bluuebunny/crossref_metadata_2025 huggingface dataset:
TransporterPAL: An integrative database Transporter Prediction ALgorithm
Authors: Dyekjær Jane Dannow , Andersen Alexander Kruhøffer Bloch , Madsen Joel August Vest , Morth Jens Preben , Jensen Lars Juhl , Borodina Irina
Published: September 2022

Motivation

Natural products are used as drugs, cosmetic ingredients, pigments, flavors, and agricultural products. The compounds are retrievable as extracts from natural sources, but the yields are often low, and the final product may contain various impurities. These challenges can be solved by expressing the biosynthetic pathway in microbial cell factories and ensuring product secretion from the cell by using an appropriate transporter. However, insufficient knowledge of transporters for specific compounds often obstructs efficient secretion of the natural product. Therefore, our goal was to develop an algorithm that predicts transporters for a given compound using available public data.

Results

The web application TransporterPAL predicts suitable transporters for compounds by interconnecting data for biosynthetic genes and their interactions with transporters. The web application queries the STITCH, STRING, and UniProtKB databases via their respective APIs and returns a set of potential transporters based on a compound and, optionally, the organism as input. For a test set of 61 transporter systems, each containing one or more transporters, a total of 90 unique transporters with a known substrate, we could retrieve 45% of the transporters. To our knowledge, this is the first bioinformatics tool for predicting transporter candidates for a given molecule.

Availability

https://transporterpal.com

Contact

irbo@biosustain.dtu.dk

Supplementary information

Supplementary data are available at Bioinformatics online.
The relationship between spectral and plant diversity: disentangling the influence of metrics and habitat types
Authors: Michela Perrone , Mirko Di Febbraro , Luisa Conti , Jan Divíšek , Milan Chytrý , Petr Keil , Laura Carranza Maria , Duccio Rocchini , Michele Torresani , Vítězslav Moudrý , Petra Šímová , Dominika Prajzlerová , Jana Müllerová , Jan Wild , Marco Malavasi
Published: September 2022

Biodiversity monitoring is crucial for ecosystem conservation, yet field data collection is limited by costs, time, and extent. Remote sensing represents a convenient approach providing frequent, near-real-time information over wide areas. According to the Spectral Variation Hypothesis (SVH), spectral diversity (SD) is an effective proxy of environmental heterogeneity, which ultimately relates to plant diversity. So far, studies testing the relationship between SD and biodiversity have reported contradictory findings, calling for a thorough investigation of the key factors (e.g., metrics applied, ecosystem type) and the conditions under which such a relationship holds true. This study investigates the applicability of the SVH for plant diversity monitoring at the landscape scale by comparing the performance of three different types of SD metrics. Species richness and functional diversity were calculated for more than 2000 cells forming a grid covering the Czech Republic. Within each cell, we quantified SD using a Landsat-8 “greenest pixel” composite by applying: i) the standard deviation of NDVI, ii) Rao’s Q entropy index, and iii) richness of “spectral communities”. Habitat type (i.e., land cover) was included in the models describing the relationship between SD and ground biodiversity. Both species richness and functional diversity show positive and significant relationships with each SD metric tested. However, SD alone accounts for a small fraction of the deviance explained by the models. Furthermore, the strength of the relationship depends significantly on habitat type and is highest in natural transitional areas. Our results underline that, despite the stability in the significance of the link between SD and plant diversity at this scale, the applicability of SD for biodiversity monitoring is context-dependent and the factors mediating such a relationship must be carefully considered to avoid drawing misleading conclusions.

Highlights

Plant species richness and functional diversity show significant and positive relationships with spectral diversity

Spectral diversity alone explains a small fraction of the total variability in ground biodiversity

Slight differences among the performances of the spectral diversity metrics tested

The relationship between spectral and plant diversity is context-dependent
In vitro−in silico correlation of three-dimensional turbulent flows in an idealized mouth-throat model
Authors: Nof Eliram , Bhardwaj Saurabh , Koullapis Pantelis , Bessler Ron , Kassinos Stavros , Sznitman Josué
Published: September 2022

There exists an ongoing need to improve the validity and accuracy of computational fluid dynamics (CFD) simulations of turbulent airflows in the extra-thoracic and upper airways. Yet, a knowledge gap remains in providing experimentally-resolved 3D flow benchmarks with sufficient data density and completeness for useful comparison with widely-employed numerical schemes. Motivated by such shortcomings, the present work details to the best of our knowledge the first attempt to deliver in vitro−in silico correlations of 3D respiratory airflows in a generalized mouth-throat model and thereby assess the performance of Large Eddy Simulations (LES) and Reynolds-Averaged Numerical Simulations (RANS). Numerical predictions are compared against 3D volumetric flow measurements using Tomographic Particle Image Velocimetry (TPIV) at three steady inhalation flowrates varying from shallow to deep inhalation conditions. We find that a RANS k-ω SST model adequately predicts velocity flow patterns for Reynolds numbers spanning 1’500 to 7’000, supporting results in close proximity to a more computationally-expensive LES model. Yet, RANS significantly underestimates turbulent kinetic energy (TKE), thus underlining the advantages of LES as a higher-order turbulence modeling scheme. In an effort to bridge future endevours across respiratory research disciplines, we provide end users with the present in vitro −in silico correlation data for improved predictive CFD models towards inhalation therapy and therapeutic or toxic dosimetry endpoints.

