bluuebunny/crossref_metadata_2025 huggingface dataset:
Tracing Quiescent Cancer Cells In Vivo
Authors: Kim Moon Jong
Published: November 2024

QCCs have long gained significant interest as potential “seeds” for recurrent cancers. Clinical evidence suggests that a subset of cancer cells exits the cell cycle and enters a quiescent state following anti-cancer treatment. These microscopic-residual QCCs are extremely challenging to trace and detect within patients. Additionally, QCCs resist conventional anti-cancer therapies due to the lack of cell activity. Notably, upon the unknown environmental cues in unknown time points, sometimes decades later, QCCs can reactivate, triggering cancer relapse at primary or secondary sites. Currently, no targeted therapies or diagnostic tools exist for QCCs, and their molecular regulatory mechanisms remain largely unknown. The major challenge in understanding QCCs lies in the limited availability of human-relevant pre-clinical models that trace and collect QCCs in vivo. This review provides an overview of existing QCC tracing systems and analyzes their limitations. It also cautiously proposes potential improvements for tracing QCCs in vivo based on recent advancements in QCC studies and lineage-tracing techniques. Developing human-relevant and easily accessible in vivo tracing systems will be a crucial step in advancing QCC diagnostics and therapeutic strategies.
An Overview for Clinicians on Intraductal Papillary Mucinous Neoplasms (IPMNs) of the Pancreas
Authors: Moris Dimitrios , Liapis Ioannis , Gupta Piyush , Ziogas Ioannis A. , Karachaliou Georgia-Sofia , Dimitrokallis Nikolaos , Nguyen Brian , Radkani Pejman
Published: November 2024

Currently, there is no reliable method of discerning between low-risk and high-risk intraductal papillary mucinous neoplasms (IPMNs). Operative resection is utilized in an effort to resect those lesions with high-grade dysplasia (HGD) prior to the development of invasive disease. The current guidelines recommend resection for IPMN that involve the main pancreatic duct. Resecting lesions with HGD before their progression to invasive disease and the avoidance of resection in those patients with low-grade dysplasia is the optimal clinical scenario. Therefore, the importance of developing preoperative models able to discern HGD in IPMN patients cannot be overstated. Low-risk patients should be managed with nonsurgical treatment options (typically MRI surveillance), while high-risk patients would undergo resection, hopefully prior to the formation of invasive disease. Current research is evolving in multiple directions. First, there is an ongoing effort to identify reliable markers for predicting malignant transformation of IPMN, mainly focusing on genomic and transcriptomic data from blood, tissue, and cystic fluid. Also, multimodal models of combining biomarkers with clinical and radiographic data seem promising for providing robust and accurate answers of risk levels for IPMN patients.
Exploring Carcinoid Syndrome in Neuroendocrine Tumors: Insights from a Multidisciplinary Narrative Review
Authors: Marasco Matteo , Romano Elena , Arrivi Giulia , Prosperi Daniela , Rinzivillo Maria , Caruso Damiano , Mercantini Paolo , Rossi Michele , Faggiano Antongiulio , Panzuto Francesco
Published: November 2024

Carcinoid syndrome (CS) is a rare condition associated with neuroendocrine tumors (NETs), particularly those originating in the gastrointestinal tract, which secrete bioactive substances like serotonin. The management of CS requires a multidisciplinary approach due to its complex clinical manifestations, including flushing, diarrhea, bronchospasm, and carcinoid heart disease. Optimal care involves collaboration between several professional figures like oncologists, endocrinologists, gastroenterologists, surgeons, and dietitians. Currently, a wide range of treatments are available, focused on both symptom control and tumor burden reduction. Somatostatin analogs (SSAs) are the first-line therapy for symptom relief. Still, in patients with progressive disease or refractory CS, other options include targeted therapies, peptide receptor radionuclide therapy (PRRT), liver-directed therapies, and surgical resection, when feasible. Furthermore, management of complications related to prolonged serotonin release and malnutrition as a result of exocrine pancreatic insufficiency, post-surgical conditions, vitamin deficit, and chronic diarrhea often requires early detection to mitigate symptoms and improve the quality of life in these patients. The complexity of CS necessitates individualized care and continuous coordination among specialists to optimize outcomes and enhance patient well-being.
Demonstrating Effectual Catalysis of Corncob with Solid Acid Sn-NUS-BH in Cyclopentyl Methyl Ether–Water for Co-Producing Reducing Sugar, Furfural, and Xylooligosaccharides
Authors: Yang Dan , Kong Linghui , He Yu-Cai
Published: November 2024

