bluuebunny/crossref_metadata_2025 huggingface dataset:
Disparities in Cancer Screening Among the Foreign-Born Population in the United States: A Narrative Review
Authors: Rosowicz Andrew , Hewitt Daniel Brock
Published: February 2025

Background: The foreign-born population in the United States has reached a record high over the last three years. Significant disparities in cancer screening rates exist among this population, resulting in later-stage diagnoses and worse outcomes. This narrative review explores the sociodemographic factors, barriers, and interventions influencing cancer screening rates among foreign-born individuals in the U.S. Methods: A comprehensive review of studies was conducted to assess colorectal, cervical, and breast cancer screening disparities among immigrants. Factors examined include length of residence, race and ethnicity, income, education, citizenship, insurance, usual source of care, language, medical literacy, and cultural barriers. Furthermore, the effectiveness of educational interventions, patient navigators, and at-home testing in addressing these screening disparities was evaluated. Results: Immigrants have lower screening rates for colorectal, cervical, and breast cancer compared to U.S.-born individuals, with the largest disparities observed in colorectal cancer. Factors influencing these gaps include shorter duration of residence, Asian ethnicity, and lower income and education levels. Lack of health insurance and of a usual source of care are currently the most significant barriers to screening. Interventions such as education, patient navigation, and at-home testing have shown moderate success in improving screening rates, though data on their effectiveness remain limited. Conclusions: Addressing cancer screening disparities within the U.S. foreign-born population is essential, especially as the immigrant population continues to reach record numbers. Targeted interventions are needed to improve screening among immigrant groups with the lowest completion rates. Future research on these interventions should prioritize larger sample sizes, longitudinal studies, and the utility of new technologies such as artificial intelligence.
Molecular Insights into HR-HPV and HCMV Co-Presence in Cervical Cancer Development
Authors: Blanco Rancés , Muñoz Juan P.
Published: February 2025

Background: Cervical cancer remains a significant health concern worldwide and the primary cause of cancerous cervical lesions is the infection with high-risk human papillomavirus (HR-HPV). However, emerging evidence suggests that HR-HPV infection alone is insufficient for cancer development, and other co-factors may contribute to cervical carcinogenesis. Human cytomegalovirus (HCMV), a common herpesvirus frequently detected in cervical cancer samples, has demonstrated oncogenic potential. Objectives: This review aims to explore the molecular interactions between HR-HPV and HCMV in promoting cervical cancer progression. Methods. A comprehensive search was conducted in PubMed and Google Scholar, focusing on articles examining the role of HCMV in cervical tissues and/or cells, selected based on relevance and significance. Results: The reviewed literature indicates that HCMV and HR-HPV share several oncogenic mechanisms that could drive cervical cell transformation. Conclusions. Both viruses may synergistically promote cervical epithelial transformation and tumor progression in multiple ways. HR-HPV may facilitate HCMV entry by increasing host cell receptors essential for viral attachment. Additionally, HR-HPV and HCMV may cooperatively disrupt cellular processes, enhancing carcinogenesis. Both viruses may also modulate the local immune environment, enabling immune evasion and lesion persistence. However, further in vitro and in vivo studies are required to validate these hypotheses.
Advancing Immunotherapy in Pancreatic Cancer: A Brief Review of Emerging Adoptive Cell Therapies
Authors: Sherpally Deepak , Manne Ashish
Published: February 2025

Pancreatic cancer has the lowest 5-year survival rate (13%) among major cancers and is the third leading cause of cancer-related deaths in the United States. The high lethality of this cancer is attributed to its insidious onset, late-stage diagnosis, rapid progression, and limited treatment options. Addressing these challenges requires a deeper understanding of the complex tumor microenvironment to identify novel therapeutic targets. Newer approaches like adoptive cell therapy have shown remarkable success in treating hematological malignancies, but their application in solid tumors, particularly pancreatic cancer, is still in the early stages of development. ACT broadly involves isolating immune cells (T lymphocytes, Natural Killer cells, and macrophages) from the patient, followed by genetic engineering to enhance and mount a specific anti-tumor response. Various ACT modalities are under investigation for pancreatic cancer, including chimeric antigen receptor T cells (CAR-T), chimeric antigen receptor NK cells (CAR-NK), tumor-infiltrating lymphocytes (TIL), T-cell receptor (TCR)-engineered T cells, and cytokine-induced killer cells (CIK). Major hurdles have been identifying actionable tumor antigens and delivering focused cellular therapies to overcome the immunosuppressive and dense fibrotic stroma surrounding the pancreatic cancer. Further studies are needed to explore the limitations faced by cellular therapy in pancreatic cancer and identify novel combination treatment approaches in order to improve clinical outcomes.
Comparison of Survival Outcomes of Breast-Conserving Surgery Plus Radiotherapy with Mastectomy in Early Breast Cancer Patients: Less Is More?
Authors: Duangkaew Chularat , Somwangprasert Areewan , Watcharachan Kirati , Wongmaneerung Phanchaporn , Ko-iam Wasana , Kaweewan Issara , Ditsatham Chagkrit
Published: February 2025

