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BACKGROUND: Fluid overload in ICU patients is associated with increased morbidity and mortality. Although studies report on optimisation of resuscitation fluids given to ICU patients, increasing evidence suggests that maintenance fluids and fluids used to administer drugs are important sources of fluid overload.

OBJECTIVES: We aimed to evaluate the volume of maintenance fluids and electrolytes on overall fluid balance and their relation to mortality in stabilised ICU patients.

DESIGN: Multicentre retrospective observational study.

SETTING: Six mixed surgical and medical ICUs in Sweden.

PATIENTS: A total of 241 adult patients who spent at least 7 days in the ICU during 2018.

MAIN OUTCOME MEASURES: The primary endpoint was the volume of maintenance, resuscitation and drug diluent fluids administered on days 3 to 7 in the ICU. Secondary endpoints were to compare dispensed amounts of maintenance fluids and electrolytes with predicted requirements. We also investigated the effects of administered fluids and electrolytes on patient outcomes.

RESULTS: During ICU days 3 to 7, 56.4% of the total fluids given were maintenance fluids, nutritional fluids or both, 25.4% were drug fluids and 18.1% were resuscitation fluids. Patients received fluids 1.29 (95% confidence interval 1.07 to 1.56) times their estimated fluid needs. Despite this, 93% of the cohort was treated with diuretics or renal replacement therapy. Patients were given 2.17 (1.57 to 2.96) times their theoretical sodium needs and 1.22 (0.75 to 1.77) times their potassium needs. The median [IQR] volume of fluid loss during the 5-day study period was 3742 [3156 to 4479] ml  day^-1, with urine output the main source of fluid loss. Death at 90 days was not associated with fluid or electrolyte balance in this cohort.

CONCLUSION: Maintenance and drug fluids far exceeded resuscitative fluids in ICU patients beyond the resuscitative phase. This excess fluid intake, in conjunction with high urinary output and treatment for fluid offload in almost all patients, suggests that a large volume of the maintenance fluids given was unnecessary.

TRIAL REGISTRATION: ClinicalTrials.org (identifier: NCT03972475).

Hyperosmolality is common in critically ill patients during body fluid volume reduction. It is unknown whether this is only a result of decreased total body water or an active osmole-producing mechanism similar to that found in aestivating animals, where muscle degradation increases urea levels to preserve water. We hypothesized that fluid volume reduction in critically ill patients contributes to a shift from ionic to organic osmolytes similar to mechanisms of aestivation. We performed a post-hoc analysis on data from a multicenter observational study in adult intensive care unit (ICU) patients in the postresuscitative phase. Fluid, electrolyte, energy and nitrogen intake, fluid loss, estimated glomerular filtration rate (eGFR), and estimated plasma osmolality (eOSM) were registered. Contributions of osmolytes Na+, K+, urea, and glucose to eOSM expressed as proportions of eOSM were calculated. A total of 241 patients were included. eOSM increased (median change 7.4 mOsm/kg [IQR−1.9–18]) during the study. Sodium's and potassium's proportions of eOSM decreased (P < .05 and P < .01, respectively), whereas urea's proportion increased (P < .001). The urea’s proportion of eOSM was higher in patients with negative vs. positive fluid balance. Urea's proportion of eOSM increased with eOSM (r = 0.63; adjusted for eGFR r = 0.80), but not nitrogen intake. In patients without furosemide and/or renal replacement therapy (n = 17), urea’s proportion of eOSM and eOSM correlated strongly (r = 0.92). Urea’s proportion of eOSM was higher in patients not surviving up to 90 d. In stabilized ICU patients, the contribution of urea to plasma osmolality increased during body water volume reduction, statistically independently of nitrogen administration and eGFR. The shift from ionic osmolytes to urea during body fluid volume reduction is similar to that seen in aestivating animals.

BACKGROUND: Iatrogenic fluid overload is associated with increased mortality in the intensive care unit (ICU). Decisions on fluid therapy may, at times, be based on other factors than physiological endpoints. We hypothesized that because of psychological factors volume of available fluid bags would affect the amount of resuscitation fluid administered to ICU patients.

METHODS: We performed a prospective intervention cross-over study at 3 Swedish ICUs by replacing the standard resuscitation fluid bag of Ringer's Acetate 1000 mL with 500 mL bags (intervention group) for 5 separate months and then compared it with the standard bag size for 5 months (control group). Primary endpoint was the amount of Ringer's Acetate per patient during ICU stay. Secondary endpoints were differences between the groups in cumulative fluid balance and change in body weight, hemoglobin and creatinine levels, urine output, acute kidney failure (measured as the need for renal replacement therapy, RRT) and 90-day mortality.

RESULTS: Six hundred and thirty-five ICU patients were included (291 in the intervention group, 344 in the control group). There was no difference in the amount of resuscitation fluid per patient during the ICU stay (2200 mL [1000-4500 median IQR] vs 2245 mL [1000-5630 median IQR]), RRT rate (11 vs 9%), 90-day mortality (11 vs 10%) or total fluid balance between the groups. The daily amount of Ringer's acetate administered per day was lower in the intervention group (1040 (280-2000) vs 1520 (460-3000) mL; P = .03).

