bluuebunny/crossref_metadata_2025_split huggingface dataset:
Understanding Occlusion and Temporomandibular Joint Function Using Deep Learning and Predictive Modeling
Authors: Farook Taseef Hasan , Dudley James 
Published: November 2024

ABSTRACTObjectivesAdvancements in artificial intelligence (AI)‐driven predictive modeling in dentistry are outpacing the clinical translation of research findings. Predictive modeling uses statistical methods to anticipate norms related to TMJ dynamics, complementing imaging modalities like cone beam computed tomography (CBCT) and magnetic resonance imaging (MRI). Deep learning, a subset of AI, helps quantify and analyze complex hierarchical relationships in occlusion and TMJ function. This narrative review explores the application of predictive modeling and deep learning to identify clinical trends and associations related to occlusion and TMJ function.ResultsDebates persist regarding best practices for managing occlusal factors in temporomandibular joint (TMJ) function analysis while interpreting and quantifying findings related to the TMJ and occlusion and mitigating biases remain challenging. Data generated from noninvasive chairside tools such as jaw trackers, video tracking, and 3D scanners with virtual articulators offer unique insights by predicting variations in dynamic jaw movement, TMJ, and occlusion. The predictions help us understand the highly individualized norms surrounding TMJ function that are often required to address temporomandibular disorders (TMDs) in general practice.ConclusionsNormal TMJ function, occlusion, and the appropriate management of TMDs are complex and continue to attract ongoing debate. This review examines how predictive modeling and artificial intelligence aid in understanding occlusion and TMJ function and provides insights into complex dental conditions such as TMDs that may improve diagnosis and treatment outcomes with noninvasive techniques.
Evaluation of Panoramic Radiography Diagnostic Accuracy in the Assessment of Interdental Alveolar Bone Loss Using CBCT
Authors: Anbiaee Najmeh , Pahlavanzadeh Pedram 
Published: November 2024

ABSTRACTObjectivesAlveolar bone loss (ABL) and periodontal lesions are common diseases that have an undeniable effect on teeth maintenance and health. Current diagnostic methods include probing, intraoral radiography, and panoramic radiography; each has its limitations. In this study, we aimed to assess the diagnostic accuracy of panoramic radiography in the diagnosis of interdental ABL.Material and MethodsIn this cross‐sectional study, panoramic and cone‐beam computed tomography (CBCT) images from 80 patients were collected from the archives of an oral and maxillofacial radiology center. The amount of ABL was obtained by measuring the distance from the Cemento‐Enamel Junction (CEJ) to the alveolar bone crest on both panoramic and CBCT images. Patients were divided into healthy (ABL ≤ 2 mm) and diseased (2 mm < ABL) groups in terms of periodontal disease.ResultsThere was no statistically significant difference in the average ABL in the premolar, maxillary molar, and mandibular molar areas between the two techniques. However, in other areas, the ABL size was significantly lower in the panoramic view (p < 0.05). Also, the panoramic technique correctly recognized 89.1% of normal and 88.4% of ABL cases. The overall accuracy of panoramic radiography in the diagnosis of ABL was 85%, indicating the good accuracy of this technique. In maxilla, the highest diagnostic accuracy of the panoramic technique was in the molars, and the lowest was in the incisors. In the mandible, the highest and lowest diagnostic accuracy of the panoramic technique was related to molars and premolars, respectively. According to the kappa statistic, there was a significant good to very good agreement between the two types of techniques in all maxillary areas (p < 0.001).ConclusionsPanoramic radiography is accurate in showing ABL. Measuring ABL in the posterior mandibular areas in panoramic radiographs is quite reliable; however, in general, digital panoramic radiography shows less ABL than the actual amount.
Cascade Catalytic Systems for Converting CO2 into C2+ Products
Authors: Shi Qiaochu , Zhang Boyu , Wu Zhenhua , Yang Dong , Wu Hong , Shi Jiafu , Jiang Zhongyi 
Published: November 2024

