Pain profile during orthodontic levelling and alignment with fixed appliances reported in randomized trials: a systematic review with meta-analyses

Objective To assess the pain profile of patients in the levelling/alignment phase of orthodontic treatment, as reported from randomized clinical trials. Materials and methods Five databases were searched in September 2022 for randomized clinical trials assessing pain during levelling/alignment with a visual analogue scale (VAS). After duplicate study selection, data extraction, and risk-of-bias assessment, random effects meta-analyses of mean differences (MDs) and their 95% confidence intervals (CIs) were performed, followed by subgroup/meta-regression, and certainty analyses. Results A total of 37 randomized trials including 2277 patients (40.3% male; mean age 17.5 years) were identified. Data indicated quick pain initiation after insertion of orthodontic appliances (n = 6; average = 12.4 mm VAS), a quick increase to a peak at day 1 (n = 29; average = 42.4 mm), and gradually daily decrease the first week until its end (n = 23; average = 9.0 mm). Every second patient reported analgesic use at least once this week (n = 8; 54.5%), with peak analgesic use at 6 h post-insertion (n = 2; 62.3%). Patients reported reduced pain in the evening compared to morning (n = 3; MD =  − 3.0 mm; 95%CI =  − 5.3, − 0.6; P = 0.01) and increased pain during chewing (n = 2; MD = 19.2 mm; 95% CI = 7.9, 30.4; P < 0.001) or occlusion of the back teeth (n = 2; MD = 12.4 mm; 95% CI = 1.4, 23.4; P = 0.3), while non-consistent effects were seen for patient age, sex, irregularity, or analgesic use. Subgroup analyses indicated increased pain among extraction cases and during treatment of the lower (rather than the upper) arch, while certainty around estimates was moderate to high. Conclusions Evidence indicated a specific pain profile during orthodontic levelling/alignment, without signs of consistent patient-related influencing factors

The effects of kisspeptin on β-cell function, serum metabolites and appetite in humans

Aims: To investigate the effect of kisspeptin on glucose-stimulated insulin secretion and appetite in humans. Materials and methods: In 15 healthy men (age: 25.2 ± 1.1 years; BMI: 22.3 ± 0.5 kg m−2), we compared the effects of 1 nmol kg−1 h−1 kisspeptin versus vehicle administration on glucose-stimulated insulin secretion, metabolites, gut hormones, appetite and food intake. In addition, we assessed the effect of kisspeptin on glucose-stimulated insulin secretion in vitro in human pancreatic islets and a human β-cell line (EndoC-βH1 cells). Results: Kisspeptin administration to healthy men enhanced insulin secretion following an intravenous glucose load, and modulated serum metabolites. In keeping with this, kisspeptin increased glucose-stimulated insulin secretion from human islets and a human pancreatic cell line in vitro. In addition, kisspeptin administration did not alter gut hormones, appetite or food intake in healthy men. Conclusions: Collectively, these data demonstrate for the first time a beneficial role for kisspeptin in insulin secretion in humans in vivo. This has important implications for our understanding of the links between reproduction and metabolism in humans, as well as for the ongoing translational development of kisspeptin-based therapies for reproductive and potentially metabolic conditions

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Polydrug Use by European Adolescents in the Context of Other Problem Behaviours

Aim – Previous studies of the association between polydrug use and other risk behaviours have generally been limited to specific substances and a small number of behaviours. The aim of this study is to obtain better insight into polydrug use (comprising legal and illegal substances: tobacco, alcohol, tranquillisers/sedatives, cannabis, and other illegal drugs) and its association with co-occurring problem behaviours drawn from various broad domains (sexual, aggressive, delinquent, school achievement, relationships) among European adolescents. METHODS – Data were obtained from 101,401 16-year-old students from 35 European countries participating in the 2011 ESPAD survey. Associations between polydrug use and other problem behaviours were examined by multinomial and binary logistic regression analyses. RESULTS – Tranquillisers/sedatives appeared among the commonest combinations in the polydrug use pattern, especially for females. A strong trend was found between levels of involvement with polydrug use and other problem behaviours for both genders. The highest associations with polydrug use were for problems with the police, risky sexual behaviour and skipping school. Gender differences showed higher prevalences among boys than girls of problem behaviours of aggressive, antisocial type, while girls prevailed over boys in relationship problems. CONCLUSION – An incremental relationship exists between the level of involvement with polydrug use and the co-occurrence of problem behaviours. Preventative interventions should consider the misuse of tranquillisers/sedatives within the context of polydrug use by adolescents and expand their target groups towards multiple problem behaviours

The human fetal thymus generates invariant effector γδ T cells.

In the mouse thymus, invariant γδ T cells are generated at well-defined times during development and acquire effector functions before exiting the thymus. However, whether such thymic programming and age-dependent generation of invariant γδ T cells occur in humans is not known. Here we found that, unlike postnatal γδ thymocytes, human fetal γδ thymocytes were functionally programmed (e.g. IFNγ, granzymes) and expressed low levels of terminal deoxynucleotidyl transferase (TdT). This low level of TdT resulted in a low number of N nucleotide insertions in the complementarity-determining region-3 (CDR3) of their TCR repertoire, allowing the usage of short homology repeats within the germline-encoded VDJ segments to generate invariant/public cytomegalovirus-reactive CDR3 sequences (TRGV8-TRJP1-CATWDTTGWFKIF, TRDV2-TRDD3-CACDTGGY, and TRDV1-TRDD3-CALGELGD). Furthermore, both the generation of invariant TCRs and the intrathymic acquisition of effector functions were due to an intrinsic property of fetal hematopoietic stem and precursor cells (HSPCs) caused by high expression of the RNA-binding protein Lin28b. In conclusion, our data indicate that the human fetal thymus generates, in an HSPC/Lin28b-dependent manner, invariant γδ T cells with programmed effector functions.info:eu-repo/semantics/publishe

Artificial intelligence extension of the OSCAR-IB criteria

Artificial intelligence (AI)-based diagnostic algorithms have achieved ambitious aims through automated image pattern recognition. For neurological disorders, this includes neurodegeneration and inflammation. Scalable imaging technology for big data in neurology is optical coherence tomography (OCT). We highlight that OCT changes observed in the retina, as a window to the brain, are small, requiring rigorous quality control pipelines. There are existing tools for this purpose. Firstly, there are human-led validated consensus quality control criteria (OSCAR-IB) for OCT. Secondly, these criteria are embedded into OCT reporting guidelines (APOSTEL). The use of the described annotation of failed OCT scans advances machine learning. This is illustrated through the present review of the advantages and disadvantages of AI-based applications to OCT data. The neurological conditions reviewed here for the use of big data include Alzheimer disease, stroke, multiple sclerosis (MS), Parkinson disease, and epilepsy. It is noted that while big data is relevant for AI, ownership is complex. For this reason, we also reached out to involve representatives from patient organizations and the public domain in addition to clinical and research centers. The evidence reviewed can be grouped in a five-point expansion of the OSCAR-IB criteria to embrace AI (OSCAR-AI). The review concludes by specific recommendations on how this can be achieved practically and in compliance with existing guidelines