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Active teaching methods are believed to facilitate higher-order thinking skills and prepare allied health students for independent clinical decision-making. This quantitative, correlational study aimed to explain the relationships between student preferences for active over traditional methods and their beliefs, the frequency and positiveness of their experiences, and the extent of knowledge they have received regarding active and traditional teaching methods. Two hundred and thirty students completed a 53-item online survey. Students were enrolled in a Doctor of Physical Therapy, Masters in Speech-language Pathology, or Bachelor of Science Nursing program in one of seventeen participating institutions across a ten-state Midwest region. A combination of student knowledge, student beliefs, and positive student experiences with active over traditional methods predicted 72.5% (R[superscript 2] = 0.725, p = <0.001) of the variance of student preferences for active methods. When students have clarity about the expectations of active learning methods, how they benefit their learning, believe they are responsible for learning and take the initiative, and perceive a positive experience, they prefer active methods over traditional methods. The results inform health professional education programs with recommendations that influence pedagogical change to support faculty and prepare students for clinical practice, higher-order thinking skills, and workforce expectations.

Lithium (Li) is one of the most effective drugs for treating bipolar disorder (BD), however, there is presently no way to predict response to guide treatment. The aim of this study is to identify functional genes and pathways that distinguish BD Li responders (LR) from BD Li non-responders (NR). An initial Pharmacogenomics of Bipolar Disorder study (PGBD) GWAS of lithium response did not provide any significant results. As a result, we then employed network-based integrative analysis of transcriptomic and genomic data. In transcriptomic study of iPSC-derived neurons, 41 significantly differentially expressed (DE) genes were identified in LR vs NR regardless of lithium exposure. In the PGBD, post-GWAS gene prioritization using the GWA-boosting (GWAB) approach identified 1119 candidate genes. Following DE-derived network propagation, there was a highly significant overlap of genes between the top 500- and top 2000-proximal gene networks and the GWAB gene list (Phypergeometric = 1.28E-09 and 4.10E-18, respectively). Functional enrichment analyses of the top 500 proximal network genes identified focal adhesion and the extracellular matrix (ECM) as the most significant functions. Our findings suggest that the difference between LR and NR was a much greater effect than that of lithium. The direct impact of dysregulation of focal adhesion on axon guidance and neuronal circuits could underpin mechanisms of response to lithium, as well as underlying BD. It also highlights the power of integrative multi-omics analysis of transcriptomic and genomic profiling to gain molecular insights into lithium response in BD.

Airborne measurements are pivotal for providing detailed, spatiotemporally resolved information about atmospheric parameters and aerosol and cloud properties, thereby enhancing our understanding of dynamic atmospheric processes. For 30 years, the US Department of Energy (DOE) Office of Science supported an instrumented Gulfstream 1 (G-1) aircraft for atmospheric field campaigns. Data from the final decade of G-1 operations were archived by the Atmospheric Radiation Measurement (ARM) Data Center and made publicly available at no cost to all registered users. To ensure a consistent data format and to improve the accessibility of the ARM airborne data, an integrated dataset was recently developed covering the final 6 years of G-1 operations (2013 to 2018, https://doi.org/10.5439/1999133; Mei and Gaustad, 2024). The integrated dataset includes data collected from 236 flights (766.4 h), which covered the Arctic, the US Southern Great Plains (SGP), the US West Coast, the eastern North Atlantic (ENA), the Amazon Basin in Brazil, and the Sierras de Córdoba range in Argentina. These comprehensive data streams provide much-needed insight into spatiotemporal variability in the thermodynamic quantities and aerosol and cloud properties for addressing essential science questions in Earth system process studies. This paper describes the DOE ARM merged G-1 datasets, including information on the acquisition, data collection challenges and future potentials, and quality control processes. It further illustrates the usage of this merged dataset to evaluate the Energy Exascale Earth System Model (E3SM) with the Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package.

Until the beginning of the 21st century, the Tulsa Race Massacre was omitted mainly from the social studies curriculum and state-mandated standards in the United States. However, the featured lesson provides a valuable springboard to explore the historical perspectives and injustices against the Black community in Tulsa, Oklahoma, on May 31, 1921. This lesson exemplifies how social studies teachers can effectively explore controversial issues, such as racial discrimination in U.S. history, by investigating the Tulsa Race Massacre. Students are encouraged to engage in a comprehensive analysis and discussion of newspaper articles to investigate the events prior to the Tulsa Race Massacre and the obstacles faced by the inhabitants of Tulsa in the aftermath of the tragedy. Through implementing the case study approach, this pedagogical lesson aims to foster higher-order thinking skills among students by providing an opportunity to analyze, compare, and contrast various reports in a secondary classroom setting.

Artificial light at night (ALAN) is increasing in extent and intensity across the globe. It has been shown to interfere with animal sensory systems, orientation and distribution, with the potential to cause significant ecological impacts. We analysed the locations of 102 mountain lions (Puma concolor) in a light-polluted region in California. We modelled their distribution relative to environmental and human-disturbance variables, including upward radiance (nearby lights), zenith brightness (sky glow) and natural illumination from moonlight. We found that mountain lion probability of presence was highly related to upward radiance, that is, related to lights within approximately 500 m. Despite a general pattern of avoidance of locations with high upward radiance, there were large differences in degree of avoidance among individuals. The amount of light from artificial sky glow was not influential when included together with upward radiance in the models, and illumination from moonlight was not influential at all. Our results suggest that changes in visibility associated with lunar cycles and sky glow are less important for mountain lions in their selection of light landscapes than avoiding potential interactions with humans represented by the presence of nearby lights on the ground. This article is part of the theme issue Light pollution in complex ecological systems.

