Vascular stents require biointerfaces that simultaneously prevent thrombosis and promote endothelialization, yet achieving a balance of these conflicting demands on a single surface remains a challenge. While cell membrane coatings have demonstrated biomimetic potential, their application to macroscale devices has been largely limited to unstable noncovalent nanoparticle-focused approaches, which suffer from disordered assembly and poor stability under physiological flow. In contrast, we introduce a platelet membrane armor strategy facilitated by epigallocatechin gallate (EGCG) cross-linking, creating a robust macroscale coating that integrates both antithrombogenicity and proendothelialization. This covalent stabilization, achieved through EGCG’s unique chemistry, effectively anchors platelet membrane vesicles to form a stable coating that ensures uniform modification across various substrates. The coating is resistant to mechanical deformation and maintains its structural continuity even after over 30 d of rinsing. Importantly, the EGCG-cross-linked platelet membrane (EPM) coating preserves functional membrane proteins (CD47 and integrins). When stents coated with EPM armor were implanted in rabbits, they exhibited a marked reduction in acute thrombus formation, alongside enhanced endothelial cell proliferation and anti-inflammation effects, without introducing smooth muscle cell hyperplasia. This EPM coating strategy offers a promising approach to biomimetic interfaces for cardiovascular implants.

Alkenes are fundamental structural motifs in organic synthesis, valued for their prevalence in natural products and their broad reactivity profile. While traditional de novo synthesis offers access to diverse alkene frameworks, strategies enabling the direct structural remodeling of alkenes offer more concise and efficient alternatives, yet remain underdeveloped. Herein, we present a molecular recasting strategy for alkene diversification, enabled by N-heterocyclic carbene/photoredox dual catalysis. The transformation involves a sequential dealkenylative acylation and realkenylation cascade, realizing precise and modular reassembly of a broad spectrum of alkenes under mild conditions. This approach demonstrates exceptional generality, accommodating up to trisubstituted alkenes, and supports interconversion among diverse alkene frameworks, as well as late-stage functionalization of complex bioactive molecules. Mechanistic investigations reveal a radical-mediated catalytic pathway and shed light on the synergy of photoredox and N-heterocyclic carbene dual catalysis. This work provides a conceptually different and synthetically valuable platform for alkene editing.

Sepsis is a life-threatening syndrome caused by dysregulated host response that culminates in organ dysfunction. Recognizing that many prior reviews treated neutrophils as largely homogeneous or discussed their functions in isolation, we present a framework centered on emergency granulopoiesis that unifies groundbreaking single-cell multi-omics discoveries, bone marrow niche remodeling, and bedside biomarkers such as the immature-to-total neutrophil ratio and sepsis endotypes to explain the shift from defense to dysfunction. As a hallmark adaptation, emergency granulopoiesis rapidly replenishes neutrophils but paradoxically yields immature neutrophils with impaired chemotaxis, excessive neutrophil extracellular trap formation (NETosis)/reactive oxygen species, and immunosuppressive activity that aggravate tissue damage, organ failure, and late immunoparalysis. We synthesize subset-level diversity and map this diversity to transcriptional shifts coupled with epigenetic and metabolic reprogramming as well as stromal inflammation. Clinically, elevated immature-to-total neutrophil ratios and these immature subsets align with disease severity and mortality, supporting biomarker-guided stratification. Stage-specific therapeutic strategies are evaluated along the continuum of emergency granulopoiesis, calibrating NETosis, and modulating metabolic reprogramming and epigenetics to restore neutrophil homeostasis. Furthermore, we delineate testable priorities for future research such as standardizing immature neutrophil phenotyping across cohorts and defining harmonized immature-to-total neutrophil ratio thresholds. By explicitly centering emergency granulopoiesis and integrating single-cell biology with bedside indicators, this review clarifies why a protective program becomes maladaptive in sepsis and outlines practical avenues for targeted interventions and trial design.

