RPEM: Randomized Monte Carlo parametric expectation maximization algorithm.

Inspired from quantum Monte Carlo, by sampling discrete and continuous variables at the same time using the Metropolis-Hastings algorithm, we present a novel, fast, and accurate high performance Monte Carlo Parametric Expectation Maximization (MCPEM) algorithm. We named it Randomized Parametric Expectation Maximization (RPEM). We compared RPEM with NONMEM's Importance Sampling Method (IMP), Monolix's Stochastic Approximation Expectation Maximization (SAEM), and Certara's Quasi-Random Parametric Expectation Maximization (QRPEM) for a realistic two-compartment voriconazole model with ordinary differential equations using simulated data. We show that RPEM is as fast and as accurate as the algorithms IMP, QRPEM, and SAEM for the voriconazole model in reconstructing the population parameters, for the normal and log-normal cases.

Individuals with higher suicide risk showed more anger and disgust during rest.

Previous research showed that suicide risk was associated with the anger trait and the facial expression of anger when advising on life dilemmas. We investigated if suicide risk was associated with the facial expression of anger during rest, a state when individuals often reflect upon their lives. Participants took a 1-min rest before being assessed for suicide risk. We measured 147 participants' frontal-view facial expressions during their rest 1475-3694 times using automated facial expression analysis technology. Participants' suicide risk was significantly positively correlated with their anger and disgust during the rest, which may be related to psychological pain and death-related thoughts among individuals with suicide risk. Therefore, rest for clinical patients should not be seen simply as a "rest" for the mind. Rather, for counselors, rest may open a window to look into patients' inner thoughts that may be important to their lives.

Global, region and national trends and age-period-cohort effects in colorectal cancer burden from 1990 to 2019, with predictions to 2039.

Nowadays, colorectal cancer (CRC) is the second leading cause of cancer deaths and contributes to a gradually increasing disease burden. We aimed to estimate the secular trends of global CRC burden, the effect of age, period, and birth cohort, and project the global burden over time. Based on the epidemiological CRC data from 1990 to 2019 in 204 countries and territories from GBD 2019, the estimated annual percentage change (EAPC), was calculated from a linear model and joinpoint regression model. We utilized an age-period-cohort model to reckon age, period, and birth cohort effects on CRC age-standardized rate. The burden of CRC was projected by conducting the BAPC model. Globally, there was a slight decline in the age-standardized DALY rate, which was more apparent in females, with high SDI regions and in Australia and Western Europe areas. Meanwhile, our model predicts a weaker increase in morbidity (EAPC of 0.37) and a speedier reduction in mortality (EAPC of -0.66) by the next 20 years. The relative risk of period for high SDI regions decreased from 1.08 (95%UI: 1.06-1.1) in 1990-1994 to 0.85 (95%UI:0.83-0.88) in 2015-2019, but worsens in low and middle SDI regions. The local drifts were more than 1 in the 30-34 and 35-39 age groups, indicating the rising tide of early-onset CRC. Given the gender and region-specific CRC, targeted efforts to reduce the prevalence of risk factors, improve screening coverage rates, and strengthen foundational medical facilities are necessary.

Effectiveness of Arbidol for COVID-19 Prevention in Health Professionals.

