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Aiming at the problem of the lack of user social attribute characteristics in the process of dividing overlapping communities in multilayer social networks, in this paper, we propose a multilayer social network overlapping community detection algorithm based on trust relationship. By combining structural trust and social attribute trust, we transform a complex multilayer social network into a single-layer trust network. We obtain the community structure according to the community discovery algorithm based on trust value and merge communities with higher overlap. The experimental comparison and analysis are carried out on the synthetic network and the real network, respectively. The experimental results show that the proposed algorithm has higher harmonic mean and modularity than other algorithms of the same type.

This paper presents an analysis of the structural behavior of both tapered ring and parallel ring linings in a tunnel design project using a shell-spring approach. This is done to examine whether the tapered ring lining can be approximated as a parallel ring lining. The results show that, under the same load conditions, the maximum positive bending moment and axial force of the tapered ring model varies little compared with the parallel ring model. However, the maximum negative bending moment and maximum deformation in these two models vary significantly. Under conditions of different joint orientations, the maximum negative bending moment and deformation differ by as much as 19%, regardless of which lining model is used. Thus, the simplification of a tapered ring lining as a parallel ring lining for use in tunnel design is not sensible.

Along with the development of IoT and mobile edge computing in recent years, smart transportation holds great potential to improve road safety and efficiency. The network that carries smart transportation service is highly dynamic. Controllability has long been recognized as one of the fundamental properties of such temporal networks, which can provide valuable insights for the construction of new infrastructures, and thus is in urgent need to be explored. In this article, under the smart transportation scenario, we first disclose the controllability problem in Internet of Vehicles (IoV), and then design DND (Driver Node Detection) algorithm based on Kalman’s controllability rank condition to analyze the controllability and control message diffusion in such a dynamic temporal network. Moreover, we use the control message diffusion efficiency as a metric to assist in selecting suitable driver nodes. At last, we conduct a series of experiments to analyze the controllability of the IoV network, and the results show the effects of vehicle density, speed, coverage radius on network controllability, and the efficiency of the control message diffusion algorithm and its feedback effect on driver nodes selection. These insights are critical for varieties of applications in the future smart transportation.

Background Autophagy-related genes (ARGs) have been significantly implicated in tumorigenesis and served as promising prognostic biomarkers for human cancer. Hence, this study was aimed to develop an ARGs-based prognostic signature for Head and neck squamous cell carcinoma (HNSCC). Methods Prognostic ARG candidates were identified by univariate and multivariate Cox regression analysis in the training dataset (TCGA-HNSC) and incorporated into a 3-ARGs (EGFR, FADD, and PARK2) prognostic signature which was further verified in two independent validation cohorts (GSE41613 and GSE42743). Kaplan-Meier plots, Cox regression analyses, and receiver operating characteristics curves (ROC) were employed to evaluate the prognostic prediction of 3-ARGs signature. Differential expression of these 3 ARG between cancer and normal counterparts as well as their associations with autophagy markers were assessed in 60 pairs of freshly collected HNSCC and adjacent non-tumor samples and datasets from Human Protein Atlas, respectively. Results Patients with high-risk score had significantly inferior overall survival. Multivariate regression analyses revealed that 3-ARGs signature could be an independent prognostic factor after adjusting various clinicopathological parameters. ROC analyses revealed high predictive accuracy and sensitivity of the 3-ARGs signature. Increased mRNA and protein expression of EGFR, FADD, and PARK2 were found in HNSCC samples, and their expression significantly correlated with the abundances of ATG5, Beclin1, and LC3. Conclusion Our results reveal that 3-ARGs signature is a powerful prognostic biomarker for HNSCC, which could be integrated into the current prognostic regime to realize individualized outcome prediction. EGFR, FADD, and PARK2 likely contributed to autophagy during HNSCC tumorigenesis.

The role of high-normal thyroid-stimulating hormone levels has been of great concern recently. However, the conclusions of different studies are inconsistent. To assess whether high-normal conditions have an impact on reproductive and obstetric outcomes in euthyroid women undergoing ART treatment, a systematic review and meta-analysis was performed. Eligible studies published up to December 30, 2020, were searched from the PubMed, EMBASE, COCHRANE, and CNKI databases. Quality assessment of the included studies, data extraction, and synthesis were performed separately. RevMan 5.2 was used to carry out the meta-analysis. A total of 23 studies that included 25,143 patients were included. We observed similar clinical pregnancy rates (RR = 1.01, 95% CI: 0.99-1.05), miscarriage rates (RR = 0.95, 95% CI: 0.84-1.08), live birth rates (RR = 1.04, 95% CI: 0.99-1.09), birth weights (SMD = 0.07, 95% CI: -0.02 to 0.16), and gestational ages (SMD = 0.07, 95% CI: -0.02 to 0.16) between the high-normal TSH group and low TSH group. Subgroup analysis showed similar results. High-normal TSH levels were associated with similar clinical pregnancy rates, live birth rates, and miscarriage rates to those of women with low TSH levels. The results suggested that preconceptional TSH levels, regardless of potentially being affected by the controlled ovarian stimulation process, had little impact on reproductive and obstetric outcomes and should not be of great concern.

Diabetes and heart failure are mutually reinforcing factors. The treatment strategy and prognosis for patients with both diabetes and heart failure are inconclusive. This article reviews the current situation of ischemic heart failure complicated with diabetes, the pathophysiological relationship between diabetes and heart failure, and disease management. Especially, we highlight the latest result from CRISIS (Coronary Revascularization in Patients with Ischemic Heart Failure and Prevention of Sudden Cardiac Death) study, which finds that diabetes associates with greater ejection fraction improvement after revascularization in patients with reduced ejection fraction. This result implies the indication for revascularization in patients with heart failure who present with DM.

With the explosive growth of mobile devices at the edge of mobile social networks (MSNs), the amount of the content that needs to be transmitted is exploded. Traditional content delivery mechanisms leverage only local information to make routing decisions, which results in both high latency and low delivery rate. Software-defined networking (SDN) is a novel network paradigm, the design philosophy of which could be applied to MSN for improving the content delivery performance. In this article, the centralized control thought of SDN is introduced into MSN to efficiently process social information. The classical routing algorithm of BubbleRap is improved from the perspective of network density, which is the basis of designing the sparse and dense routing mechanisms for MSNs. In addition, flexibly switching between these two routing mechanisms is implemented by a discriminating scheme, achieving efficient yet adaptive routing. The experimental results show that the delivery ratio of sparse routing is up to 83%, and the dense routing could reach up to 93%.

