Tutorial on survival modeling with applications to omics data.

MOTIVATION: Identification of genomic, molecular and clinical markers prognostic of patient survival is important for developing personalized disease prevention, diagnostic and treatment approaches. Modern omics technologies have made it possible to investigate the prognostic impact of markers at multiple molecular levels, including genomics, epigenomics, transcriptomics, proteomics and metabolomics, and how these potential risk factors complement clinical characterization of patient outcomes for survival prognosis. However, the massive sizes of the omics datasets, along with their correlation structures, pose challenges for studying relationships between the molecular information and patients' survival outcomes. RESULTS: We present a general workflow for survival analysis that is applicable to high-dimensional omics data as inputs when identifying survival-associated features and validating survival models. In particular, we focus on the commonly used Cox-type penalized regressions and hierarchical Bayesian models for feature selection in survival analysis, which are especially useful for high-dimensional data, but the framework is applicable more generally. AVAILABILITY AND IMPLEMENTATION: A step-by-step R tutorial using The Cancer Genome Atlas survival and omics data for the execution and evaluation of survival models has been made available at https://ocbe-uio.github.io/survomics.

Outcomes of 10 years of PSA screening for prostate cancer in Norwegian men with Lynch syndrome.

BACKGROUND: Pathogenic germline variants in the mismatch repair (MMR) genes are associated with an increased risk of prostate cancer (PCa). Since 2010 we have recommended MMR carriers annual PSA testing from the age of 40. Prospective studies of the outcome of long-term PSA screening are lacking. This study aimed to investigate the incidence and characteristics of PCa in Norwegian MMR carriers attending annual PSA screening (PSA threshold >3.0 ng/mL) to evaluate whether our recommendations should be continued. METHODS: This is a prospective observational study of 225 male MMR carriers who were recommended annual PSA screening by the Section of Inherited Cancer, Oslo University Hospital from 2010 and onwards. Incidence and tumor characteristics (age, PSA at diagnosis, Gleason score, TNM score) were described. IHC and MSI-analyses were done on available tumors. Standardized incidence ratio (SIR) was calculated based on data from the Cancer Registry of Norway. RESULTS: Twenty-two of 225 (9.8%) had been diagnosed with PCa, including 10/69 (14.5%) MSH2 carriers and 8/61 (13.1%) MSH6 carriers. Ten of 20 (50%) tumors had Gleason score ≥4 + 3 on biopsy and 6/11 (54.5%) had a pathological T3a/b stage. Eight of 17 (47.1%) tumors showed abnormal staining on IHC and 3/13 (23.1%) were MSI-high. SIR was 9.54 (95% CI 5.98-14.45) for all MMR genes, 13.0 (95% CI 6.23-23.9) for MSH2 and 13.74 for MSH6 (95% CI 5.93-27.08). CONCLUSIONS: Our results indicate that the MMR genes, and especially MSH2 and MSH6, are associated with a significant risk of PCa, and a high number of tumors show aggressive characteristics. While the impact of screening on patient outcomes remains to be more firmly established, the high SIR values we observe provide support for continued PSA screening of MSH2 and MSH6 carriers. Studies are needed to provide optimal recommendations for PSA-threshold and to evaluate whether MLH1 and PMS2 carriers should not be recommended screening.

screenwerk: a modular tool for the design and analysis of drug combination screens.

