Citations

Spatially resolved sequencing technologies help us dissect how cells are organized in space. Several available computational approaches focus on the identification of spatially variable genes (SVGs), genes whose expression patterns vary in space. The detection of SVGs is analogous to the identification of differentially expressed genes and permits us to understand how genes and associated molecular processes are spatially distributed within cellular niches. However, the expression activities of SVGs fail to encode all information inherent in the spatial distribution of cells. Here, we devised a deep learning model, Spatially Informed Artificial Intelligence (SPIN-AI), to identify spatially predictive genes (SPGs), whose expression can predict how cells are organized in space. We used SPIN-AI on spatial transcriptomic data from squamous cell carcinoma (SCC) as a proof of concept. Our results demonstrate that SPGs not only recapitulate the biology of SCC but also identify genes distinct from SVGs. Moreover, we found a substantial number of ribosomal genes that were SPGs but not SVGs. Since SPGs possess the capability to predict spatial cellular organization, we reason that SPGs capture more biologically relevant information for a given cellular niche than SVGs. Thus, SPIN-AI has broad applications for detecting SPGs and uncovering which biological processes play important roles in governing cellular organization.

Despite decades of research and numerous clinical trials, the prognosis of patients diagnosed with glioblastoma (GBM) remains dire with median observed survival at 8 months. There is a critical need for novel treatments for GBM, which is the most common malignant primary brain tumor. Major advances in cancer therapeutics such as immune checkpoint inhibitors and chimeric antigen receptor (CAR) T-cell therapy have not yet led to improved outcomes for GBM. Conventional therapy of surgery followed by chemoradiation with or without tumor treating fields remains the standard of care. One of the many approaches to GBM therapy currently being explored is viral therapies. These typically work by selectively lysing target neoplastic cells, called oncolysis, or by the targeted delivery of a therapeutic transgene via a viral vector. In this review, we discuss the underlying mechanisms of action and describe both recent and current human clinical trials using these viruses with an emphasis on promising viral therapeutics that may ultimately break the field’s current stagnant paradigm.

Cardiovascular pathology is the leading cause of death and disability in the Western world, and current diagnostic testing usually evaluates the anatomy of the vessel to determine if the vessel contains blockages and plaques. However, there is a growing school of thought that other measures, such as wall shear stress, provide more useful information for earlier diagnosis and prediction of atherosclerotic related disease compared to pulsed-wave Doppler ultrasound, magnetic resonance angiography, or computed tomography angiography. A novel algorithm for quantifying wall shear stress (WSS) in atherosclerotic plaque using diagnostic ultrasound imaging, called Multifrequency ultrafast Doppler spectral analysis (MFUDSA), is presented. The development of this algorithm is presented, in addition to its optimisation using simulation studies and in-vitro experiments with flow phantoms approximating the early stages of cardiovascular disease. The presented algorithm is compared with commonly used WSS assessment methods, such as standard PW Doppler, Ultrafast Doppler, and Parabolic Doppler, as well as plane-wave Doppler. Compared to an equivalent processing architecture with one-dimensional Fourier analysis, the MFUDSA algorithm provided an increase in signal-to-noise ratio (SNR) by a factor of 4–8 and an increase in velocity resolution by a factor of 1.10–1.35. The results indicated that MFUDSA outperformed the others, with significant differences detected between the typical WSS values of moderate disease progression (p = 0.003) and severe disease progression (p = 0.001). The algorithm demonstrated an improved performance for the assessment of WSS and has potential to provide an earlier diagnosis of cardiovascular disease than current techniques allow.

Abstract The Infectious Diseases Society of America (IDSA) has set clear priorities in recent years to promote inclusion, diversity, access, and equity (IDA&E) in infectious disease (ID) clinical practice, medical education, and research. The IDSA IDA&E Task Force was launched in 2018 to ensure implementation of these principles. The IDSA Training Program Directors Committee met in 2021 and discussed IDA&E best practices as they pertain to the education of ID fellows. Committee members sought to develop specific goals and strategies related to recruitment, clinical training, didactics, and faculty development. This article represents a presentation of ideas brought forth at the meeting in those spheres and is meant to serve as a reference document for ID training program directors seeking guidance in this area.

Background Individuals with spinal cord injury (SCI) have lower levels of physical activity compared to the nondisabled population. Exercise guidelines recommend moderate or vigorous exercise to improve cardiovascular health and reduce cardiometabolic risk factors in persons with SCI. High-intensity interval training (HIIT) is a popular exercise choice and encompasses brief periods of vigorous exercise paired with intermittent periods of recovery. Objectives This review describes the available literature on HIIT for individuals with SCI, including differences in protocol design and suggested areas of further investigation. Methods Our institution’s library system performed the comprehensive search. The primary keywords and phrases used to search included spinal cord injury, high-intensity interval training, tetraplegia, paraplegia, and several other related terms. Results Initially 62 records were screened, and 36 were deemed outside the scope of this review. Twenty-six studies published between 2001 and 2021 fulfilled the eligibility criteria and were divided among two researchers for review and analysis. All records required persons with SCI and a standardized HIIT intervention. Study design varied widely with respect to mode of exercise, prescribed intensity, duration of performance intervals, and session duration. This variability necessitates further investigation into the specifics of a HIIT prescription and the associated outcomes for persons with SCI. Conclusion Standardization of HIIT protocols may lead to more robust conclusions regarding its effects on cardiorespiratory fitness as well as mitigation of cardiometabolic risk factors. Meta-analyses will eventually be needed on proper dosing and session parameters to improve cardiorespiratory fitness and cardiometabolic risk factors.

