This study was aimed to understand the difference in forest transpiration between slope positions, and to separate the contributions of main influencing factors, for improving the accuracy of forest transpiration estimation at slope scale by up-scaling the results measured at plot, especially in semiarid regions with significant soil moisture difference along slope positions. Two plots of Larix principis-rupprechtii plantation were established, one at upper slope (less affected by terrain shading and more impacted by soil drought) and another at lower slope (more affected by terrain shading and less impacted by soil drought) on a northwest-facing slope in the semiarid area of Liupan Mountains in northwest China. The sap flow velocity ( J S , ml·cm -2·min -1) of sample trees, meteorological parameters in open field, and soil water potential in main root zone (0-60 cm) were monitored simultaneously in the growing season (from Jul. to Sep.) of 2015. Using transpiration data of selected 59 effective days after excluding the days with rainfall and data missing, the contributions to the transpiration difference between the two plots by soil water potential, sapwood area, terrain shading, and their interaction were quantitively separated using analytical method. The total transpiration of 59 effective days was 41.91 mm at the lower slope plot, slightly higher than that at the upper slope plot (37.38 mm), indicating a small difference (4.53 mm) due to the offsetting effects of multiple factors. A significant difference in the soil water potential of 0-60 cm was found between the two plots, with means of -0.240 MPa at lower slope plot and -0.582 MPa at upper slope plot. The promotion effect on the sap flow velocity at lower slope plot by its higher soil water potential increased linearly with rising soil water potential difference, with an average promotion of 0.017 ml·cm -2·min -1. The reduction effect on the sap flow velocity at lower slope plot caused by stronger terrain shading follows a parabolic equation to rising solar radiation intensity, with an average limitation of 0.003 ml·cm -2·min -1. When taking the upper slope plot as reference, the plot difference in soil water potential increased the total transpiration of 59 days at lower slope plot by 16.40 mm; while the differences in sapwood area, terrain shading, and the interaction of three factors decreased the total transpiration at lower slope plot by 6.61, 2.86, and 2.40 mm, respectively, making a net increase of 4.53 mm. Under given conditions of location, soil, climate, and vegetation in this study, the contributions of influencing factors to the stand transpiration difference between slope positions is: soil moisture (soil water potential) > stand structure (sapwood area) > solar radiation (terrain shading) > interaction of all factors. All these impacts should be considered for accurate prediction of forest transpiration at slope scale through up-scaling from measurement at plot, especially in semiarid regions.

A document by Armel Mamihaja Andrianiaina. Click on the document to view its contents.

This study investigates the impact of HTLV-2 infection on small RNA (sRNA) expression profiles, building on previous findings related to HTLV-1. Using Illumina Massive Parallel Sequencing, we analyzed sRNA profiles from asymptomatic HTLV-1 and HTLV-2 infected individuals and healthy controls. Our results reveal significant differential expression of 331 known and 441 novel sRNAs among the groups, including miRNAs, piRNAs, and tRNAs. Notably, distinct clusters of sRNA expression patterns were identified, with specific miRNAs showing significant upregulation or downregulation in HTLV-1 and HTLV-2 infections. Gene Ontology analysis indicated significant involvement of target genes in transcription regulation and RNA-binding processes, while KEGG pathway analysis highlighted enrichment in cancer-related pathways and signaling cascades such as FoxO, Ras, and MAPK. Network analysis identified key miRNAs, such as hsa-miR-20b-5p and hsa-let-7e-5p, as central regulators with extensive interactions, suggesting their potential role in the pathogenesis and immune response of HTLV infections. These findings provide a foundation for future research into the molecular mechanisms of HTLV infections and the development of targeted therapies.

This study proposes a novel method for predicting material creep behavior based on the ZC parameter method using limited creep strain data, aiming to address the limitations of traditional creep prediction methods under conditions of high data variability and incomplete experimental data. A systematic prediction of the creep behavior of DZ125 alloy was conducted, analyzing the creep curves and rupture lifespans under varying temperature and stress conditions. The results indicate that the ZC parameter method can accurately predict complete creep curves from limited creep stress-time data, with predicted values closely aligning with experimental data; all predicted data points fall within the 95% confidence interval. Furthermore, the ZC parameter method covers a broader strain range with smaller errors in lifespan predictions, offering a reliable approach for forecasting the creep behavior of high-temperature alloy materials. The study provides new theoretical support and practical application references for the prediction of creep performance in materials.

