bluuebunny/crossref_metadata_2025_split huggingface dataset:
Efficacy of a newly developed 0.025-inch guidewire for selective biliary access: Technical property analysis and a multicenter non-inferiority clinical trial
Authors: Park Do Hyun , Han Joung-Ho , Lee Tae Hoon , Yang Jae Kook , Lee Ji Sung , Lee Yong Hun , Kim Youngjung , Park Sang-Heum 
Published: August 2022

Abstract
A clinical efficacy study of 0.025-inch guidewires (GWs) according to mechanical property analysis has not been reported yet. This study was designed to evaluate the clinical efficacy of a newly developed 0.025-inch GW for biliary access according to the basic mechanical property. Commercially available 0.025-inch GWs were in vitro tested based on parameters of mechanical property. Patients with naïve papilla requiring diagnostic or therapeutic ERCP were randomly assigned to an experimental 0.025-inch newly developed GW or a control 0.025-inch GW group. Technical success rate of wire-guided cannulation (WGC), difficult biliary cannulation (DBC), and adverse event rates were measured in this multicenter randomized trial. The technical success rate of primary WGC was 79.1% (151 of 191) in the experimental group and 70.8% (131 of 185) in the control group (95% two-sided confidence interval: 8.25%; p<0.001; for a noninferiority margin of 15%). The technical success rate including cross-over to each other was also non-inferior. However, the chi-square test showed a statistical difference (81.7% vs. 68.1%; p=0.002). Median biliary cannulation time was shorter in the experimental group (53 seconds vs. 77 seconds; p=0.047). The rate of DBC was more frequent in the control group (34.6 % vs. 50.3% p=0.002). Multivariate analysis revealed that control group was one of contributing factors for DBC. Overall rate of post-ERCP pancreatitis was not different (4.7% vs. 8.6%; p=0.125). WGC using a newly developed GW with superior physical performance GW in a bench test showed similar clinical efficacy and the rate of DBC was significantly lower in experimental GW.
A Study on Wild Underutilized Edible Plant Species of Kokrajhar District of Assam (India) Consumed as Vegetables Having Ethno Medicinal Properties
Authors: Brahma Sanchita , Basumatary Mahadev Uzir , Nath Rupak Kumar , Pegu Lolesh 
Published: August 2022

Abstract
A study was attempted to take stock of the conventional underutilised edible plants available in the Kokrajhar district of Assam, NE India having ethno-medicinal properties and utilised as a source of herbal medicines by the tribal people of the district. The district is demographically inhabitted by Bodos, Rava, Koch Rajbongshi, Santhal, Orao, Muslim, Nepali, Bengali, etc., and the Bodos are the commanding inhabitants of Kokrajhar district of Assam, belonging to the schedule tribe (plain). They are mainly dependent on edible plant resources growing wild in natural habitats for their day-to-day activities. Vegetables are the protective foods that play an important role in a balanced diet. Vitamins, micronutrients, and pharmaceuticals are necessary for the correction of deficiency disorders and diseases. Utilization of underutilised edible plant resources as vegetables as well as herbal medicinal sources by the tribal communities is a common practice. However, with the change in eating habits of the people in recent times, the popularity of the same has declined among the new generations. An attempt has been made to document traditional and underutilised vegetables having medicinal properties to make the common masses aware. The methodology included a structured questionnaire, personal interviews with the village headman and knowledgeable elderly people, group meetings and discussions with both young and elderly people, women, and also the local vegetable traders. In the present study, 76 plant species belonging to 41 families have been documented, which were used as sources of vegetables and also used in the treatment of different diseases. The wealth of plant resources recognised and documented in the study included varied types of herbs, shrubs, climbers, and some trees.
Optimal Target Blood Pressure in Elderly with Septic Shock (OPTPRESS) trial: study protocol for a Randomized Controlled Trial
Authors: Endo Akira , Yamakawa Kazuma , Tagami Takashi , Umemura Yutaka , Takahashi Kyosuke , Nagasawa Hiroki , Araki Yuichi , Kojima Mitsuaki , Sera Toshiki , Yagi Masayuki , Yamamoto Ryo , Takahashi Jiro , Nakane Masaki , Takeda Chikashi , Narita Chihiro , Kazuma Satoshi , Okura Hiroko , Takahashi Hiroyuki , Wada Takeshi , Tahara Shu , Matsuoka Ayaka , Masaki Todani , Shiraishi Atsushi , Shimoyama Keiichiro , Yokokawa Yuta , Nakamura Rintaro , Sageshima Hisako , Yanagida Yuichiro , Takahashi Kunihiko , Otomo Yasuhiro 
Published: August 2022

