USSR Space Life Sciences Digest, issue 6

This is the sixth issue of NASA's USSR Space Life Sciences Digest. It contains abstracts of 54 papers recently published in Russian language periodicals and bound collections and of 10 new Soviet monographs. Selected abstracts are illustrated with figures and tables from the original. Additional features include a table of Soviet EVAs and information about English translations of Soviet materials available to readers. The topics covered in this issue have been identified as relevant to 26 areas of aerospace medicine and space biology. These areas are adaptation, biospherics, body fluids, botany, cardiovascular and respiratory systems, developmental biology, endocrinology, enzymology, exobiology, genetics, habitability and environment effects, health and medical treatment, hematology, human performance, immunology, life support systems, mathematical modeling, metabolism., microbiology, morphology and cytology, musculoskeletal system, neurophysiology, nutrition, perception, personnel selection, psychology, radiobiology, reproductive biology, and space medicine

Stress monitoring using wearable sensors:a pilot study and stress-predict dataset

With the recent advancements in the field of wearable technologies, the opportunity to monitor stress continuously using different physiological variables has gained significant interest. The early detection of stress can help improve healthcare and minimizes the negative impact of long-term stress. This paper reports outcomes of a pilot study and associated stress-monitoring dataset, named the “Stress-Predict Dataset”, created by collecting physiological signals from healthy subjects using wrist-worn watches with a photoplethysmogram (PPG) sensor. While wearing these watches, 35 healthy volunteers underwent a series of tasks (i.e., Stroop color test, Trier Social Stress Test and Hyperventilation Provocation Test), along with a rest period in-between each task. They also answered questionnaires designed to induce stress levels compatible with daily life. The changes in the blood volume pulse (BVP) and heart rate were recorded by the watch and were labelled as occurring during stress-inducing tasks or a rest period (no stress). Additionally, respiratory rate was estimated using the BVP signal. Statistical models and personalised adaptive reference ranges were used to determine the utility of the proposed stressors and the extracted variables (heart rate and respiratory rate). The analysis showed that the interview session was the most significant stress stimulus, causing a significant variation in heart rate of 27 (77%) participants and respiratory rate of 28 (80%) participants out of 35. The outcomes of this study contribute to the understanding the role of stressors and their association with physiological response and provide a dataset to help develop new wearable solutions for more reliable, valid, and sensitive physio-logical stress monitoring

Multiple stressors effects on community stability

Las actividades antropogénicas ejercen una presión constante sobre los sistemas naturales, amenazando la diversidad, la estabilidad y el funcionamiento de estos en todo el planeta. Además, existe un gran número de factores de estrés antropogénico, como son la eutrofización, la contaminación química y los eventos extremos, que actúan de manera simultánea. En esta tesis se evalúan e implementan nuevos enfoques para comprender los efectos individuales y combinados de los factores de estrés antropogénico sobre la estabilidad de las comunidades y ecosistemas de agua dulce. Esto se hace, en un primer lugar, revisando la literatura disponible sobre los efectos combinados de las olas de calor y los contaminantes químicos, destacando los vacíos de conocimiento y sugiriendo formas eficientes de integrar los eventos extremos en la evaluación del impacto ambiental de los factores de estrés múltiple. Esta tesis se basa también en grandes experimentos de mesocosmos al aire libre para investigar los efectos de los factores de estrés múltiple sobre las comunidades y ecosistemas dulceacuícolas. En estos trabajos se analizan los efectos de tres estresores agrícolas (dos pesticidas y la contaminación por nutrientes) a nivel de población, comunidad y ecosistema, y se estudian sus impactos sobre la estabilidad del ecosistema y la dimensionalidad entre los parámetros que describen dicha estabilidad. Además, se explora el potencial de las redes tróficas para dilucidar los mecanismos que impulsan la disimilitud composicional de las comunidades acuáticas después de la aplicación de una perturbación puntual, y se evalúan los mecanismos que influyen en la aparición de interacciones entre los factores de estrés en el largo plazo. Finalmente, este trabajo analiza los efectos de los eventos extremos, como las olas de calor, sobre la complejidad de los ecosistemas de agua dulce utilizando métricas topológicas y cuantitativas de redes tróficas. En ese sentido, los cambios en la complejidad de la red trófica fueron vinculados con los cuatro componentes que definen la estabilidad del sistema, y que caracterizan la estabilidad funcional, estructural y de los flujos de energía entre las especies que forman la red trófica. En general, esta tesis propone un enfoque general para dilucidar los efectos del cambio global sobre la estabilidad de los ecosistemas, brindando información útil para preservar la estructura y funcionalidad de éstos en condiciones ambientales cambiantes

