Search Results (162)

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

Background: Developmental and Epileptic Encephalopathy (DEE) is a severe and heterogeneous neurological disorder in infancy/early childhood. DEE’s genetic and phenotypic variability complicates diagnosis and treatment. This retrospective study aimed to identify genetic variants and explore genotype–phenotype correlations in children with DEE using a targeted epilepsy gene panel (TGP) and Whole Exome Sequencing (WES). Patients and Methods: Medical records of children who underwent custom-designed 55-gene TGP and WES were reviewed. The diagnostic yield of each method was determined based on the detection of pathogenic (P) and likely pathogenic (LP) variants. Results: A total of 129 patients (66 males, 63 females) underwent TGP, which identified P/LP variants in 29 cases (22.48%). Variants were detected in SCN1A, KCNQ2, STXBP1, CDKL5, PCDH19, PLCB1, WWOX, SCN2A, FGF12, HCN1, SCN8A, and SLC35A2. WES further identified several variants in children with West syndrome. A TSC1 variant was detected in a patient without cutaneous stigmata of tuberous sclerosis complex. The NALCN variant in a patient was linked to Infantile Hypotonia with Psychomotor Retardation and Characteristic Facies 1. A CTBP1 variant associated with extremely rare Hypotonia, Ataxia, Developmental Delay, and Tooth Enamel Defect Syndrome was detected in another patient. A PIEZO2 variant—associated with Marden–Walker syndrome—was found in a child with Early Infantile Developmental and Epileptic Encephalopathy. Conclusions: These findings highlight the extensive genetic heterogeneity and phenotypic variability of DEE. WES demonstrates substantial value in identifying novel gene-disease associations and may be considered as a first-tier diagnostic tool in epilepsy and DEE. Full article

The practical application of transparent supercapacitors (TSCs) is limited by the inherent trade-off between transparency and conductivity, as well as the environmental and economic drawbacks of electrode materials. This study presents a novel and scalable method for fabricating porous carbon-modified silk-derived carbon fiber meshes as electrode materials for transparent supercapacitors. The process involves the in situ growth of a cobalt organic complex on a silk mesh, followed by carbonization to produce a flexible, transparent carbon fiber mesh with a hierarchical porous structure (specific surface area: 570 m²/g). The resulting material exhibits good mechanical properties and electrical conductivity due to the nanographene-like structure formed during the cobalt-catalyzed carbonization process. This TSC achieves an optical transparency of up to 65% and an aerial capacitance of 9.65 mF/cm² at a scan rate of 0.01 V/s, surpassing many existing transparent electrodes. Additionally, the device demonstrates outstanding electrochemical stability, retaining 89% of its initial capacitance after 2000 cycles at a scan rate of 0.5 V/s, showcasing superior durability. This study presents a pioneering method for developing TSCs by utilizing sustainable silk-derived carbon materials and a cost-effective fabrication process. Full article

Top-bottom combined blowing converter steelmaking involves complex thermodynamic and kinetic processes, and predictive modeling has long been a key focus in steelmaking research. This paper proposes a kinetic process prediction model with on-site applicability. Based on actual production data, machine learning models (BP neural network, random forest, XGBoost) are employed to predict Tapping Steel Oxygen (TSO) content, which is then used as input for the kinetic model. An optimized theoretical decarburization kinetic model is selected and validated against measured Tapping Steel Carbon (TSC) data. The key innovation lies in the integration of converter control parameters into the kinetic model through a data-driven cyclic iteration algorithm. Comparison of prediction accuracy before and after integration shows that the model’s TSC prediction within the range [−0.2, +0.2] improves by 6.26%. This work presents a novel approach for enhancing kinetic models via control parameter integration, offering effective guidance for real-time monitoring and optimization in converter steelmaking. Full article

