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To address the efficient capture of volatile organic compounds such as 1,2-dichloroethane (1,2-DCA), this study proposes a directed design strategy for deep eutectic solvents (DESs) driven by the synergy of quantum chemical calculations and experimental validation. Based on theoretical calculations of solvation free energy and binding energy, systematic screening was conducted on numerous combinations of hydrogen bond acceptors and donors, identifying triphenyl phosphate (TPP) and Diethylene glycol monobutyl ether (DEGBE) as optimal pairings. Experimental validation demonstrated that TPP-DEGBE (1:4) achieved an equilibrium absorption efficiency of 98.69% for 1,2-DCA under ambient temperature and pressure conditions, with efficiencies remaining above 97% after twelve absorption-desorption cycles. Combined molecular dynamics simulations and spectroscopic analysis further confirmed that C-H···π interactions between chlorine atoms of 1,2-DCA and TPP, together with hydrogen bonding between TPP and DEGBE, synergistically constitute the core mechanism enhancing absorption performance. The design strategy established in this study provides a novel approach for the design of efficient solvents for capturing chlorinated volatile organic compounds.

Fruit-like aroma compounds play a crucial role in the sensory quality of food and are commonly utilized as natural flavoring agents. However, the extraction from plants faces challenges such as seasonal variability, low yields, and environmental impacts. Microbial biosynthesis offers a scalable and sustainable alternative. Therefore, this review focuses on, major compound classes and their biosynthetic routes, followed by recent progress in microbial production. Engineering advances are organized into five coordinated strategies: chassis optimization, heterologous pathway reconstruction, catalytic protein engineering, metabolic/cofactor redistribution, and fermentation process control. Emerging tools, including dynamic regulation, spatial enzyme co-localization, and machine learning assisted design, are surveyed for their impact on titer, selectivity, and aroma complexity. Special attention is given to consolidating compound classes, host chassis, key pathway modules, and reported titers and operating conditions, providing a comparative map of state-of-the-art performance and exposing gaps for future optimization. An in-depth examination of ongoing issues, such as enzyme versatility, product toxicity, and scalability limitations, provides actionable recommendations for developing effective, resilient, and sustainable microbial systems for the food, beverage, and fragrance sectors.

Intratumoral microbiota are increasingly recognized as essential components of the tumor microenvironment (TME) across various cancer types. This review emphasizes the regulatory roles of these microbial communities in modulating the TME and discusses their potential as targets for clinical intervention. Intratumoral microbiota contribute to an immunosuppressive TME through several mechanisms that promote tumor progression and affect therapeutic responses. They directly stimulate oncogenic pathways such as PI3K-AKT, induce chronic inflammation via NF-κB activation mediated by pattern recognition receptors, and impair CD8 + T cell function by recruiting regulatory T cells (Tregs) and myeloid-derived suppressor cells (MDSCs) or by secreting metabolites like short-chain fatty acids. These actions create a microenvironment that supports tumor growth. In the context of immunotherapy, certain microbial species can undermine the effectiveness of immune checkpoint inhibitors by upregulating PD-L1 expression or expanding immunosuppressive cell populations. Building on the understanding of microbe-TME interactions, novel intervention strategies are being developed. Techniques such as engineered bacteria, bacteriophage therapy, and bacterial extracellular vesicles (BEVs) have shown promise in remodeling the TME, overcoming therapy resistance, and enhancing the effectiveness of immunotherapy. Despite these advancements, significant challenges remain. These include deciphering the spatiotemporal dynamics of intratumoral microbiota, elucidating their mechanistic interactions with host cells, and ensuring safe and effective clinical translation. Future research that integrates spatial multi-omics, synthetic biology, and nanotechnology may lead to precision therapeutic paradigms focused on microbiota-TME modulation, offering innovative solutions to address tumor resistance.

