Drought priming at seedling stage improves photosynthetic performance and yield of potato exposed to a short-term drought stress.

Potato (Solanum tuberosum L.) is an important food and vegetable crop worldwide. In recent years, the arid environment resulting from climate change has caused a sharp decline in potato yield. To clarify the effect of drought priming at the seedling stage on the tolerance of potato plants to drought stress during tuber expansion, we conducted a pot experiment to investigate the physiological response of the plants generated from seed potatoes of the variety 'Favorita' to varied water supply conditions: normal water supply at the seedling stage (control), normal water supply at the seedling stage and drought stress at the mid-tuber-expansion stage (non-primed), and drought priming at the seedling stage plus drought stress at the mid-tuber-expansion stage (primed). Drought priming resulted in an increase in the number of small vascular bundles in potato plants compared to non-primed plants. It also altered the shape and density of stomata, enhancing water use efficiency and reducing whole-plant transpiration. The primed plants maintained the basal stem cambium for a longer time under drought stress, which gained an extended differentiation ability to generate a greater number of small vascular bundles compared to non-primed plants. Drought priming increased the amount and rate of dry matter translocation, and so reduced the adverse effects on tubers of potato under drought stress. Therefore, drought priming at the seedling stage improved the photosynthetic performance and yield, and probably enhanced the drought tolerance of potato.

Effects of exogenous trehalose on filling characteristics and sugar component content of wheat under high temperature stress during the filling period.

Taking the heat-sensitive wheat variety 'Fanmai 5' (FM5) and the heat-tolerant variety 'Huaimai 33' (HM33), which were screened out in the previous experiments, as experimental materials, we conducted a field experiment with passive heat-enhancing shelters to simulate post-flowering high-temperature environment (average temperature increase of 5.13 ℃) during 2021-2022. During the filling period, we analyzed the effects of exogenous trehalose (10, 15 and 20 mmol·L-1) on the filling characteristics and sugar fraction under high temperature, with no spraying at ordinary temperature as control (CK). The results showed that treating without spraying exogenous trehalose at high temperature (H) significantly reduced wheat grain yield and grain weight during the filling period, and spraying exogenous trehalose alleviated the reduction of grain yield and grain weight at the filling stage under high temperature stress. Compared with the H treatment, grain yield and grain weight of HM33 and FM5 wheat varie-ties increased by 3.5%, 6.7% and 4.2%, 5.4%, respectively. High temperature stress significantly increased the trehalose content and trehalase (THL) activity in flag leaves of both wheat varieties, and decreased the fructose and glucose contents. Spraying exogenous trehalose increased the contents of trehalose, fructose, and glucose in flag leaves, and decreased the trehalase activity in flag leaves compared with H treatment, which could improve the glucose metabolism capacity of wheat at filling stage. The increasing effect of FM5 was higher than that of HM33. High temperature stress significantly reduced starch content of flag leaves and grains, while spraying exogenous trehalose alleviated the decrease of starch content of flag leaves and grains under high temperature stress, which was profit able for the substance accumulation of wheat grains under high temperature stress. Under the conditions of this experiment, spraying 15 mmol·L-1 trehalose at flowering stage was the best treatment for the two wheat varieties.

Evolution Law of Concrete Interface Stress of Rigid-Frame Arch under Construction and Its Impact on Ultimate Load-Bearing Capacity.

