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Chronic liver disease is a significant public health issue that can lead to considerable morbidity and mortality, imposing an enormous burden on healthcare resources. Understanding the mechanisms underlying chronic liver disease pathogenesis and developing effective treatment strategies are urgently needed. In this regard, the activation of liver resident macrophages, namely Kupffer cells, plays a vital role in liver inflammation and fibrosis. Macrophages display remarkable plasticity and can polarize into different phenotypes according to diverse microenvironmental stimuli. The polarization of macrophages into M1 pro-inflammatory or M2 anti-inflammatory phenotypes is regulated by complex signaling pathways such as the PI3K/Akt pathway. This review focuses on investigating the potential of using plant chemicals targeting the PI3K/Akt pathway for treating chronic liver disease while elucidating the polarization mechanism of macrophages under different microenvironments. Studies have demonstrated that inhibiting M1-type macrophage polarization or promoting M2-type polarization can effectively combat chronic liver diseases such as alcoholic liver disease, non-alcoholic fatty liver disease, and liver fibrosis. The PI3K/Akt pathway acts as a pivotal modulator of macrophage survival, migration, proliferation, and their responses to metabolism and inflammatory signals. Activating the PI3K/Akt pathway induces anti-inflammatory cytokine expression, resulting in the promotion of M2-like phenotype to facilitate tissue repair and resolution of inflammation. Conversely, inhibiting PI3K/Akt signaling could enhance the M1-like phenotype, which exacerbates liver damage. Targeting the PI3K/Akt pathway has tremendous potential as a therapeutic strategy for regulating macrophage polarization and activity to treat chronic liver diseases with plant chemicals, providing new avenues for liver disease treatment.

Abstract Spintronic devices are considered as one of the most promising technologies for non‐volatile memory and computing. However, two crucial drawbacks, that is, lack of intrinsic multi‐level operation and low on/off ratio, greatly hinder their further application for advanced computing concepts, such as deep neural network (DNN) accelerator. In this paper, a spintronic multi‐level memory unit with high on/off ratio is proposed by integrating several series‐connected magnetic tunnel junctions (MTJs) with perpendicular magnetic anisotropy (PMA) and a Schottky diode in parallel. Due to the rectification effect on the PMA MTJ, an on/off ratio over 100, two orders of magnitude higher than intrinsic values, is obtained under proper proportion of alternating current and direct current. Multiple resistance states are stably achieved and can be reconfigured by spin transfer torque effect. A computing‐in‐memory architecture based DNN accelerator for image classification with the experimental parameters of this proposal to evidence its application potential is also evaluated. This work can satisfy the rigorous requirements of DNN for memory unit and promote the development of high‐accuracy and robust artificial intelligence applications.

Objective: Ischemic stroke leads to cellular death and tissue damage by depriving the areas of glucose and oxygen supplies. The effective treatment of stroke remains a challenge for modern medicine. This study used an oxygen-glucose deprivation (OGD) model of human umbilical vein endothelial cells (HUVECs) to mimic ischemic injuries and explored the role and mechanism of intelectin-1.Methods: Intelectin-1 was transduced into the HUVECs using a lentiviral vector. The PI3K/Akt signaling was examined in intelectin-induced eNOS phosphorylation. The PI3K inhibitor LY294002 was dealed in HUVECs.Results: Our results demonstrated an increase in capillary density, decrease in apoptotic cells, and increase in HIF-1α protein expression following intelectin-1 treatment. Real-time PCR and Western blotting revealed the increased intelectin-1 expression alongside eNOS and Akt phosphorylation with enhanced bcl-2 expression under OGD. Capillary density decreased significantly after LY294002 treatment.Conclusion: These results suggest intelectin-1 promotes angiogenesis, inhibits oxidative stress and reduces apoptosis by stimulating the Akt-eNOS signaling pathway in response to ischemia in vitro.

