bluuebunny/crossref_metadata_2025_split huggingface dataset:
A hybrid boundary element-finite element method to solve the EEG forward problem
Authors: Dayarian Nasireh , Khadem Ali 
Published: December 2021

AbstractThis article presents a hybrid boundary element-finite element (BE-FE) method to solve the EEG forward problem and take advantages of both the boundary element method (BEM) and finite element method (FEM). Although realistic EEG forward problems with heterogeneous and anisotropic regions can be solved by FEM accurately, the FEM modeling of the brain with dipolar sources may lead to singularity. In contrast, the BEM can solve EEG forward problems with isotropic tissue regions and dipolar sources using a suitable integral formulation. This work utilizes both FEM and BEM strengths attained by dividing the regions into some homogeneous BE regions with sources and some heterogeneous and anisotropic FE regions. Furthermore, the BEM is applied for modeling the brain, including dipole sources and the FEM for other head layers. To validate the proposed method, inhomogeneous isotropic/anisotropic three- and four-layer spherical head models are studied. Moreover, a four-layer realistic head model is investigated. Results for six different dipole eccentricities and two different dipole orientations are computed using the BEM, FEM, and hybrid BE–FE method together with statistical analysis and the related error criteria are compared. The proposed method is a promising new approach for solving realistic EEG forward problems.
PTHrP Induces STAT5 Activation, Secretory Differentiation and Mammary Tumor Progression
Authors: Grinman Diego Y. , Boras-Granic Kata , Takyar Farzin M. , Dann Pamela , Hens Julie R. , Marmol Christina , Lee Jongwon , Choi Jungmin , Chodosh Lewis A. , Garcia Sola Martin E. , Wysolmerski John J. 
Published: December 2021

AbstractBackgroundParathyroid hormone-related protein (PTHrP) is required for embryonic breast development and has important functions during lactation, when it is produced by alveolar epithelial cells and secreted into the maternal circulation to mobilize skeletal calcium used for milk production. PTHrP is also produced by breast cancers and GWAS studies suggest that it influences breast cancer risk. However, the exact functions of PTHrP in breast cancer biology remain unsettled.MethodsWe developed a tetracyline-regulated, MMTV (mouse mammary tumor virus)-driven model of PTHrP overexpression in mammary epithelial cells (Tet-PTHrP mice) and bred these mice with the MMTV-PyMT (polyoma middle tumor-antigen) breast cancer model to analyze the impact of PTHrP overexpression on normal mammary gland biology and in breast cancer progression.ResultsOverexpression of PTHrP in luminal epithelial cells caused alveolar hyperplasia and secretory differentiation of the mammary epithelium with milk production. This was accompanied by activation of Stat5 and increased expression of E74-like factor-5 (Elf5). In MMTV-PyMT mice, overexpression of PTHrP (Tet-PTHrP;PyMT mice) shortened tumor latency and accelerated tumor growth, ultimately reducing overall survival. Tumors overproducing PTHrP also displayed increased expression of nuclear pSTAT5 and Elf5, increased expression of markers of secretory differentiation and milk constituents, and histologically resembled secretory carcinomas of the breast. Overexpression of PTHrP within cells isolated from tumors, but not PTHrP exogenously added to cell culture media, led to activation of STAT5 and milk protein gene expression. In addition, neither ablating the Type 1 PTH/PTHrP receptor (PTH1R) in epithelial cells or treating Tet-PTHrP;PyMT mice with an anti-PTH1R antibody prevented secretory differentiation or altered tumor latency. These data suggest that PTHrP acts in a cell-autonomous, intracrine manner. Finally, expression of PTHrP in human breast cancers is associated with expression of genes involved in milk production and STAT5 signaling.ConclusionsOur study suggests that PTHrP promotes pathways leading to secretory differentiation and proliferation in both normal mammary epithelial cells and in breast tumor cells.
Simple and cost-effective SNP genotyping method for discriminating subpopulations of the fish pathogen, Nocardia seriolae
Authors: Le Cuong T. , Price Erin P. , Sarovich Derek S. , Nguyen Thu T.A , Vu-Khac Hung , Kurtböke Ipek , Knibb Wayne , Chen Shih-Chu , Katouli Mohammad 
Published: December 2021

