bluuebunny/crossref_metadata_2025_split huggingface dataset:
Gene regulatory network topology governs resistance and treatment escape in glioma stem-like cells
Authors: Park James H. , Hothi Parvinder , Garcia de Lomana Adrian Lopez , Pan Min , Calder Rachel , Turkarslan Serdar , Wu Wei-Ju , Lee Hwahyung , Patel Anoop P. , Cobbs Charles , Huang Sui , Baliga Nitin S. 
Published: February 2024

ABSTRACTPoor prognosis and drug resistance in glioblastoma (GBM) can result from cellular heterogeneity and treatment-induced shifts in phenotypic states of tumor cells, including dedifferentiation into glioma stem-like cells (GSCs). This rare tumorigenic cell subpopulation resists temozolomide, undergoes proneural-to-mesenchymal transition (PMT) to evade therapy, and drives recurrence. Through inference of transcriptional regulatory networks (TRNs) of patient-derived GSCs (PD-GSCs) at single-cell resolution, we demonstrate how the topology of transcription factor interaction networks drives distinct trajectories of cell state transitions in PD-GSCs resistant or susceptible to cytotoxic drug treatment. By experimentally testing predictions based on TRN simulations, we show that drug treatment drives surviving PD-GSCs along a trajectory of intermediate states, exposing vulnerability to potentiated killing by siRNA or a second drug targeting treatment-induced transcriptional programs governing non-genetic cell plasticity. Our findings demonstrate an approach to uncover TRN topology and use it to rationally predict combinatorial treatments that disrupts acquired resistance in GBM.TeaserGene regulatory networks drive glioma stem-like cell drug response and drug-induced cell-state transitions leading to resistance.
Predicting Time to Diabetes Diagnosis Using Random Survival Forests
Authors: Saha Priyonto , Marouf Yacine , Pozzebon Hunter , Guergachi Aziz , Keshavjee Karim , Noaeen Mohammad , Shakeri Zahra 
Published: February 2024

AbstractType 2 Diabetes Mellitus (T2DM) is a chronic metabolic disorder with increasing population incidence. However, T2DM takes years to develop, allowing onset prediction and prevention to be a clinically effective treatment strategy. In this study we propose and assess a novel approach to diabetes prediction which integrates a specialized extension of the random forest algorithm known as random survival forest (RSF). Rather than predicting a binary outcome, this machine learning model incorporates survival analysis methodology to predict the time until a patient will receive a diabetes diagnosis if their current lifestyle is maintained. We trained a baseline model on 7,704 electronic medical records from the Canadian Primary Care Sentinel Surveillance Network (CPCSSN) with 14 biomarker and comorbidity features across different measurement dates. Although tuning parameters were purposefully chosen for quick training rather than for predictive performance, our model exceeded expectations with a concordance index of 0.84. Thus, RSF models have been shown to produce accurate timelines of diabetes onset trajectory, providing patients with quantifiable and relatable risks that are easy to understand. The results of our study have substantial implications for advancing machine learning in clinical decision support and patient outcome predictions, emphasizing the role of innovative models in improving predictive accuracy.
IFNγ induces epithelial reprogramming driving CXCL11-mediated T cell migration
Authors: Cutilli Alessandro , Jansen Suze A. , Paolucci Francesca , Mokry Michal , Mocholi Enric , Lindemans Caroline A. , Coffer Paul J. 
Published: February 2024

AbstractThe cytokine interferon-gamma (IFNγ) plays a multifaceted role in intestinal immune responses ranging from anti-to pro-inflammatory depending on the setting. Here, using a 3D co-culture system based on human intestinal epithelial organoids, we explore the capacity of IFNγ-exposure to reprogram intestinal epithelia and thereby directly modulate lymphocyte responses. IFNγ treatment of organoids led to transcriptional reprogramming, marked by a switch to a pro-inflammatory gene expression profile, including transcriptional upregulation of the chemokines CXCL9, CXCL10, and CXCL11. Proteomic analysis of organoid-conditioned medium post-treatment confirmed chemokine secretion. Furthermore, IFNγ-treatment of organoids led to enhanced T cell migration in a CXCL11-dependent manner without affecting T cell activation status. Taken together, our results suggest a specific role for CXCL11 in T cell recruitment that can be targeted to prevent T cell trafficking to the inflamed intestine.
BayVarC: an ultra-sensitive ctDNA variant caller using Bayesian approach
Authors: Che Dongxue , Yan Cheng , Zha Jianjun , Niu Zexiong , Yang Quanyu , Cheng Xiaolei , Han Mipeng , Du Changshi , Zhang Ke , Hu Yunfu , Yang Yu-Fei 
Published: February 2024

