Browse Articles
Discover research articles across all indexed journals
AutoDyn: robust model predictive control design for trajectory tracking under varying vehicle dynamics
The undulating tripod gait as a model of the locomotion of walking fish
Abstract A large subset of fishes capable of terrestrial walking exhibit strikingly similar gaits despite spanning across the phylogenetic space and having substantial differences in morphology. This recurrent pattern suggests the existence of shared mechanical principles underlying locomotor convergence. To investigate these principles, we analyze a common strategy we term the “undulating tripod gait” , a coordinated pattern of axial body undulation coupled with alternating anterior contact with the ground. In this work, we model the undulating tripod gait by approximating a fish’s axial undulation as three rigid segments rotating with respect to each other and representing the anterior contact as a rigid beam that alternates the contact with the surface on the left and right sides of the body. Here, we focus on the grey bichir, Polypterus senegalus , as a specific exemplar of the undulating tripod gait. We perform high-speed kinematic analyses of terrestrial locomotion to identify baseline gait parameters, which we then validate as broadly representative by comparing them to those of other distantly related walking fishes. Using these parameters, we simulate the model to explore how variations in morphology and joint kinematics influence forward progression, revealing that peak locomotor performance emerges under conditions closely matching those observed in P. senegalus . Finally, we translate the model into a physical robot, demonstrating that the same simple coordination of axial undulation and anterior contact produces effective forward locomotion in the real world. By capturing core mechanical features shared across morphologically diverse species, this framework advances our understanding of terrestrial walking in fishes and offers a mechanistic lens through which to examine the evolutionary origins of locomotion in early vertebrates.
The cost of caring: Gendered health and labor market effects of grandparenthood
While the effects of the transition to parenthood are well researched, less is known about how the transition to grandparenthood affects health and labor market outcomes. Using comprehensive Norwegian register data covering the entire population born between 1950 and 1960, we examine the effects of first-born grandchildren born during 2007–2018. Employing event-study models with person-year records, we compare grandparents to not-yet grandparents. Our findings reveal a sharp increase in the likelihood of respiratory infections during the first two years of grandparenthood, with infections increasing by 56% for women and 31% for men. Additionally, grandparenthood modestly reduces the likelihood of doctor’s visits related to mental disorders (4.5%) and cardiovascular health (3.3%). Grandmothers also see a decline in musculoskeletal-related visits (3.8%). These health-related changes coincide with notable gendered effects on labor market participation. Ten years after the birth of their first grandchild, employed women are 12% less likely to hold full-time positions compared to a 2% reduction for men. Overall, our findings demonstrate that the transition to grandparenthood significantly reshapes health and economic outcomes for both women and men. The larger effects observed for women likely reflect their greater involvement in informal childcare provision. Our results underscore the intersection of health, family dynamics, and gendered labor market behaviors in late adulthood.
Imaging the impact of rotifer consumption on bacterial behaviors in the zebrafish gut
The gut microbiota influence many aspects of their host’s health and physiology including the digestion of food, and food intake in turn influences the composition of the gut microbiome. However, the ways in which food can alter the behavior of intestinal bacteria remain largely unknown, due in large part to the difficulty of assessing behavior in situ . Larval zebrafish provide a model for addressing this gap because of their optical transparency and their ability to be prepared germ-free and then associated with specific microbial species. Using light sheet fluorescence microscopy to visualize bacteria inside the intestines of live zebrafish larvae, we examine the properties of two commensal strains with markedly different physical characteristics. One is a zebrafish-commensal Enterobacter species that forms large aggregates in unfed larvae, and the other is a pathobiont Vibrio species, capable of damaging intestinal tissue, that is motile and planktonic. We use recently developed ultraviolet irradiation methods to dramatically lower the microbial content in rotifers, a common live food for larval fish, thereby enabling the assessment of feeding effects independent of the introduction of new microbes. Following host consumption of rotifers, Enterobacter clusters disintegrate into motile individuals. Vibrio remains planktonic in fed larvae but decreases the activity of its Type VI Secretion System, as revealed by a fluorescent fusion protein comprising one of the secretion apparatus proteins and green fluorescent protein, leading to a strong decrease in damage to host tissue. Our results reveal that feeding can have major impacts on bacterial behavior that should be considered in models of normal gut microbiome dynamics as well as pathogenesis.
