bluuebunny/crossref_metadata_2025 huggingface dataset:
Detecting the Emergent or Re-Emergent COVID-19 Pandemic in a Country: Modelling Study of Combined Primary Care and Hospital Surveillance
Authors: Wilson Nick , Schwehm Markus , Verrall Ayesha J , Parry Matthew , Baker Michael G , Eichner Martin
Published: May 2020

Aims: We aimed to determine the effectiveness of surveillance using testing for SARS-CoV-2 to identify an outbreak arising from a single case of border control failure at a country level.
Methods: A stochastic version of the SEIR model CovidSIM v1.1 designed specifically for COVID-19 was utilised. It was seeded with New Zealand (NZ) population data and relevant parameters sourced from the NZ and international literature.
Results: For what we regard as the most plausible scenario with an effective reproduction number of 2.0, the results suggest that 95% of outbreaks from a single imported case would be detected in the period up to day 33 after introduction. At the time point of detection, there would be a median number of 6 infected cases in the community (95%UI: 1-68). To achieve this level of detection, an on-going programme of 7,800 tests per million people per week for the NZ population would be required. The vast majority of this testing (96%) would be of symptomatic cases in primary care settings and the rest in hospitals. Despite the large number of tests required, there are plausible strategies to enhance testing yield and cost-effectiveness eg, (i) adjusting the eligibility criteria via symptom profiles; (ii) and pooling of test samples.
Conclusions: This model-based analysis suggests that a surveillance system with a very high level of routine testing is probably required to detect an emerging or re-emerging SARS-CoV-2 outbreak within one month of a border control failure in a nation.
Is there a link between temperatures and COVID-19 contagions? Evidence from Italy
Authors: Rios Vicente , Gianmoena Lisa
Published: May 2020

This study analyzes the link between temperatures and COVID-19 contagions in a sample of Italian regions during the period ranging from February 24 to April 15. To that end, Bayesian Model Averaging techniques are used to analyze the relevance of the temperatures together with a set of additional climate, environmental, demographic, social and policy factors. The robustness of individual covariates is measured through posterior inclusion probabilities. The empirical analysis provides conclusive evidence on the role played by the temperatures given that it appears as the most relevant determinant of contagions. This finding is robust to (i) the prior distribution elicitation, (ii) the procedure to assign weights to the regressors, (iii) the presence of measurement errors in official data due to under-reporting, (iv) the employment of different metrics of temperatures or (v) the inclusion of additional correlates. In a second step, relative importance metrics that perform an accurate partitioning of the R2 of the model are calculated. The results of this approach support the evidence of the model averaging analysis, given that temperature is the top driver explaining 45% of regional contagion disparities. The set of policy-related factors appear in a second level of importance, whereas factors related to the degree of social connectedness or the demographic characteristics are less relevant.
Empiric model for short-time prediction of COVID-19 spreading
Authors: Catala Marti , Alonso Sergio , Alvarez Lacalle Enrique , Lopez Daniel , Cardona Pere-Joan , Prats Clara
Published: May 2020

Covid-19 appearance and fast spreading took by surprise the international community. Collaboration between researchers, public health workers and politicians has been established to deal with the epidemic. One important contribution from researchers in epidemiology is the analysis of trends so that both current state and short-term future trends can be carefully evaluated. Gompertz model has shown to correctly describe the dynamics of cumulative confirmed cases, since it is characterized by a decrease in growth rate that is able to show the effect of control measures. Thus, it provides a way to systematically quantify the Covid-19 spreading velocity. Moreover, it allows to carry out short-term predictions and long-term estimations that may facilitate policy decisions and the revision of in-place confinement measures and the development of new protocols. This model has been employed to fit the cumulative cases of Covid-19 from several Chinese provinces and from other countries with a successful containment of the disease. Results show that there are systematic differences in spreading velocity between countries. In countries that are in the initial stages of the Covid-19 outbreak, model predictions provide a reliable picture of its short-term evolution and may permit to unveil some characteristics of the long-term evolution. These predictions can also be generalized to short-term hospital and Intensive Care Units (ICU) requirements, which together with the equivalent predictions on mortality provide key information for health officials.
Magnesium maintains length of circadian period inArabidopsis thaliana
Authors: de Melo J. Romário F. , Gutsch Annelie , De Caluwé Joëlle , Leloup Jean-Christophe , Gonze Didier , Hermans Christian , Webb Alex A.R. , Verbruggen Nathalie
Published: May 2020

The circadian clock coordinates the physiological response of a biological system to day and night rhythms through complex loops of transcriptional/ translational regulation. It can respond to external stimuli and adjust generated circadian oscillations accordingly to keep an endogenous period close to 24 h. To date, the interaction between nutritional status and circadian rhythms in plants is poorly understood. Magnesium (Mg) is essential for numerous biological processes in plants and its homeostasis is crucial to maintain optimal development and growth. Magnesium deficiency in youngArabidopsis thalianaseedlings increased the circadian period ofpCCA1:LUCoscillations and dampened its amplitude in constant light in a dose-dependent manner. Although circadian period increase by Mg deficiency was light dependent, it did not depend on active photosynthesis. Mathematical modelling of the Mg input to the circadian clock reproduced the experimental increase of the circadian period and suggested that Mg is likely to affect global transcription/translation levels rather than a single component of the circadian oscillator. The model prediction was supported by a synergistic interaction between Mg deficiency and cyclohexamide, an inhibitor of translation. These findings suggest that proper Mg supply is required to support proper timekeeping in plants.

