Molecular biomarkers of diffuse axonal injury: recent advances and future perspectives.

INTRODUCTION: Diffuse axonal injury (DAI), with high mortality and morbidity both in children and adults, is one of the most severe pathological consequences of traumatic brain injury. Currently, clinical diagnosis, disease assessment, disability identification, and postmortem diagnosis of DAI is mainly limited by the absent of specific molecular biomarkers. AREAS COVERED: In this review, we first introduce the pathophysiology of DAI, summarized the reported biomarkers in previous animal and human studies, and then the molecular biomarkers such as ß-Amyloid precursor protein, neurofilaments, S-100ß, myelin basic protein, tau protein, neuron-specific enolase, Peripherin and Hemopexin for DAI diagnosis is summarized. Finally, we put forward valuable views on the future research direction of diagnostic biomarkers of DAI. EXPERT OPINION: In recent years, the advanced technology has ultimately changed the research of DAI, and the numbers of potential molecular biomarkers was introduced in related studies. We summarized the latest updated information in such studies to provide references for future research and explore the potential pathophysiological mechanism on diffuse axonal injury.

Comparison of various chemometric methods on visible and near-infrared spectral analysis for wood density prediction among different tree species and geographical origins.

Visible and near-infrared (Vis-NIR) spectroscopy has been widely applied in many fields for the qualitative and quantitative analysis. Chemometric techniques including pre-processing, variable selection, and multivariate calibration models play an important role to better extract useful information from spectral data. In this study, a new de-noising method (lifting wavelet transform, LWT), four variable selection methods, as well as two non-linear machine learning models were simultaneously analyzed to compare the impact of chemometric approaches on wood density determination among various tree species and geographical locations. In addition, fruit fly optimization algorithm (FOA) and response surface methodology (RSM) were employed to optimize the parameters of generalized regression neural network (GRNN) and particle swarm optimization-support vector machine (PSO-SVM), respectively. As for various chemometric methods, the optimal chemometric method was different for the same tree species collected from different locations. FOA-GRNN model combined with LWT and CARS deliver the best performance for Chinese white poplar of Heilongjiang province. In contrast, PLS model showed a good performance for Chinese white poplar collected from Jilin province based on raw spectra. However, for other tree species, RSM-PSO-SVM models can improve the performance of wood density prediction compared to traditional linear and FOA-GRNN models. Especially for Acer mono Maxim, when compared to linear models, the coefficient of determination of prediction set ( R p 2 ) and relative prediction deviation (RPD) were increased by 47.70% and 44.48%, respectively. And the dimensionality of Vis-NIR spectral data was decreased from 2048 to 20. Therefore, the appropriate chemometric technique should be selected before building calibration models.

New Diagnostic Model for the Differentiation of Diabetic Nephropathy From Non-Diabetic Nephropathy in Chinese Patients.

Background: The disease pathology for diabetes mellitus patients with chronic kidney disease (CKD) may be diabetic nephropathy (DN), non-diabetic renal disease (NDRD), or DN combined with NDRD. Considering that the prognosis and treatment of DN and NDRD differ, their differential diagnosis is of significance. Renal pathological biopsy is the gold standard for diagnosing DN and NDRD. However, it is invasive and cannot be implemented in many patients due to contraindications. This article constructed a new noninvasive evaluation model for differentiating DN and NDRD. Methods: We retrospectively screened 1,030 patients with type 2 diabetes who has undergone kidney biopsy from January 2005 to March 2017 in a single center. Variables were ranked according to importance, and the machine learning methods (random forest, RF, and support vector machine, SVM) were then used to construct the model. The final model was validated with an external group (338 patients, April 2017-April 2019). Results: In total, 929 patients were assigned. Ten variables were selected for model development. The areas under the receiver operating characteristic curves (AUCROCs) for the RF and SVM methods were 0.953 and 0.947, respectively. Additionally, 329 patients were analyzed for external validation. The AUCROCs for the external validation of the RF and SVM methods were 0.920 and 0.911, respectively. Conclusion: We successfully constructed a predictive model for DN and NDRD using machine learning methods, which were better than our regression methods. Clinical Trial Registration: ClinicalTrial.gov, NCT03865914.

