Acute therapy-related myelodysplastic syndromes following capecitabine and oxaliplatin therapy in gastric malignant tumor: A case report.

RATIONAL: Patients with gastric cancer show a relatively low incidence of developing secondary myelodysplastic syndrome (MDS). PATIENT CONCERNS: A 60-year-old man was admitted because of pain and discomfort in the upper abdomen and intermittent abdominal pain. DIAGNOSES: Ulcerative moderately poorly differentiated adenocarcinoma (pT2N2M0G3, stage IIB) and MDS. INTERVENTIONS: The patient underwent chemotherapy with oxaliplatin (OXP, intravenously guttae on day 1) plus capecitabine (CAP, bis in die orally on day 1-14). The patient developed degree III myelosuppression after OXP plus CAP chemotherapy and MDS was subsequently confirmed by diagnosis of the bone marrow biopsy. Temporary but significant hematological improvements were observed after the patient received corresponding treatment, which helped achieve remission and improve pancytopenia. OUTCOMES: The patient presented partial remission after corresponding treatment and no other complications have been recorded. LESSONS: Acute MDS is an unusual adverse effect induced by OXP plus CAP chemotherapy. It is urgent to suggest implementing a supplementary assessment or examination for patients receiving these therapies in future cases.

Effects of prebiotics on the gut microbiota in vitro associated with functional diarrhea in children.

Purpose: Diarrhea is among the top five causes of morbidity and mortality in children. Dysbiosis of the gut microbiota is considered the most important risk factor for diarrhea. Prebiotics have shown efficacy in treating diarrhea by regulating the balance of the gut microbiota in vivo. Methods: In this study, we used an in vitro fermentation system to prevent the interference of host-gut microbe interactions during in vivo examination and investigated the effect of fructo-oligosaccharides (FOS) on gut microbiota composition and metabolism in 39 pediatric patients with functional diarrhea. Results: 16S rRNA sequencing revealed that FOS significantly improved α- and ß-diversity in volunteers with pediatric diarrhea (p < 0.05). This improvement manifested as a significant increase (LDA > 2, p < 0.05) in probiotic bacteria (e.g., Bifidobacterium) and a significant inhibition (LDA > 2, p < 0.05) of harmful bacteria (e.g., Escherichia-Shigella). Notably, the analysis of bacterial metabolites after FOS treatment showed that the decrease in isobutyric acid, isovaleric acid, NH3, and H2S levels was positively correlated with the relative abundance of Lachnoclostridium. This decrease also showed the greatest negative correlation with the abundance of Streptococcus. Random forest analysis and ROC curve validation demonstrated that gut microbiota composition and metabolites were distinct between the FOS treatment and control groups (area under the curve [AUC] > 0.8). Functional prediction using PICRUSt 2 revealed that the FOS-induced alteration of gut microbiota was most likely mediated by effects on starch and sucrose metabolism. Conclusion: This study is the first to evince that FOS can modulate gut microbial disorders in children with functional diarrhea. Our findings provide a framework for the application of FOS to alleviate functional diarrhea in children and reduce the use of antibiotics for managing functional diarrhea-induced disturbances in the gut microbiota.

Severe immune-mediated hepatitis caused by sindilizumab combined with local radiotherapy: a case report.

A man with diffuse large B-cell lymphoma in the nasal cavity was treated with sindilizumab, an immune checkpoint inhibitor, combined with local radiotherapy for multiple nodules of the left upper arm. After a single administration of sindilizumab and 10 radiotherapy treatments, the patient presented with liver dysfunction. Liver function tests showed that the levels of transaminases had increased abnormally and deteriorated though with intense treatment. His bilirubin level was also increased with obvious yellow staining of the skin and sclera. The patient was considered to have severe immune-mediated hepatitis (IMH) caused by sindilizumab combined with local radiotherapy. His liver function did not improve and he died of organ failure. This is a case of rare liver failure which was considered to be IMH induced by synergistic treatment with immune checkpoint therapy and radiotherapy.

Integrating Bipartite Network Projection and KATZ Measure to Identify Novel CircRNA-Disease Associations.

