bluuebunny/crossref_metadata_2025_split huggingface dataset:
WITHDRAWN: RNA-Seq based exploration of differentially expressed genes (DEGs) in cotton(Gossypium hirsutum. L) upon infection with Aspergillus tubingensis
Authors: Khizar Maria , Shi Jianxin , Haroon Urooj , Ali Musrat , Liaquat Fiza , Akbar Mahnoor , Saleem Hira , Kamal Asif , Minhas Kinza , Chaudhary Hassan Javed , Munis Muhammad Farooq Hussain 
Published: August 2021

Abstract
Differentially expressed genes help in exploring plant defense mechanism under variable stress conditions. In current investigation, RNA sequencing was executed to explore the differential gene expression in resistant and susceptible varieties of Cotton (Gossypium hirsutum), upon infection with Aspergillus tubingensis. Comparative RNA-Seq of control and infected plants was performed using Illumina HiSeq 2,500. Overall 79.84 G clean data was generated and 6,558 DEGs were identified in both varieties, in response to pathogen inoculation. Differentially expressed genes were found to be involved in defense, antifungal response, signaling pathways, oxidative burst and transcription. Genes involved in defense responses, MAPK signaling, cell wall fortification and signal transduction were highly induced in resistant variety. Real time PCR also revealed the up regulation of MAPKKK YODA like, L-ascorbate oxidase, late embryogenesis abundant protein (At1g64065) and flavonoid 3',5'-hydroxylase-like, in resistant variety. Elevated accumulation of such DEGs in resistant variety could function as the source for identifying biomarkers for breeding and these can be used as potential candidate genes for transgenic manipulation. Their study also helped in understanding complex plant-fungal interaction and advanced the understanding of plant-microbe interaction. Inclusively, our findings provide an indispensable foundation for advanced understanding of the plant resistance mechanisms of cotton.
Recombinant Follicular Stimulating Hormone Plus Recombinant Luteinizing Hormone Versus Human Menopausal Gonadotropins- Does the Source of LH Bioactivity Affect Ovarian Stimulation Outcome?
Authors: Kirshenbaum Michal , Gil Or , Haas Jigal , Nahum Ravit , Zilberberg Eran , Lebovitz Oshrit , Orvieto Raoul 
Published: August 2021

Abstract
Background: Luteinizing hormone (LH) and human chorionic gonadotropin (hCG) activate distinct intracellular signaling cascades. However, due to their similar structure and common receptor, they are used interchangeably during ovarian stimulation (OS). This study aims to assess if the source of LH used during OS affects IVF outcome. Materials and methods: This was a cross sectional study of patients who underwent two consecutive IVF cycles, one included recombinant follicular stimulating hormone (FSH) plus recombinant LH [rFSH+rLH, (Pergoveris)] and the other included urinary hCG [highly purified hMG (HP-hMG), (Menopur)]. The OS protocol, except of the LH preparation, was identical in the two IVF cycles. Results: The rate of mature oocytes was not different between the treatment cycles (0.9 in the rFSH+rLH vs 0.8 in the HP-hMG, p=0.07). Nonetheless, the mean number of mature oocytes retrieved in the rFSH+rLH treatment cycles was higher compared to the HP-hMG treatment cycles (10 ± 5.8 vs 8.3 ±4.6, respectively, P=0.01). Likewise, the mean number of fertilized oocytes was higher in the rFSH+rLH cycles compared with the HP-hMG cycles (8.5 ± 5.9 vs 6.4 ± 3.6, respectively, p=0.05). There was no difference between the treatment cycles regarding the number of top-quality embryos, the ratio of top-quality embryos per number of oocytes retrieved or fertilized oocytes or the pregnancy rate. Conclusion: The differences in treatment outcome, derived by different LH preparations reflect the distinct physiological role of these molecules. Our findings may assist in tailoring a specific GT regimen when assembling an OS protocol.
Assessment of Parasympathetic Cardiovascular Activity in Primary Open Angle Glaucoma
Authors: Awe Oluwaseun Olaniyi , Ogunlade Oluwadare , Adegbehingbe Bernice Oluwakemi 
Published: August 2021

