Citations

Abstract Objective To evaluate the short- and long-term clinical outcomes of transcatheter aortic valve replacement (TAVR) among participants with RA and aortic stenosis compared with those without RA, using real-world data from a large multicentre registry. Methods Using the TriNetX Research Network, participants with aortic stenosis undergoing TAVR with (RA+) vs without (RA−) RA were identified. Odds ratios (ORs) with 95% CIs estimated 30-day all-cause mortality, permanent pacemaker implantation, ischaemic stroke, acute kidney injury, myocardial infarction, cardiogenic shock, major vascular complications, and major or life-threatening bleeding were evaluated. Five-year outcomes included all-cause mortality, ischaemic stroke, myocardial infarction and all-cause hospitalization. Cox regression was used to estimate hazard ratios (HRs) with 95% CIs. Results A total of 1414 RA+ (4.3%) and 39 004 RA− participants were eligible. After matching, 1374 were included in each cohort. At 30 days, outcomes did not differ between RA+ and RA− groups; mortality was 2.0% vs 1.5% (OR 1.29; 95% CI 0.73–2.29), with no significant differences in other endpoints. Over 5 years, mortality was 23.8% vs 20.5% (OR 1.12; 95% CI 0.97–1.31), and stroke, myocardial infarction and hospitalization were similar; HRs were concordant with OR estimates. In sex-based analyses of RA patients, outcomes did not differ by sex. Conclusion In this large observational study, TAVR was not associated with excess short- or long-term risk in patients with RA. These findings support TAVR as a safe therapeutic option in RA patients with aortic stenosis.

Abstract Background Isocitrate dehydrogenase (IDH)-mutant gliomas are infiltrative tumors with limited treatment options at recurrence. Early studies suggest IDH inhibition has therapeutic activity. We evaluated clinical outcomes associated with IDH-1 inhibitor ivosidenib in recurrent IDH-1-mutant gliomas and molecular predictors of response. Methods We retrospectively analyzed adults treated with ivosidenib from January 2021 to August 2025 with predominantly recurrent, pretreated CNS WHO grade 2-4 astrocytoma IDH-mutant or grade 2-3 oligodendroglioma, IDH-mutant and 1p/19q codeleted. Prior anticancer treatments, toxicities, enhancement status at ivosidenib initiation, and genomic alterations were collected. The primary endpoint was progression-free survival (PFS); secondary analyses evaluated associations between PFS, genomic complexity, and CDKN2A/B homozygous deletion. Results Ninety-two adults, median age 43, were included: 61 astrocytomas and 31 oligodendrogliomas, mostly grade 2. Before ivosidenib, 69 had surgery, 64 chemotherapy, and 64 radiation. Median time from diagnosis to ivosidenib was 4.8 years, with median of two prior progressions. Median treatment duration was 5.8 months. Median PFS was 15.2, 4.6, and 2.1 months for astrocytoma grades 2-4, 14.0 and 6.9 months for oligodendroglioma grades 2-3. Increasing genomic complexity was associated with shorter PFS in univariate analysis. Patients without CDKN2A/B homozygous deletion had median PFS of 19.2 months. Two patients with homozygous deletion had median PFS of 0.6 months. Conclusions In this retrospective analysis of predominantly recurrent IDH-1-mutant glioma, ivosidenib was associated with longer PFS in lower-grade, non-enhancing tumors that received little or no prior anticancer treatment and less complex genomic profiles. These findings support a context-dependent benefit of IDH inhibition in recurrent disease.

Abstract Background Knowing the prevalence of patent foramen ovale (PFO) and the increasing number of people who inject drugs (PWID) with right-sided infective endocarditis (RSIE), we aimed to better characterize the syndrome of injection drug use, RSIE, and PFO with systemic embolic events. Method A systematic search across multiple databases was independently screened using predefined criteria (from inception until September 2025). Published cases of adult PWID diagnosed with RSIE and ischemic stroke or other systemic embolic event were included, provided they had PFO assessment. Individuals were excluded if they had cardiac implantable electronic device (CIED) infections or any other conditions associated with systemic or paradoxical embolism. Results The review identified 13 studies with 14 young patients, mostly without comorbidities, predominantly infected with Staphylococcus aureus. In most cases, echocardiography revealed large tricuspid valve vegetations. Neuroimaging confirmed multiple ischemic infarcts, while 5 patients showed emboli outside the central nervous system (4 of them as the only systemic embolism). At least 11 (79%) patients had echocardiographic evidence of right-to-left shunting. Management included cardiac surgery in 6 cases that involved valve replacement or repair, percutaneous PFO closure in 2 cases, and percutaneous mechanical aspiration in 1 case. Three patients (21%) died during hospitalization, and only 27.3% patients had outpatient follow-up. Conclusions RSIE with systemic embolism in PWID with PFO has rarely been reported, affects younger patients without sex predominance, and was usually due to S. aureus with large tricuspid vegetations. Right-to-left shunting was characteristic, and outcomes were poor despite combined medical, surgical, and interventional therapies.