To study the evolution of stress on the ring and segment interfaces during the construction process of the concrete encapsulation of the main arch ring in a rigid-frame arch bridge, alongside its impact on the ultimate load-bearing capacity of the main arch ring, a 1:10 scale model experiment was conducted by taking the 600 m Tian'e Longtan Bridge as the prototype. The key cross-section concrete strain data were collected during the entire construction process of the main arch ring via fiber-optic strain sensors, which were used to investigate the stress evolution at ring and segment interfaces. ANSYS APDL was employed to simulate the ultimate bearing capacity under various loading conditions of two different finite element models, which were, respectively, formed segmentally and by single pouring. The results revealed that (1) after the closure of the concrete encapsulation of the main arch ring, the concrete stress in the cross-section exhibits significant stress disparities. At the same cross-section, the level of the web concrete stress can reach 76% of the floor concrete stress, while the roof concrete stress level is less than 20% of the floor concrete stress. (2) At the junction of two adjacent work planes, there are considerable differences in the stress levels of the concrete on both sides. After the closure of the main arch ring, the intersegment stress ratios of the floor, web, and roof concrete are 60~70%, 40~60%, and 0~5%, respectively. (3) Loading conditions remarkably affected the ultimate bearing capacity of the main arch ring. Under mid-span loading and 1/4 span symmetrical loading conditions, compared to single-pour concrete encapsulation, the ultimate bearing capacity of the main arch ring with concrete encapsulated by segmented and ring-divided pouring decreased by 19.16% and 5.23%, respectively, compared to single-pour concrete encapsulation. This suggests that the non-uniformity of stress distribution in the concrete sheath can lead to reductions in the ultimate bearing capacity of the arch ring.

Low-temperature at booting reduces starch content and yield of wheat by affecting dry matter transportation and starch synthesis.

With the continuous change of global climate, the frequency of low-temperature stress (LTS) in spring increased greatly, which led to the increase of wheat yield decline. The effects of LTS at booting on grain starch synthesis and yield were examined in two wheat varieties with differing low-temperature sensitivities (insensitive variety Yannong 19 and sensitive variety Wanmai 52). A combination of potted and field planting was employed. For LTS treatment at booting, the wheat plants were placed in a climate chamber for 24 h at -2°C, 0°C or 2°C from 19:00 to 07:00 then 5°C from 07:00 to 19:00. They were then returned to the experimental field. The effects of flag leaf photosynthetic characteristics, the accumulation and distribution of photosynthetic products, enzyme activity related to starch synthesis and relative expression, the starch content, and grain yield were determined. LTS at booting caused a significant reduction in the net photosynthetic rate (Pn), stomatal conductance (Gs), and transpiration rate (Tr) of the flag leaves at filling. The development of starch grains in the endosperm is also hindere, there are obvious equatorial grooves observed on the surface of the A-type starch granules, and a reduction in the number of B-type starch granules. The abundance of 13C in the flag leaves and grains decreased significantly. LTS also caused a significant reduction in translocation amount of pre-anthesis stored dry matte from vegetative organs to grains and amount of post-anthesis transfer of accumulated dry matte into grains, and the distribution rate of dry matter in the grains at maturity. The grain filling time was shortened, and the grain filling rate decreased. A decrease in the activity and relative expression of enzymes related to starch synthesis was also observed, with a decrease in the total starch content. As a result, a decrease in the grain number per panicle and 1000-grain weight were also observed. These findings highlight the underlying physiological cause of decreased starch content and grain weight after LTS in wheat.

Low-cost high-speed rapidly reconfigurable integrated half-duplex optical transceiver front-end.

We present and demonstrate an integrated approach to make low-cost high-speed half-duplex optical transceiver with rapid reconfigurability. A single Distributed-Feedback (DFB) diode is employed as the unified E/O-O/E device, which is dynamically biased as laser or photodetector in transmitter or receiver mode. The bias for the DFB and the transmit/receive (T/R) signal path are provided by a custom-designed reconfigurable CMOS chip, which contains the biasing circuitry, a high-speed T/R switch and a burst-mode transimpedance amplifier (BM-TIA). The transceiver front-end operates up to 5 Gb/s for both transmitter (Tx) and receiver (Rx) mode experimentally, while its reconfiguration time is less than 131 ns. This integrated approach not only halves the transceiver optics to facilitate low cost, but also enables high-speed signal transmission as well as rapid reconfiguration, which will be critical for the fiber-to-everything paradigm shift in the near future.

