bluuebunny/crossref_metadata_2025 huggingface dataset:
Probabilistic graphical model for the evaluation of the emotional and dramatic personality disorders
Authors: García-Franco Jose D. , Díez Francisco J. , Carrasco Miguel Á.
Published: November 2022

Personality disorders are psychological ailments with a major negative impact on patients, their families, and society in general, especially those of the dramatic and emotional type. Despite all the research, there is still no consensus on the best way to assess and treat them. Traditional assessment of personality disorders has focused on a limited number of psychological constructs or behaviors using structured interviews and questionnaires, without an integrated and holistic approach. We present a novel methodology for the study and assessment of personality disorders consisting in the development of a Bayesian network, whose parameters have been obtained by the Delphi method of consensus from a group of experts in the diagnosis and treatment of personality disorders. The result is a probabilistic graphical model that represents the psychological variables related to the personality disorders along with their relations and conditional probabilities, which allow identifying the symptoms with the highest diagnostic potential. This model can be used, among other applications, as a decision support system for the assessment and treatment of personality disorders of the dramatic or emotional cluster. In this paper, we discuss the need to validate this model in the clinical population along with its strengths and limitations.
CLIP knows image aesthetics
Authors: Hentschel Simon , Kobs Konstantin , Hotho Andreas
Published: November 2022

Most Image Aesthetic Assessment (IAA) methods use a pretrained ImageNet classification model as a base to fine-tune. We hypothesize that content classification is not an optimal pretraining task for IAA, since the task discourages the extraction of features that are useful for IAA, e.g., composition, lighting, or style. On the other hand, we argue that the Contrastive Language-Image Pretraining (CLIP) model is a better base for IAA models, since it has been trained using natural language supervision. Due to the rich nature of language, CLIP needs to learn a broad range of image features that correlate with sentences describing the image content, composition, environments, and even subjective feelings about the image. While it has been shown that CLIP extracts features useful for content classification tasks, its suitability for tasks that require the extraction of style-based features like IAA has not yet been shown. We test our hypothesis by conducting a three-step study, investigating the usefulness of features extracted by CLIP compared to features obtained from the last layer of a comparable ImageNet classification model. In each step, we get more computationally expensive. First, we engineer natural language prompts that let CLIP assess an image's aesthetic without adjusting any weights in the model. To overcome the challenge that CLIP's prompting only is applicable to classification tasks, we propose a simple but effective strategy to convert multiple prompts to a continuous scalar as required when predicting an image's mean aesthetic score. Second, we train a linear regression on the AVA dataset using image features obtained by CLIP's image encoder. The resulting model outperforms a linear regression trained on features from an ImageNet classification model. It also shows competitive performance with fully fine-tuned networks based on ImageNet, while only training a single layer. Finally, by fine-tuning CLIP's image encoder on the AVA dataset, we show that CLIP only needs a fraction of training epochs to converge, while also performing better than a fine-tuned ImageNet model. Overall, our experiments suggest that CLIP is better suited as a base model for IAA methods than ImageNet pretrained networks.
Orbital hopping maneuvers with two Astrobee free-flyers: Ground and flight experiments
Authors: Kwok-Choon Stephen , Hudson Jennifer , Romano Marcello
Published: November 2022

Dynamic hopping maneuvers using mechanical actuation are proposed as a method of locomotion for free-flyer vehicles near or on large space structures. Such maneuvers are of interest for applications related to proximity maneuvers, observation, cargo carrying, fabrication, and sensor data collection. This study describes a set of dynamic hopping maneuver experiments performed using two Astrobees. Both vehicles were made to initially grasp onto a common free-floating handrail. From this initial condition, the active Astrobee launched itself using mechanical actuation of its robotic arm manipulator. The results are presented from the ground and flight experimental sessions completed at the Spacecraft Robotics Laboratory of the Naval Postgraduate School, the Intelligent Robotics Group facility at NASA Ames Research Center, and hopping maneuvers aboard the International Space Station. Overall, this study demonstrates that locomotion through mechanical actuation could successfully launch a free-flyer vehicle in an initial desired trajectory from another object of similar size and mass.
Perceived authenticity of virtual characters makes the difference
Authors: Huang Junru , Jung Younbo
Published: November 2022

Conventionally, human-controlled and machine-controlled virtual characters are studied separately under different theoretical frameworks based on the ontological nature of the particular virtual character. However, in recent years, the technological advancement has made the boundaries between human and machine agency increasingly blurred. This manuscript proposes a theoretical framework that can explain how various virtual characters, regardless of their ontological agency, can be treated as unique social actors with a focus on perceived authenticity. Specifically, drawing on the authenticity model in computer-mediated communication proposed by Lee (2020) and a typology of virtual characters, a multi-layered perceived authenticity model is proposed to demonstrate how virtual characters do not have to be perceived as humans and yet can be perceived as authentic to their human interactants.
E-guerrilla 3D participation: Approach, implementation, and usability study
Authors: Chassin Thibaud , Ingensand Jens
Published: November 2022

