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Quantification of appetite-regulating hormones in children with hypothalamic and common obesity.

CONTEXT: The pathophysiology of hypothalamic obesity (HyOb) remains incompletely understood with no effective treatments. OBJECTIVE: We examined differences in appetite-regulating hormone concentrations between patients with HyOb, common obesity, and lean controls. DESIGN: Multiway cross-sectional case-control study of patients aged 2 through 19 years. SETTING: Two tertiary pediatric endocrinology centers. PATIENTS: Cases were obese (body mass index [BMI] > +2 SD score [SDS], "HyOb") and lean ("HyLean") patients with congenital (septo-optic dysplasia) or acquired (suprasellar brain tumor) hypothalamic disorders. Controls had common obesity ("Ob") or nonhypothalamic disorders and normal BMI ("Lean"). MAIN OUTCOME MEASURES: Relationships between the Dykens' Hyperphagia Questionnaire Score (DHQS), plasma or serum concentrations of leptin, insulin, α-melanocyte stimulating hormone (αMSH), brain-derived neurotrophic factor, oxytocin, acylated ghrelin, agouti-related peptide and copeptin, and BMI SDS. RESULTS: Dykens' Hyperphagia Questionnaire Score did not differ between HyOb and Ob patients (24 [17-34] vs 24 [18-31]) but correlated with BMI SDS in patients with hypothalamic disorders (P = 0.02). HyOb and Ob patients exhibited similarly increased anorexigens (insulin, leptin) and decreased orexigens (ghrelin, agouti-related peptide) compared to HyLean and Lean patients. The rate of BMI increase was independently associated with lower αMSH (β = -0.23 [-0.36 to -0.11], P = .0007) and ghrelin (β=-0.004 [-0.01 to 0.00], P = .001) concentrations, suggesting that αMSH replacement may be a therapeutic target for HyOb. HyLean patients demonstrated intermediate insulin responses to glucose compared to other subcohorts. CONCLUSION: In our cohort, patients with HyOb appeared indistinguishable from Ob in terms of their appetite and appetite-regulating neuroendocrine circuitry. Higher αMSH concentrations are associated with reduced weight gain and may be a target for therapeutic intervention.

alpha-MSH

Compound muscle action potential amplitudes in newborn screen positive spinal muscular atrophy.

OBJECTIVE: To evaluate the utility of compound muscle action potential (CMAP) amplitudes as biomarkers of disease severity in newborn screening (NBS)-positive infants with spinal muscular atrophy (SMA). METHODS: We conducted a retrospective review of 21 infants identified through SMA NBS (11 with 2 SMN2 copies and 10 with 3 SMN2 copies). Baseline and serial right median, ulnar, and fibular motor nerve CMAP amplitudes (millivolts, mV) were obtained during the study. Functional outcomes were assessed using the Children's Hospital of Philadelphia Infant Test of Neuromuscular Disorders (CHOP-INTEND). RESULTS: At baseline, infants with 2 SMN2 copies demonstrated significantly lower median, ulnar, and fibular CMAP amplitudes compared with infants with 3 SMN2 copies (p&#xa0;<&#xa0;0.05). In contrast, baseline CHOP-INTEND scores did not differ significantly between the two groups. Prior to genetic confirmation, a right median CMAP amplitude&#xa0;&#x2265;3.2&#xa0;mV predicted&#xa0;&#x2265;3 SMN2 copies. Following treatment, right median and fibular CMAP amplitudes demonstrated significant improvement over time, including in analyses accounting for SMN2 copies number. CONCLUSION: CMAP amplitudes obtained from multiple upper- and lower-extremity motor nerves provided objective electrophysiological measures that distinguished infants with two versus three SMN2 copies, despite similar baseline CHOP-INTEND scores. Furthermore, CMAP abnormalities were detectable in some cases before confirmatory genetic testing results became available. Serial CMAP measurements demonstrated significant longitudinal changes following treatment, whereas functional assessments approached ceiling values, supporting the potential value of electrophysiological monitoring in the era of disease-modifying therapies. SIGNIFICANCE: CMAP assessment is a useful adjunct in the evaluation of infants identified through SMA NBS.

Humans

Life-course stress exposure and cognitive decline in middle-aged and older Chinese adults: The role of sex differences and educational protection.