AbstractThe excessive emission and continuous accumulation of CO2 have precipitated serious social and environmental issues. However, CO2 can also serve as an abundant, inexpensive, and non‐toxic renewable C1 carbon source for synthetic reactions. To achieve carbon neutrality and recycling, it is crucial to convert CO2 into value‐added products through chemical pathways. Multi‐carbon (C2+) products, compared to C1 products, offer a broader range of applications and higher economic returns. Despite this, converting CO2 into C2+ products is difficult due to its stability and the high energy required for C−C coupling. Cascade catalytic reactions offer a solution by coordinating active components, promoting intermediate transfers, and facilitating further transformations. This method lowers energy consumption. Recent advancements in cascade catalytic systems have allowed for significant progress in synthesizing C2+ products from CO2. This review highlights the features and advantages of cascade catalysis strategies, explores the synergistic effects among active sites, and examines the mechanisms within these systems. It also outlines future prospects for CO2 cascade catalytic synthesis, offering a framework for efficient CO2 utilization and the development of next‐generation catalytic systems.
Efficiency and explainability of design‐oriented machine learning models to estimate seismic response, fragility, and loss of a steel building inventory
Authors: Zaker Esteghamati Mohsen , Baddipalli Shivalinga 
Published: November 2024

AbstractMachine learning (ML) has recently been used as an efficient surrogate to estimate different steps of performance‐based earthquake engineering (PBEE), from dynamic structural analysis to fragility and loss assessments. However, due to the varied data, models, and features in existing literature, the relative efficiency of ML models across different PBEE steps remains unclear. Additionally, the black‐box nature of advanced ML algorithms limits their ability to provide design‐oriented insights, hindering the broader application of ML in PBEE‐based design. This study provides a comprehensive comparison of the accuracy and explainability of design‐oriented ML models across different steps of PBEE using a consistent database of 621 steel moment frames with varying designs and geometry. Eight ML algorithms were used in a careful training workflow comprising feature selection, hyperparameter tuning, cross‐validation, and model inference. The sensitivity of model accuracy to representative PBEE outputs—maximum responses, median fragility, and expected annual loss—was assessed using statistical measures. In addition, the explainability of the best models for each step was examined to explore the relationship between design parameters and the corresponding PBEE output. The results show that while ML models can reasonably map design parameters to all different PBEE outputs, models accuracy was higher for drift responses, median fragilities, and component‐based loss metrics. In addition, the optimal algorithm remained the same across different PBEE steps, where support vector machines and random forests provided the highest accuracy with an average R2 of 0.93 and 0.91 over different outputs on the test set. Although the selected feature sets varied across outputs and algorithms, height, number of stories, fundamental period, and the minimum of the beams’ moment of inertia were influential for both models and notably affected different PBEE outputs.
Imaging‐genomic spatial‐modality attentive fusion for studying neuropsychiatric disorders
Authors: Rahaman Md Abdur , Garg Yash , Iraji Armin , Fu Zening , Kochunov Peter , Hong L. Elliot , Van Erp Theo G. M. , Preda Adrian , Chen Jiayu , Calhoun Vince 
Published: November 2024

AbstractMultimodal learning has emerged as a powerful technique that leverages diverse data sources to enhance learning and decision‐making processes. Adapting this approach to analyzing data collected from different biological domains is intuitive, especially for studying neuropsychiatric disorders. A complex neuropsychiatric disorder like schizophrenia (SZ) can affect multiple aspects of the brain and biologies. These biological sources each present distinct yet correlated expressions of subjects' underlying physiological processes. Joint learning from these data sources can improve our understanding of the disorder. However, combining these biological sources is challenging for several reasons: (i) observations are domain specific, leading to data being represented in dissimilar subspaces, and (ii) fused data are often noisy and high‐dimensional, making it challenging to identify relevant information. To address these challenges, we propose a multimodal artificial intelligence model with a novel fusion module inspired by a bottleneck attention module. We use deep neural networks to learn latent space representations of the input streams. Next, we introduce a two‐dimensional (spatio‐modality) attention module to regulate the intermediate fusion for SZ classification. We implement spatial attention via a dilated convolutional neural network that creates large receptive fields for extracting significant contextual patterns. The resulting joint learning framework maximizes complementarity allowing us to explore the correspondence among the modalities. We test our model on a multimodal imaging‐genetic dataset and achieve an SZ prediction accuracy of 94.10% (p < .0001), outperforming state‐of‐the‐art unimodal and multimodal models for the task. Moreover, the model provides inherent interpretability that helps identify concepts significant for the neural network's decision and explains the underlying physiopathology of the disorder. Results also show that functional connectivity among subcortical, sensorimotor, and cognitive control domains plays an important role in characterizing SZ. Analysis of the spatio‐modality attention scores suggests that structural components like the supplementary motor area, caudate, and insula play a significant role in SZ. Biclustering the attention scores discover a multimodal cluster that includes genes CSMD1, ATK3, MOB4, and HSPE1, all of which have been identified as relevant to SZ. In summary, feature attribution appears to be especially useful for probing the transient and confined but decisive patterns of complex disorders, and it shows promise for extensive applicability in future studies.
Reduction of Chemoresistance by Claudin‐14‐Targeting Peptide in Human Colorectal Cancer Cells
Authors: Mizukami Yuko , Hashimoto Shotaro , Ando Tomoka , Ishikawa Yoshinobu , Eguchi Hiroaki , Yoshino Yuta , Matsunaga Toshiyuki , Matsuhashi Nobuhisa , Ikari Akira 
Published: November 2024