AbstractPurpose/objectiveWe compared the prognostic value of chest radiograph (CXR)‐ and computed tomography (CT)‐derived definition of large mediastinal adenopathy (LMA) in pediatric Hodgkin lymphoma (HL).Materials/methodsTotal 143 patients treated for stage IIIB/IVB HL on COG AHOD0831 were included in this study. Six definitions of LMA were investigated: (i) mediastinal mass ratio on CXR (MRCXR) > 1/3; (ii) mediastinal mass ratio on CT (MRCT) > 1/3; (iii) mediastinal mass volume on CT (MVCT) > 200 mL; (iv) normalized mediastinal mass volume (MVCT/thoracic diameter [TD]) > 1 mL/mm; (v) mediastinal mass diameter on CT (MDCT) > 10 cm; and (vi) normalized mediastinal mass diameter (MDCT/TD) > 1/3.ResultsMedian age at diagnosis was 15.8 years (range: 5.2–21.3 years). In patients with a slow early response (SER) to chemotherapy, MVCT > 200 mL, MDCT > 10 cm, and MDCT/TD > 1/3 were associated with worse relapse‐free survival (RFS) on MVA, while MRCXR > 1/3, MRCT > 1/3, and MVCT/TD > 1 mL/mm trended toward worse RFS; MDCT/TD was the most strongly prognostic for inferior RFS, with a hazard ratio of 6.41 for MDCT/TD > 1/3 versus ≤1/3 on MVA (p = .02).ConclusionLMA according to MVCT > 200 mL, MDCT > 10 cm, and MDCT/TD > 1/3 is associated with poor prognosis in advanced‐stage HL patients with SER. The normalized mediastinal diameter, MDCT/TD > 1/3 appears to be the strongest predictor of inferior RFS.

AbstractOBJECTIVEInvestigation of learning slopes in early‐onset dementias has been limited. The current study aimed to highlight the sensitivity of learning slopes to discriminate disease severity in cognitively normal participants and those diagnosed with early‐onset dementia with and without β‐amyloid positivityMETHODData from 310 participants in the Longitudinal Early‐Onset Alzheimer's Disease Study (aged 41 to 65) were used to calculate learning slope metrics. Learning slopes among diagnostic groups were compared, and the relationships of slopes with standard memory measures were determinedRESULTSWorse learning slopes were associated with more severe disease states, even after controlling for demographics, total learning, and cognitive severity. A particular metric—the learning ratio (LR)—outperformed other learning slope calculations across analysesCONCLUSIONSLearning slopes appear to be sensitive to early‐onset dementias, even when controlling for the effect of total learning and cognitive severity. The LR may be the learning measure of choice for such analyses.Highlights Learning is impaired in amyloid‐positive EOAD, beyond cognitive severity scores alone. Amyloid‐positive EOAD participants perform worse on learning slopes than amyloid‐negative participants. Learning ratio appears to be the learning metric of choice for EOAD participants.

Abstract Background Although the epidermal growth factor receptor (EGFR) is a frequent oncogenic driver in glioblastoma (GBM), efforts to therapeutically target this protein have been largely unsuccessful. The present preclinical study evaluated the novel EGFR inhibitor WSD-0922. Methods We employed flank and orthotopic patient-derived xenograft models to characterize WSD-0922 and compare its efficacy to erlotinib, a potent EGFR inhibitor that failed to provide benefit for GBM patients. We performed long-term survival studies and collected short-term tumor, plasma, and whole-brain samples from mice treated with each drug. We utilized mass spectrometry to measure drug concentrations and spatial distribution and to assess the impact of each drug on receptor activity and cellular signaling networks. Results WSD-0922 inhibited EGFR signaling as effectively as erlotinib in in vitro and in vivo models. While WSD-0922 was more CNS penetrant than erlotinib in terms of total concentration, comparable concentrations of both drugs were measured at the tumor site in orthotopic models, and the concentration of free WSD-0922 in the brain was significantly less than the concentration of free erlotinib. WSD-0922 treatment provided a clear survival advantage compared to erlotinib in the GBM39 model, with marked suppression of tumor growth and most mice surviving until the end of the study. WSD-0922 treatment preferentially inhibited phosphorylation of several proteins, including those associated with EGFR inhibitor resistance and cell metabolism. Conclusions WSD-0922 is a highly potent inhibitor of EGFR in GBM, and warrants further evaluation in clinical studies.

Renal diseases pose a significant socio‐economic burden on healthcare systems. The development of better diagnostics and prognostics is well‐recognized as a key strategy to resolve these challenges. Central to these developments are MRI biomarkers, due to their potential for monitoring of early pathophysiological changes, renal disease progression or treatment effects. The surge in renal MRI involves major cross‐domain initiatives, large clinical studies, and educational programs. In parallel with these translational efforts, the need for greater (patho)physiological specificity remains, to enable engagement with clinical nephrologists and increase the associated health impact. The ISMRM 2022 Member Initiated Symposium (MIS) on renal MRI spotlighted this issue with the goal of inspiring more solutions from the ISMRM community. This work is a summary of the MIS presentations devoted to: 1) educating imaging scientists and clinicians on renal (patho)physiology and demands from clinical nephrologists, 2) elucidating the connection of MRI parameters with renal physiology, 3) presenting the current state of leading MR surrogates in assessing renal structure and functions as well as their next generation of innovation, and 4) describing the potential of these imaging markers for providing clinically meaningful renal characterization to guide or supplement clinical decision making. We hope to continue momentum of recent years and introduce new entrants to the development process, connecting (patho)physiology with (bio)physics, and conceiving new clinical applications. We envision this process to benefit from cross‐disciplinary collaboration and analogous efforts in other body organs, but also to maximally leverage the unique opportunities of renal physiology.Level of Evidence1Technical Efficacy Stage2