ACUTE MENTAL STRESS AND ARTERIAL STIFFNESS: A COMPARISON BETWEEN HISPANIC AND NONHISPANIC WHITE ADULTS

Hispanics face a disproportionate burden of cardiovascular disease (CVD) risk factors, includingmental stress, when compared to non-Hispanic white adults (NHWA). However, the mechanismsunderlying these disparities are not fully understood. This study aimed to investigate the cardiovascularresponse to acute mental stress in Hispanic and NHWA. The randomized crossover design included sixparticipants (all female; four Hispanics) and assessed arterial stiffness using pulse wave velocity as theprimary outcome measure. Hispanics exhibited the greatest increase in PWV during the controlcondition, while NHW individuals showed the greatest increase during the experimental condition. Statestress measures also demonstrated significant differences before and after both test conditions. Thesefindings suggest a counterintuitive cardiovascular response to acute stress in Hispanic adults whencompared to NHWA. This study highlights the need for further research to understand the complexrelationship between mental stress and cardiovascular risk in different populations, in particular,Hispanic adults.Master of Art

Aerospace medicine and biology. A continuing bibliography (supplement 231)

This bibliography lists 284 reports, articles, and other documents introduced into the NASA scientific and technical information system in March 1982

Sex Differences in Measures of Wave Reflection and Aortic Arterial Stiffness in Response to Weight Machine Resistance Exercise

International Journal of Exercise Science 15(2): 1190-1201, 2022. While it has been demonstrated that acute resistance exercise (RE) alters measures of wave reflection and aortic arterial stiffness in young, healthy individuals, limited research has evaluated sex differences. Accordingly, we recruited moderately active, resistance-trained men (Age: 22 ± 3yrs, n=12) and women (23 ± 3yrs, n=10) to perform two randomized conditions consisting of an acute bout of weight machine RE or a quiet control (CON). Measures of aortic wave reflection and aortic stiffness were taken at baseline and 15 minutes following the RE (Recovery). At baseline, women had significantly higher heart rate (p = 0.05) and lower brachial systolic blood pressure (p = 0.009) compared to men. There were no significant three-way interactions for any variable. Significant condition by time interactions were noted for heart rate (Baseline: 65 ± 10bpm, Recovery: 87 ± 13bpm, p = 0.001), brachial systolic blood pressure (Baseline: 116 ± 9mmHg, Recovery: 123 ± 10mmHg, p = 0.014), and the augmentation index (AIx) normalized at 75bpm (Baseline: 7.7 ± 12.8%, Recovery: 15.5 ± 9.5%, p = 0.002) such that Recovery was augmented compared to Baseline following RE but not CON. There was also a significant main effect of time for augmentation pressure (Baseline: 4.1 ± 4.0mmHg, Recovery: 4.0 ± 3.6mmHg, p = 0.04) such that it decreased from Baseline to Recovery following RE but not the CON. There were no significant effects of sex, condition, or time on aortic arterial stiffness. Men and women have similar responses in measures of aortic wave reflection and aortic arterial stiffness following acute RE using weight machines

Autonomic nervous system biomarkers from multi-modal and model-based signal processing in mental health and illness