Typical urban participatory approaches engage citizens through lengthy sessions far from the area under transformation by an urban project. Several issues result from these settings of involvement including the mobilization of similar individuals, overwhelming participatory codes, or a gap between the affected urban landscape and the location of the session. This study introduces a modern approach that leverages the use of 3D web applications to address some of the critical challenges of popular participatory sessions. The developed approach, named e-guerrilla 3D participation, is based on five dimensions: immediate participation, ease of use, flexibility, place-based engagement, and immersivity. A prototype complying with these five dimensions was implemented in this study. The prototype promotes an in situ engagement where all the users (without distinction) of a public area can explore a future urban project and get involved within minutes. A usability study conducted with 26 expert and non-expert participants investigated the prototype through a fictive scenario. The findings demonstrate a positive outcome in terms of participatory results that are identifiable with the prototype (highlighting the controversial elements of the projects) and encourage feedback collected during a survey and interview. The usability study suggests key aspects that should be considered to improve the design of participatory sessions and their interactive mediums (or tools), such as realism, affordance, incentive, and purpose. The promising participatory approach (and prototype), which was unpacked step-by-step in this study, does not replace typical practices but could help to complement them by reaching a non-selected and broader public; hence leading to the design of more inclusive participatory approaches.
A statistical study of space hurricanes in the Northern Hemisphere
Authors: Lu Sheng , Xing Zan-Yang , Zhang Qing-He , Zhang Yong-Liang , Ma Yu-Zhang , Wang Xiang-Yu , Oksavik Kjellmar , Lyons L. R. , Nanan Balan , Liu Jing , Wang Yong , Deng Zhong-Xin , Xia Kai , Song Di
Published: November 2022

The space hurricane is a newly discovered large-scale three-dimensional magnetic vortex structure that spans the polar ionosphere and magnetosphere. At the height of the ionosphere, it has a strong circular horizontal plasma flow with a nearly zero-flow center and a coincident cyclone-shaped aurora caused by strong electron precipitation associated with intense upward magnetic field-aligned currents. By analyzing the long-term optical observation onboard the Defense Meteorological Satellite Program (DMSP) F16 satellite from 2005 to 2016, we found that space hurricanes in the Northern Hemisphere occur in summer and have a maximum occurrence rate in the afternoon sector around solar maximum. In particular, space hurricanes are more likely to occur in the dayside polar cap at magnetic latitudes greater than 80°, and their MLT (magnetic local time) dependence shows a positive relationship with the IMF (interplanetary magnetic field) clock angle. We also found that space hurricanes occur mainly under dominant positive IMF By and Bz and negative Bx conditions. It is suggested that the stable high-latitude lobe reconnection, which occurs under the conditions of a large Earth’s dipole tilt angle and high ionosphere conductivity in summer, should be the formation mechanism of space hurricanes. The result will give a better understanding of the solar wind–magnetosphere–ionosphere coupling process under northward IMF conditions.
Evaluation of the effect of jasmonic acid elicitation on composition of pigments and biological activities in green callus of neem (Azadirachta indica)
Authors: Ahmad Fauzi Nurul Syazwani , Abd Rahim Muhamad Hafiz , Abdul Majid Nazia , Othman Rashidi , Yaacob Jamilah Syafawati
Published: November 2022

This study was carried out with the aim of determining the effects of jasmonic acid (JA) elicitation on the bioactive pigments' biosynthesis and the antioxidant activities in green callus of Azadirachta indica of two different ages (4- and 8-week-old). Plant tissue culture technique was employed to induce the formation of green callus from leaf explants of A. indica on Murashige and Skoog (MS) medium supplemented with 0.6 mg/L thidiazuron (CM) and three different concentrations of JA (2, 4, and 6 mg/L). The methanolic extracts from the green callus were used for determination of total chlorophyll content (TCh), total carotenoid content (TC), total anthocyanin content (TAC), total phenolic content (TPC), and total flavonoid content (TFC) through colorimetric and HPLC analyses. The highest amount of yield was obtained from CM and 2 mg/L JA (2JA) extracts for 4- and 8-week-old samples, respectively. Phytochemical screening revealed the presence of alkaloids, flavonoids, phenols, tannins, and terpenoids in all 4- and 8-week-old samples elicited with 2, 4 and 6 mg/L JA. The highest value for TAC, TCh, TC, TPC, and TFC of 4- and 8-week-old samples were from callus cultured on media supplemented with 6 mg/L JA (6JA) and 4 mg/L JA (4JA), respectively. The lowest IC50 values were found to be 8.29 ± 0.10 mg/mL (6JA) for 4-week-old and 7.73 ± 0.03 mg/mL (4JA) for 8-week-old samples. The highest Ferric Reducing Antioxidant Power (FRAP) values obtained in this study were 90.60 ± 1.55 g/g (6JA), and 74.59 ± 3.91 g/g (4JA), respectively, for 4- and 8-week-old samples. Moreover, Pearson's correlation analysis revealed a significant correlation between TAC, TCh, TC, TPC, and TFC with ABTS and FRAP assays. In addition, PCA analysis revealed that 83.5% of the information (variances) contained in the data were retained by the first two principal components. Overall, these findings suggested that JA supplementation into the culture media significantly increase the chlorophyll, carotenoid, anthocyanin, phenolic and flavonoid contents and JA concentrations at 6 mg/L JA and 4 mg/L JA yielded the highest pigments content in 4- and 8-weeks-old callus, respectively.
Anti-BLV antibodies in whey correlate with bovine leukemia virus disease progression and BoLA-DRB3 polymorphism
Authors: Nakatsuchi Ayumi , Bao Aronggaowa , Watanuki Sonoko , Matsuura Ryosuke , Borjigin Liushiqi , Bai Lanlan , Kuroda Maho , Matsumoto Yasunobu , Kohara Junko , Aida Yoko
Published: November 2022

