bluuebunny/crossref_metadata_2025 huggingface dataset:
In Vivo Modifications of Small GTPase Rac and Cdc42 by
Bordetella
Dermonecrotic Toxin
Authors: Masuda Minako , Minami Masayoshi , Shime Hiroaki , Matsuzawa Takeshi , Horiguchi Yasuhiko
Published: March 2020

Bordetella
dermonecrotic toxin (DNT) is known to activate the small GTPase Rho through deamidation or polyamination. In this study, we examined whether Rac and Cdc42, the two other members of the Rho family, serve as intracellular targets for the toxin. Immunoprecipitation and immunoblot assays revealed that DNT deamidated or polyaminated intracellular Rac and Cdc42. After the modifications, both Rac and Cdc42 lost their GTP-hydrolyzing, but not GTP-binding, activities. The interactions of the modified Rac and Cdc42 with their respective effectors were strictly dependent on GTP. MC3T3-E1 cells treated with DNT at high concentrations demonstrated extensive formations of lamellipodia and filopodia, which indicate the intracellular activation of Rac and Cdc42, respectively.
MEMPHIS: a smartphone app using psychological approaches for women with chronic pelvic pain presenting to gynaecology clinics: a randomised feasibility trial
Authors: Forbes Gordon , Newton Sian , Cantalapiedra Calvete Clara , Birch Judy , Dodds Julie , Steed Liz , Rivas Carol , Khan Khalid , Röhricht Frank , Taylor Stephanie , Kahan Brennan C , Ball Elizabeth
Published: March 2020

Objectives

To evaluate the feasibility of a randomised trial of a modified, pre-existing, mindfulness meditation smartphone app for women with chronic pelvic pain.

Design

Three arm randomised feasibility trial.

Setting

Women were recruited at two gynaecology clinics in the UK. Interventions were delivered via smartphone or computer at a location of participants choosing.

Participants

Women were eligible for the study if they were over 18, had been experiencing organic or non-organic chronic pelvic pain for 6 months or more, and had access to a computer or smartphone. 90 women were randomised.

Interventions

Daily mindfulness meditation delivered by smartphone app, an active control app which delivered muscle relaxation techniques, and usual care without app. Interventions were delivered over 60 days.

Primary and secondary outcome measures

Outcomes included length of recruitment, follow-up rates, adherence to the app interventions, and clinical outcomes measured at baseline, two, three and 6 months.

Results

The target sample size was recruited in 145 days. Adherence to the app interventions was extremely low (mean app use 1.8 days mindfulness meditation group, 7.0 days active control). Fifty-seven (63%) women completed 6-month follow-up, and 75 (83%) women completed at least one postrandomisation follow-up. The 95% CIs for clinical outcomes were consistent with no benefit from the mindfulness meditation app; for example, mean differences in pain acceptance scores at 60 days (higher scores are better) were −2.3 (mindfulness meditation vs usual care, 95% CI: −6.6 to 2.0) and −4.0 (mindfulness meditation vs active control, 95% CI: −8.1 to 0.1).

Conclusions

Despite high recruitment and adequate follow-up rates, demonstrating feasibility, the extremely low adherence suggests a definitive randomised trial of the mindfulness meditation app used in this study is not warranted. Future research should focus on improving patient engagement.

Trial registration numbers

NCT02721108;ISRCTN10925965; Results.
Cross-sectional study of internalised stigma and medication adherence in patients with obsessive compulsive disorder
Authors: Ansari Eram , Mishra Sudha , Tripathi Adarsh , Kar Sujita Kumar , Dalal Pronob Kumar
Published: March 2020

Background

Patients suffering from psychiatric disorders tend to stigmatise themselves which had been linked to poor adherence to treatment.

Aims

The aim of the present study was to study internalised stigma and medication adherence and to assess the relationship between them in patients with obsessive compulsive disorder (OCD).

Methods

A cross-sectional study was conducted on 112 patients diagnosed with OCD who were attending the Out-patient's department at Department of Psychiatry of a tertiary care hospital in North India. Internalised stigma and current medication adherence were assessed with Internalized Stigma of Mental Illness Scale (ISMI) and Medication Adherence Rating Scale, respectively. Yale-Brown Obsessive Compulsive Scale was used to assess the current severity of OCD symptoms. Sociodemographic and clinical details were also obtained from the patients by using a semistructured sociodemographic proforma.

Results

Most of the patients reported moderate level of internalised stigma with a mean ISMI score of 77.98 (10.82). Most of the patients were compliant while 41.96% reported poor medication adherence. Internalised stigma was negatively correlated with the current medication adherence. Current severity of OCD symptoms also showed a significant positive correlation with internalised stigma and a significant negative correlation with medication adherence.

