A data-driven analysis on the mediation effect of compartment models between control measures and COVID-19 epidemics.

By collecting various control policies taken by 127 countries/territories during the first wave of COVID-19 pandemic until July 2nd, 2020, we evaluate their impacts on the epidemic dynamics quantitatively through a combination of the multiple linear regression, neural-network-based nonlinear regression and sensitivity analysis. Remarkable differences in the public health policies are observed across these countries, which affect the spreading rate and infected population size to a great extent. Several key dynamical features, like the normalized cumulative numbers of confirmed/cured/death cases on the 100th day and the half time, show statistically significant linear correlations with the control measures, which thereby confirms their dramatic impacts. Most importantly, we perform the mediation analysis on the SEIR-QD model, a representative of general compartment models, by using the structure equation modeling for multiple mediators operating in parallel. This, to the best of our knowledge, is the first of its kind in the field of epidemiology. The infection rate and the protection rate of the SEIR-QD model are confirmed to exhibit a statistically significant mediation effect between the control measures and dynamical features of epidemics. The mediation effect along the pathway from control measures in Category 2 to four dynamical features through the infection rate, highlights the crucial role of nucleic acid testing and suspected cases tracing in containing the spread of the epidemic. Our data-driven analysis offers a deeper insight into the inherent correlations between the effectiveness of public health policies and the dynamic features of COVID-19 epidemics.

SIMPLIFIED IMMUNE-DYSREGULATION INDEX: A NOVEL MARKER PREDICTS 28-DAY MORTALITY OF INTENSIVE CARE PATIENTS WITH SEPSIS.

ABSTRACT: Background: Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection. There is currently no simple immune-imbalance-driven indicator for patients with sepsis. Methods: This study was conducted in Peking Union Medical College Hospital. Patients with sepsis were identified according to Sepsis 3.0 after reviewing patient data from May 2018 through October 2022. Least absolute shrinkage and selection operator logistic regression was used for features selection. Receiver operating characteristic curves for 28-day mortality were used to compare the predictive performance of level of interleukin 6 (IL-6) and lymphocyte count (LY#) with that of the combined ratio, namely, the IL-6/LY# ratio. A Cox hazard model was also used to test the predictive performance of IL-6/LY# versus several other measurements. The dynamic trend of IL-6/LY# based on day 1 IL-6/LY# level was analyzed. Results: The mortality rate was 24.5% (220/898) in the study cohort. The LY#, IL-6 level, blood platelet count, Sequential Organ Failure Assessment score, Acute Physiology and Chronic Health Evaluation II score, heart rate, age and Fi o2 level were identified as key factors for predicting 28-day mortality. IL-6/LY# was identified as a core indicator according to Least absolute shrinkage and selection operator logistic regression analysis. IL-6/LY# was significantly higher in nonsurvivors than in survivors (348 [154.6-1371.7] vs. 42.3 [15.4-117.1]). IL-6/LY# yielded a higher area under the curve (0.852 [95% CI = 0.820-0.879]) than the level of IL-6 (0.776 [95% CI = 0.738-0.809]) and LY# (0.719 [95% CI = 0.677-0.755]) separately. Survival analysis of mortality risk versus the IL-6/LY# ratio suggested that IL-6/LY# was significantly more predictive of patient risk than the Sequential Organ Failure Assessment score or the other factors ( P = 1.5 × 10 -33 ). In trend analysis, as the trend of D1-D3-D7 IL-6/LY# decreases, the morality rate is lower than increase or fluctuate group (42.1% vs. 58.3%, 37.9% vs. 43.8%, 37.5% vs. 38.5% in high, moderate, and low D1 IL-6/LY# group separately). Conclusion: IL-6/LY# examined on first day in intensive care unit can be used as an immune-imbalance alert to identify sepsis patients with higher risk of 28-day mortality. Decreasing trend of IL-6/LY# suggests a lower 28-day mortality rate of sepsis patients.

The spatial dynamics of immune response upon virus infection through hybrid dynamical computational model.

Introduction: The immune responses play important roles in the course of disease initiation and progression upon virus infection such as SARS-CoV-2. As the tissues consist of spatial structures, the spatial dynamics of immune responses upon viral infection are essential to the outcome of infection. Methods: A hybrid computational model based on cellular automata coupled with partial differential equations is developed to simulate the spatial patterns and dynamics of the immune responses of tissue upon virus infection with several different immune movement modes. Results: Various patterns of the distribution of virus particles under different immune strengths and movement modes of immune cells are obtained through the computational models. The results also reveal that the directed immune cell wandering model has a better immunization effect. Several other characteristics, such as the peak level of virus density and onset time and the onset of the diseases, are also checked with different immune and physiological conditions, for example, different immune clearance strengths, and different cell-to-cell transmission rates. Furthermore, by the Lasso analysis, it is identified that the three main parameters had the most impact on the rate of onset time of disease. It is also shown that the cell-to-cell transmission rate has a significant effect and is more important for controlling the diseases than those for the cell-free virus given that the faster cell-to-cell transmission than cell-free transmission the rate of virus release is low. Discussion: Our model simulates the process of viral and immune response interactions in the alveola repithelial tissues of infected individuals, providing insights into the viral propagation of viruses in two dimensions as well as the influence of immune response patterns and key factors on the course of infection.

