bluuebunny/crossref_metadata_2025 huggingface dataset:
Chronic asymptomatic orchitis in dogs alters Sertoli cell number and maturation status
Authors: Rehder Pauline , Packeiser Eva-Maria , Körber Hanna , Goericke-Pesch Sandra
Published: February 2025

Infertility due to non-obstructive azoospermia is a common diagnosis in infertile male dogs. Chronic asymptomatic orchitis (CAO) has been postulated as a significant cause of non-obstructive azoospermia in acquired male canine infertility. Despite severe microenvironmental changes, some resilient spermatogonial stem cells persist in CAO-affected testes. As Sertoli cells play an essential role in spermatogenesis and the testicular micromilieu, they represent a new target for CAO potential treatment and consequently deserve further investigation. To investigate Sertoli cell number and maturational status, different markers [Vimentin, anti-Müllerian hormone (AMH), and cytokeratin-18 (CK18)] were evaluated in healthy and CAO-affected testes at mRNA and protein levels. Sertoli cell number was reduced in CAO-affected dogs. Sertoli cells also partly returned to an immature status, as indicated by the expression of AMH and CK18 at mRNA and protein levels. The degree of spermatogenesis disruption matched with the degree of Sertoli cell alterations. The investigation of CAO in this study is limited by the number of samples and the lack of testicular volume measurements, but this does not diminish its importance in new findings. In conclusion, this study identifies alterations in Sertoli cell number and maturation status as a cause or consequence of CAO. The results indicate the need to restore Sertoli cell function as a potential therapeutic target for a successful restart of spermatogenesis.
Mono-HOPE Versus Dual-HOPE in Liver Transplantation: A Propensity Score-Matched Evaluation of Early Graft Outcome
Authors: Koch Dominik Thomas , Tamai Micol , Schirren Malte , Drefs Moritz , Jacobi Severin , Lange Christian M. , Ilmer Matthias , Nieß Hanno , Renz Bernhard , Werner Jens , Guba Markus , Koliogiannis Dionysios
Published: February 2025

Hypothermic oxygenated machine perfusion (HOPE) has become an integral technique to enhance donor graft function in liver transplantation (LiTx). This study compares early posttransplant outcomes of mono-HOPE (portal vein perfusion only) versus dual- HOPE (both portal vein and hepatic artery perfusion). A retrospective analysis was conducted on 183 LiTx recipients, with 90 receiving mono-HOPE and 93 receiving dual-HOPE grafts. Propensity Score Matching (PSM) was applied, resulting in a matched cohort of 146 patients. Primary outcomes included one-year patient and graft survival, and non-anastomotic biliary strictures (NAS). Secondary outcomes included hospital length of stay (HLS). One-year patient survival was 81.7% in the mono-HOPE and 81.7% in the dual-HOPE group, and overall survival did not differ (p = 0.990). One-year death-censored graft survival was similarly comparable (91.2% vs. 93.3%, p = 0.893). NAS were observed in 10.96% in the mono-HOPE and 8.22% in the dual-HOPE group (p = 0.574). The median HLS was 29 days for both groups. Results suggest that dual-HOPE did not significantly improve patient or graft survival, nor did it reduce NAS or HLS compared to mono-HOPE. Assuming that larger cohorts and long-term follow-up data confirm this, additional cannulation of the hepatic artery during machine perfusion in hypothermic conditions may not be beneficial.
Development and External Validation of [18F]FDG PET-CT-Derived Radiomic Models for Prediction of Abdominal Aortic Aneurysm Growth Rate
Authors: Dhesi Simran Singh , Adusumilli Pratik , Ravikumar Nishant , Waduud Mohammed A. , Frood Russell , Frangi Alejandro F. , McDermott Garry , Rudd James H. F. , Huang Yuan , Boyle Jonathan R. , Elkhawad Maysoon , Newby David E. , Joshi Nikhil , Kwan Jing Yi , Coughlin Patrick , Bailey Marc A. , Scarsbrook Andrew F.
Published: February 2025

Objective (1): To develop and validate a machine learning (ML) model using radiomic features (RFs) extracted from [18F]FDG PET-CT to predict abdominal aortic aneurysm (AAA) growth rate. Methods (2): This retrospective study included 98 internal and 55 external AAA patients undergoing [18F]FDG PET-CT. RFs were extracted from manual segmentations of AAAs using PyRadiomics. Recursive feature elimination (RFE) reduced features for model optimisation. A multi-layer perceptron (MLP) was developed for AAA growth prediction and compared against Random Forest (RF), XGBoost, and Support Vector Machine (SVM). Accuracy was evaluated via cross-validation, with uncertainty quantified using dropout (MLP), standard deviation (RF), and 95% prediction intervals (XGBoost). External validation used independent data from two centres. Ground truth growth rates were calculated from serial ultrasound (US) measurements or CT volumes. Results (3): From 93 initial RFs, 29 remained after RFE. The MLP model achieved an MAE ± SEM of 1.35 ± 3.2e−4 mm/year with the full feature set and 1.35 ± 2.5e−4 mm/year with RFE. External validation yielded 1.8 ± 8.9e−8 mm/year. RF, XGBoost, and SVM models produced comparable accuracies internally (1.4–1.5 mm/year) but showed higher errors during external validation (1.9–1.97 mm/year). The MLP model demonstrated reduced uncertainty with the full feature set across all datasets. Conclusions (4): An MLP model leveraging [18F]FDG PET-CT radiomics accurately predicted AAA growth rates and generalised well to external data. In the future, more sophisticated stratification could guide individualised patient care, facilitating risk-tailored management of AAAs.
The Role of Probiotics in Modulating Gut Microbiota and Metabolic Health for Weight Management: A Mini Review
Authors: Oudat Qutaibah , Okour Anas
Published: February 2025

