bluuebunny/crossref_metadata_2025 huggingface dataset:
OptimisAtion of Diagnostic Accuracy in idioPathic inflammaTory myopathies (ADAPT study): a protocol for a prospective diagnostic accuracy study of multimodality testing in patients suspected of a treatable idiopathic inflammatory myopathy
Authors: Walter Hannah A W , Kamperman Renske G , Raaphorst Joost , Verhamme Camiel , Koelman Johannes H T M , Potters Wouter V , Hemke Robert , Smithuis Frank F , Aronica Eleonora , van Leeuwen Ester M M , Baars Paul A , de Visser Marianne , van Schaik Ivo N , Bossuyt Patrick M M , van der Kooi Anneke J
Published: December 2021

Introduction

Idiopathic inflammatory myopathies (IIMs) excluding inclusion body myositis (IBM) are a group of heterogeneous autoimmune disorders characterised by subacute-onset and progressive proximal muscle weakness, which are frequently part of a multisystem autoimmune disorder. Reaching the diagnosis can be challenging, and no gold standard for the diagnosis of IIM exists. Diagnostic modalities include serum creatine kinase activity, muscle imaging (MRI or ultrasound (US)), electromyography (EMG), myositis autoantibody testing and muscle biopsy. Several diagnostic criteria have been developed for IIMs, varying in reported sensitivity and specificity.

Hypothesis

We hypothesise that an evidence-based diagnostic strategy, using fewer and preferably the least invasive diagnostic modalities, can achieve the accuracy of a complete panel of diagnostic tests, including MRI, US, EMG, myositis-specific autoantibody testing and muscle biopsy.

Methods and analysis

The OptimizAtion of Diagnostic Accuracy in idioPathic inflammaTory myopathies study is a prospective diagnostic accuracy study with an over-complete study design. 100 patients suspected of an IIM excluding IBM will be included. A reference diagnosis will be assigned by an expert panel using all clinical information and all results of all ancillary tests available, including 6 months of follow-up. Several predefined diagnostic strategies will be compared against the reference diagnosis to find the optimal diagnostic strategy.

Ethics and dissemination

Ethical approval was obtained from the medical ethics committee of the Academic Medical Centre, University of Amsterdam, The Netherlands (2019-814). The results will be distributed through conference presentations and peer-reviewed publications.

Trial registration number

Netherlands trial register; NL8764.
Dexamethasone and hiccups: a 2000-patient, telephone-based study
Authors: Ehret Christopher J , Le-Rademacher Jennifer G , Martin Nichole , Jatoi Aminah
Published: December 2021

Objectives

Dexamethasone causes hiccups in an undefined percentage of patients, and these hiccups are often ignored (‘My doctors just shook their heads like I was joking …’). This study sought to learn the percentage of dexamethasone-treated patients who develop hiccups and to explore patients’ responses to the availability of educational materials on hiccups.

Methods

English-speaking, adult outpatients treated with oral, intravenous or epidural dexamethasone 2 weeks prior were contacted by phone and asked about hiccups. Educational materials were offered, and patients were queried on their opinion of the availability of such materials.

Results

One hundred and twenty-seven patients or 11% (95% CI 9% to 13%) reported hiccups. This percentage was derived from 1186 reachable patients from 2000 total patients. Fifty-four (43%) of those with hiccups desired to learn about educational materials. Of these, 49 completed a single-item, 5-point scale item: 21 (43%) viewed the availability of educational materials ‘extremely helpful,’ providing a 5 rating; 8 (16%) provided a 4; 4 (8%) provided a 3; and 1 (4%) provided a 2.

Conclusions

Dexamethasone-induced hiccups occur in a small percentage of patients. The fact that most patients responded favourably to learning about the availability of educational materials suggests some have unmet needs.
CUMS and dexamethasone induce depression-like phenotypes in mice by differentially altering gut microbiota and triggering macroglia activation
Authors: Wu Jing , Li Jinhang , Gaurav Chhetri , Muhammad Usman , Chen Yantian , Li Xueyi , Chen Jinghong , Wang Zejian
Published: December 2021

Background

Although the link between gut microbiota and depression has been suggested, changes of gut microbiota vary largely among individuals with depression.

Aims

Explore the heterogeneity of microbiota–gut–brain axis and new pathogenic characteristics in murine models of depression.

Methods

Adolescent female mice were randomly divided into control (CON) group (n=10), chronic unexpected mild stress (CUMS) group (n=15) and dexamethasone (DEX) group (n=15). Mice in the DEX group were gavaged twice a day with 0.2 mg/kg of DEX for 5 weeks, whereas CON mice were given the same amount of solvent. Mice in the CUMS group were exposed to stressors. After behavioural evaluations, all mice were sacrificed for harvesting tissues and blood samples. Enzyme-linked immunosorbent assay (ELISA) was conducted for measuring levels of corticosterone (CORT) and interleukin-1β (IL-1β) in sera, whereas levels of protein expression in colon and hippocampal tissues were examined by western blot. Faecal microbial communities were analysed by sequencing 16S rDNAs.

Results

Mice in CUMS and DEX groups exhibited severe depression-like behaviours. Compared with CON mice, CUMS-exposed mice showed a significant increase in both α and β diversity. Prevotellaceae and Desulfovibrio were enriched, whereas Bacilli were decreased in the faeces of mice in the CUMS group. DEX-treated mice had a decrease in the abundance ofClostridium XVIII. Levels of occludin in colon tissue of DEX-treated mice were reduced. Relative to mice in the CON and CUMS groups, DEX-treated mice contained higher serum levels of CORT and IL-1β. Compared with CON mice, mice in the DEX and CUMS groups had higher levels of IL-1β in sera and lower levels of glial fibrillary acidic protein (GFAP), Nestin, Synapsin-1 and P2Y12 receptor in the hippocampus.

