Global and national trends, gaps, and opportunities in documenting and monitoring species distributions.

Conserving and managing biodiversity in the face of ongoing global change requires sufficient evidence to assess status and trends of species distributions. Here, we propose novel indicators of biodiversity data coverage and sampling effectiveness and analyze national trajectories in closing spatiotemporal knowledge gaps for terrestrial vertebrates (1950 to 2019). Despite a rapid rise in data coverage, particularly in the last 2 decades, strong geographic and taxonomic biases persist. For some taxa and regions, a tremendous growth in records failed to directly translate into newfound knowledge due to a sharp decline in sampling effectiveness. However, we found that a nation's coverage was stronger for species for which it holds greater stewardship. As countries under the post-2020 Global Biodiversity Framework renew their commitments to an improved, rigorous biodiversity knowledge base, our findings highlight opportunities for international collaboration to close critical information gaps.

Magnetic Resonance Imaging Basics.

In this chapter, we will discuss the basic principles of signal generation and image formation in magnetic resonance imaging (MRI). We will start with a description of nuclear magnetic resonance (NMR) phenomenon and then gradually arrive at the mathematical expressions for MRI signal in spatial domain and k-space domain. Then we describe the image reconstruction methods typically used in MRI, the signal-to-noise ratio calculation methods in MRI, and common MR image formats. A key focus of the contents of this chapter is on the formation of phase images in MRI. We do not intend to provide a comprehensive overview of MRI. Instead, the contents are intended for readers interested in performing research in electromagnetic properties mapping using MRI. Nevertheless, considering the generality of the contents, any reader interested in developing a quick understanding of the physical and mathematical background of MRI can find this chapter helpful.

Brain Perfusion, Regional Volumes, and Cognitive Function in Human Immunodeficiency Virus-positive Patients Treated With Protease Inhibitor Monotherapy.

BACKGROUND: Protease inhibitor monotherapy (PIM) for human immunodeficiency virus (HIV) may exert suboptimal viral control in the central nervous system. We determined whether cerebral blood flow (CBF) and regional brain volumes were associated with PIM, and whether specific cognitive domains were associated with imaging biomarkers. METHODS: Cognitive assessments and brain magnetic resonance imaging were performed after the final visit of a randomized HIV-treatment strategy trial. Participants were virologically suppressed on triple therapy at trial entry and followed for 3-5 years. We studied 37 patients randomized to ongoing triple therapy and 39 randomized to PIM. Resting CBF and normalized volumes were calculated for brain regions of interest, and correlated with treatment strategy and neuropsychological performance. RESULTS: Mean age was 48.1 years (standard deviation 8.6 years), 63 male (83%), and 64 white (84%). Participants had median 8.1 years (interquartile range 6.4, 10.8) of antiretroviral therapy experience and CD4+ counts of median 640 cells/mm3 (interquartile range 490, 780). We found no difference between treatment arms in CBF or regional volumes. Regardless of treatment arm, poorer fine motor performance correlated with lower CBF in the caudate nucleus (P = .01), thalamus (P = .04), frontal cortex (P = .01), occipital cortex (P = .004), and cingulate cortex (P = .02), and was associated with smaller supratentorial white matter volume (decrease of 0.16 in Z-score per -1% of intracranial volume, 95% confidence interval 0.02-0.29; P = .023). CONCLUSIONS: PIM does not confer an additional risk of neurological injury compared with triple therapy. There were correlations between fine motor impairment, grey matter hypoperfusion, and white matter volume loss. CLINICAL TRIALS REGISTRATION: ISRCTN-04857074.

Dual IL-17A and IL-17F neutralisation by bimekizumab in psoriatic arthritis: evidence from preclinical experiments and a randomised placebo-controlled clinical trial that IL-17F contributes to human chronic tissue inflammation.

