"Caught by the eye of sound" : epigastric swelling due to xiphisternal tuberculosis

BACKGROUND: Common causes of an epigastric mass include hepatomegaly, pancreatic pseudocyst and epigastric hernia, less common causes being carcinoma of the stomach or pancreas, whereas diseases of the sternum presenting as an epigastric swelling is extremely uncommon. We report a case of tubercular infection of the sternum located in the xiphoid process resulting in its presentation as an epigastric swelling. CASE REPORT: A 30-year-old immunocompetent woman with complaints of an epigastric swelling and undocumented pyrexia for four months was referred for sonographic evaluation with a clinical suspicion of an incompletely treated liver abscess. The patient was examined with ultrasound, sternal radiographs, CT and MRI. Ultrasound revealed a heterogeneous epigastric collection with linear echogenic components suggestive of bone fragments. These appearances suggested chronic infective osteomyelitis of the xiphoid process of the sternum. Lateral chest radiograph demonstrated lytic destruction of the xiphisternum. Tubercular etiology was considered and further evaluation with Multidetector Computed tomography (MDCT) and Magnetic Resonance Imaging (MRI) demonstrated erosive osteomyelitis of the xiphoid process with enhancing inflammation and collection in the adjoining soft tissue. Ultrasound-guided aspiration, PCR and Amplified Mycobacterium tuberculosis DNA test confirmed tubercular infection. CONCLUSIONS: We report a new case of osteo-articular tuberculosis localized to the xiphisternum, a rare clinical entity with an extremely unusual clinical presentation as an epigastric mass. The role of ultrasound in primary diagnosis and as an interventional diagnostic modality for guided aspiration is highlighted

Online regulations of low order systems under bounded control

Time-optimal solutions provide us with the fastest means to regulate a system in presence of input constraints. This advantage of time-optimal control solutions is offset by the fact that their real-time implementation involves computationally intensive iterative techniques. Moreover, time-optimal controls depend on the initial state and have to be recalculated for even the slightest perturbation. Clearly time-optimal controls are not good candidates for online regulation. Consequently, the search for alternatives to time-optimal solutions is a very active area of research. The work described here is inspired by the simplicity of optimal-aim concept. The "optimal-aim strategies" provide online regulation in presence of bounded inputs with minimal computational effort. These are based purely on state-space geometry of the plant and are inherently adaptive in nature. Optimal-aim techniques involve aiming of trajectory derivative (or the state velocity vector) so as to approach the equilibrium state in the best possible manner. This thesis documents the efforts to develop an online regulation algorithm for systems with input constraints. Through a number of hypotheses focussed on trying to reproduce the exact time-optimal solution, the diffculty associated with this task is demonstrated. A modification of optimal-aim concept is employed to develop a novel regulation algorithm. In this algorithm, aim directions are chosen in a special manner to generate the time-optimal control approximately. The control scheme thus developed is shown to be globally stabilizing for systems having eigenvalues in the CLHP (closed left half-plane). It is expected that this method or its modifications can be extended to higher dimensional systems as a part of future research. An alternative control algorithm involving a simple state-space aiming concept is also developed and discussed

Perception of primary school teachers about the quality of pre-school education provided by anganwadis

A couple of months ago, I was reading about Early Childhood Care and Education (ECCE)in India and came across the new drafts for the policy framework, quality standards and curriculum for pre-school education by the Ministry of Women and Child Development (MWCD). One of the aims of ECCE is to make a child school ready by providing emergent literacy and math skills and I started wondering about how do we know if a child is actually school ready or not? So, I decided to meet with a few primary school teachers to understand if they thought that the children who came to their schools after attending anganwadis were actually school ready, and if not what did they expect of children who attended anganwadis and what suggestions did they have for improving the quality of pre-school education provided by anganwadis

Physiologically based pharmacokinetic modeling of transdermal selegiline and its metabolites for the evaluation of disposition differences between healthy and special populations

A physiologically based pharmacokinetic (PBPK) model of selegiline (SEL), and its metabolites, was developed in silico to evaluate the disposition differences between healthy and special populations. SEL is metabolized to methamphetamine (MAP) and desmethyl selegiline (DMS) by several CYP enzymes. CYP2D6 metabolizes the conversion of MAP to amphetamine (AMP), while CYP2B6 and CYP3A4 predominantly mediate the conversion of DMS to AMP. The overall prediction error in simulated PK, using the developed PBPK model, was within 0.5–1.5-fold after intravenous and transdermal dosing in healthy and elderly populations. Simulation results generated in the special populations demonstrated that a decrease in cardiac output is a potential covariate that affects the SEL exposure in renally impaired (RI) and hepatic impaired (HI) subjects. A decrease in CYP2D6 levels increased the systemic exposure of MAP. DMS exposure increased due to a reduction in the abundance of CYP2B6 and CYP3A4 in RI and HI subjects. In addition, an increase in the exposure of the primary metabolites decreased the exposure of AMP. No significant difference between the adult and adolescent populations, in terms of PK, were observed. The current PBPK model predictions indicate that subjects with HI or RI may require closer clinical monitoring to identify any untoward effects associated with the administration of transdermal SEL patch

Extracting Entities of Interest from Comparative Product Reviews

This paper presents a deep learning based approach to extract product comparison information out of user reviews on various e-commerce websites. Any comparative product review has three major entities of information: the names of the products being compared, the user opinion (predicate) and the feature or aspect under comparison. All these informing entities are dependent on each other and bound by the rules of the language, in the review. We observe that their inter-dependencies can be captured well using LSTMs. We evaluate our system on existing manually labeled datasets and observe out-performance over the existing Semantic Role Labeling (SRL) framework popular for this task.Comment: Source Code: https://github.com/jatinarora2702/Review-Information-Extractio

