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NXT2 is a key component of the RNA nuclear export factor complex in the human testis and essential for spermatogenesis
Get PDFIn eukaryotes, the nucleocytoplasmic export of bulk poly(A)+-mRNAs through the nuclear pore complex is mediated by the ubiquitously expressed NXT1-NXF1 heterodimer. In humans, NXT1 has an X-chromosomal paralog, NXT2, which exhibits testis-enriched expression, suggesting a role in spermatogenesis. Here, we report the in vivo interaction of NXT2 with crucial components of the nuclear export machinery, including NXF1, the testis-specific NXF1 paralogs NXF2 and NXF3, and nuclear pore complex proteins. Binding to NXF2 and NXF3 is mediated by the NTF2-like domain of NXT2. By identifying infertile men with loss-of-function variants in NXT2 and NXF3, we link the impaired NXT2-NXF activity to disturbed germ cell development. The predominant absence of germ cells in men with NXT2 deficiency indicates its critical function already during fetal or first steps of germ cell development. In contrast, loss of NXF3 affects later stages of spermatogenesis, resulting in quantitatively and qualitatively impaired sperm production
Efficient Bayesian Full Waveform Inversion and Analysis of Prior Hypotheses in 3D
Get PDFThree-dimensional seismic full-waveform inversion (3D FWI) is a highly nonlinear and computationally demanding inverse problem that constructs 3D subsurface seismic velocity structures using seismic waveform data. To characterize nonuniqueness in the solutions, we demonstrate Bayesian 3D FWI using an efficient method called physically structured variational inference and apply it to 3D acoustic Bayesian FWI. The results provide reasonable posterior uncertainty estimates, at a computational cost that is only an order of magnitude greater than that of standard, deterministic FWI. Furthermore, we deploy variational prior replacement to calculate Bayesian solutions corresponding to different classes of prior information at low additional cost. The results obtained using prior information that models should be smooth show loop-like high uncertainty structures that are consistent with the fully nonlinear inversion results presented previously. These structures disappear when smoothing is not imposed, so we conclude that they may be caused by smoothness constraints in tomographic problems. We further analyze a variety of prior hypotheses by constructing Bayesian L-curves, which reveal the sensitivity of the inversion process to different prior assumptions. To our knowledge, this is the first study that allows such prior hypotheses to be compared in probabilistic 3D FWI at a feasible computational cost. This work shows that fully probabilistic 3D FWI can be performed and used to test different prior hypotheses, at a cost that may be practical, at least for small problems
Abstraction hierarchy to define biofoundry workflows and operations for interoperable synthetic biology research and applications
Get PDFLack of standardization in biofoundries limits the scalability and efficiency of synthetic biology research. Here, we propose an abstraction hierarchy that organizes biofoundry activities into four interoperable levels: Project, Service/Capability, Workflow, and Unit Operation, effectively streamlining the Design‑Build‑Test‑Learn (DBTL) cycle. This framework enables more modular, flexible, and automated experimental workflows. It improves communication between researchers and systems, supports reproducibility, and facilitates better integration of software tools and artificial intelligence. Our approach lays the foundation for a globally interoperable biofoundry network, advancing collaborative synthetic biology and accelerating innovation in response to scientific and societal challenges
The cross-linguistic role of animacy in grammar structures
Get PDFAnimacy is a semantic feature of nominals and follows a hierarchy: personal pronouns > human > animate > inanimate. In several languages, animacy imposes hard constraints on grammar. While it has been argued that these constraints may emerge from universal soft tendencies, it has been difficult to provide empirical evidence for this conjecture due to the lack of data annotated with animacy classes. In this work, we first propose a method to reliably classify animacy classes of nominals in 11 languages from 5 families, leveraging multilingual large language models (LLMs) and word sense disambiguation datasets. Then, through this newly acquired data, we verify that animacy displays consistent cross-linguistic tendencies in terms of preferred morphosyntactic constructions, although not always in line with received wisdom: animacy in nouns correlates with the alignment role of agent, early positions in a clause, and syntactic pivot (e.g., for relativisation), but not necessarily with grammatical subjecthood. Furthermore, the behaviour of personal pronouns in the hierarchy is idiosyncratic as they are rarely plural and relativised, contrary to high-animacy nouns
Integrating dynamical modeling and phylogeographic inference to characterize global influenza circulation