Comprehensive growth index monitoring of desert steppe grassland vegetation based on UAV hyperspectral.

The goal of this study was to establish a comprehensive growth index (CGI) of grassland vegetation for monitor the overall condition of the grassland. Taking the desert grassland in Otuoke Banner, Ordos City, Inner Mongolia as the research object, this study integrates five indicators. First, the optimal band of the unmanned aerial vehicle hyperspectral data is optimized using the correlation analysis, successive projection algorithm (SPA), optimum index factor method, and band combination index method. A dual-band spectral index in good correlation with the CGI is then constructed in the optimal band. Afterwards, a CGI characterization model is established in accordance with the partial least squares regression (PLSR) algorithm and its accuracy is analyzed. Finally, the CGI of the study area is estimated. The experimental results are as follows. 1) The R2 of models built using the training samples of the spectral indices corresponding to the optimal spectra screened by the SPA method was 0.7835, RMSE was 0.0712, and RE was 6.89%, less than 10%. The R2 of the Validation samples was 0.7698, RMSE was 0.0471, and RE was 6.36%, less than 10%, highest precision. 2) Models were built using the spectral indices corresponding to the optimal spectra screened by the SPA method, and the CGI mean values were inverted. A comparison of the mean measured CGI values of the sample quadrat of the test area showed that the mean relative error was 3.82%. The results show that the vegetation growth of desert-steppe grasslands can be adequately monitored, providing technical support for the rapid and accurate diagnosis of grassland conditions. However, there are still shortcomings in this study. 1) The research area for this study was mainly in the desert steppe in Otuoke Banner, Ordos, hence the relevance and universality of the findings need to be verified, and subsequent experiments need to be carried out on desert steppes in other regions or even other types of grasslands to test the universality of the model. 2) In this study, the influence of soil background and litter on the spectral reflectance is not considered in depth. In addition, the influence of sensor observation angle and solar elevation angle on the inversion model demands further investigation efforts.

Risk assessment of type 2 diabetes in northern China based on the logistic regression model.

BACKGROUND: Type 2 diabetes mellitus (T2DM) is a complex disease with high incidence and serious harm associated with polygenic determination. This study aimed to develop a predictive model so as to assess the risk of T2DM and apply it to health care and disease prevention in northern China. OBJECTIVE: Based on genotyping results, a risk warning model for type 2 diabetes was established. METHODS: Blood samples of 1042 patients with T2DM in northern China were collected. Multiplex polymerase chain reaction and high-throughput sequencing (NGS) techniques were used to design the amplification-based targeted sequencing panel to sequence the 21 T2DM susceptibility genes. RESULT: The related key gene KQT-like subfamily member 1 played an important role in the T2DM risk model, and single-nucleotide polymorphism rs2237892 was highly significant, with a P value of 1.2 × 10-5. CONCLUSIONS: Susceptibility genes in different populations were examined, and a model was developed to assess the risk-based genetic analysis. The performance of the model reached 92.8%.

Sap flow of Salix psammophila and its principal influencing factors at different slope positions in the Mu Us desert.

The changes in sap flow of Salix psammophila growing on a gentle slope (lower slope, P1), a middle slope (P2), and an upper slope (P3), and the response of sap flow to meteorological factors at the different slope positions were studied using the continuous and synchronized observations, the instrument were wrapped stem flowmeter EMS 62 sap-flow heat-balance-based system and the LSI-LASTEM automatic weather station. The results revealed that the soil moisture content was the highest and the growth conditions of Salix psammophila were the best at P1, followed by P2. At P3, however, although good apical dominance was observed, the proportion of dead branches was the highest. Furthermore, the daily variation patterns of sap flow on the three slopes presented as multi-peak bell-shaped curves. The daily accumulation changes in sap flow showed a trend of P1 > P3 > P2, and within the same diameter range, the sap flow at P1 was significantly different from that at P2 and P3, whereas the sap flow at P2 and P3 did not vary significantly. All the three slopes showed a significant and positive correlation with photosynthetically active radiation, atmospheric temperature, and vapor pressure difference, and a significant and negative correlation with relative humidity; however, the degrees of correlation varied slightly. The stepwise regression analysis showed that, at different slopes, different variables were selected for different branch diameters, but photosynthetically active radiation and atmospheric temperature played dominant roles on all slopes. This study reveals the sap flow pattern of Salix psammophila on different slopes and its response mechanism to meteorological factors, which was essential for understanding the restoration ability, physiological adaptability, and ecosystem stability of Salix psammophila communities.

