bluuebunny/crossref_metadata_2025_split huggingface dataset:
EVOLUTION OF NATURAL DISASTER TERMINOLOGIES,
WITH A CASE STUDY OF THE COVID-19 PANDEMIC
Authors: Caldera H. Jithamala , Wirasinghe S. C. 
Published: February 2022

Abstract
Emergency, disaster, catastrophe, calamity, and cataclysm are some of the terminologies that describe the nature and severity of adverse natural events. Civilians, reporters, and even professionals often use these terminologies for communication and reporting any event's severity as using this linguistic method is the most practical way during disasters to rapidly reach all levels of local, regional, national, and international stakeholder groups. Therefore, these disaster terminologies play a significant role in the disaster management field. However, attaining the actual magnitude of a disaster’s severity cannot be comprehended simply by using this linguistic method because these terminologies are used interchangeably. Unfortunately, there is no consistent method to differentiate disaster terminologies from one another. Additionally, no globally accepted standard technique to communicate the level of severity of disasters exists; one observer’s ‘disaster’ event can be another’s ‘catastrophic’ event depending on their personal experience and knowledge. Hence, a nations’ ability to manage extreme natural events is difficult when there are no agreed terminologies among emergency management systems. Thus, a standard severity classification system is required to understand, communicate, report, and educate stakeholders during ferocious natural events. This paper presents people's perceptions about disaster terminologies, rankings and differences in disaster lexicon (dictionary) meanings and lexical (verbal) meanings. It explores how people consider major events (e.g., the Covid-19 pandemic), and proposes a ranking of disaster terminologies to create a severity classification system suitable for use on a global level.
Performance of Artificial Intelligence for Biventricular Cardiovascular Magnetic Resonance Volumetric Analysis in the Clinical Setting
Authors: Hatipoglu Suzan , Mohiaddin Raad H , Gatehouse Peter , Alpendurada Francisco , Baksi A. John , Izgi Cemil , Prasad Sanjay K. , Pennell Dudley J , Krupickova MD Sylvia 
Published: February 2022

Abstract
Background
Cardiovascular magnetic resonance (CMR) derived ventricular volumes and function guide clinical decision-making for various cardiac pathologies. We aimed to evaluate the efficiency and clinical applicability of a commercially available artificial intelligence (AI) method for performing biventricular volumetric analysis.
Methods
Three-hundred CMR studies (100 with normal CMR findings, 50 dilated cardiomyopathy, 50 hypertrophic cardiomyopathy, 50 ischaemic heart disease and 50 congenital or valvular heart disease) were randomly selected from database. Manual biventricular volumetric analysis (CMRtools) results were derived from clinical reports and automated volumetric analyses were performed using short axis volumetry AI function of CircleCVI42v5.12 software. For 20 studies, a combined method of manually adjusted AI contours was tested and all three methods were timed. Clinicians` confidence in AI method was assessed using an online survey.
Results
Although agreement was better for left ventricle than right ventricle, AI analysis results were comparable to manual method. Manual adjustment of AI contours further improved agreement: within subject coefficient of variation decreased from 5.0–4.5% for left ventricular ejection fraction (EF) and from 9.9–7.1% for right ventricular EF. Twenty manual analyses were performed in 250min12s whereas same task took 5min48s using AI method. Clinicians were open to adopt AI but concerns about accuracy and validity were raised.
Conclusions
The AI method provides clinically valid outcomes and saves significant time. To address concerns raised by survey participants and overcome shortcomings of the automated myocardial segmentation, visual assessment of contours and performing manual corrections where necessary appears to be a practical approach.
Systematic Analysis of NB-ARC Gene Family in Rice and Functional Characterization of GNP12
Authors: Pan Ying-Hua , Chen Lei , Guo Hai-Feng , Lou Qi-Jin , Feng Rui , Rashid Muhammad Abdul Rehman , Zhu Xiao-Yang , Qing Dong-Jin , Liang Hai-Fu , Gao Li-Jun , Huang Cheng-Cui , Zhao Yan , Deng Guo-Fu 
Published: February 2022

