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Should Coronary CT Angiography or Coronary Artery Calcium Testing Be Used to Guide Primary Prevention?
BST-2 inhibits SARS-CoV-2 egress at intracellular membranes and is neutralized by ORF7a
Dysregulated T Cell–Mediated Immunity Underlies Progression of Arrhythmogenic Right Ventricular Cardiomyopathy
Cold plasma, Fe and Mn nanoparticles modulate antioxidant activity, cannabinoids gene expression, and fatty acid profile in salt-stressed hemp
Letter by Jiang et al Regarding Article, “Sacubitril/Valsartan and Prevention of Cardiac Dysfunction During Adjuvant Breast Cancer Therapy: The PRADA II Randomized Clinical Trial”
Prediction of carbon dioxide solubility in sugar-water-alcohol solutions at high pressure for application to sparkling drinks
Abstract In the beverage industry, the CO 2 pressure and dissolved CO 2 reached in their packaged beverage play an important role. In this regard, the work aims to develop a thermodynamic model for the prediction of the phase equilibrium behavior of quaternary CO 2 –sugar–water-alcohol solutions up to high pressures. The Perturbed Hard Sphere Chain (PHSC) equation of state (EoS) has been used to predict the solubility of CO 2 in glucose-water-alcohol solutions. Glucose molecules have been modeled as a chain-like molecule with ten association sites. Cross-association between CO 2 , glucose, and water molecules has been considered. Temperature-dependent binary interaction parameter (BIP) has been considered to improve the model performance. The solubility of glucose in water and ethanol has been estimated at various temperatures. As well, the vapor-liquid equilibrium behavior of the ternary CO 2 -glucose-water system has been predicted. The results show that the model can predict the solubility of CO 2 in a glucose-water mixture satisfactory. In some sparking drinks, ethanol is widely used. In this regard, the prediction of CO 2 solubility in the water-ethanol-glucose mixture has been investigated. The vapor-liquid equilibrium of the quaternary CO 2 -water-ethanol-glucose system has been predicted up to 30 MPa without using any additional adjustable parameter. The results show that, the deviation between model and experimental data in liquid and vapor phases increases by increasing ethanol concentration. The proposed model can be used for the prediction of CO 2 solubility and equilibrium compositions of quaternary CO 2 -water-ethanol-glucose system over a wide range of pressures, temperatures, and sugar (or ethanol) concentrations.
Expression of Concern: Evaluating the compressive strength of glass powder-based cement mortar subjected to the acidic environment using testing and modeling approaches
Adaptive AI for Cardiovascular Event Adjudication: Cardiovascular Event Adjudication Across Different Definitions in the ODYSSEY OUTCOMES and EUCLID Trials
BACKGROUND: Clinical end point classification (CEC) is the gold standard for cardiovascular end point measurement in clinical trials but adds time and cost. We developed and validated an artificial intelligence (AI) algorithm (adaptive AI for CEC [ADAPT-CEC]) that adjudicates multiple cardiovascular end points and adapts to new definitions. METHODS: ADAPT-CEC was derived from myocardial infarction (MI), stroke, and heart failure from the ODYSSEY OUTCOMES (Evaluation of Cardiovascular Outcomes After an Acute Coronary Syndrome During Treatment With Alirocumab) trial and externally validated on MI, stroke, bleeding and cardiovascular (CV) death from the EUCLID (Examining Use of Ticagrelor in Peripheral Artery Disease) trial after adaptation with 20 EUCLID suspected events per end point. ADAPT-CEC was compared via F1 score with direct Generative Pretrained Transformer (GPT) 4o adjudication and a hybrid approach where the 30% of suspected events with the lowest AI prediction certainty used human adjudication. The EUCLID primary end point of CV death, MI, or stroke was re-estimated for all 3 adjudication strategies. RESULTS: Among 13 885 suspected EUCLID primary end point events, ADAPT-CEC, hybrid, and GPT 4o strategies correctly classified 86.4%, 95.6%, and 76.3% of all end points and 99.4%, 99.6%, and 99.8% of all non–end points compared with human adjudication, respectively. Hybrid adjudication F1 metrics were