Neuroimaging studies have revealed altered functional connectome dynamics in autism spectrum disorder (ASD) and linked these alterations to clinical symptoms. However, most studies have emphasized population-level contrasts, leaving interindividual variability in connectome dynamics and its structural underpinnings poorly understood. To address this gap, we analyzed resting-state functional and structural MRI data from 939 male participants (440 with ASD, 499 typically developing controls) across 18 sites in the Autism Brain Imaging Data Exchange (ABIDE). Whole-brain functional state dynamics was characterized using five leading activity modes and their expressions via eigen-microstate analysis. Age-related trajectories of mode expressions were constructed for typically developing controls using normative modeling, enabling quantification of individual-level deviations in functional dynamics. Compared with controls, ASD individuals showed greater interindividual variability in functional deviation profiles. Unsupervised clustering of these profiles identified two robust ASD subtypes with distinct mode-specific dysfunctions. One subtype primarily involved the visual, default-mode, frontoparietal, and dorsal attention networks, whereas the other subtype primarily involved the somatomotor, visual, frontoparietal, and ventral attention networks. These subtypes were clinically dissociable, differing in restricted and repetitive behaviors and social impairments, and exhibited mode-specific brain-symptom associations. Furthermore, the subtypes exhibited distinct cortical thickness alterations, and individual subtype membership was predicted with high accuracy (83%) using a random forest classifier based on cortical thickness. The main findings were replicated in an independent cohort outside ABIDE. This study delineates two reproducible and clinically dissociable ASD subtypes and links functional connectome dynamics to structural substrates, offering novel insights into the neurobiological basis behind ASD heterogeneity.
Cue-induced seeking engages neuronal ensembles within the nucleus accumbens core (NAcore), with neuronal ensembles defined here as neurons coactivated during specific behavioral experiences that have been implicated in cued-reinstatement. Although transient synaptic plasticity has been widely observed in unidentified ensemble and non-ensemble neuronal populations in the NAcore during reinstatement, its expression within behaviorally relevant ensembles remains unclear. Here, we used c-Fos-TRAP2-based tagging to characterize structural and functional synaptic plasticity within ensembles during cocaine-seeking in mice following cocaine intravenous self-administration, extinction, and cue-induced reinstatement. Structural plasticity was measured via spine confocal imaging, and functional changes were evaluated by AMPA/NMDA ratios using whole-cell electrophysiology across reinstatement time points. Ensemble neurons exhibited increased dendritic spine head diameter during cue-induced reinstatement and were functionally potentiated relative to non-ensemble neurons. Spine classification showed reduced mature spines during reinstatement in both ensemble and non-ensemble cells, suggesting morphological remodeling rather than new spine formation. Non-ensemble neurons showed no change in spine head diameter during reinstatement but did exhibit an increased AMPA/NMDA ratio during cued-reinstatement. Paired-pulse ratio analysis suggested that yoked-cocaine exposure decreased presynaptic vesicle release probability, while operant cocaine exposure had no effect. Ensemble neurons showed an elevated AMPA/NMDA ratio following cocaine exposure, regardless of whether intake was yoked or contingent. Together, these findings suggest that ensemble and non-ensemble neurons undergo distinct forms of synaptic plasticity during cue-induced reinstatement. By distinguishing ensemble-specific structural plasticity from non-ensemble functional plasticity, this study refines the current understanding of mechanisms underlying cue-induced relapse. SIGNIFICANCE STATEMENT: In preclinical models of substance use disorder drug seeking is associated with cue-induced reactivation of neuronal ensembles in the nucleus accumbens core. While transient synaptic plasticity has been extensively described in non-selective neuronal populations pooling recordings of both ensemble and non-ensemble neurons of the nucleus accumbens core, ensemble-specific plasticity remains unclear. Here, we combined c-Fos-TRAP2 tagging, confocal imaging, and slice electrophysiology to show that structural synaptic plasticity is selectively expressed in behaviorally relevant ensembles. By linking ensemble identity with structural and functional plasticity during cue-induced cocaine seeking, these findings refine current models of relapse and identify plasticity within the ensemble as a potential target for therapeutic intervention.