Purpose: To compare the survival outcomes of early-stage breast cancer patients treated with breast-conserving therapy (BCT) and mastectomy. Method: This retrospective study includes 1330 early-stage breast cancer patients treated at Chiang Mai University (CMU) hospital, using data from the Chiang Mai Cancer Registry between 2004 and 2015. Information pertinent to patients and their treatment was collected for analysis. Time-to-event analysis was performed using Kaplan–Meier methods. Results: The baseline characteristics of 1330 patients showed significant differences between the BCT and mastectomy groups in terms of age, tumor size, and tumor location. BCT patients were younger, had smaller tumors, and exhibited less nodal involvement. Propensity score matching created a balanced cohort of 534 patients where differences persisted in age and tumor size. Univariate analysis revealed significant survival associations for BCT, younger age, and smaller tumor size. Multivariate analysis confirmed these factors, with BCT showing an adjusted hazard ratio (HR) of 0.58 (95% CI: 0.36–0.93; p = 0.023) compared to mastectomy. Kaplan–Meier survival analysis demonstrated a significant survival advantage for BCT, particularly in HER2-enriched and triple-negative subtypes. The 15-year overall survival was 80.01% in the BCT group versus 64.33% in the mastectomy group (p < 0.001). Conclusions: This study reveals key differences between outcomes following breast-conserving therapy (BCT) and mastectomy patients, including age and tumor characteristics. BCT showed improved overall survival, particularly in HER2-enriched and triple-negative breast cancers. However, our study’s limitations may affect the results. These findings suggest that BCT may offer survival benefits for specific subtypes, highlighting the importance of personalized treatment approaches.
Aggressive Serous Carcinomas of the Female Reproductive Tract: Cancer-Prone Cell States and Genetic Drivers
Authors: Phuong Daryl J. , Pirtz Matalin G. , Ralston Coulter Q. , Cosgrove Benjamin D. , Schimenti John C. , Flesken-Nikitin Andrea , Nikitin Alexander Yu.
Published: February 2025

In 2025, gynecological cancers are projected to account for approximately 10% of cancer-related deaths in women. High-grade serous ovarian carcinoma (HGSC) and serous endometrial carcinoma (SEC) are the most lethal gynecological cancer subtypes. Both malignancies commonly have TP53 mutations, alterations of the RB1 pathway, and numerous secondary mutations. Both carcinoma types consist of poorly differentiated and highly heterogeneous cell populations at the time of detection. Latent development and rapid progression of HGSC and SEC impede the identification of definitive cells of origin and genetic drivers. Here, we review our current knowledge about cancer-prone cell states and genetic drivers. We also discuss how emerging transcriptomic and genetic tools applied to contemporary model systems may facilitate the identification of novel targets for timely detection and therapeutic intervention.
The Role of MRI Radiomics Using T2-Weighted Images and the Apparent Diffusion Coefficient Map for Discriminating Between Warthin’s Tumors and Malignant Parotid Gland Tumors
Authors: Donci Delia Doris , Solomon Carolina , Băciuț Mihaela , Dinu Cristian , Stoia Sebastian , Rusu Georgeta Mihaela , Csutak Csaba , Lenghel Lavinia Manuela , Ciurea Anca
Published: February 2025

Background/Objectives: Differentiating between benign and malignant parotid gland tumors (PGT) is essential for establishing the treatment strategy, which is greatly influenced by the tumor’s histology. The objective of this study was to evaluate the role of MRI-based radiomics in the differentiation between Warthin’s tumors (WT) and malignant tumors (MT), two entities that proved to present overlapping imaging features on conventional and functional MRI sequences. Methods: In this retrospective study, a total of 106 PGT (66 WT, 40 MT) with confirmed histology were eligible for radiomic analysis, which were randomly split into a training group (79 PGT; 49 WT; 30 MT) and a testing group (27 PGT; 17 WT, 10 MT). The radiomic features were extracted from 3D segmentations of PGT performed on the following sequences: PROPELLER T2-weighted images and the ADC map, using a dedicated software. First- and second-order features were derived for each lesion, using original and filtered images. Results: After employing several feature reduction techniques, including LASSO regression, three final radiomic parameters were identified to be the most significant in distinguishing between the two studied groups, with fair AUC values that ranged between 0.703 and 0.767. All three radiomic features were used to construct a Radiomic Score that presented the highest diagnostic performance in distinguishing between WT and MT, achieving an AUC of 0.785 in the training set, and 0.741 in the testing set. Conclusions: MRI-based radiomic features have the potential to serve as promising novel imaging biomarkers for discriminating between Warthin’s tumors and malignant tumors in the parotid gland. Nevertheless, it is still to prove how radiomic features can consistently achieve higher diagnostic performance, and if they can outperform alternative imaging methods, ideally in larger, multicentric studies.
Emerging Roles for Transcription Factors During Mitosis
Authors: Flashner Samuel , Azizkhan-Clifford Jane
Published: February 2025

