AI Scientific Illustration Gallery

Schematic Title: Schematic Diagram of Microneedle Patch Preparation Process Overall Style and Layout: Style: Simple, modern, with technological line illustrations or flat vector graphics. Use a refreshing color scheme, mainly blue, gray, and white, with key parts highlighted in orange or green. Layout: A horizontal flowchart from left to right, including 4 core steps. Each step is clearly marked with a numbered module (Step 1-4). Detailed Description of Steps: Step 1: Mold Casting Scene: On the left is a transparent/translucent polymer microneedle mold (such as a PDMS mold), with a regularly arranged array of inverted pyramid or conical pits visible on its surface. Action: A pipette or dropper is dropping a drop of viscous, translucent mixed solution onto the surface of the mold. The solution can be symbolically dotted with tiny nanoparticles (NPs) to represent DNase-PDA@C-176 NPs. Label: Label the solution as "HA and DNase-PDA@C-176 NPs mixed solution". Label the mold as "Microneedle Mold". Step 2: Vacuum Filling Scene: The mold is placed in a transparent vacuum chamber. State: The solution on the surface of the mold has spread and covered the entire mold area. A vacuum pump icon (or a simple downward arrow indicating air extraction) is connected above the vacuum chamber. Key Visual: In the pits of the mold, use an enlarged partial cross-sectional view to show that the solution is being drawn down under the action of vacuum negative pressure, completely filling every tiny corner of the pit and expelling all air bubbles. A few small upward air bubble arrows can be used to indicate the dynamic process of exhaust. Label: "Vacuum Filling" or "Vacuum Degassing". Step 3: Drying and Curing Scene: The mold is transferred to a dry environment, such as being placed under a gentle warm air flow (indicated by curved arrows) or placed in a "drying oven" icon. State: The moisture in the solution in the mold evaporates, the volume shrinks, and finally solid needles are formed in the mold pits. A partial cross-sectional view can be used again to compare: from pits filled with liquid to solid needles. Label: "Drying/Curing". Step 4: Demolding and Finished Product Action: A hand or a robotic arm is carefully peeling/removing a formed microneedle patch substrate (a transparent polymer backing) from below. Finished Product Display: The peeled patch is displayed completely. Hundreds of tiny conical needle tips stand neatly on the patch substrate, forming a perfect array. Multi-angle Display (Optional): Main View: Complete patch. Side View/Magnified View: Shows the sharp needle tip and complete shape of a single microneedle, with dimensions labeled as "Height: 1000 μm, Base Width: 600 μm". Top View (Illustration): Shows the regular arrangement of microneedles, such as a "10x10 array" or similar. Final Label: Label the finished product as "DNase-PDA"

A pipette with a tip attached.

Six jars of water kefir, two units of honey, two units of molasses, and two units of brown sugar were prepared and covered with cheesecloth.

Methods: Adult male Wistar rats were subjected to diffuse severe traumatic brain injury (TBI) using the Marmarou weight-drop model under anesthesia. Thirty minutes post-injury, pinocembrin (Pino) was administered intraperitoneally at doses of 25, 50, and 100 mg/kg. Neurological function was assessed using the Veterinary Coma Scale, beam walk, and beam balance tests at baseline, immediately after recovery from anesthesia, and at 24, 48, and 72 hours post-trauma. Cerebrospinal fluid (CSF) samples were collected for ELISA analysis of matrix metalloproteinase-9 (MMP-9), and brain tissues were fixed in 10% formalin for histological evaluation using hematoxylin and eosin staining. Results: Severe TBI induced significant neurological deficits, increased cerebral edema, disruption of blood-brain barrier (BBB) integrity, and impaired balance and motor performance. Treatment with pinocembrin at 25 and 50 mg/kg significantly attenuated these pathological changes compared with controls (p < 0.001). These doses also reduced cerebrospinal fluid MMP-9 levels, which were markedly elevated following TBI.

