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Abstract TMP95: Risk Factors, Stroke Characteristics and Outcomes in Children with Inpatient Versus Outpatient Strokes

Children who suffer arterial ischemic stroke (AIS) while hospitalized are often critically ill and may have distinct acute and chronic risk factors, stroke characteristics and outcomes compared to those with outpatient strokes. We sought to evaluate demographic, clinical and imaging profiles of children with inpatient versus outpatient strokes, and compare mortality between the two groups. Methods: The Stanford Pediatric Stroke Registry retrospectively and prospectively enrolled children with acute AIS who were admitted to our tertiary care pediatric hospital between 2007-2024. For this analysis we included patients who met the following criteria: 1) age 30 days-18 years old; 2) new diagnosis of AIS; 3) acute neuroimaging available for direct review. Inpatient strokes were defined as strokes that occurred while the child was hospitalized, either at our center or at an outside facility prior to transfer. Demographic, clinical and radiographic data were compared using chi-squared or Fishers Exact test for categorical variables and Mann-Whitney U test or t-test for continuous variables. Outcomes were reported using descriptive statistics due to the hypothesis-generating nature of the report. Results: A total of 208 children with acute AIS met inclusion criteria; 99 (47.6%) experienced a stroke while hospitalized. Inpatient stroke patients were overall younger and had higher rates of congenital heart diease and cancer than children with outpatient strokes, while trauma was more common in outpatient strokes (Table 1). There were no significant differences in imaging characteristics between groups. Cardioembolism and periprocedural strokes were more prevalent in inpatient strokes, whereas arteriopathy and cryptogenic stroke were the most common stroke etiologies in outpatients (Table 2). A significantly higher proportion of inpatient stroke patients died compared to outpatient strokes (27.3% vs 3.7%, p<0.0001); most patients died prior to discharge (Table 3). Conclusions: In our pediatric AIS cohort, nearly half had a stroke while hospitalized. Our study suggests that stroke and risk factor profiles differ between inpatient and outpatient strokes in multiple domains, and that children with inpatient strokes have higher rates of death. Further prospective studies are needed to determine factors contributing to higher mortality in order to tailor appropriate prevention strategies.

Abstract WP89: Computed Tomography Perfusion Imaging Profiles Are Similar Before and After Transfer to a Comprehensive Stroke Center.

Abstract WP89: Computed Tomography Perfusion Imaging Profiles Are Similar Before and After Transfer to a Comprehensive Stroke Center.

Improving the Seismic Impedance Inversion by Fully Convolutional Neural Network

Applying deep neural networks (DNNs) to broadband seismic wave impedance inversion is challenging, especially in generalizing from synthetic to field data, which limits the exploitation of their nonlinear mapping capabilities. While many research studies are about advanced and enhanced architectures of DNNs, this article explores how variations in input data affect DNNs and consequently enhance their generalizability and inversion performance. This study introduces a novel data pre-processing strategy based on histogram equalization and an iterative testing strategy. By employing a U-Net architecture within a fully convolutional neural network (FCN) exclusively trained on synthetic and monochrome data, including post-stack profile, and 1D linear background impedance profiles, we successfully achieve broadband impedance inversion for both new synthetic data and marine seismic data by integrating imaging profiles with background impedance profiles. Notably, the proposed method is applied to reverse time migration (RTM) data from the Ceduna sub-basin, located in offshore southern Australia, significantly expanding the wavenumber bandwidth of the available data. This demonstrates its generalizability and improved inversion performance. Our findings offer new insights into the challenges of seismic data fusion and promote the utilization of deep neural networks for practical seismic inversion and outcomes improvement.