Exogenous 6-benzylaminopurine enhances waterlogging and shading tolerance after anthesis by improving grain starch accumulation and grain filling.

Due to the frequent occurrence of extreme weather events, the area of wheat affected by continuous cloudy rainfall is increasing, with waterlogging becoming a major limiting factor of wheat yield. To alleviate the effect, spraying exogenous plant growth regulators is often used. In this study, two wheat cultivars, waterlogging-tolerant Yangmai 18 and waterlogging-sensitive Sumai 188, were selected for waterlogging and shading (WS) after anthesis for 7, 11, and 15 days respectively. Three concentrations of 6-benzylaminoadenine (6-BA) solution (15, 25, and 35 mg·L-1) were sprayed after WS treatment and water was sprayed as the control. Then, the effect of spraying 6-BA on photosynthetic characteristics, starch content, grain filling characteristics, and yield was explored under artificially stimulated continuous cloudy rainfall during anthesis. Compared with the control, the application of 6-BA caused a significant increase in grain plumpness throughout grain filling, as well as increases in the net photosynthetic rate (P n), stomatal conductance (G s), and transpiration rate (T r), and a significant decrease in the intercellular CO2 concentration (C i) of the flag leaves, all of which enhanced the photosynthetic capacity. The content of total starch, amylose, and amylopectin in the grains also increased significantly compared with the control. After WS for 15 days, the starch content increased by 3.81%-11.41% compared with the control. Spraying 6-BA also prolonged grain filling, increased the average grain filling rate, and significantly increased the 1000-grain weight and yield. The thousand-grain weight increased by 5.06%-43.28%, and wheat yield increased by 8.93%-64.27% after spraying 25 mg·L-1 of the 6-BA solution. These findings suggest that the application of 6-BA after WS stress could significantly improve the photosynthetic performance, which is propitious to the accumulation and transport of photosynthetic products after anthesis. Besides, spraying 6-BA can also increase the duration and rate of grain filling and starch accumulation content and improve grain weight, thereby alleviating the adverse effects of WS on wheat yield. Overall, spraying 25 mg·L-1 of the 6-BA solution had an optimal effect. These findings provide a theoretical basis for the exploration of cultivation techniques and measures aimed at alleviating damage caused by continuous rainfall during wheat anthesis.

Night warming at the vegetative stage improves pre-anthesis photosynthesis and plant productivity involved in grain yield of winter wheat.

We conducted pot experiments during the 2018-2020 growing seasons to study the effects of night warming at different growth stages of wheat on the photosynthetic performance; accumulation, transportation, and distribution of dry matter; and grain yield of winter wheat. Night warming at all the different growth stages resulted in an elevation of wheat yield by increasing the 1000-grain weight and the number of grains per ear. Night warming during the period from jointing to booting stage resulted in the greatest increase in wheat yield. It also increased the amount of overall dry matter and transferrable amount of dry matter in plants and increased the distribution of dry matter to grains to increase grain weight. Night warming treatments at three different growth stages enhanced pre-anthesis photosynthetic capacity by increasing flag leaf net photosynthetic rate, chlorophyll content, and photochemical efficiency of winter wheat at the early stage of grain filling, especially in the night warming treatment from jointing to booting stage. Night warming not only increased the stomatal density and stomatal index of wheat leaves but also increased stomatal conductance and transpiration rate in the early stage of grain filling, thus being conducive to the smooth progress of photosynthesis. In conclusion, night warming treatment at different growth stages increased the photosynthesis of flag leaves at the early stage of grain filling, and promoted the accumulation of dry matter in plants after anthesis, which was conducive to the grain yield of winter wheat.

Post-flowering Soil Waterlogging Curtails Grain Yield Formation by Restricting Assimilates Supplies to Developing Grains.