the highest (CV death, 0.94 [95% CI, 0.92–0.96]; MI, 0.80 [95% CI, 0.77–0.82]; stroke, 0.82 [95% CI, 0.78–0.86]; bleeding, 0.83 [95% CI, 0.82–0.85]). ADAPT-CEC F1 metrics were lower for CV death, MI, and stroke but similar to GPT 4o, while bleeding (0.78 [95% CI, 0.77–0.79]) was superior to GPT 4o. The EUCLID primary treatment effect was similar by human adjudication (hazard ratio [HR], 1.02 [95% CI, 0.93–1.13]); hybrid (HR, 1.04 [95% CI, 0.94–1.15]); ADAPT-CEC (HR, 0.98 [95% CI, 0.88–1.09]), and GPT 4.0 (HR, 1.06 [95% CI, 0.95–1.19]) adjudication. CONCLUSIONS: After brief adaptation, a single trial–derived AI algorithm can adjudicate similar (MI and stroke) and new end points (CV death and bleeding) in a second trial and replicate the EUCLID primary outcome treatment effect. A hybrid approach with humans adjudicating those suspected events with the lowest 30% of ADAPT-CEC prediction certainty was superior to ADAPT-CEC alone or GPT 4o alone and replicated the EUCLID primary outcome treatment effect. Prospective studies of adaptive AI adjudication are needed to determine future trial implementation.
Selective photocatalytic mineralization of organic pollutants using eggshell- and seashell-based hydroxyapatite–TiO2 composites
Female cyclists perceived effects and experiences of the menstrual cycle on training and performance
The aim of this study was: (1) to understand female cyclist’s experiences and perceptions of the menstrual cycle (MC) on training and competition performance, and (2) to explore female cyclist’s comfort in having conversations relating to the MC with coaches and support staff. Twenty competitive female cyclists (age 35.1 ± 7.7 yrs, cycling for 11.9 ± 7.4 yrs, 3 elite, 7 sub-elite and 10 club cyclists) were interviewed using an open-ended, semi-structured approach. An inductive thematic analysis was conducted. Female cyclists’ experiences and perceptions of the MC on training and competition performance were wide ranging with participants reporting a range of MC symptoms that varied in severity and timing in the MC. 45% of the cyclists had experienced irregular MCs either currently or in the past with participants suggesting possible causes may be due to low body weight and insufficient energy intake to support training. 73% of the participants spoke to their coach about their MC, but typically this was limited to a note on their training programme that they started their period, or a brief mention of how they are feeling. Participants highlighted the positive influence of elite athletes talking about their MCs in terms of accepting the influence of MC on performance and improving openness of conversation. Most participants said they lacked knowledge about the MC and how to manage MC related symptoms. The findings highlight the need for improved education on the MC in sport for cyclists and coaches to improve performance and athlete health and wellbeing.
Defective Trophoblast Differentiation, Endothelial Dysfunction, and Immune Dysregulation in Preeclampsia Coalesce on a Placental VGLL3-Centered Gene Network
BACKGROUND: Preeclampsia affects approximately 1 in 10 pregnancies, leading to severe complications and long-term health risks for both mother and offspring. While the etiology remains unclear, preeclampsia has been linked to both autoimmunity and the timing of menarche. METHODS: Through human single-cell and spatial analyses, coupled with in vitro, in vivo, and ex vivo models, we demonstrate that VGLL3 (Vestigial-like family member 3), a transcription coregulator in the Hippo pathway, is upregulated in preeclamptic placentas. RESULTS: VGLL3 promotes immune activation, impairs trophoblast differentiation, and induces endothelial dysfunction, all of which contribute to pregnancy-related hypertension, fetal growth restriction, and offspring mortality. Our data reveal that VGLL3 acts upstream of preeclampsia-associated processes, including the production of sFLT1 (soluble fms-like tyrosine kinase 1), a key biomarker of the disease. Notably, targeting VGLL3, either by genetic deletion in mouse placentas or through therapeutic inhibition in human placentas, protects against preeclampsia and alleviates disease pathology. CONCLUSIONS: These findings position VGLL3 as a promising novel therapeutic target for preeclampsia.
