bluuebunny/crossref_metadata_2025_split huggingface dataset:
KVarPredDB: A database for predicting pathogenicity of missense sequence variants of keratin genes associated with genodermatoses
Authors: Ying Yuyi , Lu Lu , Banerjee Santasree , Xu Lizhen , Zhao Qiang , Wu Hao , Li Ruiqi , Xu Xiao , Yu Hua , Neculai Dante , Xi Yongmei , Yang Fan , Qin Jiale , Li Chen 
Published: November 2020

Abstract
Background: Germline variants of ten keratin genes (K1, K2, K5, K6A, K6B, K9, K10, K14, K16 and K17) have been reported for causing different types of genodermatoses with an autosomal dominant mode of inheritance. Among all the variants of these ten keratin genes, most of them are missense variants. Unlike pathogenic and likely pathogenic variants, understanding the clinical importance of novel missense variants or variants of uncertain significance (VUS) is the biggest challenge for clinicians or medical geneticists. Functional characterization is the only way to understand the clinical association of novel missense variants or VUS but it is time-consuming, costly and depends on the availability of patient’s samples. Existing databases report the pathogenic variants of the keratin genes, but never emphasize the systematic effects of these variants on keratin protein structure and genotype-phenotype correlation.Results: To address this need, we developed a comprehensive database KVarPredDB, which contains information of all ten keratin genes associated with genodermatoses. We integrated and curated 400 reported pathogenic missense variants as well as 4629 missense VUS. KVarPredDB predicts the pathogenicity of novel missense variants as well as to understand the severity of disease phenotype, based on four criteria; firstly, difference in physico-chemical properties between the wild-type and substituted amino acids, secondly, the loss of inter/intra-chain interactions, thirdly, evolutionary conservation of the wild type amino acids and lastly, the effect of the substituted amino acids in the heptad repeat. Molecular docking simulations based on resolved crystal structures were adopted to predict stability changes and get the binding energy to compare the wild type protein with the mutated one. We use this basic information to determine the structural and functional impact of novel missense variants on the keratin coiled-coil heterodimer. KVarPredDB was built under the integrative web application development framework SSM (SpringBoot, Spring MVC, MyBatis) and implemented in Java, Bootstrap, React-mutation-mapper, MySQL, Tomcat. The website can be accessed through http://bioinfo.zju.edu.cn/KVarPredDB. The genomic variants and analysis results are freely available under the Creative Commons license.Conclusions: KVarPredDB provides an intuitive and user-friendly interface with computational analytical investigation for each missense variant of the keratin genes associated with genodermatoses.
Alternative approaches for clinical clerkship during the COVID-19 pandemic: Online clinical practice for inpatients and outpatients—A mixed method
Authors: Kasai Hajime , Shikino Kiyoshi , Saito Go , Tsukamoto Tomoko , Takahashi Yukiko , Kuriyama Ayaka , Tanaka Kazuhisa , Onodera Misaki , Yokoh Hidetaka , Tatsumi Koichiro , Yoshino Ichiro , Ikusaka Masatomi , Sakao Seiichiro , Ito Shoichi 
Published: November 2020

Abstract
Background: The COVID-19 pandemic has created a need for educational materials and methods that can replace clinical clerkships (CCs) for online simulated clinical practice (online-sCP). This study evaluates the impact of using simulated electronic health records (sEHR) for inpatients, and electronic problem-based learning (e-PBL) and online virtual medical interviews (online-VMI) for outpatients, for an online-sCP using a learning management system (LMS) and online meeting system facilitated by a supervising physician.Methods: The sEHR was reviewed by medical students and subsequently discussed with a supervising physician using an online meeting system. In the e-PBL, medical students reviewed the simulated patients and discussed on the LMS. For the online-VMI, a faculty member acted as an outpatient and a student acted as the doctor. Small groups of students discussed the clinical reasoning process using the online meeting system. A mixed-method design was implemented. Medical students self-assessed their clinical competence before and after the online-sCP. They answered questionnaires and participated in semi-structured focus group interviews (FGIs) regarding the advantages and disadvantages of the practice.Results: Forty-three students completed the online-sCP during May and June 2020. All students indicated significant improvement in all aspects of self-evaluation of clinical performance after the online-sCP. Students using sEHR reported significant improvement in writing daily medical records and medical summaries. Students using e-PBL and online-VMI reported significant improvement in medical interviews and counseling. Students also indicated CCs as more useful for learning associated with medical interviews, physical examinations, and humanistic qualities like professionalism than the online-sCP. Eight FGIs were conducted (n = 42). The advantages of online-sCP were segregated into five categories (learning environment, efficiency, accessibility, self-paced learning, and interactivity); meanwhile, the disadvantages of online-sCP were classified into seven categories (clinical practice experience, learning environment, interactivity, motivation, memory retention, accessibility, and extraneous cognitive load).Conclusions: Online-sCP with sEHR, e-PBL, and online-VMI could be useful in learning some of the clinical skills acquired through CC. These methods can be implemented with limited preparation and resources.
Baseline Interleukin-6 Level Predicts Risk of Severe COVID-19: A Two-Center, Retrospective Study
Authors: Zhu Weigang , Wu Yingping , Liu Yueping , Li Bin , Xiong Pian , Cui Dawei , Diao Bo , Wu Jianguo 
Published: November 2020

