Acute pancreatitis in children: efficacy of computed tomography severity index in the assessment, management, and prediction of complications

Aim The aim of the study was to describe the assessment and management aspects and the role of computed tomography severity index (CTSI) in children with acute pancreatitis.Materials and methods All the children (≤14 years) admitted to the pediatric surgery unit of our institution with acute pancreatitis from 2003 to 2014 were included. This retrospective analysis studied the demographic, clinical, diagnostic, and treatment aspects and the role of CTSI.Results The male-to-female ratio out of a total of 45 patients studied was 4 : 1. The differences in mean leukocyte count, mean serum amylase, and mean serum lipase were not significant in children with different CTSI scores. The children with higher CTSI scores are more likely to have both early and late complications, need for intensive care, and overall longer hospital stay.Conclusion CTSI plays an important role in early determination of the clinical severity, guiding the need for intensive care and in predicting the occurrence of early and late complications in children with acute pancreatitis. Keywords: acute pancreatitis, children, computed tomography severity inde

Neurofibromatosis type 1: a rare cause of parotid swelling in a child

Von Recklinghausen disease, also known as neurofibromatosis type 1, is an autosomal dominant disorder that presents as neurocutaneous syndrome. These patients have increased chances of developing other tumors such as plexiform neurofibromas. Plexiform neurofibromas are a proliferation of Schwann cells in the nerve sheath. Affliction of the parotid gland in a young child is a rare presentation of these tumors. We present the management of one such case.Keywords: neurofibromatosis type 1, parotid swelling, plexiform neurofibrom

Thermal decomposition kinetics of sodium carboxymethyl cellulose: Model-free methods

Thermal analysis techniques such as thermogravimetric analysis (TGA) have been widely used because they provide rapid quantitative determination of various processes under isothermal or non-isothermal conditions. It allows the estimation of effective kinetic and thermodynamic parameters for various decomposition and thermal reactions. In this article, thermal degradation of sodium carboxymethyl cellulose (SMC) is investigated by means of dynamic thermogravimetric/derivative thermogravimetry (TG/DTG) in helium atmosphere with the flow rate 100 mL/min at the heating rate of 10-30 °C/min until the furnace wall temperature reached 700 °C. The non-isothermal degradation of SMC found to be taking place occurred major one step and minor two steps. Using a non-isothermal kinetic method based on a TGA data, kinetic parameters (Eand ln A) are calculated by Kissinger-Akahira-Sunose (KAS), Flynn-Wall-Ozawa (FWO) and Friedman methods. The results of studied polymer demonstrated that E and ln A is varied with function of conversion (α), which is in good agreement with literature data

Synthesis, characterization and thermal decomposition kinetics of poly(2-imidazolidinthione-formaldehyde)

A polymeric ligand, 2-imidazolidinthione-formaldehyde (poly-IF), bearing nitrogen and sulfur donor group was synthesized by the polycondensation of 2-imidazolidinthione and formaldehyde in alkaline medium. The synthetic ligand was characterized with micro-analytical and spectral studies. The thermal degradation is investigated by means of dynamic thermogravimetry (TG/DTG) in helium and air atmosphere at various heating rate. The non-isothermal degradation of poly-IF compound was occurred in an inert and air atmosphere. Degradation activation energies were calculated using model free multiple heating rate methods i.e. Flynn-Wall-Ozawa (FWO), Friedman and Kissinger. The compound poly-IF was also tested against strain (Escherichia coli) and it inhibits the proliferation of bacterial growth

Formation of ZnO Micro-Flowers Prepared via Solution Process and their Antibacterial Activity

This paper presents the fabrication and characterization of zinc oxide micro-flowers and their antibacterial activity. The micro-flowers of zinc oxide composed of hexagonal nanorods have been prepared via solution process using precursor zinc acetate di-hydrate and sodium hydroxide in 3 h of refluxing time at ~90°C. The antibacterial activities of grown micro-flowers were investigated against four pathogenic bacteria namely S. aureus, E. coli, S. typhimurium and K. pneumoniae by taking five different concentrations (5–45 μg/ml) of ZnO micro-flowers (ZnO-MFs). Our investigation reveals that at lowest concentration of ZnO-MFs solution inhibiting the growth of microbial strain which was found to be 5 μg/ml for all the tested pathogens. Additionally, on the basis of morphological and chemical observations, a chemical reaction mechanism of ZnO-MFs composed of hexagonal nanorods was also proposed

