Making hard choices easier: a prospective, multicentre study to assess the efficacy of a fertility-related decision aid in young women with early-stage breast cancer

BACKGROUND: Fertility is a priority for many young women with breast cancer. Women need to be informed about interventions to retain fertility before chemotherapy so as to make good quality decisions. This study aimed to prospectively evaluate the efficacy of a fertility-related decision aid (DA). METHODS: A total of 120 newly diagnosed early-stage breast cancer patients from 19 Australian oncology clinics, aged 18–40 years and desired future fertility, were assessed on decisional conflict, knowledge, decision regret, and satisfaction about fertility-related treatment decisions. These were measured at baseline, 1 and 12 months, and were examined using linear mixed effects models. RESULTS: Compared with usual care, women who received the DA had reduced decisional conflict (β=−1.51; 95%CI: −2.54 to 0.48; P=0.004) and improved knowledge (β=0.09; 95%CI: 0.01–0.16; P=0.02), after adjusting for education, desire for children and baseline uncertainty. The DA was associated with reduced decisional regret at 1 year (β=−3.73; 95%CI: −7.12 to −0.35; P=0.031), after adjusting for education. Women who received the DA were more satisfied with the information received on the impact of cancer treatment on fertility (P<0.001), fertility options (P=0.005), and rated it more helpful (P=0.002), than those who received standard care. CONCLUSION: These findings support widespread use of this DA shortly after diagnosis (before chemotherapy) among younger breast cancer patients who have not completed their families

Selection of Single-Stranded DNA Molecular Recognition Elements against Exotoxin A Using a Novel Decoy-SELEX Method and Sensitive Detection of Exotoxin A in Human Serum

Exotoxin A is one of the virulence factors of Pseudomonas aeruginosa, a bacterium that can cause infections resulting in adverse health outcomes and increased burden to health care systems. Current methods of diagnosing P. aeruginosa infections are time consuming and can require significant preparation of patient samples. This study utilized a novel variation of the Systematic Evolution of Ligand by Exponential Enrichment, Decoy-SELEX, to identify an Exotoxin A specific single-stranded DNA (ssDNA) molecular recognition element (MRE). Its emphasis is on increasing stringency in directing binding toward free target of interest and at the same time decreasing binding toward negative targets. A ssDNA MRE with specificity and affinity was identified after fourteen rounds of Decoy-SELEX. Utilizing surface plasmon resonance measurements, the determined equilibrium dissociation constant of the MRE is between 4.2 µM and 4.5 µM, and is highly selective for Exotoxin A over negative targets. A ssDNA MRE modified sandwich enzyme-linked immunosorbent assay (ELISA) has been developed and achieved sensitive detection of Exotoxin A at nanomolar concentrations in human serum. This study has demonstrated the proof-of-principle of using a ssDNA MRE as a clinical diagnostic tool

Selection of Single-Stranded DNA Molecular Recognition Elements against Exotoxin A Using a Novel Decoy-SELEX Method and Sensitive Detection of Exotoxin A in Human Serum

Exotoxin A is one of the virulence factors of Pseudomonas aeruginosa, a bacterium that can cause infections resulting in adverse health outcomes and increased burden to health care systems. Current methods of diagnosing P. aeruginosa infections are time consuming and can require significant preparation of patient samples. This study utilized a novel variation of the Systematic Evolution of Ligand by Exponential Enrichment, Decoy-SELEX, to identify an Exotoxin A specific single-stranded DNA (ssDNA) molecular recognition element (MRE). Its emphasis is on increasing stringency in directing binding toward free target of interest and at the same time decreasing binding toward negative targets. A ssDNA MRE with specificity and affinity was identified after fourteen rounds of Decoy-SELEX. Utilizing surface plasmon resonance measurements, the determined equilibrium dissociation constant of the MRE is between 4.2 µM and 4.5 µM, and is highly selective for Exotoxin A over negative targets. A ssDNA MRE modified sandwich enzyme-linked immunosorbent assay (ELISA) has been developed and achieved sensitive detection of Exotoxin A at nanomolar concentrations in human serum. This study has demonstrated the proof-of-principle of using a ssDNA MRE as a clinical diagnostic tool

Use of partial least squares regression to impute SNP genotypes in Italian Cattle breeds

