Circulating Tumor Cell Phenotype Detection and Epithelial-Mesenchymal Transition Tracking Based on Dual Biomarker Co-Recognition in an Integrated PDMS Chip.

Circulating tumor cells (CTCs) are widely considered as a reliable and promising class of markers in the field of liquid biopsy. As CTCs undergo epithelial-mesenchymal transition (EMT), phenotype detection of heterogeneous CTCs based on EMT markers is of great significance. In this report, an integrated analytical strategy that can simultaneously capture and differentially detect epithelial- and mesenchymal-expressed CTCs in bloods of non-small cell lung cancer (NSCLS) patients is proposed. First, a commercial biomimetic polycarbonate (PCTE) microfiltration membrane is employed as the capture interface for heterogenous CTCs. Meanwhile, differential detection of the captured CTCs is realized by preparing two distinct CdTe quantum dots (QDs) with red and green emissions, attached with EpCAM and Vimentin aptamers, respectively. For combined analysis, a polydimethylsiloxane (PDMS) chip with simple structure is designed, which integrates the membrane capture and QDs-based phenotype detection of CTCs. This chip not only implements the analysis of the number of CTCs down to 2 cells mL-1, but enables EMT process tracking according to the specific signals of the two QDs. Finally, this method is successfully applied to inspect the correlations of numbers or proportions of heterogenous CTCs in 94 NSCLS patients with disease stage and whether there is distant metastasis.

Combinational delivery of TLR4 and TLR7/8 agonist enhanced the therapeutic efficacy of immune checkpoint inhibitors to colon tumor.

Immunotherapy is regarded as a potent cancer treatment, with DC vaccines playing a crucial role. Although clinical trials have demonstrated the safety and efficacy of DC vaccines, loading antigens in vitro is challenging, and their therapeutic effects remain unpredictable. Moreover, the diverse subtypes and maturity states of DCs in the body could induce both immune responses and immune tolerance, potentially affecting the vaccine's efficacy. Hence, the optimization of DC vaccines remains imperative. Our study discovered a new therapeutic strategy by using CT26 and MC38 mouse colon cancer models, as well as LLC mouse lung cancer models. The strategy involved the synergistic activation of DCs through intertumoral administration of TLR4 agonist high-mobility group nucleosome binding protein 1 (HMGN1) and TLR7/8 agonist (R848/resiquimod), combined with intraperitoneal administration of TNFR2 immunosuppressant antibody. The experimental results indicated that the combined use of HMGN1, R848, and α-TNFR2 had no effect on LLC cold tumors. However, it was effective in eradicating CT26 and MC38 colon cancer and inducing long-term immune memory. The combination of these three drugs altered the TME and promoted an increase in anti-tumor immune components. This may provide a promising new treatment strategy for colon cancer.

Efficient production of 1,2,4-butanetriol from corn cob hydrolysate by metabolically engineered Escherichia coli.

Corn cob is a major waste mass-produced in corn agriculture. Corn cob hydrolysate containing xylose, arabinose, and glucose is the hydrolysis product of corn cob. Herein, a recombinant Escherichia coli strain BT-10 was constructed to transform corn cob hydrolysate into 1,2,4-butanetriol, a platform substance with diversified applications. To eliminate catabolite repression and enhance NADPH supply for alcohol dehydrogenase YqhD catalyzed 1,2,4-butanetriol generation, ptsG encoding glucose transporter EIICBGlc and pgi encoding phosphoglucose isomerase were deleted. With four heterologous enzymes including xylose dehydrogenase, xylonolactonase, xylonate dehydratase, α-ketoacid decarboxylase and endogenous YqhD, E. coli BT-10 can produce 36.63 g/L 1,2,4-butanetriol with a productivity of 1.14 g/[L·h] using xylose as substrate. When corn cob hydrolysate was used as the substrate, 43.4 g/L 1,2,4-butanetriol was generated with a productivity of 1.09 g/[L·h] and a yield of 0.9 mol/mol. With its desirable characteristics, E. coli BT-10 is a promising strain for commercial 1,2,4-butanetriol production.

