bluuebunny/crossref_metadata_2025_split huggingface dataset:
Pure-tone audiometry and dichotic listening in primary progressive aphasia and Alzheimer’s disease
Authors: Jiang Jessica , Johnson Jeremy , Levett Benjamin A , Core Lucy B , Volkmer Anna , Koohi Nehzat , Bamiou Doris-Eva , Marshall Charles R , Warren Jason D , Hardy Chris JD 
Published: March 2024

AbstractHearing is multifaceted and the relative contributions of peripheral and central hearing loss are rarely considered together in the context of dementia. Here, we assessed peripheral (as measured with pure-tone audiometry) and central (as measured with dichotic listening) hearing in 19 patients with typical amnestic Alzheimer’s disease (tAD), 10 patients with logopenic variant primary progressive aphasia (lvPPA), 11 patients with nonfluent/agrammatic variant PPA (nfvPPA), 15 patients with semantic variant PPA (svPPA), and 28 healthy age-matched individuals. Participants also underwent neuropsychological assessment and magnetic resonance image scanning, allowing us to use voxel-based morphometry to assess associations between hearing scores and grey matter volume. Dichotic listening was impaired in all patient groups relative to healthy controls. In the combined patient (but not healthy control) cohort, dichotic listening scores were significantly correlated with measures of global cognitive functioning and speech-based neuropsychological tasks. Pure-tone audiometry scores were not significantly elevated in any patient group relative to the healthy control group, and no significant correlations were observed between peripheral hearing and neuropsychological task performance in either the combined patient or healthy control cohorts. Neuroanatomically, dichotic listening performance was associated with grey matter volume in a bilateral fronto-temporo-parietal network over the combined patient cohort, but no correlates were identified for pure-tone audiometry. Our findings highlight the importance of speech parsing mechanisms beyond elementary sound detection in driving cognitive test performance, underline the importance of assessing central hearing alongside peripheral hearing in people with dementia, and further delineate the complex auditory profiles of neurodegenerative dementias.
Predictive Modeling for Diabetes Using GraphLIME
Authors: Costi Flavia , Onchis Darian , Hogea Eduard , Istin Codruta 
Published: March 2024

AbstractThe purpose of this paper is to present a detailed investigation of the advantages of employing GraphLIME (Local Interpretable Model Explanations for Graph Neural Networks) for the trustworthy prediction of diabetes mellitus. Our pursuit involves identifying the strengths of GraphLIME combined with the attention-mechanism over the standard coupling of deep learning neural networks with the original LIME method. The system build this way, provided us a proficient method for extracting the most relevant features and applying the attention mechanism exclusively to those features. We have closely monitored the performance metrics of the two approaches and conducted a comparative analysis. Leveraging attention mechanisms, we have achieved an accuracy of 92.6% for the addressed problem. The model’s performance is meticulously demonstrated throughout the study, and the results are furthermore evaluated using the Receiver Operating Characteristic (ROC) curve. By implementing this technique on a dataset of 768 patients diagnosed with or without diabetes mellitus, we have successfully boosted the model’s performance by over 18%.
Comparative cardiovascular safety of romosozumab versus bisphosphonates in Japanese patients with osteoporosis A new-user, active comparator design with instrumental variable analyses
Authors: Tominaga Ryoji , Ikenoue Tatsuyoshi , Ishii Ryosuke , Niihata Kakuya , Aita Tetsuro , Okuda Tadahisa , Shimizu Sayaka , Taguri Masataka , Kurita Noriaki 
Published: March 2024