In this research, the biochar-based tin-loaded heterogeneous catalyst Sn-NUS-BH was used for the efficient catalytic conversion of corncob (CC) in a green biphasic system of cyclopentyl methyl ether–water (CPME-H2O). By optimizing the system conditions (CPME to H2O ratio, Sn-NUS-BH dosage, reaction time, and reaction temperature), the stubborn structure of corncobs was maximally disrupted. The chemical composition and structural characteristics (accessibility, lignin surface area, and hydrophobicity) of CC before and after treatment were assessed, demonstrating that the natural physical barriers of CC were disrupted and lignin was effectually eliminated. The accessibility was enhanced from 137.5 mg/g to 518.5 mg/g, the lignin surface area declined from 588.0 m2/g to 325.0 m2/g, and the hydrophobicity was changed from 4.7 L/g to 1.3 L/g. Through the treatment at 170 °C for 20 min, furfural (11.7 g/L) and xylooligosaccharides (4.5 g/L) were acquired in pretreatment liquor. The residual CC could be enzymatically saccharified into reducing sugars in a yield of 65.2%. The combination pretreatment with the tin-based biochar chemocatalyst Sn-NUS-BH combined with the green solvent system CPME-H2O shows great promise in the valorization of biomass.
Identification and Characterization of Fully Human FOLR1-Targeting CAR T Cells for the Treatment of Ovarian Cancer
Authors: Bethke Maria , Abramowski Pierre , Droste Miriam , Felsberger André , Kochsiek Lisa , Kotter Bettina , Plettig Luisa , Antonova Kateryna , Baghdo Salpy , Burzan Nico , Tomszak Florian , Martinez-Osuna Manuel , Eckardt Dominik , Herbel Christoph
Published: November 2024

CAR T cell therapy has been an effective treatment option for hematological malignancies. However, the therapeutic potential of CAR T cells can be reduced by several constraints, partly due to immunogenicity and toxicities. The lack of established workflows enabling thorough evaluation of new candidates, limits comprehensive CAR assessment. To improve the selection of lead CAR candidates, we established a stringent, multistep workflow based on specificity assessments, employing multiple assays and technologies. Moreover, we characterized a human FOLR1-directed CAR binding domain. Selection of binding domains was based on extensive specificity assessment by flow cytometry and imaging, to determine on-/off-target and off-tumor reactivity. CAR T cell functionality and specificity were assessed by high-throughput screening and advanced in vitro assays. Our validation strategy highlights that assays comprehensively characterizing CAR functionality and binding specificity complement each other. Thereby, critical specificity considerations can be addressed early in the development process to overcome current limitations for future CAR T cell therapies.
Non-Immune-Mediated, p27-Associated, Growth Inhibition of Glioblastoma by Class-II-Transactivator (CIITA)
Authors: Tan A Katherine , Henry Aurelie , Goffart Nicolas , Poulet Christophe , Sluijs Jacqueline A. , Hol Elly M. , Bours Vincent , Robe Pierre A.
Published: November 2024

Background: Previous works have shown that the expression of Class-II-Transactivator (CIITA) in tumor cells reduces the growth of glioblastoma (GB) in animal models, but immune effects cannot solely explain this. Here, we searched for immune-independent effects of CIITA on the proliferation of GB. Methods: Murine GL261 and human U87, GM2 and GM3 malignant glioma cells were transfected with CIITA. NSG (immunodeficient) and nude (athymic) mice were injected in the striatum with GL261-wildtype (-WT) and -CIITA, and tumor growth was assessed by immunohistology and luminescence reporter genes. Clonogenic, sphere-formation, and 3D Matrigel-based in vitro growth assays were performed to compare the growth of WT versus CIITA-expressing murine and human cells. Bulk RNA sequencing and RT2 qRT-PCR profiler arrays were performed on these four cell lines to assess RNA expression changes following CIITA transfection. Western blot analysis on several proliferation-associated proteins was performed. Results: The intracerebral growth of murine GL261-CIITA cells was drastically reduced both in immunodeficient and athymic mice. Tumor growth was reduced in vitro in three of the four cell types. RNA sequencing and RT2 profiler array experiments revealed a modulation of gene expression in the PI3-Akt, MAPK- and cell-cycle regulation pathways following CIITA overexpression. Western blot analysis showed an upregulation of p27 in the growth-inhibited cells following this treatment. PDGFR-beta was downregulated in all cells. We did not find consistent regulation of other proteins involved in GB proliferation. Conclusions: Proliferation is drastically reduced by CIITA in GB, both in vivo and in vitro, notably in association with p27-mediated inhibition of cell-cycle pathways.
Structure-Function Relationship of the Ryanodine Receptor Cluster Network in Sinoatrial Node Cells
Authors: Maltsev Alexander V. , Ventura Subirachs Valeria , Monfredi Oliver , Juhaszova Magdalena , Ajay Warrier Pooja , Rakshit Shardul , Tagirova Syevda , Maltsev Anna V. , Stern Michael D. , Lakatta Edward G. , Maltsev Victor A.
Published: November 2024

The rate of spontaneous action potentials (APs) generated by sinoatrial node cells (SANC) is regulated by local Ca2+ release (LCR) from the sarcoplasmic reticulum via Ca2+ release channels (ryanodine receptors, RyRs). LCR events propagate and self-organize within the network of RyR clusters (Ca release units, CRUs) via Ca-induced-Ca-release (CICR) that depends on CRU sizes and locations: While larger CRUs generate stronger release signals, the network’s topology governs signal diffusion and propagation. This study used super-resolution structured illumination microscopy to image the 3D network of CRUs in rabbit SANC. The peripheral CRUs formed a spatial mesh, reflecting the cell surface geometry. Two distinct subpopulations of CRUs were identified within each cell, with size distributions conforming to a two-component Gamma mixture model. Furthermore, neighboring CRUs exhibited repulsive behavior. Functional properties of the CRU network were further examined in a novel numerical SANC model developed using our experimental data. Model simulations revealed that heterogeneities in both CRU sizes and locations facilitate CICR and increase the AP firing rate in a cooperative manner. However, these heterogeneities reduce the effect of β-adrenergic stimulation in terms of its relative change in AP firing rate. The presence of heterogeneities in both sizes and locations allows SANC to reach higher absolute AP firing rates during β-adrenergic stimulation. Thus, the CICR facilitation by heterogeneities in CRU sizes and locations regulates and optimizes cardiac pacemaker cell operation under various physiological conditions. Dysfunction of this optimization could be a key factor in heart rate reserve decline in aging and disease.
Genome-Wide Screening and Characterization of Methyl-CpG-Binding Domain (MBD) Proteins in Arabidopsis Species
Authors: Cui Hong-Hui , Sun Man-Man , Huang Xiao-Juan , Liao Hong-Ze
Published: November 2024