CONCLUSIONS: The amount of resuscitation fluid administered to ICU patients was not affected by the size of the available fluid bags. However, altering fluid bag size could have influenced fluid prescription behavior.

Let G ≤ SL_n+1(C) act on R = C[X₁, . . . , X_n+1] by change of variables. Then, the skew-group algebra R_* G is bimodule (n + 1)-Calabi-Yau. In certain circumstances, this algebra admits a locally finite-dimensional grading of Gorenstein parameter 1, in which case it is the (n + 1)-preprojective algebra of its n-representation infinite degree 0 piece, as defined in [10]. If the group G is abelian, the (n +1)-preprojective algebra is said to be of type Ã. For a given group G, it is not obvious whether R_* G admits such a grading making it into an (n + 1)-preprojective algebra. We study the case when n = 2 and G is abelian. We give an explicit classification of groups such that R_* G is 3-preprojective by constructing such gradings. This is possible as long as G is not a subgroup of SL₂(C) and not C₂ x C₂. For a fixed G, the algebra R_* G admits different 3-preprojective gradings, so we associate a type to a grading and classify all types. Then we show that gradings of the same type are related by a certain kind of mutation. This gives a classification of 2-representation infinite algebras of type Ã. The involved quivers are those arising from hexagonal dimer models on the torus, and the gradings we consider correspond to perfect matchings on the dimer, or equivalently to periodic lozenge tilings of the plane. Consequently, we classify these tilings up to flips, which correspond to the mutation we consider.

Deploying reconfigurable intelligent surface (RIS) to enhance wireless transmission is a promising approach. In this paper, we investigate large-scale multi-RIS-assisted multi-cell systems, where multiple RISs are deployed in each cell. Different from the full-buffer scenario, the mutual interference in our system is not known a priori, and for this reason we apply the load coupling model to analyze this system. The objective is to minimize the total resource consumption subject to user demand requirement by optimizing the reflection coefficients in the cells. The cells are highly coupled and the overall problem is non-convex. To tackle this, we first investigate the single-cell case with given interference, and propose a low-complexity algorithm based on the Majorization-Minimization method to obtain a locally optimal solution. Then, we embed this algorithm into an algorithmic framework for the overall multi-cell problem, and prove its feasibility and convergence to a solution that is at least locally optimal. Simulation results demonstrate the benefit of RIS in time-frequency resource utilization in the multi-cell system.

In multi-access edge computing (MEC) systems, there are multiple local cache servers caching contents to satisfy the users' requests, instead of letting the users download via the remote cloud server. In this paper, a multi -cell content scheduling problem (MCSP) in MEC systems is considered. Taking into account jointly the freshness of the cached contents and the traffic data costs, we study how to schedule content updates along time in a multi -cell setting. Different from single -cell scenarios, a user may have multiple candidate local cache servers, and thus the caching decisions in all cells must be jointly optimized. We first prove that MCSP is NP -hard, then we formulate MCSP using integer linear programming, by which the optimal scheduling can be obtained for small-scale instances. For problem solving of large scenarios, via a mathematical reformulation, we derive a scalable optimization algorithm based on repeated column generation. Our performance evaluation shows the effectiveness of the proposed algorithm in comparison to an off -the -shelf commercial solver and a popularity -based caching.

We address reducing carbon footprint (CF) in the context of edge computing. The carbon intensity of electricity supply largely varies spatially as well as temporally. We consider optimal task scheduling and offloading, as well as battery charging to minimize the total CF. We formulate this optimization problem as a mixed integer linear programming model. However, we demonstrate that, via a graph-based reformulation, the problem can be cast as a minimum-cost flow problem, and global optimum can be admitted in polynomial time. Numerical results using real-world data show that optimization can reduce up to 83.3% of the total CF.

Passively cooled base stations (PCBSs) are highly relevant for achieving better efficiency in cost and energy. However, dealing with the thermal issue via load management, particularly for outdoor deployment of PCBS, becomes crucial. This is a challenge because the heat dissipation efficiency is subject to (uncertain) fluctuation over time. Moreover, load management is an online decision-making problem by its nature. In this paper, we demonstrate that a reinforcement learning (RL) approach, specifically Soft Actor-Critic (SAC), enables to make a PCBS stay cool. The proposed approach has the capability of adapting the PCBS load to the time-varying heat dissipation. In addition, we propose a denial and reward mechanism to mitigate the risk of overheating from the exploration such that the proposed RL approach can be implemented directly in a practical environment, i.e., online RL. Numerical results demonstrate that the learning approach can achieve as much as 88.6% of the global optimum. This is impressive, as our approach is used in an online fashion to perform decision-making without the knowledge of future heat dissipation efficiency, whereas the global optimum is computed assuming the presence of oracle that fully eliminates uncertainty. This paper pioneers the approach to the online PCBSs load management problem.

