Singapore-MIT Alliance
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Recent publications
New systems for agrochemical delivery in plants will foster precise agricultural practices and provide new tools to study plants and design crop traits, as standard spray methods suffer from elevated loss and limited access to remote plant tissues. Silk-based microneedles can circumvent these limitations by deploying a known amount of payloads directly in plants' deep tissues. However, plant response to microneedles' application and microneedles' efficacy in deploying physiologically relevant biomolecules are unknown. Here, we show that gene expression associated with Arabidopsis thaliana wounding response decreases within 24 hours post microneedles' application. Additionally, microinjection of gibberellic acid (GA3 ) in A. thaliana mutant ft-10 provides a more effective and efficient mean than spray to activate GA3 pathways, accelerating bolting, and inhibiting flower formation. Microneedles' efficacy in delivering GA3 is also observed in several monocot and dicot crop species, i.e., tomato (Solanum lycopersicum), lettuce (Lactuca sativa), spinach (Spinacia oleracea), rice (Oryza Sativa), maize (Zea mays), barley (Hordeum vulgare), and soybean (Glycine max). The wide range of plants that can be successfully targeted with microinjectors opens the doors to their use in plant science and agriculture. This article is protected by copyright. All rights reserved.
Organoids are simple tissue-engineered cell-based in vitro models that recapitulate many aspects of the complex structure and function of the corresponding in vivo tissue. They can be dissected and interrogated for fundamental mechanistic studies on development, regeneration and repair in human tissues, and can also be used in diagnostics, disease modelling, drug discovery and personalized medicine. Organoids are derived from either pluripotent or tissue-resident stem (embryonic or adult) or progenitor or differentiated cells from healthy or diseased tissues, such as tumours. To date, numerous organoid engineering strategies that support organoid culture and growth, proliferation, differentiation and maturation have been reported. This Primer highlights the rationale underlying the selection and development of these materials and methods to control the cellular/tissue niche; and therefore, the structure and function of the engineered organoid. We also discuss key considerations for generating robust organoids, such as those related to cell isolation and seeding, matrix and soluble factor selection, physical cues and integration. The general standards for data quality, reproducibility and deposition within the organoid community are also outlined. Lastly, we conclude by elaborating on the limitations of organoids in different applications, and the key priorities in organoid engineering for the coming years. Organoids are cell-based in vitro models derived from stem cells, reconstituting the complex structure and function of the corresponding tissue. In this Primer, Zhao, Chen, Dowbaj, Sljukic, Bratlie, Lin et al. discuss the development of organoids and methods for controlling their cellular environment.
Monitoring and managing the structural health of bridges requires expensive specialized sensor networks. In the past decade, researchers predicted that cheap ubiquitous mobile sensors would revolutionize infrastructure maintenance; yet extracting useful information in the field with sufficient precision remains challenging. Herein we report the accurate determination of critical physical properties, modal frequencies, of two real bridges from everyday vehicle trip data. We collected smartphone data from controlled field experiments and uncontrolled Uber rides on a long-span suspension bridge in the USA (The Golden Gate Bridge) and developed an analytical method to accurately recover modal properties. We also successfully applied the method to partially-controlled crowdsourced data collected on a short-span highway bridge in Italy. Further analysis projected that the inclusion of crowdsourced data in a maintenance plan for a new bridge could add over fourteen years of service (30% increase) without additional costs. Our results suggest that massive and inexpensive datasets collected by smartphones could play a role in monitoring the health of existing transportation infrastructure.
