cloned from 'bitbucket', 2013/08/13

author: Alvin Li <liweitianux@gmail.com> 2013-08-13 14:13:24 +0800
committer: Alvin Li <liweitianux@gmail.com> 2013-08-13 14:13:24 +0800
commit: 9636d4a6767f49384d5c386bc3f1142c88b90613 (patch)
tree: 3a70f6d9e4be1791d36c87cc7cbfd1d5aa2b39dd /97suifangqa/apps/sciblog
parent: 9383d9a8a5988d071766c3d08a5c946e9c5b02ae (diff)
download: 97dev-9636d4a6767f49384d5c386bc3f1142c88b90613.tar.bz2
13 files changed, 1809 insertions, 0 deletions
diff --git a/97suifangqa/apps/sciblog/__init__.py b/97suifangqa/apps/sciblog/__init__.py
new file mode 100644
index 0000000..e69de29
--- /dev/null
+++ b/97suifangqa/apps/sciblog/__init__.py
diff --git a/97suifangqa/apps/sciblog/admin.py b/97suifangqa/apps/sciblog/admin.py
new file mode 100644
index 0000000..0dfb2ef
--- /dev/null
+++ b/97suifangqa/apps/sciblog/admin.py
@@ -0,0 +1,33 @@
+# -*- coding: utf8 -*-
+from django.contrib import admin
+from django import forms
+from django.db import models
+from .models import SciBlog, ResultContent, EndPoint
+from utils.widget import MarkitUpWidget, TinyMceWidget
+
+class ResultContentInline(admin.TabularInline):
+    model = ResultContent
+
+
+class SciBlogAdmin(admin.ModelAdmin):
+    #formfield_overrides = {
+    #    models.TextField: {'widget': TinyMceWidget},
+    #}
+    inlines = [
+        ResultContentInline,
+    ]
+
+def get_blogs(endp):
+    blog = endp.blogs.all()[0]
+    return "<a href='/admin/sciblog/sciblog/%s'>%s<a>" % (blog.id, blog.title)
+
+get_blogs.short_description = "SciBlog"
+get_blogs.allow_tags = True
+
+class EndPointAdmin(admin.ModelAdmin):
+    list_display = ('__unicode__', get_blogs)
+
+
+
+admin.site.register(SciBlog, SciBlogAdmin)
+admin.site.register(EndPoint, EndPointAdmin)
diff --git a/97suifangqa/apps/sciblog/fixtures/initial_data.json b/97suifangqa/apps/sciblog/fixtures/initial_data.json
new file mode 100644
index 0000000..6038ffe
--- /dev/null
+++ b/97suifangqa/apps/sciblog/fixtures/initial_data.json
@@ -0,0 +1,1042 @@
+[
+    {
+        "pk": 1,
+        "model": "sciblog.sciblog",
+        "fields": {
+            "subhead": "\u5c0f\u4e09\u9633\u6162\u6027\u4e59\u809d\u60a3\u8005\u901a\u8fc7\u805a\u4e59\u4e8c\u9187\u5e72\u6270\u7d20\uff0c\u6216\u8005\u957f\u6548\u5e72\u6270\u7d20\uff0c\u6cbb\u7597\u7684\u6548\u679c\u5982\u4f55\uff1f\u526f\u4f5c\u7528\u662f\u5426\u5f88\u5927\uff1f\u548c\u62c9\u7c73\u592b\u5b9a\u76f8\u6bd4\u600e\u4e48\u6837\uff1f",
+            "sample": [],
+            "readed_count": 0,
+            "references": [],
+            "catched_by": [
+                1,
+                4
+            ],
+            "query": [
+                72,
+                73,
+                74,
+                75
+            ],
+            "endpoint_content": "",
+            "treatment_content": "\u6309\u71671\uff1a1\uff1a1\u5206\u7ec4\u3002\r\n\u7b2c\u4e00\u7ec4\uff1a\u5e72\u6270\u7d20\u5358\u836f\u7ec4\uff1a180ug\u6bcf\u5468\u4e00\u6b21\u805a\u4e59\u4e8c\u9187\u5e72\u6270\u7d20alfa-2a\uff08\u6d3e\u7f57\u6b23\uff0c\u7f57\u6c0f\uff09\uff1b\r\n\u7b2c\u4e8c\u7ec4\uff1a\u5e72\u6270\u7d20\u62c9\u7c73\u592b\u5b9a\u8054\u7528\u7ec4\uff1a180ug\u6bcf\u5468\u4e00\u6b21\u805a\u4e59\u4e8c\u9187\u5e72\u6270\u7d20alfa-2a\uff08\u6d3e\u7f57\u6b23\uff0c\u7f57\u6c0f\uff09\u7684\u540c\u65f6\u6bcf\u5929\u670d\u7528100mg\u62c9\u7c73\u592b\u5b9a\uff08 Epivir-HBV or Zeffix\uff0c\u845b\u5170\u7d20\u53f2\u514b\uff09\uff1b\r\n\u7b2c\u4e09\u7ec4\uff1a\u62c9\u7c73\u592b\u5b9a\u5358\u836f\u7ec4\uff1a\u6bcf\u5929\u670d\u7528100mg\u62c9\u7c73\u592b\u5b9a\uff08 Epivir-HBV or Zeffix\uff0c\u845b\u5170\u7d20\u53f2\u514b\uff09\r\n48\u5468\u7597\u7a0b\uff0c\u6cbb\u7597\u7ed3\u675f\u540e\u7ee7\u7eed\u968f\u8bbf\u89c2\u5bdf24\u5468\u3002",
+            "baseline": [],
+            "title": "\u5355\u7528\u805a\u4e59\u4e8c\u9187\u5e72\u6270\u7d20alfa-2a\u3001\u62c9\u7c73\u592b\u5b9a\u5355\u7528\u3001\u805a\u4e59\u4e8c\u9187\u5e72\u6270\u7d20\u4e0e\u62c9\u7c73\u592b\u5b9a\u8054\u5408\u7528\u836f\u5728\u6cbb\u7597e\u6297\u539f\u9634\u6027\u6162\u6027\u4e59\u809d\u65f6\u7684\u6548\u679c\u4e0e\u5b89\u5168\u6027",
+            "clinic_conditions": [
+                14
+            ],
+            "hospital": [
+                1,
+                2,
+                3,
+                4
+            ],
+            "source": null,
+            "understanded_count": 0,
+            "safety": "\u4f1a\u4e0d\u4f1a\u53d1\u751fYMDD\u53d8\u5f02\uff1f\r\n\u7ed3\u675f\u6cbb\u7597\u65f6\uff0cYMDD\u53d8\u5f02\u53d1\u751f\u7387\u5728\u62c9\u7c73\u592b\u5b9a\u7ec4\u91cc\u9762\u662f18%\uff0c\u5728\u5e72\u6270\u7d20+\u62c9\u7c73\u592b\u5b9a\u8054\u5408\u7ec4173\u540d\u60a3\u8005\u4e2d\uff0c\u53ea\u67091\u4f4d\u60a3\u8005\u53d1\u751fYMDD\u53d8\u5f02\u3002\r\n\r\n\u4e0d\u826f\u53cd\u5e94\u6709\u54ea\u4e9b\uff1f",
+            "entitle": "Peginterferon Alfa-2a Alone, Lamivudine Alone, and the Two in Combination in Patients with HBeAg-Negative Chronic Hepatitis B",
+            "konwledge_piece": [
+                1,
+                2,
+                3,
+                24
+            ],
+            "method": "\u672c\u6587\u6d89\u53ca\u7684\u7814\u7a76\u662f\u968f\u673a\u3001\u90e8\u5206\u53cc\u76f2\u7814\u7a76\uff0c\u4ece\u5168\u7403\u591a\u4e2d\u5fc3\uff0813\u4e2a\u56fd\u5bb654\u4e2a\u4e2d\u5fc3\uff0c\u6709\u4e00\u90e8\u5206\u5728\u4e9a\u6d32\u548c\u6b27\u6d32\uff09\u62db\u52df\u60a3\u8005\u3002 \r\n\r\n\u7814\u7a76\u5206\u6790\u4e86\u4e09\u7ec4\u4eba\u7fa4\uff08\u805a\u4e59\u4e8c\u9187\u5e72\u6270\u7d20alfa-2a\u3001\u805a\u4e59\u4e8c\u9187\u5e72\u6270\u7d20alfa-2a\u4e0e\u62c9\u7c73\u592b\u5b9a\u8054\u5408\u7528\u836f\u3001\u62c9\u7c73\u592b\u5b9a\u5355\u836f\u6cbb\u7597\uff09\u7684\u6cbb\u7597\u540e\u60c5\u51b5\u3002\u4e09\u7ec4\u4eba\u7fa4\u90fd\u662f48\u5468\u7684\u6cbb\u7597\u7597\u7a0b\uff0c\u6cbb\u7597\u540e\u7814\u7a76\u4eba\u5458\u4f1a\u7ee7\u7eed\u968f\u8bbf\u8ddf\u8e2a24\u5468\u75c5\u60c5\u53d1\u5c55\u3002",
+            "conclusion": "e\u6297\u539f\u9634\u6027\u7684\u6162\u6027\u4e59\u809d\u60a3\u8005\u7684\u6301\u7eed\u5e94\u7b54\u7387\u5728\u542b\u6709\u5e72\u6270\u7d20\u7684\u6cbb\u7597\u7ec4\u4e2d\u7684\u60a3\u8005\u660e\u663e\u9ad8\u4e8e\u4ec5\u7528\u62c9\u7c73\u592b\u5b9a\u7684\u60a3\u8005\u3002\r\n\r\n\u6301\u7eed\u5e94\u7b54\u6307\u7684\u662f\u505c\u836f24\u5468\u5468\u540e\u4ecd\u6709\u5e94\u7b54\u3002\r\n\r\n\u5728\u5e72\u6270\u7d20\u7684\u6cbb\u7597\u57fa\u7840\u4e0a\u52a0\u4e0a\u62c9\u7c73\u592b\u5b9a\u8fdb\u884c\u8054\u5408\u4f5c\u7528\uff0c\u76f8\u5bf9\u4e8e\u53ea\u7528\u5e72\u6270\u7d20\u6cbb\u7597\u5e76\u6ca1\u6709\u63d0\u9ad8\u4ec0\u4e48\u6548\u679c\u3002",
+            "detectionAssay": "",
+            "ifvalue": 11.0,
+            "journal": "NEJM",
+            "authors": "Patrick Marcellin , M.D., George K.K. Lau, M.D., Ferruccio Bonino, M.D., Patrizia Farci, M.D., Stephanos Hadziyannis, M.D., Rui Jin, M.D., Zhi-Meng Lu, M.D., Teerha Piratvisuth, M.D., Georgios Germanidis, M.D., Cihan Yurdaydin, M.D., Moises Diago, M.D., Selim Gurel, M.D., Ming-Yang Lai, M.D., Peter Button, M.Sc., and Nigel Pluck, M.D., for the Peginterferon Alfa-2a HBeAg-Negative Chronic Hepatitis B Study Group",
+            "abstractAE": "\u5173\u4e8e\u4e0d\u826f\u53cd\u5e94\uff0c\u5305\u62ec\u53d1\u70ed\u3001\u4e4f\u529b\u3001\u808c\u75db\u3001\u5934\u75db\u5728\u5185\u7684\u4e0d\u826f\u53cd\u5e94\u5728\u542b\u6709\u5e72\u6270\u7d20\u7684\u6cbb\u7597\u7ec4\u4eba\u7fa4\u4e2d\u8981\u7a0d\u5fae\u5927\u4e00\u4e9b\u3002",
+            "confused_count": 0,
+            "collected_by": [
+                1,
+                4
+            ],
+            "guidline": 1,
+            "aim": "<p class=\"highlight\">\u672c\u7814\u7a76\u6240\u89c2\u6d4b\u7684\u662f\u805a\u4e59\u4e8c\u9187\u5e72\u6270\u7d20\uff08\u5355\u836f\u6cbb\u7597\u3001\u5e72\u6270\u7d20\u4e0e\u62c9\u7c73\u592b\u5b9a\u8054\u5408\u6cbb\u7597\u3001\u62c9\u7c73\u592b\u5b9a\u5355\u836f\u6cbb\u7597\u8fd93\u4e2d\u4e0d\u540c\u7684\u65b9\u6cd5\u6cbb\u7597e\u6297\u539f\uff08HBeAg\uff09\u9634\u6027\u6162\u6027\u4e59\u809d\u7684\u6548\u679c\u3001\u5b89\u5168\u6027\u3002</p>",
+            "publish_date": "2005-03-27",
+            "abstract_result": "24\u5468\u968f\u8bbf\u671f\u7ed3\u675f\u4ee5\u540e\uff0c\u8c37\u4e19\u8f6c\u6c28\u9176\uff08ALT\uff09\u7684\u590d\u5e38\u7387\uff08\u6062\u590d\u6b63\u5e38\u503c\u4ee5\u5185\u7684\u51e0\u7387\uff09\u6216\u8005\u4e59\u809d\u75c5\u6bd2\uff08HBV\uff09 DNA\u6c34\u5e73\u964d\u4f4e\u523020,000\u62f7\u8d1d/mL\u7684\u51e0\u7387\u5728\u63a5\u53d7\u542b\u6709\u805a\u4e59\u4e8c\u9187\u5e72\u6270\u7d20alfa-2a\uff08 \u4e0b\u6587\u6b64\u7c7b\u5e72\u6270\u7d20\u90fd\u7b80\u79f0\u4e3a\u201c\u5e72\u6270\u7d20\u201d\uff0c\u5982\u6709\u8bf4\u5230\u666e\u901a\u5e72\u6270\u7d20\u4f1a\u7279\u522b\u6307\u51fa\uff09\u7684\u6cbb\u7597\u7ec4\u4eba\u7fa4\u4e2d\u4f1a\u66f4\u9ad8\uff08\u6bd4\u8d77\u90a3\u4e9b\u4ec5\u7528\u62c9\u7c73\u592b\u5b9a\u7684\u60a3\u8005\uff09\u3002\r\n\r\n\u5728\u7ed3\u675f\u6cbb\u759724\u5468\u540e\uff0c\u75c5\u6bd2\u6c34\u5e73\u964d\u5230400\u62f7\u8d1d/mL\u662f\u5f88\u591a\u4eba\u8ffd\u6c42\u7684\u6cbb\u7597\u7ec8\u70b9\uff0c\u5728\u542b\u6709\u5e72\u6270\u7d20\u7684\u6cbb\u7597\u7ec4\u4eba\u7fa4\u4e2d\u5927\u6982\u670920%\u5de6\u53f3\u83b7\u5f97\u4e86\u8fd9\u6837\u7684\u75c5\u6bd2\u5b66\u5e94\u7b54\uff0c\u4ec5\u7528\u62c9\u7c73\u592b\u5b9a\u7684\u60a3\u8005\u8fd9\u4e2a\u6570\u5b57\u53ea\u67097%\u3002\r\n\r\n\u8868\u9762\u6297\u539f\uff08HBsAg\uff09\u7684\u6e05\u9664\uff0c\u53ea\u670912\u4e2a\u4eba\u53d1\u751f\uff08\u90fd\u5728\u542b\u6709\u5e72\u6270\u7d20\u7684\u6cbb\u7597\u7ec4\u4eba\u7fa4\u4e2d\uff0c\u5360\u6bd43.4%\uff09\uff0c\u4ec5\u7528\u62c9\u7c73\u592b\u5b9a\u7684\u6cbb\u7597\u7ec4\u4e2d\u6ca1\u6709\u4eba\u83b7\u5f97HBsAg\u6e05\u9664\u3002",
+            "endpoints": [
+                1,
+                2,
+                3,
+                4,
+                5,
+                6
+            ]
+        }
+    },
+    {
+        "pk": 2,
+        "model": "sciblog.sciblog",
+        "fields": {
+            "subhead": "HBeAg\u9634\u6027\u6162\u4e59\u809d\u60a3\u8005\u63a5\u53d7\u805a\u4e59\u4e8c\u9187\u5e72\u6270\u7d20alfa-2a\u6cbb\u7597\u65f6\uff0c\u65e9\u671f\u53ef\u4ee5\u901a\u8fc7HBsAg\u548cHBV DNA\u7684\u5b9a\u91cf\u6c34\u5e73\u6765\u9884\u6d4b\u4ee5\u540e\u7684\u5e94\u7b54\u6548\u679c",
+            "sample": [],
+            "readed_count": 0,
+            "references": [
+                2
+            ],
+            "catched_by": [],
+            "query": [],
+            "endpoint_content": "\u672c\u7814\u7a76\u6839\u636e\u6b27\u6d32\u809d\u75c5\u534f\u4f1a\u6700\u65b0\u6307\u5357\u4e2d\u5bf9\u4e8e\u6cbb\u7597\u7ec8\u70b9\u4ee5\u53ca\uff08\u805a\u4e59\u4e8c\u9187\uff09\u5e72\u6270\u7d20\u6cbb\u7597\u7684\u75c5\u6bd2\u5b66\u5e94\u7b54\u7684\u5b9a\u4e49\u6765\u786e\u5b9a\u7814\u7a76\u7ec8\u70b9SR\u3002\u672c\u6587\u4e2d\uff0cHBeAg\u9634\u6027\u6162\u6027\u4e59\u809d\u60a3\u8005\u83b7\u5f97SR(sustained response\uff0c\u6301\u7eed\u5e94\u7b54\uff09\u662f\u6307\uff1a\r\n\u968f\u8bbf\u7ec8\u70b9\uff08\u7b2c72\u5468\uff09\u7684\u65f6\u5019\uff0cHBV DNA\u6c34\u5e73\u5c0f\u4e8e10000\u62f7\u8d1d/ml\uff08\u76f8\u5f53\u4e8e1714 IU/mL \uff09\r\n\u968f\u8bbf\u7ec8\u70b9\uff08\u7b2c72\u5468\uff09\u7684\u65f6\u5019\uff0cALT\u6062\u590d\u6b63\u5e38",
