bluuebunny/crossref_metadata_2025_split huggingface dataset:
A signature of seven immune‐related genes predicts overall survival in male gastric cancer patients
Authors: Xu Xin , Lu Yida , Wu Youliang , Wang Mingliang , Wang Xiaodong , Wang Huizhen , Chen Bo , Li Yongxiang 
Published: February 2021

AbstractBackgroundGastric cancer (GC) has a high mortality rate and is one of the most fatal malignant tumours. Male sex has been proven as an independent risk factor for GC. This study aimed to identify immune-related genes (IRGs) associated with the prognosis of male GC.MethodsRNA sequencing and clinical data were obtained from The Cancer Genome Atlas (TCGA) database. Differentially expressed IRGs between male GC and normal tissues were identified by integrated bioinformatics analysis. Univariate and multivariate Cox regression analyses were applied to screen survival-associated IRGs. Then, GC patients were separated into high- and low-risk groups based on the median risk score. Furthermore, a nomogram was constructed based on the TCGA dataset. The prognostic value of the risk signature model was evaluated by Kaplan-Meier curve, receiver operating characteristic (ROC), Harrell’s concordance index and calibration curves. In addition, the gene expression dataset from the Gene Expression Omnibus (GEO) was also downloaded for external validation. The relative proportions of 22 types of infiltrating immune cells in each male GC sample were evaluated using CIBERSORT.ResultsA total of 276 differentially expressed IRGs were screened, including 189 up-regulated and 87 down-regulated genes. Subsequently, a seven-IRGs signature (LCN12, CCL21, RNASE2, CGB5, NRG4, AGTR1 and NPR3) was identified to be significantly associated with the overall survival (OS) of male GC patients. Survival analysis indicated that patients in the high-risk group exhibited a poor clinical outcome. The results of multivariate analysis revealed that the risk score was an independent prognostic factor. The established nomogram could be used to evaluate the prognosis of individual male GC patients. Further analysis showed that the prognostic model had excellent predictive performance in both TCGA and validated cohorts. Besides, the results of tumour-infiltrating immune cell analysis indicated that the seven-IRGs signature could reflect the status of the tumour immune microenvironment.ConclusionsOur study developed a novel seven-IRGs risk signature for individualized survival prediction of male GC patients.
High frequency of the Duffy-negative genotype and absence of Plasmodium vivax infections in Ghana
Authors: Brown Charles A. , Pappoe-Ashong Prince J. , Duah Nancy , Ghansah Anita , Asmah Harry , Afari Edwin , Koram Kwadwo A. 
Published: February 2021

Abstract
Background
Recent studies from different malaria-endemic regions including western Africa have now shown that Plasmodium vivax can infect red blood cells (RBCs) and cause clinical disease in Duffy-negative people, though the Duffy-negative phenotype was thought to confer complete refractoriness against blood invasion with P. vivax. The actual prevalence of P. vivax in local populations in Ghana is unknown and little information is available about the distribution of Duffy genotypes. The aim of this study was to assess the prevalence of P. vivax in both asymptomatic and symptomatic outpatients and the distribution of Duffy genotypes in Ghana.

Methods
DNA was extracted from dried blood spots (DBS) collected from 952 subjects (845 malaria patients and 107 asymptomatic persons) from nine locations in Ghana. Plasmodium species identification was carried out by nested polymerase chain reaction (PCR) amplification of the small-subunit (SSU) rRNA genes. For P. vivax detection, a second PCR of the central region of the Pvcsp gene was carried out. Duffy blood group genotyping was performed by allele-specific PCR to detect the presence of the FYES allele.

Results
No cases of P. vivax were detected in any of the samples by both PCR methods used. Majority of infections (542, 94.8%) in the malaria patient samples were due to P. falciparum with only 1 infection (0.0017%) due to Plasmodium malariae, and 2 infections (0.0034%) due to Plasmodium ovale. No case of mixed infection was identified. Of the samples tested for the FYES allele from all the sites, 90.5% (862/952) had the FYES allele. All positive samples were genotyped as FY*B-33/FY*B-33 (Duffy-negative homozygous) and therefore classified as Fy(a−b−).

