Update app.py

app.py

@@ -800,6 +800,123 @@ with gr.Blocks(css=css, title="K R&D Lab · S1 Biomedical") as demo:
                     gr.Markdown("> Coming next — validates S1-R9 results against GEO plasma proteomics datasets.")
 
         # ── 📓 JOURNAL ──────────────────────────────────────
+        # ── 🧠 S1-F · PHYLO-RARE ───────────────────────────
+        with gr.TabItem("🧠 PHYLO-RARE"):
+            gr.HTML(section_header(
+                "S1-F", "PHYLO-RARE", "— Where almost nobody has looked yet",
+                "<b style='color:#ef4444'>⚠️ &lt;300 cases/yr · &lt;5% survival · 0–1 prior studies per gap</b><br>"
+                "S1-R12b DIPG (H3K27M) 🔶 &nbsp;·&nbsp; "
+                "S1-R12c UVM (GNAQ/GNA11) 🔶 &nbsp;·&nbsp; "
+                "S1-R12d pAML (FLT3-ITD) 🔶"
+            ))
+            with gr.Tabs(elem_classes="inner-tabs"):
+
+                with gr.TabItem("S1-R12b · DIPG"):
+                    gr.HTML(proj_badge(
+                        "S1-F · PHYLO-RARE · S1-R12b",
+                        "DIPG Toolkit — H3K27M · CSF LNP · Circadian Biology",
+                        "PBTA · GSE126319"
+                    ))
+                    gr.Markdown(
+                        "> **Why DIPG?** Diffuse Intrinsic Pontine Glioma — median survival 9–11 months. "
+                        "H3K27M oncohistone in **78%** cases. "
+                        "CSF delivery is the only viable route past the brainstem BBB. "
+                        "Circadian disruption (BMAL1 suppression) newly linked — **0 prior LNP studies**."
+                    )
+                    with gr.Tabs(elem_classes="inner-tabs"):
+                        with gr.TabItem("Variants"):
+                            sort_d = gr.Radio(["Frequency", "Drug status"], value="Frequency", label="Sort by")
+                            b_dv   = gr.Button("Load DIPG Variants", variant="primary")
+                            o_dv   = gr.Dataframe(label="H3K27M co-mutations · PBTA/GSE126319")
+                            b_dv.click(dipg_variants, sort_d, o_dv)
+                        with gr.TabItem("CSF LNP Formulations"):
+                            with gr.Row():
+                                d_peg  = gr.Slider(0.5, 3.0, value=1.5, step=0.1, label="PEG mol%")
+                                d_size = gr.Slider(60, 150, value=90, step=5, label="Target size (nm)")
+                            b_dc  = gr.Button("Rank CSF Formulations", variant="primary")
+                            o_dct = gr.Dataframe(label="CSF LNP ranking")
+                            o_dcp = gr.Image(label="ApoE% in CSF corona")
+                            b_dc.click(dipg_csf, [d_peg, d_size], [o_dct, o_dcp])
+                        with gr.TabItem("Research Gap"):
+                            gr.Markdown(
+                                "**Data:** PBTA (n=240) · GSE126319 (n=28) · GTEx circadian genes\n\n"
+                                "| Layer | Known | This study gap |\n"
+                                "|-------|-------|----------------|\n"
+                                "| Genomics | H3K27M freq=78% | H3K27M × BMAL1/CLOCK |\n"
+                                "| Delivery | CED convection | LNP corona **in CSF** |\n"
+                                "| Biology | PRC2 inhibition | Ferroptosis in H3K27M+ DIPG |"
+                            )
+
+                with gr.TabItem("S1-R12c · UVM"):
+                    gr.HTML(proj_badge(
+                        "S1-F · PHYLO-RARE · S1-R12c",
+                        "UVM Toolkit — GNAQ/GNA11 · Vitreous Corona · m6A",
+                        "TCGA-UVM n=80"
+                    ))
+                    gr.Markdown(
+                        "> **Why UVM?** Uveal Melanoma — metastatic 5-yr survival **15%**. "
+                        "GNAQ/GNA11 mutations in 78% cases. "
+                        "Vitreous humor protein corona has **never been profiled**. "
+                        "METTL3/WTAP upregulated in GNAQ+ tumors — 0 therapeutic studies."
+                    )
+                    with gr.Tabs(elem_classes="inner-tabs"):
