Identification of cell surface markers for acute myeloid leukemia prognosis based on multi-model analysis

Given the extremely high inter-patient heterogeneity of acute myeloid leukemia(AML),the identification of biomarkers for prognostic assessment and therapeutic guidance is critical.Cell surface markers(CSMs)have been shown to play an important role in AML leukemogenesis and progression.In the current study,we evaluated the prognostic potential of all human CSMs in 130 AML patients from The Cancer Genome Atlas(TCGA)based on differential gene expression analysis and univariable Cox proportional hazards regression analysis.By using multi-model analysis,including Adaptive LASSO regression,LASSO regression,and Elastic Net,we constructed a 9-CSMs prognostic model for risk stratification of the AML patients.The predictive value of the 9-CSMs risk score was further validated at the transcriptome and proteome levels.Multivariable Cox regression analysis showed that the risk score was an independent prognostic factor for the AML patients.The AML patients with high 9-CSMs risk scores had a shorter overall and event-free survival time than those with low scores.Notably,single-cell RNA-sequencing analysis indicated that patients with high 9-CSMs risk scores exhibited chemotherapy resistance.Furthermore,PI3K inhibitors were identified as potential treatments for these high-risk patients.In conclusion,we constructed a 9-CSMs prognostic model that served as an independent prognostic factor for the survival of AML patients and held the potential for guiding drug therapy.

Structure-preserving algorithms for guiding center dynamics based on the slow manifold of classical Pauli particle

The classical Pauli particle(CPP) serves as a slow manifold, substituting the conventional guiding center dynamics. Based on the CPP, we utilize the averaged vector field(AVF) method in the computations of drift orbits. Demonstrating significantly higher efficiency, this advanced method is capable of accomplishing the simulation in less than one-third of the time of directly computing the guiding center motion. In contrast to the CPP-based Boris algorithm, this approach inherits the advantages of the AVF method, yielding stable trajectories even achieved with a tenfold time step and reducing the energy error by two orders of magnitude. By comparing these two CPP algorithms with the traditional RK4 method, the numerical results indicate a remarkable performance in terms of both the computational efficiency and error elimination. Moreover, we verify the properties of slow manifold integrators and successfully observe the bounce on both sides of the limiting slow manifold with deliberately chosen perturbed initial conditions. To evaluate the practical value of the methods, we conduct simulations in non-axisymmetric perturbation magnetic fields as part of the experiments,demonstrating that our CPP-based AVF method can handle simulations under complex magnetic field configurations with high accuracy, which the CPP-based Boris algorithm lacks. Through numerical experiments, we demonstrate that the CPP can replace guiding center dynamics in using energy-preserving algorithms for computations, providing a new, efficient, as well as stable approach for applying structure-preserving algorithms in plasma simulations.

Significance of mitochondrial activity in neurogenesis and neurodegenerative diseases

Mitochondria play a multidimensional role in the function and the vitality of the neurological system.From the generation of neural stem cells to the maintenance of neurons and their ultimate demise,mitochondria play a critical role in regulating our neural pathways'homeostasis,a task that is critical to our cognitive health and neurological well-being.Mitochondria provide energy via oxidative phosphorylation for the neurotransmission and generation of an action potential along the neuron's axon.This paper will first review and examine the molecular subtleties of the mitochondria's role in neurogenesis and neuron vitality,as well as outlining the impact of defective mitochondria in neural aging.The authors will then summarize neurodegenerative diseases related to either neurogenesis or homeostatic dysfunction.Because of the significant detriment neurodegenerative diseases have on the quality of life,it is essential to understand their etiology and ongoing molecular mechanics.The mitochondrial role in neurogenesis and neuron vitality is essential.Dissecting and understanding this organelle's role in the genesis and homeostasis of neurons should assist in finding pharmaceutical targets for neurodegenerative diseases.

Long-Range Electronic Effect-Promoted Ring-Opening Polymerization of Thioctic Acid to Produce Biomimetic Ionic Elastomers for Bioelectronics

Poly(disulfide)s have been widely used in flexible wearable electronics,smart materials,and drug delivery.The synthesis of poly(disulfide)s usually utilizes external stimuli or toxic initiators to promote the polymerization.Here,we indicated that the long-range electronic effect can significantly alter the reactivity of the disulfide group.Accordingly,we established deprotonation-promoted ring-opening polymerization of thioctic acid(TA)as a highly effective and simple method to synthesize poly(disulfide)s due to the long-range electronic effect and nucleophilic carboxylate.Without external stimuli and initiators,simple mixing of TA and deprotonation reagent,choline bicarbonate,in different ratios at room temperature rapidly produced a series of high molecular weight(up to 772 kDa)ionic liquid crystal poly(disulfide)s elastomers with room temperature self-healing ability,adjustable conductivity(2.39×10^(−2)∼0.28×10^(−2)S m^(−1)),degradability,biocompatibility,antibacterial property,and tissue-like softness(Young’s moduli ranging from 18.2±6.0 to 111.1±36.7 kPa).The experiments and density functional theory calculations also revealed the principle of long-range electronic effect to establish a new synthetic strategy of poly(disulfide)s with superior properties favorable for bioelectronics.

Highly efficient degradation of emerging contaminants by magnetic CuO@Fe_(x)O_(y) derived from natural mackinawite(FeS) in the presence of peroxymonosulfate

In this study,natural mackinawite (Fe S),a chalcophilic mineral,was utilized to prepare iron/copper bimetallic oxides (Cu^(O)@Fe_(x)O_(y)) by displacement plating and calcination process.Various characterization methods prove that Cu;is successfully coated on the surface of Fe S,which were further oxidized to Cu^(O),Fe_(3)O_(4)and/or Fe_(2)O_(3)during calcination process,respectively.Cu^(O)@Fe_(x)O_(y)performed highly efficient capacity to activate PMS for the degradation of various emerging pollutants including sulfamethoxazole(SMX),carbamazepine (CBZ),bisphenol A (BPA),2,4-dichlorophenol (2,4-DCP) and diclofenac (DCF) in aqueous solution.Complete removal of the above pollutants was observed after 8 min of Cu^(O)@Fe_(x)O_(y)/PMS treatment.Taking SMX as an example,the key parameters including Cu^(O)@Fe_(x)O_(y)dosage,PMS dosage and initial p H were optimized.The results show that the catalytic system can be worked in a wide p H range (3.0-9.0).The quenching experiments and electron spin resonance (ESR) test demonstrated that the main reactive oxygen species in Cu^(O)@Fe_(x)O_(y)/PMS system were hydroxyl radicals (^(·)OH) and sulfate radicals(SO_(4)^(·ˉ)),and SO_(4)^(·ˉ)was the primary reactive species.Besides,the influence of coexisting anions (i.e.,Cl^(ˉ),NO_(3)^(ˉ),HCO_(3)^(ˉ)and H_(2)PO_(4)^(ˉ)) for the degradation of SMX was explored.Cu^(O)@Fe_(x)O_(y)/PMS system can maintain good catalytic activity and reusability in different water bodies and long-term running.This work provided a green strategy to fabricate the efficient catalyst in PMS-based advanced oxidation processes.