Atrial fibrillation (AF) commonly complicates myocardial infarction (MI) and is associated with adverse outcomes. However, the prognostic significance of AF timing after MI remains incompletely understood.

We conducted a retrospective cohort study of 3390 patients with myocardial infarction, stratified by MI subtype (NSTEMI and STEMI). AF was categorized as early (during index hospitalization), late (after discharge), or absent. Clinical, echocardiographic, and angiographic data were collected. Outcomes were assessed using Kaplan-Meier analyses and log-rank testing. The association between AF timing and outcomes was evaluated using multivariable time-dependent Cox proportional hazards models with pairwise comparisons, adjusting for relevant demographic and clinical covariates. Predictors of late AF were evaluated using multivariable logistic regression.

Among patients with myocardial infarction, AF developed in 451 patients (13.3%), 114 with STEMI and 337 with NSTEMI, occurring as early AF in 249 and late AF in 202. Kaplan-Meier analyses demonstrated significant in long-term major adverse cardiovascular events (MACE), defined as recurrent myocardial infarction with or without repeat revascularization, stroke, and all-cause mortality, according to AF timing, with late AF associated with the poorest outcomes (p<0.001). In multivariable time-dependent Cox models, late-onset AF was independently associated with an increased risk of MACE (HR: 1.5 [1.0-2.2], p=0.044, HR: 2.4 [1.1-5.3], p=0.032 in NSTEMI and STEMI, respectively). In contrast, early AF was not consistently associated with long-term MACE after adjustment (HR: 0.7 [0.4-1.0], p=0.060, HR: 1.3 [0.8-2.3], p=0.327 in NSTEMI and STEMI, respectively). Pairwise comparisons confirmed higher risk with late AF compared with no AF. In contrast, the late versus early AF comparison did not reach statistical significance in STEMI, likely due to limited event numbers. In multivariable logistic regression, older age and diabetes mellitus were independently associated with the development of late AF.

AF timing after myocardial infarction is prognostically relevant. Late-onset, but not early, AF was independently associated with adverse outcomes in time-dependent analyses, supporting a temporal classification of AF.

Pancreatic ductal adenocarcinoma (PDAC) is frequently preceded by new-onset diabetes mellitus (NODM), yet differentiating PDAC-associated DM from type 2 diabetes (T2D) remains clinically challenging. We investigated whether plasma proteomic profiling combined with machine learning could discriminate these conditions. Plasma samples from individuals with PDAC (with and without DM), long-standing T2D, and controls were analyzed by MALDI-TOF mass spectrometry. Spectral features were processed through a nested cross-validation framework to prevent data leakage, and model interpretability was explored using SHAP values. In parallel, low-molecular-weight proteins were characterized by GeLC-MS followed by LC-MS/MS and differential abundance analysis. Machine learning models distinguished PDAC-associated DM from T2D with a balanced accuracy of 85%. Proteomic analyses identified distinct signatures in PDAC- associated DM, including downregulation of erythrocyte-related proteins and PPBP, and upregulation of acute-phase reactants such as FGA, CP, and SERPINA3. Treatment-naïve cases displayed increased circulating epithelial and keratin-associated proteins, which were attenuated after therapy, suggesting dynamic tumor-related remodeling. These findings demonstrate that integrating MALDI-TOF profiling with machine learning can capture plasma signatures associated with PDAC-associated DM. Although exploratory, this approach supports further validation in prospective cohorts aimed at improving PDAC risk stratification among individuals with NODM. SIGNIFICANCE: Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy with a dismal 5-year survival rate, primarily due to late-stage diagnosis. The frequent occurrence of new-onset diabetes mellitus (NODM) as a paraneoplastic syndrome offers a critical window for early detection. However, the clinical challenge of distinguishing PDAC-associated diabetes (PDAC-DM) from type 2 diabetes mellitus (T2D) has hindered the implementation of effective screening strategies. This study addresses this significant clinical problem by leveraging a multi-faceted proteomics approach. We demonstrate that the integration of MALDI-TOF mass spectrometry peptide profiling with machine learning algorithms can accurately discriminate PDAC-DM from T2D with 85% accuracy. Furthermore, we used LC-MS/MS to identify specific low molecular weight proteins that are differentially regulated between these conditions, providing a molecular basis for the observed discrimination. Our work is significant as it presents a novel, high-throughput pipeline for biomarker discovery that combines the scalability of MALDI-TOF with the analytical power of LC-MS/MS and machine learning. The identified plasma signatures hold strong translational potential to improve risk stratification in patients with new-onset diabetes, ultimately enabling earlier diagnosis of PDAC and improving patient survival prospects. This research directly contributes to the field of clinical proteomics by providing a robust methodological framework and candidate biomarkers for the early detection of one of oncology's most challenging diseases.

