SPINDLY mediates O-fucosylation of hundreds of proteins and sugar-dependent growth in Arabidopsis.

The recent discovery of SPINDLY (SPY)-catalyzed protein O-fucosylation revealed a novel mechanism for regulating nucleocytoplasmic protein functions in plants. Genetic evidence indicates the important roles of SPY in diverse developmental and physiological processes. However, the upstream signal controlling SPY activity and the downstream substrate proteins O-fucosylated by SPY remain largely unknown. Here, we demonstrated that SPY mediates sugar-dependent growth in Arabidopsis (Arabidopsis thaliana). We further identified hundreds of O-fucosylated proteins using lectin affinity chromatography followed by mass spectrometry. All the O-fucosylation events quantified in our proteomic analyses were undetectable or dramatically decreased in the spy mutants, and thus likely catalyzed by SPY. The O-fucosylome includes mostly nuclear and cytosolic proteins. Many O-fucosylated proteins function in essential cellular processes, phytohormone signaling, and developmental programs, consistent with the genetic functions of SPY. The O-fucosylome also includes many proteins modified by O-linked N-acetylglucosamine (O-GlcNAc) and by phosphorylation downstream of the target of rapamycin (TOR) kinase, revealing the convergence of these nutrient signaling pathways on key regulatory functions such as post-transcriptional/translational regulation and phytohormone responses. Our study identified numerous targets of SPY/O-fucosylation and potential nodes of crosstalk among sugar/nutrient signaling pathways, enabling future dissection of the signaling network that mediates sugar regulation of plant growth and development.

Real-Time Search-Assisted Acquisition on a Tribrid Mass Spectrometer Improves Coverage in Multiplexed Single-Cell Proteomics.

In the young field of single-cell proteomics (scMS), there is a great need for improved global proteome characterization, both in terms of proteins quantified per cell and quantitative performance thereof. The recently introduced real-time search (RTS) on the Orbitrap Eclipse Tribrid mass spectrometer in combination with SPS-MS3 acquisition has been shown to be beneficial for the measurement of samples that are multiplexed using isobaric tags. Multiplexed scMS requires high ion injection times and high-resolution spectra to quantify the single-cell signal; however, the carrier channel facilitates peptide identification and thus offers the opportunity for fast on-the-fly precursor filtering before committing to the time-intensive quantification scan. Here, we compared classical MS2 acquisition against RTS-SPS-MS3, both using the Orbitrap Eclipse Tribrid MS with the FAIMS Pro ion mobility interface and present a new acquisition strategy termed RETICLE (RTS enhanced quant of single cell spectra) that makes use of fast real-time searched linear ion trap scans to preselect MS1 peptide precursors for quantitative MS2 Orbitrap acquisition. We show that classical MS2 acquisition is outperformed by both RTS-SPS-MS3 through increased quantitative accuracy at similar proteome coverage, and RETICLE through higher proteome coverage, with the latter enabling the quantification of over 1000 proteins per cell at an MS2 injection time of 750 ms using a 2 h gradient.

A Smartphone App for Real-Time Assessment of Malaria Prophylaxis Adverse Events.

Background: Growth of international travel to malarial areas over the last decades has contributed to more travelers taking malaria prophylaxis. Travel-related symptoms may be wrongly attributed to malaria prophylaxis and hinder compliance. Here, we aimed to assess the frequency of real-time reporting of symptoms by travelers following malaria prophylaxis using a smartphone app. Method: Adult international travelers included in this single-center study (Barcelona, Spain) used the smartphone Trip Doctor® app developed by our group for real-time tracking of symptoms and adherence to prophylaxis. Results: Six hundred four (n = 604) international travelers were included in the study; 74.3% (449) used the app daily, and for one-quarter of travelers, malaria prophylaxis was prescribed. Participants from the prophylaxis group traveled more to Africa (86.7% vs. 4.3%; p < 0.01) and to high travel medical risk countries (60.8% vs. 18%; p < 0.01) and reported more immunosuppression (30.8% vs. 23.1% p < 0.01). Regarding symptoms, no significant intergroup differences were observed, and no relationship was found between the total number of malarial pills taken and reported symptoms. Conclusions: In our cohort, the number of symptoms due to malaria prophylaxis was not significantly higher than in participants for whom prophylaxis was not prescribed, and the overall proportion of symptoms is higher compared with other studies.

vLUME: 3D virtual reality for single-molecule localization microscopy.

vLUME is a virtual reality software package designed to render large three-dimensional single-molecule localization microscopy datasets. vLUME features include visualization, segmentation, bespoke analysis of complex local geometries and exporting features. vLUME can perform complex analysis on real three-dimensional biological samples that would otherwise be impossible by using regular flat-screen visualization programs.

