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Due to population growth, climate change, and the urban heat island effect, heat exposure is becoming an important issue faced by urban built environments. Heat exposure assessment is a prerequisite for mitigation measures to reduce the impact of heat exposure. However, there is limited research on urban heat exposure assessment approaches that provides fine-scale spatiotemporal heat exposure information, integrated with meteorological status and human collective exposure as they move about in cities, to enable proactive heat exposure mitigation measures. Smart city digital twins (SCDTs) provide a new potential avenue for addressing this gap, enabling fine spatiotemporal scales, human-infrastructure interaction modeling, and predictive and decision support capabilities. This study aims to develop and test an SCDT for collective urban heat exposure assessment and forecasting. Meteorological sensors and computer vision techniques were implemented in Columbus, Georgia, to acquire temperature, humidity, and passersby count data. These data were then integrated into a collective temperature humidity index. A time-series prediction model and a crowd simulation were employed to predict future short-term heat exposures based on the data accumulated by this SCDT and to support heat exposure mitigation efforts. The results demonstrate the potential of SCDT to enhance public safety by providing city officials with a tool for discovering, predicting, and, ultimately, mitigating community exposure to extreme heat. [ABSTRACT FROM AUTHOR]

Bacterial gene repertoires reflect adaptive strategies, contribute to ecosystem functioning and are limited by genome size. However, gene functional diversity does not necessarily correlate with taxonomic diversity because average genome size may vary by community. Here, we analyse gene functional diversity (by shotgun metagenomics) and taxonomic diversity (by 16S rRNA gene amplicon sequencing) to investigate soil bacterial communities along a natural pH gradient in 12 tropical, subtropical, and temperate forests. We find that bacterial average genome size and gene functional diversity decrease, whereas taxonomic diversity increases, as soil pH rises from acid to neutral; as a result, bacterial taxonomic and functional diversity are negatively correlated. The gene repertoire of acid-adapted oligotrophs is enriched in functions of signal transduction, cell motility, secretion system, and degradation of complex compounds, while that of neutral pH-adapted copiotrophs is enriched in functions of energy metabolism and membrane transport. Our results indicate that a mismatch between taxonomic and functional diversity can arise when environmental factors (such as pH) select for adaptive strategies that affect genome size distributions. Bacterial functional diversity does not necessarily correlate with taxonomic diversity because average genome size may vary by community. Here, Wang et al. investigate bacterial communities along a natural pH gradient in forest soils, and find that average genome size and functional diversity decrease, whereas taxonomic diversity increases, as soil pH rises from acid to neutral. [ABSTRACT FROM AUTHOR]

Biomarker-based differential diagnosis of the most common forms of dementia is becoming increasingly important. Machine learning (ML) may be able to address this challenge. The aim of this study was to develop and interpret a ML algorithm capable of differentiating Alzheimer's dementia, frontotemporal dementia, dementia with Lewy bodies and cognitively normal control subjects based on sociodemographic, clinical, and magnetic resonance imaging (MRI) variables. 506 subjects from 5 databases were included. MRI images were processed with FreeSurfer, LPA, and TRACULA to obtain brain volumes and thicknesses, white matter lesions and diffusion metrics. MRI metrics were used in conjunction with clinical and demographic data to perform differential diagnosis based on a Support Vector Machine model called MUQUBIA (Multimodal Quantification of Brain whIte matter biomArkers). Age, gender, Clinical Dementia Rating (CDR) Dementia Staging Instrument, and 19 imaging features formed the best set of discriminative features. The predictive model performed with an overall Area Under the Curve of 98%, high overall precision (88%), recall (88%), and F1 scores (88%) in the test group, and good Label Ranking Average Precision score (0.95) in a subset of neuropathologically assessed patients. The results of MUQUBIA were explained by the SHapley Additive exPlanations (SHAP) method. The MUQUBIA algorithm successfully classified various dementias with good performance using cost-effective clinical and MRI information, and with independent validation, has the potential to assist physicians in their clinical diagnosis. [ABSTRACT FROM AUTHOR]

Streptococcus gallolyticus subspecies gallolyticus (Sgg) is known to be strongly associated with colorectal cancer (CRC). Recent functional studies further demonstrated that Sgg actively stimulates CRC cell proliferation and promotes the development of colon tumors. However, the Sgg factors important for the pro-proliferative and pro-tumor activities of Sgg remain unclear. Here, we identified a chromosomal locus in Sgg strain TX20005. Deletion of this locus significantly reduced Sgg adherence to CRC cells and abrogated the ability of Sgg to stimulate CRC cell proliferation. Thus, we designate this locus as the Sgg pathogenicity-associated region (SPAR). More importantly, we found that SPAR is important for Sgg pathogenicity in vivo. In a gut colonization model, mice exposed to the SPAR deletion mutant showed significantly reduced Sgg load in the colonic tissues and fecal materials, suggesting that SPAR contributes to the colonization capacity of Sgg. In a mouse model of CRC, deletion of SPAR abolished the ability of Sgg to promote the development of colon tumors growth. Taken together, these results highlight SPAR as a critical pathogenicity determinant of Sgg. [ABSTRACT FROM AUTHOR]

Parkinson's psychosis (PDP) describes a spectrum of symptoms that may arise in Parkinson's disease (PD) including visual hallucinations (VH). Imaging studies investigating the neural correlates of PDP have been inconsistent in their findings, due to differences in study design and limitations of scale. Here we use empirical Bayes harmonisation to pool together structural imaging data from multiple research groups into a large-scale mega-analysis, allowing us to identify cortical regions and networks involved in VH and their relation to receptor binding. Differences of morphometrics analysed show a wider cortical involvement underlying VH than previously recognised, including primary visual cortex and surrounding regions, and the hippocampus, independent of its role in cognitive decline. Structural covariance analyses point to the involvement of the attentional control networks in PD-VH, while associations with receptor density maps suggest neurotransmitter loss may be linked to the cortical changes. Visual hallucinations are a prevalent symptom of Parkinson's disease. Here the authors use a structural mega-analysis to show cortical regions and networks involved in visual hallucinations and associations with receptor density maps. [ABSTRACT FROM AUTHOR]

