bluuebunny/crossref_metadata_2025_split huggingface dataset:
Management of Intraductal Papilloma Using Vacuum Assisted Breast Surgery (VABB/VAE):- A Single Institute Study
Authors: Khandelwal Rohan , Sharma Pooja , Desai Dev , Mohanty Sambit 
Published: January 2024

AbstractIntraductal Papilloma has a higher upgradation rate despite being a benign tumor and warrants an immediate excision. Surgical removal is the gold standard but carries poor cosmetic results and requires general anesthesia. Ultrasound-guided Vacuum Assisted Excision (US-VAE) was used to treat 47 patients after due ethical permissions. 32 patients went US-VAE under local anesthesia and all patients were happy with the cosmetic outcome. The excision was done as a daycare procedure in all patients except indicated by the Anesthetist. Requirements of post-procedure analgesia were also minimal and only 3 patients required prolonged analgesia. The advantages of VABB-guided surgery are faster recovery, scarless procedure, and local anesthesia, thus making it an ideal OPD and daycare procedure for Intraductal Papilloma Excision.IntroductionIntraductal papilloma, although benign, has a high upgradation rate to malignant breast cancer. Surgical excision is necessary, but the rate of complications is high. Ultrasound-guided vacuum-assisted excision (US-VAE) is a new technique derived from the VABB biopsy method that can give better cosmetic results as well as fewer surgical complications.ObjectivesUnderstanding the utility of US-VAE in the diagnosis and treatment of intraductal papillomas of the breast.MethodologyWith permission from the Ethics Board and consent of the patients, records of 47 patients were recruited to undergo the US-VAE procedure. USG was used to stage the tumor with Mammography and CNB as needed and patients with single duct or adjacent duct lesions were included while the rest, including patients with malignant changes, were excluded. The Bard VABB biopsy machine and the 7G probe were used by highly trained breast surgeons to perform the procedure.ResultsOf the 47 patients included, 32 patients under local anesthesia were operated while others were under general anesthesia according to the preference of the patient and the level of apprehension. The patients received oral paracetamol as the only painkiller for 5 days. Only 3 patients required prolonged analgesics. 7 patients had prolonged bruising (lasting more than one week), which was the most common complication. All patients (100%) were happy with the cosmetic result after the procedure.ConclusionsThe advantages of VABB-guided surgery are faster recovery, scarless procedure, and the ability to perform the surgery under local anesthesia, making it an OPD and daycare procedure.
Bayesian evidence for the neural dissociation between finger and hand imitation skills
Authors: Rosenzopf Hannah , Röhrig Lisa , Goldenberg Georg , Karnath Hans-Otto 
Published: January 2024

AbstractIntroductionFor limb apraxia ‒ a heterogeneous disorder of higher motor cognition following stroke ‒ an enduring debate has arisen regarding the existence of dissociating neural correlates for finger and hand gestures in the left hemisphere. We re-assessed this question asking whether previous attempts analysing pooled samples of patients with deficits in only one and patients with deficits in both imitation types might have led to systematically biased results.MethodsWe conducted frequentist and Bayesian, voxelwise and regionwise lesion symptom mappings on a pooled sample (N=96) and subsamples containing only shared and only isolated hand and finger imitation deficits and respective controls.ResultsAnatomical analyses on the isolated sample reinforced a cortical dissociation of finger deficits (located more anteriorly) and hand deficits (located more posteriorly). The presence of patients with shared deficits did indeed dilute associations that appeared stronger in the respective isolated samples. Also, brain regions truly associated with hand imitation deficits showed a positive bias for finger imitation deficits, when the sample contained patients with shared deficits. In addition, our frequentist parameters uncovered that some of our Bayesian evidence supported reverse associations (damage protecting from rather than increasing the deficit).DiscussionJoint analyses of patients with shared and isolated imitation deficits do indeed lead to biases, which may explain why some previous studies have failed to detect the actual neural dissociation between hand and finger imitation deficits.
The inherent fragility of collective proliferative control
Authors: Caldwell Michael G. , Lander Arthur D. 
Published: January 2024

