Introduction: The use of signal dogs for cancer detection is not yet routinely performed,but dogs and their powerful olfactory system have proven to be a unique and valuable tool for many lineages and are beginning to be incorporated into medical practice. This method has great advantages; the dog can detect a tumour in the human body already in preclinical stages, when the patient has no symptoms yet. The identification of cancer biomarkers to enable early diagnosis is a need for many types of cancer, whose prognosis is strongly dependent on the stage of the disease. However, this method also has its various pitfalls that must be taken into account.
Aim: The aim of the study was to identify and highlight the factors that affect the level of detection accuracy, but also the conditions associated with olfactometric diagnosis.
Methods: The study included 48 dogs and 48 handlers, that were part of the training between 2016 and 2023.All those who started olfactometry training and remained in training for at least one year were included in the study. The dogs ranged in age from 8 months to 12 years and were of different races and sexes. After long-term observation, a qualitative analysis was performed and factors that may play a role in the early detection of the disease were listed.
Results: The results of the search for the different factors have been compiled into two groups, focussing on the actual handling of the patient biological sample from collection, processing, storage until transport, preparation of the sample,and detection. Focus on the actual work and behaviour of the dog and handler.
Conclusion: There are many factors; however, it is worth addressing them because the canine sense of smell is one of the possible uses as a diagnostic method.
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http://dx.doi.org/10.1016/j.heliyon.2024.e41604 | DOI Listing |
J Med Microbiol
January 2025
Parul Institute of Applied Sciences, Faculty of Applied Sciences, Parul University, Vadodara, Gujarat 391760, India.
The rise in antimicrobial resistance poses a significant threat to global health, particularly among diabetic patients who are prone to urinary tract infections (UTIs). Pathogens that cause UTI among diabetic patients exhibit significant multidrug resistance (MDR) patterns, necessitating more precise empirical treatment strategies..
View Article and Find Full Text PDFJ Magn Reson Imaging
January 2025
Department of Radiology, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine (Shenzhen Traditional Chinese Medicine Hospital), Shenzhen, China.
Background: Multifrequency MR elastography (mMRE) enables noninvasive quantification of renal stiffness in patients with chronic kidney disease (CKD). Manual segmentation of the kidneys on mMRE is time-consuming and prone to increased interobserver variability.
Purpose: To evaluate the performance of mMRE combined with automatic segmentation in assessing CKD severity.
Acc Chem Res
January 2025
Molecular Sensing and Imaging Center, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, China.
ConspectusIons are the crucial signaling components for living organisms. In cells, their transportation across pore-forming membrane proteins is vital for regulating physiological functions, such as generating ionic current signals in response to target molecule recognition. This ion transport is affected by confined interactions and local environments within the protein pore.
View Article and Find Full Text PDFLymphology
January 2024
Medical Biophysics Department, Medical Research Institute, Alexandria University, Alexandria, Egypt.
Lymphadenopathy is associated with lymph node abnormal size or consistency due to many causes. We employed the deep convolutional neural network ResNet-34 to detect and classify CT images from patients with abdominal lymphadenopathy and healthy controls. We created a single database containing 1400 source CT images for patients with abdominal lymphadenopathy (n = 700) and healthy controls (n = 700).
View Article and Find Full Text PDFCancer Res Commun
January 2025
University of Minnesota, Minnesota, MN, United States.
Neuroendocrine neoplasms (NENs) encompass a diverse set of malignancies with limited precision therapy options. Recently, therapies targeting DLL3 have shown clinical efficacy in aggressive NENs, including small cell lung cancers and neuroendocrine prostate cancers. Given the continued development and expansion of DLL3-targeted therapies, we sought to characterize the expression of DLL3 and identify its clinical and molecular correlates across diverse neuroendocrine and non-neuroendocrine cancers.
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