Lactate dehydrogenase A promotes nasopharyngeal carcinoma progression through the TAK1/NF-κB Axis.

BACKGROUND: Nasopharyngeal carcinoma (NPC) is a malignant tumor that originates in the nasopharyngeal mucosa and is common in China and Southeast Asian countries. Cancer cells reprogram glycolytic metabolism to promote their growth, survival and metastasis. Glycolysis plays an important role in NPC development, but the underlying mechanisms remain incompletely elucidated. Lactate dehydrogenase A (LDHA) is a crucial glycolytic enzyme, catalyzing the last step of glycolysis. This study aims to investigate the exact role of LDHA, which catalyzes the conversion of pyruvate into lactate, in NPC development. METHODS AND RESULTS: The western blot and immunohistochemical (IHC) results indicated that LDHA was significantly upregulated in NPC cells and clinical samples. LDHA knockdown by shRNA significantly inhibited NPC cell proliferation and invasion. Further knockdown of LDHA dramatically weakened the tumorigenicity of NPC cells in vivo. Mechanistic studies showed that LDHA activated TGF-ß-activated kinase 1 (TAK1) and subsequent nuclear factor κB (NF-κB) signaling to promote NPC cell proliferation and invasion. Exogenous lactate supplementation restored NPC cell proliferation and invasion inhibited by LDHA knockdown, and this restorative effect was reversed by NF-κB inhibitor (BAY 11-7082) or TAK1 inhibitor (5Z-7-oxozeaenol) treatment. Moreover, clinical sample analyses showed that LDHA expression was positively correlated with TAK1 Thr187 phosphorylation and poor prognosis. CONCLUSIONS: Our results suggest that LDHA and its major metabolite lactate drive NPC progression by regulating TAK1 and its downstream NF-κB signaling, which could become a therapeutic target in NPC.

A TCN-Linear Hybrid Model for Chaotic Time Series Forecasting.

The applications of deep learning and artificial intelligence have permeated daily life, with time series prediction emerging as a focal area of research due to its significance in data analysis. The evolution of deep learning methods for time series prediction has progressed from the Convolutional Neural Network (CNN) and the Recurrent Neural Network (RNN) to the recently popularized Transformer network. However, each of these methods has encountered specific issues. Recent studies have questioned the effectiveness of the self-attention mechanism in Transformers for time series prediction, prompting a reevaluation of approaches to LTSF (Long Time Series Forecasting) problems. To circumvent the limitations present in current models, this paper introduces a novel hybrid network, Temporal Convolutional Network-Linear (TCN-Linear), which leverages the temporal prediction capabilities of the Temporal Convolutional Network (TCN) to enhance the capacity of LSTF-Linear. Time series from three classical chaotic systems (Lorenz, Mackey-Glass, and Rossler) and real-world stock data serve as experimental datasets. Numerical simulation results indicate that, compared to classical networks and novel hybrid models, our model achieves the lowest RMSE, MAE, and MSE with the fewest training parameters, and its R2 value is the closest to 1.

Anti-TNFR2 enhanced the antitumor activity of a new HMGN1/3M-052 stimulated dendritic cell vaccine in a mouse model of colon cancer.

Immunotherapy is the new approach for cancer treatment that can be achieved through several strategies, one of which is dendritic cells (DCs) vaccine therapy. However, traditional DC vaccination lacks accurate targeting, so DC vaccine preparation needs to be optimized. Immunosuppressive CD4+Foxp3+ regulatory T cells (Tregs) in the tumor microenvironment can promote tumor immune escape. Therefore, targeting Tregs has become a strategy for tumor immunotherapy. In this study, we found that HMGN1 (N1, a dendritic cell-activating TLR4 agonist) and 3M-052 (a newly synthesized TLR7/8 agonist) synergistically stimulate DCs maturation and increase the production of proinflammatory cytokines TNFα and IL-12. In a colon cancer mice model, vaccination with N1 and 3M-052 stimulated and tumor antigen-loaded DCs combined with anti-TNFR2 inhibited tumor growth in mice, and the antitumor effect was mainly achieved through stimulation of cytotoxic CD8 T cell activation and depletion of Tregs. Overall, the combinating of DC activation by N1 and 3M-052 with inhibition of Tregs by antagonizing TNFR2 as a therapeutic strategy may represent a more effective strategy for cancer treatment.

