The bidirectional relationship between periodontal disease and pregnancy via the interaction of oral microorganisms, hormone and immune response

Periodontal disease has been suggested to be linked to adverse pregnancy outcomes such as preterm birth, low birth weight, and preeclampsia. Adverse pregnancy outcomes are a significant public health issue with important clinical and societal repercussions. This article systematically reviews the available epidemiological studies involving the relationship between periodontal disease and adverse pregnancy outcomes over the past 15 years, and finds a weak but independent association between adverse pregnancy outcomes and periodontal disease. The bidirectional association and the potential mechanisms are then explored, focusing on three possible mechanisms: inflammatory reaction, oral microorganisms and immune response. Specifically, elevated systemic inflammation and increased periodontal pathogens with their toxic products, along with a relatively suppressed immune system may lead to the disruption of homeostasis within fetal-placental unit and thus induce adverse pregnancy outcomes. This review also explains the possible mechanisms around why women are more susceptible to periodontal disease. In conclusion, pregnant women are more likely to develop periodontal disease due to hormonal changes, and periodontal disease has also been suspected to increase the incidence of adverse pregnancy outcomes. Therefore, in order to lessen the risk of adverse pregnancy outcomes, both obstetricians and dentists should pay attention to the development of periodontal diseases among women during pregnancy

Wireless, battery-free optoelectronic systems as subdermal implants for local tissue oximetry

Monitoring regional tissue oxygenation in animal models and potentially in human subjects can yield insights into the underlying mechanisms of local O2-mediated physiological processes and provide diagnostic and therapeutic guidance for relevant disease states. Existing technologies for tissue oxygenation assessments involve some combination of disadvantages in requirements for physical tethers, anesthetics, and special apparatus, often with confounding effects on the natural behaviors of test subjects. This work introduces an entirely wireless and fully implantable platform incorporating (i) microscale optoelectronics for continuous sensing of local hemoglobin dynamics and (ii) advanced designs in continuous, wireless power delivery and data output for tether-free operation. These features support in vivo, highly localized tissue oximetry at sites of interest, including deep brain regions of mice, on untethered, awake animal models. The results create many opportunities for studying various O2-mediated processes in naturally behaving subjects, with implications in biomedical research and clinical practice.Center for Bio-Integrated Electronics at Northwestern University; Soft and Hybrid Nanotechnology Experimental (SHyNE) Resource (NSF) [ECCS-1542205]; Materials Research Science and Engineering Center [DMR-1720139]; State of Illinois; Northwestern University; Developmental Therapeutics Core at Northwestern University; Robert H. Lurie Comprehensive Cancer Center [NCI CA060553]Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Assessment of Time to Clinical Response, a Proxy for Discharge Readiness, among Hospitalized Patients with Community-Acquired Pneumonia Who Received either Ceftaroline Fosamil or Ceftriaxone in Two Phase III FOCUS Trials

ABSTRACT The primary driver of health care costs for patients with community-acquired pneumonia (CAP) is the hospital length of stay (LOS). Unfortunately, hospital LOS comparisons are difficult to make from phase III CAP trials because of their structured designs and prespecified treatment durations. However, an opportunity still exists to draw inferences about potential LOS differences between treatments through the use of surrogates for hospital discharge. The intent of this study was to quantify the time to a clinical response, a proxy for the time to discharge readiness, among hospitalized CAP patients who received either ceftaroline or ceftriaxone in two phase III CAP FOCUS clinical trials. On the basis of the Infectious Diseases Society of America and American Thoracic Society CAP management guidelines and recent FDA guidance documents for community-acquired bacterial pneumonia, a post hoc adjudication algorithm was constructed a priori to compare the time to a clinical response, a proxy for the time to discharge readiness, between patients who received ceftaroline or ceftriaxone. Overall, 1,116 patients (ceftaroline, n = 562; ceftriaxone, n = 554) from the pooled FOCUS trials met the selection criteria for this analysis. Kaplan-Meier analyses showed that ceftaroline was associated with a shorter time, measured in days, to meeting the clinical response criteria ( P = 0.03). Of the patients on ceftaroline, 61.0, 76.1, and 83.6% achieved a clinical response by days 3, 4, and 5, compared to 54.3, 69.8, and 79.3% of the ceftriaxone-treated patients. In the Cox regression, ceftaroline was associated with a shorter time to a clinical response (HR, 1.16, P = 0.02). The methodology employed here provides a framework to draw comparative effectiveness inferences from phase III CAP efficacy trials. (The FOCUS trials whose data were analyzed in this study have been registered at ClinicalTrials.gov under registration no. NCT00621504 and NCT00509106.

A Small Molecule Antagonist of SMN Disrupts the Interaction Between SMN and RNAP II

Survival of motor neuron (SMN) functions in diverse biological pathways via recognition of symmetric dimethylarginine (Rme2s) on proteins by its Tudor domain, and deficiency of SMN leads to spinal muscular atrophy. Here we report a potent and selective antagonist with a 4-iminopyridine scaffold targeting the Tudor domain of SMN. Our structural and mutagenesis studies indicate that both the aromatic ring and imino groups of compound 1 contribute to its selective binding to SMN. Various on-target engagement assays support that compound 1 specifically recognizes SMN in a cellular context and prevents the interaction of SMN with the R1810me2s of RNA polymerase II subunit POLR2A, resulting in transcription termination and R-loop accumulation mimicking SMN depletion. Thus, in addition to the antisense, RNAi and CRISPR/Cas9 techniques, potent SMN antagonists could be used as an efficient tool to understand the biological functions of SMN

