Automated Brain Tumor Detection using Ideal Shallow Neural Network with Artificial Jellyfish Optimization.

INTRODUCTION: Brain tumors are predicted from Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) scan images. In recent years, image processing-based automated tools are developed to predict tumor areas with less human interference. However, such automated tools are suffering from computational complexity and reduced accuracy in certain critical images. In the proposed work, an Ideal Shallow Neural Network (ISNN) is utilized to improve the prediction accuracy, and the computational complexity is reduced by implementing an Artificial Jellyfish Optimization (AJO) algorithm for minimizing the feature dimensionality. METHOD: The proposed method utilizes MRI images for the verification process as they are more informative than the CT scan image. The BRATS and the Kaggle datasets are used in this work and a Gabor filtering technique is used for noise reduction and a histogram equalization is used for enhancing the tumor boundary regions. The classification results observed from the AJO-ISNN are further forwarded towards the segmentation process and which uses the Centroid Weighted Segmentation (WCS) along with a Grasshopper Optimization Algorithm (GOA) for improving the segmentation over the boundary regions of the brain tumor. RESULT: The experimental result indicates a classification accuracy of 95.14% on the proposed AJO-ISNN model and AJO-ISNN is comparatively better than the Convolutional Neural Network (CNN) model accuracy of 85.41% and VGG 19 model accuracy of 93.75% while implemented with the AJO optimization model. Similarly, the Dice Similarity Coefficient of the proposed CWS-GOA also reaches 93.15% when performed with both BRATS and Kaggle datasets. CONCLUSION: Apart from the accuracy attainments the proposed work classifies and segments the tumor region in around 65 seconds on average of 200 image verifications and that is comparatively better than the previous multi-cascaded CNN and the InceptionV3 models.

Evaluation of antibacterial activity induced by Staphylococcus aureus and Ent A in the hemolymph of Spodoptera littoralis.

The problem of antibiotic resistance considers one of the most dangerous challenges facing the medical field. So, it is necessary to find substitutions to conventional antibiotics. Antimicrobial peptides (AMPs) are a bio-functional derivative that have been observed as one of the important solutions to such upcoming crisis. Owing to their role as the first line of defense against bacteria, fungi, and viruses. This study was conducted to induce the immune response of Spodoptera littoralis larvae by inoculation of sub lethal doses of Staphylococcus aureus and its enterotoxin. Since Staphylococcal enterotoxin A (SEA) considers the major causative agents of Staphylococcal food poisoning, our study oriented to purify and characterize this toxin to provoke its role in yielding AMPs with broad spectrum antimicrobial activity. A great fluctuation was recorded in the biochemical properties of immunized hemolymph not only in the total protein content but also protein banding pattern. Protein bands of ∼22 kDa (attacin-like) and ∼15 kDa (lysozyme-like) were found to be common between the AMPs induced as a result of both treatments. While protein bands of molecular weight ∼70 kDa (phenoloxidase-like) and ∼14 kDa (gloverin-like) were found specific for SEA treatment. Chromatographic analysis using HPLC for the induced AMPs showed different types of amino acids appeared with differences in their quantities and velocities. These peptides exhibited noticeable antimicrobial activity against certain Gram-positive and Gram-negative bacteria. In conclusion, the antimicrobial potential of the antimicrobial peptides (AMP) induced in the larval hemolymph of S. littoralis will be a promising molecule for the development of new therapeutic alternatives.

Assessment of diabetic foot risk among diabetic patients in a tertiary care hospital, South India.

INTRODUCTION: Foot problems are most common among patients with diabetes, and they are an important cause of morbidity in patients with diabetes mellitus (DM). They can be prevented by following a simple foot care practice. The study objective was to stratify the level of risk for diabetic foot ulcer (DFU) among patients with diabetes by screening. MATERIALS AND METHODS: A descriptive cross-sectional study design was adopted in this study. The sample size was 196, and a standardized INLOW'S 60-s diabetic foot screening tool was used to assess the risk of diabetic foot. Data collection was done by face-to-face interview, and diabetic foot risk (DFR) was assessed by direct observation, inspection, and palpation methods. RESULTS: Among the 196 patients, majority required yearly foot screen in both feet. The mean and standard deviation of the level of DFR in the left foot (LF) and right foot (RF) was 4.31 ± 2.267 and 4.51 ± 2.391, respectively. There was a statistically significant association between the practice of treatment and level of foot screening recommendation in the LF with Chi-square value of χ2= 8.20 (df = 2) and RF with Chi-square value of χ2= 7.95 (df = 2) at P < 0.05 level. CONCLUSION: Health-care providers should be made aware of the regular practice of screening the foot of diabetic patients along with health education awareness programs. It may be helpful to identify the foot ulcer risk at an early stage. It will prevent further complications of DFU and recurrence of ulcer and will reduce the economic burden to patients and their family members and the health-care system.

