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Heat stress alters metabolic pathways and nitric oxide signaling in keratinocytes under hyperglycemia
No full textAbstract
Background:
Diabetic patients are particularly vulnerable to heat exposure due to impaired thermoregulation and reduced sweating ability. The impact of heat on skin cell function, particularly keratinocytes, is poorly understood. Recent studies highlight the critical role of nitric oxide (NO) in thermoregulation and heat stress responses, but its specific involvement in keratinocyte responses and metabolic profiles remains unexplored.
Objective:
This proof-of-concept study investigates the metabolic profiles of HaCat keratinocytes under normal and high-glucose conditions during varied heat exposures.
Methods:
We conducted experiments using a metabolomics approach, NO levels assessments, western blot analysis, and evaluations of mitochondrial morphology.
Results:
Our findings indicate that acute heat exposure over 90 minutes significantly alters metabolic pathways, particularly amino acid metabolism (including arginine, valine, leucine, and serine), the pyrimidine metabolite uracil, and glycolysis, notably lactate production. Arginine metabolism was uniquely affected by high glucose combined with heat, aligning with previous clinical observations.
Furthermore, we discovered that changes in NO production correlated with heat exposure duration, and that NO levels in extracellular vesicles (EVs) from HaCat cells were inversely related to intracellular NO levels. Additionally, we observed alterations in HSP-70 protein expression and mitochondrial morphology, supporting cellular adaptation to thermal stress.
Conclusion:
This study is the first to demonstrate heat-induced metabolic changes in keratinocytes involving arginine and NO, highlighting their potential as clinical biomarkers for thermal stress adaptation, with implications for both healthy individuals and diabetic patients.Abstract
Background:
Diabetic patients are particularly vulnerable to heat exposure due to impaired thermoregulation and reduced sweating ability. The impact of heat on skin cell function, particularly keratinocytes, is poorly understood. Recent studies highlight the critical role of nitric oxide (NO) in thermoregulation and heat stress responses, but its specific involvement in keratinocyte responses and metabolic profiles remains unexplored.
Objective:
This proof-of-concept study investigates the metabolic profiles of HaCat keratinocytes under normal and high-glucose conditions during varied heat exposures.
Methods:
We conducted experiments using a metabolomics approach, NO levels assessments, western blot analysis, and evaluations of mitochondrial morphology.
Results:
Our findings indicate that acute heat exposure over 90 minutes significantly alters metabolic pathways, particularly amino acid metabolism (including arginine, valine, leucine, and serine), the pyrimidine metabolite uracil, and glycolysis, notably lactate production. Arginine metabolism was uniquely affected by high glucose combined with heat, aligning with previous clinical observations.
Furthermore, we discovered that changes in NO production correlated with heat exposure duration, and that NO levels in extracellular vesicles (EVs) from HaCat cells were inversely related to intracellular NO levels. Additionally, we observed alterations in HSP-70 protein expression and mitochondrial morphology, supporting cellular adaptation to thermal stress.
