Activation and differentiation of cognate T cells by a dextran-based antigen-presenting system for cancer immunotherapy.

Immunotherapeutic modulation of antigen-specific T-cell responses instead of the whole repertoire helps avoid immune-related adverse events. We have developed an artificial antigen-presenting system (aAPS) where multiple copies of a multimeric peptide-MHC class I complex presenting a murine class I MHC restricted ovalbumin-derived peptide (signal 1), along with a costimulatory ligand (signal 2) are chemically conjugated to a dextran backbone. Cognate naive CD8+ T cells, when treated with this aAPS underwent significant expansion and showed an activated phenotype. Furthermore, elevated expression of effector cytokines led to the differentiation of these cells to cytotoxic T lymphocytes which resulted in target cell lysis, indicative of the functional efficacy of the aAPS. CD8+ T cells with decreased proliferative potential due to repeated antigenic stimulation could also be re-expanded by the developed aAPS. Thus, the developed aAPS warrants further engineering for future application as a rapidly customizable personalized immunotherapeutic agent, incorporating patient-specific MHC-restricted tumor antigens and different costimulatory signals to modulate both naive and antigen-experienced but exhausted tumor-specific T cells in cancer.

Deep Learning on Multimodal Chemical and Whole Slide Imaging Data for Predicting Prostate Cancer Directly from Tissue Images.

Prostate cancer is one of the most common cancers globally and is the second most common cancer in the male population in the US. Here we develop a study based on correlating the hematoxylin and eosin (H&E)-stained biopsy data with MALDI mass-spectrometric imaging data of the corresponding tissue to determine the cancerous regions and their unique chemical signatures and variations of the predicted regions with original pathological annotations. We obtain features from high-resolution optical micrographs of whole slide H&E stained data through deep learning and spatially register them with mass spectrometry imaging (MSI) data to correlate the chemical signature with the tissue anatomy of the data. We then use the learned correlation to predict prostate cancer from observed H&E images using trained coregistered MSI data. This multimodal approach can predict cancerous regions with ∼80% accuracy, which indicates a correlation between optical H&E features and chemical information found in MSI. We show that such paired multimodal data can be used for training feature extraction networks on H&E data which bypasses the need to acquire expensive MSI data and eliminates the need for manual annotation saving valuable time. Two chemical biomarkers were also found to be predicting the ground truth cancerous regions. This study shows promise in generating improved patient treatment trajectories by predicting prostate cancer directly from readily available H&E-stained biopsy images aided by coregistered MSI data.

Double-Bilayer polar nanoregions and Mn antisites in (Ca, Sr)3Mn2O7.

The layered perovskite Ca3Mn2O7 (CMO) is a hybrid improper ferroelectric candidate proposed for room temperature multiferroicity, which also displays negative thermal expansion behavior due to a competition between coexisting polar and nonpolar phases. However, little is known about the atomic-scale structure of the polar/nonpolar phase coexistence or the underlying physics of its formation and transition. In this work, we report the direct observation of double bilayer polar nanoregions (db-PNRs) in Ca2.9Sr0.1Mn2O7 using aberration-corrected scanning transmission electron microscopy (S/TEM). In-situ TEM heating experiments show that the db-PNRs can exist up to 650 °C. Electron energy loss spectroscopy (EELS) studies coupled with first-principles calculations demonstrate that the stabilization mechanism of the db-PNRs is directly related to an Mn oxidation state change (from 4+ to 2+), which is linked to the presence of Mn antisite defects. These findings open the door to manipulating phase coexistence and achieving exotic properties in hybrid improper ferroelectric.

High-resolution crystal structure of LpqH, an immunomodulatory surface lipoprotein of Mycobacterium tuberculosis reveals a distinct fold and a conserved cleft on its surface.

