Inter-relationship of plasma markers of oxidative stress and thyroid hormones in schizophrenics

<p>Abstract</p> <p>Background</p> <p>The relationship of oxidative stress to thyroid hormones has not been studied in the schizophrenics. The present study determined the status and interrelationship of plasma markers of oxidative stress, nitric oxide and thyroid hormones in thirty (17 males and 13 females) newly diagnosed patients with acute schizophrenia before initiation of chemotherapy. Twenty five (13 males and 12 females) mentally healthy individuals served as controls. Patients and controls with history of hard drugs (including alcohol and cigarette), pre-diagnosis medications (e.g. antiparkinsonian/antipsychotic drugs), chronic infections, liver disease and diabetes mellitus were excluded from the study. Plasma levels of total antioxidant potential (TAP), total plasma peroxides (TPP), nitric oxide (NO), malondialdehyde (MDA), thyroxine (T4), tri-iodothyronine (T3) and thyroid stimulating hormone (TSH) were determined in all participants using spectrophotometric and enzyme linked immunosorbent assay (ELISA) methods respectively. Oxidative stress index (OSI) was calculated as the percent ratio of total plasma peroxides and total antioxidant potential.</p> <p>Findings</p> <p>Significantly higher plasma levels of MDA (p < 0.01), TPP (p < 0.01), OSI (p < 0.01), T3 (p < 0.01) and T4 (p < 0.05) were observed in schizophrenics when compared with the controls. The mean levels of TAP, NO and TSH were significantly lower in schizophrenics (p < 0.01) when compared with the controls. The result shows that T3 values correlate significantly with MDA (p < 0.05) and TPP (p < 0.01) in schizophrenics.</p> <p>Conclusions</p> <p>Higher level of TPP may enhance thyroid hormogenesis in schizophrenics. Adjuvant antioxidant therapy may be a novel approach in the treatment of schizophrenic patients.</p

Lack of Phylogeographic Structure in the Freshwater Cyanobacterium Microcystis aeruginosa Suggests Global Dispersal

Background : Free-living microorganisms have long been assumed to have ubiquitous distributions with little biogeographic signature because they typically exhibit high dispersal potential and large population sizes. However, molecular data provide contrasting results and it is far from clear to what extent dispersal limitation determines geographic structuring of microbial populations. We aimed to determine biogeographical patterns of the bloom-forming freshwater cyanobacterium Microcystis aeruginosa. Being widely distributed on a global scale but patchily on a regional scale, this prokaryote is an ideal model organism to study microbial dispersal and biogeography. Methodology/Principal Findings : The phylogeography of M. aeruginosa was studied based on a dataset of 311 rDNA internal transcribed spacer (ITS) sequences sampled from six continents. Richness of ITS sequences was high (239 ITS types were detected). Genetic divergence among ITS types averaged 4% (maximum pairwise divergence was 13%). Preliminary analyses revealed nearly completely unresolved phylogenetic relationships and a lack of genetic structure among all sequences due to extensive homoplasy at multiple hypervariable sites. After correcting for this, still no clear phylogeographic structure was detected, and no pattern of isolation by distance was found on a global scale. Concomitantly, genetic differentiation among continents was marginal, whereas variation within continents was high and was mostly shared with all other continents. Similarly, no genetic structure across climate zones was detected. Conclusions/Significance : The high overall diversity and wide global distribution of common ITS types in combination with the lack of phylogeographic structure suggest that intercontinental dispersal of M. aeruginosa ITS types is not rare, and that this species might have a truly cosmopolitan distribution

Microbial diversity and biogeochemical cycling in soda lakes

Soda lakes contain high concentrations of sodium carbonates resulting in a stable elevated pH, which provide a unique habitat to a rich diversity of haloalkaliphilic bacteria and archaea. Both cultivation-dependent and -independent methods have aided the identification of key processes and genes in the microbially mediated carbon, nitrogen, and sulfur biogeochemical cycles in soda lakes. In order to survive in this extreme environment, haloalkaliphiles have developed various bioenergetic and structural adaptations to maintain pH homeostasis and intracellular osmotic pressure. The cultivation of a handful of strains has led to the isolation of a number of extremozymes, which allow the cell to perform enzymatic reactions at these extreme conditions. These enzymes potentially contribute to biotechnological applications. In addition, microbial species active in the sulfur cycle can be used for sulfur remediation purposes. Future research should combine both innovative culture methods and state-of-the-art ‘meta-omic’ techniques to gain a comprehensive understanding of the microbes that flourish in these extreme environments and the processes they mediate. Coupling the biogeochemical C, N, and S cycles and identifying where each process takes place on a spatial and temporal scale could unravel the interspecies relationships and thereby reveal more about the ecosystem dynamics of these enigmatic extreme environments

Real-Time Survivor Detection System in SaR Missions Using Robots

This paper considers the issue of the search and rescue operation of humans after natural or man-made disasters. This problem arises after several calamities, such as earthquakes, hurricanes, and explosions. It usually takes hours to locate the survivors in the debris. In most cases, it is dangerous for the rescue workers to visit and explore the whole area by themselves. Hence, there is a need for speeding up the whole process of locating survivors accurately and with less damage to human life. To tackle this challenge, we present a scalable solution. We plan to introduce the usage of robots for the initial exploration of the calamity site. The robots will explore the site and identify the location of human survivors by examining the video feed (with audio) captured by them. They will then stream the detected location of the survivor to a centralized cloud server. It will also monitor the associated air quality of the selected area to determine whether it is safe for rescue workers to enter the region or not. The human detection model for images that we have used has a mAP (mean average precision) of 70.2%. The proposed approach uses a speech detection technique which has an F1 score of 0.9186 and the overall accuracy of the architecture is 95.83%. To improve the detection accuracy, we have combined audio detection and image detection techniques

Real-Time Survivor Detection System in SaR Missions Using Robots

This paper considers the issue of the search and rescue operation of humans after natural or man-made disasters. This problem arises after several calamities, such as earthquakes, hurricanes, and explosions. It usually takes hours to locate the survivors in the debris. In most cases, it is dangerous for the rescue workers to visit and explore the whole area by themselves. Hence, there is a need for speeding up the whole process of locating survivors accurately and with less damage to human life. To tackle this challenge, we present a scalable solution. We plan to introduce the usage of robots for the initial exploration of the calamity site. The robots will explore the site and identify the location of human survivors by examining the video feed (with audio) captured by them. They will then stream the detected location of the survivor to a centralized cloud server. It will also monitor the associated air quality of the selected area to determine whether it is safe for rescue workers to enter the region or not. The human detection model for images that we have used has a mAP (mean average precision) of 70.2%. The proposed approach uses a speech detection technique which has an F1 score of 0.9186 and the overall accuracy of the architecture is 95.83%. To improve the detection accuracy, we have combined audio detection and image detection techniques