Subject: Experiment Flowchart of Bacterial Activation and Phage Treatment of Biofilm Formation Style: Concise, scientific experimental flowchart, black lines on a white background, clear icons Requirements: Use clear arrows to connect each step. All key nouns must be represented by icons/pictures, and ensure the icons are easy to understand. The process layout is from left to right and from top to bottom, with clear logic. Steps and Icon List: Start [Icon: Stock tube] (containing target bacteria) Use [Icon: Inoculation loop] to pick up bacterial solution from [Icon: Stock tube]. Perform [Icon: Streak plating] on [Icon: 90mm petri dish] (containing solid medium) to activate bacteria. Incubate in an incubator until [Icon: Single colony] grows. Use [Icon: Inoculation loop] to pick a [Icon: Single colony]. Inoculate the picked colony into [Icon: Erlenmeyer flask] containing [Icon: 2216E liquid medium] and shake culture. Measure periodically until [Icon: Spectrophotometer] shows the bacterial solution [Icon: OD600=0.1]. Branch point: Dispense the bacterial solution into two new, sterile [Icon: Erlenmeyer flasks]. Control group: Keep one [Icon: Erlenmeyer flask] as is. Experimental group: Add [Icon: Bacteriophage] to the other [Icon: Erlenmeyer flask]. Use [Icon: Pipette] to transfer the liquid from the two Erlenmeyer flasks to the wells of 4 [Icon: 24-well plates] respectively (the liquid from each Erlenmeyer flask corresponds to 2 well plates). Parallel processing: Place these 4 [Icon: 24-well plates] in [Icon: Different environments] (e.g., different temperatures or shakers) and incubate for [Icon: 24 hours]. After incubation, remove all well plates. Collect the [Icon: Biofilm] formed in each well plate. Place the collected [Icon: Biofilm] samples in [Icon: 1.5ml centrifuge tube]. End (for subsequent analysis). Layout: Please ensure that steps 1-7 are arranged vertically, and after step 8 (dispensing), the control group and the experimental group expand downwards in parallel, and steps 9-13 converge again.

APPROVED This is the abstract of my project proposal. Please generate a scheme for it. Abstract: Asymmetric segregation of protein damage and "aged proteins" during cell division is considered a key mechanism in the initiation of aging and cellular rejuvenation. However, existing studies mainly rely on observing a few fluorescently labeled molecules, lacking the ability to globally analyze at the molecular level and making it difficult to distinguish between new, old, and damaged proteins. To address these issues, this project proposes to use human cells as a model, combining live-cell fluorescence imaging, metabolic isotope labeling, and single-cell proteomics to systematically study the differential segregation patterns of protein abundance, new/old ratios, and damaged components between sister daughter cells during cell division. By constructing a SNAP-Omp25 mitochondrial temporal labeling system, we aim to capture asymmetric segregation events and perform Astral DIA single-cell proteomic analysis on strictly paired sister daughter cells to obtain high-resolution molecular readouts. Furthermore, we will introduce machine learning methods to extract stable asymmetrically segregated proteins and functional modules, and verify their regulatory roles through genetic and pharmacological interventions. This study will elucidate the molecular mechanisms of protein homeostasis resetting and damage isolation in human cells, laying the foundation for understanding aging mechanisms and intervention strategies for related diseases.

Title: Surface Chemistry Orchestrates the Immunological Identities of Nanoplastics via Protein Corona Formation Scientific Question: How do the surface functional groups of nanoplastics (PS) exposed via the bloodstream specifically encode the protein corona formed in serum? How does this differentiated protein corona, generated by surface chemistry, determine the immun recognition patterns, cellular responses, and ultimate toxic effects of nanoparticles in mice? Methods: First, 200 nm polystyrene nanoparticles with carboxyl (PS-COOH), amino (PS-NH2), and unmodified (PS) surface modifications were selected and characterized. They were then incubated with mouse serum in vitro, and proteomic analysis was performed using liquid chromatography-tandem mass spectrometry to identify the differential expression of proteins in the three protein coronas. This comparison clarified the specific regulatory effects of surface functional groups on protein corona composition. Subsequently, a blood exposure model (tail vein injection) was established, and transcriptome sequencing was performed on mouse peripheral blood cells at the single-cell level. Differential expression gene analysis and KEGG pathway enrichment analysis were conducted on the sequencing data for each cell subpopulation to systematically map the immune cell-specific transcription profiles induced by nanoplastics with different protein coronas. Finally, using mouse macrophages as an in vitro model, bare particle groups and pre-coated protein corona particle groups were established. Cell viability was assessed using the CCK-8 method, cellular uptake efficiency was quantified by flow cytometry, and inflammatory cytokine levels were measured by ELISA. Spearman correlation analysis was performed to integrate protein corona composition data with cellular function data, establishing a quantitative relationship between key protein adsorption and biological effects, with the aim of revealing the complex interaction mechanisms between surface functional groups, protein adsorption, and immune responses. Conclusions: The study demonstrates that surface charge is a crucial factor in regulating protein corona composition. Carboxylation leads to the specific enrichment of complement and coagulation proteins, while amination primarily adsorbs apolipoproteins and albumin. This specific adsorption is not random but is driven by molecular properties such as surface potential and protein isoelectric point, achieving a precise conversion of surface chemical information into biological molecular identity. PS-COOH with a complement protein corona is efficiently recognized and endocytosed by macrophages through complement receptors and other pathways, specifically activating the NF-κB signaling axis and driving classical inflammatory pathways such as TNF and IL-17, triggering a strong immune response. In contrast, PS-NH2 with an apolipoprotein corona mimics endogenous lipoprotein particles, reducing rapid clearance by the endothelial phagocytic system, prolonging blood half-life, and primarily inducing upregulation of mitochondrial respiratory chain genes and disruption of oxidative phosphorylation pathways.

