Attention bias to emotional faces varies by IQ and anxiety in Williams syndrome

Individuals with Williams syndrome (WS) often experience significant anxiety. A promising approach to anxiety intervention has emerged from cognitive studies of attention bias to threat. To investigate the utility of this intervention in WS, this study examined attention bias to happy and angry faces in individuals with WS (N=46). Results showed a significant difference in attention bias patterns as a function of IQ and anxiety. Individuals with higher IQ or higher anxiety showed a significant bias toward angry, but not happy faces, whereas individuals with lower IQ or lower anxiety showed the opposite pattern. These results suggest that attention bias interventions to modify a threat bias may be most effectively targeted to anxious individuals with WS with relatively high IQ

A connectome and analysis of the adult Drosophila central brain.

The neural circuits responsible for animal behavior remain largely unknown. We summarize new methods and present the circuitry of a large fraction of the brain of the fruit fly Drosophila melanogaster. Improved methods include new procedures to prepare, image, align, segment, find synapses in, and proofread such large data sets. We define cell types, refine computational compartments, and provide an exhaustive atlas of cell examples and types, many of them novel. We provide detailed circuits consisting of neurons and their chemical synapses for most of the central brain. We make the data public and simplify access, reducing the effort needed to answer circuit questions, and provide procedures linking the neurons defined by our analysis with genetic reagents. Biologically, we examine distributions of connection strengths, neural motifs on different scales, electrical consequences of compartmentalization, and evidence that maximizing packing density is an important criterion in the evolution of the fly's brain

Increasing frailty is associated with higher prevalence and reduced recognition of delirium in older hospitalised inpatients: results of a multi-centre study

Purpose: Delirium is a neuropsychiatric disorder delineated by an acute change in cognition, attention, and consciousness. It is common, particularly in older adults, but poorly recognised. Frailty is the accumulation of deficits conferring an increased risk of adverse outcomes. We set out to determine how severity of frailty, as measured using the CFS, affected delirium rates, and recognition in hospitalised older people in the United Kingdom. Methods: Adults over 65 years were included in an observational multi-centre audit across UK hospitals, two prospective rounds, and one retrospective note review. Clinical Frailty Scale (CFS), delirium status, and 30-day outcomes were recorded. Results: The overall prevalence of delirium was 16.3% (483). Patients with delirium were more frail than patients without delirium (median CFS 6 vs 4). The risk of delirium was greater with increasing frailty [OR 2.9 (1.8–4.6) in CFS 4 vs 1–3; OR 12.4 (6.2–24.5) in CFS 8 vs 1–3]. Higher CFS was associated with reduced recognition of delirium (OR of 0.7 (0.3–1.9) in CFS 4 compared to 0.2 (0.1–0.7) in CFS 8). These risks were both independent of age and dementia. Conclusion: We have demonstrated an incremental increase in risk of delirium with increasing frailty. This has important clinical implications, suggesting that frailty may provide a more nuanced measure of vulnerability to delirium and poor outcomes. However, the most frail patients are least likely to have their delirium diagnosed and there is a significant lack of research into the underlying pathophysiology of both of these common geriatric syndromes

Phenotypic and Genotypic Heterogeneity in Autism Spectrum Disorder

Many genetic events can cause autism spectrum disorder (ASD). One specific genetic event involves deletion or duplication of approximately 50 genes, 22q11.2 Deletion/Duplication Syndrome, and leads to ASD in 10-40% of cases. Chapter 1 describes an effort to identify a critical region that confers ASD risk within those ~50 genes and reports that the Low Copy Repeat-A to B region shows the strongest association. Next, we explore ‘background genetics’ the remainder of the genome, almost entirely inherited from one’s parents - that interact with genetic events such as 22q11.2 deletions/duplications. Quantifying a heritable phenotype in one’s parents can indirectly quantify the phenotype encoded in one’s ‘background genetics.’ Heterogeneity among individuals with 22q11.2 Deletion/Duplication Syndrome, therefore, can be partially explained by heterogeneity among their parents’ phenotypes. An ideal heritable trait in which to explore this framework is one of the most studied and understood constructs in psychology: IQ. However, few studies measure parental IQ due to the prohibitive cost and inconvenience of current IQ assessments. Chapter 2 reports the optimal methods for using small sample sizes to develop and calibrate a large, computer adaptive item pool for a new IQ assessment. The method described can be used to develop an online IQ test to facilitate data collection from families and understanding of ‘background genetics.’ Chapter 3 tests whether ‘IQ’ holds the same meaning for children with autism when assessed with the Differential Ability Scales, 2nd Edition (DAS-II) compared to the normative, standardization sample and reports that while verbal and nonverbal reasoning scores do function similarly between groups, the spatial composite score does not. Taken together, these three chapters advance our understanding of IQ assessment in autism and provide one example of a genetics-first sample in which these insights can be applied. Given the importance of IQ for predicting outcomes and its heterogeneity within genetically homogenous samples, the rapidly evolving field of ASD behavioral genetics stands to benefit from an efficient, valid online IQ assessment of verbal and nonverbal reasoning, which hold the same meaning for individuals with autism and typical individuals on the commonly used DAS-II

