The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Brian G Tripney - One of the best experts on this subject based on the ideXlab platform.
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ams 14c dating at the scottish universities environmental Research Centre suerc radiocarbon dating laboratory
Radiocarbon, 2016Co-Authors: Elaine Dunbar, Gordon Cook, P Naysmith, Brian G TripneyAbstract:This paper describes all the major procedures adopted by the Scottish Universities Environmental Research Centre (SUERC) Radiocarbon Dating Laboratory. This includes sample pretreatment, graphite production, accelerator mass spectrometry (AMS) measurement, associated stable isotope measurements, data handling, and age calculations, but with the main emphasis being on the chemical pretreatment methods. All of the above enable the laboratory to provide a complete analytical service comprising advice on sample selection, preparation and analysis of samples, and Bayesian analysis of resulting 14C (and other) data. This applies to both our Research and commercial activities. The pretreatment methods that we mainly focus on are used to remove contaminant carbon from a range of sample types or to isolate a particular chemical fraction from a sample prior to combustion/hydrolysis, graphitization, and subsequent AMS 14C measurement. The methods described are for bone (collagen extraction, with and without ultrafiltration), cremated bone, tooth enamel, charcoal, grain, carbon residues, shell, wood (including alpha-cellulose isolation), peat, sediments, textiles, fuel/biofuel, and forensic samples.
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ams 14 c dating at the scottish universities environmental Research Centre suerc radiocarbon dating laboratory
Radiocarbon, 2016Co-Authors: Elaine Dunbar, P Naysmith, G T Cook, Brian G TripneyAbstract:This paper describes all the major procedures adopted by the Scottish Universities Environmental Research Centre (SUERC) Radiocarbon Dating Laboratory. This includes sample pretreatment, graphite production, accelerator mass spectrometry (AMS) measurement, associated stable isotope measurements, data handling, and age calculations, but with the main emphasis being on the chemical pretreatment methods. All of the above enable the laboratory to provide a complete analytical service comprising advice on sample selection, preparation and analysis of samples, and Bayesian analysis of resulting 14 C (and other) data. This applies to both our Research and commercial activities. The pretreatment methods that we mainly focus on are used to remove contaminant carbon from a range of sample types or to isolate a particular chemical fraction from a sample prior to combustion/hydrolysis, graphitization, and subsequent AMS 14 C measurement. The methods described are for bone (collagen extraction, with and without ultrafiltration), cremated bone, tooth enamel, charcoal, grain, carbon residues, shell, wood (including alpha-cellulose isolation), peat, sediments, textiles, fuel/biofuel, and forensic samples.
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ams 14 c dating at the scottish universities environmental Research Centre suerc radiocarbon dating laboratory corrigendum
Radiocarbon, 2016Co-Authors: Elaine Dunbar, Gordon Cook, P Naysmith, Brian G TripneyAbstract:This paper describes all the major procedures adopted by the Scottish Universities Environmental Research Centre (SUERC) Radiocarbon Dating Laboratory. This includes sample pretreatment, graphite production, accelerator mass spectrometry (AMS) measurement, associated stable isotope measurements, data handling, and age calculations, but with the main emphasis being on the chemical pretreatment methods. All of the above enable the laboratory to provide a complete analytical service comprising advice on sample selection, preparation and analysis of samples, and Bayesian analysis of resulting 14C (and other) data. This applies to both our Research and commercial activities. The pretreatment methods that we mainly focus on are used to remove contaminant carbon from a range of sample types or to isolate a particular chemical fraction from a sample prior to combustion/hydrolysis, graphitization, and subsequent AMS 14C measurement. The methods described are for bone (collagen extraction, with and without ultrafiltration), cremated bone, tooth enamel, charcoal, grain, carbon residues, shell, wood (including alpha-cellulose isolation), peat, sediments, textiles, fuel/biofuel, and forensic samples.
Matthew Broadbent - One of the best experts on this subject based on the ideXlab platform.