Conclusions

Changes of gut microbiota diversity, intestinal integrity and neuroinflammation in the brain contribute to CUMS-induced depression, whereas pathobionts and excessive immunosuppression with damaged neuronal synapses is a basis of the DEX-induced depression.
Hyponatraemia in heart failure: time for new solutions?
Authors: Kapłon-Cieślicka Agnieszka , Soloveva Anzhela , Mareev Yura , Cabac-Pogorevici Irina , Verbrugge Frederik Hendrik , Vardas Panagiotis
Published: December 2021

Hyponatraemia is very common in heart failure (HF), especially in decompensated patients. It is associated with increased mortality and morbidity and considered a marker of advanced disease. Recognition of hyponatraemia and its causes may help guide treatment strategy. Historically, therapy has primarily focused on water restriction, decongestion with loop diuretics in case of volume overload (dilutional hyponatraemia) and sodium repletion in case of depletion. In this review, we summarise the potential benefits of established and emerging HF therapies on sodium homeostasis, with a focus on dual vasopressin antagonists, angiotensin receptor-neprilysin inhibitors, sodium-glucose cotransporter 2 inhibitors and hypertonic saline, and propose a potential therapeutic approach for hyponatraemia in HF.
Mechanism analysis and prediction of explosive formed projectile’s axial fracture
Authors: Ding Li , Jiang Jianwei , Wang Shuyou , Ji Liuqi
Published: December 2021

To explain the axial fracture phenomenon of Explosively Formed Projectile (EFP), the fracture mechanism of long rod EFP during the forming phase is analyzed by the stress wave theory. When the velocity gradient [Formula: see text] between the head and tail parts exceeds the critical value [Formula: see text], the EFP would fracture in the axial direction. Based on the Johnson–Cook constitutive model parameters and the special conditions in the forming phase of EFP, the critical velocity gradient [Formula: see text] can be determined by theoretical calculation and then validated by experimental results for both copper and tantalum EFPs. The experimental results for EFP’s fracture agree well with the prediction of the theoretical analysis. The theoretical analysis method can be applied as an important measure to determine the critical velocity gradient and predict the fracture of long rod EFP, providing reference for the application of new kinds of high density materials in the EFP research area.
Semi-Automatic Extraction and Mapping of Farmlands Based on High-Resolution Remote Sensing Images
Authors: Liu Dongsheng , Han Ling
Published: December 2021

Extraction of agricultural parcels from high-resolution satellite imagery is an important task in precision agriculture. Here, we present a semi-automatic approach for agricultural parcel detection that achieves high accuracy and efficiency. Unlike the techniques presented in previous literatures, this method is pixel based, and it exploits the properties of a spectral angle mapper (SAM) to develop customized operators to accurately derive the parcels. The main steps of the method are sample selection, textural analysis, spectral homogenization, SAM, thresholding, and region growth. We have systematically evaluated the algorithm proposed on a variety of images from Gaofen-1 wide field of view (GF-1 WFV), Resource 1-02C (ZY1-02C), and Gaofen-2 (GF-2) to aerial image; the accuracies are 99.09% of GF-1 WFV, 84.42% of ZY1-02C, 96.51% and 92.18% of GF-2, and close to 100% of aerial image; these results demonstrated its accuracy and robustness.
ROLE OF MEDIA COVERAGE IN MITIGATING AN EPIDEMIC OUTBREAK: AN OPTIMAL CONTROL MODEL
Authors: KAPOOR ANSHIKA , DEKA ANIRUDDHA , BHATTACHARYYA SAMIT
Published: December 2021

Flu is an acute respiratory infection caused by the influenza virus. The outbreak usually occurs every year in temperate region during the fall and winter seasons, but it is present year-round in tropics. Perceived risk of infection, affordability and lack of awareness among the population results in a low level of vaccination coverage. To control disease transmission and promote vaccination, public health officials use media coverage to spread awareness on vaccine safety, vaccine coverage, disease prevalence in the population through public health websites, advertisements, and other social media web pages. Media coverage acts as an incentive as it helps to decrease overall transmission potential and also at the same time increases the vaccination coverage in the population. Since the public health department has a limited budget, it needs to make optimum allocation of its effort to reduce the total cost of infection. Our paper investigates the effect of media coverage using SIR model of disease transmission. We look at three possible functional relationships — linear, exponential, and hyperbolic — the way media coverage may affect the disease transmission and vaccination rate. We derive necessary conditions of optimal solution using Optimal Control Theory and Pontryagin Maximum Principle (PMP) to minimize the total cost for infection. Analysis of our paper demonstrates that the cost of optimal management is four times less than the cost of constant control effort, and putting more effort into reducing transmission is optimal rather than an effort to increase vaccination at the beginning of the outbreak. Analysis of the role of media coverage under three different scenarios may help in formulating policies for public health programs in mitigating the influenza outbreak.
MODELING THE IMPACT OF EDUCATIONAL CAMPAIGN ON THE TRANSMISSION DYNAMICS OF EBOLA
Authors: DAUTEL KIMBERLY A. , AGYINGI EPHRAIM O.
Published: December 2021

