A CRITICAL REVIEW AND SIGNIFICANCE OF LIPID-BASED AYURVEDIC DOSAGE FORMS GHRITA AND TAILA: PART I-REVIEW AND STATUS

This review discusses in detail one of the oldest lipid-based dosage form, Sneha Kalpana as described in Ayurved, one of the ancient medical systems. Here the vital constituents of plants are extracted as assimilates in lipid forms, ghrit–the clarified butter or taila–the oil. These dosage forms are administered through different routes for specific therapeutic benefits varying from topical nourishment, anti-inflammatory activity, and healing of tissue systems or even to treat serious neuro-muscular or neurological conditions. This review highlights the basic concepts of Ayurved behind the drug delivery approach and provides details of different processes of preparation or manufacture. Lipid-based drug delivery systems (LBDDS) are one of the emerging technologies designed to address the challenges of solubility and bioavailability of poorly water-soluble ingredients. Understanding the principles behind the processes–the right amount of heat, time, and intensity is important for standardization to ensure the availability of bio constituents. Also, it is essential to understand the relevance of therapeutic principles behind these dosage forms to choose an appropriate technological adaptation for its optimum clinical effectiveness

Ayurveda and Traditional Chinese Medicine: A Comparative Overview

Ayurveda, the traditional Indian medicine (TIM) and traditional Chinese medicine (TCM) remain the most ancient yet living traditions. There has been increased global interest in traditional medicine. Efforts to monitor and regulate herbal drugs and traditional medicine are underway. China has been successful in promoting its therapies with more research and science-based approach, while Ayurveda still needs more extensive scientific research and evidence base. This review gives an overview of basic principles and commonalities of TIM and TCM and discusses key determinants of success, which these great traditions need to address to compete in global markets

An analytical survey of promotional drug literatures at C. U. Shah Medical College and Hospital, Surendranagar

Background: The research and marketing of a new drug requires a lot of money by the pharmaceutical companies. Promotion through advertising brochures and leaflets is widely used to influence the physicians. Most of the times, this information is the only source of new drug information for the physicians. Hence, this study to analyze the appropriateness, accuracy, and validity of promotional drug literatures was undertaken.Methods: Promotional materials were collected from outpatient departments of C. U. Shah Medical College and Hospital, Surendranagr. They were evaluated according to the “WHO criteria, 1988,” and the references cited to support the claims were checked for their validity and authenticity. The images and the pictorial content were evaluated to find out any biased nature of gender representation.Results: Evaluation of the total 486 brochures showed that none of them fulfilled all the nine criteria. Of the 308 claims, only 208 (42.79%) gave references to support the claims. Only 27 (39.13%) of the research articles among the 125 journal article cited were of high methodological quality. Among the 218 human figures, 144 were patients, and 103 were doctors. Female patients (62.5%) were depicted more than male patients (37.5%).Conclusion: The present study showed that pharmaceutical companies do not strictly follow the WHO guidelines and majority of the research were sponsored by companies. Hence, more stringent regulations need to be implemented for the proper promotion and dissemination of information about the new drugs

Technology for Improving Street Dog Welfare and Capturing Data in Digital Format during Street Dog Sterilisation Programmes

Street dogs survive on food handouts provided by individuals, or the wider community yet typically receive limited to no veterinary care. They can also carry a variety of zoonotic diseases such as rabies, posing a significant risk to human and dog population health. Dog sterilization is one of the most humane and effective methods available to control street dog populations. Dog sterilization programs, particularly those operating at a large-scale, often face a variety of challenges including limited resources, staffing, and less-than-ideal facilities. Record keeping is often a challenge as well, which can complicate the return of a sterilized dog to their location of capture. Street dogs are territorial, and the return of a dog to an incorrect location is fraught with various welfare issues, as well as an increased risk of postoperative complications, including death. Humane Society International developed a mobile phone-based application called ‘HSIApps’ drawing on years of field experience and data collection in street dog location recording, as well as clinical and postoperative treatment. HSIApps facilitates the return of dogs back to their exact captured location, which ensures dog welfare, and generates reports of a variety of useful data variables to maximize the efficacy and reliability of sterilization programs

A low-cost machine learning-based cardiovascular/stroke risk assessment system: integration of conventional factors with image phenotypes

Background: Most cardiovascular (CV)/stroke risk calculators using the integration of carotid ultrasound image-based phenotypes (CUSIP) with conventional risk factors (CRF) have shown improved risk stratification compared with either method. However such approaches have not yet leveraged the potential of machine learning (ML). Most intelligent ML strategies use follow-ups for the endpoints but are costly and time-intensive. We introduce an integrated ML system using stenosis as an endpoint for training and determine whether such a system can lead to superior performance compared with the conventional ML system.Methods: The ML-based algorithm consists of an offline and online system. The offline system extracts 47 features which comprised of 13 CRF and 34 CUSIP. Principal component analysis (PCA) was used to select the most significant features. These offline features were then trained using the event-equivalent gold standard (consisting of percentage stenosis) using a random forest (RF) classifier framework to generate training coefficients. The online system then transforms the PCA-based test features using offline trained coefficients to predict the risk labels on test subjects. The above ML system determines the area under the curve (AUC) using a 10-fold cross-validation paradigm. The above system so-called "AtheroRisk-Integrated" was compared against "AtheroRisk-Conventional", where only 13 CRF were considered in a feature set.Results: Left and right common carotid arteries of 202 Japanese patients (Toho University, Japan) were retrospectively examined to obtain 395 ultrasound scans. AtheroRisk-Integrated system [AUC=0.80, P<0.0001, 95% confidence interval (CI): 0.77 to 0.84] showed an improvement of similar to 18% against AtheroRisk-Conventional ML (AUC=0.68, P<0.0001, 95% CI: 0.64 to 0.72).Conclusions: ML-based integrated model with the event-equivalent gold standard as percentage stenosis is powerful and offers low cost and high performance CV/stroke risk assessment

