Analysis of the lipidomic profile of vegetable oils and animal fats and changes during aging by UPLC-Q-exactive orbitrap mass spectrometry.

Vegetable oil and animal fat residues are common evidence in the cases of homicide, arson, theft, and other crimes. However, the lipid composition and content changes during aging on complex carriers remain unclear. Therefore, this study dynamically monitored the lipid composition and content changes during aging of 13 different types of vegetable oils and animal fats on five different carriers using the UPLC-Q-Exactive Orbitrap MS method. A total of 6 subclasses of 93 lipids including lysophosphatidylcholine (2 species), phosphatidylcholine (2 species), diglyceride (5 species), triglyceride (81 species), acylGlcCampesterol ester (2 species), and acylGlcSitosterol ester (1 species), were first identified in fresh vegetable oils and animal fats. By comparing the LC-MS/MS chromatograms of fresh vegetable oils and animal fats, it was found that there were significant differences between the chromatograms of vegetable oils and animal fats, but it was difficult to distinguish between the chromatograms of vegetable oils or animal fats. After aging at 60 °C for 200 days, there was a significant decrease in the content of diglyceride, triglyceride, acylGlcCampesterol ester, and acylGlcSitosterol ester, while the content of lysophosphatidylcholine and phosphatidylcholine initially increased and then decreased. Furthermore, statistical analysis of lipid differences between vegetable oils and animal fats was performed using cluster heat maps, volcanic maps, PCA, and OPLS-DA. On average, 33 significantly different lipids were screened (VIP > 1, p < 0.05), which could serve as potential biomarkers for distinguishing vegetable oils and animal fats. It was found that the potential biomarkers still existed during aging of vegetable oils and animal fats (100 and 200 days). This research provides important reference information for the identification of vegetable oil and animal fat residues in complex carriers at crime scenes.

Multiparameter Mechanical Phenotyping for Accurate Cell Identification Using High-Throughput Microfluidic Deformability Cytometry.

Mechanical phenotyping has been widely employed for single-cell analysis over recent years. However, most previous works on characterizing the cellular mechanical properties measured only a single parameter from one image. In this paper, the quasi-real-time multiparameter analysis of cell mechanical properties was realized using high-throughput adjustable deformability cytometry. We first extracted 12 deformability parameters from the cell contours. Then, the machine learning for cell identification was performed to preliminarily verify the rationality of multiparameter mechanical phenotyping. The experiments on characterizing cells after cytoskeletal modification verified that multiple parameters extracted from the cell contours contributed to an identification accuracy of over 80%. Through continuous frame analysis of the cell deformation process, we found that temporal variation and an average level of parameters were correlated with cell type. To achieve quasi-real-time and high-precision multiplex-type cell detection, we constructed a back propagation (BP) neural network model to complete the fast identification of four cell lines. The multiparameter detection method based on time series achieved cell detection with an accuracy of over 90%. To solve the challenges of cell rarity and data lacking for clinical samples, based on the developed BP neural network model, the transfer learning method was used for the identification of three different clinical samples, and finally, a high identification accuracy of approximately 95% was achieved.

Government-enterprise green collaborative governance and urban carbon emission reduction: Empirical evidence from green PPP programs.

