The development of the presented EHR was supported over the last 20 years by internal research funding and public funding from different institutions and foundations.

<ol>
	<li>Halleck, F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Integrated+care+of+renal+transplant+patients+-+Development+of+an+electronic+health+care+service+platform.">Integrated care of renal transplant patients - Development of an electronic health care service platform.</a> Dialyse aktuell. 20 (06), 285-290 (2016).</li><li>Sonntag, D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Clinical+Data+Intelligence+Project.">The Clinical Data Intelligence Project.</a> Informatik-Spektrum. 39 (4), 290-300 (2016).</li><li>Kara, E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+Domain-adapted+Dependency+Parser+for+German+Clinical+Text.">A Domain-adapted Dependency Parser for German Clinical Text.</a> Proceedings of the 14th Conference on Natural Language Processing. , (2018).</li><li>Maier, C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Experiences+of+Transforming+a+Complex+Nephrologic+Care+and+Research+Database+into+i2b2+Using+the+IDRT+Tools.">Experiences of Transforming a Complex Nephrologic Care and Research Database into i2b2 Using the IDRT Tools.</a> Journal of Healthcare Engineering. 2019, 5640685 (2019).</li><li>Jensen, P. B., Jensen, L. J., Brunak, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mining+electronic+health+records:+towards+better+research+applications+and+clinical+care.">Mining electronic health records: towards better research applications and clinical care.</a> Nature Reviews Genetics. 13 (6), 395-405 (2012).</li><li>Schmidt, D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+novel+tool+for+the+identification+of+correlations+in+medical+data+by+faceted+search.">A novel tool for the identification of correlations in medical data by faceted search.</a> Computers in Biology and Medicine. 85, 98-105 (2017).</li><li>Veit, K., Wessels, M., Deiters, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Gesundheitsdaten+und+Digitalisierung+-+Neue+Anforderungen+an+den+Umgang+mit+Daten+im+Gesundheitswesen.">Gesundheitsdaten und Digitalisierung - Neue Anforderungen an den Umgang mit Daten im Gesundheitswesen.</a> Digitale Transformation von Dienstleistungen im Gesundheitswesen VI: Impulse f&#252;r die Forschung. , 19-33 (2019).</li><li>Ehrler, F., Geissbuhler, A., Jimeno, A., Ruch, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Data-poor+categorization+and+passage+retrieval+for+gene+ontology+annotation+in+Swiss-Prot.">Data-poor categorization and passage retrieval for gene ontology annotation in Swiss-Prot.</a> BMC Bioinformatics. 6, 23 (2005).</li><li>Esteban, C., Schmidt, D., Krompa&#223;, D., Tresp, V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Predicting+Sequences+of+Clinical+Events+by+Using+a+Personalized+Temporal+Latent+Embedding+Model.">Predicting Sequences of Clinical Events by Using a Personalized Temporal Latent Embedding Model.</a> 2015 International Conference on Healthcare Informatics. , 130-139 (2015).</li><li>Roller, R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Detecting+Named+Entities+and+Relations+in+German+Clinical+Reports.">Detecting Named Entities and Relations in German Clinical Reports.</a> Language Technologies for the Challenges of the Digital Age. , 146-154 (2018).</li><li>Roller, R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+fine-grained+corpus+annotation+schema+of+German+nephrology+records.">A fine-grained corpus annotation schema of German nephrology records.</a> Clinical Natural Language Processing Workshop (ClinicalNLP). , (2016).</li><li>Esteban, C., Staeck, O., Baier, S., Yang, Y., Tresp, V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Predicting+Clinical+Events+by+Combining+Static+and+Dynamic+Information+Using+Recurrent+Neural+Networks.">Predicting Clinical Events by Combining Static and Dynamic Information Using Recurrent Neural Networks.</a> IEEE International Conference on Healthcare Informatics (ICHI). , 93-101 (2016).</li><li>Schmidt, D., Niemann, M., Trzebiatowski, G. 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The corresponding authors have nothing to declare.

