Identification of tissue optical properties during thermal laser-tissue interactions: An ensemble Kalman filter-based approach.

In this article, we propose a computational framework to estimate the physical properties that govern the thermal response of laser-irradiated tissue. We focus in particular on two quantities, the absorption and scattering coefficients, which describe the optical absorption of light in the tissue and whose knowledge is vital to correctly plan medical laser treatments. To perform the estimation, we utilize an implementation of the ensemble Kalman filter (EnKF), a type of Bayesian filtering algorithm for data assimilation. Unlike prior approaches, in this work, we estimate the tissue optical properties based on observations of the tissue thermal response to laser irradiation. This method has the potential for straightforward implementation in a clinical setup, as it would only require a simple thermal sensor, for example, a miniaturized infrared camera. Because the optical properties of tissue can undergo shifts during laser exposure, we employ a variant of EnKF capable of tracking time-varying parameters. Through simulated experimental studies, we demonstrate the ability of the proposed technique to identify the tissue optical properties and track their dynamic changes during laser exposure, while simultaneously tracking changes in the tissue temperature at locations beneath the surface. We further demonstrate the framework's capability in estimating additional unknown tissue properties (i.e., the volumetric heat capacity and thermal conductivity) along with the optical properties of interest.

Analyzing the effects of observation function selection in ensemble Kalman filtering for epidemic models.

The Ensemble Kalman Filter (EnKF) is a popular sequential data assimilation method that has been increasingly used for parameter estimation and forecast prediction in epidemiological studies. The observation function plays a critical role in the EnKF framework, connecting the unknown system variables with the observed data. Key differences in observed data and modeling assumptions have led to the use of different observation functions in the epidemic modeling literature. In this work, we present a novel computational analysis demonstrating the effects of observation function selection when using the EnKF for state and parameter estimation in this setting. In examining the use of four epidemiologically-inspired observation functions of different forms in connection with the classic Susceptible-Infectious-Recovered (SIR) model, we show how incorrect observation modeling assumptions (i.e., fitting incidence data with a prevalence model, or neglecting under-reporting) can lead to inaccurate filtering estimates and forecast predictions. Results demonstrate the importance of choosing an observation function that well interprets the available data on the corresponding EnKF estimates in several filtering scenarios, including state estimation with known parameters, and combined state and parameter estimation with both constant and time-varying parameters. Numerical experiments further illustrate how modifying the observation noise covariance matrix in the filter can help to account for uncertainty in the observation function in certain cases.

Modeling Microglia Activation and Inflammation-Based Neuroprotectant Strategies During Ischemic Stroke.

Neural inflammation immediately follows the onset of ischemic stroke. During this process, microglial cells can be activated into two different phenotypes: the M1 phenotype, which can worsen brain injury by producing pro-inflammatory cytokines; or the M2 phenotype, which can aid in long term recovery by producing anti-inflammatory cytokines. In this study, we formulate a nonlinear system of differential equations to model the activation of microglia post-ischemic stroke, which includes bidirectional switching between the microglia phenotypes, as well as the interactions between these cells and the cytokines that they produce. Further, we explore neuroprotectant-based modeling strategies to suppress the activation of the detrimental M1 phenotype, while promoting activation of the beneficial M2 phenotype. Through use of global sensitivity techniques, we analyze the effects of the model parameters on the ratio of M1 to M2 microglia and the total number of activated microglial cells in the system over time. Results demonstrate the significance of bidirectional microglia phenotype switching on the ratio of M1 to M2 microglia, in both the absence and presence of neuroprotectant terms. Simulations further suggest that early inhibition of M1 activation and support of M2 activation leads to a decreased minimum ratio of M1 to M2 microglia and allows for a larger number of M2 than M1 cells for a longer time period.

Evaluation of the effects of altitude on biological signatures of inflammation and anxiety- and depressive-like behavioral responses.

