bluuebunny/crossref_metadata_2025_split huggingface dataset:
Overexpressed lncRNA AC068039.4 Contributes to Proliferation and Cell Cycle Progression of Pulmonary Artery Smooth Muscle Cells Via Sponging miR-26a-5p/TRPC6 in Hypoxic Pulmonary Arterial Hypertension
Authors: Qin Yuhan , Zhu Boqian , Li Linqing , Wang Dong , Qiao Yong , Liu Bo , Luo Erfei , Hou Jiantong , Yan Gaoliang , Tang Chengchun 
Published: July 2020

Abstract

Background:
Hypoxic pulmonary hypertension (HPH) is a devastating and incurable disease characterized by pulmonary vascular remodeling, resulting in right heart failure and even death. Accumulated evidence has confirmed long coding RNAs (lncRNAs) are involved in hypoxia-induced pulmonary vascular remodeling in HPH. The exact mechanism of lncRNA in hypoxic pulmonary hypertension remains unclear.

Methods:
Microarray analysis was applied to investigate the profiles of lncRNA expression in pulmonary artery smooth muscle cells (PASMCs) cultured under hypoxia and normoxia condition. qRT-PCR was performed for the expression of lncRNAs, miRNA, and mRNAs, western blot analysis was employed for the detection of the expression of proteins. CCK-8 and transwell chamber assay were applied for the assessment of PASMC proliferation and migration, respectively. Besides, flow cytometry was performed for assessments of cell cycle progression. The binding between AC068039.4 and miR-26a-5p, miR-26a-5p, and TRPC6 3’UTR was detected by dual luciferase reporter assay.

Results:
A total of 1,211 lncRNAs (698 up-regulated and 513 down-regulated) were differently expressed in hypoxia-induced PASMCs. Consistent with microarray analysis, quantitative PCR verified that AC068039.4 was obviously up-regulated in hypoxia-induced PASMCs. Knocking down AC068039.4 alleviated proliferation and migration of PASMCs and regulated cell cycle progression through inhibiting cells entering the G0/G1 cell cycle phase. Further experiment indicated AC068039.4 promoted hypoxic PASMCs proliferation via sponging miR-26–5p. In addition, transient receptor potential canonical 6 (TRPC6) was confirmed to be a target gene of miR-26a-5p.

Conclusion:
In conclusion, downregulation of lncRNA AC068039.4 inhibited pulmonary vascular remodeling through AC068039.4/miR-26a-5p/TRPC6 axis, providing new therapeutic insights for the treatment of HPH.
The Cardiac Physiology Underpinning Exsanguination Cardiac Arrest: Targets for Endovascular Resuscitation
Authors: Madurska Marta J. , Abdou Hossam , Leung Lai Yee , Richmond Michael J. , Elansary Noha N. , Scalea Thomas M. , Hu Peter , Morrison Jonathan J. 
Published: July 2020

ABSTRACT
Exsanguination leading to cardiac arrest is the terminal phase of uncontrolled hemorrhage. Resuscitative interventions have focused on preload and afterload support. Outcomes remain poor due to several factors but poor coronary perfusion undoubtedly plays a role. The aim of this study is to characterize the relationship between arterial pressure and flow during hemorrhage in an effort to better describe the terminal phases of exsanguination.
Male swine weighing 60 kg to 80 kg underwent splenectomy and instrumentation followed by a logarithmic exsanguination until asystole. Changes in hemodynamic parameters over time were compared using one-way, repeated measures analysis of variance.
Nine animals weighing 69 ± 15 kg were studied. Asystole occurred at 53 ± 13 min when 52 ± 11% of total blood volume has been shed. The greatest fall in mean hemodynamic indices were noted in the first 15 min: SBP (80–42 mm Hg, P = 0.02), left ventricular end-diastolic volume (94–52 mL, P = 0.04), cardiac output (4.8–2.4 L/min, P = 0.03), coronary perfusion pressure (57–30 mm Hg, P = 0.01), and stroke volume (60–25 mL, P = 0.02). This corresponds to the greatest rate of exsanguination. Organized cardiac activity was observed until asystole without arrythmias. Coronary flow was relatively preserved throughout the study, with a precipitous decline once mean arterial pressure was less than 20 mm Hg, leading to asystole.
In this model, initial hemodynamic instability was due to preload failure, with asystole occurring relatively late, secondary to failure of coronary perfusion. Future resuscitative therapies need to directly address coronary perfusion failure if effective attempts are to be made to salvage these patients.
Early Hemoglobin Status as a Predictor of Long-Term Mortality for Sepsis Patients in Intensive Care Units
Authors: Qi Desheng , Peng Milin 
Published: July 2020

ABSTRACT

Objectives:
It is still not clear what influences hemoglobin has on the outcomes of patients with sepsis. The intention of this research is to investigate the impact of early hemoglobin levels on clinical outcomes for sepsis.

