Image_1_The association between graded prognostic assessment and the prognosis of brain metastases after whole brain radiotherapy: a meta-analysis.tiff

IntroductionThis meta-analysis aims to provide evidence-based medical evidence for formulating rational treatment strategies and evaluating the prognosis of brain metastasis (BM) patients by assessing the effectiveness of the graded prognostic assessment (GPA) model in predicting the survival prognosis of patients with BM after whole-brain radiotherapy (WBRT).MethodsA comprehensive search was conducted in multiple databases, including the China Biomedical Literature Database (CBM), China National Knowledge Infrastructure (CNKI), PubMed, Wanfang database, Cochrane Library, Web of Science, and Embase. Cohort studies that met the inclusion and exclusion criteria were selected. The quality of the included literature was evaluated using the Newcastle-Ottawa Scale, and all statistical analyses were performed with R version 4.2.2. The effect size (ES) was measured by the hazard ratio (HR) of overall survival (OS). The OS rates at 3, 6, 12, and 24 months of patients with BM were compared between those with GPAs of 1.5–2.5, 3.0, and 3.5–4.0 and those with GPAs of 0–1 after WBRT.ResultsA total of 1,797 participants who underwent WBRT were included in this study. The meta-analysis revealed a significant association between GPA and OS rates after WBRT: compared with BM patients with GPA of 0–1, 3-month OS rates after WBRT were significantly higher in BM patients with GPA of 1.5–2.5 (HR = 0.48; 95% CI: 0.40–0.59), GPA of 3 (HR = 0.38; 95% CI: 0.25–0.57), and GPA of 3.5–4 (HR = 0.28; 95% CI: 0.15–0.52); 6-month OS rates after WBRT were significantly higher in BM patients with GPA of 1.5–2.5 (HR = 0.48; 95% CI: 0.41–0.56), GPA of 3 (HR = 0.33; 95% CI: 0.24–0.45), and GPA of 3.5–4 (HR = 0.24; 95% CI: 0.16–0.35); 12-month OS rates after WBRT were significantly higher in BM patients with GPA of 1.5–2.5 (HR = 0.49; 95% CI: 0.41–0.58), GPA of 3 (HR = 0.48; 95% CI: 0.32–0.73), and GPA of 3.5–4 (HR = 0.31; 95% CI: 0.12–0.79); and 24-month OS rates after WBRT were significantly higher in BM patients with GPA of 1.5–2.5 (HR = 0.49; 95% CI: 0.42–0.58), GPA of 3 (HR = 0.49; 95% CI: 0.32–0.74), and GPA of 3.5–4 (HR = 0.38; 95% CI: 0.15–0.94).ConclusionBM patients with higher GPAs generally exhibited better prognoses and survival outcomes after WBRT compared to those with lower GPAs.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/, identifier CRD42023422914.</p

Image_2_The association between graded prognostic assessment and the prognosis of brain metastases after whole brain radiotherapy: a meta-analysis.tiff

