bluuebunny/crossref_metadata_2025_split huggingface dataset:
A review on applications of gold nanoparticles-based biosensor for pathogen detection
Authors: Najafabad Marjan Bagheri , Rastin Sepide Jafarzadeh , Taghvaei Fatemeh , Khiyavi Azim Akbarzadeh 
Published: August 2022

Abstract
Pathogens are one of the leading causes of death globally. Early detection of pathogens seems to be necessary. Detection of bacteria and harmful viruses like severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in a fast manner is very critical for early diagnosis of infections to prevent spreading. Current tools for the detection of pathogens are challenging in terms of specificity, rapidity, and simplicity. For this purpose, biosensors have shown advances in rapid diagnosis, high sensitivity, and selectivity detection of pathogens. Nanoparticles-based biosensors are very useful in detecting pathogens due to their capability to provide a simple, rapid, and specific colour changes in response to environmental alternations. Functionalised gold nanoparticles (AuNPs) are highly accurate and sensitive biosensors for the detection of a wide range of pathogens. This review summarises optical and non-optical AuNPs biosensors for the detection of pathogens. Moreover, we focus on technologies that aim to detect pathogens using AuNPs-based biosensor and some representative examples.
Effects of geometric parameters on photoemission of AlGaN nanowire array photocathode
Authors: Cao Zhihao , Liu Lei , Lu Feifei 
Published: August 2022

Abstract
In recent years, with the continuous development of solar blind ultraviolet photodetectors, III-V compounds are widely used as semiconductor materials. The nanowire array structure has excellent ‘light trapping effect’. However, if the distance of nanowire is too close, the secondary absorption problem of the nanowire will occur. If the distance of nanowire is too far, the number of photocarriers generated in the nanowire array per unit volume will be reduced. Meanwhile, the absorption capacity of the nanowire structure with different shapes is different. Based on this background, we studied the influence of the period and geometry of AlGaN nanowires with different Al components on the optical response properties. The finite time domain difference (FDTD) method was used to compare the quantum efficiency and collection efficiency of AlGaN nanowires with different Al components, we found that the quantum efficiency of the hexagonal nanowire array with Al component of 0.42 is as high as 45%, which is the highest in our structure. At the same time, its cutoff wavelength is at 280 nm, which has excellent solar blindness. Therefore, the study in this paper can provide some theoretical reference for the experiment and preparation of AlGaN photocathode.
Self-absorption effects of laser-induced breakdown spectroscopy under different gases and gas pressures
Authors: WANG Songning , ZHANG Dianxin , CHEN Nan , HE Yaxiong , ZHANG Hong , KE Chuan , XU Tao , CHEN Yongliang , ZHAO Yong 
Published: August 2022

Abstract
The self-absorption effect is one of the main factors affecting the quantitative analysis accuracy of laser-induced breakdown spectroscopy. In this paper, the self-absorption effects of laser-induced 7050 Al alloy plasma under different pressures in air, Ar, and N2 have been studied. Compared with air and N2, Ar significantly enhances the spectral signal. Furthermore, the spectral self-absorption coefficient is calculated to quantify the degree of self-absorption, and the influences of gas species and gas pressure on self-absorption are analyzed. In addition, it is found that the spectral intensity fluctuates with the change of pressure of three gases. It can also be seen that the fluctuation of spectral intensity with pressure is eliminated after correcting, which indicates that the self-absorption leads to the fluctuation of spectral intensity under different pressures. The analysis shows that the evolution of optical thin spectral lines with pressure in different gases is mainly determined by the gas properties and the competition between plasma confinement and Rayleigh–Taylor instability.
Optimal design and performance evaluation of free-space quantum key distribution systems
Authors: Scriminich Alessia , Foletto Giulio , Picciariello Francesco , Stanco Andrea , Vallone Giuseppe , Villoresi Paolo , Vedovato Francesco 
Published: August 2022

