Search

Leucinodes orbonalis is a monophagous pest on brinjal. However, it is also being reported that it may switch to other Solanaceae plants under the stress of the non-availability of the host for feeding. The larvae feed inside the fruit and reduce its nutritive value, and yield loss may reach up to 90%. The pest has discouraged farmers from growing brinjal, which is a profitable crop labelling it as a devastating pest of brinjal. The management methods use biological means such as the use of natural enemies, and other approaches such as sex pheromones, neuropeptides, improvement of genetically modified crops, and RNA interference tools. Though these methods have faced some challenges in implementation, are harmless, supportable, and also species-specific. In the current review, we have discussed the cultural practices, chemical control, and biological methods that have been used in the past or are currently in practice for pest management. Apart from this, we have also discussed a few of the quite recent but hopeful technologies, that can be thought for a tool for the control of L. orbonalis. [ABSTRACT FROM AUTHOR]

ABSTRACT: Context: The annual incidence cases report depicts India as having the highest tuberculosis (TB) burden globally. Following a programmatic change, the daily fixed-dose combination (FDC) anti-TB treatment regimens were introduced by the Indian government's National Tuberculosis Elimination Program (NTEP). Aims: The aim of the study was to assess the treatment outcomes among drug-sensitive pulmonary TB patients receiving daily FDC drugs and the associated factors influencing the treatment outcomes. Settings and Design: A prospective study was conducted among 300 drug-sensitive pulmonary TB cases in the Bruhat Bengaluru Mahanagara Palike (BBMP) area. Materials and Methods: The TB units and designated microscopic centers (DMCs) were selected by multistage random sampling. Data were collected through a pre-tested and semi-structured questionnaire. Patients were followed up until treatment completion. Statistical Analysis Used: Data were compiled and analyzed using IBM Statistical Package for Social Sciences (SPSS) statistics version 20.0. Descriptive statistics and the Chi-square test were used for interpretation. A P -value less than 0.05 was considered statistically significant. Results: Around 86.33% of patients were cured, 4% had completed treatment, and 1% had treatment failure. Older age, human immunodeficiency virus (HIV) reactive status, alcohol intake, tobacco use, and migrants were associated with poor outcomes. Conclusions: The daily FDC regimen had better outcomes than intermittent regimens. Smokers, alcoholics, migrants, and patients with co-morbidity need to be given priority in management as they are prone to poorer outcomes. [ABSTRACT FROM AUTHOR]

Big data is a collection of heterogeneous and autonomous data sources which are available abundantly in multiple formats. Knowledge discovery and decision-making from the ever-growing abundant data are challenging tasks for data-oriented business organizations. Big data analytics investigates a large amount of data to find correlations among the available data and finally provides useful information to business organizations. Big data analytics facilitates application domains such as business, banking, healthcare, transportation, social media, agriculture, and government sectors. Existing surveys on big data are based on either of the following dimensions: characteristics, analytics, and visualization, or discuss the applications of big data analytics in the field of agriculture, transportation, etc., separately. However, this article provides a survey of big data, which integrates different dimensions of big data, such as infrastructure, analytics, visualization, and their applications. It also discusses the technologies and tools involved in the domains mentioned above. [ABSTRACT FROM AUTHOR]

Sensor networks suffer from various sensor faults and false measurements in healthcare application and this vulnerability of the delay should handle efficiently and timely response in various application of WSN. For instance, in healthcare application, the false measurements generate false alarms which require to take unnecessary action from the healthcare department. The quality of the health care service can improve in remote healthcare monitoring system by introducing a new approach to identify the true medical condition and differentiate true and false alarms. In this paper, we proposed a novel approach to analysis past historical data collected from various medical sensors to identify the sensor anomaly. The main goal of this approach is to differentiate between true and false alarms effectively. The proposed system analysis the historical data to predicts the sensor value which compares with real sensed values at a time incident. The dynamically adjust the threshold value by comparing the difference between predicted value and historic value to determine the anomaly of sensor value. This system has been worked on huge real-time healthcare dataset and result shows that the new approach has been applied on real healthcare datasets and result of this system shows the detection rate is high and false positive rate is low which conclude that this approach is very useful in WSN application such as health monitoring system and it will be competitive with others. [ABSTRACT FROM AUTHOR]

