Changes in Resting-State Networks in Children with Growth Hormone Deficiency.

Purpose: Growth hormone deficiency (GHD) refers to the partial or complete lack of growth hormone. Short stature and slow growth are characteristic of patients with GHD. Previous neuroimaging studies have suggested that GHD may cause cognitive and behavioral impairments in patients. Resting-state networks (RSNs) are regions of the brain that exhibit synchronous activity and are closely related to our cognition and behavior. Therefore, the purpose of the current study was to explore cognitive and behavioral abnormalities in children with GHD by investigating changes in RSNs. Methods: Resting-state functional magnetic resonance imaging (rs-fMRI) data of 26 children with GHD and 15 healthy controls (HCs) were obtained. Independent component analysis was used to identify seven RSNs from rs-fMRI data. Group differences in RSNs were estimated using two-sample t-tests. Correlation analysis was employed to investigate the associations among the areas of difference and clinical measures. Results: Compared with HCs, children with GHD had significant differences in the salience network (SN), default mode network (DMN), language network (LN), and sensorimotor network (SMN). Moreover, within the SN, the functional connectivity (FC) value of the right posterior supramarginal gyrus was negatively correlated with the adrenocorticotropic hormone and the FC value of the left anterior inferior parietal gyrus was positively correlated with insulin-like growth factor 1. Conclusions: These results suggest that alterations in RSNs may account for abnormal cognition and behavior in children with GHD, such as decreased motor function, language withdrawal, anxiety, and social anxiety. These findings provide neuroimaging support for uncovering the pathophysiological mechanisms of GHD in children. Impact statement Children with growth hormone deficiency (GHD) generally experience cognitive and behavioral abnormalities. However, there are few neuroimaging studies on children with GHD. Moreover, prior research has not investigated the aberrant brain function in patients with GHD from the perspective of brain functional networks. Therefore, this study employed the independent component analysis method to investigate alterations within seven commonly observed resting-state networks due to GHD. The results showed that children with GHD had significant differences in the salience network, default mode network, language network, and sensorimotor network. This provides neuroimaging support for revealing the pathophysiological mechanisms of GHD in children.

Frequency Dependent Changes of Regional Homogeneity in Children with Growth Hormone Deficiency.

Abnormal spontaneous neural activity in children with growth hormone deficiency (GHD) has been found in previous resting-state functional magnetic resonance imaging (rs-fMRI) studies. Nevertheless, the spontaneous neural activity of GHD in different frequency bands is still unclear. Here, we combined rs-fMRI and regional homogeneity (ReHo) methods to analyze the spontaneous neural activity of 26 GHD children and 15 healthy controls (HCs) with age- and sex-matching in four frequency bands: slow-5 (0.014-0.031 Hz), slow-4 (0.031-0.081 Hz), slow-3 (0.081-0.224 Hz), and slow-2 (0.224-0.25 Hz). In the slow-5 band, GHD children compared with HCs displayed higher ReHo in the left dorsolateral part of the superior frontal gyrus, triangular part of the inferior frontal gyrus, precentral gyrus and middle frontal gyrus, and right angular gyrus, while lower ReHo in the right precentral gyrus, and several medial orbitofrontal regions. In the slow-4 band, GHD children relative to HCs revealed increased ReHo in the right middle temporal gyrus, whereas reduced ReHo in the left superior parietal gyrus, right middle occipital gyrus, and bilateral medial parts of the superior frontal gyrus. In the slow-2 band, compared with HCs, GHD children showed increased ReHo in the right anterior cingulate gyrus, and several prefrontal regions, while decreased ReHo in the left middle occipital gyrus, and right fusiform gyrus and anterior cingulate gyrus. Our findings demonstrate that regional brain activity in GHD children exhibits extensive abnormalities, and these abnormalities are related to specific frequency bands, which may provide bases for understanding its pathophysiology significance.

Monocomponent Nanodots with Dichromatic Output Regulated by Synergistic Dual-Stimuli for Cervical Cancer Tissue Imaging and Photodynamic Tumor Therapy.

