Yunwei Zhang

Background
With the emergence of high-dimensional censored survival data in health and medicine, the use of survival models for risk prediction is increasing. To date, practical techniques exist for splitting data for model training and performance evaluation. While different sampling methods have been compared for their performances, the effect of data splitting ratio and survival specific characteristics have not yet been examined for high dimensional censored survival data.

Methods
We first conduct an empirical study of using the simple random sampling technique and stratified sampling technique on real high-dimensional gene expression datasets Lasso Cox model performance. For the simple random sampling technique, various data splitting ratios are investigated. For the stratified sampling, different survival specific variables are investigated. We consider C-index and Brier Score as evaluation metrics. We further develop and validate a two-stage purposive sampling approach motivated by our empirical study findings.

Results
Our findings reveal that survival specific characteristics contribute to model performance across training, testing and validation data. The proposed two-stage purposive sampling approach performs well in mitigating excessive diversity within the training data for both simulation study and real data analysis, leading to better survival model performances.

Conclusions
We recommend careful consideration of key factors in different sampling techniques when developing and validating survival models. Using methods such as the proposed method to mitigate excessive diversity provides a solution.

An optimal deceased donor allocation program requires a fair, ethical, and transparent algorithm to ensure efficient and effective allocation of deceased donor kidneys to recipients that will benefit most, by maximizing utility of the donor organs, but at the same time, ensuring all potential candidates have equitable access and equal opportunity to this scarce resource. In response to the increasing demand and the limited availability of donor organs, there has been a global concerted effort to increase the use of less optimal donor kidneys in suitable recipients. During this complex allocation process, organ acceptance decision-making is the final step. Transplant nephrologists are typically the gatekeeper of this process and make the ultimate decision regarding organ suitability for the intended patients. However, with considerable evidence suggesting the value of shared decision making, engaging patients, caregivers and their primary nephrologists prior to accepting the allocated organ, ensures the healthcare decisions align with the patients' values and their preferences. To tackle this challenge, we developed a visualisation guided simulation-based tool to assist shared decision-making. We have shown that the three-dimensional clinical information required for organ acceptance can be represented using an intuitive and user-friendly interface. By utilizing our published allocation simulation process, simKAP, this decision support system called Kidney Transplant Support System has the capacity to forecast a sequence of potential kidneys offered to a candidate on the waiting list, with the provision of estimated waiting time, donor quality and the expected post-transplant patient survivals for each consecutive offer. Implementation of this tool may inform shared decision-making and reduce organ discards.

Ischaemic cardiomyopathy is the most common cause of heart failure and often coexists with diabetes mellitus, which worsens patient symptom burden and outcomes. Yet, their combined effects are seldom investigated and are poorly understood. To uncover the influencing molecular signature defining ischaemic cardiomyopathy with diabetes, we performed multi-omic analyses of ischaemic and non-ischaemic cardiomyopathy with and without diabetes against healthy age-matched donors. Tissue was sourced from pre-mortem human left ventricular myocardium. Fatty acid transport and oxidation proteins were most downregulated in ischaemic cardiomyopathy with diabetes relative to donors. However, the downregulation of acylcarnitines, perilipin, and ketone body, amino acid, and glucose metabolising proteins indicated lipid metabolism may not be entirely impaired. Oxidative phosphorylation, oxidative stress, myofibrosis, and cardiomyocyte cytoarchitecture also appeared exacerbated principally in ischaemic cardiomyopathy with diabetes. These findings indicate that diabetes confounds the pathological phenotype in heart failure, and the need for a paradigm shift regarding lipid metabolism.