Disease awareness that informs the public about the severity and transmission pathways of infectious diseases such as Ebola is key to curtailing an outbreak. Public health education when available can limit the intensity and duration of an Ebola outbreak in any community if there is compliance. It is important that all population groups be informed about the methods in which Ebola is transmitted to control the disease when there is an outbreak. In this paper, we study the impact of public health education that leads to behavioral changes on the dynamics of Ebola spread. The model is formulated as a system of ordinary differential equations and incorporates direct transmission from infectious, hospitalized, and deceased individuals with Ebola. We establish the existence of a disease free equilibrium and an endemic equilibrium, and investigate them for local and global stability. Model predictions show that a more informed community results in fewer cases, and thus limits the impact of an Ebola outbreak. Further, the model also predicts subsequent outbreak waves within a community in the absence of complete eradication. Lastly, the model successfully captures the dynamics of the 2014–2016 West Africa Ebola outbreak and the 2018–2020 Democratic Republic of Congo Ebola outbreak.
Arabic Handwritten Word Recognition Based on Stationary Wavelet Transform Technique using Machine Learning
Authors: Al-Shatnawi Atallah Mahmoud , Al-Saqqar Faisal , Souri Alireza
Published: December 2021

This paper is aimed at improving the performance of the
word recognition system (WRS)
of handwritten Arabic text by extracting features in the frequency domain using the
Stationary Wavelet Transform (SWT)
method using machine learning, which is a wavelet transform approach created to compensate for the absence of translation invariance in the 
Discrete Wavelets Transform (DWT)
method. The proposed SWT-WRS of Arabic handwritten text consists of three main processes: word normalization, feature extraction based on SWT, and recognition. The proposed SWT-WRS based on the SWT method is evaluated on the IFN/ENIT database applying the Gaussian, linear, and polynomial support vector machine, the k-nearest neighbors, and ANN classifiers. ANN performance was assessed by applying the
Bayesian Regularization (BR)
and
Levenberg-Marquardt (LM)
training methods. Numerous
wavelet transform (WT)
families are applied, and the results prove that level 19 of the Daubechies family is the best WT family for the proposed SWT-WRS. The results also confirm the effectiveness of the proposed SWT-WRS in improving the performance of handwritten Arabic word recognition using machine learning. Therefore, the suggested SWT-WRS overcomes the lack of translation invariance in the DWT method by eliminating the up-and-down samplers from the proposed machine learning method.
A Statistical Language Model for Pre-Trained Sequence Labeling: A Case Study on Vietnamese
Authors: Liao Xianwen , Huang Yongzhong , Yang Peng , Chen Lei
Published: December 2021

By defining the computable word segmentation unit and studying its probability characteristics, we establish an unsupervised statistical language model (SLM) for a new pre-trained sequence labeling framework in this article. The proposed SLM is an optimization model, and its objective is to maximize the total binding force of all candidate word segmentation units in sentences under the condition of no annotated datasets and vocabularies. To solve SLM, we design a recursive divide-and-conquer dynamic programming algorithm. By integrating SLM with the popular sequence labeling models, Vietnamese word segmentation, part-of-speech tagging and named entity recognition experiments are performed. The experimental results show that our SLM can effectively promote the performance of sequence labeling tasks. Just using less than 10% of training data and without using a dictionary, the performance of our sequence labeling framework is better than the state-of-the-art Vietnamese word segmentation toolkit VnCoreNLP on the cross-dataset test. SLM has no hyper-parameter to be tuned, and it is completely unsupervised and applicable to any other analytic language. Thus, it has good domain adaptability.
Handwritten Annotation Spotting in Printed Documents Using Top-Down Visual Saliency Models
Authors: Pandey Shilpa , Harit Gaurav
Published: December 2021

In this article, we address the problem of localizing text and symbolic annotations on the scanned image of a printed document. Previous approaches have considered the task of annotation extraction as binary classification into printed and handwritten text. In this work, we further subcategorize the annotations as underlines, encirclements, inline text, and marginal text. We have collected a new dataset of 300 documents constituting all classes of annotations marked around or in-between printed text. Using the dataset as a benchmark, we report the results of two saliency formulations—CRF Saliency and Discriminant Saliency, for predicting salient patches, which can correspond to different types of annotations. We also compare our work with recent semantic segmentation techniques using deep models. Our analysis shows that Discriminant Saliency can be considered as the preferred approach for fast localization of patches containing different types of annotations. The saliency models were learned on a small dataset, but still, give comparable performance to the deep networks for pixel-level semantic segmentation. We show that saliency-based methods give better outcomes with limited annotated data compared to more sophisticated segmentation techniques that require a large training set to learn the model.
Combining Self-supervised Learning and Active Learning for Disfluency Detection
Authors: Wang Shaolei , Wang Zhongyuan , Che Wanxiang , Zhao Sendong , Liu Ting
Published: December 2021

