Browse Articles

Prognostic factors in first-line atezolizumab-bevacizumab treatment of intermediate or advanced hepatocellular carcinoma

Purpose To analyze the prognostic factors influencing outcomes in hepatocellular carcinoma (HCC) patients initially treated with atezolizumab-bevacizumab (Ate-Bev). Methods We conducted a retrospective study on 47 treatment-naïve HCC patients (40 men; median age, 56 years) who were treated with Ate-Bev between September 2020 and July 2022 and underwent at least one response assessment based on the Response Evaluation Criteria in Solid Tumors 1.1. We evaluated the clinical variables and imaging features of pre-treatment magnetic resonance imaging (MRI). Using multivariable Cox hazard regression analysis, we analyzed prognostic factors for progression-free survival (PFS). Results During the follow-up period (range, 1.5–24.9 months), 33 patients (70.2%) experienced tumor progression. The median PFS was 4.3 months (95% confidence interval [CI], 2.8–8.5 months). Nine patients received concomitant radiotherapy. Multivariable analysis indicated that younger age (hazard ratio [HR], 0.95; 95% CI, 0.92–0.99; P  = 0.013), absence of concomitant radiation therapy (HR, 0.22; 95% CI, 0.07–0.69; P  = 0.009), tumor extent ≥10 cm (HR, 2.54; 95% CI, 1.17–5.55; P  = 0.019), and peritumoral arterial-phase hyperenhancement on the MRI (HR, 2.15; 95% CI, 1.00–4.63; P  = 0.049) were factors associated with poor PFS. Conclusions Age, concomitant radiation therapy, tumor extent, and peritumoral arterial-phase hyperenhancement on MRI were associated with PFS in patients with HCC who were initially treated with Ate-Bev.

Multiscale acoustic temporal niche partitioning of pineland birds across a species richness gradient

Abstract Growing evidence suggests birds reduce acoustic competition by minimizing temporal overlap with neighboring species sharing similar vocal characteristics. However, few studies have tested this across ecological contexts at multiple temporal scales. We examined temporal vocalization patterns of five common pine woodland bird species across a species richness gradient in Florida, USA. We predicted that Carolina Wren ( Throthorus ludovicianus) and White-eyed Vireo ( Vireo griseus ) would exhibit temporal avoidance with the acoustically similar, highly abundant and vocal Northern Cardinal ( Cardinalis cardinalis) at fine (1-minute) and coarse (3-hour dawn chorus) temporal scales, with stronger avoidance in species-rich communities. Conversely, we predicted acoustically dissimilar species [Mourning Dove ( Zenaida macroura ) and Pine Warbler ( Setophaga pinus )] would show random temporal associations with Northern Cardinals, unaffected by richness or scale. Consistent with predictions, acoustically similar species exhibited significant temporal avoidance of Cardinals at both scales, while dissimilar species showed no consistent patterning. Contrary to expectations, species richness did not strongly influence temporal avoidance, though fine-scale temporal partitioning trended toward increasing at lower richness. Taken together, these results demonstrate that temporal niche partitioning among acoustically similar bird species operates consistently across multiple temporal scales and is structured more by acoustic similarity and asymmetric species interactions than by species richness.

Scaling dynamics of electrothermal coupling in thermoelectric materials probed by time-domain impedance spectroscopy

The time-dependent resistance R(t) in time-domain impedance spectroscopy (TDIS) is derived from the frequency-dependent impedance Z(ω) using the inverse Laplace transform within a unified electrothermal framework that incorporates the thermoelectric element, electrodes, and lead wires that act as heat-leakage paths. A normalized response function Ψ(tΩ) is introduced to separate transient dynamics from the steady-state amplitude. This function reveals a continuous transition characterized by Ψ(tΩ<1)∝tΩn (where 1/2≤n≤1), reflecting the crossover from diffusion-dominated transport to boundary-dominated behavior. The transient response is determined by a small set of dimensionless parameters that describe both the intrinsic thermoelectric properties and the measurement configuration. Notably, both the normalized time constant τΩ and the effective scaling behavior are governed primarily by the electrode-to-thermoelectric heat-capacity ratio, demonstrating that the electrode heat capacity plays a dominant role in the electrothermal response. Measurements on a thermoelectric element and a module confirm the predicted scaling behavior and power-law response. These results establish TDIS as a probe of electrothermal dynamics and provide practical guidelines for optimizing TDIS measurements through control of electrode heat capacity.

