bluuebunny/crossref_metadata_2025 huggingface dataset:
Integrating the exposome and one health approach to national health surveillance: an opportunity for Latin American countries in health preventive management
Authors: Matus Patricia , Urquidi Cinthya , Cárcamo Marcela , Vidal Veronica
Published: August 2024

The exposome approach, emphasizing lifelong environmental exposures, is a holistic framework exploring the intricate interplay between genetics and the environment in shaping health outcomes. Complementing this, the one health approach recognizes the interconnectedness of human and ecological health within a shared ecosystem, extending to planetary health, which encompasses the entire planet. Integrating Disease Surveillance Systems with exposome, one health, and planetary health signifies a paradigm shift in health management, fostering a comprehensive public health framework. This publication advocates for combining traditional health surveillance with exposome and one health/planetary health approach, proposing a three-step approach: ecological analysis, territorial intervention in identified issues, and an analytical phase for assessing interventions. Particularly relevant for Latin American countries facing a double burden of diseases, integrating the exposome into traditional health surveillance proves cost-effective by leveraging existing data and environmental measurements. In conclusion, the integration of exposome and one health approaches into traditional health surveillance presents a robust framework for monitoring population health, especially in regions like Latin America with complex health challenges. This innovative approach enables tailored interventions, disease outbreak predictions, and a holistic understanding of the intricate links between human health and the environment, offering substantial benefits for public health and disease prevention despite existing challenges.
Recommendations for clinical decision-making when offering exoskeletons for community use in individuals with spinal cord injury
Authors: Onate Derrick , Hogan Cassandra , Fitzgerald Kathryn , White Kevin T. , Tansey Keith
Published: August 2024

Approved in 2014 by the Food and Drug Administration (FDA) for use with a trained companion, personal powered exoskeletons (PPE) for individuals with spinal cord injury (SCI) provide an opportunity for the appropriate candidate to ambulate in their home and community. As an adjunct to wheeled mobility, PPE use allows those individuals who desire to ambulate the opportunity to experience the potential physiological and psychosocial benefits of assisted walking outside of a rehabilitation setting. There exists, however, a knowledge gap for clinicians regarding appropriate candidate selection for use, as well as who might benefit from ambulating with a PPE. The purpose of this paper is to provide guidance for clinicians working with individuals living with SCI by outlining an expert consensus for a PPE decision-making algorithm, as well as a discussion of potential physiological and psychosocial benefits from PPE use based on early evidence in publication.
How Healthy Eating Can Help Fight Parkinson’s Disease
Authors: Raimundo Ana Filipa , Pita Carlos , Silva Inês P. , dos Santos Cláudia Nunes , Loncarevic-Vasiljkovic Natasa
Published: August 2024

Our everyday lives depend on the cooperation of about 100 billion brain cells called neurons. Neurons are vital for every action, from breathing to moving to thinking. Regardless of the complexity and importance of the brain, it is still susceptible to diseases called neurodegenerative disorders. These terrible illnesses involve the death of neurons in particular parts of the brain. There are many neurodegenerative diseases, however, Parkinson’s disease is among the most common and causes the most severe movement problems. Although a lot has been learned about Parkinson’s disease, there is still no cure. Recently, studies have shown that small molecules found in many fruits and vegetables might help protect the brain from neurodegenerative disorders.
Development of a TaqMan-based multiplex real-time PCR for simultaneous detection of porcine epidemic diarrhea virus, Brachyspira hyodysenteriae, and Lawsonia intracellularis
Authors: Ren Jing , Li Fujun , Yu Xue , Li Yang , Li Meng , Sha Yujie , Li Xiaowen
Published: August 2024

Introduction

PEDV, Brachyspira hyodysenteriae, and Lawsonia intracellularis, are highly contagious diarrheal pathogens that have caused significant harm to the global swine industry. Co-infections with multiple pathogens are common, making it challenging to identify the actual causative agents depending only on clinical information. It is crucial to develop a reliable method to simultaneously detect and differentiate these pathogens.

Methods

Based on the conserved regions of the M gene of PEDV, NADH oxidase gene of B. hyodysenteriae, and the 16S rDNA gene of L. intracellularis, specific probes and primers for the multiplex real-time PCR assay were designed. The concentrations of primers and probes were optimized using a matrix method.

Results

The approach demonstrated high specificity and no cross-reactivity with major pathogens related to diarrheal diseases. It showed high sensitivity with a detection limit of 10 copies/μL for B. hyodysenteriae and L. intracellularis, and 100 copies/μL for PEDV, respectively. It also demonstrated high reproducibility and stability with low coefficients of variation. Results from the multiplex real-time PCR method were in complete agreement with the commercial singleplex real-time PCR kit for detecting PEDV, B. hyodysenteriae and L. intracellularis. Clinical data revealed single infection rates of 31.46% for PEDV, 58.43% for B. hyodysenteriae, and 98.6% for L. intracellularis. The co-infection rates were 16.85% for PEDV + B. hyodysenteriae, 31.46% for PEDV + L. intracellularis, 57.86% for B. hyodysenteriae + L. intracellularis, and 16.85% for PEDV + B. hyodysenteriae + L. intracellularis, respectively.

