bluuebunny/crossref_metadata_2025 huggingface dataset:
A Network Perspective on the Comorbidity of Personality Disorders and Mental Disorders: An Illustration of Depression and Borderline Personality Disorder
Authors: Köhne Annemarie C.J. , Isvoranu Adela-Maria
Published: July 2021

The comorbidity of personality disorders and mental disorders is commonly understood through three types of theoretical models: either a) personality disorders precede mental disorders, b) mental disorders precede personality disorders, c) mental disorders and personality disorders share common etiological grounds. Although these hypotheses differ with respect to their idea of causal direction, they all imply a latent variable perspective, in which it is assumed that either personality and mental disorders are latent variables that have certain causal relations [models a) and b)]; or that, as in model c), the common etiology is in fact a latent variable that causes symptomatology of both personality and mental disorders. We aim to provide another perspective on the comorbidity between personality and mental disorders, namely a network perspective. To this end, we investigated Major Depression (MD) and Borderline Personality Disorder (BPD) and hypothesized that symptoms of BPD and MD could interact with one another rather than being caused by a latent variable (e.g., identity diffusion → unstable relationships → depressed mood). To illustrate this theoretical network conceptualization of the comorbidity of BPD and MD we analyzed a cross-sectional clinical dataset of 376 patients who were asked to complete the Structured Clinical Interview for DSM-IV Axis II Disorders and the Beck Depression Inventory II. The results identify direct associations between symptoms of MD and BPD. If we take the links in this empirical network to be ‘substantive', this suggests a radical shift of our current conceptualization of the comorbidity of mental disorders and personality disorders.
Mutual Relationship Between Sleep Disorders, Quality of Life and Psychosocial Aspects in Patients With Psoriasis
Authors: Nowowiejska Julia , Baran Anna , Flisiak Iwona
Published: July 2021

Psoriasis is a chronic, autoimmune skin disease affecting about 2–4% of the worldwide population. It is now perceived as a systemic disease because of the complex pathogenesis and multiple comorbidities. It leads to decreased quality of life and productivity of patients. Nowadays, sleep disorders are investigated as well in relation to psoriasis as another possible comorbidity. This review focuses on possible negative effects of sleep deprivation, decreased quality of life, and psychosocial status in patients with psoriasis and highlights their mutual, complex relationship of divergent consequences. The relationship between sleep disorders and psychosocial status in patients with psoriasis is bidirectional and resembles a vicious circle, one abnormality triggering the other. Sleep disorders additionally increase the risk of metabolic and psychiatric diseases in psoriatic patients who are already at increased risk of developing such disorders. There should be measures taken to screen patients with psoriasis for sleep disorders in order to diagnose early and treat.
Cognitive Empathy in Subtypes of Antisocial Individuals
Authors: Chang Shou-An A. , Tillem Scott , Benson-Williams Callie , Baskin-Sommers Arielle
Published: July 2021

Cognitive empathy allows individuals to recognize and infer how others think and feel in social situations and provides a foundation for the formation and maintenance of mutually constructive relationships. It may seem intuitive to assume that individuals who engage in antisocial behavior, who disregard the rights of others, might have problems with cognitive empathy. However, careful examination of the literature suggests that any dysfunction in cognitive empathy associated with antisociality varies by subtype of antisocial individual and is specific to subcomponents of cognitive empathy. In this review, we (1) briefly define subtypes of antisocial individuals (“psychopathic” vs. “antisocial-only”), (2) summarize specific components of cognitive empathy; (3) review existing literature examining cognitive empathy through questionnaires, behavioral tasks, and neuroimaging within different antisocial subtypes; and (4) discuss the limitations of the current research and potential future directions. Individuals in the psychopathic subtype fail to implicitly engage in cognitive empathy, and potentially lack insight into this issue reflected in no self-reported problems with cognitive empathy, but show an ability to engage in cognitive empathy when explicitly required. Individuals in the antisocial-only subtype appear able to engage in cognitive empathy, showing no differences on questionnaire or behavioral tasks that tap explicit cognitive empathy, but may display subtle difficulties accurately inferring (affective theory of mind) the emotions of others. We end the review by noting areas for future research, including the need to: (1) document the patterns of equifinality that exist across levels of analysis for these antisocial subtypes; (2) examine the temporality of empathy and antisociality development; (3) carefully consider and label subcomponents of cognitive empathy in research on antisocial behavior; and (4) investigate the intersection among environmental experiences, cognitive empathy, and antisocial behavior.
Online Mental Health Assessments of COVID-19 Patients in South Korea
Authors: Lee Jung Hyun , Lee Dayoung , Hyun Soyoen , Hong Ji Sun , Kim Chang-Hoon , Kim Woojin , Sim Minyoung
Published: July 2021