Author Summary

The dispersion and ensuing deposition of inhaled airborne particulate matter in the lungs are strongly influenced by the dynamics of turbulent respiratory airflows in the mouth-throat region during inhalation. To cirumvent costly in vitro experimental measurement resources, fluid dynamics (CFD) simulations are widely sought to predict deposition outcomes but often lack detailed experimental data to first validate the three-dimensional (3D) flow structures anticipated to arise in the upper respiratory tract. In an effort to reconcile such data scarcity, we deliver experimental-numerical correlations of 3D respiratory airflows in an idealized 3D printed mouth-throat model against two widely-established numerical schemes with varying computational costs, namely coarse RANS and finer LES technique. Our time-resolved 3D flow data underline the complexity of these physiological inhalation flows, and discuss advantages and drawbacks of the different numerical techniques. With an outlook on future respiratory applications geared towards broad preclinical inhaled aerosol deposition studies, our open source data are made available for future benchmark comparisons for a broad range of end users in the respiratory research community.
Reduction of the HIV-1 reservoir in T cells from persons with HIV-1 on suppressive antiretroviral therapy using expanded natural killer cellsex vivo
Authors: Checkley Mary Ann , Luttge Benjamin G. , Dobrowolski Curtis , Wald David N. , McMahon Deborah , Haidar Ghady , Sobolewski Michele D. , Enick P. Nathan , Cyktor Joshua , Mellors John W. , Karn Jonathan
Published: September 2022

Treatment with latency-reversing agents (LRAs) alone has been ineffective in reducing HIV-1 reservoirs in persons with HIV-1 (PWH) on antiretroviral therapy (ART), due to inefficiencies in reservoir reactivation and adaptive immune responses. However, NK cells that are activated with cytokines may be able to target HIV-1 reservoirs more efficiently. To study the therapeutic potential of NK cells, we expanded blood NK cells from multiple donorsex vivointo CD56brightCD16+“eNK” cells using artificial antigen presenting cells (aAPCs) expressing membrane-bound IL21. eNK cells express multiple activating receptors and are highly cytotoxic against specific target cells. eNK cells can also kill HIV-infected CD4 T cells via antibody dependent cell-mediated cytotoxicity (ADCC) using broadly neutralizing antibodies against HIV-1 Env gp120/gp41. Importantly, eNK cells from PWH on ART efficiently killed autologous HIV-1+T cells reactivated by a combination of vorinostat (SAHA) and IL-15 or an IL-15 superagonist (N-803), as detected by declines in proviral load, inducible HIV-1 mRNA, and virus release. Adoptive immunotherapy with eNK cells is therefore a promising approach to reduce the latent HIV-1 reservoir in PWH when combined with LRA treatment.

Author Summary

Successful antiretroviral therapy (ART) eliminates progression to AIDS by reducing HIV to nearly indetectable levels by routine clinical measurements of blood samples. However, more sensitive DNA and RNA measurements show that most persons on ART retain a reservoir of long lived latently infected cells, which remain undetected by the immune system while no HIV is being produced. In nearly all cases, ART interruption results in a rebound of HIV production and spread, requiring an immediate return to ART. Currently the goal of HIV eradication is to achieve a “functional cure”, where HIV reservoirs are reduced to the point where ART can be interrupted indefinitely, and low levels of infected cells remaining can be controlled by the immune system. Our eradication strategy combines HIV latency-reversing agents (LRAs), ex vivo expansion of natural killer (NK) cells, and enhancement of specificity and killing of infected cells with broadly neutralizing antibodies against HIV. In this study, we have demonstrated that NK cells from person living with HIV can be isolated and expanded ex vivo into “eNK” cells that kill HIV-infected cells without killing uninfected cells, especially when broadly neutralizing antibodies are present, and can significantly reduce HIV reservoirs after LRA treatment.
Oocyte and cumulus cell cooperativity and metabolic plasticity under the direction of oocyte paracrine factors
Authors: Richani Dulama , Poljak Anne , Wang Baily , Mahbub Saabah B. , Biazik Joanna , Campbell Jared M. , Habibalahi Abbas , Stocker William A. , Marinova Maria B. , Nixon Brett , Bustamante Sonia , Skerrett-Byrne David , Harrison Craig A. , Goldys Ewa , Gilchrist Robert B.
Published: September 2022

Mammalian oocytes develop and mature in a mutually dependent relationship with surrounding cumulus cells. The oocyte actively regulates cumulus cell differentiation and function by secreting soluble paracrine oocyte-secreted factors (OSFs). We characterized the molecular mechanisms by which two model OSFs, cumulin and BMP15, regulate oocyte maturation and cumulus-oocyte cooperativity. Exposure to these OSFs during maturation altered the proteomic and multispectral autofluorescence profiles of both the oocyte and cumulus cells. In oocytes, cumulin significantly upregulated proteins involved in nuclear function. In cumulus cells, both OSFs elicited marked upregulation of a variety of metabolic processes (mostly anabolic), including lipid, nucleotide, and carbohydrate metabolism, while mitochondrial metabolic processes were downregulated. The mitochondrial changes were validated by functional assays confirming altered mitochondrial morphology, respiration, and content, whilst maintaining ATP homeostasis. Collectively, these data demonstrate that OSFs remodel cumulus cell metabolism during oocyte maturation in preparation for ensuing fertilization and embryonic development.

