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Lyciasalamandra species, like most amphibians, secrete a wide array of compounds from their granular and mucous skin glands, including the internally synthesized samandarine alkaloids, making their skin a complex organ performing a variety of functions. Lyciasalamandra helverseni and L. luschani basoglui are insular endemics of the Dodecanese islands of SE Greece, bearing distinct isolated populations, with well-documented phylogenetic profiles. Here, we employ a metabolomics approach, utilizing UPLC-ESI-HRMS/MS data of the skin secretions sampled from a number of specimens found in the islands of Karpathos, Kasos and Kastellorizo, in an effort to reveal aspects of their chemistry and diversity across populations. The results indicated statistically significant variation between all taxa examined, based on various secreted compounds. The underlying factors of variation highlighted by the multivariate analysis were differences in samandarine and other alkaloid content as well as in animal size. Metabolite annotation, based on dereplication tools and most importantly HRMS and HRMS/MS spectra, yielded a number of known samandarine alkaloids, reported for the first time in the currently studied Lyciasalamandra species. We also present documentation for novel members of the samandarine alkaloid family, as well as preliminary evidence for a possible dietary alkaloid sequestration. This work can set the basis for further research of this often-neglected endemic species of the Salamandridae, as well as the structural investigation of the samandarine alkaloid group.

An individual's likelihood of developing non-communicable diseases is often influenced by the types, intensities and duration of exposures at work. Job exposure matrices provide exposure estimates associated with different occupations. However, due to their time-consuming expert curation process, job exposure matrices currently cover only a subset of possible workplace exposures and may not be regularly updated. Scientific literature articles describing exposure studies provide important supporting evidence for developing and updating job exposure matrices, since they report on exposures in a variety of occupational scenarios. However, the constant growth of scientific literature is increasing the challenges of efficiently identifying relevant articles and important content within them. Natural language processing methods emulate the human process of reading and understanding texts, but in a fraction of the time. Such methods can increase the efficiency of both finding relevant documents and pinpointing specific information within them, which could streamline the process of developing and updating job exposure matrices. Named entity recognition is a fundamental natural language processing method for language understanding, which automatically identifies mentions of domain-specific concepts (named entities) in documents, e.g., exposures, occupations and job tasks. State-of-the-art machine learning models typically use evidence from an annotated corpus, i.e., a set of documents in which named entities are manually marked up (annotated) by experts, to learn how to detect named entities automatically in new documents. We have developed a novel annotated corpus of scientific articles to support machine learning based named entity recognition relevant to occupational substance exposures. Through incremental refinements to the annotation process, we demonstrate that expert annotators can attain high levels of agreement, and that the corpus can be used to train high-performance named entity recognition models. The corpus thus constitutes an important foundation for the wider development of natural language processing tools to support the study of occupational exposures.

[This corrects the article DOI: 10.1371/journal.pone.0015730.].

Walking is an important skill with positive impacts on health, function, and well-being. Many disorders impair walking and its positive impacts through a variety of complex and interrelated mechanisms. Any attempt to understand walking impairments, or the effects of interventions intended to treat these impairments, must respect this complexity. Therefore, our main objectives in conducting this study were to (1) propose a comprehensive model for quantifying the causes and consequences of walking impairments and (2) demonstrate the potential utility of the model for supporting clinical care and addressing basic scientific questions related to walking. To achieve these goals, we introduced a model, described by a directed acyclic graph, consisting of 10 nodes and 23 primary causal paths. We gave detailed descriptions of each node and path based on domain knowledge. We then demonstrated the model's utility using a large sample of gait data (N = 9504) acquired as part of routine care at a regional referral center. We analyzed five relevant examples that involved many of the model's nodes and paths. We computed causal effect magnitudes as Shapley values and displayed the overall importance of variables (mean absolute Shapley value), the variation of Shapley values with respect to underlying variables, and Shapley values for individual observations (case studies). We showed that the model was plausible, captured some well-known cause-effect relationships, provided new insights into others, and generated novel hypotheses requiring further testing through simulation or experiment. To aid in transparency, reproducibility, and future enhancements we have included an extensively commented Rmarkdown file and a deidentified data set.

