bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abnormal Cardiac Magnetic Resonance–Derived Ascending Aortic Area Strain Demonstrates Altered Ventriculo-Vascular Function in Marfan Syndrome
Authors: Jacquemyn Xander , Cordrey Kyla , Van Den Eynde Jef , Guerrerio Anthony L. , MacCarrick Gretchen , Dietz Hal C. , Kutty Shelby 
Published: April 2024

Purpose:
There remains a need for improved imaging markers for risk stratification and treatment guidance in Marfan syndrome (MFS). After aortic root replacement (ARR), vascular remodeling and progressive aneurysm formation can occur due to alterations in up- and downstream wall biomechanics and hemodynamics. We aim to compare the ventriculo-vascular properties of patients with MFS with controls, and investigate the correlation between ascending aortic area strain and descending aortic area strain (DAAS) with other clinical variables.

Patients and Methods:
Nineteen patients with MFS (47% males), including 6 with ARR were studied. In 26 studies, aortic area strain was measured using cross-sectional cardiac magnetic resonance images at the ascending and proximal descending aortic levels. Left atrial, left ventricular longitudinal, and left ventricle circumferential strain (left atrial longitudinal strain, left ventricular longitudinal strain, and left ventricular circumferential strain, respectively) were measured using cardiac magnetic resonance–feature tracking.

Results:
Compared with healthy controls, patients with MFS had significantly impaired left ventricular longitudinal strain and left ventricular circumferential strain (−15.8 ± 4.7 vs −19.7 ± 4.8, P = 0.005, and −17.7 ± 4.0 vs −27.0 ± 4.1, P < 0.001). Left atrial longitudinal strain was comparable between patients with MFS and controls. AAAS was significantly reduced (19.0 [11.9, 23.7] vs 46.1 ± 11.3, P < 0.001), whereas DAAS was not significantly decreased. AAAS and DAAS were negatively correlated with age, whereas no significant associations were identified with left ventricle function indices. No significant differences were observed between the ventriculo-vascular properties of patients with MFS who underwent ARR and those who did not.

Conclusion:
Patients with MFS demonstrated impaired ventricular and vascular function compared with healthy controls. Further investigations are warranted to determine clinical utility of aortic stiffness indices for predicting primary and repeat aortic events.
Can We Differentiate Between Primary Sjögren Syndrome and Idiopathic Multicentric Castleman Disease Based on the Characteristics of Pulmonary Cysts?
Authors: Zhou Jiamin , Zhang Lu , Liu Xueqing , Zhang Miaoyan , Liu Ziwei , Jin Ye , Feng Ruie , Shi Juhong , Li Jian , Zhang Weihong 
Published: April 2024

Purpose:
To identify radiological characteristics that could help differentiate cystic lung diseases between primary Sjögren syndrome (pSS) and idiopathic multicentric Castleman disease (iMCD).

Patients and Methods:
Patients with pSS or iMCD who had cysts were enrolled. Cyst characteristics (number, size, morphology, and distribution) and other accompanying manifestations (nodules, ground-glass opacities, calcification, and thickening of the bronchovascular bundles and interlobular septa) were compared between them.

Results:
Eleven patients with pSS and 25 patients with iMCD were eligible for our study. Eleven patients with pSS (100.0%) and 23 patients with iMCD (92.0%) had round or oval cysts. None of the patients with pSS had irregular cysts, but 21 (84.0%) patients with iMCD had irregular cysts (P = 0.005). Smooth-walled cysts were present in 11 patients with pSS (100.0%) and 18 patients with iMCD (72.0%). Only 1 patient with pSS (9.1%) exhibited non-smooth-walled cysts, whereas 23 patients with iMCD (92.0%) had non-smooth-walled cysts (P = 0.003). The presence of nodules was common in both groups (P = 1.000). However, the nodules were more likely to be larger and more numerous in patients with iMCD (P < 0.001). Cysts with mural nodules (52.2%) and central nodules (47.8%) were only observed in iMCD (P = 0.007).

