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Background Support vector machines (SVM) are a powerful tool to analyze data with a number of predictors approximately equal or larger than the number of observations. However, originally, application of SVM to analyze biomedical data was limited because SVM was not designed to evaluate importance of predictor variables. Creating predictor models based on only the most relevant variables is essential in biomedical research. Currently, substantial work has been done to allow assessment of variable importance in SVM models but this work has focused on SVM implemented with linear kernels. The power of SVM as a prediction model is associated with the flexibility generated by use of non-linear kernels. Moreover, SVM has been extended to model survival outcomes. This paper extends the Recursive Feature Elimination (RFE) algorithm by proposing three approaches to rank variables based on non-linear SVM and SVM for survival analysis. Results The proposed algorithms allows visualization of each one the RFE iterations, and hence, identification of the most relevant predictors of the response variable. Using simulation studies based on time-to-event outcomes and three real datasets, we evaluate the three methods, based on pseudo-samples and kernel principal component analysis, and compare them with the original SVM-RFE algorithm for non-linear kernels. The three algorithms we proposed performed generally better than the gold standard RFE for non-linear kernels, when comparing the truly most relevant variables with the variable ranks produced by each algorithm in simulation studies. Generally, the RFE-pseudo-samples outperformed the other three methods, even when variables were assumed to be correlated in all tested scenarios. Conclusions The proposed approaches can be implemented with accuracy to select variables and assess direction and strength of associations in analysis of biomedical data using SVM for categorical or time-to-event responses. Conducting variable selection and interpreting direction and strength of associations between predictors and outcomes with the proposed approaches, particularly with the RFE-pseudo-samples approach can be implemented with accuracy when analyzing biomedical data. These approaches, perform better than the classical RFE of Guyon for realistic scenarios about the structure of biomedical data.

Background The necessity to analyze medium-throughput data in epidemiological studies with small sample size, particularly when studying biomedical data may hinder the use of classical statistical methods. Support vector machines (SVM) models can be successfully applied in this setting because they are a powerful tool to analyze data with large number of predictors and limited sample size, especially when handling binary outcomes. However, biomedical research often involves analysis of time-to-event outcomes and has to account for censoring. Methods to handle censored data in the SVM framework can be divided into two classes: those based on support vector regression (SVR) and those based on binary classification. Methods based on SVR seem to be suboptimal to handle sparse data and yield results comparable to Cox proportional hazards model and kernel Cox regression. The limited work dedicated to assess methods based on of SVM for binary classification has been based on SVM learning using privileged information and SVM with uncertain classes. Results This paper proposes alternative methods and extensions within the binary classification framework, specifically, a conditional survival approach for weighting censored observations and a semi-supervised SVM with local invariances. Using simulation studies and some real datasets, we evaluate those two methods and compare them with a weighted SVM model, SVM extensions found in the literature, kernel Cox regression and Cox model. Conclusions Our proposed methods perform generally better under a wide variety of realistic scenarios about the structure of biomedical data. Specifically, the local invariances method using the conditional survival approach is the most robust method under different scenarios and is a good approach to consider as an alternative to other time-to-event methods. When analysing real data is a method to be considered and recommended since outperforms other methods in proportional and non-proportional scenarios and sparse data, which is something usual in biomedical data and biomarkers analysis.

Malaria causes substantial morbidity and mortality in sub-Saharan Africa. In this report from Malawi, the pathogenesis of cerebral malaria in children is evaluated. Despite recent advances in treatment, prevention, and control, malaria remains a major scourge. 1 Quinine, the mainstay of treatment for cerebral malaria for 300 years, has been supplanted by artesunate, 2 , 3 but despite more rapid parasite clearance with artesunate, the case fatality rate among African children with cerebral malaria treated with artesunate remains high at 18%. 3 Improvements in community-based care will help to prevent cerebral malaria, but additional advances in the treatment of hospitalized patients will probably require adjunctive therapies targeting key pathogenetic mechanisms. The pathogenesis of cerebral malaria is incompletely understood, and although there is considerable evidence to suggest that . . .

Malaria surveillance and interventions in endemic countries often target young children at highest risk of malaria morbidity and mortality. We aimed to determine whether school-age children and adults not captured in surveillance serve as a reservoir for malaria infection and may contribute to malaria transmission. Cross-sectional surveys were conducted in one rainy and one dry season in southern Malawi. Demographic and health information was collected for all household members. Blood samples were obtained for microscopic and PCR identification of Plasmodium falciparum. Among 5796 individuals aged greater than six months, PCR prevalence of malaria infection was 5%, 10%, and 20% in dry, and 9%, 15%, and 32% in rainy seasons in Blantyre, Thyolo, and Chikhwawa, respectively. Over 88% of those infected were asymptomatic. Participants aged 6-15 years were at higher risk of infection (OR=4.8; 95%CI, 4.0-5.8) and asymptomatic infection (OR=4.2; 95%CI, 2.7-6.6) than younger children in all settings. School-age children used bednets less frequently than other age groups. Compared to young children, school-age children were brought less often for treatment and more often to unreliable treatment sources. School-age children represent an underappreciated reservoir of malaria infection and have less exposure to antimalarial interventions. Malaria control and elimination strategies may need to expand to include this age group.

