TiME OUT: Time-specific machine-learning evaluation to optimize ultramassive transfusion.

BACKGROUND: Ultramassive transfusion (UMT) is a resource-demanding intervention for trauma patients in hemorrhagic shock, and associated mortality rates remains high. Current research has been unable to identify a transfusion ceiling or point where UMT transitions from lifesaving to futility. Furthermore, little consideration has been given to how time-specific patient data points impact decisions with ongoing high-volume resuscitation. Therefore, this study sought to use time-specific machine learning modeling to predict mortality and identify parameters associated with survivability in trauma patients undergoing UMT. METHODS: A retrospective review was conducted at a Level I trauma (2018-2021) and included trauma patients meeting criteria for UMT, defined as ≥20 red blood cell products within 24 hours of admission. Cross-sectional data were obtained from the blood bank and trauma registries, and time-specific data were obtained from the electronic medical record. Time-specific decision-tree models predicating mortality were generated and evaluated using area under the curve. RESULTS: In the 180 patients included, mortality rate was 40.5% at 48 hours and 52.2% overall. The deceased received significantly more blood products with a median of 71.5 total units compared with 55.5 in the survivors ( p < 0.001) and significantly greater rates of packed red blood cells and fresh frozen plasma at each time interval. Time-specific decision-tree models predicted mortality with an accuracy as high as 81%. In the early time intervals, hemodynamic stability, undergoing an emergency department thoracotomy, and injury severity were most predictive of survival, while, in the later intervals, markers of adequate resuscitation such as arterial pH and lactate level became more prominent. CONCLUSION: This study supports that the decision of "when to stop" in UMT resuscitation is not based exclusively on the number of units transfused but rather the complex integration of patient and time-specific data. Machine learning is an effective tool to investigate this concept, and further research is needed to refine and validate these time-specific decision-tree models. LEVEL OF EVIDENCE: Prognostic and Epidemiological; Level IV.

Themes in neuronavigation research: A machine learning topic analysis.

Objective: To understand trends in neuronavigation we employed machine learning methods to perform a broad literature review which would be impractical by manual inspection. Methods: PubMed was queried for articles with "Neuronavigation" in any field from inception-2020. Articles were designated neuronavigation-focused (NF) if "Neuronavigation" was a major MeSH. The latent dirichlet allocation topic modeling technique was used to identify themes of NF research. Results: There were 3896 articles of which 1727 (44%) were designated as NF. Between 1999-2009 and 2010-2020, the number of NF publications experienced 80% growth. Between 2009-2014 and 2015-2020, there was a 0.3% decline. Eleven themes covered 1367 (86%) NF articles. "Resection of Eloquent Lesions" comprised the highest number of articles (243), followed by "Accuracy and Registration" (242), "Patient Outcomes" (156), "Stimulation and Mapping" (126), "Planning and Visualization" (123), "Intraoperative Tools" (104), "Placement of Ventricular Catheters" (86), "Spine Surgery" (85), "New Systems" (80), "Guided Biopsies" (61), and "Surgical Approach" (61). All topics except for "Planning and Visualization", "Intraoperative Tools", and "New Systems" exhibited a monotonic positive trend. When analyzing subcategories, there were a greater number of clinical assessments or usage of existing neuronavigation systems (77%) rather than modification or development of new apparatuses (18%). Conclusion: NF research appears to focus on the clinical assessment of neuronavigation and to a lesser extent on the development of new systems. Although neuronavigation has made significant strides, NF research output appears to have plateaued in the last decade.

Glioblastomas located in proximity to the subventricular zone (SVZ) exhibited enrichment of gene expression profiles associated with the cancer stem cell state.

