搜索结果：Molecular biomedicine

Biogenic amine surveillance is central to food safety and clinical diagnostics, yet real-time, selective detection of spermine (SPM) remains challenging due to molecular similarity among amines and probe instability in complex matrices. Here, we report a reusable, wavelength-shift-responsive fluorescent probe based on two-dimensional azene nanosheets (2D-Azeno NSs), synthesized through a Schiff condensation route followed by ultrasonic exfoliation. The robust, π-extended framework exhibits intense green photoluminescence (λem = 501 nm) and achieves an ultralow detection limit of 4.35 nM via a unique ratiometric fluorescence response accompanied by a distinct hypsochromic shift. Mechanistic interrogation, supported by DFT calculations, reveals that selective sensing arises not from conventional Inner Filter Effects but from site-specific, cooperative hydrogen bonding between the polyamine functional groups of SPM and the N-H/C═N sites of the 2D-Azeno scaffold. This supramolecular recognition selectively perturbs the Intramolecular Charge Transfer (ICT) pathway, leading to a measurable widening of the frontier orbital energy gap creating a Hydrogen-bond induced charge transfer modulation (HICTM) sensor. Furthermore, this sensing pathway is inherently reversible; acid fuming protonates the amine sites, disrupting the H-bond network and fully regenerating the initial emission state over nine operational cycles. This work establishes a paradigm for supramolecular control over a solid-state electronic structure in rigid 2D organic materials, offering a generalizable design principle for developing robust, regenerable, and high-fidelity optical sensors applicable to environmental monitoring and precision biomedicine.

Manipulation of ligand-receptor interactions (LRIs) in a user-defined manner is one of the effective ways to regulate cell motility and disease progression. Molecular engines orchestrate LRIs to regulate cell motility by harnessing various forms of energy within physiological surroundings. However, engineering chemical engines remains largely unexplored, primarily due to the insufficient chemical cue density, uncertain conformational changes of scaffolds, and a limited repertoire of environment-responsive switchable scaffolds. Enzymatic biofuel cells (EBFCs) are electrochemical devices that convert biofuels into other accessible energy through electrochemical reaction for the construction of self-powered molecular tools, offering a viable strategy to overcome the above limitations. Here, we present an enzyme biofuel cell-based self-powered molecular engine (EBFC-SME) for rewiring chemical cues-based LRIs and regulating cell motility. We employ EBFC-SME as a proof-of-concept platform for reprogramming proton-responsive HGF/c-Met interaction. The system comprises a glucose dehydrogenase (GDH)-incorporated bioanode and a bilirubin oxidase (BOD)/functional nucleic acids (FNAs)-encapsulated iron-alginate (IA) hydrogel-coated biocathode. Through glucose-initiated redox reactions, this configuration enables the EBFC-SME to generate abundant protons and release FNAs. These products subsequently mediate the in-situ assembly on tumor cell membrane, which blocks c-Met pathway activation and ultimately suppresses tumor cell migration. Different from conventional chemical engines, the EBFC-SME efficiently regenerates chemical cues via intrinsic energy conversion reactions for the manipulation of scaffold-mediated LRIs. This EBFC-SME platform provides a robust "sensing-conversion-initiation" tool for the chemical regulation of cellular motility, holding significant promise in precision biomedicine.

Rice (Oryza sativa L.) is highly susceptible to drought and salinity, two major abiotic stresses that severely constrain global productivity under climate change. Endophytic microorganisms have emerged as promising biological tools for enhancing stress tolerance; however, their mechanisms and field applicability in rice remain insufficiently integrated. This review synthesizes current advances in rice-endophyte interactions with a specific focus on mechanistic and functional outcomes. Evidence from bacterial and fungal endophytes, including Bacillus, Pseudomonas, Enterobacter, and Trichoderma spp., demonstrates improved drought and salinity tolerance through measurable traits such as enhanced root architecture, increased water-use efficiency, maintenance of Na+/K+ homeostasis, and improved biomass and yield stability. These effects are mediated via key pathways including ACC deaminase activity (ethylene regulation), modulation of antioxidant systems (SOD, CAT, APX), osmolyte accumulation, and hormonal crosstalk involving abscisic acid (ABA), indole-3-acetic acid (IAA), and gibberellins. Under salinity, endophytes contribute to ion homeostasis through regulation of transporters such as HKT1;5, while under drought they enhance hydraulic conductivity via aquaporin regulation through plasma membrane intrinsic proteins (PIPs) and tonoplast intrinsic proteins (TIPs). Despite promising results under controlled conditions, inconsistencies in field performance remain a major limitation due to genotype dependence, environmental variability, and challenges in colonization and inoculum stability. This review integrates molecular, physiological, and applied perspectives and proposes a framework for linking rice genotype, endophyte function, and environmental conditions to improve reproducibility and field-scale application. These insights provide a foundation for developing climate-resilient rice systems through targeted microbial inoculants.

