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The structural exploration of three-dimensional covalent organic frameworks (3D COFs) is of great significance to the development of COF materials. Different from structurally diverse MOFs, which have a variety of connectivity (3-24), now the valency of 3D COFs is limited to only 4, 6, and 8. Therefore, the exploration of organic building blocks with higher connectivity is a necessary path to broaden the scope of 3D COF structures. Herein, for the first time, we have designed and synthesized a 12-connected triptycene-based precursor (triptycene-12-CHO) with 12 symmetrical distributions of aldehyde groups, which is also the highest valency reported until now. Based on this unique 12-connected structure, we have successfully prepared a novel 3D COF with lnj topology (termed 3D-lnj-COF). The as-synthesized 3D COF exhibits honeycomb main pores and permanent porosity with a Brunauer-Emmett-Teller surface area of 1159.6 m2 g-1. This work not only provides a strategy for synthesizing precursors with a high connectivity but also provides inspiration for enriching the variety of 3D COFs.
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Pressure can alter interatomic distances and its electrostatic interactions, exerting a profound modifying effect on electron orbitals and bonding patterns. Conventional pressure engineering relies on compressions from external sources, which raises significant challenge in precisely applying pressure on individual molecules and also consume substantial mechanical energy. Here we report ultrasmall single-layered NbSe2 flat tubes (< 2.31 nm) created by self-pressurization during the deselenization of NbSe3 within carbon nanotubes (CNTs). As the internal force (4-17 GPa) is three orders of magnitude larger than the shear strength between CNTs, the flat tube is locked to prevent slippage. Electrical transport measurements indicate that the large pressure within CNTs induces enhanced intermolecular electron correlations. The strictly one-dimensional NbSe2 flat tubes harboring the Luttinger liquid (LL) state, showing a higher tunneling exponent [Formula: see text] than pure CNTs ([Formula: see text]). This work suggests a novel chemical approach to self-pressurization for generating new material configurations and modulating electron interactions.
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Background: Numerous studies have developed or validated prediction models to estimate the likelihood of postoperative pneumonia (POP) in esophageal cancer (EC) patients. The quality of these models and the evaluation of their applicability to clinical practice and future research remains unknown. This study systematically evaluated the risk of bias and applicability of risk prediction models for developing POP in patients undergoing esophageal cancer surgery. Methods: PubMed, Embase, Web of Science, Cochrane Library, Cumulative Index to Nursing and Allied Health Literature (CINAHL), China National Knowledge Infrastructure (CNKI), China Science and Technology Journal Database (VIP), WanFang Database and Chinese Biomedical Literature Database were searched from inception to March 12, 2024. Two investigators independently screened the literature and extracted data. The Prediction Model Risk of Bias Assessment Tool (PROBAST) checklist was employed to evaluate both the risk of bias and applicability. Result: A total of 14 studies involving 23 models were included. These studies were mainly published between 2014 and 2023. The applicability of all studies was good. However, all studies exhibited a high risk of bias, primarily attributed to inappropriate data sources, insufficient sample size, irrational treatment of variables and missing data, and lack of model validation. The incidence of POP in patients undergoing esophageal cancer surgery ranged from 14.60% to 39.26%. The most frequently used predictors were smoking, age, chronic obstructive pulmonary disease(COPD), diabetes mellitus, and methods of thoracotomy. Inter-model discrimination ranged from 0.627 to 0.850, sensitivity ranged between 60.7% and 84.0%, and specificity ranged from 59.1% to 83.9%. Conclusion: In all included studies, good discrimination was reported for risk prediction models for POP in patients undergoing esophageal cancer surgery, indicating stable model performance. However, according to the PROBAST checklist, all studies had a high risk of bias. Future studies should use the predictive model assessment tool to improve study design and develop new models with larger samples and multicenter external validation. Systematic review registration: https://www.crd.york.ac.uk/prospero, identifier CRD42024527085.
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Traumatic brain injury is a serious medical condition that can be attributed to falls, motor vehicle accidents, sports injuries and acts of violence, causing a series of neural injuries and neuropsychiatric symptoms. However, limited accessibility to the injury sites, complicated histological and anatomical structure, intricate cellular and extracellular milieu, lack of regenerative capacity in the native cells, vast variety of damage routes, and the insufficient time available for treatment have restricted the widespread application of several therapeutic methods in cases of central nervous system injury. Tissue engineering and regenerative medicine have emerged as innovative approaches in the field of nerve regeneration. By combining biomaterials, stem cells, and growth factors, these approaches have provided a platform for developing effective treatments for neural injuries, which can offer the potential to restore neural function, improve patient outcomes, and reduce the need for drugs and invasive surgical procedures. Biomaterials have shown advantages in promoting neural development, inhibiting glial scar formation, and providing a suitable biomimetic neural microenvironment, which makes their application promising in the field of neural regeneration. For instance, bioactive scaffolds loaded with stem cells can provide a biocompatible and biodegradable milieu. Furthermore, stem cells-derived exosomes combine the advantages of stem cells, avoid the risk of immune rejection, cooperate with biomaterials to enhance their biological functions, and exert stable functions, thereby inducing angiogenesis and neural regeneration in patients with traumatic brain injury and promoting the recovery of brain function. Unfortunately, biomaterials have shown positive effects in the laboratory, but when similar materials are used in clinical studies of human central nervous system regeneration, their efficacy is unsatisfactory. Here, we review the characteristics and properties of various bioactive materials, followed by the introduction of applications based on biochemistry and cell molecules, and discuss the emerging role of biomaterials in promoting neural regeneration. Further, we summarize the adaptive biomaterials infused with exosomes produced from stem cells and stem cells themselves for the treatment of traumatic brain injury. Finally, we present the main limitations of biomaterials for the treatment of traumatic brain injury and offer insights into their future potential.
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Carbon nanomaterials are unique with excellent functionality and diverse structures. However, agglomerated structures are commonly formed because of small-size effects and surface effects. Their hierarchical assembly into micro particles enables carbon nanomaterials to break the boundaries of classical Geldart particle classification before stable fluidization under gas-solid interactions. Currently, there are few systematic reports regarding the structural evolution and fluidization mechanism of carbon nano agglomerations. Based on existing research on carbon nanomaterials, this article reviews the fluidized structure control and fluidization principles of prototypical carbon nanotubes (CNTs) as well as their nanocomposites. The controlled agglomerate fluidization technology leads to the successful mass production of agglomerated and aligned CNTs. In addition, the self-similar agglomeration of individual ultralong CNTs and nanocomposites with silicon as model systems further exemplify the important role of surface structure and particle-fluid interactions. These emerging nano agglomerations have endowed classical fluidization technology with more innovations in advanced applications like energy storage, biomedical, and electronics. This review aims to provide insights into the connections between fluidization and carbon nanomaterials by highlighting their hierarchical structural evolution and the principle of agglomerated fluidization, expecting to showcase the vitality and connotation of fluidization science and technology in the new era.