Limited Explanatory Power Research Articles

Linear and nonlinear causality in financial markets.

Identifying and quantifying co-dependence between financial instruments is a key challenge for researchers and practitioners in the financial industry. Linear measures such as the Pearson correlation are still widely used today, although their limited explanatory power is well known. In this paper, we present a much more general framework for assessing co-dependencies by identifying linear and nonlinear causalities in the complex system of financial markets. To do so, we use two different causal inference methods, transfer entropy and convergent cross-mapping, and employ Fourier transform surrogates to separate their linear and nonlinear contributions. We find that stock indices in Germany and the U.S. exhibit a significant degree of nonlinear causality and that correlation, while a very good proxy for linear causality, disregards nonlinear effects and hence underestimates causality itself. The presented framework enables the measurement of nonlinear causality, the correlation-causality fallacy, and motivates how causality can be used for inferring market signals, pair trading, and risk management of portfolios. Our results suggest that linear and nonlinear causality can be used as early warning indicators of abnormal market behavior, allowing for better trading strategies and risk management.

Pan-European Water Use Efficiency and Sustainability Evaluation Based on Stochastic Meta-frontier Analysis

In 2007, the European Union (EU) intended to become a water-efficient community. Yet, despite the EU’s commitment to the United Nations (UN) sustainable development goals (SDGs), relevant insights based on scientific research are still sparse. This study presents a pan-European water use performance evaluation, considering differences in production technologies and potential efficiency determinants. The empirical results are obtained by analysing country-level panel data from 2011 to 2020. Our paper provides more instructive and encompassing findings to inform holistic policy formulation and management practices than prior studies that have typically relied on partial-factor indicators with limited explanatory power. We find that European countries are subject to technological and efficiency heterogeneity, and our production function and inefficiency equation estimations attest to the existence of divergent cause-effect relationships, calling for decentralised, customised solutions. Arguably, our comparative benchmarking analysis constitutes the first comprehensive cross-country investigation for Europe of its kind, underscoring the importance of impactful science in fostering the preservation of high civilisation in line with the theme of this special issue.

Genetic and environmental considerations for the utilization of Pinus pinaster Ait. provenances across a region lacking proper local genetic materials

Maritime pine (Pinus pinaster Ait.) covers vast areas and is of economic importance in southwestern Europe, particularly in Galicia (NW Spain). Galicia is a heterogeneous region with an Atlantic climate in the coast and a Mediterranean-like climate in the inland, where forest reproductive materials (FRM) with proper adaptation, productivity and timber quality are not available. Thus, there is a need for tailored FRM recommendations for reforestation in this region. P. pinaster is particularly sensitive to environmental variation and shows significant intraspecific genetic variability in this sensitivity, so understanding population responses to environmental variation becomes crucial for proper selection of FRM. Taking advantage of volume growth and stem straightness 13 years after planting, assessed on c. 7500 trees from 25 P. pinaster populations established in seven common gardens across inland Galicia, we analyzed intraspecific variation in sensitivity to climate, geographic, edaphic and site quality factors. We used Mantel correlations and factorial regression models to distinguish the environmental parameters explaining the observed population × site interaction. We also estimated population phenotypic plasticity across sites and the existing genetic relationship between growth and stem straightness to define the optimal selection strategy for productivity purposes. Results showed a quantitatively significant population × site interaction for growth whereas it was almost negligible for stem straightness. In the case of growth, no specific environmental factor was able to explain the population relative performance across test sites, being site quality the only significant factor but with low power to describe the patterns found. Population differences were maximized in higher site quality conditions, where the largest gains from planting selected populations would be expected. Tree growth and straightness were not genetically correlated. Based on these results, subdividing inland Galicia for deployment of P. pinaster FRM throughout specific selections for each subregion is not recommended. Selecting FRM based on average growth and its phenotypic stability should be also avoided, as both properties were negatively correlated. We recommend selecting FRM based on the results from high quality sites, where Atlantic origin populations with high levels of genetic improvement showed the fastest growth. The inclusion of selection criteria based on stem straightness did not alter recommendations given that fast growing FRM showed intermediate or slightly above-average straightness. The limited explanatory power of climate factors for the population × site interaction prevents adjusting recommendations in light of the projected climate change.