Understanding sex-dependent differences in disease risk, manifestation, and treatment response is essential for precision medicine. While funding agencies now mandate consideration of Sex as a Biological Variable (SABV), existing bioinformatics tools lack systematic approaches to characterize sex-related molecular mechanisms. Current practices frequently treat sex as a confounding variable, which may obscure important biological differences such as sex-specific alterations, sex-dimorphic changes (opposite effects between sexes), and sex-modulated changes (different effect magnitudes). We present XYomics, an open-source R package for systematic analysis of sex-dependent alterations in biomedical omics data. The software identifies sex-specific, sex-dimorphic, and sex-modulated changes at both individual feature and systems levels. XYomics implements dual analytical modes: sex-disease interaction term modeling for adequately powered datasets and sex-stratified analysis with robust non-significance filtering for smaller sample sizes. Using single-cell RNA sequencing data from Alzheimer's disease patients, we demonstrate how XYomics identifies sex-dimorphic genes largely undetected by standard sex-averaged analyses. By integrating statistical categorization with pathway enrichment and network analysis using a curated hormone signaling interactome, the software facilitates discovery of sex-specific biomarkers and disease mechanisms frequently obscured in sex-aggregated analyses.

Chiral molecular materials with strong magneto-optical responses in the near-infrared III (NIR-III, 1600-2500 nm) region are attractive for applications in photonics, biomedicine, and advanced optical materials, but molecular magneto-optical phenomena in this spectral window remain largely unexplored. Here, we report six pairs of chiral 3d-4f molecular clusters, R/S-Ln3Mn4 and R/S-Ln12Mn12 (Ln = HoIII, TbIII, and YIII), and systematically investigate their chiroptical and magneto-optical properties in the NIR-III region. Circular dichroism (CD) and magnetic circular dichroism (MCD) spectroscopy reveal that R/S-Ho3Mn4 and R/S-Ho12Mn12 clusters exhibit pronounced CD and MCD responses in the NIR-III region arising from long-wavelength HoIII f-f transitions, whereas R/S-Tb3Mn4 and R/S-Tb12Mn12 show strong MCD responses but no resolved CD signals. These findings identify long-wavelength lanthanide f-f transitions as the origin of the NIR-III chiroptical and magneto-optical activity. Notably, the R/S-Ln12Mn12 series exhibits larger gMCD values and stronger NIR-III MCD responses than the corresponding R/S-Ln3Mn4 analogues. This enhancement may arise from the change in local LnIII coordination geometry from D4d in Ln3Mn4 to D2d in Ln12Mn12, which favors a stronger Zeeman-perturbed MCD response, along with cooperative LnIII-MnII weak magnetic interactions in Ln12Mn12. This work provides the first molecular example of f-f-transition-driven chiroptical and magneto-optical activity across the NIR-III window and establishes chiral 3d-4f clusters as structurally defined platforms for tuning long-wavelength magneto-optical responses.

