Predicting Sleep Quality through Biofeedback: A Machine Learning Approach Using Heart Rate Variability and Skin Temperature.

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.

Unraveling the Epigenetic Landscape: Insights into Parkinson's Disease, Amyotrophic Lateral Sclerosis, and Multiple Sclerosis.

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.

Machine learning identifies phenotypic profile alterations of human dopaminergic neurons exposed to bisphenols and perfluoroalkyls.

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.

The Effects of Combined Exposure to Bisphenols and Perfluoroalkyls on Human Perinatal Stem Cells and the Potential Implications for Health Outcomes.

The present study investigates the impact of two endocrine disruptors, namely Bisphenols (BPs) and Perfluoroalkyls (PFs), on human stem cells. These chemicals leach from plastic, and when ingested through contaminated food and water, they interfere with endogenous hormone signaling, causing various diseases. While the ability of BPs and PFs to cross the placental barrier and accumulate in fetal serum has been documented, the exact consequences for human development require further elucidation. The present research work explored the effects of combined exposure to BPs (BPA or BPS) and PFs (PFOS and PFOA) on human placenta (fetal membrane mesenchymal stromal cells, hFM-MSCs) and amniotic fluid (hAFSCs)-derived stem cells. The effects of the xenobiotics were assessed by analyzing cell proliferation, mitochondrial functionality, and the expression of genes involved in pluripotency and epigenetic regulation, which are crucial for early human development. Our findings demonstrate that antenatal exposure to BPs and/or PFs may alter the biological characteristics of perinatal stem cells and fetal epigenome, with potential implications for health outcomes at birth and in adulthood. Further research is necessary to comprehend the full extent of these effects and their long-term consequences.

Bisphenols and perfluoroalkyls alter human stem cells integrity: A possible link with infertility.

Bisphenols and Perfluoroalkyls are chemical compounds widely used in industry known to be endocrine disruptors (EDs). Once ingested through contaminated aliments, they mimic the activity of endogenous hormones leading to a broad spectrum of diseases. Due to the extensive use of plastic in human life, particular attention should be paid to antenatal exposure to Bisphenols and Perfluoroalkyls since they cross the placental barrier and accumulates in developing embryo. Here we investigated the effects of Bisphenol-A (BPA), Bisphenol-S (BPS), perfluorooctane-sulfonate (PFOS) and perfluorooctanoic-acid (PFOA), alone or combined, on human-induced pluripotent stem cells (hiPSCs) that share several biological features with the stem cells of blastocysts. Our data show that these EDs affect hiPSC inducing a great mitotoxicity and dramatic changes in genes involved in the maintenance of pluripotency, germline specification, and epigenetic regulation. We also evidenced that these chemicals, when combined, may have additive, synergistic but also negative effects. All these data suggest that antenatal exposure to these EDs may affect the integrity of stem cells in the developing embryos, interfering with critical stages of early human development that might be determinant for fertility. The observation that the effects of exposure to a combination of these chemicals are not easily foreseeable further highlights the need for wider awareness of the complexity of the EDs effects on human health and of the social and economic burden attributable to these compounds.

Impact on peri-implant connective tissue of laser treated versus traditional healing abutments: a human clinical trials.

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 < 0.05 was considered statistically significant. RESULTS: Results revealed that the connective tissue facing the laser-treated surface expressed statistically significant lower amount of MMPs (p < 0.05) and higher level of TIMPs 3 (p < 0.05), compared to the tissue surrounding the machined implant, which, in turn expressed also altered level of extracellular matrix protein (Tenascin C, Fibrillin I (p < 0.05)) and Collagen V, that are known to be altered also in peri-implantitis. CONCLUSIONS: In conclusion, the laser-treated surface holds promise in positively influencing wound healing of peri-implant connective tissue. Results demonstrated that topographic nature of the healing abutments can positively influence mucosal wound healing and molecular expression. Previous studies have been demonstrated how laser treatment can rightly influence integrity and functionality of the gingiva epithelium and cell adhesion. Regarding connective tissue different molecular expression demonstrated a different inflammatory pattern between laser treated or machined surfaces where laser treated showed better response. Targeted interventions and preventive measures on peri- implant topography could effectively minimize the risk of peri-implant diseases contributing to the long-term success and durability of restoration. However, new studies are mandatory to better understand this phenomenon and the role of this surface in the peri-implantitis process.  TRIAL REGISTRATION: This trial is registered with ClinicalTrials.gov Identifier: (Registration Number: NCT05754970 ). Registered 06/03/2023, retrospectively registered.

