FAT10 induces immune suppression by upregulating PD-L1 expression in hepatocellular carcinoma.

The upregulation of programmed death ligand 1 (PD-L1) plays a crucial role in facilitating cancer cells to evade immune surveillance through immunosuppression. However, the precise regulatory mechanisms of PD-L1 in hepatocellular carcinoma (HCC) remain undefined. The correlation between PD-L1 and ubiquitin-like molecules (UBLs) was studied using sequencing data from 20 HCC patients in our center, combined with TCGA data. Specifically, the association between FAT10 and PD-L1 was further validated at both the protein and mRNA levels in HCC tissues from our center. Subsequently, the effect of FAT10 on tumor progression and immune suppression was examined through both in vivo and in vitro experiments. Utilizing sequencing data, qPCR, and Western blotting assays, we confirmed that FAT10 was highly expressed in HCC tissues and positively correlated with PD-L1 expression. Additionally, in vitro experiments demonstrated that the overexpression of FAT10 fostered the proliferation, migration, and invasion of HCC cells. Furthermore, the overexpression of FAT10 in HCC cells led to an increase in PD-L1 expression, resulting in the inhibition of T cell proliferation and the enhancement of HCC cell resistance to T cell-mediated cytotoxicity. Moreover, in vivo experiments utilizing the C57BL/6 mouse model revealed that overexpression of FAT10 effectively suppressed the infiltration of CD8 + GZMB + and CD8 + Ki67 + T cells, as well as reduced serum levels of TNF-α and IFN-γ. Mechanistically, we further identified that FAT10 upregulates PD-L1 expression via activating the PI3K/AKT/mTOR pathway, but not in a ubiquitin-like modification. In conclusion, our findings indicate that FAT10 promotes immune evasion of HCC via upregulating PD-L1 expression, suggesting its potential as a novel target to enhance the efficiency of immunotherapy in HCC.

Identification of FOXP1 as a favorable prognostic biomarker and tumor suppressor in intrahepatic cholangiocarcinoma.

BACKGROUND: Forkhead-box protein P1 (FOXP1) has been proposed to have both oncogenic and tumor-suppressive properties, depending on tumor heterogeneity. However, the role of FOXP1 in intrahepatic cholangiocarcinoma (ICC) has not been previously reported. METHODS: Immunohistochemistry was performed to detect FOXP1 expression in ICC and normal liver tissues. The relationship between FOXP1 levels and the clinicopathological characteristics of patients with ICC was evaluated. Finally, in vitro and in vivo experiments were conducted to examine the regulatory role of FOXP1 in ICC cells. RESULTS: FOXP1 was significantly downregulated in the ICC compared to their peritumoral tissues (p < 0.01). The positive rates of FOXP1 were significantly lower in patients with poor differentiation, lymph node metastasis, invasion into surrounding organs, and advanced stages (p < 0.05). Notably, patients with FOXP1 positivity had better outcomes (overall survival) than those with FOXP1 negativity (p < 0.05), as revealed by Kaplan-Meier survival analysis. Moreover, Cox multivariate analysis showed that negative FOXP1 expression, advanced TNM stages, invasion, and lymph node metastasis were independent prognostic risk factors in patients with ICC. Lastly, overexpression of FOXP1 inhibited the proliferation, migration, and invasion of ICC cells and promoted apoptosis, whereas knockdown of FOXP1 had the opposite role. CONCLUSION: Our findings suggest that FOXP1 may serve as a novel outcome predictor for ICC as well as a tumor suppressor that may contribute to cancer treatment.

Focused Abbreviated Survey MRI Protocols for Brain and Spine Imaging.

