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Objectives: Prussak's space (PS) is an intricate middle ear region which may play an essential role in the development of middle ear disease. The three-dimensional (3D) anatomy of the human PS and its drainage routes remain relatively unknown. Earlier studies have histologically analyzed PS, by micro-dissection and endoscopy. Here, we used synchrotron-radiation phase-contrast imaging (SR-PCI), 3D reconstructions, and modeling to study the framework of the human PS, including aeration pathways. It may lead to increased understanding of development of middle ear pathology.

Design: Nine human temporal bone specimens underwent in-line SR-PCI at the Canadian Light Source in Saskatoon, Saskatchewan, Canada. Data were processed with volume-rendering software to create 3D reconstructions using scalar opacity mapping and segmentations to visualize its walls in fixed, undecalcified human temporal bones.

Results: The PS was found to be an irregular, variably shaped chamber with different aeration systems. Three different drainage pathways were found: 1) via the posterior malleolar pouch of von Troltsch in seven of nine ears; 2) directly posterior-inferior into the mesotympanum medial to the posterior malleolar pouch in one ear; and 3) anteriorly in another. The posterior-inferior communications depended on the anatomy of the posterior malleolar fold. In one bilateral case, the aeration differed between the ears. Earlier descriptions of upper ventilation routes between the PS and the epitympanic spaces could not be substantiated.

Conclusions: The 3D anatomy of the membrane folds organizing the PS in humans was demonstrated for the first time using in-line SR-PCI. The PS was always aerated into the mesotympanum, suggesting its relative independence of attic ventilation. The impact of its various drainage routes on middle ear ventilation and disease were discussed.

INTRODUCTION: Otosclerosis is a bone disorder affecting the labyrinthine capsule that leads to conductive and occasionally sensorineural hearing loss. The etiology of otosclerosis remains unknown; factors such as infection, hormones, inflammation, genetics, and autoimmunity have been discussed. Treatment consists primarily of surgical stapes replacement and cochlear implantation. High-resolution computed tomography is routinely used to visualize bone pathology. In the present study, we used synchrotron radiation phase-contrast imaging (SR-PCI) to examine otosclerosis plaques in a temporal bone for the first time. The primary aim was to study their three-dimensional (3D) outline, vascular interrelationships, and connections to the middle ear.

METHODS: A donated ear from a patient with otosclerosis who had undergone partial stapedectomy with the insertion of a stapes wire prosthesis was investigated using SR-PCI and compared with a control ear. Otosclerotic lesions were 3D rendered using the composite with shading technique. Scalar opacity and color mapping were adjusted to display volume properties with the removal of bones to enhance surfaces. Vascular bone channels were segmented, and the communications between lesions and the middle ear were established.

RESULTS: Fenestral, cochlear, meatal, and vestibular lesions were outlined three-dimensionally. Vascular bone channels were found to be frequently connected to the middle ear mucosa, perilabyrinthine air spaces, and facial nerve vessels. Round window lesions partly embedded the cochlear aqueduct which was pathologically narrowed, while the inferior cochlear vein was significantly dilated in its proximal part.

CONCLUSION: Otosclerotic/otospongiotic lesions were imaged for the first time using SR-PCI and 3D rendering. The presence of shunts and abnormal vascular connections to the labyrinth appeared to result in hyper-vascularization, overloading the venous system, and leading to sensorineural hearing loss. We speculate about possible local treatments to alleviate the impact of such critical lesions on the labyrinthine microcirculation.

Auditory sensitivity and frequency resolution depend on the optimal transfer of sound-induced vibrations from the basilar membrane (BM) to the inner hair cells (IHCs), the principal auditory receptors. There remains a paucity of information on how this is accomplished along the frequency range in the human cochlea. Most of the current knowledge is derived either from animal experiments or human tissue processed after death, offering limited structural preservation and optical resolution. In our study, we analyzed the cytoarchitecture of the human cochlear partition at different frequency locations using high-resolution microscopy of uniquely preserved normal human tissue. The results may have clinical implications and increase our understanding of how frequency-dependent acoustic vibrations are carried to human IHCs. A 1-micron-thick plastic-embedded section (mid-modiolar) from a normal human cochlea uniquely preserved at lateral skull base surgery was analyzed using light and transmission electron microscopy (LM, TEM). Frequency locations were estimated using synchrotron radiation phase-contrast imaging (SR-PCI). Archival human tissue prepared for scanning electron microscopy (SEM) and super-resolution structured illumination microscopy (SR-SIM) were also used and compared in this study. Microscopy demonstrated great variations in the dimension and architecture of the human cochlear partition along the frequency range. Pillar cell geometry was closely regulated and depended on the reticular lamina slope and tympanic lip angle. A type II collagen-expressing lamina extended medially from the tympanic lip under the inner sulcus, here named "accessory basilar membrane." It was linked to the tympanic lip and inner pillar foot, and it may contribute to the overall compliance of the cochlear partition. Based on the findings, we speculate on the remarkable microanatomic inflections and geometric relationships which relay different sound-induced vibrations to the IHCs, including their relevance for the evolution of human speech reception and electric stimulation with auditory implants. The inner pillar transcellular microtubule/actin system's role of directly converting vibration energy to the IHC cuticular plate and ciliary bundle is highlighted. Mid-modiolar semi-thin section of a human cochlea with tonotopic estimates based on synchrotron 3-D imaging.image

The paper aims to fulfil three main functions: (1) to serve as an introduction for the physics education community to the functioning of large language models (LLMs), (2) to present a series of illustrative examples demonstrating how prompt-engineering techniques can impact LLMs performance on conceptual physics tasks and (3) to discuss potential implications of the understanding of LLMs and prompt engineering for physics teaching and learning. We first summarise existing research on the performance of a popular LLM-based chatbot (ChatGPT) on physics tasks. We then give a basic account of how LLMs work, illustrate essential features of their functioning, and discuss their strengths and limitations. Equipped with this knowledge, we discuss some challenges with generating useful output with ChatGPT-4 in the context of introductory physics, paying special attention to conceptual questions and problems. We then provide a condensed overview of relevant literature on prompt engineering and demonstrate through illustrative examples how selected prompt-engineering techniques can be employed to improve ChatGPT-4's output on conceptual introductory physics problems. Qualitatively studying these examples provides additional insights into ChatGPT's functioning and its utility in physics problem-solving. Finally, we consider how insights from the paper can inform the use of LLMs in the teaching and learning of physics.

In this paper, we evaluate the performance of three freely available vision-capable chatbots – Copilot, Gemini, and Claude 3 Sonnet – on the Test of Understanding Graphs in Kinematics (TUG-K). Our analysis highlights a performance gap between these freely available chatbots and the state-of-the-art, subscriptionbased ChatGPT-4. We also report largely unclear patterns of performance of the tested chatbots on different types of tasks. We discuss the implications of our findings for using chatbots in educational contexts, point out potential challenges for educational equity, and provide some ideas for future research that could help us better understand the patterns in the chatbots’ performance on tasks that involve the interpretation of graphical input.

This study investigates the performance of eight large multimodal model (LMM)based chatbots on the Test of Understanding Graphs in Kinematics (TUG-K), a research-based concept inventory. Graphs are a widely used representation in STEM and medical fields, making them a relevant topic for exploring LMMbased chatbots’ visual interpretation abilities. We evaluated both freely available chatbots (Gemini 1.0 Pro, Claude 3 Sonnet, Microsoft Copilot, and ChatGPT-4o) and subscription-based ones (Gemini 1.0 Ultra, Gemini 1.5 Pro API, Claude 3 Opus, and ChatGPT-4). We  found that OpenAI’s chatbots outperform all the others, with ChatGPT-4o showing the overall best performance. Contrary to expectations, we found no notable differences in the overall performance between freely available and subscription-based versions of Gemini and Claude 3 chatbots, with the exception of Gemini 1.5 Pro, available via API. In addition, we found that tasks relying more heavily on linguistic input were generally easier for chatbots than those requiring visual interpretation. The study provides a basis for considerations of LMM-based chatbot applications in STEM and medical education, and suggests directions for future research.

The well-known artificial intelligence-based chatbot ChatGPT-4 has become able to process image data as input in October 2023. We investigated its performance on the test of understanding graphs in kinematics to inform the physics education community of the current potential of using ChatGPT in the education process, particularly on tasks that involve graphical interpretation. We found that ChatGPT, on average, performed similarly to students taking a high-school level physics course, but with important differences in the distribution of the correctness of its responses, as well as in terms of the displayed “reasoning” and “visual” abilities. While ChatGPT was very successful at proposing productive strategies for solving the tasks on the test and expressed correct reasoning in most of its responses, it had difficulties correctly “seeing” graphs. We suggest that, based on its performance, caution and a critical approach are needed if one intends to use it in the role of a tutor, a model of a student, or a tool for assisting vision-impaired persons in the context of kinematics graphs.

