bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploring the possible mechanism involved in the anti-nociceptive effect of β-sitosterol: Modulation of oxidative stress, nitric oxide and IL-6
Authors: Kaur Kiranjot , Singh Lovedeep , Kaur Anudeep , Bhatti Rajbir 
Published: September 2022

Abstract
β-sitosterol is a phytosterol, documented to possess various activities including inflammation, diabetes, Alzheimer's disease etc. The current investigation was designed to explore the analgesic potential of β-sitosterol and the possible molecular mechanism involved in the observed effect. β-sitosterol was administered at varying doses of 10, 20, and 40 mg/kg before subjecting the mice to acetic acid and formalin challenges. The number of writhings in acetic acid and the number of flinchings and foot tappings were quantified in the formalin test. For mechanistic studies, substance P (COX-2 stimulator) and L-NAME (NOS inhibitor) and L-arginine (NO precursor) were administered before β-sitosterol treatment. β-sitosterol (10, 20, 40 mg/kg) treatment significantly reduced acetic acid-induced writhings and ameliorated the formalin-induced inflammatory phase dose-dependently. Whereas, 40 mg/kg dose of β-sitosterol abrogated formalin-induced neurogenic phase. Substance-P abrogated the effect of β-sitosterol in both neurogenic and inflammatory phases. Whereas, L-arginine only abrogated the inflammatory phase. In biochemical analysis, β-sitosterol treatment reduced the level of IL-6, TBARS and increased the GSH level. Furthermore, L-arginine and substance-P abrogated the GSH increasing and TBARS lowering effect of β-sitosterol (40 mg/kg). Overall, the current study delineated that β-sitosterol might induce anti-nociceptive effect via inhibiting the IL-6, oxidative stress, cyclo-oxygenase and nitric oxide.
Clinical symptoms and radiologic features of airway abnormalities assessed by impulse oscillometry in patients with chronic obstructive pulmonary disease
Authors: Lu Lifei , peng Jieqi , Wu Fan , Yang Huajing , Zheng Youlan , Deng Zhishan , Zhao Ningning , Dai Cuiqiong , Xiao Shan , Wen Xiang , Xu Jianwu , Wu Xiaohui , Zhou Kunning , Ran Pixin , Zhou Yumin 
Published: September 2022

Abstract
Background: Airway abnormalities assessed by impulse oscillometry (IOS) were common in patients with chronic obstructive pulmonary disease (COPD). However, most studies only used difference from R5 to R20 (R5-R20) > 0.7kPa/L/s to diagnose airway abnormalities, which may ignore the value of other IOS indicators in the diagnosis of airway abnormalities. Our study aimed to comprehensively assess clinical symptoms and radiologic features of airway abnormalities in COPD patients in China.
Methods: We enrolled 805 COPD patients from a part of ECOPD cohort, they underwent questionnaires, symptom scores, lung function, IOS and HRCT. The criteria of airway abnormalities were based on standardized IOS reference values. Logistic regression was used to analyze risk factors of airway abnormalities. The associations between acute exacerbation of COPD (AECOPD) in the previous year and airway abnormalities were assessed by Poisson regression. Logistic regression was used to assess the associations between CT imaging and airway abnormalities.
Results: The proportion of airway abnormalities evaluated by other indicators increased gradually with COPD severity except for R20. Multivariate logistic analysis showed dyspnea, low FEV1% predicted and airway obstruction were associated with risk of airway abnormalities. Compared with normal airway group, airway abnormalities group had more clinical symptoms (wheeze and dyspnea) and higher mMRC and CAT scores. Airway abnormalities assessed by X5 and AX had more emphysema, gas trapping and higher risk of AECOPD in the previous year.
Conclusions: Reactance (X5, AX) assessment of airway abnormalities had more clinical symptoms, emphysema, gas trapping and higher risk of AECOPD in the previous year.
Spatial Proximity of Tumor Infiltrating Immune Cells Uncovers a Novel Insight in Pulmonary Lymphoepithelial Carcinoma
Authors: Hsu Wei-Hsun , Hsu Chia-Chi , Hsieh Min-Shu , Tai Pei-Chen , Huang Derek De-Rui , Lee Jih-Hsiang , Lin Chia-Chi , Chang Yih-Leong , Yang James Chih-Hsin 
Published: September 2022

