Innova4Health: an integrated approach for prevention of recurrence and personalized treatment of Major Depressive Disorder.

Background: Major Depressive Disorder (MDD) is a prevalent mental health condition characterized by persistent low mood, cognitive and physical symptoms, anhedonia (loss of interest in activities), and suicidal ideation. The World Health Organization (WHO) predicts depression will become the leading cause of disability by 2030. While biological markers remain essential for understanding MDD's pathophysiology, recent advancements in social signal processing and environmental monitoring hold promise. Wearable technologies, including smartwatches and air purifiers with environmental sensors, can generate valuable digital biomarkers for depression assessment in real-world settings. Integrating these with existing physical, psychopathological, and other indices (autoimmune, inflammatory, neuroradiological) has the potential to improve MDD recurrence prevention strategies. Methods: This prospective, randomized, interventional, and non-pharmacological integrated study aims to evaluate digital and environmental biomarkers in adolescents and young adults diagnosed with MDD who are currently taking medication. The study implements a sensor-integrated platform built around an open-source "Pothos" air purifier system. This platform is designed for scalability and integration with third-party devices. It accomplishes this through software interfaces, a dedicated app, sensor signal pre-processing, and an embedded deep learning AI system. The study will enroll two experimental groups (10 adolescents and 30 young adults each). Within each group, participants will be randomly allocated to Group A or Group B. Only Group B will receive the technological equipment (Pothos system and smartwatch) for collecting digital biomarkers. Blood and saliva samples will be collected at baseline (T0) and endpoint (T1) to assess inflammatory markers and cortisol levels. Results: Following initial age-based stratification, the sample will undergo detailed classification at the 6-month follow-up based on remission status. Digital and environmental biomarker data will be analyzed to explore intricate relationships between these markers, depression symptoms, disease progression, and early signs of illness. Conclusion: This study seeks to validate an AI tool for enhancing early MDD clinical management, implement an AI solution for continuous data processing, and establish an AI infrastructure for managing healthcare Big Data. Integrating innovative psychophysical assessment tools into clinical practice holds significant promise for improving diagnostic accuracy and developing more specific digital devices for comprehensive mental health evaluation.

A narrative review of digital biomarkers in the management of major depressive disorder and treatment-resistant forms.

Introduction: Depression is the leading cause of worldwide disability, until now only 3% of patients with major depressive disorder (MDD) experiences full recovery or remission. Different studies have tried to better understand MDD pathophysiology and its resistant forms (TRD), focusing on the identification of candidate biomarkers that would be able to reflect the patients' state and the effects of therapy. Development of digital technologies can generate useful digital biomarkers in a real-world setting. This review aims to focus on the use of digital technologies measuring symptom severity and predicting treatment outcomes for individuals with mood disorders. Methods: Two databases (PubMed and APA PsycINFO) were searched to retrieve papers published from January 1, 2013, to July 30, 2023, on the use of digital devices in persons with MDD. All papers had to meet specific inclusion criteria, which resulted in the inclusion of 12 articles. Results: Research on digital biomarkers confronts four core aspects: (I) predicting diagnostic status, (II) assessing symptom severity and progression, (III) identifying treatment response and (IV) monitoring real-word and ecological validity. Different wearable technologies have been applied to collect physiological, activity/sleep, or subjective data to explore their relationships with depression. Discussion: Depression's stable rates and high relapse risk necessitate innovative approaches. Wearable devices hold promise for continuous monitoring and data collection in real world setting. Conclusion: More studies are needed to translate these digital biomarkers into actionable interventions to improve depression diagnosis, monitoring and management. Future challenges will be the applications of wearable devices routinely in personalized medicine.

Platelet Inhibition with Ticagrelor 60 mg Versus 90 mg Twice Daily in Elderly Patients with Acute Coronary Syndrome: Rationale and Design of the PLINY THE ELDER Trial.

BACKGROUND: Elderly status is steadily increasing among patients with acute coronary syndrome (ACS). Dual antiplatelet therapy (DAPT) with aspirin and a potent P2Y12 receptor inhibitor is the cornerstone of treatment to prevent recurrent thrombotic complications in patients with ACS. However, DAPT in older patients is challenged by a concurrent heightened risk of ischemia and bleeding. The aim of this study is to evaluate the pharmacodynamic and pharmacokinetic profile of a lower dose of ticagrelor (60 mg twice daily) among elderly patients during the early phase of ACS. STUDY DESIGN: PLINY THE ELDER (PLatelet INhibition with two different doses of potent P2y12 inhibitors in THE ELDERly population) (NCT04739384) is a prospective, randomized, open-label, crossover trial to evaluate the non-inferiority of a lower dose of ticagrelor (60 mg twice daily) compared with a standard dose (90 mg twice daily) among elderly patients with ACS undergoing percutaneous coronary intervention (PCI). A total of 50 patients, aged 75 years or more, with indication to potent P2Y12 receptor inhibitors will be randomized within 3 days from PCI for the index ACS. Patients with indication to oral anticoagulant therapy, treatment with glycoprotein IIb/IIIa inhibitors, or active bleeding will be excluded. The primary endpoint is platelet reactivity determined by P2Y12 reaction units (PRU) (VerifyNow, Accumetrics, San Diego, CA, USA) after treatment with ticagrelor 60 or 90 mg twice daily for 14 days. Secondary endpoints will include other pharmacodynamic tests of ADP-induced aggregation (light transmittance aggregometry and multiple electrode aggregometry) and determination of pharmacokinetic profile (plasma levels of ticagrelor and its metabolite AR-C124910XX) by high performance liquid chromatography-tandem mass spectrometry. CONCLUSIONS: The PLINY THE ELDER trial will determine whether a lower dose of ticagrelor confers non-inferior platelet inhibition compared with the standard dose in the early phase of ACS among elderly patients undergoing PCI, informing future clinical investigation.

Site-Directed Chemical Probing to map transient RNA/protein interactions.

RNA-protein interactions are at the bases of many biological processes, forming either tight and stable functional ribonucleoprotein (RNP) complexes (i.e. the ribosome) or transitory ones, such as the complexes involving RNA chaperone proteins. To localize the sites where a protein interacts on an RNA molecule, a common simple and inexpensive biochemical method is the footprinting technique. The protein leaves its footprint on the RNA acting as a shield to protect the regions of interaction from chemical modification or cleavages obtained with chemical or enzymatic nucleases. This method has proven its efficiency to study in vitro the organization of stable RNA-protein complexes. Nevertheless, when the protein binds the RNA very dynamically, with high off-rates, protections are very often difficult to observe. For the analysis of these transient complexes, we describe an alternative strategy adapted from the Site Directed Chemical Probing (SDCP) approach and we compare it with classical footprinting. SDCP relies on the modification of the RNA binding protein to tether an RNA probe (usually Fe-EDTA) to specific protein positions. Local cleavages on the regions of interaction can be used to localize the protein and position its domains on the RNA molecule. This method has been used in the past to monitor stable complexes; we provide here a detailed protocol and a practical example of its application to the study of Escherichia coli RNA chaperone protein S1 and its transitory complexes with mRNAs.