Generalizable Patterns Research Articles

CORR Synthesis: When Should We Be Skeptical of Clinical Prediction Models?

CORR Synthesis: When Should We Be Skeptical of Clinical Prediction Models?

Dissociating memory accessibility and precision in forgetting.

Forgetting involves the loss of information over time; however, we know little about what form this information loss takes. Do memories become less precise over time, or do they instead become less accessible? Here we assessed memory for word-location associations across four days, testing whether forgetting involves losses in precision versus accessibility and whether such losses are modulated by learning a generalizable pattern. We show that forgetting involves losses in memory accessibility with no changes in memory precision. When participants learned a set of related word-location associations that conformed to a general pattern, we saw a strong trade-off; accessibility was enhanced, whereas precision was reduced. However, this trade-off did not appear to be modulated by time or confer a long-term increase in the total amount of information maintained in memory. Our results place theoretical constraints on how models of forgetting and generalization account for time-dependent memory processes. PROTOCOL REGISTRATION: The stage 1 protocol for this Registered Report was accepted in principle on 4 June 2019. The protocol, as accepted by the journal, can be found at https://doi.org/10.6084/m9.figshare.c.4368464.v1 .

Variability of surface climate in simulations of past and future

Abstract. It is virtually certain that the mean surface temperature of the Earth will continue to increase under realistic emission scenarios, yet comparatively little is known about future changes in climate variability. This study explores changes in climate variability over the large range of climates simulated by the Coupled Model Intercomparison Project Phase 5 and 6 (CMIP5/6) and the Paleoclimate Modeling Intercomparison Project Phase 3 (PMIP3), including time slices of the Last Glacial Maximum, the mid-Holocene, and idealized experiments (1 % CO2 and abrupt4×CO2). These states encompass climates within a range of 12 ∘C in global mean temperature change. We examine climate variability from the perspectives of local interannual change, coherent climate modes, and through compositing extremes. The change in the interannual variability of precipitation is strongly dependent upon the local change in the total amount of precipitation. At the global scale, temperature variability is inversely related to mean temperature change on intra-seasonal to multidecadal timescales. This decrease is stronger over the oceans, while there is increased temperature variability over subtropical land areas (40∘ S–40∘ N) in warmer simulations. We systematically investigate changes in the standard deviation of modes of climate variability, including the North Atlantic Oscillation, the El Niño–Southern Oscillation, and the Southern Annular Mode, with global mean temperature change. While several climate modes do show consistent relationships (most notably the Atlantic Zonal Mode), no generalizable pattern emerges. By compositing extreme precipitation years across the ensemble, we demonstrate that the same large-scale modes influencing rainfall variability in Mediterranean climates persist throughout paleoclimate and future simulations. The robust nature of the response of climate variability, between cold and warm climates as well as across multiple timescales, suggests that observations and proxy reconstructions could provide a meaningful constraint on climate variability in future projections.

Life-history traits moderate the susceptibility of native mammals to an invasive predator

The invasive Burmese python (Python molurus bivittatus) is causing declines in the numbers and diversity of native mammals in the Greater Everglades Ecosystem (GEE). However, limited evidence suggests that some species may be less susceptible to pythons than others. This difference in susceptibility may be a function of different life-history traits. We analysed incidence data with a multi-species hierarchical occupancy model to evaluate the influence of pythons on native mammals and examine the association between python’s influence on species occurrence and life-history traits. We also used our traits-based model to predict the effects of pythons on occupancy probabilities of five mammalian species of conservation or management concern known to occur in the GEE but not detected in our study. Ten of 18 observed mammals showed significant negative effects from pythons, while one responded positively. We found that three of the six species traits evaluated (mass, fecundity, and habitat breadth) moderated the negative effects of pythons on mammal occurrence and were, thus, useful for predicting species responses. Our results suggest larger, fecund and/or species with wide habitat breadths were less susceptible to increasing relative densities of pythons. Our results also suggest a positive and neutral associations between rodents and relative python density, likely due to wide habitat breadths, high fecundity rates, and the reduction of mammalian predators in areas with higher relative python densities. These trait relationships predicted a negative response of all five unobserved species of management concern included in our analysis. Our study provides a broader understanding of wildlife community vulnerability to invasive predators and demonstrates how trait-based models can be used to elucidate generalizable patterns and generate predictions for rare and/or undetected species.