Reconstructing and assessing global maritime transport network: based on the Port Cargo Composite Transport index

ABSTRACT Solution to the problem of limited explanatory power of transport economics due to the homogenisation of existing the Global Maritime Transport Network (GMTN) construction indicators. By integrating the Port Cargo Composite Transport (PCCT) index and considering the volume-value mismatch relationship and the type and flow of cargo transported in ports, the GMTN can be reconstructed through a bottom-up logic. Combining the complex network, natural breaks, and point mutual information method with the Leiden and PageRank algorithm, the characteristics of the GMTN were derived from three aspects, i.e. network topology, node characteristics, and inter-node dependency. The GMTN presents the characteristics as follows. Community division presents typical geographical aggregation and industrial complementarity. Node characteristics show the classic phenomenon of rich people’s clubs, with obvious heavy-tailed distribution. Maritime transport linkage preferences present a phenomenon of geographical proximity, and their expansion can clarify the direction of the main links. Enhancing their maritime links will be more targeted to support the transport of trade cargoes. These findings help us to understand the characteristics of the international maritime trade pattern, and provide decision references for industry stakeholders to provide a strategic layout of maritime transport.

The Effects of Age and Treatment Intensity on Behavioral Target Mastery With Applied Behavior Analysis (ABA) Intervention Using Causal Moderation Models.

Introduction Applied behavior analysis (ABA) is a therapy that focuses on improving specific behaviors using positive and negative reinforcement through antecedents, behaviors, and consequences, particularly in individuals with autism and other developmental disorders. It uses the principles of learning theory to bring about meaningful and positive changes in behavior. In ABA treatment, intensityrefers to the amount and frequency of therapy an individual receives. This includes weekly hours, session trials, and overall duration. Intensive treatment involves more hours and trials tailored to individual needs and responses. Younger individuals, particularly those with autism, often receive more intensive therapy because early intervention leads to better outcomes. Programs may recommend 25-40 hours per week for young children. As children age, therapy may become less intensive, focusing on specific skills. The study explores how age and treatment intensity affect the mastery of behavioral targets in ABA interventions. Materials and methods This study involved 100 participants (89 children, four adults, and seven instances where the individuals' ages were not recorded due to random data entry errors (MCAR)) who received ABA treatment over three months. The treatments included functional analysis, discrete trials, and massand naturalistic training. Data on the mastery of target behaviors were collected using the Catalystsoftware (New York, New York). The primary outcome was the percentage of mastered behavioral targets, indicating the effectiveness of the ABA treatment. Several predictors were examined, including the participant's age and treatment intensity variables, such as the average number of trials and teaching days to achieve behavioral mastery. The interaction effects between age and these treatment intensity variables were analyzed. The study used descriptive and inferential statistics to explore these interactions, including correlational and multiple regression analyses with causal moderator modeling. Results In Model 1, a baseline multiple regression analysis showed that average teaching days significantly predict the percentage of targets mastered. However, its limited explanatory power suggests other variables also play a role. Model 2 introduced interaction effects using causal models, revealing that age moderates the relationship between treatment variables and behavioral outcomes. This model provided a more nuanced understanding but still had room for improvement. Model 3 further refined the approach, achieving higher R-values and lower standard error. It highlighted age's significant role in modifying the impact of teaching days on mastery. This model's superior performance emphasizes the importance of considering age as a moderating factor in ABA interventions, leading to more effective and personalized behavior therapy. Conclusions This study significantly enhances our understanding of the complex interactions between age and treatment intensity within ABAinterventions. Practitioners and researchers can develop more tailored and effective therapeutic strategies by identifying and leveraging these interactions. This approach optimizes the treatment process and ensures that interventions are personalized to meet the unique needs of each individual. Ultimately, this leads to more successful outcomes in behavioral therapy, fostering improved adaptive behaviors and overall development.