TBase combines a web-based EHR for specialized outpatient care of KTR with a research database, creating a comprehensive long-term database for patients with kidney disease6,11,15,37. Regarding organizational structure, this is enabled by implementing a modern software design process as an institutional agent and including over 20 years of experience as developers, clinical users and researcher...

Motivation for an integrated electronic health record and research database 
Clinical research is based on the availability of high-quality data, regardless of whether classical statistical methods or Machine Learning (ML) techniques are used for analysis1,2. In addition to routine data (e.g., demographic, laboratory, and medication data), domain-specific data (e.g., transplantation-relevant data) are required with high granularity3,4. However, routine care at many university hospitals is performed with hospital information systems (HIS) that neither allow for systematic collection of research-specific data nor for easy data extraction of routine data5,6,7. As a result, clinical researchers create specific research databases, which have a variety of problems including complex process of setting up a database, manual data entry, data protection issues, and long-term maintenance (Table 1). Limited amount of data, missing data, and inconsistencies are a major problem for clinical research in general and impede the use of ML technologies8,9,10,11,12,13. These standalone research databases are usually focused on certain disease or patient aspects, not connected to other databases, and often discontinued after a certain period, resulting in inaccessible &#34;data silos&#34;. Ultimately, high-quality, long-term data on various disease aspects are sparse. In the era of digital medicine there is an increasing need for a comprehensive electronic health record (EHR)7,14,15, which enables easy documentation of domain-specific data and automated collection of routine data from the systems of inpatient and outpatient care.
These general considerations apply to transplantation medicine as well16. Hence, a complete documentation of the patient&#39;s medical history including all inpatient and outpatient treatments, clinical routine data as well as transplantation-specific data is necessary for successful follow-up care17,18. Since ordinary HIS are static and focused on inpatient treatment, they cannot integrate transplantation-specific data, such as donor data, cold ischemia times, and human leukocyte antigens (HLA) data. However, these data are a basic prerequisite for transplantation research19,20,21,22 as well as from long-term clinical care. While the initial hospital stay usually is only 1-2 weeks and processes as well as early outcomes after kidney transplantation are comparable between many transplant centers, lifelong post-transplant care is complicated and lacks a common structured approach. This motivates an integrated EHR and research database to capture the lifelong post-transplant patient journey.23
In order to integrate these functionalities for routine care and research of KTR, an EHR named &#34;TBase&#34; was developed with the idea that the routine use for post-transplant care will create a unique research database with highest data quality (Table 2).
Design and Architecture 
TBase is based on a typical client-server architecture. For development, the components and tools of SAP High Performance Analytic Appliance extended application advanced (SAP HANA XSA) were used. Based on the latest Hypertext Markup Language 5 (HTML5) web-technologies the EHR has been developed and tested for the Google Chrome Engine. This web engine is used by Chrome and the Microsoft Edge Browser and allows to use the EHR in the most frequently used web browsers24 without the need for local installation. The applied technology enables a responsive web design and allows the web-based EHR to be used on all devices (PC, tablet, smartphone). The innovative high-performance development platform is composed of various components (Web IDE, UI5 and HANA DB) and has enabled us to rapidly implement the EHR project TBase with state-of-the-art software tools (Figure 1).
For the representation of patient data, a simple table structure was implemented for an intuitive and self-explanatory design of the EHR. For example, the patient table with the PatientID as the primary key is at the center of the table structure. Almost all tables (except individual sub-tables) are connected to this central table through PatientID (Figure 2).
Figure 3 shows part of TBase&#39;s table structure and the data types used in greater detail. The end user can access the data fields via graphical user interface (GUI), for which an example is shown in Figure 4.
This EHR contains all current patient data and is used for routine outpatient care. Important routine clinical data (e.g., laboratory data, medical results, radiology, microbiology, virology and pathology data, hospital data, etc.) are directly imported into TBase via standardized interfaces (e.g., on the basis of Health Level Seven (HL7) - a standard for digital communication in the healthcare sector25). Transplant-specific data such as cold ischemia times, donor data, HLA data as well as follow-up notes, vital signs, medical reports and the medication list are entered by the users via GUI into the EHR. Before data are transferred to the database, an automated plausibility check is performed for prompt detection of erroneous data entry providing the option to correct immediately. In addition, data validation takes part during clinical routine in which clinical users routinely write reports and letters to patients and physicians. These letters must provide correct data (e.g., on medication, lab values and clinical remarks) for further treatment and medication plans. As a consequence physicians and patients constantly validate and correct the clinical data in their daily practice, a process resulting in high data quality. If data are entered via application programming interfaces (API) or other interfaces, plausibility checks are performed in the backend similarly to the plausibility checks in the frontend.
