bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploration of the potentially common pathogenic mechanisms in COVID-19 and silicosis using bioinformatics and system biology
Authors: Tian Yunze , Yu Beibei , Zhang Yongfeng , Zhang Sanpeng , lv Boqiang , Gong Shouping , Li Jianzhong 
Published: January 2023

Abstract

Silicosis is an occupational lung disease that is common worldwide. In recent years, coronavirus disease 2019 (COVID-19) has presented daunting challenges to public healthcare systems globally. However, inter-relational mechanisms between COVID-19 and silicosis remain unclear. Therefore, this study aimed to explore the shared molecular mechanisms and drug targets of COVID-19 and silicosis. Gene expression profiling identified four modules that were most closely associated with both diseases. Furthermore, we performed functional analysis and constructed a protein-protein interaction network. Seven hub genes (BUB1, PRC1, KIFC1, RPM2, CDKN3, CCNB2, and MCM6) were involved in the interaction between COVID-19 and silicosis. Thereafter, we investigated how these seven genes are regulated by diverse microRNAs and transcription factors. Subsequently, the correlation between the hub genes and infiltrating immune cells was explored. Further in-depth analyses were performed based on single-cell transcriptomic data of COVID-19, and the expression of hub-shared genes was characterized and located in multiple cell clusters. Finally, the results of the molecular docking analysis suggested that resveratrol might be a promising drug for treating both COVID-19 and silicosis. Taken together, the current study reveals the common pathogenesis of COVID-19 and silicosis, which may provide a novel reference for further research.
Deriving Controllable Local optimal Solutions through an Environment Parameter Fixed Algorithm (EPFA-CLS)
Authors: Jang Ohtae , Jo Sangho , Kim Sungho 
Published: January 2023

Abstract
In many engineering problems, an optimal solution must be derived by considering reality situations that reflect actual measured data. In the optimization problem, the objective function is modeled through a formula. Such modeling is difficult in reality situations that are affected by multiple environments, such as temperature and humidity. Therefore, this paper models the objective function as a data-driven approach under deep-learning-based nonlinear regression analysis, and we then propose the constraint optimization problem in a specific environment (trained DNN objective optimization). We define the solution to this problem as a controllable local-optimal solution (CLS) and propose an environment parameter fixed algorithm (EPFA) to derive the CLS. This changes constraint optimization into an unconstrained optimization problem by pinning down environment parameters to reflect constraints in a particular environment. After that, the proposed approach is combined with conventional Gradient Descent and algorithms such as Adagrad to derive the CLS. The situation is explained through an example of an optimal course model created for use in this study. In addition, we verify that the CLS can be derived through experiment by using an optimal course dataset and a Boston house price dataset.
A Novel Fatty Acid Metabolism Signature Predicts Prognoses, Tumor Immune Microenvironment, and Immunotherapy Response In Lung Adenocarcinoma
Authors: Fu Denggang , Zhang Biyu , Fan Wenyan , Wang Xin 
Published: January 2023

Abstract
Background: Lung adenocarcinoma (LUAD) is the most common and aggressive subtype of non-small cell lung cancer. Aberrant fatty acid metabolism (FAM) has been demonstrated to play an essential role in the tumorigenesis of human cancers, yet limited studies in LUAD.
Methods: The RNA-sequencing dataset of LUAD patients with clinical features from the TCGA database was used as the training set. Six independent LUAD cohorts totaling 1,368 encompassing diverse platforms from the GEO database were employed as validation sets. The prognostic signature was constructed by multivariate Cox regression analysis with the Akaike information criterion. The tumor immune microenvironment (TIME) was analyzed by ESTIMATE and infiltrated immune cell subsets were calculated using multiple deconvolution algorithms. Tumor characteristics such as T cell receptors richness and diversity, and tumor mutation burden (TMB) were assessed. The implication of the signature in predicting immunotherapy response was also investigated.
Results: Overall survival (OS) related FAMGs were identified. A robust prognostic signature for OS prediction was developed. Patients were divided into high- and low-risk groups and decreased OS was observed in low-risk patients. Furthermore, the signature could be an independent prognostic indicator after adjusting for clinicopathological features. Receiver operating characteristic curve analysis indicated the validity of the signature. The predictive power was validated using six LUAD validation cohorts. The signature also has strong risk stratification utility for patients’ disease relapse. TIME analysis showed increased immune activity in low-risk patients, which was convinced by higher infiltrated CD8+ T, natural killer, and B cells, as well as lower tumor purity, stemness index, TMB, and cell proliferation. Additionally, elevated activated and less senescence of immune cells were observed in low-risk patients. Differentially expressed pathways that related to resistance to immune checkpoint blockades such as DNA repair, hypoxia, cell cycle, epithelial-mesenchymal-transition, and oxidative phosphorylation were enriched in high-risk patients. T cell receptor richness and diversity were higher in low-risk patients. Responders had lower risk scores in contrast to non-responders for LUAD patients receiving anti-PD-1 treatment.
Conclusions: The study was the first time to establish a novel FAMGs-based signature in recognition of the prognosis for LUAD patients and evaluation of the possibility of immunotherapy response in personalized treatment.
13C pulse-labeling suggests separate fast and slow dynamics for two amino acid pools in ectomycorrhizal fungi
Authors: Hobbie Erik A. 
Published: January 2023

