bluuebunny/crossref_metadata_2025 huggingface dataset:
Protea maturation rates and fire return intervals in a mediterranean ecosystem: testing the rules of thumb at a local scale
Authors: Geerts Sjirk
Published: October 2021

The appropriate fire return interval of prescribed burns is critical in many fire-driven systems. I use a mediterranean-type ecosystem – Cape fynbos, South Africa – to test guidelines for fire return intervals. Guidelines state that at least 50% of a population of the slowest-maturing obligate seeder Protea species must have flowered for three successive seasons, or that 90% of individuals from the slowest-maturing Protea species must have flowered at least once before a fire occurrence. Whether these ‘rules of thumb’ will lead to similar fire return intervals for prescribed burns is unknown. I address this by assessing two obligate seeding Protea species for length of juvenile period and age at three times flowering at 17 sites across a conservation area. For the slowest maturing species, when 50% of the fastest-maturing population had flowered three times (at 11 years), no individuals had flowered three times (happens at 14 years) in the slowest-maturing population. Using the 90% rule, this was reached at 9 years in the fastest-maturing P. neriifolia population and 11 years in the slowest-maturing. The 50% rule is more conservative than the 90% rule and is preferred. I highlight the importance of testing guidelines for fire return intervals to ensure effective biodiversity conservation.
HIF-1–regulated expression of calreticulin promotes breast tumorigenesis and progression through Wnt/β-catenin pathway activation
Authors: Liu Xiaoxu , Xie Peiling , Hao Na , Zhang Miao , Liu Yang , Liu Peijun , Semenza Gregg L. , He Jianjun , Zhang Huimin
Published: October 2021

Significance

Breast cancer stem cells (BCSCs) have the property of infinite self-renewal. When these cells divide, they give rise to one BCSC and one transient amplifying cell that can rapidly proliferate but only for a limited number of cell divisions. Only BCSCs can give rise to secondary (recurrent and/or metastatic) tumors. It is believed that breast cancer recurrence is due to the survival of a small number of BCSCs. Because the BCSCs represent a very small minority of cells within the primary tumor, their unique characteristics may not be detected by bulk tumor analyses. BCSCs are often located within regions of intratumoral hypoxia, and hypoxia-inducible factors activate the transcription of genes that promote BCSC specification and/or maintenance.
Innovating postverbal negation in North Africa
Authors: Lafkioui Mena B.
Published: October 2021

The present study investigates the grammatical origin of the postverbal negatorḇuin Rif Berber (Afroasiatic, Berber; North, Northeast, and Northwest Morocco) and in Moroccan Arabic of Oujda (Afroasiatic, Semitic; Northeast Morocco), the only languages in which it is commonly attested up till now. Based on new data obtained from recent fieldwork in Morocco, the study will demonstrate that this negator is most probably of Berber origin and has been construed out of an existential by system-internal grammaticalization. The study will also provide evidence for quadruple negation marking in Rif Berber, relating to a reduplication of theḇu-negator. Moreover, it will show how Berber constantly innovates its cyclical negation system, in which, in this case, different Jespersen Cycles and a Negative Existential Cycle are interlaced. Accordingly, the study will prove thatḇuin Moroccan Arabic is an innovation phenomenon induced by contact with Rif Berber and instantiated through the processes of pattern replication and matter borrowing.
Near-zero phase-lag hyperscanning in a novel wireless EEG system
Authors: Chuang Chun-Hsiang , Lu Shao-Wei , Chao Yi-Ping , Peng Po-Hsun , Hsu Hao-Che , Hung Cheng-Chieh , Chang Che-Lun , Jung Tzyy-Ping
Published: October 2021

Objective. Hyperscanning is an emerging technology that concurrently scans the neural dynamics of multiple individuals to study interpersonal interactions. In particular, hyperscanning with electroencephalography (EEG) is increasingly popular owing to its mobility and its ability to allow studying social interactions in naturalistic settings at the millisecond scale. Approach. To align multiple EEG time series with sophisticated event markers in a single time domain, a precise and unified timestamp is required for stream synchronization. This study proposes a clock-synchronized method that uses a custom-made RJ45 cable to coordinate the sampling between wireless EEG amplifiers to prevent incorrect estimation of interbrain connectivity due to asynchronous sampling. In this method, analog-to-digital converters are driven by the same sampling clock. Additionally, two clock-synchronized amplifiers leverage additional radio frequency channels to keep the counter of their receiving dongles updated, which guarantees that binding event markers received by the dongle with the EEG time series have the correct timestamp. Main results. The results of two simulation experiments and one video gaming experiment reveal that the proposed method ensures synchronous sampling in a system with multiple EEG devices, achieving near-zero phase lag and negligible amplitude difference between the signals. Significance. According to all of the signal-similarity metrics, the suggested method is a promising option for wireless EEG hyperscanning and can be utilized to precisely assess the interbrain couplings underlying social-interaction behaviors.
Predicting speech intelligibility from EEG in a non-linear classification paradigm
*
Authors: Accou Bernd , Jalilpour Monesi Mohammad , Van hamme Hugo , Francart Tom
Published: October 2021

