Combining neuropsychological assessment and structural neuroimaging to identify early Alzheimer's disease in a memory clinic cohort.

INTRODUCTION: The current study examined the contributions of comprehensive neuropsychological assessment and volumetric assessment of selected mesial temporal subregions on structural magnetic resonance imaging (MRI) to identify patients with amnestic mild cognitive impairment (aMCI) and mild probable Alzheimer's disease (AD) dementia in a memory clinic cohort. METHODS: Comprehensive neuropsychological assessment and automated entorhinal, transentorhinal, and hippocampal volume measurements were conducted in 40 healthy controls, 38 patients with subjective memory symptoms, 16 patients with aMCI, 16 patients with mild probable AD dementia. Multinomial logistic regression was used to compare the neuropsychological and MRI measures. RESULTS: Combining the neuropsychological and MRI measures improved group membership prediction over the MRI measures alone but did not improve group membership prediction over the neuropsychological measures alone. CONCLUSION: Comprehensive neuropsychological assessment was an important tool to evaluate cognitive impairment. The mesial temporal volumetric MRI measures contributed no diagnostic value over and above the determinations made through neuropsychological assessment.

Lower-Limb Exoskeletons Appeal to Both Clinicians and Older Adults, Especially for Fall Prevention and Joint Pain Reduction.

Exoskeletons are a burgeoning technology with many possible applications to improve human life; focusing the effort of exoskeleton research and development on the most important features is essential for facilitating adoption and maximizing positive societal impact. To identify important focus areas for exoskeleton research and development, we conducted a survey with 154 potential users (older adults) and another survey with 152 clinicians. The surveys were conducted online and to ensure a consistent concept of an exoskeleton across respondents, an image of a hip exoskeleton was shown during exoskeleton-related prompts. The survey responses indicate that both older adults and clinicians are open to using exoskeletons, fall prevention and joint pain reduction are especially important features, and users are likely to wear an exoskeleton in the scenarios when it has the greatest opportunity to help prevent a fall. These findings can help inform future exoskeleton research and guide the development of devices that are accepted, used, and provide meaningful benefit to users.

Elastic energy-recycling actuators for efficient robots.

Electric motors are widely used in robots but waste energy in many applications. We introduce an elastic energy-recycling actuator that maintains the versatility of motors while improving energy efficiency in cyclic tasks. The actuator comprises a motor in parallel with an array of springs that can be individually engaged and disengaged, while retaining stored energy, by pairs of low-power electroadhesive clutches. We developed a prototype actuator and tested it in five repetitive tasks with features common in robotic applications but difficult to perform efficiently. The actuator reduced power consumption by at least 50% in all cases and by 97% in the best case. Elastic energy recovery, controlled by low-power clutches, can improve the efficiency of mobile robots, assistive devices, and other engineered systems.

Alzheimer's disease biomarker utilization at first referral enhances differential diagnostic precision with simultaneous exclusion of Creutzfeldt-Jakob disease.

Most suspected Creutzfeldt-Jakob disease (CJD) cases are eventually diagnosed with other disorders. We assessed the utility of investigating Alzheimer's disease (AD) biomarkers and neurofilament light (NfL) in patients when CJD is suspected. The study cohort consisted of cerebrospinal fluid (CSF) samples referred for CJD biomarker screening wherein amyloid beta 1-42 (Aß1-42), phosphorylated tau 181 (p-tau181), and total tau (t-tau) could be assessed via Elecsys immunoassays (n = 419) and NfL via enzyme-linked immunosorbent assay (ELISA; n = 161). In the non-CJD sub cohort (n = 371), 59% (219/371) had A+T- (abnormal Aß1-42 only) and 21% (79/371) returned A+T+ (abnormal Aß1-42 and p-tau181). In the 48 CJD subjects, a similar AD biomarker profile distribution was observed. To partially address the prevalence of likely pre-symptomatic AD, NfL was utilized to assess for neuronal damage. NfL was abnormal in 76% (25/33) of A+T- subjects 40 to 69 years of age, 80% (20/25) of whom had normal t-tau. This study reinforces AD as an important differential diagnosis of suspected CJD, highlighting that incorporating AD biomarkers and NfL at initial testing is worthwhile.

