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Abstract Background Tumor-associated macrophages (TAMs) constitute a substantial part of human hepatocellular carcinoma (HCC). The present study was devised to explore TAM diversity and their roles in HCC progression. Methods Through the integration of multiple 10 × single-cell transcriptomic data derived from HCC samples and the use of consensus nonnegative matrix factorization (an unsupervised clustering algorithm), TAM molecular subtypes and expression programs were evaluated in detail. The roles played by these TAM subtypes in HCC were further probed through pseudotime, enrichment, and intercellular communication analyses. Lastly, vitro experiments were performed to validate the relationship between CD63, which is an inflammatory TAM expression program marker, and tumor cell lines. Results We found that the inflammatory expression program in TAMs had a more obvious interaction with HCC cells, and CD63, as a marker gene of the inflammatory expression program, was associated with poor prognosis of HCC patients. Both bulk RNA-seq and vitro experiments confirmed that higher TAM CD63 expression was associated with the growth of HCC cells as well as their epithelial-mesenchymal transition, metastasis, invasion, and the reprogramming of lipid metabolism. Conclusions These analyses revealed that the TAM inflammatory expression program in HCC is closely associated with malignant tumor cells, with the hub gene CD63 thus representing an ideal target for therapeutic intervention in this cancer type.

ABSTRACTThe training of image captioning (IC) models requires a large number of caption-labeled samples, which is usually difficult to satisfy in the actual remote sensing scenarios. The performance of the models will be damaged due to the few-shot problems. We describe the few-shot problems in remote sensing image captioning (RC) and design two research schemes. Then, we propose a few-shot RC framework few-shot remote sensing image captioning framework (FRIC). FRIC does not need additional samples and uses a simple base model. FRIC tries to get performance boosts from split samples and reduce the negative effects of noises. Unlike previous works that use 100% samples to simulate few-shot scenarios, FRIC uses less than 1.0% data to simulate actual few-shot scenarios. While previous works focus on improving the encoder, FRIC focuses on optimizing the decoder with parameter ensemble, multi-model ensemble and self-distillation. FRIC can train a simple base model with limited caption-labeled samples to generate captions that meet human expectations. FRIC shows obvious advantages to other methods when trained with only 0.8% samples of RC datasets. No previous work has used such a small amount of data to train the RC model. In addition, the effectiveness of the components in FRIC is verified with ablation experiments.

Abstract Background Cholangiocarcinoma (CCA) is a biliary epithelial malignant tumor with an increasing incidence worldwide. Therefore, further understanding of the molecular mechanisms of CCA progression is required to identify new therapeutic targets. Methods The expression of RPL35A in CCA and para-carcinoma tissues was detected by immunohistochemical staining. IP-MS combined with Co-IP identified downstream proteins regulated by RPL35A. Western blot and Co-IP of CHX or MG-132 treated CCA cells were used to verify the regulation of HSPA8 protein by RPL35A. Cell experiments and subcutaneous tumorigenesis experiments in nude mice were performed to evaluate the effects of RPL35A and HSPA8 on the proliferation, apoptosis, cell cycle, migration of CCA cells and tumor growth in vivo. Results RPL35A was significantly upregulated in CCA tissues and cells. RPL35A knockdown inhibited the proliferation and migration of HCCC-9810 and HUCCT1 cells, induced apoptosis, and arrested the cell cycle in G1 phase. HSPA8 was a downstream protein of RPL35A and overexpressed in CCA. RPL35A knockdown impaired HSPA8 protein stability and increased HSPA8 protein ubiquitination levels. RPL35A overexpression promoted CCA cell proliferation and migration. HSPA8 knockdown inhibited CCA cell proliferation and migration, and reversed the promoting effect of RPL35A. Furthermore, RPL35A promoted tumor growth in vivo. In contrast, HSPA8 knockdown suppressed tumor growth, while was able to restore the effects of RPL35A overexpression. Conclusion RPL35A was upregulated in CCA tissues and promoted the progression of CCA by mediating HSPA8 ubiquitination.

