Efficacy of intraoperative blood salvage and autotransfusion in living-donor liver transplantation: a retrospective cohort study.

BACKGROUND: Liver transplantation (LT) may be associated with massive blood loss and the need for allogeneic blood transfusion. Intraoperative blood salvage autotransfusion (IBSA) can reduce the need for allogeneic blood transfusion. This study aimed to investigate the effectiveness of blood salvage in LT. METHODS: Among 355 adult patients who underwent elective living-donor LT between January 1, 2019, and December 31, 2022, 59 recipients without advanced hepatocellular carcinoma received IBSA using Cell Saver (CS group). Based on sex, age, model for end-stage liver disease (MELD) score, preoperative laboratory results, and other factors, 118 of the 296 recipients who did not undergo IBSA were matched using propensity score (non-CS group). The primary outcome was the amount of intraoperative allogenic red blood cell (RBC) transfusion. Comparisons were made between the two groups regarding the amount of other blood components transfused and postoperative laboratory findings. RESULTS: The transfused allogeneic RBC for the CS group was significantly lower than that of the non-CS group (1,506.0 vs. 1,957.5 ml, P = 0.026). No significant differences in the transfused total fresh frozen plasma, platelets, cryoprecipitate, and estimated blood loss were observed between the two groups. The postoperative allogeneic RBC transfusion was significantly lower in the CS group than in the non-CS group (1,500.0 vs. 2,100.0 ml, P = 0.039). No significant differences in postoperative laboratory findings were observed at postoperative day 1 and discharge. CONCLUSIONS: Using IBSA during LT can effectively reduce the need for perioperative allogeneic blood transfusions without causing subsequent coagulopathy.

The Impact of Persistent Noise Exposure under Inflammatory Conditions.

The aim of this study was to investigate the impact of noise exposure in an intensive care unit (ICU) environment on the development of postoperative delirium in a mouse model that mimics the ICU environment. Additionally, we aimed to identify the underlying mechanisms contributing to delirium and provide evidence for reducing the risk of delirium. In this study, to mimic an ICU environment, lipopolysaccharide (LPS)-injected sepsis mouse models were exposed to a 75 dB noise condition. Furthermore, we assessed neurobehavioral function and observed the level of neuroinflammatory response and blood-brain barrier (BBB) integrity in the hippocampal region. The LPS-injected sepsis mouse model exposed to noise exhibited increased anxiety-like behavior and cognitive impairment. Moreover, severe neuroinflammation and BBB disruption were detected in the hippocampal region. This study provides insights suggesting that persistent noise exposure under systemic inflammatory conditions may cause cognitive dysfunction and anxiety- like behavior via the mediation of BBB disruption and neuroinflammation. As a result, we suggest that the detailed regulation of noise exposure may be required to prevent the development of postoperative delirium.

Family caregivers' responses to a visitation restriction policy at a Korean surgical intensive care unit before and during the coronavirus disease 2019 pandemic.

BACKGROUND: Since the COVID-19 pandemic, restricting family visits in the ICU has increased concerns regarding negative psychosocial consequences to patients and families. OBJECTIVES: To compare the quality of life, depressive symptoms, and emotions in family caregivers of ICU patients before and during the COVID-19 pandemic, and to explore families' perceptions and suggestions for the visitation. METHODS: A cross-sectional descriptive survey was conducted in 99 family caregivers of adult surgical ICU patients from an urban academic medical center in South Korea (February to July 2021). The WHO's Quality of Life-BREF, Center for Epidemiologic Studies Depression, and Visual Analogue Scale were used to assess quality of life, depressive symptoms, and emotions, respectively. The Family Perception Checklist was used to assess families' perceptions and suggestions about the visitation restriction. Results were compared with the data from our previous survey (n = 187) in 2017. RESULTS: Family caregivers were mostly women (n = 59), adult children (n = 43) or spouse (n = 38) of patients with mean age of 47.34 years. Family caregivers surveyed during the pandemic reported worsening sadness (54.66 ± 28.93, 45.58 ± 29.44, P = 0.005) and anxiety (53.86 ± 30.07, 43.22 ± 29.02, P = 0.001) than those who were surveyed in. While majority of families were satisfied with the visitation restrictions (86.9%), only 50.5% were satisfied with the amount of information provided on the patient's condition. CONCLUSIONS: Visitation restriction is necessary during the COVID-19 pandemic despite sadness and anxiety reported in caregivers. Hence, alternative visitation strategies are needed to mitigate psychological distress and provide sufficient information to ICU family caregivers.

Prediction of drugs having opposite effects on disease genes in a directed network.

BACKGROUND: Developing novel uses of approved drugs, called drug repositioning, can reduce costs and times in traditional drug development. Network-based approaches have presented promising results in this field. However, even though various types of interactions such as activation or inhibition exist in drug-target interactions and molecular pathways, most of previous network-based studies disregarded this information. METHODS: We developed a novel computational method, Prediction of Drugs having Opposite effects on Disease genes (PDOD), for identifying drugs having opposite effects on altered states of disease genes. PDOD utilized drug-drug target interactions with 'effect type', an integrated directed molecular network with 'effect type' and 'effect direction', and disease genes with regulated states in disease patients. With this information, we proposed a scoring function to discover drugs likely to restore altered states of disease genes using the path from a drug to a disease through the drug-drug target interactions, shortest paths from drug targets to disease genes in molecular pathways, and disease gene-disease associations. RESULTS: We collected drug-drug target interactions, molecular pathways, and disease genes with their regulated states in the diseases. PDOD is applied to 898 drugs with known drug-drug target interactions and nine diseases. We compared performance of PDOD for predicting known therapeutic drug-disease associations with the previous methods. PDOD outperformed other previous approaches which do not exploit directional information in molecular network. In addition, we provide a simple web service that researchers can submit genes of interest with their altered states and will obtain drugs seeming to have opposite effects on altered states of input genes at http://gto.kaist.ac.kr/pdod/index.php/main . CONCLUSIONS: Our results showed that 'effect type' and 'effect direction' information in the network based approaches can be utilized to identify drugs having opposite effects on diseases. Our study can offer a novel insight into the field of network-based drug repositioning.

Context-based resolution of semantic conflicts in biological pathways.

BACKGROUND: Interactions between biological entities such as genes, proteins and metabolites, so called pathways, are key features to understand molecular mechanisms of life. As pathway information is being accumulated rapidly through various knowledge resources, there are growing interests in maintaining the integrity of the heterogeneous databases. METHODS: Here, we defined conflict as a status where two contradictory pieces of evidence (i.e. 'A increases B' and 'A decreases B') coexist in a same pathway. This conflict damages unity so that inference of simulation on the integrated pathway network might be unreliable. We defined rule and rule group. A rule consists of interaction of two entities, meta-relation (increase or decrease), and contexts terms about tissue specificity or environmental conditions. The rules, which have the same interaction, are grouped into a rule group. If the rules don't have a unanimous meta-relation, the rule group and the rules are judged as being conflicting. RESULTS: This analysis revealed that almost 20% of known interactions suffer from conflicting information and conflicting information occurred much more frequently in the literature than the public database. CONCLUSIONS: By identifying and resolving the conflicts, we expect that pathway databases can be cleaned and used for better secondary analyses such as gene/protein annotation, network dynamics and qualitative/quantitative simulation.