Discovery of SOD5 as a novel regulator of nitrogen-use efficiency and grain yield via altering auxin level.

Auxin has emerged as a crucial regulator of plant nitrogen (N)-use efficiency (NUE) through indirect effects on plant growth and development and direct regulation of N metabolism-related genes. We previously reported DULL NITROGEN RESPONSE1 (DNR1) as an amino transferase that inhibits auxin accumulation and negatively regulates rice (Oryza sativa) NUE and grain yield. However, the identities of molecular regulators acting upstream of DNR1 await exploration.

Standard plane localization using denoising diffusion model with multi-scale guidance.

Background And Objective: Standard planes (SPs) acquisition is a fundamental yet crucial step in routine ultrasound (US) examinations. Compared to the 2D US, 3D US offers the advantage of capturing multiple SPs in a single scan, and visualizing particular SPs (e.g.

Natural variation of OsWRKY23 drives difference in nitrate use efficiency between indica and japonica rice.

Between the two major rice subspecies, indica varieties generally exhibit higher nitrate (NO) uptake and nitrogen (N)-use efficiency (NUE) than japonica varieties. Introducing efficient NO utilization alleles from indica into japonica could improve NUE, and at the same time uncover unknown regulators of NO metabolism. Here, we identify OsWRKY23 as a key regulator of NO uptake and NUE differences between indica and japonica rice.

Symmetric deformable registration of multimodal brain magnetic resonance images via appearance residuals.

Background And Objective: Deformable registration of multimodal brain magnetic resonance images presents significant challenges, primarily due to substantial structural variations between subjects and pronounced differences in appearance across imaging modalities.

Methods: Here, we propose to symmetrically register images from two modalities based on appearance residuals from one modality to another. Computed with simple subtraction between modalities, the appearance residuals enhance structural details and form a common representation for simplifying multimodal deformable registration.

Giant Piezoelectric Coefficient of Polyvinylidene Fluoride with Rationally Engineered Ultrafine Domains Achieved by Rapid Freezing Processing.

Domains play an essential role in determining the piezoelectric properties of polymers. The conventional method for achieving ultrafine piezoelectric domain structures for polymers is multiphase polymerization, which is not the primary choice for industrial-scale applications because of its complex synthesis and weak mechanical properties. In this study, it is demonstrated for the first time that a nanoscale domain design can be achieved in a commercially available polyvinylidene fluoride (PVDF) homopolymer through a simple fabrication method involving cyclic compression and rapid freezing.

Function of hormone signaling in regulating nitrogen-use efficiency in plants.

Nitrogen (N) is one of the most important nutrients for crop plant performance, however, the excessive application of nitrogenous fertilizers in agriculture significantly increases production costs and causes severe environmental problems. Therefore, comprehensively understanding the molecular mechanisms of N-use efficiency (NUE) with the aim of developing new crop varieties that combine high yields with improved NUE is an urgent goal for achieving more sustainable agriculture. Plant NUE is a complex trait that is affected by multiple factors, of which hormones are known to play pivotal roles.

An open relaxation-diffusion MRI dataset in neurosurgical studies.

Diffusion MRI (dMRI) is a safe and noninvasive technique that provides insight into the microarchitecture of brain tissue. Relaxation-diffusion MRI (rdMRI) is an extension of traditional dMRI that captures diffusion imaging data at multiple TEs to detect tissue heterogeneity between relaxation and diffusivity. rdMRI has great potential in neurosurgical research including brain tumor grading and treatment response evaluation.

Self-poled piezoelectric polymer composites via melt-state energy implantation.

Lightweight flexible piezoelectric polymers are demanded for various applications. However, the low instinctively piezoelectric coefficient (i.e.

Corrigendum: Alterations via inter-regional connective relationships in Alzheimer's disease.

[This corrects the article DOI: 10.3389/fnhum.2023.

Prediction of preoperative microvascular invasion by dynamic radiomic analysis based on contrast-enhanced computed tomography.

Purpose: Microvascular invasion (MVI) is a common complication of hepatocellular carcinoma (HCC) surgery, which is an important predictor of reduced surgical prognosis. This study aimed to develop a fully automated diagnostic model to predict pre-surgical MVI based on four-phase dynamic CT images.

Methods: A total of 140 patients with HCC from two centers were retrospectively included (training set, n = 98; testing set, n = 42).

Synthesis-based imaging-differentiation representation learning for multi-sequence 3D/4D MRI.

Multi-sequence MRIs can be necessary for reliable diagnosis in clinical practice due to the complimentary information within sequences. However, redundant information exists across sequences, which interferes with mining efficient representations by learning-based models. To handle various clinical scenarios, we propose a sequence-to-sequence generation framework (Seq2Seq) for imaging-differentiation representation learning.

Alterations via inter-regional connective relationships in Alzheimer's disease.

Disruptions in the inter-regional connective correlation within the brain are believed to contribute to memory impairment. To detect these corresponding correlation networks in Alzheimer's disease (AD), we conducted three types of inter-regional correlation analysis, including structural covariance, functional connectivity and group-level independent component analysis (group-ICA). The analyzed data were obtained from the Alzheimer's Disease Neuroimaging Initiative, comprising 52 cognitively normal (CN) participants without subjective memory concerns, 52 individuals with late mild cognitive impairment (LMCI) and 52 patients with AD.

