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Background: Stealth assessment is a learning analytics method, which leverages the collection and analysis of learners' interaction data to make real-time inferences about their learning. Employed in digital learning environments, stealth assessment helps researchers, educators, and teachers evaluate learners' competencies and customize the learning experience to their specific needs. This adaptability is closely intertwined with theories related to learning, engagement, and motivation. The foundation of stealth assessment rests on evidence-cantered design (ECD), consisting of four core models: the Competency Model (CM), Evidence Model, Task Model, and Assembly Model. Objective: The first step in designing a stealth assessment entails producing operational definitions of the constructs to be assessed. The CM establishes a framework of latent variables representing the target constructs, as well as their interrelations. When developing the CM, assessment designers must produce clear descriptions of the claims associated with the latent variables and their states, as well as sketch out how the competencies can be measured using assessment tasks. As the designers elaborate on the assessment model, the CM definitions need to be revisited to make sure they work with the scope and constraints of the assessment. Although this is the first step, problems at this stage may result in an assessment that does not meet the intended purpose. The objective of this paper is to elucidate the necessary steps for CM development and to highlight potential challenges in the process, along with strategies for addressing them, particularly for designers without much formal assessment experience. Method: This paper is a methodological exposition, showcasing five examples of CM development. Specifically, we conducted a qualitative retrospective analysis of the CM development procedure, wherein participants unfamiliar with ECD applied the framework and showcased their work. In a stealth assessment course, four groups of students (novice stealth assessment designers) engaged in developing stealth assessments for challenging-to-measure constructs across four distinct projects. During their CM development process, we observed various activities to pinpoint areas of difficulty. Results: This paper presents five illustrative examples, including one for assessing physics understanding and four for the development of CMs for four complex competencies: (1) systems thinking, (2) online information credibility evaluation, (3) computational thinking, and (4) collaborative creativity. Each example represents a case in CM development, offering valuable insights. Conclusion: The paper concludes by discussing several guidelines derived from the examples discussed. Emphasizing the importance of dedicating ample time to fine-tune CMs can significantly enhance the accuracy of assessments related to learners' knowledge and skills. It underscores the significance of qualitative phases in crafting comprehensive stealth assessments, such as CMs, alongside the quantitative statistical modeling and technical aspects of these assessments.

The tokamak approach, utilizing a toroidal magnetic field configuration to confine a hot plasma, is one of the most promising designs for developing reactors that can exploit nuclear fusion to generate electrical energy1,2. To reach the goal of an economical reactor, most tokamak reactor designs3-10 simultaneously require reaching a plasma line-averaged density above an empirical limit-the so-called Greenwald density11-and attaining an energy confinement quality better than the standard high-confinement mode12,13. However, such an operating regime has never been verified in experiments. In addition, a long-standing challenge in the high-confinement mode has been the compatibility between a high-performance core and avoiding large, transient edge perturbations that can cause very high heat loads on the plasma-facing-components in tokamaks. Here we report the demonstration of stable tokamak plasmas with a line-averaged density approximately 20% above the Greenwald density and an energy confinement quality of approximately 50% better than the standard high-confinement mode, which was realized by taking advantage of the enhanced suppression of turbulent transport granted by high density-gradients in the high-poloidal-beta scenario14,15. Furthermore, our experimental results show an integration of very low edge transient perturbations with the high normalized density and confinement core. The operating regime we report supports some critical requirements in many fusion reactor designs all over the world and opens a potential avenue to an operating point for producing economically attractive fusion energy.

Social media has the unique capacity to expose many learners to media literacy instruction "via" targeted campaigns. Investigating learner engagement and reaction to these efforts may be a fruitful endeavor for researchers that can inform the design of future campaigns. However, the massive datasets associated with social media posts are difficult, and often impossible, to analyze with traditional qualitative methods. This study seeks to address this problem by leveraging machine learning techniques to collect and analyze Big Data from two different media literacy campaigns on the youth-oriented social media platform TikTok. Specifically, we explore the ways topic modeling, sentiment analysis, and network analysis can provide insight into learner engagement with these campaigns and discuss limitations and implications for stakeholders interested in utilizing these approaches.

