The First Discovery of Marine Polyoxygenated Cembranolides as Potential Agents for the Treatment of Ulcerative Colitis.

Cembranolides are characteristic metabolites in marine soft corals, with complex structures and widespread biological activities. However, seldom has an intensive pharmacological study been done for these intriguing marine natural products. In this work, systematic chemical investigation was performed on Sinularia pedunculata by HSQC-based small molecule accurate recognition technology (SMART), resulting in the isolation and identification of 31 cembrane-type diterpenoids, including six new ones. In the bioassay, several compounds showed significant anti-inflammatory activities on the inhibition of NO production. The structure-activity relationship (SAR) was comprehensively analyzed, and two most bioactive and less toxic compounds 8 and 9 could inhibit inflammation through suppressing NF-κB and MAPK signaling pathways, and reduce the secretion of inflammatory cytokines. In a mouse model of dextran sodium sulfate (DSS)-induced acute colitis, 8 and 9 exhibited good anti-inflammatory effects and the ability to repair the colon epithelium, giving insight into the application of cembranolides as potential ulcerative colitis (UC) agents.

Discovering potential mechanisms of intervertebral disc disease using systematic Mendelian randomization of human circulating immunocytomics.

BACKGROUND: Although intervertebral disc degeneration (IVDD) is a critical factor in many spine-related diseases and has an extremely high prevalence in the aging population, the potential pathogenesis remains to be clarified entirely. Immune cells have been found to perform an essential function during the onset and progression of IVDD in recent years. Therefore, we explored the association between immune cell characteristics and IVDD through Mendelian randomization (MR) analysis and further delved into the mediating role of potential metabolites. METHODS: Based on the MR analysis, the association of 731 immune cell phenotypes and 1400 metabolites on IVDD were assessed. Single nucleotide polymorphisms (SNPs) were closely associated the expression levels of immune cell characteristics and the concentrations of metabolites and have been used as instrumental variables (IVs) for deducing them as risk factors or protective factors for IVDD. In addition, mediation analyses have been performed to identify potential metabolite mediators between immune cell characteristics and IVDD. RESULTS: MR analysis identified 27 immune cell phenotypes and 79 metabolites significantly associated with IVDD. In addition, mediation analysis was performed by selecting the immune cell phenotype that most significantly increased the risk of IVDD - CD86 on monocytes. A total of four metabolite-mediated mediation relationships were revealed (3b-hydroxy-5-cholenoic acid, X-22509, N-acetyl-L-glutamine, and N2-acetyl, N6, N6-dimethyllysine). CONCLUSION: The findings of this analysis identified underlying association between immune cell phenotypes, metabolite, and IVDD that may serve as predictive and prognostic clinical biomarkers and benefit IVDD pathogenesis research.

Efficient Large-Area Quantum Cutting Photoconversion Films for Silicon Solar Cells on Photovoltaic Glass Using Knife Coating.

Yb3+ doped perovskite nanocrystals (PNCs) serve as efficient photoconverters, exhibiting quantum cutting emission at ∼980 nm, which aligns precisely with the optimal response region of silicon solar cells (SSCs). However, severe nonradiative recombination caused by defects in the crystal lattice and film boundaries, along with limitations in small-scale film preparation, restricts their commercial application. Here, we used Ru3+ to mitigate lattice defects in CsPbCl3 PNCs and adjusted the quantum cutting luminescence, achieving a 175% photoluminescence quantum yield (PLQY). The results show that Ru3+ ions enter the perovskite lattice, fill lead vacancies, and passivate the lattice defects. Furthermore, cysteine effectively eliminates surface defects in PNCs by forming Pb-S bonds, resulting in films with a remarkable 117% PLQY, demonstrating strong photoconversion capabilities. Uniformly knife-coated on 20 × 20 cm2 photovoltaic glass, these films increased SSC efficiency from 21.45% to 23.15%. This study showcases a cost-effective photoconverter and a scalable coating method to boost the photovoltaic efficiency of large-area SSCs.

