| 1. |
- Ekelund Ugge, Gustaf Magnus Oskar, 1990-
(author)
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Transcriptional biomarkers of toxicity – powerful tools or random noise? : An applied perspective from studies on bivalves
- 2023
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Doctoral thesis (other academic/artistic)abstract
- Aquatic organisms are constantly at risk of being exposed to potentially harmful chemical compounds of natural or anthropogenic origin. Biological life can for instance respond to chemical stressors by changes in gene expression, and thus, certain gene transcripts can potentially function as biomarkers, i.e. early warnings, of toxicity and chemical stress. A major challenge for biomarker application is the extrapolation of transcriptional data to potential effects at the organism level or above. Importantly, successful biomarker use also requires basal understanding of how to distinguish actual responses from background noise. The aim of this thesis is, based on response magnitude and variation, to evaluate the biomarker potential in a set of putative transcriptional biomarkers of general toxicity and chemical stress.Specifically, I addressed a selection of six transcripts involved in cytoprotection and oxidative stress: catalase (cat), glutathione-S-transferase (gst), heat shock proteins 70 and 90 (hsp70, hsp90), metallothionein (mt) and superoxide dismutase (sod). Moreover, I used metal exposures to serve as a proxy for general chemical stress, and due to their ecological relevance and nature as sedentary filter-feeders, I used bivalves as study organisms.In a series of experiments, I tested transcriptional responses in the freshwater duck mussel, Anodonta anatina, exposed to copper or an industrial wastewater effluent, to address response robustness and sensitivity, and potential controlled (e.g. exposure concentration) and random (e.g. gravidness) sources of variation. In addition, I performed a systematic review and meta-analysis on transcriptional responses in metal exposed bivalves to (1) evaluate what responses to expect from arbitrary metal exposures, (2) assess the influence from metal concentration (expressed as toxic unit), exposure time and analyzed tissue, and (3) address potential impacts from publication bias in the scientific literature.Response magnitudes were generally small in relationship to the observed variation, both for A. anatina and bivalves in general. The expected response to an arbitrary metal exposure would generally be close to zero, based on both experimental observations and on the estimated impact from publication bias. Although many of the transcripts demonstrated concentration-response relationships, large background noise might in practice obscure the small responses even at relatively high exposures. As demonstrated in A. anatina under copper exposure, this can be the case already for single species under high resolution exposures to single pollutants. As demonstrated by the meta-regression, this problem can only be expected to increase further upon extrapolation between different species and exposure scenarios, due to increasing heterogeneity and random variation. Similar patterns can also be expected for time-dependent response variation, although the meta-regression revealed a general trend of slightly increasing response magnitude with increasing exposure times.In A. anatina, gravidness was identified as a source of random variability that can potentially affect the baseline of most assessed biomarkers, particularly when quantified in gills. Response magnitudes and variability in this species were generally similar for selected transcripts as for two biochemical biomarkers included for comparison (AChE, GST), suggesting that the transcripts might not capture early warnings more efficiently than other molecular endpoints that are more toxicologically relevant. Overall, high concentrations and long exposure durations presumably increase the likelihood of a detectable transcriptional response, but not to an extent that justifies universal application as biomarkers of general toxicity and chemical stress. Consequently, without a strictly defined and validated application, this approach on its own appears unlikely to be successful for future environmental risk assessment and monitoring. Ultimately, efficient use of transcriptional biomarkers might require additional implementation of complementary approaches offered by current molecular techniques.
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| 2. |
- Liu, Yu, et al.
(author)
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Linking Simulation-Based LCA to Manufacturing Decision Support : An Iron Foundry Case Study
- 2022
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In: Advances in Manufacturing Technology XXXV. - : IOS Press. - 9781643683300 - 9781643683317 - 9781614994398 ; , s. 325-333
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Conference paper (peer-reviewed)abstract
- In recent years, an increasing number of legislations have mandated environmental impact evaluations of products from a life cycle perspective. This study applies a discrete-event simulation-based life cycle assessment to study the environmental consequences that respond to system configuration changes in production processes. The proposed method allows capturing the dynamic links in production processes, which is lacking in conventional static LCA modelling. This approach is demonstrated via a real-world case study of a Swedish foundry production line, where its environmental impacts’ hotspots are identified. These environmental consequences are further analyzed to link to the respective production decision domains for providing suggestions on potential improvements. This study demonstrates the value of combining DES and LCA for revealing the hidden environmental consequences of production processes that are difficult to uncover with traditional LCA studies. Moreover, the strengths and difficulties of the proposed method are also discussed.
