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Introduction Degenerative Cervical Myelopathy (DCM) is a common and disabling condition, with a relatively modest research capacity. In order to accelerate knowledge discovery, the AO Spine RECODE-DCM project has recently established the top priorities for DCM research. Uptake of these priorities within the research community will require their effective dissemination, which can be supported by identifying key opinion leaders (KOLs). In this paper, we aim to identify KOLs using artificial intelligence. We produce and explore a DCM co-authorship network, to characterise researchers’ impact within the research field. Methods Through a bibliometric analysis of 1674 scientific papers in the DCM field, a co-authorship network was created. For each author, statistics about their connections to the co-authorship network (and so the nature of their collaboration) were generated. Using these connectedness statistics, a neural network was used to predict H-Index for each author (as a proxy for research impact). The neural network was retrospectively validated on an unseen author set. Results DCM research is regionally clustered, with strong collaboration across some international borders (e.g., North America) but not others (e.g., Western Europe). In retrospective validation, the neural network achieves a correlation coefficient of 0.86 (p Discussion Analysis of the neural network shows that the nature of collaboration strongly impacts an author’s research visibility, and therefore suitability as a KOL. This also suggests greater collaboration within the DCM field could help to improve both individual research visibility and global synergy.

15 páginas, 4 figuras, 2 tablas, Cystic echinococcosis (CE) remains an important health problem in many regions of the world, including those where control programs have been implemented. In Spain, available information on CE is incomplete, and its importance tends to be underestimated due to underreporting and to the lack of compulsory notification. In this paper we used hospitalized CE discharge data to describe CE main epidemiological characteristics and CE geographical and temporal trends in Spain. Although CE hospitalization rates have decreased considerably in the last years, the overall economic losses estimations due to CE were still rather high in Spain. The need for a continuous and well-defined source, with national coverage, of epidemiological data on CE is emphasized in this paper, not only to have a more accurate picture but to monitor the control activities in place.

Sheep remains constitute the main archaeozoological evidence for the presence of Early Neolithic human groups in the highlands of the Southern Pyrenees but understanding the role of herding activities in the Neolithisation process of this mountain ecosystem calls for the analysis of large and well-dated faunal assemblages. Cova de Els Trocs (Bisaurri, Huesca, Spain), a cave located at 1564 m a.s.l on the southern slopes of the Central Pyrenees, is an excellent case study since it was seasonally occupied throughout the Neolithic (ca. 5312–2913 cal. BC) and more than 4000 caprine remains were recovered inside. The multi-proxy analytical approach here presented has allowed us to offer new data elaborating on vertical mobility practices and herd management dynamics as has not been attempted up until now within Neolithic high-mountain sites in the Iberian Peninsula. For the first time, δ18O and δ13C stable isotope analyses offer direct evidence on both the regular practice of altitudinal movements of sheep flocks and the extended breeding season of sheep. Autumn births are recorded from the second half of the fifth millennium cal. BC onwards. Age-at-death distributions illustrate the progressive decline in caprine perinatal mortality together with the rising survival rate of individuals older than six months of age and the larger frequency of adults. This trend alongside the ‘off-season’ lambing signal at the implementation of husbandry techniques over time, probably aiming to increase the size of the flocks and their productivity. Palaeoparasitological analyses of sediment samples document also the growing reliance on herding activities of the human groups visiting the Els Trocs cave throughout the Neolithic sequence. In sum, our work provides substantial arguments to conclude that the advanced herding management skills of the Early Neolithic communities arriving in Iberia facilitated the anthropisation process of the subalpine areas of the Central Pyrenees., This paper was supported by several projects awarded to MR-G: ‘Los Caminos del Neolítico’ (HAR2009-09027) and ‘Los Caminos del Neolítico II’ (HAR2013-46800 P) were granted by the National R&D&I Plan/Ministry of Economy, Industry and Competitiveness (https://www.ciencia.gob.es/portal/site/MICINN/) and co-financed by the Government of Aragón (https://www.aragon.es/), and ‘La Memoria del Camino: Ciencia y divulgación de las primeras rutas pecuarias neolíticas en el Pirineo-MEDELCA’ (FCT-2015-9947) was financed by the Spanish Foundation for Science and Technology (FECYT) (https://www.fecyt.es/). The archaeozoological research was carried out within the framework of the project awarded to MM-G ‘… y la oveja domesticó al pastor: Señales genómicas y arqueozoológicas de los primeros ovinos durante la neolitización de la península ibérica’ (HAR2016-75914-R) by the National R&D&I Plan/Ministry of Economy, Industry and Competitiveness (https://www.ciencia.gob.es/portal/site/MICINN/). AH was awarded a PhD grant by the Université Fédérale de Toulouse ANR-11-IDEX-0002-02 (https://www.univ-toulouse.fr/). Support of the publication fee was granted by the CSIC Open Access Publication Initiative through its Unit of Information Resources for Research (URICI).

