bluuebunny/crossref_metadata_2025_split huggingface dataset:
Inflammatory cytokines mediate the induction of and awakening from metastatic dormancy
Authors: Pereira Paulo , Panier Joshua , Nater Marc , Herbst Michael , Calvanese Anna Laura , Köksal Hakan , Castañón Héctor , Cecconi Virginia , Tallón de Lara Paulino , Pascolo Steve , van den Broek Maries 
Published: August 2024

SUMMARYMetastases arise from disseminated cancer cells (DCCs) that detach from the primary tumor and seed distant organs. There, quiescent DCCs can survive for an extended time, a state referred to as metastatic dormancy. The mechanisms governing the induction, maintenance, and awakening from metastatic dormancy are unclear. We show that the differentiation of dormancy-inducing CD8+T cells requires CD4+T cell help, and that IFNγ directly induces dormancy in DCCs. The maintenance of metastatic dormancy, however, is independent of T cells. Instead, awakening from dormancy requires an inflammatory signal, and we identified CD4+T cell-derived IL- 17A as an essential wake-up signal for dormant DCCs in the lungs.Thus, the induction and awakening from metastatic dormancy require an external stimulus, while the maintenance of dormancy does not rely on the continuous surveillance by lymphocytes.
Mast cell-derived chymases are essential for the resolution of inflammatory pain in mice
Authors: de Souza Sabrina , Laumet Sophie , Inyang Kufreobong E. , Hua Hannah , Sim Jaewon , Folger Joseph K. , Moeser Adam J. , Laumet Geoffroy 
Published: August 2024

AbstractImmune cells play a critical role in the transition from acute to chronic pain. However, the role of mast cells in pain remains under-investigated. Here, we demonstrated that the resolution of inflammatory pain is markedly delayed in mast-cell-deficient mice. In response to Complete Freund Adjuvant (CFA), mast-cell-deficient mice showed greater levels of nitric oxide and altered cytokine/chemokine profile in inflamed skin in both sexes. In Wild-Type (WT) mice, the number of mast cell and mast cell-derived chymases; chymase 1 (CMA1) and mast cell protease 4 (MCPT4) increased in the inflamed skin. Inhibiting chymase enzymatic activity delayed the resolution of inflammatory pain. Consistently, local pharmacological administration of recombinant CMA1 and MCPT4 promoted the resolution of pain hypersensitivity and attenuated the upregulation of cytokines and chemokines under inflammation. We identified CCL9 as a target of MCPT4. Inhibition of CCL9 promoted recruitment of CD206+myeloid cells and alleviated inflammatory pain. Our work reveals a new role of mast cell-derived chymases in preventing the transition from acute to chronic pain and suggests new therapeutic avenues for the treatment of inflammatory pain.SummaryMast cell-derived chymases play an unexpected role in the resolution of inflammatory pain and regulate the immune response.Graphical abstractMast cells derived chymase MCPT4 degrades CCL9 to promote acute inflammatory pain resolution and prevent chronic pain.CFA-induced inflammation increases mast cells that degranulate and release chymases, like MCPT4 and CMA1, which in turn cleaves cytokines and chemokines such as CCL9. CCL9 cleavage induces the recruitment of CD206+myeloid cells to promote the resolution of pain and prevent the transition from acute to chronic pain.
PGSFusionstreamlines polygenic score construction and epidemiological applications in biobank-scale cohorts
Authors: Yang Sheng , Ye Xiangyu , Ji Xiaolong , Li Zhenghui , Tian Min , Huang Peng , Cao Chen 
Published: August 2024

