Human salience is distinctive and reliable information in matching pedestrians across disjoint camera views. In this paper, we exploit the pair wise salience distribution relationship between pedestrian images, and solve the person re-identification problem by proposing a salience matching strategy. To handle the misalignment problem in pedestrian images, patch matching is adopted and patch salience is estimated. Matching patches with inconsistent salience brings penalty. Images of the same person are recognized by minimizing the salience matching cost. Furthermore, our salience matching is tightly integrated with patch matching in a unified structural Rank SVM learning framework. The effectiveness of our approach is validated on the VIPeR dataset and the CUHK Campus dataset. It outperforms the state-of-the-art methods on both datasets.
Distinction of species within the complex (i.e., and ) is relevant for epidemiological purposes and antifungal management. Two commercial matrix-assisted laser desorption ionization-time of flight mass spectrometry systems were comprehensively evaluated for the identification of fungi within this complex. None of the species ( and ) were identified correctly by Vitek mass spectrometry (MS ) v2.0 Diagnosis system and Bruker Biotyper MS v3.1, but all were correct by the Vitek MS Research Use Only system. The Bruker ClinProTools software showed 100% recognition capability and cross validation for the discrimination of and . Using Vitek MS Research Use Only and Bruker ClinProTools can overcome limitations of the Vitek MS Diagnosis and Bruker Biotyper databases in the identification of complex.
To investigate whether the is present in Eastern China and to verify the utility of a new screening process. Phenotype observation, PCR assay targeting a hypothetical nonribosomal peptide synthetase ( ) gene, phylogenetic analysis of and multilocus sequence typing were used to screen and identify strains of from 839 presumptive isolates. Eighty-nine (89/839, 10.6%) of the presumptive isolates produced white colonies on tryptone soya agar plates. Of the white-colony isolates, six (6/89, 7%) were , 75 (75/89, 84%) were and eight (8/89, 9%) were other bacteria. The PCR-based method targeting the gene can simultaneously identify and distinguish and . All representative sequences of generated in this study were deposited in GenBank under accession numbers SJTU F20002, KT767581; SJTU F20269, KT767582; SJTU F20419, KT767583; SJTU F20420, KT767584; SJTU F20124, KT767585; SJTU F21164, KT767586; SJTU F21285, KT767587; SJTU F21224, KT767588; SJTU F21155, KT767589; SJTU F21294, KT767590; SJTU F20030, KT767591; SJTU F20044, KT767592; SJTU F20135, KT767593; SJTU F20123, KT767594; SJTU F21319, KT767595, respectively. All the new sequence types (STs) were submitted to a multilocus sequence typing database and the assigned ST numbers are ST3261 (151-469-20-101-145-150-131), ST3262 (12-3-1-1-4-4-410) and ST3267 (2-471-2-2-6-3-2).
The present study aimed to investigate genetic polymorphisms and pharmacogenetic variability in the pharmacodynamics of prasugrel, a new oral antiplatelet agent, in healthy Han Chinese subjects. The inhibition of adenosine diphosphate-induced platelet aggregation was measured pre- and post-administration using the VerifyNow P2Y12 assay. The genetic sequence of exons and previously reported SNPs in the gene were investigated. A total of 28 variations were identified in . The SNPs in two regions of the gene, from rs3737224 to rs822442, and from rs1214331 to rs12566888, probably play important roles in prasugrel pharmacodynamics. Further studies with larger sample sizes are recommended to explore the clinical importance of SNPs in prasugrel and other antiplatelet therapies. Original submitted 18 December 2012; Revision submitted 26 April 2013
To measure global gene expression in primary advanced colorectal cancer patients who have undergone fluorouracil, leucovorin and oxaliplatin (FOLFOX4) chemotherapy and screen valuable biomarkers to predict the effects of chemotherapy. Samples from primary advanced colorectal cancer patients were collected. The effects of chemotherapy were evaluated, and patients were divided into an experimental group and a control group. Cancerous tissue gene expression profiles were detected by chip technology. Valuable biomarkers were screened by bioinformatic analysis. Immunohistochemical analysis was performed to characterize the pattern of and expression. HOXB8 and KLK11 signal probe values were analyzed using receiver operating characteristic analysis. There were differentially expressed genes in the two groups. HOXB8 and KLK11 proteins were observed in the nucleus and on the outside of the cancer cells, respectively. Their prediction accuracies were 79.9 and 76.7%, respectively. HOXB8 and KLK11 may be classified as valuable biomarkers, as they can predict the effects of FOLFOX4 chemotherapy in primary advanced colorectal cancer patients.
Microglia are myeloid cells of the CNS that participate both in normal CNS function and in disease. We investigated the molecular signature of microglia and identified 239 genes and 8 microRNAs that were uniquely or highly expressed in microglia versus myeloid and other immune cells. Of the 239 genes, 106 were enriched in microglia as compared with astrocytes, oligodendrocytes and neurons. This microglia signature was not observed in microglial lines or in monocytes recruited to the CNS, and was also observed in human microglia. We found that TGF-beta was required for the in vitro development of microglia that express the microglial molecular signature characteristic of adult microglia and that microglia were absent in the CNS of TGF-beta 1 deficient mice. Our results identify a unique microglial signature that is dependent on TGF-beta signaling and provide insights into microglial biology and the possibility of targeting microglia for the treatment of CNS disease.
