Three Dimensional Quantitative Structure-Activity Relationships of Sulfonamides Binding Monoclonal Antibody by Comparative Molecular Field Analysis

The three-dimensional quantitative structure-activity relationship (3D-QSAR) model of sulfonamide analogs binding a monoclonal antibody (MabSMR) produced against sulfamerazine, was carried out by comparative molecular field analysis (CoMFA). The affinities of MabSMR, expressed as Log10IC50, for 17 sulfonamide analogs were determined by competitive fluorescence polarization immunoassay (FPIA). Removal of two outliers from the initial set of 17 sulfonamide analogs improved the predictability of the models. The 3D-QSAR model of 15 sulfonamides resulted in q2cv values of 0.600, and r2 values of 0.995, respectively. This novel study combining FPIA with CoMFA demonstrates that multidisciplinary research can be used as a useful tool to investigate antigen-antibody interactions and provide information required for design of novel haptens, which may result in new antibodies with properties already optimized by an antibody-based immunoassay

HC3 Plus: A Semantic-Invariant Human ChatGPT Comparison Corpus

ChatGPT has gained significant interest due to its impressive performance, but people are increasingly concerned about its potential risks, particularly around the detection of AI-generated content (AIGC), which is often difficult for untrained humans to identify. Current datasets utilized for detecting ChatGPT-generated text primarily center around question-answering, yet they tend to disregard tasks that possess semantic-invariant properties, such as summarization, translation, and paraphrasing. Our primary studies demonstrate that detecting model-generated text on semantic-invariant tasks is more difficult. To fill this gap, we introduce a more extensive and comprehensive dataset that considers more types of tasks than previous work, including semantic-invariant tasks. In addition, the model after a large number of task instruction fine-tuning shows a strong powerful performance. Owing to its previous success, we further instruct fine-tuning Tk-instruct and built a more powerful detection system. Experimental results show that our proposed detector outperforms the previous state-of-the-art RoBERTa-based detector

Challenges and Remedies to Privacy and Security in AIGC: Exploring the Potential of Privacy Computing, Blockchain, and Beyond

Artificial Intelligence Generated Content (AIGC) is one of the latest achievements in AI development. The content generated by related applications, such as text, images and audio, has sparked a heated discussion. Various derived AIGC applications are also gradually entering all walks of life, bringing unimaginable impact to people's daily lives. However, the rapid development of such generative tools has also raised concerns about privacy and security issues, and even copyright issues in AIGC. We note that advanced technologies such as blockchain and privacy computing can be combined with AIGC tools, but no work has yet been done to investigate their relevance and prospect in a systematic and detailed way. Therefore it is necessary to investigate how they can be used to protect the privacy and security of data in AIGC by fully exploring the aforementioned technologies. In this paper, we first systematically review the concept, classification and underlying technologies of AIGC. Then, we discuss the privacy and security challenges faced by AIGC from multiple perspectives and purposefully list the countermeasures that currently exist. We hope our survey will help researchers and industry to build a more secure and robust AIGC system.Comment: 43 pages, 10 figure

InfoEntropy Loss to Mitigate Bias of Learning Difficulties for Generative Language Models

Generative language models are usually pretrained on large text corpus via predicting the next token (i.e., sub-word/word/phrase) given the previous ones. Recent works have demonstrated the impressive performance of large generative language models on downstream tasks. However, existing generative language models generally neglect an inherent challenge in text corpus during training, i.e., the imbalance between frequent tokens and infrequent ones. It can lead a language model to be dominated by common and easy-to-learn tokens, thereby overlooking the infrequent and difficult-to-learn ones. To alleviate that, we propose an Information Entropy Loss (InfoEntropy Loss) function. During training, it can dynamically assess the learning difficulty of a to-be-learned token, according to the information entropy of the corresponding predicted probability distribution over the vocabulary. Then it scales the training loss adaptively, trying to lead the model to focus more on the difficult-to-learn tokens. On the Pile dataset, we train generative language models at different scales of 468M, 1.2B, and 6.7B parameters. Experiments reveal that models incorporating the proposed InfoEntropy Loss can gain consistent performance improvement on downstream benchmarks