Abstract
Background:The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) pandemic has affected almost every country. Interleukin-6 (IL-6), a cytokine secreted by CD4+ T cell, has been shown to be a reliable marker of disease severity and a useful parameter for monitoring progression of coronavirus disease-2019 (COVID-19). However its value as a predictor of severe disease has not been assessed.Methods:A total of 160 laboratory-confirmed COVID-19 patients admitted to two hospitals were enrolledand separated into two groups according to whether or not they progressed to develop severe illness. Demographic and clinical characteristics at admission were compared between the groups.Results: Patients who developed severe COVID-19 had significantly higher baseline IL-6 levels than patients who had mild disease course in hospital (P< 0.001). Patients were further grouped according to quartiles of IL-6 level. The cumulative incidence of severe illnesswas significantly higher in the third and fourth quartiles groups than in the first quartile group (55% vs. 15% and 80% vs. 15%, respectively;bothP< 0.001). In multivariate logistic regression analysis, the risk for developing severe disease was markedly higher in the highest IL-6 quartile than in the lowest quartile (odds ratio: 14.95; 95% confidence interval: 3.65–61.30; P< 0.001). Receiver operating characteristic curve analysis of potential predictive variables showed the area under the curve to be largest for baseline IL-6, with the value of 5.20 pg/mL having the best balance of sensitivity and specificity for predicting risk of severe COVID-19.Conclusion: Serum baseline IL-6 appears to be a reliable predictor of risk of severe COVID-19. Early intervention may be advisable in patients with serum IL-6 levels >5.20 pg/mL, even if initial symptoms are mild.
Nanoscale Flow Choking at the Zero Slip Length: Universal Benchmark Data for In Silico Experiments
Authors: Kumar V R Sanal , Sankar Vigneshwaran , Chandrasekaran Nichith , Rafic Sulthan Ariﬀ Rahman Mohamed , Sukumaran Ajith , R.S. Bharath , Oommen Charlie , Radhakrishnan Pradeep Kumar , Choudhary Shiv Kumar 
Published: November 2020

Abstract
The Sanal flow choking (PMCID: PMC7267099) and the streamtube flow choking are new theoretical concepts applicable to both the continuum and non-continuum fluid flows. Once the streamlines compacted, the considerable pressure difference attains within the streamtube and the flow within the streamtube gets accelerated to the constricted section for satisfying the continuity condition set up the conservation law of nature, which leads to the Sanal flow choking and supersonic flow development at a critical-total-to-static pressure ratio (CPR) due to the convergent-divergent (CD) shape of the streamtube. As the pressure of the nanofluid/non-continuum-flows rises, average-mean-free-path diminishes and thus, the Knudsen number lowers heading to a zero-slip wall-boundary condition with compressible viscous (CV) flow regime. Sanal flow choking is a CV flow phenomenon creating a physical situation of the sonic-fluid-throat in a duct at a CPR. Herein, we presented a closed-form-analytical-model, which is capable to predict exactly the three-dimensional boundary-layer-displacement-thickness of nanoscale diabatic fluid flow (flow involves transfer of heat) systems at the zero-slip-length. The innovation of Sanal flow choking model is established herein through the entropy relation, as it satisfies all the conservation laws of nature. The exact value of the 3D boundary-layer-displacement-thickness in the sonic-fluid-throat region presented herein for each gas is a universal benchmark data for performing high-fidelity in vitro and in silico experiments for the lucrative design optimization of nanoscale systems. The physical insight of the Sanal flow choking and streamtube flow choking presented in this letter sheds light on finding solutions for numerous unresolved scientific problems.
Cerebellar transcranial direct current stimulation reconfigurates static and dynamic functional connectivity of the resting-state networks
Authors: Grami Fatma , de Marco Giovanni , Bodranghien Florian , Manto Mario , Habas C. 
Published: November 2020

