Dynamics Trajectories Research Articles

Neuroblastoma plasticity during metastatic progression stems from the dynamics of an early sympathetic transcriptomic trajectory.

Despite their indisputable importance in neuroblastoma (NB) pathology, knowledge of the bases of NB plasticity and heterogeneity remains incomplete. They may be rooted in developmental trajectories of their lineage of origin, the sympatho-adrenal neural crest. We find that implanting human NB cells in the neural crest of the avian embryo allows recapitulating the metastatic sequence until bone marrow involvement. Using deep single cell RNA sequencing, we characterize transcriptome states of NB cells and their dynamics over time and space, and compare them to those of fetal sympatho-adrenal tissues and patient tumors and bone marrow samples. Here we report remarkable transcriptomic proximities restricted to an early sympathetic neuroblast branch that co-exist with phenotypical adaptations over disease progression and recapitulate intratumor and interpatient heterogeneity. Combining avian and patient datasets, we identify a list of genes upregulated during bone marrow involvement and associated with growth dependency, validating the relevance of our multimodal approach.

Sharp Curve Trajectory Tracking of a Universal Omni-Wheeled Mobile Robot Using a Sliding Mode Controller

Abstract In our previous works, Amarasiri et al. (2022, “Robust Dynamic Modeling and Trajectory Tracking Controller of a Universal Omni-Wheeled Mobile Robot,” ASME Lett. Dyn. Sys. Control 2(4), p. 040902) and Amarasiri et al. (2024, “Investigating Suitable Combinations of Dynamic Models and Control Techniques for Offline Reinforcement Learning Based Navigation: Application of Universal Omni-Wheeled Robots,” ASME Lett. Dyn. Sys. Control 4(2), p. 021007), two dynamic models of a universal omni-wheeled mobile robot (UOWMR), and trajectory-tracking controllers (three linear and one nonlinear) were developed and presented. The purpose of that work was to identify suitable combinations of dynamic models and trajectory-tracking controllers, choosing the combination with the highest tracking accuracy and the lowest solver execution time. The ultimate purpose is to utilize these physics-based tools in a reinforcement learning (RL) agent developed for path planning and navigation in an unstructured environment. Three trajectories were investigated including a smooth path, a sharp curved path, and a smooth path with disturbance forces. The sliding mode controller (SMC) following a trajectory with sharp (right-angled) curves was not investigated in that work. The sharp corners caused indeterminacy in the path derivatives required for the SMC algorithm. In this short article, we complete our studies of the SMC on sharp corner paths utilizing slight trajectory corner smoothing.

Biologically inspired adaptive crack network reconstruction based on slime mould algorithm.

The dynamic crack propagation trajectories play a crucial role in enhancing our understanding of spatial mechanisms involved in crack expansion. However, visualization of internal cracks under complex crack conditions has always been a challenge. Biological networks have been honed by many cycles of evolutionary selection pressure and are likely to yield reasonable solutions to such combinatorial optimization problems. This study applied the slime mould algorithm to improve the accuracy of internal crack localization in rocks and employed Minimum spanning tree and Gaussian mixture model to construct the crack propagation trajectories. By introducing the concept of bond length, the evolution characteristics of crack levels were effectively characterized. Research results showed that this approach effectively preserves essential crack localization information while mitigating the influence of interfering parameters, providing crack characterization results that exhibit high consistency with actual fracture patterns. The curves of cumulative bond length and relative bond length over time conform to the trend of a Growth/Sigmoidal curve. The strength of the bond was correlated with the temporal process of crack propagation. This result could be helpful for analyzing crack trajectories and predicting rock stability.

Inferring the existence of hydrogen bonds directly from statistical analysis of molecular dynamics trajectories.

As a demonstration of how fundamental chemical concepts can be gleaned from data using machine learning methods, we demonstrate the automated detection of hydrogen bonds by statistical analysis of molecular dynamics trajectories. In particular, we infer the existence and nature of electrostatically driven noncovalent interactions by examining the relative probability of supramolecular configurations with and without electrostatic interactions. Then, using Laplacian eigenmaps clustering, we identify hydrogen bonding motifs in hydrogen fluoride, water, and methanol. The hydrogen bonding motifs that we identify support traditional geometric criteria.

StreaMD: the toolkit for high-throughput molecular dynamics simulations.