Molecular Patterns in Acute Pancreatitis Reflect Generalizable Endotypes of the Host Response to Systemic Injury in Humans.

Acute Pancreatitis (AP) is sudden onset pancreas inflammation that causes systemic injury with a wide and markedly heterogeneous range of clinical consequences. Here, we hypothesized that this observed clinical diversity corresponds to diversity in molecular subtypes that can be identified in clinical and multiomics data. Observational cohort study. n = 57 for the discovery cohort (clinical, transcriptomics, proteomics, and metabolomics data) and n = 312 for the validation cohort (clinical and metabolomics data). We integrated coincident transcriptomics, proteomics, and metabolomics data at serial time points between admission to hospital and up to 48 hours after recruitment from a cohort of patients presenting with acute pancreatitis. We systematically evaluated 4 different metrics for patient similarity using unbiased mathematical, biological, and clinical measures of internal and external validity.We next compared the AP molecular endotypes with previous descriptions of endotypes in a critically ill population with acute respiratory distress syndrome (ARDS). Our results identify 4 distinct and stable AP molecular endotypes. We validated our findings in a second independent cohort of patients with AP.We observed that 2 endotypes in AP recapitulate disease endotypes previously reported in ARDS. Our results show that molecular endotypes exist in AP and reflect biological patterns that are also present in ARDS, suggesting that generalizable patterns exist in diverse presentations of critical illness.

Forecasting cycles of seizure likelihood.

Seizure unpredictability is rated as one of the most challenging aspects of living with epilepsy. Seizure likelihood can be influenced by a range of environmental and physiological factors that are difficult to measure and quantify. However, some generalizable patterns have been demonstrated in seizure onset. A majority of people with epilepsy exhibit circadian rhythms in their seizure times, and many also show slower, multiday patterns. Seizure cycles can be measured using a range of recording modalities, including self-reported electronic seizure diaries. This study aimed to develop personalized forecasts from a mobile seizure diary app. Forecasts based on circadian and multiday seizure cycles were tested pseudoprospectively using data from 50 app users (mean of 109 seizures per subject). Individuals' strongest cycles were estimated from their reported seizure times and used to derive the likelihood of future seizures. The forecasting approach was validated using self-reported events and electrographic seizures from the Neurovista dataset, an existing database of long-term electroencephalography that has been widely used to develop forecasting algorithms. The validation dataset showed that forecasts of seizure likelihood based on self-reported cycles were predictive of electrographic seizures for approximately half the cohort. Forecasts using only mobile app diaries allowed users to spend an average of 67.1% of their time in a low-risk state, with 14.8% of their time in a high-risk warning state. On average, 69.1% of seizures occurred during high-risk states and 10.5% of seizures occurred in low-risk states. Seizure diary apps can provide personalized forecasts of seizure likelihood that are accurate and clinically relevant for electrographic seizures. These results have immediate potential for translation to a prospective seizure forecasting trial using a mobile diary app. It is our hope that seizure forecasting apps will one day give people with epilepsy greater confidence in managing their daily activities.

Mapping the socio-ecological impacts of invasive plants in South Africa: Are poorer households with high ecosystem service use most at risk?

It is generally suggested that invasive alien plant species (IAPS) negatively affect livelihoods. However, there is a need to find more generalisable patterns of IAPS impacts on livelihoods, which are useful for decision making at broad scales. Here we test the hypothesis that across South Africa poorer communities with high reliance on provisioning ecosystem services are more at risk from IAPS. To do so, we integrate two national-scale datasets; 1) The South African Plant Invaders Atlas, and 2) the National Census Data, which provides details on household income and selected provisioning ecosystem service use. Our analysis revealed that the potential impacts of IAPS increased as household income decreased, confirming that IAPS had greater negative effects in poorer landscapes. Furthermore, IAPS had the potential to be more impactful on selected provisioning ecosystem services where households were more reliant on them. Taken together, our results confirm that across South Africa, landscapes with poorer households and high reliance on the selected provisioning ecosystem services are likely the most negatively affected by IAPS. This novel broad-scale approach revealed landscape-scale patterns of the potential socio-ecological impacts of IAPS and will help decision makers direct resources for IAPS management to where they may be most effective.

