bluuebunny/crossref_metadata_2025_split huggingface dataset:
New insights on how and where to measure muscle mass
Authors: Fayh Ana Paula Trussardi , de Sousa Iasmin Matias , Gonzalez Maria Cristina 
Published: October 2020

Purpose of review
This article will discuss different muscle mass assessment methods and emphasize their highlights.

Recent findings
Several measurement techniques can be used to evaluate muscle mass, recognized as important prognostic markers for adverse functional and clinical outcomes. Choosing the best method depends on the knowledge regarding their theoretical and practical limitations and the purpose of the assessment. Image techniques are considered the gold standards, with good accuracy and precision, but not always available in clinical settings. A new biological technique, the D3-creatinine dilution, can provide not only direct information about muscle mass but also shows a strong association with physical function. With the advancement of the use of the computed tomography (CT) images to assess skeletal muscle mass, mainly in patients with cancer, the assessment of skeletal muscle radiodensity (SMD), as a marker of muscle quality, may provide additional information regarding the association between muscle composition, muscle function and prognosis. Additional muscle function assessment can improve the risk prediction in several clinical situations.

Summary
The use of the best tool for the muscle mass assessment should be performed carefully among the various methodologies, according to their characteristics and clinical situation.
Impact of a Web-Based Decisional Aid on Satisfaction in Women Undergoing Prolapse Surgery
Authors: Collins Sarah A. , Mueller Margaret G. , Geynisman-Tan Julia , Lewicky-Gaupp Christina , Kenton Kimberly 
Published: October 2020

Objectives
The objective of this study was to determine whether a computerized, condition-specific Decision Analysis Tool (DAT) for the surgical treatment of pelvic organ prolapse (POP) improves patient satisfaction and alters decision making.

Methods
Together with a health care startup company, we created a computerized DAT using the best evidence available on success rates and risks associated with sacrocolpopexy, native tissue apical suspension, and colpocleisis. Consecutively scheduled women before and after implementation of the DAT in an academic practice of 4 fellowship-trained, board-certified urogynecologists were included. The primary outcome was patient satisfaction using the Satisfaction with Decision Scale (SDS). Secondary outcomes included the Decision Regret Scale (DRS) questionnaire, differences in surgical choice, patient-reported outcomes, and individual SDS and DRS items. The SDS and DRS were administered at the 3-month postoperative visit.

Results
Forty-seven women before DAT implementation and 54 women after DAT implementation were included. There were no differences in SDS or DRS total scores (4.62 ± 0.66 vs 4.52 ± 0.72, P = 0.10 and 1.48 ± 0.79 vs 1.52 ± 0.82, P = 0.77) or individual question responses between groups. Women using the DAT were more likely to choose sacrocolpopexy than those who did not (76% vs 51%, P = 0.01). All 3 procedures led to similarly improved POP symptoms (P = 0.98), but those who underwent sacrocolpopexy had higher SDS scores compared with native tissue or colpocleisis patients (P = 0.01). Several individual SDS and DRS items were more favorable after sacrocolpopexy.

Conclusions
Women choosing surgery for POP are satisfied with their decision-making experiences with and without the assistance of a DAT. More women using a DAT, however, undergo sacrocolpopexy, which is associated with improved satisfaction.
Is Pisum sativum a good model species for the study of root responses to neighbours and barriers in soil? A bayesian hierarchical meta-analysis
Authors: Mobley Mariah L , Kruse Audrey S , McNickle Gordon G 
Published: October 2020

