| 1. |
- Ades, M., et al.
(författare)
-
Global Climate : in State of the climate in 2019
- 2020
-
Ingår i: Bulletin of The American Meteorological Society - (BAMS). - : American Meteorological Society. - 0003-0007 .- 1520-0477. ; 101:8, s. S17-S127
-
Tidskriftsartikel (refereegranskat)
|
|
| 2. |
- Ades, M., et al.
(författare)
-
GLOBAL CLIMATE
- 2020
-
Ingår i: BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY. - 0003-0007 .- 1520-0477. ; 101:8
-
Tidskriftsartikel (refereegranskat)
|
|
| 3. |
|
|
| 4. |
- Arndt, D. S., et al.
(författare)
-
STATE OF THE CLIMATE IN 2017
- 2018
-
Ingår i: Bulletin of The American Meteorological Society - (BAMS). - : American Meteorological Society. - 0003-0007 .- 1520-0477. ; 99:8, s. S1-S310
-
Forskningsöversikt (refereegranskat)
|
|
| 5. |
- Buatois, Simon, et al.
(författare)
-
cLRT-Mod : An efficient methodology for pharmacometric model-based analysis of longitudinal phase II dose finding studies under model uncertainty
- 2021
-
Ingår i: Statistics in Medicine. - : John Wiley & Sons. - 0277-6715 .- 1097-0258. ; 40:10, s. 2435-2451
-
Tidskriftsartikel (refereegranskat)abstract
- Within the challenging context of phase II dose-finding trials, longitudinal analyses may increase drug effect detection power compared to an end-of-treatment analysis. This work proposes cLRT-Mod, a pharmacometric adaptation of the MCP-Mod methodology, which allows the use of nonlinear mixed effect models to first detect a dose-response signal and then identify the doses for the confirmatory phase while accounting for model structure uncertainty. The method was evaluated through extensive clinical trial simulations of a hypothetical phase II dose-finding trial using different scenarios and comparing different methods such as MCP-Mod. The results show an increase in power using cLRT with longitudinal data compared to an EOT multiple contrast tests for scenarios with small sample size and weak drug effect while maintaining pre-specifiability of the models prior to data analysis and the nominal type I error. This work shows how model averaging provides better coverage probability of the drug effect in the prediction step, and avoids under-estimation of the size of the confidence interval. Finally, for illustration purpose cLRT-Mod was applied to the analysis of a real phase II dose-finding trial.
|
|
| 6. |
- Buatois, Simon, et al.
(författare)
-
Comparison of Model Averaging and Model Selection in Dose Finding Trials Analyzed by Nonlinear Mixed Effect Models
- 2018
-
Ingår i: AAPS Journal. - : Springer Science and Business Media LLC. - 1550-7416. ; 20:3
-
Tidskriftsartikel (refereegranskat)abstract
- In drug development, pharmacometric approaches consist in identifying via a model selection (MS) process the model structure that best describes the data. However, making predictions using a selected model ignores model structure uncertainty, which could impair predictive performance. To overcome this drawback, model averaging (MA) takes into account the uncertainty across a set of candidate models by weighting them as a function of an information criterion. Our primary objective was to use clinical trial simulations (CTSs) to compare model selection (MS) with model averaging (MA) in dose finding clinical trials, based on the AIC information criterion. A secondary aim of this analysis was to challenge the use of AIC by comparing MA and MS using five different information criteria. CTSs were based on a nonlinear mixed effect model characterizing the time course of visual acuity in wet age-related macular degeneration patients. Predictive performances of the modeling approaches were evaluated using three performance criteria focused on the main objectives of a phase II clinical trial. In this framework, MA adequately described the data and showed better predictive performance than MS, increasing the likelihood of accurately characterizing the dose-response relationship and defining the minimum effective dose. Moreover, regardless of the modeling approach, AIC was associated with the best predictive performances.
|
|
| 7. |
- Buatois, Simon, et al.
