Ruben Fossion’s research while affiliated with National Autonomous University of Mexico and other places

The autonomic nervous system and the endocrine system regulate cardiovascular physiology, and their alterations, as occurs in type 2 diabetes mellitus, are related to the development of cardiovascular complications. Sex hormones are major regulators of both cardiovascular and nervous tissue, and during postmenopause, the lack in hormone production can increase the risk for cardiovascular and autonomic diseases, even more in metabolic impairment such as in T2DM However, the evidence regarding whether sex hormones are related to autonomic activity is inconclusive. The goal of this paper was to evaluate the correlation between sex hormones and cardiac autonomic activity, as assessed by heart rate variability (HRV), women with well-controlled type 2 diabetes (T2DM) and healthy women as the control group. Subjects and methods In this study, four groups of women were designated according to their health status (control or T2DM) and fertility status (premenopausal or postmenopausal). Five serum sex hormones were measured (estradiol, progesterone, testosterone, LH and FSH), and time-domain and frequency-domain HRV indices were determined during three conditions: supine position, active standing, and rhythmic breathing. For the complete sample (n=118), bivariate Pearson correlations and linear multiple regressions were used to analyze the relationship between sex hormones, HRV indices, and other independent variables, such as glycemia and age. A p-value <0.05 was considered as significant. Results There were no differences in sex hormones or HRV indices when comparing the healthy and T2DM groups. All bivariate Pearson correlations were significant between sex hormones and HRV indices; estradiol, progesterone, and testosterone have positive correlations; meanwhile, LH and FSH were negative in the time-domain (SDNN, RMSSD, pNN20) and frequency domain (PLF and PHF) indices. Regression models adjusted for mean heartbeat intervals confirmed an association between all sex hormones and HRV indices. Estradiol maintained significance in the regression models for specific HRV indices during supine and active standing conditions even after adjusting for age and glucose levels. Conclusions All sex hormones correlate with HRV indices. Regression analysis confirms that this correlation is independent from the mean heartbeat interval. However, in regression models adjusted for age and glucose levels, only estradiol was found to be significant, and should be considered an important variable related to cardiovascular and autonomic balance in T2DM women and may provide crucial information to improve cardiovascular risk algorithms.

Objectives Chronobiology is the science that studies biological rhythms based on direct methods and empirical time series of individual subjects. In laboratory medicine, the factor of time is often underestimated, and no methods currently exist to study biological rhythms in population databases of point-like, real-world data (RWD). Methods Retrospective databases (24 months, 2022–2023) were extracted for four measurands (sodium, potassium, chloride and leukocytes) from the emergency laboratory. Two different strategies for data grouping were applied: data clouds (with or without outliers) and population-averaged profiles. Cosinor regression analysis was performed on the grouped data to derive circadian parameters. The parameters obtained here were compared to results from the literature, using direct methods and time series. Results A total of 409,719 data points were analyzed. All measurands exhibited symmetrical data distributions, except for leukocytes. The data clouds did not visually display rhythmicity, but cosinor analysis revealed a significant circadian rhythm. The removal of outliers had minimal impact on the results. In contrast, population-averaged profiles showed visible rhythmicity, which was confirmed by cosinor analysis with a better goodness-of-fit compared to the data clouds. Conclusions Population-averaged profiles have advantages over data clouds in characterizing circadian rhythms and deriving circadian parameters. Population chronobiology, based on RWD, is presented as an alternative to classical individual chronobiology, based on time series and overcomes the limitations of direct methods. Utilizing RWD provides new insights into the relationship between chronobiology and clinical laboratory practice.

Throughout the early stages of the COVID-19 pandemic in Mexico (August—December 2020), we closely followed a cohort of n = 100 healthcare workers. These workers were initially seronegative for Immunoglobulin G (IgG) antibodies against SARS-CoV-2, the virus that causes COVID-19, and maintained close contact with patients afflicted by the disease. We explored the database of demographic, physiological and laboratory parameters of the cohort recorded at baseline to identify potential risk factors for infection with SARS-CoV-2 at a follow-up evaluation six months later. Given that susceptibility to infection may be a systemic rather than a local property, we hypothesized that a multivariate statistical analysis, such as MANOVA, may be an appropriate statistical approach. Our results indicate that susceptibility to infection with SARS-CoV-2 is modulated by sex. For men, different physiological states appear to exist that predispose to or protect against infection, whereas for women, we did not find evidence for divergent physiological states. Intriguingly, male participants who remained uninfected throughout the six-month observation period, had values for mean arterial pressure and waist-to-hip ratio that exceeded the normative reference range. We hypothesize that certain risk factors that worsen the outcome of COVID-19 disease, such as being overweight or having high blood pressure, may instead offer some protection against infection with SARS-CoV-2.