+            "treatment_content": "\u60a3\u8005\u6309\u71671\uff1a1\u6bd4\u4f8b\u88ab\u968f\u673a\u5206\u914d\u5230\u4e24\u7ec4\u4eba\u5f53\u4e2d\uff0c\u4e00\u7ec4\u63a5\u53d7180ug/\u6bcf\u5468\u7684\u805a\u4e59\u4e8c\u9187\u5e72\u6270\u7d20\u8054\u5408\u5229\u5df4\u97e6\u67971000mg/\u6bcf\u5929\uff08\u4f53\u91cd\u5c0f\u4e8e75\u5343\u514b\uff09\u6216\u80051200mg/\u6bcf\u5929\uff08\u4f53\u91cd>=75\u5343\u514b\u7684\uff09\u6cbb\u7597\uff0c\u8fd8\u6709\u4e00\u7ec4\u662f\u805a\u4e59\u4e8c\u9187\u5e72\u6270\u7d20180ug/\u6bcf\u5468\u7684\u5358\u836f\u6cbb\u7597\u3002\r\n\r\n48\u5468\u7597\u7a0b\uff0c\u6cbb\u7597\u7ed3\u675f\u540e\u7ee7\u7eed\u968f\u8bbf\u89c2\u5bdf24\u5468\u3002\r\n\r\n\u75c5\u60a3\u6bcf\u4e2a\u6708\u53c2\u52a0\u4e00\u6b21\u95e8\u8bca\u3002\r\n\r\n\u8868\u9762\u6297\u539f\u5b9a\u91cf\u68c0\u6d4b\u65f6\u95f4\u70b9\uff1a\u6cbb\u7597\u671f\u95f4\u7b2c4\u30018\u300112\u300124\u300136\u300148\u5468\uff0c\u968f\u8bbf\u671f\u95f4\u7b2c60\u300172\u5468\u3002",
+            "baseline": [],
+            "title": "HBeAg\u9634\u6027\u6162\u4e59\u809d\u60a3\u8005\u63a5\u53d7\u805a\u4e59\u4e8c\u9187\u5e72\u6270\u7d20alfa-2a\u6cbb\u7597\u65f6\uff0c\u65e9\u671f\u53ef\u4ee5\u901a\u8fc7HBsAg\u548cHBV DNA\u7684\u5b9a\u91cf\u6c34\u5e73\u6765\u9884\u6d4b\u4ee5\u540e\u7684\u5e94\u7b54\u6548\u679c",
+            "clinic_conditions": [
+                13,
+                14,
+                15,
+                16,
+                17,
+                18,
+                19,
+                20,
+                21
+            ],
+            "hospital": [],
+            "source": null,
+            "understanded_count": 0,
+            "safety": "",
+            "entitle": "Early on-treatment prediction of response to peginterferon alfa-2a for hbeag-negative chronic hepatitis b using hbsag and hbv dna levels",
+            "konwledge_piece": [
+                4,
+                5,
+                6,
+                7,
+                8,
+                9,
+                10,
+                11,
+                12,
+                13,
+                14,
+                15,
+                16
+            ],
+            "method": "\u672c\u7814\u7a76\u60a3\u8005\u90fd\u662f\u63a5\u53d7PEG\u5e72\u6270\u7d20\u6cbb\u7597\u3002",
+            "conclusion": "\u9488\u5bf9\u805a\u4e59\u4e8c\u9187\u5e72\u6270\u7d20\u6cbb\u7597\u7684HBeAg\u9634\u6027\u6162\u4e59\u809d\u60a3\u8005\uff0c\u672c\u7814\u7a76\u5b66\u8005\u5efa\u8bae\u4e86\u4e00\u4e2a\u5728\u6cbb\u7597\u5f00\u59cb\u540e\u7b2c12\u5468\u65f6\u5224\u65ad\u662f\u5426\u9700\u8981\u505c\u836f\u7684\u51c6\u5219\uff0c\u8fd9\u4e2a\u51c6\u5219\u57fa\u4e8e\u8840\u6e05\u4e2dHBV DNA\u548cHBsAg\u4e24\u4e2a\u6307\u6807\u4ece\u57fa\u7ebf\u5f00\u59cb\u7684\u4e0b\u964d\u6c34\u5e73\u3002\u6362\u8a00\u4e4b\uff0c\u4e34\u5e8a\u4e2d\uff0c\u540c\u65f6\u5b9a\u91cf\u68c0\u6d4bHBsAg\u548cHBV DNA\u80fd\u591f\u8c03\u6574\u805a\u4e59\u4e8c\u9187\u6cbb\u7597HBeAg\u9634\u6027\u6162\u4e59\u809d\u7684\u7b56\u7565\u3002\r\n\r\n\u5bf9\u4e8e\u4ee5\u4e0b\u60a3\u8005\uff1a\u6cbb\u7597\u7b2c12\u5468\u65f6\uff0c\u76f8\u6bd4\u57fa\u7ebf\uff08\u6cbb\u7597\u5f00\u59cb\uff09\uff0c\u8840\u6e05HBsAg\u6c34\u5e73\u6ca1\u6709\u4e0b\u964d\u800c\u4e14HBV DNA \u4e0b\u964d<2 log \u62f7\u8d1d/mL \uff0c\u5e94\u8be5\u505c\u6b62\u5e72\u6270\u7d20\u7684\u6cbb\u7597\uff0c\u6362\u7528\u5176\u4ed6\u6cbb\u7597\u65b9\u6cd5\u3002",
+            "detectionAssay": "\u8868\u9762\u6297\u539f\uff08HBsAg\uff09\u5b9a\u91cf\u68c0\u6d4b\uff1a\u96c5\u57f9 Architect HBsAg assay (Abbott Laboratories\uff09\u63d0\u4f9b\uff0c \u7ebf\u6027\u8303\u56f4\u662f0.05-250 IU/mL\r\n\u4e59\u809d\u75c5\u6bd2\uff08HBV DNA\uff09\u68c0\u6d4b\uff1a\u7f57\u6c0f\u8bca\u65ad TaqMan HBV assay, Roche Diagnostics\u63d0\u4f9b\uff0c\u68c0\u6d4b\u4e0b\u965035copies/mL\r\n\u8c37\u4e19\u8f6c\u6c28\u9176\uff08ALT\uff09\u68c0\u6d4b\uff1a\u5728\u7814\u7a76\u5f53\u5730\u533b\u9662\u6309\u7167\u6807\u51c6\u64cd\u4f5c\r\n\u4e59\u809d\u75c5\u6bd2\uff08HBV\uff09\u57fa\u56e0\u578b\u68c0\u6d4b\uff1a INNO-LiPA assay (Innogenetics)\r\n\u809d\u7a7f\u523a\u68c0\u6d4b\uff1a\u6bcf\u4e2a\u60a3\u8005\u90fd\u6709\u5165\u7ec4\u524d\u4e00\u5e74\u5185\u7684\u809d\u7a7f\u7ed3\u679c\uff0c\u7528Ishak\u8bc4\u5206\u7cfb\u7edf\u6765\u8868\u793a\u809d\u810f\u708e\u75c7\u7684\u7b49\u7ea7\uff080-18\u5206\uff09\u548c\u809d\u810f\u7ea4\u7ef4\u5316\u7684\u7a0b\u5ea6\uff080-6\u5206\uff09",
+            "ifvalue": 11.0,
+            "journal": "Hepatology",
+            "authors": "Harry Janssen , Vincent Rijckborst\uff0cBettina E. Hansen, Yilmaz Cakaloglu, Peter Ferenci, Fehmi Tabak, Meral Akdogan, Krzysztof Simon, Ulus S. Akarca, Robert Flisiak, Elke Verhey, Anneke J. Van Vuuren, Charles A. B. Boucher, Martijn J. ter Borg Harry L. A. Janssen ",
+            "abstractAE": "",
+            "confused_count": 0,
+            "collected_by": [],
+            "guidline": null,
+            "aim": "\u8fd9\u9879\u7814\u7a76\u662f\u7814\u7a76\u8005\u4e3b\u5bfc\u578b\u3001\u591a\u4e2d\u5fc3\u3001\u968f\u673a\u3001\u53cc\u76f2\u3001\u5bf9\u7167\u7814\u7a76\uff0c\u8be5\u7814\u7a76\u9075\u5b88\u8d6b\u5c14\u8f9b\u57fa\u5ba3\u8a00\u3002\r\n1.\u7814\u7a76\u7684\u76ee\u7684\u662f\u4e3a\u5f04\u6e05\u695a\u5728\u63a5\u53d7\u805a\u4e59\u4e8c\u9187\u5e72\u6270\u7d20alpha-2a\u6cbb\u7597\u7684e\u6297\u539f\u9634\u6027\u6162\u4e59\u809d\u60a3\u8005\u4e2d\uff0c\u6cbb\u7597\u524d\u671f\u5b9a\u91cf\u7684\u8840\u6e05HBsAg\u542b\u91cf\u5728\u9884\u6d4b\u4eca\u540e\u6301\u7eed\u5e94\u7b54\u6548\u5e94\u65f6\u7684\u4f5c\u7528\u3002\r\n2. \u9488\u5bf9\u8fd9\u90e8\u5206\u60a3\u8005\u6765\u627e\u5230\u53ef\u9760\u7684\u6cbb\u7597\u6307\u5357\u65b9\u9488\u6765\u6307\u5bfc\u505c\u836f\u3002",
+            "publish_date": "2010-04-19",
+            "abstract_result": "\u56de\u987e\u8be5\u7814\u7a76\u4e2d\u7684\u6301\u7eed\u5e94\u7b54\u8005\u5728\u6cbb\u7597\u671f\u95f4\u7684\u8868\u9762\u6297\u539f\uff08HBsAg\uff09\u6c34\u5e73\u7684\u53d8\u5316\uff0c\u4ece\u6cbb\u75978\u5468\u5f00\u59cb\uff0c\u8fd9\u4e9b\u5e94\u7b54\u8005\u7684HBsAg\u7684\u6c34\u5e73\u660e\u663e\u4e0b\u964d\uff1b\u76f8\u53cd\uff0c\u7ed3\u675f\u6cbb\u7597\u540e\u6ca1\u6709\u53d1\u751f\u6301\u7eed\u5e94\u7b54\u7684\u60a3\u8005\u6cbb\u7597\u671f\u95f4HBsAg\u6c34\u5e73\u53ea\u6709\u8f7b\u5fae\u7684\u4e0b\u964d\u3002\r\n\r\n\u6839\u636e\u7edf\u8ba1\u5b66\u5904\u7406\uff0c\u6216\u8005\u8bf4\u901a\u8fc7\u53d7\u8bd5\u8005\u5de5\u4f5c\u66f2\u7ebf\u7684AUC\u5224\u65ad\uff0c\u4ec5\u4ec5\u4f9d\u9760HBsAg\u7684\u4e0b\u964d\u9884\u6d4b\u6301\u7eed\u5e94\u7b54\u6709\u9650\u5236\u3002\r\n\r\n\u628aHBsAg\u4e0b\u964d\u548c\u4e59\u809d\u75c5\u6bd2\uff08HBV DNA\uff09\u4e0b\u964d\u7ed3\u5408\u8d77\u6765\u80fd\u591f\u6700\u597d\u5730\u9884\u6d4b\u6301\u7eed\u5e94\u7b54\u3002\r\n\r\n\u672c\u6587\u88ab\u89c2\u5bdf\u7684\u901a\u8fc7\u805a\u4e59\u4e8c\u9187\u5e72\u6270\u7d20\u6cbb\u7597\u7684e\u6297\u539f\u9634\u6027\u6162\u4e59\u809d\u60a3\u8005\u4e2d\uff0c\u6cbb\u7597\u671f\u95f4HBsAg\u6ca1\u6709\u51fa\u73b0\u4e0b\u964d\u5e76\u4e14DNA\u6c34\u5e73\u4e0b\u964d\u5c0f\u4e8e2\u4e2alog \u62f7\u8d1d/ml\u7684\u4eba\uff0c\u6cbb\u7597\u7ed3\u675f\u540e\u90fd\u6ca1\u6709\u51fa\u73b0\u6301\u7eed\u5e94\u7b54\uff0c\u8fd9\u90e8\u5206\u60a3\u8005\u5360\u672c\u6587\u88ab\u89c2\u5bdf\u60a3\u800520%\u3002\r\n\r\n\u76f8\u53cd\uff0c\u5982\u679c12\u5468\u540c\u65f6\u51fa\u73b0HBsAg\u4e0b\u964d\u4ee5\u53caDNA\u6c34\u5e73\u4e0b\u964d\u5927\u4e8e2\u4e2alog \u62f7\u8d1d/ml\u60a3\u8005\u6700\u7ec8\u51fa\u73b0\u6301\u7eed\u5e94\u7b54\u7684\u51e0\u7387\u4e3a39%\uff08\u76f8\u5bf9\u672c\u7814\u7a76\u5176\u4ed6\u7ec4\u522b\u6700\u9ad8\uff09\uff0c\u8fd9\u90e8\u5206\u60a3\u8005\u5360\u672c\u7814\u7a76\u6574\u4e2a\u4eba\u7fa427%\u3002",
+            "endpoints": [
+                1,
+                7
+            ]
+        }
+    },
+    {
+        "pk": 3,
+        "model": "sciblog.sciblog",
+        "fields": {
+            "subhead": "\u805a\u4e59\u4e8c\u9187\u5e72\u6270\u7d20alfa-2a\u6cbb\u7597e\u6297\u539f\u9633\u6027\u6162\u6027\u4e59\u809d\uff0c\u8868\u9762\u6297\u539f\u6cbb\u7597\u671f\u95f412\u5468\u300124\u5468\u6c34\u5e73\u53ef\u80fd\u9884\u793a\u6301\u4e45\u5e94\u7b54",
+            "sample": [],
+            "readed_count": 0,
+            "references": [
+                3
+            ],
+            "catched_by": [
+                1
+            ],
+            "query": [],
+            "endpoint_content": "\u672c\u6587\u6cbb\u7597\u5e94\u7b54\u5b9a\u4e49\u4e3a\uff1a\u6cbb\u7597\u7ed3\u675f6\u4e2a\u6708\u540ee\u6297\u539f\uff08HBeAg\uff09\u53d1\u751f\u8840\u6e05\u5b66\u8f6c\u6362\u3002",
+            "treatment_content": "\u88ab\u7814\u7a76\u8005\uff08399\u4eba\uff09\u4e2d\uff0c \u4e00\u534a\u4eba\u63a5\u53d7\u805a\u4e59\u4e8c\u9187\u5e72\u6270\u7d20\u6cbb\u7597\uff08\u6bcf\u5468180ug\uff09\uff0c\u53e6\u4e00\u534a\u4eba\u63a5\u53d7\u8054\u5408\u6cbb\u7597\uff0c\u5373\u5728\u7b2c\u4e00\u7ec4\u6cbb\u7597\u65b9\u6848\u7684\u57fa\u7840\u4e0a\u518d\u52a0\u7528\u62c9\u7c73\u592b\u5b9a\uff08\u6bcf\u5929100mg\uff09\uff0c\u4e24\u7ec4\u6cbb\u7597\u90fd\u662f\u6301\u7eed48\u5468\u3002\r\n\u968f\u8bbf\u65f6\u95f4\u70b9\uff1a\u57fa\u7ebf\uff08\u6cbb\u7597\u5f00\u59cb\uff09\u3001\u6cbb\u7597\u5f00\u59cb\u540e12\u5468\uff0c24\u5468\uff0c48\u5468\uff08\u6cbb\u7597\u7ed3\u675f\uff09",
+            "baseline": [],
+            "title": "[\u56de\u987e\u6027\u5206\u6790]\u8868\u9762\u6297\u539f\u4e0e\u805a\u4e59\u4e8c\u9187\u5e72\u6270\u7d20alfa-2a\u6cbb\u7597e\u6297\u539f\u9633\u6027\u6162\u4e59\u809d\u60a3\u8005\u6301\u4e45\u5e94\u7b54\u7684\u5173\u7cfb",
+            "clinic_conditions": [],
+            "hospital": [
+                4,
+                5,
+                6
+            ],
+            "source": null,
+            "understanded_count": 0,
+            "safety": "",
+            "entitle": "Hepatitis B surface antigen: association with sustained response to peginterferon alfa-2a in hepatitis B e antigen-positive patients",
+            "konwledge_piece": [
+                17,
+                18,
+                19,
+                20,
+                21,
+                22,
+                23
+            ],
+            "method": "\u672c\u7814\u7a76\u662f\u9488\u5bf9\u4e00\u4e2a\u5927\u578b\u7684\u3001\u968f\u673a\u7814\u7a76\u7684\u56de\u987e\u6027\u5206\u6790\u3002\u56e0\u4e3a\u672c\u6587\u8981\u89c2\u5bdf\u60a3\u8005\u5728\u6cbb\u7597\u671f\u95f4\u8868\u9762\u6297\u539f\uff08HBsAg\uff09\u7684\u53d8\u5316\uff0c\u6240\u4ee5\u56de\u987e\u91c7\u7528\u7684\u90fd\u662f\u4fdd\u7559\u6709\u8868\u9762\u6297\u539f\u968f\u8bbf\u8bb0\u5f55\u7684\u60a3\u8005\u7684\u6570\u636e\uff0c\u539f\u6765\u7684\u5927\u578b\u7814\u7a76\u6709542\u4eba\uff0c\u672c\u6587\u5206\u6790\u7528\u5230\u7684\u6570\u636e\u6709399\u4eba\u3002\u8fd9399\u4eba\u4e2d\uff0c\u4e00\u534a\u4eba\u63a5\u53d7\u805a\u4e59\u4e8c\u9187\u5e72\u6270\u7d20alfa-2a\u6cbb\u7597\uff08\u6bcf\u5468180ug\uff09\uff0c\u53e6\u4e00\u534a\u4eba\u63a5\u53d7\u8054\u5408\u6cbb\u7597\uff0c\u5c31\u662f\u5728\u7b2c\u4e00\u7ec4\u6cbb\u7597\u65b9\u6848\u7684\u57fa\u7840\u4e0a\u518d\u52a0\u7528\u62c9\u7c73\u592b\u5b9a\uff08\u6bcf\u5929100mg\uff09\uff0c\u4e24\u7ec4\u6cbb\u7597\u90fd\u662f\u6301\u7eed48\u5468\u3002",
