NFV Platforms: Taxonomy, Design Choices and Future Challenges

Due to the intrinsically inefficient service provisioning in traditional networks, Network Function Virtualization (NFV) keeps gaining attention from both industry and academia. By replacing the purpose-built, expensive, proprietary network equipment with software network functions consolidated on commodity hardware, NFV envisions a shift towards a more agile and open service provisioning paradigm. During the last few years, a large number of NFV platforms have been implemented in production environments that typically face critical challenges, including the development, deployment, and management of Virtual Network Functions (VNFs). Nonetheless, just like any complex system, such platforms commonly consist of abounding software and hardware components and usually incorporate disparate design choices based on distinct motivations or use cases. This broad collection of convoluted alternatives makes it extremely arduous for network operators to make proper choices. Although numerous efforts have been devoted to investigating different aspects of NFV, none of them specifically focused on NFV platforms or attempted to explore their design space. In this paper, we present a comprehensive survey on the NFV platform design. Our study solely targets existing NFV platform implementations. We begin with a top-down architectural view of the standard reference NFV platform and present our taxonomy of existing NFV platforms based on what features they provide in terms of a typical network function life cycle. Then we thoroughly explore the design space and elaborate on the implementation choices each platform opts for. We also envision future challenges for NFV platform design in the incoming 5G era. We believe that our study gives a detailed guideline for network operators or service providers to choose the most appropriate NFV platform based on their respective requirements. Our work also provides guidelines for implementing new NFV platforms

Interpreting AI for Networking: Where We Are and Where We Are Going

In recent years, artificial intelligence (AI) techniques have been increasingly adopted to tackle networking problems. Although AI algorithms can deliver high-quality solutions, most of them are inherently intricate and erratic for human cognition. This lack of interpretability tremendously hinders the commercial success of AI-based solutions in practice. To cope with this challenge, networking researchers are starting to explore explainable AI (XAI) techniques to make AI models interpretable, manageable, and trustworthy. In this article, we overview the application of AI in networking and discuss the necessity for interpretability. Next, we review the current research on interpreting AI-based networking solutions and systems. At last, we envision future challenges and directions. The ultimate goal of this article is to present a general guideline for AI and networking practitioners and motivate the continuous advancement of AI-based solutions in modern communication networks

Long Noncoding RNA EGFR-AS1 Promotes Cell Proliferation by Increasing EGFR mRNA Stability in Gastric Cancer

Background/Aims: LncRNA EGFR-AS1 is an antisense transcript of EGFR, which plays a key role in gastric cancer progression. This study was aimed to explore the effects of lncRNA EGFR-AS1 on GC and the underling mechanisms. Methods: The silencing of EGFR-AS1 expression was performed by using EGFR-AS1 shRNA lentivirus in MGC803 and SGC-7901 GC cell. The levels of lncRNA EGFR-AS1 and EGFR were detected by qPCR and western blot. Cell proliferation was assessed by CCK-8, EdU, and colony formation assays. The EGFR mRNA stability was explored by using RNA synthesis inhibitor α-amanitin. Results: In our study, EGFR-AS1 significantly up-regulated in GC tissues and correlated with tumor size. And the expression of EGFR-AS1 positively correlated with EGFR in tissues. Moreover, knock-down of EGFR-AS1 inhibited the proliferation of GC cells via suppressing EGFR-dependent PI3K/AKT pathway in vitro and in vivo. Mechanismly, depletion of EGFR-AS1 was found to decrease EGFR expression by reduction of EGFR mRNA stability. Conclusion: Our findings suggested that EGFR-AS1 might have an oncogenic effect on GC and serve as a potential target of GC

Clinical Diagnosis of Gastric Cancer by High-Sensitivity THz Fiber-Based Fast-Scanning Near-Field Imaging

The distinguishable absorption contrast among healthy gastric tissues, carcinoma in situ and cancer tissues in the THz frequency range is one of the keys to realizing gastric cancer diagnosis by THz imaging. Based on microwave devices and a sub-wavelength fiber, we developed a fast-scanning THz imaging system combined with the principle of surface plasmon resonance enhancement. This imaging system has a near-field λ/17 spatial resolution and imaging S/N ratio as high as 108:1, and the image results are directly displayed within 1 min. We also successfully demonstrated the image diagnostic capability on sliced tissues from eight patients with gastric cancer. The results indicate that THz absorption images can not only clearly distinguish cancer tissue from healthy tissues but also accurately define the margins of cancer. Through a medical statistical study of 40 sliced tissues from 40 patients, we prove that THz imaging can be used as a standalone method to diagnose gastric cancer tissues with a diagnostic specificity and sensitivity of 100%. Compared with the H&E staining method, THz imaging diagnosis makes the automation of tissue-sampling pre-screening procedure possible and assists in quickly determining the boundary between cancerous and healthy tissues

Pancreatic metastases to the rectum: a case report and literature review

Pancreatic cancer is one of the most malignant tumors due to its highly aggressive nature, but pancreatic metastases to the colorectum are extremely rare. A 43-year-old male patient complained of increased stool frequency. Colonoscopy revealed a prominence lesion in the rectum and computed tomography (CT) scan confirmed a rectal mass. CT scan also showed retroperitoneal masses in the pancreatic tail involving the spleen and adjacent blood vessels. The patient was initially misdiagnosed as having rectal cancer with pancreatic metastasis. After immunohistochemical staining results became available, the diagnosis was changed to pancreatic ductal adenocarcinoma with rectal metastasis. Elevated CA19-9 also supported the diagnosis. In conclusion, we describe a case of synchronous colonic metastasis from pancreatic cancer. Although rare, the suspicion of pancreatic metastases to the rectum should be excluded when a patient has both rectal and pancreatic masses

Polymerase I and transcript release factor acts as an essential modulator of glioblastoma chemoresistance.

