Citations

Proton MRS (1H MRS) provides noninvasive, quantitative metabolite profiles of tissue and has been shown to aid the clinical management of several brain diseases. Although most modern clinical MR scanners support MRS capabilities, routine use is largely restricted to specialized centers with good access to MR research support. Widespread adoption has been slow for several reasons, and technical challenges toward obtaining reliable good‐quality results have been identified as a contributing factor. Considerable progress has been made by the research community to address many of these challenges, and in this paper a consensus is presented on deficiencies in widely available MRS methodology and validated improvements that are currently in routine use at several clinical research institutions. In particular, the localization error for the PRESS localization sequence was found to be unacceptably high at 3 T, and use of the semi‐adiabatic localization by adiabatic selective refocusing sequence is a recommended solution. Incorporation of simulated metabolite basis sets into analysis routines is recommended for reliably capturing the full spectral detail available from short TE acquisitions. In addition, the importance of achieving a highly homogenous static magnetic field (B0) in the acquisition region is emphasized, and the limitations of current methods and hardware are discussed. Most recommendations require only software improvements, greatly enhancing the capabilities of clinical MRS on existing hardware. Implementation of these recommendations should strengthen current clinical applications and advance progress toward developing and validating new MRS biomarkers for clinical use.

Background. Systemic inflammation in colorectal cancer (CRC) may be reflected by neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and mean platelet volume (MPV). This study was designed to investigate the efficiency of preoperative NLR, PLR, and MVP as a tool for the assessment of tumor characteristics in newly diagnosed patients with CRC. Patients and Methods. For 300 patients and 300 healthy volunteers, complete blood counts with automated differential counts were performed. The NLR was calculated by dividing the absolute neutrophil count by the absolute lymphocyte count; PLR was calculated by dividing the absolute platelet count by the absolute lymphocyte count. The diagnostic performance of NLR, PLR, and MVP was estimated by ROC curve. Results. ROC curve analysis showed high diagnostic efficacy of NLR and PLR in CRC patients with cut-off values of 2.15 (AUC=0.790, 95% CI 0.736-0.884, Se=74.1%, and Sp=73%) and 123 (AUC=0.846, 95% CI 0.801-0.891, Se=73.5%, and Sp=80%) compared to healthy controls, respectively. The diagnostic efficacy of three combined markers was superior compared with individual markers (AUC=0.904, 95% CI 0.812-0.989, Se=96%, and Sp=70%). Conclusion. NRL, PLR, and MPV may be useful markers in diagnostic and early recognition of different stages of CRC; additionally combined all together have stronger diagnostic efficacy.

ABSTRACT The last decade has seen a sharp increase in the number of scientific publications describing physiological and pathological functions of extracellular vesicles (EVs), a collective term covering various subtypes of cell‐released, membranous structures, called exosomes, microvesicles, microparticles, ectosomes, oncosomes, apoptotic bodies, and many other names. However, specific issues arise when working with these entities, whose size and amount often make them difficult to obtain as relatively pure preparations, and to characterize properly. The International Society for Extracellular Vesicles (ISEV) proposed Minimal Information for Studies of Extracellular Vesicles (“MISEV”) guidelines for the field in 2014. We now update these “MISEV2014” guidelines based on evolution of the collective knowledge in the last four years. An important point to consider is that ascribing a specific function to EVs in general, or to subtypes of EVs, requires reporting of specific information beyond mere description of function in a crude, potentially contaminated, and heterogeneous preparation. For example, claims that exosomes are endowed with exquisite and specific activities remain difficult to support experimentally, given our still limited knowledge of their specific molecular machineries of biogenesis and release, as compared with other biophysically similar EVs. The MISEV2018 guidelines include tables and outlines of suggested protocols and steps to follow to document specific EV‐associated functional activities. Finally, a checklist is provided with summaries of key points.

Cavernomas make up approximately 8%–15% of all intracranial vascular malformations, and the most common presenting symptom is seizures. Complete resection of the cavernoma and removal of the surrounding gliotic core presents a cure but poses a challenge if an eloquent brain is involved or with incomplete resection of the epileptogenic foci. The authors present the case of a 53-year-old man with intractable seizures from a left posterior temporal lobe cavernoma who underwent an awake craniotomy with intraoperative seizure monitoring via electrocorticography. The video can be found here: https://youtu.be/vxaikozg2g4 .

OBJECTIVELatent autoimmune diabetes in adults (LADA) shares clinical features with both type 1 and type 2 diabetes; however, there is ongoing debate regarding the precise definition of LADA. Understanding its genetic basis is one potential strategy to gain insight into appropriate classification of this diabetes subtype.RESEARCH DESIGN AND METHODSWe performed the first genome-wide association study of LADA in case subjects of European ancestry versus population control subjects (n = 2,634 vs. 5,947) and compared against both case subjects with type 1 diabetes (n = 2,454 vs. 968) and type 2 diabetes (n = 2,779 vs. 10,396).RESULTSThe leading genetic signals were principally shared with type 1 diabetes, although we observed positive genetic correlations genome-wide with both type 1 and type 2 diabetes. Additionally, we observed a novel independent signal at the known type 1 diabetes locus harboring PFKFB3, encoding a regulator of glycolysis and insulin signaling in type 2 diabetes and inflammation and autophagy in autoimmune disease, as well as an attenuation of key type 1–associated HLA haplotype frequencies in LADA, suggesting that these are factors that distinguish childhood-onset type 1 diabetes from adult autoimmune diabetes.CONCLUSIONSOur results support the need for further investigations of the genetic factors that distinguish forms of autoimmune diabetes as well as more precise classification strategies.