Comprehensive molecular classification predicted microenvironment profiles and therapy response for HCC.

BACKGROUND AND AIMS: Tumor microenvironment (TME) heterogeneity leads to a discrepancy in survival prognosis and clinical treatment response for patients with HCC. The clinical applications of documented molecular subtypes are constrained by several issues. APPROACH AND RESULTS: We integrated 3 single-cell data sets to describe the TME landscape and identified 6 prognosis-related cell subclusters. Unsupervised clustering of subcluster-specific markers was performed to generate transcriptomic subtypes. The predictive value of these molecular subtypes for prognosis and treatment response was explored in multiple external HCC cohorts and the Xiangya HCC cohort. TME features were estimated using single-cell immune repertoire sequencing, mass cytometry, and multiplex immunofluorescence. The prognosis-related score was constructed based on a machine-learning algorithm. Comprehensive single-cell analysis described TME heterogeneity in HCC. The 5 transcriptomic subtypes possessed different clinical prognoses, stemness characteristics, immune landscapes, and therapeutic responses. Class 1 exhibited an inflamed phenotype with better clinical outcomes, while classes 2 and 4 were characterized by a lack of T-cell infiltration. Classes 5 and 3 indicated an inhibitory tumor immune microenvironment. Analysis of multiple therapeutic cohorts suggested that classes 5 and 3 were sensitive to immune checkpoint blockade and targeted therapy, whereas classes 1 and 2 were more responsive to transcatheter arterial chemoembolization treatment. Class 4 displayed resistance to all conventional HCC therapies. Four potential therapeutic agents and 4 targets were further identified for high prognosis-related score patients with HCC. CONCLUSIONS: Our study generated a clinically valid molecular classification to guide precision medicine in patients with HCC.

PARP inhibitor and immune checkpoint inhibitor have synergism efficacy in gallbladder cancer.

Gallbladder cancer (GBC) is an aggressive cancer with poor prognosis. PARP inhibitors (PARPi) target PARP enzymes and have shown efficacy in patients with breast cancer gene (BRCA) mutations. Immunotherapy, especially immune checkpoint inhibitors (ICIs), has transformed cancer treatment. However, the combined impact of PARPi and ICIs in GBC remains unclear. We present a groundbreaking case of a GBC patient with BRCA2 mutations who received combination therapy with PARPi and ICIs after failing multiple lines of treatment. Next-generation sequencing (NGS-Seq) identified BRCA gene mutations. To further investigate potential mechanisms, we developed a PARP1-BRCA1-BRCA2 pathway-related risk score (PBscore) system to evaluate the impact of PARPi on the tumor immune microenvironment via RNA-Seq data. Gene expression and functional analysis identified potential mechanisms associated with the PBscore. Experimental validation assessed the impact of the combination therapy on the tumor microenvironment using multiplexed immunofluorescence imaging and immunohistochemistry in patients with BRCA gene wild type or mutations. RNA-Seq analysis revealed correlations between PBscore, immune checkpoint levels, tumor-infiltrating immune cells (TIICs), and the cancer-immunity cycle. Multiplexed immunofluorescence imaging validated that low PBscore patients might have an active tumor microenvironment. Furthermore, upon drug resistance, we observed an upregulation of negative immune checkpoints such as CEACAM1, indicating that the tumor immune microenvironment becomes suppressed after resistance. Our study revealed that PBscore could serve as a biomarker to predict immunotherapy efficacy, offering a promising alternative for BRCA2-mutated GBC patients.

Wogonin inhibits the migration and invasion of fibroblast-like synoviocytes by targeting PI3K/AKT/NF-κB pathway in rheumatoid arthritis.

