bluuebunny/crossref_metadata_2025_split huggingface dataset:
A case report of a boy suffering from Type 1 Diabetes Mellitus and Familial Mediterranean Fever
Authors: gicchino maria francesca , Iafusco Dario , Zanfardino Angela , Giudice Emanuele Miraglia del , Olivieri Alma Nunzia 
Published: December 2020

Abstract
Background: Type 1 diabetes mellitus could be associated with other autoimmune diseases, such as autoimmune thyroid disease, celiac disease, but the association with Familial Mediterranean Fever is rare, we describe a case of a boy with type 1 Diabetes Mellitus associated with Familial Mediterranean Fever (FMF)Case presentation: A 13 year old boy already suffering from Diabetes Mellitus type 1 since the age of 4 years, came to our attention because of periodic fever associated with abdominal pain, chest pain and arthralgia. The fever appeared every 15-30 days with peaks that reached 40°C and lasted 24-48 hours. Laboratory investigation, were normal between febrile episodes, but during the attacks revealed an increase in inflammatory markers. Suspecting Familial Mediterranean Fever molecular analysis of MEFV gene, was performed. The genetic analysis showed homozygous E148Q mutation. So Familial Mediterranean Fever was diagnosed and colchicine treatment was started with good response.Conclusion. Familial Mediterranean Fever could be associated with other autoimmune diseases such as Ankylosing Spondylitis, Rheumatoid Arthritis, Polyarteritis Nodosa, Behcet disease, Systemic Lupus, Henoch-Schönlein Purpura, and Hashimoto’s Thyroiditis. Association of type 1 Diabetes Mellitus and Familial Mediterranean Fever has been newly reported in the medical literature, this is the third association of these two diseases described in the medical literature so far.
Use of Machine Learning Techniques to Identify HIV Predictors for Screening
Authors: McSharry Patrick E , Mutai Charles , Ngaruye Innocent , Musabanganji Edouard 
Published: December 2020

Abstract
Aim: HIV prevention measures at sub-Saharan Africa are still short of attaining the UNAIDS 90-90-90 fast track targets set in 2014. Identifying predictors for HIV status may facilitate targeted screening interventions that improve health care. We aimed at identifying HIV predictors as well as predicting persons at high risk of the infection.Method: We applied six machine learning approaches for building models using population-based HIV Impact Assessment (PHIA) data for 41,939 male and 45,105 female respondents with 24 and 29 variables respectively from four countries in sub-Saharan countries. We trained and validated the six algorithms on 80% of data and tested on the remaining 20% where we rotated around the left-out country. An algorithm with the best mean f1 score was retained and trained on the most predictive variables. We used the model to identify people living with HIV and individuals with a higher likelihood of contracting the disease.Results: Application of XGBoost algorithm appeared to significantly improve identification of HIV positivity over the other six algorithms by f1 scoring mean of 78.9% and 92.8% for males and females respectively. Amongst the eight most predictor features in both sexes were: age, relationship with family head, the highest level of education, highest grade at that school level, work for payment, avoiding pregnancy, age at the first experience of sex, and wealth quintile. Model performance using these variables increased significantly compared to having all the variables included. We identified five males and seven females individuals that would require testing to find one HIV positive individual. We also predicted that 4·14% of males and 10.81% of females are at high risk of the infection.Conclusion: Our findings provide a potential use of XGBoost algorithm with socio-behavioural-driven data at substantially identifying HIV predictors and predicting individuals at high risk of infection for targeted screening.
WITHDRAWN: Impaired odor identification ability and olfactory hedonic capacity in children with elevated autistic traits
Authors: Huang Gao-jie , Qiu Yi-qi , Tan Shao-zhen , Ma Qian-wen , Zou Laiquan 
Published: December 2020