Risk HLA class II alleles and amino acid residues in myeloperoxidase-ANCA-associated vasculitis.

A genome-wide association study (GWAS) indicated that myeloperoxidase-ANCA associated vasculitis (AAV) is associated with HLA-DQ. However, susceptibility alleles in these loci have been under-investigated. Here we genotyped 258 Chinese patients with myeloperoxidase-AAV and 597 healthy control individuals at HLA DRB1, DQA1, DQB1 and DPB1, and extracted the encoded amino acid sequences from the IMGT/HLA database. The replication cohort included 97 cases and 107 controls. T cell epitopes of myeloperoxidase were predicted and docked to the HLA molecules. We found DQA1∗0302 (odds ratio 2.34 (95% confidence interval 1.75-3.14)) and DQB1∗0303 (odds ratio 1.89 (1.45-2.48)) were risk alleles for myeloperoxidase-AAV. They are in overt linkage disequilibrium (r2 0.69) and the haplotype DQA1∗0302-DQB1∗0303 presents a significant risk (haplotype score 6.39) as well. Aspartate160 on the DQ α chain (odds ratio 2.06 (1.60-2.67)), encoded by DQA1∗0302, and isoleucine185 on the DQ ß chain (odds ratio 1.73 (1.38-2.18)), encoded by DQB1∗0303, both located in the α2ß2 domains, conferred significant risk for myeloperoxidase-AAV. Homologous modeling showed that DQα∗160D may confer susceptibility to myeloperoxidase-AAV by altering dimerization of the HLA molecules. Thus, more attention should be paid to the roles of amino acids in the α2ß2 domains in addition to the α1ß1 binding groove of HLA class II molecules.

HLA class II alleles differing by a single amino acid associate with clinical phenotype and outcome in patients with primary membranous nephropathy.

Genome-wide associations and HLA genotyping have revealed associations between HLA alleles and susceptibility to primary membranous nephropathy. However, associations with clinical phenotypes and kidney outcome are poorly defined. We previously identified DRB1*1501 and DRB1*0301 as independent risk alleles for primary membranous nephropathy. Here, we investigated HLA associations with demographic characteristics, anti-phospholipase A2 receptor (PLA2R) antibody, treatment response and kidney outcome after a median follow-up of 52 months in 258 patients. DRB1*0301, but not DRB1*1501, was associated with a significantly higher level of PLA2R antibody (odds ratio 1.58, 95% confidence interval 1.13-2.22). Although DRB1*1502, which differs from DRB1*1501 by a single amino acid, was not a risk allele for primary membranous nephropathy (odds ratio 1.01), it was associated with significantly lower estimated glomerular filtration rates both at baseline (1.79, 1.18-2.72) and at last follow-up (1.72, 1.17-2.53), a significantly worse renal outcome by Kaplan-Meier analysis and a significantly higher risk of end-stage renal disease by Cox regression analysis (hazard ratio 4.52, 1.22-16.74). Nevertheless, the absence of remission remained the only independent risk factor for end-stage renal disease by multivariate analysis. DRB1*1502 was also associated with a significantly higher median PLA2R antibody level [161.4 vs. 36.3 U/mL] and showed interaction with DRB1*0301 for this variable. Thus, HLA genes control PLA2R antibody production and primary membranous nephropathy severity and outcome. Additionally, DRB1*1502 behaves like a modifier gene with a strong predictor value when associated with HLA risk alleles. Other modifier genes need further investigations in larger cohorts.