Post-hazard rapid response has emerged as a promising pathway towards resilient critical infrastructure systems (CISs). Nevertheless, it is challenging to scheme the optimal plan for those rapid responses, given the enormous search space and the hardship of assessment on the spatiotemporal status of CISs. We now present a new approach to post-shock rapid responses of road networks (RNs), based upon lookahead searches supported by machine learning. Following this approach, we examined the resilience-oriented rapid response of a real-world RN across Luchon, France, under destructive earthquake scenarios. Our results show that the introduction of one-step lookahead searches can effectively offset the lack of adaptivity due to the deficient heuristic of rapid responses. Furthermore, the performance of rapid responses following such a strategy is far surpassed, when a series of deep neural networks trained based solely on machine learning, without human interventions, are employed to replace the heuristic and guide the searches. [ABSTRACT FROM AUTHOR]

Over the Texas-Louisiana Shelf in the Northern Gulf of Mexico, the eutrophic, fresh Mississippi/Atchafalaya river plume isolates saltier waters below, supporting the formation of bottom hypoxia in summer. The plume also generates strong density fronts, features of the circulation that are known pathways for the exchange of water between the ocean surface and the deep. Using high-resolution ocean observations and numerical simulations, we demonstrate how the summer land-sea breeze generates rapid vertical exchange at the plume fronts. We show that the interaction between the land-sea breeze and the fronts leads to convergence/divergence in the surface mixed layer, which further facilitates a slantwise circulation that subducts surface water along isopycnals into the interior and upwells bottom waters to the surface. This process causes significant vertical displacements of water parcels and creates a ventilation pathway for the bottom water in the northern Gulf. The ventilation of bottom water can bypass the stratification barrier associated with the Mississippi/Atchafalaya river plume and might impact the dynamics of the region's dead zone. Vertical exchange in the ocean is an important conduit connecting the surface to the deep and influences the distributions of gases, nutrients, pollutants, and other tracers. Here the authors using high-resolution observations and numerical simulations of the ocean fronts in the Northern Gulf of Mexico reveal that the interaction between the fronts and land-sea breeze creates slantwise pathways for water parcels and induces significant subduction of surface water and upwelling of bottom water. [ABSTRACT FROM AUTHOR]

With the advent of neuronal oscillators in bioelectronic medicine, it has become increasingly important to understand the effect of magnetic fields on the biological rhythms they produce. In particular, cardiac pacemakers must be resilient to the magnetic fields applied during magnetic resonance imaging, but it is not known whether the nonlinearity of the neuron response would amplify some the known effects of magnetic fields in semiconductor devices. Here, we have performed a series of experiments probing the oscillations of a silicon neuron in a static magnetic field of 3T applied in the plane of the substrate and perpendicular to it. The neuron was fabricated from complementary metal-oxide-semiconductor integrated circuits, which integrated currents in the nA range to compute the output of the Hodgkin-Huxley model. The experiment reveals a small magnetic field-induced dephasing of neuron oscillations which is slightly larger when the magnetic field is in the plane rather than perpendicular to the plane. This is interpreted in terms of the differences in diffusion coefficients of cyclotron and magnetoelectric skipping orbits at room temperature. [ABSTRACT FROM AUTHOR]

Plant response to drought stress involves fungi and bacteria that live on and in plants and in the rhizosphere, yet the stability of these myco- and micro-biomes remains poorly understood. We investigate the resistance and resilience of fungi and bacteria to drought in an agricultural system using both community composition and microbial associations. Here we show that tests of the fundamental hypotheses that fungi, as compared to bacteria, are (i) more resistant to drought stress but (ii) less resilient when rewetting relieves the stress, found robust support at the level of community composition. Results were more complex using all-correlations and co-occurrence networks. In general, drought disrupts microbial networks based on significant positive correlations among bacteria, among fungi, and between bacteria and fungi. Surprisingly, co-occurrence networks among functional guilds of rhizosphere fungi and leaf bacteria were strengthened by drought, and the same was seen for networks involving arbuscular mycorrhizal fungi in the rhizosphere. We also found support for the stress gradient hypothesis because drought increased the relative frequency of positive correlations. Fungi are expected to be more resistant and less resilient than bacteria to environmental disturbances. Here, the authors report complex responses by microbial co-occurrence networks to drought in an agricultural system, challenging simple predictions of fungal and bacterial drought responses. [ABSTRACT FROM AUTHOR]

Objective cognitive impairment is a feature of Lewy body dementia (LBD), and computerised attentional tasks are commonly used as outcome measures in interventional trials. However, the reliability of these measures, in the absence of interventions, are unknown. This study examined the reliability of these attentional measures at short-term and longer-term follow-up stages. LBD patients (n = 36) completed computerised attentional tasks [simple and choice reaction time, and digit vigilance (SRT, CRT, DV)] at short-term (Day 0–Day 5) and longer-term (4 and 12 weeks) follow-up. Intra-class correlations (ICCs) were calculated to assess test–retest reliability. At short-term, the reciprocal SRT, CRT and DV mean reaction time to correct answers, the reciprocal DV coefficient of variation, and reciprocal power of attention (PoA) all showed excellent levels of reliability (all ICCs > 0.90). The reciprocal PoA showed the highest level of reliability (ICC = 0.978). At longer-term follow-up, only the reciprocal PoA had excellent levels of reliability (ICC = 0.927). Reciprocal SRT, CRT and DV reaction time to correct answers, and the CRT coefficient of variation values, showed good levels of test–retest reliability (ICCs ≥ 0.85). Contrary to expectations, most attentional measures demonstrated high levels of test–retest reliability at both short-term and longer-term follow-up time points. The reciprocal PoA composite measure demonstrated excellent levels of test–retest reliability, both in the short-term and long-term. This indicates that objective attentional tasks are suitable outcome measures in LBD studies and that the composite PoA measure may offer the highest levels of reliability. [ABSTRACT FROM AUTHOR]

