julilili42/papers huggingface dataset:
Making the effect visible – OX40 targeting nanobodies for in vivo imaging of activated T cells
2024-10-15

Purpose Human OX40 (hOX40/CD134), a member of the TNF receptor superfamily, is mainly expressed on activated T lymphocytes. Triggered by its ligand OX40L (CD252), it provides costimulatory signals that support the differentiation, proliferation and long-term survival of T cells. Besides being a relevant therapeutic target, hOX40 is also an important biomarker for monitoring the presence or infiltration of activated T cells within the tumor microenvironment (TME), the inflammatory microenvironment (IME) in immune-mediated diseases (IMIDs) and the lymphatic organs. Here, we developed novel single domain antibodies (nanobodies, Nbs) targeting hOX40 to monitor the activation status of T cells by in vivo molecular imaging. Methods Nbs against hOX40 (hOX40-Nbs) were selected from an immunized Nb-library by phage display. The identified hOX40-Nbs were characterized in vitro , including determination of their specificity, affinity, stability, epitope recognition and their impact on OX40 signaling and T cell function. A lead candidate was site-specifically conjugated with a fluorophore via sortagging and applied for noninvasive in vivo optical imaging (OI) of hOX40-expressing cells in a xenograft mouse model. Results Our selection campaign revealed four unique Nbs that exhibit strong binding affinities and high stabilities under physiological conditions. Epitope binning and domain mapping indicated the targeting of at least two different epitopes on hOX40. When analyzing their impact on OX40 signaling, an agonistic effect was excluded for all validated Nbs. Incubation of activated T cells with hOX40-Nbs did not affect cell viability or proliferation patterns, whereas differences in cytokine release were observed. In vivo OI with a fluorophore-conjugated lead candidate in experimental mice with hOX40-expressing xenografts demonstrated its specificity and functionality as an imaging probe. Conclusion Considering the need for advanced probes for noninvasive in vivo monitoring of T cell activation dynamics, we propose, that our hOX40-Nbs have a great potential as imaging probes for noninvasive and longitudinal in vivo diagnostics. Quantification of OX40 + T cells in TME or IME will provide crucial insights into the activation state of infiltrating T cells, offering a valuable biomarker for assessing immune responses, predicting treatment efficacy, and guiding personalized immunotherapy strategies in patients with cancer or IMIDs.
Polynomial Analogs of Theta Functions and Rational Solutions of the KP Equation
2024-10-15

Abstract In this paper we classify the singular curves whose theta divisors in their generalized Jacobians are algebraic, meaning that they are cut out by polynomial analogs of theta functions. We also determine the degree of an algebraic theta divisor in terms of the singularities of the curve. Furthermore, we show a precise relation between such algebraic theta functions and the corresponding tau functions for the KP hierarchy.
Developing a Pedagogically Oriented Interactive Reading Tool with Teachers in the Loops
2024-10-15

Reading is crucial for students' academic success and essential life skills. Particularly, the need for students to read in L2 English has grown due to its global significance. However, L2 readers often have limited opportunities for meaningful, interactive reading practice with immediate support. This paper introduces System A (Anonymized), a pedagogically oriented, web-based ICALL system designed to enhance L2 reading experiences, developed through an action research design involving teachers. System A offers a range of interactive features for students, including not only the autonomous identification of vocabulary and more than 650 grammar constructs, but making them interactively explorable in the text, providing detailed explanations and practical examples in contexts. To support effective teaching, System A employs a LLM for generating tailored reading comprehension questions and answer evaluation, with teachers actively involved. We present the development and application of the system from both technical and pedagogical perspectives to advance L2 learning research and refine educational tools.
Developing a Web-Based Intelligent Language Assessment Platform Powered by Natural Language Processing Technologies
2024-10-15

We introduce System, an intelligent language assessment platform and reusable module that streamlines the creation, administration and scoring of language proficiency tests supported by Natural Language Processing (NLP) technologies. As a first implementation, we realized an automatic pipeline for the Elicited Imitation Test (EIT), a popular test format that has been widely adopted in language learning research for general proficiency and formative assessments. The platform can be extended to other test formats and assessment types. System is a valuable tool for standardizing data collection in Second Language Acquisition (SLA) and Intelligent Computer Assisted Language Learning (ICALL) research as well as serving as an application for classroom assessment. In this paper, we present the design of the system and a preliminary evaluation of LLMs for generating language errors in EIT items. We conclude with a future outlook as well as limitations.
Machine learning-based personalized composite score dissects risk and protective factors for cognitive and motor function in older participants
2024-10-15

