Search Results (144)

Wirelessly charging unmanned aerial vehicles (WCUAVs) can complete charging tasks without human intervention and may help us efficiently collect various types of geographically dispersed data in unmanned data collection systems (UDCSs). However, the limited number of wireless charging stations and longer wireless charging times also pose challenges to minimizing the Age of Information (AoI). Here, we provide a heuristic method to minimize AoI for WCUAVs. Firstly, the problem of minimizing AoI is modeled as a trajectory optimization problem with nonlinear constraints involving n sensor nodes, a data center, and a limited number of wireless charging stations. Secondly, to solve this NP-hard problem, an improved artificial plant community (APC) approach is proposed, including a single-WCUAV architecture and a multi-WCUAV architecture. Thirdly, a benchmark test set is designed, and benchmark experiments are conducted. When the number of WCUAVs increased from 1 to 2, the total flight distance increased by 12.011% and the average AoI decreased by 45.674%. When the number of WCUAVs increased from 1 to 10, the total flight distance increased by 87.667% and the average AoI decreased by 78.641%. The experimental results show that the proposed APC algorithm can effectively solve AoI minimization challenges of WCUAVs and is superior to other baseline algorithms with a maximum improvement of 9.791% in average AoI. Due to its simple calculation and efficient solution, it is promising to deploy the APC algorithm on the edge computing platform of WCUAVs. Full article

(1) Background: This study proposes investigating the biomechanical stability of a novel 6-hole L-shaped plate for symphyseal fixation, which allows for reduction and stability in two planes. The results of the novel plate are compared to the standard plate; (2) Methods: The novel plate fixation and the standard 6-hole pubic symphyseal plate were tested with a pelvis model simulating an APC III injury. Each group of 10 pelves was subjected to a cyclic biomechanical single-leg-stance test for 30,000 cycles simulating partial bearing loading at 1 Hz, followed by a maximum load-to-failure test. The stiffness and displacement were evaluated and analyzed; (3) Results: Stiffness measurements during cyclic loading revealed no significant differences between the groups (p = 0.514). The cumulative plastic deformation was significantly lower in the novel plate group (p = 0.005). Load-to-failure testing demonstrated that both constructs exhibited similar ultimate strength, with no significant difference in the mean of maximum force between the novel (400.61 ± 44.65 N) and reference (433.02 ± 87.60 N) groups (p = 0.804); (4) Conclusions: The novel plate provides comparable biomechanical stability to the reference plate under the tested cyclic loading conditions, suggesting that it could be a viable alternative to the existing standard. However, further research is necessary to understand the clinical outcomes and long-term impacts. Full article

Background/Objectives: Hippocampal atrophy indicates Alzheimer’s disease (AD) progression and guides follow-up and trial enrichment. Identifying high-risk patients is crucial for optimizing care, but accessible, interpretable machine-learning models (ML) are limited. We developed an explainable ML model using clinical data and CSF erythrocyte load (CTRED) to classify adults with AD as high- or low-risk based on hippocampal volume decline. Methods: Included ADNI participants with ≥2 MRIs, baseline lumbar puncture, and vital signs within 6 months of MRI (n = 26). The outcome was the Annual Percentage Change (APC) in hippocampal volume, classified as low or high risk. Predictors were standardized; models included SVM, logistic regression, and Ridge Classifier, tuned and tested on a set (n = 6). Thresholds were based on out-of-fold predictions under a 10–90% positive rate. Explainability used PFI and SHAP for per-patient contributions. Results: All models gave identical classifications, but discrimination varied: Ridge AUC = 1.00, logistic = 0.889, and SVM = 0.667. PFI highlighted MAPres and sex as main signals; CTRED contributed, and age had a minor impact. Conclusions: The explainable ML model with clinical data and CTRED can stratify AD patients by hippocampal atrophy risk, aiding follow-up and vascular assessment planning rather than treatment decisions. Validation in larger cohorts is needed. This is the first ML study to use CSF erythrocyte load to predict hippocampal atrophy risk in AD. Full article