Background: The husband has a great role to play in the antenatal care of his wife during pregnancy. Male spouse involvement is crucial and essential in utilization of the services and benefits, antenatal services to the maximum by the woman. The male spouse involvement will have positive impact on reproductive and child health. The extent of involvement of male spouse depends on the gender role attitudes and the social network. Objective: To assess the involvement of Male spouse in Antenatal care. Methodology: A community based cross-sectional study was conducted in the month of June to November 2023 among 263 Male partners of parous women between the reproductive age 15-45yr, in the urban slum area of BMCRI, Bangalore through simple random sampling technique. A pre-tested, semi-structured, questionnaire was used to collect the data, to assess their involvement during antenatal care. Data collected was entered in MS Excel and analysis was done using SPSS version 21.0. Results: In our study, 84% were actually present at the hospital during the delivery and 82.5% had good practice of taking appointment for ANC visits of their wives. About 77.6% were aware of pregnancy related danger signs. But only 35% participants accompanied their wives to ANC visit at least four times. Conclusion: There is a need to recognize importance and positive impact of male participation in antenatal care. Knowledge and attitude of men are the prime determinants of their level of participation in antenatal care. [ABSTRACT FROM AUTHOR]

The present research endeavour was to design the dual retard technique of once daily Inlay tablet of Glibenclamide as immediate Release (IR) formulation with Metformin Hydrochloride as sustained release (SR) formulation for Diabetes mellitus. The compatibility of the drug with various excipients was studied by DSC. Five batches of SR formulations (FM1 - FM5) were developed by using polymers HPMC K4M, HPMC K100 M & ethyl 4 100 cellulose by wet granulation method and three batches of IR formulations (FG1-FG3) were developed using sodium starch glycolate by direct compression method. Both the formulations were evaluated for various parameters like thickness, hardness, weight variation, disintegration, swelling erosion behavior, UV analysis, simultaneous analysis by HPLC, in vitro drug release and stability studies at 40°±2°C, RH 70±5%. Among those different formulations, formulation FG2 containing 2% of sodium starch glycolate had the highest release of 101.33% and formulation FM5 having a release profile of 101.89% upto 24 hours were selected for the formulation of Inlay tablet and possess expected release pattern in both immediate release layer and sustained release layer. The release kinetics studies revealed that the selected formulation followed First order non fickian diffusion. Thus, the study concludes that the Inlay tablets can overcome the disadvantages of already existing antidiabetic drug formulations and can be used to treat the patients with Diabetes. [ABSTRACT FROM AUTHOR]

The prevalence of Diabetes Mellitus Worldwide has increased dramatically during the past few decades and the estimates of deaths from Diabetes suggest that it may a leading cause of death, the researchers report. Herbs are foods that have long histories of helping a body function or gland. The present study was aimed to evaluate the effect of ethanolic extracts of leaves of Ficus benghalensis Linn in two different doses (200mg/ kg, 400mg/ kg body weight) on blood Glucose level, biochemical parameters and histopathological studies in alloxan induced diabetic albino rats against glibenclamide(5mg/kg). In present study, doses of 200mg/Kg and 400mg/Kg of ethanolic extracts had shown reduction in triglycerides, chlolestrol and glucose level when compared with the standard drug. The results obtained from the experiment provided the scientific evidence in favour of the traditional use of leaves extract of Ficus benghalensis Linn for the treatment of diabetes Mellitus. [ABSTRACT FROM AUTHOR]

