Lipopolysaccharide modification enhances the inhibitory effect of clodronate liposomes on hepatic fibrosis by depletion of macrophages and hepatic stellate cells.

Hepatic fibrosis is a complex chronic liver disease in which both macrophages and hepatic stellate cells (HSCs) play important roles. Many studies have shown that clodronate liposomes (CLD-lipos) effectively deplete macrophages. However, no liposomes have been developed that target both HSCs and macrophages. This study aimed to evaluate the therapeutic efficacy of lipopolysaccharide-coupled clodronate liposomes (LPS-CLD-lipos) and the effects of liposomes size on hepatic fibrosis. Three rat models of hepatic fibrosis were established in vivo; diethylnitrosamine (DEN), bile duct ligation (BDL), and carbon tetrachloride (CCl4). Hematoxylin and eosin staining and serological liver function indices were used to analyze pathological liver damage. Masson's trichrome and Sirius red staining were used to evaluate the effect of liposomes on liver collagen fibers. The hydroxyproline content in liver tissues was determined. In vitro cell counting kit-8 (CCK-8) and immunofluorescence assays were used to further explore the effects of LPS modification and liposomes size on the killing of macrophages and HSCs. Both in vitro and in vivo experiments showed that 200 nm LPS-CLD-lipos significantly inhibited hepatic fibrosis and the abnormal deposition of collagen fibers in the liver and improved the related indicators of liver function. Further results showed that 200 nm LPS-CLD-lipos increased the clearance of macrophages and induced apoptosis of hepatic stellate cells, significantly. The present study demonstrated that 200 nm LPS-CLD-lipos could significantly inhibit hepatic fibrosis and improve liver function-related indices and this study may provide novel ideas and directions for hepatic fibrosis treatment.

Impaired autophagic flux in the human brain after traumatic brain injury.

Emerging evidence indicates that dysfunctional autophagic flux significantly contributes to the pathology of experimental traumatic brain injury (TBI). The current study aims to clarify its role post-TBI using brain tissues from TBI patients. Histological examinations, including hematoxylin and eosin, Nissl staining, and brain water content analysis, were employed to monitor brain damage progression. Electron microscopy was used to visualize autophagic vesicles. Western blotting and immunohistochemistry were performed to analyze the levels of important autophagic flux-related proteins such as Beclin1, autophagy-related protein 5, lipidated microtubule-associated protein light-chain 3 (LC3-II), autophagic substrate sequestosome 1 (SQSTM1/p62), and cathepsin D (CTSD), a lysosomal enzyme. Immunofluorescence assays evaluated LC3 colocalization with NeuN, P62, or CTSD, and correlation analysis linked autophagy-related protein levels with brain water content and Nissl bodies. Early-stage TBI results showed increased autophagic vesicles and LC3-positive neurons, suggesting autophagosome accumulation due to enhanced initiation and reduced clearance. As TBI progressed, LC3-II and P62 levels increased, while CTSD levels decreased. This indicates autophagosome overload from impaired degradation rather than increased initiation. The study reveals a potential association between worsening brain damage and impaired autophagic flux post-TBI, positioning improved autophagic flux as a viable therapeutic target for TBI.

The signature of cuproptosis-related immune genes predicts the tumor microenvironment and prognosis of prostate adenocarcinoma.

Background: Cuproptosis plays a crucial role in cancer, and different subtypes of cuproptosis have different immune profiles in prostate adenocarcinoma (PRAD). This study aimed to investigate immune genes associated with cuproptosis and develop a risk model to predict prognostic characteristics and chemotherapy/immunotherapy responses of patients with PRAD. Methods: The CIBERSORT algorithm was used to evaluate the immune and stromal scores of patients with PRAD in The Cancer Genome Atlas (TCGA) cohort. Validation of differentially expressed genes DLAT and DLD in benign and malignant tissues by immunohistochemistry, and the immune-related genes of DLAT and DLD were further screened. Univariable Cox regression were performed to select key genes. Least absolute shrinkage and selection operator (LASSO)-Cox regression analyse was used to develop a risk model based on the selected genes. The model was validated in the TCGA, Memorial Sloan-Kettering Cancer Center (MSKCC) and Gene Expression Omnibus (GEO) datasets, as well as in this study unit cohort. The genes were examined via functional enrichment analysis, and the tumor immune features, tumor mutation features and copy number variations (CNVs) of patients with different risk scores were analysed. The response of patients to multiple chemotherapeutic/targeted drugs was assessed using the pRRophetic algorithm, and immunotherapy was inferred by the Tumor Immune Dysfunction and Exclusion (TIDE) and immunophenoscore (IPS). Results: Cuproptosis-related immune risk scores (CRIRSs) were developed based on PRLR, DES and LECT2. High CRIRSs indicated poor overall survival (OS), disease-free survival (DFS) in the TCGA-PRAD, MSKCC and GEO datasets and higher T stage and Gleason scores in TCGA-PRAD. Similarly, in the sample collected by the study unit, patients with high CRIRS had higher T-stage and Gleason scores. Additionally, higher CRIRSs were negatively correlated with the abundance of activated B cells, activated CD8+ T cells and other stromal or immune cells. The expression of some immune checkpoints was negatively correlated with CRIRSs. Tumor mutational burden (TMB), mutant-allele tumor heterogeneity (MATH) and copy number variation (CNV) scores were all higher in the high-CRIRS group. Multiple chemotherapeutic/targeted drugs and immunotherapy had better responsiveness in the low-CRIRS group. Conclusion: Overall, lower CRIRS indicated better response to treatment strategies and better prognostic outcomes.

