Biology and Life Sciences

Abstract: Scrapie, a prion disease, is usually considered a protein-only infection. However, the repetitive nature of the protein-containing fibrils of prion disease and other neurodegenerations, including Alzheimer’s and Parkinson’s diseases, has led to the hypothesis that RNA, specifically a repetitive RNA, may be present [1–3]. A publicly available RNA-seq dataset from a previous study of mice infected with scrapie [4], was repurposed to test this hypothesis. Using the software superSTR [5], for detecting repetitive elements in RNA-seq data, repeat expansions were found for the known pathogenic motifs, AGC and AAG, along with other motifs, AAAAC, AAAGG, AAGAG and AGAU, all statistically significant compared to controls, with the Mann-Whitney U-test adjusted for multiple testing. They were present at both early and late time points in the disease. Using AlphaFold 3 [6], single- and double-stranded helical structures were predicted for these repetitive RNAs, with the potential to dysregulate protein translation [7] and trigger an interferon type 1 response [8]. Furthermore, the repetitive RNAs were predicted to bind to the prion protein, PrP. The present results suggest a two-component prion, a combined proteinopathy and RNAopathy, with dual toxicity, and raise the possibility of future new diagnostic tests and treatments for prion disease and other neurodegenerations.

Abstract: Pediatric traumatic brain injury (TBI) is a leading cause of death and disability in children, especially toddlers (~2-3 years old). Despite pediatric TBI’s prevalence, its underlying progression of cellular outcomes are largely extrapolated from adult studies. Notably, axonal injury and acute microglial activation following pediatric TBI remains under-characterized. We addressed this gap by utilizing a central fluid percussion injury (cFPI) model in postnatal day 16-18 male and female rats to investigate axonal injury burden, microglia morphological and Iba-1 fluorescence intensity changes acutely following sham or cFPI in the lateral cortex (CTX), subcortical white matter (SCWM) and thalamus (THAL). Microscopic assessment revealed diffuse axonal injury within the CTX, SCWM, and THAL with different temporal progressions that largely resolved within 1d post-injury. Microglial morphology changed significantly 1h post-injury in the CTX and THAL and 3h post-cFPI in the SCWM. Interestingly, microglial changes generally preceded peak axonal injury burden. These findings demonstrate rapid, region-specific, and temporally distinct microglia activation following diffuse TBI. Additionally, utilizing high-dimensional morphological profiling can define microglia responses in the developing brain, potentially revealing novel therapeutic windows for pediatric TBI intervention.

Abstract: Human Alzheimer’s disease (AD) astrocytes are transcriptionally heterogeneous across brain regions, pathological stages and cohorts, complicating the distinction between reproducible disease signals and dataset-specific effects. We asked whether CREB5, identified by donor-level pseudobulk analysis in SEA-AD middle temporal gyrus (MTG), retained a positive astrocyte association across sequential regional, independent-cohort, confirmatory and prespecified external-validation analyses, and then examined the neuropathological context of this replicated signal. CREB5 was increased in SEA-AD MTG (log2FC 1.203, FDR 0.019), remained positive in SEA-AD dorsolateral prefrontal cortex and both regions of GSE160936, and was independently confirmed in a diagnosis- and target-insulated reanalysis of GSE157827 (log2FC 0.857, P = 3.78×10−5). Three additional accessions were then analyzed under a fixed internal validation plan. GSE188545 supported the association after Holm correction, whereas GSE138852 and GSE174367 yielded smaller, nonsignificant positive estimates. Their prespecified fixed-effect meta-analysis gave a pooled log2FC of 0.678 (95% CI 0.294–1.062; P = 5.36×10−4), with moderate heterogeneity (I² = 58.6%); random-effects sensitivity remained positive. Across six cohorts and eight primary regional or cohort analyses, all eight estimates were positive. After the primary validation sequence was frozen, author-provided sample-level astrocyte data from the five-region AD Progression Atlas (GSE268599; 32 donors) were analyzed with donor as the biological unit. CREB5 was higher in Pathology Groups 3–4 than in Group 1 (donor-level Welch P = 6.19×10−5), and a region-adjusted analysis with donor-clustered standard errors supported the same association (β = 0.379, 95% CI 0.209–0.548; P = 1.16×10−5). Portal-reported correlations with local Aβ plaque or pTau/total-tau burden remained nonsignificant after correction. A separate atlas-scale Malva audit showed heterogeneous CREB5 behavior across additional AD astrocyte studies and was retained as contextual rather than inferential evidence. Together, these findings support CREB5 as a reproducible human AD astrocyte-associated signal with broader neuropathological-stage context, while arguing against a universal effect or a simple linear relationship with local plaque or tau burden.

