Mathematical model for glutathione dynamics in the retina

The retina is highly susceptible to the generation of toxic reactive oxygen species (ROS) that disrupt the normal operations of retinal cells. The glutathione (GSH) antioxidant system plays an important role in mitigating ROS. To perform its protective functions, GSH depends on nicotinamide adenine dinucleotide phosphate (NADPH) produced through the pentose phosphate pathway. This work develops the first mathematical model for the GSH antioxidant system in the outer retina, capturing the most essential components for formation of ROS, GSH production, its oxidation in detoxifying ROS, and subsequent reduction by NADPH. We calibrate and validate the model using experimental measurements, at different postnatal days up to PN28, from control mice and from the rd1 mouse model for the disease retinitis pigmentosa (RP). Global sensitivity analysis is then applied to examine the model behavior and identify the pathways with the greatest impact in control compared to RP conditions. The findings underscore the importance of GSH and NADPH production in dealing with oxidative stress during retinal development, especially after peak rod degeneration occurs in RP, leading to increased oxygen tension. This suggests that stimulation of GSH and NADPH synthesis could be a potential intervention strategy in degenerative mouse retinas with RP.

Data assimilation of synthetic data as a novel strategy for predicting disease progression in alopecia areata

The goal of patient-specific treatment of diseases requires a connection between clinical observations with models that are able to accurately predict the disease progression. Even when realistic models are available, it is very difficult to parameterize them and often parameter estimates that are made using early time course data prove to be highly inaccurate. Inaccuracies can cause different predictions, especially when the progression depends sensitively on the parameters. In this study, we apply a Bayesian data assimilation method, where the data are incorporated sequentially, to a model of the autoimmune disease alopecia areata that is characterized by distinct spatial patterns of hair loss. Using synthetic data as simulated clinical observations, we show that our method is relatively robust with respect to variations in parameter estimates. Moreover, we compare convergence rates for parameters with different sensitivities, varying observational times and varying levels of noise. We find that this method works better for sparse observations, sensitive parameters and noisy observations. Taken together, we find that our data assimilation, in conjunction with our biologically inspired model, provides directions for individualized diagnosis and treatments.

A physiological model of the inflammatory-thermal-pain-cardiovascular interactions during an endotoxin challenge

KEY POINTS

Inflammation in response to bacterial endotoxin challenge impacts physiological functions, including cardiovascular, thermal and pain dynamics, although the mechanisms are poorly understood. We develop an innovative mathematical model incorporating interaction pathways between inflammation and physiological processes observed in response to an endotoxin challenge. We calibrate the model to individual data from 20 subjects in an experimental study of the human inflammatory and physiological responses to endotoxin, and we validate the model against human data from an independent study. Using the model to simulate patient responses to different treatment modalities reveals that a multimodal treatment combining several therapeutic strategies gives the best recovery outcome.

ABSTRACT

Uncontrolled, excessive production of pro-inflammatory mediators from immune cells and traumatized tissues can cause systemic inflammatory conditions such as sepsis, one of the ten leading causes of death in the USA, and one of the three leading causes of death in the intensive care unit. Understanding how inflammation affects physiological processes, including cardiovascular, thermal and pain dynamics, can improve a patient's chance of recovery after an inflammatory event caused by surgery or a severe infection. Although the effects of the autonomic response on the inflammatory system are well-known, knowledge about the reverse interaction is lacking. The present study develops a mathematical model analyzing the inflammatory system's interactions with thermal, pain and cardiovascular dynamics in response to a bacterial endotoxin challenge. We calibrate the model with individual data from an experimental study of the inflammatory and physiological responses to a one-time administration of endotoxin in 20 healthy young men and validate it against data from an independent endotoxin study. We use simulation to explore how various treatments help patients exposed to a sustained pathological input. The treatments explored include bacterial endotoxin adsorption, antipyretics and vasopressors, as well as combinations of these. Our findings suggest that the most favourable recovery outcome is achieved by a multimodal strategy, combining all three interventions to simultaneously remove endotoxin from the body and alleviate symptoms caused by the immune system as it fights the infection.