Objective. Currently, only behavioral speech understanding tests are available, which require active participation of the person being tested. As this is infeasible for certain populations, an objective measure of speech intelligibility is required. Recently, brain imaging data has been used to establish a relationship between stimulus and brain response. Linear models have been successfully linked to speech intelligibility but require per-subject training. We present a deep-learning-based model incorporating dilated convolutions that operates in a match/mismatch paradigm. The accuracy of the model’s match/mismatch predictions can be used as a proxy for speech intelligibility without subject-specific (re)training. Approach. We evaluated the performance of the model as a function of input segment length, electroencephalography (EEG) frequency band and receptive field size while comparing it to multiple baseline models. Next, we evaluated performance on held-out data and finetuning. Finally, we established a link between the accuracy of our model and the state-of-the-art behavioral MATRIX test. Main results. The dilated convolutional model significantly outperformed the baseline models for every input segment length, for all EEG frequency bands except the delta and theta band, and receptive field sizes between 250 and 500 ms. Additionally, finetuning significantly increased the accuracy on a held-out dataset. Finally, a significant correlation (r = 0.59, p = 0.0154) was found between the speech reception threshold (SRT) estimated using the behavioral MATRIX test and our objective method. Significance. Our method is the first to predict the SRT from EEG for unseen subjects, contributing to objective measures of speech intelligibility.
Testing the effects of body depth on fish maneuverability via robophysical models
Authors: Howe Stephen , Bryant Kelly , Duff Andrew , Astley Henry
Published: October 2021

Fish show a wide diversity of body shapes which affect many aspects of their biology, including swimming and feeding performance, and defense from predators. Deep laterally compressed bodies are particularly common, and have evolved multiple times in different families. Functional hypotheses that explain these trends include predator defense and increased maneuverability. While there is strong evidence that increasing body depth helps fish avoid gape-limited predators, the evidence that body shape increases a fish’s maneuverability is ambiguous. We used a two-pronged approach to explore the effects of body shape on the control of maneuvers using both live fish and a robotic model that allowed us to independently vary body shape. We captured ventral video of two tetra species (Gymnocorymbus ternetzi and Aphyocharax anisitsi) performing a wide range of maneuvers to confirm that both species of live fish utilize fundamentally similar body deformations to execute a turn, despite their different body depths. Both species use a propagating ‘pulse’ of midline curvature that is qualitatively similar to prior studies and displayed similar trends in the relationships between body kinematics and performance. We then tested the robotic model’s maneuverability, defined as the total heading change and maximum centripetal acceleration generated during a single pulse, at a range of different input kinematics across three body shapes. We found that deepening bodies increase the robot’s ability to change direction and centripetal acceleration, though centripetal acceleration exhibits diminishing returns beyond a certain body depth. By using a robotic model, we were able to isolate the effects of body shape on maneuverability and clarify this confounded relationship. Studying the functional morphology of complex traits such as body shape and their interaction with complex behavior like maneuverability benefits from both the broad view provided by comprehensive comparative studies, and the control of variables enabled by robophysical experiments.
Spatial difference of climate change effects on wheat protein concentration in China
Authors: Zhou Weimo , Liu Yujie , Ata-Ul-Karim Syed Tahir , Ge Quansheng
Published: October 2021

Climate change effects on global food security are not only limited to its effects on the yield of cereals but also their nutritional quality. However, climate change effects on crop nutritional quality, particularly grain protein concentration (PC) on a large geographical scale have not yet been quantified in China. For this purpose, we assessed the effects of three key climatic factors (temperature, precipitation, and solar radiation) on wheat PC in ten wheat-growing areas of China using a series of statistical models on a county-level PC dataset. The results demonstrated that the average PC in China from 2006 to 2018 ranged from 12.01% to 14.50% across the ten areas, with an obvious spatial difference pattern showing an increase in PC from south to north and from west to east. The sensitivity analysis indicated that PC showed a positive response to variation in the increasing temperature, and the PC of wheat grown in the Huanghuai area was less affected than the PC of wheat grown in other areas. Conversely, solar radiation posed negative effects on the PC in the southwestern area, whereas precipitation had intricate effects on the PC in all areas. Besides, the highest explanation of climate variability during five growth periods contributed 26.0%–47.6% of the PC variability in the northeastern area, whereas the lowest explanation of climate variability during five growth periods only accounted for 2.5%–3.7% of PC variability in the Yangtze River area. Our study further demonstrated that the effects of climate change on wheat grain PC in China were spatially heterogeneous with higher effects on PC in spring wheat-growing areas as compared to winter wheat-growing areas. We suggested that the northern and the northeastern area in China could be developed as alternative areas to produce wheat with high grain PC in the face of climate warming.
Evidence of overpressure at the base of huge landslide
Authors: Luo Hui , Hu Wei
Published: October 2021

