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With the rapid development of urbanization in China, urban energy consumption increases rapidly, leading to energy shortages and environmental pollution, of which building operational energy consumption carbon emissions (BECCE) account for a large proportion. It has a vital impact on global warming and urban green and sustainable development. Chengdu city in Sichuan Province is taken as the research area in this paper. First, basic information and power data on four types of single buildings, including large-sized buildings, small- and medium-sized buildings, government agencies, and residential buildings, are collected. Second, the characteristics of the four types of buildings are extracted, and the calculation model of BECCE (“electricity-carbon” model) based on particle swarm optimization algorithm–support vector machine (PSO–SVM) is constructed, and the model is trained and verified using the method of five-fold cross-validation. Then, according to the mean absolute error (MAE), root mean square error (RMSE), and R2 evaluation indicators, the constructed “electricity-carbon” model is compared and evaluated. Finally, the generalization ability of the “electricity-carbon” model is verified. The research results show that (1) the “electricity-carbon” model constructed in this paper has a high accuracy rate, and the fitting ability of the PSO–SVM model is significantly better than that of the support vector regression (SVR) model; (2) in the testing stage, the fitting situation of large buildings is the best, and MAE, RMSE, and R2 are 858.7, 1108.6, and 0.91, respectively; and (3) the spatial distribution map of regional BECCE can be quickly obtained using the “electricity-carbon” model constructed in this paper. The “electricity-carbon” model constructed in this paper can provide a scientific reference for building emission reduction.

Ensuring the swift and precise tracking of power system signal parameters, especially the frequency, is imperative for the secure and stable operation of power grids. In instances of faults within the distribution network, abrupt changes in frequency may occur, presenting a challenge for existing algorithms that struggle to effectively track such signal variations. Addressing the need for enhanced performance in the face of frequency mutations, this paper introduces an innovative approach—the Covariance Reconstruction Extended Kalman Filter (CREKF) algorithm. Initially, the dynamic signal model of electric power is meticulously analyzed, establishing a dynamic signal relationship based on high-precision time source sampling tailored to the signal model’s characteristics. Subsequently, the filter gain, covariance matrix, and variance iteration equation are determined based on the signal relationship among three sampling points. In a final step, recognizing the impact of the covariance matrix on algorithmic tracking ability, the paper proposes a covariance matrix reset mechanism utilizing hysteresis induced by output errors. Through extensive verification with simulated signals, the results conclusively demonstrate that the CREKF algorithm exhibits superior measurement accuracy and accelerated tracking speed when confronted with mutating signals.

Soybean (Glycine max) is a vital food crop, serving as a major source of high-quality protein for human and animal consumption. Stem diameter is one of the primary determinants of the stem lodging resistance of a given plant, but there has been relatively little research to date focused on genes associated with this trait. To address this gap in the literature, 207 chromosome segment substitution lines (CSSLs) were generated in the present study through the crossing and backcrossing of the improved Suinong14 and the wild ZYD00006 soybean varieties. These CSSLs were then used for the mapping of quantitative trait loci (QTLs) associated with stem diameter in two-year field planting materials, leading to the identification of nine QTLs. Whole genome resequencing, RNA-seq, and qPCR were then used to evaluate candidate genes associated with stem diameter within these QTL intervals, ultimately leading to the selection of Glyma.04G004100 as a stem diameter-related gene. Subsequent qPCR analyses revealed that Glyma.04g004100 was upregulated in soybean plants with larger stem diameters, and haplotype analyses yielded results consistent with these stem diameter data in the population used to conduct this study. In summary, a series of QTLs associated with stem diameter were identified in the present study, resulting in the establishment of Glyma.04g004100 as a stem diameter-related gene. Together, these results offer a theoretical foundation for the future molecular-assisted breeding of lodging-resistant soybean varieties, and future functional research focused on Glyma.04g004100 may elucidate the molecular mechanisms and key signaling networks involved in soybean stem development.

