System-level Analysis Research Articles

Machine learning emulators of dynamical systems for understanding ecosystem behaviour

Minimal models (MM) aim to capture the simplified behaviour of complex systems to facilitate system-level analyses that would be unfeasible with more sophisticated numerical models. However, the choices involved in minimal model development heavily rely on expert knowledge, a source of bias that can interfere with good modelling practices. In this paper, a new method is proposed in which a machine learning (ML) model is trained with transient data generated by a detailed physically-based numerical model, predicting the rate of change of the target state variables given their current value and additional drivers. The trained model is then used to mimic the analysis made with traditional minimal models. This approach (ML-MM) is deployed in a semiarid hillslope ecosystem characterising its soil and vegetation components. The ML-MM outputs share most of the general features with previous expert-based results but show a better ability of the hillslope to (1) recover its vegetation, (2) resist total disappearance of the soil and (3) reach substantially higher soil depths in steady state. Furthermore, a new intermediate stable equilibrium is found between the already known healthy and degraded ones, revealing a more complex pattern of ecosystem collapse that avoids a critical shift, as supported by numerical model simulations. The transient behaviour is also investigated, from which we conclude that the system can exhibit strong reactivity, that is, an initial deviation away from equilibrium after a perturbation. In conclusion, the present study demonstrates the potential of ML-MM to obtain new scientific insights on complex systems that might be missed by expert-based alternatives. Hence, minimal models may benefit greatly from incorporating detailed numerical models and data-driven simplification in their development process. Ultimately, this methodology could be applicable to many fields of study and even be expanded to observational data, enhancing our understanding of real-world complex system dynamics.

Systems-level immunomonitoring in children with solid tumors to enable precision medicine.

Cancer is the leading cause of death from disease in children. Survival depends not only on surgery, cytostatic drugs, and radiation but also on systemic immune responses. Factors influencing these immune responses in children of different ages and tumor types are unknown. Novel immunotherapies can enhance anti-tumor immune responses, but few children have benefited, and markers of effective responses are lacking. Here, we present a systems-level analysis of immune responses in 191 children within a population-based cohort with diverse tumors and reveal that age and tumor type shape immune responses differently. Systemic inflammation and cytotoxic Tcell responses correlate with tumor mutation rates and immune cell infiltration. Clonally expanded Tcell responses are rarely detected in blood or tumors at diagnosis but are sometimes elicited during treatment. Expanded Tcells are similarly regulated in children and adults with more immunogenic cancers. This research aims to facilitate the development of precision immunotherapies for children with cancer.

Integrative systems-level analysis reveals a contextual crosstalk between hypoxia and global metabolism in human breast tumors.

Hypoxia is known to induce reprogramming of glucose metabolism in cancer. However, the impact of hypoxia on global metabolism remains poorly understood. Here, using the systems approach, we evaluated the potential crosstalk between hypoxia and global metabolism using data from > 2000 breast tumors. Tumor samples were scored for hypoxia and 90 metabolic pathways, and these metrics were subjected to an analysis pipeline. Hypoxia showed a very strong association with metabolic aggression and an overall contextual relationship with metabolism. Out of three (M1, M2, and M3) metabolic types in breast cancer, M3 exhibited the strongest relationship with hypoxia; that is, high hypoxic tumors were also metabolically deregulated. Further, the overall correlation pattern between hypoxia and metabolic pathway scores was specific to each type, with M1 showing maximal sensitivity to hypoxia, followed by M2 and then M3. Experimental validation using metabolic inhibitors on cell lines with high or low hypoxia scores further confirmed the metabolic type-dependence of hypoxia. In addition, evaluation of the impact of hypoxia on cancer pathways other than metabolic ones revealed a potential role of hypoxia in immune evasive characteristic of M3 tumors. Overall, the results suggest a complex interplay between hypoxia and metabolism in the context of human breast tumors, with potential implications for both basic cancer biology and breast cancer therapy.