The CDC cautioned against prescribing opioids for long-term chronic pain because opioid use disorder (OUD) risk was greater compared to short-term use for acute pain. The study objective was to describe rates and characteristics of respondents prescribed opioids for long-term chronic and short-term acute pain. National Health Interview Survey respondents for 2019 aged 18 years and over were examined (n = 31,997). Bivariate and multivariable models demonstrated opioid use for long-term and acute pain relative to sociodemographic characteristics. About 12.3% of US adults took opioids in the last 12 months, and among those with chronic pain who had been prescribed opioids in the last 3 months, over half took opioids every day. The odds of taking opioids for long-term chronic pain decreased with increasing income and increased with advancing age. Opioid prescribing diverged from CDC recommendations. Less affluent older adults may be at increased risk for OUD. [ABSTRACT FROM AUTHOR]

Our relationship with technology is constantly evolving, and how we use technology in disasters has evolved even faster. Understanding how to utilize human interactions with technology and the limitations of those interactions will be a crucial building block to contextualizing crisis data. The impact of geographic scale on behavioral change analyses is an unexplored facet of our ability to identify relative severities of crisis situations, magnitudes of localized crises, and total durations of disaster impacts. Within this paper, we aggregate Twitter and hurricane damage data across a wide range of geographic scales and assess the impact of increasing scale on both the recognition of extreme behaviors and the correlation between activity and damage. The power-law relationships identified between many of these variables indicate a direct, definable scalar dependence of social media aggregation analyses, and these relationships can be used to inform more intelligent, equitable, and actionable social media usage in emergency response. [ABSTRACT FROM AUTHOR]

Previous resting-state fMRI studies in dementia with Lewy bodies have described changes in functional connectivity in networks related to cognition, motor function, and attention as well as alterations in connectivity dynamics. However, whether these changes occur early in the course of the disease and are already evident at the stage of mild cognitive impairment is not clear. We studied resting-state fMRI data from 31 patients with mild cognitive impairment with Lewy bodies compared to 28 patients with mild cognitive impairment due to Alzheimer's disease and 24 age-matched controls. We compared the groups with respect to within- and between-network functional connectivity. Additionally, we applied two different approaches to study dynamic functional connectivity (sliding-window analysis and leading eigenvector dynamic analysis). We did not find any significant changes in the mild cognitive impairment groups compared to controls and no differences between the two mild cognitive impairment groups, using static as well as dynamic connectivity measures. While patients with mild cognitive impairment with Lewy bodies already show clear functional abnormalities on EEG measures, the fMRI analyses presented here do not appear to be sensitive enough to detect such early and subtle changes in brain function in these patients. [ABSTRACT FROM AUTHOR]

This paper endeavors to examine the basic idea in Richard Epstein's book Simple Rules for a Complex World. It does so by considering a specific simple rule which was explicitly designed for complex world. A basic idea in Epstein's book is that the more complex is the world the better is the case for simple rules. To show this, he develops six simple rules pertaining to the rights of individuals, first possession, contracts, torts, government eminent domain and the power of taxation to provide public goods. This paper considers one rule rather than six rules, and it looks at monetary policy rather than policy in general. While the context is different, the case for simple rules made here provides a useful comparison with the case made by Epstein. [ABSTRACT FROM AUTHOR]

Type 1 diabetes (T1D) etiology is complex. We developed a machine learning approach that ranked the tissue-specific transcription regulatory effects for T1D SNPs and estimated their relative contributions to conversion to T1D by integrating case and control genotypes (Wellcome Trust Case Control Consortium and UK Biobank) with tissue-specific expression quantitative trait loci (eQTL) data. Here we show an eQTL (rs6679677) associated with changes to AP4B1-AS1 transcript levels in lung tissue makes the largest gene regulatory contribution to the risk of T1D development. Luciferase reporter assays confirmed allele-specific enhancer activity for the rs6679677 tagged locus in lung epithelial cells (i.e. A549 cells; C > A reduces expression, p = 0.005). Our results identify tissue-specific eQTLs for SNPs associated with T1D. The strongest tissue-specific eQTL effects were in the lung and may help explain associations between respiratory infections and risk of islet autoantibody seroconversion in young children. Ho, Nyaga et al. develop a machine learning approach for ranking tissue-specific gene regulatory affects, used here for type 1 diabetes SNPs. They identify the lung as a site where these regulatory impacts can be most impactful, which may contribute to understanding the link between respiratory issues and risk of islet autoantibody seroconvernsion. [ABSTRACT FROM AUTHOR]

Brain's modular connectivity gives this organ resilience and adaptability. The ageing process alters the organised modularity of the brain and these changes are further accentuated by neurodegeneration, leading to disorganisation. To understand this further, we analysed modular variability—heterogeneity of modules—and modular dissociation—detachment from segregated connectivity—in two ageing cohorts and a mixed cohort of neurodegenerative diseases. Our results revealed that the brain follows a universal pattern of high modular variability in metacognitive brain regions: the association cortices. The brain in ageing moves towards a segregated modular structure despite presenting with increased modular heterogeneity—modules in older adults are not only segregated, but their shape and size are more variable than in young adults. In the presence of neurodegeneration, the brain maintains its segregated connectivity globally but not locally, and this is particularly visible in dementia with Lewy bodies and Parkinson's disease dementia; overall, the modular brain shows patterns of differentiated pathology. Chen at al used fMRI to study the brain connectivity in two ageing cohorts and a mixed cohort of patients with neurodegenerative diseases. They demonstrated that with ageing the brain moves towards a more segregated modular structure, however this is disrupted by neurodegenerative diseases. [ABSTRACT FROM AUTHOR]