Overpressuring from generation of CO2 gas caused by thermal decomposition of basal carbonates can raise pore-fluid pressure and reduce friction during landsliding. We used thermogravimetry and dilatometry to determine the evidence of raised pore-fluid pressure from carbonate thermal decomposition at the base of the 2009 Jiweishan landslide. Results from thermal expansion experiments showed that the rock undergoes expansion and thermal fracture. At a heating rate of 20°C/min, the coefficient of linear thermal expansion increased sharply at 807.3 °C and reached a maximum of 36.6×10−6 °C −1 at 827.3 °C. DTG data show that the temperature of the maximum thermal decomposition rate of calcite is 852.5°C. The evidence showed that CO2 gas can produce great pressure during the rapid sliding process of Jiweishan landslide, and it is conducive to reduce the effective normal load. In addition, thermal fracture may be a explanation for the ultra-low friction during the rapid sliding by reducing the strength of the rock at the sliding surface and making it more easily entrained.
Analysis of Fe-doped ZnO thin films for degradation of rhodamine b, methylene blue, and Escherichia coli under visible light
Authors: Sutanto Heri , Alkian Ilham , Mukholit Mukholit , Nugraha Arsyadio Aditya , Hidayanto Eko , Marhaendrajaya Indras , Priyono Priyono
Published: October 2021

ZnO is a popular photocatalyst that is often used for the degradation of dyes and bacteria. However, the catalytic performance of ZnO is only optimal under UV light exposure. This study aims to determine the degradation performance of rhodamine b, methylene blue, and Escherichia coli using 0, 5, 10, 15, and 20% Fe-doped ZnO (ZnO:Fe). Deposition of thin film was carried out using the sol-gel method with a spray-coating technique, while the degradation was carried out under halogen light exposure for 3 h. The optical characterization results show that 20% Fe-doped ZnO has the highest transmittance and the lowest energy band gap of 3.21 eV based on Tauc’s plot method. All thin films are hydrophilic with the largest contact angle of 68.54° by 20% Fe-doped ZnO and the lowest contact angle of 52.96° by 5% Fe-doped ZnO. The surface morphology of the thin film resembles a creeping root that is cracked and agglomerated. XRD test results show that the thin film is dominated by ZnO peaks with a wurtzite structure with a hexagonal plane phase and a crystal size of 115.5 A°. The 20% Fe-doped ZnO thin film had the most efficient degradation performance of 70.79% for rhodamine b, 65.31% for blue, and 67% for E. coli bacteria. Therefore, Fe-doped ZnO is a brilliant photocatalyst material that can degrade various pollutants even under visible light.
Effects of climate migration on town-to-city transitions in the United States: proactive investments in civil infrastructure for resilience and sustainability
Authors: Maxim Alexandra , Grubert Emily
Published: October 2021

Climate change is a hazard risk amplifier and contributes to changing precipitation and temperature patterns that alter an area’s risk profile. Existing infrastructure is often ill-equipped to absorb shocks associated with increased hazard frequency and severity, but active measures to implement holistic resilience plans are rare and often limited in scope. As climate change progresses, climate change-induced migration is becoming more frequent and likely, with probable changes to regionally specific needs for resilient infrastructure. People relocating to areas with actual or perceived lower risk is expected to add demand for built infrastructure and change governance needs as receiving communities grow. Anticipating demand growth can enable proactive rather than reactive investment. Here we analyze the impact of anticipated climate migration patterns on community growth in the United States (US), leveraging the US Environmental Protection Agency’s Integrated Climate and Land-Use Scenarios dataset to illustratively evaluate how domestic migration might alter regional patterns for a particularly salient target of infrastructure planning: ‘tipping points’ where towns become cities and experience qualitative changes in infrastructural and governance complexity. Projected 2010–2100 town-to-city rapid urbanization patterns are different from historical (1950–2010) patterns in the US, notably shifting from the Southwest (including California) to the Southern Plains (including Texas). Climate change is expected to shift this pattern north and east, contributing to land use change and new demand for civil infrastructure in places where past development strategies might not be regionally appropriate. Urban futures are not predetermined: this illustrative analysis highlights that despite deep uncertainty, sufficient information about climate change, migration patterns, and generalizable best practices for infrastructural development exists to support proactive planning for migration. Proactive and regionally appropriate investment in civil infrastructure in regions expected to attract climate migration can facilitate resilience, sustainability, and justice under climate change, emphasizing safe, sufficient, and equitable infrastructure.
A remark on Carleson measures of domains in ℂⁿ
Authors: Thuc Phung
Published: October 2021

We provide characterizations of Carleson measures on a certain class of bounded pseudoconvex domains. An example of a vanishing Carleson measure whose Berezin transform does not vanish on the boundary is given in the class of the Hartogs triangles<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" alttext="double-struck upper H Subscript k Baseline colon-equal StartSet left-parenthesis z 1 comma z 2 right-parenthesis element-of double-struck upper C squared colon StartAbsoluteValue z 1 EndAbsoluteValue Superscript k Baseline greater-than StartAbsoluteValue z 2 EndAbsoluteValue greater-than 1 EndSet comma k element-of double-struck upper Z Superscript plus Baseline period">Hk≔{(z1,z2)∈C2:|z1|k>|z2|>1},k∈Z+.\begin{equation*} \mathbb {H}_{k}≔\left \{ \left (z_{1},z_{2}\right )\in \mathbb {C}^{2}:\left |z_{1}\right |^{k}>\left |z_{2}\right |>1\right \},\;k\in \mathbb {Z}^{+}. \end{equation*}
Parameters of a positive chain sequence associated with orthogonal polynomials
Authors: Marcato Gustavo , Ranga A. , Lun Yen
Published: October 2021

