Analyzing entropy features in time-series data for pattern recognition in neurological conditions.

In the field of medical diagnosis and patient monitoring, effective pattern recognition in neurological time-series data is essential. Traditional methods predominantly based on statistical or probabilistic learning and inference often struggle with multivariate, multi-source, state-varying, and noisy data while also posing privacy risks due to excessive information collection and modeling. Furthermore, these methods often overlook critical statistical information, such as the distribution of data points and inherent uncertainties. To address these challenges, we introduce an information theory-based pipeline that leverages specialized features to identify patterns in neurological time-series data while minimizing privacy risks. We incorporate various entropy methods based on the characteristics of different scenarios and entropy. For stochastic state transition applications, we incorporate Shannon's entropy, entropy rates, entropy production, and the von Neumann entropy of Markov chains. When state modeling is impractical, we select and employ approximate entropy, increment entropy, dispersion entropy, phase entropy, and slope entropy. The pipeline's effectiveness and scalability are demonstrated through pattern analysis in a dementia care dataset and also an epileptic and a myocardial infarction dataset. The results indicate that our information theory-based pipeline can achieve average performance improvements across various models on the recall rate, F1 score, and accuracy by up to 13.08 percentage points, while enhancing inference efficiency by reducing the number of model parameters by an average of 3.10 times. Thus, our approach opens a promising avenue for improved, efficient, and critical statistical information-considered pattern recognition in medical time-series data.

Digital remote monitoring for screening and early detection of urinary tract infections.

Urinary Tract Infections (UTIs) are one of the most prevalent bacterial infections in older adults and a significant contributor to unplanned hospital admissions in People Living with Dementia (PLWD), with early detection being crucial due to the predicament of reporting symptoms and limited help-seeking behaviour. The most common diagnostic tool is urine sample analysis, which can be time-consuming and is only employed where UTI clinical suspicion exists. In this method development and proof-of-concept study, participants living with dementia were monitored via low-cost devices in the home that passively measure activity, sleep, and nocturnal physiology. Using 27828 person-days of remote monitoring data (from 117 participants), we engineered features representing symptoms used for diagnosing a UTI. We then evaluate explainable machine learning techniques in passively calculating UTI risk and perform stratification on scores to support clinical translation and allow control over the balance between alert rate and sensitivity and specificity. The proposed UTI algorithm achieves a sensitivity of 65.3% (95% Confidence Interval (CI) = 64.3-66.2) and specificity of 70.9% (68.6-73.1) when predicting UTIs on unseen participants and after risk stratification, a sensitivity of 74.7% (67.9-81.5) and specificity of 87.9% (85.0-90.9). In addition, feature importance methods reveal that the largest contributions to the predictions were bathroom visit statistics, night-time respiratory rate, and the number of previous UTI events, aligning with the literature. Our machine learning method alerts clinicians of UTI risk in subjects, enabling earlier detection and enhanced screening when considering treatment.

The Study of the Caudal Vertebrae of Thick-Toed Geckos after a Prolonged Space Flight by X-ray Phase-Contrast Micro-CT.

The proximal caudal vertebrae and notochord in thick-toed geckos (TG) (Chondrodactylus turneri, Gray, 1864) were investigated after a 30-day space flight onboard the biosatellite Bion-M1. This region has not been explored in previous studies. Our research focused on finding sites most affected by demineralization caused by microgravity (G0). We used X-ray phase-contrast tomography to study TG samples without invasive prior preparation to clarify our previous findings on the resistance of TG's bones to demineralization in G0. The results of the present study confirmed that geckos are capable of preserving bone mass after flight, as neither cortical nor trabecular bone volume fraction showed statistically significant changes after flight. On the other hand, we observed a clear decrease in the mineralization of the notochordal septum and a substantial rise in intercentrum volume following the flight. To monitor TG's mineral metabolism in G0, we propose to measure the volume of mineralized tissue in the notochordal septum. This technique holds promise as a sensitive approach to track the demineralization process in G0, given that the volume of calcification within the septum is limited, making it easy to detect even slight changes in mineral content.

TIHM: An open dataset for remote healthcare monitoring in dementia.