Background: Frontline health professionals are a COVID-19-susceptible population during the outbreak of COVID-19, but prophylactic drugs against SARS-CoV-2 infection are to be explored. Method: Frontline health professionals diagnosed with COVID-19 before February 9, 2020 in Tongji Hospital, Wuhan, China and the same amount of controls in the uninfected group were included in this study. Clinical and laboratory data were collected with standardized forms. Results: A total of 164 subjects were included in this study, 82 cases in the infected group and 82 controls in the uninfected group, with a median age of 37 years, including 63 males and 101 females. Nineteen (23.2%) patients in the infected group were administered oral arbidol, and 48 (58.5%) in the uninfected group (OR = 0.214, 95% CI 0.109-0.420). The cumulative uninfected rate of health professionals in the arbidol group was significantly higher than that of individuals in the non-arbidol group (log-rank test, χ2 = 98.74; P < 0.001). Forty-eight patients (58.5%) in the infection group were hospitalized, with a median age of 39 (31-49) years, of whom 7 (14.6%) were prophylactically administered arbidol. Thirty-four patients (41.5%) with mild symptoms were treated outside the hospital, among which the median age was 34 (30-39) years, and twelve patients (35.3%) took prophylactic oral arbidol. The hospitalization rate was significantly associated with age (P = 0.024) and oral arbidol administration (OR = 0.313, 95% CI 0.108-0.909). In the age-matched case-control study, the hospitalization rate was not significantly associated with arbidol administration (P = 0.091). Conclusion: Prophylactic oral arbidol was associated with a lower incidence of SARS-CoV-2 infection but not hospitalization rate in health professionals, providing a basis for the selection of prophylactic drugs for high-risk populations.

Clinical characteristics of 80 hospitalized frontline medical workers infected with COVID-19 in Wuhan, China.

More than 1,000 medical workers have been infected with COVID-19 in China. The 80 hospitalized patients included 57 SARS-CoV-2 confirmed and 23 clinically diagnosed. The median age was 39 years, 49 (61.25%) were women, and one patient died. The most common symptoms at onset were fever (65, 81.25%), cough (47, 58.75%), fatigue (28, 35%), myalgia (19, 23.75%), expectoration (19, 23.75%), and diarrhea (15, 18.75%). Patients of frontline medical workers at a single-center hospital showed some unique clinical and laboratory findings compared with other patients in Wuhan and outside of Wuhan. This study provides our experience for other frontline medical workers.

Quantifying the influence of temperature on hand, foot and mouth disease incidence in Wuhan, Central China.

Hand, foot and mouth disease (HFMD) is a substantial burden throughout Asia, but the effects of temperature pattern on HFMD risk are inconsistent. To quantify the effect of temperature on HFMD incidence, Wuhan was chosen as the study site because of its high temperature variability and high HFMD incidence. Daily series of HFMD counts and meteorological variables during 2010-2015 were obtained. Distributed lag non-linear models were applied to characterize the temperature-HFMD relationship and to assess its variability across different ages, genders, and types of child care. Totally, 80,219 patients of 0-5 years experienced HFMD in 2010-2015 in Wuhan. The cumulative relative risk of HFMD increased linearly with temperature over 7 days (lag0-7), while it presented as an approximately inverted V-shape over 14 days (lag0-14). The cumulative relative risk at lag0-14 peaked at 26.4 °C with value of 2.78 (95%CI: 2.08-3.72) compared with the 5th percentile temperature (1.7 °C). Subgroup analyses revealed that children attended daycare were more vulnerable to temperature variation than those cared for at home. This study suggests that public health actions should take into consideration local weather conditions and demographic characteristics.

Evaluation of performance of distributed delay model for chemotherapy-induced myelosuppression.

The distributed delay model has been introduced that replaces the transit compartments in the classic model of chemotherapy-induced myelosuppression with a convolution integral. The maturation of granulocyte precursors in the bone marrow is described by the gamma probability density function with the shape parameter (ν). If ν is a positive integer, the distributed delay model coincides with the classic model with ν transit compartments. The purpose of this work was to evaluate performance of the distributed delay model with particular focus on model deterministic identifiability in the presence of the shape parameter. The classic model served as a reference for comparison. Previously published white blood cell (WBC) count data in rats receiving bolus doses of 5-fluorouracil were fitted by both models. The negative two log-likelihood objective function (-2LL) and running times were used as major markers of performance. Local sensitivity analysis was done to evaluate the impact of ν on the pharmacodynamics response WBC. The ν estimate was 1.46 with 16.1% CV% compared to ν = 3 for the classic model. The difference of 6.78 in - 2LL between classic model and the distributed delay model implied that the latter performed significantly better than former according to the log-likelihood ratio test (P = 0.009), although the overall performance was modestly better. The running times were 1 s and 66.2 min, respectively. The long running time of the distributed delay model was attributed to computationally intensive evaluation of the convolution integral. The sensitivity analysis revealed that ν strongly influences the WBC response by controlling cell proliferation and elimination of WBCs from the circulation. In conclusion, the distributed delay model was deterministically identifiable from typical cytotoxic data. Its performance was modestly better than the classic model with significantly longer running time.

