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Aim: Intraspecific variation in species relative abundance is shaped by a complex interplay of abiotic and biotic factors, making it both necessary and challenging to assess their combined relative importance in explaining variations across space and time. We used two congeneric butterfly species for which extensive count data and a deep understanding of their natural history is available to test three hypotheses explaining intraspecific variation in their abundance: (H1) seasonal dispersal behaviour driven by climate, (H2) resource availability and (H3) apparent competition mediated via shared parasitoids. Taxon: Gonepteryx rhamni (Brimstone) and G. cleopatra (Cleopatra). Location: NE Iberian Peninsula, where both species coexist, and a nearby archipelago (Balearic Islands), where only Cleopatra occurs. Methods: We analysed spatial abundance variations for both species in the mainland and island–mainland differences in the abundance of Cleopatra. Abiotic and biotic factors, including temperature, host plant and overwintering habitat availability, larval parasitism and density dependence, were tested to explain the observed variations. Results: H1 can explain variation in butterfly abundance between mainland regions since in warmer summers populations increased in cooler areas but decreased in warmer areas. H2 explains the variation within mainland climate regions with a strong positive relationship between resource availability and abundance but is unlikely to explain the island–mainland variation in the abundance of Cleopatra. H3 could neither explain biogeographical variation in abundance because although richer parasitoid communities were found on the mainland, larval mortality rates were similar or lower on the mainland than in the islands. Main Conclusions: Climate and resource availability jointly account for variation in butterfly abundance across the mainland, but neither these factors nor parasitism can explain island–mainland differences. Both coexisting butterfly species and their larval parasitoids may have undergone evolutionary processes, resulting in spatial segregation that promotes the coexistence of the two butterfly species on the mainland. [ABSTRACT FROM AUTHOR]

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Background: Comprehensive management of multimorbidity can significantly benefit from advanced health risk assessment tools that facilitate value-based interventions, allowing for the assessment and prediction of disease progression. Our study proposes a novel methodology, the Multimorbidity-Adjusted Disability Score (MADS), which integrates disease trajectory methodologies with advanced techniques for assessing interdependencies among concurrent diseases. This approach is designed to better assess the clinical burden of clusters of interrelated diseases and enhance our ability to anticipate disease progression, thereby potentially informing targeted preventive care interventions. Objective: This study aims to evaluate the effectiveness of the MADS in stratifying patients into clinically relevant risk groups based on their multimorbidity profiles, which accurately reflect their clinical complexity and the probabilities of developing new associated disease conditions. Methods: In a retrospective multicentric cohort study, we developed the MADS by analyzing disease trajectories and applying Bayesian statistics to determine disease-disease probabilities combined with well-established disability weights. We used major depressive disorder (MDD) as a primary case study for this evaluation. We stratified patients into different risk levels corresponding to different percentiles of MADS distribution. We statistically assessed the association of MADS risk strata with mortality, health care resource use, and disease progression across 1 million individuals from Spain, the United Kingdom, and Finland. Results: The results revealed significantly different distributions of the assessed outcomes across the MADS risk tiers, including mortality rates; primary care visits; specialized care outpatient consultations; visits in mental health specialized centers; emergency room visits; hospitalizations; pharmacological and nonpharmacological expenditures; and dispensation of antipsychotics, anxiolytics, sedatives, and antidepressants (P <.001 in all cases). Moreover, the results of the pairwise comparisons between adjacent risk tiers illustrate a substantial and gradual pattern of increased mortality rate, heightened health care use, increased health care expenditures, and a raised pharmacological burden as individuals progress from lower MADS risk tiers to higher-risk tiers. The analysis also revealed an augmented risk of multimorbidity progression within the high-risk groups, aligned with a higher incidence of new onsets of MDD-related diseases. Conclusions: The MADS seems to be a promising approach for predicting health risks associated with multimorbidity. It might complement current risk assessment state-of-the-art tools by providing valuable insights for tailored epidemiological impact analyses of clusters of interrelated diseases and by accurately assessing multimorbidity progression risks. This study paves the way for innovative digital developments to support advanced health risk assessment strategies. Further validation is required to generalize its use beyond the initial case study of MDD. [ABSTRACT FROM AUTHOR]

"Evidence" is a key term in medicine and health services research, including Health Technology Assessment (HTA). Randomized clinical trials (RCTs) have undoubtedly dominated the scene of generating evidence for a long period of time, becoming the hallmark of evidence-based medicine (EBM). However, due to a number of misunderstandings, the lay audience and some researchers have sometimes placed too much trust in RCTs compared to other methods of investigation. One of the principal misunderstandings is to consider RCTs findings as isolated and self-apparent pieces of information. In other words, what has been essentially lacking was the awareness of the value-context of the evidence and, in particular, the value- and theory-ladenness (normativity) of scientific knowledge. This paper aims to emphasize the normativity that exists in the production of scientific knowledge, and in particular in the conduct of RCTs as well as in the performance of HTA. The work is based on some lessons learned from Philosophy of Science and the European project "VALIDATE" (VALues In Doing Assessments of healthcare TEchnologies"). VALIDATE was a three-year EU Erasmus+ strategic partnerships project (2018-2021), in which training in the field of HTA was further optimized by using insights from political science and ethics (in accordance with the recent definition of HTA). Our analysis may reveal useful insights for addressing some challenges that HTA is going to face in the future. [ABSTRACT FROM AUTHOR]

Here we apply a method for automated segmentation of the hippocampus in 3D high-resolution structural brain MRI scans. One hundred and four healthy young adults completed twenty one tasks measuring abstract, verbal, and spatial intelligence, along with working memory, executive control, attention, and processing speed. After permutation tests corrected for multiple comparisons across vertices (p less than 0.05), significant relationships were found for spatial intelligence, spatial working memory, and spatial executive control. Interactions with sex revealed significant relationships with the general factor of intelligence (g), along with abstract and spatial intelligence. These correlations were mainly positive for males but negative for females, which might support the efficiency hypothesis in women. Verbal intelligence, attention, and processing speed were not related to hippocampal structural differences. (Contains 1 table and 5 figures.)