Methods:
In this single-center, cohort study, each patient was put into one of four groups dependent on hemoglobin levels of 70 g/L, 80 g/L, or 90 g/L in the first 48 h of being admitted to intensive care unit (ICU). Adjustments for baseline/confounding factors were made using the multiple Cox regression model.

Results:
In all, 235 septic patients were examined in this research. The non-survivors exhibited significantly higher levels for early hemoglobin status at or below 80 g/L (33.7% vs. 19.4%, P = 0.016) than survivors. Survival curve demonstrated that septic patients with early hemoglobin levels at or below 80 g/L survived at significantly lower rates than those with hemoglobin above 80 g/L. Multivariate Cox analysis demonstrated that levels of 1-year mortality rose as early hemoglobin levels fell in the first 48 h after ICU admission, with relative risks for 80 g/L to 90 g/L, 70 g/L to 80 g/L, and at or below 70 g/L being respectively 1.11 (95% CI: 0.654–1.882), 1.742 (95% CI: 0.969–3.133), 1.981 (95% CI: 1.124–3.492) times higher than those for hemoglobin levels above 90 g/L.

Conclusions:
Hemoglobin levels at or below 80 g/L in the first 48 h after ICU admission are an alternative indicator for predicting long-term mortality of sepsis. Awareness should be encouraged of the importance of targeting early hemoglobin levels when treating sepsis to improve prognosis.
Molecular recognition at septin interfaces: the switches hold the key
Authors: Rosa Higor Vinícius Dias , Leonardo Diego Antonio , Brognara Gabriel , Brandão-Neto José , Pereira Humberto D’Muniz , Araújo Ana Paula Ulian , Garratt Richard Charles 
Published: July 2020

ABSTRACTThe assembly of a septin filament requires that homologous monomers must distinguish between one another in establishing appropriate interfaces with their neighbours. To understand this phenomenon at the molecular level, we present the first four crystal structures of heterodimeric septin complexes. We describe in detail the two distinct types of G-interface present within the octameric particles which must polymerize to form filaments. These are formed between SEPT2 and SEPT6 and between SEPT7 and SEPT3, and their description permits an understanding of the structural basis for the selectivity necessary for correct filament assembly. By replacing SEPT6 by SEPT8 or SEPT11, it is possible to rationalizeKinoshita’s postulatewhich predicts the exchangeability of septins from within a subgroup. Switches I and II, which in classical small GTPases provide a mechanism for nucleotide-dependent conformational change, have been repurposed in septins to play a fundamental role in molecular recognition. Specifically, it is switch I which holds the key to discriminating between the two different G-interfaces. Moreover, residues which are characteristic for a given subgroup play subtle, but pivotal, roles in guaranteeing that the correct interfaces are formed.HIGHLIGHTSHigh resolution structures of septin heterodimeric complexes reveal new interactionsSwitches of small GTPases are repurposed in septins to play key roles in interface contactsThe GTP present in catalytically inactive septins participates in molecular recognitionConservation of interface residues allows for subunit exchangeability from within septin subgroupsSpecific residues for each septin subgroup provide selectivity for proper filament assemblyGRAPHICAL ABSTRACT
RHEB/mTOR-hyperactivity causing cortical malformations drives seizures through increased axonal connectivity
Authors: Onori Martina Proietti , Koene Linda M.C. , Schafer Carmen B. , Nellist Mark , de Brito van Velze Marcel , Gao Zhenyu , Elgersma Ype , van Woerden Geeske M. 
Published: July 2020

