How and what kind of cities benefit from the development of digital inclusive finance? Evidence from the upgrading of export in Chinese cities

Employing Chinese customs data and the Peking University Digital Financial Inclusion Index of China, this paper studies the impact of China’s digital finance development on the upgrading of export at the city level and further explores the heterogeneity across cities and the mechanisms through which digital finance influences export upgrading. Benchmark results suggest that digital inclusive finance can significantly promote the upgrading of export. The heterogeneity analysis shows that cities with a smaller size, lower wage, higher human capital level, and better location advantage experience greater facilitating effects of digital inclusive finance on promoting export upgrading. It suggests that, compared with ‘icing on the cake’, the digital inclusive finance plays a better role in ‘offering fuel in snowy weather’, whereas full exertion of the inclusiveness of digital finance requires higher human capital and location advantage. Further mechanism analysis shows that innovation effect and market effect are the main channels where digital inclusive finance promotes the upgrading of a city’s export

"Why Should I Review This Paper?" Unifying Semantic, Topic, and Citation Factors for Paper-Reviewer Matching

As many academic conferences are overwhelmed by a rapidly increasing number of paper submissions, automatically finding appropriate reviewers for each submission becomes a more urgent need than ever. Various factors have been considered by previous attempts on this task to measure the expertise relevance between a paper and a reviewer, including whether the paper is semantically close to, shares topics with, and cites previous papers of the reviewer. However, the majority of previous studies take only one of these factors into account, leading to an incomprehensive evaluation of paper-reviewer relevance. To bridge this gap, in this paper, we propose a unified model for paper-reviewer matching that jointly captures semantic, topic, and citation factors. In the unified model, a contextualized language model backbone is shared by all factors to learn common knowledge, while instruction tuning is introduced to characterize the uniqueness of each factor by producing factor-aware paper embeddings. Experiments on four datasets (one of which is newly contributed by us) across different fields, including machine learning, computer vision, information retrieval, and data mining, consistently validate the effectiveness of our proposed UniPR model in comparison with state-of-the-art paper-reviewer matching methods and scientific pre-trained language models

Weakly Supervised Multi-Label Classification of Full-Text Scientific Papers

Instead of relying on human-annotated training samples to build a classifier, weakly supervised scientific paper classification aims to classify papers only using category descriptions (e.g., category names, category-indicative keywords). Existing studies on weakly supervised paper classification are less concerned with two challenges: (1) Papers should be classified into not only coarse-grained research topics but also fine-grained themes, and potentially into multiple themes, given a large and fine-grained label space; and (2) full text should be utilized to complement the paper title and abstract for classification. Moreover, instead of viewing the entire paper as a long linear sequence, one should exploit the structural information such as citation links across papers and the hierarchy of sections and paragraphs in each paper. To tackle these challenges, in this study, we propose FUTEX, a framework that uses the cross-paper network structure and the in-paper hierarchy structure to classify full-text scientific papers under weak supervision. A network-aware contrastive fine-tuning module and a hierarchy-aware aggregation module are designed to leverage the two types of structural signals, respectively. Experiments on two benchmark datasets demonstrate that FUTEX significantly outperforms competitive baselines and is on par with fully supervised classifiers that use 1,000 to 60,000 ground-truth training samples.Comment: 12 pages; Accepted to KDD 2023 (Code: https://github.com/yuzhimanhua/FUTEX

Seed-Guided Fine-Grained Entity Typing in Science and Engineering Domains

Accurately typing entity mentions from text segments is a fundamental task for various natural language processing applications. Many previous approaches rely on massive human-annotated data to perform entity typing. Nevertheless, collecting such data in highly specialized science and engineering domains (e.g., software engineering and security) can be time-consuming and costly, without mentioning the domain gaps between training and inference data if the model needs to be applied to confidential datasets. In this paper, we study the task of seed-guided fine-grained entity typing in science and engineering domains, which takes the name and a few seed entities for each entity type as the only supervision and aims to classify new entity mentions into both seen and unseen types (i.e., those without seed entities). To solve this problem, we propose SEType which first enriches the weak supervision by finding more entities for each seen type from an unlabeled corpus using the contextualized representations of pre-trained language models. It then matches the enriched entities to unlabeled text to get pseudo-labeled samples and trains a textual entailment model that can make inferences for both seen and unseen types. Extensive experiments on two datasets covering four domains demonstrate the effectiveness of SEType in comparison with various baselines.Comment: 9 pages; Accepted to AAAI 2024 (Code: https://github.com/yuzhimanhua/SEType

Cardiac-derived CTRP9 protects against myocardial ischemia/reperfusion injury via calreticulin-dependent inhibition of apoptosis.