One sentence summary

Magnesium maintains the circadian period in Arabidopsis seedlings and interferes with the circadian oscillator most likely through translational mechanisms.
Global alignment and assessment of TRP channel transmembrane domain structures to explore functional mechanisms
Authors: Huffer Katherine E. , Aleksandrova Antoniya A. , Jara-Oseguera Andrés , Forrest Lucy R. , Swartz Kenton J.
Published: May 2020

The recent proliferation of published TRP channel structures provides a foundation for understanding the diverse functional properties of this important family of ion channel proteins. To facilitate mechanistic investigations, we constructed a structure-based alignment of the transmembrane domains of 120 TRP channel structures. Comparison of structures determined in the absence or presence of activating stimuli reveals similar constrictions in the central ion permeation pathway near the intracellular end of the S6 helices, pointing to a conserved cytoplasmic gate and suggesting that most available structures represent non-conducting states. Comparison of the ion selectivity filters towards the extracellular end of the pore supports existing hypotheses for mechanisms of ion selectivity. Also conserved to varying extents are hot spots for interactions with hydrophobic ligands, lipids and ions, as well as discrete alterations in helix conformations. This analysis therefore provides a framework for investigating the structural basis of TRP channel gating mechanisms and pharmacology, and, despite the large number of structures included, reveals the need for additional structural data and for more functional studies to establish the mechanistic basis of TRP channel function.
Magneto-optical diagnosis of symptomatic malaria in Papua New Guinea
Authors: Arndt Leandra , Koleala Tamarah , Orban Agnes , Ibam Clemencia , Timinao Lincoln , Lorry Lina , Butykai Adam , Kaman Peter , Molnar Andrea P , Krohns Stephan , Nate Elma , Kucsera Istvan , Orosz Erika , Moore Brioni R , Robinson Leanne J , Laman Moses , Kezsmarki Istvan , Karl Stephan
Published: May 2020

Improved methods for malaria diagnosis are urgently needed. Here, we tested a novel rotating-crystal magneto-optical diagnostic (RMOD) test in 964 suspected malaria patients in Papua New Guinea. RMOD tests can be obtained within minutes and at low cost. Capillary blood samples were also subjected to rapid diagnostic tests, expert light microscopy and polymerase chain reaction to systematically evaluate the capability of RMOD to detect infections. Compared to light microscopy, as the gold standard, RMOD exhibited 82% sensitivity and 84% specificity to detect any malaria infection. This increased to 87% sensitivity and 88% specificity for Plasmodium vivax, indicating that RMOD could be useful in P. vivax dominated elimination settings. Parasite density correlated well with the quantitative magneto-optical signal. Importantly, residual hemozoin present in malaria negative patients was also detectable by RMOD, indicating its ability to detect previous infections, which can be exploited to reveal transmission hotspots in low-transmission settings.
Knowledge of novel coronavirus (SARS-COV-2) among a Georgian population
Authors: Butsashvili Maia , Gulbiani Lasha , Kanchelashvili George , Kochlamazashvili Marika , Nioradze George , kamkamidze George
Published: May 2020

Introduction

Georgia confirmed its first case of SARS-COV-2 infection on February 26, 2020. Despite the government’s proactive measures during the early stages of the epidemic, number of new infections of SARS-COV-2 is increasing and by March 31, a total of 110 cases have been reported. Limited understanding about epidemics can lead to panic and disrupt public health efforts to contain transmission. Thus, it is very important to understand the perceptions of the population regarding the disease and perceived level of government preparedness to fight against the spread of infection. This study reports results of a survey designed to understand attitudes and knowledge regarding SARS-COV-2 virus among Georgian population, including health care workers (HCWs).

Materials and methods

The online survey was conducted using a Facebook advertisement. The target was the whole country and the language used was Georgian. We collected information on demographic data, knowledge of symptoms and transmission modes of coronavirus, perceived differences between coronavirus and influenza, availability of antiviral medication and vaccination. We also included questions to capture the Georgian population’s perceptions about government preparedness to combat the new coronavirus.

Results

The survey was open for three days (March 2–4, 2020). 5228 participants completed the survey. Of these, 40.3% were 25–45 years old and 58.2% were female. 20.7% of respondents had university degree and 10.3% were HCWs. For 25.8% of respondents, COVID-19 and influenza are the same diseases; 10.9% did not know if they are different. The majority correctly identified the transmission route and symptoms (96.9% and 98.0%, respectively). Regarding physical distancing, 13.2% indicated they would attend public events if needed even if they had COVID-19 symptoms. 19.1% think that Georgia is ready for COVID 19 epidemic, while according to 55% the county is not ready, but HCWs are trying hard to respond to this challenge properly. For 18% response is inadequate. There was no difference in knowledge between HCWs, non-HCWs and unemployed. 20% of HCWs as well as other study subjects believe that SARS-COV-2 vaccine and medications do exist but are simply not available in Georgia.