Initial 24-h perfusion index of ICU admission is associated with acute kidney injury in perioperative critically ill patients: A retrospective cohort analysis.

Background: The relationship between perfusion index (PI) and organ dysfunction in patients in the intensive care unit (ICU) is not clear. This study aimed to explore the relationship between PI and renal function in the perioperative critical care setting and evaluate the predictive efficiency of PI on patients with acute kidney injury (AKI) in the ICU. Methods: This retrospective analysis involved 12,979 patients who had undergone an operation and were admitted to the ICU in Peking Union Medical College Hospital from January 2014 to December 2019. The distribution of average PI in the first 24 h after ICU admission and its correlation with AKI was calculated by Cox regression. Receiver operating characteristic (ROC) curves were generated to compare the ability of PI, mean arterial pressure (MAP), creatinine, blood urea nitrogen (BUN), and central venous pressure (CVP) to discriminate AKI in the first 48 h in all perioperative critically ill patients. Results: Average PI in the first 24 h served as an independent protective factor of AKI (Odds ratio [OR]=0.786, 95% confidence interval [CI]: 0.704-0.873, P <0.0001). With a decrease in PI by one unit, the incidence of AKI increased 1.74 times. Among the variables explored for the prediction of AKI (PI, MAP, creatine, BUN, and CVP), PI yielded the highest area under the ROC curve, with a sensitivity of 64.34% and specificity of 70.14%. A cut-off value of PI ≤2.12 could be used to predict AKI according to the Youden index. Moreover, patients in the low PI group (PI ≤2.12) exhibited a marked creatine elevation at 24-48 h with a slower decrease compared with those in the high PI group (PI >2.12). Conclusions: As a local blood flow indicator, the initial 24-h average PI for perioperative critically ill patients can predict AKI during their first 120 h in the ICU.

Rational evaluation of various epidemic models based on the COVID-19 data of China.

In this paper, based on the Akaike information criterion, root mean square error and robustness coefficient, a rational evaluation of various epidemic models/methods, including seven empirical functions, four statistical inference methods and five dynamical models, on their forecasting abilities is carried out. With respect to the outbreak data of COVID-19 epidemics in China, we find that before the inflection point, all models fail to make a reliable prediction. The Logistic function consistently underestimates the final epidemic size, while the Gompertz's function makes an overestimation in all cases. Towards statistical inference methods, the methods of sequential Bayesian and time-dependent reproduction number are more accurate at the late stage of an epidemic. And the transition-like behavior of exponential growth method from underestimation to overestimation with respect to the inflection point might be useful for constructing a more reliable forecast. Compared to ODE-based SIR, SEIR and SEIR-AHQ models, the SEIR-QD and SEIR-PO models generally show a better performance on studying the COVID-19 epidemics, whose success we believe could be attributed to a proper trade-off between model complexity and fitting accuracy. Our findings not only are crucial for the forecast of COVID-19 epidemics, but also may apply to other infectious diseases.

Origins of oscillation patterns in cyclical thrombocytopenia.

Cyclical thrombocytopenia (CT) is a rare hematological disease characterized by periodic oscillations in circulating platelet counts. In almost all CT patients, other cell lines show no sign of oscillation, but recently a CT patient was reported with significant oscillations in circulating neutrophils (in the same period as the platelets). In this paper, we attempt to understand this phenomenon through a previously published model of human hematopoiesis. We have investigated a variety of possible oscillation patterns that may appear when alterations occur in the control parameters in the platelet regulatory dynamics. Our results indicate that the platelet maturation time and the differentiation rate from hematopoietic stem cells (HSCs) into the platelet cell line play important roles in the emergence of various types of CT like oscillations. Moreover, we find different oscillation patterns, including CT and cyclical neutropenia like oscillations, with certain parameter values in the platelet compartment. A bifurcation analysis revealed the different origins of these oscillation patterns. We also identified bistable dynamics which indicate the potential importance of system history in the treatment of these diseases. Together, these results demonstrate the possible origins for various oscillation patterns dependent on alterations in the platelet cell line control mechanisms. One of the important origins may be related to the regulation of apoptosis in platelet precursors.

PDCD5 functions as a regulator of p53 dynamics in the DNA damage response.

