bluuebunny/crossref_metadata_2025_split huggingface dataset:
Characterization of a novel, biofilm dispersing, lytic bacteriophage against drug-resistant Enterobacter cloacae
Authors: Nair Aparna , Vyawahare Renuka , Khairnar Krishna 
Published: December 2021

Abstract

Aim
To characterize a novel bacteriophage, En5822, isolated from the environment against Enterobacter cloacae and exploring its application as an alternate antimicrobial.

Methods and Results
Bacteriophage was isolated from sewage sample by membrane-filtration immobilization technique. It was purified and studied for its various physical properties like microscopic structure, thermal and pH stability, latent period and burst time, antimicrobial and anti-biofilm activity as well as molecular aspects by genome sequencing and analysis. En5822 is a myovirus with relative pH and thermal stability. En5822 shows a notable reduction of host bacterial biofilm as well as planktonic cultures. Whole genome sequence analysis revealed that the En5822 genome does not contain undesirable temperate lifestyle genes, antibiotic resistance genes and toxin-encoding genes.

Conclusions
En5822 displays high lytic activity, specificity and biofilm reduction capability. It has a short latent period and high burst size that aid faster activity. Its genomic and physical attributes offer possibilities for its as an alternative antimicrobial for the treatment of drug-resistant E. cloacae infections.

Significance and Impact of Study
The study describes a novel, naturally virulent bacteriophage from environment capable of lysing multi-drug resistant E. cloacae effectively. The phage could potentially serve as an alternative strategy for treating antibiotic-resistant infections.
Successful management of a large mucosal fenestration at 18‐months follow‐up
Authors: Yadav Vikender Singh , Gupta Vandana , Chawla Amrita , Tewari Nitesh , Yadav Renu 
Published: December 2021

AbstractObjectivesMucosal fenestrations are infrequent and often challenging to treat depending on the extent of soft and hard tissue destruction. This article presents the successful management of a relatively larger mucosal fenestration associated with complete absence of buccal bone plate in a mandibular incisor secondary to trauma‐induced periapical pathosis.Clinical considerationsAfter non‐surgical endodontic therapy, surgery was performed for debridement of the osseous defect, root resection/shaping, connective tissue graft (CTG) placement on the affected root surface and platelet rich fibrin (PRF) in periapical osseous defect rather than use of bone graft and/or barrier membrane. Healing was uneventful, however, a small mucosal defect remained at 2 weeks follow‐up. After 3 months of primary surgery, a corrective surgery was performed utilizing an “incision‐free” approach i.e. tunnel technique with CTG in contrast to the contemporary flap approach. At 18 months follow‐up, complete closure of the mucosal defect with a thick gingival biotype, normal sulcus depth, and good esthetic outcome were achieved. No recurrence and any clinical signs of infection or inflammation were observed.ConclusionsBased on the outcomes of present case, an early intervention utilizing the minimally invasive surgical therapy and autologous biomaterials may be considered a viable approach to treat such complex lesions.Clinical significanceEndodontic therapy in combination with PRF and CTG appears to provide successful outcomes in treatment of a large mucosal fenestration with periapical osseous defect.
Prolonged ethanol exposure modulates constitutive internalization and recycling of 5‐HT1A receptors
Authors: Wang Shiyu , Liu Haoran , Roberts Jonté B. , Wiley Aidan P. , Marayati Bahjat F. , Adams Kristen L. , Luessen Deborah J. , Eldeeb Khalil , Sun Haiguo , Zhang Ke , Chen Rong 
Published: December 2021

