Clinical and Demographic Factors Associated With Kaposi Sarcoma-Associated Herpesvirus Shedding in Saliva or Cervical Secretions in a Cohort of Tanzanian Women.

Background: Reasons for the high prevalence of Kaposi sarcoma-associated herpesvirus (KSHV) in sub-Saharan Africa, and risk factors leading to viral reactivation and shedding, remain largely undefined. Preliminary studies have suggested that schistosome infection, which has been associated with impaired viral control, is associated with KSHV. In this study we sought to determine the relationship between active Schistosoma mansoni or Schistosoma haematobium infection and KSHV shedding. Methods: We quantified KSHV DNA in saliva and cervical swabs from 2 cohorts of women living in northwestern Tanzanian communities endemic for S mansoni or S haematobium by real-time polymerase chain reaction. χ2 and Fisher exact tests were used to determine differences in clinical and demographic factors between those who were and were not shedding KSHV. Results: Among 139 total women, 44.6% were KSHV seropositive. Six percent of those with S mansoni and 17.1% of those with S haematobium were actively shedding KSHV in saliva and none in cervical samples. Women from the S mansoni cohort who were shedding virus reported infertility more frequently (80% vs 19.5%, P = .009). There was no difference in frequency of KSHV salivary shedding between schistosome-infected and -uninfected women. Conclusions: In an area with high KSHV seroprevalence and endemic schistosome infections, we provide the first report with data demonstrating no association between schistosome infection and salivary or cervical herpesvirus shedding. KSHV salivary shedding was associated with infertility, a known effect of another herpesvirus, human herpesvirus 6.

Schistosome infection among pregnant women in the rural highlands of Madagascar: A cross-sectional study calling for public health interventions in vulnerable populations.

INTRODUCTION: Schistosomiasis is a parasitic infection highly prevalent in sub-Saharan Africa (SSA) with Madagascar being among the countries with highest burden of the disease worldwide. Despite WHO recommendations, suggesting treatment of pregnant women after the first trimester, this group is still excluded from Mass Drug Administration programs. Our study, had the objective to measure the prevalence of schistosome infection among pregnant women in Madagascar in order to inform public health policies for treatment in this vulnerable population. METHODS: Women were recruited for this cross-sectional study between April 2019 and February 2020 when attending Antenatal Care Services (ANCs) at one of 42 included Primary Health Care Centers. The urine-based upconverting reporter particle, lateral flow (UCP-LF) test detecting circulating anodic antigen was used for the detection of schistosome infections. To identify factors associated with the prevalence of schistosome infection crude and adjusted prevalence ratios and 95% CIs were estimated using mixed-effect Poisson regression. RESULTS: Among 4,448 participating women aged between 16 and 47 years, the majority (70.4%, 38 n = 3,133) resided in rural settings. Overall, the prevalence of schistosome infection was 55.9% (n = 2486, CI 95%: 53.3-58.5). A statistically significant association was found with age group (increased prevalence in 31-47 years old, compared to 16-20 years old (aPR = 1.15, CI 95%: 1.02-1.29) and with uptake of antimalaria preventive treatment (decreased prevalence, aPR = 0.85, CI 95%: 0.77-0.95). No other associations of any personal characteristics or contextual factors with schistosome infection were found in our multivariate regression analysis. DISCUSSION AND CONCLUSION: The high prevalence of schistosome infection in pregnant women supports the consideration of preventive schistosomiasis treatment in ANCs of the Malagasy highlands. We strongly advocate for adapting schistosomiasis programs in highly endemic contexts. This, would contribute to both the WHO and SDGs agendas overall to improving the well-being of women and consequently breaking the vicious cycle of poverty perpetuated by schistosomiasis.

Flow-S: A Field-Deployable Device with Minimal Hands-On Effort to Concentrate and Quantify Schistosoma Circulating Anodic Antigen (CAA) from Large Urine Volumes.