Conclusion

High levels of internalised stigma were associated with lower adherence to treatment which suggests that internalised stigma may be a very important factor influencing medication adherence in patients with OCD.
Faecal virome transplantation decreases symptoms of type 2 diabetes and obesity in a murine model
Authors: Rasmussen Torben Sølbeck , Mentzel Caroline Märta Junker , Kot Witold , Castro-Mejía Josué Leonardo , Zuffa Simone , Swann Jonathan Richard , Hansen Lars Hestbjerg , Vogensen Finn Kvist , Hansen Axel Kornerup , Nielsen Dennis Sandris
Published: March 2020

Objective

Development of obesity and type 2 diabetes (T2D) are associated with gut microbiota (GM) changes. The gut viral community is predominated by bacteriophages (phages), which are viruses that attack bacteria in a host-specific manner. The antagonistic behaviour of phages has the potential to alter the GM. As a proof-of-concept, we demonstrate the efficacy of faecal virome transplantation (FVT) from lean donors for shifting the phenotype of obese mice into closer resemblance of lean mice.

Design

The FVT consisted of viromes with distinct profiles extracted from the caecal content of mice from different vendors that were fed a low-fat (LF) diet for 14 weeks. Male C57BL/6NTac mice were divided into five groups: LF (as diet control), high-fat (HF) diet, HF+ampicillin (Amp), HF+Amp+FVT and HF+FVT. At weeks 6 and 7 of the study, the HF+FVT and HF+Amp+FVT mice were treated with FVT by oral gavage. The Amp groups were treated with Amp 24 hours prior to first FVT treatment.

Results

Six weeks after first FVT, the HF+FVT mice showed a significant decrease in weight gain compared with the HF group. Further, glucose tolerance was comparable between the LF and HF+FVT mice, while the other HF groups all had impaired glucose tolerance. These observations were supported by significant shifts in GM composition, blood plasma metabolome and expression levels of genes associated with obesity and T2D development.

Conclusions

Transfer of caecal viral communities from mice with a lean phenotype into mice with an obese phenotype led to reduced weight gain and normalised blood glucose parameters relative to lean mice. We hypothesise that this effect is mediated via FVT-induced GM changes.
Association of social relationships with incident cardiovascular events and all-cause mortality
Authors: Gronewold Janine , Kropp Rene , Lehmann Nils , Schmidt Börge , Weyers Simone , Siegrist Johanne , Dragano Nico , Jöckel Karl-Heinz , Erbel Raimund , Hermann Dirk M
Published: March 2020

Objective

To examine how different aspects of social relationships are associated with incident cardiovascular events and all-cause mortality.

Methods

In 4139 participants from the population-based Heinz Nixdorf Recall study without previous cardiovascular disease (mean (SD) age 59.1 (7.7) years, 46.7% men), the association of self-reported instrumental, emotional and financial support and social integration at baseline with incident fatal and non-fatal cardiovascular events and all-cause mortality during 13.4-year follow-up was assessed in five different multivariable Cox proportional hazards regression models: minimally adjusted model (adjusting for age, sex, social integration or social support, respectively); biological model (minimally adjusted+systolic blood pressure, low-density and high-density lipoprotein cholesterol, glycated haemoglobin, body mass index, antihypertensive medication, lipid-lowering medication and antidiabetic medication); health behaviour model (minimally adjusted+alcohol consumption, smoking and physical activity); socioeconomic model (minimally adjusted+income, education and employment); and depression model (minimally adjusted+depression, antidepressants and anxiolytics).

Results

339 cardiovascular events and 530 deaths occurred during follow-up. Lack of financial support was associated with an increased cardiovascular event risk (minimally adjusted HR=1.30(95% CI 1.01 to 1.67)). Lack of social integration (social isolation) was associated with increased mortality (minimally adjusted HR=1.47 (95% CI 1.09 to 1.97)). Effect estimates did not decrease to a relevant extent in any regression model.

Conclusions

Perceiving a lack of financial support is associated with a higher cardiovascular event incidence, and being socially isolated is associated with increased all-cause mortality. Future studies should investigate how persons with deficient social relationships could benefit from targeted interventions.
Predictors of outcome in 1-month survivors of large middle cerebral artery infarcts treated by decompressive hemicraniectomy
Authors: Casolla Barbara , Kyheng Maeva , Kuchcinski Gregory , Lejeune Jean-Paul , Hanafi Riyad , Bodenant Marie , Leys Didier , Labreuche Julien , Allart Etienne , Jourdain Merce , Cordonnier Charlotte , Henon Hilde
Published: March 2020

Background

Decompressive hemicraniectomy (DH) increases survival without severe dependency in patients with large middle cerebral artery (LMCA) infarcts. The objective was to identify predictors of 1-year outcome after DH for LMCA infarct.

Methods

We conducted this study in consecutive patients who underwent DH for LMCA infarcts, in a tertiary stroke centre. Using multivariable logistic regression analyses, we evaluated predictors of (1) 30-day mortality and (2) poor outcome after 1 year (defined as a modified Rankin Scale score of 4–6) in 30-day survivors.

Results

Of 212 patients (133 men, 63%; median age 51 years), 35 (16.5%) died within 30 days. Independent predictors of mortality were infarct volume before DH (OR 1.10 per 10 mL increase, 95% CI 1.04 to 1.16), delay between symptom onset and DH (OR 0.41, 95% CI 0.23 to 0.73 per 12 hours increase) and midline shift after DH (OR 2.59, 95% CI 1.09 to 6.14). The optimal infarct volume cut-off to predict death was 210 mL or more. Among the 177 survivors, 77 (43.5%) had a poor outcome at 1 year. Independent predictors of poor outcome were age (OR 1.08 per 1 year increase, 95% CI 1.03 to 1.12) and weekly alcohol consumption of 300 g or more (OR 5.30, 95% CI 2.20 to 12.76), but not infarct volume.

