Progressive resistance training ameliorates deteriorating cardiac autonomic dysfunction, subclinical inflammation and endothelial dysfunction in type 2 diabetes mellitus: A randomized control trial.

BACKGROUND AND AIMS: To investigate the effect of resistance training (RT) on outcomes of cardiac autonomic control, biomarkers of subclinical inflammation, endothelial dysfunction, and angiotensin II in T2DM patients with CAN. METHODS: Fifty six T2DM patients with CAN were recruited in the present study.After baseline assessment of all outcome variables, patients were randomly allocated into two groups - RT (n = 28) and Control (n = 28). The experimental group underwent 12 weeks of RT and the control group received usual care. RT was performed at an intensity of 65%-75% of 1 RM, 3 times/week for 12 weeks. RT program included 10 exercises of major muscle groups in the body. Cardiac autonomic control parameters, subclinical inflammation and endothelial dysfunction biomarkers, and serum angiotensin II concentration were assessed at baseline and after 12 weeks. RESULTS: Parameters of cardiac autonomic control showed significant improvement after RT (p < 0.05). Interleukin-6, interleukin-18 were significantly reduced while endothelial nitric oxide synthase was significantly increased post-RT (p < 0.05). CONCLUSIONS: Findings of the present study suggest that RT has the potential to enhance deteriorating cardiac autonomic function in T2DM patients with CAN. RT also seems to have an anti-inflammatory role and it may also play some role in vascular remodeling in these patients. TRIAL REGISTRATION: CTRI/2018/04/013321, Registered prospectively on 13th April 2018, Clinical Trial Registry, India.

Biosimilar Tenecteplase Versus Alteplase in Acute Ischemic Stroke: A Real World Study.

Background and Purpose: There is an unmet need for a more effective thrombolytic agent in acute ischemic stroke (AIS) management. Various studies and meta-analysis suggest tenecteplase (TNK) as non-inferior over alteplase (rTPA). The present single-center study compares biosimilar TNK and rTPA in a tertiary care setting. Methods: Data of patients who presented with AIS and underwent intravenous thrombolysis (IVT) were recruited retrospectively from January 2018 to July 2021. Primary efficacy outcome was a modified Rankin score (mRS) at 90 days dichotomized at < = 2. Qualitative and quantitative variables were assessed using Chi-square test and Student's t-test, respectively. Results: A total of 160 patients, 103 in the rTPA and 57 in TNK group, were analyzed. The baseline characteristics were well matched apart from hypertension. Large artery atherosclerosis was the most frequent subtype of stroke among the two groups. Good functional outcome was seen in 47.92% of patients TNK and 64.77% of patients in rTPA group (p = 0.069). No difference was seen in the rates of any ICH (p = 0.29) and mortality at 3 months (p = 0.32) among the two groups. Conclusion: This present study observed no difference in the efficacy and safety between biosimilar TNK and rTPA. Our findings are in concordance with published trials showing equivalence between the two molecules.

Post-Vaccination/Post-COVID Immune-Mediated Demyelination of the Brain and Spinal Cord: A Novel Neuroimaging Finding.

Introduction: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19), which not only produces respiratory symptoms but is known to involve almost every system, and its neuroinvasive properties have been well demonstrated throughout the pandemic. Also, to combat the pandemic, there was rapid development and induction of various vaccination drives, following which many adverse events following immunization (AEFIs) have been reported, which include neurological complications as well. Method: We present a series of three cases, post vaccination, with and without a history of COVID illness that showed remarkably similar findings on magnetic resonance imaging (MRI). Result: A 38-year-old male presented with complaints of weakness of the bilateral lower limbs with sensory loss and bladder disturbance a day after receiving his first dose of ChadOx1 nCoV-19 (COVISHIELD) vaccine. A 50-year-old male with hypothyroidism characterized by autoimmune thyroiditis and impaired glucose tolerance experienced difficulty in walking 11.5 weeks after being administered with COVID vaccine (COVAXIN). A 38-year-old male presented with subacute onset progressive symmetric quadriparesis 2 months after their first dose of a COVID vaccine. The patient also had sensory ataxia, and his vibration sensation was impaired below C7. All three patients had typical pattern of involvement of the brain and spine on MRI with signal changes in bilateral corticospinal tracts, trigeminal tracts in the brain, and both lateral and posterior columns in the spine. Conclusion: This pattern of brain and spine involvement on MRI is a novel finding and is likely a result of post-vaccination/post-COVID immune-mediated demyelination.

SALT: transfer learning-based threat model for attack detection in smart home.

