10 research outputs found
ELIXIR and Toxicology: a community in development [version 2; peer review: 2 approved]
Toxicology has been an active research field for many decades, with academic, industrial and government involvement. Modern omics and computational approaches are changing the field, from merely disease-specific observational models into target-specific predictive models. Traditionally, toxicology has strong links with other fields such as biology, chemistry, pharmacology, and medicine. With the rise of synthetic and new engineered materials, alongside ongoing prioritisation needs in chemical risk assessment for existing chemicals, early predictive evaluations are becoming of utmost importance to both scientific and regulatory purposes. ELIXIR is an intergovernmental organisation that brings together life science resources from across Europe. To coordinate the linkage of various life science efforts around modern predictive toxicology, the establishment of a new ELIXIR Community is seen as instrumental. In the past few years, joint efforts, building on incidental overlap, have been piloted in the context of ELIXIR. For example, the EU-ToxRisk, diXa, HeCaToS, transQST, and the nanotoxicology community have worked with the ELIXIR TeSS, Bioschemas, and Compute Platforms and activities. In 2018, a core group of interested parties wrote a proposal, outlining a sketch of what this new ELIXIR Toxicology Community would look like. A recent workshop (held September 30th to October 1st, 2020) extended this into an ELIXIR Toxicology roadmap and a shortlist of limited investment-high gain collaborations to give body to this new community. This Whitepaper outlines the results of these efforts and defines our vision of the ELIXIR Toxicology Community and how it complements other ELIXIR activities
Ferromagnetic particles for an improved heterogeneous bioassay performance on a digital lab-on-a-chip
A newly developed scavenging system for administration of nitrous oxide during labour: safe occupational use
Metastasectomy for visceral and skeletal oligorecurrent prostate cancer
OBJECTIVES: Metastasis direct therapy (MDT) is a common practice in different fields of oncology. However, there is a lack of data on surgical MDT in visceral/skeletal oligometastatic prostate cancer (PCa). We aimed to assess the role of surgical excision of visceral and skeletal PCa recurrence. METHODS: Seventeen PCa patients experienced metachronous visceral or skeletal oligometastatic recurrence following maximal local treatment. Oligometastatic recurrence was defined as 1-3 lesions, detected with the best imaging technique available at the time of diagnosis. All patients underwent metastasectomy and were followed for a median of 43Â months. Postoperative complications were graded using the Clavien-Dindo classification of surgical complications. Kaplan-Meier plots were used to assess overall survival. RESULTS: Fourteen patients (82%) had visceral lesions, two had bone lesions (12%), and one had an abdominal wall metastasis (6%). Four patients (24%) were under active ADT at the time of metastasectomy. PSA decreased after metastasectomy in 16 (94%) patients. Ten (77%) of the 13 ADT-naĂŻve patients had a PSA decrease ofââ„â50%. Following metastasectomy, 16 (94.1%) patients developed metastatic recurrence of which 11 (64.7%) were again oligometastatic, amenable for repeated MDT. The median time to metastatic recurrence was 14Â months (range 6.4-40). We observed 8% Clavien-Dindo grade 3-4 complications in 21 procedures. CONCLUSIONS: In this report, we analyzed the outcomes of surgical excision of visceral and skeletal PCa recurrence following primary treatment. We found that removing metastasis to the bone and viscera can be associated with long-term disease-free periods at a low rate of serious complications. These exploratory results should be confirmed in prospective studies.status: publishe
Metastasectomy for visceral and skeletal oligorecurrent prostate cancer (vol 37, pg 1543, 2019)
The authors have requested the removal of the Excel file in Electronic Supplementary Material to protect patient's privacy.status: publishe
Metastasectomy for visceral and skeletal oligorecurrent prostate cancer
Objectives Metastasis direct therapy (MDT) is a common practice in different fields of oncology. However, there is a lack of data on surgical MDT in visceral/skeletal oligometastatic prostate cancer (PCa). We aimed to assess the role of surgical excision of visceral and skeletal PCa recurrence. Methods Seventeen PCa patients experienced metachronous visceral or skeletal oligometastatic recurrence following maximal local treatment. Oligometastatic recurrence was defined as 1-3 lesions, detected with the best imaging technique available at the time of diagnosis. All patients underwent metastasectomy and were followed for a median of 43 months. Postoperative complications were graded using the Clavien-Dindo classification of surgical complications. Kaplan-Meier plots were used to assess overall survival. Results Fourteen patients (82%) had visceral lesions, two had bone lesions (12%), and one had an abdominal wall metastasis (6%). Four patients (24%) were under active ADT at the time of metastasectomy. PSA decreased after metastasectomy in 16 (94%) patients. Ten (77%) of the 13 ADT-naive patients had a PSA decrease of >= 50%. Following metastasectomy, 16 (94.1%) patients developed metastatic recurrence of which 11 (64.7%) were again oligometastatic, amenable for repeated MDT. The median time to metastatic recurrence was 14 months (range 6.4-40). We observed 8% Clavien-Dindo grade 3-4 complications in 21 procedures. Conclusions In this report, we analyzed the outcomes of surgical excision of visceral and skeletal PCa recurrence following primary treatment. We found that removing metastasis to the bone and viscera can be associated with long-term disease-free periods at a low rate of serious complications. These exploratory results should be confirmed in prospective studies
Tandem mass spectrometry identification and LCâMS quantification of intact cytokinin nucleotides in K-562 human leukemia cells
ELIXIR and Toxicology: a community in development