Inflammation exists in the microenvironment of most, if not virtually all, tumors, which greatly exacerbates the difficulty of cancer treatment. Considering the superiority of activatable photosensitizers (PSs), a novel strategy of 'making friends with the enemy' for tumor treatment was proposed. In this strategy, the "enemy" refers to inflammatory cytokines and the tumor site is targeted by detecting the enemy. Upon detection, a dichromatic fluorescence signal is released and the PS is activated specifically by the inflammatory cytokines. In this study, a multifunctional PS (TPE-PTZ-Py) was rationally designed, which can be activated specifically under the synergistic action of hypochlorous acid (HClO) (one kind of inflammatory cytokines) and acid (one typical marker of tumor), and output a ratiometric fluorescence signal simultaneously. The sulfoxide analogue (TPE-PTZO-PyH) as the response product effectively produced 1O2 (1.8-fold higher than that obtained with Rose Bengal) and showed high phototoxicity (IC50 < 7.6 µM). More importantly, imaging analyses confirmed that TPE-PTZ-Py could be activated in human cervical cancer tissue. To date, several phenothiazine (PTZ)-based fluorescent probes have been developed for the selective sensing and imaging of HClO in subcellular organelles; however, this is the first phenothiazine-based nanodrug designed for the treatment of inflammation-associated tumors with a few side effects.

Application of U-Net with Global Convolution Network Module in Computer-Aided Tongue Diagnosis.

The rapid development of intelligent manufacturing provides strong support for the intelligent medical service ecosystem. Researchers are committed to building Wise Information Technology of 120 (WIT 120) for residents and medical personnel with the concept of simple smart medical care and through core technologies such as Internet of Things, Big Data Analytics, Artificial Intelligence, and microservice framework, to improve patient safety, medical quality, clinical efficiency, and operational benefits. Among them, how to use computers and deep learning technology to assist in the diagnosis of tongue images and realize intelligent tongue diagnosis has become a major trend. Tongue crack is an important feature of tongue states. Not only does change of tongue crack states reflect objectively and accurately changed circumstances of some typical diseases and TCM syndrome but also semantic segmentation of fissured tongue can combine the other features of tongue states to further improve tongue diagnosis systems' identification accuracy. Although computer tongue diagnosis technology has made great progress, there are few studies on the fissured tongue, and most of them focus on the analysis of tongue coating and body. In this paper, we do systematic and in-depth researches and propose an improved U-Net network for image semantic segmentation of fissured tongue. By introducing the Global Convolution Network module into the encoder part of U-Net, it solves the problem that the encoder part is relatively simple and cannot extract relatively abstract high-level semantic features. Finally, the method is verified by experiments. The improved U-Net network has a better segmentation effect and higher segmentation accuracy for fissured tongue image dataset. It can be used to design a computer-aided tongue diagnosis system.

[Consensus on collaborative ethical review of multi-center clinical trials of new drugs of traditional Chinese medicine (version 1.0)].

At present, the issues regarding multi-center clinical trials of new drugs of traditional Chinese medicine(TCM) remain: the lack of agreement on the content and scope of the ethical review among the ethics committee members of the center and the participating units results in repeated review, which leads to a time-consuming ethical review process. Moreover, the review capabilities of the ethics committees of various research centers are uneven, which is not necessarily beneficial to the protection of subjects' rights and safety. In view of the existing problems, to improve the efficiency of ethical review of multi-center clinical trials of new drugs of TCM and avoid repeated reviews, the TCM Clinical Evaluation Professional Committee of Chinese Pharmaceutical Association organized experts to formulate the "Consensus on collaborative ethical review of multi-center clinical trials of new drugs of TCM(version 1.0)"(hereinafter referred to as "Consensus"). The "Consensus" is formulated in accordance with the requirements of relevant documents such as but not limited to "the opinions on deepening the reform of the evaluation and approval system to encourage the innovation of pharmaceutical medical devices", "the regulations of ethical review of biomedical research involving human subjects". The "Consensus" covers the scope of application, formulation principles, conditions for the ethics committee of the center, sharing of ethical review resources, scope and procedure of collaborative review, rights and obligations, etc. The aims of the "Consensus" is to preliminarily explore and establish a scientific and operable ethical review procedure. Additionally, on the basis of fully protecting the rights and interests of the subjects, a collaborative ethical review agreement needs to be signed to clarify the ethical review responsibilities of all parties, to avoid repeated review, and to improve the efficiency and quality of ethical review in multi-center clinical trials of new drugs of TCM.

