Risk factors contributing to infection with SARS-CoV-2 are modulated by sex.

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.

Achalasia alters physiological networks depending on sex.

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.

Physiological Network Is Disrupted in Severe COVID-19.

The human body is a complex system maintained in homeostasis thanks to the interactions between multiple physiological regulation systems. When faced with physical or biological perturbations, this system must react by keeping a balance between adaptability and robustness. The SARS-COV-2 virus infection poses an immune system challenge that tests the organism's homeostatic response. Notably, the elderly and men are particularly vulnerable to severe disease, poor outcomes, and death. Mexico seems to have more infected young men than anywhere else. The goal of this study is to determine the differences in the relationships that link physiological variables that characterize the elderly and men, and those that characterize fatal outcomes in young men. To accomplish this, we examined a database of patients with moderate to severe COVID-19 (471 men and 277 women) registered at the "Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán" in March 2020. The sample was stratified by outcome, age, and sex. Physiological networks were built using 67 physiological variables (vital signs, anthropometric, hematic, biochemical, and tomographic variables) recorded upon hospital admission. Individual variables and system behavior were examined by descriptive statistics, differences between groups, principal component analysis, and network analysis. We show how topological network properties, particularly clustering coefficient, become disrupted in disease. Finally, anthropometric, metabolic, inflammatory, and pulmonary cluster interaction characterize the deceased young male group.

Potential Therapeutic Applications of Synthetic Conotoxin s-cal14.2b, Derived from Californiconus californicus, for Treating Type 2 Diabetes.

The FDA's approval of peptide drugs such as Ziconotide or Exendin for pain relief and diabetes treatment, respectively, enhanced the interest to explore novel conotoxins from Conus species venom. In general, conotoxins can be used in pathologies where voltage-gated channels, membrane receptors, or ligands alter normal physiological functions, as in metabolic diseases such as Type 2 diabetes. In this study, the synthetic cal14.2b (s-cal14.2b) from the unusual Californiconus californicus demonstrated bioactivity on NIT-1 insulinoma cell lines stimulating insulin secretion detecting by high performance liquid chromatography (HPLC). Accordingly, s-cal14.2b increased the CaV1.2/1.3 channel-current by 35 ± 4% with a recovery τ of 10.3 ± 4 s in primary cell culture of rat pancreatic ß-cells. The in vivo results indicated a similar effect of insulin secretion on mice in the glucose tolerance curve model by reducing the glucose from 500 mg/dL to 106 mg/dL in 60 min, compared to the negative control of 325 mg/dL at the same time. The PET-SCAN with radiolabeling 99mTc-s-cal14.2b demonstrated biodistribution and accumulation in rat pancreas with complete depuration in 24 h. These findings show the potential therapeutic use of s-cal14.2b in endocrinal pathologies such as early stages of Type 2 Diabetes where the pancreas's capability to produce insulin is still effective.

Sex Differences in the Physiological Network of Healthy Young Subjects.

Within human physiology, systemic interactions couple physiological variables to maintain homeostasis. These interactions change according to health status and are modified by factors such as age and sex. For several physiological processes, sex-based distinctions in normal physiology are present and defined in isolation. However, new methodologies are indispensable to analyze system-wide properties and interactions with the objective of exploring differences between sexes. Here we propose a new method to construct complex inferential networks from a normalization using the clinical criteria for health of physiological variables, and the correlations between anthropometric and blood tests biomarkers of 198 healthy young participants (117 women, 81 men, from 18 to 27 years old). Physiological networks of men have less correlations, displayed higher modularity, higher small-world index, but were more vulnerable to directed attacks, whereas networks of women were more resilient. The networks of both men and women displayed sex-specific connections that are consistent with the literature. Additionally, we carried out a time-series study on heart rate variability (HRV) using Physionet's Fantasia database. Autocorrelation of HRV, variance, and Poincare's plots, as a measure of variability, are statistically significant higher in young men and statistically significant different from young women. These differences are attenuated in older men and women, that have similar HRV distributions. The network approach revealed differences in the association of variables related to glucose homeostasis, nitrogen balance, kidney function, and fat depots. The clusters of physiological variables and their roles within the network remained similar regardless of sex. Both methodologies show a higher number of associations between variables in the physiological system of women, implying redundant mechanisms of control and simultaneously showing that these systems display less variability in time than those of men, constituting a more resilient system.

Motor learning impairment in rats under a high sucrose diet.