A study on early-onset neonatal group B streptococcal infection, Bulgaria, 2007-2011

This study examines neonatal group B streptococcal (GBS) colonization and its relation to early-onset GBS disease (EOGBSD), based upon the experience of leading obstetrics and gynecology centers in Bulgaria. The objectives of the study were to update neonatal colonization rates and to assess relationships between clinically differentiated cases (culture-proven GBS newborns) and risk factors inherent to the infant and mother, using a computerized file. The neonatal GBS colonization rate ranged from 5.48 to 12.19 per 1000 live births. Maternal-fetal infection (MFI, a provisional clinical diagnosis in culture-proven colonized infants with initial signs of infection that is usually overcome with antibiotic treatment) and/or intrapartum asphyxia (IA) have been demonstrated as the most frequent clinical manifestations, with significant correlations for the primary diagnosis, but not affirmative for the final diagnosis at discharge, resulting from adequate treatment of neonates. MFI and IA were significantly related to prematurity, and reciprocally, prematurity was associated with the risk of MFI, indirectly suggesting that preterm birth or PPROM (preterm premature rupture of membranes, an obstetric indication associated with early labor and delivery, one of the major causes of preterm birth) is a substantial risk factor for EOGBSD. The regression analysis indicated that in the case of a newborn with MFI, a birth weight 593.58 g lower than the birth weight of an infant without this diagnosis might be expected. Testing the inverse relationship, i.e., the way birth weight influences a certain diagnosis (logistic regression) established the presence of a relationship between birth weight categories (degree of prematurity) and the diagnosis of MFI. The proportions and odds ratios, converted into probabilities that a baby would develop MFI, indicate the particularly high risk for newborns with extremely low and very low birth weight: extremely low birth weight (≤1000 g), the probability of developing a MFI is 66%; very low birth weight (1001-1500 g), 81%; low birth weight (the birth weight category including premature and small for gestational age term infants: 1501-2500 g), 40%; normal birth weight (term infants) (>2500 g), 32%. In conclusion, the need to introduce separate categories for early- and late-onset GBS disease in the registration nomenclature of neonatal infectious diseases is highlighted by these results. Drawing up intrapartum antibiotic prophylaxis (IAP) guidelines is also strongly recommended.

[A study on early-onset group "B" streptococcal neonatal infection]

The results achieved with 80% reduction in the incidence of early-onset neonatal group B streptococcal (GBS) sepsis following the implementation of the preliminary (1996, 2002) and subsequently the revised (2010) guidelines for intrapartum antibiotic prophylaxis imposed the discussion on a large scale of the updated:--algorithms for GBS screening (35-37 weeks of gestation) with the recommended dosage of penicillin-G for intrapartum antibiotic prophylaxis for women having normal labor and delivery;--algorithms for GBS screening and intrapartum antibiotic prophylaxis for women with preterm labor (PPROM) or premature rupture of membranes (PROM);--intrapartum antibiotic prophylaxis regimens for women with penicillin allergy;--algorithm for management of newborns with respect to risk of early-onset GBS disease. The present study is aimed at studying the distribution of the early-onset GBS disease in our country based on the data of leading obstetrics & gynecology clinics and wards. The aim is to diferrentiate clinically the cases and investigate the influence of the known risk factors on the part of the mother. A special accent is put over the microbiological diagnostics of cases in view of CDC expanded recommendations on the laboratory methods for identification of GBS. As a final conclusion the necessity for introduction of an official registration of the early- and late-onset GBS disease in the country is emphasized.

[A comparative study of the prognostic pH values of the fetus in utero, generated by the "quantitative cardiotocography" computer method, and the actual pH values measured immediately after delivery]

INTRODUCTION

The presented methodology for quantitative evaluation of the cardiotocographic (CTG) findings unconditionally provides essential opportunities for improving the diagnostic potential in modern obstetric practice. Current literature data concerning the clinical application of this method are scarce. Credible clinical trials are needed to determine what is the correlation between estimated and actual values of the studied variables.

MATERIALS AND METHODS

A prospective study on 110 pregnant women was performed. All patients were monitored via indirect cardiotocography. The recordings were stored and analyzed by the computerized method for "quantitative cardiotocography". We compared the last prognostic fetal pH value, generated by the "quantitative cardiotocography" software during labor, with the actual pH measured from the umbilical artery (UA) of the newborn.

RESULTS

For each of the stored CTG recordings we quantified the difference between the last forecast and the actual pH of the newborn. In 82% of these cases this difference was in range of -0081/+0074 from the projected results. However during the study we discovered that there is a significantly better correlation between the arithmetic average of the last 6 (six) predicted results and the actual pH of the newborn. In 85% of these cases the difference between forecast and actual pH values lies a in range of -0037/+0046.

CONCLUSION

Using the arithmetic average of the last 6 (six) predicted results for pH leads to a significant increase in the clinical value of the "quantitative cardiotocography". More studied are needed if we are to find opportunities to further reduce the existing prediction variability.