Severe Acute Respiratory Syndrome Coronavirus 2 is a novel strain of human beta-coronavirus that has produced over two million deaths and affected one hundred million individuals worldwide. As all the proposed drugs proved to be unstable, inducing side effects, the need to develop a vaccine crystallized in a short time. As a result, we searched the databases for articles in which the authors reported the efficacy and safety of the use of several vaccines vaccines by sex, age group, and frequency of adverse reactions. We identified a total of 19 relevant articles that were discussed throughout this manuscript. We concluded that from all eleven vaccines, three had an efficacy >90% (Pfizer–BioNTech (~95%), Moderna (~94%), and Sputnik V (~92%)) except for Oxford–AstraZeneca (~81%). However, Moderna, Sputnik V, and Oxford–AstraZeneca also alleviate severe adverse reactions, whereas in Pfizer–BioNTech this was not revealed. The remaining five (Convidicea (AD5-nCOV); Johnson & Johnson (Ad26.COV2.S); Sinopharm (BBIBP-CorV); Covaxin (BBV152), and Sinovac (CoronaVac)) were discussed based on their immunogenicity, and safety reported by the recipients since only phases 1 and 2 were conducted without clear evidence published regarding their efficacy. CoviVac and EpiVacCorona have just been approved, which is why no published article could be found. All adverse events reported following the administration of one of the four vaccines ranged from mild to moderate; limited exceptions in which the patients either developed severe forms or died, because most effects were dose-dependent. It can be concluded that aforementioned vaccines are efficient and safe, regardless of age and sex, being well-tolerated by the recipients.

Background: Having several applications in medicine, and in ophthalmology in particular, artificial intelligence (AI) tools have been used to detect visual function deficits, thus playing a key role in diagnosing eye diseases and in predicting the evolution of these common and disabling diseases. AI tools, i.e., artificial neural networks (ANNs), are progressively involved in detecting and customized control of ophthalmic diseases. The studies that refer to the efficiency of AI in medicine and especially in ophthalmology were analyzed in this review. Materials and Methods: We conducted a comprehensive review in order to collect all accounts published between 2015 and 2022 that refer to these applications of AI in medicine and especially in ophthalmology. Neural networks have a major role in establishing the demand to initiate preliminary anti-glaucoma therapy to stop the advance of the disease. Results: Different surveys in the literature review show the remarkable benefit of these AI tools in ophthalmology in evaluating the visual field, optic nerve, and retinal nerve fiber layer, thus ensuring a higher precision in detecting advances in glaucoma and retinal shifts in diabetes. We thus identified 1762 applications of artificial intelligence in ophthalmology: review articles and research articles (301 pub med, 144 scopus, 445 web of science, 872 science direct). Of these, we analyzed 70 articles and review papers (diabetic retinopathy (N = 24), glaucoma (N = 24), DMLV (N = 15), other pathologies (N = 7)) after applying the inclusion and exclusion criteria. Conclusion: In medicine, AI tools are used in surgery, radiology, gynecology, oncology, etc., in making a diagnosis, predicting the evolution of a disease, and assessing the prognosis in patients with oncological pathologies. In ophthalmology, AI potentially increases the patient’s access to screening/clinical diagnosis and decreases healthcare costs, mainly when there is a high risk of disease or communities face financial shortages. AI/DL (deep learning) algorithms using both OCT and FO images will change image analysis techniques and methodologies. Optimizing these (combined) technologies will accelerate progress in this area.

Mercury (Hg) is considered one of the most widespread toxic environmental pollutants, which seems to have multiple effects on organisms even at low concentrations. It has a critical role in many health problems with harmful consequences, with Hg primarily targeting the brain and its components, such as the central nervous system (CNS). Hg exposure was associated with numerous CNS disorders that frequently trigger Alzheimer’s disease (AD). Patients with AD have higher concentrations of Hg in blood and brain tissue. This paper aims to emphasize a correlation between Hg and AD based on the known literature in the occupational field. The outcome shows that all these concerning elements could get attributed to Hg. However, recent studies did not investigate the molecular level of Hg exposure in AD. The present review highlights the interactions between Hg and AD in neuronal degenerations, apoptosis, autophagy, oxidative stress (OS), mitochondrial malfunctions, gastrointestinal (GI) microflora, infertility and altering gene expression.

Since mid-November 2019, when the first SARS-CoV-2-infected patient was officially reported, the new coronavirus has affected over 10 million people from which half a million died during this short period. There is an urgent need to monitor, predict, and restrict COVID-19 in a more efficient manner. This is why Auto-Regressive Integrated Moving Average (ARIMA) models have been developed and used to predict the epidemiological trend of COVID-19 in Ukraine, Romania, the Republic of Moldova, Serbia, Bulgaria, Hungary, USA, Brazil, and India, these last three countries being otherwise the most affected presently. To increase accuracy, the daily prevalence data of COVID-19 from 10 March 2020 to 10 July 2020 were collected from the official website of the Romanian Government GOV.RO, World Health Organization (WHO), and European Centre for Disease Prevention and Control (ECDC) websites. Several ARIMA models were formulated with different ARIMA parameters. ARIMA (1, 1, 0), ARIMA (3, 2, 2), ARIMA (3, 2, 2), ARIMA (3, 1, 1), ARIMA (1, 0, 3), ARIMA (1, 2, 0), ARIMA (1, 1, 0), ARIMA (0, 2, 1), and ARIMA (0, 2, 0) models were chosen as the best models, depending on their lowest Mean Absolute Percentage Error (MAPE) values for Ukraine, Romania, the Republic of Moldova, Serbia, Bulgaria, Hungary, USA, Brazil, and India (4.70244, 1.40016, 2.76751, 2.16733, 2.98154, 2.11239, 3.21569, 4.10596, 2.78051). This study demonstrates that ARIMA models are suitable for making predictions during the current crisis and offers an idea of the epidemiological stage of these regions.

Intra-lysosomal accumulation of the autofluorescent “residue” known as lipofuscin, which is found within postmitotic cells, remains controversial. Although it was considered a harmless hallmark of aging, its presence is detrimental as it continually accumulates. The latest evidence highlighted that lipofuscin strongly correlates with the excessive production of reactive oxygen species; however, despite this, lipofuscin cannot be removed by the biological recycling mechanisms. The antagonistic effects exerted at the DNA level culminate in a dysregulation of the cell cycle, by inducing a loss of the entire internal environment and abnormal gene(s) expression. Additionally, it appears that a crucial role in the production of reactive oxygen species can be attributed to gut microbiota, due to their ability to shape our behavior and neurodevelopment through their maintenance of the central nervous system.

Asherman syndrome is a multifaceted condition describing the partial or complete removal of the uterine cavity and/or cervical canal. It is a highly debatable topic because of its pronounced influence on both reproductive outcomes and gynaecologic symptoms. The latest reports demonstrated that trauma to the endometrium is the main cause of intrauterine adhesion formation. Left untreated, such adhesions gradually lead to a range of repercussions ranging from mild to severe. Considering the lack of non-invasive approaches, the advent of hysteroscopy has revolutionized the entire field, being otherwise considered the most efficient tool offering new directions and amplifying the chances of treating the Asherman syndrome.