Motor learning skills are reliable indicators of behavioral acquisition and cognitive disorders. The ease with which learning skills are measured disparities the complexity of the interpretation concerning neural plasticity. Conversely, a wealth of information regarding metabolic derangements has long been reported with direct connection to high sucrose diets. However, the impact of excessive sucrose consumption on undergoing cognitive processes has been only scarcely addressed up to now. Therefore, the goal of this work was to describe the associative relationship between high sucrose consumption and changes in motor learning skills acquisition. Motor learning impairments conditioned by central alterations are hypothesized. Rotarod, elevated plus-maze and open field trials, along with metabolic and pro-inflammatory biomarkers tests in Wistar rats under a high sucrose treatment, were performed. Motor learning impairment in high sucrose diet-treated rats was found while spontaneous locomotor activity remained unchanged. Even though, no anxiety-like behavior under high sucrose diet-treatment was observed. Consistently, the worst outcome in the glucose tolerance test was developed, the worst motor learning performance was observed. Furthermore, insulin resistance correlated positively with a pro-inflammatory state and a decreased latency to fall in the rotarod test. Indeed, C-reactive protein and tumor necrosis factor-α serum levels, along with the homeostasis model assessment of insulin resistance (HOMA-IR), significantly increased in motor learning impairment. Together, these results support behavioral, metabolic and pro-inflammatory changes associated with deleterious changes in central nervous system likely involving crucial motor learning structures. Underlying pro-inflammatory-triggered processes may explain cognitive disorders in advanced states of metabolic derangements.

Cannabinoid receptors are differentially regulated in the pancreatic islets during the early development of metabolic syndrome.

The endocannabinoid system is found in tissues that regulate the glycemia, including adipose tissue, muscle, and pancreatic islets. Diet-induced metabolic syndrome changes the expression of the CB receptors in muscle, adipose tissue, and liver. However, it is poorly understood whether metabolic syndrome (MetS) affects the expression of CB receptors in pancreatic ß cells. We analyzed the expression of CB receptors in pancreatic ß cells under chronic high-sucrose diet (HSD)-induced MetS. Wistar rats fed an HSD as a model of MetS were used to investigate changes in cannabinoid receptors. After 8 weeks of treatment, we evaluated the appearance of the following MetS biomarkers: glucose intolerance, hyperinsulinemia, insulin resistance, hypertriglyceridemia, and an increase in visceral adiposity. To determine the presence of CB1 and CB2 receptors in pancreatic ß cells, immunofluorescence of primary cell cultures and pancreatic sections was performed. For whole-islet quantification of membrane-bound CB1 and CB2 receptors, western-blotting following differential centrifugation was conducted. Our results revealed that an HSD treatment closely mimics the alterations seen in MetS. We observed that in primary cell culture, CB1 and CB2 receptors were expressed at a higher level in pancreatic ß cells compared with non-ß cells. MetS resulted in a reduction of CB1 in the islet, whereas abundant CB2 was observed after the treatment. CB1 and CB2 receptors are differentially expressed in pancreatic ß cells during MetS development.

Diurnal Variation Induces Neurobehavioral and Neuropathological Differences in a Rat Model of Traumatic Brain Injury.

Traumatic brain injury (TBI) induces two types of brain damage: primary and secondary. Damage initiates a series of pathophysiological processes, such as metabolic crisis, excitotoxicity with oxidative stress-induced damage, and neuroinflammation. The long-term perpetuation of these processes has deleterious consequences for neuronal function. However, it remains to be elucidated further whether physiological variation in the brain microenvironment, depending on diurnal variations, influences the damage, and consequently, exerts a neuroprotective effect. Here, we established an experimental rat model of TBI and evaluated the effects of TBI induced at two different time points of the light-dark cycle. Behavioral responses were assessed using a 21-point neurobehavioral scale and the cylinder test. Morphological damage was assessed in different regions of the central nervous system. We found that rats that experienced a TBI during the dark hours had better behavioral performance than those injured during the light hours. Differences in behavioral performance correlated with less morphological damage in the perilesional zone. Moreover, certain brain areas (CA1 and dentate gyrus subregions of the hippocampus) were less prone to damage in rats that experienced a TBI during the dark hours. Our results suggest that diurnal variation is a crucial determinant of TBI outcome, and the hour of the day at which an injury occurs should be considered for future research.

Metabolic Physiological Networks: The Impact of Age.

Metabolic homeostasis emerges from the interplay between several feedback systems that regulate the physiological variables related to energy expenditure and energy availability, maintaining them within a certain range. Although it is well known how each individual physiological system functions, there is little research focused on how the integration and adjustment of multiple systems results in the generation of metabolic health. The aim here was to generate an integrative model of metabolism, seen as a physiological network, and study how it changes across the human lifespan. We used data from a transverse, community-based study of an ethnically and educationally diverse sample of 2572 adults. Each participant answered an extensive questionnaire and underwent anthropometric measurements (height, weight, and waist), fasting blood tests (glucose, HbA1c, basal insulin, cholesterol HDL, LDL, triglycerides, uric acid, urea, and creatinine), along with vital signs (axillar temperature, systolic, and diastolic blood pressure). The sample was divided into 6 groups of increasing age, beginning with less than 25 years and increasing by decades up to more than 65 years. In order to model metabolic homeostasis as a network, we used these 15 physiological variables as nodes and modeled the links between them, either as a continuous association of those variables, or as a dichotomic association of their corresponding pathological states. Weight and overweight emerged as the most influential nodes in both types of networks, while high betweenness parameters, such as triglycerides, uric acid and insulin, were shown to act as gatekeepers between the affected physiological systems. As age increases, the loss of metabolic homeostasis is revealed by changes in the network's topology that reflect changes in the system-wide interactions that, in turn, expose underlying health stages. Hence, specific structural properties of the network, such as weighted transitivity, i.e., the density of triangles in the network, can provide topological indicators of health that assess the whole state of the system. Overall, our findings show the importance of visualizing health as a network of organs and/or systems, and highlight the importance of triglycerides, insulin, uric acid and glucose as key biomarkers in the prevention of the development of metabolic disorders.