Cowpea ( Vigna unguiculata) is an important protein source in Sub-Saharan Africa. Optimizing resilience and productivity through genetic engineering in cowpea has been slow due in part to a lack of defined species-specific regulatory elements and difficulty testing gene function within the native system. In many plant species, Agrobacterium-mediated transient gene expression is widely used to validate constructs before investing in transgenic lines, but its implementation in legumes has been challenging. In this study, we optimized an in planta agroinfiltration assay in trifoliate cowpea leaves using a betalain reporter. To demonstrate the “intact plant” aspect of this system, we used this assay to characterize drought-inducible promoters by challenging cowpea plants with drought stress. Subsequently, to identify and broaden the pool of native promoters known in cowpea, we developed a user-friendly web application, CowPEAsy, allowing users to interrogate gene expression from our canopy-level, developmental-series RNA-Seq dataset. Finally, using CowPEAsy, we identified six promoters that showed constitutive expression across all conditions and verified these promoters with our transient system. This work provides an in vivo platform for preliminary validation of regulatory elements in cowpea and other legumes and enhances current genetic resources by identifying a suite of physiologically relevant promoters of varying strengths.

Reply to Wang et al.To the Editor,We sincerely appreciate the thoughtful response from Wang et al.1, regarding our recent study2. We are grateful for the effort the authors put into expressing potential limitations of our work, as such comments enrich the dialogue in the emerging intersection of pediatric healthcare and health geography. In this interdisciplinary field, constructive discourse is essential to refining methodologies and fostering collaborations that drive innovative solutions. We welcome the opportunity to address their concerns and engage further in this important conversation.Firstly, we acknowledge that a more diverse study sample would have been beneficial. The overall patient population in our health system are diverse across race, ethnicity, language, illness, environmental exposures, and geography. However, the nature of this single center study, as Wang et al. correctly point out, is that our patient study population are less diverse, particularly, in overall geographic composite index measures such as the Social Vulnerability Index (SVI) and Child Opportunity Index (COI). Notably, our study sample represents a group with particularly high scores on SVI and lower scores on COI. That said, a multicenter study involving patients from other health systems would indeed help us further understand the association between SVI or COI and the risk for pediatric intensive care unit (PICU) admission for status asthmaticus. Scaling out to a multicenter study using patient addresses and spatially granular data can be challenging due to the need to protect patient privacy3. Establishing the partnerships, information sharing infrastructure, and processes necessary to conduct a more comprehensive multicenter study is an ongoing area of focus for our team. We are committed to advancing this critical work.Secondly, we acknowledge that a large percentage of patients at the time of our study have reported race and ethnicity values of “other” or “unknown.” Unfortunately, this can be common across health systems with diverse patient populations. Despite the Meaningful Use mandate by the Centers for Medicare and Medicaid Services requiring the collection of race and ethnicity values in electronic health records (EHR), many health systems lack comprehensive race and ethnicity data for their patient populations4. While sub-optimal, there are multiple reasons for responses of “other” and “unknown.” For one, EHRs were traditionally designed with limited race and ethnicity options for patients to choose from, leading to an oversimplification of race and ethnicity categories. Limited options and discrete choices may not always reflect the identity of patients4. Not to mention, directly asking patients how they identify is difficult because the conversation can be uncomfortable for all those involved4. Also, the value of race and ethnicity data for research may not always be fully understood by healthcare professionals and patients leading to subpar data collection4. Still, it is worth noting that since our study was completed, our health system has conducted a large systemic effort to improve the collection of race and ethnicity data. For instance, patients are given more options to self-identify their race and ethnicity with better processes in place during clinic appointments to facilitate data collection. Efforts to minimize missing race and ethnicity data for health disparities research and other health system applications continues to be an important work for all healthcare systems.Thirdly, we concur that other factors, including the residential environment, air pollution, and indoor allergens are important considerations in pediatric healthcare and respiratory diseases. The exposome encompasses a wide array of factors that are associated with asthma5. As we work toward improving our understanding of addressing pediatric health, future work will integrate the physical, social, and environment as key drivers of health. A more holistic approach to understanding this extended environment as it relates to patient health can unlock a better understanding of health and open opportunities to create meaningful and effective interventions. Linking individual environmental factor data remains a key focus for this team.We are thankful for the insightful comments provided by Wang et al. Response to research work provides us all with the opportunity to engage in thoughtful discourse amongst our colleagues to drive research and healthcare forward. Our study of PICU admissions for status asthmaticus is ongoing and a part of a growing work in progress. We share the same ideals Wang et al. express, but more importantly, we share the same desire to advance the health of children everywhere through research.Alicia Adiwidjaja, BS1,2Justin Jones, MD1Patrick Ross, MD1,3Matthew Keefer, MD1,3Margaret J Klein, MS1Jonathan M. Tan, MD MPH MBI1,2,31Children’s Hospital Los Angeles, Los Angeles, California, USA2University of Southern California Spatial Sciences Institute, Los Angeles, California, USA3University of Southern California Keck School of Medicine, Los Angeles, California, USAConflicts of InterestJonathan Tan receives research grant funding from the Anesthesia Patient Safety Foundation, Foundation for Anesthesia Education and Research, and the Southern California Environmental Health Sciences Center. Jonathan Tan is a consultant for GE HealthCare, Edwards Lifesciences, and Medtronic. Jonathan Tan is on the Board of Directors for the Society for Pediatric Anesthesia.ReferencesWang C, Tian H, Shang J. Comment on Justin Jones et al.Pediatric Allergy and Immunology. 2024.Jones J, Klein MJ, Adiwidjaja A, Ross P, Keefer M, Tan JM. The association between composite measures of social vulnerability and PICU admission for status asthmaticus. Pediatric Allergy and Immunology. 2024;35(11). doi:https://doi.org/10.1111/pai.14278. PMID: 39526837. U.S. Department of Health and Human Services. Summary of the HIPAA Privacy Rule. 2003.Diallo MS, Tan JM, Heitmiller ES, Vetter TR. Achieving Greater Health Equity: An Opportunity for Anesthesiology. Anesth Analg. 2022 Jun 1;134(6):1175-1184. doi: 10.1213/ANE.0000000000005937. Epub 2022 Feb 2. PMID: 35110516.Guillien, A., Cadiou, S., Slama, R., & Siroux, V. (2021). The Exposome Approach to Decipher the Role of Multiple Environmental and Lifestyle Determinants in Asthma. International Journal of Environmental Research and Public Health, 18(3), 1138. https://doi.org/10.3390/ijerph18031138