(författare)
-
Item Response Theory as an Efficient Tool to Describe a Heterogeneous Clinical Rating Scale in De Novo Idiopathic Parkinson's Disease Patients
- 2017
-
Ingår i: Pharmaceutical research. - : SPRINGER/PLENUM PUBLISHERS. - 0724-8741 .- 1573-904X. ; 34:10, s. 2109-2118
-
Tidskriftsartikel (refereegranskat)abstract
- This manuscript aims to precisely describe the natural disease progression of Parkinson's disease (PD) patients and evaluate approaches to increase the drug effect detection power. An item response theory (IRT) longitudinal model was built to describe the natural disease progression of 423 de novo PD patients followed during 48 months while taking into account the heterogeneous nature of the MDS-UPDRS. Clinical trial simulations were then used to compare drug effect detection power from IRT and sum of item scores based analysis under different analysis endpoints and drug effects. The IRT longitudinal model accurately describes the evolution of patients with and without PD medications while estimating different progression rates for the subscales. When comparing analysis methods, the IRT-based one consistently provided the highest power. IRT is a powerful tool which enables to capture the heterogeneous nature of the MDS-UPDRS.
|
|
| 8. |
|
|
| 9. |
- Guintivano, Jerry, et al.
(författare)
-
Meta-Analyses of Genome-Wide Association Studies for Postpartum Depression
- 2023
-
Ingår i: American Journal of Psychiatry. - : American Psychiatric Association Publishing. - 0002-953X .- 1535-7228. ; 180:12, s. 884-895
-
Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE: Postpartum depression (PPD) is a common subtype of major depressive disorder (MDD) that is more heritable, yet is understudied in psychiatric genetics. The authors conducted meta-analyses of genome-wide association studies (GWASs) to investigate the genetic architecture of PPD.METHOD: Meta-analyses were conducted on 18 cohorts of European ancestry (17,339 PPD cases and 53,426 controls), one cohort of East Asian ancestry (975 cases and 3,780 controls), and one cohort of African ancestry (456 cases and 1,255 controls), totaling 18,770 PPD cases and 58,461 controls. Post-GWAS analyses included 1) single-nucleotide polymorphism (SNP)-based heritability ([Formula: see text]), 2) genetic correlations between PPD and other phenotypes, and 3) enrichment of the PPD GWAS findings in 27 human tissues and 265 cell types from the mouse central and peripheral nervous system.RESULTS: No SNP achieved genome-wide significance in the European or the trans-ancestry meta-analyses. The [Formula: see text] of PPD was 0.14 (SE=0.02). Significant genetic correlations were estimated for PPD with MDD, bipolar disorder, anxiety disorders, posttraumatic stress disorder, insomnia, age at menarche, and polycystic ovary syndrome. Cell-type enrichment analyses implicate inhibitory neurons in the thalamus and cholinergic neurons within septal nuclei of the hypothalamus, a pattern that differs from MDD.CONCLUSIONS: While more samples are needed to reach genome-wide levels of significance, the results presented confirm PPD as a polygenic and heritable phenotype. There is also evidence that despite a high correlation with MDD, PPD may have unique genetic components. Cell enrichment results suggest GABAergic neurons, which converge on a common mechanism with the only medication approved by the U.S. Food and Drug Administration for PPD (brexanolone).
|
|
| 10. |
- Jauslin, Petra, et al.
(författare)
-
Identification of the Mechanism of Action of a Glucokinase Activator From Oral Glucose Tolerance Test Data in Type 2 Diabetic Patients Based on an Integrated Glucose-Insulin Model
- 2012
-
Ingår i: Journal of clinical pharmacology. - : Wiley. - 0091-2700 .- 1552-4604. ; 52:12, s. 1861-1871
-
Tidskriftsartikel (refereegranskat)abstract
- A mechanistic drug-disease model was developed on the basis of a previously published integrated glucose-insulin model by Jauslin et al. A glucokinase activator was used as a test compound to evaluate the model’s ability to identify a drug’s mechanism of action and estimate its effects on glucose and insulin profiles following oral glucose tolerance tests. A kinetic-pharmacodynamic approach was chosen to describe the drug’s pharmacodynamic effects in a dose-response-time model. Four possible mechanisms of action of antidiabetic drugs were evaluated, and the corresponding affected model parameters were identified: insulin secretion, glucose production, insulin effect on glucose elimination, and insulin-independent glucose elimination. Inclusion of drug effects in the model at these sites of action was first tested one-by-one and then in combination. The results demonstrate the ability of this model to identify the dual mechanism of action of a glucokinase activator and describe and predict its effects: Estimating a stimulating drug effect on insulin secretion and an inhibiting effect on glucose output resulted in a significantly better model fit than any other combination of effect sites. The model may be used for dose finding in early clinical drug development and for gaining more insight into a drug candidate’s mechanism of action.
|
|
| 11. |
- Jauslin, Petra M, et al.
