Physiological network approach to prognosis in cirrhosis: A shifting paradigm.

Decompensated liver disease is complicated by multi-organ failure and poor prognosis. The prognosis of patients with liver failure often dictates clinical management. Current prognostic models have focused on biomarkers considered as individual isolated units. Network physiology assesses the interactions among multiple physiological systems in health and disease irrespective of anatomical connectivity and defines the influence or dependence of one organ system on another. Indeed, recent applications of network mapping methods to patient data have shown improved prediction of response to therapy or prognosis in cirrhosis. Initially, different physical markers have been used to assess physiological coupling in cirrhosis including heart rate variability, heart rate turbulence, and skin temperature variability measures. Further, the parenclitic network analysis was recently applied showing that organ systems connectivity is impaired in patients with decompensated cirrhosis and can predict mortality in cirrhosis independent of current prognostic models while also providing valuable insights into the associated pathological pathways. Moreover, network mapping also predicts response to intravenous albumin in patients hospitalized with decompensated cirrhosis. Thus, this review highlights the importance of evaluating decompensated cirrhosis through the network physiologic prism. It emphasizes the limitations of current prognostic models and the values of network physiologic techniques in cirrhosis.

Parenclitic Network Mapping Identifies Response to Targeted Albumin Therapy in Patients Hospitalized With Decompensated Cirrhosis.

INTRODUCTION: The efficacy of targeted albumin therapy in the management of decompensatory events in cirrhosis is unclear, with different reports showing conflicting results. It is possible that only certain subgroups of patients may benefit from targeted albumin administration. However, extensive conventional subgroup analyses have not yet identified these subgroups. Albumin is an important regulator of physiological networks and may interact with homeostatic mechanism differently in patients according to the integrity of their physiological network. In this study, we aimed to assess the value of network mapping in predicting response to targeted albumin therapy in patients with cirrhosis. METHODS: This is a substudy of the ATTIRE trial, a multicenter randomized trial conducted to assess the effect of targeted albumin therapy in cirrhosis. Baseline serum bilirubin, albumin, sodium, creatinine, CRP, white cell count (WCC), international normalized ratio, heart rate, and blood pressure of 777 patients followed up for 6 months were used for network mapping using parenclitic analysis. Parenclitic network analysis involves measuring the deviation of each patient from the existing network of physiological interactions in a reference population. RESULTS: Overall network connectivity and deviations along the WCC-CRP axis predicted 6-month survival independent of age and model for end-stage liver disease in the standard care arm. Patients with lower deviation along the WCC-CRP axis showed lower survival in response to targeted albumin administration over a 6-month follow-up period. Likewise, patients with higher overall physiological connectivity survived significantly less than the standard care group after targeted albumin infusion. DISCUSSION: The parenclitic network mapping can predict the survival of patients with cirrhosis and identify patient subgroups that do not benefit from targeted albumin therapy.

Iodotyrosines Are Biomarkers for Preclinical Stages of Iodine-Deficient Hypothyroidism in Dehal1-Knockout Mice.

