bluuebunny/crossref_metadata_2025 huggingface dataset:
The Influence of Mass on Dynamic Response of Cracked Timoshenko Beam with Restrained End Conditions: The Truncated Theory
Authors: De Rosa Maria Anna , Ceraldi Carla , Martin Hector D. , Onorato Antonella , Piovan Marcelo Tulio , Lippiello Maria
Published: February 2025

In this paper, the dynamic response of the Timoshenko cracked beam subjected to a mass is investigated. In turn, it is assumed that the beam has its ends restrained with both transverse and rotational elastic springs. Based on an alternative beam theory, truncated Timoshenko theory (TTT), the governing equations of motion of the cracked beam are derived and the influence of a mass on the behavior of free vibrations is investigated. The novelty of the proposed approach lies in the fact that the variational method used in the truncated theory simplifies the derivation of the equation of motion via the classical theory, and the perfect analogy between the two theories is shown. The objective of the present formulation lies in finding the equations of the truncated Timoshenko model with their corresponding boundary conditions and establishing their mathematical similarity with the geometric approach. It is shown that the differential equations with their corresponding boundary conditions, used to solve the dynamic problem of Timoshenko truncated beams through variational formulations, have the same form as those obtained through the direct method. Finally, some numerical examples are carried out to evaluate the influence of a mass and its position on the vibration performances of the cracked Timoshenko model. Additionally, the effects of the crack positions, the shear deformation and rotational inertia, and the yielding constraints on the natural frequencies are also discussed in some numerical examples.
Research on NOx Emissions Testing and Optimization Strategies for Diesel Engines Under Low-Load Cycles
Authors: Wang Fengbin , Zhao Jianfu , Li Tengteng , Guan Peng , Liu Shuangxi , Wei Haiqiao , Zhou Lei
Published: February 2025

Under low-load cycles (LLCs), the issue of high NOx emissions from diesel engines is attracting widespread attention. Through a combination of experimental and simulation approaches, the NOx emission behavior under LLC conditions was investigated. Furthermore, the optimization strategies for reducing NOx emissions was studied based on a dual selective catalytic reduction (SCR) after-treatment system. The results indicate that emissions at load rates below 30% during LLCs account for more than 67.5% of the total cycle emissions, particularly under idling and start-stop conditions. Moreover, it was found that NOx emissions decrease significantly by using a pre-positioned dual SCR after-treatment system. And, the closer the SCR is to the engine, the higher the NOx conversion efficiency becomes. As the SCR’s position is adjusted, the rate of NOx removal stabilizes, achieving a maximum reduction in NOx concentration of up to 60.1%.
On Stability of Non-Surjective Coarse Isometries of Banach Spaces
Authors: Sun Yuqi , Zhang Wen
Published: February 2025

In this paper, we establish the stability of the almost-surjective coarse isometries of Banach spaces by means of the weak stability condition. In addition, we also discuss the existence of coarse left-inverse operators in classical Banach spaces. Making use of them, we generalize several known results related to ε-isometries.
Reduced Bone Quality of Sacrum and Lumbal Vertebrae Spongiosa in Toll-like Receptor 2- and Toll-like Receptor 4-Knockout Mice: A Blinded Micro-Computerized Analysis
Authors: Roth Kilian , Pallua Johannes Dominikus , Degenhart Gerald , De Zordo Tobias , Kremser Christian , Reif Christian , Streif Werner , Schirmer Michael
Published: February 2025

Toll-like receptors (TLRs) are pivotal in modulating immune responses and have been implicated in bone remodeling. This in vivo study investigates the impact of TLR2 and TLR4 signaling on trabecular bone structure using micro-computed tomography in a murine model. Sacrum and lumbar vertebrae (L5, L6) from wildtype (WT), TLR2-knockout (TLR2-KO), and TLR4-knockout (TLR4-KO) mice were analyzed, with trabecular parameters such as connectivity density (Conn-Dens), trabecular thickness (DT-TbTh), and variability metrics (DT-Tb,(1/N),SD and DT-TbThSD) assessed. The results revealed significant differences among genotypes: TLR4-KO mice exhibited increased variability in trabecular distribution, indicating less stable bone structures, while TLR-KO mice showed lower variability in trabecular thickness, suggesting enhanced uniformity and robustness. BV/TV and 3D reconstructions highlighted lower bone volume fractions in the sacrum compared to lumbar vertebrae across genotypes, consistent with human observations of reduced sacral bone volume in spondyloarthritis (SpA). Interestingly, bone changes were independent of immunization-induced SpA, emphasizing a direct role in TLR signaling. These findings provide novel insights into the role of TLRs in bone microarchitecture and suggest implications for bone-related pathologies, particularly those involving inflammatory pathways. Future research may explore the translational relevance of TLR-mediated mechanisms in osteopenia and osteoporosis.
Enhanced Bladder Regeneration with Adipose-Derived Stem Cell-Seeded Silk Fibroin Scaffolds: A Comparative Analysis
Authors: Hendawy Hanan , Farag Ahmed , Elhaieg Asmaa , Metwllay Elsayed , Shimada Kazumi , Elfadadny Ahmed , Tanaka Ryou
Published: February 2025

