Cellular preconditioning and mesenchymal stem cell ferroptosis

In this editorial,we comment on the article published in the recent issue of the World Journal of Stem Cells.They focus on stem cell preconditioning to prevent ferroptosis by modulating the cystathionineγ-lyase/hydrogen sulfide(H_(2)S)pathway as a novel approach to treat vascular disorders,particularly pulmonary hypertension.Preconditioned stem cells are gaining popularity in regenerative medicine due to their unique ability to survive by resisting the harsh,unfavorable microenvironment of the injured tissue.They also secrete various paracrine factors against apoptosis,necrosis,and ferroptosis to enhance cell survival.Ferroptosis,a regulated form of cell death characterized by iron accumulation and oxidative stress,has been implicated in various pathologies encompassing dege-nerative disorders to cancer.The lipid peroxidation cascade initiates and sustains ferroptosis,generating many reactive oxygen species that attack and damage multiple cellular structures.Understanding these intertwined mechanisms provi-des significant insights into developing therapeutic modalities for ferroptosis-related diseases.This editorial primarily discusses stem cell preconditioning in modulating ferroptosis,focusing on the cystathionase gamma/H_(2)S ferroptosis pathway.Ferroptosis presents a significant challenge in mesenchymal stem cell(MSC)-based therapies;hence,the emerging role of H_(2)S/cystathionase gamma/H_(2) S signaling in abrogating ferroptosis provides a novel option for therapeutic intervention.Further research into understanding the precise mechanisms of H_(2)S-mediated cytoprotection against ferroptosis is warranted to enhance the thera-peutic potential of MSCs in clinical settings,particularly vascular disorders.

Semi-regularized Hermitian and Skew-Hermitian Splitting Preconditioning for Saddle-Point Linear Systems

In this paper,a two-step semi-regularized Hermitian and skew-Hermitian splitting(SHSS)iteration method is constructed by introducing a regularization matrix in the(1,1)-block of the first iteration step,to solve the saddle-point linear system.By carefully selecting two different regularization matrices,two kinds of SHSS preconditioners are proposed to accelerate the convergence rates of the Krylov subspace iteration methods.Theoretical analysis about the eigenvalue distribution demonstrates that the proposed SHSS preconditioners can make the eigenvalues of the corresponding preconditioned matrices be clustered around 1 and uniformly bounded away from 0.The eigenvector distribution and the upper bound on the degree of the minimal polynomial of the SHSS-preconditioned matrices indicate that the SHSS-preconditioned Krylov subspace iterative methods can converge to the true solution within finite steps in exact arithmetic.In addition,the numerical example derived from the optimal control problem shows that the SHSS preconditioners can significantly improve the convergence speeds of the Krylov subspace iteration methods,and their convergence rates are independent of the discrete mesh size.

Two-Parameter Block Triangular Splitting Preconditioner for Block Two-by-Two Linear Systems

This paper proposes a two-parameter block triangular splitting(TPTS)preconditioner for the general block two-by-two linear systems.The eigenvalues of the corresponding preconditioned matrix are proved to cluster around 0 or 1 under mild conditions.The limited numerical results show that the TPTS preconditioner is more efficient than the classic block-diagonal and block-triangular preconditioners when applied to the flexible generalized minimal residual(FGMRES)method.

Searching for the optimal precondition procedure for mesenchymal stem/stromal cell treatment:Facts and perspectives

Mesenchymal stem/stromal cells are potential optimal cell sources for stem cell therapies,and pretreatment has proven to enhance cell vitality and function.In a recent publication,Li et al explored a new combination of pretreatment condi-tions.Here,we present an editorial to comment on their work and provide our view on mesenchymal stem/stromal cell precondition.

