julilili42/papers huggingface dataset:
Kinetic and structure-based comparisons of silent and stimulatory flagellin interactions with TLR5
2024-12-09

Abstract The bacterial protein flagellin is the sole ligand of the innate immune receptor Toll- like receptor 5 (TLR5). Flagellins with strong agonism bind TLR5 at their D1 and D0 domains, while poor agonist “silent” flagellins bind with D1 only. However, D0-TLR5 interactions insufficiently explain the silent phenotype. Here, we characterize the D1 domain binding kinetics of the silent flagellin Rh FlaB compared to the strong canonical agonist St FliC. Using Surface Plasmon Resonance, we show that the Rh FlaB-D1 binds more strongly than St FliC-D1, but forms shorter-lived complexes. Cryo-EM analysis of Rh FlaB showed its D1 primary interface (PI) contains two distinct hydrophobic pockets, which should facilitate rapid association, while its D1’s secondary interface (SI) is dominated by negatively charged residues, which likely impede residue-residue interactions. Comparisons with an existing St FliC-D1 structure suggest that strong agonism requires strong binding at both the PI and SI of the D1, and silent flagellins evade detection partly through weaker SI interactions. These findings offer a foundation for designing targeted interventions that can modulate TLR5 activity to influence immunity, inflammation, or even gut microbiome composition.
Screening for substandard and falsified medicines in Nigeria using visual inspection and GPHF-Minilab analysis: lessons learnt for future training of health workers and pharmacy personnel
2024-12-09

Visual inspection, and screening analysis with simple, rapid and inexpensive methods, are important in the surveillance for SF medicines in LMICs. This study provides data on the potential and the limitations of such screenings.
Open-source and FAIR Research Software for Proteomics
2024-12-09

Scientific discovery relies on innovative software as much as experimental methods, especially in proteomics, where computational tools are essential for mass spectrometer setup, data analysis, and interpretation. Since the introduction of SEQUEST, proteomics software has grown into a complex ecosystem of algorithms, predictive models, and workflows, but the field faces challenges, including the increasing complexity of mass spectrometry data, limited reproducibility due to proprietary software, and difficulties integrating with other omics disciplines. Closed-source, platform-specific tools exacerbate these issues by restricting innovation, creating inefficiencies, and imposing hidden costs on the community. Open-source software (OSS), aligned with the FAIR Principles (Findable, Accessible, Interoperable, Reusable), offers a solution by promoting transparency, reproducibility, and community-driven development, which fosters collaboration and continuous improvement. In this manuscript, we explore the role of OSS in computational proteomics, its alignment with FAIR principles, and its potential to address challenges related to licensing, distribution, and standardization. Drawing on lessons from other omics fields, we present a vision for a future where OSS and FAIR principles underpin a transparent, accessible, and innovative proteomics community.
State Dependency of Dynamic and Thermodynamic Contributions to Effective Precipitation Changes
2024-12-09

Abstract Reliable projections of the future hydrological cycle are needed for designing adaptation and mitigation measures under global warming. However, uncertainties in the projected sign and magnitude of effective precipitation changes (precipitation minus evaporation, P − E ) remain high. Here, we examine the state dependency of circulation, temperature, and relative humidity contributions to P − E changes in simulations of the Last Glacial Maximum (LGM), mid-Holocene, and abrupt quadrupling of the atmospheric carbon dioxide concentration. To this purpose, we apply a moisture budget decomposition and a thermodynamic scaling approximation to CMIP6/PMIP4 simulations with the Earth system model MPI-ESM1.2. We find that the importance of thermodynamic and dynamic contributions to P − E changes and the patterns of dynamic contributions depend strongly on the underlying forcing. Greenhouse gas forcing leads to a stronger thermodynamic response than dynamic response. The LGM ice sheets yield a large dynamic contribution with zonally heterogeneous patterns. Orbital forcing induces a predominantly dynamic response with a hemispherically antisymmetric structure. We also identify state-invariant features: The importance of temperature and relative humidity contributions to specific humidity changes is consistent across states, and the wet-get-wetter–dry-get-drier paradigm proposed for global warming holds in almost all regions dominated by thermodynamic contributions. By definition, the P − E budget and the respective thermodynamic, dynamic, and transient eddy contributions vanish in the global mean. Moreover, we find that for increasing length scales, the spatial variability of these contributions decays with similar rates. We suggest repeating our analysis for more models and states which could help constrain hydroclimate projections. Significance Statement We aim at improving our understanding of the influence of changes in winds and water vapor on the local balance between precipitation and evaporation. To this end, we compare simulations for two past climate states with an idealized high carbon dioxide concentration scenario. We find characteristics that depend on the underlying state and characteristics that are consistent across states. Our results help to identify what we can learn from past climate states about precipitation changes under future greenhouse gas emission scenarios. So far, we only analyzed simulations from one model. Therefore, we suggest to repeat our analysis with more models and for more past climate states to confirm our results.
Towards collaborative data science in mental health research: The ECNP neuroimaging network accessible data repository
2024-12-09