Arlocabtagene autoleucel-a GPRC5D-targeted CAR T-cell therapy in heavily pretreated relapsed/refractory multiple myeloma
Patients with relapsed/refractory multiple myeloma (RRMM) have limited treatment options. Arlocabtagene autoleucel (arlo-cel, BMS-986393) is an autologous chimeric antigen receptor (CAR) T-cell therapy targeting G protein-coupled receptor class C group 5 member D (GPRC5D). This phase 1, dose-escalation/expansion study (NCT04674813) enrolled adult patients with RRMM and ≥3 prior antimyeloma treatment regimens, including an immunomodulatory drug (IMiD), a proteasome inhibitor, and an anti-CD38 antibody. At baseline, patients (N=84) had a median of 5 prior regimens and 49% had previously received BCMA-targeted therapy, of whom 38% received CAR T-cell therapy. Arlo-cel was administered as a one-time intravenous infusion of 25×106-450×106 CAR T cells. Primary endpoints were safety and maximum tolerated dose (MTD); secondary endpoints included overall response rate (ORR), progression-free survival (PFS), and overall survival (OS). Data cutoff was 23August2024. Cytokine release syndrome (CRS) occurred in 82% of patients, immune effector cell-associated neurotoxicity syndrome in 10%, and other select neurotoxicities in 12%; most were grade 1/2 and frequency appeared dose-dependent. One death occurred from CRS at highest dose level. On-target/off-tumor skin (30%), nail (19%), and oral (32%) adverse events were transient, grade 1/2; most resolved without intervention. MTD was not reached. With median follow-up of 16.1 months, ORR=87% (complete response rate=53%), median duration of response=18.0 months, and median PFS=18.3 months (95% CI, 11.8-21.9) (n=79). The 1-year OS rate was 90% (N=84). In conclusion, arlo-cel had a safety profile supportive of future study and demonstrated deep and durable responses, with promising PFS and OS in patients with heavily pretreated RRMM.
Ductile binary FCC materials screened by anisotropic and isotropic elastic criteria: first principle insights into deformation mechanisms
Author Correction: Community benchmarking and evaluation of human unannotated microprotein detection by mass spectrometry based proteomics
Fractionally quantized recurrence detection times in monitored quantum many-body systems
Recurrence time quantifies the duration required for a physical system to return to its initial state, playing a pivotal role in understanding the predictability of complex systems. In quantum systems with subspace measurements, recurrence times are governed by Anandan–Aharonov phases, yielding fractionally quantized recurrence times. However, the fractional quantization phenomenon in interacting quantum systems remains unexplored. Here, we address this gap by establishing universal lower and upper bounds for recurrence times in interacting many-body spin systems. Notably, we investigate scenarios where these bounds are approached, shedding light on the speed of quantum processes under monitoring. In specific cases, our findings reveal that the complex many-body system can be effectively mapped onto a dynamical system with a single quasi-particle, leading to integer-quantized recurrence times. Our work demonstrates a valuable link between recurrence times and the number of dark states in the system, thus providing a deeper understanding of the intricate interplay between Hilbert-space fragmentation, ergodicity breaking, measurements, and interaction effects. Finally, our findings have been implemented on an IBM quantum computer, revealing resonances and fractional quantization in agreement with theoretical predictions. This demonstrates the resilience of nonequilibrium topological fractional quantization to noise and highlights its potential use for benchmarking quantum devices and probing dark states.