To investigate the association between enteral nutrition (EN) timing and postoperative anion gap (AG) trajectory in ICU patients undergoing cardiac surgery. Data were extracted from the MIMIC-IV database. Cardiac surgery patients receiving EN were classified into preoperative and postoperative groups according to whether EN was first recorded before or after surgery. Baseline comparability was assessed. AG levels at admission, within 24 h after surgery, and at discharge were compared, and multivariable linear regression and subgroup analyses were performed as exploratory analyses. Among 195 cardiac surgery patients, 83 had preoperative EN and 112 had postoperative EN records. Baseline illness severity was broadly similar between groups, although age, sex, alcohol use history, and diabetes prevalence differed. No significant between-group difference in admission AG was observed, whereas the preoperative EN group had lower AG at postoperative 24 h (15 [12, 17] vs. 17 [14, 19], P = 0.035) and at discharge (15 [13, 17] vs. 17 [13, 21], P = 0.027). EN timing remained associated with postoperative 24-hour and discharge AG in multivariable models. EN timing was not clearly associated with postoperative delirium, in-hospital mortality, or length of hospital stay. It was discharge-AG that positively correlated with in-hospital mortality. Preoperative EN was associated with lower postoperative and discharge AG levels in this retrospective cohort. However, this metabolic signal did not translate into clear clinical outcome benefit, and the findings should be interpreted as hypothesis-generating because residual confounding by indication remains possible.

Oral squamous cell carcinoma (OSCC) is a malignant tumor originating from the oral mucosa, predominantly affecting the tongue, buccal mucosa, and floor of the mouth. This review summarizes recent progress in identifying novel biomarkers for OSCC, with particular focus on components of the tumor microenvironment (TME) involved in immune evasion, matrix remodeling, and angiogenesis. In addition, epigenetic alterations- including DNA methylation, histone modifications, and dysregulated non-coding RNAs-are investigated for their roles in OSCC progression. The role of extracellular vesicles (EVs) is further demonstrated, as they serve as critical mediators of intercellular communication linking the TME and epigenetic regulatory networks. Moreover, High-throughput technologies, such as single-cell sequencing and mass spectrometry, provide powerful tools to uncover the molecular mechanisms underlying these processes.

Objective, non-destructive grading of tobacco remains elusive because near-infrared (NIR) spectra of leaves from different quality classes are almost indistinguishable. Here we combine a large multi-label spectral data set with a single-pass pre-processing operator to resolve these subtleties. High-resolution NIR reflectance spectra were collected from 971 flue-cured samples and annotated by expert tasters for ten sensory attributes, each compressed into 7-10 calibrated grades. We introduce Polarization-Standard Filtering (PSF), an analytic fusion of modified max-min scaling, variance-aware centering, Centralization transformation and Savitzky-Golay smoothing. PSF increases inter-sample Euclidean distances sevenfold while preserving spectral envelopes, overcoming the 0.99 cosine similarity that hampers raw data. Support-vector machines trained on PSF spectra achieve 99.7 % accuracy for seven-level quality grading-75 % higher than models using unprocessed spectra and 23 % above the best conventional pipeline. Across nine additional sensory attributes, accuracy ranged from 67 % to 98 %, with a median accuracy of 85.2 %. Notably, Fragrance 98.3 %, Impurity 98.3 %, and Mellow 94.9 % also achieved high accuracies. Sliding-window occlusion localizes the most informative wavelengths (1700-1850 nm and 2080-2300 nm) to O-H, N-H and C-H combination bands, enabling chemically interpretable feature reduction to ≤ 8 % of the original channels with minimal accuracy loss. The open PSF-NIR framework transforms tobacco flavor evaluation from subjective bench tests to an inline, multi-attribute, machine-readable process.