The rising global prevalence of obesity and its associated metabolic disorders highlights the urgent need for innovative, sustainable interventions. Probiotics, as modulators of gut microbiota, have emerged as promising agents in weight management by influencing metabolic health. This mini-review explores the role of probiotics in modulating gut microbiota to support energy metabolism, appetite regulation, and fat storage. Evidence underscores the strain-specific benefits of probiotics, such as Lactobacillus gasseri SBT2055, Bifidobacterium breve B-3, and Akkermansia muciniphila, in reducing visceral fat, improving glucose metabolism, and mitigating obesity-related inflammation. The mechanisms underlying these effects include short-chain fatty acid (SCFA) production, modulation of appetite-regulating hormones, and improvements in gut barrier integrity. While the findings are promising, variability in outcomes highlights the importance of tailored probiotic interventions and underscores the need for standardized methodologies in future research. By addressing these challenges, probiotics can serve as integral components of personalized nutrition strategies, advancing both metabolic health and public health objectives.
Natural Antioxidants and Aquatic Animal Health
Authors: Jia Rui
Published: February 2025

In intensive aquaculture, aquatic animals inevitably encounter multiple stressors due to environmental fluctuations, triggering various stress responses, with oxidative stress being the most prevalent [...]
Investigation on Micro-Vibration Test and Image Stabilization of a High-Precision Space Optical Payload
Authors: Li Zhenchuang , Guo Junli , Qin Tao , Wang Jin , Peng Jinjin , Wu Yun , Jing Zijian , Zhang Hongming , Hou Jinge , Qi Bo
Published: February 2025

With the advancement of space exploration and optical communication toward deep space, the high-precision evaluation and image stabilization of space optical payloads under micro-vibration have become increasingly critical. To address these challenges and ensure sub-micro-radian pointing accuracy for high-precision space optical payloads (HPSOPs), this paper proposes a high-precision micro-vibration testing scheme and a two-stage image stabilization system. The micro-vibration testing scheme is based on an automated quasi-zero stiffness suspension device (AQZSSD), which enhances testing sensitivity and environmental disturbance resistance, ensuring the accuracy of the results. The two-stage image stabilization system integrates three bipod vibration isolation legs (BVILs) and a decoupled fast steering mirror (FSM), extending control bandwidth and achieving comprehensive vibration suppression. Micro-vibration testing and image stabilization experiments were conducted under disturbances from multiple vibration sources. Experimental results demonstrate that the AQZSSD introduces disturbances below 0.4 Hz, confirming its quasi-zero stiffness characteristics in alignment with theoretical predictions. Furthermore, the line-of-sight (LOS) jitter root mean square (RMS) value is reduced from 1.253 μrad to 0.276 μrad, achieving sub-micro-radian stability. Additionally, due to the coupling effect of the micro-vibration response, the collaborative testing results were found to be lower than the linear superposition of individual sources. This work offers critical theoretical and technical support for the development of HPSOPs, with potential applications in future space missions and advanced optical technologies.
Understanding Injuries in Young Female Soccer Players: A Narrative Review on Incidence, Mechanism, Location Risk Factors, and Preventive Strategies
Authors: Sanchez-Sanchez Javier , Raya-González Javier , Martín Víctor , Rodríguez Fernández Alejandro
Published: February 2025

There has been growing interest in understanding the injury profiles of young female soccer players due to their increasing participation in the sport and the unique risk factors they face. This narrative review examines the incidence, mechanisms, and location of injuries in this population, alongside the primary risk factors and effective preventive strategies. Injury incidence is higher during matches than in training sessions, with contact injuries dominating in games and non-contact injuries prevailing in practice. Knee and ankle injuries are the most prevalent, with anterior cruciate ligament (ACL) injuries being particularly concerning due to their frequency and long-term impact. The interplay of intrinsic factors, such as hormonal fluctuations, anatomical characteristics, and biomechanics, with extrinsic factors like training load, surface type, and footwear significantly influences injury risk. Prevention programs, particularly those combining neuromuscular, balance, and strength training, demonstrate high efficacy, provided that adherence is maintained. Moreover, fostering awareness among players, coaches, and stakeholders about psychosocial factors and menstrual health further enhances injury prevention. Tailored strategies addressing the specific needs of young female soccer players are crucial to ensuring their safety, optimizing performance, and supporting their long-term athletic development.
Digital Pathology and Ensemble Deep Learning for Kidney Cancer Diagnosis: Dartmouth Kidney Cancer Histology Dataset
Authors: Jain Muskan Naresh , Al-Heejawi Salah Mohammed Awad , Azzi Jamil R. , Amal Saeed
Published: February 2025

