bluuebunny/crossref_metadata_2025 huggingface dataset:
A New Three-Hit Mouse Model of Neurodevelopmental Disorder with Cognitive Impairments and Persistent Sociability Deficits
Authors: Mouffok Imane , Lahogue Caroline , Cailly Thomas , Freret Thomas , Bouet Valentine , Boulouard Michel
Published: December 2024

Background/Objectives: Cognitive deficits and negative symptoms associated with schizophrenia are poorly managed by current antipsychotics. In order to develop effective treatments, refining animal models of neurodevelopmental disorders is essential. Methods: To address their multifactorial etiology, we developed a new three-hit mouse model based on the hypoglutamatergic hypothesis of the pathology combined with early stress, offering strong construct validity. Thus, a genetic susceptibility (serine racemase deletion) was associated with an early environmental stress (24 h maternal separation at 9 days of age) and a further pharmacological treatment with phencyclidine (PCP, a glutamate receptor antagonist treatment, 10 mg/kg/day, from 8 to 10 weeks of age). The face validity of this model was assessed in female mice 1 and 6 weeks after the end of PCP treatment by a set of behavioral experiments investigating positive- and negative-like symptoms and cognitive deficits. Results: Our results showed that the three-hit mice displayed persistent hyperlocomotion (positive-like symptoms) and social behavior impairment deficits (negative-like symptoms) but non-persistent spatial working memory deficits (cognitive symptoms). Conclusions: Our work confirms the usefulness of a three-hit combination to model, particularly for negative-like symptoms associated with schizophrenia and other psychiatric disorders. The model therefore gathers powerful construct and face validities and supports an involvement of glutamate dysfunction in behavioral symptoms.
Research on the Full Life Cycle Deformation, Stress Response, and Dynamic Fatigue Performance of Concrete Structures in Pump Stations
Authors: Yuan Min , Zhu Xianhong , Han Lei , Qi Yongfeng , Xie Zhiqiang , Qin Xi , Dong Yun
Published: December 2024

Concrete structures are subjected to static and fatigue loads during long-term service, and temperature changes can cause changes in the volume of concrete, leading to stress changes and fatigue damage, which affect the mechanical properties and service life of a structure. In response to the current lack of three-dimensional analysis and the exploration of the mechanical behavior and damage evolution processes of concrete structures under variable temperature environmental conditions, this paper relies on the Fenghuangjing Pump Station project involving the Yangtze River and Huaihe River and constructs a concrete thermo-mechanical-fatigue-damage model based on the power exponent function damage constitutive model. By using multiple coupled simulation calculations to predict the performance of concrete structures; analyzing the stress, deformation, and fatigue damage of structures from construction to operation; comparing measured data; dynamically optimizing inversion to obtain concrete thermal parameters; proposing key control parameters; and warning indicators and thresholds, the research results can provide reference for the long-term safe operation of similar projects.
Enhanced Expression of N-Cadherin, but Not of E-Cadherin, in Cutaneous Squamous Cell Carcinoma in Comparison to Basal Cell Carcinoma
Authors: Pogorzelska-Dyrbuś Joanna , Nowicka-Suszko Danuta , Piotrowska Aleksandra , Woźniak Zdzisław , Dzięgiel Piotr , Szepietowski Jacek C.
Published: December 2024

Background: Adhesion molecules including E-cadherin and N-cadherin have been proven to contribute to the carcinogenesis process. It has been demonstrated that an increased expression or appearance of N-cadherin, as well as a reduction in the expression of E-cadherin, are documented in many cancers, often leading to the loss of intercellular adhesion and acquisition of a more invasive or even metastatic mesenchymal phenotype. The aim of this study was to assess the expression of E-cadherin and N-cadherin, as well as markers of proliferation Ki67 in basal cell carcinoma (BCC) and squamous cell carcinoma (SCC). Methods: A total of 123 tumor paraffin specimens, including 73 BCC and 50 SCC cases, were obtained from multiple anatomical locations. The expression of E-Cadherin and N-Cadherin, including the percentage of stained cells, was assessed using a four-grade scale, with Ki-67 assessed on the five-grade scale. Results: A significantly higher expression of N-cadherin was observed in SCC compared to BCC, with 14% of SCC cases having a more than 50% expression of N-cadherin, and 10% with 26–50% expression, in comparison with 2.7% and 8.2% in BCC, respectively (p < 0.001). No significant differences were observed with regard to E-cadherin expression between SCC and BCC. Conclusions: Our results suggest that N-cadherin expression might contribute to the acquisition of the mesenchymal phenotype, SCC, when compared with BCC, with a high expression of E-cadherin in both tumors explaining their overall low rate of metastases; however, further research on the role of adhesion molecules in these tumors is needed.
Application of Navigated Transcranial Magnetic Stimulation (nTMS) to Study the Visual–Spatial Network and Prevent Neglect in Brain Tumour Surgery
Authors: Bonaudo Camilla , Castaldi Elisa , Pedone Agnese , Capelli Federico , Enderage Don Shani , Pieropan Edoardo , Bianchi Andrea , Gobbo Marika , Maduli Giuseppe , Fedi Francesca , Baldanzi Fabrizio , Troiano Simone , Maiorelli Antonio , Muscas Giovanni , Battista Francesca , Campagnaro Luca , De Pellegrin Serena , Amadori Andrea , Fainardi Enrico , Carrai Riccardo , Grippo Antonello , Della Puppa Alessandro
Published: December 2024