AbstractNocardia seriolae has caused significant fish losses in Asia and the Americas in recent decades, including in Vietnam, which has witnessed devastating economic and social impacts due to this bacterial pathogen. Surveillance strategies are urgently needed to mitigate N. seriolae dissemination in Vietnamese aquaculture and mariculture industries. Whole-genome sequencing (WGS) offers the highest level of resolution to discriminate closely related strains and to determine their putative origin and transmission routes. However, WGS is impractical for epidemiological investigations and pathogen surveillance due to its time-consuming and costly nature, putting this technology out-of-reach for many industry end-users. To overcome this issue, we targeted two previously characterised, phylogenetically informative single-nucleotide polymorphisms (SNPs) in N. seriolae that accurately distinguish: i) Vietnamese from non-Vietnamese strains, and ii) the two Vietnamese subclades. Using the mismatch amplification mutation assay (MAMA) format, we developed assays that genotype strains based on differences in amplicon melting temperature (melt-MAMA) and size (agarose-MAMA). Our MAMA assays accurately genotyped strains both from culture and fish tissues at low cost, using either real-time (~AUD$1/per sample) or conventional (~AUD$0.50/per sample) PCR instrumentation. Our novel assays provide a rapid, reproducible, and cost-effective tool for routine genotyping of this pathogen, allowing faster identification and treatment of nocardiosis-effected permit fish within Vietnamese aquaculture/mariculture facilities, an essential step in mitigating N. seriolae-associated losses.
A versatile active learning workflow for optimization of genetic and metabolic networks
Authors: Pandi Amir , Diehl Christoph , Kharrazi Ali Yazdizadeh , Faure Léon , Scholz Scott A. , Nattermann Maren , Adam David , Chapin Nils , Foroughijabbari Yeganeh , Moritz Charles , Paczia Nicole , Cortina Niña Socorro , Faulon Jean-Loup , Erb Tobias J. 
Published: December 2021

AbstractThe study, engineering and application of biological networks require practical and efficient approaches. Current optimization efforts of these systems are often limited by wet lab labor and cost, as well as the lack of convenient, easily adoptable computational tools. Aimed at democratization and standardization, we describe METIS, a modular and versatile active machine learning workflow with a simple online interface for the optimization of biological target functions with minimal experimental datasets. We demonstrate our workflow for various applications, from simple to complex gene circuits and metabolic networks, including several cell-free transcription and translation systems, aLacI-based multi-level controller and a 27-variable synthetic CO2-fixation cycle (CETCH cycle). Using METIS, we could improve above systems between one and two orders of magnitude compared to their original setup with minimal experimental efforts. For the CETCH cycle, we explored the combinatorial space of ∼1025conditions with only 1,000 experiments to yield the most efficient CO2-fixation cascade described to date. Beyond optimization, our workflow also quantifies the relative importance of individual factors to the performance of a system. This allows to identify so far unknown interactions and bottlenecks in complex systems, which paves the way for their hypothesis-driven improvement, which we demonstrate for theLacImulti-level controller that we were able to improve by 34-fold after having identified resource competition as limiting factor. Overall, our workflow opens the way for convenient optimization and prototyping of genetic and metabolic networks with customizable adjustments according to user experience, experimental setup, and laboratory facilities.
Deciphering the quality of SARS-CoV-2 specific T-cell response associated with disease severity, immune memory and heterologous response
Authors: Pérez-Gómez Alberto , Gasca-Capote M Carmen , Vitallé Joana , Ostos Francisco J. , Serna-Gallego Ana , Trujillo-Rodríguez María , Muñoz-Muela Esperanza , Giráldez-Pérez Teresa , Praena-Segovia Julia , Navarro-Amuedo María D. , Paniagua-García María , García-Gutiérrez Manuel , Aguilar-Guisado Manuela , Rivas-Jeremias Inmaculada , Jimenez-Leon María R. , Bachiller Sara , Fernández-Villar Alberto , Pérez-González Alexandre , Gutiérrez-Valencia Alicia , Benhnia Mohammed Rafii-El-Idrissi , Weiskopf Daniela , Sette Alessandro , López-Cortes Luis F. , Poveda Eva , Ruiz-Mateos Ezequiel ,   Virgen del Rocío Hospital COVID-19,   COHVID-GS Working Teams
Published: December 2021

