Identification and validation of a platelet-related signature for predicting survival and drug sensitivity in multiple myeloma

Background: Significant progress has been achieved in the management of multiple myeloma (MM) by implementing high-dose therapy and stem cell transplantation. Moreover, the prognosis of patients has been enhanced due to the introduction of novel immunomodulatory drugs and the emergence of new targeted therapies. However, predicting the survival rates of patients with multiple myeloma is still tricky. According to recent researches, platelets have a significant impact in affecting the biological activity of tumors and are essential parts of the tumor microenvironment. Nonetheless, it is still unclear how platelet-related genes (PRGs) connect to the prognosis of multiple myeloma.Methods: We analyzed the expression of platelet-related genes and their prognostic value in multiple myeloma patients in this study. We also created a nomogram combining clinical metrics. Furthermore, we investigated disparities in the biological characteristics, immunological microenvironment, and reaction to immunotherapy, along with analyzing the drug susceptibility within diverse risk groups.Results: By using the platelet-related risk model, we were able to predict patients’ prognosis more accurately. Subjects in the high-risk cohort exhibited inferior survival outcomes, both in the training and validation datasets, as compared to those in the low-risk cohort (p < 0.05). Moreover, there were differences in the immunological microenvironments, biological processes, clinical features, and chemotherapeutic drug sensitivity between the groups at high and low risk. Using multivariable Cox regression analyses, platelet-related risk score was shown to be an independent prognostic influence in MM (p < 0.001, hazard ratio (HR) = 2.001%, 95% confidence interval (CI): 1.467–2.730). Furthermore, the capacity to predict survival was further improved when a combined nomogram was utilized. In training cohort, this outperformed the predictive value of International staging system (ISS) alone from a 5-years area under curve (AUC) = 0.668 (95% CI: 0.611–0.725) to an AUC = 0.721 (95% CI: 0.665–0.778).Conclusion: Our study revealed the potential benefits of PRGs in terms of survival prognosis of MM patients. Furthermore, we verified its potential as a drug target for MM patients. These findings open up novel possibilities for prognostic evaluation and treatment choices for MM

Identification and validation of a novel cuproptosis-related gene signature in multiple myeloma

Background: Cuproptosis is a newly identified unique copper-triggered modality of mitochondrial cell death, distinct from known death mechanisms such as necroptosis, pyroptosis, and ferroptosis. Multiple myeloma (MM) is a hematologic neoplasm characterized by the malignant proliferation of plasma cells. In the development of MM, almost all patients undergo a relatively benign course from monoclonal gammopathy of undetermined significance (MGUS) to smoldering myeloma (SMM), which further progresses to active myeloma. However, the prognostic value of cuproptosis in MM remains unknown.Method: In this study, we systematically investigated the genetic variants, expression patterns, and prognostic value of cuproptosis-related genes (CRGs) in MM. CRG scores derived from the prognostic model were used to perform the risk stratification of MM patients. We then explored their differences in clinical characteristics and immune patterns and assessed their value in prognosis prediction and treatment response. Nomograms were also developed to improve predictive accuracy and clinical applicability. Finally, we collected MM cell lines and patient samples to validate marker gene expression by quantitative real-time PCR (qRT-PCR).Results: The evolution from MGUS and SMM to MM was also accompanied by differences in the CRG expression profile. Then, a well-performing cuproptosis-related risk model was developed to predict prognosis in MM and was validated in two external cohorts. The high-risk group exhibited higher clinical risk indicators. Cox regression analyses showed that the model was an independent prognostic predictor in MM. Patients in the high-risk group had significantly lower survival rates than those in the low-risk group (p < 0.001). Meanwhile, CRG scores were significantly correlated with immune infiltration, stemness index and immunotherapy sensitivity. We further revealed the close association between CRG scores and mitochondrial metabolism. Subsequently, the prediction nomogram showed good predictive power and calibration. Finally, the prognostic CRGs were further validated by qRT-PCR in vitro.Conclusion: CRGs were closely related to the immune pattern and self-renewal biology of cancer cells in MM. This prognostic model provided a new perspective for the risk stratification and treatment response prediction of MM patients

Prognostic significance of β2-microglobulin decline index in multiple myeloma

PurposeTo assess the prognostic significance of β2-microglobulin decline index (β2M DI) in multiple myeloma (MM).Methods150 MM patients diagnosed with MM were enrolled in this study. Cox proportional hazards model was used to analyze the uni- and multivariate prognosis in training cohort (n=105). A new combined prognostic model containing β2M DI was built up based on the data in training cohort. The validation group was used to verify the model.Resultsβ2M DI showed significant correlation with prognosis in both uni- and multivariate analyses and had a good correlation with complete response (CR) rate and deep remission rate. The ROC and calibration curves in validation cohort (n=45) indicated a good predictive performance of the new model. Based on the median risk score of the training group, we classified patients into high- and low- risk groups. In both training and validation groups, patients in the low-risk group had longer overall survival (OS) time than that in the high-risk group (p<0.05).Conclusionβ2M DI is a good predictive index for predicting treatment response and survival time in MM patients. The prognostic model added with β2M DI showed a better correlation with OS