Efficient and precise genomic deletion in rice using enhanced prime editing.

Efficient and precise genomic deletion shows promise for investigating the function of proteins in plant research and enhancing agricultural traits. In this study, we tested the PRIME-Del (PDel) strategy using a pair of prime editing guide RNAs (pegRNAs) that targeted opposite DNA strands and achieved an average deletion efficiency of 55.8% for 60 bp fragment deletions at six endogenous targets. Moreover, as high as 84.2% precise deletion efficiency was obtained for a 2000 bp deletion at the OsGS1 site in transgenic rice plants. To add the bases that were unintentionally deleted between the two nicking sequences, we used the PDel/Syn strategy, which introduced multiple synonymous base mutations in the region that had to be patched in the RT template. The PDel/Syn strategy achieved an average of 58.1% deletion efficiency at six endogenous targets, which was higher than the PDel strategy. The strategies presented in this study contribute to achieving more accurate and flexible deletions in transgenic rice plants. Supplementary Information: The online version contains supplementary material available at 10.1007/s42994-024-00153-9.

Fully Optical Control of Polarization Current Direction in a Cyanide-Bridged Trinuclear Complex.

As a remote and non-contact stimulus, light offers the potential for manipulating the polarization of ferroelectric materials without physical contact. However, in current research, the non-contact write-read (erase) process lacks direct observation through the stable current as output signal. To address this limitation, we investigated the photoinduced polarization switching capabilities of the cyanide-bridged compound [Fe2Co] using visible light, leading to the achievement of rewritable polarization. By subjecting [Fe2Co] crystals to alternating irradiation with 785 nm and 532 nm light, the polarization changes exhibited a distinct square wave pattern, confirming the reliability of the writing and erasing processes. Initialization involved exposing specific crystal units to 532 nm light for storing "1" or "0" information, while reading was accomplished by scanning the units with 785 nm light, resulting in brief current pulses for "1" states and no current signal for "0" states. This research unveils new possibilities for optical storage systems, paving the way for efficient and rewritable data storage and retrieval technologies, such as the next-generation memories.

Natural aromatic extract of black tea improved the water retention of pork meat batter.

The effect of varying proportions (w/w) of natural aromatic extract of black tea (NAEBT) with pre-emulsification on the water-holding capacity (WHC) of pork meat batter was investigated. The addition of NAEBT significantly reduced the cooking loss (CL) of pork meat batter from 23.95 % to 18.30 % (P < 0.05). Furthermore, NAEBT with pre-emulsification significantly improved the color stability and increased the springiness (P < 0.05). The results of TBARS and carbonyls indicated that NAEBT with pre-emulsification significantly alleviated oxidative damage to proteins (P < 0.05), resulting in an increased level of ß-sheet (P < 0.05), as confirmed by FT-IR analysis. As a result, the water mobility of pork meat batter was restricted (P < 0.05), resulting in an increase in the energy storage modulus (P < 0.05) and a decrease in the pore size. In summary, the WHC of pork meat batter was improved by the antioxidant effect of the NAEBT.

SepM mutation in Streptococcus mutans clinical isolates and related function analysis.

