End-to-end Prediction of EGFR Mutation Status with Denseformer.

Accurate genotyping of the epidermal growth factor receptor (EGFR) is critical for the treatment planning of lung adenocarcinoma. Currently, clinical identification of EGFR genotyping highly relies on biopsy and sequence testing which is invasive and complicated. Recent advancements in the integration of computed tomography (CT) imagery with deep learning techniques have yielded a non-invasive and straightforward way for identifying EGFR profiles. However, there are still many limitations for further exploration: 1) most of these methods still require physicians to annotate tumor boundaries, which are time-consuming and prone to subjective errors; 2) most of the existing methods are simply borrowed from computer vision field which does not sufficiently exploit the multi-level features for final prediction. To solve these problems, we propose a Denseformer framework to identify EGFR mutation status in a real end-to-end fashion directly from 3D lung CT images. Specifically, we take the 3D whole-lung CT images as the input of the neural network model without manually labeling the lung nodules. This is inspired by the medical report that the mutational status of EGFR is associated not only with the local tumor nodules but also with the microenvironment surrounded by the whole lung. Besides, we design a novel Denseformer network to fully explore the distinctive information across the different level features. The Denseformer is a novel network architecture that combines the advantages of both convolutional neural network (CNN) and Transformer. Denseformer directly learns from the 3D whole-lung CT images, which preserves the spatial location information in the CT images. To further improve the model performance, we designed a combined Transformer module. This module employs the Transformer Encoder to globally integrate the information of different levels and layers and use them as the basis for the final prediction. The proposed model has been tested on a lung adenocarcinoma dataset collected at the Affiliated Hospital of Zunyi Medical University. Extensive experiments demonstrated the proposed method can effectively extract meaningful features from 3D CT images to make accurate predictions. Compared with other state-of-the-art methods, Denseformer achieves the best performance among current methods using deep learning to predict EGFR mutation status based on a single modality of CT images.

Transcriptome Analysis Reveals That SREBP Modulates a Large Repertoire of Genes Involved in Key Cellular Functions in Penaeus vannamei, although the Majority of the Dysregulated Genes Are Unannotated.

Sterol regulatory element-binding proteins (SREBPs) play vital roles in fatty acid metabolism and other metabolic processes in mammals. However, in penaeid shrimp, the repertoire of genes modulated by SREBP is unknown. Here, RNA interference-mediated knockdown followed by transcriptome sequencing on the Illumina Novaseq 6000 platform was used to explore the genes modulated by SREBP in Penaeus vannamei hepatopancreas. A total of 706 differentially expressed genes (DEGs) were identified, out of which 282 were upregulated and 424 downregulated. Although gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses revealed that most of the downregulated DEGs were involved in physiological processes related to immunity, metabolism, and cellular signaling pathways, many of the dysregulated genes have uncharacterized functions. While most of the dysregulated genes were annotated in metabolic processes, such as carbohydrate metabolism, lipid metabolism, signal transduction, and immune system, a large number (42.21%) are uncharacterized. Collectively, our current data revealed that SREBP modulates many genes involved in crucial physiological processes, such as energy metabolism, immune response, and cellular signaling pathways, as well as numerous genes with unannotated functions, in penaeid shrimp. These findings indicated that our knowledge of the repertoire of genes modulated by SREBP in shrimp lags behind that of mammals, probably due to limited research or because the complete genome of P. vannamei has just been sequenced.

The juvenile hormone epoxide hydrolase homolog in Penaeus vannamei plays immune-related functions.

Juvenile hormone epoxide hydrolase (JHEH) participates in the degradation of juvenile hormone and also involved in the development and molting process in insects. Here, the JHEH homolog in Pennaus vannamei was cloned and found to consist of a full-length cDNA of 2543 bp and an open reading frame (ORF) of 1386 bp. Transcripts of PvJHEH1 were expressed in most tissues of healthy shrimp with the highest found in the hepatopancreas and lowest in hemocytes. Both Gram-negative (Vibrio parahaemolyticus) and Gram-positive (Streptococcus iniae) bacteria induced PvJHEH1 expression in shrimp hemocytes and hepatopancreas, suggesting the involvement of PvJHEH1 in P. vannamei immune responses. Moreover, the mRNA levels of ecdysone inducible nuclear transcription factor PvE75 and crustacean hyperglycemic hormone (PvCHH), two endocrine-related genes with roles in shrimp innate immune response, decreased significantly in shrimp hemocytes after PvJHEH1 knockdown. Shrimp survival was also affected after PvJHEH1 knockdown followed by V. parahaemolyticus challenge, indicating that JHEH1 plays an essential role in shrimp survival during bacterial infection.

Functional characterization of arginine metabolic pathway enzymes in the antibacterial immune response of penaeid shrimp.

