Inulin-gel-based oral immunotherapy remodels the small intestinal microbiome and suppresses food allergy.

Despite the potential of oral immunotherapy against food allergy, adverse reactions and loss of desensitization hinder its clinical uptake. Dysbiosis of the gut microbiota is implicated in the increasing prevalence of food allergy, which will need to be regulated to enable for an effective oral immunotherapy against food allergy. Here we report an inulin gel formulated with an allergen that normalizes the dysregulated ileal microbiota and metabolites in allergic mice, establishes allergen-specific oral tolerance and achieves robust oral immunotherapy efficacy with sustained unresponsiveness in food allergy models. These positive outcomes are associated with enhanced allergen uptake by antigen-sampling dendritic cells in the small intestine, suppressed pathogenic type 2 immune responses, increased interferon-γ+ and interleukin-10+ regulatory T cell populations, and restored ileal abundances of Eggerthellaceae and Enterorhabdus in allergic mice. Overall, our findings underscore the therapeutic potential of the engineered allergen gel as a suitable microbiome-modulating platform for food allergy and other allergic diseases.

Observation of quadrupolar and dipolar excitons in a semiconductor heterotrilayer.

Van der Waals (vdW) materials have opened up many avenues for discovery through layer assembly, as epitomized by interlayer dipolar excitons that exhibit electrically tunable luminescence, lasing and exciton condensation. Extending interlayer excitons to more vdW layers, however, raises fundamental questions concerning coherence within excitons and coupling between moiré superlattices at multiple interfaces. Here, by assembling angle-aligned WSe2/WS2/WSe2 heterotrilayers, we demonstrate the emergence of quadrupolar excitons. We confirm the exciton's quadrupolar nature by the decrease in its energy of 12 meV from coherent hole tunnelling between the two outer layers, its tunable static dipole moment under an external electric field and the reduced exciton-exciton interactions. At high exciton density, we also see signatures of a phase of oppositely aligned dipolar excitons, consistent with a staggered dipolar phase predicted to be driven by attractive dipolar interactions. Our demonstration paves the way for discovering emergent exciton orderings for three vdW layers and beyond.

Asymmetric Synthesis of CIDD-0072424 via an Enantioselective Nitro-Mannich Reaction: A Central Nervous System Penetrant, Selective Small Molecule Inhibitor of Protein Kinase C Epsilon.

CIDD-0072424 is a novel small molecule developed in silico with remarkable activity for the inhibition of protein kinase C (PKC)-epsilon to treat alcohol use disorder. We developed a concise synthesis of (S)-2 that is highly enantioselective, scalable, and amenable for 3-point structure-activity relationship (SAR) studies for compound optimization. The highly enantioselective nitro-Mannich reaction was achieved through a dual-reagent catalysis system. The overall utility and the efficiency of the enantioselective route provided a scalable synthesis of both PKCε inhibitors 1 and 2.

Moiré-Assisted Strain Transfer in Vertical van der Waals Heterostructures.

Strain provides a powerful method to study 2D monolayers and to tune their properties. The same approach also has great potential for van-der-Waals (vdW) heterostructures. However, we need to understand how strain can be applied to vertically stacked vdW structures, for which strain transfer from one layer to the next remains little explored. In our experiment, we fabricated vertical heterostructures consisting of transition metal dichalcogenides (TMDCs) monolayers that were deposited on a flexible substrate. These TMDC heterostructures allowed us to read out separately the strain in each monolayer by photoluminescence measurements. We find that, in TMDC heterostructures with large twist angles (>5°), strain transfer is limited. However, for aligned heterostructures with small twist angles (≤5°), near unity strain transfer efficiency is observed. We correlate this finding with the moiré domains formed in the aligned heterostructures by reconstruction.

Site-Controlled Quantum Emitters in Monolayer MoSe2.

Atomically thin semiconductors provide a highly attractive platform for quantum emitters (QEs): They can be combined with arbitrary substrates, can be spatially aligned with photonic structures, and can be electrically driven. All QEs reported to date in these materials have, however, relied on nominally spin-forbidden transitions, with radiative rates falling substantially below those of other solid-state QE systems. Here we employ strain confinement in monolayer MoSe2 to produce engineered QEs, as confirmed in photon antibunching measurements. We discuss spin-allowed versus spin-forbidden transitions based on magneto- and time-resolved photoluminescence measurements. We calculate a radiative rate for spin-allowed quantum emission greater than 1 ns-1, which exceeds reported radiative rates of WSe2 QEs by 2 orders of magnitude.

