Altered immune cell in human severe acute pancreatitis revealed by single-cell RNA sequencing.

Background: Severe acute pancreatitis (SAP) is characterized by inflammation, with inflammatory immune cells playing a pivotal role in disease progression. This study aims to understand variations in specific immune cell subtypes in SAP, uncover their mechanisms of action, and identify potential biological markers for predicting Acute Pancreatitis (AP) severity. Methods: We collected peripheral blood from 7 untreated SAP patients and employed single-cell RNA sequencing for the first time to construct a transcriptome atlas of peripheral blood mononuclear cells (PBMCs) in SAP. Integrating SAP transcriptomic data with 6 healthy controls from the GEO database facilitated the analysis of immune cell roles in SAP. We obtained comprehensive transcriptomic datasets from AP samples in the GEO database and identified potential biomarkers associated with AP severity using the "Scissor" tool in single-cell transcriptomic data. Results: This study presents the inaugural construction of a peripheral blood single-cell atlas for SAP patients, identifying 20 cell subtypes. Notably, there was a significant decrease in effector T cell subsets and a noteworthy increase in monocytes compared to healthy controls. Moreover, we identified a novel monocyte subpopulation expressing high levels of PPBP and PF4 which was significantly elevated in SAP. The proportion of monocyte subpopulations with high CCL3 expression was also markedly increased compared to healthy controls, as verified by flow cytometry. Additionally, cell communication analysis revealed insights into immune and inflammation-related signaling pathways in SAP patient monocytes. Finally, our findings suggest that the subpopulation with high CCL3 expression, along with upregulated pro-inflammatory genes such as S100A12, IL1B, and CCL3, holds promise as biomarkers for predicting AP severity. Conclusion: This study reveals monocytes' crucial role in SAP initiation and progression, characterized by distinct pro-inflammatory features intricately linked to AP severity. A monocyte subpopulation with elevated PPBP and CCL3 levels emerges as a potential biomarker and therapeutic target.

Optimization of Hot Embossing Condition Using Taguchi Method and Evaluation of Microchannels for Flexible On-Chip Proton-Exchange Membrane Fuel Cell.

Hot embossing is a manufacturing technique used to create microchannels on polymer substrates. In recent years, microchannel fabrication technology based on hot embossing has attracted considerable attention due to its convenience and low cost. A new evaluation method of microchannels, as well as an approach to obtaining optimal hot embossing conditions based on the Taguchi method, is proposed in this paper to fabricate precise microchannels for a flexible proton-exchange membrane fuel cell (PEMFC). Our self-made hot embossing system can be used to fabricate assorted types of micro-channel structures on polymer substrates according to various applications, whose bottom width, top width, height and cross-sectional area vary in the aims of different situations. In order to obtain a high effective filling ratio, a new evaluation method is presented based on the four parameters of channel structures, and the Taguchi method is utilized to arrange three main factors (temperature, force and time) affecting the hot embossing in orthogonal arrays, quickly finding the optimal condition for the embossing process. The evaluation method for microchannels proposed in this paper, compared to traditional evaluation methods, incorporates the area factor, providing a more comprehensive assessment of the fabrication completeness of the microchannels. Additionally, it allows for the quick and simple identification of optimal conditions. The experimental results indicate that after determining the optimal embossing temperature, pressure and time using the Taguchi method, the effective filling rate remains above 95%, thereby enhancing the power density. Through variance analysis, it was found that temperature is the most significant factor affecting the hot embossing of microchannels. The high filling rate makes the process suitable for PEMFCs. The results demonstrate that under optimized process conditions, a self-made hot embossing system can effectively fabricate columnar structure microchannels for PEMFCs.

Deep learning modeling using mammography images for predicting estrogen receptor status in breast cancer.

