Risk of bias in prognostic models of hospital-induced delirium for medical-surgical units: A systematic review.

PURPOSE: The purpose of this systematic review was to assess risk of bias in existing prognostic models of hospital-induced delirium for medical-surgical units. METHODS: APA PsycInfo, CINAHL, MEDLINE, and Web of Science Core Collection were searched on July 8, 2022, to identify original studies which developed and validated prognostic models of hospital-induced delirium for adult patients who were hospitalized in medical-surgical units. The Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies was used for data extraction. The Prediction Model Risk of Bias Assessment Tool was used to assess risk of bias. Risk of bias was assessed across four domains: participants, predictors, outcome, and analysis. RESULTS: Thirteen studies were included in the qualitative synthesis, including ten model development and validation studies and three model validation only studies. The methods in all of the studies were rated to be at high overall risk of bias. The methods of statistical analysis were the greatest source of bias. External validity of models in the included studies was tested at low levels of transportability. CONCLUSIONS: Our findings highlight the ongoing scientific challenge of developing a valid prognostic model of hospital-induced delirium for medical-surgical units to tailor preventive interventions to patients who are at high risk of this iatrogenic condition. With limited knowledge about generalizable prognosis of hospital-induced delirium in medical-surgical units, existing prognostic models should be used with caution when creating clinical practice policies. Future research protocols must include robust study designs which take into account the perspectives of clinicians to identify and validate risk factors of hospital-induced delirium for accurate and generalizable prognosis in medical-surgical units.

Molluscan phylogenomics requires strategically selected genomes.

The extraordinary diversity in molluscan body plans, and the genomic mechanisms that enable it, remains one of the great questions of evolution. The eight distinct living taxonomic classes of molluscs are each unambiguously monophyletic; however, significant controversy remains about the phylogenetic relationships among those eight branches. Molluscs are the second-largest animal phylum, with over 100 000 living species with broad biological, economic and medical interest. To date, only around 53 genome assemblies have been accessioned to NCBI GenBank covering only four of the eight living molluscan classes. Furthermore, the molluscan taxa where partial or whole-genome assemblies are available are often aberrantly fast evolving or recently derived lineages. Characteristic adaptations provide interesting targets for whole-genome projects, in animals like the scaly-foot snail or octopus, but without basal-branching lineages for comparison, the context of recently derived features cannot be assessed. The currently available genomes also create a non-optimal set of taxa for resolving deeper phylogenetic branches: they are a small sample representing a large group, and those that are available come primarily from a rarefied pool. Thoughtful selection of taxa for future projects should focus on the blank areas of the molluscan tree, which are ripe with opportunities to delve into peculiarities of genome evolution, and reveal the biology and evolutionary history of molluscs. This article is part of the Theo Murphy meeting issue 'Molluscan genomics: broad insights and future directions for a neglected phylum'.

Identification of important factors in an inpatient fall risk prediction model to improve the quality of care using EHR and electronic administrative data: A machine-learning approach.

BACKGROUND: Inpatient falls, many resulting in injury or death, are a serious problem in hospital settings. Existing falls risk assessment tools, such as the Morse Fall Scale, give a risk score based on a set of factors, but don't necessarily signal which factors are most important for predicting falls. Artificial intelligence (AI) methods provide an opportunity to improve predictive performance while also identifying the most important risk factors associated with hospital-acquired falls. We can glean insight into these risk factors by applying classification tree, bagging, random forest, and adaptive boosting methods applied to Electronic Health Record (EHR) data. OBJECTIVE: The purpose of this study was to use tree-based machine learning methods to determine the most important predictors of inpatient falls, while also validating each via cross-validation. MATERIALS AND METHODS: A case-control study was designed using EHR and electronic administrative data collected between January 1, 2013 to October 31, 2013 in 14 medical surgical units. The data contained 38 predictor variables which comprised of patient characteristics, admission information, assessment information, clinical data, and organizational characteristics. Classification tree, bagging, random forest, and adaptive boosting methods were used to identify the most important factors of inpatient fall-risk through variable importance measures. Sensitivity, specificity, and area under the ROC curve were computed via ten-fold cross validation and compared via pairwise t-tests. These methods were also compared to a univariate logistic regression of the Morse Fall Scale total score. RESULTS: In terms of AUROC, bagging (0.89), random forest (0.90), and boosting (0.89) all outperformed the Morse Fall Scale (0.86) and the classification tree (0.85), but no differences were measured between bagging, random forest, and adaptive boosting, at a p-value of 0.05. History of Falls, Age, Morse Fall Scale total score, quality of gait, unit type, mental status, and number of high fall risk increasing drugs (FRIDs) were considered the most important features for predicting inpatient fall risk. CONCLUSIONS: Machine learning methods have the potential to identify the most relevant and novel factors for the detection of hospitalized patients at risk of falling, which would improve the quality of patient care, and to more fully support healthcare provider and organizational leadership decision-making. Nurses would be able to enhance their judgement to caring for patients at risk for falls. Our study may also serve as a reference for the development of AI-based prediction models of other iatrogenic conditions. To our knowledge, this is the first study to report the importance of patient, clinical, and organizational features based on the use of AI approaches.

