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Estimates of the spectrum and frequency of pathogenic variants in Parkinsons disease (PD) in different populations are currently limited and biased. Furthermore, although therapeutic modification of several genetic targets has reached the clinical trial stage, a major obstacle in conducting these trials is that PD patients are largely unaware of their genetic status and, therefore, cannot be recruited. Expanding the number of investigated PD-related genes and including genes related to disorders with overlapping clinical features in large, well-phenotyped PD patient groups is a prerequisite for capturing the full variant spectrum underlying PD and for stratifying and prioritizing patients for gene-targeted clinical trials. The Rostock Parkinsons disease (ROPAD) study is an observational clinical study aiming to determine the frequency and spectrum of genetic variants contributing to PD in a large international cohort. We investigated variants in 50 genes with either an established relevance for PD or possible phenotypic overlap in a group of 12 580 PD patients from 16 countries [62.3% male; 92.0% White; 27.0% positive family history (FH+), median age at onset (AAO) 59 years] using a next-generation sequencing panel. Altogether, in 1864 (14.8%) ROPAD participants (58.1% male; 91.0% White, 35.5% FH+, median AAO 55 years), a PD-relevant genetic test (PDGT) was positive based on GBA1 risk variants (10.4%) or pathogenic/likely pathogenic variants in LRRK2 (2.9%), PRKN (0.9%), SNCA (0.2%) or PINK1 (0.1%) or a combination of two genetic findings in two genes (∼0.2%). Of note, the adjusted positive PDGT fraction, i.e. the fraction of positive PDGTs per country weighted by the fraction of the population of the world that they represent, was 14.5%. Positive PDGTs were identified in 19.9% of patients with an AAO ≤ 50 years, in 19.5% of patients with FH+ and in 26.9% with an AAO ≤ 50 years and FH+. In comparison to the idiopathic PD group (6846 patients with benign variants), the positive PDGT group had a significantly lower AAO (4 years, P = 9 × 10-34). The probability of a positive PDGT decreased by 3% with every additional AAO year (P = 1 × 10-35). Female patients were 22% more likely to have a positive PDGT (P = 3 × 10-4), and for individuals with FH+ this likelihood was 55% higher (P = 1 × 10-14). About 0.8% of the ROPAD participants had positive genetic testing findings in parkinsonism-, dystonia/dyskinesia- or dementia-related genes. In the emerging era of gene-targeted PD clinical trials, our finding that ∼15% of patients harbour potentially actionable genetic variants offers an important prospect to affected individuals and their families and underlines the need for genetic testing in PD patients. Thus, the insights from the ROPAD study allow for data-driven, differential genetic counselling across the spectrum of different AAOs and family histories and promote a possible policy change in the application of genetic testing as a routine part of patient evaluation and care in PD.

Legacy effects describe the persistent, long-term impacts on an ecosystem following the removal of an abiotic or biotic feature. Redlining, a policy that codified racial segregation and disinvestment in minoritized neighborhoods, has produced legacy effects with profound impacts on urban ecosystem structure and health. These legacies have detrimentally impacted public health outcomes, socioeconomic stability, and environmental health. However, the collateral impacts of redlining on wildlife communities are uncertain. Here, we investigated whether faunal biodiversity was associated with redlining. We used home-owner loan corporation (HOLC) maps [grades A (i.e., "best" and "greenlined"), B, C, and D (i.e., "hazardous" and "redlined")] across four cities in California and contributory science data (iNaturalist) to estimate alpha and beta diversity across six clades (mammals, birds, insects, arachnids, reptiles, and amphibians) as a function of HOLC grade. We found that in greenlined neighborhoods, unique species were detected with less sampling effort, with redlined neighborhoods needing over 8,000 observations to detect the same number of unique species. Historically redlined neighborhoods had lower native and nonnative species richness compared to greenlined neighborhoods across each city, with disparities remaining at the clade level. Further, community composition (i.e., beta diversity) consistently differed among HOLC grades for all cities, including large differences in species assemblage observed between green and redlined neighborhoods. Our work spotlights the lasting effects of social injustices on the community ecology of cities, emphasizing that urban conservation and management efforts must incorporate an antiracist, justice-informed lens to improve biodiversity in urban environments.