Lower limb biomechanics of fully trained exoskeleton users reveal complex mechanisms behind the reductions in energy cost with human-in-the-loop optimization.

Exoskeletons that assist in ankle plantarflexion can improve energy economy in locomotion. Characterizing the joint-level mechanisms behind these reductions in energy cost can lead to a better understanding of how people interact with these devices, as well as to improved device design and training protocols. We examined the biomechanical responses to exoskeleton assistance in exoskeleton users trained with a lengthened protocol. Kinematics at unassisted joints were generally unchanged by assistance, which has been observed in other ankle exoskeleton studies. Peak plantarflexion angle increased with plantarflexion assistance, which led to increased total and biological mechanical power despite decreases in biological joint torque and whole-body net metabolic energy cost. Ankle plantarflexor activity also decreased with assistance. Muscles that act about unassisted joints also increased activity for large levels of assistance, and this response should be investigated over long-term use to prevent overuse injuries.

Optimizing exoskeleton assistance to improve walking speed and energy economy for older adults.

BACKGROUND: Walking speed and energy economy tend to decline with age. Lower-limb exoskeletons have demonstrated potential to improve either measure, but primarily in studies conducted on healthy younger adults. Promising techniques like optimization of exoskeleton assistance have yet to be tested with older populations, while speed and energy consumption have yet to be simultaneously optimized for any population. METHODS: We investigated the effectiveness of human-in-the-loop optimization of ankle exoskeletons with older adults. Ten healthy adults > 65 years of age (5 females; mean age: 72 ± 3 yrs) participated in approximately 240 min of training and optimization with tethered ankle exoskeletons on a self-paced treadmill. Multi-objective human-in-the-loop optimization was used to identify assistive ankle plantarflexion torque patterns that simultaneously improved self-selected walking speed and metabolic rate. The effects of optimized exoskeleton assistance were evaluated in separate trials. RESULTS: Optimized exoskeleton assistance improved walking performance for older adults. Both objectives were simultaneously improved; self-selected walking speed increased by 8% (0.10 m/s; p = 0.001) and metabolic rate decreased by 19% (p = 0.007), resulting in a 25% decrease in energetic cost of transport (p = 8e-4) compared to walking with exoskeletons applying zero torque. Compared to younger participants in studies optimizing a single objective, our participants required lower exoskeleton torques, experienced smaller improvements in energy use, and required more time for motor adaptation. CONCLUSIONS: Our results confirm that exoskeleton assistance can improve walking performance for older adults and show that multiple objectives can be simultaneously addressed through human-in-the-loop optimization.

Cerebrospinal fluid neurofilament light predicts longitudinal diagnostic change in patients with psychiatric and neurodegenerative disorders.

OBJECTIVE: People with neuropsychiatric symptoms often experience delay in accurate diagnosis. Although cerebrospinal fluid neurofilament light (CSF NfL) shows promise in distinguishing neurodegenerative disorders (ND) from psychiatric disorders (PSY), its accuracy in a diagnostically challenging cohort longitudinally is unknown. METHODS: We collected longitudinal diagnostic information (mean = 36 months) from patients assessed at a neuropsychiatry service, categorising diagnoses as ND/mild cognitive impairment/other neurological disorders (ND/MCI/other) and PSY. We pre-specified NfL > 582 pg/mL as indicative of ND/MCI/other. RESULTS: Diagnostic category changed from initial to final diagnosis for 23% (49/212) of patients. NfL predicted the final diagnostic category for 92% (22/24) of these and predicted final diagnostic category overall (ND/MCI/other vs. PSY) in 88% (187/212), compared to 77% (163/212) with clinical assessment alone. CONCLUSIONS: CSF NfL improved diagnostic accuracy, with potential to have led to earlier, accurate diagnosis in a real-world setting using a pre-specified cut-off, adding weight to translation of NfL into clinical practice.

AddBiomechanics: Automating model scaling, inverse kinematics, and inverse dynamics from human motion data through sequential optimization.

