Nutrition morbidity interactions in pre-school children.

Background & objectives: Research studies in the 1970s reported that in pre-school children, undernutrition increased the risk of infections and infections aggravated undernutrition. Over decades, there has been a reduction in prevalence of undernutrition and improvement in access to healthcare for treatment of infections. A mixed longitudinal study was undertaken to assess whether over time there were any changes from the earlier reported effect of undernutrition prior to infection on the risk of morbidity and effect of morbidity on nutritional status in pre-school children. Methods: Pre-school (0-59 months of age) children from urban low- and middle-income families whose parents were willing to allow their participation in the study were enrolled. Information on sociodemographic profile of the families was collected at enrolment. Weight of all children and length in infants were recorded every month; length/height in children 12-59 months of age was recorded once in three months. Morbidity information was collected through fortnightly visits. Results: 3888 pre-school children were followed up in 74636 home visits. Among these children, underweight and wasting were associated with a small increase in risk of infections. The odds ratio for risk of infection for underweight children was 1.09 (95% CI: 1.02 to 1.16) and for wasting was 1.18 (95% CI: 1.08 to 1.29). The deterioration in Z scores for weight-for-age and body mass index-for-age in children during illness and convalescence was small but significant (P<0.001). Interpretation & conclusions: The increased risk of infections in undernourished children living in overcrowded tenements in areas with poor environmental hygiene was not significant, perhaps because the risk of infection in normally nourished children was also high. The deterioration in nutritional status following infection was small because of the ready access to and utilization of health and nutrition care.

Deep Learning Mechanism for Predicting the Axillary Lymph Node Metastasis in Patients with Primary Breast Cancer.

The second largest cause of mortality worldwide is breast cancer, and it mostly occurs in women. Early diagnosis has improved further treatments and reduced the level of mortality. A unique deep learning algorithm is presented for predicting breast cancer in its early stages. This method utilizes numerous layers to retrieve significantly greater amounts of information from the source inputs. It could perform automatic quantitative evaluation of complicated image properties in the medical field and give greater precision and reliability during the diagnosis. The dataset of axillary lymph nodes from the breast cancer patients was collected from Erasmus Medical Center. A total of 1050 images were studied from the 850 patients during the years 2018 to 2021. For the independent test, data samples were collected for 100 images from 95 patients at national cancer institute. The existence of axillary lymph nodes was confirmed by pathologic examination. The feed forward, radial basis function, and Kohonen self-organizing are the artificial neural networks (ANNs) which are used to train 84% of the Erasmus Medical Center dataset and test the remaining 16% of the independent dataset. The proposed model performance was determined in terms of accuracy (Ac), sensitivity (Sn), specificity (Sf), and the outcome of the receiver operating curve (Roc), which was compared to the other four radiologists' mechanism. The result of the study shows that the proposed mechanism achieves 95% sensitivity, 96% specificity, and 98% accuracy, which is higher than the radiologists' models (90% sensitivity, 92% specificity, and 94% accuracy). Deep learning algorithms could accurately predict the clinical negativity of axillary lymph node metastases by utilizing images of initial breast cancer patients. This method provides an earlier diagnostic technique for axillary lymph node metastases in patients with medically negative changes in axillary lymph nodes.

Heart disease diagnosis using optimized features of hybridized ALCSOGA algorithm and LSTM classifier.

Cardiac disease is the predominant cause of global death mainly due to its hidden symptoms and late diagnosis. Hence, early detection is important to improve quality of life. Though traditional researches attempted to predict heart disease, most of them lacked with respect to accuracy. To solve this, the present study proposes a hybridized Ant Lion Crow Search Optimization Genetic Algorithm (ALCSOGA) to perform effective feature selection. This hybrid optimization encompasses Ant Lion, Crow Search and Genetic Algorithm. Ant lion algorithm determines the elite position. While, the Crow Search Algorithm utilizes the phenomenon of position and memory of each crow for evaluating the objective function. Both these algorithms are fed into Genetic Algorithm to improve the performance of feature selection process. Then, Stochastic Learning rate optimized Long Short Term Memory (LSTM) is proposed to classify the extracted optimized features. Finally, comparative analysis is performed in terms of accuracy, recall, F1-score, and precision. Moreover, statistical analysis is performed with respect to Sum of Squares (SS), degree of freedom (df), F Critical (F crit), F Statistics (F), p, and Mean Square (MS) value. Analytical results revealed the efficiency of proposed system over conventional methods and thereby confirming its efficiency for predicting heart disease.

Overnutrition in Indian Children: Challenges and Opportunities.

