Attributes of the turnaround CEO in South Africa

A high rate of turnaround failures is often blamed on leadership. This dissertation places the focus on the turnaround CEO in South Africa and determines the attributes of such an individual. This is a qualitative research project and the data has been sourced via in-depth interviews, conducted with business leaders who have had decades of experience at executive level. The research showed that there is a list of 10 attributes that can be considered as the essential attributes of a turnaround CEO. In addition there are a plethora of attributes that can be seen as enhancing or distinguishing. Within a South African context, distinguishing attributes are required in order to deal with issues mainly originating from historical inequalities. Some attributes relate to Black Economic Empowerment, labour legislation as well as an acute awareness of the history of the country and in particular how it has influenced the working environment post 1994 – including the possibility that we may, as a result, be cultivating soft managers. In addition people in SA are seen to be more open to change than other nationalities. However, the research has shown that in a turnaround situation the “South Africa – specific” factors are considered to be extraneous and the skills required in dealing with them are not regarded as essential, but rather as distinguishing attributes that play a role once a business has been saved from closure and control has been reinstated.Dissertation (MBA)--University of Pretoria, 2010.Gordon Institute of Business Science (GIBS)unrestricte

Preparing for Life: Plasma Proteome Changes and Immune System Development During the First Week of Human Life.

Neonates have heightened susceptibility to infections. The biological mechanisms are incompletely understood but thought to be related to age-specific adaptations in immunity due to resource constraints during immune system development and growth. We present here an extended analysis of our proteomics study of peripheral blood-plasma from a study of healthy full-term newborns delivered vaginally, collected at the day of birth and on day of life (DOL) 1, 3, or 7, to cover the first week of life. The plasma proteome was characterized by LC-MS using our established 96-well plate format plasma proteomics platform. We found increasing acute phase proteins and a reduction of respective inhibitors on DOL1. Focusing on the complement system, we found increased plasma concentrations of all major components of the classical complement pathway and the membrane attack complex (MAC) from birth onward, except C7 which seems to have near adult levels at birth. In contrast, components of the lectin and alternative complement pathways mainly decreased. A comparison to whole blood messenger RNA (mRNA) levels enabled characterization of mRNA and protein levels in parallel, and for 23 of the 30 monitored complement proteins, the whole blood transcript information by itself was not reflective of the plasma protein levels or dynamics during the first week of life. Analysis of immunoglobulin (Ig) mRNA and protein levels revealed that IgM levels and synthesis increased, while the plasma concentrations of maternally transferred IgG1-4 decreased in accordance with their in vivo half-lives. The neonatal plasma ratio of IgG1 to IgG2-4 was increased compared to adult values, demonstrating a highly efficient IgG1 transplacental transfer process. Partial compensation for maternal IgG degradation was achieved by endogenous synthesis of the IgG1 subtype which increased with DOL. The findings were validated in a geographically distinct cohort, demonstrating a consistent developmental trajectory of the newborn's immune system over the first week of human life across continents. Our findings indicate that the classical complement pathway is central for newborn immunity and our approach to characterize the plasma proteome in parallel with the transcriptome will provide crucial insight in immune ontogeny and inform new approaches to prevent and treat diseases

Heritability of fractional anisotropy in human white matter: a comparison of Human Connectome Project and ENIGMA-DTI data