Over sixteen million people suffer from a depressive episode annually in the United States, with females affected at twice the rate of males. Little is known about the effects of exposure to high altitude on the risk of development of major depressive disorder, despite reports of higher suicide rates at higher altitudes. We hypothesize that exposure to hypobaric hypoxia at high altitude increases endophenotypes of self-directed suicidal violence, including biological signatures of chronic inflammation and vulnerability to anxiety-like and depressive-like behavioral responses in a sex-specific manner. Biological signatures of inflammation, including granulocyte:lymphocyte ratios, monocyte cell counts, and monocyte:lymphocyte ratios were assessed using complete blood count data, anhedonia, and anxiety- and depressive-like behavioral responses were evaluated. We assessed biological signatures of inflammation and behavioral responses in the open-field test, sucrose preference test, and modified Porsolt forced swim test in young adult male and female Long-Evans and Sprague Dawley rats. All tests were conducted near sea level (374 ft [114 m] elevation) and at moderate-high altitude (5430 ft [1655 m] elevation) during acclimation periods of one, two, three, four, and five weeks following shipment from a sea level animal breeding facility (N = 320, n = 8 per group). Exposure to moderate-high altitude induced a biological signature of increased inflammation, as evidenced by main effects of altitude for: 1) increased granulocyte:lymphocyte ratio; 2) increased count and relative abundance of circulating monocytes; and 3) increased monocyte:lymphocyte ratios. Exposure to moderate-high altitude also increased anhedonia as assessed in the sucrose preference test in both male and female rats, when data were collapsed across strain and time. Among male and female Long Evans rats, exposure to moderate-high altitude increased immobility in the forced swim test, without changing anxiety-like behaviors in the open-field test. Finally, granulocyte:lymphocyte ratios were correlated with anhedonia in the sucrose preference test. These data are consistent with the hypothesis that hypobaric hypoxia at moderate-high altitude induces persistent endophenotypes of self-directed suicidal violence including biological signatures of inflammation, anhedonia, and depressive-like behavioral responses.

Evaluation of the gut microbiome in association with biological signatures of inflammation in murine polytrauma and shock.

Severe injuries are frequently accompanied by hemorrhagic shock and harbor an increased risk for complications. Local or systemic inflammation after trauma/hemorrhage may lead to a leaky intestinal epithelial barrier and subsequent translocation of gut microbiota, potentially worsening outcomes. To evaluate the extent with which trauma affects the gut microbiota composition, we performed a post hoc analysis of a murine model of polytrauma and hemorrhage. Four hours after injury, organs and plasma samples were collected, and the diversity and composition of the cecal microbiome were evaluated using 16S rRNA gene sequencing. Although cecal microbial alpha diversity and microbial community composition were not found to be different between experimental groups, norepinephrine support in shock animals resulted in increased alpha diversity, as indicated by higher numbers of distinct microbial features. We observed that the concentrations of proinflammatory mediators in plasma and intestinal tissue were associated with measures of microbial alpha and beta diversity and the presence of specific microbial drivers of inflammation, suggesting that the composition of the gut microbiome at the time of trauma, or shortly after trauma exposure, may play an important role in determining physiological outcomes. In conclusion, we found associations between measures of gut microbial alpha and beta diversity and the severity of systemic and local gut inflammation. Furthermore, our data suggest that four hours following injury is too early for development of global changes in the alpha diversity or community composition of the intestinal microbiome. Future investigations with increased temporal-spatial resolution are needed in order to fully elucidate the effects of trauma and shock on the gut microbiome, biological signatures of inflammation, and proximal and distal outcomes.

Activity of Shoulder Stabilizers and Prime Movers During an Unstable Overhead Press.