OBJECTIVE: Interleukin (IL)-17A has emerged as pivotal in driving tissue pathology in immune-mediated inflammatory diseases. The role of IL-17F, sharing 50% sequence homology and overlapping biological function, remains less clear. We hypothesised that IL-17F, together with IL-17A, contributes to chronic tissue inflammation, and that dual neutralisation may lead to more profound suppression of inflammation than inhibition of IL-17A alone. METHODS: Preclinical experiments assessed the role of IL-17A and IL-17F in tissue inflammation using disease-relevant human cells. A placebo-controlled proof-of-concept (PoC) clinical trial randomised patients with psoriatic arthritis (PsA) to bimekizumab (n=39) or placebo (n=14). Safety, pharmacokinetics and clinical efficacy of multiple doses (weeks 0, 3, 6 (240 mg/160 mg/160 mg; 80 mg/40 mg/40 mg; 160 mg/80 mg/80 mg and 560 mg/320 mg/320 mg)) of bimekizumab, a humanised monoclonal IgG1 antibody neutralising both IL-17A and IL-17F, were investigated. RESULTS: IL-17F induced qualitatively similar inflammatory responses to IL-17A in skin and joint cells. Neutralisation of IL-17A and IL-17F with bimekizumab more effectively suppressed in vitro cytokine responses and neutrophil chemotaxis than inhibition of IL-17A or IL-17F alone. The PoC trial met both prespecified efficacy success criteria and showed rapid, profound responses in both joint and skin (pooled top three doses vs placebo at week 8: American College of Rheumatology 20% response criteria 80.0% vs 16.7% (posterior probability >99%); Psoriasis Area and Severity Index 100% response criteria 86.7% vs 0%), sustained to week 20, without unexpected safety signals. CONCLUSIONS: These data support IL-17F as a key driver of human chronic tissue inflammation and the rationale for dual neutralisation of IL-17A and IL-17F in PsA and related conditions. TRIAL REGISTRATION NUMBER: NCT02141763; Results.

Diagnostic classification of arterial spin labeling and structural MRI in presenile early stage dementia.

Because hypoperfusion of brain tissue precedes atrophy in dementia, the detection of dementia may be advanced by the use of perfusion information. Such information can be obtained noninvasively with arterial spin labeling (ASL), a relatively new MR technique quantifying cerebral blood flow (CBF). Using ASL and structural MRI, we evaluated diagnostic classification in 32 prospectively included presenile early stage dementia patients and 32 healthy controls. Patients were suspected of Alzheimer's disease (AD) or frontotemporal dementia. Classification was based on CBF as perfusion marker, gray matter (GM) volume as atrophy marker, and their combination. These markers were each examined using six feature extraction methods: a voxel-wise method and a region of interest (ROI)-wise approach using five ROI-sets in the GM. These ROI-sets ranged in number from 72 brain regions to a single ROI for the entire supratentorial brain. Classification was performed with a linear support vector machine classifier. For validation of the classification method on the basis of GM features, a reference dataset from the AD Neuroimaging Initiative database was used consisting of AD patients and healthy controls. In our early stage dementia population, the voxelwise feature-extraction approach achieved more accurate results (area under the curve (AUC) range = 86 - 91%) than all other approaches (AUC = 57 - 84%). Used in isolation, CBF quantified with ASL was a good diagnostic marker for dementia. However, our findings indicated only little added diagnostic value when combining ASL with the structural MRI data (AUC = 91%), which did not significantly improve over accuracy of structural MRI atrophy marker by itself.

Listening to animal behavior to understand changing ecosystems.

Interpreting sound gives powerful insight into the health of ecosystems. Beyond detecting the presence of wildlife, bioacoustic signals can reveal their behavior. However, behavioral bioacoustic information is underused because identifying the function and context of animals' sounds remains challenging. A growing acoustic toolbox is allowing researchers to begin decoding bioacoustic signals by linking individual and population-level sensing. Yet, studies integrating acoustic tools for behavioral insight across levels of biological organization remain scarce. We aim to catalyze the emerging field of behavioral bioacoustics by synthesizing recent successes and rising analytical, logistical, and ethical challenges. Because behavior typically represents animals' first response to environmental change, we posit that behavioral bioacoustics will provide theoretical and applied insights into animals' adaptations to global change.

Population Pharmacokinetics and Exposure-Response for Dapirolizumab Pegol From a Phase 2b Trial in Patients With Systemic Lupus Erythematosus.