Kidney cancer has become a major global health issue over time, showing how early detection can play a very important role in mediating the disease. Traditional histological image analysis is recognized as the clinical gold standard for diagnosis, although it is highly manual and labor-intensive. Due to this issue, many are interested in computer-aided diagnostic technologies to assist pathologists in their diagnostics. Specifically, deep learning (DL) has become a viable remedy in this field. Nonetheless, the capacity of existing DL models to extract comprehensive visual features for accurate classification is limited. Toward the end, this study proposes using ensemble models that combine the strengths of multiple transformers and deep learning model architectures. By leveraging the collective knowledge of these models, the ensemble enhances classification performance and enables more precise and effective kidney cancer detection. This study compares the performance of these suggested models to previous studies, all of which used the publicly accessible Dartmouth Kidney Cancer Histology Dataset. This study showed that the Vision Transformers, with an average accuracy of over 99%, were able to achieve high detection accuracy across all complete slide picture patches. In particular, the CAiT, DeiT, ViT, and Swin models outperformed ResNet. All things considered, the Vision Transformers consistently produced an average accuracy of 98.51% across all five-folds. These results demonstrated that Vision Transformers might perform well and successfully identify important features from smaller patches. Through utilizing histopathological images, our findings will assist pathologists in diagnosing kidney cancer, resulting in early detection and increased patient survival rates.
Application of Deep Learning Framework for Early Prediction of Diabetic Retinopathy
Authors: Mostafa Fahad , Khan Hafiz , Farhana Fardous , Miah Md Ariful Haque
Published: February 2025

Diabetic retinopathy (DR) is a severe microvascular complication of diabetes that affects the eyes, leading to progressive damage to the retina and potential vision loss. Timely intervention and detection are crucial for preventing irreversible damage. With the advancement of technology, deep learning (DL) has emerged as a powerful tool in medical diagnostics, offering a promising solution for the early prediction of DR. This study compares four convolutional neural network architectures, DenseNet201, ResNet50, VGG19, and MobileNetV2, for predicting DR. The evaluation is based on both accuracy and training time data. MobileNetV2 outperforms other models, with a validation accuracy of 78.22%, and ResNet50 has the shortest training time (15.37 s). These findings emphasize the trade-off between model accuracy and computational efficiency, stressing MobileNetV2’s potential applicability for DR prediction due to its balance of high accuracy and a reasonable training time. Performing a 5-fold cross-validation with 100 repetitions, the ensemble of MobileNetV2 and a Graph Convolution Network exhibits a validation accuracy of 82.5%, significantly outperforming MobileNetV2 alone, which shows a 5-fold validation accuracy of 77.4%. This superior performance is further validated by the area under the receiver operating characteristic curve (ROC) metric, demonstrating the enhanced capability of the ensemble method in accurately detecting diabetic retinopathy. This suggests its competence in effectively classifying data and highlights its robustness across multiple validation scenarios. Moreover, the proposed clustering approach can find damaged locations in the retina using the developed Isolate Regions of Interest method, which achieves almost a 90% accuracy. These findings are useful for researchers and healthcare practitioners looking to investigate efficient and effective powerful models for predictive analytics to diagnose diabetic retinopathy.
Battery-Type Transition Metal Oxides in Hybrid Supercapacitors: Synthesis and Applications
Authors: Raut Bikash , Ahmed Md. Shahriar , Kim Hae-Yong , Rahman Khan Mohammad Mizanur , Bari Gazi A. K. M. Rafiqul , Islam Mobinul , Nam Kyung-Wan
Published: February 2025

Hybrid supercapacitors (HSCs) have garnered growing interest for their ability to combine the high energy storage capability of batteries with the rapid charge–discharge characteristics of supercapacitors. This review examines the evolution of HSCs, emphasizing the synergistic mechanisms that integrate both Faradaic and non-Faradaic charge storage processes. Transition metal oxides (TMOs) are highlighted as promising battery-type electrodes owing to their notable energy storage potential and compatibility with various synthesis routes, including hydro/solvothermal methods, electrospinning, electrodeposition, and sol–gel processes. Particular attention is directed toward Ti-, Co-, and V-based TMOs, with a focus on tailoring their properties through morphology control, composite formation, and doping to enhance electrochemical performance. Overall, the discussion underscores the potential of HSCs to meet the growing demand for next-generation energy storage systems by bridging the gap between high energy and high power requirements.
Ranking Influential Non-Content Factors on Scientific Papers’ Citation Impact: A Multidomain Comparative Analysis
Authors: Zhu Jiannan , Zhou Jiayi , Pan Jiaofeng , Gu Fu , Guo Jianfeng
Published: February 2025