AbstractAlcohol exposure alters the signaling of the serotoninergic system, which is involved in alcohol consumption, reward, and dependence. In particular, dysregulation of serotonin receptor type 1A (5‐HT1AR) is associated with alcohol intake and withdrawal‐induced anxiety‐like behavior in rodents. However, how ethanol regulates 5‐HT1AR activity and cell surface availability remains elusive. Using neuroblastoma 2a cells stably expressing human 5‐HT1ARs tagged with hemagglutinin at the N‐terminus, we found that prolonged ethanol exposure (18 h) reduced the basal surface levels of 5‐HT1ARs in a concentration‐dependent manner. This reduction is attributed to both enhanced receptor internalization and attenuated receptor recycling. Moreover, constitutive 5‐HT1AR internalization in ethanol naïve cells was blocked by concanavalin A (ConA) but not nystatin, suggesting clathrin‐dependent 5‐HT1AR internalization. In contrast, constitutive 5‐HT1AR internalization in ethanol‐treated cells was blocked by nystatin but not by ConA, indicating that constitutive 5‐HT1AR internalization switched from a clathrin‐ to a caveolin‐dependent pathway. Dynasore, an inhibitor of dynamin, blocked 5‐HT1AR internalization in both vehicle‐ and ethanol‐treated cells. Furthermore, ethanol exposure enhanced the activity of dynamin I via dephosphorylation and reduced myosin Va levels, which may contribute to increased internalization and reduced recycling of 5‐HT1ARs, respectively. Our findings suggest that prolonged ethanol exposure not only alters the endocytic trafficking of 5‐HT1ARs but also the mechanism by which constitutive 5‐HT1AR internalization occurs.
image
Communication training programmes for informal caregivers of people living with dementia: A systematic review
Authors: Perkins Luke , Felstead Cerne , Stott Joshua , Spector Aimee 
Published: December 2021

AbstractAims and ObjectivesCurrent research suggests that communication training programmes for caregivers of people living with dementia can benefit both parties by improving communication, quality of life and stress. Previous reviews in this area focus on mixed samples of formal and informal caregivers. This review aimed to evaluate current research for trainings specifically for informal caregivers, including the research quality and the key training components.Design and MethodsThe review followed the PRISMA research reporting checklist. The electronic databases CINAHL, Embase, Medline and Psychinfo and reference lists of included literature were searched for studies relevant to the aims. Of the 45 identified studies, 36 were excluded based on pre‐specified criteria. Nine studies were included in the final review and subject to quality appraisal using the Qualsyst tool.ResultsThe included studies’ programmes averaged 5 to 6 hours in length over four to five sessions, were mostly face to face in both group and individual settings and were developed using various communication and psychological theories. Studies demonstrated variable quality and outcomes, making it difficult to identify optimal components. However, careful consideration of different factors enabled some suggestions for training dose, delivery method, content and outcomes to measure.ConclusionsCommunication training programmes can benefit people living with dementia and their informal caregivers in outcomes such as communication skills and quality of life. Suggestions are made on the training components that optimise these benefits.Relevance to clinical practiceGiven the clear benefits on outcomes such as quality of life, there is a need for communication trainings to be offered in clinical contexts. However, given the limited pool of variable quality research and lack of accessible manuals, it is unlikely that this is the case. Consolidating and widening the evidence through further research is essential in making these trainings more widely available.
Genetic variation of infection degrees to blast disease among rice genotypes
Authors: Hubballi Manjunath , Pandey Abhay K. , Giriyappa Rajesha 
Published: December 2021