Publicidad y aumento de las ventas. Estudio inductivo sobre campañas vendedoras

The primacy of cognitivist methodologies, equivocal econometric studies and some fallacies in the commercial valuation of advertising have conceptually diluted sales, giving preference to other outputs and have contributed to neglecting the need to isolate and theorize advertising procedures capable of increasing sales.To overcome the deficiency, the so-called Grounded Theory, a qualitative-inductive paradigm of recent application in marketing, has been used ad experimentum, with the aim of establishing generalizable patterns from the sites of cases, both to classify and to generate predictive hypotheses, which are of value for advertising practice. Critical incidents have been revealed from a content questionnaire to a semi-random selection from among 1,104 cases of campaigns awarded for their selling efficiency –IPA (1992-2016) and Efi Awards (2015-2017)– examined until reaching saturation productivity and finishing process with 30 cases examined.The main conclusions are: 1) the advertising-sales elasticity becomes up to 3000% higher than that obtained in econometric meta-studies; 2) a distinction must be made between maintenance and sales increase campaigns; 3) effectiveness should be pre-verified not primarily with simple pretest metrics, but from an efficiency forecasting model that includes at least the following content patterns capable of increasing sales: a) Granular segmentation. b) Brand rejuvenation. c) Serialization of messages. d) Dominate cultural territory. e) Presentation of the brand as a reducer of psychosocial tensions. f) Experiential advertising, promoter or echo of tactile and vicarious experiences. g) Influential message on the consumption mode.

Moving forward with the primate microbiome: Introduction to a special issue of the American Journal of Primatology.

Primate microbiome research is a quickly growing field with exciting potential for informing our understanding of primate biology, ecology, and evolution as well as host-microbe interactions more broadly. This introductory essay to a special section of the American Journal of Primatology provides a cross-sectional snapshot of current activity in these areas by briefly summarizing the diversity of contributed papers and their relationships to key themes in host-associated microbiome research. It then uses this survey as a foundation for consolidating a set of key research questions to broadly guide future research. It also argues for the importance of methods standardization to facilitate comparative analyses and the identification of generalizable patterns and relationships. While primatology will benefit greatly from the integration of microbial datasets, it is uniquely positioned to address important questions regarding microbiology and macro-ecology and evolution more generally. We are eager to see where the primate microbiome leads us.

Effects of climate, soil, forest structure and land use on the functional composition of the understorey in Italian forests

AbstractQuestionIn functional biogeography studies, generalizable patterns in the relationship between plant traits and the environment have yet to emerge. Local drivers (i.e., soil, land use, vegetation structure) can increase our understanding of the trait–environment relationship. What is the role of climate and local drivers in shaping abundance‐weighted trait patterns of forest understories at biogeographic scales?LocationItalian forests.MethodsWe selected 201 sites that are statistically representative for the heterogeneity of Italian forests across three biogeographic regions (alpine, continental, and mediterranean). Understorey vegetation was recorded for each site on an area of 400 m2, together with 25 environmental variables related to climate, soil, land use and forest structure. Specific leaf area (SLA), plant height (H) and seed mass (SM) were obtained from databases. Community‐weighted mean (CWM) values were calculated. Variance partitioning was used to identify the relative role of groups of environmental variables on the CWM of traits. Generalized Additive Models were used to assess the relationship between traits and single variables.ResultsClimate alone and climate–soil interactions explained the largest proportion of the variation of all the traits (13.7% to 22.8%). Temperature‐related factors as well as soil N and P availability were the climatic and edaphic explanatory variables most correlated to trait variation. Forest structure and land use accounted for a smaller percentage of the variation in traits. Land‐use factors alone were important in explaining only SLA variation.ConclusionsWhile climate plays a major role in trait–environment relationships in forest understories, our results highlighted the need to integrate at least soil properties as local drivers of trait variation in broad scale functional biogeography studies of these systems.