Molecular dynamics simulations serve as a prevalent approach for investigating the dynamic behaviour of proteins and protein-ligand complexes. Due to its versatility and speed, GROMACS stands out as a commonly utilized software platform for executing molecular dynamics simulations. However, its effective utilization requires substantial expertise in configuring, executing, and interpreting molecular dynamics trajectories. Existing automation tools are constrained in their capability to conduct simulations for large sets of compounds with minimal user intervention, or in their ability to distribute simulations across multiple servers. To address these challenges, we developed a Python-based tool that streamlines all phases of molecular dynamics simulations, encompassing preparation, execution, and analysis. This tool minimizes the required knowledge for users engaging in molecular dynamics simulations and can efficiently operate across multiple servers within a network or a cluster. Notably, the tool not only automates trajectory simulation but also facilitates the computation of free binding energies for protein-ligand complexes and generates interaction fingerprints across the trajectory. Our study demonstrated the applicability of this tool on several benchmark datasets. Additionally, we provided recommendations for end-users to effectively utilize the tool.Scientific contributionThe developed tool, StreaMD, is applicable to different systems (proteins, ligands and their complexes including co-factors) and requires a little user knowledge to setup and run molecular dynamics simulations. Other features of StreaMD are seamless integration with calculation of MM-GBSA/PBSA binding free energies and protein-ligand interaction fingerprints, and running of simulations within distributed environments. All these will facilitate routine and massive molecular dynamics simulations.

Explicit Configurational Entropy of Mixing in Molecular Dynamics Simulations.

The entropy of mixing of a multicomponent system of particles is a simple expression of the molar fractions for the equilibrium state, but its intermediate values for transient (nonequilibrium) states can not be calculated directly from the particle coordinates so far. We propose a simple expression for the configurational entropy of mixing based solely on the set of instantaneous coordinates, which is suitable for the on-the-fly determination of the degree of mixing along a molecular dynamics trajectory. We illustrate the applicability of our scheme with the example of several molecular mixtures that exhibit fast and slow mixing and demixing processes within a molecular dynamics simulation.

Dynamic trajectories of left ventricular ejection fraction in heart failure with improved ejection fraction.

Heart failure with improved ejection fraction (HFimpEF) has been regarded as a new heart failure (HF) type in 2022. However, studies on the impact of left ventricular ejection fraction (LVEF) trajectories on the prognosis of patients with HFimpEF are scarce. In this study, we investigated dynamic trajectories of LVEF and different clinical outcomes in HFimpEF. This was a multi-center study included patients diagnosed with HF with reduced ejection fraction (HFrEF) between January 1, 2015, and October 31, 2022. Enrolled patients were divided into HFimpEF and persistent HFrEF groups. To further investigate different LVEF trajectories in HFimpEF patients, they were classified into persistent HFimpEF and transient HFimpEF subgroups. Adverse clinical outcomes encompassed all-cause death, cardiovascular death, and HF-related rehospitalization. A total of 734 patients were included (HFimpEF: n = 162; persistent HFrEF: n = 572). Cox regression analysis revealed that compared with persistent HFrEF, patients with HFimpEF experienced a lower risk of all-cause and cardiovascular death. Subgroup analysis determined that only 113 (69.75%) patients maintained an LVEF exceeding 40%. Cox regression analysis revealed that persistent HFimpEF patients had a lower risk of all-cause and cardiovascular death compared to those with transient HFimpEF. Finally, multivariate logistic analysis showed that gender and high-density lipoprotein cholesterol levels were independent predictors of persistent HFimpEF. HFimpEF does not accurately represent HF recovery, given that there are different trajectories of LVEF in HFimpEF. Patients with persistent HFimpEF experience better clinical outcomes, highlighting clinicians should identify clinical modifiable factors to maintain a stable HF stage for better prognosis. ChiCTR2400086622, 08/07/2024.

Monitoring C–C coupling in catalytic reactions via machine-learned infrared spectroscopy

Abstract Tracking atomic structural evolution along chemical transformation pathways is essential for optimizing chemical transitions and enhancing control. However, molecule-level knowledge of structural rearrangements during chemical processes remains a great challenge. Here, we couple infrared spectroscopy as a non-invasive method to probe molecular transformations, with a machine-learned protocol to immediately map the spectroscopic fingerprints to atomistic structures. From the theoretical perspective, we demonstrate it here with the example of C–C coupling in catalytic reactions, elucidating various structural conformations along dynamic trajectories. Within the transferable application to the specific CO–CO dimerization reaction, the structural and energetic variations of the critical chemical species could be identified via infrared spectroscopy. This approach extends the power of spectroscopy from fingerprinting chemical configurations to using them for assigning dynamic structural information.