A novel glycolysis-related gene signature for predicting the prognosis of multiple myeloma

Background: Metabolic reprogramming is an important hallmark of cancer. Glycolysis provides the conditions on which multiple myeloma (MM) thrives. Due to MM’s great heterogeneity and incurability, risk assessment and treatment choices are still difficult.Method: We constructed a glycolysis-related prognostic model by Least absolute shrinkage and selection operator (LASSO) Cox regression analysis. It was validated in two independent external cohorts, cell lines, and our clinical specimens. The model was also explored for its biological properties, immune microenvironment, and therapeutic response including immunotherapy. Finally, multiple metrics were combined to construct a nomogram to assist in personalized prediction of survival outcomes.Results: A wide range of variants and heterogeneous expression profiles of glycolysis-related genes were observed in MM. The prognostic model behaved well in differentiating between populations with various prognoses and proved to be an independent prognostic factor. This prognostic signature closely coordinated with multiple malignant features such as high-risk clinical features, immune dysfunction, stem cell-like features, cancer-related pathways, which was associated with the survival outcomes of MM. In terms of treatment, the high-risk group showed resistance to conventional drugs such as bortezomib, doxorubicin and immunotherapy. The joint scores generated by the nomogram showed higher clinical benefit than other clinical indicators. The in vitro experiments with cell lines and clinical subjects further provided convincing evidence for our study.Conclusion: We developed and validated the utility of the MM glycolysis-related prognostic model, which provides a new direction for prognosis assessment, treatment options for MM patients

Graph Component Contrastive Learning for Concept Relatedness Estimation

Concept relatedness estimation (CRE) aims to determine whether two given concepts are related. Existing methods only consider the pairwise relationship between concepts, while overlooking the higher-order relationship that could be encoded in a concept-level graph structure. We discover that this underlying graph satisfies a set of intrinsic properties of CRE, including reflexivity, commutativity, and transitivity. In this paper, we formalize the CRE properties and introduce a graph structure named ConcreteGraph. To address the data scarcity issue in CRE, we introduce a novel data augmentation approach to sample new concept pairs from the graph. As it is intractable for data augmentation to fully capture the structural information of the ConcreteGraph due to a large amount of potential concept pairs, we further introduce a novel Graph Component Contrastive Learning framework to implicitly learn the complete structure of the ConcreteGraph. Empirical results on three datasets show significant improvement over the state-of-the-art model. Detailed ablation studies demonstrate that our proposed approach can effectively capture the high-order relationship among concepts

Integrating Boronic Esters and Anthracene into Covalent Adaptable Networks toward Stimuli-Responsive Elastomers

Stimuli-responsive polymer materials have a promising potential application in many areas. However, integrating multi-stimuli into one elastomer is still a challenge. Here, we utilized boronic esters and anthracene to prepare a cross-linked poly(styrene-butadiene-styrene) (SBS) which was endowed with responsiveness to three stimuli (light, heat, and alcohols). SBS was first functionalized with a certain amount of dihydroxyl groups via a thiol-ene “click” reaction between unsaturated double bonds in PB block and thioglycerol. Then, 9-anthraceneboronic acid was applied to form a cross-linked SBS network upon heat and ultraviolet radiation (λ = 365 nm). The prepared elastomer was demonstrated to be stimuli-responsive based on the dynamic nature of boronic esters and the reversible dimerization of anthracene. In addition, the mechanical properties of the elastomer could be regulated continuously owing to the stimulus responsiveness to ultraviolet or heat

Investigation on C_f/PyC Interfacial Properties of C/C Composites by the Molecular Dynamics Simulation Method

In this paper, a molecular dynamics (MD) simulation model of carbon-fiber/pyrolytic-carbon (Cf/PyC) interphase in carbon/carbon (C/C) composites manufactured by the chemical vapor phase infiltration (CVI) process was established based on microscopic observation results. By using the MD simulation method, the mechanical properties of the Cf/PyC interphase under tangential shear and a normal tensile load were studied, respectively. Meanwhile, the deformation and failure mechanisms of the interphase were investigated with different sizes of the average length L ¯ a of fiber surface sheets. The empirical formula of the interfacial modulus and strength with the change of L ¯ a was obtained as well. The shear properties of the isotropic pyrolysis carbon (IPyC) matrix were also presented by MD simulation. Finally, the mechanical properties obtained by the MD simulation were substituted into the cohesive force model, and a fiber ejection test of the C/C composite was simulated by the finite element analysis (FEA) method. The simulation results were in good agreement with the experimental ones. The MD simulation results show that the shear performance of the Cf/PyC interphase is relatively higher when L ¯ a is small due to the effects of non-in-plane shear, the barrier between crystals, and long sheet folding. On the other hand, the size of L ¯ a has no obvious influence on the interfacial normal tensile mechanical properties

