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- el-Din, Sayed H. Seif, et al.
(författare)
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Potential effect of the medicinal plants Calotropis procera, Ficus elastica and Zingiber officinale against Schistosoma mansoni in mice
- 2014
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Ingår i: Pharmaceutical Biology. - : Informa UK Limited. - 1744-5116 .- 1388-0209. ; 52:2, s. 144-150
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Tidskriftsartikel (refereegranskat)abstract
- Context: Calotropis procera (Ait.) R. Br. (Asclepiadaceae), Ficus elastica Roxb. (Moraceae) and Zingiber officinale Roscoe (Zingiberaceae) have been traditionally used to treat many diseases. Objective: The antischistosomal activity of these plant extracts was evaluated against Schistosoma mansoni. Materials and methods: Male mice exposed to 80 +/- 10 cercariae per mouse were divided into two batches. The first was divided into five groups: (I) infected untreated, while groups from (II-V) were treated orally (500 mg/kg for three consecutive days) by aqueous stem latex and flowers of C. procera, latex of F. elastica and ether extract of Z. officinale, respectively. The second batch was divided into four comparable groups (except Z. officinale-treated group) similarly treated as the first batch in addition to the antacid ranitidine (30 mg/kg) 1 h before extract administration. Safety, worm recovery, tissues egg load and oogram pattern were assessed. Results: Calotropis procera latex and flower extracts are toxic (50-70% mortality) even in a small dose (250 mg/kg) before washing off their toxic rubber. Zingiber officinale extract insignificantly decrease (7.26%) S. mansoni worms. When toxic rubber was washed off and ranitidine was used, C. procera (stem latex and flowers) and F. elastica extracts revealed significant S. mansoni worm reductions by 45.31, 53.7 and 16.71%, respectively. Moreover, C. procera extracts produced significant reductions in tissue egg load (similar to 34-38.5%) and positively affected oogram pattern. Conclusion: The present study may be useful to supplement information with regard to C. procera and F. elastica antischistosomal activity and provide a basis for further experimental trials.
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- Duong, Vicky, et al.
(författare)
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Exploring translational gaps between basic scientists, clinical researchers, clinicians, and consumers : Proceedings and recommendations arising from the 2020 mine the gap online workshop
- 2021
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Ingår i: Osteoarthritis and Cartilage Open. - : Elsevier BV. - 2665-9131. ; 3:2
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Tidskriftsartikel (refereegranskat)abstract
- Objective: To provide a summary of the translational gaps in musculoskeletal research as identified in the Mine the Gap workshop and propose possible solutions. Methods: The Mine the Gap online workshop was hosted on October 14th and 15th, 2020. Five international panels, each comprised of a clinician, clinical researcher and basic scientist, presented gaps and proposed solutions for the themes of biomechanics, pain, biological measurements, phenotypes and imaging. This was followed by an interactive panel discussion with consumer insights. Results: A number of translational gaps and proposed solutions across each of the five themes were identified. A consumer panel provided constructive feedback highlighting the need for improved resources, communication and shared decision making, and treatment individualisation. Conclusion: This brief report provides a greater understanding of the diverse work and gaps relevant to fundamental/discovery scientists, clinical researchers and clinicians working across the musculoskeletal field. The numerous translational gaps highlight the need to improve communication and collaboration across the musculoskeletal field.
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- Teckentrup, Lina, et al.
