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Low tumor immunogenicity, immunosuppressive tumor microenvironment, and bacterial infections have emerged as significant challenges in postsurgical immunotherapy and skin regeneration for preventing melanoma recurrence. Herein, an immunotherapeutic hydrogel booster (GelMA-CJCNPs) was developed to prevent postoperative tumor recurrence and promote wound healing by incorporating ternary carrier-free nanoparticles (CJCNPs) containing chlorine e6 (Ce6), a BRD4 inhibitor (JQ1), and a glutaminase inhibitor (C968) into methacrylic anhydride-modified gelatin (GelMA) dressings. GelMA-CJCNPs reduced glutathione production by inhibiting glutamine metabolism, thereby preventing the destruction of reactive oxygen species generated by photodynamic therapy, which could amplify oxidative stress to induce severe cell death and enhance immunogenic cell death. In addition, GelMA-CJCNPs reduced M2-type tumor-associated macrophage polarization by blocking glutamine metabolism to reverse the immunosuppressive tumor microenvironment, recruiting more tumor-infiltrating T lymphocytes. GelMA-CJCNPs also downregulated IFN-γ-induced expression of programmed cell death ligand 1 to mitigate acquired immune resistance. Benefiting from the amplified systemic antitumor immunity, GelMA-CJCNPs markedly inhibited the growth of both primary and distant tumors. Moreover, GelMA-CJCNPs demonstrated satisfactory photodynamic antibacterial effects against Staphylococcus aureus infections, thereby promoting postsurgical wound healing. Hence, this immunotherapeutic hydrogel booster, as a facile and effective postoperative adjuvant, possesses a promising potential for inhibiting tumor recurrence and accelerating skin regeneration.

Abstract Background In hepatocellular carcinoma (HCC) treatment, first-line targeted therapy in combination with immune checkpoint inhibitors (ICIs) has improved patient prognosis, but the 5-year survival rate is far from satisfactory. Studies have shown that the extracellular matrix (ECM) is an essential part of the tumour microenvironment (TME) and participates in the progression of malignant tumours. ECM remodelling can enhance matrix stiffness in cirrhosis patients, induce an immunosuppressive microenvironment network, and affect the efficacy of targeted therapies and ICIs for treating HCC. However, the exact mechanism is still unclear. Methods We downloaded data from public databases, selected differentially expressed ECM proteins associated with matrix stiffness, constructed and validated a prognostic model of HCC using Lasso Cox regression, and investigated the roles and mechanism of one of the ECM proteins, dynein light chain LC8-type 1 (DYNLL1), in HCC proliferation, migration, and apoptosis via in vitro experiments. Results In this study, the risk score of the matrix stiffness-related ECM protein model effectively predicted the prognosis of HCC patients. The high- and low-risk subgroups of the model also showed differences in immune cells, immune functions, and drug sensitivity. DYNLL1 promoted HCC cell progression and migration and inhibited HCC cell apoptosis through the Wnt/β-catenin pathway in vitro. Conclusion The expression of matrix stiffness-related ECM proteins could be an independent predictor of HCC prognosis. DYNLL1, an oncogenic gene in HCC, has the potential to be a new target for HCC treatment.

Aims To validate the hypothesis that hepatic vein ligation (HVL) alone may produce similar results to liver venous deprivation (LVD or HVL + portal vein ligation [PVL]). Methods Rats were assigned to five groups, namely, the control group; the R group in which the right median hepatic vein (RMHV) was ligated; the M group in which the middle median hepatic vein (MMHV) was ligated; the RM group in which both the RMHV and MMHV were ligated (R + MMHVL, extended ligation of the hepatic veins); and the LVD group in which both the right median portal vein and the RMHV were ligated. The liver hypertrophy effect and liver enzymes were determined. Methylene blue staining and retrograde pressurized perfusion assays were performed to investigate the hemodynamic changes. Results The RM and LVD groups exhibited similar significant hypertrophy in the future liver remnants when compared to that of the control group, and almost no additional hypertrophy effect was observed in the R and M groups. There was a remarkable elevation in serum transaminase levels in both groups. The methylene blue staining experiment indicated that pressure-dependent collaterals formed between the contiguous drainage areas, and the R + MMHVL procedure blocked the outflow of the right median lobe. Conclusion Extended ligation of the hepatic vein (R + MMHVL) resulted in a similar hypertrophy effect and hepatic damage to those of LVD (HVL + PVL) treatment in a rat model, and intrahepatic venovenous collaterals play key roles.