Abstract
Background: Hemodynamic stabilization is a core component in the resuscitation of septic shock. However, the optimal target blood pressure remains debatable. Previous randomized controlled trials suggested that uniformly adopting a target mean arterial pressure (MAP) higher than 65 mmHg for all adult septic shock patients would not be beneficial; however, it has also been proposed that higher target MAP may be beneficial for elderly patients, especially those with arteriosclerosis. Methods: A multicenter, pragmatic single-blind randomized controlled trial will be conducted to compare target MAP of 80–85 mmHg (High-target) and 65–70 mmHg (Control) in the resuscitation of septic shock patients admitted to 28 hospitals in Japan. Patients with septic shock aged ≥ 65 years are randomly assigned to the high-target or control groups. The target MAP shall be maintained for 72 h after randomization or until vasopressors are no longer needed to improve patients' condition. The primary outcome is all-cause mortality at 90 days after randomization. To minimize the adverse effects related to catecholamines, if norepinephrine dose of ≥0.1 µg/kg/min is needed to maintain the target MAP, vasopressin will be initiated. Other therapeutic approaches, including fluid administration, hydrocortisone use, and antibiotic choice, will be determined by the physician in charge based on the latest clinical guidelines.Discussion: The result of this trial will provide great insight on the resuscitation strategy for septic shock in the era of global aged society. Also, it will provide the better understanding on the importance of individualized treatment strategy in hemodynamic management in critically ill patients.Trial Registration: UMIN Clinical Trials Registry; UMIN000041775. Registered 13 September 2020.
Sleep Disorders are Associated with Testosterone Deficiency and Erectile Dysfunction- A U.S. Claims Database Analysis
Authors: Agrawal Pranjal , Singh Sajya , Able Corey , Kohn Taylor , Herati Amin 
Published: August 2022

Abstract
The relationship between male genitourinary conditions and sleep disorders has only been reported in small sample sizes. Our objective was to assess the association of erectile dysfunction (ED) and testosterone deficiency with various sleep disorders using a large claims database. The TriNetX Diamond database, a research network of over 220 million patients, was queried in June 2022. In men aged 40–70 years, insomnia (ICD-10 G47.0), sleep apnea (G47.33), and circadian rhythm sleep disorder (G47.2) were each independently assessed to determine the association with ED (N52) and testicular hypofunction (E29.1). A propensity-score-matched control cohort was generated with an absence of sleep disorders (G47 & F51), sleep deprivation (Z72.820), or morbid obesity with alveolar hypoventilation (E66.2). Propensity score matching was performed for age, hypertension (I10-16), hyperlipidemia (E78), diabetes mellitus (E08-13), ischemic heart disease (I20-25), tobacco usage (Z72.0), and obesity (E66). Sensitivity analyses were conducted via a negative polysomnography testing (CPT 1013314) cohort. Men diagnosed with a sleep disorder had significantly higher odds of testosterone deficiency and ED compared to propensity-score matched controls. Our results emphasize the negative impact of poor sleep on diseases of the male genitourinary system by identifying these relationships in the largest cohort in the U.S. reported to date.
Potential of hsa-miR200a-3p and hsa-miR502-3p as blood-based biomarker for Alzheimer's disease
Authors: biglari negin , Khalaj-Kondori Mohammad , Ghasemi Tayyebeh 
Published: August 2022

