| 1. |
- Furukawa, Toshi A., et al.
(author)
-
Dismantling, optimising, and personalising internet cognitive behavioural therapy for depression : a systematic review and component network meta-analysis using individual data
- 2021
-
In: Lancet psychiatry. - London, United Kingdom : Elsevier. - 2215-0374 .- 2215-0366. ; 8:6, s. 500-511
-
Research review (peer-reviewed)abstract
- Findings We identified 76 RCTs, including 48 trials contributing individual participant data (11 704 participants) and 28 trials with aggregate data (6474 participants). The participants' weighted mean age was 42.0 years and 12 406 (71%) of 17 521 reported were women. There was suggestive evidence that behavioural activation might be beneficial (iMD -1.83 [95% credible interval (CrI) -2.90 to -0.80]) and that relaxation might be harmful (1.20 [95% CrI 0.17 to 2.27]). Baseline severity emerged as the strongest prognostic factor for endpoint depression. Combining human and automated encouragement reduced dropouts from treatment (incremental odds ratio, 0.32 [95% CrI 0.13 to 0.93]). The risk of bias was low for the randomisation process, missing outcome data, or selection of reported results in most of the included studies, uncertain for deviation from intended interventions, and high for measurement of outcomes. There was moderate to high heterogeneity among the studies and their components. 511
|
|
| 2. |
- Begnini, Fabio, et al.
(author)
-
Mining Natural Products for Macrocycles to Drug Difficult Targets
- 2021
-
In: Journal of Medicinal Chemistry. - : American Chemical Society (ACS). - 0022-2623 .- 1520-4804. ; 64:2, s. 1054-1072
-
Journal article (peer-reviewed)abstract
- Lead generation for difficult-to-drug targets that have large, featureless, and highly lipophilic or highly polar and/or flexible binding sites is highly challenging. Here, we describe how cores of macrocyclic natural products can serve as a high-quality in silico screening library that provides leads for difficult-to-drug targets. Two iterative rounds of docking of a carefully selected set of natural-product-derived cores led to the discovery of an uncharged macrocyclic inhibitor of the Keap1-Nrf2 protein- protein interaction, a particularly challenging target due to its highly polar binding site. The inhibitor displays cellular efficacy and is well-positioned for further optimization based on the structure of its complex with Keapl and synthetic access. We believe that our work will spur interest in using macrocyclic cores for in silico-based lead generation and also inspire the design of future macrocycle screening collections.
|
|
| 3. |
- Lagerlöf, Ingemar, et al.
(author)
-
No excess long-term mortality in stage I-IIA Hodgkin lymphoma patients treated with ABVD and limited field radiotherapy
- 2020
-
In: British Journal of Haematology. - : John Wiley & Sons. - 0007-1048 .- 1365-2141. ; 188:5, s. 685-691
-
Journal article (peer-reviewed)abstract
- When treating limited stage classical Hodgkin lymphoma (cHL), balancing treatment efficacy and toxicity is important. Toxicities after extended-field radiotherapy are well documented. Investigators have aimed at reducing toxicity without compromising efficacy, mainly by using combined modality treatment (CMT), i.e. chemotherapy and limited-field radiotherapy. In some clinical trials, radiotherapy has been omitted. We evaluated 364 patients with stage I-IIA cHL treated between 1999 and 2005. Patients were treated with two or four cycles of doxorubicin, bleomycin, vinblastine and dacarbazine (ABVD) according to presence of risk factors, followed by 30 Gy limited-field (reduced compared to involved-field) radiotherapy. After a median follow-up of 16 years for survival, freedom from progression at five and ten years was 93% and overall survival at 5 and 10 years was 98% and 96%, respectively. Only two relapses, out of 27, occurred after more than 5 years. There was no excess mortality compared to the general population. Of the analysed subgroups, only patients with progression within five years showed significant excess mortality. The absence of excess mortality questions the concept of omitting radiotherapy after short-term chemotherapy, a strategy that has been associated with an elevated risk of relapse but not yet with a proven reduced long-term excess mortality.
|
|
| 4. |
- Lisspers, Karin, Docent, 1954-, et al.
