Postgraduate palliative care education: Evaluation of a South African programme

Aim. We aimed to assess the postgraduate palliative care distance education programme of the University of Cape Town (UCT) in terms of its perceived ability to influence palliative care delivery. Methods. A mixed-methods approach, consisting of two surveys using open-ended and multiple-choice options, was conducted from January - December 2007 at the UCT School of Public Health and Family Medicine. All students registered in the programme from 2000 - 2007 were invited to participate; 83 (66.4% of all eligible participants) completed the general survey, and 41 (65.7%) of the programme's graduates completed the graduate survey. The survey scores and open-ended data were triangulated to evaluate UCT’s palliative care postgraduate programme. Results. General survey scores of graduates were significantly higher in 5 of the 6 categories in comparison with current students. The graduate survey indicated that curriculum and teaching strengths were in communication and dealing with challenging encounters. Graduates also stressed the need to develop a curriculum that incorporated a practical component. Conclusions. In addition to current postgraduate training, palliative care education in South Africa should be extended to undergraduate medical students, as the benefits of UCT’s programme were limited to a small cohort of practitioners

Postgraduate Palliative care education: Evaluation of a South African Programme

AIM: We aimed to assess the postgraduate palliative care distance education programme of the University of Cape Town (UCT) in terms of its perceived ability to influence palliative care delivery. METHODS: A mixed-methods approach, consisting of two surveys using open-ended and multiple-choice options, was conducted from January to December 2007 at the UCT School of Public Health and Family Medicine. All students registered in the programme from 2000 - 2007 were invited to participate; 83 (66.4% of all eligible participants) completed the general survey, and 41 (65.7%) of the programme's graduates completed the graduate survey. The survey scores and open-ended data were triangulated to evaluate UCT's palliative care postgraduate programme. RESULTS: General survey scores of graduates were significantly higher in 5 of the 6 categories in comparison with current students. The graduate survey indicated that curriculum and teaching strengths were in communication and dealing with challenging encounters. Graduates also stressed the need to develop a curriculum that incorporated a practical component. CONCLUSIONS: In addition to current postgraduate training, palliative care education in South Africa should be extended to undergraduate medical students, as the benefits of UCT's programme were limited to a small cohort of practitioners

Metaviromic characterization of betaflexivirus populations associated with a Vitis cultivar collection in South Africa

DATA AVAILABILITY STATEMENT : All RNAseq datasets are available at National Center for Biotechnology Information’s (NCBI) Sequence Read Archive (SRA), accession PRJNA626577. All assembled sequences have been submitted to NCBI GenBank, listed in Table S1.SUPPLEMENTARY MATERIALS : FIGURE S1: RNA-dependent RNA polymerase (RdRP) gene phylogeny of GRSPaV variants; FIGURE S2: pairwise ANI values shared between GRSPaV variants; FIGURE S3: RNA-dependent RNA polymerase (RdRP) gene phylogeny of GVA variants; FIGURE S4: pairwise ANI values shared between GVA variants; FIGURE S5: RNA-dependent RNA polymerase (RdRP) gene phylogeny of GVB variants; FIGURE S6: pairwise ANI values shared between GVB variants; FIGURE S7: RNA-dependent RNA polymerase (RdRP) gene phylogeny of GVE variants; FIGURE S8: pairwise ANI values shared between GVE variants; FIGURE S9: RNA-dependent RNA polymerase (RdRP) gene phylogeny of GVF variants; FIGURE S10: pairwise ANI values shared between GVF variants; FIGURE S11: RNA-dependent RNA polymerase (RdRP) gene phylogeny of GVH variants; FIGURE S12: pairwise ANI values shared between GVH variants; FIGURE S13: RNA-dependent RNA polymerase (RdRP) gene phylogeny of GVI variants; FIGURE S14: pairwise ANI values shared between GVI variants; FIGURE S15: RNA-dependent RNA polymerase (RdRP) gene phylogeny of GVM variants; FIGURE S16: pairwise ANI values shared between GVM variants; TABLE S1: sample information, number of reads, and BioSample and GenBank accession numbers for each accession; TABLE S2: mixed infections for cultivar accessions with more than one betaflexivirus present.South Africa is associated with a centuries-old viticultural industry, accompanied by a diverse range of wine and table grape cultivars and an extensive history of pervasive introductions of vine material and associated viruses. The Vitis D2 collection in Stellenbosch represents the most comprehensive collection of Vitis species, hybrids, and cultivars in South Africa. We collected leaf petiole material from 229 accessions from this collection. Our metaviromic analyses revealed a total of 406 complete/near complete genomes of various betaflexiviruses. Among these, we identified the presence of grapevine rupestris stem pitting-associated virus and grapevine viruses A, B, E, F, H (GVH), I (GVI), and M (GVM). Notably, this study marks the first report of GVH, GVI, and GVM in South Africa, which were confirmed via RT-PCR. This research significantly contributes to our understanding of viral diversity and introductions in South African viticulture and emphasizes the need for vigilant monitoring and management of viral infections. Our findings lay the groundwork for strategies that mitigate the impact of viruses on South Africa’s wine industry, which generates an annual revenue of approximately 500 million USD.National Research Foundation (NRF) of South Africa.https://www.mdpi.com/journal/virusesam2024BiochemistryForestry and Agricultural Biotechnology Institute (FABI)GeneticsMicrobiology and Plant PathologySDG-15:Life on lan

