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Background Cancer-associated fibroblasts (CAFs) have been widely reported to promote tumor angiogenesis. However, the underlying mechanisms of the proangiogenic switch of CAFs remain poorly understood. This study aims to clarify the mechanisms underlying the proangiogenic switch of CAFs. Methods NIH/3T3 cells were treated with B16 and B16F10-derived exosomes. Then the CAFs markers and proangiogenic factors were detected by RT-PCR and Western blot. CCK-8 assay, transwell migration assay, tube formation assay, and in vivo Matrigel plug assay were conducted to determine the proangiogenic capability of CAFs. Western blot and AG490 were used to investigate the role of Janus kinase 2/signal transducer and activator of transcription 3 (JAK2/STAT3) signaling pathway in the proangiogenic switch of CAFs. Bioinformatics analysis, luciferase reporter assay, microRNA mimic and inhibitor, and xenograft models were used to investigate the role of mmu-miR-155-5p (miR-155) in the proangiogenic switch of CAFs. Results In this study, we show that melanoma cell-secreted exosomes can induce reprogramming of fibroblasts into CAFs and that exosomal miR-155 can trigger the proangiogenic switch of CAFs. Mechanistically exosomal miR-155 can be delivered into fibroblasts and promote the expression of proangiogenic factors, including vascular endothelial growth factor A (VEGFa), fibroblast growth factor 2 (FGF2), and matrix metalloproteinase 9 (MMP9), by directly targetin g suppressor of cytokine signaling 1 (SOCS1) . Downregulation of SOCS1 activates JAK2/STAT3 signaling pathway and elevates the expression levels of VEGFa, FGF2, and MMP9 in fibroblasts. Treatment with exosomes containing overexpressed miR-155 can promote angiogenesis, and the reduction of miR-155 in melanoma cell-secreted exosomes alleviates angiogenesis in vitro and in vivo. Conclusions These results demonstrate that by promoting the expression of proangiogenic factors in recipient fibroblasts via SOCS1/JAK2/STAT3 signaling pathway, melanoma cell-secreted exosomal miR-155 can induce the proangiogenic switch of CAFs. Although tumor angiogenesis is modulated by various factors, exosomal miR-155 may be a potential target for controlling melanoma angiogenesis and used to set up novel strategies to treat melanoma.

Cell fusion is a highly regulated biological process that occurs under both physiological and pathological conditions. The cellular and extracellular environment is critical for the induction of the cell–cell fusion. Aberrant cell fusion is initiated during tumor progression. Tumor microenvironment is a complex dynamic system formed by the interaction between tumor cells and their surrounding cells. Cell–cell fusion mediates direct interaction between tumor cells and their surrounding cells and is associated with tumor initiation and progression. Various microenvironmental factors affect cell fusion in tumor microenvironment and generate hybrids that acquire genomes of both parental cells and exhibit novel characteristics, such as tumor stem cell-like properties, radioresistance, drug resistance, immune evasion, and enhanced migration and invasion abilities, which are closely related to the initiation, invasion, and metastasis of tumor. The phenotypic characteristics of hybrids are based on the phenotypes of parental cells, and the fusion of tumor cells with diverse types of microenvironmental fusogenic cells is concomitant with phenotypic heterogeneity. This review highlights the types of fusogenic cells in tumor microenvironment that can fuse with tumor cells and their specific significance and summarizes the various microenvironmental factors affecting tumor cell fusion. This review may be used as a reference to develop strategies for future research on tumor cell fusion and the exploration of cell fusion-based antitumor therapies.

Background Traditional preclinical teaching methods face challenges in adequately preparing oral and maxillofacial surgery (OMFS) students for the entrustable professional activities (EPA) required in their future clinical internships. This study aimed to evaluate how a 4 K live-video teaching model (LTM), integrated into a preclinical transitional course (PTC), improves students’ EPA-related performance. Methods Thirty-six fifth-year undergraduate students participated in a PTC. They were randomly divided into two groups. The control group was taught using a traditional teaching model within the PTC (direct guidance at a manikin), while the experimental group received instruction supplemented with the LTM. The module incorporated high-fidelity simulation, wherein a physician acted as a simulated patient to provide real-time verbal feedback. After the PTC, students’ competencies were comprehensively evaluated across several domains: comprehensive EPA scores (self-assessed, teacher-rated, and composite), procedural skills assessment scores, theoretical examination scores, and questionnaire-based self-evaluations and teacher evaluations of student outcomes. All assessment instruments were found to be reliable, as indicated by their ICC and Cronbach’s α values. Results The assessment instruments showed high validity. Compared to the control group, the experimental group achieved significantly higher scores in EPA self-assessment (93.05 ± 1.26 vs. 89.21 ± 1.26), teacher evaluation (88.79 ± 0.85 vs. 85.86 ± 0.85), and overall EPA performance (90.92 ± 0.91 vs. 87.54 ± 0.91) (all p  < 0.05). The experimental group also demonstrated superior procedural skill test scores (89.49 ± 0.73 vs. 79.48 ± 0.73, p  < 0.001), self-evaluations of learning (21.61 ± 1.14 vs. 13.05 ± 1.70, p  < 0.001), and teacher evaluations of their performance (21.37 ± 1.23 vs. 18.93 ± 1.31, p  < 0.001). No significant difference was found in theoretical examination scores ( p  > 0.05). Conclusion In this study, the integration of LTM into the OMFS PTC was associated with a significant enhancement in students’ foundational procedural skills, self-perceived competence, and overall performance as evaluated by faculty. These findings suggest that this teaching model can be an effective tool for improving EPA-related performance in a preclinical setting. However, given the single-center design and small sample size, further research is warranted to validate these results. This model shows potential for better preparing students for the clinical entrustment process.