Tuberculosis, caused by Mycobacterium tuberculosis, is predominantly a disease of the lungs acquired by inhaling mycobacteria from infected individuals via airborne droplets. In order to facilitate their entry into the alveolar macrophages, mycobacteria have a collection of pathogen-associated molecular patterns (PAMPs) on their surface that are known to detect certain pattern recognition receptors present on the surface of host cells. A major group of these PAMPs includes mycobacterial lipoproteins, of which, the 19 kDa surface antigen LpqH, has been reported to play a critical role in both host-pathogen interactions as well as pleiotropic immune regulation. Despite its crucial involvement in tuberculosis, the detailed structure-function relationship of this protein remains to be explored. Here, we report the high-resolution crystal structure of the non-acylated LpqH (LpqH48-159) at a resolution of 1.26 Å, which adopts a unique fold. Flow cytometry-based experiments show that the protein can bind and induce apoptosis in PMA-activated human monocytic cell line THP-1, indicative of the preservation of functionality of the protein. Furthermore, analysis of conservation of LpqH sequences from Mycobacterium species reveals a patch of conserved residues on the surface which may play a role in its binding partner recognition and hence in host-pathogen interaction.

Peptide-MHC complexes: dressing up to manipulate T cells against autoimmunity and cancer.

Antigen-specificity of T cells provides important clues to the pathogenesis of T cell-mediated autoimmune diseases and immune-evasion strategies of tumors. Identification of T cell clones involved in autoimmunity or cancer is achieved with soluble peptide-MHC (pMHC) complex multimers. Importantly, these complexes can also be used to manipulate disease-relevant T cells to restore homeostasis of T cell-mediated immune response. While auto-antigen-specific T cells can be deleted or anergized by T cell receptor engagement with cognate pMHC complexes in the absence of costimulation, integration of these complexes in artificial antigen-presenting systems can activate tumor antigen-specific T cells. Here the authors discuss the advancements in pMHC-complex-mediated immunotherapeutic strategies in autoimmunity and cancer and identify the lacunae in these strategies that need to be addressed to facilitate clinical implementation.

Picometer-Precision Atomic Position Tracking through Electron Microscopy.

The modern aberration-corrected scanning transmission electron microscopes (AC-STEM) have successfully achieved direct visualization of atomic columns with sub-angstrom resolution. With this significant progress, advanced image quantification and analysis are still at the early stages. In this work, we present the complete pathway for the metrology of atomic resolution scanning transmission electron microscopy (STEM) images. This includes (1) tips for acquiring high-quality STEM images; (2) denoising and drift-correction for enhancing measurement accuracy; (3) obtaining initial atomic positions; (4) indexing the atoms based on unit cell vectors; (5) quantifying the atom column positions with either 2D-Gaussian single peak fitting or (6) multi-peak fitting routines for slightly overlapping atomic columns; (7) quantification of lattice distortion/strain within the crystal structures or at the defects/interfaces where the lattice periodicity is disrupted; and (8) some common methods to visualize and present the analysis. Furthermore, a simple self-developed free MATLAB app (EASY-STEM) with a graphical user interface (GUI) will be presented. The GUI can assist in the analysis of STEM images without the need for writing dedicated analysis code or software. The advanced data analysis methods presented here can be applied for the local quantification of defect relaxations, local structural distortions, local phase transformations, and non-centrosymmetry in a wide range of materials.

Applying Configurational Complexity to the 2D Ruddlesden-Popper Crystal Structure.

The layered Ruddlesden-Popper crystal structure can host a broad range of functionally important behaviors. Here we establish extraordinary configurational disorder in a layered Ruddlesden-Popper (RP) structure using entropy stabilization assisted synthesis. A protype A2CuO4 RP cuprate oxide with five cations on the A-site sublattice is designed and fabricated into epitaxial single crystal films using pulsed laser deposition. When grown on a near lattice matched substrate, the (La0.2Pr0.2Nd0.2Sm0.2Eu0.2)2CuO4 film features a T'-type RP structure with uniform A-site cation mixing and square-planar CuO4 units. These observations are made with a range of combined characterizations using X-ray diffraction, atomic-resolution scanning transmission electron microscopy, energy-dispersive X-ray spectroscopy, and X-ray absorption spectroscopy measurements. It is further found that heteroepitaxial strain plays an important role in crystal phase formation during synthesis. Compressive strain over ∼1.5% results in the formation of a non-RP cubic phase consistent with a CuX2O4 spinel structure. The ability to manipulate configurational complexity and move between 2D layered RP and 3D cubic crystal structures in cuprate and related materials promises to enable flexible design strategies for a range of functionalities, such as magnetoresistance, unconventional superconductivity, ferroelectricity, catalysis, and ion transport.

