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Abstract Objective Prior research has shown strong evidence of spatial clustering of tuberculosis across a range of contexts. Identifying the spatial patterning of infectious diseases such as tuberculosis is crucial as it allows for targeted intervention strategies, directing healthcare resources efficiently to areas where tuberculosis incidence is concentrated. This is especially true for low- and middle-income countries that typically experience greater resource constraints relative to their Global North counterparts. In this study, we extend existing literature by investigating the spatial patterning of tuberculosis among vulnerable communities in South Africa, notably in the relatively under-researched provinces of the North-West and Gauteng. Results Data for this study were collected from several locations implementing community-oriented primary care in the country. Community health workers used AitaHealth™, a custom-built mobile information management application, to obtain data on tuberculosis status and environmental conditions of households. We find notable clusters of tuberculosis in these provinces which we speculate could be associated with urban formal and informal settlement densification and overcrowding, the incidence of mining activities prevalent in sampled locations and poor access to healthcare.

Abstract Background This is a study of service provider perceptions of the place, role and practices of CHWs in a four-year, large-scale private sector funded, public service ICT-enabled COPC intervention with rural and remote mining communities. Like all South African communities, apart from large mining house employees and some contractors, most people use available public healthcare services and private traditional as well as limited allopathic private sector providers. In addition to the limitations of facility centred primary healthcare and a fragmented health care system, the many negative health effects of mining on the communities, go unattended. Methods This is a rapid, qualitative pragmatic study. Using site and participation convenience sampling, 37 semi-structured individual or group interviews were conducted with 57 stakeholders from 38 of the 135 intervention PHC facilities. Using a data driven, inductive approach, the results were analysed thematically in terms of perceived changes in the role and place of CHWs. Results CHWs registered 42 490 households and captured the demographic and social profiles as well as the health status of over 154 910 individuals using AitaHealth™. These data provided healthcare professionals and managers with knowledge about community demographics, at-risk groups and vulnerable individuals. The intervention changed the locational focus of CHW practice and expanded their scope of work and competencies in household comprehensive health education, advice and care. It led to a growth in community and professional confidence in CHWs as trusted members of mining community PHC teams and to more focused and efficient clinic work. Conclusion This ICT-enabled COPC intervention adopted a comprehensive approach to healthcare delivery that started by including CHWs in PHC teams and locating them in communities. Inclusive and systematic continuous learning, clinically-led CHW service support and ICT-enabled information technology engendered trust in CHWs as competent PHC members, and grew community confidence in them and the PHC system as a whole. Although health, care and other professionals and workers valued the changes the intervention brought to their work as well as people’s lives in underserved and vulnerable mining communities, its sustainability is contingent on the vagaries of political will and financial commitment.

Abstract Alzheimer’s disease (AD) is associated with heterogeneous atrophy patterns. We employed a semi-supervised representation learning technique known as Surreal-GAN, through which we identified two latent dimensional representations of brain atrophy in symptomatic mild cognitive impairment (MCI) and AD patients: the “diffuse-AD” (R1) dimension shows widespread brain atrophy, and the “MTL-AD” (R2) dimension displays focal medial temporal lobe (MTL) atrophy. Critically, only R2 was associated with widely known sporadic AD genetic risk factors (e.g., APOE ε4) in MCI and AD patients at baseline. We then independently detected the presence of the two dimensions in the early stages by deploying the trained model in the general population and two cognitively unimpaired cohorts of asymptomatic participants. In the general population, genome-wide association studies found 77 genes unrelated to APOE differentially associated with R1 and R2. Functional analyses revealed that these genes were overrepresented in differentially expressed gene sets in organs beyond the brain (R1 and R2), including the heart (R1) and the pituitary gland, muscle, and kidney (R2). These genes were enriched in biological pathways implicated in dendritic cells (R2), macrophage functions (R1), and cancer (R1 and R2). Several of them were “druggable genes” for cancer (R1), inflammation (R1), cardiovascular diseases (R1), and diseases of the nervous system (R2). The longitudinal progression showed that APOE ε4, amyloid, and tau were associated with R2 at early asymptomatic stages, but this longitudinal association occurs only at late symptomatic stages in R1. Our findings deepen our understanding of the multifaceted pathogenesis of AD beyond the brain. In early asymptomatic stages, the two dimensions are associated with diverse pathological mechanisms, including cardiovascular diseases, inflammation, and hormonal dysfunction—driven by genes different from APOE—which may collectively contribute to the early pathogenesis of AD. All results are publicly available at https://labs-laboratory.com/medicine/ .