ZNF263–NuRD-mediated repression of STAT1 curtails MHC-I antigen presentation and IFN-γ efficacy in prostate cancer

Loss of major histocompatibility complex (MHC)-I is a hallmark of prostate cancer (PCa) immune evasion and immunotherapy failure. Here, we identify ZNF263 as a transcriptional repressor that silences MHC-I by recruiting nucleosome-remodeling and deacetylase (NuRD) to the STAT1 promoter, reducing STAT1 and MHC-I expression. Hypoxia enhances this repression through two ZNF263 modifications: phosphorylation-driven phase separation that strengthens NuRD interaction and O-GlcNAcylation at S662 that aids STAT1 promoter binding. O-GlcNAcylation also promotes interaction with protein kinase, DNA‑activated catalytic subunit (PRKDC), amplifying phosphorylation. Interferon‑gamma (IFN‑γ)‑induced MHC-I induction is augmented upon ZNF263 loss. In silico docking identified Viroptic as a Krüppel‑associated box (KRAB) pocket binder disrupting ZNF263–NuRD, derepressing STAT1, and potentiating IFN-γ antitumor immunity in vivo. High ZNF263 correlates with low MHC-I, scarce CD8+ T cells, and poor survival, providing rationale for targeting ZNF263 in PCa immunotherapy.

New insights into the Trans-Saharan gold trade in the Islamic Middle Ages revealed by multi-isotopic (Pb–Fe–Cu) and elemental characterization of Fatimid gold coins

The use of West African gold in medieval times is thought to have enabled the first globalized trade in history: the Trans-Saharan Trade, through the minting of Islamic dinars, which were considered as the equivalent of today’s dollar or euro currencies. Yet, the precise origin of this gold remains debated, as archaeological evidence for such trade is scarce. While textual sources are numerous, they provide only indirect accounts, and the large corpus of surviving dinars has so far yielded limited insight as elemental analyses are not discriminating enough to establish geological provenance. To address this, we combined multi-elemental analysis by LA-ICP-MS with multi-isotope (Pb, Cu, and Fe) data measured by MC-ICP-MS after wet purification chemistry on 11 dinars. This revealed two distinct metal stocks, differentiated by PGE concentrations and Cu isotopes. The Cu and Fe isotope signatures are consistent with supergene and oxidized ores, typical of West African gold mineralization. In contrast, the lead isotopes and calculated model ages of the gold coins do not match the signatures expected for West African mineralization, suggesting that a different, exogenous source is involved in the gold chaîne opératoire . These new data then raise two key historical questions: the location of gold processing, whether it occurred North or South of the Sahara, and the hypothetical reuse of older metal stocks.

Placental lipid handling, growth and inflammatory pathways are modified by a maternal Mediterranean diet

