Structure of the siphophage neck-Tail complex suggests that conserved tail tip proteins facilitate receptor binding and tail assembly.

Siphophages have a long, flexible, and noncontractile tail that connects to the capsid through a neck. The phage tail is essential for host cell recognition and virus-host cell interactions; moreover, it serves as a channel for genome delivery during infection. However, the in situ high-resolution structure of the neck-tail complex of siphophages remains unknown. Here, we present the structure of the siphophage lambda "wild type," the most widely used, laboratory-adapted fiberless mutant. The neck-tail complex comprises a channel formed by stacked 12-fold and hexameric rings and a 3-fold symmetrical tip. The interactions among DNA and a total of 246 tail protein molecules forming the tail and neck have been characterized. Structural comparisons of the tail tips, the most diversified region across the lambda and other long-tailed phages or tail-like machines, suggest that their tail tip contains conserved domains, which facilitate tail assembly, receptor binding, cell adsorption, and DNA retaining/releasing. These domains are distributed in different tail tip proteins in different phages or tail-like machines. The side tail fibers are not required for the phage particle to orient itself vertically to the surface of the host cell during attachment.

Consensus statement on extracellular vesicles in liquid biopsy for advancing laboratory medicine.

Extracellular vesicles (EVs) represent a diverse class of nanoscale membrane vesicles actively released by cells. These EVs can be further subdivided into categories like exosomes and microvesicles, based on their origins, sizes, and physical attributes. Significantly, disease-derived EVs have been detected in virtually all types of body fluids, providing a comprehensive molecular profile of their cellular origins. As a result, EVs are emerging as a valuable addition to liquid biopsy techniques. In this collective statement, the authors share their current perspectives on EV-related research and product development, with a shared commitment to translating this newfound knowledge into clinical applications for cancer and other diseases, particularly as disease biomarkers. The consensus within this document revolves around the overarching recognition of the merits, unresolved questions, and existing challenges surrounding EVs. This consensus manuscript is a collaborative effort led by the Committee of Exosomes, Society of Tumor Markers, Chinese anti-Cancer Association, aimed at expediting the cultivation of robust scientific and clinically applicable breakthroughs and propelling the field forward with greater swiftness and efficacy.

Structural changes in bacteriophage T7 upon receptor-induced genome ejection.

Many tailed bacteriophages assemble ejection proteins and a portal-tail complex at a unique vertex of the capsid. The ejection proteins form a transenvelope channel extending the portal-tail channel for the delivery of genomic DNA in cell infection. Here, we report the structure of the mature bacteriophage T7, including the ejection proteins, as well as the structures of the full and empty T7 particles in complex with their cell receptor lipopolysaccharide. Our near-atomic-resolution reconstruction shows that the ejection proteins in the mature T7 assemble into a core, which comprises a fourfold gene product 16 (gp16) ring, an eightfold gp15 ring, and a putative eightfold gp14 ring. The gp15 and gp16 are mainly composed of helix bundles, and gp16 harbors a lytic transglycosylase domain for degrading the bacterial peptidoglycan layer. When interacting with the lipopolysaccharide, the T7 tail nozzle opens. Six copies of gp14 anchor to the tail nozzle, extending the nozzle across the lipopolysaccharide lipid bilayer. The structures of gp15 and gp16 in the mature T7 suggest that they should undergo remarkable conformational changes to form the transenvelope channel. Hydrophobic α-helices were observed in gp16 but not in gp15, suggesting that gp15 forms the channel in the hydrophilic periplasm and gp16 forms the channel in the cytoplasmic membrane.

Association of Tumor Cell Metabolic Subtype and Immune Response With the Clinical Course of Hepatocellular Carcinoma.