Objectives: Pulse oximetry screening of newborns detects critical congenital heart disease (CCHD). Rural birth location is known to affect timing and management of when infants with CHD undergo surgery, but its association with CCHD screening is unknown. We assess the relationship between rural location and postnatal CCHD diagnosis and describe lesion-specific modes of diagnosis. Study design: Data were abstracted from medical records at 2 cardiac surgery centers in Washington state. Infants with CCHD, defined as CHD requiring either cardiac intervention or resulting in death at

Context: India’s lean cadre of 250,000 general practitioners and 30,000 government doctors has limited options to update themselves. Since 2006, Christian Medical College (CMC) Vellore has run blended-learning programs in family medicine, namely, postgraduate diploma in family medicine (PGDFM) and master in medicine in family medicine (M.MED FM) training more than 3000 doctors. A graduate follow-up study was undertaken in 2022. Aim: The aim of the study was to describe the socio-demographic characteristics of family physicians (FPs) in India who graduated between 2008 and 2018 from the FM blended-learning programs run by the CMC, Vellore. Settings and Design: Informed by an empirical-analytic paradigm, this descriptive study used a cross-sectional survey design to uncover graduate FPs’ profiles, practices and experiences. Methods and Materials: Using a purposively designed, piloted and validated electronic questionnaire, data were collected between March and July 2022, deidentified and analysed using Statistical Package for Social Sciences (SPSS)TM and Epi InfoTM. Results: Among the 438 FP respondents (36%), there was an almost even split in gender (49.3% male, 50.7% female). Moreover, 25.8% were below the age of 40 years, 37.4% were in the 40–49 age group, and 33.8% were 50 years of age or older; 86% lived and worked in urban areas. The PGDFM or M.MED FM was the highest educational qualification of 64.4% of the doctors. Male FPs pursued postgraduate studies at a significantly younger age and earned significantly more than their female counterparts. Conclusions: The blended learning model creates an important pathway for doctors, especially women, to pursue higher education with flexibility. Preferential selection criteria can target rural-based physicians. Strong policy-level advocacy is needed to establish FM as a specialty with equitable pay scales. Socio-demographic profiling can be used as an effective advocacy tool.

The diagnosis of anthrax, a zoonotic disease caused by Bacillus anthracis can be complicated by detection of closely related species. Conventional diagnosis of anthrax involves microscopy, culture identification of bacterial colonies and molecular detection. Genetic markers used are often virulence gene targets such as B. anthracis protective antigen (pagA, also called BAPA, occurring on plasmid pXO1), lethal factor (lef, on pXO1), capsule-encoding capB/C (located on pXO2) as well as chromosomal Ba-1. Combinations of genetic markers using real-time/quantitative polymerase chain reaction (qPCR) are used to confirm B. anthracis from culture but can also be used directly on diagnostic samples to avoid propagation and its associated biorisks and for faster identification. We investigated how the presence of closely related species could complicate anthrax diagnoses with and without culture to standardise the use of genetic markers using qPCR for accurate anthrax diagnosis. Using blood smears from 2012-2020 from wildlife mortalities (n = 1708) in Kruger National Park in South Africa where anthrax is endemic, we contrasted anthrax diagnostic results based on qPCR, microscopy, and culture. From smears, 113/1708 grew bacteria in culture, from which 506 isolates were obtained. Of these isolates, only 24.7% (125 isolates) were positive for B. anthracis based on genetic markers or microscopy. However, among these, merely 4/125 (3.2%) were confirmed B. anthracis isolates (based on morphology, microscopy, and sensitivity testing to penicillin and gamma-phage) from the blood smear, likely due to poor survival of spores on stored smears. This study identified B. cereus sensu lato, which included B. cereus and B. anthracis, Peribacillus spp., and Priestia spp. clusters using gyrB gene in selected bacterial isolates positive for pagA region using BAPA probe. Using qPCR on blood smears, 52.1% (890 samples) tested positive for B. anthracis based on one or a combination of genetic markers which included the 25 positive controls. Notably, the standard lef primer set displayed the lowest specificity and accuracy. The Ba-1+BAPA+lef combination showed 100% specificity, sensitivity, and accuracy. Various marker combinations, such as Ba-1+capB, BAPA+capB, Ba-1+BAPA+capB+lef, and BAPA+lef+capB, all demonstrated 100.0% specificity and 98.7% accuracy, while maintaining a sensitivity of 96.6%. Using Ba-1+BAPA+lef+capB, as well as Ba-1+BAPA+lef with molecular diagnosis accurately detects B. anthracis in the absence of bacterial culture. Systematically combining microscopy and molecular markers holds promise for notably reducing false positives. This significantly enhances the detection and surveillance of diseases like anthrax in southern Africa and beyond and reduces the need for propagation of the bacteria in culture.

