bluuebunny/crossref_metadata_2025_split huggingface dataset:
Decrease of Pdzrn3 is required for heart maturation and protects against heart failure
Authors: Pernot Mathieu , Jaspard-vinassa Béatrice , Abelanet Alice , Rubin Sebastien , Forfar Isabelle , Jeanningros Sylvie , Cetran Laura , Yu Murielle Han-Yee , Balse Elise , Hatem Stéphane , Dufourcq Pascale , Couffinhal Thierry , Duplàa Cécile 
Published: January 2022

AbstractHeart failure is the final common stage of most cardiopathies. Cardiomyocytes (CM) connect with others via their extremities by intercalated disk protein complexes. This planar and directional organization of myocytes is crucial for mechanical coupling and anisotropic conduction of the electric signal in the heart. One of the hallmarks of heart failure is alterations in the contact sites between CM. Yet no factor on its own is known to coordinate CM polarized organization. We have previously shown that PDZRN3, an ubiquitine ligase E3 expressed in various tissues including the heart, mediates a branch of the Planar cell polarity (PCP) signaling involved in tissue patterning, instructing cell polarity and cell polar organization within a tissue. PDZRN3 is expressed in the embryonic mouse heart then its expression dropped significantly postnatally corresponding with heart maturation and CM polarized elongation. A moderate CM overexpression of Pdzrn3 (Pdzrn3 OE) during the first week of life, induced a severe eccentric hypertrophic phenotype with heart failure. In models of pressure-overload stress heart failure, CM-specific Pdzrn3 knockout showed complete protection against degradation of heart function. We reported that Pdzrn3 signaling induced PKC ζ expression, c-Jun nuclear translocation and a reduced nuclear ß catenin level, consistent markers of the planar non-canonical Wnt signaling in CM. We then show that subcellular localization (intercalated disk) of junction proteins as Cx43, ZO1 and Desmoglein 2 was altered in Pdzrn3 OE mice, which provides a molecular explanation for impaired CM polarization in these mice. Our results reveal a novel signaling pathway that controls a genetic program essential for heart maturation and maintenance of overall geometry, as well as the contractile function of CM, and implicates PDZRN3 as a potential therapeutic target for the prevention of human heart failure.
Inappropriate sinus tachycardia in post-COVID-19 syndrome
Authors: Aranyó Júlia , Bazan Victor , Lladós Gemma , Dominguez Maria Jesús , Bisbal Felipe , Massanella Marta , Sarrias Axel , Adeliño Raquel , Riverola Ariadna , Paredes Roger , Clotet Bonaventura , Bayés-Genís Antoni , Mateu Lourdes , Villuendas Roger 
Published: January 2022

AbstractInappropriate sinus tachycardia (IST) is a common observation in patients with post-COVID-19 syndrome (PCS) but has not yet been fully described to date. To investigate the prevalence and the mechanisms underlying IST in a prospective population of PCS patients. Consecutive patients admitted to the PCS Unit between June and December 2020 with a resting sinus rhythm rate ≥ 100 bpm were prospectively enrolled in this study and further examined by an orthostatic test, 2D echocardiography, 24-h ECG monitoring (heart rate variability was a surrogate for cardiac autonomic activity), quality-of-life and exercise capacity testing, and blood sampling. To assess cardiac autonomic function, a 2:1:1 comparative sub-analysis was conducted against both fully recovered patients with previous SARS-CoV-2 infection and individuals without prior SARS-CoV-2 infection. Among 200 PCS patients, 40 (20%) fulfilled the diagnostic criteria for IST (average age of 40.1 ± 10 years, 85% women, 83% mild COVID-19). No underlying structural heart disease, pro-inflammatory state, myocyte injury, or hypoxia were identified. IST was accompanied by a decrease in most heart rate variability parameters, especially those related to cardiovagal tone: pNN50 (cases 3.2 ± 3 vs. recovered 10.5 ± 8 vs. non-infected 17.3 ± 10; p < 0.001) and HF band (246 ± 179 vs. 463 ± 295 vs. 1048 ± 570, respectively; p < 0.001). IST is prevalent condition among PCS patients. Cardiac autonomic nervous system imbalance with decreased parasympathetic activity may explain this phenomenon.
Country-specific optimization strategy for testing through contact tracing can help maintain a low reproduction number ($$R_{0}$$) during unlock
Authors: Sarma Uddipan , Ghosh Bhaswar 
Published: January 2022