Compound identification is widely recognized as a major bottleneck for modern metabolomic approaches and high-throughput nontargeted characterization of complex matrices. To tackle this challenge, an automated platform entitled computer-assisted structure identification (CASI) was designed and developed in order to accelerate and standardize the identification of compound structures. In the first step of the process, CAST automatically searches mass spectral libraries for matches using a NIST MS Search algorithm, which proposes structural candidates for experimental spectra from two-dimensional gas chromatography with time-of-flight mass spectrometry (GC x GC-TOF-MS) measurements, each with an associated match factor. Next, quantitative structure-property relationship (QSPR) models implemented in CASI predict three specific parameters to enhance the confidence for correct compound identification, which were Kovats Index (KO for the first dimension (1D) separation, relative retention time for the second dimension separation (2DrelRT) and boiling point (BP). In order to reduce the impact of chromatographic variability on the second dimension retention time, a concept based upon hypothetical reference points from linear regressions of a deuterated n-alkanes reference system was introduced, providing a more stable relative retention time measurement. Predicted values for KI and 2DrelRT were calculated and matched with experimentally derived values. Boiling points derived from 1D separations were matched with predicted boiling points, calculated from the chemical structures of the candidates. As a last step, CASI combines the NIST MS Search match factors (NIST MF) with up to three predicted parameter matches from the QSPR models to generate a combined CASI Score representing the measure of confidence for the identification. Threshold values were applied to the CASI Scores assigned to proposed structures, which improved the accuracy for the classification of true/false positives and true/false negatives. Results for the identification of compounds have been validated, and it has been demonstrated that identification using CASI is more accurate than using MIST MS Search alone. CASI is an easily accessible web-interfaced software platform which represents an innovative, high-throughput system that allows fast and accurate identification of constituents in complex matrices, such as those requiring 2D separation techniques.
This paper reports a large-scale experiment aimed at evaluating how state-of-art computer vision systems perform in identifying plants compared to human expertise. A subset of the evaluation dataset used within LifeCLEF 2014 plant identification challenge was therefore shared with volunteers of diverse expertise, ranging from the leading experts of the targeted flora to inexperienced test subjects. In total, 16 human runs were collected and evaluated comparatively to the 27 machine-based runs of LifeCLEF challenge. One of the main outcomes of the experiment is that machines are still far from outperforming the best expert botanists at the image-based plant identification competition. On the other side, the best machine runs are competing with experienced botanists and clearly outperform beginners and inexperienced test subjects. This shows that the performances of automated plant identification systems are very promising and may open the door to a new generation of ecological surveillance systems.
Over the past decade conceptual and empirical research in operations management has embraced the idea that collaborative supplier–buyer relationships are a source of competitive advantage for manufacturing firms. Anecdotal evidence from the Japanese and U.S. automotive industry and emerging research suggests that inter-organizational identification of suppliers with their buyers, termed supplier-to-buyer identification, is an unexplored factor of relational advantage. This study presents a model and empirical test that supplier-to-buyer identification fosters superior operational performance by enhancing trust, supplier relation-specific investments, and information exchange. Through a survey of 346 automotive supplier–buyer relationships, the findings show that supplier-to-buyer identification directly impacts supplier relationship-specific investments and information exchange, although most of the latter effect is mediated by trust. The findings also indicate that supplier relation-specific investments and information exchange play different but complementary roles in influencing operational performance. The results suggest new directions for supplier–buyer relationship research in operations management and important managerial implications.
Strawberry ( × ) fruits contain high concentrations of flavonoids. In unripe strawberries, the flavonoids are mainly represented by proanthocyanidins (PAs), while in ripe fruits the red-coloured anthocyanins also accumulate. Most of the structural genes leading to PA biosynthesis in strawberry have been characterized, but no information is available on their transcriptional regulation. In the expression of the PA biosynthetic genes is specifically induced by a ternary protein complex, composed of AtTT2 (AtMYB123), AtTT8 (AtbHLH042) and AtTTG1 (WD40-repeat protein). A strategy combining yeast-two-hybrid screening and agglomerative hierarchical clustering of transcriptomic and metabolomic data was undertaken to identify strawberry PA regulators. Among the candidate genes isolated, four were similar to and ( and , respectively) and two encode putative negative regulators ( and Δ). Interestingly, and were found to complement the and transparent testa mutants, respectively. In addition, they interacted in yeast and activated the (anthocyanidin reductase) gene promoter when coexpressed in protoplasts. Taken together, these results demonstrated that and are the respective functional homologues of and , providing new tools for modifying PA content and strawberry fruit quality.