ABSTRACTThe expression of claudins (CLDNs), major components of tight junctions (TJs), is abnormal in various solid tumors. CLDN14 is highly expressed in human colorectal cancer (CRC) tissues and confers chemoresistance. CLDN14 may become a novel therapeutic target for CRC, but CLDN14‐targeting drugs have not been developed. Here, we searched for a CLDN14‐targeting peptide, which can suppress CLDN14 expression and chemoresistance using human CRC‐derived DLD‐1 and LoVo cells. Among some short peptides which mimic the second extracellular loop structure of CLDN14, PSGMK most strongly suppressed the protein expression of CLDN14. The mRNA expression of other endogenous TJ components was unchanged by PSGMK. The PSGMK‐induced reduction of CLDN14 protein was inhibited by chloroquine, a lysosome inhibitor, and monodansylcadaverine, a clathrin‐dependent endocytosis inhibitor, indicating that PSGMK may enhance endocytosis and lysosomal degradation of CLDN14. In a three‐dimensional culture model, the oxidative stress was significantly reduced by PSGMK, whereas hypoxia stress was not. Furthermore, the expression levels of nuclear factor erythroid 2‐related factor 2, an oxidative stress response factor, and its target genes were decreased by PSGMK. These results suggest that PSGMK relieves stress conditions in spheroids. The cell viability of spheroids was decreased by anticancer drugs such as doxorubicin and oxaliplatin, which was exaggerated by the cotreatment with PSGMK. Our data indicate that CLDN14‐targeting peptide, PSGMK has an anti‐chemoresistance effect in CRC cells.
Do Social Trust and a Sense of Community Matter for the Engagement of Australian Migrants?
Authors: Miranti Riyana 
Published: November 2024

ABSTRACTPrevious studies have shown mixed results regarding the potential association between trust and community participation. Only a few studies comprehensively investigated the relationship between different forms of social trust. Most of the previous studies distinguished the different forms of social trust separately. This article investigated trust and a sense of community with a more comprehensive framework in a rarely investigated population, migrants in Australia. The increasing social capital approach has been gaining importance in studying the social/political participation of (ethnic) minorities as this has primarily been seen to suit ‘ethnic’ social capital. The article aims to fill the theoretical gap by including trust and a sense of community and examining their associations with civil engagement in society using the Household, Income and Labour Dynamics in Australia Survey data, a longitudinal survey in Australia with a particular focus on bringing the heterogeneities among groups of migrants. There has been an increasing number of people born overseas—a third of the population, according to the latest Australian Census in 2021. The results show that it is likely that the Australian‐born population requires trust to engage in the community, particularly, in the case of volunteering, but this is not significant in the case of migrants. A high sense of community matters for both types of participation, political and volunteering, among Australian‐born and the first generation of migrants. The results for the second generation of migrants in the context of trust and sense of community are limited, and other factors may influence their community engagement.
Radiographic acceptable zone of endobutton placement in ACL reconstruction: A prospective study
Authors: Sharafatvaziri Arash , Tahami Mohammad , Salimi Maryam , Rabie Hamid , Vosoughi Fardis , Karimpour Morad , Moradkhani Ghazaleh , Soleymani Mosayeb 
Published: November 2024

