Common Physiological Parameters Research Articles

Exploration of Teratogenic Effects of Bambusa vulgaris on Wistar Rats by Evaluating Morphological and Skeletal Parameters

AbstractBambusa vulgaris is a commonly consumable plant, which is widely utilized by indigenous peoples as a source of food. Consumption of these plant products in various forms is typically acceptable due to their distinct tastes, and aromatic flavor. However, there is little information on the plant's safety and toxicity profile. Although toxicity information on B. vulgaris is readily available, the impact of plants during pregnancy has yet to be fully explored. To determine the possible mechanism behind teratogenicity, pregnant albino Wistar rats are administered aqueous extracts of B. vulgaris in a dose‐dependent manner. For determining the structural malformations, Teratogenicity indices include maternal common physiological parameters, number of implantations and fetal indices, number of live, resorpsed, and dead somites, morphological malformations, and skeletal malformations of different organs are evaluated by comparing different test groups with control groups. Most developmental indices, including implantation and fetalindices, vertebral, organ, and skeletal structures are significantly altered by the crude extract at higher dosages in treated as compared to control animals. The administration of aqueous extract of B. vulgaris during the organogenesis phase in rats has a considerable deleterious effect on embryonic and fetal developmental indices. It ruthlessly impacts the embryo's numerous organs as well as their typical physiological processes in a dose‐dependent way. The present investigation validates the capacity of B. vulgaris to cause developmental toxicity in Wistar rats, as evidenced by significant alterations in their gestational morphological, structural, and skeletal anatomy and physiology. It is recommended that further scientific studies be conducted to evaluate the more advanced mechanisms of teratogenicity associated with B. vulgaris.

A review of infant apnea monitor design

Apnea detection is critical to the management of infant apnea. Effective monitoring and management of apnea using apnea monitors is known to reduce complications and possible fatalities in infants. There is a need to determine the critical design considerations in apnea monitors. This article reviews the design and development of infant apnea monitors. We conducted a targeted literature review from different databases, including PubMed, ScienceDirect, and Google Scholar. We reviewed articles published between January 1995 and February 2023. The search was done using combinations of key terms, namely, “apnea,” “apnea monitors,” and “apnea monitor design.” Articles that met the inclusion criteria were extracted and analyzed. The review investigated common physiological parameters, sensor types, and validation results of apnea monitors. The review revealed important design considerations adopted in the literature as well as the different sensor types and methods of apnea detection. It was found that thoracic impedance pneumography, thermistors, respiratory inductance plethysmography, pneumotachograph, and MEMS accelerometer are the most common sensor types used to design apnea monitors. The review revealed that most apnea monitors were designed to measure multiple physiological parameters. Device validation results varied from one device to another, with sensitivity and specificity metrics ranging between 80% and 96%. With the high burden of infant apnea in developing countries and its associated mortality and morbidity, the design of functional infant apnea monitors has become increasingly important to complement the expensive and complex polysomnography technique. Therefore, we must use appropriate sensors and design approaches for effective detection of infant apnea.

Temperature elevations can induce switches to homoclinic action potentials that alter neural encoding and synchronization

Almost seventy years after the discovery of the mechanisms of action potential generation, some aspects of their computational consequences are still not fully understood. Based on mathematical modeling, we here explore a type of action potential dynamics – arising from a saddle-node homoclinic orbit bifurcation - that so far has received little attention. We show that this type of dynamics is to be expected by specific changes in common physiological parameters, like an elevation of temperature. Moreover, we demonstrate that it favours synchronization patterns in networks – a feature that becomes particularly prominent when system parameters change such that homoclinic spiking is induced. Supported by in-vitro hallmarks for homoclinic spikes in the rodent brain, we hypothesize that the prevalence of homoclinic spikes in the brain may be underestimated and provide a missing link between the impact of biophysical parameters on abrupt transitions between asynchronous and synchronous states of electrical activity in the brain.

The Association Between White Blood Cell Count and Insulin Resistance in Community-Dwelling Middle-Aged and Older Populations in Taiwan: A Community-Based Cross-Sectional Study.