The core G protein-signaling module, namely Gα and extra-large Gα (XLG) subunits coupled with Gβγ dimer, is a master regulator of various stress responses. Here, two-species comparisons of basal and salt stress-induced transcriptomic, metabolomic and phenotypic profiles in Gα, Gβ and XLG-null mutants demonstrate that G protein mediates the shift of transcriptional and metabolic homeostasis to stress ready status. Such stress readiness serves as an intrinsic protection against further stressors by enhancing the phenylpropanoid pathway and ABA responses. WRKY transcription factors were identified as key intermediates of the G protein-mediated homeostatic shifts. Statistical and mathematical model comparisons between Arabidopsis thaliana and Marchantia polymorpha revealed evolutionary conservation of transcriptional and metabolic networks over land plant evolution, while divergence occurred in the function of the plant-specific atypical XLG subunit. Taken together, we propose the shifts of transcriptional and metabolic homeostasis as the mechanisms of G protein-coupled stress responses conserved between two distant plants.
This study is motivated by the desire to disseminate a low-cost, high-precision, high-throughput environmental chamber to test materials and devices under elevated humidity, temperature, and light. This paper documents the creation of an open-source tool with a bill of materials as low as US$2,000, and the subsequent evolution of three second-generation tools installed at three different universities spanning thin films, bulk crystals, and thin-film solar-cell devices. We introduce an optical proxy measurement to detect real-time phase changes in materials. We present correlations between this optical proxy and standard X-ray diffraction measurements, describe some edge cases where the proxy measurement fails, and report key learnings from the technology-translation process. By sharing lessons learned, we hope that future open-hardware development and translation efforts can proceed with reduced friction. Throughout the paper, we provide examples of scientific impact, wherein participating laboratories used their environmental chambers to study and improve the stabilities of halide-perovskite materials. All generations of hardware bills of materials, assembly instructions, and operating codes are available in open-source repositories.
This study is motivated by the desire to disseminate a low-cost, high-precision, high-throughput environmental chamber to test materials and devices under elevated humidity, temperature, and light. This paper documents the creation of an open-source tool with a bill of materials as low as US$2,000, and the subsequent evolution of three second-generation tools installed at three different universities spanning thin films, bulk crystals, and thin-film solar-cell devices. We introduce an optical proxy measurement to detect real-time phase changes in materials. We present correlations between this optical proxy and standard X-ray diffraction measurements, describe some edge cases where the proxy measurement fails, and report key learnings from the technology-translation process. By sharing lessons learned, we hope that future open-hardware development and translation efforts can proceed with reduced friction. Throughout the paper, we provide examples of scientific impact, wherein participating laboratories used their environmental chambers to study and improve the stabilities of halide-perovskite materials. All generations of hardware bills of materials, assembly instructions, and operating codes are available in open-source repositories.
Vaccination against SARS-CoV-2 induces protection through production of neutralization antibodies (nAb). The level of nAb is a major indicator of immunity against SARS-CoV-2 infection.
Needle-in-a-Haystack problems exist across a wide range of applications including rare disease prediction, ecological resource management, fraud detection, and material property optimization. A Needle-in-a-Haystack problem arises when there is an extreme imbalance of optimum conditions relative to the size of the dataset. For example, only 0.82% out of 146k total materials in the open-access Materials Project database have a negative Poisson's ratio. However, current state-of-the-art optimization algorithms are not designed with the capabilities to find solutions to these challenging multidimensional Needle-in-a-Haystack problems, resulting in slow convergence to a global optimum or pigeonholing into a local minimum. In this paper, we present a Zooming Memory-Based Initialization algorithm, entitled ZoMBI, that builds on conventional Bayesian optimization principles to quickly and efficiently optimize Needle-in-a-Haystack problems in both less time and fewer experiments by addressing the common convergence and pigeonholing issues. ZoMBI actively extracts knowledge from the previously best-performing evaluated experiments to iteratively zoom in the sampling search bounds towards the global optimum "needle" and then prunes the memory of low-performing historical experiments to accelerate compute times. We validate the algorithm's performance on two real-world 5-dimensional Needle-in-a-Haystack material property optimization datasets: discovery of auxetic Poisson's ratio materials and discovery of high thermoelectric figure of merit materials. The ZoMBI algorithm demonstrates compute time speed-ups of 400x compared to traditional Bayesian optimization as well as efficiently discovering materials in under 100 experiments that are up to 3x more highly optimized than those discovered by current state-of-the-art algorithms.
