bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cloning and characterization of KoOsmotin from mangrove plant Kandelia obovata under cold stress
Authors: Fei Jiao , Wang You-shao , Cheng Hao , Su Yu-bin , Zhong Yongjia , Zheng Lei 
Published: January 2021

Abstract
Background
Low temperature is a major abiotic stress that seriously limits mangrove productivity and distribution. Kandelia obovata is the most cold-resistance specie in mangrove plants, but little is known about the molecular mechanism underlying its resistance to cold. Osmotin is a key protein associated with abiotic and biotic stress response in plants but no information about this gene in K. obovata was reported.

Results
In this study, a cDNA sequence encoding osmotin, KoOsmotin (GenBank accession no. KP267758), was cloned from mangrove plant K. obovata. The KoOsmotin protein was composed of 221 amino acids and showed a calculated molecular mass of 24.11 kDa with pI 4.92. The KoOsmotin contained sixteen cysteine residues and an N-terminal signal peptide, which were common signatures to most osmotins and pathogenesis-related 5 proteins. The three-dimensional (3D) model of KoOsmotin, contained one α-helix and eleven β-strands, was formed by three characteristic domains. Database comparisons of the KoOsmotin showed the closest identity (55.75%) with the osmotin 34 from Theobroma cacao. The phylogenetic tree also revealed that the KoOsmotin was clustered in the branch of osmotin/OLP (osmotin-like protien). The KoOsmotin protein was proved to be localized to both the plasma membrane and cytoplasm by the subcellular localization analysis. Gene expression showed that the KoOsmotin was induced primarily and highly in the leaves of K. obovata, but less abundantly in stems and roots. The overexpressing of KoOsmotin conferred cold tolerance in Escherichia coli cells.

Conclusion
As we known, this is the first study to explore the osmotin of K. obovata. Our study provided valuable clues for further exploring the function of KoOsmotin response to stress.
The role of JrPPOs in the browning of walnut explants
Authors: Zhao Shugang , Wang Hongxia , Liu Kai , Li Linqing , Yang Jinbing , An Xiuhong , Li Pingping , Yun Linying , Zhang Zhihua 
Published: January 2021

Abstract
Background
Tissue culture is an effective method for the rapid breeding of seedlings and improving production efficiency, but explant browning is a key limiting factor of walnut tissue culture. Specifically, the polymerization of PPO-derived quinones that cause explant browning of walnut is not well understood. This study investigated explants of ‘Zanmei’ walnut shoot apices cultured in agar (A) or vermiculite (V) media, and the survival percentage, changes in phenolic content, POD and PPO activity, and JrPPO expression in explants were studied to determine the role of PPO in the browning of walnut explants.

Results
The results showed that the V media greatly reduced the death rate of explants, and 89.9 and 38.7% of the explants cultured in V media and A media survived, respectively. Compared with that of explants at 0 h, the PPO of explants cultured in A was highly active throughout the culture, but activity in those cultured in V remained low. The phenolic level of explants cultured in A increased significantly at 72 h but subsequently declined, and the content in the explants cultured in V increased to a high level only at 144 h. The POD in explants cultured in V showed high activity that did not cause browning. Gene expression assays showed that the expression of JrPPO1 was downregulated in explants cultured in both A and V. However, the expression of JrPPO2 was upregulated in explants cultured in A throughout the culture and upregulated in V at 144 h. JrPPO expression analyses in different tissues showed that JrPPO1 was highly expressed in stems, young leaves, mature leaves, catkins, pistils, and hulls, and JrPPO2 was highly expressed in mature leaves and pistils. Moreover, browning assays showed that both explants in A and leaf tissue exhibited high JrPPO2 activity.

Conclusion
The rapid increase in phenolic content caused the browning and death of explants. V media delayed the rapid accumulation of phenolic compounds in walnut explants in the short term, which significantly decreased explants mortality. The results suggest that JrPPO2 plays a key role in the oxidation of phenols in explants after branch injury.
Genomic survey sequencing, development and characterization of single- and multi-locus genomic SSR markers of Elymus sibiricus L
Authors: Xiong Yi , Lei Xiong , Bai Shiqie , Xiong Yanli , Liu Wenhui , Wu Wendan , Yu Qingqing , Dong Zhixiao , Yang Jian , Ma Xiao 
Published: January 2021

Abstract
Background
Siberian wildrye (Elymus sibiricus L.) attracts considerable interest for grassland establishment and pasture recovery in the Qinghai-Tibet Plateau (QTP) due to its excellence in strong stress tolerance, high nutritional value and ease to cultivate. However, the lack of genomic information of E. sibiricus hampers its genetics study and breeding process.

