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><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&amp;eacute; - Universit&amp;auml;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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4.4K Views.  Charité - Universitätsmedizin Berlin. We demonstreren de zichtbaarheid en voordelen van een database die wordt gebruikt als een elektronisch patiëntendossier voor posttransplantatiezorg en klinische routine. En heeft ook een zeer geavanceerd modulair onderzoeksontwerp voor de specifieke vereisten van transplantatieonderzoek. Ons elektronisch patiëntendossier maakt eenvoudig dagelijks klinisch gebruik en snelle toegang voor onderzoeksvragen mogelijk, terwijl de hoogste gegevenskwaliteit wordt gegarandeerd door middel van gegeven...

Video: 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.

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

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.

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

Murine Renal Transplantation Procedure

Renal orthotopic transplantation in mice is a technically challenging procedure. Although the first kidney transplants in mice were performed by Russell et al over 30 years ago (1) and refined by Zhang et al years later (2), few people in the world have mastered this procedure. In our laboratory we have successfully performed 1200 orthotopic kidney transplantations with &gt; 90% survival rate. The key points for success include stringent control of reperfusion injury, bleeding and thrombosis, both during the procedure and post-transplantation, and use of 10-0 instead of 11-0 suture for anastomoses.
Post-operative care and treatment of the recipient is extremely important to transplant success and evaluation. All renal graft recipients receive antibiotics in the form of an injection of penicillin immediately post-transplant and sulfatrim in the drinking water continually. Overall animal health is evaluated daily and whole blood creatinine analyses are performed routinely with a portable I-STAT machine to assess graft function.

Renal transplantation in mice is a technically challenging procedure that requires careful post-operative care and treatment for success.

Renal orthotopic transplantation in mice is a technically challenging procedure. Although the first kidney transplants in mice were performed by Russell ...

Biology

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.

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

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.

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

Orthotopic Kidney Auto-Transplantation in a Porcine Model Using 24 Hours Organ Preservation And Continuous Telemetry

In the present era of organ transplantation with critical organ shortage, various strategies are employed to expand the pool of available allografts for kidney transplantation (KT). Even though, the use of allografts from extended criteria donors (ECD) could partially ease the shortage of organ donors, ECD organs carry a potentially higher risk for inferior outcomes and postoperative complications. Dynamic organ preservation techniques, modulation of ischemia-reperfusion and preservation injury, and allograft therapies are in the spotlight of scientific interest in an effort to improve allograft utilization and patient outcomes in KT.
Preclinical animal experiments are playing an essential role in translational research, especially in the medical device and drug development. The major advantage of the porcine orthotopic auto-transplantation model over ex vivo or small animal studies lies within the surgical-anatomical and physiological similarities to the clinical setting. This allows the investigation of new therapeutic methods and techniques and ensures a facilitated clinical translation of the findings. This protocol provides a comprehensive and problem-oriented description of the porcine orthotopic kidney auto-transplantation model, using a preservation time of 24 hours and telemetry monitoring. The combination of sophisticated surgical techniques with highly standardized and state-of-the-art methods of anesthesia, animal housing, perioperative follow up, and monitoring ensure the reproducibility and success of this model.

Large animal models play an essential role in preclinical transplantation research. Due to its similarities to the clinical setup, the porcine model of orthotopic kidney auto-transplantation described in this article provides an excellent in vivo setting for the testing of organ preservation techniques and therapeutic interventions.

In the present era of organ transplantation with critical organ shortage, various strategies are employed to expand the pool of available allografts for ...

Digital Home-Monitoring of Patients after Kidney Transplantation: The MACCS Platform

The MACCS (Medical Assistant for Chronic Care Service) platform enables secure sharing of key medical information between patients after kidney transplantation and physicians. Patients provide information such as vital signs, well-being, and medication intake via smartphone apps. The information is transferred directly into a database and electronic health record at the kidney transplant center, which is used for routine patient care and research. Physicians can send an updated medication plan and laboratory data directly to the patient app via this secure platform. Other features of the app are medical messages and video consultations. Consequently, the patient is better-informed, and self-management is facilitated. In addition, the transplant center and the patient's local nephrologist automatically exchange notes, medical reports, laboratory values, and medication data via the platform. A telemedicine team reviews all incoming data on a dashboard and takes action, if necessary. Tools to identify patients at risk for complications are under development. The platform exchanges data via a standardized secure interface (Health Level 7 (HL7), Fast Healthcare Interoperability Resources (FHIR)). The standardized data exchange based on HL7 FHIR guarantees interoperability with other eHealth solutions and allows rapid scalability to other chronic diseases. The underlying data protection concept is in concordance with the latest European General Data Protection Regulation. Enrollment started in February 2020, and 131 kidney transplant recipients are actively participating as of July 2020. Two large German health insurance companies are currently funding the telemedicine services of the project. The deployment for other chronic kidney diseases and solid organ transplant recipients is planned. In conclusion, the platform is designed to enable home monitoring and automatic data exchange, empower patients, reduce hospitalizations, and improve adherence, and outcomes after kidney transplantation.