The genome is dynamically reorganized, partitioned, and divided during mitosis. Despite their role in organizing interphase chromatin, transcription factors were largely believed to be mitotic spectators evicted from chromatin during mitosis, only able to reestablish their position on DNA upon entry into G1. However, a panoply of evidence now contradicts this early belief. Numerous transcription factors are now known to remain active during mitosis to achieve diverse purposes, including chromosome condensation, regulation of the centromere/kinetochore function, and control of centrosome homeostasis. Inactivation of transcription factors during mitosis results in chromosome segregation errors, key features of cancer. Moreover, active transcription and the production of centromere-derived transcripts during mitosis are also known to play key roles in maintaining chromosomal stability. Finally, many transcription factors are associated with chromosomal instability through poorly defined mechanisms. Herein, we will review the emerging roles of transcription factors and transcription during mitosis with a focus on their role in promoting the faithful segregation of sister chromatids.
Examples of the Superiority of Ionic Liquids and Deep Eutectic Solvents over Aqueous Solutions in Electrodeposition Processes
Authors: Bakkar Ashraf
Published: February 2025

The current electrolytes used for metal electrodeposition mostly use aqueous solutions that limit the range and quality of possible coatings. Also, some of these solutions may contain toxic and corrosive chemicals. Thus, the importance of ionic liquids (ILs) and deep eutectic solvents (DES) becomes clear, as they can be used as green non-aqueous electrolytes for the electrodeposition of a range of reactive metals that are impossible to deposit in aqueous solutions and for the improved electrodeposition of metals that are deposable in aqueous solutions. This paper presents some examples of electrodeposition in ILs and DESs that are considered specific processes. Aluminum, as an active metal that it is impossible to electrodeposit in aqueous solution, was electrodeposited from a chloroaluminate IL. Moreover, the electrodeposition of Al was carried out in open air using a novel approach. Chromium was electrodeposited from a DES containing the environmentally friendly form of Cr (III) instead of toxic Cr (VI). Magnesium alloys, as water-sensitive substrates, were electroplated in an air and water-stable DES. Also, this paper discloses, for the first time, the procedure of pretreatment of Mg alloys for successful electroplating.
The HEARRT-C Score: Is Aspirin Protective in COVID-19 Patients? A Single-Centre Retrospective Study
Authors: Kumral Zeynep , Canturk Ali , Baskurt Ahmet Anil , Taylan Abdullah , Colak Ayse , Badak Ozer
Published: February 2025

This study aimed to develop a scoring system to predict mortality risk in hospitalised COVID-19 patients using clinical, laboratory, and imaging data. A retrospective analysis was conducted at a single centre, including 325 patients admitted between March 2020 and December 2021. The data collected included patient demographics, laboratory results, medications, and thoracic CT images. Pulmonary involvement was assessed using the CO-RADS classification, while coronary artery calcification (CAC), aortic calcification, and epicardial adipose tissue were evaluated with specific scoring methods. Mortality predictors were identified through univariate and multivariate Cox proportional hazards models. The key mortality predictors identified in this study were an age above 67 years, elevated high-sensitivity troponin levels, a heart rate greater than 100 bpm, an oxygen saturation below 90%, the presence of CAC and aortic calcification, low haemoglobin levels, and the absence of acetylsalicylic acid (ASA) use at admission. The developed HEARRT-C scoring system demonstrated a strong predictive ability, with an area under the curve (AUC) of 0.91, showing 81% sensitivity and 86% specificity for predicting mortality. This study concluded that the HEARRT-C score is an effective tool for early risk stratification in COVID-19 patients, which may guide management decisions and emphasise the importance of cardiovascular factors and the potential protective role of ASA.
Comparison of Ultrasonic Nonlinear Beamforming Algorithms for Defect Imaging in Crystalline Particle-Filled Explosives
Authors: Yu Lida , Li Haining
Published: February 2025

Ultrasonic imaging methods show significant advantages in detecting internal defects of composite crystalline materials. For polymer-bonded explosives (PBXs) with highly filled crystalline particles, the strong acoustic attenuation caused by their heterogeneous crystalline structure leads to low signal-to-noise ratios (SNRs) in the full matrix capture (FMC) signals and strong background noise in reconstructed images. To realize the high-SNR imaging of defects in PBXs, this paper is the first to schematically reorganize the nonlinear post-process algorithms which have the potential to realize high-SNR imaging of defects in crystalline particle-filled explosives. Six kinds of beamforming algorithms (DAS, F-DMAS, BB-DMAS, DMAS3, L-DMAS, and DS-DMAS) were applied to the same FMC data to reconstruct the images of prefabricated side-drilled holes (SDHs) in PBXs. The image quality in terms of SNR, lateral and axial resolution, and calculation efficiency was compared and evaluated quantitatively. The experimental results show that the nonlinear beamforming algorithms showed significant improvements in SNR and resolution. In particular, L-DMAS and DS-DMAS exhibited excellent imaging capability in SDH defect detection compared to the other algorithms, with effective suppression of crystalline structural noise.
Long-Term Durability of Bilateral Two-Level Stellate Ganglion Blocks in Posttraumatic Stress Disorder: A Six-Month Retrospective Analysis
Authors: Mulvaney Sean W. , Mahadevan Sanjay , Dineen Kyle J. , Desronvilles Roosevelt , Rae Olmsted Kristine L.
Published: February 2025