Dementia is a progressive condition that affects cognitive and functional abilities. There is a need for reliable and continuous health monitoring of People Living with Dementia (PLWD) to improve their quality of life and support their independent living. Healthcare services often focus on addressing and treating already established health conditions that affect PLWD. Managing these conditions continuously can inform better decision-making earlier for higher-quality care management for PLWD. The Technology Integrated Health Management (TIHM) project developed a new digital platform to routinely collect longitudinal, observational, and measurement data, within the home and apply machine learning and analytical models for the detection and prediction of adverse health events affecting the well-being of PLWD. This work describes the TIHM dataset collected during the second phase (i.e., feasibility study) of the TIHM project. The data was collected from homes of 56 PLWD and associated with events and clinical observations (daily activity, physiological monitoring, and labels for health-related conditions). The study recorded an average of 50 days of data per participant, totalling 2803 days.

Bridging the Gap between Gut Microbiota and Alzheimer's Disease: A Metaproteomic Approach for Biomarker Discovery in Transgenic Mice.

Alzheimer's Disease (AD) is a progressively debilitating form of dementia that affects millions of individuals worldwide. Although a vast amount of research has investigated the complex interplay between gut microbiota and neurodegeneration, the metaproteomic effects of microbiota on AD pathogenesis remain largely uncharted territory. This study aims to reveal the role of gut microbiota in AD pathogenesis, particularly regarding changes in the proteome and molecular pathways that are intricately linked to disease progression. We operated state-of-the-art Nano-Liquid Chromatography Mass Spectrometry (nLC-MS/MS) to compare the metaproteomic shifts of 3-month-old transgenic (3M-ALZ) and control (3M-ALM, Alzheimer's Littermate) mice, depicting the early onset of AD with those of 12-month-old ALZ and ALM mice displaying the late stage of AD. Combined with computational analysis, the outcomes of the gut-brain axis-focused inquiry furnish priceless knowledge regarding the intersection of gut microbiota and AD. Accordingly, our data indicate that the microbiota, proteome, and molecular changes in the intestine arise long before the manifestation of disease symptoms. Moreover, disparities exist between the normal-aged flora and the gut microbiota of late-stage AD mice, underscoring that the identified vital phyla, proteins, and pathways hold immense potential as markers for the early and late stages of AD. Our research endeavors to offer a comprehensive inquiry into the intricate interplay between gut microbiota and Alzheimer's Disease utilizing metaproteomic approaches, which have not been widely adopted in this domain. This highlights the exigency for further scientific exploration to elucidate the underlying mechanisms that govern this complex and multifaceted linkage.

New Cretaceous empidoids and the Mesozoic dance fly revolution (Diptera: Empidoidea).

Dance flies and relatives (Empidoidea) are a diverse and ecologically important group of Diptera in nearly all modern terrestrial ecosystems. Their fossil record, despite being scattered, attests to a long evolutionary history dating back to the early Mesozoic. Here, we describe seven new species of Empidoidea from Cretaceous Kachin amber inclusions, assigning them to the new genus Electrochoreutes gen.n. (type species: Electrochoreutes trisetigerus sp.n.) based on unique apomorphies among known Diptera. Like many extant dance flies, the males of Electrochoreutes are characterized by species-specific sexually dimorphic traits, which are likely to have played a role in courtship. The fine anatomy of the fossils was investigated through high-resolution X-ray phase-contrast microtomography to reconstruct their phylogenetic affinities within the empidoid clade, using cladistic reasoning. Morphology-based phylogenetic analyses including a selection of all extant family- and subfamily-ranked empidoid clades along with representatives of all extinct Mesozoic genera, were performed using a broad range of analytical methods (maximum parsimony, maximum-likelihood and Bayesian inference). These analyses converged in reconstructing Electrochoreutes as a stem-group representative of the Dolichopodidae, suggesting that complex mating rituals evolved in this lineage during the Cretaceous.

Micromorphology of pineal gland calcification in age-related neurodegenerative diseases.

