Prognostic significance of ß2-microglobulin decline index in multiple myeloma.

Purpose: To assess the prognostic significance of ß2-microglobulin decline index (ß2M DI) in multiple myeloma (MM). Methods: 150 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 ß2M DI was built up based on the data in training cohort. The validation group was used to verify the model. Results: ß2M 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). Conclusion: ß2M DI is a good predictive index for predicting treatment response and survival time in MM patients. The prognostic model added with ß2M DI showed a better correlation with OS.

Comprehensive analysis of ferroptosis-related genes in immune infiltration and prognosis in multiple myeloma.

Background: One particular type of cellular death that is known as ferroptosis is caused by the excessive lipid peroxidation. It is a regulated form of cell death that can affect the response of the tumor cells. Currently, it is not known if the presence of this condition can affect the prognosis of patients with multiple myeloma (MM). Methods: In this study, we studied the expression differences and prognostic value of ferroptosis-related genes (FRGs) in MM, and established a ferroptosis risk scoring model. In order to improve the prediction accuracy and clinical applicability, a nomogram was also established. Through gene enrichment analysis, pathways closely related to high-risk groups were identified. We then explored the differences in risk stratification in drug sensitivity and immune patterns, and evaluated their value in prognostic prediction and treatment response. Lastly, we gathered MM cell lines and samples from patients to confirm the expression of marker FRGs using quantitative real-time PCR (qRT-PCR). Results: The ability to predict the survival of MM patients is a challenging issue. Through the use of a risk model derived from ferroptosis, we were able to develop a more accurate prediction of the disease's prognosis. They were then validated by a statistical analysis, which showed that the model is an independent factor in the prognosis of MM. Patients of high ferroptosis risk scores had a much worse chance of survival than those in the low-risk groups. The calibration and power of the nomogram were also strong. We noted that the link between the ferroptosis risk score and the clinical treatment was suggested by the FRG's significant correlation with the immune checkpoint genes and the medication sensitivity. We validated the predictive model using qRT-PCR. Conclusion: We demonstrated the association between FRGs and MM, and developed a new risk model for prognosis in MM patients. Our study sheds light on the potential clinical relevance of ferroptosis in MM and highlights its potential as a therapeutic target for patients with this disease.

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.

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.

Visualized concentration sensors based on fluorescence indication in a dye-doped polymer microwire.

We demonstrate visualized microwire sensors based on fluorescence indication for detecting the concentrations of the aqueous solutions. The single Rhodamine (RhB) doped polymer microwires (PMWs) which are excited by the waveguiding excitation method are used as the sensory area. According to the fluorescent microimages of the PMWs, stable periodic oscillations could be observed in the RhB-doped PMWs. The fluorescent period which is dependent on the concentration is further analyzed by image processing and information extraction algorithms. Corresponding to a 1.0% change, the period length change of the visualized sensor reaches ∼380 nm, ∼270 nm, and ∼300 nm in NaCl, KCl, and sucrose solutions, respectively. The dection limits of the three solutions are estimated to be around 1.5 × 10-4%. The dye-doped PMW sensors by fluorescence indication and image analysis proposed here realize the direct visualized detection in concentration sensing, making it possible to avoid the challenges of stability and weak signal detection and offer a potentially stable and cost-effective approach for micro/nanofiber sensor application.

Development and validation of a cuproptosis-associated prognostic model for diffuse large B-cell lymphoma.

Diffuse large B-cell lymphoma (DLBCL) is a highly heterogeneous disease. Therefore, more reliable biomarkers are required to better predict the prognosis of DLBCL. Cuproptosis is a novel identified form of programmed cell death (PCD) that is different from oxidative stress-related cell death (e.g., apoptosis, ferroptosis, and necroptosis) by Tsvetkov and colleagues in a recent study released in Science. Cuproptosis is copper-dependent PCD that is closely tied to mitochondrial metabolism. However, the prognostic value of cuproptosis-related genes (CRGs) in DLBCL remains to be further elucidated. In the present study, we systematically evaluated the molecular changes of CRGs in DLBCL and found them to be associated with prognosis. Subsequently, based on the expression profiles of CRGs, we characterized the heterogeneity of DLBCL by identifying two distinct subtypes using consensus clustering. Two isoforms exhibited different survival, biological functions, chemotherapeutic drug sensitivity, and immune microenvironment. After identifying differentially expressed genes (DEGs) between CRG clusters, we built a prognostic model with the Least absolute shrinkage and selection operator (LASSO) Cox regression analysis and validated its prognostic value by Cox regression analysis, Kaplan-Meier curves, and receiver operating characteristic (ROC) curves. In addition, the risk score can predict clinical characteristics, levels of immune cell infiltration, and prognosis. Furthermore, a nomogram incorporating clinical features and risk score was generated to optimize risk stratification and quantify risk assessment. Compared to the International Prognostic Index (IPI), the nomogram has demonstrated more accuracy in survival prediction. Furthermore, we validated the prognostic gene expression levels through external experiments. In conclusion, cuproptosis-related gene signature can serve as a potential prognostic predictor in DLBCL patients and may provide new insights into cancer therapeutic targets.

