Variable - temperature scanning optical and force microscope

The implementation of a scanning microscope capable of working in confocal, atomic force and apertureless near field configurations is presented. The microscope is designed to operate in the temperature range 4 - 300 K, using conventional helium flow cryostats. In AFM mode, the distance between the sample and an etched tungsten tip is controlled by a self - sensing piezoelectric tuning fork. The vertical position of both the AFM head and microscope objective can be accurately controlled using piezoelectric coarse approach motors. The scanning is performed using a compact XYZ stage, while the AFM and optical head are kept fixed, allowing scanning probe and optical measurements to be acquired simultaneously and in concert. The free optical axis of the microscope enables both reflection and transmission experiments to be performed.Comment: 24 pages, 9 figures, submitted to the journal "Review of Scientific Instruments

Low temperature plasma-catalytic NOx synthesis in a packed DBD reactor: effect of support materials and supported active metal oxides

The direct synthesis of NOx from N2 and O2 by non-thermal plasma at an atmospheric pressure and low temperature is presented, which is considered to be an attractive option for replacement of the Haber-Bosch process. In this study, the direct synthesis of NOx was studied by packing different catalyst support materials in a dielectric barrier discharge (DBD) reactor. The support materials and their particle sizes both had a significant effect on the concentration of NOx. This is attributed to different surface areas, relative dielectric constants and particles shapes. The nitrogen could be fixed at substantially lowered temperatures by employing non-thermal plasma-catalytic DBD reactor, which can be used as an alternative technology for low temperature synthesis. The γ-Al2O3 with smallest particles size of 250–160 μm, gave the highest concentration of NOx and the lowest specific energy consumption of all the tested materials and particle sizes. The NOx concentration of 5700 ppm was reached at the highest residence time of 0.4 s and an N2/O2 feed ratio of 1 was found to be the most optimum for NOx production. In order to intensify the NOx production in plasma, a series of metal oxide catalysts supported on γ-Al2O3 were tested in a packed DBD reactor. A 5% WO3/γ-Al2O3 catalyst increased the NOx concentration further by about 10% compared to γ-Al2O3, while oxidation catalysts such as Co3O4 and PbO provided a minor (∼5%) improvement. These data suggest that oxygen activation plays a minor role in plasma catalytic nitrogen fixation under the studied conditions with the main role ascribed to the generation of microdischarges on sharp edges of large-surface area plasma catalysts. However, when the loading of active metal oxides was increased to 10%, NO selectivity decreased, suggesting possibility of thermal oxidation of NO to NO2 through reaction with surface oxygen species

Retroperitoneal Ancient Schwannoma

Schwannomas are rare tumors which arise from nerve sheath and are mostly benign in nature. They are usually located in the head, neck and flexor surfaces of extremities. Schwannomas are very rare in the retroperitoneal region. Amongst all schwannomas 0.7% of benign ones and 1.7% of malignant ones are located in the retroperitoneum. Preoperative diagnosis is difficult because of vague symptoms. We report a case of retroperitonal schwannoma in a 70 years female patient because of its rarity and unusual location

Early Breast Cancer Prediction using Machine Learning and Deep Learning Techniques

Breast Cancer (BC) is a considered as one of the utmost lethal diseases across the globe that has a very high morbidity and mortality rate. Accurate and early prediction along with diagnosis is one of the most crucial characteristics for the treatment of Breast Cancer. Doctors can have an edge over Breast cancer if they are able to predict it in its early stages using deep learning and machine learning techniques. This paper proposed consists of comparison between the and accuracy of various machine learning models like Support vector machine (SVM), K-Nearest Neighbours (KNN), Naïve Bayes (NB), Logistic Regression (LR), Random Forest (RF), Decision Tree (DT), XGB Classifier and deep learning model of Artificial neural networks (ANN) for the precise detection of breast cancer. The most crucial properties from the database have been chosen using one feature-selection technique. Correlation is also used to choose the most correlated features from the data. Implementing the ANN model consists of one input layer, two hidden layers, and one output layer. All Machine Learning models and ANN model are then applied to selected features. The results demonstrated that the SVM classifier achieved the highest performance with an accuracy of ~98.24%