Objective: Navigated transcranial magnetic stimulation (nTMS) has seldom been used to study visuospatial (VS) circuits so far. Our work studied (I) VS functions in neurosurgical oncological patients by using repetitive nTMS (rnTMS), (II) the possible subcortical circuits underneath, and (III) the correspondence between nTMS and direct cortical stimulation (DCS) during awake procedures. Methods: We designed a monocentric prospective study, adopting a protocol to use rnTMS for preoperative planning, including VS functions for lesions potentially involving the VS network, including neurosurgical awake and asleep procedures. nTMS-based-DTI tractography allowed the visualization of subcortical circuits. Statistical analyses on nTMS/DCS points were performed. Clinical results were collected pre- and postoperatively. Results: Finally, 27 patients with primitive intra-axial brain lesions were enrolled between April 2023 and March 2024. Specific tests and an experimental integrated VS test (VISA) were used. The clinical evaluation (at 5 ± 7, 30 ± 10, 90 ± 10 days after surgery) documented 33% of patients with neglect in the left hemisphere four days after surgery and, during the 3-month follow-up, preservation of visuospatial function/clinical recovery (90.62% in MMSE, 98.86% in the bell test, 80% in the clock test, and 98% in the OCS test). The surgical strategy was modulated according to the nTMS map. Subcortical bundles were traced to identify those most involved in these functions: SFLII > SLFII > SLFI. A comparison of the nTMS and DCS points in awake surgery (n = 10 patients) documented a sensitivity (Se) of 12%, a specificity (Sp) of 91.21%, a positive predictive value (PPV) of 42%, a negative predictive value (NPV) of 66%, and an accuracy of ~63.7%. Conclusions: Based on our preliminary results, nTMS is advantageous for studying cognitive functions, minimising neurological impairment. Further analyses are needed to validate our data.
The Tumor Metabolite 5′-Deoxy-5′Methylthioadenosine (MTA) Inhibits Maturation and T Cell-Stimulating Capacity of Dendritic Cells
Authors: Brummer Christina , Singer Katrin , Henrich Frederik , Peter Katrin , Strobl Carolin , Neueder Bernadette , Bruss Christina , Renner Kathrin , Pukrop Tobias , Herr Wolfgang , Aigner Michael , Kreutz Marina
Published: December 2024

Metabolite accumulation in the tumor microenvironment fosters immune evasion and limits the efficiency of immunotherapeutic approaches. Methylthioadenosine phosphorylase (MTAP), which catalyzes the degradation of 5′-deoxy-5′methylthioadenosine (MTA), is downregulated in many cancer entities. Consequently, MTA accumulates in the microenvironment of MTAP-deficient tumors, where it is known to inhibit tumor-infiltrating T cells and NK cells. However, the impact of MTA on other intra-tumoral immune cells has not yet been fully elucidated. To study the effects of MTA on dendritic cells (DCs), human monocytes were maturated into DCs with (MTA-DC) or without MTA (co-DC) and analyzed for activation, differentiation, and T cell-stimulating capacity. MTA altered the cytokine secretion profile of monocytes and impaired their maturation into dendritic cells. MTA-DCs produced less IL-12 and showed a more immature-like phenotype characterized by decreased expression of the co-stimulatory molecules CD80, CD83, and CD86 and increased expression of the monocyte markers CD14 and CD16. Consequently, MTA reduced the capability of DCs to stimulate T cells. Mechanistically, the MTA-induced effects on monocytes and DCs were mediated by a mechanism beyond adenosine receptor signaling. These results provide new insights into how altered polyamine metabolism impairs the maturation of monocyte-derived DCs and impacts the crosstalk between T and dendritic cells.
Psychological Impact of Distance Learning on Children and Adolescents in Saudi Arabia: A Multi-City Analysis of Behavioral and Mental Health Outcomes During the COVID-19 Pandemic
Authors: Alkhawashki Samah H. , AlTuwairqi Maram H. , Almadani Ahmad H. , Almarshedi Afnan A. , Alasiri Rahaf , Mobeireek Noha A. , Alrashoud Mishaal R. , Abouammoh Noura A. , Alshahrani Fatimah S. , AlFattani Areej A. , Alenezi Shuliweeh
Published: December 2024