Introduction

Bovine leukemia virus (BLV) belongs to the family Retroviridae and is a causative agent for enzootic bovine leucosis, the most common neoplastic disease affecting cattle worldwide. BLV proviral load (PVL) is associated with disease progression and transmission risk but requires blood collection and quantitative PCR testing. Anti-BLV antibodies in whey have been used as a diagnostic tool for BLV infection; however, quantitative utilization has not been fully investigated. Furthermore, bovine leukocyte antigen (BoLA)-DRB3 is a polymorphic gene associated with BLV infectivity and PVL, but its effect on anti-BLV antibody levels in whey from BLV infected dams is unknown. Therefore, we aimed to investigate whether it is possible to correctly predict PVL in the blood and milk based on the amount of anti-BLV antibodies in milk, and whether the BoLA-DRB3 alleles associate with the amount of anti-BLV antibodies in milk.

Methods

We examined whey from 442 dams from 11 different dairy farms located in 6 prefectures in Japan, including susceptible dams carrying at least one BoLA−DRB3*012:01 or *015:01 allele related with high PVL, resistant dams carrying at least one BoLA-DRB3*002:01, *009:02, or *014:01:01 allele related with low PVL, and neutral dams carrying other alleles.

Results

First, our results provided compelling evidence that anti-BLV antibody levels in whey were positively correlated with the anti-BLV antibody levels in serum and with BLV PVL in blood and milk, indicating the possibility of estimating BLV PVL in blood and milk by measuring anti-BLV antibody levels in whey. Thus, our results showed that antibody titers in milk might be effective for estimating BLV transmission risk and disease progression in the field. Second, we demonstrated that anti-BLV antibody levels in whey from BLV resistant dams were significantly lower than those from susceptible and neutral dams.

Discussion

This is the first report suggesting that the BoLA-DRB3 polymorphism affects anti-BLV antibody levels in whey from BLV-infected dams. Taken together, our results suggested that anti-BLV antibody levels in whey, measured by enzyme-linked immunosorbent assay, may be a useful marker to diagnose the risk of BLV infection and estimate PVL in blood and milk.
Point-of-care testing in companion and food animal disease diagnostics
Authors: Velayudhan Binu T. , Naikare Hemant K.
Published: November 2022

Laboratory diagnoses of animal diseases has advanced tremendously in recent decades with the advent of cutting-edge technologies such as real-time polymerase chain reaction, next generation sequencing (NGS), matrix-assisted laser desorption/ionization time—of—flight mass spectrometry (MALDI-TOF MS) and others However, most of these technologies need sophisticated equipment, laboratory space and highly skilled workforce. Therefore, there is an increasing market demand for point-of-care testing (POCT) in animal health and disease diagnostics. A wide variety of assays based on antibodies, antigens, nucleic acid, and nanopore sequencing are currently available. Each one of these tests have their own advantages and disadvantages. However, a number of research and developmental activities are underway in both academia and industry to improve the existing tests and develop newer and better tests in terms of sensitivity, specificity, turnaround time and affordability. In both companion and food animal disease diagnostics, POCT has an increasing role to play, especially in resource-limited settings. It plays a critical role in improving animal health and wellbeing in rural communities in low- and middle-income countries. At the same time, ensuring high standard of quality through proper validation, quality assurance and regulation of these assays are very important for accurate diagnosis, surveillance, control and management of animal diseases. This review addresses the different types of POCTs currently available for companion and food animal disease diagnostics, tests in the pipeline and their advantages and disadvantages.
Effects of Mass Attachments on Flutter Characteristics of Thin-Walled Panels
Authors: Qi Wuchao , Wang Meng , Tian Sumei
Published: November 2022

