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1.
Chunxia Qiao Xiaoling Lang Longlong Luo Shusheng Geng Ming Lv Jing Geng Xinying Li Jiannan Feng Beifen Shen Yan Li 《Biotechnology letters》2017,39(9):1309-1323
Objectives
To find a “me-better” antibody by epitope-specific antibody optimization and multi-parametric analysis.Results
Using epitope-specific library based on the commercial drug, Pertuzumab/2C4, we screened a novel human anti-HER2 antibody, MIL5, which has slightly higher affinity than the drug. MIL5 and 2C4 share the same epitope to bind HER2; however, MIL5 bound to HER2 His235–His245 more tightly than 2C4, which could be the main reason of its enhanced affinity. In vivo experiments also showed MIL5 had stronger anti-cancer activity than 2C4; however, the classical flow cytometry assays to detect cell apoptosis or cycling did not show convincing evidence of the advantages of MIL5. Thus we introduced the multi-parameter in-cell analysis method to evaluate the superiority of MIL5 to 2C4 in arresting cancer cells in G2-phase to inhibit cell growth and/or proliferation.Conclusion
Multi-parametric method confirmed stronger arrest of G2 by MIL5 to show better anti-cancer function both in vitro and in vivo than 2C4.2.
Background
Few finite element models (FEM) have been developed to describe the electric field, specific absorption rate (SAR), and the temperature distribution surrounding hepatic radiofrequency ablation probes. To date, a coupled finite element model that accounts for the temperature-dependent electrical conductivity changes has not been developed for ablation type devices. While it is widely acknowledged that accounting for temperature dependent phenomena may affect the outcome of these models, the effect has not been assessed.Methods
The results of four finite element models are compared: constant electrical conductivity without tissue perfusion, temperature-dependent conductivity without tissue perfusion, constant electrical conductivity with tissue perfusion, and temperature-dependent conductivity with tissue perfusion.Results
The data demonstrate that significant errors are generated when constant electrical conductivity is assumed in coupled electrical-heat transfer problems that operate at high temperatures. These errors appear to be closely related to the temperature at which the ablation device operates and not to the amount of power applied by the device or the state of tissue perfusion.Conclusion
Accounting for temperature-dependent phenomena may be critically important in the safe operation of radiofrequency ablation device that operate near 100°C.3.
N. Cesbron A.-L. Royer Y. Guitton A. Sydor B. Le Bizec G. Dervilly-Pinel 《Metabolomics : Official journal of the Metabolomic Society》2017,13(8):99
Introduction
Collecting feces is easy. It offers direct outcome to endogenous and microbial metabolites.Objectives
In a context of lack of consensus about fecal sample preparation, especially in animal species, we developed a robust protocol allowing untargeted LC-HRMS fingerprinting.Methods
The conditions of extraction (quantity, preparation, solvents, dilutions) were investigated in bovine feces.Results
A rapid and simple protocol involving feces extraction with methanol (1/3, M/V) followed by centrifugation and a step filtration (10 kDa) was developed.Conclusion
The workflow generated repeatable and informative fingerprints for robust metabolome characterization.4.
Dimitrios J. Floros Paul R. Jensen Pieter C. Dorrestein Nobuhiro Koyama 《Metabolomics : Official journal of the Metabolomic Society》2016,12(9):145
Introduction
Natural products from culture collections have enormous impact in advancing discovery programs for metabolites of biotechnological importance. These discovery efforts rely on the metabolomic characterization of strain collections.Objective
Many emerging approaches compare metabolomic profiles of such collections, but few enable the analysis and prioritization of thousands of samples from diverse organisms while delivering chemistry specific read outs.Method
In this work we utilize untargeted LC–MS/MS based metabolomics together with molecular networking to inventory the chemistries associated with 1000 marine microorganisms.Result
This approach annotated 76 molecular families (a spectral match rate of 28 %), including clinically and biotechnologically important molecules such as valinomycin, actinomycin D, and desferrioxamine E. Targeting a molecular family produced primarily by one microorganism led to the isolation and structure elucidation of two new molecules designated maridric acids A and B.Conclusion
Molecular networking guided exploration of large culture collections allows for rapid dereplication of know molecules and can highlight producers of uniques metabolites. These methods, together with large culture collections and growing databases, allow for data driven strain prioritization with a focus on novel chemistries.5.
Rachel A. Spicer Christoph Steinbeck 《Metabolomics : Official journal of the Metabolomic Society》2018,14(1):16
Introduction
Data sharing is being increasingly required by journals and has been heralded as a solution to the ‘replication crisis’.Objectives
(i) Review data sharing policies of journals publishing the most metabolomics papers associated with open data and (ii) compare these journals’ policies to those that publish the most metabolomics papers.Methods
A PubMed search was used to identify metabolomics papers. Metabolomics data repositories were manually searched for linked publications.Results
Journals that support data sharing are not necessarily those with the most papers associated to open metabolomics data.Conclusion
Further efforts are required to improve data sharing in metabolomics.6.
