bluuebunny/crossref_metadata_2025_split huggingface dataset:
The cortisol awakening response in a 3 month clinical trial of service dogs for veterans with posttraumatic stress disorder
Authors: Nieforth Leanne O. , Rodriguez Kerri E. , Zhuang Run , Miller Elise A. , Sabbaghi Arman , Schwichtenberg A. J. , Granger Douglas A. , O’Haire Marguerite E. 
Published: January 2024

AbstractRecent literature suggests that service dogs may be a valuable complementary intervention option for posttraumatic stress disorder (PTSD) among military veterans due to the potential influence on stress response dysregulation. The aim of this short-term longitudinal study was to quantify the impact of service dogs in US military veterans with PTSD with particular attention to the cortisol awakening response. A sub aim of the study was to empirically evaluate the physiological effects of PTSD service dogs on veteran partners. We conducted a clinical trial (ID: NCT03245814) that assessed the cortisol awakening response for 245 participants at baseline and 3 months follow-up across an intervention group (service dog: veterans n = 88, partners n = 46) and control group (usual care: n = 73, partners n = 38). A total of N = 161 veterans and N = 84 partners collected whole saliva samples via a passive drool collection immediately upon waking, 30 min after waking, and 45 min after waking on three consecutive weekdays at baseline and again at follow-up. Mixed model repeated measures (MMRM) with a fixed effect of the intervention group (service dog or control) were utilized. Covariates considered for the model included time of awakening, sleep duration, sleep efficiency, prior day experiences (measured via ecological momentary assessment), traumatic brain injury, age, gender, race, ethnicity, socioeconomic status, smoking status, alcohol use, physical health, and body mass index. A total of 3951 salivary samples were collected (veterans: 2613, partners: 1338). MMRM results demonstrated that veterans with a service dog had a statistically significant higher cortisol awakening response, including the area under the curve with respect to both increase (AUCi, β = 1.46, p = 0.046) and absolute increase (AINC, β = 0.05, p = 0.035). Results were not statistically significant for partners. Findings suggest that veterans with service dogs have a higher, less blunted CAR in comparison to veterans receiving usual care alone. In veterans with a blunted morning cortisol response, service dog placement could help boost their morning cortisol response.
Fabrication, defect chemistry and microstructure of Mn-doped UO2
Authors: Smith H. , Townsend L. T. , Mohun R. , Mosselmans J. F. W. , Kvashnina K. , Hyatt Neil C. , Corkhill C. L. 
Published: January 2024

AbstractMn-doped UO2 is under consideration for use as an accident tolerant nuclear fuel. We detail the synthesis of Mn-doped UO2 prepared via a wet co-precipitation method, which was refined to improve the yield of incorporated Mn. To verify the Mn-doped UO2 defect chemistry, X-ray absorption spectroscopy at the Mn K-edge was performed, in addition to X-ray diffraction, Raman spectroscopy and high-energy resolved fluorescence detection X-ray absorption near edge spectroscopy at the U M4-edge. It was established that Mn2+ directly substitutes for U4+ in the UO2 lattice, accompanied by oxygen vacancy (Ov) charge compensation. In contrast to other divalent-element doped UO2 materials, compelling evidence for U5+ in a charge compensating role was not found. This work furthers understanding of the structure and crystal chemistry of Mn-doped UO2, which could show potential advantages as a novel efficient advanced nuclear fuel.
Time to surgery is not an oncological risk factor in patients with cholangiocarcinoma undergoing curative-intent liver surgery
Authors: Mantas Anna , Liu Dong , Otto Carlos Constantin , Heij Lara Rosaline , Heise Daniel , Bruners Philipp , Lang Sven Arke , Ulmer Tom Florian , Neumann Ulf Peter , Bednarsch Jan 
Published: January 2024

