Search Results (93)

Background: Fibromyalgia syndrome (FMS) and post-traumatic stress disorder (PTSD) may co-occur and are associated with increased symptom burden, functional impairment, and reduced quality of life. Accumulating evidence suggests shared neurobiological mechanisms. Trauma-focused interventions targeting maladaptive memory processes may therefore represent a relevant therapeutic approach in this population. Objective: To evaluate the feasibility, tolerability, and preliminary clinical associations of a brief reconsolidation-based therapy in women with comorbid FMS and PTSD. Methods: This multicenter pilot study included adult women diagnosed with FMS and PTSD who underwent six sessions of reconsolidation therapy combining traumatic memory reactivation with propranolol administration. Clinical outcomes were assessed at baseline and at 3-month follow-up using the Fibromyalgia Impact Questionnaire (FIQ), the Impact of Event Scale–Revised (IES-R), the Montgomery–Åsberg Depression Rating Scale (MADRS), the Beck Depression Inventory (BDI), the Rosenberg Self-Esteem Scale (RSES), and the SF-36. Changes over time were analyzed using paired statistical tests and linear mixed-effects models. Results: Fourteen participants completed the intervention and follow-up assessments. The intervention was feasible and well tolerated. Changes over time were observed in fibromyalgia-related quality of life (FIQ scores), PTSD symptom severity (IES-R), and depressive symptoms (MADRS, BDI), as well as in selected SF-36 domains, including vitality, social functioning, and mental health. A progressive decrease in IES-R scores was observed across treatment sessions. Conclusions: This pilot study suggests that reconsolidation-based therapy is feasible in women with comorbid FMS and PTSD and was associated with changes in PTSD symptoms and fibromyalgia-related functional impact. Given the exploratory design and absence of a control group, these findings should be interpreted cautiously and warrant confirmation in larger, controlled trials. Full article

Sparse Distributed Memory (SDM) provides a biologically inspired mechanism for associative and online learning. Transformer architectures, despite exceptional inference performance, remain static and vulnerable to catastrophic forgetting. This work introduces Continual Associative Learning Model (CALM), a conceptual framework that defines the theoretical base and integration logic for the cognitive model seeking to establish continual, lifelong adaptation without retraining by combining SDM system with lightweight dual-transformer modules. The architecture proposes an always-online associative memory for episodic storage (System 1), as well as a pair of asynchronous transformer consolidate experience in the background for uninterrupted reasoning and gradual model evolution (System 2). The framework remains compatible with standard transformer benchmarks, establishing a shared evaluation basis for both reasoning accuracy and continual learning stability. Preliminary experiments using the SDMPreMark benchmark evaluate algorithmic behavior across multiple synthetic sets, confirming a critical radius-threshold phenomenon in SDM recall. These results represent deterministic characterization of SDM dynamics in the component level, preceding the integration in the model level with transformer-based semantic tasks. The CALM framework provides a reproducible foundation for studying continual memory and associative learning in hybrid transformer architectures, although future work should involve experiments with non-synthetic, high-load data to confirm scalable behavior in high interference. Full article

Previous anatomic and physiologic studies of the peripheral and central auditory system, with rare exceptions, have relied on the use of tonal stimuli. Here, we test the hypothesis that zebrafish, Danio rerio, can detect and discriminate between two 6 s long complex sounds—a sequence of five multi-harmonic, noise-embedded constant frequency (NCF) tone pips and a chirp sequence consisting of six rapid downward frequency-modulated (DFM) sweeps. To test our hypothesis, we develop an associative conditioning assay, requiring prediction of an unconditioned stimulus (US). A video clip of a shoal of free-swimming zebrafish presented on an LCD screen serves as a desirable or rewarding US and a bullfrog with inflating and deflating vocal sacs serves as an aversive or fearful US. Within our novel “Go-to/Go-away” (or Go/Go) assay, sound discrimination allows an animal to decide to go/swim towards the desirable US and away from the undesirable US within a short time window preceding each US. We use markerless tracking of fish locations following twelve training runs and six test runs to determine if zebrafish can discriminate between the two sounds. We discovered that on average, fish move closer to the LCD screen in response to the sound paired to the rewarding CS and farther away from the screen in response to the sound paired with the aversive US. Differences in locations and longest swim trajectories occur in the 3 s time window between the CS and the US. These differences are largely retained on the second day of testing, suggesting overnight memory consolidation. We conclude that adult zebrafish can both perceive and rapidly learn to discriminate between complex sounds and that our novel assay can be implemented for high throughput screening of drugs targeted for alleviating memory and attention deficits as well as other neurodegenerative disorders. Full article

