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PubMed2026

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 = 4-6 per group) and cerebral cortex samples (n = 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 ± 72), while values in brain-injured cases ranged from 163 to 228 copies per genome (mean 200 ± 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.

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PubMed2026

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. 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 + AI for prediction model studies. 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 + 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. 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.

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PubMed2026

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 Hz) alongside established ranges (∼200 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.

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PubMed2026

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↗

PubMed2026

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↗

PubMed2026

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↗

PubMed2026

Molecular Landscape and Advanced Diagnostic Technologies for BRAF Mutations in Cancer: From Quantitative PCR and ddPCR to CRISPR-Based Platforms.

BRAF mutations are key oncogenic alterations across multiple malignancies, including melanoma, thyroid carcinoma, colorectal cancer, non-small cell lung cancer, glioma, and hairy cell leukemia. The most prevalent variant, BRAF-V600E, induces constitutive activation of the MAPK signaling pathway, promoting tumor progression and influencing therapeutic responsiveness. Accurate detection of BRAF alterations is therefore essential for molecular classification, prognostic assessment, treatment selection, and resistance surveillance. This review summarizes the molecular heterogeneity of BRAF mutations and critically evaluates current diagnostic methodologies. Conventional approaches such as allele-specific PCR and Sanger sequencing are compared with advanced quantitative platforms, including high-resolution melting analysis, droplet digital PCR, and next-generation sequencing, with emphasis on analytical sensitivity, mutation coverage, and clinical applicability. Emerging technologies such as CRISPR-based assays, rolling circle amplification systems, and nanoparticle-based biosensors and point-of-care diagnostic platforms are also discussed for their potential to enhance ultra-sensitive detection, particularly in liquid biopsy settings. These emerging tools are highlighted for their potential to enable ultra-sensitive, rapid, and decentralized mutation detection, particularly in liquid biopsy settings. Key challenges, including intratumoral heterogeneity, low allele-frequency variants, FFPE-associated artifacts, and clonal evolution under therapeutic pressure, are examined within a translational framework. In addition, we examine critical barriers to clinical implementation, including standardization, cost, and global accessibility of molecular diagnostics, and outline potential solutions through scalable technologies and decentralized testing strategies. We propose that optimal BRAF testing requires a mutation subclass-informed and clinically integrated strategy combining comprehensive baseline profiling with longitudinal molecular monitoring. Future diagnostic paradigms will likely integrate multi-omics data and artificial intelligence (AI)-assisted interpretation to refine precision oncology implementation. Looking forward, we propose that optimal BRAF testing will require integration of multi-omics profiling with AI-assisted interpretation, enabling automated variant classification, real-time clinical decision support, and improved prediction of therapeutic response and resistance.

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PubMed2026

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 ≥ 4, defined as moderate disability or good recovery, n = 58) and an unfavorable outcome group (GOS < 4, i.e., death, persistent vegetative state, or severe disability, 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 emerged as a potentially modifiable factor in this cohort, suggesting that minimizing delays may improve outcomes.

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PubMed2026

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.

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PubMed2026

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.

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PubMed2026

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↗

PubMed2026

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↗

PubMed2026

Effects of strength and balance training on the structure of the aging brain.

BACKGROUND: While it is established that motor training induces structural changes in the brains of young adults, structural adaptations in aging brains are less studied. METHODS: This randomized controlled study investigated the impact of long-term strength and balance training on the structural plasticity in 60 elderly adults (64 - 82 years old, 70.6 ± 4.7) using multi-modal neuroimaging. We compared the effects of three months of strength training to balance training of the same duration and to a passive control group. Voxel-based morphometry (VBM) and tract-based spatial statistics (TBSS) were used to assess grey matter (GM) and white matter (WM) plasticity. White matter tract integrity (WMTI) modelling was employed to explore the microstructural underpinnings of white matter alterations. RESULTS: We found that strength training was associated with changes in diffusion metrics consistent with white matter microstructural remodeling, specifically increased extra-axonal axial diffusivity in the bilateral inferior fronto-occipital and longitudinal fasciculi. Additionally, both balance and strength training mitigated reductions in axonal water fraction in the splenium of the corpus callosum and the right posterior corona radiata observed in the control group. CONCLUSION: These results underscore the potential relevance of strength and balance training to induce beneficial neural plasticity by counteracting aging-related demyelination in the corpus callosum and highlight the specific role of strength training in facilitating white matter reorganization in key transmission fiber pathways.

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PubMed2026

Estrone disrupts early reproductive development in juvenile male Siniperca chuatsi and is associated with brain and gonadal responses.