Dynamic metabolic reprogramming in dendritic cells: An early response to influenza infection that is essential for effector function.

Infection with the influenza virus triggers an innate immune response that initiates the adaptive response to halt viral replication and spread. However, the metabolic response fueling the molecular mechanisms underlying changes in innate immune cell homeostasis remain undefined. Although influenza increases parasitized cell metabolism, it does not productively replicate in dendritic cells. To dissect these mechanisms, we compared the metabolism of dendritic cells to that of those infected with active and inactive influenza A virus and those treated with toll-like receptor agonists. Using quantitative mass spectrometry, pulse chase substrate utilization assays and metabolic flux measurements, we found global metabolic changes in dendritic cells 17 hours post infection, including significant changes in carbon commitment via glycolysis and glutaminolysis, as well as mitochondrial respiration. Influenza infection of dendritic cells led to a metabolic phenotype distinct from that induced by TLR agonists, with significant resilience in terms of metabolic plasticity. We identified c-Myc as one transcription factor modulating this response. Restriction of c-Myc activity or mitochondrial substrates significantly changed the immune functions of dendritic cells, such as reducing motility and T cell activation. Transcriptome analysis of inflammatory dendritic cells isolated following influenza infection showed similar metabolic reprogramming occurs in vivo. Thus, early in the infection process, dendritic cells respond with global metabolic restructuring, that is present in inflammatory lung dendritic cells after infection, and this is important for effector function. These findings suggest metabolic switching in dendritic cells plays a vital role in initiating the immune response to influenza infection.

Frequent detection of monkeypox virus DNA in saliva, semen, and other clinical samples from 12 patients, Barcelona, Spain, May to June 2022.

A monkeypox (MPX) outbreak has expanded worldwide since May 2022. We tested 147 clinical samples collected at different time points from 12 patients by real-time PCR. MPX DNA was detected in saliva from all cases, sometimes with high viral loads. Other samples were frequently positive: rectal swab (11/12 cases), nasopharyngeal swab (10/12 cases), semen (7/9 cases), urine (9/12 cases) and faeces (8/12 cases). These results improve knowledge on virus shedding and the possible role of bodily fluids in disease transmission.

INFERYS rescoring: Boosting peptide identifications and scoring confidence of database search results.

Database search engines for bottom-up proteomics largely ignore peptide fragment ion intensities during the automated scoring of tandem mass spectra against protein databases. Recent advances in deep learning allow the accurate prediction of peptide fragment ion intensities. Using these predictions to calculate additional intensity-based scores helps to overcome this drawback. Here, we describe a processing workflow termed INFERYS™ rescoring for the intensity-based rescoring of Sequest HT search engine results in Thermo Scientific™ Proteome Discoverer™ 2.5 software. The workflow is based on the deep learning platform INFERYS capable of predicting fragment ion intensities, which runs on personal computers without the need for graphics processing units. This workflow calculates intensity-based scores comparing peptide spectrum matches from Sequest HT and predicted spectra. Resulting scores are combined with classical search engine scores for input to the false discovery rate estimation tool Percolator. We demonstrate the merits of this approach by analyzing a classical HeLa standard sample and exemplify how this workflow leads to a better separation of target and decoy identifications, in turn resulting in increased peptide spectrum match, peptide and protein identification numbers. On an immunopeptidome dataset, this workflow leads to a 50% increase in identified peptides, emphasizing the advantage of intensity-based scores when analyzing low-intensity spectra or analytes with very similar physicochemical properties that require vast search spaces. Overall, the end-to-end integration of INFERYS rescoring enables simple and easy access to a powerful enhancement to classical database search engines, promising a deeper, more confident and more comprehensive analysis of proteomic data from any organism by unlocking the intensity dimension of tandem mass spectra for identification and more confident scoring.

Transcriptomic and proteomic profiling of glial versus neuronal Dube3a overexpression reveals common molecular changes in gliopathic epilepsies.

