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From late spring of 2020 to the present, the U.S. educational conversation about learning in K-12 public schools during the pandemic has been about the fact that students did not learn as much, widening the achievement gap due to digital learning. Some K-12 public schools and school districts have reported no learning loss. This exploratory study examined elements shared by teachers, administrators, and parents that accounted for potential reasons why these individual K-12 public school districts did not experience the learning loss during digital learning that has been at the center stage of the narrative about educational experiences during the pandemic. Analysis of the results showed four elements that were central to these school districts' experiences: having an instructional framework; determining a clear pedagogical function; connecting technology to the pedagogical function; capitalizing on formative assessments. Data also revealed that the participants tended to believe that a focus on pedagogy before technology integration was crucial.

The aim of the study was to analyze and assess the possibility of using a two-stage filtration system with ceramic membranes: a 3-tube module with 1.0 kDa cut-off (1st stage) and a one-tube module with 0.45 kDa cut-off (2nd stage) for treating effluent water from a juvenile African catfish aquaculture. The study revealed that during the 1st filtration stage of the effluent water, the highest degrees of retention were obtained with respect to: suspended solids SS (rejection coefficient RI=100%), turbidity (RI=99.40%), total iron (RI=89.20%), BOD5 (RI=76.0%), nitrite nitrogen (RI=62.30%), and CODCr (RI=41.74%). The 2nd filtration stage resulted in a lower reduction degree of the tested indicators in comparison to the 1st filtration stage. At the 2nd stage, the highest values of the rejection coefficient were noted in for the total iron content (RIV=100%), CODCr (RIV=59.52%; RV=64.28%, RVI=63.49%) and turbidity (RIV and RV = 45.0%, RVI=50.0%). The obtained results indicate that ceramic membranes (with 1.0 and 0.45 kDa cut-offs) may be used in recirculation aquaculture systems as one of the stages of effluent water treatment.

Wilms tumors (WT) are characterized by variable contributions of blastemal, epithelial and stromal elements, reflecting their diverse cellular origins and genetic drivers. In vitro models remain rare, despite a growing need to better characterize tumor biology and evaluate new treatments. Using three approaches, we have now established a large collection of long-term cultures that represent this diversity. Adherent WT cultures are predominated by stromal cells, 3D spheroids model blastema, and patient-derived organoid cultures of both tumor and healthy kidney tissue result in the preferential growth of epithelial cells. Adherent, spheroid and organoid cultures are also clearly distinguishable by their transcriptome. Preclinical drug screening experiments revealed sensitivity to a range of inhibitors, that are highly effective in other childhood solid tumors. Sensitivity was related to MYCN status, a marker associated with adverse outcome across human cancers including WT. The combination of the three culture techniques represents a promising tool to both explore tumor heterogeneity in vitro and to facilitate characterization of candidate driver genes, in order to improve treatment regimens in the future.

Canadian Arctic residents are experiencing longer open water seasons and observing significant change in aquatic species and habitats. Rapid ecosystem change threatens Inuit people’s food security and adds to existing generational trauma caused by ongoing colonialism and industrialization. Indigenous owned environmental monitoring programs prioritize safety, support community empowerment and self-determination to increase the understanding of and resilience to the impacts of this human caused global climate crisis. To this end, in 2019 local expert fishers and hunters from the Inuvialuit Settlement Region worked collaboratively with an independent research scientist to start up community owned aquatic monitoring and observation (AMO) programs in Sachs Harbour and Ulukhaktok in the Inuvialuit Settlement Region. The field teams received training to collect year-round data of lake and coastal water quality data using scientific instruments that measure water temperature, conductivity/salinity, turbidity and dissolved oxygen with depth from the surface down to 150 meters. ROV’s, drones and hydrophones extend observations and Traditional & Local Knowledge (TLK) directs the programs. External clients can hire the teams to augment core funding. AMO teams are finalizing their program and data ownership protocols, which are informed by the Canadian UNDRIP Act and OCAP® principles. Indigenous owned, directed and operated environmental monitoring programs justly deserve funding priority and ongoing public support to help conserve and protect critical areas for future generations.