While there is increasing recognition that social processes in cities like gentrification have ecological consequences, we lack nuanced understanding of the ways gentrification affects urban biodiversity. We analyzed a large camera trap dataset of mammals (>500 g) to evaluate how gentrification impacts species richness and community composition across 23 US cities. After controlling for the negative effect of impervious cover, gentrified parts of cities had the highest mammal species richness. Change in community composition was associated with gentrification in a few cities, which were mostly located along the West Coast. At the species level, roughly half (11 of 21 mammals) had higher occupancy in gentrified parts of a city, especially when impervious cover was low. Our results indicate that the impacts of gentrification extend to nonhuman animals, which provides further evidence that some aspects of nature in cities, such as wildlife, are chronically inaccessible to marginalized human populations.

As higher education diversifies, students from underrepresented groups find themselves on campuses unprepared to support them. Academic advising can cultivate belonging or reify" cultural mismatches" when students' norms do not match institutional norms. Leveraging interviews with Chinese international, Chinese American, and European American undergraduates and advisors, this study examines whether cultural mismatches in advising exist for Chinese diaspora students and, if so, on what fronts. Findings reveal cultural mismatches in definitions of autonomy; the amount of student voice expected in advising; valuation of exploration; emphasis on passion; and types of socioemotional support. This study yields important findings for advisors to improve the cultural responsiveness of their advising.

Historical policies have been shown to underpin environmental quality. In the 1930s, the federal Home Owners' Loan Corporation (HOLC) developed the most comprehensive archive of neighborhoods that would have been redlined by local lenders and the Federal Housing Administration, often applying racist criteria. Our study explored how redlining is associated with environmental quality across eight California cities. We integrated HOLC's graded maps [grades A (i.e., "best" and "greenlined"), B, C, and D (i.e., "hazardous" and "redlined")] with 10 environmental hazards using data from 2018 to 2021 to quantify the spatial overlap among redlined neighborhoods and environmental hazards. We found that formerly redlined neighborhoods have poorer environmental quality relative to those of other HOLC grades via higher pollution, more noise, less vegetation, and elevated temperatures. Additionally, we found that intraurban disparities were consistently worse for formerly redlined neighborhoods across environmental hazards, with redlined neighborhoods having higher pollution burdens (77% of redlined neighborhoods vs 18% of greenlined neighborhoods), more noise (72% vs 18%), less vegetation (86% vs 12%), and elevated temperature (72% vs 20%), than their respective city's average. Our findings highlight that redlining, a policy abolished in 1968, remains an environmental justice concern by shaping the environmental quality of Californian urban neighborhoods.

Data that influence policy and major investment decisions risk entrenching social and political inequities.

BACKGROUND: Varoglutamstat is a first-in-class, small molecule being investigated as a treatment for early Alzheimers disease (AD). It is an inhibitor of glutaminyl cyclase (QC), the enzyme that post-translationally modifies amyloid-β (Aβ) peptides into a toxic form of pyroglutamate Aβ (pGlu-Aβ) and iso-QC which post-translationally modifies cytokine monocyte chemoattractant protein-1 (CCL2) into neuroinflammatory pGlu-CCL2. Early phase clinical trials identified dose margins for safety and tolerability of varoglutamstat and biomarker data supporting its potential for clinical efficacy in early AD. OBJECTIVE: Present the scientific rationale of varoglutamstat in the treatment of early AD and the methodology of the VIVA-MIND (NCT03919162) trial, which uses a seamless phase 2A-2B design. Our review also includes other pharmacologic approaches to pGlu-Aβ. METHODS: Phase 2A of the VIVA-MIND trial will determine the highest dose of varoglutamstat that is safe and well tolerated with sufficient plasma exposure and a calculated target occupancy. Continuous safety evaluation using a pre-defined safety stopping boundary will help determine the highest tolerated dose that will carry forward into phase 2B. An interim futility analysis of cognitive function and electroencephalogram changes will be conducted to inform the decision of whether to proceed with phase 2B. Phase 2B will assess the efficacy and longer-term safety of the optimal selected phase 2A dose through 72 weeks of treatment. CONCLUSIONS: Varoglutamstat provides a unique dual mechanism of action addressing multiple pathogenic contributors to the disease cascade. VIVA-MIND provides a novel and efficient trial design to establish its optimal dosing, safety, tolerability, and efficacy in early AD.