ABSTRACTTissues achieve and maintain their sizes through active feedback, whereby cells collectively regulate proliferation and differentiation so as to facilitate homeostasis and the ability to respond to disturbances. One of the best understood feedback mechanisms—renewal control—achieves remarkable feats of robustness in determining and maintaining desired sizes. Yet in a variety of biologically relevant situations, we show that stochastic effects should cause rare but catastrophic failures of renewal control. We define the circumstances under which this occurs and raise the possibility such events account for important non-genetic steps in the development of cancer. We further suggest that the spontaneous stochastic reversal of these events could explain cases of cancer normalization or dormancy following treatment. Indeed, we show that the kinetics of post-treatment recurrence for many cancers are often better fit by a model of stochastic re-emergence due to loss of collective proliferative control, than by deterministic models of cancer relapse.
Transport Cocktails for Cancer Therapeutics
Authors: Kavousanakis Michail E. , Bhatavdekar Omkar , Bastiaannet Remco , Kevrekidis Yannis , Sofou Stavroula 
Published: January 2024

AbstractBeyond biological cell heterogeneity, evidenced by different resistances to therapeutics, “delivery heterogeneity” crucially limits treatment efficacy for advanced solid tumors: variations in therapeutic drug delivery to different tumor areas (perivascular, perinecrotic) leading to nonuniform drug concentrations/doses and to unsuccessful treatment (cancer cell kill). Short-range (40-80 µm), high energy (1-5 MeV) alpha-particles successfully address the biological heterogeneity: the double-strand DNA breaks they cause make them impervious to cell resistance mechanisms. Multiresponsive nanocarriers and/or engineered antibody-drug-conjugates are elegant approaches to delivering such alpha-particle emitters. Delivery heterogeneity, however, remains a challenge in established (i.e. large, vascularized) tumors. Remarkably, delivery properties enabling efficacy at the cell scale (targeting selectivity, affinity, cell drug uptake) may act against spatial delivery uniformity at the tumor scale (binding-site barrier effect1). We have previously demonstrated, in different mouse models, that spatial delivery uniformity, key to the effective killing of solid tumors, can be achieved utilizing combinations of different, distinct delivery carriers of the same emitter, but with different, complementary delivery properties, “leaving no cancer cell behind”. We build first principles reaction-transport models (quantitatively informed by experiments) that explain the “geographically complementary” behaviors of such carrier cocktails, and help optimally design these cocktails and their delivery protocols.
Exploring phenotypic diversity: a comparative analysis of cichlid convergence
Authors: Leal-Cardín Mariana , Bracamonte Seraina E. , Aldegunde Javier , Hudson Alan , Magalhaes Isabel S. , Ornelas-García Claudia Patricia , Barluenga Marta 
Published: January 2024

AbstractConvergent evolution of similar phenotypes suggests some predictability in the evolutionary trajectories of organisms, due to strong and repeated selective pressures, and/or developmental constraints. In adaptive radiations, particularly in cichlid fish radiations, convergent phenotypes are commonly found within and across geographical settings. There are some main axes of cichlid morphological diversification. Recurrent changes in body patterns reveal adaption to alternative habitats, and modifications of the trophic apparatus respond to the exploitation of different food resources. Here we compare two Neotropical cichlid assemblages, the Mexican desert cichlid, and the Nicaraguan Midas cichlid, with similar polymorphic body and trophic apparatus patterns despite their independent evolution and evaluate morphological and gene expression convergence and divergence. We found a single morphological axis of differentiation in pharyngeal jaws with equivalent papilliform and molariform morphotypes in both cichlid radiations. In contrast, we found two different axes of differentiation in the shape of the body, defining two alternative limnetic body patterns. Genetic differences between morphotypes seem to be specific to each radiation, with no clear patterns of convergence.
Brain-phenotype predictions can survive across diverse real-world data
Authors: Adkinson Brendan D. , Rosenblatt Matthew , Dadashkarimi Javid , Tejavibulya Link , Jiang Rongtao , Noble Stephanie , Scheinost Dustin 
Published: January 2024

