Matching Natural Language Sentences with Hierarchical Sentence Factorization

Semantic matching of natural language sentences or identifying the relationship between two sentences is a core research problem underlying many natural language tasks. Depending on whether training data is available, prior research has proposed both unsupervised distance-based schemes and supervised deep learning schemes for sentence matching. However, previous approaches either omit or fail to fully utilize the ordered, hierarchical, and flexible structures of language objects, as well as the interactions between them. In this paper, we propose Hierarchical Sentence Factorization---a technique to factorize a sentence into a hierarchical representation, with the components at each different scale reordered into a "predicate-argument" form. The proposed sentence factorization technique leads to the invention of: 1) a new unsupervised distance metric which calculates the semantic distance between a pair of text snippets by solving a penalized optimal transport problem while preserving the logical relationship of words in the reordered sentences, and 2) new multi-scale deep learning models for supervised semantic training, based on factorized sentence hierarchies. We apply our techniques to text-pair similarity estimation and text-pair relationship classification tasks, based on multiple datasets such as STSbenchmark, the Microsoft Research paraphrase identification (MSRP) dataset, the SICK dataset, etc. Extensive experiments show that the proposed hierarchical sentence factorization can be used to significantly improve the performance of existing unsupervised distance-based metrics as well as multiple supervised deep learning models based on the convolutional neural network (CNN) and long short-term memory (LSTM).Comment: Accepted by WWW 2018, 10 page

The role of EGFR mutation as a prognostic factor in survival after diagnosis of brain metastasis in non-small cell lung cancer: A systematic review and meta-analysis

Abstract Background The brain is a common site for metastasis in non-small-cell lung cancer (NSCLC). This study was designed to evaluate the relationship between the mutational of the epidermal growth factor receptor (EGFR) and overall survival (OS) in NSCLC patients with brain metastases. Methods Searches were performed in PubMed, EmBase, and the Cochrane Library to identify studies evaluating the association of EGFR mutation with OS in NSCLC patients through September 2017. Results 4373 NSCLC patients with brain metastases in 18 studies were involved. Mutated EGFR associated with significantly improved OS compared with wild type. Subgroup analyses suggested that this relationship persisted in studies conducted in Eastern, with retrospective design, with sample size ≥500, mean age of patients ≥65.0 years, percentage male < 50.0%, percentage of patients receiving tyrosine kinase inhibitor ≥30.0%. Finally, although significant publication bias was observed using the Egger test, the results were not changed after adjustment using the trim and fill method. Conclusions This meta-analysis suggests that EGFR mutation is an important predictive factor linked to improved OS for NSCLC patients with brain metastases. It can serve as a useful index in the prognostic assessment of NSCLC patients with brain metastases

The evolution of vertebrate tetraspanins: gene loss, retention, and massive positive selection after whole genome duplications

<p>Abstract</p> <p>Background</p> <p>The vertebrate tetraspanin family has many features which make it suitable for preserving the imprint of ancient sequence evolution and amenable for phylogenomic analysis. So we believe that an in-depth analysis of the tetraspanin evolution not only provides more complete understanding of tetraspanin biology, but offers new insights into the influence of the two rounds of whole genome duplication (2R-WGD) at the origin of vertebrates.</p> <p>Results</p> <p>A detailed phylogeny of vertebrate tetraspanins was constructed by using multiple lines of information, including sequence-based phylogenetics, key structural features, intron configuration and genomic synteny. In particular, a total of 38 modern tetraspanin ortholog lineages in bony vertebrates have been identified and subsequently classified into 17 ancestral lineages existing before 2R-WGD. Based on this phylogeny, we found that the ohnolog retention rate of tetraspanins after 2R-WGD was three times as the average (a rate similar to those of transcription factors and protein kinases). This high rate didn't increase the tetrapanin family size, but changed the family composition, possibly by displacing vertebrate-specific gene lineages with the lineages conserved across deuterostomes. We also found that the period from 2R-WGD to recent time is controlled by gene losses. Meanwhile, positive selection has been detected on 80% of the branches right after 2R-WGDs, which declines significantly on both magnitude and extensity on the following speciation branches. Notably, the loss of mammalian RDS2 is accompanied by strong positive selection on mammalian ROM1, possibly due to gene loss-induced compensatory evolution.</p> <p>Conclusions</p> <p>First, different from transcription factors and kinases, high duplicate retention rate after 2R-WGD didn't increase the tetraspanin family size but just reshaped the family composition. Second, the evolution of tetraspanins right after 2R-WGD had been impacted by a massive wave of gene loss and positive selection on coding sequences. Third, the lingering effect of 2R-WGD on tetraspanin gene loss and positive selection might last for 300-400 million years.</p