Conclusion

In patients with LMCA infarcts treated by DH, stroke characteristics (infarct volume before DH, midline shift after DH and early DH) predict 30-day mortality, while patients’ characteristics (age and excessive alcohol intake) predict 1-year outcome survivors.
Iron deficiency in 78 805 people admitted with heart failure across England: a retrospective cohort study
Authors: Beattie James M , Khatib Rani , Phillips Ceri J , Williams Simon G
Published: March 2020

Objectives

Iron deficiency (ID), with or without anaemia (IDA), is an important comorbidity in people with chronic heart failure (HF), but the prevalence and significance in those admitted with HF is uncertain. We assessed the prevalence of ID or IDA in adults (age ≥21 years) hospitalised with a primary diagnosis of HF, and examined key metrics associated with these secondary diagnoses.

Methods

A retrospective cohort study of Hospital Episode Statistics describing all adults admitted to National Health Service (NHS) hospitals across England from April 2015 through March 2016 with primary diagnostic discharge coding as HF, with or without subsidiary coding for ID/IDA.

Results

78 805 adults were admitted to 177 NHS hospitals with primary coding as HF: 26 530 (33.7%) with secondary coding for ID/IDA, and 52 275 (66.3%) without. Proportionately more patients coded ID/IDA were admitted as emergencies (94.8% vs 87.6%; p<0.0001). Tending to be older and female, they required a longer length of stay (15.8 vs 12.2 days; p<0.0001), with higherper capitacosts (£3623 vs £2918; p<0.0001), the cumulative excess expenditure being £21.5 million. HF-related (8.2% vs 5.2%; p<0.0001) and all-cause readmission rates (25.8% vs 17.7%; p<0.05) at ≤30 days were greater in those with ID/IDA against those without, and they manifested a small but statistically significant increased inpatient mortality (13.5% v 12.9%; p=0.009).

Conclusions

For adults admitted to hospitals in England, principally with acute HF, ID/IDA are significant comorbidities and associated with adverse outcomes, both for affected individuals, and the health economy.
Stroke and osteoporosis: a Taiwan cohort study
Authors: Zhang Li , Zhang Zi-Hao , Wang Qing-Rui , Su Ying-Ju , Lu Ying-Yi , Zhang Cong-Liang , Tsai Hung-Pei , Wu Chieh-Hsin
Published: March 2020

Background

Osteoporosis and stroke are major health problems that have potentially overlapping pathophysiological mechanisms. The aim of this study was to estimate osteoporosis risk in Taiwan patientswho had a stroke.

Method

This study retrieved data contained in the Taiwan National Health Insurance Research Database for a population-based sample of consecutive patients either hospitalised for stroke or treated for stroke on an outpatient basis. A total of 7550 newly diagnosed patientswho had a stroke were enrolled during 1996–2010. Osteoporosis risk in these patients was then compared with a matched group of patients who had not had a stroke randomly selected from the database at a ratio of 1:4 (n=30 200). The relationship between stroke history and osteoporosis risk was estimated with Cox proportional hazard regression models.

Results

During the follow-up period, osteoporosis developed in 1537 patients who had a stroke and in 5830 patients who had not had a stroke. The incidence of osteoporosis for cohorts with and without stroke was 32.97 and 14.28 per 1000 person-years, respectively. After controlling for covariates, the overall risk of osteoporosis was 1.82-fold higher in the stroke group than in the non-stroke group. The relative osteoporosis risk contributed by stroke had apparently greater impact among male gender and younger age groups.

Conclusion

History of stroke is a risk factor for osteoporosis in Taiwan. Much attention to stroke-targeted treatment modalities might minimise adverse outcomes of osteoporosis.
Novel pleural-bladder pump in malignant pleural effusions: from animal model to man
Authors: Astoul Philippe , Laroumagne Sophie , Capel Jeroen , Maskell Nicholas A
Published: March 2020

Malignant pleural effusion is common and causes disabling symptoms such as breathlessness. Treatments are palliative and centred around improving symptoms and quality of life but an optimal management strategy is yet to be universally agreed. A novel pump system, allowing fluid to be moved from the pleural space to the urinary bladder, may have a role for the management of recurrent malignant pleural effusion. We hereby describe the first animal study using this device and the results of the first application in patients.
Lines of communication with clients
Authors: Magrath Christine
Published: March 2020

Successfully communicating with clients is central to good veterinary care. But it can be difficult to get right – and when communication challenges crop up they can have a direct impact on your levels of stress and wellbeing. Here, Christine Magrath talks through some common scenarios and how to manage them effectively.
Water mould exposure induces enzymatic antioxidant defences in embryos of the Two-colored Oval Frog (Elachistocleis bicolor) (Anura: Microhylidae)
Authors: Ghirardi R. , Cazenave J. , López J.A. , Antoniazzi C.E. , Perotti M.G.
Published: March 2020

