difference. RESULTS: There were significant differences in RQA parameters of pulse signals between the two groups, including RR, DET, L, ENTR, LAM, TT and V(max), and their areas under the ROC curves were 1.000, 0.898, 0.653, 0.673, 0.885, 0.898, 0.986 and 0.994, respectively. CONCLUSION: Compared with the normal subjects, the pulse signals of the patients with CHD are presented with more certainty, regularity and stability. RQA measurements of RR, TT, Vmax, DET and LAM show good diagnostic value according to their ROC curves.

Identifying Coronary Artery Lesions by Feature Analysis of Radial Pulse Wave: A Case-Control Study.

BACKGROUND: Cardiovascular diseases have been always the most common cause of morbidity and mortality worldwide. Health monitoring of high-risk and suspected patients is essential. Currently, invasive coronary angiography is still the most direct and accurate method of determining the severity of coronary artery lesions, but it may not be the optimal clinical choice for suspected patients who had clinical symptoms of coronary heart disease (CHD) such as chest pain but no coronary artery lesion. Modern medical research indicates that radial pulse waves contain substantial pathophysiologic information about the cardiovascular and circulation systems; therefore, analysis of these waves could be a noninvasive technique for assessing cardiovascular disease. OBJECTIVE: The objective of this study was to analyze the radial pulse wave to construct models for assessing the extent of coronary artery lesions based on pulse features and investigate the latent value of noninvasive detection technology based on pulse wave in the evaluation of cardiovascular disease, so as to promote the development of wearable devices and mobile medicine. METHOD: This study included 529 patients suspected of CHD who had undergone coronary angiography. Patients were sorted into a control group with no lesions, a 1 or 2 lesion group, and a multiple (3 or more) lesion group as determined by coronary angiography. The linear time-domain features and the nonlinear multiscale entropy features of their radial pulse wave signals were compared, and these features were used to construct models for identifying the range of coronary artery lesions using the k-nearest neighbor (KNN), decision tree (DT), and random forest (RF) machine learning algorithms. The average precision of these algorithms was then compared. RESULTS: (1) Compared with the control group, the group with 1 or 2 lesions had increases in their radial pulse wave time-domain features H2/H1, H3/H1, and W2 (P < 0.05), whereas the group with multiple lesions had decreases in MSE1, MSE2, MSE3, MSE4, and MSE5 (P < 0.05). (2) Compared with the 1 or 2 lesion group, the multiple lesion group had increases in T1/T (P < 0.05) and decreases in T and W1 (P < 0.05). (3) The RF model for identifying numbers of coronary artery lesions had a higher average precision than the models built with KNN or DT. Furthermore, average precision of the model was highest (80.98%) if both time-domain features and multiscale entropy features of radial pulse signals were used to construct the model. CONCLUSION: Pulse wave signal can identify the range of coronary artery lesions with acceptable accuracy; this result is promising valuable for assessing the severity of coronary artery lesions. The technique could be used to development of mobile medical treatments or remote home monitoring systems for patients suspected or those at high risk of coronary atherosclerotic heart disease.

The redox switch: dynamic regulation of protein function by cysteine modifications.

Reactive oxygen intermediates (ROIs) and reactive nitrogen intermediates (RNIs) have now become well established as important signalling molecules in physiological settings within microorganisms, mammals and plants. These intermediates are routinely synthesised in a highly controlled and transient fashion by NADPH-dependent enzymes, which constitute key regulators of redox signalling. Mild oxidants such as hydrogen peroxide (H(2)O(2)) and especially nitric oxide (NO) signal through chemical reactions with specific atoms of target proteins that result in covalent protein modifications. Specifically, highly reactive cysteine (Cys) residues of low pK(a) are a major site of action for these intermediates. The oxidation of target Cys residues can result in a number of distinct redox-based, post-translational modifications including S-nitrosylation, S-glutathionylation; and sulphenic acid, sulphinic acid and disulphide formation. Importantly, such modifications precisely regulate protein structure and function. Cys-based redox switches are now increasingly being found to underpin many different signalling systems and regulate physiological outputs across kingdoms.

