Abstract
Intrinsically and fully stretchable active-matrix-driven displays are an important element to skin electronics that can be applied to many emerging fields, such as wearable electronics, ...consumer electronics and biomedical devices. Here, we show for the first time a fully stretchable active-matrix-driven organic light-emitting electrochemical cell array. Briefly, it is comprised of a stretchable light-emitting electrochemical cell array driven by a solution-processed, vertically integrated stretchable organic thin-film transistor active-matrix, which is enabled by the development of chemically-orthogonal and intrinsically stretchable dielectric materials. Our resulting active-matrix-driven organic light-emitting electrochemical cell array can be readily bent, twisted and stretched without affecting its device performance. When mounted on skin, the array can tolerate to repeated cycles at 30% strain. This work demonstrates the feasibility of skin-applicable displays and lays the foundation for further materials development.
Abstract
The mechanism that creates vitreous endosperm in the mature maize kernel is poorly understood. We identified
Vitreous endosperm 1
(
Ven1
) as a major QTL influencing this process.
Ven1
...encodes β-carotene hydroxylase 3, an enzyme that modulates carotenoid composition in the amyloplast envelope. The A619 inbred contains a nonfunctional
Ven1
allele, leading to a decrease in polar and an increase in non-polar carotenoids in the amyloplast. Coincidently, the stability of amyloplast membranes is increased during kernel desiccation. The lipid composition in endosperm cells in A619 is altered, giving rise to a persistent amyloplast envelope. These changes impede the gathering of protein bodies and prevent them from interacting with starch grains, creating air spaces that cause an opaque kernel phenotype. Genetic modifiers were identified that alter the effect of
Ven1
A619
, while maintaining a high β-carotene level. These studies provide insight for breeding vitreous kernel varieties and high vitamin A content in maize.
Assembly of 3D micro/nanostructures in advanced functional materials has important implications across broad areas of technology. Existing approaches are compatible, however, only with narrow classes ...of materials and/or 3D geometries. This paper introduces ideas for a form of Kirigami that allows precise, mechanically driven assembly of 3D mesostructures of diverse materials from 2D micro/nanomembranes with strategically designed geometries and patterns of cuts. Theoretical and experimental studies demonstrate applicability of the methods across length scales from macro to nano, in materials ranging from monocrystalline silicon to plastic, with levels of topographical complexity that significantly exceed those that can be achieved using other approaches. A broad set of examples includes 3D silicon mesostructures and hybrid nanomembrane–nanoribbon systems, including heterogeneous combinations with polymers and metals, with critical dimensions that range from 100 nm to 30 mm. A 3D mechanically tunable optical transmission window provides an application example of this Kirigami process, enabled by theoretically guided design.
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Maize (Zea mays) floury3 (fl3) is a classic semidominant negative mutant that exhibits severe defects in the endosperm but fl3 plants otherwise appear normal. We cloned the fl3 gene and determined ...that it encodes a PLATZ (plant AT-rich sequence and zinc binding) protein. The mutation in fl3 resulted in an Asn-to-His replacement in the conserved PLATZ domain, creating a dominant allele. Fl3 is specifically expressed in starchy endosperm cells and regulated by genomic imprinting, which leads to the suppressed expression of fl3 when transmitted through the male, perhaps as a consequence the semidominant behavior. Yeast two-hybrid screening and bimolecular luciferase complementation experiments revealed that FL3 interacts with the RNA polymerase III subunit 53 (RPC53) and transcription factor class C 1 (TFC1), two critical factors of the RNA polymerase III (RNAPIII) transcription complex. In the fl3 endosperm, the levels of many tRNAs and 5S rRNA that are transcribed by RNAPIII are significantly reduced, suggesting that the incorrectly folded fl3 protein may impair the function of RNAPIII. The transcriptome is dramatically altered in fl3 mutants, in which the downregulated genes are primarily enriched in pathways related to translation, ribosome, misfolded protein responses, and nutrient reservoir activity. Collectively, these changes may lead to defects in endosperm development and storage reserve filling in fl3 seeds.
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Circadian clocks participate in the coordination of various metabolic and biological activities to maintain homeostasis. Disturbances in the circadian rhythm and cancers are closely related. ...Circadian clock genes are differentially expressed in many tumors, and accelerate the development and progression of tumors. In addition, tumor tissues exert varying biological activities compared to normal tissues due to resetting of altered rhythms. Thus, chronotherapeutics used for cancer treatment should exploit the timing of circadian rhythms to achieve higher efficacy and mild toxicity. Due to interpatient differences in circadian functions, our findings advocate an individualized precision approach to chronotherapy. Herein, we review the specific association between circadian clocks and cancers. In addition, we focus on chronotherapies in cancers and personalized biomarkers for the development of precision chronotherapy. The understanding of circadian clocks in cancer will provide a rationale for more effective clinical treatment of tumors.
