RESUMO
Understanding the significant impact of preventable factors, such as lifestyle decisions and bad habits like smoking, on female fertility has received a lot of attention. Pervasive smoking among fertile women is a serious public health concern. Smoking has well-documented negative impacts on general health, but it also has significant consequences on fertility. Many women of reproductive age still smoke, despite a wealth of data elucidating the effects of pregnancy and the health of the fetus as a result of prenatal exposure. This review attempts to investigate the consequences of smoking on female fertility, specifically focusing on how it affects the ovaries, oviducts, and uterus through a thorough examination of numerous studies. Important topics such as ovarian reserve, steroidogenesis, ovulation, controlling the menstrual cycle, oviductal function, uterine receptivity, and implantation will receive extra focus.
RESUMO
Artificial intelligence (AI) has immense power to set up an ideal health ecosystem through "intelligent medicine" i.e., a combination of human and machine intelligence. However, the application of AI in healthcare is still unclear. Currently, India is facing huge challenges such as the scarcity of medical resources and the uneven distribution of medical services. This also highlights the opportunities linked to challenges and risks. The most recent pandemic has accelerated this process by acknowledging that medicine stands on the brink of an AI revolution. Incorporating the evidence on the role of precision medicine, cost-effective healthcare, and expanding humanistic and medical services, this paper demonstrates the digital health interventions for the "enhancement" of capabilities, "efficiency," "extension of services" and upgrading "experience" in the health sector. Through thorough literature searches from PubMed, Google Scholar, and other reliable sources, this study aims to understand the evolving needs, and greater control and to bridge gaps in access to healthcare through AI. Also, India is currently developing the potential to automate multiple tasks and calling for more human interventions. The future of AI in healthcare looks promising with digital health interventions that eventually offer flexibility and convenience to both the patient and the provider. This paper will help public health professionals address ethical considerations and policy-making where AI plays a significant role in setting up an ideal health ecosystem.
RESUMO
We manipulated the accommodative response using positive and negative lenses to study any association between symptoms of pattern glare and accommodation. Two groups of eighteen young adults were selected from seventy-eight on the basis (i) that their rate of reading increased by 5% or more with an overlay compared to their rate without it, and (ii) that they reported more than 2 symptoms of pattern glare (group 1) or had no such increment in reading speed and reported fewer than 3 symptoms (group 2). Under double-masked conditions participants observed at 0.4 m a pattern of stripes while measurements of accommodation were made using an open field autorefractor with and without positive and negative trial lenses (0.75 D), and with and without a coloured overlay. Pattern glare was also assessed with and without the trial lenses. Without lenses, the mean accommodative response in group 1 was 1.55 D, a lag of 0.95 D +/- 0.24 D relative to the demand. The lag decreased by 0.43 D (p < 0.0001) when the chosen overlay was used, an effect that was not shown in group 2 even when lag increased with negative trial lenses (p = 0.13). In both groups, pattern glare scores were reduced by the trial lenses, but were unaffected by the sign of the lenses. This suggests that symptoms of pattern glare are not strongly associated with accommodative response.