Background/Objectives: Characterizing spinal cord multiple sclerosis (MS) lesions in MRI is critical for diagnosis, monitoring, and treatment evaluation. However, current automated approaches for lesion detection and segmentation are typically designed for specific MRI contrasts or acquisition sites, limiting their generalizability in real-world clinical settings where imaging protocols vary widely. This work proposes a robust multi-site, multi-contrast segmentation framework for spinal cord lesions. Methods: The segmentation model was trained and evaluated on a large-scale dataset comprising 4428 annotated images from 1849 persons with MS across 23 imaging centers, encompassing six MRI contrasts (T1w, T2w, T2*w, PSIR, STIR, and UNIT1) acquired at 1.5 tesla (T), 3 T, and 7 T. Results: Likert-type assessment performed by neuroradiologist ratings demonstrated superior generalization of the model compared to existing contrast-specific pipelines ( p < 0.01). Additional experiments evaluated robustness across spinal levels, acquisition resolutions, binarization thresholds, and quantitative evaluation on external labeled datasets. Conclusions: The proposed model can achieve accurate and reliable spinal cord MS lesion segmentation across heterogeneous MRI data, addressing a key barrier to clinical translation. The model is available in the Spinal Cord Toolbox v7.2 and higher. Code repository: https://github.com/ivadomed/seg-sc-ms-lesion-multicontrast

Abstract Background Accurate synthesis of computed tomography (CT) images from magnetic resonance imaging (MRI) is clinically valuable for cranial applications such as attenuation correction, radiotherapy planning, and image‐guided interventions. However, the heterogeneity of MRI data across magnetic field strengths and pulse sequences limits the generalizability of existing methods, posing a barrier to clinical translation. Purpose This study aims to reformulate cranial CT synthesis as a modular, structurally coupled problem using a deep learning approach, enhancing adaptability across heterogeneous MRI conditions, including different field strengths and sequence protocols. Methods We implemented a cascaded multitask pipeline that jointly models skull segmentation and Hounsfield Unit (HU) regression in anatomically targeted regions. A 3D patch‐based training paradigm shifts the modeling focus from global image translation to localized bone feature extraction. The backbone leverages a residual Mamba‐based state space model within a 3D U‐Net structure to improve spatial representation, while a Transformer U‐Net serves as a widely recognized reference baseline comparison. The model was trained and evaluated in terms of multi‐modal (T1‐weighted and T2‐FLAIR) and cross‐domain transferability from a public 1.5 Tesla brain dataset ( n = 37) to an independent 7 Tesla clinical brain dataset ( n = 44). Performance was assessed using Dice and Jaccard indices for segmentation accuracy and mean absolute error (MAE) for HU regression. Results Quantitative analysis showed that our multitask pipeline, incorporating both morphological and HU map prediction stages, significantly outperformed conventional direct MRI‐to‐CT mapping across all metrics on the public 1.5T dataset (p < 0.05). Consistent performance on an external 7T clinical dataset (p < 0.001) further demonstrated the method's robustness and adaptability across field strengths. Conclusion These findings support that task‐structured training for modality transformation markedly improves both accuracy and generalizability of cranial CT synthesis across heterogeneous MRI conditions. The observed consistency across field strengths validates the robustness of the proposed methodology.