Conclusion

One in five Georgians believe that there is a vaccine and medication to treat coronavirus, but that it is not available in the country. Given that information regarding coronavirus is changing very rapidly, the need to reach people with time-sensitive educational messages as well as prevention strategies is vital.
COVID-19 Epidemic Forecast in Different States of India using SIR Model
Authors: Jakhar Mukesh , Ahluwalia P K , Kumar Ashok
Published: May 2020

The epidemiological data up to 12th May 2020 for India and its 24 states has been used to predict COVID-19 outbreak within classical SIR (Susceptible-Infected-Recovered) model. The basic reproduction number R0 of India is calculated to be 1.15, whereas for various states it ranges from 1.03 in Uttarakhand to 7.92 in Bihar. The statistical parameters for most of the states indicates the high significance of the predicted results. It is estimated that the epidemic curve flattening in India will start from the first week of July and epidemic may end in the third week of October with final epidemic size ~1,75,000. The epidemic in Kerala is in final phase and is expected to end by first week of June. Among Indian states, Maharashtra is severely affected where the ending phase of epidemic may occur in the second week of September with epidemic size of ~55,000. The model indicates that the fast growth of infection in Punjab is from 27th April 2020 to 2nd June 2020, thereafter, curve flattening will start and the epidemic is expected to finished by the first week of July with the estimated number of ~3300 infected people. The epidemic size of COVID-19 outbreak in Delhi, West Bengal, Gujrat, Tamil Nadu and Odisha can reach as large as 24,000, 18,000, 16,000, 13,000 and 11,000, respectively, however, these estimations may be invalid if large fluctuation of data occurs in coming days.
Mental health in the UK during the COVID-19 pandemic: early observations
Authors: Jia Ru , Ayling Kieran , Chalder Trudie , Massey Adam , Broadbent Elizabeth , Coupland Carol , Vedhara Kavita
Published: May 2020

Background:
Previous pandemics have resulted in significant consequences for mental health. Here we report the mental health sequela of the COVID-19 pandemic on the UK population and examine modifiable and non-modifiable explanatory factors associated with mental health outcomes. We focus on the short-term consequences for mental health, as reported during the first four-six weeks of social distancing measures being introduced.
Methods:
A community cohort study was conducted with adults aged ≥18 years recruited through a mainstream and social media campaign between 3/4/20-30/4/20. Consenting participants completed an online survey measuring depression, anxiety and stress and explanatory variables hypothesised to be related to these mental health outcomes.
Outcomes:
N=3097 eligible individuals participated. The cohort was predominantly female (85%); mean age forty-four years; 10% from minority ethnic groups; 50% described themselves as key-workers and 20% identified as having clinical risk factors putting them at increased risk of COVID-19. Mean scores for depression, stress and anxiety significantly exceeded population norms. Analysis of non-modifiable factors indicated that being younger and female were associated with all outcomes, with the final multivariable models accounting for 7-13% of variance. When adding modifiable factors, significant independent effects emerged for positive mood, perceived loneliness and worry about getting COVID-19 for all outcomes, with the final multivariable models accounting for 54-57% of variance.
Interpretation:
Increased psychological morbidity was evident in this UK cohort, with younger people and women at particular risk. Interventions targeting perceptions of: loneliness, risk of COVID-19, worry about COVID-19, and positive mood may be effective.
SARS-CoV-2 Detection in Different Respiratory Sites: A Systematic Review and Meta-Analysis
Authors: Mohammadi Abbas , Esmaeilzadeh Elmira , Li Yijia , Bosch Ronald J , Li Jonathan
Published: May 2020

Background: The accurate detection of SARS-CoV-2 through respiratory sampling is critical for the prevention of further transmission and the timely initiation of treatment for COVID-19. There is a diverse range of SARS-CoV-2 detection rates in reported studies, with uncertainty as to the optimal sampling strategy for COVID-19 diagnosis and monitoring.
Methods: We performed a systematic review and meta-analysis of studies comparing respiratory sampling strategies for the detection of SARS-CoV-2 RNA. The inclusion criteria were studies that assessed at least two respiratory sampling sites (oropharyngeal swab, nasopharyngeal swab, and sputum) in participants with COVID-19. The percentage positive tests were compared between sampling modalities by constructing a Z-test assuming independence and using the standard errors obtained from the random effects meta-analysis.
Findings: From 1039 total studies, we identified 11 studies that met our inclusion criteria, with SARS-CoV-2 testing results from a total of 3442 respiratory tract specimens. Compared to nasopharyngeal swab sampling, sputum testing resulted in significantly higher rates of SARS-CoV-2 RNA detection while oropharyngeal swab testing had lower rates of viral RNA detection. Earlier sampling after symptom onset was associated with improved detection rates, but the differences in SARS-CoV-2 RNA detection by sampling method was consistent regardless of the duration of symptoms.
Interpretation: The results support sputum sampling as a primary method of COVID-19 diagnosis and monitoring, and highlight the importance of early testing after symptom onset to increase the rates of COVID-19 diagnosis.
SPLUNC1: A Novel Marker of Cystic Fibrosis Exacerbations
Authors: Khanal Sara , Webster Megan , Niu Naiqian , Nunez Myra , Chupp Geoffrey , Slade Martin , Cohn Lauren , Sauler Maor , Gomez Jose L , Tarran Robert , Sharma Lokesh Kumar , DelaCruz Charles , Egan Marie , Laguna Theresa , Britto Clemente J
Published: May 2020

Acute pulmonary Exacerbations (AE) are episodes of clinical worsening in cystic fibrosis (CF), often precipitated by infection. Timely detection is critical to minimize the morbidity and lung function decline associated with acute inflammation during AE. We previously demonstrated that the airway protein Short Palate Lung Nasal epithelium Clone 1 (SPLUNC1) is regulated by inflammatory signals. Here, we investigated the use of SPLUNC1 fluctuations to diagnose and predict AE in CF.