Abstract
Pulmonary lymphoepithelial carcinoma (LEC) is a rare type of lung cancer. Though the clinical outcomes of patients with LEC are better than those for patients with other types of lung cancer, tumors frequently recur. Evidence has indicated that the immune microenvironment factors may predict outcome of cancer therapy; however, the composition of immune microenvironment in LEC remains largely unknown. We investigated the association between the immune microenvironment of LEC by using multiplex immunohistochemical staining. The densities of each tumor-infiltrating immune cell type and the amount of infiltrating immune cells spatially proximal to the closet tumor cell were analyzed. Although there was no significant correlation between the clinical outcome of LEC and the density of each tumor-infiltrating immune cell type, we found that the amount of CD4 + T lymphocyte proximal to tumor positively trended to longer disease-free survival in LEC. Additionally, the PD-L1 tumor proportion score was highly correlated with the amount of CD8 + T lymphocyte proximal to tumor, suggesting that immunotherapy might be beneficial for LEC patients. The spatial proximity of tumor-infiltrating immune cell measurement is useful for investigating the tumor-immune cells interaction. The spatial proximity of tumor-infiltrating CD4 + T lymphocytes might serve as a good prognostic factor for LEC.
Solution Printable Multifunctional Polymer-Based Composites for Smart Electromagnetic Interference Shielding with Tunable Frequency and On-Off Selectivities
Authors: Seol Mina , Hwang Uiseok , Kim Junyoung , Eom Deokjoon , Park In-Kyung , Kim Hyoungsub , Suhr Jonghwan , Nam Jae-Do 
Published: September 2022

Abstract
The advances in modern intelligent electronic systems have a pressing need for smart electromagnetic interference (EMI) shielding capabilities in a frequency-selective manner to choose which electromagnetic waves in a certain range to be blocked. Herein, we present multilayered EMI shielding composites that can provide selective on-off characteristics for specific frequency ranges across a broad spectrum. The composites are composed of outermost dielectric layers and conductive interlayers fabricated via solution-printing, wherein hexagonal boron nitride (BN) and silver-coated BN particles are embedded, respectively. The EMI shielding frequency range and on-off selectivity are controllable by varying the configuration of the composite structure in terms of the BN content and the number of composite layers, providing different interstitial spaces between the fillers and interfacial dielectric properties. Furthermore, the optimal combination of these layers permits excellent combinatorial properties of EMI shielding (32–62 dB), thermal conductivity (7.61 W/m·K), and electrical insulation (4.03 kV/mm) in the through-plane direction. The developed composites and their synthetic pathways have enormous potential for tailored material design and flexible system integration in next-generation EMI shielding technologies.
Efficient anti-tumor immunotherapy using tumor epitope-coated biodegradable nanoparticles combined with polyinosinic-polycytidylic acid and an anti-PD1 monoclonal antibody
Authors: Kim Sang-Hyun , Park Ji-Hyun , Lee Sun-Jae , Lee Hee-Sung , Jung Jae-Kyung , Lee Young-Ran , Cho Hyun-Il , Kim Jeong-Ki , Kim Kyungjae , Park Chan-Su , Lee Chong-Kil 
Published: September 2022

AbstractBackgroundVaccination with tumor peptide epitopes associated with major histocompatibility complex class I molecules is an attractive approach directed at inducing tumor-specific cytotoxic T lymphocytes (CTLs). However, challenges remain in improving the therapeutic efficacy of peptide epitope vaccines, including the low immunogenicity of peptide epitopes and insufficient stimulation of innate immune componentsin vivo. To overcome this, we aimed to develop and test an innovative strategy that elicits potent CTL responses against tumor epitopes. The essential feature of this strategy is vaccination using tumor epitope-loaded nanoparticles (NPs) in combination with polyinosinic-polycytidylic acid (poly-IC) and anti-PD1 monoclonal antibody (mAb).MethodsCarboxylated NPs were prepared using poly(lactic-co-glycolic acid) and poly(ethylene/maleic anhydride), covalently conjugated with anti-H-2KbmAbs, and then attached to H-2Kb molecules isolated from the tumor mass (H-2b). Native peptides associated with the H-2Kbmolecules of H-2Kb-attached NPs were exchanged with tumor peptide epitopes. The tumor-specific CTL-inducing and anti-tumor activities of the tumor epitope-loaded NPs were examined in mice bearing EG7-OVA thymoma or B16-F10 melanoma. In addition, the anti-tumor therapeutic efficacy of the NPs was examined in combination with poly-IC, anti-PD1 mAb, or both.ResultsTumor peptide epitope-loaded NPs efficiently induced tumor-specific CTLs when used to immunize tumor-bearing mice as well as normal mice. This activity of the NPs significantly was increased when co-administered with poly-IC. Accordingly, the NPs exerted significant anti-tumor effects in mice implanted with EG7-OVA thymoma or B16-F10 melanoma, and the anti-tumor activity of the NPs was significantly increased when applied in combination with poly-IC. The most potent anti-tumor activity was observed when the NPs were co-administered with both poly-IC and anti-PD1 mAb.ConclusionsImmunization with tumor epitope-loaded NPs in combination with poly-IC and anti-PD1 mAb in tumor-bearing mice can be a powerful means to induce tumor-specific CTLs with therapeutic anti-tumor activity.
The Effect of dialysis rate on continuous renal replacement therapy for neonatal hyperammonemia
Authors: Chu Xiaoyun , Sun Yifan , Hong Wenchao , Gong Xiaohui , Cai Cheng 
Published: September 2022

