Improving Sustainability in WaSH by Integrating Implementation Science: A Review of Implementation Outcomes in Rural Drinking Water Systems in Low- and Middle-Income Countries

Background: Despite the magnitude of resources invested in providing access to clean drinking water in rural areas of low- and middle-income countries (LMIC), sustainability of the myriad solutions available remains elusive. Issues of implementation significantly limit the potential impact of these systems on health outcomes. Existing linkages shown between implementation quality and health outcomes demonstrate the powerful impact of implementation science on sustainability. This paper assesses the extent to which implementation science is currently being used to implement drinking water interventions in LMIC. Methods: A literature review was conducted to determine if any study has directly used an implementation science approach. Finding no relevant articles, a second literature review was undertaken to determine which implementation outcomes are current being addressed in implementing these interventions. Implementation outcomes were translated to approximate their representation in drinking water system interventions. Results: Sixteen (n=16) studies show evidence of attention to implementation outcomes. Outcomes with the greatest representation in studies were Acceptability, Appropriateness and Adoption (81%-94%), while Penetration, Cost, Feasibility and Fidelity ranged from 25-63% representation. Sustainability was evaluated in 0% of studies. Discussion: The range of results shows that implementation outcomes are only partially integrated into this sector, to the detriment of achieving the Sustainable Development Goals. Resolving this gap will require a concentrated effort by both practitioners and researchers. Consequently, implementation outcomes are translated here into outcomes appropriate to drinking water system interventions, and a research agenda for the sector is proposed for the future inclusion of implementation science.Master of Public Healt

Exekutive Funktionen bei pädiatrischen, neuroonkologisch erkrankten PatientInnen

Ausgangslage: Aufgrund von Fortschritten in der Behandlung steigt die Überlebenschance pädiatrisch neuroonkologisch erkrankter Kinder und Jugendlicher. Daraus, sowie aus der Tatsache, dass für diese PatientInnen-Gruppe ein erhebliches Risiko für Beeinträchtigungen hinsichtlich der kognitiven Entwicklung besteht, ergeben sich v. a. im Bereich der neuropsychologischen Nachsorge neue Aufgaben. In der vorliegenden Arbeit soll auf den Bereich der Exekutiven Funktionen – welche eine weite Spanne an Verhaltenskompetenzen und kognitiven Prozessen umfasst - näher eingegangen werden. Einige Studien konnten zeigen, dass Störungen in diesem Bereich schwerwiegende Auswirkungen auf Aktivitäten des alltäglichen Lebens – u. a. Beeinträchtigungen in der Fähigkeit am Schulunterricht teilzunehmen – haben können (Grafman, Schwab, Warden, Pridgen, Grown & Salazar, 1996; Green, 1996). Ziel dieser Studie war es, kognitive Beeinträchtigungen, v. a. die der Exekutiven Funktionen bei Kindern mit Gehirntumoren darzustellen. Des Weiteren wurde das bislang nicht veröffentlichte „Verhaltensinventar Exekutiver Funktionen“ nach Drechsler einer Validierung unterzogen. Patienten und Methoden: Insgesamt wurden 59 Kinder mit Hirntumoren mit 15 gesunden Kindern hinsichtlich ausgewählter (Sub-)Tests neuropsychologischer Testverfahren mittels verschiedener statistischer Verfahren verglichen. Ergebnisse: Bei Betrachtung der verschiedenen Kennwerte der vorgegebenen Verfahren bzw. Fragebögen konnten signifikante Unterschiede festgestellt werden. So unterscheiden sich Kinder mit Gehirntumore hinsichtlich des Intelligenzquotienten signifikant zu den gesunden Kindern. In Anbetracht einzelner Komponenten Exekutiver Funktionen lassen sich signifikante Unterschiede bei verschiedenen (Unter-)Tests – TM, KITAP/ TAP, DSS ROCF, VLMT, VIEF – darstellen. Bezüglich der Validierung des „Verhaltensinventars Exekutiver Funktionen“ lassen sich Korrelationen mit explorativ zugeordneten konstruktnahen (Sub-)Tests aufdecken. Fazit: Aufgrund der Ergebnisse kann angenommen werden, dass pädiatrisch neuroonkologisch erkrankte Kinder und Jugendliche diverse kognitive Beeinträchtigungen – u. a. im Bereich der Exekutiven Funktionen – zeigen