Protocol for the Development of a Behavioral Family Lifestyle Intervention Supported by Mobile Health to Improve Weight Self-Management in Children With Asthma and Obesity.

BACKGROUND: Asthma is the most common chronic childhood illness and is a leading cause of emergency department visits in the United States. Obesity increases the risk of poor health outcomes, reduced quality of life, and increased health care expenditures among youth with asthma. Weight loss is crucial for improving asthma outcomes in children with obesity. Our study team developed the Childhood Health and Asthma Management Program (CHAMP), a 16-session behavioral family lifestyle intervention (BFI) for school-age children with asthma and obesity and evaluated CHAMP in a randomized controlled trial compared with attention control. There were medium effect sizes favoring CHAMP for changes in body mass index z-scores, asthma control, and lung function among completers (ie, those who attended ≥9 of 16 sessions). Despite high rates of satisfaction reported by families, attendance and trial attrition were suboptimal, which raised concerns regarding the feasibility of CHAMP. Qualitative feedback from participants indicated 3 areas for refinement: (1) a less burdensome intervention modality, (2) a more individually tailored intervention experience, and (3) that interventionists can better answer health-related questions. OBJECTIVE: We propose to improve upon our pilot intervention by developing the Mobile Childhood Health and Asthma Management Program (mCHAMP), a nurse-delivered BFI, delivered to individual families, and supported by a mobile health (mHealth) app. This study aims to (1) identify structural components of mCHAMP and (2) develop and test the usability of our mCHAMP app. METHODS: Participants will be recruited from an outpatient pediatric pulmonary clinic. We will identify the structural components of mCHAMP by conducting a needs assessment with parents of children with asthma and obesity. Subsequently, we will develop and test our mCHAMP app using an iterative process that includes usability testing with target users and pediatric nurses. RESULTS: This study was funded in 2018; 13 parents of children with asthma and obesity participated in the needs assessment. Preliminary themes from focus groups and individual meetings included barriers to engaging in health-promoting behaviors, perceived relationships between asthma and obesity, facilitators to behavior change, and intervention preferences. Participatory design sessions and usability testing are expected to conclude in late 2019. CONCLUSIONS: Outcomes from this study are expected to include an mHealth app designed with direct participation from the target audience and usability data from stakeholders as well as potential end users. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/13549.

A data-driven and practice-based approach to identify risk factors associated with hospital-acquired falls: Applying manual and semi- and fully-automated methods.

