这项工作得到了国家卫生资助研究院（以R01-AI067395-01，R21的-R022754-01和R21-I58002-01）。我们感谢尼迈耶C.手稿批判性阅读的。

1。创建LLUF探头<ol><li>聚醚砜膜（2厘米2）密封边界桨环氧树脂胶合膜与的三角形聚丙烯桨（美国加州大学圣迭戈分校）。分子量为30 kDa的截止（截留分子量），聚醚砜与带负电荷的膜。 </li><li>聚四氟乙烯氟化乙烯丙烯管（内径/外径，0.35/0.50厘米）被连接到了一个三角形的聚丙烯桨缸退出，所以LLUF探头，可以连接到20毫升的注射器。 </li><li>进入人体的唾液浸泡后，在培养皿中（直径50毫米），聚醚砜膜，负压创建撤回注射器。注射器负压驱车从唾液样品蛋白质超滤过程。 </li><li>探针用70％酒精过夜，使用前消毒。要表现出适当的密封，我们定位成一个解决方案LLUF探头TION含有蓝色葡聚糖（50毫克/毫升），平均为2小时2000 kDa的分子质量。蓝色葡聚糖中收集的样本的情况下，无泄漏，在探针的制备和抽样。 </li></ol> 2。唾液收集<ol><li>全唾液收集从三个健康志愿者服用任何药物（两名男性和一名女性之间的年龄在20和40），牙龈炎或蛀牙6没有明显的迹象。 </li><li>后用清水冲洗口腔，唾液样品收集由随地吐痰，无化学刺激，成冰水冷船只。 </li><li>所有样品均汇集和收集过程中，在冰库内。 </li><li>申请LLUF探头采样后，立即集合，唾液（200μL）。在4°C室进行抽样。 </li><li>带或不带LLUF探头收集唾液中的蛋白质（1.0微克/微升），直接受到纳米立法质量小号未经酶解pectrometry分析。蛋白质浓度测定使用Bio-Rad公司的蛋白含量12。 </li></ol> 3。 NanoLC的LTQ质谱分析<ol><li>联合国消化的唾液样本（5μL）直接加载到，Eksigent自动进样器NanoLC系统的陷阱列，使用100％的缓冲（2％乙腈％甲酸）。 NanoLC，再加上线，在Finnigan LTQ质谱仪。 </li><li>样品装载和洗涤后，阀门切换，被送到了500 nL / min的线性梯度陷阱和分离柱（10厘米长，内径100微米，内部Synergi 4微米C18的包装）。渐变是从0到50％缓冲液B（80％乙腈％甲酸）在45分钟。 </li><li>神剑传奇的数据依赖模式的nanoLC的LTQ MS仪器操作。强度1×10 5以上的四个最强的MS离子的MS / MS光谱采集与动态排斥启用和碰撞能量设置为35％。 </li><li>每个样品运行的NanoLC的LTQ MS系统的两倍。从三个不同的制剂样品使用。 补充表1和表2中列出了三个独立样本中检测到的肽。代表的NanoLC LTQ质谱如图3所示。 </li></ol> 4。数据分析和蛋白质数据库搜索<ol><li>每个RAW文件转换到一个mzXML使用Readw.exe文件。 </li><li> mzXML文件输入到SEQUEST巫师2系统，对人类数据库由相应的国家生物技术信息（NCBI）的蛋白质数据库，采用非专一性中心产生了搜查。母离子的质量公差为1.5大。 16大的一个分子质量差搜索氧化蛋氨酸。 </li><li> SEQUEST搜索后，结果自动过滤，验证1ð显示PeptideProphet和ProteinProphet [系统生物学研究所（顺义）。 PeptideProphet估计，肽的任务是“正确”与“不正确的”，它的的SEQUEST成绩（Xcorr，ΔCn，SP，可吸入悬浮粒子）和其他信息确定每个肽序列的基础上，全面的概率（P）得分。每个分配给MS / MS谱图肽的基础上的蛋白质，ProteinProphet计算的概率得分从0到1。 </li><li>为了尽量减少假阳性鉴定，我们采用了严格的筛选标准。首先，最小P得分截止0.8任何公认的肽，以保证非常低的错误（远低于3％）和相当不错的灵敏度。第二，所有肽&gt; 0.8带够得分必须有高在同一时间互相关（Xcorr）得分：1.9，2.2，3.0 +1，+2，+3负责。 </li></ol> 5。口腔细菌去除LLUF探头<ol><li> LLUF探测的能力，以确定删除口腔中的细菌，探头收集LLUF（第3节）之前和之后的唾液传播细菌检测平板。 </li><li>好氧菌生长抗生素劳里亚-Bertani（LB），在37°C琼脂板一天。 </li><li>厌氧细菌对抗生素的布氏肉汤琼脂平板（屋宇署，火花，MD）在厌氧条件下，使用天然气白（BD公司，加利福尼亚州圣何塞市）在37°C，一天生长。 </li></ol> 6。代表结果 1。 LLUF探头和采样唾液在一个模拟口腔环境中的制造如果采样唾液可以作为吮吸棒棒糖执行，程序将避免吐唾沫在唾液收集装置13-14退化。重要的是，它也将成为可能和本地动态监测患者口腔的。此外，如果可以简化样品制备用唾液，医生便很容易facilitate的程序，以加速他们的决定，在未来的临床操作。质谱是一个最敏感的技术来检测，甚至在很短的时间内蛋白质序列。然而，复杂的样品制备程序阻碍了这项技术在临床使用。此外，它是已知的高丰度蛋白质或蛋白质分子量高，临床标本中（如唾液中的淀粉酶）质谱分析的面具15-16低丰度蛋白质。为了克服上述障碍，我们开发了一个棒棒糖般的超滤装置，名为LLUF探头（ 图1）。带负电荷的聚醚砜膜在截留分子量30 kDa的（ 图1A，粘聚丙烯桨（ 图1A，B），）。它被安置在前面的LLUF探针筛选出较大的蛋白质，唾液中的意图。以模仿人类口腔环境（ 图1A，G），海绵（ 图1A，E）被浸泡在唾液的培养皿（ 图1A，F）。注射器（ 图1A，D）完全撤出后，过滤唾液开始沿着连接管（ 图1A，C）和收集。 2。土著唾液多肽鉴定NanoLC的LTQ质谱比较LC色谱图，我们发现不同的唾液色谱LLUF采样（ 图2）前后，表明有LLUF取样后唾液中不同的蛋白质组成。 ，以确定蛋白质的组成，我们采用NanoLC-的LTQ质谱，被称为是能够及时从多种蛋白质混合物的序列肽。更重要的是，简化样品准备用于临床目的，没有化学或酶消化的整个唾液申请NanoLC的LTQ质谱分析。不料，131肽我们重新确定未消化的唾液（ 参考表1）。这些肽是从各种富含脯氨酸的蛋白，肌动蛋白，α-淀粉酶，α1球蛋白，β球蛋白，histain 1，1角蛋白，粘蛋白7，聚免疫球蛋白受体，satherin，和S100A9的片段。二十六个独特的多肽被确定唾液中后过滤LLUF探头（ 参考表2）。这些肽是主要来自各种富含脯氨酸的蛋白产生的碎片。如聚免疫球蛋白受体（83.24 kDa的）和α-淀粉酶，蛋白质的多肽不到，显示出较大和丰富的蛋白质去除LLUF探测能力。