To interpret and transmit biological signals, proteins use correlated motions. Experimental determination of these dynamics and the structural distributions they generate remains a key challenge. Here, using 1146 crystal structures of the main protease (Mpro) from SARS-CoV-2, we were able to infer a model of the enzyme's structural fluctuations. Mpro is regulated by concentration, becoming enzymatically active after forming a homodimer. To understand the structural changes that enable dimerization to activate catalysis, we employed our model, predicting which regions of the dimerization domain are structurally correlated with the active site. Mutations at these positions, expected to disrupt catalysis, resulted in a dramatic reduction in activity in one case, a mild effect in the second, and none in the third. Additional crystallography and biophysical experiments provide a mechanistic explanation for these results. Our work suggests that a statistical crystallography, in which numerous crystallographic datasets are analyzed, can reveal the structural fluctuations of protein native states and help uncover their biological function.
Seismic risk assessment is a probabilistic approach that evaluates the likelihood of earthquake occurrence, structural response, expected damage levels, economic losses, and potential casualties by incorporating the inherent uncertainties associated with seismic hazards and urban building characteristics. The primary objective of this study is to quantify and spatially characterize the distribution of damage states at the urban scale. Buildings were classified according to their structural system, age, and number of stories. The structures were initially modeled, analyzed, and designed in ETABS, and the beam and column section properties were extracted for each structural type. Finite element models were subsequently developed in OpenSees, and Incremental Dynamic Analysis, IDA, was performed to evaluate the seismic performance of building groups and large-scale seismic risk. The application of this approach to urban-scale seismic risk evaluation distinguishes this research from similar previous investigations. Given the considerable number of models, the extensive dataset, and the necessity for updating results under varying input conditions, a Bayesian Probabilistic Network was employed. In addition, GIS-based mapping was used to present the findings, including the exceedance probabilities of different damage states and the spatial distribution of collapse probability. The outcomes of this study identify areas that may exhibit relatively higher seismic vulnerability, emphasizing the potential need for targeted retrofitting strategies or, enhanced preparedness for post-earthquake emergency response and rescue operations.
Aging and increased life expectancy generate growing challenges for end-of-life care in old age, particularly in rural contexts marked by territorial and health inequalities. From the perspective of gerontological geography and the notions of autonomy and agency of older adults, this study aims to generate an understanding of end-of-life as a lived experience from the subjective worlds of and with the people involved. To this end, a qualitative study, with an ethnographic approach and case study strategy, was conducted in the Los Lagos Region of Chile between 2022 and 2023. This included semi-structured interviews and ethnographic observation of rural older adults in the end-of-life stages, their caregivers, and rural health teams. The results show that remaining at home is a central desire and organizes care, sustained primarily by feminized family networks and rural primary care. The home becomes a space of care, and health teams play a key role in providing clinical and relational support at the end-of-life. It is concluded that end-of-life care in rural areas requires territorial approaches that recognize autonomy in old age and the structural inequalities of these processes. El envejecimiento y aumento de la esperanza de vida generan desafíos crecientes para los cuidados de fin de vida en la vejez, particularmente en contextos rurales marcados por desigualdades territoriales y sanitarias. Desde la geografía gerontológica, y las nociones de autonomía y agencia de las personas mayores, este estudio se propone generar una comprensión del fin de vida como experiencia vital desde los mundos subjetivos de y con las personas implicadas. Para ello, se realizó un estudio cualitativo, de enfoque etnográfico y estrategia de estudio de caso, en la Región de Los Lagos, Chile, entre 2022 y 2023, que incluyó entrevistas semiestructuradas y observación etnográfica a personas mayores rurales en etapas de fin de vida, las personas cuidadoras y los equipos de salud rural. Los resultados muestran que la permanencia en el hogar constituye un deseo central y organiza los cuidados, sostenidos principalmente por redes familiares feminizadas y por la atención primaria rural. El hogar se transforma en un espacio de cuidado y los equipos de salud cumplen un rol clave en acompañamiento clínico y relacional del fin de vida. Se concluye que los cuidados de fin de vida en la ruralidad requieren enfoques territoriales que reconozcan autonomía en la vejez y las desigualdades estructurales de estos procesos.