Creating large-scale public datasets of human motion biomechanics could unlock data-driven breakthroughs in our understanding of human motion, neuromuscular diseases, and assistive devices. However, the manual effort currently required to process motion capture data and quantify the kinematics and dynamics of movement is costly and limits the collection and sharing of large-scale biomechanical datasets. We present a method, called AddBiomechanics, to automate and standardize the quantification of human movement dynamics from motion capture data. We use linear methods followed by a non-convex bilevel optimization to scale the body segments of a musculoskeletal model, register the locations of optical markers placed on an experimental subject to the markers on a musculoskeletal model, and compute body segment kinematics given trajectories of experimental markers during a motion. We then apply a linear method followed by another non-convex optimization to find body segment masses and fine tune kinematics to minimize residual forces given corresponding trajectories of ground reaction forces. The optimization approach requires approximately 3-5 minutes to determine a subject's skeleton dimensions and motion kinematics, and less than 30 minutes of computation to also determine dynamically consistent skeleton inertia properties and fine-tuned kinematics and kinetics, compared with about one day of manual work for a human expert. We used AddBiomechanics to automatically reconstruct joint angle and torque trajectories from previously published multi-activity datasets, achieving close correspondence to expert-calculated values, marker root-mean-square errors less than 2 cm, and residual force magnitudes smaller than 2% of peak external force. Finally, we confirmed that AddBiomechanics accurately reproduced joint kinematics and kinetics from synthetic walking data with low marker error and residual loads. We have published the algorithm as an open source cloud service at AddBiomechanics.org, which is available at no cost and asks that users agree to share processed and de-identified data with the community. As of this writing, hundreds of researchers have used the prototype tool to process and share about ten thousand motion files from about one thousand experimental subjects. Reducing the barriers to processing and sharing high-quality human motion biomechanics data will enable more people to use state-of-the-art biomechanical analysis, do so at lower cost, and share larger and more accurate datasets.

Validating ASHS-T1 automated entorhinal and transentorhinal cortical segmentation in Alzheimer's disease.

The current study aimed to validate entorhinal and transentorhinal cortical volumes measured by the automated segmentation tool Automatic Segmentation of Hippocampal Subfields (ASHS-T1). The study sample comprised 34 healthy controls (HCs), 37 individuals with amnestic mild cognitive impairment (aMCI), and 29 individuals with Alzheimer's disease (AD) dementia from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Entorhinal and transentorhinal cortical volumes were assessed using ASHS-T1, manual segmentation, as well as a widely used automated segmentation tool, FreeSurfer v6.0.1. Mean differences, intraclass correlation coefficients, and Bland-Altman plots were computed. ASHS-T1 tended to underestimate entorhinal and transentorhinal cortical volumes relative to manual segmentation and FreeSurfer. There was variable consistency and low agreement between ASHS-T1 and manual segmentation volumes. There was low-to-moderate consistency and low agreement between ASHS-T1 and FreeSurfer volumes. There was a trend toward higher consistency and agreement for the entorhinal cortex in the aMCI and AD groups compared to the HC group. Despite the differences in volume measurements, ASHS-T1 was sensitive to entorhinal and transentorhinal cortical atrophy in both early and late disease stages. Based on the current study, ASHS-T1 appears to be a promising tool for automated entorhinal and transentorhinal cortical volume measurement in individuals with likely underlying AD.

Simulating the effect of ankle plantarflexion and inversion-eversion exoskeleton torques on center of mass kinematics during walking.

Walking balance is central to independent mobility, and falls due to loss of balance are a leading cause of death for people 65 years of age and older. Bipedal gait is typically unstable, but healthy humans use corrective torques to counteract perturbations and stabilize gait. Exoskeleton assistance could benefit people with neuromuscular deficits by providing stabilizing torques at lower-limb joints to replace lost muscle strength and sensorimotor control. However, it is unclear how applied exoskeleton torques translate to changes in walking kinematics. This study used musculoskeletal simulation to investigate how exoskeleton torques applied to the ankle and subtalar joints alter center of mass kinematics during walking. We first created muscle-driven walking simulations using OpenSim Moco by tracking experimental kinematics and ground reaction forces recorded from five healthy adults. We then used forward integration to simulate the effect of exoskeleton torques applied to the ankle and subtalar joints while keeping muscle excitations fixed based on our previous tracking simulation results. Exoskeleton torque lasted for 15% of the gait cycle and was applied between foot-flat and toe-off during the stance phase, and changes in center of mass kinematics were recorded when the torque application ended. We found that changes in center of mass kinematics were dependent on both the type and timing of exoskeleton torques. Plantarflexion torques produced upward and backward changes in velocity of the center of mass in mid-stance and upward and smaller forward velocity changes near toe-off. Eversion and inversion torques primarily produced lateral and medial changes in velocity in mid-stance, respectively. Intrinsic muscle properties reduced kinematic changes from exoskeleton torques. Our results provide mappings between ankle plantarflexion and inversion-eversion torques and changes in center of mass kinematics which can inform designers building exoskeletons aimed at stabilizing balance during walking. Our simulations and software are freely available and allow researchers to explore the effects of applied torques on balance and gait.