Background: The COVID-19 pandemic triggered a global transition to distance learning, which significantly impacted children’s mental health. In Saudi Arabia, remote education began on 8 March 2020, lasting between 1.5 to 2.5 years. This study aims to explore the psychological effects of distance learning on children and adolescents, with a focus on mental health challenges and coping mechanisms. Methods: A cross-sectional study was conducted using an online survey distributed to parents of children aged 6 to 18 in the major metropolitan areas of Jeddah and Riyadh. The survey included demographic questions and the Arabic version of the Vanderbilt ADHD Diagnostic Rating Scale, a tool for assessing behavioral challenges, anxiety, and symptoms of attention deficit hyperactivity disorder (ADHD). Results: A total of 71.6% of families reported a positive experience with distance learning. A significant correlation was found between parents’ marital status and children’s ability to cope with remote education. Interestingly, children without ADHD symptoms experienced three times more negative outcomes than those with ADHD symptoms. However, despite reporting fewer negative experiences, children with ADHD exhibited increased symptom severity and academic difficulties. Of the students, 5.4% were diagnosed with predominantly inattentive ADHD, 1.8% with predominantly hyperactive/impulsive ADHD, and 3.9% with combined ADHD. Additionally, 7.2% of students screened positive for oppositional defiant disorder, 1.5% for conduct disorder, and 6.6% for anxiety or depression. Children from separated or divorced families were more likely to exhibit ADHD symptoms (p = 0.002). Children with ADHD symptoms reported a more positive experience with distance learning (p < 0.05). Conclusion: This study represents the first comprehensive, multi-city investigation in Saudi Arabia examining the relationship between distance learning, sociodemographic factors, and mental health symptoms in children. The findings highlight the psychological challenges faced by children during the pandemic and emphasize the need for targeted interventions to support both mental health and academic outcomes. These results offer valuable insights for future research and inform strategies to address children’s well-being in scenarios involving distance learning.
Clinical Trial: Effect of Autologous Dendritic Cell Administration on Improving Neuropathy Symptoms and Inflammatory Biomarkers in Diabetic Neuropathy
Authors: Setiawan Erwin , Ginting Chrismis Novalinda , Jonny Jonny , Hernowo Bhimo Aji , Putranto Terawan Agus
Published: December 2024

Type 2 diabetes mellitus (T2DM) is a global health concern, with diabetic neuropathy (DN) being a prevalent complication. Current DN treatments focus on blood glucose control and pain management, which show limited efficacy. This study explored the effects of autologous dendritic cell (DC) administration on improving DN symptoms. A quasi-experimental clinical trial was conducted on 28 DN patients at Gatot Soebroto Army Hospital. Patients received autologous DC administration, with their Toronto Clinical Neuropathy Score (TCNS), Transforming Growth Factor-β (TGF-β), and Vascular Cell Adhesion Molecule-1 (VCAM-1) levels measured before and at four weeks after treatment. The results show an average TCNS reduction from 8.93 to 7.5 (p < 0.001). TGF-β levels increased slightly from 41.16 ng/mL to 44.18 ng/mL (p > 0.05). VCAM-1 levels increased from 1389.75 ng/mL to 1403.85 ng/mL. Correlation analysis showed that TGF-β levels had a significant negative correlation with the TCNS (r = −0.353; p = 0.033) and VCAM-1 levels (r = −0.521; p = 0.002). Autologous DC administration significantly improves DN. While the changes in TGF-β and VCAM-1 levels were not statistically significant, their trends suggest that there was an anti-inflammatory effect. These findings highlight the potential of autologous DC therapy as a complementary approach to manage DN through inflammation reduction and nerve repair.
Satisfaction of Patients with Multiple Sclerosis Towards the Provision of Healthcare Services at a Tertiary Care Setting in Saudi Arabia
Authors: Al-Dossari Dalal Salem , Al-Zaagi Ibrahim Abdulaziz , Salamma Mashael Abdulrahman Bin , Alghamdi Faisal Abdulaziz , Althobaiti Ahmed Hasan , Al-Harbi Abdullah Bin Dakhil Allah bin Awad , Alshelali Abdullah Rashed , Hassan Anham Nabil , Ali Baleegh Mohammed , Ali Sheraz
Published: December 2024

Background: Multiple sclerosis (MS) is an autoimmune-mediated neurological disorder and the most frequent neurological disability in young adults. Assessing MS patient satisfaction with care is necessary to evaluate healthcare service quality and factors impacting it. Objectives: We aimed to determine the satisfaction of patients with MS towards the provision of healthcare services, and the factors affecting their satisfaction. Methods: We conducted a cross-sectional survey from November 2022 to December 2022 at King Saud Medical City, Saudi Arabia. The study participants completed the CANHELP Lite27 questionnaire, which consists of 21 items. Results: A total of 300 patients with MS participated in this study. The majority were female (80%), with an average age of 31.6 years and a mean disease duration of 5.22 years. Overall, satisfaction was moderate (63.59 ± 14.54). Patients were most satisfied with general aspects of care (72.00 ± 16.46), doctor relationships (68.58 ± 14.88), and communication (67.72 ± 17.60), but less so with decision-making (64.98 ± 18.37) and illness management (59.60 ± 16.31). Correlation analysis revealed a negative association between disease duration and satisfaction across all domains (correlation coefficient ranged from −0.290 to −0.206, p < 0.01), while age showed no significant correlation (p > 0.05). Multiple linear regression identified age as positively influencing satisfaction, while longer disease duration had a negative impact. Higher education and marital status were associated with increased satisfaction, while employment status and having children showed mixed results. Conclusions: This research uncovered significant insights regarding MS patient satisfaction within healthcare services. Despite moderate satisfaction levels overall, specific interventions are necessary to address shortcomings in decision-making and illness management. The negative correlation between disease duration and satisfaction across all domains underscores the evolving needs of MS patients over time. Future research could examine the effectiveness of illness management programs in improving MS patient satisfaction.
Formulation and Evaluation of Facial Serum Containing Sacha Inchi Oil (Plukenetia volubilis L.) from Indonesia as an Anti-Aging: Stability, In Vitro, and Skin Irritation Assessments
Authors: Maya Ira , Sriwidodo Sriwidodo , Mita Soraya Ratnawulan , Kusumawulan Cahya Khairani , Putriana Norisca Aliza , Amalia Eri , Aulia Rizqa Nurul , Sofyan Hadiyan Nur , Dzulfannazhir Fauzan , Nugraha Moh Hamdan
Published: December 2024

