141 research outputs found
Pathological features in perinatal autopsy and its relation with clinical and antenatal sonography findings
Background: Perinatal mortality is considered as a yardstick of obstetric and maternal care before and around the time of death. Perinatal autopsy is an inevitable procedure which helps to ascertain the cause of death, identify rare diseases, supplements clinical diagnosis and provide risk estimates for future pregnancies. The aim of the study was to describe the pathological features in perinatal autopsy specimens and to compare the pathological features with clinical and antenatal sonography findings.Methods: A descriptive study was conducted among 43 perinatal autopsy cases. A thorough perinatal autopsy was done. Detailed maternal medical and obstetric history including the laboratory and USG findings were collected. Collected data analysed using Statistical package for social sciences (SPSS) software. Results: The results were grouped into fetal, maternal and placental findings. Congenital anomalies were detected in 20% cases. That included gastrochisis, ebstein anomaly, isolated dextrocardia, hypoplastic left heart syndrome, cleft lip and palate, prune belly syndrome, club foot. Placenta findings observed were chorioamnionitis, placental thrombotic vasculopathy and placental findings in COVID-19 positive cases. The most common maternal comorbidity was hypertension (20.9%). Perinatal mortality was high in those cases with past history of abortions and history of infertility treatment. Full agreement between perinatal autopsy and antenatal USG findings was detected in 36.36% cases. Additional anomalies detected on autopsy was 54.54%.Conclusions: A thorough clinical history, prenatal ultrasonography and perinatal autopsy features could be described in detail in all the cases. Comparison of finding at autopsy with antenatal ultrasonography finding indicate that ultrasonography finding have only a reasonable value in assessing fetal status. Advanced radiology techniques could be maximum helpful.
Ternary Mixed Magnetic Co/Mn/Ni Dichloride Dihydrate
Ternary mixed magnetic Co1-xMnyNix-yCl2 center dot 2H(2)O has as its components three well studied antiferromagnets. Each is characterized by MCl2MCl2M...chemical and structural chains, with intrachain exchange interactions antiferromagnetic for the Mn component but ferromagnetic for the other two components. Competing ferromagnetic and antiferromagnetic intrachain exchange interactions occur in two different pairwise combinations. Reported here is the magnetic behavior of an equimolar mixture of the three components. One maximum appears in the magnetic susceptibility vs temperature, at 4.85 +/- 0.05 K, a quite interesting result since decidedly lower than the locations of susceptibility maxima in the pure components. A pronounced upturn in the susceptibility below 2.3 K also appears. Magnetization vs field isotherms display increasingly strong convex upward curvature and associated hysteresis with decreasing temperature. All of these characteristics differ markedly from those of the pure components
Deterministic Modularity Optimization
We study community structure of networks. We have developed a scheme for
maximizing the modularity Q based on mean field methods. Further, we have
defined a simple family of random networks with community structure; we
understand the behavior of these networks analytically. Using these networks,
we show how the mean field methods display better performance than previously
known deterministic methods for optimization of Q.Comment: 7 pages, 4 figures, minor change
Community detection based on links and node features in social networks
© Springer International Publishing Switzerland 2015. Community detection is a significant but challenging task in the field of social network analysis. Many effective methods have been proposed to solve this problem. However, most of them are mainly based on the topological structure or node attributes. In this paper, based on SPAEM [1], we propose a joint probabilistic model to detect community which combines node attributes and topological structure. In our model, we create a novel feature-based weighted network, within which each edge weight is represented by the node feature similarity between two nodes at the end of the edge. Then we fuse the original network and the created network with a parameter and employ expectation-maximization algorithm (EM) to identify a community. Experiments on a diverse set of data, collected from Facebook and Twitter, demonstrate that our algorithm has achieved promising results compared with other algorithms
Polylactic acid/nano chitosan composite fibers and their morphological, physical characterization for the removal of cadmium(II) from water
This work discusses the fabrication of polylactic acid (PLA)/nano chitosan
(nCHS) composite fibers by electrospinning method for Cd2+ metal ion adsorption
from water. Here nCHS was synthesized by ionic gelation method and
which is used as a reinforcement for PLA. The scanning electron microscopic
analysis revealed that the addition 0.1 wt% nCHS has decreased the fiber diameter
as well as the secondary pore size and hence imparted unique properties
to electrospun composite fibers. The positive zeta potential values for the composites
indicated their higher stability, though; the inclusion of nCHS reduced
the crystallinity of the neat membranes. The contact angle measurements
showed that the hydrophilicity of the composite was increased up to 0.1 wt%
nCHS, and hence the surface energy was increased. Inverse gas chromatography
results suggested that the basic character of the composites has intensified
with the increase in nCHS addition. The adsorption capacity of the neat
electrospun PLA and PLA–nCHS composites for Cd2+ ions were investigated
and studies revealed that adsorption capacity of the composite was two times
faster (approximately 70%) in comparison with neat PLA fibers. The increase
in surface area as well as presence nCHS improved the adsorption capacity of
the electrospun membrane.info:eu-repo/semantics/publishedVersio
