Herpes labialis remains exceedingly prevalent and is one of the most common human viral infections throughout the world. Recurrent herpes labialis evolves from the initial viral infection by herpes simplex virus type 1 (HSV-1) which subsequently presents with or without symptoms. Reactivation of this virus is triggered by psychosocial factors such as stress, febrile environment, ultraviolet light susceptibility, or specific dietary inadequacy. This virus infection is also characterized by uninterrupted transitions between chronic-latent and acute-recurrent phases, allowing the virus to opportunistically avoid immunity and warrant the transmission to other vulnerable hosts simultaneously. This review comprehensively evaluates the current evidence on epidemiology, pathogenesis, transmission modes, clinical manifestations, and current management options of herpes labialis infections.

Whether “periodontal disease” can be considered as an independent risk factor for head and neck cancer (HNC) remains controversial. The aim of the current meta-analysis was to quantitatively assess this relationship in order to determine whether this represents a true risk factor, with implications for cancer prevention and management. PubMed, Scopus, and Embase databases were systematically searched. Selective studies were reviewed, and meta-analysis was performed to estimate the pooled odds ratio (OR) with 95% confidence intervals (CIs) on eligible studies using a random effects model. In total, 21 eligible observational studies (4 cohorts and 17 case-controls) were identified for qualitative synthesis after a review of 1051 articles. Significant heterogeneity could be identified in measures utilized for reporting of periodontal disease. Meta-analysis performed on nine studies that employed objective measures for reporting periodontal disease demonstrated a significant association between periodontal disease and HNC [OR 3.17, 95% CI, 1.78–5.64]. A diseased periodontium represents an independent risk marker, and a putative risk factor, for HNC. Prospective studies with standardized measures of periodontal disease severity and extent, integrated with microbiological and host susceptibility facets, are needed to elucidate the mechanisms of this positive association and whether treatment of the former influences the incidence and outcomes for HNC.

Zoonotic infections by avian influenza viruses occur at the human–poultry interface, but the modes of transmission have not been fully investigated. We assessed the potential for airborne and fomite transmission at live poultry markets in Guangzhou city and in Hong Kong Special Administrative Region (SAR), China, during 2014 and 2015. Viral genome and infectious avian influenza A viruses of H5N6, H7N9, and H9N2 subtypes were detected predominantly from particles larger or equal to 1 μm in diameter in the air sampled with cyclone-based bioaerosol samplers at the live poultry markets in Guangzhou. Influenza A(H9N2) viruses were ubiquitously isolated every month during the study period from air and environmental swabs, and different lineages of H9N2 virus were isolated from markets where chickens and minor land-based poultry were sold. The use of de-feathering devices increased the quantity of virus-laden airborne particles while market closure reduced the amount of such particles. The results highlight the possibility of airborne transmission of avian influenza viruses among poultry or from poultry to humans within such settings. This may explain epidemiological observations in which some patients with H7N9 infection reported being in markets but no direct contact with live poultry or poultry stalls.

We present NNrepair, a constraint-based technique for repairing neural network classifiers. The technique aims to fix the logic of the network at an intermediate layer or at the last layer. NNrepair first uses fault localization to find potentially faulty network parameters (such as the weights) and then performs repair using constraint solving to apply small modifications to the parameters to remedy the defects. We present novel strategies to enable precise yet efficient repair such as inferring correctness specifications to act as oracles for intermediate layer repair, and generation of experts for each class. We demonstrate the technique in the context of three different scenarios: (1) Improving the overall accuracy of a model, (2) Fixing security vulnerabilities caused by poisoning of training data and (3) Improving the robustness of the network against adversarial attacks. Our evaluation on MNIST and CIFAR-10 models shows that NNrepair can improve the accuracy by 45.56% points on poisoned data and 10.40% points on adversarial data. NNrepair also provides small improvement in the overall accuracy of models, without requiring new data or re-training.

Objective: While some oral carcinomas appear to arise de novo, others develop within long-standing conditions of the oral cavity that have malignant potential, now known as oral potentially malignant disorders (OPMDs). The oral bacteriome associated with OPMD has been studied to a lesser extent than that associated with oral cancer. To characterize the association in detail we compared the bacteriome in whole mouth fluid (WMF) in patients with oral leukoplakia, oral cancer and healthy controls. Methods: WMF bacteriome from 20 leukoplakia patients, 31 patients with oral cancer and 23 healthy controls were profiled using the Illumina MiSeq platform. Sequencing reads were processed using DADA2, and taxonomical classification was performed using the phylogenetic placement method. Sparse Partial Least Squares Regression Discriminant Analysis model was used to identify bacterial taxa that best discriminate the studied groups. Results: We found considerable overlap between the WMF bacteriome of leukoplakia and oral cancer while a clearer separation between healthy controls and the former two disorders was observed. Specifically, the separation was attributed to 14 taxa belonging to the genera Megaspheara, unclassified enterobacteria, Prevotella, Porphyromonas, Rothia and Salmonella, Streptococcus, and Fusobacterium. The most discriminative bacterial genera between leukoplakia and oral cancer were Megasphaera, unclassified Enterobacteriae, Salmonella and Prevotella. Conclusion: Oral bacteria may play a role in the early stages of oral carcinogenesis as a dysbiotic bacteriome is associated with oral leukoplakia and this resembles that of oral cancer more than healthy controls. Our findings may have implications for developing oral cancer prevention strategies targeting early microbial drivers of oral carcinogenesis.

The past decade has witnessed a surge in epidemiological studies that have explored the relationship between the oral microbiome and oral cancer. Owing to the diversity of the published data, a comprehensive systematic overview of the currently available evidence is critical. This review summarises the current evidence on the metagenomic studies on the oral microbiome in oral cancer. A systematic search was conducted in Medline and Embase databases to identify original studies examining the differences in the oral microbiome of oral cancer cases and controls. A total of twenty-six studies were identified that reported differences in microbial abundance between oral squamous cell carcinoma (OSCC) and controls. Although almost all the studies identified microbial dysbiosis to be associated with oral cancer, the detailed qualitative analysis did not reveal the presence/abundance of any individual bacteria or a consortium to be consistently enriched in OSCC samples across the studies. Interestingly, few studies reported a surge of periodontopathogenic taxa, especially Fusobacteria, whereas others demonstrated a depletion of commensal taxa Streptococci. Considerable heterogeneity could be identified in the parameters used for designing the studies as well as reporting the microbial data. If microbiome data needs to be translated in the future, to complement the clinical parameters for diagnosis and prognosis of oral cancer, further studies with the integration of clinical variables, adequate statistical power, reproducible methods, and models are required.