Results
In this study, we performed a genome survey and developed a set of SSR markers for E. sibiricus based on Next-generation sequencing (NGS). We generated 469.17 Gb clean sequence which is 58.64× of the 6.86 Gb estimated genome size. We assembled a draft genome of 4.34 Gb which has 73.23% repetitive elements, a heterozygosity ratio of 0.01% and GC content of 45.68%. Based on the gnomic sequences we identified 67,833 SSR loci and from which four hundred were randomly selected to develop markers. Finally, 30 markers exhibited polymorphism between accessions and ten were identified as single-locus SSR. These newly developed markers along with previously reported 30 ones were applied to analyze genetic polymorphism among 27 wild E. sibiricus accessions. We found that single-locus SSRs are superior to multi-loci SSRs in effectiveness.

Conclusions
This study provided insights into further whole genome sequencing of E. sibiricus in strategy selection. The novel developed SSR markers will facilitate genetics study and breeding for Elymus species.
Genome-wide association study reveals a patatin-like lipase relating to the reduction of seed oil content in Brassica napus
Authors: Wang Haoyi , Wang Qian , Pak Haksong , Yan Tao , Chen Mingxun , Chen Xiaoyang , Wu Dezhi , Jiang Lixi 
Published: January 2021

AbstractBackgroundRapeseed (Brassica napusL.) is an important oil crop world-widely cultivated, and seed oil content (SOC) is one of the most important traits for rapeseed. To increase SOC, many efforts for promoting the function of genes on lipid biosynthesis pathway have been previously made. However, seed oil formation is a dynamic balance between lipid synthesis and breakdown. It is, therefore, also reasonable to weaken or eliminate the function of genes involved in lipid degradation for a higher final SOC.ResultsWe applied a genome-wide association study (GWAS) on SOC in a collection of 290 core germplasm accessions. A total of 2,705,480 high-quality SNPs were used in the GWAS, and we identifiedBnaC07g30920D, apatatin-like lipase(PTL) gene, that was associated with SOC. In particular, six single-nucleotide-polymorphisms (SNPs) in the promoter region ofBnaC07g30920Dwere associated with the significant reduction of SOC, leading to a 4.7–6.2% reduction of SOCs. We performed in silico analysis to show a total of 40PTLs, which were divided into four clades, evenly distributed on the A and C subgenomes ofBrassica napus. RNA-seq analysis unveiled thatBnPTLswere preferentially expressed in reproductive tissues especially maturing seeds.ConclusionsWe identifiedBnaC07g30920D, aBnPTLgene, that was associated with SOC using GWAS and performed in silico analysis of 40PTLsinBrassica napus. The results enrich our knowledge about the SOC formation in rapeseed and facilitate the future study in functional characterization ofBnPTLgenes.
Improved selection of participants in genetic longevity studies: family scores revisited
Authors: Rodríguez-Girondo Mar , van den Berg Niels , Hof Michel H. , Beekman Marian , Slagboom Eline 
Published: January 2021

Abstract
Background
Although human longevity tends to cluster within families, genetic studies on longevity have had limited success in identifying longevity loci. One of the main causes of this limited success is the selection of participants. Studies generally include sporadically long-lived individuals, i.e. individuals with the longevity phenotype but without a genetic predisposition for longevity. The inclusion of these individuals causes phenotype heterogeneity which results in power reduction and bias. A way to avoid sporadically long-lived individuals and reduce sample heterogeneity is to include family history of longevity as selection criterion using a longevity family score. A main challenge when developing family scores are the large differences in family size, because of real differences in sibship sizes or because of missing data.

Methods
We discussed the statistical properties of two existing longevity family scores: the Family Longevity Selection Score (FLoSS) and the Longevity Relatives Count (LRC) score and we evaluated their performance dealing with differential family size. We proposed a new longevity family score, the mLRC score, an extension of the LRC based on random effects modeling, which is robust for family size and missing values. The performance of the new mLRC as selection tool was evaluated in an intensive simulation study and illustrated in a large real dataset, the Historical Sample of the Netherlands (HSN).