BACKGROUND: Stressful life events (SLEs) across the life course have been associated with cognitive decline, but evidence on their cumulative impact and potential modifiers remains limited. We aimed to examine the associations between SLE exposure in childhood, adulthood, or both life stages and cognitive trajectories, and to investigate whether these associations vary by sex and education. METHODS: We used data from the China Health and Retirement Longitudinal Study, a nationally representative cohort of adults aged &#x2265;45 years. Participants with complete data on SLEs, cognition, and covariates were included (n&#x202f;=&#x202f;5922). SLEs were retrospectively assessed for childhood and adulthood. Cognitive function was measured using a composite score (range 0-21) across three waves (2011-2015). Linear mixed-effects models examined longitudinal associations, adjusting for sociodemographic factors, health behaviors, and chronic conditions, with interaction analyses for sex and education. RESULTS: Compared with participants reporting no SLEs, cumulative exposure showed the strongest association with cognitive decline (&#x3b2;&#x202f;=&#x202f;-0.52, 95% CI -0.69 to -0.35), followed by childhood-only (&#x3b2;&#x202f;=&#x202f;-0.34, -0.48 to -0.20) and adulthood-only exposure (&#x3b2;&#x202f;=&#x202f;-0.22, -0.37 to -0.07). Sex significantly moderated the associations for childhood and cumulative exposure, with women exhibiting greater cognitive vulnerability. Higher educational attainment attenuated the associations between single-period stress and cognitive decline, with only partial protection observed against cumulative adversity. CONCLUSION: Cumulative life-course stress is associated with accelerated cognitive decline in Chinese middle-aged and older adults. Women appear more vulnerable to stress-related cognitive effects, whereas higher education confers partial resilience, highlighting the need for sex-sensitive and education-informed prevention strategies.

Humans

Wearable Sleep Monitoring in Pediatric Acute Lymphoblastic Leukemia: Associations With Subjective Sleep Ratings and Neurocognitive Functioning.

BACKGROUND: Sleep disturbances are associated with increased fatigue, reduced quality of life, and neurocognitive dysfunction and have emerged as a common complication among pediatric cancer survivors. Sleep disturbances are particularly concerning given their potential to exacerbate existing neurocognitive impacts of cancer treatments. This pilot study examined the feasibility and acceptability of a home-wearable EEG-based sleep device (Sleep ProfilerTM) for acute lymphoblastic leukemia (ALL) survivors as well as associations between specific sleep parameters and neurocognitive functioning. PROCEDURE: Children (ages 8-12; M = 10 years, SD = 1.6; N = 23) >6 months post-treatment for ALL were enrolled at clinical visits and wore the Sleep ProfilerTM for two consecutive nights at home, followed by neurocognitive testing of attention, inhibitory control, working memory, and processing speed. Parents completed subjective measures of child sleep, anxiety, depression, and acceptability. Feasibility reflected the percentage of children wearing the device at least one night and the percentage of nights with good EEG quality data. RESULTS: All participants wore the device both nights, with 84% meeting the threshold for good quality measurement. Few children met recommended quantity and quality sleep thresholds based on objective measurement, including 5 patients with elevated snoring levels; 43.5% of subjective ratings fell above the threshold for sleep disturbance. Greater sleep latency was associated with worse inhibitory control (r = -0.42, p = 0.046), and total sleep time was positively associated with inhibitory control and attention. CONCLUSIONS: Findings confirm the feasibility and acceptability of home EEG sleep monitoring in school-age survivors, and associations of sleep latency and snoring with reduced neurocognitive functioning may offer modifiable risk factors for aspects of neuropsychological dysfunction common in pediatric survivorship. CLINICAL TRIAL REGISTRATION: At the time this study was conducted, we were not required to register the study on ClinicalTrials.gov. It was a single-institution feasibility study without intervention, which was not considered a clinical trial.

Humans

Deimplementation of inappropriate feeding practices in early care and education: a Hybrid Type 3 cluster-randomized trial.