A laboratory-based lateral flow (LF) test that utilizes up-converting reporter particles (UCP) for ultrasensitive quantification of Schistosoma circulating anodic antigen (CAA) in urine is a well-accepted test to identify active infection. However, this UCP-LF CAA test requires sample pre-treatment steps not compatible with field applications. Flow, a new low-cost disposable, allows integration of large-volume pre-concentration of urine analytes and LF detection into a single field-deployable device. We assessed a prototype Flow-Schistosoma (Flow-S) device with an integrated UCP-LF CAA test strip, omitting all laboratory-based steps, to enable diagnosis of active Schistosoma infection in the field using urine. Flow-S is designed for large-volume (5-20 mL) urine, applying passive paper-based filtration and antibody-based CAA concentration. Samples tested for schistosome infection were collected from women of reproductive age living in a Tanzania region where S. haematobium infection is endemic. Fifteen negative and fifteen positive urine samples, selected based on CAA levels quantified in paired serum, were analyzed with the prototype Flow-S. The current Flow-S prototype, with an analytical lower detection limit of 1 pg CAA/mL, produced results correlated with the laboratory-based UCP-LF CAA test. Urine precipitates occurred in frozen banked samples and affected accurate quantification; however, this should not occur in fresh urine. Based on the findings of this study, Flow-S appears suitable to replace the urine pre-treatment required for the laboratory-based UCP-LF CAA test, thus allowing true field-based applications with fresh urine samples. The urine precipitates observed with frozen samples, though less important given the goal of testing fresh urines, warrant additional investigation to evaluate methods for mitigation. Flow-S devices permit testing of pooled urine samples with applications for population stratified testing. A field test with fresh urine samples, a further optimized Flow-S device, and larger statistical power has been scheduled.

An Unsupervised Machine Learning Approach for the Automatic Construction of Local Chemical Descriptors.

Condensing the many physical variables defining a chemical system into a fixed-size array poses a significant challenge in the development of chemical Machine Learning (ML). Atom Centered Symmetry Functions (ACSFs) offer an intuitive featurization approach by means of a tedious and labor-intensive selection of tunable parameters. In this work, we implement an unsupervised ML strategy relying on a Gaussian Mixture Model (GMM) to automatically optimize the ACSF parameters. GMMs effortlessly decompose the vastness of the chemical and conformational spaces into well-defined radial and angular clusters, which are then used to build tailor-made ACSFs. The unsupervised exploration of the space has demonstrated general applicability across a diverse range of systems, spanning from various unimolecular landscapes to heterogeneous databases. The impact of the sampling technique and temperature on space exploration is also addressed, highlighting the particularly advantageous role of high-temperature Molecular Dynamics (MD) simulations. The reliability of the resulting features is assessed through the estimation of the atomic charges of a prototypical capped amino acid and a heterogeneous collection of CHON molecules. The automatically constructed ACSFs serve as high-quality descriptors, consistently yielding typical prediction errors below 0.010 electrons bound for the reported atomic charges. Altering the spatial distribution of the functions with respect to the cluster highlights the critical role of symmetry rupture in achieving significantly improved features. More specifically, using two separate functions to describe the lower and upper tails of the cluster results in the best performing models with errors as low as 0.006 electrons. Finally, the effectiveness of finely tuned features was checked across different architectures, unveiling the superior performance of Gaussian Process (GP) models over Feed Forward Neural Networks (FFNNs), particularly in low-data regimes, with nearly a 2-fold increase in prediction quality. Altogether, this approach paves the way toward an easier construction of local chemical descriptors, while providing valuable insights into how radial and angular spaces should be mapped. Finally, this work opens the possibility of encoding many-body information beyond angular terms into upcoming ML features.

Probing Non-Covalent Interactions through Molecular Balances: A REG-IQA Study.

The interaction energies of two series of molecular balances (1-X with X = H, Me, OMe, NMe2 and 2-Y with Y = H, CN, NO2, OMe, NMe2) designed to probe carbonyl…carbonyl interactions were analysed at the B3LYP/6-311++G(d,p)-D3 level of theory using the energy partitioning method of Interacting Quantum Atoms/Fragments (IQA/IQF). The partitioned energies are analysed by the Relative Energy Gradient (REG) method, which calculates the correlation between these energies and the total energy of a system, thereby explaining the role atoms have in the energetic behaviour of the total system. The traditional "back-of-the-envelope" open and closed conformations of molecular balances do not correspond to those of the lowest energy. Hence, more care needs to be taken when considering which geometries to use for comparison with the experiment. The REG-IQA method shows that the 1-H and 1-OMe balances behave differently to the 1-Me and 1-NMe2 balances because the latter show more prominent electrostatics between carbonyl groups and undergoes a larger dihedral rotation due to the bulkiness of the functional groups. For the 2-Y balance, REG-IQA shows the same behaviour across the series as the 1-H and 1-OMe balances. From an atomistic point of view, the formation of the closed conformer is favoured by polarisation and charge-transfer effects on the amide bond across all balances and is counterbalanced by a de-pyramidalisation of the amide nitrogen. Moreover, focusing on the oxygen of the amide carbonyl and the α-carbon of the remaining carbonyl group, electrostatics have a major role in the formation of the closed conformer, which goes against the well-known n-π* interaction orbital overlap concept. However, REG-IQF shows that exchange-correlation energies overtake electrostatics for all the 2-Y balances when working with fragments around the carbonyl groups, while they act on par with electrostatics for the 1-OMe and 1-NMe2. REG-IQF also shows that exchange-correlation energies in the 2-Y balance are correlated to the inductive electron-donating and -withdrawing trends on aromatic groups. We demonstrate that methods such as REG-IQA/IQF can help with the fine-tuning of molecular balances prior to the experiment and that the energies that govern the probed interactions are highly dependent on the atoms and functional groups involved.