Spoken language is fundamentally different from the written language in that it contains frequent disfluencies or parts of an utterance that are corrected by the speaker. Disfluency detection (removing these disfluencies) is desirable to clean the input for use in downstream NLP tasks. Most existing approaches to disfluency detection heavily rely on human-annotated data, which is scarce and expensive to obtain in practice. To tackle the training data bottleneck, in this work, we investigate methods for combining self-supervised learning and active learning for disfluency detection. First, we construct large-scale pseudo training data by randomly adding or deleting words from unlabeled data and propose two self-supervised pre-training tasks: (i) a tagging task to detect the added noisy words and (ii) sentence classification to distinguish original sentences from grammatically incorrect sentences. We then combine these two tasks to jointly pre-train a neural network. The pre-trained neural network is then fine-tuned using human-annotated disfluency detection training data. The self-supervised learning method can capture task-special knowledge for disfluency detection and achieve better performance when fine-tuning on a small annotated dataset compared to other supervised methods. However, limited in that the pseudo training data are generated based on simple heuristics and cannot fully cover all the disfluency patterns, there is still a performance gap compared to the supervised models trained on the full training dataset. We further explore how to bridge the performance gap by integrating active learning during the fine-tuning process. Active learning strives to reduce annotation costs by choosing the most critical examples to label and can address the weakness of self-supervised learning with a small annotated dataset. We show that by combining self-supervised learning with active learning, our model is able to match state-of-the-art performance with just about 10% of the original training data on both the commonly used English Switchboard test set and a set of in-house annotated Chinese data.
Towards Developing Uniform Lexicon Based Sorting Algorithm for Three Prominent Indo-Aryan Languages
Authors: Ishraq Mir Ragib , Khadka Nitesh , Samir Asif Mohammed , Rahman M. Shahidur
Published: December 2021

Three different Indic/Indo-Aryan languages - Bengali, Hindi and Nepali have been explored here in character level to find out similarities and dissimilarities. Having shared the same root, the Sanskrit, Indic languages bear common characteristics. That is why computer and language scientists can take the opportunity to develop common
Natural Language Processing (NLP)
techniques or algorithms. Bearing the concept in mind, we compare and analyze these three languages character by character. As an application of the hypothesis, we also developed a uniform sorting algorithm in two steps, first for the Bengali and Nepali languages only and then extended it for Hindi in the second step. Our thorough investigation with more than 30,000 words from each language suggests that, the algorithm maintains total accuracy as set by the local language authorities of the respective languages and good efficiency.
The Commitment of Nineveh Governorate Residents to the Precautionary Measures against Global 2019 Pandemic and Dermatological Affection of Precautions
Authors: Al-Rahawe Baraa A. , Hamad Abdulsattar Abdullah , Al-Zuhairy Mohanad H. , Khalaf Hameed Hasan , Abebaw Solomon
Published: December 2021

The world has changed dramatically since the novel pandemic pours in all aspects of life, including economic, health, and social life. The first case was initially observed in the Wuhan province of China; fast spread occurs around the world. Until now, there is no proven effective treatment for it. The study’s objectives are to assess residents of Nineveh governorate’s commitment to the COVID-19 pandemic precautionary measures recommended by the WHO and Iraqi national authorities; the protective measures are used to prevent its spread and restrict the viral infectivity. Several cutaneous changes were observed in some persons as a result of prolonged contact with personal protective equipment and excessive use of personal hygiene measures.
Polymorphisms in MicroRNA Genes Associated with Schizophrenia Susceptibility but Not with Effectiveness of MECT
Authors: Zhang Danwei , Li Huihua , Ding Kaimo , Zhang Zhen , Luo Si , Li Guohai
Published: December 2021

Schizophrenia (SCZ) is a common and complex psychiatric disease associated with hereditary and environmental risk factors. MicroRNAs (miRNAs or miRs) are small, noncoding RNA molecules that endogenously regulate gene expression. Single nucleotide polymorphisms (SNPs) in related miRNA genes are associated with susceptibility of the disorder. We wonder if the SNPs have influence on the effectiveness of modified electroconvulsive therapy (MECT) for SCZ. rs1625579 within miR-137, rs6577555 within miR-34, and rs2296616 within miR-107 were sequenced in 150 cases and 150 controls to check the potential association between the SNPs and SCZ. Our results showed that allele G in rs1625579 (

p
=
0.005

,

adjusted
 
OR
=
1.379

,

95
%
CI
=
1.108
−
1.634

), allele A in rs6577555 (

p
=
0.014

,

adjusted
 
OR
=
1.246

,

95
%
CI
=
1.045
−
1.463

), allele G in rs2296616 (

p
<
0.001

,

adjusted
 
OR
=
1.646

,

95
%
CI
=
1.374
−
1.879

) are positively associated with the disorder risk. MECT courses did significantly decrease the level of the miRNAs, except for the variant of rs2296616 with the AA genotype. Schizophrenic phenotypes assessed by the positive and negative syndrome scale (PANSS) were improved after MECT, and there was no significant relevance observed between the effectiveness of MECT and the variants of these loci. Thus, our findings indicate that polymorphisms within the loci may be involved in the pathogenesis of SCZ, and MECT is effective and unbiased for patients harboring different genotypes of the loci.
Construction of College English Mobile Learning Model Based on Distributed Terminal
Authors: Wang Jianmei , Lei Linhai
Published: December 2021

The quality of English teaching cannot be separated from the students’s accumulation and mastery of vocabulary, and sufficient vocabulary can ensure that students feel easy and comfortable in the language application. However, there are still some problems in teaching English vocabulary in colleges and universities, such as single presentation method, lack of real context, and other difficulties. With the rapid development of mobile Internet, the share of smart mobile devices among college students has increased, which in turn has laid the foundation for the development of new learning modes. The mobile terminal-mediated learning mode in English classroom teaching has become a hot topic of research nowadays, of which English vocabulary teaching has become a typical example. This paper is designed as a system model of edge computing, in which the user terminal device can connect wirelessly with each MECS and offload the tasks to be processed on the MECS, which helps the user terminal device to process and return the results to the user terminal device. The research in this paper also provides a basis for students’ independent and lifelong learning of English words and for schools’ information technology to serve English vocabulary teaching and learning.
Predictive Biomarkers for Postmyocardial Infarction Heart Failure Using Machine Learning: A Secondary Analysis of a Cohort Study
Authors: Li Feng , Sun Jin-Yu , Wu Li-Da , Qu Qiang , Zhang Zhen-Ye , Chen Xu-Fei , Kan Jun-Yan , Wang Chao , Wang Ru-Xing
Published: December 2021

