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Recently, an African ancestry-specific Parkinson disease (PD) risk signal was identified at the gene encoding glucocerebrosidase (GBA1). This variant ( rs3115534 -G) is carried by ~50% of West African PD cases and imparts a dose-dependent increase in risk for disease. The risk variant has varied frequencies across African ancestry groups but is almost absent in European and Asian ancestry populations. GBA1 is a gene of high clinical and therapeutic interest. Damaging biallelic protein-coding variants cause Gaucher disease and monoallelic variants confer risk for PD and dementia with Lewy bodies, likely by reducing the function of glucocerebrosidase. Interestingly, the African ancestry-specific GBA1 risk variant is a noncoding variant, suggesting a different mechanism of action. Using full-length RNA transcript sequencing, we identified partial intron 8 expression in risk variant carriers (G) but not in nonvariant carriers (T). Antibodies targeting the N terminus of glucocerebrosidase showed that this intron-retained isoform is likely not protein coding and subsequent proteomics did not identify a shorter protein isoform, suggesting that the disease mechanism is RNA based. Clustered regularly interspaced short palindromic repeats editing of the reported index variant ( rs3115534 ) revealed that this is the sequence alteration responsible for driving the production of these transcripts containing intron 8. Follow-up analysis of this variant showed that it is in a key intronic branchpoint sequence and, therefore, has important implications in splicing and disease. In addition, when measuring glucocerebrosidase activity, we identified a dose-dependent reduction in risk variant carriers. Overall, we report the functional effect of a GBA1 noncoding risk variant, which acts by interfering with the splicing of functional GBA1 transcripts, resulting in reduced protein levels and reduced glucocerebrosidase activity. This understanding reveals a potential therapeutic target in an underserved and underrepresented population.

We assembled the first gridded burned area (BA) database of national wildfire data (ONFIRE), a comprehensive and integrated resource for researchers, non-government organisations, and government agencies analysing wildfires in various regions of the Earth. We extracted and harmonised records from different regions and sources using open and reproducible methods, providing data in a common framework for the whole period available (starting from 1950 in Australia, 1959 in Canada, 1985 in Chile, 1980 in Europe, and 1984 in the United States) up to 2021 on a common 1° × 1° grid. The data originate from national agencies (often, ground mapping), thus representing the best local expert knowledge. Key opportunities and limits in using this dataset are discussed as well as possible future expansions of this open-source approach that should be explored. This dataset complements existing gridded BA data based on remote sensing and offers a valuable opportunity to better understand and assess fire regime changes, and their drivers, in these regions. The ONFIRE database can be freely accessed at https://zenodo.org/record/8289245 .

Teacher productive disposition is considered as one of the key strands of mathematical proficiency. Teacher disposition and positioning (disposition in action) toward mathematics influence student learning. However, teachers' productive disposition does not always translate into productive positioning in the mathematics classroom, and vice versa. In this study, we selected teacher dis/position as the unit of analysis to explore the phenomenon of two middle school mathematics teachers' self-reported affective disposition and observed positioning-by-others. Grounded in positioning theory the relationship between teacher disposition and positioning-by-others was examined utilizing a cross-case analysis. Results of the study indicate that dispositional characteristics such as attitude, self-concept, and nature of mathematics were significantly different between the cases. The study findings also suggest that interconnectedness between teacher core disposition and positional situatedness could potentially contribute to understanding and addressing the complexity of teaching and learning in the mathematics classroom.

This study investigates the implementation of remote teaching activities in mathematics classrooms during the COVID-19 pandemic in Chile, a country known for its educational market model, which has led to socioeconomic segregation among schools. The outcomes of remote teaching and the challenges faced by teachers in this context are explored. By considering different school types within the Chilean education system, a comparative analysis of frequencies reveals differences in the use of two options of instructional delivery (synchronous and asynchronous teaching), software, and in the challenges experienced by the participating teachers from three different school sectors. The results highlight a tendency and flexibility to combine synchronous and asynchronous activities using a range of available tools, including WhatsApp and Zoom. Furthermore, the findings suggest that socio-economic segregation within the Chilean education system influences the utilization of simple and free access tools, primarily by teachers in public schools.

