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Abstract Purpose Rectal tumor segmentation on post neoadjuvant chemoradiotherapy (nCRT) magnetic resonance imaging (MRI) has great significance for tumor measurement, radiomics analysis, treatment planning, and operative strategy. In this study, we developed and evaluated segmentation potential exclusively on post-chemoradiation T2-weighted MRI using convolutional neural networks, with the aim of reducing the detection workload for radiologists and clinicians. Methods A total of 372 consecutive patients with LARC were retrospectively enrolled from October 2015 to December 2017. The standard-of-care neoadjuvant process included 22-fraction intensity-modulated radiation therapy and oral capecitabine. Further, 243 patients (3061 slices) were grouped into training and validation datasets with a random 80:20 split, and 41 patients (408 slices) were used as the test dataset. A symmetric eight-layer deep network was developed using the nnU-Net Framework, which outputs the segmentation result with the same size. The trained deep learning (DL) network was examined using fivefold cross-validation and tumor lesions with different TRGs. Results At the stage of testing, the Dice similarity coefficient (DSC), 95% Hausdorff distance (HD95), and mean surface distance (MSD) were applied to quantitatively evaluate the performance of generalization. Considering the test dataset (41 patients, 408 slices), the average DSC, HD95, and MSD were 0.700 (95% CI: 0.680–0.720), 17.73 mm (95% CI: 16.08–19.39), and 3.11 mm (95% CI: 2.67–3.56), respectively. Eighty-two percent of the MSD values were less than 5 mm, and fifty-five percent were less than 2 mm (median 1.62 mm, minimum 0.07 mm). Conclusions The experimental results indicated that the constructed pipeline could achieve relatively high accuracy. Future work will focus on assessing the performances with multicentre external validation.

AimOur study aimed to assess the association between UCP2 gene 3’ untranslated region insertion/deletion (3’UTR I/D) and A55V (alanine/valine) polymorphisms and neural tube defects (NTDs) susceptibility.Materials and methodsAccording to pre-determined inclusion and exclusion criteria, the article search was conducted to search articles published before October 2023. Two authors independently screened the included articles and extracted their basic characteristics. After quality evaluation, the meta-analysis and trial sequential analysis (TSA) were conducted using RevMan 5.4, Stata/MP 17, and TSA 0.9.5.10 Beta. Subgroup analysis was conducted based on country and case group composition. Sensitivity analysis was conducted using a one-by-one exclusion method. Begg’s and Egger’s tests were used to evaluate publication bias.ResultsA total of seven articles were included. Overall meta-analysis revealed significant heterogeneity among the included studies for 3’UTR I/D polymorphism of the UCP2 gene. Significant statistical data indicated that those with the DD genotype and D allele had higher chances of NTD compared to those with the II genotype and the I allele, respectively. The combined result of II vs. ID was not statistically significant. A55V variation showed no statistical significance in the risk of NTD, despite the absence of significant heterogeneity across the included studies. Most of the heterogeneity was resolved after subgrouping, and a higher risk of the ID genotype was found than the II genotype for Chinese people. Genotyping NTD patients or their mothers was not a factor affecting the heterogeneity. Sensitivity analysis and publication bias analysis suggested that positive findings supported our results.ConclusionThe UCP2 gene 3’UTR I/D polymorphism increased the likelihood of developing NTDs in the Chinese population, with the D allele being the risk factor, which contributed to the understanding of the genetic basis of NTDs. TSA indicated that more high-quality original studies were needed in the future for further validation.