Frontend (GUI) 
To implement the frontend, the UI5 Framework is used. This framework provides an extensive library for frontend elements as well as a variety of additional features such as multilingualism and graphical libraries for data visualization. Currently, TBase frontend elements are displayed either in English or German depending on the language setting of the browser.
A master-detail interface is used for the frontend to ensure a simple, intuitive page structure. The upper part of the viewing page consists of individual tabs for the detail pages (basic data, medical data, transplantation data, etc.). This master part remains unchanged regardless of which detail page is shown below (Figure 4). The detail view of each page enables an easy overview on the page topic.
For data manipulation, the EHR has different levels of user rights (&#34;read&#34;, &#34;write&#34;, &#34;delete&#34;, and &#34;administrator&#34;). There is an &#34;edit&#34; level in addition to the &#34;view&#34; level, which can only be activated by users with higher rights than &#34;read&#34;. If the user has the right to write, all input fields for data entry are activated and can be filled with data. Users with &#34;delete&#34; rights can delete data via a corresponding button, but only after confirmation through a pop-up window.
Database structure and interfaces 
The development of TBase is performed in the development database. Extensive and detailed testing of all software changes such as new functionalities is carried out in the quality assurance database. Software updates that pass the quality control checks are transferred to the live system. For research purposes the live system is copied into the replication database, which can be queried via standard Open Database Connectivity (ODBC) interfaces (e.g., via open-source software R Studio). As there is no direct connection between replication and live system the data in the live system are protected from corruption, loss or manipulation of data. This modular structure and the clear separation of the four databases (development, quality assurance, live system and replication database), which are tailored to the specific needs of developers, researchers, and clinicians facilitates maintenance and data protection of sensitive patient data.
The EHR is fully integrated into the Data Infrastructure of Charit&#233; and relies on different interfaces for data import from various data sources. The interface to the HIS imports all relevant data such as administrative data, examinations, medications, laboratory findings and discharge letters. This interface connects both systems via a staging area. Here, all new data (data delta) are transferred from the HIS to TBase in real time. Patients are identified via a patient number or case number and the corresponding data from the HIS is imported (if not already available in TBase).
For outpatients, our laboratory partner provides the laboratory results via HL7 messages. These are deployed to a shared area in the laboratory system and picked up via an HL7 interface and imported into the EHR. For bi-directional communication and data exchange with KTR (via smartphone apps) and home nephrologists, a HL7 Fast Healthcare Interoperability Resource (HL7 FHIR) interface was implemented26. This interface grants interoperability and flexibility for a safe data exchange with other data sources (e.g., Eurotransplant, patient apps) in the future.
User Management and Data Protection 
TBase is based on user management at the application level. Thus, the user can only access the frontend of the application, but not the database itself. As described above, a four-stage authorization concept was chosen, reserving user management for those with administrative rights. Administrators use an &#34;Identity Management Console&#34; application to add new users from the Charit&#233; user pool for the TBase application and to maintain their user rights (Figure 5). Most users can access all patients in the database. However, it is possible to restrict access for specific users such as study monitors to a group of patients.
Using the commercial in-memory database platform a secure database technology that protects data with strategies such as application-level authorization, single sign-on (SSO), MIT-Kerberos protocol and Security Assertion Mark-up Language (SAML) is used. The platform secures communication, data storage, and application services using the latest encryption and testing techniques. All developments on the database are controlled by authorizations. This ensures the security of data by design at a high level. In addition, all data are kept behind the certified Charit&#233; firewall. In compliance with the latest European Union General Data Protection Regulation (EU GDPR) a robust data protection concept was implemented, including data flow diagrams, data protection risk assessment (DSFA) and authorization concept. All documents are laid down in a procedure directory of the Charit&#233; Data Protection Office.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Developer platform SAP Web IDE</td>
			<td>SAP SE</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>GUI Toolbox SAPUI5</td>
			<td>SAP SE</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>In-memory database SAP-HANA</td>
			<td>SAP SE</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Interface Standard HL7</td>
			<td>Health Level Seven International</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Interface Standard HL7 FHIR</td>
			<td>Health Level Seven International</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>RStudio</td>
			<td>RStudio Inc.</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>TBase - Electronic Health Record</td>
			<td>Charit&#233; - Universit&#228;tsmedizin Berlin</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Webserver SAP-HANA XSA</td>
			<td>SAP SE</td>
			<td></td>
			<td></td>
		</tr>
	</tbody>
</table>