Abstract: Alzheimer’s disease (AD) and Parkinson’s disease (PD) are usually studied as distinct neurodegenerative disorders, yet both involve molecular changes that extend beyond vulnerable neuronal populations. We asked whether the two diseases share reproducible transcriptional organization across homologous human glial cell classes and whether components of that shared signal are independently represented in retinal and ocular proteomic datasets. We reanalyzed five human single-nucleus RNA-sequencing datasets using donor-level pseudobulk models for astrocytes, microglia, oligodendrocyte precursor cells (OPCs), and oligodendrocytes. Disease effects were estimated and replicated within AD and PD before cross-disease comparison. Across matched genes, AD and PD showed modest but permutation-supported positive effect-vector concordance in all four cell classes. Concordance was strongest in oligodendrocytes (Spearman ρ = 0.253; 60.7% directional agreement), whereas no individual gene survived a conservative AD–PD conjunction FDR criterion. Reactome analysis identified 29 pathways with formal same-direction AD–PD FDR convergence in one glial class and a broader set of 665 pathways with recurrent same-direction enrichment across at least three classes. The recurrent pathway structure exceeded a profile-preserving permutation null (95% interval, 411–476; empirical P = 1.0 × 10⁻⁴), supporting a global excess of recurrent pathway organization without implying significance for every individual recurrent pathway. We then integrated healthy retinal expression, AD retinal proteomics, and PD aqueous-humor proteomics with the brain-concordance results. Of 17,745 genes in the integrated candidate universe, 14,469 were detected in at least two healthy retinal donors. The AD retinal reanalysis tested 4,995 genes and identified 227 nominal and two FDR-significant effects; the PD aqueous-humor reanalysis tested 5,691 proteins and identified 2,713 nominal and 1,803 FDR-significant differences. No candidate reached Class A, which required AD–PD brain concordance, healthy-retinal expression, and FDR-level support in both ocular disease datasets. The highest-ranked multimodal candidates included SCAMP5, XYLB, RABEPK, ITGAM, CD38, CTCF, UBTD2, and NAPEPLD. Together, these results support a distributed, cell-class-dependent molecular architecture shared between AD and PD. Independent retinal and ocular measurements provide an additional layer for prioritizing components of this shared biology, but they do not establish clinically validated retinal or ocular biomarkers.

Abstract: A complex interplay between genes and environmental factors is recognized to contribute to the death of dopaminergic neurons in the midbrain (mDAn) in Parkinson’s disease (PD). Within the known genes associated with PD, there is Leucine-Rich Repeat Kinase (LRRK2), recognized as one most frequent causes of PD, of either familial or sporadic nature. On the other hand, the mechanisms involved in LRRK2 dysfunction that contribute to PD pathogenesis are not defined. Within the environmental factors that are involved in PD pathogenesis, there is the ageing process and inflammatory reactions, as crucial actors participating to the vulnerability to both PD and also LRRK2-PD. Both processes, i.e., ageing and inflammation, can result in increased activation of glial cells, i.e. astrocytes and microglia. Remarkably, earlier and more recent evidence corroborate “a developmental hypothesis” for PD pathogenesis, whereby genes, crucial transcription factors and developmental pathways linked to mDAn vulnerability, interacting with early life events and key hormonal and inflammatory/anti-inflammatory signalling systems, are suspected to play important roles via their expression and/or intimate dialogue with astrocytes, as developed in this work, putting forward the hypothesis that early developmental astrocyte-neuron crosstalk dysregulation may predispose individuals to increased neuronal vulnerability later in life. Of importance, as herein reviewed, the interactions between astrocytes and neurons play a vital role during development as well as in the adult brain. In our laboratory we have been studying for at least thirty years the role, mechanisms and consequences of a physiological or pathological dialogue between mDAns and astrocytes during the development of mDAns, as well as during an inflammatory/oxidative stress response and brain ageing. Here, we aimed at reviewing the evidence in support of a decisive role of LRRK2-diseased astrocytes as predisposing elements for PD susceptibility, asking a. whether and how a malfunction of astrocyte-neuron crosstalk during development might in turn affect dopaminergic neuron vulnerability in adult life; b. what underlying mechanisms of LRRK2-astrocytes are involved ; c. the extent to which astrocyte-microglia maladaptive interactions form part of such dysfunctional interplay; d. what are the consequences for programming the susceptibility of mDAns in adult life and ageing, with their implications for the ongoing understanding of PD pathology and therapeutic developments targeting the dynamics of astrocyte-neuron dialogue.