AbstractBackgroundThe polygenic score (PGS) is an estimate of an individual’s genetic susceptibility to a specific complex trait and has been instrumental to the development of precision medicine. Clinically, the simplest form of PGS, which is calculated as a weighted sum of variant counts, has been widely applied to conduct disease risk classification. Unfortunately, despite the critical importance of PGS, there are few online resources available to biologists and epidemiologists to calculate PGS in a user-friendly manner.ResultsTo address this need, we have developed a web server, PGSFusion, that streamlines the construction of PGS using a large variety of methods targeting different epidemiological requirements. PGSFusion included 16 PGS methods in four categories, which are single-trait, annotation-based, multiple-trait, and cross-ancestry. In addition, PGSFusion also utilizes UK Biobank data to provide two kinds of in-depth analyses: i) prediction performance evaluation to display the consistency between PGS and specific traits and the effect size of PGS in different genetic risk groups; ii) joint effect analysis to investigate the interaction between PGS and covariates, as well as the genetic effect size in different subgroups of covariates. PGSFusion automatically identifies the required information in uploaded summary statistics files, provides a selection of suitable methods, and outputs calculated PGSs and their corresponding epidemiological results, all without requiring prior programming knowledge. To demonstrate the function of PGSFusion, we showcase three case studies in different application scenario, highlighting its versatility and values to researchers.ConclusionsOverall, PGSFusion presents an easy-to-use, effective, and extensible platform for PGS construction, promoting the accessibility and utility of PGS for researchers in the field of precision medicine.
Specific light-regime adaptations, terpenoid profiles and engineering potential in ecologically diversePhaeodactylum tricornutumstrains
Authors: Morelli Luca , Patwari Payal , Pruckner Florian , Bastide Maxime , Fabris Michele 
Published: August 2024

AbstractMicroalgae, and among them, the diatomPhaeodactylum tricornutumstand out with their remarkable versatility and metabolic engineering potential. Diatoms exhibit substantial variability in metabolism, photosynthetic physiology and environmental adaptation, even across the same species. These factors can affect the design and outcome of metabolic engineering strategies. In this study, we profiled the diversity of biotechnologically relevant traits of threeP. tricornutumstrains (Pt1, Pt6, and Pt9) under different light regimes to identify the most suitable chassis to be employed as bio-factory to produce high-value terpenoids. We conducted detailed assessments of these strains, using pulse amplitude modulated (PAM) fluorometry to measure photosynthetic efficiency and we analyzed the composition of pigments and triterpenoids, as main terpenoid metabolic sinks. Parameters such as the maximum quantum yield of PSII (Fv/Fm), the efficiency of excitation energy capture (Fv’/Fm’), and OJIP kinetics were used to estimate photosynthetic performance in different light regimes. Additionally, we evaluated their transformation efficiency and their capacity to produce heterologous monoterpenoids, using geraniol as a model product. Our findings revealed that Pt1, widely used in laboratories, exhibits robust growth and photosynthetic performance under standard laboratory conditions. Pt6, adapted to intertidal environments, shows unique resilience in fluctuating conditions, while Pt9, with its high-temperature tolerance, excels under continuous high irradiance. Additionally, this variability across strains and light conditions influenced the metabolic output of each strain. We concluded that understanding the physiological responses of differentP. tricornutumstrains to light is crucial for optimizing their use in metabolic engineering. The insights gained from this research will facilitate the strategic selection and exploitation of these strains in algae biotechnology, enhancing the production of commercially valuable compounds such as high-value terpenoids and derivatives. This comprehensive characterization of strains under varying light conditions offers a pathway to more efficient and targeted metabolic engineering applications.HighlightsPt1, Pt6, and Pt9 exhibit distinct physiology under different light regimes.Pt9 is photosynthetically more performant in continuous light, Pt6 in photoperiod.Light regimes affect pigments and triterpenoid content in all three strains.Each strain exhibits a specific carotenoid and triterpenoid composition.Bacterial conjugation of episomes varies across strains, it is more efficient in Pt1.Pt1 is suited for the heterologous synthesis of monoterpenes (geraniol).
Brief encounters with real objects modulate medial parietal but not occipitotemporal cortex
Authors: Wardle Susan G. , Rispoli Beth , Roopchansingh Vinai , Baker Chris I. 
Published: August 2024

