CD46 (membrane cofactor protein of complement, measles virus receptor): structural and functional divergence among species (review)

OBJECT: In this retrospective study, the authors analyzed the frequency, anatomical distribution, and appearance of traumatic brain lesions in 42 patients in a posttraumatic persistent vegetative state. METHODS: Cerebral magnetic resonance (MR) imaging was used to detect the number of lesions, which ranged from as few as five to as many as 19, with a mean of 11 lesions. In all 42 cases there was evidence on MR imaging of diffuse axonal injury, and injury to the corpus callosum was detected in all patients. The second most common area of diffuse axonal injury involved the dorsolateral aspect of the rostral brainstem (74% of patients). In addition, 65% of these patients exhibited white matter injury in the corona radiata and the frontal and temporal lobes. Lesions to the basal ganglia or thalamus were seen in 52% and 40% of patients, respectively. Magnetic resonance imaging showed some evidence of cortical contusion in 48% of patients in this study; the frontal and temporal lobes were most frequently involved. Injury to the parahippocampal gyrus was detected in 45% of patients; in this subgroup there was an 80% incidence of contralateral peduncular lesions in the midbrain. The most common pattern of injury (74% in this series) was the combination of focal lesions of the corpus callosum and the dorsolateral brainstem. In patients with no evidence of diffuse axonal injury in the upper brainstem (26% in this series), callosal lesions were most often associated with basal ganglia lesions. Lesions of the corona radiata and lobar white matter were equally distributed in patients with or without dorsolateral brainstem injury. Moreover, cortical contusions and thalamic, parahippocampal, and cerebral peduncular lesions were also similarly distributed in both groups. CONCLUSIONS: The data indicate that diffuse axonal injury may be the major form of primary brain damage in the posttraumatic persistent vegetative state. In addition, the authors demonstrated in this study that MR imaging, in conjunction with a precise clinical correlation, may provide useful supportive information for the accurate diagnosis of a persistent vegetative state after traumatic brain injury.     

Evaluation of a technique for identification of Shiga-like toxin-producing Escherichia coli by using polymerase chain reaction and digoxigenin-labeled probes

A polymerase chain reaction (PCR) technique for the identification of Shiga-like toxin (SLT)-producing Escherichia coli was assessed by using 95 strains of SLT-producing E. coli and 5 Shigella dysenteriae type 1 strains. PCR was used for the amplification of slt gene sequences from whole bacterial colonies. A digoxigenin-labeled DNA probe was used for identification of the PCR products in a spot blot hybridization assay. Modifications were made to adapt this technique for the proper identification of 10 SLT-producing isolates which were refractory to the heat lysis step that was used to liberate whole-cell DNA for PCR and 6 isolates which gave nonspecific amplification products. The sensitivity and specificity of this assay were each 99% when compared with toxin neutralization results by using SLT-specific monoclonal antibodies. These values indicate that this detection technique could be suitable for use in a clinical laboratory.     

Mechanism of impaired metabolic signaling by a truncated human insulin receptor. Decreased activation of protein phosphatase 1 by insulin

Previous studies have shown that a human insulin receptor lacking the COOH-terminal 43-amino acid domain (HIR delta CT) displays a compromised ability to stimulate glucose transport and glycogen synthase, whereas mitogenic signaling and stimulation of the insulin receptor tyrosine kinase activity remain intact (Maegawa, H., McClain, D. A., Freidenberg, G., Olefsky, J. M., Napier, M., Lipari, T., Dull, T. J., Lee, J., and Ullrich, A. (1988) J. Biol. Chem. 263, 8912-8917). In this study, we examined the effect of insulin on protein phosphatase 1 (PP-1) activity and phosphorylation in cells expressing wild-type human insulin receptor (HIRc) and HIR delta CT cells using phosphorylase alpha as substrate in the presence of 3 nM okadaic acid. Basal PP-1 activity was significantly lower in HIR delta CT than in HIRc cells (p < 0.05). Insulin stimulated PP-1 activity in HIRc cells (25-30% increase over basal activity) in a time- and dose-dependent manner. Insulin failed to stimulate PP-1 activity in HIR delta CT cells. Western blotting with the catalytic subunit antibody and the regulatory subunit antibody revealed similar amounts of the 37-kDa band (catalytic subunit) and the 160-kDa band (presumed regulatory subunit) in HIRc and HIR delta CT cells. We conclude that the COOH-terminal domain of the insulin receptor is an important element in mediating the effect of insulin on PP-1 and suggest that activation of PP-1 may be linked to signaling insulin's metabolic actions.     

