Analyzing sex imbalance in EGA and dbGaP biological databases: Recommendations for better practices.

Precision medicine aims at tailoring treatments to individual patient's characteristics. In this regard, recognizing the significance of sex and gender becomes indispensable for meeting the distinct healthcare needs of diverse populations. To this end, continuing a trend of improving data quality observed since 2014, the European Genome-phenome Archive (EGA) established a policy in 2018 that mandates data providers to declare the sex of donor samples, aiming to enhance data accuracy and prevent imbalance in sex classification.

Unlocking the effective alliance of β-lapachone and hydroxytyrosol against triple-negative breast cancer cells.

Triple-negative breast cancer (TNBC) is characterised by its aggressiveness and resistance to chemotherapy, demanding the development of effective strategies against its unique characteristics. Derived from lapacho tree bark, β-lapachone (β-LP) selectively targets cancer cells with elevated levels of the detoxifying enzyme NQO1. Hydroxytyrosol (HT) is a phenolic compound derived from olive trees with important anticancer properties that include the inhibition of cancer stem cells (CSCs) and metastatic features in TNBC, as well as relevant antioxidant activities by mechanisms such as the induction of NQO1.

Raising awareness of sex and gender bias in artificial intelligence and health.

Historically, biomedical research has been led by and focused on men. The recent introduction of Artificial Intelligence (AI) in this area has further proven this practice to be discriminatory for other sexes and genders, more noticeably for women. To move towards a fair AI development, it is essential to include sex and gender diversity both in research practices and in the workplace.

Sex and gender differences and biases in artificial intelligence for biomedicine and healthcare.

Precision Medicine implies a deep understanding of inter-individual differences in health and disease that are due to genetic and environmental factors. To acquire such understanding there is a need for the implementation of different types of technologies based on artificial intelligence (AI) that enable the identification of biomedically relevant patterns, facilitating progress towards individually tailored preventative and therapeutic interventions. Despite the significant scientific advances achieved so far, most of the currently used biomedical AI technologies do not account for bias detection.

HLA class I and class II allele distribution in the Peruvian population.

The distribution of HLA-A, -B, -C, -DRB1 and -DQB1 alleles in the Peruvian population was studied and compared with those of other populations in order to provide further information about their anthropological origin. Our data are consistent with the Mestizo character of this population. In terms of genetic distance Peruvians are closest to Bolivians, which is in agreement with the geographical location and the cultural and anthropological background of the two human groups.