Get PDFGlobal seasonal influenza circulation involves a complex interplay between local (seasonality, demography, host immunity) and global factors (international mobility) shaping recurrent epidemic patterns. No studies so far have reconciled the two spatial levels, evaluating the coupling between national epidemics, considering heterogeneous coverage of epidemiological, and virological data, integrating different data sources. We propose a novel-combined approach based on a dynamical model of global influenza spread (GLEAM), integrating high-resolution demographic, and mobility data, and a generalized linear model of phylogeographic diffusion that accounts for time-varying migration rates. Seasonal migration fluxes across countries simulated with GLEAM are tested as phylogeographic predictors to provide model validation and calibration based on genetic data. Seasonal fluxes obtained with a specific transmissibility peak time and recurrent travel outperformed the raw air-transportation predictor, previously considered as optimal indicator of global influenza migration. Influenza A subtypes supported autumn–winter reproductive number as high as 2.25 and an average immunity duration of 2 years. Similar dynamics were preferred by influenza B lineages, with a lower autumn–winter reproductive number. Comparing simulated epidemic profiles against FluNet data offered comparatively limited resolution power. The multiscale approach enables model selection yielding a novel computational framework for describing global influenza dynamics at different scales—local transmission and national epidemics vs. international coupling through mobility and imported cases. Our findings have important implications to improve preparedness against seasonal influenza epidemics. The approach can be generalized to other epidemic contexts, such as emerging disease outbreaks to improve the flexibility and predictive power of modeling.</p
Speech-based digital cognitive assessments for detection of mild cognitive impairment:Validation against paper-based neurocognitive assessment scores
Get PDFBackgroundCognitive decline in Alzheimer's disease (AD) often includes speech impairments, where subtle changes may precede clinical dementia onset. As clinical trials focus on early identification of patients for disease-modifying treatments, digital speech-based assessments for scalable screening have become crucial.ObjectiveThis study aimed to validate a remote, speech-based digital cognitive assessment for mild cognitive impairment (MCI) detection through the comparison with gold-standard paper-based neurocognitive assessments.MethodsWithin the PROSPECT-AD project, speech and clinical data were obtained from the German DELCODE and DESCRIBE cohorts, including 21 healthy controls (HC), 110 participants with subjective cognitive decline (SCD), and 59 with MCI. Spearman rank and partial correlations were computed between speech-based scores and clinical measures. Kruskal-Wallis tests assessed group differences. We trained machine learning models to classify diagnostic groups comparing classification accuracies between gold-standard assessment scores and a speech-based digital cognitive assessment composite score (SB-C).ResultsGlobal cognition, as measured by SB-C, significantly differed between diagnostic groups ( H(2) = 30.93, p < 0.001). Speech-based scores were significantly correlated with global anchor scores (MMSE, CDR, PACC5). Speech-based composites for memory, executive function and processing speed were also correlated with respective domain-specific paper-based assessments. In logistic regression classification, the model combining SB-C and neuropsychological tests at baseline achieved a high discriminatory power in differentiating HC/SCD from MCI patients (Area Under the Curve = 0.86).ConclusionsOur findings support speech-based cognitive assessments as a promising avenue towards remote MCI screening, with implications for scalable screening in clinical trials and healthcare. </p
T cell responses in repeated controlled human schistosome infection compared to natural exposure
Get PDFIn Schistosoma-endemic regions a lack of natural sterilizing immunity means individuals are repeatedly infected, treated and reinfected. Due to difficulties in tracking natural infection, kinetics of host immune response during these reinfections have not been elucidated. Here, we use repeated (3x) controlled-human-Schistosoma mansoni infection (CHI) to study how antigen-specific T cells develop during reinfection (NCT05085470 study). We compared these responses to naturally infected endemic Ugandan individuals (HALLMARK study). A mixed Th1/Th2/regulatory CD4+ T cell response develops in repeated CHI. Adult-worm-specific responses after repeated CHI were similar to endemic-natural infection. However, endemic participants showed differential responses to egg- and cercariae-antigens. Repeated CHI with sequential exposure to cercariae of different sexes (male-female-male) revealed an elevated CD4+ T cell cytokine response to adult-worm and egg-antigens. Our findings demonstrate that single-sex schistosome infection elicits adult-worm-specific T cell cytokine responses that reflect endemic-natural infection. This study advances our understanding of the immunology of schistosome (re)infection in the human host.</p
Assessing Ambient Air Pollution's Effects on Birth Outcomes: A Scottish IVF Cohort Study (2010 -2018)
