bluuebunny/crossref_metadata_2025 huggingface dataset:
Epigenetic Mechanisms in the Transcriptional Regulation of Circadian Rhythm in Mammals
Authors: Mao Wei , Ge Xingnan , Chen Qianping , Li Jia-Da
Published: January 2025

Almost all organisms, from the simplest bacteria to advanced mammals, havea near 24 h circadian rhythm. Circadian rhythms are highly conserved across different life forms and are regulated by circadian genes as well as by related transcription factors. Transcription factors are fundamental to circadian rhythms, influencing gene expression, behavior in plants and animals, and human diseases. This review examines the foundational research on transcriptional regulation of circadian rhythms, emphasizing histone modifications, chromatin remodeling, and Pol II pausing control. These studies have enhanced our understanding of transcriptional regulation within biological circadian rhythms and the importance of circadian biology in human health. Finally, we summarize the progress and challenges in these three areas of regulation to move the field forward.
Caffeic Acid Phenethyl Ester Protects Neurons Against Oxidative Stress and Neurodegeneration During Traumatic Brain Injury
Authors: Sulimai Nurul , Brown Jason , Lominadze David
Published: January 2025

Traumatic brain injury (TBI) is an inflammatory disease causing neurodegeneration. One of the consequences of inflammation is an elevated blood level of fibrinogen (Fg). Earlier we found that extravasated Fg induced an increased expression of neuronal nuclear factor kappa B (NF-κB) p65. In the present study, we aimed to evaluate the effect of caffeic acid phenethyl ester (CAPE), an inhibitor of NF-κB, on Fg-induced neurodegeneration in vitro and in mice with mild-to-moderate TBI. Primary mouse brain cortical neurons were treated with Fg (0.5 or 1 mg/mL) in the presence or absence of CAPE. A cortical contusion injury -induced model of TBI in C57BL/6 mice was used. Mice were treated with CAPE for two weeks. The generation of reactive oxygen species (ROS) and neuronal viability were assessed. Mice memory was assessed using novel object recognition and contextual fear conditioning tests. The generation of ROS and viability of neurons in vitro and in the brain samples were assessed. Data showed that CAPE attenuated the Fg-induced generation of ROS and neuronal death. CAPE improved the cognitive function of the mice with TBI. The results suggest that Fg-induced generation of ROS could be a mechanism involved in cognitive impairment and that CAPE can offer protection against oxidative damage and neurodegeneration.
Measures of Joint Kinematic Reliability During Repeated Softball Pitching
Authors: Pletcher Erin R. , Lovalekar Mita , Nagai Takashi , Connaboy Chris
Published: January 2025

Background/Objectives: Three-dimensional motion analysis is often used to evaluate improvements or decrements in movement patterns in athletes. The purpose of this study was to evaluate the reliability of joint flexion/extension angles of the pitching elbow and bilateral knees and hips in softball pitchers. Methods: Fourteen softball pitchers (17.9 ± 2.3 years) were tested in one session consisting of four sets of five consecutive fastballs and a second session of two sets of five fastballs. The magnitude of systematic bias and within-subject variation was calculated between pitches. An iterative intraclass correlation coefficient (ICC) process was used to determine intra- and inter-session reliability, standard error of measurement and minimal detectable change. Results: Reductions in within-subject variation were observed for all variables when the number of pitches used in calculations was increased. Intra-session ICC values ranged from an average of 0.643 for pitching elbow to 0.989 for stride leg knee. Inter-session ICC values ranged from an average of 0.663 for pitching elbow to 0.996 for stride leg knee. Conclusions: Joint flexion/extension angles during the softball windmill pitch can be measured with good to high reliability using three-dimensional motion analysis. Biomechanical analysis can be confidently used to detect changes in the pitching motion over the course of a season or following an intervention.
Recent Advances in Vaginal Atresia: A Literature Review
Authors: Lin Xijuan , Kang Jia , Zhu Lan
Published: January 2025

Vaginal atresia is a rare anomaly of the female reproductive tract that significantly impacts women’s reproductive health and quality of life. Although there has been relatively extensive research on the clinical manifestations and differential diagnosis of vaginal atresia, there is a paucity of literature specifically addressing the genetic background, treatment protocols, and psychological status of patients with vaginal atresia, indicating a need for further investigation. In this context, this article systematically reviews the epidemiological characteristics of vaginal atresia and explores its etiology from multiple perspectives, including developmental processes, genetic factors, and environmental factors, emphasizing the importance of genetic susceptibility and environmental interactions in the pathogenesis of the condition. Building upon a summary of the clinical presentations, classification, and diagnostic methods of vaginal atresia, this article provides an overview of current treatment strategies for both partial vaginal atresia and complete vaginal atresia, discusses the psychological status of affected patients, and examines fertility outcomes and sexual function. The aim is to offer insights and recommendations for future research on vaginal atresia, ultimately striving to enhance the quality of life for affected individuals.
Sesquiterpene Lactones as Promising Anti-Glioblastoma Drug Candidates Exerting Complex Effects on Glioblastoma Cell Viability and Proneural–Mesenchymal Transition
Authors: Markov Andrey V. , Moralev Arseny D. , Odarenko Kirill V.
Published: January 2025