AIM: Tumor metabolism plays an important role in tumorigenesis and tumor progression. This study evaluated the potential association of tumor cell metabolism and immune cell tumor infiltration with the clinical course of hepatocellular carcinoma (HCC). METHODS: Gene-wise normalization and principal component analysis were performed to evaluate the metabolic system. A tumor microenvironment score system of tumor immune cell infiltration was constructed to evaluate its association with metabolic subtypes. Finally, we analyzed the impact of metabolism and immune cell infiltration on the clinical course of HCC. RESULTS: A total of 673 HCC patients were categorized into cholesterogenic (25.3%), glycolytic (14.6%), mixed (10.4%), and quiescent (49.8%) types based on glycolysis and cholesterol biosynthesis gene expression. The subgroups including the glycolytic genotyping expression (glycolytic and mixed types) showed a higher mortality rate. The glycolytic, cholesterogenic, and mixed types were positively correlated with M0 macrophage, resting mast cell, and naïve B-cell infiltration (P = .013, P = .019, and P = .006, respectively). In TCGA database, high CD8+ T cell and low M0 macrophage infiltration were associated with prolonged overall survival (OS, P = .0017 and P < .0001, respectively). Furthermore, in glycolytic and mixed types, patients with high M0 macrophage infiltration had a shorter OS (P = .03 and P = .013, respectively), and in quiescent type, patients with low naïve B-cell infiltration had a longer OS (P = .007). CONCLUSIONS: Tumor metabolism plays a prognostic role and correlates with immune cell infiltration in HCC. M0 macrophage and CD8+ T cell appear to be promising prognostic biomarker for HCC. Finally, M0 macrophages may represent a useful immunotherapeutic target in patients with HCC.

A pan-cancer analysis revealing the role of LFNG, MFNG and RFNG in tumor prognosis and microenvironment.

BACKGROUND: Fringe is a glycosyltransferase involved in tumor occurrence and metastasis. However, a comprehensive analysis of the Fringe family members lunatic fringe (LFNG), manic fringe (MFNG), radical fringe (RFNG) in human cancers is lacking. METHODS: In this study, we performed a pan-cancer analysis of Fringe family members in 33 cancer types with transcriptomic, genomic, methylation data from The Cancer Genome Atlas (TCGA) project. The correlation between Fringe family member expression and patient overall survival, copy number variation, methylation, Gene Ontology enrichment, and tumor-infiltrating lymphocytes (TILs) was investigated by using multiple databases, such as cBioPortal, Human Protein Atlas, GeneCards, STRING, MSigDB, TISIDB, and TIMER2. In vitro experiments and immunohistochemical assays were performed to validate our findings. RESULTS: High expression levels of LFNG, MFNG, RFNG were closely associated with poor overall survival in multiple cancers, particularly in pancreatic adenocarcinoma (PAAD), uveal melanoma (UVM), and brain lower-grade glioma (LGG). Copy number variation analysis revealed that diploid and gain mutations of LFNG was significantly increased in PAAD and stomach adenocarcinoma (STAD), and significantly associated with the methylation levels in promoter regions. Significant differential genes between high and low expression groups of these Fringe family members were found to be consistently enriched in immune response and T cell activation pathway, extracellular matrix adhesion pathway, RNA splicing and ion transport pathways. Correlation between the abundance of tumor-infiltrating lymphocytes (TILs) and LFNG, MFNG, and RFNG expression showed that high LFNG expression was associated with lower TIL levels, particularly in PAAD. In vitro experiment by using pancreatic cancer PANC1 cells showed that LFNG overexpression promoted cell proliferation and invasion. Immunohistochemical assay in 90 PAAD patients verified the expression level of LFNG and its relationship with the prognosis. CONCLUSIONS: Our study provides a relatively comprehensive understanding of the expression, mutation, copy number, promoter methylation level changes along with prognosis values of LFNG, MFNG, and RFNG in different tumors. High LFNG expression may serve as a poor prognosis molecular marker for PAAD.

Local environmental engineering for highly stable single-atom Pt1/CeO2catalysts: first-principles insights.

Single-atom Pt1/CeO2catalysts may cope with the high cost and durability issues of fuel cell electrocatalysts. In the present study, the stability and underlying interaction mechanisms of the Pt1/CeO2system are systematically investigated using first-principles calculations. The Pt adsorption energy on CeO2surfaces can be divided into chemical interaction and surface deformation parts. The interaction energy, mainly associated with the local chemical environment, i.e. the number of Pt-O bonds, plays a major role in Pt1/CeO2stability. When forming a Pt-4O configuration, the catalytic system has the highest stability and Pt is oxidized to Pt2+. An electronic metal-support interaction mechanism is proposed for understanding Pt1/CeO2stability. In addition, our calculations show that the Pt1/CeO2(100) system is dynamically stable, and the external O environment can promote the further oxidation of Pt to Ptn+(2 ≤n< 4). The present study provides useful guidance for the experimental development of highly stable and efficient electrocatalysts for fuel cell applications.

Robust photogalvanic effect, full spin polarization and pure spin current in the BiC photodetector by vacancy- and substitution-doping.