Deep Proteomics-Discovered Molecular Identities Reveal Biological Functions of Nanoparticle Protein Corona Key Scientific Questions: 1. Missing Causal Mechanisms: How do the key physicochemical properties of nanoparticles (surface charge, PEGylation, morphology, material) systematically and causally determine their protein corona composition, and in turn, regulate biological fates such as cellular uptake and immune recognition? 2. Data Resource Bottleneck: How can we overcome the fragmentation and low quality of existing public proteomics data to establish a high-quality, standardized nanobio interaction database that can support reliable mechanism discovery and model prediction? Research Methods: This study employs an integrated "data mining-guided experimental construction" strategy. First, a literature-mined nanoparticle protein corona database (LM-NPC-DB) was constructed through text mining and literature data integration, systematically evaluating the field's research paradigm and data quality defects. Based on this analysis, a standardized nanoparticle library covering 42 different materials, charges, PEGylation states, and morphologies was rationally designed and synthesized. Subsequently, a high-quality in-house nanoparticle protein corona database (IH-NPC-DB) was constructed by strictly following uniform standard operating procedures. This database, with its high reproducibility, high protein coverage, and minimized missing values, serves as the core data foundation for this study. On this basis, combined with bioinformatics analysis (differential protein analysis, pathway enrichment, network analysis), machine learning models (predicting morphology-specific adsorption), and functional cell experiments (such as using gene knockout cell models to verify specific uptake pathways), the quantitative relationship between nanoparticle properties, protein corona composition, and biological effects was systematically decoded. Conclusions: This study is expected to establish and validate a clear causal framework of "nanoparticle properties → protein corona composition → biological fate." Specific conclusions include: 1. Surface charge guides protein adsorption through electrostatic-hydrophobic synergistic effects. Negatively charged particles enrich adhesion proteins and mediate efficient cell uptake via Itgav, while positively charged particles preferentially bind to apolipoproteins. 2. PEGylation actively reduces the adsorption of immune-related proteins such as complement/coagulation factors, reconstructing the protein corona to achieve "immune stealth" and effectively inhibit macrophage inflammatory responses. 3. Particle morphology shapes a unique protein adsorption fingerprint. Spherical particles enrich adhesion-related proteins, while rod-shaped particles exhibit high immunogenic potential, both achieved through different physical interactions and interfacial geometric effects. 4. Different materials exhibit complementary protein adsorption profiles, which can be used as "molecular amplifiers" to specifically enrich low-abundance disease biomarkers, providing a theoretical basis for constructing multi-material combined liquid biopsy panels. Ultimately, this study not only provides a standardized database (IH-NPC-DB) that surpasses the quality of existing public data, but also enables rational...