Passively cooled base stations (PCBSs) have emerged to deliver better cost and energy efficiency. However, passive cooling necessitates intelligent thermal control via traffic management, i.e., the instantaneous data traffic or throughput of a PCBS directly impacts its thermal performance. This is particularly challenging for outdoor deployment of PCBSs because the heat dissipation efficiency is uncertain and fluctuates over time. What is more, the PCBSs are interference-coupled in multi-cell scenarios. Thus, a higher-throughput PCBS leads to higher interference to the other PCBSs, which, in turn, would require more resource consumption to meet their respective throughput targets. In this paper, we address online decision-making for maximizing the total downlink throughput for a multi-PCBS system subject to constraints related on operating temperature. We demonstrate that a reinforcement learning (RL) approach, specifically soft actor-critic (SAC), can successfully perform throughput maximization while keeping the PCBSs cool, by adapting the throughput to time-varying heat dissipation conditions. Furthermore, we design a denial and reward mechanism that effectively mitigates the risk of overheating during the exploration phase of RL. Simulation results show that our approach achieves up to 88.6% of the global optimum. This is very promising, as our approach operates without prior knowledge of future heat dissipation efficiency, which is required by the global optimum.

BACKGROUND: Body composition (BC) is an important factor in determining the risk of type 2-diabetes and cardiovascular disease. Computed tomography (CT) is a useful imaging technique for studying BC, however manual segmentation of CT images is time-consuming and subjective. The purpose of this study is to develop and evaluate fully automated segmentation techniques applicable to a 3-slice CT imaging protocol, consisting of single slices at the level of the liver, abdomen, and thigh, allowing detailed analysis of numerous tissues and organs.

METHODS: The study used more than 4000 CT subjects acquired from the large-scale SCAPIS and IGT cohort to train and evaluate four convolutional neural network based architectures: ResUNET, UNET++, Ghost-UNET, and the proposed Ghost-UNET++. The segmentation techniques were developed and evaluated for automated segmentation of the liver, spleen, skeletal muscle, bone marrow, cortical bone, and various adipose tissue depots, including visceral (VAT), intraperitoneal (IPAT), retroperitoneal (RPAT), subcutaneous (SAT), deep (DSAT), and superficial SAT (SSAT), as well as intermuscular adipose tissue (IMAT). The models were trained and validated for each target using tenfold cross-validation and test sets.

RESULTS: The Dice scores on cross validation in SCAPIS were: ResUNET 0.964 (0.909-0.996), UNET++ 0.981 (0.927-0.996), Ghost-UNET 0.961 (0.904-0.991), and Ghost-UNET++ 0.968 (0.910-0.994). All four models showed relatively strong results, however UNET++ had the best performance overall. Ghost-UNET++ performed competitively compared to UNET++ and showed a more computationally efficient approach.

CONCLUSION: Fully automated segmentation techniques can be successfully applied to a 3-slice CT imaging protocol to analyze multiple tissues and organs related to BC. The overall best performance was achieved by UNET++, against which Ghost-UNET++ showed competitive results based on a more computationally efficient approach. The use of fully automated segmentation methods can reduce analysis time and provide objective results in large-scale studies of BC.

Background Computed tomography (CT) is an imaging modality commonly used for studies of internal body structures and very useful for detailed studies of body composition. The aim of this study was to develop and evaluate a fully automatic image registration framework for inter-subject CT slice registration. The aim was also to use the results, in a set of proof-of-concept studies, for voxel-wise statistical body composition analysis (Imiomics) of correlations between imaging and non-imaging data.Methods The current study utilized three single-slice CT images of the liver, abdomen, and thigh from two large cohort studies, SCAPIS and IGT. The image registration method developed and evaluated used both CT images together with image-derived tissue and organ segmentation masks. To evaluate the performance of the registration method, a set of baseline 3-single-slice CT images (from 2780 subjects including 8285 slices) from the SCAPIS and IGT cohorts were registered. Vector magnitude and intensity magnitude error indicating inverse consistency were used for evaluation. Image registration results were further used for voxel-wise analysis of associations between the CT images (as represented by tissue volume from Hounsfield unit and Jacobian determinant) and various explicit measurements of various tissues, fat depots, and organs collected in both cohort studies.Results Our findings demonstrated that the key organs and anatomical structures were registered appropriately. The evaluation parameters of inverse consistency, such as vector magnitude and intensity magnitude error, were on average less than 3 mm and 50 Hounsfield units. The registration followed by Imiomics analysis enabled the examination of associations between various explicit measurements (liver, spleen, abdominal muscle, visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), thigh SAT, intermuscular adipose tissue (IMAT), and thigh muscle) and the voxel-wise image information.Conclusion The developed and evaluated framework allows accurate image registrations of the collected three single-slice CT images and enables detailed voxel-wise studies of associations between body composition and associated diseases and risk factors.

Obesity is associated with an increased risk of morbidity and mortality. Achieving a healthy body composition, which involves maintaining a balance between fat and muscle mass, is important for metabolic health and preventing chronic diseases. Computed tomography (CT) imaging offers detailed insights into the body’s internal structure, aiding in understanding body composition and its related factors. In this feasibility study, we utilized CT image data from 2,724 subjects from the large metabolic health cohort studies SCAPIS and IGT. We train and evaluate an uncertainty-aware deep regression based ResNet-50 network, which outputs its prediction as mean and variance, for quantification of cross-sectional areas of liver, visceral adipose tissue (VAT), and thigh muscle. This was done using collages of three single-slice CT images from the liver, abdomen, and thigh regions. The model demonstrated promising results with the evaluation metrics – including R-squared (R²) and mean absolute error (MAE) for predictions. Additionally, for interpretability, the model was evaluated with saliency analysis based on Grad-CAM (Gradient-weighted Class Activation Mapping) at stages 2, 3, and 4 of the network. Deformable image registration to a template subject further enabled cohort saliency analysis that provide group-wise visualization of image regions of importance for associations to biomarkers of interest. We found that the networks focus on relevant regions for each target, according to prior knowledge.

