Searcharxiv⌕ Search

arXiv · 0708.1993

Dynamics of glucose-lactose diauxic growth in E. coli

Abstract

We present a mathematical model of glucose-lactose diauxic growth in Escherichia coli including both the postive and negative regulation mechanisms of the lactose operon as well as the inducer exclusion. To validate this model, we first calculated the time evolution of beta-galactosidase for only the lactose nutrient and compared the numerical results with experimental data. Second, we compared the calculated cell biomass of the glucose-lactose diauxic growth with the experimental optical density of the diauxic growth for a particular E. coli MG 1655. For both cases, the numerical calculations from this model are in good agreement with these two experiments' data. The diauxic growth pattern of a wild type E. coli was also investigated.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Zhao Lu, Michael A Lee. 2011-01-28. Dynamics of glucose-lactose diauxic growth in E. coli. https://arxiv.org/abs/0708.1993

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Current validation practice undermines surgical AI development

Surgical data science (SDS) is rapidly advancing, yet clinical adoption of artificial intelligence (AI) in surgery remains limited, with inadequate validation as an important contributing factor. Existing validation practices often neglect the temporal and hierarchical structure of intraoperative videos, yielding misleading or clinically irrelevant results. We introduce a comprehensive catalogue of validation pitfalls in AI-based surgical video analysis, derived from a multi-stage Delphi process with 92 international experts. Pitfalls span three categories: (1) data, (2) metric selection/configuration, and (3) aggregation and reporting. A systematic review of surgical AI papers reveals that these pitfalls are widespread. Experiments on surgical video datasets show that ignoring temporal and hierarchical data structures can understate uncertainty, obscure critical failure modes, and alter algorithm rankings. To address these shortcomings, we provide consensus-based best practices compiled. Together, this work provides an evidence-based framework for rigorous validation of surgical video analysis algorithms, guiding benchmarking, reporting, regulatory review, and clinical translation.

q-bio.OT↗

Cancer genomics, targeted therapy to precision oncology: the treatment paradigm is a holistic approach to cancer therapeutics

Cancer is a fatal genetic disease involving unregulated cell growth and proliferation. Cellular behaviors such as growth, proliferation, survival, or death rely upon the ability of cells to communicate with the surrounding system; therefore, effective targeting of dysregulated signaling pathways involving growth factors, regulatory proteins, cell adhesion molecules, and immune system molecules is critical to cancer therapy. They are mainly driven by alterations in tumor suppressor genes and oncogenes that may vary among different cancer types. Importantly, patients with the same cancer type respond differently to available cancer treatments, likely due to tumor-specific DNA, RNA, and proteins, indicating the need for patient-specific treatment options. Precision oncology has evolved as a form of cancer therapy focused on genetic and molecular profiling of tumors to identify specific molecular alterations involved in carcinogenesis for tailored individualized cancer treatment. This article aims to briefly explain the foundations and frontiers of precision oncology, highlighting the cutting-edge innovations in tools and techniques associated with it to assess its scope and importance in achieving efficacious cancer treatment over time.

q-bio.OT↗

Model-Based Cortisol Replacement Strategies for Patients With Adrenal Insufficiency

Cortisol is an essential hormone secreted by the adrenal glands. Abnormally low level of cortisol is referred to as adrenal insufficiency. This paper focuses on devising treatment strategies for patients suffering from adrenal insufficiency using a model-based approach. Two conditions of adrenal insufficiency are analysed. They are hypothalamic-pituitary (HP) and adrenal gland disorders. The hypothalamus, pituitary, and adrenal glands constitute the hypothalamus-pituitary-adrenal (HPA) axis, which regulates stress and maintains physiological homeostasis through cortisol secretion. A comparative analysis of the existing mathematical models of the HPA axis is conducted. Based on this analysis, a novel model of the HPA axis is proposed that incorporates endogenous circadian rhythm. This proposed model is used to design effective cortisol replacement strategies. In addition, hydrocortisone replacement therapies are proposed and validated with clinical data from the literature. The results presented in this paper are applicable to patient-specific treatment strategies for individuals with adrenal insufficiency.

q-bio.OT↗