The use of ensiled olive cake in the diets of Friesian cows increases beneficial fatty acids in milk and Halloumi cheese and alters the expression of SREBF1 in adipose tissue.

This study aimed to evaluate the effect of dietary inclusion of ensiled olive cake, a by-product of olive oil production, on milk yield and composition and on fatty acid (FA) profile of milk and Halloumi cheese from cows. Furthermore, the effect of olive cake on the expression of selected genes involved in mammary and adipose lipid metabolism was assessed in a subset of animals. A total of 24 dairy cows in mid lactation were allocated into 2 isonitrogenous and isoenergetic feeding treatments, named the control (CON) diet and the olive cake (OC) diet, in which part of the forages (alfalfa, barley hay, and barley straw) were replaced with ensiled OC as 10% of dry matter according to a 2 × 2 crossover design with two 28-d experimental periods. At the end of the second experimental period, mammary and perirenal adipose tissue samples were collected from 3 animals per group for gene expression analysis by quantitative reverse-transcription PCR. The expression of 11 genes, involved in FA synthesis (ACACA, FASN, G6PDH), FA uptake or translocation (VLDLR, LPL, SLC2A1, CD36, FABP3), FA saturation (SCD1), and transcriptional regulation (SREBF1, PPARG), was evaluated. No significant differences were observed between groups concerning milk yield, fat percentage, protein percentage, and protein yield (kg/d), whereas milk fat yield (kg/d) increased in the OC group. Dietary supplementation with ensiled OC modified the FA profile of milk and Halloumi cheese produced. There was a significant decrease in the concentration of de novo synthesized FA, saturated FA, and the atherogenic index, whereas long-chain and monounsaturated FA concentration was increased in both milk and cheese. Among individual saturated FA, only stearic acid was elevated, whereas among individual monounsaturated FA, increments of oleic acid (C18:1 cis-9) and the sum of C18:1 trans-10 and trans-11 acids were demonstrated in milk and Halloumi cheese produced. Although no diet effect was reported on total polyunsaturated FA, the concentration of CLA cis-9,trans-11 was increased in both milk and Halloumi cheese fat of the OC group. The expression of the genes tested was unaffected apart from an observed upregulation of SREBF1 mRNA expression in perirenal fat from cows fed the OC diet. Milk FA differences observed were not associated with alterations in mammary expression of genes involved in FA synthesis, uptake, translocation, and regulation of lipogenesis. Overall, the inclusion of ensiled OC in cow diets for a 4-wk period improved, beneficially for human health, the lipid profile of bovine milk and Halloumi cheese produced without adversely affecting milk yield and composition or the expression of genes involved in lipid metabolism of mammary and adipose tissues in cows.

Genomewide copy number alteration screening of circulating plasma DNA: potential for the detection of incipient tumors.

Background: Early cancer diagnosis might improve survival rates. As circulating tumor DNA (ctDNA) carries cancer-specific modifications, it has great potential as a noninvasive biomarker for detection of incipient tumors. Patients and methods: We collected cell-free DNA (cfDNA) samples of 1002 elderly without a prior malignancy, carried out whole-genome massive parallel sequencing and scrutinized the mapped sequences for the presence of (sub)chromosomal copy number alterations (CNAs) predictive for a malignancy. When imbalances were detected, 6-monthly clinical follow-up was carried out. Results: In 3% of participants chromosomal imbalances were detected. Follow-up analyses, including whole-body MRI screening, confirmed the presence of five hematologic malignancies: one Hodgkin lymphoma (HL), stage II; three non-HL (type chronic lymphocytic leukemia, Rai I-Binet A; type SLL, stage III; type mucosa-associated lymphoid tissue, stage I) and one myelodysplastic syndrome with excess blasts, stage II. The CNAs detected in cfDNA were tumor-specific. Furthermore, one case was identified with monoclonal B-cell lymphocytosis, a potential precursor of B-cell malignancy. In 24 additional individuals, CNAs were identified but no cancer diagnosis was made. For 9 of them, the aberrant cfDNA profile originated from peripheral blood cells. For 15 others the origin of aberrations in cfDNA remains undetermined. Conclusion(s): Genomewide profiling of cfDNA in apparently healthy individuals enables the detection of incipient hematologic malignancies as well as clonal mosaicism with unknown clinical significance. CNA screening of cellular DNA of peripheral blood in elderly has established that clonal mosaicism for these chromosomal anomalies predicts a 5- to 10-fold enhanced risk of a subsequent cancer. We demonstrate that cfDNA screening detects CNAs, which are not only derived from peripheral blood, but even more from other tissues. Since the clinical relevance of clonal mosaics in other tissues remains unknown, long-term follow-up is warranted. Taken together, this study demonstrates that genomewide cfDNA analysis has potential as an unbiased screening approach for hematological malignancies and premalignant conditions.