Improving rice nitrogen-use efficiency by modulating a novel monouniquitination machinery for optimal root plasticity response to nitrogen.

Plant nitrogen (N)-use efficiency (NUE) is largely determined by the ability of root to take up external N sources, whose availability and distribution in turn trigger the modification of root system architecture (RSA) for N foraging. Therefore, improving N-responsive reshaping of RSA for optimal N absorption is a major target for developing crops with high NUE. In this study, we identified RNR10 (REGULATOR OF N-RESPONSIVE RSA ON CHROMOSOME 10) as the causal gene that underlies the significantly different root developmental plasticity in response to changes in N level exhibited by the indica (Xian) and japonica (Geng) subspecies of rice.

Longitudinal Prediction of Postnatal Brain Magnetic Resonance Images via a Metamorphic Generative Adversarial Network.

Missing scans are inevitable in longitudinal studies due to either subject dropouts or failed scans. In this paper, we propose a deep learning framework to predict missing scans from acquired scans, catering to longitudinal infant studies. Prediction of infant brain MRI is challenging owing to the rapid contrast and structural changes particularly during the first year of life.

Learn2Reg: Comprehensive Multi-Task Medical Image Registration Challenge, Dataset and Evaluation in the Era of Deep Learning.

Image registration is a fundamental medical image analysis task, and a wide variety of approaches have been proposed. However, only a few studies have comprehensively compared medical image registration approaches on a wide range of clinically relevant tasks. This limits the development of registration methods, the adoption of research advances into practice, and a fair benchmark across competing approaches.

Dietary Patterns and Nutrient Intake in University Students of Macao: A Cross-Sectional Study.

Background: Nutritional status affects the health of the public and is one of the key factors influencing social-economic development. To date, little research on the nutritional status of the Macao university student population has been conducted.

Objectives: To identify and evaluate the dietary pattern and the nutritional intake among Macao university students.

Weakly Supervised MR-TRUS Image Synthesis for Brachytherapy of Prostate Cancer.

Prostate magnetic resonance imaging (MRI) offers accurate details of structures and tumors for prostate cancer brachytherapy. However, it is unsuitable for routine treatment since MR images differ significantly from trans-rectal ultrasound (TRUS) images conventionally used for radioactive seed implants in brachytherapy. TRUS imaging is fast, convenient, and widely available in the operation room but is known for its low soft-tissue contrast and tumor visualization capability in the prostate area.

Fabrication of triboelectric polymer films via repeated rheological forging for ultrahigh surface charge density.

Triboelectric polymer with high charge density is the foundation to promote the wide range of applications of triboelectric nanogenerators. This work develops a method to produce triboelectric polymer based on repeated rheological forging. The fluorinated ethylene propylene film fabricated by repeated forging method not only has excellent mechanical properties and good transmittance, but also can maintain an ultrahigh tribo-charge density.

Modified Dynamic Movement Primitives: Robot Trajectory Planning and Force Control Under Curved Surface Constraints.

Dynamic movement primitives (DMPs) have been widely applied in robot motion planning and control. However, in some special cases, original discrete DMP fails to generalize proper trajectories. Moreover, it is difficult to produce trajectories on the curved surface.

Using a Convolutional Neural Network and Convolutional Long Short-term Memory to Automatically Detect Aneurysms on 2D Digital Subtraction Angiography Images: Framework Development and Validation.

Background: It is hard to distinguish cerebral aneurysms from overlapping vessels in 2D digital subtraction angiography (DSA) images due to these images' lack of spatial information.

Objective: The aims of this study were to (1) construct a deep learning diagnostic system to improve the ability to detect posterior communicating artery aneurysms on 2D DSA images and (2) validate the efficiency of the deep learning diagnostic system in 2D DSA aneurysm detection.

Methods: We proposed a 2-stage detection system.

Recurrent Tissue-Aware Network for Deformable Registration of Infant Brain MR Images.

Deformable registration is fundamental to longitudinal and population-based image analyses. However, it is challenging to precisely align longitudinal infant brain MR images of the same subject, as well as cross-sectional infant brain MR images of different subjects, due to fast brain development during infancy. In this paper, we propose a recurrently usable deep neural network for the registration of infant brain MR images.

Genetic improvement of nitrogen use efficiency in crops.

Nitrogen (N) is an essential mineral nutrient for plant growth and development. N deficiency is the major factor limiting plant growth and crop production in most natural and agricultural soils. The green revolution of the 1960's boosted crop yields through cultivation of semi-dwarf plant varieties.

Difficulty-aware hierarchical convolutional neural networks for deformable registration of brain MR images.

The aim of deformable brain image registration is to align anatomical structures, which can potentially vary with large and complex deformations. Anatomical structures vary in size and shape, requiring the registration algorithm to estimate deformation fields at various degrees of complexity. Here, we present a difficulty-aware model based on an attention mechanism to automatically identify hard-to-register regions, allowing better estimation of large complex deformations.

Y-chromosome evidence confirmed the Kerei-Abakh origin of Aksay Kazakhs.

Aksay Kazakhs are the easternmost branch of Kazakhs, residing in Jiuquan city, the forefront of the ancient Silk Road. However, the genetic diversity of Aksay Kazakhs and its relationships with other Kazakhs still lack attention. To clarify this issue, we analyzed the non-recombining portion of the Y-chromosome from 93 Aksay Kazakhs samples, using a high-resolution analysis of 106 biallelic markers and 17 STRs.