Abstract
Background and Aims

Ectomycorrhizal fungi depend on recent photosynthate from their host plants but can also assimilate soil-derived amino acids into fungal protein. The dynamics of different pools of amino acids may differ because their energy cost for acquisition may differ.

Methods

To study carbon dynamics between Pinus sylvestris and ectomycorrhizal fungi, 13CO2 was traced for 97 days into amino acids and structural carbohydrates of Cortinarius semisanguineus and Lactarius rufus sporocarps.

Results

Prior to 13C labeling, amino acid δ13C was higher in Cortinarius than Lactarius, which suggests uptake of older soil-derived amino acids by Cortinarius. 13C labeling in amino acids was 58 ± 3% of that in structural carbohydrates. In stepwise regression, 58% of amino acid carbon tracked the δ13C of the structural carbon which peaked on day 16. The other 42% of amino acid carbon peaked later, on day 30, at 19% of the 13C enrichment of structural carbon, indicating two pools of amino acids. Both structural carbohydrates and the ‘fast’ pool of amino acids derived from recent plant sugars.

Conclusion

It is hypothesized that fast cycling amino acids had simple synthesis pathways such as alanine, aspartic acid and glutamic acid, whereas slow cycling amino acids had multiple enzymatic steps to synthesis, such as lysine, leucine, and isoleucine. This slow pool is more likely than the fast pool to reflect soil-derived amino acids. Studies of amino acid use by ectomycorrhizal fungi should account for the large differences in dynamics and energetic costs between slow and fast cycling amino acids.
Effectiveness some Egyptian isolates of entomopathogenic fungi against bulb mite (Rhizoglyphus robini - Acaridae)
Authors: Mohamed A. S. M. , Hezazy Momamed Gamal , Wang Liande 
Published: January 2023

Abstract
Five fungal isolates have been evaluated from the Egyptian environment for activity against Rhizoglyphus robini; these isolates were Aspergillus terreus1, Aspergillus terreus2, Aspergillus flavus, Myrothecium advena, and Penicillin crustostum. These isolates were evaluated by different concentrations. The concentrations 3.2x106 conidia/ml for A.terreus1was effective against tested mite than M. advena, A. terreus 2, A. flavus, and P. crustostum. The mortality percentages were (78.62, 69.66, 55.86, 17.93, and 1.38%); The LC50 values exhibited by A. terrus1, M. advena, A. terreus2 were (1.06x106, 1.75x106, 3.45x106, and 7.4x109) conidia /ml, respectively.
Discrete Galerkin and iterated discrete Galerkin methods for derivative dependent Fredholm-Hammerstein integral equations with Green's kernel
Authors: Kant Kapil , Kumar Rakesh , Chakraborty Samiran 
Published: January 2023