In this work, chitosan (CS) was used as the skeleton to synthesize flame-retardant composite cryogels. Phytic acid (PA)-modified Zr-based metal-organic framework (PA-UiO-66-NH2) was integrated into the CS network to enhance flame retardant performance. The vertical combustion test (UL-94) grade was V-0, and the limiting oxygen index (LOI) value reached 39 % when the flame retardant (PA-UiO-66-NH2) addition content was 15 %. Cone calorimetry tests demonstrated that the inclusion of PA-UiO-66-NH2 significantly decreased the heat release and smoke generation, facilitating the formation of a compact carbon layer on the cryogels. With a thermal conductivity of 0.03447 W/(m·K), the modified CS-15PA-UiO-66-NH2 cryogels maintained their superior thermal insulating capabilities as compared to the pristine cryogels. The water contact angle of the cryogels hydrophobically modified with methyl trichlorosilane (MTCS) was 135.3° ± 2.3°. This study presents cryogels with excellent flame retardancy, and such material is expected to replace conventional petroleum products in energy storage and building insulation.

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Nowadays, growing particulate matter (PM) pollution poses a serious threat to human health. Due to its biodegradability, worldwide availability, easy processability and low cost, cellulose has attracted significant attention for air filter production. However, natural cellulose-based air filters feature the intrinsic limitations, such as low removal efficiency and susceptibility to bacterial contamination. Herein, we fabricated an NH2-MIL-101@cellulose composite air filter with desirable manufacturing feasibility using the in-situ growth process combined with traditional papermaking techniques. The cellulosic substrate, rich in hydroxyls, fosters uniform NH2-MIL-101 dispersion and secure anchoring, minimizing loss. Characterization techniques and Density Functional Theory calculations verified the unique interface between NH2-MIL-101(Fe) and cellulose. At a testing wind speed of 2 m/s, the PM10 (PM2.5) filtration efficiency, pressure drop and quality factor for N101@BP-2 were 95.8 % (92.3 %), 31 Pa, and 0.102 Pa-1 (0.0827 Pa-1), respectively, harnessing fiber interception and MOF-mediated electrostatic effects. Furthermore, the antibacterial and biodegradable performance of NH2-MIL-101@cellulose composite filter were assessed. This work provides instructive guidance for the research on advanced cellulose-based materials for air purification.

Tertiary lymphoid structures (TLSs) are aberrant lymphoid tissues found in persistent inflammatory settings, including malignancies, autoimmune disorders, and transplanted organs. The organization and architecture of TLS closely resemble that of secondary lymphoid organs (SLOs). The formation of TLS is an ongoing process, with varying structural features observed at different stages of maturation. The tumor microenvironment (TME) is a multifaceted milieu comprising cells, molecules, and extracellular matrix components in close proximity to the neoplasm. TLS within the TME have the capacity to actively elicit anti-tumor immune responses. TLSs exhibit tumor-specific and individual-specific characteristics, leading to varying immune responses towards tumor immunity based on their distinct cellular components, maturity levels, and spatial distribution. Cell interaction is the foundational elements of tumor immunity. Despite differences in the cellular composition of TLS, B cells and T cells are the main components of tumor-associated TLS。Recent research has highlighted the significance of diverse subtypes of B cells and T cells within TLSs in influencing the therapeutic outcomes and prognostic indicators of individual tumors. This review elucidates the diversity of TLS in terms of cellular composition, developmental stage, anatomical location, and the influence of cytokines on their initiation and progression. Furthermore, the article examines the involvement of B and T cells within TLS and the significance of TLS in relation to tumor prognosis.