Functional maturation of immature β cells: A roadblock for stem cell therapy for type 1 diabetes

Type 1 diabetes mellitus (T1DM) is a chronic autoimmune disease caused by the specific destruction of pancreatic islet β cells and is characterized as the absolute insufficiency of insulin secretion. Current insulin replacement therapy supplies insulin in a non-physiological way and is associated with devastating complications. Experimental islet transplantation therapy has been proven to restore glucose homeostasis in people with severe T1DM. However, it is restricted by many factors such as severe shortage of donor sources, progressive loss of donor cells, high cost, etc. As pluripotent stem cells have the potential to give rise to all cells including islet β cells in the body, stem cell therapy for diabetes has attracted great attention in the academic community and the general public. Transplantation of islet β-like cells differentiated from human pluripotent stem cells (hPSCs) has the potential to be an excellent alternative to islet transplantation. In stem cell therapy, obtaining β cells with complete insulin secretion in vitro is crucial. However, after much research, it has been found that the β-like cells obtained by in vitro differentiation still have many defects, including lack of adult-type glucose stimulated insulin secretion, and multi-hormonal secretion, suggesting that in vitro culture does not allows for obtaining fully mature β-like cells for transplantation. A large number of studies have found that many transcription factors play important roles in the process of transforming immature to mature human islet β cells. Furthermore, PDX1, NKX6.1, SOX9, NGN3, PAX4, etc., are important in inducing hPSC differentiation in vitro. The absent or deficient expression of any of these key factors may lead to the islet development defect in vivo and the failure of stem cells to differentiate into genuine functional β-like cells in vitro. This article reviews β cell maturation in vivo and in vitro and the vital roles of key molecules in this process, in order to explore the current problems in stem cell therapy for diabetes

Electrocatalysis of Oxygen Reduction on Te-Modified Platinum Stepped Crystal Surfaces

Te-modified platinum single-crystal surfaces in the [011̅] zone have been used as model electrocatalysts for oxygen reduction reaction (ORR). The results clearly show that (1) except for Pt(111), all other electrodes display enhanced ORR activity when Te is deposited on the surface; (2) the intrinsic ORR activity for Pt(hkl) decreases in the order of Pt(322) > Pt(755) > Pt(977) > Pt(111) > Pt(311) > Pt(100), while the enhancement factor for ORR with Te modification decreases in the order of Pt(100) > Pt(311) > Pt(977) > Pt(755) > Pt(322); (3) metallic Te and its charge transfer to Pt as well as the consequent lower d-band center and OHad binding energy are probably the reasons for the enhanced electrocatalysis for ORR with Te modification; and (4) the inhibition of Te at Pt(111) as well as the smaller extent for the enhancement of Te at Pt(S)-[n(111) × (100)] with longer terraces in the kinetic region for ORR are a result of partial oxidation of Te. The weaker electronic interaction of Te with the Pt substrate is probably the origin of its facile oxidation at lower potential. Our results imply that modification of Pt with species that can transfer electrons to Pt may be an efficient strategy to enhance the ORR activity.This work was supported by the National Natural Science Foundation of China (No. 22172151, 21972131, and 21832004). E.H. gratefully acknowledged the International Professorship by USTC and financial support from the Ministerio de Ciencia e Innovación (project PID2022–137350NB-I00)