Search Results (176)

Multi-energy coupled low-carbon distribution networks (MEC-LCDNs) face growing risks from extreme weather and high-order contingencies. Traditional deterministic criteria (e.g., N-1) often overlook these low-probability, high-impact events, while existing simulation-based probabilistic methods suffer from excessive computational burdens and a lack of intuitive visualization. To address these challenges, this paper proposes an explicit representation method for MEC-LCDN operational reliability constraints based on the probabilistic reliability region (PRR). This approach transforms the abstract probabilistic reliability criterion—loss of load probability (LOLP)—into a visualizable geometric space. Specifically, a fast contingency screening technique (FCST) is developed to identify a minimal set of boundary scenarios that anchor the target reliability threshold. Subsequently, complex probabilistic constraints are decoupled into deterministic N-k security constraints under these boundary scenarios, enabling the analytical construction of the PRR boundary. A case study demonstrates that the proposed method reduces the number of required contingency scenarios by over 90% and slashes computation time from 78.8 s to 3.1 s compared to traditional N-k truncation methods. Furthermore, the method accurately quantifies the system’s total supply capability (TSC) at 44.501 MW while providing intuitive visualizations of reliability boundaries that satisfy stringent LOLP criterion. Full article

We herein demonstrate that the thiosemicarbazone (TSC) ligand N′-(di(pyridin-2-yl)methylene)-4-(thiazol-2-yl)piperazine-1-carbothiohydrazide (HL) can coordinate with Ga³⁺ to give cationic complex [Ga(L)₂]NO₃ featuring an octahedral Ga(III) center. [Ga(L)₂]NO₃ undergoes metathesis with both Fe²⁺ and Fe³⁺, resulting in the formation of respective Fe²⁺- and Fe³⁺ complexes. [Ga(L)₂]NO₃ is also susceptible to anion exchange with sodium hyaluronate (NaA) to produce the nanoformulation [Ga(L)₂]A with boosted aqueous solubility and cell targeting. [Ga(L)₂]A demonstrated remarkable in vitro cytotoxicity against NCI-H82 and A549 (lung cancer), as well as KYSE-510 and Te-1 (esophageal cancer) cell lines, featuring half maximal inhibitory concentration (IC₅₀) values in the range 0.102–2.616 μmol L⁻¹. This work highlights the potential of using non-toxic and biocompatible Ga³⁺ as the central ion to prepare TSC-based nanomedicines for combating cancer. Full article

Thiosemicarbazones are known for their versatile coordination behavior and wide-ranging applications in the field of materials science, catalysis, and medicinal chemistry. Several investigations have reported on the biological potential of transition metal complexes of TSCs. In addition, the structural, electronic, and reactive properties of these complexes are explored through computational studies using molecular docking and density functional theory (DFT). Such investigations not only support the interpretation of experimental results but also influence synthetic design by predicting the structural behavior of the complexes. In this study, we explore the computational studies of thiosemicarbazone metal complexes along with their biological activities. Full article

Background: In melanoma diagnostics key molecular markers, such as BRAF, NRAS, and KIT mutations also paved the way for targeted therapies. Immunotherapies, including immune checkpoint inhibitors like anti-CTLA-4 and anti-PD-1/PD-L1, have revolutionized treatment, improving survival outcomes for advanced-stage melanoma patients. Despite these advances, challenges such as resistance to targeted therapies and variability in patient responses to immunotherapy remain critical issues. The purpose of the project is to characterize the molecular landscape of a set of 28 malignant melanomas using next-generation sequencing, identify the prevalence and nature of class 3–5 variants (e.g., NRAS, BRAF, KIT, TP53), assess the genetic complexity and molecular patterns, and use these insights to inform personalized therapies and optimize patient stratification for potential combination strategies (targeted therapy followed by immunotherapy). Methods: We analyzed a set of malignant melanoma of the skin of 17 women (61%) and 11 men (39%) at the age of 23 to 85 years (median: 63 years) by tumor-only next generation sequencing. Results: 22/28 cases (79%) present a pathogenic or likely pathogenic variant with an allelic frequency of ≥5%. In total 42 distinct somatic pathogenic or likely pathogenic variants with an allelic frequency of ≥5% could be detected. The most frequent pathogenic molecular alteration in these melanomas were found in NRAS (25%) and BRAF (25%). The most frequent molecular alteration of unknown significance was found in FANDC2 (46%), NOTCH3 (39%), ARID1A (32%), PMS2 (32%), POLE (29%), NOTCH1 (29%), TSC2 (25%), SMARCA4 (25%), ATR (25%) and TERT (21%). Conclusions: While NRAS and BRAF were the most frequent actionable alterations (each 25%), a broad spectrum of variants of unknown significance (e.g., FANDC2, NOTCH3, ARID1A, PMS2, POLE, NOTCH1, TSC2, SMARCA4, ATR and TERT) also predominates, underscoring the genetic complexity of melanoma. These variants complicate clinical decision-making because their contribution to tumorigenesis, therapeutic response, and prognosis remains uncertain. Nevertheless, these variants also offer a valuable resource for future research, as they may uncover novel pathogenic mechanisms or therapeutic targets once their significance is elucidated. Integrating comprehensive genetic profiling with immunologic markers can enhance patient stratification and support rational, potentially synergistic strategies, such as combining targeted therapies with immunotherapy, to optimize clinical outcomes. This study is limited due to a small cohort and limited available clinical data. Larger cohort studies and prospective clinical trials are necessary to validate and explore the interplay between molecular and immune biomarkers as well as general biological mechanism in paving therapeutic way in melanoma. Full article

