Sex Differences in E-Cigarette Use and Related Health Effects.

BACKGROUND: Electronic cigarettes (e-cigarettes) comprise a variety of products designed to deliver nicotine, flavorings, and other substances. To date, multiple epidemiological and experimental studies have reported a variety of health issues associated with their use, including respiratory toxicity, exacerbation of respiratory conditions, and behavioral and physiological effects. While some of these effects appear to be sex- and/or gender-related, only a portion of the research has been conducted considering these variables. In this review, we sought to summarize the available literature on sex-specific effects and sex and gender differences, including predictors and risk factors, effects on organ systems, and behavioral effects. METHODS: We searched and selected articles from 2018-2023 that included sex as a variable or reported sex differences on e-cigarette-associated effects. RESULTS: We found 115 relevant studies published since 2018 that reported sex differences in a variety of outcomes. The main differences reported were related to reasons for initiation, including smoking history, types of devices and flavoring, polysubstance use, physiological responses to nicotine and toxicants in e-liquids, exacerbation of lung disease, and behavioral factors such as anxiety, depression, sexuality, and bullying. CONCLUSIONS: The available literature supports the notion that both sex and gender influence the susceptibility to the negative effects of e-cigarette use. Future research needs to consider sex and gender variables when addressing e-cigarette toxicity and other health-related consequences.

Prediction and Analysis of Autism Spectrum Disorder Using Machine Learning Techniques.

Autism spectrum disorder is a severe, life-prolonged neurodevelopmental disease typified by disabilities that are chronic or limited in the development of socio-communication skills, thinking abilities, activities, and behavior. In children aged two to three years, the symptoms of autism are more evident and easier to recognize. The major part of the existing literature on autism spectrum disorder is covered by a prediction system based on traditional machine learning algorithms such as support vector machine, random forest, multiple layer perceptron, naive Bayes, convolution neural network, and deep neural network. The proposed models are validated by using performance measurement parameters such as accuracy, precision, and recall. In this research, autism spectrum disorder prediction has been investigated and compared using common parameters such as application type, simulation method, comparison methodology, and input data. The key purpose of this study is to give a centralized framework to use for researchers working on autism spectrum disorder prediction. The best results were obtained by using the random forest algorithm as it performs better than other traditional machine learning algorithms. The achieved accuracy is 89.23%. The workflow representations of the investigated frameworks assist readers in comprehending the fundamental workings and architectures of these frameworks.

Comparative cone-beam computed tomographic evaluation of maxillary incisor intrusion and associated root resorption: Intrusion arch vs mini-implants.

INTRODUCTION: Various literature has verified that apical root resorption is a common adverse effect of orthodontic treatment, particularly intrusion. Conventional radiographic techniques underestimated root lengths and overestimated tooth lengths. Cone-beam computed tomography (CBCT) is a useful diagnostic tool to detect orthodontically induced external apical root resorption. This prospective study aimed to compare maxillary incisor intrusion and associated root resorption via CBCT. METHODS: Thirty patients aged 16-23 years, having a deepbite of 6-8 mm and excessive gingival display on smiling, were divided into 2 groups: group 1, with 15 patients who were treated with Burstone intrusion arch, and group 2 with 15 patients who were treated with mini-implants applying 100 g of intrusive force for 4 months with activation done every 4 weeks. During this 4-month study period, no treatment was performed other than the intrusion of incisors. CBCT scans were obtained before and after the intrusion phase of treatment to compare the amount of intrusion and associated root resorption among both groups. RESULTS: No significant difference was found in mean incisor intrusion between groups 1 and 2 (P = 0.772), with slightly more proclination of incisors in group 1, resulting in a significant (P = 0.018) increase in the vertical change of incisal edge in group 1. A statistically significant difference was found in root resorption among both groups (P = 0.004), with more root resorption in group 2. CONCLUSIONS: The results of this study indicate intrusion with both the intrusion systems using appropriate intrusive forces is effective in opening the bite with slightly more external apical root resorption in the mini-implant group.

Forecasting the impact of environmental stresses on the frequent waves of COVID19.

