The aim of this study is to use classification methods to predict future onset of Alzheimer's disease in cognitively normal subjects through automated linguistic analysis.
To study linguistic ...performance as an early biomarker of AD, we performed predictive modeling of future diagnosis of AD from a cognitively normal baseline of Framingham Heart Study participants. The linguistic variables were derived from written responses to the cookie-theft picture-description task. We compared the predictive performance of linguistic variables with clinical and neuropsychological variables. The study included 703 samples from 270 participants out of which a dataset consisting of a single sample from 80 participants was held out for testing. Half of the participants in the test set developed AD symptoms before 85 years old, while the other half did not. All samples in the test set were collected during the cognitively normal period (before MCI). The mean time to diagnosis of mild AD was 7.59 years.
Significant predictive power was obtained, with AUC of 0.74 and accuracy of 0.70 when using linguistic variables. The linguistic variables most relevant for predicting onset of AD have been identified in the literature as associated with cognitive decline in dementia.
The results suggest that language performance in naturalistic probes expose subtle early signs of progression to AD in advance of clinical diagnosis of impairment.
Pfizer, Inc. provided funding to obtain data from the Framingham Heart Study Consortium, and to support the involvement of IBM Research in the initial phase of the study. The data used in this study was supported by Framingham Heart Study's National Heart, Lung, and Blood Institute contract (N01-HC-25195), and by grants from the National Institute on Aging grants (R01-AG016495, R01-AG008122) and the National Institute of Neurological Disorders and Stroke (R01-NS017950).
Wearable accelerometers allow for continuous monitoring of function and behaviors in the participant’s naturalistic environment. Devices are typically worn in different body locations depending on ...the concept of interest and endpoint under investigation. The lumbar and wrist are commonly used locations: devices placed at the lumbar region enable the derivation of spatio-temporal characteristics of gait, while wrist-worn devices provide measurements of overall physical activity (PA). Deploying multiple devices in clinical trial settings leads to higher patient burden negatively impacting compliance and data quality and increases the operational complexity of the trial. In this work, we evaluated the joint information shared by features derived from the lumbar and wrist devices to assess whether gait characteristics can be adequately represented by PA measured with wrist-worn devices. Data collected at the Pfizer Innovation Research (PfIRe) Lab were used as a real data example, which had around 7 days of continuous at-home data from wrist- and lumbar-worn devices (GENEActiv) obtained from a group of healthy participants. The relationship between wrist- and lumbar-derived features was estimated using multiple statistical methods, including penalized regression, principal component regression, partial least square regression, and joint and individual variation explained (JIVE). By considering multilevel models, both between- and within-subject effects were taken into account. This work demonstrated that selected gait features, which are typically measured with lumbar-worn devices, can be represented by PA features measured with wrist-worn devices, which provides preliminary evidence to reduce the number of devices needed in clinical trials and to increase patients’ comfort. Moreover, the statistical methods used in this work provided an analytic framework to compare repeated measures collected from multiple data modalities.
The ability to perform sit-to-stand (STS) transfers has a significant impact on the functional mobility of an individual. Wearable technology has the potential to enable the objective, long-term ...monitoring of STS transfers during daily life. However, despite several recent efforts, most algorithms for detecting STS transfers rely on multiple sensing modalities or device locations and have predominantly been used for assessment during the performance of prescribed tasks in a lab setting. A novel wavelet-based algorithm for detecting STS transfers from data recorded using an accelerometer on the lower back is presented herein. The proposed algorithm is independent of device orientation and was validated on data captured in the lab from younger and older healthy adults as well as in people with Parkinson's disease (PwPD). The algorithm was then used for processing data captured in free-living conditions to assess the ability of multiple features extracted from STS transfers to detect age-related group differences and assess the impact of monitoring duration on the reliability of measurements. The results show that performance of the proposed algorithm was comparable or significantly better than that of a commercially available system (precision: 0.990 vs. 0.868 in healthy adults) and a previously published algorithm (precision: 0.988 vs. 0.643 in persons with Parkinson's disease). Moreover, features extracted from STS transfers at home were able to detect age-related group differences at a higher level of significance compared to data captured in the lab during the performance of prescribed tasks. Finally, simulation results showed that a monitoring duration of 3 days was sufficient to achieve good reliability for measurement of STS features. These results point towards the feasibility of using a single accelerometer on the lower back for detection and assessment of STS transfers during daily life. Future work in different patient populations is needed to evaluate the performance of the proposed algorithm, as well as assess the sensitivity and reliability of the STS features.