Abstract Tubulin alpha-1c chain (TUBA1C), a subtype of α-tubulin, has been shown to be involved in cell proliferation and cell cycle progression in several cancers and to influence cancer development and prognosis. However, a pancancer analysis of TUBA1C to reveal its immunological and prognostic roles has not been performed. In this study, we first downloaded raw data on TUBA1C expression in cancers from The Cancer Genome Atlas (TCGA) database and multiple other databases and analysed these data with R software to investigate the prognostic and immunological value of TUBA1C in cancers. Immunohistochemical analysis was performed in gliomas to further validate our findings. Overall, TUBA1C was overexpressed in most cancers, and overexpression of TUBA1C was linked to poor prognosis and higher tumour grade in patients. In addition, TUBA1C expression was associated with tumour mutation burden (TMB), microsatellite instability (MSI), the tumour microenvironment (TME) and the infiltration of immune cells. TUBA1C was also coexpressed with most immune-related genes and influenced immune-related pathways. Immunohistochemical analysis showed that TUBA1C expression was highest in glioblastoma (GBM) tissues, second highest in low-grade glioma (LGG) tissues and lowest in normal tissues. Our study indicated that TUBA1C might be a biomarker for predicting the immune status and prognosis of cancers, offering new ideas for cancer treatment.

MAX dimerization protein 3 (MXD3), a transcriptional regulator of the MXD3 superfamily, is a part of the MYC–MAX–MXD network. However, its role in tumors has been reported in several cancers, such as B-cell acute lymphoblastic leukemia, medulloblastoma, neuroblastoma, and glioblastoma. Based on TCGA and GEO data, our first pancancer study of MXD3 confirmed the high expression of MXD3 in cancer tissues. Our results revealed that patients suffering from cancers with higher MXD3 expression had poor OS, DSS, DFI, and PFI. We further explored the methylation status of the MXD3 gene body and gene promoter in cancer. Patients with a higher MXD3 gene body have better OS, while the prognosis of patients with a high MXD3 promoter is more complex. We also verified the differential expression of three clinical phenotypes of MXD3: age, sex, and tumor stage, in a variety of tumors, suggesting a correlation between MXD3 and clinical characteristics. We explored the negative relationship between MXD3 and TMB and MSI in most types of cancer, indicating the poor prognosis of patients with high MXD3 expression. We further investigated the relationship between MXD3 and immune infiltrating cells and identified the relationship between MXD3 and immune genes, immunosuppressive genes, and antigen-presenting genes. All of the above findings established a solid relationship between MXD3 and the immune environment and immune cells. These results demonstrated that MXD3 might also be a potential immune factor. We also found a higher expression of MXD3 and promoter according to the increasing glioma WHO grade or histologic types. Glioma patients with high MXD3 or MXD3 promoter expression had poor survival. Finally, we used IHC to verify the higher expression of MXD3 in glioma samples compared to normal samples. Our study shows that MXD3, as a poor prognostic factor, plays a significant role in many cancers, especially glioma. Although more clinical evidence for MXD3 as a clinical therapeutic target and an immunotherapy site is needed, MXD3 can play an important guiding role in multiple clinical treatments, including immunotherapy and demethylation therapy.

Recently, N6-methyladenosine (m6A) RNA methylation in eukaryotic mRNA has become increasingly obvious in the pathogenesis and prognosis of cancer. Moreover, tumor microenvironment is involved in the regulation of tumorigenesis. In our research, the clinical data, including 374 tumor and 50 normal patients, were obtained from The Cancer Genome Atlas (TCGA). Then 19 m6A regulators were selected from other studies. Hepatocellular carcinoma (HCC) patients were clustered in cluster1/2, according to the consensus clustering for the m6A RNA regulators. We found that m6A regulators were upregulated in cluster1. The cluster1 was associated with higher programmed death ligand 1 (PD-L1) expression level, higher immunoscore, worse prognosis, and distinct immune cell infiltration compared with cluster2. Five risk signatures were identified, including YTH N6-methyladenosine RNA-binding protein 1, YTHDF2, heterogeneous nuclear ribonucleoprotein C, WT1-associated protein, and methyltransferase-like 3, based on univariate Cox and least absolute shrinkage and selection operator regression analysis. High-risk group and low-risk group HCC patients were selected based on the risk score. Similarly, the high-risk group was extremely associated with higher PD-L1 expression level, higher grade, and worse overall survival (OS). Also, cluster1 was mainly enriched in high-risk group. Receiver operating characteristic (ROC) and a nomogram were used to predict the ability and the probability of 3- and 5-year OS of HCC patients. The time-dependent ROC curve (AUC) reached 0.77, 0.67, and 0.68 at 1, 3, and 5 years in the training dataset. Also, AUC areas of 1, 3, and 5 years were 0.7, 0.63, and 0.55 in the validation dataset. The gene set enrichment analysis showed that MTOR signaling pathway and WNT signaling pathway were correlated with cluster1 and high-risk group. Collectively, the research showed that the m6A regulators were significantly associated with tumor immune microenvironment in HCC. Risk characteristics based on m6A regulators may predict prognosis in patients with HCC and provide a new therapeutic target for improving the efficacy of immunotherapy.

