Metachronal propulsion of non-Newtonian viscoelastic mucus in an axisymmetric tube with ciliated walls

Cilia-induced flow of viscoelastic mucus through an idealized two-dimensional model of the human trachea is presented.The cilia motion is simulated by a metachronal wave pattern which enables the mobilization of highly viscous mucus even at nonzero Reynolds numbers.The viscoelastic mucus is analyzed with the upper convected Maxwell viscoelastic formulation which features a relaxation time and accurately captures normal stress generation in shear flows.The governing equations are transformed from fixed to wave(laboratory)frame with appropriate variables and resulting differential equations are perturbed about wave number.The trachea is treated as an axisymmetric ciliated tube.Radial and axial distributions in axial velocity are calculated via the regular perturbation method and pressure rise is computed with numerical integration using symbolic software MATHEMATICA^(‘TM’).The influence of selected parameters which is cilia length,and Maxwell viscoelastic material parameter i.e.relaxation time for prescribed values of wave number are visualized graphically.Pressure rise is observed to increase considerably with elevation in both cilia length and relaxation time whereas the axial velocity is markedly decelerated.The simulations provide some insight into viscous-dominated cilia propulsion of rheological mucus and also serve as a benchmark for more advanced modeling.

Discrete biological modeling for the immune response to dengue virus

Dengue infection affects more than half of the world’s population,with 1 billion symp-tomatic cases identified per year and several distinct genetic serotypes:DENV 1–4.Transmitted via the mosquito bite,the dengue virus infects Langerhans cells.Monocytes,B lymphocytes,and mast cells infected with dengue virus produce various cytokines although it is not clear which ones are predominant during DHF disease.A mathemat-ical model of the Dengue virus infection is developed according to complex dynamics determined by many factors.Starting from a state of equilibrium that we could define as“virus-free”asymptotically stable with a viral reproduction number lower than one which means a very effective action of the innate immune system:it stops the infectious process,the mathematical analysis of stability in the presence of the virus demonstrates that the proposed model is dynamically influenced.Dengue fever affects more than half of the world’s population,with 1 billion symptomatic cases and multiple genetic serotypes confirmed each year,which simulates a network of interactions between the various populations involved without considering the speeds of the processes in question which are indicated in a separate computation.In this research,a hybrid approach of petri nets is utilized to connect the discrete models of dengue.

Artificial intelligence to link environmental endocrine disruptors(EEDs)with bone diseases

Our endocrine system is not only complex,but is also enormously sensitive to the imbalances caused by the environmental stressors,extreme weather situation,and other geographical factors.The endocrine disruptions are associated with the bone diseases.Osteoporosis is a bone disorder that occurs when bone mineral density and bone mass decrease.It affects women and men of all races and ethnic groups,causing bone weakness and the risk of fractures.Environmental stresses are referred to physical,chemical,and biological factors that can impact species productivity.This research aims to examine the impact of environmental stresses on bone diseases like osteoporosis and low bone mass(LBM)in the United States(US).For this purpose,we use an artificial neural network model to evaluate the correlation between the data.A multilayer neural network model is constructed using the Levenberg–Marquardt training algorithm,and its performance is evaluated by mean absolute error and coefficient of correlation.The data of osteoporosis and LBM cases in the US are divided into three groups,including gender group,age group,and race/ethnicity group.Each group shows a positive correlation with environmental stresses and thus the endocrinology.

Modeling and simulation of the“IL-36 cytokine”and CAR-T cells interplay in cancer onset

Background:CAR-T cells are chimeric antigen receptor(CAR)-T cells;they are targetspecific engineered cells on tumor cells and produce T cell-mediated antitumor responses.CAR-T cell therapy is the“first-line”therapy in immunotherapy for the treatment of highly clonal neoplasms such as lymphoma and leukemia.This adoptive therapy is currently being studied and tested even in the case of solid tumors such as osteosarcoma since,precisely for this type of tumor,the use of immune checkpoint inhibitors remained disappointing.Although CAR-T is a promising therapeutic technique,there are therapeutic limits linked to the persistence of these cells and to the tumor’s immune escape.CAR-T cell engineering techniques are allowed to express interleukin IL-36,and seem to be much more efficient in antitumoral action.IL-36 is involved in the long-term antitumor action,allowing CAR-T cells to be more efficient in their antitumor action due to a“cross-talk”action between the“IL-36/dendritic cells”axis and the adaptive immunity.Methods:This analysis makes the model useful for evaluating cell dynamics in the case of tumor relapses or specific understanding of the action of CAR-T cells in certain types of tumor.The model proposed here seeks to quantify the action and interaction between the three fundamental elements of this antitumor activity induced by this type of adoptive immunotherapy:IL-36,“armored”CAR-T cells(i.e.,engineered to produce IL-36)and the tumor cell population,focusing exclusively on the action of this interleukin and on the antitumor consequences of the so modified CAR-T cells.Mathematical model was developed and numerical simulations were carried out during this research.The development of the model with stability analysis by conditions of Routh–Hurwitz shows how IL-36 makes CAR-T cells more efficient and persistent over time and more effective in the antitumoral treatment,making therapy more effective against the“solid tumor”.Findings:Primary malignant bone tumors are quite rare(about 3%of all tumors)and the vast majority consist of osteosarcomas and Ewing’s sarcoma and,approximately,the 20%of patients undergo metastasis situations that is the most likely cause of death.Interpretation:In bone tumor like osteosarcoma,there is a variation of the cellular mechanical characteristics that can influence the efficacy of chemotherapy and increase the metastatic capacity;an approach related to adoptive immunotherapy with CAR-T cells may be a possible solution because this type of therapy is not influenced by the biomechanics of cancer cells which show peculiar characteristics.