The objective here is to provide a new characterization of all the parameter sequences of a positive chain sequence that has been of importance in the study of orthogonal polynomials on the real line. Connection formulas and some applications that follow from this new characterization have also been explored. Example of a class of positive chain sequences having explicit formulas for all the parameter sequences is also provided.
Extended flexibility of Lyapunov exponents for Anosov diffeomorphisms
Authors: Carrasco Pablo , Saghin Radu
Published: October 2021

Bochi-Katok-Rodriguez Hertz proposed recently a program on the flexibility of Lyapunov exponents for conservative Anosov diffeomorphisms, and obtained partial results in this direction. For conservative Anosov diffeomorphisms with strong hyperbolic properties we establish extended flexibility results for their Lyapunov exponents. We give examples of Anosov diffeomorphisms with the strong unstable exponent larger than the strong unstable exponent of the linear part. We also give examples of derived from Anosov diffeomorphisms with the metric entropy larger than the entropy of the linear part.

These results rely on a new type of deformation which goes beyond the previous Shub-Wilkinson and Baraviera-Bonatti techniques for conservative systems having some invariant directions. In order to estimate the Lyapunov exponents even after breaking the invariant bundles, we obtain an abstract result which gives bounds on exponents of some specific cocycles and which can be applied in various other settings. We also include various interesting comments in the appendices: our examples are

C

2

\mathcal {C}^2

robust, the Lyapunov exponents are continuous (with respect to the map) even after breaking the invariant bundles, a similar construction can be obtained for the case of multiple eigenvalues.
Analysis of senescence-responsive stress fiber proteome reveals reorganization of stress fibers mediated by elongation factor eEF2 in HFF-1 cells
Authors: Liu Shiyou , Matsui Tsubasa S. , Kang Na , Deguchi Shinji
Published: October 2021

We identified with proteomic analysis the whole protein components of stress fibers (SFs) and how they change with cellular senescence. We demonstrated that eEF2 (eukaryotic translation elongation factor 2) is critical to the senescence-driven reorganization of SFs, providing a novel molecular basis for SFs to be reinforced to resist senescence.
Estimating Country-Specific Incidence Rates of Rare Cancers: Comparative Performance Analysis of Modeling Approaches Using European Cancer Registry Data
Authors: Salmerón Diego , Botta Laura , Martínez José Miguel , Trama Annalisa , Gatta Gemma , Borràs Josep M , Capocaccia Riccardo , Clèries Ramon ,   for the Information Network on Rare Cancers (RARECARENet) Working Group
Published: October 2021

Estimating incidence of rare cancers is challenging for exceptionally rare entities and in small populations. In a previous study, investigators in the Information Network on Rare Cancers (RARECARENet) provided Bayesian estimates of expected numbers of rare cancers and 95% credible intervals for 27 European countries, using data collected by population-based cancer registries. In that study, slightly different results were found by implementing a Poisson model in integrated nested Laplace approximation/WinBUGS platforms. In this study, we assessed the performance of a Poisson modeling approach for estimating rare cancer incidence rates, oscillating around an overall European average and using small-count data in different scenarios/computational platforms. First, we compared the performance of frequentist, empirical Bayes, and Bayesian approaches for providing 95% confidence/credible intervals for the expected rates in each country. Second, we carried out an empirical study using 190 rare cancers to assess different lower/upper bounds of a uniform prior distribution for the standard deviation of the random effects. For obtaining a reliable measure of variability for country-specific incidence rates, our results suggest the suitability of using 1 as the lower bound for that prior distribution and selecting the random-effects model through an averaged indicator derived from 2 Bayesian model selection criteria: the deviance information criterion and the Watanabe-Akaike information criterion.
Exposure Determinants in the French Database COLCHIC (1987–2019): Statistical Modeling across 77 Chemicals
Authors: Mater Gautier , Sauvé Jean-François , Sarazin Philippe , Lavoué Jérôme
Published: October 2021

Objectives

The COLCHIC database contains workplace exposure results of chemical samples collected by the French prevention network since 1987. We aimed to investigate potential associations between exposure levels and ancillary variables in COLCHIC across a broad range of chemical agents in order to provide insight into how to best interpret and exploit the information in this national database.

Methods

We selected personal and area measurements in COLCHIC and collected outside respiratory personal protective equipment (PPE), restricted to chemical agents that had at least 1000 samples available. We used Tobit models to estimate associations between exposure concentrations and sample year, sampling duration, PPE, workforce size, collective protective equipment, origin of request, and reason for request for each chemical agent for the period 1987–2019. Models for period 2002–2019 also included type of process (open/closed) and exposure frequency. We used separate models for each combination of agent, period, and personal or area samples. We then applied Bayesian meta-analytical methods to assess average effects and effect heterogeneity of exposure factors across agents.

