Chi-square analysis of the reduction of ATP levels in L-02 hepatocytes by hexavalent chromium

This study explored the reduction of adenosine triphosphate (ATP) levels in L-02 hepatocytes by hexavalent chromium (Cr(VI)) using chi-square analysis. Cells were treated with 2, 4, 8, 16, or 32 μM Cr(VI) for 12, 24, or 36 h. Methyl thiazolyl tetrazolium (MTT) experiments and measurements of intracellular ATP levels were performed by spectrophotometry or bioluminescence assays following Cr(VI) treatment. The chi-square test was used to determine the difference between cell survival rate and ATP levels. For the chi-square analysis, the results of the MTT or ATP experiments were transformed into a relative ratio with respect to the control (%). The relative ATP levels increased at 12 h, decreased at 24 h, and increased slightly again at 36 h following 4, 8, 16, 32 μM Cr(VI) treatment, corresponding to a "V-shaped" curve. Furthermore, the results of the chi-square analysis demonstrated a significant difference of the ATP level in the 32-μM Cr(VI) group (P < 0.05). The results suggest that the chi-square test can be applied to analyze the interference effects of Cr(VI) on ATP levels in L-02 hepatocytes. The decreased ATP levels at 24 h indicated disruption of mitochondrial energy metabolism and the slight increase of ATP levels at 36 h indicated partial recovery of mitochondrial function or activated glycolysis in L-02 hepatocytes.

Genetic analysis of the ELOVL6 gene polymorphism associated with type 2 diabetes mellitus

Recent animal studies have indicated that overexpression of the elongation of long-chain fatty acids family member 6 (Elovl6) gene can cause insulin resistance and β-cell dysfunction. These are the major factors involved in the development of type 2 diabetes mellitus (T2DM). To identify the relationship between single nucleotide polymorphisms (SNP) ofELOVL6 and T2DM pathogenesis, we conducted a case-control study of 610 Han Chinese individuals (328 newly diagnosed T2DM and 282 healthy subjects). Insulin resistance and islet first-phase secretion function were evaluated by assessment of insulin resistance in a homeostasis model (HOMA-IR) and an arginine stimulation test. Three SNPs of the ELOVL6 gene were genotyped with polymerase chain reaction-restriction fragment length polymorphism, with DNA sequencing used to confirm the results. Only genotypes TT and CT of the ELOVL6 SNP rs12504538 were detected in the samples. Genotype CC was not observed. The T2DM group had a higher frequency of the C allele and the CT genotype than the control group. Subjects with the CT genotype had higher HOMA-IR values than those with the TT genotype. In addition, no statistical significance was observed between the genotype and allele frequencies of the control and T2DM groups for SNPs rs17041272 and rs6824447. The study indicated that the ELOVL6 gene polymorphism rs12504538 is associated with an increased risk of T2DM, because it causes an increase in insulin resistance.

Diastolic function is associated with quality of life and exercise capacity in stable heart failure patients with reduced ejection fraction

Exercise capacity and quality of life (QOL) are important outcome predictors in patients with systolic heart failure (HF), independent of left ventricular (LV) ejection fraction (LVEF). LV diastolic function has been shown to be a better predictor of aerobic exercise capacity in patients with systolic dysfunction and a New York Heart Association (NYHA) classification ≥II. We hypothesized that the currently used index of diastolic function E/e' is associated with exercise capacity and QOL, even in optimally treated HF patients with reduced LVEF. This prospective study included 44 consecutive patients aged 55±11 years (27 men and 17 women), with LVEF<0.50 and NYHA functional class I-III, receiving optimal pharmacological treatment and in a stable clinical condition, as shown by the absence of dyspnea exacerbation for at least 3 months. All patients had conventional transthoracic echocardiography and answered the Minnesota Living with HF Questionnaire, followed by the 6-min walk test (6MWT). In a multivariable model with 6MWT as the dependent variable, age and E/e' explained 27% of the walked distance in 6MWT (P=0.002; multivariate regression analysis). No association was found between walk distance and LVEF or mitral annulus systolic velocity. Only normalized left atrium volume, a sensitive index of diastolic function, was associated with decreased QOL. Despite the small number of patients included, this study offers evidence that diastolic function is associated with physical capacity and QOL and should be considered along with ejection fraction in patients with compensated systolic HF.