Exile Vol. VII No. 2

EDITORIAL 4 The Catcher (woodcut) by Wilford Baumes 6 The Littlest Orphan (story) by Clark Blaise 7-17 Dead Tree (poem) by Christine Cooper 17 Two Poems by Janet Tallman 18-19 Untitled (pen and ink drawing) by Virginia Piersol 20 The Monkey (story) by Nancy Schieber 21-24 To Kandinsky (poem) by Linda Chase 24 Athena (line etching) by Virginia Piersol 25 Visions of Peanut Chocolates (poem) by Linda Chase 26 The Second Day of Summer (story) by Neil J. Weintraub 27-39 Great Exploitations (poem) by Linda Chase 40 Awarded the semi-annual EXILE-Denison Bookstore Writing Prize: The Littlest Orphan by Clark Blaise 7-1

Redox regulation of cell proliferation: Bioinformatics and redox proteomics approaches to identify redox-sensitive cell cycle regulators

Plant stem cells are the foundation of plant growth and development. The balance of quiescence and division is highly regulated, while ensuring that proliferating cells are protected from the adverse effects of environment fluctuations that may damage the genome. Redox regulation is important in both the activation of proliferation and arrest of the cell cycle upon perception of environmental stress. Within this context, reactive oxygen species serve as ‘pro-life’ signals with positive roles in the regulation of the cell cycle and survival. However, very little is known about the metabolic mechanisms and redox-sensitive proteins that influence cell cycle progression. We have identified cysteine residues on known cell cycle regulators in Arabidopsis that are potentially accessible, and could play a role in redox regulation, based on secondary structure and solvent accessibility likelihoods for each protein. We propose that redox regulation may function alongside other known posttranslational modifications to control the functions of core cell cycle regulators such as the retinoblastoma protein. Since our current understanding of how redox regulation is involved in cell cycle control is hindered by a lack of knowledge regarding both which residues are important and how modification of those residues alters protein function, we discuss how critical redox modifications can be mapped at the molecular level

A new process for the combined recovery of pectin and phenolic compounds from apple pomace», Innov Food Sci Emerg

Abstract A process for the combined recovery of pectin and phenolic compounds from apple pomace, the primary by-product of apple juice production, was developed. The process includes extraction of dried apple pomace with diluted mineral acid and adsorption of phenolic constituents by a hydrophobic styrene-divinylbenzene copolymerisate. After elution with methanol, the polyphenolics were concentrated in vacuo, stabilised by lyophilisation, and characterised by high-performance liquid chromatography. The predominant compounds were phloridzin, chlorogenic acid and quercetin glycosides. Adsorptive removal especially of oxidised phenolic compounds led to a considerable decolourisation of the pomace extracts, as revealed by determination of L*a*b* values, hue angle and chroma. Gelling properties of pectin were not adversely affected. While the polyphenolics recovered from apple pomace may be used as natural antioxidants or as functional food ingredients, extended fields of application may be obtained for decolorised, refined apple pectins. Furthermore, investigations on the phenolic composition of several New Zealand apple cultivars, of apple seeds, and on the effects of pomace drying on the stability of polyphenolics were carried out. ᮊ 2002 Elsevier Science Ltd. All rights reserved. Keywords: Apple pomace; Pectin; Phenolic Acids; Flavonoids; Adsorption Industrial relevance: Apple pomace is the primary by-product of apple juice production. Its use for further product recovery is an appropriate measure for economic reasons as well as from an environmental point of view. Apple pomace is being used successfully for pectin production and recent work regards it as rich source of polyphenols. Therefore, the main objective of this study was to establish a combined recovery process for pectins and polyphenols. A successful recovery process has been developed which can easily be integrated into existing pectin production processes. Scale-up has already been initiated. Further, purification of the phenolic fraction can lead to valuable natural antioxidants and antimicrobial food ingredients

A blood-based signature of cerebrospinal fluid Aβ1-42 status.

