Abstract-The monitoring of breathing dynamics is an essential diagnostic tool in various clinical environments, such as sleep diagnostics, intensive care and neonatal monitoring. This paper introduces an innovative signal classification method that is capable of on-line detection of the presence or absence of normal breathing. Four different artificial neural networks are presented for the recognition of three different patterns in the respiration signals (normal breathing, hypopnea, and apnea). Two networks process the normalized respiration signals directly, while another two use sophisticatedly preprocessed signals. The development of the networks was based on training sets from the polysomnographic records of nine different patients. The detection performance of the networks was tested and compared by using up to 8000 untrained breathing patterns from 16 different patients. The networks which classified the preprocessed respiration signals produced an average detection performance of over 90%. In the light of the moderate computational power used, the presented method is not only viable in clinical polysomnographs and respiration monitors, but also in portable devices.

Xp11.2 translocation carcinoma is a distinct subtype of renal cell carcinoma characterized by translocations involving the TFE3 gene. Our study included the morphological, immunohistochemical and clinicopathological examination of 28 Xp11.2 RCCs. The immunophenotype has been assessed by using CA9, CK7, CD10, AMACR, MelanA, HMB45, Cathepsin K and TFE3 immunostainings. The diagnosis was confirmed by TFE3 break-apart FISH in 25 cases. The ages of 13 male and 15 female patients, without underlying renal disease or having undergone chemotherapy ranged from 8 to 72. The mean size of the tumors was 78.5 mm. Forty-three percent of patients were diagnosed in the pT3/pT4 stage with distant metastasis in 6 cases. Histological appearance was branching-papillary composed of clear cells with voluminous cytoplasm in 13 and variable in 15 cases, including one tumor with anaplastic carcinoma and another with rhabdoid morphology. Three tumors were labeled with CA9, while CK7 was negative in all cases. Diffuse CD10 reaction was observed in 17 tumors and diffuse AMACR positivity was described in 14 tumors. The expression of melanocytic markers and Cathepsin K were seen only in 7 and 6 cases, respectively. TFE3 immunohistochemistry displayed a positive reaction in 26/28 samples. TFE3 rearrangement was detected in all the analyzed cases (25/ 25), including one with the loss of the entire labeled break-point region. The follow-up time ranged from 2 to 300 months, with 7 cancer-related deaths. In summary, Xp11.2 carcinoma is an uncommon form of renal cell carcinoma with a variable histomorphology and rather aggressive clinical course.

Background Hypomethylation of long interspersed nuclear element 1 (LINE-1) is characteristic of various cancer types, including colorectal cancer (CRC). Malfunction of several factors or alteration of methyl-donor molecules’ (folic acid and S-adenosylmethionine) availability can contribute to DNA methylation changes. Detection of epigenetic alterations in liquid biopsies can assist in the early recognition of CRC. Following the investigations of a Hungarian colon tissue sample set, our goal was to examine the LINE-1 methylation of blood samples along the colorectal adenoma-carcinoma sequence and in inflammatory bowel disease. Moreover, we aimed to explore the possible underlying mechanisms of global DNA hypomethylation formation on a multi-level aspect. Methods LINE-1 methylation of colon tissue (n = 183) and plasma (n = 48) samples of healthy controls and patients with colorectal tumours were examined with bisulfite pyrosequencing. To investigate mRNA expression, microarray analysis results were reanalysed in silico (n = 60). Immunohistochemistry staining was used to validate DNA methyltransferases (DNMTs) and folate receptor beta (FOLR2) expression along with the determination of methyl-donor molecules’ in situ level (n = 40). Results Significantly decreased LINE-1 methylation level was observed in line with cancer progression both in tissue (adenoma: 72.7 ± 4.8%, and CRC: 69.7 ± 7.6% vs. normal: 77.5 ± 1.7%, p ≤ 0.01) and liquid biopsies (adenoma: 80.0 ± 1.7%, and CRC: 79.8 ± 1.3% vs. normal: 82.0 ± 2.0%, p ≤ 0.01). However, no significant changes were recognized in inflammatory bowel disease cases. According to in silico analysis of microarray data, altered mRNA levels of several DNA methylation-related enzymes were detected in tumours vs. healthy biopsies, namely one-carbon metabolism-related genes—which met our analysing criteria—showed upregulation, while FOLR2 was downregulated. Using immunohistochemistry, DNMTs, and FOLR2 expression were confirmed. Moreover, significantly diminished folic acid and S-adenosylmethionine levels were observed in parallel with decreasing 5-methylcytosine staining in tumours compared to normal adjacent to tumour tissues (p ≤ 0.05). Conclusion Our results suggest that LINE-1 hypomethylation may have a distinguishing value in precancerous stages compared to healthy samples in liquid biopsies. Furthermore, the reduction of global DNA methylation level could be linked to reduced methyl-donor availability with the contribution of decreased FOLR2 expression.

