28,129 research outputs found

    Analyses of human vaccine-specific circulating and bone marrow-resident B cell populations reveal benefit of delayed vaccine booster dosing with blood-stage malaria antigens

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    We have previously reported primary endpoints of a clinical trial testing two vaccine platforms for the delivery of Plasmodium vivax malaria DBPRII: viral vectors (ChAd63, MVA), and protein/adjuvant (PvDBPII with 50µg Matrix-M™ adjuvant). Delayed boosting was necessitated due to trial halts during the pandemic and provides an opportunity to investigate the impact of dosing regimens. Here, using flow cytometry – including agnostic definition of B cell populations with the clustering tool CITRUS – we report enhanced induction of DBPRII-specific plasma cell and memory B cell responses in protein/adjuvant versus viral vector vaccinees. Within protein/adjuvant groups, delayed boosting further improved B cell immunogenicity compared to a monthly boosting regimen. Consistent with this, delayed boosting also drove more durable anti-DBPRII serum IgG. In an independent vaccine clinical trial with the P. falciparum malaria RH5.1 protein/adjuvant (50µg Matrix-M™) vaccine candidate, we similarly observed enhanced circulating B cell responses in vaccinees receiving a delayed final booster. Notably, a higher frequency of vaccine-specific (putatively long-lived) plasma cells was detected in the bone marrow of these delayed boosting vaccinees by ELISPOT and correlated strongly with serum IgG. Finally, following controlled human malaria infection with P. vivax parasites in the DBPRII trial, in vivo growth inhibition was observed to correlate with DBPRII-specific B cell and serum IgG responses. In contrast, the CD4+ and CD8+ T cell responses were impacted by vaccine platform but not dosing regimen and did not correlate with in vivo growth inhibition in a challenge model. Taken together, our DBPRII and RH5 data suggest an opportunity for protein/adjuvant dosing regimen optimisation in the context of rational vaccine development against pathogens where protection is antibody-mediated

    Maxent and MigClim Code

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    This data set includes the code from Draper, John P, Julie K Young, Noelle G Beckman, and Trisha B Atwood. “The Differential Contribution of Coyotes and Passerines on Future Biotic Carbon Storage through Juniper Seed Dispersal,” Ecography, 2024. Included are the model code for both the Maxent and MigClim models described in the manuscript</p

    Training volume and high-speed loads vary within microcycle in elite North American soccer players.

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    The purposes of this study were to reduce dimensionality of external training load variables and examine how the selected variables varied within microcycle in elite North American soccer players. Data were collected from 18 players during 2018–2020 in-seasons. Microcycle was categorized as 1, 2, 3, 4, 5 days before match day (MD-1, MD-2, MD-3, MD-4, and MD-5, respectively). Training load variables included total distance, average speed, maximum velocity, high-speed running distance (HSR), average HSR, HSR efforts, average HSR efforts, sprint distance, average sprint distance, sprint efforts, average sprint efforts, total PlayerLoad, and average PlayerLoad. The first principal component (PC) can explain 66.0% of the variances and be represented by “high-speed load” (e.g., HSR and sprint-related variables) with the second PC relating to “volume” (e.g., total distance and PlayerLoad) accounting for 17.9% of the variance. Average sprint distance and total distance were selected for further analysis. Average sprint distance was significantly higher at MD-3 than at MD-2 (p = 0.01, mean difference = 0.36 m•minute−1, 95% confidence intervals [CIs] = 0.07–0.65 m•minute−1) and MD-4 (p = 0.012, mean difference = 0.26 m•minute−1, 95% CIs = 0.10–0.41 m•minute−1). Total distance was significantly higher at MD-3 than at MD-1 (p &lt; 0.001, mean difference = 1,465 m, 95% CIs = 1,003–1926 m), and MD-2 (p &lt; 0.001, mean difference = 941 m, 95% CIs = 523–1,360 m). Principal component analysis may simplify reporting process of external training loads. Practitioners may need to choose “volume” and “high-speed load” variables. Elite North American Soccer players may accumulate higher average sprint distance at MD-3 than at other training days