Abstract Perovskite films with large crystal size, preferred orientation, and facile fabrication process, combining advantages of single‐crystal and polycrystalline films, have gained considerable attention recently. However, there is little research on the facet properties of perovskite films. Here, (111)‐ and (001)‐oriented perovskite films with bandgaps ranging from 1.53 to 1.77 eV, and systematically investigated their orientation‐dependent properties are achieved. The (111)‐oriented films show electron‐dominated traps and the (001)‐oriented films show hole‐dominated traps, which are related to their atomic arrangement at the surface. Compared with the (001)‐oriented films, the (111)‐oriented films exhibit lower work function and superior water/oxygen robustness. For the wide‐bandgap films, the lattice of the (001)‐oriented film provides an unobstructed passage for ion migration. Comparably, the (111)‐oriented films exhibit suppressed ion migration and excellent phase stability. The optimized unencapsulated solar cells based on both (001) and (111) orientations show a similar high efficiency of ≈23%. The (111)‐oriented solar cell exhibits excellent stability, maintaining 95% of its initial efficiency after 1500 h maximum power point (MPP) tracking test, and 97% initial efficiency after 3000 h aging in ambient conditions. This work paves the way for the rational design, controllable synthesis, and targeted optimization of uniaxial‐oriented perovskite films for various electronic applications.

The Internet of Things (IoT) technology connects the real and network worlds by integrating sensors and internet technology, which has greatly changed people’s lifestyles, showing its broad application prospects. However, traditional materials for the sensors and power components used in the IoT limit its development for high-precision detection, long-term endurance, and multi-scenario applications. Metal halide perovskite, with unique advantages such as excellent photoelectric properties, an adjustable bandgap, flexibility, and a mild process, exhibits enormous potential to meet the requirements for IoT development. This paper provides a comprehensive review of metal halide perovskite’s application in sensors and energy supply modules within IoT systems. Advances in perovskite-based sensors, such as for gas, humidity, photoelectric, and optical sensors, are discussed. The application of indoor photovoltaics based on perovskite in IoT systems is also discussed. Lastly, the application prospects and challenges of perovskite-based devices in the IoT are summarized.

The Three-River Headwaters (TRH) region in the Tibetan Plateau is vulnerable to climate change; changes in summer (June–August) precipitation have a significant impact on water security and sustainability in both local and downstream areas. However, the changes in summer precipitation of different intensities over the TRH region, along with their influencing factors, remain unclear. In this study, we used observational and ERA5 reanalysis data and employed a precipitation categorization and water vapor budget analysis to quantify the categorized precipitation variations and investigate their possible linkages with the water vapor budget. Our results showed an increasing trend in summer precipitation at a rate of 0.9 mm per year (p

Cytosine arabinoside (Ara-C) is one of the most widely used chemotherapeutic agents for hematological malignancies. The residues of Ara-C have been detected in wastewater and river water with increased usage and discharge. As the ability to cross the placenta and the teratogenicity at low ng/L levels, the toxic effects on pregnant women and infants have been concerned. The toxicity of Ara-C exposure on early embryonic neurodevelopment has not been fully elucidated. In this study, pregnant C57BL/6 mice were injected with different doses of Ara-C on Gestation day (GD) 7.5 and assessed on GD11.5 and GD13.5 to explore the neural developmental effects of Ara-C. HE staining, immunofluorescence, western blot, EdU assay, and flow cytometry were utilized to determine the toxic effects of Ara-C in vivo and in vitro. Our results showed that Ara-C (15–22.5 mg/kg body weight) induced the occurrence of neural tube defects (NTDs). The expression of PH3 was markedly reduced in embryos with Ara-C-induced NTDs, compared to the control group (P

In this paper, we present and analyze two linearized Galerkin finite element schemes, which are constructed by employing the H2N2 formula and its fast version in time direction, for solving the nonlinear time-fractional diffusion-wave equation. By utilizing mathematical induction, the optimal error estimates in H1-norm are derived without any ratio restrictions between the time step size τ and the space mesh size h. The key point in our argument is the application of Sobolev’s embedding inequality to the fully discrete solution uhn. On the other hand, additional time-discrete elliptic system and the inverse inequality, which play a vital role in the temporal–spatial error splitting technique, are avoided in our numerical analysis. Finally, two numerical experiments are given to demonstrate the theoretical findings.

