bluuebunny/crossref_metadata_2025_split huggingface dataset:
Procalcitonin for sepsis management: Implementation within an antimicrobial stewardship program
Authors: Fugit Randolph V , McCoury John B , Bessesen Mary T 
Published: November 2022

Abstract

Purpose
Clinical trials of procalcitonin (PCT)–based algorithms for antibacterial therapy have shown a reduction in antimicrobial use and improved survival. Translation of PCT algorithms to clinical settings has often been unsuccessful. We hypothesized that appropriate utilization of PCT could be improved by implementing an antimicrobial stewardship team (AST) approach to PCT testing.

Methods
We completed a pre-post intervention evaluation of adult patients admitted to the intensive care unit with a diagnosis of sepsis. The standard PCT algorithm period (SPAP) cohort included patients enrolled before dedicated AST involvement. During the AST-supported PCT algorithm period (ASPAP), the AST reviewed and provided feedback for all appropriate patients. The primary outcome was adherence to the PCT algorithm.

Results
Thirty-five and 57 patients were evaluated in the SPAP and ASPAP cohorts, respectively. There were no differences in demographics or infection site between the groups. Baseline PCT assessment was ordered in a larger proportion of patients in the ASPAP cohort (90% vs 57%; P = 0.0006). Follow-up PCT measurement was performed in more patients in the ASPAP cohort (76% vs 23%; P &lt; 0.0001). Antibiotics were discontinued per algorithm in more patients in the ASPAP cohort (25/57 [44%] vs 2/35 [7%]; P &lt; 0.0001). Patients in the ASPAP cohort experienced a shorter total duration of antibiotics (5 vs 7 days; P = 0.02), with no significant difference in length of stay or 30-day readmission or mortality between the cohorts.

Conclusion
A PCT algorithm successfully implemented by an AST was associated with a significant decrease in total antibiotic days with no differences in mortality or length of stay.
Description and financial impact of ambulatory care pharmacy team interventions within an underserved patient population
Authors: Hasham Salman , Moye-Dickerson Pamela , Thurston Maria Miller 
Published: November 2022

AbstractPurposeThe purpose of this study was to characterize and quantify the types of interventions made by an ambulatory care pharmacy team (ACPT), evaluate the financial impact of such interventions, and create a cost template for the interventions using the health system’s intervention documentation system.SummaryWe conducted a retrospective, single-center cohort study covering the period from July 1, 2018, to June 30, 2020. Eligible participants included patients aged 18 years or older who had an appointment at the ambulatory care clinic and received a pharmacy consult. Most patients were uninsured. Data collected included intervention types, specific interventions, the economic impact per intervention, the average cost avoidance per intervention, the total economic impact, and the total cost avoidance. The ACPT documented a total of 1,334 interventions during the 2-year study period. The 4 major categories of interventions included patient counseling, drug utilization review, medication therapy management, and drug information. Each category was further subdivided into subcategories, for a total of 18 distinct subcategories. The economic impact per intervention was approximately $30. The average cost avoidance was estimated to be $357.62 per intervention, with a total economic impact of $40,020 and cost avoidance of $477,065 for the study period.ConclusionPharmacist interventions resulted in a significant amount of economic impact and cost avoidance for the health system. Using the data from the study, we created a cost estimate to indicate the value of each ambulatory care intervention by using the health system’s intervention documentation system.
Mechanical scarification can reduce competitive traits of boreal ericaceous shrubs and improve nutritional site quality
Authors: Reicis Krista , Bradley Robert L , Joanisse Gilles , Thiffault Nelson , Scott Dalton , Parsons William F J 
Published: November 2022