Abstract
Free-space ground-to-ground links will be an integral part of future quantum communication networks. The implementation of free-space and fiber links in daylight inter-modal configurations is however still hard to achieve, due to the impact of atmospheric turbulence, which strongly decreases the coupling efficiency into the fiber. In this work, we present a comprehensive model of the performance of a free-space ground-to-ground quantum key distribution (QKD) system based on the efficient-BB84 protocol with active decoy states. Our model takes into account the atmospheric channel contribution, the transmitter and receiver telescope design constraints, the parameters of the quantum source and detectors, and the finite-key analysis to produce a set of requirements and optimal design choices for a QKD system operating under specific channel conditions. The channel attenuation is calculated considering all effects deriving from the atmospheric propagation (absorption, beam broadening, beam wandering, scintillation, and wavefront distortions), as well as the effect of fiber-coupling in the presence of a partial adaptive optics correction with finite control bandwidth. We find that the channel fluctuation statistics must be considered to correctly estimate the effect of the saturation rate of the single-photon detectors, which may otherwise lead to an overestimation of the secret key rate. We further present strategies to minimize the impact of diffuse atmospheric background in daylight operation by means of spectral and temporal filtering.
Collective dynamics in plasmas—III. Collisionless kinetic effects
Authors: Bers Abraham 
Published: August 2022

Abstract
This chapter provides a physical description and analysis of the basic collisionless kinetic effects in collective plasma modes—the effects of phase-resonant wave-particle interactions (WPI) and finite Larmor radius (FLR), which are of importance in high-temperature plasmas. These kinetic effects were alluded to only in the previous chapters by cautioning that certain results from a hydrodynamic description may have to be modified or supplemented. Such effects appear as an integral part of a kinetic mode description of plasma dynamics, a more complex model description than the hydrodynamic one. The specific and simpler treatments of kinetic effects allow the illustration and evaluation of their consequences on the many hydrodynamic modes presented in the previous chapter, and include drawing attention to the nonlinear aspects of kinetic dynamics.
Kinetic theory of collisions and transport—I. Fully-ionized plasmas
Authors: Bers Abraham 
Published: August 2022

Abstract
This chapter explores the kinetic theory of collisions and transport for fully-ionized plasmas. It first derives the Fokker–Planck collision equation analyzed in previous chapters by presenting them in two commonly used forms—the Landau form, and the form in terms of Rosenbluth potentials—and examines electrical conductivity through the Spitzer–Härm problem. The chapter then discusses the collisional transport theory, which entails slowly-varying (low-frequency and long-wavelength) hydrodynamics in a short mean-free-path limit. It shows that responses to drives such as the thermodynamics equilibrium entail the collisional transport coefficients of electrical conductivity, particle and heat diffusivities, and viscosity that enter into, and that specify the hydrodynamic transport equations. The kinetic theory analysis of arriving at the electrical conductivity of a fully-ionized plasma is carried out and used to appreciate some general aspects in the analysis and computation required for finding any transport coefficient.
Mathematical Appendices
Authors: Bers Abraham 
Published: August 2022

Abstract
This concluding chapter addresses accounting for the remaining single-charged particle fields in a plasma, which are neglected in a fluid kinetic description: those associated with radiations and fluctuations. These cover topics such as complex Fourier–Laplace transforms, Bessel functions, and the Jacobi elliptic functions. It also contains summaries of various applied mathematics topics and techniques that are used throughout the text. References are also given to textbooks that cover the topics at the end of each section. Students are expected to have had an exposure to these topics in applied mathematics courses taken and/or in such courses that they take concurrently with their graduate studies in plasma physics and fusion plasma electrodynamics.
New horizons in the ageing autonomic nervous system: orthostatic hypotension and supine hypertension
Authors: Dani Melanie , Taraborrelli Patricia , Panagopoulos Dimitrios , Dirksen Andreas , Torocastro Miriam , Sutton Richard , Lim Phang Boon 
Published: August 2022

Abstract
Blood pressure regulation is an automatic, moment-by-moment buffering of the blood pressure in response to physiological changes such as orthostasis, exercise and haemorrhage. This finely orchestrated reflex is called the baroreflex. It is a regulated arc of afferent, central and efferent arms. Multiple physiological changes occur with ageing that can disrupt this reflex, making blood pressure regulation less effective. In addition, multiple changes can occur with ageing-related diseases such as neurodegeneration, atherosclerosis, deconditioning and polypharmacy. These changes commonly result in orthostatic hypotension, hypertension or both, and are consistently associated with multiple adverse outcomes. In this article, we discuss the healthy baroreflex, and physiological and pathophysiological reasons for impaired baroreflex function in older people. We discuss why the common clinical manifestations of orthostatic hypotension and concomitant supine hypertension occur, and strategies for balancing these conflicting priorities. Finally, we discuss strategies for treating them, outlining our practice alongside consensus and expert guidance.
Examining the prevalence and correlates of multimorbidity among community-dwelling older adults: cross-sectional evidence from the Canadian Longitudinal Study on Aging (CLSA) first-follow-up data
Authors: Im James H B , Rodrigues Rebecca , Anderson Kelly K , Wilk Piotr , Stranges Saverio , Nicholson Kathryn 
Published: August 2022

