5,11-Dimethyl­dibenzo[b,f][1,5]diazocine-6,12(5H,11H)-dione

In the mol­ecule of the title compound, C16H14N2O2, an N,N′-dimethyl­dianthranilide, the two methyl groups are disordered over two positions; site occupation factors were kept fixed as 0.75:0.25 and 0.65:0.35. The dihedral angle between the two benzene rings is 75.57 (3)°

Molecular Mechanisms Leading from Periodontal Disease to Cancer

Periodontitis is prevalent in half of the adult population and raises critical health concerns as it has been recently associated with an increased risk of cancer. While information about the topic remains somewhat scarce, a deeper understanding of the underlying mechanistic pathways promoting neoplasia in periodontitis patients is of fundamental importance. This manuscript presents the literature as well as a panel of tables and figures on the molecular mechanisms of Porphyromonas gingivalis and Fusobacterium nucleatum, two main oral pathogens in periodontitis pathology, involved in instigating tumorigenesis. We also present evidence for potential links between the RANKL–RANK signaling axis as well as circulating cytokines/leukocytes and carcinogenesis. Due to the nonconclusive data associating periodontitis and cancer reported in the case and cohort studies, we examine clinical trials relevant to the topic and summarize their outcome

Differential Expression of Ovine Innate Immune Genes by Preterm and Neonatal Lung Epithelia Infected with Respiratory Syncytial Virus

Preterm infants have increased susceptibility to severe manifestations of respiratory syncytial virus (RSV) infection. The cause(s) for this age-dependent vulnerability is/are not well-defined, but alterations in innate immune products have been implicated. In sheep, RSV disease severity has similar age-dependent characteristics and sheep have several related innate molecules for study during pulmonary infection including surfactant protein A (SP-A), surfactant protein D (SP-D), sheep beta defensin 1 (SBD1), monocyte chemotactic protein 1 (MCP1), and Toll-like receptor 4 (TLR4). However, the in vivo cellular gene expression as a response to RSV infection is poorly understood. In this study, the effect of RSV infection on expression of these innate immune genes was determined for bovine RSV-infected (bRSV+ fluorescence) epithelial cells, adjacent cells lacking bRSV antigen (adjoining cells lacking fluorescence), and control cells from non-infected lung using laser capture microdissection (LCM) and real-time RT-PCR. Control lambs had increased expression of innate immune molecules in full term (term) compared to preterm epithelia with statistical significance in SBD1, SP-D, and TLR4 mRNA. Infected cells (bRSV+ fluorescent cells) had consistently higher mRNA levels of SP-A (preterm and term), MCP1 (preterm and term), and SP-D (preterm). Interestingly, bRSV- cells of infected term lambs had significantly reduced SP-D mRNA expression compared to bRSV+ and control epithelia, suggesting that RSV infected cells may regulate the adjacent epithelial SP-D expression. This study defines specific innate immune components (e.g., SBD1, SP-D, and TLR4) that have differential age-dependent expression in the airway epithelia. Furthermore, cellular bRSV infection enhanced certain innate immune components while suppressing adjacent cellular SP-D expression in term animals. These in vivo gene expression results provide a framework for future studies on age-dependent susceptibility to RSV and RSV pathogenesis

Tailoring complexity metrics for simulink models

The size and complexity of Simulink models is constantly increasing, just as the systems which they represent. Therefore, it is beneficial to control them already at the design phase. In this paper we establish a set of complexity metrics for Simulink models to capture diverse aspects of complexity by proposing new and redefining existing metrics. To evaluate the applicability of our metrics, we compare them with the closed-source metric proposed by Mathworks. Moreover, through a case study from the automotive domain, we relate such metrics to quality attributes as determined by domain experts, and correlate them to known faults. Preliminary assessment suggests that complexity is closely related to analysability, understandability, and testability

Types and characteristics of urban and peri-urban green spaces having an impact on human mental health and wellbeing: a systematic review

Green spaces have been put forward as contributing to good mental health. In an urban context, space is a scarce resource while urbanisation and climate change are increasingly putting pressure on existing urban green space infrastructures and increasing morbidity caused by mental health disorders. Policy makers, designers, planners and other practitioners face the challenge of designing public open spaces as well as preserving and improving natural resources that are important for maintaining and optimizing human wellbeing. Knowing which types of blue and green spaces, with which characteristics, are most beneficial for mental health and wellbeing is critical. EKLIPSE received a request from the Ministry in charge of the Environment of France (MTES) to review: “Which types of urban and peri‐urban green and blue spaces, and which characteristics of such spaces, have a significant impact on human mental health and wellbeing?”. After a preliminary scoping, a decision was made to perform two systematic reviews (SR) assessing the specific types and characteristics of blue space (SR1) and green space (SR2) with respect to mental health and wellbeing. This report presents the systematic review for green space (SR2)

Does nasal surgery improve multilevel surgical outcome in obstructive sleep apnea:A multicenter study on 735 patients

Objective Does nasal surgery affect multilevel surgical success outcome. Methods Prospective eight country nonrandomized trial of 735 obstructive sleep apnea (OSA) patients, who had multilevel palate and/or tongue surgery, divided into two groups, with or without nose surgery. Results There were 575 patients in nose group, 160 patients in no nose group. The mean age for nose group 44.6 ± 11.4, no nose group 44.2 ± 11.8. Mean preoperative BMI for nose group 27.5 ± 3.6, no nose group 27.5 ± 4.1, mean postoperative BMI nose group 26.3 ± 3.7, no nose group 27.1 ± 3.8 (P = .006). Mean preoperative AHI nose group 32.7 ± 19.4, no nose group 34.3 ± 25.0 (P = .377); and mean postoperative AHI nose group 13.5 ± 10.2, no nose group 17.1 ± 16.0 (P = .001). Mean preoperative ESS nose group was 11.3 ± 4.7, no nose group was 10.4 ± 5.4 (P = .051); and mean postoperative ESS nose group was 5.3 ± 3.2, no nose group was 6.7 ± 2.8 (P = .001). The nose group had higher percentage change (adjusted for age, gender, BMI) in AHI (33.7%, 95% CI 14% to 53.5%) compared to the no nose group (P = .001); the nose group also had more percentage change in ESS (37%, 95% CI 23.6% to 50.3%) compared to the no nose group (P < .001). Change in BMI did not affect AHI nor ESS change (Cohen effect 0.03 and 0.14, respectively). AHI change in both groups were also statistically significant in the mild OSA (P = .008) and the severe OSA (P = .01). Success rate of surgery for the nose group 68.2%, while the no nose group 55.0% (P = .002). Conclusion Combining nose surgery in multilevel surgery improves surgical success. Level of evidence IIC

Objective comparison of methods to decode anomalous diffusion

Deviations from Brownian motion leading to anomalous diffusion are found in transport dynamics from quantum physics to life sciences. The characterization of anomalous diffusion from the measurement of an individual trajectory is a challenging task, which traditionally relies on calculating the trajectory mean squared displacement. However, this approach breaks down for cases of practical interest, e.g., short or noisy trajectories, heterogeneous behaviour, or non-ergodic processes. Recently, several new approaches have been proposed, mostly building on the ongoing machine-learning revolution. To perform an objective comparison of methods, we gathered the community and organized an open competition, the Anomalous Diffusion challenge (AnDi). Participating teams applied their algorithms to a commonly-defined dataset including diverse conditions. Although no single method performed best across all scenarios, machine-learning-based approaches achieved superior performance for all tasks. The discussion of the challenge results provides practical advice for users and a benchmark for developers