Abstract
The NB-ARC (nucleotide-binding adaptor shared by APAF-1, R proteins, and CED-4) gene family plays a critical role in plant development. However, our understanding of NB-ARC genes regulation of plant development mechanisms in the plant panicle is still limited. Here, we subjected 258 NB-ARC genes in rice to genome-wide analysis to characterize their structure, function, and expression patterns. The NB-ARC genes were classified into three major groups, and group II included nine subgroups. Evolutionary analysis of NB-ARC genes in dicotyledon plant (Arabidopsis thaliana) and monocotyledonous plants (Oryza sativa L. and Triticum aestivum) indicate that orthologous genome segments were conserved in monocotyledons and subjected to weak positive selective pressure during evolution. Dispersed and proximal replication events were detected. Expression analysis showed expression of most NB-ARC genes in roots, panicles, and leaves, and regulation at the panicle development stage in rice Ce253. The GNP12 gene encodes RGH1A protein, which regulates rice yield according to panicle length, grain number of panicle, and grain length, with eight major haplotypes. Most NB-ARC protein family members are predicted to contain P-loop conserved domains and are located in the membrane. The results of this study provided insight into the characteristics and evolution of NB-ARC family and suggest that GNP12 positively regulates panicle development.
Vaginal Progesterone Gel Versus İntramuscular Progesterone For Luteal Support In Suboptimal Responders According To The Poseidon Criteria (Group 1b), Undergoing Antagonist IVF/ICSI-Cycles.
Authors: Ulubasoglu Hasan , Bakay Kadir , Yavuzcan Ali , Guven Davut , Hatırnaz Safak , Dahan Michael 
Published: February 2022

Abstract
Purpose:The aim of this study is to investigate the efficacy of intravaginal micronized progesterone gel 8% (VP8) versus intramuscular progesterone in oil (IM P4) for luteal phase support after IVF/ICSI -embryo transfer cycles in POSEIDON suboptimal responder patients.Methods:We evaluated the data of 189 suboptimal responders who underwent antagonist IVF/ICSI treatments. This retrospective study was conducted on patients who were treated by a university IVF center between January 2010 and December 2015. We evaluated the data of 189 suboptimal responders who underwent antagonist IVF/ICSI treatments.The cycles were categorized into two groups based on the type of luteal support: P4 vaginal gel and P4 IM. Clinical pregnancy, ongoing pregnancy, live birth and spontaneous abortion rates were analyzed. Results: Patient and treatment characteristics were similar in both groups. However, In terms of infertile duration, significant differences were observed between groups (P<0.05). There were no significant differences in stimulation characteristics including; total gonadotropin doses, peak serum estradiol levels on the day of triggering, number of oocytes collected and number of fertilized oocyte. Multivariate logistic regression modeling failed to find the type of progesterone used as a predictor of live birth (OR 0.802, 95% CI 661-1.202, p=0.580). Conclusion:We believed in POSEIDOIN group IB patients similar pregnancy outcomes can be obtained by administering 180 mg P4 gel vaginally when compared to IM P4.
Transcriptional signature of TP53 biallelic inactivation identifies a group of multiple myeloma patients without this genetic condition but with dismal outcome.
Authors: Gutiérrez Norma C. , De Ramón Cristina , Rojas Elizabeta A. , Cardona-Benavides Igancio J. , Mateos Maria Victoria , Corchete Luis A. 
Published: February 2022

Abstract
Background: Biallelic inactivation of TP53 has been included in the definition of double-hit (DH) multiple myeloma (MM), which entails an ominous prognosis even when treated with the most innovative drugs. However, this condition, or even the presence of high-risk cytogenetic abnormalities, cannot accurately capture the 15-20% of the MM population with a median overall survival below 24 months. This prompted us to look for other MM patients who might have transcriptional characteristics similar to those with DH-TP53.Methods: We analyzed RNA-seq, whole-genome and whole-exome sequencing data from 660 newly diagnosed MM (NDMM) patients from the MMRF (Multiple Myeloma Research Foundation) CoMMpass study to characterize the transcriptional signature of DH-TP53 MM. This gene signature was used to build a score based on a Spearman correlation coefficient and a scaled GINI index. Two other gene expression series from GEO (GSE4581 and GSE136400) comprising a total of 850 patients were used as validation cohorts.Results: We found 78 genes that were exclusively deregulated in DH-TP53 patients. A score based on these genes identified a group of 50 patients who shared the same transcriptional profile (DH-TP53-like group) whose prognosis was particularly unfavorable (median overall survival [OS] < 2 years), despite not harboring the biallelic inactivation of TP53. Patients included in the DH-TP53-like group had significantly shorter OS and progression-free survival (PFS) than those without the DH-TP53 gene expression profile (hazard ratio [HR] 4.07 [95% CI, 2.76-5.98], adjusted p < 0.001, and HR 3.44 [95% CI, 2.46-4.81], adjusted p < 0.001, respectively). The prognostic value of the DH-TP53 score was externally validated using gene expression data obtained by microarray analysis. Furthermore, our DH-TP53 score refined the traditional prognostic stratification of MM patients according to the cytogenetic abnormalities and International Staging System (ISS). Conclusions: The expression signature of DH-TP53 MM was shared by other MM patients without TP53 biallelic inactivation (DH-TP53-like group). The DH-TP53 score could be a useful tool for identifying ultra-high-risk MM patients without concomitant del(17p) and TP53 mutations.
TIGIT is a novel prognostic marker and correlate for immune infiltration in invasive breast cancer
Authors: Guo Chenming , Luo Zhiwen , Ismtula Dilimulati , Bi Xiaojuan , Kong Han , Wang Yiyang , Yang Zhen , Mao Xinmin 
Published: February 2022