BACKGROUND AND PURPOSE: Electronic health record (EHR) data provides opportunities for new approaches to identify risk factors associated with iatrogenic conditions, such as hospital-acquired falls. There is a critical need to validate and translate prediction models that support fall prevention clinical decision-making in hospitals. The purpose of this study was to explore a combined data-driven and practice-based approach to identify risk factors associated with falls. PROCEDURES: We conducted an observational case-control study of EHR data from January 1, 2013 to October 31, 2013 from 14 medical-surgical units of a tertiary referral teaching hospital. Patients aged 21 or older admitted to medical surgical units were included in the study. Manual and semi- and fully-automated methods were used to identify fall risk factors across four prediction models. Sensitivity, specificity, and the Area under the Receiver Operating Characteristic (AUROC) curve were calculated for all models using 10-fold cross validation. FINDINGS: We confirmed the significance of a set of valid fall risk factors (i.e., age, gender, fall risk assessment, history of falling, mental status, mobility, and confusion) and identified set of new risk factors (i.e., # of fall risk increasing drugs, hemoglobin level, physical therapy initiation, Charlson Comorbity Index, nurse skill mix, and registered nurse staffing ratio) based on the most precise prediction approach, namely stepwise regression. CONCLUSIONS: The use of semi- and fully-automated approaches with expert clinical knowledge over expert or data-driven only approaches can significantly improve identifying patient, clinical, and organizational risk factors of iatrogenic conditions, including hospital-acquired falls.

Cell surface proteoglycan-mediated uptake and accumulation of the Alzheimer's disease peptide Aß(1-42).

Proteoglycans (PGs) have been found in Alzheimer's disease amyloid-ß (Aß) plaques and their glycosaminoglycan chains reportedly influence Aß aggregation, neurotoxicity and intracellular accumulation in cell and animal models, but their exact pathophysiological role(s) remain unclear. We have studied the cellular uptake of fluorescently labelled Aß(1-42) and Aß(1-40) peptides in normal CHO cells (K1) and the mutant cell line (pgsA-745) which lacks all protein-attached heparan and chondroitin sulfate chains. After 24 h of incubation, CHO-K1 accumulates more Aß(1-42) and Aß(1-40) compared with CHO-pgsA-745, consistent with the suggested role of PGs in Aß uptake. However, after short incubation times (≤3 h) there was no difference; moreover, the time evolution of Aß(1-42) accumulation in CHO-K1 followed an unusual sigmoidal-like trend, indicating a possible involvement of PG-mediated peptide aggregation in Aß endocytosis. Neither Aß(1-42) nor Aß(1-40) could stimulate uptake of a 10 kDa dextran (a general endocytosis marker) suggesting that Aß-induced upregulation of endocytosis does not occur. CHO-K1 cells contained a higher number of Aß(1-42)-positive vesicles, but the intensity difference per vesicle was only marginal suggesting that the superior accumulation of Aß(1-42) stems from a higher number of endocytic events. FRET imaging support that intracellular Aß(1-42) is aggregated in both cell types. We also report that CHO-pgsA-745 cells perform less endocytosis than CHO-K1 and, albeit this does not explain their difference in Aß internalisation, we discuss a general method for data compensation. Altogether, this study contributes new insights into the mechanisms of PG-mediated Aß uptake that may be relevant for our understanding of their role in AD pathology.

Co-occurrence of ecologically similar species of Hawaiian spiders reveals critical early phase of adaptive radiation.

BACKGROUND: The processes through which populations originate and diversify ecologically in the initial stages of adaptive radiation are little understood because we lack information on critical steps of early divergence. A key question is, at what point do closely related species interact, setting the stage for competition and ecological specialization? The Hawaiian Islands provide an ideal system to explore the early stages of adaptive radiation because the islands span ages from 0.5-5 Mya. Hawaiian spiders in the genus Tetragnatha have undergone adaptive radiation, with one lineage ("spiny legs") showing four different ecomorphs (green, maroon, large brown, small brown); one representative of each ecomorph is generally found at any site on the older islands. Given that the early stages of adaptive radiation are characterized by allopatric divergence between populations of the same ecomorph, the question is, what are the steps towards subsequent co-occurrence of different ecomorphs? Using a transcriptome-based exon capture approach, we focus on early divergence among close relatives of the green ecomorph to understand processes associated with co-occurrence within the same ecomorph at the early stages of adaptive radiation. RESULTS: The major outcomes from the current study are first that closely related species within the same green ecomorph of spiny leg Tetragnatha co-occur on the same single volcano on East Maui, and second that there is no evidence of genetic admixture between these ecologically equivalent species. Further, that multiple genetic lineages exist on a single volcano on Maui suggests that there are no inherent dispersal barriers and that the observed limited distribution of taxa reflects competitive exclusion. CONCLUSIONS: The observation of co-occurrence of ecologically equivalent species on the young volcano of Maui provides a missing link in the process of adaptive radiation between the point when recently divergent species of the same ecomorph occur in allopatry, to the point where different ecomorphs co-occur at a site, as found throughout the older islands. More importantly, the ability of close relatives of the same ecomorph to interact, without admixture, may provide the conditions necessary for ecological divergence and independent evolution of ecomorphs associated with adaptive radiation.

