bluuebunny/crossref_metadata_2025_split huggingface dataset:
Excessive Mitochondrial Fission Suppresses Mucosal Repair by Impairing Butyrate Metabolism in Colonocytes
Authors: Fu Shi-Chen , Qu Jun-Yan , Li Li-Xiang , Yang Xiao-Xiao , Li Yan-Qing , Zuo Xiu-Li 
Published: July 2023

Abstract

Background
Mucosal healing is one of the principal therapeutic targets for ulcerative colitis (UC). Mitochondria are dynamic organelles that undergo constant fusion and fission; however, the process that is most conducive to mucosal healing remains unclear. This study investigated the role of mitochondrial fission in mucosal healing in UC patients.

Methods
Quantitative polymerase chain reaction, Western blotting, and immunostaining were used to detect mitochondrial fission in UC patients and a dextran sulfate sodium–induced colitis model. Colonic organoids were used to investigate the role of mitochondrial fission in butyrate metabolism. Enzyme activity assays were performed to identify the key proteins involved in this mechanism.

Results
It was found that inhibition of mitochondrial fission promoted mucosal healing in mice and that there was an increase in mitochondrial fission in colonic epithelial cells of UC patients. Excessive fission inhibits stem cell proliferation by impairing butyrate metabolism in colonic organoids. The mitochondrial fission antagonist P110 failed to promote mucosal healing in antibiotic-treated mice, and the addition of exogenous butyrate reversed this effect. Increased butyrate exposure in the colonic stem cell niche has also been observed in UC patients. Mechanistically, enzyme activity assays on colonic organoids revealed that excessive fission inhibits mitochondrial acetoacetyl-CoA thiolase activity via reactive oxygen species.

Conclusions
Collectively, these data indicate that excessive mitochondrial fission suppresses mucosal repair by inhibiting butyrate metabolism and provides a potential target for mucosal healing in patients with ulcerative colitis.
LAMB3 Promotes Intestinal Inflammation Through SERPINA3 and Is Directly Transcriptionally Regulated by P65 in Inflammatory Bowel Disease
Authors: Liu Fangyuan , Xu Weimin , Wang Yaosheng , Huang Zhenyu , Zhu Zhehui , Ou Weijun , Tang Wenbo , Fu Jihong , Liu Chenying , Gu Yubei , Liu Yun , Du Peng 
Published: July 2023

Abstract

Background
Various extracellular matrix (ECM) reshaping events are involved in inflammatory bowel disease (IBD). LAMB3 is a vital subunit of laminin-332, an important ECM component. Data on the biological function of LAMB3 in intestinal inflammation are lacking. Our aim is to discuss the effect of LAMB3 in IBD.

Methods
LAMB3 expression was assessed in cultured intestinal epithelial cells, inflamed mucosal tissues of patients and mouse colitis models. RNA sequencing, quantitative real-time polymerase chain reaction and Western blotting were used to detect the LAMB3 expression distribution and potential downstream target genes. Dual-luciferase assays and chromatin immunoprecipitation-quantitative polymerase chain reaction were used to determine whether P65 could transcriptionally activate LAMB3 under tumor necrosis factor α stimulation.

Results
LAMB3 expression was increased in inflammatory states in intestinal epithelial cells and colonoids and was associated with adverse clinical outcomes in Crohn’s disease. Knockdown of LAMB3 inhibited the expression of proinflammatory cytokines. Mechanistically, LAMB3 expression was directly transcriptionally activated by P65 and was inhibited by nuclear factor kappa B inhibitors under tumor necrosis factor α stimulation. Furthermore, RNA sequencing and replenishment experiments revealed that LAMB3 upregulated SERPINA3 to promote intestinal inflammation via the integrin α3β1/FAK pathway.