Introduction Promising evidence is emerging for the procognitive, anti-inflammatory and neuroprotective properties of dietary flavonoids, particularly anthocyanins that provide red, purple and blue plant pigments.Methods and analysis The ‘Food for Thought’ study is a multicentre, 6-month randomised, parallel 3-arm clinical trial. Its primary aim is to investigate whether anthocyanin consumption, either through diet or supplementation, can prevent memory loss progression and improve inflammatory and cardiovascular health in older adults at risk for dementia. Eligible participants will include those aged 60–85 years with a diagnosis of amnestic mild cognitive impairment or with a self-referral of memory concerns and scoring ≤13 on the Memory Index Score within the Telephone Montreal Cognitive Assessment screening test. Participants will be randomised to one of three arms: High anthocyanin (‘purple foods’) diet (aiming for a target of 250 mg anthocyanins/day); freeze-dried product derived from blackcurrants (250 mg anthocyanins/day); or control (coloured maltose powder). The primary outcome is auditory anterograde memory functioning assessed by the Buschke and Grober Free and Cued Selective Reminding Test-Immediate Recall. Secondary outcomes are additional cognitive functions including processing speed, working memory, aspects of executive functioning (attentional shifting and word generativity) and premorbid estimate as well as subjective memory problems and self-reported depression symptoms. Additional secondary outcomes are blood pressure, inflammatory biomarkers, brain-derived neurotrophic factor, fatty acid profile, apolipoprotein E and polyphenol metabolites, gut microbiota composition and function and vascular and microvascular endothelial function tests. Repeated measures analysis of variance and/or mixed linear modelling will evaluate changes over time, with the inclusion of covariates.Ethics and dissemination Ethics approval has been obtained from the Greater Western Human Research Ethics Committee (2021/ETH12083). A Consumer Advisory Group was established to guide and review the protocol and dissemination strategy. The results of this trial are intended to be published in a peer-reviewed journal.Trial sponsor National Health and Medical Research Centre Dementia Collaborative Research Centre.Start date of clinical trial: 02 September 2022.Expected end date: 11 October 2024.Trial registration number ACTRN12622000065796.

Abstract Strategies to improve T cell therapy efficacy in solid tumors such as hepatocellular carcinoma (HCC) are urgently needed. The common cytokine receptor γ chain (γc) family cytokines such as IL-2, IL-7, IL-15 and IL-21 play fundamental roles in T cell development, differentiation and effector phases. This study aims to determine the combination effects of IL-21 in T cell therapy against HCC and investigate optimized strategies to utilize the effect of IL-21 signal in T cell therapy. The antitumor function of AFP-specific T cell receptor-engineered T cells (TCR-T) was augmented by exogenous IL-21 in vitro and in vivo. IL-21 enhanced proliferation capacity, promoted memory differentiation, downregulated PD-1 expression and alleviated apoptosis in TCR-T after activation. A novel engineered IL-21 receptor was established, and TCR-T armed with the novel engineered IL-21 receptors (IL-21R-TCR-T) showed upregulated phosphorylated STAT3 expression without exogenous IL-21 ligand. IL-21R-TCR-T showed better proliferation upon activation and superior antitumor function in vitro and in vivo. IL-21R-TCR-T exhibited a less differentiated, exhausted and apoptotic phenotype than conventional TCR-T upon repetitive tumor antigen stimulation. The novel IL-21 receptor in our study programs powerful TCR-T and can avoid side effects induced by IL-21 systemic utilization. The novel IL-21 receptor creates new opportunities for next-generation TCR-T against HCC.

Abstract Background Autophagy is a lysosome-dependent degradation pathway that regulates macrophage activation, differentiation, and polarization. Autophagy related 5 (Atg5) is a key protein involved in phagocytic membrane elongation in autophagic vesicles that forms a complex with Atg12 and Atg16L1. Alterations in Atg5 are related to both acute and chronic kidney diseases in experimental models. However, the role of macrophage-expressed Atg5 in acute kidney injury remains unclear. Methods Using a myeloid cell-specific Atg5 knockout (MΦ atg5 −/−) mouse, we established renal ischemia/reperfusion and unilateral ureteral obstruction models to evaluate the role of macrophage Atg5 in renal macrophage migration and fibrosis. Results Based on changes in the serum urea nitrogen and creatinine levels, Atg5 deletion had a minimal effect on renal function in the early stages after mild injury; however, MΦ atg5 −/− mice had reduced renal fibrosis and reduced macrophage recruitment after 4 weeks of ischemia/reperfusion injury and 2 weeks of unilateral ureteral obstruction injury. Atg5 deficiency impaired the CCL20-CCR6 axis after severe ischemic kidneys. Chemotactic responses of bone marrow-derived monocytes (BMDMs) from MΦ atg5 −/− mice to CCL20 were significantly attenuated compared with those of wild-type BMDMs, and this might be caused by the inhibition of PI3K, AKT, and ERK1/2 activation. Conclusions Our data indicate that Atg5 deficiency decreased macrophage migration by impairing the CCL20-CCR6 axis and inhibited M2 polarization, thereby improving kidney fibrosis.

