UC Merced

Early childhood is characterized by robust developmental changes in cognitive control. However, our understanding of intra-individual change in neural indices of cognitive control during this period remains limited. Here, we examined developmental changes in event-related potential (ERP) indices of cognitive control from preschool through first grade, in a large and diverse sample of children (N = 257). We recorded ERPs during a visual Go/No-Go task. N2 and P3b mean amplitudes were extracted from the observed waveforms (Go and No-Go) and the difference wave (No-Go minus Go, or ∆). Latent growth curve modeling revealed that while N2 Go and No-Go amplitudes showed no linear change, P3b Go and No-Go amplitudes displayed linear decreases in magnitude (became less positive) over time. ∆N2 amplitude demonstrated a linear increase in magnitude (became more negative) over time whereas ∆P3b amplitude was more positive in kindergarten compared to preschool. Younger age in preschool predicted greater rates of change in ∆N2 amplitude, and higher maternal education predicted larger initial P3b Go and No-Go amplitudes in preschool. Our findings suggest that observed waveforms and difference waves are not interchangeable for indexing neurodevelopment, and the developmental trajectories of different ERP indices of cognitive control are component-specific in early childhood.

Spt5 is an elongation factor that associates with RNA polymerase II (Pol II) during transcription and has important functions in promoter-proximal pausing and elongation processivity. Spt5 was also recognized for its roles in the transcription of expanded-repeat genes that are related to neurodegenerative diseases. Recently, a set of Spt5-Pol II small molecule inhibitors (SPIs) were reported, which selectively inhibit mutant huntingtin gene transcription. Inhibition mechanisms as well as interaction sites of these SPIs with Pol II and Spt5 are not entirely known. In this study, we predicted the binding sites of three selected SPIs at the Pol II-Spt5 interface by docking and molecular dynamics simulations. Two molecules out of three demonstrated strong binding with Spt5 and Pol II, while the other molecule was more loosely bound and sampled multiple binding sites. Strongly bound SPIs indirectly affected RNA and DNA dynamics at the exit site as DNA became more flexible while RNA was stabilized by increased interactions with Spt5. Our results suggest that the transcription inhibition mechanism induced by SPIs can be related to Spt5-nucleic acid interactions, which were altered to some extent with strong binding of SPIs.

The current study assessed cross-lagged relationships between binge drinking, implicit beliefs, and habit in undergraduate university students (N = 105). Students completed self-report survey and implicit measures in lab visits 3 months apart. A structural equation model revealed cross-lagged relations between habit and behavior, and some evidence for a reciprocal relationship between implicit beliefs and habit. Implicit beliefs were related to alcohol behavior across time, but no cross-lagged relationship was observed. Findings provide preliminary support for recent advances in habit theory, suggesting that implicit beliefs and habit may develop in tandem or even share common knowledge structures and schemas.

Understanding and controlling protein motion at atomic resolution is a hallmark challenge for structural biologists and protein engineers because conformational dynamics are essential for complex functions such as enzyme catalysis and allosteric regulation. Time-resolved crystallography offers a window into protein motions, yet without a universal perturbation to initiate conformational changes the method has been limited in scope. Here we couple a solvent-based temperature jump with time-resolved crystallography to visualize structural motions in lysozyme, a dynamic enzyme. We observed widespread atomic vibrations on the nanosecond timescale, which evolve on the submillisecond timescale into localized structural fluctuations that are coupled to the active site. An orthogonal perturbation to the enzyme, inhibitor binding, altered these dynamics by blocking key motions that allow energy to dissipate from vibrations into functional movements linked to the catalytic cycle. Because temperature jump is a universal method for perturbing molecular motion, the method demonstrated here is broadly applicable for studying protein dynamics.

Understanding the economic value of ecosystem services is necessary to facilitate sustainable land use management, and to inform policy and decision making. However, valuing and monetizing ecosystem services remains challenging. Benefit-transfer and non-market valuation methods typically rely on administrative data and surveys, but this is time consuming, limited, and requires much more resources. Social media and other types of big data provide accessible and georeferenced data that can be incorporated into valuation approaches. We use recreation as an example and the Tahoe Central Sierra Initiative (TCSI) project area in California as a case study to explore the usefulness of such data in estimating travel costs that form an integral part of determining the value of recreational ecosystem services through the travel cost model. We estimated 6,951 person user days of recreation from 2,245 visitors who uploaded photographs to the Flickr photo-sharing application between 2005 and 2019. We used metadata from the images to infer visitor origins and estimate trip distance and costs of travel for visitors that took day trips (<500 miles (∼800 kms) roundtrip) to the area. Our results show that the most demand for recreational opportunities in the TCSI came from domestic visitors, particularly those from California and Nevada who took day trips. On average, visitors spent $156 per single day trip. The total cost of travel for recreational visits to the TCSI for the period was $491,500 (an average of $32,800 per year). However, when adjusted to align with actual visitation, the travel costs could range from $1.35 to $1.84 billion per year. Estimating recreational use and highlighting the travel cost for recreational opportunities illustrates how crowdsourced data can refine valuation approaches such as the widely used travel cost approach, which may fill in data gaps in valuing ecosystem services.

