Classifying elephant behaviour through seismic vibrations

Seismic waves — vibrations within and along the Earth’s surface — are ubiquitous sources of information. During propagation, physical factors can obscure information transfer via vibrations and influence propagation range [1]. Here, we explore how terrain type and background seismic noise influence the propagation of seismic vibrations generated by African elephants. In Kenya, we recorded the ground-based vibrations of different wild elephant behaviours, such as locomotion and infrasonic vocalisations [2], as well as natural and anthropogenic seismic noise. We employed techniques from seismology to transform the geophone recordings into source functions — the time-varying seismic signature generated at the source. We used computer modelling to constrain the propagation ranges of elephant seismic vibrations for different terrains and noise levels. Behaviours that generate a high force on a sandy terrain with low noise propagate the furthest, over the kilometre scale. Our modelling also predicts that specific elephant behaviours can be distinguished and monitored over a range of propagation distances and noise levels. We conclude that seismic cues have considerable potential for both behavioural classification and remote monitoring of wildlife. In particular, classifying the seismic signatures of specific behaviours of large mammals remotely in real time, such as elephant running, could inform on poaching threats

Extragalactic Radio Continuum Surveys and the Transformation of Radio Astronomy

Next-generation radio surveys are about to transform radio astronomy by discovering and studying tens of millions of previously unknown radio sources. These surveys will provide new insights to understand the evolution of galaxies, measuring the evolution of the cosmic star formation rate, and rivalling traditional techniques in the measurement of fundamental cosmological parameters. By observing a new volume of observational parameter space, they are also likely to discover unexpected new phenomena. This review traces the evolution of extragalactic radio continuum surveys from the earliest days of radio astronomy to the present, and identifies the challenges that must be overcome to achieve this transformational change.Comment: To be published in Nature Astronomy 18 Sept 201

Maximum Likelihood Estimation of the Negative Binomial Dispersion Parameter for Highly Overdispersed Data, with Applications to Infectious Diseases

BACKGROUND: The negative binomial distribution is used commonly throughout biology as a model for overdispersed count data, with attention focused on the negative binomial dispersion parameter, k. A substantial literature exists on the estimation of k, but most attention has focused on datasets that are not highly overdispersed (i.e., those with k≥1), and the accuracy of confidence intervals estimated for k is typically not explored. METHODOLOGY: This article presents a simulation study exploring the bias, precision, and confidence interval coverage of maximum-likelihood estimates of k from highly overdispersed distributions. In addition to exploring small-sample bias on negative binomial estimates, the study addresses estimation from datasets influenced by two types of event under-counting, and from disease transmission data subject to selection bias for successful outbreaks. CONCLUSIONS: Results show that maximum likelihood estimates of k can be biased upward by small sample size or under-reporting of zero-class events, but are not biased downward by any of the factors considered. Confidence intervals estimated from the asymptotic sampling variance tend to exhibit coverage below the nominal level, with overestimates of k comprising the great majority of coverage errors. Estimation from outbreak datasets does not increase the bias of k estimates, but can add significant upward bias to estimates of the mean. Because k varies inversely with the degree of overdispersion, these findings show that overestimation of the degree of overdispersion is very rare for these datasets

Electrocardiogram-based mortality prediction in patients with COVID-19 using machine learning