Background. There are few biomarkers with an excellent predictive value for postacute myocardial infarction (MI) patients who developed heart failure (HF). This study aimed to screen candidate biomarkers to predict post-MI HF. Methods. This is a secondary analysis of a single-center cohort study including nine post-MI HF patients and eight post-MI patients who remained HF-free over a 6-month follow-up. Transcriptional profiling was analyzed using the whole blood samples collected at admission, discharge, and 1-month follow-up. We screened differentially expressed genes and identified key modules using weighted gene coexpression network analysis. We confirmed the candidate biomarkers using the developed external datasets on post-MI HF. The receiver operating characteristic curves were created to evaluate the predictive value of these candidate biomarkers. Results. A total of 6,778, 1,136, and 1,974 genes (dataset 1) were differently expressed at admission, discharge, and 1-month follow-up, respectively. The white and royal blue modules were most significantly correlated with post-MI HF (dataset 2). After overlapping dataset 1, dataset 2, and external datasets (dataset 3), we identified five candidate biomarkers, including FCGR2A, GSDMB, MIR330, MED1, and SQSTM1. When GSDMB and SQSTM1 were combined, the area under the curve achieved 1.00, 0.85, and 0.89 in admission, discharge, and 1-month follow-up, respectively. Conclusions. This study demonstrates that FCGR2A, GSDMB, MIR330, MED1, and SQSTM1 are the candidate predictive biomarker genes for post-MI HF, and the combination of GSDMB and SQSTM1 has a high predictive value.
Nanosilver Dressing in Treating Deep II Degree Burn Wound Infection in Patients with Clinical Studies
Authors: Wu Bin’e , Zhang Fengchun , Jiang Wenbin , Zhao Aiyan
Published: December 2021

Background. Patients’ clinical antibiotic treatment of deep II degree burns usually fails to achieve the ideal effect; in order to avoid the late result in pigmentation, scarring, and even limb dysfunction, it also needs to deal effectively with burn wounds. Aim. The purpose of this study is to evaluate nanosilver dressing in treating deep II degree burn wound infection in patients with clinical studies. Materials and Methods. 106 burn patients were classified into the Sulfadiazine Silver Cream (SSC) group (

n
=
53

) and the Nanosilver Burn Dressing (NSBD) group (

n
=
53

). Both of them received basic wound treatment, and wound healing time and pigmentation fading away time of all patients were recorded. And the wound healing rate of the patients was calculated. Serum levels of tumor necrosis factor alpha (TNF-α) and interleukin-1beta (IL-1β) were detected pre- and posttreatment. Results. After basic treatment for all patients, Sulfadiazine Silver Cream was used in the SSC group, and Nanosilver Burn Dressing was used in the NSBD group. It was observed that after treatment, compared with the SSC group, there was significant efficiency; wound healing rate, healing time, and pigmentation fading away time were shortened in the NSBD group, and IL-1β levels were decreased, and the positive rate of bacterial culture was decreased (all

P
<
0.05

). Conclusion. Nanosilver Burn Dressing in treating deep II degree burns can effectively reduce the wound infection and promote wound healing. The curative effect was distinct, which was worthy of popularization and application.
Selenium and Taurine Combination Is Better Than Alone in Protecting Lipopolysaccharide‐Induced Mammary Inflammatory Lesions via Activating PI3K/Akt/mTOR Signaling Pathway by Scavenging Intracellular ROS
Authors: Liu Dandan , Lin Jiashan , He Wenmiao , Huang Kehe
Published: December 2021

Mastitis is mainly induced by gram‐negative bacterial infections, causing devastating economic losses to the global cattle industry. Both selenium (Se) and taurine (Tau) exhibit multiple biological effects, including reducing inflammation. However, no studies have reported the protective effect of the combined use of Se and Tau against mastitis, and the underlying mechanisms remain unclear. In this study, lipopolysaccharide (LPS), the vital virulence factor of gram‐negative bacteria, was used to construct the in vivo and vitro mastitis models. The results of in vivo model showed that Se and Tau combination was more effective than either substance alone in reducing tissue hyperemia, edema, and neutrophil infiltration in the mammary acinar cavity, improving the blood‐milk barrier in LPS‐induced mice mastitis, and decreasing the expression of proinflammatory factors and the activity of MPO. Moreover, Se and Tau combination significantly increased the levels of LPS‐induced reduction in PI3K/Akt/mTOR, but the expressions of TLRs and NLRP3 were not significantly changed in the mammary tissue. In the in vitro experiments, the effects of Se and Tau combination or alone on inflammatory factors, inflammatory mediators, MPO activity, and blood‐milk barrier were consistent with those in vivo. The Se and Tau combination has also been found to increase the survival rate of BMECs compared with each substance alone via promoting cellular proliferation and inhibiting apoptosis. Also, it has been confirmed that this combination could restore the LPS‐induced inhibition in the PI3K/Akt/mTOR signaling pathway. Inhibition of mTOR by Rapamycin counteracted the combined protection of SeMet and Tau against LPS‐induced inflammatory damage, the inhibition of PI3K by LY294002 blocked the activation of mTOR, and the accumulation of ROS by the ROS agonist blocked the activation of PI3K. In conclusion, these findings suggested that Se and Tau combination was better than either substance alone in protecting LPS‐induced mammary inflammatory lesions by upregulating the PI3K/Akt/mTOR signaling pathway.
Levenberg–Marquardt Backpropagation for Numerical Treatment of Micropolar Flow in a Porous Channel with Mass Injection
Authors: Ullah Hakeem , Khan Imran , AlSalman Hussain , Islam Saeed , Asif Zahoor Raja Muhammad , Shoaib Muhammad , Gumaei Abdu , Fiza Mehreen , Ullah Kashif , Mizanur Rahman Sk. Md. , Ayaz Muhammad
Published: December 2021