Analysis of systemic serum vancomycin levels following intraarticular application in primary total joint arthroplasty

IntroductionPeriprosthetic joint infection (PJI) is a serious complication following primary total joint arthroplasty (TJA). PJI accounts for 15–25% of revision surgeries, therefore it is associated with PJI is associated with substantial patient morbidity and mortality as well as increased healthcare expenditures due to complex treatment strategies.Recently, intraoperative local application of vancomycin powder is increasingly being used in primary total hip and knee arthroplasty (THA, TKA) as an additive strategy for PJI prevention. Whereas local vancomycin concentrations have already been investigated in prior studies, evidence on systemic vancomycin levels and potential adverse drug reactions (ADR) is limited. Purpose of this study was to investigate systemic vancomycin levels following intraarticular application in primary TJA.Materials and methodsThis pilot study is a prospective analysis of patients undergoing primary THA and TKA between April and July 2023. One gram of vancomycin powder was applied to the prosthesis prior to wound closure. Serum vancomycin levels were measured at two standardised time points, 24 and 48 h postoperatively.ResultsIn total, 103 patients were included, and the patient collective was further stratified by surgical procedure into a THA subgroup (n = 52) and a TKA subgroup (n = 51). Mean serum vancomycin levels showed a significant group difference at both time points (24 h: p < 0.001; 48 h: p = 0.044) with higher serum vancomycin concentrations in the THA cohort. Mean serum vancomycin levels in THA patients were 1.25 μg/ml (range 0.00–7.00 μg/ml) after 24 h and 0.34 μg/ml (range 0.00–4.80 μg/ml) 48 h postoperatively. In TKA, no systemic vancomycin levels were detected. Vancomycin concentrations did not reach therapeutic levels in any patient. No ADR was detected in the whole study collective.ConclusionFollowing intraarticular administration of vancomycin powder, no systemic vancomycin levels within the therapeutic range were detected, thus it may serve as a safe and cost-effective adjunct to strategies for prevention of PJI.

Microseconds-level coding of echo delay in the auditory brainstem of an FM-echolocating bat.

Echolocating big brown bats (Eptesicus fuscus) detect changes in ultrasonic echo delay with an acuity as sharp as 1 µs or less. How this perceptual feat is accomplished in the nervous system remains unresolved. Here, we examined the precision of latency registration (latency jitter) in neural population responses as a possible mechanism underlying the bat's hyperacuity. We recorded local field potentials in the cochlear nucleus and inferior colliculus of anesthetized big brown bats to sequences of sounds consisting of a simulated frequency-modulated broadcast followed, at various echo delays, by a four-echo cascade. Latencies of the first negative response peak to the broadcast and to the first echo in the cascade were shorter in the cochlear nucleus than in the inferior colliculus, but latency jitter of this peak was comparable in both brainstem nuclei. Mean latency jitter, averaged over all stimulus conditions, was 51 µs in the cochlear nucleus and 56 µs in the inferior colliculus. Latency jitter to the successive echoes in the echo cascades was larger, with means of 125 µs and 111 µs, respectively. These values are lower than values commonly reported for single-neuron latency variability in bats and other mammals, and they approach within an order of magnitude the big brown bat's psychophysical performance. Latency jitter for synchronized population responses on a scale of microseconds reduces the gap between neurophysiological and behavioral measures of acuity. Further systems-level analysis is necessary for understanding neural mechanisms of perception.NEW & NOTEWORTHY Echolocating big brown bats resolve time delays with a sharp precision of 1 µs or less. How this hyperacuity is accomplished in the auditory system is unknown. We now report that the precision of latency registration (latency jitter) in population activity from two brainstem nuclei in response to simulated echolocation sounds is in the range of tens of microseconds. These values are smaller than observed in single neuron responses and approach the bat's psychophysical acuity.

Tracking the gene expression programs and clonal relationships that underlie mast, myeloid, and T lineage specification from stem cells.

T cells develop from hematopoietic progenitors in the thymus and protect against pathogens and cancer. However, the emergence of human Tcell-competent blood progenitors and their subsequent specification to the T lineage have been challenging to capture in real time. Here, we leveraged a pluripotent stem cell differentiation system to understand the transcriptional dynamics and cell fate restriction events that underlie this critical developmental process. Time-resolved single-cell RNA sequencing revealed that downregulation of the multipotent hematopoietic program, upregulation of >90 lineage-associated transcription factors, and cell-cycle exit all occur within a highly coordinated developmental window. Gene-regulatory network inference uncovered a role for YBX1 in T lineage specification. We mapped the differentiation cell fate hierarchy using transcribed lineage barcoding and discovered that mast and myeloid potential bifurcate from each other early in hematopoiesis, upstream of T lineage restriction. Our systems-level analyses provide a quantitative, time-resolved model of human Tcell fate specification. A record of this paper's transparent peer review process is included in the supplemental information.

