Monitoring the evolution of free and cysteinylated aldehydes from malt to fresh and forced aged beer.

During storage, beer staling coincides with a gradual increase in the concentrations of aldehydes resulting in the appearance of undesirable flavours. Cysteinylated aldehydes, also referred to as 2-substituted 1,3-thiazolidine-4-carboxylic acids, have been proposed as potential precursors of this increase. This study aimed to further understand the origin of aldehydes in aged beer, by monitoring both free and cysteinylated aldehydes throughout the brewing process, from the raw materials until the stored product. Quantification of free and cysteinylated aldehydes was performed for two different brews via headspace solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) and ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS), respectively. All selected marker aldehydes were quantified in malt, wort, and the resulting fresh and aged beer samples. Cysteinylated aldehydes were quantifiable in malt and up to the wort boiling phase. The highest levels of free aldehydes were found in malt, whereas cysteinylated aldehydes showed highest levels at mashing-in pointing to their formation during both malting and subsequent mashing-in. During beer ageing, an increase in all free aldehydes was measured. In particular, a rise in 2-methylpropanal and furfural is most striking. Although the presented experimental data obtained on malt and brewery samples do support the concept of bound-state aldehydes, cysteinylated aldehydes cannot be consider as the cause of increasing levels of staling aldehydes during beer ageing.

Validation of an ultra-high-performance liquid chromatography-mass spectrometry method for the quantification of cysteinylated aldehydes and application to malt and beer samples.

This paper describes the method validation for the simultaneous determination of seven cysteinylated aldehydes, i.e. 2-substituted 1,3-thiazolidines-4-carboxylic acids, using ultra-high-performance liquid chromatography-mass spectrometry (UHPLC-MS). Authentic reference compounds were first synthesized for identification and quantification purposes. Moreover, nuclear magnetic resonance (1H NMR and 13C NMR) was applied for verification of their structure, while ultra-high-performance liquid chromatography-mass spectrometry (UHPLC-MS) was applied for estimation of the purity. The method for quantification of cysteinylated aldehydes in model solutions has been validated according to the criteria and procedures described in international standards. The synthesized compounds were successfully identified via UHPLC-MS by comparing retention time and MS spectra with the commercial reference compounds. Method validation revealed good linearity (R2 > 0.995) over the range of 0.4-2.2 µg/L to approximately 1000 µg/L, depending on the analyte. The limits of quantification varied from 0.9 to 4.3 µg/L depending on the nature of the compound. Furthermore, evaluation of the method showed good accuracy and stability of the standard solutions. Reported chromatographic recoveries ranged from 112 to 120%. Consequently, the currently described method was applied on malt and beer samples. For the first time, quantification of cysteinylated aldehydes was obtained in malt. In contrast, in fresh beers unambiguous identification of these compounds was not achieved.

Handling missing values in support vector machine classifiers.

This paper discusses the task of learning a classifier from observed data containing missing values amongst the inputs which are missing completely at random. A non-parametric perspective is adopted by defining a modified risk taking into account the uncertainty of the predicted outputs when missing values are involved. It is shown that this approach generalizes the approach of mean imputation in the linear case and the resulting kernel machine reduces to the standard Support Vector Machine (SVM) when no input values are missing. Furthermore, the method is extended to the multivariate case of fitting additive models using componentwise kernel machines, and an efficient implementation is based on the Least Squares Support Vector Machine (LS-SVM) classifier formulation.

Absence of correlation between risk factors for endometrial cancer and the presence of tamoxifen-associated endometrial polyps in postmenopausal patients with breast cancer.

In order to investigate the presence of established risk factors for endometrial carcinoma in postmenopausal patients with breast cancer and with tamoxifen-associated endometrial polyps we compared a group of 25 patients with tamoxifen-associated endometrial polyps with 25 tamoxifen-treated patients without endometrial polyps. No significant differences were found between both groups of patients in age, parity, time after breast cancer and after menopause, duration and daily and total cumulative dose of tamoxifen intake, body mass index and serum levels of luteinising hormone (LH), follicle-stimulating hormone (FSH), oestradiol (E2), progesterone, sex hormone-binding globulin (SHBG), tamoxifen and CA125. So far there is no evidence that these polyps are premalignant lesions.

