1,276 research outputs found
A study of prescription pattern in the drug therapy of acne vulgaris at a tertiary care hospital in Mangalore, India
Background: Acne Vulgaris is the most common skin disorder of the pilosebaceous unit with excess sebum production, follicular epidermal hyperproliferation, inflammation and Propionibacterium acnes activity, affecting about 80% of teenagers and has considerable psychological and social consequences and physical disability. Use of established topical and oral drugs assumes paramount importance in the treatment of acne vulgaris. Therefore, periodic auditing of prescription is necessary to increase therapeutic benefit and decrease adverse effects. Aim and objectives of the study was to evaluate the pattern of prescription and its rationale in the drug therapy of acne vulgaris. To monitor the adverse effects, if any.Methods: A prospective, hospital based, observational study. Data was collected for a period of 1 year from January 2015 to December 2015 from the outpatient records in the OPD of Dermatology at Justice K.S. Hegde Charitable Hospital, Deralakatte, Mangalore, in a specifically designed proforma.Results: The prescription data of 346 patients were analyzed of which 45.1% were males with an average age of 21.94±0.3 years. Among the four grades of Acne Vulgaris, Grade II (53.17%) was more prevalent followed by Grade I (26.58%), Grade III (13.87%) and Grade IV (6.35%). The number of drugs prescribed for topical use was 514 of which the most commonly prescribed drugs were Benzoyl Peroxide (19.46%), a combination of Tretinoin and Clindamycin (17.12%), Tretinoin alone (12.45%), Clindamycin alone (10.51%) etc. The number of drugs prescribed for systemic use was 98 consisting of Doxycycline (55.1%), Azithromycin (34.7%), Isotretinoin (6.12%) and Erythromycin (4.08%).Conclusions: There was rationality in most of the prescriptions giving no scope for polypharmacy
In Vitro Cytotoxicity Efficiency of Extracellular L-Glutaminase Produce by Mesophilic Bacteria, Kurthia Gibsonii on Lncap, MDA-MB 231 and Hepg-2 Cell Lines
Mesophilic bacteria from soil habitat have been reported to produce extracellular L-glutaminase. The present study was carried out to anticancer screening of L-glutamiase producing bacteria (Kurthia gibsonii) from soil sample of cattle feeding site from Satara parisar, Chhatrapati Sambhajinagar. Results showed, among three soil samples of cattle feeding farms, Kurthia gibsonii was isolated. From that exhibited the highest L-glutaminase activity. Moreover, the in vitro cytotoxic activity of L-glutaminase against the (Lymph Node Carcinoma of the Prostate) LNCaP, (an epithelial, human breast cancer cell line) MDA-MB 231 and hepatocellular (HepG-2) carcinoma cell lines at different concentration (0.47, 0.94, 1.88, 3.75, 7.50, 15.00, 30.00 and 60.00 μg/ml) by the MTT assay and compared with the standard Doxrubcin. The antitumor effect against human liver carcinoma cell line revealed that L-glutaminase produced by Kurthia gibsonii showed potent cytotoxic activity of tested cell line in a dose-dependent manner with an LC50 value of 4.1 μg/ml
Enhancing Prostate Cancer Diagnosis with Deep Learning: A Study using mpMRI Segmentation and Classification
Prostate cancer (PCa) is a severe disease among men globally. It is important
to identify PCa early and make a precise diagnosis for effective treatment. For
PCa diagnosis, Multi-parametric magnetic resonance imaging (mpMRI) emerged as
an invaluable imaging modality that offers a precise anatomical view of the
prostate gland and its tissue structure. Deep learning (DL) models can enhance
existing clinical systems and improve patient care by locating regions of
interest for physicians. Recently, DL techniques have been employed to develop
a pipeline for segmenting and classifying different cancer types. These studies
show that DL can be used to increase diagnostic precision and give objective
results without variability. This work uses well-known DL models for the
classification and segmentation of mpMRI images to detect PCa. Our
implementation involves four pipelines; Semantic DeepSegNet with ResNet50,
DeepSegNet with recurrent neural network (RNN), U-Net with RNN, and U-Net with
a long short-term memory (LSTM). Each segmentation model is paired with a
different classifier to evaluate the performance using different metrics. The
results of our experiments show that the pipeline that uses the combination of
U-Net and the LSTM model outperforms all other combinations, excelling in both
segmentation and classification tasks.Comment: Accepted at CISCON-202
Studies on Characteristic of Extracellular L–Glutaminase and Identification of L-Glutaminase Producing Bacterial Strain from Cattle Feeding Farm of Chhatrapati Sambhajinagar, Maharashtra State, India