A volumetric study of the choroid plexus in neuropsychiatric systemic lupus erythematosus

Much evidence suggests that the choroid plexus (CP) plays an important role in the pathophysiology of systemic lupus erythematosus (SLE), but its imaging profile in neuropsychiatric SLE (NPSLE) remains unexplored. To evaluate CP volume in NPSLE patients using MRI. This retrospective study evaluated patients with SLE who underwent MRI of the brain, including three-dimensional T1-weighted imaging. CP volumes were automatically segmented. CP volume was evaluated using multivariable linear regression adjusted for age, sex, and total intracranial volume among three groups: NPSLE group, non-NPSLE group, and healthy control group (HC). Correlation analysis was performed between CP volume and clinical variables in the patient group. A total of 138 patients with SLE were included in the analysis. It was found that the right CP volume was greater in NPSLE compared with non-NPSLE and HC. When stratified according to their diagnosed status, newly diagnosed NPSLE had significantly greater CP volumes bilaterally compared with HC. Right CP volume was positively associated with Systemic Lupus Erythematosus Disease Activity Index (SLEDAI) scores in the patient group. All statistical significance levels were p < 0.05. CP enlargement could reflect a neuroinflammatory response that occurs at NPSLE disease onset. CP volume may serve as a promising marker for SLE, especially for newly diagnosed NPSLE.

The effects of maxillary incisor positions and chin prominences on the perception of lateral smiling profile attractiveness among orthodontists and laypersons.

To evaluate the ideal anteroposterior position of incisors in lateral smiling profiles with different chin prominences and to relate these positions to nose and chin landmarks based on the perceptions of orthodontists and laypersons. A lateral smiling profile image of a female subject was adjusted to create five levels of chin prominence (-6, -3, 0, +3, +6 mm). For each level, the anteroposterior positions of the maxillary incisors were adjusted across five positions (-4, -2, 0, +2, +4 mm). Thirty-six orthodontists and 36 laypersons rated the attractiveness of each profile using a visual analog scale. The maxillary incisor position (U1) was measured relative to the external nose and chin landmarks (E-lines). Differences in perceptions between orthodontists and laypersons were analyzed. For profiles with 6 and 3 mm chin retrusion, the most favored incisor positions were the 2 mm retrusion and unaltered positions, respectively. For the unaltered chin prominence, orthodontists preferred unaltered incisors, while laypersons favored 2 mm protrusion. Conversely, for 3 and 6 mm chin protrusion, both groups preferred 4 and 2 mm protrusion, respectively. The distance between U1 and the E-line is the most attractive images ranged from 8.5 to 11.5 mm. Based on the regression model, an optimal U1-E-line distance of 8.95 mm was recommended. The preferred incisor position is influenced by chin prominence, with the incisor position shifting in the same direction as the chin. The U1 E-line can be a useful clinical tool for determining the proper incisor positioning. Esthetic perceptions were generally consistent between orthodontists and laypersons.

Intratumoral microbiota, fatty acid metabolism, and tumor microenvironment constitute an unresolved trinity in colon adenocarcinoma

The intratumoral microbiota, fatty acid metabolism (FAM), and tumor microenvironment (TME) all provide insights into the management of colon adenocarcinoma (COAD). But the biological link among the three remains unclear. Here, we analyzed intratumoral microbiome samples and matched host transcriptome samples from 420 patients with COAD in The Cancer Genome Atlas (TCGA). All patients were divided into two subtypes (FAM_high and FAM_low) based on the Gene set variation analysis (GSVA) score of FAM pathway. Furthermore, we found significant difference in the intratumoral microbiota signatures between the two subtypes. In-depth analysis suggested that specific microbes in tumors may indirectly modify the TME, particularly stromal cell populations, by modulating the FAM process. More importantly, the crosstalk between the three can have a significant impact on prognosis, response to immunotherapy, and drug sensitivity of patients. Pathological image profiling showed that changes in the TME originating from intratumoral microbiota disturbance could be reflected in pathological image features. In summary, our study provides novel insights into the biological links among the intratumoral microbiota, FAM, and the TME in COAD, and offer guidance for the therapeutic opportunities that target intratumoral microbes.

