The effect of the “Oral-Gut” axis on periodontitis in inflammatory bowel disease: A review of microbe and immune mechanism associations

Periodontitis and inflammatory bowel diseases (IBD) are inflammatory diseases of the gastrointestinal tract that share common features of microbial-induced ecological dysregulation and host immune inflammatory response. The close relationship between periodontitis and IBD is characterized by a higher prevalence of IBD in patients with periodontitis and a higher prevalence and severity of periodontitis in patients with IBD, indicating that periodontitis and IBD are different from the traditional independent diseases and form an “Oral-Gut” axis between the two, which affect each other and thus form a vicious circle. However, the specific mechanisms leading to the association between the two are not fully understood. In this article, we describe the interconnection between periodontitis and IBD in terms of microbial pathogenesis and immune dysregulation, including the ectopic colonization of the gut by pathogenic bacteria associated with periodontitis that promotes inflammation in the gut by activating the host immune response, and the alteration of the oral microbiota due to IBD that affects the periodontal inflammatory response. Among the microbial factors, pathogenic bacteria such as Klebsiella, Porphyromonas gingivalis and Fusobacterium nucleatum may act as the microbial bridge between periodontitis and IBD, while among the immune mechanisms, Th17 cell responses and the secreted pro-inflammatory factors IL-1β, IL-6 and TNF-α play a key role in the development of both diseases. This suggests that in future studies, we can look for targets in the “Oral-Gut” axis to control and intervene in periodontal inflammation by regulating periodontal or intestinal flora through immunological methods

Evaluating cardiac disorders associated with triazole antifungal agents based on the US Food and Drug Administration Adverse Event reporting system database

IntroductionTriazole antifungal agents are widely used to treat and prevent systemic mycoses. With wide clinical use, the number of reported adverse events has gradually increased. The aim of this study was to analyze the cardiac disorders associated with TAAs (fluconazole, voriconazole, itraconazole, posaconazole and isavuconazole) based on data from the US Food and Drug Administration Adverse Event Reporting System FDA Adverse Event Reporting System.MethodsData were extracted from the FAERS database between the first quarter of 2004 and third quarter of 2022. The clinical characteristics in TAA-associated cardiac AE reports were analyzed. Disproportionality analysis was performed to evaluate the potential association between AEs and TAAs using the reporting odds ratio (ROR) and proportional reporting ratio (PRR).ResultsAmong 10,178,522 AE reports, 1719 reports were TAA-associated cardiac AEs as primary suspect drug. Most reports were related to fluconazole (38.34%), voriconazole (28.56%) and itraconazole (26.76%). Itraconazole (N = 195, 42.39%) and isavuconazole (N = 2, 14.29%) had fewer serious outcome events than three other drugs including fluconazole, voriconazole, and posaconazole. 13, 11, 26, 5 and 1 signals were detected for fluconazole, voriconazole, itraconazole, posaconazole and isavuconazole, respectively. The number of new signals unrecorded in the drug label was 9, 2, 13, 2 and 0 for fluconazole, voriconazole, itraconazole, posaconazole and isavuconazole, respectively.ConclusionIsavuconazole might be the safest of the five TAAs for cardiac AEs. TAA-associated cardiac disorders may result in serious adverse outcomes. Therefore, in addition to AEs on the drug label, we should pay attention to new AEs unrecorded on the drug label during the clinical use of TAAs

Channel Estimation for MmWave Massive MIMO with Hybrid Precoding Based on Log-Sum Sparse Constraints

Channel estimation is essential for millimeter-wave (mmWave) multiple-input multiple-output (MIMO) systems with hybrid precoding. However, accurate channel estimation is a challenging task as the number of antennas is huge, while the number of RF chains is limited. Traditional methods of compressed sensing for channel estimation lead to serious loss of accuracy due to channel angle quantization. In this paper, we propose a new iterative reweight-based log-sum constraint channel estimation scheme. Specifically, we exploit the structure sparsity of the mmWave channels by formulating the channel estimation problem as an objective optimization problem. We utilize the log-sum as a constraint, via optimizing an objective function through the gradient descent method, the proposed algorithm can iteratively move the channel estimated angle-ofarrivals (AOAs) and angle-of-departures (AODs) towards the optimal solutions, and finally improve the angle estimation performance significantly. In addition, to ensure the accuracy of channel estimation, we introduce a dynamic regularization factor to control the tradeoff between the channel sparsity and the data fitting error. Numerical experiments demonstrate that the proposed algorithm achieves better convergence behavior than conventional sparse signal recovery solutions

Designing robust schedule coordination scheme for transit networks with safety control margins