Abstract
Alzheimer's disease (AD) is one of the most important known dementia which affects thousands of people every year. Many factors are involved in this process, such as aberrant expression of miRNAs. Firstly, we analyzed two microarray datasets related to AD (GSE48552, GSE129053) to identify the differentially expressed miRNAs, and two miRNAs were selected for further validation. Dataset analysis showed that the expression of hsa-miR200a-3p and hsa-miR502-3p were up-regulated in AD. These findings were validated in plasma samples by qRT-PCR. ROC curve analysis showed that plasma levels of both miRNAs might discriminate the AD and healthy controls. In addition, in silico analysis revealed that the upregulation of these miRNAs could promote AD progression via affecting the expression of target molecules mainly ATF6 and dynactin. Totally, hsa-miR200a-3p and hsa-miR502-3p are upregulated in AD and their plasma levels can discriminate AD and healthy people, highlighting their potential as blood-based biomarker for AD.
Refractive Index Sensor Based on Surface Plasmon Resonance Excitation in a D-shaped optical fiber Coated by Tantalum
Authors: Vayghan Nader Sobhkhiz , Eftekharinia Behrooz 
Published: August 2022

Abstract
In this paper, a plasmonic refractive index sensor using a D-shaped optical fiber coated by tantalum has been proposed. The interaction between fiber fundamental mode and plasmonic mode which lead to the formation of resonance peaks depending on the analyte refractive index (RI) are investigated in detail. Using spectral sensitivity methods, the sensing performance of the proposed sensor for detecting analytes is numerically studied. The effect of various design parameters of proposed sensor are optimized numerically to achieve the maximumwavelength sensitivity. The proposed D-shaped optical fiber sensor has a RI detection range of 1.30 to 1.43 and exhibits a non-linear increasing spectral sensitivity from 1300 nm/RIU to 3900 nm/RIU. The proposed RI sensor is attractive for detecting different RI chemical and biochemical samples due to simple design, relatively large detection range, cost-effective, non-toxic nature and highly corrosion resistivity plasmonic material.
Clinico-Epidemiological Survey of Feline Parvovirus Circulating in Three Egyptian Provinces from 2020 to 2021
Authors: Abdel-Baky Mohamed , El-Khabaz Khaled , Ibrahim Maha 
Published: August 2022

Abstract
Feline parvovirus infection (FPV) is the most prevalent cause of fatal gastroenteritis in cats. Only a few reports of FPV infection in cats have been found in Egypt. Therefore, the current study was designed to detect FPV diseased cats in 3 Egyptian provinces. FPV diseased cats was detected based on clinical examination, viral antigen detection using a commercially available screening Ag rapid test kit, and molecular detection of VP-2 gene using specific primers. A total of 100 diseased cats were studied, with a variety of breeds, ages, and sexes. The cats suffered from some clinical anorexia, lethargy, fever, abdominal pain, vomiting, and/or mucoid to bloody diarrhea. These clinical signs were suggestive of FPV infection. The rapid screening test detected the infection in 35 out of 100 diseased cats, while PCR revealed the presence of the FPV infection in 43 diseased cats. Prevalence of FPV infection in Suhag, Assuit, and Cairo was 56.25%, 24.2%, and 25.7%, using rapid test and 62.5%, 27%, and 40% using PCR, respectively. Cats under the age of one year, mainly between the ages of one to six months, and unvaccinated cats had higher infection rates, particularly in the spring and winter. In addition, the relationship between clinical signs of the disease and molecular detection of FPV was extensively investigated. It could be concluded that FPV circulated among Egyptian cat populations, and the knowledge obtained in this study would help initiate preventive measures in the study areas.
Primary cilia control cellular patterning and dimension of Meibomian glands during morphogenesis but not lipid composition of the meibum
Authors: Portal Céline , Lin Yvonne , Rastogi Varuni , Peterson Cornelia , Yiu Samuel , Foster James , Wilkerson Amber , Butovich Igor , Iomini Carlo 
Published: August 2022

Abstract
Meibomian glands (MGs) are modified sebaceous glands which produce the tear film's lipid component. Despite their critical function in maintaining clear vision, the mechanisms underlying MG morphogenesis during development and disease pathogenesis remain obscure. We investigated the role of primary cilia during MG development. Most cells were ciliated during early MG development, followed by cilia disassembly during differentiation. In mature glands, ciliated cells were primarily restricted to the basal layer of the proximal gland central duct. Cilia ablation in keratine14-expressing tissue disrupted the accumulation of proliferative cells at the distal tip of developing MGs but did not affect overall rate of proliferation or apoptosis. Moreover, impaired cellular patterning and elongation processes resulted in hypertrophy of mature MGs with increased meibum volume without altering lipid composition. We demonstrate a novel role of cilia in tissue patterning which may reveal new therapeutic strategies to treat ocular surface disease caused by MG dysfunction.
Oil Palm Yield Prediction Across Blocks Using Multi-Source Data and Machine Learning
Authors: Ang Yuhao , Shafri Helmi Zulhaidi Mohd , Lee Yang Ping , Bakar Shahrul Azman , Abidin Haryati , Junaidi Mohd Umar Ubaydah Mohd , Hashim Shaiful Jahari , Che’Ya Nik Norasma , Hassan Mohd Roshdi , Lim Hwee San , Abdullah Rosni , Yusup Yusri , Muhammad Syahidah Akmal , Teh Sin Yin , Samad Mohd Na’aim 
Published: August 2022

