Weston College

Sedimentary records retrieved from Walden Pond, Concord, MA and Sluice Pond, Lynn MA show evidence of mass wasting likely triggered by strong historic and prehistoric groundshaking. The two lakes of glacial origin form steep-sided basins of 30 m and 20 m maximum water depth with Walden Pond being divided into three distinct subbasins. Because of the visually homogeneous nature of the organic-rich lacustrine muds we employed a combination of sedimentological, geophysical, geochemical, and palynological proxies to characterize background sediments and the fingerprint of the M=5.9 1755 Cape Ann earthquake, the largest historic earthquake in New England. We then used a similar multiproxy approach to investigate the longer record of Sluice Pond as well as the individual records of the three basins of Walden Pond extending the paleoseismic record about 800 years back in time. Robust age models using a combination of radioisotopes, industrial contaminants, and pollen stratigraphy allow for dating of event horizons as well as correlation between different lake basins. Deposited before the arrival of Europeans settlers, sediments in both lakes are composed of organic-rich mud reflecting a forested landscape. The rise of non-arboreal pollen including Ambrosia record the widespread logging practices of European settlers in New England starting in the mid-17th century. Subsequent erosion of soils is marked by grain size decrease, lower organic matter content, and elemental compositions characteristic of local soils. Separate from these long-term trends we identified sediment horizons that mark sudden-onset events. These are typically characterized by larger grain size, influx of nearshore palynomorphs, higher bulk densities, and/ or lower organic matter content. We interpret these horizons as underwater mass wasting events. For Sluice Pond, we were able to identify two event horizons, one associated with the M=5.9 1755 Cape Ann earthquake, and another one dated to between 1390 -1510 CE. For Walden Pond, sediments show synchronous mass wasting in at least two subbasins potentially related to the historic 1755 earthquake, as well as two older events dated to between 1380-1520 CE and 1050-1320 CE. Interestingly, a cluster of landslides in southern Maine within geotechnically sensitive clays dates to 1220-1450 CE and could correlate with the disturbed lake sediments. We analyzed the spatial distribution of event horizons in the two lakes in Massachusetts and landslides in Maine and identified possible source areas and magnitudes of prehistoric earthquakes with one possible source area within the Littleton, MA seismic zone. Our analysis suggests that the seismic hazard in the Boston area might be higher than previously appreciated.

This paper presents a reconstruction algorithm for estimating spatial temperature distribution using Optical Frequency Domain Reflectometry (OFDR) in food processing applications. OFDR provides high-resolution distributed sensing along an embedded fiber but is inherently limited to the sensor’s physical placement, leaving large regions of the matrix unsampled. To address this limitation, an interpolation-based algorithm that reconstructs thermal fields in areas beyond the direct reach of the fiber has been developed. Experimental validation was performed by embedding an OFDR sensor in mashed potatoes and subjecting the sample to controlled oven heating and cooling between 25 °C and 105 °C. Continuous temperature measurements were recorded and processed to generate reconstructed thermal maps across the tray. The results demonstrated good agreement with the expected heat transfer dynamics, capturing both spatial gradients and transient behaviors. This approach enables a more complete characterization of heat distribution in complex food systems using a minimal number of sensing fibers. The demonstrated feasibility provides a pathway toward advanced reconstruction techniques that may integrate physics-based modeling or data-driven approaches, ultimately supporting the development of intelligent thermal monitoring solutions for food safety, quality assurance, and process optimization.

Prior research has consistently shown that students’ SAT scores are influenced by factors beyond academic ability, including socioeconomic background and ethnicity. Using aggregated school-level data from Massachusetts and New York City (NYC), this study assesses the quantitative relationships between average SAT scores and school-level demographics, academic preparation, and funding to inform education policy and equity efforts. Three analytical methods, multiple linear regression, relaxed Least Absolute Shrinkage and Selection Operator (LASSO), and decision trees, were applied sequentially to capture the linear and nonlinear associations. Across all three methods, socioeconomic disadvantage exhibited the strongest and most robust correlation of lower SAT scores, with racial composition and academic preparation identified as secondary factors. Schools with high percentages of Black, Hispanic, and low-income students tend to have lower average scores than schools with high percentages of White, Asian, and well-off students. Moreover, schools with higher college attendance rates and greater funding tend to exhibit higher average SAT scores. These findings represent school-level correlations rather than causal effects and indicate that SAT score disparities are closely intertwined with broader structural inequities already embedded within the K–12 education system. Accordingly, while targeted SAT preparation initiatives may offer modest benefits, meaningful reductions in observed disparities likely require broader policy interventions to expand equitable access to educational opportunities.