Mesophilic Argonaute-Based Single Polystyrene Sphere Aptamer Fluorescence Platform for the Multiplexed and Ultrasensitive Detection of Non-Nucleic Acid Targets.

The rapid, simultaneous, and accurate identification of multiple non-nucleic acid targets in clinical or food samples at room temperature is essential for public health. Argonautes (Agos) are guided, programmable, target-activated, next-generation nucleic acid endonucleases that could realize one-pot and multiplexed detection using a single enzyme, which cannot be achieved with CRISPR/Cas. However, currently reported thermophilic Ago-based multi-detection sensors are mainly employed in the detection of nucleic acids. Herein, this work proposes a Mesophilic Argonaute Report-based single millimeter Polystyrene Sphere (MARPS) multiplex detection platform for the simultaneous analysis of non-nucleic acid targets. The aptamer is utilized as the recognition element, and a single millimeter-sized polystyrene sphere (PSmm ) with a large concentration of guide DNA on the surface served as the microreactor. These are combined with precise Clostridium butyricum Ago (CbAgo) cleavage and exonuclease I (Exo I) signal amplification to achieve the efficient and sensitive recognition of non-nucleic acid targets, such as mycotoxins (<60 pg mL-1 ) and pathogenic bacteria (<102 cfu mL-1 ). The novel MARPS platform is the first to use mesophilic Agos for the multiplex detection of non-nucleic acid targets, overcoming the limitations of CRISPR/Cas in this regard and representing a major advancement in non-nucleic acid target detection using a gene-editing-based system.

Molecular characterization of a novel victorivirus isolated from the phytopathogenic fungus Phaeobotryon rhois.

Phaeobotryon rhois is an important pathogenic fungus that causes dieback and canker disease of woody hosts. A novel mycovirus, tentatively named "Phaeobotryon rhois victorivirus 1" (PrVV1), was identified in P. rhois strain SX8-4. The PrVV1 has a double-stranded RNA (dsRNA) genome that is 5,224 base pairs long and contains two open reading frames (ORF1 and ORF2), which overlap at a AUGA sequence. ORF1 encodes a polypeptide of 786 amino acids (aa) that contains the conserved coat protein (CP) domain of victoriviruses, while ORF2, encodes a large polypeptide of 826 aa that contains the conserved RNA-dependent RNA polymerase (RdRp) domain of victoriviruses. Our analysis of genomic structure, homology, and phylogeny indicated that PrVV1 is a novel member of the genus Victorivirus in the family Totiviridae. This is the first report of the complete genome sequence of a victorivirus that infects P. rhois.

Conflicts of Interest in the Assessment of Chemicals, Waste, and Pollution.

Pollution by chemicals and waste impacts human and ecosystem health on regional, national, and global scales, resulting, together with climate change and biodiversity loss, in a triple planetary crisis. Consequently, in 2022, countries agreed to establish an intergovernmental science-policy panel (SPP) on chemicals, waste, and pollution prevention, complementary to the existing intergovernmental science-policy bodies on climate change and biodiversity. To ensure the SPP's success, it is imperative to protect it from conflicts of interest (COI). Here, we (i) define and review the implications of COI, and its relevance for the management of chemicals, waste, and pollution; (ii) summarize established tactics to manufacture doubt in favor of vested interests, i.e., to counter scientific evidence and/or to promote misleading narratives favorable to financial interests; and (iii) illustrate these with selected examples. This analysis leads to a review of arguments for and against chemical industry representation in the SPP's work. We further (iv) rebut an assertion voiced by some that the chemical industry should be directly involved in the panel's work because it possesses data on chemicals essential for the panel's activities. Finally, (v) we present steps that should be taken to prevent the detrimental impacts of COI in the work of the SPP. In particular, we propose to include an independent auditor's role in the SPP to ensure that participation and processes follow clear COI rules. Among others, the auditor should evaluate the content of the assessments produced to ensure unbiased representation of information that underpins the SPP's activities.

