Acute kidney injury in AIDS: frequency, RIFLE classification and outcome

The objective of the present study was to evaluate the characteristics of acute kidney injury (AKI) in AIDS patients and the value of RIFLE classification for predicting outcome. The study was conducted on AIDS patients admitted to an infectious diseases hospital inBrazil. The patients with AKI were classified according to the RIFLE classification: R (risk), I (injury), F (failure), L (loss), and E (end-stage renal disease). Univariate and multivariate analyses were used to evaluate the factors associated with AKI. A total of 532 patients with a mean age of 35 ± 8.5 years were included in this study. AKI was observed in 37% of the cases. Patients were classified as "R" (18%), "I" (7.7%) and "F" (11%). Independent risk factors for AKI were thrombocytopenia (OR = 2.9, 95%CI = 1.5-5.6, P < 0.001) and elevation of aspartate aminotransferase (AST) (OR = 3.5, 95%CI = 1.8-6.6, P < 0.001). General mortality was 25.7% and was higher among patients with AKI (40.2 vs17%, P < 0.001). AKI was associated with death and mortality increased according to RIFLE classification - "R" (OR 2.4), "I" (OR 3.0) and "F" (OR 5.1), P < 0.001. AKI is a frequent complication in AIDS patients, which is associated with increased mortality. RIFLE classification is an important indicator of poor outcome for AIDS patients.

Classification of brain tumor extracts by high resolution ¹H MRS using partial least squares discriminant analysis

High resolution proton nuclear magnetic resonance spectroscopy (¹H MRS) can be used to detect biochemical changes in vitro caused by distinct pathologies. It can reveal distinct metabolic profiles of brain tumors although the accurate analysis and classification of different spectra remains a challenge. In this study, the pattern recognition method partial least squares discriminant analysis (PLS-DA) was used to classify 11.7 T ¹H MRS spectra of brain tissue extracts from patients with brain tumors into four classes (high-grade neuroglial, low-grade neuroglial, non-neuroglial, and metastasis) and a group of control brain tissue. PLS-DA revealed 9 metabolites as the most important in group differentiation: γ-aminobutyric acid, acetoacetate, alanine, creatine, glutamate/glutamine, glycine, myo-inositol, N-acetylaspartate, and choline compounds. Leave-one-out cross-validation showed that PLS-DA was efficient in group characterization. The metabolic patterns detected can be explained on the basis of previous multimodal studies of tumor metabolism and are consistent with neoplastic cell abnormalities possibly related to high turnover, resistance to apoptosis, osmotic stress and tumor tendency to use alternative energetic pathways such as glycolysis and ketogenesis.

Manual and semi-automatic quantification of in vivo ¹H-MRS data for the classification of human primary brain tumors

In vivo proton magnetic resonance spectroscopy (¹H-MRS) is a technique capable of assessing biochemical content and pathways in normal and pathological tissue. In the brain, ¹H-MRS complements the information given by magnetic resonance images. The main goal of the present study was to assess the accuracy of ¹H-MRS for the classification of brain tumors in a pilot study comparing results obtained by manual and semi-automatic quantification of metabolites. In vivo single-voxel ¹H-MRS was performed in 24 control subjects and 26 patients with brain neoplasms that included meningiomas, high-grade neuroglial tumors and pilocytic astrocytomas. Seven metabolite groups (lactate, lipids, N-acetyl-aspartate, glutamate and glutamine group, total creatine, total choline, myo-inositol) were evaluated in all spectra by two methods: a manual one consisting of integration of manually defined peak areas, and the advanced method for accurate, robust and efficient spectral fitting (AMARES), a semi-automatic quantification method implemented in the jMRUI software. Statistical methods included discriminant analysis and the leave-one-out cross-validation method. Both manual and semi-automatic analyses detected differences in metabolite content between tumor groups and controls (P < 0.005). The classification accuracy obtained with the manual method was 75% for high-grade neuroglial tumors, 55% for meningiomas and 56% for pilocytic astrocytomas, while for the semi-automatic method it was 78, 70, and 98%, respectively. Both methods classified all control subjects correctly. The study demonstrated that ¹H-MRS accurately differentiated normal from tumoral brain tissue and confirmed the superiority of the semi-automatic quantification method.

