Vascular endothelial growth factor (VEGF), transforming growth factor beta (TGFbeta), angiostatin, and endostatin are increased in radiotherapy-induced gastrointestinal toxicity

Radiotherapy-induced gut toxicity (RIGT) is a debilitating effect of radiotherapy for cancer, often resulting in significant diarrhoea and pain. Previous studies have highlighted roles of the intestinal microvasculature and matrix metalloproteinases (MMPs) in the development of RIGT. We hypothesized vascular mediators would be significantly altered in a dark agouti (DA) rat model of RIGT. Additionally, we aimed to assess the effect of MMP-2 and -9 inhibition on the response of tumour-associated microvascular endothelial cells (TAMECs) to radiation.Dark Agouti (DA) rats were administered 2.5 Gy abdominal irradiation (3 times/week over 6 weeks). Vascular endothelial growth factor (VEGF), transforming growth factor beta (TGFβ), von Willebrand factor (VWF), angiostatin, and endostatin expression was assessed at 3, 6 and 15 weeks. Additionally, DA rat mammary adenocarcinoma tumour-associated microvascular endothelial cells (TAMECs) were used to assess the effects of radiation (12 Gy) and the MMP inhibitor SB-3CT on MMP, VEGF, and TGFβ expression, and cell viability.VEGF mRNA expression was significantly increased in the colon at week 15 (p = 0.0012), and TGFβ mRNA expression was significantly increased in both the jejunum and colon at week 3 (p = 0.0280, and p = 0.0310, respectively). Endostatin immunostaining was significantly increased at week 3 (p = 0.0046), and angiostatin at 3 and 6 weeks (p = 0.0022, and p = 0.0135, respectively). MMP-2 and -9 mRNA and total protein levels were significantly increased following irradiation of TAMECs. Although this increase was significantly attenuated by SB-3CT, it did not significantly alter endothelial cell viability or VEGF and TGFβ mRNA expression.Findings of this study support the involvement of VEGF, TGFβ, angiostatin, endostatin, and MMP-2 in the pathobiology of RIGT. However, the relationship between these mediators is complex and needs further investigation to improve understanding of their therapeutic potential in RIGT.Romany L. Stansborough, Emma H. Bateman, Noor Al-Dasooqi, Joanne M. Bowen, Anthony Wignall, Dorothy M. Keefe, Ann S. Yeoh, Richard M. Logan, Eric E. K. Yeoh, Andrea M. Stringer and Rachel J. Gibso

Patient navigation across the cancer care continuum: An overview of systematic reviews and emerging literature

OnlinePublPatient navigation is a strategy for overcoming barriers to reduce disparities and to improve access and outcomes. The aim of this umbrella review was to identify, critically appraise, synthesize, and present the best available evidence to inform policy and planning regarding patient navigation across the cancer continuum. Systematic reviews examining navigation in cancer care were identified in the Cochrane Central Register of Controlled Trials (CENTRAL), PubMed, Embase, Cumulative Index of Nursing and Allied Health (CINAHL), Epistemonikos, and Prospective Register of Systematic Reviews (PROSPERO) databases and in the gray literature from January 1, 2012, to April 19, 2022. Data were screened, extracted, and appraised independently by two authors. The JBI Critical Appraisal Checklist for Systematic Review and Research Syntheses was used for quality appraisal. Emerging literature up to May 25, 2022, was also explored to capture primary research published beyond the coverage of included systematic reviews. Of the 2062 unique records identified, 61 systematic reviews were included. Fifty‐four reviews were quantitative or mixed‐methods reviews, reporting on the effectiveness of cancer patient navigation, including 12 reviews reporting costs or cost‐effectiveness outcomes. Seven qualitative reviews explored navigation needs, barriers, and experiences. In addition, 53 primary studies published since 2021 were included. Patient navigation is effective in improving participation in cancer screening and reducing the time from screening to diagnosis and from diagnosis to treatment initiation. Emerging evidence suggests that patient navigation improves quality of life and patient satisfaction with care in the survivorship phase and reduces hospital readmission in the active treatment and survivorship care phases. Palliative care data were extremely limited. Economic evaluations from the United States suggest the potential cost‐effectiveness of navigation in screening programs.Raymond J. Chan, Vivienne E. Milch, Fiona Crawford, Williams, Ria Joseph, Jolyn Johal, Narayanee Dick, Matthew P. Wallen, Julie Ratcliffe, Anupriya Agarwal, Larissa Nekhlyudov, Matthew Tieu, Manaf Al, Momani, Scott Turnbull, Rahul Sathiaraj, Dorothy Keefe, Nicolas H. Har