Conclusion
We propose that LAMB3 could serve as a potential therapeutic target of IBD and a predictor of intestinal stenosis of Crohn’s disease. Our findings demonstrate the important role of ECM in the progression of IBD and offer an experimental basis for the treatment and prognosis of IBD.
Use of a reference text by pharmacists, intern pharmacists and pharmacy students: a national cross-sectional survey
Authors: Mill Deanna , Johnson Jacinta L , Corre Lauren , Lee Kenneth , D’Lima Danielle , Clifford Rhonda , Seubert Liza , Salter Sandra M , Page Amy Theresa 
Published: July 2023

Abstract

Background
Reference texts assist pharmacists by addressing knowledge gaps and enabling evidence-based decisions when providing patient care. It is unknown whether reference text utilisation patterns differ between pharmacists, intern pharmacists and pharmacy students. To describe and compare the self-reported use and perceptions of a reference text, namely the national formulary, by pharmacists, intern pharmacists and pharmacy students.

Methods
Registered pharmacists, intern pharmacists and pharmacy students living in Australia were surveyed in July 2020. The survey was electronic and self-administered. Questions considered self-reported use of a specific reference text in the preceding 12 months.

Key findings
There were 554 eligible responses out of 774 who commenced the survey: 430 (78%) pharmacists, 45 (8%) intern pharmacists and 79 (14%) pharmacy students. Most participants (529/554, 96%) reported historical use of the text, though pharmacists were significantly less likely than intern pharmacists and students to use it frequently (52/422, 12% versus 16/43, 37% versus 23/76, 30%, P &lt; 0.001). Pharmacists (44%, 177/404) reported using the text as a tool to resolve a situation when providing a service or patient care (177/404, 44%) or as a teaching resource (150/404, 38%). In contrast, intern pharmacists and students most commonly use these to familiarise themselves with the contents (30/43, 70%; 46/76, 61%) or update their knowledge (34/43, 79%; 53/76, 70%).

Conclusions
Access and use patterns varied significantly across career stages. A broader understanding of the use of reference texts may help develop interventions to optimise the content and usability. Varying usage patterns across the groups may inform the tailoring of texts for future use.
A nationwide survey of methods and barriers to adverse drug reaction monitoring and reporting among hospital pharmacists in Thailand
Authors: Jarernsiripornkul Narumol , Kayrash Sasina , Homket Prangwalai , Srisuriyachanchai Warisara 
Published: July 2023

Abstract

Objectives
To explore the methods of adverse drug reaction identification and monitoring used by hospital pharmacists in all regions of Thailand, to explore barriers to and pharmacists’ attitudes towards adverse drug reaction monitoring and reporting, and to assess the factors related to these aspects.

Methods
Pharmacists in 480 hospitals in Thailand were selected by stratified sampling. Self-administered questionnaires were sent by post and pharmacists returned completed questionnaires via QR code.

Key findings
In total, pharmacists at 286 hospitals returned the questionnaire (response rate = 59.6%). The most common adverse drug reaction (ADR) monitoring methods were the spontaneous reporting system (SRS), which was used by 100% of respondents, followed by high alert drug lists (73.1%) and routine adverse drug reaction monitoring (64.0%). The most frequently used methods of adverse drug reaction prevention were providing drug allergy card and recording allergy history in database. The major barrier to adverse drug reaction monitoring and reporting among respondents was uncertainty about whether the suspected drug caused the reaction (49.3%). Pharmacists had a good attitude towards adverse drug reaction monitoring and reporting (60.5%). Longer work experience (≥10 years) was negatively related with good attitudes towards adverse drug reaction monitoring and reporting (OR = 0.535, P = 0.040), whereas higher education level was positively related (OR = 2.201, P = 0.025).