Esta tesis se centra en técnicas de procesado multimodal y basado en modelos de señales para derivar parámetros fisiológicos, es decir, biomarcadores, relacionados con el sistema nervioso autónomo (ANS). El desarrollo de nuevos métodos para derivar biomarcadores de ANS no invasivos en la salud y la enfermedad mental ofrece la posibilidad de mejorar la evaluación del estrés y la monitorización de la depresión. Para este fin, el presente documento se estructura en tres partes principales. En la Parte I, se proporciona unaintroducción a la salud y la enfermedad mental (Cap. 1). Además, se presenta un marco teórico para investigar la etiología de los trastornos mentales y el papel del estrés en la enfermedad mental (Cap. 2). También se destaca la importancia de los biomarcadores no invasivos para la evaluación del ANS, prestando especial atención en la depresión clínica (Cap. 3, 4). En la Parte II, se proporciona el marco metodológico para derivar biomarcadores del ANS. Las técnicas de procesado de señales incluyen el análisis conjunto de la variabilidad del rítmo cardíaco (HRV) y la señal respiratoria (Cap. 6), técnicas novedosas para derivar la señal respiratoria del electrocardiograma (ECG) (Cap. 7) y un análisis robusto que se basa en modelar la forma de ondas del pulso del fotopletismograma (PPG) (Ch. 8). En la Parte III, los biomarcadores del ANS se evalúan en la quantificacióndel estrés (Cap. 9) y en la monitorización de la depresión (Ch. 10).Parte I: La salud mental no solo está relacionada con ese estado positivo de bienestar, en el que un individuo puede enfrentar a las situaciones estresantes de la vida, sino también con la ausencia de enfermedad mental. La enfermedad o trastorno mental se puede definir como un trastorno emocional, cognitivo o conductual que causa un deterioro funcional sustancial en una o más actividades importantes de la vida. Los trastornos mentales más comunes, que muchas veces coexisten, son la ansiedad y el trastorno depresivo mayor (MDD). La enfermedad mental tiene un impacto negativo en la calidad de vida, ya que se asocia con pérdidas considerables en la salud y el funcionamiento, y aumenta ignificativamente el riesgo de una persona de padecer enfermedades ardiovasculares.Un instigador común que subyace a la comorbilidad entre el MDD, la patologíacardiovascular y la ansiedad es el estrés mental. El estrés es común en nuestra vida de rítmo rapido e influye en nuestra salud mental. A corto plazo, ANS controla la respuesta cardiovascular a estímulos estresantes. La regulación de parámetros fisiológicos, como el rítmo cardíaco, la frecuencia respiratoria y la presión arterial, permite que el organismo responda a cambios repentinos en el entorno. Sin embargo, la adaptación fisiológica a un fenómeno ambiental que ocurre regularmente altera los sistemas biológicos involucrados en la respuesta al estrés. Las alteraciones neurobiológicas en el cerebro pueden alterar lafunción del ANS. La disfunción del ANS y los cambios cerebrales estructurales tienen un impacto negativo en los procesos cognitivos, emocionales y conductuales, lo que conduce al desarrollo de una enfermedad mental.Parte II: El desarrollo de métodos novedosos para derivar biomarcadores del ANS no invasivos ofrece la posibilidad de mejorar la evaluacón del estrés en individuos sanos y la disfunción del ANS en pacientes con MDD. El análisis conjunto de varias bioseñales (enfoquemultimodal) permite la cuantificación de interacciones entre sistemas biológicos asociados con ANS, mientras que el modelado de bioseãles y el análisis posterior de los parámetros del modelo (enfoque basado en modelos) permite la cuantificación robusta de cambios en mecanismos fisiológicos relacionados con el ANS. Un método novedoso, quetiene en cuenta los fenómenos de acoplo de fase y frecuencia entre la respiración y las señales de HRV para evaluar el acoplo cardiorrespiratorio no lineal cuadrático se propone en el Cap. 6.3. En el Cap. 7 se proponen nuevas técnicas paramejorar lamonitorización de la respiración. En el Cap. 8, para aumentar la robustez de algunas medidas morfológicas que reflejan cambios en el tonno arterial, se considera el modelado del pulso PPG como una onda principal superpuesta con varias ondas reflejadas.Parte III: Los biomarcadores del ANS se evalúan en la