"Rich and mellow" is a core term used to describe the taste of high-quality green tea. "Richness" mainly refers to the intensity and thickness of the tea soup, which is a direct reflection of the high content of water extract, rich in tea polyphenols, caffeine and other substances that provide a strong sensory impact. "Mellow" emphasizes the mellowness and coordination of the tea soup, referring to the moderate bitterness and astringency, balanced with freshness and sweetness, resulting in a comfortable aftertaste in the mouth after swallowing, rather than a stimulating astringent sensation. It is not limited to a single taste dimension, but is the product of the synergistic effect of multi-sensory signals such as taste, smell and oral tactile sensation, and its perceived physiological basis covers a multi-dimensional complex mechanism. First, from the perspective of taste, the formation of a rich and mellow taste is closely related to basic tastes such as sweetness and umami, and sweetness is the cornerstone of its core taste experience. For example, during the long-term withering process of white tea, the content of soluble sugar inside the tea leaves accumulates significantly, and the sweetness increases, and the mellow and smooth taste also follows, which together creates its unique rich and mellow flavor [4]; sweetness perception is mediated by the T1R2/T1R3 heterodimeric receptor, which makes the brain feel pleasant about the stimulation of sweetness, which further enhances the overall perception of the rich and mellow taste. In addition, there is a two-way interaction between sweetness and salty, sour, bitter, umami and other tastes, such as adding sugar and milk to coffee to adjust the tribological properties of the system, weakening the bitterness while enhancing the sweetness and mellowness, which confirms the regulatory effect of taste interaction on the rich and mellow flavor. Second, the sense of smell plays an indispensable synergistic role in the perception of rich and mellow taste. Volatile compounds in food combine with olfactory receptors through the orthonasal and retronasal olfactory pathways, and the rich aroma signals generated are integrated with taste information in the cerebral cortex to form a complete flavor perception. For example, the sweet floral, warm fruity, or aged woody aromas in tea drinks can complement the taste signals and significantly enhance the overall richness and mellowness [9]; the rich and mellow experience of coffee is also inseparable from complex volatile components, and different roasting degrees create differentiated flavors, such as the chocolate and caramel aromas produced by medium-roasted coffee beans, which not only enrich the flavor level, but also enhance the rich and mellow texture through the synergistic effect of aroma and taste. Third, oral tactile sensation is the key physical basis for the perception of rich and mellow taste, and its core is directly related to the physical properties of food such as texture, viscosity, smoothness and granularity. For example, the rich and mellow taste of dairy products is derived from the synergistic effect of their milky aroma, milk flavor, viscosity and smoothness, in which viscosity and smoothness can directly enhance the oral tactile perception of richness and mellowness. Relevant studies have made it clear that creaminess and smoothness are the core dimensions for evaluating the rich and mellow taste of food, and the difference in their physical properties will directly affect the perception intensity and comfort of the rich and mellow taste. In summary, the perception of rich and mellow taste is a complex physiological process of multi-sensory synergistic integration of taste, smell and oral tactile sensation, which relies on the specific recognition of multiple chemical components by taste receptors, the precise capture of volatile aroma substances by the olfactory system, the intuitive perception of the physical texture of food by oral tactile sensation, and the integration, processing and comprehensive analysis of these multi-source sensory signals by the cerebral cortex.

Illustrate the growth process of a mung bean from seed to the emergence of two true leaves, spanning two months, and culminating in yellowing leaves and the development of a few seed pods.

Lats1-AKO and Lats1^f/f^ mice were fed a high-fat diet for 12 weeks, followed by local injection of AAV-BST2 into subcutaneous adipose tissue. The high-fat diet was continued until week 24. Please draw a schematic diagram of the experimental design.

PPT Layout Suggestions (Horizontal Design Recommended): You can build the PPT according to the following steps: Step 1: Establish a Timeline Draw a horizontal line with an arrow. Label the time points below the line: Day -5, Day 0, Day 14. Step 2: Add Intervention Boxes [Day -5 to Day 0]: Draw a rectangular box above the line. Text: Abx Pre-treatment (5 days) Icon: Draw a medicine bottle or capsule (search for "Medicine" in PPT's built-in icons). [Day 1 to Day 14]: Draw two rectangular boxes side by side above the line (or one large box with two lines of text). Text 1: FMT (Daily gavage) Text 2: 5-FU Modeling (i.p. injection) Icon: Draw a syringe. Step 3: Add Endpoint Assessments [After Day 14]: Draw an endpoint box at the end of the line. Text: Behavioral Tests (e.g., MWM, NOR) & Sacrifice. Icon: Draw a maze or brain icon.

