bluuebunny/crossref_metadata_2025_split huggingface dataset:
Two fungal flavonoid-specific glucosidases/rutinosidases for rutin hydrolysis and rutinoside synthesis under homogeneous and heterogeneous reaction conditions
Authors: Kotik Michael , Javůrková Hana , Brodsky Katerina , Pelantová Helena 
Published: October 2021

AbstractThe glycosidases within GH5-23 cleave the glycosidic bond of β-glucosylated or rutinosylated flavonoids. Moreover, by virtue of their transglycosylation activity, glycoconjugates with glucosyl and rutinosyl moieties are accessible. Here we report the biochemical characterization and biotechnological assessment of two heterologously expressed members of GH5-23—McGlc fromMucor circinelloidesandPcGlc fromPenicillium chrysogenum. Both enzymes exhibited the highest hydrolytic activities with quercetin-3-β-O-glucopyranoside, whereas lower specificity constants were determined with the rutinosides narcissin, rutin and hesperidin. High stabilities against thermal, ethanol and dimethyl sulfoxide-induced inactivation, a very limited secondary hydrolysis of the formed transglycosylation products, and no detectable product inhibition were additional features appropriate for biotechnological applications. The enzymes were compared in their efficiencies to hydrolyze rutin and to synthesize 2-phenylethyl rutinoside under homogeneous and heterogeneous reaction conditions using high rutin concentrations of 100 and 300 mM. Highest transglycosylation efficiencies were achieved with fully dissolved rutin in reaction mixtures containing 25% dimethyl sulfoxide. Molecular docking and multiple sequence alignments suggest that the hydrophobic environment of aromatic residues within the + 1 subsite of GH5-23 glycosidases is very important for the binding of flavonoid glucosides and rutinosides.
Existence uniqueness of mild solutions for ψ-Caputo fractional stochastic evolution equations driven by fBm
Authors: Yang Min 
Published: October 2021

AbstractIn this paper, we investigate the existence uniqueness of mild solutions for a class of ψ-Caputo fractional stochastic evolution equations with varying-time delay driven by fBm, which seems to be the first theoretical result of the ψ-Caputo fractional stochastic evolution equations. Alternative conditions to guarantee the existence uniqueness of mild solutions are obtained using fractional calculus, stochastic analysis, fixed point technique, and noncompact measure method. Moreover, an example is presented to illustrate the effectiveness and feasibility of the obtained abstract results.
Elliptic problem driven by different types of nonlinearities
Authors: Choudhuri Debajyoti , Repovš Dušan D. 
Published: October 2021

AbstractIn this paper we establish the existence and multiplicity of nontrivial solutions to the following problem: $$\begin{aligned} \begin{aligned} (-\Delta )^{\frac{1}{2}}u+u+\bigl(\ln \vert \cdot \vert * \vert u \vert ^{2}\bigr)&=f(u)+\mu \vert u \vert ^{- \gamma -1}u,\quad \text{in }\mathbb{R}, \end{aligned} \end{aligned}$$

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,

where $\mu >0$
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, $(*)$
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is the convolution operation between two functions, $0<\gamma <1$
0
<
γ
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1
, f is a function with a certain type of growth. We prove the existence of a nontrivial solution at a certain mountain pass level and another ground state solution when the nonlinearity f is of exponential critical growth.
Singularly perturbed quasilinear Choquard equations with nonlinearity satisfying Berestycki–Lions assumptions
Authors: Yang Heng 
Published: October 2021

