BACKGROUND: The COVID-19 pandemic has significantly impacted global healthcare systems, leading to challenges in managing Long COVID. Variations in definitions and diagnostic criteria across Europe hinder recognition and treatment efforts. This study aims to analyse and compare the definitions of Long COVID used in 34 European countries. METHODS: A retrospective descriptive study was conducted involving key informants from 34 European countries, utilising an online questionnaire to gather data on Long COVID definitions. Quantitative and qualitative analyses were employed to assess the variability of definitions and challenges in managing Long COVID. RESULTS: The study found significant variation in Long COVID definitions among the participating countries; the most frequent definition was the other definition (n: 17, 50.0%), followed by the World Health Organisation's definition (n: 16, 47.0%) and the CDC definition (n: 11, 32.3%). Half of the countries reported using multiple definitions simultaneously, indicating a lack of standardisation. Qualitative analyses highlighted challenges such as difficulties in standardising terminology, variability in clinical criteria, and issues with implementing diagnostic codes. CONCLUSION: The findings underscore the need for a unified, yet adaptable, definition of Long COVID. Such a definition would support general practitioners (GPs) by simplifying diagnostic processes, improving continuity of care, and facilitating equitable patient access to multidisciplinary resources. The current lack of consensus complicates patient care, data collection, and resource allocation, impacting health policy development. Future efforts should focus on achieving agreement on definitions to ensure equitable treatment and effective healthcare responses to Long COVID.

• Keywords
• COVID-19, Europe, Primary health care, clinical coding, diagnosis, post-acute COVID-19 syndrome,
• MeSH
• COVID-19 * therapy   diagnosis   epidemiology   MeSH
• Consensus MeSH
• Humans MeSH
• Surveys and Questionnaires MeSH
• Retrospective Studies MeSH
• SARS-CoV-2 MeSH
• Terminology as Topic * MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Geographicals
• Europe epidemiology   MeSH

To avoid potentially noxious prey, predators need to discriminate between palatable and unpalatable prey species. Unpalatable prey often exhibits visual warning signals, which can consist of multiple components, such as color and pattern. Although the role of particular components of visual warning signals in predator discrimination learning has been intensively studied, the importance of different components for predator memory is considerably less understood. In this study, we tested adult wild-caught great tits (Parus major) to find out, which components of prey visual warning signals are important when the birds learn to discriminate between palatable and unpalatable prey, and when they remember their experience over a longer time period. Birds were trained to discriminate between palatable and unpalatable artificial prey items that differed in both color and pattern. After 4 wk, the birds were retested in 3 groups: the first group was presented with the same prey as in the training, the second group was tested with the two prey types differing only in color, and the third group could use only the pattern as a discrimination trait. The results suggest that the birds remember their experience with unpalatable prey even after the period of 4 wk. Although the color appears to be more important than the pattern, the combination of both signal components is more effective for prey recognition after several weeks than either the color or pattern alone.

• Keywords
• avian predators, color, discrimination learning, long-term memory, multicomponent signals, pattern, warning coloration,
• Publication type
• Journal Article MeSH

Chirality is a fundamental feature involved in most biological processes. While it can be rather readily observed on the molecular or microscopic level, enantioselective interactions on the macroscopic level are not as well understood. We chemically synthesized l-cellulose, the enantiomer of native cellulose with chains of different length by polymerizing an l-glucose-based precursor. A sufficiently high degree of polymerization was crucial for the successful application of this material as a chiral selector. After derivatization, coating onto silica, and packing into columns, the functionalized material was tested in a chiral high-performance liquid chromatography setup to investigate the enantioselective interplay between the modified cellulose mirror images and chiral molecules. We report the first-ever application of synthetic l-cellulose instead of the common column materials based on the natural d-polysaccharide counterparts. An inversion of the analyte elution order of (R) and (S) enantiomers due to reversed interaction strength with the stationary phase was observed for all tested analytes.