There has been extensive growth in both the technical development and the clinical applications of MRI, establishing this modality as one of the most powerful diagnostic imaging tools. However, long examination and image interpretation times still limit the application of MRI, especially in emergent clinical settings. Rapid and abbreviated MRI protocols have been developed as alternatives to standard MRI, with reduced imaging times, and in some cases limited numbers of sequences, to more efficiently answer specific clinical questions. A group of rapid MRI protocols used at the authors' institution, referred to as FAST (focused abbreviated survey techniques), are designed to include or exclude emergent or urgent conditions or screen for specific entities. These FAST protocols provide adequate diagnostic image quality with use of accelerated approaches to produce imaging studies faster than traditional methods. FAST protocols have become critical diagnostic screening tools at the authors' institution, allowing confident and efficient confirmation or exclusion of actionable findings. The techniques commonly used to reduce imaging times, the imaging protocols used at the authors' institution, and future directions in FAST imaging are reviewed to provide a practical and comprehensive overview of FAST MRI for practicing neuroradiologists. ©RSNA, 2023 Quiz questions for this article are available in the supplemental material.

Mechanisms of Hypothermic Machine Perfusion to Decrease Donation After Cardiac Death Graft Inflammation: Through the Pathway of Upregulating Expression of KLF2 and Inhibiting TGF-ß Signaling.

Hypothermic machine perfusion (HMP) has been known as an efficient way to improve kidney graft function, but the underlying mechanisms remain unclear. Here, we adopt a rabbit reperfusion mode to investigate the upstream mechanisms of end-ischemic HMP of kidneys from donors after cardiac death (DCD), with static cold storage (CS) as a control. Eighteen New Zealand healthy male rabbits (12 weeks old, with a weight of 3.0 ± 0.2 kg) were randomly divided into three groups: HMP group, CS group, and Normal group (n = 6). The left kidney of rabbits underwent warm ischemia for 25 min through clamping the left renal pedicle and then reperfusion for 1 h. Then the left kidneys were preserved by CS or HMP (4°C for 4 h) ex vivo respectively, after they were autotransplanted and rabbits were submitted to a right nephrectomy. Twenty-four hours after reperfusion, all left renal specimens were collected. Finally, the expression of Krüppel-like factor 2 (KLF2), transforming growth factor-ß (TGF-ß) and SMAD4 protein in renal cortical tissue were detected by immunoblotting, and the TGF-ß and SMAD4 expressions were further confirmed by immunohistochemistry analysis. We found that expression of KLF2 in HMP group was significantly higher than CS group (P = 0.011), while expression of TGF-ß and SMAD4 in HMP group were significantly lower than CS group (P = 0.002, P = 0.01, respectively); Compared with normal group, the expression of TGF-ß and SMAD4 in HMP and CS group significantly increased (P<0.05). Compared with CS group, TGF-ß and SMAD4 protein were equally down-regulated in glomerular and the tubular epithelial cells in HMP group confirmed by immunohistochemistry. In conclusion, HMP may decrease DCD kidneys inflammation through the pathway of upregulating expression of KLF2 and inhibiting TGF-ß signaling after transplantation.

The Latency of Auditory Event-Related Potential P300 Prolonged in School-Age Students with Unilateral Hearing Loss in a Mandarin Learning Environment.

Our study investigated the differences in speech performance and neurophysiological response in groups of school-age children with unilateral hearing loss (UHL) who were otherwise typically developing (TD). We recruited a total of 16 primary school-age children for our study (UHL = 9/TD = 7), who were screened by doctors at Shin Kong Wu-Ho-Su Memorial Hospital. We used the Peabody Picture Vocabulary Test-Revised (PPVT-R) to test word comprehension, and the PPVT-R percentile rank (PR) value was proportional to the auditory memory score (by The Children's Oral Comprehension Test) in both groups. Later, we assessed the latency and amplitude of auditory ERP P300 and found that the latency of auditory ERP P300 in the UHL group was prolonged compared with that in the TD group. Although students with UHL have typical hearing in one ear, based on our results, long-term UHL might be the cause of atypical organization of brain areas responsible for auditory processing or even visual perceptions attributed to speech delay and learning difficulties.

LSD-YOLO: Enhanced YOLOv8n Algorithm for Efficient Detection of Lemon Surface Diseases.