Abstract Background Lithium (Li) remains the treatment of choice for bipolar disorders (BP). Its mood-stabilizing effects help reduce the long-term burden of mania, depression and suicide risk in patients with BP. It also has been shown to have beneficial effects on disease-associated conditions, including sleep and cardiovascular disorders. However, the individual responses to Li treatment vary within and between diagnostic subtypes of BP (e.g. BP-I and BP-II) according to the clinical presentation. Moreover, long-term Li treatment has been linked to adverse side-effects that are a cause of concern and non-adherence, including the risk of developing chronic medical conditions such as thyroid and renal disease. In recent years, studies by the Consortium on Lithium Genetics (ConLiGen) have uncovered a number of genetic factors that contribute to the variability in Li treatment response in patients with BP. Here, we leveraged the ConLiGen cohort (N = 2064) to investigate the genetic basis of Li effects in BP. For this, we studied how Li response and linked genes associate with the psychiatric symptoms and polygenic load for medical comorbidities, placing particular emphasis on identifying differences between BP-I and BP-II. Results We found that clinical response to Li treatment, measured with the Alda scale, was associated with a diminished burden of mania, depression, substance and alcohol abuse, psychosis and suicidal ideation in patients with BP-I and, in patients with BP-II, of depression only. Our genetic analyses showed that a stronger clinical response to Li was modestly related to lower polygenic load for diabetes and hypertension in BP-I but not BP-II. Moreover, our results suggested that a number of genes that have been previously linked to Li response variability in BP differentially relate to the psychiatric symptomatology, particularly to the numbers of manic and depressive episodes, and to the polygenic load for comorbid conditions, including diabetes, hypertension and hypothyroidism. Conclusions Taken together, our findings suggest that the effects of Li on symptomatology and comorbidity in BP are partially modulated by common genetic factors, with differential effects between BP-I and BP-II.

Isoprene has the largest global non-methane hydrocarbon emission, and the oxidation of isoprene plays a crucial role in the formation of secondary organic aerosol (SOA). Two primary processes are known to contribute to SOA formation from isoprene oxidation: (1) the reactive uptake of isoprene-derived epoxides on acidic or aqueous particle surfaces and (2) the absorptive gas–particle partitioning of low-volatility oxidation products. In this study, we developed a new multiphase condensed isoprene oxidation mechanism that includes these processes with key molecular intermediates and products. The new mechanism was applied to simulate isoprene gas-phase oxidation products and SOA formation from previously published chamber experiments under a variety of conditions and atmospheric observations during the Southern Oxidant and Aerosol Studies (SOAS) field campaign. Our results show that SOA formation from most of the chamber experiments is reasonably reproduced using our mechanism, except when the concentration ratios of initial nitric oxide to isoprene exceed ∼ 2, the formed SOA is significantly underpredicted. The SOAS simulations also reasonably agree with the measurements regarding the diurnal pattern and concentrations of different product categories, while the total isoprene SOA remains underestimated. The molecular compositions of the modeled SOA indicate that multifunctional low-volatility products contribute to isoprene SOA more significantly than previously thought, with a median mass contribution of ∼ 57 % to the total modeled isoprene SOA. However, this contribution is intricately intertwined with IEPOX-derived SOA (IEPOX: isoprene-derived epoxydiols), posing challenges for their differentiation using bulk aerosol composition analysis (e.g., the aerosol mass spectrometer with positive matrix factorization). Furthermore, the SOA from these pathways may vary greatly, mainly dependent on the volatility estimation and treatment of particle-phase processes (i.e., photolysis and hydrolysis). Our findings emphasize that the various pathways to produce these low-volatility species should be considered in models to more accurately predict isoprene SOA formation. The new condensed isoprene chemical mechanism can be further incorporated into regional-scale air quality models, such as the Community Multiscale Air Quality Modelling System (CMAQ), to assess isoprene SOA formation on a larger scale.

Like most coastal states in the U.S., California’s shoreline communities and ecosystems have been exposed to flooding related to sea level rise and storms, which jeopardize their persistence and well-being. Shoreline transportation is especially vulnerable in certain places to flooding and failure, and because it is part of a continuously used network with little redundancy, it transfers its vulnerability to regional transportation networks. Forward-projected inundation/flooding risk is typically modeled at coarse spatial and temporal scales, which are useful at regional and decadal scales, but less useful for coastal managers and flood responders. This project improved assessment of both overall probability and short-term forecasts of water level for specific locations in San Francisco Bay that are vulnerable to flooding associated with sea level rise. The authors have developed probability assessment and forecasts through developing data-based, site-specific, model-independent approaches, which can be compared with and help to improve regional models of coastal flooding (e.g., CoSMoS). Water level data were collected across fine-scale arrays at fluvial-bay junctures in Sonoma and Marin Counties. The primary analysis is based on deconstructing water level records into multiple quasi-independent signals, which can be better predicted and recombined to produce probability of extreme events and to produce short-term forecasts during a flooding event based on predicted weather, wind, rain, and tide. In addition, real-time water level data are now available to first responders at critical locations in Novato Creek and Petaluma River when there is potential for flooding, as well as during a flood event. This is a pilot project that could be replicated at many other vulnerable locations around San Francisco Bay and elsewhere. View the NCST Project Webpage