Background/Objectives: Distraction is a form of impaired selective attention that becomes more pronounced with normal aging and in pathological conditions such as mild cognitive impairment (MCI) and Alzheimer’s disease (AD). Event-related potentials (ERPs) provide sensitive, time-resolved measures of neural mechanisms underlying distractibility. This study aimed to identify age- and disease-related ERP signatures of auditory–visual distraction as potential functional biomarkers for cognitive decline. Methods: Forty-six participants were enrolled, including young controls (Y), healthy older controls (O), individuals with MCI, and individuals with AD. Participants performed cross-modal interference tasks in which irrelevant auditory distracting sounds were paired with a relevant visual discriminating task. The distraction potential was quantified as the difference between ERP responses to novel distractors and standard stimuli, focusing on three core components: N1-enhancement, P3a, and reorienting negativity (RON). Behavioral measures (accuracy, reaction time, miss responses) were also assessed. Results: Compared to Y, O showed increased N1-enhancement and reduced P3a and RON amplitudes, consistent with age-related susceptibility to distraction. Patients with MCI and AD exhibited further abnormalities, including diminished P3a and altered RON responses, suggesting impaired orientation and reorientation of attention. Behavioral distraction effect was observed in all groups, with no significant difference between groups. ERP–cognition correlations indicated that reduced P3a amplitude and delayed RON were associated with executive dysfunction and memory deficits. Conclusions: ERP signatures of distraction, particularly altered P3a and RON components, differentiate normal aging from pathological decline and may serve as functional biomarkers for early detection of MCI and AD. These findings highlight the translational potential of distraction paradigms in clinical assessment of aging-related cognitive impairment. Full article

Transcranial direct current stimulation (tDCS) is being explored as an adjunct for diabetes-related symptoms grounded in diabetes-associated alterations in brain networks. We reviewed clinical trials of tDCS conducted in people with diabetes and summarized mechanistic findings relevant to metabolic control. Two reviewers searched PubMed/MEDLINE, Cochrane Library, Google Scholar, Scopus, and ResearchGate for studies published from 1 January 2008 to 31 August 2025. Forty-one records were identified; after screening and full-text assessment, 11 studies met the inclusion criteria. Across predominantly middle-aged adults with long-standing type 2 diabetes, protocols were low-intensity and well-tolerated. The most consistent clinical benefit was analgesia with primary motor cortex stimulation, with randomized comparisons favoring active tDCS over sham. Dorsolateral prefrontal stimulation paired with working-memory training improved cognition and reduced anxiety, while combined motor–prefrontal courses yielded gains in sleep quality and health-related quality of life; a small, randomized study in proliferative diabetic retinopathy reported short-term visual improvements after occipital stimulation. Safety was favorable, and no serious adverse events were reported. Objective metabolic endpoints in diabetic cohorts were scarce; early evidence for insulin-independent improvements in glucose handling and neurometabolic shifts derives mainly from non-diabetic or mixed samples and remains hypothesis-generating. Overall, tDCS appears to be a promising, well-tolerated adjunct for diabetes-related complications. Larger, rigorously sham-controlled trials that align targets with clinical phenotypes and include standardized metabolic outcomes are needed. Full article