[This paper is part of the Focused Collection in Artificial Intelligence Tools in Physics Teaching and Physics Education Research.] Artificial intelligence-based chatbots are increasingly influencing physics education because of their ability to interpret and respond to textual and visual inputs. This study evaluates the performance of two large multimodal model-based chatbots, ChatGPT-4 and ChatGPT-4o, on the brief electricity and magnetism assessment (BEMA), a conceptual physics inventory rich in visual representations such as vector fields, circuit diagrams, and graphs. Quantitative analysis shows that ChatGPT-4o outperforms both ChatGPT-4 and a large sample of university students, and demonstrates improvements in ChatGPT-4o's vision interpretation ability over its predecessor ChatGPT-4. However, qualitative analysis of ChatGPT-4o's responses reveals persistent challenges. We identified three types of difficulties in the chatbot's responses to tasks on BEMA: (i) difficulties with visual interpretation, (ii) difficulties in providing correct physics laws or rules, and (iii) difficulties with spatial coordination and application of physics representations. Spatial reasoning tasks, particularly those requiring the use of the right-hand rule, proved especially problematic. These findings highlight that the most broadly used large multimodal model-based chatbot, ChatGPT-4o, still exhibits significant difficulties in engaging with physics tasks involving visual representations. While the chatbot shows potential for educational applications, including personalized tutoring and accessibility support for students who are blind or have low vision, its limitations necessitate caution. On the other hand, our findings can also be leveraged to design assessments that are difficult for chatbots to solve.

We investigate the multilingual and multimodal performance of a large language model-based artificial intelligence (AI) system, GPT-4o, using a diverse set of physics concept inventories spanning multiple languages and subject categories. The inventories, sourced from the PhysPort website, cover classical physics topics such as mechanics, electromagnetism, optics, and thermodynamics, as well as relativity, quantum mechanics, astronomy, mathematics, and laboratory skills. Unlike previous text-only studies, we uploaded the inventories as images to reflect what a student would see on paper, thereby assessing the system's multimodal functionality. Our results indicate variation in performance across subjects, with laboratory skills standing out as the weakest. We also observe differences across languages, with English and European languages showing the strongest performance. Notably, the relative difficulty of an inventory item is largely independent of the language of the test. When comparing AI results to existing literature on student performance, we find that the AI system outperforms average postinstruction undergraduate students in all subject categories except laboratory skills. Furthermore, the AI performs worse on items requiring visual interpretation of images than on those that are purely text-based. While our exploratory findings show GPT-4o's potential usefulness in physics education, they highlight the critical need for instructors to foster students' ability to critically evaluate AI outputs, adapt curricula thoughtfully in response to AI advancements, and address equity concerns associated with AI integration.

Multimodal large language models (MLLMs) capable of processing both text and visual inputs are increasingly being explored for uses in physics education, such as tutoring, formative assessment, and grading. This study evaluates a range of publicly available MLLMs on a set of standardized, image-based physics research-based conceptual assessments (concept inventories). We benchmark 15 models from three major providers (Anthropic, Google, and OpenAI) across 102 physics items, focusing on two main questions: (1) How well do these models perform on conceptual physics tasks involving visual representations? and (2) What are the financial costs associated with their use? The results show high variability in both performance and cost. The performance of the tested models ranges from 81.5% to as low as 21%. We also found that expensive models do not always outperform cheaper ones and that, depending on the demands of the context, cheaper models may be sufficiently capable for some tasks. This is especially relevant in contexts where financial resources are limited or for large-scale educational implementation of MLLMs. By providing these analyses, our aim is to inform teachers, institutions, and other educational stakeholders so that they can make evidence-based decisions about the selection of models for use in AI-supported physics education.

Hepatocellular carcinoma (HCC) is characterized by a low and variable response to chemotherapeutic treatments. One contributing factor to the overall pharmacodynamics is the activation of endoplasmic reticulum (ER) stress pathways. This is a cellular stress mechanism that becomes activated when the cell's need for protein synthesis surpasses the ER's capacity to maintain accurate protein folding, and has been implicated in creating drug-resistance in several solid tumors. Objective: To identify the role of ER-stress and lipid metabolism in mediating drug response in HCC. Methods: By using a chemically-induced mouse model for HCC, we administered the ER-stress inhibitor 4m8C and/or doxorubicin (DOX) twice weekly for three weeks post-tumor initiation. Histological analyses were performed alongside comprehensive molecular biology and lipidomics assessments of isolated liver samples. In vitro models, including HCC cells, spheroids, and patient-derived liver organoids were subjected to 4m8C and/or DOX, enabling us to assess their synergistic effects on cellular viability, lipid metabolism, and oxygen consumption rate. Results: We reveal a pivotal synergy between ER-stress modulation and drug response in HCC. The inhibition of ER-stress using 4m8C not only enhances the cytotoxic effect of DOX, but also significantly reduces cellular lipid metabolism. This intricate interplay culminates in the deprivation of energy reserves essential for the sustenance of tumor cells. Conclusions: This study elucidates the interplay between lipid metabolism and ER-stress modulation in enhancing doxorubicin efficacy in HCC. This novel approach not only deepens our understanding of the disease, but also uncovers a promising avenue for therapeutic innovation. The long-term impact of our study could open the possibility of ER-stress inhibitors and/or lipase inhibitors as adjuvant treatments for HCC-patients. (c) 2023 The Author(s). Published by Elsevier GmbH. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

INTRODUCTION: Hepatocellular carcinoma (HCC) is a common cause of cancer-related death, often detected in the intermediate stage. The standard of care for intermediate-stage HCC is transarterial chemoembolisation (TACE), where idarubicin (IDA) is a promising drug. Despite the fact that TACE has been used for several decades, treatment success is unpredictable. This clinical trial has been designed believing that further improvement might be achieved by increasing the understanding of interactions between local pharmacology, tumour targeting, HCC pathophysiology, metabolomics and molecular mechanisms of drug resistance.

METHODS AND ANALYSIS: The study population of this single-centre clinical trial consists of adults with intermediate-stage HCC. Each tumour site will receive TACE with two different IDA doses, 10 and 15 mg, on separate occasions. Before and after each patient's first TACE blood samples, tissue and liquid biopsies, and positron emission tomography (PET)/MRI will be performed. Blood samples will be used for pharmacokinetics (PK) and liver function evaluation. Tissue biopsies will be used for histopathology analyses, and culturing of primary organoids of tumour and non-tumour tissue to measure cell viability, drug response, multiomics and gene expression. Multiomics analyses will also be performed on liquid biopsies. PET/MRI will be used to evaluate tumour viability and liver metabolism. The two doses of IDA will be compared regarding PK, antitumour effects and safety. Imaging, molecular biology and multiomics data will be used to identify HCC phenotypes and their relation to drug uptake and metabolism, treatment response and survival.

ETHICS AND DISSEMINATION: Participants give informed consent. Personal data are deidentified. A patient will be withdrawn from the study if considered medically necessary, or if it is the wish of the patient. The study has been approved by the Swedish Ethical Review Authority (Dnr. 2021-01928) and by the Medical Product Agency, Uppsala, Sweden.

TRIAL REGISTRATION NUMBER: EudraCT number: 2021-001257-31.

This paper seeks to understand how dominant high-carbon imaginaries, such as those associated with coal, can be disassembled from within. Although resistance can have a disruptive potential to threaten the prevailing energy narrative, in certain contexts, the complete replacement of the dominant imaginary with an alternative one may not always be feasible or preferable. The paper shows how thinking about disassembly from within can be achieved by bringing the interpretative envelope of sociotechnical imaginaries (STI) into productive conversation with the concepts of hyperobject and hyposubjects. While the analytical framework of STI accounts for the material-normative co-production of future-making, the hyperobject emphasises the effects of human-natural interconnectedness, and hyposubjects elucidate how this mesh can be used generatively through attunement and subscendence. The paper illustrates this way of thinking about disassembling from within by focusing on Upper Silesia, a region in Poland uniquely bound to coal. Through the case of a local activist group Queer Silesia, the paper provides a perspective on disassembly from within where elements of the old but prevailing imaginary can be repurposed to create visions of the post-coal future without erasing the resource's legacy or compromising social cohesion.