Extrachromosomal DNA (ecDNA) is a self-replicating circular DNA originating from the chromosomal genome and exists outside the chromosome. It contains specific gene sequences and non-coding regions that regulate transcription. Recent studies have demonstrated that ecDNA is present in various malignant tumors. Malignant tumor development and poor prognosis may depend on ecDNA's distinctive ring structure, which assists in amplifying oncogenes. During cell division, an uneven distribution of ecDNA significantly enhances tumor cells' heterogeneity, allowing tumor cells to adapt to changes in the tumor microenvironment and making them more resistant to treatments. The application of ecDNA as a cancer biomarker and therapeutic target holds great potential. This article examines the latest advancements in this area and discusses the potential clinical applications of ecDNA.

Abstract Background New oral anticoagulants (NOACs) have been becoming prevalent in recent years and are increasingly used in the treatment of port vein thrombosis. The difference of the efficacy and safety between rivaroxaban and dabigatran remains unclear in the treatment of cirrhotic patients with acute portal vein thrombosis (PVT). Methods This retrospective study included all consecutive cirrhotic patients with acute portal vein thrombosis in our institute from January 2020 to December 2021. The patients received oral anticoagulation with rivaroxaban or dabigatran. The demographic, clinical, and imaging data of patients were collected. The diagnosis of acute PVT was confirmed by imaging examinations. The severity of liver cirrhosis was assessed using Child–Pugh score and Model for End-Stage Liver Disease (MELD) score. Outcomes included recanalization (complete, partial, and persistent occlusion), liver function, bleedings, and survival. The log-rank test was used to compare Kaplan–Meier distributions of time-to-event outcomes. The Cox proportional hazards model was used to calculate hazard ratios (HRs) with 95% confidence intervals (CIs). Results A total of 94 patients were included, 52 patients (55%) received rivaroxaban and 42 (45%) with dabigatran. The complete and partial recanalization of PVT was observed in 41 patients. There was no significant difference in complete recanalization, partial recanalization, and persistent occlusion between the two groups. With multivariate analysis, D-dimer (HR 1.165, 95% CI 1.036–1.311, p = 0.011) was independent predictors of complete recanalization. The Child–Pugh score (p = 0.001) was significantly improved in both two groups after anticoagulation, respectively. However, there was no difference between the two groups. The probability of survival was 94%, 95% in the rivaroxaban and dabigatran groups (log-rank p = 0.830). Major bleedings were reported in 3 patients (6%) in rivaroxaban group and 1 patient (2%) in dabigatran group (p = 0.646). Six patients (12%) in rivaroxaban group experienced minor bleeding, and five (12%) from dabigatran group (p = 0.691). Conclusions The efficacy and safety were comparable between rivaroxaban and dabigatran in the treatment of cirrhotic patients with acute portal vein thrombosis. And D-dimer can contribute to the prediction of PVT recanalization in cirrhotic patients.

Objective: The aim of our study was to investigate whether the Dietary Inflammatory Index (DII) correlated with gout in American adults. Method: The study used data from the 2007–2018 National Health and Nutrition Examination Survey, with 27,710 adults participating. Initially, multivariable analysis was performed, with controls for covariates, to assess the link of DII and gout. Then, restricted cubic splines (RCS) were applied to model the nonlinear relationship of DII and gout. Furthermore, propensity score matching (PSM) as a further study of potential relationships was established. Eventually, subgroup analysis was performed. Result: Participants within the highest DII quartile would be more susceptible to increased risk of gout in the univariate regression model (Q4 vs. Q1, OR = 1.31, CI: 1.05–1.63). Additionally, a positive correlation was detected between gout risk and DII after adjusting on drinking, smoking, gender, race, age, and BMI. Based on RCS analysis, we observed that the risk of gout raised sharply as DII values increased, then flattened, and increased sharply again when the DII was greater than approximately 2.5. After performing the PSM, it was observed that DII correlated in a positive way to the presence of gout on a fully adjusted multivariable model. Subgroup analysis revealed that the link of DII and gout showed no statistical significance in females, blacks, Mexicans, nor in the population that smoked. Conclusion: Greater degrees of pro-inflammation correlate with a higher risk of gout and might be a predisposing factor for gout. Hence, tactics fostering an anti-inflammatory diet for preventing and improving gout in adults should be regarded.