Conclusions
No cases of P. vivax were detected by both PCRs and majority of the subjects tested carried the FYES allele. The lack of P. vivax infections observed can be attributed to the high frequency of the FYES allele that silences erythroid expression of the Duffy. These results provide insights on the host susceptibility for P. vivax infections that had not been investigated in Ghana before.
Foot progression angle estimation using a single foot-worn inertial sensor
Authors: Wouda Frank J. , Jaspar Stephan L. J. O. , Harlaar Jaap , van Beijnum Bert-Jan F. , Veltink Peter H. 
Published: February 2021

Abstract
Background
The foot progression angle is an important measure used to help patients reduce their knee adduction moment. Current measurement systems are either lab-bounded or do not function in all environments (e.g., magnetically distorted). This work proposes a novel approach to estimate foot progression angle using a single foot-worn inertial sensor (accelerometer and gyroscope).

Methods
The approach uses a dynamic step frame that is recalculated for the stance phase of each step to calculate the foot trajectory relative to that frame, to minimize effects of drift and to eliminate the need for a magnetometer. The foot progression angle (FPA) is then calculated as the angle between walking direction and the dynamic step frame. This approach was validated by gait measurements with five subjects walking with three gait types (normal, toe-in and toe-out).

Results
The FPA was estimated with a maximum mean error of ~ 2.6° over all gait conditions. Additionally, the proposed inertial approach can significantly differentiate between the three different gait types.

Conclusion
The proposed approach can effectively estimate differences in FPA without requiring a heading reference (magnetometer). This work enables feedback applications on FPA for patients with gait disorders that function in any environment, i.e. outside of a gait lab or in magnetically distorted environments.
Does insulin resistance influence neurodegeneration in non-diabetic Alzheimer’s subjects?
Authors: Femminella Grazia Daniela , Livingston Nicholas R. , Raza Sanara , van der Doef Thalia , Frangou Eleni , Love Sharon , Busza Gail , Calsolaro Valeria , Carver Stefan , Holmes Clive , Ritchie Craig W. , Lawrence Robert M. , McFarlane Brady , Tadros George , Ridha Basil H. , Bannister Carol , Walker Zuzana , Archer Hilary , Coulthard Elizabeth , Underwood Ben , Prasanna Aparna , Koranteng Paul , Karim Salman , Junaid Kehinde , McGuinness Bernadette , Passmore Anthony Peter , Nilforooshan Ramin , Macharouthu Ajayverma , Donaldson Andrew , Thacker Simon , Russell Gregor , Malik Naghma , Mate Vandana , Knight Lucy , Kshemendran Sajeev , Tan Tricia , Holscher Christian , Harrison John , Brooks David J. , Ballard Clive , Edison Paul 
Published: February 2021

Abstract
Background
Type 2 diabetes is a risk factor for Alzheimer’s disease (AD), and AD brain shows impaired insulin signalling. The role of peripheral insulin resistance on AD aetiopathogenesis in non-diabetic patients is still debated. Here we evaluated the influence of insulin resistance on brain glucose metabolism, grey matter volume and white matter lesions (WMLs) in non-diabetic AD subjects.

Methods
In total, 130 non-diabetic AD subjects underwent MRI and [18F]FDG PET scans with arterial cannula insertion for radioactivity measurement. T1 Volumetric and FLAIR sequences were acquired on a 3-T MRI scanner. These subjects also had measurement of glucose and insulin levels after a 4-h fast on the same day of the scan. Insulin resistance was calculated by the updated homeostatic model assessment (HOMA2). For [18F]FDG analysis, cerebral glucose metabolic rate (rCMRGlc) parametric images were generated using spectral analysis with arterial plasma input function.

Results
In this non-diabetic AD population, HOMA2 was negatively associated with hippocampal rCMRGlc, along with total grey matter volumes. No significant correlation was observed between HOMA2, hippocampal volume and WMLs.

