Background/Objectives: Periodontitis is caused by bacterial plaque. The oral microflora may interact with the intestinal microflora and play a role in the development of periodontitis. The periodontal inflamed surface area (PISA) has been shown to be a useful indicator of periodontal disease related to systemic diseases; however, few studies have shown an association between PISA and the bacterial flora. This study aimed to determine the association between PISA and oral and intestinal bacteria. Methods: Participants were recruited between 2018 and 2021 at the Medical and Dental Collaboration Center of Kanagawa Dental University Hospital. A periodontal clinical examination was performed, and the PISA was calculated. Salivary tests were conducted, and leukocyte scores in the saliva were calculated. Moreover, 16S rRNA amplicon sequencing was performed using saliva and stool samples to analyze oral and intestinal bacteria, respectively. Results: Higher PISA levels resulted in an increased presence of Bacteroides and a decreased presence of Proteobacteria and Actinobacteria in the saliva. An increase in Bacteroides was detected in the saliva of patients with high leukocyte scores. No correlation was observed between PISA and intestinal bacteria. Conclusions: Bacteroides was highly abundant in the saliva of patients with worsened periodontal conditions, as indicated by PISA. No association was found between PISA and intestinal bacteria.

Periodontal disease (PerioD) is a chronic inflammatory disease of dysbiotic etiology. Animal models and few human data showed a relationship between oral bacteria and gut dysbiosis. However, the effect of periodontal inflammation and subgingival dysbiosis on the gut is unknown. We hypothesized that periodontal inflammation and its associated subgingival dysbiosis contribute to gut dysbiosis even in subjects free of known gut disorders. We evaluated and compared elderly subjects with Low and High periodontal inflammation (assessed by Periodontal Inflamed Surface Area (PISA)) for stool and subgingival derived bacteria (assayed by 16S rRNA sequencing). The associations between PISA/subgingival dysbiosis and gut dysbiosis and bacteria known to produce short-chain fatty acid (SCFA) were assessed. LEfSe analysis showed that, in Low PISA, species belonging to Lactobacillus, Roseburia, and Ruminococcus taxa and Lactobacillus zeae were enriched, while species belonging to Coprococcus, Clostridiales, and Atopobium were enriched in High PISA. Regression analyses showed that PISA associated with indicators of dysbiosis in the gut mainly reduced abundance of SCFA producing bacteria (Radj = -0.38, p = 0.03). Subgingival bacterial dysbiosis also associated with reduced levels of gut SCFA producing bacteria (Radj = -0.58, p = 0.002). These results suggest that periodontal inflammation and subgingival microbiota contribute to gut bacterial changes.

Introduction Through plausible biological mechanisms, periodontitis causes systemic inflammatory burden and response, thus resulting in damage far beyond the oral cavity. Studies have demonstrated periodontitis to be a significant risk factor for coronary heart disease (CHD) and stroke. The larger the quantum of periodontal inflamed tissue, the greater the chances of periodontitis eliciting bacteremia and systemic inflammatory responses. Studies have reported that periodontitis and other common oral infections play an important role in the development of atherosclerosis. Therefore, the quantity of inflamed periodontal tissue assumes significance in determining the severity of atherosclerosis. Hence, this study investigates the impact of periodontal inflamed surface area (PISA) on the severity of coronary atherosclerosis. Materials and methods In this cross-sectional study, a total of 160 patients who presented at the department of periodontics of The British University in Egypt (BUE) from 1 January 2023 to 30 September 2023 were enrolled. Patients were only enrolled if they had undergone coronary angiography within the last six months, were less than 60 years of age, shared their previous medical history and coronary angiographic report, and gave informed written consent. Data on classic coronary risk factors and periodontal inflammatory status and angiographic findings were recorded and subjected to appropriate statistical analysis. Results The results revealed that the periodontal inflamed surface area (p = 0.002) apart from age (p < 0.047) and low-density lipoprotein cholesterol (LDL-C) (p < 0.001) is a significant independent predictor of the severity of coronary atherosclerosis. Conclusions The periodontal inflamed surface area is an independent predictor of the severity of coronary atherosclerosis.

