Thursday, April 15, 2021

Cerebral autoregulation assessed by near-infrared spectroscopy: validation using transcranial Doppler in patients with controlled hypertension, cognitive impairment and controls

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Abstract

Purpose

Cerebral autoregulation (CA) aims to attenuate the effects of blood pressure variation on cerebral blood flow. This study assessed the criterion validity of CA derived from near-infrared spectroscopy (NIRS) as an alternative for Transcranial Doppler (TCD).

Methods

Measurements of continuous blood pressure (BP), oxygenated hemoglobin (O2Hb) using NIRS and cerebral blood flow velocity (CBFV) using TCD (gold standard) were performed in 82 controls, 27 patients with hypertension and 94 cognitively impaired patients during supine rest (all individuals) and repeated sit to stand transitions (cognitively impaired patients). The BP-CBFV and BP-O2Hb transfer function phase shifts (TFφ) were computed as CA measures. Spearman correlations (ρ) and Bland Altman limits of agreement (BAloa) between NIRS- and TCD-derived CA measures were computed. BAloa separation < 50° was considered a high absolute agreement.

Results

NIRS- and TCD-derived CA estimates were significantly correlated during supine rest (ρ = 0.22–0.30, N = 111–120) and repeated sit-to-stand transitions (ρ = 0.46–0.61, N = 19–32). BAloa separation ranged between 87° and 112° (supine rest) and 65°–77° (repeated sit to stand transitions).

Conclusion

Criterion validity of NIRS-derived CA measures allows for comparison between groups but was insufficient for clinical application in individuals.

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Learning Common Time-Frequency-Spatial Patterns for Motor Imagery Classification

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The common spatial patterns (CSP) algorithm is the most popular spatial filtering method applied to extract electroencephalogram (EEG) features for motor imagery (MI) based brain-computer interface (BCI) systems. The effectiveness of the CSP algorithm depends on optimal selection of the frequency band and time window from the EEG. Many algorithms have been designed to optimize frequency band selection for CSP, while few algorithms seek to optimize the time window. This study proposes a novel framework, termed common time-fr equency-spatial patterns (CTFSP), to extract sparse CSP features from multi-band filtered EEG data in multiple time windows. Specifically, the whole MI period is first segmented into multiple subseries using a sliding time window approach. Then, sparse CSP features are extracted from multiple frequency bands in each time window. Finally, multiple support vector machine (SVM) classifiers with the Radial Basis Function (RBF) kernel are trained to identify the MI tasks and the voting result of these classifiers determines the final output of the BCI. This study applies the proposed CTFSP algorithm to three public EEG datasets (BCI competition III dataset IVa, BCI competition III dataset IIIa, and BCI competition IV dataset 1) to validate its effectiveness, compared against several other state-of-the-art methods. The experimental results demonstrate that the proposed algorithm is a promising candidate for improving the performance of MI-BCI systems.
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Passive Knee Orthoses Assistance in Functional Electrical Stimulation Cycling in an Individual With Spinal Cord Injury

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Functional Electrical Stimulation (FES) may be used in rehabilitation and assistance of people with Spinal Cord Injury (SCI). One significant application is facilitating physical exercise, mainly when combining FES with mechanical platforms, such as tricycles. However, there are still technical challenges in FES cycling protocols, such as improving control and cycling performance. Here we show how passive elements in knee orthoses during FES cycling could increase the average cadence, taking advantage of the cycling movemen t. Our approach is twofold. First, we simulated the forward dynamics of a detailed musculoskeletal model with passive elements over the knees. Simulations showed that specific spring stiffness ranges increased the crankset speed during cycling by more than 50%. Using parameters found in simulations, we built a pair of passive orthoses and performed experiments with one individual with SCI. During two days, the volunteer cycled with similar stimulation magnitude with and without the passive elements. We observed that the average crankset speed was higher by more than 10% when the springs were attached to the passive orthoses. These results show the potential of using passive elements to increase cycling speed for FES cycling with similar or even lower stimulation magnitude, leading to longer exercise duration.
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Tumor immune landscape of paediatric high-grade gliomas