INTRODUCTION: Conflicting results have been reported in the association between glioblastoma proximity to the subventricular zone (SVZ) and enrichment of cancer stem cell properties. Here, we examined this hypothesis using magnetic resonance (MR) images derived from 217 The Cancer Imaging Archive (TCIA) glioblastoma subjects. METHODS: Pre-operative MR images were segmented automatically into contrast enhancing (CE) tumor volumes using Iterative Probabilistic Voxel Labeling (IPVL). Distances were calculated from the centroid of CE tumor volumes to the SVZ and correlated with gene expression profiles of the corresponding glioblastomas. Correlative analyses were performed between SVZ distance, gene expression patterns, and clinical survival. RESULTS: Glioblastoma located in proximity to the SVZ showed increased mRNA expression patterns associated with the cancer stem-cell state, including CD133 (P = 0.006). Consistent with the previous observations suggesting that glioblastoma stem cells exhibit increased DNA repair capacity, glioblastomas in proximity to the SVZ also showed increased expression of DNA repair genes, including MGMT (P = 0.018). Reflecting this enhanced DNA repair capacity, the genomes of glioblastomas in SVZ proximity harbored fewer single nucleotide polymorphisms relative to those located distant to the SVZ (P = 0.003). Concordant with the notion that glioblastoma stem cells are more aggressive and refractory to therapy, patients with glioblastoma in proximity to SVZ exhibited poorer progression free and overall survival (P < 0.01). CONCLUSION: An unbiased analysis of TCIA suggests that glioblastomas located in proximity to the SVZ exhibited mRNA expression profiles associated with stem cell properties, increased DNA repair capacity, and is associated with poor clinical survival.

Molecular physiology of contrast enhancement in glioblastomas: An analysis of The Cancer Imaging Archive (TCIA).

The physiologic processes underlying MRI contrast enhancement in glioblastoma patients remain poorly understood. MRIs of 148 glioblastoma subjects from The Cancer Imaging Archive were segmented using Iterative Probabilistic Voxel Labeling (IPVL). Three aspects of contrast enhancement (CE) were parametrized: the mean intensity of all CE voxels (CEi), the intensity heterogeneity in CE (CEh), and volumetric ratio of CE to necrosis (CEr). Associations between these parameters and patterns of gene expression were analyzed using DAVID functional enrichment analysis. Glioma CpG island methylator phenotype (G-CIMP) glioblastomas were poorly enhancing. Otherwise, no differences in CE parameters were found between proneural, neural, mesenchymal, and classical glioblastomas. High CEi was associated with expression of genes that mediate inflammatory responses. High CEh was associated with increased expression of genes that regulate remodeling of extracellular matrix (ECM) and endothelial permeability. High CEr was associated with increased expression of genes that mediate cellular response to stressful metabolic states, including hypoxia and starvation. Our results indicate that CE in glioblastoma is associated with distinct biological processes involved in inflammatory response and tissue hypoxia. Integrative analysis of these CE parameters may yield meaningful information pertaining to the biologic state of glioblastomas and guide future therapeutic paradigms.

Immune evasion mediated by PD-L1 on glioblastoma-derived extracellular vesicles.

Binding of programmed death ligand-1 (PD-L1) to programmed cell death protein-1 (PD1) leads to cancer immune evasion via inhibition of T cell function. One of the defining characteristics of glioblastoma, a universally fatal brain cancer, is its profound local and systemic immunosuppression. Glioblastoma has also been shown to generate extracellular vesicles (EVs), which may play an important role in tumor progression. We thus hypothesized that glioblastoma EVs may be important mediators of immunosuppression and that PD-L1 could play a role. We show that glioblastoma EVs block T cell activation and proliferation in response to T cell receptor stimulation. PD-L1 was expressed on the surface of some, but not of all, glioblastoma-derived EVs, with the potential to directly bind to PD1. An anti-PD1 receptor blocking antibody significantly reversed the EV-mediated blockade of T cell activation but only when PD-L1 was present on EVs. When glioblastoma PD-L1 was up-regulated by IFN-γ, EVs also showed some PD-L1-dependent inhibition of T cell activation. PD-L1 expression correlated with the mesenchymal transcriptome profile and was anatomically localized in the perinecrotic and pseudopalisading niche of human glioblastoma specimens. PD-L1 DNA was present in circulating EVs from glioblastoma patients where it correlated with tumor volumes of up to 60 cm3. These results suggest that PD-L1 on EVs may be another mechanism for glioblastoma to suppress antitumor immunity and support the potential of EVs as biomarkers in tumor patients.

Quantification of glioblastoma mass effect by lateral ventricle displacement.