cuantificación de diferentes tipos de estrés, ya sea fisiológico o psicológico, en individuos sanos, y luego, en la monitorización de la depresión. En presencia de estrés mental (Cap. 9.1), inducido por tareas cognitivas, los sujetos sanos muestran un incremento en la frecuencia respiratoria y un mayor número de interacciones no lineales entre la respiración y la seãl de HRV. Esto podría estar asociado con una activación simpática, pero también con una respiración menos regular. En presencia de estrés hemodinámico (Cap. 9.2), inducido por un cambio postural, los sujetos sanos muestran una reducción en el acoplo cardiorrespiratoriono lineal cuadrático, que podría estar relacionado con una retracción vagal. En presencia de estrés térmico (Cap. 9.3), inducido por la exposición a emperaturas ambientales elevadas, los sujetos sanos muestran un aumento del equilibrio simpatovagal. Esto demuestra que los biomarcadores ANS son capaces de evaluar diferentes tipos de estrés y pueden explorarse más en el contexto de la monitorización de la depresión. En el Cap. 10, se evalúan las diferencias en la función del ANS entre elMDD y los sujetos sanos durante un protocolo de estrés mental, no solo con los valores brutos de los biomarcadores del ANS, sino también con los índices de reactividad autónoma, que reflejan la capacidad deun individuo para afrontar con una situación desafiante. Los resultados muestran que la depresión se asocia con un desequilibrio autonómico, que se caracteriza por una mayor actividad simpática y una reducción de la distensibilidad arterial. Los índices de reactividad autónoma cuantificados por cambios, entre etapas de estrés y de recuperación, en los sustitutos de la rigidez arterial, como la pérdida de amplitud de PPG en las ondas reflejadas, muestran el mejor rendimiento en términos de correlación con el grado de la depresión, con un coeficiente de correlación r = −0.5. La correlación negativa implicaque un mayor grado de depresión se asocia con una disminución de la reactividadautónoma. El poder discriminativo de los biomarcadores del ANS se aprecia también por su alto rendimiento diagnóstico para clasificar a los sujetos como MDD o sanos, con una precisión de 80.0%. Por lo tanto, se puede concluir que los biomarcadores del ANS pueden usarse para evaluar el estrés y que la distensibilidad arterial deteriorada podría constituir un biomarcador de salud mental útil en el seguimiento de la depresión.This dissertation is focused on multi-modal and model-based signal processing techniques for deriving physiological parameters, i.e. biomarkers, related to the autonomic nervous system (ANS). The development of novel approaches for deriving noninvasive ANS biomarkers in mental health and illness offers the possibility to improve the assessment of stress and the monitoring of depression. For this purpose, the present document is structured in three main parts. In Part I, an introduction to mental health and illness is provided (Ch. 1). Moreover, a theoretical framework for investigating the etiology of mental disorders and the role of stress in mental illness is presented (Ch. 2). The importance of noninvasive biomarkers for ANS assessment, paying particular attention in clinical depression, is also highlighted (Ch. 3, 4). In Part II, themethodological framework for deriving ANS biomarkers is provided. Signal processing techniques include the joint analysis of heart rate variability (HRV) and respiratory signals (Ch. 6), novel techniques for deriving the respiratory signal from electrocardiogram (ECG) (Ch. 7), and a robust photoplethysmogram(PPG)waveform analysis based on amodel-based approach (Ch. 8). In Part III, ANS biomarkers are evaluated in stress assessment (Ch. 9) and in the monitoring of depression (Ch. 10). Part I:Mental health is not only related to that positive state ofwell-being, inwhich an individual can cope with the normal stresses of life, but also to the absence of mental illness. Mental illness or disorder can be defined as an emotional, cognitive, or behavioural disturbance that causes substantial functional impairment in one or more major life activities. The most common mental disorders, which are often co-occurring, are anxiety and major depressive disorder (MDD). Mental illness has a negative impact on the quality