HIGHLIGHTS

During oocyte maturation, oocyte-secreted factors promote cell cooperativity between the oocyte and cumulus cells by altering the molecular composition of both cell types.

Oocyte-secreted factors downregulate protein catabolic processes, and upregulate DNA binding, translation, and ribosome assembly in oocytes.

Oocyte-secreted factors alter mitochondrial number, morphology, and function in cumulus cells.

Oocyte-secreted factors further enhance metabolic plasticity in cumulus cells by upregulating anabolic pathways for macromolecules and small molecule organics.

The oocyte, via oocyte-secreted factors, instructs cumulus cells to increase metabolic workload on its behalf, thereby subduing oocyte metabolism.
First detection ofIxodiphagus hookeri(Hymenoptera: Encyrtidae) inIxodes ricinusticks (Acari: Ixodidae) from multiple locations of Hungary
Authors: Tóth Adrienn Gréta , Farkas Róbert , Gyurkovszky Mónika , Krikó Eszter , Solymosi Norbert
Published: September 2022

The parasiotid wasp,Ixodiphagus hookeri(Hymenoptera: Encyrtidae) is the natural enemy of a wide range of hard and soft tick species. While these encyrtid wasps are supposed to be distributed worldwide, only few studies report about its actual appearance patterns around the globe. Within a shotgun sequencing based metagenome analysis, the occurrence ofI. hookeriwas screened at multipleIxodes ricinus(Acari: Ixodidae) tick sampling points of Hungary, to contribute to the assessment of the appearance patterns of the parasitoid wasps in Central Europe. To our knowledge, the first report of the species in Hungary and the description of the southernmostI. hookeriassociated geoposition in Central Europe took place within our study.I. hookeriinfestedI. ricinusnymphs were detected at five sampling points of Hungary. The results show that the exact distribution range ofI. hookeriis still barely studied. At the same time, unprecedented public health issues being brought by climate change might require steps towards the exploitation of the tick biocontrol potential or ecological bioindicator role of the parasitoid wasp in the future.
Striatal ups or downs? Neural correlates of monetary reward anticipation, cue reactivity and their interaction in alcohol use disorder and gambling disorder
Authors: van Timmeren Tim , van Holst Ruth J. , Goudriaan Anna E.
Published: September 2022

Striatal dysfunction is a key characteristic of addictive disorders, but neuroimaging studies have reported conflicting findings. An integrative model of addiction points to the presence or absence of addiction-related cues as an explanation for striatal hypo-or hyperactivations, respectively, but has never been directly tested. Here, we developed a novel paradigm to investigate striatal activation during monetary reward anticipation in the presence versus absence of addiction-related pictures using functional MRI. Across two studies, we compared 46 alcohol use disorder (AUD) patients with 30 matched healthy controls; and 24 gambling disorder (GD) patients with 22 matched healthy controls. During monetary reward anticipation, hypoactivation of the reward system was seen in AUD individuals compared to HCs. Additionally, a behavioral interaction was seen where gambling cues made participants, across groups, respond faster for bigger, but slower for smaller rewards. However, no striatal differences were seen between the participants with AUD or GD and their matched controls. In sum, these findings suggest that striatal dysfunction is a key but heterogeneous mechanism within both AUD and GD and indicates an important but complex role for addiction-related cues in explaining striatal dysfunction in addiction.
Design principles for selective polarization of PAR proteins by cortical flows
Authors: Illukkumbura Rukshala , Hirani Nisha , Borrego-Pinto Joana , Bland Tom , Ng KangBo , Hubatsch Lars , McQuade Jessica , Endres Robert G. , Goehring Nathan W.
Published: September 2022

Clustering of membrane-associated molecules is thought to promote interactions with the actomyosin cortex, enabling size-dependent transport by actin flows. Consistent with this model, in the C. elegans zygote, anterior segregation of the polarity protein PAR-3 requires oligomerization. However, through direct assessment of advection of PAR proteins, we not only find no links between PAR-3 advection and oligomer size, but also observe efficient advection of both anterior and posterior PAR proteins. Consequently, differential cortex engagement cannot account for selective size-dependent PAR protein transport. Instead, combining experiment and theory we demonstrate that segregation efficiency of PAR proteins by cortical flow is determined by the stability of membrane association, which is enhanced by clustering and specifies persistence of transport. Indeed, stabilizing membrane association was sufficient to invert polarity of a normally posterior PAR protein. Our data therefore indicate that advection of membrane-associated proteins is more pervasive than anticipated and thus cells must tune membrane association dynamics to achieve differential transport by cortical flows.
Reconstitution of a minimal ESX-5 type VII secretion system suggests a role for PPE proteins in outer membrane transport of proteins
Authors: Bunduc C. M. , Ding Y. , Kuijl C. , Marlovits T. C. , Bitter W. , Houben E.N.G.
Published: September 2022

