bluuebunny/crossref_metadata_2025_split huggingface dataset:
Tumor preventive and antioxidant efficacy of chlorogenic acid loaded chitosan nanoparticles in experimental skin carcinogenesis
Authors: Neelakandan M. , Manoharan S. , Muralinaidu R. , Monsi@Thara J. 
Published: November 2022

Abstract
Oxidative stress, a pathological condition, contributes to the pathophysiology of a number of diseases including carcinogenesis. Numerous studies pointed out the disturbed antioxidants status and accumulation of oxidative stress markers in the carcinogenesis. The present study analysed the anticancer efficacy of chlorogenic acid loaded chitosan nanoparticles by utilizing the oxidative stress biomarkers as an endpoint in mice with skin cancer developed by 7,12-dimethylbenz(a)anthracene (DMBA). Oxidative stress markers (lipid peroxidation by-products and antioxidants) levels or activities were measured using colorimetric assays. While mice exposed with DMBA alone showed a 100 percent tumour incidence, 0 and 50 percent tumor formation was seen in mice treated with DMBA + topical application of the nanoparticles and DMBA + orally administrated nanoparticles respectively. Also, the study noticed 33 percent and 67 percent tumor incidence was noticed in mice treated with DMBA + topical application of free chlorogenic acid and DMBA + orally administrated free chlorogenic acid respectively. The present study noticed that topical application of chlorogenic acid loaded chitosan nanoparticles to DMBA painted mice completely suppressed the tumour growth and restored the levels or activities of oxidative stress markers as compared to mice received DMBA + oral administration of chlorogenic acid loaded chitosan nanoparticles. The study observed chlorogenic acid loaded chitosan nanoparticles are more potent than free chlorogenic acid in preventing skin cancer in mice caused by DMBA. Thus, the present investigation explores the tumor inhibiting efficacy of chlorogenic acid loaded chitosan nanoparticles in experimental skin cancer and the tumor preventive efficiency could be attributed to their antilipid peroxitative and antioxidants effects.
Circular Economy of Medical Waste: Novel Intelligent Medical Waste Management Framework Based on Extension Linear Diophantine Fuzzy FDOSM and Neural Network Approach
Authors: Chew XinYing , Khaw Khai Wah , Alnoor Alhamzah , Ferasso Marcos , Halbusi Hussam Al , Muhsen Yousif Raad 
Published: November 2022

Abstract
The COVID-19 pandemic has caused overwhelming levels of medical waste, resulting in constant threats to environmental pollution. Furthermore, many environmental issues related to medical waste have emerged. This study aims to propose an application that allows the identification and classification of hospitals that generate overwhelming levels of medical waste aftermath of the COVID-19 pandemic by using Multi-Criteria Decision-Making methods (MCDM). MCDM was designed on the integration of the Analytic Hierarchy Process (AHP), linear diophantine fuzzy set-fuzzy decision by opinion score method (LDFN-FDOSM), and Artificial Neural Network (ANN) analysis. Ten hospital managers were interviewed to determine the volume of medical waste generated by the hospitals they manage. Five types of medical waste were identified: general waste, sharps waste, pharmaceutical waste, infectious waste, and pathological waste. Among these five types, pharmaceutical waste is appointed as one that most impacts the environment. After that 313 experts in the health sector with experience in sustainability techniques were targeted to determine the best and worst technique for the Circular Economy to manage medical waste using the neural network approach. Findings also revealed that incineration technique, microwave technique, pyrolysis technique, autoclave chemical technique, vaporised hydrogen peroxide, dry heat, ozone, and ultraviolet light were the most vital and effective methods to dispose of medical waste during the pandemic. Additionally, ozone was ranked first as the most Circular Economy-related method for medical waste disposal. Among the implications of this study for governments, policymakers, and practitioners identify actions that hospitals may consider regarding the Circular Economy concept. Another implication is the supportive role of policymakers in transitioning most pollutant hospitals to becoming more sustainable.
Prognostic Nomogram for Overall Survival in Upper Urinary Tract Urothelial Carcinoma (UTUC) Patients Treated with Chemotherapy: A SEER-Based Retrospective Cohort Study
Authors: Tian Cong , Liu Jun , An Lizhe , Hong Yang , Xu Qingquan 
Published: November 2022

