Spreading Behavior of Non-Spherical Particles with Reconstructed Shapes Using Discrete Element Method in Additive Manufacturing.

The spreading behavior of particles has a significant impact on the processing quality of additive manufacturing. Compared with spherical metal material, polymer particles are usually non-spherical in shape. However, the effects of particle shape and underlying mechanisms remain unclear. Here, the spreading process of particles with reconstructed shapes (non-spherical particles decomposed into several spherical shapes by stereo-lithography models) are simulated by integrating spherical particles with the discrete element method. The results show that more cavities form in the spreading beds of particles with reconstructed shapes than those of spheres with blade spreading. Correspondingly, particles with reconstructed shapes have lower packing densities, leading to more uniform packing patterns. Slow propagation speeds of velocity and angular velocity lead to "right-upwards" turning boundaries for particles with reconstructed shapes and "right-downwards" turning boundaries for spherical particles. Moreover, as the blade velocity increases, the packing density decreases. Our calculation results verify each other and are in good agreement with the experiment, providing more details of the behavior of non-spherical particles before additive manufacturing. The comprehensive comparison between polymer non-spherical particles and spherical particles helps develop a reasonable map for the appropriate choice of operating parameters in real processes.

A non-equilibrium dissipation system with tunable molecular fuel flux.

Cells convert macromolecule fuel into small molecule fuel through energy pathways, including glycolysis, the citric acid cycle, and oxidative phosphorylation. These processes drive vital dissipative networks or structures. Distinct from direct fuel (DF) utilization (directly acquire and utilize small molecule fuel), this macromolecule fuel mechanism is referred to as indirect fuel (IF) utilization, wherein the generation rate of small molecule fuel (fuel flux) can be effectively regulated. Here, we reported a bionic dissipation system with tunable fuel flux based on dynamic DNA nanotechnology. By regulating the rates of strand displacement and enzymatic reactions, we controlled the fuel flux and further tuned the strength of non-equilibrium transient states. Interestingly, we found that within a certain range, the fuel flux was positively correlated with the strength of the transient state. Once saturation was reached, it became negatively correlated. An appropriate fuel flux supports the maintenance of high-intensity non-equilibrium transients. Furthermore, we harnessed the dissipation system with tunable molecular fuel flux to regulate the dynamic assembly and disassembly of AuNPs. Different fuel fluxes resulted in varying assembly and disassembly rates and strengths for AuNPs, accomplishing a biomimetic process of regulating microtubule assembly through the control of fuel flux within living organisms. This work demonstrated a dissipation system with tunable molecular fuel flux, and we envision that this system holds significant potential for development in various fields such as biomimetics, synthetic biology, smart materials, biosensing, and artificial cells.

Recent advances in aptamer-based biosensors for potassium detection.

Maintaining a stable level of potassium is crucial for proper bodily function because even a slight imbalance can result in serious disorders like hyperkalemia and hypokalemia. Therefore, detecting and monitoring potassium ion (K+) levels are of utmost importance. Various biosensors have been developed for rapid K+ detection, with aptamer-based biosensors garnering significant attention due to their high sensitivity and specificity. This review focuses on aptamer-based biosensors for K+ detection, providing an overview of their signal generation strategies, including electrochemical, field-effect transistor, nanopore, colorimetric, and fluorescent systems. The analytical performance of these biosensors is evaluated comprehensively. In addition, factors that affect their efficiency, such as their physicochemical properties, regeneration for reusability, and linkers/spacers, are listed. Lastly, this review examines the major challenges faced by aptamer-based biosensors in K+ detection and discusses potential future developments.

Application of preoperative three-dimensional reconstruction combined with fluorescence imaging in simultaneous bilateral single-port thoracoscopic anatomical pneumonectomy.

We report a clinical case of preoperative three-dimensional reconstruction combined with fluorescence imaging in simultaneous bilateral single-hole thoracoscopic treatment of pulmonary nodules. Fluorescent staining is widely used in clinics to show the interface between lung segments, and there are many reports in the literature. Indocyanine green (ICG), fluorescent staining method has the advantages of no need for repeated lung inflation and short time consumption. Moreover, the development of imaging three-dimensional reconstruction technology also provides convenience for accurate positioning of anatomical structures. Finally, we think that the application of preoperative three-dimensional reconstruction combined with fluorescence imaging for simultaneous double-lung single-hole thoracoscopic pneumonectomy can quickly and clearly display the interface between lung segments, provide technical support for the operation, shorten the operation time, reduce intraoperative bleeding, and have relatively high safety, and may shorten the learning curve for the growth of clinical thoracic surgeons, which may be worth popularizing and applying.