MOTIVATION: There is a rapidly growing interest in high-throughput drug combination screening to identify synergizing drug interactions for treatment of various maladies, such as cancer and infectious disease. This creates the need for pipelines that can be used to design such screens, perform quality control on the data and generate data files that can be analyzed by synergy-finding bioinformatics applications. RESULTS: screenwerk is an open-source, end-to-end modular tool available as an R-package for the design and analysis of drug combination screens. The tool allows for a customized build of pipelines through its modularity and provides a flexible approach to quality control and data analysis. screenwerk is adaptable to various experimental requirements with an emphasis on precision medicine. It can be coupled to other R packages, such as bayesynergy, to identify synergistic and antagonistic drug interactions in cell lines or patient samples. screenwerk is scalable and provides a complete solution for setting up drug sensitivity screens, read raw measurements and consolidate different datasets, perform various types of quality control and analyze, report and visualize the results of drug sensitivity screens. AVAILABILITY AND IMPLEMENTATION: The R-package and technical documentation is available at https://github.com/Enserink-lab/screenwerk; the R source code is publicly available at https://github.com/Enserink-lab/screenwerk under GNU General Public License v3.0; bayesynergy is accessible at https://github.com/ocbe-uio/bayesynergy. Selected modules are available through Galaxy, an open-source platform for FAIR data analysis at https://oncotools.elixir.no. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Adjustment of spurious correlations in co-expression measurements from RNA-Sequencing data.

MOTIVATION: Gene co-expression measurements are widely used in computational biology to identify coordinated expression patterns across a group of samples. Coordinated expression of genes may indicate that they are controlled by the same transcriptional regulatory program, or involved in common biological processes. Gene co-expression is generally estimated from RNA-Sequencing data, which are commonly normalized to remove technical variability. Here, we demonstrate that certain normalization methods, in particular quantile-based methods, can introduce false-positive associations between genes. These false-positive associations can consequently hamper downstream co-expression network analysis. Quantile-based normalization can, however, be extremely powerful. In particular, when preprocessing large-scale heterogeneous data, quantile-based normalization methods such as smooth quantile normalization can be applied to remove technical variability while maintaining global differences in expression for samples with different biological attributes. RESULTS: We developed SNAIL (Smooth-quantile Normalization Adaptation for the Inference of co-expression Links), a normalization method based on smooth quantile normalization specifically designed for modeling of co-expression measurements. We show that SNAIL avoids formation of false-positive associations in co-expression as well as in downstream network analyses. Using SNAIL, one can avoid arbitrary gene filtering and retain associations to genes that only express in small subgroups of samples. This highlights the method's potential future impact on network modeling and other association-based approaches in large-scale heterogeneous data. AVAILABILITY AND IMPLEMENTATION: The implementation of the SNAIL algorithm and code to reproduce the analyses described in this work can be found in the GitHub repository https://github.com/kuijjerlab/PySNAIL.

Dose-response prediction for in-vitro drug combination datasets: a probabilistic approach.

In this paper we propose PIICM, a probabilistic framework for dose-response prediction in high-throughput drug combination datasets. PIICM utilizes a permutation invariant version of the intrinsic co-regionalization model for multi-output Gaussian process regression, to predict dose-response surfaces in untested drug combination experiments. Coupled with an observation model that incorporates experimental uncertainty, PIICM is able to learn from noisily observed cell-viability measurements in settings where the underlying dose-response experiments are of varying quality, utilize different experimental designs, and the resulting training dataset is sparsely observed. We show that the model can accurately predict dose-response in held out experiments, and the resulting function captures relevant features indicating synergistic interaction between drugs.

bayesynergy: flexible Bayesian modelling of synergistic interaction effects in in vitro drug combination experiments.

The effect of cancer therapies is often tested pre-clinically via in vitro experiments, where the post-treatment viability of the cancer cell population is measured through assays estimating the number of viable cells. In this way, large libraries of compounds can be tested, comparing the efficacy of each treatment. Drug interaction studies focus on the quantification of the additional effect encountered when two drugs are combined, as opposed to using the treatments separately. In the bayesynergy R package, we implement a probabilistic approach for the description of the drug combination experiment, where the observed dose response curve is modelled as a sum of the expected response under a zero-interaction model and an additional interaction effect (synergistic or antagonistic). Although the model formulation makes use of the Bliss independence assumption, we note that the posterior estimates of the dose-response surface can also be used to extract synergy scores based on other reference models, which we illustrate for the Highest Single Agent model. The interaction is modelled in a flexible manner, using a Gaussian process formulation. Since the proposed approach is based on a statistical model, it allows the natural inclusion of replicates, handles missing data and uneven concentration grids, and provides uncertainty quantification around the results. The model is implemented in the open-source Stan programming language providing a computationally efficient sampler, a fast approximation of the posterior through variational inference, and features parallel processing for working with large drug combination screens.

