Kanyakumari Government Medical College

BACKGROUND: Nonrheumatic valvular diseases are common; however, no studies have estimated their global or national burden. As part of the Global Burden of Disease Study 2017, mortality, prevalence, and disability-adjusted life-years (DALYs) for calcific aortic valve disease (CAVD), degenerative mitral valve disease, and other nonrheumatic valvular diseases were estimated for 195 countries and territories from 1990 to 2017. METHODS: Vital registration data, epidemiologic survey data, and administrative hospital data were used to estimate disease burden using the Global Burden of Disease Study modeling framework, which ensures comparability across locations. Geospatial statistical methods were used to estimate disease for all countries, because data on nonrheumatic valvular diseases are extremely limited for some regions of the world, such as Sub-Saharan Africa and South Asia. Results accounted for estimated level of disease severity as well as the estimated availability of valve repair or replacement procedures. DALYs and other measures of health-related burden were generated for both sexes and each 5-year age group, location, and year from 1990 to 2017. RESULTS: Globally, CAVD and degenerative mitral valve disease caused 102 700 (95% uncertainty interval [UI], 82 700-107 900) and 35 700 (95% UI, 30 500-42 500) deaths, and 12.6 million (95% UI, 11.4 million-13.8 million) and 18.1 million (95% UI, 17.6 million-18.6 million) prevalent cases existed in 2017, respectively. A total of 2.5 million (95% UI, 2.3 million-2.8 million) DALYs were estimated as caused by nonrheumatic valvular diseases globally, representing 0.10% (95% UI, 0.09%-0.11%) of total lost health from all diseases in 2017. The number of DALYs increased for CAVD and degenerative mitral valve disease between 1990 and 2017 by 101% (95% UI, 79%-117%) and 35% (95% UI, 23%-47%), respectively. There is significant geographic variation in the prevalence, mortality rate, and overall burden of these diseases, with highest age-standardized DALY rates of CAVD estimated for high-income countries. CONCLUSIONS: These global and national estimates demonstrate that CAVD and degenerative mitral valve disease are important causes of disease burden among older adults. Efforts to clarify modifiable risk factors and improve access to valve interventions are necessary if progress is to be made toward reducing, and eventually eliminating, the burden of these highly treatable diseases.

Aluminium alloy is the popular material in the world to produce lot of light weight parts with high strength, in additionally reinforcement is consider to these alloy is improve its strength. In this investigation consider the AA7050 aluminium alloy as a base material with reinforcement of Silicon Carbide (SiC) at various percentage level like as 0%, 4 % and 6 %. The wear of this composites are analysed through the design of experiments (Taguchi approach) for optimize the process parameters. This wear study is considered the parameters are Sliding velocity in m/s (1, 2 and 3), Sliding distance in m (1000, 1400 and 1800) and percentage of composition (0%, 43% and 6%). For this experimental investigation the sliding distance as most significant factor among three. The microstructure analysis demonstrated that there is a SiC particles which reduces wear of the samples.

Abstract In this present work, Titanium dioxide nanoparticles (TiO 2 NPs) successfully synthesized using the chemical as well as the green synthesis routine. The ethanol provoked the chemical reduction of ions. In the green synthesis, jasmine flower extract was used as a reducing and stabilizing agent because it contains alkaloids, coumarins, flavonoids. The Rutile phase of TiO 2 NPs with an average crystalline size of 31–42 nm was revealed from the XRD pattern. From the UV–Visible spectroscopy, the optically active region of TiO 2 NPs at 385 nm represents the visible region spectrum. The Ti–O–Ti and Ti–O vibration bond formation confirms the formation of TiO 2 NPs. The SEM image of TiO 2 NPs reveals that the spherical shaped NPs with randomly arranged manner. The obtained results have revealed that the property of TiO 2 nanoparticles was similar in both processes. The Photodegradation of methylene blue dye was investigated and resulted in the maximum degradation efficiency of 92% is achieved at 120 min of irradiation. The Photodegradation study shows the biosynthesized TiO 2 NPs exhibits a higher degradation efficiency compared to chemically synthesized TiO 2 NPs. The antibacterial activity of prepared TiO 2 NP’s was studied using grams-positive and gram-negative strains. The biological activities of green synthesized TiO 2 NPs are enhanced compared to the chemically synthesized TiO 2 NPs. Hence the degradation efficiency and zone inhibition layer indicate that the prepared TiO 2 NPs are the potential candidate for environmental and biomedical applications. Graphic abstract