Study on the difference in exciton generation processes for a single host and exciplex-type co-host.

We distinctly reveal the difference in the exciton generation processes in phosphorescent organic light-emitting devices with an exciplex-type co-host and a single host. Excitons in the co-host consisting of 4,4,4-tris(N-carbazolyl)-triphenylamine and 1,3,5-tris(N-phenylbenzimidazol-2-yl)benzene are created via efficient energy transfer from the exciplex to the phosphorescent dopant. In contrast, excitons in the single host of 4,4,4-tris(N-carbazolyl)-triphenylamine are formed by the combination of holes and electrons trapped by the phosphorescent dopants. The optimized device utilizing the co-host system exhibits highly superior performance relative to the single-host device. The maximum external quantum efficiency and maximum luminance are 14.88% and 90,700cd/m2 for the co-host device, being 1.6 times and 3.6 times the maximum external efficiency and maximum luminance for the single-host device, respectively. Significantly, the critical current density, evaluating the device efficiency roll-off characteristic, is as high as 327.8mA/cm2, which is highly superior to 120.8mA/cm2 for the single-host device, indicating the notable alleviation in efficiency roll-off for the co-host device. The significant improvement in device performance is attributed to eliminating the exciton quenching resulting from the captured holes and the efficient energy transfer from the exciplex-type co-host to the phosphorescent emitter incurred by the reverse intersystem crossing process.

Group Velocity Modulation and Light Field Focusing of the Edge States in Chirped Valley Graphene Plasmonic Metamaterials.

The valley degree of freedom, like the spin degree of freedom in spintronics, is regarded as a new information carrier, promoting the emerging valley photonics. Although there exist topologically protected valley edge states which are immune to optical backscattering caused by defects and sharp edges at the inverse valley Hall phase interfaces composed of ordinary optical dielectric materials, the dispersion and the frequency range of the edge states cannot be tuned once the geometrical parameters of the materials are determined. In this paper, we propose a chirped valley graphene plasmonic metamaterial waveguide composed of the valley graphene plasmonic metamaterials (VGPMs) with regularly varying chemical potentials while keeping the geometrical parameters constant. Due to the excellent tunability of graphene, the proposed waveguide supports group velocity modulation and zero group velocity of the edge states, where the light field of different frequencies focuses at different specific locations. The proposed structures may find significant applications in the fields of slow light, micro-nano-optics, topological plasmonics, and on-chip light manipulation.

Backpropagation neural network assisted concentration prediction of biconical microfiber sensors.

The response of the optical microfiber sensor has a big difference due to the slight change in fiber structure, which greatly reduces the reliability of microfiber sensors and limits its practical applications. To avoid the nonlinear influences of microfiber deformation and individual differences on sensing performance, a backpropagation neural network (BPNN) is proposed for concentration prediction based on biconical microfiber (BMF) sensors. Microfiber diameter, cone angle, and relative intensity are the key input parameters for detecting the concentration of chlorophyll-a (from ∼0.03 mg/g to ∼0.10 mg/g). Hundreds of relative intensity-concentration data pairs acquired from 32 BMF sensors are used for the network training. The prediction ability of the model is evaluated by the root-mean-square error (RMSE) and the fitness value (F). The prediction performance of BPNN is compared with the traditional linear-fitting line method. After training, BPNN could adapt to the BMF sensors with different structural parameters and predict the nonlinear response caused by the small structural changes of microfiber. The concentration prediction given by BPNN is much closer to the actual measured value than the one obtained by the linear fitting curve (RMSE 1.84×10-3 mg/g vs. 4.6×10-3 mg/g). The numbers of training data and hidden layers of the BPNN are discussed respectively. The prediction results indicate that the one-hidden-layer network trained by more training data provides the best performance (RMSE and fitness values are 1.63×10-3 mg/g and 97.91%, respectively) in our experiments. With the help of BPNN, the performance of the BMF sensor is acceptable to the geometric deformation and fabrication error of microfiber, which provides an opportunity for the practical application of sensors based on micro/nanofibers.