Results

COLCHIC contained 720 282 exposure results (62% personal and 38% area samples) to 77 agents, including 346 766 results for the more recent period 2002–2019 (67% personal and 33% area samples). Sample year and duration, PPE, and process type had the strongest and most consistent associations with exposure levels across agents. Personal and area exposure levels decreased yearly (6% for the entire period and 9% since 2002), and 30-min samples were approximately twice as high as 240-min samples. Workers wearing PPE were exposed to levels 1.7 times higher on average than those without PPE for both area and personal samples. Personal exposure levels associated with enclosed or semi-enclosed processes were approximately 20–30% lower compared with open processes. The associations for the other exposure variables were weaker and more inconsistent between agents. Between-agent heterogeneity of estimated effects, based on 80% prediction intervals, was lowest for sampling duration, time trends, and the presence of PPE.

Conclusions

Sampling duration, time trends, and the presence of PPE are important factors to take into account when analyzing COLCHIC and had similar associations with exposure levels across agents. Other variables generally showed weaker associations or variable effects. These results will be used to adjust exposure estimates for the French working population from measurements stored in COLCHIC.
Identifying correlations driven by influential observations in large datasets
Authors: Bu Kevin , Wallach David S , Wilson Zach , Shen Nan , Segal Leopoldo N , Bagiella Emilia , Clemente Jose C
Published: October 2021

Although high-throughput data allow researchers to interrogate thousands of variables simultaneously, it can also introduce a significant number of spurious results. Here we demonstrate that correlation analysis of large datasets can yield numerous false positives due to the presence of outliers that canonical methods fail to identify. We present Correlations Under The InfluencE (CUTIE), an open-source jackknifing-based method to detect such cases with both parametric and non-parametric correlation measures, and which can also uniquely rescue correlations not originally deemed significant or with incorrect sign. Our approach can additionally be used to identify variables or samples that induce these false correlations in high proportion. A meta-analysis of various omics datasets using CUTIE reveals that this issue is pervasive across different domains, although microbiome data are particularly susceptible to it. Although the significance of a correlation eventually depends on the thresholds used, our approach provides an efficient way to automatically identify those that warrant closer examination in very large datasets.
CCWeights: an R package and web application for automated evaluation and selection of weighting factors for accurate quantification using linear calibration curve
Authors: Dong Yonghui , Wachsman Tal , Morgan Liat , Gazit Ehud , Birkler Rune Isak Dupont
Published: October 2021

The accuracy of any analytical method is highly dependent on the selection of an appropriate calibration model. Here, we present CCWeights, an R package for automated assessment and selection of weighting factors for accurate quantification using linear calibration curve. Additionally, CCWeights includes a web application that allows users to analyze their data using an interactive graphical user interface, without any programming requirements. The workflow and features of CCWeights are illustrated by the analyses of two datasets acquired by liquid chromatography-mass spectrometry (LC-MS). The resulting quantification table can be directly utilized for further model assessment and subsequent data analysis.

Availability and implementation

CCWeights is publicly available on CRAN repository (https://cran.r-project.org/web/packages/CCWeights), with source code available on GitHub (https://github.com/YonghuiDong/CCWeights) under a GPL-3 license. The web application can be run locally from R console using a simple command “runGui()”. Alternatively, the web application can be freely accessed for direct online use at https://bcdd.shinyapps.io/CCWeights/.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.
CoCoPRED: coiled-coil protein structural feature prediction from amino acid sequence using deep neural networks
Authors: Feng Shi-Hao , Xia Chun-Qiu , Shen Hong-Bin
Published: October 2021

Motivation

Coiled-coil is composed of two or more helices that are wound around each other. It widely exists in proteins and has been discovered to play a variety of critical roles in biology processes. Generally, there are three types of structural features in coiled-coil: coiled-coil domain (CCD), oligomeric state and register. However, most of the existing computational tools only focus on one of them.

Results

Here, we describe a new deep learning model, CoCoPRED, which is based on convolutional layers, bidirectional long short-term memory, and attention mechanism. It has three networks, i.e. CCD network, oligomeric state network, and register network, corresponding to the three types of structural features in coiled-coil. This means CoCoPRED has the ability of fulfilling comprehensive prediction for coiled-coil proteins. Through the 5-fold cross-validation experiment, we demonstrate that CoCoPRED can achieve better performance than the state-of-the-art models on both CCD prediction and oligomeric state prediction. Further analysis suggests the CCD prediction may be a performance indicator of the oligomeric state prediction in CoCoPRED. The attention heads in CoCoPRED indicate that registers a, b and e are more crucial for the oligomeric state prediction.

Availability and implementation

CoCoPRED is available at http://www.csbio.sjtu.edu.cn/bioinf/CoCoPRED. The datasets used in this research can also be downloaded from the website.

