106 research outputs found

    Heterogeneity in Intrahepatic Macrophage Populations and Druggable Target Expression in Patients With Steatotic Liver Disease-Related Fibrosis

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    BACKGROUND & AIMS: Clinical trials for reducing fibrosis in steatotic liver disease (SLD) have targeted macrophages with variable results. We evaluated intrahepatic macrophages in patients with SLD to determine if activity scores or fibrosis stages influenced phenotypes and expression of druggable targets, such as CCR2 and galectin-3. METHODS: Liver biopsies from controls or patients with minimal or advanced fibrosis were subject to gene expression analysis using nCounter to determine differences in macrophage-related genes (n = 30). To investigate variability among individual patients, we compared additional biopsies by staining them with multiplex antibody panels (CD68/CD14/CD16/CD163/Mac387 or CD163/CCR2/galectin-3/Mac387) followed by spectral imaging and spatial analysis. Algorithms that utilize deep learning/artificial intelligence were applied to create cell cluster plots, phenotype profile maps, and to determine levels of protein expression (n = 34). RESULTS: Several genes known to be pro-fibrotic ( CONCLUSIONS: Patients with SLD have markedly varied macrophage- and druggable target-related gene and protein expression in their livers. Several patients had relatively high expression, while others were like controls. Overall, patients with more advanced disease had significantly higher expression of CCR2 and galectin-3 at both the gene and protein levels. IMPACT AND IMPLICATIONS: Appreciating individual differences within the hepatic microenvironment of patients with SLD may be paramount to developing effective treatments. These results may explain why such a small percentage of patients have responded to macrophage-targeting therapies and provide additional support for precision medicine-guided treatment of chronic liver diseases

    Heterogeneity in Intrahepatic Macrophage Populations and Druggable Target Expression in Patients With Steatotic Liver Disease-Related Fibrosis

    Get PDF
    BACKGROUND & AIMS: Clinical trials for reducing fibrosis in steatotic liver disease (SLD) have targeted macrophages with variable results. We evaluated intrahepatic macrophages in patients with SLD to determine if activity scores or fibrosis stages influenced phenotypes and expression of druggable targets, such as CCR2 and galectin-3. METHODS: Liver biopsies from controls or patients with minimal or advanced fibrosis were subject to gene expression analysis using nCounter to determine differences in macrophage-related genes (n = 30). To investigate variability among individual patients, we compared additional biopsies by staining them with multiplex antibody panels (CD68/CD14/CD16/CD163/Mac387 or CD163/CCR2/galectin-3/Mac387) followed by spectral imaging and spatial analysis. Algorithms that utilize deep learning/artificial intelligence were applied to create cell cluster plots, phenotype profile maps, and to determine levels of protein expression (n = 34). RESULTS: Several genes known to be pro-fibrotic ( CONCLUSIONS: Patients with SLD have markedly varied macrophage- and druggable target-related gene and protein expression in their livers. Several patients had relatively high expression, while others were like controls. Overall, patients with more advanced disease had significantly higher expression of CCR2 and galectin-3 at both the gene and protein levels. IMPACT AND IMPLICATIONS: Appreciating individual differences within the hepatic microenvironment of patients with SLD may be paramount to developing effective treatments. These results may explain why such a small percentage of patients have responded to macrophage-targeting therapies and provide additional support for precision medicine-guided treatment of chronic liver diseases

    Primary Hyperparathyroidism Patients with Positive Preoperative Sestamibi Scan and Negative Ultrasound Are More Likely to Have Posteriorly Located Upper Gland Adenomas (PLUGs)

