LHFPL2 Serves as a Potential Biomarker for M2 Polarization of Macrophages in Renal Cell Carcinoma.

Renal cell carcinoma (RCC) is one of the most common malignant tumors of the kidney, presenting significant challenges for clinical diagnosis and treatment. Macrophages play crucial roles in RCC, promoting tumor progression and warranting further investigation. Previous studies have identified LHFPL2 as a transmembrane protein associated with reproduction, but its relationship with tumors or macrophages has not been discussed. This study utilized transcriptomic sequencing data from 609 KIRC patients in the TCGA database and single-cell sequencing data from 34,326 renal carcinoma cells for subsequent analysis. We comprehensively evaluated the expression of LHFPL2 and its relationship with clinical features, tumor prognosis, immune infiltration, and mutations. Additionally, we further assessed the correlation between LHFPL2 and macrophage M2 polarization using single-cell data and explored its potential as a cancer therapeutic target through molecular docking. The results demonstrated that LHFPL2 is upregulated in RCC and associated with poor survival rates. In clinical staging, the proportion of malignant and high-metastasis patients was higher in the high-LHFPL2 group than in the low-LHFPL2 group. Furthermore, we found that LHFPL2 influences RCC immune infiltration, with its expression positively correlated with various immune checkpoint and M2-related gene expressions, positively associated with M2 macrophage infiltration, and negatively correlated with activated NK cells. Moreover, LHFPL2 showed specific expression in macrophages, with the high-expression subgroup exhibiting higher M2 polarization, hypoxia, immune evasion, and angiogenesis scores, promoting tumor progression. Finally, we predicted several potential drugs targeting LHFPL2, such as conivaptan and nilotinib. Our analysis elaborately delineates the immune characteristics of LHFPL2 in the tumor microenvironment and its positive correlation with macrophage M2 polarization, providing new insights into tumor immunotherapy. We also propose potential FDA-approved drugs targeting this gene, which should be tested for their binding effects with LHFPL2 in future studies.

Establishment and Validation of Novel Prognostic Subtypes in Hepatocellular Carcinoma Based on Bile Acid Metabolism Gene Signatures Using Bulk and Single-Cell RNA-Seq Data.

Hepatocellular carcinoma (HCC) is a highly detrimental cancer type and has limited therapeutic options, posing significant threats to human health. The development of HCC has been associated with a disorder in bile acid (BA) metabolism. In this study, we employed an integrative approach, combining various datasets and omics analyses, to comprehensively characterize the tumor microenvironment in HCC based on genes related to BA metabolism. Our analysis resulted in the classification of HCC samples into four subtypes (C1, C2a, C2b, and C3). Notably, subtype C2a, characterized by the highest bile acid metabolism score (BAMS), exhibited the highest survival probability. This subtype also demonstrated increased immune cell infiltration, lower cell cycle scores, reduced AFP levels, and a lower risk of metastasis compared to subtypes C1 and C3. Subtype C1 displayed poorer survival probability and elevated cell cycle scores. Importantly, the identified subtypes based on BAMS showed potential relevance to the gene expression of drug targets in currently approved drugs and those under clinical research. Genes encoding VEGFR (FLT4 and KDR) and MET were elevated in C2, while genes such as TGFBR1, TGFB1, ADORA3, SRC, BRAF, RET, FLT3, KIT, PDGFRA, and PDGFRB were elevated in C1. Additionally, FGFR2 and FGFR3, along with immune target genes including PDCD1 and CTLA4, were higher in C3. This suggests that subtypes C1, C2, and C3 might represent distinct potential candidates for TGFB1 inhibitors, VEGFR inhibitors, and immune checkpoint blockade treatments, respectively. Significantly, both bulk and single-cell transcriptome analyses unveiled a negative correlation between BA metabolism and cell cycle-related pathways. In vitro experiments further confirmed that the treatment of HCC cell lines with BA receptor agonist ursodeoxycholic acid led to the downregulation of the expression of cell cycle-related genes. Our findings suggest a plausible involvement of BA metabolism in liver carcinogenesis, potentially mediated through the regulation of tumor cell cycles and the immune microenvironment. This preliminary understanding lays the groundwork for future investigations to validate and elucidate the specific mechanisms underlying this potential association. Furthermore, this study provides a novel foundation for future precise molecular typing and the design of systemic clinical trials for HCC therapy.