Abstract
Objective: To establish a prognostic nomogram among UTUC patients who received chemotherapy.
Methods: 1195 UTUC patients who received chemotherapy were extracted from the Surveillance, Epidemiology, and End Results (SEER) database for the period between 2004 and 2015. Patients were randomly divided into a training and a validation set. Nomogram was constructed to predict 1-, 3-, and 5-year overall survival (OS) in those patients. Receiver-operating characteristic curves (ROCs), calibration plots, and Decision curve analysis (DCA) were applied to assess and compare the discrimination, accuracy, and practicability of the nomogram with 8th American Joint Committee on Cancer (AJCC) tumor node metastasis (TNM) staging system.
Results: Six clinical parameters were identified as independent prognostic factors for UTUC patients’ OS, including age, marital status, TNM stage, and surgical methods of the primary site. The ROC curves showed a satisfactory discrimination capacity of the nomogram, with 1-, 3-, and 5-year area under curve (AUC) values of 0.789, 0.772, and 0.763 in the training set and 0.772, 0.822, and 0.814 in the validation set, respectively. Calibration curves indicated a good agreement between actual observation and nomogram prediction. ROC and DCA curves showed our nomograms exhibited larger benefits than the 8th AJCC-TNM staging system.
Conclusions: A prognostic nomogram was established and validated to present individual predictions of OS among chemotherapeutic UTUC patients. This nomogram may assist clinicians in accurate survival prognostication, treatment decision-making, and design of future clinical trials.
Prevalence and risk factors of burden among caregivers of older emergency department patients
Authors: Zaalberg Tessel , Barten Dennis G. , Heugten Caroline M. , Klijnsma Petra , Knarren Lieve , Hiemstra Ytje , Kurvers Roel A.J. , Lekx Anita W. , Mooijaart Simon P. , Janssen-Heijnen Maryska 
Published: November 2022

Abstract
BACKGROUND: The number of older individuals that live independently at home is rising. These older individuals often rely on caregivers who have a similar age and health status. Therefore, caregivers may experience a high burden. We determined the prevalence and associating factors of burden among caregivers of older patients in the emergency department (ED).
METHODS: a cross-sectional study of primary caregivers of patients aged ≥ 70 years visiting the ED of a Dutch teaching hospital. Structured interviews were conducted with patients and their caregivers. Caregiver burden was measured using the caregiver strain index (CSI). Additionally, data from questionnaires and medical records were extracted to determine potential associating factors. Univariate and multivariate regression analyses were conducted to identify independent determinants for burden.
RESULTS: Seventy-eight caregivers (39%) experienced a high burden. Multivariate analysis showed a significant association between high caregiver burden and patients with cognitive impairment or dependency for instrumental activities of daily living (IADL) and more self-reported hours of care per day.
CONCLUSION: Almost 40% of older patients in the ED have a caregiver who experiences a high burden. Formal assessment in the ED may help provide adequate care to the patients and their caregivers.
Identification of Novel Immune Subtypes and Potential Hub Genes of Patients with Psoriasis
Authors: Li Yingxi , Li Lin , Tian Yao , Luo Jing , Huang Junkai , Zhang Litao , Zhang Junling , Li Xiaoxia , Hu Lizhi 
Published: November 2022

Abstract
Background
Psoriasis is a common, chronic and relapsing immune-related inflammatory dermal disease. Patients with psoriasis suffering from the recurrences is mainly caused by immnue response disorder. Thus, our study is aim to identify novel immnue subtypes and select targeted drugs for the precision therapy in different subtypes of psoriasis.
Methods
Differentially expressed genes of psoriasis were identified from the Gene Expression Omnibus database. Functional and disease enrichment were performed by Gene Set Enrichment Analysis and Disease Ontology Semantic and Enrichment analysis. Hub genes of psoriasis were selected from protein-protein interaction networks using Metascape database. The expression of hub genes were validated in human psoriasis samples by RT-qPCR and immunohistochemistry. Further, novel immune subtypes of psoriasis were identified by ConsensusClusterPlus package and its association with hub genes were calculated. Immune infiltration analysis were performed and its candidate drugs were evaluated by Connectivity Map analysis.
Results
182 differentially expressed genes of psoriasis were identified from GSE14905 corhot, in which 99 genes were significantly up-regulated and 83 genes were down-regulated. We then conducted funtional and disease enrichment in up-regulated genes of psoriasis. Five potential hub genes of psoriasis were obtained, including SOD2, PGD, PPIF, GYS1 and AHCY. The high expression of hub genes were validated in human psoriasis samples. Notably, two novel immune subtypes of psoriasis were determined and defined as C1 and C2. Bioinformatic analysis showed C1 and C2 had different enrichment in immune infiltration cells. Further, candidate drugs and mechanism of action that applicable to different subtypes were evaluated.
Conclusion
Our study identified two novel immnue subtypes and five potential hub genes of psoriasis. These findings might give insight into the pathogenesis of psoriasis and provide effective immunotherapy regimens for the precise treatment of psoriasis.
Digitizing analog seismograms of Iranian seismic stations - preserving records for strong earthquakes in Iran 1960-1990
Authors: Aghajani Mahdy , Ahmadi Hossein , Mirzaii Noorbakhsh , Batllo Josep 
Published: November 2022