The Impact of Education and Age on Metabolic Disorders.

Metabolic disorders, such as obesity, elevated blood pressure, dyslipidemias, insulin resistance, hyperglycemia, and hyperuricemia have all been identified as risk factors for an epidemic of important and widespread chronic-degenerative diseases, such as type 2 diabetes and cardiovascular disease, that constitute some of the world's most important public health challenges. Their increasing prevalence can be associated with an aging population and to lifestyles within an obesogenic environment. Taking educational level as a proxy for lifestyle, and using both logistic and linear regressions, we study the relation between a wide set of metabolic biomarkers, and educational level, body mass index (BMI), age, and sex as correlates, in a population of 1,073 students, academic and non-academic staff at Mexico's largest university (UNAM). Controlling for BMI and sex, we consider educational level and age as complementary measures-degree and duration-of exposure to metabolic insults. Analyzing the role of education across a wide spectrum of educational levels (from primary school to doctoral degree), we show that higher education correlates to significantly better metabolic health when compared to lower levels, and is associated with significantly less risk for waist circumference, systolic blood pressure, glucose, glycosylated hemoglobin, triglycerides, high density lipoprotein and metabolic syndrome (all p < 0.05); but not for diastolic blood pressure, basal insulin, uric acid, low density lipoprotein, and total cholesterol. We classify each biomarker, and corresponding metabolic disorder, by its associated set of statistically significant correlates. Differences among the sets of significant correlates indicate various aetiologies and the need for targeted population-specific interventions. Thus, variables strongly linked to educational level are candidates for lifestyle change interventions. Hence, public policy efforts should be focused on those metabolic biomarkers strongly linked to education, while adopting a different approach for those biomarkers not linked as they may be poor targets for educational campaigns.

Physiological Network From Anthropometric and Blood Test Biomarkers.

Currently, research in physiology focuses on molecular mechanisms underlying the functioning of living organisms. Reductionist strategies are used to decompose systems into their components and to measure changes of physiological variables between experimental conditions. However, how these isolated physiological variables translate into the emergence -and collapse- of biological functions of the organism as a whole is often a less tractable question. To generate a useful representation of physiology as a system, known and unknown interactions between heterogeneous physiological components must be taken into account. In this work we use a Complex Inference Networks approach to build physiological networks from biomarkers. We employ two unrelated databases to generate Spearman correlation matrices of 81 and 54 physiological variables, respectively, including endocrine, mechanic, biochemical, anthropometric, physiological, and cellular variables. From these correlation matrices we generated physiological networks by selecting a p-value threshold indicating statistically significant links. We compared the networks from both samples to show which features are robust and representative for physiology in health. We found that although network topology is sensitive to the p-value threshold, an optimal value may be defined by combining criteria of stability of topological features and network connectedness. Unsupervised community detection algorithms allowed to obtain functional clusters that correlate well with current medical knowledge. Finally, we describe the topology of the physiological networks, which lie between random and ordered structural features, and may reflect system robustness and adaptability. Modularity of physiological networks allows to explore functional clusters that are consistent even when considering different physiological variables. Altogether Complex Inference Networks from biomarkers provide an efficient implementation of a systems biology approach that is visually understandable and robust. We hypothesize that physiological networks allow to translate concepts such as homeostasis into quantifiable properties of biological systems useful for determination and quantification of health and disease.

Neuroinflamación: el ying-yang de la neuroinmunología / Neuroinflammation: the ying-yang of neuroimmunology

Resumen El área de la neuroinmunología es un campo que se encuentra en gran desarrollo y que tiene como objetivo el entender las interacciones fisiológicas entre el sistema nervioso central (SNC) y el sistema inmune periférico, llegándose a encontrar que estas relaciones son más importantes de lo que se creía y que por lo tanto son 2 sistemas íntimamente conectados y con una gran dinámica. Por otro lado, la neuroinflamación es activada después de cualquier reto inmunológico, tanto dentro como fuera del SNC, y que puede llevar a generar tanto respuestas enfocadas a la limitación del daño y la restauración del tejido, como a ser un riesgo para el desarrollo de enfermedades neurodegenerativas en el caso de que este estímulo permanezca de manera crónica.

Abstract The field of neuroimmunology has recently had a development, and its primary goal is to understand the physiological interactions between the central nervous system (CNS) and the peripheral immune system. Various data has found that these relations are more important than what was previously thought. Also, that both systems are highly dynamic and are intimately connected. On the other hand, neuroinflammation is activated after any immune challenge, both inside and outside the CNS, leading to responses focused on limiting tissue damage and restoration; as well as being a risk for developing neurodegenerative diseases when this stimulus remains chronic.