Predictors of Death in the Liver Transplantation Adult Candidates: An Artificial Neural Networks and Support Vector Machine Hybrid-Based Cohort Study

Background: Model for end-stage liver disease (MELD) is currently used for liver transplantation (LT) allocation, however, it is not a sufficient criterion. Objective: This current study aims to perform a hybrid neural network analysis of different data, make a decision tree and finally design a decision support system for improving LT prioritization.Material and Methods: In this cohort follow-up-based study, baseline characteristics of 1947 adult patients, who were candidates for LT in Shiraz Organ Transplant Center, Iran, were assessed and followed for two years and those who died before LT due to the end-stage liver disease were considered as dead cases, while others considered as alive cases. A well-organized checklist was filled for each patient. Analysis of the data was performed using artificial neural networks (ANN) and support vector machines (SVM). Finally, a decision tree was illustrated and a user friendly decision support system was designed to assist physicians in LT prioritization. Results: Between all MELD types, MELD-Na was a stronger determinant of LT candidates’ survival. Both ANN and SVM showed that besides MELD-Na, age and ALP (alkaline phosphatase) are the most important factors, resulting in death in LT candidates. It was cleared that MELD-Na <23, age <53 and ALP <257 IU/L were the best predictors of survival in LT candidates. An applicable decision support system was designed in this study using the above three factors.  Conclusion: Therefore, Meld-Na, age and ALP should be used for LT allocation. The presented decision support system in this study will be helpful in LT prioritization by LT allocators

Emerging role of microbiota derived outer membrane vesicles to preventive, therapeutic and diagnostic proposes

Abstract The role of gut microbiota and its products in human health and disease is profoundly investigated. The communication between gut microbiota and the host involves a complicated network of signaling pathways via biologically active molecules generated by intestinal microbiota. Some of these molecules could be assembled within nanoparticles known as outer membrane vesicles (OMVs). Recent studies propose that OMVs play a critical role in shaping immune responses, including homeostasis and acute inflammatory responses. Moreover, these OMVs have an immense capacity to be applied in medical research, such as OMV-based vaccines and drug delivery. This review presents a comprehensive overview of emerging knowledge about biogenesis, the role, and application of these bacterial-derived OMVs, including OMV-based vaccines, OMV adjuvants characteristics, OMV vehicles (in conjugated vaccines), cancer immunotherapy, and drug carriers and delivery systems. Moreover, we also highlight the significance of the potential role of these OMVs in diagnosis and therapy

Immune Checkpoint Inhibitors in Cancer Therapy

The discovery of immune checkpoint proteins such as PD-1/PDL-1 and CTLA-4 represents a significant breakthrough in the field of cancer immunotherapy. Therefore, humanized monoclonal antibodies, targeting these immune checkpoint proteins have been utilized successfully in patients with metastatic melanoma, renal cell carcinoma, head and neck cancers and non-small lung cancer. The US FDA has successfully approved three different categories of immune checkpoint inhibitors (ICIs) such as PD-1 inhibitors (Nivolumab, Pembrolizumab, and Cemiplimab), PDL-1 inhibitors (Atezolimumab, Durvalumab and Avelumab), and CTLA-4 inhibitor (Ipilimumab). Unfortunately, not all patients respond favourably to these drugs, highlighting the role of biomarkers such as Tumour mutation burden (TMB), PDL-1 expression, microbiome, hypoxia, interferon-γ, and ECM in predicting responses to ICIs-based immunotherapy. The current study aims to review the literature and updates on ICIs in cancer therapy.</p

Diagnostic Accuracy of Ultrasonography for Identification of Elbow Fractures in Children; a Systematic Review and Meta-analysis