Supplementary information

Supplementary data are available at Bioinformatics online.
AOP-helpFinder webserver: a tool for comprehensive analysis of the literature to support adverse outcome pathways development
Authors: Jornod Florence , Jaylet Thomas , Blaha Ludek , Sarigiannis Denis , Tamisier Luc , Audouze Karine
Published: October 2021

Motivation

Adverse outcome pathways (AOPs) are a conceptual framework developed to support the use of alternative toxicology approaches in the risk assessment. AOPs are structured linear organizations of existing knowledge illustrating causal pathways from the initial molecular perturbation triggered by various stressors, through key events (KEs) at different levels of biology, to the ultimate health or ecotoxicological adverse outcome.

Results

Artificial intelligence can be used to systematically explore available toxicological data that can be parsed in the scientific literature. Recently, a tool called AOP-helpFinder was developed to identify associations between stressors and KEs supporting thus documentation of AOPs. To facilitate the utilization of this advanced bioinformatics tool by the scientific and the regulatory community, a webserver was created. The proposed AOP-helpFinder webserver uses better performing version of the tool which reduces the need for manual curation of the obtained results. As an example, the server was successfully applied to explore relationships of a set of endocrine disruptors with metabolic-related events. The AOP-helpFinder webserver assists in a rapid evaluation of existing knowledge stored in the PubMed database, a global resource of scientific information, to build AOPs and Adverse Outcome Networks supporting the chemical risk assessment.

Availability and implementation

AOP-helpFinder is available at http://aop-helpfinder.u-paris-sciences.fr/index.php

Supplementary information

Supplementary data are available at Bioinformatics online.
Importance-Penalized Joint Graphical Lasso (IPJGL): differential network inference via GGMs
Authors: Leng Jiacheng , Wu Ling-Yun
Published: October 2021

Motivation

Differential network inference is a fundamental and challenging problem to reveal gene interactions and regulation relationships under different conditions. Many algorithms have been developed for this problem; however, they do not consider the differences between the importance of genes, which may not fit the real-world situation. Different genes have different mutation probabilities, and the vital genes associated with basic life activities have less fault tolerance to mutation. Equally treating all genes may bias the results of differential network inference. Thus, it is necessary to consider the importance of genes in the models of differential network inference.

Results

Based on the Gaussian graphical model with adaptive gene importance regularization, we develop a novel Importance-Penalized Joint Graphical Lasso method (IPJGL) for differential network inference. The presented method is validated by the simulation experiments as well as the real datasets. Furthermore, to precisely evaluate the results of differential network inference, we propose a new metric named APC2 for the differential levels of gene pairs. We apply IPJGL to analyze the TCGA colorectal and breast cancer datasets and find some candidate cancer genes with significant survival analysis results, including SOST for colorectal cancer and RBBP8 for breast cancer. We also conduct further analysis based on the interactions in the Reactome database and confirm the utility of our method.

Availability and implementation

R source code of Importance-Penalized Joint Graphical Lasso is freely available at https://github.com/Wu-Lab/IPJGL.

Supplementary information

Supplementary data are available at Bioinformatics online.
Association of painful human immunodeficiency virus distal sensory polyneuropathy with aberrant expectation of pain relief: functional magnetic resonance imaging evidence
Authors: Strigo Irina A , Keltner John R , Ellis Ronald J , Simmons Alan N
Published: October 2021

Mechanisms underlying chronic neuropathic pain associated with HIV-associated distal sensory polyneuropathy are poorly understood, yet 40% of those with distal neuropathy (or 20% of all people with HIV) suffer from this debilitating condition. Central pain processing mechanisms are thought to contribute to the development of HIV neuropathic pain, yet studies investigating central mechanisms for HIV neuropathic pain are few. Considering the motivational nature of pain, we aimed to examine the degree to which expectation of pain onset and expectation of pain offset are altered in sixty-one male patients with HIV-related distal sensory polyneuropathy with (N = 30) and without (N = 31) chronic neuropathic pain. By contrasting painful (foot) and non-painful (hand) sites between those with and without neuropathic pain, we could identify unique neural structures that showed altered activation during expectation of pain offset or relief. Our results showed no evidence for peripheral mechanisms evidenced by lack of significant between group differences in thermo-sensation, subjective pain response or epidermal nerve fibre density. Likewise, we found no significant differences between groups in subjective or brain mechanisms underlying the expectation of pain onset. Conversely, we found significant interaction within right anterior insula during expectation of pain offset in our study in that individuals in the pain group compared to the no-pain group exhibited increased anterior insula activation on the painful compared to the non-painful site. Our findings are consistent with abnormal processing of expectation of pain offset or abnormal pain relief-related mechanisms potentially due to increased emotional distress regarding the experience of chronic endogenous pain.
Pantomime of tool use: looking beyond apraxia
Authors: Osiurak François , Reynaud Emanuelle , Baumard Josselin , Rossetti Yves , Bartolo Angela , Lesourd Mathieu
Published: October 2021

