Survey to Specify SGLT2 Inhibitor Choice in T2DM Management

Objective: There are no major head-to-head comparative studies till date to compare the differences in glycemic efficacy, safety, or cardio-renal effects within SGLT2 inhibitors. This survey was conducted to understand the different parameters that clinicians identify while choosing an SGLT2 inhibitor in routine clinical practice. Materials and methods: A cross-sectional questionnaire-based survey of healthcare professionals (HCP) was conducted across India. Data were analyzed and expressed as descriptive statistics. Results: In clinical practice, the majority of HCPs identified a history of cardiovascular disease (CVD) as the most important factor for prescribing SGLT2 inhibitors in patients with T2DM. The majority of HCPs opined that among all the SGLT2 inhibitors, canagliflozin had the strongest effect on HbA1c reduction (56%), reduction in body weight (59%), and renal benefit (66%), whereas empagliflozin was associated with CV benefits (48%). In terms of heart failure, canagliflozin, empagliflozin, and dapagliflozin were similarly preferred. Conclusions: This survey gives us an understanding of the current clinical practice prevalent among Indian physicians as far as the prescription pattern of SGLT2 inhibitors is concerned

Widening Access to Applied Machine Learning with TinyML

Broadening access to both computational and educational resources is critical to diffusing machine-learning (ML) innovation. However, today, most ML resources and experts are siloed in a few countries and organizations. In this paper, we describe our pedagogical approach to increasing access to applied ML through a massive open online course (MOOC) on Tiny Machine Learning (TinyML). We suggest that TinyML, ML on resource-constrained embedded devices, is an attractive means to widen access because TinyML both leverages low-cost and globally accessible hardware, and encourages the development of complete, self-contained applications, from data collection to deployment. To this end, a collaboration between academia (Harvard University) and industry (Google) produced a four-part MOOC that provides application-oriented instruction on how to develop solutions using TinyML. The series is openly available on the edX MOOC platform, has no prerequisites beyond basic programming, and is designed for learners from a global variety of backgrounds. It introduces pupils to real-world applications, ML algorithms, data-set engineering, and the ethical considerations of these technologies via hands-on programming and deployment of TinyML applications in both the cloud and their own microcontrollers. To facilitate continued learning, community building, and collaboration beyond the courses, we launched a standalone website, a forum, a chat, and an optional course-project competition. We also released the course materials publicly, hoping they will inspire the next generation of ML practitioners and educators and further broaden access to cutting-edge ML technologies.Comment: Understanding the underpinnings of the TinyML edX course series: https://www.edx.org/professional-certificate/harvardx-tiny-machine-learnin

Widening Access to Applied Machine Learning With TinyML

Broadening access to both computational and educational resources is crit- ical to diffusing machine learning (ML) innovation. However, today, most ML resources and experts are siloed in a few countries and organizations. In this article, we describe our pedagogical approach to increasing access to applied ML through a massive open online course (MOOC) on Tiny Machine Learning (TinyML). We suggest that TinyML, applied ML on resource-constrained embedded devices, is an attractive means to widen access because TinyML leverages low-cost and globally accessible hardware and encourages the development of complete, self-contained applications, from data collection to deployment. To this end, a collaboration between academia and industry produced a four part MOOC that provides application-oriented instruction on how to develop solutions using TinyML. The series is openly available on the edX MOOC platform, has no prerequisites beyond basic programming, and is designed for global learners from a variety of backgrounds. It introduces real-world applications, ML algorithms, data-set engineering, and the ethi- cal considerations of these technologies through hands-on programming and deployment of TinyML applications in both the cloud and on their own microcontrollers. To facili- tate continued learning, community building, and collaboration beyond the courses, we launched a standalone website, a forum, a chat, and an optional course-project com- petition. We also open-sourced the course materials, hoping they will inspire the next generation of ML practitioners and educators and further broaden access to cutting-edge ML technologies

Elephant conservation: Reviewing the need and potential impact of cognition-based education

Conservation education programs centered on animal cognition seem to be effective in bringing humans closer to non-human species and thereby, influencing their conservation attitudes. Systematic evaluation of the impact of cognition-based education programs on the attitudes of participants has revealed positive feedback and an appreciation towards the species of interest. However, such evaluations are rare for species like elephants, who suffer severe conservation challenges such as high degrees of conflict with the local community. In this paper, we review the need for cognition-based education programs in elephant conservation as well as the need to evaluate these programs to assess their impact on conservation attitudes. In particular, we emphasize the need for such programs in the native ranges of elephants, which are more prone to human-elephant conflict, and argue that exposure to such programs may potentially increase the collaboration of the local community towards conservation efforts

Palliative and Supportive Care in Acrometastasis to the Hand: Case Series

Acrometastasis to the hand is an unusual presentation which might mimic an infectious, inflammatory, or a metabolic pathology. We herein describe a case series of three patients of acrometastasis to the hand. We encountered three cases of acrometastasis to the hand attending the departmental clinics from 2007 to 2010. The median age at presentation was noted to be 55 years. All were males. The primaries included squamous cell carcinoma of the skin, larynx, and esophagus. In two patients, acrometastasis was detected at presentation and in one it was detected 2 years postcompletion of radical therapy. Two patients were offered palliative radiation to acrometastasis, and best supportive care was given to one. Palliation achieved after radiation was noted to be modest to good. The brief report highlights the importance of the clinical awareness of metastatic dissemination to unusual sites in the face of increasing cancer survivorship. Acrometastasis portends a poor prognosis with limited survival, and optimal integration of the best supportive care is mandatory. A short course of hypofractionated palliative radiation therapy results in modest to good palliation