This paper examines local imaginaries of coal within the mining communities of Upper Silesia in southern Poland, offering a grounded perspective on how coal-shaped visions of a good life emerge from lived, material experiences. Drawing on the concept of bounded imaginaries, we shift focus from dominant national narratives to locally held, non-expert visions engendered by coal's material presence. Our analysis of ethnographic and historical evidence demonstrates that the material experience of coal and mining labour fosters a bounded imaginary with two interrelated dimensions: one centred on people, the other on the Earth. The people-centred dimension reveals how local visions of the good life enabled by coal are rooted in supportive and stable communities that care for their social environment. In the Earth-centred dimension, the meaning of the good life is grounded in respect for natural resources’ role in sustaining human societies, an awareness of the fragility of human life, and an ethos of sufficiency. Both dimensions stem from engagement with coal's materiality, revealing visions of a good life that are not readily accessible to those without tangible experience of coal. We argue that such imaginaries hold transformative potential for shaping socially just energy transitions that are attuned to local needs and aspirations. In Upper Silesia, where coal phase-out is gaining momentum through Just Transition Funds, these bounded imaginaries can further inform emerging models of distributed renewable energy production driven by local communities. Rather than dismissing attachments to coal as relics of the past, this paper shows how the lived experiences and material entanglements of coal communities can be mobilised generatively in designing post-coal futures. By foregrounding the material roots of local imaginaries, our findings contribute to broader debates in energy social science about the importance of place-based visions, experiential knowledge, and care in driving just transitions.

We deploy the concept of alienation to analyse how coal industry workers in Upper Silesia, Poland, view the work of energy provision and strive to cultivate meaningful attachments to social orders, cultural practices, and the environment coproduced with coal. We argue that alienation is neither a complete nor fixed state but a partial and ongoing process - members of coal communities can experience alienation in certain aspects of their lives, while simultaneously engaging in unalienated conscious life activity in other areas. By analysing ethnographic material through the lens of alienation, we discern aspects of energy-producing labour that are valued by coal miners, and how these energy workers experience both moments of alienation and unalienation. We also show that coal communities in transition desire and actively cultivate meaningful social connections. Deploying the concept of alienation in this way, we suggest, can support transitions in energy-producing labour that are dignified and meaningful.

In this paper, I ethnographically explore embodied modes of engagement with material legacies of the coal-based energy system in Polish regions in transition to discern local and materially-grounded visions of desirable futures. In doing so, I bring questions about how to disempower existing ideas of preferred social orders - and how to nourish alternative visions - into the sociotechnical imaginaries’ literature. I build on the idea of “disassembling from within”, wherein the interpretative capacity of STI is brought into conversation with Object-Oriented Ontology to centre bottom-up strategies of generative disassembly based on engagement with the material legacy of coal extraction and energy production. These situated modes of disassembling are attunement - practices based on listening to, sensing, and working with what is already there - and subscendence - relational and context-sensitive experimentation which prioritises collaboration by retooling socio-material entanglements with the past. I offer examples of attunement and subscendence from two different coal regions - Upper Silesia and Eastern Greater Poland - to show the context-specificity of these processes. I argue that the cross-fertilization of STI and OOO can sensitise social science energy research to social orders desired by people through their sensory engagement with environments altered by coal extraction. Analytical scrutiny of this material reality can lead to generative disassembly of the dominant imaginary of coal through retooling of the elements of the past, forming solidarity alliances with others (including damaged environments), and prototyping new ways of cohabiting with legacies of the extractive industry without reproducing their harmful logics. 

Objectives: C1q is a valuable biomarker of disease activity in systemic lupus erythematosus (SLE). The "gold standard" assay, rocket immunoelectrophoresis (RIE), is time-consuming, and thus a shift to soluble immune precipitation techniques such as nephelometry has occurred. However, quantification of C1q with these techniques has been questioned as a result of the antibody binding properties of C1q. In the present work, we have compared results using various techniques (RIE, nephelometry, and ELISA) and have developed and validated a new magnetic bead-based sandwich immunoassay (MBSI). Methods: C1q was quantified by nephelometry and the new sandwich immunoassay in 45 serum samples analyzed using RIE. C1q was also assessed in plasma using RIE and sandwich immunoassay in samples from SLE patients with nephritis (n = 69), SLE patients without nephritis (n = 310) as classified by BILAG score, and matched controls (n = 322). In addition, cerebrospinal fluid (CSF) samples from 31 patients, previously analyzed with ELISA, were also analyzed with the MBSI to test the behavior of this new assay in the lower detection range. Results: We found a strong correlation between the new MBSI, RIE, and ELISA, but not with nephelometry. The MBSI demonstrated lower levels of C1q in SLE patients than in matched controls (p < 0.0001), and patients with nephritis had lower levels than patients without nephritis (p < 0.01). Similarily, RIE showed significant differences between the patient groups (p < 0.0001). An association was also found between the levels of C1q and the SLE disease activity index (SLEDAI). Furthermore, there was good correlation between the values obtained by MBSI and ELISA, in both serum (r = 0.960) and CSF (r = 0.786), underscoring the ability of both techniques to measure low concentrations of C1q with high accuracy. Conclusion: The sandwich immunoassay correlated well with RIE, but soluble immune precipitation techniques, such as nephelometry, did not appear suitable alternatives, since C1q itself, and possibly anti-C1q antibodies, interfered with the measurements. The new sandwich immunoassay is therefore a good replacement for RIE in monitoring SLE disease activity.

The ongoing COVID-19 pandemic has caused significant morbidity and mortality worldwide, as well as profound effects on society. COVID-19 patients have an increased risk of thromboembolic (TE) complications, which develop despite pharmacological thromboprophylaxis. The mechanism behind COVID-19-associated coagulopathy remains unclear. Mannose-binding lectin (MBL), a pattern recognition molecule that initiates the lectin pathway of complement activation, has been suggested as a potential amplifier of blood coagulation during thromboinflammation. Here we describe data from a cohort of critically ill COVID-19 patients (n = 65) treated at a tertiary hospital center intensive care unit (ICU). A subset of patients had strongly elevated MBL plasma levels, and activity upon ICU admission, and patients who developed symptomatic TE (14%) had significantly higher MBL levels than patients without TE. MBL was strongly correlated to plasma D-dimer levels, a marker of COVID-19 coagulopathy, but showed no relationship to degree of inflammation or other organ dysfunction. In conclusion, we have identified complement activation through the MBL pathway as a novel amplification mechanism that contributes to pathological thrombosis in critically ill COVID-19 patients. Pharmacological targeting of the MBL pathway could be a novel treatment option for thrombosis in COVID-19. Laboratory testing of MBL levels could be of value for identifying COVID-19 patients at risk for TE events.

An important manifestation of severe COVID-19 is the ARDS-like lung injury that is associated with vascular endothelialitis, thrombosis, and angiogenesis. The intravascular innate immune system (IIIS), including the complement, contact, coagulation, and fibrinolysis systems, which is crucial for recognizing and eliminating microorganisms and debris in the body, is likely to be involved in the pathogenesis of COVID-19 ARDS. Biomarkers for IIIS activation were studied in the first 66 patients with COVID-19 admitted to the ICU in Uppsala University Hospital, both cross-sectionally on day 1 and in 19 patients longitudinally for up to a month, in a prospective study. IIIS analyses were compared with biochemical parameters and clinical outcome and survival. Blood cascade systems activation leading to an overreactive conjunct thromboinflammation was demonstrated, reflected in consumption of individual cascade system components, e.g., FXII, prekallikrein, and high molecular weight kininogen and in increased levels of activation products, e.g., C4d, C3a, C3d,g, sC5b-9, TAT, and D-dimer. Strong associations were found between the blood cascade systems and organ damage, illness severity scores, and survival. We show that critically ill COVID-19 patients display a conjunct activation of the IIIS that is linked to organ damage of the lung, heart, kidneys, and death. We present evidence that the complement and in particular the kallikrein/kinin system is strongly activated and that both systems are prognostic markers of the outcome of the patients suggesting their role in driving the inflammation. Already licensed kallikrein/kinin inhibitors are potential drugs for treatment of critically ill patients with COVID-19.

Astrocytes not only play a central role in orchestrating the brain's microenvironment but also are tightly connected to neurodegenerative processes. Hence, unraveling astrocytes' intercellular pathways can give important insight into disease-spreading mechanisms. Here, we describe a distinct form of actively migrating cellular vehicles, which we have named zombosomes. Zombosomes shed from astrocytes but retain their adhesive and motile properties, even though they lack nuclei. They share protein markers with their parental astrocytes, including highly packed vimentin, and are loaded with intact organelles. Importantly, zombosomes act as disease couriers, transferring alpha-synuclein aggregates from one cell to another, and have the capacity to infiltrate and induce pathology in cerebral organoids. Human brain sections show scattered vimentin-rich zombosomes with no attachments to nearby astrocytes, which contain deposits of aggregated alpha-synuclein. Taken together, our findings represent an interaction pathway between distant cells through "live" vehicles that when misused, may cause propagation of Parkinson's disease pathology.

