Understanding the preferred role in infertility treatment decision making among Chinese infertile women in Hong Kong

Session 38: Managing patient expectations: no. O-140This free journal suppl. entitled: Abstract book of the 31st ESHRE Annual Meeting, Lisbon, Portugal, 14–17 June 2015STUDY QUESTION: What are the treatment decision making preferences in Chinese women undergoing fertility treatments in Hong Kong? ...postprin

Phenomenological scaling laws for ‘‘semidilute’’ macromolecule solutions from light scattering by optical probe particles

Polymer solution dynamics may be inferred from light scattering spectra of dissolved optical probe particles. We compare a variety of probes in solutions of several polymers. In the ‘‘overlapping’’ concentration/molecular weight regime, the Stokes–Einstein equation fails by up to a factor of 2, while the probe diffusion coefficient D follows a scaling law D/D0=exp(−aMγcνRδ) (c, M, and R are the polymer concentration, molecular weight, and the probe radius, respectively). Experimentally, γ=0.8±0.1, ν=0.6–1.0, and δ=−0.1 to 0, contrary to the theoretical predictions γ=0 and δ=1. With very high molecular‐weight polymers, we observe a further ‘‘entangled’’ regime, characterized by huge (104) failures of the Stokes–Einstein equation and the appearance of ‘‘fast’’ modes in the scattering spectrum.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/70873/2/JCPSA6-82-11-5242-1.pd

Apple CRISPR-Cas9-A Recipe for Successful Targeting of AGAMOUS-like Genes in Domestic Apple

Fruit trees and other fruiting hardwood perennials are economically valuable, and there is interest in developing improved varieties. Both conventional breeding and biotechnology approaches are being utilized towards the goal of developing advanced cultivars. Increased knowledge of the effectiveness and efficiency of biotechnology approaches can help guide use of the CRISPR gene-editing technology. Here, we examined CRISPR-Cas9-directed genome editing in the valuable commodity fruit tree Malus x domestica (domestic apple). We transformed two cultivars with dual CRISPR-Cas9 constructs designed to target two AGAMOUS-like genes simultaneously. The main goal was to determine the effectiveness of this approach for achieving target gene changes. We obtained 6 Cas9 control and 38 independent CRISPR-Cas9 events. Of the 38 CRISPR-Cas9 events, 34 (89%) had gene edits and 14 (37%) showed changes to all alleles of both target genes. The most common change was large deletions, which were present in 59% of all changed alleles, followed by small deletions (21%), small insertions (12%), and a combination of small insertions and deletions (8%). Overall, a high rate of successful gene alterations was found. Many of these changes are predicted to cause frameshifts and alterations to the predicted peptides. Future work will include monitoring the floral development and floral form

Tamoxifen Initiation After Ductal Carcinoma In Situ

Endocrine therapy initiation after ductal carcinoma in situ (DCIS) is highly variable and largely unexplained. National guidelines recommend considering tamoxifen for women with estrogen receptor-positive (ER+) DCIS or who undergo excision alone. We evaluated endocrine therapy use after DCIS over a 15-year period in an integrated health care setting to identify factors related to initiation

Application of a Novel Algorithm for Expanding Newborn Screening for Inherited Metabolic Disorders across Europe

Inherited metabolic disorders (IMDs) are mostly rare, have overlapping symptoms, and can be devastating and progressive. However, in many disorders, early intervention can improve long-term outcomes, and newborn screening (NBS) programmes can reduce caregiver stress in the journey to diagnosis and allow patients to receive early, and potentially pre-symptomatic, treatment. Across Europe there are vast discrepancies in the number of IMDs that are screened for and there is an imminent opportunity to accelerate the expansion of evidence-based screening programmes and reduce the disparities in screening programmes across Europe. A comprehensive list of IMDs was created for analysis. A novel NBS evaluation algorithm, described by Burlina et al. in 2021, was used to assess and prioritise IMDs for inclusion on expanded NBS programmes across Europe. Forty-eight IMDs, of which twenty-one were lysosomal storage disorders (LSDs), were identified and assessed with the novel NBS evaluation algorithm. Thirty-five disorders most strongly fulfil the Wilson and Jungner classic screening principles and should be considered for inclusion in NBS programmes across Europe. The recommended disorders should be evaluated at the national level to assess the economic, societal, and political aspects of potential screening programmes

A whole-rock data set for the Skaergaard intrusion, East Greenland

We report a compilation of new and published whole-rock major and trace element analyses for 646 samples of the Skaergaard intrusion, East Greenland. The samples were collected in 14 stratigraphic profiles either from accessible and well-exposed surface areas or from drill core, and they cover most regions of the intrusion. This includes the Layered Series, the Upper Border Series, the Marginal Border Series and the Sandwich Horizon. The geochemical data were obtained by a combination of X-ray fluorescence and inductively coupled plasma mass spectrometry. This data set can, for example, be used to constrain processes of igneous differentiation and ore formation.

Mitigating machine learning bias between high income and low–middle income countries for enhanced model fairness and generalizability

Collaborative efforts in artificial intelligence (AI) are increasingly common between high-income countries (HICs) and low- to middle-income countries (LMICs). Given the resource limitations often encountered by LMICs, collaboration becomes crucial for pooling resources, expertise, and knowledge. Despite the apparent advantages, ensuring the fairness and equity of these collaborative models is essential, especially considering the distinct differences between LMIC and HIC hospitals. In this study, we show that collaborative AI approaches can lead to divergent performance outcomes across HIC and LMIC settings, particularly in the presence of data imbalances. Through a real-world COVID-19 screening case study, we demonstrate that implementing algorithmic-level bias mitigation methods significantly improves outcome fairness between HIC and LMIC sites while maintaining high diagnostic sensitivity. We compare our results against previous benchmarks, utilizing datasets from four independent United Kingdom Hospitals and one Vietnamese hospital, representing HIC and LMIC settings, respectively

Generalizability assessment of AI models across hospitals in a low-middle and high income country

The integration of artificial intelligence (AI) into healthcare systems within low-middle income countries (LMICs) has emerged as a central focus for various initiatives aiming to improve healthcare access and delivery quality. In contrast to high-income countries (HICs), which often possess the resources and infrastructure to adopt innovative healthcare technologies, LMICs confront resource limitations such as insufficient funding, outdated infrastructure, limited digital data, and a shortage of technical expertise. Consequently, many algorithms initially trained on data from non-LMIC settings are now being employed in LMIC contexts. However, the effectiveness of these systems in LMICs can be compromised when the unique local contexts and requirements are not adequately considered. In this study, we evaluate the feasibility of utilizing models developed in the United Kingdom (a HIC) within hospitals in Vietnam (a LMIC). Consequently, we present and discuss practical methodologies aimed at improving model performance, emphasizing the critical importance of tailoring solutions to the distinct healthcare systems found in LMICs. Our findings emphasize the necessity for collaborative initiatives and solutions that are sensitive to the local context in order to effectively tackle the healthcare challenges that are unique to these regions