Long-term Memory Research Articles

Carotid-femoral pulse wave velocity score, an estimator of cognitive performance in the elderly: results from the Toledo Study for Healthy Aging.

Ageing-related changes in the vascular wall influence the function of different organs; for this reason, we assessed how arterial stiffness measured by carotid-femoral pulse wave velocity (cf-PWV) modulates: the basal cognitive performance and the change in cognitive performance over the follow-up time. We developed a prospective, population-based cohort study with 1581 participants aged > 65years were obtained from the Toledo Study for Healthy Aging. Participants from the second wave (2011-2013) were selected for the cross-sectional analysis. Those who also performed the cognitive assessment in the third wave (2015-2017) were selected for the prospective analysis. Arterial stiffness was evaluated by cf-PWV. Multivariate segmented regression models were used to evaluate the association between cf-PWV scores and basal neuropsychological evaluation scores and change of neuropsychological evaluation scores along follow-up. Cross-sectional analysis showed that as cf-PWV grew within the cf-PWV (5- < 10) category an improvement was observed in 7-min test, free short-term memory, and hole peg test. Furthermore, in the cf-PWV (> 13-18) category a decrease was observed in total short-term memory, free long-term memory, and total long-term memory. Prospective analysis showed a progressive worsening of cognitive function as cf-PWV increases within the cf-PWV (> 13-18) category in 7-min test, object denomination, immediate and short-term memory, and hole peg test, while in the cf-PWV (5- < 10) category, there was observed a decrease in Cumulative Executive Dysfunction Index score and short-term memory. In conclusion, a higher cf-PWV score is associated with worse cognitive performance, and with a worse evolution, reinforcing the need to plan interventions to delay arterial stiffness and its consequences.

Temporal differential effects of post-injury alcohol consumption in a mouse model of blast-induced traumatic brain injury

Traumatic brain injury is a prevalent condition that affects millions worldwide with no clear understanding or effective therapeutic management available. Military soldiers have a high risk of exposure to blast-induced traumatic brain injury (bTBI). Furthermore, alcohol drinking is common in this population, and studies have shown that post-TBI alcohol exposure can result in memory loss. Hence, it is possible that alcohol could contribute to the overall pathological outcome of brain trauma. However, such a possibility has not been explored in detail. Here, we combined a mild bTBI (mbTBI) model with the drinking-in-the-dark (DID) paradigm to investigate the pathological synergy between mbTBI and alcohol consumption by examining brain oxidative stress levels and behavioral alterations in mice. The results revealed the anxiolytic and short-term memory improvement effects of post-trauma alcohol drinking examined at an early timepoint post mbTBI. However, extended alcohol drinking for up to three weeks post mbTBI impaired long-term memory and was accompanied by intensified oxidative stress in brain regions associated with memory and anxiety. These findings, as well as those from previous in vitro TBI/alcohol studies, suggest a pathological synergy of physical force and post-impact alcohol exposure. This knowledge could potentially aid in establishing guidelines for TBI victims to avoid further injury to their brains as well as to help maximize their recovery following TBI.

Lifestyle, Environment, and Dietary Measures Impacting Cognitive Impairment: The Evidence Base for Cognitive Subtypes

: Cognition includes all phases of valid functions and processes, e.g., sensitivity, judgment, assessment, and decision-making. Thinking is also a cognitive procedure since it involves considering potential opportunities. There are various types of cognition. Hot cognition involves mental procedures where emotion plays a role, while cold cognition includes mental processes that do not include feelings or emotions. Cognitive memories of various types include sensor memory, sensing touch, smell, and sight; short-term memory allows one to recall, e.g., what one had for lunch a few days ago; working memory includes remembering telephone numbers or directions to a destination; and long-term memory comprises of major milestones in life and recalling one’s childhood events. These are further classified as episodic, e.g., the first day in primary school, and semantic memories, such as recalling the capital city of a country and filling out crossword puzzles. Declarative memories include remembering significant past events, such as global information. Cognition is affected by factors, such as nutrition, aging, addiction, environment, mental health, physical activity, smoking, and keeping the brain active. Consumption of plant- based foods plays a prominent role in the prevention of cognitive memory. Playing games and instruments, reading books, and being socially active make life more satisfying, thus assisting in the preservation of mental function and slowing mental decline.

