bluuebunny/crossref_metadata_2025_split huggingface dataset:
Harnessing the potential of practice‐based clinical optometry research in the United Kingdom
Authors: Taylor Laura J. , Hobby Angharad , Bowen Michael , Jolly Jasleen K. , MacLaren Robert E. 
Published: December 2022

AbstractResearch is the core of evidence‐based practice across all healthcare, in order to ensure optimum patient care. The College of Optometrists is a national standard setting institution for optometric practice in the United Kingdom. However, the standards are only as good as the available evidence, and currently there is little evidence relating directly to optometric practice. The National Institute of Health and Care Research, the General Medical Council and The College of Optometrists, amongst others, have published research strategies describing ambitious plans to expand the scope of healthcare research. The aim of this article is to raise awareness of these government initiatives and consider how they may relate to optometric practice. To improve optometrist research engagement, we need to address the barriers to research and implement strategies to overcome them. There are many opportunities to support research, with different degrees of involvement, from signposting patients to research studies, supporting recruitment or collecting data for a multicentre clinical trial, as well as undertaking an individual research project. Healthcare research is changing and there is scope for more practice‐based research activities in optometry. Research should not be a solo endeavour but a multi‐disciplinary effort. Greater collaborations across all stakeholders, including primary care, secondary care, academia, regulators and industry is needed to make this possible.
Minimally invasive plate osteosynthesis of femoral fractures with 3D‐printed bone models and custom surgical guides: A cadaveric study in dogs
Authors: Scheuermann Logan M. , Kim Stanley E. , Lewis Daniel D. , Johnson Matthew D. , Biedrzycki Adam H. 
Published: December 2022

AbstractObjectiveAssess the accuracy and efficiency of reduction provided by application of plates precontoured to 3‐dimensional (3D)‐printed femoral bone models using a custom fracture reduction system (FRS) or intramedullary pin (IMP) to facilitate femoral minimally invasive plate osteosynthesis (MIPO) in dogs.Study designExperimental cadaveric study.Sample populationSeven dog cadavers.MethodsVirtual 3D femoral models were created using computed tomographic images. Simulated, virtual mid‐diaphyseal femoral fractures were created and reduced. Reduced femoral models were 3D‐printed and a plate was contoured. Custom drill guides for plate screw placement were designed and 3D‐printed for the FRS. Mid‐diaphyseal simulated comminuted fractures were created in cadavers, and fractures were aligned using FRS or IMP and stabilized with the precontoured plates. Number of fluoroscopic images acquired per procedure and surgical duration were recorded. Computed tomographic scans were repeated to assess femoral length and alignment.ResultsCompared to the preoperative virtual plan, median change in femoral length and frontal, sagittal, and axial alignment was less than 3 mm, 2°, 3°, and 3° postoperatively, respectively, in both reduction groups. There was no difference in length or alignment between reduction groups (P > .05). During FRS, fewer fluoroscopic images were taken (P = .001), however, surgical duration was longer than IMP procedures (P = .011).ConclusionFemoral alignment was accurate when using plates precontoured to 3D printed models, regardless of reduction method.Clinical significanceAccurate plate contouring using anatomically accurate models may improve fracture reduction accuracy during MIPO applications. Custom surgical guides may reduce fluoroscopy use associated with MIPO.
Near Field Evolution of Blade Wakes Under the Influence of Upstream Transitional Flow in a Compressor Cascade at Moderate Reynolds Numbers
Authors: Shi Lei , Ma Hongwei , Wang Tianyou 
Published: December 2022

