cMET inhibitor crizotinib impairs angiogenesis and reduces tumor burden in the C3(1)-Tag model of basal-like breast cancer

Epidemiologic studies have associated obesity with increased risk of the aggressive basal-like breast cancer (BBC) subtype. Hepatocyte growth factor (HGF) signaling through its receptor, cMET, is elevated in obesity and is a pro-tumorigenic pathway strongly associated with BBC. We previously reported that high fat diet (HFD) elevated HGF, cMET, and phospho-cMET in normal mammary gland, with accelerated tumor development, compared to low fat diet (LFD)-fed lean controls in a murine model of BBC. We also showed that weight loss resulted in a significant reversal of HFD-induced effects on latency and elevation of HGF/cMET signaling in normal mammary and cMET in normal mammary and tumors. Here, we sought to inhibit BBC tumor progression in LFD- and HFD-fed C3(1)-Tag BBC mice using a small molecule cMET inhibitor, and began crizotinib treatment (50 mg/kg body weight by oral gavage) upon identification of the first palpable tumor. We next investigated if administering crizotinib in a window prior to tumor development would inhibit or delay BBC tumorigenesis. Treatment: Crizotinib significantly reduced mean tumor burden by 27.96 and 37.29 %, and mean tumor vascularity by 35.04 and 33.52 %, in our LFD- and HFD-fed C3(1)-Tag BBC mice, respectively. Prevention: Crizotinib significantly accelerated primary tumor progression in both diet groups but had no effect on total tumor progression or total tumor burden. In sum, cMET inhibition by crizotinib limited tumor development and microvascular density in basal-like tumor-bearing mice but did not appear to be an effective preventive agent for BBC

Development and external validation of a clinical prediction model for functional impairment after intracranial tumor surgery

OBJECTIVE Decision-making for intracranial tumor surgery requires balancing the oncological benefit against the risk for resection-related impairment. Risk estimates are commonly based on subjective experience and generalized num-bers from the literature, but even experienced surgeons overestimate functional outcome after surgery. Today, there is no reliable and objective way to preoperatively predict an individual patient's risk of experiencing any functional impair-ment. METHODS The authors developed a prediction model for functional impairment at 3 to 6 months after microsurgical resection, defined as a decrease in Karnofsky Performance Status of >= 10 points. Two prospective registries in Swit- zerland and Italy were used for development. External validation was performed in 7 cohorts from Sweden, Norway, Germany, Austria, and the Netherlands. Age, sex, prior surgery, tumor histology and maximum diameter, expected major brain vessel or cranial nerve manipulation, resection in eloquent areas and the posterior fossa, and surgical approach were recorded. Discrimination and calibration metrics were evaluated. RESULTS In the development (2437 patients, 48.2% male; mean age +/- SD: 55 +/- 15 years) and external validation (2427 patients, 42.4% male; mean age +/- SD: 58 +/- 13 years) cohorts, functional impairment rates were 21.5% and 28.5%, respectively. In the development cohort, area under the curve (AUC) values of 0.72 (95% CI 0.69-0.74) were observed. In the pooled external validation cohort, the AUC was 0.72 (95% CI 0.69-0.74), confirming generalizability. Calibration plots indicated fair calibration in both cohorts. The tool has been incorporated into a web-based application available at https://neurosurgery.shinyapps.io/impairment/. CONCLUSIONS Functional impairment after intracranial tumor surgery remains extraordinarily difficult to predict, al- though machine learning can help quantify risk. This externally validated prediction tool can serve as the basis for case by-case discussions and risk-to-benefit estimation of surgical treatment in the individual patient.Scientific Assessment and Innovation in Neurosurgical Treatment Strategie

Audio Matching for the Philological Analysis of Electroacoustic Music

The analysis of electroacoustic music may benefit from the design and development of tools for automatic audio matching, allowing musicologists to compare different versions of the same work and to draw the artistic path from the synthesis of fragments to the creation of a complete work. Music alignment has been explored as a tool in many areas, from score following to music information retrieval. This paper presents a tool for the analysis of electroacoustic music based on the comparison of two audio sources. The tool has been applied to a relevant case study: Stria by John Chowning

Anxiety in neurosurgical patients undergoing nonurgent surgery during the COVID-19 pandemic

OBJECTIVE: The COVID-19 pandemic has forced many countries into lockdown and has led to the postponement of nonurgent neurosurgical procedures. Although stress has been investigated during this pandemic, there are no reports on anxiety in neurosurgical patients undergoing nonurgent surgical procedures. METHODS: Neurosurgical patients admitted to hospitals in eastern Lombardy for nonurgent surgery after the lockdown prospectively completed a pre- and postoperative structured questionnaire. Recorded data included demographics, pathology, time on surgical waiting list, anxiety related to COVID-19, primary pathology and surgery, safety perception during hospital admission before and after surgery, and surgical outcomes. Anxiety was measured with the State-Trait Anxiety Inventory. Descriptive statistics were computed on the different variables and data were stratified according to pathology (oncological vs nononcological). Three different models were used to investigate which variables had the greatest impact on anxiety, oncological patients, and safety perception, respectively. Because the variables (Xs) were of a different nature (qualitative and quantitative), mostly asymmetrical, and related to outcome (Y) by nonlinear relationships, a machine learning approach composed of three steps (1, random forest growing; 2, relative variable importance measure; and 3, partial dependence plots) was chosen. RESULTS: One hundred twenty-three patients from 10 different hospitals were included in the study. None of the patients developed COVID-19 after surgery. State and trait anxiety were reported by 30.3% and 18.9% of patients, respectively. Higher values of state anxiety were documented in oncological compared to nononcological patients (46.7% vs 25%; p = 0.055). Anxiety was strongly associated with worry about primary pathology, surgery, disease worsening, and with stress during waiting time, as expected. Worry about positivity to SARS-CoV-2, however, was the strongest factor associated with anxiety, even though none of the patients were infected. Neuro-oncological disease was associated with state anxiety and with worry about surgery and COVID-19. Increased bed distance and availability of hand sanitizer were associated with a feeling of safety. CONCLUSIONS: These data underline the importance of psychological support, especially for neuro-oncological patients, during a pandemic