Background There is a broad range of known effects of animal contact on human mental and physical health. Neurological correlates of human interaction with animals have been sparsely investigated. We investigated changes in frontal brain activity in the presence of and during contact with a dog. Methods Twenty-one healthy individuals each participated in six sessions. In three sessions, participants had contact with a dog, and in three control sessions they interacted with a plush animal. Each session had five two-minute phases with increasing intensity of contact to the dog or plush animal from the first to the fourth phase. We measured oxygenated, deoxygenated, and total hemoglobin and oxygen saturation of the blood in the frontal lobe/frontopolar area with functional near-infrared spectroscopy (SenSmart Model X-100) to assess brain activity. Findings In both conditions, the concentration of oxygenated hemoglobin increased significantly from the first to the fourth phase by 2.78 μmol/l (CI = 2.03–3.53, p < .001). Oxygenated hemoglobin concentration was 0.80 μmol/l higher in the dog condition compared to in the control condition (CI = 0.27–1.33, p = .004). Deoxygenated-hemoglobin concentration, total hemoglobin concentration, and oxygen saturation showed similar patterns. Conclusion Prefrontal brain activation in healthy subjects increased with the rise in interaction closeness with a dog or a plush animal. Moreover, interaction with a dog stimulated more brain activity compared to the control condition, suggesting that interactions with a dog can activate stronger attentional processes and elicit more emotional arousal than interacting with a nonliving stimulus.

BackgroundThe COVID-19 pandemic has already changed our globalised world and its long-term impact is not yet known. It is apparent that businesses and institutions are increasingly affected. COVID-19 discussions often focus on intensive care units in hospitals. However, COVID-19 also effects life-saving and -prolonging radiotherapy for patients suffering from cancer.MethodWe have conducted a structured online survey among medical physicists in Germany, Austria and Switzerland from March 23rd to 26th 2020. In total 154 responses (82 completed, 72 partially completed) were analysed in the context of the COVID-19 dissemination.Results72.4% of the respondent's state that their processes are affected due to COVID-19, while the top three answers are longer processing times (54.2%), patient no-shows (42.5%) and staff reduction (36.7%). 75.8% expect further unavailability of their personnel in the upcoming weeks. All participants have already taken several measures, especially providing information for patients at the entrance (89.6%) or over the phone (73.6%), restricting access for accompanying persons (77.4%) and providing disinfectant at the entrance (72.6%).DiscussionThe results presented in this article aim to support business continuity and risk management for radiotherapy centres to prepare for future challenges. The results show that most radiotherapy centres has implemented initial contingency measures, applying them pragmatically. The main problem however remains, that is the high risk of infection both for patients and medical personnel along with the associated risk of temporarily loss of personnel and ordered closure of business.

OBJECTIVE:To investigate if animal-assisted therapy (AAT) leads to higher consciousness in patients in a minimally conscious state during a therapy session, measured via behavioral reactions, heart rate and heart rate variability. METHODS:In a randomized two treatment multi-period crossover trial, 10 patients in a minimally conscious state participated in eight AAT sessions and eight paralleled conventional therapy sessions, leading to 78 AAT and 73 analyzed control sessions. Patients' responses during sessions were assessed via behavioral video coding and the Basler Vegetative State Assessment (BAVESTA), heart rate and heart rate variability (SDNN, RMSSD, HF and LF). Data were analyzed with generalized linear mixed models. RESULTS:Patients showed more eye movements (IRR = 1.31, 95% CI: 1.23 to 1.40, p < 0.001) and active movements per tactile input during AAT compared to control sessions (IRR = 1.13, 95% CI: 1.02 to 1.25, p = 0.018). No difference was found for positive emotions. With BAVESTA, patients' overall behavioral reactions were rated higher during AAT (b = 0.11, 95% CI: 0.01 to 0.22, p = 0.038). AAT led to significantly higher LF (b = 5.82, 95% CI: 0.55 to 11.08, p = 0.031) and lower HF (b = -5.80, 95% CI: -11.06 to -0.57, p = 0.030), while heart rate, SDNN, RMSSD did not differ. CONCLUSIONS:Patients in a minimally conscious state showed more behavioral reactions and increased physiological arousal during AAT compared to control sessions. This might indicate increased consciousness during therapeutic sessions in the presence of an animal. TRIAL REGISTRATION:ClinicalTrials.gov NCT02629302.

