bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fluctuation-Driven Morphological Patterning: A Novel Approach to Morphogenesis
Authors: Agam Oded , Braun Erez 
Published: May 2024

AbstractRecent experimental investigations intoHydraregeneration revealed a remarkable phenomenon: the morphological transformation of a tissue fragment from the incipient spherical configuration to a tube-like structure - the hallmark of a matureHydra- has the dynamical characteristics of a first-order phase-transition, with calcium field fluctuations within the tissue playing an essential role. This morphological transition was shown to be generated by activation over an energy barrier within an effective potential that underlies morphogenesis. Inspired by this intriguing insight, we propose a novel mechanism where stochastic fluctuations drive the emergence of morphological patterns. Thus, the inherent fluctuations determine the nature of the dynamics and are not incidental noise in the background of the otherwise deterministic dynamics. Instead, they play an important role as a driving force that defines the attributes of the pattern formation dynamics and the nature of the transition itself. Here, we present a simple model that captures the essence of this novel mechanism for morphological pattern formation. Specifically, we consider a one-dimensional tissue arranged as a closed contour embedded in a two-dimensional space, where the local curvature of the contour is coupled to a non-negative scalar field. An effective temperature parameter regulates the strength of the fluctuations in the system. The tissue exhibits fluctuations near a circular shape at sufficiently low coupling strengths, but as the coupling strength exceeds some critical value, the circular state becomes unstable. The nature of the transition to the new state, namely whether it is a first-order-like or a second-order-like transition, depends on the temperature and the effective cutoff on the wavelength of the spatial variations in the system. It is also found that entropic barriers separate the various metastable states of the system.
scDAPP: a comprehensive single-cell transcriptomics analysis pipeline optimized for cross-group comparison
Authors: Ferrena Alexander , Zheng Xiang Yu , Jackson Kevyn , Hoang Bang , Morrow Bernice , Zheng Deyou 
Published: May 2024

AbstractSingle-cell transcriptomics profiling has increasingly been used to evaluate cross-group differences in cell population and cell-type gene expression. This often leads to large datasets with complex experimental designs that need advanced comparative analysis. Concurrently, bioinformatics software and analytic approaches also become more diverse and constantly undergo improvement. Thus, there is an increased need for automated and standardized data processing and analysis pipelines, which should be efficient and flexible too. To address these, we develop thesingle-cellDifferentialAnalysis andProcessingPipeline (scDAPP), a R-based workflow for comparative analysis of single cell (or nucleus) transcriptomic data between two or more groups and at the levels of single cells or “pseudobulking” samples. The pipeline automates many steps of pre-processing using data-learnt parameters, uses previously benchmarked software, and generates comprehensive intermediate data and final results that are valuable for both beginners and experts of scRNA-seq analysis. Moreover, the analytic reports, augmented by extensive data visualization, increase the transparency of computational analysis and parameter choices, while facilitate users to go seamlessly from raw data to biological interpretation.Availability and ImplementationscDAPP is freely available for non-commercial usage as an R package under the MIT license. Source code, documentation and sample data are available at the GitHub (https://github.com/bioinfoDZ/scDAPP).
Geometrically-engineered organoid units and their assembly for pre-construction of organ structures
Authors: Kadotani Ayaka , Hayase Gen , Yoshino Daisuke 
Published: May 2024

AbstractRegenerative medicine is moving from the nascent to the transitional stage as researchers are actively engaged in creating mini-organs from pluripotent stem cells to construct artificial models of physiological and pathological conditions. Currently, mini-organs can express higher-order functions, but their size is limited to the order of a few millimeters. Therefore, one of the ultimate goals of regenerative medicine, “organ replication and transplantation with organoid,” remains a major obstacle. 3D bioprinting technology is expected to be an innovative breakthrough in this field, but various issues have been raised, such as cell damage, versatility of bioink, and printing time. In this study, we established a method for fabricating, connecting, and assembling organoid units of various shapes independent of cell type, extracellular matrix, and adhesive composition (unit construction method). We also fabricated kidney tissue-like structures using three types of parenchymal and interstitial cells that compose the human kidney and obtained findings suggesting the possibility of crosstalk between the units. We anticipate that this technique will bring us closer to the realization of highly efficient and rapid fabrication of full-scale organoids that can withstand organ transplantation.
Impact Of Learned Helplessness On Cognitive Performance And Resting-State Connectivity: An fMRI Study
Authors: Lechat Pierre , Alonso-Ortiz Eva , Bassetto Jean-Samuel 
Published: May 2024