BACKGROUND: The estrogen receptor (ER) serves as a pivotal indicator for assessing endocrine therapy efficacy and breast cancer prognosis. Invasive biopsy is a conventional approach for appraising ER expression levels, but it bears disadvantages due to tumor heterogeneity. To address the issue, a deep learning model leveraging mammography images was developed in this study for accurate evaluation of ER status in patients with breast cancer. OBJECTIVES: To predict the ER status in breast cancer patients with a newly developed deep learning model leveraging mammography images. MATERIALS AND METHODS: Datasets comprising preoperative mammography images, ER expression levels, and clinical data spanning from October 2016 to October 2021 were retrospectively collected from 358 patients diagnosed with invasive ductal carcinoma. Following collection, these datasets were divided into a training dataset (n = 257) and a testing dataset (n = 101). Subsequently, a deep learning prediction model, referred to as IP-SE-DResNet model, was developed utilizing two deep residual networks along with the Squeeze-and-Excitation attention mechanism. This model was tailored to forecast the ER status in breast cancer patients utilizing mammography images from both craniocaudal view and mediolateral oblique view. Performance measurements including prediction accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curves (AUCs) were employed to assess the effectiveness of the model. RESULTS: In the training dataset, the AUCs for the IP-SE-DResNet model utilizing mammography images from the craniocaudal view, mediolateral oblique view, and the combined images from both views, were 0.849 (95% CIs: 0.809-0.868), 0.858 (95% CIs: 0.813-0.872), and 0.895 (95% CIs: 0.866-0.913), respectively. Correspondingly, the AUCs for these three image categories in the testing dataset were 0.835 (95% CIs: 0.790-0.887), 0.746 (95% CIs: 0.793-0.889), and 0.886 (95% CIs: 0.809-0.934), respectively. A comprehensive comparison between performance measurements underscored a substantial enhancement achieved by the proposed IP-SE-DResNet model in contrast to a traditional radiomics model employing the naive Bayesian classifier. For the latter, the AUCs stood at only 0.614 (95% CIs: 0.594-0.638) in the training dataset and 0.613 (95% CIs: 0.587-0.654) in the testing dataset, both utilizing a combination of mammography images from the craniocaudal and mediolateral oblique views. CONCLUSIONS: The proposed IP-SE-DResNet model presents a potent and non-invasive approach for predicting ER status in breast cancer patients, potentially enhancing the efficiency and diagnostic precision of radiologists.

Concomitant Medications Alter Clinical Outcomes in Patients with Advanced Digestive Tract Cancer Receiving PD-1 Checkpoint Inhibitors Combined with Antiangiogenetic Agents.

PURPOSE: Our study aimed to evaluate the impact of concomitant medications on the response and survival of patients with advanced digestive tract cancer receiving an immunotherapy-antiangiogenesis combination. METHODS: We conducted a three-center observational retrospective study of patients with advanced digestive tract cancer who received programmed death-1 (PD-1) inhibitors plus antiangiogenic agents between March 2019 and July 2022 in China. The patients had one of the three types of primary tumors: hepatocellular carcinoma (HCC), colorectal cancer (CRC), and gastric cancer (GC). RESULTS: The study included 352 patients. The most frequently prescribed co-medications were nonsteroidal anti-inflammatory drugs (NSAIDs) (46.3%), proton pump inhibitors (PPIs) (38.0%), systemic antibiotics (33.8%), and corticosteroids (30.1%). Probiotics had a direct correlation with a higher objective response rate (ORR) (OR 2.4, 95% CI 1.2 to 4.7, p = 0.013). Patients who received PPIs for gastritis/gastroesophageal reflux disease (GERD) (HR 0.7, 95% CI 0.5 to 1.0, p = 0.045), anticoagulants (HR 0.5, 95% CI 0.3 to 0.9, p = 0.009), and probiotics (HR 0.7, 95% CI 0.5 to 1.0, p = 0.034) had longer progression-free survival (PFS). Patients who received PPIs for gastritis/GERD (HR 0.6, 95% CI 0.4 to 0.9; p = 0.009) had longer overall survival (OS), while patients receiving opioids (HR 1.5, 95% CI 1.1 to 2.0, p = 0.010) had a significantly higher risk of death. CONCLUSION: Patients with advanced digestive tract cancer who were administered PPIs for gastritis/GERD indication, anticoagulants, or probiotics in combination with PD-1 inhibitors and antiangiogenic agents experienced improved clinical outcomes. However, opioid administration was linked to reduced OS in patients receiving combined therapy.

Investigation on the Preparation and Performances of Epoxy-Modified Asphalt Binder and Its Mixtures.