Abstract
Background
CRRT has attracted more and more attention in the treatment of acute neonatal hyperammonemia.
Methods
We retrospectively analyzed the clinical data of hyperammonemic neonates treated with CRRT in the neonatal intensive care unit (NICU) of Shanghai Children's Hospital from August 2016 to September 2021, and further explored the relationship between the rate of decrease of blood ammonia and dialysis rate.
Results
A total of 6 cases of neonatal hyperammonemia were included, their primary diseases were 3 cases of ornithine transcarbamyltransferase deficiency (OTCD), 1 case of carbamoyl phosphate synthetase 1 deficiency (CPS1D), 1 case of methylmalonic acidemia (MMA) with homocysteinemia (combined MMA) and 1 case of transient hyperammonemia. All infants developed impaired consciousness, convulsions and severe hyperammonemia, so CRRT was superimposed on diet control and medication, and the mode of continuous venovenous hemodiafiltration (CVVHDF) was used in all cases. The gestational age at birth was (37.98 ± 1.12) weeks, the age at onset was (1.91 ± 0.91) d, and the weight at CRRT was (3157.50 ± 605.95) g. The dialysis rate was (880–3937) ml/h/1.73m2, the decrease rate of blood ammonia was (15.79–33.33) µmol/h, and the duration of CRRT diversion was 44–110 h. The decrease rate of blood ammonia increased with the increase in dialysis rate, without an increase in the incidence of serious complications.
Conclusions
CRRT can alleviate the metabolic crisis of hyperammonemic neonates, and increasing the dialysis rate of CRRT can safely and more effectively reduce blood ammonia levels in critically hyperammonemic neonates.
Amide proton transfer MRI differentiates between progressive multifocal leukoencephalopathy and malignant brain tumors: a pilot study
Authors: Koike Hirofumi , Morikawa Minoru , Ishimaru Hideki , Ideguchi Reiko , Uetani Masataka , Hiu Takeshi , Matsuo Takayuki , Miyoshi Mitsuharu 
Published: September 2022

Abstract
Background
Progressive multifocal leukoencephalopathy (PML) is a demyelinating disease of the central nerve system caused by the John Cunningham virus. On MRI, PML may sometimes appear similar to primary central nervous system lymphoma (PCNSL) and glioblastoma multiforme (GBM). The purpose of this pilot study was to evaluate the potential of amide proton transfer (APT) imaging for differentiating PML from PCNSL and GBM.
Methods
Patients with PML (n = 3; two men; mean age 52.0 ± 7.0 years), PCNSL (n = 7; four women; mean age 74.4 ± 5.8 years), or GBM (n = 11; 6 men; mean age 65.0 ± 15.2 years) who underwent APT-CEST MRI between January 2021 and July 2022 were retrospectively evaluated. Magnetization transfer ratio (MTR) values were measured on APT imaging using a region of interest within the lesion. Receiver operating characteristics curve analysis was used to determine diagnostic cutoffs for MTR.
Results
The mean MTR values were 0.005 ± 0.006 in the PML group, 0.025 ± 0.005 in the PCNLS group, and 0.025 ± 0.009 in the GBM group. There were significant differences in MTR between PML and PCNSL (P = 0.050), and between PML and GBM (P = 0.039). For differentiating PML from PCNSL, an MTR threshold of 0.0165 gave diagnostic sensitivity, specificity, positive predictive value, and negative predictive value of 100% (all). For differentiating PML from GBM, an MTR threshold of 0.015 gave diagnostic sensitivity, specificity, positive predictive value, and negative predictive value of 90.9%, 100%, 100%, and 97.6%, respectively.
Conclusion
MTR values obtained from APT imaging allowed patients with PML to be clearly discriminated from patients with PCNSL or GBM.
LFD-CNN: Levy Flight Distribution based Convolutional Neural Network for an Adaptive Learning Style Prediction in E-learning Environment
Authors: Alshmrany Sami 
Published: September 2022

