bluuebunny/crossref_metadata_2025_split huggingface dataset:
The mechanism of grape seed oligomeric procyanidins in the treatment of experimental autoimmune encephalomyelitis mice
Authors: Xue Liyuan , Wang Qing , Ding Zhibin , Miao Qiang , Li Yanqing , Song Lijuan , Li Yanhua , Yu Jiezhong , Wang Yingli , Ma Cungen 
Published: March 2021

Abstract
Objective This study aims to investigate the mechanism of grape seed oligomeric procyanidins (GPC) in the treatment of experimental autoimmune encephalomyelitis (EAE) mice, providing pharmacodynamic materials for drug development in the treatment of multiple sclerosis (MS). Methods The constituents which have nerve protective effect in GPC were collected through literature retrieval. We used PharmMapper and STITCH database to predict drug targets, GeneCards and OMIM database to predict MS-related genes. Targets of GPC treating MS were obtained from intersected targets between drug and disease. The GO functional enrichment and KEGG pathway enrichment analysis were performed by DAVID database. EAE mouse model was used to study the therapeutic mechanism of GPC. Results Forty-two targets were discovered to be related to the process of GPC treating MS. KEGG enriched a total of 32 pathways. The pharmacological experiment showed that GPC improved the clinical symptoms of EAE mice, inhibited the expression of indicators of oxidative stress and inflammatory response in CNS, and decreased the expression of P-Akt, P-ERK, and P-JNK. Conclusion The therapeutic effect of GPC in EAE mice is associated with the suppression of MAPK and PI3K-Akt signaling pathways, providing a theoretical basis for the application of GPC inMS.
Medical decisions concerning the end of life for cancer patients in three Colombian hospitals – a survey study
Authors: de Vries Esther , Arenas Fabián Alexander Leal , Heide Agnes van der , Gempeler Fritz , Murillo Raul , Morales Olga , Diaz Eduardo , Rodríguez Nelcy , Gonzalez Beatriz Juliana , Delgado Danny Steven Castiblanco , Calvache José Andrés 
Published: March 2021

Abstract
Background: Cancer patients’ end-of-life care may involve complex decision-making processes. Colombia has regulations regarding palliative care and is the only Latin American country with legislation regarding euthanasia. We describe medical end-of-life decision-making practices among cancer patients in three Colombian hospitals.Methods: Attending physicians of 261 cancer patients in participating hospitals answered a questionnaire regarding end-of-life decisions: a.) decisions regarding the withdrawal or withholding of potentially life-prolonging medical treatments, b.) intensifying measures to alleviate pain or other symptoms with hastening of death as a potential side effect, and c.) the administration, supply or prescription of drugs with an explicit intention to hasten death. For each question addressing the first two decision types, we asked if the decision was (partially) made with the intention or consideration that it may hasten the patient’s death. Results: Decisions to withdraw potentially life-prolonging treatment were made for 112 (43%) patients, 16 of them (14%) with an intention to hasten death. For 198 patients (76%) there had been some decision to not initiate potentially life-prolonging treatment. Twenty-three percent of patients received palliative sedation, 97% of all patients received opioids. Six patients (2%) explicitly requested to actively hasten their death, for two of them their wish was fulfilled. In another six patients, medications were used with the explicit intention to hasten death without their explicit request. In 44% (n=114) of all cases, physicians did not know if their patient had any advance care directives, 26% (n=38) of physicians had spoken to the patient regarding the possibility of certain treatment decisions to hasten death where this applied. Conclusions: Decisions concerning the end of life were common for patients with cancer in three Colombian hospitals, including euthanasia and palliative sedation. Physicians and patients often fail to communicate about advance care directives and potentially life-shortening effects of treatment decisions. Specific end-of-life procedures, patients’ wishes and availability of palliative care should be further investigated.
Efficacy of eastern Australian rainforests and topography as fire refugia under anthropogenic climate change
Authors: Bennell Myles Jay , Stewart Philip Le C. , Moss Patrick T. 
Published: March 2021