Abstract: The most famous dataset in behavioral science has never been fitted. Pavlov’s Conditioned Reflexes (1927) reports trial-level salivary measurements from named dogs, yet quantitative associative theory has been parameterized on animal data collected after 1960 while the founding tables are cited as illustrations. Here we transcribe every numerical value stated in the prose of Lecture IV, the extinction lecture, into a page-anchored dataset and compare two model classes on it: single-state erasure, in which nonreinforcement degrades the sole learned trace, and inhibitory write, in which the trace persists intact beneath an accumulating inhibitory state. Four structural signatures reported by Pavlov — invariable spontaneous recovery, dis-inhibition by alien stimuli, extinction beyond zero, and temporary versus permanent restoration — are each unattainable within the single-state class and natural under the inhibitory write, and the lecture’s one exactly anchored contrast identifies the inhibitory decay rate: recovery from 3 to 6 drops across 23 unreinforced minutes requires γ ≈ 0.024 min⁻¹. The founding data of conditioning establish that extinction engages a process beyond monotonic loss of the conditioned trace — the second state Pavlov argued for verbally — and bound its decay rate.

Abstract: The sickness behavior model explains many neuropsychiatric consequences of peripheral inflammation, including fatigue, anhedonia, and depressed mood, but does not account for the marked heterogeneity of presentations across inflammatory disorders, particularly paradoxical positive-polarity manifestations such as euphoria and behavioral disinhibition. We propose the Paroxysmal Network State (PNS), a transient, metastable reconfiguration of large-scale brain networks emerging during inflammatory disease activity through convergent neuroimmune pathways (humoral, vagal, and microglia-mediated signaling), together with the Network Polarity Principle (NPP), which holds that clinical phenotype emerges from the interaction between inflammatory perturbation and the functional identity of the reorganizing neural networks, rather than from inflammatory burden alone. Candidate determinants of individual variability include baseline network architecture, cerebellar circuitry, brain reserve, neuromodulatory and hormonal state, prior inflammatory history, and immunogenetic background. Experimental cerebellar inflammation models demonstrate that inflammatory signaling can induce reversible network reorganization via microglia-mediated changes in intrinsic neuronal excitability. Transdiagnostic neuroimaging evidence across depression, psychosis, rheumatoid arthritis, and multiple sclerosis, together with domain-dissociated behavioral findings in human cerebellar ataxia, provides convergent biological plausibility. We ground the model’s attractor-based account in a levels-of-explanation (supervenience) argument linking network- and clinical-level descriptions, and identify a candidate sustained, non-remitting patient subgroup as an explicit boundary condition. We outline falsifiable predictions spanning longitudinal network dynamics, neurophysiological biomarkers, topographic determination of clinical polarity, and treatment-related reversibility. Rather than replacing existing neuroimmune models, PNS–NPP offers a systems-level hypothesis linking neuroimmune mechanisms to transient network states and network-dependent clinical heterogeneity, generating explicit predictions for experimental testing.