A novel approach to link the environmental stresses with the COVID-19 cases is adopted during this research. The time-dependent data are extracted from the online repositories that are freely available for knowledge and research. Since the time series data analysis is desired for the COVID-19 time-dependent frequent waves, here in this manuscript, we have developed a time series model with the aid of "nonlinear autoregressive network with exogenous inputs (NARX)" approach. The distribution of infectious agent-containing droplets from an infected person to an uninfected person is a common form of respiratory disease transmission. SARS-CoV-2 has mainly spread via short-range respiratory droplet transmission. Airborne transmission of SARS-CoV-2 seems to have occurred over long distances or times in unusual conditions; SARS-CoV-2 RNA was found in PM10 collected in Italy. This research shows that SARS-CoV-2 particles adsorbed to outdoor PM remained viable for a long time, given the epidemiology of COVID-19, outdoor air pollution is unlikely to be a significant route of transmission. In this research, ANN time series is used to analyze the data resulting from the COVID-19 first and second waves and the forecasted results show that air pollution affects people in different areas of Italy and make more people sick with covid-19. The model is developed based on the disease transmission data of Italy.

Multisystem Inflammatory Syndrome in Children and Adolescents (MIS-C) under the Setting of COVID-19: A Review of Clinical Presentation, Workup and Management.

Earlier in its course, SARS-CoV-2 was primarily identified to cause an acute respiratory illness in adults, the elderly and immunocompromised, while children were known to be afflicted with milder symptoms. However, since mid-April of 2020, latent effects of the virus have begun emerging in children and adolescents, which is characterised by a multisystem hyperinflammatory state; thus, the term Multisystem Inflammatory Syndrome in Children (MIS-C) was introduced by the WHO and CDC. The syndrome manifests itself approximately 4 weeks after COVID-19 infection, with symptoms mimicking Kawasaki Disease and Kawasaki Disease Shock Syndrome. Demographically, MIS-C peaks in children aged 5 to 14 years, with clusters in Europe, North and Latin America seen, later followed by Asia. Although the exact pathophysiology behind the syndrome is unknown, recent studies have proposed a post-infectious immune aetiology, which explains the increased levels of immunoglobulins seen in affected patients. Patient presentation includes, but is not limited to, persistent fever, rash, gastrointestinal symptoms and cardiac complications including myocarditis. These patients also have raised inflammatory markers including C reactive protein, ferritin and interleukin-6. In poorly controlled patients, the syndrome can lead to multiorgan failure and death. The mainstay of treatment includes the use of intravenous immunoglobulins, steroids, immune modulators and aspirin. Adjunct therapy includes the use of low molecular weight heparin or warfarin for long term anticoagulation. Currently very little is known about the syndrome, highlighting the need for awareness amongst healthcare workers and parents. Moreover, with increased cases of COVID-19 as a result of the second wave, it is essential to keep MIS-C in mind when attending patients with a past history of COVID-19 exposure or infection. Additionally, once these patients have been identified and treated, strict follow-up must be done in order carry out long term studies, and to identify possible sequelae and complications.

A mathematical modelling approach for treatment and control of Echinococcus multilocularis.

Alveolar echinococcosis (AE) is a zoonotic parasitic diseases caused by a cestode parasite known as Echinococcus multilocularis. The parasite has a wildlife cycle with definitive hosts (foxes) and small mammals as intermediate hosts (rodents) while humans are the accidental hosts. Parasite infection pressure relation to time of the year and age dependent infection pressure for parasite abundance also depend on the urbanization. The aim of current work is forecasting the thresholds via the computational analysis of the disease spread which is a useful approach since it can help to design the experimental settings with better planning and efficiency. Network analysis when interlinked with the computational techniques provides better insight into the spatial and temporal heterogeneities. In the present study, a mathematical framework that describes the transmission dynamics and control measures of E. multilocularis in foxes is documented. We used treatment of foxes with baits for the prevention of the E. multilocularis infection. A novel approach of networking, called Petri net (PN), based on density dependent differential equations, is utilized during this research. The accurate description of the transmission of the parasite and the effect of drug on it is provided to the readers in this article. The transitions, which are difficult to analyse theoretically, are presented with the aid of the discrete approach of networking. A discrete mathematical framework can prove to be an accurate and robust tool to analyse and control the parasite dynamics.

Perception and Management of Obesity Among Pakistani Doctors.