Background: Iodine is required for the synthesis of thyroid hormone (TH), but its natural availability is limited. Dehalogenase1 (Dehal1) recycles iodine from mono- and diiodotyrosines (MIT, DIT) to sustain TH synthesis when iodine supplies are scarce, but its role in the dynamics of storage and conservation of iodine is unknown. Methods: Dehal1-knockout (Dehal1KO) mice were generated by gene trapping. The timing of expression and distribution was investigated by X-Gal staining and immunofluorescence using recombinant Dehal1-beta-galactosidase protein produced in fetuses and adult mice. Adult Dehal1KO and wild-type (Wt) animals were fed normal and iodine-deficient diets for 1 month, and plasma, urine, and tissues were isolated for analyses. TH status was monitored, including thyroxine, triiodothyronine, MIT, DIT, and urinary iodine concentration (UIC) using a novel liquid chromatography with tandem mass spectrometry method and the Sandell-Kolthoff (S-K) technique throughout the experimental period. Results: Dehal1 is highly expressed in the thyroid and is also present in the kidneys, liver, and, unexpectedly, the choroid plexus. In vivo transcription of Dehal1 was induced by iodine deficiency only in the thyroid tissue. Under normal iodine intake, Dehal1KO mice were euthyroid, but they showed negative iodine balance due to a continuous loss of iodotyrosines in the urine. Counterintuitively, the UIC of Dehal1KO mice is twofold higher than that of Wt mice, indicating that S-K measures both inorganic and organic iodine. Under iodine restriction, Dehal1KO mice rapidly develop profound hypothyroidism, while Wt mice remain euthyroid, suggesting reduced retention of iodine in the thyroids of Dehal1KO mice. Urinary and plasma iodotyrosines were continually elevated throughout the life cycles of Dehal1KO mice, including the neonatal period, when pups were still euthyroid. Conclusions: Plasma and urine iodotyrosine elevation occurs in Dehal1-deficient mice throughout life. Therefore, measurement of iodotyrosines predicts an eventual iodine shortage and development of hypothyroidism in the preclinical phase. The prompt establishment of hypothyroidism upon the start of iodine restriction suggests that Dehal1KO mice have low iodine reserves in their thyroid glands, pointing to defective capacity for iodine storage.

Application of short-term analysis of skin temperature variability in prediction of survival in patients with cirrhosis.

Background: Liver cirrhosis is a complex disorder, involving several different organ systems and physiological network disruption. Various physiological markers have been developed for survival modelling in patients with cirrhosis. Reduction in heart rate variability and skin temperature variability have been shown to predict mortality in cirrhosis, with the potential to aid clinical prognostication. We have recently reported that short-term skin temperature variability analysis can predict survival independently of the severity of liver failure in cirrhosis. However, in previous reports, 24-h skin temperature recordings were used, which are often not feasible in the context of routine clinical practice. The purpose of this study was to determine the shortest length of time from 24-h proximal temperature recordings that can accurately and independently predict 12-month survival post-recording in patients with cirrhosis. Methods: Forty individuals diagnosed with cirrhosis participated in this study and wireless temperature sensors (iButtons) were used to record patients' proximal skin temperature. From 24-h temperature recordings, different length of recordings (30 min, 1, 2, 3 and 6 h) were extracted sequentially for temperature variability analysis using the Extended Poincaré plot to quantify both short-term (SD1) and long-term (SD2) variability. These patients were then subsequently followed for a period of 12 months, during which data was gathered concerning any cases of mortality. Results: Cirrhosis was associated with significantly decreased proximal skin temperature fluctuations among individuals who did not survive, across all durations of daytime temperature recordings lasting 1 hour or more. Survival analysis showcased 1-h daytime proximal skin temperature time-series to be significant predictors of survival in cirrhosis, whereby SD2, was found to be independent to the Model for End-Stage Liver Disease (MELD) score and thus, the extent of disease severity. As expected, longer durations of time-series were also predictors of mortality for the majority of the temperature variability indices. Conclusion: Crucially, this study suggests that 1-h proximal skin temperature recordings are sufficient in length to accurately predict 12-month survival in patients with cirrhosis, independent from current prognostic indicators used in the clinic such as MELD.

Reduced oxygen saturation entropy is associated with poor prognosis in critically ill patients with sepsis.