tbase - an integrated electronic health record and research database for kidney transplant recipients

TBase is an electronic health record (EHR) for kidney transplant recipients (KTR) combining automated data entry of key clinical data (e.g., laboratory values, medical reports, radiology and pathology data) via standardized interfaces with manual data entry during routine treatment (e.g., clinical notes, medication list, and transplantation data). By this means, a comprehensive database for KTR is created with benefits for routine clinical care and research. It enables both easy everyday clinical use and quick access for research questions with highest data quality. This is achieved by the concept of data validation in clinical routine in which clinical users and patients have to rely on correct data for treatment and medication plans and thereby validate and correct the clinical data in their daily practice. This EHR is tailored for the needs of transplant outpatient care and proved its clinical utility for more than 20 years at Charit&#233; - Universit&#228;tsmedizin Berlin. It facilitates efficient routine work with well-structured, comprehensive long-term data and allows their easy use for clinical research. To this point, its functionality covers automated transmission of routine data via standardized interfaces from different hospital information systems, availability of transplant-specific data, a medication list with an integrated check for drug-drug interactions, and semi-automated generation of medical reports among others. Key elements of the latest reengineering are a robust privacy-by-design concept, modularity, and hence portability into other clinical contexts as well as usability and platform independence enabled by HTML5 (Hypertext Markup Language) based responsive web design. This allows fast and easy scalability into other disease areas and other university hospitals. The comprehensive long-term datasets are the basis for the investigation of Machine Learning algorithms, and the modular structure allows to rapidly implement these into clinical care. Patient reported data and telemedicine services are integrated into TBase in order to meet future needs of the patients. These novel features aim to improve clinical care as well as to create new research options and therapeutic interventions.

TBase was first released in 1999 at Charit&#233; Campus Mitte and is in use ever since. For more than 20 years the TBase-EHR prospectively collects data from all KTR. Starting in 2001, the other transplant programs at Charit&#233; used TBase for the routine care of KTR and wait-listed patients as well. Since 2007, this EHR is in use for routine care of living donors and all patients in the department of nephrology.
By providing the TBase software with its functionalities, which has been furthe...

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TBase - an Integrated Electronic Health Record and Research Database for Kidney Transplant Recipients

TBase combines an electronic health record with an innovative research database for kidney transplant recipients. TBase is built upon an in-memory database platform, connected to different hospital systems, and used for regular outpatient care. It automatically integrates all relevant clinical data including transplantation-specific data creating a unique research database.

TBase is an electronic health record (EHR) for kidney transplant recipients (KTR) combining automated data entry of key clinical data (e.g., laboratory ...

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4.3K 조회수.  Charité - Universitätsmedizin Berlin. TBase combines an electronic health record with an innovative research database for kidney transplant recipients. TBase is built upon an in-memory database platform, connected to different hospital systems, and used for regular outpatient care. It automatically integrates all relevant clinical data including transplantation-specific data creating a unique research database.