We enrolled adult CF subjects from two independent cohorts to measure AE markers of inflammation in sputum and recorded clinical outcomes for a 1-year follow-up period.

SPLUNC1 levels were high in healthy control sputum (n=9, 10.7µg/mL), and significantly decreased in CF subjects without AE (n=30, 5.7µg/mL, p=0.016). SPLUNC1 levels were 71.9% lower during AE (n=14, 1.6µg/mL, p=0.0034) regardless of age, sex, CF-causing mutation, or microbiology findings. Cytokines Il-1β and TNFα were also increased in AE, whereas lung function did not consistently decrease. Stable CF subjects with lower SPLUNC1 levels were much more likely to have an AE at 60 days (Hazard Ratio: 11.49, Standard Error: 0.83, p=0.0033). Low-SPLUNC1 stable subjects remained at higher AE risk even one year after sputum collection (Hazard Ratio: 3.21, Standard Error: 0.47, p=0.0125). SPLUNC1 was transcriptionally downregulated by inflammatory cytokines and degraded by proteases increased in sputum during AE.

Our findings suggest that low sputum SPLUNC1 levels could detect subjects at increased risk of AE in order to guide early therapeutic interventions in CF.
Age-Related Colonic Mucosal Microbiome Community Shifts in Monkeys
Authors: Vemuri Ravichandra , Sherrill Chrissy , Davis Matthew , Kavanagh Kylie
Published: May 2020

Recent evidence suggests that gut microbiome changes that occur with age impact the health of the host. While it is known that the gut microbiome and physiological systems interact, the relationship between the microbiome in an aged body system remains to be clearly defined, particularly in the context of inflammation. Therefore, we aimed to evaluate systemic inflammation and the mucosal microbiome in young and old female vervet monkeys. Ascending colon mucosal biopsies and blood samples from healthy young and old monkeys were collected for 16S rRNA gene sequencing and cytokine analyses, respectively. To demonstrate microbial co-occurrence patterns, we used Kendall’s tau correlation measure of interactions between microbes. We found elevated levels of plasma MCP-1 and CRP in old monkeys, which are indicative of higher systemic inflammation. Microbiome analysis revealed increases in abundance of opportunistic pathobionts such as members of the Proteobacteria phylum in old monkeys. At the family level, abundances ofPrevotellaceaeandHelicobacteraceaewere higher in old monkeys than in young. We also found significantly lower Firmicutes to Bacteroidetes ratio (P= 0.03) and lower abundance of butyrate-producing microbes in old monkeys, consistent with a less healthy profile. Microbial community co-occurrence analysis revealed 13 nodes and 41 associations in the young monkeys, but only 12 nodes and 21 associations in the old monkeys. Our findings provided novel insights into systemic inflammation and gut microbial interactions, highlights the importance of the mucosal niche changes with age, and may facilitate further understanding of the decline in the stability of the microbial community with aging.
Resolving complex structures at oncovirus integration loci with conjugate graph
Authors: Jia Wenlong , Xu Chang , Li Shuai Cheng
Published: May 2020

Oncovirus integrations cause copy number variations (CNVs) and complex structural variations (SVs) on host genomes. However, the understanding of how inserted viral DNA impacts the local genome remains limited. The linear structure of the oncovirus integrated local genomic map (LGM) will lay the foundations to understand how oncovirus integrations emerge and compromise the host genome’ s functioning. We propose a conjugate graph model to reconstruct the rearranged local genomic map at integrated loci. Simulation tests prove the reliability and credibility of the algorithm. Applications of the algorithm to whole-genome sequencing data of Human papillomavirus (HPV) and hepatitis B virus (HBV)-infected cancer samples gained biological insights on oncovirus integrations. We observed five affection patterns of oncovirus integrations from the HPV and HBV-integrated cancer samples, including the exon loss, promoter gain, hyper-amplification of tumor gene, the viral cis-regulation inserted at the single intron and at the intergenic region. We found that the focal duplicates and host SVs are frequent in the HPV-integrated LGMs, while the focal deletions and complex virus SVs are prevalent in HBV-integrated LGMs. Furthermore, with the results yields from our method, we found the enhanced microhomology-mediated end joining (MMEJ) might lead to both HPV and HBV integrations, and conjectured that the HPV integrations might mainly occur during the DNA replication process. The conjugate graph algorithm code and LGM construction pipeline, available athttps://github.com/deepomicslab/FuseSV.

Key points

Conjugate graph model resolves complex local genomic strcuture at oncovirus integration loci.

Local genome maps reveal five affection patterns of oncovirus integrations.

Microhomology bases and small insertions are enriched at the junctions of structural variations and virus integrations.