Conclusions
In non-diabetic AD, peripheral insulin resistance is independently associated with reduced hippocampal glucose metabolism and with lower grey matter volume, suggesting that peripheral insulin resistance might influence AD pathology by its action on cerebral glucose metabolism and on neurodegeneration.
Could graph neural networks learn better molecular representation for drug discovery? A comparison study of descriptor-based and graph-based models
Authors: Jiang Dejun , Wu Zhenxing , Hsieh Chang-Yu , Chen Guangyong , Liao Ben , Wang Zhe , Shen Chao , Cao Dongsheng , Wu Jian , Hou Tingjun 
Published: February 2021

AbstractGraph neural networks (GNN) has been considered as an attractive modelling method for molecular property prediction, and numerous studies have shown that GNN could yield more promising results than traditional descriptor-based methods. In this study, based on 11 public datasets covering various property endpoints, the predictive capacity and computational efficiency of the prediction models developed by eight machine learning (ML) algorithms, including four descriptor-based models (SVM, XGBoost, RF and DNN) and four graph-based models (GCN, GAT, MPNN and Attentive FP), were extensively tested and compared. The results demonstrate that on average the descriptor-based models outperform the graph-based models in terms of prediction accuracy and computational efficiency. SVM generally achieves the best predictions for the regression tasks. Both RF and XGBoost can achieve reliable predictions for the classification tasks, and some of the graph-based models, such as Attentive FP and GCN, can yield outstanding performance for a fraction of larger or multi-task datasets. In terms of computational cost, XGBoost and RF are the two most efficient algorithms and only need a few seconds to train a model even for a large dataset. The model interpretations by the SHAP method can effectively explore the established domain knowledge for the descriptor-based models. Finally, we explored use of these models for virtual screening (VS) towards HIV and demonstrated that different ML algorithms offer diverse VS profiles. All in all, we believe that the off-the-shelf descriptor-based models still can be directly employed to accurately predict various chemical endpoints with excellent computability and interpretability.
Nanobody Nb6 fused with porcine IgG Fc as the delivering tag to inhibit porcine reproductive and respiratory syndrome virus replication in porcine alveolar macrophages
Authors: Zhang Lu , Wang Lizhen , Cao Shuaishuai , Lv Huanhuan , Huang Jingjing , Zhang Guixi , Tabynov Kaissar , Zhao Qin , Zhou En-Min 
Published: February 2021

AbstractPorcine reproductive and respiratory syndrome virus (PRRSV) is a highly contagious virus that has led to enormous economic loss worldwide because of ineffective prevention and treatment. In view of their minimized size, high target specificity and affinity, nanobodies have been extensively investigated as diagnostic tools and treatments of many diseases. Previously, a PRRSV Nsp9-specific nanobody (Nb6) was identified as a PRRSV replication inhibitor. When it was fused with cell-penetrating peptide (CPP) TAT, Nb6-TAT could enter the cells for PRRSV suppression. However, delivery of molecules by CPP lack cell specificity and have a short duration of action. PRRSV has a tropism for monocyte/macrophage lineage, which expresses high levels of Fcγ receptors. Herein, we designed a nanobody containing porcine IgG Fc (Fcγ) to inhibit PRRSV replication in PRRSV permissive cells. Fcγ fused Nb6 chimeric antibody (Nb6-pFc) was assembled into a dimer with interchain disulfide bonds and expressed in aPichia pastorissystem. The results show that Nb6-pFc exhibits a well-binding ability to recombinant Nsp9 or PRRSV-encoded Nsp9 and that FcγR-mediated endocytosis of Nb6-pFc into porcine alveolar macrophages (PAM) was in a dose-dependent manner. Nb6-pFc can inhibit PRRSV infection efficiently not only by binding with Nsp9 but also by upregulating proinflammatory cytokine production in PAM. Together, this study proposes the design of a porcine IgG Fc-fused nanobody that can enter PRRSV susceptible PAM via FcγR-mediated endocytosis and inhibit PRRSV replication. This research reveals that nanobody-Fcγ chimeric antibodies might be effective for the control and prevention of monocyte/macrophage lineage susceptible pathogeneses.
Clonal spread of multi-resistant Gallibacterium anatis isolates among Iranian broilers and layers
Authors: Allahghadry Toloe , Ng Duncan Y. K. , Dibaei Alireza , Bojesen Anders Miki 
Published: February 2021