The current biologically uninformed psychiatric taxonomy complicates optimal diagnosis and treatment. Neuroimaging-based machine learning methods hold promise for tackling these issues, but large-scale, representative cohorts are required for building robust and generalizable models. The European College of Neuropsychopharmacology Neuroimaging Network Accessible Data Repository (ECNP-NNADR) addresses this need by collating multi-site, multi-modal, multi-diagnosis datasets that enable collaborative research. The newly established ECNP-NNADR includes 4829 participants across 21 cohorts and 11 distinct psychiatric diagnoses, available via the Virtual Pooling and Analysis of Research data (ViPAR) software. The repository includes demographic and clinical information, including diagnosis and questionnaires evaluating psychiatric symptomatology, as well as multi-atlas grey matter volume regions of interest (ROI). To illustrate the opportunities offered by the repository, two proof-of-concept analyses were performed: (1) multivariate classification of 498 patients with schizophrenia (SZ) and 498 matched healthy control (HC) individuals, and (2) normative age prediction using 1170 HC individuals with subsequent application of this model to study abnormal brain maturational processes in patients with SZ. In the SZ classification task, we observed varying balanced accuracies, reaching a maximum of 71.13% across sites and atlases. The normative-age model demonstrated a mean absolute error (MAE) of 6.95 years [coefficient of determination (<i>R</i> <sup><i>2</i></sup> ) = 0.77, <i>P</i> < .001] across sites and atlases. The model demonstrated robust generalization on a separate HC left-out sample achieving a MAE of 7.16 years [<i>R</i> <sup><i>2</i></sup> = 0.74,<i>P</i> < .001]. When applied to the SZ group, the model exhibited a MAE of 7.79 years [<i>R</i> <sup><i>2</i></sup> = 0.79, <i>P</i> < .001], with patients displaying accelerated brain-aging with a brain age gap (BrainAGE) of 4.49 (8.90) years. Conclusively, this novel multi-site, multi-modal, transdiagnostic data repository offers unique opportunities for systematically tackling existing challenges around the generalizability and validity of imaging-based machine learning applications for psychiatry.
Long-Range Azimuthal Correlation, Entanglement, and Bell Inequality Violation by Spinning Gluons at the Large Hadron Collider
2024-12-10

We apply the recently developed concept of the nucleon energy–energy correlator (NEEC) for the gluon sector to investigate the long-range azimuthal angular correlations in proton–proton collisions at the Large Hadron Collider. The spinning gluon in these collisions will introduce substantial nonzero <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"> <mml:mtext>cos</mml:mtext> <mml:mo>(</mml:mo> <mml:mrow> <mml:mn>2</mml:mn> <mml:mi>φ</mml:mi> </mml:mrow> <mml:mo>)</mml:mo> </mml:math> asymmetries in both Higgs boson and top quark pair productions, where <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"> <mml:mi>φ</mml:mi> </mml:math> is the azimuthal angle between the forward and backward energy correlators in the NEEC observables. The genesis of the <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"> <mml:mtext>cos</mml:mtext> <mml:mo>(</mml:mo> <mml:mrow> <mml:mn>2</mml:mn> <mml:mi>φ</mml:mi> </mml:mrow> <mml:mo>)</mml:mo> </mml:math> correlation lies in the intricate quantum entanglement. Owing to the substantial <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"> <mml:mtext>cos</mml:mtext> <mml:mo>(</mml:mo> <mml:mrow> <mml:mn>2</mml:mn> <mml:mi>φ</mml:mi> </mml:mrow> <mml:mo>)</mml:mo> </mml:math> effect, the NEEC observable in Higgs boson and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"> <mml:mi>t</mml:mi> <mml:mover accent="true"> <mml:mi>t</mml:mi> <mml:mo stretchy="true"> ̄</mml:mo> </mml:mover> </mml:math> production emerges as a pivotal avenue for delving into quantum entanglement and scrutinizing the Bell inequality at high-energy colliders.
Blood-based quantification of Aβ oligomers indicates impaired clearance from brain in ApoE ε4 positive subjects
2024-12-10