Effective bladder reconstruction remains a significant challenge in urology, particularly for conditions requiring partial or complete bladder replacement. In this study, the efficacy is evaluated of two types of scaffolds, silk fibroin (SF) and adipose-derived stem cells (ADSCs-SF), in promoting bladder regeneration and their associated outcomes. A rat model was used to compare the surgical outcomes and morphological recovery of bladder tissues implanted with SF and ADSCs-SF scaffolds. Post-operative recovery, including voiding ability and complication rates, was assessed. The morphological and histological changes of the regenerated bladder tissue were evaluated at multiple time points (2, 4, 8, and 12 weeks) using gross tissue analysis, histometric assessments, and immunohistochemical staining. Both scaffold types demonstrated successful integration into the bladder wall with no significant differences in body weight or voiding issues. The SF scaffold group exhibited graft shrinkage and a 41.6% incidence of bladder calculus formation. In contrast, the ADSCs-SF scaffold facilitated superior morphological restoration, with bladder tissue progressively adopting a more normal shape and no incidence of bladder calculus. Histological analysis revealed that the ADSCs-SF scaffold significantly promoted the regeneration of a more organized urothelium layer and smooth muscle tissue. It also resulted in higher vessel density and reduced infiltration of inflammatory cells when compared to the SF scaffold alone. Additionally, the ADSCs-SF group exhibited enhanced expression of key markers, including uroplakin III, a urothelial marker, and α-SMA, a smooth muscle cell marker. These findings suggest that the ADSCs-SF scaffold not only supports the structural integrity of the bladder but also improves tissue regeneration and reduces adverse inflammatory responses, offering a promising approach for bladder repair and reconstruction.
Balneotherapy as a Complementary Intervention for Stress and Cortisol Reduction: Findings from a Randomized Controlled Trial
Authors: Rapolienė Lolita , Rapolis Dovydas , Bredelytė Aelita , Taletavičienė Giedrė , Fioravanti Antonella , Martinkėnas Arvydas
Published: February 2025

Background: In our modern era, stress has become a pervasive challenge, affecting individuals across all ages and backgrounds. Acute or chronic stress and elevated cortisol levels are known to impair neurological function and hinder rehabilitation outcomes. Therefore, effective treatment methods that reduce stress, enhance mental health, and promote overall well-being are urgently needed. The aim of this study was to evaluate the seasonal impact of balneotherapy on distress, as measured by the General Symptoms Distress Scale (GSDS), and well-being, as assessed using the Arizona Integrative Outcomes Scale (AIOS), and the effect of winter balneotherapy on salivary cortisol levels. Methods: In 2023, a multicenter, single-blind, parallel-group, randomized controlled trial was carried out across six medical spa centers in Lithuania. Participants with a stress intensity greater than 3 points on the Visual Analogue Scale (VAS) underwent combined natural resource-based therapies over a 1- to 2-week treatment period. Outcomes were assessed using the General Symptom Distress and Arizona Integrative Outcomes scales, along with salivary cortisol measurements after winter intervention. Results: The results demonstrated a significant reduction in distress intensity by 1–3.5 points (VAS), with winter interventions showing greater efficacy compared to summer. Participants also experienced an increase in well-being by up to 3 points (VAS), improved stress management by up to 1.9 points (VAS), and a reduction in salivary cortisol levels by 0.9 units following winter-based treatments. Some gender differences emerged in specific groups. Conclusions: Our study provides robust evidence for the stress-reducing effects of balneotherapy, particularly highlighting the enhanced efficacy of winter interventions. These findings are especially relevant for neurological rehabilitation, where stress reduction and improved autonomic regulation can support neuroplasticity, recovery processes, and overall quality of life. This research offers valuable insights for developing holistic, seasonally optimized strategies to aid stress management and promote neurological health.
A Deep Learning Framework for Corrosion Assessment of Steel Structures Using Inception v3 Model
Authors: Huang Xinghong , Duan Zhen , Hao Shaojin , Hou Jia , Chen Wei , Cai Lixiong
Published: February 2025

Corrosion detection plays a crucial role in the effective lifecycle management of steel structures, significantly impacting maintenance strategies and operational performance. This study presents a machine vision-based approach for classifying corrosion levels in Q235 steel, providing valuable insights for lifecycle assessment and decision-making. Accelerated salt spray tests were performed to simulate corrosion progression over multiple cycles, resulting in a comprehensive dataset comprising surface images and corresponding eight loss measurements. A comparative evaluation with other architectures, namely, AlexNet, ResNet, and VggNet, demonstrated that the Inception v3 model achieved superior classification accuracy, exceeding 95%. This method offers an effective and precise solution for corrosion evaluation, supporting proactive maintenance planning and optimal resource allocation throughout the lifecycle of steel structures. By leveraging advanced deep learning techniques, the approach provides a scalable and efficient framework for enhancing the sustainability and safety of steel infrastructure.
Go Wish Card Game for Meaningful Conversations in the Oncology Healthcare Context: A Narrative Review
Authors: Paiva Bianca Sakamoto Ribeiro , Trevizan Fulvio Bergamo , de Oliveira Lívia Costa , da Costa Rosa Karla Santos , Betussi Vitória Aparecida , Lourenço Bruna Minto , Julião Miguel , Paiva Carlos Eduardo
Published: February 2025

