Cassiosomes are stinging-cell structures in the mucus of the upside-down jellyfish Cassiopea xamachana

This work is licensed under a Creative Commons Attribution 4.0 International License.Snorkelers in mangrove forest waters inhabited by the upside-down jellyfish Cassiopea xamachana report discomfort due to a sensation known as stinging water, the cause of which is unknown. Using a combination of histology, microscopy, microfluidics, videography, molecular biology, and mass spectrometry-based proteomics, we describe C. xamachana stinging-cell structures that we term cassiosomes. These structures are released within C. xamachana mucus and are capable of killing prey. Cassiosomes consist of an outer epithelial layer mainly composed of nematocytes surrounding a core filled by endosymbiotic dinoflagellates hosted within amoebocytes and presumptive mesoglea. Furthermore, we report cassiosome structures in four additional jellyfish species in the same taxonomic group as C. xamachana (Class Scyphozoa; Order Rhizostomeae), categorized as either motile (ciliated) or nonmotile types. This inaugural study provides a qualitative assessment of the stinging contents of C. xamachana mucus and implicates mucus containing cassiosomes and free intact nematocytes as the cause of stinging water

Management of Acute Traumatic Central Cord Syndrome: A Narrative Review.

Study Design Narrative review. Objectives To provide an updated overview of the management of acute traumatic central cord syndrome (ATCCS). Methods A comprehensive narrative review of the literature was done to identify evidence-based treatment strategies for patients diagnosed with ATCCS. Results ATCCS is the most commonly encountered subtype of incomplete spinal cord injury and is characterized by worse sensory and motor function in the upper extremities compared with the lower extremities. It is most commonly seen in the setting of trauma such as motor vehicles or falls in elderly patients. The operative management of this injury has been historically variable as it can be seen in the setting of mechanical instability or preexisting cervical stenosis alone. While each patient should be evaluated on an individual basis, based on the current literature, the authors' preferred treatment is to perform early decompression and stabilization in patients that have any instability or significant neurologic deficit. Surgical intervention, in the appropriate patient, is associated with an earlier improvement in neurologic status, shorter hospital stay, and shorter intensive care unit stay. Conclusions While there is limited evidence regarding management of ATCCS, in the presence of mechanical instability or ongoing cord compression, surgical management is the treatment of choice. Further research needs to be conducted regarding treatment strategies and patient outcomes

CAR-T cell. the long and winding road to solid tumors

Adoptive cell therapy of solid tumors with reprogrammed T cells can be considered the "next generation" of cancer hallmarks. CAR-T cells fail to be as effective as in liquid tumors for the inability to reach and survive in the microenvironment surrounding the neoplastic foci. The intricate net of cross-interactions occurring between tumor components, stromal and immune cells leads to an ineffective anergic status favoring the evasion from the host's defenses. Our goal is hereby to trace the road imposed by solid tumors to CAR-T cells, highlighting pitfalls and strategies to be developed and refined to possibly overcome these hurdles

A Delphi study and ranking exercise to support commissioning services:Future delivery of Thrombectomy services in England