Mass attachments may exist in the design and use of an aircraft panel, such as sensor layout, internal wiring, surface icing, etc. These mass attachments can change the flutter characteristics of the panel in supersonic flight and have important impacts on structural safety. In order to investigate the flutter characteristics of the panel with mass attachments, an assumed mode method is proposed to deal with the changes in the modal properties of the panel structure. Combined with the first order piston theory and p-k method, the flutter velocities and flutter frequencies of the panel under different cases can be obtained in the frequency domain. Firstly, based on the large displacement with a small strain assumption proposed by von Kármán and the proposed assumed mode method, the structural dynamic model of a simply supported panel with mass attachments and artificial dampers is constructed. Then, modal aerodynamic forces of the simply supported panel can be obtained based on first-order piston theory. Finally, flutter equations are transformed into the frequency domain and solved by the p-k method. The results showed that the existence of mass attachments can significantly change the flutter velocities and flutter frequencies of the panel. However, the flutter characteristics of the panel can be enhanced or recovered through some appropriate damper configuration schemes. Calculating the flutter characteristics of thin-walled panels with mass attachments can more accurately simulate real situations during flight, and one can obtain a safer design scheme of thin-walled panels.
Spatial Distribution Patterns for Identifying Risk Areas Associated with False Smut Disease of Rice in Southern India
Authors: Huded Sharanabasav , Pramesh Devanna , Chittaragi Amoghavarsha , Sridhara Shankarappa , Chidanandappa Eranna , Prasannakumar Muthukapalli K. , Manjunatha Channappa , Patil Balanagouda , Shil Sandip , Pushpa Hanumanthappa Deeshappa , Raghunandana Adke , Usha Indrajeet , Balasundram Siva K. , Shamshiri Redmond R.
Published: November 2022

False smut disease (FSD) of rice incited by Ustilaginoidea virens is an emerging threat to paddy cultivation worldwide. We investigated the spatial distribution of FSD in different paddy ecosystems of South Indian states, viz., Andhra Pradesh, Karnataka, Tamil Nadu, and Telangana, by considering the exploratory data from 111 sampling sites. Point pattern and surface interpolation analyses were carried out to identify the spatial patterns of FSD across the studied areas. The spatial clusters of FSD were confirmed by employing spatial autocorrelation and Ripley’s K function. Further, ordinary kriging (OK), indicator kriging (IK), and inverse distance weighting (IDW) were used to create spatial maps by predicting the values at unvisited locations. The agglomerative hierarchical cluster analysis using the average linkage method identified four main clusters of FSD. From the Local Moran’s I statistic, most of the areas of Andhra Pradesh and Tamil Nadu were clustered together (at I > 0), except the coastal and interior districts of Karnataka (at I < 0). Spatial patterns of FSD severity were determined by semi-variogram experimental models, and the spherical model was the best fit. Results from the interpolation technique, the potential FSD hot spots/risk areas were majorly identified in Tamil Nadu and a few traditional rice-growing ecosystems of Northern Karnataka. This is the first intensive study that attempted to understand the spatial patterns of FSD using geostatistical approaches in India. The findings from this study would help in setting up ecosystem-specific management strategies to reduce the spread of FSD in India.
Seismic Rehabilitation Techniques for Conserving and Managing Cultural Heritage of old City Fortress in Novi Pazar
Authors: Aleksić Julija , Zećirović Lejla , Dragović Danilo , Slavković Branko , Suljević Jasmin , Božović Jelena
Published: November 2022

In the last decade, increased awareness of the importance of preserving old masonry structures of cultural heritage has turned to the development of sustainable strategies for their reconstruction and seismic strengthening. This research includes the analysis and determination of the necessary measures due to the assessment of the condition of the constructive and structural parts of the buildings belonging to the old City Fortress in Novi Pazar. In this study, the fragility and vulnerability of the building is identified in order to sanction and recommend strengthening and seismic resistance to potentially strong levels of earthquakes, preserving the original structure of the building and its authenticity and integrity. The presented techniques aim to improve seismic performance and preserve structures for future generations, with the least impact on changing the value of the investigated cultural heritage. On the other hand, due to the modern demands of society, it is recommended to implement digital conservation and management of cultural heritage in order to create new content and ensure accessibility for all.
A Scaling Transition Method from SGDM to SGD with 2ExpLR Strategy
Authors: Zeng Kun , Liu Jinlan , Jiang Zhixia , Xu Dongpo
Published: November 2022

In deep learning, the vanilla stochastic gradient descent (SGD) and SGD with heavy-ball momentum (SGDM) methods have a wide range of applications due to their simplicity and great generalization. This paper uses an exponential scaling method to realize a smooth and stable transition from SGDM to SGD, which combines the advantages of the fast training speed of SGDM and the accurate convergence of SGD (named TSGD). We also provide some theoretical results on the convergence of this algorithm. At the same time, we take advantage of the learning rate warmup strategy’s stability and the learning rate decay strategy’s high accuracy. A warmup–decay learning rate strategy with double exponential functions is proposed (named 2ExpLR). The experimental results on different datasets for the proposed algorithms indicate that the accuracy is improved significantly and that the training is faster and more stable.
Effect of Thermal Treatment on Nano- and Micro-Copper Particles for Jewelry Making
Authors: Thongnopkun Pimthong , Phlayrahan Aumaparn , Madlee Dawan , Roubroumlert Worachai , Jamkratoke Matinee
Published: November 2022