BACKGROUND: The formation of concrements in human pineal gland (PG) is a physiological process and, according to many researchers, is associated with the involution of PG structures. The majority of scientific publications concern progressive calcification of PG, leaving out studies on the destruction of already formed calcified concrements. Our study fills the gap in knowledge about calcified zones destruction in PG in normal aging and neuropathological conditions, which has not been addressed until now. PURPOSE: Our objective is to gain insight into human PG tissue impairment in both normal aging and neurodegenerative conditions. X-ray phase-contrast tomography (XPCT) allowed us to study PG tissue degeneration at high spatial resolution and, for the first time, to examine the damaged PG concrements in detail. Our research finding could potentially enhance the understanding of the PG involvement in the process of aging as well as in Alzheimer's disease (AD) and vascular dementia (VD). METHODS: The research was carried out on human PG autopsy material in normal aging, VD, and AD conditions. Laboratory-based micro-computed tomography (micro-CT) was used to collect and evaluate samples of native, uncut, and unstained PG with different degrees of pineal calcification. The detailed high-resolution 3D images of the selected PGs were produced using synchrotron-based XPCT. Histology and immunohistochemistry of soft PG tissue confirmed XPCT results. RESULTS: We performed via micro-CT the evaluation of the morphometric parameters of PG such as total sample volume, calcified concrements volume, and percentage of concrements in the total volume of the sample. XPCT imaging revealed high-resolution details of age-related PG alteration. In particular, we noted signs of moderate degradation of concrements in some PGs from elderly donors. In addition, our analysis revealed noticeable degenerative change in both concrements and soft tissue of PGs with neuropathology. In particular, we observed a hollow core and separated layers as well as deep ragged cracks in PG concrements of AD and VD samples. In parenchyma of some samples, we detected wide pinealocyte-free fluid-filled areas adjacent to the calcified zones. CONCLUSION: The present work provides the basis for future scientific research focused on the dynamic nature of PG calcium deposits and PG soft tissue in normal aging and neurodegenerative diseases.

Corrigendum: X-ray Phase Contrast Tomography Serves Preclinical Investigation of Neurodegenerative Diseases.

[This corrects the article DOI: 10.3389/fnins.2020.584161.].

A computational platform for the virtual unfolding of Herculaneum Papyri.

Ancient Herculaneum papyrus scrolls, hopelessly charred in the 79 A.D. Vesuvius eruption, contain valuable writings of the Greek philosophers of the day, including works of the Epicurean Philodemus. X-ray phase contrast tomography has recently begun unlocking their secrets. However, only small portions of the text hidden inside the scroll have been recover. One of the challenging tasks in Herculaneum papyri investigation is their virtual unfolding because of their highly complicated structure and three-dimensional arrangement. Although this procedure is feasible, problems in segmentation and flattening hinder the unrolling of a large portion of papyrus. We propose a computational platform for the virtual unfolding procedure, and we show the results of its application on two Herculaneum papyrus fragments. This work paves the way to a comprehensive survey and to further interpretation of larger portions of text hidden inside the carbonized Herculaneum papyri.

X-ray Phase Contrast Tomography Serves Preclinical Investigation of Neurodegenerative Diseases.

We report a qualitative study on central nervous system (CNS) damage that demonstrates the ability of X-ray phase contrast tomography (XPCT) to confirm data obtained with standard 2D methodology and permits the description of additional features that are not detected with 2D or other 3D techniques. In contrast to magnetic resonance or computed tomography, XPCT makes possible the high-resolution 3D imaging of soft tissues classically considered "invisible" to X-rays without the use of additional contrast agents, or without the need for intense processing of the tissue required by 2D techniques. Most importantly for studies of CNS diseases, XPCT enables a concomitant multi-scale 3D biomedical imaging of neuronal and vascular networks ranging from cells through to the CNS as a whole. In the last years, we have used XPCT to investigate neurodegenerative diseases, such as Alzheimer's disease (AD) and multiple sclerosis (MS), to shed light on brain damage and extend the observations obtained with standard techniques. Here, we show the cutting-edge ability of XPCT to highlight in 3D, concomitantly, vascular occlusions and damages, close associations between plaques and damaged vessels, as well as dramatic changes induced at neuropathological level by treatment in AD mice. We corroborate data on the well-known blood-brain barrier dysfunction in the animal model of MS, experimental autoimmune encephalomyelitis, and further show its extent throughout the CNS axis and at the level of the single vessel/capillary.

Investigation of the human pineal gland 3D organization by X-ray phase contrast tomography.