Stair climb power (SCP) is a clinical measure of leg muscular function assessed in-clinic via the Stair Climb Power Test (SCPT). This method is subject to human error and cannot provide continuous ...remote monitoring. Continuous monitoring using wearable sensors may provide a more comprehensive assessment of lower-limb muscular function. In this work, we propose an algorithm to classify stair climbing periods and estimate SCP from a lower-back worn accelerometer, which strongly agrees with the clinical standard (r = 0.92, p < 0.001; ICC = 0.90, 0.82, 0.94). Data were collected in-lab from healthy adults (n = 65) performing the four-step SCPT and a walking assessment while instrumented (accelerometer + gyroscope), which allowed us to investigate tradeoffs between sensor modalities. Using two classifiers, we were able to identify periods of stair ascent with >89% accuracy sensitivity = >0.89, specificity = >0.90 using two ensemble machine learning algorithms, trained on accelerometer signal features. Minimal changes in model performances were observed using the gyroscope alone (±0−6% accuracy) versus the accelerometer model. While we observed a slight increase in accuracy when combining gyroscope and accelerometer (about +3−6% accuracy), this is tolerable to preserve battery life in the at-home environment. This work is impactful as it shows potential for an accelerometer-based at-home assessment of SCP.
Technological advances in multimodal wearable and connected devices have enabled the measurement of human movement and physiology in naturalistic settings. The ability to collect continuous activity ...monitoring data with digital devices in real-world environments has opened unprecedented opportunity to establish clinical digital phenotypes across diseases. Many traditional assessments of physical function utilized in clinical trials are limited because they are episodic, therefore, cannot capture the day-to-day temporal fluctuations and longitudinal changes in activity that individuals experience. In order to understand the sensitivity of gait speed as a potential endpoint for clinical trials, we investigated the use of digital devices during traditional clinical assessments and in real-world environments in a group of healthy younger (
= 33, 18-40 years) and older (
= 32, 65-85 years) adults. We observed good agreement between gait speed estimated using a lumbar-mounted accelerometer and gold standard system during the performance of traditional gait assessment task in-lab, and saw discrepancies between in-lab and at-home gait speed. We found that gait speed estimated in-lab, with or without digital devices, failed to differentiate between the age groups, whereas gait speed derived during at-home monitoring was able to distinguish the age groups. Furthermore, we found that only three days of at-home monitoring was sufficient to reliably estimate gait speed in our population, and still capture age-related group differences. Our results suggest that gait speed derived from activities during daily life using data from wearable devices may have the potential to transform clinical trials by non-invasively and unobtrusively providing a more objective and naturalistic measure of functional ability.
Novel Biomarkers of Bone Metabolism Fernández-Villabrille, Sara; Martín-Carro, Beatriz; Martín-Vírgala, Julia ...
Nutrients,
02/2024, Letnik:
16, Številka:
5
Journal Article
Recenzirano
Odprti dostop
Bone represents a metabolically active tissue subject to continuous remodeling orchestrated by the dynamic interplay between osteoblasts and osteoclasts. These cellular processes are modulated by a ...complex interplay of biochemical and mechanical factors, which are instrumental in assessing bone remodeling. This comprehensive evaluation aids in detecting disorders arising from imbalances between bone formation and reabsorption. Osteoporosis, characterized by a reduction in bone mass and strength leading to heightened bone fragility and susceptibility to fractures, is one of the more prevalent chronic diseases. Some epidemiological studies, especially in patients with chronic kidney disease (CKD), have identified an association between osteoporosis and vascular calcification. Notably, low bone mineral density has been linked to an increased incidence of aortic calcification, with shared molecules, mechanisms, and pathways between the two processes. Certain molecules emerging from these shared pathways can serve as biomarkers for bone and mineral metabolism. Detecting and evaluating these alterations early is crucial, requiring the identification of biomarkers that are reliable for early intervention. While traditional biomarkers for bone remodeling and vascular calcification exist, they suffer from limitations such as low specificity, low sensitivity, and conflicting results across studies. In response, efforts are underway to explore new, more specific biomarkers that can detect alterations at earlier stages. The aim of this review is to comprehensively examine some of the emerging biomarkers in mineral metabolism and their correlation with bone mineral density, fracture risk, and vascular calcification as well as their potential use in clinical practice.