BACKGROUND: Streptococcus mutans (S. mutans) is an important pathogenic bacterium that causes dental caries, while Streptococcus gordonii (S. gordonii) is a non-cariogenic bacterium that inhibits the growth of S. mutans. The SepM protein can promote the inhibitory ability of S. mutans against S. gordonii by cleaving CSP-21 and activating the ComDE two-component system. This study was designed to explore sepM mutation in S. mutans clinical isolates and related function in the regulation of interactions with S. gordonii. METHODS: The S. mutans clinical strains that can inhibit the growth of S. gordonii constitute the inhibitory group. 286 C-serotype S. mutans strains were categorized into S. gordonii inhibitory (n = 114) and non-inhibitory bacteria (n = 172). We detected sanger sequencing of sepM gene, the expression levels of related genes and proteins in clinical isolates, obtained prokaryotic expression and purification of mutated proteins, and analyzed the effect of the target mutations on the binding between SepM and CSP-21. RESULTS: We found that C482T, G533A, and G661A missense mutations were presented at significantly higher frequency in the inhibitory group relative to the non-inhibitory group. There was no significant difference in the expression of the sepM gene between selected clinical isolates harboring the G533A mutation and the control group. The expression levels of SepM, phosphorylated ComD, and ComE in the mutation group were significantly higher than those in the control group. SepM_control and SepM_D221N (G661A at the gene level) were found to contain two residues close to the active center while SepM_G178D (G533A at the gene level) contained three residues close to the active center. At 25 °C and a pH of 5.5, SepM_D221N (G661A) exhibited higher affinity for CSP-21 (KD = 8.25 µM) than did the SepM control (KD = 33.1 µM), and at 25 °C and a pH of 7.5, SepM_G178D (G533A) exhibited higher affinity (KD = 3.02 µM) than the SepM control (KD = 15.9 µM). It means that it is pH dependent. CONCLUSIONS: Our data suggest that increased cleavage of CSP-21 by the the mutant SepM may be a reason for the higher inhibitory effect of S. mutans on S. gordonii .

Metabolite Profiling Analysis of the Tongmai Sini Decoction in Rats after Oral Administration through UHPLC-Q-Exactive-MS/MS.

Tongmai Sini decoction (TSD), the classical prescriptions of traditional Chinese medicine, consisting of three commonly used herbal medicines, has been widely applied for the treatment of myocardial infarction and heart failure. However, the absorbed components and their metabolism in vivo of TSD still remain unknown. In this study, a reliable and effective method using ultra-performance liquid chromatography coupled with hybrid quadrupole-Orbitrap mass spectrometry (UHPLC-Q-Exactive-MS/MS) was employed to identify prototype components and metabolites in vivo (rat plasma and urine). Combined with mass defect filtering (MDF), dynamic background subtraction (DBS), and neutral loss filtering (NLF) data-mining tools, a total of thirty-two major compounds were selected and investigated for their metabolism in vivo. As a result, a total of 82 prototype compounds were identified or tentatively characterized in vivo, including 41 alkaloids, 35 phenolic compounds, 6 saponins. Meanwhile, A total of 65 metabolites (40 alkaloids and 25 phenolic compounds) were tentatively identified. The metabolic reactions were mainly hydrogenation, demethylation, hydroxylation, hydration, methylation, deoxylation, and sulfation. These findings will be beneficial for an in-depth understanding of the pharmacological mechanism and pharmacodynamic substance basis of TSD.

Therapeutic potential of single-nucleotide polymorphism-mediated IL6R inhibitors in ankylosing spondylitis treatment.

Objective: Interleukin-6 (IL-6) is a multiple-effect cell factor implicated in the etiopathogenesis of several rheumatologic disorders. The blockade of the IL-6 pathway via IL6R inhibitors effectively treats these disorders. However, the clinical significance of the IL6R blockade for ankylosing spondylitis (AS) therapy remains controversial. With advances in genomics, increasing evidence has revealed the role of heritability in the etiology of disease, and Mendelian randomization (MR) analyses are being used more broadly to infer causation. Therefore, this MR study aims to evaluate the potential therapeutic utility of IL6R-targeted approaches in AS. Methods: The C-reactive protein (CRP) level was used as an exposure factor, and rheumatoid arthritis (RA) was used as a positive control. As-related genome-wide association study (GWAS) data were used as the primary outcome of drug-targeted MR analyses to test the relation between IL6R blockers and AS. Inverse variance weighting (IVW) is the primary analytical approach. Various sensitivity tests were performed to check the robustness and trustworthiness of the causality estimation, including consistency, heterogeneity, and pleiotropy analyses. In addition, repeated analysis was conducted using different GWAS data related to exposures and outcomes to examine the results for stability. Results: According to the IVW results, IL6R inhibitors significantly reduced the risk of AS in ukb-b-18194 (OR: 0.995, 95% CI 0.993-0.996, P = 5.12 × 10-08) and ukb-a-88 (OR: 0.994, 95% CI 0.993-0.996, P = 6.25 × 10-15). Moreover, repeated analyses were performed using different exposure-related GWAS data, yielding similar results, ukb-b-18194 (OR: 0.995, 95% CI 0.993-0.997, P = 1.25 × 10-06) and ukb-a-88 (OR: 0.995, 95% CI 0.994-0.997, P = 7.81 × 10-09). Heterogeneity analyses and pleiotropy analyses indicated no significant heterogeneity or pleiotropy. Conclusion: This MR analysis result further validates that the IL-6 pathway may contribute to the pathogenesis of AS and that the inhibition of IL6R reduces the risk of AS. These findings may guide future studies and provide more favorable drug treatment options for people at high risk of AS.

