Climate oscillation and the invasion of alien species influence the oceanic distribution of seabirds

Spatial and temporal distribution of seabird transiting and foraging at sea is an important consideration for marine conservation planning. Using at-sea observations of seabirds (n = 317), collected during the breeding season from 2012 to 2016, we built boosted regression tree (BRT) models to identify relationships between numerically dominant seabird species (red-footed booby, brown noddy, white tern, and wedge-tailed shearwater), geomorphology, oceanographic variability, and climate oscillation in the Chagos Archipelago. We documented positive relationships between red-footed booby and wedge-tailed shearwater abundance with the strength in the Indian Ocean Dipole, as represented by the Dipole Mode Index (6.7% and 23.7% contribution, respectively). The abundance of red-footed boobies, brown noddies, and white terns declined abruptly with greater distance to island (17.6%, 34.1%, and 41.1% contribution, respectively). We further quantified the effects of proximity to rat-free and rat-invaded islands on seabird distribution at sea and identified breaking point distribution thresholds. We detected areas of increased abundance at sea and habitat use-age under a scenario where rats are eradicated from invaded nearby islands and recolonized by seabirds. Following rat eradication, abundance at sea of red-footed booby, brown noddy, and white terns increased by 14%, 17%, and 3%, respectively, with no important increase detected for shearwaters. Our results have implication for seabird conservation and island restoration. Climate oscillations may cause shifts in seabird distribution, possibly through changes in regional productivity and prey distribution. Invasive species eradications and subsequent island recolonization can lead to greater access for seabirds to areas at sea, due to increased foraging or transiting through, potentially leading to distribution gains and increased competition. Our approach predicting distribution after successful eradications enables anticipatory threat mitigation in these areas, minimizing competition between colonies and thereby maximizing the risk of success and the conservation impact of eradication programs

Lab-based X-ray micro-computed tomography coupled with machine-learning segmentation to investigate phosphoric acid leaching in high-temperature polymer electrolyte fuel cells

A machine-learning approach is used to segment 14 X-ray computed-tomography datasets acquired by lab-based scanning of laser-milled, high-temperature polymer electrolyte fuel cell samples mounted in a 3D-printed sample holder. Two modes of operation, one with constant current load and the other with current cycling, are explored and their impact on microstructural change is correlated with electrochemical performance degradation. Constant-current testing shows the overall quantity of phosphoric acid in the gas diffusion layers is effectively unchanged between 50 and 100 h of operation but that inter-electrode distribution becomes less uniform. Current-cycling tests reveal similar quantities of phosphoric acid but a different intra-electrode distribution. Membrane swelling appears more pronounced after current-cycling tests and in both cases, significant catalyst layer migration is observed. The present analysis provides a lab-based approach to monitoring microstructural degradation in high-temperature polymer electrolyte fuel cells and provides a more accessible and more statistically robust platform for assessing the impact of phosphoric acid mitigation strategies

A Study of Archiving Strategies in Multi-Objective PSO for Molecular Docking

Molecular docking is a complex optimization problem aimed at predicting the position of a ligand molecule in the active site of a receptor with the lowest binding energy. This problem can be formulated as a bi-objective optimization problem by minimizing the binding energy and the Root Mean Square Deviation (RMSD) difference in the coordinates of ligands. In this context, the SMPSO multi-objective swarm-intelligence algorithm has shown a remarkable performance. SMPSO is characterized by having an external archive used to store the non-dominated solutions and also as the basis of the leader selection strategy. In this paper, we analyze several SMPSO variants based on different archiving strategies in the scope of a benchmark of molecular docking instances. Our study reveals that the SMPSOhv, which uses an hypervolume contribution based archive, shows the overall best performance.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Clinical Implications of Complex Pharmacokinetics for Daratumumab Dose Regimen in Patients With Relapsed/Refractory Multiple Myeloma

New therapeutic strategies are urgently needed to improve clinical outcomes in patients with multiple myeloma (MM). Daratumumab is a first‐in‐class, CD38 human immunoglobulin G1κ monoclonal antibody approved for treatment of relapsed or refractory MM. Identification of an appropriate dose regimen for daratumumab is challenging due to its target‐mediated drug disposition, leading to time‐ and concentration‐dependent pharmacokinetics. We describe a thorough evaluation of the recommended dose regimen for daratumumab in patients with relapsed or refractory MM

Prevalence and Incidence of Parkinson\u27s Disease in Latin America: A Meta-Analysis