BACKGROUND: The science of deimplementation-reducing harmful or ineffective practices-has focused almost exclusively on clinical prescribing, with no studies conducted in community or educational settings. Early care and education (ECE) settings offer a strategic venue for shaping eating behaviors, with children consuming up to 500 meals annually in these environments. However, ECE educators routinely use feeding practices that undermine self-regulation, including pressuring children to eat, rushing mealtimes, and offering food as reward. These practices contribute to food aversions, diminished self-regulation, and obesity risk. METHODS: We will conduct a Hybrid Type 3 cluster-randomized trial evaluating a co-designed deimplementation strategy package (WISE Words) across 88 ECE sites in Arkansas and Louisiana. Sites will be randomized 1:1 to WISE Words or usual practice, with usual practice sites receiving the intervention after two years (waitlist design). WISE Words includes six strategies: dynamic training using improvisation methods, peer learning collaboratives with goal setting, external facilitation, audit and feedback, environmental reminders, and tailored educational materials. The primary outcome is de-adoption of inappropriate feeding practices measured via direct mealtime observation (Table Talk). Secondary outcomes include adoption of evidence-based practices, acceptability, appropriateness, and sustainability at 12- and 24-months post-intervention. Child outcomes include Body Mass Index, skin carotenoid levels (Veggie Meter) willingness to try new foods (observed) and food neophobia (teacher and caregiver report). An explanatory sequential mixed methods design will test mechanisms of change derived from the Implementation Trust Building Theory of Change examining whether trust mediates strategy effects on outcomes. DISCUSSION: This trial extends deimplementation science into community settings by targeting culturally embedded behavioral practices rather than clinical prescribing behaviors. Results will inform approaches to shifting entrenched practices in ECE and similar settings while testing trust as a deimplementation mechanism. Sustainability assessments will address a notable gap, as few studies have examined whether deimplementation effects persist. TRIAL REGISTRATION: NCT07101321, July 20, 2025.

Humans

Osimertinib With or Without Chemotherapy in Advanced Non-Small Cell Lung Cancer With EGFR and Concurrent TP53 Mutations: A Randomized Clinical Trial.

IMPORTANCE: Combination therapy has emerged as a promising therapeutic approach for patients with epidermal growth factor receptor (EGFR)-mutated non-small cell lung cancer (NSCLC). However, its clinical benefit-risk profile remains a focus of ongoing debate. Identifying patients most likely to derive benefit from such regimens remains an unmet clinical need. OBJECTIVE: To prospectively compare the efficacy and safety of first-line osimertinib plus chemotherapy with osimertinib monotherapy for patients with EGFR-mutated advanced NSCLC harboring concurrent TP53 mutations. DESIGN, SETTING, AND PARTICIPANTS: A multicenter, randomized, open-label, phase 3 study conducted at 17 sites in China. Between March 25, 2021, and July 11, 2024, a total of 294 eligible patients with treatment-naive, stage IV or recurrent nonsquamous NSCLC harboring concurrent TP53 and EGFR-sensitizing mutations were enrolled. INTERVENTIONS: Patients were randomized (1:1) to receive osimertinib plus chemotherapy (pemetrexed and carboplatin every 3 weeks for 4 cycles, followed by maintenance therapy of osimertinib plus pemetrexed; n&#x2009;=&#x2009;146) or osimertinib monotherapy (n&#x2009;=&#x2009;148). MAIN OUTCOMES AND MEASURES: The primary end point was investigator-assessed progression-free survival. Secondary end points included overall survival, response, safety, and quality of life. RESULTS: Among 294 enrolled patients, the median age was 57 years (range, 26-79 years), and 159 (54.1%) were female. The data cutoff date was November 11, 2025. At a median follow-up of 25.1 months for the osimertinib-chemotherapy group and 26.1 months for the osimertinib monotherapy group, median progression-free survival was significantly longer with osimertinib plus chemotherapy than with osimertinib monotherapy (34.0 vs 15.6 months; difference, 18.4 months [95% CI, 9.9-22.3]; hazard ratio, 0.44 [95% CI, 0.32-0.60]; P&#x2009;<&#x2009;.001). This benefit was consistent across prespecified subgroups, including those with brain metastases and L858R mutations. The overall survival data remained immature (30.6% maturity); however, a trend toward overall survival benefit with combination therapy was observed. The incidence of grade 3 or higher treatment-related adverse events was higher in the combination group, with no new safety signal identified. CONCLUSIONS AND RELEVANCE: In this randomized clinical trial, osimertinib plus chemotherapy significantly increased progression-free survival among patients with EGFR-mutated advanced NSCLC harboring concurrent TP53 mutations. These findings provided a clinical rationale for individualized combination strategies in the management of patients with EGFR-mutated NSCLC. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04695925.

Adult

Accurate quantification of canine mitochondrial DNA copy number from canine blood and brain samples.

