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Background Rapid diagnostic tests (RDTs) are increasingly becoming a paradigm for both clinical diagnosis of malaria infections and for estimating community parasite prevalence in household malaria indicator surveys in malaria-endemic countries. The antigens detected by RDTs are known to persist in the blood after treatment with anti-malarials, but reports on the duration of persistence (and the effect this has on RDT positivity) of these antigens post-treatment have been variable. Methods In this review, published studies on the persistence of positivity of RDTs post-treatment are collated, and a bespoke Bayesian survival model is fit to estimate the number of days RDTs remain positive after treatment. Results Half of RDTs that detect the antigen histidine-rich protein II (HRP2) are still positive 15 (5–32) days post-treatment, 13 days longer than RDTs that detect the antigen Plasmodium lactate dehydrogenase, and that 5% of HRP2 RDTs are still positive 36 (21–61) days after treatment. The duration of persistent positivity for combination RDTs that detect both antigens falls between that for HRP2- or pLDH-only RDTs, with half of RDTs remaining positive at 7 (2–20) days post-treatment. This study shows that children display persistent RDT positivity for longer after treatment than adults, and that persistent positivity is more common when an individual is treated with artemisinin combination therapy than when treated with other anti-malarials. Conclusions RDTs remain positive for a highly variable amount of time after treatment with anti-malarials, and the duration of positivity is highly dependent on the type of RDT used for diagnosis. Additionally, age and treatment both impact the duration of persistence of RDT positivity. The results presented here suggest that caution should be taken when using RDT-derived diagnostic outcomes from cross-sectional data where individuals have had a recent history of anti-malarial treatment.

Mitigating the threat of insecticide resistance in African malaria vector populations requires comprehensive information about where resistance occurs, to what degree, and how this has changed over time. Estimating these trends is complicated by the sparse, heterogeneous distribution of observations of resistance phenotypes in field populations. We use 6,423 observations of the prevalence of resistance to the most important vector control insecticides to inform a Bayesian geostatistical ensemble modelling approach, generating fine-scale predictive maps of resistance phenotypes in mosquitoes from the Anopheles gambiae complex across Africa. Our models are informed by a suite of 111 predictor variables describing potential drivers of selection for resistance. Our maps show alarming increases in the prevalence of resistance to pyrethroids and DDT across sub-Saharan Africa from 2005 to 2017, with mean mortality following insecticide exposure declining from almost 100% to less than 30% in some areas, as well as substantial spatial variation in resistance trends.

In cancer metastasis, intravasation of the invasive tumor cell (TCi) represents one of the most relevant events. During the last years, models regarding cancer cell intravasation have been proposed, such as the \"endocanalicular transendothelial crossing\" (ETC) theory. This theory describes the interplay between two adjacent endothelial cells and the TCi or a leukocyte during intravasation. Two endothelial cells create a channel with their cell membranes, in which the cell fits in without involving endothelial cell intercellular junctions, reaching the lumen through a transendothelial passage. In the present study, ten SCID mice were subcutaneously xenotransplanted with the HEK-EBNA293-VEGF-D cell line and euthanized after 35 days. Post-mortem examinations were performed and proper specimens from tumors were collected. Routine histology and immunohistochemistry for Ki-67, pAKT, pERK, ZEB-1, TWIST-1, F-actin, E-cadherin and LYVE-1 were performed followed by ultrastructural serial sections analysis. A novel experimental approach involving Computed Tomography (CT) combined with 3D digital model reconstruction was employed. The analysis of activated transcription factors supports that tumor cells at the periphery potentially underwent an epithelial-to-mesenchymal transition (EMT)-like process. Topographical analysis of LYVE-1 immunolabeled lymphatics revealed a peritumoral localisation. TEM investigations of the lymphatic vessels combined with 3D digital modelling enhanced the understanding of the endotheliocytes behavior during TCi intravasation, clarifying the ETC theory. Serial ultrastructural analysis performed within tumor periphery revealed numerous cells during the ETC process. Furthermore, this study demonstrates that ETC is an intravasation mode more frequently used by the TCi than by leukocytes during intravasation in the HEK-EBNA293-VEGF-D xenograft model and lays down the potential basis for promising future studies regarding intravasation blocking therapy.

