Dynamic, single-cell monitoring of CAR T cell identity and activation with Raman spectroscopy

bioRxiv (Cold Spring Harbor Laboratory) · 2026-02-23

Chimeric antigen receptor (CAR) T cell therapies have reshaped treatment for cancers and immune-mediated diseases, yet their safety and efficacy depend on both the proliferation of engineered cells and their dynamic functional state - features that remain challenging to monitor in real-time clinical settings. Current methods require labels, extensive processing, and provide only static snapshots of cell identity and activation. Here, we introduce a surface-enhanced Raman spectroscopy and machine learning approach that enables label-free single-cell identification of engineered CAR T cells and time-resolved, semi-continuous monitoring of their functional activation state. Using the intrinsic vibrational signatures from live cells, we detect spectral differences resulting from engineered receptor expression in donor-derived CD19- and GD2-targeted CAR T cells (nine and five donors, respectively) with 81-85% donor-level accuracy and resolve dynamic antigen-specific activation trajectories with temporal precision. These capabilities stem from biochemical signatures consistent with processes such as receptor expression, tonic signalling, and immune synapse formation, demonstrating a single method that reports both cellular identity and activation state with biochemical specificity. Our results extend CAR T cell monitoring beyond static phenotyping and establish the potential of SERS-ML analysis for rapid, point-of-care assessment of engineered immune cells.

Identification of CD8 + T based subtypes in gastric cancer: a predictive model from bioinformatic analysis and machine-learning methods

European journal of medical research · 2026-03-30

Gastric cancer (GC) is a leading cause of cancer death. While CD8 + T cell infiltration correlates with better prognosis, few CD8 + T based subtypes and predictive models exist for GC. Using scRNA-seq (GSE163558) and bulk RNA-seq (TCGA-STAD) data, hub CD8 + T genes were identified. Samples were clustered into two subtypes via NMF based on prognostic hub genes. Clinical features, molecular traits, immune infiltration, and treatment response were compared to define the two subtypes. Subsequently, Multiple machine learning methods were employed to select prognostic differentially expressed genes to build a gene signature. A nomogram integrated the signature and clinical characteristics was established. Finally, flow cytometry was conducted to evaluate the influence of BMP inhibitor on GC tumor microenvironment and tumor infiltrating lymphocytes. 153 CD8 + T genes were identified, while six genes (RNF19B, IRF1, TAP1, STK17A, CXCR4, SELL) had prognostic value in GC. Patients were stratified into two subtypes with distinct survival. C1 showed higher immune activity and better immunotherapy response than C2. Besides, C1 had elevated calcium/chemokine signaling and reduced BMP pathway. A CD8 + T-related gene signature was developed to predict the hot-like tumor. The final nomogram accurately stratified the risk in GC. Flow cytometry showed the BMP inhibitor could switch cold-like GC tumor to hot-like phenotype. This study identified prognostic CD8 + T hub genes, defined CD8 + T based subtypes in GC which had differing features/therapy responses, and established a CD8 + T gene signature and nomogram for risk stratification, offering new insights for GC management.

Spin-polarized scanning tunneling microscopy measurement scheme for determining the quantum geometric tensor

Physical review. B./Physical review. B · 2026-01-13 · 1 citations

The quantum geometric tensor (QGT) embodies the geometry of the eigenstates of a system's Hamiltonian, and its full characterization across diverse quantum systems is essential. However, it is challenging to characterize the QGT of solid-state systems. Here we present an electric scheme to measure the complete QGT of two-dimensional solid-state systems by using spin-polarized scanning tunneling microscopy (STM), in which the spin texture is extracted from geometric amplitudes of Friedel oscillations induced by the intentionally introduced magnetic impurity, and then the QGT is derived from the momentum differential of spin texture. As a canonical spin model, the surface states of a topological insulator offer a promising way to demonstrate the scheme. In a slab of topological insulator, the gapped surface states host complete QGT, i.e., nonvanishing quantum metric and Berry curvature as its symmetric real part and the antisymmetric imaginary part. Thus, a detailed derivation guides the use of the developed scheme to measure the QGT of gapped surface states, even with an external magnetic field. This study opens a new avenue to directly measure the complete QGT of two-dimensional solid-state systems by using spin-polarized STM.