We propose a robust schedule coordination scheme which combines timetable planning with a semi-flexible departure delayed control strategy in case of disruptions. The flexibility is provided by allowing holding for the late incoming bus within a safety control margin (SCM). In this way, the stochastic travel time is addressed by the integration of real-time control and slacks at the planning phase. The schedule coordination problem then jointly optimises the planning headways and slack times in the timetable subject to SCM. Analytical formulations of cost functions are derived for three types of operating modes: uncoordinated operation, departure punctual control and departure delayed control. The problem is formulated as a stochastic mixed integer programming model and solved by a branch-and-bound algorithm. Numerical results provide an insight into the interaction between SCM and slack times, and demonstrate that the proposed model leads to cost saving and higher efficiency when SCM is considered. Compared to the conventional operating modes, the proposed method also presents advantages in transfer reliability and robustness to delay and demand variation

Model and Algorithm of Regional Bus Scheduling with Grey Travel Time

The regional bus scheduling is the future trend of urban public transport development. It focuses on assigning trips belonged to several routes to buses located at different depots to reduce fleet size and operating costs. With consideration of the emergencies in reality interfering with vehicles to complete a trip on time, this paper studies regional bus scheduling problem with grey travel time to meet some side constraints such as multi-vehicle-type, depots capacities and fuelling, etc. The model is resolved by the improved ant colony algorithm to prepare a lowest-cost scheduling scheme. The proposed scheduling method is easily operated and can be used for different situations. At the last section, an example proves the correctness and effectiveness of the model and algorithm

Model and Algorithm of Regional Bus Scheduling with Grey Travel Time

The regional bus scheduling is the future trend of urban public transport development. It focuses on assigning trips belonged to several routes to buses located at different depots to reduce fleet size and operating costs. With consideration of the emergencies in reality interfering with vehicles to complete a trip on time, this paper studies regional bus scheduling problem with grey travel time to meet some side constraints such as multi-vehicle-type, depots capacities and fuelling, etc. The model is resolved by the improved ant colony algorithm to prepare a lowest-cost scheduling scheme. The proposed scheduling method is easily operated and can be used for different situations. At the last section, an example proves the correctness and effectiveness of the model and algorithm

A Bi-level Programming Model for Uncertain Regional Bus Scheduling Problems

Regional bus scheduling is the future trend in public transportation which deals with allocating trips belonged to several routes to buses located at different depots to reduce the size of bus fleets and their operating costs. Considering many emergency events which may affect on-time vehicle arrivals, a bi-level programming model is applied to address the relationship between bus scheduling and its procurement scheme from an overall perspective. The model takes into consideration several constraints such as depot capacities, fueling, and emissions of polluting gases. Solutions to different situations of the upper and lower model are obtained by using a genetic algorithm. Based on some established criteria for a satisfactory solution, a series of lower solutions meeting the established criteria are generated as inputs for the upper model. Thereby, the best lower and the corresponding upper solutions are generated by comparing them. Finally, an example is illustrated to prove the accuracy and effectiveness of our model and its algorithm

Semi-parametric adjustment model methods for positioning of seafloor control point

This paper focuses on solving the problem of seafloor control point absolute positioning with low vertical accuracy based on the survey ship sailing circle. The method of dealing with the systematic error based on semi-parametric adjustment model was proposed. Firstly, the influence of sound speed change on ranging error is analyzed. Secondly, a semi-parametric adjustment model for determining three-dimensional coordinates of underwater control points was established. And respectively proposed solutions under two different conditions, the observation duration is an integral multiple or non-integer multiple of the long-period term of the ranging error. Simulation experiment results show that this method can obviously improve the accuracy of vertical solution of seafloor control point compared with difference technique and least square method when internal waves exist and observation duration is less than an integer multiple of the long-period term of the ranging error

Study on Low Temperature Oxidation Characteristics of Oil Shale Based on Temperature Programmed System

Oil shale is a kind of high-combustion heat mineral, and its oxidation in mining and storage are worth studying. To investigate the low-temperature oxidation characteristics of oil shale, the temperature, CO, alkane and alkene gases were analyzed using a temperature-programmed device. The results showed that the temperature of oil shale underwent three oxidation stages, namely a slow low-temperature oxidation stage, a rapid temperature-increasing oxidation stage, and a steady temperature-increasing stage. The higher the air supply rate is, the higher the crossing point temperature is. Similar to coal, CO also underwent three stages, namely a slow low-temperature oxidation stage, a rapid oxidation stage, and a steady increase stage. However, unlike coal, alkane and alkene gases produced by oil shale underwent four stages. They all had a concentration reduction stage with the maximum drop of 24.20%. Statistical classification of inflection temperature of various gases as their concentrations change showed that the temperature of 140 °C is the key temperature for group reactions, and above the temperature of 140 °C, all alkane and alkene gases underwent the rapid concentration increase stage