Hydrodynamic dead zone in multiphase geophysical flows impacting a rigid obstacle

When a gravity-driven solid-fluid mixture, such as those in geophysical flows, hits a wall-like rigid obstacle, a metastable jammed zone called hydrodynamic dead zone (HDZ) may emerge. The unjammed-jammed transition of HDZ, controlled by the intricate interactions among the obstacle, the fluid and the solid of the flow, remains an open issue to be quantified for thorough understanding its underlying physics and mechanics. This study employs a coupled Computational Fluid Dynamics and Discrete Element Method (CFD-DEM) to examine the characteristics of HDZ formed when a geophysical flow comprised of gap-graded particles and a viscous liquid impacts an obstacle. To identify key features in the zonation of HDZ, a modified granular temperature is proposed considering the influences of inherent polydispersity and both translational and rotational motions of the particles in the impacting mixture. A source-sink model is further established to offer an interpretation of the nonlinear energy dissipation process during the unjammed-jammed transition of HDZ, where the modified granular temperature serves as a function of either time or distance. The structural anisotropy is found to serve as a good indicator for illuminating the flow-structure interaction transitions. Three regimes, namely, impact-up, roll-up and heap-up regimes, have been identified according to the statistical energy conversion and dissipation in the flowing layer upon the HDZ. The influence of particle rotation is found to be more significant in the dynamical exchange of HDZ when the impacting flow contains a wider polydispersity. (c) 2021 Elsevier B.V. All rights reserved

Assessing debris flow impact on flexible ring net barrier: A coupled CFD-DEM study

Flexible ring net barriers have become increasingly popular in practical mitigation of debris flow worldwide. Systematic assessments of their response and performance subjected to the impact of realistic debris flows remain challenging. This study presents a novel computational approach based on coupled CFD-DEM to model the impact of debris flow on a flexible ring net barrier in a unified framework. The debris flow is treated as a solid-fluid mixture, where the solid phase and the fluid phase are modeled by DEM and CFD, respectively. The barrier is simulated as a system of different deformable components, including rings, cables and energy dissipators, and is modeled with DEM. The proposed method expedites a convenient, unified consideration of multi-way interactions among the debris solid, the debris fluid, and the barrier. The simulation of a flexible barrier is calibrated against existing experimental data and past numerical results, by examining the quasi-static responses of different barrier components and the dynamic reactions of the entire barrier. The barrier system is further subjected to the impact of debris flows with different Froude numbers to examine its performance, in terms of its retaining capacity of debris mass and peak sustained forces in the barrier. Two energy-related indices, energy dissipation ratio and energy absorption ratio, are estimated for design reference. The study provides a novel, physically based predictive computational tool for future design and analysis of flexible ring net barriers in debris flow mitigation

Optimized Dispatching Method for Flexibility Improvement of AC-MTDC Distribution Systems Considering Aggregated Electric Vehicles

With the increasing use of renewable resources and electric vehicles (EVs), the variability and uncertainty in their nature put forward a high requirement for flexibility in AC distribution system incorporating voltage source converter (VSC) based multi-terminal direct current (MTDC) grids. In order to improve the capability of distribution systems to cope with uncertainty, the flexibility enhancement of AC-MTDC distribution systems considering aggregated EVs is studied. Firstly, the charging and discharging model of one EV is proposed considering the users' demand difference and traveling needs. Based on this, a vehicle-to-grid (V2G) control strategy for aggregated EVs to participate in the flexibility promotion of distribution systems is provided. After that, an optimal flexible dispatching method is proposed to improve the flexibility of power systems through cooperation of VSCs, controllable distributed generations (CDGs), aggregated EVs, and energy storage systems (ESSs). Finally, a case study of an AC-MTDC distribution system is carried out. Simulation results show that the proposed dispatching method is capable of effectively enhancing the system flexibility, reducing renewable power curtailment, decreasing load abandonment, and cutting down system cost

Experimental study on light induced influence model to mice using support vector machine

Previous researchers have made studies on different influences created by light irradiation to animals, including retinal damage, changes of inner index and so on. However, the model of light induced damage to animals using physiological indicators as features in machine learning method is never founded. This study was designed to evaluate the changes in micro vascular diameter, the serum absorption spectrum and the blood flow influenced by light irradiation of different wavelengths, powers and exposure time with support vector machine (SVM). The micro images of the mice auricle were recorded and the vessel diameters were calculated by computer program. The serum absorption spectrums were analyzed. The result shows that training sample rate 20% and 50% have almost the same correct recognition rate. Better performance and accuracy was achieved by third-order polynomial kernel SVM quadratic optimization method and it worked suitably for predicting the light induced damage to organisms

A Moving Target Tracking Framework Based on a Set and Its Topological Space

Moving target tracking is a technology that matches frames and images based on target characteristics. This technology is widely utilized in intelligent transportation, logistics transportation, public security, sports event broadcasting, and other fields. Existing research focuses primarily on improving target detection and tracking algorithms to improve target retrieval and tracking efficiency. However, the majority of studies focus on global and full-range retrieval. More importantly, in large video scenes with multiple camera collaborations, these methods rarely consider the efficiency of target retrieval and tracking. Based on relevant theories and methods of video GIS, set theory, and topology, in this paper, a set and its topology space covering road networks, cameras, videos, and key frames were constructed. Additionally, the positioning, tracking, and track representation of a moving target based on the set and its topology space were solved. Compared to the feature vector algorithm, video summarization and Meanshift algorithm, the experimental findings reveal that the target retrieval performance, algorithm stability, and robustness are improved