Communities across the United States and particularly in the Midwest continue to grapple with the complications associated with aging infrastructure. This includes the presence of lead (Pb)-bearing plumbing components such as lead service lines, downstream galvanized iron pipes, and Pb/tin solder. The community of Benton Harbor, MI, experienced six Pb action level exceedances between 2018 and 2021, leading to increasing community concern and a request from the state of Michigan for the US Environmental Protection Agency involvement. Between 9 November and 17 December 2021, US EPA Region 5 and Office of Research and Development, along with the state of Michigan, conducted a water filter efficacy and Pb-nanoparticulate (

Abstract Lithium is the gold standard treatment for bipolar disorder (BD). However, its mechanism of action is incompletely understood, and prediction of treatment outcomes is limited. In our previous multi-omics study of the Pharmacogenomics of Bipolar Disorder (PGBD) sample combining transcriptomic and genomic data, we found that focal adhesion, the extracellular matrix (ECM), and PI3K-Akt signaling networks were associated with response to lithium. In this study, we replicated the results of our previous study using network propagation methods in a genome-wide association study of an independent sample of 2039 patients from the International Consortium on Lithium Genetics (ConLiGen) study. We identified functional enrichment in focal adhesion and PI3K-Akt pathways, but we did not find an association with the ECM pathway. Our results suggest that deficits in the neuronal growth cone and PI3K-Akt signaling, but not in ECM proteins, may influence response to lithium in BD.

Research indicates facilitated debriefing is more effective than non-facilitated debriefing. However, limited published work on this topic exists within communication sciences and disorders. This study investigates speech-language pathology clinical simulation experiences examining formative assessment of debriefing sessions. Two groups of graduate students were compared to assess students' perceptions of simulated learning experiences over 6 consecutive weeks. Although no significant changes were noted, stability between-group ratings indicate students entered this experience with practical clinical skills. Future studies may consider students' ability to apply previous knowledge compared to those with no previous clinical experience.

Background: Acute kidney injury (AKI) is associated with increased complications after total hip arthroplasty (THA) and total knee arthroplasty (TKA). The purpose of this study was to determine the risk factors for AKI after THA and TKA and evaluate if preoperative use of antihypertensive drugs is a risk factor for AKI. Methods: A retrospective review of 7406 primary TKAs and THAs (4532 hips and 2874 knees) from 2013 to 2019 was performed. The following preoperative variables were obtained from medical records: medications, chemistry 7 panel, Elixhauser comorbidities, and demographic factors. AKI was defined as an increase in serum creatinine by 26.4 μmol·L−1. Multivariate analysis was performed to identify the risk factors. Results: The overall incidence of postoperative AKI was 6.2% (n = 459). Risk factors for postoperative AKI were found to be: chronic kidney disease (odds ratio [OR] = 7.09; 95% confidence interval [CI]: 4.8-9.4), diabetes (OR: 5.03; 95% CI: 2.8-6.06), ≥3 antihypertensive drugs (OR: 4.2; 95% CI: 2.1-6.2), preoperative use of an angiotensin receptor blockers or angiotensin-converting enzyme inhibitors (OR: 3.8; 95% CI: 2.2-5.9), perioperative vancomycin (OR: 2.7; 95% CI: 1.8-4.6), and body mass index >40 kg/m2 (OR: 1.9; 95% CI: 1.3-3.06). Conclusions: We have identified several modifiable risk factors for AKI that can be optimized prior to an elective THA or TKA. The use of certain antihypertensive agents namely angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, and multidrug antihypertensive regimens were found to significantly increase the risk of AKI. Therefore, perioperative management of patients undergoing joint replacement should include medical comanagement with a focus on careful management of antihypertensives.

BackgroundCognitive dysfunction in schizophrenia is the key predictor of functional disability and drives economic burden. Inflammation has been increasingly implicated in the pathogenesis of schizophrenia, yet its role in cognitive decline has not been evaluated. This study explores the association between inflammation and cognitive functioning in persons with schizophrenia.MethodsParticipants included 143 persons with schizophrenia (PwS) and 139 non-psychiatric comparison subjects (NCs) from an ongoing study of aging. Cognitive assessments included validated measures for executive functioning, processing speed, and visuospatial skills. Plasma levels of nine biomarkers associated with inflammation (high sensitivity C-reactive protein, intercellular adhesion molecule 1, serum amyloid A, interleukin-6, interleukin-8, interferon gamma-induced protein-10, monocyte chemotactic protein-1, fractalkine, and brain-derived neurotrophic factor) were quantified using commercially available, enzyme-linked immunosorbent assays. Partial least squares regression was used to develop a composite "inflammatory profile" to maximize correlations with the cognitive outcomes. We then constructed a best-fit model using these composites and their interactions with diagnosis and sex as the predictors, controlling for covariates.ResultsThe biomarker composite, which best correlated with scores on cognitive testing, included high sensitivity C-reactive protein, intercellular adhesion molecule 1, serum amyloid A, interleukin-6, and brain-derived neurotrophic factor, for a 5-biomarker "inflammatory profile." The best-fit model showed a significant biomarker composite by diagnosis by sex three-way interaction, for executive function and processing speed, but not visuospatial skill.ConclusionsThis approach to building an "inflammatory profile" may provide insight into inflammatory pathways affecting brain function and potential targets for anti-inflammatory interventions to improve cognition in schizophrenia.