Sea-water-level (SWL) prediction significantly impacts human lives and maritime activities in coastal regions, particularly at offshore locations with shallow water levels. Long-term SWL forecasts, ...which are conventionally obtained via harmonic analysis, become ineffective when nonperiodic meteorological events predominate. Artificial intelligence combined with other data-processing methods can effectively forecast highly nonlinear and nonstationary inflow patterns by recognizing historical relationships between input and output. These techniques are considerably useful in time-series data predictions. This paper reports the development of a hybrid model to realize accurate multihour SWL forecasting by combining an adaptive neuro-fuzzy inference system (ANFIS) with wavelet decomposition while using sea-level anomaly (SLA) and wind-shear-velocity components as inputs. Numerous wavelet-ANFIS (WANFIS) models have been tested using different inputs to assess their applicability as alternatives to the artificial neural network (ANN), wavelet ANN (WANN), and ANFIS models. Different error definitions have been used to evaluate results, which indicate that integrated wavelet-decomposition and ANFIS models improve the accuracy of SWL prediction and that the inputs of SLA and wind-shear velocity exhibit superior prediction capability compared to conventional SWL-only models.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Storm surges pose significant danger and havoc to the coastal residents’ safety, property, and lives, particularly at offshore locations with shallow water levels. Predictions of storm surges with ...hours of warning time are important for evacuation measures in low-lying regions and coastal management plans. In addition to experienced predictions and numerical models, artificial intelligence (AI) techniques are also being used widely for short-term storm surge prediction owing to their merits in good level of prediction accuracy and rapid computations. Convolutional neural network (CNN) and long short-term memory (LSTM) are two of the most important models among AI techniques. However, they have been scarcely utilised for surge level (SL) forecasting, and combinations of the two models are even rarer. This study applied CNN and LSTM both individually and in combination towards multi-step ahead short-term storm surge level prediction using observed SL and wind information. The architectures of the CNN, LSTM, and two sequential techniques of combining the models (LSTM-CNN and CNN-LSTM) were constructed via a trial-and-error approach and knowledge obtained from previous studies. As a case study, 11 a of hourly observed SL and wind data of the Xiuying Station, Hainan Province, China, were organised as inputs for training to verify the feasibility and superiority of the proposed models. The results show that CNN and LSTM had evident advantages over support vector regression (SVR) and multilayer perceptron (MLP), and the combined models outperformed the individual models (CNN and LSTM), mostly by 4%–6%. However, on comparing the model computed predictions during two severe typhoons that resulted in extreme storm surges, the accuracy was found to improve by over 10% at all forecasting steps.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
PLATZ proteins are a novel class of plant-specific zinc-dependent DNA-binding proteins that are classified as transcription factors (TFs). However, their common biochemical features and functions are ...poorly understood.
Here, we identified and cloned 17 PLATZ genes in the maize (Zea mays) genome. All ZmPLATZs were located in nuclei, consistent with their predicted role as TFs. However, none of ZmPLATZs was found to have intrinsic activation properties in yeast. Our recent work shows that FL3 (ZmPLATZ12) interacts with RPC53 and TFC1, two critical factors in the RNA polymerase III (RNAPIII) transcription complex. Using the yeast two-hybrid assay, we determined that seven other PLATZs interacted with both RPC53 and TFC1, whereas three had no protein-protein interaction with these two factors. The other six PLATZs interacted with either RPC53 or TFC1. These findings indicate that ZmPLATZ proteins are generally involved in the modulation of RNAPIII-mediated small non-coding RNA transcription. We also identified all of the PLATZ members in rice (Oryza sativa) and Arabidopsis thaliana and constructed a Maximum likelihood phylogenetic tree for ZmPLATZs. The resulting tree included 44 members and 5 subfamilies.
This study provides insight into understanding of the phylogenetic relationship, protein structure, expression pattern and cellular localization of PLATZs in maize. We identified nine and thirteen ZmPLATZs that have protein-protein interaction with RPC53 and TFC1 in the current study, respectively. Overall, the characterization and functional analysis of the PLATZ family in maize will pave the way to understanding RNAPIII-mediated regulation in plant development.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Maize kernels are complex biological systems composed of three genetic sources, namely maternal tissues, progeny embryos, and progeny endosperms. The lack of gene expression profiles with spatial ...information has limited the understanding of the specific functions of each cell population, and hindered the exploration of superior genes in kernels. In our study, we conduct microscopic sectioning and spatial transcriptomics analysis during the grain filling stage of maize kernels. This enables us to visualize the expression patterns of all genes through electronical RNA in situ hybridization, and identify 11 cell populations and 332 molecular marker genes. Furthermore, we systematically elucidate the spatial storage mechanisms of the three major substances in maize kernels: starch, protein, and oil. These findings provide valuable insights into the functional genes that control agronomic traits in maize kernels.
Selecting thresholds to convert continuous predictions of species distribution models proves critical for many real‐world applications and model assessments. Prevalent threshold selection methods for ...presence‐only data require unproven pseudo‐absence data or subjective researchers' decisions. This study proposes a new method, Boyce‐Threshold Quantile Regression (BTQR), to determine thresholds objectively without pseudo‐absence data. We summarize that the mutation point is a typical shape feature of the predicted‐to‐expected (P/E) curve after reviewing relevant articles. Analysis based on source‐sink theory suggests that this mutation point may represent a transition in habitat types and serve as an appropriate threshold. Threshold regression is introduced to accurately locate the mutation point. To validate the effectiveness of BTQR, we used four virtual species of varying prevalence and a real species with reliable distribution data. Six different species distribution models were employed to generate continuous suitability predictions. BTQR and nine other traditional methods transformed these continuous outputs into binary results. Comparative experiments show that BTQR has advantages in terms of accuracy, applicability, and consistency over the existing methods.
This study proposes a new method named Boyce‐Threshold Quantile Regression (BTQR). The method uses threshold regression to locate the mutation point of Boyce's predicted‐to‐expected curve. Analysis based on source‐sink theory suggests that this mutation point may represent a transition in habitat types and serve as an appropriate threshold. Comparative research shows that BTQR has significant advantages in accuracy and stability over prevalent methods.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
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