Effect of Temporal Onset of Mechanical Loading on Tendon to Bone Healing, Determined with a Novel In-Vivo Device

Background: Exposure to tensile loading has been shown to maintain tendon/ligament homeostasis, with the tensile modulus of the tissue increasing in response to greater loading frequency, and even decreasing in the absence of load. However after injury or surgical repair the effect of tensile load is controversial, with many studies implicating mechanical loading with impaired healing. It is currently unknown when the tensile loading imparted during rehabilitation exercise, can be safely reintroduced after surgical tendon repair or ligament reconstruction, and at what time point it can most benefit the remodeling process. To investigate the effect of tensile loading protocols on tendon graft to bone tunnel healing, we developed and validated a novel device to cyclically distract the knee joint in a rat model of anterior cruciate ligament reconstruction (ACL_R), thereby imposing a controlled amount of tensile strain on the tendon graft. Using this device we tested the following hypotheses; H0 which predicts that the immediate resumption of tensile load after ACL_R surgery will impair tendon-to-bone healing compared to continuous knee immobilization. And H1 which predicts that after ACL_R surgery, insertion of a of 4 to 10 day load shielding period, prior to the resumption of tensile load, will improve tendon-to-bone healing compared with both immediate load resumption or continuous immobilization. Methods: Male Sprague Dawley rats who had undergone ACL_R surgery via a flexor digitorum longus tendon auto-graft were randomly assigned to either; 1) a continuous-immobilization group to strain shield the graft or a cyclic knee distraction group using the device to achieve two-percent strain of the tendon graft. The animals receiving cyclic knee distraction were further subdivided into; 2) an immediate-loading group beginning on postoperative day one, 3) a four-day delayed-loading group beginning on postoperative day four, and 4) a ten-day delayed-loading group beginning on postoperative day ten. The above experiment was were repeated with the device applying ten-percent strain to additional four-and ten-day delayed-loading groups. All animals were sacrificed on either postoperative day fourteen or twenty-eight for immuno-histochemical, biomechanical, and micro-computed tomography analysis of the femur-graft-tibia complex. Results: Immediate-loading, beginning on postoperative day one did not result in a significantly reduced load-to-failure mechanical response or bone tunnel volume, compared with continuous-immobilization. However a significantly greater number of inflammatory macrophage cells in the immediate-loading group provided partial support for hypothesis H0. The data supported hypothesis H1, with the four- and ten-day delayed-loading groups having significantly less inflammatory macrophages and more new bone volume at both two and four weeks. The failure load of the femur-graft-tibia complex was significantly greater in the ten-day delayed-loading group at two weeks, and in the four-day delayed-loading group at four weeks. Repeating the experiment with cyclic knee joint distraction increased to ten-percent of graft length did not recapitulate the significantly greater failure loads in the delayed loading groups. Conclusion: On the basis of greatest failure load, most bone tunnel ingrowth, and lowest inflammatory cell population, the four-day delayed-loading protocol was judged most effective for tendon-to-bone healing in the rat model of ACL_R. These parameters could be extrapolated to a human clinical trial of an improved ACL rehabilitation protocol, provided a careful choice of knee exercises applying a maximum of two-percent tendon graft strain were made

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Batrachochytrium salamandrivorans (Bsal) not detected in an intensive survey of wild North American amphibians.

The salamander chytrid fungus (Batrachochytrium salamandrivorans [Bsal]) is causing massive mortality of salamanders in Europe. The potential for spread via international trade into North America and the high diversity of salamanders has catalyzed concern about Bsal in the U.S. Surveillance programs for invading pathogens must initially meet challenges that include low rates of occurrence on the landscape, low prevalence at a site, and imperfect detection of the diagnostic tests. We implemented a large-scale survey to determine if Bsal was present in North America designed to target taxa and localities where Bsal was determined highest risk to be present based on species susceptibility and geography. Our analysis included a Bayesian model to estimate the probability of occurrence of Bsal given our prior knowledge of the occurrence and prevalence of the pathogen. We failed to detect Bsal in any of 11,189 samples from 594 sites in 223 counties within 35 U.S. states and one site in Mexico. Our modeling indicates that Bsal is highly unlikely to occur within wild amphibians in the U.S. and suggests that the best proactive response is to continue mitigation efforts against the introduction and establishment of the disease and to develop plans to reduce impacts should Bsal establish

Of Microenvironments and Mammary Stem Cells

In most adult tissues there reside pools of stem and progenitor cells inside specialized microenvironments referred to as niches. The niche protects the stem cells from inappropriate expansion and directs their critical functions. Thus guided, stem cells are able to maintain tissue homeostasis throughout the ebb and flow of metabolic and physical demands encountered over a lifetime. Indeed, a pool of stem cells maintains mammary gland structure throughout development, and responds to the physiological demands associated with pregnancy. This review discusses how stem cells were identified in both human and mouse mammary glands; each requiring different techniques that were determined by differing biological needs and ethical constraints. These studies together create a robust portrait of mammary gland biology and identify the location of the stem cell niche, elucidate a developmental hierarchy, and suggest how the niche might be manipulated for therapeutic benefit

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science. © The Author(s) 2019. Published by Oxford University Press