Acute brain injury is difficult to evaluate in veterinary medicine and tools to investigate the potential involvement of mitochondrial involvement are limited. The brain is highly enriched in mitochondria and contains thousands of copies of mitochondrial DNA (mtDNA) per cell, but robust methods for quantifying mitochondrial DNA copy number (mtDNA-CN) in canine tissues are lacking. We describe the development of a quantitative real-time PCR assay for absolute measurement of mtDNA-CN which was validated in canine blood and brain tissue. To minimize amplification of nuclear mitochondrial insertion sequences (NumtS) and repetitive regions, species-specific oligonucleotide primers were designed following in silico genomic filtering. The assay was applied to a small pilot cohort comprising blood samples from dogs with and without acute brain injury (n&#xa0;=&#xa0;4-6 per group) and cerebral cortex samples (n&#xa0;=&#xa0;1 per group) to assess feasibility and biological plausibility. In non-brain injury dogs, blood mtDNA-CN ranged from 98 to 288 copies per nuclear genome (mean 193&#xa0;&#xb1;&#xa0;72), while values in brain-injured cases ranged from 163 to 228 copies per genome (mean 200&#xa0;&#xb1;&#xa0;33). Cerebral cortex samples exhibited higher mtDNA-CN than blood, consistent with known tissue-specific mitochondrial enrichment. In a single brain-injured case with serial sampling, mtDNA-CN increased over five days. This study presents a validated assay and pilot data for mtDNA-CN quantification in canine samples. While not powered for biomarker evaluation, this method may enable future studies of mitochondrial dynamics in canine brain injury and metabolic disease.

Animals

The role of artificial intelligence in the diagnosis and prognosis of traumatic brain injury based on brain CT scans: a systematic review.

Traumatic brain injury (TBI) is a leading cause of emergency department visits and a major contributor to injury-related mortality and long-term neurological disability. Non-contrast computed tomography (CT) is the gold-standard imaging modality for the rapid diagnosis of TBI. Clinical outcomes depend strongly on early detection and prompt acute management. Artificial intelligence (AI)-based models may support faster automated identification of traumatic findings and early prediction of patient prognosis.&#xa0;A systematic literature search was conducted in PubMed/MEDLINE, Scopus, IEEE Xplore, ACM Digital Library, and the Cochrane Library in accordance with PRISMA 2020 guidelines to evaluate AI-based models for automated detection of TBI-related findings on CT and for prediction of clinical outcomes. Risk of bias and applicability were assessed using QUADAS-2 for diagnostic accuracy studies and PROBAST&#x2009;+&#x2009;AI for prediction model studies.&#xa0;Twenty-two studies were included. Sixteen studies evaluated diagnostic tasks and 10 evaluated prognostic outcomes, with four studies contributing to both categories. Diagnostic performance was generally high, with many studies reporting AUC values approaching or exceeding 0.90, particularly for larger lesion volumes.Prognostic performance was more variable, with moderate to high discrimination and substantial heterogeneity. Only 9 studies incorporated independent external validation, and performance was frequently lower in external cohorts. All prognostic model studies were judged to be at high overall risk of bias using PROBAST&#x2009;+&#x2009;AI, and most diagnostic accuracy studies also demonstrated high or unclear risk of bias in at least one QUADAS-2 domain, most frequently in patient selection.&#xa0;AI-based models applied to brain CT demonstrate strong technical performance for both diagnostic and prognostic tasks in TBI. However, most studies relied on retrospective designs and lacked independent external validation which limits models generalizability and raises concern for potential overfitting. Prospective, multicenter studies with standardized methodologies and rigorous external validation are required before widespread clinical implementation.

Humans

A systematic review of macaque brain stimulation: Trends and future directions.

Neurostimulation techniques can powerfully modulate neural circuit activity and provide causal insights into the relationship between brain function and behavior. Macaque monkeys have long been a key animal model for brain stimulation studies. While stimulating the macaque brain with one or a few electrodes has already taught us much about brain function and dysfunction, recent technological advances promise a future with more precise stimulation using many more electrodes. However, such possibilities also increase the number of choices an experimenter has when designing their study. We can learn from a rich past, but a comprehensive overview of which brain regions have been studied and with what stimulation parameters is lacking. Here, we present a PRISMA-compliant systematic review of 734 macaque brain stimulation studies using electrical and/or optogenetic stimulation. We find a striking bias in which brain areas have traditionally been stimulated: a mere 10 brain regions account for half of all studies, with the remainder of studies investigating approximately 150 other areas. Across studies, stimulation frequency robustly predicted direct behavioral effects independent of brain region, while amplitude did not. Future studies could more systematically explore less studied regions through lower stimulation frequencies (e.g., 20-50&#x202f;Hz) alongside established ranges (&#x223c;200&#x202f;Hz). Tools such as fMRI or optical imaging can capture neural circuit engagement evoked by these frequencies, even when behavioral effects are absent or remain subtle. Our synthesis offers a guide towards the next steps in high-channel-count, high-precision stimulation approaches.