Type 2 diabetes mellitus (T2DM) is a complex metabolic disorder that significantly predisposes individuals to delirium and dementia through multifaceted neurobiological pathways. The essence of this neurocognitive decline involves mechanisms such as central insulin resistance, chronic low-grade inflammation, and mitochondrial dysfunction. While metformin remains the cornerstone of T2DM management, its impact on the central nervous system exhibits a "double-edged sword" nature, balancing intrinsic neuroprotective properties against the potential neurotoxicity associated with vitamin B12 deficiency. This review aims to systematically synthesize epidemiological and clinical evidence linking metformin to neurocognitive outcomes, contrasting its efficacy with newer glucose-lowering agents such as GLP-1 receptor agonists and SGLT2 inhibitors. In addition, it sheds light on the reciprocal connectivity between systemic metabolic regulation and direct CNS modulation, specifically elucidating AMPK activation, the autophagy-lysosome axis, and the gut-brain and liver-brain axes. We review these molecular mechanisms to delineate the delicate trade-off between neuroprotection and risk, providing a framework for precision pharmacotherapy and biomarker-guided stratification in high-risk T2DM populations.

The prevalence and characteristics of diabetes distress (DD) in Japanese adults with type 1 diabetes mellitus (T1D) remain unclear. Therefore, this study aimed to investigate the prevalence and associated features of DD in this population. A cross-sectional study was conducted using the Type 1 Diabetes Distress Scale (T1-DDS), the Problem Areas in Diabetes (PAID) scale, and the Hypoglycemia Fear Survey (HFS). Data from 117 adults with T1D were analyzed. Group comparisons were made using t-tests and anova, and associations were assessed using Spearman's rank correlation. Confirmatory factor analysis (CFA) was used to examine the structure of the T1-DDS.

Of the 144 screened participants, 117 (mean age: 50.6 ± 12.8 years; 44.4% male; mean diabetes duration: 18.1 ± 10.7 years; mean HbA1c: 7.6% ± 0.9%) were included in the analysis. Moderate and high DD were observed in 30.8% and 16.2%, respectively. Participants with high DD had significantly higher PAID and HFS-Worry/Behavior scores, despite no significant differences in age, sex, diabetes duration, or HbA1c. Among T1-DDS subscales, Powerlessness and Eating Distress had the highest mean scores. All subscale scores were correlated with total distress (rho = 0.636-0.916) and showed good internal consistency (Cronbach's alpha = 0.784-0.875). CFA supported the seven-factor structure with marginal-to-acceptable model fit.

DD is prevalent in Japanese adults with T1D. The T1-DDS can be a useful screening tool for identifying individuals experiencing diabetes-related emotional burden and guiding personalized interventions for these individuals.

The recent introduction of the right to oncological oblivion in some European states raises critical issues. While designed to protect cancer survivors from discrimination, this right may compromise occupational health surveillance for workers exposed to carcinogenic hazards. This commentary raises questions for future policy and research.

Giant ovarian cysts are becoming less prevalent as a result of breakthroughs in imaging, routine gynecological surveillance, and early intervention in wealthy countries. However, in resource-constrained nations, delayed access to treatment, a lack of regular prenatal and gynecological follow-up, and socioeconomic constraints all contribute to late presentation and management difficulties.

We discuss the case of a 35-year-old Somali multiparous woman (G9P7) with a five-year history of increasing abdominal distension caused by a large mucinous cystadenoma. Abdominal ultrasound, contrast-enhanced CT scans, and tumor marker assessments all contributed to the diagnosis. She was assessed at our tertiary care center after a delay in seeking to a surgical care. A massive uniloculated cystic mass was found and entirely removed with unilateral salpingo-oophorectomy. A multidisciplinary team performed definitive surgical care, which was finished successfully without major complications, and the patient made a good postoperative recovery. Histopathological investigation confirmed the diagnosis of mucinous cystadenoma, with no signs of malignancy.

This case demonstrates the significance of earlier detection and interdisciplinary surgical care in achieving favorable outcomes for large ovarian tumors in resource-limited settings. The effective treatment of a long-standing huge mucinous cystadenoma in a young Somali woman demonstrates the importance of imaging, tumor markers, and coordinated surgical expertise in lowering morbidity and improving prognosis, Raising physician awareness and enhancing access to diagnostic and surgical procedures are critical to avoiding delayed presentations and related consequences.