Abstract: The global burden of dementia is heavily concentrated in low- and middle-income countries (LMICs), yet biological diagnosis of Alzheimer’s Disease (AD) relies on positron emission tomography (PET) and cerebrospinal fluid (CSF) analysis that are operationally inaccessible in these regions. The 2024 Alzheimer’s Association revised criteria recognize sufficiently accurate plasma assays,particularly p-tau217,as Core 1 biomarkers that may support biological diagnosis, offering a scientifically credible pathway to infrastructure-light biological detection and staging. However, the machine learning literature has expanded without principled mapping to the AT(N) biological framework or rigorous consideration of deployability constraints in resource limited settings. We present a systematic scoping review synthesizing 146 included full-text publications (2018–2026) across four multidisciplinary evidence streams, establishing a novel architectural taxonomy that maps deep learning architectural families directly to AT(N) biological targets and connects model inductive biases to specific biomarker categories. We audit major AD datasets, identify critical biases in demographic and biomarker representation, and map pervasive data pathologies—label scarcity, missing modalities, scanner heterogeneity, and population bias—to corresponding ML/DL remediation strategies. Finally, we argue for a shift from binary classification toward continuous, biologically anchored disease-burden scoring, proposing the Alzheimer’s Disease Burden Index (ADBI). The ADBI equations presented herein represent a theoretical and architectural framework designed to guide future prospective validation on multi-ethnic cohorts. This work provides a methodological roadmap for developing globally deployable, equity aware AD diagnostic models.

Abstract: Huntington’s disease (HD) is an example of selective neuronal vulnerability. An expansion of the CAG trinucleotide repeat in the huntingtin gene (HTT), present in every cell of the body, drives an early and hierarchical degeneration of the striatal spiny projection neurons (SPNs), predominantly those of the indirect pathway and the striosomal compartment. For two decades, microarrays and bulk tissue RNA sequencing (bulk RNA-seq) defined the regional transcriptional signatures of the disease, but by averaging heterogeneous cell populations they could not assign these changes to defined cell types or separate the net loss of neurons from the dysregulation of the surviving cells. Single-nucleus transcriptomics (snRNA-seq) addressed this limit by providing cellular resolution. With it, the vulnerability of the SPNs was dissected into the collapse of the striosome-matrix axis, more vulnerable subpopulations, and the loss of neuronal identity through bidirectional dysregulation. Glial states that whole-tissue analysis could not separate were also resolved, among them a compensatory astrocytic state and an oligodendroglial maturation deficit, together with neuroimmune mechanisms such as neuronal innate immunity and the recruitment of cytotoxic T lymphocytes. Coupling the transcriptome with per-cell CAG measurement supports a model in which somatic expansion becomes toxic to the neuron only once it crosses a critical threshold, which places it as a temporal determinant of neurodegeneration in the striatal spiny projection neurons. Far from replacing bulk approaches, cellular resolution complements them, because it allows whole-tissue cohorts to be reinterpreted through deconvolution. This review synthesizes these findings and identifies which of them depended on cellular resolution.

Abstract: Formalin-fixed, paraffin-embedded (FFPE) brain tissue is a major archival resource, yet its suitability for high-density DNA methylation profiling is limited by fixation-induced DNA fragmentation and crosslinking. Fresh-frozen (FF) tissue is the gold standard, but its availability is limited, especially for neurodegenerative diseases. DNA methylation was profiled using the Illumina Infinium MethylationEPIC v2 array on paired FFPE and FF brain tissue from 26 donors with neurodegenerative disease (Alzheimer’s disease, Parkinson’s disease, dementia with Lewy bodies, or mixed pathology). After quality control, 50 samples remained, including 24 FFPE–FF pairs (6 matched cortical regions, 18 unmatched regions). Concordance was assessed using Pearson correlations of M-values. Variation across samples was evaluated by Principal Component Analysis (PCA) of the 10,000 most variable CpG sites. Cell-type compositions were estimated using the HiBED R package to deconvolute bulk methylation profiles. FFPE and FF samples showed high concordance (median Pearson r = 0.86). Matched-region pairs had higher correlations (median Pearson r = 0.93) than unmatched-region pairs (p < 0.001. PCA suggested that the preservation method was a major driver of variation, with PC1 explaining 24.2–48.5% of the variance, while PC2 captured additional variation (6.7–14.3%). FFPE samples had higher QC failure rates (26.5% vs. 0%) and elevated probe dropout. Preservation significantly affected cell-type composition, including astrocytes, GABAergic neurons, endothelial cells, and oligodendrocytes (FDR < 0.05), whereas diagnosis had no effect (FDR 0.81–0.98). Overall, FFPE brain tissue showed concordance with FF tissue on the EPIC v2 array. These findings support the use of FFPE brain samples for epigenome-wide association studies, particularly when fresh-frozen cohorts are unavailable. Investigators should account for preservation-related variance, and anatomical matching is recommended.

