MKG-GC: A multi-task learning-based knowledge graph construction framework with personalized application to gastric cancer.

Over the past decade, information for precision disease medicine has accumulated in the form of textual data. To effectively utilize this expanding medical text, we proposed a multi-task learning-based framework based on hard parameter sharing for knowledge graph construction (MKG), and then used it to automatically extract gastric cancer (GC)-related biomedical knowledge from the literature and identify GC drug candidates. In MKG, we designed three separate modules, MT-BGIPN, MT-SGTF and MT-ScBERT, for entity recognition, entity normalization, and relation classification, respectively. To address the challenges posed by the long and irregular naming of medical entities, the MT-BGIPN utilized bidirectional gated recurrent unit and interactive pointer network techniques, significantly improving entity recognition accuracy to an average F1 value of 84.5% across datasets. In MT-SGTF, we employed the term frequency-inverse document frequency and the gated attention unit. These combine both semantic and characteristic features of entities, resulting in an average Hits@ 1 score of 94.5% across five datasets. The MT-ScBERT integrated cross-text, entity, and context features, yielding an average F1 value of 86.9% across 11 relation classification datasets. Based on the MKG, we then developed a specific knowledge graph for GC (MKG-GC), which encompasses a total of 9129 entities and 88,482 triplets. Lastly, the MKG-GC was used to predict potential GC drugs using a pre-trained language model called BioKGE-BERT and a drug-disease discriminant model based on CNN-BiLSTM. Remarkably, nine out of the top ten predicted drugs have been previously reported as effective for gastric cancer treatment. Finally, an online platform was created for exploration and visualization of MKG-GC at https://www.yanglab-mi.org.cn/MKG-GC/.

Comparison of six Z-score formulas based on echocardiography for coronary artery lesions in Kawasaki disease.

GOAL: Kawasaki disease (KD) patients are at risk of developing the serious complication of coronary artery dilation (CAD). To diagnose CAD caused by KD, various Z-Score formulas are used worldwide. This paper aims to evaluate the differences and inclusiveness among the six most commonly used Z-Score formulas in diagnosing CAD in Suzhou, China. Additionally, the study seeks to compare the differences in CAD diagnosis among different high-risk factor groups. By doing so, this research provides a valuable reference for accurately diagnosing CAD in KD patients. METHOD: This paper presents a retrospective analysis of 1509 patients diagnosed with KD at the Children's Hospital of Soochow University between January 2018 and December 2020. We collected the patients' clinical and echocardiographic data and used six Z-Score formulas (Kobayashi et al., de Zorzi et al., Kurotobi et al., McCrindle et al., Olivieri et al., and Dallaire et al.) to diagnose the degree of CAD in different segments. We then compared the diagnostic differences and inclusiveness of these formulas, especially the diagnostic differences in medium to giant CAA. To achieve this, we divided the patients into groups based on their age (≤12 months, 13-30 months, and > 30 months) and fever duration (≤5 days, 6-7 days, 8-9 days, and ≥ 10 days). Using the McNemar test and the Kappa test, we compared the differences and the consistencies of CDA diagnosis among the six Z-Score formulas. Moreover, we used the Friedman test and Chi-square segmentation formula to compare the differences in age and number of fever duration between groups and to compare each Z-Score formula pair within the group. RESULTS: Except for the LMCA segment, where there were no statistically significant differences between de Zorzi formula and McCrindle formula, the Z-score formulas showed statistically significant differences in the degree of CAD diagnosis across all other segments. Inclusiveness assessment revealed that Kobayashi formula and Dallaire formula showed significantly higher rates of dilatation (6.58% and 5.32%), or of small aneurysms (6.52% and 4.52%) compared to other formulas (1.0%-1.73%). Medium aneurysms were also more likely to be identified with Kobayashi and Dallaire formulas (0.8% and 0.8%) compared to the remaining formulas (0.13-0.40%). There are significant differences in the diagnoses of medium to giant CAA made by these six formulas in LAD and RCA. The longer the duration of fever and the younger the age, the higher the diagnosis rates of CAD and CAA. There were no statistically significant differences between de Zorzi formula and McCrindle formula, de Zorzi formula and Oliveri formula, and Kurotobi formula and Dallaire formula within the four groups based on the duration of fever. Similarly, there were no statistically significant differences between Kobayashi formula and Dallaire formula, and between de Zorzi formula and Oliveri formula in the age groups of ≤12 months and 13-30 months. CONCLUSION: There are diagnostic differences among these six Z-score formulas, considering the aforementioned statistics. Kobayashi formula and Dallaire formula are more inclusive, and less likely to under-diagnose significant CAD. They perform evenly for dilatation only, for small aneurysms and the median size aneurysms, and that is for segments of LMCA, LAD and RCA. In addition, McCrindle formula joins the "inclusive" pack for LAD and RCA in the matter of CAD. The younger the age of the patients and the longer the duration of fever, the higher the diagnosis rates of CAD and CAA. Furthermore, the younger the age of the patients and the shorter the duration of fever, the greater the differences between the various formulas.