Pineal gland (PG) is a part of the human brain epithalamus that plays an important role in sleep, circadian rhythm, immunity, and reproduction. The calcium deposits and lesions in PG interfere with normal function of the organ and can be associated with different health disorders including serious neurological diseases. At the moment, the detailed mechanisms of PG calcifications and PG lesions formation as well as their involvement in pathological processes are not fully understood. The deep and comprehensive study of the structure of the uncut human PG with histological details, poses a stiff challenge to most imaging techniques, due to low spatial resolution, low visibility or to exceedingly aggressive sample preparation. Here, we investigate the whole uncut and unstained human post-mortem PGs by X-ray phase contrast tomography (XPCT). XPCT is an advanced 3D imaging technique, that permits to study of both soft and calcified tissue of a sample at different scales: from the whole organ to cell structure. In our research we simultaneously resolved 3D structure of parenchyma, vascular network and calcifications. Moreover, we distinguished structural details of intact and degenerated PG tissue. We discriminated calcifications with different structure, pinealocytes nuclei and the glial cells processes. All results were validated by histology. Our research clear demonstrated that XPCT is a potential tool for the high resolution 3D imaging of PG morphological features. This technique opens a new perspective to investigate PG dysfunction and understand the mechanisms of onset and progression of diseases involving the pineal gland.

Multiscale pink-beam microCT imaging at the ESRF-ID17 biomedical beamline.

Recent trends in hard X-ray micro-computed tomography (microCT) aim at increasing both spatial and temporal resolutions. These challenges require intense photon beams. Filtered synchrotron radiation beams, also referred to as `pink beams', which are emitted by wigglers or bending magnets, meet this need, owing to their broad energy range. In this work, the new microCT station installed at the biomedical beamline ID17 of the European Synchrotron is described and an overview of the preliminary results obtained for different biomedical-imaging applications is given. This new instrument expands the capabilities of the beamline towards sub-micrometre voxel size scale and simultaneous multi-resolution imaging. The current setup allows the acquisition of tomographic datasets more than one order of magnitude faster than with a monochromatic beam configuration.

A time-dependent study of nano-mechanical and ultrastructural properties of internal limiting membrane under ocriplasmin treatment.

Vitreomacular traction (VMT) syndrome has only been surgically treated for a long time. Recently, enzymatic vitreolysis with ocriplasmin has emerged as a possible option to release VMT and, in some cases, close full thickness macular holes (FTMHs). Despite its clinical relevance, gathering information about the ocriplasmin-induced alterations of the Inner Limiting Membrane (ILM) of the retina in a clinical study is a complex task, mainly because of the inter-individual variability among patients. To obtain more insights into the mechanism underlying the drug action, we studied in-vitro the mechanical and morphological changes of the ILM using Atomic Force Microscopy (AFM). To this aim, we measured the ILM average Young's modulus (YM), hysteresis (H) and adhesion work (A) over time under ocriplasmin treatment. Our data unveil a time-dependent increase in the membrane YM of 19% of its initial value, along with changes in its adhesive and dissipative behavior. Such modifications well correlate with the morphological alterations detected in the AFM imaging mode. Taken all together, the results here presented provide more insights into the mechanism underlying the ocriplasmin action in-vivo, suggesting that it is only able to alter the top-most layer of the vitreal side of the membrane, not compromising the inner ILM structure.

Automatic Fracture Characterization Using Tactile and Proximity Optical Sensing.

This paper demonstrates how tactile and proximity sensing can be used to perform automatic mechanical fractures detection (surface cracks). For this purpose, a custom-designed integrated tactile and proximity sensor has been implemented. With the help of fiber optics, the sensor measures the deformation of its body, when interacting with the physical environment, and the distance to the environment's objects. This sensor slides across different surfaces and records data which are then analyzed to detect and classify fractures and other mechanical features. The proposed method implements machine learning techniques (handcrafted features, and state of the art classification algorithms). An average crack detection accuracy of ~94% and width classification accuracy of ~80% is achieved. Kruskal-Wallis results (p < 0.001) indicate statistically significant differences among results obtained when analysing only integrated deformation measurements, only proximity measurements and both deformation and proximity data. A real-time classification method has been implemented for online classification of explored surfaces. In contrast to previous techniques, which mainly rely on visual modality, the proposed approach based on optical fibers might be more suitable for operation in extreme environments (such as nuclear facilities) where radiation may damage electronic components of commonly employed sensing devices, such as standard force sensors based on strain gauges and video cameras.

X-ray phase contrast tomography for the investigation of amyotrophic lateral sclerosis.