This study investigates the synthesis and potential applications of the coordination compound cobalt(III) complex tris[N-(prop-2-en-1-yl)hydrazinecarbothioamide]-cobalt(III) chloride ([Co(Tsc)₃]Cl₃). The complex has been synthesized via the reaction of cobalt(II) chloride hexahydrate with N-(prop-2-en-1-yl)hydrazinecarbothioamide in ethanol. Its antioxidant activity has been evaluated using 2,2′-azinobis-(3-ethylbenzothiazoline-6-sulfonic acid (ABTS) assay, demonstrating a significant effect with an IC₅₀ of 7.3 µmol/L. Toxicity evaluations using Daphnia magna showed a low half maximal inhibitory concentration (LC₅₀) of 56.3 µmol/L. Experimental results have showed that [Co(Tsc)₃]Cl₃ significantly elevated the total antioxidant status (TAS) of the hemolymph of honeybees and larvae, increasing it by 5 and 8 times, respectively. The IC₅₀ values for antioxidant activity were 2.5 mg/mL in bee hemolymph and 1.3 mg/mL in larval hemolymph, notably lower than control values of 13.6 mg/mL and 10.0 mg/mL. The stimulatory effect of the coordination compound [Co(Tsc)₃]Cl₃ on TAS was five times higher than that of vitamin C. Additionally, [Co(Tsc)₃]Cl₃ exhibited acaricidal properties, effectively inhibiting Varroa destructor with an lethal concentration (LC₅₀) of 0.2 µmol/L. These findings indicate that this cobalt complex could serve both a natural antioxidant and an effective acaricide, offering a promising approach to improv bee health and sustainability in apiculture. Full article

Uterine mesenchymal tumors encompass a diverse and diagnostically challenging group of neoplasms, including smooth muscle tumors, endometrial stromal tumors (ESS), perivascular epithelioid cell tumors (PEComas), inflammatory myofibroblastic tumors (IMTs), uterine tumor resembling ovarian sex cord tumor (UTROSCT), along with many other relatively rare entities. Traditionally classified by histomorphology and immunophenotype, these tumors are now increasingly defined by recurrent genetic alterations that refine diagnosis and elucidate tumorigenesis. For example, leiomyosarcomas display complex genomic instability with frequent TP53, RB1, and ATRX mutations. Low grade-ESS are characterized by JAZF1::SUZ12 and other related fusions, whereas high-grade tumors harbor YWHAE::NUTM2 or ZC3H7B::BCOR fusions, and BCOR internal tandem duplication (ITD) alterations. PEComas frequently contain TSC1 or TSC2 mutations, leading to aberrant activation of the mTOR pathway. Beyond their diagnostic utility, these molecular signatures increasingly inform prognosis and highlight potential therapeutic targets, including CDK4/6 inhibition, PI3K/AKT/mTOR blockade, and immunotherapy. This review summarizes the evolving molecular landscape of uterine mesenchymal tumors, underscoring the value of integrating molecular testing into clinical practice to enhance diagnostic precision and enable personalized management of these rare yet clinically significant neoplasms. Full article