Abstract
PurposeTo describe the pattern of quantitative parasympathetic cardiovascular autonomic function among patients with normal-tension glaucoma (NTG) and high-tension primary open-angle glaucoma (HTG) patients. MethodologyThis was cross-sectional study of ninety-two subjects enrolled into three groups: HTG (31 patients), NTG (31 patients) and Control (30 patients). All the participants had anthropometric assessment, ophthalmic examination, baseline cardiovascular examination and the three parasympathetic components of Ewing’s battery of autonomic cardiovascular function tests namely heart rate (HR) response to deep breathing, HR response to Valsalva manoeuvre and HR response to standing.ResultThe baseline PR intervals were significantly prolonged in HTG (0.18 ± 0.03 sec) and NTG (0.18 ± 0.04 sec) groups compared with control (0.15 ± 0.03sec) (p = 0.008). The HTG group had a significantly longer mean RR interval (1.09 ± 0.17 sec) than the NTG group (1.03 ± 0.20 sec) and control (0.97 ± 0.17 sec) during the expiratory phase of the HR response to deep breathing test (p = 0.037). The HTG group also had significantly longer mean RR intervals around the 15th beat (p = 0.033) and 30th beats (p = 0.202) post-standing during the HR response to standing test. The HR response to Valsalva manoeuvre test showed a significantly higher mean Valsalva ratio in the NTG group (1.65 ± 0.48) compared to the HTG group (1.45 ± 0.31) and control (1.43 ± 0.25) (p = 0.034).ConclusionThis study demonstrated that normal-tension and high-tension primary open-angle glaucoma have higher parasympathetic cardiovascular activity than normal individuals.
An Automatic Method for Rice Seed Vigor Classification Via Radicle Emergence Testing Using Image-Processing, Curve-Fitting and Clustering Methods
Authors: Onwimol Damrongvudhi , Sermwuthisarn Parichat , Phimcharoen Wanwisa , Chaisan Tanapon 
Published: August 2021

Abstract
Background: Rice seed vigor classification is important for seed storage management by seed producers and by farmers while planning their cultivation activities. Field emergence is a direct method of seed vigor testing but is laborious, time-consuming and subjective. The accelerated aging (AA) test is often used as an indirect method for rice seed vigor classification in the laboratory. However, the results from this method are often imprecise. This paper presents the SVRice package, a simple, cost-efficient and flexible procedure that utilizes computer image analysis for high-throughput, automatic rice seed vigor classification. SVRice consists of 4 steps: dynamic imaging, image processing, curve fitting and clustering. Seed vigor was classified based on radicle emergence indices, such as maximum radicle emergence (MaxRE), mean radicle emergence time (MRET), radicle emergence speed (t50), uniformity of radicle emergence (U7525), and area under the curve of the radicle emergence fitted curve (AUC).Results: Parameters used to classify rice seed vigor, such as MRET, U7525 and t50, were strongly negatively correlated with the saturated salt accelerated aging (SSAA) test. A germination time of 90 hours at 25°C was sufficient for effective classification based on SVRice, whereas the SSAA test took approximately 400 hours to complete. The SVRice software algorithm was created to be especially suitable for assessment after 6 months under controlled atmosphere storage (at 15°C and 37% RH in a hermetic bag). The study showed that SVRice could unambiguously classify 40 indica rice samples with different varieties, production years, production sites, storage times and storage conditions compared with the SSAA test.Conclusions: This paper confirmed the accuracy, reproducibility and flexibility of the SVRice package for automatic seed vigor classification of Oryza sativa seeds; moreover, it is also likely applicable to other species as a viable alternative to current methods that require more time and are less precise.
High Post-infection Protection after COVID-19 Among Healthcare Workers: A Population-Level Observational Study Regarding SARS-CoV-2 Reinfection, Reactivation, and Re-positivity and its Severity
Authors: Sabetian Golnar , Shahriarirad Sepehr , Moghadami Mohsen , Asmarian Naeimehossadat , Shahriarirad Reza , Askarian Mehrdad , Haghighi Leila Hashemizadeh Fard , Javadi Parisa 
Published: August 2021