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder affecting motor neurons. Pre-clinical studies drive the development of animal models that well mimic ALS disorder and enable both the dissection of disease processes and an early assessment of therapy efficacy. A comprehensive knowledge of neuronal and vascular lesions in the brain and spinal cord is an essential factor to understand the development of the disease. Spatial resolution and bidimensional imaging are important drawbacks limiting current neuroimaging tools, while neuropathology relies on protocols that may alter tissue chemistry and structure. In contrast, recent ex vivo studies in mice demonstrated that X-ray phase-contrast tomography enables study of the 3D distribution of both vasculature and neuronal networks, without sample sectioning or use of staining. Here we present our findings on ex vivo SOD1G93A ALS mice spinal cord at a micrometric scale. An unprecedented direct quantification of neuro-vascular alterations at different stages of the disease is shown.

Nanomechanical mapping helps explain differences in outcomes of eye microsurgery: A comparative study of macular pathologies.

Many ocular diseases are associated with an alteration of the mechanical and the material properties of the eye. These mechanically-related diseases include macular hole and pucker, two ocular conditions due to the presence of abnormal physical tractions acting on the retina. A complete relief of these tractions can be obtained through a challenging microsurgical procedure, which requires the mechanical peeling of the internal limiting membrane of the retina (ILM). In this paper, we provide the first comparative study of the nanoscale morphological and mechanical properties of the ILM in macular hole and macular pucker. Our nanoscale elastic measurements unveil a different bio-mechanical response of the ILM in the two pathologies, which correlates well to significant differences occurring during microsurgery. The results here presented pave the way to the development of novel dedicated microsurgical protocols based on the material ILM properties in macular hole or pucker. Moreover, they contribute to clarify why, despite a common aetiology, a patient might develop one disease or the other, an issue which is still debated in literature.

Nanoscale mechanics of brain abscess: An atomic force microscopy study.

Mechanical stimuli are a fundamental player in the pathophysiology of the brain influencing its physiological development and contributing to the onset and progression of many diseases. In some pathological states, the involvement of mechanical and physical stimuli might be extremely subtle; in others, it is more evident and particularly relevant. Among the latter pathologies, one of the most serious life-threatening condition is the brain abscess (BA), a focal infection localized in the brain parenchyma, which causes large brain mechanical deformations, giving rise to a wide range of neurological impairments. In this paper, we present the first nano-mechanical characterization of surgically removed human brain abscess tissues by means of atomic force microscopy (AFM) in the spectroscopy mode. Consistently with previous histological findings, we modeled the brain abscess as a multilayered structure, composed of three main layers: the cerebritis layer, the collagen capsule, and the internal inflammatory border. We probed the viscoelastic behavior of each layer separately through the measure of the apparent Young's modulus (E), that gives information about the sample stiffness, and the AFM hysteresis (H), that estimates the contribution of viscous and dissipative forces. Our experimental findings provide a full mechanical characterization of the abscess, showing an average E of (94 ±â€¯5) kPa and H of 0.37 ±â€¯0.01 for the cerebritis layer, an average E = (1.04 ±â€¯0.05) MPa and H = 0.10 ±â€¯0.01 for the collagen capsule and an average E = (9.8 ±â€¯0.4) kPa and H = 0.57 ±â€¯0.01 for the internal border. The results here presented have the potential to contribute to the development of novel surgical instruments dedicated to the treatment of the pathology and to stimulate the implementation of novel constitutive mechanical models for the estimation of brain compression and damage during BA progression.

Repeatability of grasp recognition for robotic hand prosthesis control based on sEMG data.

Control methods based on sEMG obtained promising results for hand prosthetics. Control system robustness is still often inadequate and does not allow the amputees to perform a large number of movements useful for everyday life. Only few studies analyzed the repeatability of sEMG classification of hand grasps. The main goals of this paper are to explore repeatability in sEMG data and to release a repeatability database with the recorded experiments. The data are recorded from 10 intact subjects repeating 7 grasps 12 times, twice a day for 5 days. The data are publicly available on the Ninapro web page. The analysis for the repeatability is based on the comparison of movement classification accuracy in several data acquisitions and for different subjects. The analysis is performed using mean absolute value and waveform length features and a Random Forest classifier. The accuracy obtained by training and testing on acquisitions at different times is on average 27.03% lower than training and testing on the same acquisition. The results obtained by training and testing on different acquisitions suggest that previous acquisitions can be used to train the classification algorithms. The inter-subject variability is remarkable, suggesting that specific characteristics of the subjects can affect repeatibility and sEMG classification accuracy. In conclusion, the results of this paper can contribute to develop more robust control systems for hand prostheses, while the presented data allows researchers to test repeatability in further analyses.