Morphological classification of living things has challenged science for several centuries and has led to a wide range of objective morphometric approaches in data gathering and analysis. In this paper we explore those methods using apple cultivars, a model biological system in which discrete groups are pre-defined but in which there is a high level of overall morphological similarity. The effectiveness of morphometric techniques in discovering the groups is evaluated using statistical learning tools. No one technique proved optimal in classification on every occasion, linear morphometric techniques slightly out-performing geometric (72.6% accuracy on test set versus 66.7%). The combined use of these techniques with post-hoc knowledge of their individual successes with particular cultivars achieves a notably higher classification accuracy (77.8%). From this we conclude that even with pre-determined discrete categories, a range of approaches is needed where those categories are intrinsically similar to each other, and we raise the question of whether in studies where potentially continuous natural variation is being categorised the level of match between categories is routinely set too high.

This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Although a large amount of acoustic indicators have already been proposed in the literature to evaluate the hypokinetic dysarthria of people with Parkinson’s Disease, the goal of this work is to identify and interpret new reliable and complementary articulatory biomarkers that could be applied to predict/evaluate Parkinson’s Disease from a diadochokinetic test, contributing to the possibility of a further multidimensional analysis of the speech of parkinsonian patients. The new biomarkers proposed are based on the kinetic behaviour of the envelope trace, which is directly linked with the articulatory dysfunctions introduced by the disease since the early stages. The interest of these new articulatory indicators stands on their easiness of identification and interpretation, and their potential to be translated into computer based automatic methods to screen the disease from the speech. Throughout this paper, the accuracy provided by these acoustic kinetic biomarkers is compared with the one obtained with a baseline system based on speaker identification techniques. Results show accuracies around 85% that are in line with those obtained with the complex state of the art speaker recognition techniques, but with an easier physical interpretation, which open the possibility to be transferred to a clinical setting., Fulbright U.S. Student Program

The Anaplastic Lymphoma Kinase (Alk) receptor tyrosine kinase (RTK) plays a critical role in the specification of founder cells (FCs) in the Drosophila visceral mesoderm (VM) during embryogenesis. Reporter gene and CRISPR/Cas9 deletion analysis reveals enhancer regions in and upstream of the Alk locus that influence tissue-specific expression in the amnioserosa (AS), the VM and the epidermis. By performing high throughput yeast one-hybrid screens (Y1H) with a library of Drosophila transcription factors (TFs) we identify Odd-paired (Opa), the Drosophila homologue of the vertebrate Zic family of TFs, as a novel regulator of embryonic Alk expression. Further characterization identifies evolutionarily conserved Opa-binding cis-regulatory motifs in one of the Alk associated enhancer elements. Employing Alk reporter lines as well as CRISPR/Cas9-mediated removal of regulatory elements in the Alk locus, we show modulation of Alk expression by Opa in the embryonic AS, epidermis and VM. In addition, we identify enhancer elements that integrate input from additional TFs, such as Binou (Bin) and Bagpipe (Bap), to regulate VM expression of Alk in a combinatorial manner. Taken together, our data show that the Opa zinc finger TF is a novel regulator of embryonic Alk expression., Author summary The Alk receptor tyrosine kinase is employed repeatedly during Drosophila development to drive signaling events in a variety of tissues. The spatial and temporal expression pattern of the Alk gene is tightly regulated. Identifying factors that influence the expression of Alk is important to better understand how Alk signaling is controlled. In this paper we characterize cis-regulatory sequences in the Alk locus and the transcription factors that bind them to govern Alk expression in the Drosophila embryo. Using a robotic protein-DNA interaction assay, we identified the Zic family transcription factor Odd-paired as a factor that binds to regulatory elements in the Alk locus. Binding of Odd-paired to Alk cis-regulatory elements varies spatially, revealing a requirement for additional transcription factors such as the NK3 and FoxF orthologues Bagpipe and Biniou in a subset of Alk-expressing tissues. Our findings provide new insight into the dynamics underlying temporal and spatial regulation of the Alk receptor during embryogenesis.