Angela Lombardi Bruno Trimarco Guido Iaccarino Gaetano Santulli 《Cell communication and signaling : CCS》2017,15(1):47
Background
One of the most common side effects of the immunosuppressive drug tacrolimus (FK506) is the increased risk of new-onset diabetes mellitus. However, the molecular mechanisms underlying this association have not been fully clarified.Methods
We studied the effects of the therapeutic dose of tacrolimus on mitochondrial fitness in beta-cells.Results
We demonstrate that tacrolimus impairs glucose-stimulated insulin secretion (GSIS) in beta-cells through a previously unidentified mechanism. Indeed, tacrolimus causes a decrease in mitochondrial Ca2+ uptake, accompanied by altered mitochondrial respiration and reduced ATP production, eventually leading to impaired GSIS.Conclusion
Our observations individuate a new fundamental mechanism responsible for the augmented incidence of diabetes following tacrolimus treatment. Indeed, this drug alters Ca2+ fluxes in mitochondria, thereby compromising metabolism-secretion coupling in beta-cells.7.
Background
Adverse drug reactions (ADRs) are unintended and harmful reactions caused by normal uses of drugs. Predicting and preventing ADRs in the early stage of the drug development pipeline can help to enhance drug safety and reduce financial costs.Methods
In this paper, we developed machine learning models including a deep learning framework which can simultaneously predict ADRs and identify the molecular substructures associated with those ADRs without defining the substructures a-priori.Results
We evaluated the performance of our model with ten different state-of-the-art fingerprint models and found that neural fingerprints from the deep learning model outperformed all other methods in predicting ADRs. Via feature analysis on drug structures, we identified important molecular substructures that are associated with specific ADRs and assessed their associations via statistical analysis.Conclusions
The deep learning model with feature analysis, substructure identification, and statistical assessment provides a promising solution for identifying risky components within molecular structures and can potentially help to improve drug safety evaluation.8.
Roman Akasov Anastasia Gileva Daria Zaytseva-Zotova Sergey Burov Isabelle Chevalot Emmanuel Guedon Elena Markvicheva 《Biotechnology letters》2017,39(1):45-53
Objectives
To design novel 3D in vitro co-culture models based on the RGD-peptide-induced cell self-assembly technique.Results
Multicellular spheroids from M-3 murine melanoma cells and L-929 murine fibroblasts were obtained directly from monolayer culture by addition of culture medium containing cyclic RGD-peptide. To reach reproducible architecture of co-culture spheroids, two novel 3D in vitro models with well pronounced core–shell structure from tumor spheroids and single mouse fibroblasts were developed based on this approach. The first was a combination of a RGD-peptide platform with the liquid overlay technique with further co-cultivation for 1–2 days. The second allowed co-culture spheroids to generate within polyelectrolyte microcapsules by cultivation for 2 weeks. M-3 cells (a core) and L-929 fibroblasts (a shell) were easily distinguished by confocal microscopy due to cell staining with DiO and DiI dyes, respectively.Conclusions
The 3D co-culture spheroids are proposed as a tool in tumor biology to study cell–cell interactions as well as for testing novel anticancer drugs and drug delivery vehicles.9.
Background
In recent years the visualization of biomagnetic measurement data by so-called pseudo current density maps or Hosaka-Cohen (HC) transformations became popular.Methods
The physical basis of these intuitive maps is clarified by means of analytically solvable problems.Results
Examples in magnetocardiography, magnetoencephalography and magnetoneurography demonstrate the usefulness of this method.Conclusion
Hardware realizations of the HC-transformation and some similar transformations are discussed which could advantageously support cross-platform comparability of biomagnetic measurements.10.