Pantomime has a long tradition in clinical neuropsychology of apraxia. It has been much more used by researchers and clinicians to assess tool-use disorders than real tool use. Nevertheless, it remains incompletely understood and has given rise to controversies, such as the involvement of the left inferior parietal lobe or the nature of the underlying cognitive processes. The present article offers a comprehensive framework, with the aim of specifying the neural and cognitive bases of pantomime. To do so, we conducted a series of meta-analyses of brain-lesion, neuroimaging, and behavioral studies about pantomime and other related tasks (i.e., real tool use, imitation of meaningless postures, and semantic knowledge). The first key finding is that the area PF (Area PF complex) within the left inferior parietal lobe is crucially involved in both pantomime and real tool use as well as in the kinematics component of pantomime. The second key finding is the absence of a well-defined neural substrate for the posture component of pantomime (both grip errors and body-part-as-tool responses). The third key finding is the role played by the intraparietal sulcus in both pantomime and imitation of meaningless postures. The fourth key finding is that the left angular gyrus seems to be critical in the production of motor actions directed toward the body. The fifth key finding is that performance on pantomime is strongly correlated with the severity of semantic deficits. Taken together, these findings invite us to offer a neurocognitive model of pantomime, which provides an integrated alternative to the two hypotheses that dominate the field: The gesture-engram hypothesis and the communicative hypothesis. More specifically, this model assumes that technical reasoning (notably the left area PF), the motor-control system (notably the intraparietal sulcus), body structural description (notably the left angular gyrus), semantic knowledge (notably the polar temporal lobes) and potentially theory of mind (notably the middle prefrontal cortex) work in concert to produce pantomime. The original features of this model open new avenues for understanding the neurocognitive bases of pantomime, emphasizing that pantomime is a communicative task that nevertheless originates in specific tool-use (not motor-related) cognitive processes.
Bayesian slip inversion with automatic differentiation variational inference
Authors: Zhang Chendong , Chen Ting
Published: October 2021

The Bayesian slip inversion offers a powerful tool for modelling the earthquake source mechanism. It can provide a fully probabilistic result and thus permits us to quantitatively assess the inversion uncertainty. The Bayesian problem is usually solved with Monte Carlo methods, but they are computationally expensive and are inapplicable for high-dimensional and large-scale problems. Variational inference is an alternative solver to the Bayesian problem. It turns Bayesian inference into an optimization task and thus enjoys better computational performances. In this study, we introduce a general variational inference algorithm, automatic differentiation variational inference (ADVI), to the Bayesian slip inversion and compare it with the classic Metropolis–Hastings (MH) sampling method. The synthetic test shows that the two methods generate nearly identical mean slip distributions and standard deviation maps. In the real case study, the two methods produce highly consistent mean slip distributions, but the ADVI-derived standard deviation map differs from that produced by the MH method, possibly because of the limitation of the Gaussian approximation in the ADVI method. In both cases, ADVI can give comparable results to the MH method but with a significantly lower computational cost. Our results show that ADVI is a promising and competitive method for the Bayesian slip inversion.
A rapid evidence assessment exploring whether antimicrobial resistance complicates non-infectious health conditions and healthcare services, 2010–20
Authors: Hocking Lucy , Ali Gemma-Claire , d’Angelo Camilla , Deshpande Advait , Stevenson Cagla , Virdee Mann , Guthrie Susan
Published: October 2021

Antimicrobial resistance (AMR) is one of the greatest public health threats at this time. While there is a good understanding of the impacts of AMR on infectious diseases, an area of less focus is the effects AMR may be having on non-communicable health conditions (such as cancer) and healthcare services (such as surgery). Therefore, this study aimed to explore what impact AMR is currently having on non-communicable health conditions, or areas of health services, where AMR could be a complicating factor impacting on the ability to treat the condition and/or health outcomes. To do this, a rapid evidence assessment of the literature was conducted, involving a systematic approach to searching and reviewing the evidence. In total, 101 studies were reviewed covering surgery, organ transplants, cancer, ICUs, diabetes, paediatric patients, immunodeficiency conditions, liver and kidney disease, and physical trauma. The results showed limited research in this area and studies often use a selective population, making the results difficult to generalize. However, the evidence showed that for all health conditions and healthcare service areas reviewed, at least one study demonstrated a higher risk of death for patients with resistant infections, compared with no or drug-susceptible infections. Poor health outcomes were also associated with resistant infections in some instances, such as severe sepsis and failure of treatments, as well as a greater need for invasive medical support. While there are gaps in the evidence base requiring further research, efforts are also needed within policy and practice to better understand and overcome these challenges.
Individual snowshoe hares manage risk differently: integrating stoichiometric distribution models and foraging ecology
Authors: Richmond Isabella C , Balluffi-Fry Juliana , Vander Wal Eric , Leroux Shawn J , Rizzuto Matteo , Heckford Travis R , Kennah Joanie L , Riefesel Gabrielle R , Wiersma Yolanda F
Published: October 2021