New models to predict depth of infiltration in endometrial carcinoma based on transvaginal sonography.

OBJECTIVES: Preoperative knowledge of the depth of myometrial infiltration is important in patients with endometrial carcinoma. This study aimed at assessing the value of histopathological parameters obtained from an endometrial biopsy (Pipelle de Cornier; results available preoperatively) and ultrasound measurements obtained after transvaginal sonography with color Doppler imaging in the preoperative prediction of the depth of myometrial invasion, as determined by the final histopathological examination of the hysterectomy specimen (the gold standard). METHODS: We first collected ultrasound and histopathological data from 97 consecutive women with endometrial carcinoma and divided them into two groups according to surgical stage (Stages Ia and Ib vs. Stages Ic and higher). The areas (AUC) under the receiver-operating characteristics curves of the subjective assessment of depth of invasion by an experienced gynecologist and of the individual ultrasound parameters were calculated. Subsequently, we used these variables to train a logistic regression model and least squares support vector machines (LS-SVM) with linear and RBF (radial basis function) kernels. Finally, these models were validated prospectively on data from 76 new patients in order to make a preoperative prediction of the depth of invasion. RESULTS: Of all ultrasound parameters, the ratio of the endometrial and uterine volumes had the largest AUC (78%), while that of the subjective assessment was 79%. The AUCs of the blood flow indices were low (range, 51-64%). Stepwise logistic regression selected the degree of differentiation, the number of fibroids, the endometrial thickness and the volume of the tumor. Compared with the AUC of the subjective assessment (72%), prospective evaluation of the mathematical models resulted in a higher AUC for the LS-SVM model with an RBF kernel (77%), but this difference was not significant. CONCLUSIONS: Single morphological parameters do not improve the predictive power when compared with the subjective assessment of depth of myometrial invasion of endometrial cancer, and blood flow indices do not contribute to the prediction of stage. In this study an LS-SVM model with an RBF kernel gave the best prediction; while this might be more reliable than subjective assessment, confirmation by larger prospective studies is required.

Model order selection for quantification of a multi-exponential magnetic resonance spectrum.

Magnetic resonance spectroscopic signals analyzed by time-domain models in order to retrieve estimates of the model parameters usually require prior knowledge about the model order. For multi-exponential signals where a superposition of peaks occurs at the same resonance frequency, but with different damping values, model order selection criteria from information theory can be used. In this study, several generalized versions of information criteria are compared using Monte-Carlo simulation signals. The best criterion is further applied for selecting the model order of experimental glycogen signals.

Color Doppler and gray-scale ultrasound evaluation of the postpartum uterus.

OBJECTIVES: To evaluate the color Doppler and gray-scale sonographic appearance of the uterus after pregnancy, with special attention to the occurrence of areas of enhanced vascularity and placental remnants. PATIENTS AND METHODS: Cross-sectional observational study involving 385 consecutive women presenting at their first visit after pregnancy. The uterus was evaluated using ultrasound with color Doppler. In the presence of placental remnants, blood was sampled for measurement of beta human chorionic gonadotropin (beta hCG), hemoglobin (Hb) and infectious parameters. If indicated, a dilatation and curettage was performed. RESULTS: In 8.3% of women, areas of enhanced vascularity were detected with color Doppler examination. Most cases (68.9%) were focal areas of one or more vessels. In 2.6% of patients abnormal vascularity extended over a large area of the whole myometrium. In 6.75% of cases, placental remnants were detected. In 46% of these, blood sampling revealed beta hCG levels below 30 mIU/mL; serological infection parameters and Hb concentration were within the normal range. CONCLUSIONS: Areas of enhanced vascularity of the uterus, ranging from a focal vascular pedicle to a larger area of the myometrium, are relatively common after pregnancy. They are predominantly seen in the presence of placental remnants, in the early postpartum period and after instrumental or manual delivery of the placenta. There are no clear risk factors for retained placental tissue, besides the history of blood transfusion in the early postpartum, and perhaps multigravidity. Serology is of little help in the diagnosis of retained gestational products. The knowledge of the ultrasound and color Doppler features of the uterus after pregnancy may prove of practical value for the management of abnormal uterine bleeding in the postpartum period.