Copper nanoparticles are being applied in the biosensors, engineering, electronic devices, and technology fields. A key advantage of nanomaterials is that their properties differ from their bulk with the same composition. However, the application of nano-copper particles for jewelry and artwork has not yet been revealed. We discovered and compared the application of nano-sized copper particles in jewelry fabrication with micro-copper particles. The nano- and micro-sized copper particles were synthesized and mixed with the same organic binders and water content to produce an alternative clay-like material for creating handmade jewelry and artwork. The article addresses the effects of thermal treatment on thermal behavior and the development of physical properties of differently sized copper particles. Their physical properties depend strongly on the size of the starting copper particles and heating conditions. We investigated the influence of thermal treatment, heating rate, firing temperature, and holding time to optimize the firing conditions for jewelry fabrication and wearing.
Variations of Secondary PM2.5 in an Urban Area over Central China during 2015–2020 of Air Pollutant Mitigation
Authors: Liang Dingyuan , Zhao Tianliang , Zhu Yan , Bai Yongqing , Fu Weikang , Zhang Yuqing , Liu Zijun , Wang Yafei
Published: November 2022

The lack of long-term observational data on secondary PM2.5 (SPM) has limited our comprehensive understanding of atmospheric environment change. This study develops an SPM estimation method, named Single-Tracer Approximate Envelope Algorithm (STAEA), to assess the long-term changes of SPM under different PM2.5 levels and in all seasons in Wuhan, Central China, over the period of anthropogenic pollutant mitigation in 2015–2020. The results show that: (1) the average proportions of SPM in ambient PM2.5 is 59.61% in a clean air environment, rising significantly to 71.60%, 73.73%, and 75.55%, respectively, in light, moderate, and heavy PM2.5 pollution, indicating the dominant role of SPM in air quality deterioration; (2) there are increasing trends of interannual changes of SPM at the light and moderate pollution levels of 1.95 and 3.11 μg·m−3·a−1 with extending SPM proportions in PM2.5 pollution, raising a challenge for further improvement in ambient air quality with mitigating light and moderate PM2.5 pollution; (3) the high SPM contributions ranging from 55.63% to 68.65% on a seasonal average and the large amplitude of seasonal SPM changes could dominate the seasonality of air quality; (4) the wintertime SPM contribution present a consistent increasing trend compared with the declining trends in spring, summer, and autumn, suggesting underlying mechanisms of SPM change for further deciphering the evolution of the atmospheric environment. Our results highlight the effects of air pollutant mitigation on long-term variations in SPM and its contributions with implications for atmospheric environment change.
Short-Term Rainfall Prediction Based on Radar Echo Using an Improved Self-Attention PredRNN Deep Learning Model
Authors: Wu Dali , Wu Li , Zhang Tao , Zhang Wenxuan , Huang Jianqiang , Wang Xiaoying
Published: November 2022

Accurate short-term precipitation forecast is extremely important for urban flood warning and natural disaster prevention. In this paper, we present an innovative deep learning model named ISA-PredRNN (improved self-attention PredRNN) for precipitation nowcasting based on radar echoes on the basis of the advanced PredRNN-V2. We introduce the self-attention mechanism and the long-term memory state into the model and design a new set of gating mechanisms. To better capture different intensities of precipitation, the loss function with weights was designed. We further train the model using a combination of reverse scheduled sampling and scheduled sampling to learn the long-term dynamics from the radar echo sequences. Experimental results show that the new model (ISA-PredRNN) can effectively extract the spatiotemporal features of radar echo maps and obtain radar echo prediction results with a small gap from the ground truths. From the comparison with the other six models, the new ISA-PredRNN model has the most accurate prediction results with a critical success index (CSI) of 0.7001, 0.5812 and 0.3052 under the radar echo thresholds of 10 dBZ, 20 dBZ and 30 dBZ, respectively.
Fractional Dynamical Behavior of an Elastic Magneto Piezo Oscillator Including Non-Ideal Motor Excitation
Authors: Ribeiro Mauricio A. , Balthazar Jose M. , Lenz Wagner B. , Felix Jorge L. P. , Litak Grzegorz , Tusset Angelo M.
Published: November 2022

In this work, we analyzed the nonlinear fractional dynamics in the equations of motion of a bar coupled to support under the effect of a potential described by two equally spaced magnetic poles. We also considered Bouc–Wen damping in the equations of motion. For external force vibrations, we considered an equation of a non-ideal motor based on the parameters that related the interaction between the oscillation and the excitation source. With such considerations, we explored the influence of the fractional derivative operator parameter on the average power generated by the device and the dynamic behavior to determine the chaotic and periodic regions. We use Bifurcation Diagrams, Test 0–1, Phase Portrait, and Poincaré Maps. As a conclusion, we established a set of parameters for the fractional differential equations to obtain higher average powers and the periodicity windows that corroborate the establishment of energetic orbits for energy harvesting.
Role of Goats in the Epidemiology of Coxiella burnetii
Authors: Anastácio Sofia , de Sousa Sérgio Ramalho , Saavedra Maria José , da Silva Gabriela Jorge
Published: November 2022

