Communications medicine最新文献

Background: Declining gait performance is seen in aging individuals, due to neural and systemic factors. Plasma biomarkers provide an accessible way to assess evolving brain changes; non-specific neurodegeneration (NfL, GFAP) or evolving Alzheimer's disease (Aβ 42/40 ratio, P-Tau181).

Methods: In a population-based cohort of older adults, we evaluate the hypothesis that plasma biomarkers of neurodegeneration and Alzheimer's Disease pathology are associated with worse gait performance. A sample of 2641 Mayo Clinic Study of Aging participants with measurements of plasma biomarkers and gait parameters was analyzed in this cross-sectional study. Linear regression models using plasma biomarkers as predictors of gait parameters and adjusted for age, sex, BMI, Charlson Comorbidity Index, and cognitive diagnosis were evaluated.

Results: In this study multiple statistically significant relationships are observed for GFAP, NfL, and P-Tau181 with gait parameters. Each standard deviation increase in GFAP, NfL, and P-Tau181 is associated with a reduction in velocity of 2.100 (95% CI: -3.004, -1.196; p = 5.4 × 10^-6), 4.400 (-5.292, -3.507; p = 9.5 × 10^-22), and 2.617 (-3.414, -1.819; p = 1.5 × 10^-10) cm/sec, respectively. Overall, NfL has the strongest associations with poor gait performance. Models with age interactions show that the strength of associations between the plasma biomarkers and the gait parameters became stronger with increasing age. There are no specific gait parameters that associate with individual plasma biomarkers.

Conclusion: Plasma biomarkers of neurodegeneration and Alzheimer's Disease pathology are not only markers of cognitive decline but also indicate motor decline in the aging population.

Background: Bronchiolitis Obliterans Syndrome (BOS), a fibrotic airway disease that may develop after lung transplantation, conventionally relies on pulmonary function tests (PFTs) for diagnosis due to limitations of CT imaging. Deep neural networks (DNNs) have not previously been used for BOS detection. This study aims to train a DNN to detect BOS in CT scans using an approach tailored for low-data scenarios.

Methods: We trained a DNN to detect BOS in CT scans using a co-training method designed to enhance performance in low-data environments. Our method employs an auxiliary task that makes the DNN more sensitive to disease manifestations and less sensitive to the patient's anatomical features. The DNN was tasked with predicting the sequence of two CT scans taken from the same BOS patient at least six months apart. We evaluated this approach on CT scans from 75 post-transplant patients, including 26 with BOS, and used a ROC-AUC metric to assess performance.

Results: We show that our DNN method achieves a ROC-AUC of 0.90 (95% CI: 0.840-0.953) in distinguishing BOS from non-BOS in CT scans. Performance correlates with BOS progression, with ROC-AUC values of 0.88 for stage I, 0.91 for stage II, and 0.94 for stage III BOS. Notably, the DNN shows comparable performance on standard- and high-resolution CT scans. It also demonstrates the ability to predict BOS in at-risk patients (FEV1 between 80% and 90% of best FEV1) with a ROC-AUC of 0.87 (95% CI: 0.735-0.974). Using visual interpretation techniques for DNNs, we reveal sensitivity to hyperlucent/hypoattenuated areas indicative of air-trapping or bronchiectasis.

Conclusions: Our approach shows potential for improving BOS diagnosis by enabling early detection and management. The ability to detect BOS from standard-resolution scans at any stage of respiration makes this method more accessible than previous approaches. Additionally, our findings highlight that techniques to limit overfitting are crucial for unlocking the potential of DNNs in low-data settings, which could assist clinicians in BOS studies with limited patient data.

Background: Sotrovimab is a neutralising monoclonal antibody (nMAB) currently available to treat extremely clinically vulnerable COVID-19 patients in England. Trials have shown it to have mild to moderate side effects, however, evidence regarding its safety in real-world settings remains insufficient.

Methods: Descriptive and multivariable logistic regression analyses were conducted to evaluate uptake, and a self-controlled case series analysis performed to measure the risk of hospital admission (hospitalisation) associated with 49 pre-specified suspected adverse outcomes in the period 2-28 days post-Sotrovimab treatment among eligible patients treated between December 11, 2021 and May 24, 2022.

Results: Here we show that among treated and untreated eligible individuals, the mean ages (54.6 years, SD: 16.1 vs 54.1, SD: 18.3) and sex distribution (women: 60.9% vs 58.1%; men: 38.9% vs 41.1%) are similar. There are marked variations in uptake between ethnic groups, which is higher amongst individuals categorised ethnically as Indian (15.0%; 95%CI 13.8, 16.3), Other Asian (13.7%; 95%CI 11.9, 15.8), white (13.4%; 95%CI 13.3, 13.6), and Bangladeshi (11.4%; 95%CI 8.8, 14.6); and lower amongst Black Caribbean individuals (6.4%; 95%CI 5.4, 7.5) and Black Africans (4.7%; 95%CI 4.1, 5.4). We find no increased risk of any of the suspected adverse outcomes in the period 2-28 days post-treatment.