Background and purpose: The electrocardiogram (ECG) is frequently obtained in the work-up of COVID-19 patients. So far, no study has evaluated whether ECG-based machine learning models have added value to predict in-hospital mortality specifically in COVID-19 patients. / Methods: Using data from the CAPACITY-COVID registry, we studied 882 patients admitted with COVID-19 across seven hospitals in the Netherlands. Raw format 12-lead ECGs recorded within 72 h of admission were studied. With data from five hospitals (n = 634), three models were developed: (a) a logistic regression baseline model using age and sex, (b) a least absolute shrinkage and selection operator (LASSO) model using age, sex and human annotated ECG features, and (c) a pre-trained deep neural network (DNN) using age, sex and the raw ECG waveforms. Data from two hospitals (n = 248) was used for external validation. / Results: Performances for models a, b and c were comparable with an area under the receiver operating curve of 0.73 (95% confidence interval [CI] 0.65–0.79), 0.76 (95% CI 0.68–0.82) and 0.77 (95% CI 0.70–0.83) respectively. Predictors of mortality in the LASSO model were age, low QRS voltage, ST depression, premature atrial complexes, sex, increased ventricular rate, and right bundle branch block. / Conclusion: This study shows that the ECG-based prediction models could be helpful for the initial risk stratification of patients diagnosed with COVID-19, and that several ECG abnormalities are associated with in-hospital all-cause mortality of COVID-19 patients. Moreover, this proof-of-principle study shows that the use of pre-trained DNNs for ECG analysis does not underperform compared with time-consuming manual annotation of ECG features

Association between H-RAS T81C genetic polymorphism and gastrointestinal cancer risk: A population based case-control study in China

<p>Abstract</p> <p>Background</p> <p>Gastrointestinal cancer, such as gastric, colon and rectal cancer, is a major medical and economic burden worldwide. However, the exact mechanism of gastrointestinal cancer development still remains unclear. <it>RAS </it>genes have been elucidated as major participants in the development and progression of a series of human tumours and the single nucleotide polymorphism at <it>H-RAS </it>cDNA position 81 was demonstrated to contribute to the risks of bladder, oral and thyroid carcinoma. Therefore, we hypothesized that this polymorphisms in <it>H-RAS </it>could influence susceptibility to gastrointestinal cancer as well, and we conducted this study to test the hypothesis in Chinese population.</p> <p>Methods</p> <p>A population based case-control study, including 296 cases with gastrointestinal cancer and 448 healthy controls selected from a Chinese population was conducted. <it>H-RAS </it>T81C polymorphism was genotyped by Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-RFLP) assay.</p> <p>Results</p> <p>In the healthy controls, the TT, TC and CC genotypes frequencies of <it>H-RAS </it>T81C polymorphism, were 79.24%, 19.87% and 0.89%, respectively, and the C allele frequency was 10.83%. Compared with TT genotype, the TC genotype was significantly associated with an increased risk of gastric cancer (adjusted OR = 3.67, 95%CI = 2.21–6.08), while the CC genotype showed an increased risk as well (adjusted OR = 3.29, 95%CI = 0.54–19.86), but it was not statistically significant. In contrast, the frequency of TC genotype was not significantly increased in colon cancer and rectal cancer patients. Further analysis was performed by combining TC and CC genotypes compared against TT genotype. As a result, a statistically significant risk with adjusted OR of 3.65 (95%CI, 2.22–6.00) was found in gastric cancer, while no significant association of <it>H-RAS </it>T81C polymorphism with colon cancer and rectal cancer was observed.</p> <p>Conclusion</p> <p>These findings indicate, for the first time, that there is an <it>H-RAS </it>T81C polymorphism existing in Chinese population, and this SNP might be a low penetrance gene predisposition factor for gastric cancer.</p

Modulation of Cytochrome P450 Metabolism and Transport across Intestinal Epithelial Barrier by Ginger Biophenolics