The degree to which genetic factors influence brain connectivity is beginning to be understood. Large-scale efforts are underway to map the profile of genetic effects in various brain regions. The NIH-funded Human Connectome Project (HCP) is providing data valuable for analyzing the degree of genetic influence underlying brain connectivity revealed by state-of-the-art neuroimaging methods. We calculated the heritability of the fractional anisotropy (FA) measure derived from diffusion tensor imaging (DTI) reconstruction in 481 HCP subjects (194/287 M/F) consisting of 57/60 pairs of mono- and dizygotic twins, and 246 siblings. FA measurements were derived using (Enhancing NeuroImaging Genetics through Meta-Analysis) ENIGMA DTI protocols and heritability estimates were calculated using the SOLAR-Eclipse imaging genetic analysis package. We compared heritability estimates derived from HCP data to those publicly available through the ENIGMA-DTI consortium, which were pooled together from five-family based studies across the US, Europe, and Australia. FA measurements from the HCP cohort for eleven major white matter tracts were highly heritable (h2 = 0.53–0.90, p < 10− 5), and were significantly correlated with the joint-analytical estimates from the ENIGMA cohort on the tract and voxel-wise levels. The similarity in regional heritability suggests that the additive genetic contribution to white matter microstructure is consistent across populations and imaging acquisition parameters. It also suggests that the overarching genetic influence provides an opportunity to define a common genetic search space for future gene-discovery studies. Uniquely, the measurements of additive genetic contribution performed in this study can be repeated using online genetic analysis tools provided by the HCP ConnectomeDB web application

Susceptibility to COPD:Differential Proteomic Profiling after Acute Smoking

Cigarette smoking is the main risk factor for COPD (Chronic Obstructive Pulmonary Disease), yet only a subset of smokers develops COPD. Family members of patients with severe early-onset COPD have an increased risk to develop COPD and are therefore defined as "susceptible individuals". Here we perform unbiased analyses of proteomic profiles to assess how "susceptible individuals" differ from age-matched "non-susceptible individuals" in response to cigarette smoking. Epithelial lining fluid (ELF) was collected at baseline and 24 hours after smoking 3 cigarettes in young individuals susceptible or non-susceptible to develop COPD and older subjects with established COPD. Controls at baseline were older healthy smoking and non-smoking individuals. Five samples per group were pooled and analysed by stable isotope labelling (iTRAQ) in duplicate. Six proteins were selected and validated by ELISA or immunohistochemistry. After smoking, 23 proteins increased or decreased in young susceptible individuals, 7 in young non-susceptible individuals, and 13 in COPD in the first experiment; 23 proteins increased or decreased in young susceptible individuals, 32 in young non-susceptible individuals, and 11 in COPD in the second experiment. SerpinB3 and Uteroglobin decreased after acute smoke exposure in young non-susceptible individuals exclusively, whereas Peroxiredoxin I, S100A9, S100A8, ALDH3A1 (Aldehyde dehydrogenase 3A1) decreased both in young susceptible and non-susceptible individuals, changes being significantly different between groups for Uteroglobin with iTRAQ and for Serpin B3 with iTRAQ and ELISA measures. Peroxiredoxin I, SerpinB3 and ALDH3A1 increased in COPD patients after smoking. We conclude that smoking induces a differential protein response in ELF of susceptible and non-susceptible young individuals, which differs from patients with established COPD. This is the first study applying unbiased proteomic profiling to unravel the underlying mechanisms that induce COPD. Our data suggest that SerpinB3 and Uteroglobin could be interesting proteins in understanding the processes leading to COPD

Study protocol: EXERcise and Cognition In Sedentary adults with Early-ONset dementia (EXERCISE-ON)