Williams, MR Jr, Hendricks, DS, Dannen, MJ, Arnold, AM, and Lawrence, MA. Activity of shoulder stabilizers and prime movers during an unstable overhead press. J Strength Cond Res 34(1): 73-78, 2020-Overhead reaching is a common movement that relies heavily on muscles for dynamic stability. Stabilizer muscle activation increased during squatting and bench pressing with an unstable load, but the overhead press (OHP) has yet to be examined. The purpose of this study is to compare muscle activity of the shoulder stabilizers and prime movers and excursions of the center of pressure (CoP) during the OHP in 2 unstable and one stable conditions. Twelve men (aged 25.3 ± 2.7 years, mass: 91.5 ± 8.4 kg, height: 1.81 ± 0.06 m) pressed 50% of their 1 repetition maximum for 10 repetitions over 3 conditions: a straight stable barbell (SS), a straight unstable (SU) barbell with kettlebells suspend by elastic bands, and an unstable Earthquake (EU) bar with kettlebells suspended by elastic bands. Activity of the shoulder stabilizers and prime movers were measured via surface and indwelling electromyography. Center of pressure excursion of the right foot was also measured. A multivariate analysis was used to determine significant differences between conditions. Pressing with the EQ increased activation of the biceps brachii, erector spinae, latissimus dorsi, pectoralis major, rectus abdominus, rhomboids, and serratus anterior over the SS condition, whereas only the SU condition increased activation in the erector spinae and latissimus dorsi muscles. The EQ condition produced greater CoP excursion (35.3 ± 7.9% foot length) compared with the SU (28.0 ± 7.2% foot length) and SS (22.2 ± 6.3% foot length) conditions. Therefore, the EU condition may be an effective exercise to activate scapular stabilizers.

Practical identifiability and uncertainty quantification of a pulsatile cardiovascular model.

Mathematical models are essential tools to study how the cardiovascular system maintains homeostasis. The utility of such models is limited by the accuracy of their predictions, which can be determined by uncertainty quantification (UQ). A challenge associated with the use of UQ is that many published methods assume that the underlying model is identifiable (e.g. that a one-to-one mapping exists from the parameter space to the model output). In this study we present a novel workflow to calibrate a lumped-parameter model to left ventricular pressure and volume time series data. Key steps include using (1) literature and available data to determine nominal parameter values; (2) sensitivity analysis and subset selection to determine a set of identifiable parameters; (3) optimization to find a point estimate for identifiable parameters; and (4) frequentist and Bayesian UQ calculations to assess the predictive capability of the model. Our results show that it is possible to determine 5 identifiable model parameters that can be estimated to our experimental data from three rats, and that computed UQ intervals capture the measurement and model error.

Uncertainty Quantification in a Patient-Specific One-Dimensional Arterial Network Model: EnKF-Based Inflow Estimator.

Successful clinical use of patient-specific models for cardiovascular dynamics depends on the reliability of the model output in the presence of input uncertainties. For 1D fluid dynamics models of arterial networks, input uncertainties associated with the model output are related to the specification of vessel and network geometry, parameters within the fluid and wall equations, and parameters used to specify inlet and outlet boundary conditions. This study investigates how uncertainty in the flow profile applied at the inlet boundary of a 1D model affects area and pressure predictions at the center of a single vessel. More specifically, this study develops an iterative scheme based on the ensemble Kalman filter (EnKF) to estimate the temporal inflow profile from a prior distribution of curves. The EnKF-based inflow estimator provides a measure of uncertainty in the size and shape of the estimated inflow, which is propagated through the model to determine the corresponding uncertainty in model predictions of area and pressure. Model predictions are compared to ex vivo area and blood pressure measurements in the ascending aorta, the carotid artery, and the femoral artery of a healthy male Merino sheep. Results discuss dynamics obtained using a linear and a nonlinear viscoelastic wall model.

K-Ras and cyclooxygenase-2 coactivation augments intraductal papillary mucinous neoplasm and Notch1 mimicking human pancreas lesions.