Water moulds are pathogens of amphibian eggs and embryos. However, little is known about oxidant or antioxidant status of amphibians in response to stress caused by water moulds. We exposed embryo stages of Two-colored Oval Frogs (Elachistocleis bicolor (Guérin-Méneville, 1838)) to a Saprolegnia-like species of water mould to explore homeostatic adjustments by the shifting of oxidative stress markers. We also tested whether water mould infection affected survivorship, hatching time, and morphology of hatching embryos. We found that the Saprolegnia-like species is a genuine stressor and substantially altered the physiological state of E. bicolor embryos. Among antioxidant defences, superoxide dismutase (SOD) and glutathione S-transferase (GST) activities increased in embryos exposed to the Saprolegnia-like species. However, no difference in lipid peroxidation levels was found between treatments, which might indicate that SOD and GST activations could be enough to prevent oxidative damage. Finally, we found higher mortality and number of malformations in the water mould treatment. We showed the stressful effect of water moulds on amphibian embryos, evidenced by the activation of their antioxidant system, and reveal the importance of considering physiological stress markers as key information when studying the potential consequences of disease outbreaks in the ecology and conservation of amphibians.
New point-like sources and a conducting surface in Maxwell–Chern–Simons electrodynamics
Authors: Borges L. H. C. , Barone F. E. , Ribeiro C. C. H. , Oliveira H. L. , Fernandez R. L. , Barone F. A.
Published: March 2020

We investigate some aspects of the Maxwell–Chern–Simons electrodynamics focusing on physical effects produced by the presence of stationary sources and a perfectly conducting plate (mirror). Specifically, in addition to point charges, we propose two new types of point-like sources called topological source and Dirac point, and we also consider physical effects in various configurations that involve them. We show that the Dirac point is the source of the vortex field configurations. The propagator of the gauge field due to the presence of a conducting plate and the interaction forces between the plate and point-like sources are computed. It is shown that the image method is valid for the point-like charges as well as for Dirac points. For the topological source we show that the image method is not valid and the symmetry of spatial refection on the mirror is broken. In all setups considered, it is shown that the topological source leads to the emergence of torques.
Greybody factors of holographic superconductors with $$z=2$$ Lifshitz scaling
Authors: Gürsel Huriye , Sakallı İzzet
Published: March 2020

We study the quasinormal modes and thermal radiation of massless spin-0 field perturbations in the background of four-dimensional (4D) non-Abelian charged Lifshitz black branes with$$z=2$$z=2hyperscaling violation, which correspond to systems with superconducting fluctuations. After having an analytical solution to the Klein–Gordon equation, we obtain exact quasinormal modes that are purely imaginary. Therefore, there is no oscillatory behavior in the perturbations that guarantees the mode stability of these solutions. We also study the greybody factors, absorption cross-section, and decay rate of the non-Abelian charged Lifshitz black branes. We derive their analytical expressions and then investigate the correspondence in the strongly coupled dual theory. This study might shed light on the mechanism governing the high-temperature superconductors in condensed matter physics.
Effect of magnetic field on holographic insulator/superconductor phase transition in higher dimensional Gauss–Bonnet gravity
Authors: Parai Diganta , Ghorai Debabrata , Gangopadhyay Sunandan
Published: March 2020

In this paper, we have investigated the effect of magnetic field numerically as well as analytically for holographic insulator/superconductor phase transition in higher dimensional Gauss–Bonnet gravity. First we have analysed the critical phenomena with magnetic field using two different numerical methods, namely, quasinormal modes method and the shooting method. Then we have carried out our calculation analytically using the Sturm–Liouville eigenvalue method. The methods show that marginally stable modes emerge at critical values of the chemical potential and the magnetic field satisfying the relation $$\Lambda ^2\equiv \mu ^2-B$$Λ2≡μ2-B. We observe that the value of the chemical potential and hence the value of $$\Lambda $$Λ increases with higher values of the Gauss–Bonnet parameter and dimension of spacetime for a fixed mass of the scalar field. This clearly indicates that the phase transition from insulator to superconductor becomes difficult in the presence of the magnetic field for higher values of the Gauss–Bonnet parameter and dimension of spacetime. Our analytic results are in very good agreement with our numerical results.
Archidendron lucidum Exerts Anti-Inflammatory Effects by Targeting PDK1 in the NF-κB Pathway
Authors: Jo Minkyeong , Yi Young-Su , Cho Jae Youl
Published: March 2020