Epilepsy affects millions of individuals worldwide and many cases are pharmacoresistant. Duplication 15q syndrome (Dup15q) is a genetic disorder caused by duplications of the 15q11.2-q13.1 region. Phenotypes include a high rate of pharmacoresistant epilepsy. We developed a Dup15q model in Drosophila melanogaster that recapitulates seizures in Dup15q by over-expressing fly Dube3a or human UBE3A in glial cells, but not neurons, implicating glia in the Dup15q epilepsy phenotype. We compared Dube3a overexpression in glia (repo>Dube3a) versus neurons (elav>Dube3a) using transcriptomics and proteomics of whole fly head extracts. We identified 851 transcripts differentially regulated in repo>Dube3a, including an upregulation of glutathione S-transferase (GST) genes that occurred cell autonomously within glial cells. We reliably measured approximately 2,500 proteins by proteomics, most of which were also quantified at the transcript level. Combined transcriptomic and proteomic analysis revealed an enrichment of 21 synaptic transmission genes downregulated at the transcript and protein in repo>Dube3a indicating synaptic proteins change in a cell non-autonomous manner in repo>Dube3a flies. We identified 6 additional glia originating bang-sensitive seizure lines and found upregulation of GSTs in 4 out of these 6 lines. These data suggest GST upregulation is common among gliopathic seizures and may ultimately provide insight for treating epilepsy.

Improved Single-Cell Proteome Coverage Using Narrow-Bore Packed NanoLC Columns and Ultrasensitive Mass Spectrometry.

Single-cell proteomics can provide unique insights into biological processes by resolving heterogeneity that is obscured by bulk measurements. Gains in the overall sensitivity and proteome coverage through improvements in sample processing and analysis increase the information content obtained from each cell, particularly for less abundant proteins. Here we report on improved single-cell proteome coverage through the combination of the previously developed nanoPOTS platform with further miniaturization of liquid chromatography (LC) separations and implementation of an ultrasensitive latest generation mass spectrometer. Following nanoPOTS sample preparation, protein digests from single cells were separated using a 20 µm i.d. in-house-packed nanoLC column. Separated peptides were ionized using an etched fused-silica emitter capable of stable operation at the ∼20 nL/min flow rate provided by the LC separation. Ultrasensitive LC-MS analysis was achieved using the Orbitrap Eclipse Tribrid mass spectrometer. An average of 362 protein groups were identified by tandem mass spectrometry (MS/MS) from single HeLa cells, and 874 protein groups were identified using the Match Between Runs feature of MaxQuant. This represents an >70% increase in label-free proteome coverage for single cells relative to previous efforts using larger bore (30 µm i.d.) LC columns coupled to a previous-generation Orbitrap Fusion Lumos mass spectrometer.

Vitamin D status and risk of incident tuberculosis disease: A nested case-control study, systematic review, and individual-participant data meta-analysis.

BACKGROUND: Few studies have evaluated the association between preexisting vitamin D deficiency and incident tuberculosis (TB). We assessed the impact of baseline vitamins D levels on TB disease risk. METHODS AND FINDINGS: We assessed the association between baseline vitamin D and incident TB in a prospective cohort of 6,751 HIV-negative household contacts of TB patients enrolled between September 1, 2009, and August 29, 2012, in Lima, Peru. We screened for TB disease at 2, 6, and 12 months after enrollment. We defined cases as household contacts who developed TB disease at least 15 days after enrollment of the index patient. For each case, we randomly selected four controls from among contacts who did not develop TB disease, matching on gender and year of age. We also conducted a one-stage individual-participant data (IPD) meta-analysis searching PubMed and Embase to identify prospective studies of vitamin D and TB disease until June 8, 2019. We included studies that assessed vitamin D before TB diagnosis. In the primary analysis, we defined vitamin D deficiency as 25-(OH)D < 50 nmol/L, insufficiency as 50-75 nmol/L, and sufficiency as >75nmol/L. We estimated the association between baseline vitamin D status and incident TB using conditional logistic regression in the Lima cohort and generalized linear mixed models in the meta-analysis. We further defined severe vitamin D deficiency as 25-(OH)D < 25 nmol/L and performed stratified analyses by HIV status in the IPD meta-analysis. In the Lima cohort, we analyzed 180 cases and 709 matched controls. The adjusted odds ratio (aOR) for TB risk among participants with baseline vitamin D deficiency compared to sufficient vitamin D was 1.63 (95% CI 0.75-3.52; p = 0.22). We included seven published studies in the meta-analysis and analyzed 3,544 participants. In the pooled analysis, the aOR was 1.48 (95% CI 1.04-2.10; p = 0.03). The aOR for severe vitamin D deficiency was 2.05 (95% CI 0.87-4.87; p trend for decreasing 25-(OH)D levels from sufficient vitamin D to severe deficiency = 0.02). Among 1,576 HIV-positive patients, vitamin D deficiency conferred a 2-fold (aOR 2.18, 95% CI 1.22-3.90; p = 0.01) increased risk of TB, and the aOR for severe vitamin D deficiency compared to sufficient vitamin D was 4.28 (95% CI 0.85-21.45; p = 0.08). Our Lima cohort study is limited by the short duration of follow-up, and the IPD meta-analysis is limited by the number of possible confounding covariates available across all studies. CONCLUSION: Our findings suggest vitamin D predicts TB disease risk in a dose-dependent manner and that the risk of TB disease is highest among HIV-positive individuals with severe vitamin D deficiency. Randomized control trials are needed to evaluate the possible role of vitamin D supplementation on reducing TB disease risk.

