205 research outputs found

    An observational study on musculoskeletal manifestations in type 2 Diabetes mellitus in rural population of Himachal Pradesh, India

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    Background: The prevalence of diabetes mellitus (DM) is increasing at an alarming rate throughout world. Diabetes is mostly known for vascular and neurological complications. Musculoskeletal manifestations though not as serious as neurovascular complications can be very disabling. These may involve, the upper as well as the lower limb. This study was performed with am to find out the prevalence of musculoskeletal manifestations in type 2 diabetics in a far-flung district of Himachal Pradesh, India.Methods: Total 350 patients with type 2 DM were included in the study. All patients underwent screening for any musculoskeletal abnormalities. The patients with musculoskeletal abnormalities were further assessed to find the exact diagnosis according to predefined criteria.Results: The shoulder was the most commonly involved joint 21.7% of the patients followed by hand in 16.28% patients and knee in 13.18% patients. Foot was involved in 12% and hand in 7% of the patients. The commonest manifestation in upper limb was adhesive capsulitis in 19.1% and in lower limb was symptomatic knee osteoarthritis in 14.57% patients.Conclusions: Author observed high prevalence of musculoskeletal complications in type 2 diabetics in this study

    Nucleation of Iron Oxide Nanoparticles Mediated by Mms6 Protein in Situ

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    Biomineralization proteins are widely used as templating agents in biomimetic synthesis of a variety of organic-inorganic nanostructures. However, the role of the protein in controlling the nucleation and growth of biomimetic particles is not well understood, because the mechanism of the bioinspired reaction is often deduced from ex situ analysis of the resultant nanoscale mineral phase. Here we report the direct visualization of biomimetic iron oxide nanoparticle nucleation mediated by an acidic bacterial recombinant protein, Mms6, during an in situ reaction induced by the controlled addition of sodium hydroxide to solution-phase Mms6 protein micelles incubated with ferric chloride. Using in situ liquid cell scanning transmission electron microscopy we observe the liquid iron prenucleation phase and nascent amorphous nanoparticles forming preferentially on the surface of protein micelles. Our results provide insight into the early steps of protein-mediated biomimetic nucleation of iron oxide and point to the importance of an extended protein surface during nanoparticle formation

    Visualization of Iron-Binding Micelles in Acidic Recombinant Biomineralization Protein, MamC

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    Biological macromolecules are utilized in low-temperature synthetic methods to exert precise control over nanoparticle nucleation and placement. They enable low-temperature formation of a variety of functional nanostructured materials with properties often not achieved via conventional synthetic techniques. Here we report on the in situ visualization of a novel acidic bacterial recombinant protein, MamC, commonly present in the magnetosome membrane of several magnetotactic bacteria, including Magnetococcus marinus, strain MC-1. Our findings provide an insight into the self-assembly of MamC and point to formation of the extended protein surface, which is assumed to play an important role in the formation of biotemplated inorganic nanoparticles. The self-organization of MamC is compared to the behavior of another acidic recombinant iron-binding protein, Mms6.This work was supported by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Materials Sciences and Engineering Division. The research was performed at the Ames Laboratory, which is operated for the U.S. Department of Energy by Iowa State University under Contract no. DE-AC02-07CH11358. MamC cloning and purification were done at the University of Granada, Spain. Concepci贸n Jim茅nez L贸pez acknowledges the support from the Spanish Government through Grant CGL2010-18274 and the program Salvador de Madariaga

    Scrub Typhus in Himalayas

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    Himachal Pradesh state of India is situated in the outer Himalayan ranges. During the rainy season, several cases of acute febrile illness of unknown origin occurred. Orientia tsutsugamushi was identified as the causative agent by microimmunofluorescence and PCR. Two new genotypes of O. tsutsugamushi were identified in the region

    Monocrotophos Induced Apoptosis in PC12 Cells: Role of Xenobiotic Metabolizing Cytochrome P450s

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    Monocrotophos (MCP) is a widely used organophosphate (OP) pesticide. We studied apoptotic changes and their correlation with expression of selected cytochrome P450s (CYPs) in PC12 cells exposed to MCP. A significant induction in reactive oxygen species (ROS) and decrease in glutathione (GSH) levels were observed in cells exposed to MCP. Following the exposure of PC12 cells to MCP (10鈭5 M), the levels of protein and mRNA expressions of caspase-3/9, Bax, Bcl2, P53, P21, GSTP1-1 were significantly upregulated, whereas the levels of Bclw, Mcl1 were downregulated. A significant induction in the expression of CYP1A1/1A2, 2B1/2B2, 2E1 was also observed in PC12 cells exposed to MCP (10鈭5 M), whereas induction of CYPs was insignificant in cells exposed to 10鈭6 M concentration of MCP. We believe that this is the first report showing altered expressions of selected CYPs in MCP-induced apoptosis in PC12 cells. These apoptotic changes were mitochondria mediated and regulated by caspase cascade. Our data confirm the involvement of specific CYPs in MCP-induced apoptosis in PC12 cells and also identifies possible cellular and molecular mechanisms of organophosphate pesticide-induced apoptosis in neuronal cells

    Extraocular retinoblastoma in Indian children:clinical, imaging and histopathological features