Needles are commonly used in the clinic for percutaneous procedures. The outcome of such procedures heavily depends on accurate placement of the needle. There are two main challenges to achieve high accuracy: First, aligning the needle with the targeted lesion, and second, compensating for the deflection of the needle in the tissue. In order to address these challenges, scientists have developed several robotic setups for needle steering. However, the subject is still under research and reliable implementations which can be used in clinical practice are not yet available. In this paper, we have taken some steps in order to bring needle steering closer to practice. A new hybrid control algorithm is developed, which enables us to control a flexible needle by combing base-manipulation and beveled-tip steering methods. A pre-operative path planner is developed which considers the clinical requirements. The proposed method is tested in the lung of a fresh-frozen human cadaver. The work-flow of the experiments are similar to the current clinical practice. Three experimental cases are used to evaluate the proposed steering algorithm. Experimental Case I shows that using the proposed steering algorithm controllability of the needle is increased. In Case II and Case III, the needle is steered in a gelatin phantom and a human cadaver, respectively. The targeting accuracy of 1.35±0.49mm in gelatin phantom and 1.97±0.89mm in cadave is achieved. A feasibility study is performed, in which a fine needle aspiration (FNA) needle is steered in the lungs of a human cadaver under computed tomography guidance. The targeting error for the feasibility study is 2.89±0.22mm. The results suggest that such a robotic system can be beneficial for clinical use and the patient receives less x-ray radiation.

Pathogenic protein accumulation and spread are fundamental principles of neurodegenerative diseases and ultimately account for the atrophy patterns that distinguish these diseases clinically. However, the biological mechanisms that link pathogenic proteins to specific neural network damage patterns have not been defined. We developed computational models for mechanisms of pathogenic protein accumulation, spread and toxic effects in an artificial neural network of cortical columns. By varying simulation parameters we assessed the effects of modelled mechanisms on network breakdown patterns. Our findings suggest that patterns of network breakdown and the convergence of patterns follow rules determined by particular protein parameters. These rules can account for empirical data on pathogenic protein spread in neural networks. This work provides a basis for understanding the effects of pathogenic proteins on neural circuits and predicting progression of neurodegeneration.

BACKGROUND:Consumption of meat prepared by barbecuing is associated with risk of cancer due to formation of carcinogenic compounds including benzo[a]pyrene (BaP). Assessment of a population's risk of disease and people's individual probability of disease given specific consumer attributes may direct food safety strategies to where impact on public health is largest. The aim of this study was to propose a model that estimates the risk of cancer caused by exposure to BaP from barbecued meat in Denmark, and to estimate the probability of developing cancer in subgroups of the population given different barbecuing frequencies. METHODS:We developed probabilistic models applying two dimensional Monte Carlo simulation to take into account the variation in exposure given age and sex and in the individuals' sensitivity to develop cancer after exposure to BaP, and the uncertainty in the dose response model. We used the Danish dietary consumption survey, monitoring data of chemical concentrations, data on consumer behavior of frequency of barbecuing, and animal dose response data. FINDINGS:We estimated an average extra lifetime risk of cancer due to BaP from barbecued meat of 6.8 × 10-5 (95% uncertainty interval 2.6 × 10-7 - 7.0 × 10-4) in the Danish population. This corresponds to approximately one to 4,074 extra cancer cases over a lifetime, reflecting wide uncertainty. The impact per barbecuing event on the risk of cancer for men and women of low body weight was higher compared to higher bodyweight. However, the difference due to sex and bodyweight between subgroups are dwarfed by the uncertainty. INTERPRETATION:This study proposes a model that can be applied to other substances and routes of exposure, and allows for deriving the change in risk following a specific change in behaviour. The presented methodology can serve as a valuable tool for risk management, allowing for the formulation of behaviour advice targeted to specific sub-groups in the population.