Transduction motif analysis of gastric cancer based on a human signaling network

To investigate signal regulation models of gastric cancer, databases and literature were used to construct the signaling network in humans. Topological characteristics of the network were analyzed by CytoScape. After marking gastric cancer-related genes extracted from the CancerResource, GeneRIF, and COSMIC databases, the FANMOD software was used for the mining of gastric cancer-related motifs in a network with three vertices. The significant motif difference method was adopted to identify significantly different motifs in the normal and cancer states. Finally, we conducted a series of analyses of the significantly different motifs, including gene ontology, function annotation of genes, and model classification. A human signaling network was constructed, with 1643 nodes and 5089 regulating interactions. The network was configured to have the characteristics of other biological networks. There were 57,942 motifs marked with gastric cancer-related genes out of a total of 69,492 motifs, and 264 motifs were selected as significantly different motifs by calculating the significant motif difference (SMD) scores. Genes in significantly different motifs were mainly enriched in functions associated with cancer genesis, such as regulation of cell death, amino acid phosphorylation of proteins, and intracellular signaling cascades. The top five significantly different motifs were mainly cascade and positive feedback types. Almost all genes in the five motifs were cancer related, including EPOR,MAPK14, BCL2L1, KRT18,PTPN6, CASP3, TGFBR2,AR, and CASP7. The development of cancer might be curbed by inhibiting signal transductions upstream and downstream of the selected motifs.

Bioinformatics analysis of biomarkers and transcriptional factor motifs in Down syndrome

In this study, biomarkers and transcriptional factor motifs were identified in order to investigate the etiology and phenotypic severity of Down syndrome. GSE 1281, GSE 1611, and GSE 5390 were downloaded from the gene expression ominibus (GEO). A robust multiarray analysis (RMA) algorithm was applied to detect differentially expressed genes (DEGs). In order to screen for biological pathways and to interrogate the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database, the database for annotation, visualization, and integrated discovery (DAVID) was used to carry out a gene ontology (GO) function enrichment for DEGs. Finally, a transcriptional regulatory network was constructed, and a hypergeometric distribution test was applied to select for significantly enriched transcriptional factor motifs. CBR1, DYRK1A, HMGN1, ITSN1, RCAN1, SON, TMEM50B, and TTC3 were each up-regulated two-fold in Down syndrome samples compared to normal samples; of these, SON and TTC3 were newly reported. CBR1, DYRK1A, HMGN1, ITSN1, RCAN1, SON, TMEM50B, and TTC3 were located on human chromosome 21 (mouse chromosome 16). The DEGs were significantly enriched in macromolecular complex subunit organization and focal adhesion pathways. Eleven significantly enriched transcription factor motifs (PAX5, EGR1, XBP1, SREBP1, OLF1, MZF1, NFY, NFKAPPAB, MYCMAX, NFE2, and RP58) were identified. The DEGs and transcription factor motifs identified in our study provide biomarkers for the understanding of Down syndrome pathogenesis and progression.

Relationship between pulmonary function and indoor air pollution from coal combustion among adult residents in an inner-city area of southwest China