The majority of oncogenic drivers are intracellular proteins, constraining their immunotherapeutic targeting to mutated peptides (neoantigens) presented by individual human leukocyte antigen (HLA) allotypes1. However, most cancers have a modest mutational burden that is insufficient for generating responses using neoantigen-based therapies2,3. Neuroblastoma is a paediatric cancer that harbours few mutations and is instead driven by epigenetically deregulated transcriptional networks4. Here we show that the neuroblastoma immunopeptidome is enriched with peptides derived from proteins essential for tumorigenesis. We focused on targeting the unmutated peptide QYNPIRTTF discovered on HLA-A*24:02, which is derived from the neuroblastoma-dependency gene and master transcriptional regulator PHOX2B. To target QYNPIRTTF, we developed peptide-centric chimeric antigen receptors (PC-CARs) through a counter panning strategy using predicted potentially cross-reactive peptides. We further proposed that PC-CARs can recognize peptides on additional HLA allotypes when presenting a similar overall molecular surface. Informed by our computational modelling results, we show that PHOX2B PC-CARs also recognize QYNPIRTTF presented by HLA-A*23:01, the most common non-A2 allele in people with African ancestry. Finally, we demonstrate potent and specific killing of neuroblastoma cells expressing these HLAs in vitro and complete tumour regression in mice. These data suggest that PC-CARs have the potential to expand the pool of immunotherapeutic targets to include non-immunogenic intracellular oncoproteins and allow targeting through additional HLA allotypes in a clinical setting.

Endometriosis is a chronic disease characterized by the presence and growth of endometrial glands and stroma outside of the uterine cavity. The pathogenesis is unclear, but a common theory attributes the condition to retrograde menstruation into the peritoneal cavity via the fallopian tubes. Hormonal influence causes these ectopic tissues to undergo cyclical bleeding, resulting in subsequent inflammation and scar tissue formation; however, it can affect postmenopausal women. In rare instances, endometriotic lesions can obstruct the ureter and result in hydroureteronephrosis and subsequent loss of renal function. This condition presents with nonspecific symptoms and is known as an often-silent disease, resulting in challenging and delayed preoperative diagnosis. In this article, we report the case of an asymptomatic 65-year old female who was diagnosed with deep pelvic endometriosis, which obstructed the right distal ureter. We focus on optimizing diagnosis and management through the application of radiological imaging modalities, specifically computed tomography (CT) and magnetic resonance imaging (MRI).

Abstract Plants possess cell surface-localized immune receptors that detect microbe-associated molecular patterns (MAMPs) and initiate defenses that provide effective resistance against microbial pathogens. Many MAMP-induced signaling pathways and cellular responses are known, yet how pattern-triggered immunity (PTI) limits pathogen growth in plants is poorly understood. Through a combined metabolomics and genetics approach, we discovered that plant-exuded proline is a virulence-inducing signal and nutrient for the bacterial pathogen Pseudomonas syringae, and that MAMP-induced depletion of proline from the extracellular spaces of Arabidopsis leaves directly contributes to PTI against P. syringae. We further show that MAMP-induced depletion of extracellular proline requires the amino acid transporter Lysine Histidine Transporter 1 (LHT1). This study demonstrates that depletion of a single extracellular metabolite is an effective component of plant induced immunity. Given the important role for amino acids as nutrients for microbial growth, their depletion at sites of infection may be a broadly effective means for defense against many pathogens.