一个内部的α-淀粉酶肽相应的PFIAIHAEAESKL肽的MS / MS谱如图3A所示。最有趣的是，取出后较大的蛋白质，18 26的测序肽成为检测探头采样LLUF唾液（ 表1）。这18肽，富含脯氨酸的蛋白或假想蛋白，结束了脯氨酸（P） -来自谷氨酰胺（Q）（PQ）的，SR-SP的或PP C-末端图3B显示一个MS / MS。在探头采样LLUF唾液检测的PQGPPQQGGHPRPP肽谱。肽可能来自富含脯氨酸的蛋白HaeIII亚科1和2（ 表1）。 <img alt="图1" src="/files/ftp_upload/4108/4108fig1.jpg" /> 图1。组成 小组 LLUF探头和从模仿人类口腔全唾液采样 答 ：（ 一 ）（ 三 ）与一个30 kDa的截留分子量半透聚醚砜（二）聚丙烯桨;聚四氟乙烯氟化乙烯丙烯管; （四）B组 ：20 ml注射器。海绵（E）（拟仿舌）浸泡到培养皿中含有人体唾液创建（F）人造人的口腔（G）。所产生的负面压力完全撤出注射器驱动器收集的流体沿着连接管（ 箭头 ），并朝着建立空间（ 箭头 ）注射器内移动。酒吧：2.0厘米。 <img alt="图2" src="/files/ftp_upload/4108/4108fig2.jpg" /> 图2。差分LC / MS / MS的色谱前后唾液LLUF采样。人类唾液中的蛋白质（1.0微克/微升），未经过滤或与LLUF探头。没有胰蛋白酶消化的蛋白质直接受到NanoLC-的LTQ MS是Eksigent纳米液相色谱系统的共轭材料和方法。基峰色谱唾液（与44 MIM保留时间）前（A）和（乙）LLUF采样进行说明。 <img alt="图3" src="/files/ftp_upload/4108/4108fig3.jpg" /> 图3。探测器TION NanoLC LTQ质谱测序。唾液蛋白唾液多肽前（A）和（二）抽样LLUF探头在实验过程描述NanoLC的LTQ质谱分析后。从自然的人类唾液唾液多肽衍生酶解证明补充表1和表2。源自α-淀粉酶一肽（PFIAIHAEAESKL）的独家收集与LLUF探针（A）的唾液样本中没有检测到，说明在去除大分子蛋白质的能力LLUF探头。许多肽-PQ的，-SR-SP或PP C-末端仅在后超滤LLUF的探针样品。一个来自各种富含脯氨酸的蛋白肽（PQGPPQQGGHPRPP）（b）所示。 MS / MS的光谱特征“Y”和“B”系列离子证实双方肽的身份。 <img alt="图4" src="/files/ftp_upload/4108/4108fig4.jpg" /> &lt;强图4去除口腔细菌在LLUF探头使用。构建一个LLUF探针材料和方法所述。探头定位到人的唾液内的一个模拟口腔环境（ 图1）。被撤销的注射器在LLUF探头年底创建一个负压力，促使唾液采样超滤过程。采样期间，全唾液越过选择性通过聚醚砜膜和注射器内积累。全唾液采样前与LLUF探针作为对照。唾液后探针取样LLUF（10μL）伸长琼脂平板上的细菌检测。A组 ：唾液（+ LLUF）和无（“+ LLUF）LLUF探头采样伸长抗生素端侧的LB琼脂平板在37°C间一天，B组 ：与不LLUF探头采样唾液传播上无抗生素的布氏肉汤琼脂平板厌氧条件下使用天然气白（BD公司，加利福尼亚州圣何塞市）在37°C，一天。细菌没有增长LLUF探头采样唾液传播的平板上，展示LLCF探头在消除有氧以及厌氧口腔细菌的能力。酒吧：1.0厘米。 <table border="1"><tbody><tr><td></td><td> 肽序列/测量肽质量 </td><td> 登录号 </td><td> 名称 </td></tr><tr><td> 1 </td><td> AGNPQGPSPQGGNKPQ GPPPPPGKPQ 2485.3 </td><td> GI | 41349484 </td><td>富含脯氨酸的蛋白BstNI亚科1亚型2前兆</td></tr><tr><td></td><td></td><td> GI | 41349482 </td><td>富含脯氨酸的蛋白BstNI亚科1亚型1前兆</td></tr><tr><td></td><td></td><td> GI | 60301553 </td><td>富含脯氨酸的蛋白BstNI亚科2 </td></tr><tr><td> 2 </td><td> GGHQQGPPPPPPGKPQ 1576.9 </td><td> GI | 4826944 </td><td>富含脯氨酸的蛋白HaeIII亚科2 </td></tr><tr><td></td><td></td><td> GI | 9945310 </td><td>富含脯氨酸的蛋白HaeIII亚科1 </td></tr><tr><td> 3 </td><td> GPPPAGGNPQQPQAPPA GKPQGPPPPPQGGRPP 3126.2 </td><td> GI | 37537692 </td><td>富含脯氨酸的蛋白质BstNI亚科4易制毒化学</td></tr><tr><td> 4 </td><td> GPPPPGGNPQQPLPPPAGKPQ 2028.3 </td><td> GI | 113423660 </td><td>预测：假定蛋白</td></tr><tr><td> 5 </td><td> GPPPPGKPQGPPPQGDKSRSP 2077.8 </td><td> GI | 113423262 </td><td>预测：假定蛋白亚型5 </td></tr><tr><td></td><td></td><td> GI | 41349482 </td><td>富含脯氨酸的蛋白BST倪亚科1亚型1前兆</td></tr><tr><td></td><td></td><td> GI | 60301553 </td><td>富含脯氨酸的蛋白BstNI亚科2 </td></tr><tr><td></td><td></td><td> GI | 113423663 </td><td>预测：假定蛋白</td></tr><tr><td></td><td></td><td> GI | 41349484 </td><td>富含脯氨酸的蛋白BstNI亚科1亚型2前兆</td></tr><tr><td></td><td></td><td> GI | 41349486 </td><td>富含脯氨酸的蛋白BstNI亚科1亚型3前兆</td></tr><tr><td> 6 </td><td> GPPPPPPGKPQGPPPQ GGRPQGPPQGQSPQ 2918.5 </td><td> GI | 9945310 </td><td>富含脯氨酸的蛋白HaeIII亚科1 </td></tr><tr><td> 