AbstractIn liquid biopsy, it is critical to detect variants of allele frequencies as low as 0.1% or even lower, especially when used to monitor secondary resistant mutations and minimal residual disease. Despite the efforts on improving experimental design, it remains challenging to distinguish low-frequency variants from technical noises in the downstream bioinformatic analysis. Here, we introduce BayVarC, a novel variant caller specifically designed for variant calling in liquid biopsy. It applies Bayesian inference to accurately quantify noise level in a locus-specific manner, enabling the discrimination between technical noise and low-frequency cancer variants. Detailed in-silico simulation and in-vitro experiments demonstrated BayVarC’ superior performance over existing state-of-the-art tools. BayVarC can effectively detect low frequency variants while maintaining low false positive rate (0.05 FP/KB). Meanwhile, it achieves Limit of Detection (LoD) as low as 0.1%. Furthermore, empowered by its architecture, BayVarC shows promising applicability in Minimal Residual Disease (MRD) detection. BayVarC is freely available athttps://github.com/GenetronBioinfomatics/BayVarC.
Altered inflammatory state and mitochondrial function identified by transcriptomics in paediatric congenital heart patients prior to surgical repair
Authors: Bartoli-Leonard Francesca , Harris Amy G. , Saunders Kelly , Madden Julie , Cherrington Carrie , Sheehan Karen , Baquedano Mai , Parolari Giulia , Bamber Andrew , Caputo Massimo 
Published: February 2024

AbstractObjectiveCongenital heart disease (CHD) remains the most common birth defect, with surgical intervention required in complex cases. Right ventricle (RV) function is known to be a major predictor in sustained cardiac health in these patients, thus by elucidating divergent profiles between CHD and control through tissue analysis this study aims to identify new avenues of investigation into the mechanisms surrounding reduced RV function.Approach & ResultsTranscriptomic profiling,in silicocellular deconvolution and functional network analysis was conducted on RV biopsies obtained from CHD and control paedatric patients. Analysis identified an increase in mitochondrial dysfunction genesRPPH1andRMPR(padj = 4.67E-132, 2.23E-107, respectively), Cytotoxic T cell markersCD8a, LAGE3andCD49a(p = 0.0006, p < 0.0001, p = 0.0118, respectively) and proinflammatory markerCaspase1(p=0.0055) in CHD compared to control. Gene set enrichment identified mitochondrial dysfunctional pathways, predominately changes to the oxidative phosphorylation processes. Negative regulation of mitochondrial functions and metabolism was identified in functional network analysis, with dysregulation of mitochondrial complex formation. Histological analysis confirmed an increase in cellular bodies with the CHD RV tissue, and positive staining for both CD45 and CD8 in CHD RV tissue, which was absent in control. Deconvolution of bulk RNAseq data suggests a reduction in CD4+ T cells (p = 0.0067) and an increase in CD8+ T cells (p = 0.0223). Network analysis identified positive regulation of the immune system and cytokine signalling clusters within the inflammation functional network as were lymphocyte activation and leukocyte differentiation.ConclusionsUtilizing RV tissue from paediatric patients undergoing CHD cardiac surgery this study identifies dysfunctional mitochondrial pathways and an increase in inflammatory T cell presence prior to reparative surgery.
The glucocorticoid receptor elicited proliferative response in human erythropoiesis is BCL11A-dependent
Authors: Mazzarini Maria , Cherone Jennifer , Nguyen Truong , Martelli Fabrizio , Varricchio Lilian , Funnell Alister P.W. , Papayannopoulou Thalia , Migliaccio Anna Rita 
Published: February 2024