AddBiomechanics: Automating model scaling, inverse kinematics, and inverse dynamics from human motion data through sequential optimization.

Creating large-scale public datasets of human motion biomechanics could unlock data-driven breakthroughs in our understanding of human motion, neuromuscular diseases, and assistive devices. However, the manual effort currently required to process motion capture data and quantify the kinematics and dynamics of movement is costly and limits the collection and sharing of large-scale biomechanical datasets. We present a method, called AddBiomechanics, to automate and standardize the quantification of human movement dynamics from motion capture data. We use linear methods followed by a non-convex bilevel optimization to scale the body segments of a musculoskeletal model, register the locations of optical markers placed on an experimental subject to the markers on a musculoskeletal model, and compute body segment kinematics given trajectories of experimental markers during a motion. We then apply a linear method followed by another non-convex optimization to find body segment masses and fine tune kinematics to minimize residual forces given corresponding trajectories of ground reaction forces. The optimization approach requires approximately 3-5 minutes to determine a subjects skeleton dimensions and motion kinematics, and less than 30 minutes of computation to also determine dynamically consistent skeleton inertia properties and fine-tuned kinematics and kinetics, compared with about one day of manual work for a human expert. We used AddBiomechanics to automatically reconstruct joint angle and torque trajectories from previously published multi-activity datasets, achieving close correspondence to expert-calculated values, marker root-mean-square errors less than 2cm, and residual force magnitudes smaller than 2% of peak external force. Finally, we confirmed that AddBiomechanics accurately reproduced joint kinematics and kinetics from synthetic walking data with low marker error and residual loads. We have published the algorithm as an open source cloud service at AddBiomechanics.org, which is available at no cost and asks that users agree to share processed and de-identified data with the community. As of this writing, hundreds of researchers have used the prototype tool to process and share about ten thousand motion files from about one thousand experimental subjects. Reducing the barriers to processing and sharing high-quality human motion biomechanics data will enable more people to use state-of-the-art biomechanical analysis, do so at lower cost, and share larger and more accurate datasets.

Creutzfeldt-Jakob disease surveillance in Australia: update to 31 December 2022.

Creutzfeldt-Jakob disease surveillance in Australia: update to 31 December 2022: Nationwide surveillance of Creutzfeldt-Jakob disease (CJD) and other human prion diseases is performed by the Australian National Creutzfeldt-Jakob Disease Registry (ANCJDR). National surveillance encompasses the period since 1 January 1970, with prospective surveillance occurring from 1 October 1993. Over this prospective surveillance period, considerable developments have occurred in pre-mortem diagnostics; in the delineation of new disease subtypes; and in a heightened awareness of prion diseases in healthcare settings. Surveillance practices of the ANCJDR have evolved and adapted accordingly. This report summarises the activities of the ANCJDR during 2022. Since the ANCJDR began offering diagnostic cerebrospinal fluid (CSF) 14-3-3 protein testing in Australia in September 1997, the annual number of referrals has steadily increased. In 2022, a total of 599 domestic CSF specimens were referred for diagnostic testing and 79 persons with suspected human prion disease were formally added to the national register. As of 31 December 2022, just under half of the 79 suspect case notifications (36/79) remain classified as 'incomplete'; 15 cases were classified as 'definite' and 23 as 'probable' prion disease; five cases were excluded through neuropathological examination. For 2022, fifty-five percent of all suspected human-prion-disease-related deaths in Australia underwent neuropathological examination. No cases of variant or iatrogenic CJD were identified. The SARS-CoV-2 pandemic did not affect prion disease surveillance outcomes in Australia during 2022.