Igome Graphs Suggest the Changes in the IgM and IgG Repertoires in Antiphospholipid Syndrome Are in Part Idiotypically Defined

Antiphospholipid Syndrome (APS) is characterized by the persistence of high-affinity antiphospholipid antibodies, manifesting clinically as pregnancy complications, thrombosis, or neurological symptoms. This study explores the changes in the IgM and IgG antibody repertoires in APS patients using igome graphs, which represent antibody repertoires through peptide libraries selected from phage display on the complete immunoglobulin fraction of the serum. Serum samples from healthy women and APS patients were processed to isolate IgM and IgG fractions, which were then used for phage selection and next-generation sequencing. Peptide sequences were analyzed using graph representation, clustering, and spectral embedding to identify significant differences between the repertoires. The study revealed that while IgM repertoires in APS patients exhibit a loss of public reactivities, the IgG repertoires do not follow this trend. Three orthogonal sequence motifs were identified in the IgM and IgG repertoires, suggesting potential idiotypic interactions. These findings highlight the intricate mechanisms of antibody selection and cross-reactivity in APS, offering insights into potential therapeutic approaches. The study underscores the importance of system-level analysis in understanding immune mechanisms and suggests that idiotypic interactions, though complex, could play a crucial role in APS pathogenesis.

Modeling the Impact of Additional Electrolyte on Lithium-Ion Convection Cell Performance

Addressing growing energy demands while balancing sustainability imperatives, environmental stewardship, and economic viability stands as a paramount global challenge. Electrochemical technologies, particularly lithium-ion batteries (LIBs), are pivotal in achieving deep decarbonization by facilitating the deployment of electric vehicles and ensuring the reliable delivery of renewable electricity. However, current LIBs fall short of the rigorous requirements for widespread adoption in these critical sectors, as well as in emerging areas such as long-haul trucking and electric vertical takeoff and landing vehicles (eVTOLs).1,2 Breakthroughs in the science and engineering of LIBs are imperative to produce devices capable of delivering high performance without sacrificing safety and cost.In addition to traditional materials-focused approaches, the development of new battery cell architectures, including the integration of electrolyte flow, presents a promising avenue for advancing performance. Prior mathematical modeling has shown forced electrolyte convection can significantly improve heat and mass transfer within LIBs, enabling operation under conditions that challenge conventional formats (e.g., high-rate charge/discharge).3,4 However, to exclude convoluting secondary effects, these studies simplify balance-of-plant systems which, in turn, may not fully describe practical operation. Specifically, these simulations use large electrolyte tanks which buffer against bulk concentration and temperature changes, aiding in the fundamental analyses. Notably, scaling under these conditions could potentially lead to cost-prohibitive and thus impractical systems.5 In this presentation, we investigate the impact of additional electrolyte volume on the complex interplay between electrochemical performance enhancements, fluid dynamic losses, and economic incentives in a convection cell. Through physics-based electrochemical modeling, we demonstrate that electrolyte convection alone can alleviate mass transport limitations even under extreme discharge rates, obviating the need for added electrolyte. In contrast, we find that extra electrolyte is necessary as a heat sink to mitigate cell temperature rise. We extend these results to practical operating conditions, where we conduct a preliminary system-level energy analysis to evaluate the energetic penalties associated with scaling this new architecture. Our findings suggest there exists a narrow added electrolyte range that effectively reduces thermal transport limitations without significantly increasing the system weight and volume. We also construct an accompanying technoeconomic framework to estimate the associated cost tradeoffs, illustrating the disparity between energy-optimized and cost-optimized designs. Ultimately, this work represents an initial exploration into practical design and operation considerations for convection batteries, laying the groundwork for future application-specific investigations.