Background: Toxoplasma gondii is a globally widespread parasite responsible for toxoplasmosis, a zoonotic disease with significant impact on both human and animal health. The current lack of safe and effective treatments underscores the need for new drugs. Earlier, thiosemicarbazones (TSCs) and their metal complexes have shown promising activities against T. gondii. This study evaluated a gold (III) complex C3 and its TSC ligand C4 for safety in host immune cells and zebrafish embryos, followed by efficacy assessment in a murine model for chronic toxoplasmosis. Methods: The effects on viability and proliferation of murine splenocytes were determined using Alamar Blue assay and BrdU ELISA, and potential effects of the drugs on zebrafish (Danio rerio) embryos were detected through daily light microscopical inspection within the first 96 h of embryo development. The parasite burden in treated versus non-treated mice was measured by quantitative real-time PCR in the brain, eyes and the heart. Results: Neither compound showed immunosuppressive effects on the host immune cells but displayed dose-dependent toxicity on early zebrafish embryo development, suggesting that these compounds should not be applied in pregnant animals. In the murine model of chronic toxoplasmosis, C4 treatment significantly reduced the parasite load in the heart but not in the brain or eyes, while C3 did not have any impact on the parasite load. Conclusions: These results highlight the potential of C4 for further exploration but also the limitations of current approaches in effectively reducing parasite burden in vivo. Full article

In industrial systems, sensors often classify collected time series data for incipient fault diagnosis. However, time series data from sensors during the initial stages of a fault often exhibits minor fluctuation characteristics. Existing time series classification (TSC) methods struggle to achieve high classification accuracy when these minor fluctuations serve as the primary distinguishing feature. This limitation arises because the low-amplitude variations of these fluctuations, compared with trends, lead the classifier to prioritize and learn trend features while ignoring the minor fluctuations crucial for accurate classification. To address this challenge, this paper proposes a novel graph-based time series classification framework, termed MFSI-TSC. MFSI-TSC first extracts the trend component of the raw time series. Subsequently, both the trend series and the raw series are represented as graphs by extracting the “visible relationship” of the series. By performing a subtraction operation between these graphs, the framework isolates the differential information arising from the minor fluctuations. The subtracted graph effectively captures minor fluctuations by highlighting topological variations, thereby making them more distinguishable. Furthermore, the framework incorporates optimizations to reduce computational complexity, facilitating its deployment in resource-constrained sensor systems. Finally, empirical evaluation of MFSI-TSC on both real-world and publicly available datasets demonstrates its effectiveness. Compared with ten benchmark methods, MFSI-TSC exhibits both high accuracy and computational efficiency, making it more suitable for deployment in sensor systems to complete incipient fault detection tasks. Full article

Tuberous sclerosis complex (TSC) is a systemic disease caused by mutations in either the TSC1 (encoding hamartin) or TSC2 (encoding tuberin) gene, with mutations in the TSC2 gene potentially leading to more severe clinical symptoms. Neurological symptoms are a common clinical manifestation of TSC, and neuroinflammation is thought to play an important role. Glial cells are a major source of neuroinflammation, but whether microglia are involved in the activation of the NOD-like receptor protein 3 (NLRP3) inflammasome and the expression of interleukin-1β (IL-1β) in TSC patients remains unclear. We used a transcriptome sequencing dataset for bioinformatics analysis to explore the differences in the expression of microglial inflammasome-associated hub genes. TSC2 knockdown (TSC2 KD) microglia (HMC3 cell line) were generated by lentivirus, and the expression of inflammasome-associated hub genes, microglial activation, and NLRP3 inflammasome activation were verified. In addition, experiments were performed to explore the regulatory effects of rapamycin. Bioinformatics analysis identified a total of eight inflammasome-associated hub genes. By detecting GFP fluorescence, TSC2 mRNA, TSC2 protein expression, and the phosphorylation of the mammalian target of rapamycin (p-mTOR)/mTOR, we confirmed that the TSC2 KD microglia model was successfully established. Compared with the control group, the TSC2 KD group presented higher mRNA levels and fluorescence intensities of microglia AIF1 and CD68, as well as greater reactive oxygen species (ROS) production. Eight inflammasome-associated hub gene mRNA assays revealed that the expression of the NLRP3 and IL1B genes was increased. Compared with the control group, the TSC2 KD group presented increased levels of NLRP3 and Pro-IL-1β proteins in cells and Cleaved-Caspase 1 and Cleaved-IL-1β proteins in the supernatant, suggesting NLRP3 inflammasome activation. Rapamycin intervention alleviated these changes, demonstrating that the TSC2 gene regulation of microglial activation and NLRP3 inflammasome activation are correlated with mTOR phosphorylation. In conclusion, microglia are activated in TSC patients and participate in the NLRP3 inflammasome-associated neuroinflammatory response, and rapamycin treatment can alleviate these changes. Full article