The Go Wish Card Game (GWCG) is emerging as a valuable tool for facilitating end-of-life (EoL) discussions, particularly in oncology care where patients face complex treatment decisions. This review investigates the GWCG’s intended use, its application in oncology settings, and best practices for introducing it to patients. It also addresses the challenges and barriers to its implementation in clinical practice. A search for scientific evidence revealed a significant gap in the literature: while various sources, including qualitative studies and reviews, were reviewed, only a small portion focused on intervention outcomes. This underscores the need for more comprehensive studies to evaluate the GWCG’s effectiveness, especially in EoL care. Despite its potential to foster meaningful conversations and support informed decision-making, successful implementation requires overcoming barriers such as patient resistance and the need for a sensitive, gradual approach to EoL topics. Further research, particularly clinical trials, is essential to confirm its broader applicability and effectiveness.
Possibilities of Overcoming Resistance to Osimertinib in NSCLC Patients with Mutations in the EGFR Gene
Authors: Nicoś Marcin , Sroka-Bartnicka Anna , Kalinka Ewa , Krawczyk Paweł
Published: February 2025

The advancement of genetic research has changed the treatment management of non-small cell lung cancer (NSCLC) and opened the era of personalized medicine. Currently, three generations of EGFR tyrosine kinase inhibitors (TKIs) are used in the treatment of NSCLC patients with activating mutations in the EGFR gene, and ongoing clinical trials examine the safety and effectiveness of new third and fourth generations. Osimertinib, a third generation of TKIs that binds irreversibly to abnormal tyrosine kinase, may be applied in various indications in patients with NSCLC: (i) in the second and subsequent lines of therapy in patients with resistance to first-generation or second-generation EGFR TKIs, (ii) in the first line of treatment in monotherapy in NSCLC patients with frequent or rare EGFR mutations, (iii) in combination with chemotherapy in patients with locally advanced or metastatic NSCLC with frequent EGFR mutations, (iv) in consolidation therapy in patients with locally advanced NSCLC who had previously received chemoradiotherapy, (v) in adjuvant treatment of NSCLC patients with stage IB—IIIA undergoing radical surgical resection. Despite the high efficacy of osimertinib in NSCLC patients harboring EGFR mutations, resistance driven in EGFR-dependent or EGFR-independent mechanisms may occur. Since resistance to osimertinib is poorly understood, the following review presents the overview of resistance mechanisms to osimertinib, methodological approaches for the resistance diagnosis, and the up-to-date treatment possibilities for overcoming the resistance process.
Ionizing Radiation May Induce Tumors Partly Through the Alteration or Regulation of Mismatch Repair Genes
Authors: Sun Mingzhu , Monahan Kevin , Moquet Jayne , Barnard Stephen
Published: February 2025

Ionizing radiation is mutagenic and carcinogenic, and it is reported to induce primary and secondary tumors with intestinal tumors being one of the most commonly observed. However, the pathological and molecular mechanism(s) underlying the radiation-associated tumorigenesis remain unclear. A link between radiation and somatic tumorigenesis partly through genetic, epigenetic alteration and/or regulation of mismatch repair (MMR) genes has been hypothesized for the first time within this review. Clinical observations and experimental findings provide significant support for this association including MMR mutations as well as altered MMR RNA and protein expressions that occurred post-exposure, although existing evidence in published literature is sparse in this niche area. Some speculative mechanisms are suggested with this review to inform future research. Further studies are needed to understand the roles of the MMR system in response to radiation and to test this possible connection which could potentially provide useful and urgently needed information for clinical guidance.
Cytokine-Induced Killer Cell Immunotherapy Reduces Recurrence in Patients with Early-Stage Hepatocellular Carcinoma
Authors: Kim Dong Hyun , Kim Eun Min , Lee Jae Seung , Kim Mi Na , Kim Beom Kyung , Kim Seung Up , Park Jun Yong , Choi Gi Hong , Ahn Sang Hoon , Lee Hye Won , Kim Do Young
Published: February 2025

Background/Objectives: Cytokine-induced killer (CIK) cell immunotherapy has shown promise in reducing recurrence and improving survival outcomes in hepatocellular carcinoma (HCC). We evaluated the efficacy and safety of CIK cell therapy in a real-world clinical setting. Methods: A retrospective analysis was conducted on 49 patients who received CIK cell therapy after curative resection or radiofrequency ablation, compared with 49 matched control patients via 1:1 propensity score matching. The primary endpoint was recurrence-free survival (RFS), and the secondary endpoint was overall survival (OS). Results: The median follow-up durations were 19.1 months for the immune cell group and 67.7 months for the control group. In univariable analysis, the immune cell group demonstrated a prolonged RFS than the control group (hazard ratio [HR], 0.32; 95% CI, 0.15–0.71; log-rank p = 0.001). The median RFS was not reached in the immune cell group but was 48.62 months in the control group. A multivariable Cox regression model identified CIK cell therapy as a significant factor associated with a reduced risk of HCC recurrence (adjusted HR, 0.32; 95% CI, 0.15–0.71; p = 0.005). The median OS was not reached in either group; no significant differences in OS were observed between the immune cell and control groups (log-rank p = 0.082). The overall incidence of adverse events was low, and no Grade 3 or 4 events were reported. Conclusions: Adjuvant CIK cell immunotherapy after curative treatment significantly prolongs RFS in early-stage HCC patients. Further research regarding the broader applications of CIK cell immunotherapy in HCC is warranted.
Effects of Microplastic Accumulation on Neuronal Death After Global Cerebral Ischemia
Authors: Kim Dong Yeon , Park Min Kyu , Yang Hyun Wook , Woo Seo Young , Jung Hyun Ho , Son Dae-Soon , Choi Bo Young , Suh Sang Won
Published: February 2025