Explaining Seeking, Scanning, and Avoidance of Information About the Mammography-Screening: Results of a Two-Wave Online Survey with a Stratified Sample of Women

ABSTRACT Whether individuals engage with or avoid health information and which sources are used is crucial for informed decision-making about mammography. Therefore, we aim to develop a typology of mammography-related information behaviors and explore their determinants, which were derived from the Theory of Motivated Information Management (TMIM). Based on a two-wave online survey of a sample of German women aged 40 to 69 years (N = 1,138), a cluster analysis resulted in five person-centric types of information behavior that cover respondents’ variety of engagement with mammography-related information: The seekers, the scanners, the avoiders, the involved, and the inactive. The types indicated that most individuals possess a high preference for one strategy of information behavior. Looking at the determinants of belonging to a particular type of information behavior, it becomes apparent that the factors of the TMIM have only limited explanatory power. The most relevant factors in distinguishing the types of information behaviors are benefit perceptions, worry, interest, avoidance efficacy, seeking, and avoidance-related outcome expectancies. Scanners and seekers had higher benefit perceptions. Seekers were further motivated by greater worries, while involved ones felt more interested and held stronger expectancies. Avoiders were more anxious and had a higher avoidance efficacy. The study suggests that inactive individuals and avoiders are highly prevalent and relevant target groups for health interventions that support informed decision-making. To facilitate informed decision-making, women should be encouraged to weigh benefits and harms of their options and to address negative emotions, such as anxiety, that may exist or arise during decision-making.

Functional Performance and Tendon Morphology After Operative or Nonoperative Treatment of Achilles Tendon Ruptures.

While controversy remains as to the relative benefit of operative (OM) versus non-operative management (NOM) of Achilles tendon (AT) ruptures (ATR), few studies have examined the effect on high impact maneuvers such as jumping and hopping. The purpose of this study was to determine if functional performance including strength, jumping, and hopping outcomes differed between OM and NOM of acute ATR. The secondary objective was to assess the degree of association between AT morphology and performance outcomes. Retrospective cohort with a single prospective evaluation. All patients were treated at an institutional secondary care center. Eligible participants (n=12 OM; 12 NOM) who were treated with OM or NOM of ATR within three weeks of injury were evaluated a minimum 20 months following ATR. AT length, thickness and gastrocnemius muscle thickness were assessed with B-mode ultrasound. Isokinetic plantar flexor strength, hop tests and countermovement and drop jumps were completed. Two-way ANOVAS were completed on all tests with unilateral values, independent t-tests were used for bilateral outcomes, and linear regressions were completed to assess the relationship between normalized AT length and performance. Affected limb AT was elongated and thickened (p\<0.01), gastrocnemius was atrophied (p\< 0.01) and angle-specific plantar flexor torque was reduced at 120°/s when measured at 20° plantar flexion (p = 0.028). Single leg drop vertical jump was higher in OM (p = 0.015) with no difference for hop and jump tests. AT length was related to plantar flexor torque but had no relationship with hopping performance. Hop test performance was maintained despite plantarflexion weakness, gastrocnemius atrophy, and AT elongation. This may be the result of compensatory movement patterns. AT length holds limited explanatory power in plantar flexor strength, although this relationship should be evaluated further. Level III.