Animals

Somatic mutations: recent advances in brain aging and neurodegeneration.

Somatic mutations are genetic variants that occur after the single-cell phase of development and have been implicated in disease pathogenesis. While most DNA lesions are detected and repaired, examination of healthy tissue has revealed that some lesions escape repair, leading to somatic mutations that accumulate at a consistent rate, including in human brain tissue and postmitotic neurons. Emerging methodological and analytical advances have revealed the presence of persistent mutagenic mechanisms during healthy brain aging as well as mutational pattern shifts in the context of neurodegenerative diseases. Here, we highlight recent methodological advances, summarize our current understanding of somatic mutagenesis in neurotypical brain aging, and examine the role of somatic mutations in neurodegenerative diseases.

Humans

Origins and timing of somatic variants in the brain.

Somatic variants accumulate in human brain cells throughout the lifespan. Variant allele fraction has traditionally been used as a proxy for both the developmental timing of somatic variants and their functional effect, based on the assumption that earlier mutations are shared by larger cell populations and therefore have greater potential for severe phenotypes. However, recent discoveries challenge this simplified model. Variables such as developmental bottlenecks, lineage restriction, and cellular and molecular context play critical roles in shaping the distribution and functional impact of somatic variants in the brain. These insights support a shift toward a context-dependent framework for interpreting somatic mosaicism.

Humans

Strategies for mosaic variant calling in brain disorders.

The human brain is a genomic mosaic, where postzygotic mutations arising from embryogenesis to senescence drive diverse neurodevelopmental and neurodegenerative diseases. Because of numerous sequencing artifacts at ultralow variant allele frequencies (VAFs), detecting these variants remains a significant analytical challenge. This review focuses on single-nucleotide variants and small indels, summarizing current strategies for aligning sampling methods, including bulk, laser capture microdissection, and single-cell genomics, with the expected clonal architecture of the brain. It emphasizes that mosaic detection sensitivity is fundamentally constrained by sequencing depth, since even the most advanced algorithms cannot identify variants not physically represented in the sequencing library. The review further recommends the selection of variant calling algorithms based on validated VAF detection performance, matching tools like MuTect2 and MosaicForecast to their optimal performance ranges. Furthermore, we discuss how multitissue sampling, as emphasized by the SMaHT project, addresses the matched-control dilemma and supports accurate variant classification via cross-tissue VAF gradients. Integrating these established pipelines with multiomics modalities, including transcriptomic and epigenetic data, could advance the field toward a functional understanding of how the somatic genome impacts human brain health and disease.

Humans

Analysis of the Relationship between Early Clinical Factors and Glasgow Outcome Scale in Patients With Traumatic Brain Injury.

OBJECTIVE: This study aimed to evaluate the association between early clinical factors and the Glasgow outcome scale (GOS) in patients with traumatic brain injury (TBI). METHODS: We conducted a retrospective analysis of 98 TBI patients who underwent emergency surgery between January 2021 and January 2024. Based on GOS scores at 6 months post-surgery, patients were classified into a favorable outcome group (GOS&#xa0;&#x2265;&#xa0;4, defined as moderate disability or good recovery,&#xa0;n = 58) and an unfavorable outcome group (GOS < 4, i.e., death, persistent vegetative state, or severe disability,&#xa0;n = 40). Baseline and early clinical parameters were compared between groups. Statistically significant variables from univariate analysis were entered into a multivariate logistic regression model to identify independent prognostic factors. RESULTS: Significant intergroup differences were observed in age, time from injury to surgery, bleeding site, midline shift, Glasgow coma scale (GCS) score at admission, blood glucose level, and D-dimer level (all p < 0.05). Multivariate analysis confirmed that age, time from injury to surgery, GCS score, blood glucose, and D-dimer level were independent predictors of GOS (all p < 0.05). CONCLUSION: Early clinical factors, including age, time to surgery, GCS score, blood glucose, and D-dimer level, independently influence GOS in TBI patients. Time from injury to surgery&#xa0;emerged as a potentially modifiable factor in this cohort, suggesting that minimizing delays may improve outcomes.