Fast Global Phosphoproteome Profiling of Jurkat T Cells by HIFU-TiO2-SCX-LC-MS/MS.

We propose a new workflow for fast phosphoproteome profiling. The workflow is based on the use of accelerated in-solution trypsin digestion under an ultrasonic field provided by high-intensity focused ultrasound (HIFU) combined with an inverse strategy based on TiO2 selective phosphopeptide enrichment, fractionation by strong cation exchange chromatography (SCX) and analysis by liquid chromatography tandem mass spectrometry (LC-MS/MS) using a high-resolution mass spectrometer. The performance of the method was established for the global phosphoproteome analysis of unstimulated human Jurkat leukemia T cells (E6.1). Using this accelerated workflow, 15367 phosphorylation sites from 13029 different phosphopeptides belonging to 3163 different phosphoproteins were efficiently identified with high-throughput and reproducibility in less than 15 h. The functional analysis revealed significant phosphorylation-based networks that are implicated in immune function and tumor development pathways. The present strategy, HIFU-TiO2-SCX-LC-MS/MS, is the fastest analytical method reported to date for generating large-scale phosphoproteomics data sets (<15 h).

Analysis of epinephrine, norepinephrine, and dopamine in urine samples of hospital patients by micellar liquid chromatography.

An analytical method based on micellar liquid chromatography was developed to determine the concentration of three catecholamines (epinephrine, norepinephrine, and dopamine) in urine. The detection of these compounds in urine can be useful to diagnose several diseases, related to stress and sympathoadrenal system dysfunction, using a non-invasive collection procedure. The sample pretreatment was a simple dilution in a micellar solution, filtration, and direct injection, thus avoiding time-consuming and tedious extraction steps. Therefore, there is no need to use an internal standard. The three catecholamines were eluted using a C18 column and a mobile phase of 0.055 M sodium dodecyl sulfate-1.5% methanol buffered at pH 3.8 running at 1.5 mL/min under isocratic mode in less than 25 min. The detection was performed by amperometry applying a constant potential of +0.5 V. The procedure was validated following the guidelines of the European Medicines Agency in terms of the following: calibration range (0.09-5 µg/mL), linearity (r(2) > 0.9995), limit of detection (0.02 µg/mL), within- and between-run accuracy (-6.5 to +8.4%) and precision (<10.2%), dilution integrity, matrix effect, robustness (<8.4), and stability. The obtained values were below those required by the guide. The method was rapid, easy-to-handle, eco-friendly, and safe and provides reliable quantitative data, and is thus useful for routine analysis. The procedure was applied to the analysis of epinephrine, norepinephrine, and dopamine in urine samples from patients of a local hospital.

Machine learning approach to identify malaria risk in travelers using real-world evidence.

