55 research outputs found

    Impaired Wound Healing in Mouse Models of Diabetes Is Mediated by TNF-α Dysregulation and Associated With Enhanced Activation of Forkhead Box O1 (FOXO1)

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    Aims/hypothesis The role of TNF-α in impaired wound healing in diabetes was examined by focusing on fibroblasts. Methods Small excisional wounds were created in the db/db mice model of type 2 diabetes and normoglycaemic littermates, and in a streptozotocin-induced type 1 diabetes mouse model and control mice. Fibroblast apoptosis was measured by the TUNEL assay, proliferation by detection of proliferating cell nuclear antigen, and forkhead box O1 (FOXO1) activity by DNA binding and nuclear translocation. TNF-α was specifically inhibited by pegsunercept. Results Diabetic wounds had increased TNF-α, fibroblast apoptosis, caspase-3/7 activity and activation of the pro-apoptotic transcription factor FOXO1, and decreased proliferating cell nuclear antigen positive fibroblasts (p \u3c 0.05). TNF-α inhibition improved healing in the diabetic mice and increased fibroblast density. This may be explained by a decrease in fibroblast apoptosis and increased proliferation when TNF-α was blocked (p  \u3c 0.05). Although decreased fibroblast proliferation and enhanced FOXO1 activity were investigated in type 2 diabetes, they may also be implicated in type 1 diabetes. In vitro, TNF-α enhanced mRNA levels of gene sets related to apoptosis and Akt and p53 but not mitochondrial or cell-cycle pathways. FOXO1 small interfering RNA reduced gene sets that regulate apoptosis, Akt, mitochondrial and cell-cycle pathways. TNF-α also increased genes involved in inflammation, cytokine, Toll-like receptor and nuclear factor-kB pathways, which were significantly reduced by FOXO1 knockdown. Conclusions/interpretation These studies indicate that TNF-α dysregulation in diabetic wounds impairs healing, which may involve enhanced fibroblast apoptosis and decreased proliferation. In vitro, TNF-α induced gene sets through FOXO1 that regulate a number of pathways that could influence inflammation and apoptosis

    Program assessment of efforts to improve the quality of postpartum counselling in health centers in Morogoro region, Tanzania

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    BACKGROUND: The postpartum period represents a critical window where many maternal and child deaths occur. We assess the quality of postpartum care (PPC) as well as efforts to improve service delivery through additional training and supervision in Health Centers (HCs) in Morogoro Region, Tanzania. METHODS: Program implementers purposively selected nine program HCs for assessment with another nine HCs in the region remaining as comparison sites in a non-randomized program evaluation. PPC quality was assessed by examining structural inputs; provider and client profiles; processes (PNC counselling) and outcomes (patient knowledge) through direct observations of equipment, supplies and infrastructure (n = 18) and PPC counselling (n = 45); client exit interviews (n = 41); a provider survey (n = 62); and in-depth provider interviews (n = 10). RESULTS: While physical infrastructure, equipment and supplies were comparable across study sites (with water and electricity limitations), program areas had better availability of drugs and commodities. Overall, provider availability was also similar across study sites, with 63% of HCs following staffing norms, 17% of Reproductive and Child Health (RCH) providers absent and 14% of those providing PPC being unqualified to do so. In the program area, a median of 4 of 10 RCH providers received training. Despite training and supervisory inputs to program area HCs, provider and client knowledge of PPC was low and the content of PPC counseling provided limited to 3 of 80 PPC messages in over half the consultations observed. Among women attending PPC, 29 (71%) had delivered in a health facility and sought care a median of 13 days after delivery. Barriers to PPC care seeking included perceptions that PPC was of limited benefit to women and was primarily about child health, geographic distance, gaps in the continuity of care, and harsh facility treatment. CONCLUSIONS: Program training and supervision activities had a modest effect on the quality of PPC. To achieve broader transformation in PPC quality, client perceptions about the value of PPC need to be changed; the content of recommended PPC messages reviewed along with the location for PPC services; gaps in the availability of human resources addressed; and increased provider-client contact encouraged