Dynamics trajectory of patient-reported quality of life and its associated risk factors among hepatocellular carcinoma patients receiving immune checkpoint inhibitors: a prospective cohort study

ObjectiveWe aimed to characterize quality of life (QOL) trajectories among patients with intermediate and advanced hepatocellular carcinoma patients treated with immunotherapy.MethodsBarcelona Clinic Liver Cancer (BCLC) stage B-C HCC patients receiving immunotherapy at Guangxi Medical University Cancer Hospital were included. Trajectories of QOL, assessed using the Functional Assessment of Cancer Therapy-Hepatobiliary (FACT-Hep) questionnaire, were identified through iterative estimations of group-based trajectory models. Associations with trajectory group membership were analyzed using multivariable multinomial logistic regression.ResultsThree trajectory groups were identified (n=156): excellent (35.3%), poor (43.6%), and deteriorating (21.1%) QOL. The deteriorating trajectory group reported a mean QOL score of 124.79 (95% CI, 116.58–133.00), but then declined significantly at month-2 (estimated QOL score 98.67 [95% CI, 84.33–113.00]), and the lowest mean score is reached at month-6 (estimated QOL score 16.58 [95% CI, 0–46.07]). Factors associated with membership to the deteriorating group included no drinking (odds ratio [OR] vs yes [95% CI], 3.70 [1.28–11.11]), no received radiotherapy (OR vs yes [95% CI], 8.33 [1.41–50.00]), diabetes (OR vs no [95% CI], 6.83 [1.57–29.73]), and extrahepatic metastasis (OR vs no [95% CI], 3.08 [1.07–8.87]). Factors associated with membership to the poor group also included body mass index ≤24.0 kg/m2 (OR vs no [95% CI], 4.49 [1.65–12.22]).ConclusionsThis latent-class analysis identified a high-risk cluster of patients with severe, persistent post-immunotherapy QOL deterioration. Screening relevant patient-level characteristics may inform tailored interventions to mitigate the detrimental impact of immunotherapy and preserve QOL.

Vibration characteristics of piezoelectric pipe conveying fluid subjected to fluid-structure-electrical interaction

This paper mainly investigates the vibration characteristics of piezoelectric pipe conveying fluid subjected to fluid-structure-electrical interaction. Based on the Hamilton’s principle, the dynamic equations of the cantilever piezoelectric pipe subjected to the weight and fluid-structure-electrical interaction are established and solved by using the Galerkin method. Ultimately, complex frequency and critical flow velocity are obtained. The main discussion focused on the influence of electromechanical coupling, resistive load, and dimensionless capacitance on the critical flow velocity under different lengths of piezoelectric materials. It also examined the dynamic trajectories of the real and imaginary parts of the complex frequency under various mass ratios and resistive loads. Furthermore, it explored the impact of parameters representing voltage on the stability of the system. The results indicate various stability evolutions under different lengths of piezoelectric materials, flow velocities, and parameters representing voltage. The stability of the system pipe is influenced by factors such as the length of the piezoelectric material and resistive load.

Regulating of Lithium‐Ion Dynamic Trajectory by Ferromagnetic CoF2 to Achieve Ultra‐Stable Deep Lithium Deposition Over 10000 h

AbstractCurrently, the realization of controllable Li electrodeposits to further extend the cycling life of Li metal anode remains challenging. Herein, it is reported that carbon nanosheet array‐loaded ferromagnetic CoF2 nanoparticles on carbon cloth (CC@CoF2/C) as an internal micro‐magnetic field source to manipulate the dynamic trajectory of Li+ deposition via the magnetohydrodynamic effect. This approach ensures uniform lithium‐ion distribution and improves deep plating capacity, achieving a prolonged cycle life of the dendrite‐free Li anode. Finite element simulations, in situ characterizations, and electrochemical tests confirm that magnetic CoF2 not only guides Li+ migration through Lorentz force to prevent dendritic growth but also improves uniform Li deposition due to the in situ conversion of LiF‐rich solid electrolyte interphase during electroplating. Meanwhile, a CC@CoF2/C‐based half‐cell operates stably over 10 000 h at 1 mA cm−2 with a low 7.8 mV overpotential. When matched with a commercial LiFePO4 cathode, the full cell reveals a high capacity of 122.96 mAh g−1 at a 2 C rate after 1000 cycles, retaining 91.95% capacity. The proposed strategy can be effectively expanded and adapted to investigate the deposition behavior of a wide range of metal anodes, offering a versatile and robust analytical framework for addressing diverse metal‐based electrochemical systems.