BackgroundInsulin resistance (IR) is a major pathophysiological factor in the development and progression of diabetes mellitus (DM). DM is highly prevalent in Taiwan and has become one of the most common health problems in family medicine and primary care. We aimed to use white blood cell count (WBC), a common physiological parameter, to develop a simple clinical prediction rule for IR in the middle-aged and old Taiwanese population.MethodsIn this cross-sectional community-based study, the participants completed a questionnaire comprising personal and medical history data and underwent anthropometric measurements and blood sampling. IR was defined as a HOMA-IR index ≥2. Independent t-test, Mann–Whitney U test, chi-square test, Pearson's correlation test, multivariate binary logistic regression, and receiver operating characteristic curves were used to evaluate the association between the WBC count and IR.ResultsA total of 398 community-dwelling middle-aged and older persons (34.9% men) with a mean age of 64.43 ± 8.45 years were enrolled for the analysis. A significant association was identified between the WBC counts and IR, with a Pearson's correlation coefficient of 0.37 (p-value <0.001). Multivariate logistic regression revealed that WBC count (OR = 1.50; 95% CI = 1.25–1.81) was an independent risk factor for IR after adjusting for confounding variables. The area under the receiver operating characteristic curve for WBC count was 0.67, and the optimal threshold value was 5.65 1,000/uL.ConclusionA high WBC count is positively related to an increased risk of IR among middle-aged and older people in Taiwan.

Разнообразие психрофильных бактерий и их биотехнологический потенциал (обзор)

Psychrophilic bacteria are a large group of microorganisms that prevail in low-temperature ecosystems. Psychrophilic bacteria have undergone a number of adaptations that help them exist in such conditions. One of such adaptations is the use of enzymes with a high specific activity at low temperatures. Such enzymes are usually called “cold-active.” These enzymes have potential applications in biotechnology and industry. In our review, we considered individual genera of psychrophilic bacteria, current global trends in the study of cold-active enzymes, their applications, and place in industrial biotechnology. Thus, the main goal of this study was to explore the diversity of psychrophilic bacteria, as well as opportunities of their application in biotechnology. The natural ecological sites of psychrophiles are numerous and varied. Psychrophiles form a permanent microflora of eternal cold regions, polar regions and oceans. Bacteria belonging to this group are found in soil, water or associated with plants and animals. An important site for psychrophilic microorganisms is a low-temperature water reservoir. At present, many new genera of psychrophiles and psychrotrophs have been derived from the bottom sediments and sea waters of the Arctic and Antarctic and described. Psychrophilic microorganisms are found in caves and in ancient ice crystal structures. The latter testifies to the very possibility of the super-long anabiosis phenomenon, as well as vital capacity preservation without division for a long period of time. Psychrophiles do not have a single form, they belong to at least several phylogenetic groups. Psychrophilic forms are found among the representatives of a large number of genera. There are no common physiological and biochemical parameters typical of psychrophilic bacteria. They comprise rods, cocci, vibrios, gram-negative and gram-positive bacteria, bacteria that produce and do not produce spores, strict aerobes, facultative and strict anaerobes. We lay greater emphasis on the diversity of psychrophilic bacteria capable of producing industrially important enzymes. The review considers bacteria belonging to the genera Vibrio and Aliivibrio, Pseudomonas, Achromobacter, Arthrobacter, Pseudoalteromonas, Bacillus, Clostridium, Micrococcus, Psychrobacter, Psychromonas, Flavobacterium, and psychrophilic methanotrophic microorganisms. These bacteria enzymes are used in agriculture, biotechnology, pharmaceuticals and household chemicals, as well as other sectors of the national economy. Psychrophilic bacteria produce a chemical compound that can be used in medicine. For example, Pseudomonas antarctica contains a cluster of genes encoding microcin B, R-type pyocins, adenosylcobalamin, and pyrroloquinoline quinone. Thus, P. antarctica has antibiotic activity. Psychrobacter proteolyticus also has an antineoplastic action and secrets an extracellular cold-adapted metalloproteinase being able to inhibit the space-occupying process. Cold-active metalloproteinases are also widely used as detergents, in currying, food sector and molecular biology. The immunogenic Pal conformable protein was derived from the psychrophilic strain of The representatives of the genus Arthrobacter capable of metabolizing diuron and petroleum products have an important property. A. agilis produces a red pigment, a bacterioruberin-type carotenoid being interesting as an antioxidant. A. psychrochitiniphilus is promising for cleaning water areas, oil-polluted coastlines, as it decomposes oil and petroleum products. Flavobacterium limicola is a potential source of cold-active protease. This bacterium is characterized by an increase in protease secretion as temperature decreases. Thus, F. limicola can be used in environmental biotransformations and bioremediations. The psychrophilic bacteria of the genus Bacillus are the participants of active studies. Their cold-active enzymes have a high potential in various areas of biomedicine, immunology, decontamination, and various industrial applications. The antifreeze proteins of psychrophilic Clostridia are considered a promising biotechnological product for use in medicine, food, beauty products, fuel, and other industries. This study reviews literary sources and indicates that at present obligate and facultative psychrophiles (psychrotrophs) and their cold-active enzymes are of scientific interest throughout the world. A significant part of the research is focused on a general understanding of the distribution of psychrophilic bacteria and a local study of enzymatic activity. A further study of psychrophilic microorganisms producing enzymes at low temperatures will reveal new ways for the development of biotechnologies in various sectors of the national economy. The paper contains 94 References. The Authors declare no conflict of interest.