    Consistent patterns of common species across tropical tree communities

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    Trees structure the Earth’s most biodiverse ecosystem, tropical forests. The vast number of tree species presents a formidable challenge to understanding these forests, including their response to environmental change, as very little is known about most tropical tree species. A focus on the common species may circumvent this challenge. Here we investigate abundance patterns of common tree species using inventory data on 1,003,805 trees with trunk diameters of at least 10 cm across 1,568 locations1,2,3,4,5,6 in closed-canopy, structurally intact old-growth tropical forests in Africa, Amazonia and Southeast Asia. We estimate that 2.2%, 2.2% and 2.3% of species comprise 50% of the tropical trees in these regions, respectively. Extrapolating across all closed-canopy tropical forests, we estimate that just 1,053 species comprise half of Earth’s 800 billion tropical trees with trunk diameters of at least 10 cm. Despite differing biogeographic, climatic and anthropogenic histories7, we find notably consistent patterns of common species and species abundance distributions across the continents. This suggests that fundamental mechanisms of tree community assembly may apply to all tropical forests. Resampling analyses show that the most common species are likely to belong to a manageable list of known species, enabling targeted efforts to understand their ecology. Although they do not detract from the importance of rare species, our results open new opportunities to understand the world’s most diverse forests, including modelling their response to environmental change, by focusing on the common species that constitute the majority of their trees

    Consistent patterns of common species across tropical tree communities

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    International audienceAbstract Trees structure the Earth’s most biodiverse ecosystem, tropical forests. The vast number of tree species presents a formidable challenge to understanding these forests, including their response to environmental change, as very little is known about most tropical tree species. A focus on the common species may circumvent this challenge. Here we investigate abundance patterns of common tree species using inventory data on 1,003,805 trees with trunk diameters of at least 10 cm across 1,568 locations 1–6 in closed-canopy, structurally intact old-growth tropical forests in Africa, Amazonia and Southeast Asia. We estimate that 2.2%, 2.2% and 2.3% of species comprise 50% of the tropical trees in these regions, respectively. Extrapolating across all closed-canopy tropical forests, we estimate that just 1,053 species comprise half of Earth’s 800 billion tropical trees with trunk diameters of at least 10 cm. Despite differing biogeographic, climatic and anthropogenic histories 7 , we find notably consistent patterns of common species and species abundance distributions across the continents. This suggests that fundamental mechanisms of tree community assembly may apply to all tropical forests. Resampling analyses show that the most common species are likely to belong to a manageable list of known species, enabling targeted efforts to understand their ecology. Although they do not detract from the importance of rare species, our results open new opportunities to understand the world’s most diverse forests, including modelling their response to environmental change, by focusing on the common species that constitute the majority of their trees

    MaxentCode.R

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    This code was used to run the ecological niche model using Maxent described in Draper et. al 2024. Code is provided to explicitly share all model settings and aid others in running a Maxent model. </p

    Determining the impact of an artificial intelligence tool on the management of pulmonary nodules detected incidentally on CT (DOLCE) study protocol: a prospective, non-interventional multicentre UK study

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    \ua9 Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. INTRODUCTION: In a small percentage of patients, pulmonary nodules found on CT scans are early lung cancers. Lung cancer detected at an early stage has a much better prognosis. The British Thoracic Society guideline on managing pulmonary nodules recommends using multivariable malignancy risk prediction models to assist in management. While these guidelines seem to be effective in clinical practice, recent data suggest that artificial intelligence (AI)-based malignant-nodule prediction solutions might outperform existing models. METHODS AND ANALYSIS: This study is a prospective, observational multicentre study to assess the clinical utility of an AI-assisted CT-based lung cancer prediction tool (LCP) for managing incidental solid and part solid pulmonary nodule patients vs standard care. Two thousand patients will be recruited from 12 different UK hospitals. The primary outcome is the difference between standard care and LCP-guided care in terms of the rate of benign nodules and patients with cancer discharged straight after the assessment of the baseline CT scan. Secondary outcomes investigate adherence to clinical guidelines, other measures of changes to clinical management, patient outcomes and cost-effectiveness. ETHICS AND DISSEMINATION: This study has been reviewed and given a favourable opinion by the South Central-Oxford C Research Ethics Committee in UK (REC reference number: 22/SC/0142).Study results will be available publicly following peer-reviewed publication in open-access journals. A patient and public involvement group workshop is planned before the study results are available to discuss best methods to disseminate the results. Study results will also be fed back to participating organisations to inform training and procurement activities. TRIAL REGISTRATION NUMBER: NCT05389774

    Determining the impact of an artificial intelligence tool on the management of pulmonary nodules detected incidentally on CT (DOLCE) study protocol: a prospective, non-interventional multicentre UK study.