From task structures to world models: what do LLMs know?

In what sense does a large language model (LLM) have knowledge? We answer by granting LLMs 'instrumental knowledge': knowledge gained by using next-word generation as an instrument. We then ask how instrumental knowledge is related to the ordinary, 'worldly knowledge' exhibited by humans, and explore this question in terms of the degree to which instrumental knowledge can be said to incorporate the structured world models of cognitive science. We discuss ways LLMs could recover degrees of worldly knowledge and suggest that such recovery will be governed by an implicit, resource-rational tradeoff between world models and tasks. Our answer to this question extends beyond the capabilities of a particular AI system and challenges assumptions about the nature of knowledge and intelligence.

FFLUX molecular simulations driven by atomic Gaussian process regression models.

Machine learning (ML) force fields are revolutionizing molecular dynamics (MD) simulations as they bypass the computational cost associated with ab initio methods but do not sacrifice accuracy in the process. In this work, the GPyTorch library is used to create Gaussian process regression (GPR) models that are interfaced with the next-generation ML force field FFLUX. These models predict atomic properties of different molecular configurations that appear in a progressing MD simulation. An improved kernel function is utilized to correctly capture the periodicity of the input descriptors. The first FFLUX molecular simulations of ammonia, methanol, and malondialdehyde with the updated kernel are performed. Geometry optimizations with the GPR models result in highly accurate final structures with a maximum root-mean-squared deviation of 0.064 Å and sub-kJ mol-1 total energy predictions. Additionally, the models are tested in 298 K MD simulations with FFLUX to benchmark for robustness. The resulting energy and force predictions throughout the simulation are in excellent agreement with ab initio data for ammonia and methanol but decrease in quality for malondialdehyde due to the increased system complexity. GPR model improvements are discussed, which will ensure the future scalability to larger systems.

Validation of artificial intelligence-based digital microscopy for automated detection of Schistosoma haematobium eggs in urine in Gabon.

INTRODUCTION: Schistosomiasis is a significant public health concern, especially in Sub-Saharan Africa. Conventional microscopy is the standard diagnostic method in resource-limited settings, but with limitations, such as the need for expert microscopists. An automated digital microscope with artificial intelligence (Schistoscope), offers a potential solution. This field study aimed to validate the diagnostic performance of the Schistoscope for detecting and quantifying Schistosoma haematobium eggs in urine compared to conventional microscopy and to a composite reference standard (CRS) consisting of real-time PCR and the up-converting particle (UCP) lateral flow (LF) test for the detection of schistosome circulating anodic antigen (CAA). METHODS: Based on a non-inferiority concept, the Schistoscope was evaluated in two parts: study A, consisting of 339 freshly collected urine samples and study B, consisting of 798 fresh urine samples that were also banked as slides for analysis with the Schistoscope. In both studies, the Schistoscope, conventional microscopy, real-time PCR and UCP-LF CAA were performed and samples with all the diagnostic test results were included in the analysis. All diagnostic procedures were performed in a laboratory located in a rural area of Gabon, endemic for S. haematobium. RESULTS: In study A and B, the Schistoscope demonstrated a sensitivity of 83.1% and 96.3% compared to conventional microscopy, and 62.9% and 78.0% compared to the CRS. The sensitivity of conventional microscopy in study A and B compared to the CRS was 61.9% and 75.2%, respectively, comparable to the Schistoscope. The specificity of the Schistoscope in study A (78.8%) was significantly lower than that of conventional microscopy (96.4%) based on the CRS but comparable in study B (90.9% and 98.0%, respectively). CONCLUSION: Overall, the performance of the Schistoscope was non-inferior to conventional microscopy with a comparable sensitivity, although the specificity varied. The Schistoscope shows promising diagnostic accuracy, particularly for samples with moderate to higher infection intensities as well as for banked sample slides, highlighting the potential for retrospective analysis in resource-limited settings. TRIAL REGISTRATION: NCT04505046 ClinicalTrials.gov.

