| 1. |
- Böhm, M., et al.
(författare)
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The conservation status of the world’s freshwater molluscs
- 2021
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Ingår i: Hydrobiologia. - : Springer Science and Business Media LLC. - 0018-8158 .- 1573-5117. ; 848, s. 3231-3254
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Tidskriftsartikel (refereegranskat)abstract
- With the biodiversity crisis continuing unchecked, we need to establish levels and drivers of extinction risk, and reassessments over time, to effectively allocate conservation resources and track progress towards global conservation targets. Given that threat appears particularly high in freshwaters, we assessed the extinction risk of 1428 randomly selected freshwater molluscs using the IUCN Red List Categories and Criteria, as part of the Sampled Red List Index project. We show that close to one-third of species in our sample are estimated to be threatened with extinction, with highest levels of threat in the Nearctic, Palearctic and Australasia and among gastropods. Threat levels were higher in lotic than lentic systems. Pollution (chemical and physical) and the modification of natural systems (e.g. through damming and water abstraction) were the most frequently reported threats to freshwater molluscs, with some regional variation. Given that we found little spatial congruence between species richness patterns of freshwater molluscs and other freshwater taxa, apart from crayfish, new additional conservation priority areas emerged from our study. We discuss the implications of our findings for freshwater mollusc conservation, the adequacy of a sampled approach and important next steps to estimate trends in freshwater mollusc extinction risk over time. © 2020, Springer Nature Switzerland AG.
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| 2. |
- König, Alexandra, et al.
(författare)
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Screening over Speech in Unselected Populations for Clinical Trials in AD (PROSPECT-AD) : Study Design and Protocol
- 2023
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Ingår i: Journal of Prevention of Alzheimer's Disease. - : SERDI. - 2274-5807. ; 10, s. 314-321
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Tidskriftsartikel (refereegranskat)abstract
- Background: Speech impairments are an early feature of Alzheimer’s disease (AD) and consequently, analysing speech performance is a promising new digital biomarker for AD screening. Future clinical AD trials on disease modifying drugs will require a shift to very early identification of individuals at risk of dementia. Hence, digital markers of language and speech may offer a method for screening of at-risk populations that are at the earliest stages of AD, eventually in combination with advanced machine learning. To this end, we developed a screening battery consisting of speech-based neurocognitive tests. The automated test performs a remote primary screening using a simple telephone. Objectives: PROSPECT-AD aims to validate speech biomarkers for identification of individuals with early signs of AD and monitor their longitudinal course through access to well-phenotyped cohorts. Design: PROSPECT-AD leverages ongoing cohorts such as EPAD (UK), DESCRIBE and DELCODE (Germany), and BioFINDER Primary Care (Sweden) and Beta-AARC (Spain) by adding a collection of speech data over the telephone to existing longitudinal follow-ups. Participants at risk of dementia are recruited from existing parent cohorts across Europe to form an AD ‘probability-spectrum’, i.e., individuals with a low risk to high risk of developing AD dementia. The characterization of cognition, biomarker and risk factor (genetic and environmental) status of each research participants over time combined with audio recordings of speech samples will provide a well-phenotyped population for comparing novel speech markers with current gold standard biomarkers and cognitive scores. Participants: N= 1000 participants aged 50 or older will be included in total, with a clinical dementia rating scale (CDR) score of 0 or 0.5. The study protocol is planned to run according to sites between 12 and 18 months. Measurements: The speech protocol includes the following neurocognitive tests which will be administered remotely: Word List [Memory Function], Verbal Fluency [Executive Functions] and spontaneous free speech [Psychological and/ or behavioral symptoms]. Speech features on the linguistic and paralinguistic level will be extracted from the recordings and compared to data from CSF and blood biomarkers, neuroimaging, neuropsychological evaluations, genetic profiles, and family history. Primary candidate marker from speech will be a combination of most significant features in comparison to biomarkers as reference measure. Machine learning and computational techniques will be employed to identify the most significant speech biomarkers that could represent an early indicator of AD pathology. Furthermore, based on the analysis of speech performances, models will be trained to predict cognitive decline and disease progression across the AD continuum. Conclusion: The outcome of PROSPECT-AD may support AD drug development research as well as primary or tertiary prevention of dementia by providing a validated tool using a remote approach for identifying individuals at risk of dementia and monitoring individuals over time, either in a screening context or in clinical trials.
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| 3. |
- Cascone, Claudia, et al.
(författare)
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AbspectroscoPY, a Python toolbox for absorbance-based sensor data in water quality monitoring
- 2022
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Ingår i: Environmental Science: Water Research & Technology. - 2053-1419. ; 8:4, s. 836-848
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Tidskriftsartikel (refereegranskat)abstract
- The long-term trend of increasing natural organic matter (NOM) in boreal and north European surface waters represents an economic and environmental challenge for drinking water treatment plants (DWTPs). High-frequency measurements from absorbance-based online spectrophotometers are often used in modern DWTPs to measure the chromophoric fraction of dissolved organic matter (CDOM) over time. These data contain valuable information that can be used to optimise NOM removal at various stages of treatment and/or diagnose the causes of underperformance at the DWTP. However, automated monitoring systems generate large datasets that need careful preprocessing, followed by variable selection and signal processing before interpretation. In this work we introduce AbspectroscoPY (“Absorbance spectroscopic analysis inPython”), a Python toolbox for processing time-series datasets collected by in situ spectrophotometers. The toolbox addresses some of the main challenges in data preprocessing by handling duplicates, systematic time shifts, baseline corrections and outliers. It contains automated functions to compute a range of spectral metrics for the time-series data, including absorbance ratios, exponential fits, slope ratios and spectral slope curves. To demonstrate its utility, AbspectroscoPY was applied to 15-month datasets from three onlinespectrophotometers in a drinking water treatment plant. Despite only small variations in surface water quality over the time period, variability in the spectrophotometric profiles of treated water could be identified, quantified and related to lake turnover or operational changes in the DWTP. This toolboxrepresents a step toward automated early warning systems for detecting and responding to potential threats to treatment performance caused by rapid changes in incoming water quality.