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cohort profile of the south london and maudsley nhs foundation trust biomedical Research Centre slam brc case register current status and recent enhancement of an electronic mental health record derived data resource
BMJ Open, 2016Co-Authors: Gayan Perera, Matthew Broadbent, Felicity Callard, Chinkuo Chang, Richard D Hayes, Johnny Downs, Rina Dutta, Andrea C Fernandes, Max Henderson, Richard J JacksonAbstract:Purpose The South London and Maudsley National Health Service (NHS) Foundation Trust Biomedical Research Centre (SLaM BRC) Case Register and its Clinical Record Interactive Search (CRIS) application were developed in 2008, generating a Research repository of real-time, anonymised, structured and open-text data derived from the electronic health record system used by SLaM, a large mental healthcare provider in southeast London. In this paper, we update this register's descriptive data, and describe the substantial expansion and extension of the data resource since its original development. Participants Descriptive data were generated from the SLaM BRC Case Register on 31 December 2014. Currently, there are over 250 000 patient records accessed through CRIS. Findings to date Since 2008, the most significant developments in the SLaM BRC Case Register have been the introduction of natural language processing to extract structured data from open-text fields, linkages to external sources of data, and the addition of a parallel relational database (Structured Query Language) output. Natural language processing applications to date have brought in new and hitherto inaccessible data on cognitive function, education, social care receipt, smoking, diagnostic statements and pharmacotherapy. In addition, through external data linkages, large volumes of supplementary information have been accessed on mortality, hospital attendances and cancer registrations. Future plans Coupled with robust data security and governance structures, electronic health records provide potentially transformative information on mental disorders and outcomes in routine clinical care. The SLaM BRC Case Register continues to grow as a database, with approximately 20 000 new cases added each year, in addition to extension of follow-up for existing cases. Data linkages and natural language processing present important opportunities to enhance this type of Research resource further, achieving both volume and depth of data. However, Research projects still need to be carefully tailored, so that they take into account the nature and quality of the source information.
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clinical risk assessment rating and all cause mortality in secondary mental healthcare the south london and maudsley nhs foundation trust biomedical Research Centre slam brc case register
Psychological Medicine, 2012Co-Authors: Chinkuo Chang, Matthew Broadbent, Matthew Hotopf, Richard D Hayes, Robert StewartAbstract:BACKGROUND: Mental disorders are widely recognized to be associated with increased risk of all-cause mortality. However, the extent to which highest-risk groups for mortality overlap with those viewed with highest concern by mental health services is less clear. The aim of the study was to investigate clinical risk assessment ratings for suicide, violence and self-neglect in relation to all-cause mortality among people receiving secondary mental healthcare. Method A total of 9234 subjects over the age of 15 years were identified from the South London and Maudsley Biomedical Research Centre Case Register who had received a second tier structured risk assessment in the course of their clinical care. A cohort analysis was carried out. Total scores for three risk assessment clusters (suicide, violence and self-neglect) were calculated and Cox regression models used to assess survival from first assessment. RESULTS: A total of 234 deaths had occurred over an average 9.4-month follow-up period. Mortality was relatively high for the cohort overall in relation to national norms [standardized mortality ratio 3.23, 95% confidence interval (CI) 2.83-3.67] but not in relation to other mental health service users with similar diagnoses. Only the score for the self-neglect cluster predicted mortality [hazard ratio (HR) per unit increase 1.14, 95% CI 1.04-1.24] with null findings for assessed risk of suicide or violence (HRs per unit increase 1.00 and 1.06 respectively). CONCLUSIONS: Level of clinician-appraised risk of self-neglect, but not of suicide or violence, predicted all-cause mortality among people receiving specific assessment of risk in a secondary mental health service. Language: en
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the south london and maudsley nhs foundation trust biomedical Research Centre slam brc case register development and descriptive data
BMC Psychiatry, 2009Co-Authors: Robert Stewart, Mishael Soremekun, Gayan Perera, Matthew Broadbent, Mike Denis, Graham Thornicroft, Felicity Callard, Matthew Hotopf, Simon LovestoneAbstract:Case registers have been used extensively in mental health Research. Recent developments in electronic medical records, and in computer software to search and analyse these in anonymised format, have the potential to revolutionise this Research tool. We describe the development of the South London and Maudsley NHS Foundation Trust (SLAM) Biomedical Research Centre (BRC) Case Register Interactive Search tool (CRIS) which allows Research-accessible datasets to be derived from SLAM, the largest provider of secondary mental healthcare in Europe. All clinical data, including free text, are available for analysis in the form of anonymised datasets. Development involved both the building of the system and setting in place the necessary security (with both functional and procedural elements). Descriptive data are presented for the Register database as of October 2008. The database at that point included 122,440 cases, 35,396 of whom were receiving active case management under the Care Programme Approach. In terms of gender and ethnicity, the database was reasonably representative of the source population. The most common assigned primary diagnoses were within the ICD mood disorders (n = 12,756) category followed by schizophrenia and related disorders (8158), substance misuse (7749), neuroses (7105) and organic disorders (6414). The SLAM BRC Case Register represents a 'new generation' of this Research design, built on a long-running system of fully electronic clinical records and allowing in-depth secondary analysis of both numerical, string and free text data, whilst preserving anonymity through technical and procedural safeguards.