Brain ischemia, a condition in which the brain is deprived of blood flow, can lead to a stroke due to blocked or unstable blood vessels. Global cerebral ischemia (GCI), characterized by an interruption in blood flow, deprives the brain of oxygen and nutrients, producing reactive oxygen species (ROS) that trigger cell death, which kills nerve cells. Microplastics (MPs), tiny environmental pollutants, can enter the human body through contaminated food, water, disposable items, cosmetics, and more. Once in the brain, MPs can increase neuroinflammation by overstimulating inflammatory factors such as microglia. MPs can also damage neurons by scratching myelin and microtubules, slowing signal transduction, causing cognitive impairment, and leading to neuronal death. Furthermore, microtubule damage may result in the release of phosphorylated tau proteins, potentially linked to Alzheimer’s disease. We hypothesized that MPs could exacerbate neuroinflammation and microtubule destruction after GCI, leading to increased neuronal death. To test this hypothesis, we administered MPs (0.5 µm) orally at a dose of 50 mg/kg before and after inducing GCI. Staining techniques such as Fluoro-Jade B (FJB), ionized calcium-binding adaptor molecule 1 (Iba-1), cluster of differentiation 68 (CD68), myelin basic protein (MBP), and microtubule-associated protein 2 (MAP2) were used, along with Western blot analysis for interleukin-6 (IL-6), TNF-α, tau-5, and phospho-tau (S396) to evaluate the effects of MPs on neuronal cell death, neuroinflammation, and microtubule destruction. The results showed that MP accumulation significantly increased neuroinflammation, microtubule disruption, and neuronal cell death in the GCI-MP group compared to the GCI-vehicle group. Therefore, this study suggests that MP accumulation in daily life may contribute to the exacerbation of the disease, potentially leading to severe neuronal cell death after GCI.
Gallic Acid Enhances Olaparib-Induced Cell Death and Attenuates Olaparib Resistance in Human Osteosarcoma U2OS Cell Line
Authors: Erdogan Mehmet Kadir , Usca Ayse Busra
Published: February 2025

Cancer remains one of the most formidable diseases globally and continues to be a leading cause of mortality. While chemotherapeutic agents are crucial in cancer treatment, they often come with severe side effects. Furthermore, the development of acquired drug resistance poses a significant challenge in the ongoing battle against cancer. Combining these chemotherapeutic agents with plant-derived phenolic compounds offers a promising approach, potentially reducing side effects and counteracting drug resistance. Phytochemicals, the bioactive compounds found in plants, exhibit a range of health-promoting properties, including anticarcinogenic, antimutagenic, antiproliferative, antioxidant, antimicrobial, neuroprotective, and cardioprotective effects. Their ability to enhance treatment, coupled with their non-toxic, multi-targeted nature and synergistic potential when used alongside conventional drugs, underscores the growing importance of natural therapeutics. In this study, we investigated the anticancer effects of olaparib (OL), a small-molecule PARP inhibitor that has shown promising results in both preclinical and clinical trials, and gallic acid (GA), a phenolic compound, in olaparib-resistant human osteosarcoma U2OS cells (U2OS-PIR). Both parental U2OS and U2OS-PIR cell lines were treated with increasing concentrations of olaparib and gallic acid, and their cytotoxic effects were assessed using the WST-1 cell viability assay. The synergistic potential of OL and GA, based on their determined IC50 values, was further explored in combination treatment. A colony survival assay revealed the combination’s ability to significantly reduce the colony-forming capacity of cancer cells. Additionally, the apoptotic effects of OL and GA, both individually and in combination, were examined in U2OS-PIR cells using acridine orange/ethidium bromide dual staining. The anti-angiogenic properties were assessed through a VEGF ELISA, while the expression of proteins involved in DNA damage and apoptotic signaling pathways was analyzed via Western blot. The results of this study demonstrate that gallic acid effectively suppresses cell viability and colony formation, particularly when used in combination therapy to combat OL resistance. Additionally, GA inhibits angiogenesis and induces DNA damage and apoptosis by modulating key apoptosis-related proteins, including cPARP, Bcl-2, and Bax. These findings highlight gallic acid as a potential compound for enhancing therapeutic efficacy in overcoming acquired drug resistance.
Study on the Effects and Mechanism of Corilagin on A2780 Cell Apoptosis
Authors: Xu Ziyang , Jiang Yuhan , Shan Tiantian , Hu Lei , Wu Minrui , Ji Hanxu , Li Longjie , Yi Yang , Wang Hongxun , Wang Limei
Published: February 2025