The reliance solely on the government or enterprises to promote climate governance is contingent upon the vested interests of economic entities and the regulatory bodies' efficiency in governance. Can the model of government-enterprise green collaborative governance evolve into a long-term mechanism for addressing the climate crisis and achieving the goals of sustainable development? By crawling data on public-private partnerships (PPP), employing ChatGPT to identify green PPP projects, and building a generalized difference-in-differences framework based on the Guidance on Building a Green Financial System issued in 2016, this present study investigates whether the involvement of private capital in government-led environmental and climate governance can effectively facilitate government-enterprise green collaborative governance, thereby mitigating urban carbon emissions. The study finds government-enterprise green collaborative governance can significantly reduce urban carbon emissions. The conclusion remains valid even after several rounds of robustness tests, including removing the influence of pertinent climate policies, adjusting the settings of independent and dependent variables, and removing self-selection issues. Heterogeneity tests show, on the first hand, the carbon emission reduction effect of government-enterprise green collaborative governance differs due to the differences in the characteristics of green PPP(Pubic-private partnership) projects such as project return mechanism, project investment volume, and project cooperation term; on the other hand, the carbon emission reduction effect also shows heterogeneity with various urban characteristics such as geographical location, city type and city size. Mechanism tests indicate government-enterprise green collaborative governance affects urban carbon emissions mainly through structural effects, technological effects and co-investment effects. This paper offers a valuable framework for effectively promoting environmental and climate co-governance between governmental bodies and enterprises, while enhancing the market's role in resource benefit allocation within climate governance to mitigate the risks associated with climate change.

Muscle-bone cross-talk through the FNIP1-TFEB-IGF2 axis is associated with bone metabolism in human and mouse.

Clinical evidence indicates a close association between muscle dysfunction and bone loss; however, the underlying mechanisms remain unclear. Here, we report that muscle dysfunction-related bone loss in humans with limb-girdle muscular dystrophy is associated with decreased expression of folliculin-interacting protein 1 (FNIP1) in muscle tissue. Supporting this finding, murine gain- and loss-of-function genetic models demonstrated that muscle-specific ablation of FNIP1 caused decreased bone mass, increased osteoclastic activity, and mechanical impairment that could be rescued by myofiber-specific expression of FNIP1. Myofiber-specific FNIP1 deficiency stimulated expression of nuclear translocation of transcription factor EB, thereby activating transcription of insulin-like growth factor 2 (Igf2) at a conserved promoter-binding site and subsequent IGF2 secretion. Muscle-derived IGF2 stimulated osteoclastogenesis through IGF2 receptor signaling. AAV9-mediated overexpression of IGF2 was sufficient to decrease bone volume and impair bone mechanical properties in mice. Further, we found that serum IGF2 concentration was negatively correlated with bone health in humans in the context of osteoporosis. Our findings elucidate a muscle-bone cross-talk mechanism bridging the gap between muscle dysfunction and bone loss. This cross-talk represents a potential target to treat musculoskeletal diseases and osteoporosis.

Genome evolution of the ancient hexaploid Platanus × acerifolia (London planetree).

Whole-genome duplication (WGD; i.e., polyploidy) and chromosomal rearrangement (i.e., genome shuffling) significantly influence genome structure and organization. Many polyploids show extensive genome shuffling relative to their pre-WGD ancestors. No reference genome is currently available for Platanaceae (Proteales), one of the sister groups to the core eudicots. Moreover, Platanus × acerifolia (London planetree; Platanaceae) is a widely used street tree. Given the pivotal phylogenetic position of Platanus and its 2-y flowering transition, understanding its flowering-time regulatory mechanism has significant evolutionary implications; however, the impact of Platanus genome evolution on flowering-time genes remains unknown. Here, we assembled a high-quality, chromosome-level reference genome for P. × acerifolia using a phylogeny-based subgenome phasing method. Comparative genomic analyses revealed that P. × acerifolia (2n = 42) is an ancient hexaploid with three subgenomes resulting from two sequential WGD events; Platanus does not seem to share any WGD with other Proteales or with core eudicots. Each P. × acerifolia subgenome is highly similar in structure and content to the reconstructed pre-WGD ancestral eudicot genome without chromosomal rearrangements. The P. × acerifolia genome exhibits karyotypic stasis and gene sub-/neo-functionalization and lacks subgenome dominance. The copy number of flowering-time genes in P. × acerifolia has undergone an expansion compared to other noncore eudicots, mainly via the WGD events. Sub-/neo-functionalization of duplicated genes provided the genetic basis underlying the unique flowering-time regulation in P. × acerifolia. The P. × acerifolia reference genome will greatly expand understanding of the evolution of genome organization, genetic diversity, and flowering-time regulation in angiosperms.