Abstract
Background: The 2019-20 Australian bushfire season was the most environmentally detrimental bushfire season on record. The extreme heat and drought exposed normally fire-resistant communities to uncharacteristically dry fuel loads and abnormally high severity burning. In eastern Australia this included mesic rainforest environments (including the World Heritage listed Gondwana Rainforests of Australia), which are often highly sensitive to fire, contain high biodiversity values, are critical habitat for threatened species, embody distinct endemism, provide valuable ecosystem services and are critical for terrestrial carbon storage. East coast rainforests are also highly fragmented, with less than half of pre-European levels remaining. Increases in fire frequency and intensity associated with climate change may threaten these already fragmented rainforest environments. This study considers the efficacy of rainforest refugia under a heightened bushfire climate, via spatial analysis of burn extent, burn severity and topographic characteristics for rainforests during the 2019-20 bushfire season within the Eastern Australian Temperate and Subtropical Forests Conservation Management Zone.Results: Burn severity, vegetation and elevation datasets were merged and analysed across mid-eastern Australia. A significant portion of rainforest was fire affected across the study area (~17%), with ~5% burnt to a high or very high severity. Elevation, topographic position (i.e. valleys), slope and aspect all contributed to maintaining rainforest fire refugia. The study resulted in a mapping product that can be utilised by researchers and protected area managers to locate and assess burnt rainforest in mid-eastern Australia.Conclusions: This study enables the identification of rainforest fire refugia and threatened rainforest communities for future research and conservation efforts in eastern Australia. The results also demonstrate the potential of climate change to enact widespread rainforest declines, with potentially dire consequences for biodiversity and ecosystem services. This event and recurrent fire events may enact positive climate feedback systems by enabling pyrophytic vegetation expansion and converting rainforest carbon pools into a carbon source.
Condensates in RNA Repeat Sequences are Heterogeneously Organized and Exhibit Reptation-like Dynamics
Authors: Nguyen Hung , Hori Naoto , Thirumalai Dave 
Published: March 2021

Abstract
Although it is known that RNA undergoes liquid–liquid phase separation (LLPS), the interplay between the molecular driving forces and the emergent features of the condensates, such as their morphologies and dynamical properties, is not well understood. We introduce a coarse-grained model to simulate phase separation of trinucleotide repeat RNAs, which are implicated in neurological disorders such as Huntington disease and amyotrophic lateral sclerosis. After establishing that the simulations reproduce key experimental findings (length and concentration dependence of the phase transition in (CAG)n repeats), we show that once recruited inside the liquid droplets, the monomers transition from hairpin-like structures to extended states. Interactions between the monomers in the condensates result in the formation of an intricate and dense intermolecular network, which severely restrains the fluctuations and mobilities of the RNAs inside large droplets. In the largest densely packed high viscosity droplets, the mobility of RNA chains is best characterized by reptation, reminiscent of the dynamics in polymer melts.
Collision-induced amplitude dynamics of fast 2D solitons in the presence of the generic nonlinear loss
Authors: Huynh Toan , Quan Nguyen Minh 
Published: March 2021

Abstract
We study the amplitude dynamics of two-dimensional (2D) solitons in a fast collision described by the coupled nonlinear Schrödinger equations with a saturable nonlinearity and weak nonlinear loss. We extend the perturbative technique for calculating the collision-induced dynamics of two one-dimensional (1D) solitons to derive the theoretical expression for the collision-induced amplitude dynamics in a fast collision of two 2D solitons. Our perturbative approach is based on two major steps. The ﬁrst step is the standard adiabatic perturbation for the calculations on the energy balance of perturbed solitons and the second step, which is the crucial one, is for the analysis of the collision-induced change in the envelope of the perturbed 2D soliton. Furthermore, we also present the dependence of the collision-induced amplitude shift on the angle of the two 2D colliding-solitons. In addition, we show that the current perturbative technique can be simply applied to study the collision-induced amplitude shift in a fast collision of two perturbed 1D solitons. Our analytic calculations are conﬁrmed by numerical simulations with the corresponding coupled nonlinear Schrödinger equations in the presence of the cubic loss and in the presence of the quintic loss.
Molecular Mapping of QTLs for Fiber Quality Traits in Gossypium hirsutum Multi-parent Recombinant Inbred Lines
Authors: Doğanlar Sami , Baytar Asena Akköse , Peynircioğlu Ceng , Sezener Volkan , Frary Anne 
Published: March 2021