Mitochondria play an important role in regulating tumor cell death and metabolism so that they can be potential therapeutic targets. Sonodynamic therapy (SDT) represents an attractive antitumor method that induces apoptosis by producing highly toxic reactive oxygen species (ROS). Mitochondria-targeting SDT can cause oxidative damage and improve the efficiency of tumor therapy. However, due to the nonselective distribution of nanosystems and the anti-apoptotic mechanism of cancer cells, the therapeutic effect of SDT is not ideal. Therefore, we proposed a novel mitochondria-targeting nanosystem (‘Mito-Bomb’) for ferroptosis-boosted SDT. Sonosensitizer IR780 and ferroptosis activator RSL-3 were both encapsulated in biocompatible poly(lactic‐co‐glycolic acid) (PLGA) nanoparticles to form ‘Mito-Bomb’ (named IRP NPs). IR780 in this nanosystem was used to mediate mitochondria-targeting SDT. RSL-3 inhibited the activity of GPX4 in the antioxidant system to induce ferroptosis of tumor cells, which could rewire tumor metabolism and make tumor cells extremely sensitive to SDT-induced apoptosis. Notably, we also found that RSL-3 can inhibit hypoxia inducible factor-1α (HIF-1α) and induce ROS production to improve the efficacy of SDT to synergistically antitumor. RSL-3 was applied as a ‘One-Stone-Three-Birds’ agent for cooperatively enhanced SDT against triple-negative breast cancer. This study presented the first example of RSL-3 boosting mitochondria-targeting SDT as a ferroptosis activator. The ‘Mito-Bomb’ biocompatible nanosystem was expected to become an innovative tumor treatment method and clinical transformation.

Abstract Cell shape is linked to cell function. The significance of cell morphodynamics, namely the temporal fluctuation of cell shape, is much less understood. Here we study the morphodynamics of MDA-MB-231 cells in type I collagen extracellular matrix (ECM). We systematically vary ECM physical properties by tuning collagen concentrations, alignment, and gelation temperatures. We find that morphodynamics of 3D migrating cells are externally controlled by ECM mechanics and internally modulated by Rho/ROCK-signaling. We employ machine learning to classify cell shape into four different morphological phenotypes, each corresponding to a distinct migration mode. As a result, we map cell morphodynamics at mesoscale into the temporal evolution of morphological phenotypes. We characterize the mesoscale dynamics including occurrence probability, dwell time and transition matrix at varying ECM conditions, which demonstrate the complex phenotype landscape and optimal pathways for phenotype transitions. In light of the mesoscale dynamics, we show that 3D cancer cell motility is a hidden Markov process whereby the step size distributions of cell migration are coupled with simultaneous cell morphodynamics. Morphological phenotype transitions also facilitate cancer cells to navigate non-uniform ECM such as traversing the interface between matrices of two distinct microstructures. In conclusion, we demonstrate that 3D migrating cancer cells exhibit rich morphodynamics that is controlled by ECM mechanics, Rho/ROCK-signaling, and regulate cell motility. Our results pave the way to the functional understanding and mechanical programming of cell morphodynamics as a route to predict and control 3D cell motility.

In order to apply the C-H activation strategy to the development of chiral organic catalysts, two novel C3-trimethylsilyl substituted chiral proline catalysts are designed and synthesized using L-proline as the starting material and C(sp 3)-H silylation as the key step, which are applied to the asymmetric aldol reaction of p-nitrobenzaldehyde with acetone and the asymmetric Mannich reaction of imine with β-methylbutyraldehyde, respectively. Both target products can be synthesized with a good enantioselectivity. This strategy effectively enriches the means of structural modification of proline and provids a new method for the development of new silicon-containing organic catalysts.