Immunological mechanisms of inflammatory diseases caused by gut microbiota dysbiosis: A review.

The gut microbiota is indispensable for maintaining host health by enhancing the host's digestive capacity, safeguarding the intestinal epithelial barrier, and preventing pathogen invasion. Additionally, the gut microbiota exhibits a bidirectional interaction with the host immune system and promotes the immune system of the host to mature. Dysbiosis of the gut microbiota, primarily caused by factors such as host genetic susceptibility, age, BMI, diet, and drug abuse, is a significant contributor to inflammatory diseases. However, the mechanisms underlying inflammatory diseases resulting from gut microbiota dysbiosis lack systematic categorization. In this study, we summarize the normal physiological functions of symbiotic microbiota in a healthy state and demonstrate that when dysbiosis occurs due to various external factors, the normal physiological functions of the gut microbiota are lost, leading to pathological damage to the intestinal lining, metabolic disorders, and intestinal barrier damage. This, in turn, triggers immune system disorders and eventually causes inflammatory diseases in various systems. These discoveries provide fresh perspectives on how to diagnose and treat inflammatory diseases. However, the unrecognized variables that might affect the link between inflammatory illnesses and gut microbiota, need further studies and extensive basic and clinical research will still be required to investigate this relationship in the future.

TWEAK Signaling-Induced ID1 Expression Drives Malignant Transformation of Hepatic Progenitor Cells During Hepatocarcinogenesis.

The malignant transformation of hepatic progenitor cells (HPCs) in the inflammatory microenvironment is the root cause of hepatocarcinogenesis. However, the potential molecular mechanisms are still elusive. The HPCs subgroup is identified by single-cell RNA (scRNA) sequencing and the phenotype of HPCs is investigated in the primary HCC model. Bulk RNA sequencing (RNA-seq) and proteomic analyses are also performed on HPC-derived organoids. It is found that tumors are formed from HPCs in peritumor tissue at the 16th week in a HCC model. Furthermore, it is confirmed that the macrophage-derived TWEAK/Fn14 promoted the expression of inhibitor of differentiation-1 (ID1) in HPCs via NF-κB signaling and a high level of ID1 induced aberrant differentiation of HPCs. Mechanistically, ID1 suppressed differentiation and promoted proliferation in HPCs through the inhibition of HNF4α and Rap1GAP transcriptions. Finally, scRNA sequencing of HCC patients and investigation of clinical specimens also verified that the expression of ID1 is correlated with aberrant differentiation of HPCs into cancer stem cells, patients with high levels of ID1 in HPCs showed a poorer prognosis. This study provides important intervention targets and a theoretical basis for the clinical diagnosis and treatment of HCC.

Combined Effects of Programmed Cell Death-1 Blockade and Endostar on Brain Metastases of Lung Cancer.

BACKGROUND: The blockade of programmed cell death-1 (PD-1) and recombinant human endostatin can be used for the treatment of non-small cell lung cancer (NSCLC) and its metastasis. This study aims to explore the therapeutically potential of PD-1 blockade plus Endostar in brain metastasis of NSCLC. METHODS: The mouse brain metastases model was established using Lewis lung carcinoma luciferase (LLC-Luc) and PC-9-Luc cells. Tumor metastasis in the brain and tumor burden were analyzed by using bioluminescence imaging (BLI), qRT-PCR and ELISA which were used to determine the mRNA and protein levels of biomarkers in tumor tissues. Immunohistochemical staining was used to determine the expression and location of CD31 in tumor tissues in the brain. RESULTS: Treatment with anti-PD-1 and Endostar suppressed tumor metastasis in the brain and prolonged overall survival rate in LLC-Luc and PC-9-Luc brain metastases mouse model. In addition, treatment with anti-PD-1 and Endostar inhibited the expressions of CD31 and VEGF in tumor tissues in the brain. Furthermore, treatment with anti-PD- 1 and Endostar significantly suppressed the levels of IL1ß, IFNγ, and TGFß in the tumor tissues. CONCLUSION: The combination of PD-1 blockade and endostar suppressed brain metastases of NSCLC.