Benjamin H Natelson Roxann Intriligator Neil S Cherniack Helena K Chandler Julian M Stewart 《Dynamic medicine : DM》2007,6(1):2
Context
Patients with chronic fatigue syndrome and those with orthostatic intolerance share many symptoms, yet questions exist as to whether CFS patients have physiological evidence of orthostatic intolerance.Objective
To determine if some CFS patients have increased rates of orthostatic hypotension, hypertension, tachycardia, or hypocapnia relative to age-matched controls.Design
Assess blood pressure, heart rate, respiratory rate, end tidal CO2 and visual analog scales for orthostatic symptoms when supine and when standing for 8 minutes without moving legs.Setting
Referral practice and research center.Participants
60 women and 15 men with CFS and 36 women and 4 men serving as age matched controls with analyses confined to 62 patients and 35 controls showing either normal orthostatic testing or a physiological abnormal test.Main outcome measures
Orthostatic tachycardia; orthostatic hypotension; orthostatic hypertension; orthostatic hypocapnia or combinations thereof.Results
CFS patients had higher rates of abnormal tests than controls (53% vs 20%, p < .002), but rates of orthostatic tachycardia, orthostatic hypotension, and orthostatic hypertension did not differ significantly between patients and controls (11.3% vs 5.7%, 6.5% vs 2.9%, 19.4% vs 11.4%, respectively). In contrast, rates of orthostatic hypocapnia were significantly higher in CFS than in controls (20.6% vs 2.9%, p < .02). This CFS group reported significantly more feelings of illness and shortness of breath than either controls or CFS patients with normal physiological tests.Conclusion
A substantial number of CFS patients have orthostatic intolerance in the form of orthostatic hypocapnia. This allows subgrouping of patients with CFS and thus reduces patient pool heterogeneity engendered by use of a clinical case definition.11.
Introduction
Untargeted metabolomics is a powerful tool for biological discoveries. To analyze the complex raw data, significant advances in computational approaches have been made, yet it is not clear how exhaustive and reliable the data analysis results are.Objectives
Assessment of the quality of raw data processing in untargeted metabolomics.Methods
Five published untargeted metabolomics studies, were reanalyzed.Results
Omissions of at least 50 relevant compounds from the original results as well as examples of representative mistakes were reported for each study.Conclusion
Incomplete raw data processing shows unexplored potential of current and legacy data.12.
13.
Background
Long-term exposure to drugs of abuse causes an upregulation of the cAMP-signaling pathway in the nucleus accumbens and other forebrain regions, this common neuroadaptation is thought to underlie aspects of drug tolerance and dependence. Phosphodiesterase 4 (PDE4) is an enzyme that the selective hydrolyzes intracellular cAMP. It is expressed in several brain regions that regulate the reinforcing effects of drugs of abuse.Objective
Here, we review the current knowledge about central nervous system (CNS) distribution of PDE4 isoforms and the effects of systemic and brain-region specific inhibition of PDE4 on behavioral models of drug addiction.Methods
A systematic literature search was performed using the Pubmed.Results
Using behavioral sensitization, conditioned place preference and drug self-administration as behavioral models, a large number of studies have shown that local or systemic administration of PDE4 inhibitors reduce drug intake and/or drug seeking for psychostimulants, alcohol, and opioids in rats or mice.Conclusions
Preclinical studies suggest that PDE4 could be a therapeutic target for several classes of substance use disorder. We conclude by identifying opportunities for the development of subtype-selective PDE4 inhibitors that may reduce addiction liability and minimize the side effects that limit the clinical potential of non-selective PDE4 inhibitors. Several PDE4 inhibitors have been clinically approved for other diseases. There is a promising possibility to repurpose these PDE4 inhibitors for the treatment of drug addiction as they are safe and well-tolerated in patients.14.
Jamie V. de Seymour Stephanie Tu Xiaoling He Hua Zhang Ting-Li Han Philip N. Baker Karolina Sulek 《Metabolomics : Official journal of the Metabolomic Society》2018,14(6):79
Introduction
Intrahepatic cholestasis of pregnancy (ICP) is a common maternal liver disease; development can result in devastating consequences, including sudden fetal death and stillbirth. Currently, recognition of ICP only occurs following onset of clinical symptoms.Objective
Investigate the maternal hair metabolome for predictive biomarkers of ICP.Methods
The maternal hair metabolome (gestational age of sampling between 17 and 41 weeks) of 38 Chinese women with ICP and 46 pregnant controls was analysed using gas chromatography–mass spectrometry.Results
Of 105 metabolites detected in hair, none were significantly associated with ICP.Conclusion
Hair samples represent accumulative environmental exposure over time. Samples collected at the onset of ICP did not reveal any metabolic shifts, suggesting rapid development of the disease.15.
Renato de Souza Pinto Lemgruber Kaspar Valgepea Mark P. Hodson Ryan Tappel Sean D. Simpson Michael Köpke Lars K. Nielsen Esteban Marcellin 《Metabolomics : Official journal of the Metabolomic Society》2018,14(3):35
Introduction
Quantification of tetrahydrofolates (THFs), important metabolites in the Wood–Ljungdahl pathway (WLP) of acetogens, is challenging given their sensitivity to oxygen.Objective
To develop a simple anaerobic protocol to enable reliable THFs quantification from bioreactors.Methods
Anaerobic cultures were mixed with anaerobic acetonitrile for extraction. Targeted LC–MS/MS was used for quantification.Results
Tetrahydrofolates can only be quantified if sampled anaerobically. THF levels showed a strong correlation to acetyl-CoA, the end product of the WLP.Conclusion
Our method is useful for relative quantification of THFs across different growth conditions. Absolute quantification of THFs requires the use of labelled standards.16.