Experiences of infectious diseases cause stressful and traumatic life events, hence, coronavirus disease 2019 (COVID-19) patients could suffer from various mental health problems requiring psychological support services. This study investigates the severity of mental health problems among confirmed COVID-19 patients. From March to November 2020, we collected the data from 118 COVID-19 patients who voluntarily participated in the National Center for Disaster Trauma's online mental health assessment consisting of self-report scales like Primary Care of Posttraumatic Stress Disorder screen (PC-PTSD), Generalized Anxiety Disorder-7 (GAD-7), Patient Health Questionnaire-9 (PHQ-9), Patient Health Questionnaire-15 (PHQ-15), and P4 Suicidality Screener. For control, 116 other disaster-experienced and 386 non-COVID-19-experienced participants were recruited. The COVID-19 patients showed more severe symptoms including post-traumatic symptoms, depression, anxiety, and somatic symptoms than control groups across all four screening scales (p < 0.001). Regarding high-risk, COVID-19 patients had an increased association with high-risk compared to the comparison groups (PC-PTSD: OR = 24.16, 95% CI = 13.52–43.16 p < 0.001; PHQ-9: OR = 14.45, 95% CI = 8.29–25.19, p < 0.001; GAD-7: OR=20.71, 95% CI = 10.74–39.96, p < 0.001; PHQ-15: OR = 5.65, 95% CI = 3.44–9.25, p < 0.001; P4: OR = 14.67, 95% CI = 8.95–25.07, p < 0.001). This study's results imply that there is a high-risk of overall mental health problems, especially stronger associations of post-traumatic stress symptoms, in COVID-19 patients. These findings help inform practitioners about the psychological responses to COVID-19 experiences and to prepare appropriate interventions and services for the incremental number of confirmed cases.
Risk Factors for SARS-CoV-2 Infection, Pneumonia, Intubation, and Death in Northeast Mexico
Authors: Cordero-Franco Hid Felizardo , De La Garza-Salinas Laura Hermila , Gomez-Garcia Salvador , Moreno-Cuevas Jorge E. , Vargas-Villarreal Javier , González-Salazar Francisco
Published: July 2021

Despite the social distancing and mobility restriction measures implemented for susceptible people around the world, infections and deaths due to COVID-19 continued to increase, even more so in the first months of 2021 in Mexico. Thus, it is necessary to find risk groups that can benefit from more aggressive preventive measures in a high-density population. This is a case-control study of suspected COVID-19 patients from Nuevo León, Mexico. Cases were: (1) COVID-19-positive patients and COVID-19-positive patients who (2) developed pneumonia, (3) were intubated and (4) died. Controls were: (1) COVID-19-negative patients, (2) COVID-19-positive patients without pneumonia, (3) non-intubated COVID-19-positive patients and (4) surviving COVID-19-positive patients. ≥ 18 years of age, not pregnant, were included. The pre-existing conditions analysed as risk factors were age (years), sex (male), diabetes mellitus, hypertension, chronic obstructive pulmonary disease, asthma, immunosuppression, obesity, cardiovascular disease, chronic kidney disease and smoking. The Mann-Whitney U tests, Chi square and binary logistic regression were used. A total of 56,715 suspected patients were analysed in Nuevo León, México, with 62.6% being positive for COVID-19 and, of those infected, 14% developed pneumonia, 2.9% were intubated and 8.1% died. The mean age of those infected was 44.7 years, while of those complicated it was around 60 years. Older age, male sex, diabetes, hypertension, and obesity were risk factors for infection, complications, and death from COVID-19. This study highlights the importance of timely recognition of the population exposed to pre-existing conditions to prioritise preventive measures against the virus.
How the Labor Market Affects the Self-Perceived Health of Older Workers. The Evidence From Central and Eastern European Countries (CEECs)
Authors: Ucieklak-Jeż Paulina , Bem Agnieszka
Published: July 2021

Background:The paper aims to analyze the impact of key labor market indicators on the self-assessed health of the population of older workers (aged 55–64).

Methods:Authors build the econometric models where the dependent variable is the self-perceived health status (for women and men separately). Explanatory variables are selected key indicators of the labor market, covering unemployment, including long-term, inactivity, or under-employment. The average household income is used to control the effect of wealth. Additionally, the models incorporate the variable describing the proximity of retirement. The research sample consists of nine countries of Central and Eastern Europe: Poland, Czech Republic, Slovakia, Hungary, Lithuania, Latvia, Estonia, Bulgaria, and Romania.

Results and Conclusions:The study confirms that in the group of elderly workers, the perceived state of health is influenced by long-term unemployment, inactivity, and, in the case of women, time-related underemployment.
Income, Relative Deprivation and the Self-Rated Health of Older People in Urban and Rural China
Authors: Qin Wenzhe , Xu Lingzhong , Wu Shoucai , Shao Hui
Published: July 2021

Background: Substantial evidence indicated that absolute income is directly associated with health. Few studies have, however, examined if relative income may be equally associated with health. This study aimed to investigate the association between absolute income/relative deprivation (RD) and self-rated health (SRH). We also investigated whether the urban-rural difference was existing in these associations.

Methods: Using cross-sectional data of 7,070 participants in the Shandong Family Health Service Survey of older people, this study applied binary logistic model and semi-parametric model to estimate the effect of absolute income and relative deprivation on SRH of older people. The Kakwani Index was used as a measure of relative deprivation at the individual level.