7 </td><td> GPPPQEGNKPQRPPPPGRPQ 2131.3 </td><td> GI | 113423660 </td><td>预测：假定蛋白</td></tr><tr><td> 8</td><td> GPPPQGGNKPQGPPPPGKPQ 2030 </td><td> GI | 113423663 </td><td>预测：假定蛋白</td></tr><tr><td></td><td></td><td> GI | 41349482 </td><td>富含脯氨酸的蛋白BstNI亚科1亚型1前兆</td></tr><tr><td></td><td></td><td> GI | 113423262 </td><td>预测：假定蛋白亚型5 </td></tr><tr><td></td><td></td><td> GI | 60301553 </td><td>富含脯氨酸的蛋白BstNI亚科2 </td></tr><tr><td> 9 </td><td> GPPPQGGRPQGPPQGQSPQ 1866.6 </td><td> GI | 4826944 </td><td>富含脯氨酸的蛋白HaeIII亚科2 </td></tr><tr><td> 10 </td><td> GPPQQGGHPPPPQGRPQ 1713.8 </td><td> GI | 9945310 </td><td>富含脯氨酸的蛋白HaeIII亚科1 </td></tr><tr><td></td><td></td><td> GI | 4826944 </tD&gt; <td>富含脯氨酸的蛋白HaeIII亚科2 </td></tr><tr><td> 11 </td><td> GPPQQGGHQQGPPPPPPGKPQ 2083.1 </td><td> GI | 9945310 </td><td>富含脯氨酸的蛋白HaeIII亚科1 </td></tr><tr><td></td><td></td><td> GI | 4826944 </td><td>富含脯氨酸的蛋白HaeIII亚科2 </td></tr><tr><td> 12 </td><td> GRPQGPPQQGGHQQGP PPPPPGKPQ 2512.6 </td><td> GI | 4826944 </td><td>富含脯氨酸的蛋白HaeIII亚科2 </td></tr><tr><td></td><td></td><td> GI | 9945310 </td><td>富含脯氨酸的蛋白HaeIII亚科1 </td></tr><tr><td> 13 </td><td> NKPQGPPPPGKPQGPP PQGGSKSRSSR 2720​​.2 </td><td> GI | 113423262 </td><td>预测：假定蛋白亚型5 </td></tr><tr><td></td><td></td><td> GI | 113423663 </td><td>预测：HYpothetical蛋白</td></tr><tr><td> 14 </td><td> PQGPPQQGGHPRPP 1450.1 </td><td> GI | 9945310 </td><td>富含脯氨酸的蛋白HaeIII亚科1 </td></tr><tr><td></td><td></td><td> GI | 4826944 </td><td>富含脯氨酸的蛋白HaeIII亚科2 </td></tr><tr><td> 15 </td><td> QGRPQGPPQQGGHPRPP 1791.1 </td><td> GI | 4826944 </td><td>富含脯氨酸的蛋白HaeIII亚科2 </td></tr><tr><td></td><td></td><td> GI | 9945310 </td><td>富含脯氨酸的蛋白HaeIII亚科1 </td></tr><tr><td> 16 </td><td> SPPGKPQGPPPQ 1186.9 </td><td> GI | 113423262 </td><td>预测：假定蛋白亚型5 </td></tr><tr><td></td><td></td><td> GI | 41349482 </td><td>富含脯氨酸的蛋白BstNI亚科1亚型1前兆</td></tr><tr><td&gt; </td><td></td><td> GI | 60301553 </td><td>富含脯氨酸的蛋白BstNI亚科2 </td></tr><tr><td></td><td></td><td> GI | 113423663 </td><td>预测：假定蛋白</td></tr><tr><td></td><td></td><td> GI | 41349484 </td><td>富含脯氨酸的蛋白BstNI亚科1亚型2前兆</td></tr><tr><td></td><td></td><td> GI | 41349486 </td><td>富含脯氨酸的蛋白BstNI亚科1亚型3前兆</td></tr><tr><td> 17 </td><td> SPPGKPQGPPPQGGNQ PQGPPPPPGKPQ 2720​​.3 </td><td> GI | 113423663 </td><td>预测：假定蛋白</td></tr><tr><td></td><td></td><td> GI | 41349482 </td><td>富含脯氨酸的蛋白BstNI亚科1亚型1前兆</td></tr><tr><td></td><td></td><td> GI | 113423262 </td><td>预测：假定蛋白亚型5 </td></tr><tr><td></td><td></td><td> GI | 60301553 </td><td>富含脯氨酸的蛋白BstNI亚科2 </td></tr><tr><td> 18 </td><td> SPPGKPQGPPQQEGNKPQ 1870.9 </td><td> GI | 37537692 </td><td>富含脯氨酸的蛋白质BstNI亚科4易制毒化学</td></tr></tbody></table> 表1。肽专门在LLUF收集样品检测。 参考表1。 <a href="http://www.jove.com/files/ftp_upload/4108/4108table1.xls" target="_blank">点击这里查看补充表1</a> 。 参考表2。 <a href="http://www.jove.com/files/ftp_upload/4108/4108table2.xls" target="_blank">点击这里查看补充表2</a> 。