The next whooping revolution after the Internet is its scion, the Internet of Things (IoT), which has facilitated every entity the power to connect to the web. However, this magnifying depth of the digital pool oil the wheels for the attackers to penetrate. Thus, these threats and attacks have become a prime concern among researchers. With promising features, Machine Learning (ML) has been the solution throughout to detect these threats. But, the general ML-based solutions have been declining with the practical implementation to detect unknown threats due to changes in domains, different distributions, long training time, and lack of labelled data. To tackle the aforementioned issues, Transfer Learning (TL) has emerged as a viable solution. Motivated by the facts, this article aims to leverage TL-based strategies to get better the learning classifiers to detect known and unknown threats targeting IoT systems. TL transfers the knowledge attained while learning a task to expedite the learning of new similar tasks/problems. This article proposes a learning-based threat model for attack detection in the Smart Home environment (SALT). It uses the knowledge of known threats in the source domain (labelled data) to detect the unknown threats in the target domain (unlabelled data). The proposed scheme addresses the workable differences in feature space distribution or the ratio of attack instances to a normal one, or both. The proposed threat model would show the implying competence of ML with the TL scheme to improve the robustness of learning classifiers besides the threat variants to detect known and unknown threats. The performance analysis shows that traditional schemes underperform for unknown threat variants with accuracy dropping to 39% and recall to 56.

Characterization of potentially inappropriate medications use in Indian elderly population and their impact on quality of life using Beers criteria.

Background: Polypharmacy is principal cause of potentially inappropriate medications (PIMs) in elderly patients, which include over prescribing, under prescribing, and misprescribing. Methods: Elderly subjects (≥60 years), of either sex, receiving two or more medications for one or more chronic ailments, attending Geriatrics Outpatient Department (OPD), at All India Institute of Medical Sciences (AIIMS) New Delhi, were included. Their prescriptions were assessed for PIMs by using Beers criteria 2015 and were further followed up at least once in 6 months for adverse events, telephonically. The results were analyzed by using suitable regression models and correlation analysis. Results: Three hundred eighty patients average age of 65.4 ± 4.7 years were enrolled. Eighty-eight percent of the people were having greater than or equal to two ailments. Each patient was prescribed 6.7 ± 2.1 medications with 65% of prescriptions having one or more PIMs. Out of the total prescribed drugs, 15% were satisfying Beers criteria for PIMs. There were 63 adverse drug reactions (ADRs) reported. A statistically significant correlation was observed among comorbidities, number of prescribed medications, PIMs, and ADRs. Quality of life (QOL) of the elderly patients was negatively corelated with polypharmacy and female sex. Conclusion: A risk-benefit analysis of prescribed medications is part and parcel of prescribing, especially in elderly patients. In order to decrease further risks associated with inappropriate prescribing, there is need for indigenous guidelines and intensive training.

Assessment of rationality of available fixed dose combinations of antibiotics in India.

OBJECTIVE: India is among the largest consumers of antibiotics. Easy availability and growing sales of Fixed Dose Combinations (FDCs) of antibiotics can worsen Antimicrobial Resistance (AMR). There is lack of comprehensive data on available antibiotic FDC formulations, their dose strengths and adequacy of scientific evidence regarding their efficacy, safety and suitability for human use. In the present work, we aimed at addressing this knowledge gap. METHODS: Availability of FDCs was ascertained from the Current Index of Medical Specialties (CIMS) [Issue Jan-April 2020]. Customized data abstraction form was used to capture pertinent information for these FDCs. Assessment of rationality was done based on standard parameters. RESULTS: More than 90% of the existing FDCs were found to be irrational; with two third of them being unapproved and or banned from use in the country. CONCLUSIONS: Although the regulatory agency has already taken cognizance of the seriousness of the matter; there is an urgent need to revisit these FDCs to promote prudent antibiotic use.High antibiotic use is associated with antimicrobial resistance; it is imperative that all factors which lead to high antibiotic use are adequately addressed. Easy availability of fixed dose combinations (FDCs) has begun to catch the attention of regulators in developing economies like India leading to a ban of 330 FDCs of which 19% were antibiotic combinations. The continuing presence and increasing sales of these irrational FDCs is a concern for effective antimicrobial stewardship.

Internet of Things: Evolution, Concerns and Security Challenges.