+            "conclusion": "\u901a\u8fc7\u805a\u4e59\u4e8c\u9187\u5e72\u6270\u7d20alfa-2a\u6cbb\u7597e\u6297\u539f\uff08HBeAg\uff09\u9633\u6027\u6162\u4e59\u809d\u60a3\u8005\u7684\u65f6\u5019\uff0c\u6cbb\u7597\u671f\u95f4\u8840\u6e05\u4e2d\u8868\u9762\u6297\u539f\u7684\u6c34\u5e73\u4e0e\u6cbb\u7597\u7ed3\u675f\u540e\u6301\u4e45\u5e94\u7b54\u6709\u5173\u8054\u3002\u57fa\u7ebf\u8868\u9762\u6297\u539f\u6c34\u5e73\u548c\u6301\u4e45\u5e94\u7b54\u662f\u5426\u6709\u5173\u7cfb\u672c\u7814\u7a76\u4e0d\u8db3\u4ee5\u8bc1\u5b9e\u3002\u4f46\u5b9a\u91cf\u68c0\u6d4b\u8868\u9762\u6297\u539f\u6216\u8bb8\u53ef\u4ee5\u5e2e\u52a9\u60a3\u8005\u6307\u5bfc\u4eca\u540e\u7684\u6cbb\u7597\u65b9\u6848\u3002[2]",
+            "detectionAssay": "\u8868\u9762\u6297\u539f(HBsAg)\u6c34\u5e73\u7684\u5b9a\u91cf\u68c0\u6d4b\uff1a Abbott Architect HBsAg assay (Abbott Laboratories, IL, USA\uff09\r\nHBV DNA\u6c34\u5e73\u68c0\u6d4b\uff1a Amplicor HBV test (\u7f57\u6c0f\u5206\u5b50\u8bca\u65ad Roche Molecular Diagnostics, Pleasanton, CA, USA\uff09",
+            "ifvalue": 2.6,
+            "journal": "Hepatol Int. ",
+            "authors": "default authors",
+            "abstractAE": "&lt;br data-mce-bogus=\"1\"&gt;",
+            "confused_count": 0,
+            "collected_by": [
+                1,
+                2
+            ],
+            "guidline": null,
+            "aim": "\u5728\u4f7f\u7528\u805a\u4e59\u4e8c\u9187\u5e72\u6270\u7d20alfa-2a\u8fdb\u884c\u6cbb\u7597e\u6297\u539f\uff08HBeAg\uff09\u9633\u6027\u6162\u6027\u4e59\u578b\u809d\u708e\u7684\u65f6\u5019\uff0c\u6cbb\u7597\u7ed3\u675f\u540e6\u4e2a\u6708\u5982\u679c\u53d1\u751fe\u6297\u539f\u8840\u6e05\u5b66\u8f6c\u6362\uff0c\u90a3\u5c31\u9884\u793a\u7740\u505c\u836f\u540e\u957f\u671f\u968f\u8bbf\u671f\u95f4\u8868\u9762\u6297\u539f\u7684\u6e05\u9664\u7387\u4f1a\u63d0\u9ad8\u3002\u800c\u672c\u6587\u5b66\u8005\u628a\u5173\u6ce8\u70b9\u653e\u5728\u4e86\u53e6\u4e00\u4e2a\u6307\u6807--\u8868\u9762\u6297\u539f\uff08HBsAg\uff09\u4e0a\uff0c\u6240\u7814\u7a76\u7684\u8bdd\u9898\u662f\u5728\u6cbb\u7597\u671f\u95f4\u7684\u65f6\u5019\u901a\u8fc7\u5b9a\u91cf\u68c0\u6d4b\u8868\u9762\u6297\u539f\u80fd\u5426\u4e5f\u53ef\u4ee5\u9884\u6d4b\u6cbb\u7597\u7ed3\u675f\u540e\u7684\u5e94\u7b54\u3002",
+            "publish_date": "2011-01-05",
+            "abstract_result": "\u6cbb\u7597\u7ed3\u675f\u540e\u83b7\u5f97\u6cbb\u7597\u5e94\u7b54\u7684\u60a3\u8005\u57fa\u7ebf\u65f6\u8868\u9762\u6297\u539f\u7684\u6c34\u5e73\uff0c\u6bd4\u8d77\u90a3\u4e9b\u6ca1\u6709\u83b7\u5f97\u5e94\u7b54\u7684\u60a3\u8005\u7684\u57fa\u7ebf\u8868\u9762\u6297\u539f\u6c34\u5e73\u8981\u4f4e\u3002\uff083.97 log10 IU/mL \u6bd4 4.21 log10IU/mL\uff09\u3002\u5e76\u4e14\u83b7\u5f97\u5e94\u7b54\u7684\u60a3\u8005\u5728\u6574\u4e2a\u6cbb\u7597\u671f\u95f4>\u9762\u6297\u539f\uff08HBsAg\uff09\u4e0b\u964d\u7a0b\u5ea6\u66f4\u5927\u3002\r\n\u5728\u6cbb\u7597\u5f00\u59cb\u540e\u7b2c12\u5468\u8868\u9762\u6297\u539f\u7684\u503c\u4e0b\u964d\u52301,500IU/mL\u4ee5\u4e0b\u7684\u60a3\u8005\uff0c\u6cbb\u7597\u7ed3\u675f\u540ee\u6297\u539f\uff08HBeAg\uff09\u8840\u6e05\u5b66\u8f6c\u6362\u7387\u4e3a56.7%\uff1b \r\n\u572824\u5468\u8868\u9762\u6297\u539f\u7684\u503c\u4e0b\u964d\u52301,500IU/mL\u4ee5\u4e0b\u7684\u60a3\u8005\uff0c\u6cbb\u7597\u7ed3\u675f\u540ee\u6297\u539f\uff08HBeAg\uff09\u8840\u6e05\u5b66\u8f6c\u6362\u7387\u4e3a54.4%\u3002\u5982\u679c\u5728\u6cbb\u7597\u5f00\u59cb\u540e12\u5468\u6216\u800524\u5468\uff0c\u8868\u9762\u6297\u539f\uff08HBsAg\uff09\u6d4b\u5f97\u66f4\u9ad8\u7684\u503c\uff0c\u6bd4\u59821,500\u523020,000IU/mL\u6216\u8005\u5927\u4e8e20,000IU/mL\uff0c\u90a3\u4e48\u6cbb\u7597\u540e\u83b7\u5f97e\u6297\u539f\u8840\u6e05\u5b66\u8f6c\u6362\u7684\u51e0\u7387\u8981\u66f4\u4f4e\u3002\uff08\u524d\u8005\u4e3a32.3%\uff0c\u540e\u8005\u4e3a15.4%\uff09",
+            "endpoints": [
+                8,
+                9,
+                10
+            ]
+        }
+    },
+    {
+        "pk": 4,
+        "model": "sciblog.sciblog",
+        "fields": {
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+            "sample": [],
+            "readed_count": 0,
+            "references": [],
+            "catched_by": [],
+            "query": [],
+            "endpoint_content": "",
+            "treatment_content": "\u63a5\u53d7\u805a\u4e59\u4e8c\u9187\u5e72\u6270\u7d20alfa\u6cbb\u7597\u7684e\u6297\u539f\u6162\u4e59\u809d\u60a3\u8005\u4e2d\u6700\u6709\u53ef\u80fd\u83b7\u5f97\u6301\u4e45\u5e94\u7b54\u7684\u4eba\u6709\uff1a\r\n<ul><li>\u57fa\u7ebf\u9ad8\u8c37\u4e19\u8f6c\u6c28\u9176\u6c34\u5e73\u6216\u8005\u4f4eHBV DNA\u6c34\u5e73\u7684HBV\u57fa\u56e0\u578b\u4e3aA\u578b\u7684\u60a3\u8005\uff1b</li>\r\n<li>\u57fa\u7ebf\u9ad8\u8c37\u4e19\u8f6c\u6c28\u9176\u6c34\u5e73\u4e14HBV DNA\u4f4e\u6c34\u5e73\u7684B\u3001C\u578b\u60a3\u8005\u3002</li></ul>\r\nD\u578b\u60a3\u8005\u83b7\u5f97\u6301\u4e45\u5e94\u7b54\u7684\u51e0\u7387\u4f4e\u3002\r\n\u8be5\u7814\u7a76\u63d0\u4f9b\u4e86\u4e00\u4e2a\u5de5\u5177\u6765\u8ba1\u7b97\u901a\u8fc7\u805a\u4e59\u4e8c\u9187\u5e72\u6270\u7d20\u6cbb\u7597e\u6297\u539f\uff08HBeAg\uff09\u9633\u6027\u60a3\u8005\u83b7\u5f97\u6301\u7eed\u5e94\u7b54\u7684\u51e0\u7387\u3002\u7814\u7a76\u5efa\u8bae\u4e86\u51e0\u4e2a\u91cd\u8981\u7684\u4eba\u7fa4\u5e94\u8be5\u8003\u8651\u63a5\u53d7\u805a\u4e59\u4e8c\u9187\u5e72\u6270\u7d20\u6cbb\u7597\u3002\r\n",
+            "baseline": [],
+            "title": "\u80fd\u591f\u9884\u6d4b\u805a\u4e59\u4e8c\u9187\u5e72\u6270\u7d20alfa\u6cbb\u7597e\u6297\u539f\u9633\u6027\u6162\u6027\u4e59\u578b\u809d\u708e\u5e94\u7b54\u7ed3\u679c\u7684\u56e0\u5b50",
+            "clinic_conditions": [],
+            "hospital": [
+                7
+            ],
+            "source": null,
+            "understanded_count": 0,
+            "safety": "",
+            "entitle": "Factors That Predict Response of Patients With Hepatitis B e Antigen\u2013Positive Chronic Hepatitis B to Peginterferon-Alfa",
+            "konwledge_piece": [
+                25,
+                26,
+                27,
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+            "conclusion": "\u63a5\u53d7\u805a\u4e59\u4e8c\u9187\u5e72\u6270\u7d20alfa\u6cbb\u7597\u7684e\u6297\u539f\u6162\u4e59\u809d\u60a3\u8005\u4e2d\u6700\u6709\u53ef\u80fd\u83b7\u5f97\u6301\u4e45\u5e94\u7b54\u7684\u4eba\u6709\uff1a\r\n<ul><li>\u57fa\u7ebf\u9ad8\u8c37\u4e19\u8f6c\u6c28\u9176\u6c34\u5e73\u6216\u8005\u4f4eHBV DNA\u6c34\u5e73\u7684HBV\u57fa\u56e0\u578b\u4e3aA\u578b\u7684\u60a3\u8005\uff1b</li>\r\n<li>\u57fa\u7ebf\u9ad8\u8c37\u4e19\u8f6c\u6c28\u9176\u6c34\u5e73\u4e14HBV DNA\u4f4e\u6c34\u5e73\u7684B\u3001C\u578b\u60a3\u8005\u3002</li></ul>\r\nD\u578b\u60a3\u8005\u83b7\u5f97\u6301\u4e45\u5e94\u7b54\u7684\u51e0\u7387\u4f4e\u3002",
+            "detectionAssay": "",
+            "ifvalue": 11.68,
+            "journal": "Gastroenterology",
+            "authors": "Harry Janssen , Erik H.C.J.\u00a0Buster, Bettina E.\u00a0Hansen, George K.K.\u00a0Lau, Teerha\u00a0Piratvisuth, Stefan\u00a0Zeuzem, Ewout W.\u00a0Steyerberg",
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+            "publish_date": "2009-12-01",
+            "abstract_result": "<ol><li>HBV\u57fa\u56e0\u578b</li></ol>\u3001\u57fa\u7ebf\u9ad8\u6c34\u5e73\u7684\u8c37\u4e19\u8f6c\u6c28\u9176\uff08ALT\uff09\u6c34\u5e73\uff08&gt2\u4e2a\u6b63\u5e38\u503c\u4e0a\u9650\uff09\u3001\u57fa\u7ebf\u4f4e\u6c34\u5e73\u7684HBV DNA\uff08&lt;2.0*10^8IU/mL\uff09\u3001\u5973\u6027\u3001\u5e74\u957f\u3001\u4ee5\u524d\u6ca1\u6709\u63a5\u53d7\u8fc7\u5e72\u6270\u7d20\u6cbb\u7597\u8fd9\u4e9b\u56e0\u7d20\u90fd\u80fd\u591f\u9884\u6d4b\u6301\u4e45\u5e94\u7b54\u3002\r\n\u4e59\u809d\u75c5\u6bd2\uff08HBV\uff09\u57fa\u56e0\u578bA\u578b\u3001\u57fa\u7ebf\u9ad8ALT\u503c\u548c/\u6216\u8005\u4f4eHBV-DNA\u6c34\u5e73\u7684\u60a3\u8005\u6709\u9ad8\u51e0\u7387\u83b7\u5f97\u6301\u4e45\u5e94\u7b54\uff08\u8d85\u8fc730%\uff09\u3002\r\n<p>\u4e0a\u8ff0\u8fd9\u4e9b\u56e0\u7d20\u4e2d\u6700\u5f3a\u7684\u9884\u6d4b\u56e0\u5b50\u662f\u57fa\u7ebf\u9ad8\u6c34\u5e73\u7684\u8c37\u4e19\u8f6c\u6c28\u9176\uff08\u5bf9\u4e8eHBV\u57fa\u56e0\u578bB\u578b\u60a3\u8005\uff09\u548c\u57fa\u7ebf\u4f4e\u6c34\u5e73\u7684HBV-DNA\uff08\u5bf9\u4e8eHBV\u57fa\u56e0\u578bC\u578b\u60a3\u8005\uff09\u3002\u57fa\u56e0\u578bD\u578b\u7684\u60a3\u8005\u83b7\u5f97\u6301\u4e45\u5e94\u7b54\u7684\u51e0\u7387\u4f4e\u3002</p>",
+            "endpoints": []
+        }
+    },
+    {
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+        "model": "sciblog.resultcontent",
+        "fields": {
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+            "blog": 1,
+            "shorttitle": "\u6cbb\u7597\u524d\u7684\u5404\u9879\u6307\u6807\u60c5\u51b5",
+            "abstract": "",
+            "content": "\u88ab\u62db\u52df\u8005\u603b\u4f53\u4eba\u7fa4\u7279\u5f81\r\n[\u88ab\u62db\u52df\u60a3\u8005\u90fd\u5fc5\u987b\u7b26\u5408\u4ee5\u4e0b\u6761\u4ef6]\r\ne\u6297\u539f\uff08HBeAg\uff09\u9634\u6027\u81f3\u5c11\u516d\u4e2a\u6708\uff1b\r\ne\u6297\u4f53\uff08HBeAb\uff09\u548c\u8868\u9762\u6297\u539f\uff08HBsAg\uff09\u81f3\u5c11\u9633\u6027\u516d\u4e2a\u6708\uff1b\r\n\u4e59\u809d\u75c5\u6bd2\uff08DNA\uff09\u6c34\u5e73\u81f3\u5c11100,000\u62f7\u8d1d/mL\r\n\u8c37\u4e19\u8f6c\u6c28\u9176\uff08ALT\uff09\u57281\u500d\u6b63\u5e38\u503c\u4e0a\u9650\uff08ULN\uff09\u548c10\u88ab\u6b63\u5e38\u503c\u4e0a\u9650\u4e4b\u95f4\uff1b\r\n\u5728\u8fc7\u53bb24\u4e2a\u6708\u5185\u809d\u810f\u6d3b\u68c0\u8bc1\u5b9e\u6709\u809d\u708e\u3002\r\n\r\n[\u88ab\u62db\u52df\u60a3\u8005\u4e0d\u5305\u62ec\u4ee5\u4e0b\u60c5\u51b5]\r\n\u60a3\u6709\u5931\u4ee3\u507f\u809d\u786c\u5316\uff1b\r\n\u66fe\u7ecf\u6709\u8fc7\u4e25\u91cd\u7684\u7cbe\u795e\u548c\u5185\u79d1\u75be\u75c5\uff1b\r\n\u4e00\u5f00\u59cb\u4e2d\u6027\u7c92\u7ec6\u80de\u6570\u5c0f\u4e8e1500/mm3;\r\n\u8840\u5c0f\u677f\u6570\u91cf\u5c0f\u4e8e90,000/mm3;\r\n\u8840\u6e05\u808c\u9150\u4e3a\u6b63\u5e38\u503c\u4e0a\u9650\u7684\u81f3\u5c111.5\u500d\u4ee5\u4e0a\uff1b\r\n\u5165\u7ec4\u524d\u4e00\u5e74\u5185\u6709\u8fc7\u8fc7\u5ea6\u996e\u9152\u6216\u8005\u6ee5\u7528\u836f\u7269\u7684\u7ecf\u5386\uff1b\r\n\u5728\u6700\u8fd1\u76846\u4e2a\u6708\u5185\u63a5\u53d7\u8fc7\u6297\uff08\u4e59\u809d\uff09\u75c5\u6bd2\u6cbb\u7597\uff1b\r\n\u5408\u5e76\u4e19\u578b\u809d\u708e\uff08HCV\uff09\u3001\u4e01\u809d\u6216\u8005HIV\u3002\r\n",
+            "sample": [],
+            "indicators": [
+                3,
+                2,
+                1
+            ],
+            "type": 1
+        }
+    },
+    {
+        "pk": 2,
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+            "blog": 1,
+            "shorttitle": "\u957f\u671f\u968f\u8bbf\u8c01\u7597\u6548\u66f4\u6301\u4e45",
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+        "fields": {