Background Elderly patients develop pressure ulcers that are very difficult to treat and current treatments have several limitations. Native skin stem cells diminish with age and may explain poor skin renewal in the elderly. Hence, an exogenous supply of stem cells to wounds in the elderly may produce a successful therapy. We evaluated the wound healing potential of an aloe vera-polycaprolactone nanocarrier impregnated with human Wharton’s jelly stem cells (hWJSCs + AV/PCL) or its conditioned medium (hWJSC-CM + AV/PCL) on elderly human skin using in vitro wound assays and on excisonal wounds created in an elderly preclinical mouse model. Methods hWJSCs and human skin fibroblasts (HSFs) were derived and characterized using our previously published protocols. The influence of hWJSC-CM on elderly human skin fibroblasts (eHSFs) were compared with that of young HSFs (yHSFs) and untreated eHSF controls. The healing of excisonal wounds created in elderly mice over a 21 day period was evaluated using various methods. Results Scratch wounds of hWJSC-CM-treated eHSFs completely closed by day 2 compared to untreated eHSF controls. Collagen and elastin levels were significantly increased while senescence-related genes were significantly downregulated in hWJSC-CM-treated eHSFs compared to untreated eHSFs. Angiogenesis assays produced significantly greater tubule numbers and ring formation in the presence of CM from hWJSC-CM-treated eHSFs. Excisional wounds in elderly mice treated with hWJSC + AV/PCL and hWJSC-CM + AV/PCL completely healed by day 21 and wound closure rates were significantly greater compared to controls. Histology of elderly mice wounds treated with hWJSC + AV/PCL and hWJSC-CM + AV/PCL showed changes in skin structure. Epidermal and dermal thickness, CD31 and gene expression levels of ECM, collagen, angiogenesis, scarless, granulation and immune cell chemoattraction were significantly greater in elderly mice treated with hWJSC + AV/PCL and hWJSC-CM + AV/PCL. Conclusions The results confirmed that hWJSCs in combination with the stem cell niches in nanoscaffolds and the antimicrobial properties of aloe vera provide an attractive wound dressing patch for treatment of chronic wounds in the elderly.
Lithium and sodium (Na) mixed polyanion solid electrolytes for all-solid-state batteries display some of the highest ionic conductivities reported to date. However, the effect of polyanion mixing on the ion-transport properties is still not fully understood. Here, we focus on Na1+xZr2SixP3−xO12 (0 ≤ x ≤ 3) NASICON electrolyte to elucidate the role of polyanion mixing on the Na-ion transport properties. Although NASICON is a widely investigated system, transport properties derived from experiments or theory vary by orders of magnitude. We use more than 2000 distinct ab initio-based kinetic Monte Carlo simulations to map the compositional space of NASICON over various time ranges, spatial resolutions and temperatures. Via electrochemical impedance spectroscopy measurements on samples with different sodium content, we find that the highest ionic conductivity (i.e., about 0.165 S cm–1 at 473 K) is experimentally achieved in Na3.4Zr2Si2.4P0.6O12, in line with simulations (i.e., about 0.170 S cm–1 at 473 K). The theoretical studies indicate that doped NASICON compounds (especially those with a silicon content x ≥ 2.4) can improve the Na-ion mobility compared to undoped NASICON compositions.