AbstractGallibacterium anatis is a common cause of reproductive tract infection in chickens, which leads to reduced egg production and increased mortality. This study was undertaken to investigate prevalence of G. anatis in 12 poultry flocks originating from Iranian provinces with leading chicken production and to determine genetic diversity, antimicrobial resistance, and the presence of major antigens of the isolates investigated. Out of the 120 chicken tracheal samples collected and tested, 84 (70%) were positive for G. anatis. Genotyping by Pulse Field Gel Electrophoresis and genome sequencing revealed a total of 24 pulsotypes for 71 strains (at a 87% similarity level) and seven genome clusters comprising 21 strains (97% similarity level), respectively. The combination of the two typing methods confirmed the presence of several genotypes originating from a common ancestor affecting poultry yet also suggested that identical clones were shared among chickens within farms and between different farms. The latter finding is to our knowledge the first example of clonal presence of G. anatis in epidemiologically unrelated farms. The 21 sequenced strains were characterized against a panel of commonly used antibiotics and showed lowered sensitivity to tetracycline (76.2%) and enrofloxacin (90.5%). The widespread presence of multiresistant G. anatis isolates calls for non-antibiotic prophylactics. Three major immunogen genes, gtxA, Gab_1309 and Gab_2312 were detected in the isolates indicating these antigens likely represent effective vaccine targets. A conserved sequence of the gtxA gene across a range of epidemiologically independent strains suggests the use of GtxA for future vaccine development purposes.
Next-generation UWB antennas gadgets for human health care using SAR
Authors: Ali Aysha Maryam , Al Ghamdi Mohammed A. , Iqbal Muhammad Munwar , Khalid Shehzad , Aldabbas Hamza , Saeed Saqib 
Published: February 2021

AbstractThe body area network is now the most challenging and most popular network for study and research. Communication about the body has undoubtedly taken its place due to a wide variety of applications in industry, health care, and everyday life in wireless network technologies. The body area network requires such smart antennas that can provide the best benefits and reduce interference with the same channel. The discovery of this type of antenna design is at the initiative of this research. In this work, to get a good variety, the emphasis is on examining different techniques. The ultra-wide band is designed, simulated, and manufactured because the ultra-wide band offers better performance compared to narrowband antennas. To analyze the specific absorption rate, we designed a multilayer model of human head and hand in the high-frequency structure simulator. In the final stage, we simulated our antennas designed with the head and hand model to calculate the results of the specific absorption rate. The analysis of the specific absorption rate for the head and hand was calculated by placing the antennas on the designed model.
Two-factor higher-order model of perfectionism in Iranian general and clinical samples
Authors: Moloodi Reza , Pourshahbaz Abbas , Mohammadkhani Parvaneh , Fata Ladan , Ghaderi Ata 
Published: February 2021

Abstract
Background
Studies in Western cultures have shown that perfectionism is conceptualized by two-factor higher-order model including perfectionistic strivings and perfectionistic concerns. However, little is known about the construct of perfectionism in Eastern societies. Thus, we examined the two-factor higher-order model of perfectionism in Iranian general and clinical samples.

Methods
We recruited a general population sample (n = 384) and patients with major depressive disorder, obsessive compulsive disorder, social anxiety disorder, and eating disorders (n = 152) from Tehran, Iran from September 2016 to December 2017. They completed the Clinical Perfectionism Questionnaire, Perfectionism Inventory, and Depression, Anxiety, Stress Scale-21.

Results
The two-factor higher-order model of perfectionism showed adequate fit with data for females from the general population and clinical sample. Data for males were only available from the general population, and the model showed adequate fit with the data first after removing the Rumination scale of the perfectionistic concerns. The perfectionistic strivings dimension showed no or negative association with depression, anxiety, and stress symptoms, but perfectionistic concerns dimension showed positive correlation with these indices in all samples for both males and females.

Conclusions
The results support the two-factor higher-order model of perfectionism in samples of Iranian females from the general population and clinical sample. However, the results were different for males from the general population. In other words, the modified two-factor higher-order model showed acceptable fit with the data for males from the general population only after removing the Rumination scale from perfectionistic concerns. These differences among males and females were discussed.
Targeted proteomics-derived biomarker profile develops a multi-protein classifier in liquid biopsies for early detection of esophageal squamous cell carcinoma from a population-based case-control study
Authors: Yang Xiaorong , Suo Chen , Zhang Tongchao , Yin Xiaolin , Man Jinyu , Yuan Ziyu , Yu Jingru , Jin Li , Chen Xingdong , Lu Ming , Ye Weimin 
Published: February 2021

Abstract
Background
Early diagnosis of esophageal squamous cell carcinoma (ESCC) remains a challenge due to the lack of specific blood biomarkers. We aimed to develop a serum multi-protein signature for the early detection of ESCC.