Sonia Liggi Christine Hinz Zoe Hall Maria Laura Santoru Simone Poddighe John Fjeldsted Luigi Atzori Julian L. Griffin 《Metabolomics : Official journal of the Metabolomic Society》2018,14(4):52
Introduction
Data processing is one of the biggest problems in metabolomics, given the high number of samples analyzed and the need of multiple software packages for each step of the processing workflow.Objectives
Merge in the same platform the steps required for metabolomics data processing.Methods
KniMet is a workflow for the processing of mass spectrometry-metabolomics data based on the KNIME Analytics platform.Results
The approach includes key steps to follow in metabolomics data processing: feature filtering, missing value imputation, normalization, batch correction and annotation.Conclusion
KniMet provides the user with a local, modular and customizable workflow for the processing of both GC–MS and LC–MS open profiling data.17.
Young-Jun Choi Hyemin Kim Ji-Woo Kim Seokjoo Yoon Han-Jin Park 《Biotechnology letters》2018,40(5):755-763
Objectives
The aim of the study is to generate a spherical three-dimensional (3D) aggregate of hepatocyte-like cells (HLCs) differentiated from human embryonic stem cells and to investigate the effect of the 3D environment on hepatic maturation and drug metabolism.Results
Quantitative real-time PCR analysis indicated that gene expression of mature hepatocyte markers, drug-metabolizing enzymes, and hepatic transporters was significantly higher in HLCs cultured in the 3D system than in those cultured in a two-dimensional system (p < 0.001). Moreover, hepatocyte-specific functions, including albumin secretion and bile canaliculi formation, were increased in HLCs cultured in the 3D system. In particular, 3D spheroidal culture increased expression of CES1 and BCHE, which encode hepatic esterases (p < 0.001). The enhanced activities of these hepatic esterases were confirmed by the cholinesterase activity assay and the increased susceptibility of HLCs to oseltamivir, which is metabolized by CES1.Conclusions
3D spheroidal culture enhances the maturation and drug metabolism of stem cell-derived HLCs, and this may help to optimize hepatic differentiation protocols for hepatotoxicity testing.18.
Andrew Brandmaier Sheng-Qi Hou Sandra Demaria Silvia C. Formenti Wen H. Shen 《生物学前沿》2017,12(3):163-174
Background
PTEN is well known to function as a tumor suppressor that antagonizes oncogenic signaling and maintains genomic stability. The PTEN gene is frequently deleted or mutated in human cancers and the wide cancer spectrum associated with PTEN deficiency has been recapitulated in a variety of mouse models of Pten deletion or mutation. Pten mutations are highly penetrant in causing various types of spontaneous tumors that often exhibit resistance to anticancer therapies including immunotherapy. Recent studies demonstrate that PTEN also regulates immune functionality.Objective
To understand the multifaceted functions of PTEN as both a tumor suppressor and an immune regulator.Methods
This review will summarize the emerging knowledge of PTEN function in cancer immunoediting. In addition, the mechanisms underlying functional integration of various PTEN pathways in regulating cancer evolution and tumor immunity will be highlighted.Results
Recent preclinical and clinical studies revealed the essential role of PTEN in maintaining immune homeostasis, which significantly expands the repertoire of PTEN functions. Mechanistically, aberrant PTEN signaling alters the interplay between the immune system and tumors, leading to immunosuppression and tumor escape.Conclusion
Rational design of personalized anti-cancer treatment requires mechanistic understanding of diverse PTEN signaling pathways in modulation of the crosstalk between tumor and immune cells.19.
Ferran Casbas Pinto Srinivarao Ravipati David A. Barrett T. Charles Hodgman 《Metabolomics : Official journal of the Metabolomic Society》2017,13(7):81
Introduction
It is difficult to elucidate the metabolic and regulatory factors causing lipidome perturbations.Objectives
This work simplifies this process.Methods
A method has been developed to query an online holistic lipid metabolic network (of 7923 metabolites) to extract the pathways that connect the input list of lipids.Results
The output enables pathway visualisation and the querying of other databases to identify potential regulators. When used to a study a plasma lipidome dataset of polycystic ovary syndrome, 14 enzymes were identified, of which 3 are linked to ELAVL1—an mRNA stabiliser.Conclusion
This method provides a simplified approach to identifying potential regulators causing lipid-profile perturbations.20.
Nadine Strehmel David Strunk Veronika Strehmel 《Metabolomics : Official journal of the Metabolomic Society》2017,13(11):135