Guizhi Shaoyao Zhimu Decoction ameliorates gouty arthritis in rats via altering gut microbiota and improving metabolic profile.

BACKGROUND: The incidence of gouty arthritis (GA) has gradually increased, and modern drug therapies have obvious side effects. Guizhi Shaoyao Zhimu Decoction (GSZD), a classic prescription in Traditional Chinese Medicine for treating various osteoarthritis, has shown significant advantages in curing GA. PURPOSE: To verify the therapeutic effect of GSZD on GA and investigate its potential pharmacological mechanism via integrated analysis of the gut microbiota and serum metabolites for the first time. METHODS: The chemical composition of GSZD was determined using UPLC-MS. The GA rat model was established by the induction of a high-purine diet combined with local injection. We examined the effects and mechanisms of GSZD after 21 d using enzyme-linked immunosorbent assays, 16S rRNA, and non-targeted metabolomics. Finally, correlation analysis and validation experiment were performed to explore the association among the gut microbiota, serum metabolites, and GA-related clinical indices. RESULTS: In total, 19 compounds were identified as GSZD. High-purine feedstuff with local injection-induced arthroceles were significantly attenuated after GSZD treatment. GSZD improved bone erosion and reduced the serum levels of inflammatory factors (lipopolysaccharide, tumor cell necrosis factor-α, and interleukin) and key indicators of GA (uric acid). 16S rRNA analysis indicated that GSZD-treated GA rats exhibited differences in the composition of the gut microbiota. The abundance of flora involved in uric acid transport, including Lactobacillus, Ruminococcaceae, and Turicibacter, was elevated to various degrees, whereas the abundance of bacteria involved in inflammatory responses, such as Blautia, was markedly reduced after treatment. Moreover, serum metabolite profiles revealed 27 different metabolites associated with the amelioration of GA, which primarily included fatty acids, glycerophospholipids, purine metabolism, amino acids, and bile acids, as well as primary metabolic pathways, such as glycerophospholipid metabolism and alanine. Finally, correlation analysis of the heat maps and validation experiment demonstrated a close relationship among inflammatory cytokines, gut microbial phylotypes, and metabolic parameters. CONCLUSION: This study demonstrated that GSZD could modulate the gut microbiota and serum metabolic homeostasis to treat GA. In addition, the application of gut microbiota and serum metabolomics correlation analyses sheds light on the mechanism of Traditional Chinese Medicine compounds in the treatment of bone diseases.

Multistage feature fusion knowledge distillation.

Generally, the recognition performance of lightweight models is often lower than that of large models. Knowledge distillation, by teaching a student model using a teacher model, can further enhance the recognition accuracy of lightweight models. In this paper, we approach knowledge distillation from the perspective of intermediate feature-level knowledge distillation. We combine a cross-stage feature fusion symmetric framework, an attention mechanism to enhance the fused features, and a contrastive loss function for teacher and student models at the same stage to comprehensively implement a multistage feature fusion knowledge distillation method. This approach addresses the problem of significant differences in the intermediate feature distributions between teacher and student models, making it difficult to effectively learn implicit knowledge and thus improving the recognition accuracy of the student model. Compared to existing knowledge distillation methods, our method performs at a superior level. On the CIFAR100 dataset, it boosts the recognition accuracy of ResNet20 from 69.06% to 71.34%, and on the TinyImagenet dataset, it increases the recognition accuracy of ResNet18 from 66.54% to 68.03%, demonstrating the effectiveness and generalizability of our approach. Furthermore, there is room for further optimization of the overall distillation structure and feature extraction methods in this approach, which requires further research and exploration.

Association between estimated glucose disposal rate and atrial fibrillation recurrence in patients undergoing radiofrequency catheter ablation: a retrospective study.

