Two sensitive and accurate stability-indicating chromatographic methods were developed and validated for the determination of rafoxanide (RFX). Degradation products were identified by mass spectrometry and IR spectroscopy. The first is ultra-performance liquid chromatography method where separation was performed using acetonitrile:0.005 M potassium dihydrogen orthophosphate (pH 3.5) in a ratio of 80:20 by volume as a mobile phase using a Hypersil GOLD™ C8 column 1.9 mm (50 × 2.1 mm), UV detection was adjusted at 220 nm and the flow rate was 0.6 mL min(-1) The other is a thin-layer chromatography-densitometry method where separation was achieved using a mobile phase composed of chloroform:ethyl acetate:toluene:ammonia (5:4:3:0.1 by volume) on silica gel 60 F254 plates, and densitometric detection was done at 280 nm. Validation was achieved as per the ICH guidelines. The proposed methods proved to be accurate, robust, specific and suitable for application as stability-indicating methods for routine analysis of RFX in quality control laboratories.

A validation study for six genomic regions previously identified by a genome-wide association study for somatic cell score was conducted with data of clinical mastitis in German Holstein cattle. Out of 10 tested SNPs, five on chromosomes 6, 13 and 19 were significantly associated with clinical mastitis (P < 0.05). Three SNPs on chromosomes 6 and 19 had the same direction of effect as those previously reported in the initial genome-wide association study for somatic cell score. The other two SNPs on chromosome 13 had opposite effects. As well as validating associations within known QTL from previous studies, e.g. chromosomes 6 and 19, novel loci on chromosome 13 were confirmed. Promising candidate genes are, for example: deoxycytidine kinase, immunoglobulin J chain, vitamin D binding protein, forkhead box K2, sodium/hydrogen exchanger 8 and cytoplasmic nuclear factor of activated T-cells 2. Our confirmation study provides additional evidence for the functional role of the linked genomic regions to immune response. This information can be used as a basis for further functional studies for those potential genes.

BACKGROUND: In head and neck squamous cell carcinomas (HNSCC) hypoxic radioresistance can be reduced by use of the hypoxic modifier nimorazole, as shown in the DAHANCA 5 trial. Recently, a 15-gene hypoxia classifier has shown predictive impact for the effect of nimorazole by identifying 'more' and 'less' hypoxic tumors in the DAHANCA 5 cohort. A prospective multicentre EORTC-1219 study is initiated, where nimorazole and prospective use of the classifier as a predictor is tested in relation to the most recent accelerated chemoradiotherapy treatment. Validation of the gene expression classification procedures is described here.

MATERIAL AND METHODS: Formalin-fixed paraffin-embedded (FFPE) tumor material from three recent HNSCC cohorts [DAHANCA 18 (n = 96), 24 (n = 40), and IAEA Hypo (n = 55)] was used to establish and validate procedures for prospective classification of patients. Repeatability was tested for the different steps in the gene expression analysis, and reproducibility was tested with xenograft tumors (FaDuDD, UTSCC33), where gene expression in complementary sections was compared after fixation and embedding locally and at international institutions, respectively. Intra-tumor heterogeneity was addressed by classifying biopsy samples from HNSCC tumors, where 2-4 biopsies from each tumor was accessible.

RESULTS: Procedures were successfully established for individual classification of HNSCC patients in retrospective and prospective cohorts. Measurements of gene expression levels were reproducible between different international institutions.

CONCLUSION: Technical validation of the 15-gene hypoxia classifier demonstrated that it is suitable for implementation in prospective clinical trials.

BACKGROUND: In head and neck squamous cell carcinomas (HNSCC) hypoxic radioresistance can be reduced by use of the hypoxic modifier nimorazole, as shown in the DAHANCA 5 trial. Recently, a 15-gene hypoxia classifier has shown predictive impact for the effect of nimorazole by identifying 'more' and 'less' hypoxic tumors in the DAHANCA 5 cohort. A prospective multicentre EORTC-1219 study is initiated, where nimorazole and prospective use of the classifier as a predictor is tested in relation to the most recent accelerated chemoradiotherapy treatment. Validation of the gene expression classification procedures is described here.

MATERIAL AND METHODS: Formalin-fixed paraffin-embedded (FFPE) tumor material from three recent HNSCC cohorts [DAHANCA 18 (n = 96), 24 (n = 40), and IAEA Hypo (n = 55)] was used to establish and validate procedures for prospective classification of patients. Repeatability was tested for the different steps in the gene expression analysis, and reproducibility was tested with xenograft tumors (FaDuDD, UTSCC33), where gene expression in complementary sections was compared after fixation and embedding locally and at international institutions, respectively. Intra-tumor heterogeneity was addressed by classifying biopsy samples from HNSCC tumors, where 2-4 biopsies from each tumor was accessible.

RESULTS: Procedures were successfully established for individual classification of HNSCC patients in retrospective and prospective cohorts. Measurements of gene expression levels were reproducible between different international institutions.

CONCLUSION: Technical validation of the 15-gene hypoxia classifier demonstrated that it is suitable for implementation in prospective clinical trials.

BACKGROUND AND STUDY AIM: The study aim was to improve and validate the accuracy of the fibrosis-4 (FIB-4) and aspartate aminotransferase-to-platelet ratio index (APRI) scores for use in a potential machine-learning (ML) method that accurately predicts the extent of liver fibrosis.

PATIENTS AND METHODS: This retrospective multicenter study included 69,106 patients with chronic hepatitis C planned for antiviral therapy from January 2010-December 2014 with liver biopsy results. FIB-4 and APRI scores were calculated and their performance for predicting significant liver fibrosis (F3-F4) assessed against the Metavir scoring system. ML was used for feature selection and reduction to identify the most relevant attributes (CfsSubseteval/best first) for prediction.

RESULTS: In this study, 57,492 (83.2%) patients were F0-F2, and 11,615 (16.8%) patients were F3-F4. The revalidation of FIB-4 and APRI showed lower accuracy and higher disagreement with the biopsy results, with AUCs of 0.68 and 0.58, respectively. FIB-4 diagnosed fewer (14%) F3-F4 patients, and the high specificity and negative predictive values of FIB-4 and APRI reflected the low prevalence of F3-F4 in the study population. Out of 15 attributes, age (>35 years), AFP (>6.5 ng/ml), and platelet count (<150,000/mm) were the most relevant risk attributes, and patients with one or more of these risk factors were likely to be F3-F4, with a classification accuracy of ≤ 92% and receiver operating characteristics area of 0.74.

CONCLUSION: FIB-4 and APRI scores were not very accurate and missed diagnosing most of the F3-F4 patients. ML implementation improved medical decisions and minimized the required clinical data to three risk factors.