Systemic lupus erythematosus (SLE) is a systemic, autoimmune disease characterized by chronic inflammation and organ damage. Dapirolizumab pegol inhibits CD40 ligand (CD40L) and is currently undergoing phase 3 trials for the treatment of SLE. To describe the pharmacokinetic characteristics of dapirolizumab pegol and the relationship between exposure and probability of achieving a British Isles Lupus Assessment Group-based Composite Lupus Assessment (BICLA) response, a population pharmacokinetic (popPK) model and an exposure-response model were developed, based on results of the phase 2b trial (RISE; NCT02804763) of dapirolizumab pegol in SLE. Dapirolizumab pegol pharmacokinetics were found to be dose proportional and well described by a 2-compartment model with first-order elimination from the central compartment. In the popPK model, body weight was the only significant covariate. The average concentration of dapirolizumab pegol, derived from the popPK model, was incorporated into the exposure-response model. Overall, the exposure-response model showed that treatment with dapirolizumab pegol increased the probability of transitioning from BICLA "Nonresponder" to "Responder." No significant covariates on BICLA responder status were identified. Notably, the half maximal effective concentration was greater for the transition from "Responder" to "Nonresponder" (150 µg/mL) than the transition from "Nonresponder" to "Responder" (12 µg/mL), indicating that sustained dapirolizumab pegol concentrations may be required to maintain BICLA response. In conclusion, dapirolizumab pegol pharmacokinetics were as expected for a PEGylated molecule and results from the exposure-response model indicate that a favorable dapirolizumab pegol effect was identified for both BICLA "Nonresponder" to "Responder" and "Responder" to "Nonresponder" transition probabilities.

Camera trapping expands the view into global biodiversity and its change.

Growing threats to biodiversity demand timely, detailed information on species occurrence, diversity and abundance at large scales. Camera traps (CTs), combined with computer vision models, provide an efficient method to survey species of certain taxa with high spatio-temporal resolution. We test the potential of CTs to close biodiversity knowledge gaps by comparing CT records of terrestrial mammals and birds from the recently released Wildlife Insights platform to publicly available occurrences from many observation types in the Global Biodiversity Information Facility. In locations with CTs, we found they sampled a greater number of days (mean = 133 versus 57 days) and documented additional species (mean increase of 1% of expected mammals). For species with CT data, we found CTs provided novel documentation of their ranges (93% of mammals and 48% of birds). Countries with the largest boost in data coverage were in the historically underrepresented southern hemisphere. Although embargoes increase data providers' willingness to share data, they cause a lag in data availability. Our work shows that the continued collection and mobilization of CT data, especially when combined with data sharing that supports attribution and privacy, has the potential to offer a critical lens into biodiversity. This article is part of the theme issue 'Detecting and attributing the causes of biodiversity change: needs, gaps and solutions'.

A vision for incorporating human mobility in the study of human-wildlife interactions.

As human activities increasingly shape land- and seascapes, understanding human-wildlife interactions is imperative for preserving biodiversity. Habitats are impacted not only by static modifications, such as roads, buildings and other infrastructure, but also by the dynamic movement of people and their vehicles occurring over shorter time scales. Although there is increasing realization that both components of human activity substantially affect wildlife, capturing more dynamic processes in ecological studies has proved challenging. Here we propose a conceptual framework for developing a 'dynamic human footprint' that explicitly incorporates human mobility, providing a key link between anthropogenic stressors and ecological impacts across spatiotemporal scales. Specifically, the dynamic human footprint integrates a range of metrics to fully acknowledge the time-varying nature of human activities and to enable scale-appropriate assessments of their impacts on wildlife behaviour, demography and distributions. We review existing terrestrial and marine human-mobility data products and provide a roadmap for how these could be integrated and extended to enable more comprehensive analyses of human impacts on biodiversity in the Anthropocene.

Pharmacokinetic-pharmacodynamic modelling of the anti-FcRn monoclonal antibody rozanolixizumab: Translation from preclinical stages to the clinic.