The impact of prenatal exposure to trace metal mixtures on children’s neurodevelopment remains debated. Many studies treat all trace metals as a single entity, overlooking the distinct biological roles of essential and toxic metals. This approach may highlight overall exposure but fails to capture their differential effects on neurodevelopment. This study aims to examine the associations between prenatal exposure to essential and toxic metals and children’s cognitive development, focusing on their independent effects. A cohort of 201 mother–infant pairs was analyzed. Maternal urinary metal levels were measured at 12 weeks of gestation, and children’s neurodevelopment was assessed at 4 years using the Wechsler Preschool and Primary Scale of Intelligence and the Developmental Neuropsychological Assessment. Generalized Additive Models (GAM), Restricted Cubic Spline (RCS), and Weighted Quantile Sum (WQS) regression were applied. GAM identified non-linear associations between essential metals (manganese and molybdenum) and cognitive outcomes, including verbal comprehension index (VCI), working memory index, full-scale IQ, and general ability index, which were confirmed by RCS. No non-linear relationships were observed for toxic metals. WQS showed negative associations between toxic metals and VCI (b = −1.07), processing speed index (b = −0.98), vocabulary acquisition index (b = −1.25), and verbal fluency (b = −0.23), mainly driven by cadmium (Cd) and antimony (Sb). Essential metal mixtures were not associated with cognitive outcomes. Prenatal exposure to toxic metals negatively affects children’s cognitive and neuropsychological development. Reducing maternal exposure during pregnancy is essential for protecting offspring development. Full article

Background/Objectives: Fragile X-associated tremor/ataxia syndrome (FXTAS) is characterized by tremor, gait ataxia, and cerebellar white matter degeneration, along with possible cognitive and cerebral changes. Although diagnostic criteria were originally developed in males, emerging evidence suggests that FXTAS may present differently in females. The present study examined sensorimotor and memory features of aging in female premutation carriers with (FXTAS+) and without FXTAS (FXTAS−). Methods: We studied 51 female premutation carriers (FXTAS+ = 16, FXTAS− = 35) and 24 age-matched female controls. Participants ranged in age from 47–80 years. All participants completed genetic testing, clinical evaluations, T2-weighted MRIs, and quantitative assessments of sensorimotor (precision grip force task) and memory (reading span; visual paired associates task) functions. Results: During precision grip testing, FXTAS+ carriers showed higher sustained force regularity than FXTAS− carriers (p = 0.03, d = 1.0) and controls (p = 0.004, d = 1.1) at low gain levels only. FXTAS+ participants were slower than controls on motor reaction time (p = 0.009, d = 0.82). Initial force output was higher in FXTAS+ than FXTAS− carriers (p = 0.03, d = 1.0) and controls (p = 0.03, d = 1.0) but at low gain only. FXTAS+ carriers exhibited poorer working memory than FXTAS− carriers (p = 0.03, d = 0.91) and controls (p = 0.02, d = 1.0). During a long-term memory task, FXTAS+ participants were less accurate than FXTAS− carriers (p = 0.04, d = 0.86) and controls (p = 0.004, d = 1.1) and showed increased reaction times relative to FXTAS− carriers (p = 0.03, d = −0.82) and controls (p = 0.01, d = −1.2). Conclusions: Together, these findings indicate that FXTAS+ females exhibit distinct motor and cognitive impairments, underscoring the value of quantitative behavioral measures for detecting and tracking neurodegenerative progression in female premutation carriers. Full article

Although associative interference has traditionally been attributed to retrieval competition, emerging evidence suggests that interference may also arise from encoding-based representational processes. The present study examined whether retroactive interference (RI) and proactive interference (PI) can occur in the absence of explicit retrieval competition and whether they reflect distinct underlying mechanisms. Participants studied two lists of word–picture pairs in an AB/AC associative learning paradigm, followed by a non-competitive two-alternative forced-choice (2AFC) associative recognition test and a source memory task. Across both frequentist and Bayesian analyses, recognition accuracy revealed a significant RI effect—lower accuracy for earlier A-B pairs relative to non-overlapping controls—whereas PI manifested as longer reaction times (RTs) for later A-C pairs, despite comparable accuracy. Source judgments showed faster correct responses for overlapping than for non-overlapping pairs, suggesting that cue overlap facilitated more fluent retrieval rather than confusion. These findings indicate that interference can emerge independently of retrieval competition and that RI and PI are supported by dissociable mechanisms: RI reflects encoding-related reorganization that weakens earlier associations, whereas PI reflects increased retrieval effort following differentiation of overlapping traces. Together, the results support a process-interaction framework in which encoding-based reactivation and reorganization shape later retrieval dynamics, demonstrating that associative interference arises from the interplay between encoding and retrieval processes rather than retrieval competition alone. Full article