Abstract Background Quantification of Amyloid beta (Aβ) oligomers in plasma enables early diagnosis of Alzheimer’s Disease (AD) and improves our understanding of underlying pathologies. However, quantification necessitates an extremely sensitive and selective technology because of very low Aβ oligomer concentrations and possible interference from matrix components. Methods In this report, we developed and validated a surface-based fluorescence distribution analysis (sFIDA) assay for quantification of Aβ oligomers in plasma. Results The blood-based sFIDA assay delivers a sensitivity of 1.8 fM, an inter- and intra-assay variation below 20% for oligomer calibration standards and no interference with matrix components. Quantification of Aβ oligomers in 359 plasma samples from the DELCODE cohort reveals lower oligomer concentrations in subjective cognitive decline and AD patients than healthy Control participants. Conclusions Correlation analysis between CSF and plasma oligomer concentrations indicates an impaired clearance of Aβ oligomers that is dependent on the ApoE ε4 status.
A unified framework for diagnostic test development and evaluation during outbreaks of emerging infections
2024-12-10

Abstract Evaluating diagnostic test accuracy during epidemics is difficult due to an urgent need for test availability, changing disease prevalence and pathogen characteristics, and constantly evolving testing aims and applications. Based on lessons learned during the SARS-CoV-2 pandemic, we introduce a framework for rapid diagnostic test development, evaluation, and validation during outbreaks of emerging infections. The framework is based on the feedback loop between test accuracy evaluation, modelling studies for public health decision-making, and impact of public health interventions. We suggest that building on this feedback loop can help future diagnostic test evaluation platforms better address the requirements of both patient care and public health.
Using test particle sum rules to construct accurate functionals in classical density functional theory
2024-12-10

Fundamental measure theory (FMT) is a successful and versatile approach for describing the properties of the hard-sphere fluid and hard-sphere mixtures within the framework of classical density functional theory (DFT). Lutsko [Phys. Rev. E 102, 062137 (2020)2470-004510.1103/PhysRevE.102.062137] introduced a version of FMT containing two free parameters, to be fixed by additional physical constraints. Whereas Lutsko focused on the stability of crystalline phases, we introduce and employ two statistical mechanical sum rules pertinent for the fluid phase that are not automatically satisfied by FMT. By minimizing the relative deviation between different routes to calculate the excess chemical potential and the isothermal compressibility, we determine the two free parameters of the theory. Our results indicate that requiring consistency with these sum rules can improve the quality of predictions of FMT for properties of the hard-sphere fluid phase. We suggest that employing these (test particle) sum rules, which apply for any interparticle pair-potential, might provide a means of testing the performance and accuracy of general DFT approximations.
Treatment of Pediatric, Adolescent, and Young Adult Patients With Fusion‐Positive Alveolar Rhabdomyosarcoma Infiltrating Regional Lymph Nodes in the European CWS‐2002P and RMS 2005 Studies and the Soft Tissue Sarcoma Registry
2024-12-10