Potential associations between altered brain function, cognitive deficits and gene expressing profiles in bipolar disorder across three clinical stages.

We aimed to determine the relationship between altered brain imaging characteristics, cognitive function and profiles of gene expression of bipolar disorder (BD). Functional magnetic resonance imaging (fMRI) was presented in three groups of BD participants (depressed, manic and euthymic) and healthy controls. Regional Homogeneity (ReHo) and region of interest based functional analysis combining with neuroimaging-transcription association analysis were utilized to investigate abnormalities and their correlation with clinical symptoms. Our data showed that all three groups of BD patients exhibited significantly altered ReHo values whilst the bilateral precuneus/posterior cingulate cortex (PCC) and lateral occipital cortex exhibited significant increase in BD. Functional connectivity (FC) revealed distinct characteristics of the precuneus/PCC-based default mode network. ReHo values in the Precuneus/middle cingulate cortex displayed significantly negative correlations with cognition and YMRS scores. Gene enrichment analysis also revealed that ReHo values were spatially correlated with pathways including chromatin organization and innate immune response. Altered ReHo values in specific brain regions may be associated with different clinical stages and increased FC in brain may potentially function as BD imaging biomarkers. The heterogeneity of gene expression was associated with altered brain imaging properties in BD, contributing to distinguishing different stages of BD from healthy individuals.

Calcified chondroid mesenchymal neoplasm: a clinicopathological and molecular analysis

AimsCalcified chondroid mesenchymal neoplasm (CCMN) is a recently identified category of soft tissue neoplasms defined by cartilage or cartilaginous matrix formation and FN1 gene fusions. Its rarity and similarities to...

Cardiovascular Profile and Cardiovascular Imaging After Bariatric Surgery: A Narrative Review.

Background and Objectives: Up until now, behavioral interventions and pharmacological therapies were the main approach available for the management of obesity. Diet and exercise, when used as a singular therapeutic method, are inadequate for a successful outcome. Research shows promising results for the surgical treatment of obesity, especially in the area of bariatric surgery (BaS). The relevance of this study is the valuable analysis of the evolution of obese patients with increased cardiovascular risk. Materials and Methods: The patients eligible for BaS commonly suffer from multiple chronic conditions, including type 2 diabetes, obstructive sleep apnea, cardiovascular diseases, and non-alcoholic fatty liver disease. Additionally, obesity contributes to an increased probability of developing certain types of cancer, osteoarthritis, urinary incontinence, and chronic kidney disease. In this review, we focused especially on the cardiovascular status of obese patients who underwent bariatric procedures. Results: BaS has been found to be strongly associated with a reduced incidence of severe complications in individuals with a history of myocardial infarction (MI) and severe obesity. Specifically, this procedure is linked to a lower occurrence of major adverse cardiovascular events and a decrease in overall mortality. Also, BaS is correlated with a reduced risk of recurrent MI and the development of new-onset heart failure. Conclusions: The results of BaS involve a significant amelioration of the BMI, contributing to a considerable decrease in cardiovascular risk factors and to a notable refinement in the cardiovascular structure and function.

Assembly and application of a low-cost high-resolution imaging device for hyphae in soil.

Soil imaging in the field and laboratory has greatly advanced our understanding of plant root systems. Soil fungi function as important plant symbionts and decomposers of complex organic material in soil environments. For fungal hyphae, however, the application of soil imaging remains scarce, limiting our understanding of hyphal systems in soil. This scarce application is partly due to the challenging development of a soil imaging device for hyphae: technical requirements to resolve fine hyphae (2-5 μm in diameter) are high, while the device cost must be low to facilitate sufficient deployment that can capture the high spatial heterogeneity of hyphal dynamics in soil. This protocol describes the do-it-yourself assembly and application of a low-cost high-resolution imaging device for observing hyphae in soil. The assembly of the open-source imaging device relies on many 3D-printed parts, reducing material costs to ca. 930 USD. The application of the imaging device yields soil profile images with a resolution of up to 0.52 μm px-1 (49000 dpi) within an observable volume of 70 × 210 × 1.5 mm. By repeatedly imaging a soil profile using the presented techniques, changes in the amount, distribution, and morphology of hyphae in soil can be observed and quantified.