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    Introduction In a small percentage of patients, pulmonary nodules found on CT scans are early lung cancers. Lung cancer detected at an early stage has a much better prognosis. The British Thoracic Society guideline on managing pulmonary nodules recommends using multivariable malignancy risk prediction models to assist in management. While these guidelines seem to be effective in clinical practice, recent data suggest that artificial intelligence (AI)-based malignant-nodule prediction solutions might outperform existing models. Methods and analysis This study is a prospective, observational multicentre study to assess the clinical utility of an AI-assisted CT-based lung cancer prediction tool (LCP) for managing incidental solid and part solid pulmonary nodule patients vs standard care. Two thousand patients will be recruited from 12 different UK hospitals. The primary outcome is the difference between standard care and LCP-guided care in terms of the rate of benign nodules and patients with cancer discharged straight after the assessment of the baseline CT scan. Secondary outcomes investigate adherence to clinical guidelines, other measures of changes to clinical management, patient outcomes and cost-effectiveness. Ethics and dissemination This study has been reviewed and given a favourable opinion by the South Central—Oxford C Research Ethics Committee in UK (REC reference number: 22/SC/0142). Study results will be available publicly following peer-reviewed publication in open-access journals. A patient and public involvement group workshop is planned before the study results are available to discuss best methods to disseminate the results. Study results will also be fed back to participating organisations to inform training and procurement activities. Trial registration number NCT05389774

    Elite North American Soccer Performance in Thermally Challenging Environments: An Explorative Approach to Tracking Outcomes

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    Abstract: Aims: The physiologic challenges related to performances in hot conditions calls for dedicated consideration when planning athlete training, although complete amelioration of the effects of heat may not be possible. We aimed to quantify within-subject correlations between different measures of environmental temperature and performance changes over multiple elite soccer competitions. Methods: Thirty-seven elite male soccer players (age:26 ± 3.4years, height:171 ± 2cm, body mass:78 ± 7.1kg) competed in North America over four seasons (range:3 to 98 matches). Players wore global positioning system devices during games and reported differential-RPE immediately post game. Temperatures at kick-off, week average temperature, the difference between game-day and week average (DiffTemp), and heat index at kick-off were obtained. Within-player correlations were calculated using general linear models to quantify associations between fluctuations in temperature measures and physical and perceived outputs. Results: Correlations between total distance and the various temperature measures were trivial to small (range: -0.08 to 0.13, p=&lt;0.001-0.02). Small negative correlations were found between all temperature measures except DiffTemp and high-speed running (HSR) (range: -0.17 to -0.14, p=&lt;0.001). Most correlations between differential-RPE and temperature measures were trivial to small and not significant (r=0.06 to 0.18 p=0.03-0.92) although breathlessness-RPE and heat index showed a small significant association (P=0.018) Conclusion: Decrements in HSR appear to be associated with increased environmental temperature however, these associations are small in magnitude

    Application of quasi solid electrolytes in organic based electrochromic devices: a mini review

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    The interest in all solid organic based electrochromic devices (ECDs) is on the increase. This is because these devices offer the applicability of electrochromic materials in products such as smart sensors, smart windows, flexible wearables and energy storage devices. The use of quasi-solid electrolytes for the construction of these ECDs is attractive because of their ease of preparation, availability, low cost, improve electrochromic performance, good ionic conductivity and prevention of leakages in ECDs. Hence, in this review, a detailed discussion is presented on the progress in the development of semi-solid electrolytes for ECDs fabrication. The preparation of the most common electrolytes that have been applied for organic based ECDs are summarized. Particular attention is given to efforts and strategies that have been adopted to improve the efficiency of quasi-solid electrolytes. Importantly, knowledge gaps that warrant further research are clearly identified and recommendations for future works are suggested. This review will be very beneficial for both established and new researchers in the field of electrochromic devices and material science
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