Epoxy-modified asphalt binder has been widely used in steel deck pavement due to its excellent properties and it is a potential candidate for long life pavements. However, its short reserve time limits its widespread application in pavement engineering. Therefore, this work developed a novel epoxy-modified asphalt binder composed of a laboratory-made curing agent as a solution. Firstly, optimization of preparation temperature of this new material was studied to balance the requirements of enough construction time and the material strength and elongation. The epoxy-modified asphalt binder, prepared at the optimal temperature of 140 °C, had a reserve time exceeding 120 min, whereas the tensile strength and the elongation at failure were 2.22 MPa and 216%, respectively, which satisfied the standard requirements of paving epoxy material well. Secondly, the asphalt mixture property tests demonstrate excellent high-temperature rutting resistance, water stability and low-temperature anti-cracking ability. Additionally, the compatibility and colloidal stability of this epoxy-modified asphalt binder were analyzed in terms of microphase structure. The uniform microphase distribution of this binder showed by the laser confocal microscope observation in both short-term aging case and long-term aging case, indicates the great compatibility between asphalt and epoxy resin during paving process and service life. Furthermore, fatigue tests were conducted to evaluate the long-term durability. The fatigue life of epoxy-modified asphalt mixtures increased by 435%, 427%, 342%, and 276% under the stress ratios of 0.3, 0.4, 0.5, and 0.6, respectively, compared to those of SBS-modified asphalt mixtures. All these results indicate that the new epoxy-modified asphalt material is promising for applications in pavement engineering, especially suitable for long-life road pavement.

Recent Progress of Vertical Graphene: Preparation, Structure Engineering, and Emerging Energy Applications.

Vertical graphene (VG) nanosheets have garnered significant attention in the field of electrochemical energy applications, such as supercapacitors, electro-catalysis, and metal-ion batteries. The distinctive structures of VG, including vertically oriented morphology, exposed, and extended edges, and separated few-layer graphene nanosheets, have endowed VG with superior electrode reaction kinetics and mass/electron transportation compared to other graphene-based nanostructures. Therefore, gaining insight into the structure-activity relationship of VG and VG-based materials is crucial for enhancing device performance and expanding their applications in the energy field. In this review, the authors first summarize the fabrication methods of VG structures, including solution-based, and vacuum-based techniques. The study then focuses on structural modulations through plasma-enhanced chemical vapor deposition (PECVD) to tailor defects and morphology, aiming to obtain desirable architectures. Additionally, a comprehensive overview of the applications of VG and VG-based hybrids d in the energy field is provided, considering the arrangement and optimization of their structures. Finally, the challenges and future prospects of VG-based energy-related applications are discussed.

Cellular senescence-related genes: predicting prognosis in hepatocellular carcinoma.

Recent studies have shown that the high incidence and low cure rate of hepatocellular carcinoma (HCC) have not improved significantly. Surgery and liver transplantation are the mainstays of prolonging the survival of HCC patients. However, the surgical resection rate of HCC patients is very low, and even after radical surgical resection, the recurrence rate at 5 years postoperatively remains high and the prognosis is very poor, so more treatment options are urgently needed. Increasing evidence suggests that cellular senescence is not only related to cancer development but may also be one of its primary driving factors. We aimed to establish a prognostic signature of senescence-associated genes to predict the prognosis and therapeutic response of HCC patients. The aim of this study was to develop a risk model associated with cellular senescence and to search for potential strategies to treat HCC. We divided HCC patients into two clusters and identified differentially expressed genes (DEGs) between clusters. In this study, low-risk patients had a better prognosis, higher levels of immune cell infiltration, and better efficacy to fluorouracil, Paclitaxel and Cytarabine chemotherapy compared to high-risk patients. To further identify potential biomarkers for HCC, we further validated the expression levels of the four signature genes in HCC and neighbouring normal tissues by in vitro experiments. In conclusion, we identified and constructed a relevant prognostic signature, which performed well in predicting the survival and treatment response of HCC patients. This helps to differentiate between low-score and high-risk HCC, and the results may contribute to precise treatment protocols in clinical practice.

Analysis on the salt tolerance of Nitraria sibirica Pall. based on Pacbio full-length transcriptome sequencing.