KCOSS: an ultra-fast k-mer counter for assembled genome analysis.

MOTIVATION: The k-mer frequency in whole genome sequences provides researchers with an insightful perspective on genomic complexity, comparative genomics, metagenomics and phylogeny. The current k-mer counting tools are typically slow, and they require large memory and hard disk for assembled genome analysis. RESULTS: We propose a novel and ultra-fast k-mer counting algorithm, KCOSS, to fulfill k-mer counting mainly for assembled genomes with segmented Bloom filter, lock-free queue, lock-free thread pool and cuckoo hash table. We optimize running time and memory consumption by recycling memory blocks, merging multiple consecutive first-occurrence k-mers into C-read, and writing a set of C-reads to disk asynchronously. KCOSS was comparatively tested with Jellyfish2, CHTKC and KMC3 on seven assembled genomes and three sequencing datasets in running time, memory consumption, and hard disk occupation. The experimental results show that KCOSS counts k-mer with less memory and disk while having a shorter running time on assembled genomes. KCOSS can be used to calculate the k-mer frequency not only for assembled genomes but also for sequencing data. AVAILABILITYAND IMPLEMENTATION: The KCOSS software is implemented in C++. It is freely available on GitHub: https://github.com/kcoss-2021/KCOSS. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Cucurbitacin I Reverses Tumor-Associated Macrophage Polarization to Affect Cancer Cell Metastasis.

The tumor microenvironment plays a critical role in tumor progression and immune regulation. As one of the most important components of the tumor microenvironment, macrophages have become a new therapeutic target for inhibiting tumor progression. Despite the well-documented anticancer activity of cucurbitacin I, its effect on macrophages remains unclear. In this study, we established a coculture system of macrophages and cancer cells under hypoxic conditions to simulate the tumor-promoting environment mediated by M2-like macrophages. We determined whether cucurbitacin I modulates M2-like polarization in macrophages in vitro and conducted RNA sequencing to identify gene expression changes induced by cucurbitacin I in macrophages. The results indicated a remarkable inhibition of the M2-like polarization phenotype in macrophages following treatment with cucurbitacin I, which was accompanied by the significant downregulation of heme oxygenase-1. Moreover, we found that cucurbitacin I-treated macrophages reduced the migration of cancer cells by inhibiting the M2 polarization in vitro. These findings highlight the potential of cucurbitacin I as a therapeutic agent that targets M2-like macrophages to inhibit cancer cell metastasis. Our study provides novel insights into the intricate interplay among macrophage polarization, cucurbitacin I, and heme oxygenase-1, thereby opening new avenues for cancer treatment.

Combined Inhibition of UBE2C and PLK1 Reduce Cell Proliferation and Arrest Cell Cycle by Affecting ACLY in Pan-Cancer.

Various studies have shown that the cell-cycle-related regulatory proteins UBE2C, PLK1, and BIRC5 promote cell proliferation and migration in different types of cancer. However, there is a lack of in-depth and systematic research on the mechanism of these three as therapeutic targets. In this study, we found a positive correlation between the expression of UBE2C and PLK1/BIRC5 in the Cancer Genome Atlas (TCGA) database, revealing a potential combination therapy candidate for pan-cancer. Quantitative real-time PCR (qRT-PCR), Western blotting (WB), cell phenotype detection, and RNA-seq techniques were used to evidence the effectiveness of the combination candidate. We found that combined interference of UBE2C with PLK1 and UBE2C with BIRC5 affected metabolic pathways by significantly downregulating the mRNA expression of IDH1 and ACLY, which was related to the synthesis of acetyl-CoA. By combining the PLK1 inhibitor volasertib and the ACLY inhibitor bempedoic acid, it showed a higher synergistic inhibition of cell viability and higher synergy scores in seven cell lines, compared with those of other combination treatments. Our study reveals the potential mechanisms through which cell-cycle-related genes regulate metabolism and proposes a potential combined targeted therapy for patients with higher PLK1 and ACLY expression in pan-cancer.