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| 3. |
- Rahman, Aminur, 1984-, et al.
(author)
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Comparative genome analysis of Lysinibacillus B1-CDA, a bacterium that accumulates arsenics
- 2015
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In: Genomics. - : Elsevier. - 0888-7543 .- 1089-8646. ; 106:6, s. 384-392
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Journal article (peer-reviewed)abstract
- Previously, we reported an arsenic resistant bacterium Lysinibacillus sphaericus B1-CDA, isolated from an arsenic contaminated lands. Here, we have investigated its genetic composition and evolutionary history by using massively parallel sequencing and comparative analysis with other known Lysinibacillus genomes. Assembly of the sequencing reads revealed a genome of ~ 4.5 Mb in size encompassing ~ 80% of the chromosomal DNA. We found that the set of ordered contigs contains abundant regions of similarity with other Lysinibacillus genomes and clearly identifiable genome rearrangements. Furthermore, all genes of B1-CDA that were predicted be involved in its resistance to arsenic and/or other heavy metals were annotated. The presence of arsenic responsive genes was verified by PCR in vitro conditions. The findings of this study highlight the significance of this bacterium in removing arsenics and other toxic metals from the contaminated sources. The genetic mechanisms of the isolate could be used to cope with arsenic toxicity.
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| 4. |
- Yewale, Priti, et al.
(author)
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Studies on Biosmotrap : A multipurpose biological air purifier to minimize indoor and outdoor air pollution
- 2022
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In: Journal of Cleaner Production. - : Elsevier. - 0959-6526 .- 1879-1786. ; 357
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Journal article (peer-reviewed)abstract
- Air pollution is a serious health concern that affects many people across the globe. The major air pollutants are particulate matter, carbon oxides, nitrogen oxides, sulphur oxides, volatile organic compounds, polycyclic aromatics and free radicals which cause severe respiratory distress and infections. The existing air cleaning systems suffer from drawbacks of high cost and generation of secondary pollutants. A novel biological air filter “Biosmotrap” which is a laminate composite of sponge gourd and algae was developed. Biosmotrap placed in a carrier assembly on exhaust of vehicles, could remove carbon monoxide, nitric oxide, nitrogen dioxide, and fine particulate matter (PM2.5) from the vehicular emissions resulting in cleaner emissions. Biosmotrap decreased carbon monoxide from 1,423,992 μg/m3 to 76,756 μg/m3, nitric oxide from 71,128 μg/m3 to 9982 μg/m3, nitrogen dioxide from 565 μg/m3 to 188 μg/m3 and PM2.5 from 3200 μg/m3 to 60 μg/m3 from a polluting vehicle. Biosmotrap removed 60–80% of indoor pollutants from cigarette smoke and incense-stick smoke. Biosmotrap could protect the human cells from oxidative DNA damage induced by indoor air pollutants. Hibiscus rosa-sinensis plants exposed to air filtered through Biosmotrap were healthy as compared to the plants directly exposed to polluted air. Biosmotrap is an economic, efficient, eco-friendly filter that is superior to existing air filtration methods.
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| 5. |
- Liu, Yu, et al.
(author)
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Review of simulation-based life cycle assessment in manufacturing industry
- 2019
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In: Production & Manufacturing Research. - : Taylor & Francis. - 2169-3277. ; 7:1, s. 490-502
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Journal article (peer-reviewed)abstract
- The manufacturing industry has a duty to minimize its environmental impact, and an increasing body of legislation mandates environmental impact evaluations from a life cycle perspective to prevent burden shift. The manufacturing industry is increasing its use of computer-based simulations to optimize production processes. In recent years, several published studies have combined simulations with life cycle assessments (LCAs) to evaluate and minimize the environmental impact of production activities. Still, current knowledge of simulations conducted for LCAs is rather disjointed. This paper accordingly reviews the literature covering simulation-based LCAs of production processes. The results of the review and cross-comparison of papers are structured in terms of seven elements in line with the ISO standard definition of LCA and report the strengths and limitations of the reviewed studies. © 2019, © 2019 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
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| 6. |
- Piikki, Kristin, 1975, et al.