AbstractSurgical resection is the only option to achieve long-term survival in cholangiocellular carcinoma (CCA). Due to limitations of health care systems and unforeseeable events, e.g., the COVID pandemic, the time from diagnosis to surgery (time-to-surgery (TTS)) has gained great interest in malignancies. Thus, we investigated whether TTS is associated with the oncological outcome in patients who underwent surgery for CCA. A cohort of 276 patients undergoing curative-intent surgery for intrahepatic and perihilar CCA excluding individuals with neoadjuvant therapy and perioperative mortality between 2010 and 2021 were eligible for analysis. Patients were grouped according to TTS (≤ 30; 31–60; 61–90; > 90 days) and compared by Kruskal–Wallis-analysis. Survival was compared using Kaplan–Meier analysis and characteristics associated with cancer-specific survival (CSS), recurrence-free survival (RFS) and overall survival (OS) using Cox regressions. The median CSS was 39 months (3-year-CSS = 52%, 5-year-CSS = 42%) and the median RFS 20 months (3-year-CSS = 38%, 5-year-CSS = 33%). In univariable Cox regressions, TTS was not associated with CSS (p = 0.971) or RFS (p = 0.855), respectively. A grouped analysis with respect to TTS (≤ 30 days, n = 106; 31–60 days, n = 134; 61–90 days, n = 44; > 90 days, n = 29) displayed a median CSS of 38, 33, 51 and 41 months and median RFS of 17, 22, 28 and 20 months (p = 0.971 log rank; p = 0.520 log rank). No statistical difference regarding oncological risk factors were observed between the groups. This study is the first comprehensive analysis of TTS in CCA patients. Within a representative European cohort, TTS was not associated with earlier tumor recurrence or reduced CCS.
Uncovering local aggregated air quality index with smartphone captured images leveraging efficient deep convolutional neural network
Authors: Mondal Joyanta Jyoti , Islam Md. Farhadul , Islam Raima , Rhidi Nowsin Kabir , Newaz Sarfaraz , Manab Meem Arafat , Islam A. B. M. Alim Al , Noor Jannatun 
Published: January 2024

AbstractThe prevalence and mobility of smartphones make these a widely used tool for environmental health research. However, their potential for determining aggregated air quality index (AQI) based on PM2.5 concentration in specific locations remains largely unexplored in the existing literature. In this paper, we thoroughly examine the challenges associated with predicting location-specific PM2.5 concentration using images taken with smartphone cameras. The focus of our study is on Dhaka, the capital of Bangladesh, due to its significant air pollution levels and the large population exposed to it. Our research involves the development of a Deep Convolutional Neural Network (DCNN), which we train using over a thousand outdoor images taken and annotated. These photos are captured at various locations in Dhaka, and their labels are based on PM2.5 concentration data obtained from the local US consulate, calculated using the NowCast algorithm. Through supervised learning, our model establishes a correlation index during training, enhancing its ability to function as a Picture-based Predictor of PM2.5 Concentration (PPPC). This enables the algorithm to calculate an equivalent daily averaged AQI index from a smartphone image. Unlike, popular overly parameterized models, our model shows resource efficiency since it uses fewer parameters. Furthermore, test results indicate that our model outperforms popular models like ViT and INN, as well as popular CNN-based models such as VGG19, ResNet50, and MobileNetV2, in predicting location-specific PM2.5 concentration. Our dataset is the first publicly available collection that includes atmospheric images and corresponding PM2.5 measurements from Dhaka. Our codes and dataset are available at https://github.com/lepotatoguy/aqi.
Synthesis and biophysical evaluation of carbosilane dendrimers as therapeutic siRNA carriers
Authors: Zawadzki Serafin , Martín-Serrano Ángela , Okła Elżbieta , Kędzierska Marta , Garcia-Gallego Sandra , López Paula O. , de la Mata Francisco J. , Michlewska Sylwia , Makowski Tomasz , Ionov Maksim , Pędziwiatr-Werbicka Elżbieta , Bryszewska Maria , Miłowska Katarzyna 
Published: January 2024

AbstractGene therapy presents an innovative approach to the treatment of previously incurable diseases. The advancement of research in the field of nanotechnology has the potential to overcome the current limitations and challenges of conventional therapy methods, and therefore to unlocking the full potential of dendrimers for use in the gene therapy of neurodegenerative disorders. The blood–brain barrier (BBB) poses a significant challenge when delivering therapeutic agents to the central nervous system. In this study, we investigated the biophysical properties of dendrimers and their complexes with siRNA directed against the apolipoprotein E (APOE) gene to identify an appropriate nanocarrier capable of safely delivering the cargo across the BBB. Our study yielded valuable insights into the complexation process, stability over time, the mechanisms of interaction, the influence of dendrimers on the oligonucleotide's spatial structure, and the potential cytotoxic effects on human cerebral microvascular endothelium cells. Based on our findings, we identified that the dendrimer G3Si PEG6000 was an optimal candidate for further research, potentially serving as a nanocarrier capable of safely delivering therapeutic agents across the BBB for the treatment of neurodegenerative disorders.
A improved pooling method for convolutional neural networks
Authors: Zhao Lei , Zhang Zhonglin 
Published: January 2024