Associative learning is a fundamental neural mechanism in human memory and cognition. It has attracted considerable attention in neuromorphic system design owing to its multimodal integration, fault tolerance, and energy efficiency. However, prior studies mostly focused on single inputs, with limited attention to multibit pairs or recall under non-orthogonal input patterns. To address these issues, this study proposes a bidirectional associative learning system using paired multibit inputs. It employs a synapse–neuron structure based on spiking neural networks (SNNs) that emulate biological learning, with simple circuits supporting synaptic operations and pattern evaluation. Importantly, the update and read functions were designed by drawing inspiration from the operational characteristics of emerging synaptic devices, thereby ensuring future compatibility with device-level implementations. The proposed system was verified through Cadence-based simulations using CMOS neurons and Verilog-A synapses. The results show that all patterns are reliably recalled under intact synaptic conditions, and most patterns are still robustly recalled under biologically plausible conditions such as partial synapse loss or noisy initial synaptic weight states. Moreover, by avoiding massive data converters and relying only on basic digital gates, the proposed design achieves associative learning with a simple structure. This provides an advantage for future extension to large-scale arrays. Full article

This study investigated how encoding strength and consolidation shape proactive interference (PI) in associative memory. Using a Modified Modified Free Recall (MMFR) paradigm, participants studied overlapping (A-B, A-C) and non-overlapping (E-F, G-H) pairs. The encoding strength of List 1 was manipulated (one vs. three study repetitions), while List 2 was held constant. Cued recall was tested immediately and after a 24-h delay. Results showed that increasing List 1’s encoding strength enhanced overall recall for both overlapping and non-overlapping pairs, indicating more effective learning, but did not alter the magnitude of PI. Instead, PI was strongly modulated by retention interval. At immediate test, robust PI emerged across conditions, reflecting cue-based retrieval competition. After a 24-h delay, PI was reduced or absent when List 1 was weakly encoded but persisted in attenuated form when List 1 was strongly encoded, suggesting differential consolidation trajectories for overlapping and non-overlapping associations. Co-retrieval analyses further revealed reliable associative dependency between B and C across all conditions, consistent with representational linkages that promote cooperative retrieval. These findings highlight the dual influence of cue overlap: at the representational level, overlapping pairs form integrated structures that foster co-retrieval, whereas at the retrieval-processing level, cue overload induces competition and PI. Taken together, the results indicate that although initial encoding strength enhances overall recall of List 2, the persistence of proactive interference is influenced by consolidation processes. Full article

Background/Objectives: This cohort study examined the effects of sleep durations (night, day, and total daily) at ages 1, 1.5, and 3 years on working memory (WM) assessed at age 4, measured using forward digit span. Methods: Because frequency of yogurt intake at 1 year has been shown to affect sleep duration at 3 years, we also accounted for the association between frequency of yogurt intake at 1 year and sleep duration, based on a recent study indicating positive effects of yogurt on sleep. The study included 164 mother–child pairs observed from ages 1 to 4. Results: Spearman correlations and hierarchical multiple regression analyses revealed that both night sleep duration and yogurt intake at age 1 were significantly associated with WM performance at age 4. In this sample, however, yogurt intake was not correlated with sleep duration. Conclusions: To a limited degree, both yogurt intake frequency and night sleep duration at 1 year were associated with WM performance at 4 years, indicating that frequent yogurt intake at 1 year and longer night sleep duration may lead to higher WM performance at 4 years. Full article