Since its first description in the late 1930s, Q fever has raised many questions. Coxiella burnetii, the causative agent, is a zoonotic pathogen affecting a wide range of hosts. This airborne organism leads to an obligate, intracellular lifecycle, during which it multiplies in the mononuclear cells of the immune system and in the trophoblasts of the placenta in pregnant females. Although some issues about C. burnetii and its pathogenesis in animals remain unclear, over the years, some experimental studies on Q fever have been conducted in goats given their excretion pattern. Goats play an important role in the epidemiology and economics of C. burnetii infections, also being the focus of several epidemiological studies. Additionally, variants of the agent implicated in human long-term disease have been found circulating in goats. The purpose of this review is to summarize the latest research on C. burnetii infection and the role played by goats in the transmission of the infection to humans.
Activin A Modulates Betaglycan Shedding via the ALK4-SMAD3-Dependent Pathway in Endometriotic Cells
Authors: Mwaura Agnes N. , Riaz Muhammad A. , Maoga Jane B. , Mecha Ezekiel , Omwandho Charles O. A. , Scheiner-Bobis Georgios , Meinhold-Heerlein Ivo , Konrad Lutz
Published: November 2022

The TGF-β superfamily members, activins and inhibins, are mainly involved in cell proliferation, cell survival, invasion, immune surveillance, and lesion growth in endometriosis. Herein, we investigated the modulation of the TGF-β type III receptor (betaglycan or BG) by activin A and inhibin A in endometriosis in vitro. Often, BG undergoes ectodomain shedding releasing soluble BG (sBG) which frequently antagonizes TGF-β signaling. The effects of activin A on BG shedding and signaling pathways involved were evaluated with the inhibitors LY364947 and SIS3, siRNA knockdown in human endometrial cells (12Z, THESC, Ishikawa, and primary stromal cells) and were quantified with BG ELISAs. The effects of activin A and inhibin A on the secretion of MMP2 and MMP3 were analyzed using ELISAs. The effects of activin A on the BG expression were analyzed using RT-qPCR and western blot. The CCK-8 and BrdU assays were used to evaluate the effects of the recombinant BG on cell viability and proliferation. Activin A stimulation resulted in a significant time- and dose-dependent reduction in BG shedding, which was found to be activin A/ALK-4/SMAD3- but not SMAD2-dependent. Activin A increased the BG mRNA expression but had no effect on the protein expression. Likewise, inhibin A was found to block BG shedding. Activin A, but not inhibin A, significantly enhanced the secretion of MMP2 and MMP3. The recombinant BG had no effect on the viability and proliferation of endometriotic cells. Together, these observations support a novel role for activin A with BG in modulating the TGF-β superfamily ligands in endometrial cells in vitro.
Developing an Improved Survival Prediction Model for Disease Prognosis
Authors: Chen Zhanbo , Wei Qiufeng
Published: November 2022

Machine learning has become an important research field in genetics and molecular biology. Survival analysis using machine learning can provide an important computed-aid clinical research scheme for evaluating tumor treatment options. However, the genomic features are high-dimensional, which limits the prediction performance of the survival learning model. Therefore, in this paper, we propose an improved survival prediction model using a deep forest and self-supervised learning. It uses a deep survival forest to perform adaptive learning of high-dimensional genomic data and ensure robustness. In addition, self-supervised learning, as a semi-supervised learning style, is designed to utilize unlabeled samples to improve model performance. Based on four cancer datasets from The Cancer Genome Atlas (TCGA), the experimental results show that our proposed method outperforms four advanced survival analysis methods in terms of the C-index and brier score. The developed prediction model will help doctors rethink patient characteristics’ relevance to survival time and personalize treatment decisions.
Cost Matrix of Molecular Pathology in Glioma—Towards AI-Driven Rational Molecular Testing and Precision Care for the Future
Authors: Jagasia Sarisha , Tasci Erdal , Zhuge Ying , Camphausen Kevin , Krauze Andra Valentina
Published: November 2022

Gliomas are the most common and aggressive primary brain tumors. Gliomas carry a poor prognosis because of the tumor’s resistance to radiation and chemotherapy leading to nearly universal recurrence. Recent advances in large-scale genomic research have allowed for the development of more targeted therapies to treat glioma. While precision medicine can target specific molecular features in glioma, targeted therapies are often not feasible due to the lack of actionable markers and the high cost of molecular testing. This review summarizes the clinically relevant molecular features in glioma and the current cost of care for glioma patients, focusing on the molecular markers and meaningful clinical features that are linked to clinical outcomes and have a realistic possibility of being measured, which is a promising direction for precision medicine using artificial intelligence approaches.
Sexual Dimorphism in Interstitial Lung Disease
Authors: Ozaki Mari , Glasgow Arlene , Oglesby Irene K. , Ng Wan Lin , Kelly Sile , Greene Catherine M. , Durcan Laura , Hurley Killian
Published: November 2022