Complex traits and diseases are highly polygenic and understanding the full set of genes involved is a central challenge in biomedicine. However, due to sample size limitations and noise (technical and biological), experimental approaches for disease-gene discovery such as transcriptomics and GWAS result in long, noisy, heterogeneous gene lists, which may be trimmed to a subset of likely relevant genes while leaving several false negatives. Computational gene classification approaches, especially those using genome-scale molecular interaction networks, are promising avenues for complementing such experimental findings by analytically expanding observed gene lists based on the functional relatedness between genes. We previously introduced the network-based gene classification approach, GenePlexus, which was rigorously benchmarked to show state-of-the-art performance, especially for predicting novel genes associated with biological processes and fine-grained phenotypes. Network-based gene classification performance, however, declines for diseases, especially when the inputs are omics and GWAS-based long gene lists. Here, we show that such disease gene lists span multiple biological processes spread across the molecular network and propose ModGenePlexus, a new network-based gene classification method that takes a two-stage approach. First, clustering and semi-supervised learning decomposes the input gene list into coherent denoised network gene modules. Then, ModGenePlexus trains supervised (GenePlexus) classifiers for each module and aggregates predictions to return genome-wide rankings. We benchmarked ModGenePlexus across simulated data, transcriptomic signatures, and GWAS datasets (together spanning hundreds of diseases), showing improved recovery of known disease genes compared to GenePlexus. Beyond improved classification, the results of enrichment analysis of ModGenePlexus outputs are much more interpretable by virtue of revealing nuanced biological processes. Together, these results establish ModGenePlexus as a scalable, interpretable tool for gene classification of GWAS and -omics derived genelists across diverse biological contexts. ModGenePlexus is freely available on GitHub at https://github.com/krishnanlab/ModGenePlexus, and the full source code and results supporting this study are available on Zenodo at https://zenodo.org/records/19857910. Supplementary data are available at Bioinformatics online.

Although adding immune checkpoint inhibitors to neoadjuvant chemotherapy improves outcomes in high-risk early-stage breast cancer, opportunities remain to further enhance response. Dual checkpoint blockade offers a potential strategy to further enhance efficacy. To evaluate the combination of anti-programmed cell death 1 protein (PD-1) cemiplimab and anti-lymphocyte activation gene 3 (LAG-3) added to neoadjuvant therapy in ERBB2-negative early-stage, high-risk breast cancer. The I-SPY2 (Investigation of Serial Studies to Predict Your Therapeutic Response With Imaging and Molecular Analysis 2) is an ongoing randomized clinical platform trial being conducted at multiple US clinical sites including patients with early-stage (II or III) ERBB2-negative, high-risk breast cancer. Participants, continuously enrolled since 2010, were adaptively randomized from February 2, 2020, to December 9, 2021, to one of several experimental neoadjuvant therapies or control groups based on receptor subtypes defined by hormone receptor (HR), ERBB2 status, and MammaPrint (Agendia Inc) molecular risk, categorized as high (MP1) or ultrahigh (MP2). Data were analyzed from January 1, 2022, to August 5, 2025. Both groups received weekly paclitaxel for 12 weeks, then doxorubicin and cyclophosphamide followed by surgery; concomitant with paclitaxel, the intervention group also received 4 doses of cemiplimab and fianlimab (PCF) every 3 weeks. Pathologic complete response (pCR). Treatments graduated when they achieved 85% bayesian probability of success in a subtype-specific phase 3 trial. Pathway-specific biomarkers were assessed for response prediction. A total of 78 participants (mean [SD] age, 47 [39-54] years) were randomized to the intervention group, with 350 participants (mean [SD] age, 48 [39-57] years) randomized to the historical control population. PCF graduated in all clinical signatures, with pCR rates vs control of 44% (95% CI, 34%-53%) vs 21% (95% CI, 17%-25%) in all ERBB2, 53% (95% CI, 39%-67%) vs 29% (95% CI, 22%-36%) in triple-negative, and 36% (95% CI, 23%-49%) vs 14% (95% CI, 9%-19%) in HR-positive and ERBB2-negative disease. Among the total participants, 16 (21%) experienced adrenal insufficiency, including hypophysitis (11% grade 3 or 4), mostly occurring after immunotherapy completion. PCF was found to be highly effective in the subset of patients with immune signature positive status (ImPrint positive). In this randomized clinical trial, the combination of PD-1 and anti-LAG-3 inhibition with standard NAC was effective in early-stage ERBB2-negative breast cancer, particularly in patients displaying a positive ImPrint immune signature. These results warrant further definitive trials. ClinicalTrials.gov Identifier: NCT01042379.