Risk-Predicting Model for Incident of Essential Hypertension Based on Environmental and Genetic Factors with Support Vector Machine.

Essential hypertension (EH) has become a major chronic disease around the world. To build a risk-predicting model for EH can help to interpose people's lifestyle and dietary habit to decrease the risk of getting EH. In this study, we constructed a EH risk-predicting model considering both environmental and genetic factors with support vector machine (SVM). The data were collected through Epidemiological investigation questionnaire from Beijing Chinese Han population. After data cleaning, we finally selected 9 environmental factors and 12 genetic factors to construct the predicting model based on 1200 samples, including 559 essential hypertension patients and 641 controls. Using radial basis kernel function, predictive accuracy via SVM with function with only environmental factor and only genetic factor were 72.8 and 54.4%, respectively; after considering both environmental and genetic factor the accuracy improved to 76.3%. Using the model via SVM with Laplacian function, the accuracy with only environmental factor and only genetic factor were 76.9 and 57.7%, respectively; after combining environmental and genetic factor, the accuracy improved to 80.1%. The predictive accuracy of SVM model constructed based on Laplacian function was higher than radial basis kernel function, as well as sensitivity and specificity, which were 63.3 and 86.7%, respectively. In conclusion, the model based on SVM with Laplacian kernel function had better performance in predicting risk of hypertension. And SVM model considering both environmental and genetic factors had better performance than the model with environmental or genetic factors only.

The susceptible HLA class II alleles and their presenting epitope(s) in Goodpasture's disease.

Goodpasture's disease is closely associated with HLA, particularly DRB1*1501. Other susceptible or protective HLA alleles are not clearly elucidated. The presentation models of epitopes by susceptible HLA alleles are also unclear. We genotyped 140 Chinese patients and 599 controls for four-digit HLA II genes, and extracted the encoding sequences from the IMGT/HLA database. T-cell epitopes of α3(IV)NC1 were predicted and the structures of DR molecule-peptide-T-cell receptor were constructed. We confirmed DRB1*1501 (OR = 4·6, P = 5·7 × 10-28 ) to be a risk allele for Goodpasture's disease. Arginine at position 13 (ARG13) (OR = 4·0, P = 1·0 × 10-17 ) and proline at position 11 (PRO11) (OR = 4·0, P = 2·0 × 10-17 ) on DRß1, encoded by DRB1*1501, were associated with disease susceptibility. α134-148 (HGWISLWKGFSFIMF) was predicted as a T-cell epitope presented by DRB1*1501. Isoleucine137 , tryptophan140 , glycine142 , phenylalanine143 and phenylalanine145 , were presented in peptide-binding pockets 1, 4, 6, 7 and 9 of DR2b, respectively. ARG13 in pocket 4 interacts with tryptophan140 and forms a hydrogen bond. In conclusion, we propose a mechanism for DRB1*1501 susceptibility for Goodpasture's disease through encoding ARG13 and PRO11 on MHC-DRß1 chain and presenting T-cell epitope, α134-148 , with five critical residues.

MHC Class II Risk Alleles and Amino Acid Residues in Idiopathic Membranous Nephropathy.