ObjectiveThe objective of this research was to screen prognostic related genes of thyroid papillary carcinoma (PTC) by single-cell RNA sequencing (scRNA-seq), to construct the diagnostic and prognostic models based on The Cancer Genome Atlas Thyroid Cancer (TCGA-THCA) data, and to evaluate the association between tumor immune microenvironment and the prognostic model.MethodThe differentially expressed genes (DEGs) and tumor evolution were analyzed by scRNA-seq based on public databases. The potential regulatory networks of DEGs related to prognosis were analyzed by multi-omics data in the THCA. Logistic regression and Cox proportional hazards regression were utilized to construct the diagnosis and prognostic model of PTC. The performance of the diagnostic model was verified by bulk RNA sequencing (RNA-seq) of our cohort. The tumor immune microenvironment associated with the prognostic model was evaluated using multi-omics data. In addition, qRT-PCR was performed on tumor tissues and adjacent normal tissues of 20 patients to verify the expression levels of DEGs.ResultsThe DEGs screened by scRNA-seq can distinguish between tumor and healthy samples. DEGs play different roles in the evolution from normal epithelial cells to malignant cells. Three DEGs ((FN1, CLU, and ANXA1)) related to prognosis were filtered, which may be regulated by DNA methylation, RNA methylation (m6A) and upstream transcription factors. The area under curve (AUC) of the diagnostic model based on 3-gene in the validation of our RNA-seq was 1. In the prognostic model based on 3-gene, the overall survival (OS) of high-risk patients was shorter. Combined with the clinical information of patients, a nomogram was constructed by using tumor size (pT) and risk score to quantify the prognostic risk. The age and tumor size of high-risk patients in the prognostic model were greater. In addition, the increase of tumor mutation burden (TMB) and diversity of T cell receptor (TCR), and the decrease of CD8+ T cells in high-risk group suggest the existence of immunosuppressive microenvironment.ConclusionWe applied the scRNA-seq pipeline to focus on epithelial cells in PTC, simulated the process of tumor evolution, and revealed a prognostic prediction model based on 3 genes, which is related to tumor immune microenvironment.

The abilities of plant biologists and breeders to characterize the genetic basis of physiological traits are limited by their abilities to obtain quantitative data representing precise details of trait variation, and particularly to collect this data at a high-throughput scale with low cost. Although deep learning methods have demonstrated unprecedented potential to automate plant phenotyping, these methods commonly rely on large training sets that can be time-consuming to generate. Intelligent algorithms have therefore been proposed to enhance the productivity of these annotations and reduce human efforts. We propose a high-throughput phenotyping system which features a Graphical User Interface (GUI) and a novel interactive segmentation algorithm: Semantic-Guided Interactive Object Segmentation (SGIOS). By providing a user-friendly interface and intelligent assistance with annotation, this system offers potential to streamline and accelerate the generation of training sets, reducing the effort required by the user. Our evaluation shows that our proposed SGIOS model requires fewer user inputs compared to the state-of-art models for interactive segmentation. As a case study of the use of the GUI applied for genetic discovery in plants, we present an example of results from a preliminary genome-wide association study (GWAS) of in planta regeneration in Populus trichocarpa (poplar). We further demonstrate that the inclusion of a semantic prior map with SGIOS can accelerate the training process for future GWAS, using a sample of a dataset extracted from a poplar GWAS of in vitro regeneration. The capabilities of our phenotyping system surpass those of unassisted humans to rapidly and precisely phenotype our traits of interest. The scalability of this system enables large-scale phenomic screens that would otherwise be time-prohibitive, thereby providing increased power for GWAS, mutant screens, and other studies relying on large sample sizes to characterize the genetic basis of trait variation. Our user-friendly system can be used by researchers lacking a computational background, thus helping to democratize the use of deep segmentation as a tool for plant phenotyping.

Abstract We study a user‐guided approach for producing global explanations of deep networks for image recognition. The global explanations are produced with respect to a test data set and give the overall frequency of different “recognition reasons” across the data. Each reason corresponds to a small number of the most significant human‐recognizable visual concepts used by the network. The key challenge is that the visual concepts cannot be predetermined and those concepts will often not correspond to existing vocabulary or have labeled data sets. We address this issue via an interactive‐naming interface, which allows users to freely cluster significant image regions in the data into visually similar concepts. Our main contribution is a user study on two visual recognition tasks. The results show that the participants were able to produce a small number of visual concepts sufficient for explanation and that there was significant agreement among the concepts, and hence global explanations, produced by different participants.