OBJECTIVE: Previous studies have shown a clear link between insulin resistance (IR) and an elevated risk of atrial fibrillation (AF). However, the relationship between the estimated glucose disposal rate (eGDR), which serves as a marker for IR, and the risk of AF recurrence after radiofrequency catheter ablation (RFCA) remains uncertain. Therefore, this study aimed to examine the potential association between the eGDR and the risk of AF recurrence following RFCA. METHODS: This retrospective study was conducted at Nanchang University Affiliated Second Hospital. The study enrolled 899 patients with AF who underwent RFCA between January 2015 and January 2022. The formula used to calculate the eGDR was as follows: 19.02 - (0.22 * body mass index) - (3.26 * hypertension) - (0.61 * HbA1c). Cox proportional hazard regression models and exposure-effect curves were used to explore the correlation between the baseline eGDR and AF recurrence. The ability of the eGDR to predict AF recurrence was evaluated using the area under the receiver operating characteristic curve (AUROC). RESULTS: The study observed a median follow-up period of 11.63 months, during which 296 patients experienced AF recurrence. K‒M analyses revealed that the cumulative incidence AF recurrence rate was significantly greater in the group with the lowest eGDR (log-rank p < 0.01). Participants with an eGDR ≥ 8 mg/kg/min had a lower risk of AF recurrence than those with an eGDR < 4 mg/kg/min, with a hazard ratio (HR) of 0.28 [95% confidence interval (CI) 0.18, 0.42]. Additionally, restricted cubic spline analyses demonstrated a linear association between the eGDR and AF recurrence (p nonlinear = 0.70). The area under the curve (AUC) for predicting AF recurrence using the eGDR was 0.75. CONCLUSIONS: The study revealed that a decrease in the eGDR is associated with a greater AF recurrence risk after RFCA. Hence, the eGDR could be used as a novel biomarker for assessing AF recurrence risk.

Fully upgrade bamboo biomass into three multifunctional products through biphasic γ-valerolactone and aqueous phosphoric acid pretreatment.

In this manuscript, three components of lignocellulosic biomass were obtained by deconstructing bamboo with γ-valerolactone-H2O biphasic system, and the delignification rate of 80.92 % was achieved at 120 °C for 90 min. Lignin nanospheres with diameters ranging from 75 nm to 2 um could be customized by varying the self-assembly rate. Furthermore, the lignin nanospheres-poly(vinyl alcohol) film was prepared by cross-linking lignin nanospheres and poly(vinyl alcohol), which can obtain 90 % ultraviolet absorption capacity, while the light transmittance in non-ultraviolet band was almost unchanged. At the same time, due to the strong hydrogen formation between lignin nanospheres and poly(vinyl alcohol) bond network, the tensile properties of the composite film were also improved by 30 %. Besides, the high specific surface area of biomass-derived porous biochar (2056 m2/g) can be obtained after carbonization of solid residues at 850 °C for 2 h, which was almost 8 times the specific surface area of the direct biomass carbonization due to the removal of lignin and hemicellulose. biomass-derived porous biochar can be used as an adsorbent, with a CO2 capture capacity of 4.5 mmol g-1 at normal temperature (25 °C, 1 bar). The filtrate after the reaction contained a large amount of hemicellulose oligomers, which can be reacted with dichloromethane at 170 °C for 1 h to obtain the furfural yield of 74 %. In summary, the proposed biorefinery scheme achieves a full-component upgrade of lignocellulose and can be further applied in various downstream fields.

A Case of Pseudothrombocytopenia due to Pre-Analytical Issues Revealed by the Presence of Fibrin in a Blood Film.

