| 1. |
- Ahmad, Tariq, et al.
(författare)
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Machine Learning Methods Improve Prognostication, Identify Clinically Distinct Phenotypes, and Detect Heterogeneity in Response to Therapy in a Large Cohort of Heart Failure Patients
- 2018
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Ingår i: Journal of the American Heart Association. - : WILEY. - 2047-9980. ; 7:8
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Tidskriftsartikel (refereegranskat)abstract
- Background-Whereas heart failure (HF) is a complex clinical syndrome, conventional approaches to its management have treated it as a singular disease, leading to inadequate patient care and inefficient clinical trials. We hypothesized that applying advanced analytics to a large cohort of HF patients would improve prognostication of outcomes, identify distinct patient phenotypes, and detect heterogeneity in treatment response. Methods and Results-The Swedish Heart Failure Registry is a nationwide registry collecting detailed demographic, clinical, laboratory, and medication data and linked to databases with outcome information. We applied random forest modeling to identify predictors of 1-year survival. Cluster analysis was performed and validated using serial bootstrapping. Association between clusters and survival was assessed with Cox proportional hazards modeling and interaction testing was performed to assess for heterogeneity in response to HF pharmacotherapy across propensity-matched clusters. Our study included 44 886 HF patients enrolled in the Swedish Heart Failure Registry between 2000 and 2012. Random forest modeling demonstrated excellent calibration and discrimination for survival (C-statistic=0.83) whereas left ventricular ejection fraction did not (C-statistic=0.52): there were no meaningful differences per strata of left ventricular ejection fraction (1-year survival: 80%, 81%, 83%, and 84%). Cluster analysis using the 8 highest predictive variables identified 4 clinically relevant subgroups of HF with marked differences in 1-year survival. There were significant interactions between propensity-matched clusters (across age, sex, and left ventricular ejection fraction and the following medications: diuretics, angiotensin-converting enzyme inhibitors, )i-blockers, and nitrates, Pamp;lt;0.001, all). Conclusions-Machine learning algorithms accurately predicted outcomes in a large data set of HF patients. Cluster analysis identified 4 distinct phenotypes that differed significantly in outcomes and in response to therapeutics. Use of these novel analytic approaches has the potential to enhance effectiveness of current therapies and transform future HF clinical trials.
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| 2. |
- Kataria, Rashmi, et al.
(författare)
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Saccharification of alkali treated biomass of Kans grass contributes higher sugar in contrast to acid treated biomass
- 2013
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Ingår i: Chemical Engineering Journal. - : Elsevier. - 1385-8947 .- 1873-3212. ; 230, s. 36-47
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Tidskriftsartikel (refereegranskat)abstract
- Economical production of biofuel is prerequisite to depletion of fossil fuel. In recent years, biomass of numerous food crops was used as a feedstock for bioethanol production. Unfortunately, due to limited availability as well as confliction with food, these sources may hold back for continuous production of bioethanol. Therefore, in the present study a waste land crop "Kans grass" was utilized as feedstock for microbial production of bio-ethanol. The Kans grass biomass obtained after NaOH pretreatment at optimum conditions (in term of lignin removal) was subjected to enzymatic saccharification by using crude enzyme (obtained from Trichoderma reesei) to total reducing sugars (TRSs), which was further fermented for bioethanol production using yeast strains. Different time (30, 60, 90 and 120min), concentrations of NaOH (0.5%, 1%, 1.5% and 2%) as well as temperatures (100, 110 and 120°C) were used for pretreatment study. At 120°C, approximately more than 50% of delignification was observed. Moreover, subsequent enzymatic saccharification contributed 350mgg-1 dry biomass of total reducing sugar (TRS) production. Interestingly, TRS was approx. fivefold higher than enzymatic saccharification of acid pretreated biomass (69.08mgg-1) as reported previously (Kataria et al., 2011) and fermentation of enzymatic hydrolysate using microbes resulted in the 0.44-0.46gg-1 ethanol yield which is a high yield when compared to the other existing literature. Another advantage of alkali pre-treatment was without production of toxic compounds in comparison to acid pre-treatment method. In conclusion, Kans grass was shown as potential feedstock for biofuel production via alkali and enzymatic saccharification in contrast to acid pre-treatment.
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| 3. |
- Keil, Paul, et al.
(författare)
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Multiple drivers of the North Atlantic warming hole
- 2020
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Ingår i: Nature Climate Change. - : Springer Science and Business Media LLC. - 1758-678X .- 1758-6798. ; 10:7, s. 667-671
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Tidskriftsartikel (refereegranskat)abstract
- The North Atlantic ocean warming hole has been linked to reduced tropical heat import. Model simulations show an anthropogenically forced increased heat export poleward from the region, by overturning and gyre circulation, and shortwave cloud feedback control the warming hole formation and growth. Despite global warming, a region in the North Atlantic ocean has been observed to cool, a phenomenon known as the warming hole. Its emergence has been linked to a slowdown of the Atlantic meridional overturning circulation, which leads to a reduced ocean heat transport into the warming hole region. Here we show that, in addition to the reduced low-latitude heat import, increased ocean heat transport out of the region into higher latitudes and a shortwave cloud feedback dominate the formation and temporal evolution of the warming hole under greenhouse gas forcing. In climate model simulations of the historical period, the low-latitude Atlantic meridional overturning circulation decline does not emerge from natural variability, whereas the accelerating heat transport to higher latitudes is clearly attributable to anthropogenic forcing. Both the overturning and the gyre circulation contribute to the increased high-latitude ocean heat transport, and therefore are critical to understand the past and future evolutions of the warming hole.
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| 4. |
- Niemi, MEK, et al.
(författare)
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- 2021
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swepub:Mat__t
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| 5. |
- Kanai, M, et al.
(författare)
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- 2023
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swepub:Mat__t
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