비디오: TBase - an Integrated Electronic Health Record and Research Database for Kidney Transplant Recipients

A Method for Murine Islet Isolation and Subcapsular Kidney Transplantation

Since the early pioneering work of Ballinger and Reckard demonstrating that transplantation of islets of Langerhans into diabetic rodents could normalize their blood glucose levels, islet transplantation has been proposed to be a potential treatment for type 1 diabetes 1,2. More recently, advances in human islet transplantation have further strengthened this view 1,3. However, two major limitations prevent islet transplantation from being a widespread clinical reality: (a) the requirement for large numbers of islets per patient, which severely reduces the number of potential recipients, and (b) the need for heavy immunosuppression, which significantly affects the pediatric population of patients due to their vulnerability to long-term immunosuppression. Strategies that can overcome these limitations have the potential to enhance the therapeutic utility of islet transplantation.
Islet transplantation under the mouse kidney capsule is a widely accepted model to investigate various strategies to improve islet transplantation. This experiment requires the isolation of high quality islets and implantation of islets to the diabetic recipients. Both procedures require surgical steps that can be better demonstrated by video than by text. Here, we document the detailed steps for these procedures by both video and written protocol. We also briefly discuss different transplantation models: syngeneic, allogeneic, syngeneic autoimmune, and allogeneic autoimmune.

Transplantation of isolated islets has been proposed to be a potential treatment for type 1 diabetes. Here we describe a method to isolate islets from mouse pancreata and transplant them to the subcapsular space of the kidney.

Murine 아일릿 절연 및 Subcapsular 신장 이식을위한 방법

Since the early pioneering work of Ballinger and Reckard demonstrating that transplantation of islets of Langerhans into diabetic rodents could normalize ...

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의학

Generation of Comprehensive Thoracic Oncology Database - Tool for Translational Research

The Thoracic Oncology Program Database Project was created to serve as a comprehensive, verified, and accessible repository for well-annotated cancer specimens and clinical data to be available to researchers within the Thoracic Oncology Research Program. This database also captures a large volume of genomic and proteomic data obtained from various tumor tissue studies. A team of clinical and basic science researchers, a biostatistician, and a bioinformatics expert was convened to design the database. Variables of interest were clearly defined and their descriptions were written within a standard operating manual to ensure consistency of data annotation. Using a protocol for prospective tissue banking and another protocol for retrospective banking, tumor and normal tissue samples from patients consented to these protocols were collected. Clinical information such as demographics, cancer characterization, and treatment plans for these patients were abstracted and entered into an Access database. Proteomic and genomic data have been included in the database and have been linked to clinical information for patients described within the database. The data from each table were linked using the relationships function in Microsoft Access to allow the database manager to connect clinical and laboratory information during a query. The queried data can then be exported for statistical analysis and hypothesis generation.

A thoracic oncology database was developed to serve as a comprehensive repository for clinical and laboratory data for the purposes of translational research. The database will serve translational cancer researchers within the Thoracic Oncology Research Program. This database is adaptable to other cancer models, as well as other human diseases.

종합 흉부 종양학 데이터베이스의 생성 - Translational 연구 도구

The Thoracic Oncology Program Database Project was created to serve as a comprehensive, verified, and accessible repository for well-annotated cancer ...

A Modified Heterotopic Swine Hind Limb Transplant Model for Translational Vascularized Composite Allotransplantation (VCA) Research

