Biology subjects

Ritchlin, C. T.

Publications and source records attributed to Ritchlin, C. T..

3 recordsLinked to original sources

bioRxiv2025

Automated Joint Space Detection Improves Bone Segmentation Accuracy

Quantitative description of complex anatomical structures remains challenging due to the expertise necessary for manual segmentation, labor, and interobserver variability. To overcome this, automated detection of specific landmarks can be provided by digital image analysis techniques including deep learning (DL) models. To this end, we undertook supervised automated analysis of micro-computed tomography (micro-CT) datasets of murine hindpaws and forepaws (30-33 bones). Advancing beyond previously published semi-automated (SA) marker-based watershed algorithms, we added structure enhancement, tensor voting, and output dilation to identify joint spaces. Segmentation was enhanced by the use of a DL joint space prediction model (3D U-Net architecture, ResNet-18 backbone) using wild-type (WT) hindpaw labels as ground truth. Prediction was then extended to hindpaws (52.4% in test group) and forepaws from WT and tumor necrosis factor transgenic (TNF-Tg) mice with inflammatory-erosive arthritis of both sexes across age. Segmentation accuracy improved dramatically using the DL methodology (WT male: SA 79.39{+/-}5.73% vs DL 98.16{+/-}1.47%, p<0.0001; WT female: SA 79.16{+/-}4.84% vs DL 99.19{+/-}1.63%, p<0.0001). Accuracy declined with increased disease severity and age in TNF-Tg mice (TNF-Tg male 93.54{+/-}4.73%, female 91.81{+/-}2.80%, p[≤]0.01). Subsequent testing in forepaws also displayed progressive reduction in accuracy with increasing arthritic severity (i.e., WT 87.29{+/-}2.07%, TNF-Tg male 72.65{+/-}11.70%, p<0.0001). Overall, this supervised automated model outperforms recent SA approaches in healthy joints to enhance investigation of complex bone anatomy. Although flexible application to novel and disease-modified datasets demonstrates deprecated performance, utilization may nonetheless catalyze structure-specific segmentation model development.

pathology↗

bioRxiv2022

Multi-omics Analysis Identifies IgG2b Class-Switching with ALCAM-CD6 Co-Stimulation in Lymph Nodes During Advanced Inflammatory-Erosive Arthritis

Defective lymphatic drainage and B-cell translocation into joint-draining lymph node sinuses are pathogenic phenomena in patients with severe rheumatoid arthritis (RA). However, the molecular mechanisms underlying this lymphatic dysfunction remain poorly understood. Here, by utilizing spatial and single-cell transcriptomics in tumor necrosis factor transgenic (TNF-Tg) mice, we characterized functional genomic changes in popliteal lymph nodes (PLNs) of "Early" and "Advanced" RA to determine the mechanisms orchestrating B-cell differentiation. We first show that Ighg2b expression localized to Marco+ sinuses and negatively correlated with bone volumes in ipsilateral joints. We further reveal that Advanced PLNs exhibited a concomitant accumulation of iron-laden macrophages and T-cells. Mechanistically, crosstalk between ALCAM+ macrophages and CD6+ T-cells was identified as a co-stimulatory pathway promoting IgG2b class-switching. These findings were validated by immunohistochemistry, flow cytometry, ELISPOT, and clinical correlates. Collectively, we propose that ALCAM-CD6 co-stimulation activates T cells, initiating IgG2b class-switching and plasma cell differentiation in RA flare.

immunology↗

bioRxiv2020

Ex vivo Demonstration of Functional Deficiencies in Popliteal Lymphatic Vessels from TNF-Tg Mice with Inflammatory Arthritis

BackgroundRheumatoid arthritis (RA) is a progressive immune-mediated inflammatory disease characterized by intermittent episodes of pain and inflammation in affected joints, or flares. Recent studies demonstrated lymphangiogenesis and expansion of draining lymph nodes during chronic inflammatory arthritis, and lymphatic dysfunction associated with collapse of draining lymph nodes in RA patients and TNF-transgenic (TNF-Tg) mice experiencing arthritic flare. As the intrinsic differences between lymphatic vessels afferent to healthy, expanding, and collapsed draining lymph nodes are unknown, we characterized the ex vivo behavior of popliteal lymphatic vessels (PLVs) from WT and TNF-Tg mice. We also interrogated the mechanisms of lymphatic dysfunction through inhibition of nitric oxide synthase (NOS). MethodsPopliteal lymph nodes (PLNs) in TNF-Tg mice were phenotyped as Expanding or Collapsed by in vivo ultrasound and age-matched to WT littermate controls. The PLVs were harvested and cannulated for ex vivo functional analysis over a relatively wide range of hydrostatic pressures (0.5 to 10 cmH2O) to quantify the end diastolic diameter (EDD), tone, amplitude (AMP), ejection fraction (EF), contraction frequency (FREQ) and fractional pump flow (FPF) with or without NOS inhibitors Data was analyzed using repeated measures two-way ANOVA with Bonferronis post hoc test. ResultsReal time videos of the cannulated PLVs demonstrated the predicted phenotypes of robust versus weak contractions of the WT versus TNF-Tg PLV, respectively. Quantitative analyses confirmed that TNF-Tg PLVs had significantly decreased AMP, EF and FPF versus WT (p<0.05). EF and FPF were recovered by NOS inhibition, while the reduction in AMP was NOS independent. No differences in EDD, tone, or FREQ were observed between WT and TNF-Tg PLVs, nor between Expanding versus Collapsed PLVs. ConclusionThese findings support the concept that chronic inflammatory arthritis leads to NOS dependent and independent draining lymphatic vessel dysfunction that exacerbates disease, and may trigger arthritic flare due to decreased egress of inflammatory cells and soluble factors from affected joints.

pathology↗