Abstract: The human visual system is characterized by a sophisticated, parallel processing architecture that begins in the retina and extends through the thalamus to the primary visual cortex and higher-order extrastriate regions. This architecture is fundamentally divided into two major functional streams, the magnocellular (M) and parvocellular (P) pathways. These pathways are not merely redundant transmission lines, but are specialized to handle distinct aspects of visual information, effectively allowing the brain to parse the environment into dynamic spatial frameworks and detailed object identities. The magnocellular pathway is optimized for the detection of motion, depth, and large-scale spatial contrast in the peripheral visual field, whereas the parvocellular pathway is specialized for high-resolution detail and color recognition in the central visual field. Action games, often questioned for their potentially detrimental effects on various human capacities, are here hypothesized to strengthen the magnocellular pathway in particular, which is due to their heavy peripheral field engagement. Twenty-five participants (13 gamers/12 non-gamers) were recruited to participate and get their brain activities recorded during passive viewing of four very simple visual presentations on black background (left white circle, right white circle, simultaneous left and right white circles (bilateral peripheral), and central white circle). In random order, each of these stimuli were presented 50 times for 300ms each. Most interestingly, the mean latency of the N2-ERP component for the condition, in which a left and a right stimulus were presented simultaneously in gamers was 237.77ms, whereas it was 263.36ms in non-gamers. This latency difference turned out statistically significant. On the other hand, the condition, where only one stimulus was presented in the center, did not lead to different latencies (mean latency for gamers was 170.96ms (P170) and for non-gamers it was 165.18ms. It is concluded that gamers show faster processing of bilateral peripheral stimulation than non-gamers, whereas central stimulation leads to comparable processing latencies in both groups.

Abstract: Background: Several recent proposals suggest that myelinated axons may conduct neural signals through a parallel optical or electromagnetic channel — via biophoton emission, cavity-enhanced generation, node-enriched gain chemistry, neuro-antennae, displacement currents, or opsin-based phototransduction — in addition to classical saltatory conduction. Methods: We constructed six independent computational falsification modules, each using measured material constants and deliberately generous upper-bound assumptions: (1) a photon-budget analysis; (2) a full-wave optical transmission sweep through the myelin wall (400 nm–10 um); (3) a Purcell-factor estimate for the myelin cavity; (4) a fluorophore-gain audit of all known neural chromophores; (5) a neuro-antenna radiation and displacement-current decomposition; and (6) an opsin audit across all endogenous photopigments; and (7) a decoherence audit of every quantum claim (thermal occupation, cavity coherence time, vibrational T2 vs emission lifetime). We further quantified the detectability of a hypothetical parallel channel via a stochastic jitter experiment (20,000 trials) and mapped the ephaptic-coupling regime with a two-axon dose-response simulation. Finally, we designed and power-analysed a dual-channel (biophoton-count and gamma-coherence) music-intervention study with head-to-head piece contrasts. Results: All eight constraints falsify an efficient parallel channel: mid-infrared transmission through the myelin wall is approximately 4 x 10^-97 per internode at the C-H stretch band; the Purcell factor is approximately 1.3 x 10^-6 (suppression, not enhancement); every neural fluorophore is a net absorber or at least 2.4 orders of magnitude short of required gain; neuro-antenna radiation is approximately 40 orders of magnitude below the required energy; and no endogenous opsin combines the required presence, kinetics and photon flux; and the thermal emitters' coherence time (approx 1 ps) collapses to essentially zero first-order coherence over any useable path, while lamellar path-length roughness accumulates pi-rad RMS phase error within a fraction of one internode — chaotic, mutually incoherent light carries no phase-locked information. The decoherence audit shows the cavity coherence time (Q/omega, 1-3 fs at biological Q) is approximately 2,000 times shorter than the internode transit, and vibrational T2 (approximately 2 ps) is 10^9 times shorter than the emission lifetime, so any cascade pair is emitted by a fully dephased classical source: the quantum version of the hypothesis is falsified independently of the classical one. A 5% photon-channel contribution is electrically invisible (jitter test), and ephaptic coupling transitions sharply from sub-threshold timing nudges to merged circuits near kappa = 0.1 with no intermediate 'separate-and-fast' window. In the study design, the photon channel requires approximately 10 subjects for 80% power while gamma coherence requires > 60, and head-to-head piece contrasts (sacred vocal vs classical) require 55–113 subjects. Conclusions: Fast parallel signal conduction in myelinated axons is excluded computationally across every physical mechanism proposed to date. What survives — ephaptic synchrony, volume transmission, and externally powered photobiomodulation — are modulatory, not conduction, channels, and we provide a power-quantified design for their experimental study.