Recent studies have found that oxygen saturation (SpO2 ) variability analysis has potential for noninvasive assessment of the functional connectivity of cardiorespiratory control systems during hypoxia. Patients with sepsis have suboptimal tissue oxygenation and impaired organ system connectivity. Our objective with this report was to highlight the potential use for SpO2 variability analysis in predicting intensive care survival in patients with sepsis. MIMIC-III clinical data of 164 adults meeting Sepsis-3 criteria and with 30 min of SpO2 and respiratory rate data were analyzed. The complexity of SpO2 signals was measured through various entropy calculations such as sample entropy and multiscale entropy analysis. The sequential organ failure assessment (SOFA) score was calculated to assess the severity of sepsis and multiorgan failure. While the standard deviation of SpO2 signals was comparable in the non-survivor and survivor groups, non-survivors had significantly lower SpO2 entropy than those who survived their ICU stay (0.107 ± 0.084 vs. 0.070 ± 0.083, p < 0.05). According to Cox regression analysis, higher SpO2 entropy was a predictor of survival in patients with sepsis. Multivariate analysis also showed that the prognostic value of SpO2 entropy was independent of other covariates such as age, SOFA score, mean SpO2 , and ventilation status. When SpO2 entropy was combined with mean SpO2 , the composite had a significantly higher performance in prediction of survival. Analysis of SpO2 entropy can predict patient outcome, and when combined with SpO2 mean, can provide improved prognostic information. The prognostic power is on par with the SOFA score. This analysis can easily be incorporated into current ICU practice and has potential for noninvasive assessment of critically ill patients.

Measurement of Electrokinetically induced hydrodynamics at Ion-selective interfaces using 3D Micro particle tracking velocimetry (µPTV).

Electrokinetic flow phenomena are ubiquitous in electrical systems for desalination, chemical conversion, or mixing at a micro-scale. However, the important features of resulting 3D flow fields are only accessible through cost-intensive numerical simulations. Experimental 2D recording of the chaotic three-dimensional velocity fields developing for example at currents exceeding the limiting current density does not capture the complex 3D structures present in such flow fields. Additionally, numerical 3D studies are limited to dimensions three orders of magnitude smaller as found in real applications and only short run times due to the enormous computational effort. To apply the theoretical knowledge in real-world systems and create the possibility for detailed parameter studies, we present the first experimental method for recording and quantifying the time-resolved velocity field in an electrochemical microfluidic cell in 3D with dimensions found in industrial applications. We utilize this method in a co-submitted paper to record the 3D velocity field of electroconvection at a cation-exchange membrane.•Cell design suitable for simultaneous electrochemical experiments with optical 3D velocity quantification•Method optimized for velocity reconstruction of membrane-to-membrane distances found in industrial cells•Highly adaptable cell design, for optical characterization of electrochemical systems.

The mechanistic and prognostic implications of heart rate variability analysis in patients with cirrhosis.

Chronic liver damage leads to scarring of the liver tissue and ultimately a systemic illness known as cirrhosis. Patients with cirrhosis exhibit multi-organ dysfunction and high mortality. Reduced heart rate variability (HRV) is a hallmark of cirrhosis, reflecting a state of defective cardiovascular control and physiological network disruption. Several lines of evidence have revealed that decreased HRV holds prognostic information and can predict survival of patients independent of the severity of liver disease. Thus, the aim of this review is to shed light on the mechanistic and prognostic implications of HRV analysis in patients with cirrhosis. Notably, several studies have extensively highlighted the critical role systemic inflammation elicits in conferring the reduction in patients' HRV. It appears that IL-6 is likely to play a central mechanistic role, whereby its levels also correlate with manifestations, such as autonomic neuropathy and hence the partial uncoupling of the cardiac pacemaker from autonomic control. Reduced HRV has also been reported to be highly correlated with the severity of hepatic encephalopathy, potentially through systemic inflammation affecting specific brain regions, involved in both cognitive function and autonomic regulation. In general, the prognostic ability of HRV analysis holds immense potential in improving survival rates for patients with cirrhosis, as it may indeed be added to current prognostic indicators, to ultimately increase the accuracy of selecting the recipient most in need of liver transplantation. However, a network physiology approach in the future is critical to delineate the exact mechanistic basis by which decreased HRV confers poor prognosis.

Prognosis and Survival Modelling in Cirrhosis Using Parenclitic Networks.