Vascularized Composite Allotransplantation (VCA) such as hand and face transplants represent a viable treatment option for complex musculoskeletal trauma and devastating tissue loss. Despite favorable and highly encouraging early and intermediate functional outcomes, rejection of the highly immunogenic skin component of a VCA and potential adverse effects of chronic multi-drug immunosuppression continue to hamper widespread clinical application of VCA. Therefore, research in this novel field needs to focus on translational studies related to unique immunologic features of VCA and to develop novel immunomodulatory strategies for immunomodulation and tolerance induction following VCA without the need for long term immunosuppression.
This article describes a reliable and reproducible translational large animal model of VCA that is comprised of an osteomyocutaneous flap in a MHC-defined swine heterotopic hind limb allotransplantation. Briefly, a well-vascularized skin paddle is identified in the anteromedial thigh region using near infrared laser angiography. The underlying muscles, knee joint, distal femur, and proximal tibia are harvested on a femoral vascular pedicle. This allograft can be considered both a VCA and a vascularized bone marrow transplant with its unique immune privileged features. The graft is transplanted to a subcutaneous abdominal pocket in the recipient animal with a skin component exteriorized to the dorsolateral region for immune monitoring.
Three surgical teams work simultaneously in a well-coordinated manner to reduce anesthesia and ischemia times, thereby improving efficiency of this model and reducing potential confounders in experimental protocols. This model serves as the groundwork for future therapeutic strategies aimed at reducing and potentially eliminating the need for chronic multi-drug immunosuppression in VCA.

A Modified Heterotopic Swine Hind Limb Transplant Model for Translational Vascularized Composite Allotransplantation VCA Research

Vascularized Composite Allotransplantations (VCA) have become a clinical reality. However, broad clinical application of VCA is limited by chronic multi-drug immunosuppression. The authors present a reliable and reproducible large animal model to translate novel immunomodulatory strategies that can minimize or potentially eliminate the need of immunosuppression in VCA.

번역 상 혈관을 조성한 복합 동종 이식 (VCA) 연구를위한 수정 된 이소성 돼지 뒷다리 이식 모델

Vascularized Composite Allotransplantation (VCA) such as hand and face transplants represent a viable treatment option for complex musculoskeletal trauma ...

Murine Heterotopic Heart Transplant Technique

It is now over forty years since this technique was first reported by Corry, Wynn and Russell. Although it took some years for other labs to become proficient in and utilize this technique, it is now widely used by many laboratories around the world. A significant refinement to the original technique was developed and reported in 2001 by Niimi. Described here are the techniques that have evolved over more than a decade in the hands of three surgeons (Plenter, Grazia, Pietra) in our center. These techniques are now being passed on to a younger generation of surgeons and researchers.
Based largely on the Niimi experience, the procedures used have evolved in the fine details - details which we will endeavor to relate here in such a way that others may be able to use this very useful model. Like Niimi, we have found that a video aid to learning is a priceless resource for the beginner.

The manuscript describes the steps required to perform the heterotopic heart transplant in the mouse.

쥐 이소성 심장 이식 기술

It is now over forty years since this technique was first reported by Corry, Wynn and Russell. Although it took some years for other labs to become ...

Murine Kidney Transplant Technique

The first mouse kidney transplant technique was published in 19731 by the Russell laboratory. Although it took some years for other labs to become proficient in and utilize this technique, it is now widely used by many laboratories around the world. A significant refinement to the original technique using the donor aorta to form the arterial anastomosis instead of the renal artery was developed and reported in 1993 by Kalina and Mottram 2 with a further advancement coming from the same laboratory in 1999 3. While one can become proficient in this model, a search of the literature reveals that many labs still experience a high proportion of graft loss due to arterial thrombosis. We describe here a technique that was devised in our laboratory that vastly reduces the arterial thrombus reported by others 4,5. This is achieved by forming a heel-and-toe cuff of the donor infra-renal aorta that facilitates a larger anastomosis and straighter blood flow into the kidney.

The goal of this manuscript is to describe the steps required to perform a kidney transplant in a mouse, paying particular attention to the details of the arterial anastomosis.

쥐 신장 이식 기술

The first mouse kidney transplant technique was published in 19731 by the Russell laboratory. Although it took some years for other labs to become ...

