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Photocatalytic 1,2-Dicarboxylation of Unactivated Alkynes with CO₂

RETRACTED: An eel-like robot based on a dielectric elastomer

Eels have attracted significant research interest because of their long-distance migration and high-endurance cruising behavior. An underwater eel-like robot design inspired by these creatures has the potential for high efficiency, strong maneuverability and high stability. The propulsive biomimetic eel-like robot has the lowest energy consumption per unit distance, and its flexible body is conducive to movement and operation in narrow spaces; this is expected to become the research and development direction for underwater biomimetic robots. Dielectric elastomers (DEs) are smart, soft materials that exhibit significant deformation under an electric field and have the characteristics of large strain, fast response, light mass, etc. Applying DEs in the effort to develop bionic robots affords a unique advantage. This study introduces an eel-inspired swimming robot. First, a cylindrical dynamic model of a DE is established. Second, considering the eel as the bionic object, a tube actuator and tube joint driving module are designed to improve manufacturability. Finally, the tube drive module is connected and the head part, tail part and tail fin are installed to make an eel-like robot based on a DE. A kinematic model of the eel-like robot is established, its forward motion speed is studied, and its propulsion speed, swimming number and swimming shape are analyzed. The results show that the robot can realize an S-type angle swinging motion.

Anoikis-related biomarkers PARP1 and SDCBP as diagnostic and therapeutic targets for asthma

Abstract This study aims to explore the association between anoikis-related genes (ARGs) and asthma. The dataset GSE143303 for asthma were sourced from the GEO database, while ARGs were retrieved from the Harmonizome web portal and the GeneCards database. Differentially expressed genes (DEGs) identification and GO, KEGG enrichment analysis were performed to reveal potential biological pathways. To identify hub anoikis-related DEGs (hub ARDEGs), we employed WGCNA and machine learning methods including LASSO and Random Forest. Additionally, we constructed risk prediction nomogram model and ROC curves to evaluate the asthma diagnostic value of hub ARDEGs. SsGSEA immune infiltration analysis was used to analyze the role of hub ARDEGs in the asthma immune microenvironment. Finally, miRNAs and transcription factors (TFs) interacting with these hub ARDEGs were investigated. DEGs of ARGs between asthma and healthy controls, along with WGCNA, led to the identification of six ARDEGs. GO and KEGG analyses revealed that these ARDEGs were primarily involved in the apoptotic signaling pathway and adherens junctions. Machine learning methods further narrowed down the six ARDEGs to two hub ARDEGs: PARP1 and SDCBP, which were significantly upregulated in asthma and validated using the GSE147878 and experimental models. Based on these two hub ARDEGs, a risk prediction model for asthma was developed, demonstrating strong diagnostic potential and tissue specificity in endobronchial biopsies. Immune analysis revealed variations in immune cell infiltration within asthma samples correlated with hub ARDEGs. Additionally, the miRNA-TF-mRNA interaction network of hub ARDEGs highlights the complexity of the regulatory process. The process of anoikis, immune dysregulation, and asthma are closely interconnected. The anoikis-related biomarkers PARP1 and SDCBP may serve as diagnostic markers and therapeutic targets for asthma.

<i>De Novo</i> Peptides That Induce the Liquid–Liquid Phase Separation of α-Synuclein

The study on the live streaming frequency strategy choices of streamers in live E-commerce

Live-streaming e-commerce, emerging as a novel business model, has garnered considerable attention from leading platforms and brands. It not only exerts a profound influence on consumers’ lifestyles and consumption habits but also presents brand owners with a fresh sales model. This paper focuses on the perspective of the live-streamer and explores the scenario where a live-streamer sells two competing products through live shows. By constructing three models—single live show, two live shows with information disclosure, and two live shows without information disclosure—it is discovered that, when the proportion of fans for the live-streamer is relatively low, the live-streamer opts for the two live shows strategy without information disclosure. When fan percentage is elevated and product competition diminishes, the streamer consistently favors the single live-show strategy. As the proportion of fans is moderate and product competition diminishes, the streamer increasingly favors a two live show strategy that includes disclosed product information. Furthermore, when the live show interval is short and the proportion of live-streamer fans is small, the live-streamer prefers to adopt the two live show strategies without product information disclosure; when the live show interval is long, the live-streamer prefers the two live show strategies under product information disclosure. When there is a high proportion of fans, regardless of the length of the interval between the two live shows, the live-streamer prefers the single live show strategy.