Exponential growth in the number of available protein sequences is unmatched by the slower growth in the number of structures. As a result, the development of efficient and fast protein secondary structure prediction methods is essential for the broad comprehension of protein structures. Computational methods that can efficiently determine secondary structure can in turn facilitate protein tertiary structure prediction, since most methods rely initially on secondary structure predictions. Recently, we have developed a fast learning optimized prediction methodology (FLOPRED) for predicting protein secondary structure (Saraswathi et al. in JMM 18:4275, ). Data are generated by using knowledge-based potentials combined with structure information from the CATH database. A neural network-based extreme learning machine (ELM) and advanced particle swarm optimization (PSO) are used with this data to obtain better and faster convergence to more accurate secondary structure predicted results. A five-fold cross-validated testing accuracy of 83.8 % and a segment overlap (SOV) score of 78.3 % are obtained in this study. Secondary structure predictions and their accuracy are usually presented for three secondary structure elements: α-helix, β-strand and coil but rarely have the results been analyzed with respect to their constituent amino acids. In this paper, we use the results obtained with FLOPRED to provide detailed behaviors for different amino acid types in the secondary structure prediction. We investigate the influence of the composition, physico-chemical properties and position specific occurrence preferences of amino acids within secondary structure elements. In addition, we identify the correlation between these properties and prediction accuracy. The present detailed results suggest several important ways that secondary structure predictions can be improved in the future that might lead to improved protein design and engineering. [ABSTRACT FROM AUTHOR]

Computational methods are rapidly gaining importance in the field of structural biology, mostly due to the explosive progress in genome sequencing projects and the large disparity between the number of sequences and the number of structures. There has been an exponential growth in the number of available protein sequences and a slower growth in the number of structures. There is therefore an urgent need to develop computational methods to predict structures and identify their functions from the sequence. Developing methods that will satisfy these needs both efficiently and accurately is of paramount importance for advances in many biomedical fields, including drug development and discovery of biomarkers. A novel method called fast learning optimized prediction methodology (FLOPRED) is proposed for predicting protein secondary structure, using knowledge-based potentials combined with structure information from the CATH database. A neural network-based extreme learning machine (ELM) and advanced particle swarm optimization (PSO) are used with this data that yield better and faster convergence to produce more accurate results. Protein secondary structures are predicted reliably, more efficiently and more accurately using FLOPRED. These techniques yield superior classification of secondary structure elements, with a training accuracy ranging between 83 % and 87 % over a widerange of hidden neurons and a cross-validated testing accuracy ranging between 81 % and 84 % and a segment overlap (SOV) score of 78 % that are obtained with different sets of proteins. These results are comparable to other recently published studies, but are obtained with greater efficiencies, in terms of time and cost. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a performance enhancement scheme for the recently developed extreme learning machine (ELM) for multi-category sparse data classification problems. ELM is a single hidden layer neural network with good generalization capabilities and extremely fast learning capacity. In ELM, the input weights are randomly chosen and the output weights are analytically calculated. The generalization performance of the ELM algorithm for sparse data classification problem depends critically on three free parameters. They are, the number of hidden neurons, the input weights and the bias values which need to be optimally chosen. Selection of these parameters for the best performance of ELM involves a complex optimization problem. In this paper, we present a new, real-coded genetic algorithm approach called ‘RCGA-ELM’ to select the optimal number of hidden neurons, input weights and bias values which results in better performance. Two new genetic operators called ‘network based operator’ and ‘weight based operator’ are proposed to find a compact network with higher generalization performance. We also present an alternate and less computationally intensive approach called ‘sparse-ELM’. Sparse-ELM searches for the best parameters of ELM using K-fold validation. A multi-class human cancer classification problem using micro-array gene expression data (which is sparse), is used for evaluating the performance of the two schemes. Results indicate that the proposed RCGA-ELM and sparse-ELM significantly improve ELM performance for sparse multi-category classification problems. [ABSTRACT FROM AUTHOR]