Glioblastoma is one of the most aggressive brain cancers, characterized by active infiltrative growth and high resistance to radiotherapy and chemotherapy. Sesquiterpene triterpenoids (STLs) and their semi-synthetic analogs are considered as a promising source of novel anti-tumor agents due to their low systemic toxicity and multi-target pharmacological effects on key processes associated with tumor progression. The current review aims to systematize the knowledge on the anti-glioblastoma potential of STLs accumulated over the last decade and to identify key processes in glioblastoma cells that are most susceptible to the action of STLs. An analysis of published data clearly demonstrated that STLs, which can successfully cross the blood–brain barrier, exert a complex inhibitory effect on glioblastoma cells through the induction of the “mitochondrial dysfunction–oxidative stress–apoptosis” axis, the inhibition of glucose metabolism and cell cycle phase transition, and the suppression of glioblastoma cell motility and invasion through the blockade of proneural–mesenchymal transition. Taken together, this review highlights the promising anti-glioblastoma potential of STLs, which are not only able to induce glioblastoma cell death, but also effectively affect their diffusive spread, and suggests the possible directions for further investigation of STLs in the context of glioblastoma to better understand their mechanism of action.
Factors Determining Rehabilitation Needs After Intradural Spinal Tumor Surgery: A Prospective Study
Authors: Krajewski Stanisław , Furtak Jacek , Zawadka-Kunikowska Monika , Kachelski Michał , Soboń Jakub , Harat Marek
Published: January 2025

Background/Objectives: While most studies on the postoperative condition of patients with spinal cord tumors describe long-term outcomes, data are needed on immediate surgical outcomes demanding rehabilitation to make informed assessments for postoperative planning. The aim of this study was to identify factors predicting function and rehabilitative needs after intradural spinal tumor surgery. Methods: Eighty-five prospectively recruited patients underwent surgery for intradural intramedullary (ID-IM; n = 23) and extramedullary (ID-EM; n = 62) tumors. Neurological and functional status were assessed before surgery, after surgery, and at discharge using the modified McCormick scale (MMS), Karnofsky performance status (KPS) scale, Barthel index (BI), and the gait index (GI). Results: There were no significant predictors of early postoperative rehabilitation in the ID-IM group. In the ID-EM group, age, thoracic level, subtotal resection (STR), repeat surgery, and functional scale scores predicted the need for rehabilitation. In multivariable analysis, MMS (odds ratio (OR) 8.7; 95% confidence interval (CI): 2.37–32.44) and STR (OR 13.00; 95%CI: 1.56–107.87) remained independent predictors of rehabilitation need (area under curve, 92%). Despite their younger age, most patients with ID-IM tumors, especially ependymomas, required rehabilitation but improved quickly (KPS, BI, p < 0.001). Among ID-EM tumors, meningiomas were characterized by poorer preoperative function and low gross total resection (GTR) rates, but did not deteriorate neurologically after surgery. Patients with schwannoma and ID-EM ependymomas achieved the highest GTR rate and had the best function both before and after surgery. Conclusions: These results may be useful for estimating early rehabilitation needs after intradural tumor surgery and counseling patients before surgery about the expected postoperative course.
Cheong Wa Dae: The Sustainability and Place-Making of a Cultural Landmark, Reflecting Its Role in History and Architecture
Authors: Kim Ja-young Eunice , Shim Yong-hwan
Published: January 2025

Cheong Wa Dae, a site of profound historical and cultural significance, holds great potential to be reimagined as a sustainable cultural landmark that meets contemporary social, economic, and environmental needs. This research explores strategies to preserve its historical identity while transforming it into a dynamic and accessible public space. Using a qualitative approach, this study integrates history and architectural reviews and sustainability frameworks, including alignment with the UN’s 17 Sustainable Development Goals (SDGs). Programs were evaluated through the Sustainability Impact Assessment tool to measure their ecological, cultural, and socio-economic impacts. The findings reveal that targeted strategies—such as utilizing the physical environment for global events, promoting biodiversity, and enhancing engagement through cultural and culinary experiences—are essential for sustainable transformation. These initiatives align with 11 of the 17 SDGs, with 7 goals showing a Direct Positive Impact and 4 showing an Indirect Positive Impact. This study concludes that by merging heritage preservation with innovation and sustainability, Cheong Wa Dae can evolve into a vibrant, economically viable public space and a model for cultural place-making, fostering public engagement, economic growth, and long-term ecological benefits.
Impacts of Thermal Activation on Physical Properties of Coal Gangue: Integration of Microstructural and Leaching Data
Authors: Fan Wangtao , Chen Yuan , Zhang Runxia , Chen Xiaoguang , Li Jin , Gu Zhaolin , Wang Jianyun
Published: January 2025

