: a tool for integrated differential expression analysis.

One of the fundamental aspects of genomic research is the identification of differentially expressed (DE) genes between two conditions. In the past decade, numerous DE analysis tools have been developed, employing various normalization methods and statistical modelling approaches. In this article, we introduce , an R package that leverages the capabilities of four state-of-the-art DE tools: edgeR, limma, DESeq2, and dearseq.

Proximal and Classic Epithelioid Sarcomas are Distinct Molecular Entities Defined by MYC/GATA3 and SOX17/Endothelial Markers, Respectively.

Epithelioid sarcoma (ES) is a rare tumor hallmarked by the loss of INI1/SMARCB1 expression. Apart from this alteration, little is known about the biology of ES. Despite recent advances in treatment, the prognosis of ES remains unsatisfactory.

Real-Time multifaceted artificial intelligence vs In-Person instruction in teaching surgical technical skills: a randomized controlled trial.

Trainees develop surgical technical skills by learning from experts who provide context for successful task completion, identify potential risks, and guide correct instrument handling. This expert-guided training faces significant limitations in objectively assessing skills in real-time and tracking learning. It is unknown whether AI systems can effectively replicate nuanced real-time feedback, risk identification, and guidance in mastering surgical technical skills that expert instructors offer.

Unveiling surgical expertise through machine learning in a novel VR/AR spinal simulator: A multilayered approach using transfer learning and connection weights analysis.

Background: Virtual and augmented reality surgical simulators, integrated with machine learning, are becoming essential for training psychomotor skills, and analyzing surgical performance. Despite the promise of methods like the Connection Weights Algorithm, the small sample sizes (small number of participants (N)) typical of these trials challenge the generalizability and robustness of models. Approaches like data augmentation and transfer learning from models trained on similar surgical tasks address these limitations.

Beyond self‑eating: Emerging autophagy‑independent functions for the autophagy molecules in cancer (Review).

Autophagy is a conserved catabolic process that controls organelle quality, removes misfolded or abnormally aggregated proteins and is part of the defense mechanisms against intracellular pathogens. Autophagy contributes to the suppression of tumor initiation by promoting genome stability, cellular integrity, redox balance and proteostasis. On the other hand, once a tumor is established, autophagy can support cancer cell survival and promote epithelial‑to‑mesenchymal transition.

Face, content, and construct validity of a novel VR/AR surgical simulator of a minimally invasive spine operation.

Mixed-reality surgical simulators are seen more objective than conventional training. The simulators' utility in training must be established through validation studies. Establish face-, content-, and construct-validity of a novel mixed-reality surgical simulator developed by McGill University, CAE-Healthcare, and DePuy Synthes.

Continuous Instrument Tracking in a Cerebral Corticectomy Ex Vivo Calf Brain Simulation Model: Face and Content Validation.

Background And Objectives: Subpial corticectomy involving complete lesion resection while preserving pial membranes and avoiding injury to adjacent normal tissues is an essential bimanual task necessary for neurosurgical trainees to master. We sought to develop an ex vivo calf brain corticectomy simulation model with continuous assessment of surgical instrument movement during the simulation. A case series study of skilled participants was performed to assess face and content validity to gain insights into the utility of this training platform, along with determining if skilled and less skilled participants had statistical differences in validity assessment.

Effect of Feedback Modality on Simulated Surgical Skills Learning Using Automated Educational Systems- A Four-Arm Randomized Control Trial.

Objective: To explore optimal feedback methodologies to enhance trainee skill acquisition in simulated surgical bimanual skills learning during brain tumor resections.

Hypotheses: (1) Providing feedback results in better learning outcomes in teaching surgical technical skill when compared to practice alone with no tailored performance feedback. (2) Providing more visual and visuospatial feedback results in better learning outcomes when compared to providing numerical feedback.

AI in Surgical Curriculum Design and Unintended Outcomes for Technical Competencies in Simulation Training.

Importance: To better elucidate the role of artificial intelligence (AI) in surgical skills training requires investigations in the potential existence of a hidden curriculum.

Objective: To assess the pedagogical value of AI-selected technical competencies and their extended effects in surgical simulation training.

Design, Setting, And Participants: This cohort study was a follow-up of a randomized clinical trial conducted at the Neurosurgical Simulation and Artificial Intelligence Learning Centre at the Montreal Neurological Institute, McGill University, Montreal, Canada.

From Canadian Surgeon to Chinese Martyr: Dr. Norman Bethune and the Making of a Medical Folk Hero.

This paper reexamines the public memory of Canadian surgeon Norman Bethune. In 1938, Bethune traveled to China to serve at the communist front and to treat soldiers fighting against the invading Japanese army. Throughout China, Bethune is a household name and a communist icon.

Performance in a Simulated Virtual Reality Anterior Cervical Discectomy and Fusion Task: Disc Residual, Rate of Removal, and Efficiency Analyses.

Background And Objectives: Anterior cervical discectomy and fusion (ACDF) is among the most common spine procedures. The Sim-Ortho virtual reality simulator platform contains a validated ACDF simulated task for performance assessment. This study aims to develop a methodology to extract three-dimensional data and reconstruct and quantitate specific simulated disc tissues to generate novel metrics to analyze performance metrics of skilled and less skilled participants.