Real-world data on niraparib maintenance treatment in patients with non-gBRCA mutated platinum-sensitive recurrent ovarian cancer.

OBJECTIVES: The aim of this study was to provide real-world efficacy and safety data on niraparib maintenance treatment in patients with non-germline (gBRCA)1/2 mutated platinum-sensitive recurrent ovarian cancer. METHODS: This retrospective multi-center cohort study included 94 platinum-sensitive recurrent ovarian cancer patients without known gBRCA1/2 mutation treated in an individual patient access program in Norway. The primary outcome was time from start of niraparib treatment to first subsequent treatment. Secondary endpoints included progression-free survival, safety, and tolerability. RESULTS: After median follow-up of 13.4 months (95% confidence interval (CI) 10.0 to 16.8), 68.1% had progressed and 22.3% had died. Of the entire cohort, 61.7% had commenced a new line of treatment, and 24.5% were still receiving niraparib. The median duration of niraparib treatment was 5.0 months (range 0.4 to 27.3), and the median time to first subsequent treatment was 10.7 months (95% CI 8.4 to 13.0). Patients with elevated CA125 prior to start of niraparib had shorter time to first subsequent treatment (7.3 months, 95% CI 4.2 to 10.3) than patients with normalized CA125 (12.2 months, 95% CI 10.9 to 13.7 (p=0.002). Patients who started on individual dose based on weight and platelet counts had fewer dose reductions (p<0.001) and interruptions (p=0.02). CONCLUSION: In a real-world setting, niraparib maintenance treatment in patients with non-gBRCA1/2 mutated recurrent platinum-sensitive ovarian cancer showed effectiveness comparable with published phase III studies and acceptable safety. Individualized dosing is essential to minimize adverse events. CA125 levels at start of niraparib treatment may help to estimate the individual prognosis.

Placenta-derived proteins across gestation in healthy pregnancies-a novel approach to assess placental function?

BACKGROUND: Placenta-derived proteins in the systemic maternal circulation are suggested as potential biomarkers for placental function. However, the identity and longitudinal patterns of such proteins are largely unknown due to the inaccessibility of the human placenta and limitations in assay technologies. We aimed to identify proteins derived from and taken up by the placenta in the maternal circulation. Furthermore, we aimed to describe the longitudinal patterns across gestation of placenta-derived proteins as well as identify placenta-derived proteins that can serve as reference curves for placental function. METHODS: We analyzed proteins in plasma samples collected in two cohorts using the Somalogic 5000-plex platform. Antecubital vein samples were collected at three time points (gestational weeks 14-16, 22-24, and 30-32) across gestation in 70 healthy pregnancies in the longitudinal STORK cohort. In the cross sectional 4-vessel cohort, blood samples were collected simultaneously from the maternal antecubital vein (AV), radial artery (RA), and uterine vein (UV) during cesarean section in 75 healthy pregnancies. Placenta-derived proteins and proteins taken up by the placenta were identified using venoarterial differences (UV-RA). Placenta-derived proteins were defined as placenta-specific by comparison to the venoarterial difference in the antecubital vein-radial artery (AV-RA). These proteins were described longitudinally based on the STORK cohort samples using a linear mixed effects model per protein. Using a machine learning algorithm, we identified placenta-derived proteins that could predict gestational age, meaning that they closely tracked gestation, and were potential read-outs of placental function. RESULTS: Among the nearly 5000 measured proteins, we identified 256 placenta-derived proteins and 101 proteins taken up by the placenta (FDR < 0.05). Among the 256 placenta-derived proteins released to maternal circulation, 101 proteins were defined as placenta-specific. These proteins formed two clusters with distinct developmental patterns across gestation. We identified five placenta-derived proteins that closely tracked gestational age when measured in the systemic maternal circulation, termed a "placental proteomic clock." CONCLUSIONS: Together, these data may serve as a first step towards a reference for the healthy placenta-derived proteome that can be measured in the systemic maternal circulation and potentially serve as biomarkers of placental function. The "placental proteomic clock" represents a novel concept that warrants further investigation. Deviations in the proteomic pattern across gestation of such proteomic clock proteins may serve as an indication of placental dysfunction.