Haplotype analysis on association between C-reactive protein gene and susceptibility to type 2 diabetes mellitus in Chinese Han population : CRP gene and type 2 diabetes mellitus.

AIMS: We aimed to evaluate the impact of C-reactive protein (CRP) gene polymorphism, additional gene-gene interaction, and haplotypes on susceptibility to type 2 diabetes mellitus (T2DM). METHODS: SNPstats online software ( https://www.snpstats.net/start.htm ) was employed to evaluate the association between CRP gene and T2DM risk. High-order interactions among SNPs was tested using generalized multifactor dimensionality reduction, and the testing balanced accuracy, training balanced accuracy and cross-validation consistency were calculated. The SHEsisPlus ( http://shesisplus.bio-x.cn/SHEsis.html ) online software was used for haplotype analysis. RESULTS: A total of 730 T2DM patients and 765 controls were enrolled. The T allele of rs1205 is associated with increased susceptibility to T2DM, OR (95% CI) were 1.51 (1.13-2.01), 1.44 (1.10-1.89) and 1.25 (1.01-1.54) for codominant, dominant and over-dominant models, respectively. We also found that minor allele of rs2794521 is associated with decreased susceptibility to T2DM under codominant and recessive models, OR (95%CI) were 0.38 (0.18-0.79) and 0.37 (0.16-0.80) for codominant and recessive models, respectively. No significant gene-gene interaction existed among CRP gene SNPs, all interaction p- values were more than 0.05. Haplotype analyses suggested the CGCA haplotype containing rs1205-C, rs1130864-G, rs2794521- C and rs3093059- A allele was associated with decreased risk of T2DM, OR (95% CI) = 0.83 (0.68-0.98), P = 0.047. CONCLUSIONS: Minor allele of rs1205 was associated with increased T2DM risk. Minor allele of rs2794521 and the CGCA haplotype were associated with decreased T2DM risk.

Interpretable machine learning for predicting the response duration to Sintilimab plus chemotherapy in patients with advanced gastric or gastroesophageal junction cancer.

Background: Sintilimab plus chemotherapy has proven effective as a combination immunotherapy for patients with advanced gastric and gastroesophageal junction adenocarcinoma (GC/GEJC). A multi-center study conducted in China revealed a median progression-free survival (PFS) of 7.1 months. However, the prediction of response duration to this immunotherapy has not been thoroughly investigated. Additionally, the potential of baseline laboratory features in predicting PFS remains largely unexplored. Therefore, we developed an interpretable machine learning (ML) framework, iPFS-SC, aimed at predicting PFS using baseline (pre-treatment) laboratory features and providing interpretations of the predictions. Materials and methods: A cohort of 146 patients with advanced GC/GEJC, along with their baseline laboratory features, was included in the iPFS-SC framework. Through a forward feature selection process, predictive baseline features were identified, and four ML algorithms were developed to categorize PFS duration based on a threshold of 7.1 months. Furthermore, we employed explainable artificial intelligence (XAI) methodologies to elucidate the relationship between features and model predictions. Results: The findings demonstrated that LightGBM achieved an accuracy of 0.70 in predicting PFS for advanced GC/GEJC patients. Furthermore, an F1-score of 0.77 was attained for identifying patients with PFS durations shorter than 7.1 months. Through the feature selection process, we identified 11 predictive features. Additionally, our framework facilitated the discovery of relationships between laboratory features and PFS. Conclusion: A ML-based framework was developed to predict Sintilimab plus chemotherapy response duration with high accuracy. The suggested predictive features are easily accessible through routine laboratory tests. Furthermore, XAI techniques offer comprehensive explanations, both at the global and individual level, regarding PFS predictions. This framework enables patients to better understand their treatment plans, while clinicians can customize therapeutic approaches based on the explanations provided by the model.