Knowledge gaps that hamper prevention and control of Mycobacterium avium subspecies paratuberculosis infection

In the last decades, many regional and country‐wide control programmes for Johne's disease (JD) were developed due to associated economic losses, or because of a possible association with Crohn's disease. These control programmes were often not successful, partly because management protocols were not followed, including the introduction of infected replacement cattle, because tests to identify infected animals were unreliable, and uptake by farmers was not high enough because of a perceived low return on investment. In the absence of a cure or effective commercial vaccines, control of JD is currently primarily based on herd management strategies to avoid infection of cattle and restrict within‐farm and farm‐to‐farm transmission. Although JD control programmes have been implemented in most developed countries, lessons learned from JD prevention and control programmes are underreported. Also, JD control programmes are typically evaluated in a limited number of herds and the duration of the study is less than 5 year, making it difficult to adequately assess the efficacy of control programmes. In this manuscript, we identify the most important gaps in knowledge hampering JD prevention and control programmes, including vaccination and diagnostics. Secondly, we discuss directions that research should take to address those knowledge gaps.http://wileyonlinelibrary.com/journal/tbed2019-05-01hj2018Veterinary Tropical Disease

Involvement of matrix metalloproteinases (MMP-3 and MMP-9) in the pathogenesis of irinotecan-induced oral mucositis

OBJECTIVES: Matrix metalloproteinases (MMPs) are involved in both maintenance of healthy mucosa and mediation of several pathologies. Recently, MMPs and their inhibitors have attracted attention as potential mediators of mucositis. We investigated tissue expression of MMP-3 and MMP-9 over time in a pre-clinical model of irinotecan-induced oral mucositis (OM). MATERIALS AND METHODS: Eighty-one female Dark Agouti rats received either a single dose of irinotecan (200 mg/kg) or vehicle control. Rats were killed at different time points over a 72-h period and tongue mucosa examined histologically. Tissue expression of MMP-3 and MMP-9 was characterized by standard qualitative immunohistochemistry. RESULTS AND DISCUSSION: Epithelial thickness was reduced without any ulceration in the oral mucosa early after chemotherapy. Epithelial atrophy was associated with significant (P < 0.05) upregulation of MMP-3 and MMP-9 in all layers of the oral epithelium. The increase of MMP-3 was also significant (P < 0.05) in lamina propria and submucosa. Most of changes in expression occurred early (1-6 h), coinciding with previously described upregulation of transcription factors and pro-inflammatory cytokines in OM. Tissue expression of MMP-3 and MMP-9 followed different patterns of change over time, suggesting involvement in various aspects of OM pathophysiology. CONCLUSIONS: These findings suggest vital roles played by MMP-3 and MMP-9 during OM pathophysiology. Further research is required to investigate the role of other MMPs and the naturally existing tissue inhibitors of MMPs. Research should also be directed to investigate beneficial effects of MMPs intervention therapies to prevent or reduce the severity of OM.Abdul R. Al-Azri, Rachel J. Gibson, Joanne M. Bowen, Andrea M. Stringer, Dorothy M. Keefe and Richard M. Loga

Precision medicine for long-term depression outcomes using the Personalized Advantage Index approach: Cognitive therapy or interpersonal psychotherapy?

Background Psychotherapies for depression are equally effective on average, but individual responses vary widely. Outcomes can be improved by optimizing treatment selection using multivariate prediction models. A promising approach is the Personalized Advantage Index (PAI) that predicts the optimal treatment for a given individual and the magnitude of the advantage. The current study aimed to extend the PAI to long-term depression outcomes after acute-phase psychotherapy. Methods Data come from a randomized trial comparing cognitive therapy (CT, n = 76) and interpersonal psychotherapy (IPT, n = 75) for major depressive disorder (MDD). Primary outcome was depression severity, as assessed by the BDI-II, during 17-month follow-up. First, predictors and moderators were selected from 38 pre-treatment variables using a two-step machine learning approach. Second, predictors and moderators were combined into a final model, from which PAI predictions were computed with cross-validation. Long-term PAI predictions were then compared to actual follow-up outcomes and post-treatment PAI predictions. Results One predictor (parental alcohol abuse) and two moderators (recent life events; childhood maltreatment) were identified. Individuals assigned to their PAI-indicated treatment had lower follow-up depression severity compared to those assigned to their PAI-non-indicated treatment. This difference was significant in two subsets of the overall sample: those whose PAI score was in the upper 60%, and those whose PAI indicated CT, irrespective of magnitude. Long-term predictions did not overlap substantially with predictions for acute benefit. Conclusions If replicated, long-term PAI predictions could enhance precision medicine by selecting the optimal treatment for a given depressed individual over the long term

Precision medicine for long-term depression outcomes using the Personalized Advantage Index approach: Cognitive therapy or interpersonal psychotherapy?