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没有利益冲突的声明。

我们已经发现，许多未消化在人类唾液中存在的多肽片段。这些多肽片段是从富含脯氨酸的蛋白，肌动蛋白，α-淀粉酶，α1球蛋白，β球蛋白，histain 1，1角蛋白，粘蛋白7，聚免疫球蛋白受体，satherin，S100A9的各种形式的衍生工具。有可能是未定的切割位点的多肽生产作出贡献的许多因素。例如，一些多肽片段可能是人类唾液中自然存在的。许多与PQ的C-末端肽（ 表1和补充表1和2）。富...

<table border="1"><tbody><tr><td> 试剂名称 </td><td> 公司 </td><td> 目录编号 </td><td> 评论 </td></tr><tr><td>聚醚砜膜</td><td>颇尔公司</td><td></td><td> 30 kDa的截留分子量</td></tr><tr><td>铁氟龙氟化乙烯丙烯管</td><td>厄普丘奇科学</td><td></td><td></td></tr><tr><td>蓝色葡聚糖</td><td>西格玛</td><td></td><td></td></tr><tr><td>纳米液相色谱系统</td><td> eksigent </td><td></td><td></td></tr><tr><td> C18陷阱列</td><td>安捷伦</td><td> 5065-9913 </td><td></td></tr><tr><td>的LTQ线性离子阱质谱仪</td><td>赛默飞世尔</td><td></td><td></td></tr><tr><td>巫师2 </td><td>圣人列印Resea星期四</td><td></td><td></td></tr><tr><td>乙腈-0.1％甲酸</td><td>托德·贝克</td><td> 9832-03 </td><td> LC / MS的等级</td></tr><tr><td>水0.1％甲酸</td><td>托德·贝克</td><td> 9834-03 </td><td> LC / MS的等级</td></tr></tbody></table>

sampling human indigenous saliva peptidome using a lollipop-like ultrafiltration probe: simplify and enhance peptide detection for clinical mass spectrometry

虽然人类唾液蛋白质和多肽已显示1-2 majorly确定从唾液蛋白的胰蛋白酶消化。土著人的唾液多肽的鉴定没有事先与外源酶消化成为当务之急，因为在人类唾液中的原生肽提供的潜在价值，为诊断疾病，预测疾病的进展，并监测治疗效果。适当的采样是提高土著人的唾液多肽鉴定的关键一步。抽样涉及人类唾液离心去除碎片3-4传统方法可能太费时，是适用于临床使用。此外，通过离心去除碎片可能无法清理，大部分受感染的病原体和去除高丰度蛋白质，常常阻碍了鉴定低丰度多肽。 传统的蛋白质组学方法，PRI共轭玛利莲利用二维凝胶电泳（2-DE）凝胶与凝胶消化能找出很多的唾液蛋白质5-6。然而，这种方法一般是不够敏感的检测低丰度的肽/蛋白质。液相色谱 - 质谱（LC-MS法）为基础的蛋白质组学是一种替代，它可以识别2-DE分离，恕不另行蛋白质。虽然这种方法提供了更高的灵敏度，它一般需要事先样品预分馏7预消化和胰蛋白酶，这使得它难以用于临床。 规避由于样品制备质谱的障碍，我们已经开发出一种技术叫做毛细管超滤（CUF）探针8-11。从我们的实验室数据表明，的CUF探测器能够捕捉各种动物在一个充满活力和微创的方式8微环境的蛋白质在体内 -11。没有离心是必要的，因为通过简单的样品采集过程中撤回注射器负压创建。 CUF探针结合的LC-MS已成功确定了胰蛋白酶消化的蛋白质8-11。在这项研究中，我们创建一个棒棒糖般的超滤（LLUF）探头，可以很容易地适合于人类口腔升级的超取样技术。没有胰蛋白酶消化的LC-MS直接分析表明，人类唾液本国包含许多肽来自各种蛋白质的片段。 LLUF探头采样唾液避免离心，但有效地消除了许多大型及高丰度蛋白。质谱结果表明，许多低丰度肽后，筛选出较大的蛋白质与LLUF探针检测。多步样品色谱分离检测低丰度唾液肽独立。为临床应用，LLUF探头纳入D可以用LC-MS在未来可能被用来从唾液，以监测疾病的进展。