Protein-polymer conjugates and polymeric nanomaterials hold great promise in many applications including biomaterials, medicine, or nanoelectronics. In this work, the first polymerization-induced self-assembly (PISA) approach performed in aqueous medium enabling protein-polymer conjugates and nanoparticles entirely composed of amino acids is presented by using ring-opening polymerization (ROP). It is indeed shown that aqueous ring-opening polymerization-induced self-assembly (ROPISA) can be used with protein or peptidic macroinitiators without prior chemical modification and afford the simple preparation of nanomaterials with protein-like property, for example, to implement biomimetic thermoresponsivity in drug delivery.

Schools have been closed across the country and will remain closed until September in most provinces. The decision to reopen should take into account current inequalities in cognitive skills across the country and the impact of school interruptions on knowledge accumulation. In this article, we use information from a companion article to estimate the socioeconomic achievement gaps of 15-year-olds across Canada and assess the impact of the pandemic on inequalities in education. Using estimates from the literature on the impact of school closures, we find that the socioeconomic skills gap measured using Programme for International Student Assessment data could increase by more than 30 percent.
Les écoles ont été fermées partout au pays et le demeureront jusqu’en septembre dans la plupart des provinces. Dans la décision de rouvrir les écoles, il faudra tenir compte des inégalités actuelles au chapitre des habiletés cognitives des élèves dans l’ensemble du Canada et de l’incidence de l’interruption du fonctionnement des écoles sur le cumul des connaissances. Les auteurs utilisent l’information provenant d’un document complémentaire pour estimer l’écart socioéconomique dans la réussite des jeunes de 15 ans sur l’ensemble du territoire canadien et évaluent les répercussions de la pandémie sur les inégalités dans l’éducation. À l’aide d’estimations tirées de la documentation sur les conséquences de la fermeture des écoles, les auteurs prévoient que les écarts socioéconomiques de compétences mesurés selon les données du PISA pourraient croître de plus de 30 pour cent.

The current study employed latent profile analysis to examine the application patterns of students\' reading metacognitive strategies using PISA 2018 data in China. Subsequently, it explored the differences in students\' mathematics learning efficiency and performance. The results revealed that: (1) Six types of reading metacognitive strategies application patterns were identified: \"Novice - indifferent,\" \"Veteran - average,\" \"Novice - low evaluating,\" \"Veteran - skilled,\" \"Novice - mixed,\" and \"Novice - arbitrary.\" (2) The primary factors that affect the classification of reading metacognitive strategies application patterns were gender, and family economic, social, and cultural statuses (ESCS). (3) Mathematics learning time could positively predict performance overall, but the mathematics learning time of \"Veteran - skilled\" and \"Novice - mixed\" students had no significant correlation with their mathematics performance. The findings suggests that educators should not blindly increase students\' mathematics learning time but instead provide appropriate guidance based on their mastery patterns of reading metacognitive strategies to enhance mathematics learning efficiency and performance.

5-Fluorouracil (5-FU) stands as one of the most widely prescribed chemotherapeutics. Despite over 60 years of study, a systematic synopsis of how 5-FU binds to proteins has been lacking. Investigating the specific binding patterns of 5-FU to proteins is essential for identifying additional interacting proteins and comprehending their medical implications. In this review, an analysis of the 5-FU binding environment was conducted based on available complex structures. From the earliest complex structure in 2001 to the present, two groups of residues emerged upon 5-FU binding, classified as P- and R-type residues. These high-frequency interactive residues with 5-FU include positively charged residues Arg and Lys (P type) and ring residues Phe, Tyr, Trp, and His (R type). Due to their high occurrence, 5-FU binding modes were simplistically classified into three types, based on interactive residues (within <4 Å) with 5-FU: Type 1 (P-R type), Type 2 (P type), and Type 3 (R type). In summary, among 14 selected complex structures, 8 conform to Type 1, 2 conform to Type 2, and 4 conform to Type 3. Residues with high interaction frequencies involving the N1, N3, O4, and F5 atoms of 5-FU were also examined. Collectively, these interaction analyses offer a structural perspective on the specific binding patterns of 5-FU within protein pockets and contribute to the construction of a structural interactome delineating the associations of the anticancer drug 5-FU.

