Identification of FAM3D as a novel endogenous chemotaxis agonist for the FPRs (formyl peptide receptors)

The family with sequence similarity 3 (FAM3) gene family is a cytokine-like gene family with four members FAM3A, FAM3B, FAM3C, and FAM3D. In this study, we found that FAM3D strongly chemoattracted human peripheral blood neutrophils and monocytes. To identify FAM3D receptor, we used chemotaxis, receptor internalization, calcium flux and radioligand-binding assays in FAM3D-stimulated HEK293 cells that transiently expressed FPR1 or FPR2 to show that FAM3D was a high affinity ligand of formyl peptide receptors (FPR1 and FPR2), both of which were highly expressed on the surface of neutrophils and monocytes/macrophages. After being injected into the mouse peritoneal cavity, FAM3D chemoattracted CD11b+Ly6G+ neutrophils in a short time. In response to FAM3D stimulation, p-ERK and p-p38 were up-regulated in the mouse neutrophils, which could be inhibited by an inhibitor of FPR1 or FPR2. FAM3D was reported to be constitutively expressed in the gastrointestinal tract. We found that FAM3D expression increased significantly in dextran sulfate sodium-induced colitis. Taken together, we propose that FAM3D plays a role in gastrointestinal homeostasis and inflammation through its receptors FPR1 and FPR2.</jats:p

DESIGN OF CONTROLLABLE LEADER–FOLLOWER NETWORKS VIA MEMETIC ALGORITHMS

In many engineered and natural networked systems, there has been great interest in leader selection and/or edge assignment during the optimal design of controllable networks. In this paper, we present our pioneering work in leader–follower network design via memetic algorithms, which focuses on minimizing the number of leaders or the amount of control energy while ensuring network controllability. We consider three problems in this paper: (1) selecting the minimum number of leaders in a pre-defined network with guaranteed network controllability; (2) selecting the leaders in a pre-defined network with the minimum control energy; and (3) assigning edges (interactions) between nodes to form a controllable leader–follower network with the minimum control energy. The proposed framework can be applied in designing signed, unsigned, directed, or undirected networks. It should be noted that this work is the first to apply memetic algorithms in the design of controllable networks. We chose memetic algorithms because they have been shown to be more efficient and more effective than the standard genetic algorithms in solving some optimization problems. Our simulation results provide an additional demonstration of their efficiency and effectiveness. </jats:p

Functional Roles of Chemokine Receptor CCR2 and Its Ligands in Liver Disease

Chemokines are a family of cytokines that orchestrate the migration and positioning of immune cells within tissues and are critical for the function of the immune system. CCR2 participates in liver pathology, including acute liver injury, chronic hepatitis, fibrosis/cirrhosis, and tumor progression, by mediating the recruitment of immune cells to inflammation and tumor sites. Although a variety of chemokines have been well studied in various diseases, there is no comprehensive review presenting the roles of all known chemokine ligands of CCR2 (CCL2, CCL7, CCL8, CCL12, CCL13, CCL16, and PSMP) in liver disease, and this review aims to fill this gap. The introduction of each chemokine includes its discovery, its corresponding chemotactic receptors, physiological functions and roles in inflammation and tumors, and its impact on different immune cell subgroups.</jats:p

Eukaryotic Community Structure and Interspecific Interactions in a Stratified Acidic Pit Lake Water in Anhui Province