With the huge success of applying deep learning (DL) methodologies to image recognition and natural language processing in recent years, researchers are now keen to use them in the machine condition monitoring (MCM) context. There are numerous papers in applying various DL techniques, such as auto-encoder, restricted Boltzmann machine, convolutional neural network and recurrent neural network, to MCM problems ranging from component level condition monitoring (machine tool wear prediction, bearing fault diagnosis and classification and hydraulic pump fault diagnosis) to system level health management (aircraft and spacecraft diagnosis). In this paper, we give a brief overview in the area of DL for MCM with a focus on reviewing the most recent papers published since 2019. In Part 1, we present some critical views regarding whether any breakthrough has been achieved from an MCM domain expert perspective, with the main conclusion that DL has great potential for MCM applications and a major breakthrough could come soon since the shortfalls lie more in data than in the DL methodologies. Our overall impression is that (a) DL models are not really showing their great potentials with only a small training data; (b) faulty-condition data is hard to come by for training DL, but normal condition data is abundant, so anomaly detection makes more sense; (c) applying DL only to the Case Western Reserve University (CWRU) bearing fault dataset is not sufficient for real-world industrial applications as it was from a very simple test rig, and applying DL to data from complex systems like helicopter gearbox data may deliver much more convincing results. In Part 2, we enhance the main conclusion of the critical review with supplement views and a case study on analyzing Bell-206B helicopter main gearbox planet bearing failure data using some traditional MCM techniques in contrast to applying the long short-term memory (LSTM) DL method. We can conclude from the case study that the DL-based methods are not necessarily always superior to the traditional MCM techniques for dataset from moderately complex machinery. [ABSTRACT FROM AUTHOR]

With the huge success of applying deep learning (DL) methodologies to image recognition and natural language processing in recent years, researchers are now keen to use them in the machine condition monitoring (MCM) context. There are numerous papers in applying various DL techniques, such as auto-encoder, restricted Boltzmann machine, convolutional neural network and recurrent neural network, etc., to MCM problems ranging from component-level condition monitoring (machine tool wear prediction, bearing fault diagnosis and classification and hydraulic pump fault diagnosis) to system-level health management (aircraft and spacecraft diagnosis). In this paper, we give a brief overview in the area of DL for MCM with a focus on reviewing the most recent papers published since 2019. In Part 1, we present some critical views regarding whether any breakthrough has been achieved from an MCM domain expert perspective, with the main conclusion that DL has great potential for MCM applications, and a major breakthrough could come soon since the shortfalls lie more in data than in the DL methodologies. Our overall impression is that (a) DL models are not really showing their great potentials with only a small training data; (b) faulty-condition data is hard to come by for training DL, but normal condition data is abundant, so anomaly detection makes more sense; (c) applying DL only to the Case Western Reserve University (CWRU) bearing fault dataset is not sufficient for real world industrial applications as it was from a very simple test rig, and applying DL to data from complex systems like helicopter gearbox data may deliver much more convincing results. In Part 2, we enhance the main conclusion of the critical review with supplement views and a case study on analysing Bell-206B helicopter main gearbox planet bearing failure data using some traditional MCM techniques in contrast to applying the long short-term memory (LSTM) DL method. We can conclude from the case study that the DL-based methods are not necessarily always superior to the traditional MCM techniques for dataset from moderately complex machinery. [ABSTRACT FROM AUTHOR]

Recent studies have demonstrated that drought leads to dramatic, highly conserved shifts in the root microbiome. At present, the molecular mechanisms underlying these responses remain largely uncharacterized. Here we employ genome-resolved metagenomics and comparative genomics to demonstrate that carbohydrate and secondary metabolite transport functionalities are overrepresented within drought-enriched taxa. These data also reveal that bacterial iron transport and metabolism functionality is highly correlated with drought enrichment. Using time-series root RNA-Seq data, we demonstrate that iron homeostasis within the root is impacted by drought stress, and that loss of a plant phytosiderophore iron transporter impacts microbial community composition, leading to significant increases in the drought-enriched lineage, Actinobacteria. Finally, we show that exogenous application of iron disrupts the drought-induced enrichment of Actinobacteria, as well as their improvement in host phenotype during drought stress. Collectively, our findings implicate iron metabolism in the root microbiome's response to drought and may inform efforts to improve plant drought tolerance to increase food security. Advances in omics provide a tool to understand mechanisms for plant–microbial interactions under stress. Here the authors apply genome-resolved metagenomics to investigate sorghum and its microbiome responses to drought, identifying an unexpected role of iron metabolism. [ABSTRACT FROM AUTHOR]

Objective: To use arterial spin labelling to investigate differences in perfusion in mild cognitive impairment with Lewy bodies (MCI-LB) compared to Alzheimer type MCI (MCI-AD) and healthy controls. Methods: We obtained perfusion images on 32 MCI-LB, 30 MCI-AD and 28 healthy subjects of similar age. Perfusion relative to cerebellum was calculated, and we aimed to examine differences in relative perfusion between MCI-LB and the other groups. This included whole brain voxelwise comparisons, as well as using predefined region-of-interest ratios of medial occipital to medial temporal, and posterior cingulate to precuneus. Differences in occipital perfusion in eyes open vs eyes closed conditions were also examined. Results: Compared to controls, the MCI-LB showed reduced perfusion in the precuneus, parietal, occipital and fusiform gyrus regions. In our predefined regions, the ratio of perfusion in occipital/medial temporal was significantly lower, and the posterior cingulate/precuneus ratio was significantly higher in MCI-LB compared to controls. Overall, the occipital perfusion was greater in the eyes open vs closed condition, but this did not differ between groups. Conclusion: We found patterns of altered perfusion in MCI-LB which are similar to those seen in dementia with Lewy bodies, with reduction in posterior parietal and occipital regions, but relatively preserved posterior cingulate. [ABSTRACT FROM AUTHOR]