Results
Empirical scores such as the FLOSS and LRC cannot properly deal with differential family size and missing data. Our simulation study showed that mLRC is not affected by family size and provides more accurate selections of long-lived families. The analysis of 1105 sibships of the Historical Sample of the Netherlands showed that the selection of long-lived individuals based on the mLRC score predicts excess survival in the validation set better than the selection based on the LRC score .

Conclusions
Model-based score systems such as the mLRC score help to reduce heterogeneity in the selection of long-lived families. The power of future studies into the genetics of longevity can likely be improved and their bias reduced, by selecting long-lived cases using the mLRC.
Development and validation of prediction model to estimate 10-year risk of all-cause mortality using modern statistical learning methods: a large population-based cohort study and external validation
Authors: Ajnakina Olesya , Agbedjro Deborah , McCammon Ryan , Faul Jessica , Murray Robin M. , Stahl Daniel , Steptoe Andrew 
Published: January 2021

Abstract
Background
In increasingly ageing populations, there is an emergent need to develop a robust prediction model for estimating an individual absolute risk for all-cause mortality, so that relevant assessments and interventions can be targeted appropriately. The objective of the study was to derive, evaluate and validate (internally and externally) a risk prediction model allowing rapid estimations of an absolute risk of all-cause mortality in the following 10 years.

Methods
For the model development, data came from English Longitudinal Study of Ageing study, which comprised 9154 population-representative individuals aged 50–75 years, 1240 (13.5%) of whom died during the 10-year follow-up. Internal validation was carried out using Harrell’s optimism-correction procedure; external validation was carried out using Health and Retirement Study (HRS), which is a nationally representative longitudinal survey of adults aged ≥50 years residing in the United States. Cox proportional hazards model with regularisation by the least absolute shrinkage and selection operator, where optimisation parameters were chosen based on repeated cross-validation, was employed for variable selection and model fitting. Measures of calibration, discrimination, sensitivity and specificity were determined in the development and validation cohorts.

Results
The model selected 13 prognostic factors of all-cause mortality encompassing information on demographic characteristics, health comorbidity, lifestyle and cognitive functioning. The internally validated model had good discriminatory ability (c-index=0.74), specificity (72.5%) and sensitivity (73.0%). Following external validation, the model’s prediction accuracy remained within a clinically acceptable range (c-index=0.69, calibration slope β=0.80, specificity=71.5% and sensitivity=70.6%). The main limitation of our model is twofold: 1) it may not be applicable to nursing home and other institutional populations, and 2) it was developed and validated in the cohorts with predominately white ethnicity.

Conclusions
A new prediction model that quantifies absolute risk of all-cause mortality in the following 10-years in the general population has been developed and externally validated. It has good prediction accuracy and is based on variables that are available in a variety of care and research settings. This model can facilitate identification of high risk for all-cause mortality older adults for further assessment or interventions.
Factors associated with caregiving self-efficacy among primary informal caregivers of persons with dementia in Singapore
Authors: Tan Gregory Tee Hng , Yuan Qi , Devi Fiona , Wang Peizhi , Ng Li Ling , Goveas Richard , Chong Siow Ann , Subramaniam Mythily 
Published: January 2021

Abstract
Background
Informal caregivers of persons with dementia (PWD) are often associated with negative health outcomes. Self-efficacy in dementia caregiving has been reported to have protective effects on caregiver’s health. This study aims to examine the factors associated with the domains of caregiving self-efficacy among informal caregivers in Singapore, a country with a rapidly aging population and a 10% prevalence of dementia among older adults.

Methods
Two hundred eighty-two informal caregivers were recruited and data including participant’s caregiving self-efficacy, sociodemographic information, perceived social support, positive aspects of caregiving, knowledge of dementia, as well as behavioral and memory problems of care recipients were collected. A confirmatory factor analysis (CFA) was performed for the 3-factor model of the Revised Scale for Caregiving Self-Efficacy (RSCSE), and multiple linear regressions were conducted using the RSCSE subscales as dependent variables.

Results
Our CFA found that the RSCSE 3-factor model proposed by the original scale developer was an acceptable fit among informal caregivers in Singapore. Having established that the 3-factor model of the RSCSE was compatible among our sample, a series of multiple regressions were conducted using each of the factors as a dependent variable. Regressions revealed several factors that were significantly associated with caregiving self-efficacy. Importantly, outlook on life was positively associated to all 3 domains of the RSCSE, while social support was positively associated with self-efficacy in obtaining respite and controlling upsetting thoughts.