Introduction With age, sensory, cognitive, and motor abilities decline, and the risk for neurodegenerative disorders increases. These impairments influence the quality of life and increase the need for care, thus putting a high burden on society, the economy, and the healthcare system. Therefore, it is important to identify factors that influence healthy aging, particularly ones that are potentially modifiable through lifestyle choices. However, large-scale studies investigating the influence of multi-modal factors on a global description of healthy aging measured by multiple clinical assessments are sparse. Methods We propose a machine learning model that simultaneously predicts multiple cognitive and motor outcome measurements on a personalized level recorded from one learned composite score. This personalized composite score is derived from a large set of multi-modal components from the TREND cohort, including genetic, biofluid, clinical, demographic, and lifestyle factors. Results We found that a model based on a single composite score was able to predict cognitive and motor abilities almost as well as a classical flexible regression model specifically trained for each single clinical score. In contrast to the flexible regression model, our composite score model is able to identify factors that globally influence cognitive and motoric abilities as measured by multiple clinical scores. The model identified several risk and protective factors for healthy aging and recovered physical exercise as a major, modifiable, protective factor. Discussion We conclude that our low parametric modeling approach successfully recovered known risk and protective factors of healthy aging on a personalized level while providing an interpretable composite score. We suggest validating this modeling approach in other cohorts.
Two-Dimensional Liquid Chromatography Tandem Mass Spectrometry Untangles the Deep Metabolome of Marine Dissolved Organic Matter
2024-10-16

Dissolved organic matter (DOM) is an ultracomplex mixture that plays a central role in global biogeochemical cycles. Despite its importance, DOM remains poorly understood at the molecular level. Over the last decades, significant efforts have been made to decipher the chemical composition of DOM by high-resolution mass spectrometry (HR-MS) and liquid chromatography (LC) coupled with tandem mass spectrometry (MS/MS). Yet, the complexity and high degree of nonresolved isomers still hamper the full structural analysis of DOM. To address this challenge, we developed an offline two-dimensional (2D) LC approach using two reversed-phase dimensions with orthogonal pH levels, followed by MS/MS data acquisition and molecular networking. 2D-LC-MS/MS reduced the complexity of DOM, enhancing the quality of MS/MS spectra and increasing spectral annotation rates. Applying our approach to analyze coastal-surface DOM from Southern California (USA) and open-ocean DOM from the central North Pacific (Hawaii), we annotated in total more than 600 structures via MS/MS spectrum matching, which was up to 90% more than that in iterative 1D LC-MS/MS analysis with the same total run time. Our data offer unprecedented insights into the molecular composition of marine DOM and highlight the potential of 2D-LC-MS/MS approaches to decipher the chemical composition of ultracomplex samples.
An evaluation of the performance of stopping rules in AI‐aided screening for psychological meta‐analytical research
2024-10-16

Abstract Several AI‐aided screening tools have emerged to tackle the ever‐expanding body of literature. These tools employ active learning, where algorithms sort abstracts based on human feedback. However, researchers using these tools face a crucial dilemma: When should they stop screening without knowing the proportion of relevant studies? Although numerous stopping rules have been proposed to guide users in this decision, they have yet to undergo comprehensive evaluation. In this study, we evaluated the performance of three stopping rules: the knee method, a data‐driven heuristic, and a prevalence estimation technique. We measured performance via sensitivity, specificity, and screening cost and explored the influence of the prevalence of relevant studies and the choice of the learning algorithm. We curated a dataset of abstract collections from meta‐analyses across five psychological research domains. Our findings revealed performance differences between stopping rules regarding all performance measures and variations in the performance of stopping rules across different prevalence ratios. Moreover, despite the relatively minor impact of the learning algorithm, we found that specific combinations of stopping rules and learning algorithms were most effective for certain prevalence ratios of relevant abstracts. Based on these results, we derived practical recommendations for users of AI‐aided screening tools. Furthermore, we discuss possible implications and offer suggestions for future research.
Incidence of Occult Hepatitis B Infection (OBI) and hepatitis B genotype characterization among blood donors in Cameroon
2024-10-16