AbstractIn the present paper, we consider the following singularly perturbed problem:$$ \textstyle\begin{cases} -\varepsilon ^{2}\Delta u+V(x)u-\varepsilon ^{2}\Delta (u^{2})u= \varepsilon ^{-\alpha }(I_{\alpha }*G(u))g(u), \quad x\in \mathbb{R}^{N}; \\ u\in H^{1}(\mathbb{R}^{N}), \end{cases} $${−ε2Δu+V(x)u−ε2Δ(u2)u=ε−α(Iα∗G(u))g(u),x∈RN;u∈H1(RN),where$\varepsilon >0$ε>0is a parameter,$N\ge 3$N≥3,$\alpha \in (0, N)$α∈(0,N),$G(t)=\int _{0}^{t}g(s)\,\mathrm{d}s$G(t)=∫0tg(s)ds,$I_{\alpha }: \mathbb{R}^{N}\rightarrow \mathbb{R}$Iα:RN→Ris the Riesz potential, and$V\in \mathcal{C}(\mathbb{R}^{N}, \mathbb{R})$V∈C(RN,R)with$0<\min_{x\in \mathbb{R}^{N}}V(x)< \lim_{|y|\to \infty }V(y)$0<minx∈RNV(x)<lim|y|→∞V(y). Under the general Berestycki–Lions assumptions ong, we prove that there exists a constant$\varepsilon _{0}>0$ε0>0determined byVandgsuch that for$\varepsilon \in (0,\varepsilon _{0}]$ε∈(0,ε0]the above problem admits a semiclassical ground state solution$\hat{u}_{\varepsilon }$uˆεwith exponential decay at infinity. We also study the asymptotic behavior of$\{\hat{u}_{\varepsilon }\}${uˆε}as$\varepsilon \to 0$ε→0.
Stochastic model of the transmission dynamics of COVID-19 pandemic
Authors: Tesfaye Aychew Wondyfraw , Satana Tesfaye Sama 
Published: October 2021

AbstractIn this paper, we formulate an SVITR deterministic model and extend it to a stochastic model by introducing intensity of stochastic factors and Brownian motion. Our basic qualitative analysis of both models includes the positivity of the solution, invariant region, disease-free equilibrium point, basic reproduction number, local and global stability of disease-free equilibrium point, endemic equilibrium point, and sensitivity. We obtain the stochastic reproduction number and local stability by using twice differentiable Itô’s formula. We prove the global stability of the disease-free equilibrium point by using a Lyapunov function. We determine the sensitivity of the effect of each parameter on basic reproduction number of the model by using a normalized sensitivity index formula. On the other hand, we demonstrate numerical simulation results of deterministic and stochastic models of COVID-19 by using Maple 18 and MATLAB software. Our simulation results indicate that reducing the contact between infected and susceptible individuals and improvement of treatment play a vital role in COVID-19 pandemic control.
Does descending health resources reform impact patient low-level hospital selection behavior? Evidence from Zhejiang, China
Authors: SUN Zesheng , WANG Shuhong , ZHAO Hongjun , ZHOU Xu , ZHANG Ludan , SHI Jiongping 
Published: October 2021

Abstract
Background
Since 2013, China launched descending resources reform, which is a new attempt to correct unbalanced allocation of health resources through human capital spillovers and brand implantation from high-level hospitals. The purpose of this paper is to explore the patients’ hospital selection response to this reform with the focus of low-level hospitals to better understand the effect of this reform on correcting regional inequality of health resources allocation.

Methods
The European Consumer Satisfaction Index model (ECSI) was used to design a questionnaire, and cross-sectional data from 17 hospitals were collected through 1287 questionnaires from Zhejiang Province. Patient hospital selection (loyalty) is measured using ordinary variables by considering patient willingness to choose a low-level hospital when suffering an illness or severe illness. Analysis of variance (ANOVA) and the structure equation model are applied to examine the effect of reforms on patient behavior.

Results
The descending resources reform promotes improvements in the capabilities and medical environment of low-level hospitals, and descending doctors also have high accessibility. Perceived quality, patient expectations, and hospital image have significant positive effects on patient satisfaction, and the explanatory power of brand implantation from cooperative high-level hospitals and descending doctors is stronger than the image of the low-level hospital itself. And descending resources reform and patient satisfaction have significant positive impacts on patient’s choice for low-level hospitals with the existence of mediating effect of satisfaction.

Conclusions
This paper provides supporting empirical evidence of the descending resources reform’s impact on patients’ low-level hospital selection. This reform has been effective in improving the capabilities of low-level hospitals, and brand implantation of high-level hospitals shows strong explanatory power. China’s reform offers a distinct and valuable approach to correcting the uneven allocation of health resources. Besides, the findings also suggest that policymakers could pay more attention to the importance of information channels in impacting patient awareness, responses, and hospital selection.
Genetic spectrum and clinical features in a cohort of Chinese patients with autosomal recessive cerebellar ataxias
Authors: Cheng Hao-Ling , Shao Ya-Ru , Dong Yi , Dong Hai-Lin , Yang Lu , Ma Yin , Shen Ying , Wu Zhi-Ying 
Published: October 2021

Abstract
Background
Although many causative genes have been uncovered in recent years, genetic diagnosis is still missing for approximately 50% of autosomal recessive cerebellar ataxia (ARCA) patients. Few studies have been performed to determine the genetic spectrum and clinical profile of ARCA patients in the Chinese population.