Rozanolixizumab is a fully humanized high-affinity anti-human neonatal Fc receptor (FcRn) monoclonal antibody (mAb) that accelerates the removal of circulating immunoglobulin G (IgG), including pathogenic IgG autoantibodies, via the natural lysosomal degradation pathway. The aim of this study was to develop a pharmacokinetic/pharmacodynamic (PK/PD) model characterizing the effect of rozanolixizumab on IgG levels in cynomolgus monkeys, translate it into humans to support the first-in-human (FIH) rozanolixizumab clinical trial study design, and, ultimately, develop a PK/PD model in humans. Simulations from the preclinical model were performed to predict IgG responses in humans and select clinically relevant doses in the FIH study. Good alignment was observed between predicted and observed reductions in IgG, which increased with increasing dose in the FIH study. The model successfully described the PK of the 4 and 7 mg/kg intravenous (i.v.) dose groups, although the PKs were underpredicted for the 1 mg/kg i.v. dose group. Updating the model with subsequent human data identified parameters that deviated from preclinical assumptions. The updated PK/PD model was able to effectively characterize the PK FcRn-IgG nonlinear system in response to rozanolixizumab in the FIH data.

Automated post-operative brain tumour segmentation: A deep learning model based on transfer learning from pre-operative images.

Automated brain tumour segmentation from post-operative images is a clinically relevant yet challenging problem. In this study, an automated method for segmenting brain tumour into its subregions has been developed. The dataset consists of multimodal post-operative brain scans (T1 MRI, post-Gadolinium T1 MRI, and T2-FLAIR images) of 15 patients who were treated with post-operative radiation therapy, along with manual annotations of their tumour subregions. A 3D densely-connected U-net was developed for segmentation of brain tumour regions and extensive experiments were conducted to enhance model accuracy. A model was initially developed using the publicly available BraTS dataset consisting of pre-operative brain scans. This model achieved Dice Scores of 0.90, 0.83 and 0.78 for predicting whole tumour, tumour core, and enhancing tumour subregions when tested on BraTS20 blind validation dataset. The acquired knowledge from BraTS was then transferred to the local dataset. For augmentation purpose, the local dataset was registered to a dataset of MRI brain scans of healthy subjects. To improve the robustness of the model and enhance its accuracy, ensemble learning was used to combine the outputs of all the trained models. Even though the size of the dataset is very small, the final model can segment brain tumours with a high Dice Score of 0.83, 0.77 and 0.60 for whole tumour, tumour core and enhancing core respectively.

pH dependent molecular self-assembly of octaphosphonate porphyrin of nanoscale dimensions: nanosphere and nanorod aggregates.

Self-assembled nanostructures of zwitterionic octaphosphanatoporphyrin 1, of either nanoparticles or nanorods, depending on small changes in the pH, is demonstrated based on the J-aggregates. Porphyrin 1 self-assembled into nanosphere aggregates with a diameter of about 70-80 nm in the pH range 5-7, and nanorod aggregates were observed at pH 8.5. Hydrogen bonding, π-π stacking and hydrophilic interactions play important roles in the formation of this nanostructure morphology. Nanostructures were characterized by UV/Vis absorbance, fluorescence, atomic force microscopy (AFM) and transmission electron microscopy (TEM). This interesting pH dependent self-assembly phenomenon could provide a basis for development of novel biomaterials.

Automated Brain Tumor Segmentation Using Multimodal Brain Scans: A Survey Based on Models Submitted to the BraTS 2012-2018 Challenges.

Reliable brain tumor segmentation is essential for accurate diagnosis and treatment planning. Since manual segmentation of brain tumors is a highly time-consuming, expensive and subjective task, practical automated methods for this purpose are greatly appreciated. But since brain tumors are highly heterogeneous in terms of location, shape, and size, developing automatic segmentation methods has remained a challenging task over decades. This paper aims to review the evolution of automated models for brain tumor segmentation using multimodal MR images. In order to be able to make a just comparison between different methods, the proposed models are studied for the most famous benchmark for brain tumor segmentation, namely the BraTS challenge [1]. The BraTS 2012-2018 challenges and the state-of-the-art automated models employed each year are analysed. The changing trend of these automated methods since 2012 are studied and the main parameters that affect the performance of different models are analysed.