This document is a correction notice for an article titled "Differential diagnosis of neurodegenerative dementias with the explainable MRI based machine learning algorithm MUQUBIA" published in Scientific Reports. The correction addresses an error in the original article regarding the names of the consortia involved. The correct consortium name is "the RIN – Neuroimaging Network." The original article has been corrected. [Extracted from the article]

Minichromosome maintenance protein 10 (MCM10) is essential for eukaryotic DNA replication. Here, we describe compound heterozygous MCM10 variants in patients with distinctive, but overlapping, clinical phenotypes: natural killer (NK) cell deficiency (NKD) and restrictive cardiomyopathy (RCM) with hypoplasia of the spleen and thymus. To understand the mechanism of MCM10-associated disease, we modeled these variants in human cell lines. MCM10 deficiency causes chronic replication stress that reduces cell viability due to increased genomic instability and telomere erosion. Our data suggest that loss of MCM10 function constrains telomerase activity by accumulating abnormal replication fork structures enriched with single-stranded DNA. Terminally-arrested replication forks in MCM10-deficient cells require endonucleolytic processing by MUS81, as MCM10:MUS81 double mutants display decreased viability and accelerated telomere shortening. We propose that these bi-allelic variants in MCM10 predispose specific cardiac and immune cell lineages to prematurely arrest during differentiation, causing the clinical phenotypes observed in both NKD and RCM patients. Minichromosome maintenance protein 10 (MCM10) is critical for eukaryotic DNA replication. Here, by modelling MCM10 variants in human cell lines, the authors reveal a mechanism of MCM10-associated disease, finding that loss of MCM10 function constrains telomerase activity. [ABSTRACT FROM AUTHOR]

Cowpeas are an inexpensive source of quality protein but their utilisation is limited by long seed cooking time. This is exacerbated by development of the hard-to-cook (HTC) defect, which also adversely affects starch and protein functionality. Gamma-irradiation can eliminate cowpea seed insect infestation and affects seed functional properties, including reducing cooking time. Hence, the potential of γ-irradiation to modify the starch- and protein-related functionalities of HTC cowpeas was investigated. Gamma-irradiation at approximately 11 kGy was applied to the seeds of two cowpea varieties, differing in HTC susceptibility, where HTC had been induced by high-temperature, high-humidity (HTHH) storage. HTHH storage increased flour pasting peak viscosity by up to 40% in the less susceptible variety and by more than 100% in the more susceptible variety. Gamma-irradiation at least completely reversed this effect, due to starch depolymerisation and debranching. Gamma-irradiation also positively impacted on some protein-related properties adversely affected by HTC; partially reversing the reduction in flour and cooked paste nitrogen solubility index of the HTC-susceptible cowpea, as a result of protein depolymerisation. The multiple benefits of γ-irradiation: disinfection, cooking time reduction and reversing some adverse effects of HTC on functional properties could make it a viable process for improving HTC cowpea quality. [ABSTRACT FROM AUTHOR]

Although extreme events are inevitable, the associated cost to infrastructure and human life is not. We can mitigate these costs through improving the information available to emergency responders during and after crisis events via social media. Recent research has identified a correlation between spikes of Twitter activity and the infrastructural damage incurred during natural disasters. This research, however, overlooks emergencies occurring in areas in which people have lost power, lack the ability to connect to the internet, or, due to differences in social media perceptions, are uncompelled to Tweet during a disaster. To assess the prevalence of Twitter activity decreases and the relative importance of those decreases in detecting areas in crisis, we study crisis-driven Twitter activity deviations from "normal" in nine cities affected by the 2017 Atlantic hurricane season. In analyzing more than 1.1 million Tweets across the season, we find that there is a stronger, more significant correlation between infrastructure damage and a metric that prioritizes both increases and decreases in Twitter activity than one that prioritizes only Twitter activity increases. These findings indicate that social media drop-offs could be representative of significant distress, and accounting for the apparent survivorship bias in social media will be critical to the equitable use of social media in crisis applications. [ABSTRACT FROM AUTHOR]

To improve cassava starch extraction by wet milling, solid-state fermentation of ground roots using cellulolytic-type alkaliphilic Bacilli spp., Bacillus akibai, B. cellulosilyticus and B. hemicellulosilyticus was investigated. Enzyme assay and scanning electron microscopy indicated that Bacillus spp. production of extracellular cellulase and polygalacturonase caused the formation of micropores through the root parenchyma cell walls and exposed the embedded cellulosic network. Gas chromatography data of the cell wall constituent sugars remaining after fermentation and Fourier transform infrared data indicated that the Bacillus treatments reduced the levels of pectin and, hemicellulose and to lesser extent cellulose. Wide-angle X-ray scattering data indicated that the Bacillus spp. cell wall degrading enzymes had partially hydrolysed the amorphous fractions of the cell wall polysaccharides. All the Bacillus spp. treatments improved starch extraction by 17–23% compared to fermentation with endogenous microflora. B. cellulosilyticus was most effective in disintegration of large root particles and as result, released marginally the most starch, probably due to it having the highest cellulase activity. Solid-state fermentation using cellulolytic-type Bacillus spp. is, therefore, promising to technology to improve the efficiency of cassava wet milling cell wall disintegration and consequent starch yield without use of commercial cell wall degrading enzymes or polluting chemicals. [ABSTRACT FROM AUTHOR]