ABSTRACT Background Patients with alveolar rhabdomyosarcoma (ARMS) with regional lymph node involvement (N1) are defined as “very‐high‐risk rhabdomyosarcoma” in Europe. Different chemotherapy regimens were used in European study protocols. Methods Patients with FOXO1 fusion‐positive N1 ARMS registered in the CWS‐2002P study, the EpSSG RMS 2005 study, and SoTiSaR were retrospectively investigated. Patients received systemic treatment with chemotherapy (CHT) and local treatment of primary tumor (PT) and involved lymph nodes (LN) with radiotherapy (RT) and/or surgery. Kaplan–Meier estimators and Cox regression were used to examine event‐free survival (EFS) and overall survival (OS) according to prognostic factors and treatment. Results A total of 156 patients registered in RMS 2005 ( n = 99), CWS‐2002P ( n = 20), and SoTiSaR ( n = 37) between 2003 and 2020 were eligible for this analysis. Median age at diagnosis was 10.2 years [0.1–21.9]. Treatment comprised CHT with IVADo (ifosfamide, vincristine, actinomycin‐D, doxorubicin, n = 93; 60%), VAIA (vincristine, actinomycin‐D, ifosfamide, adriamycin/doxorubicin, n = 53; 34%) or other regimens ( n = 10; 6%); resection of the PT ( n = 89; 57%), LN sampling or dissection ( n = 92; 59%), and/or RT ( n = 139; 89%). Maintenance treatment (MT) was added in n = 99/135 (73%) patients who achieved complete remission. Five‐year EFS and OS of the cohort were 45% and 47%, respectively. Age and tumor size were independent prognostic factors for EFS. Local treatment applied to the LN with surgery, RT or both significantly improved EFS ( p = 0.02) and OS ( p = 0.04), with no difference between the modalities ( p = 0.7). Conclusions Patients with fusion‐positive N1 ARMS carry a poor prognosis. Adequate local treatment of LN improved survival.
Plasmodium knowlesi Infection Is Associated With Elevated Circulating Biomarkers of Brain Injury and Endothelial Activation
2024-12-10

Abstract Background Malaria remains a major public health concern with substantial morbidity and mortality worldwide. In Malaysia, the emergence of Plasmodium knowlesi has led to a surge in zoonotic malaria cases and deaths in recent years. Signs of cerebral involvement have been observed in a noncomatose, fatal case of knowlesi infection, but the potential impact of this malaria species on the brain remains unexplored. To address this gap, we investigated circulating levels of brain injury, inflammation, and vascular biomarkers in a cohort of knowlesi-infected patients and controls. Methods Archived plasma samples from 19 Malaysian patients with symptomatic knowlesi infection and 19 healthy, age-matched controls were analyzed. Fifty-two biomarkers of brain injury, inflammation, and vascular activation were measured. Wilcoxon tests were used to examine group differences, and biomarker profiles were explored through hierarchical clustering heatmap analysis. Results Bonferroni-corrected analyses revealed significantly elevated brain injury biomarker levels in knowlesi-infected patients, including S100B (P &amp;lt; .0001), Tau (P = .0007), UCH-L1 (P &amp;lt; .0001), αSyn (P &amp;lt; .0001), Park7 (P = .0006), NRGN (P = .0022), and TDP-43 (P = .005). Compared to controls, levels were lower in the infected group for BDNF (P &amp;lt; .0001), CaBD (P &amp;lt; .0001), CNTN1 (P &amp;lt; .0001), NCAM-1 (P &amp;lt; .0001), GFAP (P = .0013), and KLK6 (P = .0126). Hierarchical clustering revealed distinct group profiles for brain injury and vascular activation biomarkers. Conclusions Our findings highlight for the first time a potential impact of P knowlesi infection on the brain, with specific changes in cerebral injury and endothelial activation biomarker profiles. Further studies are warranted to investigate the pathophysiology and clinical significance of these altered markers, through neuroimaging and long-term neurocognitive assessments.
Standardized assessment of historical thinking competencies in an intervention study using perspectives on German history
2024-12-10