Discussion

The new multiplex real-time PCR method can simultaneously differentiate PEDV, B. hyodysenteriae and L. intracellularis, making it a valuable diagnostic tool for preventing and controlling infectious diseases, as well as aiding in epidemiological investigations.
Generation of an infectious cDNA clone for NADC30-like PRRSV
Authors: Qiao Yang-Yang , Wang Hai-Ming , Lu Hui , Wang Yong-Juan , Zhang Wei , Gu Hao , Cai Xue-Hui , Xu Qin-Se , Chen Zhang-Yan , Tang Yan-Dong
Published: August 2024

The porcine reproductive and respiratory syndrome virus (PRRSV) is a highly significant infectious disease that poses a substantial threat to the global pig industry. In recent years, the NADC30-like strain has gradually emerged as prevalent in China, causing a profound impact on the country’s pig farming industry. Therefore, it is important to conduct an in-depth study on the characteristics and gene functions of the NADC30-like strain. An infectious cDNA clone is an indispensable tool for investigating the functions of viral genes. In this current study, we successfully isolated a NADC30-like strain and constructed its full-length infectious cDNA clone. The utilization of this clone will facilitate our investigation into the viral replication, pathogenesis, and immune response associated with the PRRSV NADC30-like strain.
The Effect of Motivation on the Behavioral Intention to Protect Industrial Techniques of High-Tech Firms’ Employees
Authors: Lee Sangwoo , Kim Boyoung , Ivan Ureta Vaquero
Published: August 2024

This study defines the intrinsic and extrinsic motivational factors that influence the prevention of industrial technology leakage by high-tech company employees. It also investigates how these factors affect the employees’ intention to prevent leakage. Based on the TPB (theory of planned behavior), this study analyzes the relationship between “attitude toward behavior”, “subjective norm”, and “perceived behavioral control”, which in turn influences the behavioral intention to prevent such leakage. Specifically, an online survey was conducted among office workers in South Korea’s high-tech industry. A total of 200 questionnaires were collected and analyzed. As the analysis results show, intrinsic motivation has a positive effect on attitude toward behavior, subjective norms, and perceived behavioral control. Extrinsic motivation has a positive effect on subjective norms and perceived behavioral control but a negative effect on attitudes toward behavior. This study also proved, based on the TPB, that the three variables impact the behavioral intention to prevent technology leakage. These results confirm that, in the high-tech sector, where employees are highly specialized and autonomous, technical security behaviors are primarily influenced by individual professional ethics and judgment rather than by organizational regulation or extrinsic motivation.
Design and Experiment of Planting Mechanism of Automatic Transplanter for Densely Planted Vegetables
Authors: Shi Jiawei , Hu Jianping , Li Jing , Liu Wei , Yue Rencai , Zhang Tengfei , Yao Mengjiao
Published: August 2024

The planting mechanism of existing transplanters cannot meet the agronomic requirements of planting densely planted vegetables with multiple rows, small plant spacing, and small row spacing. In order to solve this current problem, an eight-row duckbill planting mechanism driven by a motor and a cylinder was designed. According to the agronomic guidance and mechanism design requirements for transplanting densely planted vegetable seedlings, this paper analyzes the working principle of the planting mechanism, establishes its kinematic theoretical model, and determines the structural parameters of the driving device and opening and closing device in the planting mechanism. Aimed at the problem of large planting resistance when eight-row planting end effectors of the planting mechanism are planting at the same time, based on the existing research, three duckbill planting end effectors with double incisions, four incisions, and conical structures were selected, and the planting process was simulated using an EDEM 2022-RecurDyn 2024 coupling simulation. The single-factor analysis method and the interactive factor Box–Behnken response surface analysis method were used. It is concluded that the duckbill end effector with double incisions has the smallest planting resistance, and the rationality of the mechanism design is preliminarily verified. A planting resistance measurement platform was built based on the STM32 platform and HX711 module, and a planting resistance test of the duckbill planting end effector was carried out to verify the correctness of the planting mechanism simulation results. The planting mechanism performance test was carried out, and the test results showed that the planting qualification rate of the prototype reached 96.62%, the planting spacing variation coefficient was only 3.55%, and the planting efficiency reached about 7135 plants/h, which met the agronomic requirements of small plant spacing and small row spacing for densely planted vegetables and verified the feasibility and practicality of the planting mechanism.
Effects of Cryoprotectant Concentration and Exposure Time during Vitrification of Immature Pre-Pubertal Lamb Cumulus–Oocyte Complexes on Nuclear and Cytoplasmic Maturation
Authors: Temerario Letizia , Martino Nicola Antonio , Bennink Monika , de Wit Agnes , Hiemstra Sipke Joost , Dell’Aquila Maria Elena , Lamy Julie
Published: August 2024

