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BACKGROUND Intellectual disability (ID) affects 1-3% of the Western population and is heterogeneous in origin. Mutations in X-linked genes represent 5-10% of ID in males. Fragile X syndrome, due to the silencing of the FMR1 gene, is the most common form of ID, with a prevalence of around 15000 males. Females are usually non- or mildly affected carriers, and in a few rare cases, the only gender affected. Array comparative genome hybridization (aCGH) and next-generation sequencing (NGS) have dramatically changed the nature of human genome analysis leading to the identification of new X-linked intellectual disability syndromes and disease-causing genes. SOURCES OF DATA Original papers, reviews, guidelines and experiences of the diagnostic laboratories. AREAS OF AGREEMENT Family history and clinical examination still are essential to choose the appropriate diagnostic tests, including, a disease-specific genetic test, aCGH or FMR1 molecular analysis. If negative, NGS approaches like well-defined gene panels, wholend to develop cost-effective functional tools, which can be easily transferred to diagnostics. © The Author(s) 2020. Published by Oxford University Press. All rights reserved. For Permissions, please email journals.permissions@oup.com.AIMS Baculoviral inhibitor of apoptosis repeat containing 5 (BIRC5) plays vital roles in carcinogenesis by influencing cell division and proliferation and by inhibiting apoptosis. However, the prognostic significance of BIRC5 remains unclear in breast cancer. METHODS BIRC5 expression and methylation status were evaluated using the Oncomine and The Cancer Genome Atlas (TCGA) databases. The relevance between BIRC5 and different clinicopathological features as well as survival information was analyzed using the bc-GenExMiner database and Kaplan-Meier Plotter. BIRC5-drug interaction network was obtained using the Comparative Toxicogenomics Database. RESULTS Based on the results from databases and own hospital data, BIRC5 was higher expressed in different breast cancer subtypes compared with the matched normal individuals. mTOR inhibitor Hormone receptors were negatively correlated with BIRC5 expression, whereas the Scarff-Bloom-Richardson (SBR) grade, Nottingham Prognostic Index (NPI), human epidermal growth factor receptor-2 (HER-2) status, basal-like status, and triple-negative status were positively related to BIRC5 level in breast cancer samples with respect to normal tissues. High BIRC5 expression was responsible for shorter relapse-free survival, worse overall survival, reduced distant metastasis free survival, and increased risk of metastatic relapse event. BIRC5-drug interaction network indicated that several common drugs could modulate BIRC5 expression. Furthermore, a positive correlation between BIRC5 andcell-division cycle protein 20 (CDC20) gene was confirmed. CONCLUSION BIRC5 may be adopted as a promising predictive marker and potential therapeutic target in breast cancer. Further large-scale studies are needed to more precisely confirm the value of BIRC5 in treatment of breast cancer. © 2020 The Author(s).Drug repositioning can drastically decrease the cost and duration taken by traditional drug research and development while avoiding the occurrence of unforeseen adverse events. With the rapid advancement of high-throughput technologies and the explosion of various biological data and medical data, computational drug repositioning methods have been appealing and powerful techniques to systematically identify potential drug-target interactions and drug-disease interactions. In this review, we first summarize the available biomedical data and public databases related to drugs, diseases and targets. Then, we discuss existing drug repositioning approaches and group them based on their underlying computational models consisting of classical machine learning, network propagation, matrix factorization and completion, and deep learning based models. We also comprehensively analyze common standard data sets and evaluation metrics used in drug repositioning, and give a brief comparison of various prediction methods on the gold standard data sets. Finally, we conclude our review with a brief discussion on challenges in computational drug repositioning, which includes the problem of reducing the noise and incompleteness of biomedical data, the ensemble of various computation drug repositioning methods, the importance of designing reliable negative samples selection methods, new techniques dealing with the data sparseness problem, the construction of large-scale and comprehensive benchmark data sets and the analysis and explanation of the underlying mechanisms of predicted interactions. © The Author(s) 2020. Published by Oxford University Press. All rights reserved. For Permissions, please email journals.permissions@oup.com.BACKGROUND Collagen type X alpha 1 (COL10A1) is overexpressed in diverse tumors and displays vital roles in tumorigenesis. link2 However, the prognostic value of COL10A1 in breast cancer remains unclear. METHODS The expression of COL10A1 was analyzed by the Oncomine database and UALCAN cancer database. The relationship between COL10A1 expression level and clinical indicators including prognostic data in breast cancer were analyzed by the Kaplan-Meier Plotter, PrognoScan, and Breast Cancer Gene-Expression Miner (bc-GenExMiner) databases. RESULTS COL10A1 was up-regulated in different subtypes of breast cancer. Estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor-2 (HER-2) status and nodal status were positively correlated with COL10A1 expression. link3 Conversely, age, the Scarff-Bloom-Richardson (SBR) grade, basal-like status, and triple-negative status were negatively related to COL10A1 level in breast cancer samples compared with normal tissues. Patients with increased COL10A1 expression level showed worse overall survival (OS), relapse-free survival (RFS), distant metastasis-free survival (DMFS) and disease-free survival (DFS). COL10A1 was positively correlated with metastatic relapse-free survival. GSEA analysis revealed that enrichment of TGF-β signaling pathway. 