Previous studies have demonstrated corilagin’s inhibitory effects on the growth of various cancer cells. Given the limited research on corilagin’s impact on ovarian cancer, a particularly deadly gynecological malignancy, this study aimed to investigate corilagin’s influence on A2780 ovarian cancer cell apoptosis and its underlying mechanisms. The goal was to evaluate corilagin’s potential as a therapeutic agent for ovarian cancer. The results of the CCK-8 assay showed that corilagin inhibited the proliferation of A2780 ovarian cancer cells while exhibiting lower toxicity to normal ovarian surface epithelial cells (IOSE-80). We found that corilagin significantly altered the A2780 cell cycle, decreasing the proportion of cells in the G0/G1 and G2/M phases and inducing cell cycle arrest in the S phase. At low concentrations, corilagin induced apoptosis in A2780 cells, accompanied by a decline in mitochondrial membrane potential and calcium influx. Transcriptome sequencing analysis identified differentially expressed apoptosis-related genes in corilagin-treated A2780 cells, primarily within the PI3K-AKT pathway. Furthermore, qPCR and Western blot results confirmed the upregulation of p53 and Bax genes and the downregulation of BCL-2. Corilagin also increased the expression of apoptotic factors caspase-9, caspase-3, PUMA, and cytochrome C, indicating its ability to induce apoptosis. Overall, corilagin effectively inhibited A2780 cell proliferation, induced cell cycle arrest, and triggered apoptosis. Its anti-tumor effect in vitro suggests its potential as a therapeutic agent for ovarian cancer A2780, especially through the PI3K/p53 pathway.
Performance Study and Machine Learning Model Evaluation of Embedded Micro-Agglomerated Particle TBCs Based on Plasma-Spraying Process
Authors: Xu Shuheng , Xu Zhou , Yin Changdong , Wu Yiwen , Wu Feixiang , Liu Houli , Zhang Zhijun , Yang Guoqing , Huang Jibo , Ye Dongdong
Published: February 2025

The spraying process affects the microstructure and service life of thermal barrier coatings. In this work, by changing the plasma-spraying process, the second-phase micron-agglomerated particles were introduced to prepare embedded micron-agglomerated particle thermal barrier coatings. Conventional thermal barrier coatings and embedded micron-agglomerated particle thermal barrier coatings were prepared by setting spraying process parameters with different powder feeding rates and distances between powder feeders. Sintering experiments and thermal cycling experiments were carried out on conventional thermal barrier coatings and embedded micron-agglomerated particle thermal barrier coatings. The effects of spraying process parameters on the microstructure and thermal cycle life of embedded micron-agglomerated particle thermal barrier coatings were systematically studied. Three machine learning models of BP, SVM, and GA-SVM were established to evaluate the relationship between spraying parameters and coating microstructure and thermal cycle life. The results show that the sintering resistance of the new thermal barrier coating is 500% higher than that of the conventional thermal barrier coating. When the distance between the two powder feeders is 35 mm and the powder feeder 1 rate is 12 g/min, the thermal cycle life of the coating is the best. When using machine learning model evaluation, the evaluation results of the three machine learning models have certain accuracy. Among them, the GA-SVM machine learning model has the best prediction effect and the smallest prediction error. The results of this paper provide a new paradigm for further preparation of thermal barrier coatings with high performance and long life.
The Impact of Electrolytic Cell Parameters on the Boiling Rate of the Electrolyte During Electrolytic Plasma Processing
Authors: Kurmangaliyev Rinat , Mukhametov Yeldos , Rakhadilov Bauyrzhan , Kussainov Rinat , Kadyrbolat Nurlat
Published: February 2025

This study investigates the influence of electrolytic cell parameters on the electrolyte boiling rate during electrolytic plasma processing, a critical stage for plasma formation and subsequent surface modification. Focusing on a coaxial cell configuration with a conical anode and cylindrical cathode, this research employs analytical calculations based on the solution of the Laplace equation in spherical coordinates, validated by numerical simulations using the finite element method (Elcut 6.6), to predict electrolyte boiling times. These results are compared with experimental data, demonstrating good agreement, particularly at higher voltages (−200 V). The analysis reveals that while a simplified model provides a reasonable first approximation, it deviates at lower voltages (−50 V) due to the increasing importance of heat removal, neglected in the model construction. This discrepancy underscores the need for more sophisticated models accounting for non-uniform current distribution and heat transfer effects in complex cell geometries. The findings contribute to a deeper understanding of cathodic electrolytic plasma processing (EPP) dynamics and provide a foundation for optimizing cell design and process parameters for industrial applications such as diffusion saturation of steel components.
Transport Characteristics of Small Molecules Diffusing near Deforming Blood Cells
Authors: Nix Stephanie
Published: February 2025

Understanding the transport of small molecules such as oxygen in biological systems requires knowledge about how molecules dynamically interact with these molecules. This study investigates how red blood cells influence the diffusion of small molecules in simple shear flow by coupling Brownian dynamics simulations with a finite element–boundary integral method to simulate particle transport near spherical and red blood cells. The simulation found that the presence of a rotating cell significantly reduces the effective diffusion rate of small molecules. Specifically, the circulatory flow induced by cell deformation during tank-treading motion leads to a diminished mean squared displacement of particles. Notably, a tumbling red blood cell produces a more pronounced effect on particle motion compared with a spherical cell under identical flow conditions. This research has broader implications for understanding complex diffusion processes in various biological systems, by highlighting the complex interactions between cellular motion and molecular transport.
Big and Fast: GPS Loggers Reveal Long-Range Movements in a Large, Riverine Turtle
Authors: Sirsi Shashwat , MacLaren Andrew R. , Foley Daniel H. , Bohannon Austin M. A. , Rose Jonathan P. , Halstead Brian J. , Forstner Michael R. J.
Published: February 2025

