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In this paper, we present a framework to address the augmentation of images for the rare and minor appearance of mitotic type staining patterns, for Human Epithelium Type2 (HEp-2) cell images. The identification of mitotic patterns among non-mitotic/interphase patterns is important in the process of diagnosis of various autoimmune disorders. This task leads to a pattern classification problem between mitotic v/s interphase. However, among the two classes, typically, the number of mitotic cells are relatively very less. Thus, in this work, we propose to generate synthetic mitotic samples, which can be used to augment the number of mitotic samples and balance the samples of mitotic and interphase patterns in classification paradigm. An effective feature representation is used, to validate the usefulness of the synthetic samples in classification task, along with a subjective validation done by a medical expert. The results demonstrate that the approach of generating and mingling synthetic samples with existing training data works well and yields good performance, with 0.98 balanced class accuracy (BcA) in one case, over a public dataset, i.e., UQ-SNP I3A Task-3 mitotic cell identification dataset.

Bioacoustic classification often suffers from the lack of labeled data. This hinders the effective utilization of state-of-the-art deep learning models in bioacoustics. To overcome this problem, the authors propose a deep metric learning-based framework that provides effective classification, even when only a small number of per-class training examples are available. The proposed framework utilizes a multiscale convolutional neural network and the proposed dynamic variant of the triplet loss to learn a transformation space where intra-class separation is minimized and inter-class separation is maximized by a dynamically increasing margin. The process of learning this transformation is known as deep metric learning. The triplet loss analyzes three examples (referred to as a triplet) at a time to perform deep metric learning. The number of possible triplets increases cubically with the dataset size, making triplet loss more suitable than the cross-entropy loss in data-scarce conditions. Experiments on three different publicly available datasets show that the proposed framework performs better than existing bioacoustic classification methods. Experimental results also demonstrate the superiority of dynamic triplet loss over cross-entropy loss in data-scarce conditions. Furthermore, unlike existing bioacoustic classification methods, the proposed framework has been extended to provide open-set classification.

Purpose: To comparatively evaluate the efficacy of a pencil type wire twister and the normal wire twister in terms of various parameters during arch bars application., Method: The study involved residents of the department enrolled in MDS course. Two study groups of 60 patients each were made by randomly selecting the patients from the outpatient department of Oral and Maxillofacial surgery who required arch bar application. Group A included the patients who underwent upper and lower arch bar application with the use of a pencil type twister and group B included patients who underwent arch bar application with a normal wire twister. All respondents were given a questionnaire after the completion of procedure involving the use of medical sharps. The paired samples t test was used for statistical analysis., Result: Among group A, mean glove perforations, actual wire stick injuries, mean time taken to complete the procedure, mean wire breakage during the procedure was less than in group B. Comfort level of patients and Ease of operator while performing the procedure was more in group A than in group B. Frictional abrasion of the finger was not associated with the use of pencil type twister. Overall rating of the procedure was more in group A than group B., Conclusion: The use of pencil type wire twister outweighs normal wire twister in various ways. It increases the overall efficacy of the operator during the procedure.

Peroxisome proliferator-activated receptor-γ (PPARγ) ligands, including the insulin-sensitizing thiazolidinedione drugs, transcriptionally regulate hundreds of genes. Little is known about the relationship between PPARγ ligand-specific modulation of cellular mechanisms and insulin sensitization. We characterized the insulin sensitivity and multitissue gene expression profiles of lean and insulin-resistant, obese Zucker rats untreated or treated with one of four PPARγ ligands (pioglitazone, rosiglitazone, troglitazone, and AG-035029). We analyzed the transcriptional profiles of adipose tissue, skeletal muscle, and liver from the rats and determined whether ligand treatment insulin-sensitizing potency was related to ligand treatment-induced alteration of functional pathways. Ligand treatments improved insulin sensitivity in obese rats to varying degrees. Adipose tissue profiles revealed ligand treatment-selective modulation of inflammatory and branched-chain amino acid (BCAA) metabolic pathways, which correlated with ligand treatment-specific insulin-sensitizing potency. Skeletal muscle profiles showed that obese rats exhibited elevated expression of adipocyte and slow-twitch fiber markers, which further increased after ligand treatment, but the magnitude of the treatment-induced changes was not correlated with insulin sensitization. Although PPARγ ligand treatments heterogeneously improved dysregulated expression of cholesterol and fatty acid biosynthetic pathways in obese rat liver, these alterations were not correlated with ligand insulin-sensitizing potency. PPARγ ligand treatment-specific insulin-sensitizing potency correlated with modulation of adipose tissue inflammatory and BCAA metabolic pathways, suggesting a functional relationship between these pathways and whole body insulin sensitivity. Other PPARγ ligand treatment-induced functional pathway changes were detected in adipose tissue, skeletal muscle, and liver profiles but were not related to degree of insulin sensitization.