Oocyte vitrification allows for the storing of endangered breed female gametes. Cryoprotectant (CPA) concentration and exposure time should ensure cell protection with minimal toxicity. In the present study, a high concentration-rapid exposure (HC-RE) and a low concentration-slow exposure (LC-SE) vitrification protocol, using dimethyl sulfoxide (DMSO) and ethylene glycol (EG) as permeating CPAs, were evaluated on meiotic competence and bioenergetic-oxidative status of pre-pubertal lamb immature COCs after in vitro maturation (IVM). For each protocol, COCs vitrified through a traditional protocol and fresh ones were used as controls. Both protocols allowed COC morphology preservation after vitrification-warming (V-W) and cumulus expansion after IVM. The maturation rate (7% and 14%) was comparable to the vitrified control (13% and 21%) but not satisfactory compared to fresh ones (58% and 64%; p < 0.001). The rate of mature oocytes displaying a perinuclear/subcortical (P/S) mitochondrial distribution pattern, an index of cytoplasmic maturity, was comparable between vitrified and fresh oocytes. The LC-SE vitrification protocol did not affect quantitative bioenergetic-oxidative parameters compared to both controls whereas HC-RE protocol significantly reduced intracellular reactive oxygen species (ROS) levels, indicating cell viability loss. In conclusion, to improve pre-pubertal lamb immature COC vitrification, the combination of low CPA concentrations with prolonged exposure time could be more promising to investigate further.
Multidrug-Resistant Staphylococcus aureus Colonizing Pigs and Farm Workers in Rio de Janeiro State, Brazil: Potential Interspecies Transmission of Livestock-Associated MRSA (LA-MRSA) ST398
Authors: Talim Joana , Martins Ianick , Messias Cassio , Sabino Hellen , Oliveira Laura , Pinto Tatiana , Albuquerque Julia , Cerqueira Aloysio , Dolores Ítalo , Moreira Beatriz , Silveira Renato , Neves Felipe , Rabello Renata
Published: August 2024

Multidrug-resistant (MDR) Staphylococcus aureus has been increasingly isolated from pigs and people in close contact with them, especially livestock-associated methicillin-resistant S. aureus (LA-MRSA). In this cross-sectional study, we investigated S. aureus colonization in pigs and farm workers, their resistance profile, and genetic background to estimate interspecies transmission potential within farms from Rio de Janeiro state, Brazil, between 2014 and 2019. We collected nasal swabs from 230 pigs and 27 workers from 16 and 10 farms, respectively. Five MDR strains were subjected to whole genome sequencing. Fourteen (6.1%) pigs and seven (25.9%) humans were colonized with S. aureus, mostly (64–71%) MDR strains. Resistance to clindamycin, erythromycin, penicillin, and tetracycline was the most common among the pig and human strains investigated. MDR strains shared several resistance genes [blaZ, dfrG, fexA, lsa(E), and tet(M)]. Pig and human strains recovered from the same farm shared the same genetic background and antimicrobial resistance profile. LA-MRSA ST398-SCCmecV-t011 was isolated from pigs in two farms and from a farm worker in one of them, suggesting interspecies transmission. The association between pig management practices and MDR S. aureus colonization might be investigated in additional studies.
Innovative Alignment-Based Method for Antiviral Peptide Prediction
Authors: de Llano García Daniela , Marrero-Ponce Yovani , Agüero-Chapin Guillermin , Ferri Francesc J. , Antunes Agostinho , Martinez-Rios Felix , Rodríguez Hortensia
Published: August 2024

Antiviral peptides (AVPs) represent a promising strategy for addressing the global challenges of viral infections and their growing resistances to traditional drugs. Lab-based AVP discovery methods are resource-intensive, highlighting the need for efficient computational alternatives. In this study, we developed five non-trained but supervised multi-query similarity search models (MQSSMs) integrated into the StarPep toolbox. Rigorous testing and validation across diverse AVP datasets confirmed the models’ robustness and reliability. The top-performing model, M13+, demonstrated impressive results, with an accuracy of 0.969 and a Matthew’s correlation coefficient of 0.71. To assess their competitiveness, the top five models were benchmarked against 14 publicly available machine-learning and deep-learning AVP predictors. The MQSSMs outperformed these predictors, highlighting their efficiency in terms of resource demand and public accessibility. Another significant achievement of this study is the creation of the most comprehensive dataset of antiviral sequences to date. In general, these results suggest that MQSSMs are promissory tools to develop good alignment-based models that can be successfully applied in the screening of large datasets for new AVP discovery.
Field Evaluation and Application of Intelligent Quality Control Systems
Authors: Kim Jin-Young , Cho Jin-woo , Lee Sung-Yeol
Published: August 2024

During road construction, the accuracy of compaction work is critical for the structural stability and maintenance of the road. Although the plate load test (PLT) is commonly used for quality inspections, it is impractical to test every section due to time and cost constraints. Therefore, simpler testing methods are being extensively developed. This study compared quality inspection results using the commonly used PLT, the relatively simple dynamic cone penetrometer test (DCPT), the lightweight deflectometer (LWD) test, and an intelligent quality control system equipped with accelerometer and global positioning system (GPS) sensors in intelligent compaction (IC) rollers. The results showed a strong correlation between the conventional tests (PLT, DCPT, and LWD) and the values obtained from the intelligent quality control system. The correlation analysis between the intelligent quality control system and PLT, LWDT, and DCPT yielded R-square values of 0.69, 0.91, and 0.95, respectively, indicating significantly high correlations. The implementation of intelligent quality management systems in earthwork construction projects will facilitate a thorough verification of the compaction quality throughout all construction segments, ensuring consistent compaction across the project. By enabling real-time data acquisition and analysis, these systems differ markedly from traditional methods, reducing the frequency and necessity of manual inspections. This approach not only streamlines construction processes, but also enhances operational efficiency. As a result, integrating these intelligent systems is anticipated to significantly increase productivity by optimizing the workflow and resource utilization in earthwork construction.
Detection and Segmentation of Mouth Region in Stereo Stream Using YOLOv6 and DeepLab v3+ Models for Computer-Aided Speech Diagnosis in Children
Authors: Sage Agata , Badura Pawel
Published: August 2024