Histone lactylation inhibits RARγ expression in macrophages to promote colorectal tumorigenesis through activation of TRAF6-IL-6-STAT3 signaling.

Macrophages are phenotypically and functionally diverse in the tumor microenvironment (TME). However, how to remodel macrophages with a protumor phenotype and how to manipulate them for therapeutic purposes remain to be explored. Here, we show that in the TME, RARγ is downregulated in macrophages, and its expression correlates with poor prognosis in patients with colorectal cancer (CRC). In macrophages, RARγ interacts with tumor necrosis factor receptor-associated factor 6 (TRAF6), which prevents TRAF6 oligomerization and autoubiquitination, leading to inhibition of nuclear factor κB signaling. However, tumor-derived lactate fuels H3K18 lactylation to prohibit RARγ gene transcription in macrophages, consequently enhancing interleukin-6 (IL-6) levels in the TME and endowing macrophages with tumor-promoting functions via activation of signal transducer and activator of transcription 3 (STAT3) signaling in CRC cells. We identified that nordihydroguaiaretic acid (NDGA) exerts effective antitumor action by directly binding to RARγ to inhibit TRAF6-IL-6-STAT3 signaling. This study unravels lactate-driven macrophage function remodeling by inhibition of RARγ expression and highlights NDGA as a candidate compound for treating CRC.

Digital economy: an effective path for promoting residents' health in China.

The primary prerequisite for socioeconomic growth is good health, hence promoting residents' health is a vital objective of public policies. It is yet up for debate whether or not the digital economy (DE), which will be crucial to future economic growth, will eventually result in improvements in residents' health. Utilizing the China Family Panel Studies (CFPS) data in 2020, we explore how the DE affects residents' health. The findings reveal that residents' health is greatly enhanced by the DE. The eastern region sees a more dramatic improvement in residents' health as a result of the DE. Additionally, the DE can improve residents' health through the promotion of regional green development. The study's findings add to our knowledge of how the DE impacts residents' health while also offering recommendations for achieving universal health.

Large-scale ORF screening based on LC-MS to discover novel lncRNA-encoded peptides responding to ionizing radiation and microgravity.

In the human genome, 98% of genes can be transcribed into non-coding RNAs (ncRNAs), among which lncRNAs and their encoded peptides play important roles in regulating various aspects of cellular processes and may serve as crucial factors in modulating the biological effects induced by ionizing radiation and microgravity. Unfortunately, there are few reports in space radiation biology on lncRNA-encoded peptides below 10kD due to limitations in detection techniques. To fill this gap, we integrated a variety of methods based on genomics and peptidomics, and discovered 22 lncRNA-encoded small peptides that are sensitive to space radiation and microgravity, which have never been reported before. We concurrently validated the transmembrane helix, subcellular localization, and biological function of these small peptides using bioinformatics and molecular biology techniques. More importantly, we found that these small peptides function independently of the lncRNAs that encode them. Our findings have uncovered a previously unknown human proteome encoded by 'non-coding' genes in response to space conditions and elucidated their involvement in biological processes, providing valuable strategies for individual protection mechanisms for astronauts who carry out deep space exploration missions in space radiation environments.

A SARS-CoV-2 nanoparticle vaccine based on chemical conjugation of loxoribine and SpyCatcher/SpyTag.