1.1AbstractLearned helplessness (LH) is the phenomenon of resignation in the face of a problematic situation and is caused by the feeling of lacking control in a situation due to internal or external factors. This means that an individual does not seek to resolve the situation they are confronted with and consciously or unconsciously chooses to be passive. The Dorsal Raphe Nucleus (DRN) core could be at the root of the persistent action of the LH phenomenon and influences regions such as the striatum and amygdala. It is thought that the LH phenomenon could affect self-perception and it has been shown that the default mode network (DMN) is often associated with self-reflection during the resting state (RS) phase. It is therefore possible that LH influences both self-perception and the DMN. Based on previous studies, we investigated how LH affects participants. We used functional MRI (fMRI) to test this hypothesis. Participants were divided into two groups, subjected to solvable (control group), and solvable plus unsolvable (LH group) cognitive tasks. We also measured electrodermal signals, OCEAN (Openness, Conscientiousness, Extraversion, Agreeableness, Neuroticism) personality scores, variables related to the anagram resolution, and related these to LH. The study revealed significant differences in the RS contrast between the two groups, with the Posterior Cingulate Cortex (PCC) (an area of the DMN) being more connected to the DRN in the LH group than in the control group, and a portion of the Superior Temporal Gyrus being more connected to the PCC in the control group than in the LH group. These results suggest that LH may have a direct impact on the DMN and could lead to the start of long-term changes.
Automatic Lymph Nodes Segmentation and Histological Status Classification on Computed Tomography Scans Using Convolutional Neural Network
Authors: Shevtsov Alexey , Tominin Iaroslav , Tominin Vladislav , Malevanniy Vsevolod , Esakov Yury , Tukvadze Zurab , Nefedov Andrey , Yablonskii Piotr , Gavrilov Pavel , Kozlov Vadim , Blokhina Mariya , Nalivkina Elena , Gombolevskiy Victor , Vasilev Yuriy , Dugova Mariya , Chernina Valeria , Omelyanskaya Olga , Reshetnikov Roman , Blokhin Ivan , Belyaev Mikhail 
Published: May 2024

AbstractLung cancer is the second most common type of cancer worldwide, making up about 20% of all cancer deaths with less than 10% 5-year survival rate for the very late stage. The recent guidelines for the most common non-small-cell lung cancer (NSCLC) type recommend performing staging based on the 8th edition of TNM classification, where the mediastinal lymph node involvement plays a key role. However, most of the non-invasive methods have a very limited level of sensitivity and are relatively accurate, but invasive methods can be contradicted for some patients. Current advances in Deep Learning show great potential in solving such problems. Still, most of these works focus on the algorithmic side of the problem, not the clinical relevance. Moreover, none of them addressed individual lymph node malignancy classification problem, restricting the indirect analysis of the whole study, and limiting the interpretability of the result without giving an option for cliniciansto validate the result. This work mitigates these gaps, proposing a multi-step algorithm for each visible mediastinal lymph node segmentation and assessing the probability of its involvement in themetastatic process, using the results of histological verification on training. The developed pipelineshows 0.74 ± 0.01 average Recall with 0.53 ± 0.26 object Dice Score for the clinically relevant lymph nodes segmentation task and 0.73 ROC AUC for patient’s N-stage prediction, outperformingtraditional size-based criteria.
Nowhere to Go: A parallel convergent mixed methods study examining the health of people who experience emergency shelter service restrictions
Authors: Bansal Suraj , Pelino Stephanie Di , Pierre Jammy , Chan Kathryn , Lee Amanda , Liu Rachel , Mancini Olivia , Pitkas Avital , Kouyoumdjian Fiona , Lamarche Larkin , Lennox Robin , McIlveen Marcie , O’Shea Timothy , Bodkin Claire 
Published: May 2024