"Psychometric properties of the Norwegian foot function index revised short form".

BACKGROUND: Foot disorders affect up to one quarter of the adult population. Plantar fasciopathy is a common cause of foot pain associated with decreased activity level and quality of life. Patient-reported outcome measures are important in assessing the burden of a condition as well as in research on the effects of interventions. The Foot Function Index revised short form (FFI-RS) is a region specific questionnaire frequently used in research. This study aimed to cross-culturally adapt the FFI-RS into Norwegian and to test its psychometric properties. METHODS: The FFI-RS was translated into Norwegian (FFI-RSN) following international guidelines. 139 patients with foot disorders (88% with plantar fasciopathy) were included at baseline to measure internal consistency, explorative factor analysis, construct validity and floor and ceiling effects. 54 patients were included after 1 week for test-retest reliability and smallest detectable change analyses. 100 patients were included for responsiveness and minimal important change at 3 months. RESULTS: Cronbach's alpha for internal consistency was 0.97 and factor analysis supported the use of the total score of the FFI-RSN. Two out of three predefined hypotheses were confirmed by assessing the construct validity with Spearman's correlation coefficient. Quadratic weighted Kappa for test-retest reliability showed 0.91 (95% CI 0.86-0.96) and the smallest detectable change was 6.5%. The minimal important change was 8.4% and the area under the receiver operating characteristic curve for responsiveness was 0.78 (95% CI 0.69-0.87). We found no floor or ceiling effects on the total score of the FFI-RSN. CONCLUSIONS: The present study showed excellent reliability of the FFI-RSN and supports the use of the total score of the questionnaire. Furthermore, we found the FFI-RSN to have acceptable responsiveness in relation to change in general health. Smallest detectable change, minimal important change and responsiveness were presented as novel results of the total score of the FFI-RS. FFI-RSN can be used to evaluate global foot health in clinical or research settings with Norwegian patients suffering from plantar fasciopathy. TRIAL REGISTRATION: Clinical Trials.gov NCT04207164 . Initial release 01.11.19.

Combining heterogeneous subgroups with graph-structured variable selection priors for Cox regression.

BACKGROUND: Important objectives in cancer research are the prediction of a patient's risk based on molecular measurements such as gene expression data and the identification of new prognostic biomarkers (e.g. genes). In clinical practice, this is often challenging because patient cohorts are typically small and can be heterogeneous. In classical subgroup analysis, a separate prediction model is fitted using only the data of one specific cohort. However, this can lead to a loss of power when the sample size is small. Simple pooling of all cohorts, on the other hand, can lead to biased results, especially when the cohorts are heterogeneous. RESULTS: We propose a new Bayesian approach suitable for continuous molecular measurements and survival outcome that identifies the important predictors and provides a separate risk prediction model for each cohort. It allows sharing information between cohorts to increase power by assuming a graph linking predictors within and across different cohorts. The graph helps to identify pathways of functionally related genes and genes that are simultaneously prognostic in different cohorts. CONCLUSIONS: Results demonstrate that our proposed approach is superior to the standard approaches in terms of prediction performance and increased power in variable selection when the sample size is small.

Hand use development in children with unilateral cerebral palsy.