To assess the effectiveness of vitamin A supplementation in very low birth weight (VLBW) infants to prevent complications of prematurity. Methods: This was a retrospective cohort study to determine the effectiveness of vitamin A in preventing complications of prematurity in VLBW infants. Vitamin A was delivered intramuscularly at a dose of 5000 IU, three times weekly during the first 28 days of life. Results: Of the 187 eligible VLBW infants, we excluded from the analysis (due to death or transfer to another hospital), 16 infants weighing 1000 g, the risk associated with repeated intramuscular injections of vitamin A and the modest clinical results described, we do not believe the universal administration of vitamin A to VLBW infants to be justified as prophylaxis for bronchopulmonary dysplasia.

The expansion of higher education has led to greater diversity among students, with a significant portion of them aged 25 and above. This demographic group represents a range of intersecting identities associated with their different roles, responsibilities, and life trajectories. While older students face obstacles to engagement, persistence, and success, they also bring unique strengths that inform the educational experience. This research employs a quantitative approach to explore the perceptions of bachelor's degree students regarding belonging, self-efficacy, and motivation as student engagement factors and how these perceptions influence their persistence and academic achievement during the first year, with a focus on older students. The study compares the academic achievement of mature-aged and younger students. An analysis using ordinal logistic regression indicates that age, self-efficacy, and motivation are potential predictors of academic achievement, which in turn correlates with persistence. The findings suggest that mature-aged students are more likely to perform better academically than younger students. These students report elevated confidence in their ability to study at the university level and are intrinsically motivated to learn. Based on these findings, the study discusses implications for student engagement strategies, transition and retention support, and avenues for future research.

BACKGROUND: Limited research has studied the influence of social determinants of health (SDoH) on the receipt, disease risk, and subsequent effectiveness of neutralizing monoclonal antibodies (nMAbs) for outpatient treatment of COVID-19. OBJECTIVE: To examine the influence of SDoH variables on receiving nMAb treatments and the risk of a poor COVID-19 outcome, as well as nMAb treatment effectiveness across SDoH subgroups. DESIGN: Retrospective observational study utilizing electronic health record data from four health systems. SDoH variables analyzed included race, ethnicity, insurance, marital status, Area Deprivation Index, and population density. PARTICIPANTS: COVID-19 patients who met at least one emergency use authorization criterion for nMAb treatment. MAIN MEASURE: We used binary logistic regression to examine the influence of SDoH variables on receiving nMAb treatments and risk of a poor outcome from COVID-19 and marginal structural models to study treatment effectiveness. RESULTS: The study population included 25,241 (15.1%) nMAb-treated and 141,942 (84.9%) non-treated patients. Black or African American patients were less likely to receive treatment than white non-Hispanic patients (adjusted odds ratio (OR) = 0.86; 95% CI = 0.82-0.91). Patients who were on Medicaid, divorced or widowed, living in rural areas, or living in areas with the highest Area Deprivation Index (most vulnerable) had lower odds of receiving nMAb treatment, but a higher risk of a poor outcome. For example, compared to patients on private insurance, Medicaid patients had 0.89 (95% CI = 0.84-0.93) times the odds of receiving nMAb treatment, but 1.18 (95% CI = 1.13-1.24) times the odds of a poor COVID-19 outcome. Age, comorbidities, and COVID-19 vaccination status had a stronger influence on risk of a poor outcome than SDoH variables. nMAb treatment benefited all SDoH subgroups with lower rates of 14-day hospitalization and 30-day mortality. CONCLUSION: Disparities existed in receiving nMAbs within SDoH subgroups despite the benefit of treatment across subgroups.

Long-read sequencing technologies substantially overcome the limitations of short-reads but have not been considered as a feasible replacement for population-scale projects, being a combination of too expensive, not scalable enough or too error-prone. Here we develop an efficient and scalable wet lab and computational protocol, Napu, for Oxford Nanopore Technologies long-read sequencing that seeks to address those limitations. We applied our protocol to cell lines and brain tissue samples as part of a pilot project for the National Institutes of Health Center for Alzheimer's and Related Dementias. Using a single PromethION flow cell, we can detect single nucleotide polymorphisms with F1-score comparable to Illumina short-read sequencing. Small indel calling remains difficult within homopolymers and tandem repeats, but achieves good concordance to Illumina indel calls elsewhere. Further, we can discover structural variants with F1-score on par with state-of-the-art de novo assembly methods. Our protocol phases small and structural variants at megabase scales and produces highly accurate, haplotype-specific methylation calls.

