Awareness of over the counter antibiotics to combat antimicrobial resistance

Background: In India there is wide use of over the counter (OTC) antibiotics and unawareness of its harmful effects. In India dispensing antibiotics without prescription is a major contribution factor in development of antimicrobial resistance (AMR). The objectives of the present study were to evaluate awareness and proper use of OTC antibiotics in the community.Methods: Responses to a questionnaire covering various aspects on awareness and usage of OTC antibiotics were obtained from 100 families and 100 pharmacy shops in the community by second year MBBS students after permission from institutional ethical committee. The study period was from January 2019 to June 2019.Results: Among 100 responders 78% used OTC antibiotics for frequently reported illness like common cold (58%), body- ache (19%), fever (13%) and cough (10%). Most common reason for using OTC antibiotic is to avoid high consultation fees (64%).76% pharmacy dispense antibiotics without prescription. 60% pharmacy unaware of increase chance of developing resistance due to OTC antibiotics. 80% pharmacy maintain register book and were aware of laws and regulations of OTC prescription but still 70% dispense drugs due to fear of losing sales and profit. 50% pharmacy said they encourage patients to consult the physician and get the prescription. Most common antibiotic sold without prescription is amoxicillin (51%) and azithromycin (38%).Conclusions: We have identified unawareness among people about use and harmful effects of using OTC antibiotics. Also pharmacies are not following rules and regulations for OTC drugs. So our aim is to increase public knowledge of proper use and harmful effects of OTC antibiotics and help our global program to reduce AMR

The FASHION Visual Search using Deep Learning Approach

In recent years, the World Wide Web (WWW) has established itself as a popular source of information. Using an effective approach to investigate the vast amount of information available on the internet is essential if we are to make the most of the resources available. Visual data cannot be indexed using text-based indexing algorithms because it is significantly larger and more complex than text. Content-Based Image Retrieval, as a result, has gained widespread attention among the scientific community (CBIR). Input into a CBIR system that is dependent on visible features of the user\u27s input image at a low level is difficult for the user to formulate, especially when the system is reliant on visible features at a low level because it is difficult for the user to formulate. In addition, the system does not produce adequate results. To improve task performance, the CBIR system heavily relies on research into effective feature representations and appropriate similarity measures, both of which are currently being conducted. In particular, the semantic chasm that exists between low-level pixels in images and high-level semantics as interpreted by humans has been identified as the root cause of the issue. There are two potentially difficult issues that the e-commerce industry is currently dealing with, and the study at hand addresses them. First, handling manual labeling of products as well as second uploading product photographs to the platform for sale are two issues that merchants must contend with. Consequently, it does not appear in the search results as a result of misclassifications. Moreover, customers who don\u27t know the exact keywords but only have a general idea of what they want to buy may encounter a bottleneck when placing their orders. By allowing buyers to click on a picture of an object and search for related products without having to type anything in, an image-based search algorithm has the potential to unlock the full potential of e-commerce and allow it to reach its full potential. Inspired by the current success of deep learning methods for computer vision applications, we set out to test a cutting-edge deep learning method known as the Convolutional Neural Network (CNN) for investigating feature representations and similarity measures. We were motivated to do so by the current success of deep learning methods for computer vision applications (CV). According to the experimental results presented in this study, a deep machine learning approach can be used to address these issues effectively. In this study, a proposed Deep Fashion Convolution Neural Network (DFCNN) model that takes advantage of transfer learning features is used to classify fashion products and predict their performance. The experimental results for image-based search reveal improved performance for the performance parameters that were evaluated

A Reliable Network Routing Protocol Design with an Intelligent Mobile Sink and Energy Efficiency over Wireless Sensor Network

This is crucial for the successful operation of a Wireless Sensor Network, frequently called as WSN as each of the sensor nodes in the network's structure are in charge of transmitting the information from its original source to its final destination. Several researchers have developed a Mobile sink in an effort to enhance transmission quality. Although it has been shown to be beneficial, the network's overall reliability is compromised by the much more energy-intensive operation of the nodes. In this research, we offer a routing strategy that makes use of cluster and source portability to drastically reduce power usage. We have given this protocol its name: the Intelligent Mobile Sink Assisted Routing Protocol (IMSARP).  To get started, we divide an entire sensor environment into regions, and within each of them, members cast proportional votes to choose who will serve as the Cluster-Head (CH). To determine how to choose the most efficient choice, nodes in the network evaluate the power consumption of all feasible routes. The proposed IMSARP method uses a cluster-based paradigm to construct a mobile-sink routing protocol. The standard quantity of energy within all the clusters serves as what drives the sink's motion. The outcomes section of this research proves the legitimacy and maintains the credibility of the proposed system by presenting the results, which include throughput, delay reduction, energy efficiency, and data transfer rate