Methods
We selected 70 healthy controls, 30 precancerous patients, 60 stage I patients, 70 stage II patients and 70 stage III/IV ESCC patients from a completed ESCC case-control study in a high-risk area of China. Olink Multiplex Oncology II targeted proteomics panel was used to simultaneously detect the levels of 92 cancer-related proteins in serum using proximity extension assay.

Results
We found that 10 upregulated and 13 downregulated protein biomarkers in serum could distinguish the early-stage ESCC from healthy controls, which were validated by the significant dose-response relationships with ESCC pathological progression. Applying least absolute shrinkage and selection operator (LASSO) regression and backward elimination algorithm, ANXA1 (annexin A1), hK8 (kallikrein-8), hK14 (kallikrein-14), VIM (vimentin), and RSPO3 (R-spondin-3) were kept in the final model to discriminate early ESCC cases from healthy controls with an area under curve (AUC) of 0.936 (95% confidence interval: 0.899 ~ 0.973). The average accuracy rates of the five-protein classifier were 0.861 and 0.825 in training and test data by five-fold cross-validation.

Conclusions
Our study suggested that a combination of ANXA1, hK8, hK14, VIM and RSPO3 serum proteins could be considered as a potential tool for screening and early diagnosis of ESCC, especially with the establishment of a three-level hierarchical screening strategy for ESCC control.
Evaluation of recent advances in recommender systems on Arabic content
Authors: Srifi Mehdi , Oussous Ahmed , Ait Lahcen Ayoub , Mouline Salma 
Published: February 2021

AbstractVarious recommender systems (RSs) have been developed over recent years, and many of them have concentrated on English content. Thus, the majority of RSs from the literature were compared on English content. However, the research investigations about RSs when using contents in other languages such as Arabic are minimal. The researchers still neglect the field of Arabic RSs. Therefore, we aim through this study to fill this research gap by leveraging the benefit of recent advances in the English RSs field. Our main goal is to investigate recent RSs in an Arabic context. For that, we firstly selected five state-of-the-art RSs devoted originally to English content, and then we empirically evaluated their performance on Arabic content. As a result of this work, we first build four publicly available large-scale Arabic datasets for recommendation purposes. Second, various text preprocessing techniques have been provided for preparing the constructed datasets. Third, our investigation derived well-argued conclusions about the usage of modern RSs in the Arabic context. The experimental results proved that these systems ensure high performance when applied to Arabic content.
Performance and risk factors associated with first antibiotic treatment in two herds, raising pigs without antibiotics
Authors: Lynegaard J. C. , Larsen I. , Hansen C. F. , Nielsen J. P. , Amdi C. 
Published: February 2021

AbstractBackgroundAntibiotic (AB) consumption in production animals has a high awareness among politicians and consumers due to the risk of selection for AB resistance among potentially zoonotic bacteria. However, AB treatment of animals is at times necessary to treat diseases and ensure the wellbeing of the animals we take into our care. Raised without antibiotics (RWA) is a concept where pigs are individually ear-tagged for tracking, and if pigs are AB treated, they lose their RWA status. At slaughter, the farmer receives an additional price for non-AB treated pigs. The objective of this study was to identify risk factors for AB treatment and to investigate growth performance of pigs in two Danish RWA herds.ResultsA total of 518 pigs in herd A and 436 pigs in herd B, were individually ear-tagged and subjected to weekly investigations of AB treatment status from birth to 12 weeks of age. Bodyweight was recorded at birth, 2, 4 and 12 weeks of age. The results showed, that at 12 weeks of age, 82 of 518 liveborn pigs were AB treated in herd A and 31 of 436 liveborn pigs were AB treated in herd B. Individual pigs that required AB treatment had a reduced average daily gain from day 0 to 28 in both herds (herd A,P <  0.001; herd B,P = 0.062) and from day 0 to 84 in herd A (P <  0.001). Additionally, significant risk factors for AB treatment were identified as a low bodyweight in herd A, whereas barrows and litters with less than 19 piglets were the main risk factors in herd B.ConclusionThe results suggests that in order to reduce AB treatments particular attention should be addressed to smaller pigs and barrows in RWA herds. In these two Danish RWA herds from this study it was possible for 64 and 68% pigs to reach 12 weeks of life without any AB treatments.