+                        with gr.TabItem("Variants + m6A"):
+                            b_uv = gr.Button("Load UVM Variants", variant="primary")
+                            o_uv = gr.Dataframe(label="GNAQ/GNA11 map · TCGA-UVM")
+                            b_uv.click(uvm_variants, [], o_uv)
+                        with gr.TabItem("Vitreous LNP"):
+                            b_uw  = gr.Button("Rank Vitreous Formulations", variant="primary")
+                            o_uwt = gr.Dataframe(label="Vitreous LNP retention ranking")
+                            o_uwp = gr.Image(label="Retention (hours)")
+                            b_uw.click(uvm_vitreous, [], [o_uwt, o_uwp])
+                        with gr.TabItem("Research Gap"):
+                            gr.Markdown(
+                                "**Data:** TCGA-UVM (n=80) · GEO m6A atlases · Vitreous proteomics\n\n"
+                                "| Layer | Known | This study gap |\n"
+                                "|-------|-------|----------------|\n"
+                                "| Genomics | GNAQ/GNA11 mutations | m6A landscape GNAQ+ vs GNA11+ |\n"
+                                "| Delivery | Intravitreal injection | LNP corona **in vitreous humor** |\n"
+                                "| Biology | PLCβ→PKC→MAPK | GNAQ × METTL3 × YTHDF2 axis |"
+                            )
+
+                with gr.TabItem("S1-R12d · pAML"):
+                    gr.HTML(proj_badge(
+                        "S1-F · PHYLO-RARE · S1-R12d",
+                        "pAML Toolkit — FLT3-ITD · Bone Marrow Corona · Ferroptosis",
+                        "TARGET-AML n≈197"
+                    ))
+                    gr.Markdown(
+                        "> **Why pAML?** Pediatric AML — relapse OS **<30%**. "
+                        "FLT3-ITD in 25% cases. "
+                        "Bone marrow niche LNP corona: **never studied**. "
+                        "Ferroptosis–FLT3 intersection: 0 prior studies (FerrDb v2 confirmed)."
+                    )
+                    with gr.Tabs(elem_classes="inner-tabs"):
+                        with gr.TabItem("Ferroptosis Explorer"):
+                            var_sel = gr.Dropdown(
+                                ["FLT3-ITD", "NPM1 c.860_863dupTCAG", "DNMT3A p.R882H",
+                                 "CEBPA biallelic", "IDH1/2 mutation"],
+                                value="FLT3-ITD", label="Select variant"
+                            )
+                            b_pf  = gr.Button("Analyze Ferroptosis Profile", variant="primary")
+                            o_pft = gr.HTML()
+                            o_pfp = gr.Image(label="Target radar")
+                            b_pf.click(paml_ferroptosis, var_sel, [o_pft, o_pfp])
+                        with gr.TabItem("BM Niche LNP"):
+                            gr.Dataframe(
+                                value=pd.DataFrame(PAML_BM_LNP),
+                                label="Bone marrow niche LNP candidates · TARGET-AML context"
+                            )
+                        with gr.TabItem("Research Gap"):
+                            gr.Markdown(
+                                "**Data:** TARGET-AML (n=197) · BeatAML · FerrDb v2\n\n"
+                                "| Layer | Known | This study gap |\n"
+                                "|-------|-------|----------------|\n"
+                                "| Genomics | FLT3-ITD → Midostaurin | FLT3-ITD × GPX4/SLC7A11 |\n"
+                                "| Delivery | Liposomal daunorubicin | LNP corona **in bone marrow** |\n"
+                                "| Biology | Midostaurin inhibits FLT3 | Ferroptosis SL + FLT3i |"
+                            )
+
         with gr.TabItem("📓 Journal"):
             gr.Markdown("### Lab Journal\nEvery tool call auto-logged with project code.")
             with gr.Row():
@@ -882,4 +999,4 @@ with gr.Blocks(css=css, title="K R&D Lab · S1 Biomedical") as demo:
         "[KOSATIKS GROUP 🦈](https://kosatiks-group.pp.ua) · MIT License"
     )
 
-demo.launch()
+demo.launch(server_name="0.0.0.0", server_port=7860)