BACKGROUND: The presence of diverse secondary metabolites has been reported from species of the genus Polygonum. However, there has been not much information available on phytochemical components and biological activity in the whole plant ethanol extract of Polygonum chinense L. OBJECTIVE: This study was designed to determine the phytocomponents in the whole plant ethanol extract of P. chinense. MATERIALS AND METHODS: GC-MS analysis of the whole plant ethanol extract of P. chinense was performed using a Perkin-Elmer GC Clarus 500 system comprising an AOC-20i auto-sampler and a gas chromatograph interfaced to a mass spectrometer (GC-MS). RESULTS: This investigation was carried out to determine the possible chemical components from P. chinense by GC-MS. This analysis revealed that the ethanol extract of P. chinense (whole plant) contained mainly a triterpene compound-squalene (47.01%), and a plasticizer compound-1,2-benzenedicarboxylic acid, mono[2-ethylhexyl]ester (40.30%). All identified compounds were, generally, reported as having antimicrobial activity. In addition, the squalene compound also having anti-cancer, anti-oxidant, anti-tumor, chemo-preventive, pesticidal and sun-screen properties, while the plasticizer compound -1,2-benzenedicarboxylic acid, mono[2-ethylhexyl] ester reported to have anti-oxidant and anti-inflammatory properties. No activity was reported in the alcoholic compound-4-hexene-1-ol, 5-methyl-2-(1-methylethanyl)-acetate-(R)-. CONCLUSIONS: From the results, it is evident that P. chinense contains various bioactive compounds and is recommended as a plant of phytopharmaceutical importance.

Egg shell-based activated carbon was successfully synthesized by the simple chemical activation process. Orthophosphoric acid and sodium hydroxide used as an activation agent. XRD pattern reveals the hexagonal structure of activated carbon. The functional group presents in activated carbon was identified using FT-IR spectroscopy. SEM images show irregular shapes of carbon. The photocatalytic performance of investigated activated carbon by illuminating methylene blue dye under UV–Visible irradiations. Photocatalytic activity of activated carbon results maximum degradation efficiency of 83%. Adsorption efficiency have been increased with respect of time for degradation of dye. Free radicals and superoxide’s play a significant role is decolourization of methylene blue. Photocatalytic activity of activated carbon synthesized by Orthophosphoric acid results shows the high degradation efficiency when compared to NaOH.

The preeminent treatments for neurodegenerative disease are often unavailable due to the poor accessibility of therapeutic drugs. Moreover, the blood-brain barrier (BBB) effectively blocks the transfer of cells, particles and large molecules, ie, drugs, across the brain. The most important challenge in the treatment of neurodegenerative diseases is the development of targeted drug delivery system. Theranostic strategies are known to combine therapeutic and diagnostic capabilities together. The aim of this review was to record the response to treatment and thereby improve drug safety. Nanotechnology offers a platform for designing and developing theranostic agents that can be used as an efficient nano-carrier system. This is achieved by the manipulation of some of the properties of nanoparticles (NPs), thereby enabling the attachment of suitable drugs onto their surface. The results provide revolutionary treatments by stimulation and thus interaction with targeted sites to promote physiological response with minimum side effects. This review is a brief discussion of the administration of drugs across the brain and the advantages of using NPs as an effective theranostic platform in the treatment of Alzheimer's, Parkinson's, epilepsy and Huntington's disease.