Phenotypic and Genotypic Heterogeneity in Autism Spectrum Disorder

Many genetic events can cause autism spectrum disorder (ASD). One specific genetic event involves deletion or duplication of approximately 50 genes, 22q11.2 Deletion/Duplication Syndrome, and leads to ASD in 10-40% of cases. Chapter 1 describes an effort to identify a critical region that confers ASD risk within those ~50 genes and reports that the Low Copy Repeat-A to B region shows the strongest association. Next, we explore ‘background genetics’ the remainder of the genome, almost entirely inherited from one’s parents - that interact with genetic events such as 22q11.2 deletions/duplications. Quantifying a heritable phenotype in one’s parents can indirectly quantify the phenotype encoded in one’s ‘background genetics.’ Heterogeneity among individuals with 22q11.2 Deletion/Duplication Syndrome, therefore, can be partially explained by heterogeneity among their parents’ phenotypes. An ideal heritable trait in which to explore this framework is one of the most studied and understood constructs in psychology: IQ. However, few studies measure parental IQ due to the prohibitive cost and inconvenience of current IQ assessments. Chapter 2 reports the optimal methods for using small sample sizes to develop and calibrate a large, computer adaptive item pool for a new IQ assessment. The method described can be used to develop an online IQ test to facilitate data collection from families and understanding of ‘background genetics.’ Chapter 3 tests whether ‘IQ’ holds the same meaning for children with autism when assessed with the Differential Ability Scales, 2nd Edition (DAS-II) compared to the normative, standardization sample and reports that while verbal and nonverbal reasoning scores do function similarly between groups, the spatial composite score does not. Taken together, these three chapters advance our understanding of IQ assessment in autism and provide one example of a genetics-first sample in which these insights can be applied. Given the importance of IQ for predicting outcomes and its heterogeneity within genetically homogenous samples, the rapidly evolving field of ASD behavioral genetics stands to benefit from an efficient, valid online IQ assessment of verbal and nonverbal reasoning, which hold the same meaning for individuals with autism and typical individuals on the commonly used DAS-II

Assessing the conservation risk of Sphaerodactylus notatus, the U.S. herpetofaunal species most vulnerable to sea level rise

Keywords: Climate change; Florida; Fragmentation; Reptile; Reef gecko; Threatened species While climate change and sea level rise threaten species across the globe, species in low-lying coastal regions, such as South Florida, are projected to face particularly severe threats. One such species is the Florida reef gecko (Sphaerodactylus notatus), the only gecko native to the eastern U.S., and a highly understudied species that persists in heavily fragmented habitats of only three coastal Florida counties. To assess the conservation status of this species, we conducted surveys throughout South Florida to determine potential extirpations from historic localities and to delimit S. notatus' current distribution. We also estimated the level of threat S. notatus faces from sea level rise relative to other species by analyzing sea level risk of all herpetofauna in the U.S. We detected geckos in only 41% of sites with appropriate habitat, and in only 65% of historic localities. Geckos were only present within 1.2 km from the coast, and the minimum 2.2 m of sea level rise already expected based on current carbon emissions will place 85% of suitable S. notatus habitat under water. Our findings were used to update the conservation risk of S. notatus according to IUCN and Florida guidelines for listing threatened and endangered species, and suggest this species now fits the criteria to warrant listing. In comparison to all other U.S. herpetofaunal species, we found that S. notatus is the most at risk from sea level rise due its fidelity to low-lying coastal habitats. Author Affiliation: (1) Department of Biology, University of Miami, 1301 Memorial Drive, 33146, Coral Gables, FL, USA (a) [email protected] Article History: Registration Date: 10/31/2020 Received Date: 04/01/2020 Accepted Date: 10/31/2020 Online Date: 11/07/2020 Byline:Academi

Protect or perish: Quantitative analysis of state‐level species protection supports preservation of the Endangered Species Act

To combat biodiversity loss in the United States, imperiled species are protected under the federal Endangered Species Act (ESA), which is currently threatened by political initiatives seeking to weaken it and potentially transfer substantial authority to the states. To assess the conservation capacity of current state laws, we conducted a quantitative analysis of imperiled species protection within all 50 states by compiling data on all state‐listed species, ESA‐listed species, and IUCN Red List species in each state. We found that currently 16% of ESA‐listed species and 52% of IUCN imperiled species are not protected by any state law, and if the ESA were repealed these numbers could increase to 73% of ESA‐listed species and 81% of IUCN imperiled species unprotected. Although protection varies widely among states, our results suggest that revoking the ESA would be highly detrimental to imperiled species conservation and recovery in the United States

