Evolutionary pattern of liquid-liquid phase separation in amphiphilic molecular self-assembly during the natural aging process of strong-aroma Baijiu.

Spatial pattern separation (SPS) is a memory process that enables the discrimination of similar spatial locations. This process is vulnerable to pathophysiological changes in the early stages of Alzheimer's disease (AD), but the translational potential of its testing remains unclear. This study aimed to evaluate the potential of SPS testing as a translational cognitive marker for identifying early AD and enabling direct comparisons of cognitive outcomes in animals and humans. We used a validated SPS task to examine biomarker-defined participants with amnestic mild cognitive impairment due to AD (AD aMCI; n = 56) and cognitively normal (CN) participants (n = 60). An animal version of this task, based on a modified Morris Water Maze task, was used to test six-month-old transgenic TgF344-AD rats (n = 38) and wild-type (WT) rats (n = 36). AD aMCI participants performed worse than CN participants, with performance declining as distance decreased. These results remained unchanged when adjusted for memory performance. TgF344-AD rats performed worse than WT rats in a probe trial with a 90° SPS design, but not in probe trials with an 180° SPS design or no SPS demands. The discriminatory power of the task was similar in the human and animal experiments. The findings demonstrate comparable SPS deficits in the early stages of AD in both humans and rodent models, which are not attributable to general memory impairment. SPS testing enables direct comparisons to be made between the cognitive performance of rats and humans, making it a promising approach for translational AD research.

Humans and other primates can robustly report whether they have seen specific images before, even when those images are extremely similar to ones they have previously seen. Multiple lines of evidence suggest that pattern separation computations in the hippocampus (HC) contribute to this behavior by shaping the fidelity of visual memory. However, unclear is whether HC uniquely determines memory fidelity or whether computations in other brain areas also contribute. To investigate, we recorded neural signals from inferotemporal cortex (ITC) and HC of two rhesus monkeys (1 male, 1 female) as they performed a memory task in which they judged whether images were novel or exactly repeated in the presence of visually similar lure images with a range of visual similarities. We found behavioral evidence for sharpening, reflected as memory performance that was nonlinearly transformed relative to a benchmark defined by visual representations in ITC. As expected, we found that behavioral sharpening aligned with visual memory representations in HC. Surprisingly, and unaccounted for by HC pattern separation proposals, we also found neural correlates of behavioral sharpening reflected in ITC. These results, coupled with further analysis of the data, suggest that ITC contributes to shaping the fidelity of visual memory in the transformation from visual processing to memory storage and signaling.

Scene Graph Generation (SGG) is a challenging cross-modal task, which aims to identify entities and relationships in a scene simultaneously. Due to highly skewed long-tailed distribution, the generated scene graphs are dominated by relation categories of head samples. Current works address this problem by designing re-balancing strategies at the data level or refining relation representations at the feature level. Different from them, we attribute this impact to catastrophic interference, that is, the subsequent learning of dominant relations tends to overwrite the earlier learning of rare relations. To address it at the modeling level, a Hippocampal Memory-Like Separation-Completion Collaborative Network (HMSC2) is proposed here, which imitates the hippocampal encoding and retrieval process. Inspired by the pattern separation of dentate gyrus during memory encoding, a Gradient Separation Classifier and a Prototype Separation Learning module are proposed to relieve the catastrophic interference of tail categories by modeling the separated classifier and prototypes. In addition, inspired by the pattern completion of area CA3 of hippocampus during memory retrieval, a Prototype Completion Module is designed to supplement the incomplete information of prototypes by introducing relation representations as cues. Finally, the completed prototype and relation representations are connected within a hypersphere space by a Contrastive Connected Module. Experimental results on Visual Genome and GQA datasets show our HMSC2 achieves state-of-the-art performance on the unbiased SGG task, effectively relieving the long-tailed problem. The source codes are released on GitHub: https://github.com/Nora-Zhang98/HMSC2.