Herbivores making space use decisions must consider the trade-off between perceived predation risk and forage quality. Herbivores, specifically snowshoe hares (Lepus americanus), must constantly navigate landscapes that vary in predation risk and food quality, providing researchers with the opportunity to explore the factors that govern their foraging decisions. Herein, we tested predictions that intersect the risk allocation hypothesis (RAH) and optimal foraging theory (OFT) in a spatially explicit ecological stoichiometry framework to assess the trade-off between predation risk and forage quality. We used individual and population estimates of snowshoe hare (n = 29) space use derived from biotelemetry across three summers. We evaluated resource forage quality for lowbush blueberry (Vaccinium angustifolium), a common and readily available forage species within our system, using carbon:nitrogen and carbon:phosphorus ratios. We used habitat complexity to proxy perceived predation risk. We analyzed how forage quality of blueberry, perceived predation risk, and their interaction impact the intensity of herbivore space use. We used generalized mixed effects models, structured to enable us to make inferences at the population and individual home range level. We did not find support for RAH and OFT. However, variation in the individual-level reactions norms in our models showed that individual hares have unique responses to forage quality and perceived predation risk. Our finding of individual-level responses indicates that there is fine-scale decision-making by hares, although we did not identify the mechanism. Our approach illustrates spatially explicit empirical support for individual behavioral responses to the food quality–predation risk trade-off.
Two newly identified eclipsing binaries in open cluster NGC 3532
Authors: Özdarcan O
Published: October 2021

We present light-curve analyses of two newly identified detached eclipsing binaries, namely HD 96609 and HD 303734, in the region of the richly populated open cluster NGC 3532. HD 96609 is composed of two main sequence stars (B9-A0V + A2V) with masses and radii of M1 = 2.66 ± 0.02 M⊙, M2 = 1.84 ± 0.01 M⊙, R1 = 2.740 ± 0.006 R⊙, and R2 = 1.697 ± 0.005 R⊙. The positions of the components on logM − logR plane suggest log(age/yr) 8.55, corresponding 350 ± 40 Myr of age, which agrees with the 300 ± 100 Myr age of NGC 3532 estimated in previous studies. We find the distance of HD 96609 as 460 ± 17 pc, which is consistent with the $484^{+35}_{-30}$ pc distance of NGC 3532, estimated from Gaia parallaxes. HD 303734 is an interesting totally eclipsing binary with a quite shallow secondary eclipse. Using photometric properties of the system in conjunction with theoretical calibrations, we estimate that HD 303734 consists of A6V + K3V components. HD 96609 and HD 303734 are the second and third eclipsing binaries discovered in the region of NGC 3532, after the first one, GV Car.
The homogeneity scale and the growth rate of cosmic structures
Authors: Avila Felipe , Bernui Armando , Nunes Rafael C , de Carvalho Edilson , Novaes Camila P
Published: October 2021

We propose a novel approach to obtain the growth rate of cosmic structures, f(z), from the evolution of the cosmic homogeneity scale, RH(z). Our methodology needs two ingredients in a specific functional form: RH(z) data and the matter two-point correlation function today, i.e. ξ(r, z = 0). We use a Gaussian Process approach to reconstruct the function RH. In the absence of suitable observational information of the matter correlation function in the local Universe, z ≃ 0, we assume a fiducial cosmology to obtain ξ(r, z = 0). For this reason, our final result turns out to be a consistency test of the cosmological model assumed. Our results show a good agreement between: (i) the growth rate $f^{R_{\text{H}}}(z)$ obtained through our approach, (ii) the fΛCDM(z) expected in the fiducial model, and (iii) the best-fitting f(z) from data compiled in the literature. Moreover, using this data compilation, we perform a Gaussian Process to reconstruct the growth rate function fdata(z) and compare it with the function $f^{R_{\text{H}}}(z)$ finding a concordance of $\lt \!2 \, \sigma$, a good result considering the few data available for both reconstruction processes. With more accurate RH(z) data, from forthcoming surveys, the homogeneity scale function might be better determined and would have the potential to discriminate between ΛCDM and alternative scenarios as a new cosmological observable.
An analysis of the spectroscopic signatures of layering in the ejecta of Type Iax supernovae
Authors: Magee M R , Gillanders J H , Maguire K , Sim S A , Callan F P
Published: October 2021

Investigations of some Type Iax supernovae (SNe Iax) have led to the suggestion that their ejecta must be layered to some degree. Such an ejecta structure has been argued as inconsistent with the well-mixed composition predicted by pure deflagrations. Based on explosion models, we create toy models in which the ejecta are artificially stratified and progressively mixed until a uniform composition is obtained. We find that models that are heavily mixed, containing burned and unburned material at all velocities, produce reasonably good agreement with SN 2012Z, for which a layered structure has been suggested. We also discuss how existing ejecta compositions determined for SNe Iax do not necessarily contradict pure deflagration models and may be consistent with a steeper density profile. We investigate previous claims that differences in line profile shapes may be due to strong blending, by presenting a series of models with different plasma states. These models indicate that blending could indeed explain differences in the observed profiles. Alternatively, stratification could also explain such differences; however, all of our models indicate that this does not necessarily require stratification in abundance. Sufficient stratification in the ionization state can be achieved even for a well-mixed model. Based on our analysis, we demonstrate that there is insufficient evidence to suggest the ejecta of SNe Iax must be layered and therefore argue the pure deflagration scenario is not ruled out, even for the brightest SNe Iax. Our analysis does not indicate the ejecta cannot be layered to some degree, but observations within days of explosion are necessary to determine the extent to which the outer ejecta could be layered.