We have examined the remains of a Pilgrim burial from St Mary Magdalen, Winchester. The individual was a young adult male, aged around 18–25 years at the time of death. Radiocarbon dating showed the remains dated to the late 11th–early 12th centuries, a time when pilgrimages were at their height in Europe. Several lines of evidence in connection with the burial suggested this was an individual of some means and prestige. Although buried within the leprosarium cemetery, the skeleton showed only minimal skeletal evidence for leprosy, which was confined to the bones of the feet and legs. Nonetheless, molecular testing of several skeletal elements, including uninvolved bones all showed robust evidence of DNA from Mycobacterium leprae, consistent with the lepromatous or multibacillary form of the disease. We infer that in life, this individual almost certainly suffered with multiple soft tissue lesions. Genotyping of the M.leprae strain showed this belonged to the 2F lineage, today associated with cases from South-Central and Western Asia. During osteological examination it was noted that the cranium and facial features displayed atypical morphology for northern European populations. Subsequently, geochemical isotopic analyses carried out on tooth enamel indicated that this individual was indeed not local to the Winchester region, although it was not possible to be more specific about their geographic origin., Author Summary This multidisciplinary research article, involving biomolecular analysis, osteology, strontium and oxygen isotopic analyses and archaeology, examines the remains of a Pilgrim burial excavated from the medieval leprosy hospital of St Mary Magdalen, Winchester, UK. Radiocarbon dating showed the remains dated to the late 11th–early 12th centuries, a time when pilgrimages were at their height in Europe. The leprosarium at Winchester is one of the earliest excavated examples from Western Europe and has been the subject of a series of recent academic papers. The site is remarkable for the high number of burials displaying skeletal lesions characteristic of leprosy (86%) and the state of preservation of biomolecular markers of the disease, including mycolipids and DNA. Genotyping of the M.leprae strain showed this belonged to the 2F lineage, today associated with cases from South-Central and Western Asia. Several aspects of the burial and dietary isotope analysis indicated this was an individual of some prestige and means; an unusual cranial morphology pointed to possible origin outside of the British Isles. Strontium and oxygen isotopic analyses confirmed he was not local to the Winchester area but were not able to pinpoint his precise origins. Overall these findings confirm the benefits of a multidisciplinary approach which allows investigation of the wider relationship between leprosy, medieval pilgrimage and M.leprae transmission.

Transmission of zoonotic cutaneous leishmaniasis (ZCL) depends on the presence, density and distribution of Leishmania major rodent reservoir and the development of these rodents is known to have a significant dependence on environmental and climate factors. ZCL in Tunisia is one of the most common forms of leishmaniasis. The aim of this paper was to build a regression model of ZCL cases to identify the relationship between ZCL occurrence and possible risk factors, and to develop a predicting model for ZCL's control and prevention purposes. Monthly reported ZCL cases, environmental and bioclimatic data were collected over 6 years (2009–2015). Three rural areas in the governorate of Sidi Bouzid were selected as the study area. Cross-correlation analysis was used to identify the relevant lagged effects of possible risk factors, associated with ZCL cases. Non-parametric modeling techniques known as generalized additive model (GAM) and generalized additive mixed models (GAMM) were applied in this work. These techniques have the ability to approximate the relationship between the predictors (inputs) and the response variable (output), and express the relationship mathematically. The goodness-of-fit of the constructed model was determined by Generalized cross-validation (GCV) score and residual test. There were a total of 1019 notified ZCL cases from July 2009 to June 2015. The results showed seasonal distribution of reported ZCL cases from August to January. The model highlighted that rodent density, average temperature, cumulative rainfall and average relative humidity, with different time lags, all play role in sustaining and increasing the ZCL incidence. The GAMM model could be applied to predict the occurrence of ZCL in central Tunisia and could help for the establishment of an early warning system to control and prevent ZCL in central Tunisia., Author summary Zoonotic cutaneous leishmaniasis is a human vector-borne disease caused by the parasite Leishmania major and is well spread in rural areas where human resources in public health and infrastructure are limited. The cycle of transmission of the disease is complex because of the impact of climate change. In this study we evaluated the impact of bioclimatic factors on the transmission of the disease in three districts of Sidi Bouzid, central Tunisia. We found that the occurrence of zoonotic cutaneous leishmaniasis is mainly related to average temperature with 4 months lags, rodents' density lagged 2 months, relative humidity with 4 months lags and cumulative rainfall lagged 1 month. We also confirmed that our best-fit model predict well the occurrence of the disease.