Large Action Models (LAMs) represent a significant evolution from traditional Large Language Models (LLMs) by not only understanding natural language but also autonomously performing tasks in real-world applications. This paper explores the core differences between LLMs and LAMs, emphasizing the expanded capabilities of LAMs to handle complex, multi-step tasks that require interaction with external systems, sensors, and multimodal inputs. LAMs leverage advanced techniques in neuro-symbolic AI, combining neural networks for pattern recognition with symbolic reasoning for logical task execution. The paper highlights key applications of LAMs across industries, including healthcare, manufacturing, customer service, and smart city infrastructure, where their ability to autonomously act, learn from feedback, and interact with both digital and physical environments offers substantial advantages. The role of frameworks like the LAM Simulator is also discussed, illustrating how it accelerates LAM training by automating data generation and providing real-time feedback. This research underscores the transformative potential of LAMs in driving automation and enhancing efficiency across various sectors.

This paper presents a novel system combining machine learning (ML) and 4D-Var data assimilation to enhance the prediction of partial differential equations (PDEs) governing groundwater infiltration through soil and concrete. Utilizing the Richards' equation, simulated with OpenFOAM, our approach leverages Digital Elevation Model (DEM) files from the US Army Corps of Engineers (USACE), pre-processed with Blender, to model the initial conditions. By integrating Ten-sorFlow's auto-differentiation capabilities, our 4D-Var algorithm circumvents the need for adjoint calculations, making it adaptable to any ML framework. Our findings demonstrate that incorporating geometric features significantly enhances the surrogate model's ability to capture the complex dynamics inherent in machine learning models. Likewise, we find that the surrogate model runs considerably faster compared to the OpenFOAM model to generate next step (day ahead) predictions. Additionally, the 4D-Var data assimilation method further refines these predictions, underscoring the effectiveness of combining ML with data assimilation for superior forecast performance. This study provides key insights into the synergistic potential of machine learning and data assimilation techniques for advancing predictive modeling in geophysical applications.