Platelet hyperreactivity increases the risk of cardiovascular thrombosis in diabetes and failure of antiplatelet drug therapies. Elevated basal and agonist-induced calcium flux is a fundamental cause of platelet hyperreactivity in diabetes; however, the mechanisms responsible for this remain largely unknown. Using a high-sensitivity, unbiased proteomic platform, we consistently detected over 2,400 intracellular proteins and identified proteins that were differentially released by platelets in type 2 diabetes. We identified that SEC61 translocon subunit β (SEC61B) was increased in platelets from humans and mice with hyperglycemia and in megakaryocytes from mice with hyperglycemia. SEC61 is known to act as an endoplasmic reticulum (ER) calcium leak channel in nucleated cells. Using HEK293 cells, we showed that SEC61B overexpression increased calcium flux into the cytosol and decreased protein synthesis. Concordantly, platelets in hyperglycemic mice mobilized more calcium and had decreased protein synthesis. Platelets in both humans and mice with hyperglycemia had increased ER stress. ER stress induced the expression of platelet SEC61B and increased cytosolic calcium. Inhibition of SEC61 with anisomycin decreased platelet calcium flux and inhibited platelet aggregation in vitro and in vivo. These studies demonstrate the existence of a mechanism whereby ER stress–induced upregulation of platelet SEC61B leads to increased cytosolic calcium, potentially contributing to platelet hyperreactivity in diabetes.
This study identifies SEC61 as a novel endoplasmic reticulum calcium leak channel in platelets. Upregulation of SEC61B contributes to platelet hyperreactivity in diabetes.

With the advancement of biological and medical techniques, we can now obtain large amounts of high-dimensional omics data with censored survival information. This presents challenges in method development across various domains, particularly in variable selection. Given the inherently skewed distribution of the survival time outcome variable, robust variable selection methods offer potential solutions. Recently, there has been a focus on extending robust variable selection methods from linear regression models to survival models. However, despite these developments, robust methods are currently rarely used in practical applications, possibly due to a limited appreciation of their overall good performance. To address this gap, we conduct a selective review comparing the variable selection performance of twelve robust and non-robust penalised Cox models. Our study reveals the intricate relationship among covariates, survival outcomes, and modeling approaches, demonstrating how subtle variations can significantly impact the performance of methods considered. Based on our empirical research, we recommend the use of robust Cox models for variable selection in practice based on their superior performance in presence of outliers while maintaining good efficiency and accuracy when there are no outliers. This study provides valuable insights for method development and application, contributing to a better understanding of the relationship between correlated covariates and censored outcomes.

Heart failure (HF) with left ventricular diastolic dysfunction is a growing global concern. This study evaluated myocardial oxidized nicotinamide adenine dinucleotide (NAD + ) levels in human systolic and diastolic HF and in a murine model of HF with preserved ejection fraction, exploring NAD + repletion as therapy. We quanti fied myocardial NAD + and nicotinamide phosphoribosyltransferase levels, assessing restoration with nicotinamide riboside (NR). Findings show signi ficant NAD + and nicotinamide phosphoribosyltransferase depletion in human diastolic HF myocardium, but NR successfully restored NAD + levels. In murine HF with preserved ejection fraction, NR as preventive and therapeutic intervention improved metabolic and antioxidant pro files. This study underscores NAD + repletion 's potential in diastolic HF management. (c) 2024 The Authors. Published by Elsevier on behalf of the American College of Cardiology Foundation.

Background
Our study aims to enhance the understanding of lymph node venous networks (LNVNs) by summarising their anatomical, sonographic features, and reflux patterns.

Method
We examined 241 legs from 141 patients with primary chronic venous disease (CVD) using duplex ultrasound.

Results
The findings indicated variations in the shape, size, vascularity, and echogenicity of LNVN. The superficial inguinal lymph node with reflux appeared slightly larger, exhibiting higher velocities in the hilar artery. Regarding connections, venous flow within LNVN was predominantly drained through the saphenofemoral junction (SFJ), anterior accessory great saphenous vein (AAGSV), and great saphenous vein (GSV). A significant number of LNVNs were observed to be associated with anterolateral thigh tributaries. The study also identified valve cusps within LNVN.

