Effect of High Homocysteine Level on the Severity of Coronary Heart Disease and Prognosis After Stent Implantation.

OBJECTIVES: To determine the effect of high homocysteine (HCY) levels on the severity of coronary artery disease and prognosis after stent implantation. METHODS: A prospective study was conducted on 667 patients with coronary heart disease who underwent drug-eluting stent implantation for the first time at the Department of Cardiology, Huludao Central Hospital, from January 2015 to December 2017. The patients were divided into the control and hyperhomocysteinemia (H-HCY) groups based on the serum HCY levels. The demographic and clinical characteristics of both groups were compared. In addition, the patients were followed up for 1 year to compare the incidence of major adverse cardiovascular and cerebrovascular events (MACCE). Multivariate logistic regression was used to determine the correlation between serum HCY levels and MACCE. RESULTS: Compared with the control group, the stenosis degree was significantly higher among patients in the H-Hcy group, as indicated by more coronary artery lesions (P < 0.001) and higher SYNTAX scores (P < 0.001). After 1 year of follow-up, the incidence of MACCE was also significantly higher in the H-HCY versus control group (9.5% vs. 15.1%; P = 0.042). Furthermore, age, history of diabetes, discontinuation of antiplatelet aggregation drugs, and HCY levels were independent predictors of MACCE. CONCLUSIONS: High HCY level is associated with severe coronary artery disease in patients with coronary heart disease and is an independent predictor of MACCE after stent implantation.

DrPOCS: Drug Repositioning Based on Projection Onto Convex Sets.

Drug repositioning, i.e., identifying new indications for known drugs, has attracted a lot of attentions recently and is becoming an effective strategy in drug development. In literature, several computational approaches have been proposed to identify potential indications of old drugs based on various types of data sources. In this paper, by formulating the drug-disease associations as a low-rank matrix, we propose a novel method, namely DrPOCS, to identify candidate indications of old drugs based on projection onto convex sets (POCS). With the integration of drug structure and disease phenotype information, DrPOCS predicts potential associations between drugs and diseases with matrix completion. Benchmarking results demonstrate that our proposed approach outperforms popular existing approaches with high accuracy. In addition, a number of novel predicted indications are validated with various types of evidences, indicating the predictive power of our proposed approach.

Micro-/Nanorobots Propelled by Oscillating Magnetic Fields.

Recent strides in micro- and nanomanufacturing technologies have sparked the development of micro-/nanorobots with enhanced power and functionality. Due to the advantages of on-demand motion control, long lifetime, and great biocompatibility, magnetic propelled micro-/nanorobots have exhibited considerable promise in the fields of drug delivery, biosensing, bioimaging, and environmental remediation. The magnetic fields which provide energy for propulsion can be categorized into rotating and oscillating magnetic fields. In this review, recent developments in oscillating magnetic propelled micro-/nanorobot fabrication techniques (such as electrodeposition, self-assembly, electron beam evaporation, and three-dimensional (3D) direct laser writing) are summarized. The motion mechanism of oscillating magnetic propelled micro-/nanorobots are also discussed, including wagging propulsion, surface walker propulsion, and scallop propulsion. With continuous innovation, micro-/nanorobots can become a promising candidate for future applications in the biomedical field. As a step toward designing and building such micro-/nanorobots, several types of common fabrication techniques are briefly introduced. Then, we focus on three propulsion mechanisms of micro-/nanorobots in oscillation magnetic fields: (1) wagging propulsion; (2) surface walker; and (3) scallop propulsion. Finally, a summary table is provided to compare the abilities of different micro-/nanorobots driven by oscillating magnetic fields.

[Disability appraisal for common peroneal nerve injury in traffic accidents: 8 cases analysis].