Abstract
The variation of blade wake characteristics under the influence of upstream transitional flow has not been thoroughly studied, since few control volumes in experimental investigations capture both the blade surface transitional flow and the downstream wake. In this study, instantaneous flow fields in the near-blade and the near-wake region of a compressor cascade at various incidences (i = 0 deg, 2.5 deg, 5 deg, 7.5 deg, and 10 deg) were investigated using particle image velocimetry (PIV). The mean and fluctuating near-wake fields of the compressor blade at Rec = 24,000 were analyzed considering the upstream blade surface laminar separation bubble (LSB) types. The suction-side flow topology shifts at a critical incidence angle of 5 deg from laminar separation without reattachment (i &lt; 5 deg) into a LSB near the trailing edge (i = 5 deg) and an LSB which is advancing to the leading edge (i &gt; 5 deg). The laminar separation vortices retain sufficient strength and coherence to interact with the wake at the low incidence angles (LIA cases, i ≤ 5 deg) but lose coherence beyond the reattachment point at the high incidence angles (HIA cases, i &gt; 5 deg). Self-similarity of the asymmetrical wakes under the influence of various LSB types was established. Near field evolution of wake width, wake decay rate, and flow fluctuations are directly correlated with the LSB type. An optimal incidence exists for the minimum overall flow fluctuation with a delayed separation and alleviated vortical interactions when the LSB locates at the trailing edge.
Role of Kidney Stones in Renal Pelvis Flow
Authors: Constante-Amores C. R. , Kahouadji L. , Williams J. G. , Turney B. W. , Shin S. , Chergui J. , Juric D. , Moulton D. E. , Waters S. L. 
Published: December 2022

Abstract
Ureteroscopy is a commonly performed medical procedure to treat stones in the kidney and ureter using a ureteroscope. Throughout the procedure, saline is irrigated through the scope to aid visibility and wash-out debris from stone fragmentation. The key challenge that this research addresses is to build a fundamental understanding of the interaction between the kidney stones/stone fragments and the flow dynamics in the renal pelvis flow. We examine the time-dependent flow dynamics inside an idealized renal pelvis in the context of a surgical procedure for kidney stone removal. Here, we examine the time-dependent evolution of these vortical flow structures in three dimensions, and incorporate the presence of rigid kidney stones. We perform direct numerical simulations, solving the transient Navier–Stokes equations in a spherical domain. Our numerical predictions for the flow dynamics in the absence of stones are validated with available experimental and numerical data, and the governing parameters and flow regimes are chosen carefully in order to satisfy several clinical constraints. The results shed light on the crucial role of flow circulation in the renal cavity and its effect on the trajectories of rigid stones. We demonstrate that stones can either be washed out of the cavity along with the fluid, or be trapped in the cavity via their interaction with vortical flow structures. Additionally, we study the effect of multiple stones in the flow field within the cavity in terms of the kinetic energy, entrapped fluid volume, and the clearance rate of a passive tracer modeled via an advection–diffusion equation. We demonstrate that the flow in the presence of stones features a higher vorticity production within the cavity compared with the stone-free cases.
Machine Learning Metamodel of a Computationally Intense LOCA Code
Authors: Conner Landon A. , Worrell Clarence L. , Liao Jun , Spring James P. , Karimi Reza A. , Marquardt Jeremy S. , Wieder Joseph D. 
Published: December 2022

Abstract
The nuclear power industry is increasingly identifying applications of machine learning to reduce design, engineering, manufacturing, and operational costs. In some cases, applications have been deployed and are providing value, particularly in data rich manufacturing areas. In this paper, we use machine learning to develop metamodel approximations of a computationally intense safety analysis code used to simulate a postulated loss-of-coolant accident (LOCA). Accurate metamodels run at a fraction of the computational cost (milliseconds) compared to the LOCA analysis code. Metamodels can therefore support applications requiring a high volume of runs such as optimization, uncertainty analysis, and probabilistic decision analysis, which would otherwise not be possible using the computationally intense code. In this study, training data is first generated by running the safety analysis code over a design of experiment. Exploratory data analysis is then performed followed by an initial fitting of several model forms, including neighbor-based models, tree-based models, support vector machines, and artificial neural networks. A neural network is selected as the most promising candidate and hyperparameter optimization using a genetic algorithm is performed. Finally, the resulting model, its potential applications, and areas for further research are discussed.
Occupational exposure to respirable crystalline silica and acute myocardial infarction among men and women in Sweden
Authors: Wiebert Pernilla , Andersson Tomas , Feychting Maria , Sjögren Bengt , Plato Nils , Gustavsson Per 
Published: December 2022

