Deciphering the spectrum of astrocyte diversity: Insights into molecular, morphological, and functional dimensions in health and neurodegenerative diseases.

Astrocytes are the most abundant and morphologically complex glial cells that play active roles in the central nervous system (CNS). Recent research has identified shared and region-specific astrocytic genes and functions, elucidated the cellular origins of their regional diversity, and uncovered the molecular networks for astrocyte morphology, which are essential for their functional complexity. Reactive astrocytes exhibit a wide range of functional diversity in a context-specific manner in CNS disorders. This review discusses recent advances in understanding the molecular and morphological diversity of astrocytes in healthy individuals and those with neurodegenerative diseases, such as Alzheimer's disease, Huntington's disease, and amyotrophic lateral sclerosis.

Decreased complexity of glucose time series index associated with adverse pregnancy outcomes in gestational diabetes mellitus.

AIM: We investigated the relationship between the complexity of the glucose time series index (CGI) during pregnancy and adverse pregnancy outcomes in women with gestational diabetes mellitus (GDM). MATERIALS AND METHODS: In this retrospective cohort study, 388 singleton pregnant women with GDM underwent continuous glucose monitoring (CGM) at a median of 26.86 gestational weeks. CGI was calculated using refined composite multiscale entropy based on CGM data. The participants were categorized into tertiles according to their baseline CGI (CGI <2.32, 2.32-3.10, ≥3.10). Logistic regression was used to assess the association between CGI and composite adverse outcomes or large for gestational age (LGA). The discrimination performance of CGI was estimated using receiver operating characteristic analysis. RESULTS: Of the 388 participants, 71 (18.3%) had LGA infants and 63 (16.2%) had composite adverse outcomes. After adjustments were made for confounders, compared with those with a high CGI (CGI ≥3.10), participants with a low CGI (CGI <2.32) had a higher risk of composite adverse outcomes (odds ratio: 12.10, 95% confidence interval: 4.41-33.18) and LGA (odds ratio: 12.68, 95% confidence interval: 4.04-39.75). According to the receiver operating characteristic analysis, CGI was significantly better than glycated haemoglobin and conventional CGM indicators for the prediction of adverse pregnancy outcomes (all p < .05). CONCLUSION: A lower CGI during pregnancy was associated with composite adverse outcomes and LGA. CGI, a novel glucose homeostasis predictor, seems to be superior to conventional glucose indicators for the prediction of adverse pregnancy outcomes in women with GDM.

Differences in the Oral Health of Children with Medical Complexity.

OBJECTIVES: Children with medical complexity (CMC), a subgroup of children with special health care needs (CSHCN) with the most serious medical conditions and disabilities, are at risk for negative effects from poor oral health. CSHCN have high rates of poor oral health including cavities. This study aimed to compare oral health status between CMC and CSHCN. METHODS: This was a cross-sectional analysis of the 2016-17 National Survey of Child Health data. CMC and CSHCN were identified using validated algorithms. The primary outcome was oral health status; secondary outcomes included dental service use. Bivariate analyses compared prevalence and service use by medical complexity status. Multivariable logistic regression assessed oral health outcomes by complexity, adjusting for influencing variables. RESULTS: Of 16,178 CSHCN ages 1-17 years, 6% were CMC and 94% were non-CMC CSHCN. Compared to CSHCN, CMC had a higher prevalence of fair/poor teeth conditions (19% vs 9%; p<0.001) and higher odds for fair/poor teeth conditions after adjusting for socioeconomic factors (aOR: 1.54; 95% CI: 1.01-2.34). There was no statically significant difference between groups when assessing cavities, toothache, or receipt of most preventive dental services. CONCLUSION: 1 in 5 CMC are reported by caregivers as having poor oral health including cavities, despite high rates of receiving preventive dental services. After adjusting for socioeconomic factors, medical complexity remained associated with fair or poor teeth conditions. Understanding potentially modifiable targets could further help families of CMC prioritize dental needs and potentially reduce negative effects on overall health.

Fractional-order state space reconstruction: a new frontier in multivariate complex time series.