Elaine Dunbar - One of the best experts on this subject based on the ideXlab platform.
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ams 14c dating at the scottish universities environmental Research Centre suerc radiocarbon dating laboratory
Radiocarbon, 2016Co-Authors: Elaine Dunbar, Gordon Cook, P Naysmith, Brian G TripneyAbstract:This paper describes all the major procedures adopted by the Scottish Universities Environmental Research Centre (SUERC) Radiocarbon Dating Laboratory. This includes sample pretreatment, graphite production, accelerator mass spectrometry (AMS) measurement, associated stable isotope measurements, data handling, and age calculations, but with the main emphasis being on the chemical pretreatment methods. All of the above enable the laboratory to provide a complete analytical service comprising advice on sample selection, preparation and analysis of samples, and Bayesian analysis of resulting 14C (and other) data. This applies to both our Research and commercial activities. The pretreatment methods that we mainly focus on are used to remove contaminant carbon from a range of sample types or to isolate a particular chemical fraction from a sample prior to combustion/hydrolysis, graphitization, and subsequent AMS 14C measurement. The methods described are for bone (collagen extraction, with and without ultrafiltration), cremated bone, tooth enamel, charcoal, grain, carbon residues, shell, wood (including alpha-cellulose isolation), peat, sediments, textiles, fuel/biofuel, and forensic samples.
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ams 14 c dating at the scottish universities environmental Research Centre suerc radiocarbon dating laboratory
Radiocarbon, 2016Co-Authors: Elaine Dunbar, P Naysmith, G T Cook, Brian G TripneyAbstract:This paper describes all the major procedures adopted by the Scottish Universities Environmental Research Centre (SUERC) Radiocarbon Dating Laboratory. This includes sample pretreatment, graphite production, accelerator mass spectrometry (AMS) measurement, associated stable isotope measurements, data handling, and age calculations, but with the main emphasis being on the chemical pretreatment methods. All of the above enable the laboratory to provide a complete analytical service comprising advice on sample selection, preparation and analysis of samples, and Bayesian analysis of resulting 14 C (and other) data. This applies to both our Research and commercial activities. The pretreatment methods that we mainly focus on are used to remove contaminant carbon from a range of sample types or to isolate a particular chemical fraction from a sample prior to combustion/hydrolysis, graphitization, and subsequent AMS 14 C measurement. The methods described are for bone (collagen extraction, with and without ultrafiltration), cremated bone, tooth enamel, charcoal, grain, carbon residues, shell, wood (including alpha-cellulose isolation), peat, sediments, textiles, fuel/biofuel, and forensic samples.
