Toxicity-related antiretroviral drug treatment modifications in individuals starting therapy: a cohort analysis of time patterns, sex, and other risk factors.

BackgroundModifications to combination antiretroviral drug therapy (CART) regimens can occur for a number of reasons, including adverse drug effects. We investigated the frequency of and reasons for antiretroviral drug modifications (ADM) during the first 3 years after initiation of CART, in a closed cohort of CART-naïve adult patients who started treatment in the period 1998-2007 in Croatia.Material and methodsWe calculated differential toxicity rates by the Poisson method. In multivariable analysis, we used a discrete-time regression model for repeated events for the outcome of modification due to drug toxicity.ResultsOf 321 patients who started CART, median age was 40 years, 19% were women, baseline CD4 was <200 cells/mm3 in 71%, and viral load was ≥100 000 copies/mL in 69%. Overall, 220 (68.5%) patients had an ADM; 124 (56%) of these had ≥1 ADM for toxicity reasons. Only 12.7% of individuals starting CART in the period 1998-2002 and 39.4% in the period 2003-2007 remained on the same regimen after 3 years. The following toxicities caused ADM most often: lipoatrophy (22%), gastrointestinal symptoms (20%), and neuropathy (18%). Only 5% of drug changes were due to virologic failure. Female sex (hazard ratio [HR], 2.42 95%; confidence intervals, 1.39-4.24) and older age (HR, 1.42 per every 10 years) were associated with toxicity-related ADM in the first 3 months of a particular CART regimen, but after 3 months of CART they were not.ConclusionsLess toxic and better-tolerated HIV treatment options should be available and used more frequently in Croatia

AMR, stability and higher accuracy

Efforts to achieve better accuracy in numerical relativity have so far focused either on implementing second order accurate adaptive mesh refinement or on defining higher order accurate differences and update schemes. Here, we argue for the combination, that is a higher order accurate adaptive scheme. This combines the power that adaptive gridding techniques provide to resolve fine scales (in addition to a more efficient use of resources) together with the higher accuracy furnished by higher order schemes when the solution is adequately resolved. To define a convenient higher order adaptive mesh refinement scheme, we discuss a few different modifications of the standard, second order accurate approach of Berger and Oliger. Applying each of these methods to a simple model problem, we find these options have unstable modes. However, a novel approach to dealing with the grid boundaries introduced by the adaptivity appears stable and quite promising for the use of high order operators within an adaptive framework

Establishment of LIF-Dependent Human iPS Cells Closely Related to Basic FGF-Dependent Authentic iPS Cells

Human induced pluripotent stem cells (iPSCs) can be divided into a leukemia inhibitory factor (LIF)-dependent naïve type and a basic fibroblast growth factor (bFGF)-dependent primed type. Although the former are more undifferentiated than the latter, they require signal transduction inhibitors and sustained expression of the transgenes used for iPSC production. We used a transcriptionally enhanced version of OCT4 to establish LIF-dependent human iPSCs without the use of inhibitors and sustained transgene expression. These cells belong to the primed type of pluripotent stem cell, similar to bFGF-dependent iPSCs. Thus, the particular cytokine required for iPSC production does not necessarily define stem cell phenotypes as previously thought. It is likely that the bFGF and LIF signaling pathways converge on unidentified OCT4 target genes. These findings suggest that our LIF-dependent human iPSCs could provide a novel model to investigate the role of cytokine signaling in cellular reprogramming

Polygenic burden in focal and generalized epilepsies.

Rare genetic variants can cause epilepsy, and genetic testing has been widely adopted for severe, paediatric-onset epilepsies. The phenotypic consequences of common genetic risk burden for epilepsies and their potential future clinical applications have not yet been determined. Using polygenic risk scores (PRS) from a European-ancestry genome-wide association study in generalized and focal epilepsy, we quantified common genetic burden in patients with generalized epilepsy (GE-PRS) or focal epilepsy (FE-PRS) from two independent non-Finnish European cohorts (Epi25 Consortium, n = 5705; Cleveland Clinic Epilepsy Center, n = 620; both compared to 20 435 controls). One Finnish-ancestry population isolate (Finnish-ancestry Epi25, n = 449; compared to 1559 controls), two European-ancestry biobanks (UK Biobank, n = 383 656; Vanderbilt biorepository, n = 49 494), and one Japanese-ancestry biobank (BioBank Japan, n = 168 680) were used for additional replications. Across 8386 patients with epilepsy and 622 212 population controls, we found and replicated significantly higher GE-PRS in patients with generalized epilepsy of European-ancestry compared to patients with focal epilepsy (Epi25: P = 1.64×10-15; Cleveland: P = 2.85×10-4; Finnish-ancestry Epi25: P = 1.80×10-4) or population controls (Epi25: P = 2.35×10-70; Cleveland: P = 1.43×10-7; Finnish-ancestry Epi25: P = 3.11×10-4; UK Biobank and Vanderbilt biorepository meta-analysis: P = 7.99×10-4). FE-PRS were significantly higher in patients with focal epilepsy compared to controls in the non-Finnish, non-biobank cohorts (Epi25: P = 5.74×10-19; Cleveland: P = 1.69×10-6). European ancestry-derived PRS did not predict generalized epilepsy or focal epilepsy in Japanese-ancestry individuals. Finally, we observed a significant 4.6-fold and a 4.5-fold enrichment of patients with generalized epilepsy compared to controls in the top 0.5% highest GE-PRS of the two non-Finnish European cohorts (Epi25: P = 2.60×10-15; Cleveland: P = 1.39×10-2). We conclude that common variant risk associated with epilepsy is significantly enriched in multiple cohorts of patients with epilepsy compared to controls-in particular for generalized epilepsy. As sample sizes and PRS accuracy continue to increase with further common variant discovery, PRS could complement established clinical biomarkers and augment genetic testing for patient classification, comorbidity research, and potentially targeted treatment

