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依据科研计划书中科研方法部分（一个是按照实验设计思路写的，一个是具体的实验方法），设计一个技术路线图...

創建於：2025年12月29日

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問題

科研计划书_焦_12.28.docx
科研计划书_焦_12.25.docx

依据科研计划书中科研方法部分（一个是按照实验设计思路写的，一个是具体的实验方法），设计一个技术路线图，以具体如何实施为基础，绘制如何建模，建模后取了什么材，分别用作什么实验，达成什么结果等

思考

Creating the roadmap

I’m preparing a visual or text-based technical roadmap diagram for the user, consulting their research methods section and integrating both experimental design and specific methods. Using technology tools to generate and cite this accurately.

Parsing documents

I’m using python-docx to read and parse the 12.28 and 12.25 docx files, focusing on headings and methods sections to ensure a comprehensive technical roadmap.

Focusing on key segments

I’m honing in on paragraphs by their indices, strategically pulling out the most impactful sections. This helps in shaping a concise overview, enhancing understanding.

Taking a closer look
Wondering about how the docx file's rich formatting and possibly embedded images or text boxes might be affecting its content visibility, making table extraction necessary.

Mapping out elements

Listing 78 and 101text pieces. Considering indices and key terms like "科研方法" for a targeted approach.

Identifying key areas

I’m thinking through the method section, focusing on indices ranging from 44 to 80 to capture the relevant text.

Navigating truncated output

OK, let's clarify that lines 49-64 were skipped due to Jupyter's ellipsis, despite printing from 35-80.

Spotting the difference

I'm noting that the 12.28 version lists 65 "技术路线图" but lacks an actual image. The 12.25 version is expected to be more elaborate.

Adjusting extraction

Truncating lines up to 55 caused key details to be lost. Examining lines 55-80 to capture essential information on sample collection and experiments, ensuring all key details are included.

Evaluating print options

I’m considering not truncating key paragraphs and printing full text for indices 55, 56, and 58 in Python output. This might significantly increase print size.

Identifying truncation

I'm working through the issue of text truncation in DOCX files, noting how Python may miss segments due to zero-width breaks or Unicode ellipsis, while OBJ previews remain intact.

Charting the course

I’m mapping out a technical flowchart for Jak2V617F mutation research, detailing modeling, sample collection, and experiments across modules to achieve results and impact.

Piecing together elements

I'm crafting a technical route diagram, focusing on model building, atherosclerosis induction, and branching sample collection for experiments, aiming to show progress and relevant outputs.

Piecing together the plan

I'm outlining a detailed technical route for Jak2V617F mutation research, integrating model establishment, sample collection, and specific experiments to explore phenotype, mechanism, and intervention outcomes.

Designing the flowchart

I’m thinking through a multi-column flowchart for Jak2V617F mutation research, detailing model building, sample collection, and experiments across phenotype, mechanism, and intervention modules.

Generating flowchart diagrams

Setting up Graphviz for flowchart diagrams and considering SVG/PNG outputs. Exploring Chinese font support, possibly using "SimSun" or "Noto Sans CJK".

Verifying font installation

Hm, I’m thinking about whether Noto Sans CJK is installed on your system. There are other Noto fonts, but confirmation is key.

Mapping journey

I’m charting sample-to-assay connections, balancing clarity and detail. Using clusters to show relationships and results. Progress is steady: organizing, detailing, refining.

Arranging nodes

I'm organizing nodes by samples, assessing connections, and detailing assays and results to ensure a clear and systematic flow. This method creates a more organized flowchart.

Streamlining

I’m organizing the flowchart by focusing on outcome nodes: phenotype, mechanism, and intervention. Each node is connected to relevant assay nodes, leading to a cleaner, more intuitive design.

Processing images

I'm working on generating PNG and SVG files using the dot format. This involves parsing the dot file and producing these common image formats.

Ensuring layout fidelity

Reviewing PNG to confirm Chinese rendering and layout accuracy.

Revising layout

I'm wondering if a vertical layout with sections for hypothesis, model building, induction, harvest, and experiments might improve clarity and manageability.

Managing complexity

I'm focusing on simplifying the layout by clustering sections like hypothesis, model steps, induction, harvest, and interventions, and clearly linking key samples and assays within each module.

Converting files

I’m pulling together the file formats for PNG and SVG.

Summarizing progress

I'm mapping out the key points and ideas, shaping the content through a quick read.

Mapping the technical route

I’m considering the compact layout and providing various download options. Citations will align with user methods, and DOT files will be included for easy editing.

Ensuring comprehensive coverage

I’m making sure the technical route mapping includes all necessary experiments, interventions, and sample allocations to effectively achieve the desired outcomes.

Mapping and timeline

I’m creating a concise mapping table for samples, experiments, and readouts, including timeline details like BMT induction, reconstitution, and drug intervention.

