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The IL-22–oncostatin M axis promotes intestinal inflammation and tumorigenesis
Get PDFMulticellular cytokine networks drive intestinal inflammation and colitis-associated cancer (CAC). Interleukin-22 (IL-22) exerts both protective and pathogenic effects in the intestine, but the mechanisms that regulate this balance remain unclear. Here, we identify that IL-22 directly induces responsiveness to the IL-6 family cytokine oncostatin M (OSM) in intestinal epithelial cells (IECs) by activating STAT3 and upregulating the OSM receptor. In turn, OSM synergizes with IL-22 to sustain STAT3 activation in IECs and promote proinflammatory epithelial adaptation and immune cell chemotaxis to the inflamed intestine. Conditional deletion of the OSM receptor in IECs protects mice from both colitis and CAC, and pharmacological blockade of OSM attenuates established CAC. Thus, IL-22 and OSM form a pathogenic circuit that drives inflammation and tumorigenesis. Our findings reveal a previously unknown mechanism by which OSM supports intestinal pathology and highlight the IL-22–OSM axis as a promising therapeutic target for inflammatory bowel disease and CAC
Do transformers and CNNs learn different concepts of brain age?
Get PDF"Predicted brain age" refers to a biomarker of structural brain health derived from machine learning analysis of T1-weighted brain magnetic resonance (MR) images. A range of machine learning methods have been used to predict brain age, with convolutional neural networks (CNNs) currently yielding state-of-the-art accuracies. Recent advances in deep learning have introduced transformers, which are conceptually distinct from CNNs, and appear to set new benchmarks in various domains of computer vision. Given that transformers are not yet established in brain age prediction, we present three key contributions to this field: First, we examine whether transformers outperform CNNs in predicting brain age. Second, we identify that different deep learning model architectures potentially capture different (sub-)sets of brain aging effects, reflecting divergent "concepts of brain age". Third, we analyze whether such differences manifest in practice. To investigate these questions, we adapted a Simple Vision Transformer (sViT) and a shifted window transformer (SwinT) to predict brain age, and compared both models with a ResNet50 on 46,381 T1-weighted structural MR images from the UK Biobank. We found that SwinT and ResNet performed on par, though SwinT is likely to surpass ResNet in prediction accuracy with additional training data. Furthermore, to assess whether sViT, SwinT, and ResNet capture different concepts of brain age, we systematically analyzed variations in their predictions and clinical utility for indicating deviations in neurological and psychiatric disorders. Reassuringly, we observed no substantial differences in the structure of brain age predictions across the model architectures. Our findings suggest that the choice of deep learning model architecture does not appear to have a confounding effect on brain age studies
HDAC inhibitors engage MITF and the disease-associated microglia signature to enhance amyloid β uptake
No full textDisease-associated microglia (DAM), initially described in mouse models of neurodegenerative diseases, have been classified into two related states; starting from a TREM2-independent DAM1 state to a TREM2dependent state termed DAM2, with each state being characterized by the expression of specific marker genes (Keren-Shaul, 2017). Recently, single-cell (sc)RNA-Seq studies have reported the existence of DAM in humans (Pettas, 2022; Jauregui, 2023; Friedman, 2018; Mathys, 2019; Tuddenham, 2024); however, whether DAM play beneficial or detrimental roles in the context of neurodegeneration is still under debate (Butovsky and Weiner, 2018; Wang and Colonna, 2019). Here, we present a pharmacological approach to mimic human DAM in vitro: we validated in silico predictions that two different histone deacetylase (HDAC) inhibitors, Entinostat and Vorinostat, recapitulate aspects of the DAM signature in two human microglia-like model systems. HDAC inhibition increases RNA expression of MITF, a transcription factor previously described as a regulator of the DAM signature (Dolan, 2023). This engagement of MITF appears to be associated with one part of the DAM signature, refining our understanding of the DAM signature as a combination of at least two transcriptional programs that appear to be correlated in vivo. Further, we functionally characterized our DAM-like model system, showing that the upregulation of this transcriptional program by HDAC inhibitors leads to an upregulation of amyloid β and pHrodo Dextran uptake – while E.coli uptake is reduced – and a specific reduction of MCP1 secretion in response to IFN-γ and TNF-α. Enhanced amyloid β uptake was confirmed in iPSC-derived microglia. Overall, our strategy for compound-driven microglial polarization offers potential for exploring the function of human DAM and for an immunomodulatory strategy around HDAC inhibition
