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Tong Chen,1– 3 Shiquan Wu,1 Ling Feng,4 SiYu Long,1 Yu Liu,1,2 WenQian Lu,5 Wenya Chen,1 Guoai Hong,1 Li Zhou,1 Fang Wang,1 Yuechan Luo,1 Hequn Zou1,3,5 1Department of Nephrology, South China Hospital of Shenzhen University, Shenzhen, People’s Republic of China; 2Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, National Regional Key Technology Engineering Laboratory for Medical Ultrasound School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen, People’s Republic of China; 3Department of Nephrology, The Third Affiliated Hospital, Southern Medical University, Guangzhou, People’s Republic of China; 4Department of Nephrology, Shenzhen Hospital, Southern Medical University, Shenzhen, People’s Republic of China; 5Department of Medicine, The Chinese University of Hong Kong, Shenzhen, People’s Republic of ChinaCorrespondence: Hequn Zou, School of Medicine, The Chinese University of Hong Kong, Shenzhen, People’s Republic of China, Email zouhequn@cuhk.edu.cnBackground: The annual prevalence of metabolic syndrome (MetS) is increasing. Therefore, early screening and recognition of MetS are critical. This study aimed to evaluate the association between high-density lipoprotein (HDL) subclasses and MetS and to examine whether they could serve as early indicators in a Chinese community-based population with normal high-density lipoprotein cholesterol (HDL-C) levels.Methods: We used microfluidic chip technology to measure HDL subclasses in 463 people with normal HDL levels in 2018. We assessed how HDL subclasses correlated with and predicted insulin resistance (IR) and metabolic syndrome (MetS), evaluated by homeostatic model insulin resistance index (HOMA-IR) and the 2009 International Diabetes Federation (IDF), the American Heart Association (AHA), and the National Heart, Lung, and Blood Institute (NHLBI) criteria, respectively. We used correlation tests and ROC curves for the analysis.Results: The results indicate

At the end of the 20th century, scholars represented by Forceville dived into the construction and representation of metaphors using various modalities, leading the shift of metaphor studies towards multimodality, which consequently put the study of multimodal metaphors in the spotlight. English textbooks, as a combination of visual and linguistic modes of expression, contain a large number of metaphors. From the perspective of conceptual blending theory, the paper explores the construction and meaning of multimodal metaphors of Chinese culture in three compulsory high school English textbooks of Beijing Normal University Press. It is found that these three compulsory high school English textbooks of Beijing Normal University Press (BNUP) contain many multimodal metaphors of Chinese culture, and these multimodal metaphors can activate student’s cultural background knowledge and convey the communicative intention of the pictures, thus arousing students’ interest in Chinese culture and fostering cultural confidence.

Protein language models have demonstrated significant potential in the field of protein engineering. However, current protein language models primarily operate at the residue scale, which limits their ability to provide information at the atom level. This limitation prevents us from fully exploiting the capabilities of protein language models for applications involving both proteins and small molecules. In this paper, we propose ESM-AA (ESM All-Atom), a novel approach that enables atom-scale and residue-scale unified molecular modeling. ESM-AA achieves this by pre-training on multi-scale code-switch protein sequences and utilizing a multi-scale position encoding to capture relationships among residues and atoms. Experimental results indicate that ESM-AA surpasses previous methods in protein-molecule tasks, demonstrating the full utilization of protein language models. Further investigations reveal that through unified molecular modeling, ESM-AA not only gains molecular knowledge but also retains its understanding of proteins. The source codes of ESM-AA are publicly released at https://github.com/zhengkangjie/ESM-AA., Comment: ICML2024 camera-ready, update some experimental results, add github url