Walnuts (Juglans regia L.) are a major food crop in Beijing. Recently, walnut anthracnose has become a serious problem in walnut plantations of Beijing, and the diversity of pathogens that cause this disease is poorly understood, making targeted treatment difficult. This study investigated incidences of walnut anthracnose in seven districts of Beijing (Changping, Fangshan, Haidian, Huairou, Mentougou, Miyun and Pinggu). A total of 377 isolates of Colletotrichum spp. were obtained from walnut anthracnose infected leaves and fruits. Morphological observation and multigene phylogenetic analysis of the genes ACT, CAL, CHS-1, GAPDH, ITS and TUB2 revealed that the isolates consisted of six species, C. aenigma, C. fructicola, C. gloeosporioides, C. siamense, C. liaoningense and C. sojae. Among these, C. gloeosporioides was the dominant species, and, for the first time, C. liaoningense and C. sojae were found to cause anthracnose in walnuts. Sensitivity tests showed that prochloraz and SYP-14288 had the strongest inhibitory effect on mycelial growth. These findings have clarified the species that cause walnut anthracnose in these seven districts of Beijing, which provides a scientific basis for diagnosis and control of walnut anthracnose.

We present a study of the conformational transitions of a helical polymer by using coarse-grained molecular dynamics simulations. With focus on the variation of the dihedral angles, we are able to obtain the monomer-level details of the response of the polymer chain to environmental stimuli (e.g., temperature variation and mechanical forces). Specifically, during the thermo-induced helix–coil transition, all the helices break synchronously. On the contrary, the force-induced helix breaking always starts from the termini, and then the chain behaviors become divergent and temperature dependent. Particularly, at intermediate temperatures, we find that our polymer chain can adopt an asymmetrical half-trans conformation during the stretching procedures, although the chain itself has quite uniform and homogeneous composition.

Summary: Wide variation in amenability to transformation and regeneration (TR) among many plant species and genotypes presents a challenge to the use of genetic engineering in research and breeding. To help understand the causes of this variation, we performed association mapping and network analysis using a population of 1204 wild trees of Populus trichocarpa (black cottonwood).To enable precise and high‐throughput phenotyping of callus and shoot TR, we developed a computer vision system that cross‐referenced complementary red, green, and blue (RGB) and fluorescent‐hyperspectral images. We performed association mapping using single‐marker and combined variant methods, followed by statistical tests for epistasis and integration of published multi‐omic datasets to identify likely regulatory hubs.We report 409 candidate genes implicated by associations within 5 kb of coding sequences, and epistasis tests implicated 81 of these candidate genes as regulators of one another. Gene ontology terms related to protein–protein interactions and transcriptional regulation are overrepresented, among others.In addition to auxin and cytokinin pathways long established as critical to TR, our results highlight the importance of stress and wounding pathways. Potential regulatory hubs of signaling within and across these pathways include GROWTH REGULATORY FACTOR 1 (GRF1), PHOSPHATIDYLINOSITOL 4‐KINASE β1 (PI‐4Kβ1), and OBF‐BINDING PROTEIN 1 (OBP1). [ABSTRACT FROM AUTHOR]

Papillary thyroid carcinoma (PTC) is the most common subtype of thyroid cancer. PTC is typically curable with an excellent survival rate; however, some patients experience disease recurrence or death. This study aimed to discover potential key genes and signaling pathways of PTC, which could provide new insights for thyroid lesions. Four GEO microarray datasets were integrated to screen for candidate genes involved in PTC progression. A total of 164 upregulated and 168 downregulated differentially expressed genes (DEGs) were screened. Gene Ontology/Kyoto Encyclopedia of Genes and Genomes were used in pathway enrichment analyses for DEGs. A protein-protein interaction network was then built and analyzed utilizing STRING and Cytoscape, followed by the identification of 13 hub genes by cytoHubba. CDH3, CTGF, CYR61, OGN, FGF13, and CHRDL1 were selected through survival analyses. Furthermore, immune infiltration, mutations and methylation analysis indicated that these six hub genes played vital roles in immune surveillance and tumor progression. ROC and K-M plots showed that these genes had good prognostic values for PTC which was validated by TCGA dataset. Finally, GSEA for a single hub gene revealed that each candidate hub gene had close associations with PTC development. These findings provided new insights into PTC pathogenesis and identified six candidate gene prognosis signature for PTC.