Methyl-CpG-binding domain (MBD) proteins play vital roles in epigenetic gene regulation, and they have diverse molecular, cellular, and biological functions in plants. MBD proteins have been functionally characterized in a few plant species. However, the structure and function of MBD proteins in Arabidopsis halleri and Arabidopsis lyrata remain unknown. In this study, 12 A. halleri MBD (AhMBD) and 13 A. lyrata MBD (AlMBD) genes were identified. A phylogenetic analysis of the Arabidopsis genus showed that the MBD proteins of three species (Arabidopsis thaliana, A. helleri, and A. lyrata) could be classified into eight classes. Expression patterns suggested that the AtMBD genes were expressed in different tissues. We characterized the function of AtMBD3 and found that it was constitutively localized to the nucleus and interacted with several AtMBD protein members. Our results reveal that AtMBD3 is involved in the development of A. thaliana, which may be helpful in further studies on these genes in A. helleri and A. lyrata.
Identification and Gene Fine Mapping of the Bisexual Sterility Mutant Meiosis Abnormal Bisexual Sterility 1 in Rice
Authors: Wan Yingchun , Liu Xiaoqing , Wang Nan , Zeng Zhengming , Jiang Yudong
Published: November 2024

Exploring the genes regulating rice fertility is of great value for studying the molecular mechanisms of rice reproductive development and production practices. In this study, we identified a sterile mutant from the mutant library induced by ethyl methanesulfonate (EMS), designated as meiosis abnormal bisexual sterility 1 (mabs1). The mabs1 mutant exhibits no phenotypic differences from the wild-type during the vegetative growth phase but shows complete sterility during the reproductive growth phase. Phenotypic observations revealed that both pollen and embryo sac fertility are lost in mabs1. Notably, in mabs1, the development of the anther inner and outer walls, tapetum degeneration, and callose synthesis and degradation all proceed normally, yet meiosis fails to form normal tetrads. Genetic analysis indicated that this mutant trait is controlled by a single recessive nuclear gene. By constructing a genetic segregation population, we successfully mapped the MABS1 gene to a 49 kb region between primer markers Y7 and Y9 on chromosome 1. Resequencing revealed a single-nucleotide substitution in the exon of the LOC_Os01g66170 gene, which resulted in a change from Valine to Isoleucine. Subsequent sequencing of this locus in both wild-type and mabs1 mutants confirmed this mutation. Therefore, we have identified the gene at LOC_Os01g66170 as a candidate for MABS1, a previously unreported novel gene involved in rice meiosis. Through RT-qPCR, we found that the expression levels of multiple meiosis-related genes were significantly changed in the mabs1 mutant. Therefore, we believe that MABS1 is also involved in the process of rice meiosis. This study lays the groundwork for a functional study of MABS1.
Mechanisms of Integration and Release of AgNO3 in Chitosan Films and Their Interaction with Nosocomial Pathogens
Authors: Román-Aguirre Manuel , Barraza-Jimenez Diana , Leyva-Porras César , Peinado-Villalobos Roxana , Molina-Jáquez David , Olivas-Espino Joel Arturo , Castillo-González Alva Rocío , Camarillo-Cisneros Javier , Favila-Pérez María Alejandra , Quiñonez-Flores Celia María , Arzate-Quintana Carlos
Published: November 2024

Postsurgical infections are an important cause of implant failure, and biomaterials such as Chitosan can be used as an antimicrobial coating to address this important problem. Characterization of silver distribution was performed by several methods, including Electron scanning microscopy (SEM), Inductively coupled plasma (ICP), and Infrared spectrometry (IR). Antimicrobial activity was tested against Candida albicans ATCC 10231, Staphylococcus aureus ATCC 29213, Escherichia coli ATCC 25922, and Pseudomonas aeruginosa BAA-1744 ATCC 109246. The inhibition assays showed that Chitosan films inhibited 68% of C. albicans growth and 23.5% of E. coli growth; the rest of the microorganisms did not have any statistically relevant inhibition. E. coli, P. aeruginosa, and C. albicans were completely inhibited in films with 0.25 mg/mL of AgNO3 and inhibited 82.5% of S. aureus. The mechanism of integration and release of silver in the films was analyzed by the Density Functional Theory (DFT), considering this analysis of geometry optimization as well as infrared spectroscopy. DFT analysis showed that AgNO3 is not trapped by covalence in chitosan, being a more stable system when it is closer to an OH group. Chitosan films functionalized with antimicrobial compounds are a promising antimicrobial coating for use in biomaterials to prevent postsurgical complications.
Advancements in Parkinson’s Disease Diagnosis: A Comprehensive Survey on Biomarker Integration and Machine Learning
Authors: Pratihar Ruchira , Sankar Ravi
Published: November 2024