ABSTRACTDominant-active mutations inRas Homolog Enriched in Brain 1(RHEB), such as the recently identified RHEBp.P37L mutation, can cause malformations of cortical development (MCD) with associated epilepsy and intellectual disability through a yet unknown mechanism. We found that focal expression of RHEBp.P37L in mouse somatosensory cortex results in an MCD-like phenotype, with increased mammalian target of rapamycin (mTOR) signaling, ectopic localization of neurons and generalized seizures. In addition, the RHEBp.P37L expressing neurons showed increased axonal length and branching. By temporally controlling RHEBp.P37L expression, we found that the cortical malformation by itself was neither necessary nor sufficient to generate seizures. Rather, seizures were contingent on persistent mTOR activation and enhanced axonal connectivity of RHEBp.P37L expressing neurons, causing hyperexcitability of distally connected neurons. These results provide new evidence of the extent of anatomical and physiological abnormalities caused by mTOR hyperactivity, beyond local malformations, that can lead to generalized epilepsy.
Oviposition of the mosquitoAedes aegyptiin forest and domestic habitats in Africa
Authors: Xia Siyang , Dweck Hany K. M. , Lutomiah Joel , Sang Rosemary , McBride Carolyn S. , Rose Noah H. , Ayala Diego , Powell Jeffrey R. 
Published: July 2020

AbstractThe theory of ecological divergence provides a useful framework to understand the adaptation of many species to anthropogenic (‘domestic’) habitats. The mosquitoAedes aegypti, a global vector of several arboviral diseases, presents an excellent study system.Ae. aegyptioriginated in African forests, but the populations that invaded other continents have specialized in domestic habitats. In its African native range, the species can be found in both forest and domestic habitats like villages. A crucial behavioral change between mosquitoes living in different habitats is their oviposition choices. ForestAe. aegyptilay eggs in natural water containers like tree holes, while their domestic counterparts heavily rely on artificial containers such as plastic buckets. These habitat-specific containers likely have different environmental conditions, which could drive the incipient divergent evolution of oviposition in AfricanAe. aegypti. To examine this hypothesis, we conducted field research in two African locations, La Lopé, Gabon and Rabai, Kenya, whereAe. aegyptilive in both forests and nearby villages. We first characterized a series of environmental conditions of natural oviposition sites, including physical characteristics, microbial density, bacterial composition, and volatile profiles. Our data showed that in both locations, environmental conditions of oviposition sites did differ between habitats. To examine potential behavioral divergence, we then conducted field and laboratory oviposition choice experiments to compare the oviposition preference of forest and village mosquitoes. The field experiment suggested that forest mosquitoes readily accepted artificial containers. In laboratory oviposition assays, forest and village mosquito colonies did not show a differential preference towards several conditions that featured forest versus village oviposition sites. Collectively, there is little evidence from our study that environmental differences lead to strong and easily measurable divergence in oviposition behavior betweenAe. aegyptithat occupy nearby forest and domestic habitats within Africa, despite clear divergence between African and non-AfricanAe. aegypti.
Genetic information insecurity as state of the art
Authors: Schumacher Garrett J. , Sawaya Sterling , King Demetrius , Hansen Aaron J. 
Published: July 2020

ABSTRACTGenetic information is being generated at an increasingly rapid pace, offering advances in science and medicine that are paralleled only by the threats and risk present within the responsible ecosystem. Human genetic information is identifiable and contains sensitive information, but genetic data security is only recently gaining attention. Genetic data is generated in an evolving and distributed cyber-physical ecosystem, with multiple systems that handle data and multiple partners that utilize the data. This paper defines security classifications of genetic information and discusses the threats, vulnerabilities, and risk found throughout the entire genetic information ecosystem. Laboratory security was found to be especially challenging, primarily due to devices and protocols that were not designed with security in mind. Likewise, other industry standards and best practices threaten the security of the ecosystem. A breach or exposure anywhere in the ecosystem can compromise sensitive information. Extensive development will be required to realize the potential of this emerging field while protecting the bioeconomy and all of its stakeholders.
A unifying concept of animal breeding programs
Authors: Simianer H. , Ganesan A. , Buettgen L. , Ha N.T. , Pook T. 
Published: July 2020