Abstract
Background To assess the levels and potential therapeutic and prognostic significance of TIGIT in invasive breast cancer. Methods The Cancer Genome Atlas database was used to evaluate TIGIT levels in invasive breast cancer and its association with clinicopathological features. Immunohistochemistry (IHC) was performed to validate it. Further, the Kaplan-Meier survival curve, univariate and multivariate Cox regression models were applied in analyzing the role of TIGIT in prognosis of invasive breast cancer. Go / KEGG enrichment analyses techniques were used to investigate the possible cellular mechanism, and string database was used to explore TIGIT related proteins. Finally, the TIMER database was used to determine the association between TIGIT and immune cell infiltrations. Results TIGIT was differentially expressed in Pan cancer tissues compared with normal tissues. Relative to normal tissues, TIGIT levels in invasive breast cancer were elevated (p<0.05). TIGIT mRNA level was significantly different from T stage, age, ER and PR level (p<0.05). The high levels of TIGIT exhibited positive correlations with PFI and OS (p<0.05). Univariate analysis revealed that age, clinical stage, high TNM stage, menopausal status and radiotherapy were the factors affecting OS (p< 0.05). Multivariate analysis revealed that age, high clinical stage and menopausal status were independent risk factors for tumor progression (p<0.05). CD226, INPP5D, PVR, PVRL2 and PVRL3 proteins interact with TIGIT. The TIGIT levels were significantly correlated with infiltrations of immune cells (such as CD8+T cells) (r=0.917, p<0.05). Conclusion TIGIT is elevated in invasive breast tumor and is closely associated with the prognosis of invasive breast cancer. TIGIT may be the target of immunotherapy for invasive breast cancer.
Maintenance strategy selection: A multi-criteria group decision-making method based on cloud DEMATEL-ANP
Authors: Li Xinlong , Ran Yan , Zhang Genbao , He Yan 
Published: February 2022

Abstract
The selection of maintenance strategy is a very important work in maintenance engineering. Taking the meta-action unit(MU) as the research carrier, considering the randomness and fuzziness of expert evaluation and the interaction between evaluation criteria in the selection process of maintenance strategy, this paper proposes a maintenance strategy selection method based on cloud DEMATEL-ANP. Firstly, the cloud-DEMATEL model is used to establish the interaction model between the main criteria, determine the weighted cloud weight of the super matrix and the inner dependencies of the sub-criteria under the same main criteria. Then, the cloud-ANP model is used to determine the outer dependencies relationship and construct the cloud super matrix, so as to obtain the cloud weight of each evaluation criteria in maintenance strategy selection. By using the subjective and objective weighting method, the evaluation of different experts on different maintenance strategy criteria is integrated, and the priority of alternative maintenance strategies of MU is obtained. Finally, different methods are used to sort and compare the alternative maintenance strategies of the rotating body rotation MU of the CNC machine tool turntable, which verifies the scientificity and effectiveness of the method proposed in this paper are verified.
Deep Learning Estimation of the Industrial Wood Production Rate Depending on the Harm Factors
Authors: Sevinç Volkan 
Published: February 2022

Abstract
Protection and sustainability of forest assets are possible with planned use of the forest products. Among these products, industrial wood is the most important raw material for various sectors. Thus, industrial wood production rate estimation is important to use this product optimally and without disturbing the balance of forest assets. This article aims to estimate the industrial wood production rate based on four natural harm factors, which are forest fires, outbreaks of insects, outbreaks of diseases, and severe weather events. The estimation model was built by using a deep learning method, which is an artificial neural network model based on the multilayer perceptron architecture. The study shows that the most harmful factor decreasing the industrial wood production rate is outbreaks of diseases. The second effective factor, however, appears to be severe weather events. The third and the fourth factors were determined to be outbreaks of insects and burned forest areas respectively.
Temperate phage-antibiotic synergy across antibiotic classes reveals new mechanism for preventing lysogeny
Authors: Al-Anany Amany , Hynes Alexander 
Published: February 2022