AbstractPurposeDuring the transportal technique of anterior cruciate ligament (ACL) reconstruction, tunnel outlet location can be varied depending on certain anatomical and technical characteristics. Therefore, we aimed to find out the acceptable zone of endobutton location by introducing several radiographic values.MethodsPostoperative lateral radiographs of 72 patients were assessed to measure the distances from the centre of the button to the posterior femoral cortex (D1) and to the most distal point of the lateral condyle (D2). Furthermore, based on the anteroposterior (AP) radiographs, the distances from the centre of the button to the lateral femoral cortex (D3) and from the centre of the button to the line connecting the most distal points of the medial and lateral femoral condyles (D4) were assessed. To measure the sensitivity and specificity of each radiographic value (D1, D2, D3 and D4), the area under the receiver operating characteristic curve was calculated. The alpha angle and femoral tunnel length values were considered as gold standards.ResultsAnalyses showed that the mean values for D1, D2, D3 and D4 were 13.20 ± 0.54, 39.44 ± 0.31, 1.65 ± 0.15 and 42.66 ± 0.47 mm, respectively. The mean angle was found to be 38.6 ± 0.3°, and the mean femoral tunnel length was 38.6 ± 0.2 mm. Age was significantly related to D2 and the diameter of the femur in AP X‐ray, while body mass index had a significant relation with D3 (p < 0.05).ConclusionIn this study, a new method was proposed to evaluate the accuracy of anatomical tunnel placement in ACL reconstruction surgery postoperatively. The statistical analysis of the measured variables showed that the mean ratios were 21.79 ± 0.87 for D1, 65.65 ± 0.63 for D2 and 51.90 ± 0.73 for D4. The results indicated that if the tunnel exit location and endobutton placement in the postoperative radiological images fall within the suggested areas, it can be meaningfully concluded that the tunnel is correctly positioned intraarticularly and the ligament reconstruction is anatomical.Level of EvidenceLevel III.
Analgesia in paediatric acute pancreatitis: A scoping systematic review
Authors: Lucocq James , Joseph Nejo , Knoph Cecilie Sigaard , Abu‐EL‐Haija Maisam , Scheers Isabelle , Drewes Asbjorn M. , Pandanaboyana Sanjay 
Published: November 2024

AbstractObjectiveAcute pancreatitis (AP) is a common paediatric condition, yet there is little data to support optimal analgesic practice. The aim of this scoping review was to report analgesic practice, investigate trends in analgesic strategy and evaluate the impact of analgesic modality on outcomes.MethodsA systematic search of Medline, Embase, CENTRAL, Pubmed Central and Google Scholar was performed by two independent investigators. This review adhered to the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses extension for Scoping Reviews checklist.ResultsThree retrospective cohort studies, all conducted in North America, reported on analgesic practice in paediatric AP. The studies included 658 patients (median age, 12 years; female sex, 57%; non‐biliary aetiology, 85.9%). Overall, analgesia was administered in 67% of patients, including opioids in 59.5% (43.8%–71.4%). Rates of acetaminophen (17.9% and 77.7%) and non‐steroidal anti‐inflammatory drugs (7.7% and 40.2%) were reported in two studies. Two studies reported reducing rates of opioid administration or reduced duration of opioid administration since 2017 and 2014, respectively. One study did not find any correlation between opioid administration and sociodemographic factors, length of stay or admission to intensive care units. No studies reported on complications or quality of life. No studies investigated non‐medical modalities. There were no long‐term data on analgesic use post‐discharge.ConclusionsOpioids are the mainstay of pain treatment in paediatric AP in North America. However, factors that influence the analgesic type, the impact of analgesic modality on the post‐pancreatitis outcome and long‐term analgesic use constitute a knowledge gap. Future studies are needed to inform analgesic use in paediatric AP.
Mechanism analysis of the differences in relieving constipation in a Balb/c constipation model mouse fed human milk probiotics or fermented milk
Authors: Zhao Baoyuan , Wang Yajuan , Wang Shengyuan , Mu Guangqing , Wu Xiaomeng 
Published: November 2024