Twelve thousand recent patellogastropods from a northeastern Pacific latitudinal gradient.

Body size distributions can vary widely among communities, with important implications for ecological dynamics, energetics, and evolutionary history. Here we present a dataset of body size and shape for 12,035 extant Patellogastropoda (true limpet) specimens from the collections of the University of California Museum of Paleontology, compiled using a novel high-throughput morphometric imaging method. These specimens were collected over the past 150 years at 355 localities along a latitudinal gradient ranging from Alaska to Baja California, Mexico and are presented here with individual images, 2D outline coordinates, and 2D measurements of body size and shape. This dataset provides a resource for assemblage-scale macroecological questions and documents the size and diversity of recent patellogastropods in the northeastern Pacific.

Lipid membranes catalyse the fibril formation of the amyloid-ß (1-42) peptide through lipid-fibril interactions that reinforce secondary pathways.

Alzheimer's disease is associated with the aggregation of amyloid-ß (Aß) peptides into oligomers and fibrils. We have explored how model lipid membranes modulate the rate and mechanisms of Aß(1-42) self-assembly, in order to shed light on how this pathological reaction may occur in the lipid-rich environments that the peptide encounters in the brain. Using a combination of in vitro biophysical experiments and theoretical approaches, we show that zwitterionic DOPC lipid vesicles accelerate the Aß(1-42) fibril growth rate by interacting specifically with the growing fibrils. We probe this interaction with help of a purpose-developed Förster resonance energy transfer assay that monitors the proximity between a fibril-specific dye and fluorescent lipids in the lipid vesicle membrane. To further rationalise these findings we use mathematical models to fit the aggregation kinetics of Aß(1-42) and find that lipid vesicles alter specific mechanistic steps in the aggregation reaction; they augment monomer-dependent secondary nucleation at the surface of existing fibrils and facilitate monomer-independent catalytic processes consistent with fibril fragmentation. We further show that DOPC vesicles have no effect on primary nucleation. This finding is consistent with experiments showing that Aß(1-42) monomers do not directly bind to the lipid bilayer. Taken together, our results show that plain lipid membranes with charge and composition that is representative of outer cell membranes can significantly augment autocatalytic steps in the self-assembly of Aß(1-42) into fibrils. This new insight suggests that strategies to reduce fibril-lipid interactions in the brain may have therapeutic value.

Binding of Thioflavin-T to Amyloid Fibrils Leads to Fluorescence Self-Quenching and Fibril Compaction.

Thioflavin-T binds to and detects amyloid fibrils via fluorescence enhancement. Using a combination of linear dichroism and fluorescence spectroscopies, we report that the relation between the emission intensity and binding of thioflavin-T to insulin fibrils is nonlinear and discuss this in relation to its use in kinetic assays. We demonstrate, from fluorescence lifetime recordings, that the nonlinearity is due to thioflavin-T being sensitive to self-quenching. In addition, thioflavin-T can induce fibril compaction but not alter fibril structure. Our work underscores the photophysical complexity of thioflavin-T and the necessity of calibrating the linear range of its emission response for quantitative in vitro studies.

Detection of amyloid-ß fibrils using the DNA-intercalating dye YOYO-1: Binding mode and fibril formation kinetics.