Validation Study to Determine the Accuracy of Widespread Promoterless EGFP Reporter at Assessing CRISPR/Cas9-Mediated Homology Directed Repair.

An accurate visual reporter system to assess homology-directed repair (HDR) is a key prerequisite for evaluating the efficiency of Cas9-mediated precise gene editing. Herein, we tested the utility of the widespread promoterless EGFP reporter to assess the efficiency of CRISPR/Cas9-mediated homologous recombination by fluorescence expression. We firstly established a promoterless EGFP reporter donor targeting the porcine GAPDH locus to study CRISPR/Cas9-mediated homologous recombination in porcine cells. Curiously, EGFP was expressed at unexpectedly high levels from the promoterless donor in porcine cells, with or without Cas9/sgRNA. Even higher EGFP expression was detected in human cells and those of other species when the porcine donor was transfected alone. Therefore, EGFP could be expressed at certain level in various cells transfected with the promoterless EGFP reporter alone, making it a low-resolution reporter for measuring Cas9-mediated HDR events. In summary, the widespread promoterless EGFP reporter could not be an ideal measurement for HDR screening and there is an urgent need to develop a more reliable, high-resolution HDR screening system to better explore strategies of increasing the efficiency of Cas9-mediated HDR in mammalian cells.

Identification and Validation of Serum CST1 as a Diagnostic Marker for Differentiating Early-Stage Non-Small Cell Lung Cancer from Pulmonary Benign Nodules.

BACKGROUND: Effective means for early diagnosis are imperative to reduce death rate of non-small cell lung cancer (NSCLC) patients. We aimed to find out high-performance serologic markers to distinguish early-stage NSCLC patients from benign pulmonary nodule patients and healthy controls (HC). Cystatin-SN (CST1) is an active cysteine protease inhibitor of the CST superfamily, involving in the processes of inflammation and tumorigenesis. This is the first exploration of the diagnostic and prognostic values of serum CST1 in NSCLC. METHODS: We analyzed the transcriptome data from The Cancer Genome Atlas and the Gene Expression Omnibus database, screened biomarkers for NSCLC, and verified the candidate markers via the ONCOMINE database. Then, we performed ELISA, western blotting, and immunohistochemistry analysis to detect the expression levels of CST1 in NSCLC cell lines, tumor tissues, and serum samples of clinical cohorts. RESULTS: We identified 3 up-regulated secreted protein-encoding genes, validated the expression levels of CST1 in NSCLC tumor tissues and cell lines, and found that serum CST1 levels of NSCLC (4289 ± 2405 pg/mL) were significantly higher than those of PBN patients (1558 ± 441 pg/mL, P < .0001) and healthy controls (1529 ± 416 pg/mL, P < .0001). The AUC of the combination of CST1, Cytokeratin 19 fragment (Cyfra21-1), and Carcinoembryonic antigen (CEA) for distinguishing early-stage NSCLC from PBN/HC was as high as .914/0.925. Furthermore, our results suggested that the NSCLC patient with low serum CST1 level had a better survival rate. CONCLUSIONS: Serum CST1 may serve as a novel diagnostic marker for differentiating early-stage NSCLC from PBN and HC, and could be used as a prognosis predictor in NSCLC patients.

Multi-Omics Perspective Reveals the Different Patterns of Tumor Immune Microenvironment Based on Programmed Death Ligand 1 (PD-L1) Expression and Predictor of Responses to Immune Checkpoint Blockade across Pan-Cancer.