With the significant transformation in the classification, risk stratification, and therapy standards for gliomas in recent years, we sought to reintegrate clinical data, whole-exome sequencing data, and magnetic resonance imaging data from glioma patients to further analyze their impact on overall survival. We identified 798 primary gliomas: 355 glioblastomas, 179 IDH1/2-mutant astrocytomas, 135 oligodendrogliomas, and 129 other IDH1/2-wild-type gliomas. Kaplan–Meier analysis revealed that our cohort showed significantly prolonged survival compared to the CGGA/TCGA cohorts (median: 85.2, 60.4, and 50.5 months; P < 0.0001). Molecular reclassification criteria yielded altered final histopathologic classification for 23.7% of gliomas. Molecular alterations differ among glioma subtypes. Among the 5 tumorigenic pathways analyzed, glioblastomas exhibited the highest average number of activated pathways (mean: 2.17), followed by astrocytomas (mean: 1.40) and oligodendrogliomas (mean: 0.42). In one glioma subtype, upstream and downstream gene activations in the same pathway are mutually exclusive. In this large-scale Chinese cohort, we first confirmed a strong link between tumor location and molecular subtype: Frontal gliomas had IDH1/2 mutations in 63.5% of cases, while temporal (80.3%) and thalamic/basal ganglia gliomas (90.4%) were predominantly IDH1/2-wild-type. Age stratification confirmed these patterns: 74.7% of frontal gliomas in younger patients (<46 years) had IDH1/2 mutations versus 91.4% of temporal and 100% of thalamic/basal ganglia tumors in older patients (≥46 years) being IDH1/2-wild-type. Contemporary molecular criteria modified diagnoses in ~25% of cases. Contemporary glioma cohorts showed prolonged survival outcomes compared to historical cohorts. An association between anatomic localization and molecular subtypes was also established in this Chinese glioma cohort.

Programmable metasurfaces show great application potential in many fields, so studying their radar cross-section reduction (RCSR) characteristics is very important. Metasurfaces based on polarization conversion and artificial magnetic conductors are widely used for RCSR, but they cannot scan beams. Programmable metasurfaces can dynamically steer beams in-band and reduce RCS by changing the phase of electromagnetic waves. But to meet practical needs, they must be stealthy both in-band and out-of-band. This paper presents a low-profile self-stealth programmable metasurface. Self-stealth describes the capability of the metasurface to achieve in-band and out-of-band RCSR through its intrinsic design, without requiring additional structures such as radomes or absorbing materials. The design principle is to achieve out-of-band RCS reduction without increasing the profile height or adding extra radio frequency components. The meta-atom has a positive-intrinsic-negative (PIN) diode to control the in-band (f₀) x-polarization phase. Switching the PIN diode states gives 1-bit phase modulation. The in-band y-polarization uses a bridge design. Changing the size can get 1-bit phase, and the x- and y-polarizations can be adjusted separately. Also, the top layer has 4 cross-shaped dumbbells and 4 branch structures for out-of-band high (fh₁) and low (fl₁) frequencies. The middle layer has four 45° rotated cross-shaped dumbbells and 4 branch structures for out-of-band high (fh₂) and low (fl₂) frequencies. So, the meta-atom can modulate phase across 5 frequency bands (fl₂ < fl₁ < f₀ < fh₂ < fh₁). The profile height is 0.065λ of the in-band center frequency, which is more conducive to conformal design. A 12 × 12 prototype was made. Simulation and measurement show that the metasurface reduces RCS in 5 bands and its in-band radiation can be used in communication transmission mode, which is good for programmable metasurface technology development.

Radiation-induced skin injury (RISI) is a common and debilitating complication of radiotherapy, characterized by persistent inflammation and delayed wound healing. Macrophages play a central role in this process; however, the molecular mechanisms governing their dysfunction under radiation stress remain poorly understood. To elucidate the role of triggering receptor expressed on myeloid cells 2 (TREM2) in macrophage regulation after irradiation, we combined single-cell RNA sequencing, in vivo mouse models, and in vitro macrophage assays. Conditional knockout mice (LysM^CreTrem2^flox/flox) were used to selectively delete Trem2 in macrophages. Radiation induced a distinct TREM2⁺ macrophage subset; however, despite elevated Trem2 mRNA, protein levels declined due to ADAM17-mediated shedding driven by radiation-induced reactive oxygen species (ROS) accumulation and NRF2 activation. Inhibition or small interfering RNA (siRNA)-mediated knockdown of ADAM17 restored TREM2 protein expression, reduced soluble TREM2 release, improved macrophage survival, and promoted anti-inflammatory M2 polarization. Conversely, Trem2 deficiency enhanced apoptosis, sustained inflammation, and delayed wound healing, whereas Trem2 overexpression or local adoptive transfer of TREM2⁺ macrophages accelerated tissue repair. Mechanistically, TREM2 conferred radioprotection through extracellular signal-regulated kinase (ERK) pathway activation, linking the ROS–NRF2–ADAM17 axis to TREM2–ERK signaling in macrophage survival and polarization. Collectively, these findings identify a novel regulatory cascade, ROS–NRF2–ADAM17–TREM2–ERK, that governs macrophage fate under irradiation. Targeting this pathway or supplementing TREM2⁺ macrophages may offer promising therapeutic strategies for mitigating RISI.