A distributed delay approach for modeling delayed outcomes in pharmacokinetics and pharmacodynamics studies.

A distributed delay approach was proposed in this paper to model delayed outcomes in pharmacokinetics and pharmacodynamics studies. This approach was shown to be general enough to incorporate a wide array of pharmacokinetic and pharmacodynamic models as special cases including transit compartment models, effect compartment models, typical absorption models (either zero-order or first-order absorption), and a number of atypical (or irregular) absorption models (e.g., parallel first-order, mixed first-order and zero-order, inverse Gaussian, and Weibull absorption models). Real-life examples were given to demonstrate how to implement distributed delays in Phoenix® NLME™ 8.0, and to numerically show the advantages of the distributed delay approach over the traditional methods.

In vivo investigation of tissue-engineered periosteum for the repair of allogeneic critical size bone defects in rabbits.

AIM: The aim of the study was to evaluate the efficacy of tissue-engineered periosteum (TEP) in repairing allogenic bone defects in the long term. MATERIALS & METHODS: TEP was biofabricated with osteoinduced rabbit bone marrow mesenchymal stem cells and porcine small intestinal submucosa (SIS). A total of 24 critical sized defects were created bilaterally in radii of 12 New Zealand White rabbits. TEP/SIS was implanted into the defect site. Bone defect repair was evaluated with radiographic and histological examination at 4, 8 and 12 weeks. RESULTS: Bone defects were structurally reconstructed in the TEP group with mature cortical bone and medullary canals, however this was not observed in the SIS group at 12 weeks. CONCLUSION: The TEP approach can effectively restore allogenic critical sized defects, and achieve maturity of long-bone structure in 12 weeks in rabbit models.

A Dynamical Modeling Approach for Analysis of Longitudinal Clinical Trials in the Presence of Missing Endpoints.

Randomized longitudinal clinical trials are the gold standard to evaluate the effectiveness of interventions among different patient treatment groups. However, analysis of such clinical trials becomes difficult in the presence of missing data, especially in the case where the study endpoints become difficult to measure because of subject dropout rates or/and the time to discontinue the assigned interventions are different among the patient groups. Here we report on using a validated mathematical model combined with an inverse problem approach to predict the values for the missing endpoints. A small randomized HIV clinical trial where endpoints for most of patients are missing is used to demonstrate this approach.

Modeling Immune Response to BK Virus Infection and Donor Kidney in Renal Transplant Recipients.

In this paper we develop and validate with bootstrapping techniques a mechanistic mathematical model of immune response to both BK virus infection and a donor kidney based on known and hypothesized mechanisms in the literature. The model presented does not capture all the details of the immune response but possesses key features that describe a very complex immunological process. We then estimate model parameters using a least squares approach with a typical set of available clinical data. Sensitivity analysis combined with asymptotic theory is used to determine the number of parameters that can be reliably estimated given the limited number of observations.

Immuno-modulatory strategies for reduction of HIV reservoir cells.

Antiretroviral therapy is able to suppress the viral load to below the detection limit, but it is not able to eradicate HIV reservoirs. Thus, there is a critical need for a novel treatment to eradicate (or reduce) the reservoir in order to eliminate the need for a lifelong adherence to antiretroviral therapy, which is expensive and potentially toxic. In this paper, we investigate the possible pharmacological strategies or combinations of strategies that may be beneficial to reduce or possibly eradicate the latent reservoir. We do this via studies with a validated mathematical model, where the parameter values are obtained with newly acquired clinical data for HIV patients. Our findings indicate that the strategy of reactivating the reservoir combined with enhancement of the killing rate of HIV-specific CD8+ T cells is able to eradicate the reservoir. In addition, our analysis shows that a targeted suppression of the immune system is also a possible strategy to eradicate the reservoir.