The stratified acidic pit lake formed by the confluence of acid mine drainage has a unique ecological niche and is a model system for extreme microbial studies. Eukaryotes are a component of the AMD community, with the main members including microalgae, fungi, and a small number of protozoa. In this study, we analyzed the structural traits and interactions of eukaryotes (primarily fungi and microalgae) in acidic pit lakes subjected to environmental gradients. Based on the findings, microalgae and fungi were found to dominate different water layers. Specifically, Chlorophyta showed dominance in the well-lit aerobic surface layer, whereas Basidiomycota was more abundant in the dark anoxic lower layer. Co-occurrence network analysis showed that reciprocal relationships between fungi and microalgae were prevalent in extremely acidic environments. Highly connected taxa within this network were Chlamydomonadaceae, Sporidiobolaceae, Filobasidiaceae, and unclassified Eukaryotes. Redundancy analysis (RDA) and random forest models revealed that Chlorophyta and Basidiomycota responded strongly to environmental gradients. Further analysis indicated that eukaryotic community structure was mainly determined by nutrient and metal concentrations. This study investigates the potential symbiosis between fungi and microalgae in the acidic pit lake, providing valuable insights for future eukaryotic biodiversity studies on AMD remediation

Elevated Expression Levels of PC3-Secreted Microprotein (PSMP) in Prostate Cancer Associated With Increased Xenograft Growth and Modification of Immune-Related Microenvironment

Prostate cancer (PCa), especially metastatic PCa, is one of the main cancer types accounting for male mortality worldwide. Over decades, researchers have tried to search for effective curative methods for PCa, but many attempts have failed. The therapeutic failure of PCa is usually due to off-target or side effects; thus, finding a key molecule that could prevent PCa metastatic progression has become the most important goal for curing aggressive PCa. In this study, we collected hundreds of PCa tissues and serum and urine samples from patients to verify the upregulated expression of PC3-secreted microprotein (PSMP) in PCa tumor tissues with high Gleason scores. According to biopsy results, PSMP expression was found related to extraprostatic extension (EPE), contributing to PCa metastasis. Mechanistically, recombinant PSMP protein could promote the proliferation both in vitro and in vivo, and rhPSMP could promote epithelial–mesenchymal transition (EMT) of PC3 in vitro. Additionally, PSMP could also influence cytokine production in the xenograft model and monocyte migration and macrophage polarization in vitro. Our most important finding was that neutralizing antibodies against PSMP could suppress xenograft PC3 growth and promote the survival of PC3 metastatic mice model, providing an effective option to cure human PCa.</jats:p

A signature based on NKG2D ligands to predict the recurrence of hepatocellular carcinoma after radical resection

Abstract Introduction Due to the high recurrence, the HCC prognosis remains poor. Yet, the biomarkers for predicting the recurrence of high‐risk patients are currently lacking. We aimed to develop a signature to predict the recurrence of HCC based on NKG2D ligands. Methods The multivariate Cox proportional hazards regression was used to select recurrence‐related variables of NKG2D ligands in HCC patients from The Cancer Genome Atlas (TCGA). HCC patients from the OEP000321 dataset and Guilin cohort were used to validate the predictive signature. The mRNA expression of NKG2D ligands was measured by QRT‐PCR. Immunohistochemistry analysis of HCC tissue microarray samples was used to identify the expression of NKG2D ligands. Results In this study, NKG2D ligands expression in the mRNA and protein level was both abnormally expressed in HCC and associated with recurrence‐free survival (RFS). Then, the recurrence‐related variables of NKG2D ligands in HCC were selected by the multivariate Cox proportional hazards regression. Among the eight NKG2D ligands, MICA (HR = 1.347; 95% CI = 1.012–1.793; p = 0.041), ULBP3 (HR = 0.453; 95% CI = 0.231–0.889; p = 0.021) and ULBP5 (HR = 3.617; 95% CI = 1.819–7.194; p < 0.001) were significantly correlated with RFS in the TCGA‐LIHC cohort. Then, the signature was constructed by the three NKG2D ligands. The predictive effectiveness of this signature was also validated in the OEP000321 dataset and Guilin cohort. Further, HCC patients were classified into low‐risk and high‐risk subgroups by the predictive score. Compared with the low‐risk group, the high‐risk group had poor RFS in both training and validation cohorts. Importantly, compared with the low‐risk patients with the G1‐G2 stage, the levels of infiltrated NK‐activated cells and NKG2D expression were both lower in the high‐risk patients. Conclusions The signature based on MICA, ULBP3, and ULBP5 could predict HCC recurrence