Application of the FFLUX Force Field to Molecular Crystals: A Study of Formamide.

In this work, we present the first application of the quantum chemical topology force field FFLUX to the solid state. FFLUX utilizes Gaussian process regression machine learning models trained on data from the interacting quantum atom partitioning scheme to predict atomic energies and flexible multipole moments that change with geometry. Here, the ambient (α) and high-pressure (ß) polymorphs of formamide are used as test systems and optimized using FFLUX. Optimizing the structures with increasing multipolar ranks indicates that the lattice parameters of the α phase differ by less than 5% to the experimental structure when multipole moments up to the quadrupole are used. These differences are found to be in line with the dispersion-corrected density functional theory. Lattice dynamics calculations are also found to be possible using FFLUX, yielding harmonic phonon spectra comparable to dispersion-corrected DFT while enabling larger supercells to be considered than is typically possible with first-principles calculations. These promising results indicate that FFLUX can be used to accurately determine properties of molecular solids that are difficult to access using DFT, including the structural dynamics, free energies, and properties at finite temperature.

Interacting Quantum Atoms and Multipolar Electrostatic Study of XH···π Interactions.

The interaction energies of nine XH···π (X = C, N, and O) benzene-containing van der Waals complexes were analyzed, at the atomic and fragment levels, using QTAIM multipolar electrostatics and the energy partitioning method interacting quantum atoms/fragment (IQA/IQF). These descriptors were paired with the relative energy gradient method, which solidifies the connection between quantum mechanical properties and chemical interpretation. This combination provides a precise understanding, both qualitative and quantitative, of the nature of these interactions, which are ubiquitous in biochemical systems. The formation of the OH···π and NH···π systems is electrostatically driven, with the Qzz component of the quadrupole moment of the benzene carbons interacting with the charges of X and H in XH. There is the unexpectedly intramonomeric role of X-H (X = O, N) where its electrostatic energy helps the formation of the complex and its covalent energy thwarts it. However, the CH···π interaction is governed by exchange-correlation energies, thereby establishing a covalent character, as opposed to the literature's designation as a noncovalent interaction. Moreover, dispersion energy is relevant, statically and in absolute terms, but less relevant compared to other energy components in terms of the formation of the complex. Multipolar electrostatics are similar across all systems.

Safety and infectivity of female cercariae in Schistosoma-naïve, healthy participants: a controlled human Schistosoma mansoni infection study.

BACKGROUND: A controlled human infection model for schistosomiasis (CHI-S) can speed up vaccine development and provides insight into early immune responses following schistosome exposure. Recently, we established CHI-S model using single-sex male-only Schistosoma mansoni (Sm) cercariae in Schistosoma-naïve individuals. Given important differences in antigenic profile and human immune responses to schistosomes of different sex, we pioneered a single-sex female-only CHI-S model for future use in vaccine development. METHODS: We exposed 13 healthy, Schistosoma-naïve adult participants to 10 (n = 3) or 20 (n = 10) female cercariae and followed for 20 weeks, receiving treatment with praziquantel (PZQ) 60 mg/kg at week 8 and 12 after exposure. FINDINGS: The majority (11/13) participants reported rash and/or itch at the site of exposure, 5/13 had transient symptoms of acute schistosomiasis. Exposure to 20 cercariae led to detectable infection, defined as serum circulating anodic antigen levels >1.0 pg/mL, in 6/10 participants. Despite two rounds of PZQ treatment, 4/13 participants showed signs of persistent infection. Additional one- or three-day PZQ treatment (1 × 60 mg/kg and 3 × 60 mg/kg) or artemether did not result in cure, but over time three participants self-cured. Antibody, cellular, and cytokine responses peaked at week 4 post infection, with a mixed Th1, Th2, and regulatory profile. Cellular responses were (most) discriminative for symptoms. INTERPRETATION: Female-only infections exhibit similar clinical and immunological profiles as male-only infections but are more resistant to PZQ treatment. This limits future use of this model and may have important implications for disease control programs. FUNDING: European Union's Horizon 2020 (grant no. 81564).