Development and intercomparison of single and multicompartment physiologically-based toxicokinetic models: Implications for model selection and tiered modeling frameworks

This study describes the development and intercomparison of generic physiologically-based toxicokinetic (PBTK) models for humans comprised of internally consistent one-compartment (1Co-) and multi-compartment (MCo-) implementations (G-PBTK). The G-PBTK models were parameterized for an adult male (70 kg) using common physiological parameters and in vitro biotransformation rate estimates and subsequently evaluated using independent concentration versus time data (n = 6) and total elimination half-lives (n = 15) for diverse organic chemicals. The model performance is acceptable considering the inherent uncertainty in the biotransformation rate data and the absence of model calibration. The G-PBTK model was then applied using hypothetical neutral organics, acidic ionizable organics and basic ionizable organics (IOCs) to identify combinations of partitioning properties and biotransformation rates leading to substantial discrepancies between 1Co- and MCo-PBTK calculations for whole body concentrations and half-lives. The 1Co- and MCo-PBTK model calculations for key toxicokinetic parameters are broadly consistent unless biotransformation is rapid (e.g., half-life less than five days). When half-lives are relatively short, discrepancies are greatest for the neutral organics and least for the acidic IOCs which follows from the estimated volumes of distribution (e.g., VDSS = 9.6–15.4 L/kg vs 0.3–1.6 L/kg for the neutral and acidic compounds respectively) and the related approach to internal chemical equilibrium. The model intercomparisons demonstrate that 1Co-PBTK models can be applied with confidence to many exposure scenarios, particularly those focused on chronic or repeat exposures and for prioritization and screening-level decision contexts. However, MCo-PBTK models may be necessary in certain contexts, particularly for intermittent, short-term and highly variable exposures. A key recommendation to guide model selection and the development of tiered PBTK modeling frameworks that emerges from this study is the need to harmonize models with respect to parameterization and process descriptions to the greatest extent possible when proceeding from the application of simpler to more complex modeling tools as part of chemical assessment activities.

