162 research outputs found
Nonribosomal peptide synthetases:Engineering, characterization and biotechnological potential
Nonribosomal peptide synthetases:Engineering, characterization and biotechnological potential
Nonribosomal peptide synthetases:Engineering, characterization and biotechnological potential
Non-ribosomale peptide synthetases (NRPS) zijn uitzonderlijk grote, modulaire en complexe moleculaire systemen, die verantwoordelijk zijn voor de productie van belangrijke bioactieve stoffen, zoals antibiotica, anti-kanker medicijnen, pigmenten, enzovoorts. Ondanks dat het steeds makkelijker wordt dit soort enzymen te identificeren en (gedeeltelijk) te classificeren, is het nog steeds ongelofelijk complex om het volledige potentieel van NRPS te benutten. Sinds de ontdekking van de eerste antibiotica, is er een toenemende interesse voor de ontwikkeling van tools voor het ontrafelen en engineering van NRPS. In onze huidige wereld, waarin we geconfronteerd worden met een globale antibiotica-resistentie crisis, is het van essentieel belang dat nieuwe antibiotica ontdekt en ontwikkeld worden. Dit proefschrift beschrijft naast specifieke nieuwe tools en strategieën voor de ontwikkeling en engineering van NRPS, ook in het algemeen de fundamentele aanpak van huidige bottlenecks in de ontwikkeling van nieuwe antibiotica. De gecombineerde kennis en strategieën, omschreven in dit proefschrift, zouden niet alleen kunnen worden gebruikt voor de adaptatie van al bestaande antibiotica voor nieuwe toepassingen, maar zouden ook kunnen leiden tot alternatieve routes in de ontwikkeling van een volgende, meer robuuste generatie antibiotica, hopelijk toepasbaar als moderne geneesmiddelen.Nonribosomal peptide synthetases or NRPS, are extraordinarily large, modular and complex molecular machines responsible for the production of important bioactive compounds, such as antibiotics, anti-cancer drugs as well as pigments, among many others. Even though it has become increasingly simple to identify and partially classify this kind of enzyme, it still remains an incredibly delicate task to harness their full potential. Since the dawn of the discovery and application of early antibiotics, there has been a thriving interest in the development of tools for the understanding and especially the engineering of NRPS. In nowadays world, where we face a global antibiotic-resistance crisis, the discovery and development of novel antibiotics has never been more crucial to fight this battle. This work does not only present a series of new tools and strategies, to develop and engineer NRPS, but furthermore elucidated fundamental ways to tackle and bypass major bottlenecks in the greater scheme of novel antibiotics development. The combined knowledge and strategies laid out in this thesis, may not only allow for the adaptation of already established antibiotics towards new applications, but could also pave the road towards a new, more robust next generation of antibiotic compounds, able to fulfill the demands of modern medicine
Nonribosomal peptide synthetases:Engineering, characterization and biotechnological potential
Non-ribosomale peptide synthetases (NRPS) zijn uitzonderlijk grote, modulaire en complexe moleculaire systemen, die verantwoordelijk zijn voor de productie van belangrijke bioactieve stoffen, zoals antibiotica, anti-kanker medicijnen, pigmenten, enzovoorts. Ondanks dat het steeds makkelijker wordt dit soort enzymen te identificeren en (gedeeltelijk) te classificeren, is het nog steeds ongelofelijk complex om het volledige potentieel van NRPS te benutten. Sinds de ontdekking van de eerste antibiotica, is er een toenemende interesse voor de ontwikkeling van tools voor het ontrafelen en engineering van NRPS. In onze huidige wereld, waarin we geconfronteerd worden met een globale antibiotica-resistentie crisis, is het van essentieel belang dat nieuwe antibiotica ontdekt en ontwikkeld worden. Dit proefschrift beschrijft naast specifieke nieuwe tools en strategieën voor de ontwikkeling en engineering van NRPS, ook in het algemeen de fundamentele aanpak van huidige bottlenecks in de ontwikkeling van nieuwe antibiotica. De gecombineerde kennis en strategieën, omschreven in dit proefschrift, zouden niet alleen kunnen worden gebruikt voor de adaptatie van al bestaande antibiotica voor nieuwe toepassingen, maar zouden ook kunnen leiden tot alternatieve routes in de ontwikkeling van een volgende, meer robuuste generatie antibiotica, hopelijk toepasbaar als moderne geneesmiddelen
Nonribosomal peptide synthetases:Engineering, characterization and biotechnological potential
Five Fractions versus Seven Fractions SBRT for Intermediate- and High-Risk Prostate Cancer: A Propensity Score Matched Pair Analysis.
PURPOSE
To compare two stereotactic body radiotherapy (SBRT) regimens in patients with intermediate- or high-risk prostate cancer with regards toxicity and efficacy.
METHODS/MATERIAL
We retrospectively collected data from 198 patients treated with SBRT for prostate cancer at two different institutions. Patients received either 35-36.25 Gy in five fractions (group A) using Cyberknife robotic platform or 42.7 Gy in seven fractions (group B) using a C-arm LINAC (image-guided). Propensity score matching was done (2:1 nearest neighbor matching without replacement), resulting in 120 patients (80 patients for group A, 40 patients for group B). Toxicity, PSA nadir, biochemical failure and disease-free survival (DFS) were analyzed.
