Low-Valent Mx Al3 Cluster Salts with Tetrahedral [SiAl3 ]+ and Trigonal-Bipyramidal [M2 Al3 ]2+ Cores (M=Si/Ge)

Schnöckel's [(AlCp*)4] and Jutzi's [SiCp*][B(C6F5)4] (Cp*=C5Me5) are landmarks in modern main-group chemistry with diverse applications in synthesis and catalysis. Despite the isoelectronic relationship between the AlCp* and the [SiCp*]+ fragments, their mutual reactivity is hitherto unknown. Here, we report on their reaction giving the complex salts [Cp*Si(AlCp*)3][WCA] ([WCA]−=[Al(ORF)4]− and [F{Al(ORF)3}2]−; RF=C(CF3)3). The tetrahedral [SiAl3]+ core not only represents a rare example of a low-valent silicon-doped aluminium-cluster, but also—due to its facile accessibility and high stability—provides a convenient preparative entry towards low-valent Si−Al clusters in general. For example, an elusive binuclear [Si2(AlCp*)5]2+ with extremely short Al−Si bonds and a high negative partial charge at the Si atoms was structurally characterised and its bonding situation analysed by DFT. Crystals of the isostructural [Ge2(AlCp*)5]2+ dication were also obtained and represent the first mixed Al−Ge cluster

A generalizable deep voxel-guided morphometry algorithm for the detection of subtle lesion dynamics in multiple sclerosis

IntroductionMultiple sclerosis (MS) is a chronic neurological disorder characterized by the progressive loss of myelin and axonal structures in the central nervous system. Accurate detection and monitoring of MS-related changes in brain structures are crucial for disease management and treatment evaluation. We propose a deep learning algorithm for creating Voxel-Guided Morphometry (VGM) maps from longitudinal MRI brain volumes for analyzing MS disease activity. Our approach focuses on developing a generalizable model that can effectively be applied to unseen datasets.MethodsLongitudinal MS patient high-resolution 3D T1-weighted follow-up imaging from three different MRI systems were analyzed. We employed a 3D residual U-Net architecture with attention mechanisms. The U-Net serves as the backbone, enabling spatial feature extraction from MRI volumes. Attention mechanisms are integrated to enhance the model's ability to capture relevant information and highlight salient regions. Furthermore, we incorporate image normalization by histogram matching and resampling techniques to improve the networks' ability to generalize to unseen datasets from different MRI systems across imaging centers. This ensures robust performance across diverse data sources.ResultsNumerous experiments were conducted using a dataset of 71 longitudinal MRI brain volumes of MS patients. Our approach demonstrated a significant improvement of 4.3% in mean absolute error (MAE) against the state-of-the-art (SOTA) method. Furthermore, the algorithm's generalizability was evaluated on two unseen datasets (n = 116) with an average improvement of 4.2% in MAE over the SOTA approach.DiscussionResults confirm that the proposed approach is fast and robust and has the potential for broader clinical applicability

Diverse Toolbox of Reactive (Di-)Gallenes for Bond Activation

xyz and orca output file

Chemical- and light-induced isomerization of the P=C bond of a 1-phosphabutadiene

Treatment of Mes*P=C(Si(CH3)3)Br with CH2=CHMgBr in the presence of Pd(0) affords 1-phosphabutadiene Mes*P=C(Si(CH3)3)–CH=CH2 (1) selectively as the Z isomer. Remarkably, treatment of Z-1 with n-BuLi (0.1 equiv.) resulted in quantitative formation of E-1. The exact role of the n-BuLi is unknown; however, it appears to be required to promote the isomerization in the absence of light. The isomerization of Z-1 to E-1 was also mediated by sunlight with the reaction mixture consisting of a ca. 1:9 ratio of Z-1 to E-1. DFT calculations were consistent with the thermodynamic favorability of the isomerization of Z-1 to E-1.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Individual Assessment of Brain Tissue Changes in MS and the Effect of Focal Lesions on Short-Term Focal Atrophy Development in MS: A Voxel-Guided Morphometry Study

We performed voxel-guided morphometry (VGM) investigating the mechanisms of brain atrophy in multiple sclerosis (MS) related to focal lesions. VGM maps detect regional brain changes when comparing 2 time points on high resolution T1-weighted (T1w) magnetic resonace imaging (MRI). Two T1w MR datasets from 92 relapsing-remitting MS patients obtained 12 months apart were analysed with VGM. New lesions and volume changes of focal MS lesions as well as in the surrounding tissue were identified by visual inspection on colour coded VGM maps. Lesions were dichotomized in active and inactive lesions. Active lesions, defined by either new lesions (NL) (volume increase > 5% in VGM), chronic enlarging lesions (CEL) (pre-existent T1w lesions with volume increase > 5%), or chronic shrinking lesions (CSL) (pre-existent T1w lesions with volume reduction > 5%) in VGM, were accompanied by tissue shrinkage in surrounding and/or functionally related regions. Volume loss within the corpus callosum was highly correlated with the number of lesions in its close proximity. Volume loss in the lateral geniculate nucleus was correlated with lesions along the optic radiation. VGM analysis provides strong evidence that all active lesion types (NL, CEL, and CSL) contribute to brain volume reduction in the vicinity of lesions and/or in anatomically and functionally related areas of the brain