Mass effect has demonstrated prognostic significance for glioblastoma, but is poorly quantified. Here we define and characterize a novel neuroimaging parameter, lateral ventricle displacement (LVd), which quantifies mass effect in glioblastoma patients. LVd is defined as the magnitude of displacement from the center of mass of the lateral ventricle volume in glioblastoma patients relative to that a normal reference brain. Pre-operative MR images from 214 glioblastoma patients from The Cancer Imaging Archive (TCIA) were segmented using iterative probabilistic voxel labeling (IPVL). LVd, contrast enhancing volumes (CEV) and FLAIR hyper-intensity volumes (FHV) were determined. Associations with patient survival and tumor genomics were investigated using data from The Cancer Genome Atlas (TCGA). Glioblastoma patients had significantly higher LVd relative to patients without brain tumors. The variance of LVd was not explained by tumor volume, as defined by CEV or FLAIR. LVd was robustly associated with glioblastoma survival in Cox models which accounted for both age and Karnofsky's Performance Scale (KPS) (p = 0.006). Glioblastomas with higher LVd demonstrated increased expression of genes associated with tumor proliferation and decreased expression of genes associated with tumor invasion. Our results suggest LVd is a quantitative measure of glioblastoma mass effect and a prognostic imaging biomarker.

Cell type specificity of neurovascular coupling in cerebral cortex.

Identification of the cellular players and molecular messengers that communicate neuronal activity to the vasculature driving cerebral hemodynamics is important for (1) the basic understanding of cerebrovascular regulation and (2) interpretation of functional Magnetic Resonance Imaging (fMRI) signals. Using a combination of optogenetic stimulation and 2-photon imaging in mice, we demonstrate that selective activation of cortical excitation and inhibition elicits distinct vascular responses and identify the vasoconstrictive mechanism as Neuropeptide Y (NPY) acting on Y1 receptors. The latter implies that task-related negative Blood Oxygenation Level Dependent (BOLD) fMRI signals in the cerebral cortex under normal physiological conditions may be mainly driven by the NPY-positive inhibitory neurons. Further, the NPY-Y1 pathway may offer a potential therapeutic target in cerebrovascular disease.

Differential localization of glioblastoma subtype: implications on glioblastoma pathogenesis.

INTRODUCTION: The subventricular zone (SVZ) has been implicated in the pathogenesis of glioblastoma. Whether molecular subtypes of glioblastoma arise from unique niches of the brain relative to the SVZ remains largely unknown. Here, we tested whether these subtypes of glioblastoma occupy distinct regions of the cerebrum and examined glioblastoma localization in relation to the SVZ. METHODS: Pre-operative MR images from 217 glioblastoma patients from The Cancer Imaging Archive were segmented automatically into contrast enhancing (CE) tumor volumes using Iterative Probabilistic Voxel Labeling (IPVL). Probabilistic maps of tumor location were generated for each subtype and distances were calculated from the centroid of CE tumor volumes to the SVZ. Glioblastomas that arose in a Genetically Modified Murine Model (GEMM) model were also analyzed with regard to SVZ distance and molecular subtype. RESULTS: Classical and mesenchymal glioblastomas were more diffusely distributed and located farther from the SVZ. In contrast, proneural and neural glioblastomas were more likely to be located in closer proximity to the SVZ. Moreover, in a GFAP-CreER; PtenloxP/loxP; Trp53loxP/loxP; Rb1loxP/loxP; Rbl1-/- GEMM model of glioblastoma where tumor can spontaneously arise in different regions of the cerebrum, tumors that arose near the SVZ were more likely to be of proneural subtype (p < 0.0001). CONCLUSIONS: Glioblastoma subtypes occupy different regions of the brain and vary in proximity to the SVZ. These findings harbor implications pertaining to the pathogenesis of glioblastoma subtypes.

Characterization and Correction of Geometric Distortions in 814 Diffusion Weighted Images.