Abstract The Mediterranean diet is associated with reduced cardiometabolic risk, yet its physiological effects during pregnancy and its impact on placental metabolism remain incompletely understood. This study aimed to determine whether maternal adherence to a Mediterranean diet during pregnancy influences placental lipid metabolism and signalling pathways involved in nutrient handling, tissue remodelling, and inflammation, and to assess their relationship with pregnancy outcomes. Placental samples and clinical outcome data were analysed from pregnant women participating in an unblinded randomized clinical trial of a Mediterranean diet intervention. Placental fatty acid composition was quantified, and the expression of genes and signalling pathways involved in lipid metabolism, nutrient transport, inflammation, and tissue remodelling was evaluated. Maternal adherence to a Mediterranean diet during pregnancy was associated with significant alterations in placental fatty acid composition, including reduced C18:0 and C24:0 and increased C18:1n9c, C20:3n6, and C22:0, with lower total saturated fatty acids and higher monounsaturated fatty acids. Placental expression of lipid metabolism regulators ALOX15 and PPARγ was reduced, alongside downregulation of AKT and p38 MAPK signalling pathways. Placentas from mothers adhering to the Mediterranean diet also showed lower expression of amino acid and glucose transporters SLC3A2 and SLC2A1 , as well as altered inflammatory and extracellular matrix remodelling markers, including decreased SOCS3 and GHR and increased PAI1 and MMP3. Maternal adherence to a Mediterranean diet during pregnancy modifies placental fatty acid composition and regulates pathways involved in lipid handling, nutrient transport, inflammation, and tissue remodelling, providing insight into mechanisms linking maternal diet with placental metabolic function.

Fundamental understanding of the reliability issues of hafnium oxide-based ferroelectric field-effect transistors: A comprehensive review

Hafnium oxide (HfO2)-based ferroelectrics have significantly transformed the domain of ferroelectric materials and memory technologies, delivering extraordinary advantages in areas, such as scalability, compatibility with CMOS (complementary metal–oxide-semiconductor) technology, and impressive ferroelectric performance at nanometer dimensions. Although ferroelectricity was first discovered in the mineral Rochelle salt in 1920, its application in mainstream memory technologies was largely restricted until the groundbreaking discovery of ferroelectricity in doped HfO2 in 2007. This pivotal finding initiated a remarkable paradigm shift, establishing HfO2 as a vital material for developing the next generation of non-volatile memory solutions and extending its uses beyond traditional applications. Ferroelectric memories derived from HfO2 exhibit significant potential as storage-class memory systems, synaptic devices designed for neuromorphic computing, and highly integrated high-density systems, effectively bridging the performance divide between volatile and non-volatile memory technologies. This Review commences with an in-depth exploration of the fundamental physics and crystallography of ferroelectric HfO2, subsequently delving into the latest innovations in thin-film fabrication techniques, multifaceted device architectures, and emerging real-world applications. Additionally, key challenges regarding reliability are thoroughly scrutinized, alongside a discussion of strategic measures to mitigate these concerns. The Review also highlights innovative opportunities in areas, such as three-dimensional integration, advancements in artificial intelligence hardware, and the pursuit of energy-efficient computing solutions. The remarkable properties and versatility inherent in HfO2-based ferroelectrics firmly establish their significance as a foundational element for the future landscape of memory technology.

A minimal wake–vortex model explains formation flight of flapping birds

Collective patterns of motion emerge across biological taxa: insects swarm, fish school, and birds flock. In particular, many large migratory bird species form distinctly ordered V-shaped formations, which experiments and direct numerical simulations have demonstrated provide substantial energetic benefits during long-distance flight. However, the precise aerodynamic and morphological mechanisms which underlie these benefits remain unclear. In this work, we develop a reduced-order model of the wake–vortex interactions between two flapping birds flying in tandem. The model retains essential unsteady flapping dynamics while remaining computationally tractable. By optimizing over a six-dimensional state space, which comprises the follower’s three-dimensional relative position as well as three independent flapping parameters, we identify the energetically optimal leader–follower configuration of northern bald ibises ( Geronticus eremita ). The predicted optimum agrees quantitatively with live-bird measurements. Because of its simplicity, the model allows for direct interrogation of the physical mechanisms responsible for this optimum. In particular, it isolates precisely how the follower’s wing kinematics interact with the leader’s wake to enhance aerodynamic efficiency. The model predicts an 11% reduction in total mechanical power for a follower in formation flight—consistent with experimental estimates—and shows that this saving arises from reductions in both induced and profile power, dominated by decreased profile power enabled primarily through reduced flapping amplitude and, secondarily, reduced upstroke flexion. These results provide a mechanistic explanation for the structure of V-formations and offer insight into the aerodynamic principles governing collective flight.

