We established cell lines with doxycycline-inducible expression of wild type SLCO2A1 (WT-SLCO2A1) and the L563P mutant. Immunofluorescence staining showed that WT-SLCO2A1 and the L563P mutant were dominantly expressed on the plasma membranes of these cells. Cells expressing WT-SLCO2A1 exhibited time- and dose-dependent uptake of PGE2, while the mutant did not show any uptake activity. Residue L563 is very close to the putative substrate-binding site in SLCO2A1, R561 in helix 11. However, in a molecular model of SLCO2A1, the side chain of L563 projected outside of helix 11, indicating that L563 is likely not directly involved in substrate binding. Instead, the substitution of Pro may twist the helix and impair the transporter function. In summary, we identified a novel pathogenic variant of SLCO2A1 that caused loss-of-function and induced CEAS.

Even though all guidelines recommend generally against antipsychotic polypharmacy, antipsychotic polypharmacy appears to be a very common practice across the globe. This study aimed to examine the prescription patterns of antipsychotics in Qatar, in comparison with the international guidelines, and to scrutinize the sociodemographic and clinical features associated with antipsychotic polypharmacy.

All the medical records of all the inpatients and outpatients treated by antipsychotics at the Department of Psychiatry-Hamad Medical Corporation (HMC) in Doha, Qatar (between October 2012 and April 2014) were retrospectively analyzed. We retrieved the available sociodemographic data, psychiatric features, and details on the medication history.

Our sample consisted of 537 individuals on antipsychotics (2/3 were male; mean age 33.8±10.2 years), prescribed for a psychotic disorder in 57%, a mood disorder in 9.3%, and various other diagnoses in 33.7%. About 55.9% received one antipsychotic, 29.6% received two antipsychotics, and 14.5% received more than two antipsychotics. Polypharmacy was associated with younger age (p = 0.025), being single (p<0.001), the diagnosis of a psychotic disorder (p<0.001), and previous admissions to psychiatry (p<0.001).

Antipsychotic polypharmacy appears to be quite common in Qatar, as it is the case in many other countries, in contrast with most international recommendations. Studies are needed to explore the reasons behind this disparity.

Antipsychotic polypharmacy appears to be quite common in Qatar, as it is the case in many other countries, in contrast with most international recommendations. Studies are needed to explore the reasons behind this disparity.Evidence-based models may assist Mexican government officials and health authorities in determining the safest plans to respond to the coronavirus disease 2019 (COVID-19) pandemic in the most-affected region of the country, the Mexico City Metropolitan Area. This study aims to present the potential impacts of COVID-19 in this region and to model possible benefits of mitigation efforts. The COVID-19 Hospital Impact Model for Epidemics was used to estimate the probable evolution of COVID-19 in three scenarios (i) no social distancing, (ii) social distancing in place at 50% effectiveness, and (iii) social distancing in place at 60% effectiveness. Projections of the number of inpatient hospitalizations, intensive care unit admissions, and patients requiring ventilators were made for each scenario. Using the model described, it was predicted that peak case volume at 0% mitigation was to occur on April 30, 2020 at 11,553,566 infected individuals. Peak case volume at 50% mitigation was predicted to occur on June 1, 2020 with 5,970,093 infected individuals and on June 21, 2020 for 60% mitigation with 4,128,574 infected individuals. Occupancy rates in hospitals during peak periods at 0%, 50%, and 60% mitigation would be 875.9%, 322.8%, and 203.5%, respectively, when all inpatient beds are included. Under these scenarios, peak daily hospital admissions would be 40,438, 13,820, and 8,650. Additionally, 60% mitigation would result in a decrease in peak intensive care beds from 94,706 to 23,116 beds and a decrease in peak ventilator need from 67,889 to 17,087 units. Mitigating the spread of COVID-19 through social distancing could have a dramatic impact on reducing the number of infected people and minimize hospital overcrowding. These evidence-based models may enable careful resource utilization and encourage targeted public health responses.The overlap/distinctiveness between Attention-Deficit/Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD) has been increasingly investigated in recent years, particularly since the DSM-5 allows the dual diagnosis of ASD and ADHD, but the underlying brain mechanisms remain unclear. Although both disorders are associated with brain volumetric abnormalities, it is necessary to unfold the shared and specific volume abnormalities that could contribute to explain the similarities and differences in the clinical and neurocognitive profiles between ADHD and ASD. In this voxel-based morphometry (VBM) study, regional grey matter volumes (GMV) were compared between 22 children with ADHD, 18 children with ASD and 17 typically developing (TD) children aged 8 to 12 years old, controlling for age and total intracranial volume. ROCK inhibitor When compared to TD children or children with ASD, children with ADHD had a larger left precuneus, and a smaller right thalamus, suggesting that these brain abnormalities are specific to ADHD relative to ASD. Overall, this study contributes to the delineation of disorder-specific structural abnormalities in ADHD and ASD.Breast cancers with PIK3CA mutations can be treated with PIK3CA inhibitors in hormone receptor-positive HER2 negative subtypes. We applied a supervised elastic net penalized logistic regression model to predict PIK3CA mutations from gene expression data. This regression approach was applied to predict modeling using the TCGA pan-cancer dataset. Approximately 10,000 cases were available for PIK3CA mutation and mRNA expression data. In 10-fold cross-validation, the model with λ = 0.01 and α = 1.0 (ridge regression) showed the best performance, in terms of area under the receiver operating characteristic (AUROC). The final model was developed with selected hyper-parameters using the entire training set. The training set AUROC was 0.93, and the test set AUROC was 0.84. The area under the precision-recall (AUPR) of the training set was 0.66, and the test set AUPR was 0.39. Cancer types were the most important predictors. Both insulin like growth factor 1 receptor (IGF1R) and the phosphatase and tensin homolog (PTEN) were the most significant genes in gene expression predictors.