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Integrating climate considerations into EU stock exchange listing regimes: reform pathways and the potential role of the Capital Markets Union
No full textThis paper explores the extent to which current EU and Member State stock exchange listing regimes can adequately address the financial risks associated with climate change, particularly in relation to the admission of climate-exposed companies, such as fossil fuel enterprises, to public capital markets. While investor protection remains a core objective of EU capital markets regulation, existing listing and prospectus requirements often fail to ensure meaningful disclosure of climate-related risks or condition market access on adopting Paris- aligned transition strategies. Through comparative analysis of the Italian and German frameworks, the study reveals the fragmented and discretionary nature of national competent authorities’ powers, which limits their effectiveness in addressing climate-related financial risks. The paper further examines ESMA’s evolving mandate concerning ESG risks and considers its potential role within a reformed, centralised listing authority. It argues for EU-level legislative reform to establish binding, harmonised listing standards, including mandatory sustainability disclosures and credible transition planning requirements at the time of listing. Against the backdrop of the Capital Markets Union, the creation of a single EU listing authority, ideally situated within ESMA, is proposed as a key institutional reform to ensure regulatory consistency, enhance investor protection, and support the EU’s broader climate commitments
Zorevunersen in children and adolescents with Dravet syndrome
Get PDFBackground:
Dravet syndrome is a severe developmental and epileptic encephalopathy caused primarily by SCN1A haploinsufficiency. Risks of sudden unexpected death in epilepsy and cognitive deficits are higher among patients with this syndrome than in the general population with epilepsy. The effects of zorevunersen, an antisense oligonucleotide designed to up-regulate NaV1.1 sodium channels, in patients with Dravet syndrome are not known.
Methods:
We enrolled patients 2 to 18 years of age with Dravet syndrome who were receiving standard antiseizure medications in two phase 1–2a, open-label, multicenter studies (MONARCH and ADMIRAL). Patients were included in either a single-ascending-dose cohort, in which zorevunersen (10 to 70 mg) was administered on day 1 only, or a multiple-ascending-dose cohort, in which zorevunersen (20 to 70 mg) was administered two or three times in a 3-month period. Patients eligible for rollover to the two open-label extension studies (SWALLOWTAIL and LONGWING) continued to receive zorevunersen (≤45 mg) every 4 months. The safety and pharmacokinetics of zorevunersen were assessed in the primary analysis; clinical effects were also evaluated.
Results:
A total of 81 patients were enrolled in the phase 1–2a studies. As of May 30, 2025, a total of 75 patients had entered the extension studies. Most adverse events were mild or moderate. The most common adverse event was post–lumbar puncture syndrome (in 25% of patients) in the phase 1–2a studies and was an elevated protein level in cerebrospinal fluid (in 45%) in the extension studies. One patient had suspected unexpected serious adverse reactions, 1 had an adverse event that led to study withdrawal, 2 died from sudden unexpected death in epilepsy, and 1 died from malnutrition. Patients who received 70 mg of zorevunersen (one, two, or three doses) in the phase 1–2a studies, followed by up to 45 mg in the extension studies, had a median change from baseline in convulsive-seizure frequency ranging from −58.82% to −90.91% across 1-month intervals during the first 20 months of the extension studies. The data supported improvements in overall clinical status, quality of life, and adaptive behavior with continued treatment for up to 36 months in the extension studies.
Conclusions:
The safety profile and initial clinical improvement support the continued development of zorevunersen as a potential disease-modifying treatment for Dravet syndrome. (Supported by Stoke Therapeutics; MONARCH and SWALLOWTAIL ClinicalTrials.gov numbers, NCT04442295 and NCT04740476, respectively; ADMIRAL and LONGWING ISRCTN Registry numbers, ISRCTN99651026 and ISRCTN12811235, respectively.