Abstract

A recent demonstration of potent synergy between a temperate phage and the antibiotic ciprofloxacin suggested a scalable approach to exploiting temperate phages in therapy, termed temperate phage-antibiotic synergy (tPAS), which specifically interacted with the lysis-lysogeny decision. To determine whether this would hold true more broadly across antibiotics, we challenged Escherichia coli K12 with the well-studied model λ-like phage HK97 and a set of 13 antibiotics spanning seven classes. As expected, given the conserved induction pathway targeted, we observed synergy with classes of drugs known to induce an SOS response; a sulfa drug, other quinolones, Mitomycin C, and some β-lactams. Curiously, we observed an equally potent synergy with antibiotics not known to induce the SOS response: protein synthesis inhibitors gentamicin, kanamycin, tetracycline, and azithromycin. The synergy results in an 8-fold reduction in the effective MIC of gentamicin, complete eradication of the bacteria, and, when deliberately administered at sub-optimal doses, drastically decreases the frequency of lysogens emerging from the combined challenge – more so even than was previously described for ciprofloxacin. However, unlike ciprofloxacin, lysogens exhibit no increased sensitivity to the antibiotic, synergy was maintained in the absence of RecA, and, when quantified over time, the antibiotic reduced the initial frequency of lysogeny rather than result in selection against formed lysogens. Not only do our results confirm that SOS-inducing antibiotics broadly result in temperate-phage specific synergy, but we other antibiotics can interact with temperate phages specifically and result in potent synergy. This is the first report of a means of chemically blocking entry into lysogeny, providing a new means for manipulating the key lysis-lysogeny decision point in temperate phages.
Obtaining a relativistic dispersion formula and practice of its application.
Authors: Chernov Andrey 
Published: February 2022

Abstract
This study was based on the hypothesis that the speed of propagation of photons inside a transparent substance depends on the density of electron clouds of atoms of this substance. In the process of research, based on the relativistic formula of Einstein, a new dispersion formula was obtained, which can be applied to the widest range of transparent substances. The new physical formula was used to calculate 26 refractive indices of light in 5 transparent substances in three states of aggregation. Comparison of the obtained indicators with laboratory indicators showed the high accuracy of the new dispersion formula, which amounted to ±10 -7−10 -5 in the calculated wavelength ranges of more than 100 nm. The successful application of the relativistic formula to the processes occurring inside matter at the atomic level allows us to look at the nature of the interaction of light and matter from a new angle.
Excess All-Cause Mortality and COVID-19 Reported Fatality in Iran (April 2013 - September 2021): Age and Sex Disaggregated Time Series Analysis
Authors: Safavi-Naini Seyed Amir Ahmad , Farsi Yeganeh , Alali Walid Q , Solhpour Ali , Pourhoseingholi Mohamad Amin 
Published: February 2022

Abstract
Objective: The actual impact of the pandemic on COVID-19 specific mortality is still unclear due to the variability in access to diagnostic tools. This study aimed to estimate the excess all-cause mortality in Iran until September 2021 based on the national death statistics.Results: The autoregressive integrated moving average used to predict seasonal all-cause death in Iran (R-squared=0.45). We observed a 38.8% (95% confidence interval (CI): 29.7%-40.1%) rise in the all-cause mortality from 22 June 2020 to 21 June 2021. The excess all-cause mortality per 100,000 population were 178.86 (95% CI: 137.2 - 220.5, M:F ratio = 1.3) with 49.1% of these excess deaths due to COVID-19. Comparison of spring 2019 and spring 2021 revealed that the highest percent increase in mortality was among men, aged 65-69 years old (77%) and women, aged 60-64 years old (86.8%). Moreover, the excess mortality among 31 provinces of Iran ranged from 109.7 (Hormozgan) to 273.2 (East-Azerbaijan) per 100,000 population. In conclusion, there was a significant rise in all-cause mortality during the pandemic. Since COVID-19 fatality explains about half of this rise, the rise in other causes of death and underestimation in reported data should be concerned by further studies.
Neonatal Arterial Ischaemic Stroke: Advances in Pathologic Neural Death,
Diagnosis, Treatment, and Prognosis
Authors: Tang Jun , Mu Dezhi , He Yang , Ying Junjie , Zhou Ruixi , Qu Haibo , Qu Yi 
Published: February 2022