Apricot (Prunus armeniaca L.), a globally cultivated temperate fruit crop, represents an economically critical species for fresh consumption and value-added products. Despite its agricultural importance, genomic resources have lagged behind other Prunus species, hampering trait dissection and molecular breeding. Here, we present the first telomere-to-telomere (T2T) gap-free genome assembly for the elite cultivar 'Sungold', achieved through the integration of multi-platform sequencing technologies: Illumina short-read, PacBio HiFi, ONT ultra-long, and Hi-C scaffolding. The final assembly spans 251.36 Mb with benchmark quality metrics: a contig N50 of 32.04 Mb, BUSCO completeness score of 98.8%, LTR Assembly Index (LAI) of 15.99, and a consensus quality value (QV) of 59.75. The T2T assembly achieved the resolution of all eight centromeres, together with fourteen intact telomeres, confirming its high structural integrity. Genomic annotation revealed 43.38% of repetitive sequences and 25,999 predicted protein-coding genes. This gap-free T2T genome resource establishes the highest-resolution reference for investigating apricot genome evolution, structural variation, and trait-associated genetic mechanisms in modern breeding programs.
Cyanuric chloride is a highly reactive, widely recognized compound in medicinal chemistry, enabling rapid and selective nucleophilic substitution reactions at its three chlorine positions. In the present study, explore the structural advantages of cyanuric chloride to develop a new DOTA-linked triazine-based scaffold for PSMA. Two scaffolds, abbreviated as PSMA-C1D and PSMA-C2D, were successfully synthesized with good yields and evaluated their properties through molecular docking, in vitro studies, radiolabelling, physicochemical properties, and internalization studies. The initial screening revealed that, the PSMA-C1D had greater potential as a PSMA-targeted imaging agent than PSMA-C2D. In vitro cytotoxicity assays further indicated good biocompatibility at imaging-relevant concentrations. The molecular docking demonstrated strong site-specific binding of PSMA-C1D to the PSMA active pocket (ΔG = - 10.2 kcal/mol), with interactions closely resembling the co-crystallized ligand. The radiolabelling of PSMA-C1D with Ga-68 shows high yield with > 95% radiochemical purity, excellent stability in multiple biological media, and high apparent molar activity (508 GBq/µmol). The tracer shows hydrophilicity (logD7.4 = - 2.76 ± 0.02), low %PPB (18 ± 5.4), and has a nanomolar affinity (Kd = 0.38 nM), with the percentage of bound internalization in LNCaP cells was 15 ± 2.9% incubation for 1 h. The study highlights the value of cyanuric chloride as a modular chemical hub for the design and linking of radiopharmaceuticals. It identifies [68Ga]Ga-PSMA-C1D as a promising, efficiently synthesizable, and highly PSMA-specific PET radiotracer for imaging prostate cancer.
Ectonucleotidases, including NTPDases and ecto-5'-nucleotidase (e-5'NT/CD73), regulate extracellular purinergic signaling by converting ATP to adenosine, a pathway critically involved in immune response, inflammation, and cancer progression. In this study, a novel library of 22 N-propylsulfonyl-substituted indole-based hydrazinecarbothioamides (5a-5v) was synthesized and structurally characterized. Biological evaluation against human e-5'NT and NTPDase1, -2, -3, and - 8 revealed that several compounds exhibited low micromolar inhibitory activity, with 5n (IC50 = 1.7 µM), 5o (IC50 = 1.7 µM), 5f (IC50 = 1.0 µM), and 5i (IC50 = 1.6 µM) emerging as the most promising derivatives, showing strong potency and isoform selectivity. Structure-activity relationship analysis indicated that both electronic and steric features of substituents significantly influence activity and enzyme preference. Molecular docking studies performed on e-5'NT demonstrated that active compounds adopt consistent binding modes within the catalytic pocket, stabilized by key residues such as Asp-506, Phe-500, Phe-417 and Arg-395. Binding free energy calculations (MM-GBSA) supported strong ligand-protein interactions ( ~ - 70 kcal/mol). The docking protocol was validated by redocking, yielding an RMSD value well below the accepted threshold. Molecular dynamics simulations (500 ns) confirmed stable complex formation, with low RMSD values (~ 1-3 Å), limited residue fluctuations, and persistent interactions with catalytic residues. Surface and compactness parameters (rGyr, SASA) remained stable, indicating consistent ligand accommodation. In silico ADME analysis suggested favorable drug-like properties for most compounds, particularly for the lead candidates. Overall, these findings identify 5n and 5o as the most promising lead compounds, supported by both experimental and computational results, and highlight this scaffold as a valuable platform for the development of selective ectonucleotidase inhibitors.