Conclusion:
This study is the first to demonstrate heat-induced metabolic changes in keratinocytes involving arginine and NO, highlighting their potential as clinical biomarkers for thermal stress adaptation, with implications for both healthy individuals and diabetic patients
Ecosystem health and planetary well-being
No full textAbstract
Healthy ecosystems support the well-being of all organisms on Earth. Yet, the overexploitation of natural resources for human needs and profit has resulted in widespread ecosystem degradation, loss of biodiversity, and climate emergency, which pose fundamental threats to planetary well-being. Impoverished ecosystems may become dysfunctional and fail to provide for the needs of many organisms, including humans and wildlife. Changes in ecosystem functioning and wildlife distributions affect the prevalence and spread of pathogens, with consequences for the health and well-being of human and wildlife communities alike. Increasing contact between humans and domestic and wild animals enable pathogen spillover, while global trade and travel distribute pathogens to new areas. Human activities thus provide favourable conditions for pandemics and trigger cascading consequences for ecosystems worldwide. A better integration of ecosystem health into public health and conservation planning could alleviate disease burden and improve well-being of all organisms on the planet.Abstract
Healthy ecosystems support the well-being of all organisms on Earth. Yet, the overexploitation of natural resources for human needs and profit has resulted in widespread ecosystem degradation, loss of biodiversity, and climate emergency, which pose fundamental threats to planetary well-being. Impoverished ecosystems may become dysfunctional and fail to provide for the needs of many organisms, including humans and wildlife. Changes in ecosystem functioning and wildlife distributions affect the prevalence and spread of pathogens, with consequences for the health and well-being of human and wildlife communities alike. Increasing contact between humans and domestic and wild animals enable pathogen spillover, while global trade and travel distribute pathogens to new areas. Human activities thus provide favourable conditions for pandemics and trigger cascading consequences for ecosystems worldwide. A better integration of ecosystem health into public health and conservation planning could alleviate disease burden and improve well-being of all organisms on the planet
Induced abortion, miscarriage, and the risk of breast cancer—A registry-based study from Finland
No full textAbstract
Introduction:
The potential effect of induced abortion and miscarriage on the risk of breast cancer has remained debated and has been a persistent source of misinformation. Many previous studies have been small and based on self-reported data. We assessed the associations of induced abortion and miscarriage with the risk of pre- and postmenopausal breast cancer using high-quality Finnish registry data.
Material and Methods:
This is a case–control study based on population-based registry data. It includes 31 687 women with breast cancer diagnosed between 1972 and 2021, and their 158 433 female population controls matched by birth year and parity. Data on induced abortions, miscarriages, deliveries, use of postmenopausal hormone therapy, socioeconomic status (SES), and occupation were collected from the Finnish national registries. Multivariate conditional logistic regression analysis was performed.
Results:
The odds ratio (OR) of breast cancer among women with a history of induced abortion as compared with women with no history of induced abortion was 1.01 (95% confidence interval [CI] 0.92–1.10) in premenopausal (age <50 years) and 0.96 (95% CI 0.87–1.07) in postmenopausal (≥50 years) women. The corresponding ORs for miscarriage were 1.02 (95% CI 0.89–1.16) and 0.93 (95% CI 0.80–1.09). The OR did not vary significantly by the number of induced abortions or miscarriages, nor by the age at the time of first induced abortion or miscarriage.
Conclusion:
A history of induced abortion and miscarriage, regardless of their number or age of the woman, is not associated with an increased risk of subsequent pre- or postmenopausal breast cancer.Abstract
Introduction:
The potential effect of induced abortion and miscarriage on the risk of breast cancer has remained debated and has been a persistent source of misinformation. Many previous studies have been small and based on self-reported data. We assessed the associations of induced abortion and miscarriage with the risk of pre- and postmenopausal breast cancer using high-quality Finnish registry data.
Material and Methods:
This is a case–control study based on population-based registry data. It includes 31 687 women with breast cancer diagnosed between 1972 and 2021, and their 158 433 female population controls matched by birth year and parity. Data on induced abortions, miscarriages, deliveries, use of postmenopausal hormone therapy, socioeconomic status (SES), and occupation were collected from the Finnish national registries. Multivariate conditional logistic regression analysis was performed.
Results:
The odds ratio (OR) of breast cancer among women with a history of induced abortion as compared with women with no history of induced abortion was 1.01 (95% confidence interval [CI] 0.92–1.10) in premenopausal (age <50 years) and 0.96 (95% CI 0.87–1.07) in postmenopausal (≥50 years) women. The corresponding ORs for miscarriage were 1.02 (95% CI 0.89–1.16) and 0.93 (95% CI 0.80–1.09). The OR did not vary significantly by the number of induced abortions or miscarriages, nor by the age at the time of first induced abortion or miscarriage.