Humans

Epigenetic drift and LINE-1 activation in aging brain: Implications for neurodegenerative disease.

Brain aging and age-associated neurological diseases, such as Alzheimer's Disease (AD), Parkinson's Disease (PD), and Amyotrophic Lateral Sclerosis (ALS), are largely attributed to epigenetic drift which is characterized by the gradual accumulation of alterations in neural cell methylation patterns over time. These methylation changes are particularly evident in transposable element (TE)-derived sequences such as Long interspersed element-1 (LINE-1) which comprises approximately 17% of the human genome. During aging, LINE-1 elements gradually lose their methylation, as well as the regulatory safeguard mechanisms that usually keep them inactive. This repression loss can lead to LINE-1 reactivation, contributing to harmful effects including genomic instability, neuroinflammation, and more. Together these findings indicate that impaired epigenetic maintenance, especially in repetitive genome regions, plays a key role in biological aging of neurons and glial cells. In this narrative review, we discuss the methylation dynamics and regulatory mechanisms of LINE-1 retrotransposons, their activation processes during aging, and contribution to age-associated neurological diseases. We also highlight the potential of targeting LINE-1 methylation to restore methylation homeostasis, epigenetic stability and delay brain aging.

Humans

The interplay between circadian misalignment or sleep disturbances and cognition and brain function in individuals with different degrees of insulin resistance - a systematic review.

Disruption of sleep increases the risk of type 2 diabetes and worsens cognitive outcomes, yet few studies have evaluated the interaction between insulin resistance and sleep parameters in relation to cognitive outcomes or the risk of dementia. This systematic review examines how circadian misalignment and sleep disturbances affect cognition and neuroimaging findings in individuals with varying degrees of insulin resistance. Across 27 studies, disrupted circadian rhythmicity and sleep disturbances were negatively associated with brain health, possibly through its effects on insulin sensitivity, whereas the impact of sleep duration and quality were inconclusive. Methodological heterogeneity, reliance on cross-sectional designs, and limited control for confounders restricted definitive conclusions and highlighted the need for longitudinal and interventional studies with objective measurements. Nonetheless, the findings support circadian rhythmicity as a potentially modifiable risk factor for preserving cognition in insulin-resistant populations. Future research should prioritise prospective and interventional studies and focus on biological markers rather than self-reported outcomes.

Humans

Applications of quantum AI in brain disorder diagnosis: A systematic review.

BACKGROUND AND OBJECTIVE: Brain disorder diagnosis and prediction remain challenging because neuroimaging, electrophysiological, behavioral, and multimodal data are high-dimensional, noisy, heterogeneous, and limited by small clinical cohorts. This systematic review synthesised applications of quantum artificial intelligence (QAI) for brain disorder diagnosis, prediction, detection, and monitoring. METHODS: Following PRISMA guidelines, studies published from 2016 to 13 January 2026 were retrieved from Scopus, Web of Science, and IEEE Xplore. After screening, 36 studies met the eligibility criteria and were qualitatively analysed according to disorder category, data modality, QAI method, implementation setting, validation strategy, and performance. RESULTS: At the broader disease-group level, neurodegenerative disorders were the most frequently investigated, followed by mental health and psychiatric disorders. At the individual level, Parkinson's disease and schizophrenia were the leading applications, followed by depression, anxiety, Alzheimer's disease, and stress-related tasks. MRI-based modalities were the most frequently used data source, followed by multimodal data and EEG. Methodologically, primary QAI approaches were dominated by quantum neural and QDL architectures, followed by quantum-inspired optimization or feature-selection methods and quantum-kernel/conventional QML classifiers. Qiskit/IBM Quantum and PennyLane were the most frequently reported quantum software frameworks. However, most studies relied on simulators, classical quantum-inspired implementations, or unclear implementation settings, with limited real-hardware evaluation. CONCLUSIONS: QAI shows emerging potential for brain disorder analysis, particularly through hybrid quantum-classical learning, quantum neural architectures, quantum-kernel methods, and quantum-inspired optimization. Nevertheless, current evidence remains preliminary and requires larger datasets, subject-level and external validation, fair classical benchmarking, noise-resilient circuits, real quantum hardware evaluation, explainability, and clinical validation.