Unified and evolved approach based on neural network and deep learning methods for intrusion detection

Currently, network security has become a major concern for all entities around the world. Attackers employ various methods to disrupt services, which requires new methods to stop them all in one way. Moreover, these intrusions can evolve and overcome security measures and devices, which pushes to use new evolving methods able to accompany the evolution of these threats, to block them. In our paper, we propose a new approach for intrusion detection, founded on neural network (NN) and deep learning (DL) methods. This approach is planned to not only identify threats, but also to develop a long-term memory of them, in order to detect new ones resembling these memorized attacks, and simultaneously, to provide a single way to stop all kinds of intrusions. To test our model, we have chosen the most recently employed methods in literature, NN and DL algorithms: feedforward neural network (FNN), convolutional neural network (CNN), and long short-term memory (LSTM), then we have applied them on network security layer-knowledge discovery in databases (NSL KDD) intrusions dataset. The results of experiments were impressive for all the algorithms, with maximum performances noted by LSTM, which affirms the efficacy of our proposed method for intrusion detection.

ЗАСТОСУВАННЯ ТЕХНОЛОГІЇ ВІТАГЕННОЇ ОСВІТИ У ФОРМУВАННІ ГРОМАДЯНСЬКОЇ КОМПЕТЕНТНОСТІ СТУДЕНТІВ

The article is devoted to the justification of the feasibility of using the technology of vitamin education in the formation of civic competence of students. The principles of scientificity (scientific justification, the formation of a holistic image of a student as a citizen, his civic competence as a multifaceted phenomenon, the result of personal and professional development), cultural relevance (the unity of the formation of students’ civic competence with the history and culture of the people, its language, national traditions and customs) are taken into account; personal activity (interests of students, their involvement in solving problem situations, stimulation of various forms of educational activity) in the formation of civic competence of students.The author considers the basis of the concept of «civic competence» to be the experience of applying civic knowledge and skills, the experience of participating in the realization of one’s civic rights and duties. Life experience is interpreted as vital information from long-term memory reserves, which is the basis of self-actualization in certain situations.The stages of the transition from vitamin information to vitamin experience are distinguished: primary indivisible perception of vitamin information;clarification of the significance of the received information, its evaluation filtering; creating an installation to remember information for the conditional term «retention», which depends on its significance and practical orientation”.Emphasis is placed on the appropriateness of using the following methods of vitamin education technology for the formation of students’ civic competence: retrospective analysis of the life experience of civic activity and the disclosure of its connections in the educational process; actualization of students’ life experience (finding out the scope of students’ knowledge at the level of everyday civic consciousness before they acquire scientific knowledge; additional construction of an incomplete model of civic education (it is especially reliable if it is necessary to focus on the creative potential of students, needs for self-realization; temporal, spatial, substantive synchronization of educational projects (the theoretical material also reveals the essence of phenomena and connections in time and space between what is happening in society; creative modeling of the ideal of civic objects based on extensive experience and new information.Attention is drawn to the implementation of transformations in the context of the technology of vitamin education in the process of forming the civic competence of students for interesting cognitive activities that contribute to the development of their critical thinking. Key words: civic competence, students, technology of vitamin education, formation of civic competence, principles of formation of civic competence, techniques of vitamin education.

The information exchange between working memory and long-term memory

The information exchange between working memory and long-term memory

Inflammasome-Activating Nanovaccine for Cancer Immunotherapy.