AbstractBACKGROUNDConsumers require fermented milk that possesses constipation‐relieving functions. To cater to the ‘natural and additive‐free’ consumption habit, this study is dedicated to developing probiotic fermented milk with constipation‐relief effects. Previously, we isolated two Lactobacillus strains, Lactobacillus MWLp‐12 and Lactobacillus MWLf‐4, from breast milk. This study evaluated the efficacy of these strains and their fermented milk in alleviating constipation in a Balb/c mouse model of constipation. The evaluation criteria included fecal water content, time for first black feces expulsion and propulsion rate of the small intestine. The mechanisms of constipation relief were investigated using gastrointestinal regulatory peptides, colonic tissue pathology, short‐chain fatty acid levels and gut microbiota analyses.RESULTSFecal water content, time for first black feces expulsion and small intestine propulsion rate indicated that both MWLp‐12 and MWLf‐4, as well as their fermented milk, could alleviate constipation in mice. Fermented milk exhibited superior effectiveness for relieving constipation compared to that of the strains alone. The results related to gastrointestinal regulatory peptides and short‐chain fatty acids suggest that the mechanisms of constipation relief by the strains and their fermented milk may involve increased levels of 5‐hydroxytryptamine and substance P in the mouse serum, higher concentrations of short‐chain fatty acids in the intestines and decreased vasoactive intestinal peptide levels in the serum.CONCLUSIONMWLp‐12, MWLf‐4 and fermented milk relieve constipation in mice. © 2024 Society of Chemical Industry.
Dynamic changes in proanthocyanidin composition, biosynthesis, and histochemistry in spine grape (Vitis davidii Foëx) tissues during berry development
Authors: Yan Yinfang , Li Lin , Zheng Mingyuan , Duan Bingbing , Zhang Jiajing , Li Yashan , Liu Wei , Liu Xu 
Published: November 2024

AbstractBACKGROUNDSpine grapes are widely cultivated in southern China because of their strong adaptability to hot and humid climates. As a wild species native to China, spine grape (Vitis davidii Foëx) was studied as a resource of proanthocyanidins (PAs). PA composition, biosynthesis, and histochemistry in different tissues (skins, seeds, and stems) during berry development were analyzed in this study.RESULTSThe findings revealed that PA accumulation occurred in concurrence with flowering and was completed by veraison. High‐performance liquid chromatographic results showed that the epicatechin type was the most dominant. The skins were more likely to accumulate PA polymers. Reverse transcription–quantitative polymerase chain reaction analysis revealed that the expression levels of structural genes (flavonoid‐3′‐hydroxylase, flavonoid‐3′5′‐hydroxylase, dihydroflavonol 4‐reductase, leucoanthocyanidin reductase, and leucoanthocyanidin dioxygenase) were positively associated with PA dynamic changes. Histochemical results revealed that PAs in skins were mainly found in the hypodermis of the exocarp, PAs in seeds were mainly found in the middle layer of the outer integument of the testa, and PAs in stems were mainly found in the phloem.CONCLUSIONThis study provides a clear understanding of the spatial and temporal accumulation of PAs in spine grape, and forms a basis for the analysis of structural profiles and synthesis of PAs and their biological effects. © 2024 Society of Chemical Industry.
Mechanobullous form of epidermolysis bullosa acquisita: Insights into disease mechanisms as inferred by response to rituximab, but not to JAK inhibitors
Authors: Gueissaz L. , Junge A. , Wolf R. , Schlapbach C. , Feldmeyer L. , Borradori L. 
Published: November 2024

AbstractEpidermolysis bullosa acquisita (EBA) is a rare autoimmune blistering disease associated with IgG autoantibodies directed against type VII collagen. Different clinical forms have been described, including the classical mechanobullous variant resembling epidermolysis bullosa dystrophica, which is typically treatment‐resistant. We here describe a 67‐year‐old patient with a mechanobullous EBA characterized by trauma‐induced blisters on her hands and feet for 9 months. Despite treatments with oral prednisolone, topical steroids or calcineurin inhibitors, doxycycline, ciclosporin, and baracitinib, no improvement was observed. The patient went into complete remission only after administration of rituximab with no lesions off therapy at the 10‐month follow up. Our observation suggests that inflammatory cytokines are not primarily responsible for skin blistering and fragility in mechanobullous EBA. The effectiveness of rituximab provides some insights into the major direct role of autoantibodies in mediating dermo‐epidermal separation in this variant of EBA.