Background: Intra-arterial thrombectomy is the gold standard treatment for large artery occlusive stroke. However, the evidence of its benefits is almost entirely based on trials delivered by experienced neurointerventionists working in established teams in neuroscience centres. Those responsible for the design and prospective reconfiguration of services need access to a comprehensive and complementary array of information on which to base their decisions. This will help to ensure the demonstrated effects from trials may be realised in practice and account for regional/local variations in resources and skill-sets. One approach to elucidate the implementation preferences and considerations of key experts is a Delphi survey. In order to support commissioning decisions, we aimed to using an electronic Delphi survey to establish consensus on the options for future organisation of thrombectomy services among physicians with clinical experience in managing large artery occlusive stroke. Methods: A Delphi survey was developed with 12 options for future organisation of thrombectomy services in England. A purposive sampling strategy established an expert panel of stroke physicians from the British Association of Stroke Physicians (BASP) Clinical Standards and/or Executive Membership that deliver 24/7 intravenous thrombolysis. Options with aggregate scores falling within the lowest quartile were removed from the subsequent Delphi round. Options reaching consensus following the two Delphi rounds were then ranked in a final exercise by both the wider BASP membership and the British Society of Neuroradiologists (BSNR). Results: Eleven stroke physicians from BASP completed the initial two Delphi rounds. Three options achieved consensus, with subsequently wider BASP (97%, n=43) and BSNR members (86%, n=21) assigning the highest approval rankings in the final exercise for transferring large artery occlusive stroke patients to nearest neuroscience centre for thrombectomy based on local CT/CT Angiography. Conclusions: The initial Delphi rounds ensured optimal reduction of options by an expert panel of stroke physicians, while subsequent ranking exercises allowed remaining options to be ranked by a wider group of experts within stroke to reach consensus. The preferred implementation option for thrombectomy is conveying suspected stroke patients for CT/CT Angiography and secondary transfer of large artery occlusive stroke patients to the nearest neuroscience centre

DNA methylation profiling to predict recurrence risk in meningioma: development and validation of a nomogram to optimize clinical management

Abstract Background Variability in standard-of-care classifications precludes accurate predictions of early tumor recurrence for individual patients with meningioma, limiting the appropriate selection of patients who would benefit from adjuvant radiotherapy to delay recurrence. We aimed to develop an individualized prediction model of early recurrence risk combining clinical and molecular factors in meningioma. Methods DNA methylation profiles of clinically annotated tumor samples across multiple institutions were used to develop a methylome model of 5-year recurrence-free survival (RFS). Subsequently, a 5-year meningioma recurrence score was generated using a nomogram that integrated the methylome model with established prognostic clinical factors. Performance of both models was evaluated and compared with standard-of-care models using multiple independent cohorts. Results The methylome-based predictor of 5-year RFS performed favorably compared with a grade-based predictor when tested using the 3 validation cohorts (ΔAUC = 0.10, 95% CI: 0.03–0.018) and was independently associated with RFS after adjusting for histopathologic grade, extent of resection, and burden of copy number alterations (hazard ratio 3.6, 95% CI: 1.8–7.2, P &lt; 0.001). A nomogram combining the methylome predictor with clinical factors demonstrated greater discrimination than a nomogram using clinical factors alone in 2 independent validation cohorts (ΔAUC = 0.25, 95% CI: 0.22–0.27) and resulted in 2 groups with distinct recurrence patterns (hazard ratio 7.7, 95% CI: 5.3–11.1, P &lt; 0.001) with clinical implications. Conclusions The models developed and validated in this study provide important prognostic information not captured by previously established clinical and molecular factors which could be used to individualize decisions regarding postoperative therapeutic interventions, in particular whether to treat patients with adjuvant radiotherapy versus observation alone. </jats:sec

Use of Machine Learning and Artificial Intelligence to Drive Personalized Medicine Approaches for Spine Care

Personalized medicine is a new paradigm of healthcare in which interventions are based on individual patient characteristics rather than on “one-size-fits-all” guidelines. As epidemiological datasets continue to burgeon in size and complexity, powerful methods such as statistical machine learning and artificial intelligence (AI) become necessary to interpret and develop prognostic models from underlying data. Through such analysis, machine learning can be used to facilitate personalized medicine via its precise predictions. Additionally, other AI tools, such as natural language processing and computer vision, can play an instrumental part in personalizing the care provided to patients with spine disease. In the present report, we discuss the current strides made in incorporating AI into research on spine disease, especially traumatic spinal cord injury and degenerative spine disease. We describe studies using AI to build accurate prognostic models, extract important information from medical reports via natural language processing, and evaluate functional status in a granular manner using computer vision. Through a case illustration, we have demonstrated how these breakthroughs can facilitate an increased role for more personalized medicine and, thus, change the landscape of spine care

Surgical Outcomes Following Laminectomy With Fusion Versus Laminectomy Alone in Patients With Degenerative Cervical Myelopathy

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