This comprehensive review explores the advancements in machine learning algorithms in the diagnosis of Parkinson’s disease (PD) utilizing different biomarkers. It addresses the challenges in the assessment of PD for accurate diagnosis, treatment decisions, and patient care due to difficulties in early and differential diagnosis, subjective clinical assessments, symptom variability, limited objective biomarkers, comorbidity impacts, uneven access to specialized care, and gaps in clinical research. This review provides a detailed review of ongoing biomarker research, technological advancements for objective assessment, and enhanced healthcare infrastructure. It presents a comprehensive evaluation of the use of diverse biomarkers for diagnosing Parkinson’s disease (PD) across various datasets, utilizing machine learning models. Recent research findings are summarized in tables, showcasing key methodologies such as data preprocessing, feature selection, and classification techniques. This review also explores the performance, benefits, and limitations of different diagnostic approaches, providing valuable insights into their effectiveness in PD diagnosis. Moreover, the review addresses the integration of multimodal biomarkers, combining data from different sources to enhance diagnostic accuracy, and disease monitoring. Challenges such as data heterogeneity, variability in symptom progression, and model generalizability are discussed alongside emerging trends and future directions in the field. Ultimately, the application of machine learning (ML) in leveraging diverse biomarkers offers promising avenues for advancing PD diagnosis, paving the way for personalized treatment strategies and improving patient outcomes.
Simplified Gravity Load Collapse Dynamic Analysis of Old-Type Reinforced Concrete Frames
Authors: Megalooikonomou Konstantinos G.
Published: November 2024

The results of shaking table tests from previous studies on a one-story, two-bay reinforced concrete frame—exhibiting both shear and axial failures—were compared with nonlinear dynamic analyses using simplified models intended to evaluate the collapse potential of older reinforced concrete structures. To replicate the nonlinear behavior of columns, whether shear-critical or primarily flexure-dominant, a one-component beam model was applied. This model features a linear elastic element connected in series to a rigid plastic, linearly hardening spring at each end, representing a concentrated plasticity component. To account for strength degradation through path-dependent plasticity, a negative slope model as degradation was implemented, linking points at both shear and axial failure. The shear failure points were determined through pushover analysis of shear-critical columns using Phaethon software. Although the simplified model provided a reasonable approximation of the overall frame response and lateral strength degradation, especially in terms of drift, its reduced computational demands led to some discrepancies between the calculated and measured shear forces and drifts during certain segments of the time-history response.
Comprehensive Code List Associated with Underlying Medical Conditions Identified by the CDC as High-Risk Factors for Progression to Severe COVID-19 Outcomes
Authors: Scott Amie , Atkinson Jo , Ansari Wajeeha , Reimbaeva Maya , Stanford Richard H. , Manuel Fadi , Holtzman Linda , Draica Florin
Published: November 2024

A list of diagnosis codes mapped to CDC-defined high-risk conditions for severe COVID-19 outcomes is currently not available in the literature. We reviewed the CDC list of underlying conditions associated with severe COVID-19 and a coding expert and two clinicians mapped the relevant high-risk conditions to the appropriate ICD-10-CM codes. We additionally assessed the prevalence of these conditions in the Optum de-identified-Clinformatics® Data Mart Database and the Optum de-identified Electronic Health Record dataset. A comprehensive list of approximately 8200 codes were mapped to the CDC-defined high-risk underlying conditions; these ICD-10-CM codes were stratified into three groups corresponding with the CDC strength of evidence category (conclusive, suggestive, or mixed evidence). Applying these codes to administrative claims and EHR datasets demonstrated a consistent prevalence of high-risk conditions over four years (2018–2021). These findings present a comprehensive list of codes that can be used by clinicians and researchers to identify and characterize patients at high risk for severe COVID-19 outcomes.
Preparation and Study of Poly(Vinylidene Fluoride-Co-Hexafluoropropylene)-Based Composite Solid Electrolytes
Authors: Huang Meihong , Lan Lingxiao , Shen Pengcheng , Liang Zhiyong , Wang Feng , Zhong Yuling , Wu Chaoqun , Kong Fanxiao , Hu Qicheng
Published: November 2024

Solid-state electrolytes are widely anticipated to revitalize lithium-ion batteries with high energy density and safety. However, low ionic conductivity and high interfacial resistance at room temperature pose challenges for practical applications. This study combines the rigid oxide electrolyte LLZTO with the flexible polymer electrolyte poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP) to achieve effective coupling of rigidity and flexibility. The semi-interpenetrating network structure endows the PEL composite solid electrolyte with excellent lithium-ion transport capabilities, resulting in an ionic conductivity of up to 5.1 × 10−4 S cm−1 and lithium-ion transference number of 0.41. The assembled LiFePO4/PEL/Li solid-state battery demonstrates an initial discharge capacity of 132 mAh g−1 at a rate of 0.1 C. After 100 charge–discharge cycles, the capacity retention is 81%. This research provides a promising strategy for preparing composite solid electrolytes in solid-state lithium-ion batteries.
Finding a Pied-à-Terre: Harbour Infrastructure Facilitates the Settlement of Non-Native Corals (Tubastraea spp.) in the Southern Caribbean
Authors: Hoeksema Bert W. , van der Schoot Roeland J. , Samimi-Namin Kaveh
Published: November 2024