Background and Objectives: Thrombophilia is a prothrombotic disorder that increases the risk of blood clotting and can pose serious health problems. It is considered a condition of gene–gene or gene–environment interactions. Variation in the prevalence of thrombophilia mutations and their interaction among populations necessitates localized genetic assessments. However, population-based genetic data remains limited for developing effective preventive strategies. Materials and Methods: This cross-sectional observational study was conducted over five years (2020–2024) at a tertiary university hospital in Northern Greece. A total of 2961 individuals aged 18–85 years (mean: 50.5) were registered based on family or medical history of venous thromboembolism (VTE) or clinical symptoms of VTE. The final analysis included 2078 participants comprising 1143 males (55%) and 935 females (45%), who met all the inclusion criteria. Inclusion criteria were absence of acute illness or malignancy, informed consent, and an adequate DNA quantity for genotyping, whereas excluded criteria included incomplete laboratory data, active inflammatory or malignant disease, and cognitive or psychiatric conditions. Peripheral blood samples were collected in 2 mL K₃-EDTA tubes, and genomic DNA was analyzed using real-time polymerase chain reaction (PCR) with melting curve analysis and hybridization probes (LightMix^® in vitro diagnostics, TIB MolBiol, Berlin, Germany). Five thrombophilia-related polymorphisms, Factor V Leiden (F5 G1691A), prothrombin (F2 G20210A), methylenetetrahydrofolate reductase (MTHFR C677T and MTHFR A1298C), and Plasminogen Activator Inhibitor-1 (PAI-1) 4G/5G, were examined for allele and genotype frequencies, Hardy–Weinberg equilibrium testing, pairwise linkage disequilibrium (D′ and r²), and power analysis. For subjects tested for Factor V Leiden (n = 1476), the activated protein C resistance (APC) ratio was additionally evaluated using the ACL TOP 750 analyzer. Results: Allele frequencies were 7.3% for FV Leiden and 3.7% for FII. The PAI-1 allele was distributed at 44%, while the MTHFR (C677T and A1298C) alleles were each present at 33%. Significant linkage disequilibrium was identified between MTHFR (C677T and A1298C) and between MTHFR A1298C and PAI-1. No evolutionary pressure or demographic bias was found in the Hardy–Weinberg equilibrium. The APC ratio demonstrated a high sensitivity (99.2%) and specificity (96.6%), indicating that it may serve as a reliable screening method. Conclusions: Our findings highlight informative patterns in the genetic predisposition to thrombophilia, which may help develop rule-based strategies for implementing thromboprophylaxis guidelines and personalized medical interventions. Full article

Background/Objectives: Cerebrospinal fluid erythrocyte load (CTRED) reflects occult red-blood-cell ingress into brain/CSF and consequent heme–iron exposure, a toxic pathway relevant to Alzheimer’s disease (AD). We aimed to develop explainable machine learning (ML) models that classify high vs. low CTRED from routine, largely non-invasive inputs, and to position a blood-first workflow leveraging contemporary plasma amyloid–tau biomarkers. Methods: Twenty-six ADNI participants were analyzed. Inputs were age, sex, mean arterial pressure (MAPres), amyloid (Aβ42), total tau, phosphorylated tau, and hippocampal atrophy rate (APC) derived from longitudinal MRI. APC was computed from normalized hippocampal volumes. CTRED was binarized at the median (0 vs. >0). Data were split into train (n = 20) and held-out test (n = 6). Five classifiers (linear SVM, ridge, logistic regression, random forests, and MLP) were trained in leakage-safe pipelines with stratified five-fold cross-validation. To provide a comprehensive assessment, we presented the contribution AUC, thresholded performance metrics, summarized model performance, and the permutation feature importance (PFI). Results: On the test set, SVM, ridge, logistic regression, and random forests achieved AUC = 1.00, while the MLP achieved AUC = 0.833. Across models, PFI consistently prioritized p-tau/tau, Aβ42, and MAPres; age, sex, and APC contributed secondarily. The attribution profile aligns with mechanisms linking BBB dysfunction and amyloid-related microvascular fragility with tissue vulnerability to heme–iron. Conclusions: In this proof-of-concept study, explainable ML predicted CTRED from routine variables with biologically coherent drivers. Although ADNI measurements were CSF-based and the sample was small, the framework is non-invasive by adding plasma p-tau217/Aβ1–42 for amyloid, tau inputs, and integrating demographics, hemodynamic context, and MRI. External, plasma-based validation in larger cohorts is warranted, alongside extension to MCI and multimodal correlation (QSM, DCE-MRI) to establish clinically actionable CTRED thresholds. Full article