Stock price prediction faces substantial challenges due to nonlinearity, non-stationarity, and noise contamination. Traditional econometric models and early Deep Learning methods struggle to effectively capture complex temporal patterns. This paper proposes a novel hybrid Neural Network, BiLSTM-SDTCN-AutoCorr, which refines a BiLSTM–Transformer backbone: a sequence decomposition module partitions the input series into trend and seasonal components to filter noise and enhance pattern separation; the vanilla self-attention mechanism is replaced by autocorrelation attention to efficiently capture periodic dependencies via the Fast Fourier transform; and the Transformer decoder is modified into Temporal Convolutional Network layers to strengthen local sequence modeling. The model is evaluated on five stock index datasets, and the results demonstrate significant superiority across evaluation metrics. The proposed model offers an efficient and robust solution for stock prediction with potential practical applicability.

Forming an episodic memory requires binding together disparate elements that co-occur in a single experience. One model of this process is that neurons representing different components of a memory bind to an 'index' - a subset of neurons unique to that memory. Evidence for this model has recently been found in chickadees, which use hippocampal memory to store and recall locations of cached food. Chickadee hippocampus produces sparse, high-dimensional patterns ('barcodes') that uniquely specify each caching event. Unexpectedly, the same neurons that participate in barcodes also exhibit conventional place tuning. It is unknown how barcode activity is generated, and what role it plays in memory formation and retrieval. It is also unclear how a memory index (e.g. barcodes) could function in the same neural population that represents memory content (e.g. place). Here, we design a biologically plausible model that generates barcodes and uses them to bind experiential content. Our model generates barcodes from place inputs through the chaotic dynamics of a recurrent neural network and uses Hebbian plasticity to store barcodes as attractor states. The model matches experimental observations that memory indices (barcodes) and content signals (place tuning) are randomly intermixed in the activity of single neurons. We demonstrate that barcodes reduce memory interference between correlated experiences. We also show that place tuning plays a complementary role to barcodes, enabling flexible, contextually appropriate memory retrieval. Finally, our model is compatible with previous models of the hippocampus as generating a predictive map. Distinct predictive and indexing functions of the network are achieved via an adjustment of global recurrent gain. Our results suggest how the hippocampus may use barcodes to resolve fundamental tensions between memory specificity (pattern separation) and flexible recall (pattern completion) in general memory systems.

This systematic review aims to synthesize current literature on anterior segment optical coherence tomography (ASOCT) characteristics of blebs following minimally invasive bleb surgery (MIBS) using the XEN Gel Stent (XGS) and PreserFlo MicroShunt (PMS), and to evaluate their utility in predicting surgical success. A comprehensive search of MEDLINE, EMBASE, CENTRAL, and Scopus was conducted up to February 1, 2025, for studies evaluating ASOCT imaging of post-MIBS blebs. Eligible studies included adult patients with glaucoma who underwent MIBS and had ASOCT bleb imaging. Data on bleb morphology, surgical outcomes, and intraocular pressure (IOP) control were extracted. Eleven studies comprising 409 participants were included. Surgical success following MIBS was associated with blebs with thicker walls, lower internal reflectivity, posterior episcleral fluid lakes, greater cystic structure density, and increased bleb height. Internal cavities and sub-conjunctival spaces were also consistently associated with lower IOP. XGS blebs often exhibited microcystic multiform or sub-conjunctival separation patterns, while PMS blebs demonstrated wider fluid cavities and closer proximity to the limbus. Implant positioning significantly affected bleb morphology and outcomes. Temporal evolution of bleb morphology following MIBS was also observed. Quantitative assessment via ASOCT faced limitations due to variability in imaging protocols and manual measurement methods. ASOCT-based bleb imaging provides valuable structural insights that correlate with surgical success following MIBS. Further research with standardized imaging protocols may be needed to better refine bleb evaluation and examine longer-term surgical outcomes following MIBS.