Genotyping of Human Lice Suggests Multiple Emergences of Body Lice from Local Head Louse Populations

While being phenotypically and physiologically different, human head and body lice are indistinguishable based on mitochondrial and nuclear genes. As protein-coding genes are too conserved to provide significant genetic diversity, we performed strain-typing of a large collection of human head and body lice using variable intergenic spacer sequences. Ninety-seven human lice were classified into ninety-six genotypes based on four intergenic spacer sequences. Genotypic and phylogenetic analyses using these sequences suggested that human head and body lice are still indistinguishable. We hypothesized that the phenotypic and physiological differences between human head and body lice are controlled by very limited mutations. Under conditions of poor hygiene, head lice can propagate very quickly. Some of them will colonize clothing, producing a body louse variant (genetic or phenetic), which can lead to an epidemic. Lice collected in Rwanda and Burundi, where outbreaks of louse-borne diseases have been recently reported, are grouped tightly into a cluster and those collected from homeless people in France were also grouped into a cluster with lice collected in French non-homeless people. Our strain-typing approach based on highly variable intergenic spacers may be helpful to elucidate louse evolution and to survey louse-borne diseases

Soft Chemical Control of Superconductivity in Lithium Iron Selenide Hydroxides Li1–x_{1–x}Fex_x(OH)Fe1–y_{1–y}Se

Hydrothermal synthesis is described of layered lithium iron selenide hydroxides Li$_{1–x}$Fex(OH)Fe$_{1–y}$Se (x$\sim$0.2; 0.02 < $y$ < 0.15) with a wide range of iron site vacancy concentrations in the iron selenide layers. This iron vacancy concentration is revealed as the only significant compositional variable and as the key parameter controlling the crystal structure and the electronic properties. Single crystal X-ray diffraction, neutron powder diffraction, and X-ray absorption spectroscopy measurements are used to demonstrate that superconductivity at temperatures as high as 40 K is observed in the hydrothermally synthesized samples when the iron vacancy concentration is low ($y$ < 0.05) and when the iron oxidation state is reduced slightly below +2, while samples with a higher vacancy concentration and a correspondingly higher iron oxidation state are not superconducting. The importance of combining a low iron oxidation state with a low vacancy concentration in the iron selenide layers is emphasized by the demonstration that reductive postsynthetic lithiation of the samples turns on superconductivity with critical temperatures exceeding 40 K by displacing iron atoms from the Li$_{1–x}$Fe$_x$(OH) reservoir layer to fill vacancies in the selenide layer

Graz. Schloßberg.

Blick zum Schloßberg mit Hauptbrück

Validation of the Body Concealment Scale for Scleroderma (BCSS): Replication in the Scleroderma Patient-centered Intervention Network (SPIN) Cohort

© 2016 Elsevier Ltd Body concealment is an important component of appearance distress for individuals with disfiguring conditions, including scleroderma. The objective was to replicate the validation study of the Body Concealment Scale for Scleroderma (BCSS) among 897 scleroderma patients. The factor structure of the BCSS was evaluated using confirmatory factor analysis and the Multiple-Indicator Multiple-Cause model examined differential item functioning of SWAP items for sex and age. Internal consistency reliability was assessed via Cronbach's alpha. Construct validity was assessed by comparing the BCSS with a measure of body image distress and measures of mental health and pain intensity. Results replicated the original validation study, where a bifactor model provided the best fit. The BCSS demonstrated strong internal consistency reliability and construct validity. Findings further support the BCSS as a valid measure of body concealment in scleroderma and provide new evidence that scores can be compared and combined across sexes and ages