Early-warning signals for infectious diseases with a social-media compartment

Early-warning signals (EWSs) are crucial tools for anticipating disease emergence and guiding public-health responses, but uncertainties in transmission and incomplete data can limit their reliability. Additionally, the performance of EWSs is rarely evaluated when disease emergence is delayed, and their use in the context of interactions between disease transmission and communication through social-media platforms has largely not been considered. We evaluate the relative performance of EWSs in predicting disease emergence under varying noise conditions and explore the use of EWSs with social-media dynamics to predict disease emergence. We develop a mechanistic model coupling infectious disease and social-media dynamics, introduce stochasticity and generate simulated time series. We detect changepoints, quantify delays relative to the bifurcation point and assess the performance of EWSs across different segments of the time series. The “reporting” infected compartment proves most reliable, and variance outperforms autocorrelation in high-noise scenarios. However, in the social-media compartment, variance and autocorrelation have weak predictive power. Our work provides a framework to advance understanding of how EWSs can be applied to forecasting disease emergence, contributing to improved disease preparedness and response.

Domain-specific versus general large language models: a review and empirical benchmark in real medical texts

Abstract The rapid adoption of Large Language Models (LLMs) has led to their widespread use as a general-purpose, fast-deployment solution across a broad range of tasks. In healthcare settings, this trend has accelerated the replacement of task-specific models with large generative architectures, often without an assessment of their efficiency or suitability for structured information extraction. While transformer-based encoder models have long been established as reliable solutions for clinical Named Entity Recognition (NER) and Information Extraction (IE), the increasing reliance on LLMs raises concerns regarding computational cost, scalability, energy consumption, and practical deployment in resource- and privacy-constrained environments. This study aimed to critically evaluate the assumption that LLMs constitute a universally superior solution for clinical NER and IE, by systematically comparing encoder-based Language Models (LMs), and LLMs in terms of extraction performance, efficiency, deployment feasibility, and environmental impact. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) guidelines, a scoping literature review was conducted using Scopus and Web of Science, covering peer-reviewed studies published between 2022 and 2025. In addition, a proof-of-concept case study was performed on European Portuguese clinical notes, comparing a domain-adapted encoder model (MediAlbertina-1.5B) with quantized Llama-based LLMs executed locally under identical hardware conditions. Models were evaluated using micro-averaged precision, recall, and F1-score, together with runtime, estimated energy consumption, and CO₂ emissions. The literature review showed that LLMs and transformer-based architectures were the most frequently used even thought encoder-based and domain-adapted models often perform strongly in clinical NER, particularly when recall, structured output, and computational efficiency are important. The empirical case study showed a similar pattern: MediAlbertina-1.5B achieved the highest performance (micro-F1 = 0.430), whereas all evaluated Llama variants obtained markedly lower F1-scores (≤ 0.123) due to systematic under-extraction. Despite their lower performance, the Llama models incurred 23–95 × longer runtimes and one to two orders of magnitude higher estimated energy consumption and CO₂ emissions under the tested local CPU-only setup. In this proof-of-concept benchmark on 20 European Portuguese clinical reports, the domain-adapted MediAlbertina token-classification model achieved higher recall and micro-F1 than the evaluated locally executed, quantized Llama models. The Llama models were also substantially slower and less sustainable, with higher estimated energy use and CO₂ emissions under the tested hardware and prompting configuration. These findings suggest that domain-adapted encoder models may be preferable for similar structured clinical NER settings, although larger and externally validated benchmarks are needed before generalizing to other languages, clinical corpora, model families, or deployment environments.