Background: Liver cirrhosis involves multiple organ systems and has a high mortality. A network approach to complex diseases often reveals the collective system behaviours and intrinsic interactions between organ systems. However, mapping the functional connectivity for each individual patient has been challenging due to the lack of suitable analytical methods for assessment of physiological networks. In the present study we applied a parenclitic approach to assess the physiological network of each individual patient from routine clinical/laboratory data available. We aimed to assess the value of the parenclitic networks to predict survival in patients with cirrhosis. Methods: Parenclitic approach creates a network from the perspective of an individual subject in a population. In this study such an approach was used to measure the deviation of each individual patient from the existing network of physiological interactions in a reference population of patients with cirrhosis. 106 patients with cirrhosis were retrospectively enrolled and followed up for 12 months. Network construction and analysis were performed using data from seven clinical/laboratory variables (serum albumin, bilirubin, creatinine, ammonia, sodium, prothrombin time and hepatic encephalopathy) for calculation of parenclitic deviations. Cox regression was used for survival analysis. Result: Initial network analysis indicated that correlation between five clinical/laboratory variables can distinguish between survivors and non-survivors in this cohort. Parenclitic deviations along albumin-bilirubin (Hazard ratio = 1.063, p < 0.05) and albumin-prothrombin time (Hazard ratio = 1.138, p < 0.05) predicted 12-month survival independent of model for end-stage liver disease (MELD). Combination of MELD with the parenclitic measures could predict survival better than MELD alone. Conclusion: The parenclitic network approach can predict survival of patients with cirrhosis and provides pathophysiologic insight on network disruption in chronic liver disease.

Application of oxygen saturation variability analysis for the detection of exacerbation in individuals with COPD: A proof-of-concept study.

BACKGROUND: Individuals with chronic obstructive pulmonary disease (COPD) commonly experience exacerbations, which may require hospital admission. Early detection of exacerbations, and therefore early treatment, could be crucial in preventing admission and improving outcomes. Our previous research has demonstrated that the pattern analysis of peripheral oxygen saturation (Sp O2 ) fluctuations provides novel insights into the engagement of the respiratory control system in response to physiological stress (hypoxia). Therefore, this pilot study tested the hypothesis that the pattern of Sp O2 variations in overnight recordings of individuals with COPD would distinguish between stable and exacerbation phases of the disease. METHODS: Overnight pulse oximetry data from 11 individuals with COPD, who exhibited exacerbation after a period of stable disease, were examined. Stable phase recordings were conducted overnight and one night prior to exacerbation recordings were also analyzed. Pattern analysis of Sp O2 variations was carried examined using sample entropy (for assessment of irregularity), the multiscale entropy (complexity), and detrended fluctuation analysis (self-similarity). RESULTS: Sp O2 variations displayed a complex pattern in both stable and exacerbation phases of COPD. During an exacerbation, Sp O2 entropy increased (p = 0.029) and long-term fractal-like exponent (α2) decreased (p = 0.002) while the mean and standard deviation of Sp O2 time series remained unchanged. Through ROC analyses, Sp O2 entropy and α2 were both able to classify the COPD phases into either stable or exacerbation phase. With the best positive predictor value (PPV) for sample entropy (PPV = 70%) and a cut-off value of 0.454. While the best negative predictor value (NPV) was α2 (NPV = 78%) with a cut-off value of 1.00. CONCLUSION: Alterations in Sp O2 entropy and the fractal-like exponent have the potential to detect exacerbations in COPD. Further research is warranted to examine if Sp O2 variability analysis could be used as a novel objective method of detecting exacerbations.

1-Methyl tryptophan, an indoleamine 2,3-dioxygenase inhibitor, attenuates cardiac and hepatic dysfunction in rats with biliary cirrhosis.