Two-dimensional memristive hyperchaotic maps with different coupling frames and its hardware implementation.

Continuous-time memristors have been used in numerous chaotic circuit systems. Similarly, the discrete memristor model applied to a discrete map is also worthy of further study. To this end, this paper first proposes a discrete memristor model and analyzes the voltage-current characteristics of the memristor. Also, the discrete memristor is coupled with a one-dimensional (1D) sine chaotic map through different coupling frameworks, and two different two-dimensional (2D) chaotic map models are generated. Due to the presence of linear fixed points, the stability of the 2D memristor-coupled chaotic map depends on the choice of control parameters and initial states. The dynamic behavior of the chaotic map under different coupled map frameworks is investigated by using various analytical methods, and the results show that different coupling frameworks can produce different complex dynamical behaviors for memristor chaotic maps. The dynamic behavior based on parameter control is also investigated. The numerical experimental results show that the change of parameters can not only enrich the dynamic behavior of a chaotic map, but also increase the complexity of the memristor-coupled sine map. In addition, a simple encryption algorithm is designed based on the memristor chaotic map under the new coupling framework, and the performance analysis shows that the algorithm has a strong ability of image encryption. Finally, the numerical results are verified by hardware experiments.

The Bmtret1 Gene Family and Its Potential Role in Response to BmNPV Stress in Bombyx mori.

Trehalose is a non-reducing disaccharide and participates in physiological activities such as organ formation, energy metabolism, and stress resistance in insects. The Bmtret1 gene family is mainly involved in in the sugar metabolism of silkworm. In the present study, phylogenetic analysis divided 21 Bmtret1 orthologs into three clades. These genes are equally distributed on the nine chromosomes. The cis-elements in the promoter regions of Bmtret1s indicated the possible function of Bmtret1s in response to hormones and environmental stimulus. The qPCR analysis showed the significantly different expression levels of Bmtret1s in different tissues and organs, indicating possible functional divergence. In addition, most Bmtret1s showed disturbed expression levels in response to silkworm nuclear polyhedrosis virus (BmNPV) stresses. Our results provide a clue for further functional dissection of the Tret1s in Bombyx mori and implicate them as potential regulators of antiviral responses.

The FomYjeF Protein Influences the Sporulation and Virulence of Fusarium oxysporum f. sp. momordicae.

Fusarium oxysporum causes vascular wilt in more than 100 plant species, resulting in massive economic losses. A deep understanding of the mechanisms of pathogenicity and symptom induction by this fungus is necessary to control crop wilt. The YjeF protein has been proven to function in cellular metabolism damage-repair in Escherichia coli and to play an important role in Edc3 (enhancer of the mRNA decapping 3) function in Candida albicans, but no studies have been reported on related functions in plant pathogenic fungi. In this work, we report how the FomYjeF gene in F. oxysporum f. sp. momordicae contributes to conidia production and virulence. The deletion of the FomYjeF gene displayed a highly improved capacity for macroconidia production, and it was shown to be involved in carbendazim's associated stress pathway. Meanwhile, this gene caused a significant increase in virulence in bitter gourd plants with a higher disease severity index and enhanced the accumulation of glutathione peroxidase and the ability to degrade hydrogen peroxide in F. oxysporum. These findings reveal that FomYjeF affects virulence by influencing the amount of spore formation and the ROS (reactive oxygen species) pathway of F. oxysporum f. sp. momordicae. Taken together, our study shows that the FomYjeF gene affects sporulation, mycelial growth, pathogenicity, and ROS accumulation in F. oxysporum. The results of this study provide a novel insight into the function of FomYjeF participation in the pathogenicity of F. oxysporum f. sp. momordicae.

Discovery and Characterization of Rubrinodin Provide Clues into the Evolution of Lasso Peptides.

