Advances in experimental medicine and biology最新文献

In continuous-wave electron paramagnetic resonance (CW-EPR) imaging, many spectral projections are required to accurately reconstruct four-dimensional (4D) spectral-spatial data, which are used for oxygen mapping in tumors. The ability to obtain fewer spectral projections with less degradation of the resultant image quality is desirable because acquiring many spectral projections leads to a longer time for EPR imaging acquisition. The algebraic reconstruction technique (ART) is one of the most powerful image-reconstruction techniques for 4D spectral-spatial imaging. ART can be applied to incomplete sets of spectral projections. However, data sets of many spectral projections can provide reconstructed images of higher quality. In this study, we aimed to enhance acquisition speed by randomly collecting spectral projections and subsequently synthesizing those that had not been recorded. We applied this strategy to a numerical phantom and a mouse Hs766T xenograft model to confirm the feasibility of our concept. Random acquisition can prevent image degradation in linewidth mapping, which is the foundation for oxygen mapping with CW-EPR.

Background: The diaphragm muscle is the primary muscle involved in inspiration and is unique to mammals. Because the diaphragm is a constantly active muscle, its contraction may depend on oxidative phosphorylation and O₂ supply to create adenosine triphosphate. This study aimed to evaluate the role of intrinsic vasodilator nitric oxide (NO) in diaphragm O₂ dynamics.

Methods: Wistar male rats (n = 6, 10 wks old, 311 ± 14 g) were mechanically ventilated under isoflurane anesthesia. The diaphragm was exposed to measure microvascular partial O₂ pressure (PO₂mv) by phosphorescence quenching technique during electrical stimulation-induced diaphragm contractions (6 V, 2 ms, 2 Hz, 180 s). The 180 s of muscle contractions and PO₂mv measurement were repeated 10 min after endothelial NO synthase inhibition by the intra-arterial infusion of nitro-l-arginine methyl ester (L-NAME; eNOS inhibitor). The PO₂mv change during the transition from rest to contraction was fitted to a nonlinear regression model. Time delay, time constant (tau), rate constant (K), and nadir in PO₂mv were calculated and compared before and after eNOS inhibition. [Results] Diaphragm PO₂mv decreased during contractions both before and after eNOS inhibition. The time delay and K were not different before and after L-NAME. However, the L-NAME administration decreased the tau and nadir in PO₂mv (tau, 7.61 [5.18-13.41] vs. 3.36 [1.81-5.57] s; nadir, 7.45 [1.41-14.85] vs. 3.93 [0.89-9.47] mmHg; before vs. after eNOS inhibition, median [25-75 percentiles], P < 0.05, respectively).

Discussion: The time constant in PO₂mv is determined by oxygen supply to the capillaries and oxygen utilization. The faster time constant and lower nadir in PO₂mv possibly indicate the slower and lower oxygen supply to diaphragm capillaries after eNOS inhibition.

Conclusion: The NO has a crucial role in the diaphragm oxygen dynamics of intact rats.

Mobilization of critically ill patients within 72 hours of admission is associated with improved outcomes. Recently, the predictive value of regional cerebral oxygen saturation (rSO₂) measured via near-infrared spectroscopy (NIRS) has been emphasized. This study aimed to evaluate the differences in rSO₂ values depending on the availability of mobilization within 72 hours in the ICU. Eighty patients admitted to the emergency center between June 2020 and December 2022 were analyzed. Patients were assessed based on whether they could be mobilized within 72 hours (early mobilization group, EM) or later (non-early mobilization group, non-EM). During mobilization, prefrontal rSO₂ values were monitored. Regarding patient background, significant differences were noted between the groups, including delayed release in non-EM patients. rSO₂ values varied significantly, with the lowest values in the first half of end-sitting in both groups (non-EM 56.5 ± 4.8%, EM 58.6 ± 4.3%, p < 0.05). The rSO₂ value was also lower in the non-EM group than in the EM group (P < 0.014). A weak correlation was observed between rSO₂ and the number of days to first mobilization (r = -0.251, p = 0.025). The rSO₂ value may serve as a potential marker to guide the timing of mobilization in ICU patients.

A theoretical framework is presented to clarify the role of architectural and structural forces in ion selectivity. It expresses the relative free energy of bound ions in terms of a reduced subsystem corresponding to the local degrees of freedom coupled to the rest of the protein. The latter is separated into a first contribution that includes all the forces keeping the ion and the coordinating ligands confined to a microscopic sub-volume but do not prevent the ligands from adapting to a smaller ion, while the second contribution regroups the remaining forces that serve to dictate the precise geometry of the coordinating ligands best adapted to a given ion. The theoretical framework makes it possible to delineate two important limiting cases. In the limit where the geometric forces are dominant (rigid binding site), selectivity is controlled via the cavity size according to the familiar "snug-fit" mechanism of host-guest chemistry. In the limit where the geometric forces are negligible, the ion and ligands behave as a dynamical "confined droplet" that is free and adapt to the ion's size. In this case, selectivity is controlled by the number and the chemical type of ion-coordinating ligands.

Free energy calculations play a vital role in understanding protein behaviour at the molecular level. From protein folding and stability to ligand binding and enzyme catalysis, these calculations provide quantitative insights that are indispensable for both basic research and practical applications in fields such as drug discovery, protein engineering, and biotechnology. Due to the complex energy landscapes of proteins, traditional molecular dynamics simulations often fail to explore rare events or overcome high-energy barriers effectively. Enhanced sampling techniques, such as metadynamics, umbrella sampling, or replica exchange molecular dynamics, were developed to address these challenges, allowing for more efficient exploration of conformational space and improved accuracy in free energy predictions. These methods accelerate the sampling of relevant states and transitions, making it feasible to capture rare but biologically significant events. Recently, machine learning has also begun playing a crucial role in enhancing sampling efficiency, reducing the need for extensive computational resources. As computational power continues to increase and machine learning techniques are integrated with enhanced sampling algorithms, the scope and accuracy of free energy calculations will significantly improve, opening new avenues for more precise understanding and prediction of molecular interactions and biological processes.

