Search Results (244)

Background/Objectives: X-linked intellectual disability (XLID) is a highly heterogeneous disorder accounting for ~10% of all males with ID. Next-generation sequencing (NGS) has revolutionized the discovery of causal XLID genes and variants; however, many cases remain unresolved. We present a four-generation syndromic XLID family with multiple males exhibiting variable degree of ID, focal dystonia and epilepsy. Methods: Extensive cytogenetic and targeted genetic testing was initially performed, followed by whole-exome sequencing (WES) and short-read whole-genome sequencing (WGS). Apart from the routine NGS analysis pipelines, sequencing data was revisited by focusing on poorly covered/mapped regions on chromosome X (chrX), to potentially reveal unidentified clinically relevant variants. Candidate variant validation and family segregation analysis were performed with Sanger sequencing. Results: All initial diagnostic testing was negative. Subsequently, 300 previously reported “dark” chrX coding DNA sequences, overlapping 97 genes, were cross-checked against 29 chrX genes highly associated (p < 0.05) with ID and focal dystonia, according to Phenomizer. Manual inspection of the existing NGS data in two low-coverage regions, chrX:25013469-25013696 and chrX:111744737-111744820 (hg38), revealed a recurrent pathogenic ARX variant NM_139058.3:c.441_464dup p.(Ala148_Ala155dup) (ARXdup24) associated with non-syndromic or syndromic XLID, including Partington syndrome. Sanger sequencing confirmed ARXdup24 in all affected males, with carrier status in their unaffected mothers, and absence in other unaffected relatives. Conclusions: After several years of diagnostic odyssey, the pathogenic ARXdup24 variant was unmasked, supporting a genotype–phenotype correlation in the first Partington syndrome family in Cyprus. This study highlights that re-examining underrepresented genomic regions and using phenotype-driven tools can provide critical diagnostic insights in unresolved XLID cases. Full article

The 2020 Europe Strategy was designed as a comprehensive framework to promote smart, sustainable and inclusive growth in the European Union (EU), particularly emphasising the ‘20/20/20’ targets related to climate protection and energy policy. This study provides an ex post evaluation of the extent to which the strategy’s objectives were achieved in the member states of the EU in the period 2010–2020. The analysis is based on Eurostat data and uses Hellwig’s multidimensional comparative analysis to construct a synthetic indicator of progress. The results show that EU countries have made significant advances in reducing greenhouse gas emissions and increasing the share of renewable energy in gross final energy consumption, with Sweden and Finland identified as leaders, while Malta and Hungary lagged behind. Primary energy consumption overall decreased, although only a minority of the member states reached the planned thresholds. Progress was less evident in research and development (R&D) expenditure, where the average value of the EU remained below the 3% GDP target, and strong disparities persisted between innovation leaders and weaker performers. Improvements in higher education attainment were observed, contributing to the long-term goal of a knowledge-based economy, although labour market difficulties, especially among young people, remained unresolved. The findings suggest that, although the Strategy contributed to tangible progress in several areas, uneven achievements among member states limited its overall effectiveness. The study is limited by the reliance on aggregate statistical data and a single methodological approach. Future research should extend the analysis to longer time horizons, include qualitative assessments of national policies, and address implications for the implementation of the European Green Deal and subsequent EU development strategies. Full article

Skeletal muscle pathologies, including sarcopenia, inflammatory myopathies, and various muscular dystrophies, are strongly influenced by chronic low-grade inflammation and impaired proteostasis. Immunoproteasomes (IMPs), inducible proteolytic complexes activated by pro-inflammatory cytokines, are emerging as regulators linking immune signaling to protein quality control. Evidence suggests that IMPs have paradoxical, context-dependent roles in skeletal muscle. On one hand, they can support proteostasis and muscle regeneration under stress; on the other, persistent activation may sustain cytokine production, antigen presentation, and maladaptive immune–muscle interactions, promoting chronic inflammation and muscle wasting. Selective IMP inhibitors, such as ONX 0914 and KZR-616, display potent anti-inflammatory effects in preclinical models of autoimmune myositis and muscle atrophy. Yet, their use in skeletal muscle pathologies is controversial; while inhibition may dampen harmful immune activation, it could also impair muscle repair and proteostasis. This review summarizes current findings, highlights key contradictions, and explores unresolved questions about the role of IMPs in skeletal muscle pathologies. We emphasize the need for a deeper understanding of IMP-mediated mechanisms in skeletal muscle pathology and strategies combining selective inhibitors to enhance therapeutic efficacy while minimizing adverse effects. IMPs thus represent both a promising and potentially risky therapeutic target, with outcomes highly dependent on disease context. Full article