The MACCS platform&#160;is a comprehensive telemedicine concept aiming at better outcomes after kidney transplantation by sharing key medical information between patients and physicians. A telemedicine team reviews incoming data to detect potential complications and to improve adherence in kidney transplant recipients to achieve better long-term outcomes.

The MACCS (Medical Assistant for Chronic Care Service) platform enables secure sharing of key medical information between patients after kidney ...

Robot-Assisted Kidney Transplantation

This paper describes robot-assisted kidney transplantation (RAKT) from a living donor. The robot is docked between the parted legs of the patient, placed in the supine Trendelenburg position. Kidney allografts are provided by a living donor. Before vascular anastomosis, the kidney allograft is prepared by inserting a double-J stent in the ureter, and the temperature for the anastomosis is lowered by wrapping it in an ice-packed gauze. A 12 mm or 8 mm port for the robotic camera and three 8 mm ports for robotic arms are placed. A peritoneal pouch is created for the kidney allograft by raising the peritoneal flaps on both sides over the psoas muscle before dissecting the iliac vessels and bladder. A 6 cm Pfannenstiel incision is made to insert the kidney into the peritoneal pouch, lateral to the right iliac vessels. 
After clamping the external iliac vein with Bulldogs clamps, a venotomy is performed, and the graft renal vein is anastomosed to the external iliac vein in an end-to-side continuous manner with a 6/0 polytetrafluoroethylene suture. After clamping the graft renal vein, the iliac vein is declamped. This is followed by clamping of the external iliac artery, arteriotomy, arterial anastomosis with a 6/0 polytetrafluoroethylene suture, clamping of the graft renal artery, and declamping of the external iliac artery. Reperfusion is then carried out, and ureteroneocystostomy is performed using the Lich-Gregoir technique. The peritoneum is closed at a few locations with polymer locking clips, and a closed-suction drain is placed through one of the working ports. After deflating the pneumoperitoneum, all incisions are closed.

This paper provides technical details for robot-assisted kidney transplantation from a living donor.

This paper describes robot-assisted kidney transplantation (RAKT) from a living donor. The robot is docked between the parted legs of the patient, placed ...

A Rat Orthotopic Renal Transplantation Model for Renal Allograft Rejection

Renal allograft rejection limits the long-term survival of patients after renal transplantation. Rat orthotopic renal transplantation is an essential model to investigate the mechanism of renal allograft rejection in pre-clinical studies and could aid in the development of novel approaches to improve the long-term survival of renal allografts. Donor kidney implantation in rat orthotopic renal transplantation is commonly performed by end-to-side anastomosis to recipients' aorta and inferior vena cava. In this model, the donor's kidney was implanted using end-to-end anastomosis to the recipients' renal artery and renal vein. The donor's ureter was anastomosed to the recipient's bladder in an end-to-side 'tunnel' method. This model contributes to better healing of ureter-bladder anastomosis and increases the recipients' survival by avoiding interference with blood supply and venous reflux of the lower body. This model can be used to investigate the mechanisms of acute and chronic immune and pathologic rejection of renal allografts. Here, the study describes the detailed protocols of this orthotopic renal transplantation between rats.

The rat orthotopic renal transplantation model contributes to investigating the mechanism of renal allograft rejection. The current model increases the recipients' survival without interference with blood supply and venous reflux of the lower body using an end-to-end anastomosis of kidney implantation and an end-to-side "tunnel" method of ureter-bladder anastomosis.

Renal allograft rejection limits the long-term survival of patients after renal transplantation. Rat orthotopic renal transplantation is an essential ...

Application of Laser Microdissection to Uncover Regional Transcriptomics in Human Kidney Tissue

Gene expression analysis of human kidney tissue is an important tool to understand homeostasis and disease pathophysiology. Increasing the resolution and depth of this technology and extending it to the level of cells within the tissue is needed. Although the use of single nuclear and single cell RNA sequencing has become widespread, the expression signatures of cells obtained from tissue dissociation do not maintain spatial context. Laser microdissection (LMD) based on specific fluorescent markers would allow the isolation of specific structures and cell groups of interest with known localization, thereby enabling the acquisition of spatially-anchored transcriptomic signatures in kidney tissue. We have optimized an LMD methodology, guided by a rapid fluorescence-based stain, to isolate five distinct compartments within the human kidney and conduct subsequent RNA sequencing from valuable human kidney tissue specimens. We also present quality control parameters to enable the assessment of adequacy of the collected specimens. The workflow outlined in this manuscript shows the feasibility of this approach to isolate sub-segmental transcriptomic signatures with high confidence. The methodological approach presented here may also be applied to other tissue types with substitution of relevant antibody markers.

We describe a protocol for laser microdissection of sub-segments of the human kidney, including the glomerulus, proximal tubule, thick ascending limb, collecting duct and interstitium. The RNA is then isolated from the obtained compartments and RNA sequencing is carried out to determine changes in the transcriptomic signature within each sub-segment.

Gene expression analysis of human kidney tissue is an important tool to understand homeostasis and disease pathophysiology. Increasing the resolution and ...

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

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