Objectives Follicular variant papillary thyroid carcinoma (FVPTC) is treated similarly to classical variant papillary thyroid carcinoma (cPTC). However, FVPTC has unique tumour features and behaviours. We investigated whether a low dose of radioiodine was as effective as a high dose for remnant ablation in patients with FVPTC and evaluated the recurrence of low-intermediate risk FVPTC. Methods Data from cPTC and FVPTC patients treated with I-131 from 2004 to 2014 were reviewed. Demographics, tumour behaviour, lymph node metastasis, and local recurrence data were compared between FVPTC and cPTC patients. Then, low-intermediate risk FVPTC patients were divided into low, intermediate, and high I-131 dose groups, and postoperative I-131 activities were analysed to evaluate the effectiveness of I-131 therapy for thyroid remnant ablation. Results In total, 799 cases of FVPTC (n = 168) and cPTC (n = 631) treated with I-131 were identified. Patients with FVPTC had a larger primary nodule size than cPTC, but lymph node metastases and local recurrence were more prevalent in cPTC than in FVPTC. For the low-, intermediate-, and high-dose groups, success rates of ablation did not differ (82.0%, 80%, and 81.3%, respectively). Conclusion FVPTC differs from cPTC in behaviour. Low-dose ablation may be sufficient in FVPTC patients with low-intermediate disease risk.

BackgroundMedullary thyroid carcinoma (MTC) is a relatively rare malignant tumor subtype originated the parafollicular C cells of the thyroid gland, producing tumor markers including calcitonin (Ctn), carcinoembryonic antigen (CEA), and chromogranin A. Preoperative serum Ctn and CEA value is important for assessing disease burden, postoperative serum Ctn and CEA can help to determine whether there are recurrence and distant metastasis.Case PresentationWe report a rare case in which the CEA level continued to increase and the Ctn value was normal after total thyroidectomy and central lymph node dissection in a MTC patient. The patient was asymptomatic during one and half year follow-up until lateral lymph node metastasis was revealed. However, the CEA level raised again after lateral neck lymph node dissection and bone metastases were found by 18F-FDG PET-CT.ConclusionThis case reminded us the recurrence of MTC should be suspected for patients with simply elevated CEA after surgery for MTC. Differential diagnosis of other malignant tumors and timely lymph node biopsy is of great significance for management.

Potentilla glabra Lodd is an important traditional Chinese medicine, which is widely distributed in many areas of China. It has a variety of pharmacological activities and has been drunk as a tea for a long time. Therefore, it has great economic, research, and social value. However, no plastid genome has been reported to date. Here, we report species of this genus complete chloroplast genome of Potentilla glabra Lodd. The chloroplast genome of Potentilla glabra Lodd is found to be 152,900 bp in length with 37.24% GC contents. The cp genome sequences contained 130 genes, including 84 mRNA genes, 37 tRNA, eight rRNA genes, and one pseudogenes, respectively. A phylogenetic tree reconstructed by 42 chloroplast genomes reveals that Potentilla glabra Lodd is most related with Potentilla parvifolia. The complete chloroplast genome of these plants will be benefit for studies on the general characteristics and evolution of the Potentilla family genome.

Background: This study was aimed at identifying natural killer (NK) cell-related genes to design a risk prognosis model for the accurate evaluation of gastric cancer (GC) prognosis. Methods: We obtained NK cell-related genes from various databases, followed by Cox regression analysis and molecular typing to identify prognostic genes. Various immune algorithms and enrichment analyses were used to investigate the mutations, immune status, and pathway variations among different genotypes. The key prognostic genes were assessed using the least absolute shrinkage and selection operator (Lasso) regression analysis and univariate Cox regression analysis. Thereafter, the risk score (RS) prognosis model was constructed based on the selected important prognostic genes. A Receiver Operating Characteristics (ROC) curve was plotted for analyzing the robustness of the model. Subsequently, the decision and calibration curves were used for assessing the reliability and prediction accuracy of the proposed model. The 'pRRophetic' R software package was utilized for predicting the half-maximal inhibitory concentration (IC50) of immunotherapy and chemotherapy drugs. Results: We screened 21 prognostic genes and three molecular subtypes and found that the C1 subtype had the worst prognosis. Further, the pathways promoting tumor proliferation, such as epithelial-mesenchymal transition were significantly up-regulated. The results also showed that the macrophages in the M2 stage were significantly infiltrated in the C1 subtype, and there was significant overexpression in the C1 subtype, accompanied by a severe inflammatory reaction. The C1 was highly sensitive to drugs like 5-fluorouracil and paclitaxel. The ROC, calibration curve, and decision curve showed that the risk model was robust and strongly reliable. Conclusion: Overall, our proposed NK cell-related RS model can be used as a more accurate prediction index for GC patients, providing a valuable contribution to personalized medicine. [ABSTRACT FROM AUTHOR]