Over 300 cities are inscribed on the World Heritage List. While each site has its unique challenges and opportunities, in each of them a balance must be achieved in protecting heritage values and meeting demands of modern life, including the demand for energy efficiency and the reduction of greenhouse gas emissions. This article uses Visby (Sweden) as a case study to examine how conservation laws implementing the World Heritage Convention in light of international commitments to mitigate climate change can influence the balance between cultural heritage preservation and energy measures in historic sites. International laws must be implemented by states. But these national laws must be applied locally, in each heritage site. It is therefore important to examine how regional and local decision makers, including individual property owners, navigate and understand their obligations stemming from international laws in order to understand the impact and challenges in meeting sustainability goals in heritage sites. We find that while Visby’s World Heritage status promotes a high level of cultural heritage protection, restrictive laws alone fall short in achieving sustainability. Supportive factors such as funding, planning tools, knowledge support and dissemination, and community engagement help bridge these gaps. We recommend further support for financial incentives, place-based technological solutions, and collaboration amongst experts and others to help officials and property owners make choices that are sustainable from both energy and heritage perspectives.

World Heritage cities face the complex challenges of balancing cultural heritage protection with the UN Sustainable Development Goals, particularly reducing greenhouse gas emissions and achieving energy sustainability. However, implementing these commitments at the local level often presents challenges. Using the walled city of Jaipur, a UNESCO World Heritage site in India, as a case study, this article examines the impacts, opportunities, and challenges in implementing and applying international and national obligations to preserve cultural heritage in light of obligations to reduce energy use and greenhouse gas emissions in historic urban areas. This article is based on legal research, as well as 9 semi-structured interviews, which include one group interview with three municipal representatives and individual interviews with one state representative, five heritage professionals and consultants, and two heritage property owners. The results show that World Heritage status has enhanced cultural heritage protection while allowing measures toward energy sustainability. Traditional architectural practices, such as the passive climate design of havelis, are already energy efficient, while interventions, such as the integration of solar panels and adaptive re-use of havelis, demonstrate compatibility between heritage conservation and sustainability goals. However, there continue to be challenges, including limited expertise, capacity, and financial resources, while governance inefficiencies, commercialization pressures, inadequate support for residents, and limited community engagement further hinder progress. The study recommends strengthening the governance framework and enforcement mechanisms, providing targeted financial and technological support, and fostering inclusive collaboration and education among these actors to align heritage conservation with energy sustainability at the local level.

This article examines the effectiveness, legitimacy, and fairness of heritage conservation outcomes under the 1972 World Heritage Convention (1972 WHC), with a focus on recognising and respecting the rights of Indigenous Peoples in heritage nomination, protection, and management. Examining conflicts surrounding World Heritage sites in Kenya and Sweden, this article argues that recognition of biocultural heritage and biocultural rights can promote environmental justice and help meet global environmental challenges. To promote the conservation of both built and natural landscapes, the article recommends expanding protection for the relationship between humans and their environment. Recognising biocultural heritage under UNESCO conventions could promote Indigenous sovereignty, protect cultural and natural heritage, and contribute to global efforts to address climate change. The article calls for further research mapping biocultural heritage in natural and mixed heritage sites and advocates for fuller engagement with Indigenous Peoples to increase the ability of the 1972 WHC to promote sustainability as it enters its second half-century.

Marine energy resources could be crucial in meeting the increased demand for clean electricity. To enable the use of marine energy resources, developing efficient and durable offshore electrical systems is vital. Currently, there are no large-scale commercial projects with marine energy resources, and the question of how to design such electrical systems is still not settled. A natural starting point in investigating this is to draw on experiences and research from offshore wind power. This article reviews different collection grid topologies and key components for AC and DC grid structures. The review covers aspects such as the type of components, operation and estimated costs of commercially available components. A DC collection grid can be especially suitable for offshore marine energy resources, since the transmission losses are expected to be lower, and the electrical components could possibly be made smaller. Therefore, five DC collection grid topologies are proposed and qualitatively evaluated for marine energy resources using submerged and non-submerged marine energy converters. The properties, advantages and disadvantages of the proposed topologies are discussed, and it is concluded that a suitable electrical system for a marine energy farm will most surely be based on a site-specific techno-economic analysis.

Wave energy is one of the emerging sustainable energy resources due to its high energy density and vast untapped areas. Nevertheless, the intermittency of wave resources is a significant challenge for the grid operator. Additionally, a varying grid demand is an added complexity to wave resources. Energy storage systems such as batteries and supercapacitors can be used to smoothen the power injection into the grid and match the available energy with the grid demand. Thus, this study compares battery energy storage with the hybrid energy storage system and proposes a control strategy to reduce the power fluctuations on the battery, allowing power delivery for varying grid demands. The study found that the hybrid system increases the system efficiency, in addition to the reduction in power fluctuations and enhancement of battery's performance, among other gains when the proposed control is implemented.