Soil waterlogging is among the major factors limiting the grain yield of winter wheat crops in many parts of the world, including the middle and lower reaches of the Yangtze River China. In a field study, we investigated the relationship between leaf physiology and grain development under a varying duration of post-flowering waterlogging. A winter wheat cultivar Ningmai 13 was exposed to soil waterlogging for 0 (W0), 3 (W3), 6 (W6), and 9 d (W9) at anthesis. Increasing waterlogging duration significantly reduced flag leaf SPAD (soil plant analysis development) values and net photosynthetic rate (Pn). There was a linear reduction in flag leaf Pn and SPAD as plant growth progressed under all treatments; however, the speed of damage was greater in the waterlogged leaves. For example, compared with their respective control (W0), flag leaves of W9 treatment have experienced 46% more reduction in Pn at 21 d after anthesis (DAA) than at 7 DAA. Increasing waterlogging duration also induced oxidative damage in flag leaves, measured as malondialdehyde (MDA) contents. The capacity to overcome this oxidative damage was limited by the poor performance of antioxidant enzymes in wheat leaves. Inhibited leaf Pn and capacity to sustain assimilate synthesis under waterlogged environments reduced grain development. Compared with W0, W6 and W9 plants experienced a 20 and 22% reduction in thousand grain weight (TGW) in response to W6 and W9, respectively at 7 DAA and 11 and 19%, respectively at 28 DAA. Sustained waterlogging also significantly reduced grain number per spike and final grain yield. Averaged across two years of study, W9 plants produced 28% lesser final grain yield than W0 plants. Our study suggested that wheat crops are highly sensitive to soil waterlogging during reproductive and grain filling phases due to their poor capacity to recover from oxidative injury to photosynthesis. Management strategies such as planting time, fertilization and genotype selection should be considered for the areas experiencing frequent waterlogging problems.

Geometry-Aware Hierarchical Bayesian Learning on Manifolds.

Bayesian learning with Gaussian processes demonstrates encouraging regression and classification performances in solving computer vision tasks. However, Bayesian methods on 3D manifold-valued vision data, such as meshes and point clouds, are seldom studied. One of the primary challenges is how to effectively and efficiently aggregate geometric features from the irregular inputs. In this paper, we propose a hierarchical Bayesian learning model to address this challenge. We initially introduce a kernel with the properties of geometry-awareness and intra-kernel convolution. This enables geometrically reasonable inferences on manifolds without using any specific hand-crafted feature descriptors. Then, we use a Gaussian process regression to organize the inputs and finally implement a hierarchical Bayesian network for the feature aggregation. Furthermore, we incorporate the feature learning of neural networks with the feature aggregation of Bayesian models to investigate the feasibility of jointly learning on manifolds. Experimental results not only show that our method outperforms existing Bayesian methods on manifolds but also demonstrate the prospect of coupling neural networks with Bayesian networks.

Night-Warming Priming at the Vegetative Stage Alleviates Damage to the Flag Leaf Caused by Post-anthesis Warming in Winter Wheat (Triticum aestivum L.).

The asymmetric warming in diurnal and seasonal temperature patterns plays an important role in crop distribution and productivity. Asymmetric warming during the early growth periods of winter wheat profoundly affects its vegetative growth and post-anthesis grain productivity. Field experiments were conducted on winter wheat to explore the impact of night warming treatment in winter (Winter warming treatment, WT) or spring (Spring warming treatment, ST) on the senescence of flag leaves and yield of wheat plants later treated with night warming during grain filling (Warming treatment during grain filling, FT). The results showed that FT decreased wheat yield by reducing the number of grains per panicle and per 1,000-grain weight and that the yield of wheat plants treated with FT declined to a greater extent than that of wheat plants treated with WT + FT or ST + FT. The net photosynthetic rate, chlorophyll content, and chlorophyll fluorescence parameters of the flag leaves of wheat plants treated with WT + FT or ST + FT were higher than those under the control treatment from 0 to 7 days after anthesis (DAA) but were lower than those under the control treatment and higher than those of wheat plants treated with FT alone from 14 to 28 DAA. The soluble protein and Rubisco contents in the flag leaves of wheat plants treated with WT + FT or ST + FT were high in the early grain-filling period and then gradually decreased to below those of the control treatment. These contents were greater in wheat plants treated with WT + FT than in wheat plants treated with ST + FT from 0 to 14 DAA, whereas the opposite was true from 21 to 28 DAA. Furthermore, WT + FT and ST + FT inhibited membrane lipid peroxidation by increasing superoxide dismutase and peroxidase activities and lowering phospholipase D (PLD), phosphatidic acid (PA), lipoxygenase (LOX), and free fatty acid levels in the early grain-filling period, but their inhibitory effects on membrane lipid peroxidation gradually weakened during the late grain-filling period. Night-warming priming alleviated the adverse effect of post-anthesis warming on yield by delaying the post-anthesis senescence of flag leaves.

