Health Block: A Blockchain Based Secure Healthcare Data Storage and Retrieval System for Cloud Computing

Data in healthcare domain is highly sensitive in nature. Besides, there is need for maintaining integrity of such data. Blockchain technology has emerged to solve the problem of data integrity and non-repudiation with immutable storage in distributed repository. Thus secure data storage and retrieval in cloud environments is made possible using blockchain implementation. There are many existing healthcare systems with blockchain integration found in the literature. However, there is need for a system that supports complete set of operations that are governed by smart contracts. Another important consideration is that end users should be able to operate healthcare system without the need for knowledge of blockchain technology. Towards this end, in this paper, we proposed a Blockchain based secure healthcare data storage and retrieval system known as HealthBlock for cloud computing environments. We defined smart contract with underlying structures and functions using Solidity language for Ethereum blockchain platform. We also proposed and implemented an algorithm known as Healthcare Transactions over Blockchain (HToB). This algorithm supports secure blockchain based data storage and retrieval governed by smart contracts. Our system is evaluated using user-friendly web based client application. The experimental results showed that our system is able to ensure data integrity and non-repudiation besides reaping all benefits of blockchain technology

The Clinical Features and Progression of Late-Onset Versus Younger-Onset in an Adult Cohort of Huntington's Disease Patients.

BACKGROUND: Huntington's disease (HD) is an autosomal dominant neurodegenerative disorder that typically manifests between the ages of 30 and 50 years. However, the disease can present at any age, and phenotypic differences between younger and later-onset patients have received limited attention. OBJECTIVE: To compare clinical features of late- (>70 years of age) and younger-onset (<30 years of age) HD patients. METHODS: Patients presenting to our regional NHS HD clinic with new-onset manifest HD diagnosed over the age of 70 years (LoHD) (n = 18) were compared with a younger cohort who developed disease under the age of 30 years (YoHD) (n = 12). Rate of progression over time on standard cognitive and motor measures was compared. RESULTS: At first clinic presentation, both groups had the same total UHDRS scores. However, the LoHD group had higher chorea scores (F (1,28) = 6.52, p = 0.016), while the YoHD group had more dystonia (F (1,28) = 8.69, p = 0.006) and eye movement abnormalities (F (1,28) = 16.991, p < 0.001). The YoHD group also had a greater rate of motor progression, especially for bulbar measures (F (1, 28) = 6.96, p = 0.013) and bradykinesia (F (1, 28) = 7.99, p = 0.009). No differences were found in the rate of cognitive change (F (1,21) = 1.727, p = 0.203) nor functional capacity (F (1,28) = 1.388, p = 0.249) between the groups. CONCLUSION: Phenotypic differences between YoHD and LoHD patients were found in terms of initial presentation and rate of motor progression. This has implications for therapeutic trials involving HD patients of different ages, given their different clinical features and progression.SLM is funded by the Huntington’s Disease Association. RAB is supported by the National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre, 146281 (the views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care) and MRC/WT Stem Cell Institute 203151/Z/16/Z

Medical students consulting from home: A qualitative evaluation of a tool for maintaining student exposure to patients during lockdown.

INTRODUCTION: Lockdowns during the COVID-19 pandemic had a disruptive effect on medical education when they prevented medical students accessing real patients. To address this, we piloted 35 medical students at home consulting remotely with patients. METHOD: We evaluated the intervention using qualitative analysis of post-experience interviews with a sample of 13 students and 10 clinical supervisors. RESULTS: The experience was perceived by all those interviewed to be both acceptable and educationally valuable. Data analysis revealed different models of implementation according to type of patients involved (acute, recently treated or expert patients) and type of communication platform used (AccuRx, Microsoft Teams or telephone). Practical and educational challenges were identified in relation to the following elements of the experience: patients consulting with students remotely, students being remotely supervised and students undertaking patient contact from home. Strategies for addressing these challenges were directly suggested by interviewees and also inferred from our analysis of the data. CONCLUSIONS: Remotely supervised medical students at home undertaking remote consultations with patients can be acceptable and educationally valuable. The intervention was piloted in a UK graduate entry medical course and so it would be useful to replicate this study in other medical student populations

Relation between TRP2 allele in COL9A2 gene and lumber disc degeneration in a subset of North Indian population

