Distraction osteogenesis (DO) remains limited by prolonged consolidation and delayed bone union. This study evaluated whether a biodegradable, bone morphogenetic protein-2 (BMP-2)-releasing intramedullary implant (IMI) could enhance bone regenerate formation in a rat monofocal femoral lengthening model. We developed a Hybrid Tissue Engineering Construct (HyTEC) comprising a 3D-printed polycaprolactone-β-tricalcium phosphate IMI coated with a BMP-2-loaded hydrogel. Rats underwent standardized lengthening in three groups: control (DO only), IMI (implant without BMP-2), and IMI-BMP2 (BMP-2-releasing implant), with evaluation at postoperative days 31 and 52. The IMI-BMP2 group demonstrated significantly superior osteogenesis, achieving a bone volume fraction of 80 ± 22% at day 31, compared to 35 ± 19% (IMI) and 54 ± 25% (control), indicating accelerated regenerate formation. Radiographic and histological analyses confirmed early, uniform callus formation, while immunohistochemistry revealed elevated osteocalcin expression. Mechanical testing demonstrated restoration of approximately 50% of normal bone strength by day 52. Transcriptomic profiling revealed an exploratory BMP-2-associated regenerative gene signature, suggesting coordinated early-phase regulation of remodeling and metabolic reprogramming. This bioactive implant accelerated bone union, facilitated improved early ambulation consistent with partial mechanical competence restoration, and significantly shortened consolidation time, representing a promising clinically translatable strategy to overcome conventional DO limitations and improve patient outcomes. STATEMENT OF SIGNIFICANCE: Distraction osteogenesis is an effective strategy for managing large bone defects, but its clinical use is limited by prolonged consolidation and delayed functional recovery. This study presents a biodegradable intramedullary implant that provides sustained bone morphogenetic protein-2 (BMP-2) delivery and markedly accelerates regenerate formation, improves early mechanical strength, and enables earlier weight-bearing in a rat femoral lengthening model. In addition to demonstrating therapeutic efficacy, the work identifies a BMP-2-associated regenerative transcriptional signature linked to remodeling, osteoclast activity, and metabolic reprogramming. These findings establish a clinically translatable biomaterial-based approach to shorten treatment time and improve outcomes in distraction osteogenesis.
Tomohiro Uno, Tien-Ching Lee, Krish Shah et al.· Acta Biomaterialia· 0 citations
Background Highly variable gene (HVG) selection begins almost every single-cell RNA-seq analysis. While ranking formulas have been compared extensively, the integer gene budget at which any ranking must be truncated is typically left to the user and habitually fixed near 2,000. Relying on such a convention carries hidden costs—lists that are too short erase subtle structure, whereas lists that are too long add noise and computational overhead. Moreover, because global rankings measure variance across all cells, markers for rare populations often lose the “variance vote count” to dominant bulk variation, leading to an unfair feature allocation at the hard cutoff. Whether this convention is defensible, and whether the budget and tail can be set from data without disturbing the ranking, has not been examined systematically. Results Under a frozen seurat_v3 ranking, k-sweeps across 18 labeled datasets show that n = 2,000 is ARI-optimal on 1 of 18 datasets and that the best available budget is worth a mean ARI gain of +0.033 over it, establishing cardinality as a real and largely unexploited design axis. We present scFair, a Scanpy-compatible HVG layer that automates list length alone: geometry-aware auto_n sets a base size k from multi-seed density and stability features of an intermediate embedding (trading a modest, intentional compute increase for a safer data-driven default), and a same-rank append step acts as a conservative safeguard against cutoff unfairness by adding a short near-miss tail. The ranking is never recomputed or reweighted. On the 18-dataset panel, the default path improved Leiden–label agreement over HVG@2000 (median ΔARI = +0.016; 13/5; Wilcoxon P = 0.0077) and outperformed the neighborhood-based selector triku at author defaults on 15/18 datasets (median +0.024; P = 0.004), while triku did not improve on HVG@2000. Controls locate the effect: cell-number-only rules do not beat HVG@2000, an FDR-chosen length imposed on the frozen ranking is flat, and a fixed HVG@2200 default is not a general substitute because it cannot produce the short lists that compact matrices call for. Conclusions A fixed budget near 2,000 HVGs is frequently suboptimal, and list cardinality is a separable design axis that can be automated without changing the ranking formula. Effect sizes are modest, the short-list branch rests on four datasets, and rule thresholds were developed with partial overlap to the evaluation panel.
Zhao Li, Aaron W. James, Shengxuan Li· bioRxiv· 0 citations
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