Cesare Celeste Berra

Background: Anemia is a widespread global health issue. Hemoglobin (Hb) concentration measurement remains the most common method for anemia screening and diagnosis. In recent years, there has been growing interest in the development of noninvasive point-of-care technologies that eliminate the need for blood sampling. Objective: This pilot study explores the feasibility of using a noncontact photoplethysmography–based mobile app for Hb monitoring. Methods: Adult volunteers aged 18 years and older, of both sexes, were consecutively recruited. Participants were seated and allowed a 2-minute rest before measurements. During testing, they faced a smartphone running comestai.app , which used the front-facing camera to capture facial videos. Simultaneous readings were collected for Hb over approximately 90 seconds using the app. Ambient lighting was standardized for all remote photoplethysmography recordings. No medical decisions were made based on the app-generated data. A complete blood count, including Hb levels, was used as a reference for comparison with the data collected using comestai.app. Results: A total of 555 (female: n=313, 56.4%; male: n=242, 43.6%) individuals participated in the study. The app achieved a mean absolute error of 1.46, a mean absolute percentage error of 11.26, a mean error of −0.67, and a root mean square error of 1.88. The Bland-Altman plot evaluated the agreement between the app-based and laboratory-based Hb measurements, with the mean difference between the 2 methods being −0.70 g/dL. The method demonstrated an overall accuracy of 75%. The area under the curve was 0.701 (95% CI 0.655-0.745). Conclusions: Comestai.app offers an innovative approach to wellness monitoring by providing noninvasive Hb estimation using the smartphone’s front-facing camera. Continued development, including algorithmic refinement and larger-scale validation in diverse populations, will be key to enhancing accuracy and broadening its utility. By leveraging the ubiquity of smartphones, comestai.app contributes meaningfully to the democratization of health monitoring and the promotion of proactive self-care.

Type 2 diabetes mellitus (T2D) and cardiovascular disease (CVD) are not merely coexisting epidemics but co-evolving manifestations of a shared cardiometabolic continuum. Despite advances in glycemic, lipid, and blood pressure control, residual cardiovascular risk remains high, underscoring the limitations of siloed approaches. In this perspective, we argue for reframing T2D and CVD as interconnected conditions driven by inflammation, adipose tissue dysfunction, and organ crosstalk. Beyond metformin, which remains foundational, several glucose-lowering drug classes are now evaluated not only for glycemic control but also for their cardiovascular and renal impact. Landmark trials and recent meta-analyses confirm that sodium-glucose co-transporter 2 inhibitors and glucagon-like peptide-1 (GLP-1) receptor agonists improve cardiorenal outcomes. More recently, tirzepatide, a dual glucose-dependent insulinotropic polypeptide (GIP)/GLP-1 receptor agonist, has shown unprecedented efficacy in weight and glucose management, with potential to further transform cardiometabolic risk reduction. Yet enthusiasm for these therapies must be tempered by heterogeneity of response, treatment costs, and inequitable access. Integrated care models, supported by multidisciplinary teams, digital health tools, and value-based reimbursement, are essential to close the gap between trial efficacy and real-world outcomes. Attention to sex, age, ethnicity, and comorbidity profiles is critical to ensure equity, as is the adaptation of strategies to low- and middle-income countries where the burden of cardiometabolic disease is rapidly rising. Ultimately, advancing cardiometabolic medicine requires not only novel therapies but also a unifying framework that integrates biology, behavior, economics, and health systems to deliver the right treatment to the right patient at the right time.

Background/Objectives: Weight loss interventions in individuals with overweight or obesity result in reductions in both fat mass and lean body mass (LBM). While fat loss is the primary therapeutic target, preserving LBM may have favorable health implications. This narrative review evaluates the role of amino acid supplementation, including essential amino acids (EAAs) and branched-chain amino acids (BCAAs), in supporting the preservation of LBM during weight loss induced by lifestyle interventions, pharmacotherapy, or bariatric surgery. Methods: This is a narrative review of preclinical and clinical studies examining the effects of amino acid supplementation during calorie restriction on body composition and, when available, functional outcomes. A comprehensive search was conducted in the PubMed, Scopus, and Web of Science databases. Results: Evidence suggests that EAA and peptide-based supplementation may help preserve LBM during periods of reduced energy intake, particularly when protein intake from whole foods is limited. Benefits appear more consistent when supplementation is combined with resistance exercise. BCAA supplementation alone has shown variable effects, especially in sedentary individuals or when total protein intake is already sufficient. Anabolic resistance associated with obesity may attenuate the muscle protein synthesis response to dietary amino acids. Conclusions: Amino acid supplementation may support the maintenance of LBM during weight loss, particularly under conditions of low protein intake or in conjunction with exercise. Further research is needed to determine the clinical significance of LBM changes and identify optimal supplementation strategies.