Small extracellular vesicles from hypoxia-preconditioned bone marrow mesenchymal stem cells attenuate spinal cord injury via miR-146a-5p-mediated regulation of macrophage polarization

Spinal cord injury is a disabling condition with limited treatment options.Multiple studies have provided evidence suggesting that small extracellular vesicles(SEVs)secreted by bone marrow mesenchymal stem cells(MSCs)help mediate the beneficial effects conferred by MSC transplantation following spinal cord injury.Strikingly,hypoxia-preconditioned bone marrow mesenchymal stem cell-derived SEVs(HSEVs)exhibit increased therapeutic potency.We thus explored the role of HSEVs in macrophage immune regulation after spinal cord injury in rats and their significance in spinal cord repair.SEVs or HSEVs were isolated from bone marrow MSC supernatants by density gradient ultracentrifugation.HSEV administration to rats via tail vein injection after spinal cord injury reduced the lesion area and attenuated spinal cord inflammation.HSEVs regulate macrophage polarization towards the M2 phenotype in vivo and in vitro.Micro RNA sequencing and bioinformatics analyses of SEVs and HSEVs revealed that mi R-146a-5p is a potent mediator of macrophage polarization that targets interleukin-1 receptor-associated kinase 1.Reducing mi R-146a-5p expression in HSEVs partially attenuated macrophage polarization.Our data suggest that HSEVs attenuate spinal cord inflammation and injury in rats by transporting mi R-146a-5p,which alters macrophage polarization.This study provides new insights into the application of HSEVs as a therapeutic tool for spinal cord injury.

Hypoxia-preconditioned bone marrow-derived mesenchymal stem cells protect neurons from cardiac arrest-induced pyroptosis

Cardiac arrest can lead to severe neurological impairment as a result of inflammation,mitochondrial dysfunction,and post-cardiopulmonary resuscitation neurological damage.Hypoxic preconditioning has been shown to improve migration and survival of bone marrow–derived mesenchymal stem cells and reduce pyroptosis after cardiac arrest,but the specific mechanisms by which hypoxia-preconditioned bone marrow–derived mesenchymal stem cells protect against brain injury after cardiac arrest are unknown.To this end,we established an in vitro co-culture model of bone marrow–derived mesenchymal stem cells and oxygen–glucose deprived primary neurons and found that hypoxic preconditioning enhanced the protective effect of bone marrow stromal stem cells against neuronal pyroptosis,possibly through inhibition of the MAPK and nuclear factor κB pathways.Subsequently,we transplanted hypoxia-preconditioned bone marrow–derived mesenchymal stem cells into the lateral ventricle after the return of spontaneous circulation in an 8-minute cardiac arrest rat model induced by asphyxia.The results showed that hypoxia-preconditioned bone marrow–derived mesenchymal stem cells significantly reduced cardiac arrest–induced neuronal pyroptosis,oxidative stress,and mitochondrial damage,whereas knockdown of the liver isoform of phosphofructokinase in bone marrow–derived mesenchymal stem cells inhibited these effects.To conclude,hypoxia-preconditioned bone marrow–derived mesenchymal stem cells offer a promising therapeutic approach for neuronal injury following cardiac arrest,and their beneficial effects are potentially associated with increased expression of the liver isoform of phosphofructokinase following hypoxic preconditioning.

PRECONDITIONED GAUSS-SEIDEL TYPE ITERATIVE METHOD FOR SOLVING LINEAR SYSTEMS

The preconditioned Gauss-Seidel type iterative method for solving linear systems, with the proper choice of the preconditioner, is presented. Convergence of the preconditioned method applied to Z-matrices is discussed. Also the optimal parameter is presented. Numerical results show that the proper choice of the preconditioner can lead to effective by the preconditioned Gauss-Seidel type iterative methods for solving linear systems.

An overview of ischemic preconditioning in exercise performance:A systematic review

Ischemic preconditioning(IPC)is an attractive method for athletes owing to its potential to enhance exercise performance.However,the effectiveness of the IPC intervention in the field of sports science remains mitigated.The number of cycles of ischemia and reperfusion,as well as the duration of the cycle,varies from one study to another;Thus,the aim of this systematic review was to provide a comprehensive review examining the IPC literature in sports science.A systematic literature search was performed in PubMed(MEDLINE)(from 1946 to May 2018),Web of Science(sport sciences)(from 1945 to May 2018),and EMBASE(from 1974 to May 2018).We included all studies investigating the effects of IPC on exercise performance in human subjects.To assess scientific evidence for each study,this review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement.The electronic database search generated 441 potential articles that were screened for eligibility.A total of 52 studies were identified as eligible and valid for this systematic review.The studies included were of high quality,with 48 of the 52 studies having a ran?domized,controlled trial design.Most studied showed that IPC intervention can be beneficial to exercise performance.However,IPC intervention seems to be more beneficial to healthy subjects who wish to enhance their performance in aerobic exercises than athletes.Thus,this systematic review highlights that a better knowledge of the mechanisms generated by the IPC intervention would make it possible to optimize the protocols according to the characteristics of the subjects with the aim of suggesting to the subjects the best possible experience of IPC intervention.