Electrospun polylactic acid-chitosan composite: a bio-based alternative for inorganic composites for advanced application
Fabricating novel materials for biomedical applications mostly require the use of biodegradable materials. In this work biodegradable materials like polylactic acid (PLA) and chitosan (CHS) were used for designing electrospun mats. This work reports the physical and chemical characterization of the PLA-CHS composite, prepared by the electrospinning technique using a mixed solvent system. The addition of chitosan into PLA, offered decrease in fiber diameter in the composites with uniformity in the distribution of fibers with an optimum at 0.4wt% CHS. The fiber formation and the reduction in fiber diameter were confirmed by the SEM micrograph. The inverse gas chromatography and contact angle measurements supported the increase of hydrophobicity of the composite membrane with increase of filler concentration. The weak interaction between PLA and chitosan was confirmed by Fourier transform infrared spectroscopy and thermal analysis. The stability of the composite was established by zeta potential measurements. Cytotoxicity studies of the membranes were also carried out and found that up to 0.6% CHS the composite material was noncytotoxic. The current findings are very important for the design and development of new materials based on polylactic acid-chitosan composites for environmental and biomedical applications.info:eu-repo/semantics/publishedVersio
Macrostate Data Clustering
We develop an effective nonhierarchical data clustering method using an
analogy to the dynamic coarse graining of a stochastic system. Analyzing the
eigensystem of an interitem transition matrix identifies fuzzy clusters
corresponding to the metastable macroscopic states (macrostates) of a diffusive
system. A "minimum uncertainty criterion" determines the linear transformation
from eigenvectors to cluster-defining window functions. Eigenspectrum gap and
cluster certainty conditions identify the proper number of clusters. The
physically motivated fuzzy representation and associated uncertainty analysis
distinguishes macrostate clustering from spectral partitioning methods.
Macrostate data clustering solves a variety of test cases that challenge other
methods.Comment: keywords: cluster analysis, clustering, pattern recognition, spectral
graph theory, dynamic eigenvectors, machine learning, macrostates,
classificatio
Physical and in silico approaches identify DNA-PK in a Tax DNA-damage response interactome
<p>Abstract</p> <p>Background</p> <p>We have initiated an effort to exhaustively map interactions between HTLV-1 Tax and host cellular proteins. The resulting Tax interactome will have significant utility toward defining new and understanding known activities of this important viral protein. In addition, the completion of a full Tax interactome will also help shed light upon the functional consequences of these myriad Tax activities. The physical mapping process involved the affinity isolation of Tax complexes followed by sequence identification using tandem mass spectrometry. To date we have mapped 250 cellular components within this interactome. Here we present our approach to prioritizing these interactions via an <it>in silico </it>culling process.</p> <p>Results</p> <p>We first constructed an <it>in silico </it>Tax interactome comprised of 46 literature-confirmed protein-protein interactions. This number was then reduced to four Tax-interactions suspected to play a role in DNA damage response (Rad51, TOP1, Chk2, 53BP1). The first-neighbor and second-neighbor interactions of these four proteins were assembled from available human protein interaction databases. Through an analysis of betweenness and closeness centrality measures, and numbers of interactions, we ranked proteins in the first neighborhood. When this rank list was compared to the list of physical Tax-binding proteins, DNA-PK was the highest ranked protein common to both lists. An overlapping clustering of the Tax-specific second-neighborhood protein network showed DNA-PK to be one of three bridge proteins that link multiple clusters in the DNA damage response network.</p> <p>Conclusion</p> <p>The interaction of Tax with DNA-PK represents an important biological paradigm as suggested via consensus findings <it>in vivo </it>and <it>in silico</it>. We present this methodology as an approach to discovery and as a means of validating components of a consensus Tax interactome.</p
Review Article p16 INK4A and p14 ARF Gene Promoter Hypermethylation as Prognostic Biomarker in Oral and Oropharyngeal Squamous Cell Carcinoma: A Review
Head and neck squamous cell carcinoma is a heterogeneous group of tumors with each subtype having a distinct histopathological and molecular profile. Most tumors share, to some extent, the same multistep carcinogenic pathways, which include a wide variety of genetic and epigenetic changes. Epigenetic alterations represent all changes in gene expression patterns that do not alter the actual DNA sequence. Recently, it has become clear that silencing of cancer related genes is not exclusively a result of genetic changes such as mutations or deletions, but it can also be regulated on epigenetic level, mostly by means of gene promoter hypermethylation. Results from recent studies have demonstrated that DNA methylation patterns contain tumor-type-specific signatures, which could serve as biomarkers for clinical outcome in the near future. The topic of this review discusses gene promoter hypermethylation in oral and oropharyngeal squamous cell carcinoma (OSCC). The main objective is to analyse the available data on gene promoter hypermethylation of the cell cycle regulatory proteins p16 INK4A and p14 ARF and to investigate their clinical significance as novel biomarkers in OSCC. Hypermethylation of both genes seems to possess predictive properties for several clinicopathological outcomes. We conclude that the methylation status of p16 INK4A is definitely a promising candidate biomarker for predicting clinical outcome of OSCC, especially for recurrence-free survival
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