AI Scientific Illustration Gallery

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-

Design a clean, high-resolution graphical abstract suitable for journal publication (flat scientific style, soft gradients, white background, minimal decorative elements) illustrating an AI-integrated dark fermentation–microbial electrolysis cell (DF–MEC) system for biohydrogen production. Layout (4 vertical panels, left → right): Panel 1 – Circular Feedstock Input: Icons representing food waste, livestock manure, and wastewater converging into a funnel labeled "high-strength organic waste," emphasizing a circular bioeconomy approach. Employ minimal labeling and standardized scientific icons. Panel 2 – Two-Stage Bioprocess: Top: Dark Fermentation reactor depicting H₂ production and VFA-rich effluent generation (simple arrows, gas bubbles). Bottom: Microbial Electrolysis Cell (MEC) illustrating anode oxidation of VFAs, electron flow through an external circuit, proton transport across a membrane, and hydrogen evolution at the cathode. Utilize schematic electrochemical symbols and minimal annotations. Panel 3 – AI-Enabled Intelligence & System Integration (Core Focus): Central AI

Create a clear and aesthetically pleasing scientific diagram for a school poster, in a vector academic illustration style, divided into three vertical or horizontal panels connected by progression arrows, representing the levels of organization of a chicken eggshell. At the scale of the shell (middle or central panel): Detailed cross-sectional view of the eggshell. Clearly label the layers from the outside to the inside: • Outer cuticle (antibacterial barrier) • Palisade layer (vertical calcite columns) • Mammillary cores (anchoring points) • Shell membranes (interwoven protein fibers) Add a small magnifying glass or zoom showing the organized calcite crystals. At the system level (in the uterus) – left or top panel: Simplified diagram of the uterus of the hen's oviduct. Show the egg forming surrounded by uterine fluid. Annotations: • Complete formation in ≈ 20 hours • Specific proteins (ovocleidin)

Title: Delayed Immunomodulation Reverses Functional Connectivity and Motor Deficits in Adulthood After Neonatal Hypoxia-Ischemia (HI) Authors: Sanjana Mandhan, Eric Chin, Anushka Acharya, Riddhi Patel, Fabiola Beatriz Santiago Maldonado, Diana Ortega, Hawley Helmbrecht, Shenandoah Robinson, Lauren Jantzie. Background: Neonatal hypoxic-ischemic encephalopathy (HIE) occurs when the newborn brain is deprived of oxygen and blood flow around the time of birth. It remains a major cause of lifelong neurological and developmental disability in term infants. The resulting inflammation, oxidative stress, and cell death disrupt normal brain development, leading to long-term problems in movement, learning, and cognition. Current treatments such as therapeutic hypothermia provide only limited protection and do not completely prevent these functional disabilities. To this end, we repurposed an immunomodulatory cocktail containing melatonin to test the hypothesis that disrupted functional neural

LLM-based drug recommendation + safety (DDI) + long-tail/imbalance + molecular structure alignment + Stage2 frequency-aware fusion. Top Left: LLM output resulting in a safety failure due to drug-drug interaction. Illustrate the input for a patient visit 't' (Dx/Proc/Text) → LLM → Recommended drug set {A, B, C}. Within {A, B, C}, highlight a DDI pair (e.g., A–B) with a red lightning bolt, and label it as "unsafe combination / DDI". Top Right: Why this occurs (lack of structural constraints). Label it as "atomic label embeddings + co-occurrence shortcut". Illustrate an unstructured label space: drug points are disorganized, and unsafe pairs are in close proximity. Bottom Left: Long-tail/imbalance failure. Include a frequency binning histogram from MIMIC-IV (0–50, 50–100…>5000), showing a high head and a long tail. Label it as "tail labels: sparse supervision → poor recall / calibration". Bottom Right: Our solution (structure + frequency-aware). Stage 1: Drug node graph (DDI edges in red, EHR co-occurrence edges in blue, temporal edges as dashed lines), where each ATC3 is a 'multi-prototype' small cluster. Stage 2: Schematic bar weights illustrating LLM + frequency-aware fusion (tail relies more on molecule prior; head relies more on task signal).

The following hypothesis is proposed: BMSC-Exos act on intestinal cells, upregulating and regulating endogenous ACSF2 expression, enhancing mitochondrial fatty acid activation and promoting mitochondrial β-oxidation (FAO), thereby improving mitochondrial function, reducing ROS levels, and inhibiting the NF-κB inflammatory pathway, ultimately promoting intestinal mucosal repair and achieving a therapeutic effect on Crohn's disease. Based on this and previous conversations, could you help me create a schematic diagram of the research effects and hypotheses?