Abstract Ericaceous shrubs often interfere with the growth of black spruce seedlings on regenerating forest sites in Eastern Canada. Mechanical site preparation such as scarification may improve this situation, but it is uncertain whether this is solely due to a reduction in direct competition from the shrubs, or also from a sustained improvement in nutritional site quality. We sampled experimental plots in two boreal climate regions (i.e. warmer-drier Abitibi vs. cooler-wetter Côte-Nord) where scarification, performed 18 years earlier, had increased the growth of black spruce relative to non-scarified plots. Trees of scarified plots had closed the canopy more than trees of non-scarified plots in Côte-Nord, but not in Abitibi. Total ground cover of ericaceous shrubs was lower in scarified plots at both sites, the main species being Kalmia angustifolia (i.e. Kalmia) in Abitibi and Rhododendron groenlandicum (i.e. Labrador tea) in Côte-Nord. Scarified plots at both sites had significantly shorter current-year ericaceous rhizomes than non-scarified plots, but the difference between treatments was significantly greater in Côte-Nord than in Abitibi. In Côte-Nord, ericaceous shrubs on scarified plots had a lower specific rhizome mass, higher specific leaf area, lower tannin and higher N concentrations in leaves and litter, and lower N use efficiency than on non-scarified plots. By comparison, scarification in Abitibi affected only one foliar property, namely a reduction in the C:N ratio of Kalmia leaf litter. Forest floor N mineralization rates and black spruce needle N concentrations were higher in scarified than non-scarified plots across both sites. Taken collectively, results suggest that mechanical scarification on ericaceous shrub-dominated cutovers can reduce competitive traits of boreal ericaceous shrubs and improve nutritional site quality, especially in cooler-wetter climates.Highlights
A qualitative evaluation of priority-setting by the Health Benefits Package Advisory Panel in Kenya
Authors: Mbau Rahab , Oliver Kathryn , Vassall Anna , Gilson Lucy , Barasa Edwine 
Published: November 2022

Abstract
Kenya’s Ministry of Health established the Health Benefits Package Advisory Panel (HBPAP) in 2018 to develop a benefits package for universal health coverage. This study evaluated HBPAP’s process for developing the benefits package against the normative procedural (acceptable way of doing things) and outcome (acceptable consequences) conditions of an ideal healthcare priority-setting process as outlined in the study’s conceptual framework. We conducted a qualitative case study using in-depth interviews with national-level respondents (n = 20) and document reviews. Data were analysed using a thematic approach. HBPAP’s process partially fulfilled the procedural and outcome conditions of the study’s evaluative framework. Concerning the procedural conditions, transparency and publicity were partially met and were limited by the lack of publication of HBPAP’s report. While HBPAP used explicit and evidence-based priority-setting criteria, challenges included lack of primary data and local cost-effectiveness threshold, weak health information systems, short timelines and political interference. While a wide range of stakeholders were engaged, this was limited by short timelines and inadequate financial resources. Empowerment of non-HBPAP members was limited by their inadequate technical knowledge and experience in priority-setting. Finally, appeals and revisions were limited by short timelines and lack of implementation of the proposed benefits package. Concerning the outcome conditions, stakeholder understanding was limited by the technical nature of the process and short timelines, while stakeholder acceptance and satisfaction were limited by lack of transparency. HBPAP’s benefits package was not implemented due to stakeholder interests and opposition. Priority-setting processes for benefits package development in Kenya could be improved by publicizing the outcome of the process, allocating adequate time and financial resources, strengthening health information systems, generating local evidence and enhancing stakeholder awareness and engagement to increase their empowerment, understanding and acceptance of the process. Managing politics and stakeholder interests is key in enhancing the success of priority-setting processes.
Low-carbon supply chain operations: impacts of carbon tax and fairness concerns
Authors: Shi Song 
Published: November 2022

AbstractUnder a carbon tax, this study established game theory models of a low-carbon supply chain to investigate the effects of fairness and carbon tax rate on the retail price and on carbon emission reduction level, as well as on the profits of the manufacturer, retailer and the whole supply chain. Results show that the carbon emission reduction level and the supply chain profit under a centralized supply chain are both higher than those under a decentralized supply chain, if the manufacturer’s fairness concern, the carbon emission reduction level and the supply chain profit will further decrease, but manufacturers’ profits are taking a growing share of the supply chain’s total profits. Under three different modes, the carbon emission reduction level will increase with the increase of the carbon coefficient. The retail price and the supply chain profit are jointly determined by the carbon tax rate and the carbon coefficient. Moreover, the implementation of a carbon reduction investment cost-sharing contract can increase the demand of low-carbon products and reduce the retail price. Under a carbon tax, regardless of whether manufacturers pay attention to fairness, the carbon reduction investment cost-sharing contract can effectively improve the overall efficiency of the low-carbon supply chain.
A learning scheme by sparse grids and Picard approximations for semilinear parabolic PDEs
Authors: Chassagneux Jean-François , Chen Junchao , Frikha Noufel , Zhou Chao 
Published: November 2022