Despite influenza vaccines being widely available, influenza still causes significant morbidity and mortality annually. Vaccines typically induce humoral-mediated protection against rapidly mutating surface glycoproteins, necessitating that they be updated and administered each year. In contrast, CD8+ T cells, which can control and clear viral infections, can recognise more conserved viral epitopes. Therefore, there is considerable interest in understanding CD8+ T cell responses to influenza virus for the development of future vaccines and therapeutics. Although Alphainfluenzavirus influenzae (FLUAV) and Betainfluenzavirus influenzae (FLUBV) co-circulate in humans and both contribute to seasonal epidemics, there is limited data regarding CD8+ T cell responses to FLUBV. This knowledge gap spans both immunological and molecular insights. In the present review, we summarise the current knowledge of FLUBV-derived CD8+ T cell epitopes at both cellular and molecular levels, in comparison with FLUAV. Collectively, this highlights the limited data available on FLUBV, despite its significant role in human influenza infections.

Among molecular imaging techniques, 19F magnetic resonance imaging (19F MRI) is particularly attractive due to deep penetration and multiplexed molecular imaging. However, the further development of 19F MRI remains constrained by its limited sensitivity, which largely depends on fluorinated probe design and more fundamentally on the availability of high-performance fluorinated moieties that define probe signal intensity. Here we systematically establish 3,5-bis(2-hexafluoro-isopropoxy)phenyl (BHFIP) as a structurally simple yet highly capable fluorinated moiety for 19F MRI probe design. Starting from 1,3-bis(2-hexafluoro-isopropoxy)benzene, a simple two-step nitration-reduction procedure afforded 3,5-bis(2-hexafluoro-isopropoxy)aniline (BHFIP-NH2), a modifiable BHFIP-based building block. Besides its high fluorine loading of 12 chemically equivalent fluorine atoms, BHFIP was found to possess an intrinsically short 19F longitudinal relaxation time (T1), together enabling exceptionally high 19F MRI sensitivity. Its 19F chemical shift at approximately - 75 ppm is clearly distinguishable from those of established highly fluorinated moieties, supporting multiplexed 19F MRI. The two hydroxyl groups of BHFIP contribute to water solubility and enable O-modification, while BHFIP-NH2 further provides an additional amino handle for N-modification. Representative incorporation of BHFIP-NH2 into 19F MRI probes further verified that the advantages of BHFIP can be retained in functional probe molecules. This work establishes BHFIP as a promising fluorinated moiety for high-sensitive and multifunctional 19F MRI probes.

Conjunctival melanoma (CoM) is an ultra-rare ocular melanoma that originates from transformed melanocytes of the conjunctiva. CoM shares a common embryonic cell of origin as cutaneous melanoma and manifests as highly aggressive malignancy. Despite cellular similarity of conjunctival and cutaneous melanoma, the pathogenesis, genetic landscape, response to treatment, and prognosis of these malignancies differ significantly. Immune checkpoint therapy has shown promise in individual CoM cases, but therapeutic options for metastatic CoM remain limited. To evaluate efficacy of the latest novel cancer therapies in metastatic CoM, we performed an integrated functional ex vivo and molecular analysis in an immune checkpoint therapy resistant metastatic CoM case. PARP, MEK and RAS(ON) inhibitors along select standard chemotherapies including cisplatin and docetaxel displayed marked ex vivo efficacy in NRAS, FBXW7, TERT and TP53 mutated genetic background. Following molecular tumor board evaluation, the patient received combinatorial chemotherapy as part of standard therapy resulting in a clinical partial response. Upon progression, MEK inhibitor treatment was selected for treatment, resulting in sustained clinical benefit correlating with the ex vivo observed sensitivity. To provide further insights on efficacy of latest experimental cancer therapies including TEAD, pan-RAS/RAF and the RAS(ON) inhibitors in NRAS mutant CoM, a spontaneously immortal cell line established from the patient's tumor was used for comparative high-throughput screening against two NRAS mutant cutaneous melanomas. Results of our study demonstrate feasibility of functional ex vivo drug testing in conjunctival melanoma and warrant further studies of targeted therapies including MEK and RAS inhibitors in larger cohorts of NRAS mutant conjunctival melanomas.