Lemon, as an important cash crop with rich nutritional value, holds significant cultivation importance and market demand worldwide. However, lemon diseases seriously impact the quality and yield of lemons, necessitating their early detection for effective control. This paper addresses this need by collecting a dataset of lemon diseases, consisting of 726 images captured under varying light levels, growth stages, shooting distances and disease conditions. Through cropping high-resolution images, the dataset is expanded to 2022 images, comprising 4441 healthy lemons and 718 diseased lemons, with approximately 1-6 targets per image. Then, we propose a novel model lemon surface disease YOLO (LSD-YOLO), which integrates Switchable Atrous Convolution (SAConv) and Convolutional Block Attention Module (CBAM), along with the design of C2f-SAC and the addition of a small-target detection layer to enhance the extraction of key features and the fusion of features at different scales. The experimental results demonstrate that the proposed LSD-YOLO achieves an accuracy of 90.62% on the collected datasets, with mAP@50-95 reaching 80.84%. Compared with the original YOLOv8n model, both mAP@50 and mAP@50-95 metrics are enhanced. Therefore, the LSD-YOLO model proposed in this study provides a more accurate recognition of healthy and diseased lemons, contributing effectively to solving the lemon disease detection problem.

Cell-type specific inference from bulk RNA-sequencing data by integrating single cell reference profiles via EPIC-unmix.

Cell type specific (CTS) analysis is essential to reveal biological insights obscured in bulk tissue data. However, single-cell (sc) or single-nuclei (sn) resolution data are still cost-prohibitive for large-scale samples. Thus, computational methods to perform deconvolution from bulk tissue data are highly valuable. We here present EPIC-unmix, a novel two-step empirical Bayesian method integrating reference sc/sn RNA-seq data and bulk RNA-seq data from target samples to enhance the accuracy of CTS inference. We demonstrate through comprehensive simulations across three tissues that EPIC-unmix achieved 4.6% - 109.8% higher accuracy compared to alternative methods. By applying EPIC-unmix to human bulk brain RNA-seq data from the ROSMAP and MSBB cohorts, we identified multiple genes differentially expressed between Alzheimer's disease (AD) cases versus controls in a CTS manner, including 57.4% novel genes not identified using similar sample size sc/snRNA-seq data, indicating the power of our in-silico approach. Among the 6-69% overlapping, 83%-100% are in consistent direction with those from sc/snRNA-seq data, supporting the reliability of our findings. EPIC-unmix inferred CTS expression profiles similarly empowers CTS eQTL analysis. Among the novel eQTLs, we highlight a microglia eQTL for AD risk gene AP3B2, obscured in bulk and missed by sc/snRNA-seq based eQTL analysis. The variant resides in a microglia-specific cCRE, forming chromatin loop with AP3B2 promoter region in microglia. Taken together, we believe EPIC-unmix will be a valuable tool to enable more powerful CTS analysis.

CircNUP54 promotes hepatocellular carcinoma progression via facilitating HuR cytoplasmic export and stabilizing BIRC3 mRNA.

Circular RNAs (circRNAs) have been implicated in tumorigenesis and progression of various cancers. However, the underlying mechanisms of circRNAs in hepatocellular carcinoma (HCC) have not been fully elucidated. Herein, a new oncogenic circRNA, hsa_circ_0070039 (circNUP54), was identified to be significantly upregulated in HCC through circRNA sequencing. As verified in 68 HCC samples, circNUP54 overexpression was correlated with aggressive cancerous behaviors and poor outcomes. Moreover, the function experiments showed that knockdown of circNUP54 inhibited the malignant progression of HCC in vitro and in vivo, whereas overexpression of circNUP54 had the opposite role. Mechanistic investigations carried out by RNA pull-down, RNA immunoprecipitation, and immunofluorescence revealed that circNUP54 interacted with the RNA-binding protein Hu-antigen R (HuR) and promoted its cytoplasmic export. The cytoplasmic accumulation of HuR stabilized the downstream BIRC3 mRNA through its binding to the 3' UTR region. Consequently, the encoded protein of BIRC3, cellular inhibitor of apoptosis 2 (cIAP2), proceeded to activate the NF-κB signal pathway and ultimately contributed to HCC progression. In addition, depletion of BIRC3 rescued the pro-tumorigenic effect of circNUP54 on HCC cells. Overall, this study demonstrated that circNUP54 facilitates HCC progression via regulating the HuR/BIRC3/NF-κB axis, which may serve as a promising therapeutic target for HCC treatment.