AbstractImportanceRomosozumab, a novel anti-osteoporotic agent, confers marked improvement in bone mineral density; however, its cardiovascular safety remains a concern.ObjectiveTo compare the cardiovascular safety of romosozumab to bisphosphonates in patients with osteoporosis.DesignA cohort study using a new-user, active comparator design.SettingMedical facilities, including clinics and hospitals, visited by a wide range of populations in Japan that are covered by a commercial administrative claims database, collected from March 4, 2019 to August 31, 2021.ParticipantsJapanese adults aged ≥40 years who were diagnosed with osteoporosis or experienced a fragility fracture. Those who received romosozumab or bisphosphonates after the commercialization of romosozumab started in Japan (March 4, 2019) were included.ExposureA new prescription of romosozumab or bisphosphonate (based on verification of a 180-day washout period).Main Outcomes and MeasuresThe primary outcome was the incidence rate of cardiovascular disease (consisting of myocardial infarction and stroke) within one year of prescription. Cardiovascular disease was identified by algorithms with a combination of diagnosis, medical procedure, and drug codes. Facility-level prescription preference for romosozumab was used as an instrumental variable, defined as the proportion of romosozumab prescribed at the patient’s facility within 90 days prior to the index date.ResultsOf the 61,558 included prescriptions, 8,806 were for romosozumab and 52,752 were for bisphosphonates. The mean age of the romosozumab group was higher than that of the bisphosphonates group (80.5 vs. 78.3 years, respectively). The majority of patients were female (80.2 vs. 85.3%, respectively). The incidence of cardiovascular disease was 7.98 per 100 person-years for romosozumab versus 7.15 for bisphosphonates (unadjusted incidence rate ratio: 1.12 (95% confidence interval: 1.03-1.21)). An instrumental variable analysis using the two-stage residual inclusion method yielded a hazard ratio of 1.09 (95% confidence interval: 0.79-1.76) for romosozumab compared to bisphosphonates over one year.Conclusions and RelevanceIn this large observational study, there was no definitive evidence of increased risk of cardiovascular disease associated with romosozumab use compared with bisphosphonates in patients with osteoporosis. These findings alleviate clinicians’ excessive concerns about the potential cardiovascular safety of romosozumab in treatment decision-making for osteoporosis.
Annotation-preserving machine translation of English corpora to validate Dutch clinical concept extraction tools
Authors: Seinen Tom M , Kors Jan A , van Mulligen Erik M , Rijnbeek Peter R 
Published: March 2024

AbstractObjectiveThis work aims to explore the feasibility of validating Dutch concept extraction tools using annotated corpora translated from English, focusing on preserving annotations during translation and addressing the challenge posed by the scarcity of non-English corpora in clinical settings.Materials and methodsThree annotated corpora were standardized and translated from English to Dutch using two machine translation services, Google Translate and OpenAI GPT-4, with annotations preserved through a proposed method of embedding annotations in the text before translation. The performance of two concept extraction tools, MedSpaCy and MedCAT, was assessed across the corpora in both Dutch and English.ResultsThe translation process effectively generated Dutch annotated corpora, allowing the concept extraction tools to perform similarly in both English and Dutch. Although there were some differences in how annotations were preserved across translations, these did not affect extraction accuracy. Supervised MedCAT models consistently outperformed unsupervised models, whereas MedSpaCy demonstrated high recall but lower precision.DiscussionOur validation of Dutch concept extraction tools on corpora translated from English was successful, highlighting the efficacy of our annotation preservation method and the potential for efficiently creating multilingual corpora. Further improvements and comparisons of annotation preservation techniques and strategies for corpus synthesis could lead to more efficient development of multilingual corpora and more accurate non-English clinical concept extraction tools.ConclusionThis study has demonstrated that translated English corpora can be effectively used to validate non-English concept extraction tools. The annotation preservation method used during translation proved effective, and future research should aim to extend this corpus translation method to additional languages and clinical settings.
Translational modeling-based evidence for enhanced efficacy of standard-of-care drugs in combination with anti-microRNA-155 in non-small-cell lung cancer
Authors: Dogra Prashant , Shinglot Vrushaly , Ruiz-Ramírez Javier , Cave Joseph , Butner Joseph D. , Schiavone Carmine , Duda Dan G. , Kaseb Ahmed O. , Chung Caroline , Koay Eugene J. , Cristini Vittorio , Ozpolat Bulent , Calin George A. , Wang Zhihui 
Published: March 2024