Bone metastases continue to be a major cause of morbidity and mortality in patients with advanced cancers, driven by the dynamic remodeling of the bone marrow niche. Traditionally viewed as passive space-fillers, bone marrow adipocytes (BMAs) are now recognized as active regulators of tumor growth, therapeutic resistance, and skeletal pathology. BMAs comprise a significant portion of the adult marrow space, particularly in aging and obesity, and facilitate metastatic colonization through various mechanisms. These include metabolic coupling, where adipocyte-derived fatty acids fuel tumor oxidative phosphorylation; the secretion of adipokines such as leptin and IL-6, which promote epithelial-to-mesenchymal transition, invasion, and immune evasion; regulation of osteoclastogenesis via RANKL expression; and the release of extracellular vesicles that reprogram cancer cell metabolism. Clinical and experimental studies show that BMA expansion correlates with increased tumor burden and poorer outcomes in breast, prostate, lung cancers, and multiple myeloma. Additionally, BMAs actively promote therapeutic resistance through metabolic rewiring and drug sequestration. Experimental models, ranging from in vitro co-cultures to in vivo patient-derived xenografts, demonstrate the complex roles of BMAs and also reveal important translational gaps. Despite promising preclinical approaches such as metabolic inhibitors, PPARγ modulation, adipokine blockade, and lifestyle changes, no therapies directly targeting BMAs have yet reached clinical practice. This review compiles current evidence on the biology of BMAs, their tumor-promoting interactions, and potential therapeutic strategies, while also highlighting unresolved questions about BMA heterogeneity, lipid flux, and immunometabolic crosstalk. By revealing how bone marrow adipocytes actively shape the metastatic niche through metabolic, endocrine, and immunological pathways, this review highlights their potential as novel biomarkers and therapeutic targets for improving the management of bone metastases. Full article

Lunar dust remains one of the most critical unresolved challenges to long-duration lunar missions. Its sharp, abrasive, and electrostatically charged particles are easily inhaled and can penetrate deep into the lungs, reaching the bloodstream and the brain. Despite airlocks and HEPA filtration systems, dust will inevitably infiltrate lunar habitats and threaten astronaut health. We present a novel patent protected helmet design. This system uses a multilayered, synergistic mitigation approach combining mechanical and electrostatic defenses. The mechanical system delivers HEPA-filtered, ionized air across the user’s face, while the electrostatic barrier repels charged particles away from the respiratory zone. These two systems work together to prevent dust from entering the user’s breathing space. Designed for use inside lunar habitats, this helmet represents a potential solution to an unaddressed, life-threatening problem. It allows astronauts to eat, talk, and sleep while maintaining a protected respiratory zone and provides targeted inhalation-level protection in an environment where dust exposure is otherwise unavoidable. This concept is presented at Technology Readiness Level 2 (TRL 2) to prompt early engagement and feedback from the scientific and engineering communities. Full article

Microgravity exposure during spaceflight has been linked to cognitive impairments, including deficits in attention, executive function, and spatial memory. Both space missions and ground-based analogs—such as head-down bed rest, dry immersion, and hindlimb unloading—consistently demonstrate that altered gravity disrupts brain structure and neural plasticity. Neuroimaging data reveal significant changes in brain morphology, functional connectivity, and cerebrospinal fluid dynamics. At the cellular level, simulated microgravity impairs synaptic plasticity, alters dendritic spine architecture, and compromises neurotransmitter release. These changes are accompanied by dysregulation of neuroendocrine signaling, decreased expression of neurotrophic factors, and activation of oxidative stress and neuroinflammatory pathways. Molecular and omics-level analyses further point to mitochondrial dysfunction and disruptions in key signaling cascades governing synaptic integrity, energy metabolism, and neuronal survival. Despite these advances, discrepancies across studies—due to differences in models, durations, and endpoints—limit mechanistic clarity and translational relevance. Human data remain scarce, emphasizing the need for standardized, longitudinal, and multimodal investigations. This review provides an integrated synthesis of current evidence on the cognitive and neurobiological effects of microgravity, spanning behavioral, structural, cellular, and molecular domains. By identifying consistent patterns and unresolved questions, we highlight critical targets for future research and the development of effective neuroprotective strategies for long-duration space missions. Full article