This paper describes a multistage framework for face image analysis in computer-aided speech diagnosis and therapy. Multimodal data processing frameworks have become a significant factor in supporting speech disorders’ treatment. Synchronous and asynchronous remote speech therapy approaches can use audio and video analysis of articulation to deliver robust indicators of disordered speech. Accurate segmentation of articulators in video frames is a vital step in this agenda. We use a dedicated data acquisition system to capture the stereovision stream during speech therapy examination in children. Our goal is to detect and accurately segment four objects in the mouth area (lips, teeth, tongue, and whole mouth) during relaxed speech and speech therapy exercises. Our database contains 17,913 frames from 76 preschool children. We apply a sequence of procedures employing artificial intelligence. For detection, we train the YOLOv6 (you only look once) model to catch each of the three objects under consideration. Then, we prepare the DeepLab v3+ segmentation model in a semi-supervised training mode. As preparation of reliable expert annotations is exhausting in video labeling, we first train the network using weak labels produced by initial segmentation based on the distance-regularized level set evolution over fuzzified images. Next, we fine-tune the model using a portion of manual ground-truth delineations. Each stage is thoroughly assessed using the independent test subset. The lips are detected almost perfectly (average precision and F1 score of 0.999), whereas the segmentation Dice index exceeds 0.83 in each articulator, with a top result of 0.95 in the whole mouth.
Parameter Calibration and Verification of Elastoplastic Wet Sand Based on Attention-Retention Fusion Deep Learning Mechanism
Authors: Hu Zhicheng , Zhao Xianning , Zhang Junjie , Ba Sibo , Zhao Zifeng , Wang Xuelin
Published: August 2024

The discrete element method (DEM) is a vital numerical approach for analyzing the mechanical behavior of elastoplastic wet sand. However, parameter uncertainty persists within the mapping between constitutive relationships and inherent model parameters. We propose a Parameter calibration neural network based on Attention, Retention, and improved Transformer for Sequential data (PartsNet), which effectively captures the nonlinear mechanical behavior of wet sand and obtains the optimal parameter combination for the Edinburgh elasto-plastic adhesion constitutive model. Variational autoencoder-based principal component ordering is employed by PartsNet to reduce the high-dimensional dynamic response and extract critical parameters along with their weights. Gated recurrent units are combined with a novel sparse multi-head attention mechanism to process sequential data. The fusion information is delivered by residual multilayer perceptron, achieving the association between sequential response and model parameters. The errors in response data generated by calibrated parameters are quantified by PartsNet based on adaptive differentiation and Taylor expansion. Remarkable calibration capabilities are exhibited by PartsNet across six evaluation indicators, surpassing seven other deep learning approaches in the ablation test. The calibration accuracy of PartsNet reaches 91.29%, and MSE loss converges to 0.000934. The validation experiments and regression analysis confirmed the generalization capability of PartsNet in the calibration of wet sand. The improved sparse attention mechanism optimizes multi-head attention, resulting in a convergence speed of 21.25%. PartsNet contributes to modeling and simulating the precise mechanical properties of complex elastoplastic systems and offers valuable insights for diverse engineering applications.
Different Types of Entropy Measures for Type-2 Fuzzy Sets
Authors: Magdalena Luis , Torres-Blanc Carmen , Cubillo Susana , Martinez-Mateo Jesus
Published: August 2024

In this work, we consider De Luca and Termini’s notion of non-probabilistic entropy, and we extend some entropy-like measures of the degree of fuzziness to type-2 fuzzy sets. With this aim, we first study different entropy measures proposed in the frameworks of fuzzy, intuitionistic, and interval-valued fuzzy sets. Then, we propose three possible novel axiomatizations for entropy in type-2 fuzzy sets. The proposed types of entropy measures evaluate how much a type-2 fuzzy set is non-crisp, non-fuzzy, and non-interval-valued fuzzy. This can also be interpreted as how far a type-2 fuzzy set is from a crisp, fuzzy, or interval-valued fuzzy set. The present contribution is also novel, since we considered the interpretation of type-2 fuzzy sets that is closest to Zadeh’s original conception.
Structural Perspectives on Metal Dependent Roles of Ferric Uptake Regulator (Fur)
Authors: Kang Sung-Min , Kang Hoon-Seok , Chung Woo-Hyun , Kang Kyu-Tae , Kim Do-Hee
Published: August 2024

Iron is crucial for the metabolism and growth of most prokaryotic cells. The ferric uptake regulator (Fur) protein plays a central role in regulating iron homeostasis and metabolic processes in bacteria. It ensures the proper utilization of iron and the maintenance of cellular functions in response to environmental cues. Fur proteins are composed of an N-terminal DNA-binding domain (DBD) and a C-terminal dimerization domain (DD), typically existing as dimers in solution. Fur proteins have conserved metal-binding sites named S1, S2, and S3. Among them, site S2 serves as a regulatory site, and metal binding at S2 results in conformational changes. Additionally, as a transcriptional regulator, Fur specifically binds to a consensus DNA sequence called the Fur box. To elucidate the structural and functional properties of Fur proteins, various structures of metal- or DNA-bound Fur proteins or apo-Fur proteins have been determined. In this review, we focus on the structural properties of Fur proteins according to their ligand-bound state and the drug development strategies targeting Fur proteins. This information provides valuable insights for drug discovery.
Computational Methods to Predict Conformational B-Cell Epitopes
Authors: Carroll M. , Rosenbaum E. , Viswanathan R.
Published: August 2024