Reactive oxygen species (ROS), commonly recognized as free radicals, significantly contribute to skin damage by disrupting defense and repair mechanisms, thereby accelerating the aging process. An effective strategy to prevent and alleviate skin aging involves the application of topical formulations enriched with powerful antioxidant compounds. Sacha inchi oil (Plukenetia volubilis L.) has been reported to possess significant antioxidant activity, while its oil contains a high content of omega-3 fatty acids, offering potential anti-aging benefits. This study aims to evaluate the stability, in vitro anti-aging activity, and skin irritation assessments of a facial serum containing Sacha inchi oil (SIO) formulated as a topical anti-aging agent. The stability of the serum was assessed by analyzing its organoleptic properties, homogeneity, viscosity, spreadability, pH, microbial contamination, and heavy metal content over a three-month period under controlled climatic conditions. The in vitro anti-aging activity was evaluated through enzyme inhibition assays for neutrophil elastase and collagenase, while skin irritation was assessed via human patch testing. The results indicated that the SIO facial serum exhibits excellent stability, significant anti-aging activity, and is safe for topical application, with no irritant effects observed during skin irritation assessments.
Targeting TOP2A in Ovarian Cancer: Biological and Clinical Implications
Authors: Borella Fulvio , Fucina Stefano , Seminara Ylenia , Denti Pietro , Ferraioli Domenico , Bertero Luca , Gallio Niccolò , Cusato Jessica , Valabrega Giorgio , Revelli Alberto , Marozio Luca , Cosma Stefano
Published: December 2024

The enzyme topoisomerase II alpha (TOP2A) plays a critical role in DNA replication and cell proliferation, making it a promising target for cancer therapy. In epithelial ovarian cancer (EOC), TOP2A overexpression is associated with poor prognosis and resistance to conventional treatments. This review explores the biological functions of TOP2A in EOC and discusses its potential as a therapeutic target. We highlight studies on the mechanisms through which TOP2A contributes to tumor progression and recurrence. Additionally, we evaluate the clinical implications of targeting TOP2A, including the use of TOP2A inhibitors and their combination with novel drugs. We provide a comprehensive overview of the current understanding and future directions for targeting TOP2A in the management of EOC.
Plant Species Diversity Assessment in the Temperate Grassland Region of China Using UAV Hyperspectral Remote Sensing
Authors: Wang Hong , Feng Chunyong , Li Xiaobing , Yang Yalei , Zhang Yao , Su Jingru , Luo Dingsheng , Wei Dandan , He Yixiao
Published: December 2024

Biodiversity conservation is a critical environmental challenge, with accurate assessment being essential for conservation efforts. This study addresses the limitations of current plant diversity assessment methods, particularly in recognizing mixed and stunted grass species, by developing an enhanced species recognition approach using unmanned aerial vehicle (UAV) hyperspectral data and deep learning models in the steppe region of Xilinhot, Inner Mongolia. We compared five models—support vector machine (SVM), two-dimensional convolutional neural network (2D-CNN), three-dimensional convolutional neural network (3D-CNN), hybrid spectral CNN (HybridSN), and the improved HybridSN+—for grass species identification. The results show that SVM and 2D-CNN models have relatively poor recognition effects on mixed distribution and stunted individuals, while HybridSN and HybridSN+ models can effectively identify important grass species in the region, and the recognition accuracy of the HybridSN+ model can reach 96.45 (p < 0.05). Notably, the 3D-CNN model’s recognition performance was inferior to the HybridSN model, especially for densely populated and smaller grass species. The HybridSN+ model, optimized from the HybridSN model, demonstrated improved recognition performance for smaller grass species individuals under equivalent conditions, leading to a discernible enhancement in overall accuracy (OA). Diversity indices (Shannon–Wiener diversity, Simpson diversity, and Pielou evenness) were calculated using the identification results from the HybridSN+ model, and spatial distribution maps were generated for each index. A comparative analysis with diversity indices derived from ground survey data revealed a strong correlation and consistency, with minimal differences between the two methods. This study provides a feasible technical approach for efficient and meticulous biodiversity assessment, offering crucial scientific references for regional biodiversity conservation, management, and restoration.
Application of the U-Net Deep Learning Model for Segmenting Single-Photon Emission Computed Tomography Myocardial Perfusion Images
Authors: Alenezi Ahmad , Mayya Ali , Alajmi Mahdi , Almutairi Wegdan , Alaradah Dana , Alhamad Hamad
Published: December 2024