Encapsulation of water insoluble drugs in mesoporous silica nanoparticles using supercritical carbon dioxide

Mesoporous silica nanoparticles MCM – 41 were synthesized with two dimensional hexagonal p6mm symmetry, high specific surface area(~ 980m2/g) narrow pore size and an average particle size of 186 nm. The produced nanoparticles were used to encapsulate carbamazepine through a supercritical carbon dioxide process combined with various organic solvents. Supercritical processing was found to provide increased drug encapsulation. The loaded MCM - 41 nanoparticles were analyzed using X–ray diffraction and differential scanning calorimetry (DSC) to investigate the crystalline state of the encapsulated carbamazepine and it was found to be dependent on the nature of the organic solvent. Carbamazepine showed increased dissolution rates under sink conditions. Viability studies of Caco – 2 cells demonstrated negligible cytotoxicity for the MCM–41 nanoparticles

KALYANAKARAKAM – A GEM OF AYURVEDA

Background: The origin of Ayurveda is lost in mysteries of time; since the earliest human civilization, man has sought ways to heal himself. Human civilization progressed, bringing in sophisticated thought & research behind medicine. It is believed that a system of medicine was prevalent in India in pre Vedic times. The Vedas are the earliest written records of the wisdom & insights of Indian seekers & scholars. Medicine is an ever changing science. Literary research is must in today’s perspective to get the hidden & unexplored knowledge. On this regard many Acharya’s contributed to ancient science i.e. Ayurveda. Jain seers have written several texts in Sanskrit on Ayurveda they are similar in content & finding to Vedic text. One among them is Kalyanakarakam, was composed by Acarya Ugraditya, a Jain monk who is believed to have lived in the 9th century of the Common Era. This text comprises of 667 Sanskrit hemistich divided into 25 chapters and one special section on predicting death. The chapters cover all aspects of Ayurveda with great depth and thoroughness. Aims & Objective: 1) To compile the literature bearing Svastha Rakshana i.e. preventive aspects in the form of Dinacharya (daily regimen), Rutu-charya (seasonal regimen) etc. &some other concepts like knowledge about Prakruti (nature) Desha (region), Kala (time), important anatomical structures, and regimens for pregnant women etc. Materials & Methods: Study aims to review the preventive aspects which are mentioned in Kalyanakarakam. Conclusion: Inculcating all the concepts which elucidates the concept of prevention is much essential in today’s perspective

EFFICACY OF SUPPLEMENTATION OF PROBIOTICS ALONG WITH ANTIMICROBIAL AGENTS IN VULVOVAGINAL INFECTIONS IN A TERTIARY CARE HOSPITAL

Objectives: The objectives of the study were to ascertain the efficacy of probiotics along with antimicrobials in the treatment of vulvovaginitis and to evaluate the rate of recurrence. Methods: The study was done on 60 patients who were randomly selected and divided into two groups of 30 each. Prior permission from the Institutional Ethics Committee and higher authorities was obtained before conducting the study. One group received standard treatment including antibacterial, antiviral, and antifungal as per the gynecologist discretion and in other group along with standard treatment, probiotic capsules containing combination of Saccharomyces boulardii, Lactobacillus sporogenes (50 million), Streptococcus faecalis (30 million), Clostridium butyricum (2 million), and Bacillus mesentericus (1 million) given orally twice daily and followed up for a period of 3 months. The drugs were started on the 5th day after menstruation taking starting of the bleeding as day 1. Results: The parameters compared were symptoms and signs (significantly reduced – p-value), clue cells (significantly reduced in number), and recurrence rates (significantly reduced), in 80% of patients smears which were not consistent with BV. Maximum number of patients showed negative KOH mount (71.5%), saline wet mount was negative in 80% of patients in antimicrobial agents + probiotics group. Conclusion: From the present interventional study, probiotics along with antimicrobial agents showed better improvement than antimicrobial agents alone. Hence, supplementation of probiotics along with antimicrobial agents provides better efficacy than antimicrobial agents alone in treating vulvovaginal infections