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ams 14 c dating at the scottish universities environmental Research Centre suerc radiocarbon dating laboratory corrigendum
Radiocarbon, 2016Co-Authors: Elaine Dunbar, Gordon Cook, P Naysmith, Brian G TripneyAbstract:This paper describes all the major procedures adopted by the Scottish Universities Environmental Research Centre (SUERC) Radiocarbon Dating Laboratory. This includes sample pretreatment, graphite production, accelerator mass spectrometry (AMS) measurement, associated stable isotope measurements, data handling, and age calculations, but with the main emphasis being on the chemical pretreatment methods. All of the above enable the laboratory to provide a complete analytical service comprising advice on sample selection, preparation and analysis of samples, and Bayesian analysis of resulting 14C (and other) data. This applies to both our Research and commercial activities. The pretreatment methods that we mainly focus on are used to remove contaminant carbon from a range of sample types or to isolate a particular chemical fraction from a sample prior to combustion/hydrolysis, graphitization, and subsequent AMS 14C measurement. The methods described are for bone (collagen extraction, with and without ultrafiltration), cremated bone, tooth enamel, charcoal, grain, carbon residues, shell, wood (including alpha-cellulose isolation), peat, sediments, textiles, fuel/biofuel, and forensic samples.
Robert Stewart - One of the best experts on this subject based on the ideXlab platform.
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clinical risk assessment rating and all cause mortality in secondary mental healthcare the south london and maudsley nhs foundation trust biomedical Research Centre slam brc case register
Psychological Medicine, 2012Co-Authors: Chinkuo Chang, Matthew Broadbent, Matthew Hotopf, Richard D Hayes, Robert StewartAbstract:BACKGROUND: Mental disorders are widely recognized to be associated with increased risk of all-cause mortality. However, the extent to which highest-risk groups for mortality overlap with those viewed with highest concern by mental health services is less clear. The aim of the study was to investigate clinical risk assessment ratings for suicide, violence and self-neglect in relation to all-cause mortality among people receiving secondary mental healthcare. Method A total of 9234 subjects over the age of 15 years were identified from the South London and Maudsley Biomedical Research Centre Case Register who had received a second tier structured risk assessment in the course of their clinical care. A cohort analysis was carried out. Total scores for three risk assessment clusters (suicide, violence and self-neglect) were calculated and Cox regression models used to assess survival from first assessment. RESULTS: A total of 234 deaths had occurred over an average 9.4-month follow-up period. Mortality was relatively high for the cohort overall in relation to national norms [standardized mortality ratio 3.23, 95% confidence interval (CI) 2.83-3.67] but not in relation to other mental health service users with similar diagnoses. Only the score for the self-neglect cluster predicted mortality [hazard ratio (HR) per unit increase 1.14, 95% CI 1.04-1.24] with null findings for assessed risk of suicide or violence (HRs per unit increase 1.00 and 1.06 respectively). CONCLUSIONS: Level of clinician-appraised risk of self-neglect, but not of suicide or violence, predicted all-cause mortality among people receiving specific assessment of risk in a secondary mental health service. Language: en
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the south london and maudsley nhs foundation trust biomedical Research Centre slam brc case register development and descriptive data
BMC Psychiatry, 2009Co-Authors: Robert Stewart, Mishael Soremekun, Gayan Perera, Matthew Broadbent, Mike Denis, Graham Thornicroft, Felicity Callard, Matthew Hotopf, Simon LovestoneAbstract:Case registers have been used extensively in mental health Research. Recent developments in electronic medical records, and in computer software to search and analyse these in anonymised format, have the potential to revolutionise this Research tool. We describe the development of the South London and Maudsley NHS Foundation Trust (SLAM) Biomedical Research Centre (BRC) Case Register Interactive Search tool (CRIS) which allows Research-accessible datasets to be derived from SLAM, the largest provider of secondary mental healthcare in Europe. All clinical data, including free text, are available for analysis in the form of anonymised datasets. Development involved both the building of the system and setting in place the necessary security (with both functional and procedural elements). Descriptive data are presented for the Register database as of October 2008. The database at that point included 122,440 cases, 35,396 of whom were receiving active case management under the Care Programme Approach. In terms of gender and ethnicity, the database was reasonably representative of the source population. The most common assigned primary diagnoses were within the ICD mood disorders (n = 12,756) category followed by schizophrenia and related disorders (8158), substance misuse (7749), neuroses (7105) and organic disorders (6414). The SLAM BRC Case Register represents a 'new generation' of this Research design, built on a long-running system of fully electronic clinical records and allowing in-depth secondary analysis of both numerical, string and free text data, whilst preserving anonymity through technical and procedural safeguards.