Methods
Fifty-four Chinese index patients with unexplained autosomal recessive or sporadic ataxia were investigated by whole-exome sequencing (WES) and copy number variation (CNV) calling with ExomeDepth. Likely causal CNV predictions were validated by CNVseq.

Results
Thirty-eight mutations including 29 novel ones were identified in 25 out of the 54 patients, providing a 46.3% positive molecular diagnostic rate. Ten different genes were involved, of which four most common genes were SACS, SYNE1, ADCK3 and SETX, which accounted for 76.0% (19/25) of the positive cases. The de novo microdeletion in SACS was reported for the first time in China and the uniparental disomy of ADCK3 was reported for the first time worldwide. Clinical features of the patients carrying SACS, SYNE1 and ADCK3 mutations were summarized.

Conclusions
Our results expand the genetic spectrum and clinical profiles of ARCA patients, demonstrate the high efficiency and reliability of WES combined with CNV analysis in the diagnosis of suspected ARCA, and emphasize the importance of complete bioinformatics analysis of WES data for accurate diagnosis.
Astrocyte dysfunction in Parkinson's disease: from the perspectives of transmitted α-synuclein and genetic modulation
Authors: Wang Changjing , Yang Tongtong , Liang Meiyu , Xie Junxia , Song Ning 
Published: October 2021

AbstractParkinson’s disease (PD) is a common neurodegenerative disorder that primarily affects the elderly. While the etiology of PD is likely multifactorial with the involvement of genetic, environmental, aging and other factors, α-synuclein (α-syn) pathology is a pivotal mechanism underlying the development of PD. In recent years, astrocytes have attracted considerable attention in the field. Although astrocytes perform a variety of physiological functions in the brain, they are pivotal mediators of α-syn toxicity since they internalize α-syn released from damaged neurons, and this triggers an inflammatory response, protein degradation dysfunction, mitochondrial dysfunction and endoplasmic reticulum stress. Astrocytes are indispensable coordinators in the background of several genetic mutations, includingPARK7, GBA1, LRRK2, ATP13A2, PINK1, PRKNandPLA2G6. As the most abundant glial cells in the brain, functional astrocytes can be replenished and even converted to functional neurons. In this review, we discuss astrocyte dysfunction in PD with an emphasis on α-syn toxicity and genetic modulation and conclude that astrocyte replenishment is a valuable therapeutic approach in PD.
Food security effects of smallholders’ participation in apple and mango value chains in north-western Ethiopia
Authors: Mossie Mengistie , Gerezgiher Alemseged , Ayalew Zemen , Elias Asres 
Published: October 2021

Abstract
Background
While it has identified that linking smallholders in the agri-food value chain remains to be a promising strategy to get out of the poverty trap in many developing countries, less is known about the food security implications of smallholders’ participation in the fruits value chain. This paper examines the effects of apple and mango smallholder farmers’ participation along the value chain, focusing on their household food security in north-western Ethiopia.

Methods
Primary data for the study were obtained from a random sample of 384 households, 211 of which are fruit value chain participants, and the remainder are non-participants. The study used the propensity score matching (PSM) method to establish a causal relationship between the participation of the fruit value chain and changes in household food security.

Results and conclusions
Results indicate that participation in the apple and mango value chain has a robust and positive effect on the food security of smallholders as measured by household food consumption in kilocalorie. The unconfoundedness and overlapping assumptions were fulfilled by applying the nearest neighbor and kernel-based matching algorithms. The study confirms that the more apple and mango farmers join the value chain, the higher their household food intake becomes. Support for fruit farmers is, therefore, a promising policy approach that can help improve household food security in rural Ethiopia.
Active virus-host interactions at sub-freezing temperatures in Arctic peat soil
Authors: Trubl Gareth , Kimbrel Jeffrey A. , Liquet-Gonzalez Jose , Nuccio Erin E. , Weber Peter K. , Pett-Ridge Jennifer , Jansson Janet K. , Waldrop Mark P. , Blazewicz Steven J. 
Published: October 2021

Abstract
Background
Winter carbon loss in northern ecosystems is estimated to be greater than the average growing season carbon uptake and is primarily driven by microbial decomposers. Viruses modulate microbial carbon cycling via induced mortality and metabolic controls, but it is unknown whether viruses are active under winter conditions (anoxic and sub-freezing temperatures).

