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As a complicated and heterogeneous condition, breast cancer (BC) has posed a tremendous public health challenge across the world. Recent studies have uncovered the crucial effect of human microbiota on various perspectives of health and disease, which include cancer. The oral-gut microbiome axis, particularly, have been implicated in the occurrence and development of colorectal cancer through their intricate interactions with host immune system and modulation of systemic inflammation. However, the research concerning the impact of oral-gut microbiome axis on BC remains scarce. This study focused on comprehensively reviewing and summarizing the latest ideas about the potential bidirectional relation of the gut with oral microbiota in BC, emphasizing their potential impact on tumorigenesis, treatment response, and overall patient outcomes. This review can reveal the prospect of tumor microecology and propose a novel viewpoint that the oral-gut microbiome axis can be a breakthrough point in future BC studies.

Hydroxyapatite (HAP) materials are widely applied as biomedical materials due to their stable performance, low cost, good biocompatibility and biodegradability. Here, a green, fast and efficient strategy was designed to construct a fluorescent nanosystem for cell imaging and drug delivery based on polyethyleneimine (PEI) and functionalized HAP via simple physical adsorption. First, HAP nanorods were functionalized with riboflavin sodium phosphate (HE) to provide them with fluorescence properties based on ligand-exchange process. Next, PEI was attached on the surface of HE-functionalized HAP (HAP-HE@PEI) via electrostatic attraction. The fluorescent HAP-HE@PEI nanosystem could be rapidly taken up by NIH-3T3 fibroblast cells and successfully applied to for cell imaging. Additionally, doxorubicin hydrochloride (DOX) containing HAP-HE@PEI with high loading capacity was prepared, and in-vitro release results show that the maximum release of DOX at pH 5.4 (31.83%) was significantly higher than that at pH 7.2 (9.90%), which can be used as a drug delivery tool for cancer therapy. Finally, HAP-HE@PEI as the 3D inkjet printing ink were printed with GelMA hydrogel, showing a great biocompatible property for 3D cell culture of RAW 264.7 macrophage cells. Altogether, because of the enhanced affinity with the cell membrane of HAP-HE@PEI, this green, fast and efficient strategy may provide a prospective candidate for bio-imaging, drug delivery and bio-printing.

By integrating 3D-inkjet bioprinting technology, differentiated human cells can be assembled into artificial lung tissue structure to achieve a rapid, efficient, and reproducible disease model construction process. Here, we developed a novel 3D-inkjet bioprinting-based method to construct artificial lung tissue structure (ALTs) for acute lung injury (ALI) disease modeling, research and application. It can also be used to study the role of relevant cells in the disease by adjusting the cell type and adapted to study the bio-functions of immune cells during the cell-cell interactions. Firstly, a series of process optimizations were done to mass-produce the alginate hydrogel microspheres (Alg) with a particle size of 262.63 ± 5 μm using a 3D bioprinter, then the type I collagen and polydopamine were deposited in turns to construct a cell adhesion layer on the surfaces of Alg (P-Alg) and the particle size was increased to 328.41 ± 3.81 μm. This platform exhibites good stability, timescale-dependent behavior, and long-term cell adhesion. Subsequently, several human cells including endothelial, epithelial, fibroblast, and even immune cells such as macrophages were adhered to P-Alg through rotational culture, leading to cell contractions and aggregation, subsequently formed ALTs or ALTs with macrophages (ALTs@M) with human alveolar-like structure. Finally, we successfully constructed an ALI model with lung barrier damage on ALTs using lipopolysaccharide stimulation in vitro, and comparison of secreted inflammatory factors between ALTs and ALTs@M. Results demonstrated that ALTs@M was more effective than ALTs in stimulating the inflammatory microenvironment of the lungs, providing a novel in vitro model for cellular interactions and human macrophage research. Altogether, this artificial lung tissue structure construction strategy using 3D-inkjet bioprinting technology allowed the flexible development of artificial lung tissue structures as potential disease models for preclinical studies.

