Respir Res. 2025 Feb 28;26(1):73. doi: 10.1186/s12931-025-03136-6.

ABSTRACT

BACKGROUND: The prognostic value of patterns and quantitative measures of lung fibrosis on high-resolution computed tomography (HRCT) in patients identified as having progressive pulmonary fibrosis (PPF) has not been established. We investigated whether HRCT patterns and quantitative scores were associated with risk of progression in patients with PPF.

METHODS: Patients enrolled in the ILD-PRO Registry had an interstitial lung disease (ILD) other than idiopathic pulmonary fibrosis, reticular abnormality and traction bronchiectasis, and met criteria for ILD progression. HRCT images taken between 24 months prior to enrollment and 90 days after enrollment were analyzed using a machine learning algorithm to derive quantitative scores. Associations were assessed between HRCT pattern (usual interstitial pneumonia [UIP]-like versus other patterns) and tertiles of quantitative scores and measures of disease severity at enrollment, and between these patterns/tertiles at enrollment and ILD progression (relative decline in forced vital capacity [FVC] % predicted ≥ 10%, lung transplant, or death) over a median follow-up of 17.3 months.

RESULTS: Among 395 patients, 178 (45.1%) had a UIP-like pattern on HRCT. A UIP-like pattern did not associate with worse disease severity at enrollment or an increased risk of ILD progression (HR 1.01 [95% CI: 0.71, 1.44]). The highest quantitative lung fibrosis (QLF) score tertile (≥ 20.5%) was associated with worse disease severity. In unadjusted analyses, patients with QLF scores in the highest tertile had a significantly increased risk of ILD progression versus the middle tertile (HR [95% CI] 1.63 [1.07, 2.49] and a numerically increased risk versus the lowest tertile (HR 1.46 [0.97, 2.18]); however, after adjustment for sex, age, FVC % predicted and oxygen use at enrollment, there were no significant differences. There were no significant associations between tertiles of quantitative ILD score, quantitative ground glass score, or quantitative honeycomb cysts score and risk of ILD progression in unadjusted or adjusted analyses.

CONCLUSIONS: In a real-world cohort of patients with PPF, QLF score associated with subsequent risk of ILD progression, while HRCT pattern did not. The QLF score did not provide additional prognostic information beyond clinical variables.

TRIAL REGISTRATION: ClinicalTrials.gov; No: NCT01915511; registered August 5, 2013; URL: www.

CLINICALTRIALS: gov .

PMID:40022059 | DOI:10.1186/s12931-025-03136-6

BMC Pulm Med. 2025 Feb 28;25(1):98. doi: 10.1186/s12890-025-03555-7.

ABSTRACT

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a chronic, irreversible, and fatal disease characterized by progressive interstitial lung fibrosis. Given its insidious onset and poor outcome, there is an urgent need to elucidate the molecular mechanisms underlying IPF and identify effective therapeutic targets and diagnosis and prognosis biomarkers. Ferroptosis is an iron-dependent form of programmed cell death that occurs as lipid peroxides accumulate. Growing evidence suggests that ferroptosis is important in IPF.

METHODS: Human ferroptosis PCR array was performed on IPF and control lung tissue. The differentially expressed ferroptosis-related genes (DE-FRGs) were identified, underwent functional enrichment analyses, protein-protein interaction network construction, and potential drug target prediction. The DE-FRGs were validated and their value as diagnostic and prognostic blood biomarkers were evaluated using the Gene Expression Omnibus dataset GSE28042.

RESULTS: The array identified 13 DE-FRGs. Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analyses revealed that the DE-FRGs were mainly related to iron ion transport, blood microparticles, and oxidoreductase activity, and were involved in porphyrin metabolism, necroptosis, and the p53 signaling pathway in addition to ferroptosis. The 13 DE-FRGs were analyzed using the Drug-Gene Interaction Database to explore novel IPF therapeutic agents, yielding 42 potential drugs. Four DE-FRGs (BBC3, STEAP3, EPRS, SLC39A8) in the peripheral blood of IPF patients from the GSE28042 dataset demonstrated the same expression pattern as that observed in the lung tissue array. The receiver operating characteristic analysis demonstrated that the area under the curve of STEAP3 and EPRS were > 0.75. The survival analysis demonstrated that STEAP3 and EPRS were significantly different between the IPF and control groups.