The influence of scientific papers is measured by their citations. Although predicting the papers’ citation impact based on non-content factors has garnered extensive attention, the influence of such factors is rarely compared. In this article, we compare the influence of non-content factors on the citation counts of academic publications across three fields, i.e., math, computer science, and management. We consider different methods in this study, including three machine learning approaches, namely, XGBoost, Gradient Boosting Decision Tree, and Random Forest, along with statistical techniques such as linear regression and quantile analysis. Our findings reveal that no matter the field or analytical method applied, author prestige and the number of references consistently stand out as the most influential factors, while the breadth of categories covered by the paper has minimal impact. In mathematics, the first citation date and article length are almost equally important as author prestige, while the number of authors and the journal impact factor are crucial for computer science papers. In management, the number of collaborating countries is relatively influential with respect to the paper’s citations. The results of the quantile regression indicate that at higher quantile levels, the impact of author prestige and the number of authors on the papers’ citation impact are more pronounced across all three disciplines, while the journal impact factor and paper length have the greatest influence at low and medium quantile levels. Our findings indicate that the reliance of academic citations on author prestige and journal impact factors not only highlights the unequal distribution of resources within the current academic system but also further exacerbates citation inequality.
Looking to the Future of Viral Vectors in Ocular Gene Therapy: Clinical Review
Authors: Kharisova Chulpan B. , Kitaeva Kristina V. , Solovyeva Valeriya V. , Sufianov Albert A. , Sufianova Galina Z. , Akhmetshin Rustem F. , Bulgar Sofia N. , Rizvanov Albert A.
Published: February 2025

Eye diseases can significantly affect the quality of life of patients due to decreased visual acuity. Although modern ophthalmological diagnostic methods exist, some diseases of the visual system are asymptomatic in the early stages. Most patients seek advice from an ophthalmologist as a result of rapidly progressive manifestation of symptoms. A number of inherited and acquired eye diseases have only supportive treatment without eliminating the etiologic factor. A promising solution to this problem may be gene therapy, which has proven efficacy and safety shown in a number of clinical studies. By directly altering or replacing defective genes, this therapeutic approach will stop as well as reverse the progression of eye diseases. This review examines the concept of gene therapy and its application in the field of ocular pathologies, emphasizing the most recent scientific advances and their potential impacts on visual function status.
Serum Carnosinase 1 Is Not Associated with Insulin Resistance or Glucose Metabolism in a Type 1 Diabetes Cohort
Authors: Qiu Jiedong , Yard Benito A. , Krämer Bernhard K. , van Goor Harry , van Dijk Peter R. , Kannt Aimo
Published: February 2025

Background/Objectives: Preclinical studies suggest that the deleterious effect of a high serum carnosinase 1 (CN1) concentration is attributed to its adverse effects on insulin sensitivity and glucose metabolism. However, there is little evidence for a modulating role of CN1 in glucose metabolism in humans. Methods: We measured serum CN1 concentration in an observational type 1 diabetes cohort of 172 patients in whom glucose variability (MAGE, MODD, SD of individual blood glucose, mean, and CV) was recorded by blinded continuous glucose monitoring for 5–7 days. Furthermore, insulin dose per kg body weight was compared. Results: Insulin sensitivity (insulin dosage) and glucose variability parameters did not differ between different CN1 tertiles (p > 0.05). Conclusions: There was no association of serum CN1 with indices of glucose variability in this type 1 diabetes cohort.
Cardiac Biomarkers Predict Major Adverse Cardiac Events (MACE) in Incident Haemodialysis Patients: Results from a Global Federated Database
Authors: Davies Elin Mitford , Buckley Benjamin J. R. , Austin Philip , Lip Gregory Y. H. , Rao Anirudh , McDowell Garry
Published: February 2025

Background: Despite its many advantages, haemodialysis (HD) has been shown to be associated with significant cardiovascular events, especially in patients commencing HD. Currently, there is no specific method to risk-stratify incident HD patients. Blood-based biomarkers provide insight into myocardial injury and stress. We aimed to evaluate the association of increased circulating biomarker concentration in incident HD with incident major adverse cardiac events (MACE). Methods: This was a retrospective cohort study of incident haemodialysis cases within 3 months of treatment initiation (≥18 years) from the TriNetX database. Cohorts were grouped by biomarker thresholds: Troponin I: ≥50 ng/L, BNP ≥ 100 pg/mL and 1:1 propensity-score matched for demographic characteristics, baseline cardiovascular risk, laboratory values, and cardiovascular medication. Primary outcome: Incidence of major adverse cardiac events (MACE) censored prior to index event of HD. Secondary outcome: Risk of each individual component of the composite outcome. Cox regression reported hazard ratios (95% CI) for the outcomes. Results: In total, 62,206 and 10,476 patients were included in the troponin I and BNP cohorts, respectively. In the troponin I cohort, 5878 developed MACE (HR 1.33 (95% CI 1.26–1.41, p < 0.0001)). In the BNP cohort, 1050 developed MACE (HR 1.28 (95% CI 1.13–1.44, p < 0.0001)). Conclusions: In incident HD, routine clinical laboratory biomarkers can predict incident MACE. The results suggest the clinical need for CV mortality and morbidity risk profiling in incident HD using a combination of clinical and laboratory variables.
A Comprehensive Microscopy Analysis of the Retina of Larus audouinii (Payraudeau, 1826): Environmental and Ecological Insights
Authors: Navarro-Sempere Alicia , García Magdalena , Cobo Raúl , Pascual-García Sandra , Segovia Yolanda
Published: February 2025

