Biology subjects

Farhang-Sardroodi, S.

Publications and source records attributed to Farhang-Sardroodi, S..

3 recordsLinked to original sources

bioRxiv2023

Insights into B Cell and Antibody Kinetics Against SARS-CoV-2 Variants Using Mathematical Modelling

B cells and antibodies are crucial in protecting against infections like SARS-CoV-2. However, antibody levels decline after infection or vaccination, reducing defences against future SARS-CoV-2 infections. To understand antibody production and decline, we developed a mathematical model that predicts germinal center B cell, long-lived plasma cell, memory B cell, and antibody dynamics. Our focus was on B cell activation and antibody generation following both primary and secondary SARS-CoV-2 infections. Aligning our model with clinical data, we adjusted antibody production rates for germinal center B cells and plasma B cells during primary and secondary infections. We also assessed antibody neutralization against Delta and Omicron variants post-primary and secondary exposure. Our findings showed reduced neutralization against Omicron due to its immune evasion. In primary and secondary exposures to Delta and Omicron, our predictions indicated enhanced antibody neutralization in the secondary response within a year of the primary response. We also explored waning immunity, demonstrating how B cell kinetics affect viral neutralization post-primary infection. This study enhances our understanding of humoral immunity to SARS-CoV-2 and can predict antibody dynamics post-infection or vaccination.

immunology↗

bioRxiv2021

Chemotherapy-Induced Cachexia and Model-Informed Dosing to Preserve Lean Mass in Cancer Treatment

Although chemotherapy is a standard treatment for cancer, it comes with significant side effects. In particular, certain agents can induce severe muscle loss, known as cachexia, worsening patient quality of life and treatment outcomes. 5-fluorouracil, an anti-cancer agent used to treat several cancers, has been shown to cause muscle loss. Experimental data indicates a non-linear dose-dependence for muscle loss in mice treated with daily or week-day schedules. We present a mathematical model of chemotherapy-induced muscle wasting that captures this non-linear dose-dependence. Area-under-the-curve metrics are proposed to quantify the treatments effects on lean mass and tumour control. Model simulations are used to explore alternate dosing schedules, aging effects, and morphine use in chemotherapy treatment with the aim of better protecting lean mass while actively targeting the tumour, ultimately leading to improved personalization of treatment planning and improved patient quality of life. Author SummaryIn this paper we present a novel mathematical model for muscle loss due to cancer chemotherapy treatment. Loss of muscle mass relates to increased drug toxicity and side-effects, and to decreased patient quality of life and survival rates. With our model, we examine the therapeutic efficacy of various dosing schedules with the aim of controlling a growing tumour while also preserving lean mass. Preservation of body composition, in addition to consideration of inflammation and immune interactions, the gut microbiome, and other systemic health measures, may lead to improved patient-specific treatment plans that improve patient quality of life.

cancer biology↗

bioRxiv2020

Mathematical Model of Muscle Wasting in Cancer Cachexia

Cancer cachexia is a debilitating condition characterized by an extreme loss of skeletal muscle mass which negatively impacts patients quality of life, reduces their ability to sustain anticancer therapies, and increases the risk of mortality. Recent discoveries have identified the myostatin/activin-ActRIIB pathway as critical to muscle wasting by inducing satellite cell quiescence and increasing muscle-specific ubiquitin ligases responsible for atrophy. Remarkably, pharmacological blockade of the ActRIIB pathway has shown to reverse muscle wasting and prolong the survival time of tumor-bearing animals. To explore the implications of this signaling pathway and potential therapeutic targets in cachexia, we construct a novel mathematical model of muscle tissue subjected to tumor-derived cachexic factors. The model formulation tracks the intercellular interactions between cancer, satellite cell, and muscle cell populations. The model is parameterized by fitting to colon-26 mouse model data, and analysis provides insight into tissue growth in healthy, cancerous, and post-treatment conditions. Model predictions suggest that cachexia fundamentally alters muscle tissue health, as measured by the stem cell ratio, and this is only partially recovered by anti-cachexia treatment. Our mathematical findings suggest that the activation and proliferation of satellite cells, after blocking the myostatin/activin B pathway, is required to partially recover cancer-induced muscle loss.

cancer biology↗