Gai Ge,1 Jingzhe Shang,2,3 Tian Gan,1 Zhiming Chen,1 Chun Pan,1 Youming Mei,1 Siyu Long,4 Aiping Wu,2,3 Hongsheng Wang1,5,6 1Laboratory of Mycobacteria, Institute of Dermatology, Chinese Academy of Medical Sciences and Peking Union Medical College, Nanjing, People’s Republic of China; 2Center for Systems Medicine, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People’s Republic of China; 3Suzhou Institute of Systems Medicine, Suzhou, People’s Republic of China; 4Department of Dermatology, Beijing Chao-Yang Hospital & Capital Medical University, Beijing, People’s Republic of China; 5National Center for Sexually Transmitted Disease and Leprosy Control, China Centers for Disease Control and Prevention, Nanjing, People’s Republic of China; 6Centre for Global Health, School of Public Health, Nanjing Medical University, Nanjing, People’s Republic of ChinaCorrespondence: Hongsheng Wang, Institute of Dermatology, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 12 Jiang-wang-miao Street, Nanjing, Jiangsu Province, People’s Republic of China, Tel/Fax +86 258 5478953, Email whs33@vip.sina.comPurpose: Psoriasis (Ps) and leprosy are chronic inflammatory skin disorders, characterised by enhanced innate and adaptive immunity. Ps and leprosy rarely coexist. The molecular immune mechanism of the Ps and leprosy rarely coexistence is unclear.Patients and Methods: RNA-sequencing (RNA-seq) was performed on 20 patients with Ps, 5 adults with lepromatous leprosy (L-lep), and 5 patients with tuberculoid leprosy (T-lep) to analyse the differentially expressed genes (DEGs) between them. Moreover, the biological mechanism of Ps and leprosy was explored by Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, Gene Ontology (GO) analysis, Gene Set Enrichment Analysis analysis, and protein–protein interaction (PPI) analyses. Finally, 13 DEGs of 10 skin biopsies of Ps patients

Canonical relation extraction aims to extract relational triples from sentences, where the triple elements (entity pairs and their relationship) are mapped to the knowledge base. Recently, methods based on the encoder-decoder architecture are proposed and achieve promising results. However, these methods cannot well utilize the entity information, which is merely used as augmented training data. Moreover, they are incapable of representing novel entities, since no embeddings have been learned for them. In this paper, we propose a novel framework, Bi-Encoder-Decoder (BED), to solve the above issues. Specifically, to fully utilize entity information, we employ an encoder to encode semantics of this information, leading to high-quality entity representations. For novel entities, given a trained entity encoder, their representations can be easily generated. Experimental results on two datasets show that, our method achieves a significant performance improvement over the previous state-of-the-art and handle novel entities well without retraining.

The adsorption performances of adsorbents to dyes are hard to maintain in a wide pH range because most of the reactions are pH-dependent, developing a cost-effective strategy to break the pH-limitation is significant. In this study, an amphoteric self-floating adsorbent (Am-SA) was synthesized by hollow silica microsphere surface modification, which was useful to capture anionic acid orange 7 (AO7) and cationic crystal violet (CV) dyes, but the adsorption performances were also greatly affected by pH. Fortunately, a co-precipitation phenomenon was noticed when the AO7 and CV solutions were mixed with a 1:1 molecule ratio. The precise structures of AO7 and CV molecules were constructed and the AO7-CV-H2O mixed system was structured by Materials Studio. Besides, this system was involved in a dynamic simulation to reveal the mechanism of the co-precipitation phenomenon. The simulation results showed H2O molecules dispersed out of the system via thermal motions within 30 ps, but the AO7 and CV molecules aggregated to each other via electrostatic attractions. The energy calculations also demonstrated the electrostatic attraction between AO7 and CV is the dominant factor that induced the aggregation. The aggregation phenomena were also observed in various mixed cationic–anionic dyes systems. The removals of dyes significantly improved in a wide pH range in the mixed systems as the captures of the aggregated dye clusters were much easier than that of independent dye molecules, and both co-precipitation and adsorption contributed to it. Proper utilization of the aggregation behaviors between dyes can be regarded as a prospective strategy in cost-effective treatments. © 2022