Effect of Planting Density and Fertilizer Rate on Some Physiological Parameters of Arabica Coffee Seedlings

Planting high density can reduce photosynthetic active radiation due to mutual shading or low light interception. The nature of the canopy and utilization of solar radiation influence the performances of coffee genotype. This study was designed to evaluate the effect of planting density and fertilizer rate on physiological parameters of Arabica coffee seedlings under nursery conditions. It was conducted at the Jimma Agricultural Research Center in southwest Ethiopia in 2018 season. A factorial experimentation in a completely randomized design with three replications was used for the study. The treatments consisted of combinations of two Arabica coffee cultivars (compact-74110 and open-75227), four population densities per polythene tube (one, two, three and four) and three compound NPK fertilizer (22:6:12 + Te) rates (control, 5g and 10g). The most common plant physiological parameters including NAR, AGR, RGR and CGR were estimated and analyzed using standard procedures. The results showed that interaction between cultivar, population density and fertilizer significantly (P ≤0.05) influenced NAR and CGR, and highly significantly (P ≤0.01) influenced AGR and RGR. The highest values of NAR, AGR, RGR and CGR were recorded from the lowest population density (PD1) and increased in the order of PD1 > PD2 > PD3 > PD4 for each parameter. Application of 5g of NPK significantly enhanced NAR, AGR, RGR and CGR as compared with other fertilizer rates, while these parameters were observed to decrease for 10g of NPK perhaps due to toxicity problem. In general, high planting density decrease physiological parameters of the coffee plant, so more attention like intensive coffee tree management practices as well as optimization of population density should be done under field conditions to increase physiological parameters of the coffee plant.

Noninvasive real-time detection of cerebral blood perfusion in hemorrhagic shock rabbits based on whole-brain magnetic induction phase shift: an experimental study

Objective: This study aimed to perform experiments to investigate the change trend in brain magnetic induction phase shift (MIPS) during hemorrhagic shock of different degrees of severity and to find the correlation between brain MIPS value and commonly used physiological indicators for detecting shock so as to explore a noninvasive method suitable for prehospital real-time detection of cerebral blood perfusion in hemorrhagic shock. Approach: The self-developed MIPS detection system was used to monitor the brain MIPS value in the whole process of hemorrhagic shock models of rabbits with different degrees of severity (control, mild, moderate, and severe) of shock in real time. Meanwhile, common physiological parameters, including arterial blood lactate (ABL), mean arterial pressure (MAP), heart rate (HR),core body temperature (CBT), regional cerebral blood flow (rCBF), and electroencephalogram (EEG), were also evaluated. Main results: The findings suggested that the brain MIPS value showed a downward trend in the shock process, and the decline degree of the MIPS value positively correlated with the severity of shock. Moreover, it showed a good detection and resolution ability in time/process and severity (P < 0.05). The MIPS values significantly correlated with ABL (P < 0.01), CBT (P < 0.01), and EEG (P < 0.05) at all four shock levels; with MAP (P < 0.05) and rCBF (P < 0.05) in the control, moderate, and severe groups; and with HR (P < 0.01) only in the severe group. Significance: The results demonstrated that the brain MIPS value has the capability of detecting hemorrhagic shock. The MIPS technique is a noninvasive method suitable for prehospital real-time detection of cerebral blood perfusion in hemorrhagic shock.

Prolactin attenuates global cerebral ischemic injury in rat model by conferring neuroprotection

ABSTRACTPrimary Objective: Limited available therapeutics for ischemic stroke necessitate dire need of designing novel strategies for combating ischemic pathophysiological cascade among which neuroprotective strategies emerge as positive approaches. The neuropeptide prolactin is a pleiotropic hormone that affects various physiological conditions and reportedly combats neurotoxicity, neuronal stress and provides neuroprotection to hippocampal neurons in vitro.Research Design: The study explores the ability of prolactin in conferring neuroprotection in global cerebral ischemia in vivo and attempts to optimize the dose of prolactin which will be effective for the same.Methods and Procedure: Global cerebral ischemia was induced in male rats by bilateral common carotid occlusion (BCCAO) and different physiological and biochemical parameters were evaluated. Also, cerebral infarction and percentage of brain edema were measured.Results: The results revealed that prolactin significantly reduces cerebral infarct, brain water content and restores the physiological conditions like blood pressure, heart rate and cerebral blood flow. Also, prolactin markedly reduces the increased levels of the neurotransmitters (ɣ-aminobutyric acid and glutamate), cerebral calcium and nitrate in different brain compartments of ischemic rats.Conclusion: Prolactin is able to ameliorate ischemia-reperfusion injury in rat brain and might be a potent candidate for further neuro-therapeutics development.