Objective : To describe trends of delivery by caesarean section (CS), using the Robson classification and to assess maternal and perinatal outcomes accordingly. Design : Retrospective observational study. Setting : A tertiary university hospital in Besançon, France. Population : All births at ≥ 22 weeks of gestation from January 1st, 2017, to December 31st, 2023. Methods : All deliveries were classified using Robson Ten Group Classification System. Main outcome measures : Relative size, CS rate and contribution to the overall CS rate were described for each group. Secondary outcomes were rates of adverse maternal and perinatal outcomes. Results: A total of 19 082 women were included. The 7-year mean CS rate was 14.4% (n=2753). A significant reduction of the overall CS rate from 15.4% to 13.0% (95%CI 0.5-4.2%) was observed between 2020 to 2023. This reduction was related to a significant reduction in overall CS rate among group 5 and an important trend towards reduction in group 6. An increase in induction rates was observed. Maternal and perinatal outcomes were stable. A significant reduction of neonatal transfer was observed between 2020 and 2023 (1.4%; 95%CI 0.5-2.3%). Conclusions : CS rate below 15% on average was achieved without increasing maternal and neonatal complications in a tertiary university hospital. Potential target interventions include a better management of women with a previous CS and breech deliveries. Funding : Manon Vouga is supported by Max Cloëtta foundation and Vaudoise Academic Society. Keywords : Caesarean section, maternal and neonatal outcomes, Robson classification, Ten-Group Classification System, France

The global market for lithium-ion batteries continues to grow, and the number of spent lithium-ion batteries is increasing along with the wave of battery retirements. As an important secondary resource, the recycling of spent lithium-ion batteries is of great significance in alleviating the consumption of battery raw materials and avoiding environmental pollution. In the recycling process, the separation of the cathode active material containing valuable metals from the collector is an important prerequisite for reducing the difficulty and complexity of the subsequent metal extraction process. Unlike most reviews that focus on metal extraction, this paper discusses and analyses the separation techniques of cathode active material. Starting from the bonding mechanism between cathode active material and collector, the separation techniques (mechanical, dissolution, pyrolysis and other novel methods) are discussed in detail. The dissociation mechanisms involved in the separation technology are discussed in focus, and an outlook on the subsequent separation technology for cathode materials is presented. This paper helps to provide a systematic understanding for researchers and workers interested in the separation of electrode materials from spent lithium-ion batteries, and has important reference value.

Objective: The primary aim was to assess the feasibility of robotic OSB repair in a preclinical high-fidelity training model, documenting the learning curve and ensuring quality control among surgeons. Design: The learning curve was assessed using the cumulative summation test (LC-CUSUM). Following LC-CUSUM, six additional experiments were performed for competency-cumulative summation (C-CUSUM) analysis to ensure ongoing quality control. Setting: The simulator was created through 3D printing and hand sculpting, simulating a partially exteriorized uterus for laparotomy-assisted laparoscopic OSB surgery. It included a silicone uterus, placenta, and fetal manikin with a simulated OSB lesion, replicating the lesion sac, paraspinal muscles, and neural placode. Population: Four surgeons participated: an expert MFM consultant (TVM), a neurosurgical consultant (AK), an MFM fellow (novice 1, YK), and a neurosurgical resident (novice 2, CK). Methods: The surgical procedure included 8 steps: uterine access, working space creation, lesion exposition, junctional zone dissection, skin mobilization, dural patch application, and closure of myofascial flaps and skin. Success was defined by precise restoration (suture interval <3mm), total operative time ≤180 minutes, and a GEARS score >21/30. Main outcomes: Learning curve and competency were documented via LC-CUSUM and C-CUSUM. Results: Competence was achieved after 15–21 procedures, with novices reaching competency within this range. Participants maintained high performance in subsequent quality-controlled procedures. Conclusion: Robotic-assisted fetal OSB surgery in a high-fidelity simulation is feasible, showing promising outcomes for a large animal model and clinical translation .

Energy harvesting from waste heat is becoming more prevalent as energy conservation efforts continue to increase worldwide. Thermoelectric Generators (TEGs) are devices that can harvest such waste heat and convert it into useful electrical power. Traditionally, active cooling methods are used to maximize the thermal gradient across a TEG module in order to optimize the energy conversion process. However, active cooling is impractical for a significant number of industrial harsh-environment applications. To examine the feasibility of using passively cooled TEG devices for producing useful electrical power, a Bismuth Telluride (BiTe) TEG device was fabricated and tested from 200°C to 290°C on the hot side, without active cooling on the cold side. As such, the temperature difference across the TEG device remained consistent at approximately 50°C over the range of hot-side temperatures tested. Under these conditions, the BiTe TEG device produced a single-couple average voltage of 8 mV over the range of test temperatures, and single-couple powers up to 0.10 mW at 290°C, despite the lack of active cooling. These results show the capability of TEG module integration to power electrical circuits for high-temperature harsh-environment applications operating under passive cooling.