Identification of the chemical and biological properties of amyloid fibrils is important for understanding their roles in human diseases and to clarify the mechanisms that govern their formation. In pursuit of these goals, small molecule fluorescent dyes have received increasing attention as probes of amyloid conformations. In this study, we report on the ability of YOYO-1, a homodimeric derivative of oxazole yellow, to detect fibrils formed by the Alzheimer's disease related Aß(1-42) peptide. We find that YOYO-1 binds to Aß(1-42) fibrils with the long axes of its oxazole yellow moieties parallel to the fibril axis, resulting in a 200x emission enhancement; a result that shows that YOYO-1 is a sensitive amyloid probe. Further, YOYO-1 exhibits characteristic absorption shifts upon binding to the Aß(1-42) fibrils that we attribute to a self-stacking to non-stacking transition in its homodimer configuration; herein we show how this phenomenon can be exploited to estimate the degree of dye binding. Furthermore, we show that YOYO-1 can be used to monitor the kinetics of amyloid formation reactions. Taken together, our results show that YOYO-1 is a sensitive amyloid probe that can operate with both absorption and fluorescence read-outs, and this suggests that this commercially available dye could become a useful complement to thioflavin-T for in vitro amyloid-sensing applications.

A neurophylogenetic approach provides new insight to the evolution of Scaphopoda.

The position of scaphopods in molluscan phylogeny remains singularly contentious, with several sister relationships supported by morphological and phylogenomic data: Scaphopoda + Bivalvia (Diasoma), Scaphopoda + Cephalopoda (Variopoda), and Scaphopoda + Gastropoda. Nervous system architecture has contributed significant insights to reconstructing phylogeny in the Mollusca and other invertebrate groups, but a modern neurophylogenetic approach has not been applied to molluscs, hampered by a lack of clearly defined homologous characters that can be unequivocally compared across the radical body plan disparity among the living clades. We present the first three-dimensional reconstruction of the anterior nervous system of a scaphopod, Rhabdus rectius, using histological tomography. We also describe a new putative sensory organ, a paired and pigmented sensory mantle slit. This structure is restricted to our study species and not a general feature of scaphopods, but it forms an integral part of the description of the nervous system in R. rectius. It also highlights the potential utility of neuro-anatomical characters for multiple levels of phylogenetic inference beyond this study. This potential has not previously been exploited for the thorny problem of molluscan phylogeny. The neuroanatomy of scaphopods demonstrates a highly derived architecture that shares a number of key characters with the cephalopod nervous system, and supports a Scaphopoda + Cephalopoda grouping.

Marine extinction risk shaped by trait-environment interactions over 500 million years.

Perhaps the most pressing issue in predicting biotic responses to present and future global change is understanding how environmental factors shape the relationship between ecological traits and extinction risk. The fossil record provides millions of years of insight into how extinction selectivity (i.e., differential extinction risk) is shaped by interactions between ecological traits and environmental conditions. Numerous paleontological studies have examined trait-based extinction selectivity; however, the extent to which these patterns are shaped by environmental conditions is poorly understood due to a lack of quantitative synthesis across studies. We conducted a meta-analysis of published studies on fossil marine bivalves and gastropods that span 458 million years to uncover how global environmental and geochemical changes covary with trait-based extinction selectivity. We focused on geographic range size and life habit (i.e., infaunal vs. epifaunal), two of the most important and commonly examined predictors of extinction selectivity. We used geochemical proxies related to global climate, as well as indicators of ocean acidification, to infer average global environmental conditions. Life-habit selectivity is weakly dependent on environmental conditions, with infaunal species relatively buffered from extinction during warmer climate states. In contrast, the odds of taxa with broad geographic ranges surviving an extinction (>2500 km for genera, >500 km for species) are on average three times greater than narrow-ranging taxa (estimate of odds ratio: 2.8, 95% confidence interval = 2.3-3.5), regardless of the prevailing global environmental conditions. The environmental independence of geographic range size extinction selectivity emphasizes the critical role of geographic range size in setting conservation priorities.

Extinctions. Paleontological baselines for evaluating extinction risk in the modern oceans.