Epitopes of phospholipase A2 receptor (PLA2R), the target antigen in idiopathic membranous nephropathy (iMN), must be presented by the HLA-encoded MHC class II molecules to stimulate autoantibody production. A genome-wide association study identified risk alleles at HLA and PLA2R loci, with the top variant rs2187668 within HLA-DQA1 showing a risk effect greater than that of the top variant rs4664308 within PLA2R1. How the HLA risk alleles affect epitope presentation by MHC class II molecules in iMN is unknown. Here, we genotyped 261 patients with iMN and 599 healthy controls at the HLA-DRB1, HLA-DQA1, HLA-DQB1, and HLA-DPB1 loci with four-digit resolution and extracted the encoded amino acid sequences from the IMGT/HLA database. We predicted T cell epitopes of PLA2R and constructed MHC-DR molecule-PLA2R peptide-T cell receptor structures using Modeler. We identified DRB1*1501 (odds ratio, 4.65; 95% confidence interval [95% CI], 3.39 to 6.41; P<0.001) and DRB1*0301 (odds ratio, 3.96; 95% CI, 2.61 to 6.05; P<0.001) as independent risk alleles for iMN and associated with circulating anti-PLA2R antibodies. Strong gene-gene interaction was noted between rs4664308(AA) and HLA-DRB1*1501/DRB1*0301. Amino acid positions 13 (P<0.001) and 71 (P<0.001) in the MHC-DRß1 chain independently associated with iMN. Structural models showed that arginine13 and alanine71, encoded by DRB1*1501, and lysine71, encoded by DRB1*0301, facilitate interactions with T cell epitopes of PLA2R. In conclusion, we identified two risk alleles of HLA class II genes and three amino acid residues on positions 13 and 71 of the MHC-DRß1 chain that may confer susceptibility to iMN by presenting T cell epitopes on PLA2R.

Optimization of the genotyping-by-sequencing strategy for population genomic analysis in conifers.

Flexibility and low cost make genotyping-by-sequencing (GBS) an ideal tool for population genomic studies of nonmodel species. However, to utilize the potential of the method fully, many parameters affecting library quality and single nucleotide polymorphism (SNP) discovery require optimization, especially for conifer genomes with a high repetitive DNA content. In this study, we explored strategies for effective GBS analysis in pine species. We constructed GBS libraries using HpaII, PstI and EcoRI-MseI digestions with different multiplexing levels and examined the effect of restriction enzymes on library complexity and the impact of sequencing depth and size selection of restriction fragments on sequence coverage bias. We tested and compared UNEAK, Stacks and GATK pipelines for the GBS data, and then developed a reference-free SNP calling strategy for haploid pine genomes. Our GBS procedure proved to be effective in SNP discovery, producing 7000-11 000 and 14 751 SNPs within and among three pine species, respectively, from a PstI library. This investigation provides guidance for the design and analysis of GBS experiments, particularly for organisms for which genomic information is lacking.

Cyclosporine A-nanoparticles enhance the therapeutic benefit of adipose tissue-derived stem cell transplantation in a swine myocardial infarction model.

Treatment of myocardial infarction (MI) with adipose-derived stem cells (ASCs) has produced promising results. Cyclosporine A (CsA) inhibits apoptosis by preventing the opening of mitochondrial permeability transition pores. A CsA nanoparticle emulsion (CsA-NP) has lower toxicity and higher efficiency as compared to CsA. In this study, we hypothesized that a combination of ASCs and CsA-NP would enhance the therapeutic efficiency in a swine MI model. MI was induced in pig hearts by occlusion of the left anterior descending artery. The animals that survived MI were divided into four groups and 1 week later received intracoronary ASCs (ASCs, n=6), intracoronary culture media in combination with CsA-NP (CsA-NP, n=6), intracoronary ASCs in combination with CsA-NP (ASCs + CsA-NP, n=6), or remained untreated (control, n=4). Animals were sacrificed 8 weeks later and were evaluated for cardiac function by delayed-enhanced magnetic resonance imaging and immunohistopathology. We observed that the left ventricular ejection fraction (LVEF) was significantly increased in the ASCs + CsA-NP group, compared to the CsA-NP group (53.6%±2.4% versus 48.6%±1.5%, P,0.05), and the ASCs group (53.6%±2.4% versus 48.3%±1.8%, P,0.05). More importantly, the infarct size was significantly smaller in the ASCs + CsA-NP group as compared to the CsA-NP group (6.2±1.7 cm(3) versus 9.1±3.4 cm(3), P,0.05) and the ASCs group (6.2±1.7 cm(3) versus 7.5±0.6 cm(3), P,0.05). These findings were further confirmed by analysis of the expression of cardiomyocyte markers, myosin heavy chain (α-actinin) and troponin T. In addition, the CsA-NP + ASCs treatment promoted neovascularization (P,0.05) and inhibited cardiomyocyte apoptosis (P,0.01) compared to the control group. This study demonstrates that CsA-NP enhanced the therapeutic benefits of ASCs transplantation for MI.