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Abstract
Over the last decade, remarkable progress has been made towards elucidating the origin and genomic landscape of childhood high-grade brain tumors. It has become evident that pediatric high-grade gliomas (pHGGs) differ from adult HGGs with respect to multiple defining aspects including: DNA copy number, gene expression profiles, tumor locations within the central nervous system, and genetic alterations such as somatic histone mutations. Despite these advances, clinical trials for children with glioma have historically been based on ineffective adult regimens that fail to take into consideration the fundamental biological differences between the two. Additionally, although our knowledge of the intrinsic cellular mechanisms driving tumor progression has considerably expanded, little is known concerning the dynamic tumor immune microenvironment (TIME) in pHGGs. In this review, we explore the genetic and epigenetic landscape of pHGGs and how this driv es the creation of specific tumor sub-groups with meaningful survival outcomes. Further, we provide a comprehensive analysis of the pHGG TIME and discuss emerging therapeutic efforts aimed at exploiting the immune functions of these tumors.
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The role of gut dysbiosis in Parkinson's disease: mechanistic insights andtherapeutic options

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Abstract
Parkinson's disease is a common neurodegenerative disease in which gastrointestinal symptoms may appear prior to motor symptoms. The gut microbiota of patients with Parkinson's disease shows unique changes, which may be used as early biomarkers of disease. Alteration in gut microbiota composition may be related to the cause or effect of motor or non-motor symptoms, but the specific pathogenic mechanisms are unclear. The gut microbiota and its metabolites have been suggested to be involved in the pathogenesis of Parkinson's disease by regulating neuroinflammation, barrier function and neurotransmitter activity. There is bidirectional communication between the enteric nervous system and the central nervous system, and the microbiota-gut-brain axis may provide a pathway for the transmission of α-synuclein. We highlight recent discoveries and alterations of the gut microbiota in Parkinson's disease, and highlight current mechanistic insights on the microbiota-gut-brain axis in disease pathophysiology. We discuss the interactions between production and transmission of α-synuclein and gut inflammation and neuroinflammation. In addition, we also draw attention to diet modification, use of probiotics and prebiotics and fecal microbiota transplantation as potential therapeutic approaches that may lead to a new treatment paradigm for Parkinson's disease.
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COVID-19 neuropathology

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Abstract
Many patients with SARS-CoV-2 infection develop neurological signs and symptoms, though, to date, little evidence exists that primary infection of the brain is a significant contributing factor. We present the clinical, neuropathological, and molecular findings of 41 consecutive patients with SARS-CoV-2 infections who died and underwent autopsy in our medical center. The mean age was 74 years (38–97 years), 27 patients (66%) were male and 34 (83%) were of Hispanic/Latinx ethnicity. Twenty-four patients (59%) were admitted to the intensive care unit (ICU). Hospital-associated complications were common, including 8 (20%) with deep vein thrombosis/pulmonary embolism (DVT/PE), 7 (17%) patients with acute kidney injury requiring dialysis, and 10 (24%) with positive blood cultures during admission. Eight (20%) patients died within 24 hours of hospital admission, while 11 (27%) died more than 4 weeks after hospital admission. Neuropathological examination of 20–30 areas from each brain revealed hypoxic/ischemic changes in all brains, both global and focal; large and small infarcts, many of which appeared hemorrhagic; and microglial activation with microglial nodules accompanied by neuronophagia, most prominently in the brainstem. We observed sparse T lymphocyte accumulation in either perivascular regions or in the brain parenchyma. Many brains contained atherosclerosis of large arteries and arteriolosclerosis, though none had evidence of vasculitis. Eighteen (44%) contained pathologies of neurodegenerative diseases, not unexpected given the age range of our patients. We examined multiple fresh frozen and fixed tissues from 28 brains for the presence of viral RNA and protein, using quantitative reverse-transcriptase PCR (qRT-PCR), RNAscope, and immunocytochemistry with primers, probes, and antibodies directed against the spike and nucleocapsid regions. qRT-PCR revealed low to very low, but detectable, viral RNA levels i n the majority of brains, although they were far lower than those in nasal epithelia. RNAscope and immunocytochemistry failed to detect viral RNA or protein in brains. Our findings indicate that the levels of detectable virus in COVID-19 brains are very low and do not correlate with the histopathological alterations. These findings suggest that microglial activation, microglial nodules and neuronophagia, observed in the majority of brains, do not result from direct viral infection of brain parenchyma, but rather likely from systemic inflammation, perhaps with synergistic contribution from hypoxia/ischemia. Further studies are needed to define whether these pathologies, if present in patients who survive COVID-19, might contribute to chronic neurological problems.
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A neurogenetic analysis of female autism