Normothermic Ex Vivo Kidney Perfusion for the Preservation of Kidney Grafts prior to Transplantation

Kidney transplantation has become a well-established treatment option for patients with end-stage renal failure. The persisting organ shortage remains a serious problem. Therefore, the acceptance criteria for organ donors have been extended leading to the usage of marginal kidney grafts. These marginal organs tolerate cold storage poorly resulting in increased preservation injury and higher rates of delayed graft function. To overcome the limitations of cold storage, extensive research is focused on alternative normothermic preservation methods.
Ex vivo normothermic organ perfusion is an innovative preservation technique. The first experimental and clinical trials for ex vivo lung, liver, and kidney perfusions demonstrated favorable outcomes.
In addition to the reduction of cold ischemic injury, the method of normothermic kidney storage offers the opportunity for organ assessment and repair. This manuscript provides information about kidney retrieval, organ preservation techniques, and isolated ex vivo normothermic kidney perfusion (NEVKP) in a porcine model. Surgical techniques, set up for the perfusion solution and the circuit, potential assessment options, and representative results are demonstrated.

Normothermic Ex Vivo Kidney Perfusion for the Preservation of Kidney Grafts prior to Transplantation

The severe organ shortage has resulted in increased use of marginal kidney grafts for transplantation. This has triggered interest in alternative storage methods, since marginal grafts especially tolerate cold storage poorly. The technique of normothermic ex vivo kidney perfusion (NEVKP) represents a novel preservation method for kidney grafts prior to &#160;transplantation.

정상 체온<em&gt; 전의 VIVO</em&gt; 신장의 보존을위한 신장 관류는 이식 전에 이식

Kidney transplantation has become a well-established treatment option for patients with end-stage renal failure. The persisting organ shortage remains a ...

An &#8220;All-laser&#8221; Endothelial Transplant

The &#8220;all laser&#8221; assisted endothelial keratoplasty is a procedure that is performed with a femtosecond laser used to cut the donor tissue at an intended depth, and a near infrared diode laser to weld the corneal tissue. The proposed technique enables to reach the three main goals in endothelial keratoplasty: a precise control in the thickness of the donor tissue; its easy insertion in the recipient bed and a reduced risk of donor lenticule dislocation. The donor cornea thickness is measured in the surgery room with optical coherence tomography (OCT), in order to correctly design the donor tissue dimensions. A femtosecond laser is used to cut the donor cornea. The recipient eye is prepared by manual stripping of the descemetic membrane. The donor endothelium is inserted into a Busin-injector, the peripheral inner side is stained with a proper chromophore (a water solution of Indocyanine Green) and then it is pulled in the anterior chamber. The transplanted tissue is placed in the final and correct location and then diode laser welding is induced from outside the eyeball. The procedure has been performed on more than 15 patients evidencing an improvement in surgery performances, with a good recovery of visual acuity and a reduced donor lenticule dislocation event.

An &amp;#8220;All-laser&amp;#8221; Endothelial Transplant

An all laser procedure is proposed in the endothelial transplant. The surgical technique is based on the use of a femtosecond laser to prepare the donor tissue. Laser welding technique is then used to secure the donor endothelium in the correct position.

&quot;모든 레이저&quot;내피 세포 이식

The &#8220;all laser&#8221; assisted endothelial keratoplasty is a procedure that is performed with a femtosecond laser used to cut the donor tissue at an ...

Use of an Integrated Low-Flow Anesthetic Vaporizer, Ventilator, and Physiological Monitoring System for Rodents

Low-flow digital vaporizers commonly utilize a syringe pump to directly administer volatile anesthetics into a stream of carrier gas. Per animal welfare recommendations, animals are warmed and monitored during procedures requiring anesthesia. Common anesthesia and physiological monitoring equipment include gas tanks, anesthetic vaporizers and stands, warming controllers and pads, mechanical ventilators, and pulse oximeters. A computer is also necessary for data collection and to run equipment software. In smaller spaces or when performing field work, it can be challenging to configure all this equipment in limited space.
The goal of this protocol is to demonstrate best practices for use of a low-flow digital vaporizer using both compressed oxygen and room air, along with an integrated mechanical ventilator, pulse oximeter, and far infrared warming as an all-inclusive anesthesia and physiological monitoring suite ideal for rodents.

Here, we present a protocol to safely and effectively administer anesthetic gas to mice using a digital, low flow anesthesia system with integrated ventilator and physiological monitoring modules.

