Robust antibody response after a third BNT162b2 vaccine compared to the second among immunocompromised and healthy individuals,a prospective longitudinal cohort study

PurposeAs protection from COVID-19 following two doses of the BNT162b2 vaccine showed a time dependent waning, a third (booster) dose was administrated. This study aims to compare the antibody response following the third dose versus the second and to evaluate post-booster seroconversion.MethodsA prospective observational study conducted in Maccabi Healthcare Services. Serial SARS-CoV-2 Spike IgG tests, 1,2,3 and 6 months following the second vaccine dose and one month following the third were obtained. Neutralizing antibody levels were measured in a subset of participants. Per individual SARS-CoV-2 Spike IgG titer ratios were calculated one month after the booster administration compared to titers one month following the second dose and prior to booster.ResultsAmong 110 participants, 56 (51%) were women. Mean age was 61.7 ± 1.9 years and 66 (60%) were immunocompromised. One month after third dose, IgG titers were induced 7.83 (95 %CI 5.25–11.67) folds and 2.40 (95 %CI 1.90–3.03) folds compared to one month after the second, in the immunocompromised and immunocompetent groups, respectively. Of the 17 immunocompromised participants who were seronegative after the second dose, 4 (24%) became seropositive following the third. Comparing the titers prior to the third dose, an increase of 50.7 (95 %CI 32.5–79.1) fold in the immunocompromised group and 25.7 (95 %CI 19.1–34.7) fold in and immunocompetent group, was observed.ConclusionA third BNT162b2 vaccine elicited robust humoral response, superior to the response observed following the second, among immunocompetent and immunocompromised individuals.     

ImmunoPET imaging of hematological malignancies: From preclinical promise to clinical reality

Immuno-positron emission tomography (immunoPET) imaging is a paradigm-shifting imaging technique for whole-body and all-lesion tumor detection, based on the combined specificity of tumor-targeting vectors [e.g., monoclonal antibodies (mAbs), nanobodies, and bispecific antibodies] and the sensitivity of PET imaging. By noninvasively, comprehensively, and serially revealing heterogeneous tumor antigen expression, immunoPET imaging is gradually improving the theranostic prospects for hematological malignancies. In this review, we summarize the available literature regarding immunoPET in imaging hematological malignancies. We also highlight the pros and cons of current conjugation strategies, and modular chemistry that can be leveraged to develop novel immunoPET probes for hematological malignancies. Lastly, we discuss the use of immunoPET imaging in guiding antibody drug development.     

Evaluation of unsupervised 30-second chair stand test performance assessed by wearable sensors to predict fall status in multiple sclerosis

BackgroundOne in two people with multiple sclerosis (PwMS) will fall in a three-month period. Predicting which patients will fall remains a challenge for clinicians. Standardized functional assessments provide insight into balance deficits and fall risk but their use has been limited to supervised visits.Research questionThe study aim was to characterize unsupervised 30-second chair stand test (30CST) performance using accelerometer-derived metrics and assess its ability to classify fall status in PwMS compared to supervised 30CST.MethodsThirty-seven PwMS (21 fallers) performed instrumented supervised and unsupervised 30CSTs with a single wearable sensor on the thigh. In unsupervised conditions, participants performed bi-hourly 30CSTs and rated their balance confidence and fatigue over 48-hours. ROC analysis was used to classify fall status for 30CST performance.ResultsNon-fallers (p = 0.02) but not fallers (p = 0.23) differed in their average unsupervised 30CST performance (repetitions) compared to their supervised performance. The unsupervised maximum number of 30CST repetitions performed optimized ROC classification AUC (0.79), accuracy (78.4%) and specificity (90.0%) for fall status with an optimal cutoff of 17 repetitions.SignificanceBrief durations of instrumented unsupervised monitoring as an adjunct to routine clinical assessments could improve the ability for predicting fall risk and fluctuations in functional mobility in PwMS.     

General vaccination willingness and current vaccination status in relation to clinical and psychological variables in patients with multiple sclerosis

BackgroundInfections can have a significant impact on morbidity and mortality in multiple sclerosis (MS) patients. Therefore, vaccinations are of immense importance. If vaccination willingness is to be increased, possible influencing factors should be identified. The aim of the present study was to investigate the status of active immunisation in MS patients in association with sociodemographic, clinical-neurological, psychopathological and personality variables using the NEO-Five Factor Inventory, the Temperament and Character Inventory-Revised and the Hospital Anxiety and Depression Scale.MethodFour hundred and four MS patients from two German neurological hospitals were examined for their vaccination attitudes, in detail, the general willingness to vaccinate and the current vaccination status of mumps, measles and rubella (MMR) as well as tetanus and influenza. We also looked at the current level of disability in relation to the current vaccination status, as well as possible associated personality and psychopathological variables.ResultsPatients with a complete MMR vaccination status were significantly younger and those with a complete influenza vaccination status were significantly older than those with related incomplete vaccination status. Tetanus vaccination status completeness did not differ depending on age and did not show substantial association with personality scores. However, influenza vaccination completeness was associated with differences in personality and psychopathological variables; extraversion, openness, novelty seeking, harm avoidance and anxiety. A reported general vaccination willingness was significantly correlated with the current completeness of tetanus and influenza vaccinations. Novelty seeking, persistence, extraversion, agreeableness, conscientiousness and neuroticism were found associated with an increased vaccination willingness. Anxiety and depression were not related to general vaccination willingness.ConclusionsNo specific personality trait could be defined on its own in relation to general vaccination willingness or complete vaccination status. Younger patients should be made more aware of influenza vaccination. Reasons for rather low vaccination rates need to be further investigated.     