ABSTRACTRecent work suggests that machine learning models predicting psychiatric treatment outcomes based on clinical data may fail when applied to unharmonized samples. Neuroimaging predictive models offer the opportunity to incorporate neurobiological information, which may be more robust to dataset shifts. Yet, among the minority of neuroimaging studies that undertake any form of external validation, there is a notable lack of attention to generalization across dataset-specific idiosyncrasies. Research settings, by design, remove the between-site variations that real-world and, eventually, clinical applications demand. Here, we rigorously test the ability of a range of predictive models to generalize across three diverse, unharmonized samples: the Philadelphia Neurodevelopmental Cohort (n=1291), the Healthy Brain Network (n=1110), and the Human Connectome Project in Development (n=428). These datasets have high inter-dataset heterogeneity, encompassing substantial variations in age distribution, sex, racial and ethnic minority representation, recruitment geography, clinical symptom burdens, fMRI tasks, sequences, and behavioral measures. We demonstrate that reproducible and generalizable brain-behavior associations can be realized across diverse dataset features with sample sizes in the hundreds. Results indicate the potential of functional connectivity-based predictive models to be robust despite substantial inter-dataset variability. Notably, for the HCPD and HBN datasets, the best predictions were not from training and testing in the same dataset (i.e., cross-validation) but across datasets. This result suggests that training on diverse data may improve prediction in specific cases. Overall, this work provides a critical foundation for future work evaluating the generalizability of neuroimaging predictive models in real-world scenarios and clinical settings.
Systemic SARS-CoV-2-specific antibody responses to infection and to COVID-19 and BCG vaccination
Authors: Claus Juana , ten Doesschate Thijs , Taks Esther , Debisarun Priya , Smits Gaby , van Binnendijk Rob , van der Klis Fiona , Verhagen Lilly M. , de Jonge Marien I. , Bonten Marc J.M. , Netea Mihai G. , van de Wijgert Janneke H. H. M. 
Published: January 2024

SummarySARS-CoV-2 infections elicit antibodies against the viral spike (S) and nucleocapsid (N) proteins; COVID-19 vaccines against the S-protein only. The BCG-Corona trial, initiated in March 2020 in SARS-CoV-2-naïve Dutch healthcare workers, captured several epidemic peaks and the introduction of COVID-19 vaccines during the one-year follow-up. We assessed determinants of systemic anti-S1 and anti-N immunoglobulin type G (IgG) responses using trial data. Participants were randomized to BCG or placebo vaccination, reported daily symptoms, SARS-CoV-2 test results, and COVID-19 vaccinations, and donated blood for SARS-CoV-2 serology at two time points. In the 970 participants, anti-S1 geometric mean antibody concentrations (GMCs) were much higher than anti-N GMCs. Anti-S1 GMCs significantly increased with increasing number of immune events (SARS-CoV-2 infection or COVID-19 vaccination): 104.7 international units (IU)/ml, 955.0 IU/ml, and 2290.9 IU/ml for one, two, and three immune events, respectively (p<0.001). In adjusted multivariable linear regression models, anti-S1 and anti-N log10concentrations were significantly associated with infection severity, and anti-S1 log10concentration with COVID-19 vaccine type/dose. In univariable models, anti-N log10concentration was also significantly associated with acute infection duration, and severity and duration of individual symptoms. Antibody concentrations were not associated with Long COVID or long-term loss of smell/taste.
Highly comparative time series analysis of oxygen saturation and heart rate to predict respiratory outcomes in extremely preterm infants
Authors: Qiu Jiaxing , Di Fiore Juliann M. , Krishnamurthi Narayanan , Indic Premananda , Carroll John L. , Claure Nelson , Kemp James S. , Dennery Phyllis A. , Ambalavanan Namasivayam , Weese-Mayer Debra E. , Hibbs Anna Maria , Martin Richard J. , Bancalari Eduardo , Hamvas Aaron , Moorman J. Randall , Lake Douglas E. 
Published: January 2024