Wave energy has been an immense area of interest in research and industry in our move towards a sustainable energy production society due to its high energy density and surface area. However, the grid connection of wave energy converters is still one of the major challenges due to the complexity of varying wave resources (amplitude and frequency). Wave energy converter grid integration can lead to several potential challenges, such as voltage fluctuations, harmonics and flicker. Using an energy storage system can help mitigate a few challenges by balancing the grid demand with the wave energy converter power supply. Hence improving the power quality. This study assesses the power quality of wave energy converters equipped with energy storage against the scenario without any energy storage at different power levels. The power quality in this paper is investigated using total harmonic distortion (THD)of the grid current, dc-link voltage ripple and battery current ripple. The study shows that the addition of a hybrid energy storage system lowers the grid current THDat the point of common coupling (PCC), stabilizes the dc-link voltage ripple and reduces the stress of the battery.

The electrification of remote islands has long been a subject of research interest, primarily because of their historical reliance on fossil fuels, leading to a significant carbon footprint. Recent advancements in wave energy converters offer a promising avenue to make these islands more self-sustainable while considerably reducing carbon emissions. However, the persistent issue of voltage dips due to weaker grids continues to pose a challenge. This study introduces a multi-mode converter control strategy with the goal of electrifying remote islands, employing a linear generator-based wave energy converter in a unified electrical model. Various scenarios, including voltage dips and mainland grid disconnection, are simulated using MATLAB/Simulink. The study demonstrates the converter's ability to transition swiftly and smoothly in response to these scenarios, ensuring an uninterrupted power supply. Furthermore, the analysis indicates that the power quality at the point of common coupling remains well within acceptable standards.

As the world transitions to renewable electrification to reduce CO2 emissions, remote island electrification remains a challenge. Although some islands are connected to the grid, many still rely on fossil fuels for electricity generation. Several studies indicate that renewable energy sources, such as wave energy, have the potential to make these islands self-reliant because of their substantial power potential. However, research on the control of power electronics converters for these systems remains limited. This paper proposes isolated grid-forming control for island electrification to address this gap using a wave energy converter and an energy storage system. Resistive loading control is implemented to optimize the power absorption of the generator. The result illustrates the establishment of the required AC voltage and 50 Hz frequency in the island load, ensuring harmonics compliance with the recommended standards. Experiments were conducted to test and validate the operation of different converter controls. The results also demonstrate the converter's ability to black-start the island load and automatically transition the load current with varying loads in a few milliseconds. Furthermore, the power quality produced by the wave energy converter presents one of its significant challenges. Therefore, the performance of two distinct converter technologies was compared. The performance of the IGBT converter was evaluated against that of the SiC-based converter in terms of power quality. The study demonstrates that the use of SiC enhances power quality in all switching frequencies tested, achieving the most significant reduction of 78% in current THD and 92% in voltage THD at the 25 kHz switching frequency, thus validating its advantages for wave energy converter applications.

Aims: Pericytes in the brain play important roles for microvascular physiology and pathology and are affected in neurological disorders and neurodegenerative diseases. Mouse models are often utilized for pathophysiology studies of the role of pericytes in disease; however, the translatability is unclear as brain pericytes from mouse and human have not been systematically compared. In this study, we investigate the similarities and differences of brain pericyte gene expression between mouse and human. Our analysis provides a comprehensive resource for translational studies of brain pericytes.

Methods: We integrated and compared four mouse and human adult brain pericyte single-cell/nucleus RNAsequencing datasets derived using two single-cell RNA sequencing platforms: Smart-seq and 10x. Gene expression abundance and specificity were analyzed. Pericyte-specific/enriched genes were assigned by comparison with endothelial cells present in the same datasets, and mouse and human pericyte transcriptomes were subsequently compared to identify species-specific genes.

Results: An overall concordance between pericyte transcriptomes was found in both Smart-seq and 10x data. 206 orthologous genes were consistently differentially expressed between human and mouse from both platforms, 91 genes were specific/up-regulated in human and 115 in mouse. Gene ontology analysis revealed differences in transporter categories in mouse and human brain pericytes. Importantly, several genes implicated in human disease were expressed in human but not in mouse brain pericytes, including SLC6A1, CACNA2D3, and SLC20A2.

Conclusions: This study provides a systematic illustration of the similarities and differences between mouse and human adult brain pericytes.

Claudin-5 (CLDN5) is an endothelial tight junction protein essential for blood-brain barrier (BBB) formation. Abnormal CLDN5 expression is common in brain disease, and knockdown of Cldn5 at the BBB has been proposed to facilitate drug delivery to the brain. To study the consequences of CLDN5 loss in the mature brain, we induced mosaic endothelial-specific Cldn5 gene ablation in adult mice (Cldn5^iECKO). These mice displayed increased BBB permeability to tracers up to 10 kDa in size from 6 days post induction (dpi) and ensuing lethality from 10 dpi. Single-cell RNA sequencing at 11 dpi revealed profound transcriptomic differences in brain endothelial cells regardless of their Cldn5 status in mosaic mice, suggesting major non-cell-autonomous responses. Reactive microglia and astrocytes suggested rapid cellular responses to BBB leakage. Our study demonstrates a critical role for CLDN5 in the adult BBB and provides molecular insight into the consequences and risks associated with CLDN5 inhibition.

