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Pregnancy in women with cardiovascular disease (CVD) represents a distinct clinical condition, as the physiological adaptations of pregnancy may interact with underlying cardiac pathology in variable and sometimes unpredictable ways. Consequently, maternal and foetal risk cannot be assumed a priori and requires structured, patient- and disease-specific assessment. The new ESC guidelines on cardiovascular disease and pregnancy incorporate updated evidence following the 2018 version. The contents span from models of multidisciplinary care (the Pregnancy Heart Team, PHT), pre-pregnancy counselling, and pregnancy-related risk assessment, to novel recommendations that are both shared by all pregnancies in women with CVD and specific to each distinct disease. Due to limited prospective or randomized studies largely prevented by ethical reasons, most recommendations are based on evidence level C. This document provides a concise synthesis of innovations in shared management strategies and disease-specific pathways in pregnancy of women with known CVD. It also acknowledges that not all clinical scenarios can be fully captured by guideline-based recommendations. Beyond guidelines, and primarily because approximately 50% of recommendations are Level C evidence, there is considerable decision-making margin for cardiovascular specialists to adhere recommendations. For rare unpredictable complications/events the limited available evidence does not allow recommendations to be made. Looking to the future, the expectation is that AI, which is already generating data and models of care in pregnancy, can help support widespread access to PHT, both in hospitals equipped with the necessary requirements and remotely to all healthcare facilities serving pregnant women with CVDs.

Spinal muscular atrophy (SMA) is a severe neuromuscular disorder caused by reduced expression of the survival motor neuron (SMN) protein. In addition to affecting motor neuron survival, SMN deficiency impacts multisystem physiology and neurotransmission. Dopaminergic dysfunction has been reported in mouse models of SMA, leading to postural and locomotor impairments that improve upon treatment with L-DOPA and benserazide. However, whether altered dopamine metabolism contributes to clinical symptoms in SMA patients remains unclear. To investigate this issue, we conducted a real-world study involving patients with SMA1, SMA2, and SMA3. We measured the main dopamine-related catabolites - 3,4-dihydroxyphenylacetic acid (DOPAC) and homovanillic acid (HVA) - in cerebrospinal fluid (CSF) samples collected at baseline and after five intrathecal doses of Nusinersen, an SMN-enhancing therapy. No significant differences were observed in CSF DOPAC and HVA levels across SMA types or following treatment, and no association emerged with SMN2 copy number. In contrast, lower baseline DOPAC levels were detected in SMA1 patients requiring gastrostomy and tracheostomy, and were associated with reduced improvement on the CHOP-INTEND scale. These findings suggest that reduced central dopaminergic turnover reflects disease progression in SMA1 and is associated with more severe clinical impairment and limited functional recovery.

Advocacy is widely recognized as a catalyst for equity in health, yet its conceptual foundations, operational forms, and evaluative criteria remain fragmented. In health systems, advocacy is expected to amplify marginalized voices, address structural determinants, and promote participatory governance, but there is limited consensus on its definition and implementation. This scoping review systematically maps how advocacy has been conceptualized, practiced, and evaluated across public health and healthcare domains in democratic societies, with particular attention to its role in advancing equity. We conducted a scoping review across four databases (PubMed, Scopus, Web of Science, CINAHL) including peerreviewed literature from health, legal, political, and social domains. Eligible studies explicitly addressed advocacy in health and care contexts, providing conceptual definitions, theoretical frameworks, or descriptions of practice, education, and evaluation. Thematic synthesis was applied to identify recurrent dimensions, strategies, and values. A total of 146 documents were included. Advocacy was consistently framed as a deliberate, value-driven practice oriented toward systemic change, social justice, and equity, despite considerable conceptual and operational variability. Applications spanned clinical care, public health promotion, community mobilization, and policy reform. Relational and communicative skills were widely emphasized as enabling factors, but evaluation remained limited: only 6 studies (4%) reported the use of specific measurement instruments, none of which were standardized. From this synthesis, we developed a preliminary blueprint for equity-oriented public health advocacy, structured around six components: normative grounding; multilevel orientation; relational and communicative practices; critical and systemic literacy; reflexive professionalism and civic agency; and evaluation and accountability mechanisms. Advocacy emerges as both a professional competency and a civic practice essential for equity-driven health systems. This review provides a conceptual foundation and a translational framework to guide integration of advocacy into policy, training, and practice. Sustained collaboration between academia, civil society, and health systems is required to institutionalise advocacy as a driver of just and inclusive health governance. OSF: https://doi.org/10.17605/OSF.IO/MEJHX

BackgroundData-driven approaches identified Mild Motor Predominant (MMP), Intermediate (IM), and Diffuse Malignant (DM) as Parkinson's Disease (PD) subtypes with different motor and non-motor impairment at diagnosis. It remains unclear whether these subtypes remain stable over time or whether they represent distinct biological substrates. The alpha-synuclein seed amplification assay in CSF (CSF-αSyn-SAA) might provide further insights.Objectiveto evaluate the association between baseline CSF-αSyn-SAA parameters and 10-year clinical evolution of PD subtypes.Methods323 sporadic PD patients from PPMI dataset were classified as MMP, IM, or DM at baseline and 10-year follow-up based on motor, cognitive, sleep and dysautonomia features. CSF-αSyn-SAA parameters were collected at baseline using 150-h protocol. CSF Aβ1-42, tTau and pTau181, CSF and serum NfL were also considered at baseline.ResultsReaction times (T50, TTT) and area under the curve (AUC) respectively were shorter and larger in DM compared to IM/MMP. The difference in baseline amplification parameters was more evident when comparing subtypes based on 10-year clinical features (T50, η2 = 0.036; TTT, η2 = 0.031; AUC, η2 = 0.033; all p-values < 0.05) than when comparing subtypes based on baseline clinical features (T50, η2 = 0.012; TTT, η2 = 0.012; AUC, η2 = 0.013; all p < 0.05). Shorter T50 and TTT at baseline, or larger AUC, were associated with greater risk of DM versus MMP at 10-year follow-up (T50, OR = 4.1, p = 0.004; TTT, OR = 5.5, p < 0.001; AUC, OR = 3.5, p = 0.010). Aβ, Tau and NfL were similar between groups.ConclusionsBaseline CSF-αSyn-SAA parameters predicted long-term PD progression. Faster reactions were associated with a more severe 10-year PD phenotype considering motor and non-motor features.