The recycling of coal gangue has considerable potential to produce secondary environmental hazards, which significantly influence the high-end application of coal gangue in practical engineering. The present study investigates the effects of activation treatment on the physical, chemical properties and leaching behavior of coal gangue. The mineral composition, micro-pore structure and element leaching were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), Thermogravimetry Analysis (TG), Low-Temperature Nitrogen Adsorption (LTNA) and Inductively Coupled Plasma (ICP). The results indicate that kaolinite and pyrite in coal gangue experienced reconstruction after 600 °C during thermal activation. The density of thermally activated coal gangue is increased with the calcination temperature as well as the alkalinity (from 4.8–7.1) due to the burning of organic and the oxidation of pyrite. The calcination treatment induced the reduction in macropore volume (>50 nm), and enhancement in mesopore (<5 nm) volume. Leachable Ni, Cd, Mn, Cu, Zn and Pd decreased by 99%, 67%, 86%, 40%, 99% and 93% after calcination at 800 °C, respectively. The Si and Al in 800 °C calcined coal gangue exhibited a high leaching ability in alkalinity solution; leachable Al reached 106.4 mg/kg, while leachable Si reached 86.1 mg/kg after 48 h of dynamic leaching.
Very High-Energy Electron Therapy Toward Clinical Implementation
Authors: Panaino Costanza Maria Vittoria , Piccinini Simona , Andreassi Maria Grazia , Bandini Gabriele , Borghini Andrea , Borgia Marzia , Di Naro Angelo , Labate Luca Umberto , Maggiulli Eleonora , Portaluri Maurizio Giovanni Agostino , Gizzi Leonida Antonio
Published: January 2025

The use of very high energy electron (VHEE) beams, with energies between 50 and 400 MeV, has drawn considerable interest in radiotherapy due to their deep tissue penetration, sharp beam edges, and low sensitivity to tissue density. VHEE beams can be precisely steered with magnetic components, positioning VHEE therapy as a cost-effective option between photon and proton therapies. However, the clinical implementation of VHEE therapy (VHEET) requires advances in several areas: developing compact, stable, and efficient accelerators; creating sophisticated treatment planning software; and establishing clinically validated protocols. In addition, the perspective of VHEE to access ultra-high dose–rate regime presents a promising avenue for the practical integration of FLASH radiotherapy of deep tumors and metastases with VHEET (FLASH-VHEET), enhancing normal tissue sparing while maintaining the inherent dosimetric advantages of VHEET. However, FLASH-VHEET systems require validation of time-dependent dose parameters, thus introducing additional technological challenges. Here, we discuss recent progress in VHEET research, focusing on both conventional and FLASH modalities, and covering key aspects including dosimetric properties, radioprotection, accelerator technology, beam focusing, radiobiological effects, and clinical outcomes. Furthermore, we comprehensively analyze initial VHEET in silico studies on coverage across various tumor sites.
Location and Movement of the Oxytocin Receptor Differ Between the Normal and Diseased Prostate
Authors: Gould Maree , Potapov Daniil , Nicholson Helen
Published: January 2025

Background: In normal prostate cells, receptors for oxytocin (OT), a peptide involved in regulating prostate growth are sequestered within membrane microdomains called caveolae. During cancer progression, polymerase-transcript-release factor (PTRF) is downregulated, caveolae structures are lost and receptors move onto the cell membrane. This study investigated whether proteins responsible for caveolae formation were affected by the OT peptide, also, how OT treatment affected oxytocin receptor (OTR) movement within living cells. Methods: Normal human prostate epithelial cells (PrEC) expressing caveolin and PTRF and androgen-independent (PC3) cancer cells expressing caveolin but not PTRF were used. OTR, caveolin and PTRF expression was determined in human prostate tissue. Results: PTRF expression decreased in tissue alongside an increase in malignancy. Caveolin-1 expression was downregulated by OT treatment. Caveolin-2 was decreased by OT in PrEC cells but increased in PC3 cells. PTRF was decreased by OT in PrEC. TIRF microscopy showed OTR translocated from caveolae to caveolae in normal cells, whereas OTR moved without restraint in malignant cells, possibly stimulating signaling pathways. Conclusions: This study provides evidence for the ability of OT to regulate caveolin and PTRF expression. This study elucidates possible mechanisms by which cell receptors and caveolae proteins interact to enhance cell proliferation.
Ultrasound-Guided Histotripsy Triggers the Release of Tumor-Associated Antigens from Breast Cancers
Authors: Tang Shengzhuang , McGinnis Reliza , Cao Zhengyi , Baker James R. , Xu Zhen , Wang Suhe
Published: January 2025

Background/Objectives: There is increasing evidence to indicate that histotripsy treatment can enhance the host anti-tumor immune responses both locally at the targeting tumor site as well as systemically from abscopal effects. Histotripsy is a non-invasive ultrasound ablation technology that mechanically disrupts target tissue via cavitation. A key factor contributing to histotripsy-induced abscopal effects is believed to be the release of tumor-specific antigens (TSAs) or tumor-associated antigens (TAAs) that induce a systemic immune response. In this study, we studied the effect of histotripsy treatment on the release of HER2, a well-defined TAA target for cancer immunotherapy. Methods: A range of doses of histotripsy administered to HER2-postive mammary tumor cells in an in vitro cell culture system and an ex vivo tumor were applied. In addition, a single dose of histotripsy was used for an in vivo murine tumor model. The released proteins, and specifically HER2, in both tumor cell-free supernatants and tumor cell pellets were analyzed by a BCA protein assay, an ultra-performance liquid chromatography (UPLC) assay, and Western blot. Results: Our results showed that histotripsy could significantly trigger the release of HER2 proteins in the current study. The level of HER2 proteins was actually higher in tumor cell-free supernatants than in tumor cell pellets, suggesting that HER2 was released from the intracellular domain into the extracellular compartment. Furthermore, proportionally more HER2 protein was released at higher histotripsy doses, indicating free HER2 was histotripsy-dose-dependent. Conclusions: In conclusion, we have qualitatively and quantitatively demonstrated that histotripsy treatment triggers the release of HER2 from the tumor cells into the extracellular compartment. The histotripsy-mediated release of HER2 antigens provides important insights into the mechanism underlying its immunostimulation and suggests the potential of TSA/TAA-based immunotherapies in numerous cancer types.
AIPE-Active Neutral Ir(III) Complexes as Bi-Responsive Luminescent Chemosensors for Sensing Picric Acid and Fe3+ in Aqueous Media
Authors: Zhang Qinglong , Xu Jiangchao , Xu Qiang , Liu Chun
Published: January 2025