Recent studies have identified a complex relationship between methylation patterns and the development of various cancers. Breast cancer (BC) is the second leading cause of cancer mortality among women. Approximately 5-20% of BC patients are at risk of BC brain metastases (BCBM). Although 5-methylcytosine (m5C) has been identified as an important regulatory modifier, its distribution in BCBM is not well understood. This study aimed to investigate the distribution of m5C in BCBM. Samples from BCBM (231-BR cells) and BC (MDA-MB-231 cells) groups were subjected to a comprehensive analysis of the m5C methylation in long non-coding RNA (lncRNA) using methylated RNA immunoprecipitation next-generation sequencing (MeRIP-seq). The expression levels of methylated genes in BC and adjacent tissues were verified through quantitative real-time polymerase chain reaction (RT-qPCR). Enrichment pathway analyses were through Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) to predict the potential functions of m5C in BCBM. The MeRIP-seq analysis identified 23,934 m5C peaks in BCBM and 21,236 m5C in BC. A total of 9,480 annotated genes (BCBM) and 8,481 annotated genes (BC) were mapped. Notably, 1,819 methylation sites in lncRNA were upregulated in BCBM, whereas 2,415 methylation sites were upregulated in BC. Significant m5C hypermethylated lncRNAs included ENST00000477316, ENST00000478098 and uc002gtt.1, whereas hypomethylated lncRNAs included ENST00000600912, ENST00000493668, ENST00000544651 and ENST00000464989. These results were verified by qPCR and MeRIP-qPCR in BC and BCBM. Considering the strong association between m5C RNA methylation regulators and lncRNA, we examined the expression levels of 13 m5C RNA methylation regulators and observed significant differences between BC tissues and adjacent normal tissues. In addition, the interaction between regulators of altered expression and the differentially expressed genes in vitro was analyzed. The GO and KEGG pathways analyses revealed that genes significantly associated with m5C sites in lncRNA were linked to the BCBM signaling pathways. This uncovered significant variations in the levels and distribution of m5C in BCBM compared to BC. The findings provide a new theoretical understanding of the mechanisms of BCBM.

During the metastatic progression of cancer, tumor cells undergo widespread genetic and epigenetic alterations. The regulatory mechanism of 5-methylcytosine (m5C) methylation of PSD4 in breast cancer brain metastasis (BCBM) remains unclear. In this study, we found that PSD4 expression is markedly elevated in both BCBM tissues and cell lines. Functional assays in vitro revealed that overexpression of PSD4 significantly promoted cell proliferation, invasion, migration, and epithelial-to-mesenchymal transition (EMT). Complementary in vivo experiments confirmed the tumor-promoting and metastasis-enhancing roles of PSD4 in brain metastases. At the mechanistic level, PSD4 m5C methylation was regulated by NSUN2 via its catalytic domains (C271A/C321A), which enhanced PSD4 mRNA stability and facilitated its nuclear export, increasing its expression. Furthermore, YBX1 was identified as a critical m5C-binding protein regulating PSD4 methylation. Functional analysis also showed that PSD4 contributes to vasculogenic mimicry (VM) by promoting ferroptosis resistance, decreasing vascular permeability, and enhancing tumor growth and metastasis to the brain. These findings establish PSD4 as a key player in BCBM and suggest its potential as a diagnostic marker and therapeutic target.

The tumor suppressor gene Phosphatase and tensin homologue deleted on chromosome 10 (PTEN), possessing both protein and lipid phosphatase activities, is frequently mutated in various human cancers. PTEN aberrations disrupt critical cellular processes like proliferation, apoptosis, migration, and invasion, thereby promoting tumor growth. In the cells, PTEN localizes to the nucleus, cytoplasm, or cell membrane, and its roles depends on the subcellular localization. PTEN is regulated at the transcriptional, post-transcriptional, and post-translational levels, implying that its functions on the tumors are complex. The relationship between PTEN abnormalities and tumors has garnered significant interest in recent years. PTEN regulates essential cellular processes involved in tumorigenesis. Mutations or deletions in the PTEN gene often correlate with unfavorable prognosis and increased cancer recurrence. Numerous studies suggest that PTEN expression levels in tumors could be a valuable biomarker for cancer diagnosis, treatment, and predicting patient outcomes. This paper provides a comprehensive review of the biological function, regulatory mechanisms, and post-translational modifications of PTEN. Furthermore, this review explores the expression and regulation of PTEN in different tumor types, as well as its interactions with environmental factors in tumorigenesis. This comprehensive analysis aims to deepen our understanding of the signaling pathways between PTEN and cancer.