OBJECTIVES: This study is to investigate if polymerase I and transcript release factor (PTRF) acts as a modulator in glioblastoma (GBM) chemoresistance. METHODS: Multidrug resistant (MDR) GBM cell line U251AR was established by exposing the U251 cell line to imatinib. The 2D-DIGE and MALDI-TOF/TOF-MS were performed on U251 and U251AR cell lines to screen MDR-related proteins. The expression of PTRF was determined by Western blot and quantitative RT-PCR analyses. RESULTS: When compared with the parental U251 cells, expression of 21 proteins was significantly altered in U251AR cells. Among the 21 differentially expressed proteins, the expression of PTRF was up-regulated by 2.14 folds in U251AR cells when compared with that in the parental U251 cells. Knockdown of PTRF in GBM cell lines significantly increased chemosensitivity of cells to various chemical drugs and decreased the expression levels of caveolin1, a major structural component of caveolae. Expression levels of PTRF and caveolin1 were significantly up-regulated in the relapsed GBM patients. The mRNA level of PTRF and caveolin1 showed a positive correlation in the same GBM specimens. CONCLUSIONS: Our results indicate that PTRF acts as a modulator in GBM chemoresistance

Evaluating AI in medicine: a comparative analysis of expert and ChatGPT responses to colorectal cancer questions

Abstract Colorectal cancer (CRC) is a global health challenge, and patient education plays a crucial role in its early detection and treatment. Despite progress in AI technology, as exemplified by transformer-like models such as ChatGPT, there remains a lack of in-depth understanding of their efficacy for medical purposes. We aimed to assess the proficiency of ChatGPT in the field of popular science, specifically in answering questions related to CRC diagnosis and treatment, using the book “Colorectal Cancer: Your Questions Answered” as a reference. In general, 131 valid questions from the book were manually input into ChatGPT. Responses were evaluated by clinical physicians in the relevant fields based on comprehensiveness and accuracy of information, and scores were standardized for comparison. Not surprisingly, ChatGPT showed high reproducibility in its responses, with high uniformity in comprehensiveness, accuracy, and final scores. However, the mean scores of ChatGPT’s responses were significantly lower than the benchmarks, indicating it has not reached an expert level of competence in CRC. While it could provide accurate information, it lacked in comprehensiveness. Notably, ChatGPT performed well in domains of radiation therapy, interventional therapy, stoma care, venous care, and pain control, almost rivaling the benchmarks, but fell short in basic information, surgery, and internal medicine domains. While ChatGPT demonstrated promise in specific domains, its general efficiency in providing CRC information falls short of expert standards, indicating the need for further advancements and improvements in AI technology for patient education in healthcare

Meta-Analysis of the Prognostic Value of Smad4 Immunohistochemistry in Various Cancers

<div><p>Background</p><p>Accumulating evidence indicates that Smad4 (DPC4) plays a fundamental role in the development and prognosis of several types of cancer. The objective of this study was to conduct a meta-analysis to evaluate whether the loss of Smad4 staining could serve as a prognostic marker.</p><p>Methods</p><p>A comprehensive meta-analysis was conducted using major useful databases to determine the relationship between the immunohistochemical detection of Smad4 and the survival of patients with various cancers. We used hazard ratios (HRs) with 95% confidence interval (CIs) as the effect estimation to evaluate the association of Smad4 with overall survival (OS), cancer-specific survival (CSS) or recurrence-free survival (RFS). The relationship between the clinical characteristics of patients and Smad4 was also evaluated using the odds ratio (OR).</p><p>Results</p><p>A total of 7570 patients from 26 studies were included in the analysis. The pooled results showed that loss of Smad4 staining was a negative predictor of OS with an HR of 1.97 (95% CI: 1.55–2.51; P_{heterogeneity}<0.001) and CSS/RFS (HR = 1.81; 95% CI: 1.30–2.54; P_{heterogeneity}<0.001). In addition, loss of Smad4 staining was more likely to be found in older (OR = 1.69, 95% CI: 1.09–2.61; P_{heterogeneity} = 0.648) colorectal cancer patients with a late tumor stage (OR = 2.31, 95% CI: 1.71–3.10; P_{heterogeneity} = 0.218) and in gastric cancer patients with lymph node metastasis (OR = 2.11, 95% CI: 1.03–4.34; P_{heterogeneity} = 0.038).</p><p>Conclusion</p><p>Based on these results, our meta-analysis provided evidence that loss of Smad4 staining could act as an unfavorable biomarker in the prognosis of various cancers and should be used as a powerful tool in future clinical trials.</p></div