SARS-CoV-2 is a particularly transmissible virus that renders the worldwide COVID-19 pandemic and global severe respiratory distress syndrome. Protein-based vaccines hold great advantages to build the herd immunity for their specificity, effectiveness, and safety. Receptor-binding domain (RBD) of SARS-CoV-2 is an appealing antigen for vaccine development. However, adjuvants and delivery system are necessitated to enhance the immunogenicity of RBD. In the present study, RBD was chemically conjugated with loxoribine and SpyCatcher/SpyTag, followed by assembly to form a nanoparticle vaccine. Loxoribine (a TLR7/8 agonist) acted as an adjuvant, and nanoparticles functioned as delivery system for the antigen and the adjuvant. The nanoparticle vaccine elicited high RBD-specific antibody titers, high neutralizing antibody titer, and strong ACE2-blocking activity. It stimulated high splenic levels of Th1-type cytokines (IFN-γ and IL-2) and Th2-type cytokines (IL-4 and IL-5) in BALB/c mice. It promoted the splenocyte proliferation, enhanced the CD4+ and CD8+ T cell percentage and stimulated the maturation of dendritic cells. The vaccine did not render apparent toxicity to the organs of mice. Thus, the nanoparticle vaccine was of potential to act as a preliminarily safe and effective candidate against SARS-CoV-2.

Mucosal SARS-CoV-2 Nanoparticle Vaccine Based on Mucosal Adjuvants and Its Immune Effectiveness by Intranasal Administration.

SARS-CoV-2 is a respiratory virus that causes significant threats to human health. Mucosal immunity provides a first-line defense to prevent the infection of SARS-CoV-2 in the respiratory tract. Because most SARS-CoV-2 vaccines could not stimulate mucosal immunity in the respiratory tract, appropriate mucosal adjuvants or delivery systems are needed for mucosal vaccine development. Mannan, polyarginine, and 2',3'-cGAMP are three mucosal adjuvants that could stimulate mucosal immunity. In the present study, the three adjuvants were assembled with a receptor-binding domain (RBD) by electrostatic interaction to generate a nanoparticle vaccine (RBD-MP-cG). RBD-MP-cG elicited mucosal IgA and IgG response in bronchoalveolar lavage and nasal lavage by intranasal administration. It induced a robust RBD-specific antibody response, high levels of protective neutralizing antibody, and ACE2-blocking activity in the mouse sera. It stimulated the splenic secretion of high levels of Th1-, Th2-, and Th17-type cytokines. Thus, RBD-MP-cG elicited strong mucosal immunity and systematic immunity by intranasal administration. RBD-MP-cG was expected to act as a safe, effective, and easily produced mucosal nanoparticle vaccine to combat the infection of SARS-CoV-2.

Discovery of selective HDAC6 inhibitors based on a multi-layer virtual screening strategy.

The abnormal enhancement of histone deacetylase 6 (HDAC6) has been demonstrated to be closely related to the occurrence and development of various malignant tumors, attracting extensive attention as a promising target for cancer therapy. Currently, only limited selective HDAC6 inhibitors have entered clinical trials, making the rapid discovery of selective HDAC6 inhibitors with safety profiles particularly urgent. In this study, a multi-layer virtual screening workflow was established, and the representative compounds screened were biologically evaluated in combination with enzyme inhibitory and anti-tumor cell proliferation experiments. The experimental results showed that the screened compounds L-25, L-32, L-45 and L-81 exhibited nanomolar inhibitory activity against HDAC6, and exerted a certain degree of anti-proliferative activities against tumor cells, especially the cytotoxicity of L-45 to A375 (IC50 = 11.23 ± 1.27 µM) and the cytotoxicity of L-81 against HCT-116 (IC50 = 12.25 ± 1.13 µM). Additionally, the molecular mechanisms underlying the subtype selective inhibitory activities of the selected compounds were further elucidated using computational approaches, and the hotspot residues on HDAC6 contributing to the ligands' binding were identified. In summary, this study established a multi-layer screening scheme to quickly and effectively screen out hit compounds with enzyme inhibitory activity and anti-tumor cell proliferation, providing novel scaffolds for the subsequent anti-tumor drug design based on HDAC6 target.