With limited therapeutic progress despite aggressive multimodal treatment, glioblastoma (GBM) remains one of the deadliest primary brain tumors. Emerging evidence suggests that GSCs are key drivers of tumor initiation, intratumoral heterogeneity, therapeutic resistance, and recurrence. GSCs retain self-renewal capacity, multilineage differentiation potential, and remarkable plasticity, enabling them to adapt to diverse microenvironmental cues. These properties are upheld by dysregulated developmental and oncogenic signaling pathways, including Notch, Wnt/β-catenin, Hedgehog, PI3K/AKT/mTOR, and STAT3, as well as epigenetic and metabolic reprogramming. In addition, dedicated niches such as hypoxic and perivascular microenvironments critically support GSC maintenance and immune evasion. In this review, we summarize the current understanding of the molecular pathways governing GSC biology, examine their interactions with the tumor microenvironment, and discuss emerging therapeutic strategies targeting GSCs, including pathway inhibition, differentiation therapy, immunotherapy, and nanomedicine-based drug delivery. We highlight key challenges and future directions for translating GSC-targeted approaches into effective clinical interventions for GBM.

Background Although clinically framed as a public health concern, the meanings of suicide are fundamentally shaped by cultural narratives and visual representations. Aims To examine the evolution of sculptural representations of suicide from antiquity to the present, and to interpret these works through psychiatric and sociological lenses relevant to contemporary clinical and public health discourse. Method A structured search across PubMed, Scopus and Web of Science (up to August 2025) was integrated with museum archives and art-historical catalogues. Selected sculptural works were analysed as interpretive case studies using iconographic, semiotic and contextual approaches. Interpretation focused on affective and relational processes such as psychological pain (psychache), shame, entrapment and social disconnection prioritising cultural formulation over retrospective diagnostic attribution in historical cases. Results Sculptural representations frame suicide through shifting moral and social logics: from honour-bound self-death in antiquity and virtue-coded narratives in the early-modern period to interiority and estrangement in modernity. Contemporary public installations shift this focus towards visibility, urban space and prevention. These works externalise private suffering and structural conditions (e.g. isolation, stigma), actively shaping collective imaginaries of self-destruction. Conclusions Sculpture provides a unique medium for the translation of individual suffering and the collective meanings of suicide into public form. An interdisciplinary reading of these works supports culturally informed clinical reflection and contributes to ethically attentive public communication and prevention strategies.

Abstract Transcriptional condensates (TCs) are dynamic, membrane-less assemblies of proteins and nucleic acids that form at specific genomic loci to control gene expression. The primary drivers of TC formation and function are long stretches of polypeptide chains that lack well-defined tertiary structure, known as the intrinsically disordered regions (IDRs) of Transcription Factors (TFs). However, the role of well-structured domains such as the DNA-binding domain (DBD) in condensate formation and downstream regulation remains poorly understood. Here, we investigated whether the DBD of the Progesterone Receptor (PR), a model TF regulated by hormone binding, contributes to the formation of PR TCs. By combining Single Particle Tracking (SPT) with deep-learning-based single-trajectory analysis, we demonstrated that both the IDR and the DBD are required for the formation of PR condensates. Furthermore, transcriptomic analysis showed that mutations of either of the two domains result in the expression of a distinct set of genes, with functional assays corroborating these findings and linking domain-specific transcription to differential effects on cell proliferation and migration. Together, our results show that domains beyond IDRs also play a role in TC formation and function and uncover domain-specific regulation of transcriptional and oncogenic programs.