Abstract
Predicting yields on a bigger scale in a timely and accurate manner is essential for preventing climate risk and ensuring food security, particularly in the light of climate change and the escalation of extreme climatic events. Furthermore, crop yield estimates are affected by various factors including weather, nutrients and management practices. In this study, integrating multi-source data (i.e. satellite-derived vegetation indices (VIs), satellite-derived climatic variables (i.e. land surface temperature (LST) and rainfall precipitation, weather station and field-surveys), we built one multiple linear regression (MLR), three machine learnings (XGBoost, support vector regression, and random forest) and one deep learning (deep neural network) model to predict oil palm yield at block-level within the oil palm plantation. Moreover, time-series moving average and backward elimination feature selection techniques were implemented at the pre-processing stage. The yield prediction models were developed and tested using MLR, XGBoost, support vector regression (SVR), random forest (RF) and deep neural network (DNN) algorithms. Their model performances were then compared using evaluation metrics and generated the final spatial prediction map based on the best performance. DNN achieved the best model performances for both selected (R2=0.91; RMSE= 2.92 tonnes per ha; MAE= 2.56 tonnes per ha and MAPE= 0.09) and full predictors (R2=0.76; RMSE of 3.03 tonnes per ha; MAE of 2.88 tonnes per ha; MAPE of 0.10 tonnes per ha). In addition, advanced ensemble ML techniques such as XGBoost may be utilised as a supplementary for oil palm yield prediction at the block level. Among them, MLR recorded the lowest performance. By using backward elimination to identify the most significant predictors, the performance of all models was improved by 5% - 26% for R2, and that decreased by 3% - 31% for RMSE, 7% - 34% for MAE, and 1% - 15% for MAPE, respectively. DNN generates the most accurate statistical metrics, with an increase of around 15% for R2, 11% for RMSE, 32% for MAE and 1% for MAPE. Our study successfully developed efficient, effective and accurate yield prediction models for timely predicting oil palm yield over a large area by integrating data from multiple sources. These can be potentially handled by plantation management to estimate oil palm yields to speed up the decision-making process for sustainable production.
Deployment of Renewable Energy Sources: Empirical Evidence in Identifying Clusters with Dynamic Time Warping
Authors: Maharaj Elizabeth Ann , De Giovanni Livia , D'Urso Pierpaolo , Bhattacharya Mita 
Published: August 2022

Abstract
Deployment of renewable energy sources has caused a seismic shift in the world energy arena. Individual and coordinated efforts across countries and regions are shaping the world for the future, including business models which are supported globally to achieve net zero goals by 2050. In this paper, our aim is to identify clusters of countries at different levels of deployment of renewable energy sources. We propose a time series clustering method capturing the time-varying features of the renewable energy time series of 130 countries to enable the assessment of how similar or how different the usage is in relation to the Organisation for Economic Co-operation and Development (OECD) status of countries, their regional location and their income levels. We use Dynamic Time Warping (DTW) which is a method that calculates an optimal match between two given time series with certain restrictions. Using DTW, we the adopt the Partitioning Around Medoids (PAM) technique in a fuzzy framework to obtain cluster solutions. Our analysis shows that a 4-cluster solution best captures country separation based on OECD status, regional location and income grouping. Since renewable energy clusters share common advantages and difficulties in terms of transferring the key characteristics in deploying renewable energy resources across countries and regions, grouping together of countries could capture similarities or differences that has the potential to lead to common decisions that could benefit the countries in the same group.
Molecular characteristics of arteries in patients with intracranial aneurysm: integration of WES and RNA-seq
Authors: Chen Bo , Zeng Ming , Yan Langchao , Wang Ying , Song Laixin , Tao Wengui , Huang Zheng , Chen Fenghua 
Published: August 2022