USO DE ALGORITMOS PARA DIAGNÓSTICO PRECOCE DE ALZHEIMER, PARKINSON E ESCLEROSE MÚLTIPLA

The application of artificial intelligence (AI) algorithms in the early diagnosis of neurodegenerative diseases, such as Alzheimer's, Parkinson's, and multiple sclerosis, has made significant advances. This integrative review analyzed 22 studies published between 2013 and 2023, using databases such as PubMed, IEEE Xplore, and Scopus. The results highlight the use of Convolutional Neural Networks (CNNs) in neuroimaging, such as magnetic resonance imaging and PET scans, with an accuracy of over 90% in diagnosing Alzheimer's. Multimodal approaches that integrate clinical and genetic data have demonstrated increasing efficacy. For Parkinson's, algorithms that analyze vocal signals and tremors have a sensitivity between 85% and 92%, while deep learning tools allow the detection of minimal motor changes. In the case of multiple sclerosis, models that combine magnetic resonance imaging and immunological profiles show high accuracy in the early detection of brain lesions. Despite the advances, challenges persist, including the standardization of databases, large-scale validation, and interpretation of results by health professionals. The limitations of this study include the lack of methodological uniformity in the articles analyzed and the scarcity of data from large clinical studies. It is proposed that future research invest in the integration of different data sources, expansion of population samples, and development of more transparent algorithms, facilitating its clinical adoption. It is concluded that AI has great potential to transform early diagnosis, allowing more effective and personalized interventions, but it requires refinement to consolidate its practical applicability.

Automatic Single-Cell Harvesting for Fetal Nucleated Red Blood Cell Isolation on a Self-Assemble Cell Array (SACA) Chip.

(1) Background: Fetal chromosomal examination is a critical component of modern prenatal testing. Traditionally, maternal serum biomarkers such as free β-human chorionic gonadotropin (Free β-HCG) and pregnancy-associated plasma protein A (PAPPA) have been employed for screening, achieving a detection rate of approximately 90% for fetuses with Down syndrome, albeit with a false positive rate of 5%. While amniocentesis remains the gold standard for the prenatal diagnosis of chromosomal abnormalities, including Down syndrome and Edwards syndrome, its invasive nature carries a significant risk of complications, such as infection, preterm labor, or miscarriage, occurring at a rate of 7 per 1000 procedures. Beyond Down syndrome and Edwards syndrome, other chromosomal abnormalities, such as trisomy of chromosomes 9, 16, or Barr bodies, pose additional diagnostic challenges. Non-invasive prenatal testing (NIPT) has emerged as a powerful alternative for fetal genetic screening by leveraging maternal blood sampling. However, due to the extremely low abundance of fetal cells in maternal circulation, NIPT based on fetal cells faces substantial technical challenges. (2) Methods: Fetal nucleated red blood cells (FnRBCs) were first identified in maternal circulation in a landmark study published in The Lancet in 1959. Due to their fetal origin and presence in maternal peripheral blood, FnRBCs represent an ideal target for non-invasive prenatal testing (NIPT). In this study, we introduce a novel self-assembled cell array (SACA) chip system, a microfluidic-based platform designed to efficiently settle and align cells into a monolayer at the chip's base within five minutes using lateral flow dynamics and gravity. This system is integrated with a fully automated, multi-channel fluorescence scanning module, enabling the real-time imaging and molecular profiling of fetal cells through fluorescence-tagged antibodies. By employing a combination of Hoechst+/CD71+/HbF+/CD45- markers, the platform achieves the precise enrichment and isolation of FnRBCs at the single-cell level from maternal peripheral blood. (3) Results: The SACA chip system effectively reduces the displacement of non-target cells by 31.2%, achieving a single-cell capture accuracy of 97.85%. This isolation and enrichment system for single cells is well suited for subsequent genetic analysis. Furthermore, the platform achieves a high purity of isolated cells, overcoming the concentration detection limit of short tandem repeat (STR) analysis, demonstrating its capability for reliable non-invasive prenatal testing. (4) Conclusions: This study demonstrates that the SACA chip, combined with an automated image positioning system, can efficiently isolate single fetal nucleated red blood cells (FnRBCs) from 50 million PBMCs in 2 mL of maternal blood, completing STR analysis within 120 min. With higher purification efficiency compared to existing NIPT methods, this platform shows great promise for prenatal diagnostics and potential applications in other clinical fields.