AbstractElevated microRNA-155 (miR-155) expression in non-small-cell lung cancer (NSCLC) promotes cisplatin resistance and negatively impacts treatment outcomes. However, miR-155 can also boost anti-tumor immunity by suppressing PD-L1 expression. We developed a multiscale mechanistic model, calibrated within vivodata and then extrapolated to humans, to investigate the therapeutic effects of nanoparticle-delivered anti-miR-155 in NSCLC, alone or in combination with standard-of-care drugs. Model simulations and analyses of the clinical scenario revealed that monotherapy with anti-miR-155 at a dose of 2.5 mg/kg administered once every three weeks has substantial anti-cancer activity. It led to a median progression-free survival (PFS) of 6.7 months, which compared favorably to cisplatin and immune checkpoint inhibitors. Further, we explored the combinations of anti-miR-155 with standard-of-care drugs, and found strongly synergistic two- and three-drug combinations. A three-drug combination of anti-miR-155, cisplatin, and pembrolizumab resulted in a median PFS of 13.1 months, while a two-drug combination of anti-miR-155 and cisplatin resulted in a median PFS of 11.3 months, which emerged as a more practical option due to its simple design and cost-effectiveness. Our analyses also provided valuable insights into unfavorable dose ratios for drug combinations, highlighting the need for optimizing dose regimen to prevent antagonistic effects. Thus, this work bridges the gap between preclinical development and clinical translation of anti-miR-155 and unravels the potential of anti-miR-155 combination therapies in NSCLC.
Digital Pathology, Deep Learning, and Cancer: A Narrative Review
Authors: Williams Darnell K. Adrian , Graifman Gillian , Hussain Nowair , Amiel Maytal , Priscilla Tran , Reddy Arjun , Haider Ali , Kavitesh Bali Kumar , Li Austin , Alishahian Leael , Perera Nichelle , Efros Corey , Babu Myoungmee , Tharakan Mathew , Etienne Mill , Babu Benson A. 
Published: March 2024

AbstractBackground and ObjectiveCancer is a leading cause of morbidity and mortality worldwide. The emergence of digital pathology and deep learning technologies signifies a transformative era in healthcare. These technologies can enhance cancer detection, streamline operations, and bolster patient care. A substantial gap exists between the development phase of deep learning models in controlled laboratory environments and their translations into clinical practice. This narrative review evaluates the current landscape of deep learning and digital pathology, analyzing the factors influencing model development and implementation into clinical practice.MethodsWe searched multiple databases, including Web of Science, Arxiv, MedRxiv, BioRxiv, Embase, PubMed, DBLP, Google Scholar, IEEE Xplore, and Cochrane, targeting articles on whole slide imaging and deep learning published from 2014 and 2023. Out of 776 articles identified based on inclusion criteria, we selected 36 papers for the analysis.Key Content and FindingsMost articles in this review focus on the in-laboratory phase of deep learning model development, a critical stage in the deep learning lifecycle. Challenges arise during model development and their integration into clinical practice. Notably, lab performance metrics may not always match real-world clinical outcomes. As technology advances and regulations evolve, we expect more clinical trials to bridge this performance gap and validate deep learning models’ effectiveness in clinical care. High clinical accuracy is vital for informed decision-making throughout a patient’s cancer care.ConclusionsDeep learning technology can enhance cancer detection, clinical workflows, and patient care. Challenges may arise during model development. The deep learning lifecycle involves data preprocessing, model development, and clinical implementation. Achieving health equity requires including diverse patient groups and eliminating bias during implementation. While model development is integral, most articles focus on the pre-deployment phase. Future longitudinal studies are crucial for validating models in real-world settings post-deployment. A collaborative approach among computational pathologists, technologists, industry, and healthcare providers is essential for driving adoption in clinical settings.
Functional analysis of the epilepsy gene Pcdh19 using a novel GFP-reporter mouse model
Authors: Mincheva-Tasheva Stefka , Scherer Michaela , Robertson Louise J. , Piltz Sandra , Bensalem Julien , Pederick Daniel T. , Thomas Paul Q. 
Published: March 2024