MOF-199 is considered to be an excellent CO2 adsorbent owing to its substantial specific surface area, suitable pore structure and abundant sorption sites. However, powdered MOF-199 is prone to agglomeration and has poor recyclability. Herein, we proposed a MOF-199-based adsorbent by combining the MOF synthesis process with traditional papermaking process. Through such a design, MOF-199 particles are adhered on the surface of wood pulp fiber. The sufficient hydroxyl groups and electrostatic forces of cellulose facilitates the homogeneous and tight adhesion of MOF crystals. The optimal MP-4 sample demonstrated a high CO2 adsorption capacity (1.80 mmol·g--1 at 25 °C) and good CO2/N2 selectivity (30.06). Moreover, the composite sorbent can be easily regenerated. The adsorption mechanism was analyzed by the density functional theory approach. The simulation results showed that the carboxyl functional groups with a large number of oxygen atoms and active metal sites are the key to boost the CO2 adsorption performance.

Colitis is a refractory intestinal inflammatory disease significantly affecting the quality of a patient's life and increasing the risk of exacerbation. The primary factors leading to colitis encompass infections, insufficient blood flow, and the buildup of collagen as well as white blood cells. Among various available therapeutics, 5-methoxytryptophan (5-MTP) has emerged as one of the protectants by inhibiting inflammatory damage. Nonetheless, there is no report on the role of 5-MTP in the treatment of colitis. To verify the anti-inflammatory effect of 5-MTP in vivo, we first constructed mouse model with dextran sulfate sodium-induced colitis. Furthermore, the macrophage infiltration and release of inflammatory factors through western blot (WB) and hematoxylin-eosin staining analyses were examined. Intestinal epithelial cell tight junction damage and apoptosis were investigated by WB analysis, immunofluorescence, and terminal deoxynucleotidyl transferase dUTP nick end labeling staining. Finally, we examined the generation of cellular inflammation and analyzed the influence of 5-MTP on M1 polarization at the cellular level. This study initially confirmed that 5-MTP possessed an excellent therapeutic effect on colitis. 5-MTP inhibits macrophage infiltration and the generation of inflammatory factors. In addition to its effects on immune cells, 5-MTP significantly inhibits intestinal epithelial cell tight junction damage and apoptosis in vivo. Moreover, it inhibits inflammation and M1 polarization response in vitro. 5-MTP counteracts excessive inflammation, thereby preventing intestinal epithelial tight junction damage. In addition, inhibition of apoptosis suggests that 5-MTP may be a potential therapeutic agent for colitis.

In the field of building energy conservation, the development of biodegradable biomass aerogels with excellent mechanical performance, flame retardancy and thermal insulation properties is of particular importance. Here, a directional freeze-drying method was used for fabricating composite sodium alginate (SA) aerogels containing functionalized ammonium polyphosphate (APP) flame retardant. In particular, APP was coated with melamine (MEL) and phytic acid (PA) by a supramolecular assembly process. Through optimizing the flame retardant addition, the SA-20 AMP sample exhibited excellent flame retardant and thermal insulation properties, with the limiting oxygen index of 38.2 % and the UL-94 rating of V-0. Such aerogels with anisotropic morphology demonstrated a low thermal conductivity of 0.0288 (W/m·K) in the radial direction (perpendicular to the lamellar structure). In addition, as-obtained aerogels displayed remarkable water stability and mechanical properties, indicating significant potential for practical applications.