Publication of Study Exit Procedures in Clinical Trials of Deep Brain Stimulation: A Focused Literature Review.

Considerable variability exists in the publication of clinical research study procedures related to study enrollment and participant exit from clinical trials. Despite recent efforts to encourage research data sharing and greater transparency regarding research outcomes, reporting of research procedures remains inconsistent. Transparency about study procedures has important implications for the interpretation of study outcomes and the consistent implementation of best practices in clinical trial design and conduct. This review of publications from clinical trials of deep brain stimulation (DBS) using the MEDLINE database examines the frequency and consistency of publication of research procedures and data related to exit from DBS research. Related considerations, such as device explant or continued use, battery and other device hardware replacements, and post-trial follow-up care are also reviewed. This review finds significant variability in the publication and reporting of study exit procedures. Of the 47 clinical trials included in this review, 19% (9) disclosed procedures related to exit from research. Reporting of other exit-related data and study procedures examined in this review was identified in fewer than half of the included clinical trials. The rate of participant retention and duration of follow-up was reported more than any other category of data included in this review. Results inform efforts to improve consistency in research design, conduct, and publication of results from clinical trials in DBS and related areas of clinical research.

Management of Pediatric Movement Disorders: Present and Future.

Management of movement disorders in children is an evolving field. This article outlines the major categories of treatment options for pediatric movement disorders and general guidelines for their use. We review the evidence for existing therapies, which continue to lack large-scale controlled trials to guide treatment decisions. The field continues to rely on extrapolations from adult studies and lower quality evidence such as case reports and case series to guide treatment guidelines and consensus statements. Developments in new pharmaceuticals for rare diseases have begun to provide hope for those cases in which a genetic diagnosis can be made. Advances in surgical therapies such as deep brain stimulation as well as new modes of treatment such as gene therapy, epigenetic modulation, and stem cell therapy hold promise for improving outcomes in both primary and secondary causes of movement disorders. There is a critical need for larger, multicenter, controlled clinical trials to fully evaluate treatments for pediatric movement disorders.

Seasonal variation of the dominant allergenic fungal aerosols - One year study from southern Indian region.

Quantitative estimations of fungal aerosols are important to understand their role in causing respiratory diseases to humans especially in the developing and highly populated countries. In this study we sampled and quantified the three most dominantly found allergenic airborne fungi, Aspergillus fumigatus, Cladosporium cladosporioides, and Alternaria alternata from ambient PM10 samples using the quantitative PCR (qPCR) technique in a southern tropical Indian region, for one full year. Highest concentrations of A. fumigatus and C. cladosporioides were observed during monsoon whereas A. alternata displayed an elevated concentration in winter. The meteorological parameters such as temperature, relative humidity, wind speed, and precipitation exhibited a substantial influence on the atmospheric concentrations of allergenic fungal aerosols. The morphological features of various allergenic fungal spores present in the PM10 were investigated and the spores were found to possess distinct structural features. In a maiden attempt over this region we correlate the ambient fungal concentrations with the epidemiological allergy occurrence to obtain firsthand and preliminary information about the causative fungal allergen to the inhabitants exposed to bioaerosols. Our findings may serve as an important reference to atmospheric scientists, aero-biologists, doctors, and general public.

Terrestrial Macrofungal Diversity from the Tropical Dry Evergreen Biome of Southern India and Its Potential Role in Aerobiology.

Macrofungi have long been investigated for various scientific purposes including their food and medicinal characteristics. Their role in aerobiology as a fraction of the primary biological aerosol particles (PBAPs), however, has been poorly studied. In this study, we present a source of macrofungi with two different but interdependent objectives: (i) to characterize the macrofungi from a tropical dry evergreen biome in southern India using advanced molecular techniques to enrich the database from this region, and (ii) to assess whether identified species of macrofungi are a potential source of atmospheric PBAPs. From the DNA analysis, we report the diversity of the terrestrial macrofungi from a tropical dry evergreen biome robustly supported by the statistical analyses for diversity conclusions. A total of 113 macrofungal species belonging to 54 genera and 23 families were recorded, with Basidiomycota and Ascomycota constituting 96% and 4% of the species, respectively. The highest species richness was found in the family Agaricaceae (25.3%) followed by Polyporaceae (15.3%) and Marasmiaceae (10.8%). The difference in the distribution of commonly observed macrofungal families over this location was compared with other locations in India (Karnataka, Kerala, Maharashtra, and West Bengal) using two statistical tests. The distributions of the terrestrial macrofungi were distinctly different in each ecosystem. We further attempted to demonstrate the potential role of terrestrial macrofungi as a source of PBAPs in ambient air. In our opinion, the findings from this ecosystem of India will enhance our understanding of the distribution, diversity, ecology, and biological prospects of terrestrial macrofungi as well as their potential to contribute to airborne fungal aerosols.