ObjectivesOccupational exposure to respirable crystalline silica (RCS) is common. The study aimed to assess the risk for acute myocardial infarction (AMI) after long-term exposure to RCS and to explore differences in risk between men and women.MethodsThe cohort included all manual workers identified from the Swedish National Census in 1980 using data on job titles and demography altogether from five censuses from 1960 to 1990, in total 605 246 men and 480 607 women. Information on AMI was obtained from nationwide registers from 1992 to 2006. Exposure to RCS was assessed with a job-exposure matrix. HRs and 95% CIs were estimated by Cox regression, adjusted for age, socioeconomic status and urbanisation index.ResultsAmong manual workers ever exposed to RCS, the adjusted risk of AMI was HR 1.29 (95% CI 1.15 to 1.46) in women, and HR 1.02 (95% CI 1.00 to 1.04) in men. In the highest quartile of cumulative exposure, the risk of AMI was HR 1.66 (95% CI 1.27 to 2.18) for women, and HR 1.06 (95% CI 1.03 to 1.10) for men, respectively. The risk of AMI increased with cumulative exposure to RCS both in women (p=0.001) and in men (p=0.016). An interaction analysis showed that the relative risk from exposure to RCS was statistically significantly lower in men than in women at similar exposure levels.ConclusionsOccupational exposure to RCS was related to the risk of AMI. Women were more sensitive to exposure to RCS than men.
Spectrum of the S-wave fully-heavy tetraquark states
Authors: Zhang Jie , Wang Jin-Bao , Li Gang , An Chun-Sheng , Deng Cheng-Rong , Xie Ju-Jun 
Published: December 2022

AbstractIn present work, spectrum of the S-wave fully-heavy tetraquark states $$QQ\bar{Q}\bar{Q}$$

Q
Q

Q

¯

Q

¯

($$Q=c,b$$

Q
=
c
,
b

), i.e., $$cc\bar{c}\bar{c}$$

c
c

c

¯

c

¯

, $$bb\bar{b}\bar{b}$$

b
b

b

¯

b

¯

, $$cc\bar{b}\bar{b}$$

c
c

b

¯

b

¯

/$$bb\bar{c}\bar{c}$$

b
b

c

¯

c

¯

, $$bc\bar{c}\bar{c}$$

b
c

c

¯

c

¯

/ $$cc\bar{b}\bar{c}$$

c
c

b

¯

c

¯

, $$bb\bar{c}\bar{b}$$

b
b

c

¯

b

¯

/$$cb\bar{b}\bar{b}$$

c
b

b

¯

b

¯

, and $$bc\bar{b}\bar{c}$$

b
c

b

¯

c

¯

are systematically investigated within a nonrelativistic constituent quark model, in which the instanton-induced and one-gluon-exchange interactions are taken into account as the residual spin-dependent hyperfine interaction. Our results show that the states with $$cc\bar{c}\bar{c}$$

c
c

c

¯

c

¯

and $$bb\bar{b}\bar{b}$$

b
b

b

¯

b

¯

components could be located around 6500 MeV and 19,200 MeV, respectively. Based on our calculations, the new X(6900) state observed by LHCb may be not a ground $$cc\bar{c}\bar{c}$$

c
c

c

¯

c

¯

tetraquark state, while it could be an orbitally or radially excited state of $$cc\bar{c}\bar{c}$$

c
c

c

¯

c

¯

system. On the other hand, the recently reported X(6600) state by CMS and ATLAS can be explained as a ground $$cc\bar{c}\bar{c}$$

c
c

c

¯

c

¯

tetraquark state with spin-parity $$J^{PC} =0^{++}$$

J

PC

=

0

+
+

.
Impaired SARS-CoV-2 Variant Neutralization and CD8+ T-cell Responses Following 3 Doses of mRNA Vaccines in Myeloma: Correlation with Breakthrough Infections
Authors: Azeem Maryam I. , Nooka Ajay K. , Shanmugasundaram Uma , Cheedarla Narayanaiah , Potdar Sayalee , Manalo Renee Julia , Moreno Alberto , Switchenko Jeffrey M. , Cheedarla Suneethamma , Doxie Deon Bryant , Radzievski Roman , Ellis Madison Leigh , Manning Kelly E. , Wali Bushra , Valanparambil Rajesh M. , Maples Kathryn T. , Baymon Essence , Kaufman Jonathan L. , Hofmeister Craig C. , Joseph Nisha S. , Lonial Sagar , Roback John D. , Sette Alessandro , Ahmed Rafi , Suthar Mehul S. , Neish Andrew S. , Dhodapkar Madhav V. , Dhodapkar Kavita M. 
Published: December 2022