Revealing multiple classes of stable quantum emitters in hexagonal boron nitride with correlated optical and electron microscopy.

Defects in hexagonal boron nitride (hBN) exhibit high-brightness, room-temperature quantum emission, but their large spectral variability and unknown local structure challenge their technological utility. Here, we directly correlate hBN quantum emission with local strain using a combination of photoluminescence (PL), cathodoluminescence (CL) and nanobeam electron diffraction. Across 40 emitters, we observe zero phonon lines (ZPLs) in PL and CL ranging from 540 to 720 nm. CL mapping reveals that multiple defects and distinct defect species located within an optically diffraction-limited region can each contribute to the observed PL spectra. Local strain maps indicate that strain is not required to activate the emitters and is not solely responsible for the observed ZPL spectral range. Instead, at least four distinct defect classes are responsible for the observed emission range, and all four classes are stable upon both optical and electron illumination. Our results provide a foundation for future atomic-scale optical characterization of colour centres.

Contribution of Lipid Oxidation and Ferroptosis to Radiotherapy Efficacy.

Radiotherapy promotes tumor cell death and senescence through the induction of oxidative damage. Recent work has highlighted the importance of lipid peroxidation for radiotherapy efficacy. Excessive lipid peroxidation can promote ferroptosis, a regulated form of cell death. In this review, we address the evidence supporting a role of ferroptosis in response to radiotherapy and discuss the molecular regulators that underlie this interaction. Finally, we postulate on the clinical implications for the intersection of ferroptosis and radiotherapy.

Quantum-dot spin-photon entanglement via frequency downconversion to telecom wavelength.

Long-distance quantum teleportation and quantum repeater technologies require entanglement between a single matter quantum bit (qubit) and a telecommunications (telecom)-wavelength photonic qubit. Electron spins in III-V semiconductor quantum dots are among the matter qubits that allow for the fastest spin manipulation and photon emission, but entanglement between a single quantum-dot spin qubit and a flying (propagating) photonic qubit has yet to be demonstrated. Moreover, many quantum dots emit single photons at visible to near-infrared wavelengths, where silica fibre losses are so high that long-distance quantum communication protocols become difficult to implement. Here we demonstrate entanglement between an InAs quantum-dot electron spin qubit and a photonic qubit, by frequency downconversion of a spontaneously emitted photon from a singly charged quantum dot to a wavelength of 1,560 nanometres. The use of sub-10-picosecond pulses at a wavelength of 2.2 micrometres in the frequency downconversion process provides the necessary quantum erasure to eliminate which-path information in the photon energy. Together with previously demonstrated indistinguishable single-photon emission at high repetition rates, the present technique advances the III-V semiconductor quantum-dot spin system as a promising platform for long-distance quantum communication.

Noncoupled Fluorescent Assay for Direct Real-Time Monitoring of Nicotinamide N-Methyltransferase Activity.

Nicotinamide N-methyltransferase (NNMT) is an important biotransforming enzyme that catalyzes the transfer of a labile methyl group from the ubiquitous cofactor S-5'-adenosyl-l-methionine (SAM) to endogenous and exogenous small molecules to form methylated end products. NNMT has been implicated in a number of chronic disease conditions, including metabolic disorders, cardiovascular disease, cancer, osteoarthritis, kidney disease, and Parkinson's disease. We have developed a novel noncoupled fluorescence-based methyltransferase assay that allows direct ultrasensitive real-time detection of the NNMT reaction product 1-methylquinolinium. This is the first assay reported to date to utilize fluorescence spectroscopy to directly monitor NNMT product formation and activity in real time. This assay provided accurate kinetic data that allowed detailed comparative analysis of the NNMT reaction mechanism and kinetic parameters. A reaction model based on a random bireactant mechanism produced global curve fits that were most consistent with steady-state initial velocity data collected across an array of substrate concentrations. On the basis of the reaction mechanism, each substrate could independently bind to the NNMT apoenzyme; however, both substrates bound to the complementary binary complexes with an affinity ∼20-fold stronger compared to their binding to the apoenzyme. This reaction mechanism implies either substrate-induced conformational changes or bireactant intermolecular interactions may stabilize the binding of the substrate to the binary complex and formation of the ternary complex. Importantly, this assay could rapidly generate concentration response curves for known NNMT inhibitors, suggesting its applicability for high-throughput screening of chemical libraries to identify novel NNMT inhibitors. Furthermore, our novel assay potentially offers a robust detection technology for use in SAM substrate competition assays for the discovery and development of SAM-dependent methyltransferase inhibitors.