Accumulating biological experiments have shown that circRNAs are closely related to the occurrence and development of many complex human diseases. During recent years, the associations of circRNA with disease have caused more and more researchers to pay attention and to analyze their correlation mechanisms. However, experimental methods for determining the associations of circRNA with a particular disease are still expensive, difficult, and time consuming. Moreover, the available databases related to circRNA-disease correlations have only recently been updated, and only a few computational methods are constructed to predict potential circRNA-disease correlations. Taking into account the limitations of experimental studies, we develop a novel computational method, named IBNPKATZ, for predicting potential circRNA-disease associations, which integrates the bipartite network projection algorithm and KATZ measure. This model is based on the known circRNA-disease associations, combining circRNA similarity and disease similarity. Specifically, the circRNA similarity is derived from the average of the semantic similarity and the Gaussian interaction profile (GIP) kernel similarity of circRNA. Similarly, disease similarity is the mean of the semantic similarity and the GIP kernel similarity of disease. Furthermore, it is semi-supervised and does not require negative samples. Finally, IBNPKATZ achieves reliable AUC of 0.9352 in the leave-one-out cross validation, and case studies show that the circRNA-disease correlations predicted by our method can be successfully demonstrated by relevant experiments. The IBNPKATZ is expected to be a useful biomedical research tool for predicting potential circRNA-disease associations.

Predicting the cytotoxicity of chemicals using ensemble learning methods and molecular fingerprints.

The prediction of compound cytotoxicity is an important part of the drug discovery process. However, it usually appears as poor predictive performance because the datasets are high-throughput and have a class-imbalance problem. In this study, several strategies of performing a structure-activity relationship study for a cytotoxic endpoint in the AID364 dataset were explored to solve the class-imbalance problem. Random forest adaboost was used as the base learners for 10 types of molecular fingerprints and an ensemble method and six data-balancing methods were applied to balance the classes. As a result, the ensemble model using MACCS fingerprint was found to be the best, giving area under the curve of 85.2% ± 0.35%, sensitivity of 81.8% ± 0.65%, and specificity of 76.0% ± 0.12% in fivefold cross-validation and area under the curve of 78.8%, sensitivity of 55.5% and specificity of 78.5% in external validation. Good performance also appeared on other datasets with different sizes/degrees of imbalance. To explore the structural commonality of cytotoxic compounds, several substructures were identified as an important reference for substructure alerts. The convincing results indicate that the proposed models are helpful in predicting the cytotoxicity of chemicals.

The Bipartite Network Projection-Recommended Algorithm for Predicting Long Non-coding RNA-Protein Interactions.

With the development of science and biotechnology, many evidences show that ncRNAs play an important role in the development of important biological processes, especially in chromatin modification, cell differentiation and proliferation, RNA progressing, human diseases, etc. Moreover, lncRNAs account for the majority of ncRNAs, and the functions of lncRNAs are expressed by the related RNA-binding proteins. It is well known that the experimental verification of lncRNA-protein relationships is a waste of time and expensive. So many time-saving and inexpensive computational methods are proposed to uncover potential lncRNA-protein interactions. In this work, we propose a novel computational method to predict the potential lncRNA-protein interactions with the bipartite network projection recommended algorithm (LPI-BNPRA). Our approach is a semi-supervised method based on the lncRNA similarity matrix, protein similarity matrix, and lncRNA-protein interaction matrix. Compared with three previous methods under the leave-one-out cross-validation, our model has a more high-confidence result with the AUC value of 0.8754 and the AUPR value of 0.6283. We also do case studies by the Mus musculus dataset to further reflect the reliability of our approach. This suggests that LPI-BNPRA will be a reliable computational method to uncover lncRNA-protein interactions in biomedical research.

RWLPAP: Random Walk for lncRNA-protein Associations Prediction.

BACKGROUND: During recent years, a lot of experimental studies have shown that lncRNA-binding proteins play a key role in many biomedical processes. Therefore, it is important to predict the potential lncRNA-protein associations in biomedical researches. OBJECTIVE: To predict the associations between lncRNAs and proteins more reliably and more efficiently. METHOD: Considering the limitations of previous computational methods, we introduce a predictive model called Random Walk for lncRNA-Protein Associations Prediction (RWLPAP). It belongs to semi-supervised learning algorithms, and thus RWLPAP successfully avoids the difficulty of extracting negative data sets and features. RESULTS: By the leave-one-out cross validation, we compare RWLPAP with previous methods and conclude that RWLPAP has an AUC of 0.88, which is significantly higher than other three models. It suggests that RWLPAP is more reliable and effective in predicting the interactions between lncRNAs and proteins. CONCLUSION: In the case study, according to the rank of predictive scores, we can find that the scores of some lncRNA-protein associations are highly ranking by our method when is compared with other three methods. It indicates that our method is very effective and comprehensive. Therefore, we can expect that RWLPAP will be a useful bioinformatic tool in the future.