Regional homogeneity abnormalities of resting state brain activities in children with growth hormone deficiency.

Growth hormone deficiency (GHD) is a common developmental disorder in children characterized by low levels of growth hormone secretion, short stature, and multiple cognitive and behavioral problems, including hyperactivity, anxiety, and depression. However, the pathophysiology of this disorder remains unclear. In order to investigate abnormalities of brain functioning in children with GHD, we preformed functional magnetic resonance imaging and regional homogeneity (ReHo) analysis in 26 children with GHD and 15 age- and sex-matched healthy controls (HCs) in a resting state. Compared with HCs, children with GHD exhibited increased ReHo in the left putamen and decreased ReHo in the right precentral gyrus, reflecting a dysfunction of inhibitory control. Decreased ReHo was also identified in the orbital parts of the bilateral superior frontal gyrus and the medial part of the left superior frontal gyrus, a finding that correlated with the inappropriate anxiety and depression that are observed in this patient population. Our results provide imaging evidence of potential pathophysiologic mechanisms for the cognitive and behavioral abnormalities of children with GHD.

Abnormal amplitude of spontaneous low-frequency fluctuation in children with growth hormone deficiency: A resting-state functional magnetic resonance imaging study.

Growth hormone deficiency (GHD) is a developmental disorder caused by the partial or complete deficiency of growth hormone secreted by the pituitary gland, or its receptor. Patients with GHD are characterized by short stature, slow growth, and certain cognitive and behavioral abnormalities. Previous behavioral and neuroimaging studies indicate that GHD might affect the brain functional activity associated with cognitive and behavioral abilities. We thus investigated the spontaneous neural activity in children with GHD using amplitude of low-frequency fluctuation (ALFF) analysis. ALFF was calculated based on resting-state functional magnetic resonance imaging (rs-fMRI) data in 26 children with GHD and 15 age- and sex-matched healthy controls (HCs). Comparative analysis revealed that the ALFF of the right lingual gyrus and angular gyrus were significantly increased, while the ALFF of the right dorsolateral superior frontal gyrus, the left postcentral gyrus, superior parietal gyrus and middle temporal gyrus were significantly decreased in children with GHD relative to HCs. These findings support the presence of abnormal brain functional activity in children with GHD, which may account for the abnormal cognition and behavior, such as aggression, somatic complaints, attention deficits, and language withdrawal. This study provides imaging evidence for future studies on the pathophysiological mechanisms of abnormal behavior and cognition in children with GHD.

Effect of Conjugation Mode on Intramolecular Charge Transfer in Fabricating Acid-Responsive Fluorophores.

Solid-state acid-responsive materials are promising for the tunability of their intrinsic properties. However, the relationship between molecular structure and emission shift as a response to acid stimuli has not been systematically studied. Herein, we report the effect of protonation and subsequent intramolecular hydrogen bonding on the photophysical properties of compounds (MPP-s, MPP-d, and MPP-d-CN) with different conjugation modes between the electron-donating dimethoxyl phenyl and the electron-withdrawing benzothiazole ring. The results established that the stronger the intramolecular charge transfer feature of the compound, the smaller is the emission shift after acid stimuli. Our studies also indicated that the conjugation mode significantly affected the solid-state packing mode: MPP-s and MPP-d tended to form dimers, while MPP-d-CN exhibited the strongest aggregation-induced emission enhancement (AIEE). The exploration of structure-property relationship would provide experimental and theoretical guidance in designing acid-responsive molecular switches and developing high-performance AIEE-active luminogens.

Presurgical localization and spatial shift of resting state networks in patients with brain metastases.