Abstract
Cotton is a valuable fiber crop which supplies raw material to more than 50 industries and is produced in more than 70 countries worldwide thus, it is worthy of its reputation as “white gold”. The superiority of cotton fiber over other crops is primarily dependent on its quality. However, further improvements in fiber length, strength and fineness are required for modern processing technology and for cotton to maintain its position in the global market. Association mapping enables identification of QTLs controlling fiber quality-related traits which can be useful in cotton breeding. In the present study, we performed genetic diversity, linkage disequilibrium and association mapping analyses in 157 G. hirsutum multi-parent recombinant inbred lines using a total of 102 SSR markers. The population had depressed genetic variability (14%), a result of inbreeding of modern cotton genotypes. Despite this, we identified 13 significant and stable marker-trait associations for seed cotton yield, lint percentage, fiber length, fiber strength and fiber fineness (p < 0.005). We also detected QTL co-localizations with positive and negative marker additive effects. Our results indicate that selection against negative alleles may be as important as selection for positive alleles. Analysis of the effects of allelic combinations at different QTLs revealed significant and stable marker clusters that can be selected for or against to provide maximum quality gains in cotton fiber quality.
Prospective Randomized Evaluation of Decompressive Ipsilateral Craniectomy for Traumatic Acute Epidural Hematoma (PREDICT-AEDH): study protocol for a randomized controlled trial
Authors: Yang Chun , Huang Xianjian , Feng Junfeng , Xie Li , Hui Jiyuan , Li Weiping , Jiang Jiyao 
Published: March 2021

Abstract
Background: Expeditiously surgical evacuation of acute epidural hematoma (AEDH) is an attainable gold standard and is often expected to have a good clinical outcome for patients with surgical indications. However, controversy exists on the optimal surgical treatment for AEDH, especially for patients with brain herniation. Neurosurgeons are confronted by the decision to evacuate the hematoma with decompressive craniectomy or craniotomy. Here, we present the protocol for a randomized controlled trial targeted at comparing the outcome and economic benefits of decompressive craniectomy versus craniotomy for the treatment of traumatic brain injury (TBI) patients with cerebral herniation undergoing evacuation of AEDH.Methods/design: Patients of both genders, aged from 18 to 65 years, presenting to the emergency room with a clinical and radiological diagnosis of AEDH with herniation, comply with other inclusion and exclusion criteria are enrolled. Clinical information, including diagnosis of AEDH, clinical radiological information and treatment procedures, follow-up data of 1, 3 and 6 months post injury are collected on 120 eligible patients, randomized into groups of decompressive craniectomy versus craniotomy in a 1:1 ratio among 51 centers. The primary outcome is the Glasgow Outcome Score-Extended (GOSE) at 6 months post-injury. Secondary outcomes include incidence of post-operative cerebral infarction, incidence of additional craniocerebral surgery, and other evaluation indicator within 6 months post-injury.Discussion: This study is expected to help neurosurgeons make a better decision to evacuate the epidural hematoma with or without a DC, especially for patients with brain herniation, and improve current situation of lack of general evidence.Trial registration: Clinicaltrials.gov: NCT 04261673 (Registration date: 04 February 2020)
Integrating social determinants of health screening and referral during routine emergency department care: Evaluation of reach and implementation challenges
Authors: Wallace Andrea S , Luther Brenda L. , Sisler Shawna M. , Wong Bob , Guo Jia-Wen 
Published: March 2021