Tailored behavioural tests reveal early and progressive cognitive deficits in M1000 prion disease.

Prion diseases are pathogenically linked to the normal cellular prion protein (PrPC) misfolding into abnormal conformers (PrPSc), with PrPSc accumulation underpinning both transmission and neurotoxicity. Despite achieving this canonical understanding, however fundamental questions remain incompletely resolved, including the level of pathophysiological overlap between neurotoxic and transmitting species of PrPSc and the temporal profiles of their propagation. To further investigate the likely time of occurrence of significant levels of neurotoxic species during prion disease development, the well characterised in vivo M1000 murine model was employed. Following intracerebral inoculation, detailed serial cognitive and ethological testing at specified time points suggested subtle transition to early symptomatic disease from ∼50% of the overall disease course. In addition to observing a chronological order for impaired behaviours, different behavioural tests also showed distinctive profiles of evolving cognitive impairments with the Barnes maze demonstrating a relatively simple linear worsening of spatial learning and memory over an extended period while in contrast a conditioned fear memory paradigm previously untested in murine prion disease demonstrated more complex alterations during disease progression. These observations support the likely production of neurotoxic PrPSc from at least just prior to the mid-point of murine M1000 prion disease and illustrate the likely need to tailor the types of behavioural testing across the time course of disease progression for optimal detection of cognitive deficits.

Diagnostic performance of CSF biomarkers in a well-characterized Australian cohort of sporadic Creutzfeldt-Jakob disease.

The most frequently utilized biomarkers to support a pre-mortem clinical diagnosis of sporadic Creutzfeldt-Jakob disease (sCJD) include concentrations of the 14-3-3 and total tau (T-tau) proteins, as well as the application of protein amplification techniques, such as the real time quaking-induced conversion (RT-QuIC) assay, in cerebrospinal fluid (CSF). Utilizing CSF from a cohort of neuropathologically confirmed (definite) sCJD (n = 50) and non-CJD controls (n = 48), we established the optimal cutpoints for the fully automated Roche Elecsys® immunoassay for T-tau and the CircuLexTM 14-3-3 Gamma ELISA and compared these to T-tau protein measured using a commercially available assay (INNOTEST hTAU Ag) and 14-3-3 protein detection by western immunoblot (WB). These CSF specimens were also assessed for presence of misfolded prion protein using the RT-QuIC assay. T-tau showed similar diagnostic performance irrespective of the assay utilized, with ~90% sensitivity and specificity. The 14-3-3 protein detection by western blot (WB) has 87.5% sensitivity and 66.7% specificity. The 14-3-3 ELISA demonstrated 81.3% sensitivity and 84.4% specificity. RT-QuIC was the single best performing assay, with a sensitivity of 92.7% and 100% specificity. Our study indicates that a combination of all three CSF biomarkers increases sensitivity and offers the best chance of case detection pre-mortem. Only a single sCJD case in our cohort was negative across the three biomarkers, emphasizing the value of autopsy brain examination on all suspected CJD cases to ensure maximal case ascertainment.

Cerebrospinal fluid neurofilament light and cerebral atrophy in younger-onset dementia and primary psychiatric disorders.