Abstract: Background: Open behavioral datasets can be used to ask new questions that were not the primary inferential targets of the source studies. We used two complementary datasets to examine two distinctions relevant to intuitive judgment: whether a self-reported hunch carries more task-relevant information than a self-reported guess, and whether subjective confidence should be treated as equivalent to objective performance or metacognitive efficiency. Methods: This theory-guided, non-preregistered secondary study returned to participant- and trial-level open data rather than relying on published summary statistics. Dataset A was Experiment 2 of Monaghan et al. (22 participants; 6,336 training trials). We recomputed within-participant accuracy for Intuition versus Guess and formally tested adjacent source-attribution contrasts using paired analyses and participant-clustered generalized estimating equations (GEE). Dataset B was the multi_intero dataset of Banellis et al. We directly compared cross-domain correlations in mean confidence with corresponding correlations in metacognitive efficiency (M-ratio) in identical participant sets and tested whether self-reported interoceptive awareness (MAIA) related differentially to cardiac confidence, accuracy, and M-ratio. The datasets were analyzed separately and were not pooled. Results: In Dataset A, Intuition-attributed decisions were more accurate than Guess-attributed decisions (mean difference = 0.146, 95% CI 0.086–0.205; t(21) = 5.12, p < 0.001; dz = 1.09); the adjusted trial-level association was OR = 1.56 (95% CI 1.25–1.96). Exploratory adjacent contrasts were also positive for Recollection versus Intuition and Rule knowledge versus Recollection. In Dataset B, cross-domain confidence correlations exceeded corresponding M-ratio correlations (delta r = 0.448–0.616; all Holm-adjusted p < 0.001). MAIA was associated with cardiac confidence (r = 0.262) but not cardiac accuracy (r = 0.019) or cleaned cardiac M-ratio (r = −0.001), and the correlation differences were significant. Conclusions: These analyses do not validate a unified construct or mechanism of intuition. They provide complementary constraints on its measurement: a reported hunch was not equivalent to a guess in Dataset A, while confidence was not equivalent to objective performance or metacognitive efficiency in Dataset B. Because intuition, confidence, performance, and metacognitive efficiency were not measured jointly in the same task, stronger claims about their within-person architecture require prospective within-task testing.

Abstract: How subjective time arises from experience remains unresolved. We propose TpMT, a measure-theoretic framework grounded in minimal axioms for streams of conscious states. Like the rationals—dense yet of zero measure—countable streams of zero-measure experiences have no duration. Nonzero subjective time requires an uncountable experiential stream with at least countably infinite recurrence of experiential structures. Distinct experiences may densely coexist within the same interval, linking phenomenal multiplicity to the real continuum. TpMT thereby formalizes a necessary structural condition for awareness and provides a criterion for identifying systems that fail to meet it. The theory also yields a structural idempotence law. An exploratory analysis of sleep electroencephalography illustrates its potential for estimating perceived duration.

