In the last two decades, Computer Aided Detection (CAD) systems were developed to help radiologists analyse screening mammograms, however benefits of current CAD technologies appear to be contradictory, therefore they should be improved to be ultimately considered useful. Since 2012, deep convolutional neural networks (CNN) have been a tremendous success in image recognition, reaching human performance. These methods have greatly surpassed the traditional approaches, which are similar to currently used CAD solutions. Deep CNN-s have the potential to revolutionize medical image analysis. We propose a CAD system based on one of the most successful object detection frameworks, Faster R-CNN. The system detects and classifies malignant or benign lesions on a mammogram without any human intervention. The proposed method sets the state of the art classification performance on the public INbreast database, AUC = 0.95. The approach described here has achieved 2nd place in the Digital Mammography DREAM Challenge with AUC = 0.85. When used as a detector, the system reaches high sensitivity with very few false positive marks per image on the INbreast dataset. Source code, the trained model and an OsiriX plugin are published online at https://github.com/riblidezso/frcnn_cad.

Objective: Relapsing polychondritis (RP) is a rare autoimmune inflammatory disease that attacks mainly cartilaginous structures or causes serious damage in proteoglycan-rich structures (the eyes, heart, blood vessels, inner ear). This study shows results regarding the epidemiology, progression, and associations of this highly variable disease by collecting all cases from a 124-million-person-year Central European nationwide cohort. Methods: We used the Hungarian Health Care Database to identify all persons with possible RP infection. We followed patients who had International Classification of Diseases 10th edition code M94.1 at least once in their inpatient or outpatient records between January 1, 2002 and December 31, 2013 in Hungary. We classified these patients into disease severity groups by their drug consumption patterns between January 1, 2010 and December 31, 2013. We analyzed the regional distribution of RP incidences as well. Overall maps of comorbidity are presented with network layouts. Results: We identified 256 patients with RP among cumulatively 11.5 million registered inhabitants. We classified these patients into four severity classes as "extremely mild" (n=144), "mild" (n=22), "moderate" (n=41), and "severe" (n=4). Two additional groups were defined for patients without available drug data as "suspected only" (n=23) and "confirmed but unknown treatment" (n=22). The age and sex distributions of patients were similar to worldwide statistics. Indeed, the overall survival was good (95% confidence interval for 5 years was 83.6%–92.9% and for 10 years was 75.0%–88.3% which corresponds to the overall survival of the general population in Hungary), and the associations with other autoimmune disorders were high (56%) in Hungary. Almost any disease can occur with RP; however, the symptoms of chromosomal abnormalities are only incidental. Spondylosis can be a sign of the activation of RP, while Sjögren syndrome is the most frequent autoimmune association. Regional distribution of incidences suggests arsenic drinking water and sunlight exposure as possible triggering factors. Conclusion: The good survival rate of RP in Hungary is probably associated with the early diagnosis of the disease.

The aim of this review is to evaluate the present status of the use of cell-free DNA and its fraction of circulating tumor DNA (ctDNA) because this year July 2022, an ESMO guideline was published regarding the application of ctDNA in patient care. This review is for clinical oncologists to explain the concept, the terms used, the pros and cons of ctDNA; thus, the technical aspects of the different platforms are not reviewed in detail, but we try to help in navigating the current knowledge in liquid biopsy. Since the validated and adequately sensitive ctDNA assays have utility in identifying actionable mutations to direct targeted therapy, ctDNA may be used for this soon in routine clinical practice and in other different areas as well. The cfDNA fragments can be obtained by liquid biopsy and can be used for diagnosis, prognosis, and selecting among treatment options in cancer patients. A great proportion of cfDNA comes from normal cells of the body or from food uptake. Only a small part (<1%) of it is related to tumors, originating from primary tumors, metastatic sites, or circulating tumor cells (CTCs). Soon the data obtained from ctDNA may routinely be used for finding minimal residual disease, detecting relapse, and determining the sites of metastases. It might also be used for deciding appropriate therapy, and/or emerging resistance to the therapy and the data analysis of ctDNA may be combined with imaging or other markers. However, to achieve this goal, further clinical validations are inevitable. As a result, clinicians should be aware of the limitations of the assays. Of course, several open questions are still under research and because of it cfDNA and ctDNA testing are not part of routine care yet.

Natural autoantibodies against cholesterol are present in the sera of all healthy individuals; their function, production, and regulation, however, are still unclear. Here, we managed to produce two monoclonal anti-cholesterol antibodies (ACHAs) by immunizing mice with cholesterol-rich liposomes. The new ACHAs were specific to cholesterol and to some structurally closely related 3β-hydroxyl sterols, and they reacted with human lipoproteins VLDL, LDL, and HDL. They bound, usually with low avidity, to live human or murine lymphocyte and monocyte-macrophage cell lines, which was enhanced substantially by a moderate papain digestion of the cell surface, removing some protruding extracellular protein domains. Cell-bound ACHAs strongly colocalized with markers of cholesterol-rich lipid rafts and caveolae at the cell surface and intracellularly with markers of the endoplasmic reticulum and Golgi complex. These data suggest that these IgG ACHAs may serve as probes of clustered cholesterol (e.g., different lipid rafts) in live cells and thus may also have immunomodulatory potential.