IntroductionThis meta-analysis aims to provide evidence-based medical evidence for formulating rational treatment strategies and evaluating the prognosis of brain metastasis (BM) patients by assessing the effectiveness of the graded prognostic assessment (GPA) model in predicting the survival prognosis of patients with BM after whole-brain radiotherapy (WBRT).MethodsA comprehensive search was conducted in multiple databases, including the China Biomedical Literature Database (CBM), China National Knowledge Infrastructure (CNKI), PubMed, Wanfang database, Cochrane Library, Web of Science, and Embase. Cohort studies that met the inclusion and exclusion criteria were selected. The quality of the included literature was evaluated using the Newcastle-Ottawa Scale, and all statistical analyses were performed with R version 4.2.2. The effect size (ES) was measured by the hazard ratio (HR) of overall survival (OS). The OS rates at 3, 6, 12, and 24 months of patients with BM were compared between those with GPAs of 1.5–2.5, 3.0, and 3.5–4.0 and those with GPAs of 0–1 after WBRT.ResultsA total of 1,797 participants who underwent WBRT were included in this study. The meta-analysis revealed a significant association between GPA and OS rates after WBRT: compared with BM patients with GPA of 0–1, 3-month OS rates after WBRT were significantly higher in BM patients with GPA of 1.5–2.5 (HR = 0.48; 95% CI: 0.40–0.59), GPA of 3 (HR = 0.38; 95% CI: 0.25–0.57), and GPA of 3.5–4 (HR = 0.28; 95% CI: 0.15–0.52); 6-month OS rates after WBRT were significantly higher in BM patients with GPA of 1.5–2.5 (HR = 0.48; 95% CI: 0.41–0.56), GPA of 3 (HR = 0.33; 95% CI: 0.24–0.45), and GPA of 3.5–4 (HR = 0.24; 95% CI: 0.16–0.35); 12-month OS rates after WBRT were significantly higher in BM patients with GPA of 1.5–2.5 (HR = 0.49; 95% CI: 0.41–0.58), GPA of 3 (HR = 0.48; 95% CI: 0.32–0.73), and GPA of 3.5–4 (HR = 0.31; 95% CI: 0.12–0.79); and 24-month OS rates after WBRT were significantly higher in BM patients with GPA of 1.5–2.5 (HR = 0.49; 95% CI: 0.42–0.58), GPA of 3 (HR = 0.49; 95% CI: 0.32–0.74), and GPA of 3.5–4 (HR = 0.38; 95% CI: 0.15–0.94).ConclusionBM patients with higher GPAs generally exhibited better prognoses and survival outcomes after WBRT compared to those with lower GPAs.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/, identifier CRD42023422914.</p

Synergistic Toughening of Bioinspired Poly(vinyl alcohol)–Clay–Nanofibrillar Cellulose Artificial Nacre

Inspired by the layered aragonite platelet/nanofibrillar chitin/protein ternary structure and integration of extraordinary strength and toughness of natural nacre, artificial nacre based on clay platelet/nanofibrillar cellulose/poly(vinyl alcohol) is constructed through an evaporation-induced self-assembly technique. The synergistic toughening effect from clay platelets and nanofibrillar cellulose is successfully demonstrated. The artificial nacre achieves an excellent balance of strength and toughness and a fatigue-resistant property, superior to natural nacre and other conventional layered clay/polymer binary composites

Bioinspired Hierarchical Alumina–Graphene Oxide–Poly(vinyl alcohol) Artificial Nacre with Optimized Strength and Toughness

Due to hierarchical organization of micro- and nanostructures, natural nacre exhibits extraordinary strength and toughness, and thus provides a superior model for the design and fabrication of high-performance artificial composite materials. Although great progress has been made in constructing layered composites by alternately stacking hard inorganic platelets and soft polymers, the real issue is that the excellent strength of these composites was obtained at the sacrifice of toughness. In this work, inspired by the layered aragonite microplatelets/chitin nanofibers–protein structure of natural nacre, alumina microplatelets–graphene oxide nanosheets–poly­(vinyl alcohol) (Al₂O₃/GO–PVA) artificial nacre is successfully constructed through layer-by-layer bottom-up assembly, in which Al₂O₃ and GO–PVA act as “bricks” and “mortar”, respectively. The artificial nacre has hierarchical “brick-and-mortar” structure and exhibits excellent strength (143 ± 13 MPa) and toughness (9.2 ± 2.7 MJ/m³), which are superior to those of natural nacre (80–135 MPa, 1.8 MJ/m³). It was demonstrated that the multiscale hierarchical structure of ultrathin GO nanosheets and submicrometer-thick Al₂O₃ platelets can deal with the conflict between strength and toughness, thus leading to the excellent mechanical properties that cannot be obtained using only one size of platelet. We strongly believe that the work presented here provides a creative strategy for designing and developing new composites with excellent strength and toughness

Quantitative Design of Regulatory Elements Based on High-Precision Strength Prediction Using Artificial Neural Network