Results: Absolute income has a significant positive effect on the SRH among both urban and rural older people. When considered RD as a variable, both absolute income and RD have negative significant effects on SRH among all older people. In addition, the negative effect of RD on rural elderly is more pronounced than that of urban older populations. Semi-parametric regression results show that there was a complex non-linear relationship between income and SRH. Psychological distress substantially attenuated the association between relative deprivation and SRH.

Conclusions: Relative deprivation is negatively associated with self-rated health in both urban and rural older people after controlling the absolute income. RD may partly explain the association between income inequality and worse health status. Compared with the urban elderly, the effect of income-based relative deprivation on SRH was more pronounced among the rural elderly, and more care should be given to the lower income and rural older populations.
Performance of Basic Life Support by Lifeboat Crewmembers While Wearing a Survival Suit and Life Vest: A Randomized Controlled Trial
Authors: Venema Allart M. , Sahinovic Marko M. , Ramaker Albert J. D. W. R. , van de Riet Yvette N. , Absalom Anthony R. , Wietasch J. K. Götz
Published: July 2021

Introduction: Crewmembers of the “Royal Netherlands Sea Rescue Institution” (KNRM) lifeboats must wear heavy survival suits with integrated lifejackets. This and the challenging environment onboard (boat movements, limited space) might influence Basic Life Support (BLS) performance. The primary objective of this study was to assess the impact of the protective gear on single-rescuer BLS-quality.

Material and Methods: Sixty-five active KNRM crewmembers who had recently undergone a BLS-refresher course were randomized to wear either their protective gear (n = 32) or their civilian clothes (n = 33; control group) and performed five 2-min sessions of single rescuer BLS on a mannequin on dry land. BLS-quality was assessed according to Dutch and European Resuscitation guidelines. A between group analysis (Mann-Whitney U) and a repeated within group analysis of both groups (Friedman test) were performed.

Results: There were no major demographic differences between the groups. The protective gear did not significant impair BLS-quality. It was also not associated with a significant increase in the perceived exertion of BLS (Borg's Rating scale). Compression depth, compression frequency, the percentage of correct compression depth and of not leaning on the thorax, and ventilation volumes in both groups were suboptimal when evaluated according to the BLS-guidelines.

Conclusions: The protective gear worn by KNRM lifeboat-crewmembers does not have a significant influence on BLS-quality under controlled study conditions. The impact and significance on outcome in real life situations needs to be studied further. This study provides valuable input for optimizing the BLS-skills of lifeboat crewmembers.
The Importance of Mental Models in Implementation Science
Authors: Holtrop Jodi Summers , Scherer Laura D. , Matlock Daniel D. , Glasgow Russell E. , Green Lee A.
Published: July 2021

Implementation science is concerned with the study of adoption, implementation and maintenance of evidence-based interventions and use of implementation strategies to facilitate translation into practice. Ways to conceptualize and overcome challenges to implementing evidence-based practice may enhance the field of implementation science. The concept of mental models may be one way to view such challenges and to guide selection, use, and adaptation of implementation strategies to deliver evidence-based interventions. A mental model is an interrelated set of beliefs that shape how a person forms expectations for the future and understands the way the world works. Mental models can shape how an individual thinks about or understands how something or someone does, can, or should function in the world. Mental models may be sparse or detailed, may be shared among actors in implementation or not, and may be substantially tacit, that is, of limited accessibility to introspection. Actors' mental models can determine what information they are willing to accept and what changes they are willing to consider. We review the concepts of mental models and illustrate how they pertain to implementation of an example intervention, shared decision making. We then describe and illustrate potential methods for eliciting and analyzing mental models. Understanding the mental models of various actors in implementation can provide crucial information for understanding, anticipating, and overcoming implementation challenges. Successful implementation often requires changing actors' mental models or the way in which interventions or implementation strategies are presented or implemented. Accurate elicitation and understanding can guide strategies for doing so.
Sonoelastography of the Shoulder: A Narrative Review
Authors: Babaei-Ghazani Arash , Majdalani Carl-Elie , Luong Dien Hung , Bertrand-Grenier Antony , Sobczak Stéphane
Published: July 2021

Sonoelastography is a relatively new non-invasive imaging tool to assess the in vivo qualitative and quantitative biomechanical properties of various tissues. Two types of sonoelastography (SE) are commonly explored: strain and shear wave. Sonoelastography can be used in multiple medical subspecialties to assess pathological tissular changes by obtaining mechanical properties, shear wave speed, and strain ratio data. Although there are various radiological imaging methods, such as MRI or CT scan, to assess musculoskeletal structures (muscles, tendons, joint capsules), SE is more accessible since this approach is of low cost and does not involve radiation. As of 2018, SE has garnered promising data in multiple studies. Preliminary clinico-radiological correlations have been established to bridge tissue biomechanical findings with their respective clinical pathologies. Specifically, concerning the shoulder complex, recent findings have described mechanical tissue changes in shoulder capsulitis. The long head of the biceps and supraspinatus SE were among the recently studied structures with conditions regarding impingement, tendinosis, and tears. Since ultrasonography has established itself as an important tool in shoulder evaluation, it completes the history and physical examination skills of the clinicians. This study will provide an update on the most recent findings on SE of shoulder structures.
Alzheimer's Disease and Oral-Systemic Health: Bidirectional Care Integration Improving Outcomes
Authors: Rice Anne O.
Published: July 2021