AbstractPatients with multiple myeloma (MM) mount suboptimal neutralizing antibodies (nAb) following 2 doses of SARS-CoV-2 mRNA vaccines. Currently, circulating SARS-CoV-2 variants of concern (VOC) carry the risk of breakthrough infections. We evaluated immune recognition of current VOC including BA.1, BA.2, and BA.5 in 331 racially representative patients with MM following 2 or 3 doses of mRNA vaccines. The third dose increased nAbs against WA1 in 82%, but against BA variants in only 33% to 44% of patients. Vaccine-induced nAbs correlated with receptor-binding domain (RBD)–specific class-switched memory B cells. Vaccine-induced spike-specific T cells were detected in patients without seroconversion and cross-recognized variant-specific peptides but were predominantly CD4+ T cells. Detailed clinical/immunophenotypic analysis identified features correlating with nAb/B/T-cell responses. Patients who developed breakthrough infections following 3 vaccine doses had lower live-virus nAbs, including against VOC. Patients with MM remain susceptible to SARS-CoV-2 variants following 3 vaccine doses and should be prioritized for emerging approaches to elicit variant-nAb and CD8+ T cells.Significance:Three doses of SARS-CoV-2 mRNA vaccines fail to yield detectable VOC nAbs in nearly 60% and spike-specific CD8+ T cells in &gt;80% of myeloma patients. Patients who develop breakthrough infections following vaccination have low levels of live-virus nAb.This article is highlighted in the In This Issue feature, p. 101
Antibody Binding and Neutralization of Live SARS-CoV-2 Variants Including BA.4/5 Following Booster Vaccination of Patients with B-cell Malignancies
Authors: Chang Andres , Akhtar Akil , Lai Lilin , Orellana-Noia Victor M. , Linderman Susanne L. , McCook-Veal Ashley A. , Switchenko Jeffrey M. , Saini Manpreet , Valanparambil Rajesh M. , Blum Kristie A. , Allen Pamela B. , Lechowicz Mary Jo , Romancik Jason T. , Ayers Amy , Leal Alyssa , O'Leary Colin B. , Churnetski Michael C. , Baird Katelin , Kives Melissa , Wrammert Jens , Nooka Ajay K. , Koff Jean L. , Dhodapkar Madhav V. , Suthar Mehul S. , Cohen Jonathon B. , Ahmed Rafi 
Published: December 2022

Patients with non–Hodgkin lymphoma and chronic lymphocytic leukemia (NHL/CLL) elicit inadequate antibody responses after initial SARS-CoV-2 vaccination and remain at high risk of severe COVID-19 disease. We investigated IgG, IgA, and IgM responses after booster vaccination against recent SARS-CoV-2 variants including Omicron BA.5 in 67 patients. Patients had lower fold increase and total anti-spike binding titers after booster than healthy individuals. Antibody responses negatively correlated with recent anti-CD20 therapy and low B-cell numbers. Antibodies generated after booster demonstrated similar binding properties against SARS-CoV-2 variants compared with those generated by healthy controls with lower binding against Omicron variants. Importantly, 43% of patients showed anti-Omicron BA.1 neutralizing antibodies after booster and all these patients also had anti-Omicron BA.5 neutralizing antibodies. Patients with NHL/CLL demonstrated inferior antibody responses after booster vaccination, particularly against Omicron variants. Prioritization of prophylactic and treatment agents and vaccination of patients and close contacts with updated vaccine formulations are essential.Significance:Limited data exist on antibody responses against current SARS-CoV-2 variants after booster vaccination in patients with NHL/CLL. We showed inferior antibody responses against Omicron variants after booster vaccination in these patients but some generated anti-Omicron titers. This stresses the importance of vaccinating patients with updated formulations.
Osteoprotegerin and Ischemic Stroke Prognosis: A Prospective Multicenter Study and Mendelian Randomization Analysis
Authors: Zhu Zhengbao , Guo Daoxia , Zhang Kaixin , Yang Pinni , Jia Yiming , Shi Mengyao , Peng Yanbo , Chen Jing , Wang Aili , Xu Tan , Zhang Yonghong , He Jiang 
Published: December 2022

Background:
Osteoprotegerin was implicated in vascular injury and inflammatory responses, but its prognostic value in ischemic stroke remained unclear. We aimed to prospectively investigate the association between plasma osteoprotegerin and ischemic stroke prognosis combined with a Mendelian randomization analysis.