On the crossroads of interdisciplinary medicine in amyloidosis – study protocol for a single-center interdisciplinary registry study
Background Systemic amyloidosis comprises a heterogeneous group of rare diseases characterised by extracellular deposition of misfolded protein fibrils, leading to progressive organ dysfunction. Due to the variability in clinical presentation and course, collection of system-specific and longitudinal data is essential for understanding disease progression, treatment response and patient outcomes. At the Amyloidosis Center Charité Berlin (ACCB), a prospective amyloidosis registry has been established to systematically collect clinical, laboratory, imaging and patient-reported data with the aim of improving the characterization of the diseases and facilitating translational research. Methods This is a single-center prospective registry study that enrols patients diagnosed with systemic amyloidosis. The registry includes demographic data, multidisciplinary clinical phenotyping, biomarkers, biobanking, genetic information, imaging studies, and patient reported outcomes. Here, we describe the standardised protocol for diagnostic workup, baseline and longitudinal data collection, and disease-specific follow-up algorithms. Data will be collected digitally in interoperable data formats to ensure shareability in accordance with GDPR-policies. Discussion This registry will serve as a resource for characterizing amyloidosis as a rare disease model in a real-world setting and identifying patterns in disease progression and treatment efficacy. By prospectively collecting high-quality longitudinal data, the study aims to generate insights that can inform clinical decision-making, improve risk stratification and support future intervention studies. In addition, the registry enables collaboration in the discovery of biomarkers and new therapeutic approaches. Ongoing analysis of this cohort will provide a basis for the further development of personalised treatment strategies and the improvement of patient care. Ethics and dissemination Ethical approval was given by the local ethic committee. Dissemination of data in publications with different scientific observational and correlational questions is planned. Clinical trial registration : DRKS00032002
Ziftomenib with venetoclax and azacitidine in relapsed/refractory NPM1-mutated acute myeloid leukemia
Ziftomenib - a potent, selective, oral menin inhibitor - is approved as monotherapy for adults with relapsed/refractory (R/R) NPM1-mutated acute myeloid leukemia (NPM1-m AML). The KOMET-007 phase 1 trial investigated clinical activity and tolerability of ziftomenib in combination with standard therapies for R/R and newly diagnosed AML. Here, we report outcomes of adults with R/R NPM1-m AML treated with ziftomenib plus venetoclax/azacitidine. In phase 1a, patients received ziftomenib 200, 400, or 600 mg once daily with standard doses of venetoclax/azacitidine. In phase 1b, ziftomenib 600 mg was selected for expansion. Sixty-seven patients were treated (27 phase 1a; 40 phase 1b). Median age was 66 years, and 55% were men. Median number of prior therapies was 1 (range 1-8); 55% received prior venetoclax and 22% had prior transplantation. Most common (≥20%) grade ≥3 treatment-emergent adverse events were leukopenia (34%), thrombocytopenia (28%), febrile neutropenia and neutropenia (25% each). Six patients developed QTc prolongation (1 ziftomenib-related; grade 1), and 2 experienced differentiation syndrome (grade 3); all events were successfully managed. In patients receiving ziftomenib 600 mg, composite complete remission (CRc) rate was 46% (22/48), with 67% (12/18) achieving central measurable residual disease (MRD) negativity (<0.01% threshold). In venetoclax-naïve and -exposed patients, CRc rates were 70% (16/23) and 24% (6/25), with MRD-negativity rates of 75% (9/12) and 50% (3/6), respectively. Median duration of response was 8.6 months, and median overall survival was not reached. The combination of ziftomenib 600 mg with venetoclax/azacitidine was well tolerated with deep and durable clinical activity in R/R NPM1-m AML. This trial was registered at www.ClinicalTrials.gov as #NCT05735184.