To investigate the effect of luteolin on methamphetamine (MA)-induced behavioral sensitization and mitogen-activated protein kinase (MAPK) signal transduction pathway activation in mice. Mice received a single dose of MA to induce hyperactivity or repeated intermittent intraperitoneal injections of MA to establish an MA-induced behavioral sensitization mouse model. The effect of luteolin on the development and expression of MA-induced hyperactivity and behavioral sensitization was examined. The expression and activity of ΔFosB and the levels of phosphorylated extracellular signal-regulated kinase 1/2 (pERK1/2), phosphorylated c-Jun N-terminal kinase (pJNK), and phosphorylated p38 mitogen-activated protein kinase (pp38) in the caudate putamen (CPu) were measured by western blot. Luteolin significantly decreased hyperactivity as well as the development and expression of MA-induced behavioral sensitization in mice. ΔFosB, pERK1/2, and pJNK levels in the CPu were higher in MA-treated mice than in control mice, whereas the pp38 level did not change. Injection of luteolin inhibited the MA-induced increase in ΔFosB, pERK1/2, and pJNK levels, but did not affect the pp38 level. Luteolin inhibits MA-induced hyperactivity and behavioral sensitization in mice through the ERK1/2/ΔFosB pathway. Furthermore, the JNK signaling pathway might be involved in MA-induced neurodegeneration in the CPu, and luteolin inhibits this process.

The heritability of schizophrenia (SCZ) has been estimated to be as high as 80%, suggesting that genetic factors may play an important role in the etiology of SCZ. Cav1.2 encoded by CACNA1C and Cav1.3 encoded by CACNA1D are dominant calcium channel-forming subunits of L-type Voltage-dependent Ca 2+ channels, expressed in many types of neurons. The CACNA1C has been consistently found to be a risk gene for SCZ, but it is unknown for CACNA1D . To investigate the association of CACNA1D with SCZ, we designed a two-stage case-control study, including a testing set with 1117 cases and 1815 controls and a validation set with 1430 cases and 4295 controls in Han Chinese. A total of selected 97 tag single nucleotide polymorphisms (SNPs) in CACNA1D were genotyped and single-SNP association, imputation analysis and gender-specific association analyses were performed in the two independent datasets. None was found to associate with SCZ. Further genotype and haplotype association analyses indicated a similar pattern in the two-stage study. Our findings suggested CACNA1D might not be a risk gene for SCZ in Han Chinese population, which add to the current state of knowledge regarding the susceptibility of CACNA1D to SCZ.

In deep drinking water reservoir ecosystems, the dynamics and interactions of community compositions of phytoplankton and eukaryotes during the mixing periods are still unclear. Here, morphological characteristics combined with high-throughput DNA sequencing (HTS) were used to investigate the variations of phytoplankton and the eukaryotic community in a large canyon-shaped, stratified reservoir located at the Heihe River in Shaanxi Province for three months. The results showed that Bacillariophyta and Chlorophyta were the dominant taxa of the phytoplankton community, accounting for more than 97% of total phytoplankton abundance, which mainly consisted of Melosira sp., Cyclotella sp., and Chlorella sp., respectively. Illumina Miseq sequencing suggested that the biodiversity of eukaryotes increased over time and that species distribution was more even. Arthropoda (6.63% to 79.19%), Ochrophyta (5.60% to 35.16%), Ciliophora (1.81% to 10.93%) and Cryptomonadales (0.25% to 11.48%) were the keystone taxa in common, contributing over 50% of the total eukaryotic community. Cryptomycota as a unique fungus was observed to possess significant synchronization with algal density, reaching a maximum of 10.70% in December (when the algal density distinctly decreased) and suggesting that it might affect the growth of algae through parasitism. Co-occurrence network patterns revealed the complicated and diverse interactions between eukaryotes and phytoplankton, suggesting that eukaryotes respond to variations in dynamic structure of the phytoplankton community, although there might be antagonistic or mutualistic interactions between them. Redundancy analysis (RDA) results showed that environmental variables collectively explained a 96.7% variance of phytoplankton and 96.3% variance of eukaryotic microorganisms, indicating that the temporal variations of phytoplankton and eukaryotic microorganisms were significantly affected by environmental conditions. This study shows that potential interactions exist between phytoplankton and eukaryotic microorganism communities, andcould improve our understanding of the ecological roles of phytoplankton and eukaryotic microorganisms in changing aquatic ecosystems. However, long-term investigations are necessary in order to obtain comprehensive understandings of their complicated associations.