The Establishment of a CSF-Contacting Nucleus "Knockout" Model Animal.

To establish an entirely cerebrospinal fluid (CSF)-contacting nucleus-deficient model animal, we used cholera toxin B subunit (CB)- saporin (SAP), which is an analog of CB-HRP that specifically labels the CSF-contacting nucleus, to exclusively damage the nucleus. The effectiveness and specificity of the ablation were evaluated upon days 1–10 after CB-SAP microinjection into the brain ventricular system. The vital status, survival, and common physiological parameters of the model animals were also assessed during the experimental period. The results demonstrated that CB-SAP damaged only the CSF-contacting nucleus, but not other functional structures, in the brain. The complete ablation occurred by day 7 after CB-SAP microinjection. A model animal that had no CSF-contacting nucleus was established after survival beyond that time point. No obvious effects were observed in the vital status of the model animals, and their survival was ensured. The common physiological parameters of model animals were stable. The present study provides a method to establish a CSF-contacting nucleus “knockout” model animal, which is similar to a gene knockout model animal for studying this particular nucleus in vivo.

Application of liquid chromatography coupled to high-resolution mass spectrometry to measure urinary cortisol in loose housed sows

Cortisol is the most common physiological parameter used to measure welfare in pigs. In field studies evaluating stress in individual pigs which are group housed, the collection of spontaneously voided urine is practical. The purpose of the study was to apply a liquid chromatography coupled to high-resolution mass spectrometry approach to observe the patterns of diurnal urinary cortisol excretion among loose sows of three herds. We applied the analytical method in spontaneously voided urine of thirty, repeatedly sampled within a day, multiparous sows of three Greek herds. We found the level of urinary cortisol being highest before morning feeding [geometric mean of urinary cortisol to creatinine ratio being 2.72 (95% confidence interval: 1.17, 6.30), 5.65 (3.15, 10.14) and 2.60 (1.50, 4.50) in sows of herds A, B, and C, respectively] and lowest at 19:00 h [0.56 (0.27, 1.18), 1.24 (0.74, 2.07), 0.88 (0.55, 1.44)]. However, the patterns of diurnal urinary cortisol excretion appeared different among herds.

Determination of Leaf Water Content by Visible and Near-Infrared Spectrometry and Multivariate Calibration in Miscanthus.

Leaf water content is one of the most common physiological parameters limiting efficiency of photosynthesis and biomass productivity in plants including Miscanthus. Therefore, it is of great significance to determine or predict the water content quickly and non-destructively. In this study, we explored the relationship between leaf water content and diffuse reflectance spectra in Miscanthus. Three multivariate calibrations including partial least squares (PLS), least squares support vector machine regression (LSSVR), and radial basis function (RBF) neural network (NN) were developed for the models of leaf water content determination. The non-linear models including RBF_LSSVR and RBF_NN showed higher accuracy than the PLS and Lin_LSSVR models. Moreover, 75 sensitive wavelengths were identified to be closely associated with the leaf water content in Miscanthus. The RBF_LSSVR and RBF_NN models for predicting leaf water content, based on 75 characteristic wavelengths, obtained the high determination coefficients of 0.9838 and 0.9899, respectively. The results indicated the non-linear models were more accurate than the linear models using both wavelength intervals. These results demonstrated that visible and near-infrared (VIS/NIR) spectroscopy combined with RBF_LSSVR or RBF_NN is a useful, non-destructive tool for determinations of the leaf water content in Miscanthus, and thus very helpful for development of drought-resistant varieties in Miscanthus.

Deep learning framework for detection of hypoglycemic episodes in children with type 1 diabetes.