It is increasingly recognized that Alzheimer's disease (AD) exists before dementia is present and that shifts in amyloid beta occur long before clinical symptoms can be detected. Early detection of these molecular changes is a key aspect for the success of interventions aimed at slowing down rates of cognitive decline. Recent evidence indicates that of the two established methods for measuring amyloid, a decrease in cerebrospinal fluid (CSF) amyloid β1-42 (Aβ1-42) may be an earlier indicator of Alzheimer's disease risk than measures of amyloid obtained from Positron Emission Tomography (PET). However, CSF collection is highly invasive and expensive. In contrast, blood collection is routinely performed, minimally invasive and cheap. In this work, we develop a blood-based signature that can provide a cheap and minimally invasive estimation of an individual's CSF amyloid status using a machine learning approach. We show that a Random Forest model derived from plasma analytes can accurately predict subjects as having abnormal (low) CSF Aβ1-42 levels indicative of AD risk (0.84 AUC, 0.78 sensitivity, and 0.73 specificity). Refinement of the modeling indicates that only APOEε4 carrier status and four plasma analytes (CGA, Aβ1-42, Eotaxin 3, APOE) are required to achieve a high level of accuracy. Furthermore, we show across an independent validation cohort that individuals with predicted abnormal CSF Aβ1-42 levels transitioned to an AD diagnosis over 120 months significantly faster than those with predicted normal CSF Aβ1-42 levels and that the resulting model also validates reasonably across PET Aβ1-42 status (0.78 AUC). This is the first study to show that a machine learning approach, using plasma protein levels, age and APOEε4 carrier status, is able to predict CSF Aβ1-42 status, the earliest risk indicator for AD, with high accuracy

A blood-based signature of cerebrospinal fluid Aβ1-42 status.

It is increasingly recognized that Alzheimer's disease (AD) exists before dementia is present and that shifts in amyloid beta occur long before clinical symptoms can be detected. Early detection of these molecular changes is a key aspect for the success of interventions aimed at slowing down rates of cognitive decline. Recent evidence indicates that of the two established methods for measuring amyloid, a decrease in cerebrospinal fluid (CSF) amyloid β1-42 (Aβ1-42) may be an earlier indicator of Alzheimer's disease risk than measures of amyloid obtained from Positron Emission Tomography (PET). However, CSF collection is highly invasive and expensive. In contrast, blood collection is routinely performed, minimally invasive and cheap. In this work, we develop a blood-based signature that can provide a cheap and minimally invasive estimation of an individual's CSF amyloid status using a machine learning approach. We show that a Random Forest model derived from plasma analytes can accurately predict subjects as having abnormal (low) CSF Aβ1-42 levels indicative of AD risk (0.84 AUC, 0.78 sensitivity, and 0.73 specificity). Refinement of the modeling indicates that only APOEε4 carrier status and four plasma analytes (CGA, Aβ1-42, Eotaxin 3, APOE) are required to achieve a high level of accuracy. Furthermore, we show across an independent validation cohort that individuals with predicted abnormal CSF Aβ1-42 levels transitioned to an AD diagnosis over 120 months significantly faster than those with predicted normal CSF Aβ1-42 levels and that the resulting model also validates reasonably across PET Aβ1-42 status (0.78 AUC). This is the first study to show that a machine learning approach, using plasma protein levels, age and APOEε4 carrier status, is able to predict CSF Aβ1-42 status, the earliest risk indicator for AD, with high accuracy

Up to a Third of Renal Transplant Recipients Have Deficiencies in Cognitive Functioning

Introduction: Kidney transplantation is beneficial in improving cognitive abilities in patients with chronic kidney disease; however, there is still uncertainty concerning which cognitive domains benefit and to what extent. Aim: In the present study, cognitive functioning of renal transplant recipients was compared to normative data. Sociodemographic and clinical parameters that were associated with low cognitive performance were identified. Design: A total of 109 renal transplant recipients (63% men) participated in the study, with a mean age of 51.8 (standard deviation [SD] = 14.2) years. The cognitive test battery consisted of measurements assessing memory, attention, executive function, reproductive, and deductive ability. Results: In all tests, participants showed mean scores ranging within 1 SD of the population means. However, except for tests measuring memory, the percentage of participants scoring more than 1 SD below normed means was higher than expected in a normal distribution of performance. In certain tests, up to a third of the participants scored below average. Participants with continuous low performance (11%) showed higher age, poorer education, a longer time since transplantation, higher serum levels of urea and creatinine, and were more likely to have a deceased donor allograft. Discussion: Altough cognitive performance in renal transplant recipients matches normative data and confirms former findings, the amount of patients scoring more than 1 SD below average suggests that there are a considerable number of patients whose cognitive performance in certain domains lies below those of the general population. The identified sociodemographic and biochemical factors might be helpful to identify renal transplant recipients at risk