In recent years there has been a rapid increase of short video traffic in CDN. While the video contributors change from large video studios to distributed ordinary end users, edge computing naturally matches the cache requirements from short video network. But distributed edge caching exposes some unique characteristics: non-stationary user access pattern and temporal and spatial video popularity pattern, which severely challenge the edge caching performance. While the QoE in traditional CDN has been much improved, prior solutions become invalid in solving the above challenges. In this article, we present AutoSight, a distributed edge caching system for short video network, which significantly boosts cache performance. AutoSight consists of two main components, solving the above two challenges respectively: the CoStore predictor, which solves the non-stationary and unpredictability of local access pattern, by analyzing the complex video correlations; and a caching engine Viewfinder, which solves the temporal and spatial video popularity problem by automatically adjusting future horizon according to video life span. All these inspirations and experiments are based on the real traces of more than 28 million videos with 100 million accesses from 488 servers located in 33 cities. Experiment results show that AutoSight brings significant boosts on distributed edge caching in short video network.

The dysfunction of bone marrow stromal cells (BMSCs) may be a core factor in Type 2 diabetes mellitus (T2DM) associated osteoporosis. However, the underlying mechanism is not well understood. Here, we delineated the critical role of insulin impeding osteogenesis of BMSCs in T2DM. Compared with BMSCs from healthy people (H-BMSCs), BMSCs from T2DM patient (DM-BMSCs) showed decreased osteogenic differentiation and autophagy level, and increased senescent phenotype. H-BMSCs incubated in hyperglycemic and hyperinsulinemic conditions similarly showed these phenotypes of DM-BMSCs. Notably, enhanced TGF-β1 expression was detected not only in DM-BMSCs and high-glucose and insulin-treated H-BMSCs, but also in bone callus of streptozocin-induced diabetic rats. Moreover, inhibiting TGF-β1 signaling not only enhanced osteogenic differentiation and autophagy level of DM-BMSCs, but also delayed senescence of DM-BMSCs, as well as promoted mandible defect healing of diabetic rats. Finally, we further verified that it was TGF-β receptor II (TβRII), not TβRI, markedly increased in both DM-BMSCs and insulin-treated H-BMSCs. Our data revealed that insulin impeded osteogenesis of BMSCs by inhibiting autophagy and promoting premature senescence, which it should be responsible for T2DM-induced bone loss, at least in part. These findings suggest that inhibiting TGF-β1 pathway may be a potential therapeutic target for T2DM associated bone disorders.

Natural photosynthesis utilizes a redox cascade consisting of enzymes and molecular mediators that trap and stabilize hot carriers to achieve efficient multiple charge transfer. In this aspect, great challenges are facing artificial photochemistry regarding the extremely short lifetimes of photo-generated hot carriers. Herein, using Au nanoparticle photocatalysts as a model, we report that photoelectrodeposited catechol molecules on Au/TiO2 heterostructures trap and stabilize photo-generated hot holes on Au and further introduce a new multi-hole reaction pathway in which those long-lived catechol-trapped holes cooperate with newly generated holes on Au. The new mechanism boosts photoelectrochemical water oxidation on Au by one order of magnitude. Our study illustrates a strategy to integrate metal nanoparticles, semiconductors, and molecular redox mediators to effectively separate charge carriers and harvest hot holes for driving photochemical reactions.

The polarization singularities are directly generated by using plasmonic metasurfaces with the geometric phase profiles designed to form the Poincaré beams. Different morphologies of polarization topological structures of lemon, star, monstar, spiral, dipole and quadrupole are created by the superpositions of Laguerre–Gauss modes with different orders under orthogonal circular or linear polarization basis. The polarization ellipse patterns and topological features of the produced optical vector fields are analyzed to reveal the properties of the polarization singularities of C-points and L-lines, and the orbital angular momentum states are also measured. The demonstrated polarization singularities generated from the geometric metasurfaces will promise many potential applications related to optical polarization imaging, metrology, optical trapping and quantum information processing.

Yuchao Zhang, Gang Xu, Ping Wang Department of Vascular Surgery, The Affiliated Huaian No. 1 People’s Hospital of Nanjing Medical University, Huaian City, 223300, People’s Republic of ChinaCorrespondence: Ping Wang Tel/Fax +86-0517-80872149Email drwangping@126.comBackground: Recent researches have investigated the link between the rs1800796 polymorphism (− 572G/C) in the interleukin-6 (IL-6) gene and the risk of abdominal aortic aneurysm (AAA). However, no Chinese studies have addressed the association between the risk of AAA and this polymorphism.Methods: This case-control study included 153 AAA patients and 205 controls. Diabetes mellitus, hypertension, dyslipidemia, and coronary artery disease (CAD) status were collected. The AAA and control groups were 69.20 ± 7.56 and 68.50 ± 7.12 years old, respectively.Results: The analysis revealed that the G allele and GG genotype of the IL-6 rs1800796 polymorphism were remarkedly correlated with an elevated risk of AAA. The GG genotype displayed an association with the risk of AAA after adjustment for gender, body mass index, age, drinking, and smoking. Subgroup analyses indicated that this polymorphism elevated the risk of AAA among males, individuals aged ≥ 70 years, smokers, drinkers, individuals with a body mass index (BMI) ≥ 25 kg/m2, patients without diabetes, and patients with hypertension. Univariate and multivariate analyses indicated that smoking, hypertension, and the GG genotype (rs1800796 polymorphism) were independently related with the risk of AAA.Conclusion: The IL-6 rs1800796 polymorphism increases the risk of AAA. In addition, smoking, hypertension, and the GG genotype of the rs1800796 polymorphism are independent risk factors for AAA. Further studies of Chinese populations are needed to validate these findings.Keywords: IL-6, abdominal aortic aneurysm, rs1800796 polymorphism, risk factors