The recent developments made regarding the novel, cost-effective, and environmentally friendly nanocatalysts for the electrochemical sensing of biomolecules, pesticides, nitro compounds and heavy metal ions are discussed in this review article.

Emotion recognition from speech has developed as a recent research area in Human-Computer Interaction. The objective of this paper is to use a 3-stage Support Vector Machine classifier to classify seven different emotions present in the Berlin Emotional Database. For the purpose of classification, MFCC features from all the 535 files present in the database are extracted. Nine statistical measurements are performed over these features from each frame of a sentence. The linear and RBF kernels are employed in hierarchical SVM with RBF sigma value equal to one. For training and testing of data, 10fold cross-validation is used. Performance analysis is done by using the confusion matrix and the accuracy obtained is 68%.

Agro-industrial residues and cow dung were used as the substrate for the production of alkaline protease by Bacillus cereus strain AT. The bacterial strain Bacillus cereus strain AT produced a high level of protease using cow dung substrate (4813 ± 62 U g(-1)). Physiological fermentation factors such as the incubation time (72 h), the pH (9), the moisture content (120%), and the inoculum level (6%) played a vital role in the enzyme bioprocess. The enzyme production improved with the supplementation of maltose and yeast extract as carbon and nitrogen sources, respectively. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis and zymogram analysis of the purified protease indicated an estimated molecular mass of 46 kDa. The protease enzyme was stable over a temperature range of 40-50 °C and pH 6-9, with maximum activity at 50 °C and pH 8. Among the divalent ions tested, Ca(2+), Na(+) and Mg(2+) showed activities of 107 ± 0.7%, 103.5 ± 1.3%, and 104.6 ± 0.9, respectively. The enzyme showed stability in the presence of surfactants such as sodium dodecyl sulfate and on various commercially available detergents. The crude enzyme effectively de-haired goat hides within 18 h of incubation at 30 °C. The enzymatic properties of this protease suggest its suitable application as an additive in detergent formulation and also in leather processing. Based on the laboratory results, the use of cow dung for producing and extracting enzyme is not cumbersome and is easy to scale up. Considering its cheap cost and availability, cow dung is an ideal substrate for enzyme bioprocess in an industrial point of view.

In the present study, the silver nanoparticles (AgNPs) were synthesized from the bulbs of Allium sativum, characterized by UV-visible spectroscopy, FT-IR, SEM, HR-TEM, EDAX analysis and investigated its action on the inhibition of starch digestion. The results proved that the biosynthesized nanoparticles were uniformly dispersed, spherical shaped with the size ranging from 10 to 30 nm. The phytochemical and FT-IR analysis showed the presence of phenols, terpenoids, and amino acids in the synthesized AgNPs. The cytotoxicity analysis revealed that the synthesized AgNPs were non-toxic to the normal cells. The synthesized AgNPs exhibited significant free radical scavenging activity. The in vitro antidiabetic activity showed that the synthesized AgNPs increased glucose utilization, decreased hepatic glucose production, inhibited the activity of starch digestive enzymes such as α-amylase and α-glucosidase, and were not involved in the stimulation of pancreatic cells for the secretion of insulin. The in silico antidiabetic activity analysis (molecular docking) also revealed that the silver atoms of the AgNPs interacted with the amino acid residues of α-amylase, α-glucosidase, and insulin. The present study proved that the AgNPs synthesized from A. sativum have prominent antidiabetic activity in terms of reducing the hyperglycemia through the increased glucose utilization, decreased hepatic glucose production, and the inhibition of α-amylase and α-glucosidase enzymes. So it can be used as a promising nanomedicine for the treatment of diabetes.