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    AIM: To study eyes with extraocular dissemination (EORB), with the following aims:first to establish the mean lag period and to understand various reasons for delayed presentation, second to study their imaging profiles and third to analyze histopathological features of eyes enucleated after neoadjuvant chemotherapy.METHODS: Prospective study of clinical and imaging features of EORBs (stage 鈪 and 鈪 International Retinoblastoma Staging System) presenting to a tertiary eye care centre. Histopathological features of eyes enucleated after receiving neoadjuvant chemotherapy were analyzed. A pictorial illustration of the varied imaging profile of EORB was also presented.RESULTS: Over a period of one year, 97 eyes were diagnosed with retinoblastoma; 32 children (36 eyes) (37.1%) had EORB. Mean age 3.6卤1.9 years, 71.9% males, 71.9% unilateral, 3.1% with positive family history and 40.6% with metastasis. On imaging, there was extrascleral involvement in 22.2%, involvement of orbital part of optic nerve in 33.3%, involvement of central nervous system in 27.8% and orbital wall involvement in 2.9% eyes. On histopathological analysis of eyes enucleated after neoadjuvant chemotherapy, 25.0% had no residual viable tumour tissue and rest all tumours were poorly differentiated.CONCLUSION:There are very few human malignancies where definitive treatment is started without any confirmed histopathological diagnosis and imaging plays an important role in diagnosis and appropriate staging of the disease. Chemotherapy has a variable effect on EORB, 75.0% of eyes with EORB had residual viable tumour tissue when enucleated after receiving neoadjuvant chemotherapy

    Dosage Effects of Cohesin Regulatory Factor PDS5 on Mammalian Development: Implications for Cohesinopathies

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    Cornelia de Lange syndrome (CdLS), a disorder caused by mutations in cohesion proteins, is characterized by multisystem developmental abnormalities. PDS5, a cohesion protein, is important for proper chromosome segregation in lower organisms and has two homologues in vertebrates (PDS5A and PDS5B). Pds5B mutant mice have developmental abnormalities resembling CdLS; however the role of Pds5A in mammals and the association of PDS5 proteins with CdLS are unknown. To delineate genetic interactions between Pds5A and Pds5B and explore mechanisms underlying phenotypic variability, we generated Pds5A-deficient mice. Curiously, these mice exhibit multiple abnormalities that were previously observed in Pds5B-deficient mice, including cleft palate, skeletal patterning defects, growth retardation, congenital heart defects and delayed migration of enteric neuron precursors. They also frequently display renal agenesis, an abnormality not observed in Pds5B鈭/鈭 mice. While Pds5A鈭/鈭 and Pds5B鈭/鈭 mice die at birth, embryos harboring 3 mutant Pds5 alleles die between E11.5 and E12.5 most likely of heart failure, indicating that total Pds5 gene dosage is critical for normal development. In addition, characterization of these compound homozygous-heterozygous mice revealed a severe abnormality in lens formation that does not occur in either Pds5A鈭/鈭 or Pds5B鈭/鈭 mice. We further identified a functional missense mutation (R1292Q) in the PDS5B DNA-binding domain in a familial case of CdLS, in which affected individuals also develop megacolon. This study shows that PDS5A and PDS5B functions other than those involving chromosomal dynamics are important for normal development, highlights the sensitivity of key developmental processes on PDS5 signaling, and provides mechanistic insights into how PDS5 mutations may lead to CdLS

    Adaptive-Miner: an efficient distributed association rule mining algorithm on Spark

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    Abstract Extraction of valuable data from extensive datasets is a standout amongst the most vital exploration issues. Association rule mining is one of the highly used methods for this purpose. Finding possible associations between items in large transaction based datasets (finding frequent itemsets) is most crucial part of the association rule mining task. Many single-machine based association rule mining algorithms exist but the massive amount of data available these days is above the capacity of a single machine based algorithm. Therefore, to meet the demands of this ever-growing enormous data, there is a need for distributed association rule mining algorithm which can run on multiple machines. For these types of parallel/distributed applications, MapReduce is one of the best fault-tolerant frameworks. Hadoop is one of the most popular open-source software frameworks with MapReduce based approach for distributed storage and processing of large datasets using standalone clusters built from commodity hardware. But heavy disk I/O operation at each iteration of a highly iterative algorithm like Apriori makes Hadoop inefficient. A number of MapReduce based platforms are being developed for parallel computing in recent years. Among them, a platform, namely, Spark have attracted a lot of attention because of its inbuilt support to distributed computations. Therefore, we implemented a distributed association rule mining algorithm on Spark named as Adaptive-Miner which uses adaptive approach for finding frequent patterns with higher accuracy and efficiency. Adaptive-Miner uses an adaptive strategy based on the partial processing of datasets. Adaptive-Miner makes execution plans before every iteration and goes with the best suitable plan to minimize time and space complexity. Adpative-Miner is a dynamic association rule mining algorithm which change its approach based on the nature of dataset. Therefore, it is different and better than state-of-the-art static association rule mining algorithms. We conduct in-depth experiments to gain insight into the effectiveness, efficiency, and scalability of the Adaptive-Miner algorithm on Spark. Available: https://github.com/sanjaysinghrathi/Adaptive-Mine

    Information Fusion Architecture for Variable-Load Scheduling in a Cloud-Assisted CPS

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    This paper addresses the problem of devising an effective information fusion architecture for a task scheduling algorithm which facilitates data processing of a Cyber Physical System (CPS) under bounded latency for bursty or lossy traffic. Task scheduling traditionally caters to real-time systems where a feedback loop does not exist allowing the serviced application to be independent of the inputs from the server. However, owing to the nature of a near real-time CPS, such liberties cannot be entertained. Additionally, the advent of big data in CPS has necessitated the use of Cloud Computing as a scalable and cost effective alternative. Task scheduling in such CPSs, where inputs from the Cloud complete the feedback loop is a major research issue. Therefore, in this paper, we propose a multi-layered information fusion architecture which integrates such a task scheduling mechanism by accommodating both traffic bursts and packet losses. Our scheduling algorithm ensures that the overall latency always remains under an acceptable upper bound as required by the CPS application
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