A Novel Route for Preparation of Hollow Carbon Nanospheres Without Introducing Template

A newly developed route for the synthesis of hollow carbon nanospheres without introducing template under hydrothermal conditions was reported. Hollow carbon nanospheres with the diameter of about 100 nm were synthesized using alginate as reagent only. Many instruments were applied to characterize the morphologies and structures of carbon hollow nanospheres, such as XRD, TEM, and Raman spectroscopy. The possible formation and growth mechanism of carbon hollow spheres were discussed on the basis of the investigation of reaction influence factors, such as temperature, time, and content. The findings would be useful for the synthesis of more materials with hollow structure and for the potential use in many aspects. The loading of SnO2on the surface of carbon hollow spheres was processed, and its PL property was also characterized

Rank-Aware Negative Training for Semi-Supervised Text Classification

Semi-supervised text classification-based paradigms (SSTC) typically employ the spirit of self-training. The key idea is to train a deep classifier on limited labeled texts and then iteratively predict the unlabeled texts as their pseudo-labels for further training. However, the performance is largely affected by the accuracy of pseudo-labels, which may not be significant in real-world scenarios. This paper presents a Rank-aware Negative Training (RNT) framework to address SSTC in learning with noisy label manner. To alleviate the noisy information, we adapt a reasoning with uncertainty-based approach to rank the unlabeled texts based on the evidential support received from the labeled texts. Moreover, we propose the use of negative training to train RNT based on the concept that ``the input instance does not belong to the complementary label''. A complementary label is randomly selected from all labels except the label on-target. Intuitively, the probability of a true label serving as a complementary label is low and thus provides less noisy information during the training, resulting in better performance on the test data. Finally, we evaluate the proposed solution on various text classification benchmark datasets. Our extensive experiments show that it consistently overcomes the state-of-the-art alternatives in most scenarios and achieves competitive performance in the others. The code of RNT is publicly available at:https://github.com/amurtadha/RNT.Comment: TACL 202

G2PTL: A Pre-trained Model for Delivery Address and its Applications in Logistics System

Text-based delivery addresses, as the data foundation for logistics systems, contain abundant and crucial location information. How to effectively encode the delivery address is a core task to boost the performance of downstream tasks in the logistics system. Pre-trained Models (PTMs) designed for Natural Language Process (NLP) have emerged as the dominant tools for encoding semantic information in text. Though promising, those NLP-based PTMs fall short of encoding geographic knowledge in the delivery address, which considerably trims down the performance of delivery-related tasks in logistic systems such as Cainiao. To tackle the above problem, we propose a domain-specific pre-trained model, named G2PTL, a Geography-Graph Pre-trained model for delivery address in Logistics field. G2PTL combines the semantic learning capabilities of text pre-training with the geographical-relationship encoding abilities of graph modeling. Specifically, we first utilize real-world logistics delivery data to construct a large-scale heterogeneous graph of delivery addresses, which contains abundant geographic knowledge and delivery information. Then, G2PTL is pre-trained with subgraphs sampled from the heterogeneous graph. Comprehensive experiments are conducted to demonstrate the effectiveness of G2PTL through four downstream tasks in logistics systems on real-world datasets. G2PTL has been deployed in production in Cainiao's logistics system, which significantly improves the performance of delivery-related tasks

Comparative study on the thermoelectric effect of parent oxypnictides LaTTAsO (TT = Fe, Ni)

The thermopower and Nernst effect were investigated for undoped parent compounds LaFeAsO and LaNiAsO. Both thermopower and Nernst signal in iron-based LaFeAsO are significantly larger than those in nickel-based LaNiAsO. Furthermore, abrupt changes in both thermopower and Nernst effect are observed below the structural phase transition temperature and spin-density wave (SDW) type antiferromagnetic (AFM) order temperature in Fe-based LaFeAsO. On the other hand, Nernst effect is very small in the Ni-based LaNiAsO and it is weakly temperature-dependent, reminiscent of the case in normal metals. We suggest that the effect of SDW order on the spin scattering rate should play an important role in the anomalous temperature dependence of Hall effect and Nernst effect in LaFeAsO. The contrast behavior between the LaFeAsO and LaNiAsO systems implies that the LaFeAsO system is fundamentally different from the LaNiAsO system and this may provide clues to the mechanism of high $T_c$ superconductivity in the Fe-based systems.Comment: 6 pages, 6 figure

Emotional urgency predicts bipolar symptoms, severity, and suicide attempt better than non-emotional impulsivity: a cross-sectional study

IntroductionEmotional urgency is an emotion-based subdimension of trait impulsivity that is more clinically relevant to psychopathology and disorders of emotion dysfunction than non-emotional subdimensions (i.e., lack of perseverance, sensation seeking, lack of premeditation). However, few studies have examined the relative effects of emotional urgency in bipolar disorder. This cross-sectional study aimed to establish the clinical relevance of emotional urgency in bipolar disorders by (1) explicating clinically relevant correlates of emotional urgency and (2) comparing its effects against non-emotional impulsivity subdimensions.Methods and resultsA total of 150 individuals with bipolar disorder were recruited between October 2021 and January 2023. Zero-order correlations found that emotional urgency had the greatest effect on bipolar symptoms (r = 0.37 to 0.44). Multiple two-step hierarchical regression models showed that (1) positive urgency predicted past manic symptomology and dysfunction severity (b = 1.94, p < 0.001 and 0.35 p < 0.05, respectively), (2) negative urgency predicted current depression severity, and (3) non-emotional facets of impulsivity had smaller effects on bipolar symptoms and dysfunction by contrast, and were non-significant factors in the final step of all regression models (b < 0.30, ns); Those who had a history of attempted suicide had significantly greater levels of emotional urgency (Cohen’s d = –0.63).DiscussionNotwithstanding the study’s limitations, our findings expand status quo knowledge beyond the perennial relationship between non-emotion-based impulsivity and bipolar disorder and its implications

Multi-scale integrative analyses identify THBS2+ cancer-associated fibroblasts as a key orchestrator promoting aggressiveness in early-stage lung adenocarcinoma.