ShuffleNetV2 is a prominent player in the field of lightweight networks and has significant implications for the development of lightweight networks and edge computing. However, it has limitations, as its accuracy falls short compared to other larger models, and it is not friendly to datasets. It loses its advantage for small-sized images with fewer channels. In this study, we analysed the design structure of ShuffleNetV2 and found room for improvement in its computational complexity and accuracy. To further improve its performance, we first upgraded the ShuffleNetV2 network structure based on the lightweight network design criteria and constructed a new network model. Second, we introduced a novel attention module named the Adaptive Pooling Attention Module (APAM) and integrated it with the new network model, constructing a high-performance model referred to as LA-ShuffleNet. Then, we proposed a convolution operation acceleration strategy called Pack. Finally, we combined the two and conducted corresponding tests on the Windows and JETSON platforms. Extensive experiments indicate that our proposed model not only exhibits substantial improvements over the baseline model but also achieves noteworthy enhancements on the ImageNet dataset, with a rise of 1.4% in Top-1 accuracy and 3.6% in Top-5 accuracy, coupled with a reduction of 0.7M parameters. Moreover, its performance surpasses that of certain prevalent lightweight networks, such as MobileNet.

Here the authors show, using microglia-specific depletion techniques and single cell transcriptomics, that optimal repair after murine spinal cord injury (SCI) requires microglia.

The accurate identification of highly similar sheet metal parts remains a challenging issue in sheet metal production. To solve this problem, this paper proposes an effective mean square differences (EMSD) algorithm that can effectively distinguish highly similar parts with high accuracy. First, multi-level downsampling and rotation searching are adopted to construct an image pyramid. Then, non-maximum suppression is utilised to determine the optimal rotation for each layer. In the matching, by re-evaluating the contribution of the difference between the corresponding pixels, the matching weight is determined according to the correlation between the grey value information of the matching pixels, and then the effective matching coefficient is determined. Finally, the proposed effective matching coefficient is adopted to obtain the final matching result. The results illustrate that this algorithm exhibits a strong discriminative ability for highly similar parts, with an accuracy of 97.1%, which is 11.5% higher than that of the traditional methods. It has excellent potential for application and can significantly improve sheet metal production efficiency.

The proton exchange membrane fuel cell (PEMFC) is a promising energy conversion device due to its high reliability, fast response speed, and low pollutant emission. However, the reality of its commercial application requires further cost reduction and efficiency improvement. The material distribution in the channel and the performance of PEMFC can be improved by setting the boss inside the flow channels. In this paper, the performance of PEMFC with the boss in flow channels in a parallel flow field was analyzed by simulation. The influence of different boss arrangements and heights on gas pressure drop, distribution uniformity, gas component distribution, temperature distribution, and output performance of the fuel cell were analyzed in detail. The bosses would increase the pressure drop and the distribution uniformity of reactive gases in flow channels significantly. The cross-arrangement of bosses is better than the cross-arrangement of bosses and juxtaposition according to increasing performance and pressure drop. The cross-arrangement with a boss height of 0.4 mm is suitable for the parallel flow field in this paper. The improved scheme of flow channel design is proposed to provide a reference for fuel cells for subsequent research.

There is an inherent coupling relationship between the time when buses arrive at the station and the time when they arrive the intersection, and it is essential to study the relationship as a whole to maximize the benefits of company operations and passenger services. In this study, a coordinated control method of signal priority and speed regulation in the stop-skipping mode at peak hours is proposed. First, the decision result of stop-skipping is obtained based on the historical passenger flow data. On this basis, the signal-priority decision is made for each vehicle in combination with the signal period and the arrival time of the intersection, and coordinated control is carried out in combination with the speed adjustment. The result of the genetic algorithm shows that cooperative control and prevention can minimize the passenger delay time and enterprise operation cost. The conclusions obtained in this research lay a theoretical foundation for company operation and signal-priority triggering mechanism.

