Espersenguerra2740

Anticancer treatments, particularly chemotherapy, induce ovarian damage and loss of ovarian follicles. There are limited options for fertility restoration, one of which is pre-chemotherapy cryopreservation of ovarian tissue. Transplantation of frozen-thawed human ovarian tissue from cancer survivors has resulted in live-births. There is extensive follicular loss immediately after grafting, probably due to too slow graft revascularization. To avoid this problem, it is important to develop methods to improve ovarian tissue neovascularization. The study's purpose was to investigate if treatment of murine hosts with simvastatin or/and embedding human ovarian tissue within fibrin clots can improve human ovarian tissue grafting (simvastatin and fibrin clots promote vascularization). There was a significantly higher number of follicles in group A (ungrafted control) than in group B (untreated tissue). Group C (simvastatin-treated hosts) had the highest levels of follicle atresia. Group C had significantly more proliferating follicles (Ki67-stained) than groups B and E (simvastatin-treated hosts and tissue embedded within fibrin clots), group D (tissue embedded within fibrin clots) had significantly more proliferating follicles (Ki67-stained) than group B. On immunofluorescence study, only groups D and E showed vascular structures that expressed both human and murine markers (mouse-specific platelet endothelial cell adhesion molecule, PECAM, and human-specific von Willebrand factor, vWF). Peripheral human vWF expression was significantly higher in group E than group B. Diffuse human vWF expression was significantly higher in groups A and E than groups B and C. When grafts were not embedded in fibrin, there was a significant loss of human vWF expression compared to groups A and E. This protocol may be tested to improve ovarian implantation in cancer survivors.

Hepatitis B virus reactivation (HBVr) in patients with gastrointestinal stromal tumors (GISTs) have not been sufficiently characterized. This study aimed to review the possible mechanism of HBVr induced by imatinib and explore appropriate measures for patient management and monitoring.

The clinical data of GIST patients who experienced HBVr due to treatment with imatinib at Xiangya Hospital (Changsha, Hunan, China) were retrospectively analyzed. A literature review was also conducted.

Five cases were analyzed, including 3 cases in this study. The average age of the patients was 61.8 y, with male preponderance (4 of 5 vs. 1 of 5). These patients received imatinib as adjuvant treatment (n=4) or as neoadjuvant treatment (n=1). Primary tumors were mostly located in the stomach (n=4) or rectum (n=1). High (n=3) or intermediate (n=1) recurrence risk was categorized using the postoperative pathological results (n=4). Imatinib was then started at 400 (n=4) or 200 mg (n=1) daily. Patients first reported abnormalpt antiviral treatment and cessation of imatinib are also necessary.Delivering optimal cancer care to children, adolescents and adults with ASD has recently become a healthcare priority and represents a major challenge for all providers involved. In this review, and after consideration of the available evidence, we concisely deliver key information on this heterogenous group of neurodevelopmental disorders, as well as recommendations and concrete tools for the enhanced oncological care of this vulnerable population of patients.Intrahepatic cholangiocarcinoma (ICC) is a heterogeneous hepatobiliary tumor with poor prognosis, and it lacks reliable prognostic biomarkers and effective therapeutic targets. Long non-coding RNAs (lncRNAs) have been documented to be involved in the progression of various cancers. However, the role of lncRNAs in ICC remains largely unknown. In the present work, we used bioinformatics analysis to identify the differentially expressed lncRNAs in human ICC tissues, among which lncRNA-PAICC was found to be an independent prognostic marker in ICC. Moreover, lncRNA-PAICC promoted the proliferation and invasion of ICC cells. Mechanistically, lncRNA-PAICC acted as a competitive endogenous RNA (ceRNA) that directly sponged the tumor suppressive microRNAs miR-141-3p and miR-27a-3p. The competitive binding property was essential for lncRNA-PAICC to promote tumor growth and metastasis through activating the Hippo pathway. In summary, our results highlighted the important role of the lncRNA-PAICC-miR-141-3p/27a-3p-Yap1 axis in ICC, which offers a novel perspective on the molecular pathogenesis and may serve as a potential target for antimetastatic molecular therapies of ICC.Cerebral radiation necrosis (CRN) is one of the most prominent sequelae following radiation therapy for nasopharyngeal carcinoma (NPC), which might have devastating effects on patients' quality of life (QOL). Advances in histopathology and neuro-radiology have shed light on the management of CRN more comprehensively, yet effective therapeutic interventions are still lacking. CRN was once regarded as progressive and irreversible, however, in the past 20 years, with the application of intensity-modulated radiation therapy (IMRT), both the incidence and severity of CRN have declined. In addition, newly developed medical agents including bevacizumab-a humanized monoclonal antibody against vascular endothelial growth factor (VEGF), nerve growth factor (NGF), monosialotetrahexosylganglioside (GM1), etc., have shown great potency in successfully reversing radiation-induced CRN. As temporal lobes are most frequently compromised in NPC patients, this review will summarize the state-of-the-art progress regarding the incidence, pathophysiology, prevention, treatment, and prognosis of temporal lobe necrosis (TLN) after IMRT in NPC.