Dentistry is an effective healthcare field that can impact Alzheimer's disease through prevention and education. Every day dental providers use an arsenal of assessment protocols directly coinciding with modifiable Alzheimer's risk factors. An innovative way to help in the prevention of Alzheimer's disease is to utilize oral health professionals who reach the public in ways other health care providers may not. Bidirectional care integration is needed to stifle many systemic diseases and Alzheimer's disease is no different. Ultimately with collaborative care the patient reaps the benefits. Alzheimer's is associated with many etiologies and pathophysiological processes. These include cardiovascular health, smoking, sleep, inflammatory pathogens, and diabetes. In the United States, dental providers assess each of these factors daily and can be instrumental in educating patients on the influence of these factors for dementia prevention. Globally, by 2025, the number of people with Alzheimer's disease is expected to rise by at least 14%. Such increases will strain local and national health care systems, but for the US if Medicare were expanded to include dental services, many older adults could be spared needless suffering. The goal of this perspective article is to highlight existing practices being used in the field of dentistry that can easily be adapted to educate patients in preventive care and treat risk factors. It is the duty of healthcare professionals to explore all opportunities to stem the advance of this disease and by integrating oral and systemic health into transdisciplinary science, health care and policy may do just that.
Effects of Spatial Resolution on Burned Forest Classification With ICESat-2 Photon Counting Data
Authors: Liu Meng , Popescu Sorin , Malambo Lonesome
Published: July 2021

Accurately monitoring forest fire activities is critical to understanding carbon dynamics and climate change. Three-dimensional (3D) canopy structure changes caused by fire make it possible to adopt Light Detection and Ranging (LiDAR) in burned forest classification. This study focuses on the effects of spatial resolution when using LiDAR data to differentiate burned and unburned forests. The National Aeronautics and Space Administration’s (NASA) Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) mission provides LiDAR datasets such as the geolocated photon data (ATL03) and the land vegetation height product (ATL08), which were used in this study. The ATL03 data were filtered by two algorithms: the ATL08 algorithm (ILV) and the adaptive ground and canopy height retrieval algorithm (AGCH), producing classified canopy points and ground points. Six typical spatial resolutions: 10, 30, 60, 100, 200, and 250 m were employed to divide the classified photon points into separate segments along the track. Twenty-six canopy related metrics were derived from each segment. Sentinel-2 images were used to provide reference land cover maps. The Random Forest classification method was employed to classify burned and unburned segments in the temperate forest in California and the boreal forest in Alberta, respectively. Both weak beams and strong beams of ICESat-2 data were included in comparisons. Experiment results show that spatial resolution can significantly influence the canopy structures we detected. Classification accuracies increase along with coarser spatial resolutions and saturate at 100 m segment length, with overall accuracies being 79.43 and 92.13% in the temperate forest and the boreal forest, respectively. Classification accuracies based on strong beams are higher than those of using weak beams due to a larger point density in strong beams. The two filtering algorithms present comparable accuracies in burned forest classification. This study demonstrates that spatial resolution is a critical factor to consider when using spaceborne LiDAR for canopy structure characterization and classification, opening an avenue for improved measurement of forest structures and evaluation of terrestrial vegetation responses to climate change.
Redefining Bean Iron Biofortification: A Review of the Evidence for Moving to a High Fe Bioavailability Approach
Authors: Glahn Raymond P. , Noh Hannah
Published: July 2021

Iron biofortification of the common bean (Phaseolus vulgaris) commenced in earnest ~18 years ago. Based on knowledge at the time, the biofortification approach for beans was simply to breed for increased Fe concentration based on 3 major assumptions: (1) The average bean Fe concentration is ~50 μg/g; (2) Higher Fe concentration results in more bioavailable Fe delivered for absorption; (3) Breeding for high Fe concentration is a trait that can be achieved through traditional breeding and is sustainable once a high Fe bean sample is released to farmers. Current research indicates that the assumptions of the high Fe breeding approach are not met in countries of East Africa, a major focus area of bean Fe biofortification. Thus, there is a need to redefine bean Fe biofortification. For assumption 1, recent research indicates that the average bean Fe concentration in East Africa is 71 μg/g, thus about 20 μg/g higher than the assumed value. For assumption 2, recent studies demonstrate that for beans higher Fe concentration does not always equate to more Fe absorption. Finally, for assumption 3, studies show a strong environment and genotype by environment effect on Fe concentration, thus making it difficult to develop and sustain high Fe concentrations. This paper provides an examination of the available evidence related to the above assumptions, and offers an alternative approach utilizing tools that focus on Fe bioavailability to redefine Fe biofortification of the common bean.
Lobectomy Can Improve the Survival of Patients With Non-small Cell Lung Cancer With Lung Oligometastatic
Authors: Wang Lingwei , Jiao Fanglei , Dong Lin , Li Qinchuan , Liu Gang , Hu Xuefei
Published: July 2021

Background: This study was to evaluate the value of lobectomy in the prognosis of Non-small cell lung cancer (NSCLC) patients with primary metastasis based on the Surveillance Epidemiology and End Results (SEER) database.