AbstractThe blast of rice caused by Pyricularia oryzae is a disease prevalent throughout the world. The pathogen overwintering in rice straw and stubble for many years makes disease mitigation difficult. Among all available methods of managing disease, the use of resistant varieties is an economical approach. The objective of this study was to identify genotypes with slow‐blasting that could be used in breeding resistant hybrids. A total of 25 rice genotypes with different combinations of resistance genes were tested in 2013 and 2014 for rice blast resistance. The reactions of genotypes varied from highly resistant to highly susceptible. Of the 25 genotypes tested in 2013, only three were highly resistant to leaf blast (disease score: 1), while Rasi and RamanadStr3 were resistant (disease score: 2). Genotypes Co39 and HR12 were highly susceptible recording a disease score of 8 and the remaining genotypes were classified as susceptible with scores ranging from 5 to 7. In 2014, only Tetep genotype was found highly resistant to leaf blast with disease score ‘1’, and genotypes NILA57, RamanadStr3, Shia‐tia‐tsao, IR64, Rasi, and Tadukan were resistant with disease scores ranging from 2 to 3. The remaining genotypes were susceptible to leaf blast with disease scores of 4–7 and two genotypes Co39 and HR12 were highly susceptible to leaf blast (disease scores: 8–9). For neck blast, all genotypes were resistant (disease scores: 0–3) in both years except for CO39 and HR12, which were recorded as moderately resistant in 2013 and resistant in 2014. Based on 2 years of data on the apparent rate of infection, area under the disease progress curve, and components of slow‐blasting, the genotypes viz., IR64, Tadukan, Rasi, Tetep, and RamanadStr3 were identified as slow‐blasting types. Hence, these genotypes can be harnessed to develop blast‐resistant varieties in rice breeding programmes.
Body composition correlates with laboratory parameters and disease severity in infants with biliary atresia
Authors: Marderfeld Luba , Waisbourd‐Zinman Orith , Biran Neta , Rozenfeld Bar‐Lev Michal , Silbermintz Ari , Poraz Irit , Reznik Dana , Jack Yifat , Mozer Glassberg Yael , Shamir Raanan 
Published: December 2021

AbstractAimInfants with biliary atresia (BA) generally have chronic malnutrition. However, the best anthropometric measure to assess malnutrition and its correlation with disease severity is unknown. We aimed to assess correlations of various anthropometric measurements, including air displacement plethysmography (ADP), with laboratory parameters and with the pediatric end‐stage liver disease (PELD) score in infants with BA.MethodsInfants with BA were followed at a pediatric liver transplantation center during 2014–2018. Follow‐up comprised laboratory tests and nutritional assessment by a dietitian including dietary intake, weight, height, mid‐upper arm circumference (MUAC), and skin‐fold thickness. Fat‐free mass (FFM) and fat mass (FM) were measured by ADP.ResultsForty‐three nutritional evaluations were performed in 28 infants with BA (13 boys, 44.4%). The median age was 20.7 weeks (IQR: 13–25.9). Based on the various anthropometry modalities, infants with BA were found to be malnourished on most of the visits; 63% had a MUAC‐Z score lower than −2 standard deviations. High serum bilirubin level predicted lower weight for age, length for age, and MUAC‐Z. Lower MUAC‐Z was associated with a higher PELD score. Neither FM mass nor FFM correlated with PELD or with serum bilirubin level. However, FM correlated with skin‐fold thickness‐Z and was low in most patients.ConclusionsThe majority of BA infants suffer from malnutrition as assessed by most anthropometrics modalities; low MUAC correlated best with disease severity and serum bilirubin level. Further studies are warranted to determine the contribution of FM measurement by ADP to the anthropometric assessment of infants with BA.
Robust Predictive Energy Management of Connected Power-Split Hybrid Electric Vehicles Using Dynamic Traffic Data
Authors: Sotoudeh Seyedeh Mahsa , HomChaudhuri Baisravan 
Published: December 2021

Abstract
This research focuses on the predictive energy management of connected human-driven hybrid electric vehicles (HEVs) to improve their fuel efficiency while robustly satisfying system constraints. We propose a hierarchical control framework that effectively exploits long-term and short-term decision-making benefits by integrating real-time traffic data into the energy management strategy. A pseudo-spectral optimal controller (PSOC) with discounted cost is utilized at the high level to find an approximate optimal solution for the entire driving cycle. At the low-level, a long short-term memory neural network (NN) is developed for higher quality velocity predictions over the low-level's short time horizons. Tube-based model predictive controller is then used at the low level to ensure constraints satisfaction in the presence of velocity prediction errors. Simulation results over real-world traffic data show an improvement in fuel economy for the proposed controller that is real-time applicable and robust to the driving cycle's uncertainty.
Real-Time Ecodriving Control in Electrified Connected and Autonomous Vehicles Using Approximate Dynamic Programing
Authors: Deshpande Shreshta Rajakumar , Gupta Shobhit , Gupta Abhishek , Canova Marcello 
Published: December 2021