AIM: To describe the development of hand use during bimanual activities among children with unilateral cerebral palsy (CP). METHOD: A cohort of 166 children (79 females, 87 males; age range 18mo-13y, mean [SD] age at first assessment 37.6mo [20.5mo]) with unilateral CP, registered in the Norwegian CP Follow-up Program with two or more Assisting Hand Assessments (AHAs), were included in this longitudinal study comprising 524 AHAs. Developmental limits and rates were estimated by non-linear mixed effects models and compared between a stable limit model (SLM) and a peak and decline model. Development was described according to Manual Ability Classification System (MACS) levels and AHA performance at 18 months of age (AHA-18). RESULTS: Children in MACS level I, or in the high AHA-18 group, reached highest limits and had the most rapid development (p<0.001). The developmental trajectories were different between MACS levels I, II, and III and between the high, moderate, and low AHA-18 groups. Seventy-five per cent of the children reached 90% of their estimated limit at 5 years 10 months or earlier. The SLM showed the best model fit (Akaike information criterion: 4008.99). INTERPRETATION: Most children approached a steady performance limit before 6 years of age. Although children in MACS levels I and II reached 90% of the expected limit at 3 and 4 years respectively, the corresponding age was 8 years for children in MACS level III. The better model fit for the SLM indicates that children with unilateral CP maintain their attained limit of hand use to at least the age of 13 years. What this paper adds Development of hand use between 18 months and 13 years follows a stable-limit pattern. Most children reach a steady limit on the Assisting Hand Assessment before 6 years of age. Manual Ability Classification System levels I, II, and III represent distinct developmental trajectories, level III having a slower rise. Early hand use is an important indicator of future development.

Pre-stroke cognitive impairment is associated with vascular imaging pathology: a prospective observational study.

BACKGROUND: Chronic brain pathology and pre-stroke cognitive impairment (PCI) is predictive of post-stroke dementia. The aim of the current study was to measure pre-stroke neurodegenerative and vascular disease burden found on brain MRI and to assess the association between pre-stroke imaging pathology and PCI, whilst also looking for potential sex differences. METHODS: This prospective brain MRI cohort is part of the multicentre Norwegian cognitive impairment after stroke (Nor-COAST) study. Patients hospitalized with acute ischemic or hemorrhagic stroke were included from five participating stroke units. Visual rating scales were used to categorize baseline MRIs (N = 410) as vascular, neurodegenerative, mixed, or normal, based on the presence of pathological imaging findings. Pre-stroke cognition was assessed by interviews of patients or caregivers using the Global Deterioration Scale (GDS). Stroke severity was assessed with the National Institute of Health Stroke Scale (NIHSS). Univariate and multiple logistic regression analyses were performed to investigate the association between imaging markers, PCI, and sex. RESULTS: Patients' (N = 410) mean (SD) age was 73.6 (±11) years; 182 (44%) participants were female, the mean (SD) NIHSS at admittance was 4.1 (±5). In 68% of the participants, at least one pathological imaging marker was found. Medial temporal lobe atrophy (MTA) was present in 30% of patients, white matter hyperintensities (WMH) in 38% of patients and lacunes in 35% of patients. PCI was found in 30% of the patients. PCI was associated with cerebrovascular pathology (OR 2.5; CI = 1.4 to 4.5, p = 0.001) and mixed pathology (OR 3.4; CI = 1.9 to 6.1, p = 0.001) but was not associated with neurodegeneration (OR 1.0; CI = 0.5 to 2.2; p = 0.973). Pathological MRI markers, including MTA and lacunes, were more prevalent among men, as was a history of clinical stroke prior to the index stroke. The OR of PCI for women was not significantly increased (OR 1.2; CI = 0.8 to 1.9; p = 0.3). CONCLUSIONS: Pre-stroke chronic brain pathology is common in stroke patients, with a higher prevalence in men. Vascular pathology and mixed pathology are associated with PCI. There were no significant sex differences for the risk of PCI. TRIAL REGISTRATION: NCT02650531 , date of registration: 08.01.2016.

Loss of CBY1 results in a ciliopathy characterized by features of Joubert syndrome.