A range of advanced nanovaccines (NV) combined with immunotherapies has recently emerged for treating malignant tumors and has demonstrated promising tumor-suppressive effects. Nevertheless, their effectiveness is often limited by immunosuppression within the tumor microenvironment. To overcome this challenge, new approaches for NV development are required to improve antigen cross-presentation and to remodel the tumor microenvironment. In this issue of Cancer Research, Zhou and colleagues have developed a photo-enhanceable inflammasome-activating nanovaccine (PIN) designed for precise, in situ delivery of a tumor antigen and a hydrophobic small molecule that activates the NLRP3 inflammasome pathway. Near infrared light exposure enables the accumulation of PINs at tumor sites by inducing a photo-triggered charge reversal in the BODIPY-modified PAMAM nanocarrier. Systemic administration of PINs resulted in effective intratumoral activation of the NLRP3 inflammasome and antigen cross-presentation in antigen-presenting cells upon light exposure, leading to enhanced immune responses through increased proinflammatory cytokine production without significant systemic toxicity. Importantly, PINs also enhanced the efficacy of immune checkpoint blockade and promoted the development of long-term immune memory in mouse models of melanoma and hepatocellular carcinoma. Overall, inflammasome-activating NVs represent a cancer immunotherapy strategy by harnessing the innate immune system to achieve robust responses against tumors. Ongoing research and development are crucial to addressing current limitations and advancing this innovative technology toward clinical application. See related article by Zhou et al., p. 3834.

Gender-modulated influence of BDNF concentration and Val66Met polymorphism on cognitive outcomes in chronic limb ischemia patients

IntroductionWhile numerous studies have established associations between brain-derived neurotrophic factor (BDNF) and cognitive functioning, limited research has delved into the role of BDNF concerning cognitive outcomes in atherosclerosis-related conditions. This study aimed to investigate the correlations between cognitive performance, serum BDNF levels, and the BDNF Val66Met polymorphism in individuals diagnosed with chronic limb ischemia (CLI).Participants and procedureThe study encompassed 159 CLI patients (52 females, 107 males) aged 59-73 years. Genetic analysis involved assessing the BDNF Val66Met single-nucleotide polymorphism using a TaqMan SNP Genotyping Assay and the ViiA™ 7 Real-Time PCR System. Serum BDNF levels were quantified. Cognitive functioning was evaluated through a computerized battery of tests, including the simple reaction test (SRT) for speed and accuracy assessment, verbal memory test (VMT) for short and long-term memory evaluation, and the GoNoGo test for cognitive control and inhibition.ResultsGender differences in cognitive performance were observed, with women excelling in VMT, while men demonstrated superior performance in SRT and the GoNoGo test. No statistically significant differences were noted between the Met/Met or Met/Val and Val/Val subgroups. However, notable differences emerged in female Met carriers, exhibiting superior VMT scores but more incorrect Go responses in the GoNoGo test. Conversely, female Val homozygotes showed significantly more incorrect NoGo responses compared to male Val homozygotes. In men carrying the Met allele, higher BDNF concentrations correlated with improved GoNoGo test results (r = 0.248, p = 0.01). Conversely, in women with the Val/Val variant, lower BDNF concentrations were associated with better VMT scores.ConclusionsThis study underscores the sex-specific impact of BDNF serum levels and the BDNF polymorphism on cognitive processes among CLI patients. The findings highlight the nuanced influence of BDNF in shaping cognitive functioning, emphasizing the need for further research into these sex-dependent associations.

Exploring the Cognitive Processes of Preparation for a Spelling Bee Game to Enhance Vocabulary Learning in a Foreign Language

This study investigates the cognitive processes associated with preparation for a spelling bee game to enhance vocabulary learning in a foreign language. It draws upon the Information Processing Theory, which involves attention, perception, and memory processes. During their freshman year of college in the Department of English, a group of 30 Saudi learners, at the same level of English, ranging in age from 18 to 20 years old, were provided with a weekly set of words to memorize as part of their Reading Course. Following twelve weeks of practice, memorization, and oral performance, a spelling bee was organized for the ten students who achieved the highest scores in the spelling tests. Subsequently, individual interviews were conducted with each of the ten participants in order to understand the cognitive mechanisms underlying their preparation and memorization for the event. The study's findings reveal that most participants in the spelling bee game actively engage in key stages of information processing, including encoding, storing, and retrieving information. Additionally, learners were observed to evolve from merely acquiring factual vocabulary knowledge to applying it practically through repeated practice and memorization for the spelling bee. By engaging multiple senses—such as visual and auditory perception—alongside verbal memory, most participants develop the procedural knowledge needed to spell words accurately and effortlessly, effectively transferring words from short-term to long-term memory.