Multiple Electromechanical-Failure Detection in Induction Motor Using Thermographic Intensity Profile and Artificial Neural Network

The use of artificial intelligence-based techniques to solve engineering problems is increasing. One of the most challenging tasks facing industry is the timely diagnosis of failures in electromechanical systems, as they are an essential part of production systems. In this sense, the earlier the detection, the higher the economic loss reduction. For this reason, this work proposes the development of a new methodology based on infrared thermography and an artificial intelligence-based classifier for the detection of multiple faults in an electromechanical system. The proposal combines the intensity profile of the grey-scale image, the use of Fast Fourier Transform and an artificial neural network to perform the detection of twelve states for the state of an electromechanical system: healthy, bearing defect, broken rotor bar, misalignment and gear wear on the gearbox. From the experimental setup, 50 thermographic images were obtained for each state. The method was implemented and tested under different conditions to verify its reliability. The results show that the precision, accuracy, recall and F1-score are higher than 99%. Thus, it can be concluded that it is possible to detect multiple conditions in an electromechanical system using the intensity profile and an artificial neural network, achieving good accuracy and reliability.

IR Pulsed Laser Ablation of Carbon Materials in High Vacuum

This work aimed to understand how the energy released by short laser pulses can produce different effects in carbon targets with different allotropic states. The IR pulse laser ablation, operating at 1064 nm wavelength, 3 ns pulse duration, and 100 mJ pulse energy, has been used to irradiate different types of carbon targets in a high vacuum. Graphite, highly oriented pyrolytic graphite, glassy carbon, active carbon, and vegetable carbon have exhibited different mass densities and have been laser irradiated. Time-of-flight (TOF) measurements have permitted the evince of the maximum carbon ion acceleration in the generated plasma (of about 200 eV per charge state) and the maximum yield emission (96 μg/pulse in the case of vegetal carbon) along the direction normal to the irradiated surface. The ion energy analyzer measured the carbon charge states (four) and their energy distributions. Further plasma investigations have been performed using a fast CCD camera image and surface profiles of the generated craters to calculate the angular emission and the ablation yield for each type of target. The effects as a function of the target carbon density and binding energy have been highlighted. Possible applications for the generation of thin films and carbon nanoparticles are discussed.

Association of Laboratory and Imaging Parameters in Different Types of Pancreatitis in Children in a Tertiary Care Hospital in Bangladesh