Whether estrone (E1)-associated disruption of early reproductive development in fish is accompanied by brain responses in addition to direct gonadal effects remains unclear. Here, juvenile Siniperca chuatsi, a non-model but economically important freshwater species, were exposed for 60 d to 0, 0.01, 0.1, and 1.0 μg/L E1, spanning environmentally reported and elevated concentrations. By integrating waterborne concentration monitoring, histopathology, transcriptomics, and quantitative real-time PCR (qPCR) validation, we evaluated E1-associated changes in brain and gonadal tissues during early reproductive development. Waterborne E1 concentrations remained generally stable throughout the exposure period. At the highest tested concentration (1.0 μg/L), E1 caused neuronal vacuolation and pyknosis in the hypothalamic region and induced distinct ovarian-like structures in the gonads of genetic males. In the brain, cyp19a1, crhr1, and adcy2a were significantly upregulated, whereas egr1 was significantly downregulated, indicating transcriptional changes in genes associated with local estrogen conversion, stress-response/cAMP signaling, and neuronal activity-related regulation within a broader injury/stress-response background. In the gonad, RNA-seq analysis showed significant downregulation of star2, hsd3b1, cyp17a1, and cyp11b and significant upregulation of hsd17b1, suggesting alterations in steroidogenesis-related gene expression at the transcriptomic level. qPCR analysis of selected gonadal candidate genes showed expression directions generally consistent with the RNA-seq results, and these molecular patterns were consistent with the feminized histological phenotype. Together, these results indicate that E1 can disrupt early reproductive development in juvenile S. chuatsi and support a cautious working model in which E1 exposure is accompanied by concurrent brain and gonadal responses. This study provides new evidence for understanding the toxic effects and ecological risk implications of natural estrogen E1 during early fish development.

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PubMed2026

Pregnancy diet based on ancestral patterns increases growth in subcortical fetal brain regions.

Evidence on the biological basis for maternal nutrition effects on fetal and newborn neurodevelopment remains limited. This randomized controlled trial in Ecuador tested a maternal dietary pattern-derived from empirical studies of nutrition in human evolution and adapted locally-on offspring growth and brain development. Pregnant women (n = 215) in their first trimester were randomized to: 1) control (n = 104); or 2) Mikhuna ("nourish" in Kichwa) intervention (n = 111). The intervention, from 12 wk gestation to birth, consisted of a weekly food delivery (8 eggs, 500 g fish, and a variety of sustainably sourced fruits and vegetables) and a behavior change communication strategy encouraging diet diversity and limiting highly processed foods. Longitudinal data collection occurred at 12 wk, 21 wk, 35 wk gestation, and 2 wk postpartum, and included ultrasound imaging of fetal bone and brain parameters, maternal dietary intakes, anthropometry, socioeconomic and demographic variables, and other biomarkers. At close of intervention, a significantly higher percentage of women met the minimum dietary diversity threshold in Mikhuna (74.5%) vs. control groups (55.8%) (P = 0.004). Generalized linear regression models showed significant differences in Mikhuna compared to control for: corpus callosum length 0.19 cm (95% CI [0.02, 0.35]), gangliothalamic ovoid height 0.15 cm (95% CI [0.03 to 0.26]), and femur length -0.10 cm (95% CI [-0.19, -0.02]) from 21 wk to 35 wk; and corpus callosum Z 0.56 (95% CI [0.03, 1.09]) and femur length Z -0.21 (95% CI [-0.42, 0.00]) at 35 wk. The Mikhuna intervention increased the growth of subcortical fetal brain structures, which have established roles in motor control, cognition, and signal transmission.

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PubMed2026

Diagnostic utility of high-risk HPV polymerase chain reaction-based testing in head and neck FNA specimens with indeterminate cytomorphology.

BACKGROUND: Fine-needle aspiration (FNA) is critical in the initial diagnosis of many high-risk human papillomavirus (HR-HPV)-associated, metastatic oropharyngeal squamous cell carcinomas. Updated guidelines recommend HR-HPV-specific polymerase chain reaction (PCR) analysis over p16 immunohistochemistry on FNA specimens because p16 performs poorly on cytology material. PCR-based assays on liquid cytology material have demonstrated excellent analytic performance; however, the diagnostic utility of a positive HR-HPV PCR result in specimens with indeterminate cytomorphology remains uncharacterized. METHODS: The authors retrospectively identified 279 head and neck FNA specimens that had paired HR-HPV PCR testing on residual liquid cytology material over a 5-year period. The positive predictive value for histopathologically confirmed squamous cell carcinoma on surgical follow-up was calculated within each cytologic interpretive category. RESULTS: The HR-HPV PCR results were positive in 50.2% of specimens, negative in 40.9%, and indeterminate in 9.0%. The HR-HPV positivity rate ranged from 0% in specimens categorized as negative for malignancy to 57.3% in cytologically positive specimens, with 19.0%, 41.2%, and 50.0% positivity in the atypical, suspicious, and nondiagnostic categories, respectively. Among cytologically indeterminate specimens with positive HR-HPV PCR results (n = 14), the positive predictive value was 100% (95% confidence interval, 78.5%-100.0%). Blinded slide review additionally identified 15 cytologically positive specimens in which the definitive malignant interpretation depended substantially on HR-HPV positivity; all 15 were confirmed as squamous cell carcinoma. CONCLUSIONS: A positive HR-HPV PCR result on liquid cytology material carries a positive predictive value of 100% for malignancy in cytologically indeterminate head and neck FNA specimens. These findings support integrating HR-HPV PCR analysis into routine cytologic interpretation with the potential to upgrade some indeterminate specimens to malignant when HR-HPV is detected, expediting definitive treatment and sparing patients additional, invasive sampling.