Single Well Production Prediction Model of Gas Reservoir Based on CNN-BILSTM-AM

In the prediction of single-well production in gas reservoirs, the traditional empirical formula of gas reservoirs generally shows poor accuracy. In the process of machine learning training and prediction, the problems of small data volume and dirty data are often encountered. In order to overcome the above problems, a single-well production prediction model of gas reservoirs based on CNN-BILSTM-AM is proposed. The model is built by long-term and short-term memory neural networks, convolutional neural networks and attention modules. The input of the model includes the production of the previous period and its influencing factors. At the same time, the fitting production and error value of the traditional gas reservoir empirical formula are introduced to predict the future production data. The loss function is used to evaluate the deviation between the predicted data and the real data, and the Bayesian hyperparameter optimization algorithm is used to optimize the model structure and comprehensively improve the generalization ability of the model. Three single wells in the Daniudi D28 well area were selected as the database, and the CNN-BILSTM-AM model was used to predict the single-well production. The results show that compared with the prediction results of the convolutional neural network (CNN) model, long short-term memory neural network (LSTM) model and bidirectional long short-term memory neural network (BILSTM) model, the error of the CNN-BILSTM-AM model on the test set of three experimental wells is reduced by 6.2425%, 4.9522% and 3.0750% on average. It shows that on the basis of coupling the empirical formula of traditional gas reservoirs, the CNN-BILSTM-AM model meets the high-precision requirements for the single-well production prediction of gas reservoirs, which is of great significance to guide the efficient development of oil fields and ensure the safety of China’s energy strategy.

A combinatorial neural code for long-term motor memory.

Motor skill repertoire can be stably retained over long periods, but the neural mechanism that underlies stable memory storage remains poorly understood1-8. Moreover, it is unknown how existing motor memories are maintained as new motor skills are continuously acquired. Here we tracked neural representation of learned actions throughout a significant portion of the lifespan of a mouse and show that learned actions are stably retained in combination with context, which protects existing memories from erasure during new motor learning. We established a continual learning paradigm in which mice learned to perform directional licking in different task contexts while we tracked motor cortex activity for up to six months using two-photon imaging. Within the same task context, activity driving directional licking was stable over time with little representational drift. When learning new task contexts, new preparatory activity emerged to drive the same licking actions. Learning created parallel new motor memories instead of modifying existing representations. Re-learning to make the same actions in the previous task context re-activated the previous preparatory activity, even months later. Continual learning of new task contexts kept creating new preparatory activity patterns. Context-specific memories, as we observed in the motor system, may provide a solution for stable memory storage throughout continual learning.

Engineered Biomimetic Cancer Cell Membrane Nanosystems Trigger Gas-Immunometabolic Therapy for Spinal-Metastasized Tumors.