Parachordoma: a rare recurring case at a rare site

Parachordoma is an uncommon tumor of soft tissue and the orign is not clear. This soft tissue tumor resembles chordomas as well as extraskeletal myxoid chondrosarcomas and has only recently been fully characterized. Although it is considered a benign lesion, its behavior tends to be locally aggressive, with reports of a recurrence rate of up to 20% and of several cases of metastasis. In this article, we report a case of parachordoma in the neck with recurrence that we met in clinical works

Influence of Tinospora cordifolia on wound healing in wistar rats

Background: T.cordifolia is widely used in veterinary folk medicine ayurvedic system of medicine. It is known to possess various properties. In a study T.cordifolia promoted wound healing in diabetic patients. However, one study showed that octacosanol content in T.cordifolia possessed anti-angiogenic activity which can hinder wound healing. Therefore, effect of T.cordifolia on wound healing appears to be controversial and there is scarcity of information regarding its effect on wound healing in animal models.Methods: Excision wound, resutured incision wound and dead space wounds were inflicted under light thiopentone anesthesia in male wistar rats (n=6 in each group). Methanol extract of T.cordifolia stem in the dose of 250 mg/kg was administered orally once a day for 10 days in resutured incision (assessed by wound breaking strength), dead space (granuloma dry weight and histopathology of granulation tissue) excision wounds was monitored by planimetry. Data was expressed as mean±SEM and analyzed by student’s t-test. p <0.05 was considered as significant.Results: The results of the present study revealed that T.cordifolia significantly promotes wound healing in all the three models viz. enhanced wound contraction and decreased days for complete epithelization in excision wound; increased breaking strength in resutured incision wound; increased granuloma dry weight and cellular infiltration in granulation tissue.Conclusions: T.cordifolia significantly (p<0.05) promoted wound healing in all the three models of wound in male wistar rats

Is fumigation enough for air conditioning units in operation theatres and Intensive care units?

Background:Strict asepsis is necessary in operating theatres (OT) and intensive care units (ICU) as the patients undergo invasive procedures. The filters of contaminated air conditioning (AC) units provide a niche for proliferation of fungi and production of fungal spores.Methods: The routine procedure for maintenance of sterile atmosphere in our hospital, i.e. fumigation and mopping walls with disinfectants often fail to address these fungal spores of the AC filters. We therefore carried out a surveillance of the ACs in ICUs and OTs to find the level of contamination with fungal spores and also to improvise on intervention strategies to tackle the problem. Over 3 months period, 34 ACs from 7 OTs and 2 ICUs were screened by taking 2 swabs from each AC which were then tested for the presence of fungal spores as per standard methods.Results: The contamination rate was 88.2% before fumigation and 76.9% after fumigation. The fungal spore contamination rate was reduced to 20% (1 out of 5 ACs) after servicing of the ACs was done. Aspergillus spp. was the most common fungal isolate.Conclusion: Based on the observations, we recommend regular servicing of the ACs as well as wet mopping of the ducts with sporicidal solution at regular intervals.

GREEN SYNTHESIS OF SILVER NANOPARTICLE FROM LEAF EXTRACT OF AEGLE MARMELOS AND EVALUATION OF ITS ANTIBACTERIAL ACTIVITY

Objective: The synthesis of metal nanoparticle is a growing area of research in modern material science and technology. Utilization of the silver nanoparticles in the field of biomedical nanotechnology and nanomedicines is rapidly growing because of their antimicrobial, anticancer, antioxidant property and less toxicity. Nanoparticles are synthesized by chemical methods, but are not eco-friendly. The objective of the study is to develop a fast, eco-friendly and convenient method for silver nanoparticle synthesis.Methods: In this method utilization of the reducingproperty of Aegle marmelos leaf extract was done for synthesis of stable silver nanoparticles.  Characterization of the metal nanoparticles was carried out by UV- Vis spectroscopy, Fourier Transform Infrared Spectroscopy (FTIR), Scanning Electron Microscopy (SEM), X-ray Diffraction microscopy (XRD), Energy Dispersive X-ray spectroscopy (EDX) and zeta potential analysis.Results: This result showed the average particle size of 15 -30 nm and spherical structure of stable silver nanoparticles. Green synthesized nanoparticles tested for its antibacterial activity by the well diffusion method. Silver nanoparticles had shown a more inhibitory effect against Streptococcus pyogenes, Escherichia coli, and Pseudomonas aeruginosa than Staphylococcus aureus and Aeromonas hydrophila at 25, 50 and 100 µg/ml concentrations.Conclusion: This study is recommends the use of Aegle marmelos leaves for the synthesis of silver nanoparticles and can be applied as an antimicrobial agent.Â