BACKGROUND: Rheumatoid arthritis (RA) is currently an autoimmune inflammatory disease with an unclear pathogenesis. Fibroblast-like synoviocytes (FLSs) have tumor-like properties, and their activation and secretion of pro-inflammatory factors are important factors in joint destruction. Wogonin (5,7-dihydroxy-8-methoxyflavone), a natural flavonoid isolated from Scutellaria baicalensis root, has been shown to have significant anti-inflammatory, anti-oxidative stress, and anti-tumor effects in a variety of diseases. However, the role of wogonin in RA has not yet been demonstrated. PURPOSE: To investigate the inhibitory effect of wogonin on the invasive behavior of fibroblast-like synoviocytes and to explore the mechanism of action of wogonin in RA. METHODS: CCK-8, EdU, cell migration and invasion, immunofluorescence staining, RT-qPCR, and protein blot analysis were used to study the inhibitory effects of wogonin on migration, invasion, and pro-inflammatory cytokine overexpression in the immortalized rheumatoid synovial cell line MH7A. The therapeutic effects of wogonin were validated in vivo using arthritis scores and histopathological evaluation of collagen-induced arthritis mice. RESULTS: Wogonin inhibited the migration and invasion of MH7A cells, reduced the production of TNF-α, IL-1ß, IL-6, MMP-3 and MMP-9, and increased the expression of IL-10. Moreover, wogonin also inhibited the myofibrillar differentiation of MH7A cells, increased the expression of E-cadherin (E-Cad) and decreased the expression of α-smooth muscle actin (α-SMA). In addition, wogonin treatment effectively ameliorated joint destruction in CIA mice. Further molecular mechanism studies showed that wogonin treatment significantly inhibited the activation of PI3K/AKT/NF-κB signaling pathway in TNF-α-induced arthritic FLSs. CONCLUSION: Wogonin effectively inhibits migration, invasion and pro-inflammatory cytokine production of RA fibroblast-like synoviocytes through the PI3K/AKT/NF-κB pathway, and thus wogonin, as a natural flavonoid, has great potential for treating RA.

Chronic intermittent hypoxia-induced oxidative stress activates TRB3 and phosphorylated JNK to mediate insulin resistance and cell apoptosis in the pancreas.

This study explores the potential mechanisms of obstructive sleep apnoea (OSA) complicates type 2 diabetes mellitus (T2DM) by which chronic intermittent hypoxia (CIH) induces insulin resistance and cell apoptosis in the pancreas through oxidative stress. Four- and eight-week CIH rat models were established, and Tempol (100 mg/kg/d), was used as an oxidative stress inhibitor. This study included five groups: 4-week CIH, 4-week CIH-Tempol, 8-week CIH, 8-week CIH-Tempol and normal control (NC) groups. Fasting blood glucose and insulin levels were measured in the serum. The expression levels of 8-hidroxy-2-deoxyguanosine (8-OHdG), tribbles homologue 3 (TRB3), c-Jun N-terminal kinase (JNK), phosphorylated JNK (p-JNK), insulin receptor substrate-1 (IRS-1), phosphorylated IRS-1 (Ser307) (p-IRS-1ser307 ), protein kinase B (AKT), phosphorylated AKT (Ser473) (p-AKTser473 ), B cell lymphoma protein-2 (Bcl-2), cleaved-caspase-3 (Cl-caspase-3), and the islet cell apoptosis were detected in the pancreas. CIH induced oxidative stress in the pancreas. Compared with that in the NC group and CIH-Tempol groups individually, the homeostasis model assessment of insulin resistance (HOMA-IR) and apoptosis of islet cells was increased in the CIH groups. CIH-induced oxidative stress increased the expression of p-IRS-1Ser307 and decreased the expression of p-AKTSer473 . The expression levels of TRB3 and p-JNK were higher in the CIH groups than in both the CIH-Tempol and NC groups. Meanwhile, the expressions of Cl-caspase-3 and Bcl-2 were upregulated and downregulated, respectively, in the CIH groups. Hence, the present study demonstrated that CIH-induced oxidative stress might not only induce insulin resistance but also islet cell apoptosis in the pancreas through TRB3 and p-JNK.

Memory T follicular helper cells drive donor-specific antibodies independent of memory B cells and primary germinal center and alloantibody formation.