This study focuses on the initial wave of the COVID-19 pandemic in Spring 2020 in the United States to assess how liquidity constraints were related to loneliness among older adults. Data are from the COVID Impact Survey, which was used to collect data in April, May and June 2020 across the U.S. (n = 5,664). We use means comparison tests and linear regressions and find that emergency savings, rather than household income, predict loneliness among older adults during the initial COVID-19 wave. Emergency savings, especially enough to avoid using credit cards, was most predictive of older adult loneliness levels. Income and access to emergency savings did not influence the relationship between actions taken and personal plans changed as a result of COVID-19. Easing lockdown restrictions was unrelated to the relationship between loneliness and liquidity constraints, actions taken and personal plans changed due to the COVID-19 pandemic. Findings suggest that, in the early months of the COVID-19 pandemic, loneliness associated with the actions taken to avoid COVID-19 and personal plans changed was experienced across all socio-economic groups of older adults in this sample in similar ways, regardless of income levels and wealth. In addition, a better understanding of loneliness in older age during the COVID-19 pandemic may require a fuller analysis of households' financial situation beyond income, and points to the central role of credit card debt for loneliness in older age.

Summary: Background: Perivascular spaces (PVS) on brain MRI are surrogates for small parenchymal blood vessels and their perivascular compartment, and may relate to brain health. However, it is unknown whether PVS can predict dementia risk and brain atrophy trajectories in participants without dementia, as longitudinal studies on PVS are scarce and current methods for PVS assessment lack robustness and inter-scanner reproducibility. Methods: We developed a robust algorithm to automatically assess PVS count and size on clinical MRI, and investigated 1) their relationship with dementia risk and brain atrophy in participants without dementia, 2) their longitudinal evolution, and 3) their potential use as a screening tool in simulated clinical trials. We analysed 46,478 clinical measurements of cognitive functioning and 20,845 brain MRI scans from 10,004 participants (71.1 ± 9.7 years-old, 56.6% women) from three publicly available observational studies on ageing and dementia (the Alzheimer’s Disease Neuroimaging Initiative, the National Alzheimer’s Coordinating Centre database, and the Open Access Series of Imaging Studies). Clinical and MRI data collected between 2004 and 2022 were analysed with consistent methods, controlling for confounding factors, and combined using mixed-effects models. Findings: Our fully-automated method for PVS assessment showed excellent inter-scanner reproducibility (intraclass correlation coefficients >0.8). Fewer PVS and larger PVS diameter at baseline predicted higher dementia risk and accelerated brain atrophy. Longitudinal trajectories of PVS markers differed significantly in participants without dementia who converted to dementia compared with non-converters. In simulated placebo-controlled trials for treatments targeting cognitive decline, screening out participants at low risk of dementia based on our PVS markers enhanced the power of the trial independently of Alzheimer’s disease biomarkers. Interpretation: These robust cerebrovascular markers predict dementia risk and brain atrophy and may improve risk-stratification of patients, potentially reducing cost and increasing throughput of clinical trials to combat dementia. Funding: US National Institutes of Health.

Research consistently shows that solid assessment designs lead to better student learning outcomes. The development of well-designed assessments presents a challenge to preservice teachers in their attempts to master the process and to the teacher educators who instruct them. This exploratory study examined strategies for teaching assessment design utilized by 87 teacher educators in the United States. Analysis of the results showed that expository, collaborative, and hands-on approaches were used, with assessment approaches aligning to structured or unstructured approaches. Data also revealed that the participants tended to focus more on the vocabulary related to assessments rather than the strategies for design.

IntroductionAccurate models of lake primary production are crucial for understanding ecosystem function and predicting ecosystem responses to global change. However, current research in lake ecosystem modeling has emphasized environmental characteristics while less work has considered phytoplankton stoichiometric traits. Importantly, these traits link resource availability to primary production via organismal metabolism and thus are critical to predicting ecosystem function.MethodsHere, we use an existing database of phytoplankton traits and lake ecosystem models to demonstrate that phytoplankton minimum quotas for nitrogen and phosphorus significantly influence predictions of lake gross primary production. Additionally, we compare how different parameterizations of phytoplankton stoichiometry affect modeled gross primary production. Finally, we evaluate the ability of the models to capture observed patterns in gross primary production and seston stoichiometry for lakes in the Northern Hemisphere.Results and discussionWe argue that parameterization and calibration of phytoplankton stoichiometric traits will improve lake ecosystem models and are critical for obtaining better estimates of lake primary production.

