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Sleep quality (SQ) is a crucial aspect of overall health. Poor sleep quality may cause cognitive impairment, mood disturbances, and an increased risk of chronic diseases. Therefore, assessing sleep quality helps identify individuals at risk and develop effective interventions. SQ has been demonstrated to affect heart rate variability (HRV) and skin temperature even during wakefulness. In this perspective, using wearables and contactless technologies to continuously monitor HR and skin temperature is highly suited for assessing objective SQ. However, studies modeling the relationship linking HRV and skin temperature metrics evaluated during wakefulness to predict SQ are lacking. This study aims to develop machine learning models based on HRV and skin temperature that estimate SQ as assessed by the Pittsburgh Sleep Quality Index (PSQI). HRV was measured with a wearable sensor, and facial skin temperature was measured by infrared thermal imaging. Classification models based on unimodal and multimodal HRV and skin temperature were developed. A Support Vector Machine applied to multimodal HRV and skin temperature delivered the best classification accuracy, 83.4%. This study can pave the way for the employment of wearable and contactless technologies to monitor SQ for ergonomic applications. The proposed method significantly advances the field by achieving a higher classification accuracy than existing state-of-the-art methods. Our multimodal approach leverages the synergistic effects of HRV and skin temperature metrics, thus providing a more comprehensive assessment of SQ. Quantitative performance indicators, such as the 83.4% classification accuracy, underscore the robustness and potential of our method in accurately predicting sleep quality using non-intrusive measurements taken during wakefulness.

Abstract Background Surfactant is a well-established therapy for preterm neonates affected by respiratory distress syndrome (RDS). The goals of different methods of surfactant administration are to reduce the duration of mechanical ventilation and the severity of bronchopulmonary dysplasia (BPD); however, the optimal administration method remains unknown. This study compares the effectiveness of the INtubate-RECruit-SURfactant-Extubate (IN-REC-SUR-E) technique with the less-invasive surfactant administration (LISA) technique, in increasing BPD-free survival of preterm infants. This is an international unblinded multicenter randomized controlled study in which preterm infants will be randomized into two groups to receive IN-REC-SUR-E or LISA surfactant administration. Methods In this study, 382 infants born at 24+0–27+6 weeks’ gestation, not intubated in the delivery room and failing nasal continuous positive airway pressure (nCPAP) or nasal intermittent positive pressure ventilation (NIPPV) during the first 24 h of life, will be randomized 1:1 to receive IN-REC-SUR-E or LISA surfactant administration. The primary outcome is a composite outcome of death or BPD at 36 weeks’ postmenstrual age. The secondary outcomes are BPD at 36 weeks’ postmenstrual age; death; pulse oximetry/fraction of inspired oxygen; severe intraventricular hemorrhage; pneumothorax; duration of respiratory support and oxygen therapy; pulmonary hemorrhage; patent ductus arteriosus undergoing treatment; percentage of infants receiving more doses of surfactant; periventricular leukomalacia, severe retinopathy of prematurity, necrotizing enterocolitis, sepsis; total in-hospital stay; systemic postnatal steroids; neurodevelopmental outcomes; and respiratory function testing at 24 months of age. Randomization will be centrally provided using both stratification and permuted blocks with random block sizes and block order. Stratification factors will include center and gestational age (24+0 to 25+6 weeks or 26+0 to 27+6 weeks). Analyses will be conducted in both intention-to-treat and per-protocol populations, utilizing a log-binomial regression model that corrects for stratification factors to estimate the adjusted relative risk (RR). Discussion This trial is designed to provide robust data on the best method of surfactant administration in spontaneously breathing preterm infants born at 24+0–27+6 weeks’ gestation affected by RDS and failing nCPAP or NIPPV during the first 24 h of life, comparing IN-REC-SUR-E to LISA technique, in increasing BPD-free survival at 36 weeks’ postmenstrual age of life. Trial registration ClinicalTrials.gov NCT05711966. Registered on February 3, 2023.