Background The objective of the present study was to test the ability of the partial least squares regression technique to impute genotypes from low density single nucleotide polymorphisms (SNP) panels i.e. 3K or 7K to a high density panel with 50K SNP. No pedigree information was used. Methods Data consisted of 2093 Holstein, 749 Brown Swiss and 479 Simmental bulls genotyped with the Illumina 50K Beadchip. First, a single-breed approach was applied by using only data from Holstein animals. Then, to enlarge the training population, data from the three breeds were combined and a multi-breed analysis was performed. Accuracies of genotypes imputed using the partial least squares regression method were compared with those obtained by using the Beagle software. The impact of genotype imputation on breeding value prediction was evaluated for milk yield, fat content and protein content. Results In the single-breed approach, the accuracy of imputation using partial least squares regression was around 90 and 94% for the 3K and 7K platforms, respectively; corresponding accuracies obtained with Beagle were around 85% and 90%. Moreover, computing time required by the partial least squares regression method was on average around 10 times lower than computing time required by Beagle. Using the partial least squares regression method in the multi-breed resulted in lower imputation accuracies than using single-breed data. The impact of the SNP-genotype imputation on the accuracy of direct genomic breeding values was small. The correlation between estimates of genetic merit obtained by using imputed versus actual genotypes was around 0.96 for the 7K chip. Conclusions Results of the present work suggested that the partial least squares regression imputation method could be useful to impute SNP genotypes when pedigree information is not available

A combined long-range phasing and long haplotype imputation method to impute phase for SNP genotypes

<p>Abstract</p> <p>Background</p> <p>Knowing the phase of marker genotype data can be useful in genome-wide association studies, because it makes it possible to use analysis frameworks that account for identity by descent or parent of origin of alleles and it can lead to a large increase in data quantities via genotype or sequence imputation. Long-range phasing and haplotype library imputation constitute a fast and accurate method to impute phase for SNP data.</p> <p>Methods</p> <p>A long-range phasing and haplotype library imputation algorithm was developed. It combines information from surrogate parents and long haplotypes to resolve phase in a manner that is not dependent on the family structure of a dataset or on the presence of pedigree information.</p> <p>Results</p> <p>The algorithm performed well in both simulated and real livestock and human datasets in terms of both phasing accuracy and computation efficiency. The percentage of alleles that could be phased in both simulated and real datasets of varying size generally exceeded 98% while the percentage of alleles incorrectly phased in simulated data was generally less than 0.5%. The accuracy of phasing was affected by dataset size, with lower accuracy for dataset sizes less than 1000, but was not affected by effective population size, family data structure, presence or absence of pedigree information, and SNP density. The method was computationally fast. In comparison to a commonly used statistical method (fastPHASE), the current method made about 8% less phasing mistakes and ran about 26 times faster for a small dataset. For larger datasets, the differences in computational time are expected to be even greater. A computer program implementing these methods has been made available.</p> <p>Conclusions</p> <p>The algorithm and software developed in this study make feasible the routine phasing of high-density SNP chips in large datasets.</p

Scanning Thermal Microscopy and Ballistic Phonon Transport in Lateral Spin Valves

Using scanning thermal microscopy, we have mapped the spatial distribution of temperatures in an operating nanoscale device formed from a magnetic injector, an Ag connecting wire, and a magnetic detector. An analytical model explained the thermal diffusion over the measured temperature range (2–300 K) and injector-detector separation (400–3000 nm). The characteristic diffusion lengths of the Peltier and Joule heat differ remarkably below 60 K, a fact that can be explained by the onset of ballistic phonon heat transfer in the substrate

Selection of Single-Stranded DNA Molecular Recognition Elements against Exotoxin A Using a Novel Decoy-SELEX Method and Sensitive Detection of Exotoxin A in Human Serum

Exotoxin A is one of the virulence factors of Pseudomonas aeruginosa, a bacterium that can cause infections resulting in adverse health outcomes and increased burden to health care systems. Current methods of diagnosing P. aeruginosa infections are time consuming and can require significant preparation of patient samples. This study utilized a novel variation of the Systematic Evolution of Ligand by Exponential Enrichment, Decoy-SELEX, to identify an Exotoxin A specific single-stranded DNA (ssDNA) molecular recognition element (MRE). Its emphasis is on increasing stringency in directing binding toward free target of interest and at the same time decreasing binding toward negative targets. A ssDNA MRE with specificity and affinity was identified after fourteen rounds of Decoy-SELEX. Utilizing surface plasmon resonance measurements, the determined equilibrium dissociation constant (Kd) of the MRE is between 4.2 µM and 4.5 µM, and is highly selective for Exotoxin A over negative targets. A ssDNA MRE modified sandwich enzyme-linked immunosorbent assay (ELISA) has been developed and achieved sensitive detection of Exotoxin A at nanomolar concentrations in human serum. This study has demonstrated the proof-of-principle of using a ssDNA MRE as a clinical diagnostic tool

Extremely short duration high intensity interval training substantially improves insulin action in young healthy males