Management of adult-onset Still's disease: evidence- and consensus-based recommendations by experts.

BACKGROUND: Adult-onset Still's disease (AOSD) is a rare condition characterized by fevers, rash, and arthralgia/arthritis. Most doctors treating AOSD in the Netherlands treat <5 patients per year. Currently, there is no internationally accepted treatment guideline for AOSD. OBJECTIVES: To conduct a Delphi panel aimed at reaching consensus about diagnostic and treatment strategies for patients with AOSD and to use the outcomes as a basis for a treatment algorithm. METHODS: The Delphi panel brought together 18 AOSD experts: rheumatologists, internists and paediatricians. The Delphi process consisted of 3 rounds. In the first two rounds, online list of questions and statements were completed. In the third round, final statements were discussed during a virtual meeting and a final vote took place. Consensus threshold was set at 80%. Two targeted literature searches were performed identifying the level of evidence of the consensus-based statements. RESULTS: Consensus was reached on 29 statements, including statements related to diagnosis and diagnostic tests, definition of response and remission, the therapy, the use of methotrexate, and tapering of treatment. The panel consented on reduction of the use of glucocorticoids to avoid side-effect, and preferred the use of biologics over conventional treatment. The role of interleukin-1 and interleukin-6 blocking agents was considered important in the treatment of AOSD. CONCLUSIONS: In this Delphi panel, a high level of consensus was achieved on recommendations for diagnosis and therapy of AOSD that can serve as a basis for a treatment guideline.

Aza-Michael Addition in Explicit Solvent: A Relative Energy Gradient-Interacting Quantum Atoms Study.

Aza-Michael additions are key reactions in organic synthesis. We investigate, from a theoretical and computational point of view, several examples ranging from weak to strong electrophiles in dimethylsulfoxide treated as explicit solvent. We use the REG-IQA method, which is a quantum topological energy decomposition (Interacting Quantum Atoms, IQA) coupled to a chemical-interpretation calculator (Relative Energy Gradient, REG). We focus on the rate-limiting addition step in order to unravel the different events taking place in this step, and understand the influence of solvent on the reaction, with an eye on predicting the Mayr electrophilicity. For the first time, a link is established between an REG-IQA analysis and experimental values.

Diagnostic performance of host protein signatures as a triage test for active pulmonary TB.

The current four-symptom screen recommended by the World Health Organization (WHO) is widely used as screen to initiate diagnostic testing for active pulmonary tuberculosis (TB), yet the performance is poor especially when TB prevalence is low. In contrast, more sensitive molecular tests are less suitable for placement at primary care level in low-resource settings. In order to meet the WHO End TB targets, new diagnostic approaches are urgently needed to find the missing undiagnosed cases. Proteomics-derived blood host biomarkers have been explored because protein detection technologies are suitable for the point-of-care setting and could meet cost targets. This study aimed to find a biomarker signature that fulfills WHO's target product profile (TPP) for a TB screening. Twelve blood-based protein biomarkers from three sample populations (Vietnam, Peru, and South Africa) were analyzed individually and in combinations via advanced statistical methods and machine learning algorithms. The combination of I-309, SYWC and kallistatin showed the most promising results to discern active TB throughout the data sets meeting the TPP for a triage test in adults from two countries (Peru and South Africa). The top-performing individual markers identified at the global level (I-309 and SYWC) were also among the best-performing markers at country level in South Africa and Vietnam. This analysis clearly shows that a host protein biomarker assay is feasible in adults for certain geographical regions based on one or two biomarkers with a performance that meets minimal WHO TPP criteria.

Development of lateral flow assays to detect host proteins in cattle for improved diagnosis of bovine tuberculosis.