The retinal structure is generally conserved across vertebrates; however, variations occur due to the relationship between environmental factors and visual perception. Birds have adapted to diverse ecological contexts, evolving specialized visual characteristics. In this study, we examined the retina of Audouin’s Gull (Larus audouinii) using light and transmission electron microscopy. This species is particularly intriguing as it is considered an outlier within the Laridae family: despite being a diurnal bird, it exhibits nocturnal/crepuscular foraging behaviour. Our analysis revealed a retina well adapted for diurnal activity, with features such as a retinal thickness comparable to that of other diurnal birds, a well-developed retinal pigment epithelium, and a high cone-to-rod density ratio. However, we also observed characteristics aligned with nocturnal or crepuscular activity, including a slightly increased rod density in central regions and the presence of two distinct types of horizontal cells in the inner nuclear layer. Additionally, the inner retina showed evidence of complex visual processing. These findings suggest that Audouin’s Gull is an excellent model for visual ecology studies due to its specialized adaptations.
Defection Analysis of Post-Paid Telephone Customers in Nepal Using the Weibull Model
Authors: Gnawali Keshava Raj , Kadel Rajan
Published: February 2025

This study examines the defection patterns of post-paid telephone customers based on migrant status and season-wise acquisition using the Weibull model. Data from 48,666 post-paid customers were extracted from the data warehouse of a telephone company in Nepal. After pre-processing, the migrant status and season of acquisition for 48,583 customers were identified. Survival analysis was then conducted using the Kaplan–Meier (K-M) method to estimate the hazard of defection. Finally, the Weibull model was applied to analyse defection patterns concerning migrant status, default status, and season-wise acquisition in relation to survival periods. The results indicate that migrant customers have a significantly higher probability of defection compared to non-migrant customers. Additionally, the season of acquisition has a notable impact on customer survival duration. The study also highlights a higher risk of involuntary defection among migrant customers. These findings can inform the development of marketing strategies aimed at improving customer retention and acquisition in the telecommunications sector. Moreover, the model and methodology employed in this research can be extended to other marketing contexts.
Real-World Efficacy and Toxicity of Ipilimumab and Nivolumab as First-Line Treatment of Metastatic Renal Cell Carcinoma (mRCC) in a Subpopulation of Elderly and Poor Performance Status Patients
Authors: Shani Shrem Noa , Beltran-Bless Ana-Alicia , Ghosh Sunita , Tajzler Camilla , Wood Lori A. , Kollmannsberger Christian , Basappa Naveen S. , Graham Jeffrey , Fallah-Rad Nazanin , Heng Daniel Y.C. , Soulières Denis , Lalani Aly-Khan A. , Breau Rodney H. , Finelli Antonio , Tanguay Simon , Bhindi Bimal , Bjarnason Georg , Pouliot Frederic , Canil Christina
Published: February 2025

Background: Ipilimumab and nivolumab (ipi/nivo) improved overall survival (OS) compared to sunitinib in the pivotal Checkmate 214 trial of metastatic renal cell carcinoma (mRCC) with International Metastatic RCC Database Consortium (IMDC) intermediate/poor risk disease. We evaluated the efficacy and toxicity of ipi/nivo in older and frailer populations in a real-world mRCC cohort. Methods: Analysis was conducted on a real-world cohort with mRCC (N = 551) treated with first-line ipi/nivo from the Canadian Kidney Cancer information system (CKCis) database from January 2014 to December 2021. A comparison was made between outcomes and toxicity in patients 1. <70 versus (vs.) ≥70 yo, 2. <75 vs. ≥75 yo, and 3. KPS ≥70 vs. <70 yo. OS, progression-free survival (PFS), and time to treatment failure (TTF) were calculated by Kaplan–Meier analysis. Log-rank tests were used for comparison between groups. Results: Ipi/nivo treatment had no impact on survival outcomes or toxicity for patients >70 yo and >75 yo when controlled for IMDC. However, when comparing patients with KPS > 70 vs. KPS < 70, patients with a poor performance status had decreased median OS at 54.5 m vs. 10.8 m (p-value < 0.0001) and PFS at 11.6 vs. 3.1 m (p-value < 0.0001). Conclusions: The use of ipi/nivo in mRCC demonstrated similar survival outcomes and toxicity in an older patient population. In patients with a poor performance status, it was associated with inferior OS and PFS. We believe that ipi/nivo is a reasonable treatment option for these patient populations, particularly in older patients.
Overcoming Barriers: The AO Foundation’s Role in Latin American Scientific Growth
Authors: Pereira Rodrigo dos Santos , Cypriano Rafael Vago , Garcia Carlos Gaete , Larrañaga Juan José , Homsi Nicolas
Published: February 2025

This manuscript presents an exploratory evaluation of the challenges and opportunities in scientific research among craniomaxillofacial surgeons in Latin America. It focuses on initiatives introduced by the AO Foundation’s Research and Development (R&D) Committee to assess the current state of research involvement among AO Foundation members in the region and identify barriers to research. A survey conducted in 2023 among Latin American members of the AO Foundation gathered data on their interest in research, obstacles faced, and awareness of available opportunities, such as grants, fellowships, and mentorship programs. The outcomes revealed a strong interest in research, with 96.5% of respondents expressing a desire to engage. However, key barriers included limited time (46.5%), difficulties in project structuring and scientific writing (32.6%), and challenges in publishing (30.2%). Notably, 54.7% of respondents were unaware of the AO PEER program, and 65.6% were unfamiliar with the foundation’s research grant opportunities. The AO Foundation aims to enhance scientific development in Latin America by promoting multicenter research studies, training opportunities, and developing research group leaders. These strategies seek to support and encourage surgeons in advancing their scientific activities.
Advanced Techniques for the Fabrication of Nanostructured Porous Silicon Using Photoelectrochemical Etching and Ultrasonic Vibration
Authors: Chiang Chao-Ching , Immanuel Philip Nathaniel
Published: February 2025