Papillary renal cell carcinoma (PRCC) is a malignant neoplasm of the kidney and is highly interesting due to its increasing incidence. Many studies have shown that the basement membrane (BM) plays an important role in the development of cancer, and structural and functional changes in the BM can be observed in most renal lesions. However, the role of BM in the malignant progression of PRCC and its impact on prognosis has not been fully studied. Therefore, this study aimed to explore the functional and prognostic value of basement membrane-associated genes (BMs) in PRCC patients. We identified differentially expressed BMs between PRCC tumor samples and normal tissue and systematically explored the relevance of BMs to immune infiltration. Moreover, we constructed a risk signature based on these differentially expressed genes (DEGs) using Lasso regression analysis and demonstrated their independence using Cox regression analysis. Finally, we predicted 9 small molecule drugs with the potential to treat PRCC and compared the differences in sensitivity to commonly used chemotherapeutic agents between high and low-risk groups to better target patients for more precise treatment planning. Taken together, our study suggested that BMs might play a crucial role in the development of PRCC, and these results might provide new insights into the treatment of PRCC.

Abstract Background Cell division cycle‐associated 8 (CDCA8) is involved in numerous signaling networks, and it serves a crucial modulatory function in multiple malignant tumors. However, its significance in prognosis and immune infiltration in hepatocellular carcinoma (HCC) remains unclear. Materials and methods Herein, we examined the CDCA8 levels in tumor tissues, as well as its associated signaling pathways and correlation with immune infiltration. Additionally, we further clarified the prognostic significance of CDCA8 among HCC patients. HCC patient information was recruited from The Cancer Genome Atlas (TCGA). Using bioinformatics, the following parameters were analyzed among HCC patients: CDCA8 expression, enrichment analysis, immune infiltration, and prognosis analysis. Moreover, we employed in vitro investigations, such as, qRT‐PCR, immunohistochemistry (IHC), and cell functional experiments to validate our results. Results Elevated CDCA8 expression in HCC patients was markedly associated with T stage, pathological status (PS), tumor status (TS), histologic grade (HG), and AFP. Elevated CDCA8 expression HCC patients exhibited reduced overall survival (OS) (p

Background: Sepsis induces GAS5 expression in the vascular endothelium, but the molecular mechanism is unclear, as is the role of GAS5 in sepsis. Methods and results: We observed that GAS5 expression in the endothelium was significantly upregulated in a sepsis mouse model. ChIP-PCR and EMSA confirmed that the oxidative stress (OS)-activated MiT–TFE transcription factor (MITF, TFE3, and TFEB)-mediated GAS5 transcription. In vitro, GAS5 overexpression attenuated OS and inflammation in endothelial cells (ECs) while maintaining the structural and functional integrity of mitochondria. In vivo, GAS5 reduced tissue ROS levels, maintained vascular barrier function to reduce leakage, and ultimately attenuated sepsis-induced lung injury. Luciferase reporter assays revealed that GAS5 protected MITF from degradation by sponging miR-23, thereby forming a positive feedback loop consisting of MITF, GAS5, and miR-23. Despite the fact that the OS-activated MITF–GAS5–miR-23 loop boosted MITF-mediated p62 transcription, ECs do not need to increase mitophagy to exert mitochondrial quality control since MITF-mediated Nrf2 transcription exists. Compared to mitophagy, MITF-transcribed p62 prefers to facilitate the autophagic degradation of Keap1 through a direct interaction, thereby relieving the inhibition of Nrf2 by Keap1, indicating that MITF can upregulate Nrf2 at both the transcriptional and posttranscriptional levels. Following this, ChIP-PCR demonstrated that Nrf2 can also transcribe MITF, revealing that there is a reciprocal positive regulatory association between MITF and Nrf2. Conclusion: In sepsis, the ROS-activated MITF–GAS5–miR-23 loop integrated the antioxidant and autophagy systems through MITF-mediated transcription of Nrf2 and p62, which dynamically regulate the level and type of autophagy, as well as exert antioxidant and anti-inflammatory effects.

The chemical processes for the selective incorporation of deuterium into small molecules, of interest to organic and medicinal chemistry, are well established, while the enzymatic methods remain underdeveloped. Here, the authors use an enzymatic approach employing Chlorella variabilis NC64A photodecarboxylase that catalyses decarboxylative deuteration of various carboxylic acids with D2O, and identify enzyme variants that can employ substrates with different chain length acids.