Early detection of pancreatic cancer is crucial for survival, but detecting smalllesions remains challenging. Intraductal Ultrasound (IDUS) using intracardiac echocardiography (ICE) catheters for B-mode and Shear-Wave Elastography (SWE) potentially offers improved visualization and characterization of small tumors. This study assesses the feasibility of IDUS using ICE catheters to detect and visualize periampullary tumors in surgically resected specimens.

In this two-phase ex-vivo feasibility study, 25 pancreatic specimens were included, of which the first 10 were used to establish and standardize the imaging protocol, followed by technical feasibility evaluation in the remaining 15 specimens. Catheters were introduced into the pancreatic duct, common bile duct, or positioned extraductally to enable tumor visualization with B-mode imaging and shear-wave elastography (SWE). Tumor visualization rates, catheter insertion success, SWE measurements in normal and tumor tissue, and image quality were assessed.

ICE catheter insertion was successful in 12 of 15 specimens; unsuccessful access was primarily related to large tumor size (>4 cm) or unidentifiable ductal anatomy following surgical resection. However, extraluminal imaging successfully visualized tumors in one of these cases. Median shear-wave speed and elastic modulus for normal pancreatic parenchyma were 1.58 m/s and 7.6 kPa, respectively. SWE measurements in tumor tissue were suboptimal, likely due to ex-vivo tissue variability and catheter strain during repeated use.

IDUS with ICE is feasible for qualitative B-mode visualization of periampullary tumors and enables SWE assessment of pancreatic parenchyma in an ex-vivo setting. Reliable elastography of tumor tissue remained challenging, indicating the need for further technical refinement and in-vivo validation.

Transthoracic CT-guided biopsy performed with the coaxial technique is a minimally invasive procedure that facilitates the diagnosis of lung lesions (nodules or masses) and/or mediastinopulmonary lesions suspected of malignancy. This procedure is the source of several complications, the most frequent of which is pneumothorax.

To describe the epidemiological, diagnostic, and therapeutic aspects of iatrogenic pneumothorax after CT-guided biopsy performed using the coaxial technique.

Prospective longitudinal study, conducted over a period of 2 years and 10 months, from April 1, 2023, to February 1, 2026, at the Mohammed V Military Teaching Hospital in Rabat, including all patients who presented with a pneumothorax following a transthoracic CT-guided biopsy, according to the coaxial technique, confirmed clinically and/or radiologically.

The study included 30 cases of pneumothorax following CT-guided biopsy according to the coaxial technique. Biopsies were performed in 217 patients, and the incidence of pneumothorax was 13.8%. The median age was 68 years [58.8-71.5], with a predominance of males (90%). The most frequent characteristics observed among patients with pneumothorax were pulmonary emphysema (73.3%), lower-lobe lesions (33.3%), and central lesions with a median depth of 3.6 cm [2.9-4.2]. Procedure-related characteristics included practitioner status and biopsy needle diameter (18-gauge). Most patients were asymptomatic (60%). Diagnosis was established by chest CT during the procedure in 26.7% of cases and by chest X-ray after the procedure in 73.3% of cases. Small pneumothorax was the most common presentation (40%). Treatment was conservative in 53.3% of cases, and intervention was required in 46.7% (7 cases drained and 7 cases exsufflated). A complication was observed in 5 cases, after initial treatment. Only one patient underwent thoracoscopic pleurodesis after 14 days of chest drainage. The median length of hospital stay was 4 days [2-5.75].

Pneumothorax is a major complication of CT-guided transthoracic biopsy, whether performed coaxially or non-coaxially. In our descriptive series, pulmonary emphysema, lower-lobe location, and lesion depth were frequent characteristics among patients who developed pneumothorax. We believe that the radiologist's experience is a determining factor in preventing a very high incidence of pneumothorax cases.

Autosomal dominant acute porphyrias are rare inherited disorders of haem biosynthesis characterised by accumulation of potentially neurotoxic porphyrin precursors and attacks of severe abdominal pain with autonomic and neuropsychiatric features. Disease severity ranges from asymptomatic individuals to those with recurrent, life-threatening attacks. The International Porphyria Network invited 34 acute porphyria specialists from 17 countries to form an expert panel. The invited group included clinicians from diverse specialities (ie, internal medicine, haematology, endocrinology, gastroenterology, hepatology, neurology, and biochemistry), together with laboratory scientists and patient representatives. The panel met online (in 2023-25) to develop 15 evidence-based recommendations with the use of the Grading of Recommendations, Assessment, Development, and Evaluations framework addressing attack prevention, management of sporadic and recurrent attacks, long-term follow-up, surveillance for primary liver cancer, and family screening. The guidelines support safe, consistent clinical care and improved outcomes, recognising global variation in resources and access to high-cost drugs, and highlighting priorities for future research.