Fertility in patients with advanced-stage classic Hodgkin lymphoma treated with BrECADD versus eBEACOPP: a secondary analysis of the multicentre, randomised, parallel, open-label, phase 3 HD21 trial
Get PDFBACKGROUND: BrECADD (brentuximab vedotin, etoposide, cyclophosphamide, doxorubicin, dacarbazine, and dexamethasone) has shown higher efficacy and better acute tolerability than eBEACOPP (escalated doses of bleomycin, etoposide, doxorubicin, cyclophosphamide, vincristine, procarbazine, and prednisone) in newly diagnosed, advanced-stage classic Hodgkin lymphoma. In this secondary analysis of the HD21 trial, we aimed to compare gonadal function recovery and fertility outcomes between these two regimens. METHODS: In the multicentre, parallel, open-label, phase 3 HD21 trial, conducted across 233 trial sites in nine countries, patients aged 18–60 years with newly diagnosed, advanced-stage classic Hodgkin lymphoma and an Eastern Cooperative Oncology Group performance status of 0–2 were randomly assigned (1:1) to receive 4–6 cycles of eBEACOPP or BrECADD, guided by interim response. Patients and investigators were not masked to treatment assignment. Primary outcomes were progression-free survival and treatment-related morbidity (reported elsewhere). Here we report an unplanned analysis of fertility outcomes. Fertility outcomes included gonadal function recovery (via follicle-stimulating hormone [FSH] concentrations), concentrations of anti-Müllerian hormone (AMH; women only) and inhibin B (men only), frequencies of pregnancies, and incidence of parenthood. Gonadal function recovery, AMH, and inhibin B were assessed in the patients of childbearing potential (POCBP) cohort, which included women younger than 40 years and men younger than 50 years without baseline gonadal dysfunction. Pregnancy and parenthood analyses also included patients with baseline gonadal dysfunction. The HD21 trial was registered at ClinicalTrials.gov (NCT02661503) and is ongoing but closed to enrolment. FINDINGS: Between July 22, 2016, and Aug 27, 2020, 1183 POCBP were enrolled (592 in the eBEACOPP group, 591 in the BrECADD group; 692 men, 491 women). FSH measurements were available for 767 patients (420 men and 347 women). Median follow-up was 49·6 months (IQR 39·7–58·4). BrECADD was associated with significantly higher 4-year gonadal function recovery rates compared with eBEACOPP (95·3% [95% CI 92·0–98·8] in the BrECADD group vs 73·3% [66·9–80·4] in the eBEACOPP group, HR 1·69 [95% CI 1·34–2·14] in women; 85·6% [80·8–90·8] vs 39·7% [33·6–46·9], HR 3·28 [2·51–4·30] in men). AMH and inhibin B concentrations were generally higher in the BrECADD group compared with the eBEACOPP group. A total of 92 pregnancies were reported among female patients, and 36 among partners of male patients. These led to 108 reported childbirths in 99 patients (59 in the BrECADD group and 40 in the eBEACOPP group). After therapy, 5-year incidence of parenthood was significantly higher in men (9·3% [95% CI 6·0–14·5] vs 3·3% [1·7–6·5], p=0·014), but not significantly higher in women (19·3% [13·7–27·3] vs 17·1% [11·9–24·6], p=0·53) with BrECADD versus eBEACOPP. INTERPRETATION: Compared with eBEACOPP, BrECADD led to significantly better gonadal function recovery, as well as higher parenthood rates (significantly so in men). These findings support BrECADD as preferred first-line therapy, especially for patients wishing to preserve fertility
Additional file 2 of Co-option of an endogenous retrovirus (LTR7-HERVH) in early human embryogenesis: becoming useful and going unnoticed
No full textSupplementary Material 2: Table S2. Frequency of near-perfect TP53 sites (Two 10-mer (10 nucleotides (nt)) half-sites, linked by a short spacer region of 0–13 nt) in selected ERVs in the human genome (data source from [132])