Three neutral iridium complexes Ir1–Ir3 were synthesized using diphenylphosphoryl-substituted 2-phenylpyridine derivatives as the cyclometalating ligand and picolinic acid as the auxiliary ligand. They exhibited significant aggregation-induced phosphorescent emission (AIPE) properties in H2O/THF and were successfully used as bi-responsive luminescent sensors for the detection of picric acid (PA) and Fe3+ in aqueous media. Ir1–Ir3 possesses high efficiency and high selectivity for detecting PA and Fe3+, with the lowest limit of detection at 59 nM for PA and 390 nM for Fe3+. Additionally, the complexes can achieve naked-eye detection of Fe3+ in aqueous media. Ir1–Ir3 exhibit excellent potential for practical applications in complicated environments. The detection mechanism for PA is attributed to photo-induced electron transfer (PET) and Förster resonance energy transfer (FRET), and the detection mechanism for Fe3+ may be explained by PET and the strong interactions between Fe3+ and the complexes.
Zinc-Reduced Anticorrosive Primers—Water-Based Versus Solvent-Based
Authors: Langer Ewa , Zubielewicz Małgorzata , Królikowska Agnieszka , Komorowski Leszek , Krawczyk Katarzyna , Wanner Matthias , Aktas Lukas , Hilt Michael
Published: January 2025

Coating systems used for anticorrosion protection usually consist of a primer, intermediate layers, and topcoats. Zinc-rich primers, which serve as cathodic and barrier protection, are widely used for the corrosion protection of steel structures. Due to the fact that the functioning of the above-mentioned coatings is related to the conduction of galvanic current, these types of coatings are highly pigmented with zinc (up to 80 wt% in the dry coating). This may result not only in a deterioration of the performance of the coating system but also have a negative impact on the environment. Taking the above into account, solvent-based and water-based organic epoxy primers with zinc content reduced to approximately 50% have been developed. Zinc pigments of different shapes and with different surface treatments were used in the primers, as well as pigments without chemical treatment but with the addition of nanoparticles. It was found that, depending on the type of zinc pigment, both the developed solvent-based and water-based primers demonstrate good protective properties comparable to traditional zinc-rich coatings. Water-based paints tend to absorb more moisture compared to solvent-based systems, but their water uptake reversibility is limited. Moreover, the organic treatment of zinc flakes helps to improve this water uptake reversibility, improving the mechanical properties of coatings.
Targeted Transition Readiness Workshops for Pediatric Brain Tumor Survivors: Feasibility, Acceptability, and Preliminary Effects
Authors: Carrier Julie , Lugasi Tziona , Labonté Nathalie , Provost Carole , Saragosti Andrea , Longpré Claire , Koukoui Bénédicte , Régnier-Trudeau Émilie , Sultan Serge , Coltin Hallie , Perreault Sébastien , Bonanno Marco , Desjardins Leandra
Published: January 2025

Pediatric brain tumor survivors (PBTS) are at risk for late effects related to their diagnosis and treatment. Long-term medical follow-ups are deemed essential, implying a transition from pediatric to adult healthcare settings. This pilot study aims to assess the feasibility, acceptability, and preliminary effects of a targeted transition readiness intervention for PBTS. The program consisted of three hybrid workshops that targeted disease-related self-management skills, social skills, and cognitive functioning, as well as parallel workshops for their caregivers. The feasibility and acceptability were assessed through recruitment, retention, and satisfaction rates. Preliminary effects were primarily assessed via a pre/post assessment of transition readiness skills using the Transition Readiness Assessment (TRAQ) questionnaire. Among the eligible dyads, 12 (38%) consented to participate. Ten dyads participated in at least two workshops, and six dyads participated in all workshops. Overall, the participants were satisfied with the intervention (parents = 86%; PBTS = 73%). Although not statistically significant, a clinically relevant post-workshop increase in transition readiness skills was observed for PBTS (d = 0.36) and their caregivers (d = 0.25). The results suggest the relevance of the intervention and encourage further developments. Adjustments are needed to optimize reach and efficacy. The workshops have the potential to be adapted to be more accessible and shorter.
Cholec80-Boxes: Bounding Box Labelling Data for Surgical Tools in Cholecystectomy Images
Authors: Abdulbaki Alshirbaji Tamer , Jalal Nour Aldeen , Arabian Herag , Battistel Alberto , Docherty Paul David , ElMoaqet Hisham , Neumuth Thomas , Moeller Knut
Published: January 2025