Ciliopathies are clinically and genetically heterogeneous diseases. We studied three patients from two independent families presenting with features of Joubert syndrome: abnormal breathing pattern during infancy, developmental delay/intellectual disability, cerebellar ataxia, molar tooth sign on magnetic resonance imaging scans, and polydactyly. We identified biallelic loss-of-function (LOF) variants in CBY1, segregating with the clinical features of Joubert syndrome in the families. CBY1 localizes to the distal end of the mother centriole, contributing to the formation and function of cilia. In accordance with the clinical and mutational findings in the affected individuals, we demonstrated that depletion of Cby1 in zebrafish causes ciliopathy-related phenotypes. Levels of CBY1 transcript were found reduced in the patients compared with controls, suggesting degradation of the mutated transcript through nonsense-mediated messenger RNA decay. Accordingly, we could detect CBY1 protein in fibroblasts from controls, but not from patients by immunofluorescence. Furthermore, we observed reduced ability to ciliate, increased ciliary length, and reduced levels of the ciliary proteins AHI1 and ARL13B in patient fibroblasts. Our data show that CBY1 LOF-variants cause a ciliopathy with features of Joubert syndrome.

An extension to: Systematic assessment of commercially available low-input miRNA library preparation kits.

High-throughput sequencing has emerged as the favoured method to study microRNA (miRNA) expression, but biases introduced during library preparation have been reported. We recently compared the performance (sensitivity, reliability, titration response and differential expression) of six commercially-available kits on synthetic miRNAs and human RNA, where library preparation was performed by the vendors. We hereby supplement this study with data from two further commonly used kits (NEBNext, NEXTflex) whose manufacturers initially declined to participate. NEXTflex demonstrated the highest sensitivity, which may reflect its use of partially-randomized adapter sequences, but overall performance was lower than the QIAseq and TailorMix kits. NEBNext showed intermediate performance. We reaffirm that biases are kit specific, complicating the comparison of miRNA datasets generated using different kits.

Systematic assessment of commercially available low-input miRNA library preparation kits.

High-throughput sequencing is increasingly favoured to assay the presence and abundance of microRNAs (miRNAs) in biological samples, even from low RNA amounts, and a number of commercial vendors now offer kits that allow miRNA sequencing from sub-nanogram (ng) inputs. Although biases introduced during library preparation have been documented, the relative performance of current reagent kits has not been investigated in detail. Here, six commercial kits capable of handling <100ng total RNA input were used for library preparation, performed by kit manufactures, on synthetic miRNAs of known quantities and human total RNA samples. We compared the performance of miRNA detection sensitivity, reliability, titration response and the ability to detect differentially expressed miRNAs. In addition, we assessed the use of unique molecular identifiers (UMI) sequence tags in one kit. We observed differences in detection sensitivity and ability to identify differentially expressed miRNAs between the kits, but none were able to detect the full repertoire of synthetic miRNAs. The reliability within the replicates of all kits was good, while larger differences were observed between the kits, although none could accurately quantify the relative levels of the majority of miRNAs. UMI tags, at least within the input ranges tested, offered little advantage to improve data utility. In conclusion, biases in miRNA abundance are heavily influenced by the kit used for library preparation, suggesting that comparisons of datasets prepared by different procedures should be made with caution. This article is intended to assist researchers select the most appropriate kit for their experimental conditions.

Factors increasing the risk of inappropriate vancomycin therapy in ICU patients: A prospective observational study.