Bovine tuberculosis (bTB), caused by Mycobacterium bovis (M. bovis) infection in cattle, is an economically devastating chronic disease for livestock worldwide. Efficient disease control measures rely on early and accurate diagnosis using the tuberculin skin test (TST) and interferon-gamma release assays (IGRAs), followed by culling of positive animals. Compromised performance of TST and IGRA, due to BCG vaccination or co-infections with non-tuberculous mycobacteria (NTM), urges improved diagnostics. Lateral flow assays (LFAs) utilizing luminescent upconverting reporter particles (UCP) for quantitative measurement of host biomarkers present an accurate but less equipment- and labor-demanding diagnostic test platform. UCP-LFAs have proven applications for human infectious diseases. Here, we report the development of UCP-LFAs for the detection of six bovine proteins (IFN-γ, IL-2, IL-6, CCL4, CXCL9, and CXCL10), which have been described by ELISA as potential biomarkers to discriminate M. bovis infected from naïve and BCG-vaccinated cattle. We show that, in line with the ELISA data, the combined PPDb-induced levels of IFN-γ, IL-2, IL-6, CCL4, and CXCL9 determined by UCP-LFAs can discriminate M. bovis challenged animals from naïve (AUC range: 0.87-1.00) and BCG-vaccinated animals (AUC range: 0.97-1.00) in this cohort. These initial findings can be used to develop a robust and user-friendly multi-biomarker test (MBT) for bTB diagnosis.

Establishing a single-sex controlled human Schistosoma mansoni infection model for Uganda: protocol for safety and dose-finding trial.

Control of schistosomiasis depends on a single drug, praziquantel, with variable cure rates, high reinfection rates, and risk of drug resistance. A vaccine could transform schistosomiasis control. Preclinical data show that vaccine development is possible, but conventional vaccine efficacy trials require high incidence, long-term follow-up, and large sample size. Controlled human infection studies (CHI) can provide early efficacy data, allowing the selection of optimal candidates for further trials. A Schistosoma CHI has been established in the Netherlands but responses to infection and vaccines differ in target populations in endemic countries. We aim to develop a CHI for Schistosoma mansoni in Uganda to test candidate vaccines in an endemic setting. This is an open-label, dose-escalation trial in two populations: minimal, or intense, prior Schistosoma exposure. In each population, participants will be enrolled in sequential dose-escalating groups. Initially, three volunteers will be exposed to 10 cercariae. If all show infection, seven more will be exposed to the same dose. If not, three volunteers in subsequent groups will be exposed to higher doses (20 or 30 cercariae) following the same algorithm, until all 10 volunteers receiving a particular dose become infected, at which point the study will be stopped for that population. Volunteers will be followed weekly after infection until CAA positivity or to 12 weeks. Once positive, they will be treated with praziquantel and followed for one year. The trial registry number is ISRCTN14033813 and all approvals have been obtained. The trial will be subjected to monitoring, inspection, and/or audits.

Self-orienting in human and machine learning.

A current proposal for a computational notion of self is a representation of one's body in a specific time and place, which includes the recognition of that representation as the agent. This turns self-representation into a process of self-orientation, a challenging computational problem for any human-like agent. Here, to examine this process, we created several 'self-finding' tasks based on simple video games, in which players (N = 124) had to identify themselves out of a set of candidates in order to play effectively. Quantitative and qualitative testing showed that human players are nearly optimal at self-orienting. In contrast, well-known deep reinforcement learning algorithms, which excel at learning much more complex video games, are far from optimal. We suggest that self-orienting allows humans to flexibly navigate new settings.

Schistosoma mansoni infection alters the host pre-vaccination environment resulting in blunted Hepatitis B vaccination immune responses.

Schistosomiasis is a disease caused by parasitic flatworms of the Schistosoma spp., and is increasingly recognized to alter the immune system, and the potential to respond to vaccines. The impact of endemic infections on protective immunity is critical to inform vaccination strategies globally. We assessed the influence of Schistosoma mansoni worm burden on multiple host vaccine-related immune parameters in a Ugandan fishing cohort (n = 75) given three doses of a Hepatitis B (HepB) vaccine at baseline and multiple timepoints post-vaccination. We observed distinct differences in immune responses in instances of higher worm burden, compared to low worm burden or non-infected. Concentrations of pre-vaccination serum schistosome-specific circulating anodic antigen (CAA), linked to worm burden, showed a significant bimodal distribution associated with HepB titers, which was lower in individuals with higher CAA values at month 7 post-vaccination (M7). Comparative chemokine/cytokine responses revealed significant upregulation of CCL19, CXCL9 and CCL17 known to be involved in T cell activation and recruitment, in higher CAA individuals, and CCL17 correlated negatively with HepB titers at month 12 post-vaccination. We show that HepB-specific CD4+ T cell memory responses correlated positively with HepB titers at M7. We further established that those participants with high CAA had significantly lower frequencies of circulating T follicular helper (cTfh) subpopulations pre- and post-vaccination, but higher regulatory T cells (Tregs) post-vaccination, suggesting changes in the immune microenvironment in high CAA could favor Treg recruitment and activation. Additionally, we found that changes in the levels of innate-related cytokines/chemokines CXCL10, IL-1ß, and CCL26, involved in driving T helper responses, were associated with increasing CAA concentration. This study provides further insight on pre-vaccination host responses to Schistosoma worm burden which will support our understanding of vaccine responses altered by pathogenic host immune mechanisms and memory function and explain abrogated vaccine responses in communities with endemic infections.