Polar Oxides without Inversion Symmetry through Vacancy and Chemical Order.

One synthetic modality for materials discovery proceeds by forming mixtures of two or more compounds. In transition metal oxides (TMOs), chemical substitution often obeys Vegard's principle, and the resulting structure and properties of the derived phase follow from its components. A change in the assembly of the components into a digital nanostructure, however, can stabilize new polymorphs and properties not observed in the constituents. Here we formulate and demonstrate a crystal-chemistry design approach for realizing digital TMOs without inversion symmetry by combining two centrosymmetric compounds, utilizing periodic anion-vacancy order to generate multiple polyhedra that together with cation order produce a polar structure. We next apply this strategy to two brownmillerite-structured TMOs known to display centrosymmetric crystal structures in their bulk, Ca2Fe2O5 and Sr2Fe2O5. We then realize epitaxial (SrFeO2.5)1/(CaFeO2.5)1 thin film superlattices possessing both anion-vacancy order and Sr and Ca chemical order at the subnanometer scale, confirmed through synchrotron-based diffraction and aberration corrected electron microscopy. Through a detailed symmetry analysis and density functional theory calculations, we show that A-site cation ordering lifts inversion symmetry in the superlattice and produces a polar compound. Our results demonstrate how control of anion and cation order at the nanoscale can be utilized to produce acentric structures markedly different than their constituents and open a path toward novel structure-based property design.

Wafer-scale growth of VO2 thin films using a combinatorial approach.

Transition metal oxides offer functional properties beyond conventional semiconductors. Bridging the gap between the fundamental research frontier in oxide electronics and their realization in commercial devices demands a wafer-scale growth approach for high-quality transition metal oxide thin films. Such a method requires excellent control over the transition metal valence state to avoid performance deterioration, which has been proved challenging. Here we present a scalable growth approach that enables a precise valence state control. By creating an oxygen activity gradient across the wafer, a continuous valence state library is established to directly identify the optimal growth condition. Single-crystalline VO2 thin films have been grown on wafer scale, exhibiting more than four orders of magnitude change in resistivity across the metal-to-insulator transition. It is demonstrated that 'electronic grade' transition metal oxide films can be realized on a large scale using a combinatorial growth approach, which can be extended to other multivalent oxide systems.

Freestanding van der Waals heterostructures of graphene and transition metal dichalcogenides.

Vertical stacking of two-dimensional (2D) crystals has recently attracted substantial interest due to unique properties and potential applications they can introduce. However, little is known about their microstructure because fabrication of the 2D heterostructures on a rigid substrate limits one's ability to directly study their atomic and chemical structures using electron microscopy. This study demonstrates a unique approach to create atomically thin freestanding van der Waals heterostructures-WSe2/graphene and MoS2/graphene-as ideal model systems to investigate the nucleation and growth mechanisms in heterostructures. In this study, we use transmission electron microscopy (TEM) imaging and diffraction to show epitaxial growth of the freestanding WSe2/graphene heterostructure, while no epitaxy is maintained in the MoS2/graphene heterostructure. Ultra-high-resolution aberration-corrected scanning transmission electron microscopy (STEM) shows growth of monolayer WSe2 and MoS2 triangles on graphene membranes and reveals their edge morphology and crystallinity. Photoluminescence measurements indicate a significant quenching of the photoluminescence response for the transition metal dichalcogenides on freestanding graphene, compared to those on a rigid substrate, such as sapphire and epitaxial graphene. Using a combination of (S)TEM imaging and electron diffraction analysis, this study also reveals the significant role of defects on the heterostructure growth. The direct growth technique applied here enables us to investigate the heterostructure nucleation and growth mechanisms at the atomic level without sample handling and transfer. Importantly, this approach can be utilized to study a wide spectrum of van der Waals heterostructures.