AbstractBackgroundEmergency shelters offer temporary sleeping accommodation to people deprived of housing and connect them to services. Service restriction is the practice of limiting or denying someone access to emergency shelters. This parallel convergent mixed methods study describes the characteristics, healthcare utilization, and morbidity of people experiencing service restrictions in Hamilton, Ontario, and explores the relationship between health and service restriction.MethodsWe recruited 20 people who had experienced service restriction and accessed healthcare from the Shelter Health Network clinic. We conducted semi-structured interviews and performed reflexive thematic analysis. We reviewed participants’ medical records from January 1, 2018 to December 31, 2021 to calculate simple descriptive statistics. Mixing our qualitative and quantitative results, we generated narrative metainferences. We employed community-based research principles, including a research team with lived and living experiences of being service restricted, implementing service restrictions, or providing care to people experiencing service restrictions.ResultsWe generated six themes: 1) Losing your home shouldn’t mean losing your humanity, 2) Where am I supposed to go?, 3) The snakes and ladders of service restrictions, 4) Abandoned to survive, 5) Constantly criminalized, 6) Harnessing the wisdom of community. Participants averaged 17.4 primary care visits, 11 emergency department visits, and 4 hospital admissions over 4 years. The most common reasons for visit were infections, traumatic injuries, and substance use-related concerns. Narrative metainferences highlighted how people experience dehumanization when accessing shelters or healthcare; how service restrictions and encampment living contribute to infections; the lack of practical supports for people using substances in shelters; the ubiquitous criminalization of people experiencing homelessness; and the care people practice for one another to reduce substance-related harms.ConclusionsParticipants’ high healthcare need and utilization was shaped by criminalization, stigma, societal abandonment, and abstinence-based substance use policies. Participants practiced care for themselves and others to navigate these barriers. Shelters should have a transparent service restriction process and employ harm reduction practices. Healthcare should provide affirming and accessible treatment for common conditions. Social and health services must contend with broader social forces while building on the strengths of people with lived experience to improve the health of people who are service restricted.
Risk prediction tools for pressure injury occurrence: An umbrella review of systematic reviews reporting model development and validation methods
Authors: Hillier Bethany , Scandrett Katie , Coombe April , Hernandez-Boussard Tina , Steyerberg Ewout , Takwoingi Yemisi , Velickovic Vladica , Dinnes Jacqueline 
Published: May 2024

ABSTRACTBackgroundPressure injuries (PIs) place a substantial burden on healthcare systems worldwide. Risk stratification of those who are at risk of developing PIs allows preventive interventions to be focused on patients who are at the highest risk. The considerable number of risk assessment scales and prediction models available underscore the need for a thorough evaluation of their development, validation and clinical utility.Our objectives were to identify and describe available risk prediction tools for PI occurrence, their content and development and validation methods used.MethodsThe umbrella review was conducted according to Cochrane guidance. MEDLINE, Embase, CINAHL, EPISTEMONIKOS, Google Scholar and reference lists were searched to identify relevant systematic reviews. Risk of bias was assessed using adapted AMSTAR-2 criteria. Results were described narratively. All included reviews contributed to build a comprehensive list of risk prediction tools.ResultsWe identified 32 eligible systematic reviews only seven of which described the development and validation of risk prediction tools for PI. Nineteen reviews assessed the prognostic accuracy of the tools and 11 assessed clinical effectiveness. Of the seven reviews reporting model development and validation, six included only machine learning models. Two reviews included external validations of models, although only one review reported any details on external validation methods or results. This was also the only review to report measures of both discrimination and calibration. Five reviews presented measures of discrimination, such as area under the curve (AUC), sensitivities, specificities, F1 scores and G-means. For the four reviews that assessed risk of bias assessment using the PROBAST tool, all models but one were found to be at high or unclear risk of bias.ConclusionsAvailable tools do not meet current standards for the development or reporting of risk prediction models. The majority of tools have not been externally validated. Standardised and rigorous approaches to risk prediction model development and validation are needed.RegistrationThe protocol was registered on the Open Science Framework (https://osf.io/tepyk).
Vertebral and Carotid Artery Stenosis after Irradiation Both Raise Ischemic Stroke Risk in Head and Neck Cancer Patients
Authors: Jiang Jian-Lin , Chang Joseph Tung-Chieh , Huang Bing-Shen , Chang Ting-Yu , Sung Pi-Shan , Wei Yi-Chia , Lin Chien-Yu , Yeh Chih-Hua , Fan Kang-Hsing , Liu Chi-Hung 
Published: May 2024