Marine taxa are threatened by anthropogenic impacts, but knowledge of their extinction vulnerabilities is limited. The fossil record provides rich information on past extinctions that can help predict biotic responses. We show that over 23 million years, taxonomic membership and geographic range size consistently explain a large proportion of extinction risk variation in six major taxonomic groups. We assess intrinsic risk-extinction risk predicted by paleontologically calibrated models-for modern genera in these groups. Mapping the geographic distribution of these genera identifies coastal biogeographic provinces where fauna with high intrinsic risk are strongly affected by human activity or climate change. Such regions are disproportionately in the tropics, raising the possibility that these ecosystems may be particularly vulnerable to future extinctions. Intrinsic risk provides a prehuman baseline for considering current threats to marine biodiversity.

Steady-state and time-resolved Thioflavin-T fluorescence can report on morphological differences in amyloid fibrils formed by Aß(1-40) and Aß(1-42).

Thioflavin-T (ThT) is one of the most commonly used dyes for amyloid detection, but the origin of its fluorescence enhancement is not fully understood. Herein we have characterised the ThT fluorescence response upon binding to the Aß(1-40) and Aß(1-42) variants of the Alzheimer's-related peptide amyloid-ß, in order to explore how the photophysical properties of this dye relates to structural and morphological properties of two amyloid fibril types formed by peptides with a high degree of sequence homology. We show that the steady-state ThT fluorescence is 1.7 times more intense with Aß(1-40) compared to Aß(1-42) fibrils in concentration matched samples prepared under quiescent conditions. By measuring the excited state lifetime of bound ThT, we also demonstrate a distinct difference between the two fibril isoforms, with Aß(1-42) fibrils producing a longer ThT fluorescence lifetime compared to Aß(1-40). The substantial steady-state intensity difference is therefore not explained by differences in fluorescence quantum yield. Further, we find that the ThT fluorescence intensity, but not the fluorescence lifetime, is dependent on the fibril preparation method (quiescent versus agitated conditions). We therefore propose that the fluorescence lifetime is inherent to each isoform and sensitively reports on fibril microstructure in the protofilament whereas the total fluorescence intensity relates to the amount of exposed ß-sheet in the mature Aß fibrils and hence to differences in their morphology. Our results highlight the complexity of ThT fluorescence, and demonstrate its extended use in amyloid fibril characterisation.

Consensus and confusion in molluscan trees: evaluating morphological and molecular phylogenies.

Mollusks are the most morphologically disparate living animal phylum, they have diversified into all habitats, and have a deep fossil record. Monophyly and identity of their eight living classes is undisputed, but relationships between these groups and patterns of their early radiation have remained elusive. Arguments about traditional morphological phylogeny focus on a small number of topological concepts but often without regard to proximity of the individual classes. In contrast, molecular studies have proposed a number of radically different, inherently contradictory, and controversial sister relationships. Here, we assembled a data set of 42 unique published trees describing molluscan interrelationships. We used these data to ask several questions about the state of resolution of molluscan phylogeny compared with a null model of the variation possible in random trees constructed from a monophyletic assemblage of eight terminals. Although 27 different unique trees have been proposed from morphological inference, the majority of these are not statistically different from each other. Within the available molecular topologies, only four studies to date have included the deep sea class Monoplacophora; but 36.4% of all trees are not significantly different. We also present supertrees derived from two data partitions and three methods, including all available molecular molluscan phylogenies, which will form the basis for future hypothesis testing. The supertrees presented here were not constructed to provide yet another hypothesis of molluscan relationships, but rather to algorithmically evaluate the relationships present in the disparate published topologies. Based on the totality of available evidence, certain patterns of relatedness among constituent taxa become clear. The internodal distance is consistently short between a few taxon pairs, particularly supporting the relatedness of Monoplacophora and the chitons, Polyplacophora. Other taxon pairs are rarely or never found in close proximity, such as the vermiform Caudofoveata and Bivalvia. Our results have specific utility for guiding constructive research planning to better test relationships in Mollusca as well as other problematic groups. Taxa with consistently proximate relationships should be the focus of a combined approach in a concerted assessment of potential genetic and anatomical homology, whereas unequivocally distant taxa will make the most constructive choices for exemplar selection in higher level phylogenomic analyses.

Insights into bilaterian evolution from three spiralian genomes.