Most Type 1 diabetes mellitus (T1DM) patients have hypoglycemia problem. Low blood glucose, also known as hypoglycemia, can be a dangerous and can result in unconsciousness, seizures and even death. In recent studies, heart rate (HR) and correct QT interval (QTc) of the electrocardiogram (ECG) signal are found as the most common physiological parameters to be effected from hypoglycemic reaction. In this paper, a state-of-the-art intelligent technology namely deep belief network (DBN) is developed as an intelligent diagnostics system to recognize the onset of hypoglycemia. The proposed DBN provides a superior classification performance with feature transformation on either processed or un-processed data. To illustrate the effectiveness of the proposed hypoglycemia detection system, 15 children with Type 1 diabetes were volunteered overnight. Comparing with several existing methodologies, the experimental results showed that the proposed DBN outperformed and achieved better classification performance.

Mobile and E-Healthcare: Recent Trends and Future Directions

In the past decade, wearable sensors and devices have evolved as key technological objects which have dramatically revolutionized the next generation healthcare solutions. This is the era of cut-throat competition filled with immense stress which leads to the detection of various diseases even in the people of early age. Moreover, people are becoming more health conscious in developed as well as developing countries. The miniaturization of sensors and devices and tendency of people to be physician-independent have lead the researchers across the globe to come up with numerous healthcare solutions which are not only ubiquitous but are affordable also. Wearable medical devices (WMDs) capable of monitoring some of the most common physiological parameters- pulse, blood oxygen saturation, 2 lead ECG, heart rhythm, skin temperature etc. have already been popular. Ambulatory and long-term health monitoring for elderly people is another aspect, particularly for countries like China and Japan where population aging is increasing. With the development of networks, collected health information can be sent to the cloud server of the nearest clinic or hospital. Doctors can then provide patients with medical advice. Thus, WMDs or WMD-based applications can help both patients and doctors in daily health monitoring. The paradigm has gradually shifted to the mobile health (mHealth) - an integration of ever advancing wireless communication, ubiquitous computing, and wearable device technologies. The mHealth can be regarded as the most advanced version of healthcare monitoring.

Diabetes and hypertension, as well as obesity and Alzheimer's disease, are linked to hypohydration-induced lower brain volume.