Background Occult hepatitis B infection (OBI) is characterized by the presence of hepatitis B virus (HBV) DNA at low levels in serum (&lt;200 IU/mL) with a negative hepatitis B surface antigen (HBsAg) test. OBI remains a major challenge to blood safety, particularly in HBV-endemic regions like Cameroon, where HBV detection relies solely on HBsAg testing. This cross-sectional study aimed to investigate the actual incidence and genotype characteristics of OBI in Cameroonian blood donors. Methods Between March and June 2023, samples were collected from 288 HBsAg-negative blood donors aged 18 to 55 years and analysed for antibodies against the HBV core (anti-HBc) and surface antigens (anti-HBs). Following DNA extraction from the serum samples, qualitative nested PCR and quantitative real-time PCR were used to detect HBV viral DNA and viral load respectively. For positive samples, sequencing of a fragment of the S gene was performed to identify the circulating HBV genotypes. Results The findings revealed that 58% (n = 167/288) of blood donors tested positive for anti-HBc, 29% (n = 83/288) tested positive for anti-HBs, and 26% (n = 75/288) being positive for both anti-HBc and anti-HBs. Occult hepatitis was confirmed in 4.5% of the blood donors, all of whom belonged to either HBV genotypes A or E , which are predominant in Cameroon. The amino acid substitution sA184V associated with HBsAg detection failure in genotype E was observed in 70% of OBI sequences, and the HBsAg immune escape variants (s T131N and s S143L ) implicated in OBI were also observed. The mutation rtN139K in the reverse transcriptase (RT) domain of the overlapping HBV polymerase ( P ) gene was present in 17% of OBI-positive sequences of genotype E , likely contributing to masking HBsAg secretion. Conclusion The results suggest a considerable risk of transfusion-transmitted HBV in this region. Therefore, to ensure blood safety, nucleic acid testing (NAT) is recommended, as relying solely on HBsAg assays is insufficient to eliminate this risk.
Unifying Principles of Generalization: Past, Present, and Future
2024-10-16

Generalization, defined as applying limited experiences to novel situations, represents a cornerstone of human intelligence. Our review traces the evolution and continuity of psychological theories of generalization, from its origins in concept learning (categorizing stimuli) and function learning (learning continuous input-output relationships) to domains such as reinforcement learning and latent structure learning. Historically, there have been fierce debates between approaches based on rule-based mechanisms, which rely on explicit hypotheses about environmental structure, and approaches based on similarity-based mechanisms, which leverage comparisons to prior instances. Each approach has unique advantages: Rules support rapid knowledge transfer, while similarity is computationally simple and flexible. Today, these debates have culminated in the development of hybrid models grounded in Bayesian principles, effectively marrying the precision of rules with the flexibility of similarity. The ongoing success of hybrid models not only bridges past dichotomies but also underscores the importance of integrating both rules and similarity for a comprehensive understanding of human generalization.
A multiantigenic Orf virus-based vaccine efficiently protects hamsters and nonhuman primates against SARS-CoV-2
2024-10-16

Abstract Among the common strategies to design next-generation COVID-19 vaccines is broadening the antigenic repertoire thereby aiming to increase efficacy against emerging variants of concern (VoC). This study describes a new Orf virus-based vector (ORFV) platform to design a multiantigenic vaccine targeting SARS-CoV-2 spike and nucleocapsid antigens. Vaccine candidates were engineered, either expressing spike protein (ORFV-S) alone or co-expressing nucleocapsid protein (ORFV-S/N). Mono- and multiantigenic vaccines elicited comparable levels of spike-specific antibodies and virus neutralization in mice. Results from a SARS-CoV-2 challenge model in hamsters suggest cross-protective properties of the multiantigenic vaccine against VoC, indicating improved viral clearance with ORFV-S/N, as compared to equal doses of ORFV-S. In a nonhuman primate challenge model, vaccination with the ORFV-S/N vaccine resulted in long-term protection against SARS-CoV-2 infection. These results demonstrate the potential of the ORFV platform for prophylactic vaccination and represent a preclinical development program supporting first-in-man studies with the multiantigenic ORFV vaccine.
The high-energy cyclotron line in 2S 1417-624 discovered with Insight-HXMT during the 2018 outburst
2024-10-16

We report a detailed timing and spectral analysis of the X-ray pulsar 2S 1417−624 using the data from Insight-HXMT during the 2018 outburst. The pulse profiles are highly variable with respect to both unabsorbed flux and energy. A double-peaked pulse profile from the low flux evolved to a multi-peaked shape in the high-flux state. The pulse fraction is negatively correlated to the source flux in the range of ∼(1 − 6)×10 −9 erg cm −2 s −1 , consistent with Rossi X-ray Timing Explorer (RXTE) studies during the 2009 giant outburst. The energy-resolved pulse profiles around the peak outburst showed a four-peak shape in the low-energy bands and gradually evolved to triple peaks at higher energies. The continuum spectrum is well described by typical phenomenological models, such as the cut-off power law and the power law with high-energy cut-off models. Notably, we discovered high-energy cyclotron resonant scattering features (CRSFs) for the first time, which are around 100 keV with a statistical significance of ∼7 σ near the peak luminosity of the outburst. This CRSF line is significantly detected with different continuum models and provides very robust evidence for its presence. Furthermore, pulse-phase-resolved spectroscopy confirmed the presence of the line, whose energy varied from 97 to 107 keV over the pulse phase and appeared to have a maximum value at the narrow peak phase of the profiles.
68Ga-Labeled TRAP-Based Glycoside Trimers for Imaging of the Functional Liver Reserve
2024-10-16