Rio Grande Cooters (Pseudemys gorzugi) occupy the Rio Grande watershed and have among the smallest ranges of all North American freshwater turtles. Anthropogenic dewatering is considered to have caused range contractions and population declines. We sought to facilitate management recommendations by determining the extent of movement and potential associations with extrinsic cues. We conducted a GPS-enabled telemetry study from August 2015 to May 2017 on the Devils River in Texas, USA. We included Capture–Mark–Recapture data from 2011, 2014, and 2015–2018 to determine population status in conjunction with movement ecology. Turtles showed increased movement as streamflow and water depth increased. Larger movements were also made mid-year, coincident with the peak nesting season. We speculate that seasonality and increases in streamflow facilitate switches from slower, localized movement to transiting modes. We observed individual heterogeneity in transitory movements. Such movements led us to maintain our population estimate of 726 to 1219 individuals is representative of the entire Devils River. The extent of movement in P. gorzugi has been previously underestimated and long-range movements could explain observed genetic structure. Future efforts to re-establish natural flow regimes in the Rio Grande basin could potentially be the most effective management approach for this range-restricted chelonian.
Chemotherapy-Induced Unconjugated Hyperbilirubinemia Complicated by Other Trigger Factors in a Child with T-Cell Acute Lymphoblastic Leukaemia and UGT1A1 Mutation-Associated Gilbert Syndrome
Authors: Khoo Mohammad Shukri , Jamalullail Sharifah Naiema , Loh C-Khai , Lau Sie Chong Doris , Alias Hamidah
Published: February 2025

Gilbert syndrome (GS) is an inherited disorder characterised by unconjugated hyperbilirubinemia due to a deficiency in hepatic UDP-glucuronosyltransferase 1A1 (UGT1A1) enzyme activity, responsible for bilirubin glucuronidation. This results in decreased bilirubin conjugation and excretion, leading to elevated serum unconjugated bilirubin levels. In T-cell acute lymphoblastic leukaemia (T-ALL), treatment typically involves intensive chemotherapy regimens that include agents metabolised by the liver, requiring careful consideration of liver function and bilirubin metabolism in patients with concurrent GS. We present the case of a 15-year-old male who was diagnosed with T-ALL and treated with a chemotherapy regimen following the modified Dutch Child Oncology Group ALL-9 (High Risk) protocol. Concurrently, the patient was observed to have persistent unconjugated hyperbilirubinemia aggravated by infection and fasting despite normal to mildly deranged liver function, which was initially assumed to be attributed by 6-Mercaptopurine (6-MP). Further workup confirmed a diagnosis of GS based on clinical history, laboratory findings, and genetic testing. We recommend performing a genetic analysis of UGT1A1 in patients presenting with chemotherapy-induced hyperbilirubinemia with no signs of liver impairment. This aims to prevent unnecessary alterations in chemotherapy regimens that could potentially increase the risk of relapse.
Radical Prostatectomy in Multimodal Setting: Current Role of Neoadjuvant and Adjuvant Hormonal or Chemotherapy-Based Treatments
Authors: Oderda Marco , Calleris Giorgio , Iorio Giuseppe Carlo , Simone Giuseppe , Gontero Paolo
Published: February 2025

The role of neoadjuvant and adjuvant hormonal or chemotherapy-based treatments before or after radical prostatectomy in localized or locally advanced high-risk prostate cancer (PCa) is currently debatable. European guidelines recommend adjuvant androgen deprivation therapy (ADT) only in pN1 patients after extended pelvic lymph node dissection based on outdated evidence on standard hormonal agents. The introduction of new-generation androgen receptor targeting agents (ARTAs) has revolutionized the treatment of metastatic PCa and might also impact the perioperative management of patients with high-risk localized disease. In the last years, a renewed interest has also arisen in chemotherapy-based neoadjuvant or adjuvant treatments alone or in combination with ADT and/or ARTAs. In the present review, we gathered the current evidence on the oncological outcomes of neoadjuvant and adjuvant systemic treatments in surgically treated patients with localized or locally advanced PCa. Despite mild benefits in terms of pathologic responses or oncological outcomes reported in some studies investigating ADT and/or chemotherapy in this setting of patients, strong evidence to support their use in clinical practice is lacking. Promising data in favor of ARTAs have been gathered from phase II trials and prospective series, but definitive results from phase III trials are awaited to confirm these findings.
Stress Factors in Higher Education: A Data Analysis Case
Authors: Bojorque Rodolfo , Moscoso Fernando , Pesántez Fernando , Flores Ángela
Published: February 2025

This study investigates stressors in higher education, focusing on their impact on students and faculty at Universidad Politécnica Salesiana (UPS) and using eight years of comprehensive data. Employing data mining techniques, the research analyzed enrollment, retention, graduation, employability, socioeconomic status, academic performance, and faculty workload to uncover patterns affecting academic outcomes. The study found that UPS exhibits a stable educational system, maintaining consistent metrics across student success indicators. However, the COVID-19 pandemic presented unique stressors, evidenced by a paradoxical increase in student grades during heightened faculty stress levels. This anomaly suggests a potential link between academic rigor and faculty well-being during systemic disruptions. Stressors affecting students directly correlated with reduced academic performance, highlighting the importance of early detection and intervention. Conversely, faculty stress was reflected in adjustments to grading practices, raising questions about institutional pressures and faculty motivation. These findings emphasize the value of proactive data analytics in identifying stress-induced anomalies to support student success and faculty well-being. The study advocates for further research on faculty burnout, motivation, and institutional strategies to mitigate stressors, underscoring the potential of data-driven approaches to enhance the quality and sustainability of higher education ecosystems.
Evaluation of the Performance of a YOLOv10-Based Deep Learning Model for Tooth Detection and Numbering on Panoramic Radiographs of Patients in the Mixed Dentition Period
Authors: Peker Ramazan Berkay , Kurtoglu Celal Oguz
Published: February 2025