Pretreatment CT-based machine learning radiomics model predicts response in unresectable hepatocellular carcinoma treated with lenvatinib plus PD-1 inhibitors and interventional therapy.

BACKGROUND: Lenvatinib plus PD-1 inhibitors and interventional (LPI) therapy have demonstrated promising treatment effects in unresectable hepatocellular carcinoma (HCC). However, biomarkers for predicting the response to LPI therapy remain to be further explored. We aimed to develop a radiomics model to noninvasively predict the efficacy of LPI therapy. METHODS: Clinical data of patients with HCC receiving LPI therapy were collected in our institution. The clinical model was built with clinical information. Nine machine learning classifiers were tested and the multilayer perceptron classifier with optimal performance was used as the radiomics model. The clinical-radiomics model was constructed by integrating clinical and radiomics scores through logistic regression analysis. RESULTS: 151 patients were enrolled in this study (2:1 randomization, 101 and 50 in the training and validation cohorts), of which three achieved complete response, 69 showed partial response, 46 showed stable disease, and 33 showed progressive disease. The objective response rate, disease control rate, and conversion resection rates were 47.7, 78.1 and 23.2%. 14 features were selected from the initially extracted 1223 for radiomics model construction. The area under the curves of the radiomics model (0.900 for training and 0.893 for validation) were comparable to that of the clinical-radiomics model (0.912 for training and 0.892 for validation), and both were superior to the clinical model (0.669 for training and 0.585 for validation). Meanwhile, the radiomics model can categorize participants into high-risk and low-risk groups for progression-free survival (PFS) and overall survival (OS) in the training (HR 1.913, 95% CI 1.121 to 3.265, p=0.016 for PFS; HR 4.252, 95% CI 2.051 to 8.816, p=0.001 for OS) and validation sets (HR 2.347, 95% CI 1.095 to 5.031, p=0.012 for PFS; HR 2.592, 95% CI 1.050 to 6.394, p=0.019 for OS). CONCLUSION: The promising machine learning radiomics model was developed and validated to predict the efficacy of LPI therapy for patients with HCC and perform risk stratification, with comparable performance to clinical-radiomics model.

A novel risk score system based on immune subtypes for identifying optimal mRNA vaccination population in hepatocellular carcinoma.

PURPOSE: Although mRNA vaccines have shown certain clinical benefits in multiple malignancies, their therapeutic efficacies against hepatocellular carcinoma (HCC) remains uncertain. This study focused on establishing a novel risk score system based on immune subtypes so as to identify optimal HCC mRNA vaccination population. METHODS: GEPIA, cBioPortal and TIMER databases were utilized to identify candidate genes for mRNA vaccination in HCC. Subsequently, immune subtypes were constructed based on the candidate genes. According to the differential expressed genes among various immune subtypes, a risk score system was established using machine learning algorithm. Besides, multi-color immunofluorescence of tumor tissues from 72 HCC patients were applied to validate the feasibility and efficiency of the risk score system. RESULTS: Twelve overexpressed and mutated genes associated with poor survival and APCs infiltration were identified as potential candidate targets for mRNA vaccination. Three immune subtypes (e.g. IS1, IS2 and IS3) with distinct clinicopathological and molecular profiles were constructed according to the 12 candidate genes. Based on the immune subtype, a risk score system was developed, and according to the risk score from low to high, HCC patients were classified into four subgroups on average (e.g. RS1, RS2, RS3 and RS4). RS4 mainly overlapped with IS3, RS1 with IS2, and RS2+RS3 with IS1. ROC analysis also suggested the significant capacity of the risk score to distinguish between the three immune subtypes. Higher risk score exhibited robustly predictive ability for worse survival, which was further independently proved by multi-color immunofluorescence of HCC samples. Notably, RS4 tumors exhibited an increased immunosuppressive phenotype, higher expression of the twelve potential candidate targets and increased genome altered fraction, and therefore might benefit more from vaccination. CONCLUSIONS: This novel risk score system based on immune subtypes enabled the identification of RS4 tumor that, due to its highly immunosuppressive microenvironment, may benefit from HCC mRNA vaccination.