Background and Clinical Significance: Tuberous sclerosis complex (TSC) is an autosomal dominant disorder caused by pathogenic variants in TSC1 or TSC2. Cardiac rhabdomyoma is a common prenatal finding and can be associated with severe complications, including pericardial effusion. We administered prenatal sirolimus to mitigate pericardial effusion, which led to postnatal complications. Case Presentation: A 28-year-old pregnant woman with no significant family history underwent routine fetal ultrasound at 28.1 weeks of gestation, which identified a large right ventricular mass consistent with rhabdomyoma. Further fetal brain MRI revealed cortical-subcortical tubers and subependymal nodules, leading to a clinical diagnosis of TSC. At 30.4 weeks, oral sirolimus (3 mg/day) was started due to the significant pericardial effusion. The effusion remained after treatment, requiring pericardiocentesis at 33.6 weeks. The sirolimus dosage was raised to 6 mg/day at 35.6 weeks, reaching a plasma level of 3.76 ng/mL, but there was no discernible improvement because of the continued fluid accumulation. The mother did not experience any adverse side effects from the procedure. Genetic testing confirmed a pathogenic variant in TSC2 (c.1372C>T). After birth, the neonate received a single dose of sirolimus but subsequently developed necrotizing enterocolitis (NEC), highlighting the potential adverse effects and the need for cautious consideration of treatment options. Conclusions: This case illustrates the complexities of managing prenatal tuberous sclerosis complex (TSC). While sirolimus has been explored for fetal cardiac rhabdomyoma and associated complications, its effectiveness in resolving pericardial effusion remains uncertain. Additionally, the development of NEC postnatally raises concerns about the safety of mTOR inhibitors in this context. Further studies are necessary to assess the risks and benefits of this approach in fetal therapy. Full article

Background/Objectives: Current developments in computer-aided systems rely heavily on complex and computationally intensive algorithms. However, even a simple approach can offer a promising solution to reduce the burden on clinicians. Addressing this, we aim to employ unsupervised cluster analysis to identify prognostic subgroups of non-small-cell lung cancer (NSCLC) patients with brain metastasis (BM). Simple-yet-effective algorithms designed to identify similar group characteristics will assist clinicians in categorizing patients effectively. Methods: We retrospectively collected data from 95 NSCLC patients with BM treated at two oncology centers. To identify clinically distinct subgroups, two types of unsupervised clustering methods—two-step clustering (TSC) and hierarchical cluster analysis (HCA)—were applied to the baseline clinical data. Patients were categorized into prognostic classes according to the Diagnosis-Specific Graded Prognostic Assessment (DS-GPA). Survival curves for the clusters and DS-GPA classes were generated using Kaplan–Meier analysis, and the differences were assessed with the log-rank test. The discriminative ability of three categorical variables on survival was compared using the concordance index (C-index). Results: The mean age of the patients was 61.8 ± 0.9 years, and the majority (77.9%) were men. Extracranial metastasis was present in 71.6% of the patients, with most (63.2%) having a single BM. The DS-GPA classification significantly divided the patients into prognostic classes (p < 0.001). Furthermore, statistical significance was observed between clusters created by TSC (p < 0.001) and HCA (p < 0.001). HCA showed the highest discriminatory power (C-index = 0.721), followed by the DS-GPA (C-index = 0.709) and TSC (C-index = 0.650). Conclusions: Our findings demonstrated that the TSC and HCA models were comparable in prognostic performance to the DS-GPA index in NSCLC patients with BM. These results suggest that unsupervised clustering may offer a data-driven perspective on patient stratification, though further validation is needed to clarify its role in prognostic modeling. Full article