Surgical data analysis is crucial for developing and integrating context-aware systems (CAS) in advanced operating rooms. Automatic detection of surgical tools is an essential component in CAS, as it enables the recognition of surgical activities and understanding the contextual status of the procedure. Acquiring surgical data is challenging due to ethical constraints and the complexity of establishing data recording infrastructures. For machine learning tasks, there is also the large burden of data labelling. Although a relatively large dataset, namely the Cholec80, is publicly available, it is limited to the binary label data corresponding to the surgical tool presence. In this work, 15,691 frames from five videos from the dataset have been labelled with bounding boxes for surgical tool localisation. These newly labelled data support future research in developing and evaluating object detection models, particularly in the laparoscopic image data analysis domain.
Influence of SARS-CoV2 Pandemic on Colorectal Cancer Diagnosis, Presentation, and Surgical Management in a Tertiary Center: A Retrospective Study
Authors: Taulean Roman , Zaharie Roxana , Valean Dan , Usatiuc Lia , Dib Mohammad , Moiș Emil , Popa Calin , Ciocan Andra , Fetti Alin , Al-Hajjar Nadim , Zaharie Florin
Published: January 2025

Background: Oncological surgery during the COVID-19 pandemic was performed only in carefully selected cases, due to variation in the allocation of resources. The purpose of this study was to highlight the impact of the pandemic lockdown on the presentation, diagnosis, and surgical management of colorectal cancers as well as the post-pandemic changes in this area. Material and methods: This single center, retrospective comparative study contained 1687 patients, divided into three groups with equal time frames of two years, consisting of a pre-pandemic, pandemic, and post-pandemic period, in which preoperative and perioperative as well as postoperative parameters were compared. Results: Statistically significant differences regarding environment, type of admission, and ASA score, as well as a more advanced tumoral stage, increased number of important postoperative complications, and a lower minimally invasive surgical approach, were highlighted within the pandemic group. Statistically significant differences regarding emergency diagnosis as well as late diagnosis were highlighted. There were no significant differences regarding the tumor location, postoperative 30-day mortality, or hospitalization duration. Conclusions: COVID-19 significantly impacted the surgical timing in colorectal cancer, as well as addressability for the rural population, with a marked decrease in elective cases as well as an increased number of cases diagnosed in an emergency setting, with locally advanced tumors. However, no significant changes in postoperative mortality or hospitalization duration were highlighted. In addition, most of the changes highlighted were reverted in the post-pandemic period. Further studies are required to observe the long-term effects in terms of morbidity and mortality, regarding the delay of diagnosis and oncological treatment.
Erroneous Classification and Coding as a Limitation for Big Data Analyses: Causes and Impacts Illustrated by the Diagnosis of Clavicle Injuries
Authors: Raché Robert , Claudé Lara-Sophie , Vollmer Marcus , Haralambiev Lyubomir , Gümbel Denis , Ekkernkamp Axel , Jordan Martin , Schulz-Drost Stefan , Bakir Mustafa Sinan
Published: January 2025

Background/Objectives: Clavicle injuries are common and seem to be frequently subject to diagnostic misclassification. The accurate identification of clavicle fractures is essential, particularly for registry and Big Data analyses. This study aims to assess the frequency of diagnostic errors in clavicle injury classifications. Methods: This retrospective study analyzed patient data from two Level 1 trauma centers, covering the period from 2008 to 2019. Included were cases with ICD-coded diagnoses of medial, midshaft, and lateral clavicle fractures, as well as sternoclavicular and acromioclavicular joint dislocations. Radiological images were re-evaluated, and discharge summaries, radiological reports, and billing codes were examined for diagnostic accuracy. Results: A total of 1503 patients were included, accounting for 1855 initial injury diagnoses. In contrast, 1846 were detected upon review. Initially, 14.4% of cases were coded as medial clavicle fractures, whereas only 5.2% were confirmed. The misclassification rate was 82.8% for initial medial fractures (p < 0.001), 42.5% for midshaft fractures (p < 0.001), and 34.2% for lateral fractures (p < 0.001). Billing codes and discharge summaries were the most error-prone categories, with error rates of 64% and 36% of all misclassified cases, respectively. Over three-quarters of the cases with discharge summary errors also exhibited errors in other categories, while billing errors co-occurred with other category errors in just over half of the cases (p < 0.001). The likelihood of radiological diagnostic error increased with the number of imaging modalities used, from 19.7% with a single modality to 30.5% with two and 40.7% with three. Conclusions: Our findings indicate that diagnostic misclassification of clavicle fractures is common, particularly between medial and midshaft fractures, often resulting from errors in multiple categories. Further prospective studies are needed, as accurate classification is foundational for the reliable application of Big Data and AI-based analyses in clinical research.
Cephalometric and Photographic Evaluation of the Nasolabial Angle in Orthodontically Treated Patients: An Observational Cohort Study
Authors: Pop Silvia Izabella , Bud Eugen , Mártha Krisztina , Mureșan Izabella Éva , Jánosi Kinga Mária , Dósa Boglárka , Kerekes-Máthé Bernadette
Published: January 2025