\ua9 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. Background: Parkinson\u27s disease (PD) is a rapidly growing neurodegenerative disorder, but up-to-date epidemiological data are lacking in Latin America. We sought to estimate the prevalence and incidence of PD and parkinsonism in Latin America. Methods: We searched Medline, Embase, Scopus, Web of Science, Scientific Electronic Library Online, and Literatura Latino-Americana e do Caribe em Ci\ueancias da Sa\ufade or the Latin American and Caribbean Health Science Literature databases for epidemiological studies reporting the prevalence or incidence of PD or parkinsonism in Latin America from their inception to 2022. Quality of studies was assessed using the Joanna Briggs Institute (JBI) Critical Appraisal Checklist. Data were pooled via random-effects meta-analysis and analyzed by data source (cohort studies or administrative databases), sex, and age group. Significant differences between groups were determined by meta-regression. Results: Eighteen studies from 13 Latin American countries were included in the review. Meta-analyses of 17 studies (nearly 4 million participants) found a prevalence of 472 (95% CI, 271–820) per 100,000 and three studies an incidence of 31 (95% CI, 23–40) per 100,000 person-years for PD; and seven studies found a prevalence of 4300 (95% CI, 1863–9613) per 100,000 for parkinsonism. The prevalence of PD differed by data source (cohort studies, 733 [95% CI, 427–1255] vs. administrative databases. 114 [95% CI, 63–209] per 100,000, P < 0.01), age group (P < 0.01), but not sex (P = 0.73). PD prevalence in ≥60 years also differed significantly by data source (cohort studies. 1229 [95% CI, 741–2032] vs. administrative databases, 593 [95% CI, 480–733] per 100,000, P < 0.01). Similar patterns were observed for parkinsonism. Conclusions: The overall prevalence and incidence of PD in Latin America were estimated. PD prevalence differed significantly by the data source and age, but not sex. \ua9 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society

Fluoxetine: a case history of its discovery and preclinical development

Introduction: Depression is a multifactorial mood disorder with a high prevalence worldwide. Until now, treatments for depression have focused on the inhibition of monoaminergic reuptake sites, which augment the bioavailability of monoamines in the CNS. Advances in drug discovery have widened the therapeutic options with the synthesis of so-called selective serotonin reuptake inhibitors (SSRIs), such as fluoxetine. Areas covered: The aim of this case history is to describe and discuss the pharmacokinetic and pharmacodynamic profiles of fluoxetine, including its acute effects and the adaptive changes induced after long-term treatment. Furthermore, the authors review the effect of fluoxetine on neuroplasticity and adult neurogenesis. In addition, the article summarises the preclinical behavioural data available on fluoxetine’s effects on depressive-like behaviour, anxiety and cognition as well as its effects on other diseases. Finally, the article describes the seminal studies validating the antidepressant effects of fluoxetine. Expert opinion: Fluoxetine is the first selective SSRI that has a recognised clinical efficacy and safety profile. Since its discovery, other molecules that mimic its mechanism of action have been developed, commencing a new age in the treatment of depression. Fluoxetine has also demonstrated utility in the treatment of other disorders for which its prescription has now been approved

Applications of Direct Injection Soft Chemical Ionisation-Mass Spectrometry for the Detection of Pre-blast Smokeless Powder Organic Additives

Analysis of smokeless powders is of interest from forensics and security perspectives. This article reports the detection of smokeless powder organic additives (in their pre-detonation condition), namely the stabiliser diphenylamine and its derivatives 2-nitrodiphenylamine and 4-nitrodiphenylamine, and the additives (used both as stabilisers and plasticisers) methyl centralite and ethyl centralite, by means of swab sampling followed by thermal desorption and direct injection soft chemical ionisation-mass spectrometry. Investigations on the product ions resulting from the reactions of the reagent ions H3O+ and O2+ with additives as a function of reduced electric field are reported. The method was comprehensively evaluated in terms of linearity, sensitivity and precision. For H3O+, the limits of detection (LoD) are in the range of 41-88 pg of additive, for which the accuracy varied between 1.5 and 3.2%, precision varied between 3.7 and 7.3% and linearity showed R20.9991. For O2+, LoD are in the range of 72 to 1.4 ng, with an accuracy of between 2.8 and 4.9% and a precision between 4.5 and 8.6% and R20.9914. The validated methodology was applied to the analysis of commercial pre-blast gun powders from different manufacturers.(VLID)4826148Accepted versio

Characterization of a raspberry Pi as the core for a low-cost multimodal EEG-fNIRS platform.

Poor understanding of brain recovery after injury, sparsity of evaluations and limited availability of healthcare services hinders the success of neurorehabilitation programs in rural communities. The availability of neuroimaging ca-pacities in remote communities can alleviate this scenario supporting neurorehabilitation programs in remote settings. This research aims at building a multimodal EEG-fNIRS neuroimaging platform deployable to rural communities to support neurorehabilitation efforts. A Raspberry Pi 4 is chosen as the CPU for the platform responsible for presenting the neurorehabilitation stimuli, acquiring, processing and storing concurrent neuroimaging records as well as the proper synchronization between the neuroimaging streams. We present here two experiments to assess the feasibility and characterization of the Raspberry Pi as the core for a multimodal EEG-fNIRS neuroimaging platform; one over controlled conditions using a combination of synthetic and real data, and another from a full test during resting state. CPU usage, RAM usage and operation temperature were measured during the tests with mean operational records below 40% for CPU cores, 13.6% for memory and 58.85 ° C for temperatures. Package loss was inexistent on synthetic data and negligible on experimental data. Current consumption can be satisfied with a 1000 mAh 5V battery. The Raspberry Pi 4 was able to cope with the required workload in conditions of operation similar to those needed to support a neurorehabilitation evaluation