Studying disease-related changes in the brain vasculature is warranted due to its crucial role in supplying oxygen and nutrients and removing waste and due to the anticipated vascular dysfunction in brain dis-eases. To this end, we have developed a protocol for fast and simple isolation of brain vascular fragments without the use of transgenic reporters. We used it to isolate and analyze 22,515 cells by single-cell RNA sequencing. The cells distributed into 23 distinct clusters corresponding to all known vascular and perivas-cular cell types in the brain. Western blot analysis also suggested that the protocol is suitable for proteomic analysis. We further adapted it for the establishment of primary cell cultures. The protocol generated highly reproducible results. In conclusion, we have developed a simple and robust brain vascular isolation proto-col suitable for different experimental modalities, such as single-cell analyses, western blotting, and pri-mary cell culture.

Early cancer detection, guided by whole-body imaging, is important for the overall survival and well-being of the patients. While various computer-assisted systems have been developed to expedite and enhance cancer diagnostics and longitudinal monitoring, the detection and segmentation of tumors, especially from whole-body scans, remain challenging. To address this, we propose a novel end -to-end automated framework that first generates a tumor probability distribution map (TPDM), incorporating prior information about the tumor characteristics (e.g. size, shape, location). Subsequently, the TPDM is integrated with a state-of-the-art 3D segmentation network along with the original PET/CT or PET/MR images. This aims to produce more meaningful tumor segmentation masks compared to using the baseline 3D segmentation network alone. The proposed method was evaluated on three independent cohorts (autoPET, CAR-T, cHL) of images containing different cancer forms, obtained with different imaging modalities, and acquisition parameters and lesions annotated by different experts. The evaluation demonstrated the superiority of our proposed method over the baseline model by significant margins in terms of Dice coefficient, and lesion-wise sensitivity and precision. Many of the extremely small tumor lesions (i.e. the most difficult to segment) were missed by the baseline model but detected by the proposed model without additional false positives, resulting in clinically more relevant assessments. On average, an improvement of 0.0251 (autoPET), 0.144 (CAR-T), and 0.0528 (cHL) in overall Dice was observed. In conclusion, the proposed TPDM-based approach can be integrated with any state-of-the-art 3D UNET with potentially more accurate and robust segmentation results.

), respectively; *, p-value < 0.05; ns, non-significance. Conclusion: The increased segmentation accuracy could be attributed to the segmentation prior generated from tissue-wise SUV projections, revealing information from various tissues that was useful for segmentation of tumors. The results from this study highlight the potential of the proposed method as a valuable future tool for time-efficient quantification of tumor burden in oncologic FDG-PET/CT.

Early and accurate prediction of clinical outcomes holds great potential for patient prognostics and personalized treatment planning. Development of automated methods for estimation of medical image-based clinical parameters (e.g. total metabolic tumor volume, TMTV) could pave the way for predicting advanced clinical outcomes not explicitly available in the images, such as overall survival. We developed an automated framework that extracted tissue-wise multi-channel 2D projections from whole-body FDG-PET/CT volumes, by separating tissues based on CT Hounsfield units, and used a DenseNet-121 to estimate the TMTV from the projections. For transparency and interpretability, an image registration-based cohort saliency analysis was proposed. The network was applied on the autoPET cohort (501 scans representing lymphoma, lung cancer, melanoma) and evaluated using a single channel method (baseline) and a multi-channel method (proposed), for the purpose of comparison. The incorporation of multiple channels demonstrated an advantage in the TMTV prediction, outperforming the baseline model with a ΔMAE = –14.34 ml; ΔR2 = 0.1584; ΔICC = 0.1316 (p-value = 0.0098). The Pearson correlation coefficient (r) was computed between the ground truth (GT) tumor projections and the aggregated saliency maps. Statistical comparison, via bootstrapping, showed that the proposed model consistently outperformed the baseline, with significantly higher r across all cancer types and both sexes, except for melanoma in females. This implied that the aggregated saliency maps generated by the proposed model showed higher correspondence with the GT, compared to the baseline model. Our approach offers a promising and interpretable framework for the automated prediction of TMTV, with further potential to also predict advanced clinical outcomes.

Traumatic brain injury (TBI) is followed by secondary injury mechanisms strongly involving neuroinflammation. To monitor the complex inflammatory cascade in human TBI, we used cerebral microdialysis (MD) and multiplex proximity extension assay (PEA) technology and simultaneously measured levels of 92 protein biomarkers of inflammation in MD samples every three hours for five days in 10 patients with severe TBI under neurointensive care. One mu L MD samples were incubated with paired oligonucleotide-conjugated antibodies binding to each protein, allowing quantification by real-time quantitative polymerase chain reaction. Sixty-nine proteins were suitable for statistical analysis. We found five different patterns with either early (<48 h; e.g., CCL20, IL6, LIF, CCL3), mid (48-96 h; e.g., CCL19, CXCL5, CXCL10, MMP1), late (>96 h; e.g., CD40, MCP2, MCP3), biphasic peaks (e.g., CXCL1, CXCL5, IL8) or stable (e.g., CCL4, DNER, VEGFA)/low trends. High protein levels were observed for e.g., CXCL1, CXCL10, MCP1, MCP2, IL8, while e.g., CCL28 and MCP4 were detected at low levels. Several proteins (CCL8, -19, -20, -23, CXCL1, -5, -6, -9, -11, CST5, DNER, Flt3L, and SIRT2) have not been studied previously in human TBI. Cross-correlation analysis revealed that LIF and CXCL5 may play a central role in the inflammatory cascade. This study provides a unique data set with individual temporal trends for potential inflammatory biomarkers in patients with TBI. We conclude that the combination of MD and PEA is a powerful tool to map the complex inflammatory cascade in the injured human brain. The technique offers new possibilities of protein profiling of complex secondary injury pathways.