Objectives: This study evaluated the performance of a YOLOv10-based deep learning model in detecting and numbering teeth in the panoramic radiographs of pediatric patients in the mixed dentition period. Methods: Panoramic radiographic images from 200 pediatric patients in the mixed dentition period, each with at least 10 primary teeth and underlying permanent tooth germs, were included in the study. A total of 8153 teeth in these panoramic radiographs were manually labeled. The dataset was divided for the development of a YOLOv10-based artificial intelligence model, with 70% used for training, 15% for testing, and 15% for validation. Results: The precision, recall, mAP50, mAP50-95, and F1 score of the model for tooth detection and numbering were found to be 0.90, 0.94, 0.968, 0.696, and 0.919, respectively. Conclusions: YOLOv10-based deep learning models can be used to accurately detect and number primary and permanent teeth in the panoramic radiographs of pediatric patients in the mixed dentition period, which can support clinicians in their daily practice. Future works may focus on model optimization across varied pediatric cases to enhance clinical applicability.
Early Diagnosis of Ovarian Cancer: A Comprehensive Review of the Advances, Challenges, and Future Directions
Authors: Hong Mun-Kun , Ding Dah-Ching
Published: February 2025

Ovarian cancer (OC), the seventh most common cancer in women and the most lethal gynecological malignancy, is a significant global health challenge, with >324,000 new cases and >200,000 deaths being reported annually. OC is characterized by late-stage diagnosis, a poor prognosis, and 5-year survival rates ranging from 93% (early stage) to 20% (advanced stage). Despite advances in genomics and proteomics, effective early-stage diagnostic tools and population-wide screening strategies remain elusive, contributing to high mortality rates. The complex pathogenesis of OC involves diverse histological subtypes and genetic predispositions, including BRCA1/2 mutations; notably, a considerable proportion of OC cases have a hereditary component. Current diagnostic modalities, including imaging techniques (transvaginal ultrasound, computed/positron emission tomography, and magnetic resonance imaging) and biomarkers (CA-125 and human epididymis protein 4), with varying degrees of sensitivity and specificity, have limited efficacy in detecting early-stage OC. Emerging technologies, such as liquid biopsy, multiomics, and artificial intelligence (AI)-assisted diagnostics, may enhance early detection. Liquid biopsies using circulating tumor DNA and microRNAs are popular minimally invasive diagnostic tools. Integrated multiomics has advanced biomarker discovery. AI algorithms have improved imaging interpretation and risk prediction. Novel screening methods including organoids and multiplex panels are being explored to overcome current diagnostic limitations. This review highlights the critical need for continued research and innovation to enhance early diagnosis, reduce mortality, and improve patient outcomes in OC and posits personalized medicine, integrated emerging technologies, and targeted global initiatives and collaborative efforts, which address care access disparities and promote cost-effective, scalable screening strategies, as potential tools to combat OC.
Contrast-Enhanced Chest Computed Tomography for In-Breast Recurrence Detection: Clinical and Imaging Predictors of Visibility
Authors: Jang Ho Min , Bae Kyoungkyg , Lee Tae Young , Lim Soyeoun , Bang Minseo
Published: February 2025

Purpose: Routine surveillance chest CT is not recommended by current guidelines; however, its use has been increasing with improved accessibility. This study aimed to evaluate the utility of surveillance contrast-enhanced chest computed tomography (CT) in detecting in-breast recurrence among survivors, focusing on imaging and clinicopathological features that enhance tumor visibility. Additionally, this study sought to determine which patient populations may derive benefit from contrast-enhanced chest CT. Materials and Methods: A retrospective analysis was conducted on records of patients diagnosed with in-breast recurrence through biopsy during follow-up after breast cancer surgery between January 2016 and August 2022. Patients who underwent contrast-enhanced chest CT within one month of diagnosis were included. Two radiologists reviewed the chest CT scans for breast cancer lesions by consensus, and their findings were validated by two other radiologists blinded to tumor locations. Statistical analyses were performed to evaluate associations among clinicopathological factors, image features, and visibility. Results: Eighty-nine recurrent tumors in 85 patients were included. Fifty-eight recurrent tumors were identified by radiologists who were not blinded. The blinded radiologists independently identified 50 and 56 recurrences, with substantial inter-observer agreement (κ-value = 0.768, p < 0.001). The visible group had a significantly higher rate of invasive ductal carcinoma (IDC) compared to the non-visible group (81.0% vs. 54.8%, p = 0.002). Additionally, the visible group exhibited larger tumors than the non-visible group (mean ± SD: 1.9 ± 1.5 cm vs. 1.3 ± 0.6 cm, p = 0.018). Tumors located in fatty backgrounds demonstrated significantly greater visibility on chest CT than those in glandular backgrounds (67.2% vs. 16.1%, p < 0.001). Recurrent breast cancer was also more frequently visible on chest CT in patients who had undergone mastectomy compared to those who had received breast-conserving surgery (p < 0.001). Conclusions: Contrast-enhanced chest CT can aid in the detection of in-breast recurrence, particularly in patients who have undergone mastectomy, as a complementary imaging modality. Tumors in fatty backgrounds, large tumors, mass-type tumors, and IDCs are better visible on chest CT.
Security System Design and Verification for Zero Trust Architecture
Authors: Lee Sangdo , Huh Jun-Ho , Woo Hanchul
Published: February 2025