Methods: This was a population-based retrospective study and the clinical data were collected from the National Cancer Institute's SEER database between 2010 and 2015. The effects of pulmonary surgery and surgical procedures on lung cancer-specific survival (LCSS) and overall survival (OS) were assessed, and the COX regression models were employed to evaluate the survival of primary surgery in patients with primary metastatic NSCLC (pmNSCLC) and the survival of surgical procedure in pmNSCLC patients.

Results: A total of 55,717 patients diagnosed with pmNSCLC between 2010 and 2015 were enrolled, and pulmonary surgery was indicated in 1,575 (2.83%) patients. Surgery was an independent risk factor for LCSS (P < 0.001, HR 0.658, 95%CI: 0.637–0.680) and OS (P < 0.001, HR 0.665, 95%CI: 0.644–0.686) of pmNSCLC patients. The surgery was associated with better OS (P < 0.001, HR 0.678, 95%CI: 0.657–0.699). The site of metastasis was also related to the survival after primary tumor surgery (P = 0.001). As compared to the sublobectomy and pneumonectomy, lobectomy improved the LCSS for NSCLC patients with single-organ metastasis, rather than multiple metastases (P < 0.001). In patients receiving sublobectomy, lobectomy, and pneumonectomy, the median LCSS was 12, 28, and 13 months, respectively, and the 5-year LCSS rate was 14.39, 32.06, and 17.24%, respectively.

Conclusion: The effect of locoregional surgery on the survival of pmNSCLC patients with single-organ metastasis has been underestimated, and lobectomy may be a preferred treatment for patients with single-lung metastasis.
Comparative Transcriptome Analyses of the Developmental Stages of Taenia multiceps
Authors: Li Wen-Hui , Yang Yang , Zhang Nian-Zhang , Wang Jian-Kui , Liu Yin-Ju , Li Li , Yan Hong-Bin , Jia Wan-Zhong , Fu Baoquan
Published: July 2021

Cerebral coenurosis, caused by the larvae of Taenia multiceps (Coenurus cerebralis), is a fatal central nervous system disease in sheep and other herbivores and occasionally humans. Comparative transcriptomic profiles of the developmental stages of the parasite remain unknown. In this study, RNA sequencing was used to determine the transcriptome profiles of different stages of the life cycle of T. multiceps, including Oncosphere, Coenurus cerebralis (Pro with Cyst), and Adult (Adu), as well as scolex-neck proglottids (Snp), immature–mature proglottids (Imp), and gravid proglottids (Grp) of the adult stage. A total of 42.6 Gb (average 6.1 Gb) Illumina pair-end reads with a 125-bp read length were generated for seven samples. The total number of differentially expressed genes (DEGs) in the various life stages ranged from 2,577 to 3,879; however, for the tissues of the adult worm, the range was from 1,229 to 1,939. Kyoto Encyclopedia of Genes and Genomes analysis showed that the DEGs mainly participated in cellular and metabolic processes, binding and catalytic activity, genetic information processing, and environmental information processing. In addition, a large number of genes related to development and parasite–host interaction were identified. Quantitative reverse transcription-polymerase chain reaction confirmed that the levels of 28 selected DEGs were consistent with those determined using RNA sequencing. The present study provides insights into the mechanisms of the development and parasitic life of T. multiceps.
Pharmacokinetics and Biologic Activity of Apixaban in Healthy Dogs
Authors: Herrera Noelle D. , Birschmann Ingvild , Wolny Monika , Papich Mark G. , Brooks Marjory B. , Goggs Robert
Published: July 2021

Thrombosis is common in critically ill dogs and causes considerable morbidity and mortality. The direct factor Xa inhibitor apixaban is safe, efficacious, and convenient in humans. This study aimed to determine the pharmacokinetics (PK), bioactivity, protein binding, and bioavailability of apixaban following intravenous (IV) and oral (PO) administration to healthy dogs. Six healthy, adult, mixed-breed dogs were administered apixaban 0.18 mg/kg IV and then following a minimum 2-week washout period administered apixaban 0.2 mg/kg PO. Dogs were monitored using an apixaban-calibrated anti-Xa bioassay, prothrombin time (PT) and activated partial thromboplastin time (aPTT) and tissue-factor thromboelastography (TF-TEG). Plasma apixaban concentrations were measured using liquid chromatography-tandem mass spectrometry. Concentration-time plots were constructed, and PK modeling performed using compartmental methods. Administration of IV and PO apixaban was well-tolerated. Following IV administration, mean half-life was 4.1 h, and volume of distribution was 177 ml/kg. Apixaban was highly protein bound (98.6%). Apixaban concentrations and anti-Xa activity were highly correlated (R20.994,P< 0.0001). Intravenous apixaban significantly prolonged PT at time points up to 1 h, and aPTT at time points up to 0.25 h post-administration. Coagulation times were positively correlated with apixaban concentrations (PT R20.599,P< 0.0001; aPTT R20.430,P< 0.0001) and TF-TEG R-time was significantly prolonged 0.25 h post-administration. Following oral administration, mean bioavailability was 28.4%, lag time was 2 h, time to Cmaxwas 5 h and the apparent elimination half-life was 3.1 h. Oral apixaban significantly prolonged PT at 4, 6, and 8 h but aPTT and TF-TEG were not consistently affected by oral apixaban. Apixaban concentrations are best monitored using anti-Xa activity. Future studies should determine PK and bioactivity of other doses using commercial tablets and following multidose administration and establish safe, effective dosing ranges in sick dogs.
MCI Detection Using Kernel Eigen-Relative-Power Features of EEG Signals
Authors: Hsiao Yu-Tsung , Tsai Chia-Fen , Wu Chien-Te , Trinh Thanh-Tung , Lee Chun-Ying , Liu Yi-Hung
Published: July 2021