Functional analysis of cyclic diguanylate-modulating proteins in Vibrio fischeri.

As bacterial symbionts transition from a motile free-living state to a sessile biofilm state, they must coordinate behavior changes suitable to each lifestyle. Cyclic diguanylate (c-di-GMP) is an intracellular signaling molecule that can regulate this transition, and it is synthesized by diguanylate cyclase (DGC) enzymes and degraded by phosphodiesterase (PDE) enzymes. Generally, c-di-GMP inhibits motility and promotes biofilm formation. While c-di-GMP and the enzymes that contribute to its metabolism have been well studied in pathogens, considerably less focus has been placed on c-di-GMP regulation in beneficial symbionts. Vibrio fischeri is the sole beneficial symbiont of the Hawaiian bobtail squid (Euprymna scolopes) light organ, and the bacterium requires both motility and biofilm formation to efficiently colonize. c-di-GMP regulates swimming motility and cellulose exopolysaccharide production in V. fischeri. The genome encodes 50 DGCs and PDEs, and while a few of these proteins have been characterized, the majority have not undergone comprehensive characterization. In this study, we use protein overexpression to systematically characterize the functional potential of all 50 V. fischeri proteins. All 28 predicted DGCs and 10 of the 14 predicted PDEs displayed at least one phenotype consistent with their predicted function, and a majority of each displayed multiple phenotypes. Finally, active site mutant analysis of proteins with the potential for both DGC and PDE activities revealed potential activities for these proteins. This work presents a systems-level functional analysis of a family of signaling proteins in a tractable animal symbiont and will inform future efforts to characterize the roles of individual proteins during lifestyle transitions.IMPORTANCECyclic diguanylate (c-di-GMP) is a critical second messenger that mediates bacterial behaviors, and Vibrio fischeri colonization of its Hawaiian bobtail squid host presents a tractable model in which to interrogate the role of c-di-GMP during animal colonization. This work provides systems-level characterization of the 50 proteins predicted to modulate c-di-GMP levels. By combining multiple assays, we generated a rich understanding of which proteins have the capacity to influence c-di-GMP levels and behaviors. Our functional approach yielded insights into how proteins with domains to both synthesize and degrade c-di-GMP may impact bacterial behaviors. Finally, we integrated published data to provide a broader picture of each of the 50 proteins analyzed. This study will inform future work to define specific pathways by which c-di-GMP regulates symbiotic behaviors and transitions.

System-Level Statistical Eye Diagram for Signal Integrity

This paper reviews a statistical signal integrity (SI) analysis at the system level for a high-speed system design. An eye diagram graphically shows a system’s performance. However, an eye diagram requires a long acquisition time for accurate results. The time-consuming nature of this process makes an eye-diagram-based SI analysis inefficient. Thus, a statistical eye diagram was introduced for an efficient SI analysis. The statistical eye diagram provides not only SI metrics such as eye height (EH) and eye width (EW), but also the bit-error rate (BER) profile for each channel. The data transmitted over the high-speed channels are determined by an upper hierarchy such as a system. In other words, the data are a function of the system parameters. In conclusion, a statistical eye diagram is determined by the high-speed channels and the system parameters. Therefore, the previous works on statistical eye diagrams at the channel and system levels have been introduced, respectively. This paper reviews the previous works for a system-level statistical SI analysis with a statistical eye diagram.

The Micropaleoecology Framework: Evaluating Biotic Responses to Global Change Through Paleoproxy, Microfossil, and Ecological Data Integration.