The incidence of hepatocellular carcinoma (HCC), the most common primary liver cancer, is increasing in the US and tripled during the past two decades. The reasons for such phenomenon remain poorly understood. Texas is among continental states with the highest incidence of liver cancer with an annual increment of 5.7%. Established risk factors for HCC include Hepatitis B and C (HBV, HCV) viral infection, alcohol, tobacco and suspected risk factors include obesity and diabetes. While distribution of these risk factors in the state of Texas is similar to the national data and homogeneous, the incidence of HCC in this state is exceptionally higher than the national average and appears to be dishomogeneous in various areas of the state suggesting that other non-recognized risk factors might play a role. No population-based studies are currently available investigating the effect of exposure to Hazardous Air Pollutants (HAPs) as a contributing risk factor for liver cancer. Incidence rate of liver cancer in Texas by counties for the time period between 2002 and 2012 was obtained from the Texas Cancer Registry (TCR). Through Principal Component Analysis (PCA) a subgroup of pollutants, explaining almost all the dataset variability, were identified and used to cluster Texas counties. The analysis generated 4 clusters showing liver cancer rate either higher or lower than national average in association with either high or low levels of HAPs emission in the environment. The study shows that the selected relevant HAPs, 10 among 253 analyzed, produce a significant correlation (P = 0.01-0.05) and some of these have been previously identified as carcinogens. An association between the increased production and consequent exposure to these HAPs and a higher presence of liver cancer in certain counties is suggested. This study provides a new insight on this complex multifactorial disease suggesting that environmental substances might play a role in the etiology of this cancer.

Although the organization of bone ultrastructure, i.e. the orientation and arrangement of the mineralized collagen fibrils, has been in the focus of research for many years for cortical bone, and many models on the osteonal arrangement have been proposed, limited attention has been paid to trabecular bone ultrastructure. This is surprising because trabeculae play a crucial role for the mechanical strength of several bone sites, including the vertebrae and the femoral head. On this account, we first validated a recently developed method (3D sSAXS or 3D scanning small-angle X-ray scattering) for investigating bone ultrastructure in a quantitative and spatially resolved way, using conventional linearly polarized light microscopy as a gold standard. While both methods are used to analyze thin tissue sections, in contrast to polarized light microscopy, 3D sSAXS has the important advantage that it provides 3D information on the orientation and arrangement of bone ultrastructure. In this first study of its kind, we used 3D sSAXS to investigate the ultrastructural organization of 22 vertebral trabeculae of different alignment, types and sizes, obtained from 4 subjects of different ages. Maps of ultrastructure orientation and arrangement of the trabeculae were retrieved by stacking information from consecutive 20-μm-thick bone sections. The organization of the ultrastructure was analyzed in relation to trabecular microarchitecture obtained from computed tomography and to relevant parameters such as distance to trabecular surface, local curvature or local bone mineralization. We found that (i) ultrastructure organization is similar for all investigated trabeculae independent of their particular characteristics, (ii) bone ultrastructure exhibiting a high degree of orientation was arranged in domains, (iii) highly oriented ultrastructural areas were located closer to the bone surface, (iv) the ultrastructure of the human trabecular bone specimens followed the microarchitecture, being oriented mostly parallel to bone surface, and (v) local surface curvature seems to have an effect on the ultrastructure organization. Further studies that investigate bone ultrastructure orientation and arrangement are needed in order to understand its organization and consequently its relation to bone biology and mechanics.