ObjectiveTo compare the clinical outcomes of dydrogesterone (DYG) and medroxyprogesterone (MPA) in the progestin-primed ovarian stimulation (PPOS) protocol for patients with poor ovarian response (POR).Patients and MethodsThis was a retrospective cohort study. Women with POR who underwent IVF/ICSI at the Reproductive Center of Third Affiliated Hospital of Zhengzhou University between January 2020 and January 2021 were included. The primary outcome measure of our study was the number of oocytes retrieved. The secondary outcome measures in the present study were the number of 2PN, number of available embryos, oocyte retrieval rate, fertilization rate, viable embryo rate per oocyte retrieved, cancellation rate and pregnancy outcomes of the first embryo transfer cycle, including the biochemical pregnancy, clinical pregnancy and miscarriage rates.ResultsIn total, 118 women underwent hMG +DYG protocols, and 692 women who underwent hMG +MPA met the Bologna criteria for POR. After baseline characteristics were balanced using the PSM model, 118 hMG +DYG protocols were matched to 118 hMG +MPA protocols, and the baseline characteristics were comparable between the two groups. The numbers of oocytes retrieved, 2PN, and available embryos and the oocyte retrieval rate, fertilization rate, viable embryo rate per oocyte retrieved and cancellation rate of the hMG+DYG and hMG+MPA protocols were comparable. Altogether, 66 women in the hMG+DYG group and 87 women in the hMG+MPA group underwent first embryo transfers. In the hMG+DYG group, 81.8% (54/66) of the patients underwent cleavage embryo transfers; similarly, 79.3% (69/87) of patients in the hMG+MPA group had cleavage embryo transfers (P=0.70).The biochemical pregnancy rate of the hMG+DYG group was 42.4%, and this was comparable to the rate in the hMG+DYG group, at 34.5% (P=0.32). The clinical pregnancy rates were similar between the two groups (36.4% vs. 31.0%, P=0.49), and there was no significant difference in the rate of miscarriage between the two groups (12.5% vs. 29.6%, P=0.14).ConclusionFor women with POR, the clinical outcome of the hMG + DYG group was similar to that of the hMG + MPA group, indicating that both combinations can be useful options for PPOS protocols.

Background To analyze the characteristics of basal thyroid hormone levels in infertile women consulting for assisted reproductive technology (ART) treatment. Methods This was a retrospective study. Serum TSH, FT3 and FT4 levels of women seeking ART consultation were tested routinely. Analyses were performed based on age and sampling time. One-way ANOVA or Kruskal-Wallis rank sum test was used to compare the continuous data among the groups, and the chi-square test or Fisher’s exact test was used to compare categorical data where appropriate. Results A total of 6426 women were initially included in the study. After exclusion criteria were applied, the remaining 4126 women were categorized into different groups. The prevalence of subclinical hypothyroidism significantly decreased with age and sampling time, from 21.09 to 11.91% and from 28.57 to 10.67%, respectively (P P = 0.017, P P = 0.258, 0.300, respectively). Conclusions The prevalence of subclinical hypothyroidism significantly decreased with increasing age and sampling time, as did the serum TSH levels. Even though, the establishment of reference interval of TSH level based on age or sampling time was not recommended. Full consideration of age and sampling time should be carefully taken before initiation of treatment.

The largest blue-green infrastructures in industrialized, urbanized and developed regions in China are often multiuse wetlands, located just outside growing urban centers. These areas have multiple development pressures while providing environmental, economic, and social benefits to the local and regional populations. Given the limited information available about the tradeoffs in ecosystem services with respect to competing wetland uses, wetland managers and provincial decision makers face challenges in regulating the use of these important landscapes. In the present study, measurements made by citizen scientists were used to support a comparative study of water quality and wetland functions in two large multiuse wetlands, comparing areas of natural wetland vegetation, tourism-based wetland management and wetland agriculture. The study sites, the Nansha and Tianfu wetlands, are located in two of the most urbanized areas of China: the lower Yangtze River and Pearl River catchments, respectively. Our results indicated that the capacity of wetlands to mitigate water quality is closely related to the quality of the surrounding waters and hydrological conditions. Agricultural areas in both wetlands provided the lowest sediment and nutrient retention. The results show that the delivery of supporting ecosystem services is strongly influenced by the location and use of the wetland. Furthermore, we show that citizen scientist-acquired data can provide fundamental information on quantifying these ecosystem services, providing needed information to wetland park managers and provincial wetland administrators.

Ternary Content Addressable Memory (TCAM) is an important hardware used to store route entries in routers, which is used to assist routers to make fast decision on forwarding packets. In order to cope with the explosion of route entries due to massive IP terminals brought by 5G and the Internet of Things (IoT), today’s commercial TCAM has to keep the corresponding growth in capacity. But large TCAM capacity is causing many problems such as circuit design difficulties, production costs, and high energy consumption, so it is urgent to design a lightweight TCAM with small capacity while still maintains the original query performance.Designing such a TCAM faces two fundamental challenges. Firstly, it is essential to accurately predict the incoming flows in order to cache correct entries in limited TCAM capacity, but prediction on aggregated time-sequential data is challenging in the massive IoT scenarios. Secondly, the prediction algorithm needs to be real-time as the lookup process is in line-rate. In order to address the above two challenges, in this paper, we proposed a lightweight AI-based solution, called AIR, where we successfully decoupled the route entries and designed a parallel-LSTM prediction method. The experiment results under real backbone traffic showed that we successfully achieved comparable query performance by using just 1/8 TCAM size.

Bacterial meningitis shows a higher incidence in children than adults, but signs may be scarce. Although some pathogenic microorganisms of meningitis from cerebrospinal fluid (CSF) have been reported, the signature of the representative microbiota in CSF and blood samples from patients remains incompletely revealed. To extend the understanding of the microbiome in patients, we recruited 32 children with bacterial meningitis, 30 undiagnosed infectious children, and 10 matched healthy individuals, which was followed by untargeted metagenomic next-generation sequencing (mNGS) and bioinformatic analysis. Our results showed that children with bacterial meningitis exhibited different microbiome signatures in their CSF and blood compared with undiagnosed and healthy children, and patients could be divided into varied subsets according to these signatures, including Escherichia coli, Klebsiella pneumoniae, Thermothelomyces thermophila, Lactobacillus acidophilus, and Staphylococcus haemolyticus. To further explore their potential role in patients’ conditions, we examined their correlation with clinical parameters. Importantly, microbiome signatures with compositional changes were correlated with the C-reactive protein (CRP) level in blood and granulocyte percentage in CSF. Moreover, the blood in subsets of patients with a predominance of Klebsiella pneumoniae could replace CSF as the main specimen for clinical monitoring. IMPORTANCE This study revealed the microbial compositions in children with bacterial meningitis who were treated with antibiotics and made a comprehensive comparison between blood and CSF specimens for the risk and prognosis assessment. We found that microbiome signatures could distinguish patient subsets in the children and were correlated with the CRP level in blood and granulocyte percentage in CSF. The compositional changes in representative microbiota constituents could provide guidance for clinical monitoring and antibiotic intervention.