Patterns of Recovery From Pain After Cesarean Delivery

(Pain. 2018;159:2088–2096) There is a lack of knowledge about patterns of recovery from pain and its predictors after surgery. Often times, clinicians only witness pain experience if the patient returns for routine care after discharge, which overall limits the clinical ability to provide appropriate pain management. In order to establish clinically relevant, generalizable patterns of recovery, as well as identify predictors from preoperative and perioperative data, patients were followed for 2 months after elective cesarean delivery via text-messaging to assess daily pain scores.

Carnivore community response to anthropogenic landscape change: species-specificity foils generalizations

Human exploitation of landscapes result in widespread species range loss and spatial community redistribution. Reduced species occupancy for large ranging terrestrial carnivore communities in disturbed or fragmented landscapes is a common outcome but the underlying mechanisms are ambiguous and the complexity of interacting mechanisms often under-appreciated. To examine for similarity in spatial responses of carnivores to human-mediated landscape disturbance, we hypothesize common mechanism(s) to manifest at the community-level. To then incorporate a competitive surface, we evaluate the relative role interspecific interactions may play, where some species are benefited by altered habitat conditions. We deployed camera-trap arrays across a systematic grid-based study design to quantify carnivore occurrence. We tested hypotheses to understand spatial patterns of carnivore occurrence, in relation to biophysical and anthropogenic landscape factors, using multivariate analysis and species distribution models under an information-theoretic approach. Differential response was found within the carnivore community, with some species occurring more frequently in disturbed landscapes while others displayed landscape scale avoidance of more highly disturbed areas. Interspecific interactions played an additive role to human-mediated response by some carnivores—suggesting generalist, human-adapted species, exaggerate interference interactions for other more sensitive species. Generalizable patterns are highly sought as clues to consistent mechanisms effecting changes to spatial distributions, but evidence weighs heavily in favour of species-specificity in responses implicating mechanisms that likewise vary for each species. Our findings underscore the value of a trait-based and community-level approach to understanding and managing the effects of anthropogenic land-use change on vertebrate biodiversity.

The effect of healthy aging on within-speaker rhythmic variability: A case study on Noam Chomsky

Speech rhythm varies noticeably from language to language, and within the same language as a function of numerous linguistic, prosodic and speaker-dependent factors, among which is the speaker’s age. Cross-sectional studies comparing the acoustic characteristics of young and old voices have documented that healthy aging affects speech rhythm variability. This kind of studies, however, presents one fundamental limitation: They group together people with different life experiences, healthy conditions and aging rate. This makes it very difficult to disentangle the effect of aging from that of other factors when interpreting the rhythmic differences between younger and older adults. In the present paper, we overcame such difficulty by tracing rhythmic variability within one single individual longitudinally. We examined 5 public talks held by Noam Chomsky, from when he was 40 to when he was 89. Within-speaker rhythmic variability was quantified through a variety of rate measures (segment/consonant and vowel rate) and rhythmic metrics (%V, %Vn, nPVI-V, n-PVI-C). The results showed that physiological aging affected speech rate measures, but not the durational characteristics of vocalic and consonantal intervals. More longitudinal data from numerous speakers of the same language are necessary to identify generalizable patterns in age-related rhythmic variability.

Housing abandonment in shrinking cities of East Asia: Case study in Incheon, South Korea

Despite growing signs of urban shrinkage in countries such as Korea, Japan and China, few studies have examined the generalisable pattern of urban shrinkage and its relationship to the characteristics of housing abandonment in the East Asian context. This study explores five major paths that may explain the emergence of vacant houses in declining inner-city areas, based on empirical observations in the city of Incheon, South Korea. The paths are: (1) strong government-led new built-up area development plans (pull factor for population movement); (2) delay and cancellation of indiscriminate redevelopment projects (push factor for population movement); (3) initial poor development and concentration of substandard houses; (4) aging of the elderly population; and (5) the outflow of infrastructure and services. These paths, also found in Japan or China, are expected to be combined in a local context, leading to more serious housing abandonment. This study suggests that it is important to take appropriate countermeasures based on the identification of the paths causing vacant houses.

A strategy for early detection of response to chemotherapy drugs based on treatment-related changes in the metabolome.