Autotoxicity is a common problem being faced in protected vegetable cultivation system. Phytoremediation of plant autotoxicity is an emerging concept to minimize deterioration of soil environment and reduction of yield and quality of vegetable crops. Brassinosteroids (BRs) have been reported as a potential phytohormone to assist phytoremediation. However, the effects of BRs-induced autotoxicity stress on plant growth, photosynthesis and antioxidant defense system are poorly understood. Hence, we focused on the changes in physiological characteristics and ultrastructure of cucumber leaves in response to the application of 24-epibrassinolide (EBR) under autotoxicity stress conditions. The results showed that leaf area, plant height, fresh weight and dry weight of cucumber were obviously decreased under autotoxicity stress conditions. EBR application obviously improved the phenotypic characteristics of cucumber seedlings. Chlorophyll content, net photosynthetic rate, stomatal conductance and transpiration rate of cucumber leaves were markedly reduced under autotoxicity stress conditions. Application of EBR improved the photosynthetic pigments (chlorophyll a by 15.80%, chlorophyll b by 18.70% and total chlorophyll content by 17.30%), net photosynthetic rate by 36.40% and stomatal opening of leaves under autotoxicity stress conditions. EBR application also maintained the integrity of chloroplast and thylakoid structures under autotoxicity stress conditions. The activity of catalase (CAT), peroxidase (POD) and ascorbate peroxidase (APX) and antioxidative compounds ascorbate (AsA) and reduced glutathione (GSH) contents were markedly decreased, however, these were obviously increased after EBR application under autotoxicity stress. EBR application also increased the soluble sugar and protein, and proline concentration by 59.70%, 7.22% and 36.58%, respectively in the leaves of cucumber, decreased malondialdehyde by 24.13% and reactive oxygen species contents (H2O2 by 35.17%, O2− by 12.01% and •OH by 16.59%), and reduced the relative permeability of the cell membrane by 14.31%. These findings suggest that EBR application enhanced the photosynthetic capacity of leaves, maintained the integrity of chloroplast and thylakoid structures, and effectively alleviated the damage of membrane caused by lipid peroxidation and root damage under autotoxicity stress conditions. The growth inhibition effect of autotoxicity stress on cucumber was reduced by EBR application.

We study a user-guided approach for producing global explanations of deep networks for image recognition. The global explanations are produced with respect to a test data set and give the overall frequency of different "recognition reasons" across the data. Each reason corresponds to a small number of the most significant human-recognizable visual concepts used by the network. The key challenge is that the visual concepts cannot be predetermined and those concepts will often not correspond to existing vocabulary or have labeled data sets. We address this issue via an interactive-naming interface, which allows users to freely cluster significant image regions in the data into visually similar concepts. Our main contribution is a user study on two visual recognition tasks. The results show that the participants were able to produce a small number of visual concepts sufficient for explanation and that there was significant agreement among the concepts, and hence global explanations, produced by different participants. [ABSTRACT FROM AUTHOR]

Background The prevalence of ocular abnormalities of newborn in China has seldom been reported. To report the implementation of digital imaging in ocular screening of all newborns in multiple centres in China and to describe the abnormal findings of fundus examination, we did the cross-sectional study. Methods Fundus examinations were performed on newborns within the 42 days after birth using a RetCam wide-field digital imaging system. Digital images of the posterior pole, superior, nasal and temporal retinal fields of each participant were taken. All newborns were from eights centres across China from January 2009 to July 2017. Results A total of 199 851 newborns were included in the study. We detected 18 198 (9.11%) abnormal cases. The most frequent abnormality was severe retinal haemorrhage (RH) found in 12 810 cases (6.41%). The other anomalies included familial exudative vitreoretinopathy, retinopathy of prematurity, abnormal fundus pigmentation, subconjunctival haemorrhage, choroidal coloboma, idiopathic retinal venous tortuosity, exudative changes and other anomalies with uncertain identities. Conclusion This large-scale study of newborn fundus examination showed a relatively high prevalence of ocular abnormalities. Hundreds of neonates with rare disorders that severely impair ocular health were also detected at an early age. The long-term impact of other anomalies including RHs on the ocular system should be investigated by a perspective study. Our study suggested that fundus examination of newborns can play a beneficial role in ocular health. [ABSTRACT FROM AUTHOR]