D–π–A-type fluorescent materials are crucial tools in life sciences and medicine, with their development hinging on a precise understanding of fluorophore mechanisms, particularly twisted intramolecular charge transfer (TICT) and planar intramolecular charge transfer (PICT) processes. These fluorophores exhibit unique charge transfer properties, making them highly valuable in organic optoelectronics, fluorescent probes, and sensors. However, despite their growing applications, the structural essence of TICT and PICT fluorophores remains poorly understood. This often results in molecules with similar structures displaying charge transfer modes that contradict design expectations, substantially hindering the application of TICT and PICT fluorescent probes. In this study, we meticulously designed various computational strategies based on interpretable machine learning to thoroughly deconstruct the chemical structural essence of TICT and PICT fluorophores. Utilizing the first real-world TICT and PICT dataset, we constructed predictive models that balance both interpretability and accuracy (area under the receiver operating characteristic curve = 0.846) using a range of algorithms, including deep learning. We established artificial intelligence (AI)-guided rules comprising 5 structural factors—electron-donating group strength, electron-withdrawing group strength, alkyl cyclization, steric hindrance, and solvent–solute interactions—that influence TICT and PICT. These rules provide obvious guidance for probe design based on molecular rigidity and charge transfer driving forces. Compared to community-suggested rules, the AI-guided rules achieved an over 20% improvement in accuracy in a controlled evaluation. By applying these rules, we successfully synthesized and validated several representative fluorophores that are challenging to distinguish using chemical intuition alone. Both quantitative calculations and experimental results confirmed the accuracy of the model and the practicality of the AI-guided rules. This novel approach is expected to establish a novel paradigm for exploring ideal TICT and PICT molecules, offering a robust framework for future research and application in fluorescent materials.

Accurate prediction of drug–target molecular recognition is essential for early-stage drug discovery, spanning binding occurrence, binding site localization, and binding affinity estimation. However, current approaches frequently treat these tasks independently, thereby overlooking the shared mechanistic principles that underlie them. We present DTBind, a unified and mechanism-driven framework that hierarchically adapts to sequence, structure, and complex-level inputs for predicting binding occurrence, site, and affinity, grounded in the shared mechanistic determinants of molecular recognition. Comprehensive benchmarking demonstrates that DTBind achieves superior performance over state-of-the-art methods in terms of accuracy and generalizability. Analysis of hierarchical protein encodings demonstrates that determinant-based protein representations gradually drive the accurate prediction of molecular recognition. Validation based on molecular dynamics simulations shows that DTBind reliably predicts drug–target binding regions for 3 famous proteins that lack experimental structures.

Terahertz (THz) amplification presents promising potential for various innovative applications. Here, we achieve an ultra-broadband and high-gain THz amplification from 0.1 to 25 THz with a saturated electric field peaking at 10⁷ V/m by leveraging drift-induced plasmon instability in a single-layer gated graphene system. The plasmon instability arises from the electron concentration modulation due to the nonuniformity of the electron–phonon scattering rate distribution on the Fermi surface. The modulation will introduce increments to compensate for the plasmon loss and even achieve plasmon amplification. Specifically, we derive the nonreciprocal plasmon dispersion using Maxwell’s equations in conjunction with the Boltzmann transport equation, incorporating interactions between electrons and phonons. We find that the amplifying plasmon mode propagates against the electron drift velocity, and the amplification efficiency can be tuned by adjusting either the electron concentration or the electron drift velocity. Furthermore, the simulation shows that when the fundamental mode is amplified to saturation, higher harmonics are generated and amplified, forming a THz frequency comb. These results provide a promising avenue for developing tunable on-chip THz light sources, amplifiers, and frequency comb generators within integrated plasmonic systems.

The origin of life (OoL) is a fundamental and long-standing scientific question. Although a variety of plausible hypotheses had been put forward, how life began on the prebiotic Earth from a pile of prehistoric inert chemicals (gases) is still a puzzle to us. Here, to unify the existing hypotheses to cover the entire scenarios, the author proposed the “nanozymes hypothesis” of the OoL on Earth, in which natural mineral nanozymes (MN-zymes) and their later upgraded organic/inorganic hybridized nanozymes played multiple key roles in the initial emergence of life molecules, especially in the manner of “inorganic photosynthesis” under primitive Earth conditions. Under the hypothesis framework, proteins, DNA, and RNA might emerged near-simultaneously, as a result of the diversity of nanozymes and catalyses, and multiple physical and chemical key roles of the MN-zymes. Besides nanozyme aspects, several fundamental and key issues on the topic are briefly discussed and several essential elements and conditions for the natural selection and survival of life molecules are proposed.