With the development of communication and transmission technologies, more and more applications, like Internet of vehicles and tele-medicine, become more sensitive to network latency and accuracy, which requires routing schemes to be more efficient. In order to meet such urgent need, learning-based routing strategies emerges, with the advantages of high flexibility and accuracy. These strategies can be divided into two categories, centralized and distributed, enjoying the advantages of high precision and high efficiency, respectively. However, routing become more complex in dynamic network, where the link connections and access states are time-varying, so these learning-based routing mechanisms are required to be able to adapt to network changes in real time. In this paper, we designed and implemented both two of centralized and distributed reinforcement learning-based routing schemes (RLR-T). By conducting a series of experiments, we deeply analyzed the results and gave the conclusion that the centralized is better to cope with dynamic networks due to its faster reconvergence, while the distributed is better to handle with large-scale networks by its high scalability.

With the development of 5G access technology and the corresponding explosive growth of user requests, service providers have to activate more and more physical machines (PM) in cloud datacenters. This simple expansion of PMs results in not only low utilization of servers but also high maintenance cost. Existing researches that try to release unnecessary servers by migrating VMs always face a severe challenge-the large searching space for the optimal VM placement solution. In this paper, we prose a two-stage variable neighborhood searching (STVNS) algorithm, named FreeVM, which can significantly reduce the number of occupied servers. FreeVM works harmoniously with all kinds of VM placement schemes under various scenarios. We conducted an extensive series of experiments using real traces, and the results show that FreeVM can release at least 15% physical machines compared with existing solutions.

The orbital angular momentum (OAM) transformation of optical vortex is realized upon using aluminum metasurfaces with phase distributions derived from the caustic theory. The generated OAM transformation beam has the well-defined Bessel-like patterns with multiple designed topological charges from −1 to +2.5 including both the integer-order and fractional-order optical vortices along the propagation. The detailed OAM transformation process is observed in terms of the variations of both beam intensity and phase profiles. The dynamic distributions of OAM mode density in the transformation are further analyzed to illustrate the conservation of the total OAM. The demonstration of transforming OAM states arbitrarily for optical vortex beams will lead to many new applications in optical manipulation, quantum optics, and optical communication.

Containerization has been used in many applications for isolation purposes due to its lightweight, scalable, and highly portable properties. However, to apply containerization in large-scale Internet data centers faces a big challenge. Services in data centers are always instantiated as a group of containers, which often generate heavy communication workloads and therefore resulting in inefficient communications and downgraded service performance. Although assigning the containers of the same service to the same server can reduce the communication overhead, this may cause heavily imbalanced resource utilization since containers of the same service are usually intensive to the same resource. To reduce communication cost as well as balance the resource utilization in large-scale data centers, we further explore the container distribution issues in a real industrial environment and find that such conflict lies in two phases—container placement and container reassignment. The objective of this paper is to address the container distribution problem in these two phases. For the container placement problem, we propose an efficient communication aware worst fit decreasing algorithm to place a set of new containers into data centers. For the container reassignment problem, we propose a two-stage algorithm called Sweep&Search to optimize a given initial distribution of containers by migrating containers among servers. We implement the proposed algorithms in Baidu’s data centers and conduct extensive evaluations. Compared with the state-of-the-art strategies, the evaluation results show that our algorithms perform better up to 70% and increase the overall service throughput up to 90% simultaneously.

A reconfigurable and reliable wavelength division multiplexing (WDM) metro-access optical network architecture is proposed in this paper. With the establishment of one optical transmitter in the optical network unit (ONU) and the reuse of optical distribution network, three kinds of reconfigurable WDM optical networks can be successfully built to achieve efficient inter and intra PON communication in the physical layer. With the adoption of multiple topologies based on single ring, four-level protections of feeder and distribution fibers can be achieved. With the creative design of flexible distribution node (FDN), the transmission wavelengths in the central office can be not only transmitted to the express ONUs connected straight with FDN, but also routed to the indirect ONUs hung in the remote node. Finally, large capacity, high reliability, low cost and great transmission performances at 10 Gbps and 2.5 Gbps data rate are obtained via analyses and simulation

Objective The present study aimed to comprehensively characterize the epidemiologic characteristics, clinicopathologic characteristics, clinical treatments, and prognoses of pleomorphic adenoma (PA) identified at unusual intraoral sites. Study Design Patients diagnosed with PA in oral and maxillofacial regions at our institution in the past 16 years (2005-2020) were screened from the inpatient disease registry. All data concerning patients with PA found at unusual intraoral sites (defined as intraoral locations except sublingual gland and palate) were retrieved. Previously published cases with adequate clinicopathologic data were collected from PubMed and Embase. Eligible cases were further reviewed and included for statistical analyses. Results Among 1039 cases of PA diagnosed at our institution, 52 lesions were found at unusual intraoral sites. A literature review identified another 63 eligible cases from 32 articles. The upper lip was the most common sites for these lesions (n = 57), followed by buccal mucosa (n = 34), tongue (n = 8), lower lip (n = 8), and retromolar area (n = 2). Recurrence and malignant transformation after surgical resection were extremely rare for these lesions. Conclusions PA might rarely develop at uncommon intraoral sites with atypical presentations, thus complicating its early diagnosis. Surgical resection is the major therapeutic strategy for this rare entity and has a favorable prognosis.

Purpose: The pathological process of atopic dermatitis (AD) progressing into other types of allergic diseases such as asthma and allergic rhinitis during the first several years of life is often referred to as the atopic march. Although the phenomenon of atopic march has been recognized for decades, how asthma stems from AD is still not fully understood, confounding a universal strategy to effectively protect people from the atopic march. Methods: We established experimental atopic march mice by first inducing allergic dermatitis with 0.5% fluorescein isothiocyante (FITC) applied to the skin, followed by an ovalbumin (OVA) airway challenge. In addition, by examining serum immunoglobulin (Ig) concentrations, airway cytokines, the levels of oxidative stress markers, histopathological changes in lung tissue and airway hyperresponsiveness (AHR), we were able to validate the successful establishment of the model. Furthermore, by detecting the attenuating effects of melatonin (MT) and the levels of oxidative stress in the atopic march mice, we explored the potential molecular mechanisms involved in the development of atopic march. Results: By successfully establishing an experimental atopic march mouse model, we were able to demonstrate that overproduction of oxidative stress in the lung significantly up-regulated the activation of nuclear factor-κB (NF-κB) signaling pathways causing thymic stromal lymphopoietin (TSLP) release, which further promotes the development of atopic march. Conclusions: To mitigate the development of the atopic march, antioxidants such as MT may be imperative to inhibit NF-κB activation in the lung, especially after the onset of AD.