ABSTRACTModern animal breeding programs are constantly evolving with advances in breeding theory, biotechnology and genetics. Surprisingly, there seems to be no generally accepted succinct definition of what exactly a breeding program is, neither is there a unified language to describe breeding programs in a comprehensive, unambiguous and reproducible way. In this work, we try to fill this gap by suggesting a general definition of breeding programs that also pertains to cases where genetic progress is not achieved through selection, but e.g. through transgenic technologies, or the aim is not to generate genetic progress, but e.g. to maintain genetic diversity. The key idea of the underlying concept is to represent a breeding program in modular form as a directed graph that is composed of nodes and edges, where nodes represent cohorts of breeding units, usually individuals, and edges represent breeding activities, like ‘selection’ or ‘reproduction’. We claim, that by defining a comprehensive set of nodes and edges it is possible to represent any breeding program of arbitrary complexity by such a graph, which thus comprises a full description of the breeding program. This concept is implemented in a web-based tool (MoBPSweb, available atwww.mobps.de) which is described in a companion paper, and has a link to the R-package MoBPS (Modular Breeding Program Simulator) to simulate the described breeding programs. The approach is illustrated by showcasing three different breeding programs of increasing complexity. Finally, potential limitations of the concept are indicated and extensions to other fields, like plant breeding, are discussed.
X-ray structural analysis of single adult cardiomyocytes: tomographic imaging and micro-diffraction
Authors: Reichardt M. , Neuhaus C. , Nicolas J-D. , Bernhardt M. , Toischer K. , Salditt T. 
Published: July 2020

ABSTRACTWe present a multi-scale imaging approach to characterize the structure of isolated adult murine cardiomyocytes based on a combination of full-field three-dimensional (3d) coherent x-ray imaging and scanning x-ray diffraction. Using these modalities, we probe the structure from the molecular to the cellular scale. Holographic projection images on freeze-dried cells have been recorded using highly coherent and divergent x-ray waveguide radiation. Phase retrieval and tomographic reconstruction then yield the 3d electron density distribution with a voxel size below 50 nm. In the reconstruction volume, myofibrils, sarcomeric organisation and mitochondria can be visualized and quantified within a single cell without sectioning. Next, we use micro-focusing optics by compound refractive lenses to probe the diffraction signal of the acto-myosin lattice. Comparison between recordings of chemically fixed and untreated, living cells indicate that the characteristic lattice distances shrink by approximately 10% upon fixation.SIGNIFICANCEDiffraction with synchrotron radiation has played an important role to decipher the molecular structure underlying force generation in muscle. In this work, the diffraction signal of the actomyosin contractile unit has for the first time been recorded from living cardiomyocytes, bringing muscle diffraction to the scale of single cells. In addition to scanning diffraction, we use coherent optics at the same synchrotron endstation to perform holographic imaging and tomography on a single cardiomyocyte. By this hard x-ray microscopy modality, we extend the length scales covered by scanning diffraction and reconstruct the electron density of an entire freeze-dried cardiomyocyte, visualizing the 3d architecture of myofibrils, sarcomers, and mitochondria with a voxel size below 50 nm.
Investigation of cell nucleus heterogeneity
Authors: Reynolds Noel , McEvoy Eoin , Ghosh Soham , Pérez Juan Alberto Panadero , Neu Corey P. , McGarry Patrick 
Published: July 2020

AbstractNucleus deformation has been shown to play a key role in cell mechanotransduction and migration. Therefore, it is of wide interest to accurately characterize nucleus mechanical behavior. In this study we present the first computational investigation of the in-situ deformation of a heterogeneous cell nucleus. A novel methodology is developed to accurately reconstruct a three-dimensional finite element spatially heterogeneous model of a cell nucleus from confocal microscopy z-stack images of nuclei stained for nucleus DNA. The relationship between spatially heterogeneous distributions microscopic imaging-derived greyscale values, shear stiffness and resultant shear strain is explored through the incorporation of the reconstructed heterogeneous nucleus into a model of a chondrocyte embedded in a PCM and cartilage ECM. Externally applied shear deformation of the ECM is simulated and computed intra-nuclear strain distributions are directly compared to corresponding experimentally measured distributions. Simulations suggest that the nucleus is highly heterogeneous in terms of its mechanical behaviour, with a sigmoidal relationship between experimentally measure greyscale values and corresponding local shear moduli (μn). Three distinct phases are identified within the nucleus: a low stiffness phase (0.17kPa≤μn≤ 0.63kPa) corresponding to mRNA rich interchromatin regions; an intermediate stiffness phase (1.48kPa≤μn≤ 2.7kPa) corresponding to euchromatin; a high stiffness phase (3.58kPa≤μn≤ 4.0kPa) corresponding to heterochromatin. Our simulations indicate that disruption of the nucleus envelope associated with lamin-A/C depletion significantly increases nucleus strain in regions of low DNA concentration. A phenotypic shift of chondrocytes to fibroblast-like cells, a signature for osteoarthritic cartilage, results in a 35% increase in peak nucleus strain compared to control. The findings of this study may have broad implications for the current understanding of the role of nucleus deformation in cell mechanotransduction.
TranSynergy: Mechanism-Driven Interpretable Deep Neural Network for the Synergistic Prediction and Pathway Deconvolution of Drug Combinations
Authors: Liu Qiao , Xie Lei 
Published: July 2020