BACKGROUND AND AIMS: Neurodegeneration underpins the pathological processes of younger-onset dementia (YOD) and has been implicated in primary psychiatric disorders (PSYs). Cerebrospinal fluid (CSF) neurofilament light (NfL) has been used to investigate neurodegeneration severity through correlation with structural brain changes in various conditions, but has seldom been evaluated in YOD and PSYs. METHODS: This retrospective study included patients with YOD or PSYs with magnetic resonance imaging (MRI) of the brain and CSF NfL analysis. Findings from brain MRI were analysed using automated volumetry (volBrain) to measure white matter (WM), grey matter (GM) and whole brain (WB) volumes expressed as percentages of total intracranial volume. Correlations between NfL and brain volume measurements were computed whilst adjusting for age. RESULTS: Seventy patients (47 with YOD and 23 with PSY) were identified. YOD types included Alzheimer disease and behavioural variant frontotemporal dementia. PSY included schizophrenia and major depressive disorder. MRI brain sequences were either fast spoiler gradient-echo (FSPGR) or magnetization-prepared rapid acquisition gradient-echo (MPRAGE). In the total cohort, higher NfL was associated with reduced WB in the FSPGR and MPRAGE sequences (r = -0.402 [95% confidence interval (CI), -0.593 to -0.147], P = 0.008 and r = -0.625 [95% CI, -0.828 to -0.395], P < 0.001, respectively). Higher NfL was related to reduced GM in FSPGR (r = 0.385 [95% CI, -0.649 to -0.014], P = 0.017) and reduced WM in MPRAGE (r = -0.650 [95% CI, -0.777 to -0.307], P < 0.001). Similar relationships were seen in YOD, but not in PSY. CONCLUSION: Higher CSF NfL is related to brain atrophy in YOD, further supporting its use as a nonspecific marker of neurodegeneration severity.

Cerebrospinal fluid levels of fatty acid-binding protein 3 are associated with likelihood of amyloidopathy in cognitively healthy individuals.

Introduction: Fatty acid-binding protein 3 (FABP3) is a biomarker of neuronal membrane disruption, associated with lipid dyshomeostasis-a notable Alzheimer's disease (AD) pathophysiological change. We assessed the association of cerebrospinal fluid (CSF) FABP3 levels with brain amyloidosis and the likelihood/risk of developing amyloidopathy in cognitively healthy individuals. Methods: FABP3 levels were measured in CSF samples of cognitively healthy participants, > 60 years of age (n = 142), from the Australian Imaging, Biomarkers & Lifestyle Flagship Study of Ageing (AIBL). Results: FABP3 levels were positively associated with baseline brain amyloid beta (Aß) load as measured by standardized uptake value ratio (SUVR, standardized ß = 0.22, P = .009) and predicted the change in brain Aß load (standardized ß = 0.32, P = .004). Higher levels of CSF FABP3 (above median) were associated with a likelihood of amyloidopathy (odds ratio [OR] 2.28, 95% confidence interval [CI] 1.12 to 4.65, P = .023). Discussion: These results support inclusion of CSF FABP3 as a biomarker in risk-prediction models of AD.

Human Perception of Wrist Flexion and Extension Torque During Upper and Lower Extremity Movement.

Real-world application of haptic feedback from kinesthetic devices is implemented while the user is in motion, but human wrist torque magnitude discrimination has previously only been characterized while users are stationary. In this study, we measured wrist torque discrimination in conditions relevant to activities of daily living, using a previously developed backdrivable wrist exoskeleton capable of applying wrist flexion and extension torque. We implemented a torque comparison test using a two-alternative forced-choice paradigm while participants were both seated and walking on a treadmill, with both a stationary and a moving wrist. Like most kinesthetic haptic devices, the wrist exoskeleton output torque is commanded in an open-loop manner. Thus, the study design was informed by Monte Carlo simulations to verify that the errors in the wrist exoskeleton output torque would not significantly affect the results. Results from ten participants show that although both walking and moving wrist conditions result in higher Weber Fractions (worse perception), participants were able to detect relatively small changes in torque of 12-19% on average in all grouped conditions. The results provide insight regarding the torque magnitudes necessary to make wrist-worn kinesthetic haptic devices noticeable and meaningful to the user in various conditions relevant to activities of daily living.

Plasma p-tau181/Aß1-42 ratio predicts Aß-PET status and correlates with CSF-p-tau181/Aß1-42 and future cognitive decline.

