Lipidomic Signature of Abdominal Aortic Aneurysm and Peripheral Artery Disease.

Vascular diseases are powerful predictors of cardiovascular mortality, but they are typically under-recognized and undertreated. There is no effective treatment for either abdominal aortic aneurysm (AAA) or peripheral artery disease (PAD). Lipids are key molecules in cardiovascular diseases and good candidates for diagnosis, monitoring, and risk prediction; nonetheless, there is very limited information on the lipidomic profile of patients with AAA and PAD.

Response to biologics along a gradient of T2 involvement in patients with severe asthma: a data-driven biomarker clustering approach.

Background: Asthma with low levels of T2-biomarkers is poorly understood.

Objective: To characterize severe asthma phenotypes and compare pre- to post-biologic change in asthma outcomes along a gradient of T2-involvement.

Methods: This was a registry-based, cohort study including data from 24 countries.

Beyond black boxes: using explainable causal artificial intelligence to separate signal from noise in pharmacovigilance.

Artificial intelligence (AI), particularly machine learning (ML), is increasingly influencing pharmacovigilance (PV) by improving case triage and signal detection. Several studies have reported encouraging performance, with high F1 scores and alignment with expert assessments, suggesting that AI tools can help prioritize reports and identify potential safety issues faster than manual review. However, integrating these tools into PV raises concerns.

International Magnetic Resonance Imaging Consensus for use in Luminal Crohn's Disease Trials and Clinical Practice.

Background And Aims: Cross sectional imaging is an integral part of evaluating disease activity and complications in Crohn's disease. There remains a need to develop guidance that may be for both clinical trials and clinical practice. This initiative aimed to develop consensus statements for definitions of response and remission, transmural healing, optimal timing for assessing, and evaluation of treatment efficacy in patients with Crohn's disease using magnetic resonance enterography (MRE) in clinical trials and clinical practice.

Real-Life Clinical Validation of AI-Assisted Detection and Differentiation of Pleomorphic Lesions in Capsule Endoscopy.

Background And Aims: Capsule endoscopy (CE) is a minimally invasive procedure designed for small bowels' evaluation. However, prolonged reading times and a risk of missing clinically significant findings limit its potential. Prospective clinical validation studies of artificial intelligence (AI) for CE remain scarce.

Challenges in the preclinical design and assessment of CAR-T cells.

The advent of immunotherapy in the treatment of cancer has opened a new dimension in the management of this complex multifaceted disease, bringing hope to many patients whose tumors have failed to respond to conventional therapies. The adoptive T cell therapy has since been extended to the treatment of several hematologic malignancies, initially in relapsed settings and more recently at the forefront of treatment due to high response rates. Despite exciting initial results, the preclinical antitumor effects of the first long-term studies show that CAR (Chimeric Antigen Receptor)-T cells have been slow to translate to the clinical setting, with early clinical trials showing suboptimal responses.

Pilot study on near-infrared spectroscopy in peripheral artery disease: Differentiating upper and lower limbs and its correlation with the ankle-brachial index.

Peripheral artery disease (PAD) is a global health challenge, with current diagnostic methods, including the ankle-brachial index (ABI), having limitations, particularly in patients with arterial calcification. Near-infrared spectroscopy (NIRS) offers potential advantages as a non-invasive assessment tool, yet its clinical utility in PAD remains underexplored. This pilot study evaluated NIRS for differentiating between non-ischemic upper limbs and ischemic lower limbs, and assessed NIRS correlation with ABI.

Stopping antihypertensive Treatment amOng hypertensive patients in Primary care: The STOP-Trial.

Background: Antihypertensive therapy (AHT) is usually lifelong. The feasibility of discontinuing AHT in selected individuals is insufficiently studied.

Aims: To assess the feasibility of discontinuing AHT in patients on monotherapy or low-dose dual therapy, and identify factors associated with maintaining normotension without treatment for one year.

ESR Essentials: juvenile idiopathic arthritis; what every radiologist needs to know-practice recommendations by the European Society of Paediatric Radiology.

Juvenile Idiopathic Arthritis (JIA) is a major contributor to chronic diseases, affecting around 1-2 in 1000 children under the age of 16. With modern treatments, the morbidity has been reduced; however, there is increasing evidence that many, if not most, children with JIA will have a chronic disease with ongoing activity into adulthood. Many studies discuss the possibility of an early window of opportunity in which patients have the best chance of responding to therapy, thereby underscoring the importance of timely and appropriate imaging.

Identifying essential COVID-19 indicators for primary healthcare through Delphi analysis in 31 European countries: Eurodata eDelphi study.

Background: The COVID-19 pandemic has underlined the essential role of primary healthcare (PHC) in epidemiological surveillance and public health decision-making. Across Europe, the integration of electronic health records (EHRs) and the sentinel networks have been pivotal in monitoring COVID-19. However, the lack of standardized PHC indicators for COVID-19 hinders the comparability of data among countries.

Electromyographic assessment of agonist and antagonist muscles related to the anterior cruciate ligament following surgical Reconstruction: A Cross-Sectional study.

Background: Following anterior cruciate ligament reconstruction (ACLR), neuromuscular control alterations may persist, increasing the risk of reinjury.

Objectives: This study aimed to investigate electromyographic (EMG) muscle activation and the co-contraction index (CCI) of ACL-related agonist and antagonist muscles during side-hop tasks in ACLR individuals, offering novel insights into neuromuscular strategies during dynamic tasks.

Methods: A cross-sectional study was conducted with 15 ACLR individuals and 15 participants without ACL injury (N-ACLR).