Mutational activation of K-Ras is an initiating event of pancreatic ductal adenocarcinomas (PDAC) that may develop either from pancreatic intraepithelial neoplasia (PanIN) or intraductal papillary mucinous neoplasms (IPMN). Cyclooxygenase-2 (COX-2)-derived prostaglandin E2 (PGE2) is causally related to pancreatic carcinogenesis. Here, we deciphered the impact of COX-2, a key modulator of inflammation, in concert with active mutant K-Ras(G12D) on tumor burden and gene expression signature using compound mutant mouse lines. Concomitant activation of COX-2 and K-Ras(G12D) accelerated the progression of pancreatic intraepithelial lesions predominantly with a cystic papillary phenotype resembling human IPMN. Transcriptomes derived from laser capture microdissected preneoplastic lesions of single and compound mutants revealed a signature that was significantly enriched in Notch1 signaling components. In vitro, Notch1 signaling was COX-2-dependent. In line with these findings, human IPMN stratified into intestinal, gastric and pancreatobillary types displayed Notch1 immunosignals with high prevalence, especially in the gastric lesions. In conclusion, a yet unknown link between activated Ras, protumorigenic COX-2 and Notch1 in IPMN onset was unraveled.

Astrocytic tracer dynamics estimated from [1-¹¹C]-acetate PET measurements.

We address the problem of estimating the unknown parameters of a model of tracer kinetics from sequences of positron emission tomography (PET) scan data using a statistical sequential algorithm for the inference of magnitudes of dynamic parameters. The method, based on Bayesian statistical inference, is a modification of a recently proposed particle filtering and sequential Monte Carlo algorithm, where instead of preassigning the accuracy in the propagation of each particle, we fix the time step and account for the numerical errors in the innovation term. We apply the algorithm to PET images of [1-¹¹C]-acetate-derived tracer accumulation, estimating the transport rates in a three-compartment model of astrocytic uptake and metabolism of the tracer for a cohort of 18 volunteers from 3 groups, corresponding to healthy control individuals, cirrhotic liver and hepatic encephalopathy patients. The distribution of the parameters for the individuals and for the groups presented within the Bayesian framework support the hypothesis that the parameters for the hepatic encephalopathy group follow a significantly different distribution than the other two groups. The biological implications of the findings are also discussed.

Preinvasive duct-derived neoplasms in pancreas of keratin 5-promoter cyclooxygenase-2 transgenic mice.

BACKGROUND & AIMS: Basic research aimed at a better understanding of pancreatic carcinogenesis and improving the treatment of this disease is crucial because the majority of pancreatic cancers are highly aggressive and therapeutically nonaccessible. Cyclooxygenase (COX)-2, which is a key enzyme of prostaglandin (PG) biosynthesis, is overexpressed in around 75% of human carcinomas including those of the pancreas. METHODS: The pathologic changes of transgenic mouse pancreas with keratin 5-promoter-driven expression and activity of COX-2 were characterized. RESULTS: Aberrant expression of COX-2 in a few ductal cells and COX-2-mediated PG synthesis in the transgenic mice resulted in keratin 19- and mucin-positive intraductal papillary mucinous neoplasm- and pancreatic intraepithelial neoplasia-like structures, characterized by an increased proliferation index and serous cystadenomas. Moreover, Ras activation was enhanced and the HER-2/Neu receptor was overexpressed. Loss of acini, fibrosis, and inflammation were pronounced. Feeding a COX-2-selective inhibitor to the transgenic mice suppressed the accumulation of PG and the phenotype. The changes resemble the human disease in which COX-2 was overexpressed consistently. CONCLUSIONS: We present strong evidence for a causal relationship between aberrant COX-2 overexpression and COX-2-mediated PG synthesis and the development of serous cystadenoma, intraductal papillary mucinous, and pancreatic intraepithelial neoplasms. This model offers the unique possibility of identifying molecular pathways leading to the formation and malignant progression of the various types of preinvasive lesions of pancreatic adenocarcinomas that show different dismal outcomes.