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"Yuan, Jin"
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Management of acquired resistance to EGFR TKI–targeted therapy in advanced non-small cell lung cancer
Recent advances in diagnosis and treatment are enabling a more targeted approach to treating lung cancers. Therapy targeting the specific oncogenic driver mutation could inhibit tumor progression and provide a favorable prognosis in clinical practice. Activating mutations of epidermal growth factor receptor (
EGFR
) in non-small cell lung cancer (NSCLC) are a favorable predictive factor for EGFR tyrosine kinase inhibitors (TKIs) treatment. For lung cancer patients with
EGFR
-exon 19 deletions or an exon 21 Leu858Arg mutation, the standard first-line treatment is first-generation (gefitinib, erlotinib), or second-generation (afatinib) TKIs. EGFR TKIs improve response rates, time to progression, and overall survival. Unfortunately, patients with
EGFR
mutant lung cancer develop disease progression after a median of 10 to 14 months on EGFR TKI. Different mechanisms of acquired resistance to first-generation and second-generation EGFR TKIs have been reported. Optimal treatment for the various mechanisms of acquired resistance is not yet clearly defined, except for the T790M mutation. Repeated tissue biopsy is important to explore resistance mechanisms, but it has limitations and risks. Liquid biopsy is a valid alternative to tissue re-biopsy. Osimertinib has been approved for patients with T790M-positive NSCLC with acquired resistance to EGFR TKI. For other TKI-resistant mechanisms, combination therapy may be considered. In addition, the use of immunotherapy in lung cancer treatment has evolved rapidly. Understanding and clarifying the biology of the resistance mechanisms of
EGFR
-mutant NSCLC could guide future drug development, leading to more precise therapy and advances in treatment.
Journal Article
Covalent Organic Frameworks for Membrane Separation
Membranes with switchable wettability, solvent resistance, and toughness have emerged as promising materials for separation applications. However, challenges like limited mechanical strength, poor chemical stability, and structural defects during membrane fabrication hinder their widespread adoption. Covalent organic frameworks (COFs), crystalline materials constructed from organic molecules connected by covalent bonds, offer a promising solution due to their high porosity, stability, and customizable properties. The ordered structures and customizable functionality provide COFs with a lightweight framework, large surface area, and tunable pore sizes, which have attracted increasing attention for their applications in membrane separations. Recent research has extensively explored the preparation strategies of COF membranes and their applications in various separation processes. This review uniquely delves into the influence of various COF membrane fabrication techniques, including interfacial polymerization, layer‐by‐layer assembly, and in situ growth, on membrane thickness and performance. It comprehensively explores the design strategies and potential applications of these methods, with a particular focus on gas separation, oil/water separation, and organic solvent nanofiltration. Furthermore, future opportunities, challenges within this field, and potential directions for future development are proposed. The application of covalent organic frameworks (COFs) in membrane separation represents a significant breakthrough in materials science. This review explores the preparation strategies, synthesis methods, and application performance of COF membranes. It highlights the advantages of COFs in membrane separation and discusses the existing challenges and future development directions.
Journal Article
Efficient and accurate worm grinding of spur face gears according to an advanced geometrical analysis and a closed-loop manufacturing process
Worm grinding has been applied to manufacture gears to pursue high accuracy and fine surface finish. When the worm used to grind face gears is manufactured with multi-axis computer numerical control (CNC) machining, the machining accuracy is usually improved by increasing the number of tool paths with more time cost. Differently, this work proposes a generated method to improve the efficiency by dressing the worm surface with only one path, and a closed-loop manufacturing process is applied to ensure the machining accuracy. According to an advanced geometric analysis, the worm surface is practically approximated as a swept surface generated by a planar curve. Meanwhile, this curve is applied as the profile of a dressing wheel, which is used to dress the worm surface. The practical machining is carried out in a CNC machine tool, which was originally used to grind helical gears. Finally, a closed-loop manufacturing process including machining, measurement, and modification is proposed to compensate the machining errors. The proposed method is validated with simulations and practical experiments.
Journal Article
ProtPlat: an efficient pre-training platform for protein classification based on FastText
Background
For the past decades, benefitting from the rapid growth of protein sequence data in public databases, a lot of machine learning methods have been developed to predict physicochemical properties or functions of proteins using amino acid sequence features. However, the prediction performance often suffers from the lack of labeled data. In recent years, pre-training methods have been widely studied to address the small-sample issue in computer vision and natural language processing fields, while specific pre-training techniques for protein sequences are few.
Results
In this paper, we propose a pre-training platform for representing protein sequences, called ProtPlat, which uses the Pfam database to train a three-layer neural network, and then uses specific training data from downstream tasks to fine-tune the model. ProtPlat can learn good representations for amino acids, and at the same time achieve efficient classification. We conduct experiments on three protein classification tasks, including the identification of type III secreted effectors, the prediction of subcellular localization, and the recognition of signal peptides. The experimental results show that the pre-training can enhance model performance effectively and ProtPlat is competitive to the state-of-the-art predictors, especially for small datasets. We implement the ProtPlat platform as a web service (
https://compbio.sjtu.edu.cn/protplat
) that is accessible to the public.