Optimal Selection for Redox Couples and Enhanced Performance through Magnetic Nanofluid Electrolyte in Solar Flow Batteries

The limited photoelectric conversion efficiency poses one of the critical constraints on commercializing solar flow batteries (SFBs). This study compares the chemical and photoelectrochemical properties of three commonly used redox couples. Additionally, magnetic Fe3O4 nanoparticles, for the first time, are introduced to optimize the electrolyte, and they are compared with the original electrolyte. Across different redox couples, the variations in semiconductor flat-band potentials and carrier concentrations result in changes in photoelectric current density. Notably, FeCl2/FeCl3 redox coupled with TiO2 photoelectrodes exhibits the highest photoelectric current density, reaching 75.7 µA cm−2. However, the trade-off of this electrolyte, i.e., providing high photocurrent while being unable to supply sufficient open-circuit voltage, imposes limitations on the practical application of SFBs. Alternatively, for TEMPO and 4-OH-TEMPO electrolytes, which can provide a higher open-circuit voltage, the electrochemical activity is enhanced, and the solution ohmic resistance is reduced by introducing magnetic nanoparticles to form a magnetic nanofluid. As a result, the photoanode’s photocurrent density increases by 36.6% and 17.0%, respectively, in the two electrolytes. The work reported here effectively addresses the current issue of low photocurrent density in SFBs and presents new optimization strategies for SFBs

Cu₂O-Electrodeposited TiO₂ Photoelectrode for Integrated Solar Redox Flow Battery

TiO2 photoelectrode has become an attractive platform due to its excellent photoelectric performance and has been widely used in battery, photocatalysis, and other photoelectric fields. However, when the TiO2 photoelectrode is used in solar flow batteries, the small photo-charging current is a potential problem, which will extend the charging process and lower the battery utilization efficiency. To address this issue, Cu2O is introduced to the surface of the TiO2 photoelectrode, and Cu2O-TiO2 forms a heterojunction to improve battery performance in this work. The formation mechanism of Cu2O-TiO2 is revealed and utilized to deposit Cu2O on pre-treated FTO glass covered with TiO2 films using electrochemical deposition (ECD). The photoelectrochemical properties of Cu2O-TiO2 photoelectrodes are characterized using XRD, UV-vis diffuse reflectance spectroscopy, XPS, and electrochemical characterizations. The successful deposition of Cu2O on the surface of TiO2 photoelectrode is confirmed, and the UV-vis spectroscopic test results show that the incorporation of Cu2O enhances and broadens the absorption and utilization of sunlight in the UV range by the TiO2 photoelectrode. Furthermore, the electrochemical test results manifest that the Cu2O-TiO2 photoelectrode possesses a higher carrier concentration under illumination conditions due to the formation of a heterojunction. Finally, a 30 min unbiased photocharging test demonstrates that the Cu2O-TiO2 photoelectrode charges in a current density of 425.03 μA·cm−2, indicating an increased photogenerated carrier concentration and a decreased photogenerated carrier recombination rate, which results from the enlarged doping concentration and improved charge transfer process at the electrolyte/semiconductor interface due to the incorporation of Cu2O. Compared with the current density of 116.21 μA·cm−2 for the bare TiO2 photoelectrode, the performance can be improved by over 365%

Plasma-Derived Fibronectin Stimulates Chondrogenic Differentiation of Human Subchondral Cortico-Spongious Progenitor Cells in Late-Stage Osteoarthritis

Migration and chondrogenesis of human subchondral cortico-spongious progenitor cells (SPCs) are the key steps in the repair of microfracture-induced articular cartilage defects. The aim of this study was to evaluate the effect of human plasma-derived fibronectin (Fn) on the chondrogenic differentiation of SPCs, which was isolated from subchondrol cortico-spongious bone of late-stage osteoarthritis (OA) patients. SPCs were isolated and cultured for three passages. Stem cell surface antigens of SPCs were analyzed by flow cytometry. The osteogenic, chondrogenic and adipogenic differentiation potential were detected by histological staining. The chondrogenesis potential of SPCs with or without stimulation of either Fn or BMP-2 were studied by immunochemical staining and gene expression analysis. Cells isolated from subchondral bone presented to be positive for CD44, CD73, CD90, and CD166, and showed high capacity of osteogenic, adipogenic and chondrogenic differentiation, which suggested this cell population to be MSC-like cells. Stimulating with Fn increased the expression of SOX-9, aggrecan, collagen II while decreased the formation of collagen I by immunochemical staining. Gene expression analysis showed similar results. These results suggest that plasma-derived Fn can increase the chondrogenic differentiation of SPCs isolated from late-stage OA and improve cartilage repair after microfracture