Ultrafast charge emission at terahertz frequency in high-intensity femtosecond laser ablation process

Initial charge emission processes during femtosecond laser ablation are investigated by monitoring the waveforms of terahertz radiation in real time using echelon-based single-shot terahertz time-domain spectroscopy and by measuring the ablated depth profiles using spectral domain optical coherence tomography. High sensitivity of the single-shot terahertz detection system enabled the acquisition of full pulse-to-pulse terahertz waveforms and revealed the changes in the amplitude and phase of the emitted terahertz waves due to the different fundamental processes of laser ablation at femtosecond and picosecond timescales. At low fluence close to the ablation threshold, a cosinusoidal terahertz wave is observed, indicating that the electrons are emitted from the surface, inducing damages to the material and causing incubation of the ablation process. At medium fluence, the terahertz wave changes to sinusoidal, suggesting that electron emissions are soon screened and are accompanied by material removal. At high fluence, time-delayed high-intensity terahertz radiation is observed as a signature of secondary charge emission. The waveform and the comparison with the ablated depth profiles reveal the importance of acoustic wave generation due to rapid lattice heating, demonstrating the importance of monitoring the initial charge dynamics for understanding the subsequent laser ablation processes.

Light- and temperature-sensitive seizures are regulated by spatially distinct cortex glial populations in the central nervous system

Epilepsy is characterized by recurrent seizures due to abnormal neuronal activity originating from a population of neurons. Seizures are often associated with abnormal glial cell function at the seizure focus. Studies have shown that each glial type, such as astrocytes, displays a significant degree of heterogeneity in their development, molecular signatures, and function depending on the brain region in which they are located. It is unknown, however, if such heterogeneity differentially influences or causes seizures. Previous studies in Drosophila have shown that aberrant Cortex glia (CG) function led to light-inducible (LI) seizures in Ceramide phosphoethanolamine synthase ( cpes ) and temperature-sensitive (TS) seizures in zydeco ( zyd 1 ) mutants. Here, we have optimized Gal4/Split-Gal4/Gal80/LexA drivers to specifically express a gene of interest throughout development in CG subpopulations in different parts of the brain including optic lobe (OL), central brain (CB), and ventral nerve cord (VNC). Using these tools, we performed brain region–specific CG rescue experiments in cpes and zyd 1 mutants. We found that OL- and CB-specific, but not VNC-specific CG expression of CPES significantly suppressed LI seizures in cpes mutants. In contrast, VNC- but not OL- or CB-specific CG expression of ZYD suppressed TS seizures. In a third model, expression and activation of transient receptor potential, dTRPA1, exclusively in the VNC-specific CG was sufficient to induce TS seizures in wild-type flies. Our findings suggest that regionally specialized CG subtypes differentially regulate seizure susceptibility in seizure models.

Extent of therapeutic support in Positive Psychotherapy: A randomized comparative efficacy study for the treatment of anxiety disorders in an online group setting