O -methylguanine methyltransferase promoter methylation status of glioblastoma cell line clonal population.

Glioblastoma (GBM) remains a treatment-resistant malignant brain tumor in large part because of its genetic heterogeneity and epigenetic plasticity. In this study, we investigated the epigenetic heterogeneity of GBM by evaluating the methylation status of the O -methylguanine methyltransferase (MGMT) promoter in individual clones of a single cell derived from GBM cell lines. The U251 and U373 GBM cell lines, from the Brain Tumour Research Centre of the Montreal Neurological Institute, were used for the experiments.

In Silico Identification of a BRCA1:miR-29:DNMT3 Axis Involved in the Control of Hormone Receptors in BRCA1-Associated Breast Cancers.

Germline inactivating mutations in the BRCA1 gene lead to an increased lifetime risk of ovarian and breast cancer (BC). Most BRCA1-associated BC are triple-negative tumors (TNBC), aggressive forms of BC characterized by a lack of expression of estrogen and progesterone hormone receptors (HR) and HER2. How BRCA1 inactivation may favor the development of such a specific BC phenotype remains to be elucidated.

Utilizing artificial intelligence and electroencephalography to assess expertise on a simulated neurosurgical task.

Virtual reality surgical simulators have facilitated surgical education by providing a safe training environment. Electroencephalography (EEG) has been employed to assess neuroelectric activity during surgical performance. Machine learning (ML) has been applied to analyze EEG data split into frequency bands.

Routine Molecular Profiling in Both Resectable and Unresectable Pancreatic Adenocarcinoma: Relevance of Cytologic Samples.

Background & Aims: Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive disease, for which it is crucial to promptly detect actionable and prognostic alterations to drive specific therapeutic decisions, regardless of tumor resectability status. Endoscopic ultrasonography-guided fine-needle aspiration (EUS-FNA) is of key importance for PDAC diagnosis and can contribute significantly to tumor molecular profiling.

Methods: Comprehensive genomic profile by targeted next-generation sequencing (NGS) was performed on 2 independent PDAC patient cohorts.

Beyond SMARCB1 Loss: Recent Insights into the Pathobiology of Epithelioid Sarcoma.

Epithelioid sarcoma (ES) is a very rare and aggressive mesenchymal tumor of unclear origin and uncertain lineage characterized by a prevalent epithelioid morphology. The only recurrent genetic alteration reported in ES as yet is the functional inactivation of SMARCB1 (SWI/SNF-related matrix-associated actin-dependent regulator of chromatin subfamily B member 1), a key component of the SWI/SNF (SWItch/Sucrose Non-Fermentable) chromatin remodeling complexes. How SMARCB1 deficiency dictates the clinicopathological characteristics of ES and what other molecular defects concur to its malignant progression is still poorly understood.

Retrospective observational studies in ultra-rare sarcomas: A consensus paper from the Connective Tissue Oncology Society (CTOS) community of experts on the minimum requirements for the evaluation of activity of systemic treatments.

Background: In ultra-rare sarcomas (URS) the conduction of prospective, randomized trials is challenging. Data from retrospective observational studies (ROS) may represent the best evidence available. ROS implicit limitations led to poor acceptance by the scientific community and regulatory authorities.

ISG15 as a prognostic biomarker in solitary fibrous tumour.

Background: Solitary fibrous tumour (SFT) is a rare mesenchymal malignancy that lacks robust prognostic and predictive biomarkers. Interferon-stimulated gene 15 (ISG15) is a ubiquitin-like modifier, associated with tumour progression, and with poor survival of SFT patients, as previous published by our group. Here, we describe the role of ISG15 in the biology of this rare tumour.

CINSARC in high-risk soft tissue sarcoma patients treated with neoadjuvant chemotherapy: Results from the ISG-STS 1001 study.

Background: The Complexity INdex in SARComas (CINSARC) is a transcriptional signature derived from the expression of 67 genes involved in mitosis control and chromosome integrity. This study aims to assess CINSARC value of in an independent series of high-risk patients with localized soft tissue sarcoma (STS) treated with preoperative chemotherapy within a prospective, randomized, phase III study (ISG-STS 1001).

Patients And Methods: Patients with available pre-treatment samples, treated with 3 cycles of either standard (ST) preoperative or histotype-tailored (HT) chemotherapy, were scored according to CINSARC (low-risk, C1; high-risk, C2).

Artificial Neural Network Approach to Competency-Based Training Using a Virtual Reality Neurosurgical Simulation.

Background: The methodology of assessment and training of surgical skills is evolving to deal with the emergence of competency-based training. Artificial neural networks (ANNs), a branch of artificial intelligence, can use newly generated metrics not only for assessment performance but also to quantitate individual metric importance and provide new insights into surgical expertise.

Objective: To outline the educational utility of using an ANN in the assessment and quantitation of surgical expertise.

Nondominant Hand Skills Spatial and Psychomotor Analysis During a Complex Virtual Reality Neurosurgical Task-A Case Series Study.

Background: Virtual reality surgical simulators provide detailed psychomotor performance data, allowing qualitative and quantitative assessment of hand function. The nondominant hand plays an essential role in neurosurgery in exposing the operative area, assisting the dominant hand to optimize task execution, and hemostasis. Outlining expert-level nondominant hand skills may be critical to understand surgical expertise and aid learner training.