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Manganese-based bimetallic oxides show a high theoretical specific capacity, making them a potential next-generation lithium-ion battery anode material. However, as with metal oxide anode materials, aggregation, volume expansion, and poor conductivity are the main obstacles. In this manuscript, flexible CoMn2O4/graphene/carbon nanotube films were successfully prepared through a facile filtration strategy and a subsequent thermal treatment process. When used as anodes for lithium batteries, these films can be pressed onto nickel foam without other conductive additives and binders, which simplifies the manufacturing process. When used as an anode in the lithium-ion battery, CoMn2O4/GR/CNT film exhibits a high discharge capacity of 881 mAh g−1 after 55 cycles. This value is ~2 times higher than the discharge capacity of CoMn2O4. The three-dimensional GR/CNT carrier effectively dispersed CoMn2O4, preventing its aggregation and alleviating the problem of volume expansion. [ABSTRACT FROM AUTHOR]

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Infantile hemangioma (IH) is the most common benign tumor in infancy. Propranolol, a nonselective β‐adrenergic receptor blocker, is now the first‐line therapy for IH. Recently, low sensitivity to propranolol therapy has become one major reason for the failure of IH treatment. However, the exact underlying mechanisms are yet to be fully elucidated. Here, we reported that pyruvate kinase isoform M2 (PKM2), an essential glycolytic enzyme, played a critical role in regulating the progression of IH and the therapeutic resistance of propranolol treatment. Shikonin reversed the propranolol resistance in hemangioma‐derived endothelial cells and in hemangioma animal models. Moreover, shikonin combined with propranolol could induce excessive reactive oxygen species (ROS) accumulation and lead to autophagic dysfunction, which is essential for the enhanced therapeutic sensitivity of propranolol treatment. Taken together, our results indicated that PKM2 has a significant role in hemangiomas progression and therapeutic resistance; it could be a safe and effective therapeutic strategy for those hemangiomas with poor propranolol sensitivity combined with shikonin. [ABSTRACT FROM AUTHOR]

Background: No study has evaluated the impact of regimen on recurrence, metastasis and survival in patients with adenoid cystic carcinoma (ACC). The present study aimed to compare the efficacy of radioactive seed implantation and other regimens in treating ACC, so as to investigate the clinical applicability of radioactive seed implantation and determine the indications for this regimen. Methods: A total of 188 patients with ACC in oromaxillofacial region were allocated to four groups according to the treatment regimen: group 1 was treated with a combination of surgery and 125I seed therapy, group 2 with a combination of surgery and external radiotherapy, group 3 with surgery, whereas group 4 was untreated. The Kaplan–Meier method was used to assess the survival rates, and the Cox regression analyses were used to identify the associated prognostic factors. Results: The overall survival rates of 188 patients and groups 1, 2, 3 and 4 were 85.7%, 75%, 68.2% and 37.5%, respectively. Cox regression analysis revealed that age, T stage, N stage and regimen were independent prognostic factors of survival. Amongst patients with primary ACC, the efficacy of radioactive seed implantation was higher in those with perineural invasion than in those without. Conclusion: Patient age, T stage, N stage and regimen are independent prognostic factors of survival in patients with ACC. Patients treated with surgery combined with postoperative 125I seed radiotherapy have a higher overall survival rate, and those with perineural invasion are more suitable for radioactive seed implantation therapy. [ABSTRACT FROM AUTHOR]

Summary Limited by spatial resolution and visual contrast, bone scintigraphy interpretation is susceptible to subjective factors, which considerably affects the accuracy and repeatability of lesion detection and anatomical localization. In this work, we design and implement an end-to-end multi-task deep learning model to perform automatic lesion detection and anatomical localization in whole-body bone scintigraphy. A total of 617 whole-body bone scintigraphy cases including anterior and posterior views were retrospectively analyzed. The proposed semi-supervised model consists of two task flows. The first one, the lesion segmentation flow, received image patches and was trained in a supervised way. The other one, skeleton segmentation flow, was trained on as few as five labeled images in conjunction with the multi-atlas approach, in a semi-supervised way. The two flows joint in their encoder layers so each flow can capture more generalized distribution of the sample space and extract more abstract deep features. The experimental results show that the architecture achieved the highest precision in the finest bone segmentation task in both anterior and posterior images of whole-body scintigraphy. Such an end-to-end approach with very few manual annotation requirement would be suitable for algorithm deployment. Moreover, the proposed approach reliably balances unsupervised labels construction and supervised learning, providing useful insight for weakly labeled image analysis. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]