AbstractHumans are skilled at recognizing everyday objects from pictures, even if we have never encountered the depicted object in real life. But if we have encountered an object, how does that real-world experience affect the representation of its photographic image in the human brain? We developed a paradigm that involved brief real-world exploration of everyday objects prior to the measurement of brain activity with fMRI while viewing pictures of the objects. We discovered that while object-responsive regions in lateral occipital and ventral temporal cortex were visually driven and contained highly invariant representations of specific objects, those representations were not modulated by real-world exploration. However, real-world experience with an object produced foci of increased activation in medial parietal and posterior cingulate cortex, identifying an important associative region for the experience gained from manual object exploration. The richness of object representations beyond their photographic image has important implications for understanding object recognition in both the human brain and in computational models.
Untargeted proteomics enables ultra-rapid variant prioritization in mitochondrial and other rare diseases
Authors: Hock Daniella H. , Caruana Nikeisha J. , Semcesen Liana N. , Lake Nicole J. , Formosa Luke E. , Amarasekera Sumudu S. C. , Stait Tegan , Tregoning Simone , Frajman Leah E. , Robinson David R. L. , Ball Megan , Reljic Boris , Ryder Bryony , Wallis Mathew J. , Vasudevan Anand , Beck Cara , Peters Heidi , Lee Joy , Tan Natalie B. , Freckmann Mary-Louise ,   MitoMDT Diagnostic Network for Genomics and Omics, Karlaftis Vasiliki , Attard Chantal , Monagle Paul , Samarasinghe Amanda , Brown Rosie , Bi Weimin , Lek Monkol , McFarland Robert , Taylor Robert W. , Ryan Michael T. , Stark Zornitza , Christodoulou John , Compton Alison G. , Thorburn David R. , Stroud David A. 
Published: August 2024

AbstractOnly half of individuals with suspected rare diseases receive a definitive genetic diagnosis following genomic testing. A genetic diagnosis allows access to appropriate patient care and reduces the number of potentially unnecessary interventions and related healthcare costs. Here, we demonstrate that an untargeted quantitative mass-spectrometry approach quantifying >6,000 proteins in primary fibroblasts representing >80% of known mitochondrial disease genes can provide functional evidence for 83% of individuals in a cohort of known primary mitochondrial diseases. We profiled >90 individuals, including 28 with confirmed disease and diagnosed 6 individuals with variants in both nuclear and mitochondrial genes. Lastly, we developed an ultra-rapid proteomics pipeline using minimally invasive peripheral blood mononuclear cells to support upgrade of variant pathogenicity in as little as 54 hours in critically ill infants with suspected mitochondrial disorders. This study supports the integration of a single untargeted proteomics test into routine diagnostic practice for the diagnosis of rare genetic disorders in clinically actionable timelines, offering a paradigm shift for the functional validation of genetic variants.
Relationships between depression, anxiety, and motivation in the real-world: Effects of physical activity and screentime
Authors: Beltrán J. , Jacob Y. , Mehta M. , Hossain T. , Adams A. , Fontaine S. , Torous J. , McDonough C. , Johnson M. , Delgado A. , Murrough J. W. , Morris L. S. 
Published: August 2024