In this research work, an effective Levenberg–Marquardt algorithm‐based artificial neural network (LMA‐BANN) model is presented to find an accurate series solution for micropolar flow in a porous channel with mass injection (MPFPCMI). The LMA is one of the fastest backpropagation methods used for solving least‐squares of nonlinear problems. We create a dataset to train, test, and validate the LMA‐BANN model regarding the solution obtained by optimal homotopy asymptotic (OHA) method. The proposed model is evaluated by conducting experiments on a dataset acquired from the OHA method. The experimental results are obtained by using mean square error (MSE) and absolute error (AE) metric functions. The learning process of the adjustable parameters is conducted with efficacy of the LMA‐BANN model. The performance of the developed LMA‐BANN for the modelled problem is confirmed by achieving the best promise numerical results of performance in the range of E‐05 to E‐08 and also assessed by error histogram plot (EHP) and regression plot (RP) measures.
Attenuation of Autoimmune Phenomena in a Patient with Autoimmune Polyglandular Syndrome Type 1
Authors: Jacobson Jill D. , Broussard Julia R. , Marsh Courtney , Newell Brandon
Published: December 2021

Autoimmune polyglandular syndrome type 1 (APS1) is a progressive life-threatening illness with no known cure. Current treatments involve replacement of the hormone deficiencies that result from autoimmune destruction of multiple endocrine organs. We report on a girl whose disease was progressing rapidly until she began on immunosuppressive agents. A healthy 6-year-old girl with no remarkable medical history presented with new onset hypocalcemic seizures and primary hypoparathyroidism. Howell-Jolly bodies consistent with autoimmune hyposplenism were also noted. Genetic testing revealed compound heterozygosity for 2 disease-associated variants in the autoimmune regulator (AIRE) gene. She later developed elevated liver enzymes, primary adrenal insufficiency, and alopecia totalis. Serologic testing revealed antibodies to 21-hydroxylase, intrinsic factor, and smooth muscle. Hydrocortisone was initiated for adrenal insufficiency. Shortly afterwards, her liver enzymes normalized, and her smooth muscle antibody levels began to decline. Serologic testing performed at age 11 revealed seropositivity for glutamic acid decarboxylase (GAD) antibodies, antinuclear antibodies, and Sjögren syndrome A (SSA) antibodies. At age 12, she was given 2 doses of rituximab. Hair loss rapidly progressed to alopecia totalis and then to alopecia universalis, at which time oral methotrexate treatment was initiated. For the past 7 years while on glucocorticoid and methotrexate treatment, our patient has displayed normalization of 2 antibodies, a lack of progression to additional autoimmune diseases, and experienced reversal of alopecia universalis.
Numerical Solution of Heat Equation in Polar Cylindrical Coordinates by the Meshless Method of Lines
Authors: Hussain Arshad , Uddin Marjan , Haq Sirajul , Jan Hameed Ullah
Published: December 2021

We propose a numerical solution to the heat equation in polar cylindrical coordinates by using the meshless method of lines approach. The space variables are discretized by multiquadric radial basis function, and time integration is performed by using the Runge-Kutta method of order 4. In radial basis functions (RBFs), much of the research are devoted to the partial differential equations in rectangular coordinates. This work is an attempt to explore the versatility of RBFs in nonrectangular coordinates as well. The results show that application of RBFs is equally good in polar cylindrical coordinates. Comparison with other cited works confirms that the present approach is accurate as well as easy to implement to problems in higher dimensions.
Front-Line Therapy in EGFR Exon 19 Deletion and 21 Leu858Arg Mutations in Advanced Non-Small Cell Lung Cancer: A Network Meta-Analysis
Authors: Xie Tongji , Zou Zihua , Liu Chengcheng , Zhu Yixiang , Xu Ziyi , Wang Le , Li Junling , Xing Puyuan
Published: December 2021