Abstract
Introduction: Even though over a year has passed since the coronavirus 2019 (COVID-19) outbreak, our information regarding certain aspects of the disease, such as post-infection immunity is still very limited. This study aimed to evaluate post-infection protection and COVID-19 features among healthcare workers (HCWs), during three subsequent surges.Method: The study population consisted of all HCWs in either public or private hospitals in Fars province, Southern Iran from 20 April 2020 up to 20th February 2021. We calculated the rate of infection as the number of individuals with positive PCR tests divided by the cumulative number of person-days at risk. Poisson regression was utilized to calculate the adjusted rate ratio and estimated protection. Results: During the study period, a total of 30,546 PCR tests were performed among HCWs, of which 13,749 HCWs were positive. Among a total of 141 diagnosed cases who experienced a second episode of COVID-19, 44 (31.2%) cases of reactivation and relapse, and 97 (68.8% of infected and 1.81% of total HCWs) cases of reinfection was observed. The daily rate of infection was 4.72 for previously infected HCWs, while 2.20 for HCWs without previous infection. The estimated protection against repeat infection after a previous SARS-CoV-2 infection was 94.8% (95% CI: 93.6-95.7).Conclusion: Re-positivity, relapse, and reinfection of SARS-CoV-2 are quite rare in the population of HCWs. Also, after a first episode of infection, estimated protection of 94.8% was achieved against repeat infections.
Hypoxia Inducible Factor-1α Overexpression Enhances the Efficacy of Mesenchymal Stem Cells Derived Extracellular Vesicles for Cardiac Repair After Myocardial Infarction
Authors: Wang Qingjie , Zhang Le , Sun Zhiqin , Chi Boyu , Zou Ailin , Mao Lipeng , Xiong Xu , Jiang JianGuang , Sun Ling , Zhu Wenwu , Ji Yuan 
Published: August 2021

Abstract
Aims Naturally secreted extracellular vesicles (EVs) play important roles in stem-mediated cardioprotection. This study aimed to investigate the cardioprotective function and underlying mechanisms of EVs derived from HIF-1a engineered mesenchymal stem cells (MSCs) in a rat model of AMI.Methods and Results EVs isolated from HIF-1a engineered MSCs (HIF-1a-EVs) and control MSCs (MSCs-EVs) were prepared. In in vitro experiments, the EVs were incubated with cardiomyocytes and endothelial cells exposed to hypoxia and serum deprivation (H/SD); in in vivo experiments, the EVs were injected in the acutely infarcted hearts of Sprague-Dawley rats. Compared with MSCs-EVs, HIF-1a-EVs significantly inhibited the apoptosis of cardiomyocytes and enhanced angiogenesis of endothelial cells; meanwhile, HIF-1a-EVs also significantly shrunk fibrotic area and strengthened cardiac function in infarcted rats. After treatment with EVs/RGD-biotin hydrogels, we observed longer retention, higher stability in HIF-1a-EVs, and stronger cardiac function in the rats. Quantitative real-time PCR (qRT-PCR) displayed that miRNA-221-3p was highly expressed in HIF-1a-EVs. After miR-221-3p was inhibited in HIF-1a-EVs, the biological effects of HIF-1a EVs on apoptosis and angiogenesis were attenuated.Conclusion EVs released by MSCs with HIF-1a overexpression can promote the angiogenesis of endothelial cells and the apoptosis of cardiomyocytes via upregulating the expression of miR-221-3p. RGD hydrogels can enhance the therapeutic efficacy of HIF-1a engineered MSC-derived EVs.
Dynamical analysis of the infection status in diverse communities due to COVID-19 using a modified SIR model
Authors: Cooper Ian , Mondal Argha , Antonopoulos Chris , Mishra Arindam 
Published: August 2021

Abstract
In this article, we model and study the spread of COVID-19 in Germany, Japan, India and highly impacted states in India, i.e., Delhi, Maharashtra, West Bengal, Kerala and Karnataka. We consider recorded data published in Worldometers and COVID-19 India websites from April 2020 to July 2021, including periods of interest where these countries and states were hit severely by the pandemic. Our methodology is based on the classic susceptible-infected-removed (SIR) model and can track the evolution of infections in communities, i.e., in countries, states or groups of individuals, where we (a) allow for the susceptible and infected populations to be reset at times where surges, outbreaks or secondary waves appear in the recorded data sets, (b) consider the parameters in the SIR model that represent the probability of the infection and recovery rates to be functions of time and (c) estimate the number of deaths by combining the model solutions with the recorded data sets to approximate them between consecutive surges, outbreaks or secondary waves, providing a more accurate estimate. We report on the status of the current infections in these countries and states, and the infections and deaths in India and Japan in the end of August 2021, assuming a major outbreak occurs in early August 2021 in India and in mid-July 2021 in Japan. Our model can adapt to the recorded data and can be used to explain them and importantly, to forecast the number of infected, recovered, removed and dead individuals, as well as to estimate the probability of the infection and recovery rates as functions of time, assuming an outbreak occurs at a given time. The latter information can be used to forecast the future basic reproduction number and together with the forecast on the number of infected and dead individuals, our approach can further be used to suggest the implementation of intervention strategies and mitigation policies to keep at bay the number of infected and dead individuals. This, in conjunction with the implementation of vaccination programs worldwide, can help reduce significantly the impact of the spread around the world and improve the wellbeing of people.
Using Radiomics-based Modeling to Predict Individual Progression From Mild Cognitive Impairment to Alzheimer’s Disease
Authors: Jiang Jiehui , Sun Xiaoming , Alberts Ian , Wang Min , Rominger Axel , Zuo Chuantao , Han Ying , Shi Kuangyu 
Published: August 2021