Field evaluation of a point-of-care triage test for active tuberculosis (TriageTB).

BACKGROUND: To improve tuberculosis (TB) diagnosis, the World Health Organisation (WHO) has called for a non-sputum based triage test to focus TB testing on people with a high likelihood of having active pulmonary tuberculosis (TB). Various host or pathogen biomarker-based testing devices are in design stage and require validity assessment. Host biomarkers have shown promise to accurately rule out active TB, but further research is required to determine generalisability. The TriageTB diagnostic test study aims to assess the accuracy of diagnostic test candidates, as well as field-test, finalise the design and biomarker signature, and validate a point-of-care multi-biomarker test (MBT). METHODS: This observational diagnostic study will evaluate sensitivity and specificity of biomarker-based diagnostic candidates including the MBT and Xpert® TB Fingerstick cartridge compared with a gold-standard composite TB outcome classification defined by symptoms, sputum GeneXpert® Ultra, smear and culture, radiological features, response to TB therapy and presence of an alternative diagnosis. The study will be conducted in research sites in South Africa, Uganda, The Gambia and Vietnam which all have high TB prevalence. The two-phase design allows for finalisation of the MBT in Phase 1 in which candidate host proteins will be evaluated on stored serum from Asia, South Africa and South America and on fingerstick blood from 50 newly recruited participants per site. The MBT test will then be locked down and validated in Phase 2 on 250 participants per site. DISCUSSION: By targeting confirmatory TB testing to those with a positive triage test, 75% of negative GXPU may be avoided, thereby reducing diagnostic costs and patient losses during the care cascade. This study builds on previous biomarker research and aims to identify a point-of-care test meeting or exceeding the minimum World Health Organisation target product profile of a 90% sensitivity and 70% specificity. Streamlining TB testing by identifying individuals with a high likelihood of TB should improve TB resources use and, in so doing, improve TB care. TRIAL REGISTRATION: NCT04232618 (clinicaltrials.gov) Date of registration: 16 January 2020.

How to Compute Atomistic Insight in DFT Clusters: The REG-IQA Approach.

The relative energy gradient (REG) method is paired with the topological energy partitioning method interacting quantum atoms (IQA), as REG-IQA, to provide detailed and unbiased knowledge on the intra- and interatomic interactions. REG operates on a sequence of geometries representing a dynamical change of a system. Its recent application to peptide hydrolysis of the human immunodeficiency virus-1 (HIV-1) protease (PDB code: 4HVP) has demonstrated its full potential in recovering reaction mechanisms and through-space electrostatic and exchange-correlation effects, making it a compelling tool for analyzing enzymatic reactions. In this study, the computational efficiency of the REG-IQA method for the 133-atom HIV-1 protease quantum mechanical system is analyzed in every detail and substantially improved by means of three different approaches. The first approach of smaller integration grids for IQA integrations reduces the computational overhead by about a factor of 3. The second approach uses the line-simplification Ramer-Douglas-Peucker (RDP) algorithm, which outputs the minimal number of geometries necessary for the REG-IQA analysis for a predetermined root mean squared error (RMSE) tolerance. This cuts the computational time of the whole REG analysis by a factor of 2 if an RMSE of 0.5 kJ/mol is considered. The third approach consists of a "biased" or "unbiased" selection of a specific subset of atoms of the whole initial quantum mechanical model wave-function, which results in more than a 10-fold speed-up per geometry for the IQA calculation, without deterioration of the outcome of the REG-IQA analysis. Finally, to show the capability of these approaches, the findings gathered from the HIV-1 protease system are also applied to a different system named haloalcohol dehalogenase (HheC). In summary, this study takes the REG-IQA method to a computationally feasible and highly accurate level, making it viable for the analysis of a multitude of enzymatic systems.