Genome-wide association studies (GWAS) have identified ~20 melanoma susceptibility loci, most of which are not functionally characterized. Here we report an approach integrating massively-parallel reporter assays (MPRA) with cell-type-specific epigenome and expression quantitative trait loci (eQTL) to identify susceptibility genes/variants from multiple GWAS loci. From 832 high-LD variants, we identify 39 candidate functional variants from 14 loci displaying allelic transcriptional activity, a subset of which corroborates four colocalizing melanocyte cis-eQTL genes. Among these, we further characterize the locus encompassing the HIV-1 restriction gene, MX2 (Chr21q22.3), and validate a functional intronic variant, rs398206. rs398206 mediates the binding of the transcription factor, YY1, to increase MX2 levels, consistent with the cis-eQTL of MX2 in primary human melanocytes. Melanocyte-specific expression of human MX2 in a zebrafish model demonstrates accelerated melanoma formation in a BRAFV600E background. Our integrative approach streamlines GWAS follow-up studies and highlights a pleiotropic function of MX2 in melanoma susceptibility. There are more than 20 known melanoma susceptibility genes. Here, using a massively parallel reporter assay, the authors identify risk-associated variants that alter gene transcription, and demonstrate that expression of one such gene, MX2, leads to the promotion of melanoma in a zebrafish model. [ABSTRACT FROM AUTHOR]

Does childrearing affect the biological functioning of parents? To address this question, we analyze cross-sectional survey and biomarker data from Vanderbilt University's Nashville Stress and Health Study, a probability sample of non-Hispanic White and Black working-age adults from Davidson County, Tennessee (2011–2014; n = 1252). Multivariable regression analyses reveal a linear dose–response relationship between the number of children living in a respondent's home and (a) increased allostatic load, and (b) decreased leukocyte telomere length. We found no differences in biological functioning between childless respondents and empty-nest parents. These findings also withstood controls for a battery of socioeconomic factors. The implications of these findings and suggestions for future research are discussed. [ABSTRACT FROM AUTHOR]

Background: After the success of PET/CT as a clinical diagnostic tool, the introduction of PET/MRI is a natural development aimed at further improving combined diagnostic imaging and reduced ionising radiation dose for half-body imaging. As with PET and CT, the combination of PET and MRI presents a series of issues that need to be addressed regarding workforce training and education. At present, there is a lack of agreement over the competencies, training requirements and educational pathways needed for PET/MRI operation. In the UK, following the establishment of the MR-PET imaging network, a task force was created to investigate the status of the workforce training, identify gaps and make recommendations regarding staff training. To do this, we ran a national survey on the status of the workforce training and the local practices across the UK's seven PET/MRI sites, reviewed the literature, and convened a panel of experts, to assess all the evidence and make recommendations regarding PET/MRI competencies and training of nuclear medicine technologists and radiographers. Results: There is limited literature available specifically on competencies and training for technologists and radiographers. The recommendations on the topic needed revisiting and adapting to the UK MR-PET network. The online survey confirmed the need for developing PET/MRI competencies and training pathways. Local organisational structures and practices were shared across the seven sites, based on models derived from experience outside the UK. The panel of experts agreed on the need for PET/MRI competencies and training strategies. Professional organisations started collaborative discussions with partners from both Nuclear Medicine and Radiography to set training priorities. Multidisciplinary collaboration and partnership were suggested as a key to a successful implementation of competencies and training. Conclusions: The report identified the need for establishing competencies for the PET/MRI workforce, particularly for technologists and radiographers. It also helped defining these competencies as well as identifying the demand for bespoke training and the development of local and national courses to be implemented to fulfil this new training need. [ABSTRACT FROM AUTHOR]

Community assembly of crop-associated fungi is thought to be strongly influenced by deterministic selection exerted by the plant host, rather than stochastic processes. Here we use a simple, sorghum system with abundant sampling to show that stochastic forces (drift or stochastic dispersal) act on fungal community assembly in leaves and roots early in host development and when sorghum is drought stressed, conditions when mycobiomes are small. Unexpectedly, we find no signal for stochasticity when drought stress is relieved, likely due to renewed selection by the host. In our experimental system, the host compartment exerts the strongest effects on mycobiome assembly, followed by the timing of plant development and lastly by plant genotype. Using a dissimilarity-overlap approach, we find a universality in the forces of community assembly of the mycobiomes of the different sorghum compartments and in functional guilds of fungi. Fungal community assembly on crop plants is thought to be driven by deterministic selection exerted by the host. Here Gao et al. use a sorghum system to show that stochastic forces act on fungal community assembly in leaves and roots early in host development and when sorghum is drought stressed. [ABSTRACT FROM AUTHOR]

Recent advances in energy technologies, policies, and practices have accelerated the global rate of improvements in energy efficiency, bringing the energy targets identified in the 2030 United Nations (UN) Sustainable Development Agenda within reach. However, Target 7.3 requires this rate to double by 2030, demanding a more substantial response to energy interventions. At present, energy interventions are failing to reach optimal levels of adoption in buildings, which are the largest urban energy consumers. This is due to a combination of direct and indirect effects generally referred to as the energy efficiency gap. Here, we compare over 18.8 million positional records of individuals against Greater London's buildings energy consumption records over the course of one year. We demonstrate that indirect (i.e., spillover) effects, arising from recurrent mobility, govern the diffusion of urban buildings' energy efficiency, far outpacing direct effects. This has been understood as a consequence of underlying spatiotemporal dependencies at the intersection of energy use and social interactions. We add to this the critical role of recurrent mobility (i.e., the mobility of those urban populations who repeatedly visit certain locations, such as home and work) as a diffusion conduit. These findings suggest that in order to improve the current levels of adoption, interventions must target times and locations that function as dense hubs of energy consumption and social interactions. Recurrent mobility thus provides a viable complement to existing targeted intervention approaches aimed at improving energy efficiency, supporting efforts to meet the UN's 2030 energy targets. [ABSTRACT FROM AUTHOR]