AbstractThe pooling layer in convolutional neural networks plays a crucial role in reducing spatial dimensions, and improving computational efficiency. However, standard pooling operations such as max pooling or average pooling are not suitable for all applications and data types. Therefore, developing custom pooling layers that can adaptively learn and extract relevant features from specific datasets is of great significance. In this paper, we propose a novel approach to design and implement customizable pooling layers to enhance feature extraction capabilities in CNNs. The proposed T-Max-Avg pooling layer incorporates a threshold parameter T, which selects the K highest interacting pixels as specified, allowing it to control whether the output features of the input data are based on the maximum values or weighted averages. By learning the optimal pooling strategy during training, our custom pooling layer can effectively capture and represent discriminative information in the input data, thereby improving classification performance. Experimental results show that the proposed T-Max-Avg pooling layer achieves good performance on three different datasets. When compared to LeNet-5 model with average pooling, max pooling, and Avg-TopK methods, the T-Max-Avg pooling method achieves the highest accuracy on CIFAR-10, CIFAR-100, and MNIST datasets.
Research progress on composite material of bismuth vanadate catalyzing the decomposition of Quinolone antibiotics
Authors: Zhao Yuan , Kong Lingyuan , Li Shangdong , Zhao Zhirui , Wang Na , Pang Yunqing 
Published: January 2024

AbstractSince quinolone is a kind of synthetic broad-spectrum antibacterial drugs, with the widespread use of this class of antibiotics, the risk and harm to human health have been attendant to the sewage containing quinolones which are discharged into the environment. Photocatalysis is considered as a promising technology for antibiotic degradation for its strong redox properties and reaction rate. As a metal oxidizing substance, Bismuth vanadate (BiVO4) is such a popular and hot material for the degradation of organic pollutants recently due to its good photocatalytic activity and chemical stability. Numerous studies have confirmed that BiVO4 composites can overcome the shortcomings of pure BiVO4 and cleave the main structure of quinolone under photocatalytic conditions. This paper mainly outlines the research progress on the preparation of BiVO4 composites and the degradation of quinolone antibiotics from the perspective of improving the catalysis and degrading the efficiency mechanism of BiVO4 composites.
Neurological intervention transition model for dynamic prediction of good outcome in spontaneous subarachnoid haemorrhage
Authors: Luo Yiming , Payne Stephen John 
Published: January 2024

AbstractDeterioration of neurovascular conditions can be rapid in patients with spontaneous subarachnoid haemorrhage (SAH) and often lead to poor clinical outcomes. Therefore, it is crucial to promptly assess and continually track the progression of the disease. This study incorporated baseline clinical conditions, repeatedly measured neurological grades and haematological biomarkers for dynamic outcome prediction in patients with spontaneous SAH. Neurological intervention, mainly aneurysm clipping and endovascular embolisation, was also incorporated as an intermediate event in developing a neurological intervention transition (NIT) joint model. A retrospective cohort study was performed on 701 patients in spontaneous SAH with a study period of 14 days from the MIMIC-IV dataset. A dynamic prognostic model predicting outcome of patients was developed based on combination of Cox model and piecewise linear mixed-effect models to incorporate different types of prognostic information. Clinical baseline covariates, including cerebral oedema, cerebral infarction, respiratory failure, hydrocephalus and vasospasm, as well as repeated measured Glasgow Coma Scale (GCS), glucose and white blood cell (WBC) levels were covariates contributing to the optimal model. Incorporation of neurological intervention as an intermediate event increases the prediction performance compared with baseline joint modelling approach. The average AUC of the optimal model proposed in this study is 0.7783 across different starting points of prediction and prediction intervals. The model proposed in this study can provide dynamic prognosis for spontaneous SAH patients and significant potential benefits in critical care management.
CuO nanoparticles for green synthesis of significant anti-Helicobacter pylori compounds with in silico studies
Authors: Shehab Wesam S. , Elsayed Doaa A. , Abdel Hamid Atef M. , Assy Mohamed G. , Mouneir Samar M. , Hamed Eman O. , Mousa Sahar M. , El-Bassyouni Gehan T. 
Published: January 2024