Comparative Effectiveness of Stereo-EEG versus Subdural Grids in Epilepsy Surgery

OBJECTIVE: To compare the outcomes of subdural electrode (SDE) implantations versus stereo-electroencephalography (SEEG), the two predominant methods of intracranial EEG (iEEG) performed in difficult to localize drug-resistant focal epilepsy. METHODS: The Surgical Therapies Commission of the International League Against Epilepsy created an international registry of iEEG patients implanted between 2005-2019 with ≥ 1 year follow-up. We used propensity score matching to control exposure selection bias and generate comparable cohorts. Study endpoints: 1) likelihood of resection after iEEG; 2) seizure-freedom at last follow-up; and 3) complications (composite of either post-operative infection, symptomatic intracranial hemorrhage, or permanent neurologic deficit). RESULTS: Ten study sites from seven countries and three continents contributed 2,012 patients, including 1,468 (73%) eligible for analysis (526 SDE, 942 SEEG) of whom 988 (67%) underwent subsequent resection. Propensity score matching improved covariate balance between exposure groups for all analyses. Propensity-matched patients who underwent SDE had higher odds of subsequent resective surgery (odds ratio OR = 1.4, 95% CI 1.05 - 1.84), and higher odds of complications (OR=2.24, 95% CI 1.34-3.74; unadjusted: 9.6% after SDE vs. 3.3% after SEEG). Odds of seizure-freedom in propensity-matched resected patients were 1.66 times higher (95% CI 1.21, 2.26) for SEEG compared to SDE (unadjusted: 55% seizure-free after SEEG-guided resections vs. 41% after SDE) INTERPRETATION: Compared to SEEG, SDE evaluations are more likely to lead to brain surgery in patients with drug-resistant epilepsy, but have more surgical complications and lower probability of seizure-freedom. This comparative-effectiveness study provides the highest feasible evidence level to guide decisions on iEEG. This article is protected by copyright. All rights reserved

Topography and relationship-specific social touching in individuals displaying body image disturbances

Interpersonal touch is intimately related to the emotional bond between the touch giver and the touch receiver. Which bodily regions we touch in those individuals in our social network is relationship specific. Perception of interpersonal touch is altered in psychiatric disorders characterised by body image disturbances (BIDs). Here, we examined whether the ‘imagined’ experience of social touch in individuals with BIDs is body topography- and relationship-specific. By using an interactive media mobile App, the Virtual Touch Toolkit, high versus low levels of BIDs participants completed heatmaps of full-body virtual avatars, to indicate the body regions they find soothing/unpleasant to be touched by a loved one versus an acquaintance. Self-reports of interoceptive awareness and dysmorphic concerns were also measured. Overall, imagined touch was rated as the most soothing when received from a loved one, and also when this was delivered to ‘social’ body regions. The importance of the social relationship for the imagined tactile interactions was particularly evident for the high levels of BIDs group, with greater problems with interoceptive awareness predicting higher soothing touch ratings when this was received by a loved one. Despite the evidence that imagined bodily contacts between meaningful people is the most pleasant for socially acceptable bodily regions, our findings may suggest a greater sensitivity to relation-specific bodily patterns of social touch particularly in the high level of BIDs group. Heightened interoceptive awareness may also play a key role in this experience of bodily affective contacts. Future research for body-oriented therapy for BIDs is encouraged to systematically probe the efficacy of imagined social touch interaction protocols which use more plausible, ecological, scenarios where touch is delivered by loved ones and to socially acceptable bodily regions

Automated detection of focal cortical dysplasia type II with surface-based magnetic resonance imaging postprocessing and machine learning

Objective Focal cortical dysplasia (FCD) is a major pathology in patients undergoing surgical resection to treat pharmacoresistant epilepsy. Magnetic resonance imaging (MRI) postprocessing methods may provide essential help for detection of FCD. In this study, we utilized surface‐based MRI morphometry and machine learning for automated lesion detection in a mixed cohort of patients with FCD type II from 3 different epilepsy centers. Methods Sixty‐one patients with pharmacoresistant epilepsy and histologically proven FCD type II were included in the study. The patients had been evaluated at 3 different epilepsy centers using 3 different MRI scanners. T1‐volumetric sequence was used for postprocessing. A normal database was constructed with 120 healthy controls. We also included 35 healthy test controls and 15 disease test controls with histologically confirmed hippocampal sclerosis to assess specificity. Features were calculated and incorporated into a nonlinear neural network classifier, which was trained to identify lesional cluster. We optimized the threshold of the output probability map from the classifier by performing receiver operating characteristic (ROC) analyses. Success of detection was defined by overlap between the final cluster and the manual labeling. Performance was evaluated using k‐fold cross‐validation. Results The threshold of 0.9 showed optimal sensitivity of 73.7% and specificity of 90.0%. The area under the curve for the ROC analysis was 0.75, which suggests a discriminative classifier. Sensitivity and specificity were not significantly different for patients from different centers, suggesting robustness of performance. Correct detection rate was significantly lower in patients with initially normal MRI than patients with unequivocally positive MRI. Subgroup analysis showed the size of the training group and normal control database impacted classifier performance. Significance Automated surface‐based MRI morphometry equipped with machine learning showed robust performance across cohorts from different centers and scanners. The proposed method may be a valuable tool to improve FCD detection in presurgical evaluation for patients with pharmacoresistant epilepsy