Alzheimer’s disease (AD) and Parkinson’s disease (PD) are the most common neurodegenerative disorders, both characterized by accumulation of aggregated proteins. In AD, the pathological deposits consist predominantly of amyloid-beta (Aβ) and tau, while alpha-synuclein (αSYN) forms inclusions in PD. However, cross-seeding often generates mixed pathologies. Emerging evidence suggests a role of astrocytes in disease spreading, but the underlying mechanisms remain unclear, partly due to limitations of mouse models in replicating early human disease. To address this, we developed a human cerebral organoid platform to study early sporadic AD/PD events. We introduced fibrillar aggregates of αSYN, Aβ, and tau directly into organoids or via astrocytes pre-exposed to the aggregates. All proteins successfully penetrated the organoids with distinct morphology and distribution patterns. Twelve weeks post-exposure, organoids exposed to Aβ or αSYN-containing astrocytes showed the highest insoluble tau levels, but none developed robust tau pathology, highlighting limitations in organoid modeling of tau pathology.

Purpose Small intestinal neuroendocrine tumours (SI-NETs) are the most common malignancy of the small bowel. Curative treatment is surgical, with exploratory laparotomy considered the standard approach. This study aimed to assess the outcomes of minimally invasive surgery compared to open approach for SI-NETs at the Endocrine surgical unit at Uppsala University Hospital. Methods This retrospective cohort study included patients who underwent surgery for SI-NET between 2013 and 2023 at Uppsala University Hospital. Variables such as operative time, length of hospital stay, use of analgesia and radicality were compared between groups of patients operated on before and after 2019, when hand-port assisted laparoscopic surgery (HALS) for SI-NETs was introduced at our unit. Outcomes were further compared between open and hand-port assisted laparoscopic approaches. The primary outcome was the rate of radicality achieved for stage II-III patients. Secondary outcomes included operative time, the length of hospital stay and the use of epidural and patient-controlled analgesia. Results Of 97 patients, 58 (59.8%) underwent open surgery and 39 (40.2%) underwent hand-port assisted laparoscopic surgery. There was no significant difference in operative time (121 min [91.3-150.3] vs 108 min [83-141]), length of hospital stay, 6 days [4-7] vs 5 days [4-8]), and surgical radicality in patients with stage II-III, 85.2% vs 100%, (p = 0.079). 86.2% of patients with explorative laparotomy required epidural analgesia compared to only 23.1% with HALS (p < 0.001). Conclusion Hand-port assisted laparoscopic surgery of SI-NETs is a feasible approach that preserves radical resection while enhancing postoperative recovery, with a lower requirement of epidural analgesia.

Small intestinal neuroendocrine tumors are often diagnosed at an advanced stage, with up to 70% of patients presenting with stage IV disease. While some guidelines recommend prophylactic resection of the primary tumor and mesenteric lymph node metastasis in patients without abdominal symptoms at diagnosis to prevent future abdominal complications, the benefit of this approach remains uncertain.This retrospective cohort study included 44 asymptomatic patients with stage IV small intestinal neuroendocrine tumors treated at Uppsala University Hospital between 2014 and 2019. Additional ten symptomatic patients who underwent at least two computed tomography scans before planned surgery were included in the analysis of mesenteric metastasis volume change and tumor growth rate. The primary outcomes were abdominal symptoms development requiring surgical intervention and the assessment of mesenteric metastasis size progression. During a 10-year follow-up, only four initially asymptomatic patients (9%) developed symptoms leading to surgery. Among all 54 patients, the median volume change in mesenteric metastases was -298 mm3 (IQR: -2,785-1,294), with no significant difference between baseline and most recent scans (P = 0.38). The median interval between scans was 29 months, and the median tumor growth rate was -0.6% per month (IQR: -3.6-1.9%). Similar results were observed in the asymptomatic group. These findings suggest that a non-operative management in stage IV patients without abdominal symptoms is associated with a low incidence of symptom development and limited progression of mesenteric metastases.

Background

Awareness of the potential global overtreatment of patients with appendiceal neuroendocrine tumours (NETs) of 1–2 cm in size by performing oncological resections is increasing, but the rarity of this tumour has impeded clear recommendations to date. We aimed to assess the malignant potential of appendiceal NETs of 1–2 cm in size in patients with or without right-sided hemicolectomy.

Methods

In this retrospective cohort study, we pooled data from 40 hospitals in 15 European countries for patients of any age and Eastern Cooperative Oncology Group performance status with a histopathologically confirmed appendiceal NET of 1–2 cm in size who had a complete resection of the primary tumour between Jan 1, 2000, and Dec 31, 2010. Patients either had an appendectomy only or an appendectomy with oncological right-sided hemicolectomy or ileocecal resection. Predefined primary outcomes were the frequency of distant metastases and tumour-related mortality. Secondary outcomes included the frequency of regional lymph node metastases, the association between regional lymph node metastases and histopathological risk factors, and overall survival with or without right-sided hemicolectomy. Cox proportional hazards regression was used to estimate the relative all-cause mortality hazard associated with right-sided hemicolectomy compared with appendectomy alone. This study is registered with ClinicalTrials.gov, NCT03852693.

Findings

282 patients with suspected appendiceal tumours were identified, of whom 278 with an appendiceal NET of 1–2 cm in size were included. 163 (59%) had an appendectomy and 115 (41%) had a right-sided hemicolectomy, 110 (40%) were men, 168 (60%) were women, and mean age at initial surgery was 36·0 years (SD 18·2). Median follow-up was 13·0 years (IQR 11·0–15·6). After centralised histopathological review, appendiceal NETs were classified as a possible or probable primary tumour in two (1%) of 278 patients with distant peritoneal metastases and in two (1%) 278 patients with distant metastases in the liver. All metastases were diagnosed synchronously with no tumour-related deaths during follow-up. Regional lymph node metastases were found in 22 (20%) of 112 patients with right-sided hemicolectomy with available data. On the basis of histopathological risk factors, we estimated that 12·8% (95% CI 6·5 –21·1) of patients undergoing appendectomy probably had residual regional lymph node metastases. Overall survival was similar between patients with appendectomy and right-sided hemicolectomy (adjusted hazard ratio 0·88 [95% CI 0·36–2·17]; p=0·71).

Interpretation

This study provides evidence that right-sided hemicolectomy is not indicated after complete resection of an appendiceal NET of 1–2 cm in size by appendectomy, that regional lymph node metastases of appendiceal NETs are clinically irrelevant, and that an additional postoperative exclusion of metastases and histopathological evaluation of risk factors is not supported by the presented results. These findings should inform consensus best practice guidelines for this patient cohort.

Purpose

The build-up of large-scale COVID-19 testing required an unprecedented effort of coordination within decentralized healthcare systems around the world. The aim of the study was to elucidate the challenges of vertical policy coordination between non-political actors at the national and regional levels regarding this policy issue, using Sweden as our case.

Design/methodology/approach

Interviews with key actors at the national and regional levels were analyzed using an adapted version of a conceptualization by Adam et al. (2019), depicting barriers to vertical policy coordination.

Findings

Our results show that the main issues in the Swedish context were related to parallel sovereignty and a vagueness regarding responsibilities and mandates as well as complex governmental structures and that this was exacerbated by the unfamiliarity and uncertainty of the policy issue. We conclude that understanding the interaction between the comprehensiveness and complexity of the policy issue and the institutional context is crucial to achieving effective vertical policy coordination.

Originality/value

Many studies have focused on countries’ overall pandemic responses, but in order to improve the outcome of future pandemics, it is also important to learn from more specific response measures.

This article investigates how the institutional conditions of multi-level contexts are accommodated in central-local governance by analyzing policy agreements in the Swedish healthcare sector. These policy agreements have developed in recent decades, and are today an instrument mix that constitutes a new way for the national government to govern the decentralized healthcare sector. In the study, this new instrument mix is related to the decentralized unitary context of Sweden by investigating how steering and cooperation are combined in the formulation and composition of three policy agreements. The results show how adaptable steering is made possible by opportunities for continuous communication and a shared administrative structure between regional and national actors. Furthermore, through flexibility in the roles of involved actors, particularly the national government, the policy agreements allow for consensus-making and a sense of togetherness between governmental levels. Arguably, this shows how instrument mixes can accommodate steering and cooperation in ways that can be important for central-local governance in the future. Also, the study relates to recent scholarly work on the relation between governmental levels in unitary contexts which, until recently, has been largely neglected.