Gynecologic perivascular epithelioid cell tumors (PEComas) are rare mesenchymal neoplasms characterized by the co-expression of melanocytic markers (HMB-45 and Melan-A) and smooth muscle markers (SMA, desmin, and caldesmon). The uterus is the most common organ affected, with approximately 110 cases reported worldwide, while occurrences in the cervix, vagina, ovary, and other gynecologic locations are exceptionally rare. These tumors typically present with nonspecific symptoms such as abnormal uterine bleeding and pelvic pain, often mimicking other uterine neoplasms. Histopathologically, PEComas exhibit epithelioid and spindle cell morphology with variable nuclear atypia, mitotic activity, and characteristic immunohistochemical profiles. Although most PEComas behave benignly, a subset demonstrates malignant potential, associated with larger tumor sizes, an increased mitotic index, necrosis, and vascular invasion; however, standardized diagnostic criteria remain scarce. Molecular alterations frequently involve the mTOR signaling pathway through tuberous sclerosis complex (TSC) 1 and TSC2 gene mutations, offering potential targets for therapy. Surgical resection with clear margins remains the cornerstone of treatment. For advanced or metastatic cases, mTOR inhibitors have shown promising efficacy, whereas the role of radiotherapy remains uncertain. This review aims to synthesize current knowledge regarding the epidemiology, clinical presentation, histologic features, malignant potential, and treatment of uterine PEComas, emphasizing the importance of accurate histopathological classification and molecular profiling to guide individualized therapeutic strategies. Full article

Background/Objectives: Cancer remains a major global health challenge, driving the search for novel chemotherapeutic agents. This study aimed to evaluate the structural and biological properties of a series of Pd(II) complexes containing triphenylphosphine and thiosemicarbazone ligands, in order to assess their potential as anticancer agents. Methods: Six Pd(II) complexes with the general formula [PdCl(PPh₃)(TSC)] were synthesized and fully characterized by NMR (¹H, ¹³C, ³¹P), FTIR, mass spectrometry, and X-ray diffraction. Their cytotoxic effects were investigated through in vitro assays using 2D and 3D cancer cell models, including clonogenic, wound healing, cell cycle, and apoptosis assays via flow cytometry. Results: Complexes from the B family demonstrated significantly higher cytotoxicity than those from the C family, particularly against ovarian (IC₅₀ < 1 µM) and breast (IC₅₀~2 µM) cancer cell lines. These compounds exhibited superior potency and selectivity compared to cisplatin, with high selectivity indices toward non-tumor cells. Mechanistic studies revealed both cytotoxic and cytostatic effects depending on structural variations, with apoptosis identified as the primary mechanism of cell death. PdB1, in particular, induced a marked increase in late apoptotic populations and maintained its cytotoxic activity in 3D spheroid models by promoting disintegration, loss of cell adhesion, and nuclear fragmentation. Conclusions: The findings underscore the therapeutic promise of Pd(II) complexes, especially PdB1, as potent and selective antineoplastic agents capable of acting effectively in complex tumor environments and potentially overcoming chemoresistance. Full article

Current tourism route recommendation systems often overemphasize popular destinations, thereby overlooking geographical accessibility between attractions and the experiential coherence of the journey. Leveraging multidimensional attribute perceptions derived from tourist reviews, this study proposes a Spatial–Semantic Integrated Model for Tourist Attraction Representation (SSIM-TAR), which holistically encodes the composite attributes and multifaceted evaluations of attractions. Integrating these multidimensional features with inter-attraction relationships, three relational metrics are defined and fused: spatial proximity, resonance correlation, and thematic-sentiment similarity, forming a Tourist Attraction Multidimensional Association Network (MAN-SRT). This network enables precise characterization of complex inter-attraction dependencies. Building upon MAN-SRT, the Tourism Sentiment Chain (TSC) model is proposed that incorporates geographical accessibility, associative resonance, and thematic-sentiment synergy to optimize the selection and sequential arrangement of attractions in personalized route planning. Results demonstrate that SSIM-TAR effectively captures the integrated attributes and experiential quality of tourist attractions, while MAN-SRT reveals distinct multidimensional association patterns. Compared with popular platforms such as “Qunar” and “Mafengwo”, the TSC approach yields routes with enhanced spatial efficiency and thematic-sentiment coherence. This study advances tourism route modeling by jointly analyzing multidimensional experiential quality through spatial–semantic feature fusion and by achieving an integrated optimization of geographical accessibility and experiential coherence in route design. Full article