Pediatric sepsis is a leading cause of global morbidity and mortality, yet high-resolution, granular subnational assessments remain scarce. Chile and Mexico are the only countries in Latin America that possess robust vital registration systems and open access databases with marginal levels of missing cases. This offers a unique opportunity to quantify the subnational burden of pediatric sepsis, identify healthcare system constrictions, and guide targeted public health interventions. This retrospective longitudinal study analyzed official hospital discharge and non-fetal death records of pediatrics (< 10 years old) from Chile and Mexico between 2014 and 2024. Age-standardized incidence (ASIR) and mortality (ASMR) rates, standardized ratios, and the mortality-to-incidence ratio (MIR), were calculated to assess mortality relative to subnational hospital output. A novel dynamic risk stratification matrix was developed to classify ICD-10 sepsis-related causes into four risk/severity quadrants based on year-specific ASIR and MIR indicators. A total of 656,234 discharges and 2,035 deaths in Chile, and 964,452 discharges and 77,252 deaths in Mexico were analyzed. Subnational trends were highly heterogeneous. Chile exhibited a predominantly low pediatric MIR (median < 1%) with isolated hotspots with significant structural deviations to the North. High-severity sepsis causes in Chile were relatively rare. Conversely, Mexico displayed an alarmingly high MIR (median 7.2%), with systemic persistency in States such as Chiapas and Nuevo León. Strikingly, high-severity causes in Mexico (e.g., unspecified septicaemia, bacterial meningitis) were highly frequent, accounting for 88-97% of pediatric sepsis deaths. Furthermore, systemic instances of code-specific MIR > 1.0 in Mexico suggest significant health system fragmentation and decoupling of hospital discharge from vital statistic registries. Pediatric sepsis in Latin America encompasses distinct realities, ranging from localized critical care gaps to high-lethality persistency. One-size-fits-all national policies may be inadequate. These findings advocate for precision public health, urging the deployment of decentralized, data-driven interventions and specialized resource allocation based on high-risk subnational hotspot identification.
Incorporating redox active ligands into coordination cages offers a direct way to reach architectures whose structure or composition can be modulated in response to changes in the oxidation state. An exTTF-based ditopic ligand L affords a M2L4 cage in presence of a palladium(II) salt (M). The resulting M2L4 cavity exhibits selective binding properties for medium length α,ω-dinitrile alkanes. Modifying the coordination geometry of the ligand by oxidation to its Lox state redirects the self-assembly process toward a M2Lox 2 structure. The oxidized ligand can also be combined with a dibenzothiophene linker (L') to afford a heteroleptic M2LoxL'2 structure whose vacant coordination sites enable subsequent dimerization into an unprecedented M4L4L'4 architecture. Key intermediates and products were structurally authenticated by single-crystal x-ray diffraction. Notably, these processes are reversible. Reduction converts the M2LoxL'2 assembly back to the homoleptic M2L4 cage. This sequence illustrates how changes of oxidation state can reshape nuclearity and composition in metal organic assemblies.
Chitin is the second most abundant polysaccharide in nature, and its degradation by marine microorganisms plays a critical role in the global carbon and nitrogen cycles. This study investigated the marine bacterium Microbulbifer harenosus CGMCC 1.13584T to elucidate its chitin metabolic pathway through genomic and transcriptomic analyses. When cultured with chitin as the carbon source, the strain exhibited an extended lag phase and enhanced extracellular chitinase activity. Genome sequencing revealed the presence of genes involved in both hydrolytic and oxidative chitin degradation pathways. Transcriptomic analysis showed that genes associated with the hydrolytic pathway were significantly upregulated upon chitin induction. In contrast, within the oxidative degradation pathway, only early-stage response genes (such as those encoding LPMOs) were markedly upregulated, while genes involved in subsequent metabolic steps (converting GlcNAc1A to KDG-6-P) did not show significant upregulation. Furthermore, a gene encoding a GH10 domain-containing protein was found to be substantially upregulated during growth on chitin. These findings indicate that Microbulbifer harenosus CGMCC 1.13584T utilizes a coordinated chitin degradation mechanism, where the hydrolytic pathway dominates carbon flux during active growth, while the oxidative pathway (via LPMOs) likely provides critical initial structural disruption.
