PurposeTo evaluate the use of digital devices, reading habits and the prevalence of eyestrain among urban Indian school children, aged 11–17 years.MethodsThe study included 576 adolescents attending urban schools who were surveyed regarding their electronic device usage. Additional information on the factors that may have an effect on ocular symptoms was collected.ResultsTwenty percent of students aged 11 in the study population use digital devices on a daily basis, in comparison with 50% of students aged 17. In addition to using these devices as homework aids, one third of study participants reported using digital devices for reading instead of conventional textbooks. The majority of students preferred sitting on a chair while reading (77%; 445 students), with only 21% (123 students) preferring to lie on the bed and 8 students alternating between chair and bed. There was a significant association between the students who preferred to lie down and those who experienced eyestrain, as reported by a little over one fourth of the student population (27%). Out of 576 students, 18% (103) experienced eyestrain at the end of the day after working on digital devices.ConclusionsThe increased use of digital devices by adolescents brings a new challenge of digital eyestrain at an early age. Our study reports the patterns of electronic device usage by school children, evaluates factors associated with eyestrain and highlights the need for further investigation of these issues.

The COVID-19 pandemic has sparked unprecedented public health and social measures (PHSM) by national and local governments, including border restrictions, school closures, mandatory facemask use and stay at home orders. Quantifying the effectiveness of these interventions in reducing disease transmission is key to rational policy making in response to the current and future pandemics. In order to estimate the effectiveness of these interventions, detailed descriptions of their timelines, scale and scope are needed. The Health Intervention Tracking for COVID-19 (HIT-COVID) is a curated and standardized global database that catalogues the implementation and relaxation of COVID-19 related PHSM. With a team of over 200 volunteer contributors, we assembled policy timelines for a range of key PHSM aimed at reducing COVID-19 risk for the national and first administrative levels (e.g. provinces and states) globally, including details such as the degree of implementation and targeted populations. We continue to maintain and adapt this database to the changing COVID-19 landscape so it can serve as a resource for researchers and policymakers alike.

Psoriasis is the result of uncontrolled keratinocyte proliferation, and its pathogenesis involves the dysregulation of the immune system. The interplay among cytokines released by dendritic, Th1, Th2, and Th17 cells leads to the phenotypical manifestations seen in psoriasis. Biological therapies target the cytokine-mediated pathogenesis of psoriasis and have improved patient quality of life. This review will describe the underlying molecular pathophysiology and biologics used to treat psoriasis. A review of the literature was conducted using the PubMed and Google Scholar repositories to investigate the molecular pathogenesis, clinical presentation, and current therapeutics in psoriasis. Plaque psoriasis’, the most prevalent subtype of psoriasis, pathogenesis primarily involves cytokines TNF-α, IL-17, and IL-23. Pustular psoriasis’, an uncommon variant, pathogenesis involves a mutation in IL-36RN. Currently, biological therapeutics targeted at TNF-α, IL-12/IL-23, IL-17, and IL-23/IL-39 are approved for the treatment of moderate to severe psoriasis. More studies need to be performed to elucidate the precise molecular pathology and assess efficacy between biological therapies for psoriasis. Psoriasis is a heterogenous, chronic, systemic inflammatory disease that presents in the skin with multiple types. Recognizing and understanding the underlying molecular pathways and biological therapeutics to treat psoriasis is important in treating this common disease.

The delivery of ophthalmic drugs is challenging despite easy accessibility via the ocular surface. Topical instillation of eye drops is a relatively easy and most commonly used as a conduit for drug delivery for treating a myriad of ocular morbidities, particularly involving the anterior segment, and has an additional benefit of avoiding the first-pass metabolism while passing through the systemic circulation. The primary challenges of drug administration through traditional methods include—inadequate patient education for proper drug instillation technique, compliance, adherence, and persistence. Various dynamic (choroidal and conjunctival blood flow, lymphatic clearance, and tear dilution) and static (namely, different layers of cornea, sclera, and retina including blood aqueous and blood–retinal barriers) ocular barriers limit drug delivery to the target ocular tissues. The maintenance of the therapeutic drug levels on the ocular surface for a prolonged duration is an added challenge, thus preventing persistent delivery for longer durations. These factors result in inadequate management, leading to poor prognosis in vision loss in as many as 27% of the patients diagnosed with glaucoma. We have reviewed the research and advancements in the development of novel and well-tolerated drug delivery systems with the common goal of overcoming the factors limiting adequate drug delivery to the target tissues in glaucomatous patients with traditional techniques. In the recent past, multiple research groups have successfully designed noninvasive, sustained drug delivery systems, promoting the efficacy as well as the feasibility of delivering topical drugs to the anterior segment.

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The data mining along with emerging computing techniques have astonishingly influenced the healthcare industry. Researchers have used different Data Mining and Internet of Things (IoT) for enrooting a programmed solution for diabetes and heart patients. However, still, more advanced and united solution is needed that can offer a therapeutic opinion to individual diabetic and cardio patients. Therefore, here, a smart data mining and IoT (SMDIoT) based advanced healthcare system for proficient diabetes and cardiovascular diseases have been proposed. The hybridization of data mining and IoT with other emerging computing techniques is supposed to give an effective and economical solution to diabetes and cardio patients. SMDIoT hybridized the ideas of data mining, Internet of Things, chatbots, contextual entity search (CES), bio-sensors, semantic analysis and granular computing (GC). The bio-sensors of the proposed system assist in getting the current and precise status of the concerned patients so that in case of an emergency, the needful medical assistance can be provided. The novelty lies in the hybrid framework and the adequate support of chatbots, granular computing, context entity search and semantic analysis. The practical implementation of this system is very challenging and costly. However, it appears to be more operative and economical solution for diabetes and cardio patients.

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