DLBWE-Cys: a deep-learning-based tool for identifying cysteine S-carboxyethylation sites using binary-weight encoding

Cysteine S-carboxyethylation, a novel post-translational modification (PTM), plays a critical role in the pathogenesis of autoimmune diseases, particularly ankylosing spondylitis. Accurate identification of S-carboxyethylation modification sites is essential for elucidating their functional mechanisms. Unfortunately, there are currently no computational tools that can accurately predict these sites, posing a significant challenge to this area of research. In this study, we developed a new deep learning model, DLBWE-Cys, which integrates CNN, BiLSTM, Bahdanau attention mechanisms, and a fully connected neural network (FNN), using Binary-Weight encoding specifically designed for the accurate identification of cysteine S-carboxyethylation sites. Our experimental results show that our model architecture outperforms other machine learning and deep learning models in 5-fold cross-validation and independent testing. Feature comparison experiments confirmed the superiority of our proposed Binary-Weight encoding method over other encoding techniques. t-SNE visualization further validated the model’s effective classification capabilities. Additionally, we confirmed the similarity between the distribution of positional weights in our Binary-Weight encoding and the allocation of weights in attentional mechanisms. Further experiments proved the effectiveness of our Binary-Weight encoding approach. Thus, this model paves the way for predicting cysteine S-carboxyethylation modification sites in protein sequences. The source code of DLBWE-Cys and experiments data are available at: https://github.com/ztLuo-bioinfo/DLBWE-Cys

Formation conditions and enrichment mechanisms of the Jurassic lacustrine organic-rich shale in the East Fukang Sag, Junggar Basin, NW China: A reassessment based on organic geochemistry

Chemical composition of sediments is often used to evaluate paleoclimate condition, provenance, tectonic setting, depositional condition, and paleoproductivity. However, the validity of these proxies has long been questioned. The comprehensive use of organic and inorganic multi-indicators in combination when interpreting issues related to terrestrial shales should be advocated. The paleodepositional environment, origin of organic matter (OM) and factor controlling OM accumulation in the Early Jurassic Badaowan (J1b) and Sangonghe (J1s) as well as Middle Jurassic Xishanyao (J2x) lacustrine shales in the East Fukang Sag are reassessed by using organic geochemical characteristics of the OM. Some previous knowledge is updated, and some knowledge is further supported by more evidence. The typical clay-rich shale developed under a lacustrine sedimental environment, and the thermal maturity of these organic-rich shales has entered the oil window and formed economic hydrocarbon potential for the tight-oil and shale-oil reservoirs. The paleoclimate conditions of the study area were warm and humid from the Early to Middle Jurassic periods but were colder and drier after the Middle Jurassic period. The salinity of the water column ranged from freshwater to brackish conditions. The J2x Formation was deposited under oxic conditions, while J1b and J1s formations developed under suboxic and reducing environmental conditions. The J2x Formation OM mainly derived from higher plants was deposited in a terrestrial environment,while the OM of J1b and J1s formations was a mixed OM derived from higher plants and bacteria with little algae deposited under bay/estuary environments alternated with terrestrial environments. It is effective to reflect the paleoclimate by element index and judge the salinity by the updated element thresholds, but it is not effective to evaluate the paleoredox conditions by common elemental ratios and to evaluate the paleoproductivity by Ba in the study area

MELD-XI Score Is Associated With Short-Term Adverse Events in Patients With Heart Failure With Preserved Ejection

Aim: Accumulating evidence suggests that MELD-XI score holds the ability to predict the prognosis of congestive heart failure. However, most of the evidence is based on the end-stage heart failure population; thus, we aim to explore the association between the MELD-XI score and the prognosis in heart failure with preserved ejection fraction (HFpEF).Methods: A total of 30,096 patients hospitalized for HFpEF in Fujian Provincial Hospital between January 1, 2014 and July 17, 2020 with available measures of creatinine and liver function were enrolled. The primary endpoint was 60-day in-hospital all-cause mortality. Secondary endpoints were 60-day in-hospital cardiovascular mortality and 30-day rehospitalization for heart failure.Results: A total of 222 patients died within 60 days after admission, among which 75 deaths were considered cardiogenic. And 73 patients were readmitted for heart failure within 30 days after discharge. Generally, patients with an elevated MELD-XI score tended to have more comorbidities, higher NYHA class, and higher inflammatory biomarkers levels. Meanwhile, the MELD-XI score was positively correlated with NT-pro BNP, left atrial diameter, E/e' and negatively correlated with LVEF. After adjusting for conventional risk factors, the MELD-XI score was independently associated with 60-day in-hospital all-cause mortality [hazard ratio(HR) = 1.052, 95% confidential interval (CI) 1.022–1.083, P = 0.001], 60-day in-hospital cardiovascular mortality (HR = 1.064, 95% CI 1.013–1.118, P = 0.014), and 30-day readmission for heart failure (HR = 1.061, 95% CI 1.015–1.108, P = 0.009). Furthermore, the MELD-XI score added an incremental discriminatory capacity to risk stratification models developed based on this cohort.Conclusion: The MELD-XI score was associated with short-term adverse events and provided additional discriminatory capacity to risk stratification models in patients hospitalized for HFpEF