Conclusion:
A history of induced abortion and miscarriage, regardless of their number or age of the woman, is not associated with an increased risk of subsequent pre- or postmenopausal breast cancer
Delineating seasonal shifts in reindeer habitat and diet selection by integrating GPS telemetry and stable isotope analysis
No full textAbstract
Seasonal changes shape herbivore behaviour by altering forage availability and habitat conditions; however, few studies integrate diet and habitat selection data across temporal scales. This study uses seasonality as a unifying framework to combine fine-scale GPS-based habitat selection data with broader-scale dietary information from stable isotope analysis (δ13C, δ15N) of hairs in semi-domesticated reindeer Rangifer tarandus tarandus. Thresholds introduced within this framework detect seasonal shifts in habitat and diet selection and classify foraging strategies along a specialist–generalist continuum. Despite individual variability, most individuals exhibited pronounced seasonal changes between spring/early summer (SES) and late summer/autumn (LSA), consistent with generalist foraging strategies. Habitat selection models revealed reduced avoidance of rugged terrain and increased use of mires and bogs from SES to LSA. Concurrently, isotopic enrichment and niche expansion reflected a dietary shift from δ15N- and δ13C-depleted plants (e.g. lichens, shrubs, deciduous vegetation) to more enriched forage types such as sedges, grasses, horsetails, and mushrooms. We assessed whether individual-level shifts in diet and habitat use were linked and found an inverse correlation between the shifts in terrain ruggedness avoidance and dietary change in approximately 67% of individuals, suggesting that behavioural flexibility facilitates seasonal transitions. By integrating spatial and isotopic data, this study overcomes the limitations of single-method approaches and provides a more nuanced understanding of the seasonal foraging dynamics of a keystone Arctic and boreal ungulate. The findings highlight the plasticity of reindeer foraging within a variable environment and suggest a capacity to respond to environmental changes. This framework also offers broader applications for investigating behavioural responses and ecological strategies in other herbivores facing climate-driven habitat shifts.Abstract
Seasonal changes shape herbivore behaviour by altering forage availability and habitat conditions; however, few studies integrate diet and habitat selection data across temporal scales. This study uses seasonality as a unifying framework to combine fine-scale GPS-based habitat selection data with broader-scale dietary information from stable isotope analysis (δ13C, δ15N) of hairs in semi-domesticated reindeer Rangifer tarandus tarandus. Thresholds introduced within this framework detect seasonal shifts in habitat and diet selection and classify foraging strategies along a specialist–generalist continuum. Despite individual variability, most individuals exhibited pronounced seasonal changes between spring/early summer (SES) and late summer/autumn (LSA), consistent with generalist foraging strategies. Habitat selection models revealed reduced avoidance of rugged terrain and increased use of mires and bogs from SES to LSA. Concurrently, isotopic enrichment and niche expansion reflected a dietary shift from δ15N- and δ13C-depleted plants (e.g. lichens, shrubs, deciduous vegetation) to more enriched forage types such as sedges, grasses, horsetails, and mushrooms. We assessed whether individual-level shifts in diet and habitat use were linked and found an inverse correlation between the shifts in terrain ruggedness avoidance and dietary change in approximately 67% of individuals, suggesting that behavioural flexibility facilitates seasonal transitions. By integrating spatial and isotopic data, this study overcomes the limitations of single-method approaches and provides a more nuanced understanding of the seasonal foraging dynamics of a keystone Arctic and boreal ungulate. The findings highlight the plasticity of reindeer foraging within a variable environment and suggest a capacity to respond to environmental changes. This framework also offers broader applications for investigating behavioural responses and ecological strategies in other herbivores facing climate-driven habitat shifts
Sleep Alters the Velocity of Physiological Brain Pulsations in Humans
No full textAbstract
Introduction:
The clearance of brain metabolites increases during sleep, in association with increased spectral power of the three main cerebrospinal fluid (CSF) flow drivers: cardiovascular, respiratory, and vasomotor brain pulsations. However, little is known about how the increased power of these pulsations affects the velocity and direction of fluid flow in the sleeping brain.
Objectives:
To address this knowledge gap, we mapped the CSF oscillatory flow velocity in relation to the changing physiological pulsations in the brains of 22 healthy volunteers during sleep and waking.
