A bi-cortical neuroprosthesis to modulate locomotion after incomplete spinal cord injury

Neuroprosthetic strategies seek to immediately alleviate deficits and reinstate voluntary control of movement. To facilitate recovery, it is crucial to gain a comprehensive understanding of the mechanisms involved in the return of intentional movement. Nevertheless, the precise relationship between the resurgence of cortical commands and the recovery of locomotion remains somewhat elusive. In the study conducted by Duguay, Bonizzato, Delivet-Mongrain, Fortier-Lebel and Martinez, we introduced a neuroprosthesis designed to deliver precise bi-cortical stimulation in a clinically relevant contusive spinal cord injury model. We conducted experiments in both healthy and spinal cord injured cats, where we fine-tuned the timing, duration, amplitude, and site of stimulation to modulate hindlimb locomotor output. In healthy cats, we observed a wide range of motor programs. However, after spinal cord injury, the induced hindlimb movements became highly stereotyped but were effective in modulating gait and reducing bilateral foot dragging. These results suggest that the neural basis for motor recovery traded off selectivity for effectiveness. Through a series of longitudinal assessments, we found that the restoration of locomotion following spinal cord injury was closely linked to the recovery of the descending neural drive. This underscores the importance of directing rehabilitation interventions toward the cortical target. The study results are discussed in terms of their impact and limitations.

Grafting Strategies of Oxidation-Prone Coiled-Coil Peptides for Protein Capture in Bioassays: Impact of Orientation and the Oxidation State

Many biomedical and biosensing applications require functionalization of surfaces with proteins. To this end, the E/K coiled-coil peptide heterodimeric system has been shown to be advantageous. First, Kcoil peptides are covalently grafted onto a given surface. Ecoil-tagged proteins can then be non-covalently captured via a specific interaction with their Kcoil partners. Previously, oriented Kcoil grafting was achieved via thiol coupling, using a unique Kcoil with a terminal cysteine residue. However, cysteine-terminated Kcoil peptides are hard to produce, purify, and oxidize during storage. Indeed, they tend to homodimerize and form disulfide bonds via oxidation of their terminal thiol group, making it impossible to later graft them on thiol-reactive surfaces. Kcoil peptides also contain multiple free amine groups, available for covalent coupling through carbodiimide chemistry. Grafting Kcoil peptides on surfaces via amine coupling would thus guarantee their immobilization regardless of their terminal cysteine's oxidation state, at the expense of the control over their orientation. In this work, we compare Kcoil grafting strategies for the subsequent capture of Ecoil-tagged proteins, for applications such as surface plasmon resonance (SPR) biosensing and cell culture onto protein-decorated substrates. We compare the "classic" thiol coupling of cysteine-terminated Kcoil peptides to the amine coupling of (i) monomeric Kcoil and (ii) dimeric Kcoil-Kcoil linked by a disulfide bond. We have observed that SPR biosensing performances relying on captured Ecoil-tagged proteins were similar for amine-coupled dimeric Kcoil-Kcoil and thiol-coupled Kcoil peptides, at the expense of higher Ecoil-tagged protein consumption. For cell culture applications, Ecoil-tagged growth factors captured on amine-coupled monomeric Kcoil signaled through cell receptors similarly to those captured on thiol-coupled Kcoil peptides. Altogether, while oriented thiol coupling of cysteine-terminated Kcoil peptides remains the most reliable and versatile platform for Ecoil-tagged protein capture, amine coupling of Kcoil peptides, either monomeric or dimerized through a cysteine bond, can offer a good alternative when the challenges and costs associated with the production of monomeric cysteine-tagged Kcoil are too dissuasive for the application.