Accurate computational prediction of B-cell epitopes can greatly enhance biomedical research and rapidly advance efforts to develop therapeutics, monoclonal antibodies, vaccines, and immunodiagnostic reagents. Previous research efforts have primarily focused on the development of computational methods to predict linear epitopes rather than conformational epitopes; however, the latter is much more biologically predominant. Several conformational B-cell epitope prediction methods have recently been published, but their predictive performances are weak. Here, we present a review of the latest computational methods and assess their performances on a diverse test set of 29 non-redundant unbound antigen structures. Our results demonstrate that ISPIPab performs better than most methods and compares favorably with other recent antigen-specific methods. Finally, we suggest new strategies and opportunities to improve computational predictions of conformational B-cell epitopes.
Live Cell Monitoring of Phosphodiesterase Inhibition by Sulfonylurea Drugs
Authors: Berisha Filip , Blankenberg Stefan , Nikolaev Viacheslav O.
Published: August 2024

Sulfonylureas (SUs) are a class of antidiabetic drugs widely used in the management of diabetes mellitus type 2. They promote insulin secretion by inhibiting the ATP-sensitive potassium channel in pancreatic β-cells. Recently, the exchange protein directly activated by cAMP (Epac) was identified as a new class of target proteins of SUs that might contribute to their antidiabetic effect, through the activation of the Ras-like guanosine triphosphatase Rap1, which has been controversially discussed. We used human embryonic kidney (HEK) 293 cells expressing genetic constructs of various Förster resonance energy transfer (FRET)-based biosensors containing different versions of Epac1 and Epac2 isoforms, alone or fused to different phosphodiesterases (PDEs), to monitor SU-induced conformational changes in Epac or direct PDE inhibition in real time. We show that SUs can both induce conformational changes in the Epac2 protein but not in Epac1, and directly inhibit the PDE3 and PDE4 families, thereby increasing cAMP levels in the direct vicinity of these PDEs. Furthermore, we demonstrate that the binding site of SUs in Epac2 is distinct from that of cAMP and is located between the amino acids E443 and E460. Using biochemical assays, we could also show that tolbutamide can inhibit PDE activity through an allosteric mechanism. Therefore, the cAMP-elevating capacity due to allosteric PDE inhibition in addition to direct Epac activation may contribute to the therapeutic effects of SU drugs.
The Function of H2A Histone Variants and Their Roles in Diseases
Authors: Yin Xuemin , Zeng Dong , Liao Yingjun , Tang Chengyuan , Li Ying
Published: August 2024

Epigenetic regulation, which is characterized by reversible and heritable genetic alterations without changing DNA sequences, has recently been increasingly studied in diseases. Histone variant regulation is an essential component of epigenetic regulation. The substitution of canonical histones by histone variants profoundly alters the local chromatin structure and modulates DNA accessibility to regulatory factors, thereby exerting a pivotal influence on gene regulation and DNA damage repair. Histone H2A variants, mainly including H2A.Z, H2A.B, macroH2A, and H2A.X, are the most abundant identified variants among all histone variants with the greatest sequence diversity. Harboring varied chromatin occupancy and structures, histone H2A variants perform distinct functions in gene transcription and DNA damage repair. They are implicated in multiple pathophysiological mechanisms and the emergence of different illnesses. Cancer, embryonic development abnormalities, neurological diseases, metabolic diseases, and heart diseases have all been linked to histone H2A variant alterations. This review focuses on the functions of H2A histone variants in mammals, including H2A.Z, H2A.B, macroH2A, and H2A.X, and their current roles in various diseases.
Exploring a Novel Role of Glycerol Kinase 1 in Prostate Cancer PC-3 Cells
Authors: Park Bobae , Kim Sang-Hun , Yu Sun-Nyoung , Kim Kwang-Youn , Jeon Hoyeon , Ahn Soon-Cheol
Published: August 2024

Clinically, prostate cancer is infamous for its histological and molecular heterogeneity, which causes great challenges to pinpoint therapy and pharmaceutical development. To overcome these difficulties, researchers are focusing on modulating tumor microenvironment and immune responses in addition to genetic alteration and epigenetic regulation. Here, we aimed to identify potential biomarkers or modulators of prostate cancer by investigating genes specifically altered in prostate cancer cells treated with established anti-cancer agents. Glycerol kinase 1 (GK1) is phosphotransferase encoded on the X chromosome, is associated with the synthesis of triglycerides and glycerophospholipids, and has been mainly studied for X-linked metabolic disorder GK deficiency (GKD). Interestingly, our DNA microarray analysis showed that several anti-cancer agents highly induced the expression of GK1, especially GK1a and GK1b isoforms, in human prostate cancer PC-3 cells. To elucidate the relationship between GK1 and cancer cell death, a human GK1b-specific expression vector was constructed and transfected into the PC-3 cells. Surprisingly, GK1b overexpression dramatically reduced cell viability and significantly accelerated apoptotic cell death. These findings suggest that GK1b may serve as a promising modulator and biomarker of cell death in prostate cancer, offering potential avenues for therapeutic intervention.
Thermal Performance of the Building Envelope: Original Methods and Advanced Solutions
Authors: Evola Gianpiero , Lucchi Elena
Published: August 2024

