AI-assisted intent-based traffic grooming in a dynamically shared 5g optical fronthaul network.

The extremely high number of services with large bandwidth requirements and the increasingly dynamic traffic patterns of cell sites pose major challenges to optical fronthaul networks, rendering them incapable of coping with the extensive, uneven, and real-time traffic that will be generated in the future. In this paper, we first present the design of an adaptive graph convolutional network with gated recurrent unit (AGCN-GRU) network to learn the temporal and spatial dependencies of traffic patterns of cell sites to provide accurate traffic predictions, in which the AGCN model can capture potential spatial relations according to the similarity of network traffic patterns in different areas. Then, we innovatively consider how to deal with the unpredicted burst traffic and propose an AI-assisted intent-based traffic grooming scheme to realise automatic and intelligent cell sites clustering and traffic grooming. Finally, a software-defined testbed for 5G optical fronthaul network was established, on which the proposed schemes were deployed and evaluated by considering traffic datasets of existing optical networks. The experimental results showed that the proposed scheme can optimize network resource allocation, increase the average efficient resource utilization and reduce the average delay and the rejection ratio.

Cause-aware failure detection using an interpretable XGBoost for optical networks.

Failure detection is an important part of failure management, and network operators encounter serious consequences when operating under failure conditions. Machine learning (ML) is widely applied in the failure management of optical networks, where neural networks (NNs) have particularly attracted considerable attention and become the most extensively applied algorithm among all MLs. However, the black-box nature of NN makes it difficult to interpret or analyze why and how NNs work during execution. In this paper, we propose a cause-aware failure detection scheme for optical transport network (OTN) boards, adopting the interpretable extreme gradient boosting (XGBoost) algorithm. According to the feature importance ranking by XGBoost, the high-relevance features with the equipment failure are found. Then, SHapley Additive exPlanations (SHAP) is applied to solve the inconsistency of feature attribution under three common global feature importance measurement parameters of XGBoost, and can obtain a consistent feature attribution by calculating the contribution (SHAP value) of each input feature to detection result of XGBoost. Based on the feature importance ranking of SHAP values, the features most related to two types of OTN board failures are confirmed, enabling the identification of failure causes. Moreover, we evaluate the failure detection performance for two types of OTN boards, in which the practical data are balanced and unbalanced respectively. Experimental results show that the F1 score of the two types of OTN boards based on the proposed scheme is higher than 98%, and the most relevant features of the two types of board failures are confirmed based on SHAP value, which are the average and maximum values of the environment temperature, respectively.

In vivo activation of pH-responsive oxidase-like graphitic nanozymes for selective killing of Helicobacter pylori.

Helicobacter pylori infection is a major etiological factor in gastric diseases. However, clinical antibiotic therapy for H. pylori is limited by continuously decreased therapeutic efficacy and side effects to symbiotic bacteria. Herein, we develop an in vivo activatable pH-responsive graphitic nanozyme, PtCo@Graphene (PtCo@G), for selective treatment of H. pylori. Such nanozymes can resist gastric acid corrosion, exhibit oxidase-like activity to stably generate reactive oxygen species only in acidic gastric milieu and demonstrate superior selective bactericidal property. C18-PEGn-Benzeneboronic acid molecules are modified on PtCo@G, improving its targeting capability. Under acidic gastric pH, graphitic nanozymes show notable bactericidal activity toward H. pylori, while no bacterial killing is observed under intestinal conditions. In mouse model, high antibacterial capability toward H. pylori and negligible side effects toward normal tissues and symbiotic bacteria are achieved. Graphitic nanozyme displays the desired enzyme-like activities at corresponding physiological sites and may address critical issues in clinical treatment of H. pylori infections.

Oncogenic and drug-sensitive RET mutations in human epithelial ovarian cancer.

BACKGROUND: Epithelial ovarian cancer (EOC) is a highly lethal malignancy. Improvement in genetic characterization of EOC patients is required to propose new potential targets, since surgical resection coupled to chemotherapy, presents several limits such as cancer recurrence and drug resistance. Targeted therapies have more efficacy and less toxicity than standard treatments. One of the most relevant cancer-specific actionable targets are protein tyrosine kinases (PTKs) whose role in EOC need to be better investigated. METHODS: EOC genomic datasets are retrieved and analyzed. The biological and clinical significance of RET genomic aberrations in ovarian cancer context are investigated by a series of in vitro and in vivo experiments. RESULTS: Epithelial ovarian cancer sequencing projects identify recurrent genomic RET missense mutations in 1.98% of patients, ranking as the top-five hit among the 100 receptor tyrosine kinases-encoding genes. RET mutants R693H and A750T show oncogenic transformation properties in NIH3T3 cells. Introduction of the RET mutants into human EOC cells increases RET signaling, cell viability, anchorage-independent cell growth and tumor xenograft growth in nude mice, demonstrating that they are activating mutations. RET mutants significantly enhance the activation of RET and its downstream MAPK and AKT signaling pathway in ovarian cancer cells. Vandetanib, a clinical approved RET inhibitor, inhibits the cell viability and decreases the activation of RET-MAPK signaling pathways in EOC cells expressing oncogenic RET mutants. CONCLUSIONS: The discovery of RET pathogenic variants in the EOC patients, suggests a previously underestimated role for RET in EOC tumorigenesis. The identification of the gain-of-function RET mutations in EOC highlights the potential use of RET in targeted therapy to treat ovarian cancer patients.