The response of soil respiration (SR) to varying soil temperature and soil moisture was studied in three-year-old plantation sites of Dalbergia sissoo, Dalbergia latifolia, Albizia lebbeck, Hardwickia binata and Cassia siamea during 2005-06. Significant seasonal differences in SR rates were observed in each site (P ≤ 0.001). The highest rates of soil CO2 efflux were generally found during the rainy season and the lowest during summer in all the study sites. Highest SR rates were found in D. sissoo, 9.89 ± 0.78 μmol m-2 s-1 in November and December, followed by H. binata, 9.68 ± 0.45 μmol m-2 s-1 in September and October 2005, A. lebbeck, 8.84 ± 0.43 μmol m-2 s-1 between November 2005 and January 2006, D. latifolia, 7.6 ± 0.12 μmol m-2 s-1 in November and December 2005 and C. siamea, 7.3 μmol m-2 s-1 in December 2005. There was a positive and significant (P ≤ 0.001) relationship between SR rates and soil moisture in all the sites (r2 above 0.60), except C. siamea (r2 = 0.30). A poor relationship was observed between SR and soil temperature in all the sites (r2 below 0.2). Examination of the seasonal pattern of SR rates suggests that much of the variability could be attributed to variations in soil moisture. There was a strong indication suggesting that the soil-water deficits served to reduce SR rates during summer and after subsequent rain events. Overall sensitivity of SR rate to soil moisture seems to be good for this semi-arid ecosystem. [ABSTRACT FROM AUTHOR]

Deep learning provides the healthcare industry with the ability to analyse data at exceptional speeds without compromising on accuracy. These techniques are applicable to healthcare domain for accurate and timely prediction. Convolutional neural network is a class of deep learning methods which has become dominant in various computer vision tasks and is attracting interest across a variety of domains, including radiology. Lung diseases such as tuberculosis (TB), bacterial and viral pneumonias, and COVID-19 are not predicted accurately due to availability of very few samples for either of the lung diseases. The disease could be easily diagnosed using X-ray or CT scan images. But the number of images available for each of the disease is not as equally as other resulting in imbalance nature of input data. Conventional supervised machine learning methods do not achieve higher accuracy when trained using a lesser amount of COVID-19 data samples. Image data augmentation is a technique that can be used to artificially expand the size of a training dataset by creating modified versions of images in the dataset. Data augmentation helped reduce overfitting when training a deep neural network. The SMOTE (Synthetic Minority Oversampling Technique) algorithm is used for the purpose of balancing the classes. The novelty in this research work is to apply combined data augmentation and class balance techniques before classification of tuberculosis, pneumonia, and COVID-19. The classification accuracy obtained with the proposed multi-level classification after training the model is recorded as 97.4% for TB and pneumonia and 88% for bacterial, viral, and COVID-19 classifications. The proposed multi-level classification method produced is ~8 to ~10% improvement in classification accuracy when compared with the existing methods in this area of research. The results reveal the fact that the proposed system is scalable to growing medical data and classifies lung diseases and its sub-types in less time with higher accuracy. [ABSTRACT FROM AUTHOR]

Biology is adapted to Earth's gravity force, and the long-term effects of varying gravity on the development of animals is unclear. Previously, we reported that high gravity, called hypergravity, increases defects in the development of motor neuron axons in the nematode Caenorhabditis elegans. Here, we show that a mutation in the unc-70 gene that encodes the cytoskeletal β-spectrin protein suppresses hypergravity-induced axon defects. UNC-70 expression is required in both muscle and epidermis to promote the axon defects in high gravity. We reveal that the location of axon defects is correlated to the size of the muscle cell that the axon traverses. We also show that mutations that compromise key proteins of hemidesmosomal structures suppress hypergravity-induced axon defects. These hemidesmosomal structures play a crucial role in coupling mechanical force between the muscle, epidermis and the external cuticle. We speculate a model in which the rigid organization of muscle, epidermal and cuticular layers under high gravity pressure compresses the narrow axon migration pathways in the extracellular matrix hindering proper axon pathfinding of motor neurons. [ABSTRACT FROM AUTHOR]