Abstract
Connected and automated vehicles (CAVs), particularly those with a hybrid electric powertrain, have the potential to significantly improve vehicle energy savings in real-world driving conditions. In particular, the ecodriving problem seeks to design optimal speed and power usage profiles based on available information from connectivity and advanced mapping features to minimize the fuel consumption over an itinerary. This paper presents a hierarchical multilayer model predictive control (MPC) approach for improving the fuel economy of a 48 V mild-hybrid powertrain in a connected vehicle environment. Approximate dynamic programing (DP) is used to solve the receding horizon optimal control problem, whose terminal cost is approximated with the base policy obtained from the long-term optimization. The controller was tested virtually (with deterministic and Monte Carlo simulation) across multiple real-world routes, demonstrating energy savings of more than 20%. The controller was then deployed on a test vehicle equipped with a rapid prototyping embedded controller. In-vehicle testing confirm the energy savings obtained in simulation and demonstrate the real-time ability of the controller.
Survey Use to Validate Engineering Methodology and Enhance System Safety
Authors: Corrado Jonathan K. 
Published: December 2021

Abstract
Surveys and the resulting data provide powerful insights to an item or concept being assessed. Not only do they garner feedback that can be used to enhance the item, but, in the instance of this article, they can enhance the validity of positive change via novel concepts prior to spending the time and money in incorporating these concepts and running the risk of negligible meaningful return. In an effort to ensure the validity of proposed novel methods in a design engineering context, a survey was developed and administered to engineering subject matter experts. This was done to not only ensure that the proposed methods would be viable if implemented but gave confidence in the results of the research that drove the method development. This assessment activity served as a risk reduction activity to ensure smooth implementation of the methods from both an efficiency standpoint and, most importantly, as part of maximizing system safety. This paper discusses the composition and considerations of the survey administered in the research study, in addition to the survey results with the intention of providing a format for others in a similar context to glean from and, if practical, replicate the method.
Neural Network-Based Electric Vehicle Range Prediction for Smart Charging Optimization
Authors: Eagon Matthew J. , Kindem Daniel K. , Panneer Selvam Harish , Northrop William F. 
Published: December 2021

Abstract
Range prediction is a standard feature in most modern road vehicles, allowing drivers to make informed decisions about when to refuel. Most vehicles make range predictions through data- or model-driven means, monitoring the average fuel consumption rate or using a tuned vehicle model to predict fuel consumption. The uncertainty of future driving conditions makes the range prediction problem challenging, particularly for less pervasive battery electric vehicles (BEV). Most contemporary machine learning-based methods attempt to forecast the battery SOC discharge profile to predict vehicle range. In this work, we propose a novel approach using two recurrent neural networks (RNNs) to predict the remaining range of BEVs and the minimum charge required to safely complete a trip. Each RNN has two outputs that can be used for statistical analysis to account for uncertainties; the first loss function leads to mean and variance estimation (MVE), while the second results in bounded interval estimation (BIE). These outputs of the proposed RNNs are then used to predict the probability of a vehicle completing a given trip without charging, or if charging is needed, the remaining range and minimum charging required to finish the trip with high probability. Training data was generated using a low-order physics model to estimate vehicle energy consumption from historical drive cycle data collected from medium-duty last-mile delivery vehicles. The proposed method demonstrated high accuracy in the presence of day-to-day route variability, with the root-mean-square error (RMSE) below 6% for both RNN models.
Enabling Artificial Intelligence Studies in Off-Road Mobility Through Physics-Based Simulation of Multiagent Scenarios
Authors: Young Aaron , Taves Jay , Elmquist Asher , Benatti Simone , Tasora Alessandro , Serban Radu , Negrut Dan 
Published: December 2021

