Impact of innovative technologies on quality and safety in surgery.

Technological advancements gradually lead to the revision and transformation of healthcare, training, and research. Surgery is a field of medicine where the collaboration of human resources and the application of innovative technologies could elevate faithfulness and efficiency. The article, exploring the technologies and analyzing them in terms of their reliability, the benefits of performing precision surgeries, the effectiveness in the outcome of surgery with less psychosomatic fatigue, and the improvements in the training process for surgeons, emphasizes the safety and quality that can be achieved.

Frequencies or Absolute Numbers? Cluster Analysis of Frequencies and Absolute Numbers of B-Cell Subsets in Dialysis Patients Who Are Candidates for Kidney Transplantation Reveals Different Profiles.

Detailed characterization of B cells in dialysis patients who are candidates for kidney transplant is still lacking, with little information on how dialysis duration and modality impact B cell subsets. Cluster analysis of flow cytometry determined the frequencies and absolute numbers of B-cell subsets and divided the cohort of 78 candidates into two distinct clusters, one with shorter and one with longer dialysis duration. The immune profiles of the clusters differed depending on whether frequencies or absolute counts were considered.

Hydrogel-Based Vascularized Organ Tissue Engineering: A Systematized Review on Abdominal Organs.

Background: Biomedical engineering, especially tissue engineering, is trying to provide an alternative solution to generate functional organs/tissues for use in various applications. These include beyond the final goal of transplantation, disease modeling and drug discovery as well. The aim of this study is to comprehensively review the existing literature on hydrogel-based vascularized organ (i.

Vaccination with Tozimameran Induces T-Cell Activation, but Not Senescent or Exhaustive Alterations, in Kidney Transplant Recipients.

Background: Multiple vaccinations have potential inimical effects on the immune system aging process. We examined whether response to SARS-CoV-2 vaccination with Tozinameran is associated with immunosenescence and immunoexhaustion in kidney transplant recipients (KTRs).

Methods: In this prospective observational study, we observed 39 adult kidney transplant recipients (KTRs) who had no pre-existing anti-SARS-CoV-2 antibodies and were on stable immunosuppression.

Diagnostic and Prognostic Value of Machine Perfusion Biomarkers in Kidney Graft Evaluation.

Background: With the rising prevalence of end-stage kidney disease, the use of expanded criteria donor allografts, seen as essential for meeting organ demand, still proves challenging due to their higher risk of graft loss, delayed function, and rejection. Machine perfusion, a technique in preserving allografts, offers improved allograft outcomes compared to static cold storage while allowing for the noninvasive measurement of kidney injury biomarkers in the perfusate solution. This offers an objective method to assess graft function at various preservation stages.

Editorial: Immersive media in connected health-volume II.

Immersive media, particularly Extended Reality (XR), is at the forefront of revolutionizing the healthcare industry. Healthcare provides XR with "silver bullet" use cases that add value and societal effect to the technology. Healthcare interventions frequently require imaging or visualization to be applied correctly, and the sensation of presence that XR can provide is crucial as a training aid for healthcare learners.

Clinical Prediction Models for Prognosis of Colorectal Liver Metastases: A Comprehensive Review of Regression-Based and Machine Learning Models.

Colorectal liver metastasis (CRLM) is a disease entity that warrants special attention due to its high frequency and potential curability. Identification of "high-risk" patients is increasingly popular for risk stratification and personalization of the management pathway. Traditional regression-based methods have been used to derive prediction models for these patients, and lately, focus has shifted to artificial intelligence-based models, with employment of variable supervised and unsupervised techniques.

Artificial kidney: Challenges and opportunities.

This review aims to present the developments occurring in the field of artificial organs and particularly focuses on the presentation of developments in artificial kidneys. The challenges for biomedical engineering involved in overcoming the potential difficulties are showcased, as well as the importance of interdisciplinary collaboration in this marriage of medicine and technology. In this review, modern artificial kidneys and the research efforts trying to provide and promise artificial kidneys are presented.

Challenges involved in the application of artificial intelligence in gastroenterology: The race is on!

Gastroenterology is a particularly data-rich field, generating vast repositories of data that are a fruitful ground for artificial intelligence (AI) and machine learning (ML) applications. In this opinion review, we initially elaborate on the current status of the application of AI/ML-based software in gastroenterology. Currently, AI/ML-based models have been developed in the following applications: Models integrated into the clinical setting following real-time patient data flagging patients at high risk for developing a gastrointestinal disease, models employing non-invasive parameters that provide accurate diagnoses aiming to either replace, minimize, or refine the indications of endoscopy, models utilizing genomic data to diagnose various gastrointestinal diseases, computer-aided diagnosis systems facilitating the interpretation of endoscopy images, models to facilitate treatment allocation and predict the response to treatment, and finally, models in prognosis predicting complications, recurrence following treatment, and overall survival.