Methods:
We used the ultrafast magnetic resonance imaging sequence known as magnetic resonance encephalography (MREG) for tracing the pulsatile movement of water molecules inside the cranium. First, we conducted a phantom validation study with optical flow analysis to confirm that MREG accurately tracks pulsatile water molecule flow in a porous tissue medium. Next, we obtained MREG recordings for mapping the three physiological pulsations without aliasing in the human brain across the awake and sleep states; we thereby quantified the brain-wide 3D velocity vectors (i.e., the velocity and 3D direction ) of each pulsation band, using comprehensive dense optical flow analysis during EEG-verified sleep in comparison to the awake state. Finally, we assessed relationships among the spectral power of the physiological pulsations, their 3D velocity , and slow-delta EEG power, which is known to depict the increased interstitial volume during sleep.
Results:
In our phantom study, dense optical flow analysis reliably detected water flow in tissue driven by external pulsations. In healthy volunteers, sleep increased flow velocities () of the pulsations by more than 20% in concert with elevations in respiratory pulsations and vasomotor waves, while the velocity of cardiovascular pulsations () declined by the same percentage. There was a significant anticorrelation between cardiac mean spectral power and slow delta EEG mean power, and a significant correlation between vasomotor mean spectral power and slow delta EEG mean power over the whole brain.
Conclusions:
Phantom studies validated the optic flow analysis of fast MREG recordings. Sleep altered the 3D velocity dynamics of all neurofluidic brain pulsations in a manner consistent with increased interstitial space and greater fluid exchange, thus supporting the glymphatic model wherein physiological pulsations drive bulk flow during sleep.Abstract
Introduction:
The clearance of brain metabolites increases during sleep, in association with increased spectral power of the three main cerebrospinal fluid (CSF) flow drivers: cardiovascular, respiratory, and vasomotor brain pulsations. However, little is known about how the increased power of these pulsations affects the velocity and direction of fluid flow in the sleeping brain.
Objectives:
To address this knowledge gap, we mapped the CSF oscillatory flow velocity in relation to the changing physiological pulsations in the brains of 22 healthy volunteers during sleep and waking.
Methods:
We used the ultrafast magnetic resonance imaging sequence known as magnetic resonance encephalography (MREG) for tracing the pulsatile movement of water molecules inside the cranium. First, we conducted a phantom validation study with optical flow analysis to confirm that MREG accurately tracks pulsatile water molecule flow in a porous tissue medium. Next, we obtained MREG recordings for mapping the three physiological pulsations without aliasing in the human brain across the awake and sleep states; we thereby quantified the brain-wide 3D velocity vectors (i.e., the velocity and 3D direction ) of each pulsation band, using comprehensive dense optical flow analysis during EEG-verified sleep in comparison to the awake state. Finally, we assessed relationships among the spectral power of the physiological pulsations, their 3D velocity , and slow-delta EEG power, which is known to depict the increased interstitial volume during sleep.
Results:
In our phantom study, dense optical flow analysis reliably detected water flow in tissue driven by external pulsations. In healthy volunteers, sleep increased flow velocities () of the pulsations by more than 20% in concert with elevations in respiratory pulsations and vasomotor waves, while the velocity of cardiovascular pulsations () declined by the same percentage. There was a significant anticorrelation between cardiac mean spectral power and slow delta EEG mean power, and a significant correlation between vasomotor mean spectral power and slow delta EEG mean power over the whole brain.
