Highlights d Mechanical tension-induced Yap activation triggers hepatocyte dedifferentiation d Confinement of cell spreading is sufficient to inhibit hepatocyte dedifferentiation d A chemical cocktail, LBDXL, maintains hepatocyte functions by targeting stress fibers d LBDXL hepatocytes resemble primary hepatocytes in gene expression and functions

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Background Deficits in maintaining and manipulating sequential information online can occur even in patients with mild Parkinson's disease. The subthalamic nucleus may play a modulatory role in the neural system for sequential working memory, which also includes the lateral prefrontal cortex. Objectives The objective of this study was to investigate neural markers of sequential working memory deficits in patients with de novo Parkinson's disease. Methods A total of 50 patients with de novo Parkinson's disease and 50 healthy controls completed a digit ordering task during functional magnetic resonance imaging scanning. The task separated the maintenance (“pure recall”) and manipulation of sequences (“reorder & recall” vs “pure recall”). Results In healthy controls, individual participants' task accuracy was predicted by the regional activation and functional connectivity of the subthalamic nucleus. Healthy participants who showed lower subthalamic nucleus activation and stronger subthalamic nucleus connectivity with the putamen performed more accurately in maintaining sequences (“pure recall”). Healthy participants who showed greater ordering‐related subthalamic nucleus activation change exhibited smaller accuracy costs in manipulating sequences (“reorder & recall” vs “pure recall”). Patients performed less accurately than healthy controls, especially in “reorder & recall” trials, accompanied by an overactivation in the subthalamic nucleus and a loss of synchrony between the subthalamic nucleus and putamen. Individual patients' task accuracy was predicted only by the subthalamic nucleus connectivity. The contribution of the subthalamic nucleus activation or activation change was absent. We observed no change in the lateral prefrontal cortex. Conclusions The overactivation and weakened functional connectivity of the subthalamic nucleus are the neural markers of sequential working memory deficits in de novo Parkinson's disease. © 2020 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society

We demonstrate a label-free, high-throughput cell separation method via a SSAW-based acoustofluidic device with a serpentine channel for clinical diagnosis and point-of-care analysis.

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BackgroundTo optimize marker-assisted selection programs, knowledge of the genetic architecture of phenotypic traits is very important for breeders. Generally, most phenotypes, e.g. morphological and physiological traits, are quantitatively inherited, and thus detection of the genes underlying variation for these traits is difficult. Association mapping based on linkage disequilibrium has recently become a powerful approach to map genes or quantitative trait loci (QTL) in plants.ResultsIn this study, association analysis using 20 simple sequence repeat (SSR) markers was performed to detect the marker loci linked to 13 morphological traits and 10 physiological traits in a wild P. simonii population that consisted of 528 individuals sampled from 16 sites along the Yellow River in China. Based on a model controlling for both population structure (Q) and relative kinship (K), three SSR markers (GCPM_616-1 in 31.2 Mb on LG I, GCPM_4055-2 in 5.7 Mb on LG XV, and GCPM_3142 of unknown location) were identified for seven traits. GCPM_616-1 was associated with five morphological traits (R2 = 5.14-10.09%), whereas GCPM_3142 (15.03%) and GCPM_4055-2 (13.26%) were associated with one morphological trait and one physiological trait, respectively.ConclusionsThe results suggest that this wild population is suitable for association mapping and the identified markers will be suitable for marker-assisted selection breeding or detection of target genes or QTL in the near future.

The synthesis and reactivity of 3,8‐dibromo‐dodecafluoro‐benzo‐fused BOPHY 2 are reported, via SNAr with O‐, N‐ S‐ and C‐nucleophiles, and in Pd(0)‐catalyzed cross‐coupling reactions (Suzuki and Stille). The resulting perfluoro‐BOPHY derivatives were investigated for their reactivity in the presence of various nucleophiles. BOPHY 3 displays reversible color change and fluorescence quenching in the presence of bases (Et3N, DBU), whereas BOPHY 7 reacts preferentially at the α‐pyrrolic positions, and BOPHY 8 undergoes regioselective fluorine substitution in the presence of thiols. The structural and electronic features of the fluorinated BOPHYs were studied by TD‐DFT computations. In addition, their spectroscopic and cellular properties were investigated; BOPHY 10 shows the most red‐shifted absorption/emission (λmax 659/699 nm) and 7 the highest fluorescence (Φf=0.95), while all compounds studied showed low cytotoxicity toward human HEp2 cells and were efficiently internalized.

In this study, an improved eliminate particle swarm optimization (IEPSO) is proposed on the basis of the last-eliminated principle to solve optimization problems in engineering design. During optimization, the IEPSO enhances information communication among populations and maintains population diversity to overcome the limitations of classical optimization algorithms in solving multiparameter, strong coupling, and nonlinear engineering optimization problems. These limitations include advanced convergence and the tendency to easily fall into local optimization. The parameters involved in the imported “local-global information sharing” term are analyzed, and the principle of parameter selection for performance is determined. The performances of the IEPSO and classical optimization algorithms are then tested by using multiple sets of classical functions to verify the global search performance of the IEPSO. The simulation test results and those of the improved classical optimization algorithms are compared and analyzed to verify the advanced performance of the IEPSO algorithm.