The present investigation aims to establish the mechanical and wear behavior of Aluminum 7075 (Al7075) reinforced with Boron Carbide (B4C) (28 μm particle size) and Graphene (Gr) nano Particle (100 nm particle size) composites. These composites were prepared by stir casting process and also based on 5, 10 and 15 weight percentages (wt%) of B4C particles and 0.1, 0.2 and 0.3 wt% of Gr. Al7075 is reinforced with B4C and Gr particles for production of MMC. The mechanical properties like tensile strength, hardness, flexural, impact test and also wear properties like coefficient of friction and wear rate were investigated. The test results revealed that the tensile strength, flexural strength and hardness increased with increasing the wt% of B4C and Gr along with increase in toughness up to certain limits (10% B4C). Wear rate noticed with Gr reinforced with Al7075%-10%B4C composite is lower compared to other Al6061%-10%B4C-Gr with various Wt% composites. On comparison, the Al7075%-10%B4C-0.2%Gr composite shows better wear rate compared to other composites. TGA/DTA analysis shows that increase in % of B4C and Gr 17% increased the ignition period of the composites. The coefficient of friction and the specific wear rate were obtained in terms of sliding distance at various loads in the range of 5 N, 10 N and15 N. It was found that when B4C content in composites increase, the wear resistance also increases monotonically with hardness. In addition, the hybridization of two reinforcements enhanced the wear resistance of composites, especially in case of high sliding speeds.

Diabetic retinopathy (DR) is a microvascular complication of long‐term diabetes and it is the major cause of visual impairment because of changes in blood vessels of the retina. Major vision loss because of DR is highly preventable with regular screening and timely intervention at the earlier stages. The presence of exudates is one of the primitive signs of DR and the detection of these exudates is the first step in automated screening for DR. Hence, exudates detection becomes a significant diagnostic task, in which digital retinal imaging plays a vital role. In this study, the authors propose an algorithm to detect the presence of exudates automatically and this helps the ophthalmologists in the diagnosis and follow‐up of DR. Exudates are normally detected by their high grey‐level variations and they have used an artificial neural network to perform this task by applying colour, size, shape and texture as the features. The performance of the authors algorithm has been prospectively tested by using DIARETDB1 database and evaluated by comparing the results with the ground‐truth images annotated by expert ophthalmologists. They have obtained illustrative results of mean sensitivity 96.3%, mean specificity 99.8%, using lesion‐based evaluation criterion and achieved a classification accuracy of 99.7%.

Abstract Recently, industrial Internet of things becomes more popular and it involves a group of intelligent devices linked to create systems which observe, gather, communicate, and investigate data. In this view, the demand for compression techniques in remote sensing images is increasing since low complexity technique is required in spacecraft. Deep learning, for instance, convolutional neural network (CNN) has gained more attention in the domain of computer vision, particularly for high‐level applications like detection along with interpretation. At the same time, it is difficult to resolve the low‐level applications like image compression and it is investigated in this article. This article presents an optimal compression technique using CNNs for remote sensing images. The proposed method uses CNN for learning the compact representation of the original image which held the structural data and was then coded by Lempel Ziv Markov chain algorithm. Next, the encoded image was reconstructed to retrieve the original image with high reconstructed image quality. The proposed optimal compression technique is compatible with the available image codec standards. Wide range of experiments was carried out and the results were compared with binary tree and optimized truncation, JPEG, and JPEG2000 in terms of compression efficiency, reconstructed image quality, and space saving (SS). The obtained results apparently proved the effectiveness of the presented method, which attains an average peak signal to noise ratio of 49.90 dB and SS of 89.38%.

BACKGROUND: Image registration provides major role in real world applications and classic digital image processing. Image registration is carried out for more than one image and this image was captured from a different location, different sensors, different time and different viewpoints. DISCUSSION: This paper deals with the comparative analysis of various registration techniques and here six registration techniques depending upon intensity, phase correlation, image feature, area, control points and mutual information are compared. Comparative analysis for different methodologies shows the advantages of one method over the other methods. The foremost objective of this paper is to deliver a complete reference source for the scholars interested in registration, irrespective of specific application extents. CONCLUSION: Finally performance analyses are evaluated for the medical datasets and comparison is graphically shown with the MATLAB simulation tool.