Juridico-political conditions of exceptional security measures: Turkey (1971-2002)

ABSTRACT Contemporary literature on security measures interfering with the rights and liberties regime often relies on an exceptionalist approach grounded in the norm-exception dichotomy. This perspective oversimplifies the juridical conditions of exceptional security measures, where the law and politics coalesce, as the relationship between the norm and the exception is not necessarily dichotomous. Through an examination of Turkey’s exceptional security measures from 1971 to 2002, this paper shows that the tension between political power and the law can unfold in diverse ways, even in countries where executive decision-making is constitutionally favoured, with norms and exceptions usually coexisting within the constitutional order. It argues that exceptional security measures are ingrained in state rule other than in the times of exception, challenging the limited explanatory power of the norm-exception dichotomy. Categorising every decision avoiding legal oversight as the Schmittian exception results in theoretically reductionist interpretations, overlooking the fact that such measures may have various juridico-political conditions. By analysing threat framing and the dispersion of political power, this study proposes a categorisation as to how norms and exceptions to the norms are created.

Global richness patterns of alpine genus Gentiana depend on multiple factors.

Environmental factors impact species richness differently across taxonomic groups, and understanding the geographic patterns and drivers influencing alpine plant richness remains limited. This study compiled global distribution data of 404 species of Gentiana, an alpine genus, and analyzed the relative effects of different environmental factors and several previously proposed models on the variation of Gentiana richness. By evaluating the effects of range size and regions on the relationships between Gentiana richness and environmental factors, we found that all tested environmental factors had weak effects on richness variation for all species and wide-ranging species, while habitat heterogeneity was the best predictor for narrow-ranging species. Habitat heterogeneity was the main driver of richness variation in Europe and Asia, but not in North America. The multiple regression model that included variables for energy, water, seasonality, habitat heterogeneity and past climate change had the highest explanatory power, but it still explained less than 50% of the variation in species richness for all Gentiana species at both global and regional scale, except for Europe. The limited explanatory power of environmental factors in explaining species richness patterns for all species, along with the variations observed among regions, suggest that other factors, such as evolutionary processes and biogeographic history may have also influenced the geographic patterns of Gentiana species richness. In conclusion, our results indicate a limited influence of climate factors on alpine species richness, while habitat heterogeneity, along with its impacts on speciation and dispersal, likely play significant roles in shaping the richness of alpine Gentiana species.

When (and how) ideas become arguments: the regulation of party donations in Germany

Abstract This article aims to explain the deviant German case of an early and comprehensive regulation of party donations (combining a high level of transparency and incentives for small donations). Given the limited explanatory power of economic and institutional factors, the article emphasises the causal role of ideas for a policy stabilisation which occurred after 1993. A process-tracing analysis suggests that the 1983–1993 reform period was characterised by a conflict of ideas. During this conflict, ideas regarding undisclosed donations as an anti-democratic interference with democratic political competition came to prevail over ideas regarding all donations as a necessary condition for democratic competition irrespective of their regulation. The key actors in this conflict were, on the one hand, the new Green party which resuscitated the idea of donations being potentially anti-democratic and, on the other hand, the Constitutional Court which ultimately endorsed this ideational legacy promoted by the Greens. After 1993, donations in Germany came to be accepted as a necessary evil whose anti-democratic potential had to be limited by transparency obligations and incentives for small donations. The findings presented here suggest that policymakers need to link attempts to regulate party donations to ideational legacies (if available) to successfully tackle political corruption.

Econometric Modeling of Environmental Pollution Factors and Their Impact on Life Expectancy in Uzbekistan

The article examines the impact of environmental pollution factors on life expectancy in Uzbekistan. The study is based on econometric modeling methods, including panel data on the country’s regions for the period of 2010-2023. The area of protected natural areas, the volume of pollutant emissions into the atmosphere, the provision of doctors and hospital beds, and access to drinking water were utilized as factors influencing life expectancy. Despite the identification of some relationships, the modeling results showed limited explanatory power of the selected models, which is associated with the low quality and incompleteness of statistical data. The study revealed significant regional differentiation and polarization in environmental indicators, which requires measures to improve the quality of data and take into account additional factors.