IRWNRLPI: Integrating Random Walk and Neighborhood Regularized Logistic Matrix Factorization for lncRNA-Protein Interaction Prediction.

Long non-coding RNA (lncRNA) plays an important role in many important biological processes and has attracted widespread attention. Although the precise functions and mechanisms for most lncRNAs are still unknown, we are certain that lncRNAs usually perform their functions by interacting with the corresponding RNA- binding proteins. For example, lncRNA-protein interactions play an important role in post transcriptional gene regulation, such as splicing, translation, signaling, and advances in complex diseases. However, experimental verification of lncRNA-protein interactions prediction is time-consuming and laborious. In this work, we propose a computational method, named IRWNRLPI, to find the potential associations between lncRNAs and proteins. IRWNRLPI integrates two algorithms, random walk and neighborhood regularized logistic matrix factorization, which can optimize a lot more than using an algorithm alone. Moreover, the method is semi-supervised and does not require negative samples. Based on the leave-one-out cross validation, we obtain the AUC of 0.9150 and the AUPR of 0.7138, demonstrating its reliable performance. In addition, by means of case study in the "Mus musculus," many lncRNA-protein interactions which are predicted by our method can be successfully confirmed by experiments. This suggests that IRWNRLPI will be a useful bioinformatics resource in biomedical research.

LPI-NRLMF: lncRNA-protein interaction prediction by neighborhood regularized logistic matrix factorization.

LncRNA-protein interactions play important roles in many important cellular processes including signaling, transcriptional regulation, and even the generation and progression of complex diseases. However, experimental methods for determining proteins bound by a specific lncRNA remain expensive, difficult and time-consuming, and only a few theoretical approaches are available for predicting potential lncRNA-protein associations. In this study, we developed a novel matrix factorization computational approach to uncover lncRNA-protein relationships, namely lncRNA-protein interactions prediction by neighborhood regularized logistic matrix factorization (LPI-NRLMF). Moreover, it is a semi-supervised and does not need negative samples. As a result, new model obtained reliable performance in the leave-one-out cross validation (the AUC of 0.9025 and AUPR of 0.6924), which significantly improved the prediction performance of previous models. Furthermore, the case study demonstrated that many lncRNA-protein interactions predicted by our method can be successfully confirmed by experiments. It is anticipated that LPI-NRLMF could serve as a useful resource for potential lncRNA-protein association identification.

PPARα Agonist Stimulated Angiogenesis by Improving Endothelial Precursor Cell Function Via a NLRP3 Inflammasome Pathway.

BACKGROUND: Impaired wound healing is a common complication of diabetes and is the leading cause of lower extremity amputation. Treatment with fenofibrate, a peroxisome proliferators-activated receptor α (PPARα) agonist, was associated with a lower risk of amputations, particularly minor amputations without known large-vessel diseases, probably through non-lipid mechanisms. The current study aimed to test our hypothesis that fenofibrate stimulates angiogenesis and restores endothelial precursor cell (EPC) function via inhibiting Nod-like receptor protein 3 (NLRP3) inflammasome in streptozotocin (STZ)-induced diabetic mice. METHODS: Male C57BL/6 mice were randomly divided into three groups: control, STZ-induced diabetic mice and fenofibrate treated diabetic group. Wound closure was assessed by wound area and CD31 positive capillaries. Both the migration and tube formation capacities of EPCs were measured. Intracellular nitric oxide (NO) and superoxide (O2-) levels were determined. Activity of NLRP3 inflammasome in EPCs was assessed by measuring thioredoxin-interacting protein (TXNIP), NLRP3, and caspase-1 expression. RESULTS: Compared with the untreated diabetic mice, wound closure and capillary densities were significantly increased in fenofibrate treated group. Fenofibrate treatment restored EPC function, increased NO production, and decreased O2- level in EPCs of diabetic mice. Furthermore, fenofibrate deregulated the activity of NLRP3 inflammasome by reducing TXNIP, NLRP3 and caspase-1 expression in EPCs of diabetic mice. In vitro, fenofibrate prevented high glucose induced EPC dysfunction, deregulated NLRP3 inflammasome activity. In addition, fenofibrate inhibited IL-1ß expression caused by combination use of high glucose and lipopolysaccharide. CONCLUSION: Fenofibrate can accelerate wound healing in diabetic mice, which at least in part was mediated by improving the impaired EPC function via a NLRP3 inflammasome pathway, suggesting the significance of PPARα agonists in the treatment of diabetes.