Abstract Background Although physical activity (PA) is associated with significant health benefits, only a small percentage of adolescents meet recommended PA levels. This systematic review with meta-analysis explored the modifiable determinants of adolescents’ device-based PA and/or sedentary behaviour (SB), evaluated in previous interventions and examined the associations between PA/SB and these determinants in settings. Methods A search was conducted on five electronic databases, including papers published from January 2010 to July 2023. Randomized Controlled Trials (RCTs) or Controlled Trials (CTs) measuring adolescents’ device-based PA/SB and their modifiable determinants at least at two time points: pre- and post-intervention were considered eligible. PA/SB and determinants were the main outcomes. Modifiable determinants were classified after data extraction adopting the social-ecological perspective. Robust Bayesian meta-analyses (RoBMA) were performed per each study setting. Outcomes identified in only one study were presented narratively. The risk of bias for each study and the certainty of the evidence for each meta-analysis were evaluated. The publication bias was also checked. PROSPERO ID: CRD42021282874. Results Fourteen RCTs (eight in school, three in school and family, and one in the family setting) and one CT (in the school setting) were included. Fifty-four modifiable determinants were identified and were combined into 33 broader determinants (21 individual–psychological, four individual–behavioural, seven interpersonal, and one institutional). RoBMAs revealed none or negligible pooled intervention effects on PA/SB or determinants in all settings. The certainty of the evidence of the impact of interventions on outcomes ranged from very low to low. Narratively, intervention effects in favour of the experimental group were detected in school setting for the determinants: knowledge of the environment for practicing PA, d = 1.84, 95%CI (1.48, 2.20), behaviour change techniques, d = 0.90, 95%CI (0.09, 1.70), choice provided, d = 0.70, 95%CI (0.36, 1.03), but no corresponding effects on PA or SB were found. Conclusions Weak to minimal evidence regarding the associations between the identified modifiable determinants and adolescents’ device-based PA/SB in settings were found, probably due to intervention ineffectiveness. Well-designed and well-implemented multicomponent interventions should further explore the variety of modifiable determinants of adolescents’ PA/SB, including policy and environmental variables.

Abstract Parkinson’s disease (PD) is the second most common neurodegenerative disease and is characterized by the loss of midbrain dopaminergic neurons. Endocrine disrupting chemicals (EDCs) are active substances that interfere with hormonal signaling. Among EDCs, bisphenols (BPs) and perfluoroalkyls (PFs) are chemicals leached from plastics and other household products, and humans are unavoidably exposed to these xenobiotics. Data from animal studies suggest that EDCs exposure may play a role in PD, but data about the effect of BPs and PFs on human models of the nervous system are lacking. Previous studies demonstrated that machine learning (ML) applied to microscopy data can classify different cell phenotypes based on image features. In this study, the effect of BPs and PFs at different concentrations within the real-life exposure range (0.01, 0.1, 1, and 2 µM) on the phenotypic profile of human stem cell-derived midbrain dopaminergic neurons (mDANs) was analyzed. Cells exposed for 72 h to the xenobiotics were stained with neuronal markers and evaluated using high content microscopy yielding 126 different phenotypic features. Three different ML models (LDA, XGBoost and LightGBM) were trained to classify EDC-treated versus control mDANs. EDC treated mDANs were identified with high accuracies (0.88–0.96). Assessment of the phenotypic feature contribution to the classification showed that EDCs induced a significant increase of alpha-synuclein (αSyn) and tyrosine hydroxylase (TH) staining intensity within the neurons. Moreover, microtubule-associated protein 2 (MAP2) neurite length and branching were significantly diminished in treated neurons. Our study shows that human mDANs are adversely impacted by exposure to EDCs, causing their phenotype to shift and exhibit more characteristics of PD. Importantly, ML-supported high-content imaging can identify concrete but subtle subcellular phenotypic changes that can be easily overlooked by visual inspection alone and that define EDCs effects in mDANs, thus enabling further pathological characterization in the future.

Abstract Background Dental implant is the principal treatment for edentulism and the healthiness of the peri-implant tissue has a pivotal role for its longterm success. In addition, it has been shown that also the topography of the healing abutment can influence the outcome of the restoration. The objective of this human clinical trial was to assess the impact of a novel laser-treated healing abutment on peri-implant connective tissue and extracellular matrix proteins compared to the conventional machined surface, which served as the control group. Methods During second surgical stage a customized healing abutment were inserted on 30 single dental implants. Healing abutments were realized with two alternated different surface (two side laser-treated surfaces and two side machined surfaces) in order to be considered both as test and control on the same implant and reduce positioning bias. Following the soft tissue healing period (30 ± 7 days) a 5 mm circular biopsy was retrieved. Immuno-histochemical and quantitative real-time PCR (qPCR) analyses were performed on Collagen, Tenascin C, Fibrillin I, Metalloproteinases (MMPs) and their inhibitor (TIMPs). 15 were processed for qPCR, while the other 15 were processed for immunohistochemical analysis. Paired t-test between the two groups were performed. A value of p