Conclusions:
Phantom studies validated the optic flow analysis of fast MREG recordings. Sleep altered the 3D velocity dynamics of all neurofluidic brain pulsations in a manner consistent with increased interstitial space and greater fluid exchange, thus supporting the glymphatic model wherein physiological pulsations drive bulk flow during sleep
IoT Service Orchestration in Edge-Cloud Continuum with 6G: A Review
No full textAbstract
The development of 6th-generation (6G) mobile networks brings advancements in wireless communications, including lower latency, higher data rates, and improved spectral efficiency, as well as enhanced facilitation for the use of Artificial Intelligence (AI) technologies, integrated communications, sensing, and renewable energy sources. To harness this potential, a scalable framework integrating edge and cloud computing is needed to provide a robust computing continuum for various IoT applications and services. This paper analyses the strengths and weaknesses of existing and emerging distributed computing frameworks—ranging from traditional centralized IoT architectures, through fog, edge, and local-edge architectures, to the full three-tier edge–cloud continuum—in terms of IoT service orchestration and diverse application requirements. We emphasize the latest evolutionary step, three-tier edge-cloud continuum, which aims to resolve the most significant limitations of the previous frameworks, recognized in the literature. It enables efficient IoT service orchestration by utilizing distributed resources and computation closer to end users, while taking full advantage of the centralized resources at data centers. We evaluate the maturity of these frameworks, considering factors such as scalability, resource efficiency, adaptability to changes, resource availability, security and privacy, as well as robustness and resilience. Overall, this study aims to serve as a roadmap for researchers, network architects, and industry stakeholders to make informed decisions on implementing the computing continuum in 6G networks.Abstract
The development of 6th-generation (6G) mobile networks brings advancements in wireless communications, including lower latency, higher data rates, and improved spectral efficiency, as well as enhanced facilitation for the use of Artificial Intelligence (AI) technologies, integrated communications, sensing, and renewable energy sources. To harness this potential, a scalable framework integrating edge and cloud computing is needed to provide a robust computing continuum for various IoT applications and services. This paper analyses the strengths and weaknesses of existing and emerging distributed computing frameworks—ranging from traditional centralized IoT architectures, through fog, edge, and local-edge architectures, to the full three-tier edge–cloud continuum—in terms of IoT service orchestration and diverse application requirements. We emphasize the latest evolutionary step, three-tier edge-cloud continuum, which aims to resolve the most significant limitations of the previous frameworks, recognized in the literature. It enables efficient IoT service orchestration by utilizing distributed resources and computation closer to end users, while taking full advantage of the centralized resources at data centers. We evaluate the maturity of these frameworks, considering factors such as scalability, resource efficiency, adaptability to changes, resource availability, security and privacy, as well as robustness and resilience. Overall, this study aims to serve as a roadmap for researchers, network architects, and industry stakeholders to make informed decisions on implementing the computing continuum in 6G networks
Evoked emotions in anorexia nervosa: neural and behavioural correlates of social-emotional processing
No full textAbstract
Previous work suggests people with anorexia nervosa (AN) display reduced facial expression of emotion. This may influence illness progression as blunted emotional reactions can negatively impact social relationships and increase isolation. The present study aimed to replicate and further build on previous findings by examining facial and brain responses to naturalistic, emotional films. In total, 141 women (71 AN/weight restored AN, 70 healthy comparison) completed two tasks in a fixed order: 1.) facial affect task and 2.) functional magnetic resonance imaging (fMRI) task. In both tasks, participants reacted to positive, neutral, and negative films, and rated their mood after each one. The effects of group and film category on facial expressions, brain responses, and mood ratings were examined. The AN group displayed reduced positive facial affect over time and lower self-reported mood in response to positive but not negative or neutral films. The fMRI task revealed no significant group differences in response to positive, neutral, or negative films. However, there was widespread activation of occipital, parietal, temporal, and frontal regions in response to the emotional films across groups. The behavioural findings replicate previously reported altered reactivity to positive films in AN. Additionally, task-related brain activation was observed in regions typically associated with the processing of naturalistic emotional stimuli, suggesting the task was valid. However, the lack of group differences during the fMRI task raises questions about whether the behavioural differences could be related to slower warming up to the task among those with AN.Abstract