Bimekizumab, a Novel Humanized IgG1 Antibody That Neutralizes Both IL-17A and IL-17F.

Interleukin (IL)-17A is a key driver of inflammation and the principal target of anti-IL-17 therapeutic monoclonal antibodies. IL-17A, and its structurally similar family member IL-17F, have been shown to be functionally dysregulated in certain human immune-mediated inflammatory diseases such as psoriasis, psoriatic arthritis, and axial spondyloarthritis. Given the overlapping biology of these two cytokines, we postulated that dual neutralization of IL-17A and IL-17F may provide a greater depth of clinical response in IL-17-mediated diseases than IL-17A inhibition alone. We identified 496.g1, a humanized antibody with strong affinity for IL-17A but poor affinity for IL-17F. Affinity maturation of 496.g1 to 496.g3 greatly enhanced the affinity of the Fab fragment for IL-17F while retaining strong binding to IL-17A. As an IgG1, the affinity for IL-17A and IL-17F was 3.2 pM and 23 pM, respectively. Comparison of 496.g3 IgG1 with the commercially available anti-IL-17A monoclonal antibodies ixekizumab and secukinumab, by surface plasmon resonance and in a human in vitro IL-17A functional assay, showed that 496.g3 and ixekizumab display equivalent affinity for IL-17A, and that both antibodies are markedly more potent than secukinumab. In contrast to ixekizumab and secukinumab, 496.g3 exhibited the unique feature of also being able to neutralize the biological activity of IL-17F. Therefore, antibody 496.g3 was selected for clinical development for its ability to neutralize the biologic function of both IL-17A and IL-17F and was renamed bimekizumab (formerly UCB4940). Early clinical data in patients with psoriasis, in those with psoriatic arthritis, and from the Phase 2 studies in psoriasis, psoriatic arthritis, and ankylosing spondylitis, are encouraging and support the targeted approach of dual neutralization of IL-17A and IL-17F. Taken together, these findings provide the rationale for the continued clinical evaluation of bimekizumab in patients with immune-mediated inflammatory diseases.

Ecological insights from three decades of animal movement tracking across a changing Arctic.

The Arctic is entering a new ecological state, with alarming consequences for humanity. Animal-borne sensors offer a window into these changes. Although substantial animal tracking data from the Arctic and subarctic exist, most are difficult to discover and access. Here, we present the new Arctic Animal Movement Archive (AAMA), a growing collection of more than 200 standardized terrestrial and marine animal tracking studies from 1991 to the present. The AAMA supports public data discovery, preserves fundamental baseline data for the future, and facilitates efficient, collaborative data analysis. With AAMA-based case studies, we document climatic influences on the migration phenology of eagles, geographic differences in the adaptive response of caribou reproductive phenology to climate change, and species-specific changes in terrestrial mammal movement rates in response to increasing temperature.

Lamotrigine does not prolong QTc in a thorough QT/QTc study in healthy subjects.

AIM: To characterize the effects of lamotrigine on QT interval in healthy subjects. METHODS: Healthy subjects received a single oral dose of moxifloxacin (400 mg) or placebo in crossover design, followed by a dose-escalating regimen of lamotrigine (n = 76) over a 77-day period, or matched placebo (n = 76). Blood samples were taken for determination of moxifloxacin and lamotrigine concentrations and digital 12-lead ECGs were recorded. The relationships between individual QT values and respective individual moxifloxacin or lamotrigine concentrations were explored using population pharmacokinetic-pharmacodynamic (PK-PD) modelling. RESULTS: Moxifloxacin was associated with a maximum mean increase from baseline in QTcF of 14.81 ms [90% confidence interval (CI) 13.50, 16.11] 2.5 h after dosing. Steady-state exposure to lamotrigine (50, 150 or 200 mg b.d.) was not associated with an increase in QTc interval. Small reductions in QTcF (maximum mean difference from placebo -7.48 ms, 90% CI -10.49, -4.46) and small increases in heart rate (maximum mean difference from placebo 5.94 bpm, 90% CI 3.81, 8.06) were observed with lamotrigine 200 mg b.d. vs. placebo. No effect of lamotrigine on QRS duration or blood pressure was observed. No outliers with QTcF > 450 ms, or with an increase from baseline of >60 ms were observed in the lamotrigine group. PK-PD modelling indicated statistically significant decreases in individually corrected QT intervals for lamotrigine and statistically significant increases in individually corrected QT intervals for moxifloxacin over the concentration ranges studied. CONCLUSIONS: Therapeutic doses of lamotrigine (50-200 mg b.d.) were not associated with QT prolongation in healthy subjects.