OBJECTIVE: To investigate the characteristics of forensic clinical identification on common peroneal nerve injury in traffic accident. METHODS: Eight cases of common peroneal nerve injury in traffic accidents were analyzed, including general condition of the wounded, the way of injury, the imaging results, the EMG results, and the degree of injury, etc. RESULTS: In 8 cases, 2 cases of complete common peroneal nerve injury were determined to grade 9 (disability degree) and 6 cases of partial common peroneal nerve injury were determined to grade 10 (disability degree). CONCLUSION: By comparison, the disability degree of complete common peroneal nerve injury is higher than that of partial common peroneal nerve injury. The forensic clinical identification of common peroneal nerve should be made with synthetical consideration of medical history, symptoms, and auxiliary examinations.

Fine mapping the KLK3 locus on chromosome 19q13.33 associated with prostate cancer susceptibility and PSA levels.

Measurements of serum prostate-specific antigen (PSA) protein levels form the basis for a widely used test to screen men for prostate cancer. Germline variants in the gene that encodes the PSA protein (KLK3) have been shown to be associated with both serum PSA levels and prostate cancer. Based on a resequencing analysis of a 56 kb region on chromosome 19q13.33, centered on the KLK3 gene, we fine mapped this locus by genotyping tag SNPs in 3,522 prostate cancer cases and 3,338 controls from five case-control studies. We did not observe a strong association with the KLK3 variant, reported in previous studies to confer risk for prostate cancer (rs2735839; P = 0.20) but did observe three highly correlated SNPs (rs17632542, rs62113212 and rs62113214) associated with prostate cancer [P = 3.41 × 10(-4), per-allele trend odds ratio (OR) = 0.77, 95% CI = 0.67-0.89]. The signal was apparent only for nonaggressive prostate cancer cases with Gleason score <7 and disease stage 8 or stage ≥III (P = 0.31, per-allele trend OR = 1.12, 95% CI = 0.90-1.40). One of the three highly correlated SNPs, rs17632542, introduces a non-synonymous amino acid change in the KLK3 protein with a predicted benign or neutral functional impact. Baseline PSA levels were 43.7% higher in control subjects with no minor alleles (1.61 ng/ml, 95% CI = 1.49-1.72) than in those with one or more minor alleles at any one of the three SNPs (1.12 ng/ml, 95% CI = 0.96-1.28) (P = 9.70 × 10(-5)). Together our results suggest that germline KLK3 variants could influence the diagnosis of nonaggressive prostate cancer by influencing the likelihood of biopsy.

A comprehensive resequence analysis of the KLK15-KLK3-KLK2 locus on chromosome 19q13.33.

Single nucleotide polymorphisms (SNPs) in the KLK3 gene on chromosome 19q13.33 are associated with serum prostate-specific antigen (PSA) levels. Recent genome wide association studies of prostate cancer have yielded conflicting results for association of the same SNPs with prostate cancer risk. Since the KLK3 gene encodes the PSA protein that forms the basis for a widely used screening test for prostate cancer, it is critical to fully characterize genetic variation in this region and assess its relationship with the risk of prostate cancer. We have conducted a next-generation sequence analysis in 78 individuals of European ancestry to characterize common (minor allele frequency, MAF >1%) genetic variation in a 56 kb region on chromosome 19q13.33 centered on the KLK3 gene (chr19:56,019,829-56,076,043 bps). We identified 555 polymorphic loci in the process including 116 novel SNPs and 182 novel insertion/deletion polymorphisms (indels). Based on tagging analysis, 144 loci are necessary to tag the region at an r (2) threshold of 0.8 and MAF of 1% or higher, while 86 loci are required to tag the region at an r (2) threshold of 0.8 and MAF >5%. Our sequence data augments coverage by 35 and 78% as compared to variants in dbSNP and HapMap, respectively. We observed six non-synonymous amino acid or frame shift changes in the KLK3 gene and three changes in each of the neighboring genes, KLK15 and KLK2. Our study has generated a detailed map of common genetic variation in the genomic region surrounding the KLK3 gene, which should be useful for fine-mapping the association signal as well as determining the contribution of this locus to prostate cancer risk and/or regulation of PSA expression.