Molecular catalysts for water oxidation and other electrochemical transformations have been a focus of significant research over recent decades. Among these, α-[Fe(mcp)L2] complexes stand out as one of the most active non-heme iron-based molecular catalyst for water oxidation. This study investigates how the Fe(II)/Fe(III) redox potential of these catalysts varies with the identity of their labile ligands (L). Using cyclic voltammetry and complementary spectroscopic techniques (UV/Vis, 1H-NMR), we examined how ligands bind to the metal centre. Systematic variation of the labile ligand (L) demonstrated that the catalyst's redox potential in acetonitrile solution strongly depends on ligand identity. By introducing stoichiometric amounts of different anions to the electrolyte, the redox potential was tuned across a 1.5 V potential window.In aqueous solutions, the redox potential depended on both pH and electrolyte anion identity. These dependencies were successfully fitted to a thermodynamic model that was obtained by extending the typical proton-coupled electron transfer square scheme into a cube scheme that incorporates anion binding. The equation derived from this model provides valuable insights into the ligand-binding dynamics at the iron centre under diverse conditions.

We report the synthesis of an EDOT-functionalizedmcp ligand that enables direct immobilization of [M(mcp)X₂]complexes (M = Fe, Co, Cu, Ru) into conducting redox polymers(CRPs) via electropolymerization. Poly(EDOT-co-[Fe(EDOT-mcp)-X₂]) films were thoroughly characterized in both acetonitrile andwater using cyclic voltammetry, in situ conductance measurements,and in situ UV/Vis spectroelectrochemistry. These operando studiesdisentangle backbone doping from the Fe(III)/Fe(II) pendant groupredox transition, revealing that charge transport proceeds predominantly through the polymer backbone, while the pendant complexesoperate as discrete electroactive sites. The Fe redox potential is highlysensitive to electrolyte anion coordinating strength and concentration,reflecting ligand exchange at the labile sites. In water, theelectrochemical response is governed by proton-coupled electron transfer and is strongly affected by pH and buffer identity.Only when buffer ions penetrate the polymer bulk at sufficiently high buffer concentrations do the pendant groups experiencethe same effective proton activity as the surrounding electrolyte. Although attempts at catalytic water oxidation confirm Fe-centeredoxidation chemistry, the material undergoes rapid conductivity loss at anodic potentials, indicating backbone degradation underturnover conditions. These findings establish the EDOT-mcp platform as a versatile immobilization strategy for mcp-type metalcomplexes and highlight design requirements for improving stability in oxidative catalysis.

Surface immobilization is essential to investigate the kinetics of coupled electron transfer processes. In this study, we demonstrate a novel surface immobilization protocol for the amino-pyridyl ligand mcp and the corresponding iron complexes. The approach utilizes a maleimide linker that readily reacts with glassy carbon surfaces under mild reaction conditions without the use of a catalyst or other reagents. The obtained sub-monolayers (Γ = 1.02 × 10⁻¹⁰ mol cm⁻²) of α-[Fe(mcp)Cl₂]@GC showed good electrochemical stability in MeCN as well as in aqueous electrolytes across a range of pH values. The equilibrium potential depends on both the electrolyte anion and the pH. The thermodynamics of the system can be rationalized using a simple equation derived from two orthogonal square schemes, one for the proton-coupled electron transfer (PCET) and one for the anion-coupled electron transfer (ACET), yielding a three-dimensional Pourbaix diagram. The corresponding electron transfer kinetics were faster than the RC time constant of the given setup and could therefore not yet be resolved.

We present an efficient method to compute diffusion coefficients of multiparticle systems with strong interactions directly from the geometry and topology of the potential energy field of the migrating particles. The approach is tested on Li-ion diffusion in crystalline inorganic solids, predicting Li-ion diffusion coefficients within 1 order of magnitude of molecular dynamics simulations at the same level of theory while being several orders of magnitude faster. The speed and transferability of our workflow make it well-suited for extensive and efficient screening studies of crystalline solid-state ion conductor candidates and promise to serve as a platform for diffusion prediction even up to the density functional level of theory.

We present a method for large-scale DFT-based screening of ion diffusion in crystalline solids. This is accomplished by extending the Ionic TuTraSt method to sample the potential energy surface by using single-point DFT calculations. To drastically reduce the number of single-point DFT calculations, symmetry, interpolation, and exclusion of high-energy regions are employed. This approach is tested on a large data set of solid-state Li-ion conductors, for which the interpolation and high-energy exclusion are optimized to balance computational efficiency and accuracy of the obtained diffusion properties. Furthermore, the developed workflow is validated by comparison with ab initio molecular dynamics (AIMD) simulations on a set of known Li-ion superconducting materials.

Fast Li-ion diffusion in ceramic solid electrolytes is often explained by time-dependent ion-correlation effects such as concerted motion and the paddle-wheel effect, but many commonly used modeling approaches exclude some or all configurational entropy, which can lead to misleading results and conclusions. In this work, we separate the effects of ion distribution, ion−ion interactions, and framework dynamics using transition-state-theory-based models and ab initio molecular dynamics simulations. We show that simplified barrier-based models that neglect the full distributional space of the ions lead to overestimated diffusion, while excluding the full configurational entropy of ion−ion interactions results in a failure to accurately describe the energy landscape. However, an averaged ensemble distribution that includes configuration entropy, but lacks time resolution, is sufficient to accurately reproduce the flat energy landscapes identified in fast ionic conductors such as Li10GeP2S12, Li1.3Al0.3Ti1.7(PO4)3, and Li7La3Zr2O12. Framework dynamics further enhance diffusion in most structures by broadening low-energy regions and lowering effective barriers, increasing the diffusion on average by ∼0.5 orders of magnitude, with especially large effects in Li1.3Al0.3Ti1.7(PO4)3 and Li3PS4, while LiNbO3 shows the opposite behavior due to stronger Li−O interactions. Overall, our results show that configurational entropy plays a central role in Li-ion transport and should be clearly separated from true time-dependent correlation effects when interpreting diffusion mechanisms.

In this work, we investigate the diffusion in the prominent ceramic solid state electrolyte Lithium-Aluminum-Titanium-Phosphate(LATP) Li1+xAlxTi2–xPO4 in the entire range of substitution concentrations 0 ≤ x ≤ 2. Employing different computational tools, namely sampling the potential energy surface of the Li ions and performing molecular dynamics simulations, allows to separate the different mechanisms which lead to a change in the Li-ion diffusion upon changing the Al substitution concentration. Using a finetuned machine learning potential allows to study larger simulation cells and run longer MD simulations. This leads to converged, stable, diffusion coefficients and illustrates the spread in diffusion coefficients at constant substitution concentrations. The concentration of Li-ions is identified to have the strongest contribution to an increased diffusion, while local and cell rearrangements lead to a decreased diffusion at higher levels of Al substitution.

Aqueous solubility is one of the most important physicochemical properties of drug molecules and a major driving force for oral drug absorption. To date, the performance of in silico models for the estimation of solubility for novel chemical space is limited. To investigate possible reasons and remedies for this, the Johnson and Johnson in-house aqueous solubility data with over 40,000 compounds was leveraged. All data were generated through the same high-throughput assay, providing a unique opportunity to explore the relationship between data quality, quantity, and model estimations. Six intrinsic solubility data sets with different sizes and noise levels were generated by making use of three different approaches: (i) inclusion or exclusion of amorphous solid residue, (ii) measured or experimental log D to identify the intrinsic solubility, and (iii) adopting or omitting a quality check process in the data processing workflow. A random forest regressor was trained on the data sets with three different sets of descriptors calculated from RDKit, ADMET predictor, or Mordred, and the performances were evaluated with nested cross-validation as well as ten refined test sets. The models confirm, as expected, that with the same data set size, high-quality data leads to better model performance; however, also, models trained with larger data sets containing analytical variability can give equally accurate estimations compared to models trained with small, clean, and diverse data sets. However, noise introduced by including the presence of amorphous solid postsolubility measurement in the training data set cannot be overcome by increasing data size, as they are introducing a biased systematic positive error in the data set, confirming the importance of critical data review. Finally, two top-performing models were tested on the first test set from the second solubility challenge, achieving RMSE values of 0.74 and 0.72 and log S ± 0.5 of 46 and 48%, respectively. These results demonstrated improved performance compared to those reported in the findings of the competition, highlighting that a single-source curated data set can enhance the prediction of intrinsic solubility.Keywords: data quality; intrinsic solubility; machine learning; quantitative structure−property relationship (QSPR); solubility prediction.

Aqueous solubility of a compound plays a crucial role throughout various stages of drug discovery and development. Despite numerous efforts using various machine learning models, accurately estimating aqueous solubility remains a challenge. One primary limitation is the absence of a single source, large dataset of druglike compounds for model training. Additionally, studies have highlighted the need for improvements in prediction algorithms and molecular representations. To address these challenges, the Johnson and Johnson (J&J) in-house solubility data was leveraged. Theoretical pH-solubility equations and in-house pKa prediction tools were utilized to calculate intrinsic solubility from J&J data. A multi-task graph transformer model was developed and trained on the calculated intrinsic solubility data of 13,306 compounds along with seven relevant physicochemical properties including solubility at pH 2/7, logP, and logD at three different pHs. When evaluated making use of high-quality test data, the developed model achieved a root mean square error (RMSE) of 0.61 and coefficient of determination (R2) of 0.60, demonstrating state-of-the-art performance in estimating intrinsic solubility for drug-like compounds.