Transportation and other agencies and organizations are increasingly planning and building under- and over-crossing structures to allow wildlife to traverse busy highways. Research has shown that traffic noise and light can impede wildlife species from using these structures. However, existing guidance in the field of wildlife crossing design inadequately addresses how structural and vegetation elements can be used to reduce such disturbance. If wildlife is hesitant to or refuses to approach structures due to noise, light, and other factors, then the structures may have a much lower benefit-to-cost ratio than expected. To help address this gap in guidance for design, a research team led by UC Davis used field measurements and modeling of light and noise from traffic to inform and test wildlife crossing designs. The researchers developed wildlife-responsive designs using berms, barriers, and new paths for two crossings being considered by the California Department of Transportation: 1) the proposed Wallis Annenberg wildlife over-crossing (WAOC) across US 101 in the city of Agoura Hills, and 2) a potential over-crossing across Interstate 15, south of the City of Temecula (TOC). The researchers identified key limitations and opportunities for each design approach and concluded that creating “dark and quiet paths” could increase the wildlife-responsiveness of the designs.

Atmospheric aerosols affect the global energy budget by scattering and absorbing sunlight (direct effects) and by changing the microphysical structure, lifetime, and coverage of clouds (indirect effects). Both aerosol direct and indirect effects are affected by the vertical distribution of aerosols in the atmosphere, which is further influenced by a range of processes, such as aerosol dynamics, long-range transport, and entrainment. However, many observations of these processes are based on ground measurements, limiting our ability to understand the vertical distribution of aerosols and simulate their impact on clouds and climate. In this work, we examined the vertical heterogeneity of aerosols over the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) using data collected from the Holistic Interactions of Shallow Clouds, Aerosols and Land Ecosystems (HI-SCALE) campaign. The vertical profiles of meteorological and aerosol physiochemical properties up to 2500 m above are examined based on the 38 flights conducted during the HI-SCALE campaign. The aerosol properties over the SGP show strong vertical heterogeneity and seasonal variabilities. The aerosol concentrations at the surface are the highest due to strong emissions at ground level. In general, the mode diameter of aerosols during summer (∼ 100 nm) is larger than that during spring (∼ 30 nm), a result of enhanced condensational growth due to enriched volatile organic compounds in summer. The concentration of aerosols below 30 nm in the boundary layer (BL) (e.g., below 1000 m) during spring is higher than that during summer, a result of the stronger new particle formation (NPF) events due to the reduced condensation sink in spring. In the BL, the size of the aerosols gradually increases with altitude due to condensational growth and cloud processing. However, the chemical composition of the aerosols remained similar, with organics and sulfates representing 59.8 ± 2.2 % and 22.7 ± 2.1 %, respectively, of the total mass in the BL. Through the vertical profiles of aerosol properties, we observed NPF events in the upper BL during 7 out of 38 research flights, where the newly formed particles continue to grow as they are mixed down to the surface. There is also an indication that deep convection brings aerosols from the free troposphere (FT) to the surface, where they grow to contribute to the cloud condensation nuclei (CCN). Overall, the vertical heterogeneity of aerosols over the SGP is influenced by aerosol dynamics (new particle formation, growth, and cloud processing) and transport processes (mixing in the BL, long-range transport, entrainment, and convective downward transport). Case studies showing the influence of these factors are discussed.

Transportation and other agencies and organizations are increasingly planning and building under- and over-crossing structures for wildlife to traverse busy highways. However, if wildlife do not use these structures due to noise, light, and other factors, then the structures may have a low benefit to cost ratio. Several criteria are key for their success— sufficient safety and/or conservation need, cost, location, and anticipated use by wildlife. There is limited information in wildlife-crossing guidance on how wildlife biologists should advise designers, engineers, and architects on the use of structural and vegetation elements that could reduce noise and light disturbances. To address this problem, this study used field measurements and modeling of light and noise from traffic to inform and test the designs of two wildlife overcrossings. Wildlife-responsive designs were developed and tested for two crossings being considered or planned by California Department of Transportation in California. For the planned crossing of US 101 near the city of Agoura Hills (the Wallis-Annenberg crossing), the three designs consisted of noise/glare barriers; noise/glare barriers + berm; and noise/glare barriers + multiple berms. For the potential crossing of Interstate 15 south of Temecula, one design used noise/glare barriers of 3 different heights and the other had no barriers. Key limitations and opportunities for each design approach were identified. Creating “dark and quiet paths” using a combination of berms and noise/glare barriers could decrease disturbance in the crossing structure approach zones and increase the wildlife-responsiveness of the designs.

BackgroundThe Adolescent Brain Cognitive Development ™ Study (ABCD Study®) is an open-science, multi-site, prospective, longitudinal study following over 11,800 9- and 10-year-old youth into early adulthood. The ABCD Study aims to prospectively examine the impact of substance use (SU) on neurocognitive and health outcomes. Although SU initiation typically occurs during teen years, relatively little is known about patterns of SU in children younger than 12.MethodsThis study aims to report the detailed ABCD Study® SU patterns at baseline (n = 11,875) in order to inform the greater scientific community about cohort's early SU. Along with a detailed description of SU, we ran mixed effects regression models to examine the association between early caffeine and alcohol sipping with demographic factors, externalizing symptoms and parental history of alcohol and substance use disorders (AUD/SUD).Primary resultsAt baseline, the majority of youth had used caffeine (67.6 %) and 22.5 % reported sipping alcohol (22.5 %). There was little to no reported use of other drug categories (0.2 % full alcohol drink, 0.7 % used nicotine,