Conclusions
Spontaneous reporting system is the main method used for adverse drug reaction monitoring and reporting among hospital pharmacists in Thailand. Pharmacists had good attitudes towards adverse drug reaction monitoring and reporting, however, barriers remain.
How Not to Be a Fallibilist
Authors: Kyriacou Christos 
Published: July 2023

Abstract
I develop one partial explanation of the origins of our fallibilist intuitions about knowledge in ordinary language fallibilism and argue that this explanation indicates that our epistemic methodology should be more impartial and theory-neutral. First, I explain why the so-called Moorean constraint (cf. Hawthorne 2005, 111) that encapsulates fallibilist intuitions is fallibilism’s cornerstone. Second, I describe a pattern of fallibilist reasoning in light of the influential dual processing and heuristics and biases approach to cognition (cf. Kahneman 2011; Thaler and Sunstein 2008; Evans 2017). I suggest that this pattern of reasoning involves the question-substitution heuristic, the availability and representativeness heuristics, the focusing bias as well as framing effects, priming and the anchoring and adjusting heuristic. Third, I argue that this fallibilist pattern of reasoning is methodologically dubious because it involves a vicious circularity and briefly outline an alternative, more impartial and theory-neutral abductive methodology for the theory of knowledge. Finally, I briefly explain how this analysis sheds light on the ordinary language fallibilism of Moore (1939), Austin (1961), Wittgenstein (1969) and Chisholm (1982).
Can Voluntary Health Insurance for Non-reimbursed Expensive New Treatments Be Just?
Authors: Smids Jilles , Bunnik Eline M 
Published: July 2023

Abstract
Public healthcare systems are increasingly refusing (temporarily) to reimburse newly approved medical treatments of insufficient or uncertain cost-effectiveness. As both patient demand for these treatments and their list prices increase, a market might arise for voluntary additional health insurance (VHI) that covers effective but (very) expensive medical treatments. In this paper, we evaluate such potential future practices of VHI in public healthcare systems from a justice perspective. We find that direct (telic) egalitarian objections to unequal access to expensive treatments based on different ability to afford VHI do not stand up to scrutiny. However, such unequal access might lead to loss of self-respect among individuals, or loss of fraternity within society, rendering it more difficult for citizens to interact on equal moral footing. This would be problematic from a relational egalitarian perspective. Moreover, the introduction of VHI might turn out to have negative consequences for the comprehensiveness and/or the quality of the public healthcare services that are offered to all patients equally through basic health insurance. These consequences must be weighed against potential health gains and the value of liberty. We conclude that governments should be careful when considering the introduction of VHI in public healthcare systems.
Major Susceptibility Gene Epistasis over Minor Gene Resistance to Spot Form Net Blotch in a Commercial Barley Cultivar
Authors: Muria-Gonzalez Mariano Jordi , Lawrence Julie A. , Palmiero Elzette , D'Souza Nola K. , Gupta Sanjiv , Ellwood Simon R. 
Published: July 2023

Spot form net blotch, caused by Pyrenophora teres f. maculata, is a significant global disease of barley ( Hordeum vulgare). Baudin, a barley cultivar that was until recently extensively grown in Western Australia, was reported as having minor seedling resistance. However, Baudin was highly susceptible to a local isolate, M3, suggesting that this isolate had gained virulence against a major susceptibility gene. M3 causes atypical lesions with pale centers early in the infection, with initial screens of a segregating population indicating that this was determined by a single locus in the Baudin genome. The susceptibility was semidominant in F1 progeny and the susceptibility gene, designated Spm1 ( Susceptibility to P. teres f. maculata 1), mapped to a 190-kb section of the resistance gene-rich Mla region of chromosome 1H. Phenotyping with Ptm SP1, a non-M3 pathotype, identified a seedling resistance locus on 2H. Minor gene resistance is generally regarded as potentially durable, but our findings suggest the resistance to spot form net blotch in Baudin is nullified by strong susceptibility conferred by a separate locus on 1H. [Formula: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .
Dielectric model of asphalt pavement materials towards the future electrified road
Authors: Wang Dawei , Ye Chengsen , Lv Haotian , Meng Luopei , Tang Fujiao , Ni Yaowei , Liu Pengfei 
Published: July 2023

