We present a general physicochemical sampling model for olfaction, based on established pharmacological laws, in which arbitrary combinations of odorant ligands and receptors can be generated and their individual and collective effects on odor representations and olfactory performance measured. Individual odor ligands exhibit receptor-specific affinities and efficacies; that is, they may bind strongly or weakly to a given receptor, and can act as strong agonists, weak agonists, partial agonists, or antagonists. Ligands interacting with common receptors compete with one another for dwell time; these competitive interactions appropriately simulate the degeneracy that fundamentally defines the capacities and limitations of odorant sampling. The outcome of these competing ligand-receptor interactions yields a pattern of receptor activation levels, thereafter mapped to glomerular presynaptic activation levels based on the convergence of sensory neuron axons. The metric of greatest interest is the mean discrimination sensitivity, a measure of how effectively the olfactory system at this level is able to recognize a small change in the physicochemical quality of a stimulus. This model presents several significant outcomes, both expected and surprising. First, adding additional receptors reliably improves the system's discrimination sensitivity. Second, in contrast, adding additional ligands to an odorscene initially can improve discrimination sensitivity, but eventually will reduce it as the number of ligands increases. Third, the presence of antagonistic ligand-receptor interactions produced clear benefits for sensory system performance, generating higher absolute discrimination sensitivities and increasing the numbers of competing ligands that could be present before discrimination sensitivity began to be impaired. Finally, the model correctly reflects and explains the modest reduction in odor discrimination sensitivity exhibited by transgenic mice in which the specificity of glomerular targeting by primary olfactory neurons is partially disrupted.
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http://dx.doi.org/10.1371/journal.pcbi.1009054 | DOI Listing |
J Breath Res
January 2025
School of Medicine and Pharmacy, Ocean University of China, 5 Yushan Rd, Qingdao, Shandong, 266003, CHINA.
Lung cancer is one of the most common malignancy in the world, and early detection of lung cancer remains a challenge. The exhaled breath condensate (EBC) from lung and trachea can be collected totally noninvasively. In this study, our aim is to identify differential metabolites between non-small cell lung cancer (NSCLC) and control EBC samples and discriminate NSCLC group from control group by orthogonal projections to latent structures-discriminant analysis (OPLS-DA) models.
View Article and Find Full Text PDFPLoS One
January 2025
Instituto de Biología, Universidad Nacional Autónoma de México (UNAM), México City, México.
Dogs can discriminate between people infected with SARS-CoV-2 from those uninfected, although their results vary depending on the settings in which they are exposed to infected individuals or samples of urine, sweat or saliva. This variability likely depends on the viral load of infected people, which may be closely associated with physiological changes in infected patients. Determining this viral load is challenging, and a practical approach is to use the cycle threshold (Ct) value of a RT-qPCR test.
View Article and Find Full Text PDFDiabetes Care
January 2025
Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ.
Objective: We derive and validate D-RISK, an electronic health record (EHR)-driven risk score to optimize and facilitate screening for undiagnosed dysglycemia (prediabetes + diabetes) in clinical practice.
Research Design And Methods: We used retrospective EHR data (derivation sample) and a prospective diabetes screening study (validation sample) to develop D-RISK. Logistic regression with backward selection was used to predict dysglycemia (HbA1c ≥5.
Adv Sci (Weinh)
January 2025
Center for Advanced Biomolecular Recognition, Biomedical Research Division, Korea Institute of Science and Technology (KIST), Seoul, 02792, Republic of Korea.
During the COVID-19 pandemic, reverse transcription-quantitative polymerase chain reaction (RT-qPCR) has been recognized as the most reliable diagnostic tool. However, there is a need to develop multiplexed assays capable of analyzing multiple genes simultaneously to expand its application. To address this, a multiplexed RT-qPCR using a double emulsion (DE)-based carrier and a polymer microparticle reactor, termed primer-incorporated network tailored with Taqman probe (TaqPIN) is developed.
View Article and Find Full Text PDFAm J Transl Res
December 2024
Department of Clinical Laboratory, Hunan Provincial People's Hospital (The First Affiliated Hospital of Hunan Normal University) Changsha 410002, Hunan, China.
Objective: To develop a nomogram to predict the risk of portal vein tumor thrombosis (PVTT) in hepatocellular carcinoma (HCC) patients.
Methods: Patients diagnosed with HCC at Hunan Provincial People's Hospital between January 2010 and January 2022 were enrolled. Data on demographic characteristics, comorbidities, and laboratory tests were collected.
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