Brain metastases are the most prevalent cerebral tumors. Resting state networks (RSNs) are involved in multiple perceptual and cognitive functions. Therefore, precisely localizing multiple RSNs may be extremely valuable before surgical resection of metastases, to minimize neurocognitive impairments. Here we aimed to investigate the reliability of independent component analysis (ICA) for localizing multiple RSNs from resting-state functional MRI (rs-fMRI) data in individual patients, and further evaluate lesion-related spatial shifts of the RSNs. Twelve patients with brain metastases and 14 healthy controls were recruited. Using an improved automatic component identification method, we successfully identified seven common RSNs, including: the default mode network (DMN), executive control network (ECN), dorsal attention network (DAN), language network (LN), sensorimotor network (SMN), auditory network (AN) and visual network (VN), in both individual patients and controls. Moreover, the RSNs in the patients showed a visible spatial shift compared to those in the controls, and the spatial shift of some regions was related to the tumor location, which may reflect a complicated functional mechanism - functional disruptions and reorganizations - caused by metastases. Besides, higher cognitive networks (DMN, ECN, DAN and LN) showed significantly larger spatial shifts than perceptual networks (SMN, AN and VN), supporting a functional dichotomy between the two network groups even in pathologic alterations associated with metastases. Overall, our findings provide evidence that ICA is a promising approach for presurgical localization of multiple RSNs from rs-fMRI data in individual patients. More attention should be paid to the spatial shifts of the RSNs before surgical resection.

Altered connectivity patterns among resting state networks in patients with ischemic white matter lesions.

White matter lesions (WMLs) have been associated with cognitive and motor decline. Resting state networks (RSNs) are spatially coherent patterns in the human brain and their interactions sustain our daily function. Therefore, investigating the altered intra- and inter-network connectivity among the RSNs may help to understand the association of WMLs with impaired cognitive and motor function. Here, we assessed alterations in functional connectivity patterns based on six well-defined RSNs-the default mode network (DMN), dorsal attention network (DAN), frontal-parietal control network (FPCN), auditory network (AN), sensory motor network (SMN) and visual network (VN)-in 15 patients with ischemic WMLs and 15 controls. In the patients, Spearman's correlation analysis was further performed between these alterations and cognitive test scores, including Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scores. Our results showed wide alterations of inter-network connectivity mainly involving the SMN, DMN, FPCN and DAN, and some alterations correlated with cognitive test scores in the patients. The reduced functional connectivities in the SMN-AN, SMN-VN, FPCN-AN, DAN-VN pairs may account for the cognitive and motor decline in patients with ischemic WMLs, while the increased functional connectivities in the DMN-AN, DMN-FPCN and DAN-FPCN pairs may reflect a functional network reorganization after damage to white matter. It is unexpected that altered intra-network connectivities were found within the AN and VN, which may explain the impairments in verbal fluency and information retrieval associated with WMLs. This study highlights the importance of functional connectivity in understanding how WMLs influence cognitive and behavior dysfunction.

Abnormal functional connectivity density in patients with ischemic white matter lesions: An observational study.

White matter lesions (WMLs) are frequently detected in elderly people. Previous structural and functional studies have demonstrated that WMLs are associated with cognitive and motor decline. However, the underlying mechanism of how WMLs lead to cognitive decline and motor disturbance remains unclear. We used functional connectivity density mapping (FCDM) to investigate changes in brain functional connectivity in 16 patients with ischemic WMLs and 13 controls. Both short- and long-range FCD maps were computed, and group comparisons were performed between the 2 groups. A correlation analysis was further performed between regions with altered FCD and cognitive test scores (Mini-Mental State Examination [MMSE] and Montreal Cognitive Assessment [MoCA]) in the patient group. We found that patients with ischemic WMLs showed reduced short-range FCD in the temporal cortex, primary motor cortex, and subcortical region, which may account for inadequate top-down attention, impaired motor, memory, and executive function associated with WMLs. The positive correlation between primary motor cortex and MoCA scores may provide evidence for the influences of cognitive function on behavioral performance. The inferior parietal cortex exhibited increased short-range FCD, reflecting a hyper bottom-up attention to compensate for the inadequate top-down attention for language comprehension and information retrieval in patients with WMLs. Moreover, the prefrontal and primary motor cortex showed increased long-range FCD and the former positively correlated with MoCA scores, which may suggest a strategy of cortical functional reorganization to compensate for motor and executive deficits. Our findings provide new insights into how WMLs cause cognitive and motor decline from cortical functional connectivity perspective.