CONCLUSIONS: The FRG expression profiles in IPF and control lung tissue were characterized. The findings provided valuable ideas to elucidate the role of ferroptosis in IPF and aided the identification of novel IPF therapeutic targets and biomarkers.

PMID:40022042 | DOI:10.1186/s12890-025-03555-7

Chest. 2025 Feb 26:S0012-3692(25)00267-3. doi: 10.1016/j.chest.2025.02.018. Online ahead of print.

ABSTRACT

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a progressive fibrosing interstitial lung disease associated with lung function decline and high mortality.

RESEARCH QUESTION: What are the associations between thresholds of lung function decline and the risk of mortality in patients with IPF?

STUDY DESIGN AND METHODS: The Idiopathic Pulmonary Fibrosis-Prospective Outcomes Registry enrolled patients with IPF that was diagnosed or confirmed at the enrolling center within the prior 6 months. Associations between time to first decline in FVC or diffusing capacity of the lungs for carbon monoxide (Dlco) of ≥ 2% predicted, ≥ 5% predicted, and ≥ 10% predicted (and ≥ 15% predicted for Dlco) and risk of subsequent death or lung transplant was assessed using Cox proportional hazards models with a time-dependent covariate. Models were unadjusted or adjusted for FVC and Dlco % predicted, age, sex, smoking status, BMI, antifibrotic treatment (yes or no), and oxygen use at enrollment.

RESULTS: Among 1,001 patients, median follow-up time was 38.4 months. Significant associations were observed between all thresholds of decline in FVC and Dlco % predicted and the risk of death or lung transplant in unadjusted and adjusted analyses. In adjusted analyses, absolute declines in FVC of ≥ 2% predicted, ≥ 5% predicted, and ≥ 10% predicted were associated with 1.8-fold, 2.3-fold, and 2.7-fold increases in the risk of subsequent death or lung transplant, whereas absolute declines in Dlco of ≥ 2% predicted, ≥ 5% predicted, ≥ 10% predicted, and ≥ 15% predicted were associated with 2.0-fold, 1.4-fold, 1.5-fold, and 1.9-fold increases in the risk of subsequent death or lung transplantation, respectively. For Dlco, but not FVC, the increase in risk generally was greater for patients meeting a threshold based on a relative rather than an absolute decline.

INTERPRETATION: Even small declines in FVC and Dlco % predicted inform prognosis in patients with IPF.

PMID:40020995 | DOI:10.1016/j.chest.2025.02.018

Virol J. 2025 Feb 28;22(1):52. doi: 10.1186/s12985-025-02669-y.

ABSTRACT

Viral hemorrhagic Lassa fever (LF), caused by Lassa virus (LASV), is a significant public health concern endemic in West Africa with high morbidity and mortality rates, limited treatment options, and potential for international spread. Despite advances in interrogating its epidemiology and clinical manifestations, the molecular mechanisms driving pathogenesis of LASV and other arenaviruses remain incompletely understood. This review synthesizes current knowledge regarding the role of LASV host-virus interactions in mediating the pathogenesis of LF, with emphasis on interactions between viral and host proteins. Through investigation of these critical protein-protein interactions, we identify potential therapeutic targets and discuss their implications for development of medical countermeasures including antiviral drugs. This review provides an update in recent literature of significant LASV host-virus interactions important in informing the development of targeted therapies and improving clinical outcomes for LF patients. Knowledge gaps are highlighted as opportunities for future research efforts that would advance the field of LASV and arenavirus pathogenesis.