ST6GAL1 promotes IBD B cell recruitment to the inflamed colon in a CD22-dependent mechanism
No full textBACKGROUND AND AIMS: Since the discovery that auto-reactive anti-αvβ6 integrin antibodies are associated with ulcerative colitis, cells from the B cell lineage, especially plasmablasts and plasma cells have increasingly come into the focus of research on inflammatory bowel disease. However, the mechanisms regulating their recruitment from the circulation to the gut remain poorly understood. Here, we explored whether the B cell-specific lectin CD22 interacts with endothelial α2,6-linked sialic acid residues attached by ST6GAL1 to mediate such recruitment in IBD. METHODS: Flow cytometry, transcriptomics, immunofluorescence, dynamic adhesion assays, and in vivo homing assays were employed to study the role of ST6GAL1 and CD22 in regulating B cell trafficking to the inflamed gut. RESULTS: Plasmablasts were relatively reduced in the circulating B cell compartment of patients with IBD. CD22 was expressed on the majority of B cells and plasmablasts. ST6GAL1 was expressed on vessels in the colon and its expression was nominally increased in IBD. The interaction of CD22 with α2,6-linked sialic acids controlled dynamic B cell adhesion in vitro and, consistently, the in vivo gut homing of IBD B cells to the inflamed colon could be blocked by anti-CD22 antibodies in humanized mice. CONCLUSIONS: Our findings suggest that endothelial ST6GAL1 creates a pro-adhesive microenvironment rich in α2,6-sialic acids that engage CD22 on circulating B cells and plasmablasts to promote their recruitment into the inflamed gut mucosa. This pathway might be a novel target to interfere with B lineage cell homing and local auto-antibody production
Artifacts in cardiac T1 and T2 mapping techniques - influence on reliable quantification
Get PDFCardiac T1 and T2 mapping techniques are well-established methods for obtaining quantitative pixelwise representations of myocardial tissue properties. Mapping images are commonly evaluated quantitatively, and their resulting values play a crucial role in diagnosis and therapeutic decision-making in various cardiac pathologies. Despite the validated effectiveness of these techniques, both methodological and patient-specific confounders must be considered when applying them in clinical and research settings. Artifacts—erroneous features within the magnetic resonance image—can be misinterpreted as true anatomical structures or pathologies, potentially confounding quantitative analyses, conducted by both human readers and artificial intelligence algorithms. Artifacts can arise from sources such as patient motion, metal objects, hardware constraints, patient-specific scanner adjustments (e.g., flip-angle calibration), and processing errors, particularly within the complex environment of cardiac imaging. While artifact sources in other cardiovascular magnetic resonance sequences are well-documented, cardiac parametric mapping presents unique challenges due to its distinct image generation and quantitative assessment. This article provides an overview of artifacts encountered in cardiac T1 and T2 mapping, along with a concise explanation of their origins, aiming to raise awareness of their potential impact on clinical decision-making. Future developments, including sequences designed to mitigate mapping artifacts, are also briefly discussed. A strong interaction between scientists and clinicians is needed to overcome these challenges and maintain the reliability of quantification results
Low-grade, systemic inflammation and the risk of perioperative neurocognitive disorders in an observational study of older adults
Get PDFAIMS: The neuroinflammatory response to surgery may contribute to the pathogenesis of postoperative delirium (POD) and cognitive dysfunction (POCD), but whether inflammation before surgery enhances the risk of developing these conditions is unclear. Here, we investigate the relationship between preoperative levels of inflammation markers and the risk of POD/POCD. METHDS: 697 surgical patients aged ≥ 65 years were recruited 2014–2017 in Utrecht, the Netherlands and Berlin, Germany into the BioCog study. C-reactive protein (CRP), S100A12, interleukin-6 (IL-6) and IL-18 were measured immediately before surgery. POD was assessed twice daily up to 7 days/hospital discharge. POCD was determined from neuropsychological testing before surgery and 3 months thereafter. Multiple logistic regression analyses