Contributory science—including citizen and community science—allows scientists to leverage participant-generated data while providing an opportunity for engaging with local community members. Data yielded by participant-generated biodiversity platforms allow professional scientists to answer ecological and evolutionary questions across both geographic and temporal scales, which is incredibly valuable for conservation efforts. The data reported to contributory biodiversity platforms, such as eBird and iNaturalist, can be driven by social and ecological variables, leading to biased data. Though empirical work has highlighted the biases in contributory data, little work has articulated how biases arise in contributory data and the societal consequences of these biases. We present a conceptual framework illustrating how social and ecological variables create bias in contributory science data. In this framework, we present four filters—participation, detectability, sampling and preference—that ultimately shape the type and location of contributory biodiversity data. We leverage this framework to examine data from the largest contributory science platforms—eBird and iNaturalist—in St. Louis, Missouri, the United States, and discuss the potential consequences of biased data. Lastly, we conclude by providing several recommendations for researchers and institutions to move towards a more inclusive field. With these recommendations, we provide opportunities to ameliorate biases in contributory data and an opportunity to practice equitable biodiversity conservation. Read the free Plain Language Summary for this article on the Journal blog.

Abstract The growing use of artificial neural network (ANN) tools for computed tomography angiography (CTA) data analysis underscores the necessity for elevated data protection measures. We aimed to establish an automated defacing pipeline for CTA data. In this retrospective study, CTA data from multi-institutional cohorts were utilized to annotate facemasks (n = 100) and train an ANN model, subsequently tested on an external institution’s dataset (n = 50) and compared to a publicly available defacing algorithm. Face detection (MTCNN) and verification (FaceNet) networks were applied to measure the similarity between the original and defaced CTA images. Dice similarity coefficient (DSC), face detection probability, and face similarity measures were calculated to evaluate model performance. The CTA-DEFACE model effectively segmented soft face tissue in CTA data achieving a DSC of 0.94 ± 0.02 (mean ± standard deviation) on the test set. Our model was benchmarked against a publicly available defacing algorithm. After applying face detection and verification networks, our model showed substantially reduced face detection probability (p

Abstract Background Sequencing and annotating genomes of non-model organisms helps to understand genome architecture, the genetic processes underlying species traits, and how these genes have evolved in closely-related taxa, among many other biological processes. However, many metazoan groups, such as the extremely diverse molluscs, are still underrepresented in the number of sequenced and annotated genomes. Although sequencing techniques have recently improved in quality and quantity, molluscs are still neglected due to difficulties in applying standardized protocols for obtaining genomic data. Results In this study, we present the chromosome-level genome assembly and annotation of the sacoglossan sea slug species Elysia timida, known for its ability to store the chloroplasts of its food algae. In particular, by optimizing the long-read and chromosome conformation capture library preparations, the genome assembly was performed using PacBio HiFi and Arima HiC data. The scaffold and contig N50s, at 41.8 Mb and 1.92 Mb, respectively, are approximately 30-fold and fourfold higher compared to other published sacoglossan genome assemblies. Structural annotation resulted in 19,904 protein-coding genes, which are more contiguous and complete compared to publicly available annotations of Sacoglossa with respect to metazoan BUSCOs. We found no evidence for horizontal gene transfer (HGT), i.e. no photosynthetic genes encoded in the sacoglossan nucleus genome. However, we detected genes encoding polyketide synthases in E. timida, indicating that polypropionates are produced. HPLC–MS/MS analysis confirmed the presence of a large number of polypropionates, including known and yet uncharacterised compounds. Conclusions We can show that our methodological approach helps to obtain a high-quality genome assembly even for a "difficult-to-sequence" organism, which may facilitate genome sequencing in molluscs. This will enable a better understanding of complex biological processes in molluscs, such as functional kleptoplasty in Sacoglossa, by significantly improving the quality of genome assemblies and annotations.