BACKGROUND:Antenatal depression affects up to 19% of pregnant women. Some of these women are also in need of antidepressant treatment. Nevertheless, the impact of maternal antidepressant treatment and prenatal depression on the course of pregnancy, foetal development and delivery outcomes is not fully understood. METHODS:We analysed data from 24 818 women who gave birth at Kuopio University Hospital between 2002-2012. Logistic regression analysis was used to estimate associations between the use of selective serotonin reuptake inhibitors (SSRIs) during pregnancy and the progression of pregnancy, development of the foetus and delivery outcomes. RESULTS:Altogether, 369 (1.5%) women used SSRIs. A regression model adjusted for age, overweight, nulliparity, prior termination, miscarriages, smoking, maternal alcohol consumption, chronic illness and polyhydramnion showed that pregnant women exposed to SSRI medication had significantly lower Apgar scores at 1 minute (p < 0.0001) and 5 minutes (p < 0.0001) and more admissions to the neonatal intensive care unit (p < 0.0001) than unexposed pregnant women. In addition, exposed newborns had longer umbilical cords (p < 0.0001) than non-exposed newborns. CONCLUSION:In addition to the previously known associates with maternal SSRI exposure, such as lowered Apgar scores, SSRI exposure appeared to be associated with increased umbilical cord length. The observation related to increased umbilical cord length may be explained by an SSRI-induced increase in the movements of the developing foetus.

We present MultiElec, an open source MATLAB based application for data analysis of microelectrode array (MEA) recordings. MultiElec displays an extremely user-friendly graphic user interface (GUI) that allows the simultaneous display and analysis of voltage traces for 60 electrodes and includes functions for activation-time determination, the production of activation-time heat maps with activation time and isoline display. Furthermore, local conduction velocities are semi-automatically calculated along with their corresponding vector plots. MultiElec allows ad hoc signal suppression, enabling the user to easily and efficiently handle signal artefacts and for incomplete data sets to be analysed. Voltage traces and heat maps can be simply exported for figure production and presentation. In addition, our platform is able to produce 3D videos of signal progression over all 60 electrodes. Functions are controlled entirely by a single GUI with no need for command line input or any understanding of MATLAB code. MultiElec is open source under the terms of the GNU General Public License as published by the Free Software Foundation, version 3. Both the program and source code are available to download from http://www.cancer.manchester.ac.uk/MultiElec/.

It has been proposed that disgust evolved to protect humans from contamination. Through eliciting the overwhelming urge to withdraw from the disgusting stimuli, it would facilitate avoidance of contact with pathogens. The physical proximity implied in sexual intercourse provides ample opportunity for contamination and may thus set the stage for eliciting pathogen disgust. Building on this, it has been argued that the involuntary muscle contraction characteristic of vaginismus (i.e., inability to have vaginal penetration) may be elicited by the prospect of penetration by potential contaminants. To further investigate this disgust-based interpretation of vaginismus (in DSM-5 classified as a Genito-Pelvic Pain/Penetration Disorder, GPPPD) we used functional magnetic resonance imaging (fMRI) to examine if women with vaginismus (n = 21) show relatively strong convergence in their brain responses towards sexual penetration- and disgust-related pictures compared to sexually asymptomatic women (n = 21) and women suffering from vulvar pain (dyspareunia/also classified as GPPPD in the DSM-5, n = 21). At the subjective level, both clinical groups rated penetration stimuli as more disgusting than asymptomatic women. However, the brain responses to penetration stimuli did not differ between groups. In addition, there was considerable conjoint brain activity in response to penetration and disgust pictures, which yield for both animal-reminder (e.g., mutilation) and core (e.g., rotten food) disgust domains. However, this overlap in brain activation was similar for all groups. A possible explanation for the lack of vaginismus-specific brain responses lies in the alleged female ambiguity (procreation/pleasure vs. contamination/disgust) toward penetration: generally in women a (default) disgust response tendency may prevail in the absence of sexual readiness. Accordingly, a critical next step would be to examine the processing of penetration stimuli following the induction of sexual arousal.