ABSTRACTPlant-plant competition is ubiquitous in nature. However, studying below ground behaviour of roots has always posed certain difficulties. Pea (Pisum sativum L.) has become a sort of model species for ecological studies about how plant roots respond to neighbouring plant roots and barriers in soil. However, published results point in several different directions. This has sometimes been interpreted as pea having sophisticated context dependent responses that can change in complex ways depending on its surroundings. To explore this further, here, we combine the result of five new experiments with published results to examine 18 unique experiments from 7 different studies for a total of 254 replicates. We used a Bayesian hierarchical meta-analysis approach to estimating the likely effect size from the available data, as well as quantify heterogeneity among different experiments, studies and cultivars. The posterior distributions show that, at the coarsest possible scale of total root production, it is unlikely that P. sativum root growth is influenced by either neighbours or barriers to root growth imposed by the walls of pots that vary in volume. We suggest that further work should consider repeating experiments that reported finer scale root plasticity in pea at the rhizosphere scale, and also consider alternative model species for the study of plant root responses to external cues.
Multisensory Configural Learning of a Home Refuge in the Whip SpiderPhrynus marginemaculatus
Authors: Flanigan Kaylyn AS , Wiegmann Daniel D , Hebets Eileen A , Bingman Verner P 
Published: October 2020

ABSTRACTWhip spiders (Amblypygi) reside in structurally complex habitats and are nocturnally active yet display notable navigational abilities. From the theory that uncertainty in sensory inputs should promote multisensory representations to guide behavior, we hypothesized that their navigation is supported by a configural, multisensory representation of navigational inputs, an ability documented in a few insects and never reported in arachnids. We trainedPhrynus marginemaculatusto recognize a home shelter characterized by both discriminative olfactory and tactile stimuli. In tests, subjects readily discriminated between shelters based on the paired stimuli. However, subjects failed to recognize the shelter in tests with either of the component stimuli alone. This result is consistent with the hypothesis that the terminal phase of their navigational behavior, shelter recognition, can be supported by the integration of multisensory stimuli as a configural representation. We hypothesize that multisensory configural learning occurs in the whip spiders’ extraordinarily large mushroom bodies, which may functionally resemble the hippocampus of vertebrates.
Determination of Bacterial Surface Charge Density Via Saturation of Adsorbed Ions
Authors: Wilhelm M.J. , Sharifian Gh. M. , Chang C.M. , Wu T. , Li Y. , Ma J. , Dai H.L. 
Published: October 2020

ABSTRACTBacterial surface charge is a critical characteristic of the cell’s interfacial physiology that influences how the cell interacts with the local environment. A direct, sensitive, and accurate experimental technique capable of quantifying bacterial surface charge is needed to better understand molecular adaptations in interfacial physiology in response to environmental changes. We introduce here the method of second harmonic light scattering (SHS) which is capable of detecting the number of molecular ions adsorbed as counter charges on the exterior bacterial surface, thereby providing a measure of the surface charge. In this first demonstration, we detect the small molecular cation, malachite green, electrostatically adsorbed on the surface of representative strains of Gram-positive and Gram-negative bacteria. Surprisingly, the SHS deduced molecular transport rates through the different cellular ultra-structures are revealed to be nearly identical. However, the adsorption saturation densities on the exterior surfaces of the two bacteria were shown to be characteristically distinct. The negative charge density of the lipopolysaccharide coated outer surface of Gram-negativeE. coli(8.7±1.7 nm−2) was deduced to be seven times larger than that of the protein surface layer of Gram-positiveL. rhamnosus(1.2±0.2 nm−2). The feasibility of SHS deduced bacterial surface charge density for Gram-type differentiation is presented.STATEMENT of SIGNIFICANCEBacterial surface charge density is an important physiological characteristic which determines how the cell interacts with its local environment. Directly measuring the surface charge density, however, is experimentally non-trivial. In this work, we report an experimental method, second harmonic light scattering, that can directly and accurately quantify the surface charge density of individual living bacteria. This is achieved by measuring the number of molecular ions electrostatically adsorbed on the exterior cellular surface as counter charges. It is found that the negative charge density of a representative Gram-negative bacterium is 7 times larger than a representative Gram-positive bacterium. It is suggested that this disparity of surface charge density can be exploited as a basis for Gram-classification of bacteria.
WITHDRAWN: ToxVec: Deep Language Model-Based Representation Learning for Venom Peptide Classification
Authors: Ahmadi Meisam , Jahed-Motlagh Mohammad Reza , Asgari Ehsaneddin , Torkaman Rahmani Adel , McHardy Alice C. 
Published: October 2020

