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Glioblastoma is the most common malignant brain tumor with less than 15 months median survival. To aid prognosis, there is a need for decision tools that leverage diagnostic modalities such as MRI to inform survival. In this study, we examine higher-order spatial proximity characteristics from habitats and propose two graph-based methods (minimum spanning tree and graph run-length matrix) to characterize spatial heterogeneity over tumor MRI-derived intensity habitats and assess their relationships with overall survival as well as the immune signature status of patients with glioblastoma. A data set of 74 patients was studied based on the availability of post-contrast T1-weighted and T2-weighted fluid attenuated inversion recovery (FLAIR) image data in The Cancer Image Archive (TCIA). We assessed the predictive value of MST- and GRLM-derived features from 2D images for prediction of 12-month survival status and immune signature status of patients with glioblastoma via a receiver operating characteristic curve analysis. For 12-month survival prediction using MST-based method, sensitivity and specificity were 0.82 and 0.79 respectively. For GRLM-based method, sensitivity and specificity were 0.73 and 0.77 respectively. For immune status, sensitivity and specificity were 0.91 and 0.69, respectively, for the GRLM-based method with an immune effector. Our results show that the proposed MST- and GRLM-derived features are predictive of 12-month survival status as well as the immune signature status of patients with glioblastoma. To our knowledge, this is the first application of MST- and GRLM-based proximity analyses for the study of radiologically-defined tumor habitats in glioblastoma.

Disruption of the blood-brain barrier (BBB) by cancer cells is linked to metastatic tumor initiation and progression; however, the pathways that drive these events remain poorly understood. Here, we have developed novel patient-derived xenograft (PDX) models of brain metastases that recapitulate pathological growth features found in original patient samples, thus allowing for analysis of BBB disruption by tumor cells. We report that the BBB is selectively disrupted in brain metastases, in part, via inhibition of the endothelial cell-expressed docosahexaenoic acid (DHA) transporter, major facilitator superfamily domain 2a (Mfsd2a). Loss of Mfsd2a expression in the tumor endothelium results in enhanced BBB leakage, but reduced DHA transport and altered lipid metabolism within metastases. Mfsd2a expression in normal cerebral endothelial cells is cooperatively regulated by TGFβ and bFGF signaling pathways, and these pathways are pathologically diminished in the brain metastasis endothelium. These results not only reveal a fundamental pathway underlying BBB disruption by metastatic cancer cells, but also suggest that restoring DHA metabolism in the brain tumor microenvironment may be a novel therapeutic strategy to block metastatic cell growth and survival.

Meningiomas account for one-third of all primary brain tumors. Although typically benign, about 20% of meningiomas are aggressive, and despite the rigor of the current histopathological classification system there remains considerable uncertainty in predicting tumor behavior. Here, we analyzed 160 tumors from all 3 World Health Organization (WHO) grades (I through III) using clinical, gene expression, and sequencing data. Unsupervised clustering analysis identified 3 molecular types (A, B, and C) that reliably predicted recurrence. These groups did not directly correlate with the WHO grading system, which classifies more than half of the tumors in the most aggressive molecular type as benign. Transcriptional and biochemical analyses revealed that aggressive meningiomas involve loss of the repressor function of the DREAM complex, which results in cell-cycle activation; only tumors in this category tend to recur after full resection. These findings should improve our ability to predict recurrence and develop targeted treatments for these clinically challenging tumors.

Clinical methods of detecting diabetic peripheral neuropathy (DPN) are not objective and reproducible. We therefore evaluated if SUDOSCAN, a new method developed to provide a quick, non-invasive and quantitative assessment of sudomotor function can reliably screen for DPN. 70 subjects (45 with type 1 diabetes and 25 healthy volunteers [HV]) underwent detailed assessments including clinical, neurophysiological and 5 standard cardiovascular reflex tests (CARTs). Using the American Academy of Neurology criteria subjects were classified into DPN and No-DPN groups. Based on CARTs subjects were also divided into CAN, subclinical-CAN and no-CAN. Sudomotor function was assessed with measurement of hand and foot Electrochemical Skin Conductance (ESC) and calculation of the CAN risk score. Foot ESC (μS) was significantly lower in subjects with DPN [n = 24; 53.5(25.1)] compared to the No-DPN [77.0(7.9)] and HV [77.1(14.3)] groups (ANCOVA p<0.001). Sensitivity and specificity of foot ESC for classifying DPN were 87.5% and 76.2%, respectively. The area under the ROC curve (AUC) was 0.85. Subjects with CAN had significantly lower foot [55.0(28.2)] and hand [53.5(19.6)] ESC compared to No-CAN [foot ESC, 72.1(12.2); hand ESC 64.9(14.4)] and HV groups (ANCOVA p<0.001 and 0.001, respectively). ROC analysis of CAN risk score to correctly classify CAN revealed a sensitivity of 65.0% and specificity of 80.0%. AUC was 0.75. Both foot and hand ESC demonstrated strong correlation with individual parameters and composite scores of nerve conduction and CAN. SUDOSCAN, a non-invasive and quick test, could be used as an objective screening test for DPN in busy diabetic clinics, insuring adherence to current recommendation of annual assessments for all diabetic patients that remains unfulfilled.