Abstract
Background: Atypical olfactory function in autism spectrum disorder has been documented in numerous studies, but little is known about its occurrence in individuals with autistic traits. The aim of the current study was to investigate odor identification ability and olfactory hedonic capacity in children with autistic traits. Methods: The study included 91 children in a high autistic trait group, and 128 children in a low autistic trait group, as determined based on Short Autism Spectrum Quotient scores. The Universal Sniff (U-Sniff) test was used to measure odor identification ability and olfactory hedonic capacity. Olfactory hedonic capacity was also measured using the child’s version of the Chemosensory Pleasure Scale (CPS-C). Results: Children in the high autistic trait group exhibited significantly impaired odor identification and olfactory hedonic capacity measured by CPS-C than those in the low autistic trait group, but there was no significant difference in olfactory hedonic capacity measured by U-Sniff between the two groups. Impaired odor identification was significantly correlated with olfactory hedonic capacity measured by CPS-C. Limitations: Only a self-reporting questionnaire was used to screen children for autistic trait. The combination of a self-reporting scale and diagnosis by a clinical expert would result in more accurate screening of individuals for autistic trait.Conclusions: Children with high autistic trait exhibited poorer odor identification ability and olfactory trait hedonic capacity than children without high autistic trait. These results pertaining to odor identification and olfactory hedonic capacity may be the endophenotypic markers for autism spectrum disorder.
Did the animal move? A cross-wavelet approach to geolocation data reveals year-round whereabouts of a resident seabird.
Authors: Roy Amédée , Delord Karine , Nunes Guilherme Tavares , Barbraud Christophe , Bugoni Leandro , Bertrand Sophie 
Published: December 2020

Abstract
Background Considerable progress in our understanding of long-distance migration has been achieved thanks to the use of small lightweight geolocator devices. Such global location sensors (GLS) are particularly suitable for studying non-breeding movement and behaviour due to their small size and low energy consumption allowing multiyear deployment. Errors of geolocation are however important, difficult to estimate, have a complex structure leading to poor precision and accuracy. Therefore, understanding movement ecology of short-distance migrants or resident birds during extensive time periods remains challenging. We aimed at elucidating the sex-specific marine space uses of a resident tropical seabird, the masked booby over the full annual life cycle, including the breeding and non-breeding periods. Methods A total of 34 GLS were deployed on male and female masked boobies at the Fernando de Noronha archipelago (Brazil), and 31 of them were recovered and provided year-round data. Error range of geographical positions and habitat use of masked boobies were estimated from light-derived positions and temperature data. Synchronicity between movement and saltwater immersion data was investigated through a wavelet analysis. Results Masked boobies showed a resident behaviour over their entire annual cycle. We inferred from the wavelet analysis that birds traveled way and back from the colony on consecutive trips of short length (approx 2-4 days) and short range (approx 100-300 km) at the east of the colony. Trip duration and range depended on the sex of the individual and on the time of the year. Females had farther ranges than males during the pre-breeding period. Trip duration increased gradually from the end of the breeding period to the post-breeding period, probably due to the release of the central-place breeding constraints. Conclusions Despite inherent limits of light-based geolocation, synchronicity analysis of geolocation data revealed year round whereabouts of a resident tropical seabird and sex-specific movement behaviour. Such an approach based on the estimation of synchronicity between light-based coordinates data and any other external data (behavioural or environmental) could be used more broadly to investigate resident or short-migrants animal movement based on GLS data.
Chitosan Hydrogel-loaded MSC-derived Extracellular Vesicles Promote Skin Rejuvenation by Ameliorating the Senescence of Dermal Fibroblasts
Authors: Zhao Xiangnan , Liu Yue , Jia Pingping , Cheng Hui , Wang Chen , Chen Shang , Huang Haoyan , Han Zhibo , Han Zhong-Chao , Chen Xiaoniao , Li Zongjin 
Published: December 2020