International audienceToxicology has been an active research field for many decades, with academic, industrial and government involvement. Modern omics and computational approaches are changing the field, from merely disease-specific observational models into target-specific predictive models. Traditionally, toxicology has strong links with other fields such as biology, chemistry, pharmacology and medicine. With the rise of synthetic and new engineered materials, alongside ongoing prioritisation needs in chemical risk assessment for existing chemicals, early predictive evaluations are becoming of utmost importance to both scientific and regulatory purposes. ELIXIR is an intergovernmental organisation that brings together life science resources from across Europe. To coordinate the linkage of various life science efforts around modern predictive toxicology, the establishment of a new ELIXIR Community is seen as instrumental. In the past few years, joint efforts, building on incidental overlap, have been piloted in the context of ELIXIR. For example, the EU-ToxRisk, diXa, HeCaToS, transQST, and the nanotoxicology community have worked with the ELIXIR TeSS, Bioschemas, and Compute Platforms and activities. In 2018, a core group of interested parties wrote a proposal, outlining a sketch of what this new ELIXIR Toxicology Community would look like. A recent workshop (held September 30th to October 1st, 2020) extended this into an ELIXIR Toxicology roadmap and a shortlist of limited investment-high gain collaborations to give body to this new community. This Whitepaper outlines the results of these efforts and defines our vision of the ELIXIR Toxicology Community and how it complements other ELIXIR activities
Development and external validation of nomograms to predict adverse pathological characteristics after robotic prostatectomy : results of a prospective, multi-institutional, nationwide series
Background: The possibility of predicting pathologic features before surgery can support clinicians in selecting the best treatment strategy for their patients. We sought to develop and externally validate pretreatment nomograms for the prediction of pathological features from a prospective multicentre series of robotic-assisted laparoscopic prostatectomy (RALP) procedures.
Design, setting, and participants: Between 2009 and 2016, data from 6823 patients undergoing RALP in 25 academic and community hospitals were prospectively collected by the Belgian Cancer Registry. Logistic regression models were applied to predict extraprostatic extension (EPE; pT3a,b-4), seminal vesicle invasion (SVI; pT3b), and high-grade locally advanced disease (HGLA; pT3b-4 and Gleason score [GS] 8-10) using the following preoperative covariates: prostate-specific antigen, clinical T stage, biopsy GS, and percentage of positive biopsy cores. Internal and external validation was performed.
Outcome measurements and statistical analysis: The stability of the model was assessed via tenfold cross-validation using 80% of the cohort. The nomograms were independently externally validated using the test cohort. The discriminative accuracy of the nomograms was quantified as the area under the receiver operating characteristic curve and graphically represented using calibration plots.
Result and limitation: The nomograms predicting EPE, SVI, HGLA showed discriminative accuracy of 77%, 82%, and 88%, respectively. Following external validation, the accuracy remained stable. The prediction models showed excellent calibration properties.
Conclusion:We developed and externally validated multi-institutional nomograms to predict pathologic features after RALP. These nomograms can be implemented in the clinical setting or patient selection in clinical trials.
Patient summary: We developed novel nomograms using nationwide data to predict postoperative pathologic features and lethal prostate cancer. (C) 2018 Published by Elsevier B.V. on behalf of European Association of Urology
Development and External Validation of Nomograms To Predict Adverse Pathological Characteristics After Robotic Prostatectomy: Results of a Prospective, Multi-institutional, Nationwide series
BACKGROUND: The possibility of predicting pathologic features before surgery can support clinicians in selecting the best treatment strategy for their patients. We sought to develop and externally validate pretreatment nomograms for the prediction of pathological features from a prospective multicentre series of robotic-assisted laparoscopic prostatectomy (RALP) procedures. DESIGN, SETTING, AND PARTICIPANTS: Between 2009 and 2016, data from 6823 patients undergoing RALP in 25 academic and community hospitals were prospectively collected by the Belgian Cancer Registry. Logistic regression models were applied to predict extraprostatic extension (EPE; pT3a,b-4), seminal vesicle invasion (SVI; pT3b), and high-grade locally advanced disease (HGLA; pT3b-4 and Gleason score [GS] 8-10) using the following preoperative covariates: prostate-specific antigen, clinical T stage, biopsy GS, and percentage of positive biopsy cores. Internal and external validation was performed. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The stability of the model was assessed via tenfold cross-validation using 80% of the cohort. The nomograms were independently externally validated using the test cohort. The discriminative accuracy of the nomograms was quantified as the area under the receiver operating characteristic curve and graphically represented using calibration plots. RESULTS AND LIMITATION: The nomograms predicting EPE, SVI, HGLA showed discriminative accuracy of 77%, 82%, and 88%, respectively. Following external validation, the accuracy remained stable. The prediction models showed excellent calibration properties. CONCLUSIONS: We developed and externally validated multi-institutional nomograms to predict pathologic features after RALP. These nomograms can be implemented in the clinical setting or patient selection in clinical trials. PATIENT SUMMARY: We developed novel nomograms using nationwide data to predict postoperative pathologic features and lethal prostate cancer.status: publishe