Arginine metabolism pathway enzymes and products are important modulators of several physiological processes in animals, including immune response. Although some components of the arginine metabolic pathway have been reported in penaeid shrimps, no systematic study has explored all the key pathway enzymes involved in shrimp antimicrobial response. Here, we explored the role of the three key arginine metabolism enzymes (nitric-oxide synthase (NOS), arginase (ARG), agmatinase (AGM)) in Penaeus vannamei antimicrobial immunity. First, P. vannamei homologs of ARG and AGM (PvARG and PvAGM) were cloned and found to be evolutionally conserved with invertebrate counterparts. Transcript levels of PvARG, PvAGM, and PvNOS were ubiquitously expressed in healthy shrimp tissues and induced in hemocytes and hepatopancreas upon challenge with Gram-negative (Vibrio parahaemolyticus) and Gram-positive (Streptoccocus iniae) bacteria, suggesting their involvement in shrimp antimicrobial immune response. Besides, RNA interference knockdown and enzyme activity assay revealed an antagonistic relationship between PvARG/PvAGM and PvNOS, while this relationship was broken upon pathogen stimulation. Interestingly, knockdown of PvNOS increased Vibrio abundance in shrimp hemolymph, whereas knockdown of PvAGR reduced Vibrio abundance. Taken together, our present data shows that homologs of the key arginine metabolism pathway enzymes in penaeid shrimp (PvARG, PvAGM, and PvNOS) work synergistically and/or antagonistically to modulate antibacterial immune response.

Immunotherapy for Hepatocellular Carcinoma: Current Status and Future Prospects.

Hepatocellular carcinoma (HCC) is the most prevalent primary liver cancer with poor prognosis. Surgery, chemotherapy, and radiofrequency ablation are three conventional therapeutic options that will help only a limited percentage of HCC patients. Cancer immunotherapy has achieved dramatic advances in recent years and provides new opportunities to treat HCC. However, HCC has various etiologies and can evade the immune system through multiple mechanisms. With the rapid development of genetic engineering and synthetic biology, a variety of novel immunotherapies have been employed to treat advanced HCC, including immune checkpoint inhibitors, adoptive cell therapy, engineered cytokines, and therapeutic cancer vaccines. In this review, we summarize the current landscape and research progress of different immunotherapy strategies in the treatment of HCC. The challenges and opportunities of this research field are also discussed.

Eliminating Indefiniteness of Clinical Spectrum for Better Screening COVID-19.

The coronavirus disease 2019 (COVID-19) has swept all over the world. Due to the limited detection facilities, especially in developing countries, a large number of suspected cases can only receive common clinical diagnosis rather than more effective detections like Reverse Transcription Polymerase Chain Reaction (RT-PCR) tests or CT scans. This motivates us to develop a quick screening method via common clinical diagnosis results. However, the diagnostic items of different patients may vary greatly, and there is a huge variation in the dimension of the diagnosis data among different suspected patients, it is hard to process these indefinite dimension data via classical classification algorithms. To resolve this problem, we propose an Indefiniteness Elimination Network (IE-Net) to eliminate the influence of the varied dimensions and make predictions about the COVID-19 cases. The IE-Net is in an encoder-decoder framework fashion, and an indefiniteness elimination operation is proposed to transfer the indefinite dimension feature into a fixed dimension feature. Comprehensive experiments were conducted on the public available COVID-19 Clinical Spectrum dataset. Experimental results show that the proposed indefiniteness elimination operation greatly improves the classification performance, the IE-Net achieves 94.80% accuracy, 92.79% recall, 92.97% precision and 94.93% AUC for distinguishing COVID-19 cases from non-COVID-19 cases with only common clinical diagnose data. We further compared our methods with 3 classical classification algorithms: random forest, gradient boosting and multi-layer perceptron (MLP). To explore each clinical test item's specificity, we further analyzed the possible relationship between each clinical test item and COVID-19.

Primary chondrosarcoma of the liver: A case report.

BACKGROUND: Primary chondrosarcoma of the liver are extremely rare. Moreover, there are few reports focusing on typical clinical symptoms and imaging characteristics. Therefore, the diagnosis of chondrosarcoma of the liver remains a challenge. CASE SUMMARY: A 59-year-old male was admitted due to a lesion occupying the right liver lobe that was found by physical examination. Magnetic resonance imaging showed a lobular mass with high T2 weighted image and low T1 weighted image with enhanced internal separation and edge in the right liver. He was diagnosed with liver cystadenoma by using magnetic resonance imaging. At 3 mo later, the magnetic resonance scan showed that the mass was enlarged. Laparoscopic liver tumor resection was performed with a pathological diagnosis of liver chondrosarcoma. Then he received a surgical resection for the recurrent lesion. However, intrahepatic and abdominal metastases were found again at 8 mo after the second operation. The patient then received conservative management and is now under follow-up. CONCLUSION: Primary liver chondrosarcoma generally is presented as lobulated and heterogeneous density/signal, cystic, solid masses without calcification with enhanced edge, internal septa and solid part. The imaging features are closely related to pathology, which may be helpful for clinical diagnosis.

Physicochemical characterization of Gracilaria chouae sulfated polysaccharides and their antioxidant potential.

A complete absence of the physicochemical characterization of Gracilaria chouae polysaccharides (GCP) and its corresponding bioactivities urged the need for this study. It was found that GCP is a heteropolysaccharide which exists in linear random coil conformation. It contained a sulfate content of 7.9% in addition to 52.63% total sugar content and 9.62% galacturonic acid. Galactose and 3,6-anhydrogalactose were found in a molar ratio of 1.0:0.6. Its setting and melting points were determined as 41.3 and 71.7 °C, respectively, which makes it a suitable candidate for industrial processing where further heating is required and/or where the end-product needs to have extended shelf life in hot climate. GCP demonstrated 2,2-diphenyl-1-picrylhydrazyl, 2,2'-azino-bis and hydroxyl radical scavenging activity (36.86, 27.42 and 19.07% at 3 mg·ml-1). Moreover, the results also suggested its potential use as a prebiotic due to its perceived high fermentability.