This study presents a novel method combining photoelectrochemical etching with ultrasonic vibration for the formation of nanocrystalline porous silicon (NC-PS). This combined process enhances the band gap energy absorption (BEA) by reducing bubble accumulation in the etching area. It is found that laser irradiation can decrease the etching rate, while ultrasonic vibration aids with bubble expulsion, preventing accumulation in the etching area, resulting in more uniform etching and increasing the porosity of the porous silicon (PS). High porosity in NC-PS structures enhances the surface area, thereby increasing electron mobility and improving the electron energy distribution. Our experiments demonstrate that this combined process leads to more uniform and deeper etching and the creation of well-defined porous structures. The more uniform PS size distribution (8–14 nm) achieved by photoelectrochemical etching combined with ultrasonic vibration enhances the optical properties of the material due to quantum confinement effects. Porosity measurements provide essential surface characterization information that is crucial for determining the performance of PS diode components in various applications. Our findings demonstrate that this combination technique improves the uniformity, efficiency, and precision of porous silicon etching, producing material for high-performance applications, including sensors, catalysts, and photonic devices.
Clinical Efficacy of Belight3TM on Dark Spot Pigmentation in Caucasian Subjects
Authors: Tursi Francesco , Pourtau Line , Roveda Gloria , De Ponti Ileana , Gaudout David , Moras Benjamin , Pouchieu Camille , Nobile Vincenzo
Published: February 2025

Belight3TM, a nutricosmetic formulation containing polyphenol-rich extracts, has previously been demonstrated to be safe and effective in brightening skin color and dark spots in a clinical study involving Asian volunteers. The aim of this study was to investigate the efficacy of this formulation in lightening dark spots in a Caucasian population, which is characterized by lighter skin pigmentation and greater visibility of hyperpigmentation, as well as to determine whether the supplementation increased sensitivity to UV exposure. A randomized, double-blind, placebo-controlled clinical study was conducted on 66 male and female participants with skin phototype I to III, all exhibiting facial hyperpigmentation. The color of selected dark spots was assessed using spectrophotometry to measure the L* value of the CIELab color space and the Individual Typology Angle (ITA). L* and ITA levels of dark spots were significantly increased after 6 and 12 weeks of Belight3TM treatment (respectively by +1.2% and +2.5% for L* and by 12.1% and 22.5% for ITA), and this lightening effect was significantly higher than the placebo after 12 weeks (p < 0.05 for L*; p < 0.001 for ITA). Clinical evaluation of skin complexion evenness and dark spot visibility were also improved in subjects receiving the Belight3TM treatment, achieving a significant difference with the placebo after 12 weeks. No changes in MED or skin redness were observed during this study. This study confirmed the safety and efficacy of Belight3TM in lightening dark spots in a Caucasian population without increasing UV sensitivity.
The Role of Vitamin C in Wound Healing in Surgically Managed Diabetic Foot Disease
Authors: Kancherla Kiran , Chow Jason , Mittal Rajat , Kaushik Nakul , Kamal Tamer , Low Gary , Martin Brian
Published: February 2025

Background: Diabetic foot ulcers (DFUs) represent a significant cause of morbidity in diabetic patients, with surgical management frequently required in advanced cases. This study examines the association between preoperative vitamin C levels and wound-healing outcomes in patients with diabetic foot disease (DFD) requiring surgical debridement. Methods: A retrospective cohort study was conducted at a tertiary referral centre, with the study including diabetic patients who had undergone surgical debridement for forefoot and midfoot diabetic foot infections between January 2020 and July 2024. Patients with ISDA grades 3 and 4 ulcers and preoperative measurements of vitamin C, albumin, HbA1c, and BMI were included. The primary outcome was time to wound healing, defined as the duration from surgery to discharge from the orthopaedic diabetic foot clinic. Data were analysed using generalized linear models to assess the impact of preoperative vitamin C levels on healing time, controlling for confounding variables. Results: In the 61 patients included in the multivariable regression analysis, higher preoperative vitamin C levels were significantly associated with faster wound healing (p = 0.01). Other significant factors included albumin levels and ulcer location, with midfoot ulcers healing more slowly than forefoot ulcers. The mean time to healing was 3 months, with vitamin C levels showing a statistically significant effect on wound-healing outcomes. Conclusions: Our study demonstrates that higher preoperative vitamin C levels were associated with faster wound healing in surgically treated diabetic foot ulcers. Future prospective randomized controlled trials are needed to confirm these findings and assess the role of vitamin C supplementation in the management of surgically treated DFUs.
Alzheimer’s Prediction Methods with Harris Hawks Optimization (HHO) and Deep Learning-Based Approach Using an MLP-LSTM Hybrid Network
Authors: Ghadami Raheleh , Rahebi Javad
Published: February 2025