RTS,S/AS01E has been tested in a phase 3 malaria vaccine study with partial efficacy in African children and infants. In a cohort of 1028 subjects from one low (Bagomoyo) and two high (Nanoro, Kintampo) malaria transmission sites, we analysed IgG plasma/serum concentration and avidity to CSP (NANP-repeat and C-terminal domains) after a 3-dose vaccination against time to clinical malaria events during 12-months. Here we report that RTS,S/AS01E induces substantial increases in IgG levels from pre- to post-vaccination ( p  < 0.001), higher in NANP than C-terminus (2855 vs 1297 proportional change between means), and higher concentrations and avidities in children than infants ( p  < 0.001). Baseline CSP IgG levels are elevated in malaria cases than controls ( p  < 0.001). Both, IgG magnitude to NANP (hazard ratio [95% confidence interval] 0.61 [0.48–0.76]) and avidity to C-terminus (0.07 [0.05–0.90]) post-vaccination are significantly associated with vaccine efficacy. IgG avidity to the C-terminus emerges as a significant contributor to RTS,S/AS01E-mediated protection. RTS,S/AS01E has been tested in a phase 3 malaria vaccine trial and has shown partial efficacy in children and infants. Here, the authors analyze IgG concentration and avidity to CSP in ~1000 participants and show that IgG avidity to the C-terminus of CSP is significantly associated with vaccine-mediated protection.

Molecular interactions between male and female factors during mating profoundly affect the reproductive behavior and physiology of female insects. In natural populations of the malaria mosquito Anopheles gambiae, blood-fed females direct nutritional resources towards oogenesis only when inseminated. Here we show that the mating-dependent pathway of egg development in these mosquitoes is regulated by the interaction between the steroid hormone 20-hydroxy-ecdysone (20E) transferred by males during copulation and a female Mating-Induced Stimulator of Oogenesis (MISO) protein. RNAi silencing of MISO abolishes the increase in oogenesis caused by mating in blood-fed females, causes a delay in oocyte development, and impairs the function of male-transferred 20E. Co-immunoprecipitation experiments show that MISO and 20E interact in the female reproductive tract. Moreover MISO expression after mating is induced by 20E via the Ecdysone Receptor, demonstrating a close cooperation between the two factors. Male-transferred 20E therefore acts as a mating signal that females translate into an increased investment in egg development via a MISO-dependent pathway. The identification of this male-female reproductive interaction offers novel opportunities for the control of mosquito populations that transmit malaria.

Rights and permissions Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. Enhancing SVM for survival data using local invariances and weighting [RAW_REF_TEXT] Hector Sanz 1 , [/RAW_REF_TEXT] [RAW_REF_TEXT] Ferran Reverter1,2 & [/RAW_REF_TEXT] [RAW_REF_TEXT] Clarissa Valim3,4 [/RAW_REF_TEXT] BMC Bioinformatics volume 21, Article number: 371 (2020) Cite this article [RAW_REF_TEXT] 108 Accesses [/RAW_REF_TEXT] [RAW_REF_TEXT] 1 Altmetric [/RAW_REF_TEXT] [RAW_REF_TEXT] Metrics details [/RAW_REF_TEXT] [RAW_REF_TEXT] The original article was published in BMC Bioinformatics 2020 21:193 [/RAW_REF_TEXT] Correction to: BMC Bioinformatics 21, 193 (2020) https://doi.org/10.1186/s12859-020-3481-2 Following publication of the original article [1], the authors identified errors in the equations. Enhancing SVM for survival data using local invariances and weighting [RAW_REF_TEXT] Hector Sanz 1 , Ferran Reverter1,2 & Clarissa Valim3,4 [/RAW_REF_TEXT] BMC Bioinformatics volume 21, Article number: 371 (2020) Cite this article [RAW_REF_TEXT] 108 Accesses 1 Altmetric Metrics details The original article was published in BMC Bioinformatics 2020 21:193

In areas where malaria remains entrenched, novel transmission-reducing interventions are essential for malaria elimination. We report the impact screening-and-treatment of asymptomatic Malawian schoolchildren (n = 364 in the rainy season and 341 in the dry season) had on gametocyte—the parasite stage responsible for human-to-mosquito transmission—carriage. We used concomitant household-based surveys to predict the potential reduction in transmission in the surrounding community. Among 253 students with P. falciparum infections at screening, 179 (71%) had infections containing gametocytes detected by Pfs 25 qRT-PCR. 84% of gametocyte-containing infections were detected by malaria rapid diagnostic test. While the gametocyte prevalence remained constant in untreated children, treatment with artemether-lumefantrine reduced the gametocyte prevalence (p < 0.0001) from 51.8 to 9.7% and geometric mean gametocyte density (p = 0.008) from 0.52 to 0.05 gametocytes/microliter. In community surveys, 46% of all gametocyte-containing infections were in school-age children, who comprised only 35% of the population. Based on these estimates six weeks after the intervention, the gametocyte burden in the community could be reduced by 25–55% depending on the season and the measure used to characterize gametocyte carriage. Thus, school-based interventions to treat asymptomatic infections may be a high-yield approach to not only improve the health of schoolchildren, but also decrease malaria transmission.

Genetic modification of mesenchymal stem cells (MSCs) is a promising strategy to improve their therapeutic effects. Granulocyte-colony stimulating factor (G-CSF) is a growth factor widely used in the clinical practice with known regenerative and immunomodulatory actions, including the mobilization of regulatory T cells (Tregs) and myeloid-derived suppressor cells (MDSCs). Here we evaluated the therapeutic potential of MSCs overexpressing G-CSF (MSC_G-CSF) in a model of inflammatory cardiomyopathy due to chronic Chagas disease. C57BL/6 mice were treated with wild-type MSCs, MSC_G-CSF, or vehicle (saline) 6 months after infection with . Transplantation of MSC_G-CSF caused an increase in the number of circulating leukocytes compared to wild-type MSCs. Moreover, G-CSF overexpression caused an increase in migration capacity of MSCs to the hearts of infected mice. Transplantation of either MSCs or MSC_G-CSF improved exercise capacity, when compared to saline-treated chagasic mice. MSC_G-CSF mice, however, were more potent than MSCs in reducing the number of infiltrating leukocytes and fibrosis in the heart. Similarly, MSC_G-CSF-treated mice presented significantly lower levels of inflammatory mediators, such as IFNγ, TNFα, and Tbet, with increased IL-10 production. A marked increase in the percentage of Tregs and MDSCs in the hearts of infected mice was seen after administration of MSC_G-CSF, but not MSCs. Moreover, Tregs were positive for IL-10 in the hearts of -infected mice. analysis showed that recombinant hG-CSF and conditioned medium of MSC_G-CSF, but not wild-type MSCs, induce chemoattraction of MDSCs in a transwell assay. Finally, MDSCs purified from hearts of MSC_G-CSF transplanted mice inhibited the proliferation of activated splenocytes in a co-culture assay. Our results demonstrate that G-CSF overexpression by MSCs potentiates their immunomodulatory effects in our model of Chagas disease and suggest that mobilization of suppressor cell populations such as Tregs and MDSCs as a promising strategy for the treatment of chronic Chagas disease. Finally, our results reinforce the therapeutic potential of genetic modification of MSCs, aiming at increasing their paracrine actions.

Background Prompt diagnosis and treatment are essential for malaria control but are typically assessed only among children under five. Older children and adults also experience malaria and may act as reservoirs for transmission but barriers such as distance to facilities, supply shortages, and mistrust of the health system limit access to care across age groups. This study aimed to determine how demographic and parasitological factors influence treatment-seeking behaviour over time. Methods A community-based, open-enrollment longitudinal cohort study was conducted in rural Malawi from April 2019 to May 2020. Data were collected during monthly scheduled active case detection (ACD) visits and passive case detection (PCD) visits at local health centres. Malaria-related treatment-seeking behaviour was assessed using two outcomes: (1) self-reported treatment-seeking between ACD visits and (2) attendance at study-linked health centres during illness. Treatment-seeking was categorized as occurring in the formal or informal sectors. Mixed-effects logistic regression models were used to identify predictors of formal-sector treatment-seeking and health centre attendance, adjusting for clustering at the individual and household levels. Poisson regression was used to estimate rate ratios of PCD visits per person-year. Results The study enrolled 962 participants who contributed 7293 total visits, including 6794 ACD and 499 PCD visits. Most reported treatment-seeking (82%, 720/880 visits) occurred in the formal health sector and longer walking time and higher household head education were associated with reduced odds of formal treatment-seeking (OR = 0.28 for > 90 min vs. < 30 min; OR = 0.41 for secondary education vs. no education). In longitudinal models, older age, male sex, and greater distance to the facility were consistently associated with lower odds of attending PCD visits. Fever was positively associated with subsequent PCD visits (OR = 1.60(1.16–2.21)), but Plasmodium falciparum infection and parasite density were not. The overall PCD visit rate was 70 per 100 person-years and was significantly lower among older children, adults, males, and households farther from health facilities. Conclusions Despite free access to malaria care, barriers to treatment persist. These findings highlight the need for more equitable, community-based approaches to malaria diagnosis and treatment across all age groups.