Tetrahedral spectral feature-Based bayesian manifold learning for grey matter morphometry: Findings from the Alzheimer's disease neuroimaging initiative.

Structural and anatomical analyses of magnetic resonance imaging (MRI) data often require a reconstruction of the three-dimensional anatomy to a statistical shape model. Our prior work demonstrated the usefulness of tetrahedral spectral features for grey matter morphometry. However, most of the current methods provide a large number of descriptive shape features, but lack an unsupervised scheme to automatically extract a concise set of features with clear biological interpretations and that also carries strong statistical power. Here we introduce a new tetrahedral spectral feature-based Bayesian manifold learning framework for effective statistical analysis of grey matter morphology. We start by solving the technical issue of generating tetrahedral meshes which preserve the details of the grey matter geometry. We then derive explicit weak-form tetrahedral discretizations of the Hamiltonian operator (HO) and the Laplace-Beltrami operator (LBO). Next, the Schrödinger's equation is solved for constructing the scale-invariant wave kernel signature (SIWKS) as the shape descriptor. By solving the heat equation and utilizing the SIWKS, we design a morphometric Gaussian process (M-GP) regression framework and an active learning strategy to select landmarks as concrete shape descriptors. We evaluate the proposed system on publicly available data from the Alzheimers Disease Neuroimaging Initiative (ADNI), using subjects structural MRI covering the range from cognitively unimpaired (CU) to full blown Alzheimer's disease (AD). Our analyses suggest that the SIWKS and M-GP compare favorably with seven other baseline algorithms to obtain grey matter morphometry-based diagnoses. Our work may inspire more tetrahedral spectral feature-based Bayesian learning research in medical image analysis.

The Effects of Short-Term Exposure to Low Temperatures During the Booting Stage on Starch Synthesis and Yields in Wheat Grain.

Low temperatures (LT) in spring can have a major impact on the yields of wheat in winter. Wheat varieties with different cold sensitivities (the cold-tolerant Yannong 19 variety and the cold-sensitive Yangmai 18 variety) were used to study the responses of the wheat grain starch synthesis and dry material accumulation to short-term LT during the booting stage. The effects of short-term LT on the activities of key wheat grain starch synthesis enzymes, starch content and grain dry-matter accumulation were determined by exposing the wheat to simulated LT of from -2 to 2°C. Short-term LT stress caused a decrease in the fullness of the wheat grains along with decreased activities of adenosine diphosphate glucose pyrophosphorylase (AGPase, EC2.7.7.27), soluble starch synthase (SSS, EC2.4.1.21), granule-bound starch synthase (GBSS, EC2.4.1.21), and starch branching enzyme (SBE, EC2.4.1.18) at different spike positions during the filling stage. The rate of grain starch accumulation and starch content decreased with decreasing temperatures. Also, the duration of grain filling increased, the mean and the maximum filling rates were reduced and the quality of the grain dry-matter decreased. The number of grains per spike and the thousand-grain weight of the mature grains also decreased. Our data showed that short-term LT stress at the booting stage caused a decrease in the activities of key starch synthesis enzymes at the grain-filling stage. These changes reduced the accumulation of starch, decreased the filling rate, and lowered the accumulation of grain dry matter to ultimately decrease grain yields.