The survival analysis on histological whole-slide images (WSIs) is one of the most important means to estimate patient prognosis. Although many weakly-supervised deep learning models have been developed for gigapixel WSIs, their potential is generally restricted by classical survival analysis rules and fully-supervised learning requirements. As a result, these models provide patients only with a completely-certain point estimation of time-to-event, and they could only learn from the labeled WSI data currently at a small scale. To tackle these problems, we propose a novel adversarial multiple instance learning (AdvMIL) framework. This framework is based on adversarial time-to-event modeling, and integrates the multiple instance learning (MIL) that is much necessary for WSI representation learning. It is a plug-and-play one, so that most existing MIL-based end-to-end methods can be easily upgraded by applying this framework, gaining the improved abilities of survival distribution estimation and semi-supervised learning. Our extensive experiments show that AdvMIL not only could often bring performance improvement to mainstream WSI survival analysis methods at a relatively low computational cost, but also enables these methods to effectively utilize unlabeled data via semi-supervised learning. Moreover, it is observed that AdvMIL could help improving the robustness of models against patch occlusion and two representative image noises. The proposed AdvMIL framework could promote the research of survival analysis in computational pathology with its novel adversarial MIL paradigm.

Predicting patients' survival from gigapixel Whole-Slide Images (WSIs) has always been a challenging task. To learn effective WSI representations for survival prediction, existing deep learning methods have explored utilizing graphs to describe the complex structure inner WSIs, where graph node is respective to WSI patch. However, these graphs are often densely-connected or static, leading to some redundant or missing patch correlations. Moreover, these methods cannot be directly scaled to the very-large WSI with more than 10,000 patches. To address these, this paper proposes a scalable graph convolution network, GraphLSurv, which can efficiently learn adaptive and sparse structures to better characterize WSIs for survival prediction. GraphLSurv has three highlights in methodology: (1) it generates adaptive and sparse structures for patches so that latent patch correlations could be captured and adjusted dynamically according to prediction tasks; (2) based on the generated structure and a given graph, GraphLSurv further aggregates local microenvironmental cues into a non-local embedding using the proposed hybrid message passing network; (3) to make this network suitable for very large-scale graphs, it adopts an anchor-based technique to reduce theorical computation complexity. The experiments on 2268 WSIs show that GraphLSurv achieves a concordance-index of 0.66132 and 0.68348, with an improvement of 3.79% and 3.41% compared to existing methods, on NLST and TCGA-BRCA, respectively. GraphLSurv could often perform better than previous methods, which suggests that GraphLSurv could provide an important and effective means for WSI survival prediction. Moreover, this work empirically shows that adaptive and sparse structures could be more suitable than static or dense ones for modeling WSIs.

Diabetic retinopathy (DR) is one of the leading causes of blindness in diabetic patients. However, the pathogenesis of DR is complex, and no firm conclusions have been drawn so far. It has become a hot spot in ophthalmology research to deeply study the mechanism of DR pathological changes and find effective treatment options. Human retinal microvascular endothelial cells (HRMECs) were induced by high glucose (HG) to construct DR cell model. CCK-8 assay was used to detect the viability of HRMECs. Transwell assay was used to detect the migration ability of HRMECs. Tube formation assay was used to identify the tube formation ability of HRMECs. The expressions of USP14, ATF2 and PIK3CD were detected by Western blot analysis and qRT-PCR assay. Immunoprecipitation (IP) was used to ascertain the relationship of USP14 and ATF2. To explore the regulatory relationship between ATF2 and PIK3CD by dual-luciferase reporter gene assay and Chromatin immunoprecipitation (ChIP) assay. High glucose treatment promoted the proliferation, migration, and tube formation of HRMEC, and the expressions of USP14, ATF2 and PIK3CD were significantly up-regulated. USP14 or ATF2 knockdown inhibited HG-induced HRMECs proliferation, migration, and tube formation. USP14 regulated the expression of ATF2, and ATF2 promoted PIK3CD expression. PIK3CD overexpression attenuated the inhibitory effectiveness of USP14 knockdown on proliferation, migration and tube formation of DR cell model. Here, we revealed that USP14 regulated the ATF2/PIK3CD axis to promote proliferation, migration, and tube formation in HG-induced HRMECs.