Tunable metamaterial absorber/emitter for high-efficiency concentrated photovoltaic-thermophotovoltaic systems

Applied Energy · 2026-04-04

Magnetic Order Induced Suppression of Photoluminescence in van der Waals Magnet CrPS₄

Laser & Photonics Review · 2025-04-20 · 6 citations

Abstract The intriguing physical phenomena and significant application potential are driving the development of two‐dimensional (2D) magnetic materials. The coupling of 2D magnetic order with electrons, phonons, and photons can profoundly influence the physical properties of 2D magnets, leading to advancements in spintronics and optoelectronics. However, the practical application of 2D magnets is impeded by the air‐instability and inadequate understanding of the complex coupling effects associated with 2D magnetic ordering. A study is presented here on the temperature, wavelength, and field‐dependent photoluminescence (PL) spectra of one of the few air‐stable van der Waals magnet CrPS 4 . A notable decreasing of the dominant PL peak intensity is observed in the presence of magnetic order and external magnetic field. Combined with theoretical calculations, this study determines that the modulation of PL intensity by magnetic order stems from the spin‐restricted selection rule imposing on the electron–hole radiative combination, resulting in the darkening of the bright excitons. Since spin‐polarized electronic band structure is prevalent in 2D magnets, these findings unveil a universal spin‐charge coupling effect and offer valuable insights into the fascinating interplay between magnetism and optical properties in 2D magnets, advocating strong promises for the development of advanced magneto‐optoelectronic devices based on CrPS 4 .

Predicting targeted- and immunotherapeutic response outcomes in melanoma with single-cell Raman spectroscopy and AI

bioRxiv (Cold Spring Harbor Laboratory) · 2025-05-21 · 1 citations

Abstract PURPOSE Identifying reliable predictors of immunotherapeutic response in melanoma remains an outstanding challenge. Existing transcriptomic and proteomic profiling methods for the tumor-immune microenvironment (TIME) are costly and may not faithfully capture modifications actively impacting tumor behavior. Here, we present a non-destructive, single-cell approach combining Raman spectroscopy and machine learning (ML) that enables rapid cell profiling and therapeutic response prediction. METHODS We analyzed single-cell Raman spectra of mouse and human melanoma cell lines alongside nine melanoma patient-derived samples with known resistance profiles to targeted and immunotherapeutic inhibitors bemcentinib, cabozantinib, dabrafenib, nivolumab, and a combination of nivolumab and relatlimab. We assessed cell phenotyping classification and treatment resistance using random forests and feature importance analysis. For patient samples, we constructed a two-stage evaluation workflow to determine clinical drug resistance through aggregated single-cell predictions and identified corresponding highly variant spectral signatures using computational methods adapted from single-cell RNA sequencing methods. RESULTS In cell lines, our approach achieved >96% differentiation accuracy across tumor microenvironment cell types and induced functional phenotypes. Persistent (drug-resistant) cells formed subclusters based on genetic mutations rather than sample origin, with Raman signatures reflecting biochemical changes relevant to therapeutic pathways. For patient samples, our workflow correctly inferred resistance likelihoods for 30 of 33 clinically-relevant patient-drug combinations (91% accuracy). CONCLUSION Single-cell Raman spectroscopy combined with machine learning offers a scalable, prognostic platform to predict therapeutic resistance likelihood, with further potential to advance clinical, multi-omic biomarker efforts for melanoma. Our approach may improve first-and second-line therapy selection assessments for precision medicine by providing rapid, non-destructive prediction of therapeutic response based on cellular spectral profiles. Context Summary Key objective Can label-free, single-cell Raman spectroscopy and machine learning approach accurately profile melanoma cell states and therapeutic resistance likelihood to targeted and immunotherapeutic agents? Knowledge generated Raman spectroscopy with machine learning differentiated tumor microenvironment cell types and functional phenotypes with >96% accuracy in cell lines. When applied to patient-derived metastatic melanoma samples, the approach correctly inferred patient response to a panel of targeted and immunotherapeutic inhibitors with 91% accuracy (30 of 33 cases). High-likelihood persistent and sensitive cells across diverse patients exhibited recurrent spectral features. Relevance Single-cell Raman-based profiling supports functional-diagnostic assessment or resistance likelihood and may contribute to improved therapeutic selection and precision oncology strategies for melanoma patients.