AbstractObjectiveHighly comparative time series analysis (HCTSA) is a novel approach involving massive feature extraction using publicly available code from many disciplines. The Prematurity-Related Ventilatory Control (Pre-Vent) observational multicenter prospective study collected bedside monitor data from>700 extremely preterm infants to identify physiologic features that predict respiratory outcomes. We calculated a subset of 33 HCTSA features on>7M10-minute windows of oxygen saturation (SPO2) and heart rate (HR) from the Pre-Vent cohort to quantify predictive performance. This subset included representatives previously identified using unsupervised clustering on>3500 HCTSA algorithms. Performance of each feature was measured by individual area under the receiver operating curve (AUC) at various days of life and binary respiratory outcomes. These were compared to optimal PreVent physiologic predictor IH90 DPE, the duration per event of intermittent hypoxemia events with threshold of 90%.Main ResultsThe top HCTSA features were from a cluster of algorithms associated with the autocorrelation of SPO2 time series and identified low frequency patterns of desaturation as high risk. These features had comparable performance to and were highly correlated with IH90 DPE but perhaps measure the physiologic status of an infant in a more robust way that warrants further investigation. The top HR HCTSA features were symbolic transformation measures that had previously been identified as strong predictors of neonatal mortality. HR metrics were only important predictors at early days of life which was likely due to the larger proportion of infants whose outcome was death by any cause. A simple HCTSA model using 3 top features outperformed IH90 DPE at day of life 7 (.778 versus .729) but was essentially equivalent at day of life 28 (.849 versus .850). These results validated the utility of a representative HCTSA approach but also provides additional evidence supporting IH90 DPE as an optimal predictor of respiratory outcomes.
Evaluating the Potential of Large Language Models for Vestibular Rehabilitation Education: A Comparison of ChatGPT, Google Gemini, and Clinicians
Authors: Arbel Yael , Gimmon Yoav , Shmueli Liora 
Published: January 2024

AbstractObjectiveWe aimed to evaluate the performance of two publicly available large language models, ChatGPT and Google Gemini in response to multiple-choice questions related to vestibular rehabilitation.MethodsThe study was conducted among 30 physical therapist professionals experienced with VR (vestibular rehabilitation) and 30 physical therapy students. They were asked to complete a Vestibular Knowledge Test (VKT) consisting of 20 multiple-choice questions that were divided into three categories: (1) Clinical Knowledge, (2) Basic Clinical Practice, and (3) Clinical Reasoning. ChatGPT and Google Gemini were tasked with answering the same 20 VKT questions. Three board-certified otoneurologists independently evaluated the accuracy of each response using a 4-level scale, ranging from comprehensive to completely incorrect.ResultsChatGPT outperformed Google Gemini with a 70% score on the VKT test, while Gemini scored 60%. Both excelled in Clinical Knowledge with a perfect score of 100% but struggled in Clinical Reasoning with ChatGPT scoring 50% and Gemini scoring 25%. According to three otoneurologic experts, ChatGPT’s accuracy was considered comprehensive in 45% of the 20 questions, while 25% were found to be completely incorrect. ChatGPT provided comprehensive responses in 50% of Clinical Knowledge and Basic Clinical Practice questions, but only 25% in Clinical Reasoning.ConclusionCaution is advised when using ChatGPT and Google Gemini due to their limited accuracy in clinical reasoning. While they provide accurate responses concerning Clinical Knowledge, their reliance on web information may lead to inconsistencies. ChatGPT performed better than Gemini. Healthcare professionals should carefully formulate questions and be aware of the potential influence of the online prevalence of information on ChatGPT’s and Google Gemini’s responses. Combining clinical expertise and clinical guidelines with ChatGPT and Google Gemini can maximize benefits while mitigating limitations.Impact StatementThis study highlights the potential utility of large language models like ChatGPT in supplementing clinical knowledge for physical therapists, while underscoring the need for caution in domains requiring complex clinical reasoning. The findings emphasize the importance of integrating technological tools carefully with human expertise to enhance patient care and rehabilitation outcomes.
Neutrophil extracellular traps linked to idiopathic pulmonary fibrosis severity and survival
Authors: Matson Scott M. , Ngo Linh T. , Sugawara Yui , Fernando Veani , Lugo Claudia , Azeem Imaan , Harrison Alexis , Alsup Alex , Nissen Emily , Koestler Devin , Washburn Michael P. , Rekowski Michaella J. , Wolters Paul J. , Lee Joyce S. , Solomon Joshua J. , Demoruelle M. Kristen 
Published: January 2024