Abstract African penguins are among the most threatened seabird species globally and an African Penguin Biodiversity Management Plan (BMP) published in 2013 guides conservation strategies to prevent their extinction. To counter the impact of past guano exploitation which reduced the nesting habitat of these burrowing seabirds, rendering them vulnerable to predators and extreme weather events, a suite of artificial nests was deployed in various colonies over the past decades with varying success. The BMP called for new nest designs to maximise breeding output. This study assesses African penguin breeding success over the past 14 years in four types of artificial nests and in natural nests at all major colonies in South Africa. Overall, artificial nests outperformed natural nests and successfully increased breeding output of African penguins by 16.5% (95% CI: 6.7–26.2). No design was, however, consistently most effective across locations. For example, fibreglass nests had the poorest hatching success of all nest types at one colony (Bird Island), but outperformed cement nests at another (Boulders Beach). The latest design of double‐layered ceramic nests tended to perform better than other artificial nests, although not consistently at all colonies and occupancy rates were low in some areas. Practical implication. The deployment of artificial nests proved to be a successful conservation measure for African penguins although the variety of habitats in the different colonies seems to have prevented a one solution‐fits‐all approach. The consistent poor breeding output in some areas in all nest types (

Background/Objectives: Clavicle injuries are common and seem to be frequently subject to diagnostic misclassification. The accurate identification of clavicle fractures is essential, particularly for registry and Big Data analyses. This study aims to assess the frequency of diagnostic errors in clavicle injury classifications. Methods: This retrospective study analyzed patient data from two Level 1 trauma centers, covering the period from 2008 to 2019. Included were cases with ICD-coded diagnoses of medial, midshaft, and lateral clavicle fractures, as well as sternoclavicular and acromioclavicular joint dislocations. Radiological images were re-evaluated, and discharge summaries, radiological reports, and billing codes were examined for diagnostic accuracy. Results: A total of 1503 patients were included, accounting for 1855 initial injury diagnoses. In contrast, 1846 were detected upon review. Initially, 14.4% of cases were coded as medial clavicle fractures, whereas only 5.2% were confirmed. The misclassification rate was 82.8% for initial medial fractures (p < 0.001), 42.5% for midshaft fractures (p < 0.001), and 34.2% for lateral fractures (p < 0.001). Billing codes and discharge summaries were the most error-prone categories, with error rates of 64% and 36% of all misclassified cases, respectively. Over three-quarters of the cases with discharge summary errors also exhibited errors in other categories, while billing errors co-occurred with other category errors in just over half of the cases (p < 0.001). The likelihood of radiological diagnostic error increased with the number of imaging modalities used, from 19.7% with a single modality to 30.5% with two and 40.7% with three. Conclusions: Our findings indicate that diagnostic misclassification of clavicle fractures is common, particularly between medial and midshaft fractures, often resulting from errors in multiple categories. Further prospective studies are needed, as accurate classification is foundational for the reliable application of Big Data and AI-based analyses in clinical research.

The identification of occupied habitat is an important component of recovery efforts for threatened and endangered species. The western population of the Yellow-billed Cuckoo ( Coccyzus americanus ), federally listed as a threatened distinct population segment, has long been considered a riparian-obligate, yet recent survey efforts in southeastern Arizona have documented cuckoos occurring in xeroriparian habitat during the nesting season. We investigated the distribution and breeding status of cuckoos in southeastern Arizona xeroriparian habitat by comparing the results of standardized call-playback surveys to the results of nest searching efforts in the same sites from 2018 to 2020. We then used this information to interpret more extensive survey data from 2013 to 2020 and develop an updated breeding distribution map for southeastern Arizona. We confirmed breeding in 94% of sites categorized as occupied according to survey results. Combining our data with previous survey data, we estimated a minimum of 100 occupied sites in southeastern Arizona xeroriparian habitat, representing a substantial increase in the known breeding population in Arizona. Occupied sites were concentrated in southern and western “Sky Island” mountain and foothill drainages, from 600–1800 m, with xeroriparian vegetation in a matrix of Madrean-evergreen woodland, semi-desert grassland, or desert scrub. Breeding by cuckoos in southeastern Arizona xeroriparian habitat is important for cuckoo conservation, but this habitat also faces potential threats from grazing, climate change, and development.

Multiband superconductivity plays an important role in many emergent novel superconductors and has attracted great interest over the years. Various related experimental aspects have been intensely researched, but a quantitative understanding on the Cooper-pair transport remains still elusive, despite its fundamental and technological importance. We study a Josephson junction with a scanning tunneling microscope (STM), where both tip and sample are Pb, a prototypical type I two-band superconductor. We map the properties of the junction across a wide range of normal state conductances revealing in-gap features originating from multiple Andreev reflections (MARs) and the Josephson effect. We present the theoretical framework to extract the transmission through the transport channels and describe the Cooper-pair tunneling with quantitative precision through two superconducting bands. This paves the way for the understanding of increasingly complicated superconductors.