A High-Quality Preconditioning Technique for Multi-Length-Scale Symmetric Positive Definite Linear Systems

We study preconditioning techniques used in conjunction with the conjugate gradient method for solving multi-length-scale symmetric positive definite linear systems originating from the quantum Monte Carlo simulation of electron interaction of correlated materials. Existing preconditioning techniques are not designed to be adaptive to varying numerical properties of the multi-length-scale systems. In this paper, we propose a hybrid incomplete Cholesky （HIC） preconditioner and demonstrate its adaptivity to the multi-length-scale systems. In addition, we propose an extension of the compressed sparse column with row access （CSCR） sparse matrix storage format to efficiently accommodate the data access pattem to compute the HIC preconditioner. We show that for moderately correlated materials, the HIC preconditioner achieves the optimal linear scaling of the simulation. The development of a linear-scaling preconditioner for strongly correlated materials remains an open topic.

Biorthogonal Wavelet Based Algebraic Multigrid Preconditioners for Large Sparse Linear Systems

In this article algebraic multigrid as preconditioners are designed, with biorthogonal wavelets, as intergrid operators for the Krylov subspace iterative methods. Construction of hierarchy of matrices in algebraic multigrid context is based on lowpass filter version of Wavelet Transform. The robustness and efficiency of this new approach is tested by applying it to large sparse, unsymmetric and ill-conditioned matrices from Tim Davis collection of sparse matrices. Proposed preconditioners have potential in reducing cputime, operator complexity and storage space of algebraic multigrid V-cycle and meet the desired accuracy of solution compared with that of orthogonal wavelets.

Preconditioned Iterative Methods for Algebraic Systems from Multiplicative Half-Quadratic Regularization Image Restorations

Image restoration is often solved by minimizing an energy function consisting of a data-fidelity term and a regularization term.A regularized convex term can usually preserve the image edges well in the restored image.In this paper,we consider a class of convex and edge-preserving regularization functions,i.e.,multiplicative half-quadratic regularizations,and we use the Newton method to solve the correspondingly reduced systems of nonlinear equations.At each Newton iterate,the preconditioned conjugate gradient method,incorporated with a constraint preconditioner,is employed to solve the structured Newton equation that has a symmetric positive definite coefficient matrix. The eigenvalue bounds of the preconditioned matrix are deliberately derived,which can be used to estimate the convergence speed of the preconditioned conjugate gradient method.We use experimental results to demonstrate that this new approach is efficient, and the effect of image restoration is reasonably well.

Hypoxia and inflammatory factor preconditioning enhances the immunosuppressive properties of human umbilical cord mesenchymal stem cells

BACKGROUND Mesenchymal stem cells(MSCs)have great potential for the treatment of various immune diseases due to their unique immunomodulatory properties.However,MSCs exposed to the harsh inflammatory environment of damaged tissue after intravenous transplantation cannot exert their biological effects,and therefore,their therapeutic efficacy is reduced.In this challenging context,an in vitro preconditioning method is necessary for the development of MSC-based therapies with increased immunomodulatory capacity and transplantation efficacy.AIM To determine whether hypoxia and inflammatory factor preconditioning increases the immunosuppressive properties of MSCs without affecting their biological characteristics.METHODS Umbilical cord MSCs(UC-MSCs)were pretreated with hypoxia(2%O_(2))exposure and inflammatory factors(interleukin-1β,tumor necrosis factor-α,interferon-γ)for 24 h.Flow cytometry,polymerase chain reaction,enzyme-linked immunosorbent assay and other experimental methods were used to evaluate the biological characteristics of pretreated UC-MSCs and to determine whether pretreatment affected the immunosuppressive ability of UC-MSCs in coculture with immune cells.RESULTS Pretreatment with hypoxia and inflammatory factors caused UC-MSCs to be elongated but did not affect their viability,proliferation or size.In addition,pretreatment significantly decreased the expression of coagulationrelated tissue factors but did not affect the expression of other surface markers.Similarly,mitochondrial function and integrity were retained.Although pretreatment promoted UC-MSC apoptosis and senescence,it increased the expression of genes and proteins related to immune regulation.Pretreatment increased peripheral blood mononuclear cell and natural killer(NK)cell proliferation rates and inhibited NK cell-induced toxicity to varying degrees.CONCLUSION In summary,hypoxia and inflammatory factor preconditioning led to higher immunosuppressive effects of MSCs without damaging their biological characteristics.