[Spatial distribution patterns and intraspecific and interspecific spatial associations of Quercus myrsinifolia population in Shennongjia, China]. / ç¥žå†œæž¶å°å¶é’å†ˆç§ç¾¤çš„ç©ºé—´åˆ†å¸ƒæ ¼å±€åŠç§å† ç§é—´ç©ºé—´å ³è”.

Quercus myrsinifolia is one of the dominant species in the evergreen broad-leaf forest on the southern slope of Shennongjia. The study of spatial distribution pattern and spatial correlation of Q. myrsinifolia population will help to understand population development and potential ecological processes, as well as the structure and biodiversity maintenance mechanism of evergreen broad-leaf forests at the northern edge of the subtropics. Based on forest dynamic monitoring data from one 1 hm2 permanent plot on the southern slope of Shennongjia, we employed pair correlation functions g(r) and marked correlation functions to analyze the diameter structure of the Q. myrsinifolia population, spatial distribution patterns at different diameter classes, and intraspecific and interspecific spatial associations. The results showed that diameter structure of Q. myrsinifolia population exhibited an inverted 'J'-shaped distribution, suggesting a healthy regeneration status and belonging to a growing population type. The spatial distribution showed a decreasing trend in aggregation with increasing diameter. Positive correlations among individuals strengthened with closer diameter classes, while weakening with larger diameter differences. Interspecific spatial associations showed an increasing correlation of Q. myrsinifolia with understory dominant species with increasing spatial scales, but no correlation was observed with canopy-dominant species. Our results suggested that the spatial pattern of Q. myrsinifolia populations on the southern slope of Shennongjia was mainly influenced by habitat filtering, seed dispersal limitation, and intraspecific and interspecific competition. Furthermore, the adaptive strategies of Q. myrsinifolia varied when they coexisted with different species.

The gut microbiota-aromatic hydrocarbon receptor (AhR) axis mediates the anticolitic effect of polyphenol-rich extracts from Sanghuangporus.

Inflammatory bowel disease (IBD) is a significant global health concern. The gut microbiota plays an essential role in the onset and development of IBD. Sanghuangporus (SH), a traditional Chinese medicinal mushroom, has excellent anti-inflammatory effects and is effective at modulating the gut microbiota. Despite these attributes, the specific anticolitic effects of SH and the mechanisms through which the gut microbiota mediates its benefits remain unclear. Herein, we demonstrated that polyphenol-rich extract from SH effectively alleviated the pathological symptoms of dextran sodium sulfate (DSS)-induced colitis in mice by modulating the gut microbiota. Treatment with SH distinctly enriched Alistipes, especially Alistipes onderdonkii, and its metabolite 5-hydroxyindole-3-acetic acid (5HIAA). Oral gavage of live A. onderdonkii or 5HIAA potently mitigated DSS-induced colitis in mice. Moreover, both 5HIAA and SH significantly activated the aromatic hydrocarbon receptor (AhR), and the administration of an AhR antagonist abrogated their protective effects against colitis. These results underscore the potent efficacy of SH in diminishing DSS-induced colitis through the promotion of A. onderdonkii and 5HIAA, ultimately activating AhR signaling. This study unveils potential avenues for developing therapeutic strategies for colitis based on the interplay between SH and the gut microbiota.