of life, since it is associated with considerable losses in health and functioning, and increases significantly a person’s risk for cardiovascular diseases. A common instigator underlying the co-morbidity between MDD, cardiovascular pathology, and anxiety is mental stress. Stress is common in our fast-paced society and strongly influences our mental health. In the short term, ANS controls the cardiovascular response to stressful stimuli. Regulation of physiological parameters, such as heart rate, respiratory rate, and blood pressure, allows the organism to respond to sudden changes in the environment. However, physiological adaptation to a regularly occurring environmental phenomenon alters biological systems involved in stress response. Neurobiological alterations in the brain can disrupt the function of the ANS. ANS dysfunction and structural brain changes have a negative impact on cognitive, emotional, and behavioral processes, thereby leading to development of mental illness. Part II: The development of novel approaches for deriving noninvasive ANS biomarkers offers the possibility to improve the assessment of stress in healthy individuals and ANS dysfunction in MDD patients. Joint analysis of various biosignals (multi-modal approach) allows for the quantification of interactions among biological systems associated with ANS, while the modeling of biosignals and subsequent analysis of the model’s parameters (model-based approach) allows for the robust quantification of changes in physiological mechanisms related to the ANS. A novel method, which takes into account both phase and frequency locking phenomena between respiration and HRV signals, for assessing quadratic nonlinear cardiorespiratory coupling is proposed in Ch. 6.3. Novel techniques for improving the monitoring of respiration are proposed in Ch. 7. In Ch. 8, to increase the robustness for some morphological measurements reflecting arterial tone changes, the modeling of the PPG pulse as amain wave superposed with several reflected waves is considered. Part III: ANS biomarkers are evaluated in the assessment of different types of stress, either physiological or psychological, in healthy individuals, and then, in the monitoring of depression. In the presence of mental stress (Ch. 9.1), induced by cognitive tasks, healthy subjects show an increment in the respiratory rate and higher number of nonlinear interactions between respiration and HRV signal, which might be associated with a sympathetic activation, but also with a less regular breathing. In the presence of hemodynamic stress (Ch. 9.2), induced by a postural change, healthy subjects show a reduction in strength of the quadratic nonlinear cardiorespiratory coupling, whichmight be related to a vagal withdrawal. In the presence of heat stress (Ch. 9.3), induced by exposure to elevated environmental temperatures, healthy subjects show an increased sympathovagal balance. This demonstrates that ANS biomarkers are able to assess different types of stress and they can be further explored in the context of depression monitoring. In Ch. 10, differences in ANS function between MDD and healthy subjects during a mental stress protocol are assessed, not only with the raw values of ANS biomarkers but also with autonomic reactivity indices, which reflect the ability of an individual to copewith a challenging situation. Results show that depression is associated with autonomic imbalance, characterized by increased sympathetic activity and reduced arterial compliance. Autonomic reactivity indices quantified by changes, from stress to recovery, in arterial stiffness surrogates, such as the PPG amplitude loss in wave reflections, show the best performance in terms of correlation with depression severity, yielding to correlation coefficient r = −0.5. The negative correlation implies that a higher degree of depression is associated with a decreased autonomic reactivity. The discriminative power of ANS biomarkers is supported by their high diagnostic performance for classifying subjects as having MDD or not, yielding to accuracy of 80.0%. Therefore, it can be concluded that ANS biomarkers can be used for assessing stress and that impaired arterial compliance might constitute a biomarker of mental health useful in the monitoring of depression.<br /