Global and Indian data indicate that children from all the segments of population face dual nutrition burden and related health consequences. Long-term cohort studies have shown that both the under- and overnutrition are risk factors for overnutrition and non-communicable diseases in adult life. Halting the rise in overnutrition is one of the Sustainable Development Goal (SDG) targets to be achieved by 2030. With the development and inclusion of body mass index (BMI)-for-age in the WHO child growth standards, it has become possible to assess over- and undernutrition in short-statured children. In India, the Annual Health Survey (AHS) (2014) and the District Level Household Survey 4 (DLHS4) (2013) undertook measurement of height/length and weight (AHS 557016 and DLHS4 295663) in the 0-18-year of school-age children from selected households. Prevalence of overnutrition in 0-18-year children was calculated from these two surveys by using the WHO standards for BMI-for-age (BMI-for-age z scores (BAZ) > +2 in 0-5 and BAZ > +1 in 5-18-year children) as well as uniform norms of either > +1 or > +2 BAZ across 0-18-year children. An attempt was made to explore the policy and program implications of using different norms for assessing overnutrition in preschool and school age children in the Indian context. Body mass index-for-age curve for the 0-18-year Indian children was calculated and compared with the WHO BMI-for-age curve. Across 0-18-year children, the mean BMI-for-age of Indian boys and girls was lower than the mean of the WHO standards, but the trajectory followed was similar. Therefore, Indian high-risk under- and overnourished children can be monitored by using the WHO BMI-for-age curve. Irrespective of the cutoff used for BMI-for-age, prevalence of overnutrition was higher in preschool as compared to school-age children. Overnourished school-age children outnumbered preschool children, especially if the WHO cutoffs were used. The school health system may find it difficult to implement programs that aimed at detection and management of large number of overnourished children. If uniform norm of BAZ > +1 was used, prevalence of overnutrition in preschool children was high and almost similar to undernutrition. Currently, nutrition programs for preschool children are focused on undernutrition and they may find it difficult to manage program focused on overnutrition in large number of children. If the uniform norm of BAZ > +2 was used, both the prevalence of overnutrition and number of children requiring intervention were relatively low in all the age groups. The existing preschool and school nutrition programs can take up an integrated program aimed at early detection and effective management of both the under- (BAZ < -2) and overnutrition (BAZ > +2) in 0-18-year children and strive to achieve the SDG targets.

Therapeutic Potential of Cucumis melo (L.) Fruit Extract and Its Silver Nanopartciles Against DEN-Induced Hepatocellular Cancer in Rats.

Biosynthesized silver nanoparticles have a wide range of biological activities and using nanoparticles as one of the novel approaches in cancer therapy. In this present research work, the anti-cancer efficacy of Cucumis melo fruit extract and its silver nanoparticles was explored. Wistar rats were divided into six groups and hepatic cancer was induced with 0.01% DEN (diethylnitrosamine) through drinking water for 16 weeks. Cyclophosphamide was given as the standard drug at the dose of 50 mg/kg body weight. Hematological parameters showed a decrease in the levels of hemoglobin (Hb), packed cell volume (PCV), red blood cells (RBC), mean corpuscular volume (MCV), mean corpuscular Hb (MCH), mean corpuscular Hb concentration (MCHC), and platelets (PLTS) levels except white blood cell (WBC) in DEN-induced cancer animals. Significant alterations in the hematological parameters were observed after treatment which indicate the protective effect of Cucumis melo fruit on the hemopoietic system. The structural integrity of the cells has been damaged in cancer-induced animals, and this results in cytoplasmic leakage of enzyme into the blood stream, leads to the elevated levels of these enzymes in blood with subsequent fall in the tissues. Hence, the levels of liver function markers such as AST ALT, ALP, LDH, GGT, and 5'NT were significantly elevated in serum and the liver of cancer-induced rats. The levels of serum tumor markers, viz., alpha-fetoprotein (AFP) and carcinoembryonic antigen (CEA), elevated in rats induced with DEN, which then were reduced following Cucumis melo fruit treatment, indicating the anti-cancer activity of the drug. Histological evaluation of the liver and kidney was also performed to authenticate the present work. Treatment with crude extract and silver nanoparticles of Cucumis melo fruit indicates that Cucumis melo fruit could have exerted its protective effect.

Meta-Analysis of Quantitative Traits Loci (QTL) Identified in Drought Response in Rice (Oryza sativa L.).