HPV and HBV integrations may be induced by the enhanced microhomology-meditated mechanism.
Histone deposition pathways determine the chromatin landscapes of H3.1 and H3.3 K27M oncohistones
Authors: Sarthy Jay F. , Meers Michael P. , Janssens Derek H. , Henikoff Jorja G. , Feldman Heather , Paddison Patrick J. , Lockwood Christina M. , Vitanza Nicholas A. , Olson James M. , Ahmad Kami , Henikoff Steven
Published: May 2020

Lysine 27-to-methionine (K27M) mutations in the H3.1 or H3.3 histone genes are characteristic of pediatric diffuse midline gliomas (DMGs). These oncohistone mutations dominantly inhibit histone H3K27 trimethylation and silencing, but it is unknown how oncohistone type affects gliomagenesis. We show that the genomic distributions of H3.1 and H3.3 oncohistones in human patient-derived DMG cells are consistent with the DNA replication-coupled deposition of histone H3.1 and the predominant replication-independent deposition of histone H3.3. Although H3K27 trimethylation is reduced for both oncohistone types, H3.3K27M-bearing cells retain some domains, and only H3.1K27M-bearing cells lack H3K27 trimethylation. Neither oncohistone interferes with PRC2 binding. Using Drosophila as a model, we demonstrate that inhibition of H3K27 trimethylation occurs only when H3K27M oncohistones are deposited into chromatin and only when expressed in cycling cells. We propose that oncohistones inhibit the H3K27 methyltransferase as chromatin patterns are being duplicated in proliferating cells, predisposing them to tumorigenesis.
Effects of parity, blood progesterone, and non-steroidal anti-inflammatory treatment on the dynamics of the uterine microbiota of healthy postpartum dairy cows
Authors: Pascottini O. Bogado , Spricigo J. F. W. , Van Schyndel S. J. , Mion B. , Rousseau J. , Weese J. S. , LeBlanc S. J.
Published: May 2020

This study evaluated the effects of treatment with meloxicam (a non-steroidal anti-inflammatory drug), parity, and blood progesterone concentration on the dynamics of the uterine microbiome of clinically healthy postpartum dairy cows. Seven primiparous and 9 multiparous postpartum Holstein cows received meloxicam (0.5 mg/kg SC, n = 7 cows) once daily for 4 days (10 to 13 days in milk (DIM)) or were untreated (n = 9 cows). Endometrial cytology samples were collected by cytobrush at 10, 21, and 35 DIM, from which the metagenomic analysis was done using 16S rRNA gene sequence analysis. A radioimmunoassay was used to measure progesterone concentration in blood serum samples at 35 DIM and cows were classified as > 1 ng/mL (n = 10) or ≤ 1 ng/mL (n = 6). Alpha diversity for bacterial genera (Chao1, Shannon-Weiner, and Camargo’s evenness indices) were not affected by DIM, meloxicam treatment, parity, or progesterone category (P> 0.2). For beta diversity (genera level), principal coordinate analysis (Bray-Curtis) showed differences in microbiome between parity groups (P= 0.01).

There was lower overall abundance ofAnaerococcus, Bifidobacterium, Corynebacterium, Lactobacillus, Paracoccus, Staphylococcus, andStreptococcusand higher abundance ofBacillus, Fusobacterium, andNovosphingobiumin primiparous than multiparous cows (P< 0.05); these patterns were consistent across sampling days. Bray-Curtis dissimilarity did not differ by DIM at sampling, meloxicam treatment, or progesterone category at 35 DIM (P> 0.5). In conclusion, uterine bacterial composition was not different at 10, 21, or 35 DIM, and meloxicam treatment or progesterone category did not affect uterine microbiota in clinically healthy postpartum dairy cows. Primiparous cows presented a different composition of uterine bacteria than multiparous cows. The differences in microbiome associated with parity might be attributable to changes that occur consequent to the first calving, but this hypothesis should be investigated further.
Glycosaminoglycans are specific endosomal receptors forYersinia pseudotuberculosisCytotoxic Necrotizing Factor
Authors: Kowarschik Stefanie , Schöllkopf Julian , Müller Thomas , Tian Songhai , Knerr Julian , Bakker Hans , Rein Stephan , Dong Min , Weber Stefan , Grosse Robert , Schmidt Gudula
Published: May 2020

The Cytotoxic Necrotizing Factor Y (CNFY) is produced by the gram-negative, enteric pathogenYersinia pseudotuberculosis. The bacterial toxin belongs to a family of deamidases, which constitutively activate Rho GTPases, thereby balancing inflammatory processes. We identified heparan sulfate proteoglycans as essential host cell factors for intoxication with CNFY. Using flow cytometry, microscopy, knockout cell lines, pulsed electron–electron double resonance and bio-layer interferometry, we studied the role of glucosaminoglycans in the intoxication process of CNFY. To analyze toxin-glucosaminoglycan interaction we utilized a truncated CNFY (CNFY709-1014). Especially this C-terminal part of CNFY, which encompasses the catalytic activity, binds with high affinity to heparan sulfates. CNFY binding with the N-terminal domain to its protein receptor seems to induce a first conformational change supporting the interaction between the C-terminal domain and heparan sulfates, which seems sterically hindered in the full toxin. A second conformational change occurs by acidification of the endosome, probably allowing insertion of the hydrophobic regions of the toxin into the endosomal membrane. Our findings suggest that heparan sulfates play a major role for intoxication within the endosome, rather than being relevant for an interaction at the cell surface. Lastly, cleavage of heparin sulfate chains by heparanase is likely required for efficient uptake of the toxic enzyme into the cytosol of mammalian cells.