Recent studies using electroencephalography (EEG) suggest that alteration of coherent activity between the anterior and posterior brain regions might be used as a neurophysiologic correlate of anesthetic-induced unconsciousness. One way to assess causal relationships between brain regions is given by renormalized partial directed coherence (rPDC). Importantly, directional connectivity is evaluated in the frequency domain by taking into account the whole multichannel EEG, as opposed to time domain or two channel approaches. rPDC was applied here in order to investigate propofol induced changes in causal connectivity between four states of consciousness: awake (AWA), deep sedation (SED), loss (LOC) and return of consciousness (ROC) by gathering full 10/20 system human EEG data in ten healthy male subjects. The target-controlled drug infusion was started at low rate with subsequent gradual stepwise increases at 10 min intervals in order to carefully approach LOC (defined as loss of motor responsiveness to a verbal stimulus). The direction of the causal EEG-network connections clearly changed from AWA to SED and LOC. Propofol induced a decrease (p = 0.002-0.004) in occipital-to-frontal rPDC of 8-16 Hz EEG activity and an increase (p = 0.001-0.040) in frontal-to-occipital rPDC of 10-20 Hz activity on both sides of the brain during SED and LOC. In addition, frontal-to-parietal rPDC within 1-12 Hz increased in the left hemisphere at LOC compared to AWA (p = 0.003). However, no significant changes were detected between the SED and the LOC states. The observed decrease in back-to-front EEG connectivity appears compatible with impaired information flow from the posterior sensory and association cortices to the executive prefrontal areas, possibly related to decreased ability to perceive the surrounding world during sedation. The observed increase in the opposite (front-to-back) connectivity suggests a propofol concentration dependent association and is not directly related to the level of consciousness per se.

Epilepsy is one of the most common neurologic disorders of childhood, affecting about 0.4-0.8% of all children up to the age of 20.A population-based retrospective cohort study. Aim was to determine incidence and identify perinatal and reproductive risk factors of epilepsy in children born between 1989 and 2008 among women (n = 43,389) delivered in Kuopio University Hospital. Risk factors of childhood epilepsy were determined by using logistic regression analysis.The incidence of childhood epilepsy was 0.7% (n = 302 of 43,389). Maternal epilepsy, major congenital anomalies and use of assisted reproductive technology (ART) were associated with 4.25-, 3.61-, and 1.67- fold increased incidence of childhood epilepsy. A 10 cm increase in umbilical cord length was associated with a 15% decrease in the incidence of epilepsy (adjusted OR 0.85, 95% CI 0.78-0.94). However, the above reproductive factors accounted for less than 2% of total incidence, whereas maternal epilepsy proved to be the highest risk factor.Perinatal and reproductive factors were shown to be minor risk factors of childhood epilepsy, implying that little can be done in obstetric care to prevent childhood epilepsy. Infertility treatment and umbilical cord length, independent of gestational age and congenital malformations, may be novel markers of childhood epilepsy.

Dehydration can affect the volume of brain structures, which might imply a confound in volumetric and morphometric studies of normal or diseased brain. Six young, healthy volunteers were repeatedly investigated using three-dimensional T(1)-weighted magnetic resonance imaging during states of normal hydration, hyperhydration, and dehydration to assess volume changes in gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF). The datasets were analyzed using voxel-based morphometry (VBM), a widely used voxel-wise statistical analysis tool, FreeSurfer, a fully automated volumetric segmentation measure, and SIENAr a longitudinal brain-change detection algorithm. A significant decrease of GM and WM volume associated with dehydration was found in various brain regions, most prominently, in temporal and sub-gyral parietal areas, in the left inferior orbito-frontal region, and in the extra-nuclear region. Moreover, we found consistent increases in CSF, that is, an expansion of the ventricular system affecting both lateral ventricles, the third, and the fourth ventricle. Similar degrees of shrinkage in WM volume and increase of the ventricular system have been reported in studies of mild cognitive impairment or Alzheimer's disease during disease progression. Based on these findings, a potential confound in GM and WM or ventricular volume studies due to the subjects' hydration state cannot be excluded and should be appropriately addressed in morphometric studies of the brain.