Conclusion
The 3-factor model of the RSCSE was found to be an appropriate fit for our sample. Findings from this study elucidated important novel insights into the factors that influences caregiving self-efficacy amongst informal caregivers in Singapore. Crucially, caregivers’ outlook on life and social support should be improved in order to enhance their caregiving self-efficacy.
Campylobacter-associated hospitalisations in an Australian provincial setting
Authors: Moffatt Cameron R. M. , Kennedy Karina J. , Selvey Linda , Kirk Martyn D. 
Published: January 2021

Abstract
Background
Campylobacter spp. infections are a globally important cause of enterocolitis, causing substantial morbidity. Capturing accurate information on hospitalisations is challenging and limited population-level data exist to describe the clinico-epidemiological characteristics of hospitalised cases.

Methods
Hospital administrative and laboratory datasets were linked to identify Campylobacter-associated hospitalisations between 2004 and 2013. Accuracy of morbidity coding was assessed using laboratory diagnosis as a gold standard, with health department surveillance data used to calculate population-based rates. Additional patient-level data were collected via review of medical records. Descriptive statistics were used to assess changes in rates and proportions and to assess relationships between key variables including age, length of stay, comorbidity and complications.

Results
In total 685 Campylobacter-associated hospital admissions were identified, with the sensitivity of morbidity coding 52.8% (95% CI 48.9–56.7%). The mean annual rate of hospitalisation was 13.6%. Hospitalisation rates were higher for females across most age-groups, while for both genders marked increases were observed for those aged ≥60 years. Median admission age was 39.5 years, with an average length of stay of 3.5 days. Comorbidities were present in 34.5% (237/685) of admissions, with these patients more likely to develop electrolyte disturbances, hypotension, renal impairment or acute confusion (all p < 0.001). Bacteraemia and acute kidney injury were observed in 4.1% (28/685) and 3.6% (23/685) of admissions, respectively. Inpatient mortality was low (0.15%).

Conclusion
Under reporting of Campylobacter-associated hospitalisations is substantial but can be improved through data linkage. We observed demographic differences among those hospitalised but further work is needed to determine risk factors and predictors for hospitalisation.
High prevalence of multidrug resistant ESBL- and plasmid mediated AmpC-producing clinical isolates of Escherichia coli at Maputo Central Hospital, Mozambique
Authors: Estaleva Calvina E. L. , Zimba Tomas F. , Sekyere John Osei , Govinden Usha , Chenia Hafizah Y. , Simonsen Gunnar S. , Haldorsen Bjørg , Essack Sabiha Y. , Sundsfjord Arnfinn 
Published: January 2021

Abstract
Background
Epidemiological data of cephalosporin-resistant Enterobacterales in Sub-Saharan Africa is still restricted, and in particular in Mozambique. The aim of this study was to detect and characterize extended-spectrum β-lactamase (ESBL) - and plasmid-mediated AmpC (pAmpC)-producing clinical strains of Escherichia coli at Maputo Central Hospital (MCH), a 1000-bed reference hospital in Maputo, Mozambique.

Methods
A total of 230 clinical isolates of E. coli from urine (n = 199) and blood cultures (n = 31) were collected at MCH during August–November 2015. Antimicrobial susceptibility testing was performed by the disc diffusion method and interpreted according to EUCAST guidelines. Isolates with reduced susceptibility to 3rd generation cephalosporins were examined further; phenotypically for an ESBL−/AmpC-phenotype by combined disc methods and genetically for ESBL- and pAmpC-encoding genes by PCR and partial amplicon sequencing as well as genetic relatedness by ERIC-PCR.

Results
A total of 75 isolates with reduced susceptibility to cefotaxime and/or ceftazidime (n = 75) from urine (n = 58/199; 29%) and blood (n = 17/31; 55%) were detected. All 75 isolates were phenotypically ESBL-positive and 25/75 (33%) of those also expressed an AmpC-phenotype. ESBL-PCR and amplicon sequencing revealed a majority of blaCTX-M (n = 58/75; 77%) dominated by blaCTX-M-15. All AmpC-phenotype positive isolates (n = 25/75; 33%) scored positive for one or more pAmpC-genes dominated by blaMOX/FOX. Multidrug resistance (resistance ≥ three antibiotic classes) was observed in all the 75 ESBL-positive isolates dominated by resistance to trimethoprim-sulfamethoxazole, ciprofloxacin and gentamicin. ERIC-PCR revealed genetic diversity among strains with minor clusters indicating intra-hospital spread.