The application of rapid ultrasound-guided paraffin technique in the pathological examination of biopsy specimens from non-small cell lung cancer
Correction: Validation of the Arabic Levels of Emotional Awareness Scale (LEAS-Arb)
Role of Atrial Pacing Support in Cardiac Resynchronization Therapy: A Noninferiority Randomized Trial
BACKGROUND: The role of atrial pacing support is unclear in patients receiving cardiac resynchronization therapy–defibrillator (CRT-D) without sinus node dysfunction. METHODS: We conducted a randomized, parallel-group, noninferiority trial to evaluate whether a 2-lead CRT-D capable of atrial sensing (but no pacing) by a floating dipole on the right ventricular lead (CRT-DX) is not inferior to a 3-lead CRT-D with a conventional atrial lead. Between October 17, 2018, and March 5, 2024, a total of 636 patients (68±10 years old, 28.6% women) with standard CRT-D indication, optimized medical therapy, and resting sinus rate ≥45 beats/min were randomized 1:1 to CRT-DX (atrial tracking without atrial pacing mode 35 beats/min) or CRT-D (atrial tracking with atrial pacing mode 50 beats/min) at 23 Italian sites. A centralized block-randomization procedure stratified by site was used, with patients and primary outcome assessors blinded to treatment assignment. The primary end point was a 1-year composite of all-cause mortality, cardiovascular hospitalization, and lead-related complications (loss of functionality not correctable by device reprogramming). Secondary end points included each individual component of the primary end point separately, echocardiographic reverse remodeling, and 6-minute walk test distance at 12 months. RESULTS: The primary end point occurred in 41 (13.1%) patients in the CRT-DX group and 47 (15.6%) patients in the CRT-D group, corresponding to a hazard ratio of 0.82 (95% CI, 0.54–1.25). This confirmed noninferiority (prespecified relative margin of 1.20) in both the per-protocol ( P =0.039) and intention-to-treat ( P =0.044) analyses. Individual components showed no significant differences, except for lead complications related to right atrial functionality (4 [1.3%] patients in the CRT-DX group versus 13 [4.2%] patients in the CRT-D group; P =0.040). Reverse remodeling responders were 203 (77.5% of 262) patients receiving CRT-DX and 190 (76.3% of 249) patients receiving CRT-D ( P =0.83). Walking distance did not differ between 2 study arms (404 versus 398 m; P =0.62). After a median follow-up of 2.4 years, only 1 patient receiving CRT-DX required implantation of a standard atrial lead. CONCLUSIONS: The 2-lead CRT-DX system without atrial pacing is noninferior to conventional 3-lead CRT-D, with fewer atrial lead–related complications. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT03587064.
Development and validation of a clinical prediction model for the success of focused ultrasound ablation system for the treatment of adenomyosis
Abstract This study aimed to develop and validate a clinical prediction model for the success of the focused ultrasound ablation system (FUAS) in treating adenomyosis. A retrospective analysis was conducted on 250 patients from Qingdao Women and Children’s Hospital (2019–2022). Patients were categorized into success ( n = 108) or failure ( n = 142) groups based on a post-treatment lesion ablation rate greater than 80%. The dataset was split into training (70%) and validation (30%) sets. The multivariable analysis identified age (OR = 1.10, P = 0.014), depth of adenomyosis (OR = 1.03, P = 0.036), and uterine body (OR = 0.25, P = 0.027) as independent predictors of FUAS efficacy, which were used to build the model. In the training set, the model achieved an AUC of 0.74 for efficacy prediction. The Bootstrap ROC indicates an AUC mean of 0.751 with a standard deviation of 0.036. In conclusion, a model based on age, depth of ademyosis, and uterine body lesions treatment dose accurately predicts FUAS success for adenomyosis. This tool can aid clinical decision-making and promote personalized treatment.