Low-force pulse switching of ferroelectric polarization enabled by imprint field

Nature Communications · 2025-06-06 · 9 citations

Abstract Beyond conventional electrical modulation, flexoelectricity enables mechanical control of ferroelectric polarizations, offering a pathway for tactile-responsive ferroelectric systems. However, mechanical polarization switching typically requires substantial static threshold forces to overcome the significant energy barrier, resulting in material fatigue and slow response that compromises reliability and hinders practical applications. In this work, we address these challenges by introducing an imprint field through asymmetric electrostatic boundary design with distinct work functions. This built-in electric field stabilizes the energy landscape, effectively lowering the polarization switching barrier. Subsequently, nonvolatile polarization switching with a low threshold force of 12 nN·nm −1 is achieved in CuInP 2 S 6 without material damage. Surpassing the limitations of slow static force controls, our work marks the first experimental demonstration of fast mechanical control of polarization switching with 4 millisecond-long low force pulses. To further highlight the potential of this rapid, low-force mechanical control, we propose a van der Waals heterostructured mechanically gated transistor with asymmetric electrostatic boundary, which exhibits gate force pulses-controlled multi-level, nonvolatile conductance states. Our findings establish a paradigm for next-generation ferroelectric electronics that integrate responsiveness to mechanical stimuli.

High-efficiency bulk photovoltaic effect with ferroelectric-increased shift current

Nature Communications · 2025-11-07 · 3 citations

Bulk photovoltaic (BPV) effect primarily stems from shift currents in symmetry-breaking materials, providing the potential to smash the Shockley-Queisser limit that constrains the performance of conventional p-n junctions-based solar cells. However, limited open circuit voltages (Voc) or short circuit current densities (Jsc) from BPV devices still cause a low photoelectric conversion efficiency. Here, combining theoretical analysis and experimental evidence, we identify a range of BPV materials where both Voc and Jsc can be co-optimized, and greatly boost the efficiency through ferroelectric engineered shift current. We select ferroelectric NbOBr2 as an example and construct a two-dimensional in-plane device with a giant shift current-dominated BPV effect. In spontaneous polarization state, the devices demonstrate a record-high Jsc among all ferroelectric materials. Moreover, the electrically aligned NbOBr2 polarization enables the significant co-enhancement of both Voc and Jsc, leading to a colossal improvement of photoelectric conversion efficiency up to four orders of magnitude (1.25%), which is approximately four times greater than that of state-of-the-art BPV devices. Our work provides a promising solution for screening and creating higher efficient BPV cells. The photoelectric conversion efficiency of bulk photovoltaic devices has been limited by open circuit voltages or short circuit current densities. Here, authors construct a 2D in-plane device based on ferroelectric NbOBr2 to improve photovoltaic performance and achieve a device efficiency of 1.25%.

Emergence of cascading flat bands in breathing superlattices

Physical review. B./Physical review. B · 2025-07-14 · 2 citations

Flat bands have become a pillar of modern condensed matter physics and photonics owing to the vanishing group velocity and diverging density of states. Here, we present a paradigmatic scheme to construct arbitrary flat bands on demand by introducing a new type breathing superlattice, where both the number and spectral positions of isolated flat bands can be continuously tailored by simply controlling the breathing strength. Microscopically, the momentum-independent interband scatterings near the band edge protect them robust against weak intra-cell disorder. By dimensional reduction, we establish a duality between the one-dimensional (1D) breathing superlattice and the 2D Harper-Hofstadter model, where cascade flat bands naturally emerge as the different orders of Landau levels in the weak magnetic flux limit. As a proof of concept, photonic flat bands at optical frequencies are experimentally demonstrated with all-dielectric photonic crystal slabs. Finally, we generalize our scheme to 2D systems to realize partial and omnidirectional flat bands, and discuss the achievement of high-quality factors. Our findings shed new light on the manipulation of flat bands with high band flatness and large usable bandwidth, paving the way for the development of advanced optical devices.

Giant Nonlinear Photon-Drag Currents in Centrosymmetric Moiré Bilayers

ArXiv.org · 2025-11-21

We present a unified microscopic theory of nonlinear photon-drag currents, formulated within a geometric-loop framework that provides both transparent quantum-geometric interpretation and numerical tractability. In this picture, the photon-drag shift current corresponds to the dipole moment of the geometric loop, while the photon-drag injection current arises from the same loop weighted by a band velocity difference. We apply the theory to an exact continuum model of twisted bilayer graphene (TBG) with ab initio accuracy. Remarkably, an in-plane wavevector only a few times larger than that of free-space photons already produces sizable photon-drag currents in centrosymmetric TBG, comparable to photogalvanic responses in typical noncentrosymmetric two-dimensional materials. These currents are broadly tunable by twist angle, photon wavevector, and light polarization. Our results establish a quantum geometric framework for nonlinear photon-drag phenomena and highlight moiré bilayers as promising platforms for large, highly tunable optoelectronic responses.