Crowdsourced geotagged social media data and machine learning approaches have emerged as promising tools for mapping ecosystem services, especially cultural ecosystem services that are difficult to assess. Here, we use recreation to show how social media data, machine learning, and spatial analysis techniques can improve our understanding of human-nature interactions and the mapping of recreational ecosystem services. We extracted 80,500 photographs taken in non-urban areas of the Tahoe Central Sierra Initiative project area in California between 2005 and 2019 that were posted to the photo sharing application Flickr and used these as a proxy for recreational visits to the area. Automated image content analysis was used to identify the objects and concepts in the photographs and uncover the types of nature experiences that are important to visitors. Additionally, variable importance, a Random Forest machine learning technique, was used to examine the environmental and landscape variables that drive recreation in the area and to create a classification model that predicts the recreation potential of the entire area based on important variables. The automated image content analysis identified 1,239 unique labels linked to recreation, with mountains, hills, and rocks being the most prominent features (22%). Our Random Forest model indicates that vegetation cover, land cover, elevation, smoke days, and landscape features are major drivers of recreation in the area and are of interest to visitors in the area. The model predicted that 25.9% of the area has the potential to support recreational visits. Most of these recreation potential areas are in protected areas (77.8%), predominantly in conifer forests (66%) and within national forest boundaries, especially the Tahoe National Forest area (37.6%). These results show that recreational ecosystem services vary across landscapes and illustrate the need for improved mapping approaches to determine the provision of ecosystem services in different places. The analysis provides novel insights into the various ways social media data and machine learning techniques can be powerful components of ecosystem service research and how they hold great potential for monitoring and informing management interventions on ecosystem service provision, especially in places with limited traditional onsite visitation data.

Although exclusionary immigration policies are associated with fear of deportation and avoidance of public benefits, relationships between immigration enforcement policy and public charge policies are largely unknown. Using a California population-based survey of 1103 Asian and Latinx immigrants in 2018, we tested the relationship between immigrants experiences with law enforcement and their concern about public charge. Direct encounters with various forms of law enforcement, including being asked to show proof of citizenship by law enforcement, staying inside to avoid police or immigration officials, and having known someone who had been deported, were associated with immigrants avoidance of public benefits due to public charge concerns. Latinx immigrants were more likely to be concerns about public charge than Asians. Intersections among immigration policies deserve further consideration. There is a need to provide accurate and reliable information to immigrant communities about public benefits and advocate for inclusive immigration policies.

INTRODUCTION: High levels of sugar intake are associated with multiple maladaptive health outcomes in adult and younger populations. Identifying the psychological determinants of sugar intake in adolescents, and the processes involved, may help identify potentially modifiable targets and inform intervention development. We tested the predictions of an extended theoretical model based on the theory of planned behavior (TPB), which specified social cognition constructs, habit, and self-control as correlates of sugar intake in an adolescent sample. METHODS: Adolescents aged 12 to 14 years (N = 88) recruited via a survey panel company and consenting to participate in the study completed online self-report measures of constructs from the TPB alongside measures of habit and self-control. One month later, participants completed a follow-up measure of free-sugar intake. Hypothesized effects of our proposed extended model were tested using partial least squares structural equation modeling. RESULTS: We found statistically significant effects of attitude, subjective norm, and perceived behavioral control on sugar intake intentions. We also found significant effects of habit and self-control on sugar intake measured at follow-up, but no effect for intention. Perceived behavioral control moderated the intention-behavior relationship such that intention effects on behavior were larger when perceived behavioral control was high. However, self-control did not moderate the intention-behavior relationship. CONCLUSION: Results indicate that sugar intake in this sample was a function of habits and self-control, and the effect of sugar intake intentions was conditional on perceived behavioral control. Results contribute to an evidence base of determinants and associated processes that relate to sugar intake in adolescents and may signal potentially modifiable targets for intervention.

Understanding of the vulnerability of populations exposed to wildfires is limited. We used an index from the U.S. Centers for Disease Control and Prevention to assess the social vulnerability of populations exposed to wildfire from 2000-2021 in California, Oregon, and Washington, which accounted for 90% of exposures in the western United States. The number of people exposed to fire from 2000-2010 to 2011-2021 increased substantially, with the largest increase, nearly 250%, for people with high social vulnerability. In Oregon and Washington, a higher percentage of exposed people were highly vulnerable (>40%) than in California (~8%). Increased social vulnerability of populations in burned areas was the primary contributor to increased exposure of the highly vulnerable in California, whereas encroachment of wildfires on vulnerable populations was the primary contributor in Oregon and Washington. Our results emphasize the importance of integrating the vulnerability of at-risk populations in wildfire mitigation and adaptation plans.

The SARS-CoV-2 virion has shown remarkable resilience, capable of mutating to escape immune detection and re-establishing infectious capabilities despite new vaccine rollouts. Therefore, there is a critical need to identify relatively immutable epitopes on the SARS-CoV-2 virion that are resistant to future mutations the virus may accumulate. While hACE2 has been identified as the receptor that mediates SARS-CoV-2 susceptibility, it is only modestly expressed in lung tissue. C-type lectin receptors like DC-SIGN can act as attachment sites to enhance SARS-CoV-2 infection of cells with moderate or low hACE2 expression. We developed an easy-to-implement assay system that allows for the testing of SARS-CoV-2 trans-infection. Using our assay, we assessed how SARS-CoV-2 Spike S1-domain glycans and spike proteins from different strains affected the ability of pseudotyped lentivirions to undergo DC-SIGN-mediated trans-infection. Through our experiments with seven glycan point mutants, two glycan cluster mutants and four strains of SARS-CoV-2 spike, we found that glycans N17 and N122 appear to have significant roles in maintaining COVID-19s infectious capabilities. We further found that the virus cannot retain infectivity upon the loss of multiple glycosylation sites, and that Omicron BA.2 pseudovirions may have an increased ability to bind to other non-lectin receptor proteins on the surface of cells. Taken together, our work opens the door to the development of new therapeutics that can target overlooked epitopes of the SARS-CoV-2 virion to prevent C-type lectin-receptor-mediated trans-infection in lung tissue.