Body weight changes and incidence of cachexia after stroke

Background: Body weight loss is a frequent complication after stroke, and its adverse effect on clinical outcome has been shown in several clinical trials. The purpose of this prospective longitudinal single-centre observational study was to investigate dynamical changes of body composition and body weight after ischemic stroke and an association with functional outcome. Methods: Sixty-seven consecutive patients (age 69 ± 11 years, body mass index 27.0 ± 4.1 kg/m2, 42% female patient, mean ± SD) with acute ischemic stroke with mild to moderate neurological deficit (National Institute of Health Stroke Scale median 4, ranged 0–12) were analysed in the acute phase (4 ± 2 days) and at 12 months (389 ± 26 days) follow-up. Body composition was examined by dual energy X-ray absorptiometry. Cachexia was defined according to the consensus definition by body weight loss ≥5% within 1 year and additional clinical signs. Lean tissue wasting was considered if a ratio of upper and lower limbs lean mass sum to squared height (kg/m2) was ≤5.45 kg/m2 for female patient and ≤7.25 kg/m2 for male patient. Results: According to the body weight changes after 12 months, 42 (63%) patients had weight gain or stable weight, 11 (16%) patients had moderate weight loss, and 14 (21%) patients became cachectic. A relative decline of 19% of fat tissue and 6.5% of lean tissue was observed in cachectic patients, while no changes of lean tissue were observed in non-cachectic patients after 12 months. The modified Rankin Scale was 48% higher (2.1 ± 1.6, P < 0.05), Barthel Index was 22% lower (71 ± 39, P < 0.01), and handgrip strength was 34% lower (21.9 ± 13.0, P < 0.05) in cachectic compared to non-cachectic patients after 12 months. The low physical performance if defined by Barthel Index <60 points was linked to the lean tissue wasting (OR 44.8, P < 0.01), presence of cachexia (OR 20.8, P < 0.01), and low body mass index <25 kg/m2 (OR 11.5, P < 0.05). After adjustment for cofounders, lean tissue wasting remained independently associated with the low physical performance at 12 months follow-up (OR 137.9, P < 0.05). Conclusions: In this cohort study, every fifth patient with ischemic stroke fulfilled the criteria of cachexia within 12 months after index event. The incidence of cachexia was 21%. Cachectic patients showed the lowest functional and physical capacity

Integrase-deficient lentiviral vectors mediate efficient gene transfer to human vascular smooth muscle cells with minimal genotoxic risk

We have previously shown that injury-induced neointima formation was rescued by adenoviral-Nogo-B gene delivery. Integrase-competent lentiviral vectors (ICLV) are efficient at gene delivery to vascular cells but present a risk of insertional mutagenesis. Conversely, integrase-deficient lentiviral vectors (IDLV) offer additional benefits through reduced mutagenesis risk, but this has not been evaluated in the context of vascular gene transfer. Here, we have investigated the performance and genetic safety of both counterparts in primary human vascular smooth muscle cells (VSMC) and compared gene transfer efficiency and assessed the genotoxic potential of ICLVs and IDLVs based on their integration frequency and insertional profile in the human genome. Expression of enhanced green fluorescent protein (eGFP) mediated by IDLVs (IDLV-eGFP) demonstrated efficient transgene expression in VSMCs. IDLV gene transfer of Nogo-B mediated efficient overexpression of Nogo-B in VSMCs, leading to phenotypic effects on VSMC migration and proliferation, similar to its ICLV version and unlike its eGFP control and uninfected VSMCs. Large-scale integration site analyses in VSMCs indicated that IDLV-mediated gene transfer gave rise to a very low frequency of genomic integration compared to ICLVs, revealing a close-to-random genomic distribution in VSMCs. This study demonstrates for the first time the potential of IDLVs for safe and efficient vascular gene transfer

Projections of epidemic transmission and estimation of vaccination impact during an ongoing Ebola virus disease outbreak in Northeastern Democratic Republic of Congo, as of Feb. 25, 2019.