Abstract
Background
Transcranial direct current stimulation (tDCS) of the cerebellum dynamically modulates cerebello-thalamo-cortical excitability in a polarity-specific manner during motor, visuo- motor and cognitive tasks. It remains to be established whether tDCS of the cerebellum impact also on resting-state intrinsically connected networks (ICNs). Such impact would open novel research and therapeutical doors for the neuromodulation of ICNs in human.
Method:
We combined tDCS applied over the right cerebellum and fMRI to investigate tDCS- induced resting-state intrinsic functional reconfiguration, using a randomized, sham-controlled design. fMRI data were recorded both before and after real anodal stimulation (2 mA, 20 min) or sham tDCS in 12 right-handed healthy volunteers. We resorted to a region-of-interest static correlational analysis and to a sliding window analysis to assess temporal variations in resting state FC between the cerebellar lobule VII and nodes of the main ICNs.
Results
After real tDCS and compared with sham tDCS, functional changes were observed between the cerebellum and ICNs. Static FC showed enhanced or decreased correlation between cerebellum and brain areas belonging to visual, default-mode (DMN), sensorimotor and salience networks (SN) (p-corrected < 0.05). The temporal variability (TV) of BOLD signal was significantly modified after tDCS displaying in particular a lesser TV between the whole lobule VII and DMN and central executive network and a greater TV between crus 2 and SN. Static and dynamic FC was also modified between cerebellar lobuli.
Conclusion
These results demonstrate short- and long-range static and majorly dynamic effects of tDCS stimulation of the cerebellum affecting distinct resting-state ICNs, as well as intracerebellar functional connectivity, so that tDCS of the cerebellum appears as a non-invasive tool reconfigurating the dynamics of ICNs.
Methylation of TMEM176A, a Key ERK Signaling Regulator, is a Novel Synthetic Lethality Marker of ATM Inhibitor in Human Lung Cancer
Authors: Li Hongxia , Yang Weili , He Tao , Zhou Fuyou , Herman James G , Hu Liming , Guo Mingzhou 
Published: November 2020

Abstract
Background: Synthetic lethality is a new strategy of cancer therapy. Epigenetic based synthetic lethality may provide more opportunities for cancer prevention and treatment. TMEM176A is frequently methylated in esophageal, hepatic and colorectal cancer. The role of TMEM176A methylation in lung cancer and its therapeutic application remains unclear.Methods: Nine lung cancer cell lines and 123 cases of cancer tissue samples were employed. Methylation specific PCR, MTT assay, flow cytometry, and xenograft mouse models were applied.Results: The expression of TMEM176A was found to be regulated by promoter region methylation in lung cancer cells. TMEM176A was methylated in 53.66% (66/123) of primary lung cancer. Reduced expression of TMEM176A was associated with promoter region methylation in 40 cases of matched lung cancer and adjacent tissue samples (P<0.05). No association was found between TMEM176A methylation and age, gender, alcohol abuse, smoking, tumor size, lymph node metastasis, differentiation and TNM stage (all P >0.05). Restoration of TMEM176A expression induced cell apoptosis and G2/M phase arrest and inhibited colony formation, cell proliferation, migration and invasion in H1299 and H23 cells. TMEM176A suppressed H1299 cell xenograft growth in mice. Methylation of TMEM176A activated ERK1/2 signaling, and sensitized H1299 and H23 cells to AZD0156, an ATM inhibitor.Conclusion: TMEM176A is frequently methylated in human lung cancer, and the expression of TMEM176A is regulated by promoter region methylation. TMEM176A suppresses lung cancer growth by inhibiting ERK1/2 signaling. Methylation of TMEM176A is a potential lung cancer diagnostic marker and a novel synthetic lethal therapeutic marker for AZD0156, an ATM inhibitor.
Suspended sediment modelling with hydrological and climate input data
Authors: Cisty Milan , Soldanova Veronika , Cyprich Frantisek , Holubova Katarina , Simor Viliam 
Published: November 2020