Objective: To compare pre-eclampsia (PE) risk strategies among Black vs. White ethnicity women. Design: Prospective non-intervention cohort studies. Setting: Maternity hospitals, United Kingdom and Europe. Population: Singleton pregnancies delivering at ≥24 weeks, without major anomalies. Methods: PE risk was determined by National Institute for Health and Care Excellence (NICE) guidance, NICE guidance modified adding Black ethnicity as a moderate-risk factor, and the Fetal Medicine Foundation (FMF) competing-risks multivariable model. To compare model performance, the FMF screen-positive rate (SPR) was adjusted to match NICE. Results: At 11-13 weeks, screening for preterm PE risk occurred in 61,174 pregnancies; 493 (0.8%) developed preterm PE. At SPR=11.2%, FMF (vs. NICE) almost doubled the DR for preterm PE for Black (88.0%) vs. White (66.4%) women, but DR increased more among Black women (14.7%, 95% confidence interval [CI] 5.6-23.6). For NICE-modified, the preterm PE DR increased (85.2%), similar to FMF (89.6%), but SPR was higher (59.6% vs. 27.7%, respectively). At 35-36 weeks, screening for subsequent PE occurred in 29,035 pregnancies; 654 (2.3%) developed PE. At SPR=10.9%, FMF (vs. NICE) more than doubled the DR for subsequent PE, and DR increased more among Black vs. White women (12.1%, 95% CI 1.9-22.3). For NICE-modified, the PE DR increased (85.0%), similar to FMF (74.8%), but SPR was higher (59.1% vs. 17.6%, respectively). Conclusions: The FMF competing-risks models increased the DR for PE, particularly amongst Black women. While DRs similar to FMF were seen with addition to NICE of Black ethnicity as a moderate-risk factor, SPR was two-to-three times higher.

Iron deficiency is the prevalent and most widespread nutritional shortfall for humans, affecting over 30% of the global population and leading to anemia, particularly among preschool-aged children and pregnant women in developing countries. Simultaneously, while half of the world’s population depends on rice ( Oryza sativa L.) as a staple food, this cereal does not provide a sufficient amount of that micronutrient to meet these people’s nutritional needs: even when iron is readily available in the soil, it does not accumulate in the consumed portion of the grain, namely, the starchy endosperm, being instead retained in the aleurone layer, in the pericarp and in the embryo. In this context, the present work applies computational biology tools — such as normal mode analysis and molecular dynamics simulations — to elucidate the behavior and transport mechanism of the Vacuolar Iron Transporter 2 (OsVIT2), a central protein for iron homeostasis in rice, with the objective of laying the foundations for future OsVIT2 engineering projects that could be articulated with ongoing efforts to promote iron biofortification in rice. We shed light on the interplay between protonation state, configuration and hydration of OsVIT2’s pore; on the mechanics of its opening and on the ever-shifting hydrogen bond network contained within it. We also explore the potential contribution of the “flexible arms” to the iron-capturing function performed by the cytoplasmic domain.

Research on medical cannabis is progressing, with several cannabinoids emerging as promising compounds for clinical use. The available evidence suggests that cannabinoids may modulate glycine (GlyR) and GABA A receptors, which are part of the pentameric ligand-gated ion channels (pLGICs) superfamily and facilitate chemical communication in the nervous system. In a previous study, we employed molecular dynamics (MD) simulations to elucidate the dynamics of the GlyR/Δ 9-tetrahydrocannabinol (THC) complex and successfully identified a representative binding mode. Given the structural similarity between GlyR and GABA AR, we employed a similar strategy to investigate GABA AR-cannabinoid interactions. We initially assessed the binding mode of THC to GABA AR-α1β2γ2 at the equivalent binding site of the GlyR —i. e., on its two α-subunits— as well as the impact of this binding on the channel’s dimensions. Our results indicate, first, that the binding modes of THC to GABA AR and GlyR exhibit comparable characteristics; and second, that THC may function as a potentiator of GABA activity due to a significant opening of the channel pore. Additionally, we aimed to reduce the overall computational cost associated with exploring binding modes. To this end, we developed and validated a simplified model comprising a single-monomer system for cannabinoid binding studies. This model proved to be accurate and cost-effective, accelerating the in silico screening process and allowing for the study of GABA AR-cannabinoid binding through docking and MD simulations. Moreover, the analysis of different cannabinoids in this system suggests that cannabigerol (CBG) could act as a ligand for GABA AR, opening unexplored avenues for research.