Computing-in-memory (CIM) is proposed to alleviate the processor-memory data transfer bottleneck in traditional von Neumann architectures, and spintronics-based magnetic memory has demonstrated many facilitation in implementing CIM paradigm. Since hardware security has become one of the major concerns in circuit designs, this article, for the first time, investigates spin-based computing-in-memory (SpinCIM) from a security perspective. We focus on two fundamental questions: (1) How can the new SpinCIM computing paradigm be exploited to enhance hardware security?; (2) What security concerns has this new SpinCIM computing paradigm incurred?. [ABSTRACT FROM AUTHOR]

Abstract Background Microbial communities in both natural and applied settings reliably carry out myriads of functions, yet how stable these taxonomically diverse assemblages can be and what causes them to transition between states remains poorly understood. We studied monthly activated sludge (AS) samples collected over 9 years from a full-scale wastewater treatment plant to answer how complex AS communities evolve in the long term and how the community functions change when there is a disturbance in operational parameters. Results Here, we show that a microbial community in activated sludge (AS) system fluctuated around a stable average for 3 years but was then abruptly pushed into an alternative stable state by a simple transient disturbance (bleaching). While the taxonomic composition rapidly turned into a new state following the disturbance, the metabolic profile of the community and system performance remained remarkably stable. A total of 920 metagenome-assembled genomes (MAGs), representing approximately 70% of the community in the studied AS ecosystem, were recovered from the 97 monthly AS metagenomes. Comparative genomic analysis revealed an increased ability to aggregate in the cohorts of MAGs with correlated dynamics that are dominant after the bleaching event. Fine-scale analysis of dynamics also revealed cohorts that dominated during different periods and showed successional dynamics on seasonal and longer time scales due to temperature fluctuation and gradual changes in mean residence time in the reactor, respectively. Conclusions Our work highlights that communities can assume different stable states under highly similar environmental conditions and that a specific disturbance threshold may lead to a rapid shift in community composition. Video Abstract

Objectives: The purpose of this study was to investigate the role of 13 m5C-related regulators in colon adenocarcinoma (COAD) and determine their prognostic value.Methods: Gene expression and clinicopathological data were obtained from The Cancer Genome Atlas (TCGA) datasets. The expression of m5C-related regulators was analyzed with clinicopathological characteristics and alterations within m5C-related regulators. Subsequently, different subtypes of patients with COAD were identified. Then, the prognostic value of m5C-related regulators in COAD was confirmed via univariate Cox regression and least absolute shrinkage and selection operator (LASSO) Cox regression analyses. The prognostic value of risk scores was evaluated using the Kaplan-Meier method, receiver operating characteristic (ROC) curve. The correlation between the two m5C-related regulators, risk score, and clinicopathological characteristics were explored. Additionally, Gene Set Enrichment Analysis (GSEA), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and Gene Ontology (GO) analysis were performed for biological functional analysis. Finally, the expression level of two m5C-related regulators in clinical samples and cell lines was detected by quantitative reverse transcription-polymerase chain reaction and through the Human Protein Atlas database.Results: m5C-related regulators were found to be differentially expressed in COAD with different clinicopathological features. We observed a high alteration frequency in these genes, which were significantly correlated with their mRNA expression levels. Two clusters with different prognostic features were identified. Based on two independent prognostic m5C-related regulators (NSUN6 and ALYREF), a risk signature with good predictive significance was constructed. Univariate and multivariate Cox regression analyses suggested that the risk score was an independent prognostic factor. Furthermore, this risk signature could serve as a prognostic indicator for overall survival in subgroups of patients with different clinical characteristics. Biological processes and pathways associated with cancer, immune response, and RNA processing were identified.Conclusion: We revealed the genetic signatures and prognostic values of m5C-related regulators in COAD. Together, this has improved our understanding of m5C RNA modification and provided novel insights to identify predictive biomarkers and develop molecular targeted therapy for COAD.