Principal component analysis as an efficient method for capturing multivariate brain signatures of complex disorders—ENIGMA study in people with bipolar disorders and obesity

Multivariate techniques better fit the anatomy of complex neuropsychiatric disorders which are characterized not by alterations in a single region, but rather by variations across distributed brain networks. Here, we used principal component analysis (PCA) to identify patterns of covariance across brain regions and relate them to clinical and demographic variables in a large generalizable dataset of individuals with bipolar disorders and controls. We then compared performance of PCA and clustering on identical sample to identify which methodology was better in capturing links between brain and clinical measures. Using data from the ENIGMA-BD working group, we investigated T1-weighted structural MRI data from 2436 participants with BD and healthy controls, and applied PCA to cortical thickness and surface area measures. We then studied the association of principal components with clinical and demographic variables using mixed regression models. We compared the PCA model with our prior clustering analyses of the same data and also tested it in a replication sample of 327 participants with BD or schizophrenia and healthy controls. The first principal component, which indexed a greater cortical thickness across all 68 cortical regions, was negatively associated with BD, BMI, antipsychotic medications, and age and was positively associated with Li treatment. PCA demonstrated superior goodness of fit to clustering when predicting diagnosis and BMI. Moreover, applying the PCA model to the replication sample yielded significant differences in cortical thickness between healthy controls and individuals with BD or schizophrenia. Cortical thickness in the same widespread regional network as determined by PCA was negatively associated with different clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. PCA outperformed clustering and provided an easy-to-use and interpret method to study multivariate associations between brain structure and system-level variables. Practitioner Points: In this study of 2770 Individuals, we confirmed that cortical thickness in widespread regional networks as determined by principal component analysis (PCA) was negatively associated with relevant clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. Significant associations of many different system-level variables with the same brain network suggest a lack of one-to-one mapping of individual clinical and demographic factors to specific patterns of brain changes. PCA outperformed clustering analysis in the same data set when predicting group or BMI, providing a superior method for studying multivariate associations between brain structure and system-level variables.</p

Principal component analysis as an efficient method for capturing multivariate brain signatures of complex disorders—ENIGMA study in people with bipolar disorders and obesity

Multivariate techniques better fit the anatomy of complex neuropsychiatric disorders which are characterized not by alterations in a single region, but rather by variations across distributed brain networks. Here, we used principal component analysis (PCA) to identify patterns of covariance across brain regions and relate them to clinical and demographic variables in a large generalizable dataset of individuals with bipolar disorders and controls. We then compared performance of PCA and clustering on identical sample to identify which methodology was better in capturing links between brain and clinical measures. Using data from the ENIGMA-BD working group, we investigated T1-weighted structural MRI data from 2436 participants with BD and healthy controls, and applied PCA to cortical thickness and surface area measures. We then studied the association of principal components with clinical and demographic variables using mixed regression models. We compared the PCA model with our prior clustering analyses of the same data and also tested it in a replication sample of 327 participants with BD or schizophrenia and healthy controls. The first principal component, which indexed a greater cortical thickness across all 68 cortical regions, was negatively associated with BD, BMI, antipsychotic medications, and age and was positively associated with Li treatment. PCA demonstrated superior goodness of fit to clustering when predicting diagnosis and BMI. Moreover, applying the PCA model to the replication sample yielded significant differences in cortical thickness between healthy controls and individuals with BD or schizophrenia. Cortical thickness in the same widespread regional network as determined by PCA was negatively associated with different clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. PCA outperformed clustering and provided an easy-to-use and interpret method to study multivariate associations between brain structure and system-level variables. Practitioner Points: In this study of 2770 Individuals, we confirmed that cortical thickness in widespread regional networks as determined by principal component analysis (PCA) was negatively associated with relevant clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. Significant associations of many different system-level variables with the same brain network suggest a lack of one-to-one mapping of individual clinical and demographic factors to specific patterns of brain changes. PCA outperformed clustering analysis in the same data set when predicting group or BMI, providing a superior method for studying multivariate associations between brain structure and system-level variables.</p