Background/Objective: Alzheimer’s disease is a progressive brain syndrome causing cognitive decline and, ultimately, death. Early diagnosis is essential for timely medical intervention, with MRI medical imaging serving as a primary diagnostic tool. Machine learning (ML) and deep learning (DL) methods are increasingly utilized to analyze these images, but accurately distinguishing between healthy and diseased states remains a challenge. This study aims to address these limitations by developing an integrated approach combining swarm intelligence with ML and DL techniques for Alzheimer’s disease classification. Method: This proposal methodology involves sourcing Alzheimer’s disease-related MRI images and extracting features using convolutional neural networks (CNNs) and the Gray Level Co-occurrence Matrix (GLCM). The Harris Hawks Optimization (HHO) algorithm is applied to select the most significant features. The selected features are used to train a multi-layer perceptron (MLP) neural network and further processed using a long short-term (LSTM) memory network in order to classify tumors as malignant or benign. The Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset is utilized for assessment. Results: The proposed method achieved a classification accuracy of 97.59%, sensitivity of 97.41%, and precision of 97.25%, outperforming other models, including VGG16, GLCM, and ResNet-50, in diagnosing Alzheimer’s disease. Conclusions: The results demonstrate the efficacy of the proposed approach in enhancing Alzheimer’s disease diagnosis through improved feature extraction and selection techniques. These findings highlight the potential for advanced ML and DL integration to improve diagnostic tools in medical imaging applications.
Transcription Factor Inhibition as a Potential Additional Mechanism of Action of Pyrrolobenzodiazepine (PBD) Dimers
Authors: Mantaj Julia , Jackson Paul J. M. , Parsons Richard B. , Bui Tam T. T. , Thurston David E. , Rahman Khondaker Miraz
Published: February 2025

Background: The pyrrolobenzodiazepine (PBD) dimer SJG-136 reached Phase II clinical trials in ovarian cancer and leukaemia in the UK and USA in the 2000s. Several structural analogues of SJG-136 are currently in clinical development as payloads for Antibody-Drug Conjugates (ADCs). There is growing evidence that PBDs exert their pharmacological effects through inhibition of transcription factors (TFs) in addition to arrest at the replication fork, DNA strand breakage, and inhibition of enzymes including endonucleases and RNA polymerases. Hence, PBDs can be used to target specific DNA sequences to inhibit TFs as a novel anticancer therapy. Objective: To explore the ability of SJG-136 to bind to the cognate sequences of transcription factors using a previously described HPLC/MS method, to obtain preliminary mechanistic evidence of its ability to inhibit transcription factors (TF), and to determine its effect on TF-dependent gene expression. Methods: An HPLC/MS method was used to assess the kinetics and thermodynamics of adduct formation between the PBD dimer SJG-136 and the cognate recognition sequence of the TFs NF-κB, EGR-1, AP-1, and STAT3. CD spectroscopy, molecular dynamics simulations, and gene expression analyses were used to rationalize the findings of the HPLC/MS study. Results: Notable differences in the rate and extent of adduct formation were observed with different DNA sequences, which might explain the variations in cytotoxicity of SJG-136 observed across different tumour cell lines. The differences in adduct formation result in variable downregulation of several STAT3-dependent genes in the human colon carcinoma cell line HT-29 and the human breast cancer cell line MDA-MB-231. Conclusions: SJG-136 can disrupt transcription factor-mediated gene expression, which contributes to its exceptional cytotoxicity in addition to the DNA-strand cleavage initiated by its ability to crosslink DNA.
Crack-Detection Algorithm Integrating Multi-Scale Information Gain with Global–Local Tight–Loose Coupling
Authors: Bai Yun , Li Zhiyao , Liu Runqi , Feng Jiayi , Li Biao
Published: February 2025

In this study, an improved target-detection model based on information theory is proposed to address the difficulties of crack-detection tasks, such as slender target shapes, blurred boundaries, and complex backgrounds. By introducing a multi-scale information gain mechanism and a global–local feature coupling strategy, the model has significantly improved feature extraction and expression capabilities. Experimental results show that, on a single-crack dataset, the model’s mAP@50 and mAP@50-95 are 1.6% and 0.8% higher than the baseline model RT-DETR, respectively; on a multi-crack dataset, these two indicators are improved by 1.2% and 1.0%, respectively. The proposed method shows good robustness and detection accuracy in complex scenarios, providing new ideas and technical support for in-depth research in the field of crack detection.
Supporting Early Childhood Preservice Teachers to Effectively Integrate STEM in Their Future Teaching Practice
Authors: Kewalramani Sarika , Devi Anamika , Ng Andrea
Published: February 2025

