Publications by authors named "DUDA J"

Integration of artificial intelligence (AI) into radiology practice can create opportunities to improve diagnostic accuracy, workflow efficiency, and patient outcomes. Integration demands the ability to seamlessly incorporate AI-derived measurements into radiology reports. Common data elements (CDEs) define standardized, interoperable units of information.

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Within ovarian cancer research, patient-derived xenograft (PDX) models recapitulate histologic features and genomic aberrations found in original tumors. However, conflicting data from published studies have demonstrated significant transcriptional differences between PDXs and original tumors, challenging the fidelity of these models. We employed a quantitative mass spectrometry-based proteomic approach coupled with generation of patient-specific databases using RNA-seq data to investigate the proteogenomic landscape of serially-passaged PDX models established from two patients with distinct subtypes of ovarian cancer.

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Advances in magnetic resonance imaging (MRI) have revolutionized disease detection and treatment planning. However, as the volume and complexity of MRI data grow with increasing heterogeneity between institutions in imaging protocol, scanner technology, and data labeling, there is a need for a standardized methodology to efficiently identify, characterize, and label MRI sequences. Such a methodology is crucial for advancing research efforts that incorporate MRI data from diverse populations to develop robust machine learning models.

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Parkinson's disease is characterized by motor deficits emerging from insufficient dopamine in the striatum after degeneration of dopaminergic neurons and their long-projecting axons comprising the nigrostriatal pathway. To address this, a tissue-engineered nigrostriatal pathway (TE-NSP) featuring a tubular hydrogel with a collagen/laminin core that encases aggregated dopaminergic neurons and their axonal tracts is developed. This engineered microtissue can be implanted to replace neurons and axons with fidelity to the lost pathway and thus may provide dopamine according to feedback from host circuitry.

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3D brain atlases are key resources to understand the brain's spatial organization and promote interoperability across different studies. However, unlike the adult mouse brain, the lack of developing mouse brain 3D reference atlases hinders advancements in understanding brain development. Here, we present a 3D developmental common coordinate framework (DevCCF) spanning embryonic day (E)11.

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Understanding the neurophysiological changes that occur during loss and recovery of consciousness is a fundamental aim in neuroscience and has marked clinical relevance. Here, we utilize multimodal magnetic resonance neuroimaging to investigate changes in regional network connectivity and neurovascular dynamics as the brain transitions from wakefulness to dexmedetomidine-induced unconsciousness, and finally into early-stage recovery of consciousness. We observed widespread decreases in functional connectivity strength across the whole brain, and targeted increases in structure-function coupling (SFC) across select networks-especially the cerebellum-as individuals transitioned from wakefulness to hypnosis.

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Objective: This study aimed to examine the potential of experiencing aesthetic chills to enhance reward learning in individuals with elevated depressive symptoms, specifically anhedonia, by investigating the effect of chills on participants' ability to modulate behavior as a function of rewards.

Methods: A total of 103 participants with elevated depressive symptoms took part in the experiment. Among them, 59 participants had depressive symptoms (BDI ≥ 20), with 26 classified as "High Anhedonic" (HA) and 33 as "Low Anhedonic" (LA).

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Food production is one of the most important sources of greenhouse gas (GHG) emissions, both in primary production and in processing and the logistics chain. The most problematic and risky is the optimization of environmental effects in the stage of primary production. This is due to the significant influence of factors related to climate and soil that are difficult to predict.

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The quantity and variety of micro-pollutants infiltrating water resources have increased rapidly in recent times. The appearance of many harmful substances in the waters has resulted in so-called chemical cocktails which significantly contribute to the deterioration of water quality. Additionally, the variety of these compounds, often similar to each other in terms of molecular weights, makes their separation and identification very difficult.

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An increasing trend in ancestral and classical inbreeding coefficients as well as inbreeding depression for longevity were found in the German Brown population. In addition, the proportion of US Brown Swiss genes is steadily increasing in German Browns. Therefore, the aim of the present study was to analyze the presence and genomic localization of runs of homozygosity (ROH) in order to evaluate their associations with the proportion of US Brown Swiss genes and survival rates of cows to higher lactations.

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BACKGROUNDTwo coding alleles within the APOL1 gene, G1 and G2, found almost exclusively in individuals genetically similar to West African populations, contribute substantially to the pathogenesis of chronic kidney disease (CKD). The APOL gene cluster on chromosome 22 contains a total of 6 APOL genes that have arisen as a result of gene duplication.METHODSUsing a genome-first approach in the Penn Medicine BioBank, we identified 62 protein-altering variants in the 6 APOL genes with a minor allele frequency of >0.

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Although numerous AI algorithms have been published, the relatively small number of algorithms used clinically is partly due to the difficulty of implementing AI seamlessly into the clinical workflow for radiologists and for their healthcare enterprise. The authors developed an AI orchestrator to facilitate the deployment and use of AI tools in a large multi-site university healthcare system and used it to conduct opportunistic screening for hepatic steatosis. During the 60-day study period, 991 abdominal CTs were processed at multiple different physical locations with an average turnaround time of 2.