Figure Design Proposal: Integrated Flowchart Figure Title: Integrated Computational and Experimental Strategy for Identifying Upstream Transcriptional Regulators of Fgf4 Design Concept: Integrates a "left-to-right process narrative" with a "top-to-bottom results presentation," merging strategy and results. Employs professional colors, high information density, and clear visual guidance. Detailed Explanation and Enhancement Points for Each Module: Left Side - Strategy Flowchart Area Design: Use grayscale or low-saturation color blocks and arrows to clearly define steps, reflecting the methodology. Add small icons (such as a DNA double helix or magnifying glass) next to the "MEME Prediction" and "TOMTOM Comparison" steps to enhance recognition. Key Points: Indicate key parameters, such as sequence range, MEME's E-value threshold, and the name of the database used. Middle - Results Visualization Area Top (MEME Result Display): Sequence Logos: Display the predicted Top 3 motifs side-by-side in high-definition, colorful sequence logo format. This is the core result of the MEME analysis and must be visually appealing. Annotation: Clearly label the MEME E-value and width below each logo. Bottom (TOMTOM Results and Filtering): Bar Chart: Plot the top 3-5 candidate transcription factors with the highest significance after TOMTOM comparison as a horizontal bar chart, using their matching -log10(p-value) as the metric. Design: Use professional color schemes (such as viridis or Set2 color palettes). Arrange bars in descending order from left to right by value, and directly label the factor name (e.g., KLF5) and specific p-value at the end of the bar. Filtering Path: To the right of the bar chart, use a funnel icon or filtering icon to point to the final 1-2 "core candidate factors," highlighting them with different colors or star markers. Right Side - Experimental Validation Bridge Area Design: Delineate with dashed boxes or light-colored backgrounds to indicate this is the next step guided by prediction. Content: Briefly illustrate subsequent key validation experiments with icons and text, such as ChIP-qPCR (magnetic beads and DNA icons) and reporter gene assays (luciferase icon), with arrows pointing to "validated regulators." Function: This module greatly enhances the scientific integrity and depth of the figure, indicating that the research goes beyond computational prediction and completes closed-loop validation.

Three-stage progressive research: from basic mechanism analysis → novel molecule design → formulation development and application verification, with each stage building upon the previous, ultimately achieving efficient skin vitrification cryopreservation. Stage 1: Analysis of the Structure-Activity Relationship and Regulatory Mechanism of Vitrification Agents Core Objective: To elucidate the "structure-property" relationship and molecular synergistic mechanism of vitrification agents. Research Content and Methods: Basic Characterization of Vitrification Performance: Determine the critical vitrification concentration and analyze vitrification transition characteristics using differential scanning calorimetry. Molecular Mechanism Simulation: Computer simulation (molecular structure optimization, energy minimization, electrostatic potential distribution, interaction energy calculation, hydration and water molecule residence time analysis). Stage Output: Model of the structure-activity relationship and synergistic regulatory mechanism of vitrification agents. [Suggested Illustration]: Molecular structure model + schematic diagram of energy/hydration interaction Stage 2: Design and Synthesis of Novel Vitrification Molecules Based on Structure-Activity Relationship Core Objective: To establish a novel vitrification molecule design strategy and obtain high-performance candidate molecules. Research Content and Methods: Molecular Design and Synthesis: Design and chemically synthesize novel vitrification molecules based on the structure-activity relationship from Stage 1. Structure and Performance Verification: Characterize the molecular structure using infrared spectroscopy, nuclear magnetic resonance (hydrogen/carbon NMR), and high-resolution mass spectrometry; test its vitrification performance (critical cooling/heating rate) and ice crystal inhibition ability (ice nucleation/growth, recrystallization inhibition). Stage Output: Candidate molecules with excellent vitrification and ice crystal inhibition properties. [Suggested Illustration]: Molecular design flowchart + structural characterization spectra + microscopic images of ice crystal inhibition Stage 3: Development of Efficient Cryoprotectant Formulations and Verification of Skin Cryopreservation Effect Core Objective: To optimize cryoprotectant formulations, establish a skin vitrification cryopreservation protocol, and verify its effectiveness. Research Content and Methods: Formulation and Process Optimization: Optimize cryoprotectant formulations based on the candidate molecules from Stage 2; test the permeability of protective agents and develop loading/unloading protocols. Skin Cryopreservation and Evaluation: Design a skin vitrification cryopreservation procedure and evaluate the cryopreservation effect through cell viability tests, histological staining, and mechanical property analysis. Stage Output: Efficient vitrification cryoprotectant formulation and optimized skin cryopreservation protocol. [Suggested Illustration]: Schematic diagram of formulation optimization + skin tissue sections + mechanical property curves Progressive Relationship Stage 1 provides the "structure-property" design basis for Stage 2, Stage 2 provides the core functional molecules for Stage 3, and Stage 3 verifies the application effect of the entire process, forming a "mechanism-design-application" closed loop. Illustration Style: Clear flowchart, with three stages distinguished by color, arrows indicating progressive logic, and key nodes accompanied by simplified schematic diagrams.