AbstractWe describe a simulation environment that enables the design and testing of control policies for off-road mobility of autonomous agents. The environment is demonstrated in conjunction with the training and assessment of a reinforcement learning policy that uses sensor fusion and interagent communication to enable the movement of mixed convoys of human-driven and autonomous vehicles. Policies learned on rigid terrain are shown to transfer to hard (silt-like) and soft (snow-like) deformable terrains. The environment described performs the following: multivehicle multibody dynamics cosimulation in a time/space-coherent infrastructure that relies on the Message Passing Interface standard for low-latency parallel computing; sensor simulation (e.g., camera, GPU, IMU); simulation of a virtual world that can be altered by the agents present in the simulation; training that uses reinforcement learning to “teach” the autonomous vehicles to drive in an obstacle-riddled course. The software stack described is open source. Relevant movies: Project Chrono. Off-road AV simulations, 20202.
Support needs of carers making proxy healthcare decisions for people with dementia: a systematic review based on the Noblit and Hare meta-ethnographic synthesis of qualitative studies
Authors: Hodges Victoria , Hynes Catherine , Lassa Samuel , Mitchell Caroline 
Published: December 2021

BackgroundThere are 50 million dementia sufferers worldwide. Decisions about healthcare often need to be made when the person with dementia lacks capacity to do so.Understanding the support needs of carers acting as proxy healthcare decision-makers will be vital in improving the decision-making process for people with dementia and addressing the holistic needs of carers.ObjectiveThe objective of this study was to review the existing literature on the support needs of carers acting as proxy healthcare decision-makers for people with dementia.DesignA qualitative systematic review protocol was published on PROSPERO. The Critical Appraisal Skills Programme checklist was used to appraise study quality. A meta-ethnographic synthesis was performed to develop third-order constructs.Data sourcesA search was conducted using three online databases (MEDLINE, CINAHL and PsycINFO).Eligibility criteriaFifteen studies met the inclusion criteria: primary qualitative research involving carers of people with dementia who had been involved in making proxy healthcare decisions.Data extraction and synthesisTwo independent researchers conducted validity assessments for each paper selected for inclusion, and discrepancies were resolved by discussions with a third reviewer. Nvivo software was used and conceptual findings from study papers lead to interpretations of findings by the team.ResultsFrom the 15 papers included in the study, three main domains arose from the meta-ethnography; informational, practical and emotional. Informational support needs included information about dementia itself and the anticipated disease trajectory. Practical needs included continuity of care, person-centred care and the use of legal frameworks.Emotional support included recognising the guilt that healthcare decisions can provoke and the importance of providing guidance in an empathic manner.ConclusionsThis meta-ethnography highlights opportunities for healthcare professionals and policymakers to improve experiences of carers making proxy healthcare decisions for people with dementia.PROSPERO registration numberCRD42020124485.
Focused educational intervention improves intern knowledge of perioperative patient blood management principles
Authors: Wyssusek Kerstin , Taylor Kate , Concha-Blamey Sandra 
Published: December 2021

A perioperative patient blood management (PBM) educational intervention was implemented for first year postgraduate doctors (interns) at the Royal Brisbane and Women’s Hospital (RBWH) following identification of a perioperative PBM training requirement. This quality improvement activity evaluated the effectiveness of this educational intervention in improving intern knowledge of perioperative PBM principles.A 15-question perioperative PBM focused multiple choice questionnaire developed from information attained from comprehensive, evidence and consensus-based guidelines regarding PBM practice was distributed to interns immediately before a compulsory perioperative PBM educational intervention and then again 5 weeks later. The perioperative PBM educational intervention was delivered every 10 weeks (five interventions in total) to a different group of interns each time. Statistical analysis determined significance between mean questionnaire score before and after the intervention.The mean pre-intervention score for correctly answered questions was 7/15 (SD 2.73) and mean post-intervention score was 9/15 (SD 2.99) (p=0.02). Categorisation of questions into core domains of perioperative PBM demonstrated intern scores for correctly answered questions improved in all domains following the educational intervention.Perioperative PBM education delivered through a dedicated intervention aimed to improve knowledge is associated with objective evidence of educational benefits for interns at RBWH. It is an effective strategy to enact PBM governance and bestow clinical guideline knowledge. This is important given the global health sector’s challenge to improve patient outcomes despite increasingly restricted funding and pressure on doctors to devote more time to service and less to teaching.