U-turn speed is a valid and reliable smartphone-based measure of multiple sclerosis-related gait and balance impairment

BackgroundPeople living with multiple sclerosis (MS) experience impairments in gait and mobility, that are not fully captured with manually timed walking tests or rating scales administered during periodic clinical visits. We have developed a smartphone-based assessment of ambulation performance, the 5 U-Turn Test (5UTT), a quantitative self-administered test of U-turn ability while walking, for people with MS (PwMS).Research questionWhat is the test-retest reliability and concurrent validity of U-turn speed, an unsupervised self-assessment of gait and balance impairment, measured using a body-worn smartphone during the 5UTT?Methods76 PwMS and 25 healthy controls (HCs) participated in a cross-sectional non-randomised interventional feasibility study. The 5UTT was self-administered daily and the median U-turn speed, measured during a 14-day session, was compared against existing validated in-clinic measures of MS-related disability.ResultsU-turn speed, measured during a 14-day session from the 5UTT, demonstrated good-to-excellent test-retest reliability in PwMS alone and combined with HCs (intraclass correlation coefficient [ICC] = 0.87 [95 % CI: 0.80–0.92]) and moderate-to-excellent reliability in HCs alone (ICC = 0.88 [95 % CI: 0.69–0.96]). U-turn speed was significantly correlated with in-clinic measures of walking speed, physical fatigue, ambulation impairment, overall MS-related disability and patients’ self-perception of quality of life, at baseline, Week 12 and Week 24. The minimal detectable change of the U-turn speed from the 5UTT was low (19.42 %) in PwMS and indicates a good precision of this measurement tool when compared with conventional in-clinic measures of walking performance.SignificanceThe frequent self-assessment of turn speed, as an outcome measure from a smartphone-based U-turn test, may represent an ecologically valid digital solution to remotely and reliably monitor gait and balance impairment in a home environment during MS clinical trials and practice.     

Compensatory postural responses to backward loss of balance in patients with cerebellar disease

BackgroundImpaired control of balance and coordinated reactions are a primary deficit of cerebellar dysfunction. As compared to other neurological patients with balance impairments, there has been little research assessing the characteristics of compensatory responses associated with falls in patients with cerebellar disease (CD).Research questionThe aim of this study was to examine the effects of cerebellar disease on compensatory balance control in response to postural perturbation. Do CD patients increase the number of steps when responding to instability because of inappropriate initial step reactions or poor control of trunk motion or both?MethodsIn this explorative study, 10 patients suffering from degenerative cerebellar ataxia and 10 age-matched healthy controls were examined. The balance recovery reactions were assessed using a lean-and-release postural perturbation method. Spatiotemporal characteristics of stepping movement and COM variables associated with torso motion were analyzed using 3D motion capture system.ResultsCD patients took multiple steps whereas matched controls generally took single steps to recover balance following perturbation. The characteristics of the initial step at the time of the fall revealed that foot reaction time, foot response time, and step distance of the initial step were similar between CD patients and matched controls. However, CD patients exhibited a shorter foot-to−COM distance, higher COM velocity, and less trunk flexion with which to attenuate their body momentum after the landing of the first step than did matched controls.SignificanceAlthough initial step responses were probably adequate, poor control of torso motion appears to be a particular problem that causes multiple-step reactions in CD patients. This observation would help to guide the development of tailored fall intervention strategies in CD patients aimed at promoting their recovery capacity in response to a pronounced balance challenge.     

Brain lipidomics as a rising field in neurodegenerative contexts: Perspectives with Machine Learning approaches

Lipids are essential for cellular functioning considering their role in membrane composition, signaling, and energy metabolism. The brain is the second most abundant organ in terms of lipid concentration and diversity only after adipose tissue. However, in the central system (CNS) lipid dysregulation has been linked to the etiology, progression, and severity of neurodegenerative diseases such as Alzheimeŕs, Parkinson, and Multiple Sclerosis. Advances in the human genome and subsequent sequencing technologies allowed us the study of lipidomics as a promising approach to diagnosis and treatment of neurodegeneration. Lipidomics advances rapidly increased the amount and quality of data allowing the integration with other omic types as well as implementing novel bioinformatic and quantitative tools such as machine learning (ML). Integration of lipidomics data with ML, as a powerful quantitative predictive approach, led to improvements in diagnostic biomarker prediction, clinical data integration, network, and systems approaches for neural behavior, novel etiology markers for inflammation, and neurodegeneration progression and even Mass Spectrometry image analysis. In this sense, by exploiting lipidomics data with ML is possible to improve the identification of new biomarkers or unveil new molecular mechanisms associated with lipid impairment across neurodegeneration. In this review, we present the lipidomic neurobiology state-of-the-art highlighting its potential applications to study neurodegenerative conditions. Also, we present theoretical background, applications, and advances in the integration of lipidomics with ML. This review opens the door to new approaches in this rising field.