Background: Pre-travel consultation and chemoprophylaxis measures for malaria are a key component in the prevention of imported malaria in travelers. In this study we report a predictive tool for assessing personalized malaria risk in travelers based on the analysis of electronic medical records from travel consultations. The tool aims to guide physicians in the recommendation of appropriate prophylaxis prior to their trip. We also provide best-practice recommendations for pre-processing noisy and highly sparse real world evidence data. Methods: We leveraged a large EMR dataset, containing demographic information about travelers and their destination. The data has been previously preprocessed using various strategies to handle missing and unbalanced data. We compared multiple machine learning approaches to assess the risk of malaria acquisition in travelers during their travels. Additionally, a feature importance analysis was performed using SHAP (SHapley Additive Explanations) values to identify patterns associated with malaria risk. Results: Our study revealed that our XGB models achieved high predictive capacity (AUC >0.80). The most significant features predicting malaria infection during travel included travel destinations with low malaria risk, vaccination history, number of countries visited, age, and trip duration. Remarkably, we were able to obtain a reduced model with only five features. When comparing this model with a population of travelers recommended for malaria chemoprophylaxis, we observed that it was deemed necessary in only 40% of these travelers. This suggests that 60% received chemoprophylaxis despite having a low personalized risk of malaria. Conclusion: We have developed an algorithmic tool that utilizes a concise survey to generate a personalized travel risk assessment, effectively minimizing the prescription of unnecessary malaria chemoprophylaxis. Through the identification of patterns linked to predictions, our model significantly enhances the efficacy of pre-travel consultations.

Rapid diagnostic tests for dengue would reduce hospitalizations, healthcare costs and antibiotic prescriptions in Spain: A cost-effectiveness analysis.

BACKGROUND: Current gold standard diagnostic techniques for dengue are expensive and time-consuming. Rapid diagnostic tests (RDTs) have been proposed as alternatives, although data about their potential impact in non-endemic areas is scarce. METHODS: We performed a cost-effectiveness analysis comparing the costs of dengue RDTs to the current standard of care for the management of febrile returning travelers in Spain. Effectiveness was measured in terms of potential averted hospital admissions and reduction of empirical antibiotics, based on 2015-2020 dengue admissions at Hospital Clinic Barcelona (Spain). RESULTS: Dengue RDTs were associated with 53.6% (95% CI: 33.9-72.5) reduction of hospital admissions and were estimated to save 289.08-389.31€ per traveler tested. Moreover, RDTs would have avoided the use of antibiotics in 46.4% (95% CI: 27.5-66.1) of dengue patients. DISCUSSION: Implementation of dengue RDTs for the management of febrile travelers is a cost-saving strategy that would lead to a reduction of half of dengue admissions and a reduction of inappropriate antibiotics in Spain.

MALrisk: a machine-learning­based tool to predict imported malaria in returned travellers with fever

BACKGROUND: Early diagnosis is key to reducing the morbi-mortality associated with P. falciparum malaria among international travellers. However, access to microbiological tests can be challenging for some healthcare settings. Artificial Intelligence could improve the management of febrile travellers. METHODS: Data from a multicentric prospective study of febrile travellers was obtained to build a machine-learning model to predict malaria cases among travellers presenting with fever. Demographic characteristics, clinical and laboratory variables were leveraged as features. Eleven machine-learning classification models were evaluated by 50-fold cross-validation in a Training set. Then, the model with the best performance, defined by the Area Under the Curve (AUC), was chosen for parameter optimization and evaluation in the Test set. Finally, a reduced model was elaborated with those features that contributed most to the model. RESULTS: Out of eleven machine-learning models, XGBoost presented the best performance (mean AUC of 0.98 and a mean F1 score of 0.78). A reduced model (MALrisk) was developed using only six features: Africa as a travel destination, platelet count, rash, respiratory symptoms, hyperbilirubinemia and chemoprophylaxis intake. MALrisk predicted malaria cases with 100% (95%CI 96-100) sensitivity and 72% (95%CI 68-75) specificity. CONCLUSIONS: The MALrisk can aid in the timely identification of malaria in non-endemic settings, allowing the initiation of empiric antimalarials and reinforcing the need for urgent transfer in healthcare facilities with no access to malaria diagnostic tests. This resource could be easily scalable to a digital application and could reduce the morbidity associated with late diagnosis.

Gut microbiota composition in travellers is associated with faecal lipocalin-2, a mediator of gut inflammation.