Background: Insulin resistance is manifested in muscle, adipose tissue, and liver and is associated with adipose tissue inflammation. The cellular components and mechanisms that regulate the onset of diet-induced insulin resistance are not clearly defined., Methodology and Principal Findings: We initially observed osteopontin (OPN) mRNA over-expression in adipose tissue of obese, insulin resistant humans and rats which was normalized by thiazolidinedione (TZD) treatment in both species. OPN regulates inflammation and is implicated in pathogenic maladies resulting from chronic obesity. Thus, we tested the hypothesis that OPN is involved in the early development of insulin resistance using a 2-4 week high fat diet (HFD) model. OPN KO mice fed HFD for 2 weeks were completely protected from the severe skeletal muscle, liver and adipose tissue insulin resistance that developed in wild type (WT) controls, as determined by hyperinsulinemic euglycemic clamp and acute insulin-stimulation studies. Although two-week HFD did not alter body weight or plasma free fatty acids and cytokines in either strain, HFD-induced hyperleptinemia, increased adipose tissue inflammation (macrophages and cytokines), and adipocyte hypertrophy were significant in WT mice and blunted or absent in OPN KO mice. Adipose tissue OPN protein isoform expression was significantly altered in 2- and 4-week HFD-fed WT mice but total OPN protein was unchanged. OPN KO bone marrow stromal cells were more osteogenic and less adipogenic than WT cells in vitro. Interestingly, the two differentiation pathways were inversely affected by HFD in WT cells in vitro., Conclusions: The OPN KO phenotypes we report reflect protection from insulin resistance that is associated with changes in adipocyte biology and adipose tissue inflammatory status. OPN is a key component in the development of HFD-induced insulin resistance.

Background: Recent understanding that insulin resistance is an inflammatory condition necessitates searching for genes that regulate inflammation in insulin sensitive tissues. 12/15-lipoxygenase (12/15LO) regulates the expression of proinflammatory cytokines and chemokines and is implicated in the early development of diet-induced atherosclerosis. Thus, we tested the hypothesis that 12/15LO is involved in the onset of high fat diet (HFD)-induced insulin resistance., Methodology/principal Findings: Cells over-expressing 12/15LO secreted two potent chemokines, MCP-1 and osteopontin, implicated in the development of insulin resistance. We assessed adipose tissue inflammation and whole body insulin resistance in wild type (WT) and 12/15LO knockout (KO) mice after 2-4 weeks on HFD. In adipose tissue from WT mice, HFD resulted in recruitment of CD11b(+), F4/80(+) macrophages and elevated protein levels of the inflammatory markers IL-1beta, IL-6, IL-10, IL-12, IFNgamma, Cxcl1 and TNFalpha. Remarkably, adipose tissue from HFD-fed 12/15LO KO mice was not infiltrated by macrophages and did not display any increase in the inflammatory markers compared to adipose tissue from normal chow-fed mice. WT mice developed severe whole body (hepatic and skeletal muscle) insulin resistance after HFD, as measured by hyperinsulinemic euglycemic clamp. In contrast, 12/15LO KO mice exhibited no HFD-induced change in insulin-stimulated glucose disposal rate or hepatic glucose output during clamp studies. Insulin-stimulated Akt phosphorylation in muscle tissue from HFD-fed mice was significantly greater in 12/15LO KO mice than in WT mice., Conclusions: These results demonstrate that 12/15LO mediates early stages of adipose tissue inflammation and whole body insulin resistance induced by high fat feeding.

Obese adipose tissue is characterized by infiltration of macrophages. We and others recently showed that a specific subset of macrophages is recruited to obese adipose and muscle tissue. This subset expresses CD11c and produces high levels of proinflammatory cytokines that are linked to the development of obesity-associated insulin resistance. Here, we used a conditional cell ablation system, based on transgenic expression of the diphtheria toxin receptor under the control of the CD11c promoter, to study the effects of depletion of CD11c+ cells in obese mouse models. Our results show that CD11c+ cell depletion results in rapid normalization of insulin sensitivity. Furthermore, CD11c+ cell ablation leads to a marked decrease in inflammatory markers, both locally and systemically, as reflected by gene expression and protein levels. Together, these results indicate that these CD11c+ cells are a potential therapeutic target for treatment of obesity-related insulin resistance and type II diabetes.