Summary: Background: Brain ageing is highly heterogeneous, as it is driven by a variety of normal and neuropathological processes. These processes may differentially affect structural and functional brain ageing across individuals, with more pronounced ageing (older brain age) during midlife being indicative of later development of dementia. Here, we examined whether brain-ageing heterogeneity in unimpaired older adults related to neurodegeneration, different cognitive trajectories, genetic and amyloid-beta (Aβ) profiles, and to predicted progression to Alzheimer’s disease (AD). Methods: Functional and structural brain age measures were obtained for resting-state functional MRI and structural MRI, respectively, in 3460 cognitively normal individuals across an age range spanning 42–85 years. Participants were categorised into four groups based on the difference between their chronological and predicted age in each modality: advanced age in both (n = 291), resilient in both (n = 260) or advanced in one/resilient in the other (n = 163/153). With the resilient group as the reference, brain-age groups were compared across neuroimaging features of neuropathology (white matter hyperintensity volume, neuronal loss measured with Neurite Orientation Dispersion and Density Imaging, AD-specific atrophy patterns measured with the Spatial Patterns of Abnormality for Recognition of Early Alzheimer’s Disease index, amyloid burden using amyloid positron emission tomography (PET), progression to mild cognitive impairment and baseline and longitudinal cognitive measures (trail making task, mini mental state examination, digit symbol substitution task). Findings: Individuals with advanced structural and functional brain-ages had more features indicative of neurodegeneration and they had poor cognition. Individuals with a resilient brain-age in both modalities had a genetic variant that has been shown to be associated with age of onset of AD. Mixed brain-age was associated with selective cognitive deficits. Interpretation: The advanced group displayed evidence of increased atrophy across all neuroimaging features that was not found in either of the mixed groups. This is in line with biomarkers of preclinical AD and cerebrovascular disease. These findings suggest that the variation in structural and functional brain ageing across individuals reflects the degree of underlying neuropathological processes and may indicate the propensity to develop dementia in later life. Funding: The National Institute on Aging, the National Institutes of Health, the Swiss National Science Foundation, the Kaiser Foundation Research Institute and the National Heart, Lung, and Blood Institute.

Abstract Disease heterogeneity has been a critical challenge for precision diagnosis and treatment, especially in neurologic and neuropsychiatric diseases. Many diseases can display multiple distinct brain phenotypes across individuals, potentially reflecting disease subtypes that can be captured using MRI and machine learning methods. However, biological interpretability and treatment relevance are limited if the derived subtypes are not associated with genetic drivers or susceptibility factors. Herein, we describe Gene-SGAN – a multi-view, weakly-supervised deep clustering method – which dissects disease heterogeneity by jointly considering phenotypic and genetic data, thereby conferring genetic correlations to the disease subtypes and associated endophenotypic signatures. We first validate the generalizability, interpretability, and robustness of Gene-SGAN in semi-synthetic experiments. We then demonstrate its application to real multi-site datasets from 28,858 individuals, deriving subtypes of Alzheimer’s disease and brain endophenotypes associated with hypertension, from MRI and single nucleotide polymorphism data. Derived brain phenotypes displayed significant differences in neuroanatomical patterns, genetic determinants, biological and clinical biomarkers, indicating potentially distinct underlying neuropathologic processes, genetic drivers, and susceptibility factors. Overall, Gene-SGAN is broadly applicable to disease subtyping and endophenotype discovery, and is herein tested on disease-related, genetically-associated neuroimaging phenotypes.