AbstractIn response to the COVID19 pandemic, many countries have implemented lockdowns in multiple phases to ensure social distancing and quarantining of the infected subjects. Subsequent unlocks to reopen the economies started next waves of infection and imposed an extra burden on quarantine to keep the reproduction number ($$R_{0}$$

R
0

) < 1. However, most countries could not effectively contain the infection spread, suggesting identification of the potential sources weakening the effect of lockdowns could help design better informed lockdown-unlock cycles in the future. Here, through building quantitative epidemic models and analyzing the metadata of 50 countries from across the continents we first found that the estimated value of $$R_{0}$$

R
0

, adjusted w.r.t the distribution of medical facilities and virus clades correlates strongly with the testing rates in a country. Since the testing capacity of a country is limited by its medical resources, we investigated if a cost–benefit trade-off can be designed connecting testing rate and extent of unlocking. We present a strategy to optimize this trade-off in a country specific manner by providing a quantitative estimate of testing and quarantine rates required to allow different extents of unlocks while aiming to maintain $$R_{0} < 1$$

R
0

<
1

. We further show that a small fraction of superspreaders can dramatically increase the number of infected individuals even during strict lockdowns by strengthening the positive feedback loop driving infection spread. Harnessing the benefit of optimized country-specific testing rates would critically require minimizing the movement of these superspreaders via strict social distancing norms, such that the positive feedback driven switch-like exponential spread phase of infection can be avoided/delayed.
A computational modeling approach for dosing endoscopic intratumoral chemotherapy for advanced non-small cell lung cancer
Authors: Mori Vitor , Bates Jason H. T. , Jantz Michael , Mehta Hiren J. , Kinsey C. Matthew 
Published: January 2022

AbstractWe recently developed a computational model of cisplatin pharmacodynamics in an endobronchial lung tumor following ultrasound-guided transbronchial needle injection (EBUS-TBNI). The model suggests that it is more efficacious to apportion the cisplatin dose between injections at different sites rather than giving it all in a single central injection, but the model was calibrated only on blood cisplatin data from a single patient. Accordingly, we applied a modified version of our original model in a set of 32 patients undergoing EBUS-TBNI for non-small cell lung cancer (NSCLC). We used the model to predict clinical responses and compared them retrospectively to actual patient outcomes. The model correctly predicted the clinical response in 72% of cases, with 80% accuracy for adenocarcinomas and 62.5% accuracy for squamous-cell lung cancer. We also found a power-law relationship between tumor volume and the minimal dose needed to induce a response, with the power-law exponent depending on the number of injections administered. Our results suggest that current injection strategies may be significantly over- or under-dosing the agent depending on tumor size, and that computational modeling can be a useful planning tool for EBUS-TBNI of cisplatin in lung cancer.
Session interest model for CTR prediction based on self-attention mechanism
Authors: Wang Qianqian , Liu Fang’ai , Zhao Xiaohui , Tan Qiaoqiao 
Published: January 2022

AbstractClick-through rate prediction, which aims to predict the probability of the user clicking on an item, is critical to online advertising. How to capture the user evolving interests from the user behavior sequence is an important issue in CTR prediction. However, most existing models ignore the factor that the sequence is composed of sessions, and user behavior can be divided into different sessions according to the occurring time. The user behaviors are highly correlated in each session and are not relevant across sessions. We propose an effective model for CTR prediction, named Session Interest Model via Self-Attention (SISA). First, we divide the user sequential behavior into session layer. A self-attention mechanism with bias coding is used to model each session. Since different session interest may be related to each other or follow a sequential pattern, next, we utilize gated recurrent unit (GRU) to capture the interaction and evolution of user different historical session interests in session interest extractor module. Then, we use the local activation and GRU to aggregate their target ad to form the final representation of the behavior sequence in session interest interacting module. Experimental results show that the SISA model performs better than other models.
Robust LC3B lipidation analysis by precisely adjusting autophagic flux
Authors: Liebl Martina P. , Meister Sarah C. , Frey Lisa , Hendrich Kristina , Klemmer Anja , Wohlfart Bettina , Untucht Christopher , Nuber Judith , Pohl Christian , Lakics Viktor 
Published: January 2022