Hydroxyethyl Starch-Bovine Hemoglobin Conjugate as an Effective Oxygen Carrier with the Ability to Expand Plasma.

Hemorrhagic shock leads to intravasal volume deficiency, tissue hypoxia, and cellular anaerobic metabolism. Hemoglobin (Hb) could deliver oxygen for hypoxic tissues but is unable to expand plasma. Hydroxyethyl starch (HES) could compensate for the intravasal volume deficiency but cannot deliver oxygen. Thus, bovine Hb (bHb) was conjugated with HES (130 kDa and 200 kDa) to develop an oxygen carrier with the ability to expand plasma. Conjugation with HES increased the hydrodynamic volume, colloidal osmotic pressure, and viscosity of bHb. It slightly perturbed the quaternary structure and heme environment of bHb. The partial oxygen pressures at 50% saturation (P 50) of the two conjugates (bHb-HES130 and bHb-HES200) were 15.1 and 13.9 mmHg, respectively. The two conjugates showed no apparent side effects on the morphology and rigidity, hemolysis, and platelet aggregation of red blood cells of Wistar rats. Thus, bHb-HES130 and bHb-HES200 were expected to function as an effective oxygen carrier with the ability to expand plasma.

Identifying Lymph Node Metastasis-Related Factors in Breast Cancer Using Differential Modular and Mutational Structural Analysis.

Complex diseases are generally caused by disorders of biological networks and/or mutations in multiple genes. Comparisons of network topologies between different disease states can highlight key factors in their dynamic processes. Here, we propose a differential modular analysis approach that integrates protein-protein interactions with gene expression profiles for modular analysis, and introduces inter-modular edges and date hubs to identify the "core network module" that quantifies the significant phenotypic variation. Then, based on this core network module, key factors, including functional protein-protein interactions, pathways, and driver mutations, are predicted by the topological-functional connection score and structural modeling. We applied this approach to analyze the lymph node metastasis (LNM) process in breast cancer. The functional enrichment analysis showed that both inter-modular edges and date hubs play important roles in cancer metastasis and invasion, and in metastasis hallmarks. The structural mutation analysis suggested that the LNM of breast cancer may be the outcome of the dysfunction of rearranged during transfection (RET) proto-oncogene-related interactions and the non-canonical calcium signaling pathway via an allosteric mutation of RET. We believe that the proposed method can provide new insights into disease progression such as cancer metastasis.

MiR-200/183 family-mediated module biomarker for gastric cancer progression: an AI-assisted bioinformatics method with experimental functional survey.

BACKGROUND: Gastric cancer (GC) is a major cancer burden throughout the world with a high mortality rate. The performance of current predictive and prognostic factors is still limited. Integrated analysis is required for accurate cancer progression predictive biomarker and prognostic biomarkers that help to guide therapy. METHODS: An AI-assisted bioinformatics method that combines transcriptomic data and microRNA regulations were used to identify a key miRNA-mediated network module in GC progression. To reveal the module's function, we performed the gene expression analysis in 20 clinical samples by qRT-PCR, prognosis analysis by multi-variable Cox regression model, progression prediction by support vector machine, and in vitro studies to elaborate the roles in GC cells migration and invasion. RESULTS: A robust microRNA regulated network module was identified to characterize GC progression, which consisted of seven miR-200/183 family members, five mRNAs and two long non-coding RNAs H19 and CLLU1. Their expression patterns and expression correlation patterns were consistent in public dataset and our cohort. Our findings suggest a two-fold biological potential of the module: GC patients with high-risk score exhibited a poor prognosis (p-value < 0.05) and the model achieved AUCs of 0.90 to predict GC progression in our cohort. In vitro cellular analyses shown that the module could influence the invasion and migration of GC cells. CONCLUSIONS: Our strategy which combines AI-assisted bioinformatics method with experimental and clinical validation suggested that the miR-200/183 family-mediated network module as a "pluripotent module", which could be potential marker for GC progression.

A Protein Co-Conservation Network Model Characterizes Mutation Effects on SARS-CoV-2 Spike Protein.