[Strategies of genome-wide association study based on high-throughput sequencing].

Genome-wide association studies (GWASs) have been playing an important role on human complex diseases. Generally speaking, GWAS tries to detect the relationship between genome-wide genetic variants and measurable traits in the population level. Although fruitful, array-based GWASs still exist some problems, for example, the so-called missing heritability--significantly associated SNPs can only explain a small part of phenotypic variation. Other problems include that, in some traits, significantly associated SNPs in one study are hard to be repeated by other studies; and that the functions of significantly associated SNPs are often difficult to interpret. High-throughput sequencing, also known as next-generation sequencing (NGS), could be one of the most promising technologies to solve those problems by quickly producing accurate variations in a high-throughput way. NGS-based GWASs (NGS-GWAS), to some extent, provide a better solution compared with traditional array-based GWASs. We systematically review the strategies and methods for NGS-GWASs, pick out the most feasible and efficient strategies and methods for NGS-GWASs, and discuss their applications in personalized medicine.

[Pretreatment with cyclosporin A nanoparticles emulsion protects apoptosis of swine adipose tissue-derived stem cells].

OBJECTIVE: To investigate the effect of cyclosporine A-nanoparticles emulsion (CsA-NP) on protecting apoptosis of swine adipose tissue-derived stem cells (ASC ) and related mechanisms. METHODS: ASC were randomized to six groups: control group,single H2O2 group,CsA or CsA-NP 0.1 mg/ml+H2O2 group,CsA or CsA-NP 1.0 mg/ml+H2O2 group, CsA or CsA-NP 5.0 mg/ml+H2O2 group,CsA or CsA-NP 10.0 mg/ml+H2O2 group. ASC apoptosis was induced by hydrogen peroxide (H2O2100 µmol/L) in vitro. The morphology of apoptotic cells was observed and the number of apoptotic cells was measured. Apoptosis of ASC was detected by flow cytometry using an apoptosis kit. Cell activity was determined by CCK-8 assay. Caspase-3 activity was detected by applying a caspase-3 assay kit. Expression of cytochrome C was investigated by Western blot. RESULTS: H2O2 induced ASC apoptosis was evidenced by morphological and biochemical changes,which could be significantly reduced by pre-treatment with CsA or CsA-NP at concentration of 0.1-10.0 mg/ml, and the best effect was observed at concentration of 5 mg/ml (apoptosis rate: CsA: 10.6% ± 2.8% vs. 25.2% ± 3.8%; CsA-NP: 6.2% ± 2.6% vs. 25.2% ± 3.6% in control group, all P < 0.01). The cell activity was significantly higher in CsA or CsA-NP pre-treated ASC at concentration of 0.1-10.0 mg/ml than in H2O2 group (P < 0.01). Pre-treatment with CsA or CsA-NP (0.1-10.0 mg/ml) significantly down -regulated caspase-3 activity. Furthermore, CsA or CsA-NP (5 mg/ml) completely inhibited the H2O2-induced release of cytochrome C. CONCLUSIONS: These results suggest that CsA-NP and CsA could protect the oxidative stress-induced ASC apoptosis through decreasing the activation of caspase-3 and inhibiting the release of cytochrome C.

[Efficacy of cyclosporine A-nanoparticles emulsion combined with stem cell transplantation therapy for acute myocardial infarction].