PMID:40022100 | DOI:10.1186/s12985-025-02669-y

BMC Urol. 2025 Feb 28;25(1):41. doi: 10.1186/s12894-025-01723-9.

ABSTRACT

BACKGROUND: The application of molecular sequencing methods for microbiome profiling of biological samples are largely restricted to research use. However, they require significant resources such as time and cost and can suffer from amplification biases that may hamper interpretation of complex systems. These issues are also a barrier to adoption as standard clinical tools in, for example, diagnosis of urogenital infections. We report a new method that utilises third generation long-read nanopore sequencing to produce fast, accurate and fully quantitated metagenomic microbiome profiles. Here, as proof of principle, we apply this methodology to reassess the healthy urogenital microbiomes of asymptomatic female and male samples.

RESULTS: We show that our method is capable of accurately and reproducibly detecting both levels and composition of a synthetic mixture of ten species comprising known amounts of hard to lyse gram-positive bacteria, gram-negative bacteria and yeast. When applied to urogenital samples, we confirm previous observations that the female asymptomatic vaginal and urinary microbiomes are predominated by Gardnerella spp. or one of several Lactobacillus species (L. crispatus, L. gasseri, L. iners or L. jensenii) that conform to previously defined community state types. We show the tight relationship between vaginal and urinary populations of the same individual at both species and strain level, provide evidence for the previously observed dynamic nature of these microbiomes over a menstrual cycle and compare biomass and complexity of male and female urobiomes.

CONCLUSIONS: We set out to develop an unbiased, amplification and culture-free, fully quantitative metagenomic microbiome profiling tool. Our initial observations suggest our method represents a viable alternative to existing molecular research tools employed in the analysis of complex microbiomes.

PMID:40022097 | DOI:10.1186/s12894-025-01723-9

Nat Metab. 2025 Feb 28. doi: 10.1038/s42255-025-01239-4. Online ahead of print.

NO ABSTRACT

PMID:40021935 | DOI:10.1038/s42255-025-01239-4

Nat Commun. 2025 Feb 28;16(1):2049. doi: 10.1038/s41467-025-57271-1.

ABSTRACT

Somatic mobilization of LINE-1 (L1) has been implicated in cancer etiology. We analyzed a recent TCGA data release comprised of nearly 5000 pan-cancer paired tumor-normal whole-genome sequencing (WGS) samples and ~9000 tumor RNA samples. We developed TotalReCall an improved algorithm and pipeline for detection of L1 retrotransposition (RT), finding high correlation between L1 expression and "RT burden" per sample. Furthermore, we mathematically model the dual regulatory roles of p53, where mutations in TP53 disrupt regulation of both L1 expression and retrotransposition. We found those with Li-Fraumeni Syndrome (LFS) heritable TP53 pathogenic and likely pathogenic variants bear similarly high L1 activity compared to matched cancers from patients without LFS, suggesting this population be considered in attempts to target L1 therapeutically. Due to improved sensitivity, we detect over 10 genes beyond TP53 whose mutations correlate with L1, including ATRX, suggesting other, potentially targetable, mechanisms underlying L1 regulation in cancer remain to be discovered.

PMID:40021663 | DOI:10.1038/s41467-025-57271-1

Phys Rev Lett. 2025 Feb 14;134(6):068402. doi: 10.1103/PhysRevLett.134.068402.

ABSTRACT

The fuel-driven process of replication in living systems generates distributions of copied entities with varying degrees of copying accuracy. Here we introduce a thermodynamically consistent ensemble for investigating universal population features of template copying systems. In the context of copolymer copying, coarse-graining over molecular details, we establish a phase diagram of copying accuracy. We discover sharp non-equilibrium transitions between populations of random and accurate copies. Maintaining a population of accurate copies requires a minimum energy expenditure that depends on the configurational entropy of copolymer sequences.

PMID:40021163 | DOI:10.1103/PhysRevLett.134.068402

Cell Genom. 2025 Feb 20:100780. doi: 10.1016/j.xgen.2025.100780. Online ahead of print.