(author)
-
Developing a short-term prediction model for asthma exacerbations from Swedish primary care patients' data using machine learning - Based on the ARCTIC study
- 2021
-
In: Respiratory Medicine. - : Elsevier. - 0954-6111 .- 1532-3064. ; 185
-
Journal article (peer-reviewed)abstract
- Objective: The ability to predict impending asthma exacerbations may allow better utilization of healthcare resources, prevention of hospitalization and improve patient outcomes. We aimed to develop models using machine learning to predict risk of exacerbations. Methods: Data from 29,396 asthma patients was collected from electronic medical records and national registers covering clinical and epidemiological factors (e.g. comorbidities, health care contacts), between 2000 and 2013. Machine-learning classifiers were used to create models to predict exacerbations within the next 15 days. Model selection was done using the mean cross validation score of area under precision-recall curve (AUPRC). Results: The most important predictors of exacerbation were comorbidity burden and previous exacerbations. Model validation on test data yielded an AUPRC = 0.007 (95% CI: +/- 0.0002), indicating that historic clinical information alone may not be sufficient to predict a near future risk of asthma exacerbation. Conclusions: Supplementation with additional data on environmental triggers, (e.g. weather, pollen count, air quality) and from wearables, might be necessary to improve performance of the short-term predictive model to develop a more clinically useful tool.
|
|
| 5. |
- Mechler, Jakob, et al.
(author)
-
Therapist-guided internet-based psychodynamic therapy versus cognitive behavioural therapy for adolescent depression in Sweden : a randomised, clinical, non-inferiority trial
- 2022
-
In: The Lancet Digital Health. - : Elsevier. - 2589-7500. ; 4:8, s. E594-E603
-
Journal article (peer-reviewed)abstract
- Background Adolescent major depressive disorder (MDD) is highly prevalent and associated with lifelong adversity. Evidence-based treatments exist, but accessible treatment alternatives are needed. We aimed to compare internet-based psychodynamic therapy (IPDT) with an established evidence-based treatment (internet-based cognitive behavioural therapy [ICBT]) for the treatment of adolescents with depression. Methods In this randomised, clinical trial, we tested whether IPDT was non-inferior to ICBT in the treatment of adolescent MDD. Eligible participants were 15-19 years old, presenting with a primary diagnosis of MDD according to DSM-5. Participants were recruited nationwide in Sweden through advertisements on social media, as well as contacts with junior and senior high schools, youth associations, social workers, and health-care providers. Adolescents who scored 9 or higher on the Quick Inventory of Depressive Symptomatology for Adolescents (QIDS-A17-SR) in an initial online screening were contacted by telephone for a diagnostic assessment using the Mini International Neuropsychiatric Interview. Participants were randomly assigned to ICBT or IPDT. Both interventions comprised eight self-help modules delivered over 10 weeks on a secure online platform. The primary outcome was change in depression severity measured weekly by the QIDS-A17-SR. Primary analyses were based on an intention -to-treat sample including all participants randomly assigned. A non-inferiority margin of Cohen's d=0.30 was predefined. The study is registered at ISRCTN, ISRCTN12552584. Findings Between Aug 19, 2019, and Oct 7, 2020, 996 young people completed screening; 516 (52%) were contacted for a diagnostic interview. 272 participants were eligible and randomly assigned to ICBT (n=136) or IPDT (n=136). In the ICBT group, 51 (38%) of 136 participants were classified as remitted, and 54 (40%) of 136 participants were classified as remitted in the IPDT group. Within-group effects were large (ICBT: within-group d=1.75, 95% CI 1.49 to 2.01; IPDT: within-group d=1.93, 1.67 to 2.20; both p<0.0001). No statistically significant treatment difference was found in the intention-to-treat analysis. Non-inferiority for IPDT was shown for the estimated change in depression during treatment (d=-0.18, 90% CI -0.49 to 0.13; p=0.34). All secondary outcomes showed non-significant between-group differences. Interpretation IPDT was non-inferior to ICBT in terms of change in depression for the treatment of adolescents with MDD. This finding increases the range of accessible and effective treatment alternatives for adolescents with depression. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.
|
|
| 6. |
- Nilsson, Anders K., 1982, et al.