Abstract
To preserve the analog records of historical earthquakes which occurred in and around Iran in digital form and to make them available for modern analyses techniques that require waveforms, we decided to scan seismograms of destructive earthquakes that occurred between 1960 and 1990. The seismograms have been recorded in five seismic stations deployed in Tehran, Mashhad, Kermanshah, Tabriz, and Shiraz by the Institute of Geophysics of the University of Tehran (IGUT). The restoration project of the old analog seismograms archived in the IGUT started in 2018. Seismograms were sorted by station and date to create a hardcopy data bank, and then those from large earthquakes with significant damage and casualties, and their larger aftershocks, were chosen to scan. At present, over 600 scanned seismograms from 52 major earthquakes, and their aftershocks larger than MW = 5.0 that occurred in and around Iran and some major and great tele-seismic earthquakes from abroad are available. The current digitization process in IGUT is done manually and is based on waveform vectorization. The provided databank is one of the most important sources of information for researchers in seismology and active tectonics in and around Iran.
Evaluation of allylestrenol for clinical pregnancies in patients treated with assisted reproductive techniques: a retrospective, propensity score matched, observational study
Authors: Yu Yuexin , Yu Tingting , Ding Weiping , Xiu Yinling , Zhao Mengsi , Sun Kaixuan , Zhang Qian , Xu Xiaohang 
Published: November 2022

Abstract
Background: Allylestrenol is an oral progestogen being increasingly used for luteal phase support (LPS) inassisted reproductive techniques. However, evidence of the clinical efficacy of allylestrenol in LPS is lacking. Dydrogesterone is a representative drug used for LPS, the efficacy of which has been clinically confirmed. As such, we aimed to compare the effects of allylestrenol with the standard dydrogesterone on clinical pregnancy rates and pregnancy outcomes.
Methods: This retrospective study included 3375 assisted reproductive technique cycles using either allylestrenol or dydrogesterone between January 2015 and March 2020. Patients using either allylestrenol or dydrogesterone were matched in a 1:1 ratio using propensity scores. The primary outcomes were clinical pregnancy rate and pregnancy outcomes.
Results: No significant difference was found in the clinical pregnancy rate (54.4% vs.53.7%, P = 0.787) and pregnancy outcomes (all P > 0.05) between allylestrenol and dydrogesterone. Compared with dydrogesterone, the use of allylestrenol significantly reduced the rate of biochemical pregnancies (6.4% vs.11.8%, P < 0.001) and multiple gestation rate (16.8% vs.26.3%, P = 0.001). Moreover, endometrial thickness, morphology, and blood flow were significantly improved by allylestrenol treatment (all P < 0.05).
Conclusions: Allylestrenol exhibited similar effects on clinical pregnancy rates and pregnancy outcomes as dydrogesterone. Moreover, allylestrenol had a more positive impact on biochemical pregnancy and endometrial receptivity.
Psychometric Properties of the China Developmental Scale of Children in Infant Aged 0-1 Years old with developmental delay: A Rasch Analysis
Authors: Peng Kanglong , Wang Jinggang , Liu Guixiang , Tan Zhujiang 
Published: November 2022