Abstract This study aimed to evaluate the influence of CO2 and temperature on glyphosate-resistant and susceptible biotypes of Amaranthus palmeri (Palmer amaranth) in terms of morphological development. Height (cm), stem diameter (cm), leaf area (cm2), number of leaves, leaf, stem, and root dry matter, plant volume (m3), as well as shoot-to-root allometry were evaluated. The Palmer amaranth biotypes were grown under four different scenarios: 1—low temperature (23/33 °C) and CO2 (410 ± 25 ppm); 2—low temperature (23/33 °C) and high CO2 (750 ± 25 ppm); 3—high temperature (26/36 °C) and low CO2 (410 ± 25 ppm); and 4—high temperature (26/36 °C) and CO2 (750 ± 25 ppm). Between CO2 and temperature, the majority of differences observed were driven by CO2 levels. Palmer amaranth grown under 750 ppm of CO2 was 15.5% taller, displayed 10% more leaf area (cm2), 18% more stem dry matter, and had a 28.4% increase in volume (m3) compared to 410 ppm of CO2. GA2017 and GA2020 were 18% and 15.5% shorter, respectively. The number of leaves was 27% greater for GA2005. Plant volume decreased in GA2017 (35.6%) and GA2020 (23.8%). The shoot-to-root ratio was isomeric, except at 14 and 21 DAT, where an allometric growth towards shoot development was significant. Palmer amaranth biotypes responded differently to elevated CO2, and the impacts of temperature need further investigation on weed physiology. Thus, environmental and genetic background may affect the response of glyphosate-resistant and susceptible populations to climate change scenarios.

Klebsiella aerogenes is an important opportunistic pathogen with the potential to develop resistance against last-line antibiotics, such as carbapenems, limiting the treatment options. Here, we investigated the antibiotic resistance profiles of 10 K. aerogenes strains isolated from patient samples in the intensive-care unit of a Brazilian tertiary hospital using conventional PCR and a comprehensive genomic characterization of a specific K. aerogenes strain (CRK317) carrying both the blaKPC-2 and blaNDM-1 genes simultaneously. All isolates were completely resistant to β-lactam antibiotics, including ertapenem, imipenem, and meropenem with differencing levels of resistance to aminoglycosides, quinolones, and tigecycline also observed. Half of the strains studied were classified as multidrug-resistant. The carbapenemase-producing isolates carried many genes of interest including: β-lactams (blaNDM-1, blaKPC-2, blaTEM-1, blaCTX-M-1 group, blaOXA-1 group and blaSHVvariants in 20-80% of the strains), aminoglycoside resistance genes [aac(6’)-Ib and aph(3’)-VI, 70 and 80%], a fluoroquinolone resistance gene (qnrS, 80%), a sulfonamide resistance gene (sul-2, 80%) and a multidrug efflux system transporter (mdtK, 70%) while all strains carried the efflux pumps Acr (subunit A) and tolC. Moreover, we performed a comprehensive genomic characterization of a specific K. aerogenes strain (CRK317) carrying both the blaKPC-2 and blaNDM-1 genes simultaneously. The draft genome assembly of the CRK317 had a total length of 5,462,831 bp and a GC content of 54.8%. The chromosome was found to contain many essential genes. In silico analysis identified many genes associated with resistance phenotypes, including β-lactamases (blaOXA-9, blaTEM-1, blaNDM-1, blaCTX-M-15, blaAmpC-1, blaAmpC-2), the bleomycin resistance gene (bleMBL), an erythromycin resistance methylase (ermC), aminoglycoside-modifying enzymes [aac(6’)-Ib, aadA/ant(3”)-Ia, aph(3’)-VI], a sulfonamide resistance enzyme (sul-2), a chloramphenicol acetyltransferase (catA-like), a plasmid-mediated quinolone resistance protein (qnrS1), a glutathione transferase (fosA), PEtN transferases (eptA, eptB) and a glycosyltransferase (arnT). We also detected 22 genomic islands, eight families of insertion sequences, two putative integrative and conjugative elements with a type IV secretion system, and eight prophage regions. This suggests the significant involvement of these genetic structures in the dissemination of antibiotic resistance. The results of our study show that the emergence of carbapenemase-producing K. aerogenes, co-harboring blaKPC-2 and blaNDM-1, is a worrying phenomenon which highlights the importance of developing strategies to detect, prevent, and control the spread of these microorganisms.

Bipolar disorder (BD) is a neuropsychiatric illness defined by recurrent episodes of mania/hypomania, depression and circadian rhythm abnormalities. Lithium is an effective drug for BD, but 30-40% of patients fail to respond adequately to treatment. Previous work has demonstrated that lithium affects the expression of "clock genes" and that lithium responders (Li-R) can be distinguished from non-responders (Li-NR) by differences in circadian rhythms. However, circadian rhythms have not been evaluated in BD patient neurons from Li-R and Li-NR. We used induced pluripotent stem cells (iPSCs) to culture neuronal precursor cells (NPC) and glutamatergic neurons from BD patients characterized for lithium responsiveness and matched controls. We identified strong circadian rhythms in Per2-luc expression in NPCs and neurons from controls and Li-R, but NPC rhythms in Li-R had a shorter circadian period. Li-NR rhythms were low amplitude and profoundly weakened. In NPCs and neurons, expression of PER2 was higher in both BD groups compared to controls. In neurons, PER2 protein levels were higher in BD than controls, especially in Li-NR samples. In single cells, NPC and neuron rhythms in both BD groups were desynchronized compared to controls. Lithium lengthened period in Li-R and control neurons but failed to alter rhythms in Li-NR. In contrast, temperature entrainment increased amplitude across all groups, and partly restored rhythms in Li-NR neurons. We conclude that neuronal circadian rhythm abnormalities are present in BD and most pronounced in Li-NR. Rhythm deficits in BD may be partly reversible through stimulation of entrainment pathways.