Betaine Treatment Prevents TNF-α-Mediated Muscle Atrophy by Restoring Total Protein Synthesis Rate and Morphology in Cultured Myotubes.

Skeletal muscle atrophy is represented by a dramatic decrease in muscle mass, and it is related to a lower life expectancy. Among the different causes, chronic inflammation and cancer promote protein loss through the effect of inflammatory cytokines, leading to muscle shrinkage. Thus, the availability of safe methods to counteract inflammation-derived atrophy is of high interest. Betaine is a methyl derivate of glycine and it is an important methyl group donor in transmethylation. Recently, some studies found that betaine could promote muscle growth, and it is also involved in anti-inflammatory mechanisms. Our hypothesis was that betaine would be able to prevent tumor necrosis factor-α (TNF-α)-mediated muscle atrophy in vitro. We treated differentiated C2C12 myotubes for 72 hr with either TNF-α, betaine, or a combination of them. After the treatment, we analyzed total protein synthesis, gene expression, and myotube morphology. Betaine treatment blunted the decrease in muscle protein synthesis rate exerted by TNF-α, and upregulated Mhy1 gene expression in both control and myotube treated with TNF-α. In addition, morphological analysis revealed that myotubes treated with both betaine and TNF-α did not show morphological features of TNF-α-mediated atrophy. We demonstrated that in vitro betaine supplementation counteracts the muscle atrophy led by inflammatory cytokines.

Targeted systematic evolution of an RNA platform neutralizing DNMT1 function and controlling DNA methylation.

DNA methylation is a fundamental epigenetic modification regulating gene expression. Aberrant DNA methylation is the most common molecular lesion in cancer cells. However, medical intervention has been limited to the use of broadly acting, small molecule-based demethylating drugs with significant side-effects and toxicities. To allow for targeted DNA demethylation, we integrated two nucleic acid-based approaches: DNMT1 interacting RNA (DiR) and RNA aptamer strategy. By combining the RNA inherent capabilities of inhibiting DNMT1 with an aptamer platform, we generated a first-in-class DNMT1-targeted approach - aptaDiR. Molecular modelling of RNA-DNMT1 complexes coupled with biochemical and cellular assays enabled the identification and characterization of aptaDiR. This RNA bio-drug is able to block DNA methylation, impair cancer cell viability and inhibit tumour growth in vivo. Collectively, we present an innovative RNA-based approach to modulate DNMT1 activity in cancer or diseases characterized by aberrant DNA methylation and suggest the first alternative strategy to overcome the limitations of currently approved non-specific hypomethylating protocols, which will greatly improve clinical intervention on DNA methylation.

Prognostic Value of High-Sensitivity Cardiac Troponin in Women.

High-sensitivity cardiac troponin assays have become the gold standard for diagnosing acute and chronic myocardial injury. The detection of troponin levels beyond the 99th percentile is included in the fourth universal definition of myocardial infarction, specifically recommending the use of sex-specific thresholds. Measurable concentrations below the proposed diagnostic thresholds have been shown to inform prognosis in different categories of inpatients and outpatients. However, clinical investigations from the last twenty years have yielded conflicting results regarding the incremental value of using different cut-offs for men and women. While advocates of a sex-specific approach claim it may help reduce gender bias in cardiovascular medicine, particularly in acute coronary syndromes, other groups question the alleged incremental diagnostic and prognostic value of sex-specific thresholds, ultimately asserting that less is more. In the present review, we aimed to synthesize our current understanding of sex-based differences in cardiac troponin levels and to reappraise the available evidence with regard to (i) the prognostic significance of sex-specific diagnostic thresholds of high-sensitivity cardiac troponin assays compared to common cut-offs in both men and women undergoing cardiovascular disease risk assessment, and (ii) the clinical utility of high-sensitivity cardiac troponin assays for cardiovascular disease prevention in women.