Virtual screening of plant-derived molecules against zinc-dependent imipenemases in class B metallo-β-lactamases of Acinetobacter baumannii.

Metallo-β-lactamases (MBLs), enzymes of class B, employ zinc ions to degrade β-lactam antibiotics such as penicillins, cephalosporins, carbapenems, and cephamycins. Carbapenem-resistant Acinetobacter baumannii (CRAB) is linked to the existence of carbapenemase enzymes such as oxacillinase and MBL. The most prevalent resistance mechanisms include imipenemases (IMP), verona integron-encoded MBL, and New Delhi MBL-1. The effectiveness of current antibiotics against the MBL enzyme is limited due to the presence of metal ions, underscoring the need for new antimicrobial agents. Recent research has demonstrated that natural compounds can effectively inhibit MBL. This study aims to screen natural phytochemicals against IMP-2 MBL using in silico virtual screening techniques via AutoDock Vina and molecular dynamic simulations with GROMACS for 200ns, followed by molecular mechanics/Poisson‒Boltzmann surface area analysis. This procedure identified new lead molecules against A. baumannii that produce IMP. A total of 588 natural compounds were screened against IMP, along with the imipenem substrate and known inhibitors of L-captopril. The top four compounds, N025-0038 (NC1), N062-0008 (NC2), eupalitin, and Rosmorinic acid, demonstrated binding affinities of ‒8.5, ‒8.4, ‒7.5, and ‒7.2kcal/mol, respectively. The structural stability of these complexes was observed to be maintained throughout the simulation in a dynamic environment, as determined by molecular dynamics trajectory analysis, and all these compounds met the SWISS-ADME (adsorption, distribution, metabolism, and excretion) properties. NC1 and NC2 compounds are considered potential drug molecules against IMP. However, while these selected compounds showed superior binding energy in computational analysis, further in vitro analysis is required to establish an effective drug regimen against A. baumannii that produces IMP.

Trajectory tracking for autonomous surface ships using Gaussian process regression and model predictive control with BVS strategy

Autonomous navigation is critical to the development of next-generation shipping systems. The proposal of intelligent ships enables innovation in the shipping and shipbuilding industry and increases the safety and efficiency of ship operations. Autonomous control of surface ships to follow a prescribed trajectory is critical in a variety of maritime applications. This paper proposes a trajectory tracking control strategy for autonomous surface ships that combines nonparametric modelling using Gaussian Process Regression (GPR) with the Model Predictive Control (MPC) framework. A Bézier curve-based Virtual Ship(BVS) guidance strategy is proposed to convert dynamic trajectory points into reference heading angles and speeds, such that the trajectory tracking problem can be decomposed into heading control and speed control problems. Gaussian process regression is utilised to identify the correlation between propeller revolution speed and ship speed, as well as the correlation between rudder angle and heading angle based on experimental data. Two GPR models are therefore constructed as the prediction models for designing MPC controllers for heading control and speed control, respectively. Nonlinear optimisation algorithms are utilised to search for optimal control commands in each sampling interval to solve the optimisation problem in MPC with GPR models and input constraints. Simulations are carried out to evaluate the effectiveness of the proposed method.

DFCNet +: Cross-modal dynamic feature contrast net for continuous sign language recognition

In sign language communication, the combination of hand signs and facial expressions is used to convey messages in a fluid manner. Accurate interpretation relies heavily on understanding the context of these signs. Current methods, however, often focus on static images, missing the continuous flow and the story that unfolds through successive movements in sign language. To address this constraint, our research introduces the Dynamic Feature Contrast Net Plus (DFCNet+), a novel model that incorporates both dynamic feature extraction and cross-modal learning. The dynamic feature extraction module of DFCNet+ uses dynamic trajectory capture to monitor and record motion across frames and apply key features as an enhancement tool that highlights pixels that are critical for recognizing important sign language movements, allowing the model to follow the temporal variation of the signs. In the cross-modal learning module, we depart from the conventional approach of aligning video frames with textual descriptions. Instead, we adopt a gloss-level alignment, which provides a more detailed match between the visual signals and their corresponding text glosses, capturing the intricate relationship between what is seen and the associated text. The enhanced proficiency of DFCNet+ in discerning inter-frame details translates to heightened precision on benchmarks such as PHOENIX14, PHOENIX14-T and CSL-Daily. Such performance underscores its advantage in dynamic feature capture and inter-modal learning compared to conventional approaches to sign language interpretation. Our code is available at https://github.com/fyzjut/DFCNet_Plus.

