Word Length Perturbations in Certain Symmetric Presentations of Dihedral Groups

Given a finite group with a generating subset there is a well-established notion of length for a group element given in terms of its minimal length expression as a product of elements from the generating set. Recently, certain quantities called $\lambda_{1}$ and $\lambda_{2}$ have been defined that allow for a precise measure of how stable a group is under certain types of small perturbations in the generating expressions for the elements of the group. These quantities provide a means to measure differences among all possible paths in a Cayley graph for a group, establish a group theoretic analog for the notion of stability in nonlinear dynamical systems, and play an important role in the application of groups to computational genomics. In this paper, we further expose the fundamental properties of $\lambda_{1}$ and $\lambda_{2}$ by establishing their bounds when the underlying group is a dihedral group. An essential step in our approach is to completely characterize so-called symmetric presentations of the dihedral groups, providing insight into the manner in which $\lambda_{1}$ and $\lambda_{2}$ interact with finite group presentations. This is of interest independent of the study of the quantities $\lambda_{1},\; \lambda_{2}$. Finally, we discuss several conjectures and open questions for future consideration

A Solitary Neck Nodule as Late Evidence of Recurrent Lobular Breast Carcinoma

Recurrent lobular breast carcinoma manifesting as a cutaneous neck nodule in a woman, 14 years after successful chemotherapy, illustrates the importance of following at-risk patients with a high level of clinical suspicion. This case emphasizes the value of combining clinical findings with appropriate histopathologic and immunohistochemical analysis when evaluating a cutaneous lesion in such a patient

Position Prediction as an Effective Pretraining Strategy

Transformers have gained increasing popularity in a wide range of applications, including Natural Language Processing (NLP), Computer Vision and Speech Recognition, because of their powerful representational capacity. However, harnessing this representational capacity effectively requires a large amount of data, strong regularization, or both, to mitigate overfitting. Recently, the power of the Transformer has been unlocked by self-supervised pretraining strategies based on masked autoencoders which rely on reconstructing masked inputs, directly, or contrastively from unmasked content. This pretraining strategy which has been used in BERT models in NLP, Wav2Vec models in Speech and, recently, in MAE models in Vision, forces the model to learn about relationships between the content in different parts of the input using autoencoding related objectives. In this paper, we propose a novel, but surprisingly simple alternative to content reconstruction~-- that of predicting locations from content, without providing positional information for it. Doing so requires the Transformer to understand the positional relationships between different parts of the input, from their content alone. This amounts to an efficient implementation where the pretext task is a classification problem among all possible positions for each input token. We experiment on both Vision and Speech benchmarks, where our approach brings improvements over strong supervised training baselines and is comparable to modern unsupervised/self-supervised pretraining methods. Our method also enables Transformers trained without position embeddings to outperform ones trained with full position information.Comment: Accepted to ICML 202

Segmentation of Multiple Sclerosis Lesions across Hospitals: Learn Continually or Train from Scratch?

Segmentation of Multiple Sclerosis (MS) lesions is a challenging problem. Several deep-learning-based methods have been proposed in recent years. However, most methods tend to be static, that is, a single model trained on a large, specialized dataset, which does not generalize well. Instead, the model should learn across datasets arriving sequentially from different hospitals by building upon the characteristics of lesions in a continual manner. In this regard, we explore experience replay, a well-known continual learning method, in the context of MS lesion segmentation across multi-contrast data from 8 different hospitals. Our experiments show that replay is able to achieve positive backward transfer and reduce catastrophic forgetting compared to sequential fine-tuning. Furthermore, replay outperforms the multi-domain training, thereby emerging as a promising solution for the segmentation of MS lesions. The code is available at this link: https://github.com/naga-karthik/continual-learning-msComment: Accepted at the Medical Imaging Meets NeurIPS (MedNeurIPS) Workshop 202

Development of β-globin gene correction in human hematopoietic stem cells as a potential durable treatment for sickle cell disease

Sickle cell disease (SCD) is the most common serious monogenic disease with 300,000 births annually worldwide. SCD is an autosomal recessive disease resulting from a single point mutation in codon six of the β-globin gene (HBB). Ex vivo β-globin gene correction in autologous patient-derived hematopoietic stem and progenitor cells (HSPCs) may potentially provide a curative treatment for SCD. We previously developed a CRISPR-Cas9 gene targeting strategy that uses high-fidelity Cas9 precomplexed with chemically modified guide RNAs to induce recombinant adeno-associated virus serotype 6 (rAAV6)-mediated HBB gene correction of the SCD-causing mutation in HSPCs. Here, we demonstrate the preclinical feasibility, efficacy, and toxicology of HBB gene correction in plerixafor-mobilized CD34+ cells from healthy and SCD patient donors (gcHBB-SCD). We achieved up to 60% HBB allelic correction in clinical-scale gcHBB-SCD manufacturing. After transplant into immunodeficient NSG mice, 20% gene correction was achieved with multilineage engraftment. The long-term safety, tumorigenicity, and toxicology study demonstrated no evidence of abnormal hematopoiesis, genotoxicity, or tumorigenicity from the engrafted gcHBB-SCD drug product. Together, these preclinical data support the safety, efficacy, and reproducibility of this gene correction strategy for initiation of a phase 1/2 clinical trial in patients with SCD

Apolipoprotein E epsilon 4 (APOE-ε4) genotype is associated with decreased 6-month verbal memory performance after mild traumatic brain injury

Introduction: The apolipoprotein E (APOE) ε4 allele associates with memory impairment in neurodegenerative diseases. Its association with memory after mild traumatic brain injury (mTBI) is unclear. Methods: mTBI patients (Glasgow Coma Scale score 13–15, no neurosurgical intervention, extracranial Abbreviated Injury Scale score ≤1) aged ≥18 years with APOE genotyping results were extracted from the Transforming Research and Clinical Knowledge in Traumatic Brain Injury Pilot (TRACK-TBI Pilot) study. Cohorts determined by APOE-ε4(+/−) were assessed for associations with 6-month verbal memory, measured by California Verbal Learning Test, Second Edition (CVLT-II) subscales: Immediate Recall Trials 1–5 (IRT), Short-Delay Free Recall (SDFR), Short-Delay Cued Recall (SDCR), Long-Delay F

Magnetic Resonance Imaging for Spine Emergencies.

This article is devoted to the MR imaging evaluation of spine emergencies, defined as spinal pathologic conditions that pose an immediate risk of significant morbidity or mortality to the patient if not diagnosed and treated in a timely manner. MR imaging plays a central role in the timely diagnosis of spine emergencies. A summary of MR imaging indications and MR imaging protocols tailored for a variety of spinal emergencies will be presented followed by a review of key imaging findings for the most-encountered emergent spine pathologic conditions. Pathologic conditions will be broadly grouped into traumatic and atraumatic pathologic conditions. For traumatic injuries, a practical and algorithmic diagnostic approach based on the AO Spine injury classification system will be presented focused on subaxial spine trauma. Atraumatic spinal emergencies will be dichotomized into compressive and noncompressive subtypes. The location of external compressive disease with respect to the thecal sac is fundamental to establishing a differential diagnosis for compressive emergencies, whereas specific patterns of spinal cord involvement on MR imaging will guide the discussion of inflammatory and noninflammatory causes of noncompressive myelopathy