Background: Lewy body dementia (LBD) and Alzheimer's disease (AD) are common forms of degenerative dementia. While they are characterized by different clinical profiles, attentional deficits are a common feature. The objective of this study was to investigate how attentional problems in LBD and AD differentially affect different aspects of reaction time performance and to identify possible structural neural correlates. Methods: We studied reaction time data from an attention task comparing 39 LBD patients, 28 AD patients, and 22 age-matched healthy controls. Data were fitted to an ex-Gaussian model to characterize different facets of the reaction time distribution (mean reaction time, reaction time variability, and the subset of extremely slow responses). Correlations between ex-Gaussian parameters and grey and white matter volume were assessed by voxel-based morphometry. Results: Both dementia groups showed an increase in extremely slow responses. While there was no difference between AD and controls with respect to mean reaction time and variability, both were significantly increased in LBD patients compared to controls and AD. There were widespread correlations between mean reaction time and variability and grey matter loss in AD, but not in LBD. Conclusions: This study shows that different aspects of reaction time performance are differentially affected by AD and LBD, with a difference in structural neural correlates underlying the observed behavioural deficits. While impaired attentional performance is linked to brain atrophy in AD, in LBD it might be related to functional or microstructural rather than macrostructural changes. [ABSTRACT FROM AUTHOR]

Objective: I-123-2β-Carbomethoxy-3β-(4-iodophenyl)-N-(3-fluoropropyl)nortropane (FP-CIT) imaging is an established biomarker used in the diagnosis of Lewy body disease. Images are often reported with the aid of striatal binding ratios (SBRs), comparing uptake to a normal database via Z scores. It is well known that SBRs are age dependent. However, previous studies cover wide age ranges between 20 and 80 years, rather than focusing on older adults. Typically a linear relationship is reported, but some authors have suggested that SBRs do not decline as rapidly in old age. Commercial software packages usually adjust the SBR Z score to attempt to compensate for age-related decline, but the model used varies. Ensuring age correction is appropriate for older adults is important, given that the majority of patients referred for FP-CIT scans are aged over 60 years. We examined the relationship of SBR with age in older adults and the effect of age correction using research scans from 123 adults over 60 years of age.Methods: Twenty-nine healthy older adults and twenty-three with MCI due to Alzheimer's disease were included as controls, i.e. individuals with no evidence of Lewy body disease. Their ages ranged from 60 to 92 years (mean 76; SD 7.9). SBRs and Z scores were calculated using BRASS (Hermes Medical) and DaTQUANT (GE Healthcare). SBRs were plotted against age and linear mixed effect models applied. We tested the effect of removing age correction in BRASS using an independent dataset of 71 older adults with dementia or mild cognitive impairment.Results: The slopes of the linear fits between SBR and age per year were - 0.007 (p = 0.30) with BRASS and - 0.004 (p = 0.35) with DaTQUANT. The slopes are smaller than reported in the literature and show no statistically significant difference from zero. Switching age correction off in BRASS in the test subjects reduced Z scores by approximately 1 standard deviation at 80 years of age.Conclusion: We found no statistically significant age-related decline in SBR in adults over 60 years of age without Lewy body disease. Commercial software packages that apply a fixed rate of age correction may be overcorrecting for age in older adults, which could contribute to misdiagnosis. [ABSTRACT FROM AUTHOR]

Purpose: Emergency department thoracotomy (EDT) is a potentially life-saving procedure, performed on patients suffering traumatic cardiac arrest. Multiple indications have been reported, but overall survival remains unclear for each indication. The objective of this systematic review is to determine overall survival, survival stratified by indication, and survival stratified by geographical location for patients undergoing EDT across the world. Methods: Articles published between 2000 and 2016 were identified which detailed outcomes from EDT. All articles referring to pre-hospital, delayed, or operating room thoracotomy were excluded. Pooled odds ratios (OR) were calculated comparing differing indications. Results: Thirty-seven articles, containing 3251 patients who underwent EDT, were identified. There were 277 (8.5%) survivors. OR demonstrate improved survival for; penetrating vs blunt trauma (OR 2.10; p 0.0028); stab vs gun-shot (OR 5.45; p < 0.0001); signs of life (SOL) on admission vs no SOL (OR 5.36; p < 0.0001); and SOL in the field vs no SOL (OR 19.39; p < 0.0001). Equivalence of survival was demonstrated between cardiothoracic vs non-cardiothoracic injury (OR 1.038; p 1.000). Survival was worse for USA vs non-USA cohorts (OR 1.59; p 0.0012). Conclusions: Penetrating injury remains a robust indication for EDT. Non-cardiothoracic cause of cardiac arrest should not preclude EDT. In the absence of on scene SOL, survival following EDT is extremely unlikely. Survival is significantly higher in the non-USA publications; reasons for this are highly complex. A UK multicentre prospective study which collects standardised data on all EDTs could provide robust evidence for better patient stratification. [ABSTRACT FROM AUTHOR]

Essential mineral (iron and zinc) deficiencies are still prevalent in the Semi-arid Tropics, where many people consume monotonous, predominantly cereal-based diets. This study aimed to evaluate the potential of including tropical plant foodstuffs high in iron and zinc (moringa leaves and roselle calyces) or mineral availability enhancers (baobab fruit pulp) in a pearl millet-based food containing a plant food-based provitamin A source, with the aim of preventing iron and zinc deficiencies in the Semi-arid Tropics. Mineral bioaccessibility was assessed by dialysability assay. Moringa, roselle and baobab considerably increased iron and zinc bioaccessibility when added at 10 parts:100 parts pearl millet (dry basis). These foodstuffs, increased the contribution to the absolute iron requirements of women of reproductive age by 2.5, 2.1 and 2.3 times for moringa, roselle and baobab, respectively and to their absolute zinc requirements by 2.4, 2.1 and 2.7 times, respectively. Combining these plant foodstuffs could contribute up to 28% and 41% of the women's absolute iron and zinc requirements, respectively, from a single meal. Moringa, despite having the highest iron content, when added at a very high level (30 parts:100 parts pearl millet) decreased bioaccessible iron and zinc, most probably primarily due to its high calcium content. Food-to-food fortification of staple cereal foods with moringa leaves, roselle calyces or baobab fruit pulp plus a provitamin A source can potentially sustainably improve iron and zinc bioavailability in the diets of at-risk communities in the Semi-arid Tropics. [ABSTRACT FROM AUTHOR]