KEY MESSAGE: Nitraria sibirica Pall. regulates its tolerance to salt stress mainly by adjusting ion balance, modifying cell wall structure, and activating signal transduction pathways. N. sibirica, as a typical halophyte, can not only effectively restore saline-alkali land, but also has high economic value. However, studies on its salt tolerance at combining molecular and physiological levels were limited. In this study, the salt tolerance of N. sibirica was analyzed based on Pacbio full-length transcriptome sequencing, and the salt tolerance in the physiological level was verified by key genes. The results showed that 89,017 full-length transcripts were obtained, of which 84,632 sequences were annotated. A total of 86,482 coding sequences (CDS) were predicted and 6561 differentially expressed genes (DEGs) were identified. DEGs were significantly enriched in "sodium ion homeostasis", "response to osmotic stress", "reactive oxygen species metabolic process", "defense response by cell wall thickening", "signal transduction", etc. The expression levels for most of these DEGs increased under salt stress. A total of 69 key genes were screened based on weighted gene co-expression network analysis (WGCNA), of which 33 were first reported on salt tolerance. Moreover, NsRabE1c gene with the highest expression level was selected to verify its salt tolerance. Over-expression of NsRabE1c gene enhanced the germination potential and root length of transgenic Arabidopsis thaliana plants without salt treatment as compared to those of Col-0 and AtRabE1c mutant. The expression levels of NsRabE1c decreased in the growth stagnation phase, while significantly increased in the growth recovery phase under salt stress. We predicted that NsRabE1c gene help N. sibirica resist salt stress through the regulation of plant growth. The results of this study deepen the understanding of salinity resistance in N. sibirica.

Differential diagnosis of hepatocellular carcinoma and intrahepatic cholangiocarcinoma based on spatial and channel attention mechanisms.

BACKGROUND: The pre-operative non-invasive differential diagnosis of hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) mainly depends on imaging. However, the accuracy of conventional imaging and radiomics methods in differentiating between the two carcinomas is unsatisfactory. In this study, we aimed to establish a novel deep learning model based on computed tomography (CT) images to provide an effective and non-invasive pre-operative differential diagnosis method for HCC and ICC. MATERIALS AND METHODS: We retrospectively investigated the CT images of 395 HCC patients and 99 ICC patients who were diagnosed based on pathological analysis. To differentiate between HCC and ICC we developed a deep learning model called CSAM-Net based on channel and spatial attention mechanisms. We compared the proposed CSAM-Net with conventional radiomic models such as conventional logistic regression, least absolute shrinkage and selection operator regression, support vector machine, and random forest models. RESULTS: With respect to differentiating between HCC and ICC, the CSAM-Net model showed area under the receiver operating characteristic curve (AUC) values of 0.987 (accuracy = 0.939), 0.969 (accuracy = 0.914), and 0.959 (accuracy = 0.912) for the training, validation, and test sets, respectively, which were significantly higher than those of the conventional radiomics models (0.736-0.913 [accuracy = 0.735-0.912], 0.602-0.828 [accuracy = 0.647-0.818], and 0.638-0.845 [accuracy = 0.618-0.849], respectively. The decision curve analysis showed a high net benefit of the CSAM-Net model, which suggests potential efficacy in differentiating between HCC and ICC in the diagnosis of liver cancers. CONCLUSIONS: The proposed CSAM-Net model based on channel and spatial attention mechanisms provides an effective and non-invasive tool for the differential diagnosis of HCC and ICC on CT images, and has potential applications in diagnosis of liver cancers.

Efficacy and safety of PD­1 inhibitor plus antiangiogenic treatment in patients with unresectable biliary tract cancer: A multicenter retrospective study.

Immunotherapy and antiangiogenic therapy have shown promising clinical activity in patients with advanced biliary tract cancer (BTC) in clinical trials. As the combination of these two treatments for BTC is not well studied in the real world, the present study retrospectively analyzed the clinical outcomes of patients with unresectable BTC who received immunotherapy-antiangiogenesis combination therapy in a real-world setting. A three-center, retrospective study was performed on patients with unresectable BTC who received a combination of programmed death 1 inhibitor and antiangiogenic agent between March 26, 2019 and November 1, 2021 in China. In total, 68 patients were enrolled in the cohort. The objective response rate and disease control rate were 13.2 and 75.0%, respectively. The median time to progression, progression-free survival and overall survival were 8.2, 5.5 and 10.7 months, respectively. Adverse events of all grades occurred in 58 patients (85.3%). In conclusion, the present study demonstrated that immunotherapy-antiangiogenesis combination therapy may be considered a therapeutic option for patients with unresectable BTC. Further prospective investigations are needed.