Mycobacteria utilize type VII secretion systems (T7SSs) to secrete proteins across their highly hydrophobic and diderm cell envelope. Pathogenic mycobacteria have up to five different T7SSs, called ESX-1 to ESX-5, which are crucial for growth and virulence. Here, we use a functionally reconstituted ESX-5 system in the avirulent speciesMycobacterium smegmatisthat lacks ESX-5, to define the role of eachesx-5gene in system functionality. By creating an array of gene deletions and assessing protein levels of components and membrane complex assembly, we observed that only the five components of the inner membrane complex are required for its assembly. However, in addition to these five core components, active secretion also depends on both the Esx and PE/PPE substrates. Tagging the PPE substrates followed by subcellular fractionation, surface labeling and membrane extraction showed that these proteins localize to the mycobacterial outer membrane. This indicates that they could play a role in secretion across this enigmatic outer barrier. These results provide a first full overview of the role of eachesx-5gene in T7SS functionality.
Glucose oxidation and nutrients availability drive neural crest development
Authors: Nekooie-Marnany Nioosha , Fodil Redouane , Féréol Sophie , Depp Marine , Motterlini Roberto , Foresti Roberta , Duband Jean-Loup , Dufour Sylvie
Published: September 2022

Bioenergetic metabolism is a key regulator of cellular function and signaling activity but the exact roles of nutrient utilization and energy production in embryonic development remain unknown. Here we investigated the metabolic pathways and deciphered the role of carbon metabolism required for the development of neural crest cells (NCC), a migratory stem cell population of the vertebrate embryo. We uncovered that glucose oxidation constitutes the prominent metabolic signature of trunk NCC and supports their delamination, migration, and proliferation. Additionally, we found that glycolysis, mitochondrial respiration and the pentose phosphate pathway are all mobilized downstream of glucose uptake. These metabolic pathways do not support specific cellular processes but cooperate and are integrated to accomplish epithelium-to-mesenchyme transition, adhesion, locomotion and proliferation. Moreover, using different nutrient supplies (glucose vs. pyruvate) we show that glucose is crucial to modulate NCC migration and adaptation to environmental stiffness, control NCC stemness and drive their fate decisions through regulation of specific gene expression. Our data establish that NCC development is instructed by metabolic cues that mobilize defined metabolic pathways cooperating together in response to nutrient availability.

SUMMARY STATEMENT

Here we show that neural crest cell migration and fate decisions rely primarily on glucose oxidation for energy production and mobilize multiple cooperating metabolic pathways for their biosynthetic needs and execution of gene programs.
Sleep spindle maturation enhances slow oscillation-spindle coupling
Authors: Joechner Ann-Kathrin , Hahn Michael A. , Gruber Georg , Hoedlmoser Kerstin , Werkle-Bergner Markus
Published: September 2022

The synchronization of canonical fast sleep spindle activity (12.5-16 Hz) precisely during the slow oscillation up peak is considered an essential feature of adult non-rapid eye movement sleep. However, there is little knowledge on how this well-known coalescence between slow oscillations and sleep spindles develops. Leveraging individualized detection of single events, we first provide a detailed cross-sectional characterization of age-specific patterns of slow and fast sleep spindles, slow oscillations, and their coupling in children aged 5 to 6, 8 to 11, and 14 to 18 years. Critically, based on this, we then investigated how spindle and slow oscillation maturity substantiate age differences in their precise orchestration. While the predominant type of fast spindles was development-specific in that it was still nested in a frequency range below the canonical fast spindle range for the majority of children, the well-known slow oscillation-spindle coupling pattern was evident for sleep spindles in the canonical (adult-like) fast spindle range in all three age groups – but notably less precise in children. To corroborate these findings, we linked personalized measures of fast spindle maturity, which indicate the similarity between the prevailing development-specific and adult-like fast spindles, and slow oscillation maturity, which reflects the extent to which slow oscillations show frontal dominance, with individual slow oscillation-spindle coupling patterns. Importantly, we found that fast spindle maturity was uniquely associated with enhanced slow oscillation-spindle coupling strength and precision. Taken together, our results suggest that the increasing ability to generate canonical fast sleep spindles actuates precise slow oscillation-spindle coupling patterns across child and adolescent development.
Self-generated brain-wide spiking cascades govern replay dynamics in the hippocampus
Authors: Yang Yifan , Leopold David A. , Duyn Jeff H. , Liu Xiao
Published: September 2022