Gayan Perera - One of the best experts on this subject based on the ideXlab platform.
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cohort profile of the south london and maudsley nhs foundation trust biomedical Research Centre slam brc case register current status and recent enhancement of an electronic mental health record derived data resource
BMJ Open, 2016Co-Authors: Gayan Perera, Matthew Broadbent, Felicity Callard, Chinkuo Chang, Richard D Hayes, Johnny Downs, Rina Dutta, Andrea C Fernandes, Max Henderson, Richard J JacksonAbstract:Purpose The South London and Maudsley National Health Service (NHS) Foundation Trust Biomedical Research Centre (SLaM BRC) Case Register and its Clinical Record Interactive Search (CRIS) application were developed in 2008, generating a Research repository of real-time, anonymised, structured and open-text data derived from the electronic health record system used by SLaM, a large mental healthcare provider in southeast London. In this paper, we update this register's descriptive data, and describe the substantial expansion and extension of the data resource since its original development. Participants Descriptive data were generated from the SLaM BRC Case Register on 31 December 2014. Currently, there are over 250 000 patient records accessed through CRIS. Findings to date Since 2008, the most significant developments in the SLaM BRC Case Register have been the introduction of natural language processing to extract structured data from open-text fields, linkages to external sources of data, and the addition of a parallel relational database (Structured Query Language) output. Natural language processing applications to date have brought in new and hitherto inaccessible data on cognitive function, education, social care receipt, smoking, diagnostic statements and pharmacotherapy. In addition, through external data linkages, large volumes of supplementary information have been accessed on mortality, hospital attendances and cancer registrations. Future plans Coupled with robust data security and governance structures, electronic health records provide potentially transformative information on mental disorders and outcomes in routine clinical care. The SLaM BRC Case Register continues to grow as a database, with approximately 20 000 new cases added each year, in addition to extension of follow-up for existing cases. Data linkages and natural language processing present important opportunities to enhance this type of Research resource further, achieving both volume and depth of data. However, Research projects still need to be carefully tailored, so that they take into account the nature and quality of the source information.
-
the south london and maudsley nhs foundation trust biomedical Research Centre slam brc case register development and descriptive data
BMC Psychiatry, 2009Co-Authors: Robert Stewart, Mishael Soremekun, Gayan Perera, Matthew Broadbent, Mike Denis, Graham Thornicroft, Felicity Callard, Matthew Hotopf, Simon LovestoneAbstract:Case registers have been used extensively in mental health Research. Recent developments in electronic medical records, and in computer software to search and analyse these in anonymised format, have the potential to revolutionise this Research tool. We describe the development of the South London and Maudsley NHS Foundation Trust (SLAM) Biomedical Research Centre (BRC) Case Register Interactive Search tool (CRIS) which allows Research-accessible datasets to be derived from SLAM, the largest provider of secondary mental healthcare in Europe. All clinical data, including free text, are available for analysis in the form of anonymised datasets. Development involved both the building of the system and setting in place the necessary security (with both functional and procedural elements). Descriptive data are presented for the Register database as of October 2008. The database at that point included 122,440 cases, 35,396 of whom were receiving active case management under the Care Programme Approach. In terms of gender and ethnicity, the database was reasonably representative of the source population. The most common assigned primary diagnoses were within the ICD mood disorders (n = 12,756) category followed by schizophrenia and related disorders (8158), substance misuse (7749), neuroses (7105) and organic disorders (6414). The SLAM BRC Case Register represents a 'new generation' of this Research design, built on a long-running system of fully electronic clinical records and allowing in-depth secondary analysis of both numerical, string and free text data, whilst preserving anonymity through technical and procedural safeguards.