The microfossil record contains abundant, diverse, and well-preserved fossils spanning multiple trophic levels from primary producers to apex predators. In addition, microfossils often constitute and are preserved in high abundances alongside continuous high-resolution geochemical proxy records. These characteristics mean that microfossils can provide valuable context for understanding the modern climate and biodiversity crises by allowing for the interrogation of spatiotemporal scales well beyond what is available in neo-ecological research. Here, we formalize a research framework of "micropaleoecology," which builds on a holistic understanding of global change from the environment to ecosystem level. Location: Global. Time period: Neoproterozoic-Phanerozoic. Taxa studied: Fossilizing organisms/molecules. Our framework seeks to integrate geochemical proxy records with microfossil records and metrics, and draws on mechanistic models and systems-level statistical analyses to integrate disparate records. Using multiple proxies and mechanistic mathematical frameworks extends analysis beyond traditional correlation-based studies of paleoecological associations and builds a greater understanding of past ecosystem dynamics. The goal of micropaleoecology is to investigate how environmental changes impact the component and emergent properties of ecosystems through the integration of multi-trophic level body fossil records (primarily using microfossils, and incorporating additional macrofossil data where possible) with contemporaneous environmental (biogeochemical, geochemical, and sedimentological) records. Micropaleoecology, with its focus on integrating ecological metrics within the context of paleontological records, facilitates a deeper understanding of the response of ecosystems across time and space to better prepare for a future Earth under threat from anthropogenic climate change.

Survey of Reliability Challenges and Assessment in Power Grids with High Penetration of Inverter-Based Resources

Decarbonization is driving power systems toward more decentralized, self-governing models. While these technologies improve efficiency, planning, operations, and reduce the carbon footprint, they also introduce new challenges. In modern grids, particularly with the integration of power electronic devices and high penetration of Renewable Energy Sources (RES) and Inverter-Based Resources (IBRs), traditional reliability concepts may no longer ensure adequate performance due to systemic restructuring. This shift necessitates new or significantly modified reliability indices to capture the characteristics of the evolving power system. Ensuring converter reliability is essential for effective planning, which requires precise, component-to-system-level modeling, as different converters impact system performance indicators. However, the existing literature in this field faces a significant limitation, as most studies focus on a singular perspective. Some examine reliability at the device-level, others at the component-level, while broader reviews in power systems often emphasize system-level analysis. In this paper, we aim to bridge these gaps by comprehensively reviewing the interconnections between these levels and analyzing the mutual influence of power converter and system reliability. A key point to highlight is that, with the rapid evolution of modern power grids, decision-makers must adopt a multi-level approach that incorporates insights from all levels to enable more accurate and realistic planning and operational strategies. Our ultimate goal is to provide an in-depth investigation of studies addressing the unique challenges posed by modern power grids. Finally, we will highlight the gaps in the literature and suggest directions for future research.

System-Level Dynamic Model of Redox Flow Batteries (RFBs) for Energy Losses Analysis

This paper presents a zero-dimensional dynamic model of redox flow batteries (RFBs) for the system-level analysis of energy loss. The model is used to simulate multi-cell systems considering the effect of design and operational parameters on energy loss and overall performance. The effect and contribution of stack losses (e.g., overpotential and crossover losses) and system losses (e.g., shunt currents and pumps) to total energy loss are examined. The model is tested by using literature data from a vanadium RFB energy storage. The results show that four parameters mainly affect RFB system performance: manifold diameter, stack current, cell standard potential, and internal resistance. A reduction in manifold diameter from 60 mm to 20 mm reduced shunt current loss by a factor of four without significantly increasing pumping loss, thus boosting round-trip efficiency (RTE) by 10%. The increase in stack current at a low flow rate increases power, while the cell standard potential and internal resistance play a crucial role in influencing both power and energy output. In summary, the modeling activities enabled the understanding of critical aspects of RFB systems, thereby serving as tools for system design and operation awareness.

Damage-driven framework for reliability assessment of steam turbine rotors operating under flexible conditions

The high-temperature rotating structures (HTRS), e.g., steam turbine rotors, often operate in extremely harsh environments with a flexible load condition during peak shaving of power system. In this work, a damage-driven framework for reliability assessment is developed in terms of the cumulative damage-damage threshold interference (CD-DT) principle, in which the cumulative damage and damage threshold are regarded as two random parameters to address uncertainties. The CD-DT principle is founded on the engineering damage theory and incorporates physics-of-failure into the probabilistic modeling of high-temperature structural reliability. Probabilistic damage analysis, correlation analysis of weak sites, system-level reliability analysis, and sensitivity analysis have been encompassed in this framework. Three numerical examples are used to verify the effectiveness and applicability of the proposed framework. Application to steam turbine rotor involving multiple weak sites with multi-damage modes illustrate the implementation procedures of the framework. Results show that the reliability-based design life of rotor decreases with the increases of start-stop frequency, the implementation of a two-shift operation would pose a threat to meeting the safety requirement of a 30-year design life. Furthermore, sensitivity analysis highlights the critical influences of initial rotor temperature and speed rising rate on rotor reliability, providing insights for operational maintenance and reliability optimization.