Abstract: Biophysically detailed neuron models are essential, but they are usually built from a single best-fit parameter set, obscuring a fundamental problem. Much of the model is set by the modeler's choices, not by the data, and many different parameter sets fit the data equally well. Thus, a single best-fit model represents only one point in a much larger space of models the data allow. For claims about robustness, transferability across cell types or species, natural variability, or prediction, we argue that a family of models is needed, one that openly carries its uncertainty. We review recent advances that may make this practical: a clearer understanding of parameter degeneracy; new single-cell methods that measure a neuron's activity, shape, and gene expression together; and new tools that estimate uncertainty, identify the parameters that matter, and accelerate fitting. Finally, we propose sharing reusable model components, qualified reference components, that come with their uncertainty, tested limits, and origin, so that larger brain models can stay trustworthy.

Abstract: Background: Autism spectrum disorder (ASD) is a neurodevelopmental condition with substantial genetic contributions but incompletely understood biological mechanisms. Family history of autoimmune disease is associated with elevated ASD likelihood (pooled OR 1.28), while maternal immune-mediated conditions show additional associations, suggesting that inherited immune susceptibility and the gestational inflammatory environment may contribute to risk. A mechanism linking these observations to the characteristic developmental trajectory of ASD remains unresolved.Hypothesis: I propose an immune-metabolic framework in which multiple pro-inflammatory cytokines—including TNF-α, IL-6, IL-1β, and IFN-γ—act through distinct molecular pathways yet converge on mitochondrial dysfunction and an ATP supply that cannot meet the developing brain's energy needs. Within this framework, cumulative prenatal inflammatory burden, rather than any single cytokine, drives the energy deficit. Potential contributors include inherited immune susceptibility and fetal exposure to maternal inflammatory signaling arising from a clinically silent but biologically consequential chronic low-grade state. The resulting energy constraint may disrupt synaptic refinement, real-time social processing, synaptic protein synthesis, and flexible predictive inference—the last offering a bioenergetic interpretation of restricted repetitive behaviors and insistence on sameness as compensation for chronic energy limitation. Crucially, the mitochondrial dysfunction is proposed to persist beyond birth, with the gap between cerebral energy demand and supply widening during the rapid brain growth of the first postnatal years. This trajectory may help explain the emergence of clinical symptoms between 12 and 24 months of age, the selective vulnerability of metabolically demanding brain regions, and the regressive pattern seen in a substantial subset of children. The framework further proposes that the reported firstborn association may partly reflect incomplete maternal immune adaptation during first pregnancies.Implications: By uniting prenatal initiation with postnatal persistence into a single developmental trajectory, this framework offers an integrative account of otherwise disparate observations. It also yields directly testable predictions—prospective measurement of maternal cytokine and infant mitochondrial trajectories, registry analysis of partner change and birth order, and cerebral energy metabolism in relation to insistence-on-sameness severity—that could distinguish the proposed mechanism from competing explanations.

Abstract: Background/Objectives: Migraine is three times more common in women and worsens during perimenopause, a phase in which estrogen fluctuations are accompanied by deterioration in body composition — increased fat mass (FM) and reduced fat-free mass (FFM) — amplifying systemic inflammation. Despite this biological link, body composition is not systematically assessed in perimenopausal migraine management. This pre-specified exploratory analysis of the MEDEA study evaluates whether body composition, measured by bioelectrical impedance analysis (BIA), is associated with migraine disability in perimenopausal women, and secondarily describes changes in body composition during an anti-inflammatory nutritional intervention with prebiotics and probiotics. Methods: Single-arm, single-center, prospective interventional study (MEDEA study, Neurological Clinic ASUFC, Udine); the present work is a pre-specified exploratory secondary analysis. Seventeen women (mean age 52 ± 2.6 years) with episodic or chronic migraine, intestinal dysbiosis, and perimenopausal status (STRAW classification) were assessed with Akern BIA at baseline (T0), 3 months (T3), and 6 months (T6). Changes over time were analyzed with the Wilcoxon signed-rank test; correlations with migraine disability with Spearman's rho. Results: Over the intervention period, FM decreased selectively (median −1.60 kg at T3, p = 0.001; median −3.00 kg at T6, p < 0.001), with FFM remaining broadly stable. At baseline, higher FFM correlated with lower migraine disability (MIDAS: rho = −0.667, p = 0.009, n = 14). Longitudinal Δ-Δ associations (ECW, phase angle) are reported as exploratory. Conclusions: These exploratory findings suggest that fat-free mass is associated with migraine disability in perimenopause and warrant confirmation, with multivariable adjustment, in the complete sample (n = 54).