Crafting response

I'm including filecite tokens for source plan docs and avoiding raw terms. A markdown table for sample-assay mapping, with minimal effort on the mermaid code.

Reasoned for 17m 39s

回答

已根据你计划书里“总体实验设计思路 + 具体实验方法”把建模→取材→分流做哪些实验→得到哪些读出/结论串成一张更“可实施”的技术路线图，并做成了可编辑PPT版（方便你直接截图/导出图片放进计划书）。

下载：技术路线图（可编辑PPT）

同时附上一个可复制的 Mermaid 技术路线图代码（你也可以用它在支持Mermaid的工具里一键生成图，再截图插入Word）。

(科研计划书_焦_12.28.docx) (科研计划书_焦_12.25.docx)

技术路线图（Mermaid 可渲染版本）

mermaid
flowchart TB
  %% =========================
  %% ① 建模与时间轴
  %% =========================
  subgraph A[① 模型构建与时间轴（同一模型贯穿：表型确认→机制解析→干预验证）]
    A0[小鼠准备\n供体：Mx1-Cre;Jak2V617F & WT\n受体：Ldlr-/-（6–8周雌鼠）\n随机分组+盲法编码] --> 
    A1[供体诱导\npI:pC 10 mg/kg i.p. q48h×3\n等待约4周稳定表达]
    A1 --> A2[骨髓移植建模\n受体10.5 Gy致死照射（分次）\n尾静脉注射5×10^6 BM细胞]
    A2 --> A3[嵌合分组（含CHIP模拟）\nWT→Ldlr-/-(对照)\nJak2V617F→Ldlr-/-(全量嵌合)\n20%Jak2V617F+80%WT→Ldlr-/-(低负荷/CHIP)]
    A3 --> A4[造血重建4–6周\nQC：外周血流式(嵌合率：GFP或CD45.1/2)\n+血常规(NEU/PLT等)]
    A4 --> A5[WTD诱导动脉粥样硬化\n约7周（~21%脂肪，0.15–0.2%胆固醇）]
    A5 --> A6[体内干预（因果性验证）\nWTD第4–6周启动\n雷帕霉素(mTOR抑制) ± HIF通路调控\n毒性/耐受监测：体重、血常规、肝肾功能]
  end

  %% =========================
  %% ② 终点取材与样本分配
  %% =========================
  A6 --> B[② 终点取材与样本分配（血液—血管—分选—多模态检测）]
  B --> B1[血液（心穿）\nEDTA：流式/分选/功能实验\n血清或肝素：血脂 + 炎症因子 + 组学]
  B --> B2[主动脉根部（组织学主阵地）\n固定切片：H&E / Masson或天狼猩红\nIF/IHC：Ly6G/MPO、p-S6、HIF-1α等]
  B --> B3[全主动脉铺片\nOil Red O：脂质沉积面积]
  B --> B4[主动脉弓\n酶消化→单细胞流式\n分选Ly6G+CD11b+中性粒细胞\n用于Phosflow/WB/qPCR/RNA-seq/代谢探针/功能实验]

  %% =========================
  %% ③ 三大实验模块
  %% =========================
  subgraph C[③A 表型解析：先确认“斑块结局↑ + 中性粒细胞异常↑”】【表型】]
    C1[斑块负担/稳定性\nH&E：斑块面积、坏死核心\nMasson/天狼猩红：胶原/纤维帽\nORO铺片：整体脂质负担]
    C2[斑块中性粒细胞浸润\nIF/IHC：Ly6G、MPO\n流式：CD45+Ly6G+CD11b+数量/比例]
    C3[中性粒细胞激活与NETosis\nROS：DHR123/化学发光\nNETs：SYTOX Green + CitH3/MPO-DNA验证\nNPA：Ly6G+细胞表面CD41/CD42b]
    C4[表型结论读出\nJak2V617F组：浸润↑、NETosis/ROS/NPA↑\n伴随斑块面积↑、坏死核心↑、稳定性下降]
  end

  subgraph D[③B 机制解析：mTOR–HIF‑1α → 脂代谢重编程 → 功能放大”】【机制】]
    D1[通路激活证据\n组织：Ly6G共定位p-S6、HIF-1α\n细胞：Phosflow(p-S6/p-4EBP1)、核内HIF-1α\nWB/qPCR：通路及靶基因(Glut1/Hk2/Ldha等)]
    D2[代谢表型（中性粒细胞）\n脂滴：BODIPY 493/503\n脂肪酸摄取：BODIPY FL C16\n游离胆固醇：filipin\n可选：13C示踪区分丰度 vs 通量]
    D3[组学网络\n分选Ly6G+ RNA-seq→GSEA(mTOR/HIF/脂代谢)\n血浆/中性粒细胞/斑块脂质组&代谢组]
    D4[机制链条读出\n“通路↑ → 脂代谢↑ → NETosis/黏附/趋化↑”\n形成闭环证据链]
  end

