Preliminary phytochemical studies for the quantification of secondary metabolites of medicinal importance in the plant, Acalypha fruticosa Forssk

The medicinal plant, Acalypha fruticosa Forssk for the treatment of dyspepsia, stomachache, fever, jaundice, skin diseases and even as an antidote is generally distributed in different environments of tropical region in Coimbatore district of Tamil Nadu. However, its occurrence is more common in lower hills of Western Ghats and other habitats in this region where the soil is stony with low moisture. So far, there was no study on the influence of habitat conditions on the change in the content of secondary metabolites of medicinal importance in this plant. Hence to know the changes in the content of such secondary metabolites in the leaves of A. fruticosa, the present study was undertaken in three different habitats. Thin layer chromatography revealed the presence of phytochemical compounds viz., alkaloids, flavonoids and saponins in the leaves of all the three populations. Further the content of all these compounds are found to be higher in the population of dry habitats

Multilayer vectorization to develop a deeper image feature learning model

Computer-Aided Diagnosis (CAD) approaches categorise medical images substantially. Shape, colour, and texture can be problem-specific in medical imagery. Conventional approaches rely largely on them and their relationship, resulting in systems that can\u27t illustrate high-issue domain ideas and have weak prototype generalization. Deep learning techniques deliver an end-to-end model that classifies medical photos thoroughly. Due to the improved medical picture quality and short dataset size, this approach may have high processing costs and model layer restrictions. Multilayer vectorization and the Coding Network-Multilayer Perceptron (CNMP) are merged with deep learning to handle these challenges. This study extracts a high-level characteristic using vectorization, CNN, and conventional characteristics. The model\u27s steps are below. The input picture is vectorized into a few pixels during preprocessing. These pixel images are delivered to a coding network being trained to create high-level classification feature vectors. Medical imaging fundamentals determine picture properties. Finally, neural networks combine the collected features. The recommended technique is tested on ISIC2017 and HIS2828. The model\u27s accuracy is 91% and 92%

Simultano UV-spektrofotometrijsko određivanje ramiprila, acetilsalicilne kiseline i atorvastatin kalcija u kapsulama primjenom kemometrijskih metoda

In the present work, three different spectrophotometric methods for simultaneous estimation of ramipril, aspirin and atorvastatin calcium in raw materials and in formulations are described. Overlapped data was quantitatively resolved by using chemometric methods, viz. inverse least squares (ILS), principal component regression (PCR) and partial least squares (PLS). Calibrations were constructed using the absorption data matrix corresponding to the concentration data matrix. The linearity range was found to be 1-5, 10-50 and 2-10 µg mL–1 for ramipril, aspirin and atorvastatin calcium, respectively. The absorbance matrix was obtained by measuring the zero-order absorbance in the wavelength range between 210 and 320 nm. A training set design of the concentration data corresponding to the ramipril, aspirin and atorvastatin calcium mixtures was organized statistically to maximize the information content from the spectra and to minimize the error of multivariate calibrations. By applying the respective algorithms for PLS 1, PCR and ILS to the measured spectra of the calibration set, a suitable model was obtained. This model was selected on the basis of RMSECV and RMSEP values. The same was applied to the prediction set and capsule formulation. Mean recoveries of the commercial formulation set together with other figures of merit (calibration sensitivity, selectivity, limit of detection, limit of quantification and analytical sensitivity) were estimated. Validity of the proposed approaches was successfully assessed for analyses of drugs in the various prepared physical mixtures and formulations.U radu su opisane tri različite spektrofotometrijske metode za određivanje ramiprila, acetilsalicilne kiseline i atorvastatin kalcija u sirovinama i formulacijama. Preklapanje podataka kvantitativno je riješeno pomoću kemometrijskih metoda, tj. metodama inverznih najmanjih kvadrata (ILS), regresije glavnog sastojka (PCR) i djelomičnih najmanjih kvadrata (PLS). Kalibracije su postavljene pomoću matrice podataka za apsorpciju koja odgovara matrici pripadajućih koncentracija. Područje linearnosti za ramipril iznosilo je 1–5, za acetilsalicilnu kiselinu 10–50, a za atorvastatin kalcij 2–10 µg mL–1. Matrica s apsorbancijama dobivena je mjerenjem apsorbancije nultog reda na valnim duljinama između 210 i 320 nm. Set podataka za koncentracije ramiprila, acetilsalicilne kiseline i atorvastatin kalcija u smjesi statistički je tako organiziran da osigura maksimalnu količinu informacije u spektrima i minimalizira grešku multivarijantnih kalibracija. Primjenom odgovarajućih algoritama za PLS, PCR i ILS na snimljene spektre kalibracijskog seta dobiven je dobar model, koji je odabran na temelju RMSECV i RMSEP vrijednosti. Isti model je primijenjen i na set s predviđenim vrijednostima i na kapsule sa smjesom ove tri ljekovite tvari. Određena je srednja vrijednost povrata za komercijalnu formulaciju te ostale analitičke izvedbene značajke (kalibracijska osjetljivost, selektivnost, granica dokazivanja, granica određivanja i analitička osjetljivost). Potvrđena je primjenjljivost predloženih metoda u analizama lijekova u fizičkim smjesama i u gotovim ljekovitim oblicima