ABSTRACTSARS-CoV-2 specific T-cell response has been associated with disease severity, immune memory and heterologous response to endemic coronaviruses. However, an integrative approach combining a comprehensive analysis of the quality of SARS-CoV-2 specific T-cell response with antibody levels in these three scenarios is needed. In the present study we found that, in acute infection, while mild disease was associated with high T-cell polyfunctionality biased to IL-2 production and inversely correlated with anti-S IgG levels, combinations only including IFN-γ with absence of perforin production predominated in severe disease. Seven months after infection, both non-hospitalized and previously hospitalized patients presented robust anti-S IgG levels and SARS-CoV-2 specific T-cell response. In addition, only previously hospitalized patients showed a T-cell exhaustion profile. Finally, combinations including IL-2 in response to S protein of endemic coronaviruses, were the ones associated with SARS-CoV-2 S-specific T-cell response in pre-COVID-19 healthy donors’ samples. These results have implications for protective immunity against SARS-CoV-2 and recurrent COVID-19 and may help for the design of new prototypes and boosting vaccine strategies.
Intranasal inhibitor broadly blocks SARS-CoV-2 including recent highly immunoevasive Omicron subvariants
Authors: Mäkelä Anna R. , Uğurlu Hasan , Hannula Liina , Kant Ravi , Salminen Petja , Fagerlund Riku , Mäki Sanna , Haveri Anu , Strandin Tomas , Kareinen Lauri , Hepojoki Jussi , Kuivanen Suvi , Levanov Lev , Pasternack Arja , Naves Rauno A. , Ritvos Olli , Österlund Pamela , Sironen Tarja , Vapalahti Olli , Kipar Anja , Huiskonen Juha T. , Rissanen Ilona , Saksela Kalle 
Published: December 2021

SUMMARYThe recent emergence of novel SARS-CoV-2 variants capable of efficiently escaping neutralizing antibodies emphasizes the need for prophylactic strategies to complement vaccination in fighting the COVID-19 pandemic. Nasal epithelium is rich in the ACE2 receptor and important for SARS-CoV-2 transmission by supporting early viral replication before seeding to the lung1. Intranasal administration of SARS-CoV-2 neutralizing antibodies or antibody fragments has shown encouraging potential as a protective measure in animal models2–5. However, there remains a dire need for SARS-CoV-2 blocking agents that are less vulnerable to mutational variation in the neutralization epitopes of the viral spike glycoprotein and more economical to produce in large scale. Here we describe TriSb92, a highly manufacturable and extremely stable trimeric human SH3 domain-derived antibody mimetic targeted against a conserved region in the receptor-binding domain of spike. TriSb92 potently neutralizes SARS-CoV-2 and its variants of concern, including Omicron BA.5 as well as the latest and most immunoevasive variants like BF.7, XBB, and BQ.1.1. Intranasal administration of a modest dose of TriSb92 (5 or 50 micrograms) as early as eight hours before a challenge with SARS-CoV-2 efficiently protected mice from infection, and was still effective even when given 4 h after the viral challenge. The target epitope of TriSb92 was defined by cryo-EM, which revealed triggering of a conformational shift in the spike trimer rather than competition for ACE2 binding as the molecular basis of its strong inhibitory action. The high potency and robust biochemical properties of TriSb92 together with the remarkable resistance of its inhibitory action against viral sequence evolution suggest that TriSb92 could be useful as a nasal spray for protecting susceptible individuals from SARS-CoV-2 infection.
Effect of nebulised BromAc® on rheology of artificial sputum: relevance to muco-obstructive respiratory diseases including COVID-19
Authors: Pillai Krishna , Mekkawy Ahmed H. , Akhter Javed , Valle Sarah J. , Morris David L. 
Published: December 2021