OBJECTIVE: To evaluate the efficacy of cyclosporine A-nanoparticles emulsion (CsA-NP) combined with adipose tissue-derived stem cells (ASCs)transplantation therapy for acute myocardial infarction (AMI) in a miniswine model. METHODS: CsA-NP emulsion was prepared by the high-pressure homogenization method. Models were performed by coronary angioplasty for percutaneous balloon occlusion of left anterior descending artery (LAD). A total of 17 miniswines survived after AMI were divided into four groups: control group (n=5), CsA-NP group (n=4), ASCs group (n=4), and CsA-NP+ASCs group (n=4). ASCs or saline were delivered by intracoronary injection one week after AMI.Before cell transplantation and 8 weeks after cell transplantation, delayed-enhanced magnetic resonance imaging (DE-MRI) was performed to evaluate cardiac function and viability. The infarcted myocardium and implanted cells were histologically studied. RESULTS: Eight weeks after treatment, the left ventricular ejection fraction (LVEF)significantly increased in the CsA-NP+ASCs group when compared with the ASCs group [(53.6 ± 2.4)% vs. (48.3 ± 1.8)%, P<0.05]; meanwhile, the infarct size significantly decreased [(6.2 ± 1.7)cm(3) vs.(7.5 ± 0.6) cm(3), P<0.05] and the thickness of the ventricular wall significantly increased (P<0.05). Histology showed that the number of surviving cells increased nearly by three times in the CsA-NP+ASCs group, and the expressions of the cardiomyocyte specific markers (cTnT and α-actin) were detected. Histological samples also showed that CsA-NP+ASCs group reduced fibrotic tissue, and down-regulated the activation of Caspase-3. CONCLUSION: The CsA-NP+ASCs combination therapy can enhance the viability of ASCs by improving LVEF and preventing LV expansion, which may be explained that CsA-NP has the anti-apoptotic effect and can promote the survivals and proliferation of ASCs.

[Delayed-enhanced magnetic resonance imaging for assessing a minipig myocardial infarction model established by percutaneous balloon occlusion].

OBJECTIVE: To assess a minipig model of acute myocardial infarction (AMI) established by percutaneous balloon occlusion using delayed-enhanced magnetic resonance imaging (DE-MRI). METHODS: A minipig model of AMI was established by placement of a 2.0 mm×15.0 mm percutaneous transluminal coronary angioplasty balloon in the middle left anterior descending artery (LAD) through a percutaneous femoral puncture in the right inguinal region. The left anterior descending coronary artery (LAD) was occluded for 90 min, followed by assessment of the infarct size and cardiac function with DE-MRI, and the results were confirmed by pathological examination. RESULTS: DE-MRI showed a mean infarcts size of 10.2∓2.9 cm3 in the minipig models. Compared to the control group, the minipigs with AMI had significantly increased end-diastolic and end-systolic volumes (P<0.05) with a decreased stroke volume, ejection fraction and cardiac output (P<0.001). These DE-MRI values were matched with the microsphere values obtained from short-axis slices in pathological examination. CONCLUSION: We have established a feasible approach for evaluating minipig models of AMI as a platform for assessing the therapeutic effect of stem cell transplantation for AMI.

Secular trends in the etiology and comorbidity of hospitalized patients with congestive heart failure: A single-center retrospective study.

OBJECTIVE: To assess the secular trends in the etiology and comorbidity of patients hospitalized with congestive heart failure (CHF). METHODS: Data of 7,319 patients (mean age 59.6 years, 62.1% male) with a primary discharge diagnosis of CHF, hospitalized from January 1, 1993 to December 31, 2007 at the Chinese People's Liberation Army (PLA) General Hospital were extracted and analyzed. These patients were divided into three groups according to hospitalization period: 1993-1997 (n = 1623), 1998-2002 (n = 2444), and 2003-2007 (n = 3252). The etiological characteristics and comorbidities were assessed. RESULTS: Over the study period, the proportion of patients with ischemic heart disease (IHD) increased from 37.2% during the period 1993-1997 to 46.8% during the period 2003-2007, while that with valvular heart disease (VHD) decreased from 35.2% during the period 1993-1997 to 16.6% during the period 2003-2007 (both P < 0.05). Atrial fibrillation (AF) was the most common comorbidity of heart failure (23.2%, 23.0% and 20.6%, respectively, in the three periods). Compared to that of the period of 1993-1997 with that of, the proportion of patients with myocardial infarction, pneumonia, renal function impairment and hepatic cirrhosis of the period of 2003-2007 increased significantly (P < 0.05) and the proportion of patients with chronic obstructive pulmonary disease and atrial fibrillation decreased significantly (P < 0.05). CONCLUSIONS: This study implies that IHD has became a more common etiology of CHF, while VHD has deceased as an etiology of CHF in Chinese patients during the last two decades.