Abstract
BackgroundDespite the importance of social determinants in health outcomes, little is known about best practices for screening and referral during clinical encounters. This study aimed to implement universal social needs screening and community service referrals in an academic emergency department (ED), evaluating for feasibility, reach, and stakeholder perspectives.MethodsBetween 01/2019-02/2020, ED registration staff screened patients for social needs using a 10-item, low literacy, English-Spanish screener on touchscreens that generated automatic referrals to a community service outreach specialists and data linkages. The RE-AIM framework guided evaluation. Reach was estimated through number of approaches, and completed screenings; effectiveness was estimated through receipt of community service referrals. Adoption was addressed qualitatively via content analysis and qualitative coding techniques from (1) meetings, clinical interactions, and semi-structured interviews with ED staff; and (2) an iterative “engagement studio” with an advisory group composed of ED patients representing diverse communities.ResultsOverall, 4608 participants were approached, and 61% completed the screener. The most common reason for non-completion was patient refusal (43%). 47% of patients with completed screeners communicated one or more needs, 34% of whom agreed to follow-up by resource specialists. Of the 482 participants referred, 20% were reached by outreach specialists and referred to community agencies. Only 7% of patients completed the full process from screening to community service referral; older, male, non-white, and Hispanic patients were more likely to complete the referral process.Iterative staff (n=8) observations and interviews demonstrated that, despite instruction for universal screening, patient presentation (e.g., appearance, insurance status) drove screening decisions. Staff communicated discomfort with, and questioned the need for, screening. Patients (n=10) communicated desire for improved understanding of their unmet needs, but had concerns about stigmatization and privacy, and communicated how receptivity of screenings and outreach are influenced by perceived sincerity of screening staff. ConclusionsDespite limited time and technical barriers, few patients with social needs ultimately received service referrals. Perspectives of staff and patients suggest that social needs screening during clinical encounters should incorporate structure for facilitating patient-staff relatedness and competence, and address patient vulnerability by ensuring universal, private screenings with clear intent. Trial registration: NCT04630041
Mechanistic modeling of pesticide uptake with a 3D plant architecture model
Authors: Jorda Helena , Huber Katrin , Kunkel Asta , Vanderborght Jan , Javaux Mathieu , Oberdörster Christoph , Hammel Klaus , Schnepf Andrea 
Published: March 2021

Abstract
A new root solute uptake model based on a lumped version of the Trapp model (Trapp, 2000) was implemented in a coupled version of R-SWMS-ParTrace models for 3-D water flow and solute transport in soil and roots. Solute uptake was modeled as two individual processes: advection with the transpiration stream and diffusion through the root membrane. We parameterized the model for a FOCUS scenario used in the European Union for pesticide registration. Simulation with a single root showed a good agreement with the results produced by the 1D PEARL model. Simulations with a complex root system predicted larger water uptake from the upper root zone, leading to larger pesticide uptake when pesticides are concentrated in the upper root zone. Dilution of root water concentrations at the top root zone with water with low pesticide concentration taken up from the bottom of the root zone lead to larger uptake of solute when uptake was simulated as a diffusive process. This illustrates the importance of modeling uptake mechanistically and considering root and solute physical and chemical properties, especially when root-zone pesticide concentrations are non uniform.
Screening for Idiopathic Pulmonary Fibrosis with Comorbid Pattern Recognition in Electronic Health Records
Authors: Chattopadhyay Ishanu , Onishchenko Dmytro , Hunninghake Gary , Martinez Fernando , Marlowe Robert 
Published: March 2021

