Imaging approach to ingested foreign bodies in the neck.

Foreign body ingestion is a common clinical occurrence worldwide, with high morbidity in the pediatric population and in adult patients with intentional attempts. Coins and button battery ingestions are more common among children. Bone impaction and swallowed dentures are usually seen in older adults. While most ingested foreign bodies pass through the gastrointestinal tract spontaneously with no complications, some require endoscopic and/or surgical intervention. Complications such as pharyngoesophageal ulceration, perforation, stricture, and deep neck infection can develop without timely diagnosis and management. The purpose of this article is to familiarize radiologists with the imaging approach to assess for characteristics and impacted locations of ingested foreign bodies in the neck.

Positive Selection Drives Preferred Segment Combinations during Influenza Virus Reassortment.

Influenza A virus (IAV) has a segmented genome that allows for the exchange of genome segments between different strains. This reassortment accelerates evolution by breaking linkage, helping IAV cross species barriers to potentially create highly virulent strains. Challenges associated with monitoring the process of reassortment in molecular detail have limited our understanding of its evolutionary implications. We applied a novel deep sequencing approach with quantitative analysis to assess the in vitro temporal evolution of genomic reassortment in IAV. The combination of H1N1 and H3N2 strains reproducibly generated a new H1N2 strain with the hemagglutinin and nucleoprotein segments originating from H1N1 and the remaining six segments from H3N2. By deep sequencing the entire viral genome, we monitored the evolution of reassortment, quantifying the relative abundance of all IAV genome segments from the two parent strains over time and measuring the selection coefficients of the reassorting segments. Additionally, we observed several mutations coemerging with reassortment that were not found during passaging of pure parental IAV strains. Our results demonstrate how reassortment of the segmented genome can accelerate viral evolution in IAV, potentially enabled by the emergence of a small number of individual mutations.

TRIM13 is a negative regulator of MDA5-mediated type I interferon production.

UNLABELLED: Retinoic acid-inducible gene I (RIG-I) and melanoma differentiation-associated gene 5 (MDA5) are essential intracellular detectors of viral RNA. They contribute to the type I interferon (IFN) response that is crucial for host defense against viral infections. Given the potent antiviral and proinflammatory activities elicited by the type I IFNs, induction of the type I IFN response is tightly regulated. Members of the tripartite motif (TRIM) family of proteins have recently emerged as key regulators of antiviral immunity. We show that TRIM13, an E3 ubiquitin ligase, is expressed in immune cells and is upregulated in bone marrow-derived macrophages upon stimulation with inducers of type I IFN. TRIM13 interacts with MDA5 and negatively regulates MDA5-mediated type I IFN production in vitro, acting upstream of IFN regulatory factor 3. We generated Trim13(-/-) mice and show that upon lethal challenge with encephalomyocarditis virus (EMCV), which is sensed by MDA5, Trim13(-/-) mice produce increased amounts of type I IFNs and survive longer than wild-type mice. Trim13(-/-) murine embryonic fibroblasts (MEFs) challenged with EMCV or poly(I · C) also show a significant increase in beta IFN (IFN-ß) levels, but, in contrast, IFN-ß responses to the RIG-I-detected Sendai virus were diminished, suggesting that TRIM13 may play a role in positively regulating RIG-I function. Together, these results demonstrate that TRIM13 regulates the type I IFN response through inhibition of MDA5 activity and that it functions nonredundantly to modulate MDA5 during EMCV infection. IMPORTANCE: The type I interferon (IFN) response is crucial for host defense against viral infections, and proper regulation of this pathway contributes to maintaining immune homeostasis. Retinoic acid-inducible gene I (RIG-I) and melanoma differentiation-associated gene 5 (MDA5) are intracellular detectors of viral RNA that induce the type I IFN response. In this study, we show that expression of the gene tripartite motif 13 (Trim13) is upregulated in response to inducers of type I IFN and that TRIM13 interacts with both MDA5 and RIG-I in vitro. Through the use of multiple in vitro and in vivo model systems, we show that TRIM13 is a negative regulator of MDA5-mediated type I IFN production and may also impact RIG-I-mediated type I IFN production by enhancing RIG-I activity. This places TRIM13 at a key junction within the viral response pathway and identifies it as one of the few known modulators of MDA5 activity.

AI-based differential diagnosis of dementia etiologies on multimodal data.

Differential diagnosis of dementia remains a challenge in neurology due to symptom overlap across etiologies, yet it is crucial for formulating early, personalized management strategies. Here, we present an artificial intelligence (AI) model that harnesses a broad array of data, including demographics, individual and family medical history, medication use, neuropsychological assessments, functional evaluations and multimodal neuroimaging, to identify the etiologies contributing to dementia in individuals. The study, drawing on 51,269 participants across 9 independent, geographically diverse datasets, facilitated the identification of 10 distinct dementia etiologies. It aligns diagnoses with similar management strategies, ensuring robust predictions even with incomplete data. Our model achieved a microaveraged area under the receiver operating characteristic curve (AUROC) of 0.94 in classifying individuals with normal cognition, mild cognitive impairment and dementia. Also, the microaveraged AUROC was 0.96 in differentiating the dementia etiologies. Our model demonstrated proficiency in addressing mixed dementia cases, with a mean AUROC of 0.78 for two co-occurring pathologies. In a randomly selected subset of 100 cases, the AUROC of neurologist assessments augmented by our AI model exceeded neurologist-only evaluations by 26.25%. Furthermore, our model predictions aligned with biomarker evidence and its associations with different proteinopathies were substantiated through postmortem findings. Our framework has the potential to be integrated as a screening tool for dementia in clinical settings and drug trials. Further prospective studies are needed to confirm its ability to improve patient care.

AI-based differential diagnosis of dementia etiologies on multimodal data.

Differential diagnosis of dementia remains a challenge in neurology due to symptom overlap across etiologies, yet it is crucial for formulating early, personalized management strategies. Here, we present an AI model that harnesses a broad array of data, including demographics, individual and family medical history, medication use, neuropsychological assessments, functional evaluations, and multimodal neuroimaging, to identify the etiologies contributing to dementia in individuals. The study, drawing on 51,269 participants across 9 independent, geographically diverse datasets, facilitated the identification of 10 distinct dementia etiologies. It aligns diagnoses with similar management strategies, ensuring robust predictions even with incomplete data. Our model achieved a micro-averaged area under the receiver operating characteristic curve (AUROC) of 0.94 in classifying individuals with normal cognition, mild cognitive impairment and dementia. Also, the micro-averaged AUROC was 0.96 in differentiating the dementia etiologies. Our model demonstrated proficiency in addressing mixed dementia cases, with a mean AUROC of 0.78 for two co-occurring pathologies. In a randomly selected subset of 100 cases, the AUROC of neurologist assessments augmented by our AI model exceeded neurologist-only evaluations by 26.25%. Furthermore, our model predictions aligned with biomarker evidence and its associations with different proteinopathies were substantiated through postmortem findings. Our framework has the potential to be integrated as a screening tool for dementia in various clinical settings and drug trials, with promising implications for person-level management.