EU-Net: Automatic U-Net neural architecture search with differential evolutionary algorithm for medical image segmentation.

Medical images are crucial in clinical practice, providing essential information for patient assessment and treatment planning. However, manual extraction of information from images is both time-consuming and prone to errors. The emergence of U-Net addresses this challenge by automating the segmentation of anatomical structures and pathological lesions in medical images, thereby significantly enhancing the accuracy of image interpretation and diagnosis. However, the performance of U-Net largely depends on its encoder-decoder structure, which requires researchers with knowledge of neural network architecture design and an in-depth understanding of medical images. In this paper, we propose an automatic U-Net Neural Architecture Search (NAS) algorithm using the differential evolutionary (DE) algorithm, named EU-Net, to segment critical information in medical images to assist physicians in diagnosis. Specifically, by presenting the variable-length strategy, the proposed EU-Net algorithm can sufficiently and automatically search for the neural network architecture without expertise. Moreover, the utilization of crossover, mutation, and selection strategies of DE takes account of the trade-off between exploration and exploitation in the search space. Finally, in the encoding and decoding phases of the proposed algorithm, different block-based and layer-based structures are introduced for architectural optimization. The proposed EU-Net algorithm is validated on two widely used medical datasets, i.e., CHAOS and BUSI, for image segmentation tasks. Extensive experimental results show that the proposed EU-Net algorithm outperforms the chosen peer competitors in both two datasets. In particular, compared to the original U-Net, our proposed method improves the metric mIou by at least 6%.

CircRNA MBOAT2 promotes intrahepatic cholangiocarcinoma progression and lipid metabolism reprogramming by stabilizing PTBP1 to facilitate FASN mRNA cytoplasmic export.

The carcinogenic role of FASN by regulating lipid metabolism reprogramming has been well-established in multiple tumors. However, whether mechanisms during intrahepatic cholangiocarcinoma (ICC) progression, such as circRNAs, regulate FASN expression remains unknown. Here we demonstrate a lipid metabolism-related circRNA, circMBOAT2 (hsa_circ_0007334 in circBase), frequently upregulated in ICC tissues, and positively correlated with ICC malignant features. CircMBOAT2 knockdown inhibits the growth and metastasis of ICC cells. Mechanistically, circMBOAT2 combines with PTBP1 and protects PTBP1 from ubiquitin/proteasome-dependent degradation, impairing the function of PTBP1 to transfer FASN mRNA from the nucleus to the cytoplasm. Moreover, circMBOAT2 and FASN have the same effect on fatty acid profile, unsaturated fatty acids instead of saturated fatty acids are primarily regulated and associated with malignant behaviors of ICC cells. The levels of lipid peroxidation and ROS were significantly higher when FASN was knocked down and recovered when circMBOAT2 was overexpressed. Our results identified that circMBOAT2 was upregulated in ICC and promoted progression by stabilizing PTBP1 to facilitate FASN mRNA cytoplasmic export, which altered lipid metabolic profile and regulated redox homeostasis in ICC, suggesting that circMBOAT2 may serve as an available therapeutic target for ICC with active lipid metabolism.

Single-cell genomics improves the discovery of risk variants and genes of atrial fibrillation.