Neural-tube defects (NTDs) are one type of the most serious birth defects. Studies have shown that inositol deficiency is closely related to the occurrence of NTDs. Bone morphogenetic protein (BMP)-mediated Smad signaling pathways have been implicated in neurogenesis and neural-tube closure. However, the role of the BMP/Smad pathway in inositol-deficiency-induced NTDs remains unclear. Inositol-deficiency models in C57 mice and mouse neural stem cells (mNSCs) were induced with Li2CO3 treatment or inositol withdrawal. The role of the BMP/Smad pathway in the regulation of cell proliferation and the development of NTDs was determined utilizing qRT-PCR, HE staining, Western blot, immunostaining, MTT assay, EdU staining, and flow cytometry. The intraperitoneal injection of Li2CO3 at Embryonic Day 7.5 induced the occurrence of NTDs. The mRNA levels of Bmp2, Bmp4, Smad1, Smad5, Smad8 and Runx2, the phosphorylation of Smad1/5/8, and the nuclear translocation of Runx2 were significantly increased in NTD embryonic brain tissues and mNSCs exposed to Li2CO3 or an inositol-free medium, which were suppressed by BMP receptor selective inhibitor LDN-193189. The Li2CO3-induced phosphorylation of Smad1/5/8 was inhibited by inositol supplementation. Cell proliferation was significantly promoted by Li2CO3 exposure or the absence of inositol in mNSCs, which was reversed by LDN-193189. These results suggest that the activation of the BMP/Smad signaling pathway might play an important role in the development of NTDs induced by maternal Li2CO3 exposure via inositol deficiency.

Palate-derived growth factor receptor α (Pdgfrα) signaling has been reported to play important roles in the cardiac development. A previous study utilizing Pdgfrα conventional knockout mice reported hypoplasia of the sinus venous myocardium including the sinoatrial node (SAN) accompanied by increased expression of Nkx2.5. This mouse line embryos die by E11.5 due to embryonic lethality, rendering them difficult to investigate the details. To elucidate the underlying mechanism, in this study, we revisited this observation by generation of specific ablation of Pdgfrα in the SAN by Shox2-Cre at E9.5, using a Shox2-Cre;Pdgfrαflox/flox conditional mouse line. Surprisingly, we found that resultant homozygous mutant mice did not exhibit any malformation in SAN morphology as compared to their wild-type littermates. Further analysis revealed the normal cardiac function in adult mutant mice assessed by the record of heart rate and electrocardiogram and unaltered expression of Nkx2.5 in the E13.5 SAN of Pdgfrα conditional knockout mice. Our results unambiguously demonstrate that Pdgfrα is dispensable for SAN development after its fate commitment in mice.

The inositol polyphosphate-5-phosphatase E (Inpp5e) gene is located on chromosome 9q34.3. The enzyme it encodes mainly hydrolyzes the 5-phosphate groups of phosphatidylinositol (3,4,5)-trisphosphate (PtdIns (3,4,5) P3) and phosphatidylinositol (4,5)-bisphosphate (PtdIns (4,5)P2), which are closely related to ciliogenesis and embryonic neurodevelopment, through mechanisms that are largely unknown. Here we studied the role of Inpp5e gene in ciliogenesis during embryonic neurodevelopment using inositol-deficiency neural tube defects (NTDs) mouse and cell models. Confocal microscopy and scanning electron microscope were used to examine the number and the length of primary cilia. The dynamic changes of Inpp5e expression in embryonic murine brain tissues were observed during Embryonic Day 10.5–13.5 (E 10.5–13.5). Immunohistochemistry, western blot, polymerase chain reaction (PCR) arrays were applied to detect the expression of Inpp5e and cilia-related genes of the embryonic brain tissues in inositol deficiency NTDs mouse. Real-time quantitative PCR (RT-qPCR) was used to validate the candidate genes in cell models. The levels of inositol and PtdIns(3,4) P2 were measured using gas chromatography-mass spectrometry (GC-MS) and enzyme linked immunosorbent assay (ELISA), respectively. Our results showed that the expression levels of Inpp5e gradually decreased in the forebrain tissues of the control embryos, but no stable trend was observed in the inositol deficiency NTDs embryos. Inpp5e expression in inositol deficiency NTDs embryos was significantly decreased compared with the control tissues. The expression levels of Inpp5e gene and the PtdIns (3,4) P2 levels were also significantly decreased in the inositol deficient cell model. A reduced number and length of primary cilia were observed in NIH3T3 cells when inositol deficient. Three important cilia-related genes (Ift80, Mkks, Smo) were down-regulated significantly in the inositol-deficient NTDs mouse and cell models, and Smo was highly involved in NTDs. In summary, these findings suggested that down-regulation of Inpp5e might be associated with abnormal ciliogenesis during embryonic neurodevelopment, under conditions of inositol deficiency.