Context: In the absence of any specific treatment available for COVID-19, people started practicing traditional nonpharmacological preventive home remedies such as salt water gargling and steam inhalation. The available research evidence on some of these measures opines that steam inhalation, saline gargling, and povidone-iodine gargling does have virucidal properties and do provide symptomatic relief. Aims: The aim is to test this hypothesis, and the present trial was undertaken with an objective to assess the effect of steam inhalation, saline gargling, and povidone-iodine gargling among the COVID-19-positive patients with respect to early test negativity and clinical recovery. Methodology: Open-labeled, parallel, randomized controlled trial was conducted among asymptomatic or mild COVID-19-positive patients in Bangalore from September 2020 to February 2021. In each group of steam inhalation, saline gargling, povidone-iodine gargling, and control, twenty participants were allocated. Daily follow-up was done for 21 days to assess early test negativity and clinical recovery. Trial Registry Number: Clinical Trial Registry India/2020/09/027687. Results: Among 80 participants recruited, 65 (81.3%) were symptomatic. Early test negativity was seen in povidone-iodine gargling group of 6 days (KaplanMeier survival curve, BreslowGeneralized Wilcoxon test P = 0.7 as per the intention-to-treat and as per-protocol P = 0.8). Significant clinical recovery was seen in saline gargling group (4 days, P = 0.01). Conclusion: Povidone-iodine gargling was effective in providing early test negativity, whereas saline gargling was effective in early clinical recovery. [ABSTRACT FROM AUTHOR]

Mounting electronics circuits on a plastic flexible substrate are pertinent for biosensing applications due to their resilient nature, minimal processing conditions, lightweight and low cost. Organic Field-Effect Transistors (OFET)-based amplifier for flexible biosensors have been proposed in this paper. To design flexible biosensing circuits, Metal Oxide Semiconductor Field-Effect Transistor (MOSFET) with Polycyclic Hydrocarbon is a suitable choice. It is a big challenge to build an organic circuit using graphene electrode due to its poor performance of N -type OFET, therefore it is advisable to use Pentacene as N - and P -type Organic semiconductors. Pentacene being one among the foremost totally investigated conjugated organic molecules with a high application potential because the hole mobility in OFETs goes up to 0.2 cm2/(Vs), which exceeds that of amorphous silicon. In biosignal process, the first and most important step is to amplify the biosignal for further processing. Operational Transconductance Amplifier (OTA) plays an essential role in biological signal measuring instruments like EEG, ECG, EMG modules which measure the heart, muscle and brain activities. The OTA designed using this OFET is adaptable for flexible sensor circuits and also it derives the transconductance of 67 which is similar to silicon OTA. The amplifier designed here gives unit gain of 42 dB with a frequency of 195 Hz which is suitable for low-frequency biosignal processing applications. [ABSTRACT FROM AUTHOR]

Somatic embryogenesis (SE) is a complex stress related process regulated by numerous biological factors. SE is mainly applicable to mass propagation and genetic improvement of plants through gene transfer technology and induced mutations. In banana, SE is highly genome dependent as the efficiency varies with cultivars. To understand the molecular mechanism of SE, a proteomics approach was carried out to identify proteins expressed during embryogenic calli (EC) induction, regeneration and germination of somatic embryos in the banana cultivar cv. Rasthali (AAB). In total, 70 spots were differentially expressed in various developmental stages of SE, of which 16 were uniquely expressed and 17 were highly abundant in EC compared to non‐embryogenic calli and explants. Also, four spots were uniquely expressed in germinating somatic embryos. The functional annotation of identified proteins revealed that calcium signaling along with stress and endogenous hormones related proteins played a vital role in EC induction and germination of somatic embryos. Thus, based on this outcome, the callus induction media was modified and tested in five cultivars. Among them, cultivars Grand Naine (AAA), Monthan (ABB) and Ney Poovan (AB) showed a better response in tryptophan added media, whereas Red Banana (AAA) and Karpuravalli (ABB) showed maximum EC induction in kinetin and CaCl2 supplemented media respectively. Simultaneously, germination media were modified to induce proteins responsible for germination. In cv. Rasthali, media supplemented with 10 mM CaCl2 showed a maximum increase in germination (51.79%) over control plants. Thus, the present study revealed that media modification based on proteomic analysis can induce SE in recalcitrant cultivars and also enhance germination in cultivars amenable for SE. [ABSTRACT FROM AUTHOR]