AbstractAutophagic flux can be quantified based on the accumulation of lipidated LC3B in the presence of late-stage autophagy inhibitors. This method has been widely applied to identify novel compounds that activate autophagy. Here we scrutinize this approach and show that bafilomycin A1 (BafA) but not chloroquine is suitable for flux quantification due to the stimulating effect of chloroquine on non-canonical LC3B-lipidation. Significant autophagic flux increase by rapamycin could only be observed when combining it with BafA concentrations not affecting basal flux, a condition which created a bottleneck, rather than fully blocking autophagosome-lysosome fusion, concomitant with autophagy stimulation. When rapamycin was combined with saturating concentrations of BafA, no significant further increase of LC3B lipidation could be detected over the levels induced by the late-stage inhibitor. The large assay window obtained by this approach enables an effective discrimination of autophagy activators based on their cellular potency. To demonstrate the validity of this approach, we show that a novel inhibitor of the acetyltransferase EP300 activates autophagy in a mTORC1-dependent manner. We propose that the creation of a sensitized background rather than a full block of autophagosome progression is required to quantitatively capture changes in autophagic flux.
Panoramic tongue imaging and deep convolutional machine learning model for diabetes diagnosis in humans
Authors: Balasubramaniyan Saritha , Jeyakumar Vijay , Nachimuthu Deepa Subramaniam 
Published: January 2022

AbstractDiabetes is a serious metabolic disorder with high rate of prevalence worldwide; the disease has the characteristics of improper secretion of insulin in pancreas that results in high glucose level in blood. The disease is also associated with other complications such as cardiovascular disease, retinopathy, neuropathy and nephropathy. The development of computer aided decision support system is inevitable field of research for disease diagnosis that will assist clinicians for the early prognosis of diabetes and to facilitate necessary treatment at the earliest. In this research study, a Traditional Chinese Medicine based diabetes diagnosis is presented based on analyzing the extracted features of panoramic tongue images such as color, texture, shape, tooth markings and fur. The feature extraction is done by Convolutional Neural Network (CNN)—ResNet 50 architecture, and the classification is performed by the proposed Deep Radial Basis Function Neural Network (RBFNN) algorithm based on auto encoder learning mechanism. The proposed model is simulated in MATLAB environment and evaluated with performance metrics—accuracy, precision, sensitivity, specificity, F1 score, error rate, and receiver operating characteristics (ROC). On comparing with existing models, the proposed CNN based Deep RBFNN machine learning classifier model outperformed with better classification performance and proving its effectiveness.
Gut dysbiosis is associated with acceleration of lupus nephritis
Authors: Valiente Giancarlo R. , Munir Armin , Hart Marcia L. , Blough Perry , Wada Takuma T. , Dalan Emma E. , Willis William L. , Wu Lai-Chu , Freud Aharon G. , Jarjour Wael N. 
Published: January 2022

AbstractThe gut microbiota (GM) exerts a strong influence over the host immune system and dysbiosis of this microbial community can affect the clinical phenotype in chronic inflammatory conditions. To explore the role of the GM in lupus nephritis, we colonized NZM2410 mice with Segmented Filamentous Bacteria (SFB). Gut colonization with SFB was associated with worsening glomerulonephritis, glomerular and tubular immune complex deposition and interstitial inflammation compared to NZM2410 mice free of SFB. With SFB colonization mice experienced an increase in small intestinal lamina propria Th17 cells and group 3 innate lymphoid cells (ILC3s). However, although serum IL-17A expression was elevated in these mice, Th17 cells and ILC3s were not detected in the inflammatory infiltrate in the kidney. In contrast, serum and kidney tissue expression of the macrophage chemoattractants MCP-1 and CXCL1 were significantly elevated in SFB colonized mice. Furthermore, kidney infiltrating F4/80+CD206+M2-like macrophages were significantly increased in these mice. Evidence of increased gut permeability or “leakiness” was also detected in SFB colonized mice. Finally, the intestinal microbiome of SFB colonized mice at 15 and 30 weeks of age exhibited dysbiosis when compared to uncolonized mice at the same time points. Both microbial relative abundance as well as biodiversity of colonized mice was found to be altered. Collectively, SFB gut colonization in the NZM2410 mouse exacerbates kidney disease, promotes kidney M2-like macrophage infiltration and overall intestinal microbiota dysbiosis.
Bedside detection of intracranial midline shift using portable magnetic resonance imaging
Authors: Sheth Kevin N. , Yuen Matthew M. , Mazurek Mercy H. , Cahn Bradley A. , Prabhat Anjali M. , Salehi Sadegh , Shah Jill T. , By Samantha , Welch E. Brian , Sofka Michal , Sacolick Laura I. , Kim Jennifer A. , Payabvash Seyedmehdi , Falcone Guido J. , Gilmore Emily J. , Hwang David Y. , Matouk Charles , Gordon-Kundu Barbara , RN Adrienne Ward , Petersen Nils , Schindler Joseph , Gobeske Kevin T. , Sansing Lauren H. , Sze Gordon , Rosen Matthew S. , Kimberly W. Taylor , Kundu Prantik 
Published: January 2022