Microvesicles known as exosomes have a diameter of 40 to 160 nm and are derived from small endosomal membranes. Exosomes have attracted increasing attention over the past ten years in part because they are functional vehicles that can deliver a variety of lipids, proteins, and nucleic acids to the target cells they encounter. Because of this function, exosomes may be used for the diagnosis, prognosis and treatment of many diseases. All throughout the world, cardiovascular diseases (CVDs) continue to be a significant cause of death. Because exosomes are mediators of communication between cells, which contribute to many physiological and pathological aspects, they may aid in improving CVD therapies as biomarkers for diagnosing and predicting CVDs. Many studies demonstrated that exosomes are associated with CVDs, such as coronary artery disease, heart failure, cardiomyopathy and atrial fibrillation. Exosomes participate in the progression or inhibition of these diseases mainly through the contents they deliver. However, the application of exosomes in diferent CVDs is not very mature. So further research is needed in this field.

The present study induced in vitro-cultured passage 4 bone marrow-derived mesenchymal stem cells to differentiate into neural-like cells with a mixture of alkaloid, polysaccharide, aglycone, glycoside, essential oils, and effective components of Buyang Huanwu decoction （active principle region of decoction for invigorating yang for recuperation）. After 28 days, nestin and neuron-specific enolase were expressed in the cytoplasm. Reverse transcription-PCR and western blot analyses showed that nestin and neuron-specific enolase mRNA and protein expression was greater in the active principle region group compared with the original formula group. Results demonstrated that the active principle region of Buyang Huanwu decoction induced greater differentiation of rat bone marrow-derived mesenchymal stem cells into neural-like cells in vitro than the original Buyang Huanwu decoction formula.

The current study constructs a quasi-natural experiment based on China’s 2012 Green Credit Guidelines and develops a difference-in-difference model using the financial data of listed companies from 2006 to 2018 to conduct empirical testing. The results reveal that the green credit policy has significantly reduced the short-term and long-term debt financing of heavily polluting enterprises; however, the restrictions on short-term debt financing are insufficient. At the same time, the decline in operating performance brings financial penalty effects, among which state-owned, large-scale, and heavily polluting enterprises in high-emission areas have strong financial penalty effects. The green credit policy encourages heavy-polluting companies to increase R&D investment and increase fixed assets investments to obtain long-term credit support with short-term investment. Furthermore, it is found that the green credit policies have significantly restrained the scale of debt financing of heavily polluting companies. The Chinese government should formulate green financial policies based on local conditions and provide credit resources to favor environmentally friendly companies. Financial institutions should strictly implement green credit standards and modify financial products and services. Companies should take the initiative to eliminate outdated production capacity to obtain green credit support.

This study focuses on systematically revealing how cutting parameters influence the surface integrity of ball-end hard milled surface of AISI D2 steel and proposing optimization scheme from surface integrity, wear resistance and fatigue resistance perspective based on response surface methodology respectively. Results can be summarized into three aspects. Firstly, radial depth of cut with percent contribution ratio (PCR) 62.05% has a decisive influence on surface roughness, followed by spindle speed 13.25% and feed per tooth 6.63%. The work hardening degree was raised from 12.5% to 38.4% when spindle speed changed from 8000 rpm to 2000 rpm. Spindle speed and radial depth of cut are the most significant factor influencing residual stress. The PCR of spindle speed and radial depth of cut reached 73.47% and 18.63% for residual stress in feed direction, 47.11% and 37.51% in step-over direction, respectively. High residual compressive stress can be generated by lowering spindle speed and radial depth of cut benefiting from the aggravated squeeze between ball-end milling cutter and workpiece. Secondly, too small feed per tooth or too small radial depth of cut should be avoided from wear resistance point because though the surface microhardness can be improved, the surface quality will also be deteriorated. The combination of high spindle speed, small feed per tooth together with small radial depth of cut can meet the wear resistance and the machining efficiency requirement. Finally, a medium-sized cutting parameter combination should be adopted to realize satisfying material removal rate and fatigue resistance. This study can be used to guide the selection of cutting parameters during ball-end milling of hardened AISI D2 steel for dies/molds manufacturing industries.