The measurement of fluid biomarkers such as phosphorylated tau at threonine 181 (pTAU181), amyloid-β 40 (Aβ40), and Aβ42 is a routine medical examination that contributes to achieving an accurate diagnosis within the Alzheimer's disease (AD) clinical continuum. The aim of this study is to compare the concentration of these biomarkers in CSF and plasma and determine their relationship with the patients' clinical variant and profile. Patients were diagnosed following the NIA-AA criteria. Plasma and CSF were obtained from healthy controls (HC), mild cognitive impairment (MCI non-AD), MCI displaying positive AD markers (MCI-AD), and AD patients. Biomarker levels were assessed using the LUMIPULSE® G600II instrument (Fujirebio, Japan). Data showed a significant increase in pTAU181 concentration, specifically in the progression from MCI non-AD to AD conditions. The opposite trend was observed for Aβ42 and Aβ42/Aβ40. Furthermore, these biomarker trends appeared to change consistently with variations in the MMSE score, highlighting the relevance of plasma in detecting changes in patients' cognitive function. Considering the clinical variant, atypical patients displayed the highest pTAU181 and lowest Aβ42 levels, consistent with their lower MMSE scores. Lastly, the posterior cortical atrophy (PCA) profile showed higher pTAU181 and lower Aβ42 levels when compared to other profiles. Nevertheless, these last results are to be cautiously interpreted given the limited number of samples included in the analysis. Hence, further analyses on larger cohorts are needed to better define the role of these biomarkers in distinguishing between patients' clinical variants.

Multiplex immunofluorescence and immunohistochemistry (mIF/IHC) are increasingly employed antibody-based technologies that use tissue sparingly and facilitate the detection of co-localized or neighboring biomarkers. Specifically, these platforms enable spatial analyses of the tumor microenvironment as well as extended applications, for example, describing normal tissue anatomy, autoimmunity, infectious diseases, etc. mIF/IHC has greatly enhanced biomarker discovery efforts, and a growing number of studies suggest superiority to traditional IHC. Standardization of staining approaches, reporting of image analysis strategies and resultant data is critical for facilitating cross-study comparisons, validation, deployment, and generalization of findings. To address this challenge, The Society for Immunotherapy of Cancer (SITC) previously published two articles providing best practice guidelines for mIF/IHC staining, image analysis, and data sharing. Here, SITC convened stakeholders to develop the third article in the series, a consensus checklist for scientific reporting of mIF/IHC data to support and complement the best practice guidelines. The checklist includes critical components of mIF/IHC applications to be defined within publications such as detailed descriptions of analytical validation; image acquisition, selection, and registration methods; and cell clustering and spatial analysis strategies, amongst others. Such information will help with data reproducibility and comparison across studies towards future drug and assay development.

BackgroundThe digit span task, a measure of auditory verbal short‐term and working memory, is widely used globally. Emerging research has revealed variations in digit span performance across languages among young adults; however, studies focusing on older populations are scarce and typically involving limited languages. This study investigates digit span performance among older adults (40‐90 year‐old) across fourteen languages and explored the influence of lexical and numerical properties on cognitive assessment.MethodWe examined digit span performance among cognitively normal participants (CN), individuals with mild cognitive impairment (MCI) and Alzheimer's disease (AD) across fourteen language cohorts totalling 3,681 participants: English (n = 446), Mandarin (n = 97), Cantonese (n = 65), Spanish (n = 218), Kannada (n = 69), Hindi (n = 72), Telugu (n = 69), Malayalam (n = 70), Bengali (n = 70), French (n = 299), Korean (n = 1098), Italian (n = 540), Arabic (n = 50), and Turkish (n = 518). First, we analyzed language differences in digit span performance among CN using ANOVA and general linear models. We then conducted Receiver operating characteristic (ROC) analyses to identify the optimal cutoff values for AD. Next, we computed the digit count, syllable count, and numerical magnitude (i.e. the average sum of the digits) of all digit stimuli in the English cohort and analyzed their effects via linear and ridge regression analyses.ResultThe forward (FDS) and backward digit span (BDS) tests revealed significant differences among CN across the fourteen language cohorts even after adjusting for age and education (FDS:F=38.62, p <0.001; BDS:F=19.23, p <0.001). ROC analysis revealed varying optimal cutoff values across languages: English (FDS:6, BDS:4), Italian and Turkish (FDS:5, BDS:4), Mandarin (FDS:7, BDS:5), Cantonese (FDS:7, BDS:4), and French (FDS:6, BDS:3). Further analysis indicated that the interaction between digit and syllable counts significantly impacted FDS accuracy in English speakers (linear:p=0.00035; ridge:p< 0.000001), with no significant effect from digit count alone after adjusting for interaction. Conversely, BDS performance showed a significant negative influence from digit count (p = 0.00858), with numerical magnitude and syllable count nearing significance (p = 0.083 and p = 0.066, respectively).ConclusionVariations in digit span performance across languages illustrate the role of linguistic and numerical factors in cognitive assessments, even with tests targeting non‐language domains using digit stimuli. These findings underscore the critical value of language diversity in cognitive research.