Posttraumatic stress disorder (PTSD) is a common neuropsychiatric condition with a complex etiology. Stellate Ganglion Block (SGB) is a novel but well-observed procedure for treating the disorder. However, the long-term durability of SGB has yet to be established. The primary objective of this study was to determine if performing ultrasound-guided, bilateral, two-level cervical sympathetic chain block (2LCSB) is associated with PTSD symptom improvement across six months. A secondary objective was to characterize treatment effects between trauma types. A retrospective chart review was conducted, and 75 patients meeting inclusion and exclusion criteria were identified. Posttraumatic stress disorder checklist for DSM-5 (PCL-5) scores were collected throughout a six-month period post-procedure. In addition, patients were asked to identify the category of trauma associated with their PTSD diagnosis. Nearly all (96%) patients showed significant improvement in their PCL-5 scores between the baseline and six months, with an average improvement of 55.48%. This is the first study to be conducted that examines the effects associated with SGB over a time period of greater than one month. Bilateral 2LCSB may provide durable PTSD symptom improvement for six months. However, additional research is necessary to establish causality.
Immune Checkpoint Blockade Response in Mucinous Tubular and Spindle Cell Carcinoma
Authors: Makker Simran , Shah Neil J. , Carlo Maria I. , Kuo Fengshen , Hakimi A. Ari , Chen Ying-Bei , Iyer Gopa , Kotecha Ritesh R.
Published: February 2025

Mucinous tubular and spindle cell carcinoma (MTSCC) is a rare kidney tumor which is usually characterized by indolent disease physiology. While several high-grade and sarcomatoid MTSCC tumors have been reported, the clinical experience with contemporary immune checkpoint blockade (ICB) combination therapies extrapolated from treatment paradigms of conventional renal cell carcinoma (RCC) remains limited. Here, we report two patients with metastatic MTSCC treated with first-line ipilimumab plus nivolumab therapy who both achieved great clinical benefit. We subsequently performed immune deconvolution analysis on previously identified MTSCC-like kidney tumors from The Cancer Genome Atlas (TCGA) and discovered significantly higher PD-L1 transcriptomic expression compared to similar papillary RCC tumors, providing additional biomarker data supporting the observed ICB response. These data implicate ICB therapy as an effective treatment for patients with metastatic MTSCC.
Histologic and Immunohistochemical Patterns in Lymphomatoid Papulosis: A Systematic Review of Published Cases
Authors: Fricke Torben , Kempf Werner , Schön Michael P. , Mitteldorf Christina
Published: February 2025

Based on histologic and genetic patterns, the current World Health Organization (WHO) classification distinguishes six subtypes of lymphomatoid papulosis (Lyp). The aim of our article was to analyze the frequency of histologic and immunohistochemical features of different Lyp subtypes reported in the literature. We used PubMed advanced search builder to systematically review and evaluate English and German literature of Lyp from 1968 to April 2022. We considered only papers in which histopathologic features were mentioned in detail. We identified 48 publications with a total of 518 cases. The diagnoses were based on the diagnostic criteria at the time of publication. In Lyp A and Lyp B a CD8+ phenotype was more often reported than expected (53% and 52%, respectively). A double positive phenotype (CD4+/CD8+) was found in 28% of Lyp E and a double negative (CD4-/CD8-) in 50% of Lyp with 6p25.3 rearrangement. High rates of folliculo- and syringotropism were reported in both Lyp A and B. Surprisingly, strong epidermotropism occurred in 20/38 (53%) cases reported as Lyp B and in 43/64 (67%) of Lyp D cases. The predominating phenotype in Lyp D was CD8+, while TIA-1/granzymeB/perforin expression was reported in 37/46 (80%), and CD56 was expressed in 13/47 (28%) of the investigated cases. The limitation of the data is due to the retrospective approach with diagnostic criteria changing over time and on a case selection in some publications. However, the data indicate that the Lyp subtypes overlap more than assumed. They also show that a prospective study is needed to obtain valid data on the frequency distribution of certain histopathologic criteria.
Design and Performance Evaluation of Batch Reactor for Biomass Valorization: LHW Valorization of Coffee and Peapod Waste
Authors: Ramírez Cabrera Paula Andrea , Lozano Pérez Alejandra Sophia , Guerrero Fajardo Carlos Alberto
Published: February 2025

This study presents the design, fabrication, and performance evaluation of a batch reactor for the hydrothermal valorization of coffee and peapod waste biomass. The reactor, designed using Inventor 2023 and analyzed using ANSYS 2023, is capable of operating at elevated temperatures to facilitate the breakdown of lignocellulosic structures and promote the extraction of valuable platform chemicals. Based on the design, the reactor was manufactured, and a set of experiments was performed to test it at different temperatures ranging from 120 to 180 °C, at different times (1–4 h) and with different types of biomass (peapods and coffee cherry waste). The results demonstrate the effectiveness of the reactor in optimizing the conversion of agricultural waste into key compounds such as hydroxymethylfurfural (HMF) and furfural. For peapod biomass, optimal conditions were identified at temperatures between 150 °C and 180 °C, with a reaction time of approximately 1 h yielding up to 72.17%wt total platform chemicals. Coffee cherry biomass showed a different yield profile, with total platform chemical yields reaching 23.56%wt at 180 °C after 4 h of treatment, highlighting the importance of feedstock-specific optimization. The reactor’s performance indicates its potential for broader applications in the conversion of various lignocellulosic feedstocks into high-value chemicals, contributing to a more sustainable and circular economy. The presented design and analysis demonstrate the reactor’s compliance with necessary characteristics such as temperature, deformation, and stress, ensuring its suitability for the experiments. This study showcases the importance of innovative reactor design in advancing sustainable chemical production from biomass waste, making it a valuable contribution to the field of waste-to-value conversion technologies.
Evaluation of the HIV-1 Rapid Recency Assay and Limiting Antigen Avidity Enzyme Immunoassay for HIV Infection Status Interpretation in Long-Term Diagnosed Individuals in Thailand
Authors: Suparak Supaporn , Unpol Petai , Ngueanchanthong Kanokwan , Jomjunyoung Siriphailin , Thanyacharern Wipawee , Chisholm Sirilada Pimpa , Smanthong Nitis , Yingyong Thitipong , Okada Pilailuk Akkapaiboon
Published: February 2025