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    BackgroundStandard preoperative imaging for primary hyperparathyroidism usually includes sestamibi scanning (MIBI) and ultrasound (US). In a subset of patients with a positive MIBI and a negative US, we hypothesize that the parathyroid adenomas are more likely to be located posteriorly in the neck, where anatomically they are more difficult to detect by US.MethodsWe retrospectively reviewed the records of 661 patients treated for primary hyperparathyroidism between 2004 and 2009 at a tertiary referral center. We included patients who for their first operation had a MIBI that localized a single lesion in the neck and an US that found no parathyroid adenoma. We excluded patients with persistent or recurrent hyperparathyroidism, and patients with MIBIs that were negative, that had more than one positive focus, or that had foci outside of the neck. Sixty-six cases were included in the final analysis.ResultsA total of 54 patients (83%) had a single adenoma, 4 (6%) had double adenomas, and 7 (11%) had hyperplasia. Thirty-three patients (51%) had a single upper gland adenoma; 19 of these (58%) were posteriorly located upper gland adenomas (PLUGs). PLUGs occurred more often on the right side than on the left (P = 0.048, Fisher's test). PLUGs were also larger than other single adenomas (mean 1.85 vs. 1.48 cm, P = 0.021, t-test). Seventy-six percent of patients successfully underwent a unilateral or focused exploration. Six patients (9%) had persistent disease, which is double our group's overall average (4-5%).ConclusionsPrimary hyperparathyroid patients with preoperative positive MIBI and negative US are more likely to have PLUGs

    Acute otitis externa: Consensus definition, diagnostic criteria and core outcome set development.

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    OBJECTIVE: Evidence for the management of acute otitis externa (AOE) is limited, with unclear diagnostic criteria and variably reported outcome measures that may not reflect key stakeholder priorities. We aimed to develop 1) a definition, 2) diagnostic criteria and 3) a core outcome set (COS) for AOE. STUDY DESIGN: COS development according to Core Outcome Measures in Effectiveness Trials (COMET) methodology and parallel consensus selection of diagnostic criteria/definition. SETTING: Stakeholders from the United Kingdom. SUBJECTS AND METHODS: Comprehensive literature review identified candidate items for the COS, definition and diagnostic criteria. Nine individuals with past AOE generated further patient-centred candidate items. Candidate items were rated for importance by patient and professional (ENT doctors, general practitioners, microbiologists, nurses, audiologists) stakeholders in a three-round online Delphi exercise. Consensus items were grouped to form the COS, diagnostic criteria, and definition. RESULTS: Candidate COS items from patients (n = 28) and literature (n = 25) were deduplicated and amalgamated to a final candidate list (n = 46). Patients emphasised quality-of-life and the impact on daily activities/work. Via the Delphi process, stakeholders agreed on 31 candidate items. The final COS covered six outcomes: pain; disease severity; impact on quality-of-life and daily activities; patient satisfaction; treatment-related outcome; and microbiology. 14 candidate diagnostic criteria were identified, 8 reaching inclusion consensus. The final definition for AOE was 'diffuse inflammation of the ear canal skin of less than 6 weeks duration'. CONCLUSION: The development and adoption of a consensus definition, diagnostic criteria and a COS will help to standardise future research in AOE, facilitating meta-analysis. Consulting former patients throughout development highlighted deficiencies in the outcomes adopted previously, in particular concerning the impact of AOE on daily life

    Machine learning uncovers the most robust self-report predictors of relationship quality across 43 longitudinal couples studies

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    Given the powerful implications of relationship quality for health and well-being, a central mission of relationship science is explaining why some romantic relationships thrive more than others. This large-scale project used machine learning (i.e., Random Forests) to 1) quantify the extent to which relationship quality is predictable and 2) identify which constructs reliably predict relationship quality. Across 43 dyadic longitudinal datasets from 29 laboratories, the top relationship-specific predictors of relationship quality were perceived-partner commitment, appreciation, sexual satisfaction, perceived-partner satisfaction, and conflict. The top individual-difference predictors were life satisfaction, negative affect, depression, attachment avoidance, and attachment anxiety. Overall, relationship-specific variables predicted up to 45% of variance at baseline, and up to 18% of variance at the end of each study. Individual differences also performed well (21% and 12%, respectively). Actor-reported variables (i.e., own relationship-specific and individual-difference variables) predicted two to four times more variance than partner-reported variables (i.e., the partner’s ratings on those variables). Importantly, individual differences and partner reports had no predictive effects beyond actor-reported relationship-specific variables alone. These findings imply that the sum of all individual differences and partner experiences exert their influence on relationship quality via a person’s own relationship-specific experiences, and effects due to moderation by individual differences and moderation by partner-reports may be quite small. Finally, relationship-quality change (i.e., increases or decreases in relationship quality over the course of a study) was largely unpredictable from any combination of self-report variables. This collective effort should guide future models of relationships
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