Introduction: Lumbar disc prolapse is a disease in which the inner segment of disc ruptures from the outer segment. The disc prolapse starts as a result of lumbar disc degeneration (LDD). Various genetic factors were identified predisposing to higher risk of developing LDD. COL9A2 polymorphism is assuming a major role in the etiology of lumbar disc prolapse. Aim: This study was aimed to find the distribution of this polymorphism in the north Indian population and its true association with this disease. Methods: A total of 200 subjects (100 cases and 100 controls) were considered for this study. The cases were patients with complaint of low back pain who came to Rama Medical College Hospital and Research Centre, Kanpur between March 2018 and February 2020. The diagnosis of LDD was made by Magnetic resonance imaging (MRI) and clinical examination. The controls were volunteers (age matched), with no history of back pain or any other symptoms. Blood samples were collected from all subjects and DNA analysis was performed. Statistical analyses were analysed using SPSS version 22 (SPSS, USA).Odds Ratio (OR) with 95% Confidence Interval (CI) was applied to quantify the association of Trp2 allele to the Lumbar disc disease. Fisher’s exact test was used to find statistical significance of contingency table counts, with a p-value<0.05 as significant. Results: Mean ages of cases and controls (in years) were 43±12.6 and 42.5±13.8 respectively. BMI(kg/m2) of cases and controls were 23.71±4.27 and 22.93±3.87 respectively. The COL9A2 polymorphism was present in both cases and control. We found a 2.39 fold increase in the odds ratio of LDD when Trp2 allele present, OR 2.39 (1.06-5.38), p=0.03. Conclusion: The present study concluded that single nucleotide polymorphism in gene COL9A2 was found to be associated with the development of lumbar disc disease in the north Indian population

Chandrayaan-3 Alternate Landing Site: Pre-Landing Characterisation

India's third Moon mission Chandrayaan 3 will deploy a lander and a rover at a high latitude location of the Moon enabling us to carry out first ever in-situ science investigations of such a pristine location that will potentially improve our understanding on primary crust formation and subsequent modification processes. The primary landing site (PLS), is situated at 69.367621 degS, 32.348126 degE. As a contingency, an alternate landing site (ALS) was also selected at nearly the same latitude but nearly 450 km west to PLS. In this work, a detailed study of the geomorphology, composition, and temperature characteristics of ALS has been carried out using the best-ever high resolution Chandrayaan 2 OHRC DEMs and Ortho images, datasets obtained from Chandrayaan 1 and on-going Lunar Reconnaissance Orbiter. For understanding the thermophysical behaviour, we used a well-established thermophysical model. We found that the Chandrayaan 3 ALS is characterised by a smooth topography with an elevated central part. The ALS is a scientifically interesting site with a high possibility of sampling ejecta materials from Tycho and Moretus. Based on the spectral and elemental analysis of the site, Fe is found to be near approx. 4.8 wt.%, with Mg approx. 5 wt.%, and Ca approx. 11 wt.%. Compositionally, ALS is similar to PLS with a highland soil composition. Spatial and diurnal variability of around 40 K and 175 K has been observed in the surface temperatures at ALS. Although belonging to similar location like PLS, ALS showed reduced daytime temperatures and enhanced night-time temperatures compared to PLS, indicating a terrain of distinctive thermophysical characteristics. Like PLS, ALS is also seems to be an interesting site for science investigations and Chandrayaan 3 is expected to provide new insights into the understanding of lunar science even if it happens to land in the alternate landing site.Comment: 13 pages, 7 figure

Data-driven wildfire risk prediction in northern california

Over the years, rampant wildfires have plagued the state of California, creating economic and environmental loss. In 2018, wildfires cost nearly 800 million dollars in economic loss and claimed more than 100 lives in California. Over 1.6 million acres of land has burned and caused large sums of environmental damage. Although, recently, researchers have introduced machine learning models and algorithms in predicting the wildfire risks, these results focused on special perspectives and were restricted to a limited number of data parameters. In this paper, we have proposed two data-driven machine learning approaches based on random forest models to predict the wildfire risk at areas near Monticello and Winters, California. This study demonstrated how the models were developed and applied with comprehensive data parameters such as powerlines, terrain, and vegetation in different perspectives that improved the spatial and temporal accuracy in predicting the risk of wildfire including fire ignition. The combined model uses the spatial and the temporal parameters as a single combined dataset to train and predict the fire risk, whereas the ensemble model was fed separate parameters that were later stacked to work as a single model. Our experiment shows that the combined model produced better results compared to the ensemble of random forest models on separate spatial data in terms of accuracy. The models were validated with Receiver Operating Characteristic (ROC) curves, learning curves, and evaluation metrics such as: accuracy, confusion matrices, and classification report. The study results showed and achieved cutting-edge accuracy of 92% in predicting the wildfire risks, including ignition by utilizing the regional spatial and temporal data along with standard data parameters in Northern California