Anxiety disorders and depression are the most frequently diagnosed mental illnesses and are highly comorbid. Both have been linked to memory impairments, albeit the relationship between them remains unclear and understudied. Our review aims to investigate behavioral pattern separation performance in individuals with varying levels of anxiety and depression. We included studies where mnemonic discrimination performance is measured using mnemonic discrimination tasks designed to directly measure behavioral pattern separation, while symptoms of anxiety and/or depression are assessed using any validated and recognized scales or inventories. We only included quantitative studies. Fixed scientific databases and artificial intelligence were systematically searched, identifying nine studies on anxiety and 14 on depression. Anxiety studies presented conflicting evidence, but a trend showed optimal mnemonic discrimination with threat-based encoding and safe retrieval. Conversely, depression studies consistently suggested a negative relationship between symptom severity and pattern separation performance. Additionally, pattern separation appeared enhanced for negative stimuli and impaired for neutral stimuli in individuals with higher levels of depression. However, no clear differences were observed between clinically diagnosed groups and healthy controls. Methodological inconsistencies in anxiety studies present challenges for interpretation. Similarly, the effects of medication and the heterogeneity of clinical groups pose limitations to depression studies. Trends were identified, but further investigation with unified methodologies and clinical groups is needed to understand the relationship between anxiety, depression, and mnemonic discrimination performance.

Synapses are the fundamental units of communication and information processing in the nervous system. They show remarkable functional autonomy, as well as speed of signaling, bidirectional plasticity, and diversity. Synapses shape complex network functions, such as learning, memory, pattern separation, pattern completion, and many others. Synaptic dysfunction is responsible for a wide range of neurological and psychiatric diseases. Many of these diseases are emerging as synaptopathies, but the precise disease mechanisms are unknown. Given their micron-scale small size and seemingly compact structure, synapses were generally thought to be functionally indivisible structures. However, with the advent of high-resolution electrophysiology and imaging techniques, it is increasingly clear that synapses harbor functionally specialized nanomodules. This expanding nanobiology of the synapse provides a new perspective on synaptic signaling. The novel insight gained from this work is critical to understand disease mechanisms and to guide the development of appropriate therapeutic strategies for major brain diseases ranging from neurodegenerative and neurodevelopmental disorders to neuropsychiatric disorders such as depression and schizophrenia.

In recent years, the design priorities of modern marine propellers have shifted from maximizing efficiency to minimizing vibration-induced noise emissions and improving structural durability. However, an optimized design does not necessarily ensure optimal performance across the full operational range of a vessel. Due to operational constraints such as reduced docking times and regional speed regulations, propellers frequently operate off-design. This deviation from the design point leads to periodic turbulent boundary layer separation on the propeller blades, resulting in increased unsteady pressure fluctuations and, consequently, elevated hydroacoustic noise emissions. To mitigate these effects, bio-inspired modifications have been investigated as a means of improving flow characteristics and reducing pressure fluctuations. Tubercles, characteristic protrusions along the leading edge of humpback whale fins, have been shown to enhance lift characteristics beyond the stall angle by modifying the flow separation pattern. However, their influence on transient pressure fluctuations and the associated hydroacoustic behavior of marine propellers remains insufficiently explored. In this study, we apply the concept of tubercles to the blades of a hubless propeller, also referred to as a rim-drive propeller. We analyze the pressure fluctuations on the blades and in the wake by comparing conventional propeller blades with those featuring tubercles. The flow fields of both reference and tubercle-modified blades were simulated using the Stress Blended Eddy Simulation (SBES) turbulence model to highlight differences in the flow field. In both configurations, multiple helix-shaped vortex systems form in the propeller wake, but their decay characteristics vary, with the vortex structures collapsing at different distances from the propeller center. Additionally, Proper Orthogonal Decomposition (POD) analysis was employed to isolate and analyze the periodic, coherent flow structures in each case. Previous studies on the flow field of hubless propellers have demonstrated a direct correlation between transient pressure fluctuations in the flow field and the resulting noise emissions. It was demonstrated that the tubercle modification significantly reduces pressure fluctuations both on the propeller blades and in the wake flow. In the analyzed case, a reduction in pressure fluctuations by a factor of three to ten for the different BPF orders was observed within the wake flow.