Rice is an important grain that is the staple food for most of the world's population. Drought is one of the major stresses that negatively affects rice yield. The nature of drought tolerance in rice is complex as it is determined by various components and has low heritability. Therefore, to ensure success in breeding programs for drought tolerant rice, QTLs (quantitative trait loci) of interest must be stable in a variety of plant genotypes and environments. This study identified stable QTLs in rice chromosomes in a variety of backgrounds and environments and conducted a meta-QTL analysis of stable QTLs that have been reported by previous research for use in breeding programs. A total of 653 QTLs for drought tolerance in rice from 27 genetic maps were recorded for analysis. The QTLs recorded were related to 13 traits in rice that respond to drought. Through the use of BioMercartor V4.2, a consensus map containing QTLs and molecular markers were generated using 27 genetic maps that were extracted from the previous 20 studies and meta-QTL analysis was conducted on the consensus map. A total of 70 MQTLs were identified and a total of 453 QTLs were mapped into the meta-QTL areas. Five meta-QTLs from chromosome 1 (MQTL 1.5 and MQTL 1.6), chromosome 2 (MQTL2.1 and MQTL 2.2) and chromosome 3 (MQTL 3.1) were selected for functional annotation as these regions have high number of QTLs and include many traits in rice that respond to drought. A number of genes in MQTL1.5 (268 genes), MQTL1.6 (640 genes), MQTL 2.1 (319 genes), MQTL 2.2 (19 genes) and MQTL 3.1 (787 genes) were annotated through Blast2GO. Few major proteins that respond to drought stress were identified in the meta-QTL areas which are Abscisic Acid-Insensitive Protein 5 (ABI5), the G-box binding factor 4 (GBF4), protein kinase PINOID (PID), histidine kinase 2 (AHK2), protein related to autophagy 18A (ATG18A), mitochondrial transcription termination factor (MTERF), aquaporin PIP 1-2, protein detoxification 48 (DTX48) and inositol-tetrakisphosphate 1-kinase 2 (ITPK2). These proteins are regulatory proteins involved in the regulation of signal transduction and gene expression that respond to drought stress. The meta-QTLs derived from this study and the genes that have been identified can be used effectively in molecular breeding and in genetic engineering for drought resistance/tolerance in rice.

ROS Homeostasis in Abiotic Stress Tolerance in Plants.

Climate change-induced abiotic stress results in crop yield and production losses. These stresses result in changes at the physiological and molecular level that affect the development and growth of the plant. Reactive oxygen species (ROS) is formed at high levels due to abiotic stress within different organelles, leading to cellular damage. Plants have evolved mechanisms to control the production and scavenging of ROS through enzymatic and non-enzymatic antioxidative processes. However, ROS has a dual function in abiotic stresses where, at high levels, they are toxic to cells while the same molecule can function as a signal transducer that activates a local and systemic plant defense response against stress. The effects, perception, signaling, and activation of ROS and their antioxidative responses are elaborated in this review. This review aims to provide a purview of processes involved in ROS homeostasis in plants and to identify genes that are triggered in response to abiotic-induced oxidative stress. This review articulates the importance of these genes and pathways in understanding the mechanism of resistance in plants and the importance of this information in breeding and genetically developing crops for resistance against abiotic stress in plants.

Time trends in prevalence of anaemia in pregnancy.

Background & objectives: : The prevalence of anaemia in pregnancy in India is among the highest in the world. In the last two decades, several national surveys have estimated haemoglobin levels in pregnant women. In this study, data from these surveys were analyzed to find out changes, if any, in prevalence of anaemia in pregnancy. Methods: : National and State-level estimates on the prevalence of anaemia were tabulated from the reports of the National Family Health Survey (NFHS) 2, NFHS 3, Fact Sheets of NFHS 4 and District Level Household Survey (DLHS) 2. Unit level data from DLHS 4 and Annual Health Survey Clinical Anthropometric and Biochemical component (AHS CAB) were obtained and State level prevalence of different grades of anaemia was estimated. Time trends in the prevalence of anaemia and different grades of anaemia were assessed from these surveys. Results: : NFHS 2, 3 and 4 reported relatively lower prevalence of anaemia as compared to DLHS and AHS CAB. There was not much change in the prevalence or severity of anaemia between NFHS 2, 3 and 4. There was substantial reduction in the prevalence and severity of anaemia in all States except Uttarakhand between DLHS 2 and 4 and DLHS 2 and AHS CAB. Interpretation & conclusions: : There was a reduction in the prevalence and severity of anaemia in the last 15 years. The two-pronged strategy of increasing iron intake (dietary diversification and use of iron-fortified iodized salt) in all the population and testing, and detecting and treating pregnant women with anaemia will accelerate the pace of reduction in anaemia.