The cyanobacterium Prochloron didemni produces macrocyclic octapeptides with thiazole and oxazoline heterocycles, known as patellamides. An interesting observation is that Cu2+ binding to the patellamides is likely to be related to their biological function. First, we show that Cu2 + injection into Lissoclinum patella increases patG gene expression and patellamide levels in the ascidians. Second, x-ray absorption spectroscopy shows that biological extracts of specimen from the Great Barrier Reef match structurally synthetic carbonato-bridged dicopper(II)-patellamide complexes. Third, patellamides exhibit very high membrane permeability (PAMPA, Caco-2). Combined with intracellular pH data, patellamide-Cu2 + bioactivity in algae, and the absence of many of the typical CO2 uptake mechanisms in Prochloron, we propose that patellamides facilitate carbonate transport from the ascidians to the cyanobacteria. This provides unprecedented evidence for a link between cyanobactin metal binding and their production and function, suggesting possible novel metal-related roles for marine cyclic peptides.
The development of sustainable and highly sensitive diagnostic platforms is critical for rapid pathogen identification and effective disease management. Here, a green, magneto-electrochemical biosensing strategy is reported for the selective detection of Streptococcus pneumoniae based on pathogen-specific nuclease activity. Uniform organic-inorganic hybrid polyhedral oligomeric silsesquioxane (POSS) nanoparticles were synthesized via an ultrafast UV-initiated emulsion polymerization within 5 min using an eco-friendly approach. The nanoparticles were sequentially functionalized by in situ deposition of superparamagnetic iron oxide nanoparticles and biomimetic polydopamine coating, enabling robust and high-density immobilization of nuclease-responsive oligonucleotide probes. The resulting PDA@SPION/POSS nanohybrids exhibit controlled size, preserved structural integrity, and strong superparamagnetic behavior, allowing efficient magnetic manipulation and electrochemical signal transduction. Upon exposure to S. pneumoniae, nuclease-mediated probe cleavage produces a pronounced electrochemical response, enabling label-free detection over a wide dynamic range (102-10⁸ CFU mL⁻¹) with a detection limit of 102 CFU mL⁻¹. High selectivity against non-target bacteria highlights the specificity of the enzymatic recognition mechanism. This work establishes a sustainable and amplification-free biosensing platform with strong potential for rapid clinical diagnostics.
Limb salvage centers have increased in number over time, but lack standardized defining criteria. This systematic review aimed to assess organizational features of limb salvage centers and determine whether orthoplastic centers, in comparison to vascular limb salvage centers, represent a distinct care model that may benefit from standardization. We conducted a systematic review of publications related to limb salvage centers by searching MEDLINE, Embase, Web of Science, and Cochrane databases from their inception through 2024. We quantified binary data extraction as a reporting score of 26 organizational features across six structural care domains for limb salvage centers, based on a validated quality measurement framework. Organizational features differentiating distinct center types were identified to establish a quality framework for orthoplastic centers. Statistical comparisons between center types were performed using appropriate tests (p < 0.05). Of 118 included studies, orthoplastic (n = 43) and vascular (n = 48) centers represented 77% of all studies. Recent increases in orthoplastic publications show substantial variability in organizational features. Orthoplastic center literature more frequently reported plastic surgery consultation criteria (p < 0.001), surgical outcomes (p < 0.001), and centralized network integration (p ≤ 0.006), highlighting acute reconstructive approaches. Vascular center studies documented significantly more organizational team features (p < 0.001) and quality systems (p = 0.033), reflecting established care frameworks for chronic disease management. Six organizational features characterized orthoplastic centers with > 70% prevalence, providing a benchmark framework with standardization priorities. Orthoplastic limb salvage centers demonstrate distinct care paradigms that benefit from standardization. Our findings suggest structural benchmarks to support the need for standardized development of orthoplastic limb salvage centers.
