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Kozak, A.

Publications and source records attributed to Kozak, A..

2 recordsLinked to original sources

Ontogeny of escape response and body shape in Threespine Stickleback (Gasterosteus aculeatus L.)

Escape responses in fishes provide insight into accelerative motions and behavioral response times of these animals, linking numerous fitness-related traits. We sought to connect escape response performance to genotype and phenotype across ontogenetic stages within a single population of Threespine Stickleback (Gasterosteus aculeatus L.), to determine if a gene of major effect (Ectodysplasin; Eda) on adaptive lateral armour plate phenotype and fitness conveys a performance advantage in brackish and saltwater environments. We predicted that possession of one or more low-plated alleles would result in better escape performance in brackish environments across ontogeny, and that Eda genotype would result in variation in shape phenotype that would be predictive of escape performance before the completion of lateral plate development. We assessed three kinematic variables derived from C-start escape responses in wild-caught, F1 juvenile, and F1 adults, and found that Eda genotypes did not directly impact maximum velocity or curvature coefficient, but linked phenotypes contributed to an increase in total distance traveled in F1 adults. We further showed that Eda genotype impacted growth, producing variation in size which in turn influenced escape performance variables across age groups, with a particular focus on total distance traveled. The influence of Eda genotype on shape was confounded by sexual dimorphism, indicating that further sex-specific studies on shape and performance are needed. The presence of at least one low-plated allele conferred a growth advantage, particularly in a freshwater rearing environment, consistent with known pleiotropic effects of Eda, including on skeletal development, that may be modulating anti-predator responses before plate phenotype is fully expressed. Altogether, more ontogenic studies are needed to ensure the influence of development on adaptive traits is more clearly understood.

evolutionary biology↗

Feasibility of Integrating Canine Olfaction with Chemical and Microbial Profiling of Urine to Detect Lethal Prostate Cancer

Prostate cancer is the second leading cause of cancer death in men in the developed world. A more sensitive and specific detection strategy for lethal prostate cancer beyond serum prostate specific antigen (PSA) population screening is urgently needed. Diagnosis by canine olfaction, using dogs trained to detect cancer by smell, has been shown to be both specific and sensitive. While dogs themselves are impractical as scalable diagnostic sensors, machine olfaction for cancer detection is testable. However, studies bridging the divide between clinical diagnostic techniques, artificial intelligence, and molecular analysis remains difficult due to the significant divide between these disciplines. We tested the clinical feasibility of a cross-disciplinary, integrative approach to early prostate cancer biosensing in urine using trained canine olfaction, volatile organic compound (VOC) analysis by gas chromatography-mass spectroscopy (GC-MS) artificial neural network (ANN)-assisted examination, and microbial profiling in a double-blinded pilot study. Two dogs were trained to detect Gleason 9 prostate cancer in urine collected from biopsy-confirmed patients. Biopsy-negative controls were used to assess canine specificity as prostate cancer biodetectors. Urine samples were simultaneously analyzed for their VOC content in headspace via GC-MS and urinary microbiota content via 16S rDNA Illumina sequencing. In addition, the dogs diagnoses were used to train an ANN to detect significant peaks in the GC-MS data. The canine olfaction system was 71% sensitive and between 70-76% specific at detecting Gleason 9 prostate cancer. We have also confirmed VOC differences by GC-MS and microbiota differences by 16S rDNA sequencing between cancer positive and biopsy-negative controls. Furthermore, the trained ANN identified regions of interest in the GC-MS data, informed by the canine diagnoses. Methodology and feasibility are established to inform larger-scale studies using canine olfaction, urinary VOCs, and urinary microbiota profiling to develop machine olfaction diagnostic tools. Scalable multi-disciplinary tools may then be compared to PSA screening for earlier, non-invasive, more specific and sensitive detection of clinically aggressive prostate cancers in urine samples.

cancer biology↗