The tumor suppressor p53 plays a central role in cell fate decisions after DNA damage. Programmed Cell Death 5 (PDCD5) interacts with the p53 pathway to promote cell apoptosis. Recombinant human PDCD5 can significantly sensitize different cancers to chemotherapies. In the present paper, we construct a computational model that includes PDCD5 interactions in the p53 signaling network and study the effects of PDCD5 on p53-mediated cell fate decisions during the DNA damage response. Our results revealed that PDCD5 functions as a co-activator of p53 and regulates p53-dependent cell fate decisions via the mediation of p53 dynamics. The effects of PDCD5 are dose-dependent, such that p53 activity exhibits sustained low level, pulsed oscillations, or sustained high level dynamics depending on the PDCD5 level following DNA damage. Moreover, PDCD5 regulates caspase-3 activation via two mechanisms during the two phases of sustained and pulsed p53 dynamics. This study provides insights regarding how PDCD5 functions as a regulator of the p53 pathway and might be helpful for increasing our understanding of the molecular mechanisms by which PDCD5 can be used to treat cancers.

Bifurcation analysis and potential landscapes of the p53-Mdm2 module regulated by the co-activator programmed cell death 5.

The dynamics of p53 play important roles in the regulation of cell fate decisions in response to various stresses, and programmed cell death 5 (PDCD5) functions as a co-activator of p53 that modulates p53 dynamics. In the present paper, we investigated how p53 dynamics are modulated by PDCD5 during the deoxyribose nucleic acid damage response using methods of bifurcation analysis and potential landscape. Our results revealed that p53 activities display rich dynamics under different PDCD5 levels, including monostability, bistability with two stable steady states, oscillations, and the coexistence of a stable steady state (or two states) and an oscillatory state. The physical properties of the p53 oscillations were further demonstrated by the potential landscape in which the potential force attracts the system state to the limit cycle attractor, and the curl flux force drives coherent oscillation along the cyclic trajectory. We also investigated the efficiency with which PDCD5 induced p53 oscillations. We show that Hopf bifurcation can be induced by increasing the PDCD5 efficiency and that the system dynamics exhibited clear transition features in both barrier height and energy dissipation when the efficiency was close to the bifurcation point.

Adiabatic reduction of a model of stochastic gene expression with jump Markov process.

This paper considers adiabatic reduction in a model of stochastic gene expression with bursting transcription considered as a jump Markov process. In this model, the process of gene expression with auto-regulation is described by fast/slow dynamics. The production of mRNA is assumed to follow a compound Poisson process occurring at a rate depending on protein levels (the phenomena called bursting in molecular biology) and the production of protein is a linear function of mRNA numbers. When the dynamics of mRNA is assumed to be a fast process (due to faster mRNA degradation than that of protein) we prove that, with appropriate scalings in the burst rate, jump size or translational rate, the bursting phenomena can be transmitted to the slow variable. We show that, depending on the scaling, the reduced equation is either a stochastic differential equation with a jump Poisson process or a deterministic ordinary differential equation. These results are significant because adiabatic reduction techniques seem to have not been rigorously justified for a stochastic differential system containing a jump Markov process. We expect that the results can be generalized to adiabatic methods in more general stochastic hybrid systems.

Neutrophil dynamics in response to chemotherapy and G-CSF.

We have used a mathematical model of the combined dynamics of the hematopoietic stem cells and the differentiated neutrophil progeny to examine the effects of periodic chemotherapy in generating neutropenia, and the corresponding response of this system to granulocyte colony stimulating factor given to counteract the neutropenia. We find that there is a significant period of chemotherapy delivery that induces resonance in the system (at a period twice the average neutrophil lifespan from commitment to death) and a corresponding neutropenia suggesting that myelosuppressive protocols should avoid this period to minimize hematopoietic damage. The response to G-CSF is highly variable.

PDCD5-regulated cell fate decision after ultraviolet-irradiation-induced DNA damage.

Programmed cell death 5 (PDCD5) is a human apoptosis-related molecule that is involved in both the cytoplasmic caspase-3 activity pathway (by regulating Bax translocation from cytoplasm to mitochondria) and the nuclear pathway (by interacting with Tip60). In this study, we developed a mathematical model of the PDCD5-regulated switching of the cell response from DNA repair to apoptosis after ultraviolet irradiation-induced DNA damage. We established the model by combining several hypotheses with experimental observations. Our simulations indicate that the ultimate cell response to DNA damage is dependent on a signal threshold mechanism, and the PDCD5 promotion of Bax translocation plays an essential role in PDCD5-regulated cell apoptosis. Furthermore, the model simulations revealed that PDCD5 nuclear translocation can attenuate cell apoptosis, and PDCD5 interactions with Tip60 can accelerate DNA damage-induced apoptosis, but the final cell fate decision is insensitive to the PDCD5-Tip60 interaction. These results are consistent with experimental observations. The effect of recombinant human PDCD5 was also investigated and shown to sensitize cells to DNA damage by promoting caspase-3 activity.