Cardiokines play an essential role in maintaining normal cardiac functions and responding to acute myocardial injury. Studies have demonstrated the heart itself is a significant source of C1q/TNF-related protein 9 (CTRP9). However, the biological role of cardiac-derived CTRP9 remains unclear. We hypothesize cardiac-derived CTRP9 responds to acute myocardial ischemia/reperfusion (MI/R) injury as a cardiokine. We explored the role of cardiac-derived CTRP9 in MI/R injury via genetic manipulation and a CTRP9-knockout (CTRP9-KO) animal model. Inhibition of cardiac CTRP9 exacerbated, whereas its overexpression ameliorated, left ventricular dysfunction and myocardial apoptosis. Endothelial CTRP9 expression was unchanged while cardiomyocyte CTRP9 levels decreased after simulated ischemia/`reperfusion (SI/R) in vitro. Cardiomyocyte CTRP9 overexpression inhibited SI/R-induced apoptosis, an effect abrogated by CTRP9 antibody. Mechanistically, cardiac-derived CTRP9 activated anti-apoptotic signaling pathways and inhibited endoplasmic reticulum (ER) stress-related apoptosis in MI/R injury. Notably, CTRP9 interacted with the ER molecular chaperone calreticulin (CRT) located on the cell surface and in the cytoplasm of cardiomyocytes. The CTRP9-CRT interaction activated the protein kinase A-cAMP response element binding protein (PKA-CREB) signaling pathway, blocked by functional neutralization of the autocrine CTRP9. Inhibition of either CRT or PKA blunted cardiac-derived CTRP9\u27s anti-apoptotic actions against MI/R injury. We further confirmed these findings in CTRP9-KO rats. Together, these results demonstrate that autocrine CTRP9 of cardiomyocyte origin protects against MI/R injury via CRT association, activation of the PKA-CREB pathway, ultimately inhibiting cardiomyocyte apoptosis

EST analysis of gene expression in the tentacle of Cyanea capillata

AbstractJellyfish, Cyanea capillata, has an important position in head patterning and ion channel evolution, in addition to containing a rich source of toxins. In the present study, 2153 expressed sequence tags (ESTs) from the tentacle cDNA library of C. capillata were analyzed. The initial ESTs consisted of 198 clusters and 818 singletons, which revealed approximately 1016 unique genes in the data set. Among these sequences, we identified several genes related to head and foot patterning, voltage-dependent anion channel gene and genes related to biological activities of venom. Five kinds of proteinase inhibitor genes were found in jellyfish for the first time, and some of them were highly expressed with unknown functions

Transplanted adult human hepatic stem/progenitor cells prevent histogenesis of advanced hepatic fibrosis in mice induced by carbon tetrachloride

Transplantation of adult human hepatic stem/progenitor cells (hHSPCs) has been considered as an alternative therapy, replacing donor liver transplantation to treat liver cirrhosis. This study assessed the antifibrotic effects of hHSPCs in mice with fibrosis induced by carbon tetrachloride (CCl4) and examined the actions of hHSPCs on the fibrogenic activity of human hepatic stellate cells (HSCs) in a coculture system. Isolated hHSPCs expressed stem/progenitor cell phenotypic markers. Mice were given CCl4 (twice weekly for 7 weeks) and hHSPC transplantation weekly. CCl4 induced advanced fibrosis (bridging fibrosis and cirrhosis) in mice, which was prevented by hHSPC transplantation. The liver of hHSPC-transplanted mice showed only occasional short septa and focal parenchymal fibrosis, and a 50% reduction in hepatic collagen, assessed by Sirius red stain histomorphometry. Moreover, the proteins for α-smooth muscle actin (α-SMA) and collagen I were decreased. While α-SMA, collagen α1(I), and tissue inhibitor of metalloproproteinase-1 mRNAs were decreased, matrix metalloproteinase (MMP)-1 mRNA was increased, consistent with decreased fibrogenesis. MMP-2 and transforming growth factor-β were not affected. Alanine aminotransferase and aspartate aminotransferase were lower, suggesting improvement of liver function/damage. In coculture, hHSPCs elicited changes of α-SMA and fibrogenic molecules in HSCs similar to those observed in vivo, providing evidence for a functional link between hHSPCs and HSCs. A decreased HSC proliferation was noted. Thus, transplantation of hHSPCs prevents histogenesis of advanced liver fibrosis caused by CCl4. hHSPCs mediate downregulation of HSC activation coincident with modulation of fibrogenic molecule expression, leading to suppression of fibrogenesis both in vivo and in vitro

Direct Conversion of Fibroblasts to Neurons by Reprogramming PTB-Regulated MicroRNA Circuits

SummaryThe induction of pluripotency or trans-differentiation of one cell type to another can be accomplished with cell-lineage-specific transcription factors. Here, we report that repression of a single RNA binding polypyrimidine-tract-binding (PTB) protein, which occurs during normal brain development via the action of miR-124, is sufficient to induce trans-differentiation of fibroblasts into functional neurons. Besides its traditional role in regulated splicing, we show that PTB has a previously undocumented function in the regulation of microRNA functions, suppressing or enhancing microRNA targeting by competitive binding on target mRNA or altering local RNA secondary structure. A key event during neuronal induction is the relief of PTB-mediated blockage of microRNA action on multiple components of the REST complex, thereby derepressing a large array of neuronal genes, including miR-124 and multiple neuronal-specific transcription factors, in nonneuronal cells. This converts a negative feedback loop to a positive one to elicit cellular reprogramming to the neuronal lineage