ObjectiveTo investigate the efficiency of pre-therapy magnetic resonance imaging (MRI) features in predicting the prognosis of desmoid-type fibromatosis patients treated with imatinib.Materials and MethodsA total of 38 desmoid-type fibromatosis patients treated with imatinib were collected in this retrospective study. The high signal intensity on pre-therapy MRI was evaluated on axial T2 and T1 contrast-enhanced sequences with fat suppression. Cox regression and Kaplan–Meier analyses explored the correlation between clinical or radiographic characteristics and progression-free survival (PFS).ResultsHyperintense T1 contrast enhancement (CE) proportion (≥ 75%) was identified as an independent predictor for PFS. Patients with hyperintense T1 CE proportion

Proper vehicle operation and route planning are critical for achieving the best match between bus operation and passenger services. In order to enhance the attractiveness of public transportation, a new type of the public transportation dispatching method based on passenger reservation data is proposed. This mode can meet the requirements of multiple lines in urban centers during peak hours, which can realize direct service between two stations. Then, taking the lowest operating cost of the enterprise and the lowest passenger waiting cost as the optimization goal, a customized dynamic dispatching model of multiline and hybrid vehicles was established. Finally, a calculation example is designed and the genetic algorithm is used to solve the model. The results show that the hybrid vehicle solution is more reasonable than the traditional single-vehicle solution and reveal that the model is feasible to optimize scheduling plan. The conclusions obtained in this research lay a theoretical foundation for APP setup and operation plan formulation.

Dual-specific tyrosine phosphorylation regulated kinase 1 (DYRK1A) has been regarded as a potential therapeutic target of neurodegenerative diseases, and considerable progress has been made in the discovery of DYRK1A inhibitors. Identification of pharmacophoric fragments provides valuable information for structure- and fragment-based design of potent and selective DYRK1A inhibitors. In this study, seven machine learning methods along with five molecular fingerprints were employed to develop qualitative classification models of DYRK1A inhibitors, which were evaluated by cross-validation, test set, and external validation set with four performance indicators of predictive classification accuracy (CA), the area under receiver operating characteristic (AUC), Matthews correlation coefficient (MCC), and balanced accuracy (BA). The PubChem fingerprint-support vector machine model (CA = 0.909, AUC = 0.933, MCC = 0.717, BA = 0.855) and PubChem fingerprint along with the artificial neural model (CA = 0.862, AUC = 0.911, MCC = 0.705, BA = 0.870) were considered as the optimal modes for training set and test set, respectively. A hybrid data balancing method SMOTETL, a combination of synthetic minority over-sampling technique (SMOTE) and Tomek link (TL) algorithms, was applied to explore the impact of balanced learning on the performance of models. Based on the frequency analysis and information gain, pharmacophoric fragments related to DYRK1A inhibition were also identified. All the results will provide theoretical supports and clues for the screening and design of novel DYRK1A inhibitors.

IntroductionDiabetes is a metabolic disease with a high incidence and serious harm to human health. Islet β-cell function defects can occur in the late stage of type 1 diabetes and type 2 diabetes. Studies have shown that stem cell is a promising new approach in bioengineering regenerative medicine. In the study of stem cell differentiation, three-dimensional (3D) cell culture is more capable of mimicking the microenvironment of cell growth in vivo than two-dimensional (2D) cell culture. The natural contact between cells and cells, and cells and extracellular matrix can regulate the development process and promote the formation of the artificial regenerative organs and organization. Type IV, VI collagen and laminin are the most abundant extracellular matrix components in islets. Matrigel, a basement membrane matrix biomaterial rich in laminin and collagen IV.Materials and MethodsWe used Matrigel biomaterial to physically embed human dental pulp stem cells (hDPSCs) to provide vector and 3D culture conditions for cells, and we explored and compared the preparation methods and preliminary mechanisms of differentiation of hDPSCs into insulin-producing cells (IPCs) under 2D or 3D culture conditions.We first designed and screened the strategy by mimicking the critical events of pancreatogenesis in vivo, and succeeded in establishing a new method for obtaining IPCs from hDPSCs. Activin A, Noggin, and small molecule compounds were used to synergistically induce hDPSCs to differentiate into definitive endoderm-like cells, pancreatic progenitor like cells and IPCs step by step under 2D culture conditions. Then, we used Matrigel to simulate the microenvironment in vivo, induced hDPSCs to differentiate into IPCs in Matrigel, evaluated and compared the efficiency between 2D and 3D culture conditions.ResultsThe results showed that the synergistic combination of growth factors and small molecule compounds and 3D culture promoted the differentiation of hDPSCs into IPCs, significantly enhancing the release of insulin and C-peptide from IPCs.DiscussionSignificant support is provided for obtaining a large number of functional IPCs for disease modeling and final cell therapy in regenerative medicine.