BackgroundAs of February 25, 2019, 875 cases of Ebola virus disease (EVD) were reported in North Kivu and Ituri Provinces, Democratic Republic of Congo. Since the beginning of October 2018, the outbreak has largely shifted into regions in which active armed conflict has occurred, and in which EVD cases and their contacts have been difficult for health workers to reach. We used available data on the current outbreak, with case-count time series from prior outbreaks, to project the short-term and long-term course of the outbreak.MethodsFor short- and long-term projections, we modeled Ebola virus transmission using a stochastic branching process that assumes gradually quenching transmission rates estimated from past EVD outbreaks, with outbreak trajectories conditioned on agreement with the course of the current outbreak, and with multiple levels of vaccination coverage. We used two regression models to estimate similar projection periods. Short- and long-term projections were estimated using negative binomial autoregression and Theil-Sen regression, respectively. We also used Gott's rule to estimate a baseline minimum-information projection. We then constructed an ensemble of forecasts to be compared and recorded for future evaluation against final outcomes. From August 20, 2018 to February 25, 2019, short-term model projections were validated against known case counts.ResultsDuring validation of short-term projections, from one week to four weeks, we found models consistently scored higher on shorter-term forecasts. Based on case counts as of February 25, the stochastic model projected a median case count of 933 cases by February 18 (95% prediction interval: 872-1054) and 955 cases by March 4 (95% prediction interval: 874-1105), while the auto-regression model projects median case counts of 889 (95% prediction interval: 876-933) and 898 (95% prediction interval: 877-983) cases for those dates, respectively. Projected median final counts range from 953 to 1,749. Although the outbreak is already larger than all past Ebola outbreaks other than the 2013-2016 outbreak of over 26,000 cases, our models do not project that it is likely to grow to that scale. The stochastic model estimates that vaccination coverage in this outbreak is lower than reported in its trial setting in Sierra Leone.ConclusionsOur projections are concentrated in a range up to about 300 cases beyond those already reported. While a catastrophic outbreak is not projected, it is not ruled out, and prevention and vigilance are warranted. Prospective validation of our models in real time allowed us to generate more accurate short-term forecasts, and this process may prove useful for future real-time short-term forecasting. We estimate that transmission rates are higher than would be seen under target levels of 62% coverage due to contact tracing and vaccination, and this model estimate may offer a surrogate indicator for the outbreak response challenges

Affective Experiences of International and Home Students during the Information Search Process

An increasing number of students are studying abroad requiring that they interact with information in languages other than their mother tongue. The UK in particular has seen a large growth in international students within Higher Education. These non-native English speaking students present a distinct user group for university information services, such as university libraries. This article presents the findings from an in-depth study to understand differences between the search processes of home and international students. Data were collected using an online survey and diary-interview to capture thoughts and feelings in a more naturalistic way. International students are found to have similar information search processes to those of home students, but sometimes face additional difficulties in assessing search results such as confusion when dealing with differing cultural perspectives. The potential implications for information service providers, particularly university libraries, are discussed, such as providing assistance to students for identifying appropriate English sources

Neurological, Cognitive, and Psychological Findings Among Survivors of Ebola Virus Disease From the 1995 Ebola Outbreak in Kikwit, Democratic Republic of Congo: A Cross-sectional Study.

BackgroundClinical sequelae of Ebola virus disease (EVD) have not been described more than 3 years postoutbreak. We examined survivors and close contacts from the 1995 Ebola outbreak in Kikwit, Democratic Republic of Congo (DRC), and determined prevalence of abnormal neurological, cognitive, and psychological findings and their association with EVD survivorship.MethodsFrom August to September 2017, we conducted a cross-sectional study in Kikwit, DRC. Over 2 decades after the EVD outbreak, we recruited EVD survivors and close contacts from the outbreak to undergo physical examination and culturally adapted versions of the Folstein mini-mental status exam (MMSE) and Goldberg anxiety and depression scale (GADS). We estimated the strength of relationships between EVD survivorship and health outcomes using linear regression models by comparing survivors versus close contacts, adjusting for age, sex, educational level, marital status, and healthcare worker status.ResultsWe enrolled 20 EVD survivors and 187 close contacts. Among the 20 EVD survivors, 4 (20%) reported at least 1 abnormal neurological symptom, and 3 (15%) had an abnormal neurological examination. Among the 187 close contacts, 14 (11%) reported at least 1 abnormal neurologic symptom, and 9 (5%) had an abnormal neurological examination. EVD survivors had lower mean MMSE and higher mean GADS scores as compared to close contacts (MMSE: adjusted coefficient: -1.85; 95% confidence interval [CI]: -3.63, -0.07; GADS: adjusted coefficient: 3.91; 95% CI: 1.76, 6.04).ConclusionsEVD survivors can have lower cognitive scores and more symptoms of depression and anxiety than close contacts more than 2 decades after Ebola virus outbreaks