Tubulin alpha 1b (TUBA1B) is an important microtubule isoform that is involved in the formation of the cytoskeleton. The objective of our study was to explore the potential of TUBA1B in predicting the prognosis of HCC and patients’ response to immunotherapy. Raw data was extracted from TCGA and GEO databases, and then HCCDB, TIMER, HPA, and GEPIA websites, as well as R software, were used to perform bioinformatics analysis to investigate the potential of TUBA1B as a prognostic and immunotherapeutic marker for hepatocellular carcinoma (HCC). We found that both TUBA1B mRNA and protein were highly expressed in HCC. TUBA1B was proved to be an independent prognostic predictor of HCC. Additionally, TUBA1B expression was associated with the infiltration of several immune cells in HCC. Moreover, TUBA1B was coexpressed with immune-related genes and immune checkpoints. Patients expressing high TUBA1B responded better to immune checkpoint inhibitor (ICI) therapy. GO and KEGG analyses revealed that TUBA1B may be involved in the processes of cell cycle, spliceosome, and DNA replication. In conclusion, TUBA1B is expected to be a prognostic and immunotherapeutic marker for HCC.

Abstract Liver cancer remains one of the most prevalent malignancies worldwide with high incidence and mortality rates. Due to its subtle onset, liver cancer is commonly diagnosed at a late stage when surgical interventions are no longer feasible. This situation highlights the critical role of systemic treatments, including targeted therapies, in bettering patient outcomes. Despite numerous studies on the mechanisms underlying liver cancer, tyrosine kinase inhibitors (TKIs) are the only widely used clinical inhibitors, represented by sorafenib, whose clinical application is greatly limited by the phenomenon of drug resistance. Here we show an in-depth discussion of the signaling pathways frequently implicated in liver cancer pathogenesis and the inhibitors targeting these pathways under investigation or already in use in the management of advanced liver cancer. We elucidate the oncogenic roles of these pathways in liver cancer especially hepatocellular carcinoma (HCC), as well as the current state of research on inhibitors respectively. Given that TKIs represent the sole class of targeted therapeutics for liver cancer employed in clinical practice, we have particularly focused on TKIs and the mechanisms of the commonly encountered phenomena of its resistance during HCC treatment. This necessitates the imperative development of innovative targeted strategies and the urgency of overcoming the existing limitations. This review endeavors to shed light on the utilization of targeted therapy in advanced liver cancer, with a vision to improve the unsatisfactory prognostic outlook for those patients.

Although recent data-driven Underwater Acoustic Target Recognition (UATR) methods have played a dominant role in marine acoustics, they suffer from complex ocean environments and rather small datasets. To tackle such challenges, researchers have resorted to transfer learning in an effort to fulfill UATR tasks. However, existing pre-trained models are trained on audio speech data, and are not suitable for underwater acoustic data. Therefore, it is necessary to make further optimization on the basis of these models to make them suitable for the UATR task. Here, we propose a novel UATR framework called Attention Layer Supplement Integration (ALSI), which integrates large pre-trained neural networks with customized attention modules for acoustic. Specifically, the ALSI model consists of two important modules, namely Scale ResNet and Residual Hybrid Attention Fusion (RHAF). First, the Scale ResNet module takes the Constant-Q transform feature as input to obtain relatively important frequency information. Next, RHAF takes the temporal feature extracted by wav2vec 2.0 and the frequency feature extracted by Scale ResNet as input and aims to better integrate the time–frequency features with the temporal feature by using the attention mechanism. The RHAF module can help wav2vec 2.0, which is trained on speech data, to better adapt to underwater acoustic data. Finally, the experiments on the ShipsEar dataset demonstrated that our model can achieve recognition accuracy of 96.39%. In conclusion, extensive experiments confirm the effectiveness of our model on the UATR task.