Objectives: To investigate the clinical value of fetal heart quantification (fetal HQ) in the evaluation of normal foetal heart size, morphology and cardiac function at different gestational weeks. Materials and methods: A total of 101 pregnant women diagnosed with a healthy foetus by foetal echocardiography from September 2021 to December 2023 were selected and classified into four different periods of gestational weeks: 20-28 weeks (25 cases), 29-32 weeks (26 cases), 33-36 weeks (26 cases), 37-40 weeks (24 cases). Quantitative analyses were performed by automatically tracking the endocardium using fetal HQ software that comes with the Voluson E10 from GE. To investigate the correlation between four-chambered vesicle length end-diastolic (4CV LED), four-chambered vesicle transverse width end-diastolic (4CV TWED), global sphericity index (GSI), ejection fraction (EF), stroke volume (SV), cardiac output (CO) and gestation age (GA), and the variability of normal foetal cardiac morphology and cardiac function at different gestational weeks. Results: A statistically significant difference was observed between 4CV LED and 4CV TWED in normal foetuses at different gestational weeks ( P < 0.05), which exhibited a positive correlation with gestational week. Conversely, no significant correlation was identified between GSI and gestational week ( P > 0.05). The mean GSI of 101 normal foetuses found to be 1.25 ± 0.09. A comparative analysis of EF, SV, and CO in normal foetuses at different gestational weeks revealed statistically significant differences in SV and CO ( P < 0.05), which gradually increased with gestational weeks, whereas there was no statistically significant difference in EF ( P ＞ 0.05). Conclusions: Fetal HQ represents a straightforward and dependable method for evaluating GSI and 24-segment SI of the left and right ventricles, which can provide a certain theoretical basis for the clinical quantitative evaluation of fetal cardiac geometry and cardiac function.

Introduction: The leadless pacemakers are implanted routinely under fluoroscopic image, yet the pacing sites and corresponding paced electrocardiography (ECG) remain unclear. This study was to determine the computed tomography (CT)-verified location of the leadless Micra™ pacemakers (Micra™) and ECG characteristics. Methods: 20 consecutive patients who met the pacemaker indications for bradycardia and underwent fluoroscopy assisted Micra TM implantation were enrolled. All subjects underwent a postoperative CT scan to determine the precise location of the Micra TM pacing tip. Paced 12-lead ECG characteristics were analysed and correlated with the Micra TM tip location. Results: In the nine partitions of fluoroscopic RAO images, 14 (70%) of 20 patients had the Micra TM tip in zone 5, 5 (25%) in zone 6 and 1 in zone 2. Reconstructed CT 3-D cardiac images found Micra TM tips mostly clustered near the anterior insertion between the RV septum and free wall with 12 cases at the insertion-septal side and 8 at the free-wall side. ECG morphological analysis found that the peak deviation index in ECG lead V1 was 0.402±0.061 for Micra TM tips at the insertion-septal side and 0.542±0.053 in the free-wall side (P <0.001 between two sides) and paced clumsy R wave was often observed for tips at the free-wall side though there was no difference in QRS duration between two sides. Conclusion. In routine Micra TM implantation, the pacing sites were often located in the anterior insertion region, either at the insertion-septal or free-wall side. The ventricular activation propagation likely depended on the pacing sites.

Purpose: Linking claims data to electronic health record (EHR) data can improve completeness, often at a cost of decreased sample size. Quantifying information gained and differences in patient characteristics between EHR and EHR-claims linked cohorts may inform study design. Methods: Using ConcertAI Patient360 EHR linked to multiple closed insurance claims sources, we compared an EHR cohort of patients with incident metastatic breast cancer (mBC) to an EHR-claims subcohort (requiring ≥90 days claims coverage). We analyzed diagnosis coverage, patient-time during lookback and follow-up, baseline characteristics, and rates of 14 adverse events (AEs). Analyses were age-stratified due to insurance coverage changes at age 65. Results: For the EHR cohort (N = 6289), 1438 (23%) were in the EHR-claims subcohort. A greater proportion were aged ≥65 years in the EHR cohort (30%) than in the EHR-claims subcohort (17%). EHR-claims patients had longer observation periods and more unique diagnoses across both age groups. For most AEs, incidences were higher in both age groups in the EHR-claims subcohort than in EHR cohort. Conclusions: EHR-claims provided more diagnoses and observation time, at the cost of a reduction in sample size and underrepresentation of patients ≥65 years. Differing age proportions support age-stratified or standardized analyses for EHR-claims data. Results aid interpretation of differences between EHR and EHR-claims results due to shifts in age, completeness of diagnosis history, and duration of observation.