[Analysis of 84 ocular disability cases in traffic accident].

OBJECTIVE: To study the injury modes, the injury characteristics, the disability grade assessments and other relative problems in eye injuries after traffic accidents. METHODS: Eighty four ocular disability cases after traffic accidents collected from March 2007 to March 2009 in our institute were retrospectively analyzed. Then to study the ocular disability reasons, the assessment time and methods. RESULTS: The main cause of ocular disability is visual dysfunction, and the other causes for example eyeball missing, injury of eyelid, injury of lacrimal apparatus, traumatic cataract and defect of visual field were rare relatively. Most ocular injuries happened to single eye. The disability grades were often from VII to X. CONCLUSION: The accuracy of visual function expertise could be improved by using some tests and visual electrophysiological measurements. The vision and ophthalmology data before the injury of the wounded who has intrinsical disease should be provided. The assessment time should be delayed for people whose visual function still may change.

Comprehensive resequence analysis of a 97 kb region of chromosome 10q11.2 containing the MSMB gene associated with prostate cancer.

Genome-wide association studies of prostate cancer have identified single nucleotide polymorphism (SNP) markers in a region of chromosome 10q11.2, harboring the microseminoprotein-ß (MSMB) gene. Both the gene product of MSMB, the prostate secretory protein 94 (PSP94) and its binding protein (PSPBP), have been previously investigated as serum biomarkers for prostate cancer progression. Recent functional work has shown that different alleles of the significantly associated SNP in the promoter of MSMB found to be associated with prostate cancer risk, rs10993994, can influence its expression in tumors and in vitro studies. Since it is plausible that additional variants in this region contribute to the risk of prostate cancer, we have used next-generation sequencing technology to resequence a ~97-kb region that includes the area surrounding MSMB (chr10: 51,168,025-51,265,101) in 36 prostate cancer cases, 26 controls of European origin, and 8 unrelated CEPH individuals in order to identify additional variants to investigate in functional studies. We identified 241 novel polymorphisms within this region, including 142 in the 51-kb block of linkage disequilibrium (LD) that contains rs10993994 and the proximal promoter of MSMB. No sites were observed to be polymorphic within the exons of MSMB.

Does diffusion kurtosis imaging lead to better neural tissue characterization? A rodent brain maturation study.

Diffusion kurtosis imaging (DKI) can be used to estimate excess kurtosis, which is a dimensionless measure for the deviation of water diffusion profile from Gaussian distribution. Several recent studies have applied DKI to probe the restricted water diffusion in biological tissues. The directional analysis has also been developed to obtain the directionally specific kurtosis. However, these studies could not directly evaluate the sensitivity of DKI in detecting subtle neural tissue alterations. Brain maturation is known to involve various biological events that can affect water diffusion properties, thus providing a sensitive platform to evaluate the efficacy of DKI. In this study, in vivo DKI experiments were performed in normal Sprague-Dawley rats of 3 different ages: postnatal days 13, 31 and 120 (N=6 for each group). Regional analysis was then performed for 4 white matter (WM) and 3 gray matter (GM) structures. Diffusivity and kurtosis estimates derived from DKI were shown to be highly sensitive to the developmental changes in these chosen structures. Conventional diffusion tensor imaging (DTI) parameters were also computed using monoexponential model, yielding reduced sensitivity and directional specificity in monitoring the brain maturation changes. These results demonstrated that, by measuring directionally specific diffusivity and kurtosis, DKI offers a more comprehensive and sensitive detection of tissue microstructural changes. Such imaging advance can provide a better MR diffusion characterization of neural tissues, both WM and GM, in normal, developmental and pathological states.

Comprehensive resequence analysis of a 136 kb region of human chromosome 8q24 associated with prostate and colon cancers.