Immune checkpoint inhibitor (ICI) therapies have shown great promise in cancer treatment. However, the intra-heterogeneity is a major barrier to reasonably classifying the potential benefited patients. Comprehensive heterogeneity analysis is needed to solve these clinical issues. In this study, the samples from pan-cancer and independent breast cancer datasets were divided into four tumor immune microenvironment (TIME) subtypes based on tumor programmed death ligand 1 (PD-L1) expression level and tumor-infiltrating lymphocyte (TIL) state. As the combination of the TIL Z score and PD-L1 expression showed superior prediction of response to ICI in multiple data sets compared to other methods, we used the TIL Z score and PD-L1 to classify samples. Therefore, samples were divided by combined TIL Z score and PD-L1 to identify four TIME subtypes, including type I (3.24%), type II (43.24%), type III (6.76%), and type IV (46.76%). Type I was associated with favorable prognosis with more T and DC cells, while type III had the poorest condition and composed a higher level of activated mast cells. Furthermore, TIME subtypes exhibited a distinct genetic and transcriptional feature: type III was observed to have the highest mutation rate (77.92%), while co-mutations patterns were characteristic in type I, and the PD-L1 positive subgroup showed higher carbohydrates, lipids, and xenobiotics metabolism compared to others. Overall, we developed a robust method to classify TIME and analyze the divergence of prognosis, immune cell composition, genomics, and transcriptomics patterns among TIME subtypes, which potentially provides insight for classification of TIME and a referrable theoretical basis for the screening benefited groups in the ICI immunotherapy.

Prediction and evolution of B cell epitopes of surface protein in SARS-CoV-2.

BACKGROUND: In order to obtain antibodies that recognize natural proteins, it is possible to predict the antigenic determinants of natural proteins, which are eventually embodied as polypeptides. The polypeptides can be coupled with corresponding vectors to stimulate the immune system to produce corresponding antibodies, which is also a simple and effective vaccine development method. The discovery of epitopes is helpful to the development of SARS-CoV-2 vaccine. METHODS: The analyses were related to epitopes on 3 proteins, including spike (S), envelope (E) and membrane (M) proteins, which are located on the lipid envelope of the SARS-CoV-2. Based on the NCBI Reference Sequence: NC_045512.2, the conformational and linear B cell epitopes of the surface protein were predicted separately by various prediction methods. Furthermore, the conservation of the epitopes, the adaptability and other evolutionary characteristics were also analyzed, the sequences of the whole genome of SARS-CoV-2 were obtained from the GISAID. RESULTS: 7 epitopes were predicted, including 6 linear epitopes and 1 conformational epitope. One of the linear and one of the conformational consist of identical sequence, but represent different forms of epitopes. It is worth mentioning that all 6 identified epitopes were conserved in nearly 3500 SARS-CoV-2 genomes, showing that it is helpful to obtain stable and long-acting epitopes under the condition of high frequency of amino acid mutation, which deserved further study at the experiment level. CONCLUSION: The findings would facilitate the vaccine development, had the potential to be directly applied on the prevention in this disease, but also have the potential to prevent the possible threats caused by other types of coronavirus.

Roles of Proteoglycans and Glycosaminoglycans in Cancer Development and Progression.

The extracellular matrix (ECM) spatiotemporally controls cell fate; however, dysregulation of ECM remodeling can lead to tumorigenesis and cancer development by providing favorable conditions for tumor cells. Proteoglycans (PGs) and glycosaminoglycans (GAGs) are the major macromolecules composing ECM. They influence both cell behavior and matrix properties through direct and indirect interactions with various cytokines, growth factors, cell surface receptors, adhesion molecules, enzymes, and glycoproteins within the ECM. The classical features of PGs/GAGs play well-known roles in cancer angiogenesis, proliferation, invasion, and metastasis. Several lines of evidence suggest that PGs/GAGs critically affect broader aspects in cancer initiation and the progression process, including regulation of cell metabolism, serving as a sensor of ECM's mechanical properties, affecting immune supervision, and participating in therapeutic resistance to various forms of treatment. These functions may be implemented through the characteristics of PGs/GAGs as molecular bridges linking ECM and cells in cell-specific and context-specific manners within the tumor microenvironment (TME). In this review, we intend to present a comprehensive illustration of the ways in which PGs/GAGs participate in and regulate several aspects of tumorigenesis; we put forward a perspective regarding their effects as biomarkers or targets for diagnoses and therapeutic interventions.