The prognostic significance of MMP-8 tissue Immunoexpression in pancreatic ductal adenocarcinoma after neoadjuvant therapy

Quantum Hydrogen Tunneling in an Iridium Dihydride Complex

Clinical prediction of intravenous immunoglobulin-resistant Kawasaki disease based on interpretable Transformer model

Intravenous immunoglobulin (IVIG) has been established as the first-line therapy for Kawasaki disease (KD). However, approximately 10%–20% of pediatric patients exhibit IVIG resistance. Current machine learning (ML) models demonstrate suboptimal predictive performance in KD treatment response prediction, primarily due to their limited ability to effectively process categorical variables and interpret tabular clinical data. This study aims to develop and interpretable transformer-based clinical prediction model for IVIG resistant KD and validate its clinical utility. This retrospective study analyzed clinical records of KD patients from the Affiliated Hospital of North Sichuan Medical College (Nanchong, China) between January 1, 2014 and December 31, 2024. A cohort of 1,578 pediatric KD cases was systematically divided into training and validation sets. Six machine learning algorithms - Random Forest (RF), AdaBoost, Light Gradient Boosting Machine (LightGBM), eXtreme Gradient Boosting (XGBoost), Categorical Boosting (CatBoost), and Tabular Prior-data Fitted Network version 2.0 (TabPFN-V2) - were implemented with five-fold cross-validation to optimize model hyperparameters. Model performance was rigorously evaluated using seven metrics: accuracy, precision, recall, F1-score, Matthews correlation coefficient (MCC), area under the receiver operating characteristic (ROC-AUC), and area under the precision-recall curve (PR-AUC). The top-performing model was subsequently subjected to interpretability analysis through Shapley Additive Explanations (SHAP) to elucidate feature contributions. The transformer-based TabPFN-V2 model demonstrated superior predictive performance in KD analysis, achieving an impressive validation set accuracy of 0.97. Comprehensive evaluation metrics confirmed its robust performance: precision 0.98, recall 0.97, F1-score 0.98, MCC 0.95, ROC-AUC 0.99, and PR-AUC 0.99. Global interpretability analysis through kernel SHAP methodology identified the ten most influential predictive features ranked by significance: Coronary artery lesions (CAL), Aspartate aminotransferase (AST), C-reactive protein (CRP), whether it was incomplete KD (KDtype), Neutrophil count (N), Platelet count (PLT), Albumin (ALB), age, White blood cell count (WBC) and Hemoglobin (Hb). Local interpretability analysis revealed distinct correlation patterns with IVIG resistance:AST, CRP, and N demonstrated significant positive correlations, where elevated values corresponded to increased IVIG resistance risk; PLT and ALB showed negative correlations, with higher levels associated with reduced resistance probability. Notably, age and WBC parameters demonstrated threshold effects, where optimal cutoff values enabled re-calibration of single-variable predictive scores. This threshold-dependent relationship suggests potential clinical utility in risk stratification protocols.The TabPFN-V2 model, leveraging an interpretable transformer architecture, demonstrates dual clinical utilities in KD management: (1) accurate prediction of IVIG resistance risk, and (2) data-driven support for personalized therapeutic decision-making. This framework enables probabilistic estimation of treatment resistance likelihood while providing transparent feature contribution analyses essential for developing patient-specific management protocols.