An Efficient Watermarking Scheme for Medical Data Security With the Aid of Neural Network

ABSTRACT Digital watermarking has emerged as major technique for ensuring security for various types of data like medical data, digital copyright protection, transaction tracing and so on. With the advancement in digital data distribution over the network there has been increase in the need for protection of such data from unauthorized copying or usages. Watermarking helps in providing the security to some extent. Robustness against any sort of unauthenticated attack is the major requirement of watermarking. In this paper we proposed an efficient watermarking technique for medical data security with the aid of neural network. Usage of neural network is generally used to create and control watermarking strength automatically. This method provides better watermarked data which can be highly secured to unauthorized usage. It is observed that the proposed method provides better security for the multimedia data when compared with other data security methods.

Chemopreventive effect and HPTLC fingerprinting analysis of Jasminum sambac (L.) Ait. Extract against DLA-induced lymphoma in experimental animals.

The anticancer activity of the ethanolic extract of Jasminum sambac against Dalton's lymphoma ascites-induced lymphatic cancer in Swiss albino mice was investigated. The anticancer activity of J. sambac was studied against lymphoma using lipid profiles, biochemical parameters, and membrane-bound marker enzymes by standard procedures. A high-performance thin-layer chromatography fingerprinting analysis showed the presence of terpenoids and flavonoids. The levels of cholesterol, triglyceride, VLDL cholesterol, and LDL cholesterol were significantly decreased in tumor-induced mice, while HDL cholesterol showed increased levels compared with those profiles. On treatment with J. sambac, the levels were brought back to near normal. The albumin, creatinine, total protein, urea, and uric acid contents were also approaching normal values. There was s significant increase in the levels of ATPase in group II. These levels were brought back to normal upon plant extract treatment of mice. DNA fragmentation occurred in the tumor-induced group of tissue, and treatment with ethanolic extract reduced the DNA damage caused by lymphoma. Expression of lactate dehydrogenase (LDH) isoenzymes shows an increase in the levels of LDH-4 and LDH-5 in cancer-bearing animals which is brought back to near normal. Histopathological investigation showed normal sections of liver tissues in the treatment group. The results found in mice treated with ethanolic extract 100 mg kg(-1) body weight quite promising and were comparable with the standard drug 5-fluorouracil. The statistically processed results support the conclusion that the ethanolic extract of J. sambac flower (100 mg kg(-1)) possesses a dose-dependent significant anticancer activity against lymphoma.

Prevalence & consequences of anaemia in pregnancy.

Prevalence of anaemia in India is among the highest in the world. Prevalence of anaemia is higher among pregnant women and preschool children. Even among higher income educated segments of population about 50 per cent of children, adolescent girls and pregnant women are anaemic. Inadequate dietary iron, folate intake due to low vegetable consumption, perhaps low B12 intake and poor bioavailability of dietary iron from the fibre, phytate rich Indian diets are the major factors responsible for high prevalence of anaemia. Increased requirement of iron during growth and pregnancy and chronic blood loss contribute to higher prevalence in specific groups. In India, anaemia is directly or indirectly responsible for 40 per cent of maternal deaths. There is 8 to 10-fold increase in MMR when the Hb falls below 5 g/dl. Early detection and effective management of anaemia in pregnancy can contribute substantially to reduction in maternal mortality. Maternal anaemia is associated with poor intrauterine growth and increased risk of preterm births and low birth weight rates. This in turn results in higher perinatal morbidity and mortality, and higher infant mortality rate. A doubling of low birth weight rate and 2 to 3 fold increase in the perinatal mortality rates is seen when the Hb is <8 g/dl. Intrauterine growth retardation and low birth weight inevitably lead to poor growth trajectory in infancy, childhood and adolescence and contribute to low adult height. Parental height and maternal weight are determinants of intrauterine growth and birth weight. Thus maternal anaemia contributes to intergenerational cycle of poor growth in the offspring. Early detection and effective management of anaemia in pregnancy can lead to substantial reduction in undernutrition in childhood, adolescence and improvement in adult height.

Electrochemical oxidation for the treatment of textile industry wastewater.

This study elucidates the reduction of organics from textile effluents through electrochemical oxidation technique. Effect of pH and current intensity were investigated in this system. It was found that degradation was maximum at the current intensity of 0.6 A and at a pH of 1.3. Under the same experimental conditions the removal of chemical oxygen demand (COD), total solids, total dissolved solids and total organic carbon were found to be approximately 68%, 49.2%, 50.7% and 96.8%, respectively. Effect of current intensity on color removal was also investigated as a function of electrolysis time (30-210 minutes) and it showed that maximum removal efficiency (96%) was reached within 60 minutes at 0.6 A. While studying the effect of pH on COD removal, it was observed that a decrease in pH to an optimum of 1.3 showed maximum COD reduction of 68%. These results suggest an important role of these parameters in electrochemical process for removing organic pollutants.