During states of behavioral quiescence, neurons in the hippocampus replay sequences of spiking activity experienced in earlier behavioral episodes. While such replay sequences are hypothesized to serve learning and memory by facilitating synaptic consolidation, their generative mechanisms remain poorly understood. Increasing evidence suggests that they might be generated internally, or at least strongly constrained by internal circuit dynamics. Recent work demonstrated that, across the forebrain, approximately 70% of neurons participate in a pattern of sequential spiking cascades during rest. Like hippocampal replay sequences, these brain-wide spiking cascades occur together with high-frequency hippocampal ripples and therefore may share a common generative mechanism. Here we systematically investigated the relationship between replay activity and sequential spiking cascades by analyzing a database of intracortical electrocortical recordings in mice. For neuronal subpopulations in the hippocampus and visual cortex, we assessed spiking sequences elicited during video viewing as well as potential replay events during subsequent periods of rest. We found that replay events were unique to hippocampal time-sensitive neurons and occurred together with spiking cascades throughout the forebrain. Furthermore, forward and time-reversed replay sequences were associated with different types of spiking cascades. Overall, these findings indicate that hippocampal replay events are generated and structured according to resting state circuit dynamics manifest across a large portion of the brain.
Graph pangenome reveals functional, evolutionary, and phenotypic significance of human nonreference sequences
Authors: Wu Zhikun , Li Tong , Jiang Zehang , Zheng Jingjing , Liu Yun , Liu Yizhi , Xie Zhi
Published: September 2022

Thousands of DNA sequences in global populations are not present in the human reference genome, named nonreference sequence (NRS). Long-read sequencing (LRS) technologies enable better discovery of NRS with large length, particularly in repetitive regions. Here, wede novoassembled 539 genomes in five genetically divergent human populations sequenced by LRS technology and identified 5.1 million NRSs. These NRSs were merged into 45,284 nonredundant NRSs, of which 66.2% were novel. 78.5% of NRSs were repeat sequences, such as VNTR and STR. 38.7% of NRSs were common in the five populations, 35.6% were population specific, while 21.3% were ancestral and present in nonhuman primates. 144 NRS hotspots spanned 141 Mb of the human genome and many NRSs contained known functional domains or intersected with coding genes. Based on graph-based pangenome, we detected 565 transcript expression quantitative trait loci on NRSs, of which 467 were novel. We also detected 39 NRS candidates for adaptive selection within the human population related to the language system and diabetes. GWAS revealed 14 NRSs significantly associated with eight phenotypes, such as anaemia. Furthermore, we identified 154 NRSs in strong linkage disequilibrium with 258 phenotype-associated SNPs in the GWAS catalogue. Our work expands the landscape of human NRS and provides novel insights into functions of NRS to facilitate evolutionary and biomedical research.
SE(3) Equivalent Graph Attention Network as an Energy-Based Model for Protein Side Chain Conformation
Authors: Liu Deqin , Chen Sheng , Zheng Shuangjia , Zhang Sen , Yang Yuedong
Published: September 2022

Protein design energy functions have been developed over decades by leveraging physical forces approximation and knowledge-derived features. However, manual feature engineering and parameter tuning might suffer from knowledge bias. Learning potential energy functions fully from crystal structure data is promising to automatically discover unknown or high-order features that contribute to the protein’s energy. Here we proposed a graph attention network as an energy-based model for protein conformation, namely GraphEBM. GraphEBM is equivariant to the SE(3) group transformation, which is the important principle of modern machine learning for molecules-related tasks. GraphEBM was benchmarked on the rotamer recovery task and outperformed both Rosetta and the state-of-the-art deep learning based methods. Furthermore, GraphEBM also yielded promising results on combinatorial side chain optimization, improving 22.2% χ1 rotamer recovery to the PULCHRA method on average.
New structures of Class II Fructose-1,6-Bisphosphatase from Francisella tularensis suggest a novel catalytic mechanism for the entire Class
Authors: Selezneva Anna I. , Harding Luke N. M. , Gutka Hiten J. , Movahedzadeh Farahnaz , Abad-Zapatero Celerino
Published: September 2022

Class II Fructose-1,6-bisphosphatases (FBPaseII) (EC: 3.1.3.11) are highly conserved essential enzymes in the gluconeogenic pathway of microorganisms. Previous crystallographic studies of FBPasesII provided insights into various inactivated states of enzymes from different species. Presented here is the first crystal structure of FBPaseII in an active state, solved for the enzyme from Francisella tularensis (FtFBPaseII), containing native metal cofactor Mn2+ and complexed with catalytic product fructose-6-phosphate (F6P). Another crystal structure of the same enzyme complex is presented in inactivated state due to the structural changes introduced by crystal packing. Analysis of the interatomic distances among the substrate, product and divalent metal cations in the enzyme catalytic centers led to a revision of the catalytic mechanism suggested previously for class II FBPases. Instead of a metal cofactor for the stabilization of the transition state of the leaving phosphate group, we propose that the positive dipole of the neighboring α-helix backbone (G88-T89-T90-I91-T92-S93-K94) is responsible for retaining the cleaved phosphate. The revised catalytic mechanism involves a nucleophilic attack by a reactive water coordinated by both the T89 hydroxyl and a second water molecule coordinated directly by Mn2+. Additionally, a crystal structure of Mycobacterium tuberculosis FBPaseII (MtFBPaseII), containing the substrate fructose-1,6-bisphosphate (F1,6BP) bound, is presented in support of a novel catalytic mechanism for this class of enzymes.
Contributing Factors to Dietary Quality and Food Security in Low-Income Households with Children in the United States: A Scoping Review
Authors: Keown Denise Mc , Graves Lisa , McGowan Bethany , Eicher-Miller Heather A.
Published: September 2022