Experimental study on the dynamic behavior of rubber concrete under compression considering earthquake magnitude strain rate

To examine the compressive dynamic performance of rubber concrete, a uniaxial compression experimental study on rubber concrete was carried out using a hydraulic servo based on five different rubber substitution rates under eight different earthquake magnitude loading strain rates. The compressive failure modes and stress-strain curves of rubber concrete were obtained. By comparatively analyzing the mechanical characteristics of rubber concrete under different loading conditions, the following conclusions are drawn: with the increase in rubber substitution rate, the integrity of concrete upon compressive failure is gradually improved, and rubber particles exhibit an evident modification effect on cement mortar at the concrete interface. Under the influence of loading strain rate, the patterns of compressive failure mode of rubber concrete with different substitution rates are similar to that of ordinary concrete. Under the same loading strain rate, with the increase in rubber substitution rate, the compressive strength of rubber concrete gradually decreases while the plastic deformation capacity gradually increases. For the same rubber substitution rate, the compressive strength and elastic modulus of rubber concrete gradually increases with the increase in loading strain rate. The increase in rubber substitution rate gradually reduces the increasing amplitude of compressive strength and elastic modulus of rubber concrete under the influence of loading strain rate. Meanwhile, an equation was proposed to describe the coupling effect of rubber substitution rate and strain rate on the compressive strength dynamic increase factor of rubber concrete, and the underlying stress mechanism was further discussed. These results have significance in promoting the application of rubber concrete in engineering practice

Wenxin-Keli Regulates the Calcium/Calmodulin-Dependent Protein Kinase II Signal Transduction Pathway and Inhibits Cardiac Arrhythmia in Rats with Myocardial Infarction

Wenxin-Keli (WXKL) is a Chinese herbal compound reported to be of benefit in the treatment of cardiac arrhythmia, cardiac inflammation, and heart failure. Amiodarone is a noncompetitive inhibitor of the α- and β-adrenergic receptors and prevents calcium influx in the slow-response cells of the sinoatrial and atrioventricular nodes. Overexpression of Ca2+/calmodulin-dependent protein kinase II (CaMKII) in transgenic mice results in heart failure and arrhythmias. We hypothesised that administration of WXKL and amiodarone can reduce the incidence of arrhythmias by regulating CaMKII signal transduction. A total of 100 healthy Sprague Dawley rats were used in the study. The rats were randomly divided into four groups (a sham group, a myocardial infarction (MI) group, a WXKL-treated group, and an amiodarone-treated group). A myocardial infarction model was established in these rats by ligating the left anterior descending coronary artery for 4 weeks. Western blotting was used to assess CaMKII, p-CaMKII (Thr-286), PLB, p-PLB (Thr-17), RYR2, and FK binding protein 12.6 (FKBP12.6) levels. The Ca2+ content in the sarcoplasmic reticulum (SR) and the calcium transient amplitude were studied by confocal imaging using the fluorescent indicator Fura-4. In conclusion, WXKL may inhibit heart failure and cardiac arrhythmias by regulating the CaMKII signal transduction pathway similar to amiodarone

Normally occurring NKG2D+CD4+ T cells are immunosuppressive and inversely correlated with disease activity in juvenile-onset lupus

The NKG2D receptor stimulates natural killer cell and T cell responses upon engagement of ligands associated with malignancies and certain autoimmune diseases. However, conditions of persistent NKG2D ligand expression can lead to immunosuppression. In cancer patients, tumor expression and shedding of the MHC class I–related chain A (MICA) ligand of NKG2D drives proliferative expansions of NKG2D+CD4+ T cells that produce interleukin-10 (IL-10) and transforming growth factor-β, as well as Fas ligand, which inhibits bystander T cell proliferation in vitro. Here, we show that increased frequencies of functionally equivalent NKG2D+CD4+ T cells are inversely correlated with disease activity in juvenile-onset systemic lupus erythematosus (SLE), suggesting that these T cells may have regulatory effects. The NKG2D+CD4+ T cells correspond to a normally occurring small CD4 T cell subset that is autoreactive, primed to produce IL-10, and clearly distinct from proinflammatory and cytolytic CD4 T cells with cytokine-induced NKG2D expression that occur in rheumatoid arthritis and Crohn's disease. As classical regulatory T cell functions are typically impaired in SLE, it may be clinically significant that the immunosuppressive NKG2D+CD4+ T cells appear functionally uncompromised in this disease