MMP-1/PAR-1 signal transduction axis and its prognostic impact in esophageal squamous cell carcinoma

The matrix metalloprotease-1 (MMP-1)/protease-activated receptor-1 (PAR-1) signal transduction axis plays an important role in tumorigenesis. To explore the expression and prognostic value of MMP-1 and PAR-1 in esophageal squamous cell carcinoma (ESCC), we evaluated the expression of two proteins in resected specimens from 85 patients with ESCC by immunohistochemistry. Sixty-two (72.9%) and 58 (68.2%) tumors were MMP-1- and PAR-1-positive, respectively, while no significant staining was observed in normal esophageal squamous epithelium. MMP-1 and PAR-1 overexpression was significantly associated with tumor node metastasis (TNM) stage and regional lymph node involvement. Patients with MMP-1- and PAR-1-positive tumors, respectively, had poorer disease-free survival (DFS) than those with negative ESCC (P = 0.002 and 0.003, respectively). Univariate analysis showed a significant relationship between TNM stage [hazard ratio (HR) = 2.836, 95% confidence interval (CI) = 1.866-4.308], regional lymph node involvement (HR = 2.955, 95%CI = 1.713-5.068), MMP-1 expression (HR = 2.669, 95%CI = 1.229-6.127), and PAR-1 expression (HR = 1.762, 95%CI = 1.156-2.883) and DFS. Multivariate analysis including the above four parameters identified TNM stage (HR = 2.035, 95%CI = 1.167-3.681), MMP-1 expression (HR = 2.109, 95%CI = 1.293-3.279), and PAR-1 expression (HR = 1.967, 95%CI = 1.256-2.881) as independent and significant prognostic factors for DFS. Our data suggest for the first time that MMP-1 and PAR-1 were both overexpressed in ESCC and are novel predictors of poor patient prognosis after curative resection. The MMP-1/PAR-1 signal transduction axis might be a new therapeutic target for future therapies tailored against ESCC.

Effect of scanner acoustic background noise on strict resting-state fMRI

Functional MRI (fMRI) resting-state experiments are aimed at identifying brain networks that support basal brain function. Although most investigators consider a ‘resting-state’ fMRI experiment with no specific external stimulation, subjects are unavoidably under heavy acoustic noise produced by the equipment. In the present study, we evaluated the influence of auditory input on the resting-state networks (RSNs). Twenty-two healthy subjects were scanned using two similar echo-planar imaging sequences in the same 3T MRI scanner: a default pulse sequence and a reduced “silent” pulse sequence. Experimental sessions consisted of two consecutive 7-min runs with noise conditions (default or silent) counterbalanced across subjects. A self-organizing group independent component analysis was applied to fMRI data in order to recognize the RSNs. The insula, left middle frontal gyrus and right precentral and left inferior parietal lobules showed significant differences in the voxel-wise comparison between RSNs depending on noise condition. In the presence of low-level noise, these areas Granger-cause oscillations in RSNs with cognitive implications (dorsal attention and entorhinal), while during high noise acquisition, these connectivities are reduced or inverted. Applying low noise MR acquisitions in research may allow the detection of subtle differences of the RSNs, with implications in experimental planning for resting-state studies, data analysis, and ergonomic factors.

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.

Ultrasound method applied to characterize healthy femoral diaphysis of Wistar rats in vivo

A simple experimental protocol applying a quantitative ultrasound (QUS) pulse-echo technique was used to measure the acoustic parameters of healthy femoral diaphyses of Wistar rats in vivo. Five quantitative parameters [apparent integrated backscatter (AIB), frequency slope of apparent backscatter (FSAB), time slope of apparent backscatter (TSAB), integrated reflection coefficient (IRC), and frequency slope of integrated reflection (FSIR)] were calculated using the echoes from cortical and trabecular bone in the femurs of 14 Wistar rats. Signal acquisition was performed three times in each rat, with the ultrasound signal acquired along the femur's central region from three positions 1 mm apart from each other. The parameters estimated for the three positions were averaged to represent the femur diaphysis. The results showed that AIB, FSAB, TSAB, and IRC values were statistically similar, but the FSIR values from Experiments 1 and 3 were different. Furthermore, Pearson's correlation coefficient showed, in general, strong correlations among the parameters. The proposed protocol and calculated parameters demonstrated the potential to characterize the femur diaphysis of rats in vivo. The results are relevant because rats have a bone structure very similar to humans, and thus are an important step toward preclinical trials and subsequent application of QUS in humans.