Integration of cardiovascular risk assessment with COVID-19 using artificial intelligence

Artificial Intelligence (AI), in general, refers to the machines (or computers) that mimic "cognitive" functions that we associate with our mind, such as "learning" and "solving problem". New biomarkers derived from medical imaging are being discovered and are then fused with non-imaging biomarkers (such as office, laboratory, physiological, genetic, epidemiological, and clinical-based biomarkers) in a big data framework, to develop AI systems. These systems can support risk prediction and monitoring. This perspective narrative shows the powerful methods of AI for tracking cardiovascular risks. We conclude that AI could potentially become an integral part of the COVID-19 disease management system. Countries, large and small, should join hands with the WHO in building biobanks for scientists around the world to build AI-based platforms for tracking the cardiovascular risk assessment during COVID-19 times and long-term follow-up of the survivors

Convalescent plasma in patients admitted to hospital with COVID-19 (RECOVERY): a randomised controlled, open-label, platform trial

SummaryBackground Azithromycin has been proposed as a treatment for COVID-19 on the basis of its immunomodulatoryactions. We aimed to evaluate the safety and efficacy of azithromycin in patients admitted to hospital with COVID-19.Methods In this randomised, controlled, open-label, adaptive platform trial (Randomised Evaluation of COVID-19Therapy [RECOVERY]), several possible treatments were compared with usual care in patients admitted to hospitalwith COVID-19 in the UK. The trial is underway at 176 hospitals in the UK. Eligible and consenting patients wererandomly allocated to either usual standard of care alone or usual standard of care plus azithromycin 500 mg once perday by mouth or intravenously for 10 days or until discharge (or allocation to one of the other RECOVERY treatmentgroups). Patients were assigned via web-based simple (unstratified) randomisation with allocation concealment andwere twice as likely to be randomly assigned to usual care than to any of the active treatment groups. Participants andlocal study staff were not masked to the allocated treatment, but all others involved in the trial were masked to theoutcome data during the trial. The primary outcome was 28-day all-cause mortality, assessed in the intention-to-treatpopulation. The trial is registered with ISRCTN, 50189673, and ClinicalTrials.gov, NCT04381936.Findings Between April 7 and Nov 27, 2020, of 16 442 patients enrolled in the RECOVERY trial, 9433 (57%) wereeligible and 7763 were included in the assessment of azithromycin. The mean age of these study participants was65·3 years (SD 15·7) and approximately a third were women (2944 [38%] of 7763). 2582 patients were randomlyallocated to receive azithromycin and 5181 patients were randomly allocated to usual care alone. Overall,561 (22%) patients allocated to azithromycin and 1162 (22%) patients allocated to usual care died within 28 days(rate ratio 0·97, 95% CI 0·87–1·07; p=0·50). No significant difference was seen in duration of hospital stay (median10 days [IQR 5 to >28] vs 11 days [5 to >28]) or the proportion of patients discharged from hospital alive within 28 days(rate ratio 1·04, 95% CI 0·98–1·10; p=0·19). Among those not on invasive mechanical ventilation at baseline, nosignificant difference was seen in the proportion meeting the composite endpoint of invasive mechanical ventilationor death (risk ratio 0·95, 95% CI 0·87–1·03; p=0·24).Interpretation In patients admitted to hospital with COVID-19, azithromycin did not improve survival or otherprespecified clinical outcomes. Azithromycin use in patients admitted to hospital with COVID-19 should be restrictedto patients in whom there is a clear antimicrobial indication

A Critical Review and Significance of Ayurvedic preparation Kwatha - Herbal decoction

The standardization of Ayurvedic classical dosage forms has been an area of academic, research, industrial and regulatory interests.  It is crucial to understand the basic principles and rationality of these dosage forms for their therapeutic relevance while adapting to newer technologies for its right pharmaceutical and clinical use. Kwatha Kalpana -frequently referred to as decoctions - aqueous extraction of a group of herbs, is one of the most commonly used classical dosage forms where the therapeutic attributes are extracted from the group of botanicals into water, with the use of heat. Though clinically effective, it is seldom used due to the cumbersome preparatory method, short shelf life and poor palatability. This elaborate review covers historical and basic concepts of the dosage form, its salient features, nuances of classical preparations, traditional and newly developed methods of preparations. This paper covers intricate classical information and specifics about Kwatha, the herbal decoction.&nbsp