The achievement of rapid hemostasis represents a long-term trend in hemostatic research. Specifically, composite materials are now the focus of attention, based on the given issues and required properties. In urology, different materials are used to achieve fast and effective hemostasis. Additionally, it is desirable to exert a positive influence on local tissue reaction. In this study, three nonwoven textiles prepared by a wet spinning method and based on a combination of hyaluronic acid with either oxidized cellulose or carboxymethyl cellulose, along with the addition of etamsylate, were introduced and assessed in vivo using the rat partial nephrectomy model. A significantly shorter time to hemostasis in seconds (p < 0.05), was attributed to the effect of the carboxymethyl cellulose material. The addition of etamsylate did not noticeably contribute to further hemostasis, but its application strengthened the structure and therefore significantly improved the effect on local changes, while also facilitating any manipulation by the surgeons. Specifically, the hyaluronic acid supported the tissue healing and regeneration, and ensured the favorable results of the histological analysis. Moreover, the prepared textiles proved their bioresorbability after a three-day period. In brief, the fabrics yielded favorable hemostatic activity, bioresorbability, non-irritability, and had a beneficial effect on the tissue repair.

Objective: Focal cortical dysplasia (FCD), hippocampal sclerosis (HS), nonspecific gliosis (NG), and normal tissue (NT) comprise the majority of histopathological results of surgically treated drug‐resistant epilepsy patients. Epileptic spikes, high‐frequency oscillations (HFOs), and connectivity measures are valuable biomarkers of epileptogenicity. The question remains whether they could also be utilized for preresective differentiation of the underlying brain pathology. This study explored spikes and HFOs together with functional connectivity in various epileptogenic pathologies.Methods: Interictal awake stereoelectroencephalographic recordings of 33 patients with focal drug‐resistant epilepsy with seizure‐free postoperative outcomes were analyzed (15 FCD, 8 HS, 6 NT, and 4 NG). Interictal spikes and HFOs were automatically identified in the channels contained in the overlap of seizure onset zone and resected tissue. Functional connectivity measures (relative entropy, linear correlation, cross‐correlation, and phase consistency) were computed for neighboring electrode pairs.Results: Statistically significant differences were found between the individual pathologies in HFO rates, spikes, and their characteristics, together with functional connectivity measures, with the highest values in the case of HS and NG/NT. A model to predict brain pathology based on all interictal measures achieved up to 84.0% prediction accuracy.Significance: The electrophysiological profile of the various epileptogenic lesions in epilepsy surgery patients was analyzed. Based on this profile, a predictive model was developed. This model offers excellent potential to identify the nature of the underlying lesion prior to resection. If validated, this model may be particularly valuable for counseling patients, as depending on the lesion type, different outcomes are achieved after epilepsy surgery.

Background: The aim of this retrospective study is to assess the incidence, localization, and potential predictors of rapid early progression (REP) prior to initiation of radiotherapy in newly diagnosed glioblastoma patients and to compare survival outcomes in cohorts with or without REP in relation to the treatment. Methods: We assessed a consecutive cohort of 155 patients with histologically confirmed irradiated glioblastoma from 1/2014 to 12/2017. A total of 90 patients with preoperative, postoperative, and planning MRI were analyzed. Results: Median age 59 years, 59% men, and 39 patients (43%) underwent gross total tumor resection. The Stupp regimen was indicated to 64 patients (71%); 26 patients (29%) underwent radiotherapy alone. REP on planning MRI performed shortly prior to radiotherapy was found in 46 (51%) patients, most often within the surgical cavity wall, and the main predictor for REP was non-radical surgery (p < 0.001). The presence of REP was confirmed as a strong negative prognostic factor; median overall survival (OS) in patients with REP was 10.7 vs. 18.7 months and 2-year survival was 15.6% vs. 37.7% (hazard ratio HR 0.53 for those without REP; p = 0.007). Interestingly, the REP occurrence effect on survival outcome was significantly different in younger patients (≤ 50 years) and older patients (> 50 years) for OS (p = 0.047) and non-significantly for PFS (p = 0.341). In younger patients, REP was a stronger negative prognostic factor, probably due to more aggressive behavior. Patients with REP who were indicated for the Stupp regimen had longer OS compared to radiotherapy alone (median OS 16.0 vs 7.5; HR = 0.5, p = 0.022; 2-year survival 22.3% vs. 5.6%). The interval between surgery and the initiation of radiotherapy were not prognostic in either the entire cohort or in patients with REP. Conclusion: Especially in the subgroup of patients without radical resection, one may recommend as early initiation of radiotherapy as possible. The phenomenon of REP should be recognized as an integral part of stratification factors in future prospective clinical trials enrolling patients before initiation of radiotherapy.

Glioblastoma (GBM) is regarded as an aggressive brain tumor that rarely develops extracranial metastases. Despite well-investigated molecular alterations in GBM, there is a limited understanding of these associated with the metastatic potential. We herein present a case report of a 43-year-old woman with frontal GBM with primitive neuronal component who underwent gross total resection followed by chemoradiation. Five months after surgery, the patient was diagnosed with an intraspinal GBM metastasis. Next-generation sequencing analysis of both the primary and metastatic GBM tissues was performed using the Illumina TruSight Tumor 170 assay. The number of single nucleotide variants observed in the metastatic sample was more than two times higher. Mutations in TP53, PTEN, and RB1 found in the primary and metastatic tissue samples indicated the mesenchymal molecular GBM subtype. Among others, there were two inactivating mutations (Arg1026Ile, Trp1831Ter) detected in the NF1 gene, two novel NOTCH3 variants of unknown significance predicted to be damaging (Pro1505Thr, Cys1099Tyr), one novel ARID1A variant of unknown significance (Arg1046Ser), and one gene fusion of unknown significance, EIF2B5-KIF5B, in the metastatic sample. Based on the literature evidence, the alterations of NF1, NOTCH3, and ARID1A could explain, at least in part, the acquired invasiveness and metastatic potential in this particular GBM case.

Purpose: The aim of this study is to design a method of myocardial T1 quantification in small laboratory animals and to investigate the effects of spatiotemporal regularization and the needed acquisition duration.Methods: We propose a compressed‐sensing approach to T1 quantification based on self‐gated inversion‐recovery radial two/three‐dimensional (2D/3D) golden‐angle stack‐of‐stars acquisition with image reconstruction performed using total‐variation spatiotemporal regularization. The method was tested on a phantom and on a healthy rat, as well as on rats in a small myocardium‐remodeling study.Results: The results showed a good match of the T1 estimates with the results obtained using the ground‐truth method on a phantom and with the literature values for rats myocardium. The proposed 2D and 3D methods showed significant differences between normal and remodeling myocardium groups for acquisition lengths down to approximately 5 and 15 min, respectively.Conclusions: A new 2D and 3D method for quantification of myocardial T1 in rats was proposed. We have shown the capability of both techniques to distinguish between normal and remodeling myocardial tissue. We have shown the effects of image‐reconstruction regularization weights and acquisition length on the T1 estimates.