AbstractNeuroimaging is crucial for assessing mass effect in brain-injured patients. Transport to an imaging suite, however, is challenging for critically ill patients. We evaluated the use of a low magnetic field, portable MRI (pMRI) for assessing midline shift (MLS). In this observational study, 0.064 T pMRI exams were performed on stroke patients admitted to the neuroscience intensive care unit at Yale New Haven Hospital. Dichotomous (present or absent) and continuous MLS measurements were obtained on pMRI exams and locally available and accessible standard-of-care imaging exams (CT or MRI). We evaluated the agreement between pMRI and standard-of-care measurements. Additionally, we assessed the relationship between pMRI-based MLS and functional outcome (modified Rankin Scale). A total of 102 patients were included in the final study (48 ischemic stroke; 54 intracranial hemorrhage). There was significant concordance between pMRI and standard-of-care measurements (dichotomous, κ = 0.87; continuous, ICC = 0.94). Low-field pMRI identified MLS with a sensitivity of 0.93 and specificity of 0.96. Moreover, pMRI MLS assessments predicted poor clinical outcome at discharge (dichotomous: adjusted OR 7.98, 95% CI 2.07–40.04, p = 0.005; continuous: adjusted OR 1.59, 95% CI 1.11–2.49, p = 0.021). Low-field pMRI may serve as a valuable bedside tool for detecting mass effect.
Computational identification of 4-carboxyglutamate sites to supplement physiological studies using deep learning
Authors: Naseer Sheraz , Ali Rao Faizan , Fati Suliman Mohamed , Muneer Amgad 
Published: January 2022

AbstractIn biological systems, Glutamic acid is a crucial amino acid which is used in protein biosynthesis. Carboxylation of glutamic acid is a significant post-translational modification which plays important role in blood coagulation by activating prothrombin to thrombin. Contrariwise, 4-carboxy-glutamate is also found to be involved in diseases including plaque atherosclerosis, osteoporosis, mineralized heart valves, bone resorption and serves as biomarker for onset of these diseases. Owing to the pathophysiological significance of 4-carboxyglutamate, its identification is important to better understand pathophysiological systems. The wet lab identification of prospective 4-carboxyglutamate sites is costly, laborious and time consuming due to inherent difficulties of in-vivo, ex-vivo and in vitro experiments. To supplement these experiments, we proposed, implemented, and evaluated a different approach to develop 4-carboxyglutamate site predictors using pseudo amino acid compositions (PseAAC) and deep neural networks (DNNs). Our approach does not require any feature extraction and employs deep neural networks to learn feature representation of peptide sequences and performing classification thereof. Proposed approach is validated using standard performance evaluation metrics. Among different deep neural networks, convolutional neural network-based predictor achieved best scores on independent dataset with accuracy of 94.7%, AuC score of 0.91 and F1-score of 0.874 which shows the promise of proposed approach. The iCarboxE-Deep server is deployed at https://share.streamlit.io/sheraz-n/carboxyglutamate/app.py.
Rubicon-regulated beta-1 adrenergic receptor recycling protects the heart from pressure overload
Authors: Akazawa Yasuhiro , Taneike Manabu , Ueda Hiromichi , Kitazume-Taneike Rika , Murakawa Tomokazu , Sugihara Ryuta , Yorifuji Hiroki , Nishida Hiroki , Mine Kentaro , Hioki Ayana , Omiya Shigemiki , Nakayama Hiroyuki , Yamaguchi Osamu , Yoshimori Tamotsu , Sakata Yasushi , Otsu Kinya 
Published: January 2022