Abstract: Background/Objectives: T Lymphocyte-Secreted Protein I-309, also known as CC-motif Chemokine Ligand 1 (CCL-1), is a small glycoprotein produced by immune cells in response to infection or tissue injury. Increased circulating levels of CCL-1 have been reported in individuals with mild cognitive impairment and Alzheimer's disease (AD), suggesting a potential role in neuroinflammatory processes. However, the effects of CCL-1 on brain physiology remain poorly understood. Methods: Adeno-associated virus (AAV) vectors overexpressing CCL-1 or vector control were injected into the stratum radiatum (CA1) of 250 g Sprague- Dawley rats. Three weeks after inoculation, animals were euthanized or subjected to behavioral testing. BrdU was administered in a subset to label dividing cells. Hippocampal cell populations were assessed by immunohistochemistry using Iba-1, NeuN, GFAP and BrdU antibodies. Locomotion, learning and memory were evaluated using open field, novel object recognition and contextual fear conditioning. Results: CCL-1 overexpression resulted in a significant reduction in microglial population in stratum radiatum, and a significant increase in BrdU+ maturing neurons in the dentate. Neuronal and astrocyte populations and behavioral assays were not significantly affected by CCL-1 overexpression. Conclusions: These findings suggest that CCL-1 overexpression modulates hippocampal cellular composition, potentially exerting anti-inflammatory and neuroprotective effects without measurable changes in cognitive performance of learning and memory. This chemokine may therefore represent a potential mediator of neuroimmune interactions relevant to neurodegenerative processes.

Abstract: Launched in 2010 by the National Institutes of Health, the Human Connectome Project (HCP) represents a foundational initiative in systems neuroscience, designed to map the structural and functional architecture of the human brain. Despite its extensive impact, the expanding body of HCP-related research remains methodologically and thematically dispersed. To systematically assess this landscape, we conducted an AI-assisted, intensive review and systematic synthesis of 102 peer-reviewed publications that explicitly referenced the HCP. Using a hybrid computational-human analytic framework integrating natural language processing and manual validation, studies were categorized into six domains: cognition and learning, aging and development, mental health, neurological disorders, movement and motor skills, and behavior and personality. Quantitative and qualitative analyses revealed three dominant trends: (1) inter-individual connectivity patterns exhibit high stability, supporting their utility as neural fingerprints; (2) higher-order association networks undergo postnatal maturation and exhibit age-related decline, confirming lifespan-dependent reorganization; and (3) connectomic measures increasingly function as candidate biomarkers for neuropsychiatric and neurodegenerative disorders, including schizophrenia, Alzheimer's disease, and depression. Critical evaluation identified persistent methodological constraints, including limited spatial resolution in neuroimaging modalities, high attrition and cost in longitudinal paradigms, and data privacy risks associated with large-scale neuroinformatics. This synthesis demonstrates that while the HCP has substantially advanced mechanistic models of human brain organization, future progress will depend on integrating multimodal imaging with computational and AI-driven analytic frameworks. Our review shows that such advancements are essential to overcome current technical limitations and enable precision-level mapping of brain connectivity in health and disease.

Abstract: The future of developmental population neuroscience lies in transforming the brain’s life landscape into personalized, context‑sensitive, and actionable predictions.