Exploring translator’s style in children’s literature: A case study of Nicky Harman’s English translations of Huang Beijia’s two works
Huang Beijia’s contemporary Chinese novels Wo Yao Zuo Hao Hai Zi (a contemporary realistic children’s novel, 1996) and Ye Feng Fei Wu (a historical novel for children, 2018), translated into English by Nicky Harman as I Want to Be Good (2020) and Flight of the Bumblebee (2023), offer valuable insights into translator’s style in rendering Chinese children’s literature for English readers. Building on Baker’s (2000) translator’s style in corpus-based translation studies (CTS) that manifests translator’s recurrent patterns, this study investigates Harman’s stylistic choices at the lexical, syntactic, and textual level to reveal how Chinese specific elements are represented for target readers. A self-built bilingual corpus (parallel and comparable; 398,531 words total) enables a mixed-methods approach, integrating quantitative metrics (such as keyword analysis, readability index by Qt Readability, etc.) with qualitative close reading. By analyzing typical translation examples and the para-texts of Harman’s translated works, this study aims to explore the reasons behind Harman’s translation style and the relationship between the translator’s views on translation and translation choices. The results reveal the existence of a distinctive translator’s style and show that vividness, purity and joy reflected in the original children’s literature as the ST style has been reproduced in Harman’s translation. A preference for contracted forms (’s,’ve, ’d, etc.) and more strategic and habitual use of certain collocations (such as the employment of “keep an eye on…”, “as far as the eye could see”, etc.), tentative efforts in balancing domestication and foreignization in the translation of Chinese four-character idioms, the multimodal interaction employed by Harman as her special consideration for the young readership, etc. have all contributed to Harman’s translator’s style in translating children’s literature. These findings will contribute to the study of translator’s style and deepen the research of the English translation and international dissemination of Chinese children’s literature under the methodology of corpus-based research.
Letter by Qin et al Regarding Article “Dapagliflozin in Patients Hospitalized for Heart Failure: Primary Results of the DAPA ACT HF-TIMI 68 Randomized Clinical Trial and Meta-Analysis of Sodium-Glucose Cotransporter-2 Inhibitors in Patients Hospitalized for Heart Failure”
A strong robust multi level database image watermark embedding scheme based on the Chinese remainder theorem
A data-driven framework for modeling the dendritic spine continuum using dimensionality reduction and clustering toward understanding synaptic plasticity
Dendritic spines are dynamic extensions of dendrites that change in shape and distribution in response to neuronal activity, playing central roles in memory and learning. Computational methods are widely used to characterize spine morphology, yet feature selection, dimensionality reduction, and clustering choices are often made a priori and evaluated independently, and as a result it remains unclear how analysis decisions influence low-dimensional representations of spine shape and the biological interpretations drawn from them. We present a decision-based visual characterization framework that systematically evaluates dimensionality reduction and probabilistic clustering strategies for dendritic spine morphometry. Using a labeled two-photon laser scanning microscopy (2PLSM) dataset and a secondary dataset with differing imaging conditions to assess generalization, we compare PCA, ISOMAP, t-SNE, UMAP, and PCUMAP alongside hierarchical clustering, Fuzzy C-Means, and Gaussian Mixture Models. We additionally introduce a Biological Transition Score (BTS) to quantify how well low-dimensional embeddings reflect known developmental and functional relationships among spine types. Across datasets, dimensionality reduction methods capture complementary aspects of spine morphology. On the primary dataset, nonlinear approaches better preserve fine-scale structure, with PCUMAP providing a favorable balance between local structure preservation and global continuity. In contrast, analysis of a lower-resolution secondary dataset shows that PCA is more robust under increased feature-level noise. These findings demonstrate that the optimal dimensionality reduction strategy is dataset-dependent, underscoring the importance of systematic, data-driven method selection. When paired with probabilistic clustering, these representations reveal a morphological continuum that bridges classical “mushroom,” “stubby,” and “thin” spine categories. Increasing the number of identified sub-groups preserves or strengthens structural organization relative to expert-labeled classes, demonstrating that weakly supervised representations can resolve intra-class heterogeneity beyond discrete manual classifications. This framework provides a structured, quantitative approach for selecting dimensionality reduction and clustering strategies, enabling more consistent and biologically grounded interpretations of dendritic spine morphology.