Propofol inhibits burn injury-induced hyperpermeability through an apoptotic signal pathway in microvascular endothelial cells

Recent studies have revealed that an intrinsic apoptotic signaling cascade is involved in vascular hyperpermeability and endothelial barrier dysfunction. Propofol (2,6-diisopropylphenol) has also been reported to inhibit apoptotic signaling by regulating mitochondrial permeability transition pore (mPTP) opening and caspase-3 activation. Here, we investigated whether propofol could alleviate burn serum-induced endothelial hyperpermeability through the inhibition of the intrinsic apoptotic signaling cascade. Rat lung microvascular endothelial cells (RLMVECs) were pretreated with propofol at various concentrations, followed by stimulation with burn serum, obtained from burn-injury rats. Monolayer permeability was determined by transendothelial electrical resistance. Mitochondrial release of cytochrome C was measured by ELISA. Bax and Bcl-2 expression and mitochondrial release of second mitochondrial-derived activator of caspases (smac) were detected by Western blotting. Caspase-3 activity was assessed by fluorometric assay; mitochondrial membrane potential (Δψm) was determined with JC-1 (a potential-sensitive fluorescent dye). Intracellular ATP content was assayed using a commercial kit, and reactive oxygen species (ROS) were measured by dichlorodihydrofluorescein diacetate (DCFH-DA). Burn serum significantly increased monolayer permeability (P<0.05), and this effect could be inhibited by propofol (P<0.05). Compared with a sham treatment group, intrinsic apoptotic signaling activation - indicated by Bax overexpression, Bcl-2 downregulation, Δψm reduction, decreased intracellular ATP level, increased cytosolic cytochrome C and smac, and caspase-3 activation - was observed in the vehicle group. Propofol not only attenuated these alterations (P<0.05 for all), but also significantly decreased burn-induced ROS production (P<0.05). Propofol attenuated burn-induced RLMVEC monolayer hyperpermeability by regulating the intrinsic apoptotic signaling pathway.

Classification of different degrees of adiposity in sedentary rats

In experimental studies, several parameters, such as body weight, body mass index, adiposity index, and dual-energy X-ray absorptiometry, have commonly been used to demonstrate increased adiposity and investigate the mechanisms underlying obesity and sedentary lifestyles. However, these investigations have not classified the degree of adiposity nor defined adiposity categories for rats, such as normal, overweight, and obese. The aim of the study was to characterize the degree of adiposity in rats fed a high-fat diet using cluster analysis and to create adiposity intervals in an experimental model of obesity. Thirty-day-old male Wistar rats were fed a normal (n=41) or a high-fat (n=43) diet for 15 weeks. Obesity was defined based on the adiposity index; and the degree of adiposity was evaluated using cluster analysis. Cluster analysis allowed the rats to be classified into two groups (overweight and obese). The obese group displayed significantly higher total body fat and a higher adiposity index compared with those of the overweight group. No differences in systolic blood pressure or nonesterified fatty acid, glucose, total cholesterol, or triglyceride levels were observed between the obese and overweight groups. The adiposity index of the obese group was positively correlated with final body weight, total body fat, and leptin levels. Despite the classification of sedentary rats into overweight and obese groups, it was not possible to identify differences in the comorbidities between the two groups.

Lipase and esterase: to what extent can this classification be applied accurately?

Enzyme technology is an ever-growing field of knowledge and, in recent years, this technology has raised renewed interest, due to the search for new paradigms in several productive processes. Lipases, esterases and cutinases are enzymes used in a wide range of processes involving synthesis and hydrolysis reactions. The objective of this work was to investigate and compare the specific lipase and esterase activities of five enzymes - four already classified as lipases and one classified as cutinase - in the presence of natural and synthetic substrates. All tested enzymes presented both esterase and lipase specific activities. The highest specific esterase activity was observed for Aspergillus 1068 lipase in natural substrate and for F. oxysporum cutinase in synthetic substrate, while the highest specific lipase activity was observed for Geotrichum sp. lipase in natural substrate and for F. oxysporum cutinase in synthetic substrate. These results display some interface-independent lipolytic activity for all lipases tested. This is in accordance with the rationale that a new and broader definition of lipases may be necessary.

