462 research outputs found

    Protein substitution to produce a processed cheese with high branched-chain amino acids of medical and genetic importance

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    Background: The most important metabolic impairment in patients with advanced liver disease is characterized by low levels of circulating branched chain amino acids (BCAAs). The etiology of such abnormal amino acid metabolism is multifactorial including protein restricted diet or inadequatenutritional intake as in protein energy malnutrition. Multiple studies report the beneficial effects of BCAAs supplementation to improve plasma amino acids imbalance, several neurologic diseases, protein energy malnutrition, and subsequently the survival rate of cirrhotic patients.Methods: In the present study we used a protein substitution technique to synthesize a new processed cheese as a dairy source rich in BCAAs, with low phenylalanine content manufactured from Ras cheese, kariesh cheese, butter oil and phenylalanine-free milk. Chemical composition, aminoacids analysis, rheological properties and sensory evaluation were done to all of the cheese samples. L-Phenylalanine was selected to induce hepatic and brain affections in Begg Albino strain c (BALB/c) mice model. Effect of 2.5%, 5% and 10% protein-replacement cheese formulas was evaluated among mice groups including histopathological sections of the liver and brain; colorimetric determinationfor liver enzymes; serum total and differential cholesterol profile, serum albumin, globulin and totalprotein along with phenylalanine levels determinations.Results: Analysis of the processed cheese sample with 10% protein substitution revealed that the protein content was 7.42 mg/g (about 50% of the content in the standard processed cheese) while fat content,acidity and moisture were nearly the same. The sensory score for all the formulas ranged from 79–88. Highest content of BCAAs along with least phenylalanine content was attained in the processed cheese with 10% protein substitution. Weight of mice fed on different substitution formulasranged from 22.8 Β± 2.2–24.66 Β± 2.5 g compared with 17.8 Β± 1.9 g in the untreated diseased mice (P< 0.05). Serum phenylalanine was 1.822 Β± 0.42 mg/dl in the mice fed on 10% protein substitution formula compared to 6.2Β± 1.32 mg/dl in the untreated mice (P < 0.01). There was a highly significant difference (

    Rituximab for maintenance of remission in ANCA-associated vasculitis: expert consensus guidelinesβ€”Executive summary

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    [This is the executive summary of Rituximab for maintenance of remission in ANCA-associated vasculitis: expert consensus guidelines: full guideline, doi: 10.1093/rheumatology/kez640

    DNA Damage Triggers Genetic Exchange in Helicobacter pylori

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    Many organisms respond to DNA damage by inducing expression of DNA repair genes. We find that the human stomach pathogen Helicobacter pylori instead induces transcription and translation of natural competence genes, thus increasing transformation frequency. Transcription of a lysozyme-like protein that promotes DNA donation from intact cells is also induced. Exogenous DNA modulates the DNA damage response, as both recA and the ability to take up DNA are required for full induction of the response. This feedback loop is active during stomach colonization, indicating a role in the pathogenesis of the bacterium. As patients can be infected with multiple genetically distinct clones of H. pylori, DNA damage induced genetic exchange may facilitate spread of antibiotic resistance and selection of fitter variants through re-assortment of preexisting alleles in this important human pathogen

    Helicobacter pylori's Unconventional Role in Health and Disease

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    The discovery of a bacterium, Helicobacter pylori, that is resident in the human stomach and causes chronic disease (peptic ulcer and gastric cancer) was radical on many levels. Whereas the mouth and the colon were both known to host a large number of microorganisms, collectively referred to as the microbiome, the stomach was thought to be a virtual Sahara desert for microbes because of its high acidity. We now know that H. pylori is one of many species of bacteria that live in the stomach, although H. pylori seems to dominate this community. H. pylori does not behave as a classical bacterial pathogen: disease is not solely mediated by production of toxins, although certain H. pylori genes, including those that encode exotoxins, increase the risk of disease development. Instead, disease seems to result from a complex interaction between the bacterium, the host, and the environment. Furthermore, H. pylori was the first bacterium observed to behave as a carcinogen. The innate and adaptive immune defenses of the host, combined with factors in the environment of the stomach, apparently drive a continuously high rate of genomic variation in H. pylori. Studies of this genetic diversity in strains isolated from various locations across the globe show that H. pylori has coevolved with humans throughout our history. This long association has given rise not only to disease, but also to possible protective effects, particularly with respect to diseases of the esophagus. Given this complex relationship with human health, eradication of H. pylori in nonsymptomatic individuals may not be the best course of action. The story of H. pylori teaches us to look more deeply at our resident microbiome and the complexity of its interactions, both in this complex population and within our own tissues, to gain a better understanding of health and disease

    Improved Response to Disasters and Outbreaks by Tracking Population Movements with Mobile Phone Network Data: A Post-Earthquake Geospatial Study in Haiti

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    Linus Bengtsson and colleagues examine the use of mobile phone positioning data to monitor population movements during disasters and outbreaks, finding that reports on population movements can be generated within twelve hours of receiving data

    Phase II study of the farnesyltransferase inhibitor R115777 in advanced melanoma (CALGB 500104)