Purpose: This study proposes a novel magnetic resonance (MRI)-based classification of cortical tubers (CTs) in tuberous sclerosis complex (TSC) patients that incorporates intralesional calcifications. We evaluated prevalence, temporal evolution, and genotype correlation of intra-tuberal calcifications in pediatric TSC patients, emphasizing susceptibility-weighted imaging (SWI) for detection. Materials and Methods: We retrospectively analyzed MRI scans of 57 unrelated pediatric TSC patients followed between 2014 and 2024 at a tertiary care center. Inclusion criteria included longitudinal imaging on the same 1.5T scanner, with T1w, T2w/FLAIR, and SWI sequences. CTs were classified into four MRI-based categories (A–D), with calcified tubers subdivided into micro-calcified and macro-calcified. Descriptive statistics, binomial tests, and Chi-square analyses were performed. Results: Calcified CTs were more prevalent than cystic ones. At baseline MRI, 63% of patients had calcified tubers (19% of all CTs), increasing to 77% at follow-up MRI (24% of all CTs). Micro-calcifications predominated at baseline MRI evaluation, though a significant proportion progressed to macro-calcifications over time. Calcified CTs always progressed from lower-grade lesions. Cystic tubers were rare (<1%). Longitudinal analysis showed significant variation in CTs with inner calcification count (p = 0.0000023), but not in CTs with cystic components (p = 0.42072). No significant genotype–radiological phenotype association emerged. Conclusions: Intralesional calcifications in CTs are dynamic and detectable with SWI. The inclusion of calcification patterns in CT classification could offer insights that may prove useful for future prognostic and risk-stratification frameworks in pediatric TSC. Full article

Transmetalation, the exchange of metal ions between coordination complexes and biomolecules, has emerged as a powerful design lever in cancer metallopharmacology. Using thiosemicarbazones (TSCs) as a unifying case study, we show how redox-inert carrier states such as zinc(II) or gallium(III) can convert in situ into redox-active copper(II) or iron(III/II) complexes within acidic, metal-rich lysosomes. This conditional activation localizes reactive oxygen species (ROS) generation and iron deprivation to tumor cells. We critically compare redox-active and redox-inert states, delineating how steric and electronic tuning, backbone rigidity, and sulfur-to-selenium substitution govern exchange hierarchies and kinetics. We further map downstream consequences for metal trafficking, lysosomal membrane permeabilization, apoptosis, and ferroptosis. Beyond TSCs, iron(III)-targeted transmetalation from titanium(IV)-chelator “chemical transferrin mimetics” illustrates a generalizable Trojan horse paradigm. We conclude with translational lessons, including mitigation of hemoprotein oxidation via steric shielding, stealth zinc(II) prodrugs, and dual-chelator architectures and outline biomarker, formulation, and imaging strategies that de-risk clinical development. Collectively, these insights establish transmetalation as a central therapeutic principle. We also highlight open challenges such as quantifying in-cell exchange kinetics, predicting speciation under non-equilibrium conditions, and rationally combining these agents with existing therapies. Full article

RSCD faces persistent challenges in high-resolution imagery due to complex spatial structures, temporal heterogeneity, and semantic ambiguity. While deep learning methods have significantly advanced the field, most existing models still rely on static and homogeneous processing, treating all channels and modalities equally, which limits their capacity to capture fine-grained semantic shifts or adapt to region-dependent variations. To address these issues, we propose SynerCD, a unified Siamese encoder–decoder framework that introduces dynamic, content-adaptive perception through channel decoupling, frequency-domain enhancement, and vision-language collaboration. The encoder employs a Tri-branch Synergistic Coupling (TSC) module that dynamically rebalances channel responses and captures multi-scale spatial-frequency dependencies via Mamba-based long-sequence modeling and wavelet decomposition. The decoder integrates a vision-aware language-guided attention (VAL-Att) module, which adaptively modulates visual-textual fusion using CLIP-based semantic prompts to guide attention toward meaningful change regions. Extensive experiments on four benchmark datasets verify that SynerCD achieves superior localization accuracy and semantic robustness, establishing a dynamic and adaptive paradigm for multimodal change detection. Full article

