The Coda of the Transient Response in a Sensitive Cochlea: A Computational Modeling Study

In a sensitive cochlea, the basilar membrane response to transient excitation of any kind–normal acoustic or artificial intracochlear excitation–consists of not only a primary impulse but also a coda of delayed secondary responses with varying amplitudes but similar spectral content around the characteristic frequency of the measurement location. The coda, sometimes referred to as echoes or ringing, has been described as a form of local, short term memory which may influence the ability of the auditory system to detect gaps in an acoustic stimulus such as speech. Depending on the individual cochlea, the temporal gap between the primary impulse and the following coda ranges from once to thrice the group delay of the primary impulse (the group delay of the primary impulse is on the order of a few hundred microseconds). The coda is physiologically vulnerable, disappearing when the cochlea is compromised even slightly. The multicomponent sensitive response is not yet completely understood. We use a physiologically-based, mathematical model to investigate (i) the generation of the primary impulse response and the dependence of the group delay on the various stimulation methods, (ii) the effect of spatial perturbations in the properties of mechanically sensitive ion channels on the generation and separation of delayed secondary responses. The model suggests that the presence of the secondary responses depends on the wavenumber content of a perturbation and the activity level of the cochlea. In addition, the model shows that the varying temporal gaps between adjacent coda seen in experiments depend on the individual profiles of perturbations. Implications for non-invasive cochlear diagnosis are also discussed.     

The Antitumor Activity of the Novel Compound Jesridonin on Human Esophageal Carcinoma Cells

Jesridonin, a small molecule obtained through the structural modification of Oridonin, has extensive antitumor activity. In this study, we evaluated both its in vitro activity in the cancer cell line EC109 and its in vivo effect on tumor xenografts in nude mice. Apoptosis induced by Jesridonin was determined using an MTT assay, Annexin-V FITC assay and Hoechest 33258 staining. Apoptosis via mitochondrial and death receptor pathways were confirmed by detecting the regulation of MDM2, p53, and Bcl-2 family members and by activation of caspase-3/-8/-9. In addition, vena caudalis injection of Jesridonin showed significant inhibition of tumor growth in the xenograft model, and Jesridonin-induced cell apoptosis in tumor tissues was determined using TUNEL. Biochemical serum analysis of alkaline phosphatase (ALP), alanine transaminase (ALT), aspartate transaminase (AST), gamma-glutamyl transferase (GGT), total protein (TP) and albumin (ALB) indicated no obvious effects on liver function. Histopathological examination of the liver, kidney, lung, heart and spleen revealed no signs of JD-induced toxicity. Taken together, these results demonstrated that Jesridonin exhibits antitumor activity in human esophageal carcinomas EC109 cells both in vitro and in vivo and demonstrated no adverse effects on major organs in nude mice. These studies provide support for new drug development.     

Systematic analysis of multigene predictors in gastric cancer exploiting gene expression signature

Gastric cancer (GC) is the second most common cause of cancer death worldwide but could be more curable if diagnosed at an earlier stage. At present, the capability to predict the efficaciousness of molecular diagnosis for GC for each patient remains elusive. The purpose of this study was to identify tumor biomarkers through systems analysis of multigene predictors exploiting the available data resource. In this study, we investigated the top 10% overexpressed genes in GC from five data sets of the Oncomine platform, with 265 GC samples versus 174 normal gastric mucosa samples. Sixteen candidate genes were identified as predictors of GC, of which 14 genes were verified through the comparison of expression levels in specimens from normal (chronic gastritis, 21 samples) and GC groups (38 samples). In addition, unique molecular portraits of diffuse adenocarcinoma (DA), intestinal adenocarcinoma (IA), and mixed adenocarcinoma (MA) were studied through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis, where DA showed higher extracellular matrix alteration while IA and MA showed higher cell-cycle alteration than other types. We also found that the elevated expressions of genes during GC progression were independent of gene mutations, and high core-binding factor subunit β expression is correlated with a high overall survival rate in GC patients. Our research may provide an efficient clinical diagnosis of GC at an early stage with high accuracy and thus help improve the overall survival rate through early therapeutic interventions.     