Abstract
Background: The senescence of dermal fibroblasts (DFLs) leads to an imbalance in the synthesis and degradation of extracellular matrix (ECM) proteins, presenting so-called senescence-associated secretory phenotype (SASP), which ultimately leads to skin aging. Recently increasing evidence has supported the idea that mesenchymal stem cells (MSCs) derived extracellular vesicles (MSC-EVs) opened a new avenue for treating skin aging.Methods: In this study, we utilized chitosan (CS) hydrogel for effective loading and sustained release of EVs. In vitro, we explored the rejuvenation effects of CS hydrogel-incorporated EVs (CS-EVs) on replicative senescence DFLs through a series of experiments such as senescence-associated β-galactosidase (SA-β-gal) staining, RT-PCR, and western blots. Besides, we employed local multi-site subcutaneous injection to treat the back skin of naturally aging mice with CS-EVs and used DiI fluorescent dye to label EVs to achieve in vivo real-time tracking.Results: CS-EVs can significantly improve the biological functions of senescent fibroblasts, including promoting their proliferation, enhancing the synthesis of ECM proteins, and inhibiting the overexpression of matrix metalloproteinases (MMPs). Moreover, CS hydrogel could prolong the release of EVs and significantly increase the retention rate of EVs in vivo. After CS-EVs subcutaneous injection treatment, the aging skin tissues showed a state of rejuvenation, which was specifically manifested as enhanced expression of collagen, decreased expression of SASP-related factors, and restoration of tissue structures.Conclusions: CS hydrogel-encapsulated EVs could delay the skin aging process by ameliorating the function of aging DFLs. Our results also highlight the potential of CS hydrogel-encapsulated EVs as a novel therapeutic strategy for ameliorating aging skin to rejuvenation.
Isolation and characterization of diesel-degrading bacteria from hydrocarbon-contaminated sites, flower farms and soda lakes
Authors: Bekele Gessesse Kebede , Bogale Eshetu Mekonne , Fida Tekle Tafesse , Woldesemayat Adugna Abdi , Gemeda Mesfin Tafesse , Tuji Fassil Assefa 
Published: December 2020

Abstract
Background: Hydrocarbon-derived pollutants are becoming one of the most concerning ecological issues. Thus, there is a need to investigate and develop innovative, low-cost, eco-friendly, and fast techniques to reduce and/or eliminate pollutants using biological agents. The current study is conducted to isolate, characterize, and identify potential diesel-degrading bacteria.Results: Samples were collected from flower farms, lakeshores, old aged garages, asphalt, and bitumen soils and spread on selective medium (Bushnell Hass Mineral Salts Agar) containing diesel as the growth substrate. The isolates were characterized based on their growth patterns using OD measurement, biochemical testing and gravimetric analysis and identified using the Biolog database, and 16S rRNA gene sequencing techniques. Subsequently, six diesel degraders were identified and belong to Pseudomonas , Providencia , Roseomonas , Stenotrophomonas , Achromobacter , and Bacillus . Among these, based on gravimetric analysis, the three potent isolates AAUW23, AAUG11 and AAUG36 achieved 84%, 83.4%, and 83% diesel degradation efficiency, respectively, in 15 days. Consequently, the partial 16S rRNA gene sequences revealed that the two most potent bacterial strains (AAUW23 and AAUG11) were Pseudomonas aeruginosa , while AAUG36 was Bacillus subtilis . Conclusion: This study demonstrated that bacterial species isolated from hydrocarbon-contaminated and/or uncontaminated environments could be optimized to be used as potential bioremediation agents for diesel removal.
Forskolin enhances the antitumor effect of oncolytic measles virus by promoting Rab27a dependent vesicular transport system in the lung cancer A549 cells in vitro
Authors: Xia Mao , Xia Yongquan , Xu Xuejing , Meng Gang , Yan Hong , Shen Han 
Published: December 2020

Abstract
Background: Measles vaccine strain viruses (MV-Edm) are an ideal platform for developing safe and effective oncolytic vectors. However, despite the promising pre-clinical data, understanding of determinants of efficacy and, thus, the interplay of the oncolytic virus with particular agents remains limited.Methods: We investigated the potency of forskolin enhancing the antitumor effect of oncolytic measles virus by promoting Rab27a dependent vesicular transport system. Cells were infected with MV-Edm and the vesicles were observed by TEM. The oncolytic effects of MV-Edm/Forskolin were investigated in vitro. Results: Here we demonstrate that the MV-Edm infection and spread in tumor, which are indispensable processes for the viral oncolysis, depend on the vesicular transport system of tumor cells. On the contrary, the tumor cells display a responsive mechanism to restrain the MV-Edm spread by down-regulating the expression of Rab27a, which is a key member of the vesicle transport system. Over-expression of Rab27a promotes the oncolytic efficacy of MV-Edm towards A549 tumor cells. Finally, we find a Rab27a agonist Forskolin, is capable of promoting the oncolytic effect of MV-Edm in vitro. Conclusions: Our study reveals the important role of vesicle transporter Rab27a in the whole program of MV-Edm mediated oncolysis. We also provide a combined strategy of Forskolin and MV-Edm, which may exert a synergistic anti-tumor effect, for clinical treatment for patients with tumor.
How long-term changes in general and abdominal obesity indices in prediabetic subjects predict the incidence of diabetes in future: results from a 16-year prospective cohort study among first-degree relatives of type 2 diabetic patients
Authors: Safari Shahla , Abdoli Maryam , Amini Masoud , Aminorroaya Ashraf , Feizi Awat 
Published: December 2020