The RUNX1 transcription factor is widely recognised for its tumour suppressor effects in leukaemia. Recently a putative link to breast cancer has started to emerge, however the function of RUNX1 in breast cancer is still unknown. To investigate if RUNX1 expression was important to clinical outcome in primary breast tumours a tissue microarray (TMA) containing biopsies from 483 patients with primary operable invasive ductal breast cancer was stained by immunohistochemistry. RUNX1 was associated with progesterone receptor (PR)-positive tumours (P<0.05), more tumour CD4+(P<0.05) and CD8+(P<0.01) T-lymphocytic infiltrate, increased tumour CD138+plasma cell (P<0.01) and more CD68+macrophage infiltrate (P<0.001). RUNX1 expression did not influence outcome of oestrogen receptor (ER)-positive or HER2-positive disease, however on univariate analysis a high RUNX1 protein was significantly associated with poorer cancer-specific survival in patients with ER-negative (P<0.05) and with triple negative (TN) invasive breast cancer (P<0.05). Furthermore, multivariate Cox regression analysis of cancer-specific survival showed a trend towards significance in ER-negative patients (P<0.1) and was significant in triple negative patients (P<0.05). Of relevance, triple negative breast cancer currently lacks good biomarkers and patients with this subtype do not benefit from the option of targeted therapy unlike patients with ER-positive or HER2-positive disease. Using multivariate analysis RUNX1 was identified as an independent prognostic marker in the triple negative subgroup. Overall, our study identifies RUNX1 as a new prognostic indicator correlating with poor prognosis specifically in the triple negative subtype of human breast cancer.

Individual-based models have become important tools in the global battle against infectious diseases, yet model complexity can make calibration to biological and epidemiological data challenging. We propose using a Bayesian optimization framework employing Gaussian process or machine learning emulator functions to calibrate a complex malaria transmission simulator. We demonstrate our approach by optimizing over a high-dimensional parameter space with respect to a portfolio of multiple fitting objectives built from datasets capturing the natural history of malaria transmission and disease progression. Our approach quickly outperforms previous calibrations, yielding an improved final goodness of fit. Per-objective parameter importance and sensitivity diagnostics provided by our approach offer epidemiological insights and enhance trust in predictions through greater interpretability. Individual-based models have become important tools in the global battle against infectious diseases, yet model complexity can make calibration challenging. Here, the authors propose a Bayesian optimization framework to calibrate a complex malaria transmission simulator.

Insecticide-treated nets (ITNs) are one of the most widespread and impactful malaria interventions in Africa, yet a spatially-resolved time series of ITN coverage has never been published. Using data from multiple sources, we generate high-resolution maps of ITN access, use, and nets-per-capita annually from 2000 to 2020 across the 40 highest-burden African countries. Our findings support several existing hypotheses: that use is high among those with access, that nets are discarded more quickly than official policy presumes, and that effectively distributing nets grows more difficult as coverage increases. The primary driving factors behind these findings are most likely strong cultural and social messaging around the importance of net use, low physical net durability, and a mixture of inherent commodity distribution challenges and less-than-optimal net allocation policies, respectively. These results can inform both policy decisions and downstream malaria analyses. Insecticide treated nets (ITNs) are an important part of malaria control in Africa and WHO targets aim for 80% coverage. This study estimates the spatio-temporal access and use of ITNs in Africa from 2000-2020, and shows that both metrics have improved over time but access remains below WHO targets.

We assess progress towards improved case management of childhood diarrhea in Nigeria over a period of targeted health systems reform from 2013 to 2018. Individual and community data from three Demographic and Health Survey rounds are leveraged in a geospatial model designed for stratified estimation by venue of treatment seeking and State. Our analysis reveals a highly regionalised health system undergoing rapid change. Nationally, there have been substantial increases in the proportion of children under 5 years old with diarrhea receiving the recommended oral rehydration therapy after seeking treatment at either a health clinic (0.57 [0.44–0.69; 95% CI] in 2008; 0.70 [0.54–0.83] in 2018) or chemist/pharmacy (0.28 [0.17–0.42] in 2008; 0.48 [0.31–0.64] in 2018). Yet State-level variations in venue attendance and performance by venue have conspired to hold the overall proportion receiving this potentially life-saving therapy (0.45 [0.35–0.55] in 2018) to well-below ideal coverage levels. High performing states that have demonstrated significant improvements include Kano, Jigawa and Borno, while under-performing states that have suffered declines in coverage include Kaduna and Taraba. The use of antibiotics is not recommended for mild cases of childhood diarrhea yet remains concerningly high nationally (0.27 [0.19–0.36] in 2018) with negligible variation between venues. Antibiotic use rates are particularly high in Enugu, Kaduna, Taraba, Kano, Niger and Kebbi, yet welcome reductions were identified in Jigawa, Adamawa and Osun. These results support the conclusions of previous studies and build the strength of evidence that urgent action is needed throughout the multi-tiered health system to improve the quality and equity of care for common childhood illnesses in Nigeria.