Adrenal schwannoma is a rare tumor of Schwann cell origin that represents less than 0.2% of all adrenal tumors. These typically benign tumors are most often found in the head, neck, and limbs. However, schwannomas can also rarely occur rarely in the adrenal gland within the retroperitoneal cavity. In the adrenal gland, these tumors arise from the medulla and are difficult to diagnose, often misdiagnosed as other benign or malignant entities. In this article, we report the case of a 43-year-old female with a large left adrenal mass revealed by biopsy to be a schwannoma. We focus on the use of radiological imaging modalities and immunohistochemical analysis to optimize diagnosis and treatment intervention of this rare tumor.

Previous studies have evaluated method performance for quantifying and characterizing microplastics in clean water, but little is known about the efficacy of procedures used to extract microplastics from complex matrices. Here we provided 15 laboratories with samples representing four matrices (i.e., drinking water, fish tissue, sediment, and surface water) each spiked with a known number of microplastic particles spanning a variety of polymers, morphologies, colors, and sizes. Percent recovery (i.e., accuracy) in complex matrices was particle size dependent, with ∼60-70% recovery for particles >212 μm, but as little as 2% recovery for particles

Agrobacteria are a diverse, polyphyletic group of prokaryotes with multipartite genomes capable of transferring DNA into the genomes of host plants, making them an essential tool in plant biotechnology. Despite their utility in plant transformation, genome-wide transcriptional regulation is not well understood across the three main lineages of agrobacteria. Transcription start sites (TSSs) are a necessary component of gene expression and regulation. In this study, we used differential RNA-seq and a TSS identification algorithm optimized on manually annotated TSS, then validated with existing TSS to identify thousands of TSS with nucleotide resolution for representatives of each lineage. We extend upon the 356 TSSs previously reported in Agrobacterium fabrum C58 by identifying 1,916 TSSs. In addition, we completed genomes and phenotyping of Rhizobium rhizogenes C16/80 and Allorhizobium vitis T60/94, identifying 2,650 and 2,432 TSSs, respectively. Parameter optimization was crucial for an accurate, high-resolution view of genome and transcriptional dynamics, highlighting the importance of algorithm optimization in genome-wide TSS identification and genomics at large. The optimized algorithm reduced the number of TSSs identified internal and antisense to the coding sequence on average by 90.5% and 91.9%, respectively. Comparison of TSS conservation between orthologs of the three lineages revealed differences in cell cycle regulation of ctrA as well as divergence of transcriptional regulation of chemotaxis-related genes when grown in conditions that simulate the plant environment. These results provide a framework to elucidate the mechanistic basis and evolution of pathology across the three main lineages of agrobacteria. IMPORTANCE Transcription start sites (TSSs) are fundamental for understanding gene expression and regulation. Agrobacteria, a group of prokaryotes with the ability to transfer DNA into the genomes of host plants, are widely used in plant biotechnology. However, the genome-wide transcriptional regulation of agrobacteria is not well understood, especially in less-studied lineages. Differential RNA-seq and an optimized algorithm enabled identification of thousands of TSSs with nucleotide resolution for representatives of each lineage. The results of this study provide a framework for elucidating the mechanistic basis and evolution of pathology across the three main lineages of agrobacteria. The optimized algorithm also highlights the importance of parameter optimization in genome-wide TSS identification and genomics at large.

The capacity of beneficial microbes to compete for host infection-and the ability of hosts to discriminate among them-introduces evolutionary conflict that is predicted to destabilize mutualism. We investigated fitness outcomes in associations between legumes and their symbiotic rhizobia to characterize fitness impacts of microbial competition. Diverse Bradyrhizobium strains varying in their capacity to fix nitrogen symbiotically with a common host plant, Acmispon strigosus, were tested in full-factorial coinoculation experiments involving 28 pairwise strain combinations. We analyzed the effects of interstrain competition and host discrimination on symbiotic-interaction outcomes by relativizing fitness proxies to clonally infected and uninfected controls. More than one thousand root nodules of coinoculated plants were genotyped to quantify strain occupancy, and the Bradyrhizobium strain genome sequences were analyzed to uncover the genetic bases of interstrain competition outcomes. Strikingly, interstrain competition favored a fast-growing, minimally beneficial rhizobia strain. Host benefits were significantly diminished in coinoculation treatments relative to expectations from clonally inoculated controls, consistent with competitive interference among rhizobia that reduced both nodulation and plant growth. Competition traits appear polygenic, linked with inter-strain allelopathic interactions in the rhizosphere. This study confirms that competition among strains can destabilize mutualism by favoring microbes that are superior in colonizing host tissues but provide minimal benefits to host plants. Moreover, our findings help resolve the paradox that despite efficient host control post infection, legumes nonetheless encounter rhizobia that vary in their nitrogen fixation.