Aims: Recent evidence supports non-class cardioprotective effects of metoprolol against neutrophil-mediated ischemia-reperfusion injury during exacerbated inflammation. Whether metoprolol exerts direct anti-inflammatory effect on cardiomyocytes is unknown. Accordingly, we aimed to investigate the direct anti-inflammatory effects of metoprolol in a cellular model of human induced pluripotent stem cell-derived cardiomyocytes (hiCMs) and to explore the role of β-arrestin2 (β-ARR2) biased agonism signaling pathway. Methods and results: hiCMs were treated with TNF-α for 24 h, followed by 4-hour treatment with metoprolol or esmolol. Electrical response of hiCMs to β1-selective blockade was assessed by microelectrode arrays technology. The effect on inflammatory and adhesion molecule expression was evaluated in wild-type and β-ARR2 silenced hiCMs. To silence β-ARR2 expression, hiCMs were transfected with a specific small interfering RNA targeting β-ARR2 mRNA and preventing its translation.TNF-α stimulation boosted the expression of IκB, NF-κB, IL1β, IL6, and VCAM1 in hiCMs. TNF-α-treated hiCMs showed similar physiological responses to metoprolol and esmolol, with no difference in field potential duration and beat period recorded. Adding metoprolol significantly decreased inflammatory response patterns in wild-type hiCMs by dampening TNF-α induced expression of NF-κB, IL1β, and IL6, but not in β-ARR2-knockout hiCMs. A similar response was not observed in presence of β1-selective blockade with esmolol. Conclusions: Metoprolol exerts a non-class direct anti-inflammatory effect on hi-CMs. β1-selective blockade with metoprolol disrupts inflammatory responses induced by TNF-α and induces significant inhibition of NF-κB signaling cascade via β-ARR2 biased agonism. If confirmed at clinical level, metoprolol could be tested and repurposed to treat cardiac inflammatory disorders.

The physical activity, exercise and wellness sector is rapidly growing and seems to be an exciting field for business and professional development with great potential globally. The purpose of this observational and cross-sectional study was to determine the most popular health and fitness trends in Southern Europe for the first time, including data from Italy, Spain, Portugal, Greece and Cyprus, and to investigate any potential differences in this area compared to the Pan-European and global fitness trends for 2023. A national online survey was conducted in five Southern European countries, using the methodology of similar regional and worldwide surveys conducted by the American College of Sports Medicine since 2007. In total, a web-based questionnaire was sent to 19,887 professionals who worked in the Southern European physical activity, exercise and wellness sector. A total of 2645 responses were collected from five national surveys with an overall mean response rate of 13.3%. The ten most important fitness trends in Southern Europe for 2023 were personal training, licensure for fitness professionals, exercise is medicine, employing certified fitness professionals, functional fitness training, small group training, high-intensity interval training, fitness programs for older adults, post-rehabilitation classes and body weight training. The present findings are aligned with those reported for the European and worldwide fitness trends.

Parkinson’s disease (PD), multiple sclerosis (MS), and amyotrophic lateral sclerosis (ALS) are examples of neurodegenerative movement disorders (NMDs), which are defined by a gradual loss of motor function that is frequently accompanied by cognitive decline. Although genetic abnormalities have long been acknowledged as significant factors, new research indicates that epigenetic alterations are crucial for the initiation and development of disease. This review delves into the complex interactions that exist between the pathophysiology of NMDs and epigenetic mechanisms such DNA methylation, histone modifications, and non-coding RNAs. Here, we examine how these epigenetic changes could affect protein aggregation, neuroinflammation, and gene expression patterns, thereby influencing the viability and functionality of neurons. Through the clarification of the epigenetic terrain underpinning neurodegenerative movement disorders, this review seeks to enhance comprehension of the underlying mechanisms of the illness and augment the creation of innovative therapeutic strategies.

BackgroundAlcohol is a well-established risk factor for head and neck cancer (HNC). This study aims to explore the effect of alcohol intensity and duration, as joint continuous exposures, on HNC risk.MethodsData from 26 case-control studies in the INHANCE Consortium were used, including never and current drinkers who drunk ≤10 drinks/day for ≤54 years (24234 controls, 4085 oral cavity, 3359 oropharyngeal, 983 hypopharyngeal and 3340 laryngeal cancers). The dose-response relationship between the risk and the joint exposure to drinking intensity and duration was investigated through bivariate regression spline models, adjusting for potential confounders, including tobacco smoking.ResultsFor all subsites, cancer risk steeply increased with increasing drinks/day, with no appreciable threshold effect at lower intensities. For each intensity level, the risk of oral cavity, hypopharyngeal and laryngeal cancers did not vary according to years of drinking, suggesting no effect of duration. For oropharyngeal cancer, the risk increased with durations up to 28 years, flattening thereafter. The risk peaked at the higher levels of intensity and duration for all subsites (odds ratio = 7.95 for oral cavity, 12.86 for oropharynx, 24.96 for hypopharynx and 6.60 for larynx).ConclusionsPresent results further encourage the reduction of alcohol intensity to mitigate HNC risk.