Background: The nasolabial angle (NLA) is one of the most critical parameters of the soft tissue profile when orthodontic treatment is required. The primary aim of this prospective cohort study was to compare the differences in the evaluation made on lateral photographs and cephalograms. The secondary aim was to evaluate the modifications of the NLA (nasal and labial components) after orthodontic treatment, including upper first premolar extraction. Methods: The pre- and post-treatment lateral radiographs and profile photographs of 60 subjects (18 male and 42 female) treated with upper premolar extraction and fixed orthodontic appliances were evaluated. The nasolabial angle was measured in both investigations, while cephalometric parameters (skeletal, dental, and soft tissue parameters) were evaluated using lateral radiographs. Results: No statistically significant difference was observed between the results of the two types of measurements on the photographs and radiographs. The soft tissue parameters (ULT and UL-e) showed significant changes after orthodontic treatment, with ULT changing from 21.4 mm ± 4.07 mm to 22.9 mm ± 4.06 mm (p = 0.03) and UL-e changing from 8.42 mm ± 4.84 mm to 10.35 mm ± 4.23 mm (p < 0.001). In patients with thinner lips, the upper lip repositioning was more significant (p = 0.001). No statistically significant difference (p = 0.67) was found between the two evaluation methods. Conclusions: Both cephalometric and photographic evaluations of the nasolabial angle were similar. The soft tissue parameters (ULT and UL-e) showed significant changes after the orthodontic treatment. The repositioning of the upper lip was more acute when the lip thickness decreased.
PET-CT Imaging in Hypertrophic Cardiomyopathy: A Narrative Review on Risk Stratification and Prognosis
Authors: Marques-Alves Patrícia , Gonçalves Lino , Ferreira Maria João
Published: January 2025

Hypertrophic cardiomyopathy (HCM) is a heterogeneous cardiac disease and one of its major challenges is the limited accuracy in stratifying the risk of sudden cardiac death (SCD). Positron emission tomography (PET), through the evaluation of myocardial blood flow (MBF) and metabolism using fluorodeoxyglucose (FDG) uptake, can reveal microvascular dysfunction, ischemia, and increased metabolic demands in the hypertrophied myocardium. These abnormalities are linked to several factors influencing disease progression, including arrhythmia development, ventricular dilation, and myocardial fibrosis. Fibroblast activation can also be evaluated using PET imaging, providing further insights into early-stage myocardial fibrosis. Conflicting findings underscore the need for further research into PET’s role in risk stratification for HCM. If PET can establish a connection between parameters such as abnormal MBF or increased FDG uptake and SCD risk, it could enhance predictive accuracy. Additionally, PET holds significant potential for monitoring therapeutic outcomes. The aim of this review is to provide a comprehensive overview of the most significant data on disease progression, risk stratification, and prognosis in patients with HCM using cardiac PET-CT imaging.
Digital Competence of Rural Teachers in Depopulated Regions of Spain: A Bibliometric Review
Authors: Fernández-Arias Pablo , Sánchez-Jiménez María , Antón-Sancho Álvaro , Nieto-Sobrino María , Vergara Diego
Published: January 2025

Rural teachers have the potential to be important agents of local development. To achieve this goal, they need to acquire high digital competence in order to effectively integrate technology into their pedagogical practices, thus enriching the learning experience of students and fostering their participation. Digital competence contributes to reducing the education gap between urban and rural areas, promoting educational equity and inclusion. High digital competence also enables rural teachers to address the specific challenges of their environment, such as cultural diversity, scarce resources, and low population density. Against this backdrop, this article presents a bibliometric review of the importance of digital competence in rural teachers in Spain, where the problem of rural depopulation, as in other regions of Europe, has been accentuated in recent years. The objective of the bibliometric review is both (i) to find the strengths and weaknesses that concern researchers in relation to the digital training of teachers in rural areas and (ii) to express them explicitly in order to contribute to propose solutions. The results reveal the growing academic and political attention being paid to this issue, highlighting the need for rural teachers to acquire digital skills to adapt to current educational demands. In addition, they point to the importance of developing specific policies and programs in Europe as well as providing training opportunities and ongoing support to ensure that teachers in rural contexts can acquire or strengthen their digital competence, thereby improving the quality of education in these areas.
Tribological, Thermal, Kinetic, and Surface Microtextural Characterization of Prime p-Type <100> Silicon Wafer CMP for Direct Wafer Bonding Applications
Authors: Yap Michelle , Yap Catherine , Sampurno Yasa , Whitener Glenn , Keleher Jason , Borucki Len , Philipossian Ara
Published: January 2025

We investigated the tribological, thermal, kinetic, and surface microtextural characteristics of chemical mechanical polishing (CMP) of 300 mm p-type <100> prime silicon wafers (and their native oxide) at various pressures, sliding velocities, and starting platen temperatures. Results showed the dominant tribological mechanism for both native oxide and silicon polishing to be boundary lubrication. Using frictional data, we pinpointed the exact time that corresponded to the total removal of the native oxide and the onset of silicon polishing. This allowed us to separately characterize removal rates of each layer. For native oxide, while the rate depended on temperature, the presence of a temperature-independent shear force threshold and the low observed rates suggested that its removal by the slurry was dominantly mechanical. In contrast, for silicon polish, the absence of a distinctive shear force threshold and the fact that, for the same set of consumables, rates were more than 200 times larger for silicon than for native oxide suggested a dominantly chemical process with an average apparent activation energy of 0.34 eV. It was further confirmed that rate selectivity between native oxide and PE-TEOS based SiO2 control wafers was around 1 to 7, which underscored the importance of being able to directly measure native oxide removal rates. In all cases, we achieved excellent post-polish surfaces with Sa and Sq values of below 1 nm. Due to thermal softening of the thermoplastic pad at elevated temperatures, which we confirmed via dynamic mechanical analysis, overall process vibrations were significantly higher when platen heating was employed.
AIDS-Based Cyber Threat Detection Framework for Secure Cloud-Native Microservices
Authors: Park Heeji , EL Azzaoui Abir , Park Jong Hyuk
Published: January 2025