Kin relations among past societies can offer valuable information about the social dynamics of the population. Genetic data from prehistoric human remains can reveal genetic relatedness, and when combined with archaeological information, shed light on social factors shaping ancient communities. However, accessing such information on ancient hunter-gatherer societies has been challenging owing to the scarcity of temporally overlapping multi-burial sites. Here, we focused on the Pitted Ware Culture (PWC) cemetery from Ajvide (Gotland, Sweden), one of Stone Age Europe's largest and best-preserved hunter-gatherer burial grounds of the European Stone Age. We generated new genomic data from 10 individuals, primarily from co-burial contexts, and combined these with published genomes from 24 individuals across four PWC sites on Gotland. The genetic analyses revealed dual ancestry of the Gotlandic PWC, showing approximately 80% ancestry associated with earlier Mesolithic hunter-gatherer groups and 20% with farmer groups. We also identified close genetic relatives between the different studied PWC sites on Gotland, indicating mixing of the groups. All individuals buried together were closely related to one another, including first-, second- and third-degree relatives, and showed significantly elevated genetic relatedness. This demonstrates that genetic relatedness played a defining role in the co-burial ritual and extended beyond first-degree relatives.

In the period between 5,300 and 4,900 calibrated years before present (cal. bp), populations across large parts of Europe underwent a period of demographic decline1,2. However, the cause of this so-called Neolithic decline is still debated. Some argue for an agricultural crisis resulting in the decline3, others for the spread of an early form of plague4. Here we use population-scale ancient genomics to infer ancestry, social structure and pathogen infection in 108 Scandinavian Neolithic individuals from eight megalithic graves and a stone cist. We find that the Neolithic plague was widespread, detected in at least 17% of the sampled population and across large geographical distances. We demonstrate that the disease spread within the Neolithic community in three distinct infection events within a period of around 120 years. Variant graph-based pan-genomics shows that the Neolithic plague genomes retained ancestral genomic variation present in Yersinia pseudotuberculosis, including virulence factors associated with disease outcomes. In addition, we reconstruct four multigeneration pedigrees, the largest of which consists of 38 individuals spanning six generations, showing a patrilineal social organization. Lastly, we document direct genomic evidence for Neolithic female exogamy in a woman buried in a different megalithic tomb than her brothers. Taken together, our findings provide a detailed reconstruction of plague spread within a large patrilineal kinship group and identify multiple plague infections in a population dated to the beginning of the Neolithic decline.

During adolescence, emotion regulation and reactivity are still developing and are in many ways qualitatively different from adulthood. However, the neurobiological processes underpinning these differences remain poorly understood, including the role of maturing neurotransmitter systems. We combined magnetic resonance spectroscopy in the dorsal anterior cingulate cortex (dACC) and self-reported emotion regulation and reactivity in a sample of typically developed adolescents (n = 37; 13-16 years) and adults (n = 39; 30-40 years), and found that adolescents had higher levels of glutamate to total creatine (tCr) ratio in the dACC than adults. A glutamate i age group interaction indicated a differential relation between dACC glutamate levels and emotion regulation in adolescents and adults, and within-group follow-up analyses showed that higher levels of glutamate/tCr were related to worse emotion regulation skills in adolescents. We found no age-group differences in gamma-aminobutyric acid+macromolecules (GABA+) levels; however, emotion reactivity was positively related to GABA+/tCr in the adult group, but not in the adolescent group. The results demonstrate that there are developmental changes in the concentration of glutamate, but not GABA+, within the dACC from adolescence to adulthood, in accordance with previous findings indicating earlier maturation of the GABA-ergic than the glutamatergic system. Functionally, glutamate and GABA+ are positively related to emotion regulation and reactivity, respectively, in the mature brain. In the adolescent brain, however, glutamate is negatively related to emotion regulation, and GABA+ is not related to emotion reactivity. The findings are consistent with synaptic pruning of glutamatergic synapses from adolescence to adulthood and highlight the importance of brain maturational processes underlying age-related differences in emotion processing.

Past results suggest that fear extinction and the return of extinguished fear are compromised in adolescents. However, findings have been inconclusive as there is a lack of fear extinction and extinction retention studies including children, adolescents and adults. In the present study, 36 children (6-9 years), 40 adolescents (13-17 years) and 44 adults (30-40 years), underwent a two-day fear conditioning task. Habituation, acquisition, and extinction were performed on the first day and an extinction retention test > 24 h later. Skin conductance responses were recorded during all phases of fear conditioning and functional magnetic resonance imaging (fMRI) was conducted during the fear retention test. All groups acquired and extinguished fear as measured with SCR, with no group differences in SCR during extinction retention. The groups had largely similar neural fear responses during the retention test, apart from adolescents displaying stronger amygdala fear response than children, with no differences between adolescents and adults. The findings do not support an adolescent extinction dip, and there was only marginal evidence of progressive changes in fear conditioning across development. In contrast to findings in rodents, fear conditioning in humans may elicit similar physiological responses and recruit similar neural networks from childhood to adulthood.

Compromised vascular integrity facilitates extravasation of cancer cells and promotes metastatic dissemination. CD93 has emerged as a target for antiangiogenic therapy, but its importance for vascular integrity in metastatic cancers has not been evaluated. Here, we demonstrate that CD93 participates in maintaining the endothelial barrier and reducing metastatic dissemination. Primary melanoma growth was hampered in CD93^–/– mice, but metastatic dissemination was increased and associated with disruption of adherens and tight junctions in tumor endothelial cells and elevated expression of matrix metalloprotease 9 at the metastatic site. CD93 directly interacted with vascular endothelial growth factor receptor 2 (VEGFR2) and its absence led to VEGF-induced hyperphosphorylation of VEGFR2 in endothelial cells. Antagonistic anti-VEGFR2 antibody therapy rescued endothelial barrier function and reduced the metastatic burden in CD93^–/– mice to wild-type levels. These findings reveal a key role of CD93 in maintaining vascular integrity, which has implications for pathological angiogenesis and endothelial barrier function in metastatic cancer.

Native mass spectrometry (MS) is widely employed to study the structures and assemblies of proteins ranging from small monomers to megadalton complexes. Molecular dynamics (MD) simulation is a useful complement as it provides the spatial detail that native MS cannot offer. However, MD simulations performed in the gas phase have suffered from rapidly increasing computational costs with the system size. The primary bottleneck is the calculation of electrostatic forces, which are effective over long distances and must be explicitly computed for each atom pair, precluding efficient use of methods traditionally used to accelerate condensed-phase simulations. As a result, MD simulations have been unable to match the capacity of MS in probing large multimeric protein complexes. Here, we apply the fast multipole method (FMM) for computing the electrostatic forces, recently implemented by Kohnke et al. (J. Chem. Theory Comput.,2020, 16, 6938-6949), showing that it significantly enhances the performance of gas-phase simulations of large proteins. We assess how to achieve adequate accuracy and optimal performance with FMM, finding that it expands the accessible size range and time scales dramatically. Additionally, we simulate a 460 kDa ferritin complex over microsecond time scales, alongside complementary ion mobility (IM)-MS experiments, uncovering conformational changes that are not apparent from the IM-MS data alone.

To reduce the vulnerability of power grids to high impact low probability (HILP) events, analysis methods can be applied to quantify the criticality of the nodes in the grid. The method implemented in this article is one originating from complex network theory. It is used to quantify the structural vulnerability of an open-source transmission grid model representing the Nordic transmission grid. The analytical measures used are clustering coefficient and betweenness, closeness, degree, and combined centrality, which are weighted with respect to the estimated values of the transmission lines’ series reactance. The results, which are presented in the form of geographic and network representations, show substantial differences in terms of criticality between the nodes. The most critical ones are highlighted in geographic representations and are further compared with an open-source system analysis performed by the Swedish transmission system operator (TSO). The outcome from this study is that the weighted and combined centrality measure performed the best in terms of identifying critical nodes in the Nordic transmission grid. Thus, the method can be used as a tool for assessing the structural vulnerability of a real transmission grid, even with limited access to electrical grid data. However, the results from this method should not be considered conclusive.

The ongoing transition towards large installations of offshore wind and the electrification of the transport sector and other critical infrastructures introduce new vulnerabilities to the society. Large dependencies of power production from offshore wind are expected in the next decades, but there are large knowledge gaps regarding the power production reliability under severe weather conditions. Simultaneously, weather extremes may increase in frequency and intensity, driven by climate change. In this paper we investigate the resilience of a power system subject to a hurricane event. The power system is based on the IEEE39-bus New England system but with different scenarios for increasing penetration of offshore wind. We find that an offshore wind penetration level of 30% or less results in a power system resilient to hurricane events, with no need for load disconnection. However, when increased to 40% offshore wind penetration, 650 MW corresponding to 10% of the total load demand gets disconnected during the storm peak. With a penetration of 50% offshore wind, the disconnected load ranges from 2.2 GW of load corresponding to 1/3 of the total load demand, to a total power system blackout.