Previous work suggests people with anorexia nervosa (AN) display reduced facial expression of emotion. This may influence illness progression as blunted emotional reactions can negatively impact social relationships and increase isolation. The present study aimed to replicate and further build on previous findings by examining facial and brain responses to naturalistic, emotional films. In total, 141 women (71 AN/weight restored AN, 70 healthy comparison) completed two tasks in a fixed order: 1.) facial affect task and 2.) functional magnetic resonance imaging (fMRI) task. In both tasks, participants reacted to positive, neutral, and negative films, and rated their mood after each one. The effects of group and film category on facial expressions, brain responses, and mood ratings were examined. The AN group displayed reduced positive facial affect over time and lower self-reported mood in response to positive but not negative or neutral films. The fMRI task revealed no significant group differences in response to positive, neutral, or negative films. However, there was widespread activation of occipital, parietal, temporal, and frontal regions in response to the emotional films across groups. The behavioural findings replicate previously reported altered reactivity to positive films in AN. Additionally, task-related brain activation was observed in regions typically associated with the processing of naturalistic emotional stimuli, suggesting the task was valid. However, the lack of group differences during the fMRI task raises questions about whether the behavioural differences could be related to slower warming up to the task among those with AN
Effects of Modification and Granulation on the Microstructure of H2-DRI-Based Electric Arc Furnace Slag
No full textAbstract
To reduce the environmental impact of steel production, multiple European companies are planning a shift toward electric arc furnace (EAF) process using hydrogen-based direct-reduced iron (H2-DRI) as a raw material. The changes in the process and the raw materials are reflected on the generated slags, and ideally the slag could be used as a supplementary cementitious material. However, original air-cooled EAF slag has poor cementitious properties, so an amorphous material must be generated by means of slag modification. In this study, an H2-DRI-based EAF slag was modified using mine tailings and rapidly cooled by water granulation. Combination of modification and partial reduction of iron oxides by carbon produced a highly amorphous material, which is promising for the valorization of the slag. Additionally, the possibility of using electron backscatter diffraction technique to quantify the amorphous phase content was studied and compared to conventional quantitative x-ray diffraction. While the obtained percentages differed depending on the method, the trend of increased amorphous content with increasing modification was clear with both methods.Abstract
To reduce the environmental impact of steel production, multiple European companies are planning a shift toward electric arc furnace (EAF) process using hydrogen-based direct-reduced iron (H2-DRI) as a raw material. The changes in the process and the raw materials are reflected on the generated slags, and ideally the slag could be used as a supplementary cementitious material. However, original air-cooled EAF slag has poor cementitious properties, so an amorphous material must be generated by means of slag modification. In this study, an H2-DRI-based EAF slag was modified using mine tailings and rapidly cooled by water granulation. Combination of modification and partial reduction of iron oxides by carbon produced a highly amorphous material, which is promising for the valorization of the slag. Additionally, the possibility of using electron backscatter diffraction technique to quantify the amorphous phase content was studied and compared to conventional quantitative x-ray diffraction. While the obtained percentages differed depending on the method, the trend of increased amorphous content with increasing modification was clear with both methods
Digital twin framework for electric truck route and infrastructure planning in the Nordic region
No full textAbstract
The electrification of road transportation poses multi-faceted challenges in the Nordic region, where cold ambient temperatures, long distances, and limited charging infrastructure affect operational efficiency and feasibility. This study presents a novel integrated framework that combines artificial intelligence, digital twins, and co-simulation to support energy-efficient routing and infrastructure planning for heavy-duty electric vehicles in the Nordic region. A Gradient Boosting model was trained on over 180 real-world intercity trips of data collected from an electric truck to estimate battery depth of discharge based on key operational factors. Motor load, torque, and total weight emerged as dominant predictors, while ambient temperature had a moderate effect. A digital twin environment was developed to assess the impact of various charging infrastructure scenarios, and a real-time co-simulation model was used to evaluate energy flow and support cost analysis. Results confirm the framework’s capability to support infrastructure planning and fleet operation optimization during winter. The approach provides actionable insights for logistics operators and policymakers who are advancing the electrification of heavy-duty vehicles in the Nordic region.Abstract
The electrification of road transportation poses multi-faceted challenges in the Nordic region, where cold ambient temperatures, long distances, and limited charging infrastructure affect operational efficiency and feasibility. This study presents a novel integrated framework that combines artificial intelligence, digital twins, and co-simulation to support energy-efficient routing and infrastructure planning for heavy-duty electric vehicles in the Nordic region. A Gradient Boosting model was trained on over 180 real-world intercity trips of data collected from an electric truck to estimate battery depth of discharge based on key operational factors. Motor load, torque, and total weight emerged as dominant predictors, while ambient temperature had a moderate effect. A digital twin environment was developed to assess the impact of various charging infrastructure scenarios, and a real-time co-simulation model was used to evaluate energy flow and support cost analysis. Results confirm the framework’s capability to support infrastructure planning and fleet operation optimization during winter. The approach provides actionable insights for logistics operators and policymakers who are advancing the electrification of heavy-duty vehicles in the Nordic region