Still at sea: a patient's ongoing journey with non-obstructive hypertrophic cardiomyopathy
Get PDFNo abstract available
Conditional gains: when AI investment enhances firm efficiency
No full textThe rapid adoption of artificial intelligence (AI) has raised questions about its effect on firm performance. Using a labor- based measure of AI investment, the baseline results show no direct association between AI investment and firm efficiency. The heterogeneity analysis indicates that efficiency gains materialize primarily when firms pair AI with capable managers, face stronger competitive pressure, have more stable institutional investor ownership, and are able to secure long- term debt
HMamba-3DFT: A hierarchical Mamba framework for emotion-driven semantic 3D facial tracking
Get PDFMonocular video-based 3D face tracking is vital for interactive pattern recognition and human avatars. Most existing image-based methods fail to model temporal dependencies in video, causing jitter and inaccuracies. Furthermore, they also often neglect the continuous multi-modal signals present in facial videos such as expression dynamics and emotional cues that provide essential temporal drivers for facial modeling. To this end, this study first explores the Mamba architecture tailored for 3D facial tracking by proposing a hierarchical Mamba framework, termed HMamba-3DFT. The proposed network can efficiently capture and track variations in 3D facial shapes from a monocular video. To exploit the global spatiotemporal correlations across frames of the dynamic face, we develop a bidirectional spatiotemporal vision Mamba (BSTV-Mamba) module featuring a bidirectional spatiotemporal selective scan (BSTS-Scan) mechanism. To capture temporally evolving multi-modal emotion signals embedded in continuous video sequences, we introduce a dynamic emotion-driven mechanism. Additionally, to mitigate the potential degradation of reconstruction fidelity caused by an over-reliance on emotion-driven cues, we integrate facial semantic alignment with facial emotion driving to enhance the accuracy of emotion-driven facial modeling. This integrated dual-optimization strategy systematically guides the network during training, ensuring that the reconstructed 3D facial mesh not only accurately captures the emotional attributes of the input frames but also benefits from enhanced optimization for more precise reconstruction. Extensive evaluations on benchmark datasets show competitive performance against state-of-the-art methods
A canine PLP1 missense variant differentiates oligodendrocyte maturation in connatal and classical pelizaeus merzbacher disease
Get PDFPelizaeus-Merzbacher disease (PMD) is an X-linked hypomyelinating disorder caused by pathogenic variants in the proteolipid protein (PLP1) gene. We report a spontaneous canine dysmyelinating leukodystrophy in English Cocker Spaniel puppies. The most severely affected male pup displayed pronounced generalized tremors, progressive motor dysfunction, and markedly impaired growth. Histopathology at 5 weeks of age revealed profound central nervous system (CNS) dysmyelination with no evidence of peripheral nerve involvement. Western blotting confirmed markedly reduced expression of CNS myelin-associated proteins. Ultrastructural analysis demonstrated a near absence of compact myelin, rare myelinated axons, and significant oligodendrocyte abnormalities, the majority of which had an immature cellular morphology. More mature, yet infrequent oligodendrocytes had distended rough endoplasmic reticula. Nucleotide sequence analysis identified a hemizygous c.92T>A missense variant in the PLP1 gene predicted to cause a leucine-to-glutamine substitution in the first transmembrane domain, p.(L31Q). This variant was absent in over 1600 public canine genomes and was predicted to be deleterious by multiple bioinformatic tools. Heterozygous females exhibited variable, transient clinical signs. We compared this novel canine leukodystrophy with the previously reported shaking pup and found that it represents a more severe phenotype recapitulating key clinical, pathological, and molecular features of severe connatal PMD in humans, including extreme CNS dysmyelination and associated neurological deficits. Interestingly, this genetic variant seems to cause a defect at the oligodendrocyte progenitor stage limiting subsequent oligodendrocyte maturation and preventing myelination. The identification of this naturally occurring model provides a potential resource for investigating the mechanisms and therapeutic targets for specific PLP1 genetic variants
Laboratory An. gambiae s.l. mosquito colonies show sustained high transmission of Microsporidia sp. MB and a small fecundity cost
Get PDFMicrosporidia sp. MB, a microsporidian symbiont found naturally in Anopheles mosquitoes, has potential as a novel malaria control tool since it can inhibit Plasmodium development and
