The capacity for somatic embryogenesis was studied in lec1, lec2 and fus3 mutants of Arabidopsis thaliana (L.) Heynh. It was found that contrary to the response of wild-type cultures, which produced somatic embryos via an efficient, direct process (65-94% of responding explants), lec mutants were strongly impaired in their embryogenic response. Cultures of the mutants formed somatic embryos at a low frequency, ranging from 0.0 to 3.9%. Moreover, somatic embryos were formed from callus tissue through an indirect route in the lec mutants. Total repression of embryogenic potential was observed in double (lec1 lec2, lec1 fus3, lec2 fus3) and triple (fus3 lec1 lec2) mutants. Additionally, mutants were found to exhibit efficient shoot regenerability via organogenesis from root explants. These results provide evidence that, besides their key role in controlling many different aspects of Arabidopsis zygotic embryogenesis, LEC/FUS genes are also essential for in vitro somatic embryogenesis induction. Furthermore, temporal and spatial patterns of auxin distribution during somatic embryogenesis induction were analyzed using transgenic Arabidopsis plants expressing GUS driven by the DR5 promoter. Analysis of data indicated auxin accumulation was rapid in all tissues of the explants of both wild type and the lec2-1 mutant, cultured on somatic embryogenesis induction medium containing 2,4-D. This observation suggests that loss of embryogenic potential in the lec2 mutant in vitro is not related to the distribution of exogenously applied auxin and LEC genes likely function downstream in auxin-induced somatic embryogenesis.

In this survey paper, we systematically summarize existing literature on bearing fault diagnostics with machine learning (ML) and data mining techniques. While conventional ML methods, including artificial neural network (ANN), principal component analysis (PCA), support vector machines (SVM), etc., have been successfully applied to the detection and categorization of bearing faults for decades, recent developments in deep learning (DL) algorithms in the last five years have sparked renewed interest in both industry and academia for intelligent machine health monitoring. In this paper, we first provide a brief review of conventional ML methods, before taking a deep dive into the state-of-the-art DL algorithms for bearing fault applications. Specifically, the superiority of DL based methods over conventional ML methods are analyzed in terms of fault feature extraction and classification performances; many new functionalities enabled by DL techniques are also summarized. In addition, to obtain a more intuitive insight, a comparative study is conducted on the classification accuracy of different algorithms utilizing the open source Case Western Reserve University (CWRU) bearing dataset. Finally, to facilitate the transition on applying various DL algorithms to bearing fault diagnostics, detailed recommendations and suggestions are provided for specific application conditions such as the setup environment, the data size, and the number of sensors and sensor types. Future research directions to further enhance the performance of DL algorithms on health monitoring are also discussed.

Oregon 97403-1229 (J.R.) Arabidopsis (Arabidopsis thaliana) was transformed with a redox-sensing green fluorescent protein (reduction-oxidationsensitive green fluorescent protein [roGFP]), with expression targeted to either the cytoplasm or to the mitochondria. Both the mitochondrial and cytosolic forms are oxidation-reduction sensitive, as indicated by a change in the ratio of 510 nm light (green light) emitted following alternating illumination with 410 and 474 nm light. The 410/474 fluorescence ratio is related to the redox potential (in millivolts) of the organelle, cell, or tissue. Both forms of roGFP can be reduced with dithiothreitol and oxidized with hydrogen peroxide. The average resting redox potentials for roots are 2318 mV for the cytoplasm and 2362 mV for the mitochondria. The elongation zone of the Arabidopsis root has a more oxidized redox status than either the root cap or meristem. Mitochondria are much better than the cytoplasm, as a whole, at buffering changes in redox. The data show that roGFP is redox sensitive in plant cells and that this sensor makes it possible to monitor, in real time, dynamic changes in redox in vivo.Cellular redox status influences many processes in plants, including apoptosis (Cai and Jones, 1999), oxidative defense mechanisms (Foyer and Noctor, 2005), senescence (Groten et al., 2005), allosteric control of enzyme activities, transcription and translation (Apel and Hirt, 2004), and a variety of signal transduction pathways (Drö ge, 2002;Ermak and Davies, 2002;Neill et al., 2002). Yet, as central as is redox status to these processes, the redox potentials (oxidationreduction potential) of living plant cells have rarely been measured during the occurrence of these activities (Renew et al., 2005). Rather, most often plant tissues are homogenized and the homogenates subsequently assayed, either with redox-sensing electrodes, or, by measuring the ratios of the reduced and oxidized forms of glutathione and ascorbate, the two principal redox regulators in living systems (Foyer and Noctor, 2003). Recently the redox state of plant tissues has also been assessed using the dyes 5-(and 6-) carboxy-2#, 7#-dichlorodihydrofluorescein diacetate (C-400; Jiang et al., 2003) and dihydrofluorescein diacetate (N. Smirnoff, personal communication). While such approaches allow one to sum the oxidized and reduced species, and thereby to infer the overall redox status of a tissue, it is not possible with these approaches to obtain a measure of redox potential at the time the events of interest are occurring. Moreover, whole tissue homogenization does not allow one to more finely resolve redox status within the various compartments and organelles comprising a typical plant cell, nor does this approach allow for an assessment of the redox status of the cell wall. As well, homogenizing a tissue precludes the possibility of monitoring dynamic changes of redox status, including reversibility. As a consequence, plant biologists lack knowledge of the rapidity of redox changes in plant cells.Rece...