WITHDRAWAL STATEMENTbioRxiv has withdrawn this manuscript as it was submitted and made public without the full consent of all the authors. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.
Transcriptional regulation ofSLIT2expression in pancreatic cancer cell lines
Authors: Rheinheimer Brenna A. , Vrba Lukas , Futscher Bernard W , Heimark Ronald L 
Published: October 2020

AbstractBackgroundSLIT2 has been shown to serve as a tumor suppressor in breast, lung, colon, and liver cancers. Additionally, expression of SLIT2 has been shown to be epigenetically regulated in prostate cancer. Therefore, we sought to determine transcriptional regulation of SLIT2 in pancreatic ductal adenocarcinoma.MethodsRNA expression of SLIT2, SLIT3, and ROBO1 was examined in a panel of pancreatic ductal adenocarcinoma cell lines while protein expression of ROBO1 and SLIT2 was examined in tumor tissue. Methylation of the SLIT2 promoter was determined using Sequenom while histone modifications were queried by chromatin immunoprecipitation. Reexpression of SLIT2 was tested by treatment with 5-aza-2’deoxycytidine and Trichostatin A.ResultsPancreatic cancer cell lines fall into three distinct groups based on SLIT2 and ROBO1 expression. The SLIT2 promoter is methylated in pancreatic ductal adenocarcinoma and SLIT2 expression is dependent on the level of methylation at specific CpG sites. Treatment with 5-aza-2’deoxycytidine (but not Trichostatin A) led to SLIT2 reexpression. The SLIT2 promoter is bivalent in pancreatic ductal adenocarcinoma and histone marks around the transcriptional start site are responsible for transcription.ConclusionsLoss of SLIT2 expression modulated by epigenetic silencing may play a role in pancreatic ductal adenocarcinoma progression.
Deep-fUS: Functional ultrasound imaging of the brain using deep learning and sparse data
Authors: Di Ianni Tommaso , Airan Raag D. 
Published: October 2020

AbstractFunctional ultrasound (fUS) is a rapidly emerging modality that enables whole-brain imaging of neural activity in awake and mobile rodents. To achieve sufficient blood flow sensitivity in the brain microvasculature, fUS relies on long ultrasound data acquisitions at high frame rates, posing high demands on the sampling and processing hardware. Here we develop an end-to-end image reconstruction approach based on deep learning that significantly reduces the amount of data necessary while retaining the imaging performance. We trained a convolutional neural network to learn the power Doppler reconstruction function from sparse sequences of ultrasound data with a compression factor up to 95%, using high-quality images fromin vivoacquisitions in rats. We tested the imaging performance in a functional neuroimaging application. We demonstrate that time series of power Doppler images can be reconstructed with sufficient accuracy to detect the small changes in cerebral blood volume (~10%) characteristic of task-evoked cortical activation, even though the network was not formally trained to reconstruct such image series. The proposed platform may facilitate the development of this neuroimaging modality in any setting where dedicated hardware is not available or in clinical scanners.
A Diaphanous and Enabled dependent asymmetric actin cable array repositions nuclei during Drosophila oogenesis
Authors: Logan Gregory , McCartney Brooke M. 
Published: October 2020

AbstractCells reposition their nuclei for a diversity of specialized functions through a wide variety of cytoskeletal mechanisms. To complete oogenesis, Drosophila nurse cells employ novel actin cable arrays to reposition their nuclei. During oogenesis, 15 nurse cells connected by ring canals contract to “dump” their cytoplasmic contents into the oocyte. Just prior to dumping, actin cables initiate from the nurse cell cortex and elongate toward their nuclei, pushing them away from the ring canals to prevent obstruction. How the actin cable arrays generate directional nuclear movement is not known. We found regional differences in the actin cable growth rate that are dependent on the differential localization of the actin assembly factors Enabled (Ena) and Diaphanous (Dia). Mislocalization of Ena resulted in actin cable arrays with a uniform growth rate. In the absence of growth rate asymmetry, nuclear relocation was significantly altered and cytoplasmic dumping was incomplete. This novel mechanism for nuclear repositioning relies on the regulated cortical localization of Dia and Ena producing asymmetric actin cable arrays that push the nuclei away from the ring canals, enabling successful oogenesis.Summary statementThis work demonstrates that an asymmetric actin cable array regulated by the differential localization of Diaphanous and Enabled is necessary to reposition nurse cell nuclei and complete oogenesis in Drosophila.
Exhaled aerosol increases with COVID-19 infection, and risk factors of disease symptom severity
Authors: Edwards David A. , Ausiello Dennis , Langer Robert , Salzman Jonathan , Devlin Tom , Beddingfield Brandon J. , Fears Alyssa C. , Doyle-Meyers Lara A. , Redmann Rachel K. , Killeen Stephanie Z. , Maness Nicholas J. , Roy Chad J. 
Published: October 2020