Sirt1 inhibits kidney stones formation by attenuating calcium oxalate-induced cell injury.

Cell injury is a necessary and critical event during CaOx kidney stone formation. Sirt1 exerts a number of pleiotropic effects, protecting against renal cell injury. This study aims to explore the relationship between Sirt1 and CaOx kidney stone formation and the underlying mechanism. Sirt1 expression in renal tissues or HK-2 cells was detected by Western blot, immunohistochemistry and immunofluorescence. Apoptosis in renal tissues was examined by TUNEL staining. Renal pathological changes and the crystals deposition were detected by hematoxylin-eosin and Von Kossa staining. Crystal-cell adhesion and cell injury in HK-2 cells were assessed by atomic absorption spectrometry and flow cytometry, respectively. Sirt1 expression in nephrolithiasis patients was downregulated and the level of apoptosis was increased. Further study found that Sirt1 expression was decreased in both in vivo and in vitro models. Interestingly, the levels of cell injury were elevated in vivo and in vitro models. Suppressing Sirt1 expression promoted COM-induced crystal-cell adhesion and exacerbated cell injury. In contrast, increasing the expression of Sirt1 by lentivirus transfection in vitro and resveratrol administration in vivo, alleviated crystal deposition and cell damage. Our findings suggest that Sirt1 could inhibit kidney stone formation, at least in part, through attenuating CaOx -induced cell injury.

Capsule-LPI: a LncRNA-protein interaction predicting tool based on a capsule network.

BACKGROUND: Long noncoding RNAs (lncRNAs) play important roles in multiple biological processes. Identifying LncRNA-protein interactions (LPIs) is key to understanding lncRNA functions. Although some LPIs computational methods have been developed, the LPIs prediction problem remains challenging. How to integrate multimodal features from more perspectives and build deep learning architectures with better recognition performance have always been the focus of research on LPIs. RESULTS: We present a novel multichannel capsule network framework to integrate multimodal features for LPI prediction, Capsule-LPI. Capsule-LPI integrates four groups of multimodal features, including sequence features, motif information, physicochemical properties and secondary structure features. Capsule-LPI is composed of four feature-learning subnetworks and one capsule subnetwork. Through comprehensive experimental comparisons and evaluations, we demonstrate that both multimodal features and the architecture of the multichannel capsule network can significantly improve the performance of LPI prediction. The experimental results show that Capsule-LPI performs better than the existing state-of-the-art tools. The precision of Capsule-LPI is 87.3%, which represents a 1.7% improvement. The F-value of Capsule-LPI is 92.2%, which represents a 1.4% improvement. CONCLUSIONS: This study provides a novel and feasible LPI prediction tool based on the integration of multimodal features and a capsule network. A webserver ( http://csbg-jlu.site/lpc/predict ) is developed to be convenient for users.

From the perspective of Traditional Chinese Medicine: Treatment of mental disorders in COVID-19 survivors.

PURPOSE: The aim of this study is to explore the possible benefits of traditional Chinese medicine on the pathogenesis of psychological and mental health of COVID-19 survivors. METHODS: A literature search was conducted to confirm the effects of COVID-19 on psychological and mental health of survivors. In addition to this, on the basis of signs and symptoms, TCM were used on treat mental disorder as per suggested clinical and animal experimental data plus relevant records in classical Chinese medicine books written by Zhang Zhongiing during Han Dynasty. A series of treatment plans were prescribed for COVID-19 survivors with psychological and mental disorders. RESULTS: According to previous extensive studies focusing on effects on mental health of survivors, high incidence was observed in severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS) survivors. During investigations of mental health of COVID-19 patients and survivors, it is observed that they also had symptoms of mental disorders and immune dysfunction. Furthermore, it was also proposed that depression, anxiety and post-traumatic stress disorder (PTSD) were most common mental disorders requiring special attention after the recovery from COVID-19. The symptoms of COVID-19 were analyzed, and the TCM syndrome of the depression, anxiety and PTSD after recovered from COVID19 was interpreted as internal heat and Yin deficiency. These three mental disorders pertains the category of "Lily disease", "hysteria" and "deficient dysphoria" in TCM. CONCLUSION: Lily Bulb, Rhizoma Anemarrhena Decoction and Ganmai Dazao Decoction were used to treat depression. Suanzaoren Decoction, Huanglian Ejiao Decoction and Zhizi Chi Decoction were suggested for anxiety. Moreover, Lily Bulb, Rehmannia Decoction and Guilu Erxian Decoction were the formula for PTSD.