+            "link": "http://www.ncbi.nlm.nih.gov/pubmed/14697813",
+            "description": "Lai CL, Ratziu V, Yuen MF, Poynard T. Viral hepatitis B. Lancet 2003;362:2089-94."
+        }
+    },
+    {
+        "pk": 2,
+        "model": "sciblog.reference",
+        "fields": {
+            "link": "http://onlinelibrary.wiley.com/doi/10.1002/hep.23722/full",
+            "description": "Rijckborst V, Hansen BE, Cakaloglu Y, Ferenci P, Tabak F, Akdogan M, Simon K, Akarca US, Flisiak R, Verhey E, Van Vuuren AJ, Boucher CA, ter Borg MJ, Janssen HL. Early on-treatment prediction of response to peginterferon alfa-2a for HBeAg-negative chronic hepatitis B using HBsAg and HBV DNA levels.Hepatology. 2010 Aug;52(2):454-61. doi: 10.1002"
+        }
+    },
+    {
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+        "model": "sciblog.reference",
+        "fields": {
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+            "description": "Hepatitis B surface antigen: association with sustained response to peginterferon alfa-2a in hepatitis B e antigen-positive patients\r\n"
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+            "type": 0,
+            "title": ""
+        }
+    },
+    {
+        "pk": 4,
+        "model": "sciblog.knowledgepiece",
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+            "type": 0,
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+        }
+    },
+    {
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+        "model": "sciblog.knowledgepiece",
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+            "type": 0,
+            "title": ""
+        }
+    },
+    {
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+        "model": "sciblog.knowledgepiece",
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+            "type": 0,
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+    {
+        "pk": 7,
+        "model": "sciblog.knowledgepiece",
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+            "type": 0,
+            "title": ""
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+    },
+    {
+        "pk": 8,
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+            "type": 0,
+            "title": ""
+        }
+    },
+    {
+        "pk": 9,
+        "model": "sciblog.knowledgepiece",
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+            "type": 1,
+            "title": ""
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+    },
+    {
+        "pk": 10,
+        "model": "sciblog.knowledgepiece",
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+            "type": 1,
+            "title": ""
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+    },
+    {
+        "pk": 11,
+        "model": "sciblog.knowledgepiece",
+        "fields": {
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+            "type": 1,
+            "title": ""
+        }
+    },
+    {
+        "pk": 12,
+        "model": "sciblog.knowledgepiece",
+        "fields": {
+            "content": "DNA\u8981\u4e0b\u964d\u5230\u591a\u5c11\u5bf9\u4e8ee\u6297\u539f\uff08HBeAg\uff09\u9634\u6027\u6162\u4e59\u809d\u60a3\u8005\u6700\u5408\u9002?\r\n\u8be5\u7814\u7a76\u628a\u6301\u7eed\u5e94\u7b54\uff08SR\uff09\u5b9a\u4e49\u4e3a\u6cbb\u7597\u7ed3\u675f6 \u4e2a\u6708\u65f6\uff0cHBV DNA \u6c34\u5e73<10,000 \u62f7\u8d1d/mL\uff0c\u5e76\u4e14ALT \u6c34\u5e73\u6062\u590d\u6b63\u5e38\u3002",
+            "type": 1,
+            "title": ""
+        }
+    },
+    {
+        "pk": 13,
+        "model": "sciblog.knowledgepiece",
+        "fields": {
+            "content": "\u6709\u4e9b\u4eba\u53ef\u80fd\u4f1a\u4e89\u8bae\u8bf4HBV DNA \u7684\u4e0b\u9650\u5e94\u8be5\u66f4\u4f4e\u4e00\u70b9\u3002\u7528\u654f\u611f\u7684PCR \u68c0\u6d4b\u65b9\u6cd5\u68c0\u6d4b\u5230\u6cbb\u7597\u540eHBV DNA \u9634\u6027\u7684\u786e\u662f\u4e00\u4e2a\u4e3b\u8981\u7684\u6cbb\u7597\u7ec8\u70b9\u3002\r\n\u5c3d\u7ba1\u5982\u6b64\uff0c\u5e72\u6270\u7d20\u6cbb\u7597\u7684HBeAg \u9634\u6027\u7684CHB \u75c5\u4eba\u5e38\u5e38\u4e0d\u80fd\u8fbe\u5230\u8fd9\u4e9b\u6cbb\u7597\u7ec8\u70b9\u3002",
+            "type": 1,
+            "title": ""
+        }
+    },
+    {
+        "pk": 14,
+        "model": "sciblog.knowledgepiece",
+        "fields": {
+            "content": "\u53e6\u5916\uff0c\u5927\u6837\u672c\u7814\u7a76\u8868\u660e\uff0c\u5982\u679cHBeAg \u9634\u6027\u7684CHB \u75c5\u4ebaHBV DNA<10,000 \u62f7\u8d1d /mL\uff0c\u90a3\u4e48\u4ed6\u4eec\u53d1\u5c55\u4e3a\u809d\u786c\u5316\u548c\u809d\u7ec6\u80de\u764c\u7684\u5371\u9669\u6027\u964d\u4f4e\u3002",
+            "type": 1,
+            "title": ""
+        }
+    },
+    {
+        "pk": 15,
+        "model": "sciblog.knowledgepiece",
+        "fields": {
+            "content": "\u800c\u4e14\uff0c\u672c\u7814\u7a76\u4e2dHBV DNA \u7684\u4e34\u754c\u503c\u4ee5\u53ca\u968f\u8bbf\u671f\u9650\u4e0e\u6700\u8fd1\u7684\u6b27\u6d32\u6307\u5357\u5bf9\u5e72\u6270\u7d20\u6cbb\u7597\u5e94\u7b54\u7684\u5b9a\u4e49\u548c\u51e0\u9879\u91cd\u8981\u7684\u5173\u4e8e\u5e72\u6270\u7d20\u6cbb\u7597\u6162\u6027\u4e59\u809d\u7684\u7814\u7a76\u7684\u968f\u8bbf\u671f\u9650\u5206\u522b\u662f\u4e00\u81f4\u7684\u3002",
+            "type": 1,
+            "title": ""
+        }
+    },
+    {
+        "pk": 16,
+        "model": "sciblog.knowledgepiece",
+        "fields": {
+            "content": "\u4e3a\u4ec0\u4e48\u672c\u7814\u7a76\u7684\u603b\u4f53\u6301\u7eed\u5e94\u7b54\u51e0\u7387\u6bd4\u8d77\u5176\u4ed6\u7814\u7a76\u4f1a\u8f83\u4f4e\uff0c\u53ea\u670922%\uff1f\r\n\u8be5\u7814\u7a76\u53d7\u8bd5\u8005\u5927\u591a\u6570\u4eba\u90fd\u662f\u767d\u79cd\u4eba\uff0c\u611f\u67d3\u7684HBV\u57fa\u56e0\u578b\u4e3aA\u548cD\uff0cD\u578b\u60a3\u8005\u5e94\u7b54\u6548\u679c\u4f3c\u4e4e\u4f4e\u4e8e\u5176\u4ed6\u57fa\u56e0\u578b\uff0c\u8fd9\u4e5f\u8bb8\u80fd\u89e3\u91ca\u4e3a\u4ec0\u4e48\u6b64\u7814\u7a76\u7684\u603b\u4f53\u7597\u6548\u6b20\u4f73\u3002",
+            "type": 1,
+            "title": ""
+        }
+    },
+    {
+        "pk": 17,
+        "model": "sciblog.knowledgepiece",
+        "fields": {
+            "content": "\u4e3a\u4ec0\u4e48<a href=\"#jargon-2\" class=\"jargon\">\u8868\u9762\u6297\u539f</a>\u6e05\u9664\u662f\u91cd\u8981\u7684\u6cbb\u7597\u7ec8\u70b9\uff1f\r\n\u6cbb\u7597\u4e59\u809d\u7684\u65f6\u5019\uff0c<a href=\"#jargon-2\" class=\"jargon\">\u8868\u9762\u6297\u539f</a>\uff08HBsAg\uff09\u7684\u6e05\u9664\u80fd\u591f\u4f7f\u5f97\u7ec4\u7ec7\u5b66\u6539\u5584\uff0c\u964d\u4f4e\u809d\u786c\u5316\u548c\u809d\u7ec6\u80de\u764c\u7684\u53d1\u751f\u7387\uff0c\u4ece\u800c\u63d0\u9ad8\u751f\u5b58\u7387\u3002\u6240\u4ee5\u5b83\u73b0\u5728\u53d8\u6210\u4e86\u91cd\u8981\u7684\u6cbb\u7597\u7ec8\u70b9\u3002",
+            "type": 0,
+            "title": ""
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+    },
+    {
+        "pk": 18,
+        "model": "sciblog.knowledgepiece",
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+            "type": 0,
+            "title": ""
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+    },
+    {
+        "pk": 19,
+        "model": "sciblog.knowledgepiece",
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+            "type": 0,
+            "title": ""
+        }
+    },
+    {
+        "pk": 20,
+        "model": "sciblog.knowledgepiece",
+        "fields": {
+            "content": "\u5224\u522b\u6cbb\u7597\u65e9\u671f\u5e94\u7b54\u7684\u610f\u4e49\r\n\uff08\u65e0\u8bba\u662f\u6cbb\u7597\u524d\u8fd8\u662f\u6cbb\u7597\u671f\u95f4\uff09\u6cbb\u7597\u65e9\u671f\u65f6\u5019\u5bf9\u4e8e\u60a3\u8005\u5e94\u7b54\u7684\u5224\u522b\u5bf9\u4e8e\u4e34\u5e8a\u533b\u5e08\u662f\u5f88\u6709\u5e2e\u52a9\u7684\uff0c\u56e0\u4e3a\u8fd9\u80fd\u591f\u8ba9\u4e34\u5e8a\u533b\u5e08\u5728\u90a3\u4e9b\u6700\u6709\u53ef\u80fd\u53d1\u751f\u5e94\u7b54\u7684\u4eba\u8eab\u4e0a\u4f7f\u7528\u805a\u4e59\u4e8c\u9187\u5e72\u6270\u7d20\u6cbb\u7597\uff0c\u800c\u90a3\u4e9b\u5bf9\u4e8e\u5e72\u6270\u7d2048\u5468\u6807\u51c6\u7597\u7a0b\u7684\u6cbb\u7597\u5c06\u6765\u4e0d\u5927\u53ef\u80fd\u53d1\u751f\u5e94\u7b54\u7684\u60a3\u8005\u5e94\u8be5\u5373\u4f7f\u8c03\u6574\u6cbb\u7597\u65b9\u6848\u3002\r\n\u80fd\u591f\u5728\u65e9\u4e9b\u65f6\u5019\u80fd\u591f\u8fa8\u8ba4\u51fa\u60a3\u8005\u4e0d\u9002\u5408\u5e72\u6270\u7d20\u6cbb\u7597\uff0c\u6216\u8005\u8bf4\u5bf9\u4e8e\u5e72\u6270\u7d20\u6cbb\u7597\u4e0d\u56de\u5e94\u7b54\uff0c\u4e5f\u80fd\u591f\u9632\u6b62\u60a3\u8005\u7ecf\u53d7\u4e0d\u5fc5\u8981\u7684\u526f\u4f5c\u7528\u3002",
+            "type": 0,
+            "title": ""
+        }
+    },
+    {
+        "pk": 21,
+        "model": "sciblog.knowledgepiece",
+        "fields": {
+            "content": "\u5173\u4e8ecccDNA\u548c<a href=\"#jargon-2\" class=\"jargon\">\u8868\u9762\u6297\u539f</a>\u7684\u5173\u7cfb\uff0c\u4ece\u673a\u7406\u4e0a\u89e3\u91ca\u5b9a\u91cf\u68c0\u6d4b<a href=\"#jargon-2\" class=\"jargon\">\u8868\u9762\u6297\u539f</a>\u7684\u91cd\u8981\u6027\uff1a\r\n\r\n<a href=\"#jargon-2\" class=\"jargon\">\u8868\u9762\u6297\u539f</a>\uff08HBsAg\uff09\u548c\u5171\u4ef7\u95ed\u5408\u73af\u72b6\uff08cccDNA\uff09\u6709\u6b63\u76f8\u5173\uff0c\u4e5f\u5c31\u662f\u8bf4<a href=\"#jargon-2\" class=\"jargon\">\u8868\u9762\u6297\u539f</a>\u6c34\u5e73\u5347\u9ad8\u65f6cccDNA\u4e5f\u4f1a\u5347\u9ad8\uff0c\u53cd\u4e4b\u4ea6\u7136\u3002\r\n\r\ncccDNA\u662f\u4e59\u809d\u75c5\u6bd2\u524d\u57fa\u56e0\u7ec4RNA\u590d\u5236\u7684\u539f\u59cb\u6a21\u677f\uff0c\u867d\u7136\u5176\u542b\u91cf\u8f83\u5c11\uff0c\u6bcf\u4e2a\u809d\u7ec6\u80de\u5185\u53ea\u6709\u7ea65\uff5e50\u4e2a\u62f7\u8d1d\uff0c\u6545cccDNA\u53cd\u6620\u4e86\u611f\u67d3\u75c5\u6bd2\u7684\u809d\u7ec6\u80de\u7684\u6570\u91cf\uff0c\u800c\u4e14\u4ed6\u626e\u6f14\u7740\u75c5\u6bd2\u57fa\u56e0\u8f6c\u5f55\u6a21\u677f\u7684\u89d2\u8272\u3002\r\n\r\n\u5373\u4f7f\u4e59\u809d\u75c5\u6bd2\uff08HBV\uff09DNA\u68c0\u6d4b\u4e0d\u5230\uff08\u5373\u5316\u9a8c\u5355\u4e0a\u663e\u793a\u9634\u6027\uff09\uff0c\u4f46cccDNA\u5982\u679c\u7ee7\u7eed\u5b58\u5728\u4e8e\u809d\u7ec6\u80de\u4e2d\uff0c\u90a3\u4e48\u60a3\u8005\u8fd8\u662f\u9762\u4e34\u7740HBV\u611f\u67d3\u590d\u53d1\u7684\u53ef\u80fd\u6027\u7684\u3002\u5e72\u6270\u7d20\u7684\u514d\u75ab\u8c03\u8282\u6d3b\u6027\u80fd\u591f\u4fc3\u4f7f\u75c5\u6bd2T\u7ec6\u80de\u7684\u6d3b\u5316\uff0c\u4ece\u800c\u6e05\u9664\u611f\u67d3\u7684\u809d\u7ec6\u80de\uff0c\u4e5f\u5c31\u51cf\u5c11\u4e86cccDNA\u7684\u6570\u91cf\u3002\r\n\r\n\u603b\u7ed3\u4e0a\u9762\u51e0\u70b9\uff0c\u5b9a\u91cf\u68c0\u6d4b<a href=\"#jargon-2\" class=\"jargon\">\u8868\u9762\u6297\u539f</a>\u662f\u4e00\u4e2a\u975e\u5e38\u5408\u9002\u7684\u65b9\u6cd5\u6765\u68c0\u6d4b\u805a\u4e59\u4e8c\u9187\u5e72\u6270\u7d20\u5bf9\u4e8e\u88ab\u611f\u67d3\u7684\u809d\u7ec6\u80de\u7684\u514d\u75ab\u6e05\u9664\u60c5\u51b5\u548c\u5bf9cccDNA\u7684\u6d88\u9664\u60c5\u51b5\u3002",
+            "type": 1,
+            "title": ""
+        }
+    },
+    {
+        "pk": 22,
+        "model": "sciblog.knowledgepiece",
+        "fields": {