Background: Pancreatitis is an inflammatory condition of the pancreas, which might extend to local and distant extra-pancreatic tissues. It can be acute, acute recurrent or may be chronic. The diagnosis of different types of pancreatitis is based on a combination of clinical signs and symptoms, laboratory investigations and imaging techniques. Objective: To describe and find out the association of the laboratory and imaging profiles of different variety of pancreatitis in children. Methods: It was a an observational study conducted at the department of Paediatric Gastroenterology and Nutrition of Bangabandhu Sheikh Mujib Medical University from July 2018 through June 2020. A total of 48 cases were included in this study. The diagnosis of acute, acute recurrent and chronic pancreatitis was based on diagnostic criteria made by INSPPIRE group. Clinical characteristics, hematological, biochemical and imaging profile of the different variety of pancreatitis and their hospital outcome were observed. Result: Among 48 cases, acute recurrent pancreatitis were 56.3%. Mean age of the patients at presentation was 10.3 years. Laboratory tests showed serum calcium and C-reactive protein was significantly altered among acute, acute recurrent and chronic pancreatitis with characteristic imaging findings. Among imaging modalities, abdominal ultrasonogram showed swollen pancreas (58.3%) was significantly common in acute recurrent pancreatitis than chronic pancreatitis, whereas shrunken pancreas (28%) was significantly common findings in chronic pancreatitis. In addition to ultrasonogram, MRCP aided diagnosis of chronic pancreatitis. Complications developed in 25% of acute pancreatitis cases, which included hypocalcemia (58.3%), ascites (86.7%), pleural effusion (66.7%), pseudocyst (33.3%) and pancreatic necrosis (25%). Hospital stay was significantly prolonged in acute pancreatitis cases, when compared to other types of pancreatitis . Conclusion: Low calcium level and high CRP level were found in acute pancreatitis than in acute recurrent and chronic pancreatitis. Swollen pancreas with beaded and tortuous pancreatic ducts were found in case of chronic pancreatitis. Bangladesh J Child Health 2023; Vol 47 (2) : 95-102

Competitive Authenticity: Chinese Beauty Influencers Leverage the Hashtag #ReconcileWithPlainFace to Intensify Their Rivalries

Abstract: In China’s complex and layered digital landscape, women influencers are redefining Asian beauty ideals and challenging traditional narratives. This study investigates the uses and implications of the hashtag “# YuSuyanHejie / #ReconcileWithPlainFace.” Originating on Douyin, the Chinese version of TikTok, this hashtag explicitly promotes a makeup-free appearance. As a piece of marketing rhetoric, the hashtag is reminiscent of the recent strategic shift by Western brands from featuring unrealistic, “flawless” models to promoting “real” beauty that features “average,” everyday women. Increasingly, Chinese influencers now present viewers with makeup-free, “authentic” profile images that challenge traditional and repressive beauty norms. Ironically, such claims seem to intensify, rather than relax, the incredibly fierce competition that already characterizes the online beauty community. Through digital ethnography, this paper examines the interactions between Chinese influencers and their followers to analyze the construction of, and tensions within, the dissonant concept of competitive authenticity. This study contributes to an understanding of gender, labor, and “authenticity” within China's digital economy and demonstrates the ways in which influencers weigh self-representation against both commercial incentives and societal expectations.

Electromagnetic scattering imaging characteristics of micro-rough surface high-speed vehicle

We present improvements to the physical optics method for high-frequency computations. This involves refining the calculation model such that the number of triangular facets is adequate to accurately represent the target structure. An illumination assessment is performed using the mesh model, and this is followed by a predetermined subdivision of the illuminated facets to achieve the required computational resolution. Subsequently, using a group of high-speed vehicle RAM C-II models with surfaces of different roughness, we calculate their one-dimensional high-resolution range profile and two-dimensional inverse synthetic aperture radar images at different reentry heights. The results demonstrate that the smooth-surfaced RAM C-II exhibits imaging limited to its head and tail, whereas the rough-surfaced RAM C-II reveals its entire contour. Furthermore, the presence of plasma diminishes the imaging efficacy of rough-surfaced targets, with the effect becoming more pronounced at lower altitudes. This study provides valuable insights for the identification of high-speed vehicles.