BackgroundThe Mnemonic Similarity Task (MST) is a behavioral tool designed to tax pattern separation, a critical hippocampal function involving the transformation of similar experiences into discrete, non‐overlapping memory representations. Our pilot study aimed to assess the feasibility of MST administration among the oldest old, individuals 80 years and older, explore the association of MST performance metrics with established global cognitive measures, and evaluate potential age effects.MethodsThirty‐one participants aged 80 years and older from the UCI Alzheimer's Disease Research Center (ADRC) and the 90+ Study underwent MST as part of their cognitive assessment. Participants categorized 64 images as “indoor” or “outdoor” during the encoding phase and later classified 96 images as “old,” “similar,” or “new” in a recognition phase. Images were categorized as targets (old), lures (similar), or foils (novel). Key outcome measures included recognition memory (REC) and the lure discrimination index (LDI). Linear regression analyses were conducted to evaluate the associations between MST scores, age, and cognitive measures, i.e. the Mini‐Mental State Examination (MMSE).ResultsMean age was 92.7± 5.6 and 61.3% were female (Table 1). MST was successfully completed by all participants. Regression analyses revealed no significant association between MST scores and age (REC: p = 0.12; LDI: p = 0.09) (Table 2). A significant positive correlation was identified between MMSE and REC scores (β = 0.36, p = 0.02). No significant association was found between MMSE and LDI (β = 0.15, p = 0.28). Scatterplots indicated variability in individual MST scores with no discernible age‐related decline. (Figure 1)ConclusionThe MST is a feasible and effective task for assessing pattern separation and recognition memory in the oldest old. The observed association between MMSE and REC, but not LDI, deserves further investigation. The direct relationship between REC and MMSE underscores the utility of MST as a cognitive assessment tool. Further research with expanded cognitive measures and imaging biomarkers is warranted to elucidate the underlying mechanisms driving MST performance and its role as a digital biomarker for cognitive health.

BackgroundMixed dementia is characterized by significant clinical and pathological heterogeneity posing challenges for accurate diagnosis and treatment planning. Digital twin technology offers a transformative approach by learning data characteristics to simulate predictions of an unseen data sample. This study aims to construct a digital twin neural marker with multimodal neuroimage data to enable predictive tasks on samples with mixed dementia. We leverage cross‐site neuroimage datasets from the Dementias Platform UK (DPUK) and a Korean dementia cohort to construct the digital twin neural marker and show that the marker can be applied to delineate etiologies of mixed dementia.MethodsA digital twin neural marker of mixed dementia was constructed by training a Vision Transformer (ViT) model with a generative pre‐training approach. Specifically, Masked AutoEncoder (MAE) training of the ViT model on T1w and FLAIR neuroimage data from DPUK and a Korean dementia cohort was first constructed to capture the latent characteristics of the neurodegenerative brain etiologies. The model was further fine‐tuned on another Korean dementia cohort data with mixed dementia to delineate the etiologies of the neurocognitive disorder given a neuroimage input. Federated learning approaches were employed to train the model without data transfer across sites, maintaining data privacy within the trusted research environment.ResultsThe fine‐tuned digital twin neural marker achieved a reliable performance in delineating the mixed dementia etiology. The latent representation of the neural marker showed a separable pattern between different underlying etiologies when visualized with UMAP. These findings demonstrate the effectiveness of digital twins in leveraging global cross‐site datasets to provide actionable clinical insights.ConclusionsThe results highlight the potential of a digital twin neural marker to address the complexities of delineating mixed dementia etiologies. Most importantly, this work represents an international collaboration (Korea‐UK) to develop a digital twin neural marker using large datasets while upholding data democracy principles.