In this study, AlGaN/GaN heterostructure field-effect transistors (HFETs) with an AlN cap layer and a GaN cap layer were fabricated. The devices were of different sizes. Capacitance–voltage (C-V) and current–voltage (I-V) curves were measured. Based on two-dimensional (2D) scattering theory, electron mobility corresponding to polarization Coulomb field (PCF) scattering and other primary scattering mechanisms was quantitatively determined. The influence of the AlN cap layer on PCF scattering in AlGaN/GaN HFETs was studied. It was found that the AlN cap layer suppresses the inverse piezoelectric effect (IPE) in the AlGaN barrier layer because of its greater polarization and larger Young’s modulus, thereby reducing the generation of additional polarization charge (APC) under the gate. In addition, the 2D electron gas (2DEG) density (n_2DEG) under the gate of the samples with an AlN cap layer is higher. Both factors help reduce PCF scattering intensity. Moreover, mobility analysis of samples with different gate–drain spacings (L_GD) showed that PCF scattering is less affected by L_GD variations in devices with AlN cap layers. This study offers new insights into the structural optimization of AlGaN/GaN HFETs. Full article

The real-time, cost-effective detection of marine toxins like tetrodotoxin (TTX) remains a significant challenge for the scientific community. Traditional methods, including cell-based assays (CBAs), high-performance liquid chromatography (HPLC), and automated patch clamp (APC), are time-consuming, requiring expensive lab-based equipment and highly trained personnel. Enzyme-linked immunosorbent assays (ELISAs), lateral flow assays (LFAs), and immunosensors may not be suitable for toxin analogues. Thus, a simplified approach has been developed in this study, which involves the electrophysiological and electrochemical interrogation of N2a cells grown on ITO-coated glass electrodes by measuring extracellular field potentials (EFP) in conjunction with whole-cell patch clamp recordings and electrochemical impedance spectroscopy (EIS) measurements both before and after incubation with TTX. The ITO substrate proved biocompatible and non-toxic for N2a cells. TTX exposure caused 102% inhibition in EFP values at 300 nM, confirmed by sodium current inhibition of 93% at 300 nM and 22% at 1 nM in patch clamp studies (IC₅₀ = 6.7 nM). EIS measurements indicated concentration-dependent impedance changes in the range of 6–300 nM. This research aims to provide a proof-of-concept for integration of electrophysiological and electrochemical approaches to simplify toxin detection systems. Full article

Background/Objectives: The burden of early-onset cancer (cancer incidence <50 years) has increased globally. Early-onset cancer carries significant societal and economic consequences. We aim to provide updated estimates for incidence and mortality of early-onset cancer. Methods: We analyzed the Global Burden of Disease Study 2021 to describe the incidence, death, age-standardized incidence rate (ASIR), age-standardized death rate (ASDR) from early-onset cancer (i.e., cancer in people aged 15–49), and its changes from 2000 to 2021 (reflected as annual percent change [APC]), using Joinpoint regression analysis. Results: In 2021, there were 3.16 million new cases and 989,650 deaths from early-onset cancer. From 2000 to 2021, the ASIR of early-onset cancer increased (APC: 0.40%, 95% CI 0.32 to 0.47%), with the highest increase observed in the Eastern Mediterranean region (APC: 1.63%, 95% CI 1.53 to 1.72%), whereas the ASDR decreased across most regions. The ASIR for early-onset cancer had a higher increase in females (APC: 0.62%, 95% CI 0.51 to 0.73%) than males (APC: 0.14%, 95% CI 0.04 to 0.23%). Breast cancer (n = 567,900) constituted the highest burden of incident cases, followed by non-melanoma skin (n = 507,810) and cervical cancers (n = 307,430). The highest increase in the ASIR was observed in non-melanoma skin cancer (APC:2.18%, 95% CI 1.85–2.51%), thyroid (APC: 1.70%, 95% CI 1.60 to 1.79%), and testicular (APC:1.37%, 95% CI 0.96 to 1.78%) cancers. The greatest increases in the ASDR were observed in peripheral nervous system cancer (APC: 0.97%, 95% CI 0.82 to 1.11%) and multiple myeloma (APC: 0.62%, 95% CI 0.51 to 0.72%). Conclusions: From 2000 to 2021, the age-adjusted incidence of early-onset cancer increased, with variation across regions and cancer types. Immediate measures are required at a global, regional, and national level to mitigate the burden of early-onset cancer. Full article