With ongoing cyber threats stemming from persistent hacking attempts, relentless efforts are being made to prevent such threats at their source. Recently, the concept of “zero trust”, introduced by the United States National Institute of Standards and Technology (NIST), has emerged as a promising approach in this regard. Zero Trust (ZT) is not a standalone security solution but rather a framework of concepts aimed at achieving a higher level of security. It provides a paradigm that outlines the fundamental philosophy, core principles, and operational guidelines for enhanced security. While the guiding principle of “Never Trust, Always Verify” has gained widespread acceptance, many corporate security managers remain uncertain about how to implement ZT effectively. To address this challenge, this paper presents a security network designed to align with the corporate sector’s concept of security architecture based on the principles of ZT. Furthermore, it proposes and verifies a method to strengthen security using Secure Sockets Layer (SSL) and Digital Rights Management (DRM). These technologies were selected because, among the various principles of Zero Trust architecture (ZTA), they effectively support centralized policy management and access control. This paper is expected to be effective in preventing related risks and contribute to building a more effective information security system that helps organizations combat increasingly sophisticated cyber threats.
Improved Informed RRT*: Based on Dynamic Shrinkage Threshold Node Selection Mechanism and Adaptive Goal-Biased Strategy
Authors: Zhao Suna , Han Peijun , Diao Zhihua , He Zhendong , Li Xingyi , Lou Taishan , Jiang Liying
Published: February 2025

This study presents an improved Informed RRT* algorithm integrating a dynamic shrinkage threshold node selection mechanism with an adaptive goal-biased strategy, aimed at reducing computational iterations and accelerating convergence performance. To resolve node redundancy during Informed RRT* sampling, a dynamic shrinkage threshold-based node selection mechanism is developed. Through the dynamic evaluation of nodal distances (between newly generated nodes and the existing tree structure) against node selection thresholds, redundant nodes are eliminated to enhance spatial exploration efficiency. To address blind exploration and convergence delays, an adaptive goal-biased strategy guides the directional expansion of the search tree toward target regions, thereby optimizing convergence behavior. Systematic simulations demonstrate the effectiveness of the proposed algorithm across multiple scenarios. Comparative experiments demonstrate that the two key technologies significantly improved the speed of the initial-path generation of Informed RRT*. Moreover, the proposed method shows good adaptability and stability in different environments, which proves its potential and advantages in the path-planning field.
Optimal ATECO-Based Clustering and Photovoltaic System Sizing for Industrial Users in Renewable Energy Communities
Authors: Blasuttigh Nicola , Negri Simone , Massi Pavan Alessandro
Published: February 2025

This paper presents a new approach to optimize the clustering of industrial users and to determine the appropriate size of photovoltaic (PV) systems in renewable energy communities (RECs). By combining data including each company’s energy consumption profiles based on its ATECO classification, existing and installable PV capacity, electricity purchase and sale costs, REC incentives, and PV installation costs, the proposed algorithm identifies the optimal clustering of industrial users to form an economically efficient REC. Additionally, the optimal PV capacity for each member is evaluated, taking into account potential constraints of the available area. As a whole, the proposed algorithm can determine which cluster of companies maximizes the REC net present value (NPV) without compromising the payback time (PBT), providing a strategic framework and aid for improving the economic performance of industrial RECs, correctly sizing the community and ensuring that PV installation and investment yields the greatest possible financial and social benefits. From the analysis of the considered case studies, it appears that the proposed clustering and sizing method allows, for the REC as a whole, for an increase in the NPV from a minimum of about 25% with no change in PBT, up to about 75% in the case of a change in PBT of up to 5 years.
TSMixer- and Transfer Learning-Based Highly Reliable Prediction with Short-Term Time Series Data in Small-Scale Solar Power Generation Systems
Authors: Lee Younjeong , Jeong Jongpil
Published: February 2025

With the surge in energy demand worldwide, renewable energy is becoming increasingly important. Solar power, in particular, is positioning itself as a sustainable and environmentally friendly alternative, and is increasingly playing a role not only in large-scale power plants but also in small-scale home power generation systems. However, small-scale power generation systems face challenges in the development of efficient prediction models because of the lack of data and variability in power generation owing to weather conditions. In this study, we propose a novel forecasting framework that combines transfer learning and dynamic time warping (DTW) to address these issues. We present a transfer learning-based prediction system design that can maintain high prediction performance even in data-poor environments. In the process of developing a prediction model suitable for the target domain by utilizing multi-source data, we propose a data similarity evaluation method using DTW, which demonstrates excellent performance with low error rates in the MSE and MAE metrics compared with conventional long short-term memory (LSTM) and Transformer models. This research not only contributes to maximizing the energy efficiency of small-scale PV power generation systems and improving energy independence but also provides a methodology that can maintain high reliability in data-poor environments.