Conclusion:
Although regular and smooth-walled cysts were common in the 2 diseases, irregular and non-smooth-walled cysts were more often associated with iMCD than pSS. Nodules in iMCD tended to be larger and more numerous, and a close positional relationship between nodules and cysts was only observed in iMCD.
SARS-CoV-2 spike S2 subunit inhibits p53 activation of p21(WAF1), TRAIL Death Receptor DR5 and MDM2 proteins in cancer cells
Authors: Zhang Shengliang , El-Deiry Wafik S. 
Published: April 2024

AbstractSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and COVID-19 infection has led to worsened outcomes for patients with cancer. SARS-CoV-2 spike protein mediates host cell infection and cell-cell fusion that causes stabilization of tumor suppressor p53 protein. In-silico analysis previously suggested that SARS-CoV-2 spike interacts with p53 directly but this putative interaction has not been demonstrated in cells. We examined the interaction between SARS-CoV-2 spike, p53 and MDM2 (E3 ligase, which mediates p53 degradation) in cancer cells using an immunoprecipitation assay. We observed that SARS-CoV-2 spike protein interrupts p53-MDM2 protein interaction but did not detect SARS-CoV-2 spike bound with p53 protein in the cancer cells. We further observed that SARS-CoV-2 spike suppresses p53 transcriptional activity in cancer cells including after nutlin exposure of wild-type p53-, spike S2-expressing tumor cells and inhibits chemotherapy-induced p53 gene activation of p21(WAF1), TRAIL Death Receptor DR5 and MDM2. The suppressive effect of SARS-CoV-2 spike on p53-dependent gene activation provides a potential molecular mechanism by which SARS-CoV-2 infection may impact tumorigenesis, tumor progression and chemotherapy sensitivity. In fact, cisplatin-treated tumor cells expressing spike S2 were found to have increased cell viability as compared to control cells. Further observations on γ-H2AX expression in spike S2-expressing cells treated with cisplatin may indicate altered DNA damage sensing in the DNA damage response pathway. The preliminary observations reported here warrant further studies to unravel the impact of SARS-CoV-2 and its various encoded proteins including spike on pathways of tumorigenesis and response to cancer therapeutics.
Selective phase separation of transcription factors is driven by orthogonal molecular grammar
Authors: Driver Mark D. , Onck Patrick R. 
Published: April 2024

AbstractProtein production is critically dependent on gene transcription rates, which are regulated by RNA polymerase and a large collection of transcription factors (TFs). Previous studies identified the formation of super enhancer regions where increased transcriptional activity is observed. This has been linked to phase separation, in which the differential condensation behaviour of separate TF families has been hypothesised to cause the selectivity in gene expression. The underlying molecular forces that are responsible for this selectivity, however, are unknown. Here, we conduct phase separation studies on six TFs (FUS, EWS, TAF15, SP1, SP2, and HNF1A) from three different TF families by carrying out residue-scale coarse-grained molecular dynamics simulations. Our exploration of ternary TF phase diagrams revealed four dominant sticker motifs and two orthogonal driving forces, consisting of hydrophobic (aromatic, aliphatic) interactions and electrostatic/cation-πinteractions. The contribution of these driving forces to the homotypic and heterotypic intermolecular strengths dictate the resultant condensate morphology. These results point to sequence-dependent orthogonal grammar as a generic mechanism responsible for selective transcriptional condensation in gene expression. Interestingly, our results also show how RNA polymerase is able to overcome this orthogonality to coalesce with TF condensate providing a framework in which co-condensation is the primary nuclear organisational principle that controls selective partitioning of RNAP to targeted genes for transcription.
Genetic screen to test microRNA function in peripheral glia morphology
Authors: Paluri Sravya , Auld Vanessa J. 
Published: April 2024

