Dataset Information

Databases for technical aspects of immunohistochemistry.

ABSTRACT: With the aims of sharing information about the technical aspects of immunohistochemistry (IHC) and making it possible to make a suitable choice of antibody for histopathological examination, this technical report describes the results of a questionnaire administered during the period of 2014 to 2015 to members of the Conference on Experimental Animal Histopathology. It also describes the immunological properties of primary antibodies (clone, supplier, catalog number, species reactivity, etc.) and the IHC staining conditions (fixing solution, fixing time, embedding, antigen retrieval method, antibody dilution, incubation time, incubation temperature, positive control tissue, secondary antibody information, etc.) for a total number of 733 primary antibodies (425 kinds of primary antibody).

SUBMITTER: Furukawa S

PROVIDER: S-EPMC5293696 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

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Databases for technical aspects of immunohistochemistry.

Furukawa Satoshi S Nagaike Mika M Ozaki Kiyokazu K

Journal of toxicologic pathology 20160926 1

With the aims of sharing information about the technical aspects of immunohistochemistry (IHC) and making it possible to make a suitable choice of antibody for histopathological examination, this technical report describes the results of a questionnaire administered during the period of 2014 to 2015 to members of the Conference on Experimental Animal Histopathology. It also describes the immunological properties of primary antibodies (clone, supplier, catalog number, species reactivity, etc.) an ...[more]

PMID: 28190929

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Project description:BackgroundChatbots are applications that can conduct natural language conversations with users. In the medical field, chatbots have been developed and used to serve different purposes. They provide patients with timely information that can be critical in some scenarios, such as access to mental health resources. Since the development of the first chatbot, ELIZA, in the late 1960s, much effort has followed to produce chatbots for various health purposes developed in different ways.ObjectiveThis study aimed to explore the technical aspects and development methodologies associated with chatbots used in the medical field to explain the best methods of development and support chatbot development researchers on their future work.MethodsWe searched for relevant articles in 8 literature databases (IEEE, ACM, Springer, ScienceDirect, Embase, MEDLINE, PsycINFO, and Google Scholar). We also performed forward and backward reference checking of the selected articles. Study selection was performed by one reviewer, and 50% of the selected studies were randomly checked by a second reviewer. A narrative approach was used for result synthesis. Chatbots were classified based on the different technical aspects of their development. The main chatbot components were identified in addition to the different techniques for implementing each module.ResultsThe original search returned 2481 publications, of which we identified 45 studies that matched our inclusion and exclusion criteria. The most common language of communication between users and chatbots was English (n=23). We identified 4 main modules: text understanding module, dialog management module, database layer, and text generation module. The most common technique for developing text understanding and dialogue management is the pattern matching method (n=18 and n=25, respectively). The most common text generation is fixed output (n=36). Very few studies relied on generating original output. Most studies kept a medical knowledge base to be used by the chatbot for different purposes throughout the conversations. A few studies kept conversation scripts and collected user data and previous conversations.ConclusionsMany chatbots have been developed for medical use, at an increasing rate. There is a recent, apparent shift in adopting machine learning-based approaches for developing chatbot systems. Further research can be conducted to link clinical outcomes to different chatbot development techniques and technical characteristics.

Project description:ObjectiveTo describe the technical aspects and outcomes of robotic-assisted radical prostatectomy (RARP) following abandoned open radical prostatectomy (ORP).Patients and methodsA retrospective review was performed of patients who underwent RARP following abandonment of ORP between 2016 and 2020. RARP was undertaken by two highly experienced robotic surgeons. Analysis of patient and operative characteristics, outcomes, and reasons for abandonment of ORP were described.ResultsSix patients were included for analysis with a median age of 63.5 years [50.3-67.5]. The median body mass index (BMI) was 34.7 [27.8-36.2]. All patients had intermediate-risk prostate cancer. Small prostate and deep pelvis were given as reasons for abandoning ORP in five cases (83.3%), with four of these also attributing increased BMI as a factor. Extensive mesh from previous bilateral inguinal hernia repair was cited as the reason for abandonment in the remaining patient. One patient had commenced androgen deprivation therapy following abandoned ORP. Extensive retropubic adhesions were noted at the time of RARP in five of six patients, with intraoperative complication of small bladder lacerations encountered in the patient with prior mesh hernia repair. The median time from abandoned ORP to RARP was 128 days [40-216]. Median operating time was 160 minutes [139-190] and estimated blood loss was 225 mL [138-375]. Negative margins were obtained in four of six cases, with further salvage treatment being required in one case at a median follow-up duration of 10.5 months [6.5-25.3].ConclusionAbandonment of ORP is an uncommonly reported event, however, in this small case series, we demonstrate that, in the hands of experienced surgeons, RARP is a safe and technically feasible alternative in such cases. Increased BMI, small prostate size and pelvic anatomical constraints appear to be common catalysts for abandonment of open surgery in this cohort. Identifying these high-risk patients early and considering referral to robotic centers may be preferred.

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Databases for technical aspects of immunohistochemistry.

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Databases for technical aspects of immunohistochemistry.

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