Abstract

Introduction
multimorbidity has become an increasingly important issue for many populations around the world, including Canada. The objectives of this study were to estimate the prevalence of multimorbidity at first follow-up and to identify factors associated with multimorbidity using data from the Canadian Longitudinal Study on Aging (CLSA).

Methods
this study included 27,701 community-dwelling participants in the first follow-up of the CLSA. Multimorbidity was operationalised using two definitions (Public Health and Primary Care), as well as the cut-points of two or more chronic conditions (MM2+) and three or more chronic conditions (MM3+). The prevalence of multimorbidity was calculated at first follow-up and multivariable regression models were used to identify correlates of multimorbidity occurrence.

Results
the prevalence of multimorbidity at first follow-up was 32.3% among males and 39.3% among females when using the MM2+ Public Health definition, whereas the prevalence was 67.2% among males and 75.8% among females when using the MM2+ Primary Care definition. Older age, lower alcohol consumption, lower physical activity levels, dissatisfaction with sleep quality, dissatisfaction with life and experiencing social limitations due to health conditions were significantly associated with increased odds of multimorbidity for both males and females, regardless of the definition of multimorbidity used.

Conclusion
various sociodemographic, behavioural and psychosocial factors are associated with multimorbidity. Future research should continue to examine how the prevalence of multimorbidity changes with time and how these changes may be related to specific risk factors. This future research should be supplemented with studies examining the longitudinal impacts of multimorbidity over time.
Shared decision-making for the treatment of proximal femoral fractures in frail institutionalised older patients: healthcare providers’ perceived barriers and facilitators
Authors: Spronk Inge , Loggers Sverre A I , Joosse Pieter , Willems Hanna C , Van Balen Romke , Gosens Taco , Ponsen Kornelis J , Steens Jeroen , van de Ree C L P (Marc) , Zuurmond Rutger G , Verhofstad Michael H J , Van Lieshout Esther M M , Polinder Suzanne 
Published: August 2022

Abstract

Introduction
Proximal femoral fractures are common in frail institutionalised older patients. No convincing evidence exists regarding the optimal treatment strategy for those with a limited pre-fracture life expectancy, underpinning the importance of shared decision-making (SDM). This study investigated healthcare providers’ barriers to and facilitators of the implementation of SDM.

Methods
Dutch healthcare providers completed an adapted version of the Measurement Instrument for Determinants of Innovations questionnaire to identify barriers and facilitators. If ≥20% of participants responded with ‘totally disagree/disagree’, items were considered barriers and, if ≥80% responded with ‘agree/totally agree’, items were considered facilitators.

Results
A total of 271 healthcare providers participated. Five barriers and 23 facilitators were identified. Barriers included the time required to both prepare for and hold SDM conversations, in addition to the reflective period required to allow patients/relatives to make their final decision, and the number of parties required to ensure optimal SDM. Facilitators were related to patients’ values, wishes and satisfaction, the importance of SDM for patients/relatives and the fact that SDM is not considered complex by healthcare providers, is considered to be part of routine care and is believed to be associated with positive patient outcomes.

Conclusion
Awareness of identified facilitators and barriers is an important step in expanding the use of SDM. Implementation strategies should be aimed at managing time constraints. High-quality evidence on outcomes of non-operative and operative management can enhance implementation of SDM to address current concerns around the outcomes.
Effectiveness of exergaming-based interventions for mobility and balance performance in older adults with Parkinson’s disease: systematic review and meta-analysis of randomised controlled trials
Authors: Zhang Jiaxin , Luximon Yan , Pang Marco Y C , Wang Hailiang 
Published: August 2022

Abstract

Background
exergaming-based interventions (EbIs) have been proposed to improve older adults’ mobility and balance performance. However, the effectiveness of such interventions for older adults with Parkinson’s disease (OAPD) remains unclear.