AbstractHelicobacter pylori (H. pylori) is a universal health intimidation as mentioned by the World Health Organization. The primary causal agent linked to a number of illnesses, including inflammation and the development of stomach ulcers, is Helicobacter pylori. Since, H. pylori develops antibiotic resistance quickly, current H. pylori treatment approaches are becoming less effective. Our research aims to highlight novel formulation antibiotics using CuO-NPs as catalysts and studied their activity as anti-helicobacter pylori supported by computational studies (POM analysis and molecular docking) software. They were designed for anti-Helicobacter Pylori action. All compounds revealed a bactericidal effect better than the reference McFarland standards.
Equilibrium points and their stability of COVID-19 in US
Authors: Hu Xiaoxi , Hu Zixin , Xu Tao , Zhang Kai , Lu Henry H. , Zhao Jinying , Boerwinkle Eric , Jin Li , Xiong Momiao 
Published: January 2024

AbstractThis study aims to develop an advanced mathematic model and investigate when and how will the COVID-19 in the US be evolved to endemic. We employed a nonlinear ordinary differential equations-based model to simulate COVID-19 transmission dynamics, factoring in vaccination efforts. Multi-stability analysis was performed on daily new infection data from January 12, 2021 to December 12, 2022 across 50 states in the US. Key indices such as eigenvalues and the basic reproduction number were utilized to evaluate stability and investigate how the pandemic COVD-19 will evolve to endemic in the US. The transmissional, recovery, vaccination rates, vaccination effectiveness, eigenvalues and reproduction numbers ($${R}_{0}$$

R
0

and $${R}_{0}^{end}$$

R

0

end

) in the endemic equilibrium point were estimated. The stability attractor regions for these parameters were identified and ranked. Our multi-stability analysis revealed that while the endemic equilibrium points in the 50 states remain unstable, there is a significant trend towards stable endemicity in the US. The study's stability analysis, coupled with observed epidemiological waves in the US, suggested that the COVID-19 pandemic may not conclude with the virus's eradication. Nevertheless, the virus is gradually becoming endemic. Effectively strategizing vaccine distribution is pivotal for this transition.
Relationship between dietary characteristics and heel quantitative ultrasound parameters in postmenopausal women from the OsteoLaus cohort
Authors: Lanyan A. , Marques-Vidal P. , Métrailler A. , Gonzalez Rodriguez E. , Hans D. , Shevroja E. , Lamy O. 
Published: January 2024

AbstractThe role of dietary patterns in the development of osteoporosis is unclear. The heel quantitative ultrasound (QUS) is a potential alternative to Dual X-Ray Absorptiometry. Nutrients, foods, dietary patterns and compliance to dietary guidelines were compared between the lowest and the highest tertiles of QUS parameters [Broadband Ultrasound Attenuation (BUA), Speed of Sound (SOS), Stiffness Index (SI)], using data from the OsteoLaus cohort. Participants in the highest tertiles of QUS parameters (385 for BUA, 397 for SOS, 386 for SI) were younger, of higher body weight, and had less major osteoporotic fractures. Women in the highest tertiles of SI and BUA consumed more fat (35.1 ± 0.4 vs 33.9 ± 0.4 and 34.9 ± 0.4 vs 33.8 ± 0.4 gr/day for SI and BUA, respectively, p < 0.05), and complied less frequently with dairy intake guidelines [odds ratio (95% confidence interval): 0.70 (0.53–0.92) and 0.72 (0.55–0.95) for SI and BUA, respectively, p < 0.05] than women in the lowest tertile. No differences were found regarding dietary patterns, healthy dietary scores, or compliance to dietary guidelines. Postmenopausal women in the highest QUS tertiles were younger, of higher weight and BMI, consumed more monounsaturated fatty acids and less dairy and calcium than women in the lowest tertiles. No differences were found between QUS tertiles regarding dietary patterns.
Factors affecting patient activation among patients with systemic lupus erythematosus
Authors: Wang Zhixia , Song Yuqing , Ou Lihong , Liao Dengbin , He Lingxiao , Ning Qian , Chen Yanling , Chen Hong 
Published: January 2024