Genome-wide association studies (GWAS) have linked hundreds of loci to cardiac diseases. However, in most loci the causal variants and their target genes remain unknown. We developed a combined experimental and analytical approach that integrates single cell epigenomics with GWAS to prioritize risk variants and genes. We profiled accessible chromatin in single cells obtained from human hearts and leveraged the data to study genetics of Atrial Fibrillation (AF), the most common cardiac arrhythmia. Enrichment analysis of AF risk variants using cell-type-resolved open chromatin regions (OCRs) implicated cardiomyocytes as the main mediator of AF risk. We then performed statistical fine-mapping, leveraging the information in OCRs, and identified putative causal variants in 122 AF-associated loci. Taking advantage of the fine-mapping results, our novel statistical procedure for gene discovery prioritized 46 high-confidence risk genes, highlighting transcription factors and signal transduction pathways important for heart development. In summary, our analysis provides a comprehensive map of AF risk variants and genes, and a general framework to integrate single-cell genomics with genetic studies of complex traits.

Identification of a Novel Ferroptosis-Related Gene Signature for Predicting Prognosis and Responsiveness to Immunotherapy in Hepatocellular Carcinoma.

Purpose: Ferroptosis has been reported to regulate multiple biological behaviors. However, the prognostic and oncologic values of ferroptosis-related genes (FRGs) have not been comprehensively elucidated in hepatocellular carcinoma (HCC). Here, we aimed to construct FRGs-associated signature for stratification of the prognosis of HCC patients. Methods: A list of FRGs was generated from FerrDb. Public databases were used to extract expression matrices and clinical information. TCGA cohort was randomly divided into a training set and a validation set. Prognostic signature for Overall Survival (OS) was established in training set and validated in internal cohorts (TCGA validation set and entire set) and external cohort (ICGC cohort). Additionally, the role of signature in HCC was well investigated by analysis of mutations, gene set enrichment analysis (GSEA), analysis of immune infiltrates, and analysis of response to immune checkpoint blockade (ICB) treatment. The oncogenic effects of ZFP69B on HCC were also investigated in vitro. Results: We identified 12 FRGs-based signature for OS with LASSO regression. Patients were partitioned into different risk groups based on the signature. Overall, patients in different groups had different prognosis. The signature independently predicted OS in multivariate Cox regression analyses. Anti-tumor immune cells including activated CD8 T cells, cytolytic activity, and Th1 cells were negatively correlated with risk score in both TCGC and ICGC cohorts. Furthermore, low-risk patients responded better to ICB than high-risk patients. In addition, knockdown of ZFP69B reduced proliferation, migration, and invasion, and promoted erastin-induced ferroptosis of HCC cells. Conclusion: We developed a prognostic signature based on FRGs to predict OS of HCC patients. And the signature may facilitate clinicians in identifying those who are likely to benefit from ICIs. The results also indicated that ZFP69B might regulate the process of ferroptosis and could be used as a novel potential target for HCC.

Trends in prevalence and all-cause mortality of metabolic dysfunction-associated fatty liver disease among adults in the past three decades: Results from the NHANES study.

BACKGROUND: Given the escalating epidemic of obesity and diabetes coupled with redefined diagnostic criteria, it is critical to identify the prevalence of metabolic dysfunction-associated fatty liver disease (MAFLD). We sought to determine the prevalence and mortality outcomes of MAFLD subtypes based on diagnostic criteria in the USA over the past three decades. METHODS: Eleven cycles of the National Health and Nutrition Examination Surveys (NHANES; 1988-1994 and 1999-2020) were used, and 72,224 participants were included. MAFLD was defined according to the 2020 International Expert Consensus. Based on diagnostic criteria and risk factors, MAFLD was categorized into seven subtypes: type 1 (obesity subtype), 2 (metabolic unhealthy subtype), 3 (diabetes subtype), 4 (metabolic unhealthy non-diabetes subtype), 5 (obesity and diabetes subtype), 6 (metabolic unhealthy non-obesity subtype), and 7 (mixed subtype). RESULTS: Over the study period, the estimated prevalence of MAFLD increased significantly from 22% in 1988-1994 to 36% in 2017-2020. The prevalence of Type 4 was the highest, followed by that of Type 7, whereas other types were low and almost unchanged over time. Individuals with MAFLD had 19% and 38% increased mortality risks from all causes and cardiovascular disease, respectively. Among them, the metabolically unhealthy participants with normal weight demonstrated a 116% higher risk for all-cause mortality [hazard ratio (HR): 2.16, 95% CI: 1.52-3.08] and a 222% higher risk for cardiovascular mortality (HR: 3.22, 95% CI: 1.72-6.04). Interestingly, stratification and interaction analyses demonstrated a significant impact of metabolic parameters on the relationship between MAFLD and all-cause mortality. CONCLUSIONS: In conclusion, our study identified an increase in MAFLD prevalence and a significant association between metabolic derangements in MAFLD and all-cause or cardiovascular mortality.