Eavesdropping on the Arctic: Automated bioacoustics reveal dynamics in songbird breeding phenology.

Bioacoustic networks could vastly expand the coverage of wildlife monitoring to complement satellite observations of climate and vegetation. This approach would enable global-scale understanding of how climate change influences phenomena such as migratory timing of avian species. The enormous data sets that autonomous recorders typically generate demand automated analyses that remain largely undeveloped. We devised automated signal processing and machine learning approaches to estimate dates on which songbird communities arrived at arctic breeding grounds. Acoustically estimated dates agreed well with those determined via traditional surveys and were strongly related to the landscape's snow-free dates. We found that environmental conditions heavily influenced daily variation in songbird vocal activity, especially before egg laying. Our novel approaches demonstrate that variation in avian migratory arrival can be detected autonomously. Large-scale deployment of this innovation in wildlife monitoring would enable the coverage necessary to assess and forecast changes in bird migration in the face of climate change.

Population pharmacokinetic analysis of certolizumab pegol in patients with Crohn's disease.

Certolizumab pegol (CZP), an anti-tumor necrosis factor α agent, is an effective therapy for Crohn's disease (CD). A population pharmacokinetic (PK) analysis of subcutaneously administered CZP was performed using data from 2157 CD patients from 9 separate studies. The aim was to determine which covariates influence the disposition of CZP. The final CZP population PK model consisted of a baseline, first-order absorption, and 1-compartment disposition. CZP antibodies were treated as a structural model covariate and caused apparent clearance (CL/F) to increase from 0.685 to 2.74 L/day. Body surface area (BSA) influenced both CL/F and apparent volume of distribution (V/F) in a linear fashion; both parameters increased by more than 53% and 49%, respectively, across the range of BSA measurements in the data. Albumin influenced CZP CL/F in a nonlinear fashion; CL/F decreased from 1.05 to 0.613 L/day with increasing albumin concentrations in antibody-negative patients. C-reactive protein (CRP) had a borderline influence and CL/F increased by more than 20% across the range of CRP measurements in the data set. Race had a minor influence on V/F. The determined covariates' impact on CZP disposition may be of clinical utility in CZP therapy of CD patients when the PK/pharmacodynamic relationship becomes available.

Safety and pharmacokinetics of olokizumab, an anti-IL-6 monoclonal antibody, administered to healthy male volunteers: A randomized phase I study.

Interleukin-6 (IL-6) is implicated in the pathophysiology of several inflammatory conditions. Olokizumab, a humanized anti-IL-6 monoclonal antibody, selectively blocks the final assembly of the IL-6 signaling complex. A randomized, double-blind, placebo-controlled, phase I dose-escalation study assessed the safety and tolerability of escalating single doses of olokizumab administered intravenously (iv) or subcutaneously (sc) to 67 healthy male volunteers. The pharmacokinetics, pharmacodynamics and immunogenicity of olokizumab were also assessed. Olokizumab was tolerated at doses up to 3.0 mg/kg sc and 10.0 mg/kg iv; the maximum tolerated dose was not reached. No serious adverse events or withdrawals as a result of treatment-emergent adverse events were reported. Pharmacokinetic analysis showed that both maximum serum concentration and area under the concentration-time curve increased linearly with increasing dose. Mean terminal half-life was 31.5 days (standard deviation 12.4 days). The bioavailability of the sc doses ranged from 84.2% to 92.5%. Rapid decreases in C-reactive protein concentrations were observed, with no dose dependency.