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Abstract
Females versus males are less frequently diagnosed with autism spectrum disorder (ASD), and while understanding sex differences is critical to delineating the systems biology of the condition, female ASD is understudied. We integrated functional MRI and genetic data in a sex-balanced sample of ASD and typically developing youth (8–17 years old) to characterize female-specific pathways of ASD risk. Our primary objectives were to: (i) characterize female ASD (n =45) brain response to human motion, relative to matched typically developing female youth (n =45); and (ii) evaluate whether genetic data could provide further insight into the potential relevance of these brain functional differences. For our first objective we found that ASD females showed markedly reduced response vers us typically developing females, particularly in sensorimotor, striatal, and frontal regions. This difference between ASD and typically developing females does not resemble differences between ASD (n =47) and typically developing males (n =47), even though neural response did not significantly differ between female and male ASD. For our second objective, we found that ASD females (n =61), versus males (n =66), showed larger median size of rare copy number variants containing gene(s) expressed in early life (10 postconceptual weeks to 2 years) in regions implicated by the typically developing female > female functional MRI contrast. Post hoc analyses suggested this difference was primarily driven by copy number variants containing gene(s) expressed in striatum. This striatal finding was reproducible among n =2075 probands (291 female) from an independent cohort. Together, our findings suggest that striatal impacts may contribute to pathways of risk in female ASD and advocate caution in drawing conclusions regarding female ASD based on male-predominant cohorts.
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Monitoring skin blood flow to rapidly identify alterations in tissue perfusion during fluid removal using continuous veno-venous hemofiltration in patients with circulatory shock

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Continuous veno-venous hemofiltration (CVVH) can be used to reduce fluid overload and tissue edema, but excessive fluid removal may impair tissue perfusion. Skin blood flow (SBF) alters rapidly in shock, so it...
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Outcome of acute kidney injury: how to make a difference?

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Acute kidney injury (AKI) is one of the most frequent organ failure encountered among intensive care unit patients. In addition to the well-known immediate complications (hydroelectrolytic disorders, hypervole...
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Complex endovascular repair of type B aortic dissection and predicting left arm ischemia: a case report

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Thoracic endovascular aortic repair (TEVAR) is the gold standard for surgical management of descending thoracic aortic pathology. Depending on the anatomy, TEVAR often requires deployment across the origin of ...
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Development and validation of a novel nomogram for individualized prediction of survival in cancer of unknown primary (CUP)