A prognostic 11 long noncoding RNA expression signature for breast invasive carcinoma.

Breast cancer, the most common cancer in women worldwide, is associated with high mortality. The long non-coding RNAs (lncRNAs) with a little capacity of coding proteins is playing an increasingly important role in the cancer paradigm. Accumulating evidences demonstrate that lncRNAs have crucial connections with breast cancer prognosis while the studies of lncRNAs in breast cancer are still in its primary stage. In this study, we collected 1052 clinical patient samples, a comparatively large sample size, including 13 159 lncRNA expression profiles of breast invasive carcinoma (BRCA) from The Cancer Genome Atlas database to identify prognosis-related lncRNAs. We randomly separated all of these clinical patient samples into training and testing sets. In the training set, we performed univariable Cox regression analysis for primary screening and played the model for Robust likelihood-based survival for 1000 times. Then 11 lncRNAs with a frequency more than 600 were selected for prediction of the prognosis of BRCA. Using the analysis of multivariate Cox regression, we established a signature risk-score formula for 11 lncRNA to identify the relationship between lncRNA signatures and overall survival. The 11 lncRNA signature was validated both in the testing and the complete set and could effectively classify the high-/low-risk group with different OS. We also verified our results in different stages. Moreover, we analyzed the connection between the 11 lncRNAs and the genes of ESR1, PGR, and Her2, of which protein products (ESR, PGR, and HER2) were used to classify the breast cancer subtypes widely. The results indicated correlations between 11 lncRNAs and the gene of PGR and ESR1. Thus, a prognostic model for 11 lncRNA expression was developed to classify the BRAC clinical patient samples, providing new avenues in understanding the potential therapeutic methods of breast cancer.

Integrated analysis of transcription factors and targets co-expression profiles reveals reduced correlation between transcription factors and target genes in cancer.

Transcription factors are recognized as the key regulators of gene expression. However, the changes in the correlation of transcription factors and their target genes between normal and tumor tissues are usually ignored. In this research, we used mRNA expression profile data from The Cancer Genome Atlas which included 5726 samples across 11 major human cancers to perform co-expression analysis by the Pearson correlation coefficients. Then, integrating 81,357 pairs of transcription factors and target genes from transcription factors databases to find out the changes in the co-expression correlation of these gene pairs from normal to tumor tissues. Based on the changes in the number of co-expressed TF-TG pairs and changes in the level of co-expression, we found the generally reduced correlation between transcription factors and their target genes in cancer. Additionally, we screened out universal and specific transcription factors-target genes pairs which may significant influence particular cancer. Then, we obtained 423 cancer cell line expression profiles from Broad Institute Cancer Cell Line Encyclopedia to verify our results. Some of these pairs like XRCC5-XRCC6 have been reported to involve in multiple cancers, while pairs like IRF1-PSMB9 without any previous articles related to tumor but involve in the biological processes of cancer, which are of great potential to be therapeutic targets. Our research may provide insights to better understand the tumor development mechanisms and find potential therapeutic targets.

New method to preserve the original proportion and integrity of urinary cell-free DNA.

