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Cerebral syphilitic gumma is a rare disease and can be misdiagnosed as a common brain tumor when only conventional imaging results are adopted. Differentiating between syphilitic gumma and tumors may be achieved by applying advanced magnetic resonance (MR) techniques, such as MR spectroscopy and MR perfusion. However, the MR perfusion characteristics of cerebral syphilitic gumma have not been reported yet. Here, we report a case of cerebral syphilitic gumma in a 52-year-old woman and discuss the imaging features of conventional MR, MR spectroscopy, and MR perfusion. The results suggest that the application of MR spectroscopy and MR perfusion could provide additional information that contributes to the diagnosis of cerebral syphilitic gumma. [ABSTRACT FROM AUTHOR]

Neurosyphilis, which is caused by Treponema pallidum , is a rare sexually transmitted disease involving the central nervous system (CNS). Among all the sub-categories, spinal syphilitic gumma is extremely rare. In previous literature, limited cases of spinal syphilitic gumma have been reported, most of which underwent surgery treatment. In this study, we reported a 46-year-old man, who presented with 5-day numbness of bilateral lower limbs, lower back pain, and irregular defecation. Magnetic resonance imaging (MRI) revealed a homogeneous peripheral enhancement and intramedullary nodule at the T7 level with extensive thoracic cord edema. Combining with laboratory examination results, the syphilitic gumma was considered. One month after the administration of penicillin G, the symptoms vanished. Six months later, MRI indicated no intramedullary nodule. [ABSTRACT FROM AUTHOR]

Potassium ion storage technology as a promising substitute for the well‐developed lithium ion storage technology is still at the infancy stage of development, and exploring suitable electrode materials is critical for its practical application. Here, the great feasibility of disordered, large interlayer spacing, and oxygen‐rich carbon nanosheets (CNSs) prepared by chemical vapor deposition for potassium ion storage applications is demonstrated. As an anode material, the CNSs exhibit outstanding rate capability as well as excellent cyclic stability. Taking advantage of this, a potassium ion hybrid capacitor (PIHC) is constructed by employing such CNSs as the battery‐type anode and activated carbon as the capacitor‐type cathode. The resulting device displays a high energy density of 149 Wh kg−1, an ultrahigh power output of 21 kW kg−1, as well as a long cycling life (80% capacity retention after 5000 cycles), which are all close to the state‐of‐the‐art values for PIHCs. This work promotes the development of high‐performance anode material for potassium ion storage devices, and the designed PIHC pushes the energy density and power density to a higher level. [ABSTRACT FROM AUTHOR]

Objective: To establish a prediction model of malignancy for solitary pulmonary nodules (SPNs) on the basis of imaging, clinical characteristics and tumor marker levels., Methods: Totally, 341 cases of SPNs were enrolled in this retrospective study, in which 70% were selected as the training group (n = 238) and the rest 30% as the verification group (n = 103). The imaging, clinical characteristics and tumor marker levels of patients with benign and malignant SPNs were compared. Influencing factors were identified using multivariate logistic regression analysis. The model was assessed by the area under the curve (AUC) of the receiver operating characteristic curve., Results: Differences were evident between patients with benign and malignant SPNs in age, gender, smoking history, carcinoembryonic antigen (CEA), neuron-specific enolase, nodule location, edge smoothing, spiculation, lobulation, vascular convergence sign, air bronchogram, ground-glass opacity, vacuole sign and calcification (all P < 0.05). Influencing factors for malignancy included age, gender, nodule location, spiculation, vacuole sign and CEA (all P < 0.05). The established model was as follows: Y = -5.368 + 0.055 × age + 1.012 × gender (female = 1, male = 0) + 1.302 × nodule location (right upper lobe = 1, others = 0) + 1.208 × spiculation (yes = 1, no = 0) + 2.164 × vacuole sign (yes = 1, no = 0) -0.054 × CEA. The AUC of the model with CEA was 0.818 (95% confidence interval, 0.763-0.865), with a sensitivity of 64.80% and a specificity of 84.96%, and the stability was better through internal verification., Conclusions: The prediction model established in our study exhibits better accuracy and internal stability in predicting the probability of malignancy for SPNs., (Copyright © 2020 The Author(s). Published by Wolters Kluwer Health, Inc.)