BackgroundMultifunctional hydrogels with controllable degradation and drug release have attracted extensive attention in diabetic wound healing. This study focused on the acceleration of diabetic wound healing with selenide-linked polydopamine-reinforced hybrid hydrogels with on-demand degradation and light-triggered nanozyme release.MethodsHerein, selenium-containing hybrid hydrogels, defined as DSeP@PB, were fabricated via the reinforcement of selenol-end capping polyethylene glycol (PEG) hydrogels by polydopamine nanoparticles (PDANPs) and Prussian blue nanozymes in a one-pot approach in the absence of any other chemical additive or organic solvent based on diselenide and selenide bonding-guided crosslinking, making them accessible for large-scale mass production.ResultsReinforcement by PDANPs greatly increases the mechanical properties of the hydrogels, realizing excellent injectability and flexible mechanical properties for DSeP@PB. Dynamic diselenide introduction endowed the hydrogels with on-demand degradation under reducing or oxidizing conditions and light-triggered nanozyme release. The bioactivity of Prussian blue nanozymes afforded the hydrogels with efficient antibacterial, ROS-scavenging and immunomodulatory effects, which protected cells from oxidative damage and reduced inflammation. Further animal studies indicated that DSeP@PB under red light irradiation showed the most efficient wound healing activity by stimulating angiogenesis and collagen deposition and inhibiting inflammation.ConclusionThe combined merits of DSeP@PB (on-demand degradation, light-triggered release, flexible mechanical robustness, antibacterial, ROS-scavenging and immunomodulatory capacities) enable its high potential as a new hydrogel dressing that can be harnessed for safe and efficient therapeutics for diabetic wound healing.

Pollutants often exist in tailings and surrounding areas as complex mixtures, and the resulting combined effects make it difficult to identify the primary target pollutants, particularly common inorganic anions. To address this, high-throughput 16S rRNA gene sequencing was used to characterize the microbial community structure in groundwater around rare earth tailing ponds, and multivariate statistical analyses were applied to link community patterns to specific environmental variables. A total of 14 groundwater samples were collected from seven sites (two spatial replicates per site) along a contamination gradient. The results showed distinct differences in microbial community composition between the control site and the tailing-pond-impacted sites. Nitrosomonas was the dominant genus at highly contaminated sites, while halotolerant genera such as Seohaeicola, Pusillimonas, and Oceanibaculum also showed elevated relative abundances. Redundancy analysis (RDA) with forward selection identified the co-occurring elevated concentrations of NH4+ and SO42− (originating from tailing pond leachate) as the environmental variables most strongly associated with microbial community structure (p < 0.05). In contrast, the microbial community at the control site WLJ-5, located farthest from the tailing pond, was markedly different. These findings suggest that shifts in microbial community composition and the prevalence of specific microorganisms may serve as potential bioindicators to assist in identifying the dominant contaminant types in groundwater around rare earth tailing ponds.

Polycentric planning strategies have often failed to achieve the expected effects. The ensuing uncertainty associated with the desirability of polycentric strategies is also reflected in the early literature which offers no clear conclusion about whether the polycentricity affects economic performance and how. This paper aims at offering a clear conclusion about it, especially its dependence on city size. Against this backdrop, we conceptualize polycentricity as a process of reclustering after decentralization to reevaluate its impact on performance. To this end, we use the city proper level Chinese Economic Census (2004, 2008, and 2013) and apply a fixed-effects panel model, the results of which show that the dependence of the urban economy on spatial structure is contingent on city size. More specifically, both decentralization and clustering (and therefore the polycentric structure) facilitate economic performance only when cities reach a certain size. We use our findings as the basis for outlining an emergent research agenda for urban polycentricity.

The frozen section (FS) diagnoses of pathology experts are used in China to determine whether sentinel lymph nodes of breast cancer have metastasis during operation. Direct implementation of a deep neural network (DNN) in clinical practice may be hindered by misdiagnosis of the algorithm, which affects a patient's treatment decision. In this study, we first obtained the prediction result of the commonly used patch-DNN, then we present a relative risk classification and regression tree (RRCART) to identify the misdiagnosed whole-slide images (WSIs) and recommend them to be reviewed by pathologists. Applying this framework to 2362 WSIs of breast cancer lymph node metastasis, test on frozen section results in the mean area under the curve (AUC) reached 0.9851. However, the mean misdiagnosis rate (0.0248), was significantly higher than the pathologists’ misdiagnosis rate ( p  < 0.01). The RRCART distinguished more than 80% of the WSIs as a high-accuracy group with an average accuracy reached to 0.995, but the difference with the pathologists’ performance was not significant ( p  > 0.01). However, the other low-accuracy group included most of the misdiagnoses of DNN models. Our research shows that the misdiagnosis from deep learning model can be further enriched by our method, and that the low-accuracy WSIs must be selected for pathologists to review and the high-accuracy ones may be ready for pathologists to give diagnostic reports.