ABSTRACTCoronavirus disease-19 (COVID-19) transmits by droplets generated from surfaces of airway mucus during processes of respiration within hosts infected by severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) virus. We studied respiratory droplet generation and exhalation in human and nonhuman primate subjects with and without COVID-19 infection to explore whether SARS-CoV-2 infection, and other changes in physiological state, translates into observable evolution of numbers and sizes of exhaled respiratory droplets in healthy and diseased subjects. In our observational cohort study of the exhaled breath particles of 74 healthy human subjects, and in our experimental infection study of eight nonhuman primates infected by aerosol with SARS-CoV-2, we found that exhaled aerosol particles increase one to three orders of magnitude with aging, high BMI, and COVID-19 infection. These variances appear to be related to changes in airway mucus surface composition and the propensity for mucus surfaces to breakup into small droplets during acts of breathing. We also observed that 20% of those participating in our human study accounted for 80% of the overall exhaled bioaerosol, reflecting a bioaerosol distribution analogous to a classical 20:80 super spreader distribution.
Lineage-specific protection and immune imprinting shape the age distributions of influenza B cases
Authors: Vieira Marcos C. , Donato Celeste M. , Arevalo Philip , Rimmelzwaan Guus F. , Wood Timothy , Lopez Liza , Huang Q. Sue , Dhanasekaran Vijaykrishna , Koelle Katia , Cobey Sarah 
Published: October 2020

AbstractHow a history of influenza virus infections contributes to protection is not fully understood, but such protection might explain the contrasting age distributions of cases of the two lineages of influenza B, B/Victoria and B/Yamagata. Fitting a statistical model to those distributions using surveillance data from New Zealand, we found they could be explained by historical changes in lineage frequencies combined with cross-protection between strains of the same lineage. We found additional protection against B/Yamagata in people for whom it was their first influenza B infection, similar to the immune imprinting observed in influenza A. While the data were not informative about B/Victoria imprinting, B/Yamagata imprinting could explain the fewer B/Yamagata than B/Victoria cases in cohorts born in the 1990s and the bimodal age distribution of B/Yamagata cases. Longitudinal studies can test if these forms of protection inferred from historical data extend to more recent strains and other populations.
Bisphenol-S and Bisphenol-F alter mouse pancreatic β-cell ion channel expression and activity and insulin release through an estrogen receptor ERβ mediated pathway
Authors: Marroqui Laura , Martinez-Pinna Juan , Castellano-Muñoz Manuel , dos Santos Reinaldo S. , Medina-Gali Regla M. , Soriano Sergi , Quesada Ivan , Gustafsson Jan-Ake , Encinar José A. , Nadal Angel 
Published: October 2020