Abstract
Genetic and vascular morphology research suggested intracranial aneurysm (IA) may not be a local artery disease. IA initiation may be correlated with the histological and molecular changes of arteries. We used whole-exome sequencing (WES) of blood and RNA sequencing (RNA-seq) of superficial temporal artery (STA) to explore the artery molecular characteristics of IA under the genetic background, and try to find the potential mechanism of the IA initiation. Fifty IA patients’ and 40 controls’ blood samples were enrolled in WES; 10 IA patients’ and 5 controls’ STA were included in RNA-seq. Bioinformatic analysis was performed. RT-qPCR was used for validation. We analyze the cell types of STA by the xCell algorithm, and conducted a correlation analysis between the endothelium and mutation genes. We identified 2118 genes via RNA-seq, and via WES 43 genes harboring 54 potential deleterious variants. Four genes (ALDH1L2, KCNJ12, SPNS2, TUBB8) had both variants and differential expressions. Xcell algorithms showed that the expression of mutation genes KCNJ12 and SPSN2 were strongly associated with decreasing endothelial cells on STA and higher IA risks. KCN12 and SPSN2 expressions have been validated by RT-qPCR. In total, we have described the artery molecular characteristics of IAs by RNA-seq and WES. A total of two gene mutations (KCNJ12 and SPSN2) were found potentially to facilitate IA initiation by decreasing EC expression in brain arteries.
Strong convergent inertial two-subgradient extragradient method for finding minimum-norm solutions of variational inequality problems
Authors: Alakoya Timilehin Opeyemi , Mewomo Oluwatosin Temitope 
Published: August 2022

Abstract
In 2012, Censor et al. [11] proposed the two-subgradient extragradient method (TSEGM). This method does not require computing projection onto the feasible (closed and convex) set, but rather the two projections are made onto some half-space. However, the convergence of the TSEGM was puzzling and hence posted as open question. Very recently, some authors were able to provide a partial answer to the open question by establishing weak convergence result for the TSEGM though under some stringent conditions. In this paper, we propose and study an inertial two-subgradient extragradient method (ITSEGM) for solving monotone variational inequality problems (VIPs) with non-Lipschitz operators. Under more relaxed conditions than the existing results in the literature, we prove that proposed method converges strongly to a minimum-norm solution of non-Lipschitz monotone VIPs in Hilbert spaces. Unlike several of the existing methods in the literature for solving VIPs with non-Lipschitz operators, our method does not require any linesearch technique, which could be time-consuming to implement. Rather, we employ a simple but very efficient self-adaptive step size method that generates a non-monotonic sequence of step sizes. Moreover, we present several numerical experiments to demonstrate the efficiency of our proposed method in comparison with related results in the literature. Finally, we apply our result to image restoration problem. Our result in this paper improves and generalizes the existing results in the literature in this direction.
Mid-level data fusion combined with the fingerprint region in near-infrared and Fourier transform mid-infrared spectroscopy for classification DON levels defect of Fusarium head blight wheat
Authors: Liang Kun , Song Jinpeng , Tang Shiyu , Wang Dezhou , Jiang Pengfei , Cao Bin 
Published: August 2022

Abstract
In this study, a method of mid-level data fusion with the fingerprint region was proposed, which was combined with the characteristic wavelengths that contain fingerprint information in NIR and FT-MIR spectra to detect the DON level in FHB wheat during wheat processing. NIR and FT-MIR raw spectroscopy data on normal wheat and FHB wheat were obtained in the experiment. MSC was used for pretreatment, and characteristic wavelengths were extracted by CARS, MGS and XLW. The variables that can effectively reflect fingerprint information were retained to build the mid-level data fusion matrix. LS-SVM and PLS-DA were applied to investigate the performance of the single spectroscopic model, mid-level data fusion model and mid-level data fusion with fingerprint information model, respectively. Experimental results show that mid-level data fusion with a fingerprint information strategy based on fused NIR and FT-MIR spectra represents an effective method for the classification of DON levels in FHB wheat samples.