Background: Myocardial perfusion imaging (MPI) is a type of single-photon emission computed tomography (SPECT) used to evaluate patients with suspected or confirmed coronary artery disease (CAD). Detection and diagnosis of CAD are complex processes requiring precise and accurate image processing. Proper segmentation is critical for accurate diagnosis, but segmentation issues can pose significant challenges, leading to diagnostic difficulties. Machine learning (ML) algorithms have demonstrated superior performance in addressing segmentation problems. Methods: In this study, a deep learning (DL) algorithm, U-Net, was employed to enhance segmentation accuracy for image segmentation in MPI. Data were collected from 1100 patients who underwent MPI studies at Al-Jahra Hospital between 2015 and 2024. To train the U-Net model, 100 studies were segmented by nuclear medicine (NM) experts to create a ground truth (gold-standard coordinates). The dataset was divided into a training set (n = 100 images) and a validation set (n = 900 images). The performance of the U-Net model was evaluated using multiple cross-validation metrics, including accuracy, precision, intersection over union (IOU), recall, and F1 score. Result: A dataset of 4560 images and corresponding masks was generated. Both holdout and k-fold (k = 5) validation strategies were applied, utilizing cross-entropy and Dice score as evaluation metrics. The best results were achieved with the holdout split and cross-entropy loss function, yielding a test accuracy of 98.9%, a test IOU of 89.6%, and a test Dice coefficient of 94%. The k-fold validation scenario provided a more balanced true positive and false positive rate. The U-Net segmentation results were comparable to those produced by expert nuclear medicine technologists, with no significant difference (p = 0.1). Conclusions: The findings demonstrate that the U-Net model effectively addresses some segmentation challenges in MPI, facilitating improved diagnosis and analysis of mega data.
Optimizing Radiation Dose and Image Quality in Stroke CT Protocols: Proposed Diagnostic Reference Levels for Multiphase CT Angiography and Perfusion Imaging
Authors: Forbrig Robert , Trumm Christoph G. , Reidler Paul , Kunz Wolfgang G. , Dimitriadis Konstantinos , Kellert Lars , Rückel Johannes , Liebig Thomas , Stahl Robert
Published: December 2024

Objective: In suspected acute ischemic stroke, it is now reasonable to expand the conventional “stroke protocol” (non-contrast computed tomography (NCCT), arterial CT angiography (CTA), and optionally CT perfusion (CTP)) to early and late venous head scans yielding a multiphase CTA (MP-CTA) to increase diagnostic confidence. Diagnostic reference levels (DRLs) have been defined for neither MP-CTA nor CTP. We therefore present dosimetry data, while also considering image quality, for a large, unselected patient cohort. Methods: A retrospective single-center study of 1790 patients undergoing the extended stroke protocol with three scanners (2× dual-source, DSCT; 1× single-source, SSCT) between 07/21 and 12/23 was conducted. For each sequence, we analyzed the radiation dose (volumetric CT dose index (CTDIvol); dose length product; effective dose); objective image quality using manually placed regions of interest (contrast-to-noise ratio (CNR)); and subjective image quality (4-point scale: 1 = non-diagnostic, 4 = excellent). The DRL was defined as the 75% percentile of the CTDIvol distribution. The Kruskal-Wallis test was used initially to test for overall equality of median values in each data group. Single post-test comparisons were performed with Dunn’s test, with an overall statistical significance level of 0.05. Results: Dosimetry values were significantly higher for SSCT (p < 0.001, each). Local DRLs ranged between 37.3 and 49.1 mGy for NCCT, 3.6–5.5 mGy for arterial CTA, 1.2–2.5 mGy each for early/late venous CTA, and 141.1–220.5 mGy for CTP. Protocol adjustment (DSCT-1: CTP) yielded a 28.2% dose reduction. The highest/lowest CNRs (arterial/early venous CTA, respectively) were recorded for SSCT/DSCT-2 (p < 0.001). Subjective image quality was rated excellent except for slightly increased MP-CTA noise at DSCT-2 (median = 3). Conclusions: Our data imply that additive MP-CTA scans only yield a minor increase in radiation exposure, particularly when using DSCT. CTP should be limited to selected patients.
The Therapeutic Potential of Oral Everolimus for Facial Angiofibromas in Pediatric Tuberous Sclerosis Complex: A Case-Based Analysis of Efficacy
Authors: Imataka George , Mori Satoshi , Yui Kunio , Igawa Ken , Shiraishi Hideaki , Yoshihara Shigemi
Published: December 2024

Background: Tuberous sclerosis complex (TSC) is an autosomal dominant genetic disorder characterized by mutations in the TSC1 and TSC2 genes, leading to the dysregulation of the mammalian target of rapamycin (mTOR) pathway. This dysregulation results in the development of benign tumors across multiple organ systems and poses significant neurodevelopmental challenges. The clinical manifestations of TSC vary widely and include subependymal giant cell astrocytomas (SEGAs), renal angiomyolipomas (AMLs), facial angiofibromas (FAs), and neuropsychiatric conditions such as autism spectrum disorder (ASD). mTOR inhibitors, notably everolimus, have become central to TSC management, with documented efficacy in reducing the sizes of SEGAs and AMLs and showing promise in addressing additional TSC-related symptoms. Case Presentation: We report the case of an 11-year-old male diagnosed with TSC, presenting with hallmark features including hypopigmented macules, early-onset infantile spasms, SEGA, and AMLs. Initial interventions included adrenocorticotropic hormone (ACTH) therapy and sodium valproate for seizure management and a minimally invasive keyhole craniotomy for SEGA reduction. At age 12, oral everolimus therapy was introduced to address both SEGA recurrence risk and ASD-related social deficits. Over the course of 24 weeks, a reduction in the size and erythema of the patient’s FAs was observed, alongside improvements in social engagement, suggesting potential added benefits of systemic mTOR inhibition beyond tumor control. Results: Treatment with everolimus over a 24-month period led to significant reductions in both FA and AML size, as well as measurable improvements in ASD-associated behaviors. Therapeutic drug monitoring maintained serum levels within the effective range, minimizing adverse effects and underscoring the tolerability and feasibility of long-term everolimus administration. Conclusions: This case underscores the efficacy of oral everolimus in reducing FA size in a pediatric TSC patient, with broader therapeutic benefits that support the potential of mTOR inhibition as a multi-targeted strategy for TSC management. Further studies are needed to explore the full range of applications and long-term impact of mTOR inhibitors in TSC care.
Outcomes of Flapless Er:YAG and Er,Cr:YSGG Laser-Assisted Crown Lengthening: A Systematic Review
Authors: Elafifi Ebeid Haitham , Altayeb Walid , Parada Avendaño Isabel , Abad-Sanchez Daniel , Arnabat-Domínguez Josep
Published: December 2024