Activated protein C (APC) exerts anticoagulant and cytoprotective cell signaling activities. APC’s cell signaling requires protease-activated receptor (PAR) PAR1 and PAR3, and APC’s PAR cleavages generate peptides capable of agonizing biased G-protein coupled receptor (GPCR) cytoprotective signaling, resulting in anti-inflammatory and anti-apoptotic activities and endothelial barrier stabilization. The PAR-sequence-derived 34-residue “G10 peptide” comprising PAR1 residues 47–55 covalently attached by a 10-glycine linker to PAR3 residues 51–65 is an orthosteric/allosteric bivalent GPCR agonist that potently mimics APC’s anti-inflammatory activity and endothelial barrier stabilization activity. The objective of this study was to determine whether the G10 peptide mimics APC’s anti-apoptotic activity using cultured murine neurons challenged by N-methyl-d-aspartate that provokes neuronal apoptosis. In these new studies, the G10 peptide mimicked APC’s anti-apoptotic activity. Thus, the PAR-derived 34-residue G10 peptide mimics APC’s three major cytoprotective activities, namely anti-inflammatory and anti-apoptotic activities and endothelial barrier stabilization. Peptides that agonize GPCRs provide promising and currently approved drugs; e.g., semaglutide and tirzepatide that contain 31 and 39 amino acid residues, respectively. Thus, this new study adds to the rationale for pursuing further studies of the G10 peptide for potential therapeutic value for multiple pathologies where APC or signaling-selective APC variants are therapeutic in preclinical animal studies. Full article

Exposure to high-linear energy transfer (LET) heavy ions, such as ²⁸Si, poses a significant cancer risk for astronauts. While previous studies have linked high-LET radiation exposure to persistent oxidative stress and dysregulated stress responses in intestinal crypt cells with an increased risk of tumorigenesis, the relationship between IR-induced oxidative DNA damage and intestinal cancer risk remains incompletely understood. Here, we investigated the time-dependent effects of ²⁸Si-ion radiation on intestinal tumorigenesis and oxidative DNA damage in Apc^1638N/+ mice, a model for human intestinal cancer predisposition. Male Apc^1638N/+ mice were exposed to 10 cGy of either γ-rays (low-LET) or ²⁸Si-ions (high-LET), and intestinal tumor burden was assessed at 60 and 150 days post-irradiation. While both radiation groups showed modest, non-significant tumor increases at 60 days, ²⁸Si-irradiated mice exhibited an approximately 2.5-fold increase in tumor incidence by 150 days, with a higher incidence of invasive carcinomas compared to γ and sham groups. Serum 8-OxodG levels, a marker of systemic oxidative stress, were significantly elevated in the ²⁸Si-ion group, correlating with increased intestinal 8-OxodG staining. Additionally, assessment of the proliferation marker Cyclin D1 and metaplasia marker Guanylyl Cyclase C (GUCY2C) also revealed significant crypt cell hyperproliferation accompanied by increased metaplasia in ²⁸Si-exposed mouse intestines. Positive correlations between serum 8-OxodG and tumor-associated endpoints provide compelling evidence that exposure to ²⁸Si-ions induces progressive intestinal tumorigenesis through sustained oxidative DNA damage, crypt cell hyperproliferation, and metaplastic transformation. This study provides evidence in support of the radiation quality-dependent progressive increase in systemic and intestinal levels of 8-OxodG during intestinal carcinogenesis. Moreover, the progressive increase in oxidative DNA damage and simultaneous increase in oncogenic events after ²⁸Si exposure also suggest that non-targeted effects might be a significant player in space radiation-induced intestinal cancer development. The correlation between serum 8-OxodG and oncogenic endpoints supports its potential utility as a predictive biomarker of high-LET IR-induced intestinal carcinogenesis, with implications for astronaut health risk monitoring during long-duration space missions. Full article