In the European Union, buildings are responsible for 40% of the final energy demand and approximately 36% of greenhouse gas emissions [...]
The Architectural Design Strategies That Promote Attention to Foster Mindfulness: A Systematic Review, Content Analysis and Meta-Analysis
Authors: Thampanichwat Chaniporn , Wongvorachan Tarid , Bunyarittikit Suphat , Chunhajinda Pornteera , Phaibulputhipong Prima , Wongmahasiri Rungroj
Published: August 2024

Attention is a pivotal component and a central vehicle of mindfulness, a psychological factor improving mental health. Despite architecture’s potential to encourage attention and mindfulness, there is still a research gap. This study aimed to investigate architectural design strategies that promotes attention in order to foster mindfulness. The research was carried out in three primary stages. The first step entailed conducting a systematic review by searching publications related to architecture that promotes attention from Scopus in February 2024. After considering the suitability and accessibility, 32 articles were included. No studies were found to have investigated the field of enhancing mindfulness. The second step utilized content analysis to decode the selected articles using a framework developed from literature reviews. All three coders decoded the data independently, allowing the main researcher to compile it into the final dataset. Finally, the data underwent Python meta-analysis for word frequency and association. The result revealed certain qualities that help achieve attention through architecture. The architectural atmosphere is most effective when it features natural forms and spaces that evoke a sense of enclosure. The lighting should emphasize natural light and uniformity, whereas the sound designs primarily concern acoustics, ambient, and noises, with controlled weather emphasizing air aspects. The building should utilize natural materials and incorporate object elements; the facade and entrance are particularly crucial components. Moreover, the colors of brick and green and views encompassing gardens and vegetation are among the qualities mentioned. Based on the analysis, the material, view, and color features were most congruent with the biophilic design concept. All these factors are expected to foster mindfulness, thereby improving mental health.
The Diagnostic Pathway of Hirschsprung’s Disease in Paediatric Patients: A Single-Centre Experience
Authors: Budzanowski Annita , Geoghegan Niamh , Macdonald Alexander , Choudhry Muhammad
Published: August 2024

Background: The presenting symptoms of patients with Hirschsprung’s disease (HD) are a failure to pass meconium, abdominal distension, and bilious vomiting. The gold standard diagnosis is a rectal biopsy to confirm aganglionosis. The aim of our study was to describe the diagnostic pathway of Hirschsprung’s disease at our institution and document the indication for a rectal biopsy. Methods: We have performed a prospective collection of all patients who underwent a rectal biopsy to exclude HD from December 2022 until September 2023 including. The following data were collected: patient’s age, presenting symptoms, type of biopsy, failure rate, complications, and histopathological results. Results: We identified 33 patients who underwent 34 rectal biopsies at 0.6 years of age. A total of 17 patients had a rectal suction biopsy (RSB), and 17 patients underwent a partial thickness under general anaesthesia (GA). 1/17 (6%) patients had an inconclusive RSB and subsequently underwent a biopsy under GA. Constipation and chronic abdominal distension plus vomiting were the most common presenting symptoms throughout all ages. Five patients (15%) had a rectal biopsy that was positive for HD. Conclusion: A protocolised approach to the assessment of infants and children with suspected HD ensures the appropriate utilisation of invasive procedures such as biopsy.
Recovery of Zinc and Rhenium for the Production of Zinc Perrhenates
Authors: Leszczyńska-Sejda Katarzyna , Malarz Joanna , Kopyto Dorota , Goc Karolina , Grzybek Alicja , Ciszewski Mateusz , Palmowski Arkadiusz , Benke Grzegorz , Pianowska Karolina
Published: August 2024

This study outlines findings from an investigation into the development of a hydrometallurgical process for manufacturing various forms of zinc perrhenate, entirely from waste from recycling and from the Zn–Pb industry. Scraps of Re-bearing Ni-based superalloys and acidic waste, circulating zinc solutions generated during the production of Zn by the electrolytic method and which contain >45 g/dm3 of Zn, Na, Mn, and Mg, were used in the research. In the publication, the conditions for the production of three types of zinc perrhenate, i.e., Zn(ReO4)2·4H2O, Zn(ReO4)2, and Zn(ReO4)2·2H2O, are presented. As a result of the analysis of the obtained results, it was concluded that to obtain the above-mentioned forms of zinc perrhenate, zinc carbonate can be used, precipitated from acidic, waste, and multi-component solutions after their prior neutralization to pH 4.0 and partial purification from Mn, Mg, and Na using metallurgical zinc oxide. Zinc carbonate should be precipitated using Na2CO3 at pH 6.3 and subsequently purified from other impurities, i.e., Mg, Na, and Mn, using aqueous ammonia solutions. As a result, zinc carbonate was obtained, which was used in a reaction with an aqueous solution of HReO4 to produce zinc perrhenate. The precipitated forms of Zn(ReO4)2 were obtained by appropriately drying the crude and hydrated Zn(ReO4)2 to obtain its tetrahydrate, dihydrate, and anhydrous forms, respectively, using drying temperatures of 55, 135, and 185 °C. The developed technology has been submitted for a patent and is an example of a technology founded on the principles of sustainable development, with a particular emphasis on the minimalization of loss of rhenium and zinc at all stages of its realization.
Does an Autoimmune Disorder Following Ovarian Cancer Diagnosis Affect Prognosis?
Authors: Fröhlich Anaïs , Welter JoEllen , Witzel Isabell , Voppichler Julia , Fehr Mathias K.
Published: August 2024