The Genomes of Oryza sativa: A History of Duplications

We report improved whole-genome shotgun sequences for the genomes of indica and japonica rice, both with multimegabase contiguity, or almost 1,000-fold improvement over the drafts of 2002. Tested against a nonredundant collection of 19,079 full-length cDNAs, 97.7% of the genes are aligned, without fragmentation, to the mapped super-scaffolds of one or the other genome. We introduce a gene identification procedure for plants that does not rely on similarity to known genes to remove erroneous predictions resulting from transposable elements. Using the available EST data to adjust for residual errors in the predictions, the estimated gene count is at least 38,000–40,000. Only 2%–3% of the genes are unique to any one subspecies, comparable to the amount of sequence that might still be missing. Despite this lack of variation in gene content, there is enormous variation in the intergenic regions. At least a quarter of the two sequences could not be aligned, and where they could be aligned, single nucleotide polymorphism (SNP) rates varied from as little as 3.0 SNP/kb in the coding regions to 27.6 SNP/kb in the transposable elements. A more inclusive new approach for analyzing duplication history is introduced here. It reveals an ancient whole-genome duplication, a recent segmental duplication on Chromosomes 11 and 12, and massive ongoing individual gene duplications. We find 18 distinct pairs of duplicated segments that cover 65.7% of the genome; 17 of these pairs date back to a common time before the divergence of the grasses. More important, ongoing individual gene duplications provide a never-ending source of raw material for gene genesis and are major contributors to the differences between members of the grass family

The dynamic evolution of multipoint interplanetary coronal mass ejections observed with BepiColombo, Tianwen-1, and MAVEN

We present two multipoint interplanetary coronal mass ejections (ICMEs) detected by the Tianwen-1 and Mars Atmosphere and Volatile Evolution spacecraft at Mars and the BepiColombo (0.56 au ∼0.67 au) upstream of Mars from 2021 December 5 to 31. This is the first time that BepiColombo is used as an upstream solar wind monitor ahead of Mars and that Tianwen-1 is used to investigate the magnetic field characteristics of ICMEs at Mars. The Heliospheric Upwind Extrapolation time model was used to connect the multiple in situ observations and the coronagraph observations from STEREO/SECCHI and SOHO/LASCO. The first fast coronal mass ejection event (∼761.2 km s−1), which erupted on December 4, impacted Mars centrally and grazed BepiColombo by its western flank. The ambient slow solar wind decelerated the west flank of the ICME, implying that the ICME event was significantly distorted by the solar wind structure. The second slow ICME event (∼390.7 km s−1) underwent an acceleration from its eruption to a distance within 0.69 au and then traveled with the constant velocity of the ambient solar wind. These findings highlight the importance of background solar wind in determining the interplanetary evolution and global morphology of ICMEs up to Mars distance. Observations from multiple locations are invaluable for space weather studies at Mars and merit more exploration in the future

The effect of energy accumulation and boundary slip on laminar flow between rotating plates

The poor operating conditions of fluid lubrication equipment during the start-up process are due to the resistance of the high-viscosity lubricating liquid. Moreover, the excessive reduction in fluid viscosity due to the elevated temperature resulting from power consumption during prolonged operation is not conducive to the generation of dynamic pressure. In this study, we examine the effect of energy accumulation and boundary slip on the laminar flow of a liquid between a pair of rotating plates. The experiments are conducted using a rotary rheometer, with polymethyl methacrylate (PMMA) as the thermal insulation material and polytetrafluoroethylene (PTFE) as the slip drag reduction material, and a three-dimensional simulation model is established. This model is derived by combining the energy equation including the slip length and the heat conduction equation. Thus, the temperature changes over time are predicted by this model, and the model accuracy is verified by experiments. The results reveal the following points: 1) boundary slips function as a drag reduction mechanism for short-time continuous operation; 2) under prolonged operation, the slip reduces the extent of the oil viscosity decrease and clear control of the elevated temperature by the boundary slip is observed