This paper presents a novel approach to the phase space reconstruction technique, fractional-order phase space reconstruction (FOSS), which generalizes the traditional integer-order derivative-based method. By leveraging fractional derivatives, FOSS offers a novel perspective for understanding complex time series, revealing unique properties not captured by conventional methods. We further develop the multi-span transition entropy component method (MTECM-FOSS), an advanced complexity measurement technique that builds upon FOSS. MTECM-FOSS decomposes complexity into intra-sample and inter-sample components, providing a more comprehensive understanding of the dynamics in multivariate data. In simulated data, we observe that lower fractional orders can effectively filter out random noise. Time series with diverse long- and short-term memory patterns exhibit distinct extremities at different fractional orders. In practical applications, MTECM-FOSS exhibits competitive or superior classification performance compared to state-of-the-art algorithms when using fewer features, indicating its potential for engineering tasks.

A decade of change towards Value-Based Health Care at a Dutch University Hospital: a complexity-informed process study.

BACKGROUND: While healthcare organizations in several countries are embracing Value-Based Health Care (VBHC), there are limited insights into how to achieve this paradigm shift. This study examines the decade-long (2012-2023) change towards VBHC in a pioneering Dutch university hospital. METHOD: Through retrospective, complexity-informed process research, we study how a Dutch university hospital's strategy to implement VBHC evolved, how implementation outcomes unfolded, and the underlying logic behind these developments. Data include the hospital's internal documents (n = 10,536), implementation outcome indicators (n = 4), a survey among clinicians (n = 47), and interviews with individuals contributing to VBHC at the hospital level (n = 20). RESULTS: The change towards VBHC is characterized by three sequential strategies. Initially, the focus was on deep change through local, tailored implementation of multiple VBHC elements. The strategy then transitioned to a hospital-wide program aimed at evolutionary change on a large scale, emphasizing the integration of VBHC into mainstream IT and policies. Recognizing the advantages and limitations of both strategies, the hospital currently adopts a "hybrid" strategy. This strategy delicately combines deep and broad change efforts. The strategy evolved based on accumulated insights, contextual developments and shifts in decision-makers. The complexity of change was downplayed in plans and stakeholder communication. By the end of 2023, 68 (sub)departments engaged in VBHC, enabled to discuss patients' responses to Patient Reported Outcomes Measures (PROMs) during outpatient care. However, clinicians' use of PROMs data showed limitations. While pioneers delved deeper into VBHC, laggards have yet to initiate it. CONCLUSIONS: VBHC does not lend itself to linear planning and is not easily scalable. While there appears to be no golden standard for implementation, blending local and larger-scale actions appears advantageous. Local, deep yet harmonized and system-integrated changes culminate in large scale transformation. Embracing complexity and focusing on the ultimate aims of (re)institutionalization and (re)professionalization are crucial.

The Medical Complexity of Newly Admitted Long-Term Care Residents Before and During the COVID-19 Pandemic in Ontario, British Columbia, and Alberta: A Serial Cross-Sectional Study.

The COVID-19 pandemic had profound effects on the long-term care (LTC) setting worldwide, including changes in admission practices. We aimed to describe the characteristics and medical complexity of newly admitted LTC residents before (March 1, 2019 to February 29, 2020) and during (March 1, 2020 to March 31, 2021) the COVID-19 pandemic via a population-based serial cross-sectional study in Ontario, Alberta, and British Columbia, Canada. With data from the Minimum Data Set 2.0 we characterize the medical complexity of newly admitted LTC residents via the Geriatric 5Ms framework (mind, mobility, medication, multicomplexity, matters most) through descriptive statistics (counts, percentages), stratified by pandemic wave, month, and province. We included 45 756 residents admitted in the year prior to and 35 744 during the first year of the pandemic. We found an increased proportion of residents with depression, requiring extensive assistance with activities of daily living, hip fractures, antipsychotic use, expected to live <6 months, with pneumonia, low social engagement, and admitted from acute care. Our study confirms an increase in medical complexity of residents admitted to LTC during the pandemic and can be used to plan services and interventions and as a baseline for continued monitoring in changes in population characteristics over time.

Social prescribing for individuals with mental health problems: An ethnographic study exploring the mechanisms of action through which community groups support psychosocial well-being.