Abstract
Background Obesity indices abnormality pervasively is associated with the risk of type 2 diabetes mellitus (T2DM). This study aimed to identify the patterns of changes in obesity indices over time in prediabetic subjects and to classify these subjects as either having a low, moderate, and high risk for developing diabetes in future. Methods This prospective 16-year cohort study was conducted among 1228 prediabetic subjects. The patterns of changes in general and abdominal obesity indices based on three measurements including first, mean values during the follow-up period and last visit from these indices were evaluated by using the latent Markov model (LMM). Results The mean (standard deviation) age of subjects was 44.0 (6.8) years and 73.6% of them were female. The LMM identified three latent states of subjects in terms of change in all anthropometric indices: a low, moderate, and high tendency to progress diabetes with the state sizes (29%, 45%, and 26%), respectively. LMM showed that the probability of transitioning from a low to a moderate tendency to progress diabetes was higher than the other transition probabilities.Conclusions Based on a long-term evaluation of patterns of changes in general and abdominal obesity indices, we classified prediabetic subjects into three groups (low, moderate, and high risk to progress diabetes in future). Also, the method used enabled us to estimate the transition probabilities from low- to moderate and to high-risk states and vice versa. Our results reemphasized the values of all five obesity indices in clinical settings for identifying prediabetic subjects as a high-risk people for progressing diabetes and the need for more effective obesity prevention strategies.
IoT DoS and DDoS Attack Detection using ResNet
Authors: Hussain Faisal , Abbas Syed Ghazanfar , Husnain Muhammad , Fayyaz Ubaid U. , Shahzad Farrukh , Shah Ghalib A. 
Published: December 2020

Abstract
The network attacks are increasing both in frequency and intensity with the rapid growth of internet of things (IoT) devices. Recently, denial of service (DoS) and distributed denial of service (DDoS) attacks are reported as the most frequent attacks in IoT networks. The traditional security solutions like firewalls, intrusion detection systems, etc., are unable to detect the complex DoS and DDoS attacks since most of them filter the normal and attack traffic based upon the static predefined rules. However, these solutions can become reliable and effective when integrated with artificial intelligence (AI) based techniques. During the last few years, deep learning models especially convolutional neural networks achieved high significance due to their outstanding performance in the image processing field. The potential of these convolutional neural network (CNN) models can be used to efficiently detect the complex DoS and DDoS by converting the network traffic dataset into images. Therefore, in this work, we proposed a methodology to convert the network traffic data into image form and trained a state-of-the-art CNN model, i.e., ResNet over the converted data. The proposed methodology accomplished 99.99\% accuracy for detecting the DoS and DDoS in case of binary classification. Furthermore, the proposed methodology achieved 87\% average precision for recognizing eleven types of DoS and DDoS attack patterns which is 9\% higher as compared to the state-of-the-art.
The semi-dwarfing gene Rht-dp from dwarf Polish wheat (Triticum polonicum L.) is the “Green Revolution” gene Rht-B1b
Authors: Chai Songyue , Yao Qin , Zhang Xu , Xiao Xue , Fan Xing , Zeng Jian , Sha Lina , Kang Houyang , Zhang Haiqin , Li Jun , Zhou Yonghong , Wang Yi 
Published: December 2020