Methods
seven databases (Web of Science, Medline, Academic Search Premier, CINAHL Complete, PsycINFO, PsychARTICLE and PubMed) were searched up to 7 April 2022. We assessed mobility and balance performance between EbIs groups and control groups or traditional physical training interventions (TPTIs) groups by comparing the outcomes of the Timed Up and Go (TUG), 6-Minute Walk Test (6MWT), Berg Balance Scale (BBS), gait velocity, stride length and Functional Gait Assessment (FGA).

Results
we scanned 1,190 articles and meta-analysed 19 trials (sample size = 781). In general, the results revealed statistical differences between EbIs groups and TPTIs groups in the TUG [mean difference (MD) = −1.030 s; 95% confidence interval (CI) = −2.029 to −0.031; P = 0.043; high quality of evidence], 6MWT (MD = 63.483 m; 95% CI = 9.542 to 117.425; P = 0.021; moderate quality of evidence), BBS (MD = 2.129; 95% CI = −1.293 to 2.965; P &lt; 0.001; high quality of evidence) and FGA (MD = 2.099 95% CI = −0.306 to 3.893; P = 0.022; moderate quality of evidence). No significant difference was discovered between EbIs groups and TPTIs groups in enhancing gait velocity and stride length.

Conclusions
EbIs are statistically better than TPTIs in improving OAPD’s performance in TUG, 6MWT, BBS and FGA, whereas only the change between EbIs and TPTIs in 6MWT can reach the value of minimal clinically important difference. Further studies are needed to better assess the effectiveness of exergaming-based interventions.
Association of multimorbidity patterns with incident disability and recovery of independence among middle-aged and older adults
Authors: Zhou Jiayi , Wei Melissa Y , Zhang Jingyi , Liu Hua , Wu Chenkai 
Published: August 2022

Abstract

Objective
to identify multimorbidity patterns among middle-aged and older adults in China and examine how these patterns are associated with incident disability and recovery of independence.

Methods
data were from The China Health and Retirement Longitudinal Study. We included 14,613 persons aged ≥45 years. Latent class analysis (LCA) was conducted to identify multimorbidity patterns with clinical meaningfulness. Multinomial logistic models were used to determine the adjusted association between multimorbidity patterns and incident disability and recovery of independence.

Results
we identified four multimorbidity patterns: ‘low morbidity’ (67.91% of the sample), ‘pulmonary–digestive–rheumatic’ (17.28%), ‘cardiovascular–metabolic–neuro’ (10.77%) and ‘high morbidity’ (4.04%). Compared to the ‘low morbidity’ group, ‘high morbidity’ (OR = 2.63, 95% CI = 1.97–3.51), ‘pulmonary–digestive–rheumatic’ (OR = 1.89, 95% CI = 1.63–2.21) and ‘cardiovascular–metabolic–neuro’ pattern (OR = 1.61, 95% CI = 1.31–1.97) had higher odds of incident disability in adjusted multinomial logistic models. The ‘cardiovascular–metabolic–neuro’ (OR = 0.60, 95% CI = 0.44–0.81), ‘high morbidity’ (OR = 0.68, 95% CI = 0.47–0.98) and ‘pulmonary–digestive–rheumatic’ group (OR = 0.75, 95% CI = 0.60–0.95) had lower odds of recovery from disability than the ‘low morbidity’ group. Among people without disability, the ‘cardiovascular–endocrine–neuro’ pattern was associated with the highest 2-year mortality (OR = 2.42, 95% CI = 1.56–3.72).

Conclusions
multimorbidity is complex and heterogeneous, but our study demonstrates that clinically meaningful patterns can be obtained using LCA. We highlight four multimorbidity patterns with differential effects on incident disability and recovery from disability. These studies suggest that targeted prevention and treatment approaches are needed for people with multimorbidity.
DBFE: distribution-based feature extraction from structural variants in whole-genome data
Authors: Piernik Maciej , Brzezinski Dariusz , Sztromwasser Pawel , Pacewicz Klaudia , Majer-Burman Weronika , Gniot Michal , Sielski Dawid , Bryzghalov Oleksii , Wozna Alicja , Zawadzki Pawel 
Published: August 2022

