Early onset of effect following galcanezumab treatment in patients with previous preventive medication failures

Background Galcanezumab is a monoclonal antibody (mAb) that binds calcitonin gene-related peptide (CGRP) and is indicated for the preventive treatment of migraine. Galcanezumab demonstrated early onset of effect in patients with migraine but it is unknown whether the same holds true for patients who have not benefited from multiple prior migraine preventives. Methods Patients with episodic or chronic migraine from a 3-month, randomized, double-blind, placebo-controlled, phase 3b study (CONQUER) who had 2 to 4 migraine preventive medication category failures in the past 10 years were randomized 1:1 to placebo (N = 230) or galcanezumab 120 mg/month (240 mg loading dose; N = 232). In this post-hoc analysis, change from baseline in number of monthly and weekly migraine headache days was assessed. Monthly onset of effect was the earliest month at which significant improvement with galcanezumab compared to placebo was achieved and maintained at all subsequent months. Weekly onset was the initial week at which statistical separation was achieved and maintained at all subsequent weeks during that month. Proportion of patients with migraine headache days in the first week of treatment, and patients achieving ≥50%, ≥75%, and 100% response by month and week were also assessed. Results Galcanezumab-treated patients had a significantly greater reduction in monthly migraine headache days starting at month 1, which remained significant for all subsequent months compared to placebo (all p ≤ 0.0001, month 1 mean change from baseline: placebo − 0.7; galcanezumab − 4.0). Weekly migraine headache days was significantly reduced in galcanezumab-treated patients starting at week 1 and continued for each subsequent week of month 1 compared to placebo (all p < 0.01, week 1 mean change from baseline: placebo − 0.2; galcanezumab − 1.1). A significantly smaller percentage of patients had a migraine headache on the first day after galcanezumab treatment compared to placebo (28.4% vs 39.2%) and at each subsequent day during week 1 (all p < 0.05). A greater proportion of galcanezumab-treated patients achieved ≥50%, ≥75%, and 100% response at months 1–3 (all p < 0.05) and at weeks 1–4 of month 1 compared to placebo (all p < 0.01). Conclusion Galcanezumab showed early onset of effect beginning the day after treatment initiation in patients who had not previously benefited from migraine preventive treatments. Trial registration ClinicalTrials.gov, NCT03559257. Registered 18 June 2018.

Statistical separation of weak gravitational lensing and intrinsic ellipticities based on galaxy colour information

ABSTRACT Intrinsic alignments of galaxies are recognized as one of the most important systematic in weak lensing surveys on small angular scales. In this paper, we investigate ellipticity correlation functions that are measured separately on elliptical and spiral galaxies, for which we assume the generic alignment mechanisms based on tidal shearing and tidal torquing, respectively. Including morphological information allows to find linear combinations of measured ellipticity correlation functions that suppress the gravitational lensing signal completely or which show a strongly boosted gravitational lensing signal relative to intrinsic alignments. Specifically, we find that (i) intrinsic alignment spectra can be measured in a model-independent way at a significance of Σ ≃ 60 with a wide-angle tomographic survey such as Euclid’s, (ii) the underlying intrinsic alignment model parameters can be determined at per cent-level precision, (iii) this measurement is not impeded by misclassifying galaxies and assuming a wrong alignment model, (iv) parameter estimation from a cleaned weak lensing spectrum is possible with almost no bias, and (v) the misclassification would not strongly impact parameter estimation from the boosted weak lensing spectrum.