AbstractBackgroundMood and anxiety disorders are highly prevalent and comorbid worldwide, with variability in symptom severity that fluctuates over time. Digital phenotyping, a growing field that aims to characterize clinical, cognitive and behavioral features via personal digital devices, enables continuous quantification of symptom severity in the real world, and in real-time.MethodsIn this study, N=114 individuals with a mood or anxiety disorder (MA) or healthy controls (HC) were enrolled and completed 30-days of ecological momentary assessments (EMA) of symptom severity. Novel real-world measures of anxiety, distress and depression were developed based on the established Mood and Anxiety Symptom Questionnaire (MASQ). The full MASQ was also completed in the laboratory (in-lab). Additional EMA measures related to extrinsic and intrinsic motivation, and passive activity data were also collected over the same 30-days. Mixed-effects models adjusting for time and individual tested the association between real-world symptom severity EMA and the corresponding full MASQ sub-scores. A graph theory neural network model (DEPNA) was applied to all data to estimate symptom interactions.ResultsThere was overall good adherence over 30-days (MA=69.5%, HC=71.2% completion), with no group difference (t(58)=0.874, p=0.386). Real-world measures of anxiety/distress/depression were associated with their corresponding MASQ measure within the MA group (t’s > 2.33, p’s < 0.024). Physical activity (steps) was negatively associated with real-world distress and depression (IRRs > 0.93, p’s ≤ 0.05). Both intrinsic and extrinsic motivation were negatively associated with real-world distress/depression (IRR’s > 0.82, p’s < 0.001). DEPNA revealed that both extrinsic and intrinsic motivation significantly influenced other symptom severity measures to a greater extent in the MA group compared to the HC group (extrinsic/intrinsic motivation: t(46)= 2.62, p < 0.02, q FDR < 0.05, Cohen’sd= 0.76; t(46)= 2.69, p < 0.01, q FDR < 0.05, Cohen’sd= 0.78 respectively), and that intrinsic motivation significantly influenced steps (t(46)= 3.24, p < 0.003, q FDR < 0.05, Cohen’sd= 0.94).ConclusionsNovel real-world measures of anxiety, distress and depression significantly related to their corresponding established in-lab measures of these symptom domains in individuals with mood and anxiety disorders. Novel, exploratory measures of extrinsic and intrinsic motivation also significantly related to real-world mood and anxiety symptoms and had the greatest influencing degree on patients’ overall symptom profile. This suggests that measures of cognitive constructs related to drive and activity may be useful in characterizing phenotypes in the real-world.
Talking while Walking After Concussion: Acute effects of concussion on speech pauses and gait speed
Authors: Yang Shu , Johnson Paula K. , Hansen Colby R. , Wilde Elisabeth A. , Cortez Melissa M. , Dibble Leland E. , Fino Peter C. , Raffegeau Tiphanie E. 
Published: August 2024

ABSTRACTBackgroundDeficits in dual-tasks (DT) are frequently observed post-concussion (i.e., mild Traumatic Brain Injury). However, traditional DT may not be relevant to daily life. Walking while talking elicits DT costs in healthy adults and is part of daily life.ObjectiveWe investigated the effect of concussion on walking with extemporaneous speech and explored relationships between DT and acute symptoms.MethodsParticipants with recent concussion (<14 days post-injury) and controls completed three tasks: single-task gait without speaking (STG), single-task speaking without walking (STS) and walking while speaking (DT). Silent pauses in speech audio reflected cognitive performance, and gait was quantified using inertial sensors. We used linear mixed models to compare groups and conditions and explored associations with self-reported symptoms.ResultsBoth concussion (n=19) and control (n=18) groups exhibited longer speech pauses (p< 0.001), slower walking speeds (p< 0.001), and slower cadence (p< 0.001) during the DT compared to ST conditions. There were no group differences or interactions for speech pauses (p> 0.424). The concussion group walked slower (p= 0.010) and slowed down more during DT than the control group (group*taskp= 0.032). Vestibular symptoms strongly associated with ST speech pause duration (ρ= 0.72), ST gait speed (ρ= −0.75), and DT gait speed (ρ= −0.78).ConclusionsExtemporaneous speech is well-practiced, but challenging to complete while walking post-concussion. Strong associations between DT outcomes and vestibular-related symptoms suggest DT deficits vary with post-concussion symptomology. DT deficits may be deleterious to daily tasks post-concussion.
Clonal Hematopoiesis of Indeterminate Potential in Crohn’s Disease and Ulcerative Colitis
Authors: Esai Selvan Myvizhi , Nathan Daniel I. , Guisado Daniela , Collatuzzo Giulia , Iruvanti Sushruta , Boffetta Paolo , Mascarenhas John , Hoffman Ronald , Cohen Louis J. , Marcellino Bridget K. , Gümüş Zeynep H. 
Published: August 2024

