Search

BackgroundAfter craniotomy, patients require rehabilitation efforts for the recovery process, and neurologists are mostly engaged for that (in the management of post-craniotomy complications). However, neurologists are not always available for care after neurosurgery during follow-up (situation of our institute). The objectives of the study were to compare the effects of two different types of care (nurse-led and neurologist-led) on various long-term outcomes in patients who have undergone craniotomy due to traumatic brain injuries.MethodsElectronic medical records of patients (aged ≥18 years) who underwent craniotomy for traumatic brain injuries and their caregivers were extracted and retrospectively reviewed. Patients received nurse-led care (NL cohort, n = 109) or neurologist-led care (GL cohort, n = 121) for 6 months after craniotomy.ResultsBefore the nurse-or neurologist-led care (BC), all patients had activities of daily living (ADL) ≤ 11, ≤ 50 quality of life (QoL), and 69% of patients had definitive anxiety, 87% of patients had definitive depression, and all caregivers had Zarit Burden interview scores ≥50. Nurse-led post-surgical care was associated with improved ADL and QoL, relieved anxiety and depression of patients, relieved the burden on caregivers, and the higher overall satisfaction of patients and their caregivers after 6-months of care (AC) as compared to their BC condition (p

HER2-positive breast cancer is a highly heterogeneous tumor, and about 30% of patients still suffer from recurrence and metastasis after trastuzumab targeted therapy. Predicting individual prognosis is of great significance for the further development of precise therapy. With the continuous development of computer technology, more and more attention has been paid to computer-aided diagnosis and prognosis prediction based on Hematoxylin and Eosin (H&E) pathological images, which are available for all breast cancer patients undergone surgical treatment. In this study, we first enrolled 127 HER2-positive breast cancer patients with known recurrence and metastasis status from Cancer Hospital of the Chinese Academy of Medical Sciences. We then proposed a novel multimodal deep learning method integrating whole slide H&E images (WSIs) and clinical information to accurately assess the risk of relapse and metastasis in patients with HER2-positive breast cancer. Specifically, we obtained the whole H&E staining images from the surgical specimens of breast cancer patients, and these images were adjusted to size 512 × 512 pixels. The deep convolutional neural network (CNN) was applied to these images to retrieve image features, which were combined with the clinical data. Based on the combined features. After that, a novel multimodal model was constructed for predicting the prognosis of each patient. The model achieved an area under curve (AUC) of 0.76 in the two-fold cross-validation (CV). To further evaluate the performance of our model, we downloaded the data of all 123 HER2-positive breast cancer patients with available H&E image and known recurrence and metastasis status in The Cancer Genome Atlas (TCGA), which was severed as an independent testing data. Despite the huge differences in race and experimental strategies, our model achieved an AUC of 0.72 in the TCGA samples. As a conclusion, H&E images, in conjunction with clinical information and advanced deep learning models, could be used to evaluate the risk of relapse and metastasis in patients with HER2-positive breast cancer.

The skills and strategies of effective communication are at the heart of literacy teaching and learning; engaging with digital technologies to communicate puts new demands on teachers and students. The communication tools of the 21st century require a rethinking of our 19th century educational approach to fully integrate digital tools into the classroom. We must help pre-service teachers learn how to leverage technology to build students’ communication skills across the curriculum. The authors describe two different Digital Strategy Backpacks that were integrated into a pre-service teacher education instructional technology class. The backpacks illustrate how learners apply communication skills and strategies with a range of technologies. The authors acknowledge that the Digital Strategy Backpacks are just a taste of this technique, however, we contend that they demonstrate how teachers and teacher educators can put communication goals at the front and center of teaching with technology.

OBJECTIVE To discuss the pathologic characteristics and the prognosis of neuroendocrine carcinoma of the bladder (NECB) in order to assist in making a precise diagnosis and to effectively treat the disease. METHODS Clinicopathologic features of the 6 cases with NECB were analyzed retrospectively. The personal data of the patients and the pathologic and immunohistochemical characteristics of the tumor were investigated. The follow-up of these patients was conducted over a time period ranging from 3 months to 9 years. RESULTS Transurethral resection of the bladder tumor was performed in all 6 patients. Based on the results of the pathologic examination, 4 of the cases were diagnosed as small cell neuroendocrine carcinoma and the other 2 were diagnosed as atypical carcinoid tumor. On immunohistochemical staining all tumors expressed neuroendocrine markers including neuronspecific enolase (CD56), synaptophysin (Syn) and chromogranin (CgA). In patients receiving partial cystectomy followed by postoperative chemotherapy, relapse was found in 4 of the 6 cases on follow up. CONCLUSION NECB is a rare entity and a tumor with high malignant potential and characteristic pathologic features. Hematuria is the cardinal symptom of NECB. Metastasis may occur at an early stage and the prognosis of the disease is poor. Final diagnosis of NECB depends on histopathologic examination and immunohistochemical assays. Surgical excision combined with radiotherapy and chemotherapy is considered an effective treatment.