Imaging Inflammation in a Patient with Epilepsy Due to Focal Cortical Dysplasia

BACKGROUND AND PURPOSE Evidence from animal models and examination of human epilepsy surgery specimens indicates that inflammation plays an important role in epilepsy. Positron emission tomography (PET) using [C11]PK11195, a marker of activated microglia, provides a means to visualize neuroinflammation in vivo in humans. We hypothesize that in patients with active epilepsy, [C11]PK11195 PET (PK-PET) may be able to identify areas of focally increased inflammation corresponding to the seizure onset zone. METHODS A young woman with intractable epilepsy underwent PK-PET as part of an approved research study. PK-PET results were compared with results from other clinical studies. RESULTS PK-PET revealed an area of focally increased radiotracer uptake in the right frontal lobe corresponding to this patient’s seizure focus as identified by ictal and interictal 18Ffluorodeoxyglucose (FDG)-PET and EEG. Routine brain magnetic resonance imaging (MRI) was initially considered normal, though high-resolution studies showed possible subtle dysplasia of the right frontal lobe. The patient underwent a right frontal lobe resection, and pathological evaluation showed focal cortical dysplasia with activated microglia. CONCLUSIONS PK-PET can identify neuroinflammation associated with subtle focal cortical dysplasia, and may therefore have a clinical role in guiding epilepsy surgery for patients with difficult-to-localize seizure foci

The Effectiveness of Protected Areas in Conserving Globally Threatened Western Tragopan Tragopan melanocephalus.

Protected areas are a critical tool to conserve biodiversity in the face of the global crisis of species extinction. Here, we present the first ever management effectiveness assessment of Pakistan's Protected Areas (PAs). We link these assessments to the delivery of conservation outcomes focusing on the threatened Western Tragopan (Tragopan melanocephalus) endemic to Pakistan and India. We used two approaches, first mapping the spatial distribution of potential habitat coverage using machine learning ensemble models and second, an assessment of the management effectiveness of protected areas. Our results show that only Machiara National Park scored just above 40% (indicating relatively weak management), 22 of the PAs fell within the 25-50% quantile (indicating weak management), and 3 scored below 25% (indicating poor management). PAs within the species distributional range covered 92,387 ha which is only 2% of the total potential habitat of the Tragopan. Scoring of Planning element was insufficient both in term of the site and species. Likewise, inputs (e.g., research and monitoring program, staff numbers, staff training, current budget, security of budget, and management after process) were also inadequate. Finally, we recommend the establishment of more protected areas within the species potential habitat and inclusion of species-specific plans in Pakistan's PAs management

PANC Study (Pancreatitis: A National Cohort Study): national cohort study examining the first 30 days from presentation of acute pancreatitis in the UK

Abstract Background Acute pancreatitis is a common, yet complex, emergency surgical presentation. Multiple guidelines exist and management can vary significantly. The aim of this first UK, multicentre, prospective cohort study was to assess the variation in management of acute pancreatitis to guide resource planning and optimize treatment. Methods All patients aged greater than or equal to 18 years presenting with acute pancreatitis, as per the Atlanta criteria, from March to April 2021 were eligible for inclusion and followed up for 30 days. Anonymized data were uploaded to a secure electronic database in line with local governance approvals. Results A total of 113 hospitals contributed data on 2580 patients, with an equal sex distribution and a mean age of 57 years. The aetiology was gallstones in 50.6 per cent, with idiopathic the next most common (22.4 per cent). In addition to the 7.6 per cent with a diagnosis of chronic pancreatitis, 20.1 per cent of patients had a previous episode of acute pancreatitis. One in 20 patients were classed as having severe pancreatitis, as per the Atlanta criteria. The overall mortality rate was 2.3 per cent at 30 days, but rose to one in three in the severe group. Predictors of death included male sex, increased age, and frailty; previous acute pancreatitis and gallstones as aetiologies were protective. Smoking status and body mass index did not affect death. Conclusion Most patients presenting with acute pancreatitis have a mild, self-limiting disease. Rates of patients with idiopathic pancreatitis are high. Recurrent attacks of pancreatitis are common, but are likely to have reduced risk of death on subsequent admissions. </jats:sec

A Survey on Deep Reinforcement Learning for Audio-Based Applications

Deep reinforcement learning (DRL) is poised to revolutionise the field of artificial intelligence (AI) by endowing autonomous systems with high levels of understanding of the real world. Currently, deep learning (DL) is enabling DRL to effectively solve various intractable problems in various fields. Most importantly, DRL algorithms are also being employed in audio signal processing to learn directly from speech, music and other sound signals in order to create audio-based autonomous systems that have many promising application in the real world. In this article, we conduct a comprehensive survey on the progress of DRL in the audio domain by bringing together the research studies across different speech and music-related areas. We begin with an introduction to the general field of DL and reinforcement learning (RL), then progress to the main DRL methods and their applications in the audio domain. We conclude by presenting challenges faced by audio-based DRL agents and highlighting open areas for future research and investigation.Comment: Under Revie