Human leukocyte antigen antibodies are important immunologic mediators of renal allograft loss and are difficult to control. The inability to permanently eliminate donor-specific antibodies (DSA) is partly due to an incomplete understanding of the cellular mechanisms driving alloantibody formation, recurrence, and maintenance. Memory T follicular helper (mTfh) cells rapidly interact with memory B cells upon antigen re-exposure for anamnestic humoral responses, but little is known about Tfh memory in transplantation. We hypothesized that alloreactive mTfh cells form after transplantation and play a critical role in DSA formation following alloantigen re-encounter. To test this hypothesis, we utilized murine skin allograft models to identify and characterize Tfh memory and interrogate its ability to mediate alloantibody responses. We identified alloreactive Tfh memory as a mediator of accelerated humoral alloresponses independent of memory B cells and primary germinal center, or DSA, formation. Furthermore, we demonstrate that mTfh-driven alloantibody formation is susceptible to CD28 costimulation blockade. These findings provide novel insight into a pathologic role for memory Tfh in alloantibody responses and strongly support shifting therapeutic focus from the singular targeting of B cell lineage cells and alloantibodies themselves to multimodal strategies that include inhibition of mTfh cells to treat DSA.

A multi-omics analysis reveals CLSPN is associated with prognosis, immune microenvironment and drug resistance in cancers.

BACKGROUND: Immunotherapy is effective only in limited patients. It is urgent to discover a novel biomarker to predict immune cells infiltration status and immunotherapy response of different cancers. CLSPN has been reported to play a pivotal role in various biological processes. However, a comprehensive analysis of CLSPN in cancers has not been conducted. METHODS: To show the whole picture of CLSPN in cancers, a pan-cancer analysis was conducted in 9125 tumor samples across 33 cancer types by integrating transcriptomic, epigenomic and pharmacogenomics data. Moreover, the role of CLSPN in cancer was validated by CCK-8, EDU, colony formation and flow cytometry in vitro and tumor cell derived xenograft model in vivo. RESULTS: CLSPN expression was generally upregulated in most cancer types and was significantly associated with prognosis in different tumor samples. Moreover, elevated CLSPN expression was closely correlated with immune cells infiltration, TMB (tumor mutational burden), MSI (microsatellite instability), MMR (mismatch repair), DNA methylation and stemness score across 33 cancer types. Enrichment analysis of functional genes revealed that CLSPN participated in the regulation of numerous signaling pathways involved in cell cycle and inflammatory response. The expression of CLSPN in LUAD patients were further analyzed at the single-cell level. Knockdown CLSPN significantly inhibited cancer cell proliferation and cell cycle related cyclin-dependent kinase (CDK) family and Cyclin family expression in LUAD (lung adenocarcinoma) both in vitro and in vivo experiments. Finally, we conducted structure-based virtual screening by modelling the structure of CHK1 kinase domain and Claspin phosphopeptide complex. The top five hit compounds were screened and validated by molecular docking and Connectivity Map (CMap) analysis. CONCLUSION: Our multi-omics analysis offers a systematic understanding of the roles of CLSPN in pan-cancer and provides a potential target for future cancer treatment.

Identification of disease-related genes in Plasmodium berghei by network module analysis.

BACKGROUND: Plasmodium berghei has been used as a preferred model for studying human malaria, but only a limited number of disease-associated genes of P. berghei have been reported to date. Identification of new disease-related genes as many as possible will provide a landscape for better understanding the pathogenesis of P. berghei. METHODS: Network module analysis method was developed and applied to identify disease-related genes in P. berghei genome. Sequence feature identification, gene ontology annotation, and T-cell epitope analysis were performed on these genes to illustrate their functions in the pathogenesis of P. berghei. RESULTS: 33,314 genes were classified into 4,693 clusters. 4,127 genes shared by six malaria parasites were identified and are involved in many aspects of biological processes. Most of the known essential genes belong to shared genes. A total of 63 clusters consisting of 405 P. berghei genes were enriched in rodent malaria parasites. These genes participate in various stages of parasites such as liver stage development and immune evasion. Combination of these genes might be responsible for P. berghei infecting mice. Comparing with P. chabaudi, none of the clusters were specific to P. berghei. P. berghei lacks some proteins belonging to P. chabaudi and possesses some specific T-cell epitopes binding by class-I MHC, which might together contribute to the occurrence of experimental cerebral malaria (ECM). CONCLUSIONS: We successfully identified disease-associated P. berghei genes by network module analysis. These results will deepen understanding of the pathogenesis of P. berghei and provide candidate parasite genes for further ECM investigation.

Melanoma differentiation-Associated gene 5 protects against NASH in mice.