Conclusion
This study revealed a 12% prevalence of primary LNVN. Understanding the anatomical and haemodynamic features of LNVN informs treatment strategies and potentially helps prevent the recurrence of varicose veins.

Organ shortage is a major barrier in transplantation and rules guarding organ allocation decisions should be robust, transparent, ethical and fair. Whilst numerous allocation strategies have been proposed, it is often unrealistic to evaluate all of them in real-life settings. Hence, the capability of conducting simulations prior to deployment is important. Here, we developed a kidney allocation simulation framework (simKAP) that aims to evaluate the allocation process and the complex clinical decision-making process of organ acceptance in kidney transplantation. Our findings have shown that incorporation of both the clinical decision-making and a dynamic wait-listing process resulted in the best agreement between the actual and simulated data in almost all scenarios. Additionally, several hypothetical risk-based allocation strategies were generated, and we found that these strategies improved recipients' long-term post-transplant patient survival and reduced wait time for transplantation. The importance of simKAP lies in its ability for policymakers in any transplant community to evaluate any proposed allocation algorithm using in-silico simulation.

Accurate prediction of allograft survival after kidney transplantation allows early identification of at-risk recipients for adverse outcomes and initiation of preventive interventions to optimize post-transplant care. Many prediction algorithms do not model cohort heterogeneity and may lead to inaccurate assessment of longer-term graft outcomes among minority groups. Using data from a national Australian kidney transplant cohort (2008–2017) as the derivation set, we developed P-Cube, a multi-step precision prediction pathway model for predicting overall graft survival in three ethnic subgroups: European Australians, Asian Australians and Aboriginal and Torres Strait Islander Peoples. The concordance index for the European Australians, Asian Australians, and Aboriginal and Torres Strait Islander Peoples subpopulations were 0.99 (0.98–0.99), 0.93 (0.92–0.94) and 0.92 (0.91–0.93), respectively. Similar findings were observed when validating P-cube using an external dataset [Scientific Registry of Transplant Recipient Registry (2006–2020)]. Six sub-categories of recipients with distinct risk factor profiles were identified. Some factors such as blood group compatibility were considered important across the entire transplant population. Other factors such as human leukocyte antigen (HLA)-DR mismatches were unique to older recipients. The P-cube model identifies allograft survival specific risk factors within a heterogenous population and offers personalized survival predictions in a diverse cohort.

Extracellular protein disulfide isomerases (PDIs), including PDI, endoplasmic reticulum protein 57 (ERp57), ERp72, ERp46, and ERp5, are required for in vivo thrombus formation in mice. Platelets secrete PDIs upon activation, which regulate platelet aggregation. However, platelets secrete only ∼10% of their PDI content extracellularly. The intracellular role of PDIs in platelet function is unknown. Here, we aim to characterize the role of ERp5 (gene Pdia6) using platelet conditional knockout mice, platelet factor 4 (Pf4) Cre+/ERp5floxed (fl)/fl. Pf4Cre+/ERp5fl/fl mice developed mild macrothrombocytopenia. Platelets deficient in ERp5 showed marked dysregulation of their ER, indicated by a twofold upregulation of ER proteins, including PDI, ERp57, ERp72, ERp46, 78 kilodalton glucose-regulated protein (GRP78), and calreticulin. ERp5-deficient platelets showed an enhanced ER stress response to ex vivo and in vivo ER stress inducers, with enhanced phosphorylation of eukaryotic translation initiation factor 2A and inositol-requiring enzyme 1 (IRE1). ERp5 deficiency was associated with increased secretion of PDIs, an enhanced response to thromboxane A2 receptor activation, and increased thrombus formation in vivo. Our results support that ERp5 acts as a negative regulator of ER stress responses in platelets and highlight the importance of a disulfide isomerase in platelet ER homeostasis. The results also indicate a previously unanticipated role of platelet ER stress in platelet secretion and thrombosis. This may have important implications for the therapeutic applications of ER stress inhibitors in thrombosis.