Underwater Acoustic Target Recognition (UATR) plays a crucial role in underwater detection devices. However, due to the difficulty and high cost of collecting data in the underwater environment, UATR still faces the problem of small datasets. Few-shot learning (FSL) addresses this challenge through techniques such as Siamese networks and prototypical networks. However, it also suffers from the issue of overfitting, which leads to catastrophic forgetting and performance degradation. Current underwater FSL methods primarily focus on mining similar information within sample pairs, ignoring the unique features of ship radiation noise. This study proposes a novel cross-domain contrastive learning-based few-shot (CDCF) method for UATR to alleviate overfitting issues. This approach leverages self-supervised training on both source and target domains to facilitate rapid adaptation to the target domain. Additionally, a base contrastive module is introduced. Positive and negative sample pairs are generated through data augmentation, and the similarity in the corresponding frequency bands of feature embedding is utilized to learn fine-grained features of ship radiation noise, thereby expanding the scope of knowledge in the source domain. We evaluate the performance of CDCF in diverse scenarios on ShipsEar and DeepShip datasets. The experimental results indicate that in cross-domain environments, the model achieves accuracy rates of 56.71%, 73.02%, and 76.93% for 1-shot, 3-shot, and 5-shot scenarios, respectively, outperforming other FSL methods. Moreover, the model demonstrates outstanding performance in noisy environments.

PURPOSE: To compare the corneal biomechanical properties before and after small incision lenticule extraction (SMILE) and femtosecond laser-assisted LASIK in different levels of myopia with the Ocular Response Analyzer (Reichert Ophthalmic Instruments, Depew, NY). METHODS: A total of 187 and 79 eyes that received SMILE or LASIK, respectively, between January and June 2013 at Zhongshan Ophthalmic Center were enrolled in this study. Patients were grouped according to surgery type (SMILE or LASIK) and -6.00 diopters (D) or less (≤ -6.00 D) or myopia greater than -6.00 D (> -6.00 D). Corneal hysteresis, corneal resistance factor, and 37 waveform parameters were recorded and compared preoperatively and at 1 week and 1 and 3 months post-operatively. RESULTS: There was a significant decrease of cor-neal hysteresis, corneal resistance factor, p1area, and p2area, and an increase of path1 and path2 in both SMILE and LASIK. In myopia -6.00 D or less, the differences between SMILE and LASIK were not significant (P > .05), but in myopia greater than -6.00 D, the cor-neal hysteresis, corneal resistance factor, p1area, and p2area decreased significantly more in LASIK than in SMILE (P < .05). CONCLUSIONS: When comparing SMILE with LASIK, myopia was greater than -6.00 D, and the corneal hysteresis, corneal resistance factor, p1area, and p2area decrease was less after SMILE. [ABSTRACT FROM AUTHOR]

Al-5Ti-C master alloy was prepared and used to modify hypereutectic Al-20%Si alloy. The microstructure evolution and mechanical properties of hypereutectic Al-20%Si alloy with Al-5Ti-C master alloy additions (0, 0.4, 0.6, 1.0, 1.6 and 2.0 wt%) were investigated. The results show that, Al-5Ti-C master alloy (0.6 wt%, 10 min) can significantly refine both eutectic and primary Si of hypereutectic Al-20%Si alloy. The morphology of the primary Si crystals was significantly refined from a coarse polygonal and star-like shape to a fine polyhedral shape and the grain size of the primary Si was refined from roughly 90-120 μm to 20-50 μm. The eutectic Si phases were modified from a coarse platelet-like/needle-like structure to a fine fibrous structure with discrete particles. The Al-5Ti-C master alloy (0.6 wt%, 30 min) still has a good refinement effect. The ultimate tensile strength (UTS), elongation (El) and Brinell hardness (HB) of Al-20%Si alloy modified by the Al-5Ti-C master alloy (0.6 wt%, 10 min) increased by roughly 65%, 70% and 51%, respectively, due to decreasing the size and changing the morphology on the primary and eutectic Si crystals. The change in mechanical properties corresponds to evolution of the microstructure. [ABSTRACT FROM AUTHOR]

The article discusses the development of an inhaled delivery system, iSEND, using nanovesicles loaded with dexamethasone (DEX) to attenuate the cytokine storm in COVID-19 disease. Inhalation of nanoDEX showed improved anti-inflammatory effects with a lower dose compared to intravenous administration, presenting a safe and effective treatment platform for COVID-19.