RESULTS
Median follow up of all patients was 13 months (range 1-91 months). Overall, 23.3% of patients had ≥G2 acute GU toxicity (21.1% group A versus 30% group B (p = 0.222)) and 6.6% of patients ≥G2 GI toxicity (2.5% versus 15% (p = 0.010)). There was one acute G3 GU toxicity in arm A and one acute G4 rectal bleeding in group B (anticoagulated patient). Regarding late toxicity, 14.1% of patients had ≥G2 late GU toxicity (17.4% versus 6.6% (p = 0.159)) and 5.0% of patients had ≥G2 late GI toxicity (1.4% versus 13.3% (p = 0.013)). There was one G3 late GU toxicity in arm B and two G3 late GI toxicities, one in each arm. Relative median PSA reduction was 92.4% (-53.9-99.9%) from baseline PSA (93.7% (-53.9-99.9%) in group A versus 87.7% (39.8-99.9%) in group B (p = 0.043). In total, 4.2% of patients had biochemical relapse, 5.0% in group A and 2.5% in group B (p = 0.518). One-year DFS in the overall cohort was 97.3%, 98.8% in group A and 94.3% in group B (p = 0.318).
CONCLUSION
Both SBRT regimens have acceptable acute and late toxicity and good efficacy. There are significantly more GI toxicities in the seven-fraction regimen. Longer follow-up is warranted for better comparison of long-term efficacy
Impact of Surgical Training on Incidence of Surgical Site Infection
Background: Despite availability of other training forms, tutorial assistance cannot be entirely replaced in surgical education. Concerns exist that tutorial assistance may lead to an increased rate of surgical site infection (SSI). The purpose of the present study was to investigate whether the risk of SSI is higher after surgery with tutorial assistance than after surgery performed autonomously by a fully trained surgeon. Methods: All consecutive visceral, vascular, and traumatological inpatient procedures at a Swiss University Hospital were prospectively recorded during a 24-month period, and the patients were followed for 12months to ascertain the occurrence of SSI. Using univariable and multivariable logistic regressions, we assessed the association of tutorial assistance surgery with SSI in 6,103 interventions. Results: Autonomously performed surgery was associated with SSI in univariable analysis (5.36% SSI vs. 3.81% for tutorial assistance, p=0.006). In multivariable analysis, the odds of SSI for tutorial assistance was no longer significantly lower (Odds Ratio [OR]=0.82; 95% Confidence Interval [CI]: 0.62-1.09; p=0.163). Conclusions: Surgical training does not lead to higher SSI rate if trainees are adequately supervised and interventions are carefully selected. Although other forms of training are useful, tutorial assistance in the operating room continues to be the mainstay of surgical educatio
Applications of Machine Learning in Palliative Care: A Systematic Review
Objective: To summarize the available literature on using machine learning (ML) for palliative care practice as well as research and to assess the adherence of the published studies to the most important ML best practices. Methods: The MEDLINE database was searched for the use of ML in palliative care practice or research, and the records were screened according to PRISMA guidelines. Results: In total, 22 publications using machine learning for mortality prediction (n = 15), data annotation (n = 5), predicting morbidity under palliative therapy (n = 1), and predicting response to palliative therapy (n = 1) were included. Publications used a variety of supervised or unsupervised models, but mostly tree-based classifiers and neural networks. Two publications had code uploaded to a public repository, and one publication uploaded the dataset. Conclusions: Machine learning in palliative care is mainly used to predict mortality. Similarly to other applications of ML, external test sets and prospective validations are the exception
Applications of Machine Learning in Palliative Care: A Systematic Review.
Objective: To summarize the available literature on using machine learning (ML) for palliative care practice as well as research and to assess the adherence of the published studies to the most important ML best practices. Methods: The MEDLINE database was searched for the use of ML in palliative care practice or research, and the records were screened according to PRISMA guidelines. Results: In total, 22 publications using machine learning for mortality prediction (n = 15), data annotation (n = 5), predicting morbidity under palliative therapy (n = 1), and predicting response to palliative therapy (n = 1) were included. Publications used a variety of supervised or unsupervised models, but mostly tree-based classifiers and neural networks. Two publications had code uploaded to a public repository, and one publication uploaded the dataset. Conclusions: Machine learning in palliative care is mainly used to predict mortality. Similarly to other applications of ML, external test sets and prospective validations are the exception
Economic Burden of Surgical Site Infections at a European University Hospital
Objective. To quantify the economic burden of in-hospital surgical site infections (SSIs) at a European university hospital. Design. Matched case-control study nested in a prospective observational cohort study. Setting. Basel University Hospital in Switzerland, where an average of 28,000 surgical procedures are performed per year. Methods. All in-hospital occurrences of SSI associated with surgeries performed between January 1, 2000, and December 31, 2001, by the visceral, vascular, and traumatology divisions at Basel University Hospital were prospectively recorded. Each case patient was matched to a control patient by age, procedure code, and National Nosocomial Infection Surveillance System risk index. The case-control pairs were analyzed for differences in cost of hospital care and in provision of specialized care. Results. A total of 6,283 procedures were performed:187 SSIs were detected in inpatients, 168 of whom were successfully matched with a control patient. For case patients, the mean additional hospital cost was SwF19,638 (95% confidence interval [CI], SwF8,492-SwF30,784); the mean additional postoperative length of hospital stay was 16.8 days (95% CI, 13-20.6 days); and the mean additional in-hospital duration of antibiotic therapy was 7.4 days (95% CI, 5.1-9.6 days). Differences were primarily attributable to organ space SSIs (n = 76). Conclusions. Ina European university hospital setting, SSIs are costly and constitute a heavy and potentially preventable burden on both patients and healthcare provider
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