The exclusive asialoglycoprotein receptor (ASGR) expression on hepatocytes makes it an attractive target for imaging of the functional liver reserve. Here, we present a set of TRAP-based glycoside trimers and evaluate their imaging properties compared to the gold standard [<sup>99m</sup>Tc]Tc-GSA. The click-chemistry-based synthesis approach provided easy access to trimeric low-molecular-weight compounds. Labeling with <sup>68</sup>Ga was carried out in high radiochemical yields (>99%). Complexes showed high stability and hydrophilicity. Protein binding ranged between 10 and 25%. Highest binding affinity (IC<sub>50</sub>) and best liver accumulation were found for [<sup>68</sup>Ga]Ga-<b>T3N3</b>, followed by [<sup>68</sup>Ga]Ga-<b>T3G3</b> and [<sup>68</sup>Ga]Ga-<b>T0G3</b>. Rapid elimination from the rest of the body resulted in excellent target-to-background ratios. Our studies confirmed that high ASGR uptake depends on the correct spacer design and that <i>N</i>-acetylgalactosamine improves targeting properties <i>in vivo</i>. Thus, [<sup>68</sup>Ga]Ga-<b>T3N3</b> represents a new low-molecular-weight radiopharmaceutical with pharmacokinetics similar to those of [<sup>99m</sup>Tc]Tc-GSA.
Performance Effects of Different Shutdown Methods on Three Electrode Materials for Electromethanogenesis
2024-10-16

Abstract Industrial applications of microbial electrochemical systems will require regular maintenance shutdowns, involving inspections and component replacements to extend the lifespan of the system. Here, we examined the impact of such shutdowns on the performance of three electrode materials ( i. e ., platinized titanium, graphite, and nickel) as cathodes in a microbial electrochemical system that would be used for electromethanogenesis in power‐to‐gas applications. We focused on methane (CH 4 ) production from hydrogen (H 2 ) and carbon dioxide (CO 2 ) using Methanothermobacter thermautotrophicus . We showed that the platinized titanium cathode resulted in high volumetric CH 4 production rates and Coulombic efficiencies. Using a graphite cathode would be more cost‐effective than using the platinized titanium cathode in microbial electrochemical systems, but showed an inferior performance. The microbial electrochemical system with the nickel cathode showed improvements compared to the graphite cathode. Additionally, this system with a nickel cathode demonstrated the fastest recovery during a shutdown experiment compared to the other two cathodes. Fluctuations in pH and nickel concentrations in the catholyte during power interruptions affected CH 4 production recovery in the system with the nickel cathode. This research enhances understanding of the integration of biological and electrochemical processes in microbial electrochemical systems, providing insights into electrode selection and operating strategies for effective and sustainable CH 4 production.
Dissociation of movement and outcome representations in metacognition of agency
2024-10-16

Abstract We studied the role of movement and outcome information in forming metacognitive representations of agency. Participants completed a goal-oriented task, a virtual version of a ball-throwing game. In two conditions, we manipulated either the visual representation of the throwing movement or its distal outcome (the resulting ball flight/trajectory). We measured participants’ accuracy in a discrimination agency task, as well as confidence in their responses and tested for differences in the electrophysiological (EEG) signal using linear mixed effect models. We found no mean differences between participants’ metacognitive efficiency between conditions, but we also found that metacognitive sensitivity did not correlate between the two conditions, suggesting a dissociation in their underlying mechanisms. Furthermore, exploratory analyses pointed toward a difference in the EEG signal between the two conditions. Taken together, our results suggest that while movement and outcome information contribute equally to participants’ sense of agency, they may do so through distinct underlying processes.
Biotic resistance predictably shifts microbial invasion regimes
2024-10-16

Invading new territory is a central aspect of the microbial lifestyle, allowing microbes to expand to remote locations and pathogens to spread and infect their hosts. However, invading microbes rarely find novel territories uninhabited. In such a scenario, resident microbes can interact with the newcomers and, in many cases, impede their invasion, an effect known as biotic resistance. Accordingly, invasions are shaped by the interplay between dispersal and resistance. However, these two factors are difficult to disentangle or manipulate in natural systems, making their interplay difficult to understand. To address this challenge, we tracked microbial invasions in the lab over space and time, first in a model system of two interacting microbes, then in a multi-strain system involving a pathogen invading resident communities. In the presence of biotic resistance, we observed three qualitatively different invasion regimes: consistent, pulsed, and pinned, where, in the third regime, strong biotic resistance stalled the invasion entirely despite ongoing invader dispersal. Surprisingly, these rich invasion dynamics could be qualitatively predicted with a simple, parameter-free framework that ignores individual species interactions, even for rather complex communities. Moreover, we showed that this simple framework could accurately predict simulated invasions from different mechanistic models, indicating its broad applicability. Our work offers a thorough understanding of how biotic resistance impacts invasions and introduces a predictive tool to identify invasion-resistant communities.