Background: Traditional high volume aerobic exercise training reduces cardiovascular and metabolic disease risk but involves a substantial time commitment. Extremely low volume high-intensity interval training (HIT) has recently been demonstrated to produce improvements to aerobic function, but it is unknown whether HIT has the capacity to improve insulin action and hence glycemic control. Methods: Sixteen young men (age: 21 ± 2 y; BMI: 23.7 ± 3.1 kg·m-2; VO2peak: 48 ± 9 ml·kg-1·min-1) performed 2 weeks of supervised HIT comprising of a total of 15 min of exercise (6 sessions; 4-6 × 30-s cycle sprints per session). Aerobic performance (250-kJ self-paced cycling time trial), and glucose, insulin and NEFA responses to a 75-g oral glucose load (oral glucose tolerance test; OGTT) were determined before and after training. Results: Following 2 weeks of HIT, the area under the plasma glucose, insulin and NEFA concentration-time curves were all reduced (12%, 37%, 26% respectively, all P < 0.001). Fasting plasma insulin and glucose concentrations remained unchanged, but there was a tendency for reduced fasting plasma NEFA concentrations post-training (pre: 350 ± 36 v post: 290 ± 39 μmol·l-1, P = 0.058). Insulin sensitivity, as measured by the Cederholm index, was improved by 23% (P < 0.01), while aerobic cycling performance improved by ∼6% (P < 0.01). Conclusion: The efficacy of a high intensity exercise protocol, involving only ∼250 kcal of work each week, to substantially improve insulin action in young sedentary subjects is remarkable. This novel time-efficient training paradigm can be used as a strategy to reduce metabolic risk factors in young and middle aged sedentary populations who otherwise would not adhere to time consuming traditional aerobic exercise regimes

Standardising outcome reporting for clinical trials of interventions for heavy menstrual bleeding: Development of a core outcome set

OBJECTIVE: To develop a core outcome set for heavy menstrual bleeding (HMB). DESIGN: Core outcome set (COS) development methodology described by the COMET initiative. SETTING: University hospital gynaecology department, online international survey and web-based international consensus meetings. POPULATION OR SAMPLE: Phase 1: Systematic review of previously reported outcomes to identify potential core outcomes. Phase 2: Qualitative studies with patients to identify outcomes most important to them. Phase 3: Online two-round Delphi survey to achieve consensus about which outcomes are most important. Phase 4: A consensus meeting to finalise the COS. METHODS: Phase 1: Systematic review of previously reported outcomes to identify potential core outcomes. Phase 2: Qualitative studies with patients to identify outcomes most important to them. Phase 3: Online two-round Delphi survey to achieve consensus about which outcomes are most important. Phase 4: A consensus meeting to finalise the COS. MAIN OUTCOME MEASURES: Outcome importance was assessed in the Delphi survey on a 9-point scale. RESULTS: From the ‘long list’ of 114, 10 outcomes were included in the final COS: subjective blood loss; flooding; menstrual cycle metrics; severity of dysmenorrhoea; number of days with dysmenorrhoea; quality of life; adverse events; patient satisfaction; number of patients going on to have further treatment for HMB and haemoglobin level. CONCLUSIONS: The final COS includes variables that are feasible for use in clinical trials in all resource settings and apply to all known underlying causes of the symptom of HMB. These outcomes should be reported in all future trials of interventions, their systematic reviews, and clinical guidelines to underpin policy

The Magnitude of Androgen Receptor Positivity in Breast Cancer Is Critical for Reliable Prediction of Disease Outcome

Purpose: Consensus is lacking regarding the androgen receptor (AR) as a prognostic marker in breast cancer. The objectives of this study were to comprehensively review the literature on AR prognostication and determine optimal criteria for AR as an independent predictor of breast cancer survival. Experimental Design: AR positivity was assessed by immunostaining in two clinically validated primary breast cancer cohorts [training cohort, n = 219; validation cohort, n = 418; 77% and 79% estrogen receptor alpha (ERα) positive, respectively]. The optimal AR cut-point was determined by ROC analysis in the training cohort and applied to both cohorts. Results: AR was an independent prognostic marker of breast cancer outcome in 22 of 46 (48%) previous studies that performed multivariate analyses. Most studies used cut-points of 1% or 10% nuclear positivity. Herein, neither 1% nor 10% cut-points were robustly prognostic. ROC analysis revealed that a higher AR cut-point (78% positivity) provided optimal sensitivity and specificity to predict breast cancer survival in the training (HR, 0.41; P = 0.015) and validation (HR, 0.50; P = 0.014) cohorts. Tenfold cross-validation confirmed the robustness of this AR cut-point. Patients with ERα-positive tumors and AR positivity ≥78% had the best survival in both cohorts (P 0.87) had the best outcomes (P < 0.0001). Conclusions: This study defines an optimal AR cut-point to reliably predict breast cancer survival. Testing this cut-point in prospective cohorts is warranted for implementation of AR as a prognostic factor in the clinical management of breast cancer