Background: Social prescribing involves connecting individuals to community groups and activities, often to support their mental health and well-being. It has received increasing support in recent years across the NHS. There is a strong evidence base for the benefits of different types of community activities, including exercise groups, arts groups and nature interventions, on mental health outcomes, however, less is known about how these groups impact mental health and well-being. This study explores through what individual-level mechanisms (the 'how') these groups support psychosocial well-being. Methods: An ethnographic study was conducted over 12-months to explore key shared, individual-level mechanisms across 4 social prescribing community groups: football, singing, gardening and reading. This study focused mostly on those with severe mental illness, whereas previously most social prescribing studies have focused on mild to moderate mental health problems. To frame the findings, a 'multi-level theoretical framework of mechanisms of action' of leisure activities was used. Results: Key shared psychological mechanisms were: increased self-confidence and self-esteem, increased purpose/meaning, increased sense of achievement, experience of pleasure; social mechanisms included: increased social support, formation of friendships and reduced loneliness, enhanced sense of community and belonging; behavioural mechanisms were: increased independence and openness to experience, reduction in addictive behaviours and building healthier habits, increased work-seeking behaviour, and provision of structure & routine. Conclusions: It is hoped that the findings of this study can help referring professionals increase their understanding of exactly how such groups support individuals' mental health, thus enhancing referring practices.

This study uses ethnographic methods, wherein the lead researcher spent over a year participating in 4 different community groups, using interviews, conversations and observation to explore the mental health impact of such groups on individuals' lives. The participants had moderate to severe mental health conditions, and the groups consisted of a reading, gardening, singing and football group. The study explored 'mechanisms' underlying the mental health benefits of these groups. Key shared psychological mechanisms were: increased self-confidence and self-esteem, increased purpose/meaning, increased sense of achievement, experience of pleasure; social mechanisms included: increased social support, formation of friendships and reduced loneliness, enhanced sense of community and belonging; behavioural mechanisms were: increased independence and openness to experience, reduction in addictive behaviours and building healthier habits, increased work-seeking behaviour, and provision of structure & routine. It is hoped that the findings of this study can help referring professionals (e.g. GPs, social workers, link workers) increase their understanding of exactly how such groups support individuals' mental health, thus improving referring skills.

Response inhibition in premotor cortex corresponds to a complex reshuffle of the mesoscopic information network.

Recent studies have explored functional and effective neural networks in animal models; however, the dynamics of information propagation among functional modules under cognitive control remain largely unknown. Here, we addressed the issue using transfer entropy and graph theory methods on mesoscopic neural activities recorded in the dorsal premotor cortex of rhesus monkeys. We focused our study on the decision time of a Stop-signal task, looking for patterns in the network configuration that could influence motor plan maturation when the Stop signal is provided. When comparing trials with successful inhibition to those with generated movement, the nodes of the network resulted organized into four clusters, hierarchically arranged, and distinctly involved in information transfer. Interestingly, the hierarchies and the strength of information transmission between clusters varied throughout the task, distinguishing between generated movements and canceled ones and corresponding to measurable levels of network complexity. Our results suggest a putative mechanism for motor inhibition in premotor cortex: a topological reshuffle of the information exchanged among ensembles of neurons.

In this study, we investigated the dynamics of information transfer among functionally identified neural modules during cognitive motor control. Our focus was on mesoscopic neural activities in the dorsal premotor cortex of rhesus monkeys engaged in a Stop-signal task. Leveraging multivariate transfer entropy and graph theory, we uncovered insights on how behavioral control shapes the topology of information transmission in a local brain network. Task phases modulated the strength and hierarchy of information exchange between modules, revealing the nuanced interplay between neural populations during generated and canceled movements. Notably, during successful inhibition, the network displayed a distinctive configuration, unveiling a novel mechanism for motor inhibition in the premotor cortex: a topological reshuffle of information among neuronal ensembles.

Dragon boat exercise reshapes the temporal-spatial dynamics of the brain.

Although exercise training has been shown to enhance neurological function, there is a shortage of research on how exercise training affects the temporal-spatial synchronization properties of functional networks, which are crucial to the neurological system. This study recruited 23 professional and 24 amateur dragon boat racers to perform simulated paddling on ergometers while recording EEG. The spatiotemporal dynamics of the brain were analyzed using microstates and omega complexity. Temporal dynamics results showed that microstate D, which is associated with attentional networks, appeared significantly altered, with significantly higher duration, occurrence, and coverage in the professional group than in the amateur group. The transition probabilities of microstate D exhibited a similar pattern. The spatial dynamics results showed the professional group had lower brain complexity than the amateur group, with a significant decrease in omega complexity in the α (8-12 Hz) and ß (13-30 Hz) bands. Dragon boat training may strengthen the attentive network and reduce the complexity of the brain. This study provides evidence that dragon boat exercise improves the efficiency of the cerebral functional networks on a spatiotemporal scale.

A comparative evaluation of measures to assess randomness in human-generated sequences.