Publisher Correction: Digital removal of dermal denticle layer using geometric AI from 3D CT scans of shark craniofacial structures enhances anatomical precision

Dynamic Relocation of Copper Catalysts in Gas Diffusion Electrodes during CO₂ Electroreduction

Emotional skills and health assessment in interventions for intimate partner violence perpetrators: A systematic review of randomized controlled trials

The present study had two objectives: 1) To analyze the effectiveness of intervention programs for intimate partner violence (IPV) perpetrators that include learning emotional skills; and 2) to examine whether these programs assess variables related to the health and well-being of IPV perpetrators as a result of the intervention, and whether the obtained personal benefits are leveraged to enhance motivation towards therapy. This systematic review was carried out following the PRISMA guidelines. PsycINFO, PubMed, Scopus and PsycARTICLES databases were searched for articles published between January 2000 and December 2023, in order to identify randomized controlled trials of interventions for IPV perpetrators that included learning emotional skills, and that considered the health and well-being of the participants as motivational aspects in therapy. Fifteen primary studies that met the selection and eligibility criteria were included. The results indicated that slightly over half of the intervention programs for IPV perpetrators who develop emotional competencies were more effective in reducing recidivism and improving variables associated with this type of violence than were those that did not include this type of learning (53% of the trials showed significant differences in favor of the intervention groups). In addition, it became evident that the personal benefits obtained by the participants during therapy, which are related to their health and degree of well-being, are barely considered in efforts to improve motivational strategies. These results have important practical implications: firstly, they allow adjusting the contents of intervention programs for IPV perpetrators more effectively and, secondly, they add new elements that help the participants to improve their motivation and adherence to therapy.

Drug-induced xerostomia and hyposalivation in patients with overactive bladder: a prospective open-label observational study comparing antimuscarinics and β3-adrenoceptor agonists

Abstract Drug-induced xerostomia significantly affects quality of life. This study evaluated subjective and objective oral dryness in 101 patients with overactive bladder (OAB) receiving solifenacin (5 or 10 mg) or mirabegron (50 mg). Fox and Xerostomia Inventory questionnaires assessed subjective xerostomia, while unstimulated salivary flow measured objective changes. Overall, salivary flow declined from 0.35 to 0.27 ml/min (− 15.1%; p &lt; 0.001), with the greatest reduction in the solifenacin 10 mg group (− 19.3%; p &lt; 0.001). Mirabegron had a minimal, non-significant impact (− 5.9%; p = 0.42). Hyposalivation prevalence rose from 12.9% pre-treatment to 25.7% post-therapy (p &lt; 0.001), especially among solifenacin users. Men had higher baseline salivation (0.45 vs. 0.27 ml/min; p &lt; 0.001), though both sexes experienced comparable proportional decreases. Mirabegron in multivariable analysis markedly reduced the risk of hyposalivation (OR 0.12, 95% CI 0.02–0.90), whereas hypertension increased it six-fold (OR 6.13, 95% CI 1.02–36.78); each additional 0.1 mL of baseline saliva independently decreased the odds (OR 0.32, 95% CI 0.27–0.38). These findings underscore the need for collaboration among urologists, dentists, and otolaryngologists to identify high-risk individuals early and implement preventive strategies. Adjusting OAB pharmacotherapy regimens may help optimize treatment efficacy while minimizing xerostomia’s detrimental impact on oral health and patient quality of life.

High-Throughput Electrochemical Delamination of Two-Dimensional Covalent Organic Frameworks

C1-linker region of PARG1 RhoGAP promotes the catalytic recognition fold of RhoA substrate