AbstractClonal hematopoiesis of indeterminate potential (CHIP) is the presence of somatic mutations in myeloid and lymphoid malignancy genes in the blood cells of individuals without a hematologic malignancy. Inflammation is hypothesized to be a key mediator in the progression of CHIP to hematologic malignancy and patients with CHIP have a high prevalence of inflammatory diseases. This study aimed to identify the prevalence and characteristics of CHIP in patients with inflammatory bowel disease (IBD). We analyzed whole exome sequencing data from 587 Crohn’s disease (CD), 441 ulcerative colitis (UC), and 293 non-IBD controls to assess CHIP prevalence and used logistic regression to study associations with clinical outcomes. Older UC patients (age>45) harbored increased myeloid-CHIP mutations compared to younger patients (age≤45) (p=0.01). Lymphoid-CHIP was more prevalent in older IBD patients (p=0.007). Young CD patients were found to have myeloid-CHIP with high-risk features. IBD patients with CHIP exhibited unique mutational profiles compared to controls. Steroid use was associated with increased CHIP (p=0.05), while anti-TNF therapy was associated with decreased myeloid-CHIP (p=0.03). Pathway enrichment analyses indicated overlap between CHIP genes, IBD phenotypes, and inflammatory pathways. Our findings underscore a connection between IBD and CHIP pathophysiology. Patients with IBD and CHIP had unique risk profiles especially among older UC patients and younger CD patients. These findings suggest distinct evolutionary pathways for CHIP in IBD and necessitate awareness among IBD providers and hematologists to identify patients potentially at risk for CHIP-related complications including malignancy, cardiovascular disease and acceleration of their inflammatory disease.
Evaluating Traditional, Deep Learning, and Subfield Methods for Automatically Segmenting the Hippocampus from MRI
Authors: Sghirripa Sabrina , Bhalerao Gaurav , Griffanti Ludovica , Gillis Grace , Mackay Clare , Voets Natalie , Wong Stephanie , Jenkinson Mark ,   the Alzheimer’s Disease Neuroimaging Initiative
Published: August 2024

AbstractGiven the relationship between hippocampal atrophy and cognitive impairment in various pathological conditions, hippocampus segmentation from MRI is an important task in neuroimaging. Manual segmentation, though considered the gold standard, is time-consuming and error-prone, leading to the development of numerous automatic segmentation methods. However, no study has yet independently compared the performance of traditional, deep learning-based, and hippocampal subfield segmentation methods within a single investigation. We evaluated nine automatic hippocampal segmentation methods (FreeSurfer, FastSurfer, FIRST, e2dhipseg, HippMapper, Hippodeep, FreeSurfer-Subfields, HippUnfold and HSF) across three datasets with manually segmented hippocampus labels. Performance metrics included overlap with manual labels, correlations between manual and automatic volumes, diagnostic group differentiation, and systematically located false positives and negatives. Most methods, especially deep learning-based ones, performed well on public datasets but showed more error and variability on unseen data. Many methods tended to over-segment, particularly at the anterior hippocampus border, but were able to distinguish between healthy controls, MCI, and dementia patients based on hippocampal volume. Our findings highlight the challenges in hippocampal segmentation from MRI and the need for more publicly accessible datasets with manual labels across diverse ages and pathological conditions.Key MessagesWe evaluated nine automatic hippocampal segmentation methods, including traditional and deep learning-based approaches, across three datasets with manually segmented hippocampus labels.While deep learning-based methods perform well on public datasets, they show more error and variability on unseen data that is more reflective of a clinical population.More publicly accessible datasets with manual labels are required for automatic hippocampal segmentations to be accurate and reliable, particularly for clinical populations.Practitioner PointsAlthough deep learning based automatic hippocampal segmentation methods offer faster processing times—a requirement for translation to clinical practice—the lack of variance within training sets (such as sample demographics and scanner sequences) currently prevents transfer of learning to novel data, such as those acquired clinically.More training data with varying demographics, scanner sequences and pathologies are required to adequately train deep learning methods to quickly, accurately and reliably segment the hippocampus for use in clinical practice.
Pilot Study of Large Language Models as an Age-Appropriate Explanatory Tool for Chronic Pediatric Conditions
Authors: Young Cameron C. , Enichen Elizabeth , Rao Arya , Hilker Sidney , Butler Alex , Laird-Gion Jessica , Succi Marc D. 
Published: August 2024

AbstractThere exists a gap in existing patient education resources for children with chronic conditions. This pilot study assesses large language models’ (LLMs) capacity to deliver developmentally appropriate explanations of chronic conditions to pediatric patients. Two commonly used LLMs generated responses that accurately, appropriately, and effectively communicate complex medical information, making them a potentially valuable tool for enhancing patient understanding and engagement in clinical settings.