In their excellent systematic review Meusel et al. (2014) put forward a hypothesis of a possible bias in imaging the brain during studies of cognitive aging with the inclusion of type 2 diabetics (T2DM) and hypertensive patients as part of the healthy controls. Their overview of metabolic and vascular changes associated with T2DM and hypertension raised again the interesting issue of what is similar between the two illnesses. It is known, furthermore, that a certain percentage of T2DM patients have also, or will go on to develop, hypertension. The same could be said for T2DM who have also, or who will develop, obesity and/or Alzheimer's disease. As these 4 diseases are currently affecting a large percentage of the population, especially the elderly, it might be of interest to consider what could be a common physiological parameter linking these illnesses that could affect also brain imaging and/or cognitive aging. A lower brain volume has been observed in Alzheimer's disease with or without mild cognitive impairment, in people with a high BMI (obesity), and in patients with progressive mild cognitive impairment (Ho et al., 2010; Liu et al., 2010; Raji et al., 2010). Furthermore, brain atrophy similar to that of preclinical Alzheimer's disease has been reported also in T2DM patients (Moran et al., 2013). These very interesting findings could suggest a common cause for altered brain function in these patients. It has been hypothesized that chronic hypovolemia (due to hypohydration) is perhaps one of the principal mechanisms behind the development of obesity, diabetes, hypertension, and even Alzheimer's disease (Fetissov and Thornton, 2009; Thornton and Benetos, 2011; Thornton, 2012). Now, if this were the case, then hypovolemia resulting from systemic dehydration could also reduce brain volume (Dickson et al., 2005; Duning et al., 2005). This “hypothesis” of dehydration is supported further by work showing that total body water decreases with age (Chumlea et al., 1999) as well as with increasing BMI (Ritz et al., 2008), thus suggesting that aged and/or obese and/or diabetic patients could be chronically dehydrated. Furthermore, the majority of medications used to treat cardiovascular disease block the renin-angiotensin (aldosterone) system yet this system is activated physiologically by hypovolemia (Thornton, 2010). Furthermore, high blood pressure levels have been associated with brain volume decreases (Beauchet et al., 2013), further adding support to overall dehydration–induced pathophysiology. Dehydration has an important negative effect on cell metabolism (Schliess and Haussinger, 2003; Fetissov and Thornton, 2009; Thornton et al., 2009) which may go part way to explaining the association of cognitive dysfunction with decreases in brain volume and signs of atrophy. It has been suggested that increased drinking would go some way to alleviating some of the signs of the dehydration and the decreased metabolism. An increased fluid intake would also allow the brain to rehydrate (Duning et al., 2005). It would be very interesting to investigate just what influence these changes in brain volume, and thus neuronal volume and metabolism with dehydration and rehydration, would have on cognitive impairment associated with aging and associated with T2DM, obesity, as well as cardiovascular, and Alzheimer's disease. In contrast to what has been found in the pathophysiology mentioned above, dehydration in healthy humans does not appear to have a great influence on brain volume changes (Kempton et al., 2009). Whereas in healthy adolescences, again with no obvious changes in brain volume, dehydration appeared to negatively impact “executive functions such as planning and visuo-spatial processing” where individuals needed to exert a higher level of neuronal activity in order to achieve the same performance level (Kempton et al., 2011). It should be noted that these effects were noticed with short-term dehydration, whereas the overall effects of long-term, or chronic, dehydration appear to be more global affecting various parts of the body (obesity, insulin resistance, blood pressure) as well as the brain (cognitive dysfunction). A screening method for whole body dehydration (angiotensin and aldosterone hormone levels) should perhaps be recommended as a new norm for imaging studies of cognitive aging.

Human males and females body thermoregulation: Perfusion effect analysis

Skin temperature is a common physiological parameter that reflects thermal responses. Blood perfusion is an important part of the physiological processes that the human body undergoes in order to maintain homeostasis. This study focuses on the effect of perfusion on the temperature distribution in human males and females body in different thermal environment. The study has been carried out for one dimensional steady cases using finite element method. The input parameter of the model is the blood perfusion or volumetric flow rate within the tissue. The appropriate physical and physiological parameters together with suitable boundary conditions that affect the heat regulations have been incorporated in the model. The study is to have a better understanding that how does thermoregulation change in human males and females skin layered due to perfusion.

Industrial Application of Evolvable Block-Based Neural Network to Hypoglycemia Monitoring System

Insulin-dependent diabetes mellitus is classified as type 1 diabetes mellitus (T1DM), and it can be further classified as immune-mediated or idiopathic. It is dangerous and can result in unconsciousness, seizures, and even sudden death. The most common physiological parameters to be effected from a hypoglycemic reaction are heart rate and corrected QT interval of the electrocardiogram (ECG) signal. Considering the correlation between physiological parameters of an ECG signal and the status of hypoglycemia, a noninvasive hypoglycemia monitoring system is tested and introduced by proposing a hybrid particle-swarm-optimization-based block-based neural network (BBNN) algorithm. The proposed BBNN model offers advantages over conventional neural networks by performing the simultaneous optimization of both structure and weights. The hybrid particle swarm optimization with wavelet mutation searches for optimized structure and network parameters through particle information over a search space. All the actual data sets of 15 T1DM children were collected at the Department of Health, Government of Western Australia. Several experiments showed that the proposed BBNN performed well in terms of better sensitivity and specificity.