Background The incidence of obesity has been on the rise worldwide. In Pakistan alone, one in four adults is overweight/obese and thus at risk of developing a number of comorbidities such as cardiovascular disease and diabetes. This research aimed to examine how doctors perceived and managed their obese patients. Methods A standardized questionnaire was filled by 100 doctors working in Pakistan, either by hand or online. The study was conducted from November 2017 to January 2018. Results It was found that only 8% of doctors had completed a training course on obesity. Doctors discussed the links between obesity and diabetes (88%) most often whilst neglecting cancer (30%) and dementia (17%). Only 60% of doctors calculated body mass index (BMI) for adult obese patients, with general practitioners (GPs) being the most confident in discussing their weight issues (p=0.001). In terms of childhood obesity, 54% of doctors were confident in putting in place a weight management program. Doctors who checked their weight more than four times a year were found to calculate the BMI of children and adult patients more often (p=0.000 and p=0.044). Comparably, doctors of normal weight were more confident in managing the complications of adult obesity (p=0.015). Conclusion Training courses regarding obesity should be provided to doctors not only to increase their knowledge but also to increase their confidence levels in managing such patients. Further research needs to be carried out in order to understand the patients' perception of obesity management.

p53 isoforms regulate premature aging in human cells.

Cellular senescence is a hallmark of normal aging and aging-related syndromes, including the premature aging disorder Hutchinson-Gilford Progeria Syndrome (HGPS), a rare genetic disorder caused by a single mutation in the LMNA gene that results in the constitutive expression of a truncated splicing mutant of lamin A known as progerin. Progerin accumulation leads to increased cellular stresses including unrepaired DNA damage, activation of the p53 signaling pathway and accelerated senescence. We previously established that the p53 isoforms ∆133p53 and p53ß regulate senescence in normal human cells. However, their role in premature aging is unknown. Here we report that p53 isoforms are expressed in primary fibroblasts derived from HGPS patients, are associated with their accelerated senescence and that their manipulation can restore the replication capacity of HGPS fibroblasts. We found that in near-senescent HGPS fibroblasts, which exhibit low levels of ∆133p53 and high levels of p53ß, restoration of Δ133p53 expression was sufficient to extend replicative lifespan and delay senescence, despite progerin levels and abnormal nuclear morphology remaining unchanged. Conversely, Δ133p53 depletion or p53ß overexpression accelerated the onset of senescence in otherwise proliferative HGPS fibroblasts. Our data indicate that Δ133p53 exerts its role by modulating full-length p53 (FLp53) signaling to extend the replicative lifespan and promotes the repair of spontaneous progerin-induced DNA double-strand breaks (DSBs). We showed that Δ133p53 dominant-negative inhibition of FLp53 occurs directly at the p21/CDKN1A and miR-34a promoters, two p53 senescence-associated genes. In addition, Δ133p53 expression increased the expression of DNA repair RAD51, likely through upregulation of E2F1, a transcription factor that activates RAD51, to promote repair of DSBs. In summary, our data indicate that Δ133p53 modulates p53 signaling to repress progerin-induced early onset of senescence in HGPS cells. Therefore, restoration of ∆133p53 expression may be a novel therapeutic strategy to treat aging-associated phenotypes of HGPS in vivo.

Effect of meal size and texture on gastric pouch emptying and glucagon-like peptide 1 after gastric bypass surgery.

BACKGROUND: Roux-en-Y gastric bypass (RYGB) accelerates gastric pouch emptying, enhances postprandial glucagon-like peptide 1 (GLP-1) and insulin, and lowers glucose concentrations. To prevent discomfort and reactive hypoglycemia, it is recommended that post-RYGB patients eat small, frequent meals and avoid caloric drinks. However, the effect of meal size and texture on GLP-1 and metabolic response has not been studied. OBJECTIVES: To demonstrate that frequent minimeals and solid meals (S) elicit less GLP-1 and insulin release and less reactive hypoglycemia and are better tolerated compared with a single isocaloric liquid meal (L). SETTING: A university hospital. METHODS: In this prospective study, 32 RYGB candidates were enrolled and randomized to L or S groups before gastric bypass. Each subject received an L or S 600-kcal single meal (SM) administered at hour 0 or three 200-kcal minimeals administered at hours 0, 2, and 4 on 2 separate days. Twenty-one patients were retested 1 year after RYGB. Blood and visual analogue scale measurements were collected up to 6 hours postprandially. Outcome measures included gastric pouch emptying, glucose, insulin, and GLP-1; hunger, fullness, and stomach discomfort were measured by visual analogue scale. RESULTS: Twenty-one were patients retested after RYGB (L: n = 12; S: n = 9). Meal texture had a significant effect on peak GLP-1 (L-SM: 106.1 ± 67.2 versus S-SM: 45.3 ± 25.2 pM, P = .004), peak insulin, and postprandial glucose. Hypoglycemia was more frequent after the L-SM meal compared with the S-SM. Gastric pouch emptying was 2.4 times faster after RYGB but was not affected by texture. CONCLUSIONS: Meal texture and size have significant impact on tolerance and metabolic response after RYGB.