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Published in Song S. Qian, Mark R. DuFour, Ibrahim Alameddine, Bayesian Applications in Environmental and Ecological Studies with R and Stan, 2023
Song S. Qian, Mark R. DuFour, Ibrahim Alameddine
The intended analysis method was regression: modeling of various watershed-level indicators calculated based on observed biological data as functions of the watershed urbanization level. The biological data are counts of individuals of various species representing aquatic biota (fish, invertebrates, and algae) in samples collected using the same sampling protocol throughout the EUSE studies. For example, benthic macroinvertebrate communities are widely used to represent stream ecological conditions. Species in these communities are relatively long-lived (compared to algae), to integrate the temporal changes in water quality, and are of limited mobility (compared to fish), to reflect the impact of activities in the immediate upstream watershed.
Reliable Biomedical Applications Using AI Models
Published in Punit Gupta, Dinesh Kumar Saini, Rohit Verma, Healthcare Solutions Using Machine Learning and Informatics, 2023
Shambhavi Mishra, Tanveer Ahmed, Vipul Mishra
Future scientists will devise novel methods for monitoring and interpreting a wide range of biological data, including genetic, genomic, cellular, clinical, behavioral, physiological, and environmental factors. Integrative mining can provide a holistic view and therefore give comprehensive insights into healthcare. In contrast to other computers, where enormous data sets can be acquired, patient data is typically limited here.
ŠUnderstanding Artificial Intelligence (AI)
Published in Louis J. Catania, AI for Immunology, 2021
The term informatics, similar to big data analytics, describes the computational science of how to use data, information, and knowledge to improve human health and the delivery of health care services.32 Bioinformatics is thus a biological subdiscipline of informatics that is concerned with the acquisition, storage, analysis, and dissemination of biological data. And from those general disciplines flows the science of “immunoinformatic” (or computational immunology), which is the science that helps to create significant immunological information using bioinformatics software and applications.33 Some of the main areas of immunoinformatics include vaccinology, antibody analyses, predictions regarding specific epitopes for B-cell recognition and T-cell, cancer immunotherapies, and in the field of immunogenomics.
ELANE Promotes M2 Macrophage Polarization by Down-Regulating PTEN and Participates in the Lung Cancer Progression
Published in Immunological Investigations, 2023
Sinuo Song, Yunping Zhao, Tianyu Fu, Yunfei Fan, Jie Tang, Xiaoxing Wang, Chao Liu, Xiaobo Chen
Bioinformatics is a new subject that integrates computer science, statistics and informatics technologies to comprehensively analyze biological data and reveal their possible internal relationships. The TCGA database is an important data source for cancer research. By analyzing the transcriptome expression matrix and clinical information data of patients with LUAD in the TCGA database, we identified 33 candidate genes associated with LUAD development. CIBERSORTx was used to predict the components of immune cells, and eight types of immune cells were obtained. Further evaluation of the relationship between genes and immune cells revealed that the genes most significantly correlated with immune cells were EDN3 and ELANE, among which ELANE was significantly positively correlated with M2 macrophages. In malignant tumors, TAMs are mainly similar to M2 phenotypes (Geng et al. 2019). Studies have shown that M2-like TAMs can promote tumor cell survival, proliferation, invasion and metastasis by driving neovascularization, mediating apoptosis resistance and inhibiting adaptive immune response, and play an important role in extracellular matrix remodeling (Brown et al. 2017). Previous studies have shown that M2-type macrophages can secrete a variety of cytokines (IL-6, IL-10, TGF-β, etc.), chemokines (CCL17, CCL18, CXCL8, CXCL9, CXCL10, etc.) and fibroblast growth factors to inhibit inflammation (Najafi et al. 2019; Shapouri-Moghaddam et al. 2018).
Application of radiation omics in the development of adverse outcome pathway networks: an example of radiation-induced cardiovascular disease
Published in International Journal of Radiation Biology, 2022
Omid Azimzadeh, Simone Moertl, Raghda Ramadan, Bjorn Baselet, Evagelia C. Laiakis, Soji Sebastian, Danielle Beaton, Jaana M. Hartikainen, Jan Christian Kaiser, Afshin Beheshti, Sisko Salomaa, Vinita Chauhan, Nobuyuki Hamada
Although maintaining linear and simplified biological pathways is the main philosophy behind the AOP approach, systems biology can provide the opportunity to give more mechanistic information, fill gaps in biological data, and translate them at different levels of the organism from molecule to cell up to the individual organism. The integrated approaches may facilitate profiling of the radiation response in a dose- and time-dependent manner to identify the critical exposure criteria leading to the adverse effect on individuals and populations. To fully translate this information at a population level, further research is needed on molecular epidemiology to test and validate the proposed connections between the AOPs and actual health outcomes. Such ‘big data’ approaches would typically use information from omics platforms, biobanks, and health registries. Such a comprehensive platform can identify attractive genes, proteins, or metabolites as measurable bioindicators for screening and risk assessment.
World Trade Center dust induces nasal and neurological tissue injury while propagating reduced olfaction capabilities and increased anxiety behaviors
Published in Inhalation Toxicology, 2022
Michelle Hernandez, Joshua Vaughan, Terry Gordon, Morton Lippmann, Sam Gandy, Lung-Chi Chen
Molecular studies tend to contain biological data which inform on the occurrence of significant biological changes. However, these studies are often deficient, in that many of the observed molecular changes may or may not be directly related to functional changes at a whole- tissue or organism level. Given the complex dynamic of molecular pathophysiology, it is important to question – if exposure-related molecular changes are observed, do phenotypic evaluations exist that could inform on disease pathogenesis or overt disease progression? Within the nasal passages, olfactory information is processed in olfactory epithelial cells lining the upper regions of the nasal cavity. The remaining nasal cavity is lined with neuron-lacking respiratory epithelia which serve as a protective surface. Within the olfactory epithelia, olfactory sensing neurons/receptor neurons are responsible for transmitting olfactory information back to the CNS. Of utmost importance are olfactory sensing neurons- the only CNS tissue with direct links to the external world, which contain unique stem cells that give rise to new olfactory neurons throughout adult life, with capacity to replace olfactory receptor neurons after damage to the olfactory nerve. Olfactory receptor neuron turnover is critical and key considering it is the only CNS tissue to also regenerate (Suzuki et al. 2000; Slotnick et al. 2010).