A Novel DUF569 Gene Is a Positive Regulator of the Drought Stress Response in Arabidopsis

In the last two decades, global environmental change has increased abiotic stress on plants and severely affected crops. For example, drought stress is a serious abiotic stress that rapidly and substantially alters the morphological, physiological, and molecular responses of plants. In Arabidopsis, several drought-responsive genes have been identified; however, the underlying molecular mechanism of drought tolerance in plants remains largely unclear. Here, we report that the “domain of unknown function” novel gene DUF569 (AT1G69890) positively regulates drought stress in Arabidopsis. The Arabidopsis loss-of-function mutant atduf569 showed significant sensitivity to drought stress, i.e., severe wilting at the rosette-leaf stage after water was withheld for 3 days. Importantly, the mutant plant did not recover after rewatering, unlike wild-type (WT) plants. In addition, atduf569 plants showed significantly lower abscisic acid accumulation under optimal and drought-stress conditions, as well as significantly higher electrolyte leakage when compared with WT Col-0 plants. Spectrophotometric analyses also indicated a significantly lower accumulation of polyphenols, flavonoids, carotenoids, and chlorophylls in atduf569 mutant plants. Overall, our results suggest that novel DUF569 is a positive regulator of the response to drought in Arabidopsis.     

Synthesis and characterization of polyurethane/poly(vinylidene chloride) interpenetrating polymer networks

A series of polyurethane (PU)/poly(vinylidene chloride) (PVDC) interpenetrating polymer networks (IPNs) were synthesized through variations in the amounts of the prepolyurethane and vinylidene chloride monomer via sequential polymerization (80/20, 60/40, 50/50, 40/60, 30/70, and 20/80 PU/PVDC). The physicomechanical and optical properties of the IPNs were investigated. Thermogravimetric analysis (TGA) studies of the IPNs were performed to establish their thermal stability. TGA thermograms showed that the thermal degradation of the IPNs proceeded in three steps. Microcrystalline parameters, such as the crystal size and lattice disorder, of the PU/PVDC IPNs were estimated with wide‐angle X‐ray scattering. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 103: 1375–1381, 2007     

H ∞ filtering for singular bilinear systems with application to a single-link flexible-joint robot

In this paper, we consider the H _∞ filters design for singular bilinear systems. The approach is based on the parameterized solution of a set of constrained Sylvester equations. The exponential convergence and l ₂ gain attenuation problems are solved by using the bounded real lemma, which leads to linear matrix inequalities (LMI) formulation. Finally, a detailed design procedure is given for the estimation of the states of a flexible joint robot, which demonstrates the effectiveness of the proposed method.     

Isolation and characterization of cellulose nanowhiskers from Acacia caesia plant

Acacia caesia (L.) Willd (soap bark) fiber is an abundant natural resource, that is rich in cellulose. The study reports the effective utilization of underutilized Acacia caesia fiber for the isolation of nanocellulose whiskers. The nanocellulose whiskers were isolated successfully from Acacia caesia fibers by following alkali, bleaching, and sulfuric acid treatment. The obtained nanocellulose whiskers were carefully investigated for its chemical composition, structure, morphology, crystallinity, and thermal stability. The chemical composition and Fourier transform infrared spectra of nanocellulose whiskers showed the elimination of the non-cellulosic parts present in the raw Acacia caesia fibers. The X-ray diffraction analysis showed an upsurge in the crystallinity of the cellulose fibers after the chemical treatments. The isolation of nanocellulose whiskers from Acacia caesia raw fiber was confirmed by electron microscopy analysis. The thermogravimetric analysis showed remarkably high char residue for the nanocellulose whiskers compared to raw fibers. Based on the properties of nanocellulose whiskers, it can be concluded that the nanocellulose whiskers produced from Acacia caesia raw fibers are potential reinforcing material for developing high-performance green composites.     