BACKGROUND: Vancomycin trough levels are frequently subtherapeutic in intensive care unit (ICU) patients. The aim of this study was to identify patients at risk of therapeutic failure defined as vancomycin area-under-the-curve0-24 /minimum inhibitory concentration (AUC0-24 /MIC) <400, and to examine possible effects of different MICs, the variability in renal clearance and continuous renal replacement therapy (CRRT), and the relevance of vancomycin therapy. METHODS: A prospective observational study of ICU patients ≥ 18 years at initiation of vancomycin therapy was conducted from May 2013 to October 2015. The patients were divided into four groups according to renal function and CRRT-mode as follows: normal- or augmented renal clearance and continuous venovenous hemodialysis or -hemofiltration. Vancomycin peak and trough levels were measured at 24, 48, and 72 hours after therapy initiation. Relevance of vancomycin therapy was retrospectively evaluated based on microbiological results. RESULTS: Eighty-three patients were included, median age 54.5 years, 74.5% male, SAPS II score 46, and 90 day mortality 28%. Vancomycin therapy was initiated on ICU-day 8 (IQR, 5-12), with a median treatment time of 7.5 (IQR, 5-12) days. AUC0-24 /MIC > 400 was reached in 81% and 8% with MIC = 1 and 2 mg/L respectively. The CRRT groups had higher AUC0-24 /MIC-ratios than the non-CRRT groups (P < .001). Augmented renal clearance increased the risk of AUC0-24 /MIC < 400, independent of MIC-value. Initiation of vancomycin therapy was retrospectively considered relevant in 28 patients (34%). CONCLUSION: A MIC-value >1 mg/L and augmented renal clearance, were factors increasing the risk of therapeutic failure. Vancomycin treatments could have been omitted or shortened in most of these patients.

The effects of a dialogue-based intervention to promote psychosocial well-being after stroke: a randomized controlled trial.

OBJECTIVE: To evaluate the effect of a dialogue-based intervention targeting psychosocial well-being at 12 months post-stroke. DESIGN: Multicenter, prospective, randomized, assessor-blinded, controlled trial with two parallel groups. SETTING: Community. SUBJECTS: Three-hundred and twenty-two adults (⩾18 years) with stroke within the last four weeks were randomly allocated into intervention group (n = 166) or control group (n = 156). INTERVENTIONS: The intervention group received a dialogue-based intervention to promote psychosocial well-being, comprising eight individual 1-1½ hour sessions delivered during the first six months post-stroke. MAIN MEASURES: The primary outcome measure was the General Health Questionnaire-28 (GHQ-28). Secondary outcome measures included the Stroke and Aphasia Quality of Life Scale-39g, the Sense of Coherence scale, and the Yale Brown single-item questionnaire. RESULTS: The mean (SD) age of the participants was 66.8 (12.1) years in the intervention group and 65.7 (13.3) years in the control group. At 12 months post-stroke, the mean (SE) GHQ-28 score was 20.6 (0.84) in the intervention group and 19.9 (0.85) in the control group. There were no between-group differences in psychosocial well-being at 12 months post-stroke (mean difference: -0.74, 95% confidence interval (CI): -3.08, 1.60). The secondary outcomes showed no statistically significant between-group difference in health-related quality of life, sense of coherence, or depression at 12 months. CONCLUSION: The results of this trial did not demonstrate lower levels of emotional distress and anxiety or higher levels of health-related quality of life in the intervention group (dialogue-based intervention) as compared to the control group (usual care) at 12 months post-stroke.

Associations between clinical symptoms, plasma norepinephrine and deregulated immune gene networks in subgroups of adolescent with Chronic Fatigue Syndrome.

BACKGROUND: Chronic Fatigue Syndrome (CFS) is one of the most important causes of disability among adolescents while limited knowledge exists on genetic determinants underlying disease pathophysiology. METHODS: We analyzed deregulated immune-gene modules using Pathifier software on whole blood gene expression data (29 CFS patients, 18 controls). Deconvolution of immune cell subtypes based on gene expression profile was performed using CIBERSORT. Supervised consensus clustering on pathway deregulation score (PDS) was used to define CFS subgroups. Associations between PDS and immune, neuroendocrine/autonomic and clinical markers were examined. The impact of plasma norepinephrine level on clinical markers over time was assessed in a larger cohort (91 patients). RESULTS: A group of 29 immune-gene sets was shown to differ patients from controls and detect subgroups within CFS. Group 1P (high PDS, low norepinephrine, low naïve CD4+ composition) had strong association with levels of serum C-reactive protein and Transforming Growth Factor-beta. Group 2P (low PDS, high norepinephrine, high naïve CD4+ composition) had strong associations with neuroendocrine/autonomic markers. The corresponding plasma norepinephrine level delineated 91 patients into two subgroups with significant differences in fatigue score. CONCLUSION: We identified 29 immune-gene sets linked to plasma norepinephrine level that could delineate CFS subgroups. Plasma norepinephrine stratification revealed that lower levels of norepinephrine were associated with higher fatigue. Our data suggests potential involvement of neuro-immune dysregulation and genetic stratification in CFS.