Human fetal membrane-mesenchymal stromal cells generate functional spinal motor neurons in vitro.

Human fetal membrane mesenchymal stromal cells (hFM-MSCs) are a cell population easily isolable from the amniochorionic membrane of term placentas, without ethical issues or safety limitations. We previously reported that hFM-MSCs share some epigenetic characteristics with pluripotent stem cells and can overcome the mesenchymal commitment. Here, we demonstrated that hFM-MSCs can give rise to spinal motor neurons by the sequential exposure to specific factors that induced a neuralization, caudalization and ventralization of undifferentiated cells, leading to a gradual gene and protein upregulation of early and late MN markers. Also, spontaneous electrical activity (spikes and bursts) was recorded. Finally, when co-cultured with myotubes, differentiated MNs were able to create functional neuromuscular junctions that induced robust skeletal muscle cell contractions. These data demonstrated the hFM-MSCs can generate a mature and functional MN population that may represent an alternative source for regenerative medicine, disease modeling or drug screening.

Human mesenchymal amniotic fluid stem cells reveal an unexpected neuronal potential differentiating into functional spinal motor neurons.

Human amniotic fluids stem cells (hAFSCs) can be easily isolated from the amniotic fluid during routinely scheduled amniocentesis. Unlike hiPSCs or hESC, they are neither tumorigenic nor immunogenic and their use does not rise ethical or safety issues: for these reasons they may represent a good candidate for the regenerative medicine. hAFSCs are generally considered multipotent and committed towards the mesodermal lineages; however, they express many pluripotent markers and share some epigenetic features with hiPSCs. Hence, we hypothesized that hAFSCs may overcome their mesodermal commitment differentiating into to ectodermal lineages. Here we demonstrated that by the sequential exposure to specific factors, hAFSCs can give rise to spinal motor neurons (MNs), as evidenced by the gradual gene and protein upregulation of early and late MN markers (PAX6, ISL1, HB9, NF-L, vAChT). When co-cultured with myotubes, hAFSCs-derived MNs were able to create functional neuromuscular junctions that induced robust skeletal muscle contractions. These data demonstrated the hAFSCs are not restricted to mesodermal commitment and can generate functional MNs thus outlining an ethically acceptable strategy for the study and treatment of the neurodegenerative diseases.

Estimation of Heart Rate Variability Parameters by Machine Learning Approaches Applied to Facial Infrared Thermal Imaging.

Heart rate variability (HRV) is a reliable tool for the evaluation of several physiological factors modulating the heart rate (HR). Importantly, variations of HRV parameters may be indicative of cardiac diseases and altered psychophysiological conditions. Recently, several studies focused on procedures for contactless HR measurements from facial videos. However, the performances of these methods decrease when illumination is poor. Infrared thermography (IRT) could be useful to overcome this limitation. In fact, IRT can measure the infrared radiations emitted by the skin, working properly even in no visible light illumination conditions. This study investigated the capability of facial IRT to estimate HRV parameters through a face tracking algorithm and a cross-validated machine learning approach, employing photoplethysmography (PPG) as the gold standard for the HR evaluation. The results demonstrated a good capability of facial IRT in estimating HRV parameters. Particularly, strong correlations between the estimated and measured HR (r = 0.7), RR intervals (r = 0.67), TINN (r = 0.71), and pNN50 (%) (r = 0.70) were found, whereas moderate correlations for RMSSD (r = 0.58), SDNN (r = 0.44), and LF/HF (r = 0.48) were discovered. The proposed procedure allows for a contactless estimation of the HRV that could be beneficial for evaluating both cardiac and general health status in subjects or conditions where contact probe sensors cannot be used.

Resveratrol Enhances the Cytotoxic Activity of Lymphocytes from Menopausal Women.