New Insights into Separation Patterns: A Volumetric and Metabolic Perspective

ABSTRACTOur everyday experiences share many overlapping features, as we often engage in repeated activities and routines. This leads to interference across our experiences, making it difficult to remember specific, unique events. Hippocampal pattern separation enables the discrimination of highly similar experiences to be stored orthogonally, especially in the face of interference. Mnemonic discrimination tasks have been designed to tax hippocampal pattern separation by including perceptually similar “lure” stimuli during memory retrieval. However, we experience vast interference beyond a single instance of overlap. Thus, a key feature of our memory system is to overcome this high interference. Furthermore, some experiences tend to be better remembered by most people than others, a feature known as memorability. However, it is unclear how memorability may impact the effect of interference on memory. To this end, we designed a mnemonic discrimination task with multiple forms of interference, such that target (repeated) and lure (similar) images of a baseline image were shown to participants during a memory test designed to increase interference during memory retrieval. We additionally varied image memorability by including memorable and forgettable images to examine interactions with interference conditions. We found that greater interference during retrieval enhanced lure discrimination for memorable images, but impaired lure discrimination for forgettable images. This suggests that interference does not uniformly impact memory, with greater interference in memory leading to exaggerated memorable and forgettable experiences.

Diabetes mellitus profoundly disturbs hepatic metabolism by impairing lipid and amino acid homeostasis, yet spatially resolved molecular evidence of these alterations remains limited. This study employed Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS) to visualise and quantify metabolic remodelling in rat liver under diabetic conditions and following metformin treatment. Liver cryosections from lean controls (LEAN), diabetic rats (P1), and metformin-treated diabetic rats (P2) were analysed in the negative ion mode, and all spectra were normalised to total ion counts. One-way ANOVA with false discovery rate (FDR) correction identified 43 lipid-related and 20 amino acid-related ions with significant group differences. Diabetic livers exhibited a marked depletion of phospholipid- and fatty acid-related ions (e.g., m/z 241.04, 281.25, 536.38) accompanied by increased ceramide fragments (m/z 805–806), indicating lipotoxic remodelling and mitochondrial stress. Simultaneously, aromatic and neutral amino acids such as phenylalanine, tyrosine, and glutamine were reduced, while small acidic fragments were elevated, consistent with enhanced proteolysis and gluconeogenic flux. Metformin administration partially restored both lipid and amino acid profiles toward the control phenotype. Hierarchical clustering and spatial ion maps revealed distinct group separation and partial normalisation of hepatic molecular patterns. These results demonstrate that ToF-SIMS provides label-free, spatially resolved insights into diabetes-induced metabolic disturbances and metformin-driven hepatoprotection.

Adult hippocampal neurogenesis is essential for discriminating between similar contexts (pattern separation) in animals. In humans, the link between neurogenesis and pattern separation remains tenuous due to the inherent constraints on manipulating neurogenesis. Here, we report a longitudinal study of patients with benign cavernous sinus meningiomas localized immediately adjacent to the hippocampus. Patients underwent focal stereotactic radiotherapy, which, while targeted at the tumor, inevitably affected the ipsilateral hippocampus. At different timepoints post-therapy (up to 2 years), patients were presented with mnemonic similarity task (MST) to assess pattern separation, pattern completion, and recognition memory. While hippocampal irradiation did not affect the overall recall or recognition memory, we found delayed, transient, laterally-restricted effects on pattern separation and completion. In patients with right-sided (but not left-sided) hippocampal irradiation deficits in pattern separation and completion accumulated by 12 months post-treatment, but returned to the initial levels by 24 months. The observed changes are consistent with the vulnerability of dividing neural progenitors in the dentate gyrus, the protracted maturation of new neurons in the adult human brain, and the involvement of adult-born neurons in pattern separation and pattern completion. Our findings support the notion that ongoing hippocampal neurogenesis contributes to defined cognitive functions in humans.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-29852-z.