AbstractHeart failure has high morbidity and mortality in the developed countries. Autophagy is important for the quality control of proteins and organelles in the heart. Rubicon (Run domain Beclin-1-interacting and cysteine-rich domain-containing protein) has been identified as a potent negative regulator of autophagy and endolysosomal trafficking. The aim of this study was to investigate the in vivo role of Rubicon-mediated autophagy and endosomal trafficking in the heart. We generated cardiomyocyte-specific Rubicon-deficient mice and subjected the mice to pressure overload by means of transverse aortic constriction. Rubicon-deficient mice showed heart failure with left ventricular dilatation, systolic dysfunction and lung congestion one week after pressure overload. While autophagic activity was unchanged, the protein amount of beta-1 adrenergic receptor was decreased in the pressure-overloaded Rubicon-deficient hearts. The increases in heart rate and systolic function by beta-1 adrenergic stimulation were significantly attenuated in pressure-overloaded Rubicon-deficient hearts. In isolated rat neonatal cardiomyocytes, the downregulation of the receptor by beta-1 adrenergic agonist was accelerated by knockdown of Rubicon through the inhibition of recycling of the receptor. Taken together, Rubicon protects the heart from pressure overload. Rubicon maintains the intracellular recycling of beta-1 adrenergic receptor, which might contribute to its cardioprotective effect.
Synthesis of zeolitic imidazolate framework-8 and gold nanoparticles in a sustained out-of-equilibrium state
Authors: Dúzs Brigitta , Holló Gábor , Schuszter Gábor , Horváth Dezső , Tóth Ágota , Szalai István , Lagzi István 
Published: January 2022

AbstractThe design and synthesis of crystalline materials are challenging due to the proper control over the size and polydispersity of the samples, which determine their physical and chemical properties and thus applicability. Metal − organic frameworks (MOFs) are promising materials in many applications due to their unique structure. MOFs have been predominantly synthesized by bulk methods, where the concentration of the reagents gradually decreased, which affected the further nucleation and crystal growth. Here we show an out-of-equilibrium method for the generation of zeolitic imidazolate framework-8 (ZIF-8) crystals, where the non-equilibrium crystal growth is maintained by a continuous two-side feed of the reagents in a hydrogel matrix. The size and the polydispersity of the crystals are controlled by the fixed and antagonistic constant mass fluxes of the reagents and by the reaction time. We also present that our approach can be extended to synthesize gold nanoparticles in a redox process.
Expanding structural diversity in a library of disulfide macrocycles through in-situ imide hydrolysis
Authors: Konopka Marcin , Stefankiewicz Artur R. 
Published: January 2022

AbstractWe describe here an unorthodox approach to dynamic covalent chemistry in which the initially-unexpected in-situ hydrolysis of a bis-imide is employed to control the composition of a library of structurally diverse macrocycles. A single building block is used to generate a library of numerous disulfide-based architectures in a one-pot single-step process. The dual-stimuli method is based on simultaneous changes in pH and DMSO concentration to expand the structural diversity of the macrocyclic products. Mechanistic details of this complex process are investigated by the kinetics analysis. We delivered a facile strategy for the synthesis of water-soluble, multicomponent and dynamic macrocycles equipped with number of different functional groups, thus giving a prospect of their application in guest-driven phase transfer.
Geographic and temporal variation in racial and ethnic disparities in SARS-CoV-2 positivity between February 2020 and August 2021 in the United States
Authors: Ferguson Jacqueline M. , Justice Amy C. , Osborne Thomas F. , Magid Hoda S. Abdel , Purnell Amanda L. , Rentsch Christopher T. 
Published: January 2022

AbstractThe coronavirus pandemic has disproportionally impacted racial and ethnic minority communities in the United States. Patterns of these disparities may be changing over time as outbreaks occur in different communities. Utilizing electronic health record data from the US Department of Veterans Affairs (VA), we estimated odds ratios, stratified by time period and region, for testing positive among 1,313,402 individuals tested for SARS-CoV-2 between February 12, 2020 and August 16, 2021 at VA medical facilities. We adjusted for personal characteristics (sex, age, rural/urban residence, VA facility) and a wide range of clinical characteristics that have been evaluated in prior SARS-CoV-2 reports and could potentially explain racial/ethnic disparities in SARS-CoV-2. Our study found racial and ethnic disparities for testing positive were most pronounced at the beginning of the pandemic and decreased over time. A key finding was that the disparity among Hispanic individuals attenuated but remained elevated, while disparities among Asian individuals reversed by March 1, 2021. The variation in racial and ethnic disparities in SARS-CoV-2 positivity by time and region, independent of underlying health status and other demographic characteristics in a nationwide cohort, provides important insight for strategies to prevent further outbreaks.