Why has farming in Europe changed? A farmers’ perspective on the development since the 1960s

Farming in Europe has been the scene of several important socio-economic and environmental developments and crises throughout the last century. Therefore, an understanding of the historical driving forces of farm change helps identifying potentials for navigating future pathways of agricultural development. However, long-term driving forces have so far been studied, e.g. in anecdotal local case studies or in systematic literature reviews, which often lack context dependency. In this study, we bridged local and continental scales by conducting 123 oral history interviews (OHIs) with elderly farmers across 13 study sites in 10 European countries. We applied a driving forces framework to systematically analyse the OHIs. We find that the most prevalent driving forces were the introduction of new technologies, developments in agricultural markets that pushed farmers for farm size enlargement and technological optimisation, agricultural policies, but also cultural aspects such as cooperation and intergenerational arrangements. However, we find considerable heterogeneity in the specific influence of individual driving forces across the study sites, implying that generic assumptions about the dynamics and impacts of European agricultural change drivers hold limited explanatory power on the local scale. Our results suggest that site-specific factors and their historical development will need to be considered when addressing the future of agriculture in Europe in a scientific or policy context.

Housing Market Dynamics in Kazakhstan: An Estimated DSGE Model

This study investigates the drivers of housing price fluctuations in Kazakhstan by using a dynamic stochastic general equilibrium (DSGE) model with the housing market. We estimate the model by using Bayesian methods with data for the period of 2010Q1 to 2020Q4. We find that housing preference shocks play a crucial role in explaining for housing market fluctuations. These shocks account for a substantial portion of housing price and consumption behavior variations. Surprisingly, monetary policy, government spending, productivity and markup shocks show limited explanatory power for housing price fluctuations. Our findings suggest the importance of monitoring potential housing bubbles, as well as the impact of housing market fluctuations on the broader economy, thus highlighting the housing wealth effect. Additionally, our analysis indicates that the pension withdrawal policy has a minor long-term effect on business-cycle fluctuations in Kazakhstan. Overall, technology shocks are key drivers of gross domestic product (GDP) variance, while inflation rate variation is mainly explained by monetary policy and foreign demand shocks.

A Genomic Score to Predict Local Control among Patients with Brain Metastases Managed with Radiation

Clinical predictors of local recurrence following radiation among patients with brain metastases (BrM) provide limited explanatory power. As a result, radiation doses and fractionation schemes are relatively homogeneous and prescribed with a "one-size-fits-all" approach. We hypothesized that tumor-specific genomic alterations may underlie radiation sensitivity among patients with BrM and sought to develop a DNA-based signature of radiation-based efficacy in this patient population, utilizing genes that are readily testable in modern-day assays, to identify subpopulations at greater vs. lesser risk of recurrence. We identified 570 patients with 1,487 distinct BrM managed with whole-brain (WBRT) or stereotactic radiation therapy (SRS/SRT) at a tertiary cancer center (2013-2020) for whom next-generation sequencing panel data (OncoPanel, 239 genes) were available on at least one extracranial or intracranial tumor specimen. Fine/Gray's competing risks regression was utilized to compare local recurrence on a per-metastasis level among patients with vs. without somatic alterations of likely biological significance across 84 OncoPanel genes with a mutational frequency of >0.5%. Genes with a q-value<0.10 were utilized to develop a numeric "Brain-Radiation Prediction Score" ("Brain-RPS") to quantify local recurrence risk. Genomic alterations of potential biological relevance in 11 (ATM, MYCL, PALB2, FAS, PRDM1, PAX5, CDKN1B, EZH2, NBN, DIS3, MDM4) and two genes (FBXW7 and AURKA) were associated with a decreased or increased risk of local recurrence, respectively (q-value<0.10). Weighted scores corresponding to the strength of association with local failure for each gene were summed to calculate a patient-level Brain-RPS. On multivariable Fine/Gray's competing risks regression, Brain-RPS [1.66 (1.44-1.92, p<0.001)], metastasis-associated edema [1.89 (1.38-2.59), p<0.001], and receipt of WBRT without SRS/SRT or neurosurgical resection [2.73 (1.78-4.20), p<0.001] were independent predictors of local failure. Utilizing a targeted panel of genes with a known role in cancer pathogenesis, we developed a genomic score that can be calculated from an extracranial or intracranial site to quantify local recurrence risk following brain-directed radiation. Prior attempts to develop a biomarker-based radiation response signature have not focused on patients with BrM and have primarily relied on RNA-based measures of radiosensitivity, limiting their utility in real-world clinical practice for this patient population. To our knowledge, this represents the first study to systemically correlate DNA-based alterations with radiation-based outcomes among patients with BrM. If validated, Brain-RPS has potential to facilitate clinical trials aimed at genome-based personalization of radiation treatment among patients with BrM.