Skeletal muscle undergoes a progressive decline in mass and function with aging, a condition that in its extreme form is known as sarcopenia. This is driven by complex cellular and molecular alterations, such as shifts in myonucleus composition, increased fibrosis, and fat or immune cell infiltration. Despite extensive research, effective therapeutic interventions for sarcopenia remain limited. Recent advances in single-cell omics technologies have begun to unravel the cellular and molecular heterogeneity of mouse and human skeletal muscle across the lifespan, identifying age-enriched cell states and dynamic transcriptional changes. However, epigenetic regulation during skeletal muscle aging is less well characterized. To help address this gap, we performed single-nucleus Assay for Transposase-Accessible Chromatin using sequencing (snATAC-seq) on skeletal muscle from young adult and aged male mice, generating chromatin accessibility profiles from over 43,000 nuclei. Among other findings, our analyses reveal an age-enriched pro-atrophy subpopulation of type IIb myonuclei marked by increased chromatin accessibility at the Ampd3 locus. Furthermore, we delineate the epigenetic mechanisms underlying the transition of healthy type IIb myonuclei into Ampd3+ myonuclei, revealing key chromatin remodeling events that drive this phenotypic shift. Moreover, by integrating with an existing single-nucleus RNA sequencing dataset of the same anatomical origin, we identified thousands of cell-type-specific cis-regulatory elements related to aging programs. Within these elements, we observed a broad depletion of binding motifs for transcription factors with roles in cellular identity and muscle regeneration, concomitant with the gain of stress-responsive transcription factors. Our work helps understand the epigenetic events underlying mammalian skeletal muscle aging.

Enrichment and detection of trace antibiotics in complex matrices are challenged by severe matrix interference and low analyte abundance. Herein, a synergistic recognition interface was engineered on magnetic imprinted polymers by integrating acryloyl-calix[4]arene (AC[4]A) and aptamer (Apt). This dual-receptor interface exploits complementary binding modes to specifically recognize enrofloxacin (ENR). Specifically, AC[4]A captures the hydrophobic moiety of ENR via host-guest inclusion, while the aptamer targets its aromatic/carboxyl groups through hydrogen bonding and π-π stacking. Multimodal analyses (1H NMR, CD, molecular docking, and MD simulations) reveal spatially distinct binding sites. Molecular docking indicates a synergistic enhancement of -2.9 kcal/mol in the ternary complex relative to binary sums, while MD simulations reveal that the cooperativity arises from entropy-driven conformational adaptation and interface complementarity. Moreover, the imprinted framework stabilizes the aptamer, retaining >80% extraction capacity after DNase I treatment. With an imprinting factor (IF) of 8.5 and a synergistic recognition factor (SRF) of 1.5, this dual-receptor interface demonstrates a clear "1 + 1>2" effect and the resulting method offers a wide linear range (2.5-300 μg/L) with a low detection limit (0.42 μg/L), well below regulatory limits. Applied to the enrichment and analysis of animal-derived samples, it significantly reduces matrix interference with recoveries of 83.3-98.2%. This dual-receptor strategy provides a reliable and sensitive platform for trace antibiotic enrichment and detection in complex matrices.

Wilms Tumour (WT), the most common kidney cancer in children, presents features of altered kidney development and frequently exhibits molecular alterations at the 11p15.5 imprinted locus, affecting the IGF2 and H19 genes, which contribute to tumour growth and predisposition. The epigenetic landscape beyond 11p15.5 suggests diagnostic and prognostic potential, but its link to transcriptomic changes is largely unexplored. We integrated methylomic and transcriptomic datasets of 27 primary tumours and matched non-neoplastic kidneys. DNA methylation profiling identified around 9000 differentially methylated CpG sites distinguishing neoplastic from non-neoplastic tissue and other paediatric cancers, thus representing a novel WT-specific epigenetic signature. We found that cases with Imprinting Centre 1 (IC1) gain of methylation exhibited the most extensive epigenetic alterations; cases with 11p15.5 loss of heterozygosity showed intermediate changes, whereas regressive tumours with largely normal 11p15.5 status were less affected. Three methylation clusters corresponding to transcriptomic subtypes were identified, characterised by distinct tumour microenvironment and chemosensitivity predictions: a regressive-enriched, immune-infiltrated group predicted to respond to paclitaxel, a proliferative group sensitive to doxorubicin, and a stromal-like intermediate group. Combined analysis of methylation and expression data revealed more than 900 genes under epigenetic control, which contributed to defining the WT subtypes. Analysis of the IGF2/H19 locus uncovered multiple regulatory mechanisms underlying IGF2 activation, including imprinting defects at IC1, methylation changes at DMR0, differential promoter usage and transcriptional modulation by PLAG1 and BAHD1. These findings define the epigenetic alterations underlying WT heterogeneity and support improved molecular stratification and therapeutic approaches.