Interstitial lung diseases (ILD) are a group of heterogeneous progressive pulmonary disorders, characterised by tissue remodelling and/or fibrotic scarring of the lung parenchyma. ILD patients experience lung function decline with progressive symptoms, poor response to treatment, reduced quality of life and high mortality. ILD can be idiopathic or associated with systemic or connective tissue diseases (CTD) but idiopathic pulmonary fibrosis (IPF) is the most common form. While IPF has a male predominance, women are affected more greatly by CTD and therefore associated ILDs. The mechanisms behind biological sex differences in these progressive lung diseases remain unclear. However, differences in environmental exposures, variable expression of X-chromosome related inflammatory genes and sex hormones play a role. Here, we will outline sex-related differences in the incidence, progression and mechanisms of action of these diseases and discuss existing and novel cellular and pre-clinical studies. Furthermore, we will highlight how sex-differences are not adequately considered in pre-clinical disease models, how gender bias exists in clinical diagnosis and how women are underrepresented in clinical trials. Future action on these observations will hopefully shed light on the role of biological sex in disease development, identify potential targets for intervention and increase female participant numbers in clinical trials.
PPARα in the Epigenetic Driver Seat of NAFLD: New Therapeutic Opportunities for Epigenetic Drugs?
Authors: Theys Claudia , Lauwers Dorien , Perez-Novo Claudina , Vanden Berghe Wim
Published: November 2022

Nonalcoholic fatty liver disease (NAFLD) is a growing epidemic and the most common cause of chronic liver disease worldwide. It consists of a spectrum of liver disorders ranging from simple steatosis to NASH which predisposes patients to further fibrosis, cirrhosis and even hepatocarcinoma. Despite much research, an approved treatment is still lacking. Finding new therapeutic targets has therefore been a main priority. Known as a main regulator of the lipid metabolism and highly expressed in the liver, the nuclear receptor peroxisome proliferator-activated receptor-α (PPARα) has been identified as an attractive therapeutic target. Since its expression is silenced by DNA hypermethylation in NAFLD patients, many research strategies have aimed to restore the expression of PPARα and its target genes involved in lipid metabolism. Although previously tested PPARα agonists did not ameliorate the disease, current research has shown that PPARα also interacts and regulates epigenetic DNMT1, JMJD3, TET and SIRT1 enzymes. Moreover, there is a growing body of evidence suggesting the orchestrating role of epigenetics in the development and progression of NAFLD. Therefore, current therapeutic strategies are shifting more towards epigenetic drugs. This review provides a concise overview of the epigenetic regulation of NAFLD with a focus on PPARα regulation and highlights recently identified epigenetic interaction partners of PPARα.
Design and Development of a qPCR-Based Mitochondrial Analysis Workflow for Medical Laboratories
Authors: Krause Thomas , Glau Laura , Jolkver Elena , Leonardi-Essmann Fernando , Kevitt Paul Mc , Kramer Michael , Hemmje Matthias
Published: November 2022

Mitochondrial DNA (mtDNA) damage is closely associated with typical diseases of aging, such as Alzheimer’s or Parkinson’s disease, and other health conditions, such as infertility. This damage manifests in reduced mitochondrial copy number and deletion mutations in mtDNA. Consequently, the analysis of mitochondrial damage by determining the parameters copy number and deletion ratio using quantitative real-time PCR (qPCR) is of interest for clinical diagnostics. To bring the findings from research into laboratory practice, a suitable and reliable process is needed, which must be thoroughly validated. This process includes the software used for the analysis, which must meet extensive regulatory and process requirements. Existing software does not adequately implement the requirements of laboratories and, in particular, does not provide direct support for the calculation of the aforementioned mtDNA parameters. The paper discusses the development of a new software-based analysis workflow that is designed specifically for laboratories to help with the calculation of mtDNA parameters. The software was developed using the User-Centered Design method and is based on the recently introduced prototype, “PlateFlow”. Initial user tests provide positive feedback. In the future, this workflow could form the basis for validations of mitochondrial tests in medical laboratories.
Recent Advances in the Roles of MicroRNA and MicroRNA-Based Diagnosis in Neurodegenerative Diseases
Authors: Zhang Juan , Chen Zhu , Chen Hui , Deng Yan , Li Song , Jin Lian
Published: November 2022

Neurodegenerative diseases manifest as progressive loss of neuronal structures and their myelin sheaths and lead to substantial morbidity and mortality, especially in the elderly. Despite extensive research, there are few effective treatment options for the diseases. MicroRNAs have been shown to be involved in the developmental processes of the central nervous system. Mounting evidence suggest they play an important role in the development of neurodegenerative diseases such as Alzheimer’s disease and Parkinson’s disease. However, there are few reviews regarding the roles of miRNAs in neurodegenerative diseases. This review summarizes the recent developments in the roles of microRNAs in neurodegenerative diseases and presents the application of microRNA-based methods in the early diagnosis of these diseases.
Modeling and Investigation of an Industrial Dehydration and Hydrocarbon-Removal Process by Temperature Swing Adsorption
Authors: Ghasemzadeh Hossein , Mehrpooya Mehdi , Pourfayaz Fathollah , Jarrahian Azad , Ganjali Mohammad Reza
Published: November 2022

