Cell fate conversion prediction by group sparse optimization method utilizing single-cell and bulk OMICs data.

Cell fate conversion by overexpressing defined factors is a powerful tool in regenerative medicine. However, identifying key factors for cell fate conversion requires laborious experimental efforts; thus, many of such conversions have not been achieved yet. Nevertheless, cell fate conversions found in many published studies were incomplete as the expression of important gene sets could not be manipulated thoroughly. Therefore, the identification of master transcription factors for complete and efficient conversion is crucial to render this technology more applicable clinically. In the past decade, systematic analyses on various single-cell and bulk OMICs data have uncovered numerous gene regulatory mechanisms, and made it possible to predict master gene regulators during cell fate conversion. By virtue of the sparse structure of master transcription factors and the group structure of their simultaneous regulatory effects on the cell fate conversion process, this study introduces a novel computational method predicting master transcription factors based on group sparse optimization technique integrating data from multi-OMICs levels, which can be applicable to both single-cell and bulk OMICs data with a high tolerance of data sparsity. When it is compared with current prediction methods by cross-referencing published and validated master transcription factors, it possesses superior performance. In short, this method facilitates fast identification of key regulators, give raise to the possibility of higher successful conversion rate and in the hope of reducing experimental cost.

A modified viscosity implicit-type proximal point algorithm for monotone inclusions and asymptotically nonexpansive mappings in Hadamard spaces.

The purpose of this article is to propose a modified viscosity implicit-type proximal point algorithm for approximating a common solution of a monotone inclusion problem and a fixed point problem for an asymptotically nonexpansive mapping in Hadamard spaces. Under suitable conditions, some strong convergence theorems of the proposed algorithms to such a common solution are proved. Our results extend and complement some recent results in this direction.

On stability analysis for generalized Minty variational-hemivariational inequality in reflexive Banach spaces.

The stability for a class of generalized Minty variational-hemivariational inequalities has been considered in reflexive Banach spaces. We demonstrate the equivalent characterizations of the generalized Minty variational-hemivariational inequality. A stability result is presented for the generalized Minty variational-hemivariational inequality with ( f , J ) -pseudomonotone mapping.

Abnormal cortical-basal ganglia network in amyotrophic lateral sclerosis: A voxel-wise network efficiency analysis.

Evidence suggests that dysfunctional cortical-basal ganglia (CBG) network plays important roles in the motor symptoms in amyotrophic lateral sclerosis (ALS). However, little effort has been made to investigate the functional abnormalities of CBG network in ALS. Here, we constructed voxel-wise CBG networks using the resting-state fMRI data of 20 patients with ALS and 21 normal controls, and characterized the differences of their efficiency parameters between the two groups. Compared to normal controls, patients with ALS exhibited decreased nodal efficiency in the right thalamus (THA), the left caudate (CAU) and the right precentral gyrus (preCG), and increased nodal efficiency in the left preCG. In the patient group, we observed a significant negative correlation between the nodal efficiency of the right preCG and disease progression rate. These results demonstrate that both ineffective information transfer and compensatory mechanisms are involved in the pathophysiological mechanism underlying the motor dysfunctions in patients with ALS. In summary, the present study provides a novel perspective on pathophysiological explanation for the motor symptoms in patients with ALS.