  subgraph E[③C 干预与转化：验证“抑制通路→代谢可逆→功能可逆→结局改善”】【干预】]
    E1[体内干预终点\n雷帕霉素±HIF调控后：复测斑块负担/稳定性\n同步检测血脂/炎症因子\n靶点命中：p-S6/HIF-1α变化]
    E2[体外/离体干预\n分离/分选中性粒细胞短时加药\n检测：p-S6/HIF-1α、脂滴/摄取/胆固醇\n功能：NETosis/ROS、趋化(Transwell)]
    E3[炎症-血栓轴与内皮互作\n活体显微镜：滚动/黏附\n剪切流黏附：Ibidi μ-slide(ICAM-1/VCAM-1/P-selectin)\nNPA变化]
    E4[干预结论读出\n通路抑制 → 代谢下降 → NETosis/黏附下降\n→ 斑块负担下降/稳定性改善\n并沉淀生物标志物（p-S6、HIF-1α、脂滴/NETs）]
  end

  %% 连接样本到模块
  B --> C
  B --> D
  B --> E

“建模后取材→分别做什么实验→达成什么结果”一页式分流表

阶段取材/样本主要去向（做哪些实验）关键读出（你路线图里要写清的“结果”）
建模QC外周血嵌合率（GFP或CD45.1/2流式）、血常规模型质量控制：嵌合成功；NEU/PLT等作为协变量/表型线索
WTD+干预过程体重、一般状态；血常规；肝肾功能安全性/耐受性监测确保干预可解释：排除明显毒性导致的假阳性/假阴性
终点-血液EDTA血流式：NPA（Ly6G+CD41/42b）；中性粒细胞分离后做ROS/NETosis；必要时分选Ly6G+用于通路检测炎症-血栓轴/NETosis功能读出：Jak2V617F组↑；干预后↓
终点-血清/血浆血清/肝素血血脂(TC/TG/HDL-C)；炎症因子(IL‑1β、TNF‑α、IL‑6、CXCL1/2等)；可做代谢组/脂质组系统层面协同证据：炎症负荷与斑块结局/中性粒细胞表型联动；干预后改善
终点-主动脉根部固定切片H&E：斑块面积、坏死核心；Masson/天狼猩红：胶原/纤维帽；IF/IHC：Ly6G/MPO、p‑S6、HIF‑1α（与Ly6G共定位）斑块结局 + 通路在位证据：Jak2V617F组斑块更重/更不稳；p‑S6/HIF‑1α在Ly6G+细胞中↑
终点-全主动脉铺片Oil Red O整体斑块负担宏观读出：Jak2V617F组↑；干预后↓
终点-主动脉弓单细胞酶消化细胞悬液流式定量浸润中性粒细胞（CD45+Ly6G+CD11b+）；分选Ly6G+做Phosflow/WB/qPCR/RNA-seq/代谢探针“浸润↑ + 通路↑ + 代谢↑”细胞层证据链
分离/分选中性粒细胞（血/主动脉弓）纯化Ly6G+细胞Phosflow：p‑S6/p‑4EBP1；核内HIF‑1α；代谢探针：BODIPY493/503、BODIPY‑C16、filipin；功能：NETosis/ROS/趋化核心机制闭环：mTOR–HIF‑1α激活 → 脂代谢重编程 → NETosis/黏附/趋化增强；药物可逆
血栓相关/内皮互作模块活体显微镜、剪切流黏附系统滚动/黏附计数；Ibidi μ-slide(ICAM‑1/VCAM‑1/P-selectin)黏附定量“炎症-血栓轴”功能终点：Jak2V617F组增强；干预下降

你在图里建议明确写出的“关键对照与结论句式”

为了让路线图“像真的会做、且能回答问题”，图中每个模块建议都配一句比较关系 + 结论：

  1. 模型层对照
  • WT→Ldlr-/- vs Jak2V617F→Ldlr-/-（稳健表型）
  • WT→Ldlr-/- vs 20%Jak2V617F嵌合（贴近CHIP转化场景）
  1. 机制链条（用箭头写在图底部）
  • Jak2V617F（造血背景） → 中性粒细胞 p‑S6/HIF‑1α↑ → 脂滴/脂肪酸摄取/胆固醇↑ → NETosis/ROS/黏附↑ → 斑块进展与不稳定
  1. 因果验证（干预）
  • Jak2V617F+WTD+Vehicle vs Jak2V617F+WTD+Rapamycin（±HIF调控）
  • 结论写法：“靶点命中（p‑S6/HIF‑1α改变）→代谢读出下降→功能读出下降→斑块结局改善”

如果你希望我把这张路线图按你学校常用格式再做一个“更像论文图1”的版本（比如横向时间轴+下方三栏模块、或按“研究内容1/2/3”三段式），我也可以直接在你这份PPT里改出第二版排版给你对比使用。

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