Projections of Ebola outbreak size and duration with and without vaccine use in Équateur, Democratic Republic of Congo, as of May 27, 2018.

As of May 27, 2018, 6 suspected, 13 probable and 35 confirmed cases of Ebola virus disease (EVD) had been reported in Équateur Province, Democratic Republic of Congo. We used reported case counts and time series from prior outbreaks to estimate the total outbreak size and duration with and without vaccine use. We modeled Ebola virus transmission using a stochastic branching process model that included reproduction numbers from past Ebola outbreaks and a particle filtering method to generate a probabilistic projection of the outbreak size and duration conditioned on its reported trajectory to date; modeled using high (62%), low (44%), and zero (0%) estimates of vaccination coverage (after deployment). Additionally, we used the time series for 18 prior Ebola outbreaks from 1976 to 2016 to parameterize the Thiel-Sen regression model predicting the outbreak size from the number of observed cases from April 4 to May 27. We used these techniques on probable and confirmed case counts with and without inclusion of suspected cases. Probabilistic projections were scored against the actual outbreak size of 54 EVD cases, using a log-likelihood score. With the stochastic model, using high, low, and zero estimates of vaccination coverage, the median outbreak sizes for probable and confirmed cases were 82 cases (95% prediction interval [PI]: 55, 156), 104 cases (95% PI: 58, 271), and 213 cases (95% PI: 64, 1450), respectively. With the Thiel-Sen regression model, the median outbreak size was estimated to be 65.0 probable and confirmed cases (95% PI: 48.8, 119.7). Among our three mathematical models, the stochastic model with suspected cases and high vaccine coverage predicted total outbreak sizes closest to the true outcome. Relatively simple mathematical models updated in real time may inform outbreak response teams with projections of total outbreak size and duration

Identifying Community-Engaged Translational Research Collaboration Experience and Health Interests of Community-Based Organizations Outside of Metropolitan Atlanta

Background: While rural health research has increased over the last two decades, there is limited understanding of the self-reported health priorities and research interests of rural and suburban community-based representatives and residents. These insights can be used to inform more successful intervention strategies that are responsive to the lived experiences of local residents and leaders who are the gatekeepers to buy-in and sustainability of community engaged research. The Georgia Clinical and Translational Science Alliance, a collaboration between four academic institutions includes a Community Engagement Program (CE) designed to facilitate community-academic research partnerships. This study aimed to assess the health priorities, community-academic research experience, and interests of community respondents outside of Metropolitan Atlanta through the Community Engagement Facilitation Survey (CEFS). Methods: CE Program and Community Steering Board created the CEFS to assess the health topic priorities, research experience, and interests of community-based representatives and community members across the state of Georgia. The 11-item survey was administered (paper and electronic surveys) statewide at community events and professional organization meetings. Descriptive statistics were analyzed, and geospatial mapping was conducted. Data were analyzed in SPSS and Microsoft Excel software systems to clean data and to calculate data counts and percentages. Three maps were created in Tableau Version 19.2 depicting all counties represented by the survey sample superimposed with the counties from which at least one respondent indicated each of the top three health priorities for this sample. Results: Four-hundred six (406) surveys were analyzed, representing 83.6% of rural and suburban Georgia counties. The most frequently identified health priorities and research interests were diabetes, cancer, high blood pressure, and mental health