ABSTRACT

Deep learning models have advanced our ability to predict cell-type-specific chromatin patterns from transcription factor (TF) binding motifs, but their application to perturbed contexts remains limited. We applied transfer learning to predict how concentrations of the dosage-sensitive TFs TWIST1 and SOX9 affect regulatory element (RE) chromatin accessibility in facial progenitor cells, achieving near-experimental accuracy. High-affinity motifs that allow for heterotypic TF co-binding and are concentrated at the center of REs buffer against quantitative changes in TF dosage and predict unperturbed accessibility. Conversely, low-affinity or homotypic binding motifs distributed throughout REs drive sensitive responses with minimal impact on unperturbed accessibility. Both buffering and sensitizing features display purifying selection signatures. We validated these sequence features through reporter assays and demonstrated that TF-nucleosome competition can explain low-affinity motifs' sensitizing effects. This combination of transfer learning and quantitative chromatin response measurements provides a novel approach for uncovering additional layers of the cis-regulatory code.

PMID:40020686 | DOI:10.1016/j.xgen.2025.100780

Immunity. 2025 Feb 21:S1074-7613(25)00068-8. doi: 10.1016/j.immuni.2025.02.001. Online ahead of print.

ABSTRACT

Generating balanced populations of CD8+ effector and memory T cells is necessary for immediate and durable immunity to infections and cancer. Yet, a definitive understanding of how a diverse CD8+ T cell repertoire differentiates remains unclear. We identified several hundred T cell receptor (TCR) clonotypes that constitute the polyclonal response against a single antigen and found that a majority of TCR clonotypes were highly biased toward memory or effector fates. TCR-intrinsic biases were not stochastic and were dominant over environmental cues. Differential gene expression analysis of memory- or effector-biased TCR clonotypes showed bifurcation of differential fates at the early effector stage. Additionally, phylogenetic analysis revealed that memory-biased clonotypes retain their fate preferences in subclonal populations but effector-biased subclones can switch to a memory fate. Our study highlights that the polyclonal CD8+ T cell response is a composite of unbiased and biased clonotypes with varying capacity to incorporate environmental cues in their cell fate decisions.

PMID:40020673 | DOI:10.1016/j.immuni.2025.02.001

Cell. 2025 Feb 21:S0092-8674(25)00108-4. doi: 10.1016/j.cell.2025.01.039. Online ahead of print.

ABSTRACT

Space habitation provides unique challenges in built environments isolated from Earth. We produced a 3D map of the microbes and metabolites throughout the United States Orbital Segment (USOS) of the International Space Station (ISS) with 803 samples collected during space flight, including controls. We find that the use of each of the nine sampled modules within the ISS strongly drives the microbiology and chemistry of the habitat. Relating the microbiology to other Earth habitats, we find that, as with human microbiota, built environment microbiota also align naturally along an axis of industrialization, with the ISS providing an extreme example of an industrialized environment. We demonstrate the utility of culture-independent sequencing for microbial risk monitoring, especially as the location of sequencing moves to space. The resulting resource of chemistry and microbiology in the space-built environment will guide long-term efforts to maintain human health in space for longer durations.

PMID:40020666 | DOI:10.1016/j.cell.2025.01.039

Curr Opin Struct Biol. 2025 Feb 27;91:102994. doi: 10.1016/j.sbi.2025.102994. Online ahead of print.

ABSTRACT

Missense variants can affect the severity of disease, choice of treatment, and treatment outcomes. While the number of known variants has been increasing at a rapid pace, available evidence of their clinical effect has been lagging behind, constituting a challenge for clinicians and researchers. Multiplexed assays of variant effects (MAVEs) are important to close the gap; nonetheless, computational predictions of pathogenicity are still often the only available data for scoring variants. Such methods are not designed to provide a mechanistic explanation for the effect of amino acid substitutions. To this purpose, we propose structure-based frameworks as ensemble methodologies, with each method tailored to predict a different aspect among those exerted by amino acid substitutions to link predicted pathogenicity to mechanistic indicators. We review available frameworks, as well as advancements in underlying structure-based methods that predict variant effects on several protein features, such as protein stability, biomolecular interactions, allostery, post-translational modifications, and more.