+            "content": "\u5bf9\u805a\u4e59\u4e8c\u9187\u5e72\u6270\u7d20\u4ea7\u751f\u514d\u75ab\u5e94\u7b54\u7684\u60a3\u8005\u548c\u6ca1\u6709\u4ea7\u751f\u514d\u75ab\u5e94\u7b54\u7684\u60a3\u8005\uff0c\u5728\u6cbb\u7597\u671f\u95f4<a href=\"#jargon-2\" class=\"jargon\">\u8868\u9762\u6297\u539f</a>\u7684\u4e0b\u964d\u7a0b\u5ea6\u662f\u4e0d\u540c\u7684\u3002\u5728\u6cbb\u7597\u671f\u95f4\uff0c\u4f4e<a href=\"#jargon-2\" class=\"jargon\">\u8868\u9762\u6297\u539f</a>\u6c34\u5e73\u548c\u66f4\u9ad8\u7684\u5e94\u7b54\u7387\u6709\u5173\u3002",
+            "type": 1,
+            "title": ""
+        }
+    },
+    {
+        "pk": 23,
+        "model": "sciblog.knowledgepiece",
+        "fields": {
+            "content": "\u6cbb\u7597\u9636\u6bb5\u7684\u65e9\u671f\u5e94\u7b54\uff0c\u8bf8\u5982<a href=\"#jargon-2\" class=\"jargon\">\u8868\u9762\u6297\u539f</a>\u4e0b\u964d\u663e\u8457\uff0c\u5bf9\u4e8e\u60a3\u8005\u575a\u6301\u5b8c\u621048\u5468\u7597\u7a0b\u7684\u6cbb\u7597\u662f\u4e00\u4e2a\u9f13\u52b1\u3002",
+            "type": 1,
+            "title": ""
+        }
+    },
+    {
+        "pk": 24,
+        "model": "sciblog.knowledgepiece",
+        "fields": {
+            "content": "\u7528\u4e8e\u9884\u6d4b\u6301\u7eed\u5e94\u7b54\uff08SR\uff09\u7684\u6700\u4f73\u65b9\u6cd5\u662f\u5c06<a href=\"#jargon-2\" class=\"jargon\">\u8868\u9762\u6297\u539f</a>\uff08HBsAg\uff09\u5b9a\u91cf\u6c34\u5e73\u4e0e\u4e59\u809d\u75c5\u6bd2\uff08HBV\uff09 DNA\u4e0b\u964d\u6c34\u5e73\u7ed3\u5408\u8d77\u6765\u770b\u3002\u7ecf\u7edf\u8ba1\u5904\u7406\u53d1\u73b0\uff0c\u51b3\u5b9a\u662f\u5426\u7ee7\u7eed\u6cbb\u7597\u4e5f\u4e0d\u9700\u8981\u592a\u665a\uff0c\u6bd4\u598224\u5468\uff0c\u56e0\u4e3a\u4e0e12\u5468\u76f8\u6bd4\uff0c24\u5468\u9884\u6d4bSR\u7684\u4f5c\u7528\u5e76\u6ca1\u6709\u66f4\u597d\u4e00\u4e9b\u3002",
+            "type": 1,
+            "title": ""
+        }
+    },
+    {
+        "pk": 25,
+        "model": "sciblog.knowledgepiece",
+        "fields": {
+            "content": "\u4e59\u578b\u809d\u708e\u662f\u4e00\u4e2a\u5168\u7403\u8303\u56f4\u5185\u4e3b\u8981\u7684\u5065\u5eb7\u95ee\u9898\u3002\u4e16\u754c\u536b\u751f\u7ec4\u7ec7\uff08WHO\uff09\u66fe\u62a5\u9053\u5927\u7ea6\u5168\u7403\u6709\u8d85\u8fc74\u4ebf\u4e59\u809d\u75c5\u6bd2\u643a\u5e26\u8005\uff0c\u5c06\u8fd175%\u7684\u643a\u5e26\u8005\u5c45\u4f4f\u5728\u4e9a\u6d32\u548c\u897f\u592a\u5e73\u6d0b\u5730\u533a\u3002\u5728\u8fd9\u4e9b\u5730\u533a\uff0cHBV\u611f\u67d3\u7ecf\u5e38\u53d1\u751f\u5728\u56f4\u4ea7\u671f\u548c\u5e7c\u513f\u65f6\u671f\u3002\r\n\u5927\u591a\u6570\u6765\u81ea\u8fd9\u4e9b\u5730\u533a\u7684\u60a3\u8005\u662f\u5178\u578b\u7684e\u6297\u539f\uff08HBeAg\uff09\u9633\u6027\u6162\u6027\u4e59\u578b\u809d\u708e\u60a3\u8005\uff0c\u4ed6\u4eec\u4f53\u5185\u6709\u7740\u9ad8\u6c34\u5e73\u7684\u4e59\u809d\u75c5\u6bd2\uff0c\u5728\u611f\u67d3\u540e\u768410-30\u5e74\uff0c\u4ed6\u4eec\u4f1a\u9010\u6e10\u53d1\u5c55\u6210\u4e25\u91cd\u7684\u809d\u708e\uff0c<a href=\"#jargon-1\" class=\"jargon\">\u8c37\u4e19\u8f6c\u6c28\u9176</a>\uff08ALT\uff09\u4f1a\u4e0a\u5347\u3002\u76f8\u53cd\uff0c\u5728\u7ae5\u5e74\u665a\u671f\u3001\u9752\u6625\u671f\u3001\u6210\u5e74\u540e\u611f\u67d3\u7684\u60a3\u8005\u4f1a\u5728\u611f\u67d3\u540e\u5f88\u77ed\u4e00\u6bb5\u65f6\u95f4\u5185\u51fa\u73b0\u8c37\u4e19\u8f6c\u6c28\u9176\u5347\u9ad8\u3002\r\n\u5c3d\u7ba1\u81ea\u53d1\u7684e\u6297\u539f\u8840\u6e05\u5b66\u8f6c\u6362\u4f1a\u5728\u5927\u591a\u6570e\u6297\u539f\u9633\u6027\u7684\u60a3\u8005\u4e2d\u51fa\u73b0\uff0c\u4f46\u662f\u809d\u708e\u7684\u6301\u7eed\u65f6\u95f4\u4f1a\u53d8\u957f\u800c\u4e14\u75c5\u75c7\u4f1a\u53d8\u5f97\u8d8a\u6765\u8d8a\u4e25\u91cd\uff0c\u53ef\u80fd\u53d1\u5c55\u6210\u809d\u786c\u5316\u3002\u56e0\u6b64\uff0c\u5728ALT\u51fa\u73b0\u5347\u9ad8\u540e\u76843\u52306\u4e2a\u6708\u5185\u5982\u679c\u4e59\u809d\u75c5\u6bd2\uff08HBV\uff09DNA\u59cb\u7ec8\u4fdd\u6301\u9ad8\u6c34\u5e73\u7684e\u6297\u539f\u9633\u6027\u60a3\u8005\u5e94\u8be5\u63a5\u53d7\u6297\u75c5\u6bd2\u6cbb\u7597\u3002",
+            "type": 0,
+            "title": "\u4e59\u809d\u6982\u51b5"
+        }
+    },
+    {
+        "pk": 26,
+        "model": "sciblog.knowledgepiece",
+        "fields": {
+            "content": "\u4e0d\u7ba1\u662f\u7528\u4ec0\u4e48\u6297\u75c5\u6bd2\u836f\u7269\uff0c\u6210\u529f\u6cbb\u7597\u6162\u6027\u4e59\u809d\u75c5\u6bd2\u611f\u67d3\u90fd\u662f\u6307e\u6297\u539f\u7684\u6e05\u9664\u3001\u8840\u6e05\u4e59\u809d\u75c5\u6bd2DNA\u6c34\u5e73\u7684\u4e0b\u964d\u4ee5\u53ca<a href=\"#jargon-1\" class=\"jargon\">\u8c37\u4e19\u8f6c\u6c28\u9176</a>\u6c34\u5e73\u6062\u590d\u6b63\u5e38\uff0c\u56e0\u4e3a\u8fd9\u4e9b\u6307\u6807\u53d8\u5316\u90fd\u548c\u826f\u597d\u7684\u957f\u671f\u7597\u6548\u6709\u5173\u8054\u3002\r\n<p>\r\n\u5728e\u6297\u539f\u9633\u6027\u7684\u60a3\u8005\u4e2d\uff0c\u8840\u6e05\u4e2d\u6301\u4e45\u7684e\u6297\u539f\u6e05\u9664\u548c\u65e5\u540e\u8840\u6e05\u4e2d<a href=\"#jargon-2\" class=\"jargon\"><a href=\"#jargon-2\" class=\"jargon\">\u8868\u9762\u6297\u539f</a></a>\uff08HBsAg\uff09\u7684\u6e05\u9664\u3001\u6f14\u53d8\u6210\u809d\u786c\u5316\u548c\u809d\u7ec6\u80de\u764c\u7684\u51e0\u7387\u7684\u964d\u4f4e\u4ee5\u53ca\u6700\u7ec8\u751f\u5b58\u8d28\u91cf\u7684\u6539\u5584\u6709\u5173\u3002</p>",
+            "type": 0,
+            "title": "\u6cbb\u7597\u4e59\u809d\u7684\u666e\u904d\u7684\u6cbb\u7597\u7ec8\u70b9"
+        }
+    },
+    {
+        "pk": 27,
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+        "fields": {
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+            "type": 0,
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+        }
+    },
+    {
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+            "type": 0,
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+            "figures": [],
+            "keywords": [
+                1
+            ],
+            "brief_content": "\u8c37\u4e19\u8f6c\u6c28\u9176",
+            "type": 1
+        }
+    },
+    {
+        "pk": 2,
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+                1,
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+            ],
+            "collected_by": [
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+        "model": "sciblog.guideline",
+        "fields": {
+            "content": "HBeAg\u9634\u6027\u4e59\u809d\u60a3\u8005\u63a5\u53d7\u805a\u4e59\u4e8c\u9187\u6cbb\u7597\u7684\u8fc7\u7a0b\u4e2d\uff0c\u540c\u65f6\u5b9a\u91cf\u68c0\u6d4bHBsAg\u548cHBV DNA\u80fd\u591f\u5e2e\u52a9\u51b3\u5b9a\u7ee7\u7eed\u8fd8\u662f\u505c\u6b62\u6cbb\u7597\u65b9\u6848\u3002\r\n\r\n\u5f53\u7136\u5f88\u660e\u663e\u7684\u662f\uff0c\u6700\u7ec8\u7684\u51b3\u5b9a\u662f\u5426\u7ee7\u7eed\u6cbb\u7597\u8fd8\u8981\u57fa\u4e8e\u533b\u751f\u7684\u5224\u5b9a\uff0c\u4ed6\uff08\u5979\uff09\u5e94\u8be5\u5c06\u5176\u4ed6\u56e0\u7d20\uff0c\u8bf8\u5982\u75c5\u4eba\u5bf9\u4e8e\u836f\u7269\u7684\u8010\u53d7\uff0c\u8003\u8651\u8fdb\u53bb\u3002\r\n\r\n\u5173\u4e8e\u51b3\u5b9a\u65f6\u95f4\uff1a\r\n\r\n\u6cbb\u7597\u768412\u5468\u4ee5\u524d\u8fd8\u4e0d\u80fd\u4e3a\u662f\u5426\u8981\u505c\u6b62\u6cbb\u7597\u5236\u5b9a\u4e34\u5e8a\u6307\u5bfc\u539f\u5219\uff0c\u56e0\u4e3aHBsAg\u548cHBV DNA\u6c34\u5e73\u5728\u524d8\u5468\u7684\u53d8\u5316\u4e0d\u80fd\u63d0\u4f9b\u8db3\u591f\u7684\u8bc1\u636e\u3002\r\n\r\n\u53e6\u4e00\u65b9\u9762\uff0c\u8fc7\u4e8612\u5468\uff0c\u51b3\u5b9a\u201c\u662f\u5426\u7ee7\u7eed\u6cbb\u7597\u201d\u4e0d\u5e94\u8be5\u63a8\u8fdf\u5230\u592a\u665a\uff0c\u56e0\u4e3a\u6570\u5b66\u7edf\u8ba1\u5904\u7406\u8868\u793a\u9884\u6d4b\u83b7\u5f97SR\u51e0\u7387\u7684\u4f5c\u7528\uff08\u6216\u8005\u7cbe\u51c6\u5ea6\uff09\u572824\u5468\u5e76\u6ca1\u6709\u6bd412\u5468\u66f4\u597d\u3002",
+            "figures": []
+        }
+    },
+    {
+        "pk": 1,
+        "model": "sciblog.endpoint",
+        "fields": {
+            "content": "\u6cbb\u7597\u7ed3\u675f\u968f\u8bbf24\u5468\u4ee5\u540e\uff0c<a href=\"#jargon-1\" class=\"jargon\"><a href=\"#jargon-1\" class=\"jargon\">\u8c37\u4e19\u8f6c\u6c28\u9176</a></a>\uff08ALT\uff09\u6062\u590d\u6b63\u5e38\u6c34\u5e73",
+            "indicator": null,
+            "type": 1
+        }
+    },
+    {
+        "pk": 2,
+        "model": "sciblog.endpoint",
+        "fields": {
+            "content": "\u6cbb\u7597\u7ed3\u675f\u968f\u8bbf24\u5468\u4ee5\u540e\uff0c\u4e59\u809d\u75c5\u6bd2\uff08HBV\uff09DNA\u6c34\u5e73\u4e0b\u964d\u523020,000\u62f7\u8d1d/mL",
+            "indicator": null,
+            "type": 1
+        }
+    },
+    {
+        "pk": 3,
+        "model": "sciblog.endpoint",
+        "fields": {
+            "content": "\u6cbb\u7597\u7ed3\u675f\u968f\u8bbf24\u5468\u4ee5\u540e\uff0c<a href=\"#jargon-2\" class=\"jargon\">\u8868\u9762\u6297\u539f</a>\uff08HBsAg\uff09\u6e05\u9664",
+            "indicator": null,
+            "type": 2
+        }
+    },
+    {
+        "pk": 4,
+        "model": "sciblog.endpoint",
+        "fields": {
+            "content": "\u6cbb\u7597\u7ed3\u675f\u968f\u8bbf24\u5468\u4ee5\u540e\uff0c<a href=\"#jargon-2\" class=\"jargon\">\u8868\u9762\u6297\u539f</a>\uff08HBsAg\uff09\u8840\u6e05\u5b66\u8f6c\u6362\uff08\u5b9a\u4e49\u4e3a<a href=\"#jargon-2\" class=\"jargon\">\u8868\u9762\u6297\u539f</a>HBsAg\u6e05\u9664\u800c\u4e14\u8868\u9762\u6297\u4f53HBsAb\u51fa\u73b0\uff09",
+            "indicator": null,
+            "type": 2
+        }
+    },
+    {
+        "pk": 5,
+        "model": "sciblog.endpoint",
+        "fields": {
+            "content": "\u6cbb\u7597\u7ed3\u675f\u968f\u8bbf24\u5468\u4ee5\u540e\uff0c\u7ec4\u7ec7\u5b66\u5e94\u7b54\uff08\u5b9a\u4e49\u4e3aMHAI, The Ishak modified histological activity index\u4e0b\u964d\u81f3\u5c112\u5206\uff09",
+            "indicator": null,
+            "type": 2
+        }
+    },
+    {
+        "pk": 6,
+        "model": "sciblog.endpoint",
+        "fields": {
+            "content": "\u6cbb\u7597\u7ed3\u675f\u968f\u8bbf24\u5468\u4ee5\u540e\uff0c\u4e59\u809d\u75c5\u6bd2\uff08DNA\u6c34\u5e73\uff09\u4e0b\u964d\u5230400\u62f7\u8d1d\u4ee5\u4e0b",
+            "indicator": null,
+            "type": 2
+        }
+    },
+    {
+        "pk": 7,
+        "model": "sciblog.endpoint",
+        "fields": {
+            "content": "\u968f\u8bbf\u7ec8\u70b9\uff08\u7b2c72\u5468\uff09\u7684\u65f6\u5019\uff0cHBV DNA\u6c34\u5e73\u5c0f\u4e8e10000\u62f7\u8d1d/ml\uff08\u76f8\u5f53\u4e8e1714 IU/mL \uff09",
+            "indicator": null,
+            "type": 1
+        }
+    },
+    {
+        "pk": 8,
+        "model": "sciblog.endpoint",
+        "fields": {
+            "content": "e\u6297\u539f\uff08HBeAg\uff09\u8840\u6e05\u5b66\u8f6c\u6362",
+            "indicator": null,
+            "type": 1
+        }
+    },
+    {
+        "pk": 9,
+        "model": "sciblog.endpoint",
+        "fields": {
+            "content": "\u4e59\u809d\u75c5\u6bd2\uff08HBV\uff09DNA\u5c0f\u4e8e\u7b49\u4e8e2,000IU/mL\uff08\u76f8\u5f53\u4e8e\u5927\u698210,000\u62f7\u8d1d/mL\uff09",
+            "indicator": null,
+            "type": 1
+        }
+    },
+    {
+        "pk": 10,