Cloud-native architectures continue to redefine application development and deployment by offering enhanced scalability, performance, and resource efficiency. However, they present significant security challenges, particularly in securing inter-container communication and mitigating Distributed Denial of Service (DDoS) attacks in containerized microservices. This study proposes an Artificial Intelligence Intrusion Detection System (AIDS)-based cyber threat detection solution to address these critical security challenges inherent in cloud-native environments. By leveraging a Resilient Backpropagation Neural Network (RBN), the proposed solution enhances system security and resilience by effectively detecting and mitigating DDoS attacks in real time in both the network and application layers. The solution incorporates an Inter-Container Communication Bridge (ICCB) to ensure secure communication between containers. It also employs advanced technologies such as eXpress Data Path (XDP) and the Extended Berkeley Packet Filter (eBPF) for high-performance and low-latency security enforcement, thereby overcoming the limitations of existing research. This approach provides robust protection against evolving security threats while maintaining the dynamic scalability and efficiency of cloud-native architectures. Furthermore, the system enhances operational continuity through proactive monitoring and dynamic adaptability, ensuring effective protection against evolving threats while preserving the inherent scalability and efficiency of cloud-native environments.
Short-Term Load Forecasting Model Based on Time Series Clustering and Transformer in Smart Grid
Authors: Liu Yan , Zheng Ruijuan , Liu Muhua , Zhu Junlong , Zhao Xuhui , Zhang Mingchuan
Published: January 2025

Accurate Short-Term Load Forecasting (STLF) is a critical task in managing and operating smart grids. Existing STLF methods primarily rely on mathematical modeling or neural networks, often struggle to effectively capture the correlations between influencing factors and load data, and frequently lack interpretability. To address these challenges, this paper proposes an intelligent framework for STLF that combines a pattern extraction and attention mechanism, which leverages the characteristics of electricity consumption data. The proposed framework facilitates the integration of prior knowledge, identifies intrinsic data patterns, and more accurately maps the relationships between influencing factors and load patterns. Finally, we conduct experiments on real-world and publicly available datasets to evaluate the performance of the proposed model. Specifically, the proposed model improves the accuracy of STLF compared to that of existing methods and reduces the mean absolute percentage error by 2% to 5%. The model performs superiorly on the real datasets, with root mean squared error and mean absolute percentage error values of 0.810 MWh and 7.09%.
A Unified Design Methodology for Front-End RF/mmWave Receivers
Authors: Michailidis Anastasios , Chatzis Alexandros , Tsimpou Panayiota , Gogolou Vasiliki , Noulis Thomas
Published: January 2025

In this work, a unified design methodology for front-end RF/mmWave receivers is presented, aiming to significantly accelerate the design procedure of the front-end RF blocks in complex RX/TX chain implementations. The proposed design methodology is based on optimization loops with well-defined cost functions so as to minimize the design iterations that may be encountered during specification tuning. As proof of concept, two essential RF blocks widely used in RF receivers, a low-noise amplifier (LNA) and a voltage-controlled oscillator (VCO), were designed using the proposed unified methodology with a 65 nm RF-CMOS processing node. Finally, the derived designs were compared to similar designs in the literature, proving that the proposed unified methodology is capable of synthesizing RF/mmWave LNAs and VCOs with industry-standard specifications within a significantly faster time frame.
Unsupervised Anomaly Detection for Improving Adversarial Robustness of 3D Object Detection Models
Authors: Cai Mumuxin , Wang Xupeng , Sohel Ferdous , Lei Hang
Published: January 2025

Three-dimensional object detection based on deep neural networks (DNNs) is widely used in safety-related applications, such as autonomous driving. However, existing research has shown that 3D object detection models are vulnerable to adversarial attacks. Hence, the improvement on the robustness of deep 3D detection models under adversarial attacks is investigated in this work. A deep autoencoder-based anomaly detection method is proposed, which has a strong ability to detect elaborate adversarial samples in an unsupervised way. The proposed anomaly detection method operates on a given Light Detection and Ranging (LiDAR) scene in its Bird’s Eye View (BEV) image and reconstructs the scene through an autoencoder. To improve the performance of the autoencoder, an augmented memory module with typical normal patterns recorded is introduced. It is designed to help the model to amplify the reconstruction errors of malicious samples with normal samples negligibly affected. Experiments on several public datasets show that the proposed anomaly detection method achieves an AUC of 0.8 under adversarial attacks and improves the robustness of 3D object detection.
Transformer-Based Re-Ranking Model for Enhancing Contextual and Syntactic Translation in Low-Resource Neural Machine Translation
Authors: Javed Arifa , Zan Hongying , Mamyrbayev Orken , Abdullah Muhammad , Ahmed Kanwal , Oralbekova Dina , Dinara Kassymova , Akhmediyarova Ainur
Published: January 2025