Strategies for the development of metalloimmunotherapies.

Metal ions play crucial roles in the regulation of immune pathways. In fact, metallodrugs have a long record of accomplishment as effective treatments for a wide range of diseases. Here we argue that the modulation of interactions of metal ions with molecules and cells involved in the immune system forms the basis of a new class of immunotherapies. By examining how metal ions modulate the innate and adaptive immune systems, as well as host-microbiota interactions, we discuss strategies for the development of such metalloimmunotherapies for the treatment of cancer and other immune-related diseases.

STING-activating cyclic dinucleotide-manganese nanoparticles evoke robust immunity against acute myeloid leukemia.

Acute myeloid leukemia (AML) is one of the most common types of leukemia in adults with a 5-year survival rate of 30.5%. These poor patient outcomes are attributed to tumor relapse, stemming from ineffective innate immune activation, T cell tolerance, and a lack of immunological memory. Thus, new strategies are needed to activate innate and effector immune cells and evoke long-term immunity against AML. One approach to address these issues is through Stimulator of Interferon Genes (STING) pathway activation, which produces Type I Interferons (Type I IFN) critical for innate and adaptive immune activation. Here, we report that systemic immunotherapy with a lipid-based nanoparticle platform (CMP) carrying Mn2+ and STING agonist c-di-AMP (CDA) exhibited robust anti-tumor efficacy in a mouse model of disseminated AML. Moreover, CMP immunotherapy combined with immune checkpoint blockade against cytotoxic T-lymphocyte-associated protein 4 (anti-CTLA-4) elicited robust innate and adaptive immune activation with enhanced cytotoxic potential against AML, leading to extended animal survival after re-challenge with AML. Overall, this CMP combination immunotherapy may be a promising approach against AML and other disseminated cancer.

Immune escape of head and neck cancer mediated by the impaired MHC-I antigen presentation pathway.

Tumor immune evasion is a hallmark of Head and Neck Cancers. The advent of immune checkpoint inhibitors (ICIs) in the first-line setting has transformed the management of these tumors. Unfortunately, the response rate of Head and Neck Squamous Cell Carcinomas (HNSCC) to ICIs is below 15%, regardless of the human papillomavirus (HPV) status, which might be partially related with impaired antigen presentation machinery (APM). Mechanistically, HNSCC cells are usually defective in the expression of MHC-I associated APM, while this transcriptional pathway is critical for the activation of tumor-killing effector T-cells. To specifically illuminate the phenomenon and seek for therapeutic strategies, this review summarizes the most recently identified role of genetic and functional dysregulation of the MHC-I pathway, specifically through changes at the genetic, epigenetic, post-transcriptional, and post-translational levels, which substantially contributes to HNSCC immune escape and ICI resistance. Several treatment modalities can be potentially exploited to restore APM signaling in tumors, which improves anti-tumor immunity through the activation of interferons, vaccines or rimantadine against HPV and the inhibition of EGFR, SHP-2, PI3K and MEK. Additionally, the combinatorial use of radiotherapy or cytotoxic agents with ICIs can synergize to potentiate APM signaling. Future directions would include further dissection of MHC-I related APM signaling in HNSCC and whether reversing this inhibition in combination with ICIs would elicit a more robust immune response leading to improved response rates in HNSCC. Therapeutic approaches to restore the MHC-I antigen presentation machinery in Head and Neck Cancer. (Red color texts represent the according strategies and the outcomes).

Self-Assembled STING-Activating Coordination Nanoparticles for Cancer Immunotherapy and Vaccine Applications.