Paediatric COVID-19 Outcomes: Haematology Parameters, Mortality Rates, and Hospitalization Duration.

The global COVID-19 pandemic has strained healthcare systems around the globe, necessitating extensive research into the variables that affect patient outcomes. This study examines the relationships between key haematology parameters, duration of hospital stay (LOS), and mortality rates in COVID-19 cases in paediatric patients. Researchers analyse relationships between independent variables (COVID-19 status, age, sex) and dependent variables (mortality, LOS, coagulation parameters, WBC count, RBC parameters) using multivariate regression models. Although the R-square values (0.6-3.7%) indicate limited explanatory power, coefficients with statistical significance establish the impact of independent variables on outcomes. Age emerges as a crucial predictor of mortality; the mortality rate decreases by 1.768% per age group. Both COVID-19 status and age have an inverse relationship with length of stay, emphasising the milder hospitalisation of children. Platelet counts decline with age and male gender, potentially revealing the influence of COVID-19 on haematological markers. There are significant correlations between COVID-19 status, age, gender and coagulation measures. Lower prothrombin time and D-dimer concentrations in elder COVID-19 patients are indicative of distinct coagulation profiles. WBC and RBC parameters exhibit correlations with variables: COVID-19-positive patients have lower WBC counts, whereas male COVID-19-positive patients have higher RBC counts. In addition, correlations exist between independent variables and the red cell distribution width, mean corpuscular volume, and mean corpuscular haemoglobin. However, there is no correlation between mean corpuscular haemoglobin concentration and outcomes, indicating complex interactions between haematological markers and outcomes. In essence, this study underlines the importance of age in COVID-19 mortality, provides novel insights into platelet counts, and emphasises the complexity of the relationships between haematological parameters and disease outcomes.

Causally informed activity flow models provide mechanistic insight into network-generated cognitive activations

Brain activity flow models estimate the movement of task-evoked activity over brain connections to help explain network-generated task functionality. Activity flow models have been shown to accurately generate task-evoked brain activations across a wide variety of brain regions and task conditions. However, these models have had limited explanatory power, given known issues with causal interpretations of the standard functional connectivity measures used to parameterize activity flow models. We show here that functional/effective connectivity (FC) measures grounded in causal principles facilitate mechanistic interpretation of activity flow models. We progress from simple to complex FC measures, with each adding algorithmic details reflecting causal principles. This reflects many neuroscientists’ preference for reduced FC measure complexity (to minimize assumptions, minimize compute time, and fully comprehend and easily communicate methodological details), which potentially trades off with causal validity. We start with Pearson correlation (the current field standard) to remain maximally relevant to the field, estimating causal validity across a range of FC measures using simulations and empirical fMRI data. Finally, we apply causal-FC-based activity flow modeling to a dorsolateral prefrontal cortex region (DLPFC), demonstrating distributed causal network mechanisms contributing to its strong activation during a working memory task. Notably, this fully distributed model is able to account for DLPFC working memory effects traditionally thought to rely primarily on within-region (i.e., not distributed) recurrent processes. Together, these results reveal the promise of parameterizing activity flow models using causal FC methods to identify network mechanisms underlying cognitive computations in the human brain.