Patients with chronic kidney disease (CKD) have an increased incidence of cardiovascular events (CVE). The contribution of subclinical atheromatosis extent, including femoral arteries, to CVE in CKD patients has not been investigated. In this paper, we examine the prognostic value of subclinical atheromatosis extent, assessed as the number of arterial territories with plaque, in predicting the incidence of major and minor CVE. The NEFRONA is a multicenter, prospective cohorts study that recruited 2445 CKD subjects and 559 controls, free from previous cardiovascular disease, in 81 medical centers across Spain. The presence of atheroma plaque was assessed by arterial ultrasound in ten arterial territories (carotid and femoral). The predictive power of the presence or absence of atheroma plaque in any territory was compared with the quantification of atheroma extent as the number of territories with plaque. During the median follow up of 48 months, 216 CVE were reported. Factors predicting the incidence of CVE in the whole cohort were being male, CKD patient, lower levels of 25(OH) vitamin D, higher levels of cholesterol and the extent of subclinical atheromatosis, yielding a higher concordance (C) index than the presence or absence of plaque. In stratified analysis including specific factors of CKD patients not on dialysis, the variables predicting CVE were the same as in the whole cohort, plus higher levels of potassium. Again, the inclusion of the information about atheromatosis as number of territories with plaque, presented a higher C index than the presence or absence of plaque. In the dialysis population, significant variables were older age, diabetes, dialysis vintage and higher levels of cholesterol and phosphate. In this case the higher C index was obtained with the information about plaque presence. Subclinical atheromatosis extent, including femoral arteries, influences CVE in CKD and its detection could improve the prediction of cardiovascular events. The NEFRONA study is funded by a research grant from AbbVie and the Spanish government RETIC (RD16/0009/0011), FIS PI16/01354 and FEDER funds

In computational biology, modeling is a fundamental tool for formulating, analyzing and predicting complex phenomena. Most neuron models, however, are designed to reproduce certain small sets of empirical data. Hence their outcome is usually not compatible or comparable with other models or datasets, making it unclear how widely applicable such models are. In this study, we investigate these aspects of modeling, namely credibility and generalizability, with a specific focus on auditory neurons involved in the localization of sound sources. The primary cues for binaural sound localization are comprised of interaural time and level differences (ITD/ILD), which are the timing and intensity differences of the sound waves arriving at the two ears. The lateral superior olive (LSO) in the auditory brainstem is one of the locations where such acoustic information is first computed. An LSO neuron receives temporally structured excitatory and inhibitory synaptic inputs that are driven by ipsi- and contralateral sound stimuli, respectively, and changes its spike rate according to binaural acoustic differences. Here we examine seven contemporary models of LSO neurons with different levels of biophysical complexity, from predominantly functional ones (‘shot-noise’ models) to those with more detailed physiological components (variations of integrate-and-fire and Hodgkin-Huxley-type). These models, calibrated to reproduce known monaural and binaural characteristics of LSO, generate largely similar results to each other in simulating ITD and ILD coding. Our comparisons of physiological detail, computational efficiency, predictive performances, and further expandability of the models demonstrate (1) that the simplistic, functional LSO models are suitable for applications where low computational costs and mathematical transparency are needed, (2) that more complex models with detailed membrane potential dynamics are necessary for simulation studies where sub-neuronal nonlinear processes play important roles, and (3) that, for general purposes, intermediate models might be a reasonable compromise between simplicity and biological plausibility., Author summary Computational models help our understanding of complex biological systems, by identifying their key elements and revealing their operational principles. Close comparisons between model predictions and empirical observations ensure our confidence in a model as a building block for further applications. Most current neuronal models, however, are constructed to replicate only a small specific set of experimental data. Thus, it is usually unclear how these models can be generalized to different datasets and how they compare with each other. In this paper, seven neuronal models are examined that are designed to reproduce known physiological characteristics of auditory neurons involved in the detection of sound source location. Despite their different levels of complexity, the models generate largely similar results when their parameters are tuned with common criteria. Comparisons show that simple models are computationally more efficient and theoretically transparent, and therefore suitable for rigorous mathematical analyses and engineering applications including real-time simulations. In contrast, complex models are necessary for investigating the relationship between underlying biophysical processes and sub- and suprathreshold spiking properties, although they have a large number of unconstrained, unverified parameters. Having identified their advantages and drawbacks, these auditory neuron models may readily be used for future studies and applications.