Watch this Scientific Journal Video about Sampling Human Indigenous Saliva Peptidome Using a Lollipop-Like Ultrafiltration Probe: Simplify and Enhance Peptide Detection for Clinical Mass Spectrometry 

Sampling Human Indigenous Saliva Peptidome Using a Lollipop-Like Ultrafiltration Probe: Simplify and Enhance Peptide Detection for Clinical Mass Spectrometry

考虑为今后的临床应用唾液取样，棒棒糖般超滤（LLUF）的探针制作，以适应在人类口腔。直接未消化唾液NanoLC-LTQ质谱分析表明LLUF探头的能力，消除大量的蛋白质和高丰度蛋白，使更多检测​​低丰度肽。

采样使用超探头棒棒糖样的土著人的唾液多肽：简化和增强肽的临床质谱检测

Although human saliva proteome and peptidome have been revealed 1-2 they were majorly identified from tryptic digests of saliva proteins. Identification ...

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JoVE Journal

Medicine

11.4K 次观看.  Sanford-Burnham Medical Research Institute. 考虑为今后的临床应用唾液取样，棒棒糖般超滤（LLUF）的探针制作，以适应在人类口腔。直接未消化唾液NanoLC-LTQ质谱分析表明LLUF探头的能力，消除大量的蛋白质和高丰度蛋白，使更多检测​​低丰度肽。

视频: Sampling Human Indigenous Saliva Peptidome Using a Lollipop-Like Ultrafiltration Probe: Simplify and Enhance Peptide Detection for Clinical Mass Spectrometry

Using Visual and Narrative Methods to Achieve Fair Process in Clinical Care

The Institute of Medicine has targeted patient-centeredness as an important area of quality improvement. A major dimension of patient-centeredness is respect for patient's values, preferences, and expressed needs. Yet specific approaches to gaining this understanding and translating it to quality care in the clinical setting are lacking. From a patient perspective quality is not a simple concept but is best understood in terms of five dimensions: technical outcomes; decision-making efficiency; amenities and convenience; information and emotional support; and overall patient satisfaction. Failure to consider quality from this five-pronged perspective results in a focus on medical outcomes, without considering the processes central to quality from the patient's perspective and vital to achieving good outcomes. In this paper, we argue for applying the concept of fair process in clinical settings. Fair process involves using a collaborative approach to exploring diagnostic issues and treatments with patients, explaining the rationale for decisions, setting expectations about roles and responsibilities, and implementing a core plan and ongoing evaluation. Fair process opens the door to bringing patient expertise into the clinical setting and the work of developing health care goals and strategies. This paper provides a step by step illustration of an innovative visual approach, called photovoice or photo-elicitation, to achieve fair process in clinical work with acquired brain injury survivors and others living with chronic health conditions. Applying this visual tool and methodology in the clinical setting will enhance patient-provider communication; engage patients as partners in identifying challenges, strengths, goals, and strategies; and support evaluation of progress over time. Asking patients to bring visuals of their lives into the clinical interaction can help to illuminate gaps in clinical knowledge, forge better therapeutic relationships with patients living with chronic conditions such as brain injury, and identify patient-centered goals and possibilities for healing. The process illustrated here can be used by clinicians, (primary care physicians, rehabilitation therapists, neurologists, neuropsychologists, psychologists, and others) working with people living with chronic conditions such as acquired brain injury, mental illness, physical disabilities, HIV/AIDS, substance abuse, or post-traumatic stress, and by leaders of support groups for the types of patients described above and their family members or caregivers.

This paper illustrates an innovative visual approach (photovoice or photo-elicitation) to achieve fair process in clinical care for patients living with chronic health conditions, illuminate gaps in clinical knowledge, forge better therapeutic relationships, and identify patient-centered goals and possibilities for healing.

利用视觉和叙事方法，以实现公平的进程中，在临床护理

The Institute of Medicine has targeted patient-centeredness as an important area of quality improvement. A major dimension of patient-centeredness is ...