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    BACKGROUND: Multiple farnesylated proteins are involved in signal transduction in cancer. Farnesyltransferase inhibitors (FTIs) have been developed as a strategy to inhibit the function of these proteins. As FTIs inhibit proliferation of melanoma cell lines, we undertook a study to assess the impact of a FTI in advanced melanoma. As farnesylated proteins are also important for T cell activation, measurement of effects on T cell function was also pursued. METHODS: A 3-stage trial design was developed with a maximum of 40 patients and early stopping if there were no responders in the first 14, or fewer than 2 responders in the first 28 patients. Eligibility included performance status of 0–1, no prior chemotherapy, at most 1 prior immunotherapy, no brain metastases, and presence of at least 2 cutaneous lesions amenable to biopsy. R115777 was administered twice per day for 21 days of a 28-day cycle. Patients were evaluated every 2 cycles by RECIST. Blood and tumor were analyzed pre-treatment and during week 7. RESULTS: Fourteen patients were enrolled. Two patients had grade 3 toxicities, which included myelosuppression, nausea/vomiting, elevated BUN, and anorexia. There were no clinical responses. All patients analyzed showed potent inhibition of FT activity (85-98%) in tumor tissue; inhibition of phosphorylated ERK and Akt was also observed. T cells showed evidence of FT inhibition and diminished IFN-Ξ³ production. CONCLUSIONS: Despite potent target inhibition, R115777 showed no evidence of clinical activity in this cohort of melanoma patients. Inhibition of T cell function by FTIs has potential clinical implications. Clinicaltrials.gov number NCT0006012

    Evaluation of seven tumour markers in pleural fluid for the diagnosis of malignant effusions

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    Carcinoembryonic antigen (CEA), carbohydrate antigens 15–3, 19–9 and 72–4 (CA 15–3, CA 19–9 and CA 72–4), cytokeratin 19 fragments (CYFRA 21–1), neuron-specific enolase (NSE) and squamous cell carcinoma antigen (SCC) were evaluated in pleural fluid for the diagnosis of malignant effusions. With a specificity of 99%, determined in a series of 121 benign effusions, the best individual diagnostic sensitivities in the whole series of 215 malignant effusions or in the subgroup of adenocarcinomas were observed with CEA, CA 15–3 and CA 72–4. As expected, a high sensitivity was obtained with SCC in squamous cell carcinomas and with NSE in small-cell lung carcinomas. CYFRA and/or CA 15–3 were frequently increased in mesotheliomas. Discriminant analysis showed that the optimal combination for diagnosis of non-lymphomatous malignant effusions was CEA + CA 15–3 + CYFRA + NSE: sensitivity of 94.4% with an overall specificity of 95%. In malignant effusions with a negative cytology, 83.9% were diagnosed using this association. The association CYFRA + NSE + SCC was able to discriminate adenocarcinomas from small-cell lung cancers. Regarding their sensitivity and their complementarity, CEA, CA 15–3, CYFRA 21–1, NSE and SCC appear to be very useful to improve the diagnosis of malignant pleural effusions. Β© 1999 Cancer Research Campaig

    Quantitative Proteomic and Interaction Network Analysis of Cisplatin Resistance in HeLa Cells

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    Cisplatin along with other platinum based drugs are some of the most widely used chemotherapeutic agents. However drug resistance is a major problem for the successful chemotherapeutic treatment of cancer. Current evidence suggests that drug resistance is a multifactorial problem due to changes in the expression levels and activity of a wide number of proteins. A majority of the studies to date have quantified mRNA levels between drug resistant and drug sensitive cell lines. Unfortunately mRNA levels do not always correlate with protein expression levels due to post-transcriptional changes in protein abundance. Therefore global quantitative proteomics screens are needed to identify the protein targets that are differentially expressed in drug resistant cell lines. Here we employ a quantitative proteomics technique using stable isotope labeling with amino acids in cell culture (SILAC) coupled with mass spectrometry to quantify changes in protein levels between cisplatin resistant (HeLa/CDDP) and sensitive HeLa cells in an unbiased fashion. A total of 856 proteins were identified and quantified, with 374 displaying significantly altered expression levels between the cell lines. Expression level data was then integrated with a network of protein-protein interactions, and biological pathways to obtain a systems level view of proteome changes which occur with cisplatin resistance. Several of these proteins have been previously implicated in resistance towards platinum-based and other drugs, while many represent new potential markers or therapeutic targets

    Enzymes Are Enriched in Bacterial Essential Genes

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    Essential genes, those indispensable for the survival of an organism, play a key role in the emerging field, synthetic biology. Characterization of functions encoded by essential genes not only has important practical implications, such as in identifying antibiotic drug targets, but can also enhance our understanding of basic biology, such as functions needed to support cellular life. Enzymes are critical for almost all cellular activities. However, essential genes have not been systematically examined from the aspect of enzymes and the chemical reactions that they catalyze. Here, by comprehensively analyzing essential genes in 14 bacterial genomes in which large-scale gene essentiality screens have been performed, we found that enzymes are enriched in essential genes. Essential enzymes have overrepresented ligases (especially those forming carbon-oxygen bonds and carbon-nitrogen bonds), nucleotidyltransferases and phosphotransferases, while have underrepresented oxidoreductases. Furthermore, essential enzymes tend to associate with more gene ontology domains. These results, from the aspect of chemical reactions, provide further insights into the understanding of functions needed to support natural cellular life, as well as synthetic cells, and provide additional parameters that can be integrated into gene essentiality prediction algorithms
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