Objective Positive Psychotherapy (PPT) is increasingly being studied as a potential treatment option for psychological diseases. In recent years the internet has been incorporated into traditional face-to-face therapy which, if successful in its treatment outcome, could lead to a more economic and affordable therapy since a certain proportion of therapy could be done without real-time therapist contact. The aim of this study is to investigate whether significant differences in outcome are found when comparing the effectiveness of PPT with complete therapeutic support (cPPT) in treating anxiety disorders compared to PPT with minimal therapeutic supervision (mPPT) in an online group setting. Participants in the cPPT group took part in ten weekly 120-minute online sessions with a therapist, while the mPPT group only had three 60-minute online sessions. For the remaining seven sessions, participants received videos. This paper presents the outcomes of both groups. Methods This randomized controlled trial involved 106 participants allocated into either a group with complete therapeutic support (cPPT; n  = 53) or a group with minimal supervision (mPPT; n  = 53) for ten weeks. Data collection occurred through online questionnaires, evaluating anxiety levels, subjective happiness, quality of life, and psychological distress. These assessments were conducted at three time points: baseline (T0), post-intervention (T1), and three-month follow-up (T2). Results Significant improvements over time were observed in both the cPPT and mPPT groups across several outcomes. Anxiety symptoms decreased substantially from pre-treatment to post-treatment and remained stable at the three-month follow-up. Significant time effects were found for fear and anxiety-related outcomes, including FQ ( η 2 = 0.10 , η w 2 = 0.32 ), BAI ( η 2 = 0.17 , η w 2 = 0.42 ), PAS ( η 2 = 0.14 , η w 2 = 0.39 ), GAD-7 ( η 2 = 0.16 , η w 2 = 0.36 ), with gains maintained at the three-month follow-up. Positive psychological outcomes also improved significantly over time. Significant effects were observed for subjective well-being and flourishing, including PPTI ( η 2 = 0.04 , η w 2 = 0.15 ), FS ( η 2 = 0.02 , η w 2 = 0.07 ), and SWLS ( η 2 = 0.04 , η w 2 = 0.14 ). Psychological distress likewise decreased significantly across treatment. Significant time effects were found for ISR ( η 2 = 0.11 , η w 2 = 0.29 ), PHQ-9 ( η 2 = 0.06 , η w 2 = 0.17 ), with improvements remaining stable at follow-up. In all cases, there were no significant group × time interactions, indicating that the mPPT and cPPT groups showed comparable changes over time. Conclusion Our study did not find significant differences between Positive Psychotherapy with minimal therapeutic supervision and PPT with complete therapeutic supervision. These findings challenge the traditional notion regarding the significance of face-to-face contact and therapist-patient interaction and suggest an economic and efficient alternative to the regular individual face-to-face therapy. As the participants were predominately female, further research should focus on a more gender-equal sample to generalize these findings.

Brain subcellular proteomics reveals chromosome segregation as a potentially key molecular pathway in Down syndrome

Evolution of the crystal structure, morphology, and magnetic properties of cobalt-based nanoparticles during heat treatment

Carbon-encapsulated cobalt nanoparticles (NPs) were synthesized by thermal decomposition of a solution of organic components and cobalt acetate followed by heat treatment in an argon atmosphere at different temperatures Theat from 400 to 1000 °C. The crystal structure, morphology, magnetic properties, and magnetic circular dichroism (MCD) of NPs formed at each Theat were studied. The decomposition resulted in the formation of Co3O4 NPs in a carbon shell with an average diameter of ∼10 nm. Heat treatment ensured the reduction of Co3O4 first to CoO monoxide and then to metallic cobalt with an increasingly perfect crystalline structure and a higher degree of carbon shell graphitization as Theat increased. The as-synthesized (initial) Co3O4 NPs were paramagnetic in the temperature range used in magnetization measurements. Starting with NPs treated at Theat = 500 °C, a hysteresis loop was observed. The shape of the hysteresis loop was identical for all the samples heat-treated at Theat ≥ 500 °C. The saturation magnetization (Ms) increased significantly with increasing Theat and reached 110 emu/g at Theat = 1000 °C, with a low coercivity Hc (75 Oe). The value of the MCD signal and its spectrum varied significantly with Theat.

Correction for Kuyyamudi et al., Heterotypic intercellular adhesion tunes efficiency of cell-on-cell migration

A mask-based peak-to-average power ratio reduction scheme for affine frequency division multiplexing systems using Volterra Series-Driven PolyNet