GRADE Concept Paper 9: Rationale and process for creating a GRADE Ontology.

Context: As the rate of research production accelerates, the ability to efficiently and unambiguously communicate judgements relating to the synthesis, evaluation, and use of scientific information becomes paramount.

Perspective: Scientific information can be viewed as a "layered infrastructure" of data, evidence, knowledge, and use. The GRADE approach serves as a de facto data standard in this infrastructure, reducing ambiguity in claims to knowledge (in the form of judgements of certainty in the evidence when answering research questions) and level of commitment to possible solutions to problems (in the form of strength of recommendations for interventions).

A preliminary assessment of a stool-based microRNA profile for early colorectal cancer screening.

Colorectal cancer screening methods are well established worldwide as a fundamental pilar in CRC management, namely through non-invasive faecal occult blood testing. However, the limited sensitivity of faecal occult blood test for detecting precancerous lesions highlights the need to search for alternative tools, such as microRNAs (miRs). The main aim of this study was to identify stool-based miR profiles for early colorectal cancer detection.

Evaluation of Residual Axillary Lymph Node Metastases After Neoadjuvant Treatment in Breast Cancer.

Background: The present study aims to evaluate the volume of residual axillary nodal disease after neoadjuvant chemotherapy (NACT) in breast cancer.

Methods: Predictive factors for low-volume residual axillary nodal disease were analyzed in patients with histologically proven breast cancer (cT1-3 cN0-2) who were treated with NACT and surgery between 2015 and 2019.

Results: A total of 734 patients were analyzed.

Segmentation of coronary calcifications with a domain knowledge-based lightweight 3D convolutional neural network.

Cardiovascular diseases are the leading cause of death in the world, with coronary artery disease being the most prevalent. Coronary artery calcifications are critical biomarkers for cardiovascular disease, and their quantification via non-contrast computed tomography is a widely accepted and heavily employed technique for risk assessment. Manual segmentation of these calcifications is a time-consuming task, subject to variability.

Portuguese Pancreatic Club Perspective on the Surveillance Strategy for Intraductal Papillary Mucinous Neoplasms: When and How to Do It?

Background: Pancreatic cysts are increasingly recognized nowadays, with estimated prevalence that may reach 50% in aging populations. Most cysts are of benign origin, and only a small proportion has malignant potential, including intraductal papillary mucinous neoplasms (IPMNs). Since pancreatic cysts are common, the most important goal was to identify the small percentage at high risk of developing malignancy.

Kidney function trajectories before and after hospitalization for heart failure with reduced ejection fraction.

Background And Aims: Worsening kidney function is a key prognostic factor in heart failure (HF) with reduced ejection fraction (HFrEF). However, associations between kidney function trajectories and HF-related events remain unclear.

Methods: Longitudinal changes in estimated glomerular filtration rate (eGFR) before and after a HF-related event, defined as HF hospitalization or HF death, were examined using individual patient data from two clinical trials (EPHESUS and EMPHASIS-HF) and a real-world cohort (BARCELONA).

Artificial intelligence in pharmacovigilance: a narrative review and practical experience with an expert-defined Bayesian network tool.

Background: Pharmacovigilance is vital for monitoring adverse drug reactions (ADRs) and ensuring drug safety. Traditional methods are slow and inconsistent, but artificial intelligence (AI), through automation and advanced analytics, improves efficiency and accuracy in managing increasing data complexity.

Aim: To explore AI's practical applications in pharmacovigilance, focusing on efficiency, process acceleration, and task automation.

Translational mapping of mechanistic and biomarker-driven clinical trials in oral squamous cell carcinoma and oral potentially malignant disorders.

Oral squamous cell carcinoma (OSCC) and oral potentially malignant disorders (OPMDs) present a major global health burden because of limited progress in early detection and prevention. Understanding the integration of biomarkers and their mechanisms in ongoing clinical trials is critical for advancing precision strategies for oral oncology. A total of 105 interventional clinical trials were identified through a structured search of ClinicalTrials.

Patency and maturation rates after forearm arteriovenous fistulas: systematic review with meta-analysis.

Background: The growing burden of chronic kidney disease has significantly increased the demand for hemodialysis, with reliable vascular access being vital for treatment success. Although the radiocephalic arteriovenous fistula (AVF) remains the first option as a long term hemodialysis access, challenges related to aging patient population and prevalence of comorbidities may compromise maturation and durability. Therefore, this systematic review with meta-analysis aims to determine the patency and maturation rates of radiocephalic AVF, focusing on how different patient characteristics and surgical methodologies impact these rates.

Deep learning for multiclass tumor cell detection in histopathology slides of hereditary diffuse gastric cancer.

Hereditary diffuse gastric cancer (HDGC) is a rare condition where early tumor detection is challenging due to diffuse infiltration and tumor heterogeneity. Accurate identification of DGC cells is essential for understanding tumor behavior. This study aimed to develop deep learning models to automatically detect key tumor cell types-typical and atypical signet ring cells and non-signet ring tumor cells-in H&E-stained digital pathology slides from HDGC patients.

Enhanced dynamic cerebral autoregulation and impaired vasoreactivity may contribute to white matter damage in hypertension: A correlational tractography and transcranial Doppler study.

Hypertension (HT) is the leading risk factor for cerebral small vessel disease (CSVD). White matter lesions (WML) linked to CSVD are visible on conventional neuroimaging, likely reflecting late irreversible stages of the CSVD pathological cascade. Despite the prevalence of this disease, the mechanistic link between CSVD, hypertension and WML remains poorly understood.