+        "model": "sciblog.endpoint",
+        "fields": {
+            "content": "\u6cbb\u7597\u7ed3\u675f\u540e6\u4e2a\u6708\u968f\u8bbf\u671f\u95f4\u53d1\u751f<a href=\"#jargon-2\" class=\"jargon\">\u8868\u9762\u6297\u539f</a>\uff08HBsAg\uff09\u6e05\u9664",
+            "indicator": null,
+            "type": 1
+        }
+    },
+    {
+        "pk": 1,
+        "model": "sciblog.cliniccondition",
+        "fields": {
+            "content": "e\u6297\u539f\uff08HBeAg\uff09\u9634\u6027\u81f3\u5c11\u516d\u4e2a\u6708",
+            "indicator": null,
+            "type": 0
+        }
+    },
+    {
+        "pk": 2,
+        "model": "sciblog.cliniccondition",
+        "fields": {
+            "content": "e\u6297\u4f53\uff08HBeAb\uff09\u81f3\u5c11\u9633\u6027\u516d\u4e2a\u6708",
+            "indicator": null,
+            "type": 0
+        }
+    },
+    {
+        "pk": 3,
+        "model": "sciblog.cliniccondition",
+        "fields": {
+            "content": "\u4e59\u809d\u75c5\u6bd2\uff08DNA\uff09\u6c34\u5e73\u81f3\u5c11100,000\u62f7\u8d1d/mL",
+            "indicator": null,
+            "type": 0
+        }
+    },
+    {
+        "pk": 4,
+        "model": "sciblog.cliniccondition",
+        "fields": {
+            "content": "\u8c37\u4e19\u8f6c\u6c28\u9176\uff08ALT\uff09\u57281\u500d\u6b63\u5e38\u503c\u4e0a\u9650\uff08ULN\uff09\u548c10\u88ab\u6b63\u5e38\u503c\u4e0a\u9650\u4e4b\u95f4",
+            "indicator": null,
+            "type": 0
+        }
+    },
+    {
+        "pk": 5,
+        "model": "sciblog.cliniccondition",
+        "fields": {
+            "content": "\u5728\u8fc7\u53bb24\u4e2a\u6708\u5185\u809d\u810f\u6d3b\u68c0\u8bc1\u5b9e\u6709\u809d\u708e",
+            "indicator": null,
+            "type": 0
+        }
+    },
+    {
+        "pk": 6,
+        "model": "sciblog.cliniccondition",
+        "fields": {
+            "content": "\u60a3\u6709\u5931\u4ee3\u507f\u809d\u786c\u5316",
+            "indicator": null,
+            "type": 1
+        }
+    },
+    {
+        "pk": 7,
+        "model": "sciblog.cliniccondition",
+        "fields": {
+            "content": "\u66fe\u7ecf\u6709\u8fc7\u4e25\u91cd\u7684\u7cbe\u795e\u548c\u5185\u79d1\u75be\u75c5",
+            "indicator": null,
+            "type": 1
+        }
+    },
+    {
+        "pk": 8,
+        "model": "sciblog.cliniccondition",
+        "fields": {
+            "content": "\u4e00\u5f00\u59cb\u4e2d\u6027\u7c92\u7ec6\u80de\u6570\u5c0f\u4e8e1500/mm3",
+            "indicator": null,
+            "type": 1
+        }
+    },
+    {
+        "pk": 9,
+        "model": "sciblog.cliniccondition",
+        "fields": {
+            "content": "\u8840\u5c0f\u677f\u6570\u91cf\u5c0f\u4e8e90,000/mm3",
+            "indicator": null,
+            "type": 1
+        }
+    },
+    {
+        "pk": 10,
+        "model": "sciblog.cliniccondition",
+        "fields": {
+            "content": "\u8840\u6e05\u808c\u9150\u4e3a\u6b63\u5e38\u503c\u4e0a\u9650\u7684\u81f3\u5c111.5\u500d\u4ee5\u4e0a",
+            "indicator": null,
+            "type": 1
+        }
+    },
+    {
+        "pk": 11,
+        "model": "sciblog.cliniccondition",
+        "fields": {
+            "content": "\u5165\u7ec4\u524d\u4e00\u5e74\u5185\u6709\u8fc7\u8fc7\u5ea6\u996e\u9152\u6216\u8005\u6ee5\u7528\u836f\u7269\u7684\u7ecf\u5386",
+            "indicator": null,
+            "type": 1
+        }
+    },
+    {
+        "pk": 12,
+        "model": "sciblog.cliniccondition",
+        "fields": {
+            "content": "\u5728\u6700\u8fd1\u76846\u4e2a\u6708\u5185\u63a5\u53d7\u8fc7\u6297\uff08\u4e59\u809d\uff09\u75c5\u6bd2\u6cbb\u7597",
+            "indicator": null,
+            "type": 1
+        }
+    },
+    {
+        "pk": 13,
+        "model": "sciblog.cliniccondition",
+        "fields": {
+            "content": "\u5408\u5e76\u4e19\u578b\u809d\u708e\uff08HCV\uff09\u3001\u4e01\u809d\u6216\u8005HIV",
+            "indicator": null,
+            "type": 1
+        }
+    },
+    {
+        "pk": 14,
+        "model": "sciblog.cliniccondition",
+        "fields": {
+            "content": "<a href=\"#jargon-2\" class=\"jargon\">\u8868\u9762\u6297\u539f</a>\uff08HBsAg\uff09\u81f3\u5c11\u9633\u6027\u516d\u4e2a\u6708",
+            "indicator": null,
+            "type": 0
+        }
+    },
+    {
+        "pk": 15,
+        "model": "sciblog.cliniccondition",
+        "fields": {
+            "content": "\u5165\u7ec4\u524d2\u4e2a\u6708\u5185\uff0ce\u6297\u539f\uff08HBeAg\uff09\u88ab\u53d1\u73b0\u9634\u6027\u81f3\u5c11\u4e24\u6b21",
+            "indicator": null,
+            "type": 0
+        }
+    },
+    {
+        "pk": 16,
+        "model": "sciblog.cliniccondition",
+        "fields": {
+            "content": "\u5165\u7ec4\u524d2\u4e2a\u6708\uff0ce\u6297\u4f53\uff08HBeAb\uff09\u88ab\u53d1\u73b0\u9634\u6027\u81f3\u5c11\u4e24\u6b21",
+            "indicator": null,
+            "type": 0
+        }
+    },
+    {
+        "pk": 17,
+        "model": "sciblog.cliniccondition",
+        "fields": {
+            "content": "\u5165\u7ec4\u524d2\u4e2a\u6708\uff0c\u81f3\u5c11\u4e24\u6b21<a href=\"#jargon-1\" class=\"jargon\">\u8c37\u4e19\u8f6c\u6c28\u9176</a>\uff08ALT\uff09\u5904\u57281.5\u523010\u500d\u6b63\u5e38\u503c\u4e0a\u9650\uff08ULN\uff09\u4e4b\u95f4",
+            "indicator": null,
+            "type": 0
+        }
+    },
+    {
+        "pk": 18,
+        "model": "sciblog.cliniccondition",
+        "fields": {
+            "content": "\u4e59\u809d\u75c5\u6bd2\uff08HBV DNA\uff09\u6c34\u5e73\u5927\u4e8e100,000\u62f7\u8d1d/ml\uff08\u76f8\u5f53\u4e8e17,143IU/ml\uff09",
+            "indicator": null,
+            "type": 0
+        }
+    },
+    {
+        "pk": 19,
+        "model": "sciblog.cliniccondition",
+        "fields": {
+            "content": "\u5165\u7ec4\u524d\u516d\u4e2a\u6708\u524d\u63a5\u53d7\u8fc7\u6297\u75c5\u6bd2\u6216\u8005\u514d\u75ab\u6291\u5236\u5242\u6cbb\u7597",
+            "indicator": null,
+            "type": 1
+        }
+    },
+    {
+        "pk": 20,
+        "model": "sciblog.cliniccondition",
+        "fields": {
+            "content": "\u60a3\u6709\u5176\u4ed6\u83b7\u5f97\u6027\u6216\u8005\u9057\u4f20\u6027\u7684\u809d\u810f\u75be\u75c5",
+            "indicator": null,
+            "type": 1
+        }
+    },
+    {
+        "pk": 21,
+        "model": "sciblog.cliniccondition",
+        "fields": {
+            "content": "\u66fe\u7ecf\u6709\u8fc7\u7ec6\u80de\u51cf\u5c11\u75c7\u6216\u8005\u5931\u4ee3\u507f\u809d\u75c5",
+            "indicator": null,
+            "type": 1
+        }
+    }
+]
+\ No newline at end of file
diff --git a/97suifangqa/apps/sciblog/forms.py b/97suifangqa/apps/sciblog/forms.py
new file mode 100644
index 0000000..88a4659
--- /dev/null
+++ b/97suifangqa/apps/sciblog/forms.py
@@ -0,0 +1,38 @@
+# -*- coding: utf-8 -*-
+from haystack.forms import SearchForm
+
+from .models import SciBlog, BlogAnnotation
+
+class SciBlogSearchForm(SearchForm):
+    u'''
+    问题查询表单,主要完成两个工作：
+        1. 指定查询的model为Query
+        2. 重载clean_q，对查询语句进行分词
+    >>> from sciblog.forms import SciBlogSearchForm
+    >>> form = SciBlogSearchForm({'q':u'干扰素'})
+    >>> form.search()
+        [<SearchResult: sciblog.sciblog (pk=u'1')>, <SearchResult: sciblog.sciblog (pk=u'3')>, <SearchResult: sciblog.sciblog (pk=u'2')>]
+    '''
+
+    def __init__(self,*args, **kwargs):
+        u'''
+        在__init__中指定查询的model为SciBlog
+        '''
+        super(SciBlogSearchForm, self).__init__(*args, **kwargs)
+        self.searchqueryset = self.searchqueryset.models(SciBlog)
+
+
+class ProperNounSearchForm(SearchForm):
+    u'''
+    专业名词搜索表单
+    >>> from sciblog.forms import ProperNounSearchForm
+    >>> form = ProperNounSearchForm({'q':u'乙肝'})
+    >>> form.search()
+        [<SearchResult: sciblog.blogannotation (pk=u'1')>]
+    '''
+    def __init__(self,*args, **kwargs):
+        u'''
+        在__init__中指定查询的model为BlogAnnotation
+        '''
+        super(ProperNounSearchForm, self).__init__(*args, **kwargs)
+        self.searchqueryset = self.searchqueryset.models(BlogAnnotation)
diff --git a/97suifangqa/apps/sciblog/managers.py b/97suifangqa/apps/sciblog/managers.py
new file mode 100644
index 0000000..ae6beb3
--- /dev/null
+++ b/97suifangqa/apps/sciblog/managers.py
@@ -0,0 +1,80 @@
+# -*- coding: utf-8 -*-
+import json
+from django.db import models
+from django.contrib.auth.models import AnonymousUser
+
+class AnnotationManager(models.Manager):
+    use_for_related_fields = True
+
+    def paracomments(self):
+        u'''
+        获取段落注释
+        '''
+        return self.filter(type = 0)
+
+    def propernouns(self):
+        u'''
+        获取专有名词
+        '''
+        return self.filter(type = 1)
+    
+    def all_json(self, user = AnonymousUser()):
+        u'''
+        通过json格式获取专有名词和段落注释
+        '''
+        result = {p.id:{'id':p.id,
+                        'name':p.firstkeyword() if p.type == 1 else p.brief_content,
+                        'type':p.type,
+                        'content':p.detail,
+                        'collected_times':p.collected_by.count(),
+                        'is_collected': p.is_collected_by(user)} 
+                  for p in self.all()}
+        return  json.dumps(result)
+    
+
+class KnowledgePieceManager(models.Manager):
+    use_for_related_fields = True
+
+    def knowledges(self):
+        u'''
+        获取科普知识类型的条目
+        '''
+        return self.filter(type = 0)
+
+    def comments(self):
+        u'''
+        获取科学评论类型的条目
+        '''
+        return self.filter(type = 1)
+
+
+class EndPointManager(models.Manager):
+    use_for_related_fields = True
+    
+    def primary(self):
+        u'''
+        获取主要治疗终点
+        '''
+        return self.filter(type = 1)
+
+    def secondary(self):
+        u'''
+        获取次要治疗终点
+        '''
+        return self.filter(type = 2)
+
+
+class ClinicConditionManager(models.Manager):
+    use_for_related_fields = True
+
+    def inclusive(self):
+        u'''
+        获取允许类型的临床条件
+        '''
+        return self.filter(type = 0)
+
+    def exclusive(self):
+        u'''
+        获取排除类型的临床条件
+        '''
+        return self.filter(type = 1)
diff --git a/97suifangqa/apps/sciblog/models.py b/97suifangqa/apps/sciblog/models.py
new file mode 100644
index 0000000..22514c9
--- /dev/null
+++ b/97suifangqa/apps/sciblog/models.py
@@ -0,0 +1,326 @@
+# -*- coding: utf-8 -*-
+
+from django.db import models
+from django.contrib import admin
+from django.contrib.auth.models import User
+from utils import get_abstract
+from .managers import *
+
+
+# Create your models here.
+
+
+# SciBlog {{{
+class SciBlog(models.Model):
+
+    title              = models.CharField(u"标题", max_length=400)
+    subhead            = models.CharField(u"副标题", max_length=400, blank=True)
+    entitle            = models.CharField(u"英文标题", max_length=400, blank=True)
+    journal            = models.CharField(u"期刊", max_length=400, blank= True)
+    publish_date       = models.DateField(u"出版日期", blank=True, null=True)