科研

医学

The &alpha;-test: Rapid Cell-free CD4 Enumeration Using Whole Saliva

There is an urgent need for affordable CD4 enumeration to monitor HIV disease. CD4 enumeration is out of reach in resource-limited regions due to the time and temperature restrictions, technical sophistication, and cost of reagents, in particular monoclonal antibodies to measure CD4 on blood cells, the only currently acceptable method. A commonly used cost-saving and time-saving laboratory strategy is to calculate, rather than measure certain blood values. For example, LDL levels are calculated using the measured levels of total cholesterol, HDL, and triglycerides1. Thus, identification of cell-free correlates that directly regulate the number of CD4+ T cells could provide an accurate method for calculating CD4 counts due to the physiological relevance of the correlates.
The number of stem cells that enter blood and are destined to become circulating CD4+ T cells is determined by the chemokine CXCL12 and its receptor CXCR4 due to their influence on locomotion2. The process of stem cell locomotion into blood is additionally regulated by cell surface human leukocyte elastase (HLECS) and the HLECS-reactive active &alpha;1proteinase inhibitor (&alpha;1PI, &alpha;1antitrypsin, SerpinA1)3. In HIV-1 disease, &alpha;1PI is inactivated due to disease processes 4. In the early asymptomatic categories of HIV-1 disease, active &alpha;1PI was found to be below normal in 100% of untreated HIV-1 patients (median=12 &mu;M, and to achieve normal levels during the symptomatic categories4, 5. This pattern has been attributed to immune inactivation, not to insufficient synthesis, proteolytic inactivation, or oxygenation. We observed that in HIV-1 subjects with &gt;220 CD4 cells/&mu;l, CD4 counts were correlated with serum levels of active &alpha;1PI (r2=0.93, p&lt;0.0001, n=26) and inactive &alpha;1PI (r2=0.91, p&lt;0.0001, n=26) 5. Administration of &alpha;1PI to HIV-1 infected and uninfected subjects resulted in dramatic increases in CD4 counts suggesting &alpha;1PI participates in regulating the number of CD4+ T cells in blood 3.
With stimulation, whole saliva contains sufficient serous exudate (plasma containing proteinaceous material that passes through blood vessel walls into saliva) to allow measurement of active &alpha;1PI and the correlation of this measurement is evidence that it is an accurate method for calculating CD4 counts. Briefly, sialogogues such as chewing gum or citric acid stimulate the exudation of serum into whole mouth saliva. After stimulating serum exudation, the activity of serum &alpha;1PI in saliva is measured by its capacity to inhibit elastase activity. Porcine pancreatic elastase (PPE) is a readily available inexpensive source of elastase. PPE binds to &alpha;1PI forming a one-to-one complex that prevents PPE from cleaving its specific substrates, one of which is the colorimetric peptide, succinyl-L-Ala-L-Ala-L-Ala-p-nitroanilide (SA3NA). Incubating saliva with a saturating concentration of PPE for 10 min at room temperature allows the binding of PPE to all the active &alpha;1PI in saliva. The resulting inhibition of PPE by active &alpha;1PI can be measured by adding the PPE substrate SA3NA. (Figure 1). Although CD4 counts are measured in terms of blood volume (CD4 cells/&mu;l), the concentration of &alpha;1PI in saliva is related to the concentration of serum in saliva, not to volume of saliva since volume can vary considerably during the day and person to person6. However, virtually all the protein in saliva is due to serum content, and the protein content of saliva is measurable7. Thus, active &alpha;1PI in saliva is calculated as a ratio to saliva protein content and is termed the &alpha;1PI Index. Results presented herein demonstrate that the &alpha;1PI Index provides an accurate and precise physiologic method for calculating CD4 counts.

The &amp;#945;-test: Rapid Cell-free CD4 Enumeration Using Whole Saliva

A CD4 enumeration method, the &#x03B1;-test, is described which uses whole saliva to provide rapid and accurate CD4 counts. The &alpha;-test costs pennies and eliminates the need for technical training, costly reagents such as monoclonal antibodies, instrumentation, refrigeration, transport of samples, as well as collection and handling of blood.

测试：α-细胞快速免费的CD4计数，使用全唾液

There is an urgent need for affordable CD4 enumeration to monitor HIV disease. CD4 enumeration is out of reach in resource-limited regions due to the time ...

Collecting Saliva and Measuring Salivary Cortisol and Alpha-amylase in Frail Community Residing Older Adults via Family Caregivers

Salivary measures have emerged in bio-behavioral research that are easy-to-collect, minimally invasive, and relatively inexpensive biologic markers of stress. This article we present the steps for collection and analysis of two salivary assays in research with frail, community residing older adults-salivary cortisol and salivary alpha amylase. The field of salivary bioscience is rapidly advancing and the purpose of this presentation is to provide an update on the developments for investigators interested in integrating these measures into research on aging. Strategies are presented for instructing family caregivers in collecting saliva in the home, and for conducting laboratory analyses of salivary analytes that have demonstrated feasibility, high compliance, and yield quality specimens. The protocol for sample collection includes: (1) consistent use of collection materials; (2) standardized methods that promote adherence and minimize subject burden; and (3) procedures for controlling certain confounding agents. We also provide strategies for laboratory analyses include: (1) saliva handling and processing; (2) salivary cortisol and salivary alpha amylase assay procedures; and (3) analytic considerations.

We demonstrate: (1) procedures for collection of salivary samples in cognitive impaired older adults by family caregivers in the home setting, (2) procedures for measuring stress activity via salivary cortisol and alpha amylase, and (3) representative profiles. Protocols that allow researchers to study stress-linked processes advance our understanding of biological sensitivity and susceptibility.

Salivary measures have emerged in bio-behavioral research  that are easy-to-collect, minimally invasive, and relatively inexpensive  biologic markers of ...

Quantitative Mass Spectrometric Profiling of Cancer-cell Proteomes Derived From Liquid and Solid Tumors

In-depth analyses of cancer cell proteomes are needed to elucidate oncogenic pathomechanisms, as well as to identify potential drug targets and diagnostic biomarkers. However, methods for quantitative proteomic characterization of patient-derived tumors and in particular their cellular subpopulations are largely lacking. Here we describe an experimental set-up that allows quantitative analysis of proteomes of cancer cell subpopulations derived from either liquid or solid tumors. This is achieved by combining cellular enrichment strategies with quantitative Super-SILAC-based mass spectrometry followed by bioinformatic data analysis. To enrich specific cellular subsets, liquid tumors are first immunophenotyped by flow cytometry followed by FACS-sorting; for solid tumors, laser-capture microdissection is used to purify specific cellular subpopulations. In a second step, proteins are extracted from the purified cells and subsequently combined with a tumor-specific, SILAC-labeled spike-in standard that enables protein quantification. The resulting protein mixture is subjected to either gel electrophoresis or Filter Aided Sample Preparation (FASP) followed by tryptic digestion. Finally, tryptic peptides are analyzed using a hybrid quadrupole-orbitrap mass spectrometer, and the data obtained are processed with bioinformatic software suites including MaxQuant. By means of the workflow presented here, up to 8,000 proteins can be identified and quantified in patient-derived samples, and the resulting protein expression profiles can be compared among patients to identify diagnostic proteomic signatures or potential drug targets.