AbstractMotivationDrug combinations have demonstrated great potential in cancer treatments. They alleviate drug resistance and improve therapeutic efficacy. With the fast-growing number of anti-cancer drugs, the experimental investigation of all drug combinations is costly and time-consuming. Computational techniques can improve the efficiency of drug combination screening. Despite recent advances in applying machine learning to synergistic drug combinations prediction, several challenges remain. First, the performance of existing methods is suboptimal. There is still much space for improvement. Second, biological knowledge has not been fully incorporated into the model. Finally, many models are lack of interpretability, limiting their clinical applications.ResultsWe develop a knowledge-enabled and self-attention boosted deep learning model, TranSynergy, to improve the performance and interpretability of synergistic drug combinations prediction. TranSynergy is well designed such that cellular effect of drug actions can be explicitly modeled through cell-line gene dependency, gene-gene interaction, and genome-wide drug-target interaction. A novel Shapley Additive Gene Set Enrichment Analysis (SA-GSEA) method is developed to deconvolute biological pathways that contribute to the synergistic drug combination and improve model interpretability. Extensive benchmark studies demonstrate that TranSynergy significantly outperforms the state-of-the-art method, suggesting the potential of mechanism-driven machine learning. Novel pathways that are associated with the synergistic combinations are revealed and supported by experimental evidence. They may provide new insights into identifying biomarkers for precision medicine and discovering new anti-cancer therapies. Several new synergistic drug combinations are predicted with high confidence for ovarian cancer which has few treatment options.AvailabilityThe code is available athttps://github.com/qiaoliuhub/drug_combinationContactlxie@iscb.org
Learning the language of viral evolution and escape
Authors: Hie Brian , Zhong Ellen , Berger Bonnie , Bryson Bryan 
Published: July 2020

AbstractViral mutation that escapes from human immunity remains a major obstacle to antiviral and vaccine development. While anticipating escape could aid rational therapeutic design, the complex rules governing viral escape are challenging to model. Here, we demonstrate an unprecedented ability to predict viral escape by using machine learning algorithms originally developed to model the complexity of human natural language. Our key conceptual advance is that predicting escape requires identifying mutations that preserve viral fitness, or “grammaticality,” and also induce high antigenic change, or “semantic change.” We develop viral language models for influenza hemagglutinin, HIV Env, and SARS-CoV-2 Spike that we use to construct antigenically meaningful semantic landscapes, perform completely unsupervised prediction of escape mutants, and learn structural escape patterns from sequence alone. More profoundly, we lay a promising conceptual bridge between natural language and viral evolution.One sentence summaryNeural language models of semantic change and grammaticality enable unprecedented prediction of viral escape mutations.
Genetic, textual, and archaeological evidence of the historical global spread of cowpea (Vigna unguiculata[L.] Walp)
Authors: Herniter Ira A. , Muñoz-Amatriaín María , Close Timothy J. 
Published: July 2020

ABSTRACTCowpea (Vigna unguiculata[L.] Walp.) was originally domesticated in sub-Saharan Africa but is now cultivated on every continent except Antarctica. Utilizing archaeological, textual, and genetic resources, the spread of cultivated cowpea has been reconstructed. Cowpea was domesticated in Africa, likely in both West and East Africa, before 2500 BCE and by 400 BCE was long established in all the modern major production regions of the Old World, including sub-Saharan Africa, the Mediterranean Basin, India, and Southeast Asia. Further spread occurred as part of the Columbian Exchange, which brought African germplasm to the Caribbean, the southeastern United States, and South America, and Mediterranean germplasm to Cuba, the southwestern United States and Northwest Mexico.