Modelling of inquiry diagnosis for coronary heart disease in Traditional Chinese Medicine by using multi-label learning.

BACKGROUND: Coronary heart disease (CHD) is a common cardiovascular disease that is extremely harmful to humans. In Traditional Chinese Medicine (TCM), the diagnosis and treatment of CHD have a long history and ample experience. However, the non-standard inquiry information influences the diagnosis and treatment in TCM to a certain extent. In this paper, we study the standardization of inquiry information in the diagnosis of CHD and design a diagnostic model to provide methodological reference for the construction of quantization diagnosis for syndromes of CHD. In the diagnosis of CHD in TCM, there could be several patterns of syndromes for one patient, while the conventional single label data mining techniques could only build one model at a time. Here a novel multi-label learning (MLL) technique is explored to solve this problem. METHODS: Standardization scale on inquiry diagnosis for CHD in TCM is designed, and the inquiry diagnostic model is constructed based on collected data by the MLL techniques. In this study, one popular MLL algorithm, ML-kNN, is compared with other two MLL algorithms RankSVM and BPMLL as well as one commonly used single learning algorithm, k-nearest neighbour (kNN) algorithm. Furthermore the influence of symptom selection to the diagnostic model is investigated. After the symptoms are removed by their frequency from low to high; the diagnostic models are constructed on the remained symptom subsets. RESULTS: A total of 555 cases are collected for the modelling of inquiry diagnosis of CHD. The patients are diagnosed clinically by fusing inspection, pulse feeling, palpation and the standardized inquiry information. Models of six syndromes are constructed by ML-kNN, RankSVM, BPMLL and kNN, whose mean results of accuracy of diagnosis reach 77%, 71%, 75% and 74% respectively. After removing symptoms of low frequencies, the mean accuracy results of modelling by ML-kNN, RankSVM, BPMLL and kNN reach 78%, 73%, 75% and 76% when 52 symptoms are remained. CONCLUSIONS: The novel MLL techniques facilitate building standardized inquiry models in CHD diagnosis and show a practical approach to solve the problem of labelling multi-syndromes simultaneously.

Conditioned medium from renal tubular epithelial cells stimulated by hypoxia influences rat bone marrow-derived endothelial progenitor cells.

BACKGROUND AND AIMS: It has been well documented that endothelial progenitor cells (EPCs) participate in neovascularization in adults and that rarefaction of peritubular capillaries (PTCs) is closely associated with progressive kidney disease. Therefore, we investigated whether EPCs were influenced by conditioned medium (CM) of renal tubular epithelial cells (RTECs) stimulated by hypoxia, to provide evidence for EPCs transplantation in vivo in the future. METHODS: Mononuclear cells of rat bone marrow were isolated by density gradient centrifugation and were cultured according to previously described techniques. RTECs were cultured primarily with routine tissue block adhering wall method. In addition, CM was harvested from RTECs cultivated for 48 h in 5% O(2). EPCs proliferation and migration were evaluated by MTT [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide] assay and transwell. The protein and mRNA expression of stromal cell-derived factor (SDF-1), vascular endothelial growth factor (VEGF), angiogenin 1 (Ang-1), and C-X-C chemokine receptor 4 (CXCR4) was separately assessed by Western blot, enzyme-linked immunosorbent assay (ELISA), and reverse transcriptase-polymerase chain reaction (RT-PCR) methods. RESULTS: We showed that hypoxia increased the expression of SDF-1 and VEGF in RTEC. In addition, hypoxic CM improved proliferation, migration, and expression of VEGF, Ang-1, and CXCR4 of EPCs. CONCLUSIONS: These results suggest that hypoxic CM improves neovascularization of EPCs and may also be considered as therapeutic agents to supply the potent origin of reconstituion of PTCs of progressive kidney disease.