Pharmacological activities of some Leguminosae family members were reported. Pharmacological activities of Archidendron lucidum, a Leguminosae family member have never been explored. Therefore, this study investigated anti-inflammatory effects of an Archidendron lucidum methanol extract (Al-ME). In this study, anti-inflammatory effects of Al-ME were investigated in LPS-stimulated RAW264.7 cells and HCl/EtOH-induced gastritis mice by MTT assay, nitric oxide (NO) production assay, semi-quantitative reverse transcriptase-polymerase chain reaction (RT-PCR), luciferase reporter assay, and Western blotting. High-performance liquid chromatography (HPLC) analysis identified ethnopharmacological compounds in Al-ME. Al-ME inhibited NO production without cytotoxicity in peritoneal macrophages and RAW264.7 cells stimulated with LPS or Pam3CSK4. Al-ME downregulated mRNA expression of inflammatory genes (inducible NO synthase (iNOS) and cyclooxygenase-2 (COX-2)) and pro-inflammatory cytokines (tumor necrosis factor-[Formula: see text] (TNF-[Formula: see text]), interleukin-1[Formula: see text] (IL-1[Formula: see text]), and IL-6). Al-ME exerted anti-inflammatory activity in LPS-stimulated RAW264.7 cells by inhibiting nuclear factor-kappa B (NF-[Formula: see text]B) signaling pathway. HPLC analysis identified quercetin, luteolin, and kaempferol as major anti-inflammatory components in Al-ME. Al-ME ameliorated HCl/EtOH-induced gastritis symptoms in mice by suppressing iNOS and IL-6 mRNA expressions and I[Formula: see text]B[Formula: see text] phosphorylation. Therefore, these results suggest that Al-ME exhibited anti-inflammatory activity by targeting NF-[Formula: see text]B signaling pathway, implying that Al-ME could be potent anti-inflammatory medications to prevent and treat inflammatory diseases.
Forecasting the Growth of Structures from NMR and X-Ray Crystallography Experiments Released Per Year
Authors: Al Nasr Kamal , Al-Haija Qasem Abu
Published: March 2020

In this paper, we present a forecasting scheme for the growth of molecular structures from NMR and X-ray Crystallography experimental techniques released every year by employing an autoregressive (AR) process. The proposed scheme maximises the forecasting accuracy by utilising the optimal AR process order. The optimal model order was derived as the model with the least prediction error. Therefore, the proposed scheme has been efficiently employed to model and predict the annual growth of structures-based NMR and X-ray Crystallography experimental data for the next decade 2019–2028 using the time series of the past 43 years of both experimental datasets. The experimental results showed that the optimal model order to estimate both datasets was [Formula: see text] which belongs to a forecasting accuracy of [Formula: see text], for both datasets. Indeed, such a high level of accuracy referred to the amount of linearity between the consecutive elements of the original times series. Hence, the forecasting results reveals of an exponential increasing behaviour in the future growth in the annual structures released from both NMR and X-ray Crystallography experiments.
Integration of Data Envelopment Analysis and Clustering Methods
Authors: Najadat Hassan , Alaiad Ahmad , Alasal Sanaa Abu , Mrayyan Ghadeer Anwar , Alsmadi Izzat
Published: March 2020

Data Envelopment Analysis (DEA) has been applied creatively in various study domains to compare and evaluate different Decision Making Units (DMUs) based on multiple input–output attributes. In this paper, the performance of Jordanian public hospitals is assessed via a methodology combining DEA with data mining methods, specifically, clustering. Initially, inputs of inefficient hospitals were altered to check for waste in the allocated resources. Then, the number of inputs–outputs was manipulated to test if the number is strongly influencing the productivity of the DMUs. The number of DMUs used was 27 public hospitals and the applicable efficiency measurements used were constant return to scale (CRS) and variable return to scale (VRS) through the DEAP software. Experiments showed that the efficiency of a hospital might be more meaningfully assessed if it is compared with a group of hospitals that are similar in some factors. More specifically, results of applying the CRS model proved that 77% of the hospitals were efficient. Additionally, we found that the inefficiencies of some hospitals are linked to weak resource utilization. It is concluded that number of inputs–outputs inserted in the efficiency evaluation process impacts the resulted values.
A New Automated Forms Generation Algorithm for Online Assessment
Authors: Albazar Hussein
Published: March 2020

Modern learning techniques require technologies to be embedded within the process. The assessment strategy of testing students has been developed through the past few decades and have presented online computer-based examination systems as a replacement for the conventional paper-based testing. However, a major challenge that is still faced by those examination systems is that there is no any guarantee that students sitting adjacently will have different questions or forms, and the questions of exams’ form are not duplicated for any adjacent students within a lab. In fact, this can influence the reliability pertaining to the online examination systems. Consequently, a new algorithm is proposed in this paper for an online examination system that is capable of effectively generating several exam forms with minimal similarity for the constitutional questions, and that guarantees that two adjacent student’s terminals will not have the same forms. Further, the paper provides an explanation for the proposed algorithm and provides a real-life case for the implementation pertaining to the produced algorithm in a conducted experiment. It is found to be proven from the obtained results that the implementation, which is related to the produced form generation algorithm within this research reveals an evidence that is in line with the research assumptions in which an online system’s assessment reliability can be improved based on eliminating adjacent locations of a form similarity.
Data Imbalance in Autism Pre-Diagnosis Classification Systems: An Experimental Study
Authors: Abdelhamid Neda , Padmavathy Arun , Peebles David , Thabtah Fadi , Goulder-Horobin Daymond
Published: March 2020