Kynurenine Pathway (KP) is the dominant metabolic route of tryptophan which is catalyzed by indoleamine-2,3-dioxygenase (IDO). This pathway is upregulated in liver disease where the level of KP metabolites correlates with the severity of disease. Cirrhosis is associated with cardiac dysfunction, which manifests itself during severe physiological challenges such as liver transplantation. Cardiac dysfunction in cirrhosis is linked to systemic inflammation and impaired cardiac beta-adrenergic signaling pathways. The KP pathway is involved in modulation of cardiac signaling and is upregulated by systemic inflammation. Therefore, this study aimed to evaluate the effect of IDO inhibition on development of cardiac dysfunction in an experimental model of cirrhosis. Cirrhosis was induced by bile duct ligation (BDL). Experimental groups were given either 1-methyl tryptophan (1-MT, 1, 3, 9 mg/kg), or saline. 28 days after BDL, cardiac chronotropic response to epinephrine was assessed ex vivo. HPLC was employed to measure hepatic and cardiac levels of tryptophan, kynurenine and kynurenic acid. Cirrhosis in rats was associated with impaired cardiac chronotropic responsiveness to adrenergic stimulation. 1-MT dose-dependently improved cirrhosis-induced chronotropic dysfunction as well as elevated serum levels of CRP and IL-6 in BDL rats. Hepatic and cardiac kynurenine/tryptophan ratio were elevated in cirrhotic rats and were reduced following 1-MT administration. Chronic administration of 1-MT could also reduce hepatic inflammation, fibrosis and ductular proliferation. 1-MT attenuates cardiac dysfunction in rats with biliary cirrhosis. This protective effect is not limited to the cardiac function as liver histopathologic changes were also improved following chronic 1-MT administration.

Heart rate variability in patients with cirrhosis: a systematic review and meta-analysis.

Background. Cirrhosis is associated with abnormal autonomic function and regulation of cardiac rhythm. Measurement of heart rate variability (HRV) provides an accurate and non-invasive measurement of autonomic function as well as liver disease severity currently calculated using the MELD, UKELD, or Child-Pugh scores. This review assesses the methods employed for the measurement of HRV, and evaluates the alteration of HRV indices in cirrhosis, as well as their value in prognosis.Method.We undertook a systematic review using Medline, Embase and Pubmed databases in July 2020. Data were extracted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The risk of bias of the included studies was assessed by a modified version of the Newcastle-Ottawa Scale. The descriptive studies were analysed and the standardized mean differences of HRV indices were pooled.Results.Of the 247 studies generated from our search, 14 studies were included. One of the 14 studies was excluded from meta-analysis because it reported only the median of HRV indices. The studies included have a low risk of bias and include 583 patients with cirrhosis and 349 healthy controls. The HRV time and frequency domains were significantly lower in cirrhotic patients. Between-studies heterogeneity was high in most of the pooled studies (P < 0.05). Further, HRV indices predict survival independent of the severity of liver disease as assessed by MELD.Conclusion.HRV is decreased in patients with cirrhosis compared with healthy matched controls. HRV correlated with severity of liver disease and independently predicted survival. There was considerable variation in the methods used for HRV analysis, and this impedes interpretation and clinical applicability. Based on the data analysed, the standard deviation of inter-beat intervals (SDNN) and SDNN corrected for basal heart rate (cSDNN) are the most suitable indices for prognosis in patients with cirrhosis.

Overlimiting Current in Nonuniform Arrays of Microchannels: Recirculating Flow and Anticrystallization.

Overlimiting current (OLC) through electrolytes interfaced with perm-selective membranes has been extensively researched for understanding fundamental nano-electrokinetics and developing efficient engineering applications. This work studies how a network of microchannels in a nonuniform array, which mimics a natural pore configuration, can contribute to OLC. Here, micro/nanofluidic devices are fabricated with arrays of parallel microchannels with nonuniform size distributions, which are faced with a perm-selective membrane. All cases maintain the same surface and bulk conduction to allow probing of the sensitivity only by the nonuniformity. Rigorous experimental and theoretical investigation demonstrates that overlimiting conductance has a maximum value depending on the nonuniformity. Furthermore, in operando visualization reveals that the nonuniform arrays induce flow loops across the microchannel network enhancing advective transport. This recirculating flow eliminates local salt accumulations so that it can effectively suppress undesirable salt crystallization. Therefore, these results can significantly advance not only the fundamental understanding of the driving mechanism of the OLC but also the design rule of electrochemical membrane applications.