Accurate storage tank detection in remote sensing images is vital for monitoring methane emissions, a potent greenhouse gas, from the oil and gas industry. Existing methods, such as traditional geometric and spectral feature-based approaches, suffer from high false detection rates due to background variations and imaging conditions, while deep learning models like YOLO series and EfficientDet struggle with small objects, multi-scale features, background interference, and regression sensitivity, leading to missed detections and false positives. This study introduces a novel method integrating circular bounding boxes and a Large Selective Kernel (LSK) to address these gaps. Circular bounding boxes, aligned with storage tanks’ typical circular shape, stabilize Intersection over Union (IoU) for small objects, while LSK dynamically adjusts the receptive field to leverage contextual information effectively. Implemented on a YOLO-v10 framework and evaluated on a comprehensive dataset comprising DIOR, NWPUU_RESISC45, NWPU VHR-10, TGRS-HRRSD, and a self-built dataset (totaling 3568 images and 46075 storage tanks), our approach achieved a precision of 0.911, recall of 0.902, and mean Average Precision (mAP@0.5) of 0.931. These results represent improvements of 2.0% in precision, 2.7% in recall, and 1.8% in mAP@0.5 over the state-of-the-art YOLO-v10 baseline, offering a robust tool for pinpointing methane emission sources and supporting environmental sustainability efforts in the oil and gas sector.

The extensive application of perfluoroalkyl and polyfluoroalkyl substances (PFASs) causes their frequent detection in various environments. In this work, two typical PFASs, perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS), are selected to investigate their effects on soil microorganisms. Microbial community structure and microbe–microbe relationships were investigated by high-throughput sequencing and co-occurrence network analysis. Under 90 days of exposure, the alpha-diversity of soil microbial communities was increased with the PFOS treatment, followed by the PFOA treatment. The exposure of PFASs substantially changed the compositions of soil microbial communities, leading to the enrichment of more PFASs-tolerant bacteria, such as Proteobacteria, Burkholderiales, and Rhodocyclales. Comparative co-occurrence networks were constructed to investigate the microbe–microbe interactions under different PFASs treatments. The majority of nodes in the PFOA and PFOS networks were associated with the genus Azospirillum and Hydrogenophaga, respectively. The LEfSe analysis further identified a set of biomarkers in the soil microbial communities, such as Azospirillum, Methyloversatilis, Hydrogenophaga, Pseudoxanthomonas, and Fusibacter. The relative abundances of these biomarkers were also changed by different PFASs treatments. Functional gene prediction suggested that the microbial metabolism processes, such as nucleotide transport and metabolism, cell motility, carbohydrate transport and metabolism, energy production and conversion, and secondary metabolites biosynthesis transport and catabolism, might be inhibited under PFAS exposure, which may further affect soil ecological services.

Ethylamine (EA), the precursor of theanine biosynthesis, is synthesized from alanine decarboxylation by alanine decarboxylase (AlaDC) in tea plants. AlaDC evolves from serine decarboxylase (SerDC) through neofunctionalization and has lower catalytic activity. However, lacking structure information hinders the understanding of the evolution of substrate specificity and catalytic activity. In this study, we solved the X-ray crystal structures of AlaDC from Camellia sinensis (CsAlaDC) and SerDC from Arabidopsis thaliana (AtSerDC). Tyr 341 of AtSerDC or the corresponding Tyr 336 of CsAlaDC is essential for their enzymatic activity. Tyr 111 of AtSerDC and the corresponding Phe 106 of CsAlaDC determine their substrate specificity. Both CsAlaDC and AtSerDC have a distinctive zinc finger and have not been identified in any other Group II PLP-dependent amino acid decarboxylases. Based on the structural comparisons, we conducted a mutation screen of CsAlaDC. The results indicated that the mutation of L110F or P114A in the CsAlaDC dimerization interface significantly improved the catalytic activity by 110% and 59%, respectively. Combining a double mutant of CsAlaDC L110F/P114A with theanine synthetase increased theanine production 672% in an in vitro system. This study provides the structural basis for the substrate selectivity and catalytic activity of CsAlaDC and AtSerDC and provides a route to more efficient biosynthesis of theanine.