37 research outputs found
Effects of mesenchymal stromal cells versus serum on tendon healing in a controlled experimental trial in an equine model
Abstract Background Mesenchymal stromal cells (MSC) have shown promising results in the treatment of tendinopathy in equine medicine, making this therapeutic approach seem favorable for translation to human medicine. Having demonstrated that MSC engraft within the tendon lesions after local injection in an equine model, we hypothesized that they would improve tendon healing superior to serum injection alone. Methods Quadrilateral tendon lesions were induced in six horses by mechanical tissue disruption combined with collagenase application 3Â weeks before treatment. Adipose-derived MSC suspended in serum or serum alone were then injected intralesionally. Clinical examinations, ultrasound and magnetic resonance imaging were performed over 24Â weeks. Tendon biopsies for histological assessment were taken from the hindlimbs 3Â weeks after treatment. Horses were sacrificed after 24Â weeks and forelimb tendons were subjected to macroscopic and histological examination as well as analysis of musculoskeletal marker expression. Results Tendons injected with MSC showed a transient increase in inflammation and lesion size, as indicated by clinical and imaging parameters between week 3 and 6 (pâ<â0.05). Thereafter, symptoms decreased in both groups and, except that in MSC-treated tendons, mean lesion signal intensity as seen in T2w magnetic resonance imaging and cellularity as seen in the histology (pâ<â0.05) were lower, no major differences could be found at week 24. Conclusions These data suggest that MSC have influenced the inflammatory reaction in a way not described in tendinopathy studies before. However, at the endpoint of the current study, 24Â weeks after treatment, no distinct improvement was observed in MSC-treated tendons compared to the serum-injected controls. Future studies are necessary to elucidate whether and under which conditions MSC are beneficial for tendon healing before translation into human medicine
Competitive Interactions between Invasive Nile Tilapia and Native Fish: The Potential for Altered Trophic Exchange and Modification of Food Webs
Recent studies have highlighted both the positive and negative impacts of species invasions. Most of these studies have been conducted on either immobile invasive plants or sessile fauna found at the base of food webs. Fewer studies have examined the impacts of vagile invasive consumers on native competitors. This is an issue of some importance given the controlling influence that consumers have on lower order plants and animals. Here, we present results of laboratory experiments designed to assess the impacts of unintended aquaculture releases of the Nile tilapia (Oreochromis niloticus), in estuaries of the Gulf of Mexico, on the functionally similar redspotted sunfish (Lepomis miniatus). Laboratory choice tests showed that tilapia prefer the same structured habitat that native sunfish prefer. In subsequent interspecific competition experiments, agonistic tilapia displaced sunfish from their preferred structured habitats. When a piscivore (largemouth bass) was present in the tank with both species, the survival of sunfish decreased. Based on these findings, if left unchecked, we predict that the proliferation of tilapia (and perhaps other aggressive aquaculture fishes) will have important detrimental effects on the structure of native food webs in shallow, structured coastal habitats. While it is likely that the impacts of higher trophic level invasive competitors will vary among species, these results show that consequences of unintended releases of invasive higher order consumers can be important
Solving Large p-median Problems by a Multistage Hybrid Approach Using Demand Points Aggregation and Variable Neighbourhood Search
A hybridisation of a clustering-based technique and of a variable neighbourhood
search (VNS) is designed to solve large-scale p-median problems. The approach is based
on a multi-stage methodology where learning from previous stages is taken into account
when tackling the next stage. Each stage is made up of several subproblems that are solved
by a fast procedure to produce good feasible solutions. Within each stage, the solutions
returned are put together to make up a new promising subset of potential facilities. This
augmented p-median problem is then solved by VNS. As these problems used aggregation,
a cost evaluation based on the original demand points instead of aggregation is computed
for each of the âaggregationâ-based solution. The one yielding the least cost is then selected
and its chosen facilities included into the next stages. This multi-stage process is repeated
several times until a certain criterion is met. This approach is enhanced by an efficient way
to aggregate the data and a neighbourhood reduction scheme when allocating demand points
to their nearest facilities. The proposed approach is tested, using various values of p, on
the largest data sets from the literature with up to 89,600 demand points with encouraging
results
A Computational Comparison of Different Algorithms for Very Large p -median Problems
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