Methods:
Our prospective study follows the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) reporting guideline. We measured baseline plasma osteoprotegerin levels for 3490 ischemic stroke patients recruited between August 2009 and May 2013 in 26 hospitals across China. The primary outcome was a composite outcome of death and major disability at 3 months after ischemic stroke.

Results:

After adjustment for age, sex, admission National Institutes of Health Stroke Scale score, and other important covariates, elevated osteoprotegerin levels were associated with increased risks of primary outcome (odds ratio, 1.40 [95% CI, 1.05–1.88]), death (hazard ratio, 2.05 [95% CI, 1.04–4.08]), and composite outcome of death and vascular events (hazard ratio, 2.00 [95% CI, 1.15–3.48]) when 2 extreme quartiles were compared. Each 1-SD higher log-osteoprotegerin was associated with a 18% (95% CI, 6%–32%) increased risk of primary outcome, 69% (95% CI, 31%–118%) increased risk of death, and 53% (95% CI, 24%–89%) increased risk of composite outcome of death and vascular events, respectively. Multiple-adjusted spline regression model showed a linear association of osteoprotegerin with primary outcome (
P
for linearity <0.001). Adding osteoprotegerin to conventional risk factors did not significantly improve discriminatory power (C statistics, 0.817 versus 0.818;
P
=0.232) but did slightly improve the risk reclassification of primary outcome (net reclassification improvement: 13.68%,
P
<0.001; integrated discrimination improvement: 0.23%,
P
=0.039). In Mendelian randomization analysis, genetically determined high plasma osteoprotegerin was associated with increased risk of primary outcome (odds ratio, 5.74 [95% CI, 1.12–29.44];
P
=0.036).

Conclusions:
Elevated plasma osteoprotegerin was associated with poor prognosis of ischemic stroke, and genetically determined high plasma osteoprotegerin was associated with an increased risk of primary outcome in Mendelian randomization analysis.

Registration:

URL:
https://www.clinicaltrials.gov
; Unique identifier: NCT01840072.
A Real-Time Spatiotemporal Machine Learning Framework for the Prediction of Nearshore Wave Conditions
Authors: Chen Jiaxin , Ashton Ian G. C. , Steele Edward C. C. , Pillai Ajit C. 
Published: December 2022

Abstract
The safe and successful operation of offshore infrastructure relies on a detailed awareness of ocean wave conditions. Ongoing growth in offshore wind energy is focused on very large-scale projects, deployed in ever more challenging environments. This inherently increases both cost and complexity and therefore the requirement for efficient operational planning. To support this, we propose a new machine learning framework for the short-term forecasting of ocean wave conditions to support critical decision-making associated with marine operations. Here, an attention-based long short-term memory (LSTM) neural network approach is used to learn the short-term temporal patterns from in situ observations. This is then integrated with an existing, low computational cost spatial nowcasting model to develop a complete framework for spatiotemporal forecasting. The framework addresses the challenge of filling gaps in the in situ observations and undertakes feature selection, with seasonal training datasets embedded. The full spatiotemporal forecasting system is demonstrated using a case study based on independent observation locations near the southwest coast of the United Kingdom. Results are validated against in situ data from two wave buoy locations within the domain and compared to operational physics-based wave forecasts from the Met Office (the United Kingdom’s national weather service). For these two example locations, the spatiotemporal forecast is found to have an accuracy of R2 = 0.9083 and 0.7409 in forecasting 1-h-ahead significant wave height and R2 = 0.8581 and 0.6978 in 12-h-ahead forecasts, respectively. Importantly, this represents respectable levels of accuracy, comparable to traditional physics-based forecast products, but requires only a fraction of the computational resources.

Significance Statement
Spectral wave models, based on modeling the underlying physics and physical processes, are traditionally used to generate wave forecasts but require significant computational cost. In this study, we propose a machine learning forecasting framework developed using both in situ buoy observations and a surrogate regional numerical wave model. The proposed framework is validated against in situ measurements at two renewable energy sites and found to have very similar 12-h forecasting errors when benchmarked against the Met Office’s physics-based forecasting model but requires far less computational power. The proposed framework is highly flexible and has the potential for offering a low-cost, low computational resource approach for the provision of short-term forecasts and can operate with other types of observations and other machine learning algorithms to improve the availability and accuracy of the prediction.