Whether and how well people can behave randomly is of interest in many areas of psychological research. The ability to generate randomness is often investigated using random number generation (RNG) tasks, in which participants are asked to generate a sequence of numbers that is as random as possible. However, there is no consensus on how best to quantify the randomness of responses in human-generated sequences. Traditionally, psychologists have used measures of randomness that directly assess specific features of human behavior in RNG tasks, such as the tendency to avoid repetition or to systematically generate numbers that have not been generated in the recent choice history, a behavior known as cycling. Other disciplines have proposed measures of randomness that are based on a more rigorous mathematical foundation and are less restricted to specific features of randomness, such as algorithmic complexity. More recently, variants of these measures have been proposed to assess systematic patterns in short sequences. We report the first large-scale integrative study to compare measures of specific aspects of randomness with entropy-derived measures based on information theory and measures based on algorithmic complexity. We compare the ability of the different measures to discriminate between human-generated sequences and truly random sequences based on atmospheric noise, and provide a systematic analysis of how the usefulness of randomness measures is affected by sequence length. We conclude with recommendations that can guide the selection of appropriate measures of randomness in psychological research.

Making the most of life: environmental choice during rearing enhances the ability of laying hens to take opportunities.

Introduction: The potential of aviary housing for improving laying hen (Gallus gallus domesticus) welfare will be constrained if rearing conditions limit the hens' behavioral ability to take opportunities. Incorporating theories on developmental plasticity and animal agency, this study aimed to determine: (1) whether a choice of litter and perch types during rearing would promote long-lasting changes in use of novel locations and resources, and (2) the influence of timing of choice provision. Methods: Laying hen chicks were assigned to either a "Single-choice" (one litter and perch type) or "Multi-choice" environment (four litter and perch types) during "Early" (day 1-week 4) and "Late" rearing (week 5-15). The environments were switched in half of the 16 pens in week 5, resulting in a 2 × 2 factorial design with four choice environment by period combinations. The allocation of perch and litter space was the same across all treatment combinations. In week 16, all groups were moved to standard aviary laying pens (Laying period, week 16-27). Results: When first moved to the laying pens, hens with Multi-choice in either or both rearing periods were quicker to spread out in their pen than hens with Single-choice throughout rearing. Multi-choice in Early rearing also reduced the latency to use novel elevated structures (perches and nests) in the laying pens. Multi-choice during Late rearing increased success in finding and consuming hidden mealworms (tested in weeks 9-17) and increased the proportion of eggs laid on elevated nesting trays. Numerically, hens switched from Multi-choice to Single-choice in week 5 used the outdoor range less than hens switched from Single-choice to Multi-choice. Discussion: These results support the hypothesis that offering multiple resource choices during rearing improves hens' ability to make the most of new opportunities by being more proactive in exploring and exploiting newly available resources. In different opportunity challenges, hens showed positive outcomes in response to choice during Early, Late or both stages of rearing, suggesting that best results can be obtained by offering environmental choice throughout rearing.

Diversity, equity and inclusiveness in healthcare: A primary care perspective.

Addressing Diversity, Equity and Inclusion in health care is a multidimensional challenge. From a US perspective, the third-party payment system has disempowered and depersonalized health-care delivery. The net result is wasteful and inefficient use of human and financial resources, burnout among providers, as well as care inequities. Financial integration at the point of patient care is essential to aligning the needs of patients with advances in medical technology. Complexity theory offers valuable insights into the roles of government, intermediaries and patients. The government must focus on equity as a rule compiler and referee of the system. Patient and providers who are actively engaged in shared decision-making will naturally address the diverse needs of multitudinous communities. Intermediaries address inclusion by connecting resources with the point of care. In a dynamic, emerging health-care system that serves diverse communities, patient and community-based financing, vouchers and defined contributions are necessary first steps in addressing cultural diversity, inclusion and equity.

Combating COVID-19 health disparities in Black, Indigenous, and People of Colour Communities-A call for critical systems thinking.