Abstract
Relying on the classical connection between backward stochastic differential equations and nonlinear parabolic partial differential equations (PDEs), we propose a new probabilistic learning scheme for solving high-dimensional semilinear parabolic PDEs. This scheme is inspired by the approach coming from machine learning and developed using deep neural networks in Han et al. (2018, Solving high-dimensional partial differential equations using deep learning. Proc. Natl. Acad. Sci., 115, 8505–8510. Our algorithm is based on a Picard iteration scheme in which a sequence of linear-quadratic optimization problem is solved by means of stochastic gradient descent algorithm. In the framework of a linear specification of the approximation space, we manage to prove a convergence result for our scheme, under some smallness condition. In practice, in order to be able to treat high-dimensional examples, we employ sparse-grid approximation spaces. In the case of periodic coefficients and using pre-wavelet basis functions, we obtain an upper bound on the global complexity of our method. It shows, in particular, that the curse of dimensionality is tamed in the sense that in order to achieve a root mean squared error of order $\varepsilon $, for a prescribed precision $\varepsilon $, the complexity of the Picard algorithm grows polynomially in $\varepsilon ^{-1}$ up to some logarithmic factor $|\!\log (\varepsilon )|$, whose exponent grows linearly with respect to the PDE dimension. Various numerical results are presented to validate the performance of our method, and to compare them with some recent machine learning schemes proposed in E et al. (2017, Deep learning-based numerical methods for high-dimensional parabolic partial differential equations and backward stochastic differential equations. Commun. Math. Stat., 5, 349–380) and Huré et al. (2020, Deep backward schemes for high-dimensional nonlinear PDEs. Math. Comput., 89, 1547–1579).
Nonlinear model fitting analysis of feather growth and development curves in the embryonic stages of Jilin white geese (Anser cygnoides)
Authors: Wang Yudong , Fu Xianou , Wang Sihui , Mabrouk Ichraf , Zhou Yuxuan , Song Yupu , Liu Tuoya , Ma Jingyun , Zhuang Fangming , Zhang Xue , Xu Keyi , Sun Yongfeng 
Published: November 2022

Abstract
Poultry is subject to varying degrees of feather loss and feather pecking during production, which seriously affects the live appearance and carcass appearance of their commercial traits and greatly reduces the production profitability of the farming enterprise. It also has an impact on down production and quality in the case of geese. In this study, mathematical models (Logistic, Gompertz, and Von Bertalanffy) were used to assess feather growth and development during the embryonic period in Jilin white geese (Anser cygnoides) predicting the weight and length of feathers from the back, chest, and belly tracts at different embryonic ages, to determine which growth model more accurately described feather growth patterns. The result first showed that the primary feather follicles of the Jilin white goose developed at E14 and secondary feather follicles at E18; primary feather follicle density increased and then decreased, whereas secondary feather follicle density increased continuously and the primary and secondary feather follicles developed independently. Secondly, the embryonic feather growth followed a slow–fast–slow pattern, with feathers growing slowly from E12 to E18, quickly from E18 to E24, and then decreasing after E24 until just before emergence (E30). In addition, before E14, feathers were concentrated in the back tracts, and no feathers were found on the head, neck, chest, abdomen, or wings. By E22, the whole body of the embryo was covered with feathers, and the back feathers were the earliest and fastest to develop. Compared to the Gompertz and von Bertalanffy models, the logistic model fit (R2 = 0.997) was the highest, while the sum of residual squares (RSS = 25661.67), Akaike’s information criterion (AIC = 77.600), Bayesian information criterion (BIC = 78.191), and mean square error (MSE = 2851.296) were the lowest. Therefore, the logistic model was more suitable for describing the changes in whole-body feather growth during the embryonic period in Jilin white geese. In conclusion, using the growth curve model to explain the relationship between feather growth and embryonic age in geese will potentially speed up the process of genetic improvement in Jilin white geese (A. cygnoides) and thus provide scientific support for molecular genetic breeding.
An In silico study of derivative of Newcastle disease virus epitopes based vaccine against Hemagglutunin neuraminidase protein
Authors: Jamil Farrukh , Aslam Laiba , Laraib  , Ali Hira , Shoukat Kainaat , Rasheed Muhammad Asif , Raza Sohail , Ibrahim Muhammad 
Published: November 2022