The precise reconstruction of target scattering centers (TSCs) using sensors plays a crucial role in feature extraction and identification of non-cooperative targets. Radar sensor networks (RSNs) are well suited for this task, as they are capable of illuminating targets from multiple aspect angles and rapidly capturing reflected signals. However, the complex geometry and diverse material composition of real-world targets result in significant variations in the radar cross-section (RCS) observed at different angles. Although these RCS responses are interrelated, they exhibit considerable angular diversity. Furthermore, achieving precise spatiotemporal registration and fully coherent processing is infeasible for RSNs composed of small mobile sensor platforms, such as drone swarms. Therefore, an intelligent algorithm is required to extract and accumulate correlated and meaningful information from the target echoes received by the RSN. In this work, a novel collaborative TSC reconstruction framework for RSNs is proposed. The framework performs similarity evaluation on wide-angle high-resolution range profiles (HRRPs) to achieve adaptive angular segmentation of TSC models. It combines the expectation–maximization (EM) algorithm with an enhanced Arctic puffin optimization (EAPO) algorithm to effectively integrate echo information from the RSN in a non-coherent manner, thereby enabling accurate TSC estimation. The proposed method outperforms existing mainstream approaches in terms of spatiotemporal registration requirements, estimation accuracy, and stability. Comparative experiments on measured datasets demonstrate the robustness of the framework and its adaptability to complex target scattering characteristics, confirming its practical value. Full article

Background: Tuberous sclerosis complex (TSC) is a rare genetic disorder characterized by the growth of benign tumors in various organ systems, with particularly significant effects on the kidneys. Renal manifestations of TSC include angiomyolipomas (AMLs), renal cysts, and a higher risk of renal cell carcinoma (RCC). Nephrological monitoring is crucial for the early detection of kidney changes, the management of hypertension, and the assessment of the risk of developing chronic kidney disease. Ultrasound is typically the initial imaging choice for diagnosis and monitoring, with magnetic resonance imaging (MRI) being a preferred imaging modality for long-term surveillance. Patients with TSC have an increased risk of arterial hypertension, renal artery stenosis, and urolithiasis. In some patients, the co-occurrence of TSC and autosomal dominant polycystic kidney disease (ADPKD) is caused by the TSC2/PKD1 contiguous gene syndrome (CGS). The primary medical treatment for TSC is a mammalian target of rapamycin kinase inhibitors (mTOR), as they effectively shrink tumors, often reducing or eliminating the need for surgical intervention. Methods: This article aims to review the most recent literature on the diagnosis and management of renal lesions in tuberous sclerosis complex (TSC), with a particular focus on the role of various imaging techniques. Conclusions: Given the multifactorial nature of this disease, this review emphasizes the importance of a multidisciplinary approach, including various imaging methods, to improve the care and treatment outcomes of children with tuberous sclerosis complex. Full article

Background: Cortical tubers (CTs) are hallmark brain lesions in tuberous sclerosis complex (TSC), historically considered stable in number over time; prior literature has correlated overall CT burden on magnetic resonance imaging (MRI) with disease severity. As longitudinal imaging studies assessing CTs’ evolution over time are lacking, we aim to investigate temporal changes in CTs—both in number and signal—on MRI in a cohort of pediatric TSC patients. Methods: A retrospective single-center analysis was conducted on 57 pediatric TSC patients who underwent longitudinal MRI studies in a 10-year span. Required MRI sequences included volumetric unenhanced T1-weighted, SWI, T2w and/or FLAIR. CTs were evaluated by two neuroradiologists and classified into five subtypes (A, B, C1, C2, D) according to signal characteristics. Statistical comparison was performed using t-tests. Results: Paired t-test analysis demonstrated a significant longitudinal increase in the overall number of CTs, rising from 16.11 ± 12.43 at baseline to 18.77 ± 13.29 at follow-up (mean difference = −2.67, 95% CI [−3.94, −1.39]; t (56) = 4.19; p < 0.0001), corresponding to a moderate effect size (Cohen’s d ≈ 0.56). When stratified by age, patients <2 years—representing the incompletely myelinated subgroup—showed a more pronounced increase in CT burden, from 19.46 ± 15.21 to 24.17 ± 15.75 (mean difference = −4.71, 95% CI [−7.37, −2.04]; t (23) = 3.65; p = 0.0013; d ≈ 0.75). In contrast, patients aged ≥2 years demonstrated a smaller but still significant increase, from 13.67 ± 9.45 to 14.85 ± 9.64 (mean difference = −1.18, 95% CI [−2.08, −0.28]; t (32) = 2.68; p = 0.0115; d ≈ 0.46). Direct comparison between the two subgroups using Welch’s two-sample t-test confirmed that the mean CT count in patients <2 years was significantly higher than in those ≥2 years (mean difference = 3.53 ± 1.36; t = 2.59; df = 28.4; p = 0.0075), with a large effect size (Cohen’s d ≈ 0.78). Type C1-C2 tubers evolved from pre-existing earlier-stage lesions, while most newly visible CTs over time were type A-B. Type D tubers remained rare and derived from earlier-stage CTs. Conclusions: Contrary to previous assumptions, CTs in pediatric TSC showed a tendency to increase in number and evolve in signal over time, thus challenging the notion of stability and suggesting dynamic behavior. Incomplete myelination in early infancy may impact MRI CTs detection by reducing contrast with surrounding brain tissue, potentially leading to their underestimation/misidentification. Full article