Skeletal ontogeny of the vertebral column and of the fins in shi drum Umbrina cirrosa (Teleostei: Perciformes: Sciaenidae), a new candidate species for aquaculture.

The osteological development of the vertebral column and fins in shi drum Umbrina cirrosa was studied in order to improve knowledge for its introduction in Mediterranean aquaculture. The osteological development was studied in 171 individuals, of total length (LT ) from 2·7 to 30·2 mm that were reared under the mesocosm technique. Vertebral ontogeny starts at 3·4 and 4·0 mm LT , with the formation of the first cartilaginous neural and haemal arches, and spines, respectively, and is completed with the full attainment of epicentrals (12·5 mm LT ). The formation of vertebral centra occurs between 4·1 and 7·4 mm LT . Pectoral supports are the first fin elements to develop (3·0 mm LT ), followed by those of the caudal fin (3·8 mm LT ), pelvic fin (3·9 mm LT ) and finally by those of the dorsal and anal fins (4·5 mm LT ). The caudal fin is the first to develop fin rays and attain the full count of principal fin rays (4·5-6·8 mm LT ), but the last to be fully completed with the formation of procurrent fin rays (6·9-17·5 mm LT ). The next fins starting to present rays are the dorsal (5·3 mm LT ) and the pectoral fins (5·6 mm LT ), while the anal and pelvic fins are the last (5·7 mm LT ). Following the caudal principal fin rays (6·8 mm LT ), the dorsal, anal (6·9 mm LT ), pelvic (7·4 mm LT ) and pectoral fins (9·8 mm LT ) are the next with fully completed ray counts. Aggregation of qualitative changes, such as the appearance of cartilages, the beginning and the complement of the ossification process and the full complement of elements in U. cirrosa were measured as cumulative frequency counts. These measurements reveal three ontogenetic intervals: one very developmentally active period during early life stages (from 3 to 5·9 mm LT ), a second slower developmental period (from 6·0 to 8·9 mm LT ) and finally a period of ontogeny more focused on structure refinement up to metamorphosis and settlement (>9·0 mm LT ).

Electronic Health Record Application Support Service Enablers.

There is a huge need for open source software solutions in the healthcare domain, given the flexibility, interoperability and resource savings characteristics they offer. In this context, this paper presents the development of three open source libraries - Specific Enablers (SEs) for eHealth applications that were developed under the European project titled "Future Internet Social and Technological Alignment Research" (FI-STAR) funded under the "Future Internet Public Private Partnership" (FI-PPP) program. The three SEs developed under the Electronic Health Record Application Support Service Enablers (EHR-EN) correspond to: a) an Electronic Health Record enabler (EHR SE), b) a patient summary enabler based on the EU project "European patient Summary Open Source services" (epSOS SE) supporting patient mobility and the offering of interoperable services, and c) a Picture Archiving and Communications System (PACS) enabler (PACS SE) based on the dcm4che open source system for the support of medical imaging functionality. The EHR SE follows the HL7 Clinical Document Architecture (CDA) V2.0 and supports the Integrating the Healthcare Enterprise (IHE) profiles (recently awarded in Connectathon 2015). These three FI-STAR platform enablers are designed to facilitate the deployment of innovative applications and value added services in the health care sector. They can be downloaded from the FI-STAR cataloque website. Work in progress focuses in the validation and evaluation scenarios for the proving and demonstration of the usability, applicability and adaptability of the proposed enablers.

Computer-aided diagnosis in hysteroscopic imaging.

The paper presents the development of a computer-aided diagnostic (CAD) system for the early detection of endometrial cancer. The proposed CAD system supports reproducibility through texture feature standardization, standardized multifeature selection, and provides physicians with comparative distributions of the extracted texture features. The CAD system was validated using 516 regions of interest (ROIs) extracted from 52 subjects. The ROIs were equally distributed among normal and abnormal cases. To support reproducibility, the RGB images were first gamma corrected and then converted into HSV and YCrCb. From each channel of the gamma-corrected YCrCb, HSV, and RGB color systems, we extracted the following texture features: 1) statistical features (SFs), 2) spatial gray-level dependence matrices (SGLDM), and 3) gray-level difference statistics (GLDS). The texture features were then used as inputs with support vector machines (SVMs) and the probabilistic neural network (PNN) classifiers. After accounting for multiple comparisons, texture features extracted from abnormal ROIs were found to be significantly different than texture features extracted from normal ROIs. Compared to texture features extracted from normal ROIs, abnormal ROIs were characterized by lower image intensity, while variance, entropy, and contrast gave higher values. In terms of ROI classification, the best results were achieved by using SF and GLDS features with an SVM classifier. For this combination, the proposed CAD system achieved an 81% correct classification rate.