BACKGROUND: The occurrence of drug resistant infectious disease causing microbial pathogens was highly spreaded because of the wide level application of the commercially available antimicrobial agents. However, the eradication of the microbial pathogens was of huge demand. Although, many antimicrobial compounds were commercially available in the market however the spreading of the pathogens were hugely increased. Actinomycetes produce various secondary metabolites against pathogenic bacteria and fungi. The present investigation aimed to study the antimicrobial potential of the Streptomyces sp. towards infectious diseases causing pathogens. METHODS: Culture dependable isolation techniques were followed for the isolation of the active actinomycetes isolates and the antimicrobial properties of the actinomcyetes were detected by primary screening techniques using modified starch casein agar medium. The active isolate was confirmed by various biochemical and morphological techniques. RESULTS: In this study, 10 actinomycetes were isolated and later five were selected for secondary screening and noted significant activity against Enterobacter aerogenes and Proteus mirabilis. Among the selected Streptomyces sp., ES2 showed potent activity against selected microbes and was identified as Streptomyces sp. The studied isolates were resisitant towards streptomycin (10μg), ampicillin (50μg) and ciprofloxacin (5μg). The organic solvent extracts of the promising isolate ES2 prononunced comparatively better inhibitory properties towards the studied pathogenic bacteria. CONCLUSION: Overall, the present study evidenced that the actinomycetes were promising candidate for the eradication of the pathogenic strains.

Magnetic drug targeting is a drug delivery system that can be used in loco-regional cancer treatment. Coated magnetic particles, called carriers, are very useful for delivering chemotherapeutic drugs. Magnetic carriers were synthesized by co-precipitation of iron oxide followed by coating with polyvinyl pyrrolidone (PVP). Characterization was performed using X-ray diffraction, TEM, TGA, FTIR and UV-Vis Spectroscopy. Magnetite (Fe3O4) remained as the core of the carrier. The amount of PVP bound to the iron oxide nanoparticles was estimated by thermogravimetric analysis (TGA) and the attachment of PVP to the iron oxide nanoparticles confirmed by FTIR analysis. The loading efficiency of Epirubicin hydrochloride onto the PVP coated and uncoated iron oxide nanoparticles was measured at intervals such as 1 hr and 24 hrs by UV-Vis Spectroscopy. The binding of Epirubicin hydrochloride to the PVP coated and uncoated iron oxide nanoparticles were confirmed by FTIR analysis. The present findings showed that Epirubicin hydrochloride loaded PVP coated iron oxide nanoparticles are promising for magnetically targeted drug delivery. The drug displayed increased cell cytotoxicity at lower concentrations when conjugated with the nanoparticles than being administered conventionally as individual drugs.

BACKGROUND AND AIMS: As annual crops develop, transpirational water loss increases substantially. This increase has to be matched by an increase in water uptake through the root system. The aim of this study was to assess the contributions of changes in intrinsic root hydraulic conductivity (Lp, water uptake per unit root surface area, driving force and time), driving force and root surface area to developmental increases in root water uptake. METHODS: Hydroponically grown barley plants were analysed during four windows of their vegetative stage of development, when they were 9-13, 14-18, 19-23 and 24-28 d old. Hydraulic conductivity was determined for individual roots (Lp) and for entire root systems (Lp(r)). Osmotic Lp of individual seminal and adventitious roots and osmotic Lp(r) of the root system were determined in exudation experiments. Hydrostatic Lp of individual roots was determined by root pressure probe analyses, and hydrostatic Lp(r) of the root system was derived from analyses of transpiring plants. KEY RESULTS: Although osmotic and hydrostatic Lp and Lp(r) values increased initially during development and were correlated positively with plant transpiration rate, their overall developmental increases (about 2-fold) were small compared with increases in transpirational water loss and root surface area (about 10- to 40-fold). The water potential gradient driving water uptake in transpiring plants more than doubled during development, and potentially contributed to the increases in plant water flow. Osmotic Lp(r) of entire root systems and hydrostatic Lp(r) of transpiring plants were similar, suggesting that the main radial transport path in roots was the cell-to-cell path at all developmental stages. CONCLUSIONS: Increase in the surface area of root system, and not changes in intrinsic root hydraulic properties, is the main means through which barley plants grown hydroponically sustain an increase in transpirational water loss during their vegetative development.