(author)
-
PSB33 protein sustains photosystem II in plant chloroplasts under UV-A light
- 2020
-
In: Journal of Experimental Botany. - OXFORD ENGLAND : Oxford University Press (OUP). - 0022-0957 .- 1460-2431. ; 71:22, s. 7210-7223
-
Journal article (peer-reviewed)abstract
- Plants can quickly and dynamically respond to spectral and intensity variations of the incident light. These responses include activation of developmental processes, morphological changes, and photosynthetic acclimation that ensure optimal energy conversion and minimal photoinhibition. Plant adaptation and acclimation to environmental changes have been extensively studied, but many details surrounding these processes remain elusive. The photosystem II (PSII)-associated protein PSB33 plays a fundamental role in sustaining PSII as well as in the regulation of the light antenna in fluctuating light. We investigated how PSB33 knock-out Arabidopsis plants perform under different light qualities. psb33 plants displayed a reduction of 88% of total fresh weight compared to wild type plants when cultivated at the boundary of UV-A and blue light. The sensitivity towards UV-A light was associated with a lower abundance of PSII proteins, which reduces psb33 plants' capacity for photosynthesis. The UV-A phenotype was found to be linked to altered phytohormone status and changed thylakoid ultrastructure. Our results collectively show that PSB33 is involved in a UV-A light-mediated mechanism to maintain a functional PSII pool in the chloroplast.
|
|
| 7. |
- Salt Ducaju, Julian M., et al.
(author)
-
Joint Stiction Avoidance with Null-Space Motion in Real-Time Model Predictive Control for Redundant Collaborative Robots
- 2021
-
In: 2021 30th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2021. - 1944-9445 .- 1944-9437. - 9781665404921 ; , s. 307-314
-
Conference paper (peer-reviewed)abstract
- Model Predictive Control (MPC) is an efficient point-to-point trajectory-generation method for robots that can be used in situations that occur under time constraints. The motion plan can be recalculated online to increase the accuracy of the trajectory when getting close to the goal position. We have implemented this strategy in a Franka Emika Panda robot, a redundant collaborative robot, by extending previous research that was performed on a 6-DOF robot. We have also used null-space motion to ensure a continuous movement of all joints during the entire trajectory execution as an approach to avoid joint stiction and allow accurate kinesthetic teaching. As is conventional for collaborative and industrial robots, the Panda robot is equipped with an internal controller, which allows to send position and velocity references directly to the robot. Therefore, null-space motion can be added directly to the MPC-generated velocity references. The observed trajectory deviation caused by discretization approximations of the Jacobian matrix when implementing null-space motion has been corrected experimentally using sensor feedback for the real-time velocity-reference recalculation and by performing a fast sampling of the null-space vector. Null-space motion has been experimentally seen to contribute to reducing the friction torque dispersion present in static joints.
|
|
| 8. |
- Ställberg, Björn, Docent, et al.
(author)
-
Predicting Hospitalization Due to COPD Exacerbations in Swedish Primary Care Patients Using Machine Learning - Based on the ARCTIC Study
- 2021
-
In: The International Journal of Chronic Obstructive Pulmonary Disease. - : Taylor & Francis. - 1176-9106 .- 1178-2005. ; 16, s. 677-688
-
Journal article (peer-reviewed)abstract
- Purpose: Chronic obstructive pulmonary disease (COPD) exacerbations can negatively impact disease severity, progression, mortality and lead to hospitalizations. We aimed to develop a model that predicts a patient's risk of hospitalization due to severe exacerbations (defined as COPD-related hospitalizations) of COPD, using Swedish patient level data. Patients and Methods: Patient level data for 7823 Swedish patients with COPD was collected from electronic medical records (EMRs) and national registries covering healthcare contacts, diagnoses, prescriptions, lab tests, hospitalizations and socioeconomic factors between 2000 and 2013. Models were created using machine-learning methods to predict risk of imminent exacerbation causing patient hospitalization due to COPD within the next 10 days. Exacerbations occurring within this period were considered as one event. Model performance was assessed using the Area under the Precision-Recall Curve (AUPRC). To compare performance with previous similar studies, the Area Under Receiver Operating Curve (AUROC) was also reported. The model with the highest mean cross validation AUPRC was selected as the final model and was in a final step trained on the entire training dataset. Results: The most important factors for predicting severe exacerbations were exacerbations in the previous six months and in whole history, number of COPD-related healthcare contacts and comorbidity burden. Validation on test data yielded an AUROC of 0.86 and AUPRC of 0.08, which was high in comparison to previously published attempts to predict COPD exacerbation. Conclusion: Our work suggests that clinically available information on patient history collected via automated retrieval from EMRs and national registries or directly during patient consultation can form the basis for future clinical tools to predict risk of severe COPD exacerbations.
|
|