Despite great progress in enhancing tumor immunogenicity, conventional gas therapy cannot effectively reverse the tumor immunosuppressive microenvironment (TIME), limiting immunotherapy. The development of therapeutic gases that are tumor microenvironment responsive and efficiently reverse the TIME for precisely targeted tumor gas-immunometabolic therapy remains a great challenge. In this study, a novel cancer cell membrane-encapsulated pH-responsive nitric oxide (NO)-releasing biomimetic nanosystem (MP@AL) is prepared. Lactate oxidase (Lox) in MP@AL consumed oxygen to promote the decomposition of lactate, a metabolic by-product of tumor glycolysis, and the generation of H2O2, while L-arginine (L-Arg) in MP@AL is oxidized by H2O2 to generate nitric oxide (NO). For one thing, NO led to mitochondrial dysfunction in tumor cells to reduce oxygen consumption and promote the efficiency of Lox in lactate decomposition, thus reversing lactate-induced TIME; for another, NO effectively triggered immunogenic cell death, activated anti-tumor immune response and long-term immune memory, and ensured a favorable effect in the synergistic interaction with PD-L1 antibody for inhibiting tumor growth and recurrence. Therefore, a novel gas-immunometabolic therapy dual closed-loop nanosystem for enhancing tumor immunogenicity and remodeling lactate-induced TIME is established. Overall, this work will provide new ideas for gas therapy to effectively remodel the TIME to enhance cancer immunotherapy.

A VOx-based optoelectronic memristor for application in visual perception

Abstract While biological vision systems excel at in-memory processing with low power consumption, traditional silicon-based vision chips struggle with high energy demands. This gap motivates the exploration of alternative materials for artificial intelligence applications. This paper presents a VOx-based optoelectronic synaptic memristive device. The proposed artificial synaptic device ITO/VO x /Pt mimics biological functions such as potentiation (P), depression (D), long-term memory, short-term memory (STM), and paired-pulse facilitation (PPF). The PPF index, standing at 105%, suggests a favorable pattern in STM function. The device served as synapses within a spiking neural network showing an achievable pattern classification accuracy of 88.68%, highlighting the potential of the VO x synaptic device for pattern classification tasks. The suggested VO x -based synaptic devices could represent an efficient pattern recognition and visual perception application.

Long-Run Volatility Memory Dynamics and Inter-Market Linkages in GCC Equity Markets: Application of DCC-FIGARCH Models

Abstract The study investigates volatility persistence, long-term memory and time-varying conditional correlations among the stock markets of the Gulf Cooperation Council (GCC) countries. Daily equity index data between 2012 and 2024 were analyzed using univariate fractionally integrated generalized autoregressive conditional heteroskedasticity (FIGARCH) models to examine long-memory behavior and multivariate dynamic conditional correlation (DCC) models to assess conditional correlations between these markets. For each of the GCC equity markets, the analysis highlighted large degrees of long-memory and volatility persistence. Finally, the DCC model shows that strong and dynamic Intermarket links among the GCC, especially between KSA and UAE, exist and reflect significant volatility spillover from good economic ties. This study fills the gap in the literature by providing a comprehensive understanding of long-run volatility memory and inter-market associations in the GCC stock markets.

IMMU-45. MYELOID-ASSOCIATED WILD-TYPE IDH1 PROMOTES IMMUNOSUPPRESSION IN GLIOBLASTOMA

Abstract Tumor-associated myeloid cells (TAMCs) promote immunosuppression in the GBM tumor microenvironment (TME) and resistance to immune checkpoint therapy (ICT). However, the metabolic and epigenetic mechanisms underlying TAMC activation and the therapeutic potential of fine-tuning TAMC activation remain largely unexplored. Our analyses of GBM patient single-cell RNA sequencing (scRNA-Seq) datasets demonstrated that in addition to tumor cells, wild-type isocitrate dehydrogenase (wt-IDH1) is also highly expressed in TAMCs. Using a murine model with myeloid cell-specific deletion of wt-IDH1 (LysM-cre-ERT2; wt-IDH1L/L), we demonstrated that the loss of wt-IDH1 promoted inflammatory myeloid phenotypes, increased CD8+ T cells in the TME, improved survival of GBM tumor-bearing mice, and enhanced anti-tumor effects of PD1 checkpoint blockade. Further, the pharmacological inhibition of wt-IDH1 using systemic administration of a first-in-class wt-IDH1-specific, brain-penetrant small molecule inhibitor or intrathecal delivery of siRNA targeted to wt-IDH1 mirrored the functional phenotype of wt-IDH1-deleted myeloid cells, overcame ICT resistance, and promoted long-term survival and anti-tumor immune memory. Mechanistically, in myeloid cells, the genetic or pharmacological inactivation of wt-IDH1 inhibited oxidative phosphorylation, reduced myeloid cell proliferation, increased their tumoricidal activity, and altered chromatin accessibility of key transcription factors implicated in the regulation of myeloid cell states, including AP-1, IRFs, STAT1/2, NFATs, and CEPBPs. These studies define wt-IDH1 as a metabolic checkpoint of myeloid cell activation and credential the inhibition of wt-IDH1 as a novel immunotherapeutic strategy to increase ICT efficacy for patients with GBM.