BACKGROUND: Pseudothrombocytopenia (PTCP) can be caused by anticoagulants or pre-analytical issues. The authors present a case of PTCP attributed to pre-analytical issues in a 68-year-old male patient. METHODS: The platelet count results were obtained using both the impedance and fluorescence channels of Sysmex XN-10. The blood film was scanned using both Cellavision DM96 and a microscope. RESULTS: The flag for PLT-Clumps and the scattergram from the PLT-F channel indicated the presence of platelet aggregation. Fibrin could be observed at the feathered end of the blood film. A diagnosis of PTCP resulting from pre-analytical issues was made. CONCLUSIONS: The presence of fibrin in a blood film is a critical indicator for diagnosing PTCP due to pre-analytical issues.

Industrial Metaverse-Based Intelligent PID Optimal Tuning System for Complex Industrial Processes.

In this article, the method of dynamic performance monitoring and adaptive self-tuning of parameters for actual PID control systems of industrial processes in virtual reality scenes is proposed. This method combines the digital twin model of the PID control process based on system identification and adaptive deep learning and the PID tuning intelligent algorithm based on reinforcement learning with virtual reality and immersive interaction of industrial metaverse. An industrial metaverse-based intelligent PID tuning system is proposed by combining the above method with the end-edge-cloud collaboration technology of Industrial Internet. The challenging problem that the actual operating PID control system in complex industrial processes cannot be optimized online is solved. Using the energy-intensive equipment, the fused magnesium furnace, as an industrial object, we conducted comparative simulation experiments between the proposed control method and several advanced control methods, as well as industrial experiments for the proposed intelligent system. Simulation experiments demonstrate the effectiveness of the proposed control method. The industrial experimental results indicate that the performance monitoring and adaptive self-tuning of parameters for actual PID control systems of industrial processes in virtual reality scenes can be realized, which achieves excellent control effects.

Bottom-Up Assembling Hierarchical Enamel-Like Bulk Materials with Excellent Optical and Mechanical Properties for Tooth Restoration.

Enamel has good optical and mechanical properties because of its multiscale hierarchical structure. Biomimetic construction of enamel-like 3D bulk materials at nano-, micro-, mesh- and macro-levels is a challenge. A novel facile, cost-effective, and easy large-scale bottom-up assembly strategy to align 1D hydroxyapatite (HA) nanowires bundles to 3D hierarchical enamel structure with the nanowires bundles layer-by-layer interweaving orientation, is reported. In the strategy, the surface of oleate templated ultralong HA nanowires with a large aspect ratio is functionalized with amphiphilic 10-methacryloyloxydecyl dihydrogen phosphate (MDP). Furtherly, the MDP functionalized HA nanowire bundles are assembled layer-by-layer with oriented fibers in a single layer and cross-locked between layers at a certain angle at mesoscale and macroscale in the viscous bisphenol A-glycidyl methacrylate (Bis-GMA) ethanol solution by shear force induced by simple agitation and high-speed centrifugation. Finally, the excessive Bis-GMA and ethanol are removed, and (Bis-GMA)-(MDP-HA nanowire bundle) matrix is densely packed under hot pressing and polymerized to form bulk enamel-like materials. The composite has superior optical properties and comparable comprehensive mechanic performances through a combination of strength, hardness, toughness, and friction. This method may open new avenues for controlling the nanowires assembly to develop hierarchical nanomaterials with superior properties for many different applications.

Mice hepatic organoids for modeling nonalcoholic fatty liver disease and drug response.