SARS-CoV, MERS-CoV, SARS-CoV-2, Dengue, Zika, bats, camels, pigs, civets, monkeys, Aedes mosquitoes, humans

Image depicting the disruption of the HBV viral envelope lipid layer, resulting in increased exposure of surface antigens and a greater number of antibody binding sites.

**Title:** Dissecting Host Protein Interactions Mediating LNP Lysosomal Escape Using Proximity Labeling Technology **Key Scientific Questions:** 1. How do the lipid components of LNPs specifically influence their lysosomal escape efficiency? Are there key lipid structural features that determine escape efficiency? 2. Which host cell proteins functionally interact with LNPs at the critical spatiotemporal nodes of lysosomal escape? How do these interacting proteins mediate or hinder the escape process? **Research Methods:** First, a multi-component lipid library will be constructed and screened in LLC-luc cells using the Siluc reporter system to identify "high-escape" and "low-escape" LNPs with significantly different lysosomal escape efficiencies. The subcellular localization of LNPs will be dynamically tracked using confocal microscopy to precisely determine their escape time window. Subsequently, at the critical time point of escape, Ce6 photoactivated proximity labeling technology will be used to spatiotemporally label host proteins proximal to LNPs, and interacting protein groups will be identified by mass spectrometry analysis. Candidate regulatory proteins will be screened by comparing the differential interacting proteins of high and low escape LNPs. Finally, CRISPR-Cas9 gene knockout technology will be used to verify the functional role of key proteins in LNP lysosomal escape. **Expected Conclusions:** This study is expected to establish a direct correlation map between LNP lipid composition and lysosomal escape efficiency, revealing key lipid chemical features that affect escape efficiency. For the first time, the dynamic interaction network between LNPs and host proteins will be captured at the precise spatiotemporal node of lysosomal escape, and several key host factors (such as specific membrane fusion proteins, lipid transfer proteins, or ion channels) that mediate or hinder the escape process will be identified. These findings will elucidate the molecular mechanism of LNP lysosomal escape, provide a theoretical basis and new engineering targets for the rational design of efficient delivery systems, and promote the development of nucleic acid drug delivery technology.

Microalgae-Derived Biomaterials Applications: This illustration visually represents the diverse applications of biomaterials derived from microalgae. The central image depicts microalgae, branching out to showcase its use in drug delivery (e.g., a localized drug release system), wound healing (e.g., a hydrogel patch applied to a wound), and tissue regeneration (e.g., a scaffold promoting new tissue growth).

Low concentrations of compound Af can stimulate tumor-associated macrophages (TAMs) to adopt an M1-like anti-tumor phenotype. Furthermore, the 'find me' and 'eat me' signals released by Af-induced glioblastoma multiforme (GBM) cells can further enhance the killing of GBM cells by M1-like TAMs. Af can exert toxicity on GBM cells through this TAM-dependent effect. High concentrations of Af disable TAMs and disrupt the interaction between GBM cells and TAMs, such as the positive feedback loop mediated by IL-6/STAT3, thereby eliminating its pro-GBM functions. By targeting GBM with Af-loaded platelets for Af delivery, it can synergize with chemotherapy and immunotherapy to produce anti-GBM efficacy. By loading Af together with the sonosensitizer fluorescein (Flu) onto platelets and then combining these dual-loaded platelets with directional ultrasound irradiation of GBM, Af and Flu can be targeted and actively delivered to GBM through 'ultrasound-controlled release', thereby enhancing the activity of Flu-mediated GBM sonodynamic therapy (GBM-SDT).

A schematic diagram illustrating the molecular mechanism by which the extracellular matrix protein Fibronectin (FN) promotes viral infection. FN interacts with the grass carp reovirus (GCRV) outer capsid protein VP7 and the host membrane receptor protein ITGB1, activating the NF-κB signaling pathway and cytoskeletal protein rearrangement, inducing the formation of "pseudopodia" on the cell surface, and promoting viral infection. The pro-viral mechanism of FN is evolutionarily conserved and also applies to other aquatic viruses such as SVCV and KHV, as well as the mammalian virus VSV.