Clear cell meningioma (CCM) is a rare subtype of meningioma, accounting for approximately 0.2% of all meningiomas. The present study aimed to analyze the epidemiology and outcome of CCMs using the Surveillance, Epidemiology, and End Results (SEER) database.

Patients diagnosed with central nervous system CCM between 2004 and 2016 were identified from the SEER database. Descriptive analyses were performed to evaluate the distribution of patients and tumor-related characteristics. The survival analysis was performed using Kaplan-Meier curves. The Cox proportional hazards model was used for the univariate and multivariate analyses.

The age-adjusted incidence rate was 0.032 per 1,000,000 person-years. The median age was 52 years. Most of the CCMs were intracranial CCMs that were larger than 3cm. The overall cumulative survival rates at 1, 3, and 5 years were 97.6, 93.2, and 86.9%, respectively. The log-rank test and Cox proportional hazards regression analysis revealed that age at diagnosis and primary site of the tumor were independent prognostic factors.

CCM is an extremely rare entity with a favorable survival rate. CCMs usually affect patients during the fourth to fifth decades of life. Patients diagnosed at 21-60 years old and patients with spinal CCMs have a better prognosis.

CCM is an extremely rare entity with a favorable survival rate. CCMs usually affect patients during the fourth to fifth decades of life. Patients diagnosed at 21-60 years old and patients with spinal CCMs have a better prognosis.Survival analysis is important for guiding further treatment and improving lung cancer prognosis. this website It is a challenging task because of the poor distinguishability of features and the missing values in practice. A novel multi-task based neural network, SurvNet, is proposed in this paper. The proposed SurvNet model is trained in a multi-task learning framework to jointly learn across three related tasks input reconstruction, survival classification, and Cox regression. It uses an input reconstruction mechanism cooperating with incomplete-aware reconstruction loss for latent feature learning of incomplete data with missing values. Besides, the SurvNet model introduces a context gating mechanism to bridge the gap between survival classification and Cox regression. A new real-world dataset of 1,137 patients with IB-IIA stage non-small cell lung cancer is collected to evaluate the performance of the SurvNet model. The proposed SurvNet achieves a higher concordance index than the traditional Cox model and Cox-Net. The difference between high-risk and low-risk groups obtained by SurvNet is more significant than that of high-risk and low-risk groups obtained by the other models. Moreover, the SurvNet outperforms the other models even though the input data is randomly cropped and it achieves better generalization performance on the Surveillance, Epidemiology, and End Results Program (SEER) dataset.High computational cost associated with digital pathology image analysis approaches is a challenge towards their translation in routine pathology clinic. Here, we propose a computationally efficient framework (SuperHistopath), designed to map global context features reflecting the rich tumor morphological heterogeneity. SuperHistopath efficiently combines i) a segmentation approach using the linear iterative clustering (SLIC) superpixels algorithm applied directly on the whole-slide images at low resolution (5x magnification) to adhere to region boundaries and form homogeneous spatial units at tissue-level, followed by ii) classification of superpixels using a convolution neural network (CNN). To demonstrate how versatile SuperHistopath was in accomplishing histopathology tasks, we classified tumor tissue, stroma, necrosis, lymphocytes clusters, differentiating regions, fat, hemorrhage and normal tissue, in 127 melanomas, 23 triple-negative breast cancers, and 73 samples from transgenic mouse models of high-risk childhood neuroblastoma with high accuracy (98.8%, 93.1% and 98.3% respectively). Furthermore, SuperHistopath enabled discovery of significant differences in tumor phenotype of neuroblastoma mouse models emulating genomic variants of high-risk disease, and stratification of melanoma patients (high ratio of lymphocyte-to-tumor superpixels (p = 0.015) and low stroma-to-tumor ratio (p = 0.028) were associated with a favorable prognosis). Finally, SuperHistopath is efficient for annotation of ground-truth datasets (as there is no need of boundary delineation), training and application (~5 min for classifying a whole-slide image and as low as ~30 min for network training). These attributes make SuperHistopath particularly attractive for research in rich datasets and could also facilitate its adoption in the clinic to accelerate pathologist workflow with the quantification of phenotypes, predictive/prognosis markers.CKLF-like MARVEL transmembrane domain-containing 6 (CMTM6) reportedly stabilizes programmed death-ligand 1 (PD-L1) and enhances the efficacy of immunotherapy. However, correlations between CMTM6 expression and the immune microenvironment and its prognostic value remain unknown in a variety of tumors. CMTM6 expression data were obtained from The Cancer Genome Atlas (TCGA) for 33 cancer types classified into high and low expression subgroups according to the median CMTM6 expression value. Pan-cancer analysis of CMTM6 protein expression in 20 tumor types was performed using a cohort from the Human Protein Atlas (HPA). PD-L1 protein expression data were obtained from The Cancer Proteome Atlas (TCPA) for 32 cancer types. Frequencies of CMTM6 copy number alterations and mutations were analyzed using cBioPortal. MANTIS was employed to estimate microsatellite instability in the TCGA cohort. CIBERSORT and the ESTIMATE algorithm were applied to estimate the relative fractions of infiltrating immune cell types and immune scores, respectively.