Introduction: In spite of the results of previous studies regarding the benefits of ultrasonography for diagnosis of elbow fractures in children, the exact accuracy of this imaging modality is still under debate. Therefore, in this diagnostic systematic review and meta-analysis, we aimed to investigate the accuracy of ultrasonography in this regard. Methods: Two independent reviewers performed systematic search in Web of Science, Embase, PubMed, Cochrane, and Scopus for studies published from inception of these databases to May 2023. Quality assessment of the included studies was performed using Quality Assessment Tool for Diagnostic Accuracy Studies (QUADAS-2). Meta-Disc software version 1.4 and Stata statistical software package version 17.0 were used for statistical analysis. Results: A total of 648 studies with 1000 patients were included in the meta-analysis. The pooled sensitivity and specificity were 0.95 (95% CI: 0.93-0.97) and 0.87 (95% CI: 0.84-0.90), respectively. Pooled positive likelihood ratio (PLR) was 6.71 (95% CI: 3.86-11.67), negative likelihood ratio (NLR) was 0.09 (95% CI: 0.03-0.22), and pooled diagnostic odds ratio (DOR) of ultrasonography in detection of elbow fracture in children was 89.85 (95% CI: 31.56-255.8). The area under the summary receiver operating characteristic (ROC) curve for accuracy of ultrasonography in this regard was 0.93. Egger's and Begg's analyses showed that there is no significant publication bias (P=0.11 and P=0.29, respectively). Conclusion: Our meta-analysis revealed that ultrasonography is a relatively promising diagnostic imaging modality for identification of elbow fractures in children. However, clinicians employing ultrasonography for diagnosis of elbow fractures should be aware that studies included in this meta-analysis had limitations regarding methodological quality and are subject to risk of bias. Future high-quality studies with standardization of ultrasonography examination protocol are required to thoroughly validate ultrasonography for elbow fractures

The global burden of childhood and adolescent cancer in 2017. An analysis of the Global Burden of Disease Study 2017

Force LM, Abdollahpour I, Advani SM, et al. The global burden of childhood and adolescent cancer in 2017. An analysis of the Global Burden of Disease Study 2017. Lancet Oncology. 2019;20(9):1211-1225.Background Accurate childhood cancer burden data are crucial for resource planning and health policy prioritisation. Model-based estimates are necessary because cancer surveillance data are scarce or non-existent in many countries. Although global incidence and mortality estimates are available, there are no previous analyses of the global burden of childhood cancer represented in disability-adjusted life-years (DALYs). Methods Using the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 methodology, childhood (ages 0-19 years) cancer mortality was estimated by use of vital registration system data, verbal autopsy data, and population-based cancer registry incidence data, which were transformed to mortality estimates through modelled mortality-to-incidence ratios (MIRs). Childhood cancer incidence was estimated using the mortality estimates and corresponding MIRs. Prevalence estimates were calculated by using MIR to model survival and multiplied by disability weights to obtain years lived with disability (YLDs). Years of life lost (YLLs) were calculated by multiplying age-specific cancer deaths by the difference between the age of death and a reference life expectancy. DALYs were calculated as the sum of YLLs and YLDs. Final point estimates are reported with 95% uncertainty intervals. Findings Globally, in 2017, there were 11.5 million (95% uncertainty interval 10.6-12.3) DALYs due to childhood cancer, 97.3% (97.3-97.3) of which were attributable to YLLs and 2.7% (2.7-2.7) of which were attributable to YLDs. Childhood cancer was the sixth leading cause of total cancer burden globally and the ninth leading cause of childhood disease burden globally. 82.2% (82.1-82.2) of global childhood cancer DALYs occurred in low, low-middle, or middle Socio-demographic Index locations, whereas 50.3% (50.3-50.3) of adult cancer DALYs occurred in these same locations. Cancers that are uncategorised in the current GBD framework comprised 26.5% (26.5-26.5) of global childhood cancer DALYs. Interpretation The GBD 2017 results call attention to the substantial burden of childhood cancer globally, which disproportionately affects populations in resource-limited settings. The use of DALY-based estimates is crucial in demonstrating that childhood cancer burden represents an important global cancer and child health concern. (C) 2019 The Author(s). Published by Elsevier Ltd