Abstract
In this article, we look at a class of two point nonlinear boundary value problems and transforms this into derivative dependent Fredholm-Hammerstein integral equations i.e., the integral equation, where the kernel is of Green's type and nonlinear function inside the integral is dependent on the derivative. We obtain the error analysis by replacing all the integrals in Galerkin method by numerical integrations. We propose the discrete Galerkin and iterated discrete Galerkin methods by piecewise polynomials to obtain the convergence analysis of these type of derivative dependent Fredholm-Hammerstein integral equations. By choosing the numerical quadrature rule appropriately, the convergence rates in Galerkin and iterated Galerkin methods are preserved. We show that the iterated discrete Galerkin method improves on the discrete Galerkin method in terms of order of convergence. To demonstrate the theoretical results, several numerical examples are provided.
Modeling Secured User’s Recent-Past History Tracking System Using Location Information for Controlling the Spread of COVID-19
Authors: Balcha Bereket Simon , Tamirat Amanuel 
Published: January 2023

Abstract
Currently, the world is one under an umbrella of novel and pandemic disease called Covid-19 which is a deadly pandemic disease caused by a novel corona virus. As it is reported in worldometer up to the day of this report, the total deaths are around more than 6.5 million in the world and more than 7.5 thousand deaths in Ethiopia so that it has been observed as the world big challenge which knocks everybody’s door directly or indirectly. Therefore, all concerned bodies are struggling to stop or reduce it through many preventive techniques. One of the most effective techniques is utilizing digital technology to create awareness for community and tracking suspected users on behalf of infected persons. The main aim of this paper is to design user’s recent-past history tracking system using location information with the help of Global Positioning System (GPS). The designed model has two main components. The security and intelligent searching algorithms. In implementing the security system, the user authentication part has been implemented by using hashing technique called Security Hash Algorithm (SHA). The input for this authentication key is user’s current latitude, longitude, hour and minute having appended correctly with consideration of integral part of the parameters. Then, message encryption has been implemented by using Advanced Encryption Standard (AES). The encryption key used for AES is considering the half of left-hand side of result of authentication key whose key bit size is 256. So, the bit size for encryption key is 128 since the type of AES used here is AES-128. These both user authentication and message encryption have been implemented at the side of assumed client-side entity. Another component of our designed model is implementation of intelligent searching algorithm called Tabu Searching (TS) Algorithm. The algorithm is efficiently implemented by listing some further components like searching for Tabu List (TL), risky areas list, and solution area lists. Along with this implementation, TS uses two types of memory called recency memory (short term) memory used to store TL temporarily and long-term memory used to store problem instance, risky area list and solution list as well. The thing made our searching design called intelligent is since the searching mechanism is adaptive to problem instance size, the necessity or conditionality of searching for all problem instances depends on the result of risky area list and solution list. The document is organized into five parts as part one states about introduction, part two describes the related works and gaps in the existing works. The part three clearly describes about methodology which makes our dreams true in showing the right way for implementing the security and searching parts. Part four implements the methodology conceptually designed in chapter three by simulating it with Python programming language and the last part states about conclusion and future recommendation.
Termites Infestation on Different Eucalyptus Wood Species and Control Using Natural Oil from Plants
Authors: ALAMU Olaniyi Thomas , EWETE Francis Kolawole 
Published: January 2023

Abstract

Termites are one of the major pests of wood and the use of synthetic insecticides in the control constitutes a major challenge to environmental health. This study assessed the level of damage on the wood of four Eucalyptus species on exposure to subterranean termites using preference and non preference tests in the field; and the efficacy of different plant oils to protect wood damage. Physical properties responsible for wood resistance were determined using standard procedures. Pearson correlation, Analysis of Variance (ANOVA) and Tukey’s Honestly Significant Difference (p < 0.05) were used for data analysis. The results showed that the highest and lowest wood damages were recorded in Eucalyptus tereticornis and Eucalyptus cloeziana, respectively throughout the period of observation in Samaru-Zaria and Afaka, Kaduna. The results also showed that wood of E. cloeziana was harder than that of E. tereticornis; and correlated significantly with the percentage wood loss. Solignum, a synthetic wood protectant, reduced wood loss to termite infestation more than the plant oils. Oil extracts from neem seed, Jatropha seed and palm kernel significantly reduced wood loss than in the control treatment. However, the potency of these plant oils reduced with time. The wood of E. cloeziana demonstrated high level of resistance against termite infestation; and neem oil, Jatropha oil and palm kernel oils can be used as wood protectants as alternatives to synthetic wood preservatives.
Context-Based and Image-Based Subsea Pipeline Degradation Monitoring
Authors: Spahic Rialda , Lundteigen Mary Ann , Hepsø Vidar 
Published: January 2023