BACKGROUND AND AIMS: NASH is a complicated disease characterized by hepatocyte steatosis, inflammation infiltration, and liver fibrosis. Accumulating evidence suggests that the innate immunity plays a key role in NASH progression. Here, we aimed to reveal the role of melanoma differentiation-associated gene 5 (MDA5, also known as Ifih1), a conventional innate immune regulator following viral infection, in the progression of NASH and investigate its underlying mechanism. APPROACH AND RESULTS: We first examined the expression of MDA5 and found that MDA5 was markedly down-regulated in the livers with NASH in human individuals and mice models. MDA5 overexpression significantly inhibits the free fatty acid-induced lipid accumulation and inflammation in hepatocyte in vitro, whereas MDA5 knockdown promotes hepatocyte lipotoxicity. Using hepatocyte-specific Mda5 gene knockout and transgenic mice, we found that diet-induced hepatic steatosis, inflammation, and liver fibrosis were markedly exacerbated by Mda5 deficiency but suppressed by Mda5 overexpression. Mechanistically, we found that the activation of apoptosis signal-regulating kinase 1 (ASK1)-mitogen-activated protein kinase pathway was significantly inhibited by MDA5 but enhanced by MDA5 deletion. We further validated that MDA5 directly interacted with ASK1 and suppressed its N-terminal dimerization. Importantly, blockage of ASK1 with adenovirus-expressing dominant negative ASK1 obviously reversed the lipid accumulation and ASK1 pathway activation when Mda5 was knocked out. CONCLUSIONS: These data indicate that MDA5 is an essential suppressor in NASH. The findings support MDA5 as a regulator of ASK1 and a promising therapeutic target for NASH.

SY-Net: A Rice Seed Instance Segmentation Method Based on a Six-Layer Feature Fusion Network and a Parallel Prediction Head Structure.

During the rice quality testing process, the precise segmentation and extraction of grain pixels is a key technique for accurately determining the quality of each seed. Due to the similar physical characteristics, small particles and dense distributions of rice seeds, properly analysing rice is a difficult problem in the field of target segmentation. In this paper, a network called SY-net, which consists of a feature extractor module, a feature pyramid fusion module, a prediction head module and a prototype mask generation module, is proposed for rice seed instance segmentation. In the feature extraction module, a transformer backbone is used to improve the ability of the network to learn rice seed features; in the pyramid fusion module and the prediction head module, a six-layer feature fusion network and a parallel prediction head structure are employed to enhance the utilization of feature information; and in the prototype mask generation module, a large feature map is used to generate high-quality masks. Training and testing were performed on two public datasets and one private rice seed dataset. The results showed that SY-net achieved a mean average precision (mAP) of 90.71% for the private rice seed dataset and an average precision (AP) of 16.5% with small targets in COCO2017. The network improved the efficiency of rice seed segmentation and showed excellent application prospects in performing rice seed quality testing.

Patterns of Circulating Microbiota during the Acute Phase Following ST-Segment Elevation Myocardial Infarction Predict Long-Term Cardiovascular Events.

Limited information exists regarding whether circulating microbiota could predict long-term clinical outcomes following ST-segment elevation myocardial infarction (STEMI). A total of 244 consecutive patients with STEMI were followed for 2.8 years, and 64 first major adverse cardiovascular events (MACEs) were recorded. Both microbiota abundance [Corynebacterium tuberculostearicum (HR, 1.28; 95% CI, 1.03-1.58) and Staphylococcus aureus (S. aureus) (HR, 1.16; 95% CI, 1.02-1.33) ] and microbiota clusters (Cluster 2 versus Cluster 1: HR, 1.84; 95% CI, 1.04-3.27) could independently predict MACE. Furthermore, a model based on established independent predictors alone was significantly improved by the addition of different microbiota patterns. In addition, CD14++CD16+ monocytes (Mon2) had a significant mediation effect on the microbiota patterns → MACE association. The present study demonstrated that the abundance and clusters of circulating microbiota are associated with future adverse cardiovascular events independent of traditional risk factors, which were partially mediated by an increase in Mon2.

Pembrolizumab versus paclitaxel for previously treated advanced gastric or gastroesophageal junction cancer (KEYNOTE-063): A randomized, open-label, phase 3 trial in Asian patients.