Introduction Medications for opioid use disorder (MOUD) are the most effective interventions for this condition, yet many patients discontinue treatment. Though adjunct psychosocial treatments are recommended to increase retention and reduce relapse, the scarcity of trained providers hinders access to and utilization of evidence-based interventions. We conducted a Phase 1 study to assess the feasibility of a virtual reality-delivered Mindfulness-Oriented Recovery Enhancement (MORE-VR) intervention for patients receiving MOUD.Patients and Methods Patients receiving buprenorphine or methadone for OUD (N = 34) were scheduled for 8 weekly sessions of MORE-VR. Enrollment and retention rates were analyzed. Participants reported on the usability and acceptability of MORE-VR, opioid use, and craving and affect before and after each VR session. Heart rate was monitored during one session of MORE-VR.Results Twenty-three participants completed four or more MORE-VR sessions (minimum recommended intervention dose). Participants reported high usability and acceptability of MORE-VR, which had an excellent safety profile. Illicit opioid use decreased significantly from pre- to post-treatment (F = 4.44, p=.04). We observed a significant within-session decrease in opioid craving (F = 39.3, p

Sclerosing epithelioid fibrosarcoma is a rare fibrosarcoma variant in which more than half of patients experience local recurrence or metastatic spread. In the current literature, there is limited and nonspecific imaging data, contributing to frequent misdiagnosis and delays in treatment intervention. Given the poor prognosis associated with this malignancy and the high probability of metastases, accurate and prompt diagnoses are critical. In this article, we report the case of a 27-year-old female diagnosed with metastatic sclerosing epithelioid fibrosarcoma following the discovery of a growing palpable mass on her right gluteus maximus muscle. We focus on the use of radiological imaging modalities in optimizing diagnosis and correlate our imaging and pathological findings.

A plasmacytoma is a cancerous growth of abnormal plasma cells that arise within osseous or soft tissue structures. In soft tissue structures, plasmacytomas can present as solitary or multiple masses in the absence of systemic involvement. Solitary plasmacytomas can be subcategorized as extramedullary plasmacytoma (derived from plasma cells located in soft tissues) or osseous plasmacytoma (derived from plasma cells located in the bone marrow). Infrequently, these tumors can arise as extramedullary lesions from the pancreas and present similarly to other tumors, such as pancreatic neuroendocrine tumors (PNETs). In this article, we report the case of a 62-year-old male with a diagnosis of solitary plasmacytoma of the pancreas. We focus on optimizing diagnosis and management through the application of radiological imaging modalities, specifically computed tomography (CT) scans and positron emission tomography-computed tomography (PET-CT) scans.

Liposarcomas are infrequent malignant tumors of mesenchymal origin most commonly seen in the extremities. Although infrequent, these can develop as primary lesions in the soft tissue of the kidney, making them difficult to diagnose through imaging modalities alone. Primary renal liposarcomas are associated with poor prognoses, increasing the importance of timely and accurate diagnosis. In extremely rare instances, the tumor can arise directly from the fat in the epicenter of the kidney, disguised as an angiomyolipoma. In this article, we report the case of a 54-year-old female who was diagnosed with a well-differentiated liposarcoma of the kidney and underwent radical nephrectomy. Our objective is to evaluate unique radiological imaging findings and correlate with histopathological analysis to optimize diagnosis