APPROVED Conceptual schematic illustrating the workflow for identifying and validating potential therapeutic targets of Polyphyllin III in breast cancer. The schematic, designed in a Nature-style format with a clean white background and horizontal left-to-right flow, begins with public breast cancer cohorts and clinical datasets, such as TCGA and METABRIC, represented by database icons and patient silhouettes. A central module depicts the bioinformatic integration of subtype-stratified gene expression analysis, focusing on potential targets including HER2, STAT3, Bcl-2 family proteins, and HIF-1α, across Luminal A, Luminal B, HER2-enriched, and TNBC subtypes. Conceptual association links connect target expression levels with clinical endpoints, specifically overall survival and recurrence-free survival, using abstract survival curve icons. A parallel branch illustrates a comparison between paclitaxel-sensitive and paclitaxel-resistant cohorts, highlighting differential target expression and its association with therapy response. The schematic emphasizes the clinical relevance of these findings.

2.2 Elucidate the key molecular mechanisms of polyphyllin III's action on different subtypes of breast cancer cells. ① Based on previous sensitivity difference results, select four cell lines: MCF-7 (Luminal A), BT-474 (Luminal B), SK-BR-3 (HER2-enriched), and MDA-MB-231 (TNBC). Use RNA-seq technology to systematically compare the transcriptome changes of each subtype before and after polyphyllin III treatment. Focus on the enrichment of apoptosis, oxidative stress, and subtype-specific signaling pathways (such as ER, HER2, STAT3), and screen for key differentially expressed genes. Combine Western blotting and qRT-PCR to verify the expression changes of candidate targets (such as Bcl-2 family members, NOXA, PUMA, EGFR, p-STAT3, etc.), and identify the core effector molecules with the most significant response in each subtype. ② Conduct functional intervention experiments targeting the dominant mechanisms of each subtype: In TNBC, set up a control group, a polyphyllin III group, an NAC (ROS scavenger) group, and a polyphyllin III + NAC group to detect apoptosis (Cleaved Caspase-3/PARP), ROS levels, mitochondrial membrane potential, and JNK/p38 phosphorylation status. In HER2⁺ cells, set up a control group, a polyphyllin III group, and a HER2 overexpression/knockdown group to evaluate HER2-AKT/ERK pathway activity and cell survival rate. In Luminal A cells, combine ER inhibitors (fulvestrant) or ERα siRNA to observe whether drug resistance is reversed. At the same time, evaluate functional phenotypic changes through Annexin V/PI flow cytometry, cell cycle analysis, and scratch/Transwell experiments. ③ Construct stable knockout or overexpression cell lines of key node genes (such as HIF-1α, STAT3, or HER2) to verify their necessity in polyphyllin III-induced cell death, signal inhibition, and phenotypic changes, and detect related protein ubiquitination or subcellular localization changes, thereby establishing the core molecular mechanism axis driving drug efficacy differences in each subtype.

A graphical abstract illustrating BPS-induced neurotoxicity in mice via the gut-brain axis.

APPROVED Scientific Illustration Style and Rendering Guidelines: Illustrations should adhere to a scientific illustration style, characterized by flat vector graphics, clean lines, and a white background. All figures must be high-resolution and suitable for publication. Color coding should be consistent with the following scheme: * Biological processes: green * Electrochemical processes: blue * AI & control intelligence: cyan Decorative or artistic elements are prohibited. Layout: The illustration should consist of four vertical panels arranged from left to right with balanced spacing and thin separators. Panel 3 (AI & integration) should be visually dominant. Panel 1 – Circular Feedstock Input: This panel should depict a circular feedstock input using standard scientific icons to represent food waste, animal manure, and wastewater. These inputs should converge into a single funnel labeled "high-strength organic feedstock." A circular arrow motif should be included to indicate the circular bioeconomy concept. No explanatory text is permitted in this panel. Panel 2 – Two-Stage Bioelectrochemical Conversion: * Top: A dark fermentation bioreactor (cylindrical vessel) should be shown. Arrows should indicate the conversion of organic matter into H₂ (gas bubbles) and a VFA-rich effluent. * Bottom: A schematic of a microbial electrolysis cell should be displayed, including the anode, cathode, proton exchange membrane, and external circuit. Show electro-