BACKGROUND: KEYNOTE-063 (NCT03019588) investigated pembrolizumab versus paclitaxel as second-line therapy in Asian patients with advanced programmed death ligand 1 (PD-L1)-positive (combined positive score ≥1) gastric/gastroesophageal junction (GEJ) cancer. METHODS: This randomized, open-label, phase 3 study was conducted at 36 medical centers in China (mainland), Malaysia, South Korea, and Taiwan. Patients were randomly assigned 1:1 to 200 mg of pembrolizumab intravenously every 3 weeks for ≤2 years or 80 mg/m2 of paclitaxel intravenously every week. Primary end points were overall survival (OS) and progression-free survival (PFS). Secondary end points were objective response rate (ORR) per Response Evaluation Criteria in Solid Tumors version 1.1 and safety. RESULTS: Between February 16, 2017, and March 12, 2018, 94 patients were randomly assigned (47 pembrolizumab/47 paclitaxel) after screening; enrollment was stopped on March 12, 2018, based on the results of the global KEYNOTE-061 study, and patients were followed until the last patient's last visit. Median OS was 8 months (95% confidence interval [CI], 4-10 months) with pembrolizumab versus 8 months (95% CI, 5-11 months) with paclitaxel (hazard ratio [HR], 0.99; 95% CI, 0.63-1.54). Median PFS was 2 months (95% CI, 1-3 months) with pembrolizumab versus 4 months (95% CI, 3-6 months) with paclitaxel (HR, 1.62; 95% CI, 1.04-2.52). ORR was 13% for pembrolizumab versus 19% for paclitaxel. Any-grade treatment-related adverse events occurred in 28 pembrolizumab-treated patients (60%) and 42 paclitaxel-treated patients (96%); grades 3 to 5 events occurred in 5 patients (11%) and 28 patients (64%), respectively. CONCLUSIONS: Definitive conclusions about the efficacy of second-line pembrolizumab in Asian patients with advanced PD-L1-positive gastric/GEJ cancer are limited because of insufficient power, but pembrolizumab was well tolerated in this patient population. Efficacy followed a trend similar to that observed in the phase 3 KEYNOTE-061 trial.

BMP4 promotes the metastasis of gastric cancer by inducing epithelial-mesenchymal transition via ID1.

Epithelial-mesenchymal transition (EMT) is a crucial process for cancer cells to acquire metastatic potential, which primarily causes death in gastric cancer (GC) patients. Bone morphogenetic protein 4 (BMP4) is a member of the TGF-ß family that plays an indispensable role in human cancers. However, little is known about its roles in GC metastasis. In this study, BMP4 was found to be frequently overexpressed in GC tissues and was correlated with poor patient's prognosis. BMP4 was upregulated in GC cell lines and promoted EMT and metastasis of GC cells both in vitro and in vivo, whereas knockdown of BMP4 significantly inhibited EMT and metastasis of GC cells. Furthermore, the inhibitor of DNA binding 1 (also known as DNA-binding protein inhibitor ID1) was identified as a downstream target of BMP4 using PCR arrays and was upregulated via SMAD1/5/8 phosphorylation. ID1 knockdown attenuated BMP4-induced EMT and invasion in GC cells. Moreover, ID1 overexpression in BMP4 knockdown cells restored the promotion of EMT and cell invasion. In summary, BMP4 induced EMT and promoted GC metastasis by upregulating ID1 expression. Antagonizing BMP4 could be a potential therapeutic strategy for GC metastasis.

AMICA1 is a diagnostic and prognostic biomarker and induces immune cells infiltration by activating cGAS-STING signaling in lung adenocarcinoma.