Author Summary

The RhoA deamidating Cytotoxic Necrotizing Factor Y (CNFY) fromYersinia pseudotuberculosisis a crucial virulence factor that is important for successful infection of mammalian cells by the pathogen. The mode of action by which CNFY is able to intoxicate cells can be divided into the following steps: Binding to the cell surface, internalization, translocation from the endosome to the cytosol and deamidation of RhoA. We show, that CNFY uses heparan sulfates to maximize the amount of molecules entering the cytosol. While not being necessary for toxin binding and uptake, the sugars hold a key role in the intoxication process. We show that CNFY undergoes a conformational change at a low endosomal pH, allowing the C-terminal domain to be released from the endosomal membrane by the action of heparanase. This study reveals new insights into the CNFY-host interaction and promotes understanding of the complex intoxication process of bacterial toxins.
Learning receptive field properties of complex cells in V1
Authors: Lian Yanbo , Almasi Ali , Grayden David B. , Kameneva Tatiana , Burkitt Anthony N. , Meffin Hamish
Published: May 2020

There are two distinct classes of cells in the primary visual cortex (V1): simple cells and complex cells. One defining feature of complex cells is their spatial phase invariance; they respond strongly to oriented grating stimuli with a preferred orientation but with a wide range of spatial phases. A classical model of complete spatial phase invariance in complex cells is the energy model, in which the responses are the sum of the squared outputs of two linear spatially phase-shifted filters. However, recent experimental studies have shown that complex cells have a diverse range of spatial phase invariance and only a subset can be characterized by the energy model. While several models have been proposed to explain how complex cells could learn to be selective to orientation but invariant to spatial phase, most existing models overlook many biologically important details. We propose a biologically plausible model for complex cells that learns to pool inputs from simple cells based on the presentation of natural scene stimuli. The model is a three-layer network with rate-based neurons that describes the activities of LGN cells (layer 1), V1 simple cells (layer 2), and V1 complex cells (layer 3). The first two layers implement a recently proposed simple cell model that is biologically plausible and accounts for many experimental phenomena. The neural dynamics of the complex cells is modeled as the integration of simple cells inputs along with response normalization. Connections between LGN and simple cells are learned using Hebbian and anti-Hebbian plasticity. Connections between simple and complex cells are learned using a modified version of the Bienenstock, Cooper, and Munro (BCM) rule. Our results demonstrate that the learning rule can describe a diversity of complex cells, similar to those observed experimentally.

Author summary

Many cortical functions originate from the learning ability of the brain. How the properties of cortical cells are learned is vital for understanding how the brain works. There are many models that explain how V1 simple cells can be learned. However, how V1 complex cells are learned still remains unclear. In this paper, we propose a model of learning in complex cells based on the Bienenstock, Cooper, and Munro (BCM) rule. We demonstrate that properties of receptive fields of complex cells can be learned using this biologically plausible learning rule. Quantitative comparisons between the model and experimental data are performed. Results show that model complex cells can account for the diversity of complex cells found in experimental studies. In summary, this study provides a plausible explanation for how complex cells can be learned using biologically plausible plasticity mechanisms. Our findings help us to better understand biological vision processing and provide us with insights into the general signal processing principles that the visual cortex employs to process visual information.
Controlling the SARS-CoV-2 Spike Glycoprotein Conformation
Authors: Henderson Rory , Edwards Robert J , Mansouri Katayoun , Janowska Katarzyna , Stalls Victoria , Gobeil Sophie , Kopp Megan , Hsu Allen , Borgnia Mario , Parks Rob , Haynes Barton F. , Acharya Priyamvada
Published: May 2020

The coronavirus (CoV) viral host cell fusion spike (S) protein is the primary immunogenic target for virus neutralization and the current focus of many vaccine design efforts. The highly flexible S-protein, with its mobile domains, presents a moving target to the immune system. Here, to better understand S-protein mobility, we implemented a structure-based vector analysis of available β-CoV S-protein structures. We found that despite overall similarity in domain organization, different β-CoV strains display distinct S-protein configurations. Based on this analysis, we developed two soluble ectodomain constructs in which the highly immunogenic and mobile receptor binding domain (RBD) is locked in either the all-RBDs ‘down’ position or is induced to display a previously unobserved in SARS-CoV-2 2-RBDs ‘up’ configuration. These results demonstrate that the conformation of the S-protein can be controlled via rational design and provide a framework for the development of engineered coronavirus spike proteins for vaccine applications.
Comprehensive analyses of 723 transcriptomes enhance genetic and biological interpretations for complex traits in cattle
Authors: Fang Lingzhao , Cai Wentao , Liu Shuli , Canela-Xandri Oriol , Gao Yahui , Jiang Jicai , Rawlik Konrad , Li Bingjie , Schroeder Steven G. , Rosen Benjamin D. , Li Cong-jun , Sonstegard Tad S. , Alexander Leeson J. , Van Tassell Curtis P. , VanRaden Paul M. , Cole John B. , Yu Ying , Zhang Shengli , Tenesa Albert , Ma Li , Liu George E.
Published: May 2020