BACKGROUND: Due to high nuclease activity and complex contents in urine, urinary cell-free DNA (ucfDNA) was prone to degrade. So, we developed standardized urine collection tube (UCT) to prevent ucfDNA degradation and simultaneously maintain urinary cells in their original form during the sample collection process, ensuring stabilization of the original proportion and integrity of ucfDNA. METHODS: Urine samples were collected from bladder cancer patients and divided into 10-mL normal tubes and 10-mL UCTs, respectively, and kept at ambient temperature. Urine supernatant was separated by centrifuging, and ucfDNA was extracted. Then ucfDNA was quantified by quantitative real-time polymerase chain reaction. UcfDNA fragments distribution was analyzed by Agilent 2200, and the frequency of specific mutations of urinary system disease was detected by next-generation sequencing method. RESULTS: Urine collected into UCTs showed no statistically significant changes in their original proportion and integrity of ucfDNA up to 7 days at ambient temperature and also ucfDNA fragments were maintained well. Conversely, urine collected into normal tubes was observed an obviously decline in their original proportion of ucfDNA and ucfDNA fragments changed greatly. The △% of allele fraction (AF) for specific genes of ucfDNA from UCTs was lower than from normal tubes by 3.7-fold. CONCLUSION: Using UCTs, they can maximally keep the original proportion and integrity of ucfDNA and stabilize urinary cells and minimize the background noise caused by urinary cellular DNA releasing, it will be help to open the door of next-generation noninvasive liquid biopsy applications utilizing urine.

Integrative Proteomics-Metabolomics Strategy for Pathological Mechanism of Vascular Depression Mouse Model.

Vascular depression (VD), a subtype of depression, is caused by vascular diseases or cerebrovascular risk factors. Recently, the proportion of VD patients has increased significantly, which severely affects their quality of life. However, the current pathogenesis of VD has not yet been fully understood, and the basic research is not adequate. In this study, on the basis of the combination of LC-MS-based proteomics and metabolomics, we aimed to establish a protein metabolism regulatory network in a murine VD model to elucidate a more comprehensive impact of VD on organisms. We detected 44 metabolites and 304 proteins with different levels in the hippocampus samples from VD mice using a combination of metabolomic and proteomics analyses with an isobaric tags for relative and absolute quantification (iTRAQ) method. We constructed a protein-to-metabolic regulatory network by correlating and integrating the differential metabolites and proteins using ingenuity pathway analysis. Then we quantitatively validated the levels of the bimolecules shown in the bioinformatics analysis using LC-MS/MS and Western blotting. Validation results suggested changes in the regulation of neuroplasticity, transport of neurotransmitters, neuronal cell proliferation and apoptosis, and disorders of amino acids, lipids and energy metabolism. These proteins and metabolites involved in these dis-regulated pathways will provide a more targeted and credible direction to study the mechanism of VD. Therefore, this paper presents an approach and strategy that was applied in integrative proteomics and metabolomics for research and screening potential targets and biomarkers of VD, which could be more precise and credible in a field lacking adequate basic research.

Cholesterol inhibits entotic cell-in-cell formation and actomyosin contraction.

Cell-in-cell structure is prevalent in human cancer, and associated with several specific pathophysiological phenomena. Although cell membrane adhesion molecules were found critical for cell-in-cell formation, the roles of other membrane components, such as lipids, remain to be explored. In this study, we attempted to investigate the effects of cholesterol and phospholipids on the formation of cell-in-cell structures by utilizing liposome as a vector. We found that Lipofectamine-2000, the reagent commonly used for routine transfection, could significantly reduce entotic cell-in-cell formation in a cell-specific manner, which is correlated with suppressed actomyosin contraction as indicated by reduced ß-actin expression and myosin light chain phosphorylation. The influence on cell-in-cell formation was likely dictated by specific liposome components as some liposomes affected cell-in-cell formation while some others didn't. Screening on a limited number of lipids, the major components of liposome, identified phosphatidylethanolamine (PE), stearamide (SA), lysophosphatidic acid (LPA) and cholesterol (CHOL) as the inhibitors of cell-in-cell formation. Importantly, cholesterol treatment significantly inhibited myosin light chain phosphorylation, which resembles the effect of Lipofectamine-2000, suggesting cholesterol might be partially responsible for liposomes' effects on cell-in-cell formation. Together, our findings supporting a role of membrane lipids and cholesterol in cell-in-cell formation probably via regulating actomyosin contraction.

