Biphasic pretreatment excels over conventional sulfuric acid in pinewood biorefinery: An environmental analysis.

This study assesses the environmental impact of pine chip-based biorefinery processes, focusing on bioethanol, xylonic acid, and lignin production. A cradle-to-gate Life Cycle Assessment (LCA) is employed, comparing a novel biphasic pretreatment method (p-toluenesulfonic acid (TsOH)/pentanol, Sc-1) with conventional sulfuric acid pretreatment (HSO, Sc-2). The analysis spans biomass handling, pretreatment, enzymatic hydrolysis, yeast fermentation, and distillation.

Assessment of Glycemic Control Protocol (STAR) Through Compliance Analysis Amongst Malaysian ICU Patients.

Purpose: This paper presents an assessment of an automated and personalized stochastic targeted (STAR) glycemic control protocol compliance in Malaysian intensive care unit (ICU) patients to ensure an optimized usage.

Patients And Methods: STAR proposes 1-3 hours treatment based on individual insulin sensitivity variation and history of blood glucose, insulin, and nutrition. A total of 136 patients recorded data from STAR pilot trial in Malaysia (2017-quarter of 2019*) were used in the study to identify the gap between chosen administered insulin and nutrition intervention as recommended by STAR, and the real intervention performed.

Model-based glycemic control in a Malaysian intensive care unit: performance and safety study.

Stress-induced hyperglycemia is common in critically ill patients. A few forms of model-based glycemic control have been introduced to reduce this phenomena and among them is the automated STAR protocol which has been used in the Christchurch and Gyulá hospitals' intensive care units (ICUs) since 2010. This article presents the pilot trial assessment of STAR protocol which has been implemented in the International Islamic University Malaysia Medical Centre (IIUMMC) Hospital ICU since December 2017.

Performance of Stochastic Targeted Blood Glucose Control Protocol by virtual trials in the Malaysian intensive care unit.

Background And Objective: Blood glucose variability is common in healthcare and it is not related or influenced by diabetes mellitus. To minimise the risk of high blood glucose in critically ill patients, Stochastic Targeted Blood Glucose Control Protocol is used in intensive care unit at hospitals worldwide. Thus, this study focuses on the performance of stochastic modelling protocol in comparison to the current blood glucose management protocols in the Malaysian intensive care unit.

A model-based control protocol for transition from ICU to HDU: Robustness analysis.

The robustness of a model-based control protocol as a less intensive TGC protocol using insulin Glargine for provision of basal insulin is simulated in this study. To quantify the performance and robustness of the protocol to errors, namely physiological variability and sensor errors, an in-silico Monte Carlo analysis is performed. Actual patient data from Christchurch Hospital, New Zealand were used as virtual trial patients.

A physiological Intensive Control Insulin-Nutrition-Glucose (ICING) model validated in critically ill patients.

Intensive insulin therapy (IIT) and tight glycaemic control (TGC), particularly in intensive care unit (ICU), are the subjects of increasing and controversial debate in recent years. Model-based TGC has shown potential in delivering safe and tight glycaemic management, all the while limiting hypoglycaemia. A comprehensive, more physiologically relevant Intensive Control Insulin-Nutrition-Glucose (ICING) model is presented and validated using data from critically ill patients.

Tight glycemic control in critical care--the leading role of insulin sensitivity and patient variability: a review and model-based analysis.

Tight glycemic control (TGC) has emerged as a major research focus in critical care due to its potential to simultaneously reduce both mortality and costs. However, repeating initial successful TGC trials that reduced mortality and other outcomes has proven difficult with more failures than successes. Hence, there has been growing debate over the necessity of TGC, its goals, the risk of severe hypoglycemia, and target cohorts.

Impact of glucocorticoids on insulin resistance in the critically ill.

Glucocorticoids (GCs) have been shown to reduce insulin sensitivity in healthy individuals. Widely used in critical care to treat a variety of inflammatory and allergic disorders, they may inadvertently exacerbate stress-hyperglycaemia. This research uses model-based methods to quantify the reduction in insulin sensitivity from GCs in critically ill patients, and thus their impact on glycaemic control.

Development of a model-based clinical sepsis biomarker for critically ill patients.

Sepsis occurs frequently in the intensive care unit (ICU) and is a leading cause of admission, mortality, and cost. Treatment guidelines recommend early intervention, however positive blood culture results may take up to 48 h. Insulin sensitivity (S(I)) is known to decrease with worsening condition and could thus be used to aid diagnosis.