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PubMed2026

Effect of ketofol versus Fentanyl-Midazolam sedation on neurological recovery in traumatic brain Injury: A randomised study.

Neurological recovery after traumatic brain injury (TBI) is multifactorial, and sedation is a cornerstone of neurocritical care because of its neuroprotective role. Although ketofol is widely used for anaesthesia, its effectiveness as a sedative regimen in the intensive care unit (ICU) has not been well studied. This preliminary exploratory double-blind, randomised study compared ketofol (KP) with fentanyl-midazolam (FM) sedation in adults with moderate-to-severe TBI. Sedation was administered for 72 h and titrated to a Richmond Agitation-Sedation Scale (RASS) score ≤  - 3. The primary outcome was the Extended Glasgow Outcome Scale (GOSE) at 30 days. Secondary outcomes included GOSE at 90 days, incidence of propofol infusion syndrome (PRIS), duration of mechanical ventilation, haemodynamic stability, and ICU and hospital length of stay. Of 120 enrolled patients, 111 were included in the final analysis (57 FM, 54 KP). Baseline characteristics, including injury severity and Marshall CT scores, were comparable. At 30 days, good neurological recovery (GOSE 7-8) was more frequent in the KP group than the FM group (26% vs. 10.5%, p = 0.03). At 90 days, recovery remained higher with KP (44.4% vs. 33.3%), though the difference was not statistically significant (p = 0.16). Multivariate analysis confirmed ketofol as an independent predictor of good recovery at 30 days (adjusted OR 3.63, 95% CI 1.11-11.85, p = 0.033). No PRIS occurred, and secondary outcomes were similar. Ketofol-based sedation was safe and may be associated with improved early neurological recovery compared with fentanyl-midazolam, with a favourable trend toward improved long-term neurological recovery.

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PubMed2026

Effects of permissive hypercapnia on intraoperative cerebral oxygenation and early postoperative cognitive function in older patients with fragile brain function during the non-acute phase undergoing laparoscopic colorectal surgery: A randomized controlled trial.

BACKGROUND AND PURPOSE: Older adults with non-acute fragile brain function (NFBF) may be particularly susceptible to perioperative disturbances in cerebral oxygenation and postoperative neurocognitive decline. Permissive hypercapnia (PHC) may enhance cerebral oxygenation, but its effects in this population remain unclear. We examined whether PHC-based ventilation improves intraoperative regional cerebral oxygen saturation (rSO2) and early postoperative cognitive outcomes in older patients with NFBF undergoing elective laparoscopic colorectal surgery. METHODS: In this single-center, single-blind randomized trial, 76 patients were assigned in a 1:1 ratio to PHC-based or conventional ventilation. The primary outcome was the absolute change in rSO2 from baseline (T0) to the end of surgery (T4). Analyses followed the intention-to-treat principle, with prespecified per-protocol sensitivity analysis. Secondary outcomes included intraoperative rSO2 trajectories, cerebral oxygen extraction-related indices, early postoperative cognitive screening, serum neuron-specific enolase and interleukin-6, and safety outcomes. RESULTS: PHC significantly increased rSO2 relative to conventional ventilation (left: adjusted mean difference [aMD] 10.64, 95% CI 8.96-12.33; right: aMD 10.16, 95% CI 8.22-12.11; both P < 0.001), with consistent sensitivity results. Repeated-measures analyses showed persistently higher intraoperative rSO2 in the PHC group. Cerebral oxygen extraction-related indices were generally lower with PHC. However, early postoperative cognitive outcomes and serum biomarkers did not differ between groups. Emergence time was modestly longer with PHC, whereas adverse events were comparable. CONCLUSIONS: PHC-based ventilation favorably modified intraoperative cerebral oxygenation and oxygen-extraction profiles but did not translate into detectable early postoperative cognitive or biomarker benefits in older adults with NFBF.

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