The emergence of numerous variants of SARS-CoV-2 has presented challenges to the global efforts to control the COVID-19 pandemic. The major mutation is in the SARS-CoV-2 viral envelope spike protein that is responsible for virus attachment to the host, and is the main target for host antibodies. It is critically important to study the biological effects of the mutations to understand the mechanisms of how mutations alter viral functions. Here, we propose a protein co-conservation weighted network (PCCN) model only based on the protein sequence to characterize the mutation sites by topological features and to investigate the mutation effects on the spike protein from a network view. Frist, we found that the mutation sites on the spike protein had significantly larger centrality than the non-mutation sites. Second, the stability changes and binding free energy changes in the mutation sites were positively significantly correlated with their neighbors' degree and the shortest path length separately. The results indicate that our PCCN model provides new insights into mutations on spike proteins and reflects the mutation effects on protein function alternations.

DeepTP: A Deep Learning Model for Thermophilic Protein Prediction.

Thermophilic proteins have important value in the fields of biopharmaceuticals and enzyme engineering. Most existing thermophilic protein prediction models are based on traditional machine learning algorithms and do not fully utilize protein sequence information. To solve this problem, a deep learning model based on self-attention and multiple-channel feature fusion was proposed to predict thermophilic proteins, called DeepTP. First, a large new dataset consisting of 20,842 proteins was constructed. Second, a convolutional neural network and bidirectional long short-term memory network were used to extract the hidden features in protein sequences. Different weights were then assigned to features through self-attention, and finally, biological features were integrated to build a prediction model. In a performance comparison with existing methods, DeepTP had better performance and scalability in an independent balanced test set and validation set, with AUC values of 0.944 and 0.801, respectively. In the unbalanced test set, DeepTP had an average precision (AP) of 0.536. The tool is freely available.

Integrated multi-dimensional analysis highlights DHCR7 mutations involving in cholesterol biosynthesis and contributing therapy of gastric cancer.

BACKGROUND: Genetic background plays an important role in the occurrence and development of gastric cancer (GC). With the application of genome-wide association study (GWAS), an increasing number of tumor susceptibility genes in gastric cancer have been discovered. While little of them can be further applicated in clinical diagnosis and treatment due to the lack of in-depth analysis. METHODS: A GWAS of peripheral blood leukocytes from GC patients was performed to identify and obtain genetic background data. In combination with a clinical investigation, key SNP mutations and mutated genes were screened. Via in vitro and in vivo experiments, the function of the mutated gene was verified in GC. Via a combination of molecular function studies and amino acid network analysis, co-mutations were discovered and further identified as potential therapeutic targets. RESULTS: At the genetic level, the G allele of rs104886038 in DHCR7 was a protective factor identified by the GWAS. Clinical investigation showed that patients with the rs104886038 A/G genotype, age ≥ 60, smoking ≥ 10 cigarettes/day, heavy drinking and H. pylori infection were independent risk factors for GC, with odds ratios of 12.33 (95% CI, 2.10 ~ 72.54), 20.42 (95% CI, 2.46 ~ 169.83), and 11.39 (95% CI, 1.82 ~ 71.21), respectively. Then molecular function studies indicated that DHCR7 regulated cell proliferation, migration, and invasion as well as apoptosis resistance via cellular cholesterol biosynthesis pathway. Further amino acid network analysis based on the predicted structure of DHCR7 and experimental verification indicated that rs104886035 and rs104886038 co-mutation reduced the stability of DHCR7 and induced its degradation. DHCR7 mutation suppressed the malignant behaviour of GC cells and induced apoptosis via inhibition on cell cholesterol biosynthesis. CONCLUSION: In this work, we provided a comprehensive multi-dimensional analysis strategy which can be applied to in-depth exploration of GWAS data. DHCR7 and its mutation sites identified by this strategy are potential theratic targets of GC via inhibition of cholesterol biosynthesis.

Next-Generation Sequencing Markup Language (NGSML): A Medium for the Representation and Exchange of NGS Data.