AbstractGlial cells perform many functions in the nervous system, including maintaining the blood-brain/nerve barriers and structurally supporting axons. While their functions are well-characterized, the complex molecular mechanisms important for their development are less known. Here, we investigated whether microRNA-mediated post-transcriptional regulation is involved during glial development, ensheathment and blood-nerve-barrier formation inDrosophila. In this study, we systematically knocked down 120 different microRNAs by competitive inhibition using microRNA-sponges and analyzed peripheral glial morphology. Knockdown of miRNA-125 in the blood-nerve barrier-forming glia (subperineurial glia) resulted in the most penetrant morphological defects. Since microRNA-125 is co-transcribed with miRNAs-let7 and −100 in a genetic cluster, our further verification for subperineurial glia function included miRNA-125 plus all other members of this cluster. However, the loss of each individual gene and the entire cluster did not lead to any morphological defects in the subperineurial glia. To test the efficiency of the microRNA sponge approach in subperineurial glia, we expressed a sponge targeting a microRNA established to be vital for blood-brain barrier formation (microRNA-285) and found no defects in brain lobes and peripheral nerves. Given that a scrambled-sponge control also generated morphological defects, this suggests that using miRNA sponge lines may not be an effective approach to study miRNA function in Drosophila peripheral glia.
An Efficient and Principled Model to Jointly Learn the Agnostic and Multifactorial Effect in Large-Scale Biological Data
Authors: Cheng Zuolin , Wei Songtao , Wang Yinxue , Wang Yizhi , Lu Q Richard , Wang Yue , Yu Guoqiang 
Published: April 2024

AbstractThe rich information contained in biological data is often distorted by multiple interacting intrinsic or extrinsic factors. Modeling the effects of these factors is necessary to uncover the underlying true signals. However, this is challenging in real applications, because biological data usually consist of tens of thousands or millions of factors, and no reliable prior knowledge is available on how these factors exert the effect, to what degree the effect is, as well as how they interact with each other. Thus, the existing approaches rely on excessive simplification or unrealistic assumptions such as the probabilistic independence among factors. In this paper, we report the finding that after reformulating the data as a contingency tensor the problem can be well addressed by a fundamental machine learning principle, Maximum Entropy, with an extra effort of designing an efficient algorithm to solve the large-scale optimization problem. Based on the principle of maximum entropy, and by constraining the marginals of the contingency tensor using the observed values, our Conditional Multifactorial Contingency (CMC) model imposes minimum but essential assumptions about the multifactorial joint effects and leads to a conceptually simple distribution, which informs how these factors exert the effects and interact with each other. By replacing hard constraints with expected values, CMC avoids the NP-hard problem and results in a theoretically solvable convex problem. However, due to the large scale of variables and constraints, the standard convex solvers do not work. Exploring the special properties of the CMC model we developed an efficient iterative optimizer, which reduces the running time from infeasible to minutes or from days to seconds. We applied CMC to quite a few cutting-edge biological applications, including the detection of driving transcription factor, scRNA-seq normalization, cancer-associated gene identification, GO-term activity transformation, and quantification of single-cell-level similarity. CMC gained much better performance than other methods with respect to various evaluation criteria. Our source code of CMC as well as its example applications can be found athttps://github.com/yu-lab-vt/CMC.One-Sentence SummaryCMC jointly learns intertwined effects of numerous factors in biologival data and outperform existing methods in multiple cutting-edge biological applications.
Super-resolution Left Ventricular Flow and Pressure Mapping by Navier-Stokes-Informed Neural Networks
Authors: Maidu Bahetihazi , Martinez-Legazpi Pablo , Guerrero-Hurtado Manuel , Nguyen Cathleen M. , Gonzalo Alejandro , Kahn Andrew M. , Bermejo Javier , Flores Oscar , del Alamo Juan C. 
Published: April 2024

AbstractIntraventricular vector flow mapping (VFM) is a growingly adopted echocardiographic modality that derives time-resolved two-dimensional flow maps in the left ventricle (LV) from color-Doppler sequences. Current VFM models rely on kinematic constraints arising from planar flow incompressibility. However, these models are not informed by crucial information about flow physics; most notably the pressure and shear forces within the fluid and the resulting accelerations. This limitation has rendered VFM unable to combine information from different time frames in an acquisition sequence or derive fluctuating pressure maps. In this study, we leveraged recent advances in artificial intelligence (AI) to develop AI-VFM, a vector flow mapping modality that uses physics-informed neural networks (PINNs) encoding mass conservation and momentum balance inside the LV, and no-slip boundary conditions at the LV endocardium. AI-VFM recovers the flow and pressure fields in the LV from standard echocardiographic scans. It performs phase unwrapping and recovers flow data in areas without input color-Doppler data. AI-VFM also recovers complete flow maps at time points without color-Doppler input data, producing super-resolution flow maps. We show that informing the PINNs with momentum balance is essential to achieving temporal super-resolution and significantly increases the accuracy of AI-VFM compared to informing the PINNs only with mass conservation. AI-VFM is solely informed by each patient’s flow physics; it does not utilize explicit smoothness constraints or incorporate data from other patients or flow models. AI-VFM takes 15 minutes to run in off-the-shelf graphics processing units and its underlying PINN framework could be extended to map other flow-associated metrics like blood residence time or the concentration of coagulation species.
Characterization of spike processing and entry mechanisms of seasonal human coronaviruses NL63, 229E and HKU1
Authors: Neerukonda Sabari Nath , Vassell Russell , Lusvarghi Sabrina , Liu Shufeng , Akue Adovi , KuKuruga Mark , Wang Tony T. , Weiss Carol D , Wang Wei 
Published: April 2024