It is critical that teachers are equipped with Science, Technology, Engineering and Mathematics (STEM) skills and knowledge as we move into a digital future. By integrating STEM into early childhood education, we can provide young children with invaluable opportunities to build their scientific knowledge from the very start, setting them up for success in their later STEM educational journeys. However, many educators within early childhood settings find it challenging to create engaging STEM-based activities for young children. Unfortunately, there is a scarcity of information on how teacher educators can support preservice teachers in developing their STEM competence. This study examined the perspectives of early childhood preservice teachers (PSTs) regarding their confidence and pedagogical content knowledge (PCK) in integrating STEM into their teaching practice. Utilising a qualitative multi-case study approach, semi-structured interviews with 11 PSTs and a document analysis of their assignment tasks and teaching artefacts were conducted to deepen our understanding of PCK skills. Data were analysed using Bryman’s thematic analysis, revealing key themes through a narrative analysis of PSTs’ responses. Several crucial themes emerged, with PSTs acknowledging that embedding STEM content into both theoretical classwork and practical placement significantly enhanced their content knowledge and confidence when teaching STEM in early childhood settings. It is essential for future research to explore and expand university–preschool partnerships to create immersive STEM experiences that benefit preservice teachers and future in-service teachers in this field.
Automated Transformer Selection for RFIC Design: Accelerating Development with a Comprehensive Database
Authors: Torres-Clarke Jeffrey , Mendoza-Calvo Neda , del Pino Javier , Khemchandani Sunil , Galante-Sempere David
Published: February 2025

The design of transformers, a key component of radio frequency integrated circuits (RFICs), is traditionally carried out through an iterative process involving extensive electromagnetic simulations. While process design kits (PDKs) offer tools based on interpolation or fitting equations to simplify parameter estimation, these tools are restricted to standard geometries, leaving designers to manually simulate and optimize custom designs. This approach is inefficient and resource intensive. This paper proposes an automated process to generate a database containing the physical and electrical parameters of a wide range of transformers. This database is part of a tool designed to efficiently identify the desired transformer. To evaluate the tool’s effectiveness in reducing the time required for design, a millimeter-wave (mm-Wave) 69.4–74.2 GHz differential low-noise amplifier (LNA) is designed using GlobalFoundries 45 nm silicon-on-insulator (SOI) technology. This circuit demonstrates a noise figure (NF) of 4.1 dB, a gain of 10.1 dB, an input third-order intercept point (IIP3) of −10.78 dBm, and a power consumption of 4.7 mW from a 0.406 V DC supply. Moreover, the simulated performance achieves these specifications within a highly compact area of 0.12 mm2. The transformer selection process for the circuit takes only a few seconds, whereas the conventional method of manual transformer design and electromagnetic simulation would require a significantly greater amount of time.
Data-Driven Dynamics Learning on Time Simulation of SF6 HVDC-GIS Conical Solid Insulators
Authors: Urazaki Junior Kenji , Lucchini Francesco , Marconato Nicolò
Published: February 2025

An HVDC-GIL system with a conical spacer in a radioactive environment is studied in this work using simulated data on COMSOL® Multiphysics. Electromagnetic simulations on a 2D model were performed with varying ion-pair generation rates and potential applied to the system. This article explores machine learning methods to derive time to steady state, dark current, gas conductivity, and surface charge density expressions. The focus was on constructing symbolic representations, which could be interpretable and less prone to overfitting, using the symbolic regression (SR) and sparse identification of nonlinear dynamics (SINDy) algorithms. The study successfully derived the intended expressions, demonstrating the power of symbolic regression. Predictions of dark currents in the gas–ground electrode interface reported an absolute error and mean absolute percentage error (MAPE) of 1.04 × 10−4 pA and 0.01%, respectively. The solid–ground electrode interface reported an error of 8.99 × 10−5 pA and MAPE of 0.04%, showing strong agreement with simulation data. Expressions for time to steady state had a test error of approximately 110 h with MAPE of around 3%. Steady-state gas conductivity expression achieved an absolute error of 0.55 log(S/m) and MAPE of 1%. An interpretable equation was created with SINDy to model the time evolution of surface charge density, achieving a root mean squared error of 1.12 nC/m2/s across time-series data. These results demonstrate the capability of SR and SINDy to provide interpretable and computationally efficient alternatives to time-consuming numerical simulations of HVDC systems under radiation conditions. While the model provides useful insights, performance and practical applications of the expressions can improve with more diverse datasets, which might include experimental data in the future.
SAM-PAY: A Location-Based Authentication Method for Mobile Environments
Authors: Berbecaru Diana Gratiela
Published: February 2025

Wireless, satellite, and mobile networks are increasingly used in application scenarios to provide advanced services to mobile or nomadic devices. For example, to authenticate mobile users while obtaining access to remote services, a two-factor authentication mechanism is typically used, e.g., based on the ownership of a personal mobile phone, device, or (smart)card and the knowledge of a (static) username and password. Nevertheless, two-factor authentication is considered roughly “adequate” for security problems encountered today on the Internet and even less for ubiquitous or mobile environments. To increase the authentication level, several authentication methods of different classes may be combined to achieve more reliable user identification. In particular, location technologies allow ubiquitous applications to better exploit the (physical) location information in the authentication process. Consequently, in security applications based on multiple authentication factors, an additional authentication factor could be the location information protected for integrity against undesired modification. We present the SAM-PAY authentication method, which combines different authentication factors to obtain a more reliable user identification. The mechanism is based on the use of a (location-aware) device, the location information certified by a trusted external party, such as a component or element in a telecom network, and the knowledge of data, like a static PIN and a dynamically generated one-time password. We also describe the design and implementation of a real case scenario exploiting our SAM-PAY method, namely the refueling service at a self-service gas station. The test-bed put in place for this service demonstrates the feasibility and effectiveness of the SAM-PAY method in open mobile environments.