Human Leukocyte Antigen (HLA) Class II (HLA-II) molecules bind peptides of phagocytosed non-self proteins and present them on the cell surface to circulating CD4+ T lymphocytes. A successful binding of the presented peptide with the T cell receptor (TCR) activates the CD4+ T cell, leading to the production of antibodies against the peptide (and the protein of its origin) by the B cell and augmentation of the cytotoxic and memory functions of CD8+ T cells. The first and essential step in this process is the successful formation of a stable peptide-HLA-II complex (pHLA-II), which is achieved when the peptide binds with high affinity to the HLA-II molecule. Such highly antigenic non-self peptides occur in melanoma-associated proteins and could be used as antitumor agents when bound to a matching HLA-II molecule. The objective of this study was to identify such peptides from 15 melanoma-associated proteins. We determined in silico the predicted binding affinity (IC₅₀) of all pHLA-II pairs between 192 common HLA-II molecules and all possible linear 15-amino acid (15-mer) peptides (epitopes) of 15 known melanoma-associated antigens (N = 3466 epitopes) for a total of 192 × 3466 = 665,472 determinations. From this set, we identified epitopes with strong antigenicity (predicted best binding affinity [PBBA] IC₅₀ < 50 nM). Of a total of 665,472 pHLA-II tested, 5941 (0.89%) showed strong PBBA, stemming from 117 HLA-II alleles and 679 distinct epitopes. This set of 5941 pHLA-II pairs with predicted high antigenicity possesses the requisite information for devising multipeptide vaccines with those epitopes alone or in combination with the corresponding HLA-II molecules. The results obtained have a major implication for cancer therapy, namely that the administration of subsets of the 679 high antigenicity epitopes above, alone or in combination with their associated HLA-II molecules, would be successful in engaging CD4+ T helper lymphocytes to augment the cytotoxic action and memory of CD8+ T lymphocytes and induce the production of antitumor antibodies by B cells. This therapy would be effective in other solid tumors (in addition to melanoma) and would be enhanced by concomitant immunotherapy with immune checkpoint inhibitors. Full article

With the continuous acceleration of industrialization, air pollution has become increasingly severe and has, to some extent, contributed to the progression of global climate change. Against this backdrop, accurate temperature forecasting plays a vital role in various fields, including agricultural production, energy scheduling, environmental governance, and public health protection. To improve the accuracy and stability of temperature prediction, this study proposes a hybrid modeling approach that integrates convolutional neural networks (CNNs), Long Short-Term Memory (LSTM) networks, and random forests (RFs). This model fully leverages the strengths of CNNs in extracting local spatial features, the advantages of LSTM in modeling long-term dependencies in time series, and the capabilities of RF in nonlinear modeling and feature selection through ensemble learning. Based on daily temperature, meteorological, and air pollutant observation data from Wuhan during the period 2015–2023, this study conducted multi-scale modeling and seasonal performance evaluations. Pearson correlation analysis and random forest-based feature importance ranking were used to identify two key pollutants (PM_2.5 and O₃) and two critical meteorological variables (air pressure and visibility) that are strongly associated with temperature variation. A CNN-LSTM model was then constructed using the meteorological variables as input to generate preliminary predictions. These predictions were subsequently combined with the concentrations of the selected pollutants to form a new feature set, which was input into the RF model for secondary regression, thereby enhancing the overall model performance. The main findings are as follows: (1) The six major pollutants exhibit clear seasonal distribution patterns, with generally higher concentrations in winter and lower in summer, while O₃ shows the opposite trend. Moreover, the influence of pollutants on temperature demonstrates significant seasonal heterogeneity. (2) The CNN-LSTM-RF hybrid model shows excellent performance in temperature prediction tasks. The predicted values align closely with observed data in the test set, with a low prediction error (RMSE = 0.88, MAE = 0.66) and a high coefficient of determination (R² = 0.99), confirming the model’s accuracy and robustness. (3) In multi-scale forecasting, the model performs well on both daily (short-term) and monthly (mid- to long-term) scales. While daily-scale predictions exhibit higher precision, monthly-scale forecasts effectively capture long-term trends. A paired-sample t-test on annual mean temperature predictions across the two time scales revealed a statistically significant difference at the 95% confidence level (t = −3.5299, p = 0.0242), indicating that time granularity has a notable impact on prediction outcomes and should be carefully selected and optimized based on practical application needs. (4) One-way ANOVA and the non-parametric Kruskal–Wallis test were employed to assess the statistical significance of seasonal differences in daily absolute prediction errors. Results showed significant variation across seasons (ANOVA: F = 2.94, p = 0.032; Kruskal–Wallis: H = 8.82, p = 0.031; both p < 0.05), suggesting that seasonal changes considerably affect the model’s predictive performance. Specifically, the model exhibited the highest RMSE and MAE in spring, indicating poorer fit, whereas performance was best in autumn, with the highest R² value, suggesting a stronger fitting capability. Full article