Abstract:
Neonatal arterial ischaemic stroke (NAIS) is caused by focal arterial occlusion and often
leads to severe neurological sequelae. Neural deaths after NAIS mainly include necrosis, apoptosis,
necroptosis, autophagy, ferroptosis, and pyroptosis. These neural deaths are mainly caused by upstream
stimulations, including excitotoxicity, oxidative stress, inflammation, and death receptor
pathways. The current clinical approaches to managing NAIS mainly focus on supportive treatments,
including seizure control and anticoagulation. In recent years, research on the pathology, early
diagnosis, and potential therapeutic targets of NAIS has progressed. In this review, we summarise
the latest progress of research on the pathology, diagnosis, treatment, and prognosis of NAIS and
highlight newly potential diagnostic and treatment approaches.
Comparison of Aptamer-Based and Antibody-Based Assays for Protein Quantification in Chronic Kidney Disease
Authors: Lopez-Silva Carolina , Surapaneni Aditya , Coresh Josef , Reiser Jochen , Parikh Chirag R. , Obeid Wassim , Grams Morgan E. , Chen Teresa K. 
Published: February 2022

Background and objectives
Novel aptamer-based technologies can identify >7000 analytes per sample, offering a high-throughput alternative to traditional immunoassays in biomarker discovery. However, the specificity for distinct proteins has not been thoroughly studied in the context of CKD.

Design, setting, participants, & measurements
We assessed the use of SOMAscan, an aptamer-based technology, for the quantification of eight immune activation biomarkers and cystatin C among 498 African American Study of Kidney Disease and Hypertension (AASK) participants using immunoassays as the gold standard. We evaluated correlations of serum proteins as measured by SOMAscan versus immunoassays with each other and with iothalamate-measured GFR. We then compared associations between proteins measurement with risks of incident kidney failure and all-cause mortality.

Results
Six biomarkers (IL-8, soluble TNF receptor superfamily member 1B [TNFRSF1B], cystatin C, soluble TNF receptor superfamily member 1A [TNFRSF1A], IL-6, and soluble urokinase-type plasminogen activator receptor [suPAR]) had non-negligible correlations (r=0.94, 0.93, 0.89, 0.85, 0.46, and 0.23, respectively) between SOMAscan and immunoassay measurements, and three (IL-10, IFN-γ, and TNF-α) were uncorrelated (r=0.08, 0.07, and 0.02, respectively). Of the six biomarkers with non-negligible correlations, TNFRSF1B, cystatin C, TNFRSF1A, and suPAR were negatively correlated with measured GFR and associated with higher risk of kidney failure. IL-8, TNFRSF1B, cystatin C, TNFRSF1A, and suPAR were associated with a higher risk of mortality via both methods. On average, immunoassay measurements were more strongly associated with adverse outcomes than their SOMAscan counterparts.

Conclusions
SOMAscan is an efficient and relatively reliable technique for quantifying IL-8, TNFRSF1B, cystatin C, and TNFRSF1A in CKD and detecting their potential associations with clinical outcomes.

Podcast
This article contains a podcast at https://www.asn-online.org/media/podcast/CJASN/2022_02_23_CJN11700921.mp3
Trinta anos de séries de desenhos animados francesas feitas com ajuda dos japoneses (1970-1990)
Authors: Públio Marcelo Abilio 
Published: February 2022

A França só conseguiu alavancar suas produções de séries de desenhos animados televisivos entre os anos 70 e 90. Diversos foram os fatores envolvidos, entre eles, a expertise japonesa. Mas essa virada não aconteceu sem interesse político. Esse artigo apresenta assim esse emaranhado de fatores e a importância das parcerias franco-japonesas para alavancar a França como a terceira maior produtora mundial de séries de desenhos animados no mundo. Para tanto, é preciso conhecer as primeiras produções de séries de desenhos animados dessa época como por exemplo: Oum le dauphin blanc, Era uma vez… O Homem, Era uma vez… O Espaço, Ulysse 31, Les mystérieuses cités d’Or. Assim, este estudo tem a intenção de conhecer os bastidores da realização dessas séries pioneiras para conhecer como as parcerias franco-japonesas ajudaram no desenvolvimento da animação francesa.