Systemic omics analysis of the hub genes, proteins, metabolites and metabolic pathways related to the hypoxia preconditioning in mice

Hypoxia preconditioning （HPC） is associated with many complicated pathophysiological and biochemical processes that integrated and regulated via molecular levels. HPC could protect cells, tissues, organs and systems from hypoxia injury, but up to date, the molecular mechanism still remained unclear. The acute and repetitive hy- poxia preconditioning model was constructed and the related parameters were observed. The high-throughput mi- croarray analysis and multiple bioinformatics were used to explore the differentially expressed genes in HPC mice brain and the related gene network, pathways and biological processes related to HPC. The 2D-DIGE coupled with MALDI-TOF/TOF-MS was performed to identify these proteins that were differentially expressed during HPC. The UPLC-HRMS based metabolomics method was utilized to explore the key endogenous metabolites and metabolic pathways related to HPC. The results showed that （1） 1175 differentially expressed genes in HPC mice brain were identified. Fourteen of these genes were the related hub genes for HPC, including Cacna2dl, Grin2a, Npylr, Mef2c, Epha4, Rxfpl, Chrm3, Pdela, Atp2b4, Glral, Idil , Fgfl, Grin2b and Cda. The change trends of all the detected genes by RT-PCR were consistent with the data of gene chips. There were 113 significant functions up- regulated and 138 significant functions down-regulated in HPC mice. （2） About 2100 proteins were revealed via the gel imaging and spot detection. 66, 45 and 70 of proteins were found to have significantly difference between the control group and three times of HPC group, the control and six times of HPC, and the three times of HPC and six times of HPC group. （3）Some endogenous metabolites such as phenylalanine, valine, proline, leucine and glu- tamine were increased, while ereatine was decreased, both in HPC brain and heart; in addition, y-aminobutyric acid was markedly decreased in brain. The sphingolipid metabolic pathways were noticed due to the low p-value and high pathway impact. Especially, the sphingolipid compound sphingomyelin, ceramide, glucosyleeramide, galactosylceramide and laetosylceramide were mapping in this metabolic pathway. Interestingly, these sphingolipid metabolites with olefinic bond in the long fatty chain were up-regulated, while those sphingolipids without olefinic bond were down-regulated. The functions of these differentially expressed genes mainly involved the cellular proces- ses including MAPK pathway, ion transport, neurotransmitter transport and neuropeptide signal pathway. The pro- tein levels related the ATP synthesis and citric acid cycle decreased while the proteins with the glycolysis and oxy- gen-binding increased. Glutathione, GNBP-1 and GPD1L were related to preventing hypoxic damage. The results indicated that C24：l-Cers played a critical role in HPC and had potential in endogenous protective mechanism. The combinations of the system omies data of the different molecules were sufficient to give a further understanding of the molecular pathways affected by HPC. Our data provided an important insight to reveal the protection mechanism of HPC.

A NEW ILU PRECONDITIONER FOR BORDERED LINEAR SYSTEMS

Bordered linear systems arise from many industrial applications, such as reservoir simulation and structural engineering. Traditional ILU preconditioners which throw away the additional equations are often too crude for these systems. We describe a practical implementation of ILU preconditioners which are more accurate and more robust. The emphasis of this paper is on implementation rather than on theory.