Lasso peptides are unique natural products that comprise a class of ribosomally synthesized and post-translationally modified peptides. Their defining three-dimensional structure is a lariat knot, in which the C-terminal tail is threaded through a macrolactam ring formed between the N-terminal amino group and an Asp or Glu side chain (i.e., an isopeptide bond). Recent genome mining strategies have revealed various types of lasso peptide biosynthetic gene clusters and have thus redefined the known chemical space of lasso peptides. To date, over 20 different types of these gene clusters have been discovered, including several different clades from Proteobacteria. Despite the diverse architectures of these gene clusters, which may or may not encode various tailoring enzymes, most currently known lasso peptides are synthesized by two discrete clades defined by the presence of an ATP-binding cassette transporter or its absence and (sometimes) concurrent appearance of an isopeptidase, raising questions about their evolutionary history. Herein, we discovered and characterized the lasso peptide rubrinodin, which is assembled by a gene cluster encoding both an ATP-binding cassette transporter and an isopeptidase. Our bioinformatics analyses of this and other representative cluster types provided new clues into the evolutionary history of lasso peptides. Furthermore, our structural and biochemical investigations of rubrinodin permitted the conversion of this thermolabile lasso peptide into a more thermostable scaffold.

Fracture behaviour of silver nanowire films during shear deformation.

Silver nanowire films have a wide application prospect in flexible electronics, while it is a noticeable problem that the silver nanowires break due to the shear force under the mass production film cutting or extreme service conditions. In this paper, the shear fracture behaviour of silver nanowire films with different structural parameters was studied under the extreme shear failure tests. The load-displacement curve was obtained from the nano-indentation test, while the hardnessH, the elastic modulusEand the plastic properties represented by the ratio ofH3/E2of silver nanowire films with different diameters and thicknesses were calculated. On the other hand, based on the load-displacement curve, the stress-strain curve can be obtained through the finite element method simulation. The plastic properties can also be judged by the lower limit of yield strength from simulated stress-strain curve. Combined with characteristic crack propagation range, the relationship between plasticity and shear fracture was found, which was further disclosed by in-depth microstructure analysis. The results show that the better the plasticity of silver nanowire films, the stronger the resistance to shear fracture.

Identifying the spatial heterogeneity in the effects of the construction land scale on carbon emissions: Case study of the Yangtze River Economic Belt, China.

Low-carbon emissions are a major research focus to solve the problem of global warming and an important area that China needs to focus on to achieve high-quality development. Construction land scale is a non-negligible factor affecting carbon emissions. However, carbon emission impacts of county-scale spatial heterogeneity in construction land scale are under addressed in contemporary research. To address this gap, this paper took 1042 counties in China's Yangtze River Economic Belt (YREB) and developed datasets of the influencing factors including the construction land scale, GDP, secondary industry output proportion in GDP, residential population, and fixed asset investment. After comparing the ordinary least squares and geographically weighted regression (GWR) models, we applied GWR for more in-depth analyses. The global regression model results showed that the effect of the scale of construction land on carbon emissions was exceedingly significant and that the directions of the impacts coincided with the predictions. Further, local regression model results showed that construction land scale had significant spatial heterogeneity in the impact on carbon emissions and most counties (69.58%) showed significant positive correlations. The counties with significant construction land scale impacts on carbon emissions were concentrated and contiguous in spatial distribution and spatially clustered areas varied, with the clearest impact in the downstream region. The findings help to further identify the spatial heterogeneity of construction land scale impacts on carbon emissions, which provides evidence-based and theoretical support for policymakers to develop spatially differentiated emission reduction measures.

Analysis of Blueberry Plant Rhizosphere Bacterial Diversity and Selection of Plant Growth Promoting Rhizobacteria.

Microbial metabolites in rhizosphere soil are important to plant growth. In this study, microbial diversity in blueberry plant rhizosphere soil was characterized using high-throughput amplicon sequencing technology. There were 11 bacterial phyla and three fungal phyla dominating in the soil. In addition, inorganic-phosphate-solubilizing bacteria (iPSB) in the rhizosphere soil were isolated and evaluated by molybdenum-antimony anti-coloration method. Their silicate solubilizing, auxin production, and nitrogen fixation capabilities were also determined. Eighteen iPSB in the rhizosphere soil strains were isolated and identified as Buttiauxella, Paraburkholderia and Pseudomonas. The higher phosphorus-solubilizing capacity and auxin production in blueberry rhizosphere belonged to genus Buttiauxella sp. The strains belong to genus Paraburkholderia had the same function of dissolving both phosphorus and producing auxin, as well as silicate and nitrogen fixation. The blueberry seeds incubated with the strains had higher germination rates. The results of this study could be helpful in developing the plant growth-promoting rhizobacteria (PGPR) method for enhancing soil nutrients to blueberry plant.