Acridine derivatives, such as proflavine, acriflavine, and acridine orange, have been used extensively in biology and biomedicine as fluorescent probes by forming DNA-intercalating complexes. This approach benefits from a comprehensive understanding of their photophysical properties. In this context, we studied the fluorescence properties of proflavine, a reference compound, and its methylated derivatives under cryogenic, isolated conditions. Fluorescence excitation and dispersed emission spectra were measured, and spectral interpretation was supported by time-dependent density functional theory (TD-DFT) calculations at the ωB97XD/aug-cc-pVDZ level of theory. The excitation and emission spectra exhibit progressively red-shifted maxima with increasing methylation, reaching shifts up to 0.270 eV in emission, while the vibronic structure evolves from sharp to broad depending on the methylation site. Molecular geometry optimization, in both ground and excited states, predicts that the methylation of the amino side groups maintains the planar geometry observed in proflavine. In contrast, methylation of the nitrogen heterocycle disrupts symmetry, leading to an out-of-plane bend. These geometric differences lead to distinct active vibronic modes in Franck-Condon simulations, providing an explanation for the observed spectral differences. Additionally, TD-DFT calculations reproduce the red-shift trend experimentally observed, although they systematically overestimate excitation energies. Overall, the findings establish methylation as an effective strategy for tuning the photophysics of diaminoacridines, demonstrating that side substitution enables controlled spectral shifts without compromising emission efficiency or spectral resolution. These insights provide a rational framework for designing functional dyes with tailored optical properties for biological applications.

The discovery of potentially many hundreds of risk genes for schizophrenia does not resolve the mystery of the illness at the level of an individual. The diversity of implicated gene functions has encouraged speculation that there are convergent biological pathways that mediate risk at the systems level, perhaps represented in gene coexpression patterns. The authors emphasize that gene coexpression varies across development, with some molecular elements related to schizophrenia risk losing importance or gaining momentum over time. The systems biology of risk and environmental exposures associated with risk are both time-dependent. The authors propose that the dynamic gene-environment interplay subtended by shifting coexpression patterns may explain variable expressivity of genetic risk during development. In particular, gene-environment correlations provide a mechanism for the individual-hence for their genes-to affect the environment and thus individual experience, promoting chains of life events. The authors envision the paired study of molecular and behavioral patterns over time as a way to identify novel treatments and preventive strategies to change the course of schizophrenia.

Prognostication in chronic myelomonocytic leukemia (CMML) remains a challenge due to the biological complexity and variable clinical course of the disease. This study aimed to evaluate the prognostic utility of the International Prognostic Scoring System-Molecular (IPSS-M) in CMML and its applicability across the myelodysplastic and myeloproliferative subsets of the disease. We conducted a multicenter, retrospective study including 511 patients diagnosed with CMML. Clinical, cytogenetic, and molecular data were collected at diagnosis, including targeted NGS. Patients were stratified using IPSS-M, CPSS-Mol, and the recently developed iCPSS. IPSS-M effectively stratified patients into risk groups with significantly different overall survival (OS) and cumulative incidence of acute myeloid leukemia (AML) progression. Discrimination was maintained after merging overlapping intermediate risk categories, yielding a four-tier model with a c-index of 0.678 for OS and 0.628 for AML progression. This model retained its prognostic performance in both MD-CMML and MP-CMML subsets, with higher discrimination for OS in the MD-CMML group. When compared with CPSS-Mol and iCPSS, adapted IPSS-M showed comparable prognostic performance to iCPSS and improved discrimination compared with CPSS-Mol. These findings support the applicability of an adapted IPSS-M to CMML, extending its use beyond myelodysplastic syndromes and highlighting its potential utility in guiding clinical decision-making and therapeutic strategies. Moreover, this study also provides an external validation of the iCPSS in an independent and genetically well-characterized CMML cohort, reinforcing its clinical utility.

