Graph convolution networks model identifies and quantifies gene and cancer specific transcriptome signatures of cancer driver events.

Background: The identification and drug targeting of cancer causing (driver) genetic alterations has seen immense improvement in recent years, with many new targeted therapies developed. However, identifying, prioritizing, and treating genetic alterations is insufficient for most cancer patients. Current clinical practices rely mainly on DNA level mutational analyses, which in many cases fail to identify treatable driver events.

Cancer mutational signatures identification in clinical assays using neural embedding-based representations.

While mutational signatures provide a plethora of prognostic and therapeutic insights, their application in clinical-setting, targeted gene panels is extremely limited. We develop a mutational representation model (which learns and embeds specific mutation signature connections) that enables prediction of dominant signatures with only a few mutations. We predict the dominant signatures across more than 60,000 tumors with gene panels, delineating their landscape across different cancers.

Efficacy of a gamified digital therapy for speech production in people with chronic aphasia (iTalkBetter): behavioural and imaging outcomes of a phase II item-randomised clinical trial.

Background: Aphasia is among the most debilitating of symptoms affecting stroke survivors. Speech and language therapy (SLT) is effective, but many hours of practice are required to make clinically meaningful gains. One solution to this 'dosage' problem is to automate therapeutic approaches via self-supporting apps so people with aphasia (PWA) can amass practice as it suits them.

Extending the boundaries of cancer therapeutic complexity with literature text mining.

Drug combination therapy is a main pillar of cancer therapy. As the number of possible drug candidates for combinations grows, the development of optimal high complexity combination therapies (involving 4 or more drugs per treatment) such as RCHOP-I and FOLFIRINOX becomes increasingly challenging due to combinatorial explosion. In this paper, we propose a text mining (TM) based tool and workflow for rapid generation of high complexity combination treatments (HCCT) in order to extend the boundaries of complexity in cancer treatments.

Incorporating Prostate-specific Membrane Antigen Positron Emission Tomography in Management Decisions for Men with Newly Diagnosed or Biochemically Recurrent Prostate Cancer.

Context: Prostate-specific membrane antigen (PSMA) is a promising molecular target for prostate cancer (PCa) that has allowed the development of a novel diagnostic approach to PCA in the primary and recurrent settings.

Objective: To summarize available data and recommendations regarding the use of PSMA in newly diagnosed and recurrent PCa via a narrative review.

Evidence Acquisition: A literature review was conducted using MEDLINE (via PubMed) and Scopus.

Recovery after stroke: the severely impaired are a distinct group.

Introduction: Stroke causes different levels of impairment and the degree of recovery varies greatly between patients. The majority of recovery studies are biased towards patients with mild-to-moderate impairments, challenging a unified recovery process framework. Our aim was to develop a statistical framework to analyse recovery patterns in patients with severe and non-severe initial impairment and concurrently investigate whether they recovered differently.

"Could you give us an idea on what we are all doing here?" the Patient Voice in Cancer Research (PVCR) starting the journey of involvement in Ireland.

Background: Involving patients and their carers in research has become more common, as funders demand evidence of involvement. The 'Patient Voice in Cancer Research' (PVCR) is an initiative led by University College Dublin (UCD) in Ireland. It encourages and enables people affected by cancer, and their families to become involved in shaping and informing the future of cancer research across the island of Ireland.

Inflated Estimates of Proportional Recovery From Stroke: The Dangers of Mathematical Coupling and Compression to Ceiling.

The proportional recovery rule states that most survivors recover a fixed proportion (≈70%) of lost function after stroke. A strong (negative) correlation between the initial score and subsequent change (outcome minus initial; ie, recovery) is interpreted as empirical support for the proportional recovery rule. However, this rule has recently been critiqued, with a central observation being that the correlation of initial scores with change over time is confounded in the situations in which it is typically assessed.

Use of advanced PET-volume metrics predicts risk of local recurrence and overall survival in anal cancer.

Objective: Anal cancer is an uncommon malignancy with the primary treatment for localized disease being concurrent radiation and chemotherapy. Pre-treatment PET/CT is useful for target delineation, with minimal exploration of its use in prognostication. In the post-treatment setting there is growing evidence for advanced PET metrics in assessment of treatment response, and early identification of recurrence essential for successful salvage, however this data is limited to small series.

Viral Science: Masks, Speed Bumps, and Guard Rails.

The speed of science, especially while solving the recent pandemic puzzles, is causing concerns. We describe some salient issues as well as a framework for making the process of publishing, organizing, and retrieving scientific literature more efficient. Emerging building blocks leveraging AI, including natural language processing tools such as SciSight from the Allen Institute for AI, that permit faceted navigation and research group detection are highlighted.

Scaling up analogical innovation with crowds and AI.

Analogy-the ability to find and apply deep structural patterns across domains-has been fundamental to human innovation in science and technology. Today there is a growing opportunity to accelerate innovation by moving analogy out of a single person's mind and distributing it across many information processors, both human and machine. Doing so has the potential to overcome cognitive fixation, scale to large idea repositories, and support complex problems with multiple constraints.

Intraoperative sonography during carotid endarterectomy: normal appearance and spectrum of complications.

Carotid endarterectomy is a commonly performed procedure for prevention of stroke related to carotid stenosis. Intraoperative sonography is used to identify potentially correctable technical defects during carotid endarterectomy. The main risk of endarterectomy is perioperative stroke, and great effort has been put into trying to reduce this risk through various surgical techniques and evaluation of the surgical bed.

Spontaneous superior sagittal sinus thrombosis secondary to type II heparin-induced thrombocytopenia presenting as an acute subarachnoid hemorrhage.

Cerebral sinus thrombosis is a rare cause of spontaneous subarachnoid hemorrhage. The development of cerebral sinus thrombosis as a complication of heparin-induced thrombocytopenia is even rarer. In this paper, we present a 59-year-old patient admitted to our service with cerebral sinus thrombosis secondary to type II heparin-induced thrombocytopenia.