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In this work, we investigate the online MapReduce processing problem on mm uniform parallel machines, aiming at minimizing the makespan. Each job consists of two sets of tasks, namely, the map tasks and the reduce tasks. A job’s map tasks can be arbitrarily split and processed on different machines simultaneously, while its reduce tasks can only be processed after all its map tasks have been completed. We assume that the reduce tasks are preemptive, but cannot be processed on different machines in parallel. We provide a new lower bound for this problem and present an online algorithm with a competitive ratio of 2−1m2-\frac{1}{m} (mm is the number of machines) when the speeds of the machines are 1.

[Objective] In recent decades, with the rapid industrial growth and urbanization in China, pollution incidents like oil spills and heavy metal contamination have become frequent. Under this background, accurate assessment of the entire pollution process and control of polluted sites are crucial steps in achieving pollution site remediation and restoration. [Methods] This study adopts an object-based perspective and a systematic analysis approach to describe the migration of pollutants from source to sink, emphasizing the environmental behavior during their migration. It abstractly represents contaminated sites and associated entities as spatiotemporal objects, focusing on pollutant concentrations and their attributes. It also explores the interrelationships among spatiotemporal objects from temporal, spatial, and attribute perspectives, as well as describes their dynamic influences. [Results] (1) Taking the real incident of an oil spill in 2014 as an example, an object-based representation model of the contaminated site was constructed using the XML structure. (2) A visualization method for expressing contaminated site objects has been established, which displays the interrelationships and attribute characteristics of various spatiotemporal objects. (3) Attempts to apply the respresentation model to conduct attribution analysis of pollutant concentrations have been made, allowing for the rapid acquisition of relevant calculation parameters for exposure assessment indicators, thereby facilitating more convenient health risk evaluations. [Conclusion] The experimental results demonstrate that the proposed object-based representation method can effectively describe and model contaminated sites, facilitating the comprehensive analysis and evaluation of pollution processes from source to sink. It provides significant support for the management and remediation of contaminated sites. Furthermore, the object-based representation method proposed offers practical guidance in addressing complex problems. By considering the research subject as an object and analyzing and expressing it from various aspects such as composition, attribute features, interrelationships, and behavioral dynamics, a better understanding of the internal relationships and interactions within the research object can be achieved, thereby providing a clear perspective for the analysis and evaluation of related issues.

Cyclic di-adenosine monophosphate (c-di-AMP) is a bacterial second messenger that can be recognized by infected host cells and activate the immunoinflammatory response. The purpose of this study is to demonstrate the effect of c-di-AMP on the differentiation of human periodontal ligament stem cells (hPDLSCs) and its underlying mechanisms. In the present study, we find that the gingival crevicular fluid (GCF) of patients with chronic periodontitis has a higher expression level of c-di-AMP than that of healthy people. In vitro, c-di-AMP influences the differentiation of hPDLSCs by upregulating Toll-like receptors (TLRs); specifically, it inhibits osteogenic differentiation by activating NF-κB and ERK/MAPK and promotes adipogenic differentiation through the NF-κB and p38/MAPK signaling pathways. Inhibitors of TLRs or activated pathways reduce the changes induced by c-di-AMP. Our results establish the potential correlation among bacterial c-di-AMP, periodontal tissue homeostasis and chronic periodontitis pathogenesis.

Objective To systematically evaluate the efficacy and safety of Bifidobacteria in preventing caries. Methods Databases including PubMed, Embase, The Cochrane Library, Web of Science, Scopus, Clinicaltrials. gov, CNKI, WanFang Data and VIP were electronically searched from inception to April 2020 to collect randomized controlled trials of Bifidobacterium for caries. Meta-analysis was performed using Revman 5.4 software. Results In total, 10 randomized controlled trials (RCT) of 518 patients, including 262 in the test group and 256 in the control group, were included. Meta-analysis results reveal no statistically significant differences in salivary Streptococcus mutans counts (SMD=-0.31, 95%CI -0.66 to 0.04, P=0.08) (RR=0.53, 95%CI 0.17 to 1.66, P=0.28) and salivary Lactobacilli counts (SMD=-0.07, 95%CI -0.39 to 0.26, P=0.69) (RR=0.87, 95%CI 0.59 to 1.29, P=0.50). No statistical differences in the counts of Streptococcus mutans and Lactobacillus counts were noted in dental plaque, and no statistical difference in the occurrence of caries in deciduous teeth. Three of the 10 RCTS included in this study did not report adverse events, 5 had no adverse reactions, and 2 reported gastrointestinal discomfort.Conclusion Current evidence suggests that Bifidobacteria do not effectively reduce Streptococcus mutans counts and Lactobacillus counts in saliva and dental plaque, or reduce the occurrence of caries in deciduous teeth. The safety of this treatment also requires further investigation.

Mucositis is a common gastrointestinal complication in cancer patients undergoing chemoradiotherapy, including oral mucositis and gastrointestinal mucositis, with clinical manifestations of oral ulcers, vomiting, diarrhea and pain that seriously reduce the quality of life of patients and even affect anticancer therapy. Toll-like receptor (TLR) are important receptors involved in innate immunity and in the development of chemoradiation-induced mucositis by mediating the effect between microorganisms and the host. A comprehensive understanding of the role of TLR in mucositis is helpful to guide the prevention and treatment of mucositis. This paper reviews the available studies on TLR and mucositis. The results of the literature review indicate that different TLR have different roles in chemoradiation-induced mucositis: TLR2 is an important receptor in the inflammatory cascade of chemoradiation-induced mucositis; TLR4 activation can increase gastrointestinal mucosal inflammation and lead to oral epithelial ulceration; TLR5 agonists can reduce the degree of radiation-induced mucositis damage; and antagonizing or knocking out TLR9 can reduce chemoradiation-induced gastrointestinal mucositis. However, no TLR agonists or inhibitors have yet been applied in clinical practice, and additional studies are needed to explore the role of different TLR in mucositis in the future to provide a reference for the precise prevention and treatment of chemoradiation-induced mucositis.