Unlocking the design principles of programmable RNA catalysts capable of site-specific chemical modification is critical for expanding the functional and therapeutic potential of RNA. The SAM analogue-utilizing ribozyme (SAMURI) enables site-specific RNA alkylation using either S-adenosylmethionine (SAM) or the synthetic cofactor propargylic Se-2,6-diaminopurinribosyl-selenomethionineamide (ProSeDMA), yet the molecular determinants of its reactivity remain incompletely understood. Here, we combined molecular dynamics, 3D-RISM solvation analysis, alchemical free energy calculations, quantum pKa shift predictions, and ab initio QM/MM free energy simulations to characterize the conformational and electronic factors that govern catalysis. Simulations show that, although the global fold of SAMURI remains stable in solution, the formation of catalytically competent near-attack configurations is rare, indicating that the observed rate depends on access to a minor fraction of these reactive conformations (freact). A putative Mg2+ binding site between the SAM carboxylate and the G30 phosphate, together with a hydrogen bond between the cofactor α-amine and U8:O2, enriches freact. QM/MM simulations support an SN2-like alkyl transfer mechanism and show that ProSeDMA reacts more readily than SAM primarily due to its more favorable electronic leaving group properties that enhance the intrinsic rate (kint). Atomic substitutions at A52 that tune the N3 pKa enhance nucleophilicity, further lower the activation barrier, and increase kint. Together, these results show that SAMURI catalysis is governed by a combination of conformational preorganization and electronic effects, providing a framework to guide the design of new programmable RNA alkyltransferases.

Fertility-sparing treatment is an established option for reproductive-age women with early-stage endometrioid endometrial cancer or atypical endometrial hyperplasia. Despite high initial response rates with progestin-based therapy, predicting treatment response and recurrence remains challenging. This narrative review summarizes current evidence on prognostic and predictive biomarkers for conservative management. Progesterone receptor positivity is the most consistent favorable predictor of response, while POLE ultra-mutated tumors show excellent remission and low recurrence. Mismatch repair deficiency and p53 abnormalities are strong negative predictors, associated with poor response and higher relapse risk. PTEN loss and PIK3CA mutations may contribute to hormonal resistance, especially in combination. Ki-67 and L1 neuronal cell adhesion molecule provide additional prognostic value for recurrence risk. Elevated serum human epididymis protein 4 levels predict poor response to progestin-based therapy and represent the most promising non-invasive biomarker for patient selection and monitoring. Urine metabolomics is emerging as a complementary non-invasive tool. Magnetic resonance imaging-based radiomics and apparent diffusion coefficient histogram analysis show promise in predicting complete response and identifying resistance patterns before treatment. However, no single biomarker is sufficient for clinical decision-making. Future progress requires multi-modal strategies integrating molecular, serum, and imaging data, validated in prospective multi-center studies.

Chronic inflammatory skin diseases require safe and repeatable access to localized molecular information to enable mechanistic studies and precision management, yet existing sampling methods remain invasive or poorly representative of the skin microenvironment. Here, we develop xylem-inspired anisotropic porous silk microneedle (APSMNs)for rapid, high-yield, and minimally invasive sampling of skin interstitial fluid (ISF). By integrating directional cryo-templating, ice-templated solvent-exchange crosslinking, and Hofmeister effect-induced salting-out, APSMNs feature vertically aligned microchannels and high mechanical robustness, ensuring reliable skin penetration and swelling-independent ISF uptake. A single patch collects >10 μL ISF within 5 min, supports transport of macromolecules of at least 150 kDa, and achieves recovery efficiencies above 95%, yielding >180 μg total protein from mouse skin. In psoriasis-like mice, APSMN-collected ISF enables ELISA quantification of inflammatory biomarkers with sensitivity higher than serum and comparable to skin biopsy. Proteomic analysis identifies >6300 proteins in APSMN-collected ISF, exceeding serum and approaching skin biopsy, with significantly more upregulated proteins (2.89- and 2.54-fold increase compared with serum and biopsy, respectively). These findings demonstrate APSMNs as a robust platform for minimally invasive ISF sampling, enabling biomarker quantification and proteomic analysis. It supports longitudinal monitoring and discovery of disease-relevant molecular signatures in skin disorders.