(1) पूरे खंड के आभासी स्लाइस पर कब्जा, (2) बड़े पैमाने पर डेटा के मास विश्लेषण, (3) 2 डी आभासी स्लाइस के पुनर्निर्माण: उपन्यास बड़े पैमाने पर और immunohistochemically दाग अग्नाशय के नमूनों की खरीद विश्लेषण के कंप्यूटर की सहायता तरीकों में वर्णित हैं 3D आइलेट मानचित्रण (4), और (5) गणितीय विश्लेषण.
The pancreatic islet is a unique micro-organ composed of several hormone secreting endocrine cells such as beta-cells (insulin), alpha-cells (glucagon), and delta-cells (somatostatin) that are embedded in the exocrine tissues and comprise 1-2% of the entire pancreas. There is a close correlation between body and pancreas weight. Total beta-cell mass also increases proportionately to compensate for the demand for insulin in the body. What escapes this proportionate expansion is the size distribution of islets. Large animals such as humans share similar islet size distributions with mice, suggesting that this micro-organ has a certain size limit to be functional. The inability of large animal pancreata to generate proportionately larger islets is compensated for by an increase in the number of islets and by an increase in the proportion of larger islets in their overall islet size distribution. Furthermore, islets exhibit a striking plasticity in cellular composition and architecture among different species and also within the same species under various pathophysiological conditions. In the present study, we describe novel approaches for the analysis of biological image data in order to facilitate the automation of analytic processes, which allow for the analysis of large and heterogeneous data collections in the study of such dynamic biological processes and complex structures. Such studies have been hampered due to technical difficulties of unbiased sampling and generating large-scale data sets to precisely capture the complexity of biological processes of islet biology. Here we show methods to collect unbiased “representative” data within the limited availability of samples (or to minimize the sample collection) and the standard experimental settings, and to precisely analyze the complex three-dimensional structure of the islet. Computer-assisted automation allows for the collection and analysis of large-scale data sets and also assures unbiased interpretation of the data. Furthermore, the precise quantification of islet size distribution and spatial coordinates (i.e. X, Y, Z-positions) not only leads to an accurate visualization of pancreatic islet structure and composition, but also allows us to identify patterns during development and adaptation to altering conditions through mathematical modeling. The methods developed in this study are applicable to studies of many other systems and organisms as well.
कंप्यूटर की मदद से बड़े पैमाने पर दृश्य और मात्रा का ठहराव यहाँ प्रस्तुत अग्नाशय आइलेट अध्ययन में चार महत्वपूर्ण बिंदुओं को वहन: (1) अग्नाशय के नमूनों की बड़े पैमाने पर विश्लेषण समग्र आइलेट आकार के वित?…
The authors have nothing to disclose.
अध्ययन के द्वारा समर्थित है अमेरिका के सार्वजनिक स्वास्थ्य सेवा डी.के.-081,527 अनुदान, डी.के. – ०,७२,४७३ और शिकागो मधुमेह अनुसंधान और प्रशिक्षण केन्द्र (पशु मॉडल कोर) के विश्वविद्यालय, और Kovler परिवार फाउंडेशन से एक उपहार के लिए डी.के.-+२०,५९५.
Material Name | Type | Company | Catalogue Number | Comment |
---|---|---|---|---|
Fluorescent microscope | Microscope | Olympus | IX-81 | |
Stereo Investigator | Program | MicroBrightField | ||
MIP-GFP mice | Mice | Jackson Laboratory | ||
Mathematica | Program | Wolfram | ||
Image J | Program | NIH | ||
Slidebook | Program | Olympus |