We investigated whether developing an autoimmune disorder (AID) following a high-grade epithelial ovarian cancer diagnosis improves overall survival. This retrospective study included data from women treated for high-grade serous, endometrioid, or transitional cell ovarian, fallopian tube, or peritoneal cancer FIGO stage III or IV at a Swiss cantonal gynecological cancer center (2008–2023). We used Kaplan–Meier estimates and the Cox proportional hazards model using time-varying covariates for the survival function estimation. In all, 9 of 128 patients developed an AID following a cancer diagnosis. The median time from cancer diagnosis to AID was 2 years (IQR 2–5). These women survived for a median of 3031 days (IQR 1765–3963) versus 972 days (IQR 568–1819) for those who did not develop an AID (p = 0.001). The median overall survival of nine women with a pre-existing AID was 1093 days (IQR 716–1705), similar to those who never had an AID. The multivariate analyses showed older age (p = 0.003, HR 1.04, 95% CI 1.013–1.064) was associated with a poorer prognosis, and developing an AID after a cancer diagnosis was associated with longer survival (p = 0.033, HR 0.113, 95% CI 0.015–0.837). Clinical manifestations of autoimmune disorders following ovarian cancer diagnoses were associated with better overall survival (8 versus 2.7 years), indicating an overactive immune response may improve cancer control.
Enhancing Precision in HIV Treatment: Validation of a Robust Next-Generation Sequencing System for Drug Resistance Mutation Analysis
Authors: Vashisht Ashutosh , Mondal Ashis K. , Vashisht Vishakha , Ananth Sudha , Alptekin Ahmet , Jones Kimya , Farmaha Jaspreet K. , Kolhe Ravindra
Published: August 2024

Background: Multidrug-resistant HIV strains challenge treatment efficacy and increase mortality rates. Next-generation sequencing (NGS) technology swiftly detects variants, facilitating personalized antiretroviral therapy. Aim: This study aimed to validate the Vela Diagnostics NGS platform for HIV drug resistance mutation analysis, rigorously assessed with clinical samples and CAP proficiency testing controls previously analyzed by Sanger sequencing. Method: The experimental approach involved the following: RNA extraction from clinical specimens, reverse transcription polymerase chain reaction (RT-PCR) utilizing the Sentosa SX 101 platform, library preparation with the Sentosa SQ HIV Genotyping Assay, template preparation, sequencing using the Sentosa SQ301 instrument, and subsequent data analysis employing the Sentosa SQ Suite and SQ Reporter software. Drug resistance profiles were interpreted using the Stanford HIV Drug Resistance Database (HIVdb) with the HXB2 reference sequence. Results: The Vela NGS system successfully identified a comprehensive array of drug resistance mutations across the tested samples: 28 nucleoside reverse transcriptase inhibitors (NRTI), 25 non-nucleoside reverse transcriptase inhibitors (NNRTI), 25 protease inhibitors (PI), and 10 integrase gene-specific variants. Dilution experiments further validated the system’s sensitivity, detecting drug resistance mutations even at viral loads lower than the recommended threshold (1000 copies/mL) set by Vela Diagnostics. Scope: This study underscores the validation and clinical applicability of the Vela NGS system, and its implementation may offer clinicians enhanced precision in therapeutic decision-making for individuals living with HIV.
Safety, Identity, Attitude, Cognition, and Capability: The ‘SIACC’ Framework of Early Childhood AI Literacy
Authors: Luo Wenwei , He Huihua , Gao Minqi , Li Hui
Published: August 2024

With the rapid advancement of Artificial Intelligence (AI) in early childhood education (ECE), young children face the challenge of learning to use AI ethically and appropriately. Developing AI education programs requires an age- and culturally-appropriate AI literacy framework. This study addresses this fundamental gap by creating a Chinese framework for early childhood AI literacy through an expert interview study with a grounded theory approach. Seven Chinese experts, including ECE and AI professors, kindergarten principals, and Directors of ECE Information Departments, were purposely sampled and interviewed, representing scholars, policymakers, and practitioners. The synthesis of the transcribed evidence generated five dimensions of young children’s AI literacy, namely Safety, Identity, Attitude, Cognition, and Capability, collectively forming a holistic framework titled the ‘SIACC’ framework. The Chinese definition of early childhood AI literacy was also reported. This study introduces the Chinese framework of AI literacy and provides a scientific basis for policymakers to establish AI literacy standards for young children. Additionally, it offers a conceptual structure for developing systematic indicators and scales within AI literacy in ECE.
Pure Question-Based Learning
Authors: Bälter Olle , Glassey Richard , Jemstedt Andreas , Bosk Daniel
Published: August 2024