Peripheral blood eosinophils: an important reference for radiologists to distinguish between pulmonary paragonimiasis and tuberculous pleurisy in children.

OBJECTIVE: In this study, we examined the value of chest CT signs combined with peripheral blood eosinophil percentage in differentiating between pulmonary paragonimiasis and tuberculous pleurisy in children. METHODS: Patients with pulmonary paragonimiasis and tuberculous pleurisy were retrospectively enrolled from January 2019 to April 2023 at the Kunming Third People's Hospital and Lincang People's Hospital. There were 69 patients with pulmonary paragonimiasis (paragonimiasis group) and 89 patients with tuberculous pleurisy (tuberculosis group). Clinical symptoms, chest CT imaging findings, and laboratory test results were analyzed. Using binary logistic regression, an imaging model of CT signs and a combined model of CT signs and eosinophils were developed to calculate and compare the differential diagnostic performance of the two models. RESULTS: CT signs were used to establish the imaging model, and the receiver operating characteristic (ROC) curve was plotted. The area under the curve (AUC) was 0.856 (95% CI: 0.799-0.913), the sensitivity was 66.7%, and the specificity was 88.9%. The combined model was established using the CT signs and eosinophil percentage, and the ROC was plotted. The AUC curve was 0.950 (95% CI: 0.919-0.980), the sensitivity was 89.9%, and the specificity was 90.1%. The differential diagnostic efficiency of the combined model was higher than that of the imaging model, and the difference in AUC was statistically significant. CONCLUSION: The combined model has a higher differential diagnosis efficiency than the imaging model in the differentiation of pulmonary paragonimiasis and tuberculous pleurisy in children. The presence of a tunnel sign on chest CT, the absence of pulmonary nodules, and an elevated percentage of peripheral blood eosinophils are indicative of pulmonary paragonimiasis in children.

Super-resolution spatial spectrum reconstruction under unknown near-field interferences.

In underwater acoustic signal processing, conventional spatial spectrum estimation and the associated direction-of-arrival estimation are often impaired by strong near-field interferences at the same frequency as the far-field target signal, leading to significant performance degradation and even detection failure. In contrast to prevalent near-field interference suppression algorithms that require prior knowledge of near-field interference positions, this paper proposes a super-resolution spatial spectrum reconstruction algorithm designed for more general scenarios where crucial information about the near-field interference, such as positions and magnitudes, is unknown. The proposed algorithm demonstrates its adaptability in mitigating unknown near-field interference and achieves this by leveraging rank constraint-based relaxation and alternating minimization, resulting in an effective spatial spectrum reconstruction strategy. The efficacy of the proposed spatial spectrum reconstruction method in handling strong near-field interference is confirmed through analysis of simulated and synthetic experimental data. It exhibits superiority over traditional competitors in terms of resolution, denoising capabilities, and estimation accuracy. Moreover, it achieves comparable results to algorithms that utilize prior information about near-field interference positions. The enhanced performance remains consistent even in challenging scenarios such as snapshot deficiency and low signal-to-noise ratios.

Radiomics models of contrast-enhanced computed tomography for predicting the activity and prognosis of acute pancreatitis.