CBAM meets DropBlock: enhancing robot steering-angle prediction with hybrid attention and structured dropout
Symbiotic bacteria produce non-lytic vesicles with nucleic acid cargo
Boson peak in covalent network glasses: Isostaticity and marginal stability
The excess vibrational states relative to the Debye model of solids, referred to as the boson peak (BP), are a key feature of glasses and amorphous materials. These excess states underlie anomalous thermal properties such as excess specific heat and low thermal conductivity, as well as mechanical characteristics such as nonaffine elasticity and brittle plasticity. Despite its importance, understanding of the BP remains limited in covalent network glasses. The most promising concepts are isostaticity and marginal stability, which have been established in theories of rigidity percolation and the jamming transition. While these concepts, supported by extensive data, account for the BP in packing-based glasses, comparable explanations have not yet been demonstrated for covalent network glasses. Here we study silica glass, a prototypical covalent network glass, using molecular dynamics simulations. We show that the BP in silica glass is governed by near-isostatic constraints and marginal stability, supporting the universality of these concepts across diverse glassy systems. Furthermore, we reveal that these principles manifest as a wavenumber-independent band in the dynamical structure factor, and we demonstrate agreement with inelastic X-ray scattering data. Our results provide an experimentally testable framework for deciphering the BP and for refining the interpretation of scattering data in amorphous materials.
Retraction: Prediction of thermal distribution and fluid flow in the domain with multi-solid structures using Cubic-Interpolated Pseudo-Particle model
Missing-data–aware machine learning prediction of in-hospital major adverse cardiovascular events after primary percutaneous coronary intervention for ST-segment elevation myocardial infarction
Probing contact electrification processes from interfacial charge transfer to bulk transport in semicrystalline polymers
Traveling waves in a continuum model of schooling swimmers
The complex formations exhibited by schooling fish have long been the object of fascination for biologists and physicists. However, the physical and sensory mechanisms leading to organized collective behavior remain elusive. On the physical side in particular, it is unknown how the flows generated by individual fish influence the collective patterns that emerge in large schools. To address this question, we here present a continuum theory for a school of swimmers in an inline formation. The swimmers are modeled as flapping wings that interact through temporally nonlocal hydrodynamic forces, as arise when one swimmer moves through the lingering vortex wakes shed by the others, leading to a system of time-delay-differential equations. Through coarse-graining, we derive a system of partial differential equations for the evolution of swimmer density and collective vorticity-induced hydrodynamic force. Linear stability analysis of the governing equations shows that there is a range of swimmer densities for which the uniform (constant-density) state is unstable to perturbations. Numerical simulations in periodic domains reveal families of stable traveling wave solutions, where a uniform school destabilizes into a collection of densely populated “subschools” separated by relatively sparse regions that move as a propagating wave. We find that distinct propagating waves may be stable for the same set of kinematic parameters. We also find that finite schools can evolve into packets of coarsening traveling waves whose overall spreading is described by a rarefaction fan moving upstream and a terminating downstream shock. Generally, our results show that temporally nonlocal hydrodynamic interactions can lead to rich collective behavior in schools of swimmers.
An AI-driven fire risk forecasting framework for urban villages using IGWO-optimized LSTM with incremental learning
Artificial intelligence (AI) is reshaping decision-support systems across multiple domains, including risk management and urban safety. Urban villages, characterized by high population density and informal infrastructure, are particularly vulnerable to fire hazards. This study presents an AI-driven fire risk forecasting framework based on an Improved Grey Wolf Optimizer (IGWO) and a Long Short-Term Memory (LSTM) neural network, further enhanced by an incremental learning strategy. IGWO improves hyperparameter convergence and avoids local optima, while the incremental component allows real-time model updates without full retraining. Using real fire incident data from 55 urban villages in Beijing, the proposed IGWO-LSTM-IL model achieves a 92.57% reduction in mean squared error compared to baseline LSTM. The model demonstrates high predictive accuracy, stability, and adaptability, making it a practical tool for intelligent fire risk monitoring and urban safety systems within the scope of AI-transforming urban infrastructure.