Glioblastoma is an aggressive primary brain tumor marked by rapid growth, invasiveness, poor prognosis, and an over 90 % tumor recurrence rate. Current radiation and chemotherapy treatments are limited by non-selectivity and toxicity, creating a need for safer complementary treatments. Historically, natural health products (NHPs) have been used medicinally across cultures for their anti-inflammatory and antioxidant effects. More recently, they have gained recognition for their selective, non-toxic properties in cancer treatment, suggesting their potential as adjuncts to conventional therapies. Black maitake (Grifola frondosa) extract, a well-tolerated NHP with known immunomodulatory properties, has demonstrated anticancer effects in breast cancer models. This study investigates the ability of Black Maitake Odaira Extract - Prothera (BMOE; a trade name of the extract manufactured by Shogun Maitake Canada, London, ON) to induce cell death in the U-87 MG glioblastoma cell line using 2D and 3D models, alone and in combination with the standard chemotherapy: temozolomide (TMZ). Apoptosis was assessed via Hoechst 33,342, annexin V, and propidium iodide staining, along with morphological analyses. Mitochondrial depolarization was measured using TMRM, cell migration was assessed via wound-healing assays, and structural integrity was evaluated using 3D spheroids. BMOE, alone and with TMZ, induced dose-dependent apoptosis, mitochondrial depolarization, and impaired glioblastoma cell migration. BMOE also disrupted 3D spheroid structures and promoted nuclear condensation, consistent with apoptotic processes. Most notably, BMOE significantly enhanced the anti-cancer effects of TMZ. These findings support the potential of BMOE as a complementary therapy that enhances the efficacy of current glioblastoma treatments.
Optical Chemical Structure Recognition (OCSR) aims to convert two-dimensional molecular images into machine-readable formats such as SMILES strings. Deep learning has substantially improved OCSR performance, yet most methods rely on synthetic training data and struggle to generalize to real-world inputs, especially hand-drawn diagrams, where stroke width, geometry, and drawing conventions vary widely across individuals. In this work, we propose an image-to-graph model AdaptMol that enables effective transfer from synthetic to real-world data without requiring manual graph annotations in the target domains. AdaptMol is an integrated pipeline that starts with training a base model on synthetic data, and then refines model representations through unsupervised domain adaptation and self-training. Our key insight is that bond features are domain-invariant in nature; they encode structural relationships between atoms that are independent of visual variations across domains. Thus, during domain adaptation, we align bond-level feature distributions via class-conditional Maximum Mean Discrepancy (MMD) to enforce cross-domain consistency. We also design a comprehensive data augmentation strategy to enhance the robustness of the base model, facilitating stable self-training on unlabeled target samples. On hand-drawn molecular images, our model achieves 82.6% accuracy and outperforms the best prior method by 10.7 points, while maintaining competitive performance across four benchmarks comprising molecular images from scientific literature and patent documents.Scientific contributionWe propose AdaptMol, an image-to-graph model that predicts molecular structures as graphs of atoms and bonds, achieving effective transfer from synthetic to hand-drawn molecular images without requiring target domain graph annotations. We combine class-conditional Maximum Mean Discrepancy to align bond features across domains with comprehensive data augmentation to increase training data variation, jointly improving base model accuracy sufficiently for self-training and addressing the critical failure mode of prior approaches that begin with insufficient accuracy. We further introduce a dual position representation that supervises atom positions through both discrete coordinate tokens and continuous spatial heatmaps to reduce false positives in atom localization.
Accurate localization of wireless capsule endoscopy is essential for reliable gastrointestinal diagnosis, yet magnetic tracking systems are often degraded by sensor distortions, misalignment, and patient motion in wearable settings. This study presents a magnetic localization framework that combines cylindrical magnetic field modelling with neural network-based sensor calibration to improve robustness under wearable operating conditions. By exploiting the structural properties of cylindrical magnetic field representations, the proposed approach decouples axial and transverse components of the magnetic field, enabling staged estimation of magnetic capsule position and orientation with improved numerical stability. A data-driven calibration model is employed to compensate for nonlinear sensor distortions arising from hard-iron effects, soft-iron effects, and dynamic misalignment. Experimental validation using a four-sensor wearable array demonstrates a mean static localization error of 0.12 cm and [Formula: see text], and a dynamic localization error of 0.20 cm and [Formula: see text], indicating improved performance under both stable and motion-affected conditions. These results suggest that accurate and robust magnetic capsule localization can be achieved with a minimal sensor configuration, supporting practical implementation in wearable capsule endoscopy systems.