Noise Calculation Charts and Indoor Environmental Quality for Evaluating Industrial Indoor Environment and Health

Noise, defined as “a sensation of unwanted intensity of a wave,” is perception of a pollutant and a type of environmental stressor. An environmental stressor such as noise may have detrimental effects on various aspects of health. The unwanted intensity of a wave is a propagation of noise due to transmission of waves (viz. physical agents) such as sun, light, sound, heat, electricity, fluid, and fire. The effects of these physical agents on human health as noise-intruding elements in an industrial indoor environment are discussed. Noise characterization is discussed from indoor air quality and health perspective. The noise calculation charts are detailed for interference of noise waves based on a benchmark solution. These charts calculate positive and negative magnitudes of noise based on noise characterization of waves due to power difference of two intensities. The noise interference is calculated from newly devised noise measurement equations and their units. The grades and flag colors are notated to the noise calculation charts. Furthermore, illustrated examples of noise characterization calculations for indoor environment are presented using devised noise measurement equations. Indoor environmental quality and noise instrumentation are discussed. Adverse effects of pollutants on human health are summarized. Ventilation systems for dispersion of pollutants from industrial indoor environment are also elaborated

Hyperspectral imaging for the remote sensing of blood oxygenation and emotions

This PhD project is a basic research and it concerns with how human’s physiological features, such as tissue oxygen saturation (StO2), can be captured from a stand-off distance and then to understand how this remotely acquired physiological feature can be deployed for biomedical and other applications. This work utilises Hyperspectral Imaging (HSI) within the diffuse optical scattering framework, to assess the StO2 in a contactless remote sensing manner. The assessment involves a detailed investigation about the wavelength dependence of diffuse optical scattering from the skin as well as body tissues, under various forms of optical absorption models. It is concluded that the threechromophore extended Beer Lambert Law model is better suited for assessing the palm and facial tissue oxygenations, especially when spectral data in the wavelengths region of [516-580]nm is used for the analysis. A first attempt of using the facial StO2 to detect and to classify people’s emotional state is initiated in this project. The objective of this work is to understand how strong emotions, such as distress that caused by mental or physical stimulations, can be detected using physiological feature such as StO2. Based on data collected from ~20 participants, it is found that the forehead StO2 is elevated upon the onset of strong emotions that triggered by mental stimulation. The StO2 pattern in the facial region upon strong emotions that are initiated by physical stimulations is quite complicated, and further work is needed for a better understanding of the interplays between bodily physique, individual’s health condition and blood transfusion control mechanism. Most of this work has already been published and future research to follow up when the author returns back to China is highlighted

Detecting Moments of Stress from Measurements of Wearable Physiological Sensors

There is a rich repertoire of methods for stress detection using various physiological signals and algorithms. However, there is still a gap in research efforts moving from laboratory studies to real-world settings. A small number of research has verified when a physiological response is a reaction to an extrinsic stimulus of the participant’s environment in real-world settings. Typically, physiological signals are correlated with the spatial characteristics of the physical environment, supported by video records or interviews. The present research aims to bridge the gap between laboratory settings and real-world field studies by introducing a new algorithm that leverages the capabilities of wearable physiological sensors to detect moments of stress (MOS). We propose a rule-based algorithm based on galvanic skin response and skin temperature, combing empirical findings with expert knowledge to ensure transferability between laboratory settings and real-world field studies. To verify our algorithm, we carried out a laboratory experiment to create a “gold standard” of physiological responses to stressors. We validated the algorithm in real-world field studies using a mixed-method approach by spatially correlating the participant’s perceived stress, geo-located questionnaires, and the corresponding real-world situation from the video. Results show that the algorithm detects MOS with 84% accuracy, showing high correlations between measured (by wearable sensors), reported (by questionnaires and eDiary entries), and recorded (by video) stress events. The urban stressors that were identified in the real-world studies originate from traffic congestion, dangerous driving situations, and crowded areas such as tourist attractions. The presented research can enhance stress detection in real life and may thus foster a better understanding of circumstances that bring about physiological stress in humans