Purpose: The indications for pre-hospital resuscitative thoracotomy (PHRT) remain undefined. The aim of this paper is to explore the variation in practice for PHRT in the UK, and review the published literature.Methods: MEDLINE and PUBMED search engines were used to identify all relevant articles and 22 UK Air Ambulance Services were sent an electronic questionnaire to assess their PHRT practice.Results: Four European publications report PHRT survival rates of 9.7, 18.3, 10.3 and 3.0% in 31, 71, 39 and 33 patients, respectively. All patients sustained penetrating chest injury. Six case reports also detail survivors of PHRT, again all had sustained penetrating thoracic injury. One Japanese paper presents 34 cases of PHRT following blunt trauma, of which 26.4% survived to the intensive therapy unit but none survived to discharge. A UK population reports a single survivor of PHRT following blunt trauma but the case details remain unpublished. Ten (45%) air ambulance services responded, each service reported different indications for PHRT. All perform PHRT for penetrating chest trauma, however, length of allowed pre-procedure down time varied, ranging from 10 to 20 min. Seventy percent perform PHRT for blunt traumatic cardiac arrest, a procedure which is likely to require aggressive concurrent circulatory support, despite this only 5/10 services carry pre-hospital blood products.Conclusions: Current indications for PHRT vary amongst different geographical locations, across the UK, and worldwide. Survivors are likely to have sustained penetrating chest injury with short down time. There is only one published survivor of PHRT following blunt trauma, despite this, PHRT is still being performed in the UK for this indication. [ABSTRACT FROM AUTHOR]

Understanding population dynamics during natural disasters is important to build urban resilience in preparation for extreme events. Social media has emerged as an important source for disaster managers to identify dynamic polarity of sentiments over the course of disasters, to understand human mobility patterns, and to enhance decision making and disaster recovery efforts. Although there is a growing body of literature on sentiment and human mobility in disaster contexts, the spatiotemporal characteristics of sentiment and the relationship between sentiment and mobility over time have not been investigated in detail. This study therefore addresses this research gap and proposes a new lens to evaluate population dynamics during disasters by coupling sentiment and mobility. We collected 3.74 million geotagged tweets over 8 weeks to examine individuals’ sentiment and mobility before, during and after the M6.0 South Napa, California Earthquake in 2014. Our research results reveal that the average sentiment level decreases with the increasing intensity of the earthquake. We found that similar levels of sentiment tended to cluster in geographical space, and this spatial autocorrelation was significant over areas of different earthquake intensities. Moreover, we investigated the relationship between temporal dynamics of sentiment and mobility. We examined the trend and seasonality of the time series and found cointegration between the series. We included effects of the earthquake and built a segmented regression model to describe the time series finding that day-to-day changes in sentiment can either lead or lag daily changed mobility patterns. This study contributes a new lens to assess the dynamic process of disaster resilience unfolding over large spatial scales. [ABSTRACT FROM AUTHOR]

Purpose: Artificial neural networks (ANN) are increasingly applied to complex medical problem solving algorithms because their outcome prediction performance is superior to existing multiple regression models. ANN can successfully identify symptomatic cerebral vasospasm (SCV) in adults presenting after aneurysmal subarachnoid hemorrhage (aSAH). Although SCV is unusual in children with aSAH, the clinical consequences are severe. Consequently, reliable tools to predict patients at greatest risk for SCV may have significant value. We applied ANN modeling to a consecutive cohort of pediatric aSAH cases to assess its ability to predict SCV. Methods: A retrospective chart review was conducted to identify patients < 21 years of age who presented with spontaneously ruptured, non-traumatic, non-mycotic, non-flow-related intracranial arterial aneurysms to our institution between January 2002 and January 2015. Demographics, clinical, radiographic, and outcome data were analyzed using an adapted ANN model using learned value nodes from the adult aneurysmal SAH dataset previously reported. The strength of the ANN prediction was measured between − 1 and 1 with − 1 representing no likelihood of SCV and 1 representing high likelihood of SCV. Results: Sixteen patients met study inclusion criteria. The median age for aSAH patients was 15 years. Ten underwent surgical clipping and 6 underwent endovascular coiling for definitive treatment. One patient experienced SCV and 15 did not. The ANN applied here was able to accurately predict all 16 outcomes. The mean strength of prediction for those who did not exhibit SCV was − 0.86. The strength for the one patient who did exhibit SCV was 0.93. Conclusions: Adult-derived aneurysmal SAH value nodes can be applied to a simple AAN model to accurately predict SCV in children presenting with aSAH. Further work is needed to determine if ANN models can prospectively predict SCV in the pediatric aSAH population in toto; adapted to include mycotic, traumatic, and flow-related origins as well. [ABSTRACT FROM AUTHOR]

Based on previous investigations, adult Australian plague locusts are believed to migrate on warm nights (with evening temperatures >25 °C), provided daytime flight is suppressed by surface winds greater than the locusts' flight speed, which has been shown to be 3.1 m s. Moreover, adult locusts are believed to undertake briefer 'dispersal' flights on nights with evening temperature >20 °C. To reassess the utility of these conditions for forecasting locust flight, contingency tests were conducted comparing the nights selected on these bases (predicted nights) for the months of November, January, and March and the nights when locust migration were detected with an insect monitoring radar (actual nights) over a 7-year period. In addition, the wind direction distributions and mean wind directions on all predicted nights and actual nights were compared. Observations at around 395 m above ground level (AGL), the height at which radar observations have shown that the greatest number of locusts fly, were used to determine the actual nights. Tests and comparisons were also made for a second height, 990 m AGL, as this was used in the previous investigation. Our analysis shows that the proposed criteria are successful from predicting migratory flight only in March, when the surface temperature is effective as a predicting factor. Surface wind speed has no predicting power. It is suggested that a strong daytime surface wind speed requirement should not be considered and other meteorological variables need to be added to the requirement of a warm surface temperature around dusk for the predictions to have much utility. [ABSTRACT FROM AUTHOR]