Global change is increasing the frequency and severity of human-wildlife interactions by pushing people and wildlife into increasingly resource-limited shared spaces. To understand the dynamics of human-wildlife interactions and what may constitute human-wildlife coexistence in the Anthropocene, there is a critical need to explore the spatial, temporal, sociocultural and ecological variables that contribute to human-wildlife conflicts in urban areas. Due to their opportunistic foraging and behavioural flexibility, coyotes (Canis latrans) frequently interact with people in urban environments. San Francisco, California, USA hosts a very high density of coyotes, making it an excellent region for analysing urban human-coyote interactions and attitudes toward coyotes over time and space. We used a community-curated long-term data source from San Francisco Animal Care and Control to summarise a decade of coyote sightings and human-coyote interactions in San Francisco and to characterise spatiotemporal patterns of attitudes and interaction types in relation to housing density, socioeconomics, pollution and human vulnerability metrics, and green space availability. We found that human-coyote conflict reports have been significantly increasing over the past 5 years and that there were more conflicts during the coyote pup-rearing season (April–June), the dry season (June–September) and the COVID-19 pandemic. Conflict reports were also more likely to involve dogs and occur inside of parks, despite more overall sightings occurring outside of parks. Generalised linear mixed models revealed that conflicts were more likely to occur in places with higher vegetation greenness and median income. Meanwhile reported coyote boldness, hazing and human attitudes toward coyotes were also correlated with pollution burden and human population vulnerability indices. Synthesis and applications: Our results provide compelling evidence suggesting that human-coyote conflicts are intimately associated with social-ecological heterogeneities and time, emphasizing that the road to coexistence will require socially informed strategies. Additional long-term research articulating how the social-ecological drivers of conflict (e.g. human food subsidies, interactions with domestic species, climate-induced droughts, socioeconomic disparities, etc.) change over time will be essential in building adaptive management efforts that effectively mitigate future conflicts from occurring. Read the free Plain Language Summary for this article on the Journal blog.

Abstract: The behavioral mechanisms by which urban wildlife adapt to urban landscapes and disturbances within these environments are poorly understood. Such understanding can be important for wildlife managers, especially if the species is of concern to human and pet safety, such as the coyote (Canis latrans). Here, we evaluate coyote tolerance to the presence of humans, pets, and anthropogenic landscapes, to better understand how coyotes are conditioned to live in urbanizing landscapes. Using continuous focal follow and instantaneous scan sampling, we collected data on metrics of anthropogenic development and coyote flight response. We used cumulative link mixed models to determine that intensity of behavioral response to observation was impacted by habitat, human visitation to sites, and coyote group composition. These data may be useful to managers for profiling potentially problematic individual animals and identifying strategies for human–coyote coexistence.

Human-driven environmental changes shape ecological communities from local to global scales. Within cities, landscape-scale patterns and processes and species characteristics generally drive local-scale wildlife diversity. However, cities differ in their structure, species pools, geographies and histories, calling into question the extent to which these drivers of wildlife diversity are predictive at continental scales. In partnership with the Urban Wildlife Information Network, we used occurrence data from 725 sites located across 20 North American cities and a multi-city, multi-species occupancy modelling approach to evaluate the effects of ecoregional characteristics and mammal species traits on the urbanization-diversity relationship. Among 37 native terrestrial mammal species, regional environmental characteristics and species traits influenced within-city effects of urbanization on species occupancy and community composition. Species occupancy and diversity were most negatively related to urbanization in the warmer, less vegetated cities. Additionally, larger-bodied species were most negatively impacted by urbanization across North America. Our results suggest that shifting climate conditions could worsen the effects of urbanization on native wildlife communities, such that conservation strategies should seek to mitigate the combined effects of a warming and urbanizing world.

Goal: We previously demonstrated that near-infrared spectroscopy in vivo presents spectral features at 895 and 861 nm that accurately classify Alzheimer's disease, mild cognitive impairment, and age-matched control subjects. Our purpose here is to associate the 895 nm signal with $\beta$-amyloid. Methods: We applied our feature selection technique to subjects with and without leptomeningeal amyloid. We developed a novel concept, optical taxonomic signal, to determine the dependence of signal on source-detector distance. Results: Features at 891 and 768 nm discriminate between subjects with and without leptomeningeal $\beta$-amyloid. The variation of optical taxonomic signal with source-detector distance indicates that both signals come from the leptomeninges and not cerebral cortex. The two features are highly correlated and likely result from the same cellular material. Conclusions: The discovery of an 891 nm feature that clearly depends upon the presence of $\beta$-amyloid supports our hypothesis that the 895 nm feature previously discovered also reports $\beta$-amyloid.