Acarbose Accelerates Wound Healing via Akt/eNOS Signaling in db/db Mice.

Refractory wound is a dreaded complication of diabetes and is highly correlated with EPC dysfunction caused by hyperglycemia. Acarbose is a widely used oral glucose-lowering drug exclusively for T2DM. Previous studies have suggested the beneficial effect of acarbose on improving endothelial dysfunction in patients with T2DM. However, no data have been reported on the beneficial efficacy of acarbose in wound healing impairment caused by diabetes. We herein investigated whether acarbose could improve wound healing in T2DM db/db mice and the possible mechanisms involved. Acarbose hastened wound healing and enhanced angiogenesis, accompanied by increased circulating EPC number in db/db mice. In vitro, a reversed BM-EPC dysfunction was observed after the administration of acarbose in db/db mice, as reflected by tube formation assay. In addition, a significantly increased NO production was also witnessed in BM-EPCs from acarbose treated db/db mice, with decreased O2 levels. Akt inhibitor could abolish the beneficial effect of acarbose on high glucose induced EPC dysfunction in vitro, accompanied by reduced eNOS activation. Acarbose displayed potential effect in promoting wound healing and improving angiogenesis in T2DM mice, which was possibly related to the Akt/eNOS signaling pathway.

Metformin ameliorates insulitis in STZ-induced diabetic mice.

BACKGROUND & AIMS: Metformin is currently the most widely used first-line hypoglycemic agent for diabetes mellitus. Besides glucose-lowering action, there is increasingly interest in the potential anti-inflammatory action of this drug. In the present study, we investigated the actions of metformin on experimental insulitis using STZ-induced diabetic mice. METHODS: Mice with acute diabetes induced by STZ were administered metformin by gavage. Changes of blood glucose and body weight, and the daily amount of food and water intake were measured. Pancreatic tissues were collected for histologic analyses. Pathological assessment and immunohistochemistry analysis were used to determine the effect of metformin on insulitis. Inflammatory cytokines in the pancreas and insulin levels were measured through ELISA analysis. RESULTS: Metformin significantly reduced blood glucose levels and improved aberrant water intake behavior in experimental diabetic mice. No significant differences were observed in terms of body weight and food intake behavior in metformin-treated animals. In the STZ-induced model of diabetes, we found the appearance of pronounced insulitis. However, metformin administration reduced the severity of insulitis assessed by blind pathological scoring. In addition, metformin treatment improved insulin levels in experimental diabetic mice. ELISA assay revealed decreased levels of inflammatory response marker IL-1ß and TNF-α in the pancreatic tissues following metformin treatment. CONCLUSION: Metformin attenuated insulitis in the STZ-induced mice model of diabetes. This islet-protective effect might be partly correlated with the anti-inflammatory action of metformin.

Metformin improves the angiogenic functions of endothelial progenitor cells via activating AMPK/eNOS pathway in diabetic mice.

BACKGROUND: Endothelial dysfunction has been suggested as a possible causal link between hyperglycemia and microvascular complications in diabetes mellitus. The effect of metformin on endothelial progenitor cells (EPCs) is still unclear. This study was designed to test the hypothesis that metformin could accelerate wound healing by improving the impaired EPC functions in streptozotocin-induced diabetic mice. METHODS: Streptozotocin (STZ, 60 mg/kg/d × 5 d, i.p.) was injected to induce type 1 diabetes in male C57BL/6 mice. Mice were treated with metformin (250 mg/kg/d, i.g.) for consecutive 14 days. Wound closure was evaluated by wound area and number of CD31 stained capillaries. Functions of bone marrow-endothelial progenitor cells (BM-EPCs) were assessed by tube formation and migration assays, and expression of AMP-activated protein kinase (AMPK) and endothelial nitric oxide synthase (eNOS) was determined by western blot analysis. RESULTS: Metformin accelerated wound closure and stimulated angiogenesis in diabetic mice. The number of circulating EPCs was increased significantly in metformin treated diabetic mice. Abilities of tube formation and migration of BM-EPCs were impaired in diabetic mice, which were improved by metformin. Expression of both phosphorylated-AMPK and phosphorylated-eNOS was significantly increased, and nitric oxide (NO) production was enhanced by metformin in BM-EPCs of diabetic mice. In vitro, metformin improved impaired BM-EPC functions, and increased phosphorylated-eNOS expression and NO production in cultured BM-EPCs caused by high glucose, which was prevented by the AMPK inhibitor compound C. CONCLUSIONS: Our results suggest that metformin could improve BM-EPC functions in STZ-induced diabetic mice, which was possibly dependent on the AMPK/eNOS pathway.