Altered functional and structural connectivity networks in psychogenic non-epileptic seizures.

Psychogenic non-epileptic seizures (PNES) are paroxysmal behaviors that resemble epileptic seizures but lack abnormal electrical activity. Recent studies suggest aberrant functional connectivity involving specific brain regions in PNES. Little is known, however, about alterations of topological organization of whole-brain functional and structural connectivity networks in PNES. We constructed functional connectivity networks from resting-state functional MRI signal correlations and structural connectivity networks from diffusion tensor imaging tractography in 17 PNES patients and 20 healthy controls. Graph theoretical analysis was employed to compute network properties. Moreover, we investigated the relationship between functional and structural connectivity networks. We found that PNES patients exhibited altered small-worldness in both functional and structural networks and shifted towards a more regular (lattice-like) organization, which could serve as a potential imaging biomarker for PNES. In addition, many regional characteristics were altered in structural connectivity network, involving attention, sensorimotor, subcortical and default-mode networks. These regions with altered nodal characteristics likely reflect disease-specific pathophysiology in PNES. Importantly, the coupling strength of functional-structural connectivity was decreased and exhibited high sensitivity and specificity to differentiate PNES patients from healthy controls, suggesting that the decoupling strength of functional-structural connectivity might be an important characteristic reflecting the mechanisms of PNES. This is the first study to explore the altered topological organization in PNES combining functional and structural connectivity networks, providing a new way to understand the pathophysiological mechanisms of PNES.

A blind deconvolution approach to recover effective connectivity brain networks from resting state fMRI data.

A great improvement to the insight on brain function that we can get from fMRI data can come from effective connectivity analysis, in which the flow of information between even remote brain regions is inferred by the parameters of a predictive dynamical model. As opposed to biologically inspired models, some techniques as Granger causality (GC) are purely data-driven and rely on statistical prediction and temporal precedence. While powerful and widely applicable, this approach could suffer from two main limitations when applied to BOLD fMRI data: confounding effect of hemodynamic response function (HRF) and conditioning to a large number of variables in presence of short time series. For task-related fMRI, neural population dynamics can be captured by modeling signal dynamics with explicit exogenous inputs; for resting-state fMRI on the other hand, the absence of explicit inputs makes this task more difficult, unless relying on some specific prior physiological hypothesis. In order to overcome these issues and to allow a more general approach, here we present a simple and novel blind-deconvolution technique for BOLD-fMRI signal. In a recent study it has been proposed that relevant information in resting-state fMRI can be obtained by inspecting the discrete events resulting in relatively large amplitude BOLD signal peaks. Following this idea, we consider resting fMRI as 'spontaneous event-related', we individuate point processes corresponding to signal fluctuations with a given signature, extract a region-specific HRF and use it in deconvolution, after following an alignment procedure. Coming to the second limitation, a fully multivariate conditioning with short and noisy data leads to computational problems due to overfitting. Furthermore, conceptual issues arise in presence of redundancy. We thus apply partial conditioning to a limited subset of variables in the framework of information theory, as recently proposed. Mixing these two improvements we compare the differences between BOLD and deconvolved BOLD level effective networks and draw some conclusions.

Altered functional-structural coupling of large-scale brain networks in idiopathic generalized epilepsy.