PARG1 (ArhGAP29) belongs to a class of F-BAR proteins that contain a GTPase activating (GAP) domain that stimulates the GTP-to-GDP conversion of RhoGTPases. In this study, the substrate-recognition mechanism of human PARG1 was structurally modeled in computational approaches. Docking analysis using HDOCK showed that the predicted RhoGAP domain containing the N-terminal C1 region harbored structural determinants only for RhoA recognition with its catalytic loop and the α4- and α9–10 helices of the GAP domain. Molecular dynamics of wild-type PARG1-RhoA complex revealed that the predicted C1 structure depicted unique interface for the α3 helix of RhoA, leading to stable interaction with the RhoA substrate. Interestingly, RhoA interacted with the C1-GAP domains with missense mutations such as p.Thr622Met (T622M) and p.Ile845Val (I845V) differently, but the several interface residues in the catalytic loop and C-terminal α9-α10 helices were not matched to the known crystallized complexes in molecular dynamics simulation. PARG1 I845V mutant complex was theoretically deduced to disorganize RhoA interfaces and T622M mutation decreased the substrate affinity to 80% of that of WT PARG1 complex. The C-terminal C1 domain that formed a coiled-coil structure in a wild-type specific manner and the loop regions adjacent to the GAP region modulated the corresponding C1 interaction interfaces in RhoA. There were differences in motions of the conserved and variable interface residues among RhoGAP domains that locate in the α9–10 loop and C-terminal α4 and N-terminal α9−10 helices of the GAP domain between WT and mutant RhoGAP-RhoA complexes. The stable RhoA interaction specific to wild-type PARG1 is attributed to the motions of the GAP region including the C1 domain, in contrast to mutant PARG1 GAP domains that tended to disorganize the catalytic complex.

Mapping residual stresses in AlSi10Mg alloy fabricated by powder bed fusion-laser beam method

Abstract Residual stresses in metal alloys fabricated by the powder bed fusion-laser beam (PBF-LB) method exhibit anisotropy influenced by laser scanning and building orientations. This study maps nanoscale residual stresses within a single grain of PBF-LB AlSi10Mg alloy using various transmission electron microscopy (TEM) modalities. Residual stress maps were obtained for both as-built and T6 heat-treated samples along scanning and building orientations. Post-analysis revealed that T6 heat treatment reduced tensile stress compared to as-built samples. For example, in the [1̅00] crystallographic direction, average tensile and compressive residual stresses in the building direction decreased by ~ 70% after T6 treatment. Anisotropy in residual stresses was also observed; in the [1̅00] direction, average residual stresses in scanning orientation were ~ 13% and ~ 23% higher than the building direction in as-built and T6-treated samples, respectively. Heat treatment effects were further examined using image-based finite element method (FEM) simulations to understand the stress-driven mechanisms behind Si eutectic break-up and Si precipitate diffusion into the Al matrix. The results revealed regions of tensile and compressive stress within Si eutectic zones, identifying them as sources for Si diffusion and nucleation of Si-based precipitates within the matrix.

Electroreductive Borylation of Chloroalkanes and Polyvinyl Chloride Plastics

A retrospective analysis from NHANES 2003–2018 on the associations between inflammatory markers and coronary artery disease, all-cause mortality and cardiovascular mortality

Background The objective of this research was to investigate the associations between inflammation markers and coronary artery disease (CAD), along with all-cause mortality and cardiovascular mortality. Methods This study utilized data from the National Health and Nutrition Examination Survey (NHANES) collected between 2003 and 2018. The platelet-to-lymphocyte ratio (PLR), neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), and systemic immune inflammation index (SII) were calculated based on blood test results. The diagnosis of CAD was obtained from self-reported cardiovascular health questionnaires. Participants’ survival status was sourced from the National Death Index (NDI) of the National Center for Health Statistics (NCHS). Logistic and Cox regression models were employed to investigate the associations between PLR, NLR, MLR, and SII with CAD, all-cause mortality, and cardiovascular mortality. Results A total of 32,683 individuals from the 2003–2018 NHANES were involved. After adjusting for potential confounders, each 1-unit increase in log (NLR) and log (MLR) was associated with a 29% (95% CI: 1.15–1.46, P &lt; 0.001) and 67% (95% CI: 1.40–1.99, P &lt; 0.001) increase in the risk of CAD, respectively. Notably, when log (PLR) exceeded 4.93(PLR = 138.38) and log (SII) surpassed 6.11(SII = 450.34), the risk of CAD increased sharply (P &lt; 0.001). Furthermore, individuals in the highest quartiles (Q4) of PLR, NLR, MLR, and SII had significantly higher risks of all-cause mortality (13%, 88%, 91%, and 42%, respectively) and cardiovascular mortality (48%, 194%, 139%, and 90%, respectively) compared to those in the lowest quartile (Q1), with all P-values &lt;0.001. Moreover, MLR had the highest the area under the curve (AUC) value (AUC:0.642, 95% CI: 0.629–0.654), followed by NLR (AUC:0.600, 95% CI: 0.587–0.612) for distinguishing CAD. Conclusion In this study, we found that PLR, NLR, MLR, and SII were associated with increased prevalence of CAD, as well as increased risks of all-cause and cardiovascular mortality. These inflammatory markers may serve as valuable clinical indicators for CAD, all-cause and cardiovascular mortality in the general population.