With the increasing demand for low-cost high-throughput sequencing of large genomes, next-generation sequencing (NGS) technology has developed rapidly. NGS can not only be used in basic scientific research but also in clinical diagnostics and healthcare. Numerous software systems and tools have been developed to analyze NGS data, and various data formats have been produced to accommodate different sequencing equipment providers or analytical software. However, the data interoperability between these tools brings great challenges to researchers. A generic format that could be shared by most of the software and tools in the NGS field would make data interoperability and sharing easier. In this paper, we defined a general XML-based NGS markup language (NGSML) format for the representation and exchange of NGS data. We also developed a user-friendly GUI tool, NGSMLEditor, for presenting, creating, editing, and converting NGSML files. By using NGSML, various types of NGS data can be saved in one unified format. Compared with the unstructured plain text file, a structured data format based on XML technology solves the incompatibility of various NGS data formats. The NGSML specifications are freely available from http://www.sysbio.org.cn/NGSML. NGSMLEditor is open source under GNU GPL and can be downloaded from the website.

A comprehensive review on knowledge graphs for complex diseases.

In recent years, knowledge graphs (KGs) have gained a great deal of popularity as a tool for storing relationships between entities and for performing higher level reasoning. KGs in biomedicine and clinical practice aim to provide an elegant solution for diagnosing and treating complex diseases more efficiently and flexibly. Here, we provide a systematic review to characterize the state-of-the-art of KGs in the area of complex disease research. We cover the following topics: (1) knowledge sources, (2) entity extraction methods, (3) relation extraction methods and (4) the application of KGs in complex diseases. As a result, we offer a complete picture of the domain. Finally, we discuss the challenges in the field by identifying gaps and opportunities for further research and propose potential research directions of KGs for complex disease diagnosis and treatment.

SLC6A14 facilitates epithelial cell ferroptosis via the C/EBPß-PAK6 axis in ulcerative colitis.

Emerging evidence suggests that ferroptosis is involved in the pathogenesis of ulcerative colitis (UC). However, the key regulator of this process remains uncertain. In this study, we aimed to explore the roles of solute carrier (SLC) family 6 member 14 (SLC6A14) in regulating ferroptosis in UC. The expression of SLC6A14 was significantly increased and positively associated with that of prostaglandin-endoperoxide synthase 2 (PTGS2) in tissue samples from patients with UC. Moreover, a series of in vitro and in vivo experiments showed that SLC6A14 knockdown markedly suppressed ferroptosis. RNA sequencing revealed that SLC6A14 inhibited the expression of P21 (RAC1)-activated kinase 6 (PAK6) and that PAK6 knockdown abolished the effects of SLC6A14 on RAS-selective lethal 3 (RSL3)-induced ferroptosis in Caco-2 cells. Furthermore, chromatin immunoprecipitation (ChIP) and Western blot analysis demonstrated that SLC6A14 negatively regulated PAK6 expression in a CCAAT enhancer binding protein beta (C/EBPß)-dependent manner. Collectively, these findings indicate that SLC6A14 facilitates ferroptosis in UC by promoting C/EBPß expression and binding activity to inhibit PAK6 expression, suggesting that targeting SLC6A14-C/EBPß-PAK6 axis-mediated ferroptosis may be a promising therapeutic alternative for UC.

A SARS-CoV-2 vaccine based on conjugation of SARS-CoV-2 RBD with IC28 peptide and mannan.

SARS-CoV-2 is a particularly transmissible virus that causes a severe respiratory disease known as COVID-19. Safe and effective vaccines are urgently needed to combat the COVID-19 pandemic. The receptor-binding domain (RBD) of SARS-CoV-2 spike protein elicits most neutralizing antibodies during viral infection and is an ideal antigen for vaccine development. In particular, RBD expressed by E. coli is amenable to low cost and high-yield manufacturability. The adjuvant is necessitated to improve the immunogenicity of RBD. IC28, a TLR5-dependent adjuvant, is a peptide from bacterial flagellin. Mannan is a ligand of TLR-4 or TLR-2 and a polysaccharide adjuvant. Here, IC28 and mannan were both covalently conjugated with RBD from E. coli. The conjugate (RBD-IC28-M) elicited high RBD-specific IgG titers, and a neutralization antibody titer of 201.4. It induced high levels of Th1-type cytokines (IFN-γ) and Th2-type cytokines (IL-5 and IL-10), along with high antigenicity and no apparent toxicity to the organs. The mouse sera of the RBD-IC28-M group competitively interfered with the interaction of RBD and ACE2. Thus, conjugation with IC28 and mannan additively enhanced the humoral and cellular immunity. Our study was expected to provide the feasibility to develop an affordable, easily scalable, effective vaccine SARS-CoV-2 vaccine.