<div><p>Accurate and controllable regulatory elements such as promoters and ribosome binding sites (RBSs) are indispensable tools to quantitatively regulate gene expression for rational pathway engineering. Therefore, <i>de novo</i> designing regulatory elements is brought back to the forefront of synthetic biology research. Here we developed a quantitative design method for regulatory elements based on strength prediction using artificial neural network (ANN). One hundred mutated Trc promoter & RBS sequences, which were finely characterized with a strength distribution from 0 to 3.559 (relative to the strength of the original sequence which was defined as 1), were used for model training and test. A precise strength prediction model, NET90_19_576, was finally constructed with high regression correlation coefficients of 0.98 for both model training and test. Sixteen artificial elements were <i>in silico</i> designed using this model. All of them were proved to have good consistency between the measured strength and our desired strength. The functional reliability of the designed elements was validated in two different genetic contexts. The designed parts were successfully utilized to improve the expression of BmK1 peptide toxin and fine-tune deoxy-xylulose phosphate pathway in <i>Escherichia coli</i>. Our results demonstrate that the methodology based on ANN model can <i>de novo</i> and quantitatively design regulatory elements with desired strengths, which are of great importance for synthetic biology applications.</p> </div

Collective motions obtained by principal component analysis on the simulation trajectory.

<p>(A) and (B) Motions corresponding to PC1 and PC2 of the unliganded α-HL, which account for 68.7 and 19.8% of the total movements, respectively. (C) and (D) Motions corresponding to PC1 and PC2 of the α-HL-OLG complex, which account for 65.4% and 18.7% of the total movements, respectively.</p

Promoter & RBS sequence design based on ANN prediction model.

<p>(A) Sequence with desired strength can be designed by the following strategies: i) 8 out of 10,000 sequences (s01–s08) are randomly selected from an <i>in silico</i> Trc promoter & RBS library generated based on ANN predicting model NET90_19_576; ii) sequences (s11–s15) with desired strength can be generated by repeated introduction of random mutations into the wild-type sequence under a certain mutation rate; iii) sequences (s21–s23) with desired strength can be generated by using different combinations of ‘key site’ mutations based on the prediction of NET90_19_576. All designed sequences were synthesized and their strengths were tested and compared with the design strength.</p

Hierarchical Layered Heterogeneous Graphene-poly(<i>N</i>‑isopropylacrylamide)-clay Hydrogels with Superior Modulus, Strength, and Toughness

Biological composites are renowned for their elaborate heterogeneous architectures at multiple scales, which lead to a unique combination of modulus, strength, and toughness. Inspired by biological composites, mimicking the heterogeneous structural design principles of biological composites is a powerful strategy to construct high-performance structural composites. Here, we creatively transfer some heterogeneous principles of biological composites to the structural design of nanocomposite hydrogels. Unique heterogeneous conductive graphene-PNIPAM-clay hydrogels are prepared through a combination of inhomogeneous water removal processes, <i>in situ</i> free-radical polymerization, and chemical reduction of graphene oxide. The nanocomposite hydrogels exhibit hierarchical layered heterogeneous architectures with alternate stacking of dense laminated layers and loose porous layers. Under tensile load, the stiff dense laminated layers serve as sacrificial layers that fracture at a relatively low strain, while the stretchable loose porous layers serve as energy dissipation layers by large extension afterward. Such local inhomogeneous deformation of the two heterogeneous layers enables the nanocomposite hydrogels to integrate superior modulus, strength, and toughness (9.69 MPa, 0.97 MPa, and 5.60 MJ/m³, respectively). The study might provide meaningful enlightenments for rational structural design of future high-performance nanocomposite hydrogels

The RMS fluctuations of the whole residues in the complex and free α-HL.

<p>The region of the protein backbone exhibits different fluctuations, which are dependent on the local environment (binding with inhibitors), specifically residues 100–150. The region is highlighted with gray bars.</p

Application of designed elements for peptide BmK1 expression and DXP pathway engineering in <i>E. coli</i>.

<p>(A) Sketch maps of plasmids for designed elements applications. Plasmids s21-<i>gfp</i>, s05-<i>gfp</i> and s14-<i>gfp</i> contain gene <i>gfp</i> between BamHI/EcoRI sites, plasmids s21-<i>bmk</i>1, s05-<i>bmk</i>1 and s14-<i>bmk</i>1 contain gene <i>bmk</i>1 between NcoI/HindIII sites, plasmids s21-<i>dxs</i>, s05-<i>dxs</i> and s14-<i>dxs</i> contain gene <i>dxs</i> between NcoI/EcoRI sites. (B) Effect of applying designed elements for peptide BmK1 expression and DXP pathway engineering in <i>E. coli</i>. The wild-type Trc promoter and RBS (without inserting <i>dxs</i> gene) served as the blank control.</p