Background/Objectives: Accurate surveillance of recent HIV infections is crucial for effective epidemic control and timely intervention. The Limited Antigen Avidity Enzyme Immunoassay (LAg-EIA) allows precise differentiation between recent and long-term HIV infections. To enhance accessibility, it has been developted into a point-of-care test, the Asanté™ HIV-1 Rapid Recency® Assay (ARRA), a rapid immunoassay. This study evaluated the performance and false recent rates (FRRs) of the ARRA, interpreted both visually and via a strip reader, in comparison with the LAg-EIA. Methods: Plasma samples were collected from two groups: 634 long-term HIV-infected individuals, identified through routine diagnostic testing, who had not received antiretroviral therapy for over one year, and 224 individuals from high-risk populations. High-risk individuals, including pregnant women, female sex workers, and men who have sex with men, were selected based on behavioral and demographic risk factors. Concordance between the ARRA and LAg-EIA was assessed, and FRRs were calculated for both assays. McNemar’s test was used to evaluate agreement, while Spearman’s rho was applied to assess correlation between the two methods. Results: Visual interpretation of ARRA demonstrated perfect agreement with LAg-Avidity EIA results (FRR = 0.00%), while the strip reader misclassified two specimens as recent infections (FRR = 0.32%). McNemar’s test indicated no significant differences between the methods (p > 0.05). Moderate agreement (Spearman’s rho = 0.434) was observed between ARRA strip reader results and LAg-Avidity EIA optical density values. Among high-risk populations, ARRA misclassified one sample as recent, resulting in an inconsistency rate of 0.45%. Conclusions: This study highlights ARRA’s reliability in identifying long-term infections and its potential as a point-of-care tool. Its rapid results and ease of use make it a valuable asset for effective HIV surveillance, facilitating targeted epidemic monitoring and enhancing public health interventions.
Distinct Phenotypic and Molecular Characteristics of CD34− and CD34+ Hematopoietic Stem/Progenitor Cell Subsets in Cord Blood and Bone Marrow Samples: Implications for Clinical Applications
Authors: Gaafar Ameera , Hamza Fatheia Nabeil , Yousif Rama , Shinwari Zakia , Alotaibi Aminah Ghazi , Iqniebi Alia , Al-Hussein Khalid , Al-Mazrou Amer , Manogaran Pulicat Subramanian , Elhassan Tusneem , Marquez-Méndez Marcela , Aljurf Mahmood , Al-Humaidan Hind , Alaiya Ayodele
Published: February 2025

Background/Objectives: We aimed to identify the molecular signatures of primitive CD34+ and CD34− hematopoietic stem/progenitor cell (HSC/HPC) subsets in cord blood and bone marrow samples. Methods: CD34+ and CD34− HSC/HPC subsets from cord blood and bone marrow were characterized using flow cytometry, real-time PCR, and proteomic analysis to evaluate their phenotypic and molecular profiles. Results: Our findings revealed a significantly higher percentage of Lin−CD34−CD38Low/− (−/−) cells than of Lin−CD34+CD38Low/− (+/−) cells in cord blood. Aldehyde dehydrogenase levels were significantly lower in (−/−) than in (+/−) cells. Clonogenic ability was lower in (−/−) than in (+/−) cells. However, CD34− cells exhibited potent megakaryocyte/erythrocyte differentiation ability. Importantly, the HSC/HPC subsets expressed pluripotency or stemness genes (SOX2, Nanog, and OCT4); however, OCT4 expression significantly increased in (−/−) compared with (+/−) cells. We identified 304 proteins in the HSC/HPC subsets—85.6% had similar expression patterns in the two subsets; only 14.4% were differentially expressed between (−/−) and (+/−) cells. This implies their comparability at the protein level. Certain proteins were implicated in cellular-development-, gene-expression-, and embryonic-development-related signaling networks. Conclusions: Distinct biological and functional characteristics were observed between (−/−) and (+/−) HSC/HPC subsets. Some of the identified proteins may be novel HSC/HPC subsets markers for clinical applications after validation.
Immediate Implant Therapy with Full-Digital Workflow to Replace a Central Incisor
Authors: Garcia-Torres Francisco , Jurado Carlos A. , Rojas-Rueda Silvia , Conner Clint , Mohamed Ali Abulkasim , Azpiazu-Flores Francisco X.
Published: February 2025