Humoral and Cellular Immunity Are Significantly Affected in Renal Transplant Recipients, following Vaccination with BNT162b2.

Background: Renal transplant recipients (RTRs) tend to mount weaker immune responses to vaccinations, including vaccines against the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

Methods: Humoral immunity was assessed using anti-receptor binding domain (RBD) and neutralizing antibodies (NAb) serum levels measured by ELISA, and cellular immunity was assessed using T-, B-, NK, natural killer-like T (NKT)-cell subpopulations, and monocytes measured by flow cytometry, and also specific T-cell immunity, at predefined time points after BNT162b2 vaccination, in 57 adult RTRs.

Results: Administration of three booster doses was necessary to achieve anti-RBD and NAb protective levels in almost all patients (92.

Immune Profile Determines Response to Vaccination against COVID-19 in Kidney Transplant Recipients.

Background And Aim: Immune status profile can predict response to vaccination, while lymphocyte phenotypic alterations represent its effectiveness. We prospectively evaluated these parameters in kidney transplant recipients (KTRs) regarding Tozinameran (BNT162b2) vaccination.

Method: In this prospective monocenter observational study, 39 adult KTRs, on stable immunosuppression, naïve to COVID-19, with no protective humoral response after two Tozinameran doses, received the third vaccination dose, and, based on their immunity activation, they were classified as responders or non-responders.

Three-Dimensional Printing and Bioprinting in Renal Transplantation and Regenerative Medicine: Current Perspectives.

For patients with end-stage kidney disease (ESKD), renal transplantation is the treatment of choice, constituting the most common solid organ transplantation. This study aims to provide a comprehensive review regarding the application of three-dimensional (3D) printing and bioprinting in renal transplantation and regenerative medicine. Specifically, we present studies where 3D-printed models were used in the training of surgeons through renal transplantation simulations, in patient education where patients acquire a higher understanding of their disease and the proposed operation, in the preoperative planning to facilitate decision-making, and in fabricating customized, tools and devices.

Exploring Perturbations in Peripheral B Cell Memory Subpopulations Early after Kidney Transplantation Using Unsupervised Machine Learning.

Background: B cells have a significant role in transplantation. We examined the distribution of memory subpopulations (MBCs) and naïve B cell (NBCs) phenotypes in patients soon after kidney transplantation. Unsupervised machine learning cluster analysis is used to determine the association between the cellular phenotypes and renal function.

Artificial intelligence-based preventive, personalized and precision medicine for cardiovascular disease/stroke risk assessment in rheumatoid arthritis patients: a narrative review.

The challenges associated with diagnosing and treating cardiovascular disease (CVD)/Stroke in Rheumatoid arthritis (RA) arise from the delayed onset of symptoms. Existing clinical risk scores are inadequate in predicting cardiac events, and conventional risk factors alone do not accurately classify many individuals at risk. Several CVD biomarkers consider the multiple pathways involved in the development of atherosclerosis, which is the primary cause of CVD/Stroke in RA.

Cardiovascular disease/stroke risk stratification in deep learning framework: a review.

The global mortality rate is known to be the highest due to cardiovascular disease (CVD). Thus, preventive, and early CVD risk identification in a non-invasive manner is vital as healthcare cost is increasing day by day. Conventional methods for risk prediction of CVD lack robustness due to the non-linear relationship between risk factors and cardiovascular events in multi-ethnic cohorts.

Global dissemination of minimally invasive living donor hepatectomy: What are the barriers?

Minimally invasive donor hepatectomy (MIDH) is a relatively novel procedure that can potentially increase donor safety and contribute to faster rehabilitation of donors. After an initial period in which donor safety was not effectively validated, MIDH currently seems to provide improved results, provided that it is conducted by experienced surgeons. Appropriate selection criteria are crucial to achieve better outcomes in terms of complications, blood loss, operative time, and hospital stay.

Ensemble Deep Learning Derived from Transfer Learning for Classification of COVID-19 Patients on Hybrid Deep-Learning-Based Lung Segmentation: A Data Augmentation and Balancing Framework.

Background And Motivation: Lung computed tomography (CT) techniques are high-resolution and are well adopted in the intensive care unit (ICU) for COVID-19 disease control classification. Most artificial intelligence (AI) systems do not undergo generalization and are typically overfitted. Such trained AI systems are not practical for clinical settings and therefore do not give accurate results when executed on unseen data sets.

Streamlining Tangible 3D Printed and Intangible XR Content Creation and Evaluation: The ENTICE Experience.

ENTICE aimed to use co-creative methodologies in order to build a solid creation pipeline for medical experiential content. The project has developed and evaluated immersive learning resources and tools aiming to support well-defined learning objectives using tangible and intangible resources (AR/VR/MR, 3D printing) that are highly sought in the fields of anatomy and surgery. In this paper the preliminary results from the evaluation of the learning resources and tools in 3 countries as well as the lessons learnt are presented towards to the improvement of the medical education process.