Abstract
Measured records of suspended sediment concentrations are vital information to support water management activities. However, these measured time series are often incomplete and, as such, are not suitable for some analyses. This paper sets out the options for modelling suspended sediment concentrations to determine them in periods when measurements were not performed. The Danube River profile in Bratislava was selected as the case study. Regression using least absolute selection and shrinkage operator, support vector regression and deep learning neural network are compared in the paper to solve this task using various data sources. The results obtained show a significant increase in the precision of modelling suspended sediment concentrations over the standard method, which is a rating curve. Several variables were used to establish the suspended sediment concentration, because the same data as in this study may not be available everywhere. In particular, the use of climatic (precipitation and temperature) and hydrological inputs (flows) is assessed in order to promote the more general benefit of work. In the article, the authors propose an original method of modification of input climate data, which significantly increases the accuracy of modelling. The authors demonstrate that when using proposed methodology, the use of climate data, which are usually better available than hydrological data, resulted in a comparable degree of precision to standard modelling based on river flow data.
Removal of Zn(II), Mn(II) and Cu(II) by adsorption onto banana stalk biochar: adsorption process and mechanisms
Authors: Deng Hua , Li Qiuyan , Huang Meijia , Li Anyu , Zhang Junyu , Li Yafen , Li Shuangli , Kang Caiyan , Mo Weiming 
Published: November 2020

Abstract
Low-cost banana stalk (Musa nana Lour.) biochar was prepared using oxygen-limited pyrolysis (at 500 °C and used), to remove heavy metal ions (including Zn(II), Mn(II) and Cu(II)) from aqueous solution. Adsorption experiments showed that the initial solution pH affected the ability of the biochar to adsorb heavy metal ions in single- and polymetal systems. Compared to Mn(II) and Zn(II), the biochar exhibited highly selective Cu(II) adsorption. The adsorption kinetics of all three metal ions followed the pseudo-second-order kinetic equation. The isotherm data demonstrated the Langmuir model fit for Zn(II), Mn(II) and Cu(II). The results showed that the chemical adsorption of single molecules was the main heavy metal removal mechanism. The maximum adsorption capacities (mg·g−1) were ranked as Cu(II) (134.88) &gt; Mn(II) (109.10) &gt; Zn(II) (108.10)) by the single-metal adsorption isotherms at 298 K. Moreover, characterization analysis was performed using Fourier transform infrared spectroscopy, the Brunauer-Emmett-Teller method, scanning electron microscopy with energy-dispersive X-ray spectroscopy, X-ray diffraction, and X-ray photoelectron spectroscopy. The results revealed that ion exchange was likely crucial in Mn(II) and Zn(II) removal, while C-O, O-H and C = O possibly were key to Cu(II) removal by complexing or other reactions.
Soluble Expression, One-Step Purification and Characterization of Recombinant Human Growth Hormone Fused with ompA3 in Escherichia coli
Authors: Zhou Zhen-Ru , Huang Wei , Liu Kang-Jia , Lin Fo-Lan , Wang Xiao-Lu , Wang Feng , Jiang Ren-Wang 
Published: November 2020

Background:
Human growth hormone (hGH) is the first recombinant protein approved for the treatment of human growth hormone deficiency. However, expression in inclusion bodies and low expression levels are enormous challenges for heterologous expression of hGH in Escherichia coli.

Objective:
To increase the soluble expression of recombinant hGH with correct folding in E. coli.

Methods:
We constructed a new recombinant expression plasmid containing the coding sequence
of the outer membrane protein A (ompA3) which was used for the expression in Transetta (DE3)
E. coli. In order to simplify the purification process and cleavage of recombinant proteins, the fusion
sequence should contain hexahistidine-tag (His6) and enterokinase recognition sites (D4K).
The effect of different expression conditions on recombinant hGH expression was optimized in
flask cultivations. Furthermore, the periplasmic solution containing soluble hGH was purified by
Ni-NTA affinity chromatography. Circular dichroism (CD), western blot and mass spectrometry
analyses were used to characterize the protein. Moreover, the growth-promoting effect of the purified
hGH was also evaluated by cell proliferation assay.

Results:
High-level expression (800 g/mL) was achieved by induction with 0.5 mM IPTG at 30 ºC for 10 hours. The purity
of hGH was over 90%. The immunological activity, secondary structure and molecular weight of the purified hGH were
consistent with native hGH. The purified hGH was found to promote the growth of MC3T3-E1 cells, and was found to show
the highest activity at a concentration of 100 ng/mL.