Advancing the predictivity of skin sensitization by applying a novel HMOX1 reporter system.

Reporter cell lines are a particularly useful tool to screen for the skin sensitization potential of chemicals. Current cell models based on Keap1-Nrf2 mimic induction by conducting antioxidant response element-luciferase plasmids. However, plasmid-based reporters may ignore comprehensive aspects of induction, thus affecting the accuracy of hazard identification. Herein, we developed a novel HaCaT-based reporter system, EndoSens, whereby luciferase was specifically inserted into the cassette for heme oxygenase (decycling) 1 (HMOX1, the most consistent marker induced by skin sensitizers) by CRISPR/Cas9. Testing data from 20 coded substances showed an accuracy of 90%, sensitivity of 91.7%, and specificity of 87.5%, which exceeded the OECD requirement. Among the 35 chemicals examined, predictivity was better than reported for the validated KeratinoSens™. These results indicate that the EndoSens assay could advance the predictivity of skin sensitization, thus making it a promising tool for in vitro skin sensitization testing.

Metabolic analysis of the antidepressive effects of Yangxinshi Tablet in a vascular depression model in mice.

In recent years, vascular depression has become the focus of international attention. Yangxinshi Tablet (YXST) is usually used in cthe linic for the treatment of arrhythmia and heart failure, but we found that it also has antidepressive effects. The objective of the study was to identify biomarkers related to vascular depression in hippocampus and explore the antidepressive effects of YXST on the mouse model. Untargeted metabolomics based on UHPLC-Q-TOF/MS was applied to identify significantly differential biomarkers between the model group and control group. Unsupervised principal component analysis (PCA) was used to scan the tendency of groups and partial least squares-discriminant analysis (PLS-DA) to distinguish between the vascular depressive mice and the sham. PCA stores showed clear differences in metabolism between the vascular depressive mice and sham groups. The PLS-DA model exhibited 38 metabolites as the biomarkers to distinguish the vascular depressive mice and the sham. Further, YXST significantly regulated 22 metabolites to normal levels. The results suggested that YXST has a comprehensive antidepressive effect on vascular depression via regulation of multiple metabolic pathways including amino acid, the tricarboxylic acid cycle and phosphoglyceride metabolisms. These findings provide insight into the pathophysiological mechanism underlying vascular depression and the mechanism of YXST.

Ancestry, Plasmodium cynomolgi prevalence and rhesus macaque admixture in cynomolgus macaques (Macaca fascicularis) bred for export in Chinese breeding farms.

BACKGROUND: Most cynomolgus macaques (Macaca fascicularis) used in the United States as animal models are imported from Chinese breeding farms without documented ancestry. Cynomolgus macaques with varying rhesus macaque ancestry proportions may exhibit differences, such as susceptibility to malaria, that affect their suitability as a research model. METHODS: DNA of 400 cynomolgus macaques from 10 Chinese breeding farms was genotyped to characterize their regional origin and rhesus ancestry proportion. A nested PCR assay was used to detect Plasmodium cynomolgi infection in sampled individuals. RESULTS: All populations exhibited high levels of genetic heterogeneity and low levels of inbreeding and genetic subdivision. Almost all individuals exhibited an Indochinese origin and a rhesus ancestry proportion of 5%-48%. The incidence of P. cynomolgi infection in cynomolgus macaques is strongly associated with proportion of rhesus ancestry. CONCLUSIONS: The varying amount of rhesus ancestry in cynomolgus macaques underscores the importance of monitoring their genetic similarity in malaria research.

Metabolic profiles revealed synergistically antidepressant effects of lilies and Rhizoma Anemarrhenae in a rat model of depression.