IntroductionTicks are obligate ectoparasites recognized worldwide as major vectors of several disease-causing pathogens and are good indicators of disease distribution and epidemiology. Recent years have seen a growing concern regarding emerging and re-emerging of economically important tick-borne pathogens of livestock and humans worldwide. The overall objective of the study was to give an insight into current tick distribution and associated bacterial pathogens that may pose a threat to cattle in the sampled study sites.MethodsA total of 150 cattle were randomly selected from three study sites, Harrismith and Phuthaditjhaba in Free State Province and Bergville in KwaZulu Natal Province, South Africa. Blood samples were collected from the cattle and DNA was subjected to the 16S rRNA gene microbiome sequencing on the circular consensus PacBio sequencing platform. Ticks were also collected from various predilection sites of the sampled animals.ResultsA total of eight tick species were identified and Rhipicephalus evertsi evertsi (79.4%) was the most abundant followed by R. appendiculatus (11.7%), R. afranicus (2.6%), R. simus (2.6%), Hyalomma rufipes (1.2%), R. decoloratus (1.0%), H. truncatum (0.7%) and R. microplus (0.7%). The bacterial microbiome sequence analysis revealed up to 16 phyla and 30 classes in the three study sites. Proteobacteria was the most dominant bacterial phyla with a relative abundance of 67.2% (Bergville), 73.8% (Harrismith) and 84.8% (Phuthaditjhaba), followed by Firmicutes at 9.6% (Phuthaditjhaba), 18.9% (Bergville) and 19.6% (Harrismith).Conclusion and perspectivesThe Chao 1 index estimator revealed significant differences in the α-diversity of microbial communities among three study sites. This study expands the knowledge on tick fauna and microbial communities in the three study sites.

Abstract Background Opioid use disorder (OUD) is overrepresented among people with criminal justice involvement; HIV is a common comorbidity in this population. This study aimed to examine how formerly incarcerated men living with HIV and OUD in South Africa experienced HIV and OUD services in correctional facilities and the community. Methods Three focus group discussions were conducted with 16 formerly incarcerated men living with HIV and OUD in Gauteng, South Africa. Discussions explored available healthcare services in correctional facilities and the community and procedural and practice differences in health care between the two types of settings. Data were analyzed thematically, using a comparative lens to explore the relationships between themes. Results Participants described an absence of medical services for OUD in correctional facilities and the harms caused by opioid withdrawal without medical support during incarceration. They reported that there were limited OUD services in the community and that what was available was not connected with public HIV clinics. Participants perceived correctional and community HIV care systems as readily accessible but suggested that a formal system did not exist to ensure care continuity post-release. Conclusions OUD was perceived to be medically unaddressed in correctional facilities and marginally attended to in the community. In contrast, HIV treatment was widely available within the two settings. The current model of OUD care in South Africa leaves many of the needs of re-entrants unmet. Integrating harm reduction into all primary care medical services may address some of these needs. Successful HIV care models provide examples of approaches that can be applied to developing and expanding OUD services in South Africa.

Abstract Background Globally, the rise in the number of people living with a substance use disorder (SUD) carries a multitude of individual and social health implications for carers and their families, often impacting negatively on their quality of life. Considered from a harm reduction approach, SUD is understood as a chronic protracted, complex health and social condition. From the extant literature, there is no evidence of the harm reduction approach being applied to address the needs of carers/family members who carry the burden of SUD care. This study preliminarily evaluated the Care4Carers Programme. It is a purposively designed set of brief interventions to improve the coping self-efficacy of carers of people with SUD (PwSUD carers) by equipping them to think about ways to exert control over their motivation, behaviours and social environment. Methods A pre-experimental, one group pretest–posttest design was implemented with 15 purposively selected participants in the Gauteng Province of South Africa. The intervention was conducted by the lead researcher, a registered social worker. Eight brief intervention sessions were held, over 5–6 weeks at research sites where the participants were identified. The coping self-efficacy scale was completed before and directly after exposure to the programme. Results were analysed using paired t-tests. Results There were statistically significant (p

Jupiter’s Great Red Spot (GRS) is known to exhibit oscillations in its westward drift with a 90-day period. The GRS was observed with the Hubble Space Telescope on eight dates over a single oscillation cycle in 2023 December to 2024 March to search for correlations in its physical characteristics over that time. Measured longitudinal positions are consistent with a 90-day oscillation in drift, but no corresponding oscillation is found in latitude. We find that the GRS size and shape also oscillate with a 90-day period, having a larger width and aspect ratio when it is at its slowest absolute drift (minimum date-to-date longitude change). The GRS’s UV and methane gas absorption-band brightness variations over this cycle were small, but the core exhibited a small increase in UV brightness in phase with the width oscillation; it is brightest when the GRS is largest. The high-velocity red collar also exhibited color changes, but out of phase with the other oscillations. Maximum interior velocities over the cycle were about 20 m s ^−1 larger than minimum velocities, slightly larger than the mean uncertainty of 13 m s ^−1 , but velocity variability did not follow a simple sinusoidal pattern as did other parameters such as longitude width or drift. Relative vorticity values were compared with aspect ratios and show that the GRS does not currently follow the Kida relation.

