Sibling Rivalry among Paralogs Promotes Evolution of the Human Brain

Geneticists have long sought to identify the genetic changes that made us human, but pinpointing the functionally relevant changes has been challenging. Two papers in this issue suggest that partial duplication of SRGAP2, producing an incomplete protein that antagonizes the original, contributed to human brain evolution

EXAFS study of rare-earth element coordination in calcite

Extended X-ray absorption fine-structure (EXAFS) spectroscopy is used to characterize the local coordination of selected rare-earth elements (Nd3+, Sm3+, Dy3+, Yb3+) coprecipitated with calcite in minor concentrations from room-temperature aqueous solutions. Fitting results confirm substitution in the Ca site, but first-shell Nd-O and Sm-O distances are longer than the Ca-O distance in calcite and longer than what is consistent with ionic radii sums for sixfold coordination in the octahedral Ca site. In contrast, first-shell Dy-O and Yb-O distances are shorter than the Ca-O distance and are consistent with ionic radii sums for sixfold coordination. Comparison of Nd-O and Sm-O bond lengths with those in lanthanide sesquioxides and with ionic radii trends across the lanthanide series suggests that Nd3+ and Sm3+ have sevenfold coordination in a modified Ca site in calcite. This would require some disruption of the local structure, with an expected decrease in stability, and possibly a different charge compensation mechanism between Nd and Sm vs. Yb and Dy. A possible explanation for the increased coordination for the larger rare-earth elements involves bidentate ligation from a CO3 group. Because trivalent actinides such as Am3+ and Cm3+ have ionic radii similar to Nd3+, their incorporation in calcite may result in a similar defect structure

Treatment detection and movement disorder society-unified Parkinson's disease rating scale, part III estimation using finger tapping tasks

The validation of objective and easy-to-implement biomarkers that can monitor the effects of fast-acting drugs among Parkinson's disease (PD) patients would benefit antiparkinsonian drug development. We developed composite biomarkers to detect levodopa/carbidopa effects and to estimate PD symptom severity. For this development, we trained machine learning algorithms to select the optimal combination of finger tapping task features to predict treatment effects and disease severity. Data were collected during a placebo-controlled, crossover study with 20 PD patients. The alternate index and middle finger tapping (IMFT), alternative index finger tapping (IFT), and thumb-index finger tapping (TIFT) tasks and the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) III were performed during treatment. We trained classification algorithms to select features consisting of the MDS-UPDRS III item scores; the individual IMFT, IFT, and TIFT; and all three tapping tasks collectively to classify treatment effects. Furthermore, we trained regression algorithms to estimate the MDS-UPDRS III total score using the tapping task features individually and collectively. The IFT composite biomarker had the best classification performance (83.50% accuracy, 93.95% precision) and outperformed the MDS-UPDRS III composite biomarker (75.75% accuracy, 73.93% precision). It also achieved the best performance when the MDS-UPDRS III total score was estimated (mean absolute error: 7.87, Pearson's correlation: 0.69). We demonstrated that the IFT composite biomarker outperformed the combined tapping tasks and the MDS-UPDRS III composite biomarkers in detecting treatment effects. This provides evidence for adopting the IFT composite biomarker for detecting antiparkinsonian treatment effect in clinical trials. & COPY; 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.Perioperative Medicine: Efficacy, Safety and Outcome (Anesthesiology/Intensive Care

Efficient algorithms for the smallest enclosing ball problem

10.1007/s10589-005-4565-7Computational Optimization and Applications302147-160CPPP