Classification between individuals with mild cognitive impairment (MCI) and healthy controls (HC) based on electroencephalography (EEG) has been considered a challenging task to be addressed for the purpose of its early detection. In this study, we proposed a novel EEG feature, the kernel eigen-relative-power (KERP) feature, for achieving high classification accuracy of MCI versus HC. First, we introduced the relative powers (RPs) between pairs of electrodes across 21 different subbands of 2-Hz width as the features, which have not yet been used in previous MCI-HC classification studies. Next, the Fisher’s class separability criterion was applied to determine the best electrode pairs (five electrodes) as well as the frequency subbands for extracting the most sensitive RP features. The kernel principal component analysis (kernel PCA) algorithm was further performed to extract a few more discriminating nonlinear principal components from the optimal RPs, and these components form a KERP feature vector. Results carried out on 51 participants (24 MCI and 27 HC) show that the newly introduced subband RP feature showed superior classification performance to commonly used spectral power features, including the band power, single-electrode relative power, and also the RP based on the conventional frequency bands. A high leave-one-participant-out cross-validation (LOPO-CV) classification accuracy 86.27% was achieved by the RP feature, using a simple linear discriminant analysis (LDA) classifier. Moreover, with the same classifier, the proposed KERP further improved the accuracy to 88.24%. Finally, cascading the KERP feature to a nonlinear classifier, the support vector machine (SVM), yields a high MCI-HC classification accuracy of 90.20% (sensitivity = 87.50% and specificity = 92.59%). The proposed method demonstrated a high accuracy and a high usability (only five electrodes are required), and therefore, has great potential to further develop an EEG-based computer-aided diagnosis system that can be applied for the early detection of MCI.
Correction: Chidepatil et al. (2020). From Trash to Cash: How Blockchain and Multi-Sensor-Driven Artificial Intelligence Can Transform Circular Economy of Plastic Waste? Administrative Sciences 10: 23
Authors: Chidepatil Aditya , Bindra Prabhleen , Kulkarni Devyani , Qazi Mustafa , Kshirsagar Meghana , Sankaran Krishnaswamy
Published: July 2021

The authors would like to make the following corrections about the published paper [...]
Cultivating Patriotism—A Pioneering Note on a Russian Dimension of Corporate Ethics Management
Authors: Yashalova Natalia N. , Ruban Dmitry A. , Latushko Natalia A.
Published: July 2021

Corporate codes of conduct address various issues, some of which can be country-specific. A tentative analysis of the content of 42 codes of the leading Russian private companies implies that about a quarter of them consider patriotism, which generally matches the significant attention paid to this issue in Russian society. Of 10 companies with the biggest annual revenue, four (40%) consider patriotism in their codes. The main topics are pride in a company’s relevance to state development, initiatives, and interests, as well as care for the veterans of the World War II. The present study implies that patriotism can be an important dimension of corporate ethics management in some countries.
Applications and Potential of Genome-Editing Systems in Rice Improvement: Current and Future Perspectives
Authors: Tabassum Javaria , Ahmad Shakeel , Hussain Babar , Mawia Amos Musyoki , Zeb Aqib , Ju Luo
Published: July 2021

Food crop production and quality are two major attributes that ensure food security. Rice is one of the major sources of food that feeds half of the world’s population. Therefore, to feed about 10 billion people by 2050, there is a need to develop high-yielding grain quality of rice varieties, with greater pace. Although conventional and mutation breeding techniques have played a significant role in the development of desired varieties in the past, due to certain limitations, these techniques cannot fulfill the high demands for food in the present era. However, rice production and grain quality can be improved by employing new breeding techniques, such as genome editing tools (GETs), with high efficiency. These tools, including clustered, regularly interspaced short palindromic repeats (CRISPR) systems, have revolutionized rice breeding. The protocol of CRISPR/Cas9 systems technology, and its variants, are the most reliable and efficient, and have been established in rice crops. New GETs, such as CRISPR/Cas12, and base editors, have also been applied to rice to improve it. Recombinases and prime editing tools have the potential to make edits more precisely and efficiently. Briefly, in this review, we discuss advancements made in CRISPR systems, base and prime editors, and their applications, to improve rice grain yield, abiotic stress tolerance, grain quality, disease and herbicide resistance, in addition to the regulatory aspects and risks associated with genetically modified rice plants. We also focus on the limitations and future prospects of GETs to improve rice grain quality.
Assessment of the SASI Spectral Shape Index Time Series for Mapping Rice Ecosystems in the Mediterranean Region
Authors: Tornos Lucía , Domínguez José Antonio , Moyano Maria C. , Recuero Laura , Cicuéndez Víctor , García-García María Jesús , Palacios-Orueta Alicia
Published: July 2021