Background Standard morphologic evaluation has been the most widely adopted approach to embryo selection, and remains the most common strategy.The objective of the study to determine the association between the morphologic grading and implantation rate of euploid blastocysts in single frozen-thawed embryo transfer (SET) cycles. Methods A total of 271 patients aged 20–40 years undergoing euploid SET from January 2017 to December 2019 were included in retrospective cohort study.The cycles were divided into three groups based on their morphologic grading before cryopreservation: good-quality (n = 58), average-quality (n = 88) and poor-quality blastocysts (n = 125). The pregnancy outcome of the three morphologic groups were analyzed and a logistic regression of implantation rate was conducted. Results Good-quality blastocysts yielded statistically significantly higher implantation rates than poor-quality (79.31% vs. 48%; PPP = 0.172). The implantation rates were higher among women with good-quality blastocysts on both Day 5 and Day 6 of TE biopsy than among those with poor-quality blastocysts (Day 5, aOR = 3.294, 95% CI:1.260–8.616, P = 0.015; Day 6, aOR = 4.179, 95% CI:1.004 ~ 17.399, P = 0.049). Day 5 euploid blastocysts had no significant difference in implantation potential and early spontaneous abortion rate compared with similarly graded Day 6 euploid blastocysts. Conclusions Blastocyst morphologic grading was associated with implantation rate for euploid embryo transfers after adjustment for potential confounders. These findings suggest that evaluating blastocyst morphology is critical when selecting the best euploid blastocyst.

Incorporating user trust relationships can effectively alleviate the cold start and data sparse problems in traditional collaborative filtering algorithms. But in real life, the user trust relationships that can be collected also face data sparse problems. In addition, the existing recommendation algorithm based on user implicit trust relationship does not consider the negative and enthusiasm of certain products that have special significance to users and the common experience items between users when mining implicit trust relationships among users. In response to this type of problem, this article uses the historical scoring information of users to infer the meaning of the project to users, and the influence of the negative and enthusiasm of the user experience project on the implicit trust relationship between users, supplementing the existing trust statement between users to improve the accuracy of recommendation. Firstly, divide the community based on user trust relationships. Second, use the divided community user rating information to dig out the meaning of different items for different users, and infer the implicit direct trust value between users based on the positive and negative ratings between users, then the implicit direct trust between users is used to obtain the implicit indirect trust value according to the trust propagation. Finally, the implicit trust relationship between users was obtained according to the implicit direct and indirect trust between users, and the implicit trust between users was used to replace the similarity in traditional collaborative filtering, so as to find the recommended nearest neighbors of target users and predict the score of missing items. In the experimental results of the real data set FilmTrust and Epinions, compared with the comparison algorithm given in this article, it can effectively improve the accuracy of recommendation.

With the emerging and development of lowlatency applications (such as autonomous driving, SmartCity, telemedicine), low-latency has become one of the key requirements of current network services, especially in edge computing and 5G network. While under the state-of-the-art architecture, the request resolution is provided by Internet Service Provider’s localDNS, which assigns a specific edge server for each request, but this method is now suffering from inaccurate scheduling problem, and fails to adapt to network changes due to the relatively fixed allocation strategy. These drawbacks result in the long response latency, and are becoming more severe in nowadays 5G edge networks. In this paper, we propose a flexible HttpDNS architecture for 5G edge server exploration and selection, where the domain names of users’ requests are resolved by HttpDNS instead of the traditional localDNS. Under such architecture, user’s request is directly transmitted to HttpDNS servers, which will then allocate a specific edge server for this request. With a server scoring module, the proposed HttpDNS architecture can finally ensure user requests be guided to the optimal edge server. We implement a prototype of HttpDNS architecture and conduct a series of experiments, the results show that such architecture not only reduces at least 10% latency compared with the traditional localDNS, but also has higher stability when network changes.

In this Letter, a high-accuracy, two-dimensional displacement sensor is proposed, designed, and demonstrated based on the concept of an extrinsic Fabry–Perot Interferometer. The sensor is composed of two bundled single-mode optic fibers in parallel and two plasmonic metasurface resonators inscribed on a gold substrate via a focused ion beam. The fiber end surface and the metasurface are in parallel with a small cavity between. The cavity change or Z -component displacement is determined from the pattern of interference fringes. The X -component displacement, perpendicular to the Z component, is identified from wavelength-selective metasurface resonators, which possess unique resonant wavelengths due to different nanostructure designs. The sensor was calibrated with six displacements applied through a three-axis precision linear stage. Test results indicated that the proposed interferometer can measure displacements with a maximum error of 5.4 µm or 2.2%.

Background The aim of this study was to investigate the impact of TSH levels on clinical outcomes 14 days after frozen-thawed embryo transfer. Methods Blood samples were collected on the first visit to our department and 14 days after embryo transfer. Women were divided into three groups based on D14 TSH levels, which were compared to basal TSH levels in groups with different clinical outcomes. TSH levels between pregnant and nonpregnant women were also compared. Results The clinical pregnancy rate in women with lower TSH levels 14 days after transfer was slightly but significantly lower (56%, P = 0.05) compared to those with higher TSH levels. Furthermore, TSH levels were significantly elevated 14 days after transfer compared to basal TSH levels in pregnant women and in women who successfully became pregnant (P Conclusions Elevated TSH levels 14 days after embryo transfer compared to basal TSH levels seem to play a protective role and predict favorable clinical outcomes under specific conditions.

Purpose: Adjuvant chemotherapy following resection is recommended by clinical practice guidelines for all patients with pancreatic ductal adenocarcinoma (PDAC). This study aimed to evaluate the efficacy of adjuvant chemotherapy among the staging groups of the American Joint Committee on Cancer (AJCC) for PDAC. Patients and Methods: This retrospective cohort analysis was performed by the Surveillance Epidemiology and End Results (SEER) (2004-2015) database and multi-institutional dataset (2010-2018). Baseline clinicopathologic characteristics of PDAC patients, including age, gender, ethnicity, marital status, education level, county income level, county unemployed rate, insurance status, grade, stage, chemotherapy, and radiotherapy, were collected. Overall survival (OS) was analyzed using the Kaplan-Meier method. The SEER and multi-institutional data were adjusted with 1:1 ratio propensity score matching (PSM). Results: In total, 6,274 and 1,361 PDAC patients were included from the SEER database and multi-institutional dataset, respectively. Regardless of the count of resected lymph nodes, adjuvant chemotherapy prolonged the long-term OS time for stage IB, IIA, IIB, and III patients in both SEER and multi-institutional cohorts. Nevertheless, adjuvant chemotherapy did not provide additional clinical benefits even after a PSM adjustment for stage IA patients in both SEER and multi-institutional cohorts. Conclusion: Adjuvant chemotherapy improved the long-term survival of stage IB, IIA, IIB, and III PDAC patients; however, it demonstrated no survival benefit in stage IA PDAC patients. Thus, adjuvant chemotherapy should not be recommended for stage IA PDAC patients. These would significantly reduce the economic burden of society and improve the life quality of stage IA PDAC patients.