To assess the efficacy of an intervention study on the German post-1990 transformation targeting historical thinking, this paper presents the development of a standardized test designed to measure epistemological understanding and methodological competencies. Following a validation study (N = 354 students), we employed a revised test in an intervention study with N = 1,301 high school students in Baden-Württemberg. The newly developed tests underwent analysis concerning their psychometric criteria. The final test contained 38 items with various stimuli (e.g., interview snippets, cartoons) utilizing closed-format responses. The methodological test exhibited sufficient reliability and extensive overlap with a selection of items from an established test. However, the epistemological test showed some limitations in both reliability and validity, suggesting a potential opportunity for improvement through revision. Students’ grades in history and German, cognitive skills, and socioeconomic status predicted their ability scores based on two-parameter logistic (2PL) item response models for both tests.
An Unsupervised Approach to Identify Patient-Specific EMG Detector to Trigger Robot-Assisted Therapy
2024-12-10

A bstract In severely impaired stroke patients, implementing EMG-driven robot-assisted therapy requires the presence of sufficient residual EMG and a patient-specific detector for accurate and low-latency EMG detection. However, identifying such a detector is challenging, especially when the level of residual EMG in a given patient is unknown . This paper proposes an unsupervised approach to distinguish between EMG data when the patient is relaxed versus attempting a movement – the maximally separating detector . We investigated six different detector types and separation measures using EMG data from a previous randomized controlled trial. The results indicate that the approximate generalized likelihood ratio detector, along with the modified Hodges and modified Lidierth detectors, achieved the best separation. Using a subset of clinician annotated data to evaluate the detection performance, the modified Hodges detector employing the probability difference-sum ratio measure had the best detection performance in terms of detection accuracy and latency. Using the data from 30 participants, we propose a probability difference-sum ratio threshold of 0.7 for the modified Hodges detector to identify patients with sufficient residual EMG to trigger robotic assistance. From the results, we propose the use of modified Hodges detector along with a probability difference-sum ratio measure to learn the maximally separating detector for a given patient, which will screen the patient for sufficient residual EMG and provide a detector to trigger robotic assistance if sufficient EMG is present. The validation of this approach using a large dataset and investigating the quality of the human-machine interaction implemented with such a detector is warranted.
Effects of computer-generated patterns with different temporal and spatial frequencies on choroidal thickness, retinal dopamine and candidate genes in chickens wearing lenses
2024-12-10

Purpose Changes in choroidal thickness (ChT) are proposed to predict myopia development but evidence is mixed. We investigated time courses of choroidal responses, following different types of dynamic artificial stimulation in chicks with and without spectacle lenses, as well as changes in retinal dopamine metabolism and expression of candidate genes. Methods Chicks were kept in an arena surrounded by computer monitors presenting dynamic checkerboard fields of small, medium and large size. Fields were displayed with different cycle frequencies, as ON (rapid rise, slow decay) or OFF (slow rise, rapid decay) temporal luminance profile. Refractive errors, ocular biometry and ChT were assessed. Dopamine metabolism and candidate gene expression levels were also measured. Stimuli were applied for (1) 3 h with no lens, (2) 3 h and monocular treatment with −7D or +7D lenses, (3) 3 or 7 days. Results (1) The smallest fields caused the largest decrease in ChT. (2) Negative lens treatment induced on average 11.7 μm thinner choroids. ChT thinning was enhanced by 10 Hz-ON medium field size flicker which also reduced choroidal thickening with positive lenses. (3) With prolonged treatment, the choroid recovered from initial thinning in all groups although to varying degrees which were dependent on stimulus parameters. Relative ChT changes were positively correlated with the vitreal level of dopamine metabolites. Retinal EGR-1 mRNA level was positively correlated with choroidal thickness. Retinal melanopsin mRNA was increased by 10 Hz-ON stimulation and choroidal BMPR1A mRNA increased with 10 Hz-OFF stimulation. On average, early choroidal thinning did not predict the amount of negative lens-induced eye growth changes after 7 days, whereas later ChT changes showed a weak association. Conclusion Negative lenses caused long-lasting choroidal thinning, with some recovery during lens wear, especially after stimulation with 10 Hz. The dynamic stimuli modulated choroidal thinning but effects were small. There was little difference between ON and OFF stimulation, perhaps because the checkerboard patterns were too coarse. 10 Hz cycle frequency increased dopamine release. Less dopamine was correlated with thinner choroids. Result do not exclude a predictive value of choroidal thickening for future refractive development since we almost exclusively tested choroidal thinning effects.