One of the most common and aggressive malignant brain tumors is Glioblastoma multiforme. Despite the multimodality treatment such as radiation therapy and chemotherapy (temozolomide: TMZ), the median survival rate of glioblastoma patient is less than 15 months. In this study, we investigated the association between measures of spatial diversity derived from spatial point pattern analysis of multiparametric magnetic resonance imaging (MRI) data with molecular status as well as 12-month survival in glioblastoma. We obtained 27 measures of spatial proximity (diversity) via spatial point pattern analysis of multiparametric T1 post-contrast and T2 fluid-attenuated inversion recovery MRI data. These measures were used to predict 12-month survival status (≤12 or >12 months) in 74 glioblastoma patients. Kaplan-Meier with receiver operating characteristic analyses was used to assess the relationship between derived spatial features and 12-month survival status as well as molecular subtype status in patients with glioblastoma. Kaplan-Meier survival analysis revealed that 14 spatial features were capable of stratifying overall survival in a statistically significant manner. For prediction of 12-month survival status based on these diversity indices, sensitivity and specificity were 0.86 and 0.64, respectively. The area under the receiver operating characteristic curve and the accuracy were 0.76 and 0.75, respectively. For prediction of molecular subtype status, proneural subtype shows highest accuracy of 0.93 among all molecular subtypes based on receiver operating characteristic analysis. We find that measures of spatial diversity from point pattern analysis of intensity habitats from T1 post-contrast and T2 fluid-attenuated inversion recovery images are associated with both tumor subtype status and 12-month survival status and may therefore be useful indicators of patient prognosis, in addition to providing potential guidance for molecularly-targeted therapies in Glioblastoma multiforme.

Few studies implicate immunoregulatory gene expression in tumor cells in arbitrating brain tumor progression. Here we show that fibrinogen-like protein 2 (FGL2) is highly expressed in glioma stem cells and primary glioblastoma (GBM) cells. FGL2 knockout in tumor cells did not affect tumor-cell proliferation in vitro or tumor progression in immunodeficient mice but completely impaired GBM progression in immune-competent mice. This impairment was reversed in mice with a defect in dendritic cells (DCs) or CD103 + DC differentiation in the brain and in tumor-draining lymph nodes. The presence of FGL2 in tumor cells inhibited granulocyte-macrophage colony-stimulating factor (GM-CSF)-induced CD103 + DC differentiation by suppressing NF-κB, STAT1/5, and p38 activation. These findings are relevant to GBM patients because a low level of FGL2 expression with concurrent high GM-CSF expression is associated with higher CD8B expression and longer survival. These data provide a rationale for therapeutic inhibition of FGL2 in brain tumors. Fibrinogen-like protein 2 (FGL2) mediates immune suppression in glioblastoma (GBM). Here, the authors show that FGL-2 expressed by GBM cancer cells acts by suppressing the differentiation of CD103+ DC cells required to activate the anti-tumor CD8+ T cell response via blocking GM-CSF signalling at NFKB, STAT1/5 and p38 level.

Fibrinogen-like protein 1 (FGL1) has been associated with improved survival in hepatocellular carcinoma (HCC). However, recent evidence suggests that FGL1 may bind to surface receptors on lymphocytes and induce immune senescence. In this issue of the JCI, Lin and co-authors show that FGL1 may be acetylated by aspirin and targeted for degradation, which is associated with increased antitumor immunity and improved survival. Similar findings were obtained with inhibitors of sirtuin 2 (SIRT2), a histone deacetylase. These findings expand our current understanding of the role of FGL1 in cancer and provide an impetus for the evaluation of alternative immunotherapy combinations in HCC.