Polyphenol rich extract from Sesbania grandiflora (L.) Pers. bark reduces rheumatism by mediating the expression of NF kappa B in rats

Sesbania grandiflora (L.) Pers. (Fabaceae) commonly called Agati or Vegetable Hummingbird, is autochthonal from Malaysia to North Australia; plant is cultivated in several parts of India. Root and bark paste is applied externally to relive pain and inflammation associated with arthritis. It has long been used as a traditional medicine for rheumatism. Keeping this in cognizance, the study was designed to explore the antirheumatic potential of S. grandiflora. The bark extracts were prepared and studied for their phytochemical study, in vitro antioxidant potential using 2, 2-diphenyl-1-picrylhydrazyl (DPPH) and nitric oxide (NO) radicals and antiarthritic activity against Complete Freund Adjuvant (CFA) induced arthritis. To probe into the causal mechanism of action, NFκB suppressing activity in paraventricular nucleus (PVN) of hypothalamus using potent extract was also studied. Polyphenol rich extract supplementation significantly normalizes the altered blood parameters and reverses the increase in paw thickness, a sign of arthritis in rats. Further, immunohistochemical analysis revealed significant reduction in the NFκB immunoreactive cells in 50% methanolic extract treated (14 days) arthritic rats (57%; p<0.001) as compared to control. These results consolidate the observation, that inhibition of NFκB may be a beneficial approach in the treatment of arthritis. This study corroborates the traditional use of S. grandiflora plant in rheumatism

Polyphenol rich extract from Sesbania grandiflora (L.) Pers. bark reduces rheumatism by mediating the expression of NF kappa B in rats

44-53Sesbania grandiflora (L.) Pers. (Fabaceae) commonly called Agati or Vegetable Hummingbird, is autochthonal from Malaysia to North Australia; plant is cultivated in several parts of India. Root and bark paste is applied externally to relive pain and inflammation associated with arthritis. It has long been used as a traditional medicine for rheumatism. Keeping this in cognizance, the study was designed to explore the antirheumatic potential of S. grandiflora. The bark extracts were prepared and studied for their phytochemical study, in vitro antioxidant potential using 2, 2-diphenyl-1-picrylhydrazyl (DPPH) and nitric oxide (NO) radicals and antiarthritic activity against Complete Freund Adjuvant (CFA) induced arthritis. To probe into the causal mechanism of action, NFκB suppressing activity in paraventricular nucleus (PVN) of hypothalamus using potent extract was also studied. Polyphenol rich extract supplementation significantly normalizes the altered blood parameters and reverses the increase in paw thickness, a sign of arthritis in rats. Further, immunohistochemical analysis revealed significant reduction in the NFκB immunoreactive cells in 50% methanolic extract treated (14 days) arthritic rats (57%; p<0.001) as compared to control. These results consolidate the observation, that inhibition of NFκB may be a beneficial approach in the treatment of arthritis. This study corroborates the traditional use of S. grandiflora plant in rheumatism

Balanced Deep CCA for Bird Vocalization Detection

Event detection improves when events are captured by two different modalities rather than just one. But to train detection systems on multiple modalities is challenging, in particular when there is abundance of unlabelled data but limited amounts of labeled data. We develop a novel self-supervised learning technique for multi- modal data that learns (hidden) correlations between simultaneously recorded microphone (sound) signals and accelerometer (body vibration) signals. The key objective of this work is to learn useful embeddings associated with high performance in downstream event detection tasks when labeled data is scarce and the audio events of interest — songbird vocalizations — are sparse. We base our approach on deep canonical correlation analysis (DCCA) that suffers from event sparseness. We overcome the sparseness of positive labels by first learning a data sampling model from the labelled data and by applying DCCA on the output it produces. This method that we term balanced DCCA (b-DCCA) improves the performance of the unsupervised embeddings on the down-stream supervised audio detection task compared to classsical DCCA. Because data labels are frequently imbalanced, our method might be of broad utility in low-resource scenarios

Advances in experimental and mechanistic computational models to understand pulmonary exposure to inhaled drugs

Abstract Prediction of local exposure following inhalation of a locally acting pulmonary drug is central to the successful development of novel inhaled medicines, as well as generic equivalents. This work provides a comprehensive review of the state of the art with respect to multiscale computer models designed to provide a mechanistic prediction of local and systemic drug exposure following inhalation. The availability and quality of underpinning in vivo and in vitro data informing the computer based models is also considered. Mechanistic modelling of local exposure has the potential to speed up and improve the chances of successful inhaled API and product development. Although there are examples in the literature where this type of modelling has been used to understand and explain local and systemic exposure, there are two main barriers to more widespread use. There is a lack of generally recognised commercially available computational models that incorporate mechanistic modelling of regional lung particle deposition and drug disposition processes to simulate free tissue drug concentration. There is also a need for physiologically relevant, good quality experimental data to inform such modelling. For example, there are no standardized experimental methods to characterize the dissolution of solid drug in the lungs or measure airway permeability. Hence, the successful application of mechanistic computer models to understand local exposure after inhalation and support product development and regulatory applications hinges on: (i) establishing reliable, bio-relevant means to acquire experimental data, and (ii) developing proven mechanistic computer models that combine: a mechanistic model of aerosol deposition and post-deposition processes in physiologically-based pharmacokinetic models that predict free local tissue concentrations