Chromium stress in Brassica juncea L. cv. 'Pusa Jai Kissan' under hydroponic culture

Chromium (Cr) entering plant tissue inhibits most physiological processes at all levels of metabolism including inhibition of growth, photosynthesis and nitrate assimilation. Since Cr exists in many forms, its toxicity to plants depends on its valence state, with Cr (VI) found to be highly toxic and mobile than Cr (III). Different concentrations of Cr (0, 25, 50 and 100 μM) in the form of K2Cr2O7 was added to 30 days old Brassica juncea plant and harvested on the 3rd and 5th days after treatment for estimation of plant growth, chlorophyll, total soluble protein, free amino acids and nitrate reductase activity. Cr was found to cause deleterious effects on whole plant growth. The potential of plants with the capacity to accumulate or to stabilize Cr compounds for bioremediation of Cr contamination has gained interest in recent years. The biochemical aspects like photosynthetic pigments (Chl a and Chl b), total protein and amino acids content decreased with Cr concentration. A significant increase in nitrate reductase activity was observed corresponding to Cr concentration.Key words: Brassica juncea, chromium, heavy metal, phytoremediation

Determination of the Processes Driving the Acquisition of Immunity to Malaria Using a Mathematical Transmission Model

Acquisition of partially protective immunity is a dominant feature of the epidemiology of malaria among exposed individuals. The processes that determine the acquisition of immunity to clinical disease and to asymptomatic carriage of malaria parasites are poorly understood, in part because of a lack of validated immunological markers of protection. Using mathematical models, we seek to better understand the processes that determine observed epidemiological patterns. We have developed an age-structured mathematical model of malaria transmission in which acquired immunity can act in three ways (“immunity functions”): reducing the probability of clinical disease, speeding the clearance of parasites, and increasing tolerance to subpatent infections. Each immunity function was allowed to vary in efficacy depending on both age and malaria transmission intensity. The results were compared to age patterns of parasite prevalence and clinical disease in endemic settings in northeastern Tanzania and The Gambia. Two types of immune function were required to reproduce the epidemiological age-prevalence curves seen in the empirical data; a form of clinical immunity that reduces susceptibility to clinical disease and develops with age and exposure (with half-life of the order of five years or more) and a form of anti-parasite immunity which results in more rapid clearance of parasitaemia, is acquired later in life and is longer lasting (half-life of >20 y). The development of anti-parasite immunity better reproduced observed epidemiological patterns if it was dominated by age-dependent physiological processes rather than by the magnitude of exposure (provided some exposure occurs). Tolerance to subpatent infections was not required to explain the empirical data. The model comprising immunity to clinical disease which develops early in life and is exposure-dependent, and anti-parasite immunity which develops later in life and is not dependent on the magnitude of exposure, appears to best reproduce the pattern of parasite prevalence and clinical disease by age in different malaria transmission settings. Understanding the effector mechanisms underlying these two immune functions will assist in the design of transmission-reducing interventions against malaria

Loss of Population Levels of Immunity to Malaria as a Result of Exposure-Reducing Interventions: Consequences for Interpretation of Disease Trends

BACKGROUND: The persistence of malaria as an endemic infection and one of the major causes of childhood death in most parts of Africa has lead to a radical new call for a global effort towards eradication. With the deployment of a highly effective vaccine still some years away, there has been an increased focus on interventions which reduce exposure to infection in the individual and -by reducing onward transmission-at the population level. The development of appropriate monitoring of these interventions requires an understanding of the timescales of their effect. METHODS & FINDINGS: Using a mathematical model for malaria transmission which incorporates the acquisition and loss of both clinical and parasite immunity, we explore the impact of the trade-off between reduction in exposure and decreased development of immunity on the dynamics of disease following a transmission-reducing intervention such as insecticide-treated nets. Our model predicts that initially rapid reductions in clinical disease incidence will be observed as transmission is reduced in a highly immune population. However, these benefits in the first 5-10 years after the intervention may be offset by a greater burden of disease decades later as immunity at the population level is gradually lost. The negative impact of having fewer immune individuals in the population can be counterbalanced either by the implementation of highly-effective transmission-reducing interventions (such as the combined use of insecticide-treated nets and insecticide residual sprays) for an indefinite period or the concurrent use of a pre-erythrocytic stage vaccine or prophylactic therapy in children to protect those at risk from disease as immunity is lost in the population. CONCLUSIONS: Effective interventions will result in rapid decreases in clinical disease across all transmission settings while population-level immunity is maintained but may subsequently result in increases in clinical disease many years later as population-level immunity is lost. A dynamic, evolving intervention programme will therefore be necessary to secure substantial, stable reductions in malaria transmission