Impact of animated instruction on tablets and hands-on training in applying bimanual perineal support on episiotomy rates: an intervention study.

INTRODUCTION AND HYPOTHESIS: In Palestine, episiotomy is frequently used among primiparous women.This study assesses the effect of training birth attendants in applying bimanual perineal support during delivery by either animated instruction on tablets or hands-on training on episiotomy rates among primiparous women. METHODS: An interventional cohort study was performed from 15 October 2015 to 31 January 2017, including all primiparous women with singletons and noninstrumental vaginal deliveries at six Palestinian hospitals. Intervention 1 (animated instructions on tablets) was conducted in Hospitals 1, 2, 3, and 4. Intervention 2 (bedside hands-on training) was applied in Hospitals 1 and 2 only. Hospitals 5 and 6 did not receive interventions. Differences in episiotomy rates in intervention and nonintervention hospitals were assessed before and after the interventions and presented as p values using chi-square test, and odds ratios (OR) with 95% confidence intervals (CI). Differences in the demographic and obstetric characteristics were presented as p values using the Kruskal-Wallis test. RESULTS: Of 46,709 women, 12,841 were included. The overall episiotomy rate in the intervention hospitals did not change significantly after intervention 1, from 63.1 to 62.1% (OR = 0.96, 95% CI 0.84-1.08), but did so after intervention 2, from 61.1 to 38.1% (OR = 0.39, 95% CI 0.33-0.47). Rates after Intervention 2 changed from 65.0 to 47.3% (OR = 0.52, 95% CI 0.40-0.67) in Hospital 1 and from 39.4 to 25.1% (OR = 0.49, 95% CI 0.35-0.68) in Hospital 2. CONCLUSIONS: Hands-on training of bimanual perineal support during delivery of primiparous women was significantly more effective in reducing episiotomy rates than animated instruction videos alone.

NFATC1 activation by DNA hypomethylation in chronic lymphocytic leukemia correlates with clinical staging and can be inhibited by ibrutinib.

B cell receptor (BCR) signaling is a key for survival of chronic lymphocytic leukemia (CLL) cells, and BCR signaling inhibitors are clinically active. However, relapse and resistance to treatment require novel treatment options. To detect novel candidate therapeutic targets, we performed a genome-wide DNA methylation screen with custom arrays and identified aberrant promoter DNA methylation in 2,192 genes. The transcription factor NFATC1 that is a downstream effector of BCR signaling was among the top hypomethylated genes and was concomitantly transcriptionally upregulated in CLL. Intriguingly, NFATC1 promoter DNA hypomethylation levels were significantly variant in clinical trial cohorts from different disease progression stages and furthermore correlated with Binet disease staging and thymidine kinase levels, strongly suggesting a central role of NFATC1 in CLL development. Functionally, DNA hypomethylation at NFATC1 promoter inversely correlated with RNA levels of NFATC1 and dysregulation correlated with expression of target genes BCL-2, CCND1 and CCR7. The inhibition of the NFAT regulator calcineurin with tacrolimus and cyclosporin A and the BCR signaling inhibitor ibrutinib significantly reduced NFAT activity in leukemic cell lines, and NFAT inhibition resulted in increased apoptosis of primary CLL cells. In summary, our results indicate that the aberrant activation of NFATC1 by DNA hypomethylation and BCR signaling plays a major role in the pathomechanism of CLL.