• Keywords
• Cellulose, Chiral recognition, Chiral stationary phase, Chirality, Enantiomer separation, HPLC, Polysaccharide-based chiral selectors, l-Cellulose,
• Publication type
• Journal Article MeSH

To identify clinical features that predict the risk of meeting difficult-to-treat (D2T) rheumatoid arthritis (RA) definition in advance. This retrospective analysis included RA patients from the ATTRA registry who initiated biologic (b-) or targeted synthetic (ts-) disease-modifying anti-rheumatic drugs (DMARDs) between 2002 and 2023. Patients with D2T RA met the EULAR criteria, while controls achieved sustained remission, defined as a Simple Disease Activity Index (SDAI) < 3.3 and a Swollen Joint Count (SJC) ≤ 1, maintained across two consecutive visits 12 weeks apart. Patients were assessed at baseline and at one and two years before fulfilling the D2T RA definition. Predictive models were developed using machine learning techniques (lasso and ridge logistic regression, support vector machines, random forests, and XGBoost). Shapley additive explanation (SHAP) values were used to assess the contribution of individual variables to model predictions. Among 8,543 RA patients, 641 met the criteria for D2T RA, while 1,825 achieved remission. The machine learning models demonstrated an accuracy range of 0.606-0.747, with an area under the receiver operating characteristic curve (AUC) of 0.656-0.832 for predicting D2T RA. SHAP analysis highlighted key predictive variables, including disease activity measures (DAS28-ESR, CDAI, CRP), patient-reported outcomes (HAQ), and the duration of b/tsDMARD treatment. We identified clinical features predictive of D2T RA at baseline and up to one year before meeting the formal criteria. These findings provide valuable insights into early indicators of D2T RA progression and support the importance of earlier recognition and timely therapeutic intervention to improve long-term patient outcomes.

• Keywords
• Difficult-to-treat rheumatoid arthritis, Explainable artificial intelligence, Machine learning, Real-world data,
• MeSH
• Antirheumatic Agents * therapeutic use   MeSH
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Registries MeSH
• Retrospective Studies MeSH
• Arthritis, Rheumatoid * drug therapy   diagnosis   MeSH
• Aged MeSH
• Machine Learning * MeSH
• Severity of Illness Index MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• Antirheumatic Agents * MeSH

INTRODUCTION: The purported predominance of the biopsychosocial model is reviewed, including its underlying factors that determine the etiology and treatment of sexual disorders. We recommend that sexual health professionals embrace a broader recognition of all facets of the model. Periodic re-examination is necessary to optimize its strengths and minimize misapplication. OBJECTIVES: Improving the application of the full scope of the biopsychosocial model will help ensure that it remains robust and inclusive. Awareness of its limitations should prompt clinicians to expand their knowledge through continuing education. METHODS: Co-authors reviewed database searches, including PubMed, Google Scholar, and ClinicalTrials.gov. Publications, sexual society presentations, and guidelines were also considered, along with expert opinions. Authored by an intentionally recruited, diverse group of experts representing different disciplines, geographic regions, genders, and perspectives, our manuscript deserves substantial consideration. However, this work does not employ the rigorous methodology used by professional societies in producing guidelines. RESULTS: The biopsychosocial model is widely used; however, too many sex therapists and sexual medicine experts claim to adopt the model while merely paying it lip service. Clinicians support multidisciplinary approaches, yet siloed thinking persists. Collegial respect is increasing, but perspectives remain divided. While sex therapists recognize psychosocial nuances, many are unaware of biomedical advances in diagnosis and treatment that impact sexuality. Conversely, many physicians lack sufficient awareness of the cognitive, emotional, behavioral, and cultural factors contributing to sexual disorders. Physicians who prefer broader assessments often find that time constraints in clinical practice hinder multilayered engagement. CONCLUSION: The biopsychosocial model must encompass all predisposing, precipitating, and maintaining biological, medical/surgical, cognitive, behavioral, emotional, social, and cultural factors involved in the etiology and management of sexual disorders. Etiology is best understood at a granular level that acknowledges multiple proportional contributing factors. We recommend that clinicians across disciplines increase their awareness of all relevant etiologic and treatment factors while continuing to use the accessible term "biopsychosocial."