(författare)
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Opening Pandora's box : Reducing global circulation model uncertainty in Australian simulations of the carbon cycle
- 2023
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Ingår i: Earth System Dynamics. - 2190-4979. ; 14:3, s. 549-576
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Tidskriftsartikel (refereegranskat)abstract
- Climate projections from global circulation models (GCMs), part of the Coupled Model Intercomparison Project 6 (CMIP6), are often employed to study the impact of future climate on ecosystems. However, especially at regional scales, climate projections display large biases in key forcing variables such as temperature and precipitation. These biases have been identified as a major source of uncertainty in carbon cycle projections, hampering predictive capacity. In this study, we open the proverbial Pandora's box and peer under the lid of strategies to tackle climate model ensemble uncertainty. We employ a dynamic global vegetation model (LPJ-GUESS) and force it with raw output from CMIP6 to assess the uncertainty associated with the choice of climate forcing. We then test different methods to either bias-correct or calculate ensemble averages over the original forcing data to reduce the climate-driven uncertainty in the regional projection of the Australian carbon cycle. We find that all bias correction methods reduce the bias of continental averages of steady-state carbon variables. Bias correction can improve model carbon outputs, but carbon pools are insensitive to the type of bias correction method applied for both individual GCMs and the arithmetic ensemble average across all corrected models. None of the bias correction methods consistently improve the change in simulated carbon over time compared to the target dataset, highlighting the need to account for temporal properties in correction or ensemble-averaging methods. Multivariate bias correction methods tend to reduce the uncertainty more than univariate approaches, although the overall magnitude is similar. Even after correcting the bias in the meteorological forcing dataset, the simulated vegetation distribution presents different patterns when different GCMs are used to drive LPJ-GUESS. Additionally, we found that both the weighted ensemble-averaging and random forest approach reduce the bias in total ecosystem carbon to almost zero, clearly outperforming the arithmetic ensemble-averaging method. The random forest approach also produces the results closest to the target dataset for the change in the total carbon pool, seasonal carbon fluxes, emphasizing that machine learning approaches are promising tools for future studies. This highlights that, where possible, an arithmetic ensemble average should be avoided. However, potential target datasets that would facilitate the application of machine learning approaches, i.e., that cover both the spatial and temporal domain required to derive a robust informed ensemble average, are sparse for ecosystem variables.
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- Tejani, Sanaa, et al.
(författare)
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Cardiometabolic Health Outcomes Associated With Discordant Visceral and Liver Fat Phenotypes: Insights From the Dallas Heart Study and UK Biobank
- 2022
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Ingår i: Mayo Clinic proceedings. - New York, United States : Elsevier. - 0025-6196 .- 1942-5546. ; 97:2, s. 225-237
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Tidskriftsartikel (refereegranskat)abstract
- Objective: To evaluate the cardiometabolic outcomes associated with discordant visceral adipose tissue (VAT) and liver fat (LF) phenotypes in 2 cohorts.Patients and Methods: Participants in the Dallas Heart Study underwent baseline imaging from January 1, 2000, through December 31, 2002, and were followed for incident cardiovascular disease (CVD) and type 2 diabetes mellitus (T2DM) through 2013. Associations between VAT-LF groups (low-low, high-low, low-high, and high-high) and outcomes were assessed using multivariable- adjusted regression and were replicated in the independent UK Biobank.Results: The Dallas Heart Study included 2064 participants (mean SD age, 449 years; 54% female; 47% black). High VATehigh LF and high VATelow LF were associated with prevalent atheroscle- rosis, whereas low VATehigh LF was not. Of 1731 participants without CVD/T2DM, 128 (7.4%) developed CVD and 95 (5.5%) T2DM over a median of 12 years. High VATehigh LF and high VATelow LF were associated with increased risk of CVD (hazard ratios [HRs], 2.0 [95% CI, 1.3 to 3.2] and 2.4 [95% CI, 1.4 to 4.1], respectively) and T2DM (odds ratios [ORs], 7.8 [95% CI, 3.8 to 15.8] and 3.3 [95% CI, 1.4 to 7.8], respectively), whereas low VATehigh LF was associated with T2DM (OR, 2.7 [95% CI, 1.1 to 6.7]). In the UK Biobank (N1⁄422,354; April 2014-May 2020), only high VATelow LF remained associated with CVD after multivariable adjustment for age and body mass index (HR, 1.5 [95% CI, 1.2 to 1.9]).Conclusion: Although VAT and LF are each associated with cardiometabolic risk, these observations demonstrate the importance of separating their cardiometabolic implications when there is presence or absence of either or both in an individual.
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