Model validation for a noninvasive arterial stenosis detection problem.

A current thrust in medical research is the development of a non-invasive method for detection, localization, and characterization of an arterial stenosis (a blockage or partial blockage in an artery). A method has been proposed to detect shear waves in the chest cavity which have been generated by disturbances in the blood flow resulting from a stenosis. In order to develop this methodology further, we use one-dimensional shear wave experimental data from novel acoustic phantoms to validate a corresponding viscoelastic mathematical model. We estimate model parameters which give a good fit (in a sense to be precisely defined) to the experimental data, and use asymptotic error theory to provide confidence intervals for parameter estimates. Finally, since a robust error model is necessary for accurate parameter estimates and confidence analysis, we include a comparison of absolute and relative models for measurement error.

High-order space-time finite element schemes for acoustic and viscodynamic wave equations with temporal decoupling.

We revisit a method originally introduced by Werder et al. (in Comput. Methods Appl. Mech. Engrg., 190:6685-6708, 2001) for temporally discontinuous Galerkin FEMs applied to a parabolic partial differential equation. In that approach, block systems arise because of the coupling of the spatial systems through inner products of the temporal basis functions. If the spatial finite element space is of dimension D and polynomials of degree r are used in time, the block system has dimension (r + 1)D and is usually regarded as being too large when r > 1. Werder et al. found that the space-time coupling matrices are diagonalizable over [Formula: see text] for r ⩽100, and this means that the time-coupled computations within a time step can actually be decoupled. By using either continuous Galerkin or spectral element methods in space, we apply this DG-in-time methodology, for the first time, to second-order wave equations including elastodynamics with and without Kelvin-Voigt and Maxwell-Zener viscoelasticity. An example set of numerical results is given to demonstrate the favourable effect on error and computational work of the moderately high-order (up to degree 7) temporal and spatio-temporal approximations, and we also touch on an application of this method to an ambitious problem related to the diagnosis of coronary artery disease. Copyright © 2014 The Authors. International Journal for Numerical Methods in Engineering published by John Wiley & Sons Ltd.

Rapid and sensitive liquid chromatography-tandem mass spectrometry method for determination of 1-ß-d-arabinofuranosyluracil in human plasma and application to therapeutic drug monitoring in patient with leukemia.

A specific and reliable HPLC-MS/MS method was developed and validated for the determination of ara-U in human plasma. The analyte was separated on a C18 column (50 mm × 2.1mm, 1.7 µm) and a triple-quadrupole mass spectrometry equipped with an electrospray ionization (ESI) source was applied for detection. The plasma sample was prepared by a simple protein precipitation pretreatment and the recovery was about 80%. The calibration curves were linear over a concentration range of 1.0-7000.0 ng/mL for ara-U. The intra-day and inter-day precision was less than 15% and the relative error (RE) was all within ± 15%. It was successfully applied to assess the disposition characteristics of ara-U and support the therapeutic drug monitoring after the patients with leukemia were infused with ara-C.

Modelling and optimal control of immune response of renal transplant recipients.

We consider the increasingly important and highly complex immunological control problem: control of the dynamics of immunosuppression for organ transplant recipients. The goal in this problem is to maintain the delicate balance between over-suppression (where opportunistic latent viruses threaten the patient) and under-suppression (where rejection of the transplanted organ is probable). First, a mathematical model is formulated to describe the immune response to both viral infection and introduction of a donor kidney in a renal transplant recipient. Some numerical results are given to qualitatively validate and demonstrate that this initial model exhibits appropriate characteristics of primary infection and reactivation for immunosuppressed transplant recipients. In addition, we develop a computational framework for designing adaptive optimal treatment regimes with partial observations and low-frequency sampling, where the state estimates are obtained by solving a second deterministic optimal tracking problem. Numerical results are given to illustrate the feasibility of this method in obtaining optimal treatment regimes with a balance between under-suppression and over-suppression of the immune system.