Complex cytogenetic rearrangements at the DURS1 locus in syndromic Duane retraction syndrome

Key Clinical Message A patient with syndromic Duane retraction syndrome harbors a chromosome 811.1q13.2 inversion and 8p11.1-q12.3 marker chromosome containing subregions with differing mosaicism and allele frequencies. This case highlights the potential requirement for multiple genetic methods to gain insight into genotype–phenotype correlation, and ultimately into molecular mechanisms that underlie human disease

A survey study on the assessment of food handler’s compliance to personal hygiene practices regulation in selected Malaysia food outlets

Food safety remains a major issue around the world particularly when the COVID-19 pandemic becomes the main issue nowadays. Food safety is essential to the human population worldwide because food is the primary energy source and nutrition for humans. Therefore, food handlers' personal hygiene is one of the factors that are necessary to maintain food safety. The purpose of this study was to assess the food handler’s compliance with personal hygiene practices in randomly any food outlets across Malaysia including Kuching, Sarawak; Lawas, Sarawak; Johor Bahru, Johor; Kuala Penyu, Sabah, and Gurun, Kedah. A quantitative method, a cross-sectional descriptive study to one thousand and five (N = 1005) food handlers who participated in the questionnaire and observation checklist was developed by modifying questions in accordance with the Food Hygiene Regulations 2009. Overall, the mean percentage of conformity in adhering to food handler attire was the highest observed at Gurun, Kedah and Kuala Penyu, Sabah with 86.96% and 80.79%, respectively, followed by Kuching, Sarawak with 77.5%, Johor Bahru with 76.71%, and Lawas, Sarawak with 74.93%. Personal hygiene practices conformity showed a high mean percentage with all districts scoring >91% higher than non-conformity. The food handlers also show less unhygienic behaviour while on duty and scored a mean percentage of > 92%. Although in that positive behaviour, some of the food handlers did not perform some unhygienic practices (≤ 8 %). In conclusion, there is no significant difference (p-value > 0.05) in the level of conformity between the mean percentages among all districts. Thus, this issue shall raise a concern to the food industries in order to make sure their workers comply with the legal requirement and to avoid any food poisoning outbreak related to food hygiene and food safety in the future

Vascular Implications of COVID-19: Role of Radiological Imaging, Artificial Intelligence, and Tissue Characterization: A Special Report

The SARS-CoV-2 virus has caused a pandemic, infecting nearly 80 million people worldwide, with mortality exceeding six million. The average survival span is just 14 days from the time the symptoms become aggressive. The present study delineates the deep-driven vascular damage in the pulmonary, renal, coronary, and carotid vessels due to SARS-CoV-2. This special report addresses an important gap in the literature in understanding (i) the pathophysiology of vascular damage and the role of medical imaging in the visualization of the damage caused by SARS-CoV-2, and (ii) further understanding the severity of COVID-19 using artificial intelligence (AI)-based tissue characterization (TC). PRISMA was used to select 296 studies for AI-based TC. Radiological imaging techniques such as magnetic resonance imaging (MRI), computed tomography (CT), and ultrasound were selected for imaging of the vasculature infected by COVID-19. Four kinds of hypotheses are presented for showing the vascular damage in radiological images due to COVID-19. Three kinds of AI models, namely, machine learning, deep learning, and transfer learning, are used for TC. Further, the study presents recommendations for improving AI-based architectures for vascular studies. We conclude that the process of vascular damage due to COVID-19 has similarities across vessel types, even though it results in multi-organ dysfunction. Although the mortality rate is ~2% of those infected, the long-term effect of COVID-19 needs monitoring to avoid deaths. AI seems to be penetrating the health care industry at warp speed, and we expect to see an emerging role in patient care, reduce the mortality and morbidity rate

The embryonic development of orange mud crab, Scylla olivacea (Herbst, 1796) held in the captivity