There is a growing need to map rice ecosystems and to develop methods for monitoring rice distribution in order to account for rapid land use changes worldwide. In this study, we evaluated a methodology based on Vegetation Indices time series derived from an 8-day MODIS composite to identify rice fields and develop rice maps that can be timely updated in the long term. We have assessed the potential of the Spectral Shape Index time series and compared its performance with the Normalized Difference Vegetation Index in two coastal locations and in an inland location in the Mediterranean Region for 2012. A profile similarity comparison method, the Spectral Angle Mapper, was accomplished between the reference rice annual profile and the annual profiles of both indices in a pixel basis in order to determine rice pixels. The resultant maps were validated with rice masks, where available, or ortophotos and crop surface statistics where not. The results obtained demonstrated the potential of both indices to provide accurate rice maps when applied together with spectral matching techniques. The overall accuracy was 92.8%, 98.1% and 90.1% for the Spectral Shape Index and 92.4%, 77.24% and 82.8% for the Normalized Difference Vegetation Index in each location. The excellent performance of the Spectral Shape Index in the three locations highlighted the importance of exploring angular indices to improve the identification of land cover dynamics.
Evaluation of the Regional-Scale Optimal K Rate Based on Sustainable Apple Yield and High-Efficiency K Use in Loess Plateau and Bohai Bay of China: A Meta-Analysis
Authors: Tang Wenzheng , Wang Wene , Chen Dianyu , Cui Ningbo , Yang Haosheng , Hu Xiaotao
Published: July 2021

In order to meet the growing food demand of the global population and maintain sustainable soil fertility, there is an urgent need to optimize fertilizer application amount in agricultural production practices. Most of the existing studies on the optimal K rates for apple orchards were based on case studies and lack information on optimizing K-fertilizer management on a regional scale. Here, we used the method of combining meta-analysis with the K application rate-yield relationship model to quantify and summarize the optimal K rates of the Loess Plateau and Bohai Bay regions in China. We built a dataset based on 159 observations obtained from 18 peer-reviewed literature studies distributed in 15 different research sites and evaluated the regional-scale optimal K rates for apple production. The results showed that the linear plus platform model was more suitable for estimating the regional-scale optimal K rates, which were 208.33 and 176.61 kg K ha−1 for the Loess Plateau and Bohai Bay regions of China, respectively. Compared with high K application rates, the optimal K rates increased K use efficiency by 45.88–68.57%, with almost no yield losses. The optimal K rates also enhanced the yield by 6.30% compared with the low K application rates.
Identifying Suitable Genotypes for Different Cassava Production Environments—A Modeling Approach
Authors: Phoncharoen Phanupong , Banterng Poramate , Vorasoot Nimitr , Jogloy Sanun , Theerakulpisut Piyada , Hoogenboom Gerrit
Published: July 2021

Crop simulation models can be used to identify appropriate genotypes and growing environments for improving cassava yield. The aim of this study was to determine the best genotypes for different cassava production environments using the cropping system model (CSM)–MANIHOT–Cassava. Data from cassava experiments that were conducted from 2009–2011 and 2014–2015 at Khon Kaen, Thailand, were used to evaluate the model. Simulations were then conducted for different scenarios using four cassava genotypes (Kasetsart 50, Rayong 9, Rayong 11, and CMR38–125–77), twelve planting dates (at monthly intervals starting in January and ending in December), and ten locations in Thailand under fully irrigated and rainfed conditions using 30 years of historical weather data. Model evaluation with the experimental data for total biomass and storage root yield indicated that the model classified well for relative productivity among different planting dates. The model indicated that growing cassava under irrigated conditions generally produced higher biomass and storage root yield than under rainfed conditions. The cassava genotype CMR38–125–77 was identified for high biomass, while the genotype Rayong 9 was identified as a good genetic resource for high yield. The December planting date resulted in the highest biomass for all locations, while the February planting date produced the highest storage root yield for almost all locations. The results from this study suggest that the CSM–MANIHOT–Cassava model can assist in determining suitable genotypes for different cassava production environments for Thailand, and that this approach could be applicable to other cassava growing areas.
Evaluation of Factors Affecting Colostrum Quality and Quantity in Holstein Dairy Cattle
Authors: Soufleri Aikaterini , Banos Georgios , Panousis Nikolaos , Fletouris Dimitrios , Arsenos Georgios , Kougioumtzis Alexandros , Valergakis Georgios E.
Published: July 2021

The objective of this study was to conduct a large-scale investigation of colostrum composition and yield and an evaluation of factors affecting them. In this study, 1017 clinically healthy Holstein cows from 10 farms were used. The colostrum TS were measured using a digital Brix refractometer. Fat, protein and lactose content were determined using an infrared Milk Analyzer. Statistical analysis was conducted using a series of univariate general linear models. The mean (±SD) percentage of colostrum fat, protein, lactose and TS content were 6.37 (3.33), 17.83 (3.97), 2.15 (0.73) and 25.80 (4.68), respectively. Parity had a significant positive effect on the protein and TS content and a negative one on fat content. The time interval between calving and colostrum collection had a significant negative effect on the fat, protein and TS contents and a positive one on lactose. Colostrum yield had a significant negative effect on the protein and TS content, and it was affected by all factors considered. In addition to TS, the evaluation of the colostrum fat content appears essential when neonates’ energy needs are considered. The Brix refractometer, an inexpensive and easy to use devise, can be used effectively in colostrum quality monitoring.
Digital Phenotyping in Livestock Farming
Authors: Neethirajan Suresh , Kemp Bas
Published: July 2021