The dielectric properties of asphalt mixture are crucial for future electrified road (e-road) and pavement non-destructive detection. Few investigations have been conducted on the temperature and frequency influencing the dielectric properties of asphalt pavement materials. The development of e-road requires more accurate prediction models of pavement dielectric properties. To quantify the influence of temperature and frequency on the dielectric properties of asphalt mixtures, the dielectric constants, dielectric loss factor and dielectric loss tangents of aggregate, asphalt binders and asphalt mixtures were tested over the temperature range of −30 to 60°C and frequency range of 200 to 2 000 000 Hz. The results showed that the dielectric constants and dielectric loss factors of aggregate, asphalt binders and asphalt mixtures vary linearly with temperature, while the growth rates vary with the frequency. A model based on nonlinear fitting was first presented to estimate the dielectric loss factor, and another prediction model of the dielectric constant of asphalt mixtures considering the temperature impact was proposed afterwards. Compared with classical models, the average relative error of the proposed model of the dielectric constant is the smallest and is less sensitive to the asphalt mixture. This investigation can cast light on the utilization of non-destructive pavement testing and is potentially valuable for e-road using the electromagnetic properties of asphalt pavement materials.
This article is part of the theme issue 'Artificial intelligence in failure analysis of transportation infrastructure and materials'.
Automatic pavement texture recognition using lightweight few-shot learning
Authors: Pan Shuo , Yan Hai , Liu Zhuo , Chen Ning , Miao Yinghao , Hou Yue 
Published: July 2023

Texture is a crucial characteristic of roads, closely related to their performance. The recognition of pavement texture is of great significance for road maintenance professionals to detect potential safety hazards and carry out necessary countermeasures. Although deep learning models have been applied for recognition, the scarcity of data has always been a limitation. To address this issue, this paper proposes a few-shot learning model based on the Siamese network for pavement texture recognition with a limited dataset. The model achieved 89.8% accuracy in a four-way five-shot task classifying the pavement textures of dense asphalt concrete, micro surface, open-graded friction course and stone matrix asphalt. To align with engineering practice, global average pooling (GAP) and one-dimensional convolution are implemented, creating lightweight models that save storage and training time. Comparative experiments show that the lightweight model with GAP implemented on dense layers and one-dimensional convolution on convolutional layers reduced storage volume by 94% and training time by 99%, despite a 2.9% decrease in classification accuracy. Moreover, the model with only GAP implemented on dense layers achieved the highest accuracy at 93.5%, while reducing storage volume and training time by 83% and 6%, respectively.
This article is part of the theme issue 'Artificial intelligence in failure analysis of transportation infrastructure and materials'.
Feasibility of determining asphalt pavement condition from falling weight deflectometer test and finite element model updating
Authors: Deng Yong , Zhang Yazhou , Shi Xianming 
Published: July 2023

Determination of pavement internal condition from a non-destructive field test is a persistent topic for its practical necessity and difficulty. It is essentially an inverse problem calibrating pavement material and structural properties from pavement responses. Considering the intrinsic complexity of asphalt pavement materials (e.g., time and temperature dependencies of asphalt mixture and stress dependency of unbound granular materials), this problem has become a typical high-dimensional optimization problem with a large and diverse set of calibrated parameters. This study investigated the feasibility of artificial intelligence-based finite element model updating in addressing this problem, and focused on the accuracy as well as stability of the backcalculated results. For a comprehensive evaluation of this method, the effects of its components such as the surrogate model representing the pavement system, the applied pavement response, the optimization algorithm and the backcalculation scheme were characterized. Finally, we found that the sensitivity of applied pavement responses to thebackcalculated pavement condition, the number of applied pavement responses and the balance between the backcalculated pavement condition and the applied test were of significant importance to achieving accurate and stable backcalculation results. Corresponding modifications were recommended to be conducted in future research for improving the performance of the proposed backcalculation method.This article is part of the theme issue ‘Artificial intelligence in failure analysis of transportation infrastructure and materials’.
Automatic identification of pavement cracks in public roads using an optimized deep convolutional neural network model
Authors: Lv Zhihan , Cheng Chen , Lv Haibin 
Published: July 2023