Results
We used stable isotope probing (SIP) targeted metagenomics to reveal the genomic potential of active soil microbial populations under simulated winter conditions, with an emphasis on viruses and virus-host dynamics. Arctic peat soils from the Bonanza Creek Long-Term Ecological Research site in Alaska were incubated under sub-freezing anoxic conditions with H218O or natural abundance water for 184 and 370 days. We sequenced 23 SIP-metagenomes and measured carbon dioxide (CO2) efflux throughout the experiment. We identified 46 bacterial populations (spanning 9 phyla) and 243 viral populations that actively took up 18O in soil and respired CO2 throughout the incubation. Active bacterial populations represented only a small portion of the detected microbial community and were capable of fermentation and organic matter degradation. In contrast, active viral populations represented a large portion of the detected viral community and one third were linked to active bacterial populations. We identified 86 auxiliary metabolic genes and other environmentally relevant genes. The majority of these genes were carried by active viral populations and had diverse functions such as carbon utilization and scavenging that could provide their host with a fitness advantage for utilizing much-needed carbon sources or acquiring essential nutrients.

Conclusions
Overall, there was a stark difference in the identity and function of the active bacterial and viral community compared to the unlabeled community that would have been overlooked with a non-targeted standard metagenomic analysis. Our results illustrate that substantial active virus-host interactions occur in sub-freezing anoxic conditions and highlight viruses as a major community-structuring agent that likely modulates carbon loss in peat soils during winter, which may be pivotal for understanding the future fate of arctic soils' vast carbon stocks.
Inefficient quality control of ribosome stalling during APP synthesis generates CAT-tailed species that precipitate hallmarks of Alzheimer’s disease
Authors: Rimal Suman , Li Yu , Vartak Rasika , Geng Ji , Tantray Ishaq , Li Shuangxi , Huh Sungun , Vogel Hannes , Glabe Charles , Grinberg Lea T. , Spina Salvatore , Seeley William W. , Guo Su , Lu Bingwei 
Published: October 2021

AbstractAmyloid precursor protein (APP) metabolism is central to Alzheimer’s disease (AD) pathogenesis, but the key etiological driver remains elusive. Recent failures of clinical trials targeting amyloid-β (Aβ) peptides, the proteolytic fragments of amyloid precursor protein (APP) that are the main component of amyloid plaques, suggest that the proteostasis-disrupting, key pathogenic species remain to be identified. Previous studies suggest that APP C-terminal fragment (APP.C99) can cause disease in an Aβ-independent manner. The mechanism of APP.C99 pathogenesis is incompletely understood. We used Drosophila models expressing APP.C99 with the native ER-targeting signal of human APP, expressing full-length human APP only, or co-expressing full-length human APP and β-secretase (BACE), to investigate mechanisms of APP.C99 pathogenesis. Key findings are validated in mammalian cell culture models, mouse 5xFAD model, and postmortem AD patient brain materials. We find that ribosomes stall at the ER membrane during co-translational translocation of APP.C99, activating ribosome-associated quality control (RQC) to resolve ribosome collision and stalled translation. Stalled APP.C99 species with C-terminal extensions (CAT-tails) resulting from inadequate RQC are prone to aggregation, causing endolysosomal and autophagy defects and seeding the aggregation of amyloid β peptides, the main component of amyloid plaques. Genetically removing stalled and CAT-tailed APP.C99 rescued proteostasis failure, endolysosomal/autophagy dysfunction, neuromuscular degeneration, and cognitive deficits in AD models. Our finding of RQC factor deposition at the core of amyloid plaques from AD brains further supports the central role of defective RQC of ribosome collision and stalled translation in AD pathogenesis. These findings demonstrate that amyloid plaque formation is the consequence and manifestation of a deeper level proteostasis failure caused by inadequate RQC of translational stalling and the resultant aberrantly modified APP.C99 species, previously unrecognized etiological drivers of AD and newly discovered therapeutic targets.
Cys-SH based quantitative redox proteomics of salt induced response in sugar beet monosomic addition line M14
Authors: Li Jinna , Wang Kun , Ji Meichao , Zhang Tingyue , Yang Chao , Liu He , Chen Sixue , Li Hongli , Li Haiying 
Published: October 2021