Computing Univariate Neurodegenerative Biomarkers with Volumetric Optimal Transportation: A Pilot Study.

Changes in cognitive performance due to neurodegenerative diseases such as Alzheimer's disease (AD) are closely correlated to the brain structure alteration. A univariate and personalized neurodegenerative biomarker with strong statistical power based on magnetic resonance imaging (MRI) will benefit clinical diagnosis and prognosis of neurodegenerative diseases. However, few biomarkers of this type have been developed, especially those that are robust to image noise and applicable to clinical analyses. In this paper, we introduce a variational framework to compute optimal transportation (OT) on brain structural MRI volumes and develop a univariate neuroimaging index based on OT to quantify neurodegenerative alterations. Specifically, we compute the OT from each image to a template and measure the Wasserstein distance between them. The obtained Wasserstein distance, Wasserstein Index (WI) for short to specify the distance to a template, is concise, informative and robust to random noise. Comparing to the popular linear programming-based OT computation method, our framework makes use of Newton's method, which makes it possible to compute WI in large-scale datasets. Experimental results, on 314 subjects (140 Aß + AD and 174 Aß- normal controls) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) baseline dataset, provide preliminary evidence that the proposed WI is correlated with a clinical cognitive measure (the Mini-Mental State Examination (MMSE) score), and it is able to identify group difference and achieve a good classification accuracy, outperforming two other popular univariate indices including hippocampal volume and entorhinal cortex thickness. The current pilot work suggests the application of WI as a potential univariate neurodegenerative biomarker.

Cortical thickness computation by solving tetrahedron-based harmonic field.

Cortical thickness computation in magnetic resonance imaging (MRI) is an important method to study the brain morphological changes induced by neurodegenerative diseases. This paper presents an algorithm of thickness measurement based on a volumetric Laplacian operator (VLO), which is able to capture accurately the geometric information of brain images. The proposed algorithm is a novel three-step method: 1) The rule of parity and the shrinkage strategy are combined to detect and fix the intersection error regions between the cortical surface meshes separated by FreeSurfer software and the tetrahedral mesh is constructed which reflects the original morphological features of the cerebral cortex, 2) VLO and finite element method are combined to compute the temperature distribution in the cerebral cortex under the Dirichlet boundary conditions, and 3) the thermal gradient line is determined based on the constructed local isothermal surfaces and linear geometric interpolation results. Combined with half-face data storage structure, the cortical thickness can be computed accurately and effectively from the length of each gradient line. With the obtained thickness, we set experiments to study the group differences among groups of Alzheimer's disease (AD, N = 110), mild cognitive impairment (MCI, N = 101) and healthy control people (CTL, N = 128) by statistical analysis. The results show that the q-value associated with the group differences is 0.0458 between AD and CTL, 0.0371 between MCI and CTL, and 0.0044 between AD and MCI. Practical tests demonstrate that the algorithm of thickness measurement has high efficiency and is generic to be applied to various biological structures that have internal and external surfaces.

Convolutional Bayesian Models for Anatomical Landmarking on Multi-Dimensional Shapes.

The anatomical landmarking on statistical shape models is widely used in structural and morphometric analyses. The current study focuses on leveraging geometric features to realize an automatic and reliable landmarking. The existing implementations usually rely on classical geometric features and data-driven learning methods. However, such designs often have limitations to specific shape types. Additionally, calculating the features as a standalone step increases the computational cost. In this paper, we propose a convolutional Bayesian model for anatomical landmarking on multi-dimensional shapes. The main idea is to embed the convolutional filtering in a stationary kernel so that the geometric features are efficiently captured and implicitly encoded into the prior knowledge of a Gaussian process. In this way, the posterior inference is geometrically meaningful without entangling with extra features. By using a Gaussian process regression framework and the active learning strategy, our method is flexible and efficient in extracting arbitrary numbers of landmarks. We demonstrate extensive applications on various publicly available datasets, including one brain imaging cohort and three skeletal anatomy datasets. Both the visual and numerical evaluations verify the effectiveness of our method in extracting significant landmarks.

