Assessing the Impact of Sodium Hyaluronate Eye Drops on the Ocular Surface Microbiome: Implications for Dry Eye Management and Ocular Health : Eye Microbiome

Abstract: Background: A powerful immunoregulatory function is provided by the ocular surface microbiome, which contributes to ocular pathogenesis, physiological integrity, and pathogenesis of ocular diseases. Using sodium hyaluronate eye drops (with or without a preservative) as a remedy for dry eye, we contrasted the bacterial communities' diversity and composition on the ocular surface before and after usage. Methods: We randomly divided 16 healthy adults into two groups. From each participant was required to provide a microbial sample at the start and after two weeks of the intervention. After sodium hyaluronate eye drops were administered, diversity and classification differences were compared between the groups. Results: Results of the present study indicated that there was a significant difference between the bacterial communities in the eyes of the two groups of healthy individuals. Although sodium hyaluronate eye drops (with or without preservatives) did alter the bacterial community, the results of alpha and beta diversity showed no significant differences between individuals or between groups. Conclusion: Eye drops containing sodium hyaluronate may affect the eye's bacterial community with or without benzalkonium chloride (BAC) levels. Depending on the individual and the eye, these changes may vary. &nbsp

Impact of Perioperative Management on Ocular Microbiota Composition and Diversity: A Study of Intravitreal Injection Patients with 16S rRNA Sequencing

Background: The ocular microbiota, which includes both commensal and pathogenic microorganisms, is constantly exposed to the ocular surface.  Material and Methods: In this study, two groups of patients were analyzed. Group A included 19 individuals who had not received intravitreal injections or undergone perioperative management. Group B, on the other hand, consisted of 22 patients who had received one, two, or more two treatments. The microbial samples collected from the ocular surface of these patients were subjected to 16S rRNA sequencing using the HiSeq 2500 platform. Further analysis of the alpha/beta diversity and clustering of operating taxonomic units (OTUs) was carried out. Results: Our results show a significant difference in beta diversity was observed between group A (15 patients without intravitreal injections or perioperative management) and group B (patients with at least one, twice, or more than twice treatment) with a P value of 0.014. It was found that both the composition and relative abundance of cells were impacted by perioperative management in the lead-up to intravitreal injection. Additionally, a greater diversity of Gram-negative bacteria was observed and the most significant groups of microbiotas were found to be phyla and genera. Conclusion: In conclusion, our study found that perioperative management has a significant impact on the ocular microbiota, altering its composition and disrupting its balance. Therefore, it is important for clinicians to carefully consider perioperative management prior to administering intravitreal injections

A Review of the Management of Eye Diseases Using Artificial Intelligence, Machine Learning, and Deep Learning in Conjunction with Recent Research on Eye Health Problems: Eye Microbiome

In the field of computer science, Artificial Intelligence can be considered one of the branches that study the development of algorithms that mimic certain aspects of human intelligence. Over the past few years, there has been a rapid advancement in the technology of computer-aided diagnosis (CAD). This in turn has led to an increase in the use of deep learning methods in a variety of applications. For us to be able to understand how AI can be used in order to recognize eye diseases, it is crucial that we have a deep understanding of how AI works in its core concepts. This paper aims to describe the most recent and applicable uses of artificial intelligence in the various fields of ophthalmology disease

Low-Dose Fentanyl, Propofol, Midazolam, Ketamine and Lidocaine Combination vs. Regular Dose Propofol and Fentanyl Combination for Deep Sedation Induction; a Randomized Clinical Trial