Medical knowledge and practice are usually structured and implemented by dividing the various organs and systems of the human body. This makes it easier to provide healthcare services and education, and to distribute tasks and responsibilities among different professionals. However, this approach has its limitations, as it overlooks the interactions between different systems that often transcend these divisions. Moreover, it neglects the systemic properties and behavior of the whole organism. Calmecac is a transdisciplinary research group at the National Autonomous University of Mexico (UNAM), founded in 2019, with the goal of enhancing human health by viewing the human body as a complex system. The group carries out innovative research on physiological networks, exploring how human physiological systems and organs are interconnected. To share its main findings with various audiences, Calmecac hired a science communicator who followed a three-step method: 1. A thorough immersion into Calmecac's research, including involvement in experimental activities. 2. The identification and concise explanation of the main concepts and results to be communicated. 3. The integration of three essential elements of discursive strategies (credibility, legitimacy, and attention capture) in the creation of science communication materials: a popular science article and a series of TikTok videos. The next stage of this research will consist of evaluating the effectiveness of these videos in transmitting scientific information using four memory tasks: recall, identify, remember, and contextualize (RIRC Method). The study will also aim to ascertain if the information best remembered by participants matches well with the features related to the three elements of discursive strategies.

Achalasia is a rare esophageal motility disorder for which the etiology is not fully understood. Evidence suggests that autoimmune inflammatory infiltrates, possibly triggered by a viral infection, may lead to a degeneration of neurons within the myenteric plexus. While the infection is eventually resolved, genetically susceptible individuals may still be at risk of developing achalasia. This study aimed to determine whether immunological and physiological networks differ between male and female patients with achalasia. This cross-sectional study included 189 preoperative achalasia patients and 500 healthy blood donor volunteers. Demographic, clinical, laboratory, immunological, and tissue biomarkers were collected. Male and female participants were evaluated separately to determine the role of sex. Correlation matrices were constructed using bivariate relationships to generate complex inferential networks. These matrices were filtered based on their statistical significance to identify the most relevant relationships between variables. Network topology and node centrality were calculated using tools available in the R programming language. Previous occurrences of chickenpox, measles, and mumps infections have been proposed as potential risk factors for achalasia, with a stronger association observed in females. Principal component analysis (PCA) identified IL-22, Th2, and regulatory B lymphocytes as key variables contributing to the disease. The physiological network topology has the potential to inform whether a localized injury or illness is likely to produce systemic consequences and the resulting clinical presentation. Here we show that immunological involvement in achalasia appears localized in men because of their highly modular physiological network. In contrast, in women the disease becomes systemic because of their robust network with a larger number of inter-cluster linkages.

The extraction of circadian cycles from experimental data can be interpreted as a specific case of time-series or signal analysis, but chrono- biology and time-series analysis appear to have developed according to separate paths. Whereas some techniques such as continuous (CWT) and discrete wavelet analysis (DWT) are used frequently in rhythmobiology, other specialized methdos such as digital filters, nonlinear mode decomposition (NMD), singular spectrum analysis (SSA), empirical mode decomposition (EMD), ensemble empirical mode decomposition (EEMD) and complete ensemble empirical model decomposition with adaptive noise (CEEMDAN) have only occasionally been applied. No studies are available that compare the applicability between a wide variety of different methods or for different variables, and this is the purpose of the present contribution. These methods improve the goodness-of-fit of the circadian cycle with respect to the standard approach of cosinor analysis. They have the additional advantage of being able to quantify the day-to-day variability of the circadian parameters of mesor, amplitude, period and acrophase around their average values, with potential clinical applications to distinguish between healthy and unhealthy populations. Finally, the circadian parameters are interpreted within the context of homeostatic regulation with distinctive statistics for regulated and effector variables.

Most gait parameters decrease with age and are even more importantly reduced with frailty. However, other gait parameters exhibit different or even opposite trends for aging and frailty, and the underlying reason is unclear. Literature focuses either on aging, or on frailty, and a comprehensive understanding of how biomechanical gait regulation evolves with aging and with frailty seems to be lacking. We monitored gait dynamics in young adults (19-29 years, n = 27, 59% women), middle-aged adults (30-59 years, n = 16, 62% women), and non-frail (>60 years, n = 15, 33% women) and frail older adults (>60 years, n = 31, 71% women) during a 160 m walking test using the triaxial accelerometer of the Zephyr Bioharness 3.0 device (Zephyr Technology, Annapolis, MD, USA). Frailty was evaluated using the Frail Scale (FS) and the Clinical Frailty Scale (CFS). We found that in non-frail older adults, certain gait parameters, such as cadence, were increased, whereas other parameters, such as step length, were decreased, and gait speed is maintained. Conversely, in frail older adults, all gait parameters, including gait speed, were decreased. Our interpretation is that non-frail older adults compensate for a decreased step length with an increased cadence to maintain a functional gait speed, whereas frail older adults decompensate and consequently walk with a characteristic decreased gait speed. We quantified compensation and decompensation on a continuous scale using ratios of the compensated parameter with respect to the corresponding compensating parameter. Compensation and decompensation are general medical concepts that can be applied and quantified for many, if not all, biomechanical and physiological regulatory mechanisms of the human body. This may allow for a new research strategy to quantify both aging and frailty in a systemic and dynamic way.