Background: Replacing a maxillary central incisor and immediately placing an implant represents a clinical challenge. Methods: This case report demonstrates a full digital workflow to achieve a predictable implant placement and esthetically pleasing restoration for a 35-year-old male patient who suffered a horizontal root fracture after a sports accident. The patient’s treatment included digital implant planning, minimally traumatic tooth extraction, computer-guided implant placement, soft tissue augmentation, and a provisional restoration to contour the augmented gingival tissues. The process began with cone beam computed tomography (CBCT) evaluation and patient consultation on treatment options, with the patient opting for implant therapy. Using a 3D-printed surgical guide, the implant was placed precisely, and a soft tissue graft was used to enhance the gingival architecture and volume. A provisional restoration was designed to support the emergence profile and condition the peri implant soft tissues. A final digital impression was made, and a screw-retained all-ceramic crown was fabricated uneventfully after healing. Results: This digital approach allowed accurate planning and allowed the efficient execution of a technique-sensitive procedure such as immediate implant placement, thus providing an esthetic and functional solution while minimizing treatment time. Conclusions: The case highlights that immediate implant therapy in the esthetic zone requires meticulous planning and execution, and that incorporating advanced digital tools and techniques is required to achieve favorable clinical outcomes.
Research on the Effects of Carbon Emissions from China’s Technology Transfer: Domestic and International Perspectives
Authors: Wei Ling , Zeng Bing
Published: February 2025

Technology transfer represents a critical avenue for addressing the challenges associated with carbon emission reduction, warranting thorough investigation into the effects of both domestic and international technology transfer on carbon emissions. This study employs data mining techniques to extract comprehensive data on patent transfers across 334 prefecture-level cities in China from 2000 to 2021, analyzing the influence of technology transfer on carbon emissions from both domestic and international perspectives. The findings indicate that domestic technology transfer and international technology transfer significantly contribute to carbon emission reduction, with international technology transfer exerting a more substantial effect than its domestic counterpart. To mitigate endogeneity concerns, the study utilizes the shortest distance from each city to the telegraph lines established during the late Qing Dynasty as an instrumental variable and the resulting conclusions remain robust. Heterogeneity tests reveal significant regional disparities, particularly in areas located southeast and northwest of the Hu Huanyong line, as well as between regions inside and outside the five major urban agglomerations. The mechanisms underlying carbon reduction suggest that improvements in energy efficiency and upgrades in industrial structure serve as the primary pathways for carbon emission reductions resulting from both domestic and foreign technology transfers. These conclusions provide a theoretical foundation and empirical insights to facilitate the acceleration of technology flow within the context of high-quality development, particularly concerning environmental protection.
Advancing Logic-Driven and Complex Event Perception Frameworks for Entity Alignment in Knowledge Graphs
Authors: Zeng Yajian , Hou Xiaorong , Wang Xinrui , Li Junying
Published: February 2025

Entity alignment in knowledge graphs plays a crucial role in ensuring the consistency and integration of data across different domains. For example, in power topology, accurate entity matching is essential for optimizing system design and control. However, traditional approaches to entity alignment often rely heavily on language models to extract general features, which can overlook important logical aspects such as temporal and event-centric relationships that are crucial for precise alignment.To address this issue, we propose EAL (Entity Alignment with Logical Capturing), a novel and lightweight RNN-based framework designed to enhance logical feature learning in entity alignment tasks. EAL introduces a logical paradigm learning module that effectively models complex-event relationships, capturing structured and context-aware logical patterns that are essential for alignment. This module encodes logical dependencies between entities to dynamically capture both local and global temporal-event interactions. Additionally, we integrate an adaptive logical attention mechanism that prioritizes influential logical features based on task-specific contexts, ensuring the extracted features are both relevant and discriminative. EAL also incorporates a key feature alignment framework that emphasizes critical event-centric logical structures. This framework employs a hierarchical feature aggregation strategy combining low-level information on temporal events with high-level semantic patterns, enabling robust entity matching while maintaining computational efficiency. By leveraging a multi-stage alignment process, EAL iteratively refines alignment predictions, optimizing both precision and recall. Experimental results on benchmark datasets demonstrate the effectiveness and robustness of EAL, which not only achieves superior performance in entity alignment tasks but also provides a lightweight yet powerful solution that reduces reliance on large language models.
Simultaneous Localization of Two Talkers Placed in an Area Surrounded by Asynchronous Six-Microphone Arrays
Authors: Takahashi Toru , Kanbayashi Taiki , Nakayama Masato
Published: February 2025

If we can understand dialogue activities, it will be possible to know the role of each person in the discussion, and it will be possible to provide basic materials for formulating facilitation strategies. This understanding can be expected to be used for business negotiations, group work, active learning, etc. To develop a system that can monitor speech activity over a wide range of areas, we propose a method for detecting multiple acoustic events and localizing sound sources using an asynchronous distributed microphone array arranged in a regular hexagonal repeating structure. In contrast to conventional methods based on sound source direction using triangulation with microphone arrays, we propose a method for detecting acoustic events and determining sound sources from local maximum positions based on estimation of the spatial energy distribution inside the observation space. We evaluated the conventional method and the proposed method in an experimental environment in which a dialogue between two people was simulated under 22,104 conditions by using the sound source signal convolving the measured impulse response.We found that the performance changes depending on the selection of the microphone array used for estimation. Our finding is that it is best to choose five microphone arrays close to the evaluation position.
A Content-Aware Method for Detecting External-Force-Damage Objects on Transmission Lines
Authors: Liu Min , Chen Ming , Wu Benhui , Wu Minghu , Wang Juan , Wang Jianda , Hu Hengbo , Ye Yonggang
Published: February 2025