Currently, large volumes of data are being collected on farms using multimodal sensor technologies. These sensors measure the activity, housing conditions, feed intake, and health of farm animals. With traditional methods, the data from farm animals and their environment can be collected intermittently. However, with the advancement of wearable and non-invasive sensing tools, these measurements can be made in real-time for continuous quantitation relating to clinical biomarkers, resilience indicators, and behavioral predictors. The digital phenotyping of humans has drawn enormous attention recently due to its medical significance, but much research is still needed for the digital phenotyping of farm animals. Implications from human studies show great promise for the application of digital phenotyping technology in modern livestock farming, but these technologies must be directly applied to animals to understand their true capacities. Due to species-specific traits, certain technologies required to assess phenotypes need to be tailored efficiently and accurately. Such devices allow for the collection of information that can better inform farmers on aspects of animal welfare and production that need improvement. By explicitly addressing farm animals’ individual physiological and mental (affective states) needs, sensor-based digital phenotyping has the potential to serve as an effective intervention platform. Future research is warranted for the design and development of digital phenotyping technology platforms that create shared data standards, metrics, and repositories.
Identification of Animal-Based Welfare Indicators in Captive Reptiles: A Delphi Consultation Survey
Authors: Whittaker Alexandra L. , Golder-Dewar Brianna , Triggs Jordyn L. , Sherwen Sally L. , McLelland David J.
Published: July 2021

There is an increasing focus on evidence-based welfare assessment by animal care staff in zoos, along with a strong interest in animal welfare by the zoo-visiting public, to the extent that this can influence their choice of institutions to visit. Regulatory oversight of animal welfare standards continues to strengthen across many jurisdictions. Zoos are increasingly formalizing their practices with the development and refinement of evidence-based welfare assessment tools. There has been a drive for welfare assessment tools to comprise both resource-based and animal-based measures. However, animal-based indicators are not always well characterized, in terms of their nature and whether they infer a positive or negative affective state. This is especially so for reptiles, which are often considered behaviorally inexpressive and are under-researched. In this study, a Delphi consultation approach was used to gather expert opinion on the suitability of potential animal-based indicators of welfare for inclusion in a welfare assessment tool across four families of reptiles: Agamidae, Chelidae, Pythonidae, and Testudinidae. Two rounds of online surveys were conducted eliciting responses from a global group of professionals who work with reptiles. In the first survey, respondents were provided with an author-derived list of potential animal-based indicators for consideration of their validity and practicality as welfare indicators. The indicators were refined for the second survey including only those indicators that were considered valid or practical on the first survey (≥4 on a 5-point Likert scale), and that achieved ≥70% consensus amongst experts. In the second survey, respondents were asked to re-evaluate the reliability and practicality of the indicators and to rank them on these facets. Eight to ten assessment indicators for each family of reptiles were identified from Survey 2. These indicators were often health related, for example, presence of oculo-nasal discharge or wounds. However, some true behavioral indicators were identified, such as showing species-specific interest and alertness. These indicators should now be incorporated into taxon-tailored welfare assessment tools for trial and validation in captive reptile populations. This study provides a next step towards developing reptile-specific animal welfare assessment tools for these often-overlooked animals.
Age-Related Changes in the Primary Motor Cortex of Newborn to Adult Domestic Pig Sus scrofa domesticus
Authors: Desantis Salvatore , Minervini Serena , Zallocco Lorenzo , Cozzi Bruno , Pirone Andrea
Published: July 2021

The pig has been increasingly used as a suitable animal model in translational neuroscience. However, several features of the fast-growing, immediately motor-competent cerebral cortex of this species have been adequately described. This study analyzes the cytoarchitecture of the primary motor cortex (M1) of newborn, young and adult pigs (Sus scrofa domesticus). Moreover, we investigated the distribution of the neural cells expressing the calcium-binding proteins (CaBPs) (calretinin, CR; parvalbumin, PV) throughout M1. The primary motor cortex of newborn piglets was characterized by a dense neuronal arrangement that made the discrimination of the cell layers difficult, except for layer one. The absence of a clearly recognizable layer four, typical of the agranular cortex, was noted in young and adult pigs. The morphometric and immunohistochemical analyses revealed age-associated changes characterized by (1) thickness increase and neuronal density (number of cells/mm2 of M1) reduction during the first year of life; (2) morphological changes of CR-immunoreactive neurons in the first months of life; (3) higher density of CR- and PV-immunopositive neurons in newborns when compared to young and adult pigs. Since most of the present findings match with those of the human M1, this study strengthens the growing evidence that the brain of the pig can be used as a potentially valuable translational animal model during growth and development.