Nonalcoholic fatty liver disease (NAFLD) is a serious disease. There are no specific drugs for it, in part because of the lack of effective models to aid drug development. However, it has been shown that three-dimensional organoid culture systems can reproduce the organ structure and maintain the gene expression profile of the original tissue. Therefore, we aimed to construct NAFLD models from liver organoids for pharmacological and mechanism studies. We successfully observed morphological changes in normal liver tissue in mouse liver organoids with positive albumin (ALB) expression and potential for differentiation toward hepatocyte-like cells. The mRNA expression of the hepatocyte markers ALB and hepatocyte nuclear factor 4 alpha increased after liver organoid differentiation. We observed free fatty acid (FFA)-induced lipid accumulation in organoids with significant increases in alanine aminotransferase, aspartate aminotransferase, total bilirubin, and triglyceride levels. Moreover, FFA-induced inflammatory cytokines (interleukin-6, tumor necrosis factor-α, and nitric oxide) and fibrosis indicators (collagen type I alpha 1 and laminin α1) were also increased. In addition, RNA sequencing results showed that the expression of key genes (NOD-like receptor family apoptosis inhibitory protein, interferon regulatory factor (IRF)3 and IRF7) involved in NAFLD metabolic abnormalities and insulin resistance in the NOD-like receptor signaling pathway was altered after FFA induction of the liver organoids. Finally, we found that JC2-11 and lanifibranor limited the FFA-induced increase in oil-red lipid droplets, liver damage, inflammation, and liver fibrosis. In conclusion, tissue structure, gene expression, and the response of mouse liver organoids to drugs can partially mimic in vivo liver tissue. Liver organoids can successfully construct NAFLD models for drug discovery research.

Ultra-thin FeCoNi-LDH hollow nanoflower as solid-phase microextraction coating for targeted capture of six pesticides by electrostatic adsorption.

Pesticides are common pollutants that cause detriment to the ecological environmental safety and health of human due to their toxicity, volatility and bioaccumulation. In this work, an ultra-thin polymetallic layered double hydroxide (FeCoNi-LDH) with hollow nanoflower structure composite was synthesized using ZIF-67 as a self-sacrificial template, which was used as solid-phase microextraction (SPME) coating for the targeted capture pesticides, which could be combined with high-performance liquid chromatography (HPLC) to sensitive inspection pesticides in real water samples. Orthogonal experimental design (OAD) was applied to ensure the best SPME condition. Additionally, the adsorption properties were evaluated by chemical thermodynamics and kinetics. Under the optimized conditions, high adsorption capacity was obtained (117.0-21.5 mg g-1). A wide linear range (0.020-1000.0 µg L-1), low detection limit (0.008-0.172 µg L-1) and excellent reproducibility were obtained under the established method. This research provided a new strategy for designing hollow materials with multiple cations for the adsorption of anion or organic pollutants.

FAM3D regulation of head and neck squamous cell carcinoma behaviour through the EMT pathway.

OBJECTIVES: Head and neck squamous cell carcinoma present challenges in effective treatment, with 50%-60% of cases exhibiting recurrence or metastasis, often resistant to surgery alone. Immunotherapy, a promising approach, does not guarantee benefits for all patients. Thus, the imperative lies in identifying reliable biomarkers for predicting immunotherapy efficacy. FAM3D, a protein-coding gene known for its potent chemotactic activity in human peripheral blood monocytes and neutrophils, plays a crucial role in regulating tumour immune responses and holds promise as an immune biomarker. MATERIALS AND METHODS: We employed comprehensive database analysis to scrutinise FAM3D, evaluating its gene expression, mutation profiles and prognostic implications in head and neck squamous cell carcinoma, along with its associations with clinical characteristics and immune cell infiltration. Complementary functional experiments were conducted to delve into the potential mechanisms governed by FAM3D. RESULTS: Our findings establish a significant correlation between low FAM3D expression and the invasiveness and metastatic potential of head and neck squamous cell carcinoma. FAM3D likely exerts its influence through the regulation of epithelial-mesenchymal transition. CONCLUSIONS: FAM3D emerges as a valuable biomarker for predicting the responsiveness of patients with head and neck squamous cell carcinoma to immunotherapy, holding substantial clinical diagnostic and therapeutic relevance.

Functional and structural dissection of glycosyltransferases underlying the glycodiversity of wolfberry-derived bioactive ingredients lycibarbarspermidines.