ABSTRACTBisphenol-S (BPS) and Bisphenol-F (BPF) are current Bisphenol-A (BPA) substitutes. Here we used pancreatic β-cells from wild type (WT) and estrogen receptor β (ERβ) knockout (BERKO) mice to investigate the effects of BPS and BPF on insulin secretion, and the expression and activity of ion channels involved in β-cell function. BPS or BPF rapidly increased insulin release and diminished ATP-sensitive K+(KATP) channel activity. Similarly, 48 h treatment with BPS or BPF enhanced insulin release and decreased the expression of several ion channel subunits in β-cells from WT mice, yet no effects were observed in cells from BERKO mice. PaPE-1, a ligand designed to preferentially trigger extranuclear-initiated ER pathways, mimicked the effects of bisphenols, suggesting the involvement of extranuclear-initiated ERβ pathways. Molecular dynamics simulations indicated differences in ERβ ligand-binding domain dimer stabilization and solvation free energy among different bisphenols and PaPE-1. Our data suggest a mode of action involving ERβ whose activation alters three key cellular events in β-cell, namely ion channel expression and activity, and insulin release. These results may help to improve the hazard identification of bisphenols.
Immunization by exposure to live virus (SIVmne/HIV-2287) during antiretroviral drug prophylaxis reduces risk of subsequent viral challenge
Authors: Frenkel LM , Kuller L , Beck IA , Tsai C-C , Joy JP , Mulvania TM , Montefiori DC , Anderson DM 
Published: October 2020

AbstractRationale/Study DesignA major challenge in the development of HIV vaccines is finding immunogens that elicit protection against a broad range of viral strains. Immunity to a narrow range of viral strains may protect infants of HIV-infected women or partners discordant for HIV. We hypothesized that immunization to the relevant viral variants could be achieved by exposure to infectious virus during prophylaxis with antiretroviral drugs. To explore this approach in an animal model, macaques were exposed to live virus (SIVmneor HIV-2287) during prophylaxis with parenteral tenofovir. The humoral and cellular immune responses were quantified. Subsequently, experimental animals were challenged with homologous virus to evaluate protection from infection, and if infection occurred, the course of disease was compared to control animals. Experimental animals uninfected with SIVmnewere challenged with heterologous HIV-2287to assess resistance to retroviral infection.Methodology/Principal FindingsJuvenileMacaca nemestrina(N=8) were given ten weekly intravaginal exposures with either moderately (SIVmne) or highly (HIV-2287) pathogenic virus during tenofovir prophylaxis. Tenofovir protected all 8 experimental animals from infection, while all untreated control animals became infected. Specific non-neutralizing antibodies were elicited in blood and vaginal secretions of experimental animals, but no ELISPOT responses were detected. Six weeks following the cessation of tenofovir, intravaginal challenge with homologous virus infected 2/4 (50%) of the SIVmne-immunized animals and 4/4 (100%) of the HIV-2287-immunized animals. The two SIVmne-infected and 3 (75%) HIV-2287-infected had attenuated disease, suggesting partial protection.Conclusions/SignificanceRepeated exposure to SIVmneor HIV-2287during antiretroviral prophylaxis blocked infection induced binding antibodies in the blood and mucosa, but not neutralizing antibodies or specific cellular immune responses. Studies to determine whether antibodies are similarly induced in breastfeeding infants and sexual partners discordant for HIV infection and receiving pre-exposure antiretroviral prophylaxis are warranted, including whether these antibodies appear to confer partial or complete protection from infection.
A deep learning framework for characterization of genotype data
Authors: Ausmees Kristiina , Nettelblad Carl 
Published: October 2020

ABSTRACTDimensionality reduction is a data transformation technique widely used in various fields of genomics research. The application of dimensionality reduction to genotype data is known to capture genetic similarity between individuals, and is used for visualization of genetic variation, identification of population structure as well as ancestry mapping. Among frequently used methods are PCA, which is a linear transform that often misses more fine-scale structures, and neighbor-graph based methods which focus on local relationships rather than large-scale patterns.Deep learning models are a type of nonlinear machine learning method in which the features used in data transformation are decided by the model in a data-driven manner, rather than by the researcher, and have been shown to present a promising alternative to traditional statistical methods for various applications in omics research. In this paper, we propose a deep learning model based on a convolutional autoencoder architecture for dimensionality reduction of genotype data.Using a highly diverse cohort of human samples, we demonstrate that the model can identify population clusters and provide richer visual information in comparison to PCA, while preserving global geometry to a higher extent than t-SNE and UMAP. We also discuss the use of the methodology for more general characterization of genotype data, showing that models of a similar architecture can be used as a genetic clustering method, comparing results to the ADMIXTURE software frequently used in population genetic studies.