The koala (Phascolarctos cinereus) is Australia’s largest arboreal folivore that inhabits eastern and south-eastern Australia. While its populations are in decline in areas of New South Wales and Queensland, high and increasing densities in the Mount Lofty Ranges of South Australia raise concerns of overbrowsing. This challenge highlights the need for optimized fertility-control strategies to balance sustainable population management with ecological, ethical, and logistic complexities. Demographic models are valuable tools for predicting population dynamics, but their accuracy hinges on reliable estimates of population density, often influenced by biases in expert-elicited and citizen-science data. We developed and combined a point-process model, an ensemble species distribution model, and a demographic model to project koala populations in the Mount Lofty Ranges over the next 25 years to assess the efficiency and cost-effectiveness of fertility-control interventions. We tested two hypotheses: (1) koala distribution is driven by rainfall, temperature, and native vegetation, with summer rainfall boosting habitat suitability, and (2) spatially targeted fertility intervention is more cost-effective than generalized strategies due to subpopulation connectivity. Accounting for sampling biases and local densities, our models estimate that highly suitable areas in the Mount Lofty Ranges are determined by rainfall, temperature, and vegetation. Without intervention, this population could increase by ~10% in 25 years. Fertility control focusing on adult females was the most cost-effective (~AU$28 million) strategy, although this scenario was slower at reducing population size compared to an intervention also sterilizing female back young. While the choice of sterilization scenario has minimal impact on overall costs, ethical considerations and long-term conservation goals such as population density thresholds will have more influence on managing expenses effectively.

Objectives: To identify novel protein biomarkers and evaluate their combination with traditional inflammatory markers for early diagnosis of moderate-to-severe bronchopulmonary dysplasia (BPD) in very low birth weight (VLBW) preterm infants. Working Hypothesis: A combination of novel protein biomarkers and traditional inflammatory markers could improve early diagnostic accuracy for moderate-to-severe BPD. Study Design: Prospective cohort study. Patient Selection: 92 VLBW preterm infants (<1500g) were enrolled and categorized into mild BPD (n=42), moderate-to-severe BPD (n=30), and non-BPD (n=10) groups. Methodology: Blood samples were collected within 24 hours after birth. Peripheral inflammatory markers were measured, and plasma proteome was analyzed using Astral-DIA technology. Results: Proteomic analysis identified 127 differentially expressed proteins, with three proteins (IGFBP-2, S100A8, and IL-1Ra) showing the most significant changes in moderate-to-severe BPD. The combination of these three proteins achieved an AUC of 0.921 (95% CI: 0.864-0.978) for predicting moderate-to-severe BPD, outperforming traditional inflammatory markers including CRP (AUC=0.847). Integration of the protein panel with CRP further improved diagnostic accuracy (AUC=0.945). Conclusions: The study establishes a novel protein signature that, when combined with traditional inflammatory indicators, provides improved early diagnostic accuracy for moderate-to-severe BPD in VLBW infants.

Introduction: Laryngotracheoesophageal clefts (LTEC) are well-known aspiration-associated lesions. Results of swallow studies, and respiratory, feeding, and swallowing symptoms are commonly used indications for repair, despite being unclear predictors of disease. Although lung inflammation and injury are primary concerns, such findings are uncommonly and inconsistently evaluated and reported and therefore it remains unclear how well swallow studies predict lung disease. Methods: Children seen in our Aerodigestive program 10/1/2012 and 9/30/2023, with a LTEC and a videofluoroscopic swallow study (VFSS) or flexible endoscopic evaluation of swallowing (FEES) were included. Data regarding clinical history and risk factors, BAL, chest CT, and impedance probe results were abstracted, along with VFSS/FEES results and functional oral intake scale (FOIS-P/I) at baseline and follow-up. Results: 82 subjects identified. Lung inflammation and bronchiectasis were common and correlated. Clinical factors, impedance probe, and the presence/severity of swallowing abnormalities on VFSS/FEES were not predictive of lung disease. 57 patients underwent LTEC repair for a range of indications, only 49% based on CT and/or BAL findings. LTEC repair was associated with a trend towards improvement feeding and swallowing, yet none of these met statistical significance. Discussion: Children with LTEC have a high prevalence of inflammatory lung disease and injury and undergo repair for a variety of reasons. The insufficient ability of swallow study to identify patients with lung disease suggests that such studies identify functional abnormalities but not a disease state, per se. Nevertheless, LTEC repair is associated with improvements in feeding and swallowing in a subset of patients.