Abstract
Background
Salt stress is a major abiotic stress that limits plant growth, development and productivity. Studying the molecular mechanisms of salt stress tolerance may help to enhance crop productivity. Sugar beet monosomic addition line M14 exhibits tolerance to salt stress.

Results
In this work, the changes in the BvM14 proteome and redox proteome induced by salt stress were analyzed using a multiplex iodoTMTRAQ double labeling quantitative proteomics approach. A total of 80 proteins were differentially expressed under salt stress. Interestingly, A total of 48 redoxed peptides were identified for 42 potential redox-regulated proteins showed differential redox change under salt stress. A large proportion of the redox proteins were involved in photosynthesis, ROS homeostasis and other pathways. For example, ribulose bisphosphate carboxylase/oxygenase activase changed in its redox state after salt treatments. In addition, three redox proteins involved in regulation of ROS homeostasis were also changed in redox states. Transcription levels of eighteen differential proteins and redox proteins were profiled. (The proteomics data generated in this study have been submitted to the ProteomeXchange and can be accessed via username: reviewer_pxd027550@ebi.ac.uk, password: q9YNM1Pe and proteomeXchange# PXD027550.)

Conclusions
The results showed involvement of protein redox modifications in BvM14 salt stress response and revealed the short-term salt responsive mechanisms. The knowledge may inform marker-based breeding effort of sugar beet and other crops for stress resilience and high yield.
Performance testing on Transparent Data Encryption for SQL Server's reliability and efficiency
Authors: Madyatmadja Evaristus Didik , Hakim Aditya Nur , Sembiring David Jumpa Malem 
Published: October 2021

AbstractData security is being one of the most crucial aspects to be focused on system development. However, using such a feature to enhance the security of data might affect the system's performance. This study aims to observe how substantial Transparent Data Encryption as a solution for data security on Microsoft SQL Server will affect the database management system's performance. Each of the system performance is conducted with stress and load test. This paper concentrates on the upsides of using Transparent Data Encryption over standard database by finding how significant performance degradation has occurred in terms of Reliability and Efficiency.
Dissimilarity space reinforced with manifold learning and latent space modeling for improved pattern classification
Authors: Rezazadeh Hamedani Azadeh , Moattar Mohammad Hossein , Forghani Yahya 
Published: October 2021

AbstractDissimilarity representation plays a very important role in pattern recognition due to its ability to capture structural and relational information between samples. Dissimilarity space embedding is an approach in which each sample is represented as a vector based on its dissimilarity to some other samples called prototypes. However, lack of neighborhood-preserving, fixed and usually considerable prototype set for all training samples cause low classification accuracy and high computational complexity. To address these challenges, our proposed method creates dissimilarity space considering the neighbors of each data point on the manifold. For this purpose, Locally Linear Embedding (LLE) is used as an unsupervised manifold learning algorithm. The only goal of this step is to learn the global structure and the neighborhood of data on the manifold and mapping or dimension reduction is not performed. In order to create the dissimilarity space, each sample is compared only with its prototype set including its k-nearest neighbors on the manifold using the geodesic distance metric. Geodesic distance metric is used for the structure preserving and is computed using the weighted LLE neighborhood graph. Finally, Latent Space Model (LSM), is applied to reduce the dimensions of the Euclidean latent space so that the second challenge is resolved. To evaluate the resulted representation ad so called dissimilarity space, two common classifiers namely K Nearest Neighbor (KNN) and Support Vector Machine (SVM) are applied. Experiments on different datasets which included both Euclidean and non-Euclidean spaces, demonstrate that using the proposed approach, classifiers outperform the other basic dissimilarity spaces in both accuracy and runtime.