BackgroundThe immunohistochemical detection of estrogen (ER) and progesterone (PR) receptors in breast cancer is routinely used for prognostic and predictive testing. Whole slide digitalization supported by dedicated software tools allows quantization of the image objects (e.g. cell membrane, nuclei) and an unbiased analysis of immunostaining results. Validation studies of image analysis applications for the detection of ER and PR in breast cancer specimens provided strong concordance between the pathologist's manual assessment of slides and scoring performed using different software applications.MethodsThe effectiveness of two connected semi-automated image analysis software (NuclearQuant v. 1.13 application for Pannoramic™ Viewer v. 1.14) for determination of ER and PR status in formalin-fixed paraffin embedded breast cancer specimens immunostained with the automated Leica Bond Max system was studied. First the detection algorithm was calibrated to the scores provided an independent assessors (pathologist), using selected areas from 38 small digital slides (created from 16 cases) containing a mean number of 195 cells. Each cell was manually marked and scored according to the Allred-system combining frequency and intensity scores. The performance of the calibrated algorithm was tested on 16 cases (14 invasive ductal carcinoma, 2 invasive lobular carcinoma) against the pathologist's manual scoring of digital slides.ResultsThe detection was calibrated to 87 percent object detection agreement and almost perfect Total Score agreement (Cohen's kappa 0.859, quadratic weighted kappa 0.986) from slight or moderate agreement at the start of the study, using the un-calibrated algorithm. The performance of the application was tested against the pathologist's manual scoring of digital slides on 53 regions of interest of 16 ER and PR slides covering all positivity ranges, and the quadratic weighted kappa provided almost perfect agreement (κ = 0.981) among the two scoring schemes.ConclusionsNuclearQuant v. 1.13 application for Pannoramic™ Viewer v. 1.14 software application proved to be a reliable image analysis tool for pathologists testing ER and PR status in breast cancer.

The objective of the study was to examine proliferation and apoptosis associated gene expression in the whole sequence parathyroid lesions to reveal specific features of carcinoma. This study was based on surgically removed parathyroid tissues, gene expression analysis was performed both at gene and protein level. First, mRNA isolation was performed from deep-frozen tissue samples, and further apoptosis pathway-specific cDNA macroarray analysis was carried out. The results were validated with real-time PCR. Subsequently, protein expression was analyzed with immunhistochemistry on Tissue Micro Array multi-blocks derived from several paraffin-embedded samples. cDNA macroarrays revealed elevated expression of both pro-apoptotic (FAS receptor, TRAIL ligand, CASPASE8, and -4) and anti-apoptotic (cIAP1, APOLLON) genes in benign proliferative lesions compared to that in normal gland. TMA studies showed overexpression of KI67, P53, SURVIVIN and APOLLON protein and failure of expression of P27, BCL2, BAX, CHROMOGRANIN-A, SYNAPTOPHYSIN, CYCLIND1, FLIP, TRAIL, CK8, CK18, CK19 in parathyroid carcinoma was detected. These alterations in gene expression of the investigated products could be used in differentiation between beningn and malignant proliferative processes of the parathyroid gland. Authors conclude that a series of alterations in gene expression such as overexpression of APOLLON, P53, KI67 and suppression of P27, BCL2, BAX lead to uncontrolled cell proliferation, but still not leading to increased apoptotic activity in parathyroid carcinoma.

We have found significantly differentially expressed miRNAs in AML and adrenocortical tumors. Circulating hsa-miR-451a might be a promising minimally invasive biomarker of AML. The lack of significantly different expression of hsa-miR-483-3p and hsa-miR-483-5p between AML and ACC might limit their applicability as diagnostic miRNA markers for ACC.

In DNA microarray technology, repeatability and reliability are very important to compare multiple RNA samplesfrom different experiments. The application of common or universal RNA as a standard control equalizes the differences in hybridization parameters and array variations. For this purpose, high-quality reference RNA is necessary in bulk amounts. A novel approach was developed to get milligrams of sense or antisense RNA, starting from micrograms of pooled total RNA from different cell lines, tissues, or organisms. This method is inexpensive and allows further labeling procedures using poly(dT) or random oligomers as primers. In addition, amplified, sense reference RNA is suitable for standard labeling protocols, while the antisense reference RNA can be used with antisense RNA from the linear sample amplification method. Here we produced universal RNA for human, rat, and alfalfa and demonstrated the quality using specific cDNA microarrays.

Nuclear estrogen receptor (ER), progesterone receptor (PR) and Ki-67 protein positive tumor cell fractions are semiquantitatively assessed in breast cancer for prognostic and predictive purposes. These biomarkers are usually revealed using immunoperoxidase methods resulting in diverse signal intensity and frequent inhomogeneity in tumor cell nuclei, which are routinely scored and interpreted by a pathologist during conventional light-microscopic examination. In the last decade digital pathology-based whole slide scanning and image analysis algorithms have shown tremendous development to support pathologists in this diagnostic process, which can directly influence patient selection for targeted- and chemotherapy. We have developed an image analysis algorithm optimized for whole slide quantification of nuclear immunostaining signals of ER, PR, and Ki-67 proteins in breast cancers. In this study, we tested the consistency and reliability of this system both in a series of brightfield and DAPI stained fluorescent samples. Our method allows the separation of overlapping cells and signals, reliable detection of vesicular nuclei and background compensation, especially in FISH stained slides. Detection accuracy and the processing speeds were validated in routinely immunostained breast cancer samples of varying reaction intensities and image qualities. Our technique supported automated nuclear signal detection with excellent efficacy: Precision Rate/Positive Predictive Value was 90.23 ± 4.29%, while Recall Rate/Sensitivity was 88.23 ± 4.84%. These factors and average counting speed of our algorithm were compared with two other open source applications (QuPath and CellProfiler) and resulted in 6-7% higher Recall Rate, while 4- to 30-fold higher processing speed. In conclusion, our image analysis algorithm can reliably detect and count nuclear signals in digital whole slides or any selected large areas i.e. hot spots, thus can support pathologists in assessing clinically important nuclear biomarkers with less intra- and interlaboratory bias inherent of empirical scoring. © 2017 International Society for Advancement of Cytometry.