Background

Low income and food insecure households are at risk of poor dietary quality and food insecurity. Especially in childhood, consuming a nutritionally adequate diet is an essential driver of health, growth, and development. Prior research has shown many household-level factors can present challenges to support the nutritional needs of the members of low income and food insecure households.

Objective

The aim of the scoping review is to identify the contributing factors to dietary quality and food security in U.S. households of school-aged children and synthesize the evidence.

Methods

The scoping review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols Extension for Scoping Reviews (PRISMA-ScR) using search terms addressing food insecurity, low-income and dietary behaviors in the database PubMed (NCBI). Screening by 3 independent reviewers at the title, abstract, and full study phases identified forty-three studies included in the review.

Results

The studies addressed six themes: parental behaviors, child/adolescent behaviors, food procurement behaviors, food preparation behaviors, and psychosocial factors. Most studies were cross-sectional (n = 40, 93%) and focused on parental behaviors (n = 24, 56%), followed by food procurement behaviors, and food preparation behaviors.

Conclusion

The findings can be used to inform the development of future nutritional education interventions aimed at improving the dietary quality and food security in households with children. The themes identified were interrelated and suggest that providing parents with education on the following topics: 1) the importance of modeling positive eating behaviors in the home, 2) approaches to support and encourage positive feeding practices with their children, and 3) practical strategies to overcome barriers to purchasing and preparing foods of high nutrient quality. For example, delivering educational sessions on meal selection and preparation and improving nutritional knowledge hold promise to improve dietary quality among food insecure and low-income households.
Inference of core needle biopsy whole slide images requiring definitive therapy for prostate cancer
Authors: Tsuneki Masayuki , Abe Makoto , Ichihara Shin , Kanavati Fahdi
Published: September 2022

Prostate cancer is often a slowly progressive indolent disease. Unnecessary treatments from overdiagnosis are a significant concern, particularly low-grade disease. Active surveillance has being considered as a risk management strategy to avoid potential side effects by unnecessary radical treatment. In 2016, American Society of Clinical Oncology (ASCO) endorsed the Cancer Care Ontario (CCO) Clinical Practice Guideline on active surveillance for the management of localized prostate cancer. Based on this guideline, we developed a deep learning model to classify prostate adenocarcinoma into indolent (applicable for active surveillance) and aggressive (necessary for definitive therapy) on core needle biopsy whole slide images (WSIs). In this study, we trained deep learning models using a combination of transfer, weakly supervised, and fully supervised learning approaches using a dataset of core needle biopsy WSIs (n=1300). We evaluated the models on a test set (n=645), achieving ROC-AUCs 0.846 (indolent) and 0.980 (aggressive). The results demonstrate the promising potential of deployment in a practical prostate adenocarcinoma histopathological diagnostic workflow system.
Divergence in bacterial ecology is reflected by difference in population genetic structure, phage-predator load and host range
Authors: Cahier Karine , Piel Damien , Barcia-Cruz Rubén , Goudenège David , Wegner K. Mathias , Monot Marc , Romalde Jesús L , Roux Frédérique Le
Published: September 2022

Phages depend on their bacterial host to replicate, but how habitat, density and diversity of the host population drive phage ecology is not well understood. Here, we addressed this question by comparing two populations of marine bacteria and their phages collected during a time series sampling in an oyster farm.Vibrio crassostreaereproduces more specifically in oysters. This population is genetically structured into clades of near clonal strains favoring infection by closely related phages and leading to a modular structure of the phage-bacterial infection network.Vibrio chagasii, on the other hand, blooms in the water column from where it can colonize oysters via filter-feeding. We found higher phage predation pressure onV. chagasiithat did not result from a broader host range of the phages but rather from a greater burst size generating more infectious particles in the environment. We showed that contrasting patterns of genetic diversity for host and phage lead to different infection network architectures. We also provided evidence that a bloom of phages generates epigenetic and genetic variability that can be selected to counteract host defense systems.
A qualitative study of food choice behaviors among college students with food allergies in the US
Authors: Lee Yee Ming , Sozen Erol , Wen Han
Published: September 2022

Purpose

This study explored how food allergies have affected food-related behaviors and quality of life of college students with food allergies and identified factors influencing food choice decisions among this group of individuals.

Design/methodology/approach

One-on-one interviews were conducted with 26 college students with self-reported or clinically diagnosed food allergies, recruited from two universities located in the southern region of the United States. The participants were asked a series of questions based on a semi-structured discussion guide. Each interview lasted about 30 min; all interviews were audio-recorded and transcribed verbatim. The transcriptions were coded independently by three researchers, and themes were identified.