Introduction: In recent years, erbium-doped yttrium aluminum garnet (Er:YAG) and erbium, chromium/yttrium–scandium–gallium–garnet (Er,Cr:YSGG) lasers have been introduced as another possibility to perform less-invasive flapless (FL) crown-lengthening (CL) procedures. Objectives: The aim of this review is to describe the outcomes and complications of this approach. Materials and methods: A literature review was conducted to retrieve clinical studies and case reports that analyze different variables related to laser-assisted flapless crown lengthening and report their outcomes in terms of gingival margin level stability (GMLS), and postoperative complications. Results: A total of five studies were included in the final qualitative analysis; two of them were randomized controlled trials (RCTs) and the rest were case reports. The common variable measured in all studies was the GMLS, finding good stability in the FL groups at 3 months follow-up, but more tissue rebound was observed in patients with the thick biotype. Other variables were reported in different articles as the plaque index (PI), gingival index (GI), bone margin level, biotype, bleeding on probing (BP), probing depth (PD), and postoperative pain by the numeric rating scale (NRS). Discussion: There are a wide range of heterogenous clinical variables used to evaluate outcomes, as well as variations in the type of laser used and its parameters in terms of the applied technique. However, most analyzed studies showed better GMLS for the flapless technique, as well as less postoperative inflammation. Conclusions: The included studies showed promising clinical outcomes in the FL laser-assisted CL groups concerning GMLS at the 3-month postoperative period. However, more RCTs are needed with respect to fixed laser parameters and patient biotype selection to reach a definitive clinical protocol.
DRL-Based Improved UAV Swarm Control for Simultaneous Coverage and Tracking with Prior Experience Utilization
Authors: Chen Yiting , Chen Runfeng , Huang Yuchong , Xiong Zehao , Li Jie
Published: December 2024

Area coverage and target tracking are important applications of UAV swarms. However, attempting to perform both tasks simultaneously can be a challenge, particularly under resource constraints. In such scenarios, UAV swarms must collaborate to cover extensive areas while simultaneously tracking multiple targets. This paper proposes a deep reinforcement learning (DRL)-based, scalable UAV swarm control method for a simultaneous coverage and tracking (SCT) task, called the SCT-DRL algorithm. SCT-DRL simplifies the interaction between UAV swarms into a series of pairwise interactions and aggregates the information of perceived targets in advance, based on which forms the control framework with a variable number of neighboring UAVs and targets. Another highlight of SCT-DRL is using the trajectories of the traditional one-step optimization method to initialize the value network, which encourages the UAVs to select the actions leading to the state with less rest time to task completion to avoid extensive random exploration at the beginning of training. SCT-DRL can be seen as a special improvement of the traditional one-step optimization method, shaped by the samples derived from the latter, and gradually overcomes the inherent myopic issue with the far-sighted value estimation through RL training. Finally, the effectiveness of the proposed method is demonstrated through numerical experiments.
Lossless Image Compression Using Context-Dependent Linear Prediction Based on Mean Absolute Error Minimization
Authors: Ulacha Grzegorz , Łazoryszczak Mirosław
Published: December 2024

This paper presents a method for lossless compression of images with fast decoding time and the option to select encoder parameters for individual image characteristics to increase compression efficiency. The data modeling stage was based on linear and nonlinear prediction, which was complemented by a simple block for removing the context-dependent constant component. The prediction was based on the Iterative Reweighted Least Squares (IRLS) method which allowed the minimization of mean absolute error. Two-stage compression was used to encode prediction errors: an adaptive Golomb and a binary arithmetic coding. High compression efficiency was achieved by using an author’s context-switching algorithm, which allows several prediction models tailored to the individual characteristics of each image area. In addition, an analysis of the impact of individual encoder parameters on efficiency and encoding time was conducted, and the efficiency of the proposed solution was shown against competing solutions, showing a 9.1% improvement in the bit average of files for the entire test base compared to JPEG-LS.
Text-Based Prompt Injection Attack Using Mathematical Functions in Modern Large Language Models
Authors: Kwon Hyeokjin , Pak Wooguil
Published: December 2024

Prompt injection is a type of attack that induces violent or discriminatory responses via the input of a prompt containing illegal instructions to the large language model (LLM). Most early injection attacks used simple text prompts; however, recently, injection attacks employing elaborately designed prompts to overcome the strong security policies of modern LLMs have been applied to input prompts. This study proposed a method to perform injection attacks that can bypass existing security policies via the replacement of sensitive words that may be rejected by a language model in the text prompt with mathematical functions. By hiding the contents of the prompt so that the LLM cannot easily detect the contents of the illegal instructions, we achieved a considerably higher success rate than existing injection attacks, even for the latest securely aligned LLMs. As the proposed method employed only text prompts, it was capable of attacking most LLMs. Moreover, it exhibited a higher attack success rate than multimodal attacks using images despite using only text. An understanding of the newly proposed injection attack is expected to aid in the development of methods to further strengthen the security of current LLMs.
A Wideband dB-Linear Analog Baseband for a Millimeter-Wave Receiver with Error Compensation in 40 nm CMOS Technology
Authors: Hu Shiwei , Wang Hao , Wang Yanjie
Published: December 2024