Recently, genome-wide association studies have identified loci across a segment of chromosome 8q24 (128,100,000-128,700,000) associated with the risk of breast, colon and prostate cancers. At least three regions of 8q24 have been independently associated with prostate cancer risk; the most centromeric of which appears to be population specific. Haplotypes in two contiguous but independent loci, marked by rs6983267 and rs1447295, have been identified in the Cancer Genetic Markers of Susceptibility project ( http://cgems.cancer.gov ), which genotyped more than 5,000 prostate cancer cases and 5,000 controls of European origin. The rs6983267 locus is also strongly associated with colorectal cancer. To ascertain a comprehensive catalog of common single-nucleotide polymorphisms (SNPs) across the two regions, we conducted a resequence analysis of 136 kb (chr8: 128,473,000-128,609,802) using the Roche/454 next-generation sequencing technology in 39 prostate cancer cases and 40 controls of European origin. We have characterized a comprehensive catalog of common (MAF > 1%) SNPs within this region, including 442 novel SNPs and have determined the pattern of linkage disequilibrium across the region. Our study has generated a detailed map of genetic variation across the region, which should be useful for choosing SNPs for fine mapping of association signals in 8q24 and investigations of the functional consequences of select common variants.

Towards better MR characterization of neural tissues using directional diffusion kurtosis analysis.

MR diffusion kurtosis imaging (DKI) was proposed recently to study the deviation of water diffusion from Gaussian distribution. Mean kurtosis, the directionally averaged kurtosis, has been shown to be useful in assessing pathophysiological changes, thus yielding another dimension of information to characterize water diffusion in biological tissues. In this study, orthogonal transformation of the 4th order diffusion kurtosis tensor was introduced to compute the diffusion kurtoses along the three eigenvector directions of the 2nd order diffusion tensor. Such axial (K(//)) and radial (K( upper left and right quadrants)) kurtoses measured the kurtoses along the directions parallel and perpendicular, respectively, to the principal diffusion direction. DKI experiments were performed in normal adult (N=7) and formalin-fixed rat brains (N=5). DKI estimates were documented for various white matter (WM) and gray matter (GM) tissues, and compared with the conventional diffusion tensor estimates. The results showed that kurtosis estimates revealed different information for tissue characterization. For example, K(//) and K( upper left and right quadrants) under formalin fixation condition exhibited large and moderate increases in WM while they showed little change in GM despite the overall dramatic decrease of axial and radial diffusivities in both WM and GM. These findings indicate that directional kurtosis analysis can provide additional microstructural information in characterizing neural tissues.

Advanced MR diffusion characterization of neural tissue using directional diffusion kurtosis analysis.

MR Diffusion kurtosis imaging (DKI) was proposed recently to study the deviation of water diffusion from Gaussian distribution. Mean kurtosis (MK), directionally averaged kurtosis, has been shown to be useful in assessing pathophysilogical changes. However, MK is not sensitive to kurtosis change occurring along a specific direction. Therefore, orthogonal transformation of the 4th order kurtosis tensor was introduced in the current study to compute kurtoses along the 3 eigenvector directions of the 2nd order diffusion tensor. Such axial (K( parallel)) and radial (K perpendicular) kurtoses measured the kurtoses along the directions parallel and perpendicular, respectively, to the principal diffusion direction. DKI experiments were performed in normal adult and formalin-fixed rat brain, and developmental brains. The results showed that directional kurtosis analysis revealed different information for tissue characterization.

SNP500Cancer: a public resource for sequence validation, assay development, and frequency analysis for genetic variation in candidate genes.