By uniformly analyzing 723 RNA-seq data from 91 tissues and cell types, we built a comprehensive gene atlas and studied tissue specificity of genes in cattle. We demonstrated that tissue-specific genes significantly reflected the tissue-relevant biology, showing distinct promoter methylation and evolution patterns (e.g., brain-specific genes evolve slowest, whereas testis-specific genes evolve fastest). Through integrative analyses of those tissue-specific genes with large-scale genome-wide association studies, we detected relevant tissues/cell types and candidate genes for 45 economically important traits in cattle, including blood/immune system (e.g., CCDC88C) for male fertility, brain (e.g., TRIM46 and RAB6A) for milk production, and multiple growth-related tissues (e.g., FGF6 and CCND2) for body conformation. We validated these findings by using epigenomic data across major somatic tissues and sperm. Collectively, our findings provided novel insights into the genetic and biological mechanisms underlying complex traits in cattle, and our transcriptome atlas can serve as a primary source for biological interpretation, functional validation, studies of adaptive evolution, and genomic improvement in livestock.
Determining the impact of uncharacterized inversions in the human genome by droplet digital PCR
Authors: Puig Marta , Lerga-Jaso Jon , Giner-Delgado Carla , Pacheco Sarai , Izquierdo David , Delprat Alejandra , Gayà-Vidal Magdalena , Regan Jack F. , Karlin-Neumann George , Cáceres Mario
Published: May 2020

Despite the interest in characterizing genomic variation, the presence of large repeats at the breakpoints hinders the analysis of many structural variants. This is especially problematic for inversions, since there is typically no gain or loss of DNA. Here, we tested novel linkage-based droplet digital PCR (ddPCR) assays to study 20 inversions ranging from 3.1 to 742 kb flanked by inverted repeats (IRs) up to 134 kb long. Of those, we validated 13 inversions predicted by different genome-wide techniques. In addition, we obtained new experimental human population information across 95 African, European, and East Asian individuals for 16 inversions, including four already validated variants without high-throughput genotyping methods. Through comparison with previous data, independent replicates and both inversion breakpoints, we demonstrate that the technique is highly accurate and reproducible. Most studied inversions are widespread across continents, and their frequency is negatively correlated with genetic length. Moreover, all except two show clear signs of being recurrent, and we could better define the factors affecting recurrence levels and estimate the inversion rate across the genome. Finally, the generated genotypes have allowed us to check inversion functional effects, validating gene expression differences reported before for two inversions and finding new candidate associations. Therefore, the developed methodology makes it possible to screen these and other complex genomic variants quickly in a large number of samples for the first time, highlighting the importance of direct genotyping to assess their potential consequences and clinical implications.
Global fitness landscapes of the Shine-Dalgarno sequence
Authors: Kuo Syue-Ting , Jahn Ruey-Lin , Cheng Yuan-Ju , Chen Yi-Lan , Lee Yun-Ju , Hollfelder Florian , Wen Jin-Der , Chou Hsin-Hung David
Published: May 2020

Shine-Dalgarno sequences (SD) in prokaryotic mRNA facilitate protein translation by pairing with rRNA in ribosomes. Although conventionally defined as AG-rich motifs, recent genomic surveys reveal great sequence diversity, questioning how SD functions. Here, we determined the molecular fitness (i.e., translation efficiency) of 49 synthetic 9-nt SD genotypes in three distinct mRNA contexts in Escherichia coli. We uncovered generic principles governing the SD fitness landscapes: (1) Guanine contents, rather than canonical SD motifs, best predict the fitness of both synthetic and endogenous SD; (2) the genotype-fitness correlation of SD promotes its evolvability by steadily supplying beneficial mutations across fitness landscapes; and (3) the frequency and magnitude of deleterious mutations increase with background fitness, and adjacent nucleotides in SD show stronger epistasis. Epistasis results from disruption of the continuous base pairing between SD and rRNA. This “chain-breaking” epistasis creates sinkholes in SD fitness landscapes and may profoundly impact the evolution and function of prokaryotic translation initiation and other RNA-mediated processes. Collectively, our work yields functional insights into the SD sequence variation in prokaryotic genomes, identifies a simple design principle to guide bioengineering and bioinformatic analysis of SD, and illuminates the fundamentals of fitness landscapes and molecular evolution.
Femtosecond soft X-ray absorption spectroscopy of warm dense matter at the PAL-XFEL
Authors: Lee Jong-Won , Kang Gyeongbo , Kim Minju , Kim Minseok , Park Sang Han , Kwon Soonnam , Yang Seonghyeok , Cho Byoung Ick
Published: May 2020

Free-electron laser pulse-based X-ray absorption spectroscopy measurements on warm dense copper are presented. The incident X-ray pulse energies were measured with a detector assembly consisting of a photocathode membrane and microchannel plates, and the transmitted energies were measured simultaneously with a photodiode detector. The precision of the absorption measurements was evaluated. For a warm dense copper foil irradiated by an intense femtosecond laser pulse, the enhanced X-ray absorption below the L
3-edge, followed by the rapid evolution of highly excited Fermi liquid within a picosecond, were successfully measured. This result demonstrates a unique capability to study femtosecond non-equilibrium electron–hole dynamics in extreme states of matter.
Snack foods from brewing waste: consumer-led approach to developing sustainable snack options
Authors: Crofton Emily C. , Scannell Amalia G.M.
Published: May 2020

Purpose

Using a consumer-led approach, the purpose of this research is to examine how consumers perceive new cereal-based snack food concepts using healthy brewers spent grain (BSG) as a sustainable and functional ingredient.