RATIONALE: The Black, Indigenous, and People of Colour populations in the United States are disproportionately affected by the emerging health threat SARS-CoV-2, which causes COVID-19. AIMS AND OBJECTIVES: This paper aims to demonstrate the usefulness of critical systems thinking by using scenario planning based on epidemiological data and tying epidemiology with soft systems methodology to investigate COVID-19 disparities among disproportionately affected Black, Indigenous, and People of Colour populations. METHODS: Using a review of the COVID-19 literature and publicly available US COVID-19 data, critical systems thinking is applied in a scenario planning example and a call to link soft systems methodology with epidemiology. RESULTS: According to the four plausible Endgame scenarios, levels of community transmission as well as the current state transmission are based on the driving forces of the scenarios. In addition, soft systems methodology explores the effect on stakeholders and strengthens the picture of disease burden beyond sole reliance on traditional data sources. CONCLUSION: This analysis underscores employing critical systems thinking to critically assess diverse methods appropriate for the ongoing complexity of global crises. It is argued that critically engaged subjectivity should be given space alongside data-dependent objectivity. COVID-19 disparities are reliant on the social determinants of health's effects as driving forces on disease transmission in Black, Indigenous, and People of Colour populations. It is moreover argued that critical systems thinking is demonstrated by linking epidemiological evidence with scenario planning and soft systems methodology. This in turn supports a critical systems thinking approach to uncover the state of health disparities among minoritized communities under COVID-19.

Harnessing health information technology to promote equitable care for patients with limited English proficiency and complex care needs.

BACKGROUND: Patients with language barriers encounter healthcare disparities, which may be alleviated by leveraging interpreter skills to reduce cultural, language, and literacy barriers through improved bidirectional communication. Evidence supports the use of in-person interpreters, especially for interactions involving patients with complex care needs. Unfortunately, due to interpreter shortages and clinician underuse of interpreters, patients with language barriers frequently do not get the language services they need or are entitled to. Health information technologies (HIT), including artificial intelligence (AI), have the potential to streamline processes, prompt clinicians to utilize in-person interpreters, and support prioritization. METHODS: From May 1, 2023, to June 21, 2024, a single-center stepped wedge cluster randomized trial will be conducted within 35 units of Saint Marys Hospital & Methodist Hospital at Mayo Clinic in Rochester, Minnesota. The units include medical, surgical, trauma, and mixed ICUs and hospital floors that admit acute medical and surgical care patients as well as the emergency department (ED). The transitions between study phases will be initiated at 60-day intervals resulting in a 12-month study period. Units in the control group will receive standard care and rely on clinician initiative to request interpreter services. In the intervention group, the study team will generate a daily list of adult inpatients with language barriers, order the list based on their complexity scores (from highest to lowest), and share it with interpreter services, who will send a secure chat message to the bedside nurse. This engagement will be triggered by a predictive machine-learning algorithm based on a palliative care score, supplemented by other predictors of complexity including length of stay and level of care as well as procedures, events, and clinical notes. DISCUSSION: This pragmatic clinical trial approach will integrate a predictive machine-learning algorithm into a workflow process and evaluate the effectiveness of the intervention. We will compare the use of in-person interpreters and time to first interpreter use between the control and intervention groups. TRIAL REGISTRATION: NCT05860777. May 16, 2023.

What does it mean for consciousness to be multidimensional? A narrative review.

A recent development in the psychological and neuroscientific study of consciousness has been the tendency to conceptualize consciousness as a multidimensional phenomenon. This narrative review elucidates the notion of dimensionality of consciousness and outlines the key concepts and disagreements on this topic through the viewpoints of several theoretical proposals. The reviewed literature is critically evaluated, and the main issues to be resolved by future theoretical and empirical work are identified: the problems of dimension selection and dimension aggregation, as well as some ethical considerations. This narrative review is seemingly the first to comprehensively overview this specific aspect of consciousness science.

Deconstructing nursing's paradoxical relationship with the concept of complexity.

Although nursing seems to understand itself and its practice as complex, the literature is less clear about what this actually means. While complexity is discussed as an attribute of nursing, it is also suggested that complexity in nursing remains misunderstood and poorly articulated, is devalued, is not considered as a measure of health outcomes and remains invisible. Despite the overarching lack of a definition, some nurse scholars have conceptualized complexity as a complex intervention. For these authors, complexity becomes a complex intervention defined as that which is composed of component parts interacting in a variety of ways that influence the delivery of and outcomes of health-related interventions for populations. Conceptualizing complexity as a complex intervention forces nursing to embrace and adopt a received interpretation of complexity as expressed through complexity theory and complexity science. While complexity theory may afford us some tools for thinking about complexity, when we deconstruct nursing complexity to explicitly determinate and quantifiable tasks, this artificially narrowed orientation to complexity reveals an oversimplified explanation of the complexities associated with nursing and serves to blind us to its real qualities. Through a consideration of complexity from a Western philosophical tradition, I demonstrate that when nursing adopts the received interpretation of complexity as a complex intervention, this perspective on complexity contains nursing epistemologically and ontologically. I offer an extended conceptualization of complexity framed upon the consideration that nurses assume complexity and do not reduce it; that nurses have the capacity to not be paralysed by complexity and have developed logics to mobilize it in productive ways. Mobilizing complexity through navigating paradox and contradiction shapes an orientation to complexity that embraces an extended epistemology. This extended epistemology is characterized by a 'yes/and' mindset that expresses the dynamic and generative relationship between forms of knowledge which reflects complexity that characterizes nursing.