+    readed_count       = models.PositiveIntegerField(u"被阅读次数", default=0)
+    understanded_count = models.PositiveIntegerField(u"懂按钮被按次数", default=0)
+    confused_count     = models.PositiveIntegerField(u"不懂按钮被按次数", default=0)
+    ifvalue            = models.FloatField(u"影响因子", default=1.0)
+    authors            = models.CharField(u"作者", max_length=1000, default="default authors")
+    method             = models.TextField(u"治疗手段", blank=True)
+    aim                = models.TextField(u"目标", blank=True)
+    abstract_result    = models.TextField(u"结果简述", blank=True)
+    abstractAE         = models.TextField(u"abstractAE", blank=True)
+    treatment_content  = models.TextField(u"treatmentContent", blank=True)
+    safety             = models.TextField(u"安全性", blank=True)
+
+    hospital           = models.ManyToManyField("location.Hospital", verbose_name=u"作者医院", related_name="sciblogs", null=True, blank=True)
+    guidline           = models.OneToOneField("Guideline", verbose_name=u"临床策略", related_name="blog", null=True, blank=True)
+    baseline           = models.ManyToManyField("BaseLine", verbose_name=u"研究基线", related_name="blog", null=True, blank=True)
+    endpoint_content   = models.TextField(u"治疗终点文本", blank=True)
+    endpoints          = models.ManyToManyField("EndPoint", verbose_name=u"治疗终点", related_name="blogs", null=True, blank=True)
+    clinic_conditions  = models.ManyToManyField("ClinicCondition", verbose_name=u"临床条件", related_name="blogs", null=True, blank=True)
+    detectionAssay     = models.TextField(u"检测方法", blank=True)
+    collected_by       = models.ManyToManyField(User, verbose_name=u"收藏者", related_name="blog_collection", null=True, blank=True)
+    catched_by         = models.ManyToManyField(User, verbose_name=u"懂了的", related_name="blogs_catched", null=True, blank=True)
+
+    # 从原BlogBlock拷贝过来的fields
+    conclusion         = models.TextField(u"本文结论", blank=True)
+    konwledge_piece    = models.ManyToManyField("KnowledgePiece", verbose_name=u"知识条目", related_name="blogs", null=True, blank=True)
+    sample             = models.ManyToManyField("subjects.Sample", verbose_name=u"人群", related_name="blogs", null=True, blank=True)
+    source             = models.OneToOneField("Source", verbose_name=u"出处", related_name="blog", null=True, blank=True)
+    references         = models.ManyToManyField("Reference", verbose_name=u"参考信息", related_name="blogs", null=True, blank=True)
+    query              = models.ManyToManyField("info.Query", verbose_name=u"问题", related_name="blogs", null=True, blank=True)
+
+    class Meta:
+        verbose_name_plural = u"文章"
+
+    def __unicode__(self):
+        return "< SciBlog: %s >" % self.title
+
+    def show(self):
+        """
+        used in 'search/search.html'
+        to show search result
+        """
+        return self.__unicode__()
+
+    def level(self):
+        u'''
+        计算文章难度等级
+        '''
+        return 1        #TODO:添加实现代码
+
+    def quality_value(self):
+        u'''
+        计算文章质量
+        '''
+        return 1.0     #TODO:添加实现代码
+
+    def communication_author(self):
+        u'''
+        找出通讯作者放在blog list
+        '''
+        return self.authors.split(',')[0]
+# }}}
+
+
+# ResultContent {{{
+class ResultContent(models.Model):
+    u'''
+    实验结果内容
+    '''
+    type_choices = ((1, "total"),
+                    (2, "now"),
+                    (3, "future"))
+    
+    type = models.IntegerField(u"类型", choices=type_choices, null=True, blank=True)
+    shorttitle = models.CharField(u"简标题", max_length=36, blank=True)
+    abstract = models.CharField(u"摘要", max_length=100, blank=True)
+    content = models.TextField(u"内容", blank = True)
+    card_content = models.TextField(u"卡片内容", blank=True)
+    sample  = models.ManyToManyField("subjects.Sample", verbose_name=u"人群", related_name="results", null=True, blank=True)
+    blog = models.ForeignKey("SciBlog", verbose_name=u"文章", related_name="results", null=True, blank=True)
+    indicators = models.ManyToManyField("indicator.Indicator", null=True, blank=True)
+
+    class Meta:
+        verbose_name_plural = u"实验结果"
+
+    def __unicode__(self):
+        return "<ResultContent: %s>" % get_abstract(self.content)
+
+    def color(self):
+        u'''
+        根据type返回卡片颜色
+        '''
+
+        return ['grey', 'green', 'blue'][self.type - 1]
+# }}}
+
+
+# Source {{{
+class Source(models.Model):
+    u'''
+        这篇文章原论文的来源
+    '''
+
+    ensrc = models.CharField(u"英文出处", max_length=400, blank= True)
+    chsrc = models.CharField(u"中文出处", max_length=400, blank= True)
+    link  = models.URLField(verify_exists=False, max_length=400, blank=True, verbose_name = u"外网链接")
+
+
+    class Meta:
+        verbose_name_plural = u"出处"
+
+    def __unicode__(self):
+        return "< Source: %s >" % self.id
+# }}}
+
+
+# Reference {{{
+class Reference(models.Model):
+    u'''
+        参考消息：这篇文章其他相关论文等信息的来源
+    '''
+
+    description = models.TextField(u"描述", blank=True)
+    link        = models.URLField(verify_exists=False, max_length=400, blank=True, verbose_name = u"链接")
+
+
+    class Meta:
+        verbose_name_plural = u"参考信息"
+
+    def __unicode__(self):
+        return "< Reference: %s >" % self.description
+# }}}
+
+
+# KnowledgePiece {{{
+class KnowledgePiece(models.Model):
+    u'''
+        知识条目：知识条目很可能是问题的答案。
+    '''
+
+    type_choices = ((0, u"科普知识"),
+                    (1, u"科学评论"),
+                   )
+    
+    title = models.CharField(u"标题", max_length=100, blank= True)
+    content = models.TextField(u"条目内容", blank=True)
+    type    = models.IntegerField(u"种类", choices=type_choices)
+    objects = KnowledgePieceManager()
+    
+
+    class Meta:
+        verbose_name_plural = u"知识条目"
+
+    def __unicode__(self):
+        return "< KnowledgePiece: %s %s >" % (self.id, self.content if len(self.content) < 20 else self.content[0:20])
+# }}}
+
+
+# BlogAnnotation {{{
+class BlogAnnotation(models.Model):
+    u'''
+        文章注释
+    '''
+
+    type_choices = ((0, u"段落注释"),
+                    (1, u"专有名词"),)
+
+    type = models.IntegerField(u"注释类型", choices=type_choices)
+    no   = models.IntegerField(u"编号", blank=True, null=True)
+    brief_content = models.CharField(u"简短内容", max_length=400, blank= True)
+    detail = models.TextField(u"详细内容", blank=True)
+    blogs = models.ManyToManyField("SciBlog", verbose_name=u"文章", related_name="annotations", null=True, blank=True)
+    keywords = models.ManyToManyField("info.KeyWord", verbose_name=u"关键词", related_name="annotations", null=True, blank=True)
+    figures = models.ManyToManyField("figure.Figure", verbose_name=u"图片", related_name="annotations", null=True, blank=True)
+    collected_by = models.ManyToManyField(User, verbose_name=u"收藏者", related_name="annotation_collection", null=True, blank=True)
+    objects = AnnotationManager()
+	
+
+    class Meta:
+        verbose_name_plural = u"文章注释"
+
+    def __unicode__(self):
+        return "<BlogAnnotation: %s>" % get_abstract(self.brief_content)
+
+    def show(self):
+        """
+        used in 'search/search.html'
+        to show search result
+        """
+        return self.__unicode__()
+
+    def firstkeyword(self):
+        u'''
+        第一个关键词,注意对于专有名词，通常只有一个
+        '''
+
+        return self.keywords.all()[0].content 
+
+    def firstparagraph(self):
+        u'''
+        bloglist页面二上内容的阶段，django里面的注释第一段的末尾都是一个空格
+        '''
+        return self.detail.split(' ')[0]
+
+    def is_collected_by(self, user):
+        u'''
+        该注释是否已经被user收藏
+        '''
+        if user.is_authenticated() and user.annotation_collection.filter(id=self.id):
+            return True
+        return False
+# }}}
+
+
+# Guideline {{{
+class Guideline(models.Model):
+    u'''
+       临床策略 
+    '''
+
+    content = models.TextField(u"内容", blank=True)
+    figures = models.ManyToManyField("figure.Figure", verbose_name=u"图片", related_name="guidlines", null=True, blank=True)
+
+
+    class Meta:
+        verbose_name_plural = u"临床策略"
+
+    def __unicode__(self):
+        return "<Guideline: %s>" % get_abstract(self.content)
+# }}}
+
+
+# EndPoint {{{
+class EndPoint(models.Model):
+    u'''
+        治疗终点
+    '''
+
+    type_choices = ((1, "primary"),
+                    (2, "secondary"),)
+
+    content = models.TextField(u"内容", blank=True)
+    type = models.IntegerField(u"类型", choices=type_choices, blank=True)
+    indicator = models.ForeignKey("indicator.Indicator", verbose_name=u"医学指标", related_name="endpoints", null=True, blank=True)
+    objects = EndPointManager()
+
+    class Meta:
+        verbose_name_plural = u"治疗终点"
+
+    def __unicode__(self):
+        return "<EndPoint: %s>" % get_abstract(self.content)
+# }}}
+
+
+# ClinicCondition {{{
+class ClinicCondition(models.Model):
+    u'''
+        临床条件
+    '''
+
+    type_choices = ((0, "允许"),
+                    (1, "排除"),)
+
+    content = models.TextField(u"内容", blank=True)
+    type = models.IntegerField(u"类型", choices=type_choices, blank=True)
+    indicator = models.ForeignKey("indicator.Indicator", verbose_name=u"医学指标", related_name="clinic_conditions", null=True, blank=True)
+    objects = ClinicConditionManager()
+
+
+    class Meta:
+        verbose_name_plural = u"临床条件"
+
+    def __unicode__(self):
+        return "<ClinicCondition: %s>" % get_abstract(self.content)
+# }}}
+
+
+# BaseLine {{{
+class BaseLine(models.Model):
+    u'''
+        基线水平
+    '''
+
+    content = models.TextField(u"内容", blank=True)
+    figures = models.ManyToManyField("figure.Figure", verbose_name=u"图片", related_name="baselines", null=True, blank=True)
+    base_line_items = models.ManyToManyField("subjects.BaseLineItem", verbose_name=u"研究基线项目", related_name="baselines", null=True, blank=True)
+
+
+    class Meta:
+        verbose_name_plural = u"基线水平"
+
+    def __unicode__(self):
+        return "<BaseLine: %s>" % get_abstract(self.content)
+# }}}
+
+
+import signals
+admin.site.register([
+                     Source,
+                     Reference,
+                     KnowledgePiece,
+                     Guideline,
+                     ClinicCondition,
+                     BaseLine,
+                     ResultContent,
+                     BlogAnnotation,
+                    ])
diff --git a/97suifangqa/apps/sciblog/search_indexes.py b/97suifangqa/apps/sciblog/search_indexes.py
new file mode 100644
index 0000000..0037d5b
--- /dev/null
+++ b/97suifangqa/apps/sciblog/search_indexes.py
@@ -0,0 +1,35 @@
+# -*- coding: utf-8 -*-
+from haystack import indexes
+import datetime
+from .models import SciBlog, BlogAnnotation
+
+
+class SciBlogIndex(indexes.SearchIndex, indexes.Indexable):
+    u'''
+    科学文章索引
+    '''
+    text = indexes.CharField(document=True, use_template=True)
+
+    def get_model(self):
+        return SciBlog
+
+    def index_queryset(self, using=None):
+        u'''
+        对所有文章进行索引
+        '''
+        return self.get_model().objects.all()
+