The cGAS-STING pathway plays a crucial role in innate immune activation against cancer and infections, and STING agonists based on cyclic dinucleotides (CDN) have garnered attention for their potential use in cancer immunotherapy and vaccines. However, the limited drug-like properties of CDN necessitate an efficient delivery system to the immune system. To address these challenges, we developed an immunostimulatory delivery system for STING agonists. Here, we have examined aqueous coordination interactions between CDN and metal ions and report that CDN mixed with Zn2+ and Mn2+ formed distinctive crystal structures. Further pharmaceutical engineering led to the development of a functional coordination nanoparticle, termed the Zinc-Mn-CDN Particle (ZMCP), produced by a simple aqueous one-pot synthesis. Local or systemic administration of ZMCP exerted robust antitumor efficacy in mice. Importantly, recombinant protein antigens from SARS-CoV-2 can be simply loaded during the aqueous one-pot synthesis. The resulting ZMCP antigens elicited strong cellular and humoral immune responses that neutralized SARS-CoV-2, highlighting ZMCP as a self-adjuvant vaccine platform against COVID-19 and other infectious pathogens. Overall, this work establishes a paradigm for developing translational coordination nanomedicine based on drug-metal ion coordination and broadens the applicability of coordination medicine for the delivery of proteins and other biologics.

Microbiota-dependent activation of CD4+ T cells induces CTLA-4 blockade-associated colitis via Fcγ receptors.

Immune checkpoint inhibitors can stimulate antitumor immunity but can also induce toxicities termed immune-related adverse events (irAEs). Colitis is a common and severe irAE that can lead to treatment discontinuation. Mechanistic understanding of gut irAEs has been hampered because robust colitis is not observed in laboratory mice treated with checkpoint inhibitors. We report here that this limitation can be overcome by using mice harboring the microbiota of wild-caught mice, which develop overt colitis following treatment with anti-CTLA-4 antibodies. Intestinal inflammation is driven by unrestrained activation of IFNγ-producing CD4+ T cells and depletion of peripherally induced regulatory T cells through Fcγ receptor signaling. Accordingly, anti-CTLA-4 nanobodies that lack an Fc domain can promote antitumor responses without triggering colitis. This work suggests a strategy for mitigating gut irAEs while preserving antitumor stimulating effects of CTLA-4 blockade.

Antigen-Clustered Nanovaccine Achieves Long-Term Tumor Remission by Promoting B/CD 4 T Cell Crosstalk.

Current cancer vaccines using T cell epitopes activate antitumor T cell immunity through dendritic cell/macrophage-mediated antigen presentation, but they lack the ability to promote B/CD4 T cell crosstalk, limiting their anticancer efficacy. We developed antigen-clustered nanovaccine (ACNVax) to achieve long-term tumor remission by promoting B/CD4 T cell crosstalk. The topographic features of ACNVax were achieved using an iron nanoparticle core attached with an optimal number of gold nanoparticles, where the clusters of HER2 B/CD4 T cell epitopes were conjugated on the gold surface with an optimal intercluster distance of 5-10 nm. ACNVax effectively trafficked to lymph nodes and cross-linked with BCR, which are essential for stimulating B cell antigen presentation-mediated B/CD4 T cell crosstalk in vitro and in vivo. ACNVax, combined with anti-PD-1, achieved long-term tumor remission (>200 days) with 80% complete response in mice with HER2+ breast cancer. ACNVax not only remodeled the tumor immune microenvironment but also induced a long-term immune memory, as evidenced by complete rejection of tumor rechallenge and a high level of antigen-specific memory B, CD4, and CD8 cells in mice (>200 days). This study provides a cancer vaccine design strategy, using B/CD4 T cell epitopes in an antigen clustered topography, to achieve long-term durable anticancer efficacy through promoting B/CD4 T cell crosstalk.

De novo asymmetric synthesis of oligo-rhamno di- and tri-saccharides related to the anthrax tetrasaccharide.

An asymmetric synthesis of the di- and trisaccharide portion of the naturally occurring anthrax tetrasaccharide from acetylfuran has been developed. The construction of the di- and trisaccharide subunits is based upon our previously disclosed route to anthrax tetrasaccharide. The approach uses iterative diastereoselective palladium-catalyzed glycosylations, Luche reductions, diastereoselective dihydroxylations, and regioselective protections for the assembly of the rhamno- di- and tri-saccharide. The route was also modified for the preparation of the mixed D-/L-disaccharide analogue.

Unlocking the promise of systemic STING agonist for cancer immunotherapy.