AbstractAlthough much has been learned about the entry mechanism of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the details of entry mechanisms of seasonal human coronaviruses (HCoVs) remain less well understood. In the present study, we established that 293T cell lines that stably express angiotensin converting enzyme (ACE2), aminopeptidase N (APN), or transmembrane serine protease 2 (TMPRSS2) support high level transduction of lentiviral pseudoviruses bearing spike proteins of seasonal HCoVs, HCoV-NL63, -229E, or -HKU1, respectively. Our results showed that entry of HCoV-NL63, -229E and -HKU1 pseudoviruses is sensitive to endosomal acidification inhibitors (chloroquine and NH4Cl), indicating virus entry via the endocytosis route. Although HCoV-HKU1 pseudovirus infection requires TMPRSS2 expression on cell surface, endocytosis-mediated HCoV-HKU1 entry requires the serine protease domain but not the serine protease activity of TMPRSS2. We also show that amino acids in the predicted S1/S2 junctions of spike proteins of HCoV-NL63, and - 229E are essential for optimal entry but non-essential for spike-mediated entry of HCoV-HKU1. Our findings provide insights into entry mechanism of seasonal HCoVs that may support the development of novel treatment strategies.ImportanceDetails of the entry mechanisms of seasonal human coronaviruses (HCoVs) remain to be fully explored. To investigate the entry of HCoV-NL63, -229E and -HKU1 CoVs, we employed 293T cells that stably express angiotensin converting enzyme (ACE2) aminopeptidase N (APN), or transmembrane serine protease 2 (TMPRSS2) to study entry mechanisms of pseudoviruses bearing spike proteins of HCoV-NL63, -229E and - HKU1 respectively. Our results provide new insights into the predicted S1/S2 subunit junctions, cellular receptor, and protease requirements for seasonal HCoV pseudovirus entry via endocytic route and may support the development of novel treatment strategies.
Antimicrobial blue light-bathing therapy for wound infection control
Authors: Hui Jie , Moon Wonjoon , Dong Pu-Ting , Anjos Carolina dos , Negri Laisa , Yan Hao , Wang Ying , Tam Joshua , Dai Tianhong , Anderson R. Rox , Goverman Jeremy , Gelfand Jeffrey , Yun Seok-Hyun 
Published: April 2024

AbstractThe prevalence of antibiotic resistance and tolerance in wound infection management poses a serious and growing health threat, necessitating the exploration of alternative approaches. Antimicrobial blue light therapy offers an appealing, non-pharmacological solution. However, its practical application has been hindered by the requirement for high irradiance levels, which particularly raises safety concerns. Here, we introduce a light-bathing strategy that employs prolonged, continuous exposure to blue light at an irradiance range lower by more than an order of magnitude (5 mW/cm2). This method consistently applies bacteriostatic pressure, keeping wound bioburden low, all while minimizing photothermal risks. Leveraging tailor-made, wearable light-emitting patches, we conducted preclinical trials on rat models of wound infection, demonstrating its safety and efficacy for suppressing infections induced by methicillin- resistantS. aureusand multidrug-resistantP. aeruginosa. Our results pave a new way for the application of blue light therapy in wound care.
Competition for resources can reshape the evolutionary properties of spatial structure
Authors: Devadhasan Anush , Kolodny Oren , Carja Oana 
Published: April 2024