Characterization and classification of pequi trees (Caryocar brasiliense Camb.) based on the profile of volatile constituents using headspace solid-phase microextraction - gas chromatography - mass spectrometry and multivariate analysis

In order to determine the variability of pequi tree (Caryocar brasiliense Camb.) populations, volatile compounds from fruits of eighteen trees representing five populations were extracted by headspace solid-phase microextraction and analyzed by gas chromatography-mass spectrometry. Seventy-seven compounds were identified, including esters, hydrocarbons, terpenoids, ketones, lactones, and alcohols. Several compounds had not been previously reported in the pequi fruit. The amount of total volatile compounds and the individual compound contents varied between plants. The volatile profile enabled the differentiation of all of the eighteen plants, indicating that there is a characteristic profile in terms of their origin. The use of Principal Component Analysis and Cluster Analysis enabled the establishment of markers (dendrolasin, ethyl octanoate, ethyl 2-octenoate and β-cis-ocimene) that discriminated among the pequi trees. According to the Cluster Analysis, the plants were classified into three main clusters, and four other plants showed a tendency to isolation. The results from multivariate analysis did not always group plants from the same population together, indicating that there is greater variability within the populations than between pequi tree populations.

Blue and Uv-Emitting Upconversion Nanoparticles: Synthesis and (Bio) Analytical Applications.

Rare-earth based upconverting nanoparticles (UCNPs) have attracted much attention due to their unique luminescent properties. The ability to convert multiple photons of lower energy to ones with higher energy through an upconversion (UC) process offers a wide range of applications for UCNPs. The emission intensities and wavelengths of UCNPs are important performance characteristics, which determine the appropriate applications. However, insufficient intensities still limit the use of UCNPs; especially the efficient emission of blue and ultraviolet (UV) light via upconversion remains challenging, as these events require three or more near-infrared (NIR) photons. The aim of the study was to enhance the blue and UV upconversion emission intensities of Tm3+ doped NaYF4 nanoparticles and to demonstrate their utility in in vitro diagnostics. As the distance between the sensitizer and the activator significantly affect the energy transfer efficiency, different strategies were explored to change the local symmetry around the doped lanthanides. One important strategy is the intentional co-doping of active (participate in energy transfer) or passive (do not participate in energy transfer) impurities into the host matrix. The roles of doped passive impurities (K+ and Sc3+) in enhancing the blue and UV upconversions, as well as in influencing the intense UV upconversion emission through excess sensitization (active impurity) were studied. Additionally, the effects of both active and passive impurity doping on the morphological and optical performance of UCNPs were investigated. The applicability of UV emitting UCNPs as an internal light source for glucose sensing in a dry chemistry test strip was demonstrated. The measurements were in agreement with the traditional method based on reflectance measurements using an external UV light source. The use of UCNPs in the glucose test strip offers an alternative detection method with advantages such as control signals for minimizing errors and high penetration of the NIR excitation through the blood sample, which gives more freedom for designing the optical setup. In bioimaging, the excitation of the UCNPs in the transparent IR region of the tissue permits measurements, which are free of background fluorescence and have a high signal-to-background ratio. In addition, the narrow emission bandwidth of the UCNPs enables multiplexed detections. An array-in-well immunoassay was developed using two different UC emission colours. The differentiation between different viral infections and the classification of antibody responses were achieved based on both the position and colour of the signal. The study demonstrates the potential of spectral and spatial multiplexing in the imaging based array-in-well assays.

Observations of Acoustic Emission in Power Semiconductors

Industrial, electrical power generation, and transportation systems, to name but a few, rely heavily on power electronics to control and convert electrical power. Each of these systems, when encountering an unexpected failure, can cause significant financial losses, or even an emergency. A condition monitoring system would help to alleviate these concerns, but for the time being, there is no generally accepted and widely adopted method for power electronics. Acoustic emission is used as a failure precursor in many applications, but it has not been studied in power electronics so far. In this doctoral dissertation, observations of acoustic emission in power semiconductor components are presented. The acoustic emissions are caused by the switching operation and failure of power transistors. Three types of acoustic emission are observed. Furthermore, aspects related to the measurement and detection of acoustic phenomena are discussed. These include sensor performance and mechanical construction of experimental setups. The results presented in this dissertation are the outset of a research program where it will be determined whether an acoustic-emission-based condition monitoring method can be developed.