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The spinal cord has a poor ability to regenerate after an injury, which may be due to cell loss, cyst formation, inflammation, and scarring. A promising approach to treating a spinal cord injury (SCI) is the use of biomaterials. We have developed a novel hydrogel scaffold fabricated from oligo(poly(ethylene glycol) fumarate) (OPF) as a 0.08 mm thick sheet containing polymer ridges and a cell-attractive surface on the other side. When the cells are cultured on OPF via chemical patterning, the cells attach, align, and deposit ECM along the direction of the pattern. Animals implanted with the rolled scaffold sheets had greater hindlimb recovery compared to that of the multichannel scaffold control, which is likely due to the greater number of axons growing across it. The immune cell number (microglia or hemopoietic cells: 50–120 cells/mm2 in all conditions), scarring (5–10% in all conditions), and ECM deposits (Laminin or Fibronectin: approximately 10–20% in all conditions) were equal in all conditions. Overall, the results suggest that the scaffold sheets promote axon outgrowth that can be guided across the scaffold, thereby promoting hindlimb recovery. This study provides a hydrogel scaffold construct that can be used in vitro for cell characterization or in vivo for future neuroprosthetics, devices, or cell and ECM delivery.

Machine learning is a powerful tool that is increasingly being used in many research areas, including neuroscience. The recent development of new algorithms and network architectures, especially in the field of deep learning, has made machine learning models more reliable and accurate and useful for the biomedical research sector. By minimizing the effort necessary to extract valuable features from datasets, they can be used to find trends in data automatically and make predictions about future data, thereby improving the reproducibility and efficiency of research. One application is the automatic evaluation of micrograph images, which is of great value in neuroscience research. While the development of novel models has enabled numerous new research applications, the barrier to use these new algorithms has also decreased by the integration of deep learning models into known applications such as microscopy image viewers. For researchers unfamiliar with machine learning algorithms, the steep learning curve can hinder the successful implementation of these methods into their workflows. This review explores the use of machine learning in neuroscience, including its potential applications and limitations, and provides some guidance on how to select a fitting framework to use in real-life research projects.

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QUESTION The role of temozolomide chemotherapy alone in isocitrate dehydrogenase (IDH)-mutant astrocytomas has not been conclusively determined. Recent studies have linked temozolomide therapy with induction of hypermutation and poor clinical course in some IDH-mutant gliomas. METHODS In this retrospective, single-center study, 183 patients with astrocytoma, IDH-mutant, CNS WHO grade 2 or 3 diagnosed between 2003 and 2019 were included. Patients initially monitored by means of a wait-and-scan strategy, or treated with radiotherapy alone, or receiving temozolomide alone, after histological sampling through biopsy or tumor resection, were studied. Progression-free and overall survival was analysed. A matched-pair analysis accounting for post-surgical tumor volume was conducted. RESULTS Initial T2 tumor volume and WHO grade were associated with survival in univariate analyses (p < 0.01). The proportion of WHO grade 2 gliomas was highest in the wait-and-scan cohort (p < 0.01). Tumor volumes were largest in the temozolomide cohort (p < 0.01). Radiotherapy was associated with longer progression-free survival than temozolomide (6.2 vs 3.4 years, p = 0.02) and wait-and-scan strategies (6.2 vs 4 years, p = 0.03). Patients treated with radiotherapy showed longer overall survival than patients treated with temozolomide (14.4 vs 10.7 years, p = 0.02). Survival was longer in patients initially monitored by means of a wait-and-scan strategy than in patients treated with temozolomide (not reached vs 10.7 years, p < 0.0001). The same association was seen in a subgroup analysis of WHO grade 2 astrocytomas (p = 0.02) and by trend in a matched pair analysis (p = 0.09). CONCLUSION The results suggest superiority for progression-free survival of radiotherapy alone over temozolomide alone or wait-and-scan strategies and for overall survival of radiotherapy alone and wait-and-scan therapies over temozolomide in IDH-mutant WHO grade 2 and 3. Recent study results indicating that temozolomide might compromise prognosis in some patients with IDH-mutant gliomas might be supported by our data.

Purpose The role of temozolomide chemotherapy alone in isocitrate dehydrogenase (IDH)-mutant astrocytomas has not been conclusively determined. Radiotherapy might be superior to temozolomide. Recent studies have linked temozolomide with induction of hypermutation and poor clinical course in some IDH-mutant gliomas. Methods In this retrospective study, 183 patients with astrocytoma, IDH-mutant, CNS WHO grade 2 or 3 and diagnosed between 2001 and 2019 were included. Patients initially monitored by wait-and-scan strategies or treated with radiotherapy or temozolomide alone were studied. Patient data were correlated with outcome. Matched pair and subgroup analyses were conducted. Results Radiotherapy was associated with longer progression-free survival than temozolomide (6.2 vs 3.4 years, p = 0.02) and wait-and-scan strategies (6.2 vs 4 years, p = 0.03). Patients treated with radiotherapy lived longer than patients treated with temozolomide (14.4 vs 10.7 years, p = 0.02). Survival was longer in the wait-and-scan cohort than in the temozolomide cohort (not reached vs 10.7 years, p Conclusion The results suggest superiority of radiotherapy over temozolomide and wait-and-scan strategies regarding progression-free survival and superiority of radiotherapy over temozolomide regarding overall survival. Our results are consistent with the notion that early temozolomide might compromise outcome in some patients.

BACKGROUND Lower grade gliomas show heterogenous appearance on T2-weighted MRI. Some tumors grow diffusely along axonal structures whereas others distort adjacent brain tissue through local mass effect. The diagnostic, therapeutic and prognostic implication of differential growth patterns on MRI remain unknown and are difficult to assess quantitatively. METHODS A web-based application allowing for image preprocessing and providing a comprehensive edge detection tool by means of quantifying tumor border delineation on T2-weighted images based on the canny edge detection algorithm was developed. A sigma value between 1 and 100 determined the threshold where tumor borders where not detected anymore, with 1 equating to the lowest threshold and thus detection of all edges contained in the image. Two experienced faculty members assigned sigma values to axial T2 images of a random sample of 20 WHO grade 2 astrocytomas, IDH-mutant and 1p/19q-non-codeleted. The sigma values were then compared with a binary, subjective rating by the same faculty staff according to the perceived predominant growth pattern (diffuse versus circumscript) of each glioma. RESULTS When subjectively categorizing tumors binarily (diffuse versus circumscript), there was moderate interrater variability between observers (cohen’s kappa=0.6). Raters agreed in 16 of 20 cases, terming 7 gliomas unanimously diffuse and 9 gliomas circumscript. In 4 cases, the raters opinions diverged. The sigma values differed significantly between diffuse and circumscript tumors in both raters (rater 1, p=0.002; rater 2, p=0.018). For rater 1, the mean sigma difference between diffuse and circumscript tumors was 10.7 and 9.3 for rater 2. The mean overall sigma value was 13.3 for rater 1 and 18.7 for rater 2 (p=0.005). CONCLUSION Edge detection algorithms can be efficiently applied on MRI scans and are highly accurate in differentiating diffuse from circumscript gliomas. Objectification demands defining imaging criteria for diffuse and circumscript appearance of lower grade gliomas on MRI.