We describe a biomarker-based approach to delivering chemotherapy that entails monitoring treatment changes in the circulating metabolome that reflect efficacy. In-vitro, multiple tumor cell lines were exposed to numerous chemotherapeutics. Supernatants were collected at baseline and 72 hours post treatment. MTT assays were used to quantify growth inhibition. Clinical samples were derived from a phase II clinical trial of second-line axitinib in patients with advanced hepatocellular carcinoma. Sera were collected at baseline and 2–4 weeks after treatment initiation. Response to therapy was estimated by CT scan at 8 weeks. Samples were analyzed by gas chromatography-mass spectrometry to identify metabolomic changes associated with response. In vitro, we found drug-specific and generalizable patterns of change in the extracellular metabolome accompany growth inhibition. A cell death signature was also identified. This approach was also applied to clinical samples. While the in vitro signatures were detectable in vivo, a more robust signal was identified clinically that appeared within 4 weeks of administering drug that distinguished individuals with a treatment response. These changes were extinguished as tumor growth resumed. Serial monitoring of the metabolome during chemotherapy is a means to follow treatment efficacy and emergence of resistance, informing the oncologist whether to modify treatment.

Human consciousness is supported by dynamic complex patterns of brain signal coordination.

Adopting the framework of brain dynamics as a cornerstone of human consciousness, we determined whether dynamic signal coordination provides specific and generalizable patterns pertaining to conscious and unconscious states after brain damage. A dynamic pattern of coordinated and anticoordinated functional magnetic resonance imaging signals characterized healthy individuals and minimally conscious patients. The brains of unresponsive patients showed primarily a pattern of low interareal phase coherence mainly mediated by structural connectivity, and had smaller chances to transition between patterns. The complex pattern was further corroborated in patients with covert cognition, who could perform neuroimaging mental imagery tasks, validating this pattern's implication in consciousness. Anesthesia increased the probability of the less complex pattern to equal levels, validating its implication in unconsciousness. Our results establish that consciousness rests on the brain's ability to sustain rich brain dynamics and pave the way for determining specific and generalizable fingerprints of conscious and unconscious states.

Changes in the spatial distribution of the under-five mortality rate: Small-area analysis of 122 DHS surveys in 262 subregions of 35 countries in Africa.

The under-five mortality rate (U5MR) is a critical and widely available population health indicator. Both the MDGs and SDGs define targets for improvement in the U5MR, and the SDGs require spatial disaggregation of indicators. We estimate trends in the U5MR for Admin-1 subnational areas using 122 DHS surveys in 35 countries in Africa and assess progress toward the MDG target reductions for each subnational region and each country as a whole. In each country, direct weighted estimates of the U5MR from each survey are calculated and combined into a single estimate for each Admin-1 region across five-year periods. Our method fully accounts for the sample design of each survey. The region-time-specific estimates are smoothed using a Bayesian, space-time model that produces more precise estimates (when compared to the direct estimates) at a one-year scale that are consistent with each other in both space and time. The resulting estimated distributions of the U5MR are summarized and used to assess subnational progress toward the MDG 4 target of two-thirds reduction in the U5MR during 1990–2015. Our space-time modeling approach is tractable and can be readily applied to a large collection of sample survey data. Subnational, regional spatial heterogeneity in the levels and trends in the U5MR vary considerably across Africa. There is no generalizable pattern between spatial heterogeneity and levels or trends in the U5MR. Subnational, small-area estimates of the U5MR: (i) identify subnational regions where interventions are still necessary and those where improvement is well under way; and (ii) countries where there is very little spatial variation and others where there are important differences between subregions in both levels and trends. More work is necessary to improve both the data sources and methods necessary to adequately measure subnational progress toward the SDG child survival targets.

Testing Darwin's Naturalization Conundrum using phylogenetic relationships: Generalizable patterns across disparate communities?