Purpose This study aims to examine the impact of environmental sustainability, social sustainability and corporate reputation on the business performance of energy companies operating in an emerging market. Design/methodology/approach A self-administered questionnaire was distributed to 400 managers in top and middle-level positions in energy companies located in Kuala Lumpur, Malaysia were collected through an online survey. These managers had a strong understanding of the operational aspects of the companies and possessed good knowledge of the company’s performance. The collected data were analyzed using multiple regression analysis to assess the hypothesized relationships. Findings The findings reveal significant influences of corporate reputation, environmental sustainability and social sustainability on the business performance of energy companies operating in an emerging market. Notably, corporate reputation emerges as the primary predictor, underscoring the significance of emphasizing the fundamental aspects of companies such as superior products or services, effective management practices and investment quality. A strong reputation is essential for attracting investors, customers and other stakeholders by meeting their expectations for high-quality products or services. It serves as a crucial factor in establishing trust and credibility, which are vital for sustained success in the market. Practical implications Energy companies should proactively integrate corporate reputation into their operational strategies to enhance business performance. Furthermore, they should develop and execute comprehensive environmental and social sustainability initiatives within their organizations. By doing so, they can effectively enhance both financial and non-financial performance while fostering a culture of employee engagement aimed at further enhancing productivity. Originality/value This study stands out as a unique and significant contribution to theory by using the triple bottom line framework as the underlying theory and integrating corporate reputation into the proposed framework. It represents a novel approach, particularly within the context of energy companies operating in an emerging market. This research serves as a valuable complement to prior studies primarily conducted in developed (Western) economies, expanding the knowledge base in this field.

MRI-guided laser interstitial thermal therapy (LITT) is the selective ablation of a lesion or a tissue using heat emitted from a laser device. LITT is considered a less invasive technique compared to open surgery that provides a nonsurgical solution for patients who cannot tolerate surgery. Although laser ablation has been used to treat brain lesions for decades, recent advances in MRI have improved lesion targeting and enabled real-time accurate monitoring of the thermal ablation process. These advances have led to a plethora of research involving the technique, safety, and potential applications of LITT. LITT is a minimally invasive treatment modality that shows promising results and is associated with decreased morbidity. It has various applications, such as treatment of glioma, brain metastases, radiation necrosis, and epilepsy. It can provide a safer alternative treatment option for patients in whom the lesion is not accessible by surgery, who are not surgical candidates, or in whom other standard treatment options have failed. Our aim is to review the current literature on LITT and provide a descriptive review of the technique, imaging findings, and clinical applications for neurosurgery.

ObjectiveTo assess clinical, electrophysiological and whole-body muscle MRI measurements of progression in patients with motor neuron disease (MND), as tools for future clinical trials, and to probe pathophysiological mechanisms in vivo.MethodsA prospective, longitudinal, observational, clinicoelectrophysiological and radiological cohort study was performed. Twenty-nine patients with MND and 22 age-matched and gender-matched healthy controls were assessed with clinical measures, electrophysiological motor unit number index (MUNIX) and T2-weighted whole-body muscle MRI, at first clinical presentation and 4 months later. Between-group differences and associations were assessed using age-adjusted and gender-adjusted multivariable regression models. Within-subject longitudinal changes were assessed using paired t-tests. Patterns of disease spread were modelled using mixed-effects multivariable regression, assessing associations between muscle relative T2 signal and anatomical adjacency to site of clinical onset.ResultsPatients with MND had 30% higher relative T2 muscle signal than controls at baseline (all regions mean, 95% CI 15% to 45%, p<0.001). Higher T2 signal was associated with greater overall disability (coefficient −0.009, 95% CI −0.017 to –0.001, p=0.023) and with clinical weakness and lower MUNIX in multiple individual muscles. Relative T2 signal in bilateral tibialis anterior increased over 4 months in patients with MND (right: 10.2%, 95% CI 2.0% to 18.4%, p=0.017; left: 14.1%, 95% CI 3.4% to 24.9%, p=0.013). Anatomically, contiguous disease spread on MRI was not apparent in this model.ConclusionsWhole-body muscle MRI offers a new approach to objective assessment of denervation over short timescales in MND and enables investigation of patterns of disease spread in vivo. Muscles inaccessible to conventional clinical and electrophysiological assessment may be investigated using this methodology.