PMID:40020537 | DOI:10.1016/j.sbi.2025.102994

Eur J Pharmacol. 2025 Feb 26:177431. doi: 10.1016/j.ejphar.2025.177431. Online ahead of print.

ABSTRACT

Safe and effective pharmacotherapy not only requires biomedical and pharmacological knowledge, but also insight into the patient's perspective. Although factors such as personal beliefs, acceptance of side effects or medicine costs influence pharmacotherapy, these non-clinical factors are not extensively discussed within the health professions education (HPE) curricula. Incorporating patient-perspective into pharmacology could therefore help minimize drug-related problems in patients. As videos provide a holistic depiction of the patient's life, using patient videos, instead of commonly used, paper-based case studies, could be suitable to reach this objective. Here we aim to study effectiveness of patient videos as a tool for teaching HPE students on the value of patient's perspective in pharmacology and pharmacotherapy. An interactive lecture on pharmacokinetics was developed for first-year bachelor medical and pharmacy undergraduate students. The educational intervention included watching a patient video, followed by focused exercises and plenary discussions on various pharmacological and patient-perspective related topics. The lecture concluded with students filling up a questionnaire with both open-ended questions and Likert-scale based statements. Besides learning about pharmacological principles (e.g. clinical relevance of pharmacokinetics), students additionally learnt about other prescribing-related topics (e.g. therapy failure, shared decision making) and were able to identify skills required of healthcare professionals, beyond those connected directly to pharmacotherapy (e.g. empathy, listening). The study identifies patient videos as a highly suitable educational tool. Not only do videos teach about the various pharmacological principles, but they also add an extra dimension to pharmacology teaching and learning and can easily be integrated into existing teaching modalities.

PMID:40020985 | DOI:10.1016/j.ejphar.2025.177431

Sci Adv. 2025 Feb 28;11(9):eads1568. doi: 10.1126/sciadv.ads1568. Epub 2025 Feb 28.

ABSTRACT

A reduced sense of smell is a common condition in people with cystic fibrosis (CF) that negatively affects their quality of life. While often attributed to nasal mucosa inflammation, the underlying causes of the olfactory loss remain unknown. Here, we characterized gene expression in olfactory epithelium cells from patients with CF using single-nuclei RNA sequencing and found altered expression of olfactory receptors (ORs) and genes related to progenitor cell proliferation. We confirmed these findings in newborn, inflammation-free samples of a CF animal model and further identified ultrastructural alterations in the olfactory epithelium and bulbs of these animals. We established that CFTR, the anion channel whose dysfunction causes CF, is dispensable for odor-evoked signaling in sensory neurons, yet CF animals displayed defective odor-guided behaviors consistent with the morphological and molecular alterations. Our study highlights CF's major role in modulating epithelial structure and OR expression, shedding light on the mechanisms contributing to olfactory loss in CF.

PMID:40020072 | DOI:10.1126/sciadv.ads1568

Biomed Phys Eng Express. 2025 Feb 28. doi: 10.1088/2057-1976/adbb71. Online ahead of print.

ABSTRACT


Polygenic risk scores (PRS) summarise genetic information into a single number with clinical and research uses. Machine learning (ML) has revolutionised multiple fields, however, the impact of ML on PRSs has been less significant. We explore how ML can improve the generation of PRSs.
Methods:
We train ML models on known PRSs using UK Biobank data. We explore whether the models can recreate human programmed PRSs, including using a single model to generate multiple PRSs, and ML difficulties in PRS generation. We investigate how ML can compensate for missing data and constraints on performance.
Results:
We demonstrate almost perfect generation of multiple PRSs with little loss of performance with reduced quantity of training data. For an example set of missing SNPs the MLP produces predictions that enable separation of cases from population samples with an area under the receiver operating characteristic curve of 0.847 (95% CI: 0.828-0.864) compared to 0.798 (95% CI: 0.779-0.818) for the PRS.
Conclusions:
ML can accurately generate PRSs, including with one model for multiple PRSs. The models are transferable and have high longevity. With certain missing SNPs the ML models can improve on PRS generation. Further improvements likely require use of additional input data.&#xD.