BACKGROUND: The modified pancreatitis activity scoring system (mPASS) was proposed to assess the activity of acute pancreatitis (AP) while it doesn't include indicators that directly reflect pathophysiology processes and imaging characteristics. OBJECTIVES: To determine the threshold of admission mPASS and investigate radiomics and laboratory parameters to construct a model to predict the activity of AP. METHODS: AP inpatients at institution 1 were randomly divided into training and validation groups based on a 5:5 ratio. AP inpatients at Institution 2 were served as test group. The cutoff value of admission mPASS scores in predicting severe AP was selected to divide patients into high and low level of disease activity group. LASSO was used in screening features. Multivariable logistic regression was used to develop radiomics model. Meaningful laboratory parameters were used to construct combined model. RESULTS: There were 234 (48 years ± 10, 155 men) and 101 (48 years ± 11, 69 men) patients in two institutions. The threshold of admission mPASS score was 112.5 in severe AP prediction. The AUC of the radiomics model was 0.79, 0.72, and 0.76 and that of the combined model incorporating rad-score and white blood cell were 0.84, 0.77, and 0.80 in three groups for activity prediction. The AUC of the combined model in predicting disease without remission was 0.74. CONCLUSIONS: The threshold of admission mPASS was 112.5 in predicting severe AP. The model based on CECT radiomics has the ability to predict AP activity. Its ability to predict disease without remission is comparable to mPASS. CRITICAL RELEVANCE STATEMENT: This work is the first attempt to assess the activity of acute pancreatitis using contrast-enhanced CT radiomics and laboratory parameters. The model provides a new method to predict the activity and prognosis of AP, which could contribute to further management. KEY POINTS: Radiomics features and laboratory parameters are associated with the activity of acute pancreatitis. The combined model provides a new method to predict the activity and prognosis of AP. The ability of the combined model is comparable to the modified Pancreatitis Activity Scoring System.

Influence of ABC stroke score on late recurrence of paroxysmal atrial fibrillation following radiofrequency catheter ablation.

BACKGROUND: In this study we investigated the impact of ABC stroke score on the recurrence of paroxysmal atrial fibrillation (PAF) following radiofrequency catheter ablation (RFCA). METHODS: A total of 132 patients with PAF who underwent RFCA from October 2018 to September 2019 were included in this study. During the first phase of this study the patients were categorized into two groups based on late recurrence of atrial fibrillation after RFCA. In the second phase, the patients were further divided into two groups based on whether their ABC stroke score was ≥ 6.5. RESULT: The univariate analysis indicated that the risk factors for late recurrence of PAF included early recurrence, ABC stroke score, CHA2DS2-VASc score, and NT-proBNP (P < 0.05). Cox multivariate regression analysis revealed that ABC stroke score (P = 0.006) and early recurrence (P = 0.000) were independent predictors of late recurrence, and ABC stroke score ≥ 6.5 was a risk for predicting recurrence of PAF after RFCA with a sensitivity of 66.7% and specificity of 65.7%. After the completion of the 1:1 matching, the univariate Cox analysis indicated that an elevated score of ABC stroke (≥ 6.5) was an independent predictor of late recurrence of PAF (HR = 2.687, 95% CI: 1.036-6.971, P = 0.042). However, using an ABC stroke score cut off at 6.4 predicted the recurrence of atrial tachyarrhythmia with 85% sensitivity and 58.5% specificity. CONCLUSION: An ABC stroke score ≥ 6.4 is a predictor for late recurrence of PAF after RFCA.

Prediction of drug-target binding affinity based on multi-scale feature fusion.

Accurate prediction of drug-target binding affinity (DTA) plays a pivotal role in drug discovery and repositioning. Although deep learning methods are widely used in DTA prediction, two significant challenges persist: (i) how to effectively represent the complex structural information of proteins and drugs; (ii) how to precisely model the mutual interactions between protein binding sites and key drug substructures. To address these challenges, we propose a MSFFDTA (Multi-scale feature fusion for predicting drug target affinity) model, in which multi-scale encoders effectively capture multi-level structural information of drugs and proteins are designed. And then a Selective Cross Attention (SCA) mechanism is developed to filter out the trivial interactions between drug-protein substructure pairs and retain the important ones, which will make the proposed model better focusing on these key interactions and offering insights into their underlying mechanism. Experimental results on two benchmark datasets demonstrate that MSFFDTA is superior to several state-of-the-art methods across almost all comparison metrics. Finally, we provide the ablation and case studies with visualizations to verify the effectiveness and the interpretability of MSFFDTA. The source code is freely available at https://github.com/whitehat32/MSFF-DTA/.