Strip Surface Defect Detection Algorithm Based on YOLOv5.

In order to improve the detection accuracy of the surface defect detection of industrial hot rolled strip steel, the advanced technology of deep learning is applied to the surface defect detection of strip steel. In this paper, we propose a framework for strip surface defect detection based on a convolutional neural network (CNN). In particular, we propose a novel multi-scale feature fusion module (ATPF) for integrating multi-scale features and adaptively assigning weights to each feature. This module can extract semantic information at different scales more fully. At the same time, based on this module, we build a deep learning network, CG-Net, that is suitable for strip surface defect detection. The test results showed that it achieved an average accuracy of 75.9 percent (mAP50) in 6.5 giga floating-point operation (GFLOPs) and 105 frames per second (FPS). The detection accuracy improved by 6.3% over the baseline YOLOv5s. Compared with YOLOv5s, the reference quantity and calculation amount were reduced by 67% and 59.5%, respectively. At the same time, we also verify that our model exhibits good generalization performance on the NEU-CLS dataset.

Expression, tumor immune infiltration, and prognostic impact of HMGs in gastric cancer.

Background: In the past decade, considerable research efforts on gastric cancer (GC) have been expended, however, little advancement has been made owing to the lack of effective biomarkers and treatment options. Herein, we aimed to examine the levels of expression, mutations, and clinical relevance of HMGs in GC to provide sufficient scientific evidence for clinical decision-making and risk management. Methods: GC samples were obtained from The Cancer Genome Atlas (TCGA). University of California Santa Cruz (UCSC) XENA, Human Protein Atlas (HPA), Gene Expression Profiling Interactive Analysis (GEPIA), Kaplan-Meier Plotter, cBioPortal, GeneMANIA, STRING, LinkedOmics, and DAVID databases were employed. The "ggplot2" package in the R software (×64 3.6.3) was used to thoroughly analyze the effects of HMGs. qRT-PCR was performed to assess HMG levels in GC cell lines. Results: A total of 375 GC tissues and 32 paraneoplastic tissues were analyzed. The levels of HMGA1, HMGA2, HMGB1, HMGB2, HMGB3, HMGN1, HMGN2, and HMGN4 expression were increased in GC tissues relative to normal gastric tissues. HMGA1, HMGA2, HMGB1, HMGB2, and HMGB3 were highly expressed in GC cell lines. The OS was significantly different in the group showing low expressions of HMGA1, HMGA2, HMGB1, HMGB2, HMGB3, HMGN2, HMGN3, and HMGN5. There was a significant difference in RFS between the groups with low HMGA2, HMGB3, and high HMGN2 expression. The levels of HMGA2, HMGB3, and HMGN1 had a higher accuracy for prediction to distinguish GC from normal tissues (AUC value > 0.9). HMGs were tightly associated with immune infiltration and tumor immune escape and antitumor immunity most likely participates in HMG-mediated oncogenesis in GC. GO and KEGG enrichment analyses showed that HMGs played a vital role in the cell cycle pathway. Conclusions: Our results strongly suggest a vital role of HMGs in GC. HMGA2 and HMGB3 could be potential markers for prognostic prediction and treatment targets for GC by interrupting the cell cycle pathway. Our findings might provide renewed perspectives for the selection of prognostic biomarkers among HMGs in GC and may contribute to the determination of the optimal strategy for the treatment of these patients.

1,25(OH)2D3 Promotes Macrophage Efferocytosis Partly by Upregulating ASAP2 Transcription via the VDR-Bound Enhancer Region and ASAP2 May Affect Antiviral Immunity.