ANTIBIOGRAM PROFILING OF HELICOBACTER PYLORI STRAINS AND THE EFFICACY OF BRASSICA CAPITATA AGAINST RESISTANT STRAINS ISOLATED FROM THE PATIENTS SUFFERING FROM GASTRODUODENAL DISEASES IN GUWAHATI, ASSAM

  Objective: Helicobacter pylori resistance toward commonly used antibiotics is increasing leading to the treatment failure; hence, our aim is to determine the antibiogram susceptibility pattern of H. pylori strains isolated from Guwahati, Assam (Northeast India) and also to test the efficacy of the Brassica capitata against the multi and dual drug-resistant strains of North and Northeast India.Methods: Minimum inhibitory concentration of different antibiotics was determined by agar dilution method. Disc diffusion method was used to check the efficacy of B. capitata against clarithromycin (CLR), metronidazole (MTZ), and levofloxacin (LEV)-resistant H. pylori strains.Results: All the H. pylori strains were 100% sensitive to CLR, tetracycline, amoxicillin, and furazolidone. 72.8% of the strains were sensitive toward MTZ and 54.5% were sensitive toward LEV. B. capitata showed good efficacy against the resistant strains of H. pylori of North and Northeast India.Conclusion: Most of the H. pylori strains from Northeast India were sensitive toward the commonly used antibiotics for the treatment regime. B. capitata is effective against H. pylori infection, suggesting its potential as an alternative therapy, and opens the way for further studies on identification of novel antimicrobial targets of B. capitata

Adoption of BIM by architectural firms in India: technology–organization–environment perspective

Building information modelling (BIM) is being heralded as a remarkable innovation in the built environment sector with expectations of lofty sector-wide improvements. Some countries have shown remarkable levels of uptake of BIM, along the way documenting some evidence of benefits stemming from BIM. However, countries such as India and China are late entrants in the BIM adoption journey and are seeing a slower adoption rate. This study develops a model using the technology–organization–environment framework to study the factors influencing BIM adoption by architectural firms in India and reasons for this slow adoption. The proposed model of BIM adoption is tested using the partial least square method against responses collected from 184 industry professionals based in India. Findings reveal that the adoption of BIM by Indian architectural firms is at the ‘experimentation’ stage with variables such as expertise, trialability, and management support exhibiting a strong positive influence on BIM adoption. The study also explains the status of BIM adoption in India with the help of a multi-level social construct, which places the level of BIM adoption in India between the micro- and meso-levels of organizational scales. Similarities and dissimilarities with previous findings are discussed in the paper to highlight the findings of this study. © 2016 Informa UK Limited, trading as Taylor & Francis Grou

Major Advances in Monkeypox Vaccine Research and Development – An Update

Monkeypox (MPX) is a zoonotic disease that is endemic to the western and central regions of Africa and it is caused by monkeypox virus (MPXV), which is classified as a member of the Poxviridae family, specifically the Chordopoxvirinae subfamily, and the Orthopoxvirus genus. The current multiregional outbreak of MPX, which started in May of 2022, has since swiftly spread across the globe and thus has been declared a global public health emergency by the World Health Organization (WHO). Protective immunity against MPXV can be achieved by administering a smallpox vaccination, as the two viruses share antigenic properties. Although smallpox was declared eradicated in 1980, the vaccine campaign was halted the following year, leaving the population with significantly less immunity than it had before. The potential for human-to-human transmission of MPXV has grown as a result. Due to the lack of a particular treatment for MPX infection, anti-viral medications initially designed for the smallpox virus are being employed. However, the prognosis for MPX may vary depending on factors like immunization history, pre-existing illnesses, and comorbidities, even though the majority of persons who develop MPX have a mild, self-limiting illness. Vaccines and antiviral drugs are being researched as potential responses to the latest 2022 MPX epidemic. The first-generation smallpox vaccinations maintained in national stockpiles of several countries are not recommended due to not meeting the current safety and manufacturing criteria, as stated by the WHO. Newer, safer (second- and third-generation) smallpox vaccines, such as JYNNEOSTM, which has been licensed for the prevention of MPX, are indicated as potentially useful in the interim guideline. Studies on vaccines and antiviral drugs are still being investigated as possible remedies to the recent MPX outbreak. This mini-review article serves as a retrospective look at the evolution of smallpox vaccines from their inception in the 1700s to the current trends up to the end of year 2022, specifically for developing monkeypox vaccines