Prior studies of aging and Alzheimer disease have evaluated resting state functional connectivity (FC) using either seed-based correlation (SBC) or independent component analysis (ICA), with a focus on particular functional systems. SBC and ICA both are insensitive to differences in signal amplitude. At the same time, accumulating evidence indicates that the amplitude of spontaneous BOLD signal fluctuations is physiologically meaningful. We systematically compared covariance-based FC, which is sensitive to amplitude, vs. correlation-based FC, which is not, in affected individuals and controls drawn from two cohorts of participants including autosomal dominant Alzheimer disease (ADAD), late onset Alzheimer disease (LOAD), and age-matched controls. Functional connectivity was computed over 222 regions of interest and group differences were evaluated in terms of components projected onto a space of lower dimension. Our principal observations are: (1) Aging is associated with global loss of resting state fMRI signal amplitude that is approximately uniform across resting state networks. (2) Thus, covariance FC measures decrease with age whereas correlation FC is relatively preserved in healthy aging. (3) In contrast, symptomatic ADAD and LOAD both lead to loss of spontaneous activity amplitude as well as severely degraded correlation structure. These results demonstrate a double dissociation between age vs. Alzheimer disease and the amplitude vs. correlation structure of resting state BOLD signals. Modeling results suggest that the AD-associated loss of correlation structure is attributable to a relative increase in the fraction of locally restricted as opposed to widely shared variance.

Abstract Background Chronic traumatic encephalopathy (CTE) is a neurodegenerative disease that has been neuropathologically diagnosed in brain donors exposed to repetitive head impacts, including boxers and American football, soccer, ice hockey, and rugby players. CTE cannot yet be diagnosed during life. In December 2015, the National Institute of Neurological Disorders and Stroke awarded a seven-year grant (U01NS093334) to fund the “Diagnostics, Imaging, and Genetics Network for the Objective Study and Evaluation of Chronic Traumatic Encephalopathy (DIAGNOSE CTE) Research Project.” The objectives of this multicenter project are to: develop in vivo fluid and neuroimaging biomarkers for CTE; characterize its clinical presentation; refine and validate clinical research diagnostic criteria (i.e., traumatic encephalopathy syndrome [TES]); examine repetitive head impact exposure, genetic, and other risk factors; and provide shared resources of anonymized data and biological samples to the research community. In this paper, we provide a detailed overview of the rationale, design, and methods for the DIAGNOSE CTE Research Project. Methods The targeted sample and sample size was 240 male participants, ages 45–74, including 120 former professional football players, 60 former collegiate football players, and 60 asymptomatic participants without a history of head trauma or participation in organized contact sports. Participants were evaluated at one of four U.S. sites and underwent the following baseline procedures: neurological and neuropsychological examinations; tau and amyloid positron emission tomography; magnetic resonance imaging and spectroscopy; lumbar puncture; blood and saliva collection; and standardized self-report measures of neuropsychiatric, cognitive, and daily functioning. Study partners completed similar informant-report measures. Follow-up evaluations were intended to be in-person and at 3 years post-baseline. Multidisciplinary diagnostic consensus conferences are held, and the reliability and validity of TES diagnostic criteria are examined. Results Participant enrollment and all baseline evaluations were completed in February 2020. Three-year follow-up evaluations began in October 2019. However, in-person evaluation ceased with the COVID-19 pandemic, and resumed as remote, 4-year follow-up evaluations (including telephone-, online-, and videoconference-based cognitive, neuropsychiatric, and neurologic examinations, as well as in-home blood draw) in February 2021. Conclusions Findings from the DIAGNOSE CTE Research Project should facilitate detection and diagnosis of CTE during life, and thereby accelerate research on risk factors, mechanisms, epidemiology, treatment, and prevention of CTE. Trial registration NCT02798185