Objective. This study aimed to compare the efficacy of different first-line strategies based on different EGFR mutation types (19 deletion and 21 Leu858Arg mutations). Methods. We conducted a systematic review and network meta-analysis (NMA) by searching and analyzing RCTs on PubMed, Embase, Cochrane Library, ASCO.org, and ESMO.org, from inception to September 30th, 2020. Results. Nineteen RCTs involving 5450 patients were finally included in this study, covering 10 different treatment strategies. The Bayesian ranking results suggested that, in terms of PFS, in the overall population and in patients with 19del mutation, osimertinib was most likely to rank the first, with the cumulative probabilities of 41.89% and 45.73%, respectively, while for patients with 21 Leu858Arg mutation, standard of care (SoC, represents first-generation EGFR-TKIs in this NMA) + chemotherapy was most likely to rank the first, with the cumulative probabilities of 30.81% in PFS. Moreover, SoC + chemotherapy provided the best overall survival benefit for the overall population and patients with 19del, with the cumulative probabilities of 57.85% and 33.51%, respectively. In contrast, for patients with 21 Leu858Arg mutation, dacomitinib showed the most favorable overall survival, with the cumulative probabilities of 36.73%. Conclusions. In this NMA, osimertinib and SoC combined with chemotherapy would be the optimal first-line treatment options for advanced NSCLC patients harboring EGFR 19 deletion mutation and 21 Leu858Arg mutation, respectively. This finding is likely to be adopted in clinical practice and provide guidance for future clinical study design. Systematic review registration: INPLASY2020100059.
The Association with Subclinical Thyroid Dysfunction and Uric Acid
Authors: Xing Yuling , Yang Linlin , Liu Jing , Ma Huijuan
Published: December 2021

The relationship between subclinical thyroid dysfunction and uric acid was not well established. This study aimed to determine if subclinical thyroid dysfunction is associated with hyperuricemia risk and to evaluate the levels of uric acid in patients with different forms of subclinical thyroid dysfunction. A systematic search was conducted in 4 databases to obtain relevant studies on subclinical thyroid dysfunction (subclinical hyperthyroidism and subclinical hypothyroidism) and uric acid. The standardized mean difference (SMD) or odds ratio (OR) and 95% confidence interval (95% CI) were used for evaluation, and the sensitivity analysis was conducted. Publication bias was estimated by funnel plot, Egger’s test, and Begg’s test. A total of 73 studies were included in this meta-analysis. The results demonstrated that serum levels of uric acid in patients with subclinical hypothyroidism were significantly higher than those of controls and patients with subclinical hyperthyroidism. Patients with subclinical thyroid dysfunction had a higher prevalence of hyperuricemia compared with normal clinical thyroid function. Subclinical thyroid dysfunction was associated with the prevalence of hyperuricemia. Different types of subclinical thyroid dysfunction had varied effects on serum levels of uric acid.
Phase Separation Mediates NUP98 Fusion Oncoprotein Leukemic Transformation
Authors: Chandra Bappaditya , Michmerhuizen Nicole L. , Shirnekhi Hazheen K. , Tripathi Swarnendu , Pioso Brittany J. , Baggett David W. , Mitrea Diana M. , Iacobucci Ilaria , White Michael R. , Chen Jingjing , Park Cheon-Gil , Wu Huiyun , Pounds Stanley , Medyukhina Anna , Khairy Khaled , Gao Qingsong , Qu Chunxu , Abdelhamed Sherif , Gorman Scott D. , Bawa Simranjot , Maslanka Carolyn , Kinger Swati , Dogra Priyanka , Ferrolino Mylene C. , Di Giacomo Danika , Mecucci Cristina , Klco Jeffery M. , Mullighan Charles G. , Kriwacki Richard W.
Published: December 2021

NUP98 fusion oncoproteins (FO) are drivers in pediatric leukemias and many transform hematopoietic cells. Most NUP98 FOs harbor an intrinsically disordered region from NUP98 that is prone to liquid–liquid phase separation (LLPS) in vitro. A predominant class of NUP98 FOs, including NUP98–HOXA9 (NHA9), retains a DNA-binding homeodomain, whereas others harbor other types of DNA- or chromatin-binding domains. NUP98 FOs have long been known to form puncta, but long-standing questions are how nuclear puncta form and how they drive leukemogenesis. Here we studied NHA9 condensates and show that homotypic interactions and different types of heterotypic interactions are required to form nuclear puncta, which are associated with aberrant transcriptional activity and transformation of hematopoietic stem and progenitor cells. We also show that three additional leukemia-associated NUP98 FOs (NUP98–PRRX1, NUP98–KDM5A, and NUP98–LNP1) form nuclear puncta and transform hematopoietic cells. These findings indicate that LLPS is critical for leukemogenesis by NUP98 FOs.

Significance:

We show that homotypic and heterotypic mechanisms of LLPS control NUP98–HOXA9 puncta formation, modulating transcriptional activity and transforming hematopoietic cells. Importantly, these mechanisms are generalizable to other NUP98 FOs that share similar domain structures. These findings address long-standing questions on how nuclear puncta form and their link to leukemogenesis.

This article is highlighted in the In This Issue feature, p. 873
High Glycemic Variability Is Associated with Worse Continuous Glucose Monitoring Metrics in Children and Adolescents with Type 1 Diabetes
Authors: Piona Claudia , Marigliano Marco , Mozzillo Enza , Di Candia Francesca , Zanfardino Angela , Iafusco Dario , Maltoni Giulio , Zucchini Stefano , Delvecchio Maurizio , Maffeis Claudio
Published: December 2021