[Fifteen-year evolving trends of etiology and prognosis in hospitalized patients with heart failure].

OBJECTIVE: To investigate the etiological and prognostic changes of hospitalized patients with chronic heart failure. METHODS: This retrospective study analyzed 7319 hospitalized patients (male 62.07%) with validated primary discharge diagnosis of chronic heart failure in Chinese PLA General Hospital in Beijing from January 1, 1993 to December 31, 2007. Etiological characteristics, comorbidities and 30-day hospitalized mortality in the following three periods: 1993 - 1997 (n = 1623), 1998 - 2002 (n = 2444), and 2003 - 2007 (n = 3252) were compared. RESULTS: (1) The patient age increased [(56.0 ± 17.5) years, (57.8 ± 17.6) years and (62.7 ± 15.5) years, P < 0.01] and hospital stay time decreased [(31.3 ± 17.4) days, (22.7 ± 14.1) days and (20.1 ± 15.2) days, P < 0.01] from 1993 to 2007. (2) The common causes of heart failure were coronary heart disease, hypertension, rheumatic valvular heart disease and diabetes mellitus. From 1993 - 1998 to 2003 - 2007, the proportion of patients with coronary heart disease, hypertension and diabetes mellitus rose from 37.2%, 23.3% and 12.3% to 46.8%, 46.7% and 21.1%, respectively (all P < 0.05). Meanwhile the proportion of patients with rheumatic valvular heart disease fell from 35.2% to 16.6% (P < 0.05). (3) The main etiologies and comorbidities were atrial fibrillation, myocardial infarction, pneumonia, chronic obstructive pulmonary disease and renal failure. From 1993 - 1998 to 2003 - 2007, atrial fibrillation was the most common cause of heart failure, and the rate of myocardial infarction, pneumonia and renal failure rose from 11.0%, 8.9% and 5.2% to 14.7%, 14.5% and 9.1%, respectively (all P < 0.05) and the rate of COPD fell from 12.9% to 8.4% (P < 0.05). (4) The 30-day hospitalized mortalities in the three periods were 7.0%, 4.5% and 5.1%, respectively, and the mortalities in the 1998 - 2002 and 2003 - 2007 periods were lower than those of in the 1993 - 1998 period (all P < 0.05). The mortality related to coronary heart disease decreased significantly from 1993 to 2007 (9.3%, 5.0% and 3.8% in the three periods, respectively, P < 0.05). CONCLUSIONS: It is demonstrated that the primary diseases causing heart failure were coronary heart disease, hypertension, diabetes mellitus and rheumatic valvular heart disease, and the former three diseases exhibited a upward trend and the later one exhibited a downward trend. Moreover, the proportion of comorbidities in patients with heart failure increased over the study period. The 30-day hospital mortality exhibited a downward trend and decreased significantly in patients with coronary heart disease or myocardial infarction.

Prediction of nucleosome DNA formation potential and nucleosome positioning using increment of diversity combined with quadratic discriminant analysis.

In this work, a novel method was developed to distinguish nucleosome DNA and linker DNA based on increment of diversity combined with quadratic discriminant analysis (IDQD), using k-mer frequency of nucleotides in genome. When used to predict DNA potential for forming nucleosomes, the model achieved a high accuracy of 94.94%, 77.60%, and 86.81%, respectively, for Saccharomyces cerevisiae, Homo sapiens, and Drosophila melanogaster. The area under the receiver operator characteristics curve of our classifier was 0.982 for S. cerevisiae. Our results indicate that DNA sequence preference is critical for nucleosome formation potential and is likely conserved across eukaryotes. The model successfully identified nucleosome-enriched or nucleosome-depleted regions in S. cerevisiae genome, suggesting nucleosome positioning depends on DNA sequence preference. Thus, IDQD classifier is useful for predicting nucleosome positioning.