Abstract
Idiopathic pulmonary fibrosis (IPF) is an irreversible, debilitating, and ultimately lethal fibrosing interstitial lung disease (ILD) of unknown cause. The poor prognosis of IPF (mean survival less than 2-5 years post diagnosis), combined with its worldwide prevalence greater than all but the most common cancers, makes it a serious health problem. Thus, the need for early diagnosis is paramount. Currently, early screening is hampered by the absence of reliable screening tools, non-specific symptomology, a limited understanding of the phenotypic and genetic markers for early-stage IPF, and the potential need for invasive procedures for confirmatory diagnosis. In this study we introduce a new screening tool that requires no new diagnostic tests, may be universally administered, and does not necessarily require recognition of early symptoms by the patients or care providers. Applying novel pattern discovery algorithms on the detailed history of past medical encounters of individual patients, we leverage subtle comorbidity patterns to compute the Zero-burden Co-Morbidity Risk Score for IPF (ZCoR-IPF), which is expected to be widely, readily, rapidly and inexpensively applicable at points of care. Our algorithm is trained and validated on a large national insurance claims database (n=2,059,559). In out-of-sample validation, we demonstrate that ZCoR-IPF identifies IPF patients with an AUC approaching 84% at 4 years, ~86% at 3 years, ~87% at 2 years, and exceeding >88% at 1 year before conventional diagnosis. Our out-of-sample accuracy indicates that on average, we correctly predict the eventual IPF status 94-98 out of every 100 patients, with a positive predictive value >50% irrespective of sex at a specificity of 99%. Maximum PPV and NPV achieved are >70% and ~98% respectively. We investigate several important sub-populations, including high risk patients with known IPF co-morbidities, low risk patients who lack those indications, in older (>65 years) and younger populations, in patients who already have a diagnosis of Chronic obstructive pulmonary disease (COPD), asthma or have cardiac disorders, and for patients who are never recorded to have experienced dyspnea and thus are at a higher risk of a missed diagnosis. High performance of the ZCoR-IPF score across clinically relevant situations suggests that it may aid providers to more selectively flag patients for detailed diagnostic evaluation, substantially improving patient outcomes and quality-of-life, as well as efficiency of healthcare resource utilization. Additionally, earlier diagnosis may improve the odds of disease modifying therapy, optimal timing of a lung transplantation, and accelerate access to interventions and palliative care.
Twentieth Century Precipitation Trends in the Upper Mzingwane Sub-catchment of the Northern Limpopo Basin, Zimbabwe
Authors: Maviza Auther , Grab Stefan , Engelbrecht Francois 
Published: March 2021

Abstract
This study evaluates precipitation trends in the upper Mzingwane sub-catchment (UMS) of Zimbabwe for the variables of annual precipitation, extremely wet days, consecutive wet days and consecutive dry days. The UMS is of strategic socio-economic significance in terms of its provision of water security and sustenance to livelihoods. The analysis is undertaken at four stations: Bulawayo Goetz, Filabusi, Mbalabala and Matopos National Park, and for the period 1921–2000. In general trends were found not to have local statistical significance, with the exception of the Matopos station (in the westernmost extent of UMS) which records significant increasing (declining) trends for most dryness (wetness) extreme indices. A general north to south-western declining precipitation gradient during the past ~ 69 years over the UMS was also found. The findings provide a baseline for future extended historical and future precipitation trend studies, and are important in the context of the socio-economic impacts of extreme events in this region.
Tool Remaining Useful Life Prediction Using Deep Transfer Reinforcement Learning Based on Long Short Term Memory Networks
Authors: Yao Jiachen , Lu Baochun , Zhang Junli 
Published: March 2021

Abstract
Tool wear and faults will affect the quality of machined workpiece and damage the continuity of manufacturing. The accurate prediction of remaining useful life (RUL) is significant to guarantee processing quality and improve productivity of automatic system. At present, the most methods for tool RUL prediction are trained by history fault data. However, when researching on new types of tools or processing high value parts, fault datasets are difficult to acquired, which led to RUL prediction a challenge under limited fault data. To overcome shortcomings of above prediction methods, a deep transfer reinforcement learning (DTRL) network based on long short term memory (LSTM) network is presented in this paper. Local features are extracted from consecutive sensor data to track the tool states, and the trained network size can be dynamically adjusted by controlling time sequence length. Then in DTRL network, LSTM network is employed to construct the value function approximation for smoothly processing temporal information and mining long-term dependencies. On this basis, a novel strategies of Q-function update and transfer are presented to transfer the DRL network trained by historical fault data to a new tool for RUL prediction. Finally, tool wear experiments are performed to validate effectiveness of the DTRL model. The prediction result demonstrate that the proposed method has high accuracy and generalization for similar tools and cutting conditions.