AbstractPurposeTo study the risk of ischemic stroke (IS) following carotid (CAS) or vertebral artery stenosis (VAS) in head and neck cancer (HNC) patients after radiation therapy (RT).MethodsWe included HNC patients who received RT between 2010 and 2023. They underwent regular head and neck imaging monitoring to evaluate cancer recurrence at the department of radiation-oncology and vascular examinations at the department of neurology. Patients were initially divided into nasopharyngeal carcinoma (NPC) and non-NPC groups. The primary outcome was the occurrence of IS after RT, and the secondary outcomes included the development of >50% CAS or >50% VAS after RT. Cox regression and Kaplan–Meier analyses were conducted to compare the outcomes of the study groups. Further analysis was conducted based on the presence or absence of >50% CAS or >50% VAS during the follow-up period.ResultsOf the 1,423 HNC patients, 19%, 6.8%, and 2.3% developed >50% CAS, >50% VAS, and IS during a 58-month follow-up. Compared with the NPC group, the non-NPC group exhibited a higher incidence of >50% CAS (25.4% vs. 10.7%, p<0.001) and >50% VAS (8.8% vs. 4.3%, p<0.001), but similar risks of IS. In patients with HNC, >50% CAS (adjusted hazard ratio [HR]=3.21, 95% confidence interval [CI]=1.53-6.71), and >50% VAS (adjusted HR=2.89, 95% CI=1.28-6.53) were both the independent predictors of IS. In the patients with NPC, >50% CAS was an independent predictor of anterior circulation IS (adjusted HR=4.39, 95% CI=1.17-16.47). By contrast, >50% VAS emerged as a predictor of posterior circulation IS in both the NPC (adjusted HR=15.02, 95% CI=3.76-60.06) and non-NPC groups (adjusted HR=13.59, 95% CI=2.21-83.46).ConclusionHNC patients with >50% CAS or >50% VAS after RT had an increased risk of IS within their corresponding vascular territory. CAS is a major predictor of IS in NPC patients, whereas VAS is a major predictor of IS in both NPC and non-NPC patients.
Statin Initiation and early stroke recurrence in the POINT Trial Population
Authors: Azizi Elham , Prabhakaran Shyam , Brorson James R. 
Published: May 2024