Diagnostic and prognostic significance of mRNA expressions of apolipoprotein A and C family genes in hepatitis B virus-related hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is among the most common and lethal malignancies worldwide. Apolipoproteins (APOs) have been reported increasingly for their relationships with tumors. We aim at exploring the potential relationships of apolipoprotein A (APOA) and apolipoprotein C (APOC) family members with HCC. METHODS: A data set, containing 212 hepatitis B virus-related HCC patients, was used for analysis. The diagnostic and prognostic ability of APOA and APOC family genes was figured out. Risk score models and nomograms were developed for the HCC prognosis prediction. Moreover, molecular mechanism exploration were identified biological processes and metabolic pathways of these genes involved in. Validation analysis was carried out using online website. RESULTS: APOA1, APOC1, APOC3, and APOC4 showed robust diagnosis significance (all P < 0.05). APOA4, APOC3, and APOC4 were associated with the overall survival (OS) while APOA4 and APOC4 were linked to recurrence-free survival (RFS, all P ≤ 0.05). Risk score models and nomograms had the advantage of predicting OS and RFS for HCC. Molecular mechanism exploration indicated that these genes were involved in the steroid metabolic process, the PPAR signaling pathway, and fatty acid metabolism. Besides that, validation analysis revealed that APOC1 and APOC4 had an association with OS; and APOC3 was associated with OS and RFS (all P ≤ 0.05). CONCLUSIONS: APOA1, APOC1, APOC3, and APOC4 are likely to be potential diagnostic biomarkers and APOC3 and APOC4 are likely to be potential prognostic biomarkers for hepatitis B virus-related HCC. They may be involved in the steroid metabolic process, PPAR signaling pathway, and fatty acid metabolism.

Distinct Prognostic Values of Phospholipase C Beta Family Members for Non-Small Cell Lung Carcinoma.

BACKGROUND: Non-small cell lung cancer (NSCLC) is a main cause of cancer-related mortality worldwide. The relationships of the phospholipase C beta (PLCB) enzymes, which are encoded by the genes PLCB1, PLCB2, PLCB3, and PLCB4, with NSCLC have not been investigated. Therefore, the aim of the present study was to identify any correlations between NSCLC prognosis and the expression patterns of PLCB family members. MATERIALS AND METHODS: The prognostic values of the PLCB gene family members in NSCLC patients were evaluated using the "Kaplan-Meier plotter" database, which includes updated gene expression data and survival information of a total of 1,926 NSCLC patients. The GeneMANIA plugin of Cytoscape software was used to evaluate the relationships of the four PLCB family members at the gene and protein levels. Gene ontology enrichment analysis and KEGG pathway analysis were performed using the Database for Annotation, Visualization, and Integrated Discovery. RESULTS: High mRNA expression levels of PLCB1, PLCB2, and PLCB3 were significantly associated with poor overall survival (OS) of all NSCLC patients and significantly associated with poor prognosis of adenocarcinoma. In contrast, high mRNA expression of PLCB4 was associated with better OS of adenocarcinoma patients. In addition, the expression levels of the PLCB family members were correlated to smoking status, clinical stage, and patient sex but not radiotherapy and chemotherapy outcomes. CONCLUSIONS: PLCB1, PLCB2, PLCB3, and PLCB4 appear to be potential biomarkers for the prognosis of patients with NSCLC. The prognostic values of the PLCB genes require further investigations.

Distinct Diagnostic and Prognostic Values of Kinesin Family Member Genes Expression in Patients with Breast Cancer.

BACKGROUND This study investigated the diagnostic and prognostic values of kinesin superfamily proteins (KIFs) in breast cancer (BC) patients. MATERIAL AND METHODS All data were obtained from the Cancer Genome Atlas. DESeq was run to test for differentially expressed KIF genes. Patients were divided into high- and low-expression groups according to the median expression values of each KIF genes. Survival data were calculated using the Cox proportional hazard model. Comprehensive survival analysis was performed to evaluate the prognostic value of the prognostic signature. Gene set enrichment analysis (GSEA) was conducted to identify associated gene ontology and KEGG pathways. RESULTS Bioinformatics analysis showed that all KIF genes were significantly enriched during DNA replication and the cell cycle, and co-expressed with each other. Thirteen KIF genes were differentially expressed in cancer and adjacent tissues, and high levels of KIF15, KIF20A, KIF23, KIF2C and KIF4A genes were significantly correlated with poor overall survival (OS). GSEA showed that BC patients with high expression of KIF15, KIF20A, KIF23, KIF2C and KIF4A were enriched in the cell cycle process, P53 regulation pathway and mismatch repair. Combinations of low expression of KIF15, KIF20A, KIF23, KIF2C and KIF4A were more highly correlated with favorable OS. Nomograms showed that the KIF4A risk score provided the maximum number of risk points (range 0-100), whereas other genes made a lower contribution. CONCLUSIONS We conclude that 13 KIF genes are differentially expressed in BC tumor tissues, and KIF15, KIF20A, KIF23, KIF2C and KIF4A are associated with prognostic factors in BC.