Heat identification by 17\u3b2-estradiol and progesterone quantification in individual raw milk samples by enzyme immunoassay

Background: There is a substantial decline in first-service-pregnancy-rate in dairy cows. In this regard, future prospects are to measure milk hormones on-farm and progesterone levels in milk are not enough to precise ovulation unless connected to other data. The objectives of this study were to investigate whether 17\u3b2-estradiol could be measured from individual cow milk samples using a commercially available non-radiolabelled enzyme immunoassay kit (EIA) with no previously reported milk application, and whether those detections could precisely illustrate 17\u3b2-estradiol pre-ovulation peak in spite of its limited concentration and short manifestation in milk. Results: Milk sample treatments for progesterone and 17\u3b2-estradiol EIA measurements are described. Hormonal profiles from daily milk samples of six different cows were reported and 17\u3b2-estradiol pre-ovulation peak was visualized in all cases. Heat detection was possible by EIA using one every 2 days milking samples in almost all studied cases. Only in one case, morning and afternoon milking samples were required to visualize the 17\u3b2-estradiol pre-ovulation peak. Conclusions: 17\u3b2-estradiol EIA quantification in raw milk is a reliable, rapid, economic and a precise method to describe cow heat along with EIA progesterone determination

A new method for determining physician decision thresholds using empiric, uncertain recommendations

<p>Abstract</p> <p>Background</p> <p>The concept of risk thresholds has been studied in medical decision making for over 30 years. During that time, physicians have been shown to be poor at estimating the probabilities required to use this method. To better assess physician risk thresholds and to more closely model medical decision making, we set out to design and test a method that derives thresholds from actual physician treatment recommendations. Such an approach would avoid the need to ask physicians for estimates of patient risk when trying to determine individual thresholds for treatment. Assessments of physician decision making are increasingly relevant as new data are generated from clinical research. For example, recommendations made in the setting of ocular hypertension are of interest as a large clinical trial has identified new risk factors that should be considered by physicians. Precisely how physicians use this new information when making treatment recommendations has not yet been determined.</p> <p>Results</p> <p>We derived a new method for estimating treatment thresholds using ordinal logistic regression and tested it by asking ophthalmologists to review cases of ocular hypertension before expressing how likely they would be to recommend treatment. Fifty-eight physicians were recruited from the American Glaucoma Society. Demographic information was collected from the participating physicians and the treatment threshold for each physician was estimated. The method was validated by showing that while treatment thresholds varied over a wide range, the most common values were consistent with the 10-15% 5-year risk of glaucoma suggested by expert opinion and decision analysis.</p> <p>Conclusions</p> <p>This method has advantages over prior means of assessing treatment thresholds. It does not require physicians to explicitly estimate patient risk and it allows for uncertainty in the recommendations. These advantages will make it possible to use this method when assessing interventions intended to alter clinical decision making.</p

A Proof-Of-Principle Study of Epigenetic Therapy Added to Neoadjuvant Doxorubicin Cyclophosphamide for Locally Advanced Breast Cancer

BACKGROUND: Aberrant DNA methylation and histone deacetylation participate in cancer development and progression; hence, their reversal by inhibitors of DNA methylation and histone deacetylases (HDACs) is at present undergoing clinical testing in cancer therapy. As epigenetic alterations are common to breast cancer, in this proof-of-concept study demethylating hydralazine, plus the HDAC inhibitor magnesium valproate, were added to neoadjuvant doxorubicin and cyclophosphamide in locally advanced breast cancer to assess their safety and biological efficacy. METHODOLOGY: This was a single-arm interventional trial on breast cancer patients (ClinicalTrials.gov Identifier: NCT00395655). After signing informed consent, patients were typed for acetylator phenotype and then treated with hydralazine at 182 mg for rapid-, or 83 mg for slow-acetylators, and magnesium valproate at 30 mg/kg, starting from day –7 until chemotherapy ended, the latter consisting of four cycles of doxorubicin 60 mg/m(2) and cyclophosphamide 600 mg/m(2) every 21 days. Core-needle biopsies were taken from primary breast tumors at diagnosis and at day 8 of treatment with hydralazine and valproate. MAIN FINDINGS: 16 patients were included and received treatment as planned. All were evaluated for clinical response and toxicity and 15 for pathological response. Treatment was well-tolerated. The most common toxicity was drowsiness grades 1–2. Five (31%) patients had clinical CR and eight (50%) PR for an ORR of 81%. No patient progressed. One of 15 operated patients (6.6%) had pathological CR and 70% had residual disease <3 cm. There was a statistically significant decrease in global 5(m)C content and HDAC activity. Hydralazine and magnesium valproate up- and down-regulated at least 3-fold, 1,091 and 89 genes, respectively. CONCLUSIONS: Hydralazine and magnesium valproate produce DNA demethylation, HDAC inhibition, and gene reactivation in primary tumors. Doxorubicin and cyclophosphamide treatment is safe, well-tolerated, and appears to increase the efficacy of chemotherapy. A randomized phase III study is ongoing to support the efficacy of so-called epigenetic or transcriptional cancer therapy

Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified

Ion mobility mass spectrometry for extracting spectra of N-glycans directly from incubation mixtures following glycan release : application to glycans from engineered glycoforms of intact, folded HIV gp120

The analysis of glycosylation from native biological sources is often frustrated by the low abundances of available material. Here, ion mobility combined with electrospray ionization mass spectrometry have been used to extract the spectra of N-glycans released with PNGase F from a serial titration of recombinantly expressed envelope glycoprotein, gp120, from the human immunodeficiency virus (HIV). Analysis was also performed on gp120 expressed in the α-mannosidase inhibitor, and in a matched mammalian cell line deficient in GlcNAc transferase I. Without ion mobility separation, ESI spectra frequently contained no observable ions from the glycans whereas ions from other compounds such as detergents and residual buffer salts were abundant. After ion mobility separation on a Waters T-wave ion mobility mass spectrometer, the N-glycans fell into a unique region of the ion mobility/m/z plot allowing their profiles to be extracted with good signal:noise ratios. This method allowed N-glycan profiles to be extracted from crude incubation mixtures with no clean-up even in the presence of surfactants such as NP40. Furthermore, this technique allowed clear profiles to be obtained from sub-microgram amounts of glycoprotein. Glycan profiles were similar to those generated by MALDI-TOF MS although they were more susceptible to double charging and fragmentation. Structural analysis could be accomplished by MS/MS experiments in either positive or negative ion mode but negative ion mode gave the most informative spectra and provided a reliable approach to the analysis of glycans from small amounts of glycoprotein