A comparison of computational efficiencies of stochastic algorithms in terms of two infection models.

In this paper, we investigate three particular algorithms: a stochastic simulation algorithm (SSA), and explicit and implicit tau-leaping algorithms. To compare these methods, we used them to analyze two infection models: a Vancomycin-resistant enterococcus (VRE) infection model at the population level, and a Human Immunodeficiency Virus (HIV) within host infection model. While the first has a low species count and few transitions, the second is more complex with a comparable number of species involved. The relative efficiency of each algorithm is determined based on computational time and degree of precision required. The numerical results suggest that all three algorithms have the similar computational efficiency for the simpler VRE model, and the SSA is the best choice due to its simplicity and accuracy. In addition, we have found that with the larger and more complex HIV model, implementation and modification of tau-Leaping methods are preferred.

Nonlinear stochastic Markov processes and modeling uncertainty in populations.

We consider an alternative approach to the use of nonlinear stochastic Markov processes (which have a Fokker-Planck or Forward Kolmogorov representation for density) in modeling uncertainty in populations. These alternate formulations, which involve imposing probabilistic structures on a family of deterministic dynamical systems, are shown to yield pointwise equivalent population densities. Moreover, these alternate formulations lead to fast efficient calculations in inverse problems as well as in forward simulations. Here we derive a class of stochastic formulations for which such an alternate representation is readily found.

Host immune responses that promote initial HIV spread.

The host inflammatory response to HIV invasion is a necessary component of the innate antiviral activity that vaccines and early interventions seek to exploit/enhance. However, the response is dependent on CD4+ T-helper cell 1 (Th1) recruitment and activation. It is this very recruitment of HIV-susceptible target cells that is associated with the initial viral proliferation. Hence, global enhancement of the inflammatory response by T-cells and dendritic cells will likely feed viral propagation. Mucosal entry sites contain inherent pathways, in the form of natural regulatory T-cells (nTreg), that globally dampen the inflammatory response. We created a model of this inflammatory response to virus as well as inherent nTreg-mediated regulation of Th1 recruitment and activation. With simulations using this model we sought to address the net effect of nTreg activation and its specific functions as well as identify mechanisms of the natural inflammatory response that are best targeted to inhibit viral spread without compromising initial antiviral activity. Simulation results provide multiple insights that are relevant to developing intervention strategies that seek to exploit natural immune processes: (i) induction of the regulatory response through nTreg activation expedites viral proliferation due to viral production by nTreg itself and not to reduced Natural Killer (NK) cell activity; (ii) at the same time, induction of the inflammation response through either DC activation or Th1 activation expedites viral proliferation; (iii) within the inflammatory pathway, the NK response is an effective controller of viral proliferation while DC-mediated stimulation of T-cells is a significant driver of viral proliferation; and (iv) nTreg-mediated DC deactivation plays a significant role in slowing viral proliferation by inhibiting T-cell stimulation, making this function an aide to the antiviral immune response.

A comparison of nonlinear filtering approaches in the context of an HIV model.

In this paper three different filtering methods, the Extended Kalman Filter (EKF), the Gauss-Hermite Filter (GHF), and the Unscented Kalman Filter (UKF), are compared for state-only and coupled state and parameter estimation when used with log state variables of a model of the immunologic response to the human immunodeficiency virus (HIV) in individuals. The filters are implemented to estimate model states as well as model parameters from simulated noisy data, and are compared in terms of estimation accuracy and computational time. Numerical experiments reveal that the GHF is the most computationally expensive algorithm, while the EKF is the least expensive one. In addition, computational experiments suggest that there is little difference in the estimation accuracy between the UKF and GHF. When measurements are taken as frequently as every week to two weeks, the EKF is the superior filter. When measurements are further apart, the UKF is the best choice in the problem under investigation.