Accurate data on crashes and other traffic incidents are critical for analyzing the rates, costs, and causes of crashes, and for evaluating the effects of safety policies and engineering solutions. There are two official sources of data on traffic incidents in California: 1) the Statewide Integrated Traffic Records System (SWITRS),1 managed by the California Highway Patrol (CHP), which includes post-processed data on traffic incidents leading to human injury or death; and 2) Caltrans’ Performance Measurement System (PeMS),2 which includes data on traffic incidents as well as traffic counts, lane closures, and other information. Both databases draw from CHP incident reports that describe the location, conditions, and other important details and observations surrounding each incident. Traffic safety researchers rely heavily on both databases, but each has limitations. PeMS data are limited to state highways. Incident data can take months to appear in SWITRS and may omit crucial information.

In 2015, the Road Ecology Center at UC Davis developed a web-based method to collect all incident data that appear on the CHP real-time incident-reporting website (https://cad.chp.ca.gov/). These data are assembled into a database called CHIPS, the California Highway Incident Processing System. Previous analyses suggest that these data are more spatially accurate than other state resources (e.g., the Statewide Integrated Traffic Records System (SWITRS)). Because they are collected and organized in real-time, they can also be shared and queried more easily. The current project developed a web-portal that supports queries for counties and specific highways (https://roadecology.ucdavis.edu/resources/covid19- traffic). The results shown make apparent the reduction in crashes and traffic during the summer 2020 peak of the COVID19 pandemic.

Response to lithium varies widely between individuals with bipolar disorder (BD). Polygenic risk scores (PRSs) can uncover pharmacogenomics effects and may help predict drug response. Patients (N = 2,510) with BD were assessed for long-term lithium response in the Consortium on Lithium Genetics using the Retrospective Criteria of Long-Term Treatment Response in Research Subjects with Bipolar Disorder score. PRSs for attention-deficit/hyperactivity disorder (ADHD), major depressive disorder (MDD), and schizophrenia (SCZ) were computed using lassosum and in a model including all three PRSs and other covariates, and the PRS of ADHD (β = -0.14; 95% confidence interval [CI]: -0.24 to -0.03; p value = 0.010) and MDD (β = -0.16; 95% CI: -0.27 to -0.04; p value = 0.005) predicted worse quantitative lithium response. A higher SCZ PRS was associated with higher rates of medication nonadherence (OR = 1.61; 95% CI: 1.34-1.93; p value = 2e-7). This study indicates that genetic risk for ADHD and depression may influence lithium treatment response. Interestingly, a higher SCZ PRS was associated with poor adherence, which can negatively impact treatment response. Incorporating genetic risk of ADHD, depression, and SCZ in combination with clinical risk may lead to better clinical care for patients with BD.

Marine low clouds play an important role in the climate system, and their properties are sensitive to cloud condensation nuclei concentrations. While new particle formation represents a major source of cloud condensation nuclei globally, the prevailing view is that new particle formation rarely occurs in remote marine boundary layer over open oceans. Here we present evidence of the regular and frequent occurrence of new particle formation in the upper part of remote marine boundary layer following cold front passages. The new particle formation is facilitated by a combination of efficient removal of existing particles by precipitation, cold air temperatures, vertical transport of reactive gases from the ocean surface, and high actinic fluxes in a broken cloud field. The newly formed particles subsequently grow and contribute substantially to cloud condensation nuclei in the remote marine boundary layer and thereby impact marine low clouds.

Lithium is the gold standard therapy for Bipolar Disorder (BD) but its effectiveness differs widely between individuals. The molecular mechanisms underlying treatment response heterogeneity are not well understood, and personalized treatment in BD remains elusive. Genetic analyses of the lithium treatment response phenotype may generate novel molecular insights into lithium's therapeutic mechanisms and lead to testable hypotheses to improve BD management and outcomes. We used fixed effect meta-analysis techniques to develop meta-analytic polygenic risk scores (MET-PRS) from combinations of highly correlated psychiatric traits, namely schizophrenia (SCZ), major depression (MD) and bipolar disorder (BD). We compared the effects of cross-disorder MET-PRS and single genetic trait PRS on lithium response. For the PRS analyses, we included clinical data on lithium treatment response and genetic information for n = 2283 BD cases from the International Consortium on Lithium Genetics (ConLi+Gen; www.ConLiGen.org ). Higher SCZ and MD PRSs were associated with poorer lithium treatment response whereas BD-PRS had no association with treatment outcome. The combined MET2-PRS comprising of SCZ and MD variants (MET2-PRS) and a model using SCZ and MD-PRS sequentially improved response prediction, compared to single-disorder PRS or to a combined score using all three traits (MET3-PRS). Patients in the highest decile for MET2-PRS loading had 2.5 times higher odds of being classified as poor responders than patients with the lowest decile MET2-PRS scores. An exploratory functional pathway analysis of top MET2-PRS variants was conducted. Findings may inform the development of future testing strategies for personalized lithium prescribing in BD.