Ultrasonographic features of the endometrium and the ovaries in women on etonogestrel implant.

OBJECTIVE: To evaluate the ultrasound features of the endometrium and ovaries in women on etonogestrel implant, and to correlate these features with the bleeding pattern. METHODS: Observational study including 188 consecutive women presenting for follow-up transvaginal ultrasound examination after insertion of an etonogestrel implant contraceptive device. Thirty women had more than one follow-up examination. The bleeding pattern was considered abnormal if, in the last 3 months, there were more than five episodes of vaginal bleeding, or there was prolonged bleeding exceeding 14 consecutive days. RESULTS: At first follow-up examination, the mean age was 29.7 years and 47% of women had an abnormal bleeding pattern. Most bleeding episodes were of less intensity than menses. The mean endometrial thickness (ET) on ultrasound was 2.9 mm (standard deviation, 2.0). Ovarian follicle growth exceeding 5 mm was observed in 60% of the cases. Ovulation was demonstrated in one woman. Univariate analysis showed a positive association (P < 0.01) between ET, bleeding pattern, and bleeding intensity. Follicle growth was positively associated (P < 0.01) with ET, bleeding pattern, and interval between insertion and examination. Multivariate analysis showed that the ET was on average 1.25 mm greater in women with abnormal bleeding (P = 0.0001). The odds of finding follicle growth were 2.8 times higher (95% confidence interval, 1.2-6.2) in women presenting with a three-layer type of endometrial morphology. There was no association between the other patients' characteristics and the bleeding pattern. CONCLUSIONS: Abnormal uterine bleeding in women on etonogestrel implant was associated with follicle growth and a thicker, three-layer type of endometrium, suggesting incomplete ovarian inhibition and estrogen stimulation of the endometrium.

Prognostic importance of degree of differentiation and cyst rupture in stage I invasive epithelial ovarian carcinoma.

BACKGROUND: Previous studies on prognostic factors in stage I invasive epithelial ovarian carcinoma have been too small for robust conclusions to be reached. We undertook a retrospective study in a large international database to identify the most important prognostic variables. METHODS: 1545 patients with invasive epithelial ovarian cancer (International Federation of Gynaecology and Obstetrics [FIGO] stage I) were included. The records of these patients were examined and data extracted for univariate and multivariate analysis of disease-free survival in relation to various clinical and pathological variables. FINDINGS: The multivariate analyses identified degree of differentiation as the most powerful prognostic indicator of disease-free survival (moderately vs well differentiated hazard ratio 3.13 [95% CI 1.68-5.85], poorly vs well differentiated 8.89 [4.96-15.9]), followed by rupture before surgery (2.65 [1.53-4.56]), rupture during surgery (1.64 [1.07-2.51]), FIGO 1973 stage Ib vs Ia 1.70 [1.01-2.85]) and age (per year 1.02 [1.00-1.03]). When the effects of these factors were accounted for, none of the following were of prognostic value: histological type, dense adhesions, extracapsular growth, ascites, FIGO stage 1988, and size of tumour. INTERPRETATION: Degree of differentiation, the most powerful prognostic indicator in stage I ovarian cancer, should be used in decisions on therapy in clinical practice and in the FIGO classification of stage I ovarian cancer. Rupture should be avoided during primary surgery of malignant ovarian tumours confined to the ovaries.