Structure of Psychopathology in Romanian Preschool-Aged Children in an Epidemiological and a High-Risk Sample

Research on bifactor models of psychopathology in early childhood is limited to community samples with little longitudinal follow-up. We examined general and specific forms of psychopathology within 2 independent samples of preschool-aged Romanian children. Within a sample with children exposed to psychosocial deprivation, we also examined antecedents and longitudinal outcomes of the general factor. One sample consisted of 350 Romanian children (mean age = 39.7 months, SD = 10.9) from an epidemiological study; the second sample consisted of 170 Romanian children (mean age = 55.6 months, SD = 1.9) exposed to severe early-life deprivation, as well as community comparison children, with longitudinal follow-up at 8 and 12 years. Psychopathology symptoms were assessed through caregiver-reported structured clinical interviews. An SI-1 bifactor model of psychopathology was supported in both samples and included specific factors for externalizing, internalizing, and disturbed relatedness symptoms. In the second sample, longer duration of psychosocial deprivation and lower-quality caregiving were associated with higher scores on the general and all specific factors. Higher scores on the general factor were associated with later cognitive function, competence, and psychopathology symptoms. Considering all factors together, only the general factor explained variance in later childhood outcomes and was slightly stronger compared to a total symptom count for some, but not all, outcomes. General psychopathology in early childhood explains meaningful variance in child outcomes across multiple domains of functioning in later childhood. However, important questions remain regarding its clinical utility and usefulness, given complex measurement and limited explanatory power beyond the more accessible approach of a total symptom count. The Bucharest Early Intervention Project; https://clinicaltrials.gov/; NCT00747396.

A genomic score to predict local control among patients with brain metastases managed with radiation.

2011 Background: Clinical predictors of local recurrence following radiation among patients with brain metastases (BrM) provide limited explanatory power. As a result, radiation doses and fractionation schemes are prescribed with a “one-size-fits-all” approach. We sought to develop a DNA-based signature of radiation-based efficacy among patients with BrM, utilizing readily testable genes, to identify subpopulations at greater vs. lesser risk of recurrence. Methods: We retrospectively identified 570 patients with 1,487 distinct BrM managed with whole-brain (WBRT) or stereotactic radiation therapy (SRS/SRT) at a tertiary cancer center (2013-2020) for whom next-generation sequencing panel data (OncoPanel, 239 genes) were available on at least one tumor specimen. Local recurrence was assessed in a manner consistent with Response Assessment in Neuro-Oncology – Brain Metastases guidelines (i.e., radiographic enlargement of &gt;20% in maximal cross-sectional diameter). Enlarging lesions managed with salvage treatment prior to &gt;20% enlargement were considered to have recurred on the date of salvage therapy. Fine/Gray’s competing risks regression was utilized to compare local recurrence on a per-metastasis level among patients with vs. without somatic alterations of likely biological significance across 84 OncoPanel genes with a mutational frequency &gt;0.5%. Genes with a q-value&lt;0.10 were utilized to develop a numeric “Brain-Radiation Prediction Score” (“Brain-RPS”) to quantify local recurrence risk. Results: Genomic alterations of potential biological relevance in 11 ( ATM, MYCL, PALB2, FAS, PRDM1, PAX5, CDKN1B, EZH2, NBN, DIS3, MDM4) and two genes ( FBXW 7 and AURKA) were associated with a decreased or increased risk of local recurrence, respectively (q-value&lt;0.10). Weighted scores corresponding to the strength of association with local failure for each gene were summed to calculate a patient-level RPS. On multivariable Fine/Gray’s competing risks regression, RPS [1.66 (1.44-1.92, p&lt;0.001)], metastasis-associated edema [1.89 (1.38-2.59), p&lt;0.001] and receipt of WBRT without SRS/SRT or neurosurgical resection [2.73 (1.78-4.20), p&lt;0.001] were independent predictors of local failure. Conclusions: We developed a genomic score that can be calculated from an extracranial or intracranial site to quantify local recurrence risk following brain-directed radiation. Prior attempts to develop a biomarker-based radiation response signature have not been BrM-specific and have primarily relied on RNA-based measures of radiosensitivity, limiting their utility in clinical practice. To our knowledge, this represents the first study to systemically correlate DNA-based alterations with radiation-based outcomes among patients with BrM. If validated, Brain-RPS has potential to facilitate clinical trials aimed at genomic personalization of radiation treatment among patients with BrM.