The human brain is a large-scale integrated network in the functional and structural domain. Graph theoretical analysis provides a novel framework for analysing such complex networks. While previous neuroimaging studies have uncovered abnormalities in several specific brain networks in patients with idiopathic generalized epilepsy characterized by tonic-clonic seizures, little is known about changes in whole-brain functional and structural connectivity networks. Regarding functional and structural connectivity, networks are intimately related and share common small-world topological features. We predict that patients with idiopathic generalized epilepsy would exhibit a decoupling between functional and structural networks. In this study, 26 patients with idiopathic generalized epilepsy characterized by tonic-clonic seizures and 26 age- and sex-matched healthy controls were recruited. Resting-state functional magnetic resonance imaging signal correlations and diffusion tensor image tractography were used to generate functional and structural connectivity networks. Graph theoretical analysis revealed that the patients lost optimal topological organization in both functional and structural connectivity networks. Moreover, the patients showed significant increases in nodal topological characteristics in several cortical and subcortical regions, including mesial frontal cortex, putamen, thalamus and amygdala relative to controls, supporting the hypothesis that regions playing important roles in the pathogenesis of epilepsy may display abnormal hub properties in network analysis. Relative to controls, patients showed further decreases in nodal topological characteristics in areas of the default mode network, such as the posterior cingulate gyrus and inferior temporal gyrus. Most importantly, the degree of coupling between functional and structural connectivity networks was decreased, and exhibited a negative correlation with epilepsy duration in patients. Our findings suggest that the decoupling of functional and structural connectivity may reflect the progress of long-term impairment in idiopathic generalized epilepsy, and may be used as a potential biomarker to detect subtle brain abnormalities in epilepsy. Overall, our results demonstrate for the first time that idiopathic generalized epilepsy is reflected in a disrupted topological organization in large-scale brain functional and structural networks, thus providing valuable information for better understanding the pathophysiological mechanisms of generalized tonic-clonic seizures.

Topological fractionation of resting-state networks.

Exploring topological properties of human brain network has become an exciting topic in neuroscience research. Large-scale structural and functional brain networks both exhibit a small-world topology, which is evidence for global and local parallel information processing. Meanwhile, resting state networks (RSNs) underlying specific biological functions have provided insights into how intrinsic functional architecture influences cognitive and perceptual information processing. However, topological properties of single RSNs remain poorly understood. Here, we have two hypotheses: i) each RSN also has optimized small-world architecture; ii) topological properties of RSNs related to perceptual and higher cognitive processes are different. To test these hypotheses, we investigated the topological properties of the default-mode, dorsal attention, central-executive, somato-motor, visual and auditory networks derived from resting-state functional magnetic resonance imaging (fMRI). We found small-world topology in each RSN. Furthermore, small-world properties of cognitive networks were higher than those of perceptual networks. Our findings are the first to demonstrate a topological fractionation between perceptual and higher cognitive networks. Our approach may be useful for clinical research, especially for diseases that show selective abnormal connectivity in specific brain networks.

The synchronization of spontaneous BOLD activity predicts extraversion and neuroticism.

There is an increasing body of evidence pointing to a relationship between personality and brain markers. The purpose of this study was to identify the associations between personality dimensions of extraversion and neuroticism and the local synchronization of spontaneous blood oxygen level-dependent (BOLD) activity assessed by regional homogeneity (ReHo) approach. Our results revealed the significant negative correlation between neuroticism and ReHo in the left middle frontal gyrus, providing evidence for the left frontal activation involved in pleasant emotion. ReHo was correlated negatively with extraversion in the medial prefrontal cortex (MPFC), an important portion of the default mode network (DMN), thus further indicating the relationship between DMN and personality. In addition, ReHo in the insula, cerebellum and cingulate gyrus was correlated positively with extraversion, suggesting the associations between individual difference in extraversion and specific brain regions involved in affective processing. These findings shed light on the important relationship between the synchronization of spontaneous fluctuations and personality dimensions of extraversion and neuroticism, which provide further evidence for the neural underpinning of individual difference in personality traits.

Induction of systemic stress tolerance by brassinosteroid in Cucumis sativus.