Glibenclamide attenuates myocardial injury by lipopolysaccharides in streptozotocin-induced diabetic mice.

BACKGROUND: Sepsis is a common disease that continues to increase in incidence in the world. Diseases, such as diabetes mellitus, may make the situation worse. Diabetic patients are at increased risk for common infections. This study was designed to investigate the role of glibenclamide on myocardial injury by lipopolysaccharides (LPS) in streptozotocin induced diabetic mice (STZ-mice). METHODS: LPS was used to induce endotoxemia in STZ-mice. Heart rate and mean arterial pressure were measured by MPA-HBBS. Serum epinephrine level was measured by enzyme-linked immunosorbent assays (ELISA). Myocardial injury was examined by light and transmission electron microscope and TUNEL staining. Macrophage infiltration was measured by immunohistochemistry. Interleukin-1ß (IL-1ß) and tumor necrosis factor-α (TNF-α) levels in myocardial tissue and serum in STZ-mice, and in conditional medium of primary cultured peritoneal macrophages were determined by ELISA. Nalp3 and Caspase-1 protein levels were measured by Western blotting analysis. RESULTS: STZ administration decreased body weight and increased blood glucose in C57BL/6 mice. LPS injection caused decreases of heart rate and mean arterial pressure, and elevated serum epinephrine level in C57BL/6 mice. Compared with control mice without STZ treatment, LPS induced more severe myocardial injury and macrophage infiltration in STZ-mice, which was attenuated by pretreatment of glibenclamide. LPS stimulation enhanced the levels of IL-1ß and TNF-α in both cardiac tissue and serum. Glibenclamide pretreatment significantly inhibited the serum levels of pro-inflammatory cytokines. Either high glucose or LPS increased the levels of IL-1ß and TNF-α in the conditional medium of peritoneal macrophages. Glibenclamide treatment suppressed the increase of IL-1ß level induced by high glucose and LPS. Furthermore, Nalp3 and Caspase-1 levels were markedly increased by high glucose plus LPS, and both proteins were significantly inhibited by glibenclamide treatment. CONCLUSIONS: We conclude that glibenclamide could attenuate myocardial injury induced by LPS challenge in STZ-mice, which was possibly related to inhibiting inflammation through Nalp3 inflammasomes.

Shell cross-linked stearic acid grafted chitosan oligosaccharide self-aggregated micelles for controlled release of paclitaxel.

Stearic acid grafted chitosan oligosaccharide (CSO-SA) with different degree of amino substitution (SD) was synthesized by 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDC)-mediated coupling reaction. The critical micelle concentration (CMC) of CSO-SA with different SD was about 0.06, 0.04, 0.01 mg/ml, respectively. With the increase of micelle concentration, the micelle size decreased, and the zeta potential increased. On the other hand, with the increase of SD of CSO-SA, the micelle size and zeta potential decreased due to the increased hydrophobic interaction of SA and the reduced free amino groups. To increase the stability of the micelle in vivo and controll drug release, the shells of micelles were cross-linked by glutaraldehyde. By controlling the molar ratio of CSO-SA to glutaraldehyde, the cross-linking of intra-micelle could be reached, and the nanoparticle with smaller size than that of its initial micelle was obtained. Paclitaxel was then used as model drug to incorporate into the micelles, and the surfaces of the micelles were further cross-linked by glutaraldehyde to form drug loaded and shell cross-linked nanoparticles. The effects of drug loading, SD of CSO-SA and cross-link degree on the size, zeta potential, drug entrapment efficiency and in vitro drug release behavior of micelles and its cross-linked nanoparticles were investigated. The higher drug entrapment efficiencies (above 94%) were observed in all case. The charged amounts of drug did not affect the drug release behavior. The drug release rate decreased with the increase of SD of CSO-SA and cross-link degree.