Abstract
Background: Children development is a multidimensional construct encompassing gross motor, fine motor, adaptive behavior, speech and language, and social behavior. The China Developmental Scale of Children (CDSC) has been tested using traditional methods. This study aimed to make amendment to previous evidence by using Rasch Model and elaborate the psychometric properties of the CDSC in a new perspective.
Methods: 200 children and infants were recruited and finished the CDSC. Data were collected and used for the analysis. Rasch Model was adopted to test the psychometric properties of the CDSC regard the fitness to the prediction of the Model. Unidimensionality was tested using principal component analysis. Differential item functioning (DIF) analysis was performed across gender and age group (older or younger than 6.5 months old).
Result: Data from 200 children with developmental delays were obtained. The result showed that the items from the CDSC presented acceptable fitness to the Rasch Model(Person Infit MNSQ:0.83~0.9;Item Infit MNSQ:0.9~0.93). Besides, 11 unfitting(misfitting or overfitting) items were found. The impact of the unfitting items on the average fit statistics was evaluate by reanalysis, and the result showed that the person reliability and separation were lower while the infit MNSQ got higher. The unidimensionality was supported by the result of the principal component analysis(Measures explained variance:79.6%~87.8%). Further, the reliability and the separation index of the item and person indicated that the assumption of the internal consistency was confirmed (Person.Reliability:0.91~0.96; Person.Separation:4.27~3.5; Item.Reliablity:0.99~1; Item.Separation:13.39~19.28).
Conclusion: Our study found that the CDSC had shown reasonable fitness to the Rasch Model. The result support that the CDSC was established based on a unidimensional structure with good internal consistency. The misfitting items still required reformulation to demonstrate corresponding content more clearly.
Identification of key genes in platelets associated with COVID-19 using a weighted gene co-expression network analysis
Authors: You Hongjun , Zhao Qianqian , Dong Mengya , Gou Qiling 
Published: November 2022

Abstract
There is growing evidence of a strong relationship between COVID-19 and thrombosis. However, few bioinformatics-based analyses of critical genes and the mechanisms related to COVID-19 thrombosis existed. This study aimed to identify critical genes related to COVID-19 thrombosis by bioinformatic methods and explore the biological mechanisms and gene regulatory networks. The gene expression data were obtained from the Gene Expression Omnibus (GEO). Significant modular genes in GSE176480 were identified by weighted gene correlation network analysis and overlapped with differentially expressed genes by R package ‘DESeq2’ to obtain common genes. Functional enrichment analyses indicated that common genes were mainly enriched in biological processes such as platelet activation, signaling and aggregation, neutrophil degranulation and immune system and VEGFA-VEGFR2 signaling pathway et al. Finally, 16 genes (RPLP0, RPS4X, RPL13A, RPL13, RPL10, TPT1, PSMA7, ATP5D, AKT1, HIST1H2AC, HIST1H2BH, H3F3B, KDM6A, GATA3, ITGAM and RBMX) were identified as potential hub genes. Our study provides a new perspective to explore the pathogenesis and gene regulatory networks of thrombosis in COVID-19. It is worth highlighting that critical genes may be potential biomarkers and treatment targets of COVID-19 thrombosis for future study.
The Use of Oral Benzodiazepines for the Management of Dental Anxiety: A Web-based Survey of UK Dentists
Authors: Thompson Wendy , Finn Kathryn , Moore Deborah , Dailey Yvonne 
Published: November 2022