A series of 22 stilbene derivatives based on resveratrol were synthesized incorporating acetoxy-, benzyloxy-, carboxy-, chloro-, hydroxy- and methoxy functional groups. We examined the cytotoxicity of these 22 stilbenes in human K562 chronic myelogenous leukemia cells. Only four compounds were cytotoxic namely 4'-hydroxy-3-methoxystilbene (15), 3'-acetoxy-4-chlorostilbene (19), 4'-hydroxy- 3,5-dimethoxystilbene or pterostilbene (3) and 3,5-dibenzyloxy-4'-hydroxystilbene (28) with IC50s of 78 µM, 38 µM, 67 µM and 19.5 µM respectively. Further apoptosis assessment on the most potent compound, 28, confirmed that the cells underwent apoptosis based on phosphatidylserine externalization and loss of mitochondrial membrane potential. Importantly, we observed a concentration-dependent activation of caspase-9 as early as 2 hr with resultant caspase-3 cleavage in 28-induced apoptosis. Additionally, a structure-activity relationship (SAR) study proposed a possible mechanism of action for compound 28. Taken together, our data suggests that the pro-apoptotic effects of 28 involve the intrinsic mitochondrial pathway characterized by an early activation of caspase-9. [ABSTRACT FROM AUTHOR]

A study was carried out to analyse the trend, seasonal and spatial variations in wholesale and retail egg prices in major market centres of South India. The data on monthly average wholesale NECC prices of egg from major market centres of South India viz., Namakkal, Hyderabad, Nellore, Vijayawada and Mysore and monthly average retail NECC prices of egg from major consumption centres of South India viz., Bangalore, Chennai and Mumbai for the period from August 2000 to July 2009 were collected from various secondary sources. The slope of linear trend equations revealed that the wholesale egg price hiked at rate of four-fifth of a paise per month. The retail egg price trend equation fitted for major consumption centres of South India revealed that the egg price had increased by 0.79 to 0.81 paise per egg. The intercept of trend equations was more (Rs. 99.84 to 107.05) for retail price when compared to the wholesale price (Rs. 92.33 to 96.79). The monthly price indices of egg price in various market centres of South India inferred that the price indices of all the observed centres coincides with each other over various months. The monthly egg price index was observed to be the minimum during the months of March and April and started increasing to reach peak during the month of June. Further, it started decreasing and reached lower value during the months of August and September. The monthly price index was found to increase to reach higher index values during the months of November to January. The seasonal wholesale/ retail egg price index was found to be the highest during the month of November and December and the lowest during the month of April. [ABSTRACT FROM AUTHOR]

Background: Workplace bullying is an important and serious issue in a healthcare setting because of its potential impact on the welfare of care-providers as well as the consumers. Aims: To gauge the extent of bullying among the medical community in India; as a subsidiary objective, to assess the personality trait of the bullying victims. Settings and Design: A cross-sectional, anonymous, self-reported questionnaire survey was undertaken among a convenient sample of all the trainee doctors at a Government Medical College in Tamil Nadu, India. Materials and Methods: A questionnaire, in English with standard written explanation of bullying was used. Basic information like age, sex, job grade and the specialty in case of Postgraduates (PGs) were also collected. Statistical Analysis: The results were subjected to descriptive statistical analysis and Chi-square test for comparison of frequencies. Results: A total of 174 doctors (115 PGs and 59 junior doctors), took part in the study with a cent percent response. Nearly half of the surveyed population reported being subjected to bullying. Nearly 54 (53%) of the men and 35 (48%) of women were subjected to bullying. Significant proportions (P<0.0001) of medical personnel and paramedical staff bullied the PGs and junior doctors, respectively. More than 85 (90%) of bullying incidents went unreported. A significant (P<0.0001) percentage of PGs and junior doctors revealed a personality trait towards bully. Conclusions: Workplace bullying is common among trainee doctors and usually goes unreported. [ABSTRACT FROM AUTHOR]