The Functional Annotation of Variants Online Resource (FAVOR), http://favor.genohub.org, is a whole genome variant annotation database and portal that provides comprehensive variant functional annotations of all possible variants across the genome. It can facilitate the analysis of whole-genome sequencing studies, support the interpretation of variant functional impacts, and help prioritize causal variants of diseases or traits. To support the growing popularity and expand the scope of FAVOR, we present here a substantial platform update. The new release features dramatically expanded annotations, a completely redesigned infrastructure powered by a newly implemented application programming interface (FAVOR-API), and a revamped web interface with advanced data-visualization capabilities and enhanced query performance. Key expansions include much more comprehensive variant annotations, including global, tissue- and cell-type-specific variant annotations; gene and protein annotations; support for both hg38 and hg19 reference genomes; and an interactive genome-browser for visualization of multi-faceted variant annotations. The updated platform also includes FAVOR-GPT, a large language model-powered interface for navigating the FAVOR database and interpreting results. FAVOR continues to evolve to keep pace with advances in research on interpreting the functional and phenotypic impact of genomic variation.

Abstract Background Previous research papers have suggested that with each successive episode of depression or anxiety disorder the chance of recurrence significantly increases. However, the causes of such recurrences have been less well studied. Indeed, studies often report multiple, often conflicting, risk factors. The current review aimed to systematically collate recent literature on this topic to both estimate the likelihood of recurrence after an initial episode of depression or generalised anxiety disorder and elucidate factors which make recurrence more or less likely. Methods In May 2022, searches were conducted across four electronic databases: Medline, Global Health, PsycInfo and Embase for records published in English since 2018 in peer-reviewed journals reporting on the prevalence of recurrence of depressive/anxiety disorders, or risk factors for recurrence of depressive/anxiety disorders. Results A total of 2,173 citations were screened and 36 papers were included in the review. Recurrence rate reported in the retained papers ranged from 11.6–91.8%, with a mean and median recurrence rate of 42%. There was limited consensus on factors associated with recurrence, but previous experience of trauma, especially during childhood, was found to be the most predictive. Limitations: Grey literature was not included within this review which may have resulted in a loss of potentially important studies. Conclusion We found no evidence that disease-related factors were predictive of relapse. Instead, our results also showed that, other than exposure to prior trauma, there was no clear consensus as to what risk factors impacted risk of recurrence. Suggestions for future research are suggested.

IntroductionEarly identification of individuals at high-risk of Parkinson’s disease (PD) may allow for the use of disease modifying treatments. We aimed to define those at risk of incident PD through environmental and genetic risk factors, comorbidities and prodromal symptoms of PD.MethodsWe identified incident cases of PD (n=1276) in the UK Biobank and unmatched controls without a PD diagnosis (n=500,406). Odds ratios for a range of determinants were calculated. A non-genetic model and polygenic risk score (PRS) were constructed. Basic gene-environment interactions were explored.ResultsStrong evidence of association (FDR < 0.05) was found between PD and family history of PD or dementia, not smoking, low alcohol consumption, depression, daytime somnolence, epilepsy and earlier menarche. Individuals in the top PRS decile had an increased risk of PD compared to those in the lowest decline and high scores were associated with an earlier age of diagnosis. There was evidence for a strong interaction between diabetes and PRS.DiscussionWe report the novel finding of a strong association between earlier menarche and increased PD. Analysis of gene-environment interactions found strong evidence that the effect of diabetes is modified by genetic risk. Replication and understanding the mechanism of this observation is an important next step.d.belete@nhs.net

N/A

ABSTRACTBACKGROUNDThe financial costs and human resource requirements at the school and district level to implement a SARS‐CoV‐2 screening program are not well known.METHODSA consortium of Massachusetts public K‐12 schools was formed to implement and evaluate a range of SARS‐CoV‐2 screening approaches. Participating districts were surveyed weekly about their programs, including: type of assay used, individual vs. pooled screening, approaches to return of results and deconvolution of positive pools, number and type of personnel, and hours spent implementing the screening program, and hours spent on program implementation.RESULTSIn 21 participating districts, over 21 weeks from January to June 2021, the positivity rate was 0.0% to 0.21% among students and 0.0% to 0.13% among educators/staff. The average weekly cost to implement a screening program, including assay and personnel costs, was $17.00 per person tested; this was $46.68 for individual screenings and $15.61 for pooled screenings. The total weekly costs by district ranged from $1,644 to $93,486, and districts screened between 58 and 3675 people per week.CONCLUSIONSWhere screening is recommended for the 2021 to 2022 school year due to high COVID‐19 incidence, understanding the human resources and finances required to implement screening will assist district policymakers in planning.