Findings

Food allergies affected the participants' food-related behaviors, including eating, food preparation and shopping, as well as some aspects of their quality of life. Individual factors, such as mood, other diseases, cultural background and sensory properties, also influenced food choices. Friends and families were the two most important social influencers of food choices. Regarding physical environmental factors, cost, convenience, value and variety were considered important in selecting food. However, the participants' food choices were less influenced by food advertisements and social media. Additionally, experiences and complex cuisines were also key factors in making food choices.

Research limitations/implications

Theoretically, this qualitative study applied a food choice decision framework in the context of college students with food allergies. Practical recommendations are provided, particularly to campus dining facilities, to fulfill the needs of college students with food allergies.

Originality/value

This study advanced the understanding of the complexity of food choice decision-making among college students with food allergies. A path diagram specific to food choice among college students with food allergies was developed based on the results of this study. This study also highlighted that food allergy management would involve various behavioral changes and revealed that the food choices are influenced by a wide range of factors.
Missing data estimates related to soybean production in the state of Mato Grosso, Brazil, from 1990 to 2018
Authors: Ribeiro João Gabriel , Piedade Sônia Maria de Stefano
Published: September 2022

Purpose

The state of Mato Grosso represents the largest producer and exporter of soybeans in Brazil; given this importance, it was aimed to propose to use the univariate imputation tool for time series, through applications of splines interpolations, in 46 of its municipalities that had missing data in the variables soybean production in thousand tons, production value and soy derivatives in R$ thousand, and also to assess the differences between the observed series and those with imputed values, in each of these municipalities, in these variables.

Design/methodology/approach

The proposed methodology was based on the use of the univariate imputation method through the application of cubic spline interpolation in each of the 46 municipalities, for each of the 3 variables. Then, for each municipality, the original series were compared with each observed series plus the values imputed in these variables by the Quenouille test of correlation of time series.

Findings

It was observed that, after imputation, all series were compared with those observed and are equal by the Queinouille test in the 46 municipalities analyzed, and the Wilcoxon test also showed equality for the accumulated total of the three variables involved with the production of soybeans. And there were increases of 5.92%, 3.58% and 2.84% for soy production, soy production value and soy derivatives value accumulated in the state after imputation in the 46 municipalities.

Originality/value

The present research and its results facilitate the process of estimates and monitoring the total soy production in the state of Mato Grosso and its municipalities from 1990 to 2018.
Identification of urban-rural integration types in China – an unsupervised machine learning approach
Authors: Zeng Qiyan , Chen Xiaofu
Published: September 2022

Purpose

Development of urban-rural integration is essential to fulfill sustainable development goals worldwide, and comprehension about urban-rural integration types has been highlighted as increasingly relevant for an efficient policy design. This paper aims to utilize an unsupervised machine learning approach to identify urban-rural integration typologies based on multidimensional metrics regarding economic, population and social integration in China.

Design/methodology/approach

The study introduces partitioning around medoids (PAM) for the identification of urban-rural integration typologies. PAM is a powerful tool for clustering multidimensional data. It identifies clusters by the representative objects called medoids and can be used with arbitrary distance, which help make clustering results more stable and less susceptible to outliers.

Findings

The study identifies four clusters: high-level urban-rural integration, urban-rural integration in transition, low-level urban-rural integration and early urban-rural integration in backward stage, showing different characteristics. Based on the clustering results, the study finds continuous improvement in urban-rural integration development in China which is reflected by the changes in the predominate type. However, the development still presents significant regional disparities which is characterized by leading in the east regions and lagging in the western and central regions. Besides, achievement in urban-rural integration varies significantly across provinces.

Practical implications

The machine learning techniques could identify urban-rural integration typologies in a multidimensional and objective way, and help formulate and implement targeted strategies and regionally adapted policies to boost urban-rural integration.

Originality/value

This is the first paper to use an unsupervised machine learning approach with PAM for the identification of urban-rural integration typologies from a multidimensional perspective. The authors confirm the advantages of this machine learning techniques in identifying urban-rural integration types, compared to a single indicator.
Double-wall pipe-type power-frequency electromagnetic heating device with diversion ring and its heating mode optimization
Authors: Zhou Feng , Wang Zixuan , Zhao Yuxiang
Published: September 2022

Purpose

The purpose of this paper is to study the pipe-type electromagnetic induction heating device under power frequency condition.

Design/methodology/approach

To reduce eddy current loss and improve heating efficiency, the structure of a pipe-type power-frequency electromagnetic heating device was optimized. Based on the maximum load flow formula, a parallel excitation winding structure is designed, and the distribution of electromagnetic field under four different powers is analyzed by simulation. Four heating modes were proposed according to the structure of diversion ring, inner wall and outer wall. Two heating modes with better heating effect were obtained by comprehensively considering the factors such as magnetic field distribution, thermal power and energy consumption.