Introduction: We examined the gut microbiota of travellers returning from tropical areas with and without traveller's diarrhoea (TD) and its association with faecal lipocalin-2 (LCN2) levels. Methods: Participants were recruited at the Hospital Clinic of Barcelona, Spain, and a single stool sample was collected from each individual to perform the diagnostic of the etiological agent causing gastrointestinal symptoms as well as to measure levels of faecal LCN2 as a biomarker of gut inflammation. We also characterised the composition of the gut microbiota by sequencing the region V3-V4 from the 16S rRNA gene, and assessed its relation with the clinical presentation of TD and LCN2 levels using a combination of conventional statistical tests and unsupervised machine learning approaches. Results: Among 61 participants, 45 had TD, with 40% having identifiable etiological agents. Surprisingly, LCN2 levels were similar across groups, suggesting gut inflammation occurs without clinical TD symptoms. Differential abundance (DA) testing highlighted a microbial profile tied to high LCN2 levels, marked by increased Proteobacteria and Escherichia-Shigella, and decreased Firmicutes, notably Oscillospiraceae. UMAP analysis confirmed this profile's association, revealing distinct clusters based on LCN2 levels. The study underscores the discriminatory power of UMAP in capturing meaningful microbial patterns related to clinical variables. No relevant differences in the gut microbiota composition were found between travellers with or without TD. Discussion: The findings suggest a correlation between gut microbiome and LCN2 levels during travel, emphasising the need for further research to discern the nature of this relationship.

MXene-Polydopamine-antiCEACAM1 Antibody Complex as a Strategy for Targeted Ablation of Melanoma.

Photothermal therapy (PTT) is a method for eradicating tumor tissues through the use of photothermal materials and photosensitizing agents that absorb light energy from laser sources and convert it into heat, which selectively targets and destroys cancer cells while sparing healthy tissue. MXenes have been intensively investigated as photosensitizing agents for PTT. However, achieving the selectivity of MXenes to the tumor cells remains a challenge. Specific antibodies (Ab) against tumor antigens can achieve homing of the photosensitizing agents toward tumor cells, but their immobilization on MXene received little attention. Here, we offer a strategy for the selective ablation of melanoma cells using MXene-polydopamine-antiCEACAM1 Ab complexes. We coated Ti3C2Tx MXene with polydopamine (PDA), a natural compound that attaches Ab to the MXene surface, followed by conjugation with an anti-CEACAM1 Ab. Our experiments confirm the biocompatibility of the Ti3C2Tx-PDA and Ti3C2Tx-PDA-antiCEACAM1 Ab complexes across various cell types. We also established a protocol for the selective ablation of CEACAM1-positive melanoma cells using near-infrared irradiation. The obtained complexes exhibit high selectivity and efficiency in targeting and eliminating CEACAM1-positive melanoma cells while sparing CEACAM1-negative cells. These results demonstrate the potential of MXene-PDA-Ab complexes for cancer therapy. They underline the critical role of targeted therapies in oncology, offering a promising avenue for the precise and safe treatment of melanoma and possibly other cancers characterized by specific biomarkers. Future research will aim to refine these complexes for clinical use, paving the way for new strategies for cancer treatment.

Assessing viral metagenomics for the diagnosis of acute undifferentiated fever in returned travellers: a multicenter cohort study.

BACKGROUND: Up to 45% of febrile returning travellers remain undiagnosed after a thorough diagnostic work-up, even at referral centres. Although metagenomic next-generation sequencing (mNGS) has emerged as a promising tool, evidence of its usefulness in imported fever is very limited. METHODS: Travellers returning with fever were prospectively recruited in three referral clinics from November 2017 to November 2019. Unbiased mNGS optimised for virus detection was performed on serum samples of participants with acute undifferentiated febrile illness (AUFI), and results were compared to those obtained by reference diagnostic methods (RDM). RESULTS: Among 507 returned febrile travellers, 433(85.4%) presented with AUFI. Dengue virus (n = 86) and Plasmodium spp. (n = 83) were the most common causes of fever. 103/433(23.8%) AUFI remained undiagnosed at the end of the follow-up.Metagenomic next-generation sequencing unveiled potentially pathogenic microorganisms in 196/433(38.7%) AUFI. mNGS identifications were more common in patients with a shorter duration of fever (42.3% in ≤5 days vs 28.7% in >5 days, P = 0.005). Potential causes of fever were revealed in 25/103(24.2%) undiagnosed AUFI and 5/23(21.7%) travellers with severe undiagnosed AUFI. Missed severe aetiologies included eight bacterial identifications and one co-infection of B19 parvovirus and Aspergillus spp.Additional identifications indicating possible co-infections occurred in 29/316(9.2%) travellers with AUFI, and in 11/128(8.6%) travellers with severe AUFI, who had received a diagnosis through RDM. The most common co-infections detected in severe AUFI were caused by Gram-negative bacteria. Serum mNGS was unable to detect >50% of infectious diagnoses achieved by RDM and also yielded 607 non-pathogenic identifications. DISCUSSION: mNGS of serum can be a valuable diagnostic tool for selected travellers with undiagnosed AUFI or severe disease in addition to reference diagnostic techniques, especially during the first days of symptoms. Nevertheless, mNGS results interpretation presents a great challenge. Further studies evaluating the performance of mNGS using different sample types and protocols tailored to non-viral agents are needed.