Humans

Brain network alterations underlying cue reactivity and craving in abstinent methamphetamine users: a systematic review of functional MRI findings.

BACKGROUND: Methamphetamine use disorder (MUD) is marked by intense craving and high relapse risk, often triggered by drug-related cues. Functional magnetic resonance imaging (fMRI) provides key insight into the neural basis of this cue reactivity, implicating large-scale brain networks for reward, motivation, and control. Yet, findings remain inconsistent across studies due to differences in task design, abstinence duration, and participant characteristics. OBJECTIVE: This systematic review synthesises evidence on how abstinence influences brain network alterations underlying cue reactivity and craving in methamphetamine users, integrating task-based and resting-state fMRI findings within leading neurobiological models of addiction. METHODS: A systematic search of PubMed, Scopus, Web of Science, and Ovid was conducted up to August 10, 2025, following PRISMA 2020 guidelines. Eligible fMRI studies examined cue reactivity or craving in abstinent methamphetamine users. Data were extracted on activation, connectivity, and brain-behaviour associations, and synthesised narratively. RESULTS: Task-based studies revealed heightened activation across reward, salience, and control networks during cue exposure, which diminished as parietal and executive control systems re-engaged with longer abstinence. Resting-state findings showed disrupted intrinsic connectivity among default mode, salience, and frontoparietal networks, reflecting persistent imbalances linked to craving and use severity. CONCLUSION: fMRI evidence shows that MUD is marked by network-level disruption linking reward, salience, and control systems. Task-based findings reveal strong cue reactivity in reward circuits, while resting-state data show persistent imbalance among default mode and control networks. With abstinence, partial restoration of network integrity emerges, highlighting both vulnerability and opportunities for targeted, recovery-based interventions.

Humans

Height variation independent of known genetic variants and health in later life: a cohort study.

BACKGROUND: Adult-attained height is associated with later-life health, but it reflects both genetic and nongenetic influences. The health implications of height variation not explained by known common height-associated genetic variants remain unclear. OBJECTIVES: This study aimed to examine associations of residual height (height variation independent of known genetic variants) with multiple disease incidence and all-cause mortality in later life. METHODS: In this cohort study of 407,366 adults of European ancestry (aged 40-70 y) in the United Kingdom Biobank (2006-2010), sex- and age-specific genetically predicted height was estimated from 9863 height-associated variants, adjusted for 30 principal components of ancestry. Residual height was calculated as the difference between observed and genetically predicted height. Plasma proteomics (2054 proteins; Olink Explore) were profiled. Deaths and 49 incident diseases were ascertained through national registries. Multivariable Cox models estimated associations of residual height and related proteins with disease incidence and mortality. RESULTS: Higher residual height [mean (standard deviation, SD), 0.0 (4.8)] was associated with more favorable self-reported preadulthood exposures (e.g., later birth years, no maternal smoking around birth, being breastfed as an infant, no adoption experience, and lower childhood adversity scores) and lower hazard ratios (HRs) of 32 out of 49 diseases (median follow-up = &#x223c;12.5 y). Using participants with residual height within &#xb1;0.5 SDs from the mean as reference, those with residual height < -2 SDs had higher adjusted HRs of mortality [1.61; 95% confidence interval (CI): 1.50, 1.72], multimorbidity (1.28; 95% CI: 1.12, 1.46), cardiovascular disease (1.45; 95% CI: 1.32, 1.60), psychiatric/neurological disease (1.38; 95% CI: 1.28, 1.48), and other disease categories (e.g., diabetes, digestive, and musculoskeletal diseases). In contrast, higher genetically predicted height was associated with a higher incidence of 19 diseases, including subtypes of cancer, non-atherosclerotic cardiovascular diseases, and musculoskeletal diseases, as well as higher all-cause mortality. We identified 806 plasma proteins related to inflammation, immune response, and autophagy via tumor necrosis factor, Nuclear factor-kappa B, phosphoinositide-3 kinase/protein kinase B, and Janus kinase/signal transducer and activator of transcription signaling pathways, which were associated with residual height and multiple diseases and mortality. CONCLUSIONS: Higher residual height is associated with lower disease incidence and mortality, with associations that are distinct from those for genetically predicted height.

Humans