• Keywords
• biomedical, biopsychosocial model, sex therapy, sexual disorder/dysfunction diagnosis, sexual disorder/dysfunction treatment, sexual medicine, sexual tipping point model,
• MeSH
• Models, Biopsychosocial * MeSH
• Humans MeSH
• Sexual Dysfunction, Physiological * therapy   psychology   MeSH
• Sexual Dysfunctions, Psychological * therapy   psychology   MeSH
• Sexual Health MeSH
• Sexology * MeSH
• Check Tag
• Humans MeSH
• Male MeSH
• Publication type
• Journal Article MeSH
• Review MeSH

Monitoring cognitive load is critical in diverse, demanding environments, yet conventional assessment methods face limitations in real-time applicability. While machine learning approaches using physiological signals show promise, they often require long data segments, exhibit high computational complexity, or neglect underlying causal dynamics. This paper proposes an efficient framework for cognitive load decoding using causal spatiotemporal patterns derived from multimodal peripheral biosignals. We introduce a novel feature engineering pipeline that transforms short signal segments into image-like representations capturing temporal dynamics via Gramian Angular Difference Fields and Motif Difference Fields, alongside causal interdependencies assessed using forward-backward copula Granger causality networks. These fused multimodal features are classified using a lightweight capsule neural network employing a self-attention routing mechanism. To evaluate the proposed solution, we conducted experiments on two widely used benchmark datasets, WESAD and CLAS. Our model achieved up to 94% accuracy using only 5-second signal segments, and maintained robust performance (84% accuracy) even with 1-second windows, a configuration rarely addressed in prior research. The proposed architecture includes only 323K trainable parameters, offering a favorable balance between model complexity and classification performance. The results confirm the framework's potential for computationally efficient, real-time cognitive load assessment suitable for resource-constrained environments and biofeedback applications.

• Keywords
• Capsule network, Cognitive load, Electrocardiogram, Electrodermal activity, Machine learning, Pattern recognition, Physiology,
• MeSH
• Cognition * physiology   MeSH
• Humans MeSH
• Neural Networks, Computer * MeSH
• Signal Processing, Computer-Assisted * MeSH
• Machine Learning MeSH
• Check Tag
• Humans MeSH
• Male MeSH
• Publication type
• Journal Article MeSH

Manganese(III)-porphyrins - Mn(III)P-exhibit remarkable redox activity, influencing oxidative and antioxidative processes in biological systems. In this study, we explore the dual roles of Mn(III)-2-TE-PyP5+ and Mn(III)-4-TE-PyP5+ in modulating hyaluronan degradation, a key factor in both neuroprotection and cancer therapy. While Mn(III)-2-TE-PyP5+ enhances oxidative degradation of high-molecular weight hyaluronan, facilitating immune recognition of cancer cells, its structural isomer Mn(III)-4-TE-PyP5+ acts as a potent antioxidant, safeguarding neuronal integrity against oxidative stress. Employing rotational viscometry, oximetry, electron paramagnetic resonance (EPR), and gas chromatography-mass spectrometry (GC-MS), we delineate the mechanisms underlying the redox transformations of Mn(III)P-derivatives and their impact on glycocalyx integrity. Our findings provide new insights into the selective therapeutic applications of Mn(III)P-derivatives, offering promising strategies for targeted cancer treatment and neurodegenerative disease prevention.

• Keywords
• Glycocalyx, Hyaluronan, Mn(III)-porphyrins, Neuroprotection, Rotational viscometry, Targeted cancer treatment,
• MeSH
• Antioxidants * pharmacology   MeSH
• Hyaluronic Acid metabolism   MeSH
• Humans MeSH
• Manganese * pharmacology   chemistry   MeSH
• Metalloporphyrins * pharmacology   chemistry   therapeutic use   MeSH
• Cell Line, Tumor MeSH
• Neoplasms * drug therapy   metabolism   MeSH
• Neurodegenerative Diseases * drug therapy   metabolism   MeSH
• Neuroprotective Agents * pharmacology   MeSH
• Oxidation-Reduction MeSH
• Oxidative Stress drug effects   MeSH
• Antineoplastic Agents * pharmacology   MeSH
• Animals MeSH
• Check Tag
• Humans MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• Antioxidants * MeSH
• Hyaluronic Acid MeSH
• Manganese * MeSH
• Metalloporphyrins * MeSH
• Neuroprotective Agents * MeSH
• Antineoplastic Agents * MeSH

Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) have transformed the management of obesity, demonstrating significant efficacy in inducing weight loss and improving metabolic parameters. However, emerging clinical and paraclinical evidence suggests that these agents may also contribute to an unintended reduction in skeletal muscle mass, potentially exacerbating or precipitating sarcopenic obesity, particularly in older or frail individuals with limited muscular reserves. This review critically examines current data on the effects of GLP-1 RAs on body composition, explores the underlying pathophysiological mechanisms of skeletal muscle wasting, and offers evidence-based strategies for attenuating these potential adverse outcomes. While GLP-1 RAs therapy remains central to obesity management, optimizing its use through early recognition and management of associated risks is essential to preserve muscular health, patient functional status and quality of life.

• Keywords
• GLP-1 receptor agonists, Muscle mass, Obesity, Sarcopenia, Skeletal muscle loss, Weight loss,
• MeSH
• Glucagon-Like Peptide-1 Receptor Agonists * adverse effects   pharmacology   MeSH
• Weight Loss MeSH
• Hypoglycemic Agents adverse effects   pharmacology   MeSH
• Muscle, Skeletal * drug effects   MeSH
• Anti-Obesity Agents adverse effects   pharmacology   MeSH
• Humans MeSH
• Obesity drug therapy   MeSH
• Sarcopenia * chemically induced   MeSH
• Body Composition MeSH
• Animals MeSH
• Check Tag
• Humans MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH
• Review MeSH
• Names of Substances
• Glucagon-Like Peptide-1 Receptor Agonists * MeSH
• Hypoglycemic Agents MeSH
• Anti-Obesity Agents MeSH

Renal vein thrombosis (RVT) and inferior vena cava thrombosis are extremely rare conditions, yet potentially life-threatening complications of pyelonephritis. This report describes the case of a 66-year-old patient with undiagnosed pyelonephritis, who subsequently developed RVT with an extension to the inferior vena cava. The management of the condition involved a multidisciplinary approach that resulted in nephrectomy with an extraction of the thrombus through cavotomy. This case report emphasizes the necessity of early recognition of RVT owing to pyelonephritis and complex management of this condition to prevent the adverse outcomes of impending complications.

• Keywords
• Acute pyelonephritis, Cavotomy, Nephrectomy, Renal vein thrombosis, Thromboinflammation,
• Publication type
• Journal Article MeSH
• Case Reports MeSH

The RNA editing enzyme adenosine deaminase acting on RNA 1 (ADAR1) has recently emerged from relative obscurity to be recognized as a key player in a variety of inflammatory diseases, including cancer. This growing recognition has generated interest in developing ADAR1 inhibitors; however, several fundamental questions about the enzyme need to be answered before ADAR1-based therapies can be successful. In this review, we summarize the current understanding of ADAR1, including its protein structure, RNA substrates, and roles in both innate and adaptive immunity. Recent studies have shed light on ADAR1 protein interactions and its RNA editing-independent functions. We also explore the involvement of ADAR1 in human diseases, with a focus on its roles in various cancers. Drosophila lacks an ADAR1 homolog; instead, the ADAR2 homolog is responsible for editing double-stranded RNA to prevent aberrant activation of the innate immune system. Finally, we address major questions in the field that still remain unanswered.

• Keywords
• ADAR, AGS, Aicardi-Goutières syndrome, cancer, innate immunity, interferon,
• MeSH
• Adaptive Immunity MeSH
• Adenosine Deaminase * metabolism   genetics   chemistry   MeSH
• RNA Editing * genetics   MeSH
• Humans MeSH
• Neoplasms genetics   immunology   MeSH
• Immunity, Innate MeSH
• RNA-Binding Proteins * metabolism   genetics   MeSH
• Animals MeSH
• Check Tag
• Humans MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH
• Review MeSH
• Names of Substances
• ADAR protein, human MeSH Browser
• Adenosine Deaminase * MeSH
• RNA-Binding Proteins * MeSH