The photogalvanic effects (PGEs) in low-dimensional devices have attracted great interests recently. Herein, based on non-equilibrium Green's function combined with density functional theory, we investigated spin-dependent PGE phenomena in the BiC photodetector for the case of linearly polarized light and zero bias. Due to the presence of strong spin-orbital interaction (SOI) and C3v symmetry for the BiC monolayer, the armchair and zigzag BiC photodetectors produce robust spin-dependent PGEs which possess the cos(2θ) and sin(2θ) relations on the photon energies. Especially, the armchair and Bi-vacancy armchair BiC photodetector can produce fully spin polarization, and pure spin current was found in the armchair and zigzag BiC photodetector. Furthermore, after introducing the Bi-vacancy, C-vacancy, Bi-doping and C-doping respectively, corresponding armchair and zigzag BiC photodetector can produce higher spin-dependent PGEs for their Cs symmetry. Moreover, the behaviors of spin-dependent photoresponse are highly anisotropic and can be tuned by the photon energy. This work suggested great potential applications of the BiC monolayer on PGE-driven photodetectors in low energy-consumption optoelectronics and spintronic devices. .

Enhancing Electrocatalytic Methanol Oxidation on PtCuNi Core-Shell Alloy Structures in Acid Electrolytes.

A key challenge for direct methanol fuel cells is the sluggish reaction kinetics, poor anti-CO poisoning ability, and insufficient Pt utilization of platinum-based catalysts during methanol oxidation reaction (MOR). Herein, we report a facile approach for PtCuNi electrocatalysts with adjustable inner and surface configurations. By judiciously controlling the nucleation/growth kinetics, PtCuNi core-shell alloy nanoparticles (PtCuNi-CS NPs) fortified with a Cu-rich core and a Pt-rich shell are obtained. Especially, PtCuNi-CS NPs show the highest mass activity and specific activity toward MOR, 5.7 and 5.1 times higher than those of commercial Pt/C. Density functional theory calculations reveal that the PtCuNi-CS NPs with a suitable d-band center possess excellent electro-oxidation activity. Additionally, the doping of Cu and Ni atoms endows the PtCuNi-CS NPs with enhanced OH* adsorption. This work provides an effective design strategy to develop Pt-based trimetallic electrocatalysts as efficient anode materials for fuel cell applications.

Multi-Image Encryption Method via Computational Integral Imaging Algorithm.

Under the framework of computational integral imaging, a multi-image encryption scheme based on the DNA-chaos algorithm is proposed. In this scheme, multiple images are merged to one image by a computational integral imaging algorithm, which significantly improves the efficiency of image encryption. Meanwhile, the computational integral imaging algorithm can merge images at different depth distances, thereby the different depth distances of multiple images can also be used as keys to increase the security of the encryption method. In addition, the high randomness of the chaos algorithm is combined to address the outline effect caused by the DNA encryption algorithm. We have experimentally verified the proposed multi-image encryption scheme. The entropy value of the encrypted image is 7.6227, whereas the entropy value of the merge image with two input images is 3.2886, which greatly reduces the relevance of the image. The simulation results also confirm that the proposed encryption scheme has high key security and can protect against various attacks.

Civil airline fare prediction with a multi-attribute dual-stage attention mechanism.

Airfare price prediction is one of the core facilities of the decision support system in civil aviation, which includes departure time, days of purchase in advance and flight airline. The traditional airfare price prediction system is limited by the nonlinear interrelationship of multiple factors and fails to deal with the impact of different time steps, resulting in low prediction accuracy. To address these challenges, this paper proposes a novel civil airline fare prediction system with a Multi-Attribute Dual-stage Attention (MADA) mechanism integrating different types of data extracted from the same dimension. In this method, the Seq2Seq model is used to add attention mechanisms to both the encoder and the decoder. The encoder attention mechanism extracts multi-attribute data from time series, which are optimized and filtered by the temporal attention mechanism in the decoder to capture the complex time dependence of the ticket price sequence. Extensive experiments with actual civil aviation data sets were performed, and the results suggested that MADA outperforms airfare prediction models based on the Auto-Regressive Integrated Moving Average (ARIMA), random forest, or deep learning models in MSE, RMSE, and MAE indicators. And from the results of a large amount of experimental data, it is proven that the prediction results of the MADA model proposed in this paper on different routes are at least 2.3% better than the other compared models.