(author)
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The open-top chamber impact on vapour pressure deficit and its consequences for stomatal ozone uptake
- 2008
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In: Atmospheric Environment. - : Elsevier BV. - 1352-2310 .- 1873-2844. ; 42:26, s. 6513-6522
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Journal article (peer-reviewed)abstract
- The vapour pressure deficit (VPD) in open-top chambers (OTCs) was analysed in relation to time of day and ambient meteorology. Effects of observed VPD differences (ΔVPD) between OTCs and the ambient air (AA) on stomatal conductance (gs) were simulated using 10 model functions from the literature. The dataset originated from 17 OTC crop experiments performed in Belgium, Germany and Sweden. ΔVPD is the resulting difference between the OTC effect on es(T), which is the temperature-dependent saturation pressure of water vapour and the OTC effect on ea, which is the prevailing partial pressure of water vapour in the air (ΔVPD = Δes(T) − Δea). Both Δes(T) and Δea were positive during daylight hours. ΔVPD was small in comparison and sensitive to changes in Δes(T) or Δea. ΔVPD was negative between 07:30 and 10:30 and positive thereafter with a maximum at 20:30 (local time). The positive afternoon ΔVPD was due to an early decrease in Δea, probably caused by ceased transpiration, while the positive Δes(T) persisted throughout the evening, most likely because of restrained cooling in the OTCs. Both the negative morning ΔVPD and the positive evening ΔVPD were more pronounced during clear, warm and dry weather. Circumstances when VPD had a stronger limiting effect on gs inside the OTCs compared to in the ambient air coincided with high ambient ozone concentrations ([O3]). Calculated wheat O3 uptake over an [O3] threshold of 40 nmol mol−1 was reduced by 8.7% in OTCs, assuming that VPD was the only factor limiting gs and that gs was the only resistance for O3 uptake. VPD is one factor of considerable importance for gs and the OTC impact on VPD may contribute to an underestimation of O3 effects expressed in relation to the external O3 exposure.
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| 7. |
- Hardisty, Alex R., et al.
(author)
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BioVeL: A virtual laboratory for data analysis and modelling in biodiversity science and ecology
- 2016
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In: BMC Ecology. - : Springer Science and Business Media LLC. - 1472-6785. ; 16
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Journal article (peer-reviewed)abstract
- © 2016 The Author(s).Background: Making forecasts about biodiversity and giving support to policy relies increasingly on large collections of data held electronically, and on substantial computational capability and capacity to analyse, model, simulate and predict using such data. However, the physically distributed nature of data resources and of expertise in advanced analytical tools creates many challenges for the modern scientist. Across the wider biological sciences, presenting such capabilities on the Internet (as "Web services") and using scientific workflow systems to compose them for particular tasks is a practical way to carry out robust "in silico" science. However, use of this approach in biodiversity science and ecology has thus far been quite limited. Results: BioVeL is a virtual laboratory for data analysis and modelling in biodiversity science and ecology, freely accessible via the Internet. BioVeL includes functions for accessing and analysing data through curated Web services; for performing complex in silico analysis through exposure of R programs, workflows, and batch processing functions; for on-line collaboration through sharing of workflows and workflow runs; for experiment documentation through reproducibility and repeatability; and for computational support via seamless connections to supporting computing infrastructures. We developed and improved more than 60 Web services with significant potential in many different kinds of data analysis and modelling tasks. We composed reusable workflows using these Web services, also incorporating R programs. Deploying these tools into an easy-to-use and accessible 'virtual laboratory', free via the Internet, we applied the workflows in several diverse case studies. We opened the virtual laboratory for public use and through a programme of external engagement we actively encouraged scientists and third party application and tool developers to try out the services and contribute to the activity. Conclusions: Our work shows we can deliver an operational, scalable and flexible Internet-based virtual laboratory to meet new demands for data processing and analysis in biodiversity science and ecology. In particular, we have successfully integrated existing and popular tools and practices from different scientific disciplines to be used in biodiversity and ecological research.
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| 8. |
- Eero, Margit, et al.
(author)
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Food for Thought Eastern Baltic cod in distress : biological changes and challenges for stock assessment
- 2015
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In: ICES Journal of Marine Science. - : Oxford University Press (OUP). - 1054-3139 .- 1095-9289. ; 72:8, s. 2180-2186
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Journal article (peer-reviewed)abstract
- The eastern Baltic (EB) cod (Gadus morhua) stock was depleted and overexploited for decades until the mid-2000s, when fishing mortality rapidly declined and biomass started to increase, as shown by stock assessments. These positive developments were partly assigned to effective management measures, and the EB cod was considered one of the most successful stock recoveries in recent times. In contrast to this optimistic view, the analytical stock assessment failed in 2014, leaving the present stock status unclear. Deteriorated quality of some basic input data for stock assessment in combination with changes in environmental and ecological conditions has led to an unusual situation for cod in the Baltic Sea, which poses new challenges for stock assessment and management advice. A number of adverse developments such as low nutritional condition and disappearance of larger individuals indicate that the stock is in distress. In this study, we (i) summarize the knowledge of recent changes in cod biology and ecosystem conditions, (ii) describe the subsequent challenges for stock assessment, and (iii) highlight the key questions where answers are urgently needed to understand the present stock status and provide scientifically solid support for cod management in the Baltic Sea.