BACKGROUND: Adhesion molecule interacting with CXADR antigen 1 (AMICA1), also known as Junction Adhesion Molecule Like (JAML), a recently identified member of the JAMs family, plays a critical role in mediating cancer development and immune cells transmigration. However, AMICA1 has never been reported to be related to the genesis, development and immunotherapy effect of lung adenocarcinoma (LUAD). In this research, we investigated the role of AMICA1 in LUAD through bioinformatic analysis and in vitro experiments. METHODS: Bioinformatic analysis from TCGA and GEO databases were used to investigate the expression level of AMICA1 and the correlation between AMICA1 and clinical parameters in LUAD patients. The LinkedOmics database was analyzed to investigate the co-expression network of AMICA1. TIMER and TISIDB databases were used to analyze the correlation between AMICA1 expression and immune infiltration level. Except for bioinformatic analysis, the AMICA1 mRNA (26 patients) and protein level (6 patients) were also detected by real-time PCR and western blot. The infiltration level of CD8+ T cells (15 patients) and PD1+ T cells (13 patients) were detected by immunohistochemistry. The diagnostic value of AMICA1 was revealed by receiver operating characteristic (ROC) curves. The Spearman correlation coefficient was used to analyze the correlation between AMICA1 expression and CD8+ T cells and PD1+ T cells infiltration level. RESULTS: Bioinformatic data from public database and our data showed that AMICA1 was significantly downregulated in LUAD. Decreased AMICA1 expression in LUAD was associated with higher T stage, M stage and pathological stage. Kaplan-Meier survival analysis indicated that patients with low AMICA1 expression had a worse prognosis. ROC curves showed that AMICA1 had high diagnostic accuracy for LUAD patients. Multivariate Cox analysis further displayed that AMICA1 expression level was an independent prognostic factor for LUAD patients. Moreover, the expression of AMICA1 was significantly different in the immune cells subtype and was obviously linked to immune cells infiltration. In vitro experiments suggested that AMICA1 significantly suppressed the proliferation of LUAD cells and played an important role in activating cGAS-STING signaling. CONCLUSIONS: Our study suggested that AMICA1 might function as a diagnostic and prognostic biomarker and significantly suppressed the proliferation of LUAD cells. Besides, AMICA1 is positively correlated with immune cells infiltration in LUAD, and cGAS-STING signaling might play an important role in the process.

Orthotopic Versus Allotopic Implantation: Comparison of Radiological and Pathological Characteristics.

BACKGROUND: In experimental animal models, implantation location might influence the heterogeneity and overall development of the tumor, leading to an interpretation bias. PURPOSE: To investigate the effects of implantation location in experimental tumor model using magnetic resonance imaging (MRI) and pathological findings. STUDY TYPE: Prospective. SUBJECTS: Forty-five breast cancer-bearing mice underwent orthotopic (N = 15) and heterotopic (intrahepatic [N = 15] and subcutaneous [N = 15]) implantation. FIELD STRENGTH/SEQUENCE: Sequences including: T1-weighted turbo spin echo sequence, T2-weighted blade sequence, diffusion-weighted imaging, pre- and post-contrast T1 mapping, multi-echo T2 mapping at 3.0 T. ASSESSMENT: MRI was performed at 7, 14, and 21 days after implantation. Native T1, post-contrast T1, T2, and apparent diffusion coefficient (ADC) of tumors, the tumor volume and necrosis volume within tumor were obtained. Lymphocyte cells from H&E staining, Ki67-positive, and CD31-positive cells from immunohistochemistry were determined. STATISTICAL TESTS: One-way analysis of variance and Spearman's rank correlation were performed. P value <0.05 was considered statistically significant. RESULTS: The tumor volume (intrahepatic vs. orthotopic vs. subcutaneous: 587.50 ± 77.62 mm3 vs. 814.00 ± 43.85 mm3 vs. 956.13 ± 119.22 mm3 ), necrosis volume within tumor (89.10 ± 26.60 mm3 vs. 292.41 ± 57.92 mm3 vs. 179.91 ± 31.73 mm3 , respectively), ADC at day 21 (543.41 ± 42.28 vs. 542.92 ± 99.67 vs. 369.83 ± 42.90, respectively), and post-contrast T1 at all timepoints (day 7: 442.00 ± 11.52 vs. 435.00 ± 22.90 vs. 394.33 ± 29.95; day 14: 459.00 ± 26.11 vs. 436.83 ± 26.01 vs. 377.00 ± 27.83; day 21: 463.50 ± 23.49 vs. 458.00 ± 34.28 vs. 375.00 ± 30.55) were significantly different between three groups. Necrosis volumes of subcutaneous and intrahepatic tumors were significantly lower than those of orthotopic tumors. The CD31-positive rate in the intrahepatic implantation was significantly higher than in orthotopic and subcutaneous groups. Necrosis volume (r = -0.71), ADC (r = -0.85), and post-contrast T1 (r = -0.75) were strongly correlated with vascular invasion index. DATA CONCLUSION: Orthotopic and heterotopic tumors have their unique growth kinetics, necrosis volume, and vascular invasion. Non-invasive MR quantitative parameters, including ADC and post-contrast T1, may reflect vascular invasion in mice. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 3.