Abstract The viability of using cellulosic Cymbopogon flexuosus root (CFR) fiber waste from the industry as a reinforcing material in a polyester‐reinforced composite was investigated. Initially, CFR anatomy, mechanical, thermal, physio‐chemical, morphological, and spectroscopy behaviors were investigated. Spectroscopy and chemical analysis were evidence for the richness of cellulose content (74.33%) in the fiber which reflected in increased tensile strength of 315.22 ± 61.72 MPa and thermal stability 272.31°C. Fiber reinforcement was varied from 0 to 50 wt% at random orientation and mechanical, and water absorption properties were correlated with the glass fiber reinforced composite of the same weight percentage. The composite with a 40% fiber combination has an enhancement in mechanical, morphological, and thermal characterization. This comprehensive study confirms the usage of this bio‐material in replacing harmful synthetic material in structural, marine and mechanical industrial applications.

<b>Introduction:</b> Dermatophytosis are the most common fungal infections globally. Terbinafine is considered to have good potency against dermatophytes, but resistance to terbinafine is on the rise. <b>Objective:</b> The objective of this study was to evaluate the efficacy and safety of terbinafine 500 mg given once daily in treatment of patients with superficial dermatophytosis. <b>Materials and Methods:</b> It was a retrospective questionnaire-based survey. Each doctor was given survey questionnaire booklet containing survey forms. Clinical response was graded according to the improvement in the affected lesion. Mycological cure was defined as negative microscopy under potassium hydroxide examination and a negative culture in Sabouraud's dextrose agar. Patients were divided into three groups depending on the duration of therapy, Group A – terbinafine 500 mg for 2 weeks, Group B – terbinafine 500 mg for 4 weeks, and Group C – terbinafine 500 mg for 6 weeks. <b>Results:</b> Total 50 doctors completed the survey involving 440 patients. In Group A, out of 194 patients, 87% (<i>n</i> = 169) patients showed very good response. In Group B, out of 211 patients, 92% (<i>n</i> = 194) of the patients showed very good response with >75% improvement in their lesion. In Group C, out of 35 patients, 80% (<i>n</i> = 30) patients showed very good response. Adverse drug reactions of mild to moderate intensity related to terbinafine were seen in 57 patients. <b>Conclusion:</b> Our survey indicates that terbinafine in a dose of 500 mg given once daily was efficacious and safe in the treatment of patients with dermatophytosis.

In the past few years, big data has flattering more dominant in healthcare, due to three major reasons, such as the huge amount of data available, expanding healthcare costs, and a target on personalized care. Big data processing in healthcare refers to generating, collecting, analyzing, and holding clinical data that is too vast or complex to be inferred by classical means of data processing methods. Big data sources for healthcare include, the Internet of Things (IoT), Electronic Medical Record/Electronic Health Record (EMR/EHR) contains patientos medical history, diagnoses, medications, treatment plans, allergies, laboratory and test results, genomic sequencing, Medical Imaging, Insurance Providers and other clinical data. This paper discusses different machine learning algorithms that were applied to various healthcare data. Also, the challenges of processing, handling big data, and their applications. The scope of the paper is to elaborate on the application of machine learning algorithms and the need for handling and utilizing big data from a different perspective.