AbstractMany evolving ecosystems have spatial structures that can be conceptualized as networks, with nodes representing individuals or homogeneous subpopulations and links the patterns of interaction and replacement between them. Prior models of evolution on networks do not take ecological niche differences and eco-evolutionary interplay into account. Here, we combine a resource competition model with evolutionary graph theory to study how heterogeneous topological structure shapes evolutionary dynamics under global frequency-dependent ecological interactions. We find that the addition of ecological competition for resources can produce a reversal of roles between amplifier and suppressor networks for deleterious mutants entering the population. Moreover, we show that this effect is a non-linear function of ecological niche overlap and discuss intuition for the observed dynamics using simulations and analytical approximations.
Wearable Gait Analysis is Highly Sensitive in Detection of Fatigue-Induced Exercise in Low Intensity Training Among University Football Players
Authors: Shin Seungmin , Tomar Rakesh , Son Minji , Kim Seoungeun , Lee Yongho 
Published: April 2024

AbstractGait analysis is crucial for understanding human movement patterns and detecting changes induced by factors such as fatigue. Fatigue can significantly impact gait dynamics, especially in athletes engaged in low-intensity training sessions like university football players. This study aimed to investigate the sensitivity of wearable sensors in detecting fatigue induced by low-intensity football training among university players. Twenty healthy male university football players participated in the study, undergoing gait analysis using wearable sensors before and after a 90-minute football training session. Data were collected using shoe-type IMU sensors for gait analysis, GPS trackers for exercise monitoring, and heart rate monitors for heart rate assessment. Participants also reported their perceived exertion using the Borg RPE scale. Results showed significant changes in various gait parameters post-exercise, including decreased cadence, increased percentage of double support, decreased percentage of single support, and increased time of toe-off. However, parameters like stride length remained unchanged. Center of gravity parameters did not show significant differences except for an increase in the ML(Y) acceleration post-exercise. The study suggests that even low to moderate-intensity exercise can induce fatigue, impacting walking dynamics. Wearable IMU sensors proved highly sensitive in detecting accumulated fatigue, even in low-intensity exercises, providing valuable insights into athletes’ physical deterioration during daily activities. This method could be crucial for monitoring fatigue and preventing injuries among athletes engaged in various sports activities. Further research is recommended to explore the impact of fatigue on other gait features and to evaluate gender differences. Additionally, examining muscle phosphocreatine readings could provide further insights into fatigue-related changes in gait. Nonetheless, the study highlights the effectiveness of wearable IMU sensor gait tests in detecting fatigue induced by low to moderate-intensity exercises, emphasizing the importance of monitoring fatigue for injury prevention and performance optimization in athletes.
AUTS2, a causative gene for microcephaly, regulates division of intermediate progenitor cells and production of upper-layer neurons
Authors: Shimaoka Kazumi , Hori Kei , Miyashita Satoshi , Inoue Yukiko U. , Sakamoto Asami , Hasegawa Ikuko , Yamashiro Kunihiko , Egusa Saki F. , Tatsumoto Shoji , Go Yasuhiro , Abe Manabu , Sakimura Kenji , Inoue Takayoshi , Imamura Takuya , Hoshino Mikio 
Published: April 2024

AbstractAUTS2mutations often exhibit neurodevelopmental disorders and microcephaly. However, how AUTS2 regulates neuron production and affects brain size remains unclear. Here, we show that AUTS2 cooperates with the Polycomb complex PRC2 to regulate gene expression and cortical neurogenesis.Auts2mutant mice exhibit reduced division of intermediate progenitor cells (IPCs), leading to decreased neurons and thickness in the upper-layer cortex. Expression ofRobo1is increased in the mutants, which in turn suppresses IPC division. Transcriptome and chromatin profiling experiments show that, in IPCs, AUTS2 primarily represses transcription of genes, includingRobo1. Promoter region of AUTS2 target genes is enriched with H3K27me3, a repressive histone modification, but its levels are reduced inAuts2mutants. AUTS2 interacts with PRC2, and together, they promote IPC division. These suggest that AUTS2 collaborates with PRC2 to repress gene transcription through H3K27 trimethylation, promoting neuron production. This sheds light on AUTS2 pathophysiological mechanisms in neurogenesis and microcephaly.