Abstract
Background: Predicting the risk of disease progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD) has important clinical significance. This study aims at providing a personalized MCI-to-AD conversion prediction via radiomics-based predictive modeling (RPM) with multicentre 18F-Fluorodeoxyglucose positron emission tomography (FDG PET) data. Method: Three cohorts of 18F-FDG PET data and neuropsychological assessments were gathered from patients examined at Huashan Hospital (n=22), Xuanwu Hospital (n=80), and from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (n=355). Of these, amyloid images were selected for the ADNI and Xuanwu cohorts. First, 430 radiomic features were extracted from the 80 regions of interest (ROIs) for all PET images. These features were then concatenated for feature selection and an RPM model was constructed on the ADNI dataset. In addition, we used clinical scale data to establish a clinical Cox model, and a combined model for comparison. Afterwards, the images from Huashan Hospital were used to validate the stability and reliability of RPM, and the images from Xuanwu Hospital were used to explore the differences of biomarkers at different cognitive stages. Finally, correlation analysis was conducted between the radiomic biomarkers, neuropsychological assessments, and amyloid burden. Results: Experimental results show that the predictive performance of the PET-modal cox model was better than clinical cox model. In the two test data sets, the C index of PET model is 0.75 and 0.73, respectively; The C index of clinical model is 0.68. Moreover, most crucial image biomarkers had significant differences at different cognitive stages, and were significantly correlated with cognitive ability and the amyloid global level standardized uptake value ratio.Conclusion: The preliminary results demonstrated that the developed RPM approach has the potential to monitor the progress in high-risk populations with AD.
Predicting Postoperative Hypertension Among Patients With Ventricular Septal Defect in Infants
Authors: Kawamura Junpei , Ueno Kentaro , Shimozono Tsubasa , Takahashi Yoshihiro , Nakae Koji , Okamoto Yasuhiro 
Published: August 2021

Abstract
Purpose: Patients with strong pulmonary vascular occlusive lesions are at risk of developing postoperative pulmonary hypertension (PH). We aimed to evaluate preoperative right ventricular (RV) function in patients with ventricular septal defect (VSD) who required cardiac surgery during infancy and consequently developed postoperative PH and to determine whether we could preliminarily evaluate postoperative PH in these patients.Methods: We retrospectively analyzed 55 infants with VSD who underwent cardiac surgery between March 2014 and April 2020. We evaluated the measurements of preoperative atrial/ventricular general function and 2D atrial/ventricular strain between these two groups: a group with postoperative PH (post-PH) and a group without postoperative PH (post-NPH). Results: Post-PH patients had a significantly lower tricuspid annular plane systolic excursion (TAPSE) (11.2 mm) and TAPSERA (the proportion of TAPSE due to RA contraction alone) (6.6 mm) than the post-NPH patients (14.1 mm, 8.5 mm). Furthermore, the post-PH group had a significantly lower peak right atrial (RA) longitudinal strain (PRALS) (31.0%) than the post-NPH group (43.0%). Multivariate logistic regression analysis identified that PRALS and TAPSERA were independent echocardiographic parameters for the presence of post-PH. The sensitivity and specificity of predicting post-PH for ≤38% of the PRALS were 83.0% and 100.0%, respectively, with an area under the curve of 0.94 (p < 0.01).Conclusion: Preoperative RA function and RV diastolic function decreased in the post-PH group. The RA strain and TAPSERA could be useful factors for predicting postoperative PH.
Network controllability solutions for computational drug repurposing using genetic algorithms
Authors: Popescu Victor-Bogdan , Kanhaiya Krishna , Nastac Iulian , Czeizler Eugen , Petre Ion 
Published: August 2021