A network physiology approach to oxygen saturation variability during normobaric hypoxia.

NEW FINDINGS: What is the central question of this study? What is the physiological interpretation of SpO2 fluctuations observed during normobaric hypoxia in healthy individuals? What is the main finding and its importance? There is a significant flow of information between SpO2 and other cardio-respiratory time series during graded hypoxia. Analysis of the pattern of SpO2 variations has potential for non-invasive assessment of the engagement of respiratory control system in health and disease. ABSTRACT: Peripheral capillary oxygen saturation ( SpO2 ) exhibits a complex pattern of fluctuations during hypoxia. The physiological interpretation of SpO2 variability is not well understood. In this study, we tested the hypothesis that SpO2 fluctuation carries information about integrated cardio-respiratory control in healthy individuals using a network physiology approach. We explored the use of transfer entropy in order to compute the flow of information between cardio-respiratory signals during hypoxia. Twelve healthy males (mean (SD) age 22 (4) years) were exposed to four simulated environments (fraction of inspired oxygen ( FIO2 ): 0.12, 0.145, 0.17, and 0.2093) for 45 min, in a single blind randomized controlled design. The flow of information between different physiological parameters ( SpO2 , respiratory frequency, tidal volume, minute ventilation, heart rate, end-tidal pressure of O2 and CO2 ) were analysed using transfer entropy. Normobaric hypoxia was associated with a significant increase in entropy of the SpO2 time series. The transfer entropy analysis showed that, particularly at FIO2 0.145 and 0.12, the flow of information between SpO2 and other physiological variables exhibits a bidirectional relationship. While reciprocal interactions were observed between different cardio-respiratory parameters during hypoxia, SpO2 remained the main hub of this network. SpO2 fluctuations during graded hypoxia exposure carry information about cardio-respiratory control. Therefore, SpO2 entropy analysis has the potential for non-invasive assessment of the functional connectivity of respiratory control system in various healthcare settings.

Heart Rate Turbulence Predicts Survival Independently From Severity of Liver Dysfunction in Patients With Cirrhosis.

BACKGROUND: Reduced heart rate variability (HRV) is an independent predictor of mortality in patients with cirrhosis. However, conventional HRV indices can only be interpreted in individuals with normal sinus rhythm. In patients with recurrent premature ventricular complexes (PVCs), the predictive capacity of conventional HRV indices is compromised. Heart Rate Turbulence (HRT) represents the biphasic change of the heart rate after PVCs. This study was aimed to define whether HRT parameters could predict mortality in cirrhotic patients. MATERIALS AND METHODS: 24 h electrocardiogram recordings were collected from 40 cirrhotic patients. Turbulence Onset was calculated as HRT indices. The enrolled patients were followed up for 12 months after the recruitment in relation to survival and/or transplantation. RESULTS: During the follow-up period, 21 patients (52.5%) survived, 12 patients (30%) died and 7 patients (17.5%) had liver transplantation. Turbulence Onset was found to be strongly linked with mortality on Cox regression (Hazard ratio = 1.351, p < 0.05). Moreover, Turbulence Onset predicted mortality independently of MELD and Child-Pugh's Score. CONCLUSION: This study provides further evidence of autonomic dysfunction in cirrhosis and suggests that HRT is reliable alternative to HRV in patients with PVCs.

Organ System Network Disruption Is Associated With Poor Prognosis in Patients With Chronic Liver Failure.