The active form of vitamin D3, i.e., 1,25(OH)2D3, exerts an anti-inflammatory effect on the immune system, especially macrophage-mediated innate immunity. In a previous study, we identified 1,25(OH)2D3-responsive and vitamin D receptor (VDR)-bound super-enhancer regions in THP-1 cells. Herein, we examined the transcriptional regulation of ArfGAP with SH3 Domain, Ankyrin Repeat and PH Domain 2 (ASAP2) (encoding a GTPase-activating protein) by 1,25(OH)2D3 through the top-ranked VDR-bound super-enhancer region in the first intron of ASAP2 and potential functions of ASAP2 in macrophages. First, we validated the upregulation of ASAP2 by 1,25(OH)2D3 in both THP-1 cells and macrophages. Subsequently, we identified three regulatory regions (i.e., the core, 1,25(OH)2D3-responsive, and inhibitory regions) in the VDR bound-enhancer of ASAP2. ASAP2 promoted RAC1-activity and macrophage efferocytosis in vitro. Next, we assessed the functions of ASAP2 by mass spectrometry and RNA sequencing analyses. ASAP2 upregulated the expressions of antiviral-associated genes and interacted with SAM and HD domain-containing deoxynucleoside triphosphate triphosphohydrolase 1 (SAMHD1). In vivo, vitamin D reduced the number of apoptotic cells in experimental autoimmune encephalomyelitis (EAE) and promoted macrophage efferocytosis in peritonitis without changing the mRNA level of ASAP2. Thus, we could better understand the regulatory mechanism underlying ASAP2 transcription and the function of ASAP2, which may serve as a potential treatment target against inflammatory diseases and virus infections.

Clinical applications of machine learning in the survival prediction and classification of sepsis: coagulation and heparin usage matter.

BACKGROUND: Sepsis is a life-threatening syndrome eliciting highly heterogeneous host responses. Current prognostic evaluation methods used in clinical practice are characterized by an inadequate effectiveness in predicting sepsis mortality. Rapid identification of patients with high mortality risk is urgently needed. The phenotyping of patients will assistant invaluably in tailoring treatments. METHODS: Machine learning and deep learning technology are used to characterize the patients' phenotype and determine the sepsis severity. The database used in this study is MIMIC-III and MIMIC-IV ('Medical information Mart for intensive care') which is a large, public, and freely available database. The K-means clustering is used to classify the sepsis phenotype. Convolutional neural network (CNN) was used to predict the 28-day survival rate based on 35 blood test variables of the sepsis patients, whereas a double coefficient quadratic multivariate fitting function (DCQMFF) is utilized to predict the 28-day survival rate with only 11 features of sepsis patients. RESULTS: The patients were grouped into four clusters with a clear survival nomogram. The first cluster (C_1) was characterized by low white blood cell count, low neutrophil, and the highest lymphocyte proportion. C_2 obtained the lowest Sequential Organ Failure Assessment (SOFA) score and the highest survival rate. C_3 was characterized by significantly prolonged PTT, high SIC, and a higher proportion of patients using heparin than the patients in other clusters. The early mortality rate of patients in C_3 was high but with a better long-term survival rate than that in C_4. C_4 contained septic coagulation patients with the worst prognosis, characterized by slightly prolonged partial thromboplastin time (PTT), significantly prolonged prothrombin time (PT), and high septic coagulation disease score (SIC). The survival rate prediction accuracy of CNN and DCQMFF models reached 92% and 82%, respectively. The models were tested on an external dataset (MIMIC-IV) and achieved good performance. A DCQMFF-based application platform was established for fast prediction of the 28-day survival rate. CONCLUSION: CNN and DCQMFF accurately predicted the sepsis patients' survival, while K-means successfully identified the phenotype groups. The distinct phenotypes associated with survival, and significant features correlated with mortality were identified. The findings suggest that sepsis patients with abnormal coagulation had poor outcomes, abnormal coagulation increase mortality during sepsis. The anticoagulation effects of appropriate heparin sodium treatment may improve extensive micro thrombosis-caused organ failure.

Efficacy and safety of PD-1 inhibitor combined with antiangiogenic therapy for unresectable hepatocellular carcinoma: A multicenter retrospective study.