Abstract
The causative agent of Newcastle disease (ND) is Newcastle disease virus. It belongs to avian species of Orthoavulavirus, Avulavirinae subfamily and if left untreated it may cause epidemic in poultry. Many vaccines have been made against Newcastle disease based on inactivated and attenuated viruses but become useless due to the genetic changes in the virus. We have recently reported epitope based vaccine by using immunoinformatics approaches. The vaccine was previously constructed against Hemagglutunin neuraminidase protein of Newcastle disease virus. Here we extended our work to develop several chimera of the proposed vaccine to design a new multi-epitope vaccine by shuffling the cytotoxic T lymphocytes (CTL) segments of the vaccine. Total 5040 constructs have been analyzed by shuffling 7 CTL epitopes. Highest antigenic multi-epitope construct was selected for the further study. Our new multi-epitope vaccine (MEV) construct contains 259 amino acids and is immunogenic, more antigenic and non-allergen. The refinement of the structure of MEV construct was performed. Molecular docking analyses showed its maximum binding with avian Toll-like 4 receptor. Subsequently, immune simulations showed its predicted ability to induce the host primary and secondary responses. Study suggests that our new multi-epitope vaccine chimera is more effective and stable protein against Newcastle disease virus strains in Pakistan. However, further studies are required to validate the vaccine through In vitro and In vivo studies.
Tolerance levels of mass density for adaptive helical tomotherapy using MVCT
Authors: Tsunemine Shogo , Ozawa Shuichi , Nakao Minoru , Miura Hideharu , Saito Akito , Kawahara Daisuke , Onishi Yasuhiko , Onishi Takashi , Okawa Fumito , Terai Atsushi , Hashiguchi Taiki , Yamasaki Hidetoshi , Maruta Tsutomu , Murakami Yuji , Nagata Yasushi 
Published: November 2022

Abstract
Daily dose distributions for adaptive radiotherapy (ART) using helical tomotherapy (HT) are calculated using megavoltage computed tomography (MVCT). Generally, the MVCT number is converted to mass density (MD) using an MD calibration table (MVCT-MD table). The aims of this study are to calculate the tolerance levels of the MD for ART and to evaluate the tolerance levels using clinical patient plans. These tolerance levels of MD were calculated based on the tissue maximum ratio (TMR) of 6MV flattening-filter-free (FFF) beam of HT and the effective tissue thickness data from an International Commission on Radiological Protection 110 phantom data for lung, adipose/muscle and cartilage/spongy-bone. These tolerance levels were determined by considering both the MD causing a dose error of 2% and the variation in MVCT numbers. Subsequently, the stability of the MD values was estimated with the standard deviations (SD) in the MVCT number over 6 months. The dose distribution for clinical patient plans was calculated using the MVCT-MD table with added tolerance levels. These tolerance levels were determined as MD differences causing a dose error of 2%, and were ± 0.049 g/cm3, ± 0.030 g/cm3 and ± 0.049 g/cm3 for lung, adipose/muscle and cartilage/spongy-bone, respectively. The calculated dose distribution errors using the MVCT-MD table added tolerance levels were within 2%. We proposed these tolerance levels in MD for the quality control of the MVCT-MD table.
Correlation between the expression of LAT1 in cancer cells and the potential efficacy of boron neutron capture therapy
Authors: Watanabe Tsubasa , Sanada Yu , Hattori Yoshihide , Suzuki Minoru 
Published: November 2022