Nutraceuticals and functional foods are the main sources of antioxidants and have positive effects on health through regulation of the redox balance. Accordingly, they represent a useful nutritional source for the prevention of noncommunicable diseases (NCDs). Menopausal women have an increased risk of developing NCDs due to hormonal dysregulation and the ongoing aging process. Accordingly, a healthy lifestyle and good nutritional habits are of utmost importance in this population. Resveratrol (RSV) is a natural polyphenol, and it is used as a nutraceutical given its estrogenic, anti-inflammatory, and antioxidant properties. The aim of this study was to analyze the effects of RSV on the lymphocyte cytotoxicity in menopausal women. Lymphocytes from 13 healthy menopausal women (56.18 ± 4.24 years) were isolated, and then cocultured with hTERT-HME1, a breast cell line with a precancerous phenotype. The results showed that, when treated with RSV, lymphocytes significantly increased the TNF-α production (p < 0.001), the formation of immune synapses (p = 0.009), and the target cell lysis (p = 0.002). No effects were detected in the lymphocyte total antioxidant capacity. In conclusion, RSV might enhance the immune surveillance in menopausal women by increasing the cytotoxic activity of lymphocytes.

Bioelectrical Impedance Vector Analysis of Young Elite Team Handball Players.

Team handball is a highly dynamic sport where physical demands differ between categories and roles. Thus, physical characteristics are fundamental for the final performance. This study aims to (a) characterize a sample of young male and female elite team handball players with a non-athletic reference population; (b) to generate their 50%, 75%, and 95% percentiles of the bioelectrical variables. The study included 55 young elite team handball players (Males, n = 37, age = 17.0 ± 1.2 yrs, height = 185.8 ± 7.3 cm, weight = 82.0 ± 11.0 kg, body mass index (BMI) = 23.7 ± 2.5; Females, n = 18, age = 17.8 ± 0.9 yrs, height = 171.2 ± 6.4 cm, weight = 67.4 ± 7.2 kg, BMI = 23.0 ± 2.0). Height and bioelectrical variables were assessed in a state of euhydration and standard conditions. Bioelectrical impedance vector analysis (BIVA) was used to characterize the bioelectrical vector (BIA vector) distribution pattern for each group. Compared to the reference values, BIA vector showed statistically significant differences in males U17 (n = 19, T2 = 51.0, p < 0.0001), males U19 (n = 18, T2 = 82.0, p < 0.0001) and females U19 (n = 18, T2 = 85.8, p < 0.0001). Male groups were also bioelectrically different (T2 = 13.7, p = 0.0036). BIVA showed specific bioelectrical characteristics in young male and female elite handball players. This study provides an original data set of bioelectrical impedance reference values of young male and female elite team handball players. Our result might help to interpret individual bioimpedance vectors and define target regions for young handball players.

NAD Modulates DNA Methylation and Cell Differentiation.

Nutritional intake impacts the human epigenome by directing epigenetic pathways in normal cell development via as yet unknown molecular mechanisms. Consequently, imbalance in the nutritional intake is able to dysregulate the epigenetic profile and drive cells towards malignant transformation. Here we present a novel epigenetic effect of the essential nutrient, NAD. We demonstrate that impairment of DNMT1 enzymatic activity by NAD-promoted ADP-ribosylation leads to demethylation and transcriptional activation of the CEBPA gene, suggesting the existence of an unknown NAD-controlled region within the locus. In addition to the molecular events, NAD- treated cells exhibit significant morphological and phenotypical changes that correspond to myeloid differentiation. Collectively, these results delineate a novel role for NAD in cell differentiation, and indicate novel nutri-epigenetic strategies to regulate and control gene expression in human cells.

Real-Time Monitoring of Levetiracetam Effect on the Electrophysiology of an Heterogenous Human iPSC-Derived Neuronal Cell Culture Using Microelectrode Array Technology.