Takayasu's arteritis (TA) is a rare, idiopathic, chronic inflammatory disease associated with cell-mediated inflammation and involving predominantly the aorta and its primary branches. TA results in stenosis, occlusion or aneurysmal degeneration of large arteries pathologically. However, the incidence of dissection in arteries is low. As one of the primary causes of aortic dissection-associated ischemic stroke in young adults, only a limited number of TA cases presenting with aortic dissection have been published to date. In the present study, a case of common carotid artery dissection in a young patient with TA, without evident clinical manifestations, is presented. This is a rare clinical phenomenon, but may be a risk factor of acute cerebrovascular events. Clinical examination and satisfactory imaging are crucial for the correct diagnosis and management of patients with TA with dissection in arteries, and great attention is required in order to prevent the occurrence of cerebrovascular ischemia. [ABSTRACT FROM AUTHOR]

Many microorganisms, growing on aging flue-cured tobacco leaves, play a part in its fermentation process. These microflora were identified and described by culture-dependent methods earlier. In this study we report the identity of the microflora growing on the tobacco leaf surface by employing culture-independent methods. We have amplified microbial 16S rDNA sequences directly from the leaf surface and used denaturing gradient gel electrophoresis (DGGE) to identify bacterial community on the tobacco leaves. Our culture-independent methods for the study of microbial community on tobacco leaves showed that microbial community structures on leaves of variety Zhongyan 100, NC89 and Zhongyan 101 were similar between 0 and 6 months aging, and between 9 and 12 months aging, while the similarity is low between 0 and 6, and between 9 and 12 months aging, respectively. There were certain similarities of bacterial communities (similarity up to 63%) among the three tobacco varieties for 0 to 6 months aging. Five dominant 16S rDNA DGGE bands A, B, C, D and E were isolated, cloned, and sequenced. They were most similar to two cultured microbial species Bacteriovorax sp. EPC3, Bacillus megaterium, and three uncultured microbial species, respectively. [ABSTRACT FROM AUTHOR]

Plant regeneration is an important dimension of plant propagation and a key step in the production of transgenic plants. However, regeneration capacity varies widely among genotypes and species, the molecular basis of which is largely unknown. Association mapping methods such as genome-wide association studies (GWAS) have long demonstrated abilities to help uncover the genetic basis of trait variation in plants; however, the performance of these methods depends on the accuracy and scale of phenotyping. To enable a large-scale GWAS of in planta callus and shoot regeneration in the model tree Populus , we developed a phenomics workflow involving semantic segmentation to quantify regenerating plant tissues over time. We found that the resulting statistics were of highly non-normal distributions, and thus employed transformations or permutations to avoid violating assumptions of linear models used in GWAS. We report over 200 statistically supported quantitative trait loci (QTLs), with genes encompassing or near to top QTLs including regulators of cell adhesion, stress signaling, and hormone signaling pathways, as well as other diverse functions. Our results encourage models of hormonal signaling during plant regeneration to consider keystone roles of stress-related signaling (e.g. involving jasmonates and salicylic acid), in addition to the auxin and cytokinin pathways commonly considered. The putative regulatory genes and biological processes we identified provide new insights into the biological complexity of plant regeneration, and may serve as new reagents for improving regeneration and transformation of recalcitrant genotypes and species. [ABSTRACT FROM AUTHOR]

Ion-beam-induced structural changes in rutile (TiO[sub 2]) have been examined in detail using transmission electron microscopy (TEM). Single crystals of rutile with (100) orientation were irradiated with 360 keV Xe ions at room temperature to a fluence of 4x10[sup 15]/cm[sup 2]. In addition to a buried damage layer induced by projectile ions, a damage layer was formed near the surface (thickness about 10 nm). Nanobeam electron diffraction measurements and high-resolution TEM observations revealed that the surface damage layer consists of rutile crystallites with different orientations compared to the original single crystal. We discuss damage recovery processes in ion irradiated rutile within the context of our results as well as previous observations. © 2000 American Institute of Physics. [ABSTRACT FROM AUTHOR]