This chapter explores the pivotal roles of planar lipid bilayers and liposomes in advancing our understanding of protein function. These artificial membrane systems serve as essential models that mimic natural cellular environments, providing a versatile platform for studying protein-lipid interactions. We delve into methods for assembling planar lipid bilayers and liposomes, examining their composition and diversity, and the techniques employed to integrate membrane proteins for functional analysis. We consider the influence of osmotic dynamics on membrane behavior and protein interactions through pressure gradients and review studies of signal transduction in artificial membrane systems aimed at elucidating how proteins interact with lipids to mediate cellular communication. We also discuss the contributions of these systems to structural studies, involving techniques like cryo-electron microscopy and X-ray crystallography, to reveal high-resolution insights into membrane protein conformations. Discussing challenges and limitations, we review the biological relevance and technical constraints that shape experimental outcomes. Looking forward, we consider innovations in lipid bilayer model systems and new research directions that promise to expand their utility. This chapter underscores the continued importance of these systems as indispensable tools in unraveling the complexities of protein function within biological membranes.

Undergraduate nursing education is an important starting point for promoting patient safety in the areas of knowledge, attitude, and skills in the preparation of future nurses. Nursing students are considered an integral and necessary component of the health care system. Therefore, exposing them to the concept of patient safety will help new graduates in the workplace to become ambassadors for promoting a culture of safety which will be key to reducing patient mortality and the level of adverse events actions.The purpose of this research is to investigate the attitudes of nursing students towards patient safety. A qualitative study was conducted with audio-recorded, face-to-face, semistructured interviews lasting an average of 15 min.The "under study" population consists of students of the Nursing Department of the University of Thessaly and was obtained by convenience sampling.The number of interviews (n = 17) conducted was determined after data saturation was reached. From the responses of the participants, important conclusions about patient safety emerge. The term patient safety mainly refers to the protection of the patient at a physical and psychological level, including falls, medication errors, and other risks. Factors affecting patient safety include staff training, working conditions, and collaboration. Nurse education is highlighted as important in preparing for safe care. Finally, reporting and recording errors are considered vital to improving the quality of care, although many factors such as fear dominate the decision to report errors. Overall, patient safety is a vital aspect of nursing practice and requires professional education, collaboration, and commitment to error reporting.

Preeclampsia is a multifaceted pregnancy syndrome that significantly contributes to maternal and neonatal morbidity and mortality. Characterized by hypertension, proteinuria, and multi-organ involvement, it is influenced by genetic, immunological, and environmental factors. Recent research has highlighted the role of epigenetic modifications, such as DNA methylation, histone modifications, and microRNA regulation, in the pathogenesis of preeclampsia. This study examines how these epigenetic mechanisms impact gene expression in the placenta, contributing to abnormal trophoblastic invasion, immune maladaptation, and endothelial dysfunction observed in preeclampsia. Focus is given to the role of altered DNA methylation patterns, such as those observed in the HSD11B2 and IGF2 genes, which could serve as potential biomarkers for early diagnosis. Understanding these epigenetic changes offers opportunities for developing novel diagnostic tools and therapeutic interventions, with the potential to improve pregnancy outcomes for affected women and their infants.

With opioids being increasingly prescribed and illicit opioids being misused, substance use disorder has become a growing public health concern. The impacts of the opioid epidemic have been devastating, especially for pregnant people, infants, and children. Pre- and perinatal opioid exposure is complex. Opioids affect multiple body systems and have detrimental effects on the placenta, brain, and immune system. Pharmacological properties make each class of opioid unique, thereby compounding effects on development based on the type, receptors engaged, or combination of drugs used. Accordingly, animal models are necessary to elucidate the mechanisms, pathways, and developmental processes affected by opioid exposure during and after pregnancy. However, the complexity of opioid use in humans means that preclinical modeling is also complicated with variation by species type, duration, and timing of exposure, and combinations of opioids studied. In this chapter, we present a summary of numerous, intricate preclinical models of perinatal opioid exposure. Specifically, we discuss (1) the inherent variability and difficulty in modeling complex patterns of opioid use by pregnant and peripartum people, (2) provide background on opioids and their receptors, and (3) present evidence for long-term changes in brain structure and function secondary to prenatal opioid exposure. Together, we emphasize the significant immunological, structural, and cognitive changes documented in animals and humans after opioid exposure to highlight the potential for translatability and illustrate a path forward for improved mechanistic and therapeutic discovery.

This chapter provides an introduction and overview of animal models that have been used to investigate the teratogenic effects of alcohol. Since the first model was developed in 1899, prenatal alcohol exposure (PAE) has been studied in species ranging from invertebrates to primates. Here, we contextualize and outline critical experimental considerations, including blood alcohol concentration, timing of exposure, and routes of ethanol administration. Detailed comparisons of vertebrate and invertebrate models, particularly rodents, guinea pigs, and non-human primates, highlight their translational relevance and limitations in replicating human gestational processes, and the pathophysiology of fetal alcohol spectrum disorder (FASD). This chapter also examines behavioral outcomes across motor, executive, cognitive, and social domains, illustrating how PAE disrupts neural development and function throughout the lifespan. Collectively, we emphasize the importance of recognizing the pros and cons when selecting an animal model and experimental paradigm.