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| 4. |
- Peters, Ruth, et al.
(författare)
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An investigation of antihypertensive class, dementia, and cognitive decline: A meta-analysis.
- 2020
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Ingår i: Neurology. - 1526-632X. ; 94:3
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Tidskriftsartikel (refereegranskat)abstract
- High blood pressure is one of the main modifiable risk factors for dementia. However, there is conflicting evidence regarding the best antihypertensive class for optimizing cognition. Our objective was to determine whether any particular antihypertensive class was associated with a reduced risk of cognitive decline or dementia using comprehensive meta-analysis including reanalysis of original participant data.To identify suitable studies, MEDLINE, Embase, and PsycINFO and preexisting study consortia were searched from inception to December 2017. Authors of prospective longitudinal human studies or trials of antihypertensives were contacted for data sharing and collaboration. Outcome measures were incident dementia or incident cognitive decline (classified using the reliable change index method). Data were separated into mid and late-life (>65 years) and each antihypertensive class was compared to no treatment and to treatment with other antihypertensives. Meta-analysis was used to synthesize data.Over 50,000 participants from 27 studies were included. Among those aged >65 years, with the exception of diuretics, we found no relationship by class with incident cognitive decline or dementia. Diuretic use was suggestive of benefit in some analyses but results were not consistent across follow-up time, comparator group, and outcome. Limited data precluded meaningful analyses in those ≤65 years of age.Our findings, drawn from the current evidence base, support clinical freedom in the selection of antihypertensive regimens to achieve blood pressure goals.The review was registered with the international prospective register of systematic reviews (PROSPERO), registration number CRD42016045454.
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| 5. |
- Reimer, Paula J., et al.
(författare)
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The IntCal20 Northern Hemisphere Radiocarbon Age Calibration Curve (0-55 cal kBP)
- 2020
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Ingår i: Radiocarbon. - 0033-8222. ; 62:4, s. 725-757
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Tidskriftsartikel (refereegranskat)abstract
- Radiocarbon (C) ages cannot provide absolutely dated chronologies for archaeological or paleoenvironmental studies directly but must be converted to calendar age equivalents using a calibration curve compensating for fluctuations in atmospheric C concentration. Although calibration curves are constructed from independently dated archives, they invariably require revision as new data become available and our understanding of the Earth system improves. In this volume the international C calibration curves for both the Northern and Southern Hemispheres, as well as for the ocean surface layer, have been updated to include a wealth of new data and extended to 55,000 cal BP. Based on tree rings, IntCal20 now extends as a fully atmospheric record to ca. 13,900 cal BP. For the older part of the timescale, IntCal20 comprises statistically integrated evidence from floating tree-ring chronologies, lacustrine and marine sediments, speleothems, and corals. We utilized improved evaluation of the timescales and location variable C offsets from the atmosphere (reservoir age, dead carbon fraction) for each dataset. New statistical methods have refined the structure of the calibration curves while maintaining a robust treatment of uncertainties in the C ages, the calendar ages and other corrections. The inclusion of modeled marine reservoir ages derived from a three-dimensional ocean circulation model has allowed us to apply more appropriate reservoir corrections to the marine C data rather than the previous use of constant regional offsets from the atmosphere. Here we provide an overview of the new and revised datasets and the associated methods used for the construction of the IntCal20 curve and explore potential regional offsets for tree-ring data. We discuss the main differences with respect to the previous calibration curve, IntCal13, and some of the implications for archaeology and geosciences ranging from the recent past to the time of the extinction of the Neanderthals.
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| 6. |
- Cascone, C., et al.
(författare)
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AbspectroscoPY, a Python toolbox for absorbance-based sensor data in water quality monitoring
- 2022
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Ingår i: Environmental Science. - : Royal Society of Chemistry (RSC). - 2053-1400 .- 2053-1419. ; 8:4, s. 836-848
-
Tidskriftsartikel (refereegranskat)abstract
- The long-term trend of increasing natural organic matter (NOM) in boreal and north European surface waters represents an economic and environmental challenge for drinking water treatment plants (DWTPs). High-frequency measurements from absorbance-based online spectrophotometers are often used in modern DWTPs to measure the chromophoric fraction of dissolved organic matter (CDOM) over time. These data contain valuable information that can be used to optimise NOM removal at various stages of treatment and/or diagnose the causes of underperformance at the DWTP. However, automated monitoring systems generate large datasets that need careful preprocessing, followed by variable selection and signal processing before interpretation. In this work we introduce AbspectroscoPY (“Absorbance spectroscopic analysis in Python”), a Python toolbox for processing time-series datasets collected by in situ spectrophotometers. The toolbox addresses some of the main challenges in data preprocessing by handling duplicates, systematic time shifts, baseline corrections and outliers. It contains automated functions to compute a range of spectral metrics for the time-series data, including absorbance ratios, exponential fits, slope ratios and spectral slope curves. To demonstrate its utility, AbspectroscoPY was applied to 15-month datasets from three online spectrophotometers in a drinking water treatment plant. Despite only small variations in surface water quality over the time period, variability in the spectrophotometric profiles of treated water could be identified, quantified and related to lake turnover or operational changes in the DWTP. This toolbox represents a step toward automated early warning systems for detecting and responding to potential threats to treatment performance caused by rapid changes in incoming water quality.
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