A Systems-Level Analysis of 2-[18F]FDG PET in Pigs Reveals Complex Skeletal Metabolism Networks in vivo which are altered with Osteomyelitis

Our understanding of complex tissue interactions at a systems level remains rudimentary, limiting our ability to dissect mechanisms underlying diseases and develop novel therapeutics. Skeletal research has focused on the pathogenicity of obesity and diabetes mellitus on the skeleton; however, it has been recently revealed that the skeleton is not merely an endocrine target but also a secretory organ, modulating systemic energy homeostasis1,2. We recently discovered that different bones within the murine skeleton have a unique glucose metabolism and form a complex metabolic network3. Thus, we hypothesised that different bones within the porcine skeleton would have unique molecular signatures and form a distinct metabolic network, and these networks would be altered by osteomyelitis, an inflammatory condition of the bone. Five healthy mini and three Danish Landrace-Yorkshire pigs (inoculated with S. aureus to induce osteomyelitis) underwent static 2-[18F]FDG PET/CT and were analysed to measure bone and bone marrow adipose tissue (BMAT) glucose metabolism. Analyze was used for image analysis and processing. Bone and bone marrow volumes of interest were segmented in CT images using Hounsfield Unit (HU) &gt; 300 (bone) and HU -200 to 115 (BMAT; Fig1). PET images were used to extract average standard uptake values. Network analysis was performed using Graphia. Osteomyelitis pigs had a lower bone density and increased BMAT volume compared to healthy controls. There was an increased incorporation of 2-[18F]FDG into the bone and BMAT of osteomyelitis pigs. Similar to what has previously been observed in the mouse3 and human4, there was an increased incorporation of 2-[18F]FDG in the axial skeleton compared to the appendicular skeleton. Network analysis indicated a shift in bone metabolic profiles between healthy and osteomyelitis pigs. Please click on the 'PDF' for the full abstract!

7820 Immune system adaptation during gender-affirming testosterone treatment

Abstract Disclosure: T. Lakshmikanth: None. C. Consiglio: None. F. Sardh: None. R. Forlin: None. J. Wang: None. Z. Tan: None. H. Barencilla: None. L. Rodriguez: None. J. Sugrue: None. P. Noori: None. M. Ivanchenko: None. L. Piñero Páez: None. L. Gonzalez: None. C. Habimana Mugabo: None. A. Johnsson: None. H. Ryberg: None. Å. Hallgren: None. C. Pou: None. Y. Chen: None. J. Mikeš: None. A. James: None. P.M. Dahlqvist: None. J. Wahlberg Hughes: None. A. Hagelin: None. M. Holmberg: None. M. Degerblad: None. M. Isaksson: None. D. Duffy: None. O. Kampe: None. N. Landegren: None. P. Brodin: None. Immune system adaptation during gender-affirming testosterone treatment Infectious, inflammatory and autoimmune conditions present differently in males and females. Following SARS-CoV-2 infection, male sex is associated with increased risk of death, while female sex is associated with increased risk of the postinfectious disorder, long COVID. Similar trends are seen in other infections. Female immune responses to vaccines are typically stronger, and adverse reactions are more frequent, like most autoimmune diseases. Immunological sex-differences stem from genetic, hormonal and behavioural factors but their relative importance is poorly understood. To understand the consequences of changing sex-hormones in vivo, we performed longitudinal, systems-level analyses in 22 adults, assigned female at birth, and undergoing gender-affirming testosterone treatment (trans-men). We find that sex hormones modulate a cross-regulation axis of type-I interferon (IFN-I) and TNFα in humans. This is mediated by a reduced frequency of plasmacytoid dendritic cells (pDC), and functional attenuation of IFN-I responses in both pDCs and monocytes. Conversely, testosterone potentiates monocyte responses to lipopolysaccharide (LPS) leading to increased TNFα, IL-6 and IL-15 production and downstream epigenetic opening of NFκB regulated genes and potentiation of IFNγ responses, primarily by NK cells. IFNγ in turn feeds back onto monocytes leading to upregulation of SLAMF7 and further enhanced TNFα responses by myeloid cells. These results are corroborated by sex-divergent responses in multiple public datasets and collectively illustrate the dynamic recalibration of human immune systems by sex hormones with implications for individuals undergoing gender-affirming hormone therapy, but also better understanding of divergent responses to infection, vaccines and self-antigens in cisgender individuals. Presentation: 6/2/2024