Machine learning (ML) is a branch of computer science that is rapidly gaining popularity within the healthcare arena due to its ability to explore large datasets to discover useful patterns that can be interepreted for decision-making and prediction. ML techniques are used for the analysis of clinical parameters and their combinations for prognosis, therapy planning and support and patient management and wellbeing. In this research, we investigate a crucial problem associated with medical applications such as autism spectrum disorder (ASD) data imbalances in which cases are far more than just controls in the dataset. In autism diagnosis data, the number of possible instances is linked with one class, i.e. the no ASD is larger than the ASD, and this may cause performance issues such as models favouring the majority class and undermining the minority class. This research experimentally measures the impact of class imbalance issue on the performance of different classifiers on real autism datasets when various data imbalance approaches are utilised in the pre-processing phase. We employ oversampling techniques, such as Synthetic Minority Oversampling (SMOTE), and undersampling with different classifiers including Naive Bayes, RIPPER, C4.5 and Random Forest to measure the impact of these on the performance of the models derived in terms of area under curve and other metrics. Results pinpoint that oversampling techniques are superior to undersampling techniques, at least for the toddlers’ autism dataset that we consider, and suggest that further work should look at incorporating sampling techniques with feature selection to generate models that do not overfit the dataset.
Road-Type Classification through Deep Learning Networks Fine-Tuning
Authors: Saleh Yaser , Otoum Nesreen
Published: March 2020

Road-type classification is increasingly becoming important to be embedded in interactive maps to provide additional useful information for users. The ubiquity of smartphones supported with high definition cameras offers a rich source of information that can be utilised by machine learning techniques. In this paper, we propose a novel Convolutional Neural Network (CNN)-based approach to classify road types using a collection of publicly available images. To overcome the challenge of having huge dataset to train and test CNNs, our approach employs fine-tuning. We conducted an experiment where the VGG-16, VGG-S and GoogLeNet networks were constructed and fine-tuned with the dataset gathered. Our approach achieved an accuracy of 99% in VGG-16 and 100% in VGG-S, while using the GoogLeNet model produced results up to 98%.
PCR SURVEILLANCE OF FOUR PROTOTYPIC RAT PARVOVIRUSES IN LABORATORY RAT COLONIES IN TAIWAN
Authors: Chang Yung-Hui , Liao Yi-Chun , Wang Ko-Wei , Wang Ming-Hseng , Fang Ber-Hsiung , Wan Cho-Hua
Published: March 2020

Prototypic rat parvoviruses are among the most common infectious agents in laboratory rats worldwide. It is important to determine the infectious condition of rat parvoviruses in research colonies in Taiwan. In this study, virus species-specific PCR assays were applied to screen Kilham rat virus (KRV), Toolan’s H-1 virus (H-1 virus), rat parvovirus (RPV) and rat minute virus (RMV) in 203 rats from five different research colonies in Taiwan. In this survey, the infection rate of rat parvoviruses was 19.2% (39/203), including KRV (12.3%; 25/203), RMV (8.9%; 18/203) and RPV (1.0%; 2/203). Dual infection of KRV and RMV were detected in 3.0% (6/203) of samples. No rats were positive for H-1 virus. The infectious rates of KRV and RMV detected in this study are much higher than those reported in USA and in Europe. Rat parvovirus PCR assays reported in this paper could be a useful tool for routine rat health monitoring program applied in laboratory rat facilities. [Chang YH, Liao YC, Wang KW, Hsieh SC, Wang MH, Fang BH, Chang CY, Chueh LL, Wan CH, PCR Surveillance of four prototypic rat parvoviruses in laboratory rat colonies in Taiwan, Taiwan Vet J 46(1): 1–7, 2020]
Efficient Multi-Factor User Authentication Protocol with Forward Secrecy for Real-Time Data Access in WSNs
Authors: Wang Ding , Wang Ping , Wang Chenyu
Published: March 2020

It is challenging to design a secure and efficient multi-factor authentication scheme for real-time data access in wireless sensor networks. On the one hand, such real-time applications are generally security critical, and various security goals need to be met. On the other hand, sensor nodes and users’ mobile devices are typically of a resource-constrained nature, and expensive cryptographic primitives cannot be used. In this work, we first revisit four foremost multi-factor authentication schemes (i.e., those of Amin et al. (JNCA’18), Srinivas et al. (IEEE TDSC’18), Li et al. (JNCA’18), and Li et al. (IEEE TII’18)) and use them as case studies to reveal the difficulties and challenges in designing a multi-factor authentication scheme for wireless sensor networks correctly. We identify the root causes for their failures in achieving truly multi-factor security and forward secrecy. We further propose a robust multi-factor authentication scheme that makes use of the imbalanced computational nature of the RSA cryptosystem, particularly suitable for scenarios where sensor nodes (but not the user’s device) are the main energy bottleneck. Comparison results demonstrate the superiority of our scheme. As far as we know, it is the first two-factor authentication scheme for real-time data access in WSNs that can satisfy all 12 criteria of the state-of-the-art evaluation metric under the harshest adversary model so far.
Explaining Financial Uncertainty through Specialized Word Embeddings
Authors: Theil Christoph Kilian , Štajner Sanja , Stuckenschmidt Heiner
Published: March 2020