Few studies evaluate the amount of particulate matter less than 2.5 mm in diameter (PM2.5) in relation to a change in lung function among adults in a population. The aim of this study was to assess the association of coal as a domestic energy source to pulmonary function in an adult population in inner-city areas of Zunyi city in China where coal use is common. In a cross-sectional study of 104 households, pulmonary function measurements were assessed and compared in 110 coal users and 121 non-coal users (≥18 years old) who were all nonsmokers. Several sociodemographic factors were assessed by questionnaire, and ventilatory function measurements including forced vital capacity (FVC), forced expiratory volume in 1 s (FEV1), the FEV1/FVC ratio, and peak expiratory flow rate (PEFR) were compared between the 2 groups. The amount of PM2.5 was also measured in all residences. There was a significant increase in the relative concentration of PM2.5 in the indoor kitchens and living rooms of the coal-exposed group compared to the non-coal-exposed group. In multivariate analysis, current exposure to coal smoke was associated with a 31.7% decrease in FVC, a 42.0% decrease in FEV1, a 7.46% decrease in the FEV1/FVC ratio, and a 23.1% decrease in PEFR in adult residents. The slope of lung function decrease for Chinese adults is approximately a 2-L decrease in FVC, a 3-L decrease in FEV1, and an 8 L/s decrease in PEFR per count per minute of PM2.5 exposure. These results demonstrate the harmful effects of indoor air pollution from coal smoke on the lung function of adult residents and emphasize the need for public health efforts to decrease exposure to coal smoke.

Correlation between heart rate variability and pulmonary function adjusted by confounding factors in healthy adults

The autonomic nervous system maintains homeostasis, which is the state of balance in the body. That balance can be determined simply and noninvasively by evaluating heart rate variability (HRV). However, independently of autonomic control of the heart, HRV can be influenced by other factors, such as respiratory parameters. Little is known about the relationship between HRV and spirometric indices. In this study, our objective was to determine whether HRV correlates with spirometric indices in adults without cardiopulmonary disease, considering the main confounders (e.g., smoking and physical inactivity). In a sample of 119 asymptomatic adults (age 20-80 years), we evaluated forced vital capacity (FVC) and forced expiratory volume in 1 s (FEV1). We evaluated resting HRV indices within a 5-min window in the middle of a 10-min recording period, thereafter analyzing time and frequency domains. To evaluate daily physical activity, we instructed participants to use a triaxial accelerometer for 7 days. Physical inactivity was defined as <150 min/week of moderate to intense physical activity. We found that FVC and FEV1, respectively, correlated significantly with the following aspects of the RR interval: standard deviation of the RR intervals (r =0.31 and 0.35), low-frequency component (r =0.38 and 0.40), and Poincaré plot SD2 (r =0.34 and 0.36). Multivariate regression analysis, adjusted for age, sex, smoking, physical inactivity, and cardiovascular risk, identified the SD2 and dyslipidemia as independent predictors of FVC and FEV1 (R2=0.125 and 0.180, respectively, for both). We conclude that pulmonary function is influenced by autonomic control of cardiovascular function, independently of the main confounders.

Morphometric analysis of feedforward pathways from the primary somatosensory area (S1) of rats

We used biotinylated dextran amine (BDA) to anterogradely label individual axons projecting from primary somatosensory cortex (S1) to four different cortical areas in rats. A major goal was to determine whether axon terminals in these target areas shared morphometric similarities based on the shape of individual terminal arbors and the density of two bouton types: en passant (Bp) and terminaux (Bt). Evidence from tridimensional reconstructions of isolated axon terminal fragments (n=111) did support a degree of morphological heterogeneity establishing two broad groups of axon terminals. Morphological parameters associated with the complexity of terminal arbors and the proportion of beaded Bp vs stalked Bt were found to differ significantly in these two groups following a discriminant function statistical analysis across axon fragments. Interestingly, both groups occurred in all four target areas, possibly consistent with a commonality of presynaptic processing of tactile information. These findings lay the ground for additional work aiming to investigate synaptic function at the single bouton level and see how this might be associated with emerging properties in postsynaptic targets.