AbstractMutations in the X-linked genePCDH19are the cause of PCDH19-Clustering epilepsy, an infantile-onset disorder characterized by seizures and intellectual disabilities. Although several intra and extracellular functions of PCDH19 have been identified, the spatiotemporal impact ofPcdh19deletionin vivois poorly understood. To investigate the consequences of eliminatingPcdh19in specific cell and brain regions, we generated a novelPcdh19floxed mouse with a GFP reporter (Pcdh19-cKO-GFP). UsingPcdh19-cKO-GFP andSyn1-Cre mouse lines we demonstrated thatPcdh19elimination in neurons leads to abnormal hippocampal neurogenesis and impaired mouse behaviour. To assess the impact of region-specific elimination ofPcdh19on brain physiology we used aGfap-Cre mice line. SpecificPcdh19deletion in the hippocampus resulted in increased neurogenesis and decreased memory formation. Finally, we assessed the feasibility of using our conditional mouse model for stage-specificPcdh19elimination during embryogenesis using a Dox-inducible Cre-deletor line. Taken together, these results demonstrate the utility of our uniquePcdh19-cKO-GFP mouse model to investigate PCDH19 function in brain physiology and pathology.
Chalkophomycin Biosynthesis Revealing Unique Enzyme Architecture for a Hybrid Nonribosomal Peptide Synthetase and Polyketide Synthase
Authors: Yang Long , Yi Liwei , Gong Bang , Chen Lili , Li Miao , Zhu Xiangcheng , Duan Yanwen , Huang Yong 
Published: March 2024

AbstractChalkophomycin is a novel chalkophore with antibiotic activities isolated fromStreptomycessp. CB00271, while its potential in studying cellular copper homeostasis makes it an important probe and drug lead. The constellation ofN-hydroxylpyrrole, 2H-oxazoline, diazeniumdiolate, and methoxypyrrolinone functional groups into one compact molecular architecture capable to coordinate cupric ion draws interest to unprecedented enzymology responsible for chalkophomycin biosynthesis. To elucidate the biosynthetic machinery for chalkophomycin production, thechmbiosynthetic gene cluster from S. sp. CB00271 was identified, and its involvement in chalkophomycin biosynthesis was confirmed by gene replacement. Thechmcluster was localized to a ∼31 kb DNA region, consisting of 19 open reading frames that encode five non-ribosomal peptide synthetase (ChmHIJLO), one modular polyketide synthases (ChmP), six tailoring enzymes (ChmFGMNQR), two regulatory proteins (ChmAB), and four resistance proteins (ChmA′CDE). A model for chalkophomycin biosynthesis is proposed based on functional assignments from sequence analysis and structure modelling, and is further supported by analogy to over 100chm-type gene clusters in public databases. Our studies thus set the stage to fully investigate chalkophomycin biosynthesis and to engineer chalkophomycin analogues through a synthetic biology approach.
Investigating working memory updating processes of the human subcortex using 7T MRI
Authors: Trutti Anne C. , Sjoerds Zsuzsika , Boag Russell J. , Walstra Solenn L.Y. , Miletić Steven , Isherwood Scott S.J. , Bazin Pierre-Louis , Hommel Bernhard , Habli Sarah , Tse Desmond H.Y. , Håberg Asta K. , Forstmann Birte 
Published: March 2024

AbstractA growing body of research suggests that dopamine is involved in working memory updating and that the striatum takes up a critical role in the subprocess of working memory gating (Braver & Cohen, 2000; Cools & D’Esposito, 2011; D’Ardenne et al., 2012; Jongkees, 2020). In this study, we investigated subcortical–in particular, possible dopaminergic–involvement in working memory updating subprocesses using the reference-back task and ultra-high field 7 Tesla fMRI. Using a scanning protocol optimized for BOLD-sensitivity in the subcortex, we found no evidence of subcortical activation during working memory gate opening, predominantly activations in frontoparietal network regions, which challenges the idea of a striatal gating mechanism. However, during gate closing, subcortical activation was observed. Furthermore, a ready-to-update mode demonstrated large-spread subcortical activation, including basal ganglia nuclei, suggesting that the basal ganglia are engaged in general updating processes rather than specifically controlling the working memory gate. Moreover, substituting new information into working memory elicited activation in dopamine-producing midbrain regions along with the striatum, thalamus, and prefrontal cortex, indicating engagement of the basal ganglia-thalamo-cortical loop possibly driven by (potential) dopaminergic activity. These findings expand our understanding of subcortical regions involved in working memory updating, shifting the focus from gate opening to substitution as a midbrain-driven updating process.
Perceptual awareness of near-threshold tones scales gradually with auditory cortex activity and pupil dilation
Authors: Doll Laura , Dykstra Andrew R. , Gutschalk Alexander 
Published: March 2024