Cerebral protein profiling in traumatic brain injury (TBI) is needed to better comprehend secondary injury pathways. Cerebral microdialysis (CMD), in combination with the proximity extension assay (PEA) technique, has great potential in this field. By using PEA, we have previously screened >500 proteins from CMD samples collected from TBI patients. In this study, we customized a PEA panel prototype of 21 selected candidate protein biomarkers, involved in inflammation (13), neuroplasticity/-repair (six), and axonal injury (two). The aim was to study their temporal dynamics and relation to age, structural injury, and clinical outcome. Ten patients with severe TBI and CMD monitoring, who were treated in the Neurointensive Care Unit, Uppsala University Hospital, Sweden, were included. Hourly CMD samples were collected for up to 7 days after trauma and analyzed with the 21-plex PEA panel. Seventeen of the 21 proteins from the CMD sample analyses showed significantly different mean levels between days. Early peaks (within 48 h) were noted with interleukin (IL)-1 beta, IL-6, IL-8, granulocyte colony-stimulating factor, transforming growth factor alpha, brevican, junctional adhesion molecule B, and neurocan. C-X-C motif chemokine ligand 10 peaked after 3 days. Late peaks (>5 days) were noted with interleukin-1 receptor antagonist (IL-1ra), monocyte chemoattractant protein (MCP)-2, MCP-3, urokinase-type plasminogen activator, Dickkopf-related protein 1, and DRAXIN. IL-8, neurofilament heavy chain, and TAU were biphasic. Age (above/below 22 years) interacted with the temporal dynamics of IL-6, IL-1ra, vascular endothelial growth factor, MCP-3, and TAU. There was no association between radiological injury (Marshall grade) or clinical outcome (Extended Glasgow Outcome Scale) with the protein expression pattern. The PEA method is a highly sensitive molecular tool for protein profiling from cerebral tissue in TBI. The novel TBI dedicated 21-plex panel showed marked regulation of proteins belonging to the inflammation, plasticity/repair, and axonal injury families. The method may enable important insights into complex injury processes on a molecular level that may be of value in future efforts to tailor pharmacological TBI trials to better address specific disease processes and optimize timing of treatments.

The central nervous system (CNS) evokes a complex inflammatory response to injury. Inflammatory cascades are present in traumatic, infectious, and noninfectious disorders affecting the brain. It contains a mixture of pro- andanti-inflammatory reactions involving well-known proteins, but also numerous proteins less explored in these processes. The aim of this study was to explore the distinct inflammatory response in traumatic brain injury (TBI)compared with other CNS injuries by utilization of mass-spectrometry. In total, 46 patients had their cerebrospinal fluid (CSF) analyzed with the use of mass-spectrometry. Among these, CSF was collected via an external ventricular drain (EVD) from n = 12 patients with acute TBI. The resulting protein findings were then compared with CSF obtained by lumbar puncture from n = 14 patients with noninfectious CNS disorders comprising relapsing–remitting multiple sclerosis, anti-N-methyl-D-aspartate-receptor encephalitis, acute disseminated encephalomyelitis, and n = 13 patients with progressive multifocal leukoencephalopathy, herpes simplex encephalitis, and other types ofviral meningitis. We also utilized n = 7 healthy controls (HC). In the comparison between TBI and noninfectious inflammatory CNS disorders, concentrations of 57 proteins significantly differed between the groups. Among them, 20 and 37 proteins were up- and downregulated, respectively. No proteins were uniquely identified in the TBI group. In the comparison of TBI and HC, 55 proteins were significantly different, with 24 and 31 proteins being up- and downregulated, respectively. Four proteins were uniquely identified in the TBI group, (FGG, HBA1, TKT,CA1). In the TBI versus infectious inflammatory CNS disorders, 57 proteins differed significantly between the groups, with 17 and 40 proteins being up- and down regulated, respectively. No proteins were uniquely identified in the TBI group. Due to large discrepancies between the groups compared, the following proteins were selected for further deeper analysis among those being differentially regulated: APOE, CFB, CHGA, CHI3L1, C3, FCGBP, FGA,GSN, IGFBP7, SERPINA3, SOD3, and TTR. We found distinct proteomic profiles in the CSF of TBI patients compared with HC and different disease controls, indicating a specific interplay between inflammatory factors, metabolic response, and cell integrity. In relation to primarily infectious or inflammatory disorders, unique inflammatory pathways seem to be engaged, and could potentially serve as future treatment targets.