15-leucine-rich repeat containing membrane protein (LRRC15) is a correlated gene of COL10A1. CONCLUSION Bioinformatics analysis revealed that COL10A1 might be considered as a predictive biomarker for prognosis of breast cancer. Further experiments and clinical trials are essential to elucidate the value of COL10A1 in breast cancer treatment. © 2020 The Author(s).BACKGROUND Longitudinal evidence of poor visual acuity associating with higher risk of incident dementia is mixed. This study aimed to examine if poor visual acuity was associated with higher dementia incidence in a large community cohort of older adults, independent of the possible biases relating to misclassification error, reverse causality, and confounding effects due to health problems and behaviours. METHODS A total of 15,576 community-living older adults without dementia at baseline were followed for 6 years to the outcome of incident dementia, which was diagnosed according to the ICD-10 or a Clinical Dementia Rating of 1 to 3. Visual acuity was assessed using the Snellen's chart at baseline and follow-up. Important variables including demographics (age, sex, education, and socioeconomic status), physical and psychiatric comorbidities (cardiovascular risks, ophthalmological conditions, hearing impairment, poor mobility, and depression), and lifestyle behaviours (smoking, diet, physical, intellectual, and social activities) were also assessed. RESULTS Over 68,904 person-years of follow-up, 1,349 participants developed dementia. Poorer visual acuity at baseline was associated with higher dementia incidence in 6 years, even after adjusting for demographics, health problems, and lifestyle behaviours, and excluding those who developed dementia within 3 years after baseline. Compared with normal vision, the hazard ratio of dementia was 1.19 (p=0.31), 2.09 (p less then 0.001), and 8.66 (p less then 0.001) for mild, moderate, and severe visual impairment, respectively. CONCLUSIONS Moderate-to-severe visual impairment could be a potential predictor and possibly a risk factor for dementia. From a clinical perspective, older adults with poor visual acuity might warrant further risk assessment for dementia. © The Author(s) 2020. Published by Oxford University Press on behalf of The Gerontological Society of America.Biofilms that form on reusable medical devices are a cause of hospital acquired infections; however, sanitization of biofilms is a challenge due to their dense extracellular matrix. This work presents an innovative strategy using biocide-loaded iron oxide nanoparticles transported within the matrix via a magnetic field to eradicate biofilms. Results show that the active delivery of the biocide to underlying cells effectively penetrates the extracellular matrix and inactivates Methicillin resistant Staphylococcus aureus (MRSA) biofilms (responsible for several difficult-to-treat infections in humans). To optimize this treatment, the loading of spherical, cubic and tetrapod-shaped nanoparticles with a model biocide, CTAB (cetyltrimethylammonium bromide) was studied. Biocide loading was determined to be dependent on the shapes' surface charge density instead of the surface area, meaning that biocide attachment is greater for nanoparticles with sharp edges (e.g. cubes and tetrapods). These results can be used to optimize treatment efficacy, and help further understanding of biofilm and nanoparticle surface zeta potentials, and the nanoparticle-biofilm interactions.Hybrid nanostructures are constructed by the direct coupling of fluorescent quantum dots and plasmonic gold nanoparticles. Self-assembly is directed by the strong affinity between two artificial α-repeat proteins that are introduced in the capping layers of the nanoparticles at a controlled surface density. The proteins have been engineered to exhibit a high mutual affinity, corresponding to a dissociation constant in the nanomolar range, towards the protein-functionalized quantum dots and gold nanoparticles. Protein-mediated self-assembly is evidenced by surface plasmon resonance and gel electrophoresis. The size and the structure of colloidal superstructures of complementary nanoparticles are analyzed by transmission electron microscopy and small angle X-ray scattering. The size of the superstructures is determined by the number of proteins per nanoparticle. The well-defined geometry of the rigid protein complex sets a highly uniform interparticle distance of 8 nm that affects the emission properties of the quantum dots in the hybrid ensembles. Our results open the route to the design of hybrid emitter-plasmon colloidal assemblies with controlled near-field coupling and better optical response.The electrocatalytic hydrogen evolution reaction (HER) is an efficient and economic pathway to generate clean hydrogen energy in a sustainable manner. To improve the HER activity of Earth-abundant catalysts, reducing the dimension of materials is an effective strategy, and in this context two-dimensional (2D) materials have received substantial research attention owing to their large surface area and 2D charge transport channels. However, the thermodynamically stable basal surface of 2D catalysts is usually inactive in catalysis, which significantly impedes further optimization of the 2D HER catalysts. In this Minireview, we highlight in detail that defect engineering in 2D catalysts could bring multiple benefits in improving the HER activity. From the point of view of kinetics, defect sites could serve as active sites for catalyzing the HER process directly, and the introduction of defect structures may result in the optimization of electronic structures of the catalysts, thereby facilitating the HER process.