The detection of vague, speculative, or otherwise uncertain language has been performed in the encyclopedic, political, and scientific domains yet left relatively untouched in finance. However, the latter benefits from public sources of big financial data that can be linked with extracted measures of linguistic uncertainty as a mean of extrinsic model validation. Doing so further helps in understanding how the linguistic uncertainty of financial disclosures might induce financial uncertainty to the market. To explore this field, we use term weighting methods to detect linguistic uncertainty in a large dataset of financial disclosures. As a baseline, we use an existing dictionary of financial uncertainty triggers; furthermore, we retrieve related terms in specialized word embedding models to automatically expand this dictionary. Apart from an industry-agnostic expansion, we create expansions incorporating industry-specific jargon. In a set of cross-sectional event study regressions, we show that the such enriched dictionary explains a significantly larger share of future volatility, a common financial uncertainty measure, than before. Furthermore, we show that—different to the plain dictionary—our embedding models are well suited to explain future analyst forecast uncertainty. Notably, our results indicate that enriching the dictionary with industry-specific vocabulary explains a significantly larger share of financial uncertainty than an industry-agnostic expansion.
Active Balancing Mechanism for Imbalanced Medical Data in Deep Learning–Based Classification Models
Authors: Zhang Hongyi , Zhang Haoke , Pirbhulal Sandeep , Wu Wanqing , Albuquerque Victor Hugo C. De
Published: March 2020

Imbalanced data always has a serious impact on a predictive model, and most under-sampling techniques consume more time and suffer from loss of samples containing critical information during imbalanced data processing, especially in the biomedical field. To solve these problems, we developed an active balancing mechanism (ABM) based on valuable information contained in the biomedical data. ABM adopts the Gaussian naïve Bayes method to estimate the object samples and entropy as a query function to evaluate sample information and only retains valuable samples of the majority class to achieve under-sampling. The Physikalisch Technische Bundesanstalt diagnostic electrocardiogram (ECG) database, including 5,173 normal ECG samples and 26,654 myocardial infarction ECG samples, is applied to verify the validity of ABM. At imbalance rates of 13 and 5, experimental results reveal that ABM takes 7.7 seconds and 13.2 seconds, respectively. Both results are significantly faster than five conventional under-sampling methods. In addition, at the imbalance rate of 13, ABM-based data obtained the highest accuracy of 92.23% and 97.52% using support vector machines and modified convolutional neural networks (MCNNs) with eight layers, respectively. At the imbalance rate of 5, the processed data by ABM also achieved the best accuracy of 92.31% and 98.46% based on support vector machines and MCNNs, respectively. Furthermore, ABM has better performance than two compared methods in
F
1-measure, G-means, and area under the curve. Consequently, ABM could be a useful and effective approach to deal with imbalanced data in general, particularly biomedical myocardial infarction ECG datasets, and the MCNN can also achieve higher performance compared to the state of the art.
CirclePIN
Authors: Guerar Meriem , Verderame Luca , Merlo Alessio , Palmieri Francesco , Migliardi Mauro , Vallerini Luca
Published: March 2020

In the last months, the market for personal wearable devices has been booming significantly, and, in particular, smartwatches are starting to assume a fundamental role in the Bring Your Own Device (BYOD) arena as well as in the more general Internet of Things (IoT) ecosystem, by acting both as sensitive data sources and as user identity proxies. These new roles, complementing the more traditional personal assistance and telemetry/tracking ones, open new perspectives in their integration in complex IoT-based critical infrastructures such as e-payment, health care monitoring, and emergency systems, as well as in their usage as remote control facilities in smart services. Users can access their IoT devices at any time from any place through smartwatches. We argue that this new scenario calls for a strengthened and more resilient authentication of users on these devices, despite their limitations in terms of dimensions and hardware constraints that may considerably affect the usability of security mechanisms. In this article, we present an innovative authentication scheme targeted at smartwatches, namely CirclePIN, that provides both resilience to most common attacks and a high level of usability in tests with real users.
Guest Column
Authors: Broda Sabine , Machiavelo Antonio , Moreira Nelma , Reis Rogerio
Published: March 2020

Average-case complexity results provide important information about computational models and methods, as worst-case scenarios usually occur for a negligible amount of cases. The framework of analytic combinatorics provides an elegant tool for that analysis, completely avoiding the use of statistical methods, by relating combinatorial objects to algebraic properties of complex analytic generating functions. We have previously used this framework to study the average size of di erent nondeterministic nite automata simulations of regular expressions. In some cases it was not feasible to obtain explicit expressions for the generating functions involved, and we had to resort to Puiseux expansions. This is particularly important when dealing with families of generating functions indexed by a parameter, e.g. the size of underlying alphabets, and when the corresponding generating functions are obtained by algebraic curves of degree higher than two. In this paper we expound our approach in a tutorial pace, providing sufficient details to make it available to the reader.
Regional collagen turnover and composition of the human patellar tendon
Authors: Zhang Cheng , Couppé Christian , Scheijen Jean L. J. M. , Schalkwijk Casper G. , Kjaer Michael , Magnusson S. Peter , Svensson Rene B.
Published: March 2020

Tendon pathology (tendinopathy) typically occurs in specific regions of a tendon, and growth in response to exercise also appears to be more pronounced in specific regions. In a previous study in animals we found evidence of regional differences in tendon turnover, but whether the turnover of human patellar tendon differs in different regions still remains unknown. Patellar tendons were obtained from cadavers of healthy men and women (body donation program, n = 5 donors, >60 yr of age). Samples were taken from 10 different regions along the length, width, and thickness of the tendon. Turnover was measured by14C bomb pulse dating and also estimated from the accumulation of advanced glycation end products (AGEs) by fluorescence (340/460 nm) in addition to measurement of specific AGEs by mass spectrometry. Composition in terms of collagen, glycosaminoglycans (GAGs), and DNA was also assessed in each region.14C results showed that all tendon regions had a similar14C concentration, which was equal to the average atmospheric14C concentration during the first 15 yr of the person’s life. Fluorescence normalized to dry weight did not differ between regions, nor did specific AGEs. Higher GAG content was observed in the proximal and near the distal insertion of the tendon. In conclusion, healthy human patellar tendon displays no regional differences in collagen turnover throughout life.