AimTo examine individual variability between perceived physical features and hormones of pubertal maturation in 9-10-year-old children as a function of sociodemographic characteristics.MethodsCross-sectional metrics of puberty were utilized from the baseline assessment of the Adolescent Brain Cognitive Development (ABCD) Study-a multi-site sample of 9-10 year-olds (n = 11,875)-and included perceived physical features via the pubertal development scale (PDS) and child salivary hormone levels (dehydroepiandrosterone and testosterone in all, and estradiol in females). Multi-level models examined the relationships among sociodemographic measures, physical features, and hormone levels. A group factor analysis (GFA) was implemented to extract latent variables of pubertal maturation that integrated both measures of perceived physical features and hormone levels.ResultsPDS summary scores indicated more males (70%) than females (31%) were prepubertal. Perceived physical features and hormone levels were significantly associated with child's weight status and income, such that more mature scores were observed among children that were overweight/obese or from households with low-income. Results from the GFA identified two latent factors that described individual differences in pubertal maturation among both females and males, with factor 1 driven by higher hormone levels, and factor 2 driven by perceived physical maturation. The correspondence between latent factor 1 scores (hormones) and latent factor 2 scores (perceived physical maturation) revealed synchronous and asynchronous relationships between hormones and concomitant physical features in this large young adolescent sample.ConclusionsSociodemographic measures were associated with both objective hormone and self-report physical measures of pubertal maturation in a large, diverse sample of 9-10 year-olds. The latent variables of pubertal maturation described a complex interplay between perceived physical changes and hormone levels that hallmark sexual maturation, which future studies can examine in relation to trajectories of brain maturation, risk/resilience to substance use, and other mental health outcomes.

The large concentrations of ultrafine particles consistently observed at high altitudes over the tropics represent one of the world's largest aerosol reservoirs, which may be providing a globally important source of cloud condensation nuclei. However, the sources and chemical processes contributing to the formation of these particles remain unclear. Here we investigate new particle formation (NPF) mechanisms in the Amazon free troposphere by integrating insights from laboratory measurements, chemical transport modeling, and field measurements. To account for organic NPF, we develop a comprehensive model representation of the temperature-dependent formation chemistry and thermodynamics of extremely low volatility organic compounds as well as their roles in NPF processes. We find that pure-organic NPF driven by natural biogenic emissions dominates in the uppermost troposphere above 13 km and accounts for 65 to 83% of the column total NPF rate under relatively pristine conditions, while ternary NPF involving organics and sulfuric acid dominates between 8 and 13 km. The large organic NPF rates at high altitudes mainly result from decreased volatility of organics and increased NPF efficiency at low temperatures, somewhat counterbalanced by a reduced chemical formation rate of extremely low volatility organic compounds. These findings imply a key role of naturally occurring organic NPF in high-altitude preindustrial environments and will help better quantify anthropogenic aerosol forcing from preindustrial times to the present day.

Lithium remains the gold standard for the treatment of bipolar disorder (BD); however, its use has declined over the years mainly due to the side effects and the subjective experience of cognitive numbness reported by patients. In the present study, we aim to methodically test the effects of lithium on neurocognitive functioning in the largest single cohort (n = 262) of BD patients reported to date by harnessing the power of a multi-site, ongoing clinical trial of lithium monotherapy. At the cross-sectional level, multivariate analysis of covariance (MANCOVA) was conducted to examine potential group differences across neurocognitive tests [California Verbal Learning Test (CVLT trials 1-5,CVLT delayed recall), Wechsler Digit Symbol, Trail-making Test parts A and B (TMT-A; TMT-B), and a global cognition index]. At the longitudinal level, on a subset of patients (n = 88) who achieved mood stabilization with lithium monotherapy, we explored the effect of lithium treatment across time on neurocognitive functioning. There were no differences at baseline between BD patients that were taking lithium compared with those that were not. At follow-up a significant neurocognitive improvement in the global cognitive index score [F = 31.69; p

There are two official sources of data on traffic incidents in California: 1) the Statewide Integrated Traffic Records System (SWITRS), intended to include incidents leading to injury or death; and 2) the California Highway Patrol (CHP) data on Caltrans’ Performance Measurement System, PeMS. Traffic safety researchers rely heavily on the post-processed SWITRS database, which provides only some crucial information about crashes. In 2015, the Road Ecology Center at UC Davis developed a third method to collect all incident data that appear on the CHP real-time incident-reporting web-site (https://cad.chp.ca.gov/). These data are assembled into a database called CHIPS, for California Highway Incident Processing System. Analyses indicate that the number of incidents recorded in a given period are similar in CHIPS and SWITRS but lower in PeMS. Also, many SWITRS records (e.g., 36% in 2018), but no CHIPS records, lack or have inaccurate location information on incidents. Through case studies, the research group examined three ways that CHIPS can be used to support data and policy analysis. This report proposes future pathways for creating a more integrated system for collecting and analyzing crashes.

As roads and other developed land uses proliferate, the resulting habitat fragmentation and loss of wildlife connectivity hinder animals’ ability to forage, establish new territories, and maintain genetic diversity. Wildlife crossing structures such as culverts and bridges theoretically can reduce these impacts by allowing species to effectively cross highways. However, previous research has shown that traffic presence and density can disrupt wildlife use of highway crossing structures, and that noise and light from human activities can affect animal behavior. Researchers at the University of California, Davis, Road Ecology Center measured traffic noise and light levels and placed motion- and heat-triggered cameras at 26 bridges and culverts along four interstate highways, 11 state highways and one major county road across California. The presence and behavior of animals at these highway crossing structures were compared to those detected at sites unaffected by roads to understand the effects of noise and light from a highway on wildlife behavior. This policy brief summarizes findings from that research and provides policy implications.View the NCST Project Webpage

Organic aerosol (OA) constitutes a significant fraction of atmospheric fine particle mass. However, the precursors and chemical processes responsible for a majority of OA are rarely conclusively identified. We use online observations of hundreds of simultaneously measured molecular components obtained from 15 laboratory OA formation experiments with constraints on their effective saturation vapor concentrations to attribute the VOC precursors and subsequent chemical pathways giving rise to the vast majority of OA mass measured in two forested regions. We find that precursors and chemical pathways regulating OA composition and volatility are dynamic over hours to days, with their variations driven by coupled interactions between multiple oxidants. The extent of physical and photochemical aging, and its modulation by NOx, were key to a uniquely comprehensive combined composition-volatility description of OA. Our findings thus provide some of the most complete mechanistic-level guidance to the development of OA descriptions in air quality and Earth system models.

