A global sensitivity analysis of a mechanistic model of neoadjuvant chemotherapy for triple negative breast cancer constrained by in vitro and in vivo imaging data.

Unlabelled: Neoadjuvant chemotherapy (NAC) is a standard-of-care treatment for locally advanced triple negative breast cancer (TNBC) before surgery. The early assessment of TNBC response to NAC would enable an oncologist to adapt the therapeutic plan of a non-responding patient, thereby improving treatment outcomes while preventing unnecessary toxicities. To this end, a promising approach consists of obtaining in silico personalized forecasts of tumor response to NAC via computer simulation of mechanistic models constrained with patient-specific magnetic resonance imaging (MRI) data acquired early during NAC.

Interpreting Variations in Fugl-Meyer Assessment Protocols: Results and Recommendations From a Nominal Group Consensus Process.

Objective: To identify variations among administration and scoring instructions of 6 upper extremity Fugl-Meyer Assessment (FMA-UE) protocols and to achieve consensus regarding optimal administration procedures.

Design: Nominal group consensus technique comprised of iterative independent reviews of protocol content, anonymous voting, and group consensus meetings.

Setting: Clinicians working in clinical practice and research settings participated in virtual meetings via Zoom.

Histopathologic Features of Unmasked Inflammatory Bowel Disease Following Immune Checkpoint Inhibitor Therapy in Colon Biopsies.

Background And Aims: Typical immune checkpoint inhibitor-induced colitis (T-ICI) has significant histomorphologic overlap with inflammatory bowel disease (IBD), a distinction further complicated in ICI-treated patients with pre-existing inflammatory bowel disease (P-IBD) and those with potentially "unmasked" inflammatory bowel disease (U-IBD) after ICI therapy. This study describes histopathologic findings seen in U-IBD colonic biopsies and assesses for distinguishing features from T-ICI and P-IBD biopsies.

Methods: Initial colon biopsies after symptom onset from 34 patients on ICI therapy were reviewed, and histopathologic features were tabulated.

The Development of Persistent Gastrointestinal Symptoms in Patients With Melanoma Who Have Had an Immune Checkpoint Inhibitor-Related Gastrointestinal Toxicity.

Introduction: Immune-related adverse events (irAE) secondary to immune checkpoint inhibitors (ICI) have gastrointestinal (GI) manifestations, including gastritis, enteritis, and/or colitis. The long-term sequelae of ICI-associated GI toxicities (GI-irAE), particularly the development of disorders of gut-brain interaction, are not well known. We characterized the incidence of persistent GI symptoms after GI-irAE.

The Quest for an Integrated Set of Neural Mechanisms Underlying Object Recognition in Primates.

Inferences made about objects via vision, such as rapid and accurate categorization, are core to primate cognition despite the algorithmic challenge posed by varying viewpoints and scenes. Until recently, the brain mechanisms that support these capabilities were deeply mysterious. However, over the past decade, this scientific mystery has been illuminated by the discovery and development of brain-inspired, image-computable, artificial neural network (ANN) systems that rival primates in these behavioral feats.

A unifying framework for functional organization in early and higher ventral visual cortex.

A key feature of cortical systems is functional organization: the arrangement of functionally distinct neurons in characteristic spatial patterns. However, the principles underlying the emergence of functional organization in the cortex are poorly understood. Here, we develop the topographic deep artificial neural network (TDANN), the first model to predict several aspects of the functional organization of multiple cortical areas in the primate visual system.

How does the primate brain combine generative and discriminative computations in vision?

Vision is widely understood as an inference problem. However, two contrasting conceptions of the inference process have each been influential in research on biological vision as well as the engineering of machine vision. The first emphasizes bottom-up signal flow, describing vision as a largely feedforward, discriminative inference process that filters and transforms the visual information to remove irrelevant variation and represent behaviorally relevant information in a format suitable for downstream functions of cognition and behavioral control.

