Cervical Spine Inhomogeneously Enhancing Lesion: Avoiding Confirmation Bias

Confirmation bias is the tendency to seek information and evidence in order to confirm a preexisting hypothesis while giving less importance and overlook an alternative solution. This report describes the case of a 52-year-old man with a long history of neck pain and bilateral upper limbs paresthesias with a cervical intracanal inhomogeneously enhancing lesion. Despite all the preoperative radiological findings, a spinal meningioma an anterior approach was performed. The mass ended up being a large migrated hernia with the involvement of two levels. Before suggesting treatment, especially surgery, physicians and practitioners need to evaluate all of the possible alternatives in order to optimize patient outcome

Tuber borchii fruit body: 2-dimensional profile and protein identification

The formation of the fruit body represents the final phase of the ectomycorrhizal fungus T. borchii life cycle. Very little is known concerning the molecular and biochemical processes involved in the fructification phase. 2-DE maps of unripe and ripe ascocarps revealed different protein expression levels and the comparison of the electropherograms led to the identification of specific proteins for each developmental phase. Associating micropreparative 2-DE to microchemical approaches, such as N-terminal sequencing and 2-D gel-electrophoresis mass-spectrometry, proteins playing pivotal roles in truffle physiology were identifie

3D-printed guides for cervical pedicle screw placement in primary spine tumor: Case report and technical description

INTRODUCTION: For spine surgeons, dealing with unstable cervical spine has been usually challenging, and this becomes more difficult when facing a primary craniovertebral junction tumor. Primary spine tumor surgery should always include column reconstruction in order to guarantee biomechanical stability of the spine, but surgeons should always be aware that instrumentations could create interferences with postoperative radiations. However, although carbon fiber instrumentations have started to be used in thoracolumbar oncology for few years, these options are still not available for cervical spine. In the reported case, the adopted strategy to obtain adequate column reconstruction was based on the idea of reducing the amount of titanium needed for posterior fixation and maximizing the distance between the radiation target and titanium rods. CASE REPORT AND AIM: We present the case of a 53-year-old woman harboring a craniovertebral junction chordoma. A short occipito-C3 construct was selected. Specifically, titanium cervical pedicle screws were placed by using a new technology consisting in patient-tailored and customized 3D-printed guides. The aim of this case report is to determine the feasibility and safety of 3D-printed guides for cervical pedicle screw (CPS) positioning, even in the case of cervical spine tumor. CONCLUSION: CPS could represent a good solution by providing strong biomechanical purchase and tailored 3D-printed guides could increase the safety and the accuracy of this challenging screw placement, even in oncological patients

Nine weeks of high-intensity indoor cycling training induced changes in the microbiota composition in non-athlete healthy male college students

Background: The gut microbiota constitutes a dynamic microbial system constantly challenged by environmental conditions, including physical exercise. Limited human studies suggest that exercise could play a beneficial role for gut health, increasing microbial diversity, even if the effects of exercise on gut microbial microorganisms depends on its intensity and duration. This study aimed to investigate the effects of nine weeks of high-intensity interval exercise on gut microbiota composition in healthy young adults. Methods: The gut microbiota composition of seventeen healthy male college students was analysed before and after nine weeks of high-intensity interval cycling training by 16S rRNA amplicon sequencing. PERMANOVA for repeated measures was used to test pre-post differences in the relative abundance of all taxonomic levels, and correlations between variations in microbial composition and physical and dietary features were also assessed. Results: Physical exercise induced changes in microbiota composition, at all taxonomic levels analysed (phyla: F [1, 32]=3.97, p=0.029; classes: F [1, 32]=3.39, p=0.033, orders: F [1, 32]=3.17, p=0.044, families: F [1, 32]=1.54, p=0.037, genera: F [1, 32]=1.46, p=0.015, species: F [1, 32]=1.38, p=0.007). Conversely, no differences were found between pre and post-training conditions for microbial community richness (Chao1: V=105, p=0.06) or diversity (Shannon index: V=62, p=0.52; Simpson index: V=59, p=0.43). Changes in the relative abundance of eighteen genera were correlated to changes of twenty environmental factors grouped in physical features, sport-related features, and dietary features. Conclusions: Nine weeks of high-intensity exercise induced modifications in gut microbiota composition in healthy male college students, shifting the gut microbial population towards a healthier microbiome with benefit to human health in general

Deep learning-based algorithm for postoperative glioblastoma MRI segmentation: a promising new tool for tumor burden assessment

Objective: Clinical and surgical decisions for glioblastoma patients depend on a tumor imaging-based evaluation. Artificial Intelligence (AI) can be applied to magnetic resonance imaging (MRI) assessment to support clinical practice, surgery planning and prognostic predictions. In a real-world context, the current obstacles for AI are low-quality imaging and postoperative reliability. The aim of this study is to train an automatic algorithm for glioblastoma segmentation on a clinical MRI dataset and to obtain reliable results both pre- and post-operatively. Methods: The dataset used for this study comprises 237 (71 preoperative and 166 postoperative) MRIs from 71 patients affected by a histologically confirmed Grade IV Glioma. The implemented U-Net architecture was trained by transfer learning to perform the segmentation task on postoperative MRIs. The training was carried out first on BraTS2021 dataset for preoperative segmentation. Performance is evaluated using DICE score (DS) and Hausdorff 95% (H95). Results: In preoperative scenario, overall DS is 91.09 (± 0.60) and H95 is 8.35 (± 1.12), considering tumor core, enhancing tumor and whole tumor (ET and edema). In postoperative context, overall DS is 72.31 (± 2.88) and H95 is 23.43 (± 7.24), considering resection cavity (RC), gross tumor volume (GTV) and whole tumor (WT). Remarkably, the RC segmentation obtained a mean DS of 63.52 (± 8.90) in postoperative MRIs. Conclusions: The performances achieved by the algorithm are consistent with previous literature for both pre-operative and post-operative glioblastoma's MRI evaluation. Through the proposed algorithm, it is possible to reduce the impact of low-quality images and missing sequences