The security of ultra-high-voltage (UHV) overhead transmission lines is frequently threatened by diverse external-force damages. As real-world transmission line scenarios are complex and external-force-damage objects exhibit varying scales, deep learning-based object detection methods necessitate the capture of multi-scale information. However, the downsampling and upsampling operations employed to learn multi-scale features work locally, resulting in the loss of details and boundaries, which makes it difficult to accurately locate external-force-damage objects. To address this issue, this paper proposes a content-aware method based on the generalized efficient layer aggregation network (GELAN) framework. A newly designed content-aware downsampling module (CADM) and content-aware upsampling module (CAUM) were integrated to optimize the operations with global receptive information. CADM and CAUM were embedded into the GELAN detection framework, providing a new content-aware method with improved cost accuracy trade-off. To validate the method, a large-scale dataset of external-force damages on transmission lines with complex backgrounds and diverse lighting was constructed. The experimental results demonstrate the proposed method’s superior performance, achieving 96.50% mean average precision (mAP) on the transmission line dataset and 91.20% mAP on the pattern analysis, statical modeling and computational learning visual object classes (PASCAL VOC) dataset.
KeypointNet: An Efficient Deep Learning Model with Multi-View Recognition Capability for Sitting Posture Recognition
Authors: Cao Zheng , Wu Xuan , Wu Chunguo , Jiao Shuyang , Xiao Yubin , Zhang Yu , Zhou You
Published: February 2025

Numerous studies leverage pose estimation to extract human keypoint data and then classify sitting postures. However, employing neural networks for direct keypoint classification often yields suboptimal results. Alternatively, modeling keypoints into other data representations before classification introduces redundant information and substantially increases inference time. In addition, most existing methods perform well only under a single fixed viewpoint, limiting their applicability in complex real-world scenarios involving unseen viewpoints. To better address the first limitation, we propose KeypointNet, which employs a decoupled feature extraction strategy consisting of a Keypoint Feature Extraction module and a Multi-Scale Feature Extraction module. In addition, to enhance multi-view recognition capability, we propose the Multi-View Simulation (MVS) algorithm, which augments the viewpoint information by first rotating keypoints and then repositioning the camera. Simultaneously, we propose the multi-view sitting posture (MVSP) dataset, designed to simulate diverse real-world viewpoints. The experimental results demonstrate that KeypointNet outperforms the other state-of-the-art methods on both the proposed MVSP dataset and the other public datasets, while maintaining a lightweight and efficient design. Ablation studies demonstrate the effectiveness of MVS and all KeypointNet modules. Furthermore, additional experiments highlight the superior generalization, small-sample learning capability, and robustness to unseen viewpoints of KeypointNet.
Integrating Classification and Regression Tree Algorithm for Operational Optimization in AC-DC Hybrid Power System Planning: A Novel Approach
Authors: Yang Yuyao , Zhang Boyuan , Zhang Jun , Gong Guoxian , Pan Feng , Feng Lei , Zheng Yi , Wang Peng
Published: February 2025

The increasing demand for electricity and the imperatives of climate change have made the optimization of power system planning critical for the energy transition and grid efficiency. This study presents an innovative planning method for inter-regional AC-DC hybrid power systems, leveraging the Classification and Regression Tree (CART) algorithm to optimize the operational characteristics of direct current (DC) channels. By designing a closed-loop iteration, precise operational constraints are considered by the CART algorithm, which immerged into the planning model to achieve safe and economic optimization. Based on the empirical analysis of the HRP-38 system, this study concludes that the CART algorithm offers a constructive approach to managing the operational complexities of modern power grids. By optimizing and refining DC operational characteristics based on actual system requirements, the algorithm contributes to improvements in safety, economic efficiency, and environmental sustainability within the confines of the HRP-38 node system. Consequently, the effectiveness of the CART optimization approach could be corroborated. Meanwhile, this study also acknowledges the limitations in generalizing these results to other power grid configurations and the need for further exploration in developing environmentally conscious planning methods.
Development of a Comprehensive Model for Drying Optimization and Moisture Management in Power Transformer Manufacturing
Authors: Brahami Youssouf , Betie Amidou , Meghnefi Fethi , Fofana Issouf , Yeo Zié
Published: February 2025

The presence of moisture in the insulation of power transformers accelerates the degradation of both paper and oil, thereby increasing the risk of unexpected failures. Due to the hygroscopic nature of cellulose, the insulation can retain up to 8% moisture after the transformer manufacturing process. Reducing this moisture content is crucial in extending the operational lifespan of transformers. The drying cycle of paper insulation is a critical step in power transformer manufacturing, directly influencing the insulation’s longevity and overall performance. This paper introduces a nomogram that combines degradation and drying models, enabling the precise optimization of the drying process based on various parameters such as the temperature, paper mass, and extraction rate. The results of this study demonstrate that for a given extraction rate threshold, the required drying time can be determined based on the mass of paper to be dried, the drying temperature, and the degree of paper degradation (degree of polymerization). These predictive tools are essential for engineers and researchers aiming to enhance transformer reliability.
Dynamic NOx Emission Modeling in a Utility Circulating Fluidized Bed Boiler Considering Denoising and Multi-Frequency Domain Information
Authors: Li Qianyu , Wang Guanglong , Li Xian , Bao Qing , Li Wei , Zhu Yukun , Yu Cong , Ma Huan
Published: February 2025