Transparent conductive oxides exhibit attractive optical nonlinearity with ultrafast response and giant refractive index change near the epsilon-near-zero (ENZ) wavelength, originating from the intraband dynamics of conduction electrons. The optical nonlinearity of ENZ materials has been explained by using the overall-effective-mass and the overall-scattering-time of electrons in the extended Drude model. However, their response to optical excitation is yet the last building block to complete the theory. In this paper, the concept of thermal energy is theoretically proposed to account for the total energy of conduction electrons exceeding their thermal equilibrium value. The time-varying thermal energy is adopted to describe the transient optical response of indium-tin-oxide (ITO), a typical ENZ material. A spectrally-resolved femtosecond pump-probe experiment was conducted to verify our theory. By correlating the thermal energy with the pumping density, both the giant change and the transient response of the permittivity of ITO can be predicted. The results in this work provide a new methodology to describe the transient permittivities of ENZ materials, which will benefit the design of ENZ-based nonlinear photonic devices.
Isoprenoids are a large family of natural products with diverse structures, which allow them to play diverse and important roles in the physiology of plants and animals. They also have important commercial uses as pharmaceuticals, flavouring agents, fragrances, and nutritional supplements. Recently, metabolic engineering has been intensively investigated and emerged as the technology of choice for the production of isoprenoids through microbial fermentation. Isoprenoid biosynthesis typically originates in plants from acetyl-coA in central carbon metabolism, however, a recent study reported an alternative pathway, the Isopentenol Utilization pathway (IUP), that can provide the building blocks of isoprenoid biosynthesis from affordable C5 substrates. In this work, we expressed the IUP in Escherichia coli to efficiently convert isopentenols into geranate, a valuable isoprenoid compound. We first established a geraniol-producing strain in E. coli that uses the IUP. Then, we extended the geraniol synthesis pathway to produce geranate through two oxidation reactions catalysed by two alcohol/aldehyde dehydrogenases from Castellaniella defragrans . The geranate titer was further increased by optimizing the expression of the two dehydrogenases and also parameters of the fermentation process. The best strain produced 764 mg/L geranate in 24 h from 2 g/L isopentenols (a mixture of isoprenol and prenol). We also investigated if the dehydrogenases could accept other isoprenoid alcohols as substrates.
The development of inexpensive batteries based on magnesium (Mg) chemistry will contribute remarkably toward developing high-energy-density storage systems that can be used worldwide. Significant challenges remain in developing practical Mg batteries, the chief of which is designing materials that can provide facile transport of Mg. In this review, we cover the experimental and theoretical methods that can be used to quantify Mg mobility in a variety of host frameworks, the specific transport quantities that each technique is designed to measure or calculate, and some practical examples of their applications. We then list the unique challenges faced by different experimental and computational techniques in probing Mg ion transport in materials. This review concludes with an outlook on the directions that the scientific community could soon pursue as we strive to construct a pragmatic Mg battery. Expected final online publication date for the Annual Review of Materials Research, Volume 52 is July 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
The immunostimulatory intracellular domains (ICDs) of chimaeric antigen receptors (CARs) are essential for converting antigen recognition into antitumoural function. Although there are many possible combinations of ICDs, almost all current CARs rely on combinations of CD3𝛇, CD28 and 4-1BB. Here we show that a barcoded library of 700,000 unique CD19-specific CARs with diverse ICDs cloned into lentiviral vectors and transduced into Jurkat T cells can be screened at high throughput via cell sorting and next-generation sequencing to optimize CAR signalling for antitumoural functions. By using this screening approach, we identified CARs with new ICD combinations that, compared with clinically available CARs, endowed human primary T cells with comparable tumour control in mice and with improved proliferation, persistence, exhaustion and cytotoxicity after tumour rechallenge in vitro. The screening strategy can be adapted to other disease models, cell types and selection conditions, and could be used to improve adoptive cell therapies and to expand their utility to new disease indications. Screening a large barcoded library of unique CD19-specific chimaeric antigen receptors with diverse intracellular domains allows for the discovery of receptors that elicit enhanced antitumoural functions.