Background Psychotherapies for depression are equally effective on average, but individual responses vary widely. Outcomes can be improved by optimizing treatment selection using multivariate prediction models. A promising approach is the Personalized Advantage Index (PAI) that predicts the optimal treatment for a given individual and the magnitude of the advantage. The current study aimed to extend the PAI to long-term depression outcomes after acute-phase psychotherapy. Methods Data come from a randomized trial comparing cognitive therapy (CT, n = 76) and interpersonal psychotherapy (IPT, n = 75) for major depressive disorder (MDD). Primary outcome was depression severity, as assessed by the BDI-II, during 17-month follow-up. First, predictors and moderators were selected from 38 pre-treatment variables using a two-step machine learning approach. Second, predictors and moderators were combined into a final model, from which PAI predictions were computed with cross-validation. Long-term PAI predictions were then compared to actual follow-up outcomes and post-treatment PAI predictions. Results One predictor (parental alcohol abuse) and two moderators (recent life events; childhood maltreatment) were identified. Individuals assigned to their PAI-indicated treatment had lower follow-up depression severity compared to those assigned to their PAI-non-indicated treatment. This difference was significant in two subsets of the overall sample: those whose PAI score was in the upper 60%, and those whose PAI indicated CT, irrespective of magnitude. Long-term predictions did not overlap substantially with predictions for acute benefit. Conclusions If replicated, long-term PAI predictions could enhance precision medicine by selecting the optimal treatment for a given depressed individual over the long term

Precision medicine for long-term depression outcomes using the Personalized Advantage Index approach: Cognitive therapy or interpersonal psychotherapy?

Background Psychotherapies for depression are equally effective on average, but individual responses vary widely. Outcomes can be improved by optimizing treatment selection using multivariate prediction models. A promising approach is the Personalized Advantage Index (PAI) that predicts the optimal treatment for a given individual and the magnitude of the advantage. The current study aimed to extend the PAI to long-term depression outcomes after acute-phase psychotherapy. Methods Data come from a randomized trial comparing cognitive therapy (CT, n = 76) and interpersonal psychotherapy (IPT, n = 75) for major depressive disorder (MDD). Primary outcome was depression severity, as assessed by the BDI-II, during 17-month follow-up. First, predictors and moderators were selected from 38 pre-treatment variables using a two-step machine learning approach. Second, predictors and moderators were combined into a final model, from which PAI predictions were computed with cross-validation. Long-term PAI predictions were then compared to actual follow-up outcomes and post-treatment PAI predictions. Results One predictor (parental alcohol abuse) and two moderators (recent life events; childhood maltreatment) were identified. Individuals assigned to their PAI-indicated treatment had lower follow-up depression severity compared to those assigned to their PAI-non-indicated treatment. This difference was significant in two subsets of the overall sample: those whose PAI score was in the upper 60%, and those whose PAI indicated CT, irrespective of magnitude. Long-term predictions did not overlap substantially with predictions for acute benefit. Conclusions If replicated, long-term PAI predictions could enhance precision medicine by selecting the optimal treatment for a given depressed individual over the long term

Cognitive Learning Styles and Digital Equity: Searching for the Middle Way

This research is driven by a desire to understand the lifelong learner in the context of styles of learning and the emerging implications of technology enhanced learning for digital equity. Recognizing cognitive learning styles is the first step educators need to take in order to be most effective in working with students of diversity and bridging across formal and informal settings. Learning environments as a characterising feature of learning styles have undergone unprecedented change over the past decade with learning environments now blending physical and virtual space. To support the increasing diversity of learners pedagogy has to be fair, culturally responsive, equitable and relevant to the ‘virtual generation’. This in turn will inform our understanding of the ‘middle way’ in recognising cognitive learning styles , associated cultural context, and the implications to digital pedagogy equity