AbstractMotivationWhole-genome sequencing has revolutionized biosciences by providing tools for constructing complete DNA sequences of individuals. With entire genomes at hand, scientists can pinpoint DNA fragments responsible for oncogenesis and predict patient responses to cancer treatments. Machine learning plays a paramount role in this process. However, the sheer volume of whole-genome data makes it difficult to encode the characteristics of genomic variants as features for learning algorithms.ResultsIn this article, we propose three feature extraction methods that facilitate classifier learning from sets of genomic variants. The core contributions of this work include: (i) strategies for determining features using variant length binning, clustering and density estimation; (ii) a programing library for automating distribution-based feature extraction in machine learning pipelines. The proposed methods have been validated on five real-world datasets using four different classification algorithms and a clustering approach. Experiments on genomes of 219 ovarian, 61 lung and 929 breast cancer patients show that the proposed approaches automatically identify genomic biomarkers associated with cancer subtypes and clinical response to oncological treatment. Finally, we show that the extracted features can be used alongside unsupervised learning methods to analyze genomic samples.Availability and implementationThe source code of the presented algorithms and reproducible experimental scripts are available on Github at https://github.com/MNMdiagnostics/dbfe.Supplementary informationSupplementary data are available at Bioinformatics online.
Neural Collective Matrix Factorization for integrated analysis of heterogeneous biomedical data
Authors: Mariappan Ragunathan , Jayagopal Aishwarya , Sien Ho Zong , Rajan Vaibhav 
Published: August 2022

AbstractMotivationIn many biomedical studies, there arises the need to integrate data from multiple directly or indirectly related sources. Collective matrix factorization (CMF) and its variants are models designed to collectively learn from arbitrary collections of matrices. The latent factors learnt are rich integrative representations that can be used in downstream tasks, such as clustering or relation prediction with standard machine-learning models. Previous CMF-based methods have numerous modeling limitations. They do not adequately capture complex non-linear interactions and do not explicitly model varying sparsity and noise levels in the inputs, and some cannot model inputs with multiple datatypes. These inadequacies limit their use on many biomedical datasets.ResultsTo address these limitations, we develop Neural Collective Matrix Factorization (NCMF), the first fully neural approach to CMF. We evaluate NCMF on relation prediction tasks of gene–disease association prediction and adverse drug event prediction, using multiple datasets. In each case, data are obtained from heterogeneous publicly available databases and used to learn representations to build predictive models. NCMF is found to outperform previous CMF-based methods and several state-of-the-art graph embedding methods for representation learning in our experiments. Our experiments illustrate the versatility and efficacy of NCMF in representation learning for seamless integration of heterogeneous data.Availability and implementationhttps://github.com/ajayago/NCMF_bioinformatics.Supplementary informationSupplementary data are available at Bioinformatics online.
Gene therapy targeting the blood–brain barrier improves neurological symptoms in a model of genetic MCT8 deficiency
Authors: Sundaram Sivaraj M , Arrulo Pereira Adriana , Müller-Fielitz Helge , Köpke Hannes , De Angelis Meri , Müller Timo D , Heuer Heike , Körbelin Jakob , Krohn Markus , Mittag Jens , Nogueiras Ruben , Prevot Vincent , Schwaninger Markus 
Published: August 2022

Abstract
A genetic deficiency of the solute carrier monocarboxylate transporter 8 (MCT8), termed Allan–Herndon–Dudley syndrome, is an important cause of X-linked intellectual and motor disability. MCT8 transports thyroid hormones across cell membranes. While thyroid hormone analogues improve peripheral changes of MCT8 deficiency, no treatment of the neurological symptoms is available so far. Therefore, we tested a gene replacement therapy in Mct8- and Oatp1c1-deficient mice as a well-established model of the disease. Here, we report that targeting brain endothelial cells for Mct8 expression by intravenously injecting the vector AAV-BR1-Mct8 increased tri-iodothyronine (T3) levels in the brain and ameliorated morphological and functional parameters associated with the disease. Importantly, the therapy resulted in a long-lasting improvement in motor coordination. Thus, the data support the concept that MCT8 mediates the transport of thyroid hormones into the brain and indicate that a readily accessible vascular target can help overcome the consequences of the severe disability associated with MCT8 deficiency.