Synthesis, characterization and effect of pH variation on zinc oxide nanostructures

Here we present a systematic study on the morphological deviation of ZnO nanostructure (from sheets to micro-flowers) by varying pH of the solution via precipitation method. In this regard, zinc nitrate hexa-hydrate, NaOH and hydroxylamine hydrochloride (NH 2 OHÁHCl) were used. The solution of all three compounds was refluxed at a very low temperature (60 C) for short time (20 min). The solution pH was calibrated from 6 to 12 by the controlled addition of NaOH and HCl. We have observed from FESEM (field emission scanning electron microscopy) that the morphology of ZnO microballs composed with thin sheets markedly varies from sheet (at pH ¼ 6) to micro-flower composed with sheets of zinc oxide (pH ¼ 10{12). Further the morphology and crystallinity were also studied by the TEM (transmission electron microscopy) and HR-TEM (High resolution transmission electron microscopy) and it's clearly consistent with the FESEM observations. The FTIR spectroscopic measurement also confirms the compositional analysis of ZnO and it comes in the range of 475 to 424 cm À1 which is a standard peak of ZnO. In addition to this, the amount of H þ and OH À ions are found a key to control the structure of studied material and discussed in the growth mechanism

Plasma‐treated flammulina velutipes‐derived extract showed anticancer potential in human breast cancer cells

Natural products with medicinal properties are among alternative therapies of interest due to their high body tolerance. We aimed to determine whether nonthermal gas plasma could enhance the medicinal value of Flammulina velutipes mushrooms. Generated gas plasma was characterized by its emission spectrum in ambient air, pH, temperature, and H2O2 and NOx concentrations after exposure for various periods. Phenolic and flavonoid contents in the extracts were measured using antioxidant assays and Fourier transform infrared and ultraviolet‐visible spectroscopy. We analyzed the effects of the plasma‐treated mushroom‐derived extracts against breast carcinoma using the MCF7 and MDA‐MB231 cell lines. The extracts significantly and concentration dependently inhibited the growth of breast cancer cells without inducing toxicity in normal MCF10A cells, and induced apoptosis via oxidative stress, evidenced by DNA damage (γ‐ H2AX foci formation), and increased the population of MCF7 breast cancer cells arrested in the G2/M phase of the cell cycle. The extracts also induced mitochondrion‐mediated apoptosis of MCF7 cells through cytochrome c release and caspase cleavage activity. The plasma improved the biological activity of mushrooms by increasing their phenolic compounds that prevented the growth of breast cancer cells in vitro. © 2020 by the authors. Licensee MDPI, Basel, Switzerland

End-to-end deep convolutional recurrent models for noise robust waveform speech enhancement

Because of their simple design structure, end-to-end deep learning (E2E-DL) models have gained a lot of attention for speech enhancement. A number of DL models have achieved excellent results in eliminating the background noise and enhancing the quality as well as the intelligibility of noisy speech. Designing resource-efficient and compact models during real-time processing is still a key challenge. In order to enhance the accomplishment of E2E models, the sequential and local characteristics of speech signal should be efficiently taken into consideration while modeling. In this paper, we present resource-efficient and compact neural models for end-to-end noise-robust waveform-based speech enhancement. Combining the Convolutional Encode-Decoder (CED) and Recurrent Neural Networks (RNNs) in the Convolutional Recurrent Network (CRN) framework, we have aimed at different speech enhancement systems. Different noise types and speakers are used to train and test the proposed models. With LibriSpeech and the DEMAND dataset, the experiments show that the proposed models lead to improved quality and intelligibility with fewer trainable parameters, notably reduced model complexity, and inference time than existing recurrent and convolutional models. The quality and intelligibility are improved by 31.61% and 17.18% over the noisy speech. We further performed cross corpus analysis to demonstrate the generalization of the proposed E2E SE models across different speech datasets