Colorectal cancer (CRC) remains a leading cause of cancer-related mortality worldwide, highlighting the need for a deeper understanding of the genetic mechanisms driving its development and progression. Identifying genetic mutations that affect key molecular pathways is crucial for advancing CRC diagnosis, prognosis, and treatment. Patient-derived xenograft (PDX) models are essential tools in precision medicine and preclinical research, aiding in the development of personalized therapeutic strategies. In this study, a comparative analysis was conducted on the most frequently mutated genes—APC, TP53, KRAS, BRAF, NRAS, and ERBB2—using data from publicly available databases (n = 7894) and models from University Medicine Rostock (n = 139). The aim of this study was to evaluate the accuracy of these models in reflecting the mutational landscape observed in patient-derived samples, with a focus on both individual mutations and co-occurring mutational patterns. Our comparative analysis demonstrated that while the ranking of individual mutations remained consistent, their overall frequencies were slightly lower in the PDX models. Interestingly, we observed a notably higher prevalence of BRAF mutations in the PDX cohort. When examining co-occurring mutations, TP53 and APC mutations—both individually and in combination with other alterations—were the most frequent in both datasets. While the PDX models showed a greater prevalence of single mutations and a slightly higher proportion of tumors without detectable mutations compared to the public dataset, these findings present valuable insights into CRC’s mutational landscape. The discrepancies highlight important considerations, such as selective engraftment bias favoring more aggressive tumors, differences in sample size between the two cohorts, and potential bottleneck effects during PDX engraftment. Understanding these factors can help refine the use of PDX models in CRC research, enhancing their potential for more accurate and relevant applications in precision oncology. Full article

Background/Objectives: The Brazilian Unified Health System was established in 1988 as a public health system with principles of universality, equity, and integrality. One of Brazil’s main strategies to strengthen universal healthcare is the Family Health Strategy (FHS), a primary health care policy established in 1994 and fully incorporated in the country in 2006. This study aims to describe the time trends of FHS coverage in Brazil and its states from 2008 to 2023 and to correlate this coverage with the states’ Human Development Index (HDI). Methods: Data on the number of FHS teams, population, and HDI during the period were collected for each Brazilian state in the Brazilian Ministry of Health’s public-access databases. Prais–Winsten regression was used to conduct a time series analysis for each state and country. The annual percentage change (APC) was used to describe time trends in time series. Linear regression was used to identify a correlation between HDI and FHS coverage across states. Results: The FHS coverage in the country increased from 66.81% to 84.66% from 2009 to 2023. Disparities in coverage between regions are evident throughout the entire study period. The Northeast region (NE) exhibited higher FHS coverage but lower APC rates compared to other regions. Results suggest a negative correlation between HDI and FHS coverage in all Brazilian states for 2009, 2012, 2015, 2018, 2021, and 2023. Conclusions: The FHS coverage increased in Brazil and its states during the period. The highest coverages were found in states from the North (N) and NE regions, and the lowest were in the Southeast region. Nine federative units achieved full coverage (100%) and maintained it afterward, with seven from the N and NE. A negative correlation was found between FHS and HDI, suggesting that the expansion of FHS effectively targets vulnerable populations. Full article

Background/Objectives: This population-based study examined epidemiological trends of primary cancers in adolescents and young adults (AYAs) to enhance the understanding of the specific spectrum of cancers impacting AYAs in Belgium. Methods: Data on incidence, prevalence, mortality, and survival were obtained from the Belgian Cancer Registry (2004–2020, N = 43,535). (A)APC statistics were compared with children (5–14 years) and adults (40–49 years). Results: Cancer incidence increased by 0.4% annually from 66 to 80 per 100,000 person-years (ESR2013) but stabilised after 2015, except for Hodgkin lymphoma, chronic myeloid neoplasms, and testicular and breast cancer, which continued to rise. Mortality decreased by 1% annually, from 10 to 7 per 100,000 person-years (2004–2019). Five-year relative survival (RS) was 87% but remained low for certain cancers, including ovary (78%), central nervous system (67%), precursor haematopoietic neoplasms (64%), gastrointestinal (excl. colorectal) (49%), and lung-bronchus-trachea cancers (42%). Conclusions: From 2004–2020, the cancer burden among AYAs in Belgium increased due to improved survival, while incidence stabilised after 2015. Five-year RS exceeds 80% overall but remains lower for some cancers compared to children (e.g., precursor haematopoietic neoplasms) or older adults (e.g., breast cancer, sarcoma). The Belgian epidemiological trends align with those in neighbouring countries (Netherlands, France, Germany). Full article