(författare)
-
An integrated glucose-insulin model to describe oral glucose tolerance test data in type 2 diabetics
- 2007
-
Ingår i: Journal of clinical pharmacology. - : Wiley. - 0091-2700 .- 1552-4604. ; 47:10, s. 1244-1255
-
Tidskriftsartikel (refereegranskat)abstract
- An integrated model for the glucose-insulin system describing oral glucose tolerance test data was developed, extending on a previously introduced model for intravenous glucose provocations. Model extensions comprised the description of glucose absorption by a chain of transit compartments with a mean transit time of 35 minutes, a bioavailability of 80%, and a representation of the incretin effect, expressed as a direct effect of the glucose absorption rate on insulin secretion. The ability of the model to predict the incretin effect was assessed by simulating the observed difference in insulin response following an oral glucose tolerance test compared with an isoglycemic glucose infusion mimicking an oral glucose tolerance test profile. The extension of the integrated glucose-insulin model to gain information from oral glucose tolerance test data considerably expands its range of applications because the oral glucose tolerance test is one of the most common glucose challenge experiments for assessing the efficacy of hypoglycemic agents in clinical drug development.
|
|
| 12. |
- Jauslin, Petra, et al.
(författare)
-
Modeling of 24-Hour Glucose and Insulin Profiles of Patients With Type 2 Diabetes
- 2011
-
Ingår i: Journal of clinical pharmacology. - : Wiley. - 0091-2700 .- 1552-4604. ; 51:2, s. 153-164
-
Tidskriftsartikel (refereegranskat)abstract
- A model able to simultaneously characterize and simulate 24-hour glucose and insulin profiles following multiple meal tests was developed, extending an integrated glucose-insulin model for oral glucose tolerance tests that was previously published. The analysis was based on glucose and insulin measurements from 59 placebo-treated patients with type 2 diabetes. Circadian variations in glucose homeostasis were assessed on relevant parameters based on literature review. They were best described by a nighttime dip in insulin secretion between approximately 9 p.m. and 5 a.m. using a modulator function. The integrated glucose-insulin model has thus been shown to be applicable to real-life situations determined by multiple meals over the course of a day. This provides the basis for the analysis and simulation of long-term glucose and insulin data. The model may also prove useful for understanding antidiabetic drug actions and requirements in the context of circadian changes in glucose-insulin regulation.
|
|
| 13. |
- Jauslin-Stetina, Petra, 1976-
(författare)
-
Mechanism-Based Modeling of the Glucose-Insulin Regulation during Clinical Provocation Experiments
- 2008
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Type 2 diabetes is a complex chronic metabolic disorder characterized by hyperglycemia associated with a relative deficiency of insulin secretion and a reduced response of target tissues to insulin. Considerable efforts have been put into the development of models describing the glucose-insulin system. The best known is Bergman’s “minimal” model for glucose, which is estimating glucose concentrations using fixed insulin concentrations as input. However, due to the involved feedback mechanisms, simultaneous modeling of both entities would be advantageous. This is particularly relevant if the model is intended to be used as a predictive tool. The mechanism-based glucose-insulin model presented in this thesis is able to simultaneously describe glucose and insulin profiles following a wide variety of clinical provocation experiments, such as intravenous and oral glucose tolerance tests, clamp studies and sequential meal tests over 24 hours. It consists of sub-models for glucose, labeled glucose and insulin kinetics. It also incorporates control mechanisms for the regulation of glucose production, insulin secretion, and glucose uptake. Simultaneous analysis of all data by nonlinear mixed effect modeling was performed in NONMEM. Even if this model is a crude representation of a complex physiological system, its ability to represent the main processes of this system was established by identifying: 1) the difference in insulin secretion and insulin sensitivity between healthy volunteers and type 2 diabetics, 2) the action of incretin hormones after oral administration of glucose, 3) the circadian variation of insulin secretion and 4) the correct mechanism of action of a glucokinase activator, a new oral antidiabetic compound acting on both the pancreas and the liver. These promising results represent a proof of concept of a mechanistic drug-disease model that could play an important role in the clinical development of anti-diabetic drugs.
|
|
| 14. |
- Kjellsson, Maria C., et al.
