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Metasurfaces are planar optical elements that hold promise for overcoming the limitations of refractive and conventional diffractive optics. Original dielectric metasurfaces are limited to transparency windows at infrared wavelengths because of significant optical absorption and loss at visible wavelengths. Thus, it is critical that new materials and nanofabrication techniques be developed to extend dielectric metasurfaces across the visible spectrum and to enable applications such as high numerical aperture lenses, color holograms, and wearable optics. Here, we demonstrate high performance dielectric metasurfaces in the form of holograms for red, green, and blue wavelengths with record absolute efficiency (>78%). We use atomic layer deposition of amorphous titanium dioxide with surface roughness less than 1 nmand negligible optical loss. We use a process for fabricating dielectric metasurfaces that allows us to produce anisotropic, subwavelength-spaced dielectric nanostructures with shape birefringence. This process is capable of realizing any high-efficiency metasurface optical element, e.g., metalenses and axicons.

Subwavelength resolution imaging requires high numerical aperture (NA) lenses, which are bulky and expensive. Metasurfaces allow the miniaturization of conventional refractive optics into planar structures. We show that high-aspect-ratio titanium dioxide metasurfaces can be fabricated and designed as metalenses with NA = 0.8. Diffraction-limited focusing is demonstrated at wavelengths of 405, 532, and 660 nm with corresponding efficiencies of 86, 73, and 66%. The metalenses can resolve nanoscale features separated by subwavelength distances and provide magnification as high as 170x, with image qualities comparable to a state-of-the-art commercial objective. Our results firmly establish that metalenses can have widespread applications in laser-based microscopy, imaging, and spectroscopy.

Single-cell RNA sequencing (scRNA-seq) enables the systematic identification of cell populations in a tissue, but characterizing their spatial organization remains challenging. We combine a microarray-based spatial transcriptomics method that reveals spatial patterns of gene expression using an array of spots, each capturing the transcriptomes of multiple adjacent cells, with scRNA-Seq generated from the same sample. To annotate the precise cellular composition of distinct tissue regions, we introduce a method for multimodal intersection analysis. Applying multimodal intersection analysis to primary pancreatic tumors, we find that subpopulations of ductal cells, macrophages, dendritic cells and cancer cells have spatially restricted enrichments, as well as distinct coenrichments with other cell types. Furthermore, we identify colocalization of inflammatory fibroblasts and cancer cells expressing a stress-response gene module. Our approach for mapping the architecture of scRNA-seq-defined subpopulations can be applied to reveal the interactions inherent to complex tissues. Combining single-cell RNA-seq data and microarray-based spatial transcriptomics maps the location of different cell types and cell states in pancreatic tumors.

Optical elements that convert the spin angular momentum (SAM) of light into vortex beams have found applications in classical and quantum optics. These elements—SAM-to–orbital angular momentum (OAM) converters—are based on the geometric phase and only permit the conversion of left- and right-circular polarizations (spin states) into states with opposite OAM. We present a method for converting arbitrary SAM states into total angular momentum states characterized by a superposition of independent OAM. We designed a metasurface that converts left- and right-circular polarizations into states with independent values of OAM and designed another device that performs this operation for elliptically polarized states. These results illustrate a general material-mediated connection between SAM and OAM of light and may find applications in producing complex structured light and in optical communication.

Genome-scale metabolic modeling is a growing area of computational biology, rich in biotechnology applications, including the study of human metabolism for drug development and the design of synthetic microbial communities for health environmental and engineering purposes.Incorporating omics data into genome-scale metabolic models is an important avenue for improved predictive accuracy. We revisit and categorize the major challenges that still limit the applicability of these approaches, pointing to opportunities for future research.Predicting distributions of all possible fluxes, rather than optimal flux vectors, is a valuable and underused approach for incorporating uncertainty and capturing phenotypic diversity of metabolic states. Multiple tools are available for generating these distributions, but special care must be taken to obtain meaningful results. Genome-scale metabolic models are used in fields ranging from metabolic engineering to drug discovery and microbiome design. Although these models are often used to predict putatively optimal states, some applications, including modeling human tissues for drug development and microbial communities for synthetic ecology, may require sampling the whole space of feasible fluxes to obtain distributions of biologically relevant states. Additionally, many applications involve using transcriptomic or proteomic data to predict fluxes for specific tissues, diseases, or patients. We revisit different methods used toward these goals and focus on their limitations and challenges, providing guidelines on how to avoid some of the shortcomings of existing approaches and highlighting conceptual barriers that will require new methodologies and offer opportunities for future development. Genome-scale metabolic models are used in fields ranging from metabolic engineering to drug discovery and microbiome design. Although these models are often used to predict putatively optimal states, some applications, including modeling human tissues for drug development and microbial communities for synthetic ecology, may require sampling the whole space of feasible fluxes to obtain distributions of biologically relevant states. Additionally, many applications involve using transcriptomic or proteomic data to predict fluxes for specific tissues, diseases, or patients. We revisit different methods used toward these goals and focus on their limitations and challenges, providing guidelines on how to avoid some of the shortcomings of existing approaches and highlighting conceptual barriers that will require new methodologies and offer opportunities for future development.