When organic peat soils are sufficiently dry, they become flammable. In Southeast Asian peatlands, widespread deforestation and associated drainage create dry conditions that, when coupled with El Niño-driven drought, result in catastrophic fire events that release large amounts of carbon and deadly smoke to the atmosphere. While the effects of anthropogenic degradation on peat moisture and fire risk have been extensively demonstrated, climate change impacts to peat flammability are poorly understood. These impacts are likely to be mediated primarily through changes in soil moisture. Here, we used neural networks (trained on data from the NASA Soil Moisture Active Passive satellite) to model soil moisture as a function of climate, degradation, and location. The neural networks were forced with regional climate model projections for 1985-2005 and 2040-2060 climate under RCP8.5 forcing to predict changes in soil moisture. We find that reduced precipitation and increased evaporative demand will lead to median soil moisture decreases about half as strong as those observed during recent El Niño droughts in 2015 and 2019. Based on previous studies, such reductions may be expected to accelerate peat carbon emissions. Our results also suggest that soil moisture in degraded areas with less tree cover may be more sensitive to climate change than in other land use types, motivating urgent peatland restoration. Climate change may play an important role in future soil moisture regimes and by extension, future peat fire in Southeast Asian peatlands.
In this work, the metal-semiconductor-metal photodetectors were demonstrated on the Ge <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0.91</sub> Sn <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0.09</sub> -on-insulator (GeSnOI) platform. The responsivity was 0.24 and 0.06 A/W at wavelengths of 1,600 and 2,003 nm, respectively. Through a systematic study, it is revealed that the photodetectors can potentially detect wavelength beyond 2,200 nm. The dark current density was measured to be 4.6 A/cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> for GeSnOI waveguide-shaped photodetectors. The 3 dB bandwidth was observed to be 1.26 and 0.81 GHz at 1,550 and 2,000 nm wavelengths, respectively. This work opens up an opportunity for low-cost 2 µm wavelength photodetection on the GeSn/Ge interface-free GeSnOI platform.
With rapid ongoing urbanization, cities across the world face a multitude of challenges in urban logistics. Delivery of goods to retail districts is particularly challenging as these places are typically located in congested urban centers. In response, policy makers have explored various freight management initiatives, including urban consolidation centers (UCC) and off-hour deliveries (OHD). This study examines the impact of these initiatives on freight flows to a retail district in Singapore. The study approach pairs empirical behavioral models and an agent-based simulation. First, using results from a stated preference survey, the choice behavior of two relevant actors—establishments that ship goods and establishments that receive goods within a retail district—and their likelihood of participating in UCC or OHD are analyzed. Then, the resulting behavioral models are incorporated into a city-scale agent-based simulator to evaluate the impact of these initiatives on freight flows, tracking multiple logistics-related performance indicators. The results show that the likelihood of participating in UCC and OHD declines when multiple actors are involved in the participation decision. Both UCC and OHD have the potential to reduce freight traffic and parking demand, although in different ways. For UCC, a minimum level of participation must be achieved to guarantee increase in vehicle load factors. OHD decreases load factors as well as the required number of dedicated trips to the retail district.
*Note well: This is a preprint that has not yet been peer-reviewed.* We used neural networks (trained on data from the NASA SMAP satellite) to model soil moisture in peatlands of Sumatra, Borneo and Peninsular Malaysia as a function of climate, degradation, and location. The neural networks were forced with regional climate model projections for 1985-2005 and 2040-2060 climate under RCP8.5 forcing to predict changes in soil moisture. We find that reduced precipitation and increased evaporative demand will lead to median soil moisture decreases about half as strong as those observed during recent El Niño droughts. Such reductions may be expected to accelerate peat emissions. Our results also suggest that soil moisture in degraded areas with less tree cover may be more sensitive to climate change than in other land use types, motivating urgent peatland restoration. Climate change may play an important role in future soil moisture regimes and by extension, future peat fire in Southeast Asian peatlands.
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Andreas Luch
  • Product Safety and Alternatives to Animal Testing
Steven E. Kissel
  • Kavli Institute for Astrophysics and Space Research (MKI)
Andrew Weinert
  • Lincoln Laboratory
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