(författare)
-
A Model-Based Approach to Predict Longitudinal HbA1c, Using Early Phase Glucose Data From Type 2 Diabetes Mellitus Patients After Anti-Diabetic Treatment
- 2013
-
Ingår i: Journal of clinical pharmacology. - : Wiley. - 0091-2700 .- 1552-4604. ; 53:6, s. 589-600
-
Tidskriftsartikel (refereegranskat)abstract
- Predicting late phase outcomes from early-phase findings can help inform decisions in drug development. If the measurements in early-phase differ from those in late phase, forecasting is more challenging. In this paper, we present a model-based approach for predicting glycosylated hemoglobin (HbA1c) in late phase using glucose and insulin concentrations from an early-phase study, investigating an anti-diabetic treatment. Two previously published models were used; an integrated glucose and insulin (IGI) model for meal tolerance tests and an integrated glucose-red blood cell-HbA1c (IGRH) model predicting the formation of HbA1c from the average glucose concentration (Cg,av). Output from the IGI model was used as input to the IGRH model. Parameters of the IGI model and drug effects were estimated using data from a phase1 study in 59 diabetic patients receiving various doses of a glucokinase activator. Cg,av values were simulated according to a Phase 2 study design and used in the IGRH model for predictions of HbA1c. The performance of the model-based approach was assessed by comparing the predicted to the actual outcome of the Phase 2 study. We have shown that this approach well predicts the longitudinal HbA1c response in a 12-week study using only information from a 1-week study where glucose and insulin concentrations were measured.
|
|
| 15. |
|
|
| 16. |
- Martin, Francis, et al.
(författare)
-
The genome of Laccaria bicolor provides insights into mycorrhizal symbiosis
- 2008
-
Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 452:7183, s. 7-88
-
Tidskriftsartikel (refereegranskat)abstract
- Mycorrhizal symbioses -- the union of roots and soil fungi -- are universal in terrestrial ecosystems and may have been fundamental to land colonization by plants1,2. Boreal, temperate, and montane forests all depend upon ectomycorrhizae1. Identification of the primary factors that regulate symbiotic development and metabolic activity will therefore open the door to understanding the role of 2 ectomycorrhizae in plant development and physiology, allowing the full ecological significance of this symbiosis to be explored. Here, we report the genome sequence of the ectomycorrhizal basidiomycete Laccaria bicolor (Fig. 1) and highlight gene sets involved in rhizosphere colonization and symbiosis. This 65-million-base genome assembly contains ~ 20,000 predicted protein-encoding genes and a very large number of transposons and repeated sequences. We detected unexpected genomic features most notably a battery of effector-type small secreted proteins (SSP) with unknown function, several of which are only expressed in symbiotic tissues. The most highly expressed SSP accumulates in the proliferating hyphae colonizing the host root. The ectomycorrhizae-specific proteins likely play a decisive role in the establishment of the symbiosis. The unexpected observation that the genome of L. bicolor lacks carbohydrate-active enzymes involved in degradation of plant cell walls, but maintains the ability to degrade non-plant cell walls, reveals the dual saprotrophic and biotrophic lifestyle of the mycorrhizal fungus which enables it to grow within both soil and living plant roots. The predicted gene inventory of the L. bicolor genome, therefore, points to previously unknown mechanisms of symbiosis operating in biotrophic mycorrhizal fungi. The availability of this genome provides an unparalleled opportunity to develop a deeper understanding of the processes by which symbionts interact with plants within their ecosystem in order to perform vital functions in the carbon and nitrogen cycles that are fundamental to sustainable plant productivity.
|
|
| 17. |
- Silber, Hanna E., 1977-, et al.
(författare)
-
An integrated glucose-insulin model to describe oral glucose tolerance test data in healthy volunteers
- 2010
-
Ingår i: Journal of clinical pharmacology. - : Wiley. - 0091-2700 .- 1552-4604. ; 50:3, s. 246-256
-
Tidskriftsartikel (refereegranskat)abstract
- The extension of the previously developed integrated models for glucose and insulin (IGI) to include the oral glucose tolerance test (OGTT) in healthy volunteers could be valuable to better understand the differences between healthy individuals and those with type 2 diabetes mellitus (T2DM). Data from an OGTT in 23 healthy volunteers were used. Analysis was based on the previously developed intravenous model with extensions for glucose absorption and incretin effect on insulin secretion. The need for additional structural components was evaluated. The model was evaluated by simulation and a bootstrap. Multiple glucose and insulin concentration peaks were observed in most individuals as well as hypoglycemic episodes in the second half of the experiment. The OGTT data were successfully described by the extended basic model. An additional control mechanism of insulin on glucose production improved the description of the data. The model showed good predictive properties, and parameters were estimated with good precision. In conclusion, a previously presented integrated model has been extended to describe glucose and insulin concentrations in healthy volunteers following an OGTT. The characterization of the differences between the healthy and diabetic stages in the IGI model could potentially be used to extrapolate drug effect from healthy volunteers to T2DM.
|
|
| 18. |
- Silber, Hanna E, et al.