This study attempts to observe and record early embryonic developments of the orange mud crab, Scylla olivacea. The period taken by the eggs to hatch was 8 days and the colour of the eggs gradually changed from yellow to brown, gray and dark gray. During the embryonic development, the developing embryos reached the blastula stage within 24 hours with a mean egg diameter of 329.91 ± 6.62 µm. The embryo developed into the gastrula stage on the 2nd day with a mean egg diameter of 337.10 ± 8.37 µm. Eyes were consequently observed on the 3rd day and there was a further increase in the yolk-free portion with a mean egg diameter of 338.16 ± 6.57 µm. On the 4th day, the eye-spot became crescent and there was a clearer tissue formation with a mean egg diameter of 358.45 ± 14.80 µm. Meanwhile, on the 7th day prior hatching, there were many chromatophores present, mostly dark in colour and the yolk granules had further reduced in size. The heart beats faster than previous days before and the embryo occupied most of the available egg volume with a mean egg diameter of 377.26 ± 11.50 µm

Economics of Artificial Intelligence in Healthcare: Diagnosis vs. Treatment

Motivation: The price of medical treatment continues to rise due to (i) an increasing population; (ii) an aging human growth; (iii) disease prevalence; (iv) a rise in the frequency of patients that utilize health care services; and (v) increase in the price. Objective: Artificial Intelligence (AI) is already well-known for its superiority in various healthcare applications, including the segmentation of lesions in images, speech recognition, smartphone personal assistants, navigation, ride-sharing apps, and many more. Our study is based on two hypotheses: (i) AI offers more economic solutions compared to conventional methods; (ii) AI treatment offers stronger economics compared to AI diagnosis. This novel study aims to evaluate AI technology in the context of healthcare costs, namely in the areas of diagnosis and treatment, and then compare it to the traditional or non-AI-based approaches. Methodology: PRISMA was used to select the best 200 studies for AI in healthcare with a primary focus on cost reduction, especially towards diagnosis and treatment. We defined the diagnosis and treatment architectures, investigated their characteristics, and categorized the roles that AI plays in the diagnostic and therapeutic paradigms. We experimented with various combinations of different assumptions by integrating AI and then comparing it against conventional costs. Lastly, we dwell on three powerful future concepts of AI, namely, pruning, bias, explainability, and regulatory approvals of AI systems. Conclusions: The model shows tremendous cost savings using AI tools in diagnosis and treatment. The economics of AI can be improved by incorporating pruning, reduction in AI bias, explainability, and regulatory approvals. © 2022 by the authors

Electric and Magnetic Fields for the Proposed Microstrip Antenna with DGS for Breast Cancer Detection

This paper presents the design of microstrip antenna with defected ground structure (DGS) for the detection of breast tumor in microwave imaging system at operating frequency of 2.45GHz. Four types of microstrip patch antennas have been designed using microstrip feed inset with grounding patches at 2.45 GHz operating frequency using dielectric substrates, FR4 (ɛr = 4.4 F / m). The results are collected via the intensity of electric (E), magnetic fields (H) and current densities. The antenna is examined with a 3D breast model structure with specific dielectric value and conductivity. From the results, it shows that antenna with design structure, Design 4 produce a good intensities values of both E and H fields respectively with the presence of the tumour, and gives the value of 7083 V/m and 35.5 A/m while without the presence of tumour is 7186 V/m and 35.8 A/m compare to other proposed antennas

Acute kidney disease and renal recovery : consensus report of the Acute Disease Quality Initiative (ADQI) 16 Workgroup

Consensus definitions have been reached for both acute kidney injury (AKI) and chronic kidney disease (CKD) and these definitions are now routinely used in research and clinical practice. The KDIGO guideline defines AKI as an abrupt decrease in kidney function occurring over 7 days or less, whereas CKD is defined by the persistence of kidney disease for a period of > 90 days. AKI and CKD are increasingly recognized as related entities and in some instances probably represent a continuum of the disease process. For patients in whom pathophysiologic processes are ongoing, the term acute kidney disease (AKD) has been proposed to define the course of disease after AKI; however, definitions of AKD and strategies for the management of patients with AKD are not currently available. In this consensus statement, the Acute Disease Quality Initiative (ADQI) proposes definitions, staging criteria for AKD, and strategies for the management of affected patients. We also make recommendations for areas of future research, which aim to improve understanding of the underlying processes and improve outcomes for patients with AKD