Effects of Obesity and Weight Loss Following Bariatric Surgery on Brain Function, Structural Integrity and Metabolism

Obesity is one of the key challenges to health care system worldwide and its prevalence is estimated to rise to pandemic proportions. Numerous adverse health effects follow with increasing body weight, including increased risk of hypertension, diabetes, hypercholesterolemia, musculoskeletal pain and cancer. Current evidence suggests that obesity is associated with altered cerebral reward circuit functioning and decreased inhibitory control over appetitive food cues. Furthermore, obesity causes adverse shifts in metabolism and loss of structural integrity within the brain. Prior cross-sectional studies do not allow delineating which of these cerebral changes are recoverable after weight loss. We compared morbidly obese subjects with healthy controls to unravel brain changes associated with obesity. Bariatric surgery was used as an intervention to study which cerebral changes are recoverable after weight loss. In Study I we employed functional magnetic resonance imaging (fMRI) to detect the brain basis of volitional appetite control and its alterations in obesity. In Studies II-III we used diffusion tensor imaging (DTI) and voxel-based morphometry (VBM) to quantify the effects of obesity and the effects of weight loss on structural integrity of the brain. In study IV we used positron emission tomography (PET) with [18F]-FDG in fasting state and during euglycemic hyperinsulinemia to quantify effects of obesity and weight loss on brain glucose uptake. The fMRI experiment revealed that a fronto-parietal network is involved in volitional appetite control. Obese subjects had lower medial frontal and dorsal striatal brain activity during cognitive appetite control and increased functional connectivity within the appetite control circuit. Obese subjects had initially lower grey matter and white matter densities than healthy controls in VBM analysis and loss of integrity in white matter tracts as measured by DTI. They also had initially elevated glucose metabolism under insulin stimulation but not in fasting state. After the weight loss following bariatric surgery, obese individuals’ brain volumes recovered and the insulin-induced increase in glucose metabolism was attenuated. In conclusion, obesity is associated with altered brain function, coupled with loss of structural integrity and elevated glucose metabolism, which are likely signs of adverse health effects to the brain. These changes are reversed by weight loss after bariatric surgery, implicating that weight loss has a causal role on these adverse cerebral changes. Altogether these findings suggest that weight loss also promotes brain health.Key words: brain, obesity, bariatric surgery, appetite control, structural magnetic resonance

Optimization of the HS-SPME-GC/MS technique for the analysis of volatile compounds in caprine Coalho cheese using response surface methodology

Abstract Caprine Coalho cheese presents great potential for a typical protected designation of origin, considering that this traditional Brazilian cheese presents a slightly salty and acid flavor, combined with a unique texture. This study optimized the HS-SPME-GC-MS methodology for volatile analysis of Coalho cheese, which can be used as a tool to help in the identification of the distinctive aroma profile of this cheese. The conditions of equilibrium time, extraction temperature and time were optimized using the statistical tool factorial experimental design 23, and applying the desirability function. After the evaluation, it was concluded that the optimum extraction conditions comprised equilibrium and extraction time of 20 and 40 minutes, respectively; and ideal extraction temperature of 45 °C. The optimum extraction of volatile compounds in goat Coalho cheese captured 32 volatile compounds: 5 alcohols, 5 esters, 3 ketones, 6 acids, 3 aldehydes, 3 terpenes, and 7 hydrocarbons.

Early initiation of dialysis: mortality and renal function recovery in acute kidney injury patients

INTRODUCTION: The decision of when to start dialysis in Acute Kidney Injury (AKI) patients with overt uremia is strongly established, however, when blood urea nitrogen (BUN) levels is < 100 mg/dL the timing of initiation of dialysis remains uncertain. Purpose: The aim of this study was to assess mortality and renal function recovery AKI patients started on dialysis at different BUN levels. METHODS: This was a retrospective study performed at Medical School Hospital, São Paulo, Brazil, enrolling 86 patients underwent to dialysis. RESULTS: Dialysis was started when BUN < 75 mg/dl in 23 patients (Group I) and BUN > 75 mg/dl in 63 patients (Group II). Hypervolemia and mortality were higher in Group I than in Group II (65.2% vs. 14.3% - p < 0.05, 39.1% vs. 68.9%- p < 0.05, respectively). Among survivors, the rate of renal function recovery was higher in Group I (71.4% and 36.8%, respectively - p < 0.05). Multivariate analysis showed that sepsis, age > 60 years, peritoneal dialysis and BUN > 75 mg/dl at dialysis initiation were independently related with mortality. CONCLUSIONS: Lower mortality and higher renal function recovery rates were associated with early dialysis initiated at lower BUN leves in AKI patients.