Conclusion:
Our research provides a feasible and convenient method for the soluble expression of recombinant hGH in E.
coli, and may lay a foundation for the production and application of hGH in the industry.
Novel N-(2-Methoxydibenzofuran-3-yl)-2-aryloxyacetamide Derivatives: Synthesis and Biological Investigation
Authors: Yurttaş Leyla , Çavuşoğlu Betül Kaya , Temel Halide Edip , Çiftçi Gülşen Akalın 
Published: November 2020

Background:
Dibenzofuran ring is a typical heterocyle that is found in many natural
sources and its derivatives exhibit a wide scale of biological applications similar to its analog ring
systems; furan and benzofuran.

Materials and Methods:
Novel N-(2-methoxydibenzofuran-3-yl)-2-aryloxyacetamide derivatives
(2a-l) were synthesized and evaluated for their cytotoxic activity against A549 lung cancer and
NIH/3T3 mouse embryofibroblast cell lines. The inhibition percentages of cathepsin D, L, acetylcholinesterase
(AChE) and butrylcholinesterase (BuChE) enzymes provoked by the compounds
were also determined.

Results and Discussion:
Most of the compounds exhibited significant cytotoxicity whose IC50 values
were identified lower than the tested lowest concentration (<3.90 μg/mL). Compound 2i against
cathepsin D and compound 2k against cathepsin L displayed the highest inhibitory activity. Regrettably,
the compounds demonstrated very weak AChE and BuChE inhibition.

Conclusion:
Compounds 2b, 2c, 2e, 2i and 2k exhibited the highest antiproliferative activity
against A549 cell lines with selective profile. However, they did not display satisfying results on
tested enzymes.
Green Miniaturized Extraction and Microextraction of Polycyclic Aromatic Hydrocarbons from Foods and Beverages
Authors: Manousi Natalia , Zachariadis George A. 
Published: November 2020

Background:
Polycyclic aromatic hydrocarbons (PAHs) are common environmental
contaminants consisting of two or more fused benzene rings. PAHs can be introduced into foodstuffs
through different ways, such as smoking, roasting and grilling for meat and fish, absorption
from the environment for edible oils, chemical treatment of crops for plant-based products, or
contamination through packaging during storage. Due to the low concentrations of PAHs in foodstuffs,
a clean-up and preconcentration sample preparation technique is of high importance. Until
recently, solid-phase and liquid-liquid extraction were the most popular sample preparation techniques
for the extraction of PAHs from food matrices. However, due to the fundamental drawbacks
of those extraction procedures, a plethora of novel methods, including micro-extraction
techniques and miniaturized extraction techniques, have been developed. Moreover, a wide variety
of novel adsorbent materials (e.g., metal-organic frameworks, carbon-based materials, etc.)
have been synthesized and applied for PAHs’ extraction.

Objective:
This review aims to discuss recent advances in the extraction techniques of PAHs
from food samples, utilizing novel sample preparation approaches and adsorbents.

Conclusion:
Compared with the traditional sample preparation techniques, the herein discussed
green miniaturized extraction and microextraction techniques offer multiple benefits, including
simplicity, reduced sample preparation time, as well as reduced consumption of organic solvents.
A Study on Multi-class Classification of Breast Cancer Images using Ensemble Network and Transfer Learning
Authors: Tipirneni Lahari , Patan Rizwan 
Published: November 2020

Background:
Breast cancer causes millions of deaths all over the world every year. It has
become the most common type of cancer in women. Early detection will help in better prognosis
and increase the chance of survival. Automating the classification using Computer-Aided Diagnosis
(CAD) systems can make the diagnosis less prone to errors. Multi-class classification and Binary
classification of breast cancer is a challenging problem. Convolutional neural network architectures
extract specific feature descriptors from images, which cannot represent different types of breast
cancer. This leads to false positives in classification, which is undesirable in disease diagnosis.

Methods:
The current paper presents an ensemble Convolutional neural network for multi-class
classification and Binary classification of breast cancer. The feature descriptors from each network
are combined to produce the final classification. In this paper, histopathological images are taken
from the publicly available BreakHis dataset and classified into 8 classes.

Results:
The proposed ensemble model can perform better when compared to the methods proposed
in the literature. The results showed that the proposed model could be a viable approach for breast
cancer classification.

Conclusion:
In this paper, an approach for multi-class classification on the breast images for cancer
detection is proposed. The proposed architecture can be a viable option for the classification of histopathology
images.