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.

Background: As early gastric cancer (EGC) has a far better prognosis than advanced gastric cancer (GC), early diagnosis and treatment are essential. However, understanding the mechanism of the process from gastric precancerous lesion (GPL) becoming EGC has made little advances. Besides, biomarkers that can monitor the progression of GPL-to-GC are still much insufficient.Methods: Key gene modules associated with GPL progression to EGC were identified by integrating two GPL-related data sets, GSE55696 and GSE130823, using the WGCNA method. Combining with the TCGA-STAD cohort, hub genes were identified. Immunofluorescence was conducted to validate the expression. To explore the implication of hub genes in GPL malignant transformation, a correlation test was conducted to identify their co-expression genes, co-expression cytokines, and co-expression immune cells. Least absolute shrinkage and selection operator (LASSO) Cox regression was applied to shrink CXCR4-related predictors and construct a prognostic model. Functional enrichment was applied for exploring the potential mechanism.Results: The green module in GSE55696 and the yellow module in GSE130823 were regarded as key gene modules associated with GPL progression to EGC, and 219 intersection genes from them were mainly enriched in critical immune biological processes. Combining with the TCGA-STAD cohort, CXCR4 was identified as a novel biomarker correlated with the malignant transformation of GPL, the positive rate of which was increased with GPL progression according to immunofluorescence. CXCR4 co-expression genes were found mainly involved in regulation of actin. CXCR4 co-expression cytokines were enriched in regulation of chemotaxis, cell chemotaxis, mononuclear cell migration, leukocyte chemotaxis, etc. As for co-expression immune cells, the expression level of CXCR4 was positively correlated with the abundance of macrophages but negatively correlated with that of effector memory T cells and NKT cells during GPL malignant transformation. In addition, the CXCR4-related prognostic model was able to predict the prognosis of GC and serve as an independent predictor for overall survival (OS).Conclusions: CXCR4 was a novel biomarker correlated with malignant transformation of GPL and played a vital role in the control of tumor immunity. CXCR4 is possible to serve as a therapeutic target for malignant transformation of GPL.

ObjectivesThe purpose of this study was to investigate the role of m6A-related lncRNAs in gastric adenocarcinoma (STAD) and to determine their prognostic value.MethodsGene expression and clinicopathological data were obtained from The Cancer Genome Atlas (TCGA) database. Correlation analysis and univariate Cox regression analysis were conducted to identify m6A-related prognostic lncRNAs. Subsequently, different clusters of patients with STAD were identified via consensus clustering analysis, and a prognostic signature was established by least absolute shrinkage and selection operator (LASSO) Cox regression analyses. The clinicopathological characteristics, tumor microenvironment (TME), immune checkpoint genes (ICGs) expression, and the response to immune checkpoint inhibitors (ICIs) in different clusters and subgroups were explored. The prognostic value of the prognostic signature was evaluated using the Kaplan-Meier method, receiver operating characteristic curves, and univariate and multivariate regression analyses. Additionally, Gene Set Enrichment Analysis (GSEA), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and Gene Ontology (GO) analysis were performed for biological functional analysis.ResultsTwo clusters based on 19 m6A-related lncRNAs were identified, and a prognostic signature comprising 14 m6A-related lncRNAs was constructed, which had significant value in predicting the OS of patients with STAD, clinicopathological characteristics, TME, ICGs expression, and the response to ICIs. Biological processes and pathways associated with cancer and immune response were identified.ConclusionsWe revealed the role and prognostic value of m6A-related lncRNAs in STAD. Together, our finding refreshed the understanding of m6A-related lncRNAs and provided novel insights to identify predictive biomarkers and immunotherapy targets for STAD.