From protein structure to function with bioinformatics

It has long been known that amino acids are the building blocks for proteins and govern their folding into specific three-dimensional structures. However, the details of this process are still unknown and represent one of the main problems in structural bioinformatics, which is a highly active research area with the focus on the prediction of three-dimensional structure and its relationship to protein function. The protein structure prediction procedure encompasses several different steps from searches and analyses of sequences and structures, through sequence alignment to the creation of the structural model. Careful evaluation and analysis ultimately results in a hypothetical structure, which can be used to study biological phenomena in, for example, research at the molecular level, biotechnology and especially in drug discovery and development. In this thesis, the structures of five proteins were modeled with templatebased methods, which use proteins with known structures (templates) to model related or structurally similar proteins. The resulting models were an important asset for the interpretation and explanation of biological phenomena, such as amino acids and interaction networks that are essential for the function and/or ligand specificity of the studied proteins. The five proteins represent different case studies with their own challenges like varying template availability, which resulted in a different structure prediction process. This thesis presents the techniques and considerations, which should be taken into account in the modeling procedure to overcome limitations and produce a hypothetical and reliable three-dimensional structure. As each project shows, the reliability is highly dependent on the extensive incorporation of experimental data or known literature and, although experimental verification of in silico results is always desirable to increase the reliability, the presented projects show that also the experimental studies can greatly benefit from structural models. With the help of in silico studies, the experiments can be targeted and precisely designed, thereby saving both money and time. As the programs used in structural bioinformatics are constantly improved and the range of templates increases through structural genomics efforts, the mutual benefits between in silico and experimental studies become even more prominent. Hence, reliable models for protein three-dimensional structures achieved through careful planning and thoughtful executions are, and will continue to be, valuable and indispensable sources for structural information to be combined with functional data.

Phylogenetic Analysis of Avidins and Expression of Novel Avidins from Lactrodectus hesperus and Hoeflea phototrophica

Avidins (Avds) are homotetrameric or homodimeric glycoproteins with typically less than 130 amino acid residues per monomer. They form a highly stable, non-covalent complex with biotin (vitamin H) with Kd = 10-15 M (for chicken Avd). The best-studied Avds are the chicken Avd from Gallus gallus and streptavidin from Streptomyces avidinii, although other Avd studies have also included Avds from various origins, e.g., from frogs, fishes, mushrooms and from many different bacteria. Several engineered Avds have been reported as well, e.g., dual-chain Avds (dcAvds) and single-chain Avds (scAvds), circular permutants with up to four simultaneously modifiable ligand-binding sites. These engineered Avds along with the many native Avds have potential to be used in various nanobiotechnological applications. In this study, we made a structure-based alignment representing all currently available sequences of Avds and studied the evolutionary relationship of Avds using phylogenetic analysis. First, we created an initial multiple sequence alignment of Avds using 42 closely related sequences, guided by the known Avd crystal structures. Next, we searched for non-redundant Avd sequences from various online databases, including National Centre for Biotechnology Information and the Universal Protein Resource; the identified sequences were added to the initial alignment to expand it to a final alignment of 242 Avd sequences. The MEGA software package was used to create distance matrices and a phylogenetic tree. Bootstrap reproducibility of the tree was poor at multiple nodes and may reflect on several possible issues with the data: the sequence length compared is relatively short and, whereas some positions are highly conserved and functional, others can vary without impinging on the structure or the function, so there are few informative sites; it may be that periods of rapid duplication have led to paralogs and that the differences among them are within the error limit of the data; and there may be other yet unknown reasons. Principle component analysis applied to alternative distance data did segregate the major groups, and success is likely due to the multivariate consideration of all the information. Furthermore, based on our extensive alignment and phylogenetic analysis, we expressed two novel Avds, lacavidin from Lactrodectus Hesperus, a western black widow spider, and hoefavidin from Hoeflea phototrophica, an aerobic marine bacterium, the ultimate aim being to determine their X-ray structures. These Avds were selected because of their unique sequences: lacavidin has an N-terminal Avd-like domain but a long C-terminal overhang, whereas hoefavidin was thought to be a dimeric Avd. Both these Avds could be used as novel scaffolds in biotechnological applications.