Conclusion
We have observed a high prevalence of MDR pAmpC- and/or ESBL-producing clinical E. coli isolates with FOX/MOX and CTX-Ms as the major β-lactamase types, respectively. ERIC-PCR analyses revealed genetic diversity and some clusters indicating within-hospital spread. The overall findings strongly support the urgent need for accurate and rapid diagnostic services to guide antibiotic treatment and improved infection control measures.
Melanoma diagnosis using deep learning techniques on dermatoscopic images
Authors: Jojoa Acosta Mario Fernando , Caballero Tovar Liesle Yail , Garcia-Zapirain Maria Begonya , Percybrooks Winston Spencer 
Published: January 2021

Abstract
Background
Melanoma has become more widespread over the past 30 years and early detection is a major factor in reducing mortality rates associated with this type of skin cancer. Therefore, having access to an automatic, reliable system that is able to detect the presence of melanoma via a dermatoscopic image of lesions and/or skin pigmentation can be a very useful tool in the area of medical diagnosis.

Methods
Among state-of-the-art methods used for automated or computer assisted medical diagnosis, attention should be drawn to Deep Learning based on Convolutional Neural Networks, wherewith segmentation, classification and detection systems for several diseases have been implemented. The method proposed in this paper involves an initial stage that automatically crops the region of interest within a dermatoscopic image using the Mask and Region-based Convolutional Neural Network technique, and a second stage based on a ResNet152 structure, which classifies lesions as either “benign” or “malignant”.

Results
Training, validation and testing of the proposed model was carried out using the database associated to the challenge set out at the 2017 International Symposium on Biomedical Imaging. On the test data set, the proposed model achieves an increase in accuracy and balanced accuracy of 3.66% and 9.96%, respectively, with respect to the best accuracy and the best sensitivity/specificity ratio reported to date for melanoma detection in this challenge. Additionally, unlike previous models, the specificity and sensitivity achieve a high score (greater than 0.8) simultaneously, which indicates that the model is good for accurate discrimination between benign and malignant lesion, not biased towards any of those classes.

Conclusions
The results achieved with the proposed model suggest a significant improvement over the results obtained in the state of the art as far as performance of skin lesion classifiers (malignant/benign) is concerned.
Quick evaluation of lower leg ischemia in patients with peripheral arterial disease by time maximum intensity projection CT angiography: a pilot study
Authors: Zhang Daming , Zhou Xueyan , Zhang Haiping , Fan Xiaobing , Lin Zehong , Xue Huadan , Wang Yining , Jin Zhengyu , Chen Yuexin 
Published: January 2021

Abstract
Background
The purpose of this study is to evaluate a new method involving time maximum intensity projection (t-MIP) postprocessed from dynamic computed tomographic angiography (dyn-CTA) in diagnosing peripheral arterial disease (PAD).

Methods
A population of 34 patients with known PAD was examined with a combined CTA protocol consisting of a standard CTA (s-CTA) scan of the lower extremities and a dyn-CTA scan of the calves. For each lower leg, t-MIP images consisting of the MIP0 (sagittal MIP), MIP+θ (45° lateral MIP), and MIP−θ (− 45° lateral MIP) were automatically generated from dyn-CTA. An objective evaluation of the vascular CT attenuation of the best enhancement phase of dyn-CTA and t-MIP was measured; a subjective evaluation of vessel stenosis and occlusion was performed, assigning a score for t-MIP and s-CTA. The CT attenuation of t-MIP and dyn-CTA was compared, as were the runoff scores of t-MIP and s-CTA.

Results
The CT attenuation of t-MIP CTA of three vascular segments from 68 lower extremities was higher than that of the best enhancement phase of dyn-CTA and s-CTA, with statistically significant differences at the posterior tibial artery and fibular artery (all p < 0.05). There were strong correlations (r ≥ 0.75, p < 0.05) of the runoff scores between t-MIP and s-CTA.

Conclusions
There is potential clinical applicability of t-MIP in assisting with the diagnosis of lower leg vascular stenosis in dyn-CTA with reliable diagnostic accuracy and convenient immediacy.