(författare)
-
An integrated model for glucose and insulin regulation in healthy volunteers and type 2 diabetic patients following intravenous glucose provocations
- 2007
-
Ingår i: Journal of clinical pharmacology. - : Wiley. - 0091-2700 .- 1552-4604. ; 47:9, s. 1159-1171
-
Tidskriftsartikel (refereegranskat)abstract
- An integrated model for the regulation of glucose and insulin concentrations following intravenous glucose provocations in healthy volunteers and type 2 diabetic patients was developed. Data from 72 individuals were included. Total glucose, labeled glucose, and insulin concentrations were determined. Simultaneous analysis of all data by nonlinear mixed effect modeling was performed in NONMEM. Integrated models for glucose, labeled glucose, and insulin were developed. Control mechanisms for regulation of glucose production, insulin secretion, and glucose uptake were incorporated. Physiologically relevant differences between healthy volunteers and patients were identified in the regulation of glucose production, elimination rate of glucose, and secretion of insulin. The model was able to describe the insulin and glucose profiles well and also showed a good ability to simulate data. The features of the present model are likely to be of interest for analysis of data collected in antidiabetic drug development and for optimization of study design.
|
|
| 19. |
- Silber, Hanna E., et al.
(författare)
-
An Integrated Model for the Glucose-Insulin System
- 2010
-
Ingår i: Basic & Clinical Pharmacology & Toxicology. - : Wiley. - 1742-7835 .- 1742-7843. ; 106:3, s. 189-194
-
Forskningsöversikt (refereegranskat)abstract
- The integrated glucose-insulin model was originally developed on a variety of intravenous glucose provocation experiments in healthy volunteers and type 2 diabetic patients. The model, which simultaneously describes time-courses of glucose and insulin based on mechanism-based components for production, elimination and homeostatic feedback, has been further extended to oral glucose provocations, meal tests and insulin administration. The model has been used to describe experiments ranging from 4 to 24 hr. Applications of the integrated glucose-insulin model include the clinical assessment of the mechanism of action of anti-diabetic drugs and the magnitude of their effects. Finally, the model was used for optimizing the design of provocation experiments.
|
|
| 20. |
- Silber, Hanna, 1977-
(författare)
-
Integrated Modeling of Glucose and Insulin Regulation Following Provocation Experiments
- 2009
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Blood glucose is controlled by a complex system of insulin and other hormones to assure a constant supply of glucose to the tissues. Type 2 diabetes is a metabolic disorder which is characterized by progressively worsening glycemic control due to a relative deficiency of insulin secretion and a decreased response to insulin. Numerous mathematical models have been developed with the aim of describing glucose and insulin regulation. A drawback with most previously presented models is that they use an open-loop approach which simplifies the model development but at the same time limits the possible use for predictive purposes. The integrated glucose-insulin model presented in this thesis is a semi-mechanistic model which describes glucose and insulin simultaneously. The model has been used to analyze both intravenous and oral provocations and has been shown to describe and predict healthy and diabetic individuals well. Important differences between healthy and diabetic individuals were identified in insulin secretion and sensitivity. The model was used for design optimization of the intravenous glucose tolerance test and it was shown that the design could be improved and simplified by reduction of the number of samples and by change of glucose and insulin dose. Two methodological aspects which were of importance for model development were evaluated. These were (i) comparison of methods for incorporation of baseline data, and (ii) evaluation of the effects of model misspecification on hypothesis testing for covariate inclusion. Baseline information should be included in the model using either of three presented methods and normalization or subtraction of baseline should be avoided. The likelihood ratio test performed well in most cases except when serial correlation was present. In conclusion, a new model for glucose and insulin regulation has been proposed which is expected to play an important role in clinical development of anti-diabetic drugs.
|
|