Conclusions
To enhance the feature representation of protein amino acid sequences and improve the performance of sequence-based classification tasks, we develop ProtPlat, a general platform for the pre-training of protein sequences, which is featured by a large-scale supervised training based on Pfam database and an efficient learning model, FastText. The experimental results of three downstream classification tasks demonstrate the efficacy of ProtPlat.
Journal Article
Quercetin-loaded mesoporous nano-delivery system remodels osteoimmune microenvironment to regenerate alveolar bone in periodontitis via the miR-21a-5p/PDCD4/NF-κB pathway
Background
Impaired osteo-/angiogenesis, excessive inflammation, and imbalance of the osteoimmune homeostasis are involved in the pathogenesis of the alveolar bone defect caused by periodontitis. Unfortunately, there is still a lack of ideal therapeutic strategies for periodontitis that can regenerate the alveolar bone while remodeling the osteoimmune microenvironment. Quercetin, as a monomeric flavonoid, has multiple pharmacological activities, such as pro-regenerative, anti-inflammatory, and immunomodulatory effects. Despite its vast spectrum of pharmacological activities, quercetin’s clinical application is limited due to its poor water solubility and low bioavailability.
Results
In this study, we fabricated a quercetin-loaded mesoporous bioactive glass (Quercetin/MBG) nano-delivery system with the function of continuously releasing quercetin, which could better promote the bone regeneration and regulate the immune microenvironment in the alveolar bone defect with periodontitis compared to pure MBG treatment. In particular, this nano-delivery system effectively decreased injection frequency of quercetin while yielding favorable therapeutic results. In view of the above excellent therapeutic effects achieved by the sustained release of quercetin, we further investigated its therapeutic mechanisms. Our findings indicated that under the periodontitis microenvironment, the intervention of quercetin could restore the osteo-/angiogenic capacity of periodontal ligament stem cells (PDLSCs), induce immune regulation of macrophages and exert an osteoimmunomodulatory effect. Furthermore, we also found that the above osteoimmunomodulatory effects of quercetin via macrophages could be partially blocked by the overexpression of a key microRNA——miR-21a-5p, which worked through inhibiting the expression of PDCD4 and activating the NF-κB signaling pathway.
Conclusion
In summary, our study shows that quercetin-loaded mesoporous nano-delivery system has the potential to be a therapeutic approach for reconstructing alveolar bone defects in periodontitis. Furthermore, it also offers a new perspective for treating alveolar bone defects in periodontitis by inhibiting the expression of miR-21a-5p in macrophages and thereby creating a favorable osteoimmune microenvironment.
Graphical Abstract
Journal Article
A Hybrid Handover Scheme for Vehicular VLC/RF Communication Networks
Visible light communication (VLC) is a promising complementary technology to its radio frequency (RF) counterpart to satisfy the high quality-of-service (QoS) requirements of intelligent vehicular communications by reusing LED street lights. In this paper, a hybrid handover scheme for vehicular VLC/RF communication networks is proposed to balance QoS and handover costs by considering the vertical handover and horizontal handover together judging from the mobile state of the vehicle. A Markov decision process (MDP) is formulated to describe this hybrid handover problem, with a cost function balancing the handover consumption, delay, and reliability. A value iteration algorithm was applied to solve the optimal handover policy. The simulation results demonstrated the performance of the proposed hybrid handover scheme in comparison to other benchmark schemes.
Journal Article
Functionally Graded Scaffolds with Programmable Pore Size Distribution Based on Triply Periodic Minimal Surface Fabricated by Selective Laser Melting
Functional graded materials are gaining increasing attention in tissue engineering (TE) due to their superior mechanical properties and high biocompatibility. Triply periodic minimal surface (TPMS) has the capability to produce smooth surfaces and interconnectivity, which are very essential for bone scaffolds. To further enhance the versatility of TPMS, a parametric design method for functionally graded scaffold (FGS) with programmable pore size distribution is proposed in this study. Combining the relative density and unit cell size, the effect of design parameters on the pore size was also considered to effectively govern the distribution of pores in generating FGS. We made use of Gyroid to generate different types of FGS, which were then fabricated using selective laser melting (SLM), followed by investigation and comparison of their structural characteristics and mechanical properties. Their morphological features could be effectively controlled, indicating that TPMS was an effective way to achieve functional gradients which had bone-mimicking architectures. In terms of mechanical performance, the proposed FGS could achieve similar mechanical response under compression tests compared to the reference FGS with the same range of density gradient. The proposed method with control over pore size allows for effectively generating porous scaffolds with tailored properties which are potentially adopted in various fields.
Journal Article