A study of human skin and surface temperatures in stable and unstable thermal environments

Skin temperature is a common physiological parameter that reflects human thermal responses. The purpose of this research was to investigate the effects of radiant temperature on human skin temperature and surface temperature in stable and unstable thermal environments. For a clothed human body, the skin temperature is the surface temperature of the skin, while the surface temperature is the outer surface temperature of the clothes. For this aim, the radiant temperature from 26 to 38°C and then from 38 to 26°C was controlled in three different ways; in stable condition keeping stable above 40min, in unstable condition at a rate of 2°C/5min, and in another unstable condition at a rate of 2°C/10min. Experimental data showed that at the same radiant temperature, the local skin/surface temperatures during the radiant temperature decrease were higher compared to those during the radiant temperature increase. During the radiant temperature increase/decrease, the increments/decrements of the mean skin temperature and the mean surface temperature decreased gradually from the stable condition, 2°C/10min to 2°C/5min. Compared to surface temperature, the faster the radiant temperature changed, the more obviously the change in skin temperature was delayed. These data demonstrated that the human body has physiological adaptability to unstable thermal environments.

NON-INVASIVE NOCTURNAL HYPOGLYCEMIA DETECTION FOR INSULIN-DEPENDENT DIABETES MELLITUS USING GENETIC FUZZY LOGIC METHOD

Hypoglycemia, or low blood glucose, is the most common complication experienced by Type 1 diabetes mellitus (T1DM) patients. It is dangerous and can result in unconsciousness, seizures and even death. The most common physiological parameter to be effected from hypoglycemic reaction are heart rate (HR) and correct QT interval (QTc) of the electrocardiogram (ECG) signal. Based on physiological parameters, a genetic algorithm based fuzzy reasoning model is developed to recognize the presence of hypoglycemia. To optimize the parameters of the fuzzy model in the membership functions and fuzzy rules, a genetic algorithm is used. A validation strategy based adjustable fitness is introduced in order to prevent the phenomenon of overtraining (overfitting). For this study, 15 children with 569 sampling data points with Type 1 diabetes volunteered for an overnight study. The effectiveness of the proposed algorithm is found to be satisfactory by giving better sensitivity and specificity compared with other existing methods for hypoglycemia detection.

Normal Ranges of Renal Physiological Parameters for Technetium-99m Mercaptoacetyltriglycine and the Influence of Age and Sex Using a Camera-Based Method

162 normal Chinese men and women underwent a ^99mTc MAG3 renal study. Seventy-two males and 90 females were evaluated in 5 age groups: group 1, 61–80 years; group 2, 51–60 years; group 3, 41–50 years; group 4, 31–40 years, and group 5, 21–30 years. Each subject was required to fit the following criteria: (1) clinically no history of renal, urinary disorders and systemic diseases, normal blood pressure, kidney morphology, urinary examination and serum creatinine, and (2) for the gamma camera study normal hydration and renal images, and no pelvic, ureteric dilatation or retention of tracer should be found. The normal range of common physiological parameters for ^99mTc MAG3 renal studies was measured in normal subjects. The effective renal plasma flow (ERPF, camera-based Schlegel method), percent function in each kidney (renal index, RI), time of peak renal parenchymal activity (T_max) and half time of parenchymal activity following the peak (T¹/₂) were evaluated. The T_max and T¹/₂ were determined with regions of interest over the entire kidney. The results showed that (1) between the sexes, there were no significant differences for any parameter; (2) between the age groups, the only significant difference was a decrease in ERPF, normalized for body surface area, with increasing age (group 1, 511.3 ± 91.2; group 2, 559.5 ± 102.1; group 3, 577.1 ± 79.2; group 4, 607.8 ± 101.1, and group 5, 610.2 ± 109.2), and (3) the RI, T_max and T¹/₂ were symmetrical and did not vary between the sexes or age groups (left vs. right: RI = 49.6 ± 2.2 vs. 50.4 ± 2.2%, T_max = 3.63 ± 1.13 vs. 3.75 ± 1.11 min, and T¹/₂ = 5.38 ± 1.65 vs. 5.83 ± 1.88 min). We find that (1) ERPF for ^99mTc MAG3 decreases with age in normal Chinese, which is similar to the results of Western countries, and (2) the RI, T_max and T¹/₂ were symmetrical and did not vary between the sexes or age groups in normal Chinese, and are also similar to the results of Western countries.