The increasing complexity of urban traffic networks has highlighted the potential of Multi-Agent Reinforcement Learning (MARL) for Traffic Signal Control (TSC). However, most existing MARL methods assume homogeneous observation and action spaces among agents, ignoring the inherent heterogeneity of real-world intersections in topology and signal phasing, which limits their practical applicability. To address this gap, we propose HAPS-PPO (Heterogeneity-Aware Policy Sharing Proximal Policy Optimization), a novel MARL framework for coordinated signal control in heterogeneous road networks. HAPS-PPO integrates two key mechanisms: an Observation Padding Wrapper (OPW) that standardizes varying observation dimensions, and a Dynamic Multi-Strategy Grouping Learning (DMSGL) mechanism that trains dedicated policy heads for agent groups with distinct action spaces, enabling adequate knowledge sharing while maintaining structural correctness. Comprehensive experiments in a high-fidelity simulation environment based on a real-world road network demonstrate that HAPS-PPO significantly outperforms Fixed-time control and mainstream MARL baselines (e.g., MADQN, FMA2C), reducing average delay time by up to 44.74% and average waiting time by 59.60%. This work provides a scalable and plug-and-play solution for deploying MARL in realistic, heterogeneous traffic networks. Full article

This paper proposes an innovative hybrid optimization framework for the optimal installation and operation of thyristor-switched capacitors (TSCs) within medium-voltage distribution networks, targeting both energy losses reduction and cost efficiency. The core of the approach combines the exploratory capabilities of the atan-sinc optimization algorithm (ASOA), a recent metaheuristic inspired by mathematical functions, with the local refinement power of the IPOPT solver within a master–slave architecture. This integrated method addresses the inherent complexity of a multi-objective, mixed-integer nonlinear programming problem that seeks to balance conflicting goals: minimizing annual system losses and investment costs. Extensive testing on IEEE 33- and 69-bus systems under fixed and dynamic reactive power injection scenarios demonstrates that our framework consistently delivers superior solutions when compared to traditional and state-of-the-art algorithms. Notably, the variable operation case yields energy savings of up to 12%, translating into annual monetary gains exceeding USD 1000 in comparison with the fixed support scenario.The solutions produce well-distributed Pareto fronts that illustrate valuable trade-offs, allowing system planners to make informed decisions. The findings confirm that the proposed strategy constitutes a scalable, and robust tool for reactive power planning, supporting the deployment of smarter and more resilient distribution systems. Full article

Autism spectrum disorder (ASD) is a heritable neurodevelopmental condition with a complex genetic architecture. Dissecting the interplay between inherited variants and high-impact de novo variants is critical for understanding its etiology. We conducted a family-based study involving 42 families with ASD (139 individuals). Using a targeted next-generation sequencing (NGS) panel of 236 genes, we identified and characterized rare inherited and de novo variants in affected probands, parents, and unaffected siblings. Our analysis revealed a complex genetic landscape marked by diverse inheritance patterns. De novo variants were predominantly observed in individuals with atypical autism, while biparental (homozygous) inheritance was more common in Asperger syndrome. Maternally inherited variants showed significant enrichment in intronic regions, pointing to a potential regulatory role. We also detected variants in several high-confidence ASD risk genes, including SHANK3, MYT1L, MCPH1, NIPBL, and TSC2, converging on pathways central to synaptic function and neurogenesis. Across the cohort, five variants of uncertain significance (VUS) were identified, comprising two inherited variants in ABCC8 and additional variants in CUL23, TSC2, and MCPH1. Our findings underscore the profound genetic heterogeneity of ASD and suggest that distinct genetic mechanisms and inheritance patterns may contribute to different clinical presentations within the spectrum. This highlights the power of family-based genomic analyses in elucidating the complex interplay of inherited and de novo variants that underlies ASD. Full article