In this study, a water- and heavy hydrocarbon-removal process of a natural gas refinery currently in operation using the temperature swing adsorption method is modeled and investigated. The aim of this process is to decrease the hydrocarbon dew point to −10 °C and diminish the water content of the gas to about 0.1 ppm. This unit consists of four beds with two layers in which two beds are in the adsorption state, while the others are kept in the regeneration state. The gas composition and the bed specification are obtained from the available data from the refinery. The Ergun equation is considered for the pressure drop calculation. The results show that the developed model can predict the outputs with good accuracy. Sensitivity analysis of operating condition parameters such as temperature, pressure, and regeneration gas flowrate are carried out. Analysis of the regeneration temperature proved that temperature reduction from 268 °C to 210 °C can improve recovery of the heavy components. In addition, the regeneration gas flow rate can be reduced to about 0.4 kmole·s−1 as an optimum value. Moreover, 303 to 310 °C is the optimum range for the feed temperature. Due to the presence of the air cooler in the upstream process, and according to the ambient air temperature, feed temperature can be decreased to obtain better results.
Ferumoxytol-Enhanced Cardiac Magnetic Resonance Angiography and 4D Flow: Safety and Utility in Pediatric and Adult Congenital Heart Disease
Authors: Renella Pierangelo , Li Jennifer , Prosper Ashley E. , Finn J. Paul , Nguyen Kim-Lien
Published: November 2022

Cardiac magnetic resonance imaging and angiography have a crucial role in the diagnostic evaluation and follow up of pediatric and adult patients with congenital heart disease. Although much of the information required of advanced imaging studies can be provided by standard gadolinium-enhanced magnetic resonance imaging, the limitations of precise bolus timing, long scan duration, complex imaging protocols, and the need to image small structures limit more widespread use of this modality. Recent experience with off-label diagnostic use of ferumoxytol has helped to mitigate some of these barriers. Approved by the U.S. FDA for intravenous treatment of anemia, ferumoxytol is an ultrasmall superparamagnetic iron oxide nanoparticle that has a long blood pool residence time and high relaxivity. Once metabolized by macrophages, the iron core is incorporated into the reticuloendothelial system. In this work, we aim to summarize the evolution of ferumoxytol-enhanced cardiovascular magnetic resonance imaging and angiography and highlight its many applications for congenital heart disease.
For the Parent, by the Parent: Creating a Program to Empower Parents of Refugee Background in Canada Using Novel Participatory Approaches
Authors: Benipal Pardeep Kaur , Ho Bernice , Kaukab Tanvir , Rashid Meb , Bowry Ashna , Yousafzai Aisha K. , Minhas Ripudaman Singh
Published: November 2022

Background: Families of refugee background have complex, multigenerational mental health and developmental needs that are not accounted for in current programming frameworks in Canada. Providing appropriate support services and educational resources that address the unique concerns of families of refugee background will allow for improved family cohesion and developmental outcomes for children. Parenting programs have been shown to be successful in improving parental stress, parental efficacy, and children’s mental health and well-being. This study gathers data about the experiences of caregivers of refugee background in order to develop a novel, multi-dimensional parenting program model using Community-Based Participatory Research (CBPR) principles. Methodology: This was a qualitative, CBPR study using a formative research framework. In-depth interviews (IDIs) were conducted with caregivers of refugee background and service providers that work closely with this population. Data were recorded, transcribed, and coded using deductive and inductive coding methods by two independent coders. Results: A total of 20 IDIs were conducted (7 caregivers and 13 service providers). The main topics that were identified to be incorporated into the program include: features of child development, how to address resettlement issues, child advocacy, and parenting after resettlement. Participants felt that tackling language barriers, addressing the overlapping responsibilities of caregivers attending the sessions, providing incentives, increasing awareness of the program, and using an anti-racist and anti-oppressive approach was key to the program’s success. Participants emphasized the need for trauma-informed mental health supports within the program model. Conclusion: This study describes the key considerations for a novel parenting program for families of refugee background, by engaging them as key stakeholders in the program design process. Future iterations of this project would involve a pilot and evaluation of the program.
Acute Appendicitis as the Initial Presentation of Kawasaki Disease Shock Syndrome in Children
Authors: Chang Yuan-Hao , Lin Chien-Yu , Liu Lu-Hang , Huang Fu-Huan , Cheng Yu-Jyun
Published: November 2022

Kawasaki disease shock syndrome (KDSS) is a severe form of Kawasaki disease (KD). The hemodynamic instability and atypical manifestations of this syndrome delay its correct diagnosis and timely treatment. We report here an eight-year-old girl who presented with appendicitis. Her fever persisted after appendectomy, accompanied by hemodynamic instability. The girl was diagnosed with KDSS. Intravenous immunoglobulin (IVIG) and corticosteroids were administered. Her symptoms resolved. She had left coronary artery dilatation, which resolved three months later. We also reviewed two other possible cases identified as KDSS with appendicitis. These cases have a more atypical clinical course, prolonged treatment, and a higher rate of IVIG resistance. Better awareness of KDSS is needed for early diagnosis and treatment in children experiencing prolonged fever after appendectomy.