Not all severe malaria cases are severe: Is it time to redefine severity criteria for malaria in non-endemic regions?

BACKGROUND: The current definition of severe malaria in non-endemic areas follows WHO criteria, which mainly target children in malaria-endemic areas, potentially misclassifying cases in non-endemic regions. We assessed the performance of a modified severe malaria classification criteria within our patient cohort. METHODS: A cohort study of patients managed for malaria in a non-endemic setting (2005-2023) was analyzed. We classified patients into severe malaria (SM) using WHO 2013 criteria except for hyperparasitemia, where 2 % threshold was applied. Patients with SM were distinguished as very severe malaria (VSM) when presenting at least one of the following conditions: parasitemia >10 %, pulmonary edema, impaired consciousness, seizures, renal failure, metabolic acidosis or hyperlactatemia, shock or hypoglycemia. In patients with SM and no criteria for VSM, less severe malaria (LSM) was defined by: 2-10 % parasitemia, hyperbilirubinemia, prostration, anemia or minor bleeding. The primary composite outcome was death or the need for a life-saving intervention, as analyzed in the three comparative groups. Secondary outcome was the prevalence of co-infections. RESULTS: Among 506 patients with malaria, 176 (34.8 %) presented with SM. A total of 37 (7.3 %) patients developed a life-threatening condition, namely death (n = 4) and/or the need for life-saving interventions (n = 34). All fatalities and 33 out of the 34 life-saving interventions occurred in the VSM group. Patients in LSM group did not develop any life-threatening conditions. As to co-infections, 28 (5.5 %) patients had a community-acquired co-infection, with no differences between groups (p = 0.763). CONCLUSIONS: Severity criteria definitions would benefit from a review when assessing patients with malaria in non-endemic areas. Within the spectrum of SM, patients reclassified as LSM have a low risk of developing a life-threatening condition and present low co-infection incidence and could benefit from management out of intensive care units and a restrictive use of empirical antibiotics.

Consensus definitions in imported human schistosomiasis: a GeoSentinel and TropNet Delphi study.

Terminology in schistosomiasis is not harmonised, generating misunderstanding in data interpretation and clinical descriptions. This study aimed to achieve consensus on definitions of clinical aspects of schistosomiasis in migrants and returning travellers. We applied the Delphi method. Experts from institutions affiliated with GeoSentinel and TropNet, identified through clinical and scientific criteria, were invited to participate. Five external reviewers revised and pilot-tested the statements. Statements focusing on the definitions of acute or chronic; possible, probable, or confirmed; active; and complicated schistosomiasis were managed through REDCap and replies managed in a blinded manner. Round 1 mapped the definitions used by experts; subsequent rounds were done to reach consensus, or quantify disagreement, on the proposed statements. Data were analysed with percentages, medians, and IQRs of a 5-point Likert scale. The study was terminated on the basis of consensus or stability-related and time-related criteria. 28 clinicians and scientists met the criteria for experts. 25 (89%) of 28 experts replied to Round 1, 18 (64%) of 28 to Round 2, 19 (68%) of 28 to Round 3, and 21 (75%) of 28 to at least two rounds. High-level consensus (79-100% agreement and IQRs ≤1) was reached for all definitions. Consensus definitions will foster harmonised scientific and clinical communication and support future research and development of management guidelines for schistosomiasis.