Integrated transcriptomic and proteomic analysis of the immune response in Hyalomma anatolicum to bacterial invasion

BackgroundHyalomma anatolicum is a multi-host ectoparasite that carries and transmits a variety of zoonotic pathogens. Understanding the immune response of ticks to bacterial infections is of research significance for deciphering their immune defense mechanisms and harnessing tick - derived molecules.MethodsIn the current study, transcriptomic and proteomic analyses on H. anatolicum injected with Staphylococcus aureus (SA group), Proteus mirabilis (PM group) or phosphate buffered saline (PBS group) were performed.ResultsIn pairwise comparisons among the experimental groups, we identified 9,776 (SA/PBS), 10,230 (PM/PBS), and 1,309 (SA/PM) differentially expressed genes (DEGs), as well as 175 (SA/PBS), 277 (PM/PBS), and 223 (SA/PM) differentially expressed proteins (DEPs), respectively. Subsequent KEGG pathway analysis revealed that these DEGs and DEPs were significantly enriched in a range of pertinent pathways, including the immune system and apoptosis, Toll and IMD signaling pathways, MAPK signaling pathway, and NF - κB signaling pathway. The RT - qPCR detection data exhibited a concordant trend with the RNA - seq data, indicating a substantial alignment in the observed results. Notably, the defensin and lectin gene families emerged as potentially pivotal components within the innate immune defense system of ticks.ConclusionOverall, in this study, genes, proteins, and signaling pathways integral to the immune defense of H. anatolicum were identified, offering substantial potential for future research focused on harnessing its intricate immune defense mechanisms for antimicrobial applications

Fuzzy aesthetic semantics description and extraction for art image retrieval

AbstractMore and more digitized art images are accumulated and expanded in our daily life and techniques are needed to be established on how to organize and retrieve them. Though content-based image retrieval (CBIR) made great progress, current low-level visual information based retrieval technology in CBIR does not allow users to search images by high-level semantics for art image retrieval. We propose a fuzzy approach to describe and to extract the fuzzy aesthetic semantic feature of art images. Aiming to deal with the subjectivity and vagueness of human aesthetic perception, we utilize the linguistic variable to describe the image aesthetic semantics, so it becomes possible to depict images in linguistic expression such as ‘very action’. Furthermore, we apply neural network approach to model the process of human aesthetic perception and to extract the fuzzy aesthetic semantic feature vector. The art image retrieval system based on fuzzy aesthetic semantic feature makes users more naturally search desired images by linguistic expression. We report extensive empirical studies based on a 5000-image set, and experimental results demonstrate that the proposed approach achieves excellent performance in terms of retrieval accuracy

A Fourier Transform Framework for Domain Adaptation

By using unsupervised domain adaptation (UDA), knowledge can be transferred from a label-rich source domain to a target domain that contains relevant information but lacks labels. Many existing UDA algorithms suffer from directly using raw images as input, resulting in models that overly focus on redundant information and exhibit poor generalization capability. To address this issue, we attempt to improve the performance of unsupervised domain adaptation by employing the Fourier method (FTF).Specifically, FTF is inspired by the amplitude of Fourier spectra, which primarily preserves low-level statistical information. In FTF, we effectively incorporate low-level information from the target domain into the source domain by fusing the amplitudes of both domains in the Fourier domain. Additionally, we observe that extracting features from batches of images can eliminate redundant information while retaining class-specific features relevant to the task. Building upon this observation, we apply the Fourier Transform at the data stream level for the first time. To further align multiple sources of data, we introduce the concept of correlation alignment. To evaluate the effectiveness of our FTF method, we conducted evaluations on four benchmark datasets for domain adaptation, including Office-31, Office-Home, ImageCLEF-DA, and Office-Caltech. Our results demonstrate superior performance.Comment: The paper contains significant errors and the experimental methodology is not rigorous. The experimental section and methodology need to be rewritte