The NO/ET-1 System Is Involved in the Protection of the Hepatic Ischemic Preconditioning

To study the relationship between the disturbance of nitric oxide/endothelin-1 (NO/ET-1) and the hepatic ischemia/reperfusion (I/R) injury as well as the regulation of the NO/ET-1 system by the hepatic ischemic preconditioning (IPC), the changes of the NO/ET-1 system and their relationship with the hepatic I/R injury were compared between the I/R group and the IPC+I/R group in a rat hepatic I/R model. 2 h after reperfusion, the liver tissues were examined for expressed inducible nitric oxide synthase (iNOS) mRNA by RT-PCR. In the acute phase of hepatic reperfusion, the ratio of NO/ET-1 was reduced, which was due to the significant reduction of NO - 2/NO - 3 (the metabolic product of NO) and significant elevation of ET-1 in the blood plasma. The content of ALT, AST, LDH and TNF-α in blood plasma, and level of MDA in liver tissue were increased but ATP in liver tissue was reduced, and the hepatic damage was deteriorated. The protection of the hepatic IPC was associated with the elevated ratio of NO/ET-1 caused by the elevation of NO - 2/NO - 3, and reduction of ET-1 as well. No iNOS mRNA was detected in the liver tissues. It was concluded that hepatic I/R injury was related to the disturbance of NO/ET-1. The protection of the hepatic IPC in the acute phase might be mediated by its regulation of NO/ET-1 system. The cNOS rather than the iNOS generated the NO in this scenario.

Preconditioning Schur Complement Systems of Highly-Indefinite Linear Systems for a Parallel Hybrid Solver

A parallel hybrid linear solver based on the Schur complement method has the potential to balance the robustness of direct solvers with the efficiency of preconditioned iterative solvers.However,when solving large-scale highly-indefinite linear systems,this hybrid solver often suffers from either slow convergence or large memory requirements to solve the Schur complement systems.To overcome this challenge,we in this paper discuss techniques to preprocess the Schur complement systems in parallel. Numerical results of solving large-scale highly-indefinite linear systems from various applications demonstrate that these techniques improve the reliability and performance of the hybrid solver and enable efficient solutions of these linear systems on hundreds of processors,which was previously infeasible using existing state-of-the-art solvers.

On the Preconditioning Properties of RHSS Preconditioner for Saddle-Point Linear Systems

In this paper,for the regularized Hermitian and skew-Hermitian splitting(RHSS)preconditioner introduced by Bai and Benzi(BIT Numer Math 57:287–311,2017)for the solution of saddle-point linear systems,we analyze the spectral properties of the preconditioned matrix when the regularization matrix is a special Hermitian positive semidefinite matrix which depends on certain parameters.We accurately describe the numbers of eigenvalues clustered at(0,0)and(2,0),if the iteration parameter is close to 0.An estimate about the condition number of the corresponding eigenvector matrix,which partly determines the convergence rate of the RHSS-preconditioned Krylov subspace method,is also studied in this work.

Using Spatial Data Mining to Predict the Solvability Space of Preconditioned Sparse Linear Systems

The solution of large sparse linear systems is one of the most important problems in large scale scientific computing. Among the many methods developed, the preconditioned Krylov subspace methods [1] are considered the preferred methods. Selecting an effective preconditioner with appropriate parameters for a specific sparse linear system presents a challenging task for many application scientists and engineers who have little knowledge of preconditioned iterative methods. The purpose of this paper is to predict the parameter solvability space of the preconditioners with two or more parameters. The parameter solvability space is usually irregular, however, in many situations it shows spatial locality, i.e. the parameter locations that are closer in parameter space are more likely to have similar solvability. We propose three spatial data mining methods to predict the solvability of ILUT which make usage of spatial locality in different ways. The three methods are MSC （multi-points SVM classifier）, OSC （overall SVM classifier）, and OSAC （overall spatial autoregressive classifier）. The experimental results show that both MSC and OSAC can obtain 90% accuracy in prediction, but OSAC is much simpler to implement. We focus our work on ILUT preconditioner [2], but the proposed strategies should be applicable to other preconditioners with two or more parameters.

A New Preconditioner with Two Variable Relaxation Parameters for Saddle Point Linear Systems with Highly Singular(1,1) Blocks

In this paper, we provide new preconditioner for saddle point linear systems with (1,1) blocks that have a high nullity. The preconditioner is block triangular diagonal with two variable relaxation paremeters and it is extension of results in [1] and [2]. Theoretical analysis shows that all eigenvalues of preconditioned matrix is strongly clustered. Finally, numerical tests confirm our analysis.

The AOR Iterative Method for Preconditioned Linear Systems

The preconditioned methods for solving linear system are discussed. The convergence rate of accelerated overrelaxation (AOR) method can be enlarged by using the preconditioned method when the classical AOR method converges, and the preconditioned method is invalid when the classical iterative method does not converge. The results in corresponding references are improved and perfected.