In the next decades, the dependencies on power production from renewable energy sources are expected to increase dramatically. A transition towards large-scale offshore wind farms together with an increased electrification of the industry and transportation sectors introduces new vulnerabilities to society. Further, extreme weather events are expected to increase in intensity and frequency, driven by climate change. However, there are significant knowledge gaps concerning the impacts of severe weather conditions on the resilience of power systems with large dependencies on offshore wind. In the present study, a comparison between two different power systems’ resilience to historical extreme storm conditions has been conducted. The power systems are the IEEE39-bus New England model and the Great Britain model. The results show significant differences between the two power systems, which underlying reasons are analysed and explained. With an offshore wind penetration level of 30 %, the New England model stays intact in terms of connected load. When increasing the penetration level to 40 %, about 10 % of the total connected load gets disconnected, whereas about 33 % of the load gets disconnected with a penetration level of 50 %. The Great Britain model stays intact in terms of connected load with a penetration level of at least 49 %.

In this study, the impact of data time resolution on long-term voltage stability assessment of a power grid with high penetration of wind-solar hybrid power plants is investigated. Historical and synthetic wind data as well as solar irradiance are used to calculate power output from hypothetical offshore wind-solar hybrid power plants, geographically located off the coast of Massachusetts, USA. The results show that using hourly input data can overestimate the long-term voltage stability, compared with using minute data. However, the relative difference in terms of voltage mean value and standard deviation is marginal whilst the most significant difference is the intensity of the voltage fluctuations. The main drawback of using high-resolution data is the execution time, increasing proportionally with the number of time steps. Thus, it is argued that the choice of da ta time resolution should be based on the aspects of long-term voltage stability and the size of the power grid to be studied.

To mitigate climate change and meet increasing electricity demand, the global installed capacity of renewable energy sources like wind power is rapidly increasing. Further, external threats against the power system are expected to increase. The threats can arise from extreme weather events driven by climate change, or from antagonistic attacks like sabotage or military conflicts. The power grid is extensive and difficult to oversee due to its complexity and size and is therefore sensitive to such threats. Transmission lines are particularly vulnerable due to their exposure to harsh weather and the difficulty in monitoring them, making them susceptible to sabotage. With more wind power and external threats, it is crucial to study how wind farm integration affects power system resilience to severe line outages. In the present study, this scenario is investigated by simulating 29 different grid topologies 1 000 times each though Monte Carlo simulations. Each topology represents a case where conventional generators are replaced by wind farms. Severe line outages are triggered, and the effect is quantified in terms of disconnected load. The results show that replacing conventional generation by wind power can enhance the power system resilience. The outcome is determined by underlaying factors such as the installed wind power capacity, the electrical distance between wind farms, and the electrical distance between wind farms and loads. The finding that deliberate integration of wind power can enhance the resilience of a power system to severe line outages is important knowledge for transmission system operators and policymakers.

The large-scale deployment of renewable energy at sea offers an opportunity to combine complementary resources within shared offshore infrastructure. While co-location of wind, wave, and solar energy has been proposed as a means to reduce variability and costs, the global conditions under which hybrid offshore power parks are economically preferable remain poorly understood. This study performs a global, temporally high-resolved, techno-economic assessment of offshore wind, wave, and floating solar power, both as stand-alone and co-located systems. Using hourly ERA5 reanalysis data for the period 2020–2024, energy generation from each technology is modelled, and the levelized cost of energy (LCOE) for hybrid parks is minimized subject to shared grid infrastructure and curtailment. The optimization is performed for two cost scenarios representing present-day and near-future capital expenditure levels. Results show that LCOE ranges from 0.04–0.16 €/kWh under present-day conditions and 0.02–0.09 €/kWh under near-future scenarios. Co-location is rarely cost-optimal in regions with excellent single-resource conditions, but can yield lower LCOE than single-technology deployment in locations with moderate and complementary resources. Negative correlations between hourly energy profiles, even when weak (−0.3 to −0.2), are shown to systematically reduce LCOE in mixed systems. While the optimal technology mix is sensitive to assumed cost levels, the underlying drivers (solar capacity factor, resource availability and intersource correlation) for co-location remain robust. These findings provide a global perspective on where and why hybrid offshore energy systems can contribute to a cost-efficient and resilient future energy supply.

With an expected increase in urbanisation and low-carbon transition efforts, the planning of cities is becoming more challenging, and societies need to rethink how urban infrastructures will be constructed in the future. There is a growing recognition that the use of space below the city will need to be significantly enhanced. However, once transformed, underground space becomes a permanent feature, and major metropolitan areas worldwide are gradually acknowledging the subsurface as a valuable, non-renewable resource, emphasising the necessity for long-term, comprehensive, and sustainable planning of its utilisation. Sweden, including the Stockholm region, has favourable geological conditions for building underground facilities and a long tradition of subsurface engineering. Despite these advantages, Stockholm lacks a comprehensive, long-term underground plan or strategy. For years, major subsurface projects have been driven by short-term needs, potentially hindering the optimal use of space below the cityscape. The overall purpose of this paper is twofold. First, we explore the nascent area of scholarly work concerned with the case of Stockholm’s subsurface. We do so by evaluating the current status and potential of urban underground planning in Stockholm municipality. Second, we seek to advance existing planning knowledge and practices concerning Stockholm’s subsurface by identifying several distinct but interrelated gaps and challenges that impede the immediate integration of urban underground space into strategic decision-making for the future of underground planning in Stockholm. We suggest that further research is necessary in several key areas to facilitate the effectiveness and sustainability of long-term urban underground use and planning in Stockholm City and its metropolitan area.

In the absence or unavailability of geometric information about underground structures, conventional quantitative indicators of Urban Underground Space (UUS) usage become challenging to obtain. Socio-economic proxy indicators, that are reportedly well correlated with these conventional indicators, are inherently unstable measures given their susceptibility to non-linear human decision-making processes. To address this limitation, we evaluated the potential of geophysical proxy indicators, specifically the magnetic 3D analytic signal (AS), as a basis for UUS assessment. We also assessed the suitability of the magnetic susceptibility model as a framework for three-dimensional subsurface planning. Stockholm's airborne magnetic data acquired in 1995 were processed to generate an AS map that delineated its metro system (tunnelbana) and similar subsurface structures. Observed signatures, correlated with the overlain metro layout, were independently validated on an electrical current density map derived from co-acquired tensor very low-frequency electromagnetic data. Because AS emphasizes the sharp edges of magnetic contrasts, it provides a direct geophysical marker of anthropogenic underground structures and, consequently, an effective proxy indicator for UUS utilization. We introduce two new indicators: analytic signal density (ASD, expressed in nT/m per hectare, interpreted as "the amount of underground structure from a certain depth range that fits a surface area of 1 ha"), and analytic signal per capita (ASPC, expressed in nT/m per 100 person, interpreted as "the amount of underground structure from a certain depth range per capita". Both demonstrate strong correlations, comparable with those of conventional indicators, with population density (r = 0.88 and r = -0.69, respectively). The 3D magnetic susceptibility inversion model further predicted known infrastructure with a vertical accuracy of similar to 20 m, which can be improved with better data quality. Our results indicate that central Stockholm exhibited significantly higher UUS usage in 1995 (> 1.2 nT/m per hectare and < 2.0 nT/m per 100 person) than other Stockholm areas in the same year. The model for 2023, based on population density, estimated a 20-60 % increase in UUS use in central Stockholm since 1995. This trend underscores the need to integrate UUS in planning and development in both the central districts and the development focus areas of Stockholm city plan, where substantial UUS use was also evident. We conclude that, pending the establishment and adoption of standards for UUS use, Stockholm municipality needs a rethink of its population-driven (coined as "first-full first-developed") underground development strategy, identified through the comparative analysis of the geophysical proxy UUS use indicators of 1995 and model estimates for 2023. Given the rapid and extensive coverage afforded by airborne magnetic surveys, ASD and ASPC provide a novel, scalable, and tangible proxy for estimating and comparing UUS use across cities, particularly in data-limited or data-denied environments.