Abstract
This research examines the factors contributing to the exterior material degradation of subsea oil and gas pipelines monitored with autonomous underwater systems (AUS). The AUS have a role of gathering image data that is further analyzed with artificial intelligence data analysis methods. Corrosion and potential ruptures on pipeline surfaces are complex processes involving several competing elements, such as the geographical properties, composition of soil, atmosphere, and marine life, whose effects can result in substantial environmental damage and financial loss. Despite extensive research, corrosion monitoring and prediction remain a persistent challenge in the industry. There is a lack of knowledge map that can enable image analysis using an AUS to recognize ongoing degradation processes and potentially prevent substantial damage. The main contribution of this research is the knowledge map for increased context and risk awareness to improve the reliability of image-based monitoring and inspection by autonomous underwater systems in detecting hazards and early signs of material degradation on subsea pipeline surfaces.
Predictors of Serious Adverse Events and High-Level Cardiorespiratory Support in Patients Undergoing Transcatheter Pulmonary Vein Interventions
Authors: Barreto Jessica A , Gauvreau Kimberlee , Porras Diego , Esch Jesse J , Maschietto Nicola , Quinn Brian , Stein Mary , Bergersen Lisa , Callahan Ryan 
Published: January 2023

Abstract
Background
Patients with pulmonary vein stenosis (PVS) often require frequent transcatheter pulmonary vein (PV) interventions for management of restenosis. Predictors of serious adverse events (AEs) and need for high-level cardiorespiratory support (mechanical ventilation, vasoactive support, and/or extracorporeal membrane oxygenation) 48 hours after transcatheter PV interventions have not been reported.
Methods
Single-center retrospective cohort analysis of patients with PVS who underwent transcatheter PV interventions from 3/1/2014 to 12/31/2021. Univariate and multivariable analyses were performed using generalized estimating equations to account for within-patient correlation.
Results
240 patients underwent 841 catheterizations involving PV interventions (median 2 catheterizations per patient [1, 3]). At least one serious AE was reported in 100 (12%) cases, the most common of which were pulmonary hemorrhage (n = 20) and arrhythmia (n = 17). There were 14 severe/catastrophic AEs (1.7% of cases) including 3 strokes and 1 patient death. On multivariable analysis, age less than 6 months, low systemic arterial saturation (< 95% in patients with biventricular [BiV] physiology, < 78% in single ventricle [SV] physiology), and severely elevated mean PA pressure (≥ 45 mmHg in BiV, ≥ 17 mmHg in SV) were associated with SAEs. Age less than 1 year, hospitalization prior to catheterization, and moderate-severe RV dysfunction were associated with high-level support after catheterization.
Conclusion
Serious AEs during transcatheter PV interventions in patients with PVS are common, although major events such as stroke or death are uncommon. Younger patients and those with abnormal hemodynamics are more likely to experience serious AEs and require high-level cardiorespiratory support after catheterization.
Reducing honeycomb-generated turbulence with a passive grid
Authors: Schipper N.R.M. , Kuerten J.G.M. , Zeegers J.C.H. 
Published: January 2023

Abstract
Honeycombs are widely used to laminarize fluid streams by inhibiting the lateral components of the fluctuating velocity. However, they also produce additional turbulence by themselves due to the formation of large-scale instabilities and the break-up of the individual velocity profiles stemming from the honeycomb cells. In the present research, we use 2D-planar particle image velocimetry (PIV) to study how honeycomb-generated turbulence is affected by a downstream grid. It is found that placing a grid near the honeycomb discharge drastically enhances flow uniformity by separating the strong jets stemming from the individual honeycomb cells into many smaller jets that are much more rapidly dissipated. Furthermore, the grid can reduce the magnitude of peak turbulence intensity by as much as 95%, as long as it is positioned upstream of the onset of the large-scale honeycomb-induced instabilities. A downstream grid is highly beneficial for both a laminar and turbulent honeycomb discharge and is most effective when there is a slight offset between the grid and honeycomb. Even though longer honeycombs generally produce more turbulence than short ones due to the larger length-scale of the shear layers, these effects are almost entirely decoupled when using a honeycomb-grid combination. Finally, a honeycomb-grid combination effectively inhibits both axial and lateral turbulence.
Fission yeast Cdc14-like phosphatase Flp1/Clp1 modulates the transcriptional response to oxidative stress
Authors: Canete Juan A. , Andrés Sonia , Díaz-Cuervo Helena , Bueno Avelino , Sacristán María P. 
Published: January 2023