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| 9. |
- Salgaonkar, Neeta A., et al.
(author)
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Use of N,N-diacetylchitobiose in decreasing toxic effects of indoor air pollution by preventing oxidative DNA damage
- 2016
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In: Biologia. - Bratislava : Springer. - 0006-3088 .- 1336-9563. ; 71:5, s. 505-515
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Journal article (peer-reviewed)abstract
- Indoor air pollution occurs due to hazardous pollutants, such as tobacco smoke, pesticides and carbon oxides, sulphur oxides and nitrogen oxides arising from combustion of biomass fuels. Exposure to these pollutants results in respiratory conditions like asthma, chronic obstructive pulmonary disease, lung cancer, pneumonia and other lower respiratory infections. Several of these infections are a result of inflammation and oxidative stress. Here we demonstrate the ability of N,N-diacetylchitobiose in preventing oxidative DNA damage in peripheral blood mononuclear cells exposed to biomass smoke extracts and cigarette smoke extract. The cytotoxic effect of these pollutants was determined by trypan blue exclusion assay in peripheral blood mononuclear cells, where cytotoxicity in decreasing order was garette > wood > sawdust > cowdung. Cytotoxicity could be due to single- and double-strand breaks in the DNA as a result of oxidative stress. Comet assay measures the extent of DNA damage in the cells exposed to toxic agents. When mononuclear cells were treated with N,N-diacetylchitobiose and later exposed to smoke extracts, the extent of DNA damage decreased by 44.5% and 57.5% as compared to untreated cells. The protection offered by N,N-diacetylchitobiose towards oxidative DNA damage was at par with quercetin, a popular herbal medicine. Glutathione-S-transferase activity was determined in mononuclear cells exposed to smoke extracts, where oxidative stress in cells exposed to cigarette smoke extract was maximum. The present study demonstrates for the first time the ability of N,N -diacetylchitobiose to alleviate the harmful effects of indoor air pollutants.
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| 10. |
- Al Mamun, Md Abdullah, 1982, et al.
(author)
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Effects of measurements on correlations of software code metrics
- 2019
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In: Empirical Software Engineering. - : Springer Science and Business Media LLC. - 1382-3256 .- 1573-7616. ; 24:4, s. 2764-2818
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Journal article (peer-reviewed)abstract
- ContextSoftware metrics play a significant role in many areas in the life-cycle of software including forecasting defects and foretelling stories regarding maintenance, cost, etc. through predictive analysis. Many studies have found code metrics correlated to each other at such a high level that such correlated code metrics are considered redundant, which implies it is enough to keep track of a single metric from a list of highly correlated metrics.ObjectiveSoftware is developed incrementally over a period. Traditionally, code metrics are measured cumulatively as cumulative sum or running sum. When a code metric is measured based on the values from individual revisions or commits without consolidating values from past revisions, indicating the natural development of software, this study identifies such a type of measure as organic. Density and average are two other ways of measuring metrics. This empirical study focuses on whether measurement types influence correlations of code metrics.MethodTo investigate the objective, this empirical study has collected 24 code metrics classified into four categories, according to the measurement types of the metrics, from 11,874 software revisions (i.e., commits) of 21 open source projects from eight well-known organizations. Kendall's tau-B is used for computing correlations. To determine whether there is a significant difference between cumulative and organic metrics, Mann-Whitney U test, Wilcoxon signed rank test, and paired-samples sign test are performed.ResultsThe cumulative metrics are found to be highly correlated to each other with an average coefficient of 0.79. For corresponding organic metrics, it is 0.49. When individual correlation coefficients between these two measure types are compared, correlations between organic metrics are found to be significantly lower (with p <0.01) than cumulative metrics. Our results indicate that the cumulative nature of metrics makes them highly correlated, implying cumulative measurement is a major source of collinearity between cumulative metrics. Another interesting observation is that correlations between metrics from different categories are weak.ConclusionsResults of this study reveal that measurement types may have a significant impact on the correlations of code metrics and that transforming metrics into a different type can give us metrics with low collinearity. These findings provide us a simple understanding how feature transformation to a different measurement type can produce new non-collinear input features for predictive models.
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