The image-based modeling and simulation of plant growth have numerous and diverse applications. In this study, we used image-based and manual field measurements to develop and validate a methodology to simulate strawberry (Fragaria × ananassa Duch.) plant canopies throughout the Florida strawberry growing season. The simulated plants were used to create a synthetic image using radiative transfer modeling. Observed canopy properties were incorporated into an L-system simulator, and a series of strawberry canopies corresponding to specific weekly observation dates were created. The simulated canopies were compared visually with actual plant images and quantitatively with in-situ leaf area throughout the strawberry season. A simple regression model with L-system-derived and in-situ total leaf areas had an Adj R2 value of 0.78. The L-system simulated canopies were used to derive information needed for image simulation, such as leaf area and leaf angle distribution. Spectral and plant canopy information were used to create synthetic high spatial resolution multispectral images using the Discrete Anisotropic Radiative Transfer (DART) software. Vegetation spectral indices were extracted from the simulated image and used to develop multiple regression models of in-situ biophysical parameters (leaf area and dry biomass), achieving Adj R2 values of 0.63 and 0.50, respectively. The Normalized Difference Vegetation Index (NDVI) and the Red Edge Simple Ratio (SRre) vegetation indices, which utilize the red, red edge, and near infrared bands of the spectrum, were identified as statistically significant variables (p < 0.10). This study showed that both geometric (canopy seize metrics) and spectral variables were successful in modeling in-situ biomass and leaf area. Combining the geometric and spectral variables, however, only slightly improved the prediction model. These results show the feasibility of simulating strawberry canopies and images with inherent geometrical, topological, and spectral properties of real strawberry plants. The simulated canopies and images can be used in applications beyond creating realistic computer graphics for quantitative applications requiring the depiction of vegetation biological processes, such as stress modeling and remote sensing mission planning.

Two types of energetic semiconductor bridges (ESCBs), with 3μm and 6μm Al/MoO3 energetic multilayer nanofilms integrated respectively, were prepared with microfabrication technique. The influence of Al/MoO3 nanofilms thickness on the firing and initiation characteristics of ESCBs was investigated. Results show that critical firing time and critical firing energy of ESCBs do not change significantly. The flame size of SCB-Al/MoO3(6μm) is twice than that of SCB-Al/MoO3(3μm) at 100μs. Furthermore, the firing duration of SCB-Al/MoO3(6μm) is 540μs, much higher than SCB-Al/MoO3(3μm) 300μs, which is very useful for the initiation of energetic materials. However, the contact and non-contact initiation of ESCBs on HMX-Al/MoO3 composite explosives show that the film thickness of Al/MoO3 has the remarkable influence on the initiation ability of ESCBs. The results from experiments deepen the understanding of the influence of thickness of Al/MoO3 nanofilms on the firing performance of SCB, which is very meaningful for the initiation of energetic materials.DOI: http://dx.doi.org/10.5755/j01.ms.24.2.18266

In this paper, we first introduce the concept of a Rota–Baxter operator on a cocommutative weak Hopf algebra H and give some examples. We then construct Rota–Baxter operators from the normalized integral, antipode, and target map of H. Moreover, we construct a new multiplication “∗” and an antipode SB from a Rota–Baxter operator B on H such that HB=(H,∗,η,Δ,ε,SB) becomes a new weak Hopf algebra. Finally, all Rota–Baxter operators on a weak Hopf algebra of a matrix algebra are given.