Being accurate about verbal credibility assessment

Purpose: Verbal credibility assessments examine language to discern lie from the truth. These tests are used for the scientific study of the language of lies in US Presidential candidates and fraudulent scientists, but also in criminal proceedings for evaluating allegations of child sexual abuse. The dominant approach in psycholegal deception research to date (used in 81% of recent studies that report on accuracy) to estimate the accuracy of a method is to find the optimal statistical separation between lies and truths in a single dataset. However, this method lacks safeguards against accuracy overestimation. Method &amp; Results: A simulation study and empirical data show that this procedure produces overoptimistic accuracy rates that, especially for small sample size studies typical of this field, yield misleading conclusions up to the point that a non-diagnostic tool can be shown to be a valid one. Cross-validation is a cheap and easy remedy to this problem.Conclusions: We propose a set of guidelines to make the psycholegal research meet highest standards and encourage researchers to be more accurate about accuracy and to conduct proper validation when reporting accuracy rates.

Slicing: a sustainable approach to the analysis of long-term biobanks

The longitudinal study of populations is a core tool for understanding ecological and evolutionary processes. These studies typically collect samples over individual lifetimes and across multiple generations, building up a continuously growing biobank from which samples are then analysed in clusters over time in the laboratory. To ensure data are comparable among clusters we need to account for among-cluster variation and confounding variables, yet this is often ignored. The commonly used approaches in structuring samples for analysis, sequential and randomisation, generate bias due to non-independence between their time of collection and cluster. We propose a new sample selection strategy, slicing, specifically designed to statistically account for this bias. Slicing would, however, be suboptimal if aggregating longitudinal samples of the same individual within a single batch reduces measurement error and thereby increases statistical power to detect within-individual effects, a notion we challenge using simulations. Our slicing approach, whereby recently and previously collected samples are analysed in a cluster together, enables statistical separation of collection time and cluster effects through appropriate mixed models. Additionally, we recommend the use of internal controls (reference samples) to further assess among-cluster variation. Our simulations show similar precision and higher statistical power to detect cohort, within- and between-individual effects when samples are sliced across batches, compared with strategies that aggregate longitudinal samples or use randomised allocation. While the best approach to analysing long-term datasets depends on the structure of the data and questions of interest, it is vital to account for among-cluster and batch variation. This can be achieved through mixed models and appropriate sample selection strategies. Our slicing approach is simple to apply and creates the necessary statistical independence of batch and cluster from environmental or biological variables of interest. Crucially, it allows subsequent samples to be added in later analyses without completely confounding them with cluster. Our approach maximises the value of every sample, as each will optimally contribute to unbiased statistical inference from the data. Slicing therefore has the potential to maximise the power of growing biobanks to address important ecological, epidemiological and evolutionary questions.

Functional and topological diversity of LOV domain photoreceptors

Light–oxygen–voltage sensitive (LOV) flavoproteins are ubiquitous photoreceptors that mediate responses to environmental cues. Photosensory inputs are transduced into signaling outputs via structural rearrangements in sensor domains that consequently modulate the activity of an effector domain or multidomain clusters. Establishing the diversity in effector function and sensor–effector topology will inform what signaling mechanisms govern light-responsive behaviors across multiple kingdoms of life and how these signals are transduced. Here, we report the bioinformatics identification of over 6,700 candidate LOV domains (including over 4,000 previously unidentified sequences from plants and protists), and insights from their annotations for ontological function and structural arrangements. Motif analysis identified the sensors from ∼42 million ORFs, with strong statistical separation from other flavoproteins and non-LOV members of the structurally related Per-aryl hydrocarbon receptor nuclear translocator (ARNT)-Sim family. Conserved-domain analysis determined putative light-regulated function and multidomain topologies. We found that for certain effectors, sensor–effector linker length is discretized based on both phylogeny and the preservation of α-helical heptad repeats within an extended coiled-coil linker structure. This finding suggests that preserving sensor–effector orientation is a key determinant of linker length, in addition to ancestry, in LOV signaling structure–function. We found a surprisingly high prevalence of effectors with functions previously thought to be rare among LOV proteins, such as regulators of G protein signaling, and discovered several previously unidentified effectors, such as lipases. This work highlights the value of applying genomic and transcriptomic technologies to diverse organisms to capture the structural and functional variation in photosensory proteins that are vastly important in adaptation, photobiology, and optogenetics.