Trans-spectral transfer of spatio-temporal optical Ferris wheel with nonlinear wave mixing

The trans-spectral manipulation of spatio-temporal structured light, characterized by dynamic inhomogeneous trajectories and a unique nature in the space–time domain, opens myriad possibilities for high-dimensional optical communication in the ultraviolet band. Here, we experimentally demonstrate the high-performance transfer of the spatio-temporal optical Ferris wheel beam from near-infrared to blue–violet wavelengths. Owing to the energy conservation and momentum conservation mechanism, the 420 nm output signal beam accurately retains the spatio-temporal characteristics of the 776 nm input probe optical Ferris wheel beam, facilitated by the 780 nm Gaussian pump beam. The identical multi-petal intensity profiles confirm the successful transfer of spatial characteristics from the input probe to the output signal beams. The fully synchronized rotation velocities and directions of the probe and signal beams demonstrate the precise transfer of temporal characteristics, achieving approximately 98% conversion accuracy. This work enables efficient information transfer across different wavelength bands and offers a promising approach for achieving high-dimensional quantum communication.

The genomic natural history of the aurochs.

Now extinct, the aurochs (Bos primigenius) was a keystone species in prehistoric Eurasian and North African ecosystems, and the progenitor of cattle (Bos taurus), domesticates that have provided people with food and labour for millennia1. Here we analysed 38 ancient genomes and found 4 distinct population ancestries in the aurochs-European, Southwest Asian, North Asian and South Asian-each of which has dynamic trajectories that have responded to changes in climate and human influence. Similarly to Homo heidelbergensis, aurochsen first entered Europe around 650 thousand years ago2, but early populations left only trace ancestry, with both North Asian and European B. primigenius genomes coalescing during the most recent glaciation. North Asian and European populations then appear separated until mixing after the climate amelioration of the early Holocene. European aurochsen endured the more severe bottleneck during the Last Glacial Maximum, retreating to southern refugia before recolonizing from Iberia. Domestication involved the capture of a small number of individuals from the Southwest Asian aurochs population, followed by early and pervasive male-mediated admixture involving each ancestral strain of aurochs after domestic stocks dispersed beyond their cradle of origin.

Effects of Bio-Inspired Wing Dihedral Variations on Dynamic Soaring Performance of Unmanned Aerial Vehicles

On the basis of a self-developed albatross imitation unmanned aerial vehicle (UAV), three different dihedral angle configurations for the wing’s mid and outer sections are explored: fixed at −50°, fixed at −5°, and varying arbitrarily between −50° and −5°. By solving the optimal loitering dynamic soaring trajectory optimization problem for each configuration, the effect of dihedral angle variation on the dynamic soaring performance of the bio-inspired wings is investigated. The results indicate that under all three configurations, the UAV achieves energy-neutral flight in specific wind field environments. Compared to the fixed dihedral angle of −5°, the UAV demonstrated superior dynamic soaring performance when the dihedral angle was fixed at −50°. When the dihedral angle varied dynamically, the UAV outperformed both fixed configurations across all relevant parameters. Specifically, compared to the fixed dihedral angle of −5°, the total energy increased by 25.43%, and the minimum required wind gradient decreased by 15.56%. Similarly, compared to the fixed dihedral angle of −50°, the total energy increased by 2.52%, and the minimum required wind gradient decreased by 2.07%. These findings suggest that the use of variable dihedral angle technology in bio-inspired UAV wings can significantly enhance dynamic soaring performance and provide theoretical support for the design of morphing wings with superior dynamic soaring capabilities.

Experimental Study on Liquid Jet Trajectory in Cross Flow of Swirling Air at Elevated Pressure Condition

Abstract Motivated by fuel atomization applications in gas turbine combustors, this paper presents an experimental examination of liquid jet trajectory and spray dynamics in crossflow of swirling air, at elevated pressure conditions. The study was conducted within an annular passage and was focused on momentum flux ratio and swirl number as the main parameters. The momentum flux ratio was varied from 2 to 25 through incremental adjustments to the liquid injection velocity and the swirl number values of 0.42 and 0.74 were used, representing typical gas turbine fuel atomization conditions. Jet trajectories were captured by imaging the three-dimensional helical path traced by the liquid jet using two mutually perpendicular optical windows. Radial penetration was quantified by solving the equations of a helix. The key findings revealed that radial penetration of the liquid jet is larger for higher momentum flux ratios and is influenced by the helical arc length. Notably, the radial penetration observed at low momentum flux ratios was larger for crossflow with lower swirl number and the radial penetration observed at high momentum flux ratios was more for crossflows with higher swirl number. In comparison to the spray characteristics in swirling crossflows at atmospheric pressure, condition of elevated gaseous pressure resulted in lower radial penetration, jet spread and jet area. Jet trajectory correlations for elevated pressure conditions are additionally presented, developed using curve fitting to the experimental data, which will be useful to the industry for estimation of spray trajectory in swirling crossflows at high pressure conditions.