Use of standardized methods to improve extinction‐risk classification

Standardized classification methods based on quantifiable risk metrics are critical for evaluating extinction threats because they increase objectivity, consistency, and transparency of listing decisions. Yet, in the United States, neither federal nor state agencies use standardized methods for listing species for legal protection, which could put listing decisions at odds with the magnitude of the risk. We used a recently developed set of quantitative risk metrics for California herpetofauna as a case study to highlight discrepancies in listing decisions made without standardized methods. We also combined such quantitative metrics with classification tree analysis to attempt to increase the transparency of previous listing decisions by identifying the criteria that had inherently been given the most weight. Federally listed herpetofauna in California scored significantly higher on the risk‐metric spectrum than those not federally listed, whereas state‐listed species did not score any higher than species that were not state listed. Based on classification trees, state endemism was the most important predictor of listing status at the state level and distribution trend (decline in a species’ range size) and population trend (decline in a species’ abundance at localized sites) were the most important predictors at the federal level. Our results emphasize the need for governing bodies to adopt standardized methods for assessing conservation risk that are based on quantitative criteria. Such methods allow decision makers to identify criteria inherently given the most weight in determining listing status, thus increasing the transparency of previous listing decisions, and produce an unbiased comparison of conservation threat across all species to promote consistency, efficiency, and effectiveness of the listing process. Article impact statement: Using standardized, quantitative methods to assess extinction risk can improve listing decisions by increasing consistency and transparency Uso de Métodos Estandarizados para Mejorar la Clasificación del Riesgo de Extinción Resumen Los métodos estandarizados de clasificación basados en medidas cuantificables del riesgo de extinción son sumamente importantes para evaluar las amenazas de extinción ya que incrementan la objetividad, consistencia y transparencia de las decisiones de listado. Aún así, en los Estados Unidos, ni las agencias federales ni las estatales usan métodos estandarizados para enlistar a las especies para su protección legal, lo que podría poner en discrepancia a las decisiones de listado con la magnitud del riesgo. Usamos un conjunto de medidas cuantitativas del riesgo, desarrollado recientemente para la herpetofauna de California, como un estudio de caso que nos permitiera resaltar las discrepancias en las decisiones de listado hechas sin métodos estandarizados. También combinamos dichas medidas cuantitativas con un análisis de árbol de clasificación para intentar incrementar la transparencia de las decisiones de listado previas al identificar los criterios a los cuales se les había otorgado mayor peso inherentemente. La herpetofauna de California que se encontraba enlistada a nivel federal tuvo un puntaje significativamente más alto en el espectro de la medida del riesgo que aquellas especies que no estaban enlistadas, mientras que las especies enlistadas a nivel estatal no tuvieron un puntaje más alto que aquellas especies que no estaban enlistadas a nivel estatal. Con base en los árboles de clasificación, el endemismo estatal fue el indicador más importante del estado de listado a nivel estatal y tanto la tendencia de distribución (declinación del tamaño de la extensión de una especie) y como la tendencia poblacional (declinación de la abundancia de una especie en sitios localizados) fueron los indicadores más importantes a nivel federal. Nuestros resultados enfatizan la necesidad que tienen los cuerpos de gobierno de adoptar los métodos estandarizados que están basados en criterios cuantitativos para la evaluación del riesgo de conservación. Dichos métodos permiten que quienes toman las decisiones identifiquen los criterios a los cuales se les otorga inherentemente el mayor peso al determinar el estado de listado, lo que incrementa la transparencia de las decisiones previas de listado, y produce una comparación sin sesgos de la amenaza de conservación en todas las especies para promover la regularidad, eficiencia y efectividad de los procesos de listado. 摘要 基于定量风险指标的标准化分类方法可以提高濒危物种名录确定的客观性、一致性和透明度, 因而对评估物种的灭绝风险十分重要。然而, 在美国, 无论是联邦机构还是州立机构, 都没有使用标准化方法来确定法律保护的濒危物种, 这可能会导致濒危物种名录决策与物种面临的灭绝风险程度不相一致。我们以最近开发的一套美国加州爬行动物区系定量风险指标为例, 展示了标准化方法的使用与否在濒危物种名录确定中产生的差异。我们还将这些定量指标与分类树分析相结合, 试图通过找出之前的确定方法中占权重最大的指标来增加决策的透明度。被联邦政府列入名录的加州爬行动物的风险指标谱得分明显高于那些没有列入名录的物种, 而州政府列入名录的物种得分却并不比没有列入的物种高。分类树结果还显示, 州级濒危等级最重要的预测因子为州级特有性, 而在联邦一级最重要的预测因子则是分布趋势 (物种分布范围的缩小) 和种群趋势 (局部地区物种丰度的下降) 。我们的研究结果突出表明管理机构应采用基于定量指标的标准化方法来评估保护风险。这些方法可以帮助决策者找到濒危等级确定中最重要的指标, 从而增加已有确定方法的透明度, 还可以通过公正地比较所有物种面临的保护威胁, 以提升濒危物种名录确定过程中的一致性、效率和效果。【翻译: 胡怡思; 审校: 聂永刚