AbstractBackgroundIdiopathic pulmonary fibrosis (IPF) leads to progressive loss of lung function and mortality. Understanding mechanisms and markers of lung injury in IPF is paramount to improving outcomes for these patients. Despite the lack of systemic involvement in IPF, many analyses focus on identifyingcirculatingprognostic markers. Using a proteomic discovery method followed by ELISA validation in multiple IPF lung compartments and cohorts we explored novel markers of IPF survival.MethodsIn our discovery analysis, agnostic label-free quantitative proteomics differentiated lung tissue protein expression based on survival trajectory (n=10). Following selection of the candidate pathway (neutrophil extracellular trap (NET) formation), we subsequently validated the presence of NETs in the IPF lung microenvironment using fully quantitative assays of known NET remnants in separate IPF cohorts (n=156 and n=52) with bronchoalveolar lavage fluid. We then assessed the correlation of these markers with baseline pulmonary function and survival.ResultsDiscovery lung tissue proteomics identified NET formation as significantly associated with poor IPF survival. Using fully quantitative confirmatory tests for reproducibility we confirmed the presence of NET markers in IPF BALF and found significant correlations with worse pulmonary function in both cohorts (p<0.03 and p = 0.04 respectively). In the survival cohort, higher levels of NET markers predicted worse survival after adjusting for gender, age, and baseline physiologic severity (hazard ratio range: 1.79–2.19).ConclusionsNET markers were associated with disease severity and worse survival in IPF. These findings suggest NET formation contributes to lung injury and decreased survival in IPF and may represent a potential therapeutic target.
Enhancing Chemotherapy Response Prediction via Matched Colorectal Tumor-Organoid Gene Expression Analysis and Network-Based Biomarker Selection
Authors: Zhang Wei , Wu Chao , Huang Hanchen , Bleu Paulina , Zambare Wini , Alvarez Janet , Wang Lily , Paty Philip B. , Romesser Paul B. , Smith J. Joshua , Chen X. Steven 
Published: January 2024

AbstractColorectal cancer (CRC) poses significant challenges in chemotherapy response prediction due to its molecular heterogeneity. This study introduces an innovative methodology that leverages gene expression data generated from matched colorectal tumor and organoid samples to enhance prediction accuracy. By applying Consensus Weighted Gene Co-expression Network Analysis (WGCNA) across multiple datasets, we identify critical gene modules and hub genes that correlate with patient responses, particularly to 5-fluorouracil (5-FU). This integrative approach advances precision medicine by refining chemotherapy regimen selection based on individual tumor profiles. Our predictive model demonstrates superior accuracy over traditional methods on independent datasets, illustrating significant potential in addressing the complexities of high-dimensional genomic data for cancer biomarker research.
Growth characterization and biostimulant potential ofCoelastrellasp. D14 a green microalga isolated from a solar panel
Authors: Baldanta Sara , Ferreira Alice , Gouveia Luisa , Navarro Llorens Juana Maria , Guevara Govinda 
Published: January 2024

AbstractExtremophile environments are an important source for finding microorganisms with a potential for biotechnological applications. Among these microorganisms, microalgae contribute to several sustainable processes such as wastewater treatments or nutrition. In this work it was characterized a microalga isolated from a solar panel. The morphological and phylogenetic analysis revealed that the isolate collected was aCoelastrellastrain. Cultivation and stress experiments has shown thatCoelastrella sp.D14 can resist a long period of desiccation and it can grow on cheap sources such as piggery wastewaters (PWW). This work reports that aCoelastrellastrain displays biostimulant properties with a germination index of 123% onLepidium sativumwhen D14 biomass grown at 10% piggery effluent was used. Altogether, these results suggest that this novel strain could be a good chassis for further biotechnological applications.HighlightsCoelastrellasp. D14, a xero-tolerant strain, has been isolated from a solar panelThis strain can grow on piggery wastewaterCoelastrellasp. D14 can promote germination ofLepidium sativum