Conclusions: We find no safety signals of concern for possible adverse outcomes in the period 2-28 days post treatment with Sotrovimab. However, there is evidence of unequal uptake of Sotrovimab treatment across ethnic groups.

Background: Alzheimer's disease (AD) is a serious neurodegenerative disorder without a clear understanding of pathophysiology. Recent experimental data have suggested neuronal excitation-inhibition (E-I) imbalance as an essential element of AD pathology, but E-I imbalance has not been systematically mapped out for either local or large-scale neuronal circuits in AD, precluding precise targeting of E-I imbalance in AD treatment.

Method: In this work, we apply a Multiscale Neural Model Inversion (MNMI) framework to the resting-state functional MRI data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) to identify brain regions with disrupted E-I balance in a large network during AD progression.

Results: We observe that both intra-regional and inter-regional E-I balance is progressively disrupted from cognitively normal individuals, to mild cognitive impairment (MCI) and to AD. Also, we find that local inhibitory connections are more significantly impaired than excitatory ones and the strengths of most connections are reduced in MCI and AD, leading to gradual decoupling of neural populations. Moreover, we reveal a core AD network comprised mainly of limbic and cingulate regions. These brain regions exhibit consistent E-I alterations across MCI and AD, and thus may represent important AD biomarkers and therapeutic targets. Lastly, the E-I balance of multiple brain regions in the core AD network is found to be significantly correlated with the cognitive test score.

Conclusions: Our study constitutes an important attempt to delineate E-I imbalance in large-scale neuronal circuits during AD progression, which may facilitate the development of new treatment paradigms to restore physiological E-I balance in AD.

Background: To assess the integrity of the developing nervous system, the Prechtl general movement assessment (GMA) is recognized for its clinical value in diagnosing neurological impairments in early infancy. GMA has been increasingly augmented through machine learning approaches intending to scale-up its application, circumvent costs in the training of human assessors and further standardize classification of spontaneous motor patterns. Available deep learning tools, all of which are based on single sensor modalities, are however still considerably inferior to that of well-trained human assessors. These approaches are hardly comparable as all models are designed, trained and evaluated on proprietary/silo-data sets.

Methods: With this study we propose a sensor fusion approach for assessing fidgety movements (FMs). FMs were recorded from 51 typically developing participants. We compared three different sensor modalities (pressure, inertial, and visual sensors). Various combinations and two sensor fusion approaches (late and early fusion) for infant movement classification were tested to evaluate whether a multi-sensor system outperforms single modality assessments. Convolutional neural network (CNN) architectures were used to classify movement patterns.

Results: The performance of the three-sensor fusion (classification accuracy of 94.5%) is significantly higher than that of any single modality evaluated.

Conclusions: We show that the sensor fusion approach is a promising avenue for automated classification of infant motor patterns. The development of a robust sensor fusion system may significantly enhance AI-based early recognition of neurofunctions, ultimately facilitating automated early detection of neurodevelopmental conditions.

Background: The optimal timing for initiating dialysis and prognostic markers in chronic kidney disease (CKD) patients are under debate, with mortality and cardiovascular risks varying among patients. This study investigates whether the apoptosis inhibitor of macrophage (AIM), which is mostly bound to pentameric IgM, could serve as an effective indicator.

Methods: We prospectively followed 423 patients at dialysis initiation and 563 at various CKD stages. AIM dissociation from IgM and other serum components were measured in their serum samples. In vitro treatment of IgM-AIM complexes with their serum was conducted to assess AIM release from IgM. Survival analysis determined the associations of each variable with mortality and cardiovascular risk, and a cutoff value was calculated and validated using cross-validation.

Results: AIM dissociation from IgM increases with CKD progression and correlates with the serum uremic state, as shown by enhanced AIM release from IgM in vitro with sera from patients starting dialysis, but not those at earlier CKD stages. Patients at dialysis initiation with high proportion of serum IgM-free AIM (fAIM%) show elevated uremic toxins and other toxic metabolites, higher mortality, and increased cardiovascular risk compared to those with low fAIM%. This prognostic association is not seen with other CKD biomarkers, such as eGFR, creatinine, or inositol-phosphate. We determined the fAIM% cutoff of 46.27%, which predicts mortality two years post-dialysis initiation.

Conclusions: These findings suggest that the serum fAIM% could function as a prognostic marker at dialysis initiation and may have potential as a criterion for determining dialysis timing.