Neural machine translation (NMT) plays a vital role in modern communication by bridging language barriers and enabling effective information exchange across diverse linguistic communities. Due to the limited availability of data in low-resource languages, NMT faces significant translation challenges. Data sparsity limits NMT models’ ability to learn, generalize, and produce accurate translations, which leads to low coherence and poor context awareness. This paper proposes a transformer-based approach incorporating an encoder–decoder structure, bilingual curriculum learning, and contrastive re-ranking mechanisms. Our approach enriches the training dataset using back-translation and enhances the model’s contextual learning through BERT embeddings. An incomplete-trust (in-trust) loss function is introduced to replace the traditional cross-entropy loss during training. The proposed model effectively handles out-of-vocabulary words and integrates named entity recognition techniques to maintain semantic accuracy. Additionally, the self-attention layers in the transformer architecture enhance the model’s syntactic analysis capabilities, which enables better context awareness and more accurate translations. Extensive experiments are performed on a diverse Chinese–Urdu parallel corpus, developed using human effort and publicly available datasets such as OPUS, WMT, and WiLi. The proposed model demonstrates a BLEU score improvement of 1.80% for Zh→Ur and 2.22% for Ur→Zh compared to the highest-performing comparative model. This significant enhancement indicates better translation quality and accuracy.
RLVS: A Reinforcement Learning-Based Sparse Adversarial Attack Method for Black-Box Video Recognition
Authors: Song Jianxin , Yu Dan , Teng Hongfei , Chen Yongle
Published: January 2025

To address the challenges of black-box video adversarial attacks, such as excessive query times and suboptimal attack performance due to the lack of result feedback during the attack process, we propose a reinforcement learning-based sparse adversarial attack method called RLVS. This approach leverages reinforcement learning to identify key frames for efficient gradient estimation, significantly reducing the number of queries. First, a self-attention network is integrated into the agent policy network to enable more precise selection of key frames. Second, designed reward functions allow the agent to continuously adapt to the sparse key frames by querying the black-box threat model and receiving feedback on attack outcomes. Lastly, gradient estimation is applied solely to the selected key frames, estimating only the gradient sign rather than the full gradient, further enhancing attack efficiency. We conducted experiments on two video recognition models using three popular action datasets. The experimental results demonstrate that our method outperforms other black-box video attack methods in terms of attack efficiency and effectiveness, achieving higher fooling rates with fewer queries and minimal perturbations.
Lithium-Ion Battery Degradation Based on the CNN-Transformer Model
Authors: Shi Yongsheng , Wang Leicheng , Liao Na , Xu Zequan
Published: January 2025

Due to its innovative structure and superior handling of long time series data with parallel input, the Transformer model has demonstrated a remarkable effectiveness. However, its application in lithium-ion battery degradation research requires a massive amount of data, which is disadvantageous for the online monitoring of batteries. This paper proposes a lithium-ion battery degradation research method based on the CNN-Transformer model. By leveraging the efficiency of the CNN model in feature extraction, it reduces the dependency of the Transformer model on data volume, thereby ensuring faster overall model training without a significant loss in model accuracy. This facilitates the online monitoring of battery degradation. The dataset used for training and validation consists of charge–discharge data from 124 lithium iron phosphate batteries. The experimental results include an analysis of the model training results for both single-battery and multiple-battery data, compared with commonly used models such as LSTM and Transformer. Regarding the instability of single-battery data in the CNN-Transformer model, statistical analysis is conducted to analyze the experimental results. The final model results indicate that the root mean square error (RMSE) of capacity predictions for the majority of batteries among the 124 batteries is within 3% of the actual values.
AI-Assisted Forecasting of a Mitigated Multiple Steam Generator Tube Rupture Scenario in a Typical Nuclear Power Plant
Authors: Spisak Sonia , Diab Aya
Published: January 2025

This study is focused on developing a machine learning (ML) meta-model to predict the progression of a multiple steam generator tube rupture (MSGTR) accident in the APR1400 reactor. The accident was simulated using the thermal–hydraulic code RELAP5/SCDAPSIM/MOD3.4. The model incorporates a mitigation strategy executed through operator interventions. Following this, uncertainty quantification employing the Best Estimate Plus Uncertainty (BEPU) methodology was undertaken by coupling RELAP5/SCDAPSIM/MOD3.4 with the statistical software, DAKOTA 6.14.0. The analysis concentrated on critical safety parameters, including Reactor Coolant System (RCS) pressure and temperature, as well as reactor vessel upper head (RVUH) void fraction. These simulations generated a comprehensive dataset, which served as the foundation for training three ML architectures: Gated Recurrent Unit (GRU), Long Short-Term Memory (LSTM), and Convolutional LSTM (CNN+LSTM). Among these models, the CNN+LSTM hybrid configuration demonstrated superior performance, excelling in both predictive accuracy and computational efficiency. To bolster the model’s transparency and interpretability, Integrated Gradients (IGs)—an advanced Explainable AI (XAI) technique—was applied, elucidating the contribution of input features to the model’s predictions and enhancing its trustworthiness.