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.

One of the main aims in regenerative medicine is to find stem cells that are easy to obtain and are safe and efficient in either an autologous or allogenic host when transplanted. This review provides an overview of the potential use of the fetal annexes in regenerative medicine: we described the formation of the annexes, their immunological features, the new advances in the phenotypical characterization of fetal annexes-derived stem cells, the progressions obtained in the analysis of both their differentiative potential and their secretoma, and finally, the potential use of decellularized fetal membranes. Normally discarded as medical waste, the umbilical cord and perinatal tissue not only represent a rich source of stem cells but can also be used as a scaffold for regenerative medicine, providing a suitable environment for the growth and differentiation of stem cells.

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.

Surface electromyography (sEMG) is the acquisition, from the skin, of the electrical signal produced by muscle activation. Usually, sEMG is measured through electrodes with electrolytic gel, which often causes skin irritation. Capacitive contactless electrodes have been developed to overcome this limitation. However, contactless EMG devices are still sensitive to motion artifacts and often not comfortable for long monitoring. In this study, a non-invasive contactless method to estimate parameters indicative of muscular activity and fatigue, as they are assessed by EMG, through infrared thermal imaging (IRI) and cross-validated machine learning (ML) approaches is described. Particularly, 10 healthy participants underwent five series of bodyweight squats until exhaustion interspersed by 1 min of rest. During exercising, the vastus medialis activity and its temperature were measured through sEMG and IRI, respectively. The EMG average rectified value (ARV) and the median frequency of the power spectral density (MDF) of each series were estimated through several ML approaches applied to IRI features, obtaining good estimation performances (r = 0.886, p < 0.001 for ARV, and r = 0.661, p < 0.001 for MDF). Although EMG and IRI measure physiological processes of a different nature and are not interchangeable, these results suggest a potential link between skin temperature and muscle activity and fatigue, fostering the employment of contactless methods to deliver metrics of muscular activity in a non-invasive and comfortable manner in sports and clinical applications.

Degeneration of dopaminergic neurons represents the cause of many neurodegenerative diseases, with increasing incidence worldwide. The replacement of dead cells with new healthy ones may represent an appealing therapeutic approach to these pathologies, but currently, only pluripotent stem cells can generate dopaminergic neurons with high efficiency. However, with the use of these cells arises safety and/or ethical issues. Human mesenchymal stromal cells (hFM-MSCs) are perinatal stem cells that can be easily isolated from the amniochorionic membrane after delivery. Generally considered multipotent, their real differentiative potential is not completely elucidated. The aim of this study was to analyze their stemness characteristics and to evaluate whether they may overcome their mesenchymal fate, generating dopaminergic neurons. We demonstrated that hFM-MSCs expressed embryonal genes OCT4, NANOG, SOX2, KLF4, OVOL1, and ESG1, suggesting they have some features of pluripotency. Moreover, hFM-MSCs that underwent a dopaminergic differentiation protocol gradually increased the transcription of dopaminergic markers LMX1b, NURR1, PITX3, and DAT. We finally obtained a homogeneous population of cells resembling the morphology of primary midbrain dopaminergic neurons that expressed the functional dopaminergic markers TH, DAT, and Nurr1. In conclusion, our results suggested that hFM-MSCs retain the expression of pluripotency genes and are able to differentiate not only into mesodermal cells, but also into neuroectodermal dopaminergic neuron-like cells.