Abstract
One of the essential factors in any learning environment is a learning style that deals with individual learning. With different learning styles, each learner has different ways of understanding, retaining, processing, and perceiving new knowledge. Automatic student learning style determination has become an important ability of the e-learning system. For learning events, the evolution of e-learning platforms provides students with higher opportunities online. In this article, we proposed a Convolutional Neural Network-based Levy Flight Distribution (CNN-LFD) algorithm for learning style prediction. An adaptive e-learning system is broken up into an automatic learning style prediction and classification based on the number of learning styles incorporated. Initially, the learner's login the ID, and the data are stored in the database. The features such as questionnaire score, login credentials (session ID, learner ID, and course ID), and login time (location, session ID) are extracted. After that, the CNN-LFD algorithm predicts the learners learning styles namely Active/reflective, Sensing/intuitive, visual/verbal, sequential/global based on the extracted features. The dataset details are obtained from Massive Open Online Course (MOOC) and the proposed model is implemented in JAVA software. The experimental results demonstrate higher classification accuracy during learning style prediction.
Intentional and actional components of engaged participation in public health research studies: qualitative synthesis of a recruitment and retention process into the theory-informed INTACT-RS framework
Authors: Lander Jonas , Heiberger Andrea , von Sommoggy Julia , Schulz Anja Alexandra , Dresch Carolin , Hala Altawil , Schmitt Gwendolyn , Wirtz Markus Antonius 
Published: September 2022

Abstract
Background
Ensuring motivated and successful study participation is a key challenge in the design and conduct of health research studies. Previously, recruitment barriers and facilitators have been identified mainly from experience, and rarely based on theoretical approaches. We developed a framework of intentional and actional components of engaged participation in public health research studies (INTACT-RS) based on psychological behavioral models. We aimed a) to identify precise indicators for each component of the framework and b) to better understand which components and decision processes are essential to interested and committed participation by study participants.
Methods
Within a multicenter research network, we applied various approaches to recruit parents of newborns, pediatricians, and midwives. All recruitment processes were documented from the perspective of both participants and researchers. We used different qualitative and quantitative data material, which we applied in a multistage process according to the basic principles of qualitative content analysis.
Results
INTACT-RS encompasses pre-intentional, intentional and actional phases with a total of n = 15 components covering all aspects of an individual’s involvement with a research study. During intention formation, an understanding of efforts and benefits, why participation is valuable beyond contributing to research, and how others perceive the study, were particularly important to (potential) participants. Subsequently (intentional phase), participants consider how and when participation is compatible with their own resources, ability and availability, and hence seek for close communication with, and flexibility and support from the research team. During and after (initial) participation (actional phase), participants’ assessment of whether expectations and interests have been met impact crucial further steps, especially the willingness to continue and to recommend participation to others. A strong topic-wise and or supportive participation interest as well as active, continuous exchange with the researchers appeared to be central determinants of study completion and data validity.
Conclusions
A theoretical framework is now available to plan and conduct recruitment of different target groups, which accounts for essential motivational and volitional decision-making processes. Based on empirically specified constructs, possible barriers can be addressed even before the initial recruitment process. Therefore, recommendations for scientific practice have been formulated.
Diuretic resistance in acute decompensated HFpEF vs. HFrEF
Authors: Sharma Akash , Patel Rahul , Prasad Anand , Bansal Shweta 
Published: September 2022