BACKGROUND Anemia is a widespread global health issue. Hemoglobin (Hb) concentration measurement remains the most common method for anemia screening and diagnosis. In recent years, there has been growing interest in the development of non-invasive point of care technologies that eliminate the need for blood sampling. OBJECTIVE This study explores the feasibility of using a non-contact, PPG-based mobile application for Hb monitoring. METHODS Adult volunteers aged 18 years and older, of both sexes, were consecutively recruited. Data acquisition using remote photoplethysmography (rPPG) was performed by recording participants’ facial images via the front camera of mobile devices for roughly 90 seconds. A complete blood count, including Hb levels, was used as a reference for comparison with the data collected using the comestai application RESULTS A total of 555 individuals (313 F/ 242 M) participated in the study. The app achieved a MAE of 1.46, MAPE of 11.26, with a ME of -0.67 and RMSE of 1.88. The Bland-Altman plot in evaluated the agreement between the app-based and laboratory-based Hb measurements, with the mean difference between the two methods being -0.70 g/dL. The method demonstrated an overall accuracy of 75.0%. CONCLUSIONS The comestai.app mobile application offers an innovative approach to wellness monitoring by providing non-invasive Hb estimation using the smartphone’s front-facing camera. Continued development, including algorithmic refinement and larger-scale validation in diverse populations, will be key to enhancing accuracy and broadening its utility. By leveraging the ubiquity of smartphones, comestai.app contributes meaningfully to the democratization of health monitoring and the promotion of proactive self-care. CLINICALTRIAL ClinicalTrials.gov (ID: NCT06427564)

Background: Early detection of vital sign changes is key to recognizing patient deterioration promptly, enabling timely interventions and potentially preventing adverse outcomes. Objective: In this study, vital parameters (heart rate, respiratory rate, oxygen saturation, and blood pressure) will be measured using the Comestai app to confirm the accuracy of photoplethysmography methods compared to standard clinical practice devices, analyzing a large and diverse population. In addition, the app will facilitate big data collection to enhance the algorithm’s performance in measuring hemoglobin, glycated hemoglobin, and total cholesterol. Methods: A total of 3000 participants will be consecutively enrolled to achieve the objectives of this study. In all patients, personal data, medical condition, and treatment overview will be recorded. The “by face” method for remote photoplethysmography vital sign data collection involves recording participants’ faces using the front camera of a mobile device (iOS or Android) for approximately 1.5 minutes. Simultaneously, vital signs will be continuously collected for about 1.5 minutes using the reference devices alongside data collected via the Comestai app; biochemical results will also be recorded. The accuracy of the app measurements compared to the reference devices and standard tests will be assessed for all parameters. CIs will be calculated using the bootstrap method. The proposed approach’s effectiveness will be evaluated using various quality criteria, including the mean error, SD, mean absolute error, root mean square error, and mean absolute percentage error. The correlation between measurements obtained using the app and reference devices and standard tests will be evaluated using the Pearson correlation coefficient. Agreement between pairs of measurements (app vs reference devices and standard tests) will be represented using Bland-Altman plots. Sensitivity, specificity, positive predictive value, negative predictive value, accuracy, and likelihood ratios will be calculated to determine the ability of the new app to accurately measure vital signs. Results: Data collection began in June 2024. As of March 25, 2025, we have recruited 1200 participants. The outcomes of the study are expected at the end of 2025. The analysis plan involves verifying and validating the parameters collected from mobile devices via the app, reference devices, and prescheduled blood tests, along with patient demographic data. Conclusions: Our study will enhance and support the accuracy of data on vital sign detection through PPG, also introducing measurements of biochemical risk indicators. The evaluation of a large population will allow for continuous improvement in the performance and accuracy of artificial intelligence algorithms, reducing errors. Expanding research on mobile health solutions like Comestai can support preventive care by validating their effectiveness as screening tools and guiding future health care technology developments. Trial Registration: ClinicalTrials.gov NCT06427564; https://clinicaltrials.gov/study/NCT06427564

Low-grade inflammation (LGI) represents a key driver of type 2 diabetes (T2D) and its associated cardiovascular diseases (CVDs). Indeed, inflammatory markers such as hs-CRP and IL-6 predict the development of T2D and its complications, suggesting that LGI already increases before T2D diagnosis and remains elevated even after treatment. Overnutrition, unhealthy diets, physical inactivity, obesity, and aging are all recognized triggers of LGI, promoting insulin resistance and sustaining the pathogenesis of T2D. Once developed, and even before frank appearance, people with T2D undergo a pathological metabolic remodeling, with an alteration of multiple CVD risk factors, i.e., glycemia, lipids, blood pressure, and renal function. In turn, such variables foster a range of inflammatory pathways and mechanisms, e.g., immune cell stimulation, the accrual of senescent cells, long-lasting epigenetic changes, and trained immunity, which are held to chronically fuel LGI at the systemic and tissue levels. Targeting of CVD risk factors partially ameliorates LGI. However, some long-lasting inflammatory pathways are unaffected by common therapies, and LGI burden is still increased in many T2D patients, a phenomenon possibly underlying the residual inflammatory risk (i.e., having hs-CRP > 2 mg/dL despite optimal LDL cholesterol control). On the other hand, selected disease-modifying drugs, e.g., GLP-1RA, seem to also act on the pathogenesis of T2D, curbing the inflammatory trajectory of the disease and possibly preventing it if introduced early. In addition, selected trials demonstrated the potential of canonical anti-inflammatory therapies in reducing the rate of CVDs in patients with this condition or at high risk for it, many of whom had T2D. Since colchicine, an inhibitor of immune cell activation, is now approved for the prevention of CVDs, it might be worth exploring a possible therapeutic paradigm to identify subjects with T2D and an increased LGI burden to treat them with this drug. Upcoming studies will reveal whether disease-modifying drugs reverse early T2D by suppressing sources of LGI and whether colchicine has a broad benefit in people with this condition.