BackgroundMacrolides have been widely used to treat moderate-to-severe acne for more than 50 years. However, the prevalent antibiotic resistance of Propionibacterium acnes, along with the absence of clinically available resistance tests, has made macrolide misuse a frequent occurrence around the globe, with serious consequences.ObjectiveWe developed Cutibacterium acnes quantitative PCR (qPCR)-based antibiotics resistance assay (ACQUIRE) to enable fast and accurate detection of C. acnes macrolide resistance in clinical settings, representing an opportunity to administer antibiotics more wisely and improve the quality of care.MethodsA cross-sectional observational study (n = 915) was conducted to probe into the macrolide resistance of C. acnes in patients with acne.ResultsThe high sensitivity of ACQUIRE enabled us to reveal a much higher C. acnes 23S recombinant DNA (rDNA) point mutation rate (52%) and thus a higher macrolide resistance (75.5%) compared to previous reports. Carriage of ermX gene was discovered on 472 (53%) subjects, which concurs with previous studies.ConclusionThe macrolide resistance of C. acnes is much higher than previously reported. Integrating ACQUIRE into acne treatment modalities may eliminate macrolide misuse and achieve better clinical improvements.

Large-scale caption-labeled remote sensing image samples are expensive to acquire, and the training samples available in practical application scenarios are generally limited. Therefore, remote sensing image caption generation tasks will inevitably fall into the dilemma of few-shot, resulting in poor qualities of the generated text descriptions. In this study, we propose a self-learning method named SFRC for few-shot remote sensing image captioning. Without relying on additional labeled samples and external knowledge, SFRC improves the performance in few-shot scenarios by ameliorating the way and efficiency of the method of learning on limited data. We first train an encoder for semantic feature extraction using a supplemental modified BYOL self-supervised learning method on a small number of unlabeled remote sensing samples, where the unlabeled remote sensing samples are derived from caption-labeled samples. When training the model for caption generation in a small number of caption-labeled remote sensing samples, the self-ensemble yields a parameter-averaging teacher model based on the integration of intermediate morphologies of the model over a certain training time horizon. The self-distillation uses the self-ensemble-obtained teacher model to generate pseudo labels to guide the student model in the next generation to achieve better performance. Additionally, when optimizing the model by parameter back-propagation, we design a baseline incorporating self-critical self-ensemble to reduce the variance during gradient computation and weaken the effect of overfitting. In a range of experiments only using limited caption-labeled samples, the performance evaluation metric scores of SFRC exceed those of recent methods. We conduct percentage sampling few-shot experiments to test the performance of the SFRC method in few-shot remote sensing image captioning with fewer samples. We also conduct ablation experiments on key designs in SFRC. The results of the ablation experiments prove that these self-learning designs we generated for captioning in sparse remote sensing sample scenarios are indeed fruitful, and each design contributes to the performance of the SFRC method.

As microtubule-based structures, primary cilia are typically present on the cells during the G0 or G1-S/G2 phase of the cell cycle and are closely related to the development of the central nervous system. The presence or absence of this special organelle may regulate the central nervous system tumorigenesis (e.g., glioblastoma) and several degenerative diseases. Additionally, the development of primary cilia can be regulated by several pathways. Conversely, primary cilia are able to regulate a few signaling transduction pathways. Therefore, development of the central nervous system tumors in conjunction with abnormal cilia can be regulated by up- or downregulation of the pathways related to cilia and ciliogenesis. Here, we review some pathways related to ciliogenesis and tumorigenesis, aiming to provide a potential target for developing new therapies at genetic and molecular levels.

Although the means of catching remote sensing images are becoming more effective and more abundant, the samples that can be collected in some specific environments can be quite scarce. When there are limited labeled samples, the methods for analyzing remote sensing images for scene classification perform drastically worse. Methods that classify few-shot remote sensing image scenes are often based on meta-learning algorithms for the handling of sparse data. However, this research shows they will be affected by supervision collapse where features in remote sensing images that help with out-of-distribution classes are discarded, which is harmful for the generation of unseen classes and new tasks. In this work, we wish to remind readers of the existence of supervision collapse in scene classification of few-shot remote sensing images and propose a method named SSMR based on multi-layer feature contrast to overcome supervision collapse. First of all, the method makes use of the label information contained in a finite number of samples for supervision and guides self-supervised learning to train the embedding network with supervision generated by multilayer feature contrast. This can prevent features from losing intra-class variation. Intra-class variation is always useful in classifying unseen data. What is more, the multi-layer feature contrast is merged with self-distillation, and the modified self-distillation is used to encourage the embedding network to extract sufficiently general features that transfer better to unseen classes and new domains. We demonstrate that most of the existing few-shot scene classification methods suffer from supervision collapse and that SSMR overcomes supervision collapse well in the experiments on the new dataset we specially designed for examining the problem, with a 2.4–17.2% increase compared to the available methods. Furthermore, we performed a series of ablation experiments to demonstrate how effective and necessary each structure of the proposed method is and to show how different choices in training impact final performance.