The aim of the study was to evaluate the effects of Active or Sedentary lifestyle on saliva microbiota composition in Italian schoolchildren.MethodsMale (114) and female children (8–10 years) belonging to five primary schools in the neighborhoods of Turin were classified as active (A) or sedentary (S) based on PAQ-C-It questionnaire. PCR amplification of salivary DNA targeted the hypervariable V3–V4 regions of the 16S rRNA bacterial genes. DADA2 workflow was used to infer the Amplicon Sequence Variants and the taxonomic assignments; the beta-diversity was obtained by PCoA with the UniFrac method; LEfSe algorithm, threshold at 5%, and Log LDA cutoff at ±0.5 were used to identify differently abundant species in A compared to S saliva sample. Daily food intake was assessed by 3-Days food record. The metabolic potential of microbial communities was assessed by PICRUSt.ResultsNo significant differences were found in individual’s gender distribution (p = 0.411), anthropometry, BMI (p > 0.05), and all diet composition between A and S groups (p > 0.05). Eight species were differently abundant: Prevotella nigrescens (LDA score = −3.76; FDR = 1.5×10–03), Collinsella aerofaciens (LDA score = −3.17; FDR = 7.45×10–03), Simonsiella muelleri (LDA score = −2.96; FDR = 2.76×10–05), Parabacteroides merdae (LDA score = −2.43; FDR = 1.3×10–02) are enriched in the A group; Gemella parahaemolysans, Prevotella aurantiaca (LDA score = −3.9; FDR = 5.27×10–04), Prevotella pallens (LDA score = 4.23; FDR = 1.93×10–02), Neisseria mucosa (LDA score = 4.43; FDR = 1.31×10–02; LDA score = 2.94; FDR = 7.45×10–03) are enriched in the S group. A prevalence of superpathway of fatty acid biosynthesis initiation (E. coli) and catechol degradation II (meta-cleavage pathway) was found in saliva from A compared to S children.ConclusionOur results showed that active children had an enrichment of species and genera mainly associated with a healthier profile. By contrast, the genera and the species enriched in the sedentary group could be linked to human diseases.

ObjectivesThis study aimed at re-evaluating the strength and shape of the dose-response relationship between the combined (or joint) effect of intensity and duration of cigarette smoking and the risk of head and neck cancer (HNC). We explored this issue considering bivariate spline models, where smoking intensity and duration were treated as interacting continuous exposures.Materials and methodsWe pooled individual-level data from 33 case-control studies (18,260 HNC cases and 29,844 controls) participating in the International Head and Neck Cancer Epidemiology (INHANCE) consortium. In bivariate regression spline models, exposures to cigarette smoking intensity and duration (compared with never smokers) were modeled as a linear piecewise function within a logistic regression also including potential confounders. We jointly estimated the optimal knot locations and regression parameters within the Bayesian framework.ResultsFor oral-cavity/pharyngeal (OCP) cancers, an odds ratio (OR) >5 was reached after 30 years in current smokers of ∼20 or more cigarettes/day. Patterns of OCP cancer risk in current smokers differed across strata of alcohol intensity. For laryngeal cancer, ORs >20 were found for current smokers of ≥20 cigarettes/day for ≥30  years. In former smokers who quit ≥10  years ago, the ORs were approximately halved for OCP cancers, and ∼1/3 for laryngeal cancer, as compared to the same levels of intensity and duration in current smokers.ConclusionReferring to bivariate spline models, this study better quantified the joint effect of intensity and duration of cigarette smoking on HNC risk, further stressing the need of smoking cessation policies.