Conservation strategies for African elephants would be advanced by resolution of conflicting claims that they comprise one, two, three or four taxonomic groups, and by development of genetic markers that establish more incisively the provenance of confiscated ivory. We addressed these related issues by genotyping 555 elephants from across Africa with microsatellite markers, developing a method to identify those loci most effective at geographic assignment of elephants (or their ivory), and conducting novel analyses of continent-wide datasets of mitochondrial DNA. Results showed that nuclear genetic diversity was partitioned into two clusters, corresponding to African forest elephants (99.5% Cluster-1) and African savanna elephants (99.4% Cluster-2). Hybrid individuals were rare. In a comparison of basal forest "F" and savanna "S" mtDNA clade distributions to nuclear DNA partitions, forest elephant nuclear genotypes occurred only in populations in which S clade mtDNA was absent, suggesting that nuclear partitioning corresponds to the presence or absence of S clade mtDNA. We reanalyzed African elephant mtDNA sequences from 81 locales spanning the continent and discovered that S clade mtDNA was completely absent among elephants at all 30 sampled tropical forest locales. The distribution of savanna nuclear DNA and S clade mtDNA corresponded closely to range boundaries traditionally ascribed to the savanna elephant species based on habitat and morphology. Further, a reanalysis of nuclear genetic assignment results suggested that West African elephants do not comprise a distinct third species. Finally, we show that some DNA markers will be more useful than others for determining the geographic origins of illegal ivory. These findings resolve the apparent incongruence between mtDNA and nuclear genetic patterns that has confounded the taxonomy of African elephants, affirm the limitations of using mtDNA patterns to infer elephant systematics or population structure, and strongly support the existence of two elephant species in Africa.

Cell-cell adhesion regulates the development and function of epithelia by providing mechanical support and by guiding cell proliferation and differentiation. The tight junction (TJ) protein zonula occludens (ZO)-1 regulates cell proliferation and gene expression by inhibiting the activity of the Y-box transcription factor ZONAB in cultured epithelial cells. We investigated the role of this TJ-associated signalling pathway in the retinal pigment epithelium (RPE) in vivo by lentivirally-mediated overexpression of ZONAB, and knockdown of its cellular inhibitor ZO-1. Both overexpression of ZONAB or knockdown of ZO-1 resulted in increased RPE proliferation, and induced ultrastructural changes of an epithelial-mesenchymal transition (EMT)-like phenotype. Electron microscopy analysis revealed that transduced RPE monolayers were disorganised with increased pyknosis and monolayer breaks, correlating with increased expression of several EMT markers. Moreover, fluorescein angiography analysis demonstrated that the increased proliferation and EMT-like phenotype induced by overexpression of ZONAB or downregulation of ZO-1 resulted in RPE dysfunction. These findings demonstrate that ZO-1 and ZONAB are critical for differentiation and homeostasis of the RPE monolayer and may be involved in RPE disorders such as proliferative vitroretinopathy and atrophic age-related macular degeneration.

An individual's likelihood of developing non-communicable diseases is often influenced by the types, intensities and duration of exposures at work. Job exposure matrices provide exposure estimates associated with different occupations. However, due to their time-consuming expert curation process, job exposure matrices currently cover only a subset of possible workplace exposures and may not be regularly updated. Scientific literature articles describing exposure studies provide important supporting evidence for developing and updating job exposure matrices, since they report on exposures in a variety of occupational scenarios. However, the constant growth of scientific literature is increasing the challenges of efficiently identifying relevant articles and important content within them. Natural language processing methods emulate the human process of reading and understanding texts, but in a fraction of the time. Such methods can increase the efficiency of both finding relevant documents and pinpointing specific information within them, which could streamline the process of developing and updating job exposure matrices. Named entity recognition is a fundamental natural language processing method for language understanding, which automatically identifies mentions of domain-specific concepts (named entities) in documents, e.g., exposures, occupations and job tasks. State-of-the-art machine learning models typically use evidence from an annotated corpus, i.e., a set of documents in which named entities are manually marked up (annotated) by experts, to learn how to detect named entities automatically in new documents. We have developed a novel annotated corpus of scientific articles to support machine learning based named entity recognition relevant to occupational substance exposures. Through incremental refinements to the annotation process, we demonstrate that expert annotators can attain high levels of agreement, and that the corpus can be used to train high-performance named entity recognition models. The corpus thus constitutes an important foundation for the wider development of natural language processing tools to support the study of occupational exposures., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Thompson et al. 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.)