INTRODUCTION: Diffusion Weighted Imaging (DWI), which is based on Echo Planar Imaging (EPI) protocols, is becoming increasingly important for neurosurgical applications. However, its use in this context is limited in part by significant spatial distortion inherent to EPI. METHOD: We evaluated an efficient algorithm for EPI distortion correction (EPIC) across 814 DWI scans from 250 brain tumor patients and quantified the magnitude of geometric distortion for whole brain and multiple brain regions. RESULTS: Evaluation of the algorithm's performance revealed significantly higher mutual information between T1-weighted pre-contrast images and corrected b = 0 images than the uncorrected b = 0 images (p < 0.001). The distortion magnitude across all voxels revealed a median EPI distortion effect of 2.1 mm, ranging from 1.2 mm to 5.9 mm, the 5th and 95th percentile, respectively. Regions adjacent to bone-air interfaces, such as the orbitofrontal cortex, temporal poles, and brain stem, were the regions most severely affected by DWI distortion. CONCLUSION: Using EPIC to estimate the degree of distortion in 814 DWI brain tumor images enabled the creation of a topographic atlas of DWI distortion across the brain. The degree of displacement of tumors boundaries in uncorrected images is severe but can be corrected for using EPIC. Our results support the use of distortion correction to ensure accurate and careful application of DWI to neurosurgical practice.

Orthogonal targeting of EGFRvIII expressing glioblastomas through simultaneous EGFR and PLK1 inhibition.

We identified a synthetic lethality between PLK1 silencing and the expression of an oncogenic Epidermal Growth Factor Receptor, EGFRvIII. PLK1 promoted homologous recombination (HR), mitigating EGFRvIII induced oncogenic stress resulting from DNA damage accumulation. Accordingly, PLK1 inhibition enhanced the cytotoxic effects of the DNA damaging agent, temozolomide (TMZ). This effect was significantly more pronounced in an Ink4a/Arf(-/-) EGFRvIII glioblastoma model relative to an Ink4a/Arf(-/-) PDGF-ß model. The tumoricidal and TMZ-sensitizing effects of BI2536 were uniformly observed across Ink4a/Arf(-/-) EGFRvIII glioblastoma clones that acquired independent resistance mechanisms to EGFR inhibitors, suggesting these resistant clones retain oncogenic stress that required PLK1 compensation. Although BI2536 significantly augmented the anti-neoplastic effect of EGFR inhibitors in the Ink4a/Arf(-/-) EGFRvIII model, durable response was not achieved until TMZ was added. Our results suggest that optimal therapeutic effect against glioblastomas requires a "multi-orthogonal" combination tailored to the molecular physiology associated with the target cancer genome.

Axinellamines as broad-spectrum antibacterial agents: scalable synthesis and biology.

Antibiotic-resistant bacteria present an ongoing challenge to both chemists and biologists as they seek novel compounds and modes of action to out-maneuver continually evolving resistance pathways, especially against Gram-negative strains. The dimeric pyrrole-imidazole alkaloids represent a unique marine natural product class with diverse primary biological activity and chemical architecture. This full account traces the strategy used to develop a second-generation route to key spirocycle 9, culminating in a practical synthesis of the axinellamines and enabling their discovery as broad-spectrum antibacterial agents, with promising activity against both Gram-positive and Gram-negative bacteria. While their detailed mode of antibacterial action remains unclear, the axinellamines appear to cause secondary membrane destabilization and impart an aberrant cellular morphology consistent with the inhibition of normal septum formation. This study serves as a rare example of a natural product initially reported to be devoid of biological activity surfacing as an active antibacterial agent with an intriguing mode of action.

A genome-wide miRNA screen revealed miR-603 as a MGMT-regulating miRNA in glioblastomas.

MGMT expression is a critical determinant for therapeutic resistance to DNA alkylating agents. We previously demonstrated that MGMT expression is post-transcriptionally regulated by miR-181d and other miRNAs. Here, we performed a genome-wide screen to identify MGMT regulating miRNAs. Candidate miRNAs were further tested for inverse correlation with MGMT expression in clinical specimens. We identified 15 candidate miRNAs and characterized the top candidate, miR-603. Transfection of miR-603 suppressed MGMT mRNA/protein expression in vitro and in vivo; this effect was reversed by transfection with antimiR-603. miR-603 affinity-precipitated with MGMT mRNA and suppressed luciferase activity in an MGMT-3'UTR-luciferase assay, suggesting direct interaction between miR-603 and MGMT 3'UTR. miR-603 transfection enhanced the temozolomide (TMZ) sensitivity of MGMT-expressing glioblastoma cell lines. Importantly, miR-603 mediated MGMT suppression and TMZ resistance were reversed by expression of an MGMT cDNA. In a collection of 74 clinical glioblastoma specimens, both miR-603 and miR-181d levels inversely correlated with MGMT expression. Moreover, a combined index of the two miRNAs better reflected MGMT expression than each individually. These results suggest that MGMT is co-regulated by independent miRNAs. Characterization of these miRNAs should contribute toward strategies for enhancing the efficacy of DNA alkylating agents.