The prognostic prediction of hepatocellular carcinoma (HCC) is still challenging. Immune cells play a crucial role in tumor initiation, progression, and drug resistance. However, prognostic value of immune-related genes in HCC remains to be further clarified. In this study, the mRNA expression profiles and corresponding clinical information of HCC patients were downloaded from public databases. Then, we estimated the abundance of immune cells and identified the differentially infiltrated and prognostic immune cells. The weighted gene co-expression network analysis (WGCNA) was performed to identify immune-related genes in TCGA cohort and GEO cohort. The least absolute shrinkage and selection operator (LASSO) Cox regression model was applied to establish a risk-scoring model in the TCGA cohort. HCC patients from the GSE14520 datasets were utilized for risk model validation. Our results found that high level of dendritic cell (DC) infiltration was associated with poor prognosis. Over half of the DC-related genes (58.2%) were robustly differentially expressed between HCC and normal specimens in the TCGA cohort. 17 differentially expressed genes (DEGs) were found to be significantly associated with overall survival (OS) by univariate Cox regression analysis. A 12-gene risk-scoring model was established to evaluate the prognosis of HCC. The high-risk group exhibits significantly lower OS rate of HCC patients than the low-risk group. The risk-scoring model shows benign predictive capacity in both GEO dataset and TCGA dataset. The 12-gene risk-scoring model may independently perform prognostic value for HCC patients. Receiver operating characteristic (ROC) curve analysis of the risk-scoring model in GEO cohort and TCGA cohort performed well in predicting OS. Taken together, the 12-gene risk-scoring model could provide prognostic and potentially predictive information for HCC. SDC3, NCF2, BTN3A3, and WARS were noticed as a novel prognostic factor for HCC.

Background & Aims: Gastric cancer is the common malignancies from cancer worldwide. Endoscopy is currently the most effective method to detect early gastric cancer (EGC). However, endoscopy is not infallible and EGC can be missed during endoscopy. Artificial intelligence (AI)-assisted endoscopic diagnosis is a recent hot spot of research. We aimed to quantify the diagnostic value of AI-assisted endoscopy in diagnosing EGC.Method: The PubMed, MEDLINE, Embase and the Cochrane Library Databases were searched for articles on AI-assisted endoscopy application in EGC diagnosis. The pooled sensitivity, specificity, and area under the curve (AUC) were calculated, and the endoscopists' diagnostic value was evaluated for comparison. The subgroup was set according to endoscopy modality, and number of training images. A funnel plot was delineated to estimate the publication bias.Result: 16 studies were included in this study. We indicated that the application of AI in endoscopic detection of EGC achieved an AUC of 0.96 (95% CI, 0.94–0.97), a sensitivity of 86% (95% CI, 77–92%), and a specificity of 93% (95% CI, 89–96%). In AI-assisted EGC depth diagnosis, the AUC was 0.82(95% CI, 0.78–0.85), and the pooled sensitivity and specificity was 0.72(95% CI, 0.58–0.82) and 0.79(95% CI, 0.56–0.92). The funnel plot showed no publication bias.Conclusion: The AI applications for EGC diagnosis seemed to be more accurate than the endoscopists. AI assisted EGC diagnosis was more accurate than experts. More prospective studies are needed to make AI-aided EGC diagnosis universal in clinical practice.

Background: Human glypican-3 (hGPC3) is a protein highly expressed in hepatocellular carcinoma (HCC) but limited in normal tissues, making it an ideal target for immunotherapy. The adoptive transfer of hGPC3-specific chimeric antigen receptor T (CAR-T) cells for HCC treatment has been conducted in clinical trials. Due to the rigid construction, conventional CAR-T cells have some intrinsic limitations, like uncontrollable overactivation and inducing severe cytokine release syndrome. Methods: We redesigned the hGPC3-specific CAR by splitting the traditional CAR into two parts. By using coculturing assays and a xenograft mouse model, the in vitro and in vivo cytotoxicity and cytokine release of the split anti-hGPC3 CAR-T cells were evaluated against various HCC cell lines and compared with conventional CAR-T cells. Results: In vitro data demonstrated that split anti-hGPC3 CAR-T cells could recognize and lyse hGPC3 + HepG2 and Huh7 cells in a dose-dependent manner. Impressively, split anti-hGPC3 CAR-T cells produced and released a significantly lower amount of proinflammatory cytokines, including IFN-γ, TNF-α, IL-6, and GM-CSF, than conventional CAR-T cells. When injected into immunodeficient mice inoculated subcutaneously with HepG2 cells, our split anti-hGPC3 CAR-T cells could suppress HCC tumor growth, but released significantly lower levels of cytokines than conventional CAR-T cells. Conclusions: We describe here for the first time the use of split anti-hGPC3 CAR-T cells to treat HCC; split anti-hGPC3 CAR-T cells could suppress tumor growth and reduce cytokine release, and represent a more versatile and safer alternative to conventional CAR-T cells treatment.