Pertussis is a contagious respiratory disease which mainly affects young children and can be fatal if left untreated. The World Health Organization estimates 16 million pertussis cases annually worldwide resulting in over 200,000 deaths. It is prevalent mainly in developing countries where it is difficult to diagnose due to the lack of healthcare facilities and medical professionals. Hence, a low-cost, quick and easily accessible solution is needed to provide pertussis diagnosis in such areas to contain an outbreak. In this paper we present an algorithm for automated diagnosis of pertussis using audio signals by analyzing cough and whoop sounds. The algorithm consists of three main blocks to perform automatic cough detection, cough classification and whooping sound detection. Each of these extract relevant features from the audio signal and subsequently classify them using a logistic regression model. The output from these blocks is collated to provide a pertussis likelihood diagnosis. The performance of the proposed algorithm is evaluated using audio recordings from 38 patients. The algorithm is able to diagnose all pertussis successfully from all audio recordings without any false diagnosis. It can also automatically detect individual cough sounds with 92% accuracy and PPV of 97%. The low complexity of the proposed algorithm coupled with its high accuracy demonstrates that it can be readily deployed using smartphones and can be extremely useful for quick identification or early screening of pertussis and for infection outbreaks control.

This paper is a country case study for the Universal Health Coverage Collection, organized by WHO. Gemini Mtei and colleagues illustrate progress towards UHC and its monitoring and evaluation in Tanzania. Please see later in the article for the Editors' Summary.

__Introduction:__ Inconsistency in the time trade-off (TTO) task in EQ-5D-5L occurs when a respondent gives a higher value to a logically worse health state, the occurrence of inconsistency compromises the quality of the data. It is not yet clear which factors are associated with individual level inconsistency. Relating inconsistency to the characteristics of the respondent, interviewer, and the interview process could be helpful in understanding the causes of inconsistency. The objective of this paper is to discover the factors associated with individual level inconsistencies. __Methods:__ Twenty interviewers interviewed 1,296 respondents and each respondent valued 10 health states using the EQ-VT platform in 5 cities in China. At the respondent level, inconsistency was identified in terms of severity and quantity and related to the respondent’s background characteristics, the time and iterations spent on the wheelchair example task, and the formal TTO tasks, using multilevel multinomial regression analyses. Interviewers’ impact on inconsistencies was analyzed using single level multinomial regression analyses. __Results:__ In the full dataset, slight inconsistency was more related to the interview process (Time spent on TTO task: RRR = 1.246 with 95%CI: 1.076,1.441; time spent on Wheelchair example: RRR = 0.815 with 95%CI:0.699,0.952) while severe inconsistency was more related to respondent’s gender (Gender: RRR = 2.347 with 95%CI:1.429,3.855). One Interviewer (Interviewer 7: RRR = 7.335 with 95%CI:1.908,28.195) and interviewer’s experience (Sequence: RRR = 0.511 with 95%CI:0.385,0.678) in general showed strong influence over inconsistency in the TTO task. __Conclusion:__ In conclusion, logical inconsistency in the valuation of EQ-5D-5L health states is associated not only with respondents’ characteristics but also with interviewers’ performance and the interview process. The role of interviewers and the importance of interviewer training may be more crucial than hitherto believed. This finding could be generalizable to other interviewer-administered health-state valuation study.