Background: Hyperphosphorylation of tau leads to conformational changes that destabilize microtubules and hinder axonal transport in Alzheimer's disease (AD). However, it remains unknown whether white matter (WM) decline due to AD is associated with specific Tau phosphorylation site(s). Methods: In autosomal dominant AD (ADAD) mutation carriers (MC) and non-carriers (NC) we compared cerebrospinal fluid (CSF) phosphorylation at tau sites (pT217, pT181, pS202, and pT205) and total tau with WM measures, as derived from diffusion tensor imaging (DTI), and cognition. A WM composite metric, derived from a principal component analysis, was used to identify spatial decline seen in ADAD. Results: The WM composite explained over 70% of the variance in MC. WM regions that strongly contributed to the spatial topography were located in callosal and cingulate regions. Loss of integrity within the WM composite was strongly associated with AD progression in MC as defined by the estimated years to onset (EYO) and cognitive decline. A linear regression demonstrated that amyloid, gray matter atrophy and phosphorylation at CSF tau site pT205 each uniquely explained a reduction in the WM composite within MC that was independent of vascular changes (white matter hyperintensities), and age. Hyperphosphorylation of CSF tau at other sites and total tau did not significantly predict WM composite loss. Conclusions: We identified a site-specific relationship between CSF phosphorylated tau and WM decline within MC. The presence of both amyloid deposition and Tau phosphorylation at pT205 were associated with WM composite loss. These findings highlight a primary AD-specific mechanism for WM dysfunction that is tightly coupled to symptom manifestation and cognitive decline.

Abstract Background Caledonian Stadium, the main mass temporary shelter for homeless people in the City of Tshwane, was created as a local response to the imperatives of the novel coronavirus disease (COVID-19) National State of Disaster lockdown in South Africa. This is a case study of the coordinated emergency healthcare response provided by the University of Pretoria’s Department of Family Medicine between 24 March and 6 April 2020. Methods This study uses a narrative approach to restory situated, transient, partial and provisional knowledge. Analysis is based on documented data and iteratively triangulated interviews on the operational experiences of selected healthcare first responders directly involved in the shelter. Results The impending lockdown generated intense interactions by UP-DFM to prepare for the provision of COVID-19 and essential generalist primary with partners involved in the Community Oriented Substance Use Programme (COSUP). With approximately 2000 people at the shelter at its peak, the numbers exceeded expectations. Throughout, while government officials tried to secure bedding, food and toilets, the shelter was poorly equipped and without onsite management. The COSUP clinical team prioritised opioid substitution therapy using methadone and COVID-19 screening over generalist healthcare to manage withdrawal and contain tension and anxiety. COSUP and its partners helped the city plan and implement the safe re-sheltering of all Caledonian residents. Conclusion The Caledonian shelter is an account of organisational resilience in the face of homelessness and substance use emergencies triggered by lockdown. Through community-oriented, bottom-up self-organisation, a clinically led team navigated a response to the immediate needs of people who are homeless and/or use drugs that evolved into a more sustainable intervention. Key lessons learnt were the importance of communicating with people directly affected by emergencies, the value of using methadone to reduce harms during emergencies and the imperative of including OST in essential primary healthcare.

Bovine anaplasmosis, caused by Anaplasma marginale, is one of the most important tick-borne diseases of cattle. Anaplasma marginale is known to be present in the Mnisi community, Mpumalanga Province, with frequent cases of anaplasmosis reported. This study investigated the infection dynamics in calves (n = 10) in two habitats in the study area over 12 months. A duplex real-time PCR assay targeting the msp1β gene of A. marginale and the groEL gene of A. centrale confirmed the presence of A. marginale in five calves in a peri-urban area from the first month, but in only two calves at the wildlife–livestock interface and only after six months. These results were confirmed by 16S rRNA microbiome analysis. Over 50 A. marginale msp1α genotypes were detected in the calves along with five novel Msp1a repeats. Calves in the peri-urban area were more likely to be infected with A. marginale than calves in the wildlife–livestock interface. Cattle management, acaricide treatment, and cattle density could explain differences in infection prevalence in the two areas. Our results revealed that most calves were superinfected by distinct A. marginale strains within the study period, indicating continuous challenge with multiple strains that should lead to robust immunity in the calves and endemic stability in the area.