AbstractBackground Oral benzodiazepines can facilitate treatment of dentally anxious patients and are widely used in countries such as Australia and the United States. Dentists in the United Kingdom (UK) prescribe them much less often. Aims To examine oral benzodiazepine prescribing by dentists in the UK, including patterns of practice, barriers to use, and alternative anxiety management strategies. Methods An online mixed-methods survey was conducted utilising Qualtrics™. Participants were recruited via the Facebook private group: For Dentists, By Dentists during April to June 2021. Quantitative data were analysed with descriptive statistics and qualitative data with thematic analysis. Results 235 dentists participated, with 91% being general dentists. Only 18% were confident in their use. Half had previously prescribed oral benzodiazepines, of which 36% were in the last year. Diazepam was the anxiolytic preferred by respondents. Two thirds of dentists who had never prescribed anxiolytics were interested in doing so in the future. Concerns about managing anxious patients with benzodiazepines included: inadequate training, confusion about guidelines, medico-legal risk, and issues of GPs prescribing anxiolytics to dental patients unbeknown to their dentist. Conclusions A lack of confidence prescribing oral benzodiazepines for anxiolysis exists among UK dentists. Guidelines should be clarified, and training provided.
Quartet RNA reference materials and ratio-based reference datasets for reliable transcriptomic profiling
Authors: Yu Ying , Hou Wanwan , Wang Haiyan , Dong Lianhua , Liu Yaqing , Sun Shanyue , Yang Jingcheng , Cao Zehui , Zhang Peipei , Zi Yi , Li Zhihui , Liu Ruimei , Gao Jian , Chen Qingwang , Zhang Naixin , Li Jingjing , Ren Luyao , Jiang He , Shang Jun , Zhu Sibo , Wang Xiaolin , Qing Tao , Bao Ding , Li Bingying , Li Bin , Suo Chen , Pi Yan , Wang Xia , Dai Fangping , Scherer Andreas , Mattila Pirkko , Han Jinxiong , Zhang Lijun , Jiang Hui , Thierry-Mieg Danielle , Thierry-Mieg Jean , Xiao Wenming , Hong Huixiao , Tong Weida , Wang Jing , Li Jinming , Fang Xiang , Jin Li , Xu Joshua , Qian Feng , Zhang Rui , Zheng Yuanting , Shi Leming 
Published: November 2022

Abstract
As an indispensable tool for transcriptome-wide analysis of differential gene expression, RNA sequencing (RNAseq) has demonstrated great potential in clinical applications such as companion diagnostics and prognostics. However, there is a lack of certified RNA reference materials and the corresponding reference datasets of differential expression for assessing the reliability of RNAseq for its intended use in detecting intrinsically small biological differences in clinical settings such as molecular subtyping of diseases. As part of the Quartet Project for quality control and data integration of multiomics profiling, we established four RNA reference materials derived from immortalized B-lymphoblastoid cell lines from four members of a monozygotic twin family. Additionally, we constructed ratio-based transcriptome-wide reference datasets between two reference samples, providing "ground truth" for cross-platform and cross-lab proficiency test. Moreover, Quartet-sample-based quality metrics were developed for assessing the reliability of RNAseq technology in terms of intra-batch measurement and cross-batch data integration. The small intrinsic biological differences among the Quartet samples enabled sensitive assessment of performance of transcriptomic measurements and their cross-batch integration at the ratio level. The Quartet RNA reference materials combined with the ratio-based reference datasets can serve as unique resources for assessing data quality and improving reliability of transcriptomic profiling.
Inconsistency in the 11-point (0-10) Likert scale: evidence from subjective well-being survey
Authors: Chen Yue-mei-tong , Fang Zhou 
Published: November 2022

Abstract
In this paper, we verified an inconsistency of understanding in the 0 to 10 Likert Scales with a survey experiment. We recruited 121 college students at a public university in California and had them answer a hypothetical subjective well-being survey. The survey contains 23 happy or unhappy events, and the students are told to report how happy/unhappy they would feel if the event happened to them on 11-point Likert Scales. We found an inconsistent understanding in the responses when the expected value is around 7 to 8 on a 0 to 10 Likert scale. Our finding suggests that a scale of another length or a -5 to 5 scale can be used as an alternative to improve the data quality.
Complexity-driven Risk Decision Framework for Cost Overrun using Fuzzy-Bayesian Network
Authors: Afzal Farman , Afzal Fahim , Junaid Danish , Shah Imran Ahmed , Yunfei Shao 
Published: November 2022

Abstract
This study adheres to find important complexity-risk interdependent causes of cost overrun in infrastructure transport projects rather considering an independent state of project risk. Aiming for addressing cost overrun problem to facilitate decision-makers, a hierarchical breakdown structure of complex elements and complexity-driven risk factors at different levels of severity is conceptualized along with their interdependency network of key relationships. In this work, an integrated approach of fuzzy logic with the Bayesian belief network is employed for cost-risk assessment while assuming linguistic scales of likelihood and consequences parameters. The simulated results of cost-risk decision framework imply that poor design issues, increase in material prices and delay in relocating facilities show higher complexity-risk dependency and increase the risk of cost overrun in complex projects. This study contributes to the body of knowledge by providing a practical hybrid risk decision framework to identify and evaluate the key complexity-risk interdependencies in underline relations to the cost overrun problem in construction.