Tumors are a serious threat to human health, and tumor treatments have continued to evolve from chemotherapy to targeted therapy, immunotherapy, and individualized immunotherapy. Tumor cells have many mutations that cause the production of neoantigens, which are unique to tumor cells. Tumor neoantigen vaccines can effectively activate the body’s immune system to kill tumor cells, making individualized immunotherapy based on tumor neoantigens a new direction for the development of personalized immunotherapy for tumors. This technique is unique in that it can kill cancer cells without damaging healthy tissues, it can target and attack tumors in any part of the body, it has minimal toxicity, and it is effective for almost all forms of cancer, allowing immune cells to “remember” cancer cells to prevent tumor recurrence. Tumor neoantigen vaccines are not only therapeutic but may also exert a preventive effect in high-risk groups. This therapy may also be applied to other diseases that can produce neoantigens, including infectious diseases, which increases the potential for broad application.

State-of-the-art microservices are starting to get more and more attention in recent years. A broad spectrum of online interactive applications are now programmed to service chains on cloud, seeking for better system scalability and lower operation cost. Different from the conventional batch jobs, most of these applications are composed of multiple stand-alone services that communicate with each other. These step-by-step operations unavoidably introduce higher latency to the delay-sensitive chained services.

Purpose. To investigate the association between high-normal preconception TSH levels and reproductive outcomes in infertile women undergoing the first single fresh D5 blastocyst transfer. Methods. This was a retrospective study. Euthyroid patients undergoing the first single fresh D5 blastocyst transfer from January 2018 to May 2019 were initially included. The patients were divided into a low TSH (0.27–2.5 mIU/L) group and a high-normal TSH (2.5–4.2 mIU/L) group. The reproductive outcomes were compared between the groups. Results. A total of 824 women were ultimately included, 460 of whom had serum TSH levels less than 2.5 mIU/L and 364 of whom had serum TSH levels between 2.5 and 4.2 mIU/L. The patients were highly homogeneous in terms of general characteristics. High-normal TSH levels had no adverse impact on the clinical pregnancy rate, miscarriage rate, or live birth rate (respectively, aOR = 0.84, 0.65, 0.61, and P=0.234, 0.145, 0.083). No significant differences were observed in terms of gestational age, single live birth rates, birth weight, or birth length. Conclusion. High-normal TSH levels did not significantly influence reproductive outcomes in infertile women undergoing the first single fresh D5 blastocyst transfer. Further studies are needed to test whether the results might be applicable to a wider population.

Recent years have witnessed a rapid increase of short video traffic in content delivery network (CDN). While the video contributors change from large video studios to distributed ordinary end users, edge computing naturally matches the cache requirements from short video network. But the distributed edge caching exposes some unique characteristics: non-stationary user access pattern and temporal and spatial video popularity pattern, which severely challenge the edge caching performance. While the Quality of Experience (QoE) in traditional CDN has been much improved, prior solutions become invalid in solving the above challenges. In this chapter, we present AutoSight, a distributed edge caching system for short video network, which significantly boosts cache performance. AutoSight consists of two main components, solving the above two challenges, respectively: (i) the CoStore predictor, which solves the non-stationary and unpredictability of local access pattern, by analyzing the complex video correlations, and (ii) a caching engine Viewfinder, which solves the temporal and spatial video popularity problem by automatically adjusting future horizon according to video life span. All these inspirations and experiments are based on the real traces of more than 28 million videos with 100 million accesses from 488 servers located in 33 cities. Experiment results show that AutoSight brings significant boosts on distributed edge caching in short video network.

As the emerging entertainment applications, short video platforms, such as Youtube, Kuaishou, quickly dominant the Internet multimedia traffic. The caching problem will surely provide a great reference to network management (e.g., traffic engineering, content delivery). The key to cache is to make precise popularity prediction. However, different from traditional multimedia applications, short video network exposes unique characteristics on popularity prediction due to the explosive video quantity and the mutual impact among these countless videos, making the state-of-the-art solutions invalid. In this paper, we first give an in-depth analysis on 105,231,883 real traces of 12,089,887 videos from Kuaishou Company, to disclose the characteristics of short video network. We then propose a graph convolutional neural-based video popularity prediction algorithm called GraphInf. In particular, GraphInf clusters the countless short videos by region and formulates the problem in a graph-based way, thus addressing the explosive quantity problem. GraphInf further models the influence among these regions with a customized graph convolutional neural (GCN) network, to capture video impact. Experimental results show that GraphInf outperforms the traditional Graph-based methods by 44.7%. We believe such GCN-based popularity prediction would give a strong reference to related areas.

Along with the development of IoT and mobile edge computing in recent years, everything can be connected into the network at anytime, resulting in quite dynamic networks with time-varying connections. Controllability has long been recognized as one of the fundamental properties of such temporal networks, which can provide valuable insights for the construction of new infrastructures, and thus is in urgent need to be explored. In this chapter, we take smart transportation as an example, first disclose the controllability problem in IoV (Internet of Vehicles) and then design a DND (driver node) algorithm based on Kalman’s rank condition to analyze the controllability of dynamic temporal network and also to calculate the minimum number of driver nodes. At last, we conduct a series of experiments to analyze the controllability of IoV network, and the results show the effects from vehicle density, speed, and connection radius on network controllability. These insights are critical for varieties of applications in the future smart connected living.