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Purpose: Prognostic uncertainty is a major challenge for cancer of unknown primary (CUP). Current models limit a meaningful patient-provider dialogue. We aimed to establish a nomogram for predicting overall survival (OS) in CUP based on robust clinicopathological prognostic factors. Experimental Design: We evaluated 521 patients with CUP at MDACC [MD Anderson Cancer Center, Houston, USA] (2012-2016). Baseline variables were analyzed using Cox-regression and nomogram developed using significant predictors. Predictive accuracy and discriminatory performance were assessed by calibration curves, concordance probability estimate (CPE) ({plus minus}standard error [SE]) and concordance statistic (C-index). The model was subjected to bootstrapping and multi-institutional external validations using two independent CUP cohorts: V1 (MDACC [2017], N=103) and V2 (BC Cancer, Vancouver, Canada and Sarah Cannon Cancer Center/Tennessee Oncology, USA, N=302). Re sults: Baseline characteristics of entire cohort (N=926) included: median age (63 years), women (51%), ECOG-PS 0-1 (64%), adenocarcinomas (52%), {greater than or equal to}3 sites of metastases (30%), median follow-up duration and OS of 40.1 and 14.7 months, respectively. Five independent prognostic factors were identified: gender, ECOG-PS, histology, number of metastatic sites and neutrophil-lymphocyte ratio. The resulting model predicted OS with CPE of 0.69 (SE: {plus minus}0.01) [C-index: 0.71 (95%CI:0.68-0.74)] outperforming Culine/Seve prognostic models (CPE: 0.59{plus minus}0.01). CPE for external validation cohorts V1 and V2 were 0.67 ({plus minus}0.02) and 0.70 ({plus minus}0.01), respectively. Calibration curves for 1-year OS showed strong agreement between nomogram prediction and actual observations in all cohorts. Conclusions: Our user-friendly CUP nomogram integrating commonly available baseline factors provides robust personalized prognostication which can aid cli nical decision making and selection/stratification for clinical trials.

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Article intro - Non-Technical Skill Assessment and Mental Load Evaluation in RAMIS

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Nagyné Elek et Haidegger: "Non-Techn ical Skill Assessment and Mental Load Evaluation in Robot-Assisted Minimally Invasive Surgery" has just appeared in MDPI Sensors 2021, 21(8), 2666; as part of the Special Issue on Medical Robotics.

Abstract

BACKGROUND: Sensor technologies and data collection practices are changing and improving quality metrics across various domains. Surgical skill assessment in Robot-Assisted Minimally Invasive Surgery (RAMIS) is essential for training and quality assurance. The mental workload on the surgeon (such as time criticality, task complexity, distractions) and non-technical surgical skills (including situational awareness, decision making, stress resilience, communication, leadership) may directly influence the clinical outcome of the sur gery. METHODS: A literature search in PubMed, Scopus and PsycNet databases was conducted for relevant scientific publications. The standard PRISMA method was followed to filter the search results, including non-technical skill assessment and mental/cognitive load and workload estimation in RAMIS. Publications related to traditional manual Minimally Invasive Surgery were excluded, and also the usability studies on the surgical tools were not assessed. RESULTS: 50 relevant publications were identified for non-technical skill assessment and mental load and workload estimation in the domain of RAMIS. The identified assessment techniques ranged from self-rating questionnaires and expert ratings to autonomous techniques, citing their most important benefits and disadvantages. CONCLUSIONS: Despite the systematic research, only a limited number of articles was found, indicating that non-technical skill and mental load assessment in RAMIS is not a well-studied area. Workload assessment and s oft skill measurement do not constitute part of the regular clinical training and practice yet. Meanwhile, the importance of the research domain is clear based on the publicly available surgical error statistics. Questionnaires and expert-rating techniques are widely employed in traditional surgical skill assessment; nevertheless, recent technological development in sensors and Internet of Things-type devices show that skill assessment approaches in RAMIS can be much more profound employing automated solutions. Measurements and especially big data type analysis may introduce more objectivity and transparency to this critical domain as well. SIGNIFICANCE: Non-technical skill assessment and mental load evaluation in Robot-Assisted Minimally Invasive Surgery is not a well-studied area yet; while the importance of this domain from the clinical outcome's point of view is clearly indicated by the available surgical error statistics.

Should you be interested in publishing with MDPI Sensors, the Medical Robotics Special Issue is open for submissions.

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