Stroke is one of the leading causes of death and disability worldwide. Reducing this disease burden through drug discovery and evaluation of stroke patient outcomes requires broader characterization of stroke pathophysiology, yet the underlying biologic and genetic factors contributing to outcomes are largely unknown. Remedying this critical knowledge gap requires deeper phenotyping, including large-scale integration of demographic, clinical, genomic, and imaging features. Such big data approaches will be facilitated by developing and running processing pipelines to extract stroke-related phenotypes at large scale. Millions of stroke patients undergo routine brain imaging each year, capturing a rich set of data on stroke-related injury and outcomes. The Stroke Neuroimaging Phenotype Repository (SNIPR) was developed as a multi-center centralized imaging repository of clinical computed tomography (CT) and magnetic resonance imaging (MRI) scans from stroke patients worldwide, based on the open source XNAT imaging informatics platform. The aims of this repository are to: (i) store, manage, process, and facilitate sharing of high-value stroke imaging data sets, (ii) implement containerized automated computational methods to extract image characteristics and disease-specific features from contributed images, (iii) facilitate integration of imaging, genomic, and clinical data to perform large-scale analysis of complications after stroke; and (iv) develop SNIPR as a collaborative platform aimed at both data scientists and clinical investigators. Currently, SNIPR hosts research projects encompassing ischemic and hemorrhagic stroke, with data from 2,246 subjects, and 6,149 imaging sessions from Washington University’s clinical image archive as well as contributions from collaborators in different countries, including Finland, Poland, and Spain. Moreover, we have extended the XNAT data model to include relevant clinical features, including subject demographics, stroke severity (NIH Stroke Scale), stroke subtype (using TOAST classification), and outcome [modified Rankin Scale (mRS)]. Image processing pipelines are deployed on SNIPR using containerized modules, which facilitate replicability at a large scale. The first such pipeline identifies axial brain CT scans from DICOM header data and image data using a meta deep learning scan classifier, registers serial scans to an atlas, segments tissue compartments, and calculates CSF volume. The resulting volume can be used to quantify the progression of cerebral edema after ischemic stroke. SNIPR thus enables the development and validation of pipelines to automatically extract imaging phenotypes and couple them with clinical data with the overarching aim of enabling a broad understanding of stroke progression and outcomes.

Glioblastoma multiforme (GBM) is the most frequently occurring brain malignancy. Due to its poor prognosis with currently available treatments, there is a pressing need for easily accessible, non-invasive techniques to help inform pre-treatment planning, patient counseling, and improve outcomes. In this study we determined the feasibility of resting-state functional connectivity (rsFC) to classify GBM patients into short-term and long-term survival groups with respect to reported median survival (14.6 months). We used a support vector machine with rsFC between regions of interest as predictive features. We employed a novel hybrid feature selection method whereby features were first filtered using correlations between rsFC and OS, and then using the established method of recursive feature elimination (RFE) to select the optimal feature subset. Leave-one-subject-out cross-validation evaluated the performance of models. Classification between short- and long-term survival accuracy was 71.9%. Sensitivity and specificity were 77.1 and 65.5%, respectively. The area under the receiver operating characteristic curve was 0.752 (95% CI, 0.62–0.88). These findings suggest that highly specific features of rsFC may predict GBM survival. Taken together, the findings of this study support that resting-state fMRI and machine learning analytics could enable a radiomic biomarker for GBM, augmenting care and planning for individual patients.

Background: In complex health settings, care coordination is required to link patients to appropriate and effective care. Although articulated as system and professional values, coordination and cooperation are often absent within and across levels of service, between facilities and across sectors, with negative consequences for clinical outcomes as well as service load. Aim: This article presents the results of an applied research initiative to facilitate the coordination of patient care. Setting: The study took place at three hospitals in the sub-district 3 public health complex (Tshwane district). Method: Using a novel capability approach to learning, interdisciplinary, clinician-led teams made weekly coordination-of-care ward rounds to develop patient-centred plans and facilitate care pathways for patients identified as being stuck in the system. Notes taken during three-stage assessments were analysed thematically to gain insight into down referral and discharge. Results: The coordination-of-care team assessed 94 patients over a period of six months. Clinical assessments yielded essential details about patients’ varied and multimorbid conditions, while personal and contextual assessments highlighted issues that put patients’ care needs and possibilities into perspective. The team used the combined assessments to make patient-tailored action plans and apply them by facilitating cooperation through interprofessional and intersectoral networks. Conclusion: Effective patient care-coordination involves a set of referral practices and processes that are intentionally organised by clinically led, interprofessional teams. Empowered by richly informed plans, the teams foster cooperation among people, organisations and institutions in networks that extend from and to patients. In so doing, they embed care coordination into the discharge process and make referral to a link-to-care service.