Natural and complementary therapies in conjunction with mainstream cancer care are steadily gaining popularity. Ginger extract (GE) confers significant health-promoting benefits owing to complex additive and/or synergistic interactions between its bioactive constituents. Recently, we showed that preservation of natural ‘‘milieu’’ confers superior anticancer activity on GE over its constituent phytochemicals, 6-gingerol (6G), 8-gingerol (8G), 10-gingerol (10G) and 6-shogaol (6S), through enterohepatic recirculation. Here we further evaluate and compare the effects of GE and its major bioactive constituents on cytochrome P450 (CYP) enzyme activity in human liver microsomes by monitoring metabolites of CYPspecific substrates using LC/MS/MS detection methods. Our data demonstrate that individual gingerols are potent inhibitors of CYP isozymes, whereas GE exhibits a much higher half-maximal inhibition value, indicating no possible herb-drug interactions. However, GE’s inhibition of CYP1A2 and CYP2C8 reflects additive interactions among the constituents. In addition, studies performed to evaluate transporter-mediated intestinal efflux using Caco-2 cells revealed that GE and its phenolics are not substrates of P-glycoprotein (Pgp). Intriguingly, however, 10G and 6S were not detected in the receiver compartment, indicating possible biotransformation across the Caco-2 monolayer. These data strengthen the notion that an interplay of complex interactions among ginger phytochemicals when fed as whole extract dictates its bioactivity highlighting the importance of consuming whole foods over single agents. Our study substantiates the need for an indepth analysis of hepatic biotransformation events and distribution profiles of GE and its active phenolics for the design of safe regimens

Integration in primary community care networks (PCCNs): examination of governance, clinical, marketing, financial, and information infrastructures in a national demonstration project in Taiwan

Background. Taiwan's primary community care network (PCCN) demonstration project, funded by the Bureau of National Health Insurance on March 2003, was established to discourage hospital shopping behavior of people and drive the traditional fragmented health care providers into cooperate care models. Between 2003 and 2005, 268 PCCNs were established. This study profiled the individual members in the PCCNs to study the nature and extent to which their network infrastructures have been integrated among the members (clinics and hospitals) within individual PCCNs. Methods. The thorough questionnaire items, covering the network working infrastructures - governance, clinical, marketing, financial, and information integration in PCCNs, were developed with validity and reliability confirmed. One thousand five hundred and fifty-seven clinics that had belonged to PCCNs for more than one year, based on the 2003-2005 Taiwan Primary Community Care Network List, were surveyed by mail. Nine hundred and twenty-eight clinic members responded to the surveys giving a 59.6 % response rate. Results. Overall, the PCCNs' members had higher involvement in the governance infrastructure, which was usually viewed as the most important for establishment of core values in PCCNs' organization design and management at the early integration stage. In addition, it found that there existed a higher extent of integration of clinical, marketing, and information infrastructures among the hospital-clinic member relationship than those among clinic members within individual PCCNs. The financial infrastructure was shown the least integrated relative to other functional infrastructures at the early stage of PCCN formation. Conclusion. There was still room for better integrated partnerships, as evidenced by the great variety of relationships and differences in extent of integration in this study. In addition to provide how the network members have done for their initial work at the early stage of network forming in this study, the detailed surveyed items, the concepts proposed by the managerial and theoretical professionals, could be a guide for those health care providers who have willingness to turn their business into multi-organizations. © 2007 Lin; licensee BioMed Central Ltd.published_or_final_versio

An NMR strategy for fragment-based ligand screening utilizing a paramagnetic lanthanide probe

A nuclear magnetic resonance-based ligand screening strategy utilizing a paramagnetic lanthanide probe is presented. By fixing a paramagnetic lanthanide ion to a target protein, a pseudo-contact shift (PCS) and a paramagnetic relaxation enhancement (PRE) can be observed for both the target protein and its bound ligand. Based on PRE and PCS information, the bound ligand is then screened from the compound library and the structure of the ligand–protein complex is determined. PRE is an isotropic paramagnetic effect observed within 30 Å from the lanthanide ion, and is utilized for the ligand screening in the present study. PCS is an anisotropic paramagnetic effect providing long-range (~40 Å) distance and angular information on the observed nuclei relative to the paramagnetic lanthanide ion, and utilized for the structure determination of the ligand–protein complex. Since a two-point anchored lanthanide-binding peptide tag is utilized for fixing the lanthanide ion to the target protein, this screening method can be generally applied to non-metal-binding proteins. The usefulness of this strategy was demonstrated in the case of the growth factor receptor-bound protein 2 (Grb2) Src homology 2 (SH2) domain and its low- and high-affinity ligands