Gene functional descriptions offer a crucial line of evidence for candidate genes underlying trait variation. Conversely, plant responses to environmental cues represent important resources to decipher gene function and subsequently provide molecular targets for plant improvement through gene editing. However, biological roles of large proportions of genes across the plant phylogeny are poorly annotated. Here we describe the Joint Genome Institute (JGI) Plant Gene Atlas, an updateable data resource consisting of transcript abundance assays spanning 18 diverse species. To integrate across these diverse genotypes, we analyzed expression profiles, built gene clusters that exhibited tissue/condition specific expression, and tested for transcriptional response to environmental queues. We discovered extensive phylogenetically constrained and condition-specific expression profiles for genes without any previously documented functional annotation. Such conserved expression patterns and tightly co-expressed gene clusters let us assign expression derived additional biological information to 64 495 genes with otherwise unknown functions. The ever-expanding Gene Atlas resource is available at JGI Plant Gene Atlas (https://plantgeneatlas.jgi.doe.gov) and Phytozome (https://phytozome.jgi.doe.gov/), providing bulk access to data and user-specified queries of gene sets. Combined, these web interfaces let users access differentially expressed genes, track orthologs across the Gene Atlas plants, graphically represent co-expressed genes, and visualize gene ontology and pathway enrichments.

Record-breaking summer forest fires have become a regular occurrence in California. Observations indicate a fivefold increase in summer burned area (BA) in forests in northern and central California during 1996 to 2021 relative to 1971 to 1995. While the higher temperature and increased dryness have been suggested to be the leading causes of increased BA, the extent to which BA changes are due to natural variability or anthropogenic climate change remains unresolved. Here, we develop a climate-driven model of summer BA evolution in California and combine it with natural-only and historical climate simulations to assess the importance of anthropogenic climate change on increased BA. Our results indicate that nearly all the observed increase in BA is due to anthropogenic climate change as historical model simulations accounting for anthropogenic forcing yield 172% (range 84 to 310%) more area burned than simulations with natural forcing only. We detect the signal of combined historical forcing on the observed BA emerging in 2001 with no detectable influence of the natural forcing alone. In addition, even when considering fuel limitations from fire-fuel feedbacks, a 3 to 52% increase in BA relative to the last decades is expected in the next decades (2031 to 2050), highlighting the need for proactive adaptations.

We characterized the role of structural variants, a largely unexplored type of genetic variation, in two non-Alzheimer's dementias, namely Lewy body dementia (LBD) and frontotemporal dementia (FTD)/amyotrophic lateral sclerosis (ALS). To do this, we applied an advanced structural variant calling pipeline (GATK-SV) to short-read whole-genome sequence data from 5,213 European-ancestry cases and 4,132 controls. We discovered, replicated, and validated a deletion in TPCN1 as a novel risk locus for LBD and detected the known structural variants at the C9orf72 and MAPT loci as associated with FTD/ALS. We also identified rare pathogenic structural variants in both LBD and FTD/ALS. Finally, we assembled a catalog of structural variants that can be mined for new insights into the pathogenesis of these understudied forms of dementia.

Objective. The goals were to isolate and study the genetic susceptibility to retinopathy of prematurity (ROP), as well as the gene-environment interaction established in this disease. Methods. A retrospective study (2000–2014) was performed about the heritability of retinopathy of prematurity in 257 infants who were born at a gestational age of ≤32 weeks. The ROP was studied and treated by a single pediatric ophthalmologist. A binary logistic regression analysis was completed between the presence or absence of ROP and the predictor variables. Results. Data obtained from 38 monozygotic twins, 66 dizygotic twins, and 153 of simple birth were analyzed. The clinical features of the cohorts of monozygotic and dizygotic twins were not significantly different. Genetic factors represented 72.8% of the variability in the stage of ROP, environmental factors 23.08%, and random factors 4.12%. The environmental variables representing the highest risk of ROP were the number of days of tracheal intubation (p < 0.001), postnatal weight gain (p = 0.001), and development of sepsis (p = 0.0014). Conclusion. The heritability of ROP was found to be 0.73. The environmental factors regulate and modify the expression of the genetic code.