Efficient allocation of mineral nutrients and photoassimilates is essential for grain development in rice. However, the transcriptional programs governing nutrient transport at key reproductive stages remain largely unresolved. Here, we performed a comprehensive transcriptome analysis of rice (Oryza sativa L.) across spatial (nodes, roots, and five other tissues) and temporal (seven reproductive stages) dimensions to elucidate the molecular basis of nutrient transport and allocation. RNA-seq profiling of node I identified stage-specific gene expression patterns, with the grain filling stage marked by strong induction of transporters involved in mineral allocation (e.g., OsYSL2, OsZIP3, OsSULTR3;3, SPDT) and carbohydrate distribution (e.g., OsSWEET13, OsSWEET14, OsMST6). Comparative analysis with the neck-panicle node (NPN) and root revealed tissue-specific regulatory networks, including nitrate (OsNRT1.1A, OsNRT2.3) and phosphate (OsPHT1;4, OsPHO1;3) transporters enriched at the grain filling stage. Root expression of Cd/As-related transporters (OsNRAMP5, OsCd1, OsLsi1, OsLsi2, OsLsi3) during grain filling highlights the contribution of belowground uptake to grain metal accumulation. Together, our study establishes a spatiotemporal atlas of nutrient transporter gene activity during rice reproductive development and identifies candidate genes regulating upward and lateral nutrient allocation. These findings provide insights into improving nutrient use efficiency and reducing toxic metal accumulation in rice grains through targeted manipulation of nodal and root transport systems. Full article

Objectives: Sub-second motor timing is critical for skilled performance in domains such as sport, music, and safety-critical multitasking; however, its robustness under cognitive load remains unresolved. Dual-task paradigms offer a method to test whether attentional demands selectively disrupt temporal precision. This study intended to investigate the effects of cognitive load on rhythmic finger tapping at a sub-second interval. Methods: A sample of 103 college students (19–25 years) performed a synchronization–continuation tapping task at 500 ms intervals under single- and dual-task conditions across five trials. The dual-task condition included a distracting letter-span task imposing working memory load. Inter-response intervals (IRIs), their variability (IRI SD), and accuracy (AI) were analyzed using linear mixed-effects models. Results: Tapping intervals were consistently shorter than the 500 ms target by approximately 70 ms in both conditions, showing anticipatory mechanisms that remained stable under cognitive load. Mean accuracy did not vary between single- and dual-task conditions. By contrast, temporal variability was significantly higher in the dual-task condition, reflecting diminished trial-to-trial consistency. These effects continued throughout trials and were supported by model estimates, which indicated robust between-subject variability but selective disruption of consistency rather than mean performance. Conclusions: Dual-tasking selectively hinders temporal stability in sub-second motor timing while ensuring that the reproduction and accuracy of the mean interval remain unchanged. This pattern supports dual-process accounts of timing, suggesting distinct roles for predictive control and attentional allocation. The results have applied relevance for situations requiring precise rhythmic performance under cognitive load, including sports, ensemble music, and safety-critical tasks. Full article

Cardiovascular–kidney–metabolic syndrome (CKMS) encompasses interconnected cardiovascular, renal, and metabolic disorders, including obesity, hypertension, and type 2 diabetes. Oxidative stress is increasingly recognized as a central driver of this multi-organ dysfunction. Among maternal influences, exposure to a high-fat diet (HFD) during pregnancy and lactation consistently predisposes offspring to CKMS-related phenotypes in animal models. While oxidative stress is implicated as a key mediator, its precise role in developmental programming remains unclear, and comparing the differences in its role between overt CKMS and CKM programming is critical. Critical gaps include whether oxidative stress acts uniformly or in an organ- and time-specific manner, which signals initiate long-term redox alterations, and whether these effects are reversible. Furthermore, its interactions with other programming pathways—such as renin–angiotensin system activation, epigenetic dysregulation, gut microbiota imbalance, and altered nutrient sensing—remain insufficiently explored. This review uniquely highlights maternal HFD-induced oxidative stress as a mechanistic axis of CKMS programming and delineates unresolved questions that limit translation. By integrating evidence across organ systems and proposing priorities for multi-organ profiling, refined models, and longitudinal human studies, we outline a forward-looking agenda for the field. Ultimately, clarifying how maternal HFD and oxidative stress shape offspring CKMS risk is essential to inform targeted antioxidant strategies to reduce the intergenerational transmission of CKMS risk. Full article