Chiral graphene plasmonic Archimedes' spiral nanostructure with tunable circular dichroism and enhanced sensing performance.

Circular dichroism spectroscopy is frequently used to characterize the chiral biomolecules by measuring the absorption spectra contrast between the left-handed circularly polarized light and the right-handed circularly polarized light. Compared with biomolecules, chiral metal plasmonic nanostructures also produce a strong circular dichroism response in the range of near-infrared. However, due to the large damping rate, the non-adjustable resonant frequency of the conventional metals, the applications of chiral metal plasmonic nanostructures in the fields of photoelectric detection and chemical and biochemical sensing are restricted. Here, we present a chiral graphene plasmonic Archimedes' spiral nanostructure that displays a significant circular dichroism response under the excitation of two polarizations of circularly polarized light. By manipulating the material and geometric parameters of the Archimedes' spiral, the stronger circular dichroism responses and modulation of the resonant wavelength are achieved. The optimized plasmonic nanostructure has outstanding refractive index sensing performance, where the sensitivity and figure of merit reach 7000nm/RIU and 68.75, respectively. Our proposed chiral graphene plasmonic Archimedes' spiral nanostructure might find potential applications in the fields of optical detection and high performance of index sensing.

Multiple Fano Resonances with Tunable Electromagnetic Properties in Graphene Plasmonic Metamolecules.

Multiple Fano resonances (FRs) can be produced by destroying the symmetry of structure or adding additional nanoparticles without changing the spatial symmetry, which has been proved in noble metal structures. However, due to the disadvantages of low modulation depth, large damping rate, and broadband spectral responses, many resonance applications are limited. In this research paper, we propose a graphene plasmonic metamolecule (PMM) by adding an additional 12 nanodiscs around a graphene heptamer, where two Fano resonance modes with different wavelengths are observed in the extinction spectrum. The competition between the two FRs as well as the modulation depth of each FR is investigated by varying the materials and the geometrical parameters of the nanostructure. A simple trimer model, which emulates the radical distribution of the PMM, is employed to understand the electromagnetic field behaviors during the variation of the parameters. Our proposed graphene nanostructures might find significant applications in the fields of single molecule detection, chemical or biochemical sensing, and nanoantenna.

Dual-cavity digital laser for intra-cavity mode shaping and polarization control.

In this paper, we present a digital laser for on-demand modes with polarization control based on a single intra-cavity spatial light modulator (SLM). We employ a phase-only SLM as the back reflector in a dual-cavity resonator. We prove that we can digitally control and switch lasing modes with desired linear polarization at video rates. Moreover, we experimentally generate vector beams based on the selection and coherent summation of two orthogonally polarized Hermite-Gaussian (HG) beams inside the resonator.

Experimental investigation on a nonuniformly correlated partially coherent laser.

We demonstrate, to the best of our knowledge, a new kind of laser, called a partially coherent digital laser, producing nonuniformly correlated partially coherent light beams by "playing a video" inside the cavity directly. In this laser, a spatial light modulator (SLM) with dynamic phase modulation acts as a cavity mirror. The coherence degree distribution of the output beams can be controlled simply by varying the waists of the computer-generated holograms on the SLM. The experimental results show that the coherence degree between two points on the observation plane is not only dependent on the distance between them, but also on the positions that are observed across the beam.

Dynamic tailoring of electromagnetic behaviors of graphene plasmonic oligomers by local chemical potential.

In the mid-infrared and terahertz (THz) regime, graphene supports tunable surface plasmon resonance (SPR) by controlling the chemical potential, which promotes light-matter interaction at the selected wavelength, showing exceptional promise for optoelectronic applications. In this article, we show that the electromagnetic (EM) response of graphene oligomers can be substantially modified by the modification of the local chemical potential, strengthening or reducing the intrinsic plasmonic modes. The effect mechanism is corroborated by a graphene nanocluster composed of 13 nanodisks with D6h symmetry; by transforming to D3h symmetry, the effect mechanism was retained and more available plasmonic resonance modes appeared. The intriguing properties open a new way to design nanodevices made of graphene oligomers with highly efficient photoresponse enhancement and tunable spectral selectivity for highly accurate photodetection.

Pseudospin Dependent One-Way Transmission in Graphene-Based Topological Plasmonic Crystals.