Targeting epigenetic mechanisms has emerged as a potential therapeutic approach for the treatment of kidney diseases. Specifically, inhibiting the bromodomain and extra-terminal (BET) domain proteins ...using the small molecule inhibitor JQ1 has shown promise in preclinical models of acute kidney injury (AKI) and chronic kidney disease (CKD). However, its clinical translation faces challenges due to issues with poor pharmacokinetics and side effects. Here, we developed engineered liposomes loaded with JQ1 with the aim of enhancing kidney drug delivery and reducing the required minimum effective dose by leveraging cargo protection. These liposomes efficiently encapsulated JQ1 in both the membrane and core, demonstrating superior therapeutic efficacy compared to freely delivered JQ1 in a mouse model of kidney ischemia-reperfusion injury. JQ1-loaded liposomes (JQ1-NPs) effectively targeted the kidneys and only one administration, one-hour after injury, was enough to decrease the immune cell (neutrophils and monocytes) infiltration to the kidney—an early and pivotal step to prevent damage progression. By inhibiting BRD4, JQ1-NPs suppress the transcription of pro-inflammatory genes, such as cytokines (il-6) and chemokines (ccl2, ccl5). This success not only improved early the kidney function, as evidenced by decreased serum levels of BUN and creatinine in JQ1-NPs-treated mice, along with reduced tissue expression of the damage marker, NGAL, but also halted the production of extracellular matrix proteins (Fsp-1, Fn-1, α-SMA and Col1a1) and the fibrosis development. In summary, this work presents a promising nanotherapeutic strategy for AKI treatment and its progression and provides new insights into renal drug delivery.
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•JQ1-NPs circumvent its poor pharmacokinetics and severe side effects of this inhibitor.•JQ1-NPs reach efficiently the kidney of mice with acute kidney injury (AKI).•Administration of JQ1-NPs avoid the AKI induced by bilateral kidney IRI.•JQ1-NPs significantly reduce the recruitment of neutrophils and monocytes to the damaged kidney.•The renal fibrosis development and CKD progression is halted by JQ1-NPs treatment.
Abstract Deprived urban areas, commonly referred to as ‘slums,’ are the consequence of unprecedented urbanisation. Previous studies have highlighted the potential of Artificial Intelligence (AI) and ...Earth Observation (EO) in capturing physical aspects of urban deprivation. However, little research has explored AI’s ability to predict how locals perceive deprivation. This research aims to develop a method to predict citizens’ perception of deprivation using satellite imagery, citizen science, and AI . A deprivation perception score was computed from slum-citizens’ votes. Then, AI was used to model this score, and results indicate that it can effectively predict perception, with deep learning outperforming conventional machine learning. By leveraging AI and EO, policymakers can comprehend the underlying patterns of urban deprivation, enabling targeted interventions based on citizens’ needs. As over a quarter of the global urban population resides in slums, this tool can help prioritise citizens’ requirements, providing evidence for implementing urban upgrading policies aligned with SDG-11.
There has been relatively little research on caregivers of people experiencing their first episode of psychosis.
To investigate dimensions of caregiving and morbidity in caregivers of people with ...first-episode psychosis.
Caregivers of 40 people with first-episode psychosis were interviewed at home about their experience of caregiving, coping strategies and distress.
Caregivers used emotional and practical strategies to cope with participants' negative symptoms and difficult behaviours and experienced more worry about these problems. They increased supervision when the participants displayed difficult behaviours. Twelve per cent of caregivers were suffering from psychiatric morbidity as defined by the General Health Questionnaire. Those living with the participant had more frequent visits to their general practitioner.
At first-episode psychosis, caregivers are already having to cope with a wide range of problems and are developing coping strategies. Caregivers worried most about difficult behaviours and negative symptoms in participants.
Neuropsychological impairment is ubiquitous in schizophrenia even at the first presentation of psychotic symptoms. We sought to elucidate the nature of the neuropsychological profile at the onset of ...the illness by examining the neuropsychological functioning of 40 patients experiencing their first episode of psychosis and 22 matched controls. All participants completed a battery of neuropsychological tasks designed to assess attention, verbal learning/memory, non-verbal memory, spatial ability, psychomotor speed, and executive function. First-episode patients showed significant impairment on tasks of executive function, including those requiring the ability to form and initiate a strategy, to inhibit prepotent responses, and to shift cognitive set, and also on tasks of verbal fluency. Memory impairments were seen on verbal learning and delayed non-verbal memory only. Impairment on tasks of psychomotor speed suggests that there may be a significant amount of cognitive slowing even at the first onset of psychosis. We suggest that our patients may be experiencing difficulty in specific aspects of executive functions, including the ability to form and execute a strategy, and these difficulties may be mediating the deficits observed on tasks of verbal learning.
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