AbstractBackground and PurposeBenefits of statin therapy in reducing the long-term risk of ischemic stroke are well-established, but the immediate effects of statin therapy on early stroke recurrence after an initial ischemic event are less clear.MethodsIn this secondary analysis of POINT data, we evaluated the effects of statins on early stroke recurrence (within 7 days) and recurrence over 90 days. We also examined the effect of early statin initiation in the subgroup of subjects not on statins prior to the index event using logistic and proportional hazards models.ResultsIn the POINT trial, 175 of 267 (65.5%) of ischemic stroke recurrences were early (within 7 days). Baseline statin treatment at the time of study entry was marginally associated with a decrease in the odds of early ischemic stroke recurrence in adjusted logistical regression analysis (OR 0.70, 95% CI 0.50-0.99, p=0.04), but with a non-significant effect in adjusted Cox proportional hazard analysis (HR=0.72, 95% CI 0.52–1.01, p=0.05). In the subset of subjects not taking statin medications at baseline, initiation of statin treatment had no significant effect on the rate of early stroke recurrence (adjusted HR 0.80, 95% CI 0.54–1.20, p=0.22).ConclusionIn the POINT trial population, prior treatment with statin was weakly associated with decreased risk of early recurrence of stroke. However initiating statin treatment had no detectable effect in reducing risk of early stroke recurrence. The POINT trial provides no evidence for an immediate protective effect of statins against stroke recurrence.
A description of Lineage 1Mycobacterium tuberculosisfrom Papua, Indonesia
Authors: Djunaedy Hanif A. K. , Febinia Clarissa A. , Hamers Raph L. , Baird Kevin , Elyazar Iqbal , Thuong Nguyen Thuy Thuong , Trimarsanto Hidayat , Malik Safarina G. , Thwaites Guy , van Crevel Reinout , Alisjahbana Bachti , Chaidir Lidya , Ashton Philip M. 
Published: May 2024

AbstractIndonesia has the third highest number of tuberculosis (TB) patients infected with Mycobacterium tuberculosis (MTB) Lineage 1 (L1). Most of these MTB L1 cases can be found in Indonesia’s remote easternmost province of Papua, one of Indonesia’s most underdeveloped provinces with a particularly high burden for TB. In this study, we sequenced and described 42MTBL1 isolates from a well-characterized cohort of patients. We found a genetically diverseMTBL1 population with no association between pathogen genetic relatedness and place of residence or pathogen genetic relatedness and patient ethnicity, which could reflect mixing between different locales and ethnicities or our low sampling fraction. Only a small number showed genetic variants associated with drug resistance (5/42, 11.9%), probably due to a lack of effective treatment programs. The Papuan isolates showed similarities to other Island Southeast Asian Countries due to the high proportion of L1.2.1.2.1 (30/42, 71.4%), especially East Timor and the Philippines. This study fills a research gap of MTB L1 in Indonesian Papua and should serve as a stepping stone for further research in the region.
Resting state brain network segregation is associated with walking speed and working memory in older adults
Authors: Sato Sumire D. , Shah Valay A. , Fettrow Tyler , Hall Kristina G. , Tays Grant D. , Cenko Erta , Roy Arkaprava , Clark David J. , Ferris Daniel P. , Hass Chris J. , Manini Todd M. , Seidler Rachael D. 
Published: May 2024

ABSTRACTOlder adults exhibit larger individual differences in walking ability and cognitive function than young adults. Characterizing intrinsic brain connectivity differences in older adults across a wide walking performance spectrum may provide insight into the mechanisms of functional decline in some older adults and resilience in others. Thus, the objectives of this study were to: (1) determine whether young adults and high– and low-functioning older adults show group differences in brain network segregation, and (2) determine whether network segregation is associated with working memory and walking function in these groups. The analysis included 21 young adults and 81 older adults. Older adults were further categorized according to their physical function using a standardized assessment; 54 older adults had low physical function while 27 were considered high functioning. Structural and functional resting state magnetic resonance images were collected using a Siemens Prisma 3T scanner. Working memory was assessed with the NIH Toolbox list sorting test. Walking speed was assessed with a 400 m-walk test at participants’ self-selected speed. We found that network segregation in mobility-related networks (sensorimotor, vestibular) was higher in older adults with higher physical function compared to older adults with lower physical function. There were no group differences in laterality effects on network segregation. We found multivariate associations between working memory and walking speed with network segregation scores. The interaction of left sensorimotor network segregation and age groups was associated with higher working memory function. Higher left sensorimotor, left vestibular, right anterior cingulate cortex, and interaction of left anterior cingulate cortex network segregation and age groups were associated with faster walking speed. These results are unique and significant because they demonstrate higher network segregation is largely related to higher physical function and not age alone.HighlightsOlder adults with high and low physical function have network segregation differences.Network segregation for high-functioning older adults was more similar to that of young adults.Laterality of functional network segregation is not different between age groups.Higher network segregation is associated with faster walking speed.