BACKGROUND: A healthy individual has a high degree of functional connectivity between organ systems, which can be represented graphically in a network map. Disruption of this system connectivity is associated with mortality in life-threatening acute illnesses, demonstrated by a network approach. However, this approach has not been applied to chronic multisystem diseases and may be more reliable than conventional individual organ prognostic scoring methods. Cirrhosis is a chronic disease of the liver with multisystem involvement. Development of an efficient model for prediction of mortality in cirrhosis requires a profound understanding of the pathophysiologic processes that lead to poor prognosis. In the present study, we use a network approach to evaluate the differences in organ system connectivity between survivors and non-survivors in a group of well-characterized patients with cirrhosis. METHODS: 201 patients with cirrhosis originally referred to the Clinic five at the University Hospital of Padova, with 13 clinical variables available representing hepatic, metabolic, haematopoietic, immune, neural and renal organ systems were retrospectively enrolled and followed up for 3, 6, and 12 months. Software was designed to compute the correlation network maps of organ system interaction in survivors and non-survivors using analysis indices: A. Bonferroni corrected Pearson's correlation coefficient and B. Mutual Information. Network structure was quantitatively evaluated using the measures of edges, average degree of connectivity and closeness, and qualitatively using clinical significance. Pair-matching was also implemented as a further step after initial general analysis to control for sample size and Model for End-Stage Liver Disease (MELD-Na) score between the groups. RESULTS: There was a higher number of significant correlations in survivors, as indicated by both the analysis indices of Bonferroni corrected Pearson's correlation coefficient and the Mutual Information analysis. The number of edges, average degree of connectivity and closeness were significantly higher in survivors compared to non-survivors group. Pair-matching for MELD-Na was also associated with increased connectivity in survivors compared to non-survivors over 3 and 6 months follow up. CONCLUSION: This study demonstrates the application of a network approach in evaluating functional connectivity of organ systems in liver cirrhosis, demonstrating a significant degree of network disruption in organ systems in non-survivors. Network analysis of organ systems may provide insight in developing novel prognostic models for organ allocation in patients with cirrhosis.

Skin temperature variability is an independent predictor of survival in patients with cirrhosis.

BACKGROUND: Cirrhosis is a disease with multisystem involvement. It has been documented that patients with cirrhosis exhibit abnormal patterns of fluctuation in their body temperature. However, the clinical significance of this phenomenon is not well understood. The aim of this study was to determine if temperature variability analysis can predict survival in patients with cirrhosis. METHODS: Thirty eight inpatients with cirrhosis were enrolled in the study. Wireless temperature sensors were used to record patients' proximal skin temperature for 24 hr. The pattern of proximal temperature fluctuation was assessed using the extended Poincaré plot to measure short-term and long-term proximal temperature variability (PTV). Patients were followed up for 12 months, and information was collected on the occurrence of death/liver transplantation. RESULTS: During the follow-up period, 15 patients (39%) died or underwent transplantation for hepatic decompensation. Basal proximal skin temperature absolute values were comparable in survivors and nonsurvivors. However, nonsurvivors showed a significant reduction in both short-term and long-term HRV indices. Cox regression analysis showed that both short-term and long-term PTV indices could predict survival in these patients. However, only measures of short-term PTV were shown to be independent of the severity of hepatic failure in predicting survival. Finally, the prognostic value of short-term PTV was also independent of heart rate variability, that is, a measure of autonomic dysfunction. CONCLUSION: Changes in the pattern of patients' temperature fluctuations, rather than their absolute values, hold key prognostic information, suggesting that impaired thermoregulation may play an important role in the pathophysiology of cirrhosis.

Investigation on the Stability of Random Vortices in an Ion Concentration Polarization Layer with Imposed Normal Fluid Flow.