The adsorption performances of adsorbents to dyes are hard to maintain in a wide pH range because most of the reactions are pH-dependent, developing a cost-effective strategy to break the pH-limitation is significant. In this study, an amphoteric self-floating adsorbent (Am-SA) was synthesized by hollow silica microsphere surface modification, which was useful to capture anionic acid orange 7 (AO7) and cationic crystal violet (CV) dyes, but the adsorption performances were also greatly affected by pH. Fortunately, a co-precipitation phenomenon was noticed when the AO7 and CV solutions were mixed with a 1:1 molecule ratio. The precise structures of AO7 and CV molecules were constructed and the AO7-CV-H2O mixed system was structured by Materials Studio. Besides, this system was involved in a dynamic simulation to reveal the mechanism of the co-precipitation phenomenon. The simulation results showed H2O molecules dispersed out of the system via thermal motions within 30 ps, but the AO7 and CV molecules aggregated to each other via electrostatic attractions. The energy calculations also demonstrated the electrostatic attraction between AO7 and CV is the dominant factor that induced the aggregation. The aggregation phenomena were also observed in various mixed cationic–anionic dyes systems. The removals of dyes significantly improved in a wide pH range in the mixed systems as the captures of the aggregated dye clusters were much easier than that of independent dye molecules, and both co-precipitation and adsorption contributed to it. Proper utilization of the aggregation behaviors between dyes can be regarded as a prospective strategy in cost-effective treatments. © 2022

Drug design is a crucial step in the drug discovery cycle. Recently, various deep learning-based methods design drugs by generating novel molecules from scratch, avoiding traversing large-scale drug libraries. However, they depend on scarce experimental data or time-consuming docking simulation, leading to overfitting issues with limited training data and slow generation speed. In this study, we propose the zero-shot drug design method DESERT (Drug dEsign by SkEtching and geneRaTing). Specifically, DESERT splits the design process into two stages: sketching and generating, and bridges them with the molecular shape. The two-stage fashion enables our method to utilize the large-scale molecular database to reduce the need for experimental data and docking simulation. Experiments show that DESERT achieves a new state-of-the-art at a fast speed., Comment: NeurIPS 2022 camera-ready

The adsorption performances of adsorbents to dyes are hard to maintain in a wide pH range because most of the reactions are pH-dependent, developing a cost-effective strategy to break the pH-limitation is significant. In this study, an amphoteric self-floating adsorbent (Am-SA) was synthesized by hollow silica microsphere surface modification, which was useful to capture anionic acid orange 7 (AO7) and cationic crystal violet (CV) dyes, but the adsorption performances were also greatly affected by pH. Fortunately, a co-precipitation phenomenon was noticed when the AO7 and CV solutions were mixed with a 1:1 molecule ratio. The precise structures of AO7 and CV molecules were constructed and the AO7-CV-H2O mixed system was structured by Materials Studio. Besides, this system was involved in a dynamic simulation to reveal the mechanism of the co-precipitation phenomenon. The simulation results showed H2O molecules dispersed out of the system via thermal motions within 30 ps, but the AO7 and CV molecules aggregated to each other via electrostatic attractions. The energy calculations also demonstrated the electrostatic attraction between AO7 and CV is the dominant factor that induced the aggregation. The aggregation phenomena were also observed in various mixed cationic–anionic dyes systems. The removals of dyes significantly improved in a wide pH range in the mixed systems as the captures of the aggregated dye clusters were much easier than that of independent dye molecules, and both co-precipitation and adsorption contributed to it. Proper utilization of the aggregation behaviors between dyes can be regarded as a prospective strategy in cost-effective treatments. © 2022

Chun Pan,1 Jingzhe Shang,2,3 Haiqin Jiang,1 Ying Shi,1 Wenyue Zhang,1 Jingshu Xiong,1 Youming Mei,1 Siyu Long,1 Gai Ge,1 Zhenzhen Wang,1 Ziwei Wu,1 Hongsheng Wang,1 Aiping Wu2,3 1Institute of Dermatology, Chinese Academy of Medical Sciences and Peking Union Medical College, Nanjing, 210046, People’s Republic of China; 2Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100005, People’s Republic of China; 3Suzhou Institute of Systems Medicine, Suzhou, 215123, People’s Republic of ChinaCorrespondence: Hongsheng WangInstitute of Dermatology, Chinese Academy of Medical Sciences and Peking Union Medical College, Nanjing, 210046, People’s Republic of ChinaEmail whs33@vip.sina.comAiping WuInstitute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100005, People’s Republic of ChinaEmail wap@ism.cams.cnBackground: Given their similar appearance and histology, halo nevi (HN) were considered as a type of vitiligo. However, whether HN have stronger immune response than stable vitiligo (VL) remains unclear. In addition, the molecular alterations in HN compared with normal nevocytic nevi (NN) and primary cutaneous melanoma (MM) must be determined. This study aimed to systematically characterize the molecular immunological features of HN.Methods: Skin samples from patients with HN, VL, NN, and MM were obtained with informed consent. Each of the four groups underwent transcriptome sequencing and data analysis were for pairwise comparison. Quantitative real-time PCR (RT-qPCR) was conducted to confirm the transcriptional expression of some differentially expressed genes (DEGs) that were closely related to immunity.Results: A total of 441 and 1507 DEGs were found in the HN/NN and HN/MM groups, respectively. Compared with those of VL, HN lesions contained 162 up-regulated DEGs and 12 down-regulated DEGs. Bioinformatics analysis showed that the up-regulated genes i