Background: People living with dementia often experience changes in independence and daily living, affecting their well-being and quality of life. Behavioural changes correlate with cognitive decline, functional impairment, caregiver distress, and care availability.

Methods: We use data from a 3-year prospective observational study of 141 people with dementia at home, using the Bristol Activities of Daily Living Scale, Neuropsychiatric Inventory and cognitive assessments, alongside self-reported and healthcare-related data.

Results: Here we show, psychiatric behavioural symptoms and difficulties in activities of daily living, fluctuate alongside cognitive decline. 677 activities of daily living and 632 psychiatric behaviour questionnaires are available at intervals of 3 months. Clustering shows three severity-based groups. Mild cognitive decline associates with higher caregiver anxiety, while the most severe group interacts more with community services, but less with hospitals.

Conclusions: We characterise behavioural symptoms and difficulties in activities of daily living in dementia, offering clinically relevant insights not commonly considered in current practice. We provide a holistic overview of participants' health during their progression of dementia.

Background: The Supporting Harm Reduction through Peer Support (SHARPS) study involved designing and implementing a peer-delivered, harm reduction intervention for people experiencing homelessness and problem substance use. Normalisation Process Theory (NPT) provided a framework for the study.

Methods: Four Peer Navigators (individuals with personal experience of problem substance use and/or homelessness) were recruited and hosted in six third sector (not-for-profit) homelessness services in Scotland and England (United Kingdom). Each worked with participants to provide practical and emotional support, with the aim of reducing harms, and improving well-being, social functioning and quality of life. NPT guided the development of the intervention and, the process evaluation, which assessed the acceptability and feasibility of the intervention for this cohort who experience distinct, and often unmet, health challenges. While mixed-methods data collection was undertaken, this paper draws only on the qualitative data.

Results: The study found that, overall, the intervention is feasible, and acceptable to, the intervention participants, the Peer Navigators and staff in host settings. Some challenges were encountered but these were outweighed by benefits. NPT is particularly useful in encouraging our team to focus on the relationship between different aspects of the intervention and context(s) and identify ways of maximising 'fit'.

Conclusions: To our knowledge, this is the first application of NPT to this cohort, and specifically by non-clinicians (peers) in non-healthcare settings (homelessness services). Our application of NPT helped us to identify ways in which the intervention could be enhanced, with the key aim of improving the health/well-being of this underserved group.

Background: Alzheimer's disease (AD) is a major neurodegenerative disorder with significant environmental factors, including diet and lifestyle, influencing its onset and progression. Although previous studies have suggested that certain diets may reduce the incidence of AD, the underlying mechanisms remain unclear.

Method: In this post-hoc analysis of a randomized crossover study of 20 elderly adults, we investigated the effects of a modified Mediterranean ketogenic diet (MMKD) on the plasma lipidome in the context of AD biomarkers, analyzing 784 lipid species across 47 classes using a targeted lipidomics platform.

Results: Here we identified substantial changes in response to MMKD intervention, aside from metabolic changes associated with a ketogenic diet, we identified a a global elevation across all plasmanyl and plasmenyl ether lipid species, with many changes linked to clinical and biochemical markers of AD. We further validated our findings by leveraging our prior clinical studies into lipid related changeswith AD (n = 1912), and found that the lipidomic signature with MMKD was inversely associated with the lipidomic signature of prevalent and incident AD.

Conclusions: Intervention with a MMKD was able to alter the plasma lipidome in ways that contrast with AD-associated patterns. Given its low risk and cost, MMKD could be a promising approach for prevention or early symptomatic treatment of AD.

Background: Multiple sulfatase deficiency (MSD) is an exceptionally rare neurodegenerative disorder due to the absence or deficiency of 17 known cellular sulfatases. The activation of all these cellular sulfatases is dependent on the presence of the formylglycine-generating enzyme, which is encoded by the SUMF1 gene. Disease-causing homozygous or compound heterozygous variants in SUMF1 result in MSD. Other than symptomatic treatment, no curative therapy exists as of yet for MSD. Eight out of these 17 sulfatases are primarily localized in the lysosome.

Methods: Two siblings with attenuated MSD underwent hematopoietic cell transplantation (HCT), evaluating the possibility of lysosomal enzymatic cross-correction from the donor cells.

Results: There is evidence of correction of currently available biomarkers within 3 months post-HCT. Untargeted metabolomics also shows continued correction of multiple biochemical abnormalities in the post-HCT period. Furthermore, this article also presents the neuropsychological outcomes of these children as well as the results of untargeted metabolomics analysis in this condition.

Conclusions: These data suggest biochemical benefits post-transplant along with slowing of disease progression. Long-term follow-up is necessary to fully evaluate the therapeutic benefit of HCT in MSD.