Wildlife-vehicle conflict (WVC) occurs when traffic coincides with a place where animals decide to cross the surface of a roadway. State departments of transportation have a consistent need to understand rates and locations of WVC but inconsistent access to tools to measure statistical significance of clusters of WVC which could need mitigation. This research brief summarizes the findings from the associated project, the objective of which was to develop a standard method for analyzing WVC “hotspots” (areas of concern) that any state could use to identify potential locations for WVC mitigation.

Creating and maintaining sustainable transportation systems depends in part on understanding and mitigating ecological impacts. Wildlife crossing structures (WCS) are often used to mitigate impacts on wildlife populations. WCS and existing structures may provide passage for multiple species, depending on their sensitivity to traffic disturbance and perception of the roadway. In a previous project, the research team found that traffic conditions and traffic noise could reduce WCS effectiveness in facilitating passage of diverse and sensitive species. In the current project, they expanded the geographic scope to 26 sites throughout California, including detailed measurements of vehicle noise and lighting impacts on wildlife use of structures. They investigated individual animal behavior as the animals approached structures as a possible mechanism for reducing species diversity due to traffic disturbance. In order to inform future WCS planning, placement and construction, the team studied traffic noise and light impacts on wildlife in the vicinity of the proposed Liberty Canyon wildlife over-crossing (over US 101), the first and largest of its kind in California. They improved a preliminary statistical model of the effects of traffic on WCS use of existing structures. The authors recommend strategies for transportation agencies to use in developing and modifying WCS to improve wildlife passage.View the NCST Project Webpage

AimTo examine individual variability between perceived physical features and hormones of pubertal maturation in 9-10-year-old children as a function of sociodemographic characteristics.MethodsCross-sectional metrics of puberty were utilized from the baseline assessment of the Adolescent Brain Cognitive Development (ABCD) Study-a multi-site sample of 9-10 year-olds (n = 11,875)-and included perceived physical features via the pubertal development scale (PDS) and child salivary hormone levels (dehydroepiandrosterone and testosterone in all, and estradiol in females). Multi-level models examined the relationships among sociodemographic measures, physical features, and hormone levels. A group factor analysis (GFA) was implemented to extract latent variables of pubertal maturation that integrated both measures of perceived physical features and hormone levels.ResultsPDS summary scores indicated more males (70%) than females (31%) were prepubertal. Perceived physical features and hormone levels were significantly associated with child's weight status and income, such that more mature scores were observed among children that were overweight/obese or from households with low-income. Results from the GFA identified two latent factors that described individual differences in pubertal maturation among both females and males, with factor 1 driven by higher hormone levels, and factor 2 driven by perceived physical maturation. The correspondence between latent factor 1 scores (hormones) and latent factor 2 scores (perceived physical maturation) revealed synchronous and asynchronous relationships between hormones and concomitant physical features in this large young adolescent sample.ConclusionsSociodemographic measures were associated with both objective hormone and self-report physical measures of pubertal maturation in a large, diverse sample of 9-10 year-olds. The latent variables of pubertal maturation described a complex interplay between perceived physical changes and hormone levels that hallmark sexual maturation, which future studies can examine in relation to trajectories of brain maturation, risk/resilience to substance use, and other mental health outcomes.

Abstract Stony coral tissue loss disease (SCTLD) has been causing significant whole colony mortality on reefs in Florida and the Caribbean. The cause of SCTLD remains unknown, with the limited concurrence of SCTLD-associated bacteria among studies. We conducted a meta-analysis of 16S ribosomal RNA gene datasets generated by 16 field and laboratory SCTLD studies to find consistent bacteria associated with SCTLD across disease zones (vulnerable, endemic, and epidemic), coral species, coral compartments (mucus, tissue, and skeleton), and colony health states (apparently healthy colony tissue (AH), and unaffected (DU) and lesion (DL) tissue from diseased colonies). We also evaluated bacteria in seawater and sediment, which may be sources of SCTLD transmission. Although AH colonies in endemic and epidemic zones harbor bacteria associated with SCTLD lesions, and aquaria and field samples had distinct microbial compositions, there were still clear differences in the microbial composition among AH, DU, and DL in the combined dataset. Alpha-diversity between AH and DL was not different; however, DU showed increased alpha-diversity compared to AH, indicating that, prior to lesion formation, corals may undergo a disturbance to the microbiome. This disturbance may be driven by Flavobacteriales, which were especially enriched in DU. In DL, Rhodobacterales and Peptostreptococcales–Tissierellales were prominent in structuring microbial interactions. We also predict an enrichment of an alpha-toxin in DL samples which is typically found in Clostridia. We provide a consensus of SCTLD-associated bacteria prior to and during lesion formation and identify how these taxa vary across studies, coral species, coral compartments, seawater, and sediment.