were run adjusted for age, sex, surgery site, and BMI. RESULTS: 140 out of 697 patients (20.1%) developed POD during 7 days/by discharge; 50 out of 469 patients (10.9%) attending the 3-month follow-up developed POCD. CRP ≥ 10 mg/L was found in 149 patients and was not associated with POD/POCD. Among patients with CRP < 10 mg/L, higher S100A12 and higher CRP concentrations were each associated with higher POD risk (OR per SD higher concentrations, S100A12, 1.26, 95% CI 1.03, 1.54; CRP,1.42, 95% CI 1.15, 1.76). Higher S100A12 was associated with higher POCD risk (OR 1.40 per SD, 95% CI 1.04, 1.88). No associations were found for IL-6 and IL-18. Of note, only the result on CRP and POD survived Bonferroni correction with cut-off p < 0.006. CONCLUCION: Lowgrade inflammation may influence individual vulnerability to cognitive complications of surgery. Our results warrant further examination. TRIAL REGISTRATION: NCT02265263
CSF biomarkers of neuroinflammation are associated with regional atrophy
Get PDFBACKGROUND: Neuroinflammation is central to Alzheimer’s disease (AD) pathogenesis, yet its contribution to region‐specific brain atrophy remains unclear. We examined whether cerebrospinal fluid (CSF) biomarkers predict longitudinal atrophy in the hippocampus and basal forebrain and mediate the impact of AD pathology. METHODS: Data from 227 DELCODE participants with baseline CSF measures and longitudinal structural MRI were analyzed. Four latent factors (synaptic, microglia, chemokine/cytokine, complement) were derived to capture shared variance across biomarkers. Latent factors represent unobserved biological domains inferred from related CSF markers. In addition, four single biomarkers (neurogranin, sTREM2, YKL-40, ferritin) were tested separately. Regional atrophy rates were estimated using linear mixed-effects models including biomarker × time, A/T classification, diagnosis, and covariates (age, sex, education, ApoE-ε4). Individual slopes were then entered into mediation models. RESULTS: Higher synaptic latent factor (β = - 0.019, pFDR = 0.021) and YKL-40 (β = - 0.020, pFDR = 0.025) significantly predicted hippocampal atrophy. Only these two markers remained significant after correction for multiple comparisons. Mediation analyses revealed significant indirect effects of the synaptic latent factor and YKL-40 on hippocampal atrophy across all A/T groups. No biomarker was associated with basal forebrain atrophy (pFDR > 0.05). CONCLUSIONS: Latent factors captured shared biological variance across related biomarkers and provided a more robust representation of underlying biological domains than single biomarkers. This approach identified synaptic dysfunction and astroglial activation as key links between AD pathology and hippocampal neurodegeneration. These findings highlight synaptic and glial pathways as promising targets for disease-modifying interventions
Automated phenotyping of rodent behavior in the Novel Cylinder Test using machine learning
No full textRodent models are essential in neuroscience research for investigating brain function, CNS disease mechanisms, and therapeutic interventions. Beyond molecular and physiological analyses, precise behavioral characterization provides crucial functional readouts of neural circuit changes. Accurate behavioral phenotyping is critical for detecting genotype-phenotype relationships, enabling cross-model comparisons, and measuring treatment efficacy. Here we developed a machine learning framework for automated rodent behavior analysis in the Novel Cylinder Test (NCT) using pose estimation and explainable machine learning. The framework quantifies freezing, rearing, exploratory movement, and general locomotion activity while identifying key behavioral features that differentiate between experimental conditions. To validate this approach, we phenotyped two rat strains with dopaminergic and serotonergic dysfunction: dopamine transporter knockout (DAT-KO), tryptophan hydroxylase 2 knockout (Tph2-KO), and their wild-type controls. The analysis successfully identified distinct strain-specific behavioral phenotypes and characterized the discriminative features between genotypes, achieving high classification accuracy (AUC = 0.84 for DAT-KO versus DAT-WT and AUC = 0.98 for Tph2-KO versus Tph2-WT). These findings demonstrate that automated NCT can detect genotype-specific signatures and establish a scalable method for standardized phenotyping in preclinical neuroscience