BACKGROUND: Immunotherapy-antiangiogenesis combination therapy has achieved excellent survival outcomes in hepatocellular carcinoma (HCC) in clinical trials. However, the combination therapy for HCC outside clinical trials is not well studied, and predictive factors are lacking. Here, we retrospectively analyzed the efficacy and safety of immunotherapy-antiangiogenesis combination therapy in unresectable HCC patients in a real-world setting. METHODS: We conducted a four-center, retrospective study of unresectable HCC patients who received the combination of programmed death 1 (PD-1) inhibitor and antiangiogenic agent between April 2018 and July 2021 in China. RESULTS: In total, 136 patients were enrolled in the cohort. The objective response rate (ORR) and disease control rate (DCR) were 38.0% and 81.8%, respectively. The median time to progression (TTP), progression-free survival (PFS), and overall survival (OS) were 7.2, 7.3, and 19.6 months, respectively. The multivariate analysis indicated that ECOG performance status score (PS) 2 was a significantly independent negative factor of ORR. Moreover, ECOG PS 2, peritoneum metastasis and previous immunotherapy were found to be independent negative predictors of PFS. A shorter OS was associated with ECOG PS 2, peritoneum metastasis, the presence of previous immunotherapy, Child-Pugh stage B, and high alpha-fetoprotein (AFP) concentration. One hundred and twenty-five patients (91.9%) reported adverse events (AEs) with any grade. CONCLUSION: We elucidated the efficacy and safety of immunotherapy-antiangiogenesis combination therapy and identified potential predictors for response and survival in a real-world cohort of patients with unresectable HCC.

In Situ Monitored (N, O)-Doping of Flexible Vertical Graphene Films with High-Flux Plasma Enhanced Chemical Vapor Deposition for Remarkable Metal-Free Redox Catalysis Essential to Alkaline Zinc-Air Batteries.

Rechargeable zinc-air batteries (ZABs) have attracted great interests for emerging energy applications. Nevertheless, one of the major bottlenecks lies in the fabrication of bifunctional catalysts with high electrochemical activity, high stability, low cost, and free of precious and rare metals. Herein, a high-performance metal-free bifunctional catalyst is synthesized in a single step by regulating radicals within the recently invented high-flux plasma enhanced chemical vapor deposition (HPECVD) system equipped with in situ plasma diagnostics. Thus-derived (N, O)-doped vertical few-layer graphene film (VGNO) is of high areal population with perfect vertical orientation, tunable catalytic states, and configurations, thus enabling significantly enhanced electrochemical kinetic processes of oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) with reference to milestone achievements to date. Application of such VGNO to aqueous ZABs (A-ZABs) and flexible solid-state ZABs (S-ZABs) exhibited high discharge power density and excellent cycling stability, which remarkably outperformed ZABs using benchmarked precious-metal based catalysts. The current work provides a solid basis toward developing low-cost, resource-sustainable, and eco-friendly ZABs without using any metals for outstanding OER and ORR catalysis.

CD3+CD4-CD8- (Double-Negative) T Cells in Inflammation, Immune Disorders and Cancer.

The crucial role of CD4+ and CD8+ T cells in shaping and controlling immune responses during immune disease and cancer development has been well established and used to achieve marked clinical benefits. CD3+CD4-CD8- double-negative (DN) T cells, although constituting a rare subset of peripheral T cells, are gaining interest for their roles in inflammation, immune disease and cancer. Herein, we comprehensively review the origin, distribution and functions of this unique T cell subgroup. First, we focused on characterizing multifunctional DN T cells in various immune responses. DN regulatory T cells have the capacity to prevent graft-versus-host disease and have therapeutic value for autoimmune disease. T helper-like DN T cells protect against or promote inflammation and virus infection depending on the specific settings and promote certain autoimmune disease. Notably, we clarified the role of DN tumor-infiltrating lymphocytes and outlined the potential for malignant proliferation of DN T cells. Finally, we reviewed the recent advances in the applications of DN T cell-based therapy for cancer. In conclusion, a better understanding of the heterogeneity and functions of DN T cells may help to develop DN T cells as a potential therapeutic tool for inflammation, immune disorders and cancer.

The role of SPI1-TYROBP-FCER1G network in oncogenesis and prognosis of osteosarcoma, and its association with immune infiltration.