Constructed wetland as a low cost and sustainable solution for wastewater treatment adapted to rural settlements: the Chorfech wastewater treatment pilot plant

The paper presents the detailed design and some preliminary results obtained from a study regarding a wastewater treatment pilot plant (WWTPP), serving as a multistage constructed wetland (CW) located at the rural settlement of 'Chorfech 24' (Tunisia). The WWTPP implemented at Chorfech 24 is mainly designed as a demonstration of sustainable water management solutions (low-cost wastewater treatment), in order to prove the efficiency of these solutions working under real Tunisian conditions and ultimately allow the further spreading of the demonstrated techniques. The pilot activity also aims to help gain experience with the implemented techniques and to improve them when necessary to be recommended for wide application in rural settlements in Tunisia and similar situations worldwide. The selected WWTPP at Chorfech 24 (rural settlement of 50 houses counting 350 inhabitants) consists of one Imhoff tank for pre-treatment, and three stages in series: as first stage a horizontal subsurface flow CW system, as second stage a subsurface vertical flow CW system, and a third horizontal flow CW. The sludge of the Imhoff tank is treated in a sludge composting bed. The performances of the different components as well as the whole treatment system were presented based on 3 months monitoring. The results shown in this paper are related to carbon, nitrogen and phosphorus removal as well as to reduction of micro-organisms. The mean overall removal rates of the Chorfech WWTPP during the monitored period have been, respectively, equal to 97% for total suspended solids and biochemical oxygen demand (BOD5), 95% for chemical oxygen demand, 71% for total nitrogen and 82% for P-PO4. The removal of E. coli by the whole system is 2.5 log units.     

EEG‐based brain source localization using visual stimuli

Electroencephalography (EEG) is widely used in variety of research and clinical applications which includes the localization of active brain sources. Brain source localization provides useful information to understand the brain's behavior and cognitive analysis. Various source localization algorithms have been developed to determine the exact locations of the active brain sources due to which electromagnetic activity is generated in brain. These algorithms are based on digital filtering, 3D imaging, array signal processing and Bayesian approaches. According to the spatial resolution provided, the algorithms are categorized as either low resolution methods or high resolution methods. In this research study, EEG data is collected by providing visual stimulus to healthy subjects. FDM is used for head modelling to solve forward problem. The low‐resolution brain electromagnetic tomography (LORETA) and standardized LORETA (sLORETA) have been used as inverse modelling methods to localize the active regions in the brain during the stimulus provided. The results are produced in the form of MRI images. The tables are also provided to describe the intensity levels for estimated current level for the inverse methods used. The higher current value or intensity level shows the higher electromagnetic activity for a particular source at certain time instant. Thus, the results obtained demonstrate that standardized method which is based on second order Laplacian (sLORETA) in conjunction with finite difference method (FDM) as head modelling technique outperforms other methods in terms of source estimation as it has higher current level and thus, current density (J) for an area as compared to others.     

Multimodal magnetic resonance imaging for Alzheimer's disease diagnosis using hybrid features extraction and ensemble support vector machines

Magnetic resonance imaging (MRI) is increasingly used in the diagnosis of Alzheimer's disease (AD) in order to identify abnormalities in the brain. Indeed, cortical atrophy, a powerful biomarker for AD, can be detected using structural MRI (sMRI), but it cannot detect impairment in the integrity of the white matter (WM) preceding cortical atrophy. The early detection of these changes is made possible by the novel MRI modality known as diffusion tensor imaging (DTI). In this study, we integrate DTI and sMRI as complementary imaging modalities for the early detection of AD in order to create an effective computer-assisted diagnosis tool. The fused Bag-of-Features (BoF) with Speeded-Up Robust Features (SURF) and modified AlexNet convolutional neural network (CNN) are utilized to extract local and deep features. This is applied to DTI scalar metrics (fractional anisotropy and diffusivity metric) and segmented gray matter images from T1-weighted MRI images. Then, the classification of local unimodal and deep multimodal features is first performed using support vector machine (SVM) classifiers. Then, the majority voting technique is adopted to predict the final decision from the ensemble SVMs. The study is directed toward the classification of AD versus mild cognitive impairment (MCI) versus cognitively normal (CN) subjects. Our proposed method achieved an accuracy of 98.42% and demonstrated the robustness of multimodality imaging fusion.