Semi-submersible platforms are used in the offshore oil and gas industry. They are specialised marine vessels that float on submersed drafts, which are composed of pontoons and columns and can serve as habitats for biofouling marine benthic communities. When these vessels sail from one place to another, either by using their own propellers or being towed, they can act as vectors for introducing non-native marine species. To establish themselves in new areas, these exotic species require suitable benthic habitats. Artificial substrates, such as harbour infrastructure where such vessels are moored, appear to be highly suitable for this purpose. In the present study, a mooring buoy and a harbour piling at Curaçao (southern Caribbean), frequently used by semi-submersible platforms, were found to be colonised by the sun corals Tubastraea coccinea and T. tagusensis at shallow depths. This report presents the first record of T. tagusensis as an introduced non-native species in the southern Caribbean, highlighting the potential role of harbour infrastructure in facilitating coral settlement at depths shallower than those typically observed. These findings underscore the ecological impact of artificial substrates in supporting invasive species and emphasise the need for monitoring programs and defouling facilities.
Diagnostic Efficacy of Bone SPECT Techniques in Differentiating Unilateral and Bilateral Condylar Hyperplasia
Authors: Anzola Luz Kelly , Venegas Natalia , Jaramillo Maria Clara , Moreno Sergio , Hinojosa Mauricio , Amador Enrique , Orozco Martin , Mut Fernando
Published: November 2024

Objectives: This analytical cross-sectional study evaluates diagnostic approaches for active condylar hyperplasia using bone SPECT techniques. Methods: it was compared the effectiveness of relative activity assessments between condyles and quantitative analysis using the condyle/clivus ratio. Results: This study’s findings reveal that the condyle/clivus ratio method significantly outperforms the relative uptake method, achieving a sensitivity of 90.1% (95% CI: 84.1–94) compared to 40.7% (95% CI: 33.5–48.2), and a specificity of 77.1% (95% CI: 67.4–85) versus 72.9% (95% CI: 62.9–81.5). The condyle/clivus ratio also showed a more favorable negative likelihood ratio of 0.13 compared to 0.82 for relative uptake, and a higher area under the curve (AUC) of 0.8360 versus 0.5679. Statistically significant differences were noted (p = 0.0001). The condyle/clivus ratio method effectively identifies affected condyles in unilateral and bilateral condylar hyperplasia cases. Conclusions: This study emphasizes the importance of incorporating comprehensive clinical evaluations and imaging modalities for assessing condylar growth activity, underscoring the need for tailored reference values in different populations to ensure reliable diagnostic interpretations.
Age as a Predictor of Overall Survival in Colorectal Cancer
Authors: Carbajal-López Berenice , Coronel-Hernández Jossimar , Herrera Marytere , Ruiz-Garcia Erika , Miyagui-Adame Sayako M. , Diaz-Romero Consuelo , Madrigal-Santillán Eduardo Osiris , Esponda-Mendoza Priscila Morales , Pérez-Plasencia Carlos , Calderillo-Ruiz Germán
Published: November 2024

Background: The diagnosis of colorectal cancer (CRC) at early ages has become a challenging trend for oncology due to high rates of mortality worldwide. The correlation of clinical features with young-age prognosis in CRC remains unclear. Therefore, we aimed to describe the clinicopathological features and their impact on the overall survival of young Mexican adults diagnosed with CRC treated in the National Cancer Institute. Methods: This was a retrospective, observational study. The included patients were treated at the National Cancer Institute between 2004 and 2020. The statistical analyses comprised the X2 and t tests, Kaplan–Meier, log rank, and Cox regression. Statistical significances were assessed when p was bilaterally < 0.05. Results: A total of 3652 patients diagnosed with CRC attended the National Cancer Institute. Cases of early onset of CRC increased over the 16 years under study, with significant differences between the median age, from 57 in 2004 to 55 years old in 2020 (F = 5.49; gl: 12 p = 0.019). For this analysis, the population was divided in three groups: young (≤30 years), adults (31–70), and elderly (>70). The young population was mostly composed of men (62%; (n = 63), (p = 0.020), with high rates of metastatic disease (44%) (p = 0.001) and right-side tumors (57%), (p = 0.046), and with 44% with a moderate grade (p = 0.750). According to the overall survival (OS) analysis, the median OS was 29 months for young, versus 170 months for adult and 56 months for elderly patients (p <0.001, HR 1.53, 95% CI 1.11–2.10). A sub-analysis was performed considering only patients with metastatic disease. The median OS was 12 months for young, versus 17 and 9 months for adults and elderly (p = 0.08, HR 1.27, 95% CI 1.02–1.46). Conclusions: CRC diagnosis in the young population is increasing due unhealthy lifestyle habits and lack of screening. This population have clinical features of bad prognosis, such as left side, poor grade differentiation, and metastatic disease, precluding prognosis and OS.
Comparative Investigation of Thromboelastometry and Thrombin Generation for Patients Receiving Direct Oral Anticoagulants or Vitamin K Antagonists
Authors: Tripodi Armando , Capecchi Marco , Scalambrino Erica , Clerici Marigrazia , Scimeca Barbara , Agosti Pasquale , Bucciarelli Paolo , Artoni Andrea , Peyvandi Flora
Published: November 2024