The SNP500Cancer database provides sequence and genotype assay information for candidate SNPs useful in mapping complex diseases, such as cancer. The database is an integral component of the NCI Cancer Genome Anatomy Project (http://cgap.nci.nih.gov). SNP500Cancer reports sequence analysis of anonymized control DNA samples (n = 102 Coriell samples representing four self-described ethnic groups: African/African-American, Caucasian, Hispanic and Pacific Rim). The website is searchable by gene, chromosome, gene ontology pathway, dbSNP ID and SNP500Cancer SNP ID. As of October 2005, the database contains >13 400 SNPs, 9124 of which have been sequenced in the SNP500Cancer population. For each analysed SNP, gene location and >200 bp of surrounding annotated sequence (including nearby SNPs) are provided, with frequency information in total and per subpopulation as well as calculation of Hardy-Weinberg equilibrium for each subpopulation. The website provides the conditions for validated sequencing and genotyping assays, as well as genotype results for the 102 samples, in both viewable and downloadable formats. A subset of sequence validated SNPs with minor allele frequency >5% are entered into a high-throughput pipeline for genotyping analysis to determine concordance for the same 102 samples. In addition, the results of genotype analysis for select validated SNP assays (defined as 100% concordance between sequence analysis and genotype results) are posted for an additional 280 samples drawn from the Human Diversity Panel (HDP). SNP500Cancer provides an invaluable resource for investigators to select SNPs for analysis, design genotyping assays using validated sequence data, choose selected assays already validated on one or more genotyping platforms, and select reference standards for genotyping assays. The SNP500Cancer database is freely accessible via the web page at http://snp500cancer.nci.nih.gov.

A novel neural network for variational inequalities with linear and nonlinear constraints.

Variational inequality is a uniform approach for many important optimization and equilibrium problems. Based on the sufficient and necessary conditions of the solution, this paper presents a novel neural network model for solving variational inequalities with linear and nonlinear constraints. Three sufficient conditions are provided to ensure that the proposed network with an asymmetric mapping is stable in the sense of Lyapunov and converges to an exact solution of the original problem. Meanwhile, the proposed network with a gradient mapping is also proved to be stable in the sense of Lyapunov and to have a finite-time convergence under some mild condition by using a new energy function. Compared with the existing neural networks, the new model can be applied to solve some nonmonotone problems, has no adjustable parameter, and has lower complexity. Thus, the structure of the proposed network is very simple. Since the proposed network can be used to solve a broad class of optimization problems, it has great application potential. The validity and transient behavior of the proposed neural network are demonstrated by several numerical examples.

Deriving sufficient conditions for global asymptotic stability of delayed neural networks via nonsmooth analysis--II.

Following our recent approach of nonsmooth analysis, we report a new set of sufficient conditions and its implications for the global asymptotic stability of delayed cellular neural networks (DCNN). The new conditions not only unify a string of previous stability results, but also yield strict improvement over them by allowing the symmetric part of the feedback matrix positive definite, hence enlarging the application domain of DCNNs. Advantages of the new results over existing ones are illustrated with examples. We also compare our results with those related results obtained via LMI approach.

Deriving sufficient conditions for global asymptotic stability of delayed neural networks via nonsmooth analysis.

In this paper, we obtain new sufficient conditions ensuring existence, uniqueness, and global asymptotic stability (GAS) of the equilibrium point for a general class of delayed neural networks (DNNs) via nonsmooth analysis, which makes full use of the Lipschitz property of functions defining DNNs. Based on this new tool of nonsmooth analysis, we first obtain a couple of general results concerning the existence and uniqueness of the equilibrium point. Then those results are applied to show that existence assumptions on the equilibrium point in some existing sufficient conditions ensuring GAS are actually unnecessary; and some strong assumptions such as the boundedness of activation functions in some other existing sufficient conditions can be actually dropped. Finally, we derive some new sufficient conditions which are easy to check. Comparison with some related existing results is conducted and advantages are illustrated with examples. Throughout our paper, spectral properties of the matrix (A + Atau) play an important role, which is a distinguished feature from previous studies. Here, A and Atau are, respectively, the feedback and the delayed feedback matrix defining the neural network under consideration.