AbstractAimAlternative hypotheses of Darwin's Naturalization Conundrum (DNC) predict that the non‐native species that successfully establish within a community are those either more closely or more distantly related to the resident native species. Despite the increasing number of studies using phylogenetic data to test DNC and evaluate community assembly, it remains unknown whether phylogenetic relationships alone can be used to predict invasion susceptibility across communities differing environmentally and in disturbance history. In this study, we evaluate whether phylogenetic structure of diverse native communities predicts the occurrence of non‐native species and offers insight into community assembly.LocationEastern United States of America.MethodsWe examine multiple communities across a north–south transect of the eastern United States to test whether non‐native species richness and abundance are associated with phylogenetic diversity measures of the native community. We also test whether non‐native species are consistently closely or distantly related to native species using two approaches differing in phylogenetic scale and whether this differs with ecologically successful species.ResultsOur analyses did not unambiguously resolve DNC. Non‐native species richness and abundance decreased with increasing native species phylogenetic diversity. Within some communities, non‐native species were significantly more closely related to native species than expected by chance, and tended to be more often closely related to a native species than that native species was to other native relatives. When considering species abundance, only one community showed that ecologically successful non‐native species were closely related to resident species.Main conclusionsPhylogenetic relationships can reveal important details about community assembly in diverse ecological settings. However, given the multifaceted nature of community assembly, phylogenetic metrics alone have limited utility as a general predictive tool for community invasion. Our study highlights a need to incorporate additional types of data to better understand why some communities are more susceptible to non‐native species establishment.

Meta‐analysis of the effects of upstream land cover on stream recovery

Unpredictable or variable ecosystem recovery from disturbance presents a challenge to conservation, particularly as the scale of human disturbance continues to increase. Theory suggests land-cover and disturbance characteristics affect recovery, but individual studies of disturbance and recovery frequently struggle to uncover generalizable patterns because of high levels of site-specific variation. To understand how land-cover, disturbance type, and disturbance duration influence ecosystem recovery, we used studies documenting recovery of 50 streams to perform a global meta-analysis of stream recovery from disturbances that affect water quality (e.g., oil spill, fire, wastewater). We extracted upstream natural and urban land-cover percentages for each site and performed model selection and averaging to identify influences on recovery completeness. Most streams improved following the end of a disturbance (median 240% of disturbed condition) but did not recover fully to baseline predisturbance condition within the studied period (median study period 2years; median recovery 60% of baseline). Scale of disturbance in time and space did not predict recovery, but sites with higher percentages of upstream natural land cover had less complete recovery relative to sites with more urban or agricultural cover, possibly due to higher baseline conditions in these streams. Our findings suggest impacts to systems with low anthropogenic stress may be more irreversible than impacts to already modified systems. We call for more long-term evaluations of ecosystem response to disturbance and the inclusion of regional references and predisturbance reference conditions for comparison. A more thorough understanding of the role of the surrounding landscape in shaping stream response to disturbance can help managers calibrate expectations for recovery and prioritize protection.

Altered fire regimes cause long-term lichen diversity losses.

Many global ecosystems have undergone shifts in fire regimes in recent decades, such as changes in fire size, frequency, and/or severity. Recent research shows that increases in fire size, frequency, and severity can lead to long-persisting deforestation, but the consequences of shifting fire regimes for biodiversity of other vegetative organisms (such as understory plants, fungi, and lichens) remain poorly understood. Understanding lichen responses to wildfire is particularly important because lichens play crucial roles in nutrient cycling and supporting wildlife in many ecosystems. Lichen responses to fire have been little studied, and most previous research has been limited to small geographic areas (e.g. studies of a single fire), making it difficult to establish generalizable patterns. To investigate long-term effects of fire severity on lichen communities, we sampled epiphytic lichen communities in 104 study plots across California's greater Sierra Nevada region in areas that burned in five wildfires, ranging from 4 to 16years prior to sampling. The conifer forest ecosystems we studied have undergone a notable increase in fire severity in recent decades, and we sample across the full gradient of fire severity to infer how shifting fire regimes may influence landscape-level biodiversity. We find that low-severity fire has little to no effect on lichen communities. Areas that burned at moderate and high severities, however, have significantly and progressively lower lichen richness and abundance. Importantly, we observe very little postfire lichen recolonization on burned substrates even more than 15years after fire. Our multivariate model suggests that the hotter, drier microclimates that occur after fire removes forest canopies may prevent lichen reestablishment, meaning that lichens are not likely to recolonize until mature trees regenerate. These findings suggest that altered fire regimes may cause broad and long-persisting landscape-scale biodiversity losses that could ultimately impact multiple trophic levels.