Background/Objectives: Vitamin D deficiency is a global epidemic. In certain populations, such as the United Arab Emirates (UAE), low nutritional intake of vitamin D, inadequate exposure to sunlight, and cultural dress codes can lead to deficiencies in blood vitamin D levels, predisposing them to musculoskeletal disorders, diabetes, and cardiovascular diseases. There are also notable associations between vitamin D deficiency, physical inactivity, and lower cognitive performance. The aim of this study was to determine how vitamin D status may affect physical inactivity and cognitive performance in a young UAE population. Methods: Primary data were obtained on vitamin D status, cardiorespiratory fitness, body composition, and blood profiles of students in the UAE. Following initial assessment, a cohort of vitamin D-deficient/insufficient individuals participated in a 10-week physical activity intervention (Group A), whilst another cohort was supplemented with 5000 IU vitamin D3 daily and an exercise intervention (Group B). Both groups underwent physiological and biochemical profiling, and the effects of vitamin D supplementation on cognitive function were assessed. Statistical analysis included paired samples t-tests between pre- and post-intervention values and the Wilcoxon signed rank test for within-group comparisons and the Mann–Whitney U test for between-group comparisons. Results: The findings suggest that physical exercise alone improves overall cardiorespiratory fitness, as shown by an increased VO₂ max (p < 0.05), while vitamin D supplementation combined with physical exercise did not significantly improve fitness over a 10-week period (p > 0.05). However, vitamin D combined with physical exercise significantly improved cognitive performance in Group B only, specifically in working memory, verbal memory, and cognitive flexibility (p < 0.05). Conclusions: This study highlights the need for targeted interventions such as physical exercise and vitamin D supplementation to be conducted at an early stage in order to improve physical and cognitive function and reduce the risk of disease. Full article

Background: Thyroid neoplasms exhibit a diverse molecular landscape, and the 2022 WHO classification emphasizes the critical role of molecular profiling in thyroid cancer management; however, comprehensive mutational data from fine-needle aspiration cytology (FNAC) samples using targeted next-generation sequencing (NGS) are still limited, necessitating further investigation to guide clinical practice. Purpose: To characterize the mutational landscape of thyroid neoplasms using targeted NGS of FNAC samples and to assess the clinical implications of molecular profiling. Materials and Methods: This retrospective study included 952 patients with thyroid carcinomaneoplasms who underwent surgery at Sun Yat-sen Memorial Hospital from 2021 to 2023. Preoperative ultrasound, FNAC, and targeted NGS were performed. NGS panels covering 18, 88, and pan-cancer genes were used to analyze FNAC samples. Molecular alterations were correlated with clinical and pathological features. Results: The most frequent mutation was BRAF^V600E (84.45%), followed by RET (6.41%), BRCA1/2 (4.41%) and RAS (4.41%). Patients were categorized into BRAF-like (830 cases), RAS-like (36 cases), high-risk mutations (25 cases), and other mutations (28 cases). High-risk mutations were associated with older age and larger tumor size. BRAF-like tumors had a higher lymph node metastasis rate (58.77%) compared to RAS-like tumors (33.33%). Tumor mutation burden varied significantly among different thyroid neoplasm subtypes. Conclusions: Molecular profiling using targeted NGS of FNAC samples provides valuable insights into the genetic landscape of thyroid neoplasms and has significant clinical implications for diagnosis and personalized treatment strategies. Further validation with paired tumor and plasma samples is warranted. Full article