textabstractBackground: Italy has a population of 60 million and a universal coverage single-payer healthcare system, which mandates collection of healthcare administrative data in a uniform fashion throughout the country. On the other hand, organization of the health system takes place at the regional level, and local initiatives generate natural experiments. This is happening in particular in primary care, due to the need to face the growing burden of chronic diseases. Health services research can compare and evaluate local initiatives on the basis of the common healthcare administrative data.However reliability of such data in this context needs to be assessed, especially when comparing different regions of the country. In this paper we investigated the validity of healthcare administrative databases to compute indicators of compliance with standards of care for diabetes, ischaemic heart disease (IHD) and heart failure (HF). Methods: We compared indicators estimated from healthcare administrative data collected by Local Health Authorities in five Italian regions with corresponding estimates from clinical data collected by General Practitioners (GPs). Four indicators of diagnostic follow-up (two for diabetes, one for IHD and one for HF) and four indicators of appropriate therapy (two each for IHD and HF) were considered. Results: Agreement between the two data sources was very good, except for indicators of laboratory diagnostic follow-up in one region and for the indicator of bioimaging diagnostic follow-up in all regions, where measurement with administrative data underestimated quality. Conclusion: According to evidence presented in this study, estimating compliance with standards of care for diabetes, ischaemic heart disease and heart failure from healthcare databases is likely to produce reliable results, even though completeness of data on diagnostic procedures should be assessed first. Performing studies comparing regions using such indicators as outcomes is a promising development with potential to improve quality governance in the Italian healthcare system.

In small animal imaging studies, when the locations of the micro-structures of interest are unknown a priori, there is a simultaneous need for full-body coverage and high resolution. In MRI, additional requirements to image contrast and acquisition time will often make it impossible to acquire such images directly. Recently, a resolution enhancing post-processing technique called super-resolution reconstruction (SRR) has been demonstrated to improve visualization and localization of micro-structures in small animal MRI by combining multiple low-resolution acquisitions. However, when the field-of-view is large relative to the desired voxel size, solving the SRR problem becomes very expensive, in terms of both memory requirements and computation time. In this paper we introduce a novel local approach to SRR that aims to overcome the computational problems and allow researchers to efficiently explore both global and local characteristics in whole-body small animal MRI. The method integrates state-of-the-art image processing techniques from the areas of articulated atlas-based segmentation, planar reformation, and SRR. A proof-of-concept is provided with two case studies involving CT, BLI, and MRI data of bone and kidney tumors in a mouse model. We show that local SRR-MRI is a computationally efficient complementary imaging modality for the precise characterization of tumor metastases, and that the method provides a feasible high-resolution alternative to conventional MRI.

Generalization of the dynamic clamp concept in neurophysiology and behavior. Chamorro et al. PLoS ONE. 2012. 7(7) doi: 10.1371/journal.pone.0040887, The idea of closed-loop interaction in in vitro and in vivo electrophysiology has been successfully implemented in the dynamic clamp concept strongly impacting the research of membrane and synaptic properties of neurons. In this paper we show that this concept can be easily generalized to build other kinds of closed-loop protocols beyond (or in addition to) electrical stimulation and recording in neurophysiology and behavioral studies for neuroethology. In particular, we illustrate three different examples of goal-driven real-time closed-loop interactions with drug microinjectors, mechanical devices and video event driven stimulation. Modern activity-dependent stimulation protocols can be used to reveal dynamics (otherwise hidden under traditional stimulation techniques), achieve control of natural and pathological states, induce learning, bridge between disparate levels of analysis and for a further automation of experiments. We argue that closed-loop interaction calls for novel real time analysis, prediction and control tools and a new perspective for designing stimulus-response experiments, which can have a large impact in neuroscience research., This work was supported by Spanish MICINN (Ministerio de Ciencia e Innovacion) BFU2009-08473 and TIN-2010-19607.