Background. Alterations induced by direct oral anticoagulants (DOACs) or vitamin K antagonists (VKAs) to thromboelastometry and thrombin generation are not well defined. We performed a simultaneous investigation of thromboelastometry and thrombin generation for patients who were chronically anticoagulated with DOACs or VKAs. Methods. A total of 131 patients on DOACs [apixaban (n = 37), rivaroxaban (n = 34), dabigatran (n = 30), edoxaban (n = 30)] and 33 on VKAs were analyzed. Whole blood was analyzed for thromboelastometry and plasma was analyzed for thrombin generation. Results. While the thromboelastometry clotting time (CT) was responsive to the hypocoagulability induced by DOACs or VKAs, clot formation time and maximal clot formation were not. Cumulatively, the parameters denoting the velocity of thrombin generation (lag time, time-to-peak) were relatively less responsive to the hypocoagulability induced by VKAs than DOACs. Conversely, the parameters denoting the quantity of thrombin generation [peak-thrombin and the endogenous thrombin potential (ETP)] were more responsive to the hypocoagulability induced by VKAs than DOACs. Apixaban showed relatively small differences (peak vs. trough) in the plasma concentration and a relatively small (peak vs. trough) difference of hypocoagulability when assessed by the CT or the ETP. The CT and the ETP were strongly correlated with DOAC concentrations or with the VKA-INR. Conclusions. DOACs and VKAs altered thromboelastometry and thrombin generation to an extent that probably reflects the mode of action of these drugs and may also have practical implications for patients’ management. Apixaban showed a small difference of hypocoagulability (peak vs. trough), suggesting a more stable anticoagulation over the daily course of treatment. Based on the correlations of the CT or the ETP vs. the DOAC concentrations, we estimated that critical values of the CT or the ETP would correspond to DOAC concentrations of 400 or 20 ng/mL. Whenever dedicated tests for DOAC concentrations are not available, the CT or the ETP can be used as surrogates to evaluate the level of anticoagulation induced by DOACs.
Comparative CBCT Analysis of Maxillofacial Skeletal Structures in Patients with Unilateral Cleft Lip and Palate and Non-Cleft Individuals
Authors: Haylaz Emre , Kalabalık Fahrettin , Cicek Orhan , Gümüşsoy İsmail , Aytuğar Emre
Published: November 2024

Background: The aim of this study was to evaluate and compare the maxillofacial structures of individuals with unilateral cleft lip and palate (UCLP) and healthy controls using cone beam computed tomography (CBCT). Methods: The study included a total of 90 subjects, comprising 45 randomly selected individuals with UCLP (30 males and 15 females, mean age 14.69 ± 3.95 years) in the study group and 45 healthy individuals (30 males and 15 females, mean age 14.46 ± 3.65 years) in the control group. Maxillofacial measurements were taken in three different planes and categorized into five groups, namely vertical, facial, cranial, maxillary, and mandibular. In the statistical comparison between groups, the significance level was determined as p < 0.05. Results: There were no significant differences in the age and gender distributions between the groups (p > 0.05). Upper anterior face height and posterior face height in the UCLP group were found to be significantly shorter than the control group (p < 0.05). Midface width and depth were inadequate in the UCLP group (p < 0.05). Anterior and posterior cranial base lengths were significantly shorter in individuals with UCLP (p < 0.05). Nasal width and interorbital width were significantly greater in the UCLP group (p < 0.05). In addition, maxillary width, maxillary length, and mandibular width were significantly shorter in the UCLP group than in the control group (p < 0.05). Conclusions: While the control group exhibited generally longer measurements in all three dimensions compared to the study group, the skeletal structures adjacent to the cleft demonstrated the most notable developmental deficiency.
Contributions Regarding the Study of Pulsatility and Resistivity Indices of Uterine Arteries in Term Pregnancies—A Prospective Study in Bucharest, Romania
Authors: Zampieri Giorgia , Matei Alexandra , Roșu George Alexandru , Marin Andrei , Poenaru Mircea Octavian , Ionescu Cringu Antoniu
Published: November 2024

Pregnancy is a complex stage in a woman’s life, considering the physical and psychological changes that occur. The introduction of Doppler studies of the pregnant woman’s vessels and those of the fetus has proven to be a useful tool in evaluating the maternal-fetal relationship. Objective: The study aims to assess the correlations of PI and RI values in term pregnancies. Methods: This analysis is based on the prospective evaluation of medical data from 60 patients who were admitted to the Obstetrics and Gynecology department of Saint Pantelimon Hospital in Bucharest, Romania, from May to August 2024. Among the examined parameters are patient age, blood pressure, amniotic fluid quantity, placenta location, and pulsatility and resistivity indices of uterine arteries. Results: A higher diastolic blood pressure is associated with higher mean PI and RI values, indicating that diastolic blood pressure has a significant correlation to these values. The mean RI shows a moderately negative and significant correlation, suggesting that a lower level of amniotic fluid is associated with a higher mean RI. Regarding the PI value of the uterine arteries, the p-value suggests that the difference between the groups with and without associated diseases is statistically significant. Placental insertion on the anterior or posterior uterine wall does not have a significant impact on the PI and RI values of the uterine arteries, but the values are higher in the contralateral part of the placental insertion. Conclusions: These results strengthen the evidence previously demonstrated. Uterine artery Doppler ultrasonography is an extremely useful tool in monitoring and managing high-risk pregnancies.
A New Laboratory Tool for COVID-19 Severity Prediction, CENIL Score
Authors: Saricaoglu Elif Mukime , Coskun Belgin , Ayhan Muge , Akinci Esragul , Kayaaslan Bircan , Aypak Adalet , Tekce Ayse Yasemin Tezer , Hasanoglu Imran , Kaya Ayse , Eser Fatma , Bilir Yesim Aybar , Ozdemir Burcu , Buzgan Turan , Guner Rahmet
Published: November 2024