Depression is a major cause of illness and disability. We applied untargeted metabolomics using mass spectrometry to identify metabolic signatures associated with depression in serum and explored the antidepressant effects of lilies and Rhizoma Anemarrhenae on an experimental model of chronic unpredictable mild stress (CUMS). Meanwhile metabolomics based on UHPLC-Q-TOF-MS was used to study the change in metabolites in CUMS rat serum and to evaluate the effects of Rhizoma Anemarrhenae and lilies (alone and in combination). Partial least squares-discriminant analysis identified 30 metabolites as decisive marker compounds that discriminated the CUMS rats and the control rats. The majority of these metabolites were involved in amino acid metabolism, the tricarboxylic acid cycle, and phosphoglyceride metabolism. The reliability of the metabolites was evaluated by the administration of lilies, Rhizoma Anemarrhenae, fluoxetine and the combination of lilies and Rhizoma Anemarrhenae to the CUMS rats. Behavior studies demonstrated that treatment with the combination of lilies and Rhizoma Anemarrhenae resulted in optimal antidepressant effects. The combination treatment was almost as effective as fluoxetine. Our results suggest that lilies and Rhizoma Anemarrhenae demonstrate synergistically antidepressant effects in CUMS via the regulation of multiple metabolic pathways. These findings provide insight into the pathophysiological mechanisms underlying CUMS and suggest innovative and effective treatments for this disorder.

Improving the MR Imaging Sensitivity of Upconversion Nanoparticles by an Internal and External Incorporation of the Gd(3+) Strategy for in Vivo Tumor-Targeted Imaging.

Gd(3+)-ion-doped upconversion nanoparticles (UCNPs), integrating the advantages of upconversion luminescence and magnetic resonance imaging (MRI) modalities, are capturing increasing attention because they are promising to improve the accuracy of diagnosis. The embedded Gd(3+) ions in UCNPs, however, have an indistinct MRI enhancement owing to the inefficient exchange of magnetic fields with the surrounding water protons. In this study, a novel approach is developed to improve the MR imaging sensitivity of Gd(3+)-ion-doped UCNPs. Bovine serum albumin (BSA) bundled with DTPA-Gd(3+) (DTPA(Gd)) is synthesized both as the MR imaging sensitivity synergist and phase-transfer ligand for the surface engineering of UCNPs. The external Gd(3+) ion attachment strategy is found to significant improve the MR imaging sensitivity of Gd(3+)-ion-doped UCNPs. The relaxivity analysis shows that UCNPs@BSA·DTPA(Gd) exhibit higher relaxivity values than do UCNPs@BSA without DTPA(Gd) moieties. Another relaxivity study discloses a striking message that the relaxivity value does not always reflect the realistic MRI enhancement capability. The high concentration of Gd(3+)-ion-containing UCNPs with further surface-engineered BSA·DTPA(Gd) (denoted as UCNPs-H@BSA·DTPA(Gd)) exhibits a more pronounced MRI enhancement capability compared to the other two counterparts [UCNPs-N@BSA·DTPA(Gd) and UCNPs-L@BSA·DTPA(Gd) (-N and -L are denoted as zero and low concentrations of Gd(3+) ion doping, respectively)], even though it holds the lowest r1 of 1.56 s(-1) per mmol L(-1) of Gd(3+). The physicochemical properties of UCNPs are essentially maintained after BSA·DTPA(Gd) surface decoration with good colloidal stability, in addition to improving the MR imaging sensitivity. In vivo T1-weighted MRI shows potent tumor-enhanced MRI with UCNPs-H@BSA·DTPA(Gd). An in vivo biodistribution study indicates that it is gradually excreted from the body via hepatobiliary and renal processing with no obvious toxicity. It could therefore be concluded, with improved MR imaging sensitivity by an internal and external incorporation of Gd(3+) strategy, that UCNPs-H@BSA·DTPA(Gd) presents great potential as an alternative in tumor-targeted MR imaging.