Content caching in mobile edge networks has stirred up tremendous research attention. However, most existing studies focus on predicting content popularity in mobile edge servers (MESs). In addition, they overlook how the content is cached, especially how to cache the content with user devices. In this paper, we propose CMU, a three-layer (Cloud-MES-Users) content caching framework and investigate the performance of different caching strategies under this framework. A user device who has cached the content can offer the content sharing service to other user devices through device-to-device communication. In addition, we prove that optimizing the transmission performance of CMU is an NP-hard problem. We provide a solution to solve this problem and describe how to calculate the number of distributed caching nodes under different parameters, including time, energy and storage. Finally, we evaluate CMU through a numerical analysis. Experiment results show that content caching with user devices could reduce the requests to Cloud and MESs, and decrease the content delivery time as well.

This chapter is to summarize the processing of the business, starting from the service access to the data center, to the data transmission control, to the server back-end communication, and the data synchronization service support, tracking the complete service flow of the data flow. And carry out comprehensive and in-depth research work for each of these links.

Data centers are now used as the underlying infrastructure of many modern commercial operations, powering both large Internet services and a growing number of data-intensive scientific applications. The tasks in these applications always consist of rich and complex flows which require different resources at different time slots. The existing data center scheduling frameworks are however base on either task- or flow-level metrics. This simplifies the design and deployment but hardly unleashes the potentials of obtaining low task completion time for delay-sensitive applications.

Purpose. To investigate the association between high-normal preconception TSH levels and reproductive outcomes in infertile women undergoing the first fresh D3 embryo transfer. Methods. This was a retrospective study. Euthyroid patients undergoing the first fresh D3 embryo transfer from January 2018 to May 2019 were initially included. The patients were divided into a low-TSH (0.27–2.5 mIU/L) group and a high-normal TSH (2.5–4.2 Miu) group. The reproductive outcomes were compared between the groups. Results. A total of 1786 women were ultimately included, in which 1008 of whom had serum TSH levels between 0.27 and 2.5 mIU/L and 778 of whom had serum TSH levels between 2.5 and 4.2 mIU/L. The patients were highly homogeneous in terms of general characteristics. High-normal TSH levels had no adverse impact on the clinical pregnancy rate, miscarriage rate, or live birth rate (respectively, aOR = 0.92, 1.30, and 0.88 and P = 0.416, 0.163, and 0.219). No significant differences were observed in terms of gestational age, single live birth rates, and birth weight, or birth length. Conclusion. High-normal TSH levels did not significantly influence reproductive outcomes in infertile women undergoing the first fresh D3 embryo transfer. Further studies are needed to test whether the results might be applicable to a wider population.

Many important cloud services require replicating massive data from one datacenter (DC) to multiple DCs. While the performance of pair-wise inter-DC data transfers has been much improved, prior solutions are insufficient to optimize bulk-data multicast, as they fail to explore the rich inter-DC overlay paths that exist in geo-distributed DCs, as well as the remaining bandwidth reserved for online traffic under fixed bandwidth separation scheme. To take advantage of these opportunities, we present BDS+, a near-optimal network system for large-scale inter-DC data replication. BDS+ is an application-level multicast overlay network with a fully centralized architecture, allowing a central controller to maintain an up-to-date global view of data delivery status of intermediate servers, in order to fully utilize the available overlay paths. Furthermore, in each overlay path, it leverages dynamic bandwidth separation to make use of the remaining available bandwidth reserved for online traffic. By constantly estimating online traffic demand and rescheduling bulk-data transfers accordingly, BDS+ can further speed up the massive data multicast. Through a pilot deployment in one of the largest online service providers and large-scale real-trace simulations, we show that BDS+ can achieve 3–5× speedup over the provider’s existing system and several well-known overlay routing baselines of static bandwidth separation. Moreover, dynamic bandwidth separation can further reduce the completion time of bulk data transfers by 1.2 to 1.3 times.

Containerization has been used in many applications for isolation purposes due to its lightweight, scalable, and highly portable properties. However, to apply containerization in large-scale Internet data centers faces a big challenge. Services in data centers are always instantiated as a group of containers, which often generate heavy communication workloads and therefore resulting in inefficient communications and downgraded service performance. Although assigning the containers of the same service to the same server can reduce the communication overhead, this may cause heavily imbalanced resource utilization since containers of the same service are usually intensive to the same resource.

Along with the development of IoT and mobile edge computing in recent years, everything can be connected into the network at anytime, resulting in quite dynamic networks with time-varying connections. Controllability has long been recognized as one of the fundamental properties of such temporal networks, which can provide valuable insights for the construction of new infrastructures, and thus is in urgent need to be explored. In this paper, we take smart transportation as an example, first disclose the controllability problem in IoV (Internet of Vehicles), and then design an DND (Driver NoDe) algorithm based on Kalman's rank condition to analyze the controllability of dynamic temporal network and also to calculate the minimum number of driver nodes. At last, we conduct a series of experiments to analyze the controllability of IoV network, and the results show the effects from vehicle density, speed, connection radius on network controllability. These insights are critical for varieties of applications in the future smart connected living.

Serum anti-Mullerian hormone (AMH) shows a strong positive correlation to the number of oocytes retrieved but the patients undergoing assisted reproductive technology (ART) with lower AMH concentrations also could retrieve an ideal number of oocytes sometimes. The aim of the current study was to assess the performance of this population. This retrospective study included a total of 44 in vitro fertilization (IVF)/intracytoplasmic sperm injection (ICSI) treatment cycles as test group, in which their AMH levels were below the limit of reference range but more than 7 eggs were retrieved, and 103 control cases enrolled from May 2016 to December 2018 after matched with the same range of age from 24 to 38 years old and the same number range of retrieved oocytes from 7 to 18 and chosen randomly according to clinical ovarian stimulation protocols by the ratio of 3:7. Several parameters, which include age, basal endocrine status, number of oocytes, the maturation rate of eggs, 2PN fertilization rate, 3PN rate, total fertilization rate, cleavage rate, 8-cell embryo rate of D3 and the utilization rate of embryo, were compared and evaluated between two groups by Wilcoxon rank-sum test and t test for two independent samples. Although the same age range from 24 to 38 years and the same retrieval eggs from 7 to 18, compared with the control group, the test group showed less number of oocytes collected (9.455 vs 10.767, p = 0.016), younger ages (28.36 vs 32.59, p = 0.000), and higher FSH of basal endocrine status (9.783 vs 7.338, p = 0.021). Between the two groups, there were no significant differences in parameters such as the mature eggs (7.05 vs 7.92, p = 0.079), the mature oocyte rate (74.189% vs 73.916%, p = 0.924), the number of 2PNs (5.36 vs 5.91, p = 0.236), 2PN rate (73.678% vs 75.125%, p = 0.769), the number of 3PNs (0.39 vs 0.50, p = 0.773), 3PN rate (5.104% vs 5.592%, p = 0.697), number of total fertilizations (6.77 vs 7.35, p = 0.241), total fertilization rate (96.461% vs 93.166%, p = 0.332), cleavage rate (82.003% vs 81.382%, p = 0.673), the number of 8-cells on D3 (1.59 vs 1.91, p = 0.227), the rate of 8-cell on D3 (36.259% vs 41.084%, p = 0.551) and the utilization rate of embryo (62.853% vs 61.824%, p = 0.806). These findings indicate that there are no significant differences in the maturation of oocytes and the embryo quality for the women with low AMH level and ideal retrieval eggs but they should undergo IVF treatment and achieve successful pregnancy as soon as possible due to the higher basal FSH, the relatively fewer number of retrieval eggs and the possibility of coming diminished ovarian reserve (DOR) or poor respond (PR) despite their younger ages.