NEW & NOTEWORTHY Tendon injuries and tendinopathies typically occur in specific regions of the tendon, but the reason for this specificity is not well understood. A potential factor in injury susceptibility is tissue turnover, and previous work suggests that the tendon core has practically no turnover during adult life; however, it is not known whether this is true for other regions of the tendon. Our present results on healthy human patellar tendon clearly demonstrate that turnover does not differ between regions and thereby cannot explain differences in injury susceptibility. The findings also indicate that all regions of the tendon are formed simultaneously during skeletal maturation and do not turn over appreciably during adulthood. This is an important finding because little is known about tendon growth during maturation in humans.
Mechanical cardiopulmonary interactions during exercise in health and disease
Authors: Cheyne William S. , Harper Megan I. , Gelinas Jinelle C. , Sasso John P. , Eves Neil D.
Published: March 2020

The heart and lungs are anatomically coupled through the pulmonary circulation and coexist within the sealed thoracic cavity, making the function of these systems highly interdependent. Understanding of the complex mechanical interactions between cardiac and pulmonary systems has evolved over the last century to appreciate that changes in respiratory mechanics significantly impact pulmonary hemodynamics and ventricular filling and ejection. Furthermore, given that the left and right heart share a common septum and are surrounded by the nondistensible pericardium, direct ventricular interaction is an important mediator of both diastolic and systolic performance. Although it is generally considered that cardiopulmonary interaction in healthy individuals at rest minimally affects hemodynamics, the significance during exercise is less clear. Adverse heart-lung interaction in respiratory disease is of growing interest as it may contribute to the pathogenesis of comorbid cardiovascular dysfunction and exercise intolerance in these patients. Similarly, heart failure represents a pathological uncoupling of the cardiovascular and pulmonary systems, whereby cardiac function may be impaired by the normal ventilatory response to exercise. Despite significant research contributions to this complex area, the mechanisms of cardiopulmonary interaction in the intact human and the clinical consequences of adverse interactions in common respiratory and cardiovascular diseases, particularly during exercise, remain incompletely understood. The purpose of this review is to present the key physiological principles of cardiopulmonary interaction as they pertain to resting and exercising hemodynamics in healthy humans and the clinical implications of adverse cardiopulmonary interaction during exercise in chronic obstructive pulmonary disease (COPD), pulmonary hypertension, and heart failure.
Postprandial skeletal muscle metabolism following a high-fat diet in sedentary and endurance-trained males
Authors: Baugh Mary Elizabeth , Bowser Suzanne M. , McMillan Ryan P. , Davy Brenda M. , Essenmacher Lauren A. , Neilson Andrew P. , Hulver Matthew W. , Davy Kevin P.
Published: March 2020

Our objective was to determine the influence of a high-fat diet (HFD) on fasting and postprandial skeletal muscle substrate metabolism in endurance-trained (ET) compared with sedentary (SED) humans. SED ( n = 17) and ET ( n = 7) males were control-fed a 10-day moderate-fat diet followed by a 5-day isocaloric HFD (55% fat, 30% carbohydrate). Skeletal muscle biopsies were taken in the fasted condition and 4 h after a high-fat meal (820 kcals; 63% fat and 25% carbohydrate). Palmitate-induced suppression of pyruvate oxidation, an indication of substrate preference, and oxidation of fat and glucose were measured in homogenized skeletal muscle in fasted and fed states. Postprandial responses were calculated as percent changes from fasting to fed states. Postprandial suppression of pyruvate oxidation was maintained after the HFD in ET, but not SED skeletal muscle, suggesting greater adaptability to dietary intake changes in the former. Fasting total fat oxidation increased due to the HFD in ET skeletal muscle ( P = 0.006), which was driven by incomplete fat oxidation ( P = 0.008). Fasting fat oxidation remained unchanged in skeletal muscle of SED individuals. Yet, postprandial fat oxidation was similar between groups. Fasting glucose oxidation was elevated after the HFD in ET ( P = 0.036), but not SED, skeletal muscle. Postprandial glucose oxidation was reduced due to the HFD in SED ( P = 0.002), but not ET, skeletal muscle. These findings provide insight into differing substrate metabolism responses between SED and ET individuals and highlight the role that the prevailing diet may play in modulating fasting and postprandial metabolic responses in skeletal muscle.

NEW & NOTEWORTHY The relationship between high dietary fat intake and physical activity level and their combined effect on skeletal muscle substrate metabolism remains unclear. We assessed the influence of the prevailing diet in modulating substrate oxidation in skeletal muscle of endurance-trained compared with sedentary humans during a high-fat challenge meal. Collectively, our findings demonstrate the adaptability of skeletal muscle in endurance-trained individuals to high dietary fat intake.