Zero-Shot Learning via Structure-Aligned Generative Adversarial Network.

In this article, we propose a structure-aligned generative adversarial network framework to improve zero-shot learning (ZSL) by mitigating the semantic gap, domain shift, and hubness problem. The proposed framework contains two parts, i.e., a generative adversarial network with a softmax classifier part, and a structure-aligned part. In the first part, the generative adversarial network aims at generating pseudovisual features through the guiding generator and discriminator play the minimax two-player game together. At the same time, the softmax classifier is committed to increasing the interclass distance and reducing intraclass distance. Then, the harmful effect of domain shift and hubness problems can be mitigated. In another part, we introduce a structure-aligned module where the structural consistency between visual space and semantic space is learned. By aligning the structure between visual space and semantic space, the semantic gap between them can be bridged. The performance of classification is improved when the structure-aligned visual-semantic embedding space is transferred to the unseen classes. Our framework reformulates the ZSL as a standard fully supervised classification task using the pseudovisual features of unseen classes. Extensive experiments conducted on five benchmark data sets demonstrate that the proposed framework significantly outperforms state-of-the-art methods in both conventional and generalized settings.

SLC39A1 Overexpression is Associated with Immune Infiltration in Hepatocellular Carcinoma and Promotes Its Malignant Progression.

BACKGROUND: Solute carrier family 39 member 1 (SLC39A1) has been identified as a zinc ion transport protein that possesses oncogenic properties in various types of cancers. However, its potential function in hepatocellular carcinoma (HCC) remains unknown. This study aimed to investigate the expression profile and potential mechanisms of SLC39A1 in HCC. METHODS: SLC39A1 expression was analyzed using multiple databases. The clinical significance and associated biological pathways of SLC39A1 were investigated using bioinformatics analysis. Potential correlations between SLC39A1 expression and tumor immunity in HCC were also evaluated using single-sample gene set enrichment analysis (GSEA). Sixty paired HCC samples were used to verify the expression pattern of SLC39A1. In vitro studies were performed to investigate the oncogenic effects of SLC39A1 in HCC. Western blot analysis was conducted to further investigate the possible involved signaling pathways. RESULTS: The overexpression of SLC39A1 in HCC was determined by bioinformatics analysis and was confirmed in tissues from our center. SLC39A1 overexpression was also significantly correlated with worse prognosis, advanced TNM stage, and histological grade. GSEA analysis demonstrated that SLC39A1 overexpression was involved in various tumor-related pathways, such as the cell cycle and Wnt signaling pathway. SLC39A1 knockdown repressed the proliferation, invasion, and migration abilities of HCC cells. Furthermore, SLC39A1 knockdown decreased the expression of the tumor progression-related proteins (eg, cyclin D1 and MMP2) and Wnt signaling pathway-related proteins (eg, Wnt3A and ß-catenin). In addition, SLC39A1 overexpression may be associated with impaired tumor immunity in HCC, as evidenced by the increased infiltration of Th2 cells and reduced infiltration of cytotoxic cells. CONCLUSION: These findings preliminarily suggested the crucial effect of SLC39A1 overexpression on HCC tumor progression and immunosuppression, suggesting its potential as a novel prognostic and therapeutic target in HCC.

Identification of LSM Family Members as Novel Unfavorable Biomarkers in Hepatocellular Carcinoma.