Genome-wide shRNA screen revealed integrated mitogenic signaling between dopamine receptor D2 (DRD2) and epidermal growth factor receptor (EGFR) in glioblastoma.

Glioblastoma remains one of the deadliest of human cancers, with most patients succumbing to the disease within two years of diagnosis. The available data suggest that simultaneous inactivation of critical nodes within the glioblastoma molecular circuitry will be required for meaningful clinical efficacy. We conducted parallel genome-wide shRNA screens to identify such nodes and uncovered a number of G-Protein Coupled Receptor (GPCR) neurotransmitter pathways, including the Dopamine Receptor D2 (DRD2) signaling pathway. Supporting the importance of DRD2 in glioblastoma, DRD2 mRNA and protein expression were elevated in clinical glioblastoma specimens relative to matched non-neoplastic cerebrum. Treatment with independent si-/shRNAs against DRD2 or with DRD2 antagonists suppressed the growth of patient-derived glioblastoma lines both in vitro and in vivo. Importantly, glioblastoma lines derived from independent genetically engineered mouse models (GEMMs) were more sensitive to haloperidol, an FDA approved DRD2 antagonist, than the premalignant astrocyte lines by approximately an order of magnitude. The pro-proliferative effect of DRD2 was, in part, mediated through a GNAI2/Rap1/Ras/ERK signaling axis. Combined inhibition of DRD2 and Epidermal Growth Factor Receptor (EGFR) led to synergistic tumoricidal activity as well as ERK suppression in independent in vivo and in vitro glioblastoma models. Our results suggest combined EGFR and DRD2 inhibition as a promising strategy for glioblastoma treatment.

In vivo stimulus-induced vasodilation occurs without IP3 receptor activation and may precede astrocytic calcium increase.

Calcium-dependent release of vasoactive gliotransmitters is widely assumed to trigger vasodilation associated with rapid increases in neuronal activity. Inconsistent with this hypothesis, intact stimulus-induced vasodilation was observed in inositol 1,4,5-triphosphate (IP3) type-2 receptor (R2) knock-out (KO) mice, in which the primary mechanism of astrocytic calcium increase-the release of calcium from intracellular stores following activation of an IP3-dependent pathway-is lacking. Further, our results in wild-type (WT) mice indicate that in vivo onset of astrocytic calcium increase in response to sensory stimulus could be considerably delayed relative to the simultaneously measured onset of arteriolar dilation. Delayed calcium increases in WT mice were observed in both astrocytic cell bodies and perivascular endfeet. Thus, astrocytes may not play a role in the initiation of blood flow response, at least not via calcium-dependent mechanisms. Moreover, an increase in astrocytic intracellular calcium was not required for normal vasodilation in the IP3R2-KO animals.

Cognition, glucose metabolism and amyloid burden in Alzheimer's disease.

The authors investigated relationships between glucose metabolism, amyloid load, and measures of cognitive and functional impairment in Alzheimer's disease (AD). Patients meeting criteria for probable AD underwent (11)C-labeled Pittsburgh Compound-B ([(11)C]PIB) and 18F-fluorodeoxyglucose ([(18)F]FDG) positron emission tomography (PET) imaging and were assessed on a set of clinical measures. The Pittsburgh Compound-B (PIB) Distribution volume ratios and fluorodeoxyglucose (FDG) scans were spatially normalized and average PIB counts from regions-of-interest (ROI) were used to compute a measure of global PIB uptake. Separate voxel-wise regressions explored local and global relationships between metabolism, amyloid burden, and clinical measures. Regressions reflected cognitive domains assessed by individual measures, with visuospatial tests associated with more posterior metabolism, and language tests associated with metabolism in the left hemisphere. Correlating regional FDG uptake with these measures confirmed these findings. In contrast, no correlations were found between either voxel-wise or regional PIB uptake and any of the clinical measures. Finally, there were no associations between regional PIB and FDG uptake. We conclude that regional and global amyloid burden does not correlate with clinical status or glucose metabolism in AD.