PMID:40020248 | DOI:10.1088/2057-1976/adbb71

Arch Cardiol Mex. 2025 Feb 28. doi: 10.24875/ACM.24000195. Online ahead of print.

ABSTRACT

OBJECTIVES: We aimed to assess the performance of an artificial intelligence-electrocardiogram (AI-ECG)-based model capable of detecting acute coronary occlusion myocardial infarction (ACOMI) in the setting of patients with acute coronary syndrome (ACS).

METHODS: This was a prospective, observational, longitudinal, and single-center study including patients with the initial diagnosis of ACS (both ST-elevation acute myocardial infarction [STEMI] & non-ST-segment elevation myocardial infarction [NSTEMI]). To train the deep learning model in recognizing ACOMI, manual digitization of a patient's ECG was conducted using smartphone cameras of varying quality. We relied on the use of convolutional neural networks as the AI models for the classification of ECG examples. ECGs were also independently evaluated by two expert cardiologists blinded to clinical outcomes; each was asked to determine (a) whether the patient had a STEMI, based on universal criteria or (b) if STEMI criteria were not met, to identify any other ECG finding suggestive of ACOMI. ACOMI was defined by coronary angiography findings meeting any of the following three criteria: (a) total thrombotic occlusion, (b) TIMI thrombus grade 2 or higher + TIMI grade flow 1 or less, or (c) the presence of a subocclusive lesion (> 95% angiographic stenosis) with TIMI grade flow < 3. Patients were classified into four groups: STEMI + ACOMI, NSTEMI + ACOMI, STEMI + non-ACOMI, and NSTEMI + non-ACOMI.

RESULTS: For the primary objective of the study, AI outperformed human experts in both NSTEMI and STEMI, with an area under the curve (AUC) of 0.86 (95% confidence interval [CI] 0.75-0.98) for identifying ACOMI, compared with ECG experts using their experience (AUC: 0.33, 95% CI 0.17-0.49) or under universal STEMI criteria (AUC: 0.50, 95% CI 0.35-0.54), (p value for AUC receiver operating characteristic comparison < 0.001). The AI model demonstrated a PPV of 0.84 and an NPV of 1.0.

CONCLUSION: Our AI-ECG model demonstrated a higher diagnostic precision for the detection of ACOMI compared with experts and the use of STEMI criteria. Further research and external validation are needed to understand the role of AI-based models in the setting of ACS.

PMID:40020200 | DOI:10.24875/ACM.24000195

Opt Lett. 2025 Mar 1;50(5):1723-1726. doi: 10.1364/OL.546727.

ABSTRACT

With the development of medical imaging technology, magnetic resonance imaging (MRI) has become an important tool for diagnosing and monitoring a variety of diseases. However, traditional MRI techniques are limited in terms of imaging speed and resolution. In this study, we developed an efficient body mode metasurface composite MRI enhancement system based on deep learning network training and realized the design and control of metasurface in the MHz band. Firstly, forward neural network is used to predict the electromagnetic response characteristics quickly. On this basis, the network is reverse-designed and the structural parameters of the metasurface are predicted. The experimental results show that the combination of deep neural network and electromagnetic metasurface significantly improves the design efficiency of metasurface and has great application potential in the MRI system.

PMID:40020024 | DOI:10.1364/OL.546727

Opt Lett. 2025 Mar 1;50(5):1719-1722. doi: 10.1364/OL.541330.