EXTH-40. IMMUNOPHENOTYPING OF RWTC-MBTA AUTOLOGOUS CANCER VACCINE IN PRECLINICAL GLIOBLASTOMA MODELS

Abstract Despite advances in immunotherapy, glioblastoma multiforme (GBM) remains challenging to treat due to its low inherent immunogenicity and a suppressive tumor microenvironment. Converting “cold” GBMs to “hot” tumors is crucial for effective immune activation and improved patient outcomes. We comprehensively characterized the rWTC-MBTA autologous cancer vaccine, consisting of Mannan-BAM-anchored irradiated whole tumor cells, Toll-like receptor ligands (LTA, Poly(I:C), R-848), and an anti-CD40 agonistic antibody, in preclinical GL261 and SB28 GBM models. A substantial number of vaccinated mice exhibited complete regression of GBM tumors in a T-cell-dependent manner, with no significant toxicity. Long-term tumor-specific immune memory was confirmed upon tumor rechallenge. In the vaccine-draining lymph nodes of the SB28 model, rWTC-MBTA vaccination triggered a major rise in cDC1 12 hours post-treatment, followed by an increase in cDC2, moDC, and pDC on Days 5 and 13. Enhanced cytotoxicity of CD4+ and CD8+ T cells in vaccinated mice was verified in co-culture with tumor cells. Comprehensive immunophenotyping in the GL261 and SB28 GBM microenvironments confirmed decreased regulatory T cells and increased CD4+ and CD8+ T cell infiltration in vaccinated mice. T-cell exhaustion analyses revealed an increase in the Tim3+CD8+ T cells. No significant differences were observed in the quantification of M-MDSC and PMN-MDSC between control and vaccinated mice, but PD-L1 expression significantly increased in M2 macrophages in vaccinated mice. Our findings demonstrate that rWTC-MBTA induces potent and long-term adaptive immune responses against GBM, warranting further investigation of combinations with other immunotherapies for enhanced efficacy.

Investigation of self-selective RRAM based on V/ITO structure with rapid thermal annealed ITO for synapse emulation

This paper focuses on the investigation of V/ITO (O2 Rapid Thermal Annealing)-based Self-Selective Resistive Random-Access Memory (RRAM) device. In this study, the natural oxidation of Vanadium top electrode and the rapid thermal annealing (RTA) process greatly simplified the device fabrication process. The VO2-based Selector, formed by the natural oxidation of the Vanadium electrode, effectively suppresses current and is directly integrated with the ITO layer, eliminating the need for additional serial Selector. The oxygen content of the ITO film is significantly increased by the RTA process, enabling the previously conductive ITO material to be used as the RRAM insulating layer without the need for additional deposition of insulating layer. This V/ITO (O2 RTA) structure not only exhibits highly uniform resistance distributions (σ/μ<2.8 %) and endurance stability (10000 cycles), but also effectively simulates synaptic plasticity, exhibiting both short-term and long-term memory behaviors. Notably, potentiation and depression characteristics are displayed by the device when continuous pulse voltage is applied. These advancements underscore the innovation and applicability of RTA-treated ITO films in next-generation memory technologies.

Towards theoretically understanding how long-term memory semantics can support working memory performance.