Deciphering the in vivo Dynamic Proteomics of Mesenchymal Stem Cells in Critical Limb Ischemia.

OBJECTIVE: Regenerative therapy using mesenchymal stem cells (MSC) is a promising therapeutic method for critical limb ischemia (CLI). To understand how the cells are involved in the regenerative process of limb ischemia locally, we proposed a metabolic protein labeling method to label cell proteomes in situ and then decipher the proteome dynamics of MSCs in ischemic hind limb. METHODS AND RESULTS: In this study, we overexpressed mutant methionyl-tRNA synthetase (MetRS), which could utilize azidonorleucine (ANL) instead of methionine (Met) during protein synthesis in MSCs. Fluorescent non-canonical amino-acid tagging (FUNCAT) was performed to detect the utilization of ANL in mutant MSCs. Mice with hindlimb ischemia (HLI) or Sham surgery were treated with MetRSmut MSCs or PBS, followed by i.p. administration of ANL at days 0, 2 6, and 13 after surgery. FUNCAT was also performed in hindlimb tissue sections to demonstrate the incorporation of ANL in transplanted cells in situ. At days 1, 3, 7, and 14 after the surgery, laser doppler imaging were performed to detect the blood reperfusion of ischemic limbs. Ischemic tissues were also collected at these four time points for histological analysis including HE staining and vessel staining, and processed for click reaction based protein enrichment followed by mass spectrometry and bioinformatics analysis. The MetRSmut MSCs showed strong green signal in cell culture and in HLI muscles as well, indicating efficient incorporation of ANL in nascent protein synthesis. By 14 days post-treatment, MSCs significantly increased blood reperfusion and vessel density, while reducing inflammation in HLI model compared to PBS. Proteins enriched by click reaction were distinctive in the HLI group vs. the Sham group. 34, 31, 49, and 26 proteins were significantly up-regulated whereas 28, 32, 62, and 27 proteins were significantly down-regulated in HLI vs. Sham at days 1, 3, 7, and 14, respectively. The differentially expressed proteins were more pronounced in the pathways of apoptosis and energy metabolism. CONCLUSION: In conclusion, mutant MetRS allows efficient and specific identification of dynamic cell proteomics in situ, which reflect the functions and adaptive changes of MSCs that may be leveraged to understand and improve stem cell therapy in critical limb ischemia.

H19 promotes aerobic glycolysis, proliferation, and immune escape of gastric cancer cells through the microRNA-519d-3p/lactate dehydrogenase A axis.

Long noncoding RNAs (lncRNAs) have been investigated in multiple human cancers including gastric cancer (GC). Our research aims to explore the role of H19 in aerobic glycolysis, proliferation, and immune escape of GC cells. The expression of H19 in GC samples was analyzed using Gene Expression Profiling Interactive Analysis, Gene Expression Omnibus data, and real-time quantitative PCR analysis. Relative quantification of glucose consumption and lactate production from cell supernatant were applied to assess the aerobic glycolysis of GC cells. Subcellular fractionation, luciferase reporter, and western blot assays certified the binding between genes. Cell Counting Kit-8 and colony formation assays were used to determine GC cell proliferation. Flow cytometry, ELISA, and real-time quantitative PCR assays were applied to analyze the immunosuppressive effect of H19. H19 was highly expressed in samples of patients with GC, and associated with tumor growth in vivo. H19 knockdown suppressed glucose consumption, lactate production, and proliferation of GC cells by regulating the microRNA (miR)-519d-3p/lactate dehydrogenase A (LDHA) axis. Both miR-519d-3p depletion and LDHA overexpression could reverse the H19 knockdown-induced decrease in aerobic glycolysis and proliferation. Moreover, conditioned medium from stable knockdown H19 GC cells modulated the activity of immune cells including γδT cells, Jurkat cells, and tumor-associated macrophages in a miR-519d-3p/LDHA/lactate axis-dependent manner. The H19/miR-519d-3p/LDHA axis mainly contributed to aerobic glycolysis, proliferation, and immune escape of GC cells.