AbstractRespiratory diseases such as cystic fibrosis, COPD, bronchiectasis asthma and COVID-19 are difficult to treat owing to viscous secretions in the airways that evade mucocilliary clearance. Since earlier studies have shown success with BromAc® as mucolytic agent for treating a rare disease known as pseudomyxoma peritonei (PMP), we tested the formulation on two gelatinous airway representative sputa models, in order to determine whether similar efficacy exist.The sputum (1.5 ml) lodged in an endotracheal tube was treated to aerosolised N-acetylcysteine, bromelain, or their combination (BromAc®) using a nebuliser with 6.0 ml of the agents in phosphate buffer saline, over 25 min. Controls received phosphate buffer saline. The dynamic viscosity was measured before and after treatment using a capillary tube method, whilst the sputum flow (ml/sec) was assessed using a 0.5 ml pipette. Finally, the sequestered agents (concentration) in the sputa after treatment were quantified using standard bromelain and N-acetylcysteine chromogenic assays.Results indicated that bromelain and N-acetylcysteine affected both the dynamic viscosities and pipette flow in the two sputa models, with changes in the former parameter having immense effect on the latter. BromAc® showed a greater rheological effect on both the sputa models compared to individual agents. Further, correlation was found between the rheological effects and the concentration of agents in the sputa.Hence, this study indicates that BromAc® may be used as a successful mucolytic for clearing airway congestion caused by thick mucinous immobile secretion, however further studies with patient sputum samples using aerosol BromAc® is warranted.
SynLethDB 2.0: A web-based knowledge graph database on synthetic lethality for novel anticancer drug discovery
Authors: Wang Jie , Wu Min , Huang Xuhui , Wang Li , Zhang Sophia , Liu Hui , Zheng Jie 
Published: December 2021

AbstractTwo genes are synthetic lethal if mutations in both genes result in impaired cell viability, while mutation of either gene does not affect the cell survival. The potential usage of synthetic lethality (SL) in anticancer therapeutics has attracted many researchers to identify synthetic lethal gene pairs. To include newly identified SLs and more related knowledge, we present a new version of the SynLethDB database to facilitate the discovery of clinically relevant SLs. We extended the first version of SynLethDB database significantly by including new SLs identified through CRISPR screening, a knowledge graph about human SLs, and new web interface, etc. Over 16,000 new SLs and 26 types of other relationships have been added, encompassing relationships among 14,100 genes, 53 cancers, and 1,898 drugs, etc. Moreover, a brand-new web interface has been developed to include modules such as SL query by disease or compound, SL partner gene set enrichment analysis and knowledge graph browsing through a dynamic graph viewer. The data can be downloaded directly from the website or through the RESTful APIs. The database is accessible online at http://synlethdb.sist.shanghaitech.edu.cn/v2.
Towards Generalizable Predictions for the Effects of Mutations on G-Protein Coupled Receptor Expression
Authors: Kuntz Charles P. , Woods Hope , McKee Andrew G. , Zelt Nathan B. , Mendenhall Jeffrey L. , Meiler Jens , Schlebach Jonathan P. 
Published: December 2021

ABSTRACTMissense mutations that compromise the plasma membrane expression (PME) of integral membrane proteins (MPs) are the root cause of numerous genetic diseases. Differentiation of this class of mutations from those that specifically modify the activity of the folded protein has proven useful for the development and targeting of precision therapeutics. Nevertheless, it remains challenging to predict the effects of mutations on the stability and/ or expression of MPs. In this work, we utilize deep mutational scanning data to train a series of artificial neural networks to predict the effects of mutations on the PME of the G-protein coupled receptor (GPCR) rhodopsin from structural and/ or evolutionary features. We show that our best performing network, which we term PMEpred, can differentiate pathogenic rhodopsin variants that induce misfolding from those that primarily compromise signaling. This network also generates statistically significant predictions for the effects of mutations on the PME of another GPCR (β2 adrenergic receptor) but not for an unrelated voltage-gated potassium channel (KCNQ1). Notably, our analyses of these networks suggest structural features alone are generally sufficient to recapitulate the observed mutagenic trends. Moreover, our findings imply that networks trained in this manner may be generalizable to proteins that share a common fold. Implications of our findings for the design of mechanistically specific genetic predictors are discussed.
Identifying food fraud vulnerability factors in food fraud incidents – a review of global incidents 2000–2018
Authors: Rezazade Faeze , Summers Jane , Lai Teik Derek Ong 
Published: December 2021