Working memory is the system that supports the temporary storage and processing of information. It is generally agreed that working memory is a mental workspace, with a combination of resources operating together to maintain information in mind for potential use in thought and action. Theories typically acknowledge the contributions of long-term memory to this system. One particular aspect of long-term memory, namely semantic long-term memory, can effectively supplement or "boost" working memory performance. This may be a relatively automatic process via the semantic properties of the stimuli or more active via strategy development and implementation. However, the precise mechanisms require greater theoretical understanding. In this review of the literature, we critically discuss theoretical models of working memory and their proposed links with long-term memory. We also explore empirical research that contributes to our understanding of the ways in which semantics can support performance of both verbal and visuospatial working memory tasks, with a view to potential intervention development. This includes the possibility of training people with lower performance (e.g., older adults) to use semantics during working memory tasks. We conclude that semantics may offer an opportunity to maximise working memory performance. However, to realise this potential, more research is needed, particularly in the visuospatial domain.

Metaphorical Idioms in Extended Conceptual Metaphor Theory

Abstract In Extended Conceptual Metaphor Theory (Kövecses, 2020), I offered a comprehensive overhaul of “standard” conceptual metaphor theory. The present paper attempts to demonstrate how the new view of CMT can handle metaphorical idioms. To this end, I analyze four metaphorical idioms from the thematic area of money (throw money about, money slips through someone’s fingers, be a cash cow, money keeps someone/something afloat). The analysis assumes and starts out from the observation that money-related metaphors are based on two generic-level conceptual metaphors: money is a moving entity and money is a force. Extended CMT adds to CMT the notion of “mental space-level metaphors” that were largely ignored in “standard” CMT, but are given an important role in extended CMT. These are the metaphors that represent actual, contextual meanings in a metaphorical usage event. Traditional CMT-type analysis cannot account for the emergence of such idiomatic meanings because the mappings, or correspondences, of standard CMT work on a single, generic level (frame-, domain-, or even image schema level). However, the contextual meanings of naturally used metaphors (including those of metaphorical idioms) are much more information-rich and specific. The conceptual metaphors on the image schema, domain, and frame levels are offline structures in long-term memory, whereas the conceptual metaphors on the mental space level occur only online in working memory. In online communication, speakers mobilize the static image schema-, domain-, and frame-level metaphors at the mental space level, where they create highly specific mental space-level metaphors. Given this framework, it becomes possible to explain how and why the four metaphorical idioms have different contextual meanings (as represented by different mental space-level metaphors), but, at the same time, why they also share certain conceptual metaphors on the frame-, domain-, or image schema-level. Additionally, we gain new insight into how the emergence of novel metaphorical idioms occurs with the help of and constrained by a previously existing large system of hierarchically arranged conceptual metaphors.

Photochemistry dominates over photothermal effects in the laser-induced reduction of graphene oxide by visible light

Graphene oxide (GO) possesses specific properties that are revolutionizing materials science, with applications extending from flexible electronics to advanced nanotechnology. A key method for harnessing GO’s potential is its laser-induced reduction, yet the exact mechanisms — photothermal versus photochemical effects — remain unclear. Herein, we discover the dominant role of photochemical reactions in the laser reduction of GO under visible light, challenging the prevailing assumption that photothermal effects are dominant. Employing a combination of Raman thermometry, X-ray photoelectron and photoluminescence spectroscopies, and electrical atomic force microscopy, we quantify the temperature and map the reduction process across micro and nano scales. Our findings demonstrate that the photochemical cleavage of oxygen-containing groups below a reduction threshold temperature is a decisive factor in GO reduction, leading to distinct characteristics that cannot be replicated by heating alone. This work clarifies the fundamental mechanisms of GO transformation under visible laser irradiation, highlighting the dominant role of photochemical processes. Distinguishing these subtleties enables the development of laser-reduced GO platforms for graphene-based applications compatible with industrial scales. We illustrate this potential by encoding information on GO surfaces as optical storage, allowing us to write binary sequences in long-term memory encoding invisible even through an optical microscope.