L-glutaminase is gaining marked importance due to its potential clinical applications. A variety of microorganisms, including bacteria, yeast, and lamentous fungi, from soil habitat have been reported to produce L-glutaminase. The present investigation was carried out to isolate and screening of L-glutamiase producing bacteria from soil samples of cattle feeding sites. Among twenty three soil samples of cattle feeding farms around Aurangabad, nineteen bacteria’s were isolated. From that one isolate (AGT-19) that showed significant L-glutaminase activity. Morphological characteristics and 16S rRNA sequencing were used for phylogenetic analysis to identified strain AGT-19 as Kurthia gibsonii. Moreover, Kurthia gibsonii was grown in a medium containing 2.5% succinate and 2.5% L-glutamine showed significant activity of L-glutaminase (0.079 U/mg). The optimum conditions for L-glutaminase production were temperature was 39°C and pH was 7.0. The present isolation of K. gibsonii from cattle feeding site indicated that this bacterium is suitably adapted to the environment of excretion and to point of forming a microbiota in the fecal product. It revealed that soil of cattle feeding farm has diverse bacterial strains and its habitat nature allowed the bacteria expressed the protease activity
First-Principles Calculation of Born Effective Charges and Spontaneous Polarization of Ferroelectric Bismuth Titanate
In this study, we present the results of our first-principles calculations of
the band structure, density of states and the Born effective charge tensors for
the ferroelectric (ground state B1a1) and paraelectric (I4/mmm) phases of
bismuth titanate. The calculations are done using the generalized gradient
approximation (GGA) as well as the local density approximation (LDA) of the
density functional theory. In contrast to the literature, our calculations on
B1a1 structure using GGA and LDA yield smaller indirect band gaps as compared
to the direct band gaps, in agreement with the experimental data. The density
of states shows considerable hybridization among Ti 3d, Bi 6p and O 2p states
indicating covalent nature of the bonds leading to the ferroelectric
instability. The Born effective charge tensors of the constituent ions for the
ground state (B1a1) and paraelectric (I4/mmm) structures were calculated using
the Berry phase method. This is followed by the calculation of the spontaneous
polarization for the ferroelectric B1a1 phase using the Born effective charge
tensors of the individual ions. The calculated value for the spontaneous
polarization of ferroelectric bismuth titanate using different Born effective
charges was found to be in the range of 55+/-13 C/cm2 in comparison to the
reported experimental value of (50+/-10 C/cm2) for single crystals. The
origin of ferroelectricity is attributed to the relatively large displacements
of those oxygen ions in the TiO6 octahedra that lie along the a-axis of the
bismuth titanate crystal.Comment: 36 pages, 5 figure
Public health response to a measles outbreak in a large correctional facility, Queensland, 2013
This report documents the prompt, co-ordinated and effective public health response to a measles outbreak in Queensland in 2013. There were 17 cases in a large, high-security, regional correctional facility, a setting with unique challenges. Recommendations are provided to reduce the likelihood and magnitude of measles outbreaks in correctional facilities
Band-Engineered LaFeO-LaNiO Thin Film Interfaces for Electrocatalysis of Water
Transition metal oxides have generated significant interest for their
potential as catalysts for the oxygen evolution reaction (OER) in alkaline
environments. Iron and nickel-based perovskite oxides have proven particularly
promising, with catalytic over-potentials rivaling precious metal catalysts
when the alignment of the valence band relative to the OER reaction potential
is tuned through substitutional doping or alloying. Here we report that
engineering of band alignment in LaFeO/LaNiO (LFO/LNO)
heterostructures via interfacial doping yields greatly enhanced catalytic
performance. Using density functional theory modeling, we predict a 0.2 eV
valence band offset (VBO) between metallic LNO and semiconducting LFO that
significantly lowers the barrier for hole transport through LFO compared to the
intrinsic material and make LFO a p-type semiconductor. Experimental band
alignment measurements using in situ X-ray photoelectron spectroscopy of
epitaxial LFO/LNO heterostructures agree quite well with these predictions,
producing a measured VBO of 0.3(1) eV. OER catalytic measurements on the same
samples in alkaline solution show an increase in catalytic current density by a
factor of ~275 compared to LFO grown on n-type Nb-doped SrTiO. These
results demonstrate the power of tuning band alignments through interfacial
band engineering for improved catalyticComment: 13 pages, 5 figures; Supplemental info: 5 pages, 5 figure
Colorimetric method for simultaneous estimation of amlodipine besylate from plasma
Aim: The present work was to develop the method of analysis which can estimate drug in combined form without prior separation.