Identification of chalcone synthase genes and their expression patterns reveal pollen abortion in cotton

Chalcone synthase (CHS) is a key enzyme and producing flavonoid derivatives as well play a vital roles in sustaining plant growth and development. However, the systematic and comprehensive analysis of CHS genes in island cotton (G. barbadense) has not been reported yet especially response to cytoplasmic male sterility (CMS). To fill this knowledge gap, a genome-wide investigation of CHS genes were studied in island cotton. A total of 20 GbCHS genes were identified and grouped into five GbCHSs. The gene structure analysis revealed that most of GbCHS genes consisted of two exons and one intron, and 20 motifs were identified. Twenty five pairs duplicated events (12 GbCHS genes) were identified including 23 segmental duplication pairs and two tandem duplication events, representing that GbCHS gene family amplification mainly owned to segmental duplication events and evolving slowly. Gene expression analysis exhibited that the GbCHS family genes presented a diversity expression patterns in various organs of cotton. Coupled with functional predictions and gene expression, the abnormal expression of GbCHS06, 10, 16 and 19 might be associated with pollen abortion of CMS line in island cotton. Conclusively, GbCHS genes exhibited diversity and conservation in many aspects, which will help to better understand functional studies and a reference for CHS research in island cotton and other plants.     

Mitochondrial ribosomal protein S9M is involved in male gametogenesis and seed development in Arabidopsis

• Mitochondrial function is critical for cell vitality in all eukaryotes including plants. Although plant mitochondria contain many proteins, few have been studied in the context of plant development and physiology.
• We used knock‐down mutant RPS9M to study its important role in male gametogenesis and seed development in Arabidopsis thaliana.
• Knock‐down of RPS9M in the rps9m‐3 mutant led to abnormal pollen development and impaired pollen tube growth. In addition, both embryo and endosperm development were affected. Phenotype analysis revealed that the rps9m‐3 mutant contained a lower amount of endosperm and nuclear proteins, and both embryo cell division and embryo pattern were affected, resulting in an abnormal and defective embryo. Lowering the level of RPS9M in rps9m‐3 affects mitochondrial ribosome biogenesis, energy metabolism and production of ROS.
• Our data revealed that RPS9M plays important roles in normal gametophyte development and seed formation, possibly by sustaining mitochondrial function.

     

Production Task Queue Optimization Based on Multi-Attribute Evaluation for Complex Product Assembly Workshop

The production task queue has a great significance for manufacturing resource allocation and scheduling decision. Man-made qualitative queue optimization method has a poor effect and makes the application difficult. A production task queue optimization method is proposed based on multi-attribute evaluation. According to the task attributes, the hierarchical multi-attribute model is established and the indicator quantization methods are given. To calculate the objective indicator weight, criteria importance through intercriteria correlation (CRITIC) is selected from three usual methods. To calculate the subjective indicator weight, BP neural network is used to determine the judge importance degree, and then the trapezoid fuzzy scale-rough AHP considering the judge importance degree is put forward. The balanced weight, which integrates the objective weight and the subjective weight, is calculated base on multi-weight contribution balance model. The technique for order preference by similarity to an ideal solution (TOPSIS) improved by replacing Euclidean distance with relative entropy distance is used to sequence the tasks and optimize the queue by the weighted indicator value. A case study is given to illustrate its correctness and feasibility.     

Trust-Enhanced Cloud Service Selection Model Based on QoS Analysis

Cloud computing technology plays a very important role in many areas, such as in the construction and development of the smart city. Meanwhile, numerous cloud services appear on the cloud-based platform. Therefore how to how to select trustworthy cloud services remains a significant problem in such platforms, and extensively investigated owing to the ever-growing needs of users. However, trust relationship in social network has not been taken into account in existing methods of cloud service selection and recommendation. In this paper, we propose a cloud service selection model based on the trust-enhanced similarity. Firstly, the direct, indirect, and hybrid trust degrees are measured based on the interaction frequencies among users. Secondly, we estimate the overall similarity by combining the experience usability measured based on Jaccard’s Coefficient and the numerical distance computed by Pearson Correlation Coefficient. Then through using the trust degree to modify the basic similarity, we obtain a trust-enhanced similarity. Finally, we utilize the trust-enhanced similarity to find similar trusted neighbors and predict the missing QoS values as the basis of cloud service selection and recommendation. The experimental results show that our approach is able to obtain optimal results via adjusting parameters and exhibits high effectiveness. The cloud services ranking by our model also have better QoS properties than other methods in the comparison experiments.