설치류를 위한 통합 저유량 마취 기화기, 인공호흡기 및 생리적 모니터링 시스템 사용

Low-flow digital vaporizers commonly utilize a syringe pump to directly administer volatile anesthetics into a stream of carrier gas. Per animal welfare ...

Delivery of Exogenous Artificially Synthesized miRNA Mimic to the Kidney Using Polyethylenimine Nanoparticles in Several Kidney Disease Mouse Models

microRNAs&#160;(miRNAs), small noncoding RNAs (21-25 bases) that are not translated into proteins, inhibit lots of target messenger RNAs (mRNAs) by destabilizing and inhibiting their translation in various kidney diseases. Therefore, alternation of miRNA expression by exogenous artificially synthesized miRNA mimics is a potentially useful treatment option for inhibiting the development of many kidney diseases. However, because serum RNAase immediately degrades systematically administered exogenous miRNA mimics in vivo, delivery of miRNA to the kidney remains a challenge. Therefore, vectors that can protect exogenous miRNA mimics from degradation by RNAase and significantly deliver them to the kidney are necessary. Many studies have used viral vectors to deliver exogenous miRNA mimics or inhibitors to the kidney. However, viral vectors may cause an interferon response and/or genetic instability. Therefore, the development of viral vectors is also a hurdle for the clinical use of exogenous miRNA mimics or inhibitors. To overcome these concerns regarding viral vectors, we developed a nonviral vector method to deliver miRNA mimics to the kidney using tail vein injection of polyethylenimine nanoparticles (PEI-NPs), which led to significant overexpression of target miRNAs in several mouse models of kidney disease.

Here, we deliver exogenous artificially synthesized miRNA mimics to the kidney via tail vein injection of a nonviral vector and polyethylenimine nanoparticles in several kidney disease mouse models. This led to significant overexpression of target miRNA in the kidney, resulting in inhibited progression of kidney disease in several mouse models.

여러 신장 질환 마우스 모델에서 폴리에틸레니민 나노입자를 사용하여 신장에 외인성 인공 합성 miRNA 모방체의 전달

microRNAs&#160;(miRNAs), small noncoding RNAs (21-25 bases) that are not translated into proteins, inhibit lots of target messenger RNAs (mRNAs) by ...

폐결절의 진단 및 치료를 위한 3D 재구성

A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules

The three-dimensional (3D) reconstruction of pulmonary nodules using medical images has introduced new technical approaches for diagnosing and treating pulmonary nodules, and these approaches are progressively being acknowledged and adopted by physicians and patients. Nonetheless, constructing a relatively universal 3D digital model of pulmonary nodules for diagnosis and treatment is challenging due to device differences, shooting times, and nodule types. The objective of this study is to propose a new 3D digital model of pulmonary nodules that serves as a bridge between physicians and patients and is also a cutting-edge tool for pre-diagnosis and prognostic evaluation. Many AI-driven pulmonary nodule detection and recognition methods employ deep learning techniques to capture the radiological features of pulmonary nodules, and these methods can achieve a good area under-the-curve (AUC) performance. However, false positives and false negatives remain a challenge for radiologists and clinicians. The interpretation and expression of features from the perspective of pulmonary nodule classification and examination are still unsatisfactory. In this study, a method of continuous 3D reconstruction of the whole lung in horizontal and coronal positions is proposed by combining existing medical image processing technologies. Compared with other applicable methods, this method allows users to rapidly locate pulmonary nodules and identify their fundamental properties while also observing pulmonary nodules from multiple perspectives, thereby providing a more effective clinical tool for diagnosing and treating pulmonary nodules.

저자 스포트라이트: 폐 결절의 진단 및 치료를 위한 3D 디지털 모델  

The objective of this study is to develop a novel 3D digital model of pulmonary nodules that serves as a communication bridge between physicians and patients and is also a cutting-edge tool for pre-diagnosis and prognostic evaluation.

폐 결절의 진단 및 치료를 위한 3D 디지털 모델

The three-dimensional (3D) reconstruction of pulmonary nodules using medical images has introduced new technical approaches for diagnosing and treating ...