Machine reading comprehension (MRC) is the task that asks a machine to answer questions based on a given context. For Chinese MRC, due to the non-literal and non-compositional semantic characteristics, Chinese idioms pose unique challenges for machines to understand. Previous studies tend to treat idioms separately without fully exploiting the relationship among them. In this paper, we first define the concept of literal meaning coverage to measure the consistency between semantics and literal meanings for Chinese idioms. With the definition, we prove that the literal meanings of many idioms are far from their semantics, and we also verify that the synonymic relationship can mitigate this inconsistency, which would be beneficial for idiom comprehension. Furthermore, to fully utilize the synonymic relationship, we propose the synonym knowledge enhanced reader. Specifically, for each idiom, we first construct a synonym graph according to the annotations from a high-quality synonym dictionary or the cosine similarity between the pre-trained idiom embeddings and then incorporate the graph attention network and gate mechanism to encode the graph. Experimental results on ChID, a large-scale Chinese idiom reading comprehension dataset, show that our model achieves state-of-the-art performance., Comment: 12 pages, 3 figure, accepted by COLING2020

There has been constant research about audit fee determinants across the world over the last three decades. However, there has been no research about the audit fee determinants in the French audit market. The purpose of this report is to investigate whether the audit fee determinants which have been proved to be significant in previous studies are also effective in the French audit market. Tests are conducted on all public companies in the U.K. and 160 top companies in France using regression models. The empirical results show that the U.K. audit fee determinants model is fairly powerful, while the French audit fee determinants model is much less effective. In addition, variables in the two models present distinct characteristics and a great amount of independent variables in the French audit fee determinant model are not statistically significant. Key words: audit fee determinants model U.K. French

There has been constant research about audit fee determinants across the world over the last three decades. However, there has been no research about the audit fee determinants in the French audit market. The purpose of this report is to investigate whether the audit fee determinants which have been proved to be significant in previous studies are also effective in the French audit market. Tests are conducted on all public companies in the U.K. and 160 top companies in France using regression models. The empirical results show that the U.K. audit fee determinants model is fairly powerful, while the French audit fee determinants model is much less effective. In addition, variables in the two models present distinct characteristics and a great amount of independent variables in the French audit fee determinant model are not statistically significant. Key words: audit fee determinants model U.K. French

There has been constant research about audit fee determinants across the world over the last three decades. However, there has been no research about the audit fee determinants in the French audit market. The purpose of this report is to investigate whether the audit fee determinants which have been proved to be significant in previous studies are also effective in the French audit market. Tests are conducted on all public companies in the U.K. and 160 top companies in France using regression models. The empirical results show that the U.K. audit fee determinants model is fairly powerful, while the French audit fee determinants model is much less effective. In addition, variables in the two models present distinct characteristics and a great amount of independent variables in the French audit fee determinant model are not statistically significant. Key words: audit fee determinants model U.K. French

There has been constant research about audit fee determinants across the world over the last three decades. However, there has been no research about the audit fee determinants in the French audit market. The purpose of this report is to investigate whether the audit fee determinants which have been proved to be significant in previous studies are also effective in the French audit market. Tests are conducted on all public companies in the U.K. and 160 top companies in France using regression models. The empirical results show that the U.K. audit fee determinants model is fairly powerful, while the French audit fee determinants model is much less effective. In addition, variables in the two models present distinct characteristics and a great amount of independent variables in the French audit fee determinant model are not statistically significant. Key words: audit fee determinants model U.K. French