This paper presents a low power wideband dB-linear analog baseband (ABB) circuit for a millimeter-wave (mmW) wireless receiver in 40 nm CMOS technology. The proposed ABB system consists of a multi-stage variable gain amplifier (VGA) and a low-pass filter (LPF). The 5-stage VGA is composed of two variable gain units followed by three fixed gain units with DC offset cancellation (DCOC). The first variable gain unit with a self-compensated transistor pair and compact active inductor load is designed for dB-linear functionality and bandwidth extension, respectively. Moreover, a proposed error compensation method is applied to the second cascaded variable gain unit for further dB-linear gain error correction. A 4th-order Butterworth transconductance-capacitance (Gm-C) LPF with flipped source follower (FSF) as an input transconductance stage for linearity enhancement is designed after the VGA stage. The prototype chip is implemented, and measurement results show a dB-linear gain range from −18 to 26 dB with less than 0.5 dB-linear gain error with a bandwidth of 4 GHz. The VGA and LPF consume 8.3 mW and 3 mW, respectively, under a 1 V power supply, while the entire ABB occupies an area of 0.94 mm2 with an active core area of only 0.045 mm2.
Research on the Economic Scheduling Problem of Cogeneration Based on the Improved Artificial Hummingbird Algorithm
Authors: Kong Xiaohong , Li Kunyan , Zhang Yihang , Tian Guocai , Dong Ning
Published: December 2024

With the increasing application of Combined Heat and Power (CHP) units, Combined Heat and Power Economic Dispatch (CHPED) has emerged as a significant issue in power system operations. To address the complex CHPED problem, this paper proposes an effective economic dispatch method based on the Improved Artificial Hummingbird Algorithm (IAHA). Given the complex constraints of the CHPED problem and the presence of valve point effects and prohibited operating zones, it requires the algorithm to have high traversal capability in the solution space and be resistant to becoming trapped in local optima. IAHA has introduced two key improvements based on the characteristics of the CHPED problem and the shortcomings of the standard Artificial Hummingbird Algorithm (AHA). Firstly, IAHA uses chaotic mapping to initialize the initial population, enhancing the algorithm’s traversal capability. Second, the guided foraging of the standard AHA has been modified to enhance the algorithm’s ability to escape from local optima. Simulation experiments were conducted on CHP systems at three different scales: 7 units, 24 units, and 48 units. Compared to other algorithms reported in the literature, the IAHA algorithm reduces the cost in the three testing systems by up to USD 18.04, 232.7894, and 870.7461. Compared to other swarm intelligence algorithms reported in the literature, the IAHA algorithm demonstrates significant advantages in terms of convergence accuracy and convergence speed. These results confirm that the IAHA algorithm is effective in solving the CHPED problem while overcoming the limitations of the standard AHA.
Potential for Using Composts Produced from Agri-Food Industry Waste as Biocomponents of Liquid and Solid Fuels
Authors: Sienkiewicz Aneta , Cwalina Paweł , Obidziński Sławomir , Krasowska Małgorzata , Kowczyk-Sadowy Małgorzata , Piotrowska-Niczyporuk Alicja , Bajguz Andrzej
Published: December 2024

The growing awareness of the depletion of fossil fuels and numerous environmental issues have led to increased interest in finding natural components that can be used to produce various types of fuels. In this study, composts made from the organic fraction of agri-food waste (i.e., two composts produced in a bioreactor and one obtained from a Municipal Waste Disposal Facility) were evaluated for the first time as potential sources of additives for fuel production. The presence of fatty acid methyl esters was determined using gas chromatography–mass spectrometry (GC-MS/SIM), while the calorific value and heat of combustion of the samples were measured in accordance with the PN-EN ISO 1928:2002 standard using a calorimeter. Chromatographic studies identified the presence of 33 compounds, predominantly unsaturated esters. The highest ester content was noted in the compost obtained from the company, while the lowest content was found in the compost containing grass, buckwheat husk, and apple pomace. Of the studied raw materials, the highest calorific value and heat of combustion on a dry matter basis were observed for the compost containing grass, buckwheat husk, and apple pomace, while the lowest values were recorded for the compost obtained from the company. Based on the obtained results, it can be concluded that composts could serve as biocomponents of fuels.
An Investigative Study on Energy Harvesting by Hydrofoils: Simple vs. Undulated
Authors: Mehmood Asad , Qureshi Saad , Ghafoor Usman , Swati Raees , Gillani Fouzia , Bibi Sameena , Bakkar Abu , Shah Muhammad
Published: December 2024