Applications of Artificial Intelligence in Fixed Tooth-Supported Prosthodontics: A Systematic Review Abstract Background: Artificial intelligence is being increasingly integrated into dental practice, especially within fixed prosthodontics. Its application demonstrates potential for improving diagnostic precision, aiding clinical workflows, and enhancing the quality of dental restorations. Nevertheless, despite its increasing adoption, robust and consolidated evidence concerning its efficacy in essential prosthodontic procedures remains limited. Objective: To thoroughly assess the effectiveness of artificial intelligence-based systems in tooth-supported fixed prosthodontics, emphasizing their applications in automated crown design, margin and finish-line identification, crack detection, and the analysis of retention loss in fixed partial dentures. Methods: A systematic literature search was conducted across several databases, including PubMed, Scopus, Google Scholar, and Web of

A Transwell image, 6-well plate.

Style: Clean scientific schematic with a white background, minimal text, and flat vector icons arranged horizontally. Left-to-right flow, emphasizing a scientific approach with no legends and concise text. Layout: Two connected panels: Stage 1 (left) transitions to Stage 2 (right). Stage 1: Electro-Assisted Dark Fermentation (DFMEC). A single anaerobic reactor contains an anode and cathode, connected to a power supply illustrating electron flow from anode to cathode. Inputs: Food waste (C-rich), swine manure (N-rich), optimized C/N ratio, and self-buffering. Inside the reactor: Mixed fermentation broth and SCG-derived biochar coated with a redox-active polymer. Short label: "Zoom in showing Redox-engineered SCG–PEDOT biochar." Key functions (icons): Electron shuttling / DIET. Electrode potential control → NADH/NAD⁺ regulation, indicating that a higher ratio enhances H₂ production, while a lower ratio enhances VFA production. Outputs: H₂ gas (bubbles leaving the reactor). Effluent arrow labeled: "VFA-rich (acetate)". Stage 2: Microbial Electrolysis Cell (MEC).

APPROVED Category: Biomedical Translation: Schematic diagram of a two-stage bioprocess for enhanced hydrogen and volatile fatty acid (VFA) production from organic waste. The diagram features a clean, scientific style with a white background, minimal text, and flat vector icons, illustrating a left-to-right flow. Stage 1: Electro-Assisted Dark Fermentation (DFMEC) A single anaerobic reactor containing an anode and cathode connected to a power supply, indicating electron flow from anode to cathode. Inputs include carbon-rich food waste and nitrogen-rich swine manure. The reactor contains a mixed fermentation broth and redox-engineered biochar composed of spent coffee grounds (SCG) coated with a redox-active polymer (PEDOT). A zoomed-in view highlights the redox-engineered SCG–PEDOT biochar. Key functions: * Electron shuttling / Direct Interspecies Electron Transfer (DIET) * Electrode potential control regulating the NADH/NAD+ ratio, where a higher ratio enhances H2 production and a lower ratio enhances VFA production. Outputs: * H2 gas (bubbles leaving the reactor) * Effluent stream labeled "VFA-rich (acetate)" Stage 2: Microbial Electrolysis Cell (MEC) A two-chamber MEC separated by a membrane. The anode chamber contains an acetate-oxidizing biofilm and exoelectrogenic microorganisms.

APPROVED. Clean, professional scientific schematic depicting a two-panel horizontal layout with a white background, flat vector icons, minimal text, and a left-to-right process flow with color-coded stages. The schematic illustrates Stage 1 (left) and Stage 2 (right) connected by an effluent flow arrow. Stage 1 details Electro-Assisted Dark Fermentation (DFMEC) with a single anaerobic fermentation reactor containing an anode and cathode connected by an external power supply. Inputs include food waste (labeled "C-rich") and swine manure (labeled "N-rich"). Inside the reactor, a mixed substrate slurry and SCG-derived biochar coated with redox-active polymer (labeled "Redox-engineered SCG–PEDOT biochar (DIET & EET)") are shown. The anode and cathode are immersed in the fermentation broth and connected to a small power supply. Key innovations highlighted are "Redox-active electron interface" near the biochar and "Electrode potential control" near the electrodes. The metabolic effect is represented iconically.

1. In vitro CC50, IC50, and plaque assays of the HSP90 inhibitor AUY922 demonstrate its antiviral activity against GCRV. 2. Pre-incubation of cells with AUY922 validates its ability to prevent GCRV infection by inhibiting the expression of genes related to cell membrane receptors, inflammation, and apoptosis. 3. Co-incubation of cells with AUY922 validates its anti-GCRV activity by inhibiting the expression of genes related to cell membrane receptors, inflammation, and apoptosis. 4. Post-incubation of cells with AUY922 validates its therapeutic effect against GCRV infection by inhibiting the expression of genes related to cell membrane receptors, inflammation, and apoptosis. 5. Cell-based assays using inflammation and apoptosis agonists confirm that AUY922 exerts its antiviral activity by inhibiting the expression of inflammation- and apoptosis-related genes. 6. Individual-level validation using techniques such as immunofluorescence, RT-PCR, Western blotting, electron microscopy, and immunohistochemistry confirms that AUY922 inhibits the expression of genes related to cell membrane receptors, inflammation, and apoptosis, thereby exerting its anti-GCRV activity.