• Brassinosteroids (BRs) are a new class of plant hormones that are essential for plant growth and development. Here, the involvement of BRs in plant systemic tolerance to biotic and abiotic stresses was studied. • The effects of 24-epibrassinolide (EBR) on plant stress tolerance were studied through the assessment of symptoms of photooxidative stress by chlorophyll fluorescence imaging pulse amplitude modulation, the analysis of gene expression using quantitative real-time PCR and the measurement of hydrogen peroxide (H2O2) production using a spectrophotometric assay or confocal laser scanning microscopy. • Treatment of primary leaves with EBR induced systemic tolerance to photooxidative stress in untreated upper and lower leaves. This was accompanied by the systemic accumulation of H2O2 and the systemic induction of genes associated with stress responses. Foliar treatment of EBR also enhanced root resistance to Fusarium wilt pathogen. Pharmacological study showed that EBR-induced systemic tolerance was dependent on local and systemic H2O2 accumulation. The expression of BR biosynthetic genes was repressed in EBR-treated leaves, but elevated significantly in untreated systemic leaves. Further analysis indicated that EBR-induced systemic induction of BR biosynthetic genes was mediated by systemically elevated H2O2. • These results strongly argue that local EBR treatment can activate the continuous production of H2O2, and the autopropagative nature of the reactive oxygen species signal, in turn, mediates EBR-induced systemic tolerance.

Developing new SSR markers from ESTs of pea (Pisum sativum L.).

The development of expressed sequence tags (ESTs) from pea has provided a useful source for mining novel simple sequence repeat (SSR) markers. In the present research, in order to find EST-derived SSR markers, 18 552 pea ESTs from the National Center for Biotechnology Information (NCBI) database were downloaded and assembled into 10 086 unigenes. A total of 586 microsatellites in 530 unigenes were identified, indicating that merely 5.25% of sequences contained SSRs. The most abundant SSRs within pea were tri-nucleotide repeat motifs, and among all the tri-nucleotide repeats, the motif GAA was the most abundant type. In total, 49 SSRs were used for primer design. EST-SSR loci were subsequently screened on 10 widely adapted varieties in China. Of these, nine loci showed polymorphic profiles that revealed two to three alleles per locus. The polymorphism information content value ranged from 0.18 to 0.58 with an average of 0.41. Furthermore, transferable analysis revealed that some of these loci showed transferability to faba bean. Because of their polymorphism and transferability, these nine novel EST-SSRs will be valuable tools for marker-assisted breeding and comparative mapping of pea in the future.

Generation and characterization of 11 novel est derived microsatellites from Vicia faba (Fabaceae).

PREMISE OF THE STUDY: Simple sequence repeat (SSR) markers were developed for faba bean using expressed sequence tags (ESTs) from the NCBI database to study for genetic diversity. • METHODS AND RESULTS: A total of 11 novel EST-SSR loci were generated and characterized when tested on four populations of 29 faba bean individuals from China and Europe. The number of alleles (A) ranged from 1 to 3 in each population, and observed heterozygosity (H(O)) and expected heterozygosity (H(E)) ranged from 0 to 0.5000 and 0.6400, respectively. Furthermore, transferable analysis revealed that eight of these loci (72.73%) amplified in Pisum sativum L., six of which (75.00%) detected polymorphism. • CONCLUSIONS: The developed markers in this study will provide valuable tools for genetic diversity, resource conservation, genetic mapping, and marker-assisted breeding of faba bean in the future.

Selective trans-cinnamic acid uptake impairs [Ca2+]cyt homeostasis and growth in Cucumis sativus L.

To obtain insight into interspecies interactions mediated by allelochemicals, the response of cucumber (Cucumis sativus L. cv Jinyan No.4) and figleaf gourd (Cucurbita ficifolia Bouché) seedlings to trans-cinnamic acid (CA) (1) was investigated. While trans-CA is an autotoxin in cucumber root exudates, figleaf gourd is resistant to it. Cucumber, however, had a high rate of trans-CA uptake by the roots, leading to reduced root growth. The trans-CA treatment also resulted in an intracellular release of Ca(2+) from the vacuole to the cytoplasm, and, thus, an increased [Ca(2+)](cyt) level accompanied by gradual loss of cell viability in cucumber roots. Taken together, these results suggest that [Ca(2+)](cyt) homeostatic disturbance is one of the primary triggers for trans-CA phytotoxicity in cucumber.