Spectral Analysis of Symmetric and Anti-Symmetric Pairwise Kernels

This work investigates theoretical properties of symmetric and anti-symmetric kernels. First chapters give an overview of the theory of kernels used in supervised machine learning. Central focus is on the regularized least squares algorithm, which is motivated as a problem of function reconstruction through an abstract inverse problem. Brief review of reproducing kernel Hilbert spaces shows how kernels define an implicit hypothesis space with multiple equivalent characterizations and how this space may be modified by incorporating prior knowledge. Mathematical results of the abstract inverse problem, in particular spectral properties, pseudoinverse and regularization are recollected and then specialized to kernels. Symmetric and anti-symmetric kernels are applied in relation learning problems which incorporate prior knowledge that the relation is symmetric or anti-symmetric, respectively. Theoretical properties of these kernels are proved in a draft this thesis is based on and comprehensively referenced here. These proofs show that these kernels can be guaranteed to learn only symmetric or anti-symmetric relations, and they can learn any relations relative to the original kernel modified to learn only symmetric or anti-symmetric parts. Further results prove spectral properties of these kernels, central result being a simple inequality for the the trace of the estimator, also called the effective dimension. This quantity is used in learning bounds to guarantee smaller variance.

Bayesian analysis of SEIR epidemic models

This thesis concerns the analysis of epidemic models. We adopt the Bayesian paradigm and develop suitable Markov Chain Monte Carlo (MCMC) algorithms. This is done by considering an Ebola outbreak in the Democratic Republic of Congo, former Zaïre, 1995 as a case of SEIR epidemic models. We model the Ebola epidemic deterministically using ODEs and stochastically through SDEs to take into account a possible bias in each compartment. Since the model has unknown parameters, we use different methods to estimate them such as least squares, maximum likelihood and MCMC. The motivation behind choosing MCMC over other existing methods in this thesis is that it has the ability to tackle complicated nonlinear problems with large number of parameters. First, in a deterministic Ebola model, we compute the likelihood function by sum of square of residuals method and estimate parameters using the LSQ and MCMC methods. We sample parameters and then use them to calculate the basic reproduction number and to study the disease-free equilibrium. From the sampled chain from the posterior, we test the convergence diagnostic and confirm the viability of the model. The results show that the Ebola model fits the observed onset data with high precision, and all the unknown model parameters are well identified. Second, we convert the ODE model into a SDE Ebola model. We compute the likelihood function using extended Kalman filter (EKF) and estimate parameters again. The motivation of using the SDE formulation here is to consider the impact of modelling errors. Moreover, the EKF approach allows us to formulate a filtered likelihood for the parameters of such a stochastic model. We use the MCMC procedure to attain the posterior distributions of the parameters of the SDE Ebola model drift and diffusion parts. In this thesis, we analyse two cases: (1) the model error covariance matrix of the dynamic noise is close to zero , i.e. only small stochasticity added into the model. The results are then similar to the ones got from deterministic Ebola model, even if methods of computing the likelihood function are different (2) the model error covariance matrix is different from zero, i.e. a considerable stochasticity is introduced into the Ebola model. This accounts for the situation where we would know that the model is not exact. As a results, we obtain parameter posteriors with larger variances. Consequently, the model predictions then show larger uncertainties, in accordance with the assumption of an incomplete model.