Abstract
Reactive oxygen species (ROS) are an important source of cellular damage. When ROS intracellular levels increase, oxidative stress takes place affecting DNA stability and metabolic functions. To prevent these effects, stress-activated protein kinases (SAPKs) delay cell cycle progression and induce a transcriptional response that activates antioxidant mechanisms ensuring cell adaptation and survival. Fission yeast Cdc14-like phosphatase Flp1 (also known as Clp1) has a well-established role in cell cycle regulation. Moreover, Flp1 contributes to checkpoint activation during replication stress. Here, we show that Flp1 has a role in fine-tuning the cellular oxidative stress response. Rad24-dependent nucleolar release of Flp1 in response to oxidative stress conditions plays a role in the cellular transcriptional response. Thus, Flp1 ablation increases the transcriptional response to oxidative stress, in both intensity and duration, upregulating Atf1/Pcr1 transcription factors and, consequently, genes such as ctt1 + , hsp9 + , gpd1 + and pyp2 +. Remarkably, we found that Flp1 interacts with the Atf1/Pcr1 complex with Pcr1 acting as a direct substrate. Our results provide evidence that Flp1 modulates the oxidative stress response by limiting the Atf1/Pcr1-mediated transcription.
Sociocultural aspect of care is definitely part of the “problem”: Developing preclinical students’ cross-cultural care competence through problem-based learning
Authors: Lu Peih-ying , Hsu Anna Shan Chun 
Published: January 2023

Abstract
Increasing diversity issues have posed challenges on pedagogical strategies of medical education, particularly in the post-pandemic era. Medical students are not only expected to have essential medical skills, but also be equipped with the abilities to stay attuned to the sociocultural needs of diverse patient groups. Providing students safe environments to hone these abilities is essential in helping them prepare for future patient encounters in the clinical setting. This study adopted mixed methods to explore the effectiveness of integrating issues on cross-cultural care competence (CCC) into problem-based learning (PBL) to enhance medical students’ CCC preparedness. With bases in constructivism and social cognitive learning theories, and drawing from Bloom’s taxonomy and the Conscious-Competence model in the development of adaptive expertise, this article included discussions of students’ and tutors’ perceptions of the effectiveness of integrating CCC issues into problem-based learning (PBL) in a Taiwanese medical school. We incorporated into PBL scenarios diversity issues students identified as being less prepared for in a previous study. For quantitative analysis, undergraduate medical students completed pre- and post-PBL questionnaires (pre =124, post = 239) and 24 tutors completed a tutor version of pre-PBL questionnaire. For qualitative analysis, we conducted two student focus groups (n = 8) and 12 individual tutor interviews. Scripts were transcribed, coded, and analyzed using inductive thematic analysis. Quantitative results revealed students generally considered CCC-integrated PBL to be effective in providing them with learning experiences to better understand diversity issues and preparing them for clinical learning. From interviews and focus groups, we further identified four themes: awareness raising- CCC topics in medical training; students’ engagement in CCC-issues- reasons affecting participation; tutors’ concerns- competence in facilitation of CCC learning; and competition in a crowded curriculum. These themes showed that participation in CCC-integrated PBL sessions can raise students’ awareness of sociocultural aspects, biases, stereotypes, diverse cultural groups’ healthcare needs and CCC issues. However, there are still gaps to fill including insufficient student engagement, tutors’ own competence (or capabilities) in addressing CCC, and inadequate time. In conclusion, strategically integrating CCC into PBL provide opportunities that allow students to raise awareness of the impact patients’ diverse backgrounds have on health care. Nevertheless, it is pivotal to address gaps in tutors’ perceptions and students’ learning experiences to design curricular content that can broaden students’ adaptive expertise and sensitivity to diverse patient needs.