Current genomic perspectives on animal diversity neglect two prominent phyla, the molluscs and annelids, that together account for nearly one-third of known marine species and are important both ecologically and as experimental systems in classical embryology. Here we describe the draft genomes of the owl limpet (Lottia gigantea), a marine polychaete (Capitella teleta) and a freshwater leech (Helobdella robusta), and compare them with other animal genomes to investigate the origin and diversification of bilaterians from a genomic perspective. We find that the genome organization, gene structure and functional content of these species are more similar to those of some invertebrate deuterostome genomes (for example, amphioxus and sea urchin) than those of other protostomes that have been sequenced to date (flies, nematodes and flatworms). The conservation of these genomic features enables us to expand the inventory of genes present in the last common bilaterian ancestor, establish the tripartite diversification of bilaterians using multiple genomic characteristics and identify ancient conserved long- and short-range genetic linkages across metazoans. Superimposed on this broadly conserved pan-bilaterian background we find examples of lineage-specific genome evolution, including varying rates of rearrangement, intron gain and loss, expansions and contractions of gene families, and the evolution of clade-specific genes that produce the unique content of each genome.

Extinctions in ancient and modern seas.

In the coming century, life in the ocean will be confronted with a suite of environmental conditions that have no analog in human history. Thus, there is an urgent need to determine which marine species will adapt and which will go extinct. Here, we review the growing literature on marine extinctions and extinction risk in the fossil, historical, and modern records to compare the patterns, drivers, and biological correlates of marine extinctions at different times in the past. Characterized by markedly different environmental states, some past periods share common features with predicted future scenarios. We highlight how the different records can be integrated to better understand and predict the impact of current and projected future environmental changes on extinction risk in the ocean.

The taxonomist - an endangered race. A practical proposal for its survival.

BACKGROUND: Taxonomy or biological systematics is the basic scientific discipline of biology, postulating hypotheses of identity and relationships, on which all other natural sciences dealing with organisms relies. However, the scientific contributions of taxonomists have been largely neglected when using species names in scientific publications by not citing the authority on which they are based. DISCUSSION: Consequences of this neglect is reduced recognition of the importance of taxonomy, which in turn results in diminished funding, lower interest from journals in publishing taxonomic research, and a reduced number of young scientists entering the field. This has lead to the so-called taxonomic impediment at a time when biodiversity studies are of critical importance.Here we emphasize a practical and obvious solution to this dilemma. We propose that whenever a species name is used, the author(s) of the species hypothesis be included and the original literature source cited, including taxonomic revisions and identification literature - nothing more than what is done for every other hypothesis or assumption included in a scientific publication. In addition, we postulate that journals primarily publishing taxonomic studies should be indexed in ISISM. SUMMARY: The proposal outlined above would make visible the true contribution of taxonomists within the scientific community, and would provide a more accurate assessment for funding agencies impact and importance of taxonomy, and help in the recruitment of young scientists into the field, thus helping to alleviate the taxonomic impediment. In addition, it would also make much of the biological literature more robust by reducing or alleviating taxonomic uncertainty.

Comparative analysis of chromosome counts infers three paleopolyploidies in the mollusca.

The study of paleopolyploidies requires the comparison of multiple whole genome sequences. If the branches of a phylogeny on which a whole-genome duplication (WGD) occurred could be identified before genome sequencing, taxa could be selected that provided a better assessment of that genome duplication. Here, we describe a likelihood model in which the number of chromosomes in a genome evolves according to a Markov process with one rate of chromosome duplication and loss that is proportional to the number of chromosomes in the genome and another stochastic rate at which every chromosome in the genome could duplicate in a single event. We compare the maximum likelihoods of a model in which the genome duplication rate varies to one in which it is fixed at zero using the Akaike information criterion, to determine if a model with WGDs is a good fit for the data. Once it has been determined that the data does fit the WGD model, we infer the phylogenetic position of paleopolyploidies by calculating the posterior probability that a WGD occurred on each branch of the taxon tree. Here, we apply this model to a molluscan tree represented by 124 taxa and infer three putative WGD events. In the Gastropoda, we identify a single branch within the Hypsogastropoda and one of two branches at the base of the Stylommatophora. We also identify one or two branches near the base of the Cephalopoda.