Get PDFBackgroundAmbient air pollution exposure during and before the pregnancy could result in adverse birth outcomes. This study uses data from women undergoing in vitro fertilization (IVF) data to investigate the associations between ambient air pollution exposure and adverse birth outcomes.MethodsThis study analyses the associations between adverse birth outcomes, namely low birth weight (LBW), small for gestational age (SGA), and preterm birth and daily mean air pollution exposure during each of four IVF windows. The air pollutants considered were particulate matter with an aerodynamic diameter of less than 10 µm (PM10) and 2.5 µm (PM2.5), as well as nitrogen dioxide (NO2), which were estimated using the Atmospheric Dispersion Modelling System (ADMS-Urban). This data was linked to the IVF patients' postcode providing estimates of exposure to air pollutants. Logistic regression models were used to quantify the associations between air pollution exposure and adverse birth outcomes, and conditioning confounding factors. A subgroup analysis was conducted to investigate the differences in the effects of ambient air pollution exposure on the ICSI and IVF groups.ResultsFrom January 2010 to May 2018, there are 2069 babies were able to be included in this study. We found no significant associations between air pollution exposure and the risk of adverse birth outcomes during window 1(85 days before oocyte retrieval) and 2 (14 days after gonadotrophin medication). With 1 µg⋅m−3 increase in PM10 concentration during window 3 (14 days after embryo transfer) and 4 (embryo transfer to delivery) led to a 5% (95% CI: 1.05—1.06) and 10% (95% CI: 1.01—1.21) increase in the odds of preterm birth, but not other outcomes. In window 3, every 1 µg⋅m−3 increase in NO2 concentrations resulted in a 2% (95% CI: 1.00 – 1.04) increase in the odds of LBW and a 3% (95% CI: 1.00 —1.05) increase in the odds of SGA but showed no effect for preterm birth. The results of the subgroup analysis suggest that the air pollution exposure may have a greater impact on the IVF group compared to the ICSI group
The adoption of handwritten text recognition at the National Library of Scotland
Get PDFThis chapter analyses the impact of AI and ML on library practices and workflows. Many aspects of AI in libraries have been explored in detail, including in this collection, but there remains a gap in our understanding of how libraries assess and adopt new tools. This gap will be addressed by exploring how the NLS is responding to the possibilities of HTR toolsthat might improve the legibility and accessibility of their digitised collections. This chapter draws on the findings of a research placement at the NLS, alongside project reports, conference papers and published research. It is organised into two sections:• The first section, entitled ‘Artificial intelligence and library values,’ briefly sets out the critical context for the adoption of AI and ML inlibraries. It builds upon existing work in the sector to emphasise that AI adoption must be grounded in the values and priorities of the sector. It also establishes the need for a research agenda based around the conscious reporting of the issues surrounding AI tool integration for digitisation and access pipelines.• The second section, ‘Investigating HTR at the NLS’, outlines how HTR has developed and explores its existing application to digitised handwritten collections. It draws upon existing research, including the authors’ previous work, to outline the current state of play for HTR in libraries. It then presents the findings of Nockels’ placement at the NLS, exploring how HTR might impact upon existing working practices. It concludes by considering how AI technologies might challenge us to reconsider the strategic objectives of libraries, and howtechnological change might unlock new types of usage and access
What measures have been used to explore the outcomes of family members of critically ill patients:a scoping review
Get PDFBackgroundFamily members of critically ill patients are known to experience short and longer term challenges, including emotional and social problems. To undertake robust future interventional research to support this cohort, we undertook a comprehensive evaluation of the measures used in family outcome research to date.DesignScoping review. We searched Medline, PsycINFO, Scopus, CINAHL, and Web of Science (core collection) for articles published between 2000 and 2024 which examined the outcomes of family members of critically ill patients. Data on outcome measures, study design, and population characteristics were extracted from eligible studies.ResultsWe reviewed 9873 abstracts and identified 388 eligible unique family member cohorts. Across these studies, there were 59 (15.2%) randomised control trials, 287 (74.0%) observational cohorts, 8 (2.1%) quality improvement programmes, and 34 (8.8%) non-randomised controlled interventional studies. Most research was undertaken in USA, Canada, and Europe (n = 264, 67.5%). A total of 218 different outcomes measures were used across the studies included. In this review, 345 (89%) studies measured emotional or psychological outcomes, 85 (22%) measured family experience outcomes, 65 (17%) measured general functional status, quality of life or well-being outcomes, 35 (9%) measured environmental or social outcomes, and 10 (3%) measured cognitive outcomes.ConclusionsWe identified 388 studies which reported the outcomes of family members of critically ill patients. Over 200 different outcomes measures were utilised, exploring conceptual domains such as quality of life as well as psychological and social outcomes. The majority of studies were observational in nature with variable follow-up timelines. This review has highlighted that a core outcome measure set is essential to enable reliable, robust, and comparable interventional research in this area.<br/
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