ABSTRACT

Single-photon detection has significant potential in the field of imaging due to its high sensitivity and has been widely applied across various domains. However, achieving high spatial and depth resolution through scattering media remains challenging because of the limitations of low light intensity, high background noise, and inherent time jitter of the detector. This paper proposes a physics-driven, learning-based photon-detection ghost imaging method to address these challenges. By co-designing the computational ghost imaging system and the network, we integrate imaging and reconstruction more closely to surpass the physical resolution limitations. Fringe patterns are employed to encode the depth information of the object into different channels of an image cube. A specialized depth fusion network with attention mechanisms is then designed to extract inter-depth correlation features, enabling super-resolution reconstruction at 256 × 256 pixels. Experimental results demonstrate that the proposed method presents superior imaging performance across various scenarios, offering a more compact and cost-effective alternative for photon-detection imaging.

PMID:40020023 | DOI:10.1364/OL.541330

PLoS One. 2025 Feb 28;20(2):e0316317. doi: 10.1371/journal.pone.0316317. eCollection 2025.

ABSTRACT

PURPOSE: The present study compared the performance of a Large Language Model (LLM; ChatGPT) and human interviewers in interviewing children about a mock-event they witnessed.

METHODS: Children aged 6-8 (N = 78) were randomly assigned to the LLM (n = 40) or the human interviewer condition (n = 38). In the experiment, the children were asked to watch a video filmed by the researchers that depicted behavior including elements that could be misinterpreted as abusive in other contexts, and then answer questions posed by either an LLM (presented by a human researcher) or a human interviewer.

RESULTS: Irrespective of condition, recommended (vs. not recommended) questions elicited more correct information. The LLM posed fewer questions overall, but no difference in the proportion of the questions recommended by the literature. There were no differences between the LLM and human interviewers in unique correct information elicited but questions posed by LLM (vs. humans) elicited more unique correct information per question. LLM (vs. humans) also elicited less false information overall, but there was no difference in false information elicited per question.

CONCLUSIONS: The findings show that the LLM was competent in formulating questions that adhere to best practice guidelines while human interviewers asked more questions following up on the child responses in trying to find out what the children had witnessed. The results indicate LLMs could possibly be used to support child investigative interviewers. However, substantial further investigation is warranted to ascertain the utility of LLMs in more realistic investigative interview settings.

PMID:40019879 | DOI:10.1371/journal.pone.0316317

Proc Natl Acad Sci U S A. 2025 Mar 4;122(9):e2406474122. doi: 10.1073/pnas.2406474122. Epub 2025 Feb 28.

ABSTRACT

B cells generate pathogen-specific antibodies and play an essential role in providing adaptive protection against infection. Antibody genes are modified in evolutionary processes acting on the B cell populations within an individual. These populations proliferate, differentiate, and migrate to long-term niches in the body. However, the dynamics of these processes in the human immune system are primarily inferred from mouse studies. We addressed this gap by sequencing the antibody repertoire and transcriptomes from single B cells in four immune-rich tissues from six individuals. We find that B cells descended from the same pre-B cell ("lineages") often colocalize within the same tissue, with the bone marrow harboring the largest excess of lineages without representation in other tissues. Within lineages, cells with different levels of somatic hypermutation are uniformly distributed among tissues and functional states. This suggests that the relative probabilities of localization and differentiation outcomes change negligibly during affinity maturation, and quantitatively agrees with a simple dynamical model of B cell differentiation. While lineages strongly colocalize, we find individual B cells nevertheless appear to make independent differentiation decisions. Proliferative antibody-secreting cells, however, deviate from these global patterns. These cells are often clonally expanded, their clones appear universally distributed among all sampled organs, and form lineages with an excess of cells of the same type. Collectively, our findings show the limits of peripheral blood monitoring of the immune repertoire, and provide a probabilistic model of the dynamics of antibody memory formation in humans.

PMID:40020190 | DOI:10.1073/pnas.2406474122