The wall-associated kinase (WAK) gene family, one of the receptor-like kinase (RLK) gene families in plants, plays important roles in cell expansion, pathogen resistance, and heavy-metal stress tolerance in Arabidopsis (Arabidopsis thaliana). Through a reiterative database search and manual reannotation, we identified 125 OsWAK gene family members from rice (Oryza sativa) japonica cv Nipponbare; 37 (approximately 30%) OsWAKs were corrected/reannotated from earlier automated annotations. Of the 125 OsWAKs, 67 are receptor-like kinases, 28 receptor-like cytoplasmic kinases, 13 receptor-like proteins, 12 short genes, and five pseudogenes. The two-intron gene structure of the Arabidopsis WAK/WAK-Likes is generally conserved in OsWAKs; however, extra/missed introns were observed in some OsWAKs either in extracellular regions or in protein kinase domains. In addition to the 38 OsWAKs with full-length cDNA sequences and the 11 with rice expressed sequence tag sequences, gene expression analyses, using tiling-microarray analysis of the 20 OsWAKs on chromosome 10 and reverse transcription-PCR analysis for five OsWAKs, indicate that the majority of identified OsWAKs are likely expressed in rice. Phylogenetic analyses of OsWAKs, Arabidopsis WAK/WAK-Likes, and barley (Hordeum vulgare) HvWAKs show that the OsWAK gene family expanded in the rice genome due to lineage-specific expansion of the family in monocots. Localized gene duplications appear to be the primary genetic event in OsWAK gene family expansion and the 125 OsWAKs, present on all 12 chromosomes, are mostly clustered.

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BackgroundHuman epidermal growth factor receptor-2 (HER2) is regarded as an important and promising target in the treatment of HER2-positive breast cancers. However, the correlation of clinicopathological characteristics and prognostic significance of HER2 overexpression in gastric cancer patients remains unclear. Our aim was to clarify this issue.MethodsEmbase, PubMed, and the Cochrane Library were searched for relevant articles published up to May 2016. Outcomes of interest contained sex, age, tumor size, tumor site, tumor node metastasis (TNM) stage, distant metastasis, lymph node metastasis, Lauren’s classification, differentiation grade, lymphovascular invasion, neural invasion, and multivariate analysis data for overall survival.ResultsA total of 41 studies of 17,494 gastric cancer patients were identified with HER2 test. HER2 positive rate was 19.07% (95% CI = 9.16, 28.98). There existed statistical significance between HER2 overexpression and patients’ prognosis (RR = 1.47, 95% CI = 1.09, 1.98). Male patients (OR = 1.48, 95% CI = 1.34, 1.65), proximal tumors (OR = 1.25, 95% CI = 1.07, 1.47), intestinal-type tumors (OR = 3.37, 95% CI = 2.54, 4.47), advanced stage cancers (OR = 1.35, 95% CI = 1.10, 1.66), lymph node metastasis (OR = 1.26, 95% CI = 1.14, 1.41), well-differentiated cancers (OR = 1.79, 95% CI = 1.15, 2.76), and distant metastasis (OR = 1.91, 95% CI = 1.08, 3.38) were correlated with higher HER2 expression rates. However, no statistical differences existed in age, tumor size, lymphovascular invasion, or neural invasion. Subgroup analysis revealed that HER2 expression rates reported in articles from Asian (19.52%) countries were quantitatively higher than those from European (16.91%) areas. Results were consistent with those reports that define HER2 status according to trastuzumab for gastric cancer (ToGA) criteria.ConclusionThis study showed that HER2 overexpression was associated with poor prognosis in gastric cancer patients. HER2 positive rates may be associated with sex, tumor site, TNM staging system, distant metastasis, lymph node metastasis, Lauren’s classification, and differentiation grade in gastric cancer patients. The HER2 expression rate in Asians may be higher than that in Europeans. This study offers a convenient way for doctors to select patients for relevant HER2 detection and following treatment.Electronic supplementary materialThe online version of this article (doi:10.1186/s12957-017-1132-5) contains supplementary material, which is available to authorized users.

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