Color multiscale texture classification of hysteroscopy images of the endometrium.

The objective of this study was to investigate the diagnostic performance of a Computer Aided Diagnostic (CAD) system based on color multiscale texture analysis for the classification of hysteroscopy images of the endometrium, in support of the early detection of gynaecological cancer. A total of 416 Regions of Interest (ROIs) of the endometrium were extracted (208 normal and 208 abnormal) from 45 subjects. RGB images were gamma corrected and were converted to the YCrCb color system. The following texture features were extracted from the Y, Cr and Cb channels: (i) Statistical Features (SF), (ii) Spatial Gray Level Dependence Matrices (SGLDM), and (iii) Gray Level Difference Statistics (GLDS). The Probabilistic Neural Network (PNN), statistical learning and the Support Vector Machine (SVM) neural network classifiers were also applied for the investigation of classifying normal and abnormal ROIs in different scales. Results showed that the highest percentage of correct classification (%CC) score was 79% and was achieved for the SVM models trained with the SF and GLDS features for the 1x1 scale. This %CC was higher by only 2% when compared with the CAD system developed, based on the SF and GLDS feature sets computed from the Y channel only. Further increase in scale from 2x2 to 9x9, dropped the %CC in the region of 60% for the SF, SGLDM, and GLDS, feature sets, and their combinations. Concluding, a CAD system based on texture analysis and SVM models can be used to classify normal and abnormal endometrium tissue in difficult cases of gynaecological cancer. The proposed system has to be investigated with more cases before it is applied in clinical practise.

Color based texture--classification of hysteroscopy images of the endometrium.

The objective of this study was to develop a CAD system for the classification of hysteroscopy images of the endometrium based on color texture analysis for the early detection of gynaecological cancer. A total of 416 Regions of Interest (ROIs) of the endometrium were extracted (208 normal and 208 abnormal) from 40 subjects. RGB images were gamma corrected and were converted to the HSV and YCrCb color systems. The following texture features were extracted for each channel of the RGB, HSV, and YCrCb systems: (i) Statistical Features, (ii) Spatial Gray Level Dependence Matrices and (iii) Gray Level Difference Statistics. The PNN statistical learning and SVM neural network classifiers were also investigated for classifying normal and abnormal ROIs. Results show that there is significant difference (using the Wilcoxon Rank Sum Test at a=0.05) between the texture features of normal and abnormal ROIs of the endometrium. Abnormal ROIs had higher gray scale median, variance, entropy and contrast and lower gray scale median and homogeneity values when compared to the normal ROIs. The highest percentage of correct classifications score was 79% and was achieved for the SVM models trained with the SF and GLDS features for differentiating between normal and abnormal ROIs. Concluding, a CAD system based on texture analysis and SVM models can be used to classify normal and abnormal endometrium tissue. Further work is needed to validate the system in more cases and organs.

Texture-based classification of hysteroscopy images of the endometrium.

The objective of this study was to classify hysteroscopy images of the endometrium based on texture analysis for the early detection of gynaecological cancer. A total of 418 regions of interest (ROIs) were extracted (209 normal and 209 abnormal) from 40 subjects. Images were gamma corrected and were converted to gray scale. The following texture features were extracted: (i) statistical features, (ii) spatial gray level dependence matrices (SGLDM), and (iii) gray level difference statistics (GLDS). The PNN and SVM neural network classifiers were also investigated for classifying normal and abnormal ROIs. Results show that there is significant difference (using Wilcoxon rank sum test at a=0.05) between the texture features of normal and abnormal ROIs for both the gamma corrected and uncorrected images. Abnormal ROIs had lower gray scale median and homogeneity values, and higher entropy and contrast values when compared to the normal ROIs. The highest percentage of correct classifications score was 77% and was achieved for the SVM models trained with the SF and GLDS features. Concluding, texture features provide useful information differentiating between normal and abnormal ROIs of the endometrium.

Qualitative visual image analysis of bruise age determination: a survey.

The evaluation of bruise color imaging is a very important task in forensic medicine. However, there is no standardized methodology in carrying out this task. In this paper, an attempt was made to review the different papers published in the literature on the visual assessment of bruise age determination, and derive color charts of daily bruise aging. Based on the color charts derived, the following observations can be made: (i) the bruise is red for day 1, (ii) there is no dominant color for day 2, whereas for day 3, blue is becoming slightly dominant, (iii) green is becoming dominant for days 4-6, with yellow color emerging, (iv) for day 7, there is coexistence of green and yellow, (v) yellow is highly dominant for days 7 to 14, with brown emerging. These charts can serve as guidelines for the qualitative evaluation of bruise imaging by visual analysis. Clearly, the need exists for the quantitative analysis of bruise color imaging.