PurposeGlobal food fraud incidents are regularly reported and are on the rise due to the ineffectiveness of traditional food safety intervention strategies. The increase in food fraud opportunity is prevalent in the state of the COVID-19 pandemic as well. Food fraud vulnerability assessment (FFVA) is acknowledged as a critical requirement by the Global Food Safety Initiatives (GFSIs) and the World Health Organisation for an effective food fraud mitigation plan. However, there is no clear direction or ways to identify and analyse food fraud vulnerability factors based on real-data.Design/methodology/approachCombining the barrier analysis technique and the routine activity theory to review the 580 cases of food fraud recorded in the Decernis database, this paper identified new food fraud vulnerability dimensions and insights pinpointed to three categories of opportunity, motivation and countermeasures.FindingsNew dimensions of food fraud vulnerability factors are identified in this paper over the period 2000–2018. Where possible, new insights related to each food fraud vulnerability factor and dimension were identified, and literature evidence was used to confirm their contribution.Originality/valueThere is a gap observed in the first step of FFVA in the literature. This paper is the first study to undertake a FFVA based on evidence recorded in a global food fraud database. This paper offers critical insights into global food fraud regulations by exploring the new emerging root causes of food fraud and analysing them, supporting developing effective food fraud prevention plans (FFPPs).
The effects of COVID-19 pandemic on the UK construction industry and the process of future-proofing business
Authors: Stride Mark , Renukappa Suresh , Suresh Subashini , Egbu Charles 
Published: December 2021

Purpose
COVID-19 was officially declared as a worldwide pandemic by the World Health Organisation on 11th March 2020, before the UK was put into lockdown on the 23rd March 2020. Organisations had to reconsider their policies and procedures to allow their businesses to continue. This paper aims to focus on the effects of COVID-19 that the UK construction sector has had to undertake to enable businesses while employees had to adhere to COVID-19 lockdown rules. In addition, how the sector can positively continue once normality has returned within the industry. In doing so, this paper understands the historical issues within the construction sector and has had an effect during COVID-19.

Design/methodology/approach
A qualitative research methodology approach was taken to help obtain live information. In total, 19 semi-structured interviews from 15 organisations related to the construction sector were conducted to collect data. This information was evaluated using thematic analysis to arrive at the results, inferences and recommendations to the sector.

Findings
This research has revealed that companies have had to adopt a three-stage process to overcome a new dimensional challenge of COVID-19. These include: 1. Making quick decisions during the first stage of the pandemic. 2. Producing new policies and procedures to restart businesses enabling staff to return to the workplace safely. 3. Implementing methods to future-proof organisations against any potential pandemics. To help organisations future-proof their business five C’s are recommended.

Originality/value
This paper provides a rich insight into the understanding and awareness of the effects of COVID-19 and the changes that the construction sector has had to undertake to adhere to the lockdown rules while remaining productive. This research contributes towards informing policymakers on some of the lessons learned during the management of the COVID-19 pandemic from a construction sector perspective.
Unified and non-ideal switch model for analysis of switching circuits
Authors: Pekdemir Alperen , Yildiz Ali Bekir 
Published: December 2021

Purpose
This paper aims to propose a new unified and non-ideal switch model for analysis of switching circuits.

Design/methodology/approach
The model has a single unified structure that includes all possible states (on, off) of the switches. The analysis with the proposed switch model requires only one topology and uses the single system equation regardless of states of switches. Moreover, to improve accuracy, the model contains the on-state resistance and capacitive effect of switches. The system equations and the states of switches are updated by control variables, used in the model.

Findings
There are no restrictions on circuit topology and switch connections. Switches can be internally and externally controlled. The non-ideal nature of the model allows the switch to be modeled more realistically and eliminates the drawbacks of the ideal switch concept. After modeling with the proposed switch model, a linear circuit is obtained. Two examples related to switching circuits are included into the study. The results confirm the accuracy of the model.

Originality/value
This paper contributes a different switch model for analysis of switching converters to the literature. The main advantage of the model is that it has a unified and non-ideal property. With the proposed switch model, the transient events, like voltage spikes and high-frequency noises, caused by inductor and capacitor elements at switching instants can be observed properly.