Background: Smith-like (LSM) family members play critical roles in multiple oncologic processes in several types of malignancies. The study on LSM family members of HCC might provide new insights into the tumorigenesis and therapeutic strategies of HCC. Methods: The clinical significance and oncologic biological functions of LSM family members were assessed through multiple bioinformatics methods and in vitro studies. The potential correlation between LSM family members and tumor immunity was also investigated using single sample gene set enrichment analysis (ssGSEA) and the ESTIMATE algorithm. Results: LSM family member overexpression in HCC was significantly correlated with poor clinical outcomes such as higher TNM stage, advanced histologic grade, and worse prognosis. A risk score system based on LSM5, LSM10, LSM12, and LSM14B showed a reliable predictive ability for OS of HCC patients. Functional enrichment analysis demonstrated that LSM family members overexpressed were all involved in cell cycle related biological processes. Besides, LSM12, LSM14A, and LSM14B were found to be significantly associated with PI3K-Akt-mTOR and T cell receptor signaling pathways. Tumors with LSM12, LSM14A, and LSM14B overexpression exhibited lower infiltration of activated CD8+ T cells with declined cytolytic activity and immune score, but increased infiltration of Th2 cells and Th2/Th1. LSM12, LSM14A, and LSM14B overexpression is also associated with higher tumor-related immune checkpoints (e.g., PD-L1, B7-H3, and PVR) expression and increased therapeutic insensitivity to immune checkpoint blockade (ICB). Moreover, the knockdown of LSM12, LSM14A, and LSM14B significantly inhibited the proliferation and invasion of HCC cells. Conclusion: This study systematically investigated the expression pattern and biological values of LSM family members in HCC and identified LSM family members as novel therapeutic targets in HCC.

Combination of certainty and uncertainty: Using FusionGAN to create abstract paintings.

In the study of generative art, it is relatively easy at present to achieve a high degree of certainty or uncertainty. However, the combination of certainty and uncertainty has always been an area of difficulty in generative art. In this paper, we present a novel FusionGAN system to automate the generation of abstract paintings. These generated abstract paintings combine the factors of certainty and uncertainty. First, we collect an APdataset consisting of three parts: abstract paintings drawn by artists, sketches, and abstract paintings generated by other neural network methods. We then train the proposed FusionGAN system on the collected dataset to learn the expression of abstract paintings. Corresponding to the two-step operation of the combination of certainty and uncertainty in the artist's creation, the proposed FusionGAN system is also divided into two steps for the generation of abstract paintings. More specifically, the first step is the basic structure establishment, which corresponds to the fundamental certainty element in the painting creation. The second step is the realization of details, which integrates the uncertain details based on the basic structure. The experimental results achieved by our system in abstract painting generation enrich the diversity of artistic creation and have been recognized by art institutions, with some results displayed on their websites.

Effects of temperature and physical state on heterogeneous oxidation of oleic acid droplets with ozone.

The heterogeneous reactions of pure micrometer-sized oleic acid droplets with ozone were studied as a function of temperature and physical state. Oxidation reactions were monitored using attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FT-IR) and UV-vis spectrometry. Variations in droplet morphology due to the extent of oxidation were monitored using an optical microscope. Oleic acid droplets were maintained in either solid or liquid state at 9.0 °C. The physical state of the aerosol was determined from the IR absorbance spectra. Oxidation of solid state oleic acid with ozone at 9.0 °C was rapidly converted to the liquid state, which was most likely due to the presence of oxidation products on the surface of the droplets. The fast melting process that resulted from exposure of solid-phase droplets to ozone produced an oxidation rate similar to that for liquid-phase droplets exposed to ozone at the same temperature. Analysis of the carboxylic IR absorbance ratio for esters vs carboxylic acids indicates that the larger ester C═O-to-carboxylic acid C═O ratios at higher temperature appeared to correspond to the production of α-acyloxyalkyl hydroperoxide oligomers and polymers. The wide variation in product yields will result in vastly different physical properties of aerosol particles under different ambient environmental conditions.