LncLocation: Efficient Subcellular Location Prediction of Long Non-Coding RNA-Based Multi-Source Heterogeneous Feature Fusion.

Recent studies uncover that subcellular location of long non-coding RNAs (lncRNAs) can provide significant information on its function. Due to the lack of experimental data, the number of lncRNAs is very limited, experimentally verified subcellular localization, and the numbers of lncRNAs located in different organelle are wildly imbalanced. The prediction of subcellular location of lncRNAs is actually a multi-classification small sample imbalance problem. The imbalance of data results in the poor recognition effect of machine learning models on small data subsets, which is a puzzling and challenging problem in the existing research. In this study, we integrate multi-source features to construct a sequence-based computational tool, lncLocation, to predict the subcellular location of lncRNAs. Autoencoder is used to enhance part of the features, and the binomial distribution-based filtering method and recursive feature elimination (RFE) are used to filter some of the features. It improves the representation ability of data and reduces the problem of unbalanced multi-classification data. By comprehensive experiments on different feature combinations and machine learning models, we select the optimal features and classifier model scheme to construct a subcellular location prediction tool, lncLocation. LncLocation can obtain an 87.78% accuracy using 5-fold cross validation on the benchmark data, which is higher than the state-of-the-art tools, and the classification performance, especially for small class sets, is improved significantly.

High glucose induced-macrophage activation through TGF-ß-activated kinase 1 signaling pathway.

OBJECTIVE AND DESIGN: Transforming growth factor-ß-activated kinase 1 (TAK1) plays a pivotal role in innate immune responses and kidney disease, and is critically involved in macrophage activation. However, there is a paucity of data to explore the role of high glucose (HG) in the regulation of TAK1 signaling and its functional role in macrophage activation. We assume that TAK1 signaling in hyperglycemic condition could be a key factor leading to macrophage activation and inflammation response. METHODS: Mice macrophages were seeded on a 96-well cell culture plate; cell viability was tested after treatment with different concentration of TAK1 inhibitors. Cells were divided into groups (OZ300; MC; NC; HG; HG + OZ30, 100, 300 nM) and treated for given time course. Monocyte chemotactic protein1(MCP-1) and tumor necrosis factor-α (TNF-α) mRNA levels were evaluated by qRT-PCR. Flow cytometry and confocal microscopy are used to analyse the activated macrophage induced by HG. Expression levels of p-TAK1, TAB 1, p-JNK, p-p38MAPK, NF-κBpp65 were detected by western blot. Nuclear translocation of NF-κBp65 was assessed by confocal microscopy. RESULTS: Our data revealed that high glucose not only significantly increased macrophage activation and subsequently abnormal high-expression of MCP-1 and TNF-α, but likewise remarkably enhanced TAK1 activation, MAPK phosphorylation, NF-κB expression in macrophages. Furthermore, pharmacological inhibition of TAK1 attenuated high glucose-triggered signal pathways, macrophage activation and inflammatory cytokines in a simulated diabetic environment. CONCLUSION: Our findings suggested that high glucose activated macrophages mainly in TAK1/MAPKs and TAK1/NF-κB-dependent manners, which lead to the polarization of macrophages towards a pro-inflammatory phenotype, and finally lead to diabetic nephropathy. In sum, the study raises novel data about the molecular mechanisms involved in the high glucose-mediated inflammatory response in macrophages.

Blockade of TGF-ß-activated kinase 1 prevents advanced glycation end products-induced inflammatory response in macrophages.

Advanced glycation end products (AGEs), inflammatory-activated macrophages are essential in the initiation and progression of diabetic nephropathy (DN). TGF-ß-activated kinase 1 (TAK1) plays a vital role in innate immune responses and inflammation. However, little information has been available about the effects of AGEs on the regulation of TAK1 expression and underlying mechanisms in AGEs-stimulated macrophage activation. We hypothesized TAK1 signal pathway in AGEs conditions could be a vital factor contributing to macrophage activation and inflammation. Thus, in the present study, we used bone marrow-derived macrophages (BMMs) to explore the functional role and potential mechanisms of TAK1 pathway under AGEs conditions. Results indicated that TAK1 played important roles in AGEs-induced mitogen-activated protein kinases (MAPKs) and nuclear factor kappa B protein (NF-κB) activation, which regulated the production of monocyte chemo-attractant protein-1 (MCP-1) and tumor necrosis factor-alpha (TNF-α) in AGEs-stimulated macrophages. The results also suggested that TAK1 inhibitor (5Z-7-oxozeaenol) could inhibit AGEs-induced macrophage activation to down-regulate inflammatory cytokine production via MAPKs and NF-κB pathways, indicating that 5Z-7-oxozeaenol might be an immunoregulatory agent against AGEs-stimulated inflammatory response in DN.