Rationale: Subsets of patients with early-stage lung adenocarcinoma (LUAD) have a poor post-surgical course after curative surgery. However, biomarkers stratifying this high-risk subset and molecular underpinnings underlying the aggressive phenotype remain unclear. Methods: We integrated bulk and single-cell transcriptomics, proteomics, secretome and spatial profiling of clinical early-stage LUAD samples to identify molecular underpinnings that promote the aggressive phenotype. Results: We identified and validated THBS2, at multi-omic levels, as a tumor size-independent biomarker that robustly predicted post-surgical survival in multiple independent clinical cohorts of early-stage LUAD. Furthermore, scRNA-seq data revealed that THBS2 is exclusively derived from a specific cancer-associated fibroblast (CAF) subset that is distinct from CAFs defined by classical markers. Interestingly, our data demonstrated that THBS2 was preferentially secreted via exosomes in early-stage LUAD tumors with high aggressiveness, and its levels in the peripheral plasma associated with short recurrence-free survival. Further characterization showed that THBS2-high early-stage LUAD was characterized by suppressed antitumor immunity. Specifically, beyond tumor cells, THBS2+ CAFs mainly interact with B and CD8+ T lymphocytes as well as macrophages within tumor microenvironment of early-stage LUAD, and THBS2-high LUAD was associated with decreased immune cell infiltrates but increased immune exhaustion marker. Clinically, high THBS2 expression predicted poor response to immunotherapies and short post-treatment survival of patients. Finally, THBS2 recombinant protein suppressed ex vivo T cells proliferation and promoted in vivo LUAD tumor growth and distant micro-metastasis. Conclusions: Our multi-level analyses uncovered tumor-specific THBS2+ CAFs as a key orchestrator promoting aggressiveness in early-stage LUAD

An absence of platelet activation following thalidomide treatment in vitro or in vivo

Increased risk of thromboembolism and platelet hyperreactivity has been reported in patients receiving thalidomide therapy. Whether thalidomide induces platelet activation directly or through other factors remains unclear. The aim of this study was to evaluate the effect of thalidomide on platelet activation under resting conditions in vitro and in vivo. Isolated human or mouse platelets were treated with different concentrations of thalidomide (10, 50 and 100 μg/ml) for 60 min at 37°C followed by analysis of platelet surface expression of platelet receptors GPIbα, GPVI, αIIbβ3 and P-selectin, and PAC-1 or fibrinogen binding, by flow cytometry and collagen- or ADP-induced platelet aggregation. In addition, thalidomide (200 mg/kg) was intraperitoneally injected into mice for analysis of the effect of thalidomide on platelet activation in vivo. No increased expression of P-selectin, PAC-1 or fibrinogen binding was observed in either human and mouse platelets after thalidomide treatment in vitro for 60 min at 37oC. Thalidomide treatment also did not affect expression of GPIbα, GPVI or αIIbβ3, nor did it affect collagen- or ADP-induced platelet aggregation at threshold concentrations. However, while mice injected with thalidomide displayed no increased surface expression of platelet P-selectin or αIIbβ3, there was a significantly shortened tail bleeding time, thrombin time, prothrombin time together with higher levels of Factor IX and fibrinogen. In conclusion, thalidomide at therapeutic doses does not directly induce platelet activation under resting conditions in vitro or in vivo, but results in increased procoagulant activity, which could explain the thalidomide-dependent prothrombotic tendency in patients.This research was supported by National Natural Science Foundation of China (grant no. 81400082 and 81370602), the Natural Science Foundation of Jiangsu Province (grant no. BK20140219), China Postdoctoral Science Foundation funded project (project no. 2015M570479), the funding for the Distinguished Professorship Program of Jiangsu Province, the Six Talent Peaks Project of Jiangsu Province (project no. WSN-133), the Shuangchuang Project of Jiangsu Province, the Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry, and the Science and Technology Foundation for the Selected Overseas Chinese Scholars, State Ministry of Human Resources and Social Security

Recognition of aminoacyl-tRNA: a common molecular mechanism revealed by cryo-EM

The accuracy of ribosomal translation is achieved by an initial selection and a proofreading step, mediated by EF-Tu, which forms a ternary complex with aminoacyl(aa)-tRNA. To study the binding modes of different aa-tRNAs, we compared cryo-EM maps of the kirromycin-stalled ribosome bound with ternary complexes containing Phe-tRNAPhe, Trp-tRNATrp, or Leu-tRNALeuI. The three maps suggest a common binding manner of cognate aa-tRNAs in their specific binding with both the ribosome and EF-Tu. All three aa-tRNAs have the same ‘loaded spring' conformation with a kink and twist between the D-stem and anticodon stem. The three complexes are similarly integrated in an interaction network, extending from the anticodon loop through h44 and protein S12 to the EF-Tu-binding CCA end of aa-tRNA, proposed to signal cognate codon–anticodon interaction to the GTPase centre and tune the accuracy of aa-tRNA selection

An expanded evaluation of protein function prediction methods shows an improvement in accuracy

Background: A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging. Results: We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2. Conclusions: The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent. Keywords: Protein function prediction, Disease gene prioritizationpublishedVersio

An Expanded Evaluation of Protein Function Prediction Methods Shows an Improvement In Accuracy

Background: A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging. Results: We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2. Conclusions: The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent