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The presence of the endogenous Leishmania RNA virus 1 (LRV1) replicating stably within some parasite species has been associated with the development of more severe forms of leishmaniasis and relapses after drug treatment in humans. Here, we show that the disease-exacerbatory role of LRV1 relies on type I IFN (type I IFNs) production by macrophages and signaling in vivo. Moreover, infecting mice with the LRV1-cured Leishmania guyanensis (LgyLRV1⁻) strain of parasites followed by type I IFN treatment increased lesion size and parasite burden, quantitatively reproducing the LRV1-bearing (LgyLRV1⁺) infection phenotype. This finding suggested the possibility that exogenous viral infections could likewise increase pathogenicity, which was tested by coinfecting mice with L. guyanensis and lymphocytic choriomeningitis virus (LCMV), or the sand fly-transmitted arbovirus Toscana virus (TOSV). The type I IFN antiviral response increased the pathology of L. guyanensis infection, accompanied by down-regulation of the IFN-γ receptor normally required for antileishmanial control. Further, LCMV coinfection of IFN-γ–deficient mice promoted parasite dissemination to secondary sites, reproducing the LgyLRV1⁺ metastatic phenotype. Remarkably, LCMV coinfection of mice that had healed from L. guyanensis infection induced reactivation of disease pathology, overriding the protective adaptive immune response. Our findings establish that type I IFN-dependent responses, arising from endogenous viral elements (dsRNA/LRV1), or exogenous coinfection with IFN-inducing viruses, are able to synergize with New World Leishmania parasites in both primary and relapse infections. Thus, viral infections likely represent a significant risk factor along with parasite and host factors, thereby contributing to the pathological spectrum of human leishmaniasis.

Torque teno virus (TTV) is considered to be an ubiquitous member of the commensal human blood virome commonly reported in mixed genotype co-infections. This study investigates the genomic diversity of TTV in blood samples from 816 febrile Tanzanian children. Metagenomic next-generation sequencing was used to screen for TTV in individual blood samples from a cohort of 816 febrile Tanzanian paediatric outpatients. For positive samples, the number of TTV species and genotypes present were evaluated. We investigate the linear relationship between individual TTV diversity and the patient age by linear regression. TTV was detected in 97.2% of sera. ORF1 analysis revealed the presence of 149 genotypes from 38 species, suggesting the presence of 13 new species. These genotypes were mostly present as co-infections with a median of 11 genotypes/subject (range: 1–71). In terms of species, we found a median of nine species/subject (range: 1–29). We further show a significant association between the diversity of co-detected TTV and the age of the subjects (p value < 0.0001). This study shows that significant TTV genomic diversity is acquired by the age of five and that this diversity tends to increase with age, which indicates a repetitive TTV acquisition during the first months/years of life.

Currently, the WHO guidelines on the Integrated Management for Childhood Illnesses (IMCI) only recommend antimalarial treatment in the presence of a positive standard mRDT result [9]. [...]far, this strategy has proven to be safe in clinical practice and has considerably improved case management and rational use of antimalarial drugs both in endemic environments [10, 11] and in travelers (in whom parasite densities are typically lower) [12]. Because of the successful experience with standard mRDTs and their wide margin of safety, more sensitive methods are not being promoted for routine use in febrile case management. Clinical data and data collection Data were thus collected via systematic clinical questionnaires embedded in a mobile app and included (1) demographic information (age, sex, region, date of consultation, etc.); (2) relevant medical history (HIV status, antibiotic or antimalarial consumption in the past 7 days, history of chronic illness, etc.); and (3) presence, severity, and duration of symptoms (fever, pain, or specific complaints of the respiratory, gastrointestinal, neurological, or dermatological system). [...]follow-up was performed physically at days 3 and 7 (except for children entirely cured at day 3 who were followed by telephone at day 7) and telephonically at day 28, to perform a follow-up assessment and management, if needed, and collect clinical outcomes (clinical failure, secondary hospitalization, or death).

Background New vaccines with broader protection against SARS-CoV-2 are needed to reduce the risk of immune escape and provide broad and long-lasting cellular immunity. The objectives of the naNO-COVID trial were to evaluate the safety and immunogenicity of a CD8 + T cell, gold nanoparticle-based, peptide COVID-19 vaccine. Methods A randomized, double-blind, vehicle-controlled, phase 1 trial in healthy adults to receive PepGNP-Covid19 or Vehicle-GNP, followed over 180 days, using a dose-escalation strategy. Results Twenty participants received PepGNP-Covid19 (low dose [LD] or high dose [HD], n  = 10 each) and six Vehicle-GNP (LD or HD, n  = 3 each). Vaccinations were safe. No serious adverse events were reported. Most of the adverse events were mild, two adverse events of special interest related to the product (fever and fatigue). Reactogenicity was similar overall between vaccine, comparator, and doses. Virus-specific humoral responses in LD PepGNP-Covid19 and Vehicle-GNP groups coincided with SARS-CoV-2 infections. PepGNP-Covid19 vaccination induced the modulation of Covid19-specific CD137 + CD69 + CD8 + , and an increase at day 35 particularly in central and effector memory T cells in LD group, and in late effector memory cells in HD group. Conclusions The favourable safety profile and cellular responses observed support further development of PepGNP-Covid19. Trial registration ClinicalTrials.gov, NCT05113862, approved 09.11.2021.

Cutaneous leishmaniasis has various outcomes, ranging from self-healing reddened papules to extensive open ulcerations that metastasise to secondary sites and are often resistant to standard therapies. In the case of L. guyanensis (L.g), about 5-10% of all infections result in metastatic complications. We recently showed that a cytoplasmic virus within L.g parasites (LRV1) is able to act as a potent innate immunogen, worsening disease outcome in a murine model. In this study, we investigated the immunophenotype of human patients infected by L.g and found a significant association between the inflammatory cytokine IL-17A, the presence of LRV1 and disease chronicity. Further, IL-17A was inversely correlated to the protective cytokine IFN-γ. These findings were experimentally corroborated in our murine model, where IL-17A produced in LRV1+ L.g infection contributed to parasite virulence and dissemination in the absence of IFN-γ. Additionally, IL-17A inhibition in mice using digoxin or SR1001, showed therapeutic promise in limiting parasite virulence. Thus, this murine model of LRV1-dependent infectious metastasis validated markers of disease chronicity in humans and elucidated the immunologic mechanism for the dissemination of Leishmania parasites to secondary sites. Moreover, it confirms the prognostic value of LRV1 and IL-17A detection to prevent metastatic leishmaniasis in human patients.

Background Interstitial lung diseases (ILD), such as idiopathic pulmonary fibrosis (IPF) and non-specific interstitial pneumonia (NSIP), and chronic obstructive pulmonary disease (COPD) are severe, progressive pulmonary disorders with a poor prognosis. Prompt and accurate diagnosis is important to enable patients to receive appropriate care at the earliest possible stage to delay disease progression and prolong survival. Artificial intelligence-assisted lung auscultation and ultrasound (LUS) could constitute an alternative to conventional, subjective, operator-related methods for the accurate and earlier diagnosis of these diseases. This protocol describes the standardised collection of digitally-acquired lung sounds and LUS images of adult outpatients with IPF, NSIP or COPD and a deep learning diagnostic and severity-stratification approach. Methods A total of 120 consecutive patients (≥ 18 years) meeting international criteria for IPF, NSIP or COPD and 40 age-matched controls will be recruited in a Swiss pulmonology outpatient clinic, starting from August 2022. At inclusion, demographic and clinical data will be collected. Lung auscultation will be recorded with a digital stethoscope at 10 thoracic sites in each patient and LUS images using a standard point-of-care device will be acquired at the same sites. A deep learning algorithm ( DeepBreath ) using convolutional neural networks, long short-term memory models, and transformer architectures will be trained on these audio recordings and LUS images to derive an automated diagnostic tool. The primary outcome is the diagnosis of ILD versus control subjects or COPD. Secondary outcomes are the clinical, functional and radiological characteristics of IPF, NSIP and COPD diagnosis. Quality of life will be measured with dedicated questionnaires. Based on previous work to distinguish normal and pathological lung sounds, we estimate to achieve convergence with an area under the receiver operating characteristic curve of > 80% using 40 patients in each category, yielding a sample size calculation of 80 ILD (40 IPF, 40 NSIP), 40 COPD, and 40 controls. Discussion This approach has a broad potential to better guide care management by exploring the synergistic value of several point-of-care-tests for the automated detection and differential diagnosis of ILD and COPD and to estimate severity. Trial registration Registration: August 8, 2022. ClinicalTrials.gov Identifier: NCT05318599.

Distributed collaborative learning is a promising approach for building predictive models for privacy-sensitive biomedical images. Here, several data owners (clients) train a joint model without sharing their original data. However, concealed systematic biases can compromise model performance and fairness. This study presents MyThisYourThat (MyTH) approach, which adapts an interpretable prototypical part learning network to a distributed setting, enabling each client to visualize feature differences learned by others on their own image: comparing one client’s 'This’ with others’ 'That’. Our setting demonstrates four clients collaboratively training two diagnostic classifiers on a benchmark X-ray dataset. Without data bias, the global model reaches 74.14% balanced accuracy for cardiomegaly and 74.08% for pleural effusion. We show that with systematic visual bias in one client, the performance of global models drops to near-random. We demonstrate how differences between local and global prototypes reveal biases and allow their visualization on each client’s data without compromising privacy.

ObjectivesOwing to its ease-of-use and excellent diagnostic performance for the assessment of respiratory symptoms, point-of-care lung ultrasound (POC-LUS) has emerged as an attractive skill in resource-low settings, where limited access to specialist care and inconsistent radiology services erode health equity.To narrow down the research to practice gap, this study aims to gain in-depth insights in the perceptions on POC-LUS and computer-assisted POC-LUS for the diagnosis of lower respiratory tract infections (LRTIs) in a low-income and middle-income country (LMIC) of sub-Saharan Africa.Design and settingQualitative study using face-to-face semi-structured interviews with three pneumologists and five general physicians in a tertiary centre for pneumology and tuberculosis in Benin, West Africa. The center hosts a prospective cohort study on the diagnostic performance of POC-LUS for LRTI. In this context, all participants started a POC-LUS training programme 6 months before the current study. Transcripts were coded by the interviewer, checked for intercoder reliability by an independent psychologist, compared and thematically summarised according to grounded theory methods.ResultsVarious barriers− and facilitators+ to POC-LUS implementation were identified related to four principal categories: (1) hospital setting (eg, lack of resources for device renewal or maintenance−, need for POC tests+), (2) physician’s perceptions (eg, lack of opportunity to practice−, willingness to appropriate the technique+), (3) tool characteristics (eg, unclear lifespan−, expedited diagnosis+) and (4) patient’s experience (no analogous image to keep−, reduction in costs+). Furthermore, all interviewees had positive attitudes towards computer-assisted POC-LUS.ConclusionsThere is a clear need for POC affordable lung imaging techniques in LMIC and physicians are willing to implement POC-LUS to optimise the diagnostic approach of LRTI with an affordable tool. Successful integration of POC-LUS into clinical routine will require adequate responses to local challenges related to the lack of available maintenance resources and limited opportunity to supervised practice for physicians.

Background Objective assessment of skills after training is essential for safe implementation of lung point-of-care ultrasound (POCUS). In low-and middle-income countries (LMIC) there is a need for assessment tools without onsite experts to scale up POCUS access. Our objective is to develop a web-based assessment tool and evaluate trainees across different countries and at different time points after initial lung POCUS training. Methods We adapted the objective and validated lung ultrasound score (LUS-OSAUS) to a web-based tool with quiz and practical skills test. Trainees were evaluated after a short (4-day) standardized lung POCUS training and were classified in distinct groups according to (i) their geographical location (Benin vs. South-Africa) and (ii) time elapsed since training (Benin 0 months vs. Benin 6 months). The Benin 6 months group had minimal continuous education. Skills test images were read by two blinded experts. We report the overall success rates and then compare these rates based on location and timing since training, using the Fischer’s exact test. Results A total of 35 out of 43 participants completed the online LUS-OSAUS quiz and skills test. The overall success rate was 0.84 (95%CI 0.80–0.88), with lower success rates for “correct depth” 0.54 (0.37–0.71), “correct assessment of pleura” 0.63 (0.45–0.79) and “conclusion” 0.71 (0.54–0.85). There were no differences based on location, with respective rates of 0.86 (0.80–0.92) and 0.83 (0.75–0.91) ( p -value = 0.125) for Benin and South Africa at 0 months, respectively. Similarly, there were no differences according to timing with success rates of 0.86 (0.80–0.92) and 0.82 (0.72–0.93) ( p -value = 0.563) for Benin at 0 months and 6 months, respectively. Conclusion Web-based objective and structured assessment of lung POCUS skills in LMIC following a short-standardized training is feasible and has a good overall success rate with consistent results across regions and up to 6 months after training given minimal continuous education. Overall, technical and POCUS-based clinical conclusion skills are the most difficult to acquire.

Despite the notoriety of Ebola virus disease (EVD) as one of the world's most deadly infections, EVD has a wide range of outcomes, where asymptomatic infection may be almost as common as fatality. With increasingly sensitive EVD diagnosis, there is a need for more accurate prognostic tools that objectively stratify clinical severity to better allocate limited resources and identify those most in need of intensive treatment. This retrospective cohort study analyses the clinical characteristics of 158 EVD(+) patients at the GOAL-Mathaska Ebola Treatment Centre, Sierra Leone. The prognostic potential of each characteristic was assessed and incorporated into a statistically weighted disease score. The mortality rate among EVD(+) patients was 60.8% and highest in those aged <5 or >25 years (p<0.05). Death was significantly associated with malaria co-infection (OR = 2.5, p = 0.01). However, this observation was abrogated after adjustment to Ebola viral load (p = 0.1), potentially indicating a pathologic synergy between the infections. Similarly, referral-time interacted with viral load, and adjustment revealed referral-time as a significant determinant of mortality, thus quantifying the benefits of early reporting as a 12% mortality risk reduction per day (p = 0.012). Disorientation was the strongest unadjusted predictor of death (OR = 13.1, p = 0.014) followed by hiccups, diarrhoea, conjunctivitis, dyspnoea and myalgia. Including these characteristics in multivariate prognostic scores, we obtained a 91% and 97% ability to discriminate death at or after triage respectively (area under ROC curve). This study proposes highly predictive and easy-to-use prognostic tools, which stratify the risk of EVD mortality at or after EVD triage.