Bessel beams are of great interest due to their unique non-diffractive properties. Using a conical prism or an objective paired with an annular aperture are two typical approaches for generating zeroth-order Bessel beams. However, the former approach has a limited numerical aperture (NA), and the latter suffers from low efficiency, as most of the incident light is blocked by the aperture. Furthermore, an additional phase-modulating element is needed to generate higher-order Bessel beams, which in turn adds complexity and bulkiness to the system. We overcome these problems using dielectric metasurfaces to realize meta-axicons with additional functionalities not achievable with conventional means. We demonstrate meta-axicons with high NA up to 0.9 capable of generating Bessel beams with full width at half maximum about as small as ~ λ /3 ( λ =405 nm). Importantly, these Bessel beams have transverse intensity profiles independent of wavelength across the visible spectrum. These meta-axicons can enable advanced research and applications related to Bessel beams, such as laser fabrication, imaging and optical manipulation. Ultra-thin metasurfaces to generate wavelength-independent sub-wavelength Bessel beams Custom-designed metasurfaces can act as compact and efficient generators of special light beams known as Bessel beams. These beams are of great interest because unlike other kinds of light beams they do not diffract as they propagate. Wei Ting Chen and co-workers from Harvard University in the USA have made a metasurface that functions as an axicon — a special type of lens with a conical front surface that converts plane waves into Bessel beams. The metasurfaces consists of tiny TiO 2 fins arranged in concentric ring-like patterns; each fin has a precisely defined orientation. On striking this metasurface axicon, a plane wave of light is transformed into a Bessel beam. The team fabricated and tested two ‘meta-axicons’ designed for operation with blue and green light and found that the beams' intensity profiles were independent of wavelength.

Genome-scale metabolic models (GSMMs) are used to predict metabolic fluxes, with applications ranging from identifying novel drug targets to engineering microbial metabolism. Erroneous or missing reactions, scattered throughout densely interconnected networks, are a limiting factor in these applications. We present Metabolic Accuracy Check and Analysis Workflow (MACAW), a suite of algorithms that helps to identify and visualize errors at the level of connected pathways, rather than individual reactions. We show how MACAW highlights inaccuracies of varying severity in manually curated and automatically generated GSMMs for humans, yeast, and bacteria and helps to identify systematic issues to be addressed in future model construction efforts.

Metasurfaces as artificially nanostructured interfaces hold significant potential for multi-functionality, which may play a pivotal role in the next-generation compact nano-devices. The majority of multi-tasked metasurfaces encode or encrypt multi-information either into the carefully tailored metasurfaces or in pre-set complex incident beam arrays. Here, we propose and demonstrate a multi-momentum transformation metasurface (i.e., meta-transformer), by fully synergizing intrinsic properties of light, e.g., orbital angular momentum (OAM) and linear momentum (LM), with a fixed phase profile imparted by a metasurface. The OAM meta-transformer reconstructs different topologically charged beams into on-axis distinct patterns in the same plane. The LM meta-transformer converts red, green and blue illuminations to the on-axis images of “R”, “G” and “B” as well as vivid color holograms, respectively. Thanks to the infinite states of light-metasurface phase combinations, such ultra-compact meta-transformer has potential in information storage, nanophotonics, optical integration and optical encryption. Here, the authors demonstrate a multi-momentum transformation metasurface. The orbital angular momentum meta-transformer reconstructs different vortex beams into on-axis distinct patterns, and the linear momentum meta-transformer converts red, green and blue beams to vivid color images.

Fulvestrant is a selective estrogen receptor downregulator (SERD) and highly effective antagonist to hormone-sensitive breast cancers following failure of previous tamoxifen or aromatase inhibitor therapies. However, after prolonged fulvestrant therapy, acquired resistance eventually occurs in the majority of breast cancer patients, due to poorly understood mechanisms. To examine a possible role(s) of aberrantly expressed microRNAs (miRNAs) in acquired fulvestrant resistance, we compared antiestrogen-resistant and -sensitive breast cancer cells, revealing the overexpression of miR-221/222 in the SERD-resistant cell lines. Fulvestrant treatment of estradiol (E2)- and fulvestrant-sensitive MCF7 cells resulted in increased expression of endogenous miR-221/222. Ectopic upregulation of miR-221/222 in estrogen receptor-α (ERα)-positive cell lines counteracted the effects of E2 depletion or fulvestrant-induced cell death, thus also conferring hormone-independent growth and fulvestrant resistance. In cells with acquired resistance to fulvestrant, miR-221/222 expression was essential for cell growth and cell cycle progression. To identify possible miR-221/222 targets, miR-221- or miR-222- induced alterations in global gene expression profiles and target gene expression at distinct time points were determined, revealing that miR-221/222 overexpression resulted in deregulation of multiple oncogenic signaling pathways previously associated with drug resistance. Activation of β-catenin by miR-221/222 contributed to estrogen-independent growth and fulvestrant resistance, whereas TGF-β-mediated growth inhibition was repressed by the two miRNAs. This first in-depth investigation into the role of miR-221/222 in acquired fulvestrant resistance, a clinically important problem, demonstrates that these two ‘oncomirs’ may represent promising therapeutic targets for treating hormone-independent, SERD-resistant breast cancer.

Alfred Edwin Eaton (1844–1929) was amongst numerous Victorian naturalists whose exotic collections disseminated to the natural history museums of Britain laid the groundwork for our understanding of biodiversity. What sets him apart from his contemporaries was his first-hand knowledge of organisms at the polar extremes. This paper describes Eaton’s contributions to polar biology, especially in the field of entomology, from two high-latitude expeditions: the 1873 Benjamin Leigh Smith Expedition to Svalbard in the European Arctic and the 1874 British Transit of Venus Expedition to Kerguelen Island in the southern Indian Ocean. His observations of flightless polar and subpolar insects, in particular, lent support to the work of Challenger naturalist Henry Moseley and botanist Joseph Hooker on species dispersal in the Southern Ocean and on adaptations that arise in response to the unique selection pressures in harsh, isolated conditions.