Background The 2022 Global Initiative for Asthma guidelines emphasise the inhaled long-acting β2-agonist formoterol as part of the first treatment step, and therefore formoterol use among athletes will probably increase. However, prolonged supratherapeutic use of inhaled β2-agonists impairs training outcomes in moderately trained men. We investigated whether inhaled formoterol, at therapeutic doses, imposes detrimental effects in endurance-trained individuals of both sexes. Methods 51 endurance-trained participants (31 male, 20 female; mean±sd maximal oxygen consumption (V̇O2max) 62±6 mL·min−1·kg bw−1 and 52±5 mL·min−1·kg bw−1, respectively) inhaled formoterol (24 µg; n=26) or placebo (n=25) twice daily for 6 weeks. At baseline and follow-up, we assessed V̇O2max and incremental exercise performance during a bike-ergometer ramp-test; body composition by dual-energy X-ray absorptiometry; muscle oxidative capacity by high-resolution mitochondrial respirometry, enzymatic activity assays and immunoblotting; intravascular volumes by carbon monoxide rebreathing; and cardiac left ventricle mass and function by echocardiography. Results Compared to placebo, formoterol increased lean body mass by 0.7 kg (95% CI 0.2–1.2 kg; treatment×trial p=0.022), but decreased V̇O2max by 5% (treatment×trial p=0.013) and incremental exercise performance by 3% (treatment×trial p

Skeletal muscle mass plays a pivotal role in metabolic function, but conditions such as bed rest or injury often render resistance training impractical. The beta2‐adrenergic receptor has been highlighted as a potential target to promote muscle hypertrophy and treat atrophic conditions. Here, we investigate the proteomic changes associated with beta2‐adrenergic‐mediated muscle hypertrophy, using resistance training as a hypertrophic comparator. We utilize MS‐based proteomics to map skeletal muscle proteome remodeling in response to beta2‐adrenergic stimulation or resistance training as well as cell model validation. We report that beta2‐adrenergic stimulation mimics multiple features of resistance training in proteome‐wide remodeling, comprising systematic upregulation of ribosomal subunits and concomitant downregulation of mitochondrial proteins. Approximately 20% of proteins were regulated in both conditions, comprising proteins involved in steroid metabolism (AKR1C1, AKR1C2, AKRC1C3), protein‐folding (SERPINB1), and extracellular matrix organization (COL1A1, COL1A2). Among overall most significantly upregulated proteins were kelch‐like family members (KLHL) 40 and 41. In follow‐up experiments, we identify KLHL41 as having novel implications for beta2‐adrenergic‐mediated muscle hypertrophy. Treating C2C12 cells with beta2‐agonist for 96 h increased myotube diameter by 48% (p < 0.001). This anabolic effect was abolished by prior knockdown of KLHL41. Using siRNA, KLHL41 abundance was decreased by 60%, and the anabolic response to beta2‐agonist was diminished (+ 15%, i.e., greater in the presence of KLHL41, knock‐down × treatment: p = 0.004). In conclusion, protein‐wide remodeling induced by beta2‐adrenergic stimulation mimics multiple features of resistance training, and thus the beta2‐adrenergic receptor may be a target with therapeutic potential in the treatment of muscle wasting conditions without imposing mechanical load. [ABSTRACT FROM AUTHOR]

Sleep quality (SQ) is a crucial aspect of overall health. Poor sleep quality may cause cognitive impairment, mood disturbances, and an increased risk of chronic diseases. Therefore, assessing sleep quality helps identify individuals at risk and develop effective interventions. SQ has been demonstrated to affect heart rate variability (HRV) and skin temperature even during wakefulness. In this perspective, using wearables and contactless technologies to continuously monitor HR and skin temperature is highly suited for assessing objective SQ. However, studies modeling the relationship linking HRV and skin temperature metrics evaluated during wakefulness to predict SQ are lacking. This study aims to develop machine learning models based on HRV and skin temperature that estimate SQ as assessed by the Pittsburgh Sleep Quality Index (PSQI). HRV was measured with a wearable sensor, and facial skin temperature was measured by infrared thermal imaging. Classification models based on unimodal and multimodal HRV and skin temperature were developed. A Support Vector Machine applied to multimodal HRV and skin temperature delivered the best classification accuracy, 83.4%. This study can pave the way for the employment of wearable and contactless technologies to monitor SQ for ergonomic applications. The proposed method significantly advances the field by achieving a higher classification accuracy than existing state-of-the-art methods. Our multimodal approach leverages the synergistic effects of HRV and skin temperature metrics, thus providing a more comprehensive assessment of SQ. Quantitative performance indicators, such as the 83.4% classification accuracy, underscore the robustness and potential of our method in accurately predicting sleep quality using non-intrusive measurements taken during wakefulness. [ABSTRACT FROM AUTHOR]