In order to solve the problem of inefficient long-term operation of urban public transport vehicles and the difficulty of finding the cause of the disease, a new analysis idea was designed using machine learning methods. This study aimed to provide a rapid, accurate, and convenient solution model and algorithm to address the drawbacks of traditional analysis tools that are incapable of handling multiple sources of public transport data. Based on a full process analysis of the bus operation status, the influencing factors and calculation methods were defined. Afterwards, the calculation results were used to construct a training set with a Random Forest regression model to obtain the weight ranking of different influencing factors. The results of the simulation validation proved that the model can use the basic data of bus operation to quickly find out the primary factors affecting the operation condition and pinpoint to the bottleneck interval. The method has high accuracy and feasibility. It can be universally applied to the analysis of regular bus scenarios to provide strong decision support for the operation level.

Capturing high spatial resolution imagery is becoming a standard operation in many agricultural applications. The increased capacity for image capture necessitates corresponding advances in analysis algorithms. This study introduces automated raster geoprocessing methods to automatically extract strawberry (Fragaria × ananassa) canopy size metrics using raster image analysis and utilize the extracted metrics in statistical modeling of strawberry dry weight. Automated canopy delineation and canopy size metrics extraction models were developed and implemented using ArcMap software v 10.7 and made available by the authors. The workflows were demonstrated using high spatial resolution (1 mm resolution) orthoimages and digital surface models (2 mm) of 34 strawberry plots (each containing 17 different plant genotypes) planted on raised beds. The images were captured on a weekly basis throughout the strawberry growing season (16 weeks) between early November and late February. The results of extracting four canopy size metrics (area, volume, average height, and height standard deviation) using automatically delineated and visually interpreted canopies were compared. The trends observed in the differences between canopy metrics extracted using the automatically delineated and visually interpreted canopies showed no significant differences. The R2 values of the models were 0.77 and 0.76 for the two datasets and the leave-one-out (LOO) cross validation root mean square error (RMSE) of the two models were 9.2 g and 9.4 g, respectively. The results show the feasibility of using automated methods for canopy delineation and canopy metric extraction to support plant phenotyping applications.

DNA methylation is thought to be involved in the etiology of neural tube defects (NTDs). However, the exact mechanism between DNA methylation and NTDs remains unclear. Herein, we investigated the change of methylation in mouse model of NTDs associated with folate dysmetabolism by use of ultraperformance liquid chromatography tandem mass spectrometry (UPLC/MS/MS), liquid chromatography-electrospray ionization tandem mass spectrometry (LC-MS/MS), microarray, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and Real time quantitative PCR. Results showed that NTD neural tube tissues had lower concentrations of 5-methyltetrahydrofolate (5-MeTHF, P = 0.005), 5-formyltetrahydrofolate (5-FoTHF, P = 0.040), S-adenosylmethionine (SAM, P = 0.004) and higher concentrations of folic acid (P = 0.041), homocysteine (Hcy, P = 0.006) and S-adenosylhomocysteine (SAH, P = 0.045) compared to control. Methylation levels of genomic DNA decreased significantly in the embryonic neural tube tissue of NTD samples. 132 differentially methylated regions (35 low methylated regions and 97 high methylated regions) were selected by microarray. Two genes (Siah1b, Prkx) in Wnt signal pathway demonstrated lower methylated regions (peak) and higher expression in NTDs (P

BACKGROUND: Epidemiological surveys and animal studies have revealed that inositol metabolism is associated with NTDs, but the mechanisms are not clear. Inositol 1,3,4-trisphosphate 5/6-kinase (ITPK1) is a pivotal regulatory enzyme in inositol metabolic pathway. The objective was to assess the potential impact of the maternal ITPK1 genotypes on the inositol parameter and on the NTD risk in a NTD high-risk area in China. METHODOLOGY/RESULTS: A case-control study of pregnant women affected with NTDs (n = 200) and controls (n = 320) was carried out. 13 tag SNPs of ITPK1 were selected and genotyped by the Sequenom MassArray system. We found that 4 tag SNPs were statistically significant in spina bifida group (P