Background/Objectives: Several studies investigated the risk factors for severe COVID-19-related outcomes. Early identification and proper treatment of COVID-19 patients who may develop severe pneumonia are crucial. The aim of this study was to detect the importance of the laboratory parameters for risk prediction of severe pneumonia in COVID-19 patients. Methods: This retrospective cohort study included COVID-19 patients’ laboratory parameters at admission. Biochemical, hematological, coagulation, and inflammatory parameters values were compared between the non-severe and severe groups. Results: A total of 534 COVID-19 patients were screened, and 472 of them were included in this study. The mean age of patients was 64 (±3.1) years; 242 (51.3%) were men. A total of 204 (43.2%) patients were diagnosed as severe cases. The independent predictors of severe illness were C-reactive peptide, Eosinophil, neutrophil–lymphocyte ratio, interleukin-6, and lactate dehydrogenase. These parameters were named as CENIL scores from 0 to 5 points. The findings of this study indicate that these biomarkers identified tend to increase progressively with disease severity in severe COVID-19 patients. Additionally, the CENIL risk score identified a specific cut-off value of 3, highlighting it as a critical threshold for identifying patients at high risk of severe COVID-19 progression. Conclusions: In this study, we identified biomarkers—including CRP, eosinophil count, NLR, IL-6, and LDH—named as CENIL risk score that can help predict the likelihood of severe disease at diagnosis. Clinicians may be more vigilant regarding the development of severe disease in patients with high CENIL risk scores, guided by clinical and radiological findings.
Three-Dimensional Path Following Control for Underactuated AUV Based on Ocean Current Observer
Authors: He Long , Zhang Ya , Li Shizhong , Li Bo , Yuan Zeihui
Published: November 2024

In the marine environment, the motion characteristics of Autonomous Underwater Vehicles (AUVs) are influenced by unknown factors such as time-varying ocean currents, thereby amplifying the complexity involved in the design of path-following controllers. In this study, a backstepping sliding mode control method based on a current observer and nonlinear disturbance observer (NDO) has been developed, addressing the 3D path-following issue for AUVs operating in the ocean environment. Accounting for uncertainties like variable ocean currents, this research establishes the AUV’s kinematics and dynamics models and formulates the tracking error within the Frenet–Serret coordinate system. The kinematic controller is designed through the line-of-sight method and the backstepping method, and the dynamic controller is developed using the nonlinear disturbance observer and the integral sliding mode control method. Furthermore, an ocean current observer is developed for the real-time estimation of current velocities, thereby mitigating the effects of ocean currents on navigational performance. Theoretical analysis confirms the system’s asymptotic stability, while numerical simulation attests to the proposed method’s efficacy and robustness in 3D path following.
Autonomous Underwater Vehicle Docking Under Realistic Assumptions Using Deep Reinforcement Learning
Authors: Palomeras Narcís , Ridao Pere
Published: November 2024

This paper addresses the challenge of docking an Autonomous Underwater Vehicle (AUV) under realistic conditions. Traditional model-based controllers are often constrained by the complexity and variability of the ocean environment. To overcome these limitations, we propose a Deep Reinforcement Learning (DRL) approach to manage the homing and docking maneuver. First, we define the proposed docking task in terms of its observations, actions, and reward function, aiming to bridge the gap between theoretical DRL research and docking algorithms tested on real vehicles. Additionally, we introduce a novel observation space that combines raw noisy observations with filtered data obtained using an Extended Kalman Filter (EKF). We demonstrate the effectiveness of this approach through simulations with various DRL algorithms, showing that the proposed observations can produce stable policies in fewer learning steps, outperforming not only traditional control methods but also policies obtained by the same DRL algorithms in noise-free environments.
A Fuzzy Logic Control-Based Adaptive Gear-Shifting Considering Load Variation and Slope Gradient for Multi-Speed Automated Manual Transmission (AMT) Electric Heavy-Duty Commercial Vehicles
Authors: Wang Shanglin , Liu Xiaodong , Zhang Xuening , Zhao Yulong , Xiong Yanfeng
Published: November 2024

The current trend in pure electric heavy-duty commercial vehicles (PEHCVs) is the increasing utilization of automated manual transmission (AMT) to optimize driveline efficiency. However, the existing gear-shift schedule of AMT fails to account for crucial factors such as vehicle load and slope gradient, leading to frequent gear position changes during uphill driving, compromising driving comfort. This study proposes a novel approach incorporating the vehicle’s load and slope gradient to develop an enhanced gear-shift strategy based on fuzzy logic control to address this issue more effectively. Initially, a dynamic gear-shift schedule was formulated for a 6-speed AMT-equipped PEHCV, followed by an analysis of the impact of vehicle load and slope gradient on the gear-shift schedule. Subsequently, an adaptive gear-shift design framework was developed using fuzzy logic control, considering inputs such as acceleration pedal opening, vehicle load, and slope gradient. Simultaneously, the velocity correction factor was designed as an output to adjust the velocity of gear-shift points based on the dynamic gear-shift schedule. Finally, simulations were conducted under various operating scenarios, including different slope gradients, varying vehicle loads, changing pedal openings, and random scenarios to compare and validate the proposed gear-shift schedule against its predecessor—the previous dynamic gear-shift schedule. The results demonstrate that the proposed gear-shift schedule exhibits exceptional adaptability to various driving scenarios. The average acceleration time can be reduced by over 20%, while the gear-shift frequency within 200 s can be decreased by more than 30 times.
Characterization of Single-Event Effects in a Microcontroller with an Artificial Neural Network Accelerator
Authors: Imianosky Carolina , Mattos André M. P. , Santos Douglas A. , Melo Douglas R. , Kastriotou Maria , Cazzaniga Carlo , Dilillo Luigi
Published: November 2024