ABSTRACTPrior evidence indicates that the erythroid cellular response to glucocorticoids (GC) has developmental specificity, namely, that developmentally more advanced cells that are undergoing or have undergone fetal to adult globin switching are more responsive to GC-induced expansion. To investigate the molecular underpinnings of this, we focused on the major developmental globin regulator BCL11A. We compared:a)levels of expression and nuclear content of BCL11A in adult erythroid cells upon GC stimulation;b)response to GC of CD34+ cells from patients withBCL11Amicrodeletions and reducedBCL11Aexpression, and;c)response to GC of two cellular models (HUDEP-2 and adult CD34+ cells) before and after reduction ofBCL11Aexpression by shRNA. We observed that:a)GC-expanded erythroid cells from a large cohort of blood donors displayed amplified expression and nuclear accumulation of BCL11A;b)CD34+ cells fromBCL11Amicrodeletion patients generated fewer erythroid cells when cultured with GC compared to their parents, while the erythroid expansion of the patients was similar to that of their parents in cultures without GC, and;c)adult CD34+ cells and HUDEP-2 cells with shRNA-depleted expression ofBCL11Aexhibit reduced expansion in response to GC. In addition, RNA-seq profiling of shRNA-BCL11A CD34+ cells cultured with and without GC was similar (very few differentially expressed genes), while GC-specific responses (differential expression ofGILZand of numerous additional genes) were observed only in controls cells with unperturbed BCL11A expression. These data indicate that BCL11A is an important participant of certain aspects of the stress pathway sustained by GC.
SMORES: A Simple Microfluidic Operating Room for the Examination and Surgery ofStentor coeruleus
Authors: Zhang Kevin S. , Rodriguez Ramon , Tang Sindy K.Y. 
Published: February 2024

ABSTRACTCiliates are powerful unicellular model organisms that have been used to elucidate fundamental biological processes. However, the high motility of ciliates presents a major challenge in studies using live-cell microscopy and microsurgery. While various immobilization methods have been developed, they are physiologically disruptive to the cell and incompatible with microscopy and/or microsurgery. Here, we describe a Simple Microfluidic Operating Room for the Examination and Surgery ofStentor coeruleus(SMORES). SMORES uses Quake valve-based microfluidics to trap, compress, and perform surgery onStentoras our model ciliate. Compared with previous methods, immobilization by physical compression in SMORES is more effective and uniform. The mean velocity of compressed cells is 24 times less than that of uncompressed cells. The compression is minimally disruptive to the cell and is easily applied or removed using a 3D-printed pressure rig. We demonstrate cell immobilization for up to 2 hours without sacrificing cell viability. SMORES is compatible with confocal microscopy and is capable of media exchange for pharmacokinetic studies. Finally, the modular design of SMORES allows laser ablation or mechanical dissection of a cell into many cell fragments at once. These capabilities are expected to enable biological studies previously impossible in ciliates and other motile species.
TP53mutation screening for patients at risk of myeloid malignancy
Authors: Mukherjee Devdeep , Lawal Rialnat A. , Fitzhugh Courtney D. , Hourigan Christopher S. , Dillon Laura W. 
Published: February 2024

ABSTRACTThere is increasing recognition of the risk of developing therapy-related myeloid malignancy, including after cellular therapy. While retrospective studies have implicated pre-existingTP53mutated hematopoietic clones as a common causative mechanism, no prospective screening to identify those patients at greatest risk is currently possible. We demonstrate that ultradeep DNA-sequencing prior to therapy may be used for discovery ofTP53mutations that are subsequently associated with malignancy.
Prospective Clinical Evaluation of a Deep Learning Algorithm for Guided Point-of-Care Ultrasonography Screening of Abdominal Aortic Aneurysms
Authors: Chiu I-Min , Chen Tien-Yu , Zheng You-Cheng , Lin Xin-Hong , Cheng Fu-Jen , Ouyang David , Cheng Chi-Yung 
Published: February 2024