The current study aims to improve the efficiency of automatic identification of pavement distress and improve the status quo of difficult identification and detection of pavement distress. First, the identification method of pavement distress and the types of pavement distress are analysed. Then, the design concept of deep learning in pavement distress recognition is described. Finally, the mask region-based convolutional neural network (Mask R-CNN) model is designed and applied in the recognition of road crack distress. The results show that in the evaluation of the model's comprehensive recognition performance, the highest accuracy is 99%, and the lowest accuracy is 95% after the test and evaluation of the designed model in different datasets. In the evaluation of different crack identification and detection methods, the highest accuracy of transverse crack detection is 98% and the lowest accuracy is 95%. In longitudinal crack detection, the highest accuracy is 98% and the lowest accuracy is 92%. In mesh crack detection, the highest accuracy is 98% and the lowest accuracy is 92%. This work not only provides an in-depth reference for the application of deep CNNs in pavement distress recognition but also promotes the improvement of road traffic conditions, thus contributing to the progression of smart cities in the future.
This article is part of the theme issue 'Artificial intelligence in failure analysis of transportation infrastructure and materials'.
TransCrack: revisiting fine-grained road crack detection with a transformer design
Authors: Lin Chunmian , Tian Daxin , Duan Xuting , Zhou Jianshan 
Published: July 2023

Prior convolution-based road crack detectors typically learn more abstract visual representation with increasing receptive field via an encoder–decoder architecture. Despite the promising accuracy, progressive spatial resolution reduction causes semantic feature blurring, leading to coarse and incontiguous distress detection. To these ends, an alternative sequence-to-sequence perspective with a transformer network termed TransCrack is introduced for road crack detection. Specifically, an image is decomposed into a grid of fixed-size crack patches, which is flattened with position embedding into a sequence. We further propose a pure transformer-based encoder with multi-head reduced self-attention modules and feed-forward networks for explicitly modelling long-range dependencies from the sequential input in a global receptive field. More importantly, a simple decoder with cross-layer aggregation architecture is developed to incorporate global with local attentions across different regions for detailed feature recovery and pixel-wise crack mask prediction. Empirical studies are conducted on three publicly available damage detection benchmarks. The proposed TransCrack achieves a state-of-the-art performance over all counterparts by a substantialmargin, and qualitative results further demonstrate its superiority in contiguous crack recognition and fine-grained profile extraction.
This article is part of the theme issue ‘Artificial intelligence in failure analysis of transportation infrastructure and materials’.
A hybrid approach for fatigue life prediction of in-service asphalt pavement
Authors: Luo Xue , Wang Hang , Cao Shunqin , Ling Jian , Yang Siyuan , Zhang Yuqing 
Published: July 2023

Fatigue cracking is one of the main pavement failures, which makes accurate fatigue life prediction for the design and maintenance of asphalt pavements crucial. The majority of traditional prediction methods are based entirely on the laboratory fatigue test, without considering the field condition and maintenance data. This paper aims to propose a hybrid approach to fill this gap. The key idea is that the damage condition is back-calculated by an artificial intelligence-based finite-element (FE) model updating using field-monitoring information (data-driven component), which is used to update the parameters in the mechanistic composition-specific fatigue life prediction equation (model-driven component). The laboratory test of field cores gives the material non-destructive properties. The simulated pavement response subjected to truck loading shows good agreement with measured values, which indicates that the verified constitutive relationship could be used in the data-driven component. Furthermore, in view that the fatigue test is time- and money-consuming, this paper proposes a non-test estimation of the fatigue characteristic curve based on FE simulation of a repeated direct tension test. Three test pavement sections were employed as case studies. Results showed that the predicted fatigue life changes with the service time. At the early age, semi-rigid pavement has a larger fatigue life than flexible and inverted pavements.
This article is part of the theme issue 'Artificial intelligence in failure analysis of transportation infrastructure and materials'.