Browse Articles

Tunable Microporous Bimetallic Carboxylate-Pyrazolate Metal–Organic Frameworks for CO ₂ Capture

A privacy-aware healthcare framework with model pattern-deviation detection for heart-disease prediction using L2-GNAE and PDDP

Abstract Sensitive patient data protection is essential to ensure medical reliability in healthcare. Yet, the traditional studies didn’t analyze the deviation in the shared model pattern, thus resulting in poor diagnosis. Therefore, this article proposes a privacy-aware healthcare framework with model pattern deviation detection for Heart Disease (HD) prediction using L2 Gini Norm Auto-Encoder (L2-GNAE) and Polynomial Differential Decay Privacy (PDDP). Firstly, the patients are registered into the healthcare applications, followed by data sensing, data encryption, and hash code generation. Meanwhile, to authenticate the data integrity, the data decryption and hash code verification are done. During testing, the verified data is subjected to the trained proposed local model for HD prediction. Next, to perform model privacy, PDDP is used. Afterward, to effectively classify the HD, the Triple Gated Lipschitz Recurrent Unit (TGLRU) is utilized. Also, the local model gradients are updated in the global model, where L2-GNAE is utilized to detect the deviations in the shared model pattern. If the deviation is detected, then the alert is sent to the hospital; otherwise, the model update is carried out. The experimental testing of the proposed framework is done by using the “Heart Disease Prediction Dataset”. From the validation, the proposed framework achieves 99.2145% accuracy, 99.0237% precision, and 99.1046% F-measure during HD prediction. Thus, the proposed work significantly outperforms the traditional works by obtaining a high security level (256 bits) with enhanced privacy-preserved HD prediction in healthcare maintenance.

Inhalable Polymeric PROTAC Nanococktail for Targeted Protein Degradation in Idiopathic Pulmonary Fibrosis

Neonatal hypoxic ischemia in rats induces myelin injury and structural lateralization of sensorimotor connectivity

Abstract Neonatal hypoxic ischemia (HI) around the birth impairs structural and functional networks in the whole brain, leading residual motor impairment necessary for therapeutic intervention. Myelin, which is essential for sensorimotor functional improvement, increases around the birth but is susceptible to HI. However, the involvement of myelin injury in the structural network changes in the brain after HI remains unclear. To investigate this issue, we clarified the relationship between the brain’s structural network and myelin injury by using HI rat model. The HI rat model was established by transecting the right common carotid artery (CCA) and exposure to a hypoxic environment containing 8% oxygen for 90 minutes. Using ex vivo diffusion tensor imaging (DTI) and immunohistology, the changes in myelin sheaths in the corpus callosum (CC) and the structural network of the whole brain were analyzed. HI rats showed significantly decreased fractional anisotropy and increased radial diffusivity in the CC ipsilateral to CCA transection compared with the Sham group (n = 6/group, p < 0.05, respectively). Immunohistology revealed a decreased myelin density in the ipsilateral CC of HI rats compared with the Sham group ( n = 6/group, p < 0.05). Furthermore, in structural connectome analysis, HI rats showed significantly decreased connectivity in the ipsilateral hemisphere compared with Sham group ( p < 0.01). Particularly, the ipsilateral M1-S1 and bilateral S1-striatum connectivity of HI rats showed significantly reduced tract numbers compared with Sham rats ( p < 0.05, respectively). These results suggest myelin damage following HI disrupts structural connectivity in the ipsilateral hemisphere, including the M1-S1 and S1-striatum connectivity. Furthermore, these findings identified the S1-centered structural network alterations as key contributors to brain dysfunction, such as motor impairment, after HI, and could highlight these networks as potential targets for therapeutic interventions to promote functional recovery.

Repetitive Ethylene Insertion into the Pd–OAc Bond: Synthesis of Heterotelechelic Polyethylene and Effective Copolymerization of Ethylene with Vinyl or Allyl Acetate

Cloud point thermodynamics and phase behavior of EVOH–DMSO systems for selective polymer recycling