AbstractThere are limited published studies on patient activation among patients with systemic lupus erythematosus (SLE) in China. Disease activity can significantly influence a patient's perception of their condition, subsequently impacting patient activation. However, the mechanisms through which disease activity influences patient activation remain poorly understood. This study aimed to investigate patient activation among patients with SLE in China and explore the influencing factors. We conducted a cross-sectional study from June to December 2021 at a rheumatology and immunology department of a tertiary hospital in Chengdu, China. Data were collected by questionnaire, including general information, disease activity, quality of chronic illness care, health literacy, self-efficacy, motivation, social support, and patient activation. A patient activation model was constructed based on the conceptual framework derived from the individual and family self-management theory. To evaluate the moderating effect of disease activity on patient activation model, participants were divided into two subgroups (low disease activity group and high disease activity group). 426 SLE patients were included. The mean score of patient activation among SLE patients was 63.28 ± 11.82, indicating that most SLE patients lacked skills and confidence to stick with health-promoting behaviors. Health literacy, social support, and self-efficacy had the greatest effect on patient activation. In the multi-group analysis, social support and health literacy contributed more to patient activation in SLE patients with high and low disease activity, respectively. Patient activation among SLE patients in China was at the third level. Healthcare professionals should help them adhere to health-promoting behaviors. Health literacy, social support, and self-efficacy are vital factors for patient activation. These factors should be prioritized based on disease activity when developing individually tailored interventions for patient activation.
Factors associated with cam deformity in Japanese local residents
Authors: Tomomatsu Koichi , Taniguchi Takaya , Hashizume Hiroshi , Harada Teiji , Iidaka Toshiko , Asai Yoshiki , Oka Hiroyuki , Muraki Shigeyuki , Akune Toru , Kawaguchi Hiroshi , Nakamura Kozo , Yoshida Munehito , Tanaka Sakae , Yoshimura Noriko , Yamada Hiroshi 
Published: January 2024

AbstractFemoroacetabular impingement has increasingly been recognized as a cause of primary hip osteoarthritis; however, its epidemiological indications remain unclear. We aimed to clarify the epidemiological indications and factors associated with cam deformity in a large-scale population-based cohort in Japan. Overall, 1480 participants (2960 hips) (491 men, 989 women; mean age, 65.3 years) analyzed in the third survey of the Research on Osteoarthritis/Osteoporosis Against Disability study were included. The α angle and spinopelvic parameters (lumbar lordosis, sacral slope, pelvic tilt, and pelvic incidence) were radiographically measured. Cam deformity was defined as α angle ≥ 60°. Overall, the cam deformity prevalence was 147/2960 (5.0%). Cam deformity prevalence tended to increase with age; in the univariate analysis, a higher percentage of men was observed in the group with cam deformity than in the group without it. No relationship was observed between cam deformity and hip pain. Factors associated with α angle were examined via multiple regression analysis for each gender; α angle was significantly associated with age and BMI in each gender. The α angle and PT were correlated in women. Thus, α angle and cam deformity prevalence increase with age in Japanese individuals. Accordingly, cam deformity can be considered a developmental disease.
Advancing wavefront shaping with resonant nonlocal metasurfaces: beyond the limitations of lookup tables
Authors: Isnard Enzo , Héron Sébastien , Lanteri Stéphane , Elsawy Mahmoud 
Published: January 2024

AbstractResonant metasurfaces are of paramount importance in addressing the growing demand for reduced thickness and complexity, while ensuring high optical efficiency. This becomes particularly crucial in overcoming fabrication challenges associated with high aspect ratio structures, thereby enabling seamless integration of metasurfaces with electronic components at an advanced level. However, traditional design approaches relying on lookup tables and local field approximations often fail to achieve optimal performance, especially for nonlocal resonant metasurfaces. In this study, we investigate the use of statistical learning optimization techniques for nonlocal resonant metasurfaces, with a specific emphasis on the role of near-field coupling in wavefront shaping beyond single unit cell simulations. Our study achieves significant advancements in the design theoretical conception of resonant metasurfaces. For transmission-based metasurfaces, a beam steering design outperforms the classical design by achieving an impressive efficiency of 80% compared to the previous 23%. Additionally, our optimized extended depth-of-focus (EDOF) metalens yields a remarkable five-fold increase in focal depth, a four-fold enhancement in focusing power compared to conventional designs and an optical resolution superior to 600 cycle/mm across the focus region. Moreover, our study demonstrates remarkable performance with a wavelength-selected beam steering metagrating in reflection, achieving exceptional efficiency surpassing 85%. This far outperforms classical gradient phase distribution approaches, emphasizing the immense potential for groundbreaking applications in the field of resonant metasurfaces.