transmission. The most feasible MB-based Plasmodium control strategy would involve dissemination
through live mosquito releases, or release of spores infective to mosquito larvae. To implement either
strategy, establishment of stable mosquito colonies carrying MB at a high frequency is likely to be
essential. The progeny of field caught An. gambiae s.l from Burkina Faso were isolated for individual
egg laying and tested for MB. The progeny of the MB positive females were pooled and this process
was repeated for multiple generations. The relative density of MB in different life stages and tissues
of the An. coluzzii host was examined using a novel duplex qPCR assay. We also examined the
impact of MB on fecundity through individualization for egg laying and counting of eggs. Finally,
we examined laid eggs for presence of MB spores. Three An. coluzzii colonies and one An. gambiae
s.l hybrid colony were established with high prevalence and density of MB and were maintained for
more than two years with minimal intervention. MB prevalence and density was highest in eggs and
adult females and lowest in L4 larvae; in adults density was highest in the gonads. Additionally, MB density increased in ovary samples following blood feeding which was likely due to the activation of
sporogony. The production of spores is the reason why MB-carrying females lay more white non hatching eggs and show a small reduction in fecundity. Establishment of several stable MB carrying An. gambiae s.l colonies and understanding the impact of spores on fecundity are significant steps forward in developing MB as a malaria control tool
The role of artificial intelligence in advancing population-based cancer registration
No full textCancer has become the second leading cause of death, the global cancer burden is rapidly increasing, and there are marked disparities between and within countries worldwide. Population-based cancer registries systematically collect data on cancer patients in defined populations, which play a crucial role in planning and assessing cancer prevention and control strategies. While the development of cancer registration has been marked by increasing standardization of definitions and methods and the electronic processing of data, the advent of artificial intelligence (AI) offers opportunities to further reduce the labor-intensive nature of registry operations, particularly where registry resources are scarce. These include enabling the processing of large datasets, extracting complex or unstructured data patterns to support cancer registration data abstraction, and facilitating data quality and control. The analysis and dissemination of registry data are also increasingly integrating AI methodologies. This paper provides a comprehensive overview of the application of AI in cancer registration. We investigate the challenges associated with integrating AI into existing cancer registry structures, with a particular emphasis on network and computational constraints, uneven resource allocation, and potential b iases and limitations within AI systems. We propose a forward-looking AI-enhanced framework for cancer registration, highlighting AI’s potential to optimize efficiency in cancer registration and the use of registry data for cancer control and cancer research
Markers of Fibromyalgia: Classification and Subtyping Using Self-Reported Measures
No full textFibromyalgia (FM) is a chronic pain disorder marked by widespread physical symptoms and psychological comorbidities. While neuroimaging has dominated FM research, such methods are often impractical or inaccessible in routine clinical care. This study investigates whether self-reported features can effectively distinguish FM patients from healthy controls (HC) and identify clinically meaningful FM subtypes, using the Emo-Fibro dataset (N = 66; 33 FM, 33 HC). We trained and evaluated supervised machine learning models including Logistic Regression, Random Forest and Support Vector Machine on the Toronto Alexithymia Scale (TAS-20) and the Positive and Negative Affect Schedule (PANAS), assessing feature importance using absolute coefficients, Gini importance, and permutation importance. The Random Forest model achieved the highest classification performance (Accuracy = 0.81, ROC-AUC = 0.82), indicating that these features alone can offer robust diagnostic insight. We then applied K-Means clustering to the FM group and identified two subtypes: high-distress versus lower-distress, characterized by emotional regulation, psychological burden, and affect. These findings suggest that patient-reported psychological data not only aid FM diagnosis but also reveal meaningful heterogeneity to guide personalized care. By focusing on accessible, self-reported measures, this study supports a practical and emotion-informed approach to FM research and management
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