In this paper, we propose a novel tangent-ring TWDM metro-access network providing flexible reconfiguration and high reliability. With the innovate design of flexible distribution node (FDN) and distributed control mechanism (DCM), three kinds of reconfigurable TWDM-PONs can be built to achieve efficient intra and inter ONU direct communication by reusing optical distribution network (ODN). In addition, three-level protections covering both feeder and distribution fibers are also separately supported by the use of optical switches and natural advantage of single-fiber tangent ring topology. Moreover, with the use of simplified RN* and ONU*, the proposed network can upgrade smoothly and achieve pay-as-you grow. The network capacity, OSNR, cost and transmission performances are also studied, which suggests that this network has a good performance.

An optical time-and-wavelength-division-multiplexing metro-access network (TWDM-MAN) is proposed and demonstrated in this paper. By the reuse of tangent-ring optical distribution network and the design of distributed control mechanism, ONUs needing to communicate with each other can be flexibly accessed to successfully make up three kinds of reconfigurable networks. By the nature advantage of ring topology in protection, three-level comprehensive protections covering both feeder and distribution fibers are also achieved. Besides, a distributed wavelength allocation (DWA) is designed to support efficient parallel upstream transmission. The analyses including capacity, congestion and transmission simulation show that this network has a great performance.

State-of-the-art microservices have been attracting more attention in recent years. A broad spectrum of online interactive applications are now programmed to service chains on the cloud, seeking better system scalability and lower operating costs. Different from the conventional batch jobs, most of these applications consist of multiple stand-alone services that communicate with each other. These step-by-step operations unavoidably introduce higher latency to the delay-sensitive chained services. In this article, we aim at designing an optimization approach for reducing the latency of chained services. Specifically, presenting the measurement and analysis of chained services on Baidu's cloud platform, our real-world trace indicates that these chained services are suffering from significantly high latency because they are mostly handled by different queues on cloud servers for multiple times. However, such a unique feature introduces significant challenges to optimize a microservice's overall queueing delay. To address this problem, we propose a delay-guaranteed approach to accelerate the overall queueing of chained services while obtaining fairness across all the workloads. Our evaluations on Baidu servers shows that the proposed design can successfully reduce the latency of chained services by 35 percent with minimal impact on other workloads.

DBA scheme based on Load balance algorithm (LBA) and wavelength recycle mechanism (WRM) for multi-wavelength upstream transmission is proposed in this paper. According to 1 Gbps and 10 Gbps line rates, ONUs are grouped into different VPONs. To facilitate wavelength management, resource pool is proposed to record wavelength state. To realize quantitative analysis, a mathematical model describing metro-access network (MAN) environment is presented. To 10G-EPON upstream, load balance algorithm is designed to ensure load distribution fairness for 10G-OLTs. To 1G-EPON upstream, wavelength recycle mechanism is designed to share remained wavelengths. Finally, the effectiveness of the proposed scheme is demonstrated by simulation and analysis.

With the rapid development of science and technology, the internet has become a large media of information spread. There is a large quantity message on this platform. And online articles are the main form of information propagation. If the press can know what kind of articles will be more popular, they can construct an article that can help them spread the information they want to spread. Therefore, it’s very important to predict the popularity of these articles. Some models in machine learning could be applied to this problem. In this paper, it will introduce an approach based on Random Forest. To avoid too much calculation, the experiment first uses PCA to make dimension reduction. Then the model evaluation uses the ROC area values to assess the accuracy of the model. Its performance is better than CART and C4.5.

Background We aimed to develop novel diagnostic and prognostic signatures based on preoperative inflammatory, immunological, and nutritional parameters in blood (PIINPBs) by machine learning algorithms for patients with oral squamous cell carcinoma (OSCC). Methods A total of 486 OSCC patients and 200 age and gender-matched non-OSCC patients who were diagnosed and treated at our institution for noninfectious, nontumor diseases were retrospectively enrolled and divided into training and validation cohorts. Based on PIINPB, 6 machine learning classifiers including random forest, support vector machine, extreme gradient boosting, naive Bayes, neural network, and logistic regression were used to derive diagnostic models, while least absolute shrinkage and selection operator (LASSO) analyses were employed to construct prognostic signatures. A novel prognostic nomogram integrating a PIINPB-derived prognostic signature and selected clinicopathological parameters was further developed. Performances of these signatures were assessed by receiver operating characteristic (ROC) curves, calibrating curves, and decision tree. Results Diagnostic models developed by machine learning algorithms from 13 PIINPBs, which included counts of white blood cells (WBC), neutrophils (N), monocytes (M), lymphocytes (L), platelets (P), albumin (ALB), and hemoglobin (Hb), along with albumin-globulin ratio (A/G), neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), lymphocyte-monocyte ratio (LMR), systemic immune-inflammation index (SII), and prognostic nutritional index (PNI), displayed satisfactory discriminating capabilities in patients with or without OSCC, and among OSCC patients with diverse pathological grades and clinical stages. A prognostic signature based on 6 survival-associated PIINPBs (L, P, PNI, LMR, SII, A/G) served as an independent factor to predict patient survival. Moreover, a novel nomogram integrating prognostic signature and tumor size, pathological grade, cervical node metastasis, and clinical stage significantly enhanced prognostic power [3-year area under the curve (AUC) =0.825; 5-year AUC =0.845]. Conclusions Our results generated novel and robust diagnostic and prognostic signatures derived from PIINPBs by machine learning for OSCC. Performance of these signatures suggest the potential for PIINPBs to supplement current regimens and provide better patient stratification and prognostic prediction.