The escalated growth of the Internet of Things (IoT) has started to reform and reshape our lives. The deployment of a large number of objects adhered to the internet has unlocked the vision of the smart world around us, thereby paving a road towards automation and humongous data generation and collection. This automation and continuous explosion of personal and professional information to the digital world provides a potent ground to the adversaries to perform numerous cyber-attacks, thus making security in IoT a sizeable concern. Hence, timely detection and prevention of such threats are pre-requisites to prevent serious consequences. The survey conducted provides a brief insight into the technology with prime attention towards the various attacks and anomalies and their detection based on the intelligent intrusion detection system (IDS). The comprehensive look-over presented in this paper provides an in-depth analysis and assessment of diverse machine learning and deep learning-based network intrusion detection system (NIDS). Additionally, a case study of healthcare in IoT is presented. The study depicts the architecture, security, and privacy issues and application of learning paradigms in this sector. The research assessment is finally concluded by listing the results derived from the literature. Additionally, the paper discusses numerous research challenges to allow further rectifications in the approaches to deal with unusual complications.

An environmental screening model to assess the consequences to soil and groundwater from railroad-tank-car spills of light non-aqueous phase liquids.

North American railroads transport a wide variety of chemicals, chemical mixtures and solutions in railroad tank cars. In the event of an accident, these materials may be spilled and impact the environment. Among the chemicals commonly transported are a number of light non-aqueous phase liquids (LNAPLs). If these are spilled they can contaminate soil and groundwater and result in costly cleanups. Railroads need a means of objectively assessing the relative risk to the environment due to spills of these different materials. Environmental models are often used to determine the extent of contamination, and the associated environmental risks. For LNAPL spills, these models must account for NAPL infiltration and redistribution, NAPL dissolution and volatilization, and remediation systems such as pump and treat. This study presents the development and application of an environmental screening model to assess NAPL infiltration and redistribution in soils and groundwater, and to assess groundwater cleanup time using a pumping system. Model simulations use parameters and conditions representing LNAPL releases from railroad tank cars. To take into account unique features of railroad-tank-car spill sites, the hydrocarbon spill screening model (HSSM), which assumes a circular surface spill area and a circular NAPL lens, was modified to account for a rectangular spill area and corresponding lens shape at the groundwater table, as well as the effects of excavation and NAPL evaporation to the atmosphere. The modified HSSM was first used to simulate NAPL infiltration and redistribution. A NAPL dissolution and groundwater transport module, and a pumping system module were then implemented and used to simulate the effects of chemical properties, excavation, and free NAPL removal on NAPL redistribution and cleanup time. The amount of NAPL that reached the groundwater table was greater in coarse sand with high permeability than in fine sand or silt with lower permeabilities. Excavation can reduce the amount of NAPL that reaches the groundwater more effectively in lower permeability soils. The effect of chemical properties including vapor pressure and the ratio of density to viscosity become more important in fine sand and silt soil due to slow NAPL movement in the vadose zone. As expected, a pumping system was effective for high solubility chemicals, but it was not effective for low solubility chemicals due to rate-limited mass transfer by transverse dispersion and flow bypassing. Free NAPL removal can improve the removal efficiency for moderately low solubility chemicals like benzene, but cleanup times even after free NAPL removal can be prolonged for very low solubility chemicals like cyclohexane and styrene.

Contrast-enhanced flair imaging in the evaluation of infectious leptomeningeal diseases.

PURPOSE: The purpose of our study was to compare contrast-enhanced fluid-attenuated inversion recovery (FLAIR) images with contrast-enhanced T1 weighted images for infectious leptomeningitis. MATERIALS AND METHODS: We studied twenty-four patients with a clinical suspicion of infectious meningitis with unenhanced FLAIR, contrast-enhanced T1 weighted and contrast-enhanced FLAIR MR sequences. Twelve patients had cytologic and biochemical diagnosis of meningitis on cerebrospinal fluid (CSF) examination obtained 48 h before or after the MR study. Sequences were considered positive if abnormal signal was seen in the subarachnoid space (cistern or sulci) or along pial surface. RESULTS: Twenty-seven examinations in 24 patients were performed. Of the 12 patients (thirteen studies) in whom cytology was positive, unenhanced FLAIR images were positive in six cases (sensitivity 46%), contrast-enhanced FLAIR images were positive in 11 (sensitivity 85%), and contrast-enhanced T1 weighted MR images were positive in 11 patients (sensitivity 85%). Of the 12 patients (14 studies) in whom cerebrospinal fluid study was negative, unenhanced FLAIR images were negative in 13, contrast-enhanced FLAIR images were negative in 11, and contrast-enhanced T1 weighted MR images were negative in eight. Thus, the specificity of unenhanced FLAIR, contrast-enhanced FLAIR and contrast-enhanced T1 weighted images was 93, 79 and 57%, respectively. CONCLUSION: Our results suggest that post-contrast FLAIR images have similar sensitivity but a higher specificity compared to contrast-enhanced T1 weighted images for detection of leptomeningeal enhancement. It can be a useful adjunct to post-contrast T1 weighted images in evaluation of infectious leptomeningitis.