Abstract Understanding phase behavior of polymer-solvent mixtures is crucial for applications ranging from plastic recycling to crude oil extraction from reservoirs. One method for investigating polymer-solvent solution behavior is through understanding the cloud point thermodynamics. In this study, the cloud points of three different grades of ethylene vinyl alcohol (EVOH) copolymers (27 mol%, 32 mol%, and 48 mol% ethylene content) are characterized in dimethyl sulfoxide solutions for two conditions: isobaric-non-isothermal and isothermal-non-isobaric. Notably, increasing ethylene content in the EVOH copolymer shifts the cloud point to higher temperatures and pressures. Additionally, cloud points for EVOH in DMSO/Water (solvent-antisolvent) mixtures were characterized to optimize solvent use and polymer recovery. The combined cloud point data is used to construct a working phase diagram, delineating an EVOH grade-based separation zone, defining a boundary between homogenous and phase separated regions. These results contribute to our understanding of EVOH solution phase behavior and are critical for optimizing solvent requirements for selective polymer recycling technologies, enhancing dissolution efficiency, and sustainability in polymer processing. Furthermore, insights into the phase separation behavior of EVOH support more efficient separation strategies in multilayer packaging systems, enabling targeted extraction of EVOH from complex waste streams and facilitating high-purity recovery for reuse.

Daily briefing: Mountain bongos still roam the forest

Supramolecular Integration of 18-Crown-6 and an N-Capped Short Peptide Enables Multivalent Recognition and Modulation of Amyloid-β Proteotoxicity

Influence of molecular structure and size of cyclic and spherical carbon allotropes on high-order harmonic generation efficiency: a TDDFT study

Chromatin landscape and epigenetic heterogeneity of acute myeloid leukaemia

Revealing the Topological Analogy between End-Linked and Pendant Cross-Linked Polymer Networks for Mechanophore-Enabled Toughening

Public genomic surveillance of African Klebsiella pneumoniae species complex reveals uneven sampling and high ESBL gene carriage

Diet–microbiome synergy underlies obesity-associated immunotherapy efficacy

Revisiting Purported Solvothermal “Black Phosphorus”: Beyond Elemental Allotrope to Organic Ammonium Polyphosphides

l-Tartaric acid mitigates diabetic cardiac damage and is associated with changes in autophagy, apoptosis, and inflammatory markers

Intergenerational mobility fosters innovation in Europe

S-to-O Atom Swapping Unlocks a Promising Difuranphthalimide-Based Polymer Donor with Efficiency over 20%

Synergistic effect of carbon fabric metastructure and magnetic layers in a composite for electromagnetic radiation shielding

Abstract The widespread use of high-frequency electromagnetic radiation (EMR) in communication, defense, medical, and household technologies raises health and safety concerns, underscoring the demand for efficient shielding and absorption materials. This work presents flexible protective composites based on conductive carbon fabric coated with thin magnetic polymer films. Several multilayer configurations were prepared and characterized, consisting of carbon fabric coated with epoxy polymer layers containing Ni or Fe $$_2$$ O $$_3$$ fillers. The shielding performance, primarily governed by the fabric’s regular metastructure, exhibits strong polarization dependence in the $$90-330$$ GHz range. The combined interaction of conductive carbon fabric and magneto-responsive polymer layers enhances absorption, induces multiple resonances, and broadens the effective shielding bandwidth, resulting in significantly reduced reflection across a wide spectral range.

Architecture of the 8 MDa Hdr–Vhu–Fwd super-assembly in class I methanogens

Abstract Methanogens are central to global carbon cycling and among the largest biological sources of methane, a potent greenhouse gas 1 . At the heart of their energy metabolism lies the Hdr–Vhu–Fwd super-assembly, which couples H 2 oxidation with CO 2 reduction through flavin-based electron bifurcation. Here we present the cryogenic electron microscopy structure of the Hdr–Vhu–Fwd super-assembly from Methanococcus maripaludis , revealing an 8 MDa complex comprising 252 polypeptide chains and over 600 redox cofactors. Cryo-electron tomography further support that this super-assembly forms an intact structure within the cytoplasm of intact cells. This architecture comprises two hexameric HdrABC–Vhu rings linked by a tetrameric FwdF core, forming a continuous, circular electron chain. In this unique arrangement, 12 polyferredoxin subunits (VhuB) connect the Vhu–Hdr and Fwd complexes, thereby coupling electron bifurcation with CO 2 reduction and directly linking the last and the first step of methanogenesis. Moreover, we identify a modular variant of the complex in which the [NiFe]-hydrogenase Vhu is substituted by tungsten-containing formate dehydrogenase (FdhAB), indicating flexible integration of electron-input modules facilitating metabolic adaptation under diverse environmental conditions 2 . Analysis of the taxonomic distribution reveals that this architecture is specific to class I methanogens and is distinct from the smaller Hdr–Fmd complex of class II 3 . Together, our study reveals that the the Hdr–Vhu–Fwd super-assembly has a modular and adaptable bioenergetic assembly, suggesting a lineage-specific architecture to adapt to diverse anaerobic niches.

Correction to “Photoactive Iminobismuthanes for Catalytic C–H Amination”