Research on Frequency Regulation with Dynamic Trajectory Planning of Participation Factors

The energy transformation has led to a high proportion of new energy entering the grid. New energy has high randomness, which challenges the frequency stability of the power system. A new approach to improve frequency based on dynamic trajectory planning of participation factors is proposed in this work. In the frequency regulation interval, the trajectory and termination time of participation factors are regarded as the variables to be optimized. Then, taking the frequency regulation performance and economy as the goals, a multi-objective optimization problem is constructed. The participation factors are used to dispatch the output power of different units, which breaks the constraint that the output characteristics of different units are consistent in the original regulation process. Therefore, the generator units with different regulation characteristics in the system achieve complementary coordination on the second time scale. In simulation cases, frequency oscillation is reduced, while the overall economy of the system is improved. The numerical evaluation results show that the frequency performance is improved by 2.7% at most and 2.9% of the economy is improved at most simultaneously. The above results demonstrate the effectiveness of the proposed approach.

Unveiling the prognostic journey: renal function trajectories in 'de novo' heart failure with reduced ejection fraction - insights from a cohort study and their impact on patient outcomes

Abstract Background HFrEF poses significant clinical challenges globally. Renal dysfunction frequently coexists with HF, exacerbating prognosis. However, the dynamic trajectory of renal function in 'de novo' HFrEF patients and its prognostic implications remain understudied. Methods We conducted a prospective cohort study involving 370 'de novo' HFrEF patients. Renal function was initially assessed upon admission and re-evaluated at the end of the titration period. The CKD-EPI formula was used for renal function assessment. Patients were followed up for a median of 15 months. Statistical analyses were performed to evaluate predictors of adverse outcomes. Results Baseline renal function significantly influenced outcomes, with eGFR < 45 ml/min associated with higher mortality and heart failure readmissions. Among patients with available renal function data at discharge (n=354), 87 (24.6%) had eGFR < 45 ml/min, while 267 (72.2%) ≥ 45 ml/min. Patients with eGFR < 45 ml/min exhibited older age, higher prevalence of comorbidities, lower haemoglobin levels, and higher creatinine and NT-proBNP levels, both at admission and discharge. Furthermore, they were less likely to receive certain heart failure medications at discharge. During follow-up, 46 deaths (13.0%) and 105 events of combined all-cause death and readmission due to heart failure (29.6%) occurred. Patients with eGFR ≥ 45 ml/min exhibited a lower overall mortality (HR: 0.29, p < 0.001) and all-cause death and heart failure readmissions (HR: 0.32, p < 0.001) both in univariate and multivariate analysis (HR: 0.63, p = 0.028 for mortality; HR: 0.53, p = 0.038 for combined endpoint). See Figure 1. Among patients with available renal function data at follow-up (n=304), 240 (78.9%) had eGFR ≥ 45 ml/min (stabilization or improvement), and 64 (21.1%) had eGFR < 45 ml/min (deterioration or previously < 45 ml/min). Patients with eGFR < 45 ml/min at follow-up exhibited older age, lower BMI, higher prevalence of comorbidities, lower haemoglobin levels, and higher NTproBNP levels at admission and discharge. They were also less likely to receive certain crucial heart failure medications at discharge and follow-up (Table 1). During follow-up, 31 deaths (10.1%) and 87 events of combined death and readmission due to heart failure (38.6%) occurred. In univariate analysis, patients with eGFR ≥ 45 ml/min exhibited a lower overall mortality (HR: 0.27, p < 0.001) and admissions (HR: 0.30, p < 0.001), which remained significant in multivariate analysis (HR: 0.43, p = 0.048 for mortality; HR: 46, p = 0.014 for admissions). See Figure 1. Conclusion Our findings underscore the importance of integrated heart-kidney care in 'de novo' HFrEF patients. Continuous monitoring of renal function and interventions to prevent deterioration are crucial for optimizing outcomes. Further research is needed to validate these findings and explore targeted therapeutic strategies for renal protection in HFrEF.