Fanconi anemia (FA) is a genetic disorder characterized by congenital anomalies, bone marrow failure, and cancer predisposition. Among other solid cancers, head and neck squamous cell carcinoma (FA HNSCC) is the most common cancer type in individuals with FA. The FA pathway is required for the complete repair of DNA interstrand crosslinks (ICLs), and unresolved ICLs result in cell cycle arrest, apoptosis, or complex chromosomal rearrangements due to chromosome breaks, ultimately leading to tumorigenesis. FA HNSCCs present earlier (median age of onset in the 30s) and exhibit a more aggressive course with frequent recurrence and second primaries, and entail a poorer survival rate compared to sporadic HNSCC. FA HNSCCs are mostly human papillomavirus (HPV)-negative and frequently carry somatic copy number variations (CNVs), which amplify oncogenes implicated in sporadic HNSCC, but single-nucleotide variants or small insertions and deletions are less frequent than in HPV-negative sporadic HNSCC. A subset of sporadic HNSCC carries pathogenic mutations or promoter methylation in FA genes, which also harbor characteristic somatic CNVs, suggesting shared molecular underpinnings with FA HNSCC. Heightened inflammation from genomic instability and transcriptional activation of retrotransposons contribute to tumorigenesis and increased invasiveness by the epithelial-to-mesenchymal transition. Due to heightened sensitivity to DNA crosslinking agents in patients with FA, platinum-based chemotherapy is generally avoided, which presents a significant hurdle for treatment and thereby leaves limited therapeutic options. Surgical management is the mainstay of therapy if possible, and targeted therapy has been increasingly studied in HNSCC in FA. Full article

One of the unresolved questions in stress-response biology is how plants coordinate expression levels between the response and adaptation. In this work, we proposed a two-level analysis that examines both transcriptional and translational profiles of Solanum lycopersicum under conditions of short-term cold stress, hardening, and their combination. By combining polysome profiling and total transcriptome analysis, we revealed that expression under cold stress is not a simple linear process but a structurally distinct system with two coordinated regulation centres. Hardening triggers a strong transcriptional program focused on biogenesis, light signalling, and structural adaptations. In contrast, acute stress prompts selective translation of metabolic and defence proteins without prior transcriptional increase. Modular analysis (WGCNA) showed little overlap between transcriptional and translational networks, indicating functional differences between regulation levels. This work demonstrates that the cold response involves a strategic reallocation of resources between transcription and translation based on the type of signal. It bridges basic biology and applied breeding, providing targets promising for improving plant stress tolerance and advancing bioengineering of adaptive agriculture. Full article

Small-target detection in Unmanned Aerial Vehicle (UAV) aerial images remains a significant and unresolved challenge in aerial image analysis, hampered by low target resolution, dense object clustering, and complex, cluttered backgrounds. In order to cope with these problems, we present AeroLight, a novel and efficient detection architecture that achieves high-fidelity performance in resource-constrained environments. AeroLight is built upon three key innovations. First, we have optimized the feature pyramid at the architectural level by integrating a high-resolution head specifically designed for minute object detection. This design enhances sensitivity to fine-grained spatial details while streamlining redundant and computationally expensive network layers. Second, a Dynamic Feature Fusion (DFF) module is proposed to adaptively recalibrate and merge multi-scale feature maps, mitigating information loss during integration and strengthening object representation across diverse scales. Finally, we enhance the localization precision of irregular-shaped objects by refining bounding box regression using a Shape-IoU loss function. AeroLight is shown to improve mAP50 and mAP50-95 by 7.5% and 3.3%, respectively, on the VisDrone2019 dataset, while reducing the parameter count by 28.8% when compared with the baseline model. Further validation on the RSOD dataset and Huaxing Farm Drone dataset confirms its superior performance and generalization capabilities. AeroLight provides a powerful and efficient solution for real-world UAV applications, setting a new standard for lightweight, high-precision object recognition in aerial imaging scenarios. Full article