Objective: The primary aim of this study was to quantify the prevalence of children and adolescents with type 1 diabetes (T1D) who achieve the recommended target for coefficient of variation (CV) identifying the determining factors to reach this target. The secondary aim was to examine the relationship between CV, the other metrics derived from continuous glucose monitoring (CGM) data and clinical parameters. Method: CGM data were collected from 805 children/adolescents with T1D. Several CGM metrics and patients’ characteristics were evaluated. Participants were stratified by CV ≤36% and CV >36%. Binary logistic regression analysis was run to identify the determining factors of high CV. Results: CV was positively correlated with %TBR <70 mg/dL, %TBR <54 mg/dL, %TAR >250 mg/dL, low blood glucose index, and high blood glucose index and negatively with %TIR. CV ≤36% was found in 31.4% of the subjects. The CV >36% group spent less time in %TIR, more time in hypoglycemia and hyperglycemia with lower proportion of subjects using real-time CGM and continuous subcutaneous insulin infusion. Percentage of TBR <70 mg/dL and TAR >250 mg/dL were significant predictors of CV >36%, whereas age, gender, BMI, duration of diabetes, type of CGM device, type of insulin therapy administration and %TIR were not significant predictors (p < 0.001, R2 Nagelkerke = 0.48). Conclusions: CV identifies children and adolescents with worse glycemic control at higher risk of both hypoglycemia and hyperglycemia.
The Algae Society BioArt Design Lab: Exploring Multispecies Entanglements and Making Kin with Algae
Authors: Harrower Juniper , Felice Gene , Parker Jennifer , Espinel José Carlos , Harris David , Hillary Fiona , Ribeaux Tiare
Published: December 2021

The Algae Society BioArt Design Lab is a global collective of interdisciplinary researchers working together with algae as nonhuman international research partners. As a collaborative group of artists, scientists, and scholars, they experiment and coproduce with algae, seeking to highlight complex human interdependence and kinship with algal beings. Here the founding members introduce the Algae Society and share a collective collage of their evolving artistic works while reflecting on each researcher’s process, materiality, and aesthetic considerations. With these works, they endeavor to shift our perspectives from human-centric exceptionalism to greater appreciation and cultural reframing of our responsibility as participants in multispecies worlding.
Just an artifact? The concordance between peer review and bibliometrics in economics and statistics in the Italian research assessment exercise
Authors: Baccini Alberto , De Nicolao Giuseppe
Published: December 2021

During the Italian research assessment exercise (2004–2010), the governmental agency (ANVUR) in charge of its realization performed an experiment on the concordance between peer review and bibliometrics at an individual article level. The computed concordances were at most weak for science, technology, engineering, and mathematics. The only exception was the moderate concordance found for the area of economics and statistics. In this paper, the disclosed raw data of the experiment are used to shed light on the anomalous results obtained for economics and statistics. In particular, the data permit us to document that the protocol of the experiment adopted for economics and statistics was different from the one used in the other areas. Indeed, in economics and statistics the same group of scholars developed the bibliometric ranking of journals for evaluating articles, managing peer reviews and forming the consensus groups for deciding the final scores of articles after having received the referee’s reports. This paper shows that the highest level of concordance in economics and statistics was an artifact mainly due to the role played by consensus groups in boosting the agreement between bibliometrics and peer review.
Researching women and men 1996–2020: Is androcentrism still dominant?
Authors: Thelwall Mike , Abdullah Abrizah , Fairclough Ruth
Published: December 2021

This article assesses the balance of research concerning women and men over the past quarter century using the crude heuristic of counting Scopus-indexed journal articles relating to women or men, as suggested by their titles or abstracts. A manual checking procedure together with a word-based heuristic was used to identify whether an article related to women or men. The heuristic includes both explicit mentions of women and men, implicit mentions, and a set of gender-focused health issues and medical terminology. Based on the results, more published articles now relate to women than to men. Moreover, more than twice as many articles relate exclusively to women than exclusively to men, with the ratio increasing from 2.16 to 1 in 1996 to 2.25 to 1 in 2020. Monogender articles mostly addressed primarily female health issues (maternity, breast cancer, cervical cancer) with fewer about primarily male health issues (testicular cancer, pancreatic cancer, health needs of men who have sex with men). Some articles also explicitly addressed gender inequality, such as empowering women entrepreneurs. The findings suggest that the androcentrism of early science has eroded in terms of research topics. This apparent progress should be encouraging for women researchers and society.
Quasi-Idealized Numerical Simulations of Processes Involved in Orogenic Convection Initiation over the Sierras de Córdoba
Authors: Singh Itinderjot , Nesbitt Stephen W. , Davis Christopher A.
Published: December 2021

The Sierras de Córdoba (SDC) range in Argentina is a hotspot of deep moist convection initiation (CI). Radar climatology indicates that 44% of daytime CI events that occur near the SDC in spring and summer seasons and that are not associated with the passage of a cold front or an outflow boundary involve a northerly low-level jet (LLJ), and these events tend to preferentially occur over the southeast quadrant of the main ridge of the SDC. To investigate the physical mechanisms acting to cause CI, idealized convection-permitting numerical simulations with a horizontal grid spacing of 1 km were conducted using Cloud Model 1 (CM1). The sounding used for initializing the model featured a strong northerly LLJ, with synoptic conditions resembling those in a previously postulated conceptual model of CI over the region, making it a canonical case study. Differential heating of the mountain caused by solar insolation in conjunction with the low-level northerly flow sets up a convergence line on the eastern slopes of the SDC. The southern portion of this line experiences significant reduction in convective inhibition, and CI occurs over the SDC southeast quadrant. The simulated storm soon acquires supercellular characteristics, as observed. Additional simulations with varying LLJ strength also show CI over the southeast quadrant. A simulation without background flow generated convergence over the ridgeline, with widespread CI across the entire ridgeline. A simulation with mid- and upper-tropospheric westerlies removed indicates that CI is minimally influenced by gravity waves. We conclude that the low-level jet is sufficient to focus convection initiation over the southeast quadrant of the ridge.