We have evaluated a new pedagogical approach, pure question-based learning, or rather, a modern, digitized version of a really old approach: the Socratic method of learning. The pedagogical approach was evaluated and improved using a design-based research methodology. An online course was developed with pure question-based learning to explain its predecessor: question-based learning. The course was successively taken by students, researchers, and practitioners, and discussed in four group seminars. Feedback from each iteration was integrated into the next version and the course is still in use, see link below. Results from the design-based research process were positive (n≈78 participants, over four iterations) with the main negative results coming from the unfamiliarity of the format and feelings of exam-like stress during the first encounter. While pure question-based learning is new, it builds upon well-tested pedagogical methods. The method has several potential advantages: learning can be broken down into smaller modules, there is less passive learning for the students, less learning material needs to be created and AI could be used for this creation.
Kidney Tumor Segmentation Based on DWR-SegFormer
Authors: Deng Yani , Liu Xin , Shao Lianhe , Wang Kai , Wang Xihan , Gao Quanli
Published: August 2024

Kidney cancer is a malignant tumor with a high mortality rate. The accurate segmentation of tumors from computed tomography (CT) scans can assist physicians in clinical diagnosis. We introduced a new segmentation network called DWR-SegFormer to address the challenge of accurately segmenting kidney tumors in CT images. The method involved binarizing the label maps of clear cell renal cell carcinoma and papillary renal cell carcinoma CT images for identification, and the cancer lesion area was obtained by the label so that the model could accurately identify the area and enhance the feature extraction ability. Secondly, an optimized segmentation model combining a DWR attention mechanism and SegFormer network was constructed. MiT-B0 was used as the encoder of the model to establish long-distance feature dependencies and effectively extract feature information at different resolutions. The decoder with a multi-branch DWR module was implemented to utilize multi-scale feature information effectively and enhance segmentation accuracy. Comparing the experimental results with other existing models shows that the model significantly outperformed the comparison methods in all evaluation metrics on the CT image dataset of clear cell renal cancer. Furthermore, the experimental findings highlight the robustness of the proposed model across other datasets.
Research into the Correlation between Carbon Emissions, Foreign Energy Investment, and China’s Financial Advancement
Authors: Mi Jialong
Published: August 2024

Carbon dioxide emissions are the primary driver of global climate change. This study aims to analyze the relationship between inward foreign direct investment in the energy sector and CO2 emissions in China versus other countries. For this, the co-integration methods were used. The results suggested that China should encourage the adoption of green technologies in order to reduce CO2 emissions and enforce strict environmental laws. Another necessary step is to stop the licensing of polluting industries that emit high amounts of CO2 emissions. The present findings can be used to develop state programs for environmental protection. Future research can examine the relationship of FDI in the energy sector with indicators other than pollution with CO2 emissions, for example, with the consumption of renewable energy sources.
Comparison of Pore Structure Characteristics of Shale-Oil and Tight-Oil Reservoirs in the Fengcheng Formation in Mahu Sag
Authors: Liu Guoyong , Tang Yong , Liu Kouqi , Liu Zuoqiang , Zhu Tao , Zou Yang , Liu Xinlong , Yang Sen , Xie An
Published: August 2024

Despite the abundance of shale-oil and tight-oil reserves in the Fengcheng Formation within the Mahu Sag, exploration and development efforts for both types of reservoir are still in their early stages. A comprehensive examination and comparison of the pore structures of these reservoirs can establish rational classification and evaluation criteria. However, there is a dearth of comparative analyses focusing on the pore structures of shale-oil and tight-oil reservoirs within the Fengcheng Formation. This study addresses this gap by systematically analyzing and comparing the pore structures of these reservoirs using various techniques such as X-ray diffraction (XRD), scanning electron microscopy (SEM), low-temperature nitrogen adsorption, and mercury intrusion capillary pressure experiments (MICP). The results show that the shale oil within the Fengcheng Formation exhibits a higher content of carbonic acid compared to the tight-oil samples. Furthermore, it demonstrates smaller displacement pressure and median pressure, a larger sorting coefficient, and superior permeability in contrast to tight oil. Notably, the shale oil within the Fengcheng Formation is characterized by abundant striated layer structures and micro-fractures, which significantly contribute to the microstructural disparities between shale-oil and tight-oil reservoirs. These differences in microstructures between shale oil and tight oil within the Fengcheng Formation in the Mahu Sag region delineate distinct criteria for evaluating sweet spots in shale-oil and tight-oil reservoirs.
Predicting Energy Production in Renewable Energy Power Plants Using Deep Learning
Authors: Karakan Abdil
Published: August 2024

It is very important to analyze and forecast energy production for investments in renewable energy resources. In this study, the energy production of wind and solar power plants, which are among the leading renewable energy sources, was estimated using deep learning. For a solar power plant, three different solar power plants with 1MW installed power were examined. Three-year energy production data of power plants were taken. These data were used with the deep learning method long short-term memory (LSTM) and seasonal autoregressive moving average (SARIMA). Results were obtained for each dataset; they were subjected to five different (MSE, RMSE, NMSE, MAE, and MAPE) error performance measurement systems. In the LSTM model, the highest accuracy rate was 81% and the lowest accuracy rate was 59%. In the SARIMA model, the highest accuracy rate was 66% and the lowest accuracy rate was 41%. As for wind energy, wind speeds in two different places were estimated. Wind speed data were taken from meteorological stations. Datasets were tested with MAPE, R2, and RMSE error performance measurement systems. LSTM, GRU, CNN-LSTM, CNN-RNN, LSTM-GRU, and CNN-GRU deep learning methods were used in this study. The CNN-GRU model achieved a maximum accuracy of 99.81% in wind energy forecasting.