Osteosarcoma is an aggressive malignant bone sarcoma worldwide. A causal gene network with specific functions underlying both the development and progression of OS was still unclear. Here we firstly identified the differentially expressed genes (DEGs) between control and OS samples, and then defined the hub genes and top clusters in the protein-protein interaction (PPI) network of these DEGs. By focusing on the hub gene TYROBP in the top 1 cluster, a conserved TYROBP co-expression network was identified. Then the effect of the network on OS overall survival was analyzed. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses and Gene Set Enrichment Analysis (GSEA) were used to explore the functions of the network. XCell platform and ssGSEA algorithm were conducted to estimate the status of immune infiltration. ChEA3 platform, GSEA enrichment analysis, and Drug Pair Seeker (DPS) were used to predict the key transcription factor and its upstream signal. We identified the downregulated SPI1-TYROBP-FCER1G network in OS, which were significantly enriched in immune-related functions. We also defined a two-gene signature (SPI1/FCER1G) that can predict poorer OS overall survival and the attenuated immune infiltration when downregulated. The SPI1-TYROBP-FCER1G network were potentially initiated by transcription factor SPI1 and would lead to the upregulated CD86, MHC-II, CCL4/CXCL10/CX3CL1 and hence increased immune infiltrations. With this study, we could better explore the mechanism of OS oncogenesis and metastasis for developing new therapies.

Tetrandrine attenuates ischemia/reperfusion­induced neuronal damage in the subacute phase.

Ischemic stroke, the third leading cause of disability globally, imposes a notable economic burden. Tetrandrine (Tet), which has been widely used clinically, exhibits potential protective effects against stroke. However, there has been little pre­clinical research to evaluate the therapeutic effects of Tet on stroke. The present study investigated the beneficial effect of Tet on ischemia­reperfusion (I/R) injury and its underlying mechanism in rats. Rats were subjected to occlusion of the middle cerebral artery, then treated with Tet (30 mg/kg/day, intraperitoneal) in the subacute phase for 7 days. In order to detect the effects of Tet on the behavior of rats, modified neurological severity score and longa behavior, grasping capability and inclined plane tests were conducted on days 1, 3 and 7 following cerebral ischemia. In addition, neuronal apoptosis in the cortex and hippocampus following ischemia was assessed by Nissl staining and TUNEL assay. Finally, oxidative stress was evaluated by measurement of free radicals and immunofluorescence staining of LC3 was used to assess autophagy. Tet improved neurological function and decreased infarct volume in I/R injury rats. Tet also prevented neuronal apoptosis in the cortex and hippocampus region. In addition, Tet protected against oxidative damage following ischemia, which was reflected by decreased levels of nitric oxide and malondialdehyde and increased levels of glutathione (GSH) and GSH peroxidase. In addition, the expression levels of the autophagy marker LC3 decreased in the Tet treatment group. In conclusion, Tet attenuated I/R­induced neuronal damage in the subacute phase by decreasing oxidative stress, apoptosis and autophagy.

Sputtered Ga-Doped SnOx Electron Transport Layer for Large-Area All-Inorganic Perovskite Solar Cells.

The scalability processing of all functional layers in perovskite solar cells (PSCs) is one of the critical challenges in the commercialization of perovskite photovoltaic technology. In response to this issue, a large-area and high-quality gallium-doped tin oxide (Ga-SnOx) thin film is deposited by direct current magnetron sputtering and applied in CsPbBr3 all-inorganic PSCs as an electron transport layer (ETL). It is found that oxygen defects of SnOx can be remarkably offset by regulating oxygen flux and acceptor-like Ga doping level, resulting in higher carrier mobility and suitable energy level alignment, which is beneficial in accelerating electron extraction and suppressing charge recombination at the perovskite/ETL interface. At the optimal O2 flux (12 sccm) and Ga doping level (5%), the device based on sputtered Ga-SnOx ETL without any interface modification shows a power conversion efficiency (PCE) of 8.13%, which is significantly higher than that of undoped SnOx prepared by sputtering or spin coating. Furthermore, a PCE of 5.98% for a device with an active area of 1 cm2 is obtained, demonstrating great potential in fabricating efficient and stable large-area PSCs.