Climate change poses a significant global challenge that necessitates concerted efforts toward carbon neutrality. Circulating fluidized bed (CFB) boilers have gained prominence in various industries due to their adaptability and reduced emissions. However, many current control systems rely heavily on manual operator intervention and lack advanced automation, which constrains the operational efficiency. This study addressed the need for dynamic models capable of monitoring and optimizing NOx emissions in CFB boilers, especially under fluctuating loads and strict regulatory standards. We introduced the TimesNet model, which utilizes fast Fourier transform (FFT) to extract key frequency components, transforming 1D time series data into 2D tensors for enhanced feature representation. The model employs Inception blocks for multi-scale feature extraction and incorporates residual connections with amplitude-weighted aggregation to mitigate catastrophic forgetting during training. The results indicated that TimesNet achieved R2 values of 0.98, 0.97, and 0.95 across training, validation, and testing datasets, respectively, surpassing conventional models with a reduced MAE of 1.63 mg/m3 and RMSE of 3.35 mg/m3. Additionally, it excelled in multi-step predictions and effectively managed long-term dependencies. In conclusion, TimesNet provides an innovative solution for the precise monitoring of NOx emissions in CFB boilers by enhancing predictive stability and robustness and addressing salient limitations in existing models to optimize combustion efficiency and regulatory compliance.
Bridging Technical Challenges and Economic Goals: Project Management for Energy Transition in Maritime Retrofitting
Authors: Lyridis Dimitrios , Kostidi Evanthia
Published: February 2025

The maritime industry, a cornerstone of global trade, faces mounting pressure to decarbonize and align with international greenhouse gas (GHG) reduction targets set by the International Maritime Organization (IMO). This study investigates how project management frameworks and techno-economic analysis (TEA) can jointly address the technical, economic, and strategic challenges of retrofitting maritime vessels for alternative fuels. A mixed-methods approach was employed, combining systematic literature synthesis, case study analysis, and theoretical modeling. Key findings highlight the pivotal role of project management in mitigating retrofitting risks, optimizing lifecycle costs, and aligning retrofitting projects with organizational objectives, including sustainability and regulatory compliance. The study also identifies best practices, such as leveraging interdisciplinary collaboration and smart energy management systems, to enhance retrofitting outcomes. By integrating TEA with project management, the research contributes actionable insights to advance the maritime industry’s energy transition and decarbonization efforts.
Development and Performance Evaluation of a Hybrid AI-Based Method for Defects Detection in Photovoltaic Systems
Authors: Thakfan Ali , Bin Salamah Yasser
Published: February 2025

Maintenance and monitoring of solar photovoltaic (PV) systems are essential for enhancing reliability, extending lifespan, and maintaining efficiency. Some defects in PV cells cannot be detected through output measurements due to the string configuration of interconnected cells. Inspection methods such as thermal imaging, electroluminescence, and photoluminescence are commonly used for fault detection. Among these, thermal imaging is widely adopted for diagnosing PV modules due to its rapid procedure, affordability, and reliability in identifying defects. Similarly, current–voltage (I-V) curve analysis provides valuable insights into the electrical performance of solar cells, offering critical information on potential defects and operational inconsistencies. Different data types can be effectively managed and analyzed using artificial intelligence (AI) algorithms, enabling accurate predictions and automated processing. This paper presents the development of a machine learning algorithm utilizing transfer learning, with thermal imaging and I-V curves as dual and single inputs, to validate its effectiveness in detecting faults in PV cells at King Saud University, Riyadh. Findings demonstrate that integrating thermal images with I-V curve data significantly enhances defect detection by capturing both surface-level and performance-based information, achieving an accuracy and recall of more than 98% for both dual and single inputs. The approach reduces resource requirements while improving fault detection accuracy. With further development, this hybrid method holds the potential to provide a more comprehensive diagnostic solution, improving system performance assessments and enabling the adoption of proactive maintenance strategies, with promising prospects for large-scale solar plant implementation.
Multi-Criteria Analysis for Integrating Renewable Energy Solutions in the Restoration of Surface Waters—Selected Lakes Case Study
Authors: Boguniewicz-Zabłocka Joanna , Łukasiewicz Ewelina
Published: February 2025

The protection and reclamation of surface waters, particularly lakes, necessitates the implementation of novel approaches that effectively integrate natural biological processes with sophisticated technological solutions. This paper examines the potential of bioremediation techniques utilising artificial aeration systems, with renewable energy sources serving as a viable power source. The objective of the analysis is to enhance the sustainability of the remediation of aquatic ecosystems. A multi-criteria analysis (MCA) was employed to evaluate the performance and environmental impact of the selected methods. Based on the results of the MCA, the SHPP (small hydro power plant) technology achieved the highest score for both lakes, 0.85 and 0.78, respectively, making it the optimal technology. In comparison, wind energy scored around 0.5 and photovoltaic (PV) around 0.6, showing a poorer fit with local conditions. By integrating reclamation with renewable energy applications, this research presents a strategy for developing more resilient and environmentally sound water management strategies.