A comprehensive analysis of the efficacy and safety of COVID-19 vaccines.

The numbers of cases and deaths from coronavirus disease 2019 (COVID-19) are continuously increasing. Many people are concerned about the efficacy and safety of the COVID-19 vaccines. We performed a comprehensive analysis of the published trials of COVID-19 vaccines and the real-world data from the Vaccine Adverse Event Reporting System. Globally, our research found that the efficacy of all vaccines exceeded 70%, and RNA-based vaccines had the highest efficacy of 94.29%; moreover, Black or African American people, young people, and males may experience greater vaccine efficacy. The spectrum of vaccine-related adverse drug reactions (ADRs) is extremely broad, and the most frequent ADRs are pain, fatigue, and headache. Most ADRs are tolerable and are mainly grade 1 or 2 in severity. Some severe ADRs have been identified (thromboembolic events, 21-75 cases per million doses; myocarditis/pericarditis, 2-3 cases per million doses). In summary, vaccines are a powerful tool that can be used to control the COVID-19 pandemic, with high efficacy and tolerable ADRs. In addition, the spectrum of ADRs associated with the vaccines is broad, and most of the reactions appear within a week, although some may be delayed. Therefore, ADRs after vaccination need to be identified and addressed in a timely manner.

End-to-End Point Cloud Completion Network with Attention Mechanism.

We propose a conceptually simple, general framework and end-to-end approach to point cloud completion, entitled PCA-Net. This approach differs from the existing methods in that it does not require a "simple" network, such as multilayer perceptrons (MLPs), to generate a coarse point cloud and then a "complex" network, such as auto-encoders or transformers, to enhance local details. It can directly learn the mapping between missing and complete points, ensuring that the structure of the input missing point cloud remains unchanged while accurately predicting the complete points. This approach follows the minimalist design of U-Net. In the encoder, we encode the point clouds into point cloud blocks by iterative farthest point sampling (IFPS) and k-nearest neighbors and then extract the depth interaction features between the missing point cloud blocks by the attention mechanism. In the decoder, we introduce a new trilinear interpolation method to recover point cloud details, with the help of the coordinate space and feature space of low-resolution point clouds, and missing point cloud information. This paper also proposes a method to generate multi-view missing point cloud data using a 3D point cloud hidden point removal algorithm, so that each 3D point cloud model generates a missing point cloud through eight uniformly distributed camera poses. Experiments validate the effectiveness and superiority of PCA-Net in several challenging point cloud completion tasks, and PCA-Net also shows great versatility and robustness in real-world missing point cloud completion.

A Method for Detection of Corn Kernel Mildew Based on Co-Clustering Algorithm with Hyperspectral Image Technology.

Hyperspectral imaging can simultaneously acquire spectral and spatial information of the samples and is, therefore, widely applied in the non-destructive detection of grain quality. Supervised learning is the mainstream method of hyperspectral imaging for pixel-level detection of mildew in corn kernels, which requires a large number of training samples to establish the prediction or classification models. This paper presents an unsupervised redundant co-clustering algorithm (FCM-SC) based on multi-center fuzzy c-means (FCM) clustering and spectral clustering (SC), which can effectively detect non-uniformly distributed mildew in corn kernels. This algorithm first carries out fuzzy c-means clustering of sample features, extracts redundant cluster centers, merges the cluster centers by spectral clustering, and finally finds the category of corresponding cluster centers for each sample. It effectively solves the problems of the poor ability of the traditional fuzzy c-means clustering algorithm to classify the data with complex structure distribution and the complex calculation of the traditional spectral clustering algorithm. The experimental results demonstrated that the proposed algorithm could describe the complex structure of mildew distribution in corn kernels and exhibits higher stability, better anti-interference ability, generalization ability, and accuracy than the supervised classification model.

TPFusion: Texture Preserving Fusion of Infrared and Visible Images via Dense Networks.