Diagnostic classification models (DCMs) have seen wide applications in educational and psychological measurement, especially in formative assessment. DCMs in the presence of testlets have been studied in recent literature. A key ingredient in the statistical modeling and analysis of testlet-based DCMs is the superposition of two latent structures, the attribute profile and the testlet effect. This paper extends the standard testlet DINA (T-DINA) model to accommodate the potential correlation between the two latent structures. Model identifiability is studied and a set of sufficient conditions are proposed. As a byproduct, the identifiability of the standard T-DINA is also established. The proposed model is applied to a dataset from the 2015 Programme for International Student Assessment. Comparisons are made with DINA and T-DINA, showing that there is substantial improvement in terms of the goodness of fit. Simulations are conducted to assess the performance of the new method under various settings.

Metal-free organic photocatalysts for photo-mediated reversible deactivation radical polymerization (photo-RDRP) are witnessed to make increasing advancement in the precise synthesis of polymers. However, challenges still exist in the development of high-efficiency and environmentally sustainable carbon dots (CDs)-based organocatalysts. Herein, N-doped CDs derived from phenanthroline derivative (Aphen) are prepared as metal-free photocatalysts for photoinduced electron transfer reversible addition-fragmentation chain transfer (PET-RAFT) polymerization. The introduction of phenanthroline structure enhances the excited state lifetime of CDs and expands the conjugated length of their internal structure to enable the light-absorption to reach green light region, thereby enhancing photocatalytic activity. The as-designed CDs exhibit unprecedented photocatalytic capacity in photopolymerization even in large-volume reaction (100 mL) with high monomer conversion and narrow polymer dispersity (Mw/Mn < 1.20) under green light. The photocatalytic system is compatible with PET-RAFT polymerization of numerous monomers and the production of high molecular weight polyacrylate (Mn >250 000) with exquisite spatiotemporal control. Above results confirm the potential of CDs as photocatalyst, which has not been achieved with other CDs catalysts used in photo-RDRP. In addition, the construction of fluorescent polymer nanoparticles using CDs as both photocatalyst and phosphor through photoinitiated polymerization-induced self-assembly (Photo-PISA) technology is successfully demonstrated for the first time.

UNASSIGNED: The World Health Organization (WHO) developed a structured framework to enable countries to rapidly assess the severity of an influenza pandemic. This framework, the Pandemic Influenza Severity Assessment (PISA), is intended to be performed weekly during seasonal epidemics so that assessing influenza severity during a pandemic can be done with greater ease and efficiency.
UNASSIGNED: Using influenza surveillance indicators within Canada\'s FluWatch program from seasons 2014-2015 to 2018-2019, national PISA thresholds were developed and assessed against seasonal data for seasons 2019-2020 to June of 2022-2023.
UNASSIGNED: Canada developed thresholds for each required indicator (transmissibility, seriousness of disease and impact) for multiple WHO-recommended parameters. The thresholds were assessed against four seasons, and it was determined that there was a good agreement between the PISA assessments and the characterization of the season by FluWatch epidemiologists.
UNASSIGNED: With confidence in the validity of the PISA thresholds, the FluWatch program will begin to share PISA assessments weekly through the FluWatch report in the 2023-2024 seasons to help characterize influenza activity in Canada and inform responses to the seasonal influenza epidemic.