Morphometric Gaussian Process for Landmarking on Grey Matter Tetrahedral Models.

High-dimensional manifold modeling increases the precision and performance of cortical morphometry analysis by densely sampling on the grey matters. But this also brings redundant information and increased computational burden. Gaussian process regression has been used to tackle this problem by learning a mapping to a low-dimensional subspace. However, current methods may not take relevant morphometric properties, usually measured by geometric features, into account, and as a result, may generate morphometrically insignificant selections. In this paper, we propose a morphometric Gaussian process (M-GP) as a novel Bayesian model on the gray matter tetrahedral meshes. We also implement an M-GP regression landmarking algorithm as a manifold learning method for non-linear dimensionality reduction. The definition of M-GP involves a scale-invariant wave kernel signature distance map measuring the local similarities of geometric features, and a heat flow entropy which implicitly embeds the global curvature flow. With such a design, the prior knowledge fully encodes the geometric information so that a posterior predictive inference is morphometrically significant. In experiments, we use 518 grey matter tetrahedral meshes generated from structural magnetic resonance images of a publicly available Alzheimer's disease imaging cohort to empirically and numerically evaluate our method. The results verify that our method is theoretically and experimentally valid in selecting a representative subset from the original massive data. Our work may benefit any studies involving large-scale or iterative computations on extensive manifold-valued data, including morphometry analyses and general medical data processing.

Long noncoding RNA Neat1 modulates myogenesis by recruiting Ezh2.

Neat1 is widely expressed in many tissues and cells and exerts pro-proliferation effects on many cancer cells. However, little is known about the function of Neat1 in myogenesis. Here we characterized the roles of Neat1 in muscle cell formation and muscle regeneration. Gain- or loss-of-function studies in C2C12 cells demonstrated that Neat1 accelerates myoblast proliferation but suppresses myoblast differentiation and fusion. Further, knockdown of Neat1 in vivo increased the cross-sectional area of muscle fibers but impaired muscle regeneration. Mechanically, Neat1 physically interacted with Ezh2 mainly through the core binding region (1001-1540 bp) and recruited Ezh2 to target gene promoters. Neat1 promoted myoblast proliferation mainly by decreasing the expression of the cyclin-dependent kinase inhibitor P21 gene but inhibited myoblast differentiation by suppressing the transcription of myogenic marker genes, such as Myog, Myh4, and Tnni2. Altogether, we uncover a previously unknown function of Neat1 in muscle development and the molecular mechanism by which Neat1 regulates myogenesis.

Effects of Low Temperature at Booting Stage on Sucrose Metabolism and Endogenous Hormone Contents in Winter Wheat Spikelet.

Low spring temperatures often occur during the winter wheat booting stage, when the young ears are very sensitive to cold. In this study, we used two wheat varieties differing in cold sensitivity (sensitive variety Yangmai 18 and tolerant variety Yannong 19) to examine the effect of low temperature on wheat grain number at booting stage. Low temperature stress was simulated in an artificial climate chamber at 4°C for 60 h in 2016 and at 2, 0, or -2°C for 24 h in morphological assays, showing that the development of wheat spikelets was inhibited and floret growth was delayed following low temperature stress. However, an increase in the sucrose content of young panicles was also observed, and the activity of enzymes involved in sucrose metabolism was dynamically altered. Sucrose phosphate synthase activity was enhanced, and sucrose synthase activity significantly increased after treatment at 4 and 2°C, respectively. However, activities of sucrose synthase and invertase decreased with a reduction in temperature. Gene expression assays further revealed downregulation of TaSuS1 expression and upregulation of TaSuS2, while expression of CWINV was inhibited. Moreover, phytohormone content assays showed an increase in the content of abscisic acid in young wheat ears, but a decrease in the content of auxin and gibberellins. The grain number per spike and 1000-grain weight also showed a downward trend following low temperature stress. Overall, these findings suggest that low temperature at booting induces abscisic acid accumulation in winter wheat, altering the activity of the enzymes involved in sucrose metabolism, which leads to an accumulation of sucrose in the young ears, thereby having a negative effect on wheat production.