Where do families turn? Ethical dilemmas in the care of chronically critically Ill children.

Advancements in early diagnosis and novel treatments for children with complex and chronic needs have improved their chances of survival. But many survive with complex medical needs and ongoing medical management in the setting of prognostic uncertainty. Their medical care relies more and more on preference-sensitive decisions, requiring medical team and family engagement in ethically challenging situations. Many families are unprepared as they face these ethical challenges and struggle to access relevant ethical resources. In this paper, Timmy's narrative, situated in the context of what is known about ethical challenges in the care of children with chronic critical illness (CCI), serves as a case study of the gap in available ethical resources to guide families in their approach to difficult decision making for children with significant medical complexity and CCI. Our author group, inclusive of parents of children with complex medical needs and medical professionals, identifies domains of ethical challenges facing families of children with CCI and we highlight the development of family/caregiver-oriented ethics resources as an essential expansion of pediatric bioethics.

«I can't imagine it without my nurse¼: Experiences of people with chronic kidney disease in the evaluation process as kidney transplant candidates.

This qualitative study aimed to explore the experiences of 11 adults with chronic kidney disease (CKD) undergoing evaluation for kidney transplant (KT) and examine the role played by the nurse in the process. Employing a descriptive phenomenology approach, semi-structured interviews were conducted between October 2022 and July 2023. Thematic analysis, facilitated by Atlas. ti software, revealed a systemic management diagram with "The candidate for kidney transplant and their reality" at the center, followed by "The process of chronic kidney disease and kidney transplantation," and concluding with the most distal category centered on "The kidney transplant access nurse." This organizational framework provided insights into the layers of relationships between emerging themes. The findings underscored the complexity and multidimensionality of the CKD and KT process, emphasizing the nurse's pivotal role as a guide and protector throughout the evaluation process for accessing kidney transplantation. The convergence of results with existing literature highlighted the need to address challenges such as lack of time, resources, and emotional support to enhance the quality of care. Recognizing the nurse's crucial importance in this process, the study emphasizes the significance of addressing these challenges to improve patient care and calls for attention to the nurse's role in guiding individuals through the intricate journey of CKD and kidney transplantation.

Assessing biological self-organization patterns using statistical complexity characteristics: a tool for diffusion tensor imaging analysis.

OBJECT: Diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI) are well-known and powerful imaging techniques for MRI. Although DTI evaluation has evolved continually in recent years, there are still struggles regarding quantitative measurements that can benefit brain areas that are consistently difficult to measure via diffusion-based methods, e.g., gray matter (GM). The present study proposes a new image processing technique based on diffusion distribution evaluation of López-Ruiz, Mancini and Calbet (LMC) complexity called diffusion complexity (DC). MATERIALS AND METHODS: The OASIS-3 and TractoInferno open-science databases for healthy individuals were used, and all the codes are provided as open-source materials. RESULTS: The DC map showed relevant signal characterization in brain tissues and structures, achieving contrast-to-noise ratio (CNR) gains of approximately 39% and 93%, respectively, compared to those of the FA and ADC maps. DISCUSSION: In the special case of GM tissue, the DC map obtains its maximum signal level, showing the possibility of studying cortical and subcortical structures challenging for classical DTI quantitative formalism. The ability to apply the DC technique, which requires the same imaging acquisition for DTI and its potential to provide complementary information to study the brain's GM structures, can be a rich source of information for further neuroscience research and clinical practice.

The Impact of Coronavirus Disease 2019 on Nursing Education: Evidence, Experience, and Lessons Learned.

This article examines the multifaceted impact of the coronavirus disease 2019 pandemic on nursing education, with a focus on implications for critical care. Issues including the rapid transition to remote learning, stress and burnout, disengagement, challenges in clinical education, ethical dilemmas, and the influence of workforce dynamics on nursing education are discussed. The article explores challenges, opportunities, and the invaluable lessons learned from this unprecedented crisis. Understanding the evolving dynamics is essential for nursing education and practice, offering a pathway toward a more resilient and promising future for both individuals and the nursing profession as a whole.