Lycibarbarspermidines are unusual phenolamide glycosides characterized by a dicaffeoylspermidine core with multiple glycosyl substitutions, and serve as a major class of bioactive ingredients in the wolfberry. So far, little is known about the enzymatic basis of the glycosylation of phenolamides including dicaffeoylspermidine. Here, we identify five lycibarbarspermidine glycosyltransferases, LbUGT1-5, which are the first phenolamide-type glycosyltransferases and catalyze regioselective glycosylation of dicaffeoylspermidines to form structurally diverse lycibarbarspermidines in wolfberry. Notably, LbUGT3 acts as a distinctive enzyme that catalyzes a tandem sugar transfer to the ortho-dihydroxy group on the caffeoyl moiety to form the unusual ortho-diglucosylated product, while LbUGT1 accurately discriminates caffeoyl and dihydrocaffeoyl groups to catalyze a site-selective sugar transfer. Crystal structure analysis of the complexes of LbUGT1 and LbUGT3 with UDP, combined with molecular dynamics simulations, revealed the structural basis of the difference in glycosylation selectivity between LbUGT1 and LbUGT3. Site-directed mutagenesis illuminates a conserved tyrosine residue (Y389 in LbUGT1 and Y390 in LbUGT3) in PSPG box that plays a crucial role in regulating the regioselectivity of LbUGT1 and LbUGT3. Our study thus sheds light on the enzymatic underpinnings of the chemical diversity of lycibarbarspermidines in wolfberry, and expands the repertoire of glycosyltransferases in nature.

Extrafibrillar demineralization: Yes or no?

OBJECTIVE: Extrafibrillar demineralization is considered to be an ideal solution for addressing the durability of resin-dentin bonding interfaces. However, its theoretical basis is contradictory to ionization equilibrium of hydroxyapatite dissolution. In this study, various calcium chelators were selected as dentin conditioners to explore the essence of dentin demineralization with chelators and its effect on resin-dentin adhesion. METHODS: Polyethyleneimine grafted with EDTA and polyacrylic acid sodium (PAAN450k) larger than 40 kDa, as well as PAAN (PAAN3k) and EDTA smaller than 6 kDa, were prepared as dentin conditioners. The dentin powder was designed to characterize whether it would demineralize without contact with PAAN450k. Dentin demineralization effect with four conditioners was evaluated with field emission scanning electron microscopy, transmission electron microscopy, X-ray photoelectron spectroscopy, atomic force microscopy and quantification of hydroxyproline concentration after enzymatic degradation. Micro-tensile bond strength (µTBS) test and failure mode analysis were employed to assess the bonding effect of the four chelators in both wet and dry bonding, with H3PO4 wet bonding serving as the control group. RESULTS: Demineralization occurs when PAAN450k was not in direct contact with the dentin powder. The extrafibrillar demineralization cannot be induced by any chelator regardless of its molecular weight. Complete demineralization including extrafibrillar and intrafibrillar demineralization would occur with sufficient interaction time. Moreover, chelators could not provide a reliable dentin bonding effect under a short interaction time. SIGNIFICANCE: From the perspective of theory and application, extrafibrillar demineralization is not a reliable strategy, which provides a reminder for exploring new strategies in the future.

The role of FERMT2 in the tumor microenvironment and immunotherapy in pan-cancer using comprehensive single-cell and bulk sequencing.