Up to 80% of diffuse midline gliomas (DMGs) are characterized by a lysine to methionine driver mutation (K27M) in the tail of histone variant H3.3, pointing to likely roles for epigenetic mechanisms in K27M-driven tumorigenesis. Understanding the effects of mutant histone H3.3 on the complex patterns of histone modifications and interactions with chromatin structure and modifying enzymes is essential to developing effective combination treatment therapies for K27M DMG such as targeting multiple epigenetic enzymes at once. Here, using a genomics approach, we identified combinatorial patterns of epigenetic modifications that are affected by mutant H3.3 in DMG. We also characterized a strong association between H3.3 and the structural chromatin regulator CTCF, finding that mutant H3.3 leads to ectopic binding of CTCF at many additional sites across the genome in DMG. Notably, a number of these ectopic CTCF binding events occur within the HOX gene loci and are associated with an increase in H3K27me3 levels at bivalent domains and a decrease in HOX gene expression. We also find an association of H3.3 and CTCF at genomic sites adjacent to regions with active or repressive modifications, suggesting a potential role for these two factors in segmenting the chromatin and regulating, perhaps insulating, different types of domains. Together our data suggest that H3.3 K27M both affects epigenetic marks and chromatin organization in part through interaction with CTCF and point to a potentially novel contributory role for CTCF in promoting oncogenesis in DMG. These findings could have potential implications for designing therapy regimens to more effectively target the chromatin changes and genomic instability observed in H3.3K27M glioma cells.
Helical ladder polymers possess rigid, helically fused backbones that confer distinctive chiroptical properties, yet their integration into polymer brush architectures remains highly challenging. Here, we report the first synthesis of bottlebrush polymers with a helically fused ladder backbone, achieved through acid-catalyzed intramolecular cyclization followed by controlled ATRP grafting-from polymerization. By integrating a single-handed ladder scaffold with flexible, water-soluble PNIPAM side chains, the resulting architecture markedly enhances the processability and structural tunability of helical ladder polymers. Moreover, the traditional helical ladder, long regarded as completely rigid and static, has been found to exhibit dynamic transition properties. This change was caused by conformational triggering of the thermally driven binaphthyl dihedral angles, which was quantitatively confirmed by the thermodynamic dynamics and molecular dynamics simulations, demonstrating the hierarchy of the transition from axial chirality to helical chirality. Overall, this work establishes a promising synthetic method for helical ladder bottlebrush polymers and demonstrates their potential as versatile platforms for designing dynamic chiral materials.
Deep learning models for medical image analysis often rely on large-scale parameterization, which may limit their practical use in resource-constrained settings. This study aims to design a structurally compact multi-source framework capable of delivering competitive diagnostic performance with reduced computational overhead. We propose ML-ConvNet, a lightweight architecture comprising approximately 4.2 K parameters and 924 M FLOPs at 512×512 input resolution. The network incorporates Multi-Branch Re-parameterized Convolutions for scale-aware feature extraction, Hierarchical Dual-Path Attention for feature localization, Feature Self- Transformation for cross-feature interaction, and a Local Variance Weighted optimization strategy to address class imbalance. The framework is evaluated independently on three publicly available benchmark datasets representing heterogeneous imaging modalities: brain MRI, lung CT, and chest X-ray. Ablation studies, precision-recall analysis, cross-modality validation, and computational benchmarking are conducted to assess performance, stability, and efficiency under controlled experimental conditions. Within the evaluated settings, results indicate competitive diagnostic accuracy relative to established lightweight baselines, including EfficientNet and MobileNet variants, while substantially reducing parameter count. Class-wise F1-scores and PR-AUC values suggest relatively stable minority-class performance under repeated cross-validation sampling. Attention visualizations show activations concentrated over regions broadly associated with pathological findings, though these observations are qualitative in nature. Inference latency measurements on CPU and mobile hardware suggest feasibility for low-latency deployment under the tested single-image batch configurations, though real-world throughput may differ depending on hardware and operational conditions. These findings suggest that careful architectural design and domain-informed inductive biases may support competitive medical image classification on public benchmark datasets without extensive parameter scaling. The framework was evaluated exclusively under controlled conditions on publicly available data, and multi-institutional external validation is required before conclusions regarding generalizability or clinical applicability can be drawn.