Abstract Background Antimicrobial agents have been widely used in animal farms to prevent and treat animal diseases and to promote growth. Antimicrobial agents may change the bacterial community and enhance the resistome in animal feces. We used metagenome-wide analysis to investigate the changes in bacterial community, variations in antibiotic resistance genes (ARGs), and their bacterial hosts in the feces of broiler chickens over a full-treatment course of chlortetracycline at low and therapeutic dose levels. Results The effects of chlortetracycline on resistome were dependent on the specific ARG subtypes and not simply the overall community-level ARGs. Therapeutic dose of chlortetracycline promoted the abundance of tetracycline resistance genes (tetA and tetW) and inhibited multidrug resistance genes (mdtA, mdtC, mdtK, ompR, and TolC). The therapeutic dose of chlortetracycline led to loss of Proteobacteria mainly due to the decrease of Escherichia/Shigella (from 72 to 58%). Inhibition of Escherichia by chlortetracycline was the primary reason for the decrease of genes resistant to multiple drugs in the therapeutic dose group. The ARG host Bifidobacterium were enriched due to tetW harbored by Bifidobacterium under chlortetracycline treatment. Escherichia was always the major host for multidrug resistance genes, whereas the primary host was changed from Escherichia to Klebsiella for aminoglycoside resistance genes with the treatment of therapeutic dose of chlortetracycline. Conclusions We provided the first metagenomic insights into antibiotic-mediated alteration of ARG-harboring bacterial hosts at community-wide level in chicken feces. These results indicated that the changes in the structure of antibiotic-induced feces microbial communities accompany changes in the abundance of bacterial hosts carrying specific ARGs in the feces microbiota. These findings will help to optimize therapeutic schemes for the effective treatment of antibiotic resistant pathogens in poultry farms. Graphical abstract Resistome variations in faecal microbiome of chickens exposed to chlortetracycline

Abstract Background Bacterial communities are essential to the biogeochemical cycle in riverine ecosystems. However, little is presently known about the integrated biogeography of planktonic and sedimentary bacterial communities in large rivers. Results This study provides the first spatiotemporal pattern of bacterial communities in the Yangtze River, the largest river in Asia with a catchment area of 1,800,000 km2. We find that sedimentary bacteria made larger contributions than planktonic bacteria to the bacterial diversity of the Yangzte River ecosystem with the sediment subgroup providing 98.8% of 38,906 operational taxonomic units (OTUs) observed in 280 samples of synchronous flowing water and sediment at 50 national monitoring stations covering a 4300 km reach. OTUs within the same phylum displayed uniform seasonal variations, and many phyla demonstrated autumn preference throughout the length of the river. Seasonal differences in bacterial communities were statistically significant in water, whereas bacterial communities in both water and sediment were geographically clustered according to five types of landforms: mountain, foothill, basin, foothill-mountain, and plain. Interestingly, the presence of two huge dams resulted in a drastic fall of bacterial taxa in sediment immediately downstream due to severe riverbed scouring. The integrity of the biogeography is satisfactorily interpreted by the combination of neutral and species sorting perspectives in meta-community theory for bacterial communities in flowing water and sediment. Conclusions Our study fills a gap in understanding of bacterial communities in one of the world’s largest river and highlights the importance of both planktonic and sedimentary communities to the integrity of bacterial biogeographic patterns in a river subject to varying natural and anthropogenic impacts.