+class ProperNounIndex(indexes.SearchIndex, indexes.Indexable):
+    u'''
+    专业名词索引
+    '''
+    text = indexes.CharField(document=True, use_template=True)
+
+    def get_model(self):
+        return BlogAnnotation
+
+    def index_queryset(self, using=None):
+        u'''
+        返回所有类型为专业名词类型的注释
+        '''
+        return self.get_model().objects.propernouns()
diff --git a/97suifangqa/apps/sciblog/signals.py b/97suifangqa/apps/sciblog/signals.py
new file mode 100644
index 0000000..03e1968
--- /dev/null
+++ b/97suifangqa/apps/sciblog/signals.py
@@ -0,0 +1,60 @@
+# -*- coding: utf-8 -*-
+
+from django.db.models.signals import pre_save, m2m_changed
+from django.dispatch import receiver
+from models import SciBlog, BlogAnnotation, ResultContent, Reference, BaseLine,\
+                   ClinicCondition, KnowledgePiece, Guideline, EndPoint
+
+import re
+
+def mark_keywords_in_textfield(model, fields, related_name='NONE'):
+    u'''
+    fields:需要处理的field名称
+    handler:消息处理函数，对instance中的fields进行关键词过滤
+    related_name:model实例在BlogAnnotation中的反向关系名称,如文章注释通过blogs属性关联到Sciblog
+    '''
+
+    @receiver(pre_save, sender = model, weak=False)
+    def handler(sender, **kwargs):
+        instance = kwargs['instance']
+        for annotation in BlogAnnotation.objects.propernouns():
+            keyword = annotation.firstkeyword()
+            for field in set(fields):
+                content = getattr(instance, field)
+                if keyword not in content:
+                    continue
+                try:
+                    relate = getattr(annotation, related_name)
+                    relate.add(instance)
+                    annotation.save()
+                except:
+                    pass
+
+mark_keywords_in_textfield(SciBlog, ['abstract_result', 'method', 'aim', 
+                                     'abstractAE', 'treatment_content', 
+                                     'endpoint_content', 'detectionAssay'], 'blogs')
+mark_keywords_in_textfield(ResultContent, ['abstract', 'content', 'card_content'])
+mark_keywords_in_textfield(Reference, ['description'])
+mark_keywords_in_textfield(KnowledgePiece, ['content'])
+mark_keywords_in_textfield(Guideline, ['content'])
+mark_keywords_in_textfield(EndPoint, ['content'])
+mark_keywords_in_textfield(ClinicCondition, ['content'])
+mark_keywords_in_textfield(BaseLine, ['content'])
+
+def mark_keywords_in_m2mfields(sender, **kwargs):
+    if kwargs['action'] != 'pre_add':
+        return 
+    blog = kwargs['instance']
+    model = kwargs['model']
+    objs = model.objects.filter(pk__in = kwargs.get('pk_set') or [])
+    for annotation in BlogAnnotation.objects.propernouns():
+        keyword = annotation.firstkeyword()
+        for obj in objs:
+            if keyword not in obj.content:
+                continue
+            annotation.blogs.add(blog)
+            annotation.save()
+            return 
+
+for m2m in ['konwledge_piece', 'baseline', 'endpoints', 'clinic_conditions']:
+    m2m_changed.connect(mark_keywords_in_m2mfields, sender=getattr(SciBlog, m2m).through)
diff --git a/97suifangqa/apps/sciblog/templatetags/__init__.py b/97suifangqa/apps/sciblog/templatetags/__init__.py
new file mode 100644
index 0000000..e69de29
--- /dev/null
+++ b/97suifangqa/apps/sciblog/templatetags/__init__.py
diff --git a/97suifangqa/apps/sciblog/templatetags/group_list.py b/97suifangqa/apps/sciblog/templatetags/group_list.py
new file mode 100644
index 0000000..cb96d13
--- /dev/null
+++ b/97suifangqa/apps/sciblog/templatetags/group_list.py
@@ -0,0 +1,20 @@
+#import itertools
+
+from django import template
+import itertools
+
+register = template.Library()
+
+@register.filter
+def chunks(value, chunk_length):
+    """
+    Breaks a list up into a list of lists of size <chunk_length>
+    """
+    clen = int(chunk_length)
+    i = iter(value)
+    while True:
+        chunk = list(itertools.islice(i, clen))
+        if chunk:
+            yield chunk
+        else:
+            break
diff --git a/97suifangqa/apps/sciblog/tests.py b/97suifangqa/apps/sciblog/tests.py
new file mode 100644
index 0000000..501deb7
--- /dev/null
+++ b/97suifangqa/apps/sciblog/tests.py
@@ -0,0 +1,16 @@
+"""
+This file demonstrates writing tests using the unittest module. These will pass
+when you run "manage.py test".
+
+Replace this with more appropriate tests for your application.
+"""
+
+from django.test import TestCase
+
+
+class SimpleTest(TestCase):
+    def test_basic_addition(self):
+        """
+        Tests that 1 + 1 always equals 2.
+        """
+        self.assertEqual(1 + 1, 2)
diff --git a/97suifangqa/apps/sciblog/urls.py b/97suifangqa/apps/sciblog/urls.py
new file mode 100644
index 0000000..722984b
--- /dev/null
+++ b/97suifangqa/apps/sciblog/urls.py
@@ -0,0 +1,17 @@
+from django.conf.urls import patterns, url
+
+from .models import SciBlog, BlogAnnotation
+from .views import  *
+
+blog_blocks = '|'.join(['source','abstract', 'knowledge','follow', 'results', 'comment','refrences', 'test','results-detail'])
+urlpatterns = patterns('',
+       url(r'^$', query, name='list_blogs'),
+       url(r'^result(\d+)/?$', show_result, name='blog_result'),
+       url(r'^index$', blog_index, name='index'),
+       url(r'^query/?$', query, name='query_blogs'),
+       url(r'^collection/?$', blog_collection, name='blog_collection'),
+       url(r'^(\d+)/(%s)?/?$' % blog_blocks, blog_detail, name='blog_detail'),
+       url(r'^(\d+)/collect/?$', add_user_to_m2m, name='blog_collect', kwargs={'m2m':'collected_by'}),
+       url(r'^(\d+)/understand/?$', add_user_to_m2m, name='blog_understood', kwargs={'m2m':'catched_by'}),
+       url(r'^annotation/(\d+)/collect/?$', add_user_to_m2m, name='annotation_collect', kwargs={'m2m':'collected_by', 'model': BlogAnnotation}),
+                       )
diff --git a/97suifangqa/apps/sciblog/views.py b/97suifangqa/apps/sciblog/views.py
new file mode 100644
index 0000000..7c6a4e7
--- /dev/null
+++ b/97suifangqa/apps/sciblog/views.py
@@ -0,0 +1,142 @@
+# -*- coding: utf-8 -*-
+
+import json
+from django.http import HttpResponse, HttpResponseNotFound
+from django.views.generic.list_detail import object_detail
+from django.shortcuts import render, get_object_or_404
+from django.contrib.auth.decorators import login_required
+
+from .models import SciBlog, ResultContent
+from .forms import SciBlogSearchForm, ProperNounSearchForm
+from info.forms import QuerySearchForm
+import itertools
+
+def blog_detail(request, blogid, block):
+    u'''
+    /blog/1/
+    一个简单的显式blog详细内容的view函数
+    '''
+    block = block or "source"
+    template = 'sciblog/blog_detail_%s.html' % block
+    blog = get_object_or_404(SciBlog, id=blogid)
+
+    blockid = block
+    
+    # 用户已经收藏？
+    collected = request.user.is_authenticated() and blog.collected_by.filter(id=request.user.id)
+
+    # 用户已经懂了？
+    understood = request.user.is_authenticated() and blog.catched_by.filter(id=request.user.id)
+
+    # 与该文章相关的段落注释和专业名词
+    annotations = blog.annotations.all_json(user=request.user)
+    return render(request, template, locals())
+
+
+def blog_index(request):
+    """
+    Temporary handler for index page render
+    You might want to rename/relocate this
+    """
+    return render(request,"sciblog/index.html",locals())
+
+def generator_has_content(generator):
+    '''
+    Returns (has_content, generator) based on the input generator
+
+    If generator has at least one item, has_content is True.
+    Otherwise, has_content is False.
+
+    generator will return all items in the input generator
+    '''
+    #Simplified logic using itertools
+    checkgen, outputgen = itertools.tee(generator, 2)
+    has_content = False
+    for item in checkgen:
+        has_content = True
+        break
+    return (has_content, outputgen)
+
+def objects_of_sqs(sqs):
+    u'''
+    返回search squery set结果对应的model object
+    '''
+    return itertools.imap(lambda x: x.object, sqs)
+
+def limit(resultSet, count = 10):
+    return itertools.islice(resultSet, count)
+
+def query(request):
+    u'''
+    Blog查询
+    '''
+
+    tab = 'list'
+    search_history = request.session.get('search_history', '').split('&&&')
+
+    if request.method == 'GET':
+        form = SciBlogSearchForm(request.GET)
+    elif request.method == 'POST':
+        form = SciBlogSearchForm(request.POST)
+
+    if form.is_valid() and form.cleaned_data['q']:
+        q = form.cleaned_data['q']
+        search_history = [s for s in search_history if s != q]
+        search_history.insert(0, q)
+        search_history = search_history[0:5] #只保存最新的五条搜索记录
+        request.session['search_history'] = '&&&'.join(search_history)
+
+        results = form.search()
+        (has_blogs, blogs) = generator_has_content(limit(objects_of_sqs(results),10))
+        questuinsqs = QuerySearchForm(request.GET).search()
+        (has_relate_questions, questions) = generator_has_content(limit(objects_of_sqs(questuinsqs),8))
+        ppnounsqs = ProperNounSearchForm(request.GET).search()
+        (hasppnouns, ppnouns) = generator_has_content(limit(objects_of_sqs(ppnounsqs),10))
+        return render(request, 'sciblog/blog_list.html', locals())
+    else:
+        (has_blogs, blogs) = generator_has_content(limit(SciBlog.objects.all(),10))
+        return render(request, 'sciblog/blog_list.html', locals())
+
+
+@login_required
+def blog_collection(request):
+    blogs = request.user.blog_collection.all()
+    tab   = 'collection'
+    has_blogs = len(blogs) > 0
+    ppnouns = request.user.annotation_collection.all()
+    has_ppnouns = request.user.annotation_collection.count() > 0
+    return render(request, 'sciblog/blog_list.html', locals())
+
+
+@login_required
+def add_user_to_m2m(request, objid, m2m ='collected_by', model = SciBlog):
+    u'''
+    响应收藏按钮和'懂了'按钮的点击
+    '''
+    
+    result = {"error":False, 'added':True}
+    result['id'] = objid 
+    result['model'] = model._meta.verbose_name_plural
+    user = request.user
+    try:
+        obj  = model.objects.get(id=objid)
+        m2m  = getattr(obj, m2m)
+        if not m2m.filter(id = user.id):
+            # 还没有收藏或点击懂了
+            m2m.add(user)
+        else:
+            # 已经收藏或点击了懂了
+            m2m.remove(user)
+            result['added'] = False
+        result['times'] = m2m.count()
+    except:
+        result['error'] = True
+        result['added'] = False
+
+    return HttpResponse(json.dumps(result),
+                       mimetype = 'application/json')
+
+def show_result(request, resultid):
+    result  = get_object_or_404(ResultContent, id=resultid)
+    blog = result.blog
+    return render(request, 'sciblog/blog_detail_results-detail.html', locals())
author	Alvin Li <liweitianux@gmail.com>	2013-08-13 14:13:24 +0800
committer	Alvin Li <liweitianux@gmail.com>	2013-08-13 14:13:24 +0800
commit	9636d4a6767f49384d5c386bc3f1142c88b90613 (patch)
tree	3a70f6d9e4be1791d36c87cc7cbfd1d5aa2b39dd /97suifangqa/apps/sciblog
parent	9383d9a8a5988d071766c3d08a5c946e9c5b02ae (diff)
download	97dev-9636d4a6767f49384d5c386bc3f1142c88b90613.tar.bz2