Accurate and efficient detection of cell nuclei is an important step towards the development of a pathology-based Computer Aided Diagnosis. Generally, high-resolution histopathology images are very large, in the order of billion pixels, therefore nuclei detection is a highly compute intensive task, and software implementation requires a significant amount of processing time. To assist the doctors in real time, special hardware accelerators, which can reduce the processing time, are required. In this paper, we propose a Field Programmable Gate Array (FPGA) implementation of automated nuclei detection algorithm using generalized Laplacian of Gaussian filters. The experimental results show that the implemented architecture has the potential to provide a significant improvement in processing time without losing detection accuracy.

Radix Aconiti, a classic traditional Chinese medicine (TCM), has been widely used throughout China for disease treatment due to its various pharmacological activities, such as anti-inflammatory, cardiotonic, and analgesic effects. However, improper use of Radix Aconiti often generated severe acute toxicity. Currently, research on the toxic substances of Radix Aconiti is not rare. In our previous study, acute toxic biomarkers of Radix Aconiti have been found. However, few studies were available to find the relationships between these endogenous biomarkers and exogenous toxic substances. Therefore, in this study, toxic substances of Radix Aconiti have been found using UPLC-Q-TOF-MS technology. Then, we used biochemical indicators as a bridge to find the relationships between biomarkers and toxic substances of Radix Aconiti through Pearson correlation analysis and canonical correlation analysis (CCA). Finally, the CCA results showed that LysoPC(22:5) is related to 14-acetyl-talatisamine, mesaconitine, talatisamine and deoxyaconitine in varying degrees; l-acetylcarnitine is negatively correlated with deoxyaconitine and demethyl-14-acetylkaracoline; shikimic acid has a good correlation with karacoline, demethyl-14-acetylkaracoline and deoxyaconitine; and valine is correlated with talatisamine and deoxyaconitine. Research on these relationships provides an innovative way to interpret the toxic mechanism of traditional Chinese medicine, and plays a positive role in the overall study of TCM toxicity.

To explore how microRNA-29a-3p influences the differentiation of neural stem cells into neurons and to identify any potential mechanisms involved. The program TargetScan, available online was utilized to examine and make predictions about the microRNA-29a-3p located upstream that regulate doublecortin X messenger ribonucleic acid. Ultimately, microRNA-29a-3p was preferred as the main central point of the investigation. The targeting of doublecortin X gene by microRNA-29a-3p was validated by employing a dual-luciferase reporter gene system. Before subjecting to adherent differentiation, the neural stem cells were transfected with microRNA-29a-3p inhibitor, microRNA-29a-3p mimic and normal control. MicroRNA and doublecortin X messenger ribonucleic acid levels were measured through quantitative reverse transcriptionpolymerase chain reaction and doublecortin X protein levels were determined through Western blot assays. The differentiation of neuronal precursor cells was detected by doublecortin X immunofluorescence. Neuronal differentiation was detected by microtubule-associated protein 2 immunofluorescence. According to the dual-luciferase reporter gene system, miR-29a-3p targeted the doublecortin X gene; microRNA-29a-3p significantly decreased in differentiated cells for 3 d was observed, along with a significant reduction in levels of doublecortin X protein and messenger ribonucleic acid. On the other hand, a significant raise in microRNA-29a-3p in differentiated cells of microRNA-29a-3p mimic group for a period of 3 d was noticed with a significant drop in protein levels, doublecortin X messenger ribonucleic acid and doublecortin X immunofluorescence-positive neuronal precursor cells. From the microtubule-associated protein 2 immunofluorescence, it was confirmed that microRNA-29a-3p inhibitor group significantly elevated the total number of neurons, while microRNA-29a-3p mimic reduced the neurons on 7 d. Therefore, low expression of microRNA-29a-3p promote differentiation of neural stem cells into neurons via targeting doublecortin X. [ABSTRACT FROM AUTHOR]