FERMT2 has been identified as a participant in integrin-linked kinase signaling pathways, influencing epithelial-mesenchymal transition and thereby affecting tumor initiation, progression, and invasion. While the character of FERMT2 in the tumor microenvironment (TME) as well as its implications for immunotherapy remain unclear. Thus, we conducted a comprehensive analysis to assess the prognostic significance of FERMT2 using Kaplan-Meier analysis. In addition, we employed enrichment analysis to uncover potential underlying molecular mechanisms. Using "Immunedeconv" package, we evaluated the immune characteristics of FERMT2 within TME. Furthermore, we determined the expression levels of FERMT2 in various cell types within TME, based on single-cell sequencing data. To confirm the co-expression of FERMT2 and markers of cancer-associated fibroblasts (CAFs), we performed multiplex immunofluorescence staining on tissue paraffin sections across various cancer types. Our analysis disclosed a significant correlation between elevated FERMT2 expression and unfavorable prognosis in specific cancer types. Furthermore, we identified a strong correlation between FERMT2 expression and diverse immune-related factors, including immune checkpoint molecules, immune cell infiltration, microsatellite instability (MSI), and tumor mutational burden (TMB). Additionally, there was a significant correlation between FERMT2 expression and immune-related pathways, particularly those associated with activating, migrating, and promoting the growth of fibroblasts in diverse cancer types. Interestingly, we observed consistent co-expression of FERMT2 in both malignant tumor cells and stromal cells, particularly within CAFs. Notably, our findings also indicated that FERMT2, in particular, exhibited elevated expression levels within tumor tissues and co-expressed with α-SMA in CAFs based on the multiplex immunofluorescence staining results.

Comprehensive analysis of ETS1 expression and its prognostic value in clear cell renal cell carcinoma.

BACKGROUND: ETS1, a member of the large ETS domain family of transcription factors, plays a role in the progression of many types of carcinoma. ETS1 expression has been linked to a more favorable prognosis in renal cell carcinoma. The objective of this study was to assess the predictive significance of ETS1 in individuals suffering from clear cell renal cell carcinoma (ccRCC). METHODS: The correlation between ETS1 expression and ccRCC was analyzed. Data on ETS1 and clinical information for ccRCC patients were obtained from the Cancer Genome Atlas database and analyzed using R software. Then, we presented validation results using RT-qPCR (quantitative reverse transcription PCR). The receiver operator characteristic (ROC) curves were generated using the pROC software package to determine the cutoff values for ETS1. Additionally, the ImmuneScore, StromalScore, and ESTIMATEScore were calculated using the ESTIMATES algorithm. The connection between ccRCC and ETS1 was investigated using enrichment analysis based on Gene Oncology and the Kyoto Encyclopedia of Genes and Genomes. The tumor immunity estimation resource (TIMER) and the integrated repository portal for tumor-immune system interactions (TISIDB) databases were utilized to analyze the association between ETS1 expression and immune cell infiltration in ccRCC. The impact of ETS1 on the survival of ccRCC patients was evaluated using the PrognoScan database. We evaluated the Tumor Mutation Burden (TMB) value between the two sets of samples with high and low ETS1 expression, as well as the differences in gene mutations between the two groups. RESULTS: The mRNA expression of ETS1 in ccRCC was higher compared to normal tissues. Results showed a significant positive correlation between elevated ETS1 expression levels and improved overall survival (OS), disease-specific survival (DSS), and progression-free survival (PFS), with a P < 0.05. Furthermore, high ETS1 expression levels were closely linked to early tumor stage and prolonged survival time. TMB in the ETS1-high expression group was significantly less than that in the ETS1-low expression group. CONCLUSIONS: Downregulation of ETS1 expression correlated with poor prognosis and immune infiltration in ccRCC, further suggesting that ETS1 may be a biomarker for better prognosis in ccRCC patients.

A super-hydrophilic graphite directly from lignin enabled by a room-temperature cascade catalytic carbonization.

A cost-effective, and low-energy room-temperature cascade catalytic carbonization strategy is demonstrated for converting lignin into graphite with a high yield of 87 %, a high surface potential of -37 eV and super-hydrophilicity. This super-hydrophilic feature endows the lignin-derived graphite to be dispersed in a variety of polar solvents, which is important for its future applications. Encapsulating of liquid metals with the graphite for electrical circuit patterning on flexible substrates is also advocated. These written patterns show superb conductivity of 4.9 × 106 S/m, offering good performance stability and reliability while being repeatedly stretched, folded, twisted, and bent. This will offer new designs for flexible electronic devices, sensors, and biomedical devices.