7820 Immune system adaptation during gender-affirming testosterone treatment

Abstract Disclosure: T. Lakshmikanth: None. C. Consiglio: None. F. Sardh: None. R. Forlin: None. J. Wang: None. Z. Tan: None. H. Barencilla: None. L. Rodriguez: None. J. Sugrue: None. P. Noori: None. M. Ivanchenko: None. L. Piñero Páez: None. L. Gonzalez: None. C. Habimana Mugabo: None. A. Johnsson: None. H. Ryberg: None. Å. Hallgren: None. C. Pou: None. Y. Chen: None. J. Mikeš: None. A. James: None. P.M. Dahlqvist: None. J. Wahlberg Hughes: None. A. Hagelin: None. M. Holmberg: None. M. Degerblad: None. M. Isaksson: None. D. Duffy: None. O. Kampe: None. N. Landegren: None. P. Brodin: None. Infectious, inflammatory and autoimmune conditions present differently in males and females. Following SARS-CoV-2 infection, male sex is associated with increased risk of death, while female sex is associated with increased risk of the postinfectious disorder, long COVID. Similar trends are seen in other infections. Female immune responses to vaccines are typically stronger, and adverse reactions are more frequent, like most autoimmune diseases. Immunological sex-differences stem from genetic, hormonal and behavioural factors but their relative importance is poorly understood. To understand the consequences of changing sex-hormones in vivo, we performed longitudinal, systems-level analyses in 22 adults, assigned female at birth, and undergoing gender-affirming testosterone treatment (trans-men). We find that sex hormones modulate a cross-regulation axis of type-I interferon (IFN-I) and TNFα in humans. This is mediated by a reduced frequency of plasmacytoid dendritic cells (pDC), and functional attenuation of IFN-I responses in both pDCs and monocytes. Conversely, testosterone potentiates monocyte responses to lipopolysaccharide (LPS) leading to increased TNFα, IL-6 and IL-15 production and downstream epigenetic opening of NFκB regulated genes and potentiation of IFNγ responses, primarily by NK cells. IFNγ in turn feeds back onto monocytes leading to upregulation of SLAMF7 and further enhanced TNFα responses by myeloid cells. These results are corroborated by sex-divergent responses in multiple public datasets and collectively illustrate the dynamic recalibration of human immune systems by sex hormones with implications for individuals undergoing gender-affirming hormone therapy, but also better understanding of divergent responses to infection, vaccines and self-antigens in cisgender individuals. Presentation: 6/2/2024