AbstractBackgroundAbdominal Aortic Aneurysm (AAA) is a critical condition that can lead to fatal consequences if not detected and treated early. Despite the high prevalence in smokers and guideline recommendation for screening, AAA often remains undetected due to availability of diagnostic ultrasound examinations. This prospective clinical trial aimed to investigate the use of a Deep Learning (DL) algorithm to guide AAA screening.MethodsThis prospective, comparative diagnostic study was conducted at the Kaohsiung Chang Gung Memorial Hospital. We developed and deployed an object detection-based DL algorithm providing real-time guidance for novice users performing AAA screening using point of care ultrasound. 10 registered nurses with no prior ultrasonography experience were recruited and performed at least 15 scans on patients over 65 years old to acquire abdominal aorta videos. These scans were compared with those of physicians using the same ultrasound hardware but without DL guidance.ResultsA total of 184 patients (median [IQR] age of 72 [67-79], and 105 (57.1%) male) completed this study. The DL-guided novices achieved adequate scan quality in 87.5% (95% CI: 82.7 - 92.3%) of patients, comparable to the 91.3% (95% CI: 87.2-95.4%) rate of physician scans (p=0.310). This performance did not vary by BMI. The DL model predicted AAA with an AUC of 0.975, showing 100% sensitivity and 94.3% specificity. The DL model predicted the maximal width of abdominal aorta with mean absolute error of 2.8mm compared to physician measurements. 3 AAA with maximal width of aorta > 3cm were found in this study cohort.ConclusionDL-guided POCUS is an effective tool for AAA screening, providing comparable performance to experienced physicians. The use of this DL system could democratize AAA screening and improve access, thereby aiding in early disease detection and treatment.Clinical PerspectiveWhat is NewOur study presents a deep learning (DL) guidance system that enables novice users to perform Abdominal Aortic Aneurysm (AAA) screening with POCUS, yielding image quality comparable to experienced physicians.The DL algorithm accurately identifies AAA from scans conducted by novice users, maintains consistent performance across patients with varying BMIs, and demonstrates increased scan efficiency with repeated use.Clinical ImplicationsDL-guided POCUS can potentially expand AAA screening capabilities to non-specialist settings and increase throughput for screening at risk individuals.The implementation of our DL model for AAA screening could enhance early detection, particularly in underserved areas, but also optimize clinical workflows by decreasing diagnostic wait times and increasing ultrasound utilization efficiency.
Abrupt and gradual changes in neuronal processing upon falling asleep and awakening
Authors: Marmelshtein Amit , Lavy Barak , Hadad Barak , Nir Yuval 
Published: February 2024

AbstractThe neural processes that change when falling asleep are only partially understood. At the cortical level, features of both spontaneous neural activity and sensory responses change between wakefulness and sleep. For example, in early auditory cortex sleep increases the occurrence of post-onset silent (OFF) periods and elevates population synchrony. However, it remains unknown whether such changes occur abruptly or gradually around sleep onset and awakening. Here, we recorded spontaneous and sound-evoked neuronal spiking activity in early auditory cortex along with polysomnography during thousands of episodes when rats fell asleep or woke up. We found that when falling asleep, stimulus-induced neuronal silent periods (OFF periods), characteristic of non-rapid eye movement (NREM) sleep, increased within few seconds around sleep onset. By contrast, a gradual increase in neuronal population synchrony built up over dozens of seconds until reaching maximal levels. EEG auditory-evoked potentials representing stimulus-triggered “K complexes” changed along with post-onset neuronal firing, whereas ongoing EEG slow wave activity was associated with neuronal population synchrony. Similar effects, but with opposite direction, were observed around awakenings. The results highlight late stimulus-induced neuronal silence as a key feature changing abruptly around transitions between vigilance states, likely reflecting neuronal bistability and manifesting also in EEG evoked potentials. More generally, these findings emphasize the added value of going beyond monitoring ongoing activity and perturbing the nervous system to reveal its state - an insight that could also help guide development of more sensitive non-invasive monitors of falling asleep in humans.
DOT1L stimulates MYC/Mondo transcription factor activity by promoting its degradation cycle on chromatin
Authors: Sepulveda Gian P. , Gushchanskaia Ekaterina S. , Mora-Martin Alexandra , Esse Ruben , Nikorich Iana , Ceballos Ainhoa , Kwan Julian , Blum Benjamin C. , Dholiya Prakruti , Emili Andrew , Perissi Valentina , Cardamone Maria D. , Grishok Alla 
Published: February 2024