OBJECTIVE: Unicoronal craniosynostosis (UCS) is characterized by complex orbital deformity and is typically treated by asymmetrical fronto-orbital remodeling (FOR) during the 1st year of life. The aim of this study was to elucidate to what extent orbital morphology is corrected by surgical treatment.

METHODS: The extent to which orbital morphology was corrected by surgical treatment was tested by analysis of differences in volume and shape between synostotic, nonsynostotic, and control orbits at two time points. In total, 147 orbits were analyzed from patient CT images obtained preoperatively (mean age 9.3 months), at follow-up (mean age 3.0 years), and in matched controls. Semiautomatic segmentation software was used to determine orbital volume. For analysis of orbital shape and asymmetry, geometrical models, signed distance maps, principal modes of variation, and three objective parameters (mean absolute distance, Hausdorff distance, and dice similarity coefficient) were generated by statistical shape modeling.

RESULTS: Orbital volumes on both the synostotic and nonsynostotic sides were significantly smaller at follow-up than volumes in controls and significantly smaller both preoperatively and at follow-up than orbital volumes on the nonsynostotic side. Significant differences in shape were identified globally and locally, both preoperatively and at 3 years of age. Compared with controls, deviations were mostly found on the synostotic side at both time points. Asymmetry between synostotic and nonsynostotic sides was significantly decreased at follow-up, but not compared with the inherent asymmetry of controls. On a group level, the preoperative synostotic orbit was mainly expanded in the anterosuperior and anteroinferior regions and smallest on the temporal side. At follow-up, the mean synostotic orbit was still larger superiorly but also expanded in the anteroinferior temporal region. Overall, the morphology of nonsynostotic orbits was more simi-lar to that of controls than to synostotic orbits. However, the individual variation in orbital shape was greatest for nonsynostotic orbits at follow-up.

CONCLUSIONS: In this study, the authors presented what is, to their knowledge, the first objective automatic 3D bony evaluation of orbital shape in UCS, defining in greater detail than has been done previously how synostotic orbits differ from nonsynostotic and control orbits, and how orbital shape changes from 9.3 months of age preoperatively to 3 years of age at the postoperative follow-up. Despite surgical treatment, both local and global deviations in shape persist. These findings may have implications for future directions in the development of surgical treatment. Future studies connecting orbital morphology to ophthalmic disorders, aesthetics, and genetics could provide further insight to enable better outcomes in UCS.

Background

Preoperative severity of unicoronal synostosis varies greatly and involves the frontal bone, skull base and orbits. Degree of deformity affects long-term morphological and functional outcomes after surgery. The aim of this study was to describe the morphological heterogenicity and investigate its relation to patient-specific factors.

Materials and methods

In this retrospective cohort study, non-syndromic unicoronal synostosis patients treated between 2006 and 2022 at Necker Hospital, France or Uppsala University Hospital, Sweden, were included and matched to controls. Severity of skull base, orbital and posterior skull asymmetry, degree of anterior plagiocephaly and Harlequin deformity, lateralisation, head circumference, age, timing of metopic fusion and fusion of peri-pterionic sutures were investigated.

Results

Ninety-five patients and ninety-three controls were included. Skull base asymmetry was linearly related to orbital asymmetry (p < 0.001), correlated with earlier CT scans (p = 0.004) and anterior (p < 0.001) and posterior (p = 0.03) plagiocephaly. Posterior plagiocephaly was more common in patients (31%) compared with controls (5%) (p < 0.001). A patent metopic suture above nine months of age was associated with severe Harlequin deformity (p = 0.04) and a lower head circumference when fused (p = 0.03). Fronto-sphenoidal suture fusion was associated with later CT scans (p < 0.001) and less skull base asymmetry (p = 0.002). Spheno-parietal fusion was correlated with decreased skull base asymmetry (p = 0.03). Right lateralisation was more common in females.

Conclusions

Heterogenicity of unicoronal synostosis seems to be predominantly explained by variability in skull base morphology. Peri-pterionic fusions might limit deformity.

Nonsyndromic unicoronal synostosis is associated with variability of severity in orbital morphology and ophthalmological manifestations. The relation between the two is not fully understood, nor how surgical treatment with fronto-orbital advancement and remodelling (FOAR) changes the relation.The aim of this study was to elucidate associations between ophthalmological manifestations and variations in orbital morphology and globe:orbit volume ratios preoperatively and at long-term follow-up after surgery. Twelve children referred to Uppsala Craniofacial Center who underwent computed tomography and standardized ophthalmological examinations regarding strabismus, spherical equivalent, astigmatism, anisometropia, and subnormal vision preoperatively and at 3 years of age were included. Orbits and globes were segmented. Principal component analysis elucidated morphological variation, and symmetry between orbital pairs was measured as the Dice similarity coefficient and globe:orbit volume ratios were calculated. The defined orbital shape variations were correlated with strabismus, refractive error, and subnormal vision. Different shape variations were associated with strabismus pre- and postoperatively and ipsi- and contralateral astigmatism. Greater improvement in orbital symmetry after surgery was associated with improvement in astigmatic anisometropia and new onset strabismus at follow-up. A small globe:orbit volume ratio was associated with preoperative strabismus, while the opposite was seen at follow-up. Different mechanisms seem to cause strabismus pre- and postoperatively, and FOAR might not sufficiently correct orbital morphology.