Deep learning (DL)-based resolution and denoising of potential field grids have recently been proposed as a superior alternative to the conventional downward continuation (DC) in geophysics. Therefore, we performed a benchmarking of the performances of successful DL models in image representation learning for these tasks in the image domain against DC in the data domain. The DL model used is the Residual U-shaped network (ResUNet) and its hybrids, specifically those integrated with attention-gate and shifted window transformer blocks. We also quantitatively analysed the sensitivity of both DL models’ and DC filter’s performances to data acquisition heights and noise. We applied the method to six ground magnetic field datasets and two noise-contaminated synthetic datasets. The added noises simulated various characters such as random, correlated,line bias and outlier which might be typical when collecting data in urban areas. The noises were normalized relative to the maximum magnetic anomalies. Our results show that at or below a certain noise threshold (noise level 3 in this study), the performance of both DL models and DC worsens as altitude increases; beyond this threshold, both become ineffective. When at or below the noise threshold, DC performs comparably to, and even outperforms, some DL models at lower altitudes. However, at higher altitudes, DC’s performance declines rapidly, whereas the DL models’ performance declines more gradually, indicating that the latter is less sensitive to the combined effects of noise and acquisition height. In all comparisons, only the transformer-based model performs comparably to, and could even outperform, the DC due to its transformer’s ability to learn both short- and long-range spatial dependencies in the magnetic data. We conclude that DL models, especially transformer-based models trained on real data, can effectively approximate the physics of the DC operator and outperform it in resolving and denoising coherent features in noisy grids acquired at higher altitudes. Conversely, the DC can outperform DL models when the input grid is of sufficient quality—based on image-based metrics, we found this would approximately be < 12% for L1 loss, > 77% for structural similarity index, and > 12 for peak signal-to-noise ratio. In future work, we recommend research into how DL models with a physics-driven loss function would perform compared to the DC for these tasks, and how sensitive they would be to data noise and acquisition heights.

Macrophages reside in all organs and participate in homeostatic- and immune regulative processes. Little is known about pancreatic macrophage gene expression. In the present study, global gene expression was characterized in human pancreatic macrophage subpopulations. CD206- and CD206 + macrophages were sorted separately from pancreatic islets and exocrine tissue to high purity using flow cytometry, followed by RNA-seq analysis. Comparing CD206- with CD206 + macrophages, CD206- showed enrichment in histones, proliferation and cell cycle regulation, glycolysis and SPP1-associated immunosuppressive polarization while CD206 + showed enrichment in complement and coagulation-, IL-10 and IL-2RA immune regulation, as well as scavenging-related gene sets. Comparing islet CD206- with exocrine CD206-, enrichments in islet samples included two sets involved in immune regulation, while enrichments in exocrine samples included sets related to extracellular matrix and immune activation. Fewer differences were found between CD206 + macrophages, with enrichments in islet samples including two IL2-RA related gene sets, while enrichments in exocrine samples included sets related to extracellular matrix and immune activation. Comparing macrophages between individuals with normoglycemia, elevated HbA1c or type 2 diabetes, only a few diverse differentially expressed genes were identified. This work characterizes global gene expression and identifies differences between CD206- and CD206 + macrophage populations within the human pancreas.

In experimental studies, pancreatic islet microvasculature is essential for islet endocrine function and mass, and islet vascular morphology is altered in diabetic subjects. Even so, almost no information is available concerning human islet microvascular endothelial cell (MVEC) physiology and gene expression. In this study, islets and exocrine pancreatic tissue were acquired from organ donors with normoglycemia or impaired glucose metabolism (IGM) immediately after islet isolation. Following single-cell dissociation, primary islet- and exocrine MVECs were obtained through fluorescence-activated cell sorting (FACS) and transcriptional profiles were generated using AmpliSeq. Multiple gene sets involved in general vascular development and extracellular matrix remodeling were enriched in islet MVEC. In exocrine MVEC samples, multiple enriched gene sets that relate to biosynthesis and biomolecule catabolism were found. No statistically significant enrichment was found in gene sets related to autophagy or endoplasmic reticulum (ER) stress. Although ample differences were found between islet- and exocrine tissue endothelial cells, no differences could be observed between normoglycemic donors and donors with IGM at gene or gene set level. Our data is consistent with active angiogenesis and vascular remodeling in human islets and support the notion of ongoing endocrine pancreas tissue repair and regeneration even in the adult human.

Aims: The transcriptome of different dissociated pancreatic islet cells has been described in enzymatically isolated islets in both health and disease. However, the isolation, culturing, and dissociation procedures likely affect the transcriptome profiles, distorting the biological conclusions. The aim of the current study was to characterize the cells of the islets of Langerhans from subjects with and without type 1 diabetes in a way that reflects the in vivo situation to the highest possible extent.

Methods: Islets were excised using laser capture microdissection directly from frozen pancreatic tissue sections obtained from organ donors with (n = 7) and without (n = 8) type 1 diabetes. Transcriptome analysis of excised samples was performed using AmpliSeq. Consecutive pancreatic sections were used to estimate the proportion of beta-, alpha-, and delta cells using immunofluorescence and to examine the presence of CD31 positive endothelial regions using immunohistochemistry.

Results: The proportion of beta cells in islets from subjects with type 1 diabetes was reduced to 0% according to both the histological and transcriptome data, and several alterations in the transcriptome were derived from the loss of beta cells. In total, 473 differentially expressed genes were found in the islets from subjects with type 1 diabetes. Functional enrichment analysis showed that several of the most upregulated gene sets were related to vasculature and angiogenesis, and histologically, vascular density was increased in subjects with type 1 diabetes. Downregulated in type 1 diabetes islets was the gene set epithelial mesenchymal transition.

Conclusion: A number of transcriptional alterations are present in islets from subjects with type 1 diabetes. In particular, several gene sets related to vasculature and angiogenesis are upregulated and there is an increased vascular density, suggesting an altered microvasculature in islets from subjects with type 1 diabetes. By studying pancreatic islets extracted directly from snap-frozen pancreatic tissue, this study reflects the in vivo situation to a high degree and gives important insights into islet pathophysiology in type 1 diabetes.

Despite a long duration of disease, an often reported finding in subjects with type 1 diabetes (T1D) is the presence of islets with remaining beta cells within some regions of the pancreas. The aim of the current study was to investigate the transcriptome of persisting beta cells as well as other parenchyma of pancreatic samples obtained from human organ donors with long- standing T1D. The Spatial Transcriptomics technology GeoMx (DSP) was applied to well-preserved tissue sections from three donors with a long duration of T1D containing some regions with preserved beta cells, and eight non-diabetic control-donors. In addition, one donor with that died at the onset of T1D was included. A median of 28.5 regions of interest per donor (range 15-52) were assessed for the expression of 18 815 genes. Subsequent Differential Expression Analysis (DEA) and Gene set enrichment-analysis (GSEA), using CAMERA, was used to examine transcriptional differences within tissue types between long-standing T1D and non-diabetic subjects. 

The beta cell regions in long-standing T1D were found to have a gene expression profile suggesting a dysregulated ER stress response and a reduced beta-cell maturity compared to corresponding regions in non-diabetic donors, while the data from the exocrine compartments suggests substantial alterations, with possible links to chronic pancreatitis. The beta cell regions in the acute onset case had a gene expression profile consistent with a reduced beta cell function, and an overexpression of interferon-stimulated genes. 

In conclusion, using spatial transcriptomics, we found persisting beta cells in donors with a long duration of T1D to have a substantially different transcriptome profile as compared to donors without diabetes, and provide data that may help guide further research.

Antibodies against galactose-α-1,3-galactose (αGal) are among the most abundant natural antibodies in humans and have been exploited in cancer immunotherapy, with their efficacy partly attributed to complement activation. We aim to enhance this response by employing properdin [also known as factor P (FP)], the only known positive complement regulator. We expressed a membrane-anchored properdin (mFP) on mouse and human pancreatic cancer cells and assessed its ability to enhance αGal-mediated complement activation. We showed here that ectopic expression of mFP on Panc02 cells increased the deposition level of C3 in vitro and induced more potent complement-dependent cytotoxicity in the presence of human complement source. In an immunized Ggta1 knockout mouse model, which has circulating anti-αGal antibodies as a mimicry of the human system, mFP expression conferred significantly delayed tumor growth and was associated with pronounced remodeling of the immune landscape in the tumor microenvironment (TME). Specifically, we observed a marked increase in conventional type 1 dendritic cells, a reduction in tumor-associated monocytes/macrophages with a shift toward a pro-inflammatory phenotype, and a transition of CD8⁺ T cells toward a progenitor-exhausted state. Reconfiguring the structure of mFP to create an artificial C3 convertase binding site and incorporating an intracellular oligomerization domain improved target cell killing and monocyte-mediated phagocytosis in a human whole-blood loop model. These findings suggest that amplifying complement activation can delay tumor growth and alter the TME in the context of a murine pancreatic cancer model. Furthermore, we have developed a novel membrane-bound oligomerized FP functional unit, which effectively elicits robust complement activation.