Stimulator of interferon genes (STING) pathway is the key innate immune pathway involving in cancer immunity. Emerging new molecules and drug delivery systems have made systemic STING agonist immunotherapy possible and demonstrated efficient tumor eradication in preclinical studies. In this perspective, we will discuss the potential mechanisms of STING agonism as a multifaceted anti-cancer therapy and the pharmacological challenges associated with systemic delivery of STING agonists on the level of organs, tissues, cells, and intracellular compartments. We will present and discuss drug delivery strategies to address these challenges. New advances in the field can unlock the promise of systemic STING agonist as effective and safe cancer immunotherapy.

Super-resolution and segmentation deep learning for breast cancer histopathology image analysis.

Traditionally, a high-performance microscope with a large numerical aperture is required to acquire high-resolution images. However, the images' size is typically tremendous. Therefore, they are not conveniently managed and transferred across a computer network or stored in a limited computer storage system. As a result, image compression is commonly used to reduce image size resulting in poor image resolution. Here, we demonstrate custom convolution neural networks (CNNs) for both super-resolution image enhancement from low-resolution images and characterization of both cells and nuclei from hematoxylin and eosin (H&E) stained breast cancer histopathological images by using a combination of generator and discriminator networks so-called super-resolution generative adversarial network-based on aggregated residual transformation (SRGAN-ResNeXt) to facilitate cancer diagnosis in low resource settings. The results provide high enhancement in image quality where the peak signal-to-noise ratio and structural similarity of our network results are over 30 dB and 0.93, respectively. The derived performance is superior to the results obtained from both the bicubic interpolation and the well-known SRGAN deep-learning methods. In addition, another custom CNN is used to perform image segmentation from the generated high-resolution breast cancer images derived with our model with an average Intersection over Union of 0.869 and an average dice similarity coefficient of 0.893 for the H&E image segmentation results. Finally, we propose the jointly trained SRGAN-ResNeXt and Inception U-net Models, which applied the weights from the individually trained SRGAN-ResNeXt and inception U-net models as the pre-trained weights for transfer learning. The jointly trained model's results are progressively improved and promising. We anticipate these custom CNNs can help resolve the inaccessibility of advanced microscopes or whole slide imaging (WSI) systems to acquire high-resolution images from low-performance microscopes located in remote-constraint settings.

Giant room-temperature nonlinearities in a monolayer Janus topological semiconductor.

Nonlinear optical materials possess wide applications, ranging from terahertz and mid-infrared detection to energy harvesting. Recently, the correlations between nonlinear optical responses and certain topological properties, such as the Berry curvature and the quantum metric tensor, have attracted considerable interest. Here, we report giant room-temperature nonlinearities in non-centrosymmetric two-dimensional topological materials-the Janus transition metal dichalcogenides in the 1 T' phase, synthesized by an advanced atomic-layer substitution method. High harmonic generation, terahertz emission spectroscopy, and second harmonic generation measurements consistently show orders-of-the-magnitude enhancement in terahertz-frequency nonlinearities in 1 T' MoSSe (e.g., > 50 times higher than 2H MoS2 for 18th order harmonic generation; > 20 times higher than 2H MoS2 for terahertz emission). We link this giant nonlinear optical response to topological band mixing and strong inversion symmetry breaking due to the Janus structure. Our work defines general protocols for designing materials with large nonlinearities and heralds the applications of topological materials in optoelectronics down to the monolayer limit.

Recurrent and convolutional neural networks for sequential multispectral optoacoustic tomography (MSOT) imaging.

Multispectral optoacoustic tomography (MSOT) is a beneficial technique for diagnosing and analyzing biological samples since it provides meticulous details in anatomy and physiology. However, acquiring high through-plane resolution volumetric MSOT is time-consuming. Here, we propose a deep learning model based on hybrid recurrent and convolutional neural networks to generate sequential cross-sectional images for an MSOT system. This system provides three modalities (MSOT, ultrasound, and optoacoustic imaging of a specific exogenous contrast agent) in a single scan. This study used ICG-conjugated nanoworms particles (NWs-ICG) as the contrast agent. Instead of acquiring seven images with a step size of 0.1 mm, we can receive two images with a step size of 0.6 mm as input for the proposed deep learning model. The deep learning model can generate five other images with a step size of 0.1 mm between these two input images meaning we can reduce acquisition time by approximately 71%.