Materials and method: By using UV spectroscopy colorimetric method was used for determination of Amlodipine besylate (AML) from plasma.
Result and conclusion: This method is based on the formation of green colour in reaction between AML and 0.4 % Ferric chloride (FC) and 0.2 % Potassium ferricyanide (PF).The absorbance was measured at 775 nm. Result of tablet analysis showed % S.D. values in the range of 098.22 to 100,63%.
Standard deviation value for tablet analysis by using methanol ranging from 98.01 to 101,13 % which proves the ability of the method to remain unaffected by small but deliberate change in reaction conditions and this method is used for estimation of AML from biological samples.Objetivo. El objetivo del presente estudio era desarrollar un método de análisis que permitiera estimar la cantidad de fármaco en forma combinada sin separación previa.
Material y Método. Se utilizó espectroscopÃa colorimétrica UV para la determinación de Amlodipino Besilato (AML) plasmático
Resultados. El presente método está basado en la formación de color verde en la reacción entre Amlodipino Besilato (AML) y cloruro férrico 0,4% y ferrocianuro potásico 0,2%. La medida de la absorbancia se realizó a 775nm. El resultado del análisis de los comprimidos mostró unos valores de DE comprendidos entre 098,22 y 100,63%. El valor de la DE utilizando metanol oscilan entre 98,01
y 101,13% lo que demuestra la capacidad del método de permanecer inalterado por pequeños pero intencionados cambios en las condiciones de la reacción, este método es usado para la estimación de Amlodipino Besilato (AML) en muestras biológicas
Analysis of Genetic Diversity in Twelve Cultivars of Pea Based on Morphological and Simple Sequence Repeat Markers
Pea(Pisum sativum L.)is the second most important legume crop worldwide after chickpea (Cicer arietinum L.) and valuable resources for their genetic improvement. This study aimed to analyze genetic diversity of pea cultivars through morphological and molecular markers. The present investigation was carried out with 12 pea cultivars using 28 simple sequence repeat markers. A total of 60 polymorphic bands with an average of 2.31 bands per primer were obtained. The polymorphic information content, diversity index and resolving power were ranged from 0.50 to 0.33, 0.61 to 0.86 and 0.44 to 1.0 with an average of 0.46, 0.73 and 0.76, respectively. The 12 pea cultivars were grouped into 3 clusters obtained from cluster analysis with a Jaccardd's similarity coefficient range of 0.47-0.78, indicating the sufficient genetic divergence among these cultivars of pea. The principal component analysis showed that first three principal components explained 86.97% of the total variation, suggesting the contribution of quantitative traits in genetic variability. The contribution of 32.59% for number of seeds per plant, stem circumference, number of pods per plant and number of seeds per pod in the PC1 leads to the conclusion that these traits contribute more to the total variation observed in the 12 pea cultivars and would make a good parental stock material. Overall, this SSR analysis complements morphological characters of initial selection of these pea germplasms for future breeding program
- …