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Early diagnosis of Type 2 Diabetes Mellitus (T2DM) is crucial to enable timely therapeutic interventions and lifestyle modifications. As the time available for clinical office visits shortens and medical imaging data become more widely available, patient image data could be used to opportunistically identify patients for additional T2DM diagnostic workup by physicians. We investigated whether image-derived phenotypic data could be leveraged in tabular learning classifier models to predict T2DM risk in an automated fashion to flag high-risk patients the need for additional blood laboratory measurements.

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The study of muscle mass as an imaging-derived phenotype (IDP) may yield new insights into determining the normal and pathologic variations in muscle mass in the population. This can be done by determining 3D abdominal muscle mass from 12 distinct abdominal muscle regions and groups using computed tomography (CT) in a racially diverse medical biobank. To develop a fully automatic technique for assessment of CT abdominal muscle IDPs and preliminarily determine abdominal muscle IDP variations with age and sex in a clinically and racially diverse medical biobank.

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Background: Aortic structure impacts cardiovascular health through multiple mechanisms. Aortic structural degeneration occurs with aging, increasing left ventricular afterload and promoting increased arterial pulsatility and target organ damage. Despite the impact of aortic structure on cardiovascular health, three-dimensional (3D) aortic geometry has not been comprehensively characterized in large populations.

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Precision mapping techniques coupled with high resolution image acquisition of the mouse brain permit the study of the spatial organization of gene expression and their mutual interaction for a comprehensive view of salient structural/functional relationships. Such research is facilitated by standardized anatomical coordinate systems, such as the well-known Allen Common Coordinate Framework (AllenCCFv3), and the ability to spatially map to such standardized spaces. The Advanced Normalization Tools Ecosystem is a comprehensive open-source software toolkit for generalized quantitative imaging with applicability to multiple organ systems, modalities, and animal species.

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Objective: Preclinical work suggests that excess glucocorticoids and reduced cortical γ-aminobutyric acid (GABA) may affect sex-dependent differences in brain regions implicated in stress regulation and depressive phenotypes. The authors sought to address a critical gap in knowledge, namely, how stress circuitry is functionally affected by glucocorticoids and GABA in current or remitted major depressive disorder (MDD).

Methods: Multimodal imaging data were collected from 130 young adults (ages 18-25), of whom 44 had current MDD, 42 had remitted MDD, and 44 were healthy comparison subjects.

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Background: Neurocognitive factors including aberrant reward learning, blunted GABA (gamma-aminobutyric acid), and potentiated stress sensitivity have been linked to anhedonia, a hallmark depressive symptom, possibly in a sex-dependent manner. However, previous research has not investigated the putative associations among these factors or the extent to which they represent trait- or state-based vulnerabilities for depression.

Methods: Young adults with current major depressive disorder (MDD) (n = 44), remitted MDD (n = 42), and healthy control participants (HCs) (n = 44), stratified by sex assigned at birth, underwent magnetic resonance spectroscopy to assess macromolecular contaminated GABA (GABA+) and then a reward learning task before and after acute stress.

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The alkaline comet assay is frequently used as in vivo follow-up test within different regulatory environments to characterize the DNA-damaging potential of different test items. The corresponding OECD Test guideline 489 highlights the importance of statistical analyses and historical control data (HCD) but does not provide detailed procedures. Therefore, the working group "Statistics" of the German-speaking Society for Environmental Mutation Research (GUM) collected HCD from five laboratories and >200 comet assay studies and performed several statistical analyses.

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Background: Understanding the neurobiological effects of stress is critical for addressing the etiology of major depressive disorder (MDD). Using a dimensional approach involving individuals with differing degree of MDD risk, we investigated 1) the effects of acute stress on cortico-cortical and subcortical-cortical functional connectivity (FC) and 2) how such effects are related to gene expression and receptor maps.

Methods: Across 115 participants (37 control, 39 remitted MDD, 39 current MDD), we evaluated the effects of stress on FC during the Montreal Imaging Stress Task.

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Article Synopsis
  • Researchers utilized deep learning techniques to automatically identify myocardial bone uptake, which indicates transthyretin cardiac amyloid cardiomyopathy (ATTR-CM) in patients undergoing specific imaging tests (SPECT/CT).
  • They analyzed data from 170 patients across two hospitals, visually scoring myocardial uptake and using a 2D U-net model for segmentation, achieving a comparison rate of 100% accuracy in the primary group and 98% in the validation group.
  • The study found that 55% of patients showed abnormal uptake, with a significant difference in average heart-to-blood pool ratios between patients with positive and negative cardiac uptake, highlighting the effectiveness of the deep learning model in diagnosing ATTR-CM
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Background: The Probabilistic Reward Task (PRT) is a signal detection task that assesses reward learning. In laboratory versions of the task, individuals with current or past major depressive disorder (MDD) were characterized by reduced response bias towards a more frequently rewarded stimuli, compared to controls. Our main goal was to develop and validate a novel online version of the PRT, and, in exploratory analyses, evaluate whether lifetime history of depression was associated with blunted reward learning.

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