A series of experiments were performed using multiple configurations of hydrofoils to assess the energy harvesting capabilities present within the wake of streamlined bodies. The experiments were performed in a low-speed water tunnel, with energy harvesting assessed using a piezoelectric eel and imaging equipment. Half-sinusoidal undulations were introduced in different combinations on the leading and trailing edges of the hydrofoil. All hydrofoils utilized a NACA 0012 cross-sectional profile. A piezoelectric eel was placed at a variable distance downstream of the hydrofoil’s trailing edge, and the hydrofoil’s angle of attack (α) was varied in order to assess the variation in power generation. The maximum power output was achieved at x/c = 1–1.5 downstream of the trailing edge in all configurations. It was observed that harvested energy is dependent on the oscillation of the eel, α, the streamwise distance between the trailing edge of the hydrofoils and the eel, as well as the geometry of the hydrofoils. Particle image velocimetry was also performed on selected cases for which the recorded energy harvest was high. The results showed that the NACA 0012 base profile has a higher extractable energy capacity in its wake than do the serrated hydrofoils, which confirms the results found in the literature.
Applications of Deep Reinforcement Learning for Home Energy Management Systems: A Review
Authors: Latoń Dominik , Grela Jakub , Ożadowicz Andrzej
Published: December 2024

In the context of the increasing integration of renewable energy sources (RES) and smart devices in domestic applications, the implementation of Home Energy Management Systems (HEMS) is becoming a pivotal factor in optimizing energy usage and reducing costs. This review examines the role of reinforcement learning (RL) in the advancement of HEMS, presenting it as a powerful tool for the adaptive management of complex, real-time energy demands. This review is notable for its comprehensive examination of the applications of RL-based methods and tools in HEMS, which encompasses demand response, load scheduling, and renewable energy integration. Furthermore, the integration of RL within distributed automation and Internet of Things (IoT) frameworks is emphasized in the review as a means of facilitating autonomous, data-driven control. Despite the considerable potential of this approach, the authors identify a number of challenges that require further investigation, including the need for robust data security and scalable solutions. It is recommended that future research place greater emphasis on real applications and case studies, with the objective of bridging the gap between theoretical models and practical implementations. The objective is to achieve resilient and secure energy management in residential and prosumer buildings, particularly within local microgrids.
A Study on Bio-Coke Production—The Influence of Biochar Addition to the Coking Blend on Bio-Coke Quality Parameters
Authors: Rejdak Michał , Książek Michał , Wojtaszek-Kalaitzidi Małgorzata , Rodź Anna , Mertas Bartosz , Larsen Sten Yngve , Szecówka Piotr
Published: December 2024

Carbon dioxide is emitted in several industrial processes and contributes to global warming. One of the industries that is considered a significant emitter is metallurgy. Therefore, it is necessary to search for and implement methods to reduce its emissions from metallurgical processes. An alternative option to the use of conventional coke, which is produced solely from fossil coal, is the utilization of bio-coke. The production of bio-coke involves the use of coking coal and the incorporation of biomass-derived substances such as biochar (charcoal). The article presents the results of the research on the influence of the biochar addition on the structural, textural, and technological properties of produced bio-coke. Research on the production and analysis of the properties of the obtained bio-coke aimed at assessing the potential possibilities of applying it in the process of a carbothermal reduction of manganese ore in order to smelt ferroalloys. Studies have shown that biochar addition to the coking blend in an amount of up to 20% allows a bio-coke characterized by properties enabling the mentioned use to be obtained. Bio-coke was characterized by higher CO2 reactivity index (CRI), lower post-reaction strength (CSR), and higher reactivity to synthetic manganese ore than regular metallurgical coke. In the context of industrial applications of bio-coke, it is necessary to verify its production and use on a pilot and industrial scale.
Analysis of Sustainable Energy and Environmental Policies in Agriculture in the EU Regarding the European Green Deal
Authors: Prigoreanu Ioan , Ungureanu Bianca Antonela , Ungureanu George , Ignat Gabriela
Published: December 2024

The paper analyzes energy and environmental policies in agriculture in the context of the European Green Deal, emphasizing the contribution of the Common Agricultural Policy in supporting sustainability objectives. The study explores how Member States implement specific measures to reduce greenhouse gas emissions, conserve natural resources, and protect biodiversity by 2030. The analysis focuses on three main objectives: reducing emissions and adapting to climate and energy changes, managing natural resources sustainably and ensuring energy efficiency, and promoting organic farming and conserving biodiversity. Using a methodology that aligns Green Deal goals with CAP measures, this research involves a comparative analysis between Member States, highlighting disparities in policy implementation, particularly between Eastern and Western Europe, suggesting that a coordinated EU approach is needed to support equitable progress. The paper provides a detailed perspective on the progress made and offers recommendations for harmonizing agricultural policies in the EU, supporting farmers in adopting ecological and energy efficient practices, and ensuring a consistent approach in achieving Green Deal objectives by 2030.
Distributed Optimal Control of DC Network Using Convex Relaxation Techniques
Authors: Fu Yongbo , Shi Min , Li Gongming , Liu Zhangjie , Li Juntao , Jia Pengzhou , Yue Haiqun , Liu Xiaqing , Zhao Xin , Wang Meng
Published: December 2024

This paper proposes a novel distributed control strategy for DC microgrids using a convex relaxation method to ensure the system operates at the optimal power flow solution. Initially, a suitable convex relaxation technique is applied to transform the non-convex optimal power flow problem into a convex form, with the accuracy of this method being rigorously demonstrated. Next, the Karush–Kuhn–Tucker (KKT) optimality conditions of the relaxed problem are equivalently transformed, and a synchronization term is derived to facilitate the distributed control, thereby ensuring operation under optimal power flow. This paper also analyzes the impacts of communication delay and network structure on the performance of the proposed control strategy. Finally, simulations and numerical experiments are presented to validate the effectiveness of the proposed method.