Objectives. The relationships among neuropathic pain, gut microbiota, microbiome-derived metabolites, and neuropathology have received increasing attention. This study examined the effects of two dosages of gingerol-enriched ginger (GEG) on mechanical hypersensitivity, anxiety-like behavior, gut microbiome composition and its metabolites, and neuropathology markers in female rats in the spinal nerve ligation (SNL) model of neuropathic pain. Methods. Forty female rats were assigned to 4 groups: sham-vehicle, SNL-vehicle, SNL+GEG at 200 mg/kg BW, and SNL+GEG at 600 mg/kg BW via oral gavage. All animals were given an AIN-93G diet for 5 weeks. Mechanical hypersensitivity was assessed by the von Frey test. Anxiety-like behavior was assessed by the open field test. Fecal microbiota composition and metabolites were determined using 16S rRNA gene sequencing and GC-MS, respectively. Neuropathology gene expression profiling of the amygdala was assessed by an nCounter^® Neuropathology pathway panel. Results. Both GEG-treated groups showed decreased mechanical hypersensitivity and anxiety-like behavior in the SNL model. Gut microbiome diversity in both GEG groups was decreased compared with untreated SNL rats. In the SNL model, phyla such as Bacteroidota, Proteobacteria and Verrucomicrobiota were decreased. Compared with the untreated SNL group, both GEG groups exhibited increased abundance of the phyla Bacteroidota (i.e., Rikenella, Alistipes, Muribaculaceae, Odoribacter), Firmicutes (i.e., UBA1819, Ruminococcaceae, Oscillospiraceae, Roseburia), and Verrucomicrobiota (i.e., Victivallis). GEG groups had higher levels of nine hydrophilic positive metabolites [val-glu, urocanic acid, oxazolidinone, L-threonine, L-norleucine, indole, imino-tryptophan, 2,3-octadiene-5,7-diyn-1-ol, and (2E)-3-(3-hydroxyphenyl) acrylaldehyde] and two hydrophilic negative metabolites [methylmalonic acid and metaphosphoric acid], as well as lower levels of five hydrophilic metabolites [xanthine, N-acetylmuramic acid, doxaprost, adenine, and 1-myristoyl-2-oleoyl-sn-glycero-3-phosphoethanolamine]. Among the 770 neuropathology genes, 1 gene (PLA2G4A) was upregulated and 2 genes (CDK5R1 and SHH) were downregulated in SNL rats. GEG caused the upregulation of nine genes (APC, CCNH, EFNA5, GRN, HEXB, ITPR1, PCSK2, TAF9, and WFS1) and downregulation of three genes (AVP, C4A, and TSPO) in the amygdala. Conclusions. GEG supplementation mitigated pain-associated behaviors in female rats with neuropathic pain, in part by reversing the molecular neuropathology signature of the amygdala. This was associated with changes in the gut microbiome composition and fecal metabolites, which could play a role in mediating the effects of GEG on neuropathic pain. Full article

Background: While unhealthy dietary trends, such as elevated confectionery consumption and decreased fruit intake, have been documented in adults, the longitudinal patterns of food consumption during childhood remain inadequately characterized. This study aimed to describe national trends in food group intakes among children and adolescents in Japan. Methods: Data on participants aged 1–19 years in the National Health and Nutrition Survey from 2001 to 2019 (n = 37,072) were used in this study. A 1-day, semi-weighed, household-based dietary record was used to assess dietary intake. Results: Decreasing trends in the intakes of animal-based foods, potatoes and starches, sugars and sweeteners, fruits (annual percentage change [APC] range: −5.04 to −0.62), algae, fish and shellfish (APC range: −3.22 to −2.02), eggs, milks, fats and oils, and confectionery were observed, while intakes of meats (APC range: 1.02 to 1.92) and beverages (APC range: 1.36 to 2.51) increased. Consumption of plant-based foods, cereals, legumes, nuts and seeds, vegetables, and mushrooms was mostly unchanged, whereas variable intakes of seasonings and spices were observed. Conclusions: This study showed that the intakes of many food groups (e.g., fruits, fish and shellfish, and milk) decreased among children and adolescents, but some increased (e.g., meats and beverages) or remained stable (e.g., cereals and vegetables). Further evidence is needed to enable policymakers to set target interventions to improve children’s diets. Full article