In-depth analyses of cancer cell proteomes facilitate identification of novel drug targets and diagnostic biomarkers. We describe an experimental workflow for quantitative analysis of (phospho-)proteomes in cancer cell subpopulations derived from liquid and solid tumors. This is achieved by combining cellular enrichment strategies with quantitative Super-SILAC-based mass spectrometry.

对源自液体和固体肿瘤癌症细胞定量蛋白质组质谱剖析

In-depth analyses of cancer cell proteomes are needed to elucidate oncogenic pathomechanisms, as well as to identify potential drug targets and diagnostic ...

Pre-clinical Orthotopic Murine Model of Human Prostate Cancer

To study the multifaceted biology of prostate cancer, pre-clinical in vivo models offer a range of options to uncover critical biological information about this disease. The human orthotopic prostate cancer xenograft mouse model provides a useful alternative approach for understanding the specific interactions between genetically and molecularly altered tumor cells, their organ microenvironment, and for evaluation of efficacy of therapeutic regimens. This is a well characterized model designed to study the molecular events of primary tumor development and it recapitulates the early events in the metastatic cascade prior to embolism and entry of tumor cells into the circulation. Thus it allows elucidation of molecular mechanisms underlying the initial phase of metastatic disease. In addition, this model can annotate drug targets of clinical relevance and is a valuable tool to study prostate cancer progression. In this manuscript we describe a detailed procedure to establish a human orthotopic prostate cancer xenograft mouse model.

Prostate cancer is the second most common cause of cancer-related deaths in the United States. An orthotopic cancer model provides a useful approach to understand the biology of prostate cancer and to evaluate the efficacy of therapeutic regimens. This protocol describes detailed steps necessary to establish an orthotopic prostate cancer mouse model.

人前列腺癌的临床前原位小鼠模型

To study the multifaceted biology of prostate cancer, pre-clinical in vivo models offer a range of options to uncover critical biological information ...

A Detailed Protocol for Perspiration Monitoring Using a Novel, Small, Wireless Device

Perspiration monitoring can be utilized for the detection of certain diseases, such as thermoregulation and mental disorders, particularly when the patients are unaware of such disorders or are having difficulty expressing their symptoms. Until now, several devices for perspiration monitoring have been developed; however, such devices tend to have a relatively large exterior, considerable power consumption, and/or less sensitivity.
Recently, we developed a small, wireless device for perspiration monitoring. The device consists of a temperature/relative humidity (T/RH) sensor, battery-driven small data logger, and silica gel as a desiccant in a small cylindrical exterior. The T/RH sensor is placed between the detection windows (through which the water vapor from the skin enters) and the silica gel. The underlying principle of the perspiration monitoring device is based on Fick&#39;s law of diffusion, which means that water vapor flux from the skin to the silica gel (i.e.&#160;transepidermal water loss and perspiration) can be captured by change in humidity at the T/RH sensor. In addition, a baseline subtraction method was adopted to distinguish perspiration and transepidermal water loss.
As shown in the previous report, the developed device can monitor the perspiration at any sites of the body in an easy, wireless manner. However, detailed methods of how to use the device have not been disclosed yet. In this article, therefore, we would like to show the point-by-point tutorials of how to use the device for perspiration monitoring, by showing the sympathetic activity test with the sympathetic skin response monitoring as an example.

Recently, we developed a small wireless device for perspiration monitoring. In this article, we present detailed protocols on how to use the device for perspiration monitoring with an example of the sympathetic activity test.

详细的汗渍监控协议使用一种新的，小的，无线设备

Perspiration monitoring can be utilized for the detection of certain diseases, such as thermoregulation and mental disorders, particularly when the ...

A Novel Clinical Grade Isolation Method for Human Kidney Perivascular Stromal Cells

Mesenchymal Stromal Cells (MSCs) are tissue homeostatic and immune modulatory cells that have shown beneficial effects in kidney diseases and transplantation. Perivascular Stromal Cells (PSCs) share characteristics with bone marrow MSCs (bmMSCs). However, they also possess, most likely due to local imprinting, tissue-specific properties and play a role in local tissue homeostasis. This tissue specificity may result in tissue specific repair, also within the human kidney. We previously showed that human kidney PSCs (kPSCs) have enhanced kidney epithelial wound healing whereas bmMSCs did not have this potential. Moreover, kPSCs can ameliorate kidney injury in vivo. Therefore, kPSCs constitute an interesting source for cell therapy, particularly for kidney diseases and renal transplantation. Here we show the detailed isolation and culture method for kPSCs from transplant-grade human kidneys based on whole-organ perfusion of digestive enzymes via the renal artery and enrichment for the perivascular marker NG2. In this way, large cell quantities can be obtained that are suitable for cellular therapy.

Here we present a novel clinical grade isolation and culture method for kidney Perivascular Stromal Cells (kPSCs) based on whole organ perfusion with digestive enzymes and NG2-cell enrichment. With this method, it is possible to acquire sufficient cell numbers for cellular therapy.