During the Millennium Development Goal (MDG) era, many countries in Africa achieved marked reductions in under-5 and neonatal mortality. Yet the pace of progress toward these goals substantially varied at the national level, demonstrating an essential need for tracking even more local trends in child mortality. With the adoption of the Sustainable Development Goals (SDGs) in 2015, which established ambitious targets for improving child survival by 2030, optimal intervention planning and targeting will require understanding of trends and rates of progress at a higher spatial resolution. In this study, we aimed to generate high-resolution estimates of under-5 and neonatal all-cause mortality across 46 countries in Africa. We assembled 235 geographically resolved household survey and census data sources on child deaths to produce estimates of under-5 and neonatal mortality at a resolution of 5 × 5 km grid cells across 46 African countries for 2000, 2005, 2010, and 2015. We used a Bayesian geostatistical analytical framework to generate these estimates, and implemented predictive validity tests. In addition to reporting 5 × 5 km estimates, we also aggregated results obtained from these estimates into three different levels—national, and subnational administrative levels 1 and 2—to provide the full range of geospatial resolution that local, national, and global decision makers might require. Amid improving child survival in Africa, there was substantial heterogeneity in absolute levels of under-5 and neonatal mortality in 2015, as well as the annualised rates of decline achieved from 2000 to 2015. Subnational areas in countries such as Botswana, Rwanda, and Ethiopia recorded some of the largest decreases in child mortality rates since 2000, positioning them well to achieve SDG targets by 2030 or earlier. Yet these places were the exception for Africa, since many areas, particularly in central and western Africa, must reduce under-5 mortality rates by at least 8·8% per year, between 2015 and 2030, to achieve the SDG 3.2 target for under-5 mortality by 2030. In the absence of unprecedented political commitment, financial support, and medical advances, the viability of SDG 3.2 achievement in Africa is precarious at best. By producing under-5 and neonatal mortality rates at multiple levels of geospatial resolution over time, this study provides key information for decision makers to target interventions at populations in the greatest need. In an era when precision public health increasingly has the potential to transform the design, implementation, and impact of health programmes, our 5 × 5 km estimates of child mortality in Africa provide a baseline against which local, national, and global stakeholders can map the pathways for ending preventable child deaths by 2030. Bill & Melinda Gates Foundation.

Dissecting and identifying the major actors and pathways in the genesis, progression and aggressive advancement of breast cancer is challenging, in part because neoplasms arising in this tissue represent distinct diseases and in part because the tumors themselves evolve. This review attempts to illustrate the complexity of this mutational landscape as it pertains to the RUNX genes and their transcription co-factor CBFβ. Large-scale genomic studies that characterize genetic alterations across a disease subtype are a useful starting point and as such have identified recurring alterations in CBFB and in the RUNX genes (particularly RUNX1). Intriguingly, the functional output of these mutations is often context dependent with regards to the estrogen receptor (ER) status of the breast cancer. Therefore, such studies need to be integrated with an in-depth understanding of both the normal and corrupted function in mammary cells to begin to tease out how loss or gain of function can alter the cell phenotype and contribute to disease progression. We review how alterations to RUNX/CBFβ function contextually ascribe to breast cancer subtypes and discuss how the in vitro analyses and mouse model systems have contributed to our current understanding of these proteins in the pathogenesis of this complex set of diseases.

Malaria is a serious threat to global health, with over 95 % of the cases reported in 2020 by the World Health Organization in African countries, including Sudan. Sudan is a low-income country with a limited healthcare system and a substantial burden of malaria. The epidemiology of malaria in Sudan is rapidly changing due to factors including the rapidly developing resistance to drugs and insecticides among the parasites and vectors, respectively; the growing population living in humanitarian settings due to political instability; and the recent emergence of Anopheles stephensi in the country. These factors contribute to changes in the distribution of the parasites species as well as malaria vectors in Sudan, and the shifting patterns of malaria epidemiology underscore the need for investment in improved situational awareness, early preparedness, and a national prevention and control strategy that is updated, evidence based, and proactive. A key component of this strategy is accurate, high-resolution endemicity maps of species-specific malaria. Here, we present a spatiotemporal Bayesian model, developed in collaboration with the Sudanese Ministry of Health, that predicts a fine-scale (1 km  ×  1 km) clinical incidence and seasonality profiles for Plasmodium falciparum and Plasmodium vivax across the country. We use monthly malaria case counts for both species collected via routine surveillance between January 2017 and December 2019, as well as a suite of high-resolution environmental covariates to inform our predictions. These epidemiological maps provide a useful resource for strategic planning and cost-effective implementation of malaria interventions, thus informing policymakers in Sudan to achieve success in malaria control and elimination.