AbstractPerceptual awareness covaries with negative-going responses in sensory cortex, but the derived concept of perceptual awareness negativity has been criticized a.o. because of its presence for undetected stimuli. To evaluate this objection, we combined magnetoencephalography, electroencephalography, and pupillometry to study the roles of sustained attention and response criterion on the auditory awareness negativity. Participants first detected distractor sounds and denied hearing task-irrelevant near-threshold tones, which evoked neither awareness negativity nor pupil dilation. These same tones evoked responses when task-relevant, stronger for hit but also present for miss trials. To explore if response criterion could explain the presence of responses for miss trials, participants rated their perception on a six-point scale. Decreasing perception ratings were associated with gradually reduced evoked responses, consistent with signal detection theory. These results support the concept of an awareness negativity that is modulated by attention, but does not exhibit a non-linear threshold mechanism.
Developmental assembly of multi-component polymer systems through interconnected gene networksin vitro
Authors: Sorrentino Daniela , Ranallo Simona , Ricci Francesco , Franco Elisa 
Published: March 2024

AbstractLiving cells regulate the dynamics of developmental events through interconnected signaling systems that activate and deactivate inert precursors. This suggests that similarly, synthetic biomaterials could be designed to develop over time by using chemical reaction networks to regulate the availability of assembling components. Here we demonstrate how the sequential activation or deactivation of distinct DNA building blocks can be modularly coordinated to form distinct populations of self-assembling polymers using a transcriptional signaling cascade of synthetic genes. Our building blocks are DNA tiles that polymerize into nanotubes, and whose assembly can be controlled by RNA molecules produced by synthetic genes that target the tile interaction domains. To achieve different RNA production rates, we use a strategy based on promoter “nicking” and strand displacement. By changing the way the genes are cascaded and the RNA levels, we demonstrate that we can obtain spatially and temporally different outcomes in nanotube assembly, including random DNA polymers, block polymers, and as well as distinct autonomous formation and dissolution of distinct polymer populations. Our work demonstrates a way to construct autonomous supramolecular materials whose properties depend on the timing of molecular instructions for self-assembly, and can be immediately extended to a variety of other nucleic acid circuits and assemblies.
Decoding the Cognitive map: Learning place cells and remapping
Authors: Pettersen Markus Borud , Schøyen Vemund Sigmundson , Malthe-Sørenssen Anders , Lepperød Mikkel Elle 
Published: March 2024

AbstractHippocampal place cells are known for their spatially selective firing and are believed to encode an animal’s location while forming part of a cognitive map of space. These cells exhibit marked tuning curve and rate changes when an animal’s environment is sufficiently manipulated, in a process known as remapping. Place cells are accompanied by many other spatially tuned cells such as border cells and grid cells, but how these cells interact during navigation and remapping is unknown. In this work, we build a normative place cell model wherein a neural network is tasked with accurate position reconstruction and path integration. Motivated by the notion of a cognitive map, the network’s position is estimated directly from its learned representations. To obtain a position estimate, we propose a non-trainable decoding scheme applied to network output units, inspired by the localized firing patterns of place cells. We find that output units learn place-like spatial representations, while upstream recurrent units become boundary-tuned. When the network is trained to perform the same task in multiple simulated environments, its place-like units learn to remap like biological place cells, displaying global, geometric and rate remapping. These remapping abilities appear to be supported by rate changes in upstream units. While the model does not learn grid-like units, its place cell centers form clusters organized in a hexagonal lattice in open fields. When we decode the center locations of CA1 place fields in mice, we find a similar clustering tendency. This suggests a potential mechanism for the interaction between place cells, border cells, and grid cells. Our model provides a normative framework for learning spatial representations previously reserved for biological place cells, providing new insight into place cell field formation and remapping.