Memory reactivation during rest forms shortcuts in a cognitive map

Abstract Efficient and flexible cognition relies upon cognitive maps—representations of concepts and the relations between them. Cognitive maps integrate relations that were learned separately into a cohesive whole. Memory reactivation during rest and sleep may contribute to cognitive map formation in two ways: by simply strengthening memories for directly experienced relations, or by reorganising concepts and creating new relations that capture the underlying structure. We designed a multi-stage learning task to test whether reactivation during rest is involved in restructuring memories as opposed to simply consolidating what was experienced. We causally manipulated memory reactivation during rest using awake, contextual targeted memory reactivation. We found that promoting memory reactivation during rest qualitatively reorganises the cognitive map by forming ‘shortcuts’ between events which have not been experienced together. These shortcuts in memory extend beyond direct experience to facilitate our ability to make novel inferences. Using a series of control tests we show that inference performance cannot be explained by quantitative strengthening of the experienced component links. Interestingly, we show that representing a shortcut may come with limitations, as shortcuts cannot be readily updated in response to rapid changes in the environment. Together, these findings reveal how memories are reorganised during awake rest to construct a cognitive map of our environment, while highlighting the constraints set by a trade-off between efficient and flexible behaviour.

A Concise Total Synthesis of Glycinoeclepin A

Understanding the needs of undergraduate healthcare students in relation to suicide prevention training: A qualitative study

Background International evidence indicates that many healthcare workers are not adequately prepared to support patients during suicidal crises. As a result, healthcare students need appropriate training in order to effectively intervene once they qualify. In Ireland, there is no standardised suicide prevention training for students who are undertaking a degree in the health professions. The aim of this study was to explore the perspectives of undergraduate healthcare students to inform the design, implementation and evaluation of a suicide prevention module. Methods Ethical approval was obtained to conduct focus groups with undergraduate healthcare students. Recruitment was by convenience and snowball sampling within the research team’s networks. Eligible participants for this study were students over the age of 18 who were enrolled in an undergraduate healthcare course. Focus groups were held online via MS Teams, and were subsequently transcribed and qualitatively analysed using Braun and Clarke’s thematic analysis. Results A total of 12 participants from Graduate Entry Medicine (n = 9) and Pharmacy (n = 3) took part across four focus groups, which averaged 53 minutes in duration. Six key themes emerged from the data: (i) the need for suicide prevention training for healthcare students; (ii) “tiptoeing” around the topic of suicide; (iii) creating a safe environment; (iv) student self-care and support – different strokes for different folks; (v) module implementation and (vi) appropriate teaching methodologies. Conclusions Healthcare students would positively receive the embedding of suicide prevention training into their respective degrees. The findings of this study serve to include the student voice in a suicide prevention curriculum design, and have since been used to inform its subsequent pilot and evaluation. This will ultimately improve the suicide prevention knowledge and competence of our future healthcare professionals.