Breast Multiparametric MRI for Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer: The BMMR2 Challenge.

Purpose To describe the design, conduct, and results of the Breast Multiparametric MRI for prediction of neoadjuvant chemotherapy Response (BMMR2) challenge. Materials and Methods The BMMR2 computational challenge opened on May 28, 2021, and closed on December 21, 2021. The goal of the challenge was to identify image-based markers derived from multiparametric breast MRI, including diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) MRI, along with clinical data for predicting pathologic complete response (pCR) following neoadjuvant treatment.

How well do rudimentary plasticity rules predict adult visual object learning?

A core problem in visual object learning is using a finite number of images of a new object to accurately identify that object in future, novel images. One longstanding, conceptual hypothesis asserts that this core problem is solved by adult brains through two connected mechanisms: 1) the re-representation of incoming retinal images as points in a fixed, multidimensional neural space, and 2) the optimization of linear decision boundaries in that space, via simple plasticity rules applied to a single downstream layer. Though this scheme is biologically plausible, the extent to which it explains learning behavior in humans has been unclear-in part because of a historical lack of image-computable models of the putative neural space, and in part because of a lack of measurements of human learning behaviors in difficult, naturalistic settings.

Let's move forward: Image-computable models and a common model evaluation scheme are prerequisites for a scientific understanding of human vision.

In the target article, Bowers et al. dispute deep artificial neural network (ANN) models as the currently leading models of human vision without producing alternatives. They eschew the use of public benchmarking platforms to compare vision models with the brain and behavior, and they advocate for a fragmented, phenomenon-specific modeling approach.

Sensitivity to Change and Responsiveness of the Upper Extremity Fugl-Meyer Assessment in Individuals With Moderate to Severe Acute Stroke.

Background: The Fugl-Meyer Assessment-Upper Extremity (FMA-UE) is a widely used outcome measure for quantifying motor impairment in stroke recovery. Meaningful change (responsiveness) in the acute to subacute phase of stroke recovery has not been determined.

Objective: Determine responsiveness and sensitivity to change of the FMA-UE from 1-week to 6-weeks (subacute) after stroke in individuals with moderate to severe arm impairment who received standard clinical care.

A Unifying Principle for the Functional Organization of Visual Cortex.

A key feature of many cortical systems is functional organization: the arrangement of neurons with specific functional properties in characteristic spatial patterns across the cortical surface. However, the principles underlying the emergence and utility of functional organization are poorly understood. Here we develop the Topographic Deep Artificial Neural Network (TDANN), the first unified model to accurately predict the functional organization of multiple cortical areas in the primate visual system.

Distinguishing Distinct Neural Systems for Proximal vs Distal Upper Extremity Motor Control After Acute Stroke.

Background And Objectives: The classic and singular pattern of distal greater than proximal upper extremity motor deficits after acute stroke does not account for the distinct structural and functional organization of circuits for proximal and distal motor control in the healthy CNS. We hypothesized that separate proximal and distal upper extremity clinical syndromes after acute stroke could be distinguished and that patterns of neuroanatomical injury leading to these 2 syndromes would reflect their distinct organization in the intact CNS.

Methods: Proximal and distal components of motor impairment (upper extremity Fugl-Meyer score) and strength (Shoulder Abduction Finger Extension score) were assessed in consecutively recruited patients within 7 days of acute stroke.

Toward Practical Integration of Omic and Imaging Data in Co-Clinical Trials.

Co-clinical trials are the concurrent or sequential evaluation of therapeutics in both patients clinically and patient-derived xenografts (PDX) pre-clinically, in a manner designed to match the pharmacokinetics and pharmacodynamics of the agent(s) used. The primary goal is to determine the degree to which PDX cohort responses recapitulate patient cohort responses at the phenotypic and molecular levels, such that pre-clinical and clinical trials can inform one another. A major issue is how to manage, integrate, and analyze the abundance of data generated across both spatial and temporal scales, as well as across species.