Situation Awareness-Oriented Dashboard in ICUs in Support of Resource Management in Time of Pandemics

In a pediatric intensive care unit (PICU) of 32 beds, clinicians manage resources 24 hours a day, 7 days a week, from a large-screen dashboard implemented in 2017. This resource management dashboard efficiently replaces the handwriting information displayed on a whiteboard, offering a synthetic view of the bed's layout and specific information on staff and equipment at bedside. However, in 2020 when COVID-19 hit, the resource management dashboard showed several limitations. Mainly, its visualization offered to the clinicians limited situation awareness (SA) to perceive, understand and predict the impacts on resource management and decision-making of an unusual flow of patients affected by the most severe form of coronavirus. To identify the SA requirements during a pandemic, we conducted goal-oriented interviews with 11 clinicians working in ICUs. The result is the design of an SA-oriented dashboard with 22 key indicators (KIs): 1 on the admission capacity, 15 at bedside and 6 displayed as statistics in the central area. We conducted a usability evaluation of the SA-oriented dashboard compared to the resource management dashboard with 6 clinicians. The results showed five usability improvements of the SA-oriented dashboard and five limitations. Our work contributes to new knowledge on the clinicians' SA requirements to support resource management and decision-making in ICUs in times of pandemics.

Identification of intraductal carcinoma of the prostate on tissue specimens using Raman micro-spectroscopy: A diagnostic accuracy case-control study with multicohort validation

BACKGROUND

Prostate cancer (PC) is the most frequently diagnosed cancer in North American men. Pathologists are in critical need of accurate biomarkers to characterize PC, particularly to confirm the presence of intraductal carcinoma of the prostate (IDC-P), an aggressive histopathological variant for which therapeutic options are now available. Our aim was to identify IDC-P with Raman micro-spectroscopy (RμS) and machine learning technology following a protocol suitable for routine clinical histopathology laboratories.

METHODS AND FINDINGS

We used RμS to differentiate IDC-P from PC, as well as PC and IDC-P from benign tissue on formalin-fixed paraffin-embedded first-line radical prostatectomy specimens (embedded in tissue microarrays [TMAs]) from 483 patients treated in 3 Canadian institutions between 1993 and 2013. The main measures were the presence or absence of IDC-P and of PC, regardless of the clinical outcomes. The median age at radical prostatectomy was 62 years. Most of the specimens from the first cohort (Centre hospitalier de l'Université de Montréal) were of Gleason score 3 + 3 = 6 (51%) while most of the specimens from the 2 other cohorts (University Health Network and Centre hospitalier universitaire de Québec-Université Laval) were of Gleason score 3 + 4 = 7 (51% and 52%, respectively). Most of the 483 patients were pT2 stage (44%-69%), and pT3a (22%-49%) was more frequent than pT3b (9%-12%). To investigate the prostate tissue of each patient, 2 consecutive sections of each TMA block were cut. The first section was transferred onto a glass slide to perform immunohistochemistry with H&E counterstaining for cell identification. The second section was placed on an aluminum slide, dewaxed, and then used to acquire an average of 7 Raman spectra per specimen (between 4 and 24 Raman spectra, 4 acquisitions/TMA core). Raman spectra of each cell type were then analyzed to retrieve tissue-specific molecular information and to generate classification models using machine learning technology. Models were trained and cross-validated using data from 1 institution. Accuracy, sensitivity, and specificity were 87% ± 5%, 86% ± 6%, and 89% ± 8%, respectively, to differentiate PC from benign tissue, and 95% ± 2%, 96% ± 4%, and 94% ± 2%, respectively, to differentiate IDC-P from PC. The trained models were then tested on Raman spectra from 2 independent institutions, reaching accuracies, sensitivities, and specificities of 84% and 86%, 84% and 87%, and 81% and 82%, respectively, to diagnose PC, and of 85% and 91%, 85% and 88%, and 86% and 93%, respectively, for the identification of IDC-P. IDC-P could further be differentiated from high-grade prostatic intraepithelial neoplasia (HGPIN), a pre-malignant intraductal proliferation that can be mistaken as IDC-P, with accuracies, sensitivities, and specificities > 95% in both training and testing cohorts. As we used stringent criteria to diagnose IDC-P, the main limitation of our study is the exclusion of borderline, difficult-to-classify lesions from our datasets.

CONCLUSIONS

In this study, we developed classification models for the analysis of RμS data to differentiate IDC-P, PC, and benign tissue, including HGPIN. RμS could be a next-generation histopathological technique used to reinforce the identification of high-risk PC patients and lead to more precise diagnosis of IDC-P.