A new systems approach to diseased states and wellness result in a new branch in the healthcare services, namely, Personalized and Precision Medicine (PPM). To achieve the implementation of PPM concept, it is necessary to create a fundamentally new strategy based upon the recogni-tion of biomarkers and thus the targets to secure the grand future of drug design and drug dis-covery.Each decision-maker values the impact of their decision to use PPM on their own budget and well-being, which may not necessarily be optimal for society as a whole. It would be extremely useful to integrate data harvesting from different databanks for applications to provide more tai-lored measures for the patients resulting in improved patient outcomes, reduced adverse events, and more cost-effective use of the latest health care resources including diagnostic (companion ones or theranostics), preventive and therapeutic (targeted molecular and cellular) etc.Meanwhile, along with the impact of genomics and bioinformatics, pathology is the central specialty of PPM-related resources. Coupled with IT, the upgraded tools are ever more efficient and robust within clinical cancer settings. The latest algorithms may be able to identify and vali-date patterns which humans are not capable of quantifying easily, such as slight differences in textures or morphologies. In this sense, the impact of pathology allows a modular approach, as its various aspects are under development in several areas of PPM.Among the above-mentioned medical specialists involved in PPM, the pathologists play an im-portant and key role in the implementation and development of PPM-driven resources that are in the center of decision of many therapeutic choices. Recent advances in systems biology have tremendously affected the practice of precision pathology, gradually transforming it from a morphology-based into a precise molecular-based discipline. The enormous development of precision pathology research (integrating molecular OMICS and digital approaches) has raised great expectations concerning its impact on PPM aiming to custom-ize medical practice with a focus on the individual, based on the use of molecular tests, identifi-cation of genomic biomarkers, and development of targeted drugs.The precision pathology process introduces a new paradigm in pathology by leveraging digital imaging and IT technologies, and provides significant advancements in accuracy, efficiency, and collaboration. Among the latest innovations the precision pathology supported by digital tools, would dictate the implementation of high-resolution imaging, image analysis tools and integra-tion with molecular OMICS data. Integration of the approaches and resources will provide a true challenge for the future, requiring collaboration between oncologists, pathologists, biodesigners and bioengineers and remaining a challenge to precision cancer practice and profiled bioindustry.The latter requires precision pathologists highly trained in pre-analytic processes, tumor area mi-crodissection for tumor cell enrichment, methodology analysis and results. The in-depth study of molecular alterations in patients allows optimizing molecular diagnosis and selecting candidates for receive novel treatments against specific molecular targets. These patients would benefit from multidisciplinary approach and learning. In this sense, molecular diagnostics has a long tradition in pathology, especially in clinical one, where various OMICS-analyses of cancers are incorpo-rated into diagnostic and decision-making algorithms to secure a way where the pathologists con-tinue to play an essential role in developing and implementing molecular profiling tests in practice and communicate the results and their relevance with cancer practitioners.Cancer pathology is the central specialty of personalized and precision oncology (PPO). Meanwhile, the combination of comprehensive biobanking and the next wave of theranostic pathology technologies provides a natural, externally visible infrastructure that now allows pa-thology as a discipline – to engage directly with the biotechnology and pharma sector. We’re at an exciting junction in precision cancer pathology’s growth as a medical specialty, and pathology-driven biobanking is becoming both central to our core expertise and, even more importantly, a powerful enabler for many of the most promising growth areas of our discipline: PPM healthcare, clinical trials and drug development, theranostics, and functional assessment and monitoring of disease. In the context of these changes and challenges, the precision cancer pathology can play a fundamental role in both PPO-guided clinical practice and biodesign-driven cancer research.

ABSTRACT Background Clinical T 2 ‐weighted (T2W) MRI of prostate cancer (PCa) usually implements a 2D fast‐spin‐echo (FSE) sequence, but understanding the echo‐time‐dependent contrast behavior is not straightforward due to the complicated FSE signal evolution. Consequently, consensus‐based recommendations on the optimal effective echo time (TE eff ) to maximize contrast are lacking. Purpose To investigate the effect of TE eff on PCa lesion contrast in prostate T2W MRI. Study Type Phantom and in vivo prospective study. Subjects A standard MRI phantom and 53 prostate cancer patients (29 for image evaluation and 24 for quantitative lesion analysis). Field Strength and Sequence Multi‐slice T2W FSE sequence at 3 T acquired at multiple TE eff values. Assessment Three readers (13, 25, and 27 years' experience) evaluated TE eff = 100 ms versus 150 ms on diagnostic quality and reader preference. The effective T 2 relaxation rates ( T 2,eff ) were measured using FSE sequences in the phantom and used to predict the optimal TE eff maximizing T2W contrasts. From multi‐TE eff scans of subjects with suspected PCa, T 2,eff values of PCa lesions and healthy tissue were measured and used to calculate the optimal TE eff maximizing the lesion contrast. In vivo contrast metrics were measured as a function of TE eff . Statistical Tests Wilcoxon test of reader scores, with p < 0.05 defining statistical significance. Results No statistically significant difference was found in diagnostic quality between TE eff = 150 ms and 100 ms images, but all three readers significantly favored TE eff = 150 ms. Phantom experiments demonstrated that TE eff ‐dependent FSE signal progression can be characterized by T 2,eff values typically 40% longer than actual T 2 values, allowing accurate prediction of optimal TE eff within 2%–5%. Applied to PCa imaging, in vivo measurements indicated that effective T 2 relaxation times of the prostate are on average 1.5× longer than published T 2 values. Data Conclusion The benefits of TE eff = 150 ms versus 100 ms in prostate T2W FSE were supported by reader preference, phantom experiments, in vivo measurements, and analytic optimizations. Evidence Level 2. Technical Efficacy 2.