The paper reports longitudinal analyses examining the extent to which institutional trust mediates the relationship between individuals' sense of precarity and their adherence to conspiracy beliefs. Across three waves, 925 participants (50.2% female) between the ages of 18 and 85 (M = 49.53; SD = 15.81) reported subjective appraisals of their financial situation (precarity), trust in institutions and adherence to conspiracy beliefs. The current study extends the previous analyses by including three‐wave longitudinal data. The preregistered autoregressive cross‐lagged panel model supports the notion that a sense of precarity follows adherence to conspiracy beliefs rather than preceding them, while institutional (dis)trust and conspiracy beliefs show a bidirectional pattern. However, the random‐intercept cross‐lagged panel model does not corroborate this, suggesting that the effects may be driven by stable between‐person differences rather than actual within‐person changes. Additionally, the latter model reveals two separate temporal patterns linking conspiracy beliefs with either the sense of precarity or institutional trust, opening the possibility that our results were driven by two distinct underlying mechanisms. The paper discusses the importance of longitudinal studies for a more accurate understanding of social‐psychological realities in which conspiracy beliefs and suspicions of institutions may flourish.

Session-based recommendation (SBR) systems have increasingly focused on hypergraph-based approaches due to their potent capability in capturing high-order item relationships. Typically, existing approaches rely on sequential item relations to manually construct fixed hypergraphs. However, this methodology neglects the multiple relations inherent in the original sequences, thereby impeding the hypergraph's precision in discerning user preferences. Furthermore, the rigidity of fixed hypergraph structures tends to emphasize explicit relationships, ignoring the latent implicit patterns. In light of this, we present a novel Multi-relation enhanced Dynamic HyperGraph (MDHG) learning framework for session-based recommendation, to model intricate and variable item relations. Initially, we establish three distinct relation graphs which capture separate user behavior patterns to extract personalized interest preferences under differentiated intentions. Subsequently, we propose an enhanced dynamic hypergraph paradigm that adaptively generates hypergraph structures based on prior relation graph, thereby reinforcing and unveiling implicit connectivity relations in a layer-aware manner. Finally, to mitigate the noise among diverse relations, we introduce the maximum mutual information auxiliary task and employ the attention mechanism as a cross-relation aggregator. Extensive experiments on various real-world datasets verify the superiority of our MDHG model. Our code is publicly available at https://github.com/Qin-lab-code/MDHG .

ABSTRACT In China, the vernacular houses of ethnic minorities are gradually losing their distinctive features. Spatial configuration research is regarded as a viable approach to excavating the intrinsic characteristics of architectural layout. To investigate the spatial configuration of the Nu ethnic group’s dwellings, the spatial configuration of Nu’s houses in Gongshan County was quantified by calculating the global integration value and the mean step depth using Depthmap X. Three typical spatial configuration patterns of the Nu’s dwellings were identified using cluster analysis: the separate central room pattern, the three-step-depth central room pattern, and the three-room main house pattern. After investigating the cultural genes that influence the typical patterns, it was found that the separate central room type reflects the custom of “using the central room as the core for daily life” and “relatives live together as a big family”. The three-step-depth central room type reflects the custom of “organic renewal of houses” and “the preference for an enclosed space”. The three-room main house type is the result of modern trends. Commonalities across the three patterns were identified to further illuminate the correlation between spatial layout and ethnic culture. Finally, recommendations for the renewal and construction of Nu’s houses were proposed.

Cell assemblies are considered fundamental units of brain activity, underlying diverse functions ranging from perception to memory and decision-making. Cell assemblies have generally been studied in relation to specific stimuli or actions, but this approach does not readily extend to more abstract constructs. An alternative approach is to assess cell assemblies without making reference to external variables, and instead focus on internal brain processes—by assessing assemblies by their endogenous ability to effectively elicit specific responses in downstream (“reader”) neurons. However, this compelling idea currently lacks experimental support. Here, we provide evidence for assembly–reader communication. Large-scale cross-structural recordings in rats revealed that reader activation was genuinely collective, functionally selective, yet flexible, implementing both pattern separation and completion. These processes occurred at the time scale of membrane integration, synaptic plasticity, and gamma oscillations. Finally, assembly–reader couplings were selectively modified upon associative learning, indicating that they were plastic and could become bound to behaviorally relevant variables. These results support cell assemblies as an endogenous mechanism for brain function.