Artificial neural networks (ANNs) have become essential components in various safety-critical applications, including autonomous vehicles, medical devices, and avionics, where system failures can lead to severe risks. Edge AI devices, which process data locally without relying on the cloud, are increasingly used to meet the performance and real-time demands of these applications. However, their reliability in radiation-prone environments is a significant concern. In this context, this paper evaluates the MAX78000, an ultra-low-power Edge AI microcontroller with a hardware-based convolutional neural network (CNN) accelerator, focusing on its behavior in radiation environments. To assess the reliability of the MAX78000, we performed a test campaign at the ChipIR neutron irradiation facility using two different ANNs. We implemented techniques to improve system observability during ANN inference and analyzed the radiation-induced errors observed. The results present a comparative analysis between the two ANN architectures, which shows that the complexity of the ANN directly impacts its reliability.
Design of High-Speed Thin-Film Lithium Niobate Modulator Utilizing Flip-Chip Bonding with Bump Contacts
Authors: Yin Yihui , Yang Jiayu , Li Haiou , Yang Wanli , Li Yue , Li Hanyu
Published: November 2024

Currently, the high-speed performance of thin-film lithium niobate electro-optic modulator chips is evolving rapidly. Nevertheless, due to the inherent technical limitations imposed by the packaging design and material architecture, the intrinsic electro-optic bandwidth of thin-film lithium niobate electro-optic modulator chips often exceeds the bandwidth of their packaging interfaces, which can constrain the realization of modulation performance. Bump bonding emerges as a high-bandwidth EO interconnection technology, outperforming wire bonding for faster optical communication. In this paper, we present a high-speed thin-film lithium niobate modulator chip tailored for concave–convex bonding, alongside an analysis and design of the chip’s flip-chip bonding packaging. By exploiting the superior electrical characteristics of concave–convex bonding, we effectively mitigate the radio frequency losses of modulator chip and packaging. The simulated half-wave voltage (Vπ) of 3.5 V and E-O modulation bandwidth greater than 150 GHz is obtained for a 0.5 cm long modulator after flip-chip bonding packaging.
LIDeepDet: Deepfake Detection via Image Decomposition and Advanced Lighting Information Analysis
Authors: Lai Zhimao , Li Jicheng , Wang Chuntao , Wu Jianhua , Jiang Donghua
Published: November 2024

The proliferation of AI-generated content (AIGC) has empowered non-experts to create highly realistic Deepfake images and videos using user-friendly software, posing significant challenges to the legal system, particularly in criminal investigations, court proceedings, and accident analyses. The absence of reliable Deepfake verification methods threatens the integrity of legal processes. In response, researchers have explored deep forgery detection, proposing various forensic techniques. However, the swift evolution of deep forgery creation and the limited generalizability of current detection methods impede practical application. We introduce a new deep forgery detection method that utilizes image decomposition and lighting inconsistency. By exploiting inherent discrepancies in imaging environments between genuine and fabricated images, this method extracts robust lighting cues and mitigates disturbances from environmental factors, revealing deeper-level alterations. A crucial element is the lighting information feature extractor, designed according to color constancy principles, to identify inconsistencies in lighting conditions. To address lighting variations, we employ a face material feature extractor using Pattern of Local Gravitational Force (PLGF), which selectively processes image patterns with defined convolutional masks to isolate and focus on reflectance coefficients, rich in textural details essential for forgery detection. Utilizing the Lambertian lighting model, we generate lighting direction vectors across frames to provide temporal context for detection. This framework processes RGB images, face reflectance maps, lighting features, and lighting direction vectors as multi-channel inputs, applying a cross-attention mechanism at the feature level to enhance detection accuracy and adaptability. Experimental results show that our proposed method performs exceptionally well and is widely applicable across multiple datasets, underscoring its importance in advancing deep forgery detection.
An Explainable Data-Driven Optimization Method for Unmanned Autonomous System Performance Assessment
Authors: Yi Hang , Zhang Haisong , Wang Hao , Wang Wenming , Jia Lixin , Feng Lihang , Wang Dong
Published: November 2024

Unmanned autonomous systems (UASs), including drones and robotics, are widely employed across various fields. Despite significant advances in AI-enhanced intelligent systems, there remains a notable deficiency in the interpretability and comprehensive quantitative evaluation of these systems. The existing literature has primarily focused on constructing evaluation frameworks and methods, but has often overlooked the rationality and reliability of these methods. To address these challenges, this paper proposes an innovative optimization evaluation method for data-driven unmanned autonomous systems. By optimizing the weights of existing indicators based on data distribution characteristics, this method enhances the stability and reliability of assessment outcomes. Furthermore, interpretability techniques such as Local Interpretable Model-agnostic Explanations (LIMEs) and Partial Dependence Plots (PDPs) were employed to verify the effectiveness of the designed evaluation indicators, thereby ensuring the robustness of the evaluation system. The experimental results validated the effectiveness of the proposed approach.