<p>Abstract</p> <p>Background</p> <p>Although the development of early-onset dementia is a radical and invalidating experience for both patient and family there are hardly any non-pharmacological studies that focus on this group of patients. One type of a non-pharmacological intervention that appears to have a beneficial effect on cognition in older persons without dementia and older persons at risk for dementia is exercise. In view of their younger age early-onset dementia patients may be well able to participate in an exercise program. The main aim of the EXERCISE-ON study is to assess whether exercise slows down the progressive course of the symptoms of dementia.</p> <p>Methods/Design</p> <p>One hundred and fifty patients with early-onset dementia are recruited. After completion of the baseline measurements, participants living within a 50 kilometre radius to one of the rehabilitation centres are randomly assigned to either an <it>aerobic exercise program in a rehabilitation centre</it> or a <it>flexibility and relaxation program in a rehabilitation centre</it>. Both programs are applied three times a week during 3 months. Participants living outside the 50 kilometre radius are included in a feasibility study where participants join in a <it>daily physical activity program set at home making use of pedometers</it>. Measurements take place at baseline (entry of the study), after three months (end of the exercise program) and after six months (follow-up). Primary outcomes are cognitive functioning; psychomotor speed and executive functioning; (instrumental) activities of daily living, and quality of life. Secondary outcomes include physical, neuropsychological, and rest-activity rhythm measures.</p> <p>Discussion</p> <p>The EXERCISE-ON study is the first study to offer exercise programs to patients with early-onset dementia. We expect this study to supply evidence regarding the effects of exercise on the symptoms of early-onset dementia, influencing quality of life.</p> <p>Trial registration</p> <p>The present study is registered within The Netherlands National Trial Register (ref: NTR2124)</p

Medical conditions at enrollment do not impact efficacy and safety of the adjuvanted recombinant zoster vaccine:a pooled post-hoc analysis of two parallel randomized trials

In two pivotal efficacy studies (ZOE-50; ZOE-70), the adjuvanted recombinant zoster vaccine (RZV) demonstrated >90% efficacy against herpes zoster (HZ). Adults aged ≥50 or ≥70 years (ZOE-50 [NCT01165177]; ZOE-70 [NCT01165229]) were randomized to receive 2 doses of RZV or placebo 2 months apart. Vaccine efficacy and safety were evaluated post-hoc in the pooled (ZOE-50/70) population according to the number and type of selected medical conditions present at enrollment. At enrollment, 82.3% of RZV and 82.7% of placebo recipients reported ≥1 of the 15 selected medical conditions. Efficacy against HZ ranged from 84.5% (95% Confidence Interval [CI]: 46.4–97.1) in participants with respiratory disorders to 97.0% (95%CI: 82.3–99.9) in those with coronary heart disease. Moreover, efficacy remained >90% irrespective of the number of selected medical conditions reported by a participant. As indicated by the similarity of the point estimates, this post-hoc analysis suggests that RZV efficacy remains high in all selected medical conditions, as well as with increasing number of medical conditions. No safety concern was identified by the type or number of medical conditions present at enrollment

Corrigendum: Clinical Protocol for a Longitudinal Cohort Study Employing Systems Biology to Identify Markers of Vaccine Immunogenicity in Newborn Infants in The Gambia and Papua New Guinea.

[This corrects the article DOI: 10.3389/fped.2020.00197.]

Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury

Objective: We aimed to explore the added value of common machine learning (ML) algorithms for prediction of outcome for moderate and severe traumatic brain injury. Study Design and Setting: We performed logistic regression (LR), lasso regression, and ridge regression with key baseline predictors in the IMPACT-II database (15 studies, n = 11,022). ML algorithms included support vector machines, random forests, gradient boosting machines, and artificial neural networks and were trained using the same predictors. To assess generalizability of predictions, we performed internal, internal-external, and external validation on the recent CENTER-TBI study (patients with Glasgow Coma Scale <13, n = 1,554). Both calibration (calibration slope/intercept) and discrimination (area under the curve) was quantified. Results: In the IMPACT-II database, 3,332/11,022 (30%) died and 5,233(48%) had unfavorable outcome (Glasgow Outcome Scale less than 4). In the CENTER-TBI study, 348/1,554(29%) died and 651(54%) had unfavorable outcome. Discrimination and calibration varied widely between the studies and less so between the studied algorithms. The mean area under the curve was 0.82 for mortality and 0.77 for unfavorable outcomes in the CENTER-TBI study. Conclusion: ML algorithms may not outperform traditional regression approaches in a low-dimensional setting for outcome prediction after moderate or severe traumatic brain injury. Similar to regression-based prediction models, ML algorithms should be rigorously validated to ensure applicability to new populations