    Ensemble-based multi-filter feature selection method for DDoS detection in cloud computing

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    Widespread adoption of cloud computing has increased the attractiveness of such services to cybercriminals. Distributed denial of service (DDoS) attacks targeting the cloud’s bandwidth, services and resources to render the cloud unavailable to both cloud providers, and users are a common form of attacks. In recent times, feature selection has been identified as a pre-processing phase in cloud DDoS attack defence which can potentially increase classification accuracy and reduce computational complexity by identifying important features from the original dataset during supervised learning. In this work, we propose an ensemble-based multi-filter feature selection method that combines the output of four filter methods to achieve an optimum selection. We then perform an extensive experimental evaluation of our proposed method using intrusion detection benchmark dataset, NSL-KDD and decision tree classifier. The findings show that our proposed method can effectively reduce the number of features from 41 to 13 and has a high detection rate and classification accuracy when compared to other classification techniques

    Routine health management information system data in Ethiopia: consistency, trends, and challenges.

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    Background: Ethiopia is investing in the routine Health Management Information System. Improved routine data are needed for decision-making in the health sector. Objective: To analyse the quality of the routine Health Management Information System data and triangulate with other sources, such as the Demographic and Health Surveys. Methods: We analysed national Health Management Information System data on 19 indicators of maternal health, neonatal survival, immunization, child nutrition, malaria, and tuberculosis over the 2012-2018 time period. The analyses were conducted by 38 analysts from the Ministry of Health, Ethiopia, and two government agencies who participated in the Operational Research and Coaching for Analysts (ORCA) project between June 2018 and June 2020. Using a World Health Organization Data Quality Review toolkit, we assessed indicator definitions, completeness, internal consistency over time and between related indicators, and external consistency compared with other data sources. Results: Several services reported coverage of above 100%. For many indicators, denominators were based on poor-quality population data estimates. Data on individual vaccinations had relatively good internal consistency. In contrast, there was low external consistency for data on fully vaccinated children, with the routine Health Management Information System showing 89% coverage but the Demographic and Health Survey estimate at 39%. Maternal health indicators displayed increasing coverage over time. Indicators on child nutrition, malaria, and tuberculosis were less consistent. Data on neonatal mortality were incomplete and operationalised as mortality on day 0-6. Our comparisons with survey and population projections indicated that one in eight early neonatal deaths were reported in the routine Health Management Information System. Data quality varied between regions. Conclusions: The quality of routine data gathered in the health system needs further attention. We suggest regular triangulation with data from other sources. We recommend addressing the denominator issues, reducing the complexity of indicators, and aligning indicators to international definitions

    Willingness to pay for Drought Tolerance (DT) in Maize in Communal Areas of Zimbabwe

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    This study aimed at estimating the implicit prices farmers are willing to pay (WTP) for maize traits with deliberate focus on drought tolerance. Using choice experiment, we generated 12600 observations from a random sample of 1400 households in communal areas within 14 districts of Zimbabwe. Taste parameters and heterogeneities (scale and residual taste) were estimated using the generalized multinomial logit model (G-MNL) and its different versions. Drought tolerance, grain yield, large grain size, covered cob tip, big cob and semi flint texture were the most preferred traits by rural Zimbabweans. The WTP values were estimated using the WTP space approach. Sample farmers are, for example, willing to pay a premium for drought tolerance that is 1.75 times the amount they are willing to pay for an increase of 1 ton in grain yield per acre, 8.3 times the value they attach for a change from small to big cob size, and 14.7 times the willingness to pay for semi-flint texture over dent texture of maize. The uncertainty that DT might not be appealing to poor farmers as much as some other technologies can only be cleared only if the promotion of DT materials is done in the right manner and to the right farm community. Innovative ways of promoting DT maize vis-à-vis creating awareness in contextual understanding of drought and drought risk shall be employed to enhance adoption of new DT maize varieties by risk prone farming communities. Given the high level of rural literacy and the high rate of adoption of improved maize in Zimbabwe, trait based promotion and marketing of varieties would be the right strategy
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