While nanoscale electrokinetic studies based on ion concentration polarization has been actively researched recently, random vortices naturally occur, leading to significantly destabilize in laboratory experiments or practical applications. These random vortices agitate the fluid inside microchannels and let the sample molecules seriously leak out preventing them from being controlled. Therefore, several trials have been reported to regulate those uninvited fluctuations by fluid flow tangential to a nanoporous membrane. Indeed, the influence of normal flow should be studied since the mass transport happens in the normal direction to the membrane. Thus, in this work, the nonlinear influence of normal flow to the instability near ion-selective surface was investigated by fully-coupled direct numerical simulation using COMSOL Multiphysics. The investigation on the effect of normal flow revealed that a space charge layer plays a significant role in the onset and growth of instability. The normal flow from the reservoir into the ion-selective surface pushed the space charge layer and decreased the size of vortices. However, there existed a maximum point for the growth of instability. The squeeze of the space charge layer increased the gradient of ion concentration in the layer, which resulted in escalating the velocity of vortices. On the other hand, the normal flow from the ion-selective surface into the reservoir suppressed the instability by spreading ions in the expanding space charge layer, leading to the reduction of ion concentration delayed the onset of instability. These two different mechanisms rendered asymmetric transition of stability as a function of the Peclet number and applied voltage. Therefore, this investigation would help understand the growth of instability and control the inevitable random vortices for the inhibition of fluid-agitation and leakage.

Effects of Normobaric Hypoxia on Oxygen Saturation Variability.

Background: The study is the first to evaluate the effects of graded normobaric hypoxia on SpO2 variability in healthy individuals. Materials and Methods: Twelve healthy males (mean [standard deviation] age 22 [4] years) were exposed to four simulated environments (fraction of inspired oxygen [FIO2]: 0.12, 0.145, 0.17, and 0.21) for 45 minutes, in a balanced crossover design. Results: Sample entropy, a tool that quantifies the irregularity of pulse oximetry fluctuations, was used as a measure of SpO2 variability. SpO2 entropy increased as the FIO2 decreased, and there was a strong significant negative correlation between mean SpO2 and its entropy during hypoxic exposure (r = -0.841 to -0.896, p < 0.001). In addition, SpO2 sample entropy, but not mean SpO2, was correlated (r = 0.630-0.760, p < 0.05) with dyspnea in FIO2 0.17, 0.145, and 0.12 and importantly, SpO2 sample entropy at FIO2 0.17 was correlated with dyspnea at FIO2 0.145 (r = 0.811, p < 0.01). Conclusions: These findings suggest that SpO2 variability analysis may have the potential to be used in a clinical setting as a noninvasive measure to identify the negative sequelae of hypoxemia.

Neonatal Sepsis Alters the Excitability of Regular Spiking Cells in the Nucleus of the Solitary Tract in Rats.

OBJECTIVE: Sepsis is a leading cause of mortality and morbidity in infants. Although the measures of autonomic dysfunction (e.g., reduced heart rate variability) predict mortality in sepsis, the mechanism of sepsis-induced autonomic dysfunction has remained elusive. The nucleus of the solitary tract (NTS) is a vital structure for the integrated autonomic response to physiological challenges. In the present study we hypothesized that sepsis alters the excitability of NTS neurons in a rat model of neonatal sepsis (14-day-old rats). METHODS AND RESULTS: Sepsis was induced by intraperitoneal injection of cecal slurry (CS) in rat neonates. The presence of autonomic dysfunction was confirmed by observing a significant reduction in both short-term and long-term heart rate variably following CS injection. We investigated the effect of polymicrobial sepsis on the electrophysiological properties of the medial NTS neurons using a whole cell patch clamp recording. Our results showed that the resting membrane potential in regular spiking neurons was significantly less polarized in the septic group (-37.6 ±â€Š1.76 mv) when compared with the control group (-54.7 ±â€Š1.73 mv, P < 0.001). The number of spontaneous action potentials in the septic group was also significantly higher than the control group (P < 0.05). In addition, the frequency and amplitude of the spontaneous excitatory post synaptic potentials was significantly higher in neurons recorded in the septic group (P < 0.001). Interestingly, regular spiking cells in the CS group exhibited a rebound action potential following hyperpolarization. Injection of depolarizing currents was associated with lower first spike latency and changes in rise slope of action potential (P < 0.001). CONCLUSIONS: We showed that polymicrobial sepsis increases the excitability of regular spiking cells in the medial NTS. These alterations can potentially affect neural coding and thus may contribute to an abnormal homeostatic or allostatic physiological response to sepsis and systemic inflammation.