人类肾脏血管周围间质细胞新型临床分级分离方法

Mesenchymal Stromal Cells (MSCs) are tissue homeostatic and immune modulatory cells that have shown beneficial effects in kidney diseases and ...

In Vitro and In Vivo Detection of Mitophagy in Human Cells, C. Elegans, and Mice

Mitochondria are the powerhouses of cells and produce cellular energy in the form of ATP. Mitochondrial dysfunction contributes to biological aging and a wide variety of disorders including metabolic diseases, premature aging syndromes, and neurodegenerative diseases such as Alzheimer's disease (AD) and Parkinson's disease (PD). Maintenance of mitochondrial health depends on mitochondrial biogenesis and the efficient clearance of dysfunctional mitochondria through mitophagy. Experimental methods to accurately detect autophagy/mitophagy, especially in animal models, have been challenging to develop. Recent progress towards the understanding of the molecular mechanisms of mitophagy has enabled the development of novel mitophagy detection techniques. Here, we introduce several versatile techniques to monitor mitophagy in human cells, Caenorhabditis elegans (e.g., Rosella and DCT-1/ LGG-1 strains), and mice (mt-Keima). A combination of these mitophagy detection techniques, including cross-species evaluation, will improve the accuracy of mitophagy measurements and lead to a better understanding of the role of mitophagy in health and disease.

In Vitro and In Vivo Detection of Mitophagy in Human Cells, C. Elegans, and Mice

Mitophagy, the process of clearing damaged mitochondria, is necessary for mitochondrial homeostasis and health maintenance. This article presents some of the latest mitophagy detection methods in human cells, Caenorhabditis elegans, and mice.

体外和体内检测人类细胞中的 Mitophagy,线虫和小鼠

Mitochondria are the powerhouses of cells and produce cellular energy in the form of ATP. Mitochondrial dysfunction contributes to biological aging and a ...

Surgical Training for the Implantation of Neocortical Microelectrode Arrays Using a Formaldehyde-fixed Human Cadaver Model

This protocol describes a procedure to assist surgeons in training for the implantation of microelectrode arrays into the neocortex of the human brain. Recent technological progress has enabled the fabrication of microelectrode arrays that allow recording the activity of multiple individual neurons in the neocortex of the human brain. These arrays have the potential to bring unique insight onto the neuronal correlates of cerebral function in health and disease. Furthermore, the identification and decoding of volitional neuronal activity opens the possibility to establish brain-computer interfaces, and thus might help restore lost neurological functions. The implantation of neocortical microelectrode arrays is an invasive procedure requiring a supra-centimetric craniotomy and the exposure of the cortical surface; thus, the procedure must be performed by an adequately trained neurosurgeon. In order to provide an opportunity for surgical training, we designed a procedure based on a human cadaver model. The use of a formaldehyde-fixed human cadaver bypasses the practical, ethical and financial difficulties of surgical practice on animals (especially non-human primates) while preserving the macroscopic structure of the head, skull, meninges and cerebral surface and allowing realistic, operating room-like positioning and instrumentation. Furthermore, the use of a human cadaver is closer to clinical daily practice than any non-human model. The major drawbacks of the cadaveric simulation are the absence of cerebral pulsation and of blood and cerebrospinal fluid circulation. We suggest that a formaldehyde-fixed human cadaver model is an adequate, practical and cost-effective approach to ensure proper surgical training before implanting microelectrode arrays in the living human neocortex.

We designed a procedure in which a formaldehyde-fixed human cadaver is used to assist neurosurgeons in training for the implantation of microelectrode arrays into the neocortex of the human brain.

应用甲醛固定人尸体模型植入皮层微电极阵列的外科训练

This protocol describes a procedure to assist surgeons in training for the implantation of microelectrode arrays into the neocortex of the human brain. ...

Sampling Strategies and Processing of Biobank Tissue Samples from Porcine Biomedical Models

In translational medical research, porcine models have steadily become more popular. Considering the high value of individual animals, particularly of genetically modified pig models, and the often-limited number of available animals of these models, establishment of (biobank) collections of adequately processed tissue samples suited for a broad spectrum of subsequent analyses methods, including analyses not specified at the time point of sampling, represent meaningful approaches to take full advantage of the translational value of the model. With respect to the peculiarities of porcine anatomy, comprehensive guidelines have recently been established for standardized generation of representative, high-quality samples from different porcine organs and tissues. These guidelines are essential prerequisites for the reproducibility of results and their comparability between different studies and investigators. The recording of basic data, such as organ weights and volumes, the determination of the sampling locations and of the numbers of tissue samples to be generated, as well as their orientation, size, processing and trimming directions, are relevant factors determining the generalizability and usability of the specimen for molecular, qualitative, and quantitative morphological analyses. Here, an illustrative, practical, step-by-step demonstration of the most important techniques for generation of representative, multi-purpose biobank specimen from porcine tissues is presented. The methods described here include determination of organ/tissue volumes and densities, the application of a volume-weighted systematic random sampling procedure for parenchymal organs by point-counting, determination of the extent of tissue shrinkage related to histological embedding of samples, and generation of randomly oriented samples for quantitative stereological analyses, such as isotropic uniform random (IUR) sections generated by the &#34;Orientator&#34; and &#34;Isector&#34; methods, and vertical uniform random (VUR) sections.

The practical application and performance of methods for generation of representative tissue samples of porcine animal models for a broad spectrum of downstream analyses in biobank projects are demonstrated, including volumetry, systematic random sampling, and differential processing of tissue samples for qualitative and quantitative morphologic and molecular analyses types.

猪生物医学模型生物库组织样品的取样策略与处理

In translational medical research, porcine models have steadily become more popular. Considering the high value of individual animals, particularly of ...