Introduction: Need for procedural sedation and analgesia (PSA) is felt in emergency department (ED) more and more each day. This study aimed to compare the effectiveness of low-dose fentanyl, propofol, midazolam, ketamine and lidocaine combination with regular dose of propofol and fentanyl combination for induction of deep sedation.Methods: In this single-blind clinical trial, candidate patients for sedation and analgesia aged more than 15 and less than 60 years old, with pain score ≥6 were allocated to one of the groups using block randomization and were compared regarding onset of action, recovery time, and probable side effects.Results: 125 patients with the mean age of 37.8 ± 14.3 years were randomly allocated to each group. 100% of the patients in group 1 (5 drugs) and 56.5% of the patients in group 2 (2 drugs) were deeply sedated in the 3rd minute after injection. The 2 groups were significantly different regarding onset of action (p = 0.440), recovery time (p = 0.018), and treatment failure (p < 0.001).Conclusion: Low-dose fentanyl, propofol, midazolam, ketamine and lidocaine combination was more successful in induction of deep sedation compared to regular dose of propofol and fentanyl combination. Recovery time was a little longer in this group and both groups were similar regarding drug side effects and effect on vital signs

Investigating air quality status and air pollutant trends over the Metropolitan Area of Tehran, Iran over the past decade between 2005 and 2014

Studies on the trend of air pollution in Tehran, Iran, as one of the most polluted metropolis in the world are scant, and today Tehran is known for its high levels of air pollutants. In this study, the trend of air pollution concentration was evaluated over the past 10 years (2004-2015). The data were collected from 22 stations of the Air Quality Control Company. Daily concentrations of CO, NO2, SO2, O3, PM10 were analyzed using SPSS 16 based on the statistical method, repeated measures, and intra-group test to determine the pattern of each pollutant changes. As a result of the 22 air pollution monitoring stations, NO2 and SO2 concentrations have been increasing over the period of 10 years. The highest anomaly is related to SO2. The CO concentrations represent a descending pattern over the period, although there was a slight increase in 2013 and 2014. The O3 concentrations declined in the following years. The average concentration of PM10 has been rising during the period. Also we evaluated changes of each pollutant in different months and calculated the number of clean, healthy, unhealthy days for sensitive, unhealthy, very unhealthy, and dangerous groups. The study findings illustrated the necessity for larger investment in air pollution abatement. Overall, trends have been progressed to worsening, the number of healthy days has been declined and the number of unhealthy days has been increased in recent years

Mapping 123 million neonatal, infant and child deaths between 2000 and 2017

Since 2000, many countries have achieved considerable success in improving child survival, but localized progress remains unclear. To inform efforts towards United Nations Sustainable Development Goal 3.2—to end preventable child deaths by 2030—we need consistently estimated data at the subnational level regarding child mortality rates and trends. Here we quantified, for the period 2000–2017, the subnational variation in mortality rates and number of deaths of neonates, infants and children under 5 years of age within 99 low- and middle-income countries using a geostatistical survival model. We estimated that 32% of children under 5 in these countries lived in districts that had attained rates of 25 or fewer child deaths per 1,000 live births by 2017, and that 58% of child deaths between 2000 and 2017 in these countries could have been averted in the absence of geographical inequality. This study enables the identification of high-mortality clusters, patterns of progress and geographical inequalities to inform appropriate investments and implementations that will help to improve the health of all populations

Mapping local patterns of childhood overweight and wasting in low- and middle-income countries between 2000 and 2017

A double burden of malnutrition occurs when individuals, household members or communities experience both undernutrition and overweight. Here, we show geospatial estimates of overweight and wasting prevalence among children under 5 years of age in 105 low- and middle-income countries (LMICs) from 2000 to 2017 and aggregate these to policy-relevant administrative units. Wasting decreased overall across LMICs between 2000 and 2017, from 8.4% (62.3 (55.1–70.8) million) to 6.4% (58.3 (47.6–70.7) million), but is predicted to remain above the World Health Organization’s Global Nutrition Target of <5% in over half of LMICs by 2025. Prevalence of overweight increased from 5.2% (30 (22.8–38.5) million) in 2000 to 6.0% (55.5 (44.8–67.9) million) children aged under 5 years in 2017. Areas most affected by double burden of malnutrition were located in Indonesia, Thailand, southeastern China, Botswana, Cameroon and central Nigeria. Our estimates provide a new perspective to researchers, policy makers and public health agencies in their efforts to address this global childhood syndemic