Neurocutaneous syndromes represent a clinically and genetically heterogeneous group of disorders, with tuberous sclerosis complex (TSC), von Hippel–Lindau syndrome (VHL), and ataxia–telangiectasia (A-T) exemplifying some of the most complex entities within this category. These syndromes have traditionally been considered monogenic disorders, caused by germline mutations in tumor suppressor or regulatory genes. However, they exhibit a striking degree of phenotypic variability and divergent clinical trajectories that cannot be fully explained by their underlying genetic alterations alone. Increasingly, epigenetic regulatory mechanisms, such as DNA methylation, histone modifications, chromatin remodeling, and non-coding RNA (ncRNA) activity, are recognized as key modulators of gene expression, cellular differentiation, and tissue-specific function. Disruption of these mechanisms has been implicated in disease pathogenesis, tumorigenesis, and neurodegeneration associated with TSC, VHL, and A-T. Aberrant epigenetic profiles may underlie the observed variability in clinical outcomes, even among individuals with identical mutations. This review consolidates current evidence on the epigenetic landscape of these syndromes, elucidating how these modifications may influence disease behavior and contribute to incomplete genotype–phenotype correlations. By integrating epigenetic insights with known molecular pathways, a more nuanced understanding of disease biology emerges, with potential implications for diagnostic stratification, prognostic assessment, and therapeutic innovation. Full article

Within the scope of digital transformation in nuclear power plants (NPPs), task complexity in human–computer interaction (HCI) has become a critical factor affecting the safe and stable operation of NPPs. This study systematically reviews and analyzes existing complexity sources and assessment methods and suggests that complexity is primarily driven by core factors such as the quantity of, variety of, and relationships between elements. By innovatively introducing Halstead’s E measure, this study constructs a quantitative model of dynamic task execution complexity (TEC), addressing the limitations of traditional entropy-based metrics in analyzing interactive processes. By combining entropy metrics and the E measure, a task complexity quantification framework is established, encompassing both the task execution and intrinsic dimensions. Specifically, Halstead’s E measure focuses on analyzing operators and operands, defining interaction symbols between humans and interfaces to quantify task execution complexity (TEC). Entropy metrics, on the other hand, measure task logical complexity (TLC), task scale complexity (TSC), and task information complexity (TIC) based on the intrinsic structure and scale of tasks. Finally, the weighted Euclidean norm of these four factors determines the task complexity (TC) of each step. Taking the emergency operating procedures (EOP) for a small-break loss-of-coolant accident (SLOCA) in an NPP as an example, the entropy and E metrics are used to calculate the task complexity of each step, followed by experimental validation using NASA-TLX task load scores and step execution time for regression analysis. The results show that task complexity is significantly positively correlated with NASA-TLX subjective scores and task execution time, with the determination coefficients reaching 0.679 and 0.785, respectively. This indicates that the complexity metrics have high explanatory power, showing that the complexity quantification model is effective and has certain application value in improving human–computer interfaces and emergency procedures. Full article

Introduction: Tuberous sclerosis complex (TSC) is a rare multisystemic genetic disorder characterized by the formation of benign tumors in various organs, including the central nervous system, skin, kidneys, and heart. The diagnosis is based on well-defined clinical criteria, such as those from Schwartz (2007) updated in 2012 by the International Tuberous Sclerosis Complex Consensus Group. The study aims to investigate the clinical, imaging, and molecular characteristics of patients diagnosed with tuberous sclerosis and to explore the correlation between specific genetic mutations (TSC1 and TSC2 genes) and the severity of clinical manifestations. Material and Methods: This is a retrospective longitudinal study of 13 patients diagnosed with tuberous sclerosis, identified in the records of the Bihor Regional Center for Medical Genetics (BRCMG) within the Bihor County Emergency Clinical Hospital from 1984 to 2024. Clinical, imaging, and molecular features were assessed. Patients were evaluated by a multidisciplinary team, including a geneticist, pediatrician, neurologist, psychiatrist, and psychologist. Clinical and imaging data were retrospectively collected from the congenital malformations and genetic disease records of BRCMG Bihor and statistically analyzed. Results: All patients showed clinical and imaging signs consistent with the diagnosis of tuberous sclerosis. Neurological manifestations were present in 83% of patients, including epilepsy and cognitive delays. Renal lesions were detected in 46% of cases, and dermatological lesions, such as facial angiofibromas, were observed in 69% of patients. Mutational variants identified in the TSC2 gene correlated with a more severe clinical presentation, including severe intellectual disability and treatment-resistant seizures, compared to variants in the TSC1 gene. Conclusions: Our study, although involving a small number of patients, highlights the clinical heterogeneity of tuberous sclerosis and the importance of a multidisciplinary approach in patient management. Early diagnosis and ongoing monitoring are essential to improving the quality of life for patients. Further studies are needed to assess the impact of therapeutic interventions and genetic correlations within the studied population. Full article