Phage Displayed Short Peptides against Cells of Candida albicans Demonstrate Presence of Species, Morphology and Region Specific Carbohydrate Epitopes

Candida albicans is a commensal opportunistic pathogen, which can cause superficial infections as well as systemic infections in immuocompromised hosts. Among nosocomial fungal infections, infections by C. albicans are associated with highest mortality rates even though incidence of infections by other related species is on the rise world over. Since C. albicans and other Candida species differ in their susceptibility to antifungal drug treatment, it is crucial to accurately identify the species for effective drug treatment. Most diagnostic tests that differentiate between C. albicans and other Candida species are time consuming, as they necessarily involve laboratory culturing. Others, which employ highly sensitive PCR based technologies often, yield false positives which is equally dangerous since that leads to unnecessary antifungal treatment. This is the first report of phage display technology based identification of short peptide sequences that can distinguish C. albicans from other closely related species. The peptides also show high degree of specificity towards its different morphological forms. Using fluorescence microscopy, we show that the peptides bind on the surface of these cells and obtained clones that could even specifically bind to only specific regions of cells indicating restricted distribution of the epitopes. What was peculiar and interesting was that the epitopes were carbohydrate in nature. This gives insight into the complexity of the carbohydrate composition of fungal cell walls. In an ELISA format these peptides allow specific detection of relatively small numbers of C. albicans cells. Hence, if used in combination, such a test could help accurate diagnosis and allow physicians to initiate appropriate drug therapy on time

Deflection of Steel Reinforced Concrete Beam Prestressed With CFRP Bar

Carbon Fiber Reinforced polymer (CFRP) bars are weak in yielding property which results in sudden failure of structure at failure load. Inclusion of non-pretensioned steel reinforcement in the tension side of CFRP based prestressed concrete beam will balance the yielding requirements of member and it will show the definite crack failure pattern before failure. Experimental investigation has been carried out to study the deflection behavior of partially prestressed beam. Experimental works includes four beam specimens stressed by varying degree of prestressing. The Partial Prestressing Ratio (PPR) of specimen is considered for experimental works in the range of 0.6 to 0.8. A new deflection model is recommended in the present study considering the strain contribution of CFRP bar and steel reinforcement for the fully bonded member. New deflection model converges to experimental results with the error of less than 5%

Deflection of Steel Reinforced Concrete Beam Prestressed with CFRP Bar

Carbon Fiber Reinforced polymer (CFRP) bars are weak in yielding property which results in sudden failure of structure at failure load. Inclusion of non-pretensioned steel reinforcement in the tension side of CFRP based prestressed concrete beam will balance the yielding requirements of member and it will show the definite crack failure pattern before failure. Experimental investigation has been carried out to study the deflection behavior of partially prestressed beam. Experimental works includes four beam specimens stressed by varying degree of prestressing. The Partial Prestressing Ratio (PPR) of specimen is considered for experimental works in the range of 0.6 to 0.8. A new deflection model is recommended in the present study considering the strain contribution of CFRP bar and steel reinforcement for the fully bonded member. New deflection model converges to experimental results with the error of less than 5%

BREAST CANCER: TYPES, EPIDEMIOLOGY & AETIOLOGY -A REVIEW

ABSTRACT Breast carcinoma is the most widespread cancer in women worldwide. Breast cancer is the most common cancer among women and is the second leading cause of cancer related death. According to the American Cancer Society, about 2 49,100 women will be diagnosed with breast cancer and more than 39,840 women are expected to die from breast cancer in 20111. The average women's lifetime risk of developing breast cancer is approximately 12%. The risk factors involved in the development of breast cancer include: older age, environmental factors, early menarche, late menopause, family history, prolonged hormone replacement therapy and alcohol consumption. A number of genes including BRCA1, BRCA2, HER-2 are also identified as causative agents. Hence this review highlights the types, epidemiology and causes of breast cancer briefly