Findings

The double-wall structure of the pipe-type electromagnetic heating device can make the heat source distribution more uniform, and the use of power-frequency power supply can increase security, the installation of diversion ring can make the heating more sufficient and the heating efficiency of the two heating methods selected according to the structural performance is more than 90%.

Originality/value

In view of the medium or high frequency of pipe-type electromagnetic heating device, it is necessary to configure high power electronic frequency conversion drive system, and eddy current can only be produced on the tube wall, resulting in uneven distribution of heat sources. A pipe-type power-frequency electromagnetic heating device with double-wall structure was proposed.
Evolutionary mechanism of green innovation behavior in construction enterprises: evidence from the construction industry
Authors: Li Xingwei , Liu Xiang , Huang Yicheng , Li Jingru , He Jinrong , Dai Jiachi
Published: September 2022

Purpose

The green innovation behavior of construction enterprises is the key to reducing the construction industry's carbon emissions and realizing the green transformation of the construction industry. The purpose of this study is to reveal the evolutionary mechanism of green innovation behavior in construction enterprises.

Design/methodology/approach

This study is based on resource-based theory, Porter's hypothesis and signaling theory. First, a measurement model of the green innovation behavior of construction enterprises was constructed from three aspects: environmental regulation, enterprise resources and public opinion through hierarchical analysis. Then, the state values of the measurement model of green innovation behavior of construction enterprises were calculated through the time series data from 2011–2018. Finally, the Markov chain model was used to predict the evolutionary trend of green innovation behavior of construction enterprises, and the accuracy of the prediction effect of the Markov chain model was verified using the time series data of 2019.

Findings

The Markov chain model of green innovation behavior of construction enterprises constructed in this study has high accuracy. This model finds that the transition of the growth state of green innovation behavior in China's construction industry is fluid and predicts the evolution trend of the innovation behavior of construction enterprises. In the future, the green innovation behavior of construction enterprises has a probability of 70.17% to be in a continuous growth state and 40.27% to be in a rapid growth state.

Originality/value

Based on the Markov chain model of green innovation behavior of construction enterprises, this study finds that the transition of the growth state of green innovation behavior of construction enterprises in China has the characteristics of liquidity. In addition, it reveals the development process of the green innovation behavior of construction enterprises from 2011–2018 and predicts the evolution trend of the green innovation behavior of construction enterprises.
Flow mechanism of Gaussian light-induced vortex motion inside a nanofluid droplet
Authors: Liu Zhe , Yu Zexiong , Wang Leilei , Chen Li , Cui Haihang , Sun Bohua
Published: September 2022

Purpose

The purpose of this study is to use a weak light source with spatial distribution to realize light-driven fluid by adding high-absorbing nanoparticles to the droplets, thereby replacing a highly focused strong linear light source acting on pure droplets.

Design/methodology/approach

First, Fe3O4 nanoparticles with high light response characteristics were added to the droplets to prepare nanofluid droplets, and through the Gaussian light-driven flow experiment, the Marangoni effect inside a nanofluid droplet was studied, which can produce the surface tension gradient on the air/liquid interface and induce the vortex motion inside a droplet. Then, the numerical simulation method of multiphysics field coupling was used to study the effects of droplet height and Gaussian light distribution on the flow characteristics inside a droplet.

Findings

Nanoparticles can significantly enhance the light absorption, so that the Gaussian light is enough to drive the flow, and the formation of vortex can be regulated by light distribution. The multiphysics field coupling model can accurately describe this problem.

Originality/value

This study is helpful to understand the flow behavior and heat transfer phenomenon in optical microfluidic systems, and provides a feasible way to construct the rapid flow inside a tiny droplet by light.
Conceptualizing “classroom teaching-learning process” that engages students in Indian business school
Authors: Kumar Ajit
Published: September 2022

Purpose

Case-based classroom teaching-learning process (hereafter, case method) has provided a very productive teaching-learning environment for a long time. In the case method, students are expected to meet some prerequisites, such as reading and analyzing the case in advance, listening to the classroom discussion and actively participating in the discussion. However, it is frequently reported in Indian business schools that students do not prepare the assigned case before the scheduled class. The under-preparation of cases results in low-quality discussion, high absenteeism, passive attitude and lack of energy.

Design/methodology/approach

This study modeled the case method using an IGEO (input-guide-enablers-output, commonly used in any process modeling) framework to identify challenges in the case-based classroom teaching-learning process. A novel customized classroom teaching-learning process called the EPDE (explain, practice, discuss, explore) method replaced the case method. These two teaching-learning processes were used for teaching two groups of MBA students.

Findings

The novel EPDE method effectively addressed the case method challenges. It resulted in better learning outcomes in the Indian B-school context.

Originality/value

The purpose of the study is to examine the impact of an alternative to the traditional case study method in a college classroom among MBA students. Two points make this study original and unique: (1) The IGOE process modeling framework is used to model teaching-learning processes, such as the case and EPDE methods. Using IGOE for teaching-learning processes is unique and is not available in the literature and (2) the EPDE method is a novel concept.