A SHORT COMMUNICATION ON INHIBITORY AGENTS AGAINST SARS-COV2: VIRTUAL SCREENING AND DRUG REPURPOSING STUDIES

Severe Acute Respiratory Syndrome (SARS-CoV2) infected about 93 million people and killed over two million worldwide. The disease transmits very quickly, therefore; due to its severity and widespread the World Health Organization has declared this menace as ‘Global Pandemic’. An urgent need was felt to manage this disease through aggressive and efficient research process all over the globe. That’s why drug re-purposing of 212 chemical entities (CEs) against SARS-COV2 was found to be one of the efficient ways in finding new indications of already discovered drugs amisdst of the discovery of a new drug. Results of this study revealed that out of 212 CEs, only Etodolac forms a hydrogen (H)-bond with a relatively low energy and active central fragment, demonstrating more significant interaction with SARS-CoV2 viral proteins. Other CEs exhibit good pharmacokinetics properties with the least acute toxicity through ADMET analysis. We also discovered other therapeutic applications of these CEs through Molinspiration. Etodolac, a non-steroidal anti-inflammatory drug forms H-bonding with 5.6 kcal/mol binding energy with active residues of this receptor. This drug created H-bonding with PHE326 and PRO328, with pyridine group, and was found more suitable to control SARS-CoV2.</div

The Effectiveness of Protected Areas in Conserving Globally Threatened Western Tragopan Tragopan melanocephalus

Protected areas are a critical tool to conserve biodiversity in the face of the global crisis of species extinction. Here, we present the first ever management effectiveness assessment of Pakistan’s Protected Areas (PAs). We link these assessments to the delivery of conservation outcomes focusing on the threatened Western Tragopan (Tragopan melanocephalus) endemic to Pakistan and India. We used two approaches, first mapping the spatial distribution of potential habitat coverage using machine learning ensemble models and second, an assessment of the management effectiveness of protected areas. Our results show that only Machiara National Park scored just above 40% (indicating relatively weak management), 22 of the PAs fell within the 25–50% quantile (indicating weak management), and 3 scored below 25% (indicating poor management). PAs within the species distributional range covered 92,387 ha which is only 2% of the total potential habitat of the Tragopan. Scoring of Planning element was insufficient both in term of the site and species. Likewise, inputs (e.g., research and monitoring program, staff numbers, staff training, current budget, security of budget, and management after process) were also inadequate. Finally, we recommend the establishment of more protected areas within the species potential habitat and inclusion of species-specific plans in Pakistan’s PAs management

Biochemical and Metabolic Changes in Arsenic Contaminated Boehmeria nivea L.

Arsenic (As) is identified by the EPA as the third highest toxic inorganic contaminant. Almost every 9th or 10th human in more than 70 countries including mainland China is affected by As. Arsenic along with other toxins not only affects human life but also creates alarming situations such as the deterioration of farm lands and desertion of industrial/mining lands. Researchers and administrators have agreed to opt for phytoremediation of As over costly cleanups. Boehmeria nivea L. can soak up various heavy metals, such as Sb, Cd, Pb, and Zn. But the effect of As pollution on the biology and metabolism of B. nivea has been somewhat overlooked. This study attempts to evaluate the extent of As resistance, chlorophyll content, and metabolic changes in As-polluted (5, 10, 15, and 20 mg L−1 As) B. nivea in hydroponics. Toxic effects of As in the form of inhibited growth were apparent at the highest level of added As. The significant changes in the chlorophyll, electrolyte leakage, and H2O2, significant increases in As in plant parts, catalase (CAT), and malondialdehyde (MDA), with applied As revealed the potential of B. nivea for As decontamination. By employing the metabolic machinery of B. nivea, As was sustainably removed from the contaminated areas

A Comparative Study of Land Cover Classification by Using Multispectral and Texture Data

The main objective of this study is to find out the importance of machine vision approach for the classification of five types of land cover data such as bare land, desert rangeland, green pasture, fertile cultivated land, and Sutlej river land. A novel spectra-statistical framework is designed to classify the subjective land cover data types accurately. Multispectral data of these land covers were acquired by using a handheld device named multispectral radiometer in the form of five spectral bands (blue, green, red, near infrared, and shortwave infrared) while texture data were acquired with a digital camera by the transformation of acquired images into 229 texture features for each image. The most discriminant 30 features of each image were obtained by integrating the three statistical features selection techniques such as Fisher, Probability of Error plus Average Correlation, and Mutual Information (F + PA + MI). Selected texture data clustering was verified by nonlinear discriminant analysis while linear discriminant analysis approach was applied for multispectral data. For classification, the texture and multispectral data were deployed to artificial neural network (ANN: n-class). By implementing a cross validation method (80-20), we received an accuracy of 91.332% for texture data and 96.40% for multispectral data, respectively