A genomic score to predict local control among patients with brain metastases managed with radiation.

Clinical predictors of local recurrence following radiation among patients with brain metastases (BrM) provide limited explanatory power. We developed a DNA-based signature of radiotherapeutic efficacy among patients with BrM to better characterize recurrence risk. We identified 570 patients with 1487 BrM managed with whole-brain (WBRT) or stereotactic radiation therapy at Brigham and Women's Hospital/Dana-Farber Cancer Institute (2013-2020) for whom next-generation sequencing panel data (OncoPanel) were available. Fine/Gray's competing risks regression was utilized to compare local recurrence on a per-metastasis level among patients with versus without somatic alterations of likely biological significance across 84 genes. Genes with a q-value ≤ 0.10 were utilized to develop a "Brain-Radiation Prediction Score" ("Brain-RPS"). Genomic alterations in 11 (ATM, MYCL, PALB2, FAS, PRDM1, PAX5, CDKN1B, EZH2, NBN, DIS3, and MDM4) and 2 genes (FBXW7 and AURKA) were associated with decreased or increased risk of local recurrence, respectively (q-value ≤ 0.10). Weighted scores corresponding to the strength of association with local failure for each gene were summed to calculate a patient-level RPS. On multivariable Fine/Gray's competing risks regression, RPS [1.66 (1.44-1.91, P < .001)], metastasis-associated edema [1.60 (1.16-2.21), P = .004], baseline size [1.02 (1.01-1.03), P < .001] and receipt of WBRT without local therapy [4.04 (2.49-6.58), P < .001] were independent predictors of local failure. We developed a genomic score to quantify local recurrence risk following brain-directed radiation. To the best of our knowledge, this represents the first study to systematically correlate DNA-based alterations with radiotherapeutic outcomes in BrM. If validated, Brain-RPS has potential to facilitate clinical trials aimed at genome-based personalization of radiation in BrM.

Climate-driven variation in dispersal ability predicts responses to forest fragmentation in birds.

Species sensitivity to forest fragmentation varies latitudinally, peaking in the tropics. A prominent explanation for this pattern is that historical landscape disturbance at higher latitudes has removed fragmentation-sensitive species or promoted the evolution of more resilient survivors. However, it is unclear whether this so-called extinction filter is the dominant driver of geographic variation in fragmentation sensitivity, particularly because climatic factors may also cause latitudinal gradients in dispersal ability, a key trait mediating sensitivity to habitat fragmentation. Here we combine field survey data with a morphological proxy for avian dispersal ability (hand-wing index) to assess responses to forest fragmentation in 1,034 bird species worldwide. We find that fragmentation sensitivity is strongly predicted by dispersal limitation and that other factors-latitude, body mass and historical disturbance events-have relatively limited explanatory power after accounting for species differences in dispersal. We also show that variation in dispersal ability is only weakly predicted by historical disturbance and more strongly associated with intra-annual temperature fluctuations (seasonality). Our results suggest that climatic factors play a dominant role in driving global variation in the impacts of forest fragmentation, emphasizing the need for more nuanced environmental policies that take into account local context and associated species traits.