In this paper, we design an infrared (IR) and visible (VIS) image fusion via unsupervised dense networks, termed as TPFusion. Activity level measurements and fusion rules are indispensable parts of conventional image fusion methods. However, designing an appropriate fusion process is time-consuming and complicated. In recent years, deep learning-based methods are proposed to handle this problem. However, for multi-modality image fusion, using the same network cannot extract effective feature maps from source images that are obtained by different image sensors. In TPFusion, we can avoid this issue. At first, we extract the textural information of the source images. Then two densely connected networks are trained to fuse textural information and source image, respectively. By this way, we can preserve more textural details in the fused image. Moreover, loss functions we designed to constrain two densely connected convolutional networks are according to the characteristics of textural information and source images. Through our method, the fused image will obtain more textural information of source images. For proving the validity of our method, we implement comparison and ablation experiments from the qualitative and quantitative assessments. The ablation experiments prove the effectiveness of TPFusion. Being compared to existing advanced IR and VIS image fusion methods, our fusion results possess better fusion results in both objective and subjective aspects. To be specific, in qualitative comparisons, our fusion results have better contrast ratio and abundant textural details. In quantitative comparisons, TPFusion outperforms existing representative fusion methods.

CLEC10A is a prognostic biomarker and correlated with clinical pathologic features and immune infiltrates in lung adenocarcinoma.

CLEC10A, (C-type lectin domain family 10, member A), as the member of C-type lectin receptors (CLRs), plays a vital role in modulating innate immunity and adaptive immunity and has shown great potential as an immunotherapy target for cancers. However, there is no functional research of CLEC10A in prognostic risk, immunotherapy or any other treatment of lung adenocarcinoma (LUAD). We performed bioinformatics analysis on LUAD data downloaded from TCGA (The Cancer Genome Atlas) and GEO (Gene Expression Omnibus), and jointly analysed with online databases such as HPA, LinkedOmics, TIMER, ESTIMATE and TISIDB. We found that lower expression of CLEC10A was accompanied with worse outcomes of LUAD patients. Moreover, CLEC10A expression was significantly correlated with a variety of the tumour-infiltrating immune cells (TIICs). As a promising prognosis predictor and potential immunotherapy target, the potential influence and mechanisms of CLEC10A in LUAD deserve further exploring.

Cost-Effectiveness of Pembrolizumab plus Axitinib Versus Sunitinib as First-Line Therapy in Advanced Renal Cell Carcinoma in the U.S.

BACKGROUND: The data from the phase III clinical trial KEYNOTE-426 indicated that pembrolizumab plus axitinib compared with sunitinib could generate clinical benefits in patients with previously untreated advanced renal cell carcinoma (RCC). Given the incremental clinical benefits, we examined the potential cost-effectiveness of pembrolizumab plus axitinib versus sunitinib in the first-line setting for patients with advanced RCC from the U.S. payers' perspective. MATERIALS AND METHODS: Cost and health outcomes were estimated at a willingness-to-pay (WTP) threshold of $100,000 to $150,000 per quality-adjusted life-year (QALY). One-way and probabilistic sensitivity analyses were performed by varying potentially modifiable parameters, and additional subgroup analyses were performed as well. RESULTS: Upon our analyses, the total treatment costs in the pembrolizumab plus axitinib and sunitinib groups were $522,796 and $348,424 and the QALYs gained 2.90 and 1.72, respectively. In the base-case analysis, compared with receiving sunitinib, patients with advanced RCC receiving pembrolizumab plus axitinib gained 1.18 more QALYs at an incremental cost-effectiveness ratio of $148,676/QALY. The results of subgroup analyses demonstrated that pembrolizumab plus axitinib was most cost-effective for patients who had one organ with metastasis. CONCLUSION: First-line treatment with pembrolizumab plus axitinib, compared with sunitinib, is a cost-effective strategy when the value of WTP is from $100,000 to $150,000 per QALY in patients with advanced RCC. For patients with one-organ metastasis and those in International Metastatic Renal Cell Carcinoma Database Consortium poor risk group, first-line treatment with pembrolizumab plus axitinib is more cost-effective than others. IMPLICATIONS FOR PRACTICE: This was the first study to examine the cost-effectiveness of pembrolizumab plus axitinib versus sunitinib in advanced renal cell carcinoma (RCC). This study found that first-line treatment with pembrolizumab plus axitinib is a cost-effective strategy when the value of willingness-to-pay is from $100,000 to $150,000 per quality-adjusted life-year in patients with advanced RCC from the U.S. payers' perspective.