A New Fault Diagnosis of Rolling Bearing Based on Markov Transition Field and CNN.

The rolling bearing is a crucial component of the rotating machine, and it is particularly vital to ensure its normal operation. In addition, the selection of different category features will add uncertainty and bias to the classification results. In order to decrease the interference of these factors to fault diagnosis, a new method that automatically learns the features of the data combined with Markov transition field (MTF) and convolutional neural network (CNN) is proposed in this paper, namely MTF-CNN. The MTF contributes to convert the original time series into corresponding figures, and the CNN is used to extract the deep feature information in the figure to complete the fault diagnosis. The effectiveness of the proposed method is verified by two public data sets. The experimental results show that MTF-CNN can classify different types of faults, and the highest accuracy rate can reach 100%. Likewise, the classification accuracy of this method is higher than some existing methods.

Rapid Naked-Eye Tracking of On-Cell Phenotype Based on Dual-Aptamer-Weaved Cascade Assembly of Nanostructures.

Phenotypic plasticity is an emerging paradigm for providing biological and clinical insights into cancer initiation, progression, and resistance to therapy. However, it is a great challenge to track phenotypic information on live cells with high levels of sensitivity, specificity, and simplicity, when a specific cancer-cell subset is being targeted. In this work, we have successfully achieved cascade assembly of nanoparticles on the surface of specific cancer cells by designing a dual-aptamer-weaved molecular AND logic system. Taking advantage of spatial addressability, precise controllability, and targeting recognition of the nanostructure assemblies, we can precisely label the target-cell subset in a large population of similar cells and rapidly obtain phenotypic information in response to the surface changes of captured cancer cells. Without sophisticated instruments, we can know the phenotypic information on HepG2 cells in whole blood with a high level of sensitivity and rapid naked-eye tracking of on-cell phenotype changes of HepG2 cells undergoing epithelial-mesenchymal transition.

[Research progress on rutin derivatives].

Compounds derived from natural products present satisfactory efficacy in disease prevention and treatment. The use of chemical substances in plants to promote healthhas increasingly attracted people's attention. Rutin, a typical flavonoid, is mainly found in various vegetables, fruits and Chinese herbal medicines. As a natural antioxidant, it features many pharmacological activities, such as anti-inflammation, anti-virus, anti-tumor, and prevention and treatment of cardiovascular and cerebrovascular diseases. However, the low bioavailability and poor water solubility limit its clinical application. In view of this, its structure is optimized and modified to afford rutin derivatives with good solubility, high bioavailability, stable metabolism and small toxic side effects. So far, a large number of rutin ethers, esters, and complexes have been synthesized and undergone activity testing. This paper reviews the structural modification of rutin in recent years, and the obtained derivatives have excellent properties and significant biological activity.

Mechanotransduction pathways in the regulation of cartilage chondrocyte homoeostasis.

Mechanical stress plays a critical role in cartilage development and homoeostasis. Chondrocytes are surrounded by a narrow pericellular matrix (PCM), which absorbs dynamic and static forces and transmits them to the chondrocyte surface. Recent studies have demonstrated that molecular components, including perlecan, collagen and hyaluronan, provide distinct physical properties for the PCM and maintain the essential microenvironment of chondrocytes. These physical signals are sensed by receptors and molecules located in the cell membrane, such as Ca2+ channels, the primary cilium and integrins, and a series of downstream molecular pathways are involved in mechanotransduction in cartilage. All mechanoreceptors convert outside signals into chemical and biological signals, which then regulate transcription in chondrocytes in response to mechanical stresses. This review highlights recent progress and focuses on the function of the PCM and cell surface molecules in chondrocyte mechanotransduction. Emerging understanding of the cellular and molecular mechanisms that regulate mechanotransduction will provide new insights into osteoarthritis pathogenesis and precision strategies that could be used in its treatment.