Design/methodology/approach

In-depth laddering interviews based on means–end chain theory were conducted with 40 healthy snack consumers in Dublin, Ireland.

Findings

Four hierarchical value maps (HVM) representing data from each snack concept dimensions were generated. The results identified the crispy crackers concept as the most promising for further development, followed by crispy sticks with dip, fruity biscuits and twisted breadsticks. Consumer cognitions regarding the crispy sticks with dip and fruity biscuits were more dominantly associated with a hedonic orientation, while crispy crackers and twisted breadsticks were more strongly associated with health- related dimensions. The HVMs also identified factors which could potentially prevent the acceptance of these snacks. Although consumers displayed a level of environmental consciousness regarding the perceived packaging type, outcomes also showed that the environmental benefit of using BSG in foods is not viewed as a means to attain a desired end state in the consumers’ mind. Our findings also suggest the rich protein content of BSG is not considered relevant in the context of a cereal snack product.

Practical implications

BSG is an abundant, low-cost, nutritious waste material which is available globally in large quantities. This study provides new actionable consumer insights with important implications for snack manufacturers regarding the design and development of cereal snack foods containing this healthy by-product.

Originality/value

This study contributes to a limited body of literature by illustrating which product characteristics are considered important for consumers when selecting healthy, cereal-based snack foods using BSG as an ingredient.
An adaptive sparse polynomial-chaos technique based on anisotropic indices
Authors: Salis Christos , Kantartzis Nikolaos V. , Zygiridis Theodoros
Published: May 2020

Purpose

The fabrication of electromagnetic (EM) components may induce randomness in several design parameters. In such cases, an uncertainty assessment is of high importance, as simulating the performance of those devices via deterministic approaches may lead to a misinterpretation of the extracted outcomes. This paper aims to present a novel heuristic for the sparse representation of the polynomial chaos (PC) expansion of the output of interest, aiming at calculating the involved coefficients with a small computational cost.

Design/methodology/approach

This paper presents a novel heuristic that aims to develop a sparse PC technique based on anisotropic index sets. Specifically, this study’s approach generates those indices by using the mean elementary effect of each input. Accurate outcomes are extracted in low computational times, by constructing design of experiments (DoE) which satisfy the D-optimality criterion.

Findings

The method proposed in this study is tested on three test problems; the first one involves a transmission line that exhibits several random dielectrics, while the second and the third cases examine the effects of various random design parameters to the transmission coefficient of microwave filters. Comparisons with the Monte Carlo technique and other PC approaches prove that accurate outcomes are obtained in a smaller computational cost, thus the efficiency of the PC scheme is enhanced.

Originality/value

This paper introduces a new sparse PC technique based on anisotropic indices. The proposed method manages to accurately extract the expansion coefficients by locating D-optimal DoE.
How fringe cyclone experience affects predictions of damage severity
Authors: Scovell Mitchell , McShane Connar , Swinbourne Anne , Smith Daniel
Published: May 2020

Purpose

This paper aims to understand how experience with the fringe effects of a cyclone influences perception of cyclone severity. Understanding how certain types of experience influences risk perception should help to clarify why there is an unclear link between experience and risk perception within the existing literature.

Design/methodology/approach

A total of 155 respondents with fringe cyclone experience were recruited to fill in a closed-ended question survey. The survey was designed to assess perceptions of a previous cyclone and future cyclone severity.

Findings

Most respondents who had experienced the fringe effects of a cyclone overestimated the wind speed in their location. Respondents who overestimated previous cyclone wind speed also predicted less damage from future Category 5 cyclones.

Research limitations/implications

This research indicates that overestimating the severity of past cyclones can have a detrimental effect on how people predict damage due to high category cyclones.

Practical implications

The findings suggest that people with fringe cyclone experience need additional information to help reshape their perceptions of cyclone severity.

Originality/value

This paper provides a unique perspective on the relationship between experience and risk perception by demonstrating that experience on the fringe of a cyclone has a negative influence on risk perception.
Digital marketing and business-to-business relationships: a close look at the interface and a roadmap for the future
Authors: Hofacker Charles , Golgeci Ismail , Pillai Kishore Gopalakrishna , Gligor David Marius
Published: May 2020

Purpose

This study aims to introduce the special issue on digital marketing and business-to-business (B2B) relationships. In general, only modest attention has been devoted to the study of digitalization in the B2B sector and even less on the importance of the perils and promises of digitalization for B2B relationships. This study’s goal is to help focus scholarly attention on the implications of digitalization on B2B relationships.

Design/methodology/approach

In this conceptual paper, the authors’ approach is to carefully review relevant literature, and to lay out the field of digital marketing and B2B relationships, conceptualizing it for future research.

Findings

The authors find that the following areas are critically important to understanding future trends in digital marketing and B2B relationships: coopetition, value co-creation, B2B branding, servitization, innovation networks, relationship dynamics and power and trust.

Originality/value

The intersection of digitalization and B2B relationships is an under-researched topic. With this paper and the accompanying special issues papers, the authors hope to begin to fill this critical gap.