Abstract
Control theory has seen recently impactful applications in network science, especially in connections with applications in network medicine. A key topic of research is that of finding minimal external interventions that offer control over the dynamics of a given network, a problem known as network controllability. We propose in this article a new solution for this problem based on genetic algorithms. We tailor our solution for applications in computational drug repurposing, seeking to maximize its use of FDA-approved drug targets in a given disease-specific protein-protein interaction network. We show how our algorithm identifies a number of potentially efficient drugs for breast, ovarian, and pancreatic cancer. We demonstrate our algorithm on several benchmark networks from cancer medicine, social networks, electronic circuits, and several random networks with their edges distributed according to the Erdös-Rényi, the scale-free, and the small world properties. Overall, we show that our new algorithm is more efficient in identifying relevant drug targets in a disease network, advancing the computational solutions needed for new therapeutic and drug repurposing approaches.
Multitaper Time-frequency Peak-based Longitudinal Sleep Analysis in 5XFAD Mouse Model
Authors: Kim Chaeyeon , Drew Victor James , Park Mincheol , Kim Tae 
Published: August 2021

Abstract
Background: Sleep disturbance is common in Alzheimer’s disease (AD), but the characteristics of sleep disturbance remain unclear. Multitaper spectral analysis (MSA) is a novel method for investigating sleep. However, MSA-based sleep research in AD is lacking; hence we applied MSA to examine the sleep of AD.Methods: Electroencephalograms were recorded on 3-, 6-, and 10-month-old 5XFAD mice, and the time-frequency (TF) peaks were detected using MSA. We comparatively analyzed the TF peaks between genotypes and age groups.Results: The sigma TF peaks (~80%) were sleep spindles. MSA-based TF plot showed distinct patterns, agreeing with manual scoring. With AD progression, the characteristics of TF peaks coherently changed; shorter sigma TF peaks outnumbered longer ones; dark-period fast spindle TF peak density decreased significantly at both 6 and 10 months.Conclusions: Multitaper TF peaks might provide biomarkers for the progression of AD. Further investigations are warranted.
Relations Between Performance Enhancement Drugs and Health-defining Parameters During the Competition Preparation Period of World-class Bodybuilders
Authors: Wiacek Magdalena , Trabka Bartosz , Markuszewski Leszek , Tomasiuk Ruszard , Zubrzycki Igor Z. 
Published: August 2021

Abstract
Fluctuations in biochemical parameters defining cardiovascular, liver and muscoskeletal health were analyzed to evaluate the health status of world class bodybuilders using performance enhancement drugs such as anabolic-androgenic steroids (AAS) [testosterone propionate, drostanolone propionate (Masteron), trenbolone acetate (Finajet), oxandrolone (Anavar), stanozolol (Winstrol) and boldenone undecylenate], human growth hormone (HGH) and “fat-burning drugs” [triiodothyronine (t3), clenbuterol, mesterolone (Proviron), tamoxifen citrate (Nolvadex) and 2,4-Dinitrophenol (2,4-DNP)], and a 6-month preparation period. Changes in serum levels of total cholesterol (TC), triglyceride (TG), high-density lipoprotein (HDL-C), low-density lipoprotein (LDL-C), aspartate aminotransferase (AST), alanine transaminase (ALT), and bilirubin, as well as body mass (BM) and total body fat percentage (BF%), were measured as a function of the competition preparation period. The study shows a continuous increase in BM, accompanied by a decrease in BF% to the physiologically optimal level. TC levels varied significantly within the desired concentration range (TC < 5.18 mmol / L), and TG fluctuated between the ranges of concentrations borderline high (1.69 mmol / L ≤ TG < 2.26 mmol / L) and high (2.26 mmol / L ≤ TG < 5.65 mmol / L) concentration ranges. HDL-C levels remained within the low range (TG < 1.03 mmol / L), whereas LDL-C fluctuated across all physiologically important ranges, that is, near-optimal / above optimal (2.59 mmol / L ≤ LDL-C < 3.34 mmol / L), borderline high (3.35 mmol / L ≤ LDL-C < 4.11 mmol / L), and high (4.14 mmol / L ≤ LDL-C < 4.91 mmol / L). AST and ALT concentrations remained within the high-concentration region, i.e., > 0.58 mkat / L and > 0.91 mkat / L. Bilirubin concentration fluctuated within the desirable limits (3.42 mmol / L ≤ Bilirubin < 2.53 mmol / L), and urea concentration were between desirable (3.2 mmol / L ≤ Urea < 7.9 mmol / L) and high values (Urea ≥ 7.9 mmol / L). Although most of the changes are within physiologically acceptable ranges, there are evident disturbances in LDL-C and Urea levels induced by performance-enhancing drugs. To our knowledge, this study is among the few, if not the only, that discloses the physiological changes associated with doping-assisted preparations for an international bodybuilding contest.