Association of Brain Age, Lesion Volume, and Functional Outcome in Patients With Stroke.

Background And Objectives: Functional outcomes after stroke are strongly related to focal injury measures. However, the role of global brain health is less clear. In this study, we examined the impact of brain age, a measure of neurobiological aging derived from whole-brain structural neuroimaging, on poststroke outcomes, with a focus on sensorimotor performance.

Catalyzing next-generation Artificial Intelligence through NeuroAI.

Neuroscience has long been an essential driver of progress in artificial intelligence (AI). We propose that to accelerate progress in AI, we must invest in fundamental research in NeuroAI. A core component of this is the embodied Turing test, which challenges AI animal models to interact with the sensorimotor world at skill levels akin to their living counterparts.

SMS-text messaging for collecting outcome measures after acute stroke.

Introduction: Traditional methods for obtaining outcomes for patients after acute stroke are resource-intensive. This study aimed to examine the feasibility, reliability, cost, and acceptability of collecting outcomes after acute stroke with a short message service (SMS)-text messaging program.

Methods: Patients were enrolled in an SMS-text messaging program at acute stroke hospitalization discharge.

Medication Profiles at Hospital Discharge Predict Poor Outcomes After Acute Ischemic Stroke.

To examine the relationship between medications prescribed during the first 6-months post-stroke and functional outcome. A retrospective analysis of ischemic stroke survivors enrolled in an observational stroke recovery study from June-2017 to July-2019 was performed. Survivors with favorable outcomes (modified rankin scale (mRS) score 0-2) were compared to those with unfavorable outcomes (mRS ≥3) 6-months after stroke on the following: discharge medication classes prescribed, achievement of recommended targets for blood pressure control, glycemic control, and LDL ≤70 mg/dL, medication changes, medication interactions, and medication list discrepancies.

An untrained deep learning method for reconstructing dynamic MR images from accelerated model-based data.

Purpose: To implement physics-based regularization as a stopping condition in tuning an untrained deep neural network for reconstructing MR images from accelerated data.

Methods: The ConvDecoder (CD) neural network was trained with a physics-based regularization term incorporating the spoiled gradient echo equation that describes variable-flip angle data. Fully-sampled variable-flip angle k-space data were retrospectively accelerated by factors of R = {8, 12, 18, 36} and reconstructed with CD, CD with the proposed regularization (CD + r), locally low-rank (LR) reconstruction, and compressed sensing with L1-wavelet regularization (L1).

A minimal role for synonymous variation in human disease.

Synonymous mutations change the DNA sequence of a gene without affecting the amino acid sequence of the encoded protein. Although some synonymous mutations can affect RNA splicing, translational efficiency, and mRNA stability, studies in human genetics, mutagenesis screens, and other experiments and evolutionary analyses have repeatedly shown that most synonymous variants are neutral or only weakly deleterious, with some notable exceptions. Based on a recent study in yeast, there have been claims that synonymous mutations could be as important as nonsynonymous mutations in causing disease, assuming the yeast findings hold up and translate to humans.

Novel Platform for Quantitative Assessment of Functional Object Interactions After Stroke.

Many persons with stroke exhibit upper extremity motor impairments. These impairments often lead to dysfunction and affect performance in activities of daily living, where successful manipulation of objects is essential. Hence, understanding how upper extremity motor deficits manifest in functional interactions with objects is critical for rehabilitation.

Hidden in plain sight: urinary Cryptococcus neoformans missed by routine diagnostics in a patient with acute leukemia.

Cryptococcuria is a rare manifestation of localized cryptococcal disease. We present a case of Cryptococcus neoformans urinary tract infection in an immunocompromised host missed by routine laboratory workup. The patient had negative blood cultures, a negative serum cryptococcal antigen (CrAg), and "non-Candida yeast" growing in urine culture that was initially dismissed as non-pathogenic.