Abstract
Background: The wheat dwarfing gene increases lodging resistance, the grain number per spike and harvest index. Dwarf Polish wheat (Triticum polonicum L., 2n = 4x = 28, AABB, DPW), initially collected from Tulufan, Xinjiang, China, carries a semi-dwarfing gene Rht-dp on chromosome 4BS. However, Rht-dp and its dwarfing mechanism are unknown.Results: Homologous cloning and fine mapping revealed that Rht-dp is the ‘Green Revolution’ gene Rht-B1b. A haplotype analysis in 59 tetraploid wheat accessions showed that Rht-B1b was only present in T. polonicum. Transcriptomic analysis of two pairs of near-isogenic lines (NILs) of DPW×Tall Polish wheat (Triticum polonicum L., 2n = 4x = 28, AABB, TPW) revealed 41 differentially expressed genes (DEGs) as potential dwarfism-related genes. Among them, 28 functionally annotated DEGs were classed into five sub-groups: hormone-related signalling transduction genes, transcription factor genes, cell wall structure-related genes, reactive oxygen-related genes, and nitrogen regulation-related genes. Conclusions: These results indicated that Rht-dp is Rht-B1b, which regulates pathways related to hormones, reactive oxygen species, and nitrogen assimilation to modify the cell wall structure, and then limits cell wall loosening and inhibits cell elongation, thereby causing dwarfism in DPW.
Once is rarely enough: Can social prescribing facilitate adherence to non-clinical community and voluntary sector health services? Empirical evidence from Germany
Authors: Golubinski Veronika , Wild Eva-Maria , Winter Vera , Schreyögg Jonas 
Published: December 2020

Abstract
Background: Non-clinical health interventions provided by the voluntary and community sector can improve patients’ health and well-being and reduce pressure on primary and secondary care, but only if patients adhere to them. This study provides novel insights into the impact of doctor referrals to such services, known as social prescribing, on patients’ adherence to them. Methods: Using a negative binomial model, we analysed electronic visitor records from a community health advice and navigation service in Germany between January 2018 and December 2019 to determine whether social prescribing was associated with greater adherence to the service (measured in terms of return visits) compared to patients who self-referred. We also explored whether this effect differed according to patient characteristics. Results: Based on 1,734 observations, we found that social prescribing was significantly associated with a greater number of return visits compared to patient self-referrals (p<0.05). For patients who visited the service because of psychological concerns, the effect of social prescribing was lower. For all other patient characteristics, the effect remained unchanged, suggesting relevance to all other patient groups. Conclusions: The results of our study indicate that social prescribing may be an effective way to facilitate adherence to non-clinical community and voluntary sector health services. This knowledge is important for policy makers who are deciding whether to implement or expand upon social prescribing schemes.
Bio-sorption for Effective Removal of Chromium (VI) from Wastewater Using Moringa Stenopetala Seed Powder (MSSP) and Banana Peel Powder (BPP)
Authors: Badessa Tolera Seda , Wakuma Esayas , Yimer Ali Mohammed 
Published: December 2020

Abstract
Chromium is an extremely toxic metal in the form of Cr (VI) that causes severe environmental and health problems. Therefore, the aim of this study was to remove chromium ions from wastewater by using cost effective and environmentally friendly bio-sorbents; Moringa stenopetala Seed Powder (MSSP), and Banana Peel Powder (BPP) and to evaluate its adsorption capacities as bio-sorbents. FT-IR characterization of the adsorbents showed that there was a change in the functional groups of the structure of both adsorbents before and after the adsorption that might be due to the adsorption processes taken place on the surface of adsorbent. Adsorption experiments were carried out as batch studies with different contact times, pH, adsorbent dose, initial metal ion concentration, and temperature. Results showed maximum removal efficiency for Cr (VI) at 120 minutes contact time, adsorbent dose of 20 g/L and pH 2 by MSSP and pH 4 by BPP. The percentage removal of Cr(VI) increased with increasing adsorbent dose( from 5g/L to 20 g/L) and contact time (from 60 min to 120 min). Freundlich isotherm model showed a better fit to the equilibrium data than the Langmuir model. The kinetics of adsorption for chromium was well represented by pseudo-second order kinetic model and the calculated equilibrium sorption capacity of the model showed good agreement with the sorption capacity obtained from Experimental results.