While negotiating agents have achieved remarkable success, one critical challenge that remains unresolved is the inherent inefficiency of learning negotiation strategies from scratch when encountering previously unencountered opponents. To address this limitation, Transfer Learning (TL) emerges as a promising solution, leveraging knowledge acquired from prior tasks to accelerate learning and enhance adaptability in new negotiation contexts. This study introduces Transfer Learning-based Negotiating Agent (TLNAgent), a novel framework enabling autonomous negotiating agents to systematically leverage knowledge from pretrained source policies. The proposed transfer mechanism not only enhances negotiation performance but also substantially accelerates policy adaptation in unfamiliar negotiation environments. TLNAgent integrates three core components: (1) a negotiation module that interacts with opponents; (2) a critic module that determines whether to activate the transfer process and selects which source policies to transfer; and (3) a transfer module that facilitates knowledge integration between source and target policies. Specifically, the negotiation module interacts with opponents during the negotiation to execute core decision-making processes; in addition, it trains new policies using reinforcement learning. The critic module serves dual critical functions: (1) it dynamically triggers the transfer module according to interaction analysis; and (2) it selects the source policies via its adaptation model. The transfer module establishes lateral parameter-level connections between source and target policy networks, facilitating systematic knowledge transfer while ensuring training stability. Empirical findings from our extensive experiments indicate that transfer learning considerably enhances both the efficiency and utility of outcomes in cross-domain negotiation tasks. The proposed framework attains superior performance when compared to the state-of-the-art negotiating agents from the Automated Negotiating Agents Competition (ANAC). Full article

Age-related macular degeneration (AMD) is a common eye disease that significantly affects daily activities and impedes the quality of life in aging adults, yet effective treatments to halt or reverse disease progression are currently lacking. Ongoing research aims at understanding the complex mechanisms underlying AMD pathophysiology involving retinal pigment epithelium (RPE) dysfunction, drusen formation, inflammation, neovascularization, and RPE/photoreceptor degeneration. Sigma 2 receptor/transmembrane protein 97 (σ₂R/TMEM97) is a multifunctional protein implicated in cellular processes including cholesterol homeostasis, lysosome-dependent autophagy, calcium homeostasis, and integrated stress response (ISR). Recent genome-wide association studies (GWASs) have identified σ₂R/TMEM97 as a novel genetic risk factor strongly associated with AMD development. In this review, we summarize recent research progress on σ₂R/TMEM97 in age-related neurodegenerative diseases, highlighting its implication as a molecular target in AMD via regulating oxidative stress, inflammation, lipid uptake, drusen formation, and epithelial–mesenchymal transition (EMT). We also discuss the potential of modulating σ₂R/TMEM97 function with novel small-molecule drugs as a promising treatment for dry AMD and the unresolved questions in understanding the mechanistic basis of their actions. Full article

Orthodontic tooth movement (OTM) is accompanied by sterile inflammation, a necessary biological process that facilitates tooth displacement but also contributes to adverse effects, including hyalinization and orthodontically induced external apical root resorption (OEARR). Despite advancements in orthodontic therapies, the inflammatory response—regulated by dynamic interactions between tissue-specific cells and their molecular mediators—remains a critical factor influencing treatment outcomes. This review summarizes the current understanding of the cellular and molecular mechanisms underlying OTM, with a focus on how these insights can support the development of targeted therapeutic strategies. These include cell- and molecule-based therapies, biomaterial-mediated delivery systems, and applications of artificial intelligence (AI). Notably, AI offers promising opportunities for modeling and simulating biological responses, enabling the optimization of individualized treatment planning. We further discuss current clinical practices and highlight emerging experimental findings, with an emphasis on unresolved research questions pivotal to improving therapeutic efficacy and reducing complications such as OEARR. This comprehensive overview aims to inform future directions in orthodontics by integrating mechanistic knowledge with technological innovation. Full article