Affine frequency division multiplexing (AFDM) demonstrates exceptional resilience to Doppler effects in doubly dispersive channels, making it a promising waveform for 6G high-mobility communications, but its high peak-to-average power ratio (PAPR) problem severely limits system energy efficiency. When migrated to AFDM, existing mask-based deep learning PAPR reduction schemes face the challenges of contextual loss caused by local sampling and the lack of physical interpretability in black-box models. Therefore, this paper proposes a physics-aware mask-based PAPR reduction scheme tailored for AFDM. First, a full-frame input strategy is introduced to exploit the global time-domain correlation of AFDM signals for precisely recovering the impaired symbols. Second, to address the nonlinear distortion induced by masking, a PolyNet-Volterra network is proposed by integrating Volterra series theory. Departing from the traditional design of blindly stacking layers, this model explicitly constructs first-order linear and third-order power feature layers, which substantially enhances the nonlinear reconstruction accuracy while avoiding overfitting. Simulation results demonstrate that, under a threshold of 0.9, the proposed scheme achieves a significant PAPR reduction of approximately 5.9 dB. Furthermore, requiring only about 165,000 parameters, the PolyNet-Volterra model comprehensively outperforms baseline models such as DNN and ResNet in terms of both bit error rate (BER) and mean squared error (MSE). Compared with the conventional PolyNet, the proposed model reduces the parameter and computational overhead, suggesting its potential as a low-complexity receiver-side reconstruction module for resource-constrained future wireless systems. Further hardware-oriented and over-the-air validation is still needed before drawing deployment-level conclusions.

Differential proteome profiling reveals curcuminoid-induced changes in metabolic and physiological pathways in aging dogs

Abstract Curcuminoid effects on aging dog proteomes remain underexplored. Plasma shotgun proteomics revealed that 135-day curcuminoid supplementation significantly altered 2,224 proteins (p < 0.05), with 1,154 differentially expressed (fold-change > 2): 582 upregulated and 572 downregulated versus baseline. Curcuminoids enhanced proteins involved in metabolism, autophagy, and repair while suppressing inflammation, calcium signaling, and coagulation factors. Notably, curcuminoids modulated JAK-STAT signaling by upregulating negative regulators PIAS2 and SOCS2, reducing pro-inflammatory complement and coagulation factors, indicating diminished inflammaging. mTOR pathway modulation featured upregulation of negative regulators including stress-inducible geroprotective SESN2, plus GRB10, SGK1, ULK1, and PRKCA. Curcuminoids rebalanced calcium signaling networks via ITPR1, CALML4, CACNA1H, STIM2, and MYLK4 regulation—essential for muscle function and neuronal health—reducing age-related dysregulation. Proteomic shifts corresponded to improved oxidative stress markers: lower plasma malondialdehyde and restored glutathione redox status. Curcuminoids enhance metabolic flexibility, proteostasis, and immune resilience, emphasizing their geroprotective potential with translational relevance to humans.

Experimental study on the Rayleigh–Taylor instability of metallic interfaces with dual-mode driven by explosion

Planar detonation-driven experiments and numerical simulations were combined to investigate the evolution of Rayleigh–Taylor instability at copper interfaces under single-mode and dual-mode initial perturbations. A planar wave lens was used to drive a high-energy explosive, achieving quasi-isentropic loading on oxygen-free copper (grade TU1) with purity greater than 99.97% through a 3.5 mm gap, with peak pressures ranging from 34 to 37 GPa. Simultaneously, x-ray images of the sample profile with a time resolution of less than 100 ns and free surface Doppler Pins System velocity histories with a sampling interval of 0.5 mm were acquired. Explicit dynamics numerical simulations, employing the Steinberg–Guinan (SG) constitutive model for the experimental samples, were integrated to quantitatively characterize perturbation development. The results indicate that the free surface velocity at the trough of dual-mode perturbations is significantly higher than that of single-mode perturbations, and pressure convergence in the peak region induces multiple jumps in free surface velocity. The growth of perturbation amplitude at the loading surface during dual-mode coupling shows good agreement between numerical simulations and x-ray images, with the SG constitutive model accurately predicting amplitude development with error less than 5%. The thickness of the specimen shows an obvious stabilization effect, and there is a critical value for the thickness. Reducing the initial wavelength and increasing the initial amplitude both accelerate the growth of perturbations on the loading surface. The initial amplitude is the core factor controlling the development of dual-mode perturbations.

He Was Always There

Not every patient is on the chart—this essay is about learning to see the one who was always there.