7310 System-level Analysis in Polycystic Ovary Syndrome on a Panel of Genetically Diverse Strains of Mice

Abstract Disclosure: L.M. Velez: None. C. Johnson: None. I. Tamburrini: None. M. Zhou: None. C. Viesi: None. N. Ujagar: None. D. Ashbrook: None. M. Nelson: None. A. Senior: None. D. James: None. R. Williams: None. D. Nicholas: None. M. Seldin: None. Polycystic ovary syndrome (PCOS) is the most common endocrinopathy in women, with a prevalence of ∼4-20% in women of reproductive age. The diagnosis of the syndrome generally occurs when the patient consults for fertility issues and is only based on a reproductive criterion, which includes (1) hyperandrogenism, (2) oligo-anovulation, and (3) polycystic ovary morphology. However, the overlap of PCOS with cardiometabolic diseases is significant. To put in numbers; up to 75% of PCOS women present some degree of insulin insensitivity, 38-88% present obesity or overweight, 20-50% develop type 2 diabetes by age 40, and PCOS women are at increased risk of cardiovascular disease. Despite these facts, shared reproductive/metabolic mechanisms are largely underexplored. Moreover, studies addressing the genetic architecture of PCOS are missing. Here, we induced a PCOS-like condition in 25 recombinant and classical inbred female strains and matched placebo controls over 6 weeks. Comprehensive in vivo and terminal reproductive/metabolic analyses were performed, as well as ovary and adipose RNA-Seq. These strains varied in PCOS response in a number of key metabolic and reproductive traits, including circulating hormone levels, glucose metabolism, and cardiac function. We applied a linear mixed-effects model to estimate heritability, and genetic (h2), PCOS, and gene-by-PCOS interactions. High h2 was observed for lean and fat mass, glucose, and AUC, whereas PCOS effects were high for the BW change, testosterone, and AUC. Substantial gene-by-PCOS interactions were found for reproductive hormones. Undirected network construction and centrality estimates showed that the reproductive hormones LH and LH/FSH ratio were the strongest central traits connecting metabolic phenotypes. We also showed select strains represent subtypes of human PCOS-metabolism interaction with varied susceptibilities to disease in a PCOS setting. Ovarian RNA-seq analysis of PCOS DEGs showed strong enrichments with human disease settings such as hyperandrogenism, inflammation, and pregnancy hypertension. Similar analyses in GWAT RNA-seq showed enrichments in weight gain, liposarcoma, inflammation, and reproductive diseases were at the top, with adipose genes connecting these diseases and potentially involved with PCOS. In conclusion, we established a PCOS model to study relevant mechanisms intersecting reproduction with metabolism in the context of genetic variation. Presentation: 6/2/2024

A web portal for exploring kinase-substrate interactions

Interactions between protein kinases and their substrates are critical for the modulation of complex signaling pathways. Currently, there is a large amount of information available about kinases and their substrates in disparate public databases. However, these data are difficult to interpret in the context of cellular systems, which can be facilitated by examining interactions among multiple proteins at once, such as the network of interactions that constitute a signaling pathway. We present KiNet, a user-friendly web portal that integrates and shares information about kinase-substrate interactions from multiple databases of post-translational modifications. KiNet enables the visual exploration of these interactions in systems contexts, such as pathways, domain families, and custom protein set inputs, in an interactive fashion. We expect KiNet to be useful as a knowledge discovery tool for kinase-substrate interactions, and the aggregated KiNet dataset to be useful for protein kinase studies and systems-level analyses. The portal is available at https://kinet.kinametrix.com/.

Pathways for Strengthening Lived Experience Leadership for Transformative Systems Change: Reflections on Research and Collective Change Strategies.

The Activating Lived Experience Leadership (ALEL) project was a South Australian participatory action research project that aimed to improve the ways lived experience is recognised, valued and integrated across mental health and social sector systems. ALEL was completed during 2019-2021, where it engaged 182 participants in generating community action and research knowledge. Our paper discusses the project's processes of building a collective partnership among lived experience leaders and other leaders from within the sector, so that the actions and strategies identified through research could be implemented by systems-level impact. We describe the collaborative process and key learnings that resulted in eight key action areas for transformative systems change in South Australia. The project invited a diverse range of self-identified lived experience and other leaders to be involved in a PAR process featuring formal qualitative research (focus groups, surveys and interviews) as well as community development activities (leaders' summit meetings, consultations, training and community of practice meetings). These processes were used to help us describe the purpose, achievements and potential of lived experience leadership. Project priorities and systems-level analysis was also undertaken with lived experience sector leaders and project advisors across two leaders' summit meetings, integrating research outcomes with sector planning to define high-level actions and a vision for transformational change. Participatory action research as informed by systems change and collective impact strategies assisted the project to generate detailed findings about the experiences and complexities of lived experience leadership, and collective responses of how systems could better support, be accountable to and leverage lived experience perspectives, experience and peer-work approaches. Systems change to define, value and embed lived experience leadership benefits from collective efforts in both formal research and sector development activities. These can be used to generate foundational understandings and guidance for working together in genuine ways for transforming mental health and social sector systems, experience and outcomes. Members of lived experience communities codesigned the project, and contributed to project governance and the development of all findings and project reports.