Levetiracetam (LEV) is a broad-spectrum and widely used antiepileptic drug that also has neuroprotective effects in different neurological conditions. Given its complex interaction with neuronal physiology, a better comprehension of LEV effects on neurons activity is needed. Microelectrode arrays (MEAs) represent an advanced technology for the non-invasive study of electrophysiological activity of neuronal cell cultures. In this study, we exploited the Maestro Edge MEA system, a platform that allows a deep analysis of the electrical network behavior, to study the electrophysiological effect of LEV on a mixed population of human neurons (glutamatergic, GABAergic and dopaminergic neurons, and astrocytes). We found that LEV significantly affected different variables such as spiking, single-electrode bursting, and network bursting activity, with a pronounced effect after 15 min. Moreover, neuronal cell culture completely rescued its baseline activity after 24 h without LEV. In summary, MEA technology confirmed its high sensitivity in detecting drug-induced electrophysiological modifications. Moreover, our results allow one to extend the knowledge on the electrophysiological effects of LEV on the complex neuronal population that resembles the human cortex.

The Prediction of Running Velocity during the 30-15 Intermittent Fitness Test Using Accelerometry-Derived Metrics and Physiological Parameters: A Machine Learning Approach.

Measuring exercise variables is one of the most important points to consider to maximize physiological adaptations. High-intensity interval training (HIIT) is a useful method to improve both cardiovascular and neuromuscular performance. The 30-15IFT is a field test reflecting the effort elicited by HIIT, and the final velocity reached in the test is used to set the intensity of HIIT during the training session. In order to have a valid measure of the velocity during training, devices such as GPS can be used. However, in several situations (e.g., indoor setting), such devices do not provide reliable measures. The aim of the study was to predict exact running velocity during the 30-15IFT using accelerometry-derived metrics (i.e., Player Load and Average Net Force) and heart rate (HR) through a machine learning (ML) approach (i.e., Support Vector Machine) with a leave-one-subject-out cross-validation. The SVM approach showed the highest performance to predict running velocity (r = 0.91) when compared to univariate approaches using PL (r = 0.62), AvNetForce (r = 0.73) and HR only (r = 0.87). In conclusion, the presented multivariate ML approach is able to predict running velocity better than univariate ones, and the model is generalizable across subjects.

Chemical and Biological Molecules Involved in Differentiation, Maturation, and Survival of Dopaminergic Neurons in Health and Parkinson's Disease: Physiological Aspects and Clinical Implications.

Parkinson's disease (PD) is one of the most common neurodegenerative disease characterized by a specific and progressive loss of dopaminergic (DA) neurons and dopamine, causing motor dysfunctions and impaired movements. Unfortunately, available therapies can partially treat the motor symptoms, but they have no effect on non-motor features. In addition, the therapeutic effect reduces gradually, and the prolonged use of drugs leads to a significative increase in the number of adverse events. For these reasons, an alternative approach that allows the replacement or the improved survival of DA neurons is very appealing for the treatment of PD patients and recently the first human clinical trials for DA neurons replacement have been set up. Here, we review the role of chemical and biological molecules that are involved in the development, survival and differentiation of DA neurons. In particular, we review the chemical small molecules used to differentiate different type of stem cells into DA neurons with high efficiency; the role of microRNAs and long non-coding RNAs both in DA neurons development/survival as far as in the pathogenesis of PD; and, finally, we dissect the potential role of exosomes carrying biological molecules as treatment of PD.

The Influence of Maturity Status on Anthropometric Profile and Body Composition of Youth Goalkeepers.

The anthropometric profile assessment is an important aspect to consider during the growth stages of youth sport practitioners due to its usefulness in controlling maturity status and overall health. We performed an anthropometric profile evaluation in a sample of youth goalkeepers (n = 42) during a training camp, dividing them into three categories based on their years from peak height velocity (YPHV). We also checked if the selection of goalkeepers was associated with the birth quartile. The results showed that most of the participants' anthropometric parameters followed the normal trend according to the maturation stages. However, several subjects showed an overweight/obese condition and/or high waist circumference. Non-optimal values were found, mostly in the group of goalkeepers around the PHV. In addition, no selection based on birth quartile was seen. Therefore, the anthropometric profile and body composition of youth goalkeepers are physiologically affected by maturity status. However, several subjects were found to be overweight/obese and at cardiometabolic risk, suggesting that children and adolescents, although practicing sport, should pay attention to potentially contributing factors such as the attainment of the recommended levels of physical activity, lowering sedentary time, and adopt a healthy lifestyle.