Originating from the investigation of condensed matter states, the concept of quantum Hall effect and quantum spin Hall effect (QSHE) has recently been expanded to other field of physics and engineering, e.g., photonics and phononics, giving rise to strikingly unconventional edge modes immune to scattering. Here, we present the plasmonic analog of QSHE in graphene plasmonic crystal (GPC) in mid-infrared frequencies. The band inversion occurs when deforming the honeycomb lattice GPCs, which further leads to the topological band gaps and pseudospin features of the edge states. By overlapping the band gaps with different topologies, we numerically simulated the pseudospin-dependent one-way propagation of edge states. The designed GPC may find potential applications in the fields of topological plasmonics and trigger the exploration of the technique of the pseudospin multiplexing in high-density nanophotonic integrated circuits.

Double closed-loop control of integrated optical resonance gyroscope with mean-square exponential stability.

A new double closed-loop control system with mean-square exponential stability is firstly proposed to optimize the detection accuracy and dynamic response characteristic of the integrated optical resonance gyroscope (IORG). The influence mechanism of optical nonlinear effects on system detection sensitivity is investigated to optimize the demodulation gain, the maximum sensitivity and the linear work region of a gyro system. Especially, we analyze the effect of optical parameter fluctuation on the parameter uncertainty of system, and investigate the influence principle of laser locking-frequency noise on the closed-loop detection accuracy of angular velocity. The stochastic disturbance model of double closed-loop IORG is established that takes the unfavorable factors such as optical effect nonlinearity, disturbed disturbance, optical parameter fluctuation and unavoidable system noise into consideration. A robust control algorithm is also designed to guarantee the mean-square exponential stability of system with a prescribed H∞ performance in order to improve the detection accuracy and dynamic performance of IORG. The conducted experiment results demonstrate that the IORG has a dynamic response time less than 76us, a long-term bias stability 7.04°/h with an integration time of 10s over one-hour test, and the corresponding bias stability 1.841°/h based on Allan deviation, which validate the effectiveness and usefulness of the proposed detection scheme.

Topologically protected edge states in graphene plasmonic crystals.

A two-dimensional graphene plasmonic crystal composed of periodically arranged graphene nanodisks is proposed. We show that the band topology effect due to inversion symmetry broken in the proposed plasmonic crystals is obtained by tuning the chemical potential of graphene nanodisks. Utilizing this kind of plasmonic crystal, we constructed N-shaped channels and realized topologically edged transmission within the band gap. Furthermore, topologically protected exterior boundary propagation, which is immune to backscattering, was also achieved by modifying the chemical potential of graphene nanodisks. The proposed graphene plasmonic crystals with ultracompact size are subject only to intrinsic material loss, which may find potential applications in the fields of topological plasmonics and high density nanophotonic integrated systems.

Investigation of beam splitter in a zero-refractive-index photonic crystal at the frequency of Dirac-like point.

The Dirac-like cone dispersion of the photonic crystal induced by the three-fold accidental degeneracy at the Brillouin center is calculated in this paper. Such photonic crystals can be mapped to zero-refractive-index materials at the vicinity of the Dirac-like point frequency, and utilized to construct beam splitter of high transmission efficiency. The splitting ratio is studied as a function of the position of the input/output waveguides. Furthermore, variant beam splitters with asymmetric structures, bulk defects, and some certain bending angles are numerically simulated. Finally, we show that 1 × 2 to 1 × N beam splitting can be realized with high transmission efficiency in such a zero-refractive-index photonic crystal at the frequency of Dirac-like point. The proposed structure could be a fundamental component of the high density photonic integrated circuit technique.

Optimization of the Fano Resonance Lineshape Based on Graphene Plasmonic Hexamer in Mid-Infrared Frequencies.

In this article, the lineshape of Fano-like resonance of graphene plasmonic oligomers is investigated as a function of the parameters of the nanostructures, such as disk size, chemical potential and electron momentum relaxation time in mid-infrared frequencies. Also, the mechanism of the optimization is discussed. Furthermore, the environmental index sensing effect of the proposed structure is revealed, and a figure of merit of 25.58 is achieved with the optimized graphene oligomer. The proposed nanostructure could find applications in the fields of chemical or biochemical sensing.

Electromagnetic field coupling characteristics in graphene plasmonic oligomers: from isolated to collective modes.

In this paper, we propose a plasmonic tetramer composed of coupled graphene nanodisks. The transformation from the isolated to the collective modes of the proposed structure is investigated by analysing the whispering-gallery modes and extinction spectra with various inter-nanodisk gap distances. In addition, the effect of introducing a central nanodisk into the tetramer on the extinction spectra is explored, which leads to Fano resonance. Furthermore, the refractive index sensing properties of the proposed graphene plasmonic oligomer have been demonstrated. The proposed nanostructures might pave the road toward the application of graphene plasmonic oligomers in fields such as nanophotonics, and chemical or biochemical sensing.