Prediction Model for Lumbar Curve Correction after Selective Thoracic Fusion in Lenke 1 and 2 Adolescent Idiopathic Scoliosis.

STUDY DESIGN: A retrospective study. OBJECTIVE: To identify independent risk factors and construct a prediction model for lumbar curve correction (LCC) after selective thoracic fusion (STF) in patients with Lenke 1 and 2 adolescent idiopathic scoliosis (AIS). SUMMARY OF BACKGROUND DATA: STF has been widely applied in Lenke 1 and 2 AIS patients. However, LCC after STF is still controversial. METHODS: 128 patients undergoing STF with at least 2 years follow-up were included. Cases were divided into high-LCC group and low-LCC group according to a rounded-up median of 65%. 49 variables were taken into account. Logistic regression was applied to identify independent predictive factors. Prediction model was established by backward stepwise regression, and its evaluation was implemented on R. RESULTS: Five parameters showed independent predictive value for low LCC: Right shoulder higher before surgery [right shoulder higher vs. balanced: odds ratio (OR)=0.244, P=0.014], postoperative Cobb angle of lumbar curve (LC) (OR=1.415, P=0.001, cut-off value=11°), lowest instrumented vertebra (LIV) distal to end vertebra (no vs. yes: OR=4.587, P=0.013), postoperative LIV tilt (OR=0.686, P=0.010, cut-off value=6.85°) and postoperative LIV+1 tilt (OR=1.522, P=0.005, cut-off value=6.25°). The prediction model included six variables: lumbar modifier, preoperative shoulder balance, postoperative Cobb angle of LC, LIV position, postoperative LIV tilt and postoperative LIV+1 tilt. Model evaluation demonstrated satisfactory capability and stability [area under curve=0.890, 10-fold cross-validation accuracy=0.782]. CONCLUSION: Preoperative shoulder balance, Cobb angle of LC, LIV position, postoperative LIV and LIV+1 tilt could be used to prognosticate LCC after STF. A model with solid prediction ability was established, which could further our understanding of LCC and assist in making clinical decisions.

Integrative analysis of cancer multimodality data identifying COPS5 as a novel biomarker of diffuse large B-cell lymphoma.

Preventing, diagnosing, and treating diseases requires accurate clinical biomarkers, which remains challenging. Recently, advanced computational approaches have accelerated the discovery of promising biomarkers from high-dimensional multimodal data. Although machine-learning methods have greatly contributed to the research fields, handling data sparseness, which is not unusual in research settings, is still an issue as it leads to limited interpretability and performance in the presence of missing information. Here, we propose a novel pipeline integrating joint non-negative matrix factorization (JNMF), identifying key features within sparse high-dimensional heterogeneous data, and a biological pathway analysis, interpreting the functionality of features by detecting activated signaling pathways. By applying our pipeline to large-scale public cancer datasets, we identified sets of genomic features relevant to specific cancer types as common pattern modules (CPMs) of JNMF. We further detected COPS5 as a potential upstream regulator of pathways associated with diffuse large B-cell lymphoma (DLBCL). COPS5 exhibited co-overexpression with MYC, TP53, and BCL2, known DLBCL marker genes, and its high expression was correlated with a lower survival probability of DLBCL patients. Using the CRISPR-Cas9 system, we confirmed the tumor growth effect of COPS5, which suggests it as a novel prognostic biomarker for DLBCL. Our results highlight that integrating multiple high-dimensional data and effectively decomposing them to interpretable dimensions unravels hidden biological importance, which enhances the discovery of clinical biomarkers.

An organometallic swap strategy for bottlebrush polymer-protein conjugate synthesis.

Polymer-protein bioconjugation offers a powerful strategy to alter the physical properties of proteins, and various synthetic polymer compositions and architectures have been investigated for this purpose. Nevertheless, conjugation of molecular bottlebrush polymers (BPs) to proteins remains an unsolved challenge due to the large size of BPs and a general lack of methods to transform the chain ends of BPs into functional groups suitable for bioconjugation. Here, we present a strategy to address this challenge in the context of BPs prepared by "graft-through" ring-opening metathesis polymerization (ROMP), one of the most powerful methods for BP synthesis. Quenching ROMP of PEGylated norbornene macromonomers with an activated enyne terminator facilitates the transformation of the BP Ru alkylidene chain ends into Pd oxidative addition complexes (OACs) for facile bioconjugation. This strategy is shown to be effective for the synthesis of two BP-protein conjugates (albumin and ERG), setting the stage for a new class of BP-protein conjugates for future therapeutic and imaging applications.

Fluorine Incorporation for Enhanced Gas Separation Performance in Porous Organic Polymers: Investigating Reaction Pathways and Pore Structure Control.

The precise control of pore structures in porous organic polymer (POP) materials is of paramount importance in addressing a wide range of challenges associated with gas separation processes. In this study, we present a novel approach to optimize the gas separation performance of POPs through the introduction of fluorine groups and figure out an important factor of reaction decision that whether the AlCl3-catalyzed polymerization is Scholl reaction or Friedel-Crafts alkylation. In the chloroform system, the steric hindrance of function groups could make direct coupling between the benzene rings difficult, which would lead to part solvent knitting (Friedel-Crafts alkylation) instead. The fluorinated polymers show enhanced surface area and pore size characteristics. Notably, the fluorinated polymers exhibited significantly improved adsorption and separation performance for SF6, as evidenced by an ideal adsorbed solution theory selectivity (SF6/N2, v: v = 50:50, 273 K) increase of 75.0, 668.8, and 502.8% compared to the nonfluorinated POPs. These findings highlight the potential of fluorination as a strategy for tailoring the properties of POP materials for advanced gas separation applications.