Cyber-attacks pose a security threat to military command and control networks, Intelligence, Surveillance, and Reconnaissance (ISR) systems, and civilian critical national infrastructure. The use of artificial intelligence and autonomous agents in these attacks increases the scale, range, and complexity of this threat and the subsequent disruption they cause. Autonomous Cyber Defence (ACD) agents aim to mitigate this threat by responding at machine speed and at the scale required to address the problem. Additionally, they reduce the burden on the limited number of human cyber experts available to respond to an attack. Sequential decision-making algorithms such as Deep Reinforcement Learning (RL) provide a promising route to create ACD agents. These algorithms focus on a single objective such as minimizing the intrusion of red agents on the network, by using a handcrafted weighted sum of rewards. This approach removes the ability to adapt the model during inference, and fails to address the many competing objectives present when operating and protecting these networks. Conflicting objectives, such as restoring a machine from a back-up image, must be carefully balanced with the cost of associated down-time, or the disruption to network traffic or services that might result. Instead of pursing a Single-Objective RL (SORL) approach, here we present a simple example of a multi-objective network defence game that requires consideration of both defending the network against red-agents and maintaining critical functionality of green-agents. Two Multi-Objective Reinforcement Learning (MORL) algorithms, namely Multi-Objective Proximal Policy Optimization (MOPPO), and Pareto-Conditioned Networks (PCN), are used to create two trained ACD agents whose performance is compared on our Multi-Objective Cyber Defence game. The benefits and limitations of MORL ACD agents in comparison to SORL ACD agents are discussed based on the investigations of this game.

Objective: Using action research principles, in consultation with members and administrators of Wellspring Canada, the purpose of the current study was to adapt and examine the impact of a positive body image program (Body Image Awareness Seminars; BIAS) on positive and negative body image in individuals living with cancer. Methods: The project used a single-group pretest–posttest design with a 6–week follow-up. Over the 6-week program, 37 participants engaged in 90-minute weekly group sessions consisting of researcher-led psychoeducation, group discussion and activities grounded in positive body image research. Each seminar had a unique theme designed to promote respect, acceptance and appreciation for the body. Participants completed the Body Image Scale, Body Appreciation Scale-2, Functionality Appreciation Scale, Measure of Body Apperception, Appearance Evaluation subscale and Self-Compassion Scale anonymously using Qualtrics at the 3 data collection points. Homework assignments included optional readings and writing exercises based on the positive body image tenet taught that week. Results: Participants reported statistically significant improvements in positive body image (i.e., body appreciation, functionality appreciation), self-compassion, and negative body image (i.e., body image distress and disturbance, investment in body integrity and appearance evaluation), which were sustained at the 6-week follow-up in a subsample of participants ( n=11). Conclusions: This study suggests that the adapted BIAS program can lead to improvements in both positive and negative body image in individuals living with diverse types of cancer. Results support the implementation of BIAS in the standard of care for those living with cancer to continue to affect positive change.

Most studies have focused on mother-to-child transmission and postpartum hepatitis flare. We intended to evaluate the expression profile of pregenomic RNA (pgRNA) and its factors in chronic HBV infection (CHB) patients during pregnancy and postpartum. 134 pregnant and 100 postpartum CHB patients were enrolled, and the levels of serum pgRNA were quantified. There were significant differences in clinical characteristics between the pregnant and postpartum CHB patients, but there was no significant difference in pgRNA levels between the two groups. When the levels of HBV DNA and HBV antigen were low, the corresponding pgRNA detection rate decreased. pgRNA was positively correlated with DNA and HBV antigen in the pregnancy and postpartum CHB patients. In the pregnant group, antiviral treatment was an independent risk factor for pgRNA levels; in the postpartum period, HBeAg levels and antiviral treatment were independent risk factors for pgRNA levels. Considering that patients under antiviral treatment are often accompanied by a high DNA load or positive HBeAg, it is the DNA level and HBeAg that affect the level of pgRNA essentially. pgRNA levels show different profiles in pregnancy and postpartum, which is of great significance for the diagnosis and management of these particular groups.