Abstract
Background: Diuretic resistance (DR) is a common cause of inadequate decongestion in patients hospitalized with acute decompensated heart failure (ADHF). DR has not been characterized in patients with HF with preserved ejection fraction (HFpEF).
Methods: In a post-hoc analysis of a pilot study evaluating the role of high-dose spironolactone in ADHF patients with DR, we analyzed the prevalence and potential pathophysiologic factors of DR in HFpEF (n=20) and compared those with HF with reduced EF (HFrEF) (n=27). DR was defined as weight loss<1lb/day despite intravenous furosemide>160mg/day (at least one dose of 80mg/day).
Results: DR was observed in 10 (50%) of HFpEF participants as compared to 10 (37%) of HFrEF participants (p=ns). DR-HFpEF participants were older and had lower kidney function compared to DR-HFrEF. There was no difference in clinical presentation and lab parameters. Moreover, urine sodium/potassium ratio, plasma renin activity, plasma aldosterone and epinephrine levels were lower in DR-HFpEF as compared to DR-HFrEF, though still higher than diuretic responsive-HFpEF patients. Weight loss in response to high-dose spironolactone was similar in DR-HFpEF and HFrEF.
Conclusion: We demonstrate that DR is more prevalent in HFpEF compared to HFrEF patients. Despite similar clinical features of congestion and response to high-dose spironolactone, a state of reduced neurohormonal activation points that additional factors might be contributing to DR in HFpEF versus HFrEF patients.
A novel multi-pass machining accuracy prediction method for thin-walled parts
Authors: Huang Qiang , Wang Sibao , Wang Shilong , Zhao Zengya , Wang Zehua , Tang Binrui 
Published: September 2022

Abstract
Thin-Walled Parts (TWP) are widely used in aerospace, whose service performance is significantly affected by the machining accuracy. Considering the poor stiffness of TWP, multi-pass machining is used to machine TWP for better surface accuracy. However, it is difficult to accurately predict the final machining accuracy due to the surface topography error’s propagation and accumulation in multi-pass machining. Therefore, this paper proposes a multi-pass machining accuracy prediction method for TWP based on dynamic factors (cutting force and stiffness). Firstly, a flexible cutting force prediction model, which considers the axial errors determined by the initial surface topography and part deflection, is proposed. Secondly, a Position-Pass-Dependent Stiffness (PPDS) model is established considering position-dependent of stiffness and multi-pass machining material removal. Finally, combining the two models above, a multi-pass machining accuracy prediction method based on Genetic Algorithm - Back Propagation (GA-BP) neural network is proposed. The experiments under various conditions have been carried out to validate the proposed method. The machining accuracy (flatness as an example) is as high as 90.8% using the method in this paper, while it is only 73.9% when the accumulative error is neglected. The proposed method can significantly improve the performance of machining accuracy prediction by analyzing the error propagation mechanism and the effect of dynamic factors between multi-pass machining. Furthermore, this also provides a theoretical basis for process parameters optimization and machining accuracy improvement in TWP machining.
Small-Area Estimation and Analysis of HIV/AIDS Indicators for Precise Geographical Targeting of Health Interventions in Nigeria. A Spatial Microsimulation Approach
Authors: ABUBAKAR Eleojo Oluwaseun , CUNNINGHAM Niall 
Published: September 2022

Abstract
Background: Precise geographical targeting is well recognised as an indispensable intervention strategy for achieving many Sustainable Development Goals (SDGs). This is more cogent for health-related goals such as the reduction of the HIV/AIDS pandemic, which exhibits substantial spatial heterogeneity at various spatial scales (including at microscale levels). Despite the dire data limitations in Low and Middle Income Countries (LMICs), it is essential to produce fine-scale estimates of health-related indicators such as HIV/AIDS. Existing small-area estimates (SAEs) incorporate limited synthesis of the spatial and socio-behavioural aspects of the HIV/AIDS pandemic and/or are not adequately grounded in international indicator frameworks for sustainable development initiatives. They are, therefore, of limited policy-relevance, not least because of their inability to provide necessary fine-scale socio-spatial disaggregation of relevant indicators.
Methods: The current study attempts to overcome these challenges through innovative utilisation of gridded demographic datasets for SAEs as well as the mapping of standard HIV/AIDS indicators in LMICs using spatial microsimulation (SMS).
Results: The result is a spatially enriched synthetic individual-level population of the study area as well as microscale estimates of four standard HIV/AIDS and sexual behaviour indicators. The analysis of these indicators follows similar studies with the added advantage of mapping fine-grained spatial patterns to facilitate precise geographical targeting of relevant interventions. In doing so, the need to explicate socio-spatial variations through proper socioeconomic disaggregation of data is reiterated.
Conclusions: In addition to creating SAEs of standard health-related indicators from disparate multivariate data, the outputs make it possible to establish more robust links (even at individual levels) with other mesoscale models, thereby enabling spatial analytics to be more responsive to evidence-based policymaking in LMICs. It is hoped that international organisations concerned with producing SDG-related indicators for LMICs move towards SAEs of such metrics using methods like SMS.