A Tetrahedron-based Heat Flux Signature for Cortical Thickness Morphometry Analysis.

Cortical thickness analysis of brain magnetic resonance images is an important technique in neuroimaging research. There are two main computational paradigms, namely voxel-based and surface-based methods. Recently, a tetrahedron-based volumetric morphometry (TBVM) approach involving proper discretization methods was proposed. The multi-scale and physics-based geometric features generated through such methods may yield stronger statistical power. However, several challenges, such as the lack of well-defined thickness statistics and the difficulty in filling tetrahedrons into the thin and curvy cortex structure, impede the broad application of TBVM. In this paper, we present a universal cortical thickness morphometry analysis approach called tetrahedron-based Heat Flux Signature (tHFS) to address these challenges. We define the tetrahedron-based weak form heat equation and Laplace-Beltrami eigen decomposition and give an explicit FEM-based discretization formulation to compute the tHFS. We further show a tHFS metric space with which cortical morphometric distances can be directly visualized. Additionally, we optimize the cortical tetrahedral mesh generation pipeline and fill dense high-quality tetrahedra in the grey matters without sacrificing data integrity. Compared with existing cortical thickness analysis approaches, our experimental results of distinguishing among Alzheimer's disease (AD), cognitively normal (CN) and mild cognitive impairment (MCI) subjects shows that tHFS yields a more accurate representation of cortical thickness morphometry. The tHFS metric experiment provides a more vivid visualization of tHFS's power in separating different clinical groups.

Heat Priming During Early Reproductive Stages Enhances Thermo-Tolerance to Post-anthesis Heat Stress via Improving Photosynthesis and Plant Productivity in Winter Wheat (Triticum aestivum L.).

Heat stress during grain filling substantially decreases wheat productivity; thus, to ensure food security, heat tolerance in wheat needs to be developed. In this study, we evaluated the effect of heat priming applied during the stem-elongation stage, booting and anthesis, followed by 5 days of severe heat stress (a 7.86°C rise in temperature) during the grain-filling stage on physiological activities and grain yield of winter wheat in pot experiments during the 2015-2017 growing seasons using the winter wheat cultivars Yangmai 18 (a vernal type) and Yannong 19 (a facultative type). Compared with the damage observed in non-primed plants, heat priming during the stem-elongation stage and booting significantly prevented the grain-yield damage caused by heat stress during grain filling. Heat-primed plants displayed higher sucrose contents and sucrose-phosphate activity in leaves and greater above-ground dry matter than non-primed plants. Priming during stem elongation and booting led to increased photosynthetic capacity, stomatal conductance and chlorophyll contents in comparison with non-priming. Improved tolerance to heat stress due to the enhanced activities of antioxidant enzymes superoxide dismutase and peroxidase and reductions in reactive oxygen species and malondialdehyde production was observed in primed plants compared with non-primed plants of both cultivars. The positive effect of heat priming on the response to heat stress during grain filling was more pronounced in plants primed at the booting stage than in those primed at the stem-elongation or anthesis stage. Moreover, the vernal-type Yangmai 18 benefited more from heat priming than did Yannong 19, as evidenced by its higher productivity. We conclude that heat priming during early reproductive-stage growth can improve post-anthesis heat tolerance in winter wheat.