Identification of high‐performance blood‐based biomarkers for early screening and staging of Alzheimer’s disease by large‐scale plasma proteomic profiling in mild cognitive impairments

AbstractBackgroundEarly detection of Alzheimer's disease (AD), particularly during the mild cognitive impairment (MCI) stage, is crucial for effective intervention and treatment. However, existing diagnostic methods, through cognitive assessments, brain imaging, or cerebrospinal fluid profiling, are subjective, expensive or invasive. We previously showed that the plasma proteome is altered in AD, suggesting the feasibility of utilizing blood biomarkers for AD detection. Therefore, to develop a blood test for early screening and staging of AD, it is important to identify blood biomarkers associated with MCI/early AD and the features of AD progression.MethodWe conducted a comprehensive profiling of the plasma proteome of MCI by measuring 1,160 proteins in a Hong Kong Chinese cohort, to identify novel blood biomarkers for MCI/early AD. We further developed a biomarker panel based on the identified MCI/AD‐associated blood biomarkers and validated its performance in an independent amyloid‐PET‐defined cohort.ResultWe identified 496 proteins that were dysregulated in MCI plasma, and these proteins, involved in different biological processes, exhibited distinct dysregulating patterns with disease progression. We further categorized these proteins into different groups based on their dysregulating patterns. By performing co‐expression network analysis, we identified an 18‐protein panel that captures the profile changes of plasma proteome in MCI and AD. This panel accurately classified MCI (AUC = 0.913‐0.925) and AD (AUC = 0.970‐0.993) in two independent cohorts. Moreover, this panel correlates with cognitive decline and the development of Aβ pathology in the brain, which outperforms some of the existing plasma ATN biomarkers.ConclusionThis study comprehensively profiled the MCI plasma proteome and demonstrates the feasibility of a blood‐based biomarker assay for early detection and staging of MCI and AD, potentially facilitating early screening, monitoring, and intervention in future clinical settings.

A prognostic molecular signature of hepatic steatosis is spatially heterogeneous and dynamic in human liver.

Hepatic steatosis is a central phenotype in multi-system metabolic dysfunction and is increasing in parallelwith the obesity pandemic. We use a translational approach integrating clinical phenotyping and outcomes, circulating proteomics, and tissue transcriptomics to identify dynamic, functional biomarkers of hepatic steatosis. Using multi-modality imaging and broad proteomic profiling, we identify proteins implicated in the progression of hepatic steatosis that are largely encoded by genes enriched at the transcriptional level in the human liver. These transcripts are differentially expressed across areas of steatosis in spatial transcriptomics, and several are dynamic during stages of steatosis. Circulating multi-protein signatures of steatosis strongly associate with fatty liver disease and multi-system metabolic outcomes. Using a humanized "liver-on-a-chip" model, we induce hepatic steatosis, confirming cell-specific expression of prioritized targets. These results underscore the utility of this approach to identify a prognostic, functional, dynamic "liquid biopsy" of human liver, relevant to biomarker discovery and mechanistic research applications.

Recent developments in olfactory neuroblastoma research.

Olfactory neuroblastoma (ONB) is a rare malignancy originating from olfactory neuroepithelial cells. Given its uncommon nature and complex clinical presentation, this comprehensive review highlights recent findings and treatment approaches for advancing clinical practice and research. Recent literature emphasizes significant advancements in the genomic profiling and molecular classification of ONB. Emerging targeted therapies include somatostatin analogs and programmed death-ligand 1 (PD-L1) inhibitors. In addition, the development of genetically engineered mouse models has provided valuable platforms for testing new treatment strategies, revealing similarities between ONB and small cell lung cancer, which may inform future therapeutic approaches. These findings have profound implications on clinical practice. Improved diagnostic accuracy through advanced imaging and genomic profiling in addition to identifying specific mutations for targeted therapy can lead to personalized treatments of patients with ONB. Developments in genetically engineered mouse models and multiinstitutional collaborative efforts are vital for advancing research and standardizing molecular testing. The integration of advanced imaging techniques, genomic profiling, and targeted therapies holds promise for improving patient outcomes and understanding this rare malignancy.