SUMMARYThe proto-oncogene c-MYC is a key representative of the MYC transcription factor network regulating growth and metabolism. MML-1 (Myc- and Mondo-like) is its homolog inC. elegans. The functional and molecular cooperation between c-MYC and H3 lysine 79 methyltransferase DOT1L was demonstrated in several human cancer types, and we have earlier discovered the connection betweenC. elegansMML-1 and DOT-1.1. Here, we demonstrate the critical role of DOT1L/DOT-1.1 in regulating c-MYC/MML-1 target genes genome-wide by ensuring the removal of “spent” transcription factors from chromatin by the nuclear proteasome. Moreover, we uncover a previously unrecognized proteolytic activity of DOT1L, which may facilitate c-MYC turnover. This new mechanism of c-MYC regulation by DOT1L may lead to the development of new approaches for cancer treatment.
Intra-Striatal Dopaminergic Inter-Subject Covariance in Social Drinkers and Nontreatment-Seeking Alcohol Use Disorder Participants
Authors: Chumin Evgeny J. , Dzemidzic Mario , Yoder Karmen K. 
Published: February 2024

AbstractOne of the neurobiological correlates of alcohol use disorder (AUD) is the disruption of striatal dopaminergic function. While regional differences in dopamine (DA) function have been well studied, inter-regional relationships (represented as inter-subject covariance) have not been investigated and may offer a novel avenue for understanding DA function.Positron emission tomography (PET) data with [11C]raclopride in 22 social drinking controls and 17 AUD participants were used to generate group-level striatal covariance (partial Pearson correlation) networks, which were compared edgewise, also comparing global network metrics and community structure. An exploratory analysis examined the impact of tobacco cigarette use status. Striatal covariance was validated in an independent publicly available [18F]fallypride PET sample of healthy volunteers.Striatal covariance of control participants from both datasets showed a clear bipartition of the network into two distinct communities, one in the anterior and another in the posterior striatum. This organization was disrupted in the AUD participant network, with significantly lower network metrics in AUD compared to the control network. Stratification by cigarette use suggests differential consequences on group covariance networks.This work demonstrates that network neuroscience can quantify group differences in striatal DA and that its inter-regional interactions offer new insight into the consequences of AUD.
Formylation facilitates the reduction of oxidized initiator methionines
Authors: Tan Ruiyue , Hoare Margaret , Bellomio Philip , Broas Sarah , Camacho Konttessa , Swovick Kyle , Welle Kevin A. , Hryhorenko Jennifer R. , Ghaemmaghami Sina 
Published: February 2024

AbstractWithin a cell, protein-bound methionines can be oxidized by reactive oxygen species (ROS) or monooxygenases, and subsequently reduced by methionine sulfoxide reductases (Msrs). Methionine oxidation can result in structural damage or be the basis of functional regulation of enzymes. In addition to participating in redox reactions, methionines play an important role as the initiator residue of translated proteins where they are commonly modified at their α-amine group by formylation or acetylation. Here, we investigated how formylation and acetylation of initiator methionines impact their propensity for oxidation and reduction. We show thatin vitro, N-terminal methionine residues are particularly prone to chemical oxidation, and that their modification by formylation or acetylation greatly enhances their subsequent enzymatic reduction by MsrA and MsrB. Concordantly,in vivoablation of methionyl-tRNA formyltransferase (MTF) inE. coliincreases the prevalence of oxidized methionines within synthesized proteins. We show that oxidation of formylated initiator methionines is detrimental in part because it obstructs their ensuing deformylation by peptide deformylase (PDF) and hydrolysis by methionyl aminopeptidase (MAP). Thus, by facilitating their reduction, formylation mitigates the misprocessing of oxidized initiator methionines.Classification: Biological Sciences; Biochemistry