Abstract
Boron neutron capture therapy (BNCT) is a binary cancer therapy that involves boron administration and neutron irradiation. The nuclear reaction caused by the interaction of boron atom and neutron produces heavy particles with highly cytocidal effects and destruct tumor cells, which uptake the boron drug. p-Boronophenylalanine (BPA), an amino acid derivative, is used in BNCT. Tumor cells with increased nutrient requirements take up more BPA than normal tissues via the enhanced expression of LAT1, an amino acid transporter. The current study aimed to assess the correlation between the expression of LAT1 and the uptake capacity of BPA using genetically modified LAT1-deficient/enhanced cell lines. We conducted an in vitro study, SCC7 tumor cells wherein LAT1 expression was altered using CRISPR/Cas9 were used to assess BPA uptake capacity. Data from The Cancer Genome Atlas (TCGA) were used to examine the expression status of LAT1 in human tumor tissues, the potential impact of LAT1 expression on cancer prognosis and the potential cancer indications for BPA-based BNCT. We discovered that the strength of LAT1 expression strongly affected the BPA uptake ability of tumor cells. Among the histologic types, squamous cell carcinomas express high levels of LAT1 regardless of the primary tumor site. The higher LAT1 expression in tumors was associated with a higher expression of cell proliferation markers and poorer patient prognosis. Considering that BPA concentrate more in tumors with high LAT1 expression, the results suggest that BNCT is effective for cancers having poor prognosis with higher proliferative potential and nutritional requirements.
Hydraulic integrity of plant organs during drought stress and recovery in herbaceous and woody plant species
Authors: Huber Annika E , Melcher Peter J , Bauerle Taryn L 
Published: November 2022

Abstract
The relationship between root, stem, and leaf hydraulic status and stomatal conductance during drought (field capacities: 100–25%) and drought recovery was studied in Helianthus annuus and five tree species (Populus×canadensis, Acer saccharum, A. saccharinum, Picea glauca, and Tsuga canadensis). Measurements of stomatal conductance (gs), organ water potential, and vessel embolism were performed and the following was observed: (i) cavitation only occurred in the petioles and not the roots or stems of tree species regardless of drought stress; (ii) in contrast, all H. annuus organs exhibited cavitation to an increasing degree from root to petiole; and (iii) all species initiated stomatal closure before cavitation events occurred or the expected turgor loss point was reached. After rewatering: (i) cavitated vessels in petioles of Acer species recovered whereas those of P. ×canadensis did not and leaves were shed; (ii) in H. annuus, cavitated xylem vessels were refilled in roots and petioles, but not in stems; and (iii) despite refilled embolisms in petioles of some species during drought recovery, gs never returned to pre-drought conditions. Conclusions are drawn with respect to the hydraulic segmentation hypothesis for above- and below-ground organs, and the timeline of embolism occurrence and repair is discussed.
Chemical evolution of elliptical galaxies I: supernovae and AGN feedback
Authors: Molero Marta , Matteucci Francesca , Ciotti Luca 
Published: November 2022

ABSTRACT
We study the formation and evolution of elliptical galaxies and how they suppress star formation and maintain it quenched. A one-zone chemical model which follows in detail the time evolution of gas mass and its chemical abundances during the active and passive evolution is adopted. The model includes both gas infall and outflow as well as detailed stellar nucleosynthesis. Elliptical galaxies with different infall masses, following a down-sizing in star formation scenario, are considered. In the chemical evolution simulation, we include a novel calculation of the feedback processes. We include heating by stellar wind, core-collapse supernovae (SNe), Type Ia SNe (usually not highlighted in galaxy formation simulations), and active galactic nucleus (AGN) feedback. The AGN feedback is a novelty in this kind of models and is computed by considering a Bondi-Eddington limited accretion onto the central supermassive black hole. We successfully reproduce several observational features, such as the [α/Fe] ratios increasing with galaxy mass, mass-metallicity, MBH–σ and MBH–M* relations. Moreover, we show that stellar feedback and in particular Type Ia SNe, has a main role in maintaining quenched the star formation after the occurrence of the main galactic wind, especially in low-mass ellipticals. For larger systems, the contribution from AGN to thermal energy of gas appears to be necessary. However, the effect of the AGN on the development of the main galactic wind is negligible, unless an unreasonable high-AGN efficiency or an extremely low-stellar feedback are assumed. We emphasize the important role played by Type Ia SNe in the energy budget of early-type galaxies.