Stable gold graphitic nanocapsule doped hydrogels for efficient photothermal antibacterial applications.

Herein, we have fabricated gold nanorod graphitic nanocapsule (AuNR@G) doped poly(vinyl alcohol) (PVA)/chitosan (CS) hydrogels, which possessed highly efficient and stable photothermal antibacterial properties for both Gram-negative E. coli and Gram-positive S. aureus under the irradiation of a near-infrared laser.

New developments in molecular targeted therapy of ovarian cancer.

Ovarian cancer remains the most mortal gynecological cancer in the world. The standard treatment for ovarian cancer remains cytoreductive surgery followed by platinum-based chemotherapy. Although most patients are platinum-sensitive initially, the majority of them will develop platinum resistance after multiple relapses, and platinum-resistant patients have a low response to the second-line chemotherapy. Besides, ovarian cancer is considered to be a highly heterogeneous disease at the molecular level. Molecular targeted therapy is expected to be a more effective and less toxic therapeutic strategy for ovarian cancer. PARP (poly-ADP-ribose polymerase) inhibitors and anti-VEGF monoclonal antibodies are two types of approved and most effective targeted drugs for ovarian cancer at present. Other potential therapeutic targets include folate receptor α, RAS/RAF/MER pathway, PI3K/AKT pathway, and immune checkpoints. Herein, we review the related clinical trials assessing the efficacy and safety of promising targets in ovarian cancer, discuss the main challenges facing targeted therapy, and propose possible solutions to optimize the treatment effects. With the advance of next-generation sequencing technology and molecular biology techniques, we are able to recognize more targetable molecular alterations in a larger group of ovarian cancer patients. Targeting these molecular abnormalities will bring us closer to the goal of personalized therapy and improve prognosis for patients with ovarian cancer.

Endometriosis does not confer improved prognosis in ovarian clear cell carcinoma: a retrospective study at a single institute.

BACKGROUND: Considered as the precursor lesion of a subset of ovarian clear cell carcinoma (OCCC), the prognostic role of endometriosis in OCCC patients remains controversial. This study aimed to investigate the prognostic role of coexisting endometriosis in the survival of patients with OCCC, and also sought to identify other prognostic factors. RESULTS: A total of 125 patients were diagnosed with OCCC during the study period. Of these, 55 (44.0%) patients had coexisting endometriosis. Patients with endometriosis were younger (p = 0.030), had smaller tumor diameter (p = 0.005) and lower preoperative CA125 levels (p = 0.005). More patients with endometriosis had International Federation of Gynecology and Obstetrics (FIGO) stage I disease (83.6% vs. 51.4%, p = 0.000) and exhibited sensitivity to platinum-based regimen (89.6% vs. 66.7%, p = 0.003). Univariate and multivariate analysis revealed that coexisting endometriosis was not a predictor of 5-year overall survival (OS) or progression-free survival (PFS) of OCCC patients. For OS, chemosensitivity was the only useful prognostic factor (Hazards ratio (HR) 109.33, 95% Confidence Interval (CI) 23.46-511.51; p = 0.000). For PFS, the useful prognostic factors were ascites (HR 2.78, 95% CI 1.21-6.47; p = 0.016), FIGO stage (HR 1.61, 95% CI 1.04-2.49; p = 0.033), and chemosensitivity (HR 101.60, 95% CI 29.45-350.49; p = 0.000). Moreover, higher FIGO stage was the only risk factor for resistance to platinum-based chemotherapy (Exp (B) = 0.292, 95% CI 0.123-0.693; p = 0.005). CONCLUSIONS: In this study, coexisting endometriosis was not a prognostic factor for the survival of OCCC patients. The most important predictor of both 5-year OS and PFS was chemosensitivity to platinum-based regimen, which decreased significantly with increase in FIGO stage.

Clear cell carcinoma of the ovary: Clinicopathologic features and outcomes in a Chinese cohort.

This retrospective analysis aimed to clarify the clinical and pathologic features of ovarian clear cell carcinoma (OCCC), and to determine the factors predictive of survival.Data waereextracted from OCCC patients who underwent primary surgery followed by adjuvant chemotherapy in Obstetrics & Gynecology Hospital of Fudan University between January2007 and December 2014. Kaplan-Meier survival estimates and Cox proportional hazards model were used for survival analyses.Of 130 patients (mean age = 56.2 years), 66.2% had stage I disease when the 5-year overall survival and 5-year disease-free survival were 89.2% and 88.1%, respectively. Patients frequently presented with large pelvic mass (>10 cm) and mild-to-moderate elevation of serological CA125 (≤200U/ mL). 60.7% of the cases at stage III/IV exhibited resistance to platinum-based chemotherapy; 37.69% of the tumors arose from endometriosis. On multivariate analysis, stage and chemoresistance were independent prognostic factors predictive for poorer survival. Survival at stage IC1 (surgical rupture) was comparable to that at stage IA (capsule intact), whereas survival at stage IC2/IC3 (rupture before surgery) was significantly worse than that at stage IA.OCCC shows distinct features compared to other epithelial ovarian cancers. FIGO stage and response to chemotherapy affect prognosis independently. Arising from endometriosis is not associated with better survival. Preoperative rupture rather than intraoperative rupture confers an adverse prognosis in otherwise stage IA disease.