Background: In Alzheimer's disease (AD), plasma amyloid beta (Aß)1-42 and phosphorylated tau (p-tau) predict high amyloid status from Aß positron emission tomography (PET); however, the extent to which combination of these plasma assays can predict remains unknown. Methods: Prototype Simoa assays were used to measure plasma samples from participants who were either cognitively normal (CN) or had mild cognitive impairment (MCI)/AD in the Australian Imaging, Biomarkers and Lifestyle (AIBL) study. Results: The p-tau181/Aß1-42 ratio showed the best prediction of Aß-PET across all participants (area under the curve [AUC] = 0.905, 95% confidence interval [CI]: 0.86-0.95) and in CN (AUC = 0.873; 0.80-0.94), and symptomatic (AUC = 0.908; 0.82-1.00) adults. Plasma p-tau181/Aß1-42 ratio correlated with cerebrospinal fluid (CSF) p-tau181 (Elecsys, Spearman's ρ = 0.74, P < 0.0001) and predicted abnormal CSF Aß (AUC = 0.816; 0.74-0.89). The p-tau181/Aß1-42 ratio also predicted future rates of cognitive decline assessed by AIBL Preclinical Alzheimer Cognitive Composite or Clinical Dementia Rating Sum of Boxes (P < 0.0001). Discussion: Plasma p-tau181/Aß1-42 ratio predicted both Aß-PET status and cognitive decline, demonstrating potential as both a diagnostic aid and as a screening and prognostic assay for preclinical AD trials.

Cerebrospinal fluid neurofilament light chain differentiates behavioural variant frontotemporal dementia progressors from non-progressors.

BACKGROUND: Distinguishing behavioural variant frontotemporal dementia (bvFTD) from non-neurodegenerative 'non-progressor' mimics of frontal lobe dysfunction, can be one of the most challenging clinical dilemmas. A biomarker of neuronal injury, neurofilament light chain (NfL), could reduce misdiagnosis and delay. METHODS: Cerebrospinal fluid (CSF) NfL, amyloid beta 1-42 (AB42), total and phosphorylated tau (T-tau, P-tau) levels were examined in patients with an initial diagnosis of bvFTD. Based on follow-up information, patients were categorised as Progressors or Non-Progressors: further subtyped into Non-Progressor Revised (non-neurological/neurodegenerative final diagnosis), and Non-Progressor Static (static deficits, not fully explained by non-neurological/neurodegenerative causes). RESULTS: Forty-three patients were included: 20 Progressors, 23 Non-Progressors (15 Non-Progressor Revised, 8 Non-Progressor Static), and 20 controls. NfL concentrations were lower in Non-Progressors (Non-Progressors Mean, M = 554 pg/mL, 95%CI:[461, 675], Non-Progressor Revised M = 459 pg/mL, 95%CI:[385, 539], and Non-Progressor Static M = 730 pg/mL, 95%CI:[516, 940]), compared to Progressors (M = 2397 pg/mL, 95%CI:[1607, 3332]). NfL distinguished Progressors from Non-Progressors with the highest accuracy (area under the curve 0.92, 90%/87% sensitivity/specificity, 86%/91% positive/negative predictive value, 88% accuracy). Non-Progressor Static tended to have higher T-tau and P-tau levels compared to Non-Progressor Revised Diagnoses. CONCLUSION: This study demonstrated strong diagnostic utility of CSF NfL to distinguish bvFTD from non-progressor variants, at baseline, with high accuracy, in a real-world clinical setting. This has important clinical implications, to improve outcomes for patients and clinicians facing this challenging clinical dilemma, healthcare services, and clinical trials. Further research is required to investigate heterogeneity within the non-progressor group and potential diagnostic algorithms, and prospective studies are underway assessing plasma NfL.

Personalizing exoskeleton assistance while walking in the real world.

Personalized exoskeleton assistance provides users with the largest improvements in walking speed1 and energy economy2-4 but requires lengthy tests under unnatural laboratory conditions. Here we show that exoskeleton optimization can be performed rapidly and under real-world conditions. We designed a portable ankle exoskeleton based on insights from tests with a versatile laboratory testbed. We developed a data-driven method for optimizing exoskeleton assistance outdoors using wearable sensors and found that it was equally effective as laboratory methods, but identified optimal parameters four times faster. We performed real-world optimization using data collected during many short bouts of walking at varying speeds. Assistance optimized during one hour of naturalistic walking in a public setting increased self-selected speed by 9 ± 4% and reduced the energy used to travel a given distance by 17 ± 5% compared with normal shoes. This assistance reduced metabolic energy consumption by 23 ± 8% when participants walked on a treadmill at a standard speed of 1.5 m s-1. Human movements encode information that can be used to personalize assistive devices and enhance performance.