Causal role of immune cells in chronic periodontitis: a bidirectional Mendelian randomization study.

BACKGROUND: This study aims to explore the bidirectional causal relationship between immune cell phenotypes and chronic periodontitis using a Mendelian randomization framework. MATERIALS AND METHODS: Through a two-sample Mendelian randomization analysis, this research examined genetic data related to 731 immune cell traits and chronic periodontitis. Instrumental variables were chosen based on their genetic links to either immune traits or periodontitis. Various statistical techniques, including MR-Egger regression, weighted median, and inverse-variance weighted (IVW) analysis, were employed to determine the causal connections. RESULTS: Predominantly using the IVW method, 26 distinct immune phenotypes were identified as potentially influencing periodontitis (P < 0.05). Conversely, periodontitis potentially affected 33 different immune phenotypes (P < 0.05). The results for pleiotropy and sensitivity tests were stable. However, these associations lost significance after adjusting for the False Discovery Rate. CONCLUSION: This study uncovers a complex bidirectional causal relationship between certain immune cell phenotypes and chronic periodontitis, underscoring the intricate interaction between the immune system and the pathogenesis of periodontal disease.

Long-term LDR exposure may induce cognitive impairments: A possible association through targeting gut microbiota-gut-brain axis.

Environmental and occupational low-dose radiation (LDR) exposure may be harmful for health but the previous reports regarding effect of LDR on cognition are contradictory. Here we investigated the effect of long-term LDR exposure on cognition. In this study, male Balb/c mice' cognitive functions were tested at 15 weeks after being exposed to 0.5 Gy LDR in 10 fractions at each dose of 0.05 Gy. The results demonstrated that long-term LDR exposure increases escape latency and the time spent in finding exits in mice compared with non LDR exposure. Meanwhile, the inflammation-related proteins including NFκB and p38 also increased. Lipopolysaccharide (LPS) increased and short-chain fatty acid (SCFA) levels decreased following long term LDR exposure. Treatment with microbiota-derived LPS and SCFAs reversed these effects in mice. Furthermore, the gut barrier integrity was damaged in a time-dependent manner with the decreased expression of intestinal epithelial-related biomarkers such as ZO-1 and occludin. Mechanistically, long after exposure to LDR, increased LPS levels may cause cognitive impairment through the regulation of Akt/mTOR signaling in the mouse hippocampus. These findings provide new insight into the clinical applications of LDR and suggest that the gut microbiota-plasma LPS and SCFAs-brain axis may underlie long-term LDR-induced cognition effects.

Relevant factors of posterior mandible lingual plate perforation during immediate implant placement: a virtual implant placement study using CBCT.

BACKGROUND: To explore the influence of cross-sectional type and morphological parameters at the mandibular molar sites on lingual plate perforation (LPP) during the immediate implant placement (IIP). METHODS: 181 implants were virtually placed in the mandibular molar sites on the cone beam computed tomography (CBCT). Each cross-section of the implantation site was divided into the Undercut (U)/Parallel (P)/Convex (C) types. Morphologically relevant parameters were measured on the cross-sections, including width of the upper end (Wb), width of the lower end (Wc), vertical height (V), angle between the natural crown axis and the alveolar bone axis (∠ß), LC depth (LCD), LC height, and angle between the horizontal line and the line connecting the most prominent point and the most concave point of lingual plate (∠α). Besides, the distance from the end of the virtual implant and the lingual bone plate of the cross-section (DIL) was calculated. Relationships between all the morphologically relevant parameters and the DIL were further analyzed. RESULTS: A total of 77 (42.5%) cross-sections were classified as U-type, which was the most common one, accounting for 63% of the second molar regions. All LPP cases and most of the nearly LPP (87.9%) cases occurred at the U-type cross-sections, and the relationship between the DIL and the morphological parameters can be expressed by a multivariate linear equation. CONCLUSIONS: The occurrence rate of U-type cross-sections in the second molar region was very high, and the risk of LPP should be considered during IIP. Except for the U-type, significant large LCD, small Wc, and large âˆ ß were the important relevant factors. CBCT and multivariate linear equations could help to assess the LPP risk and provide a reference for implant placement design pre-surgery.

Intermolecular Formal Cycloaddition of Indoles with Bicyclo[1.1.0]butanes by Lewis Acid Catalysis.

Herein, we develop a new approach to directly access architecturally complex polycyclic indolines from readily available indoles and bicyclo[1.1.0]butanes (BCBs) through formal cycloaddition promoted by commercially available Lewis acids. The reaction proceeded through a stepwise pathway involving a nucleophilic addition of indoles to BCBs followed by an intramolecular Mannich reaction to form rigid indoline-fused polycyclic structures, which resemble polycyclic indole alkaloids. This new reaction tolerated a wide range of indoles and BCBs, thereby allowing the one-step construction of various rigid indoline polycycles containing up to four contiguous quaternary carbon centers.

A tensor-based bi-random walks model for protein function prediction.

BACKGROUND: The accurate characterization of protein functions is critical to understanding life at the molecular level and has a huge impact on biomedicine and pharmaceuticals. Computationally predicting protein function has been studied in the past decades. Plagued by noise and errors in protein-protein interaction (PPI) networks, researchers have undertaken to focus on the fusion of multi-omics data in recent years. A data model that appropriately integrates network topologies with biological data and preserves their intrinsic characteristics is still a bottleneck and an aspirational goal for protein function prediction. RESULTS: In this paper, we propose the RWRT (Random Walks with Restart on Tensor) method to accomplish protein function prediction by applying bi-random walks on the tensor. RWRT firstly constructs a functional similarity tensor by combining protein interaction networks with multi-omics data derived from domain annotation and protein complex information. After this, RWRT extends the bi-random walks algorithm from a two-dimensional matrix to the tensor for scoring functional similarity between proteins. Finally, RWRT filters out possible pretenders based on the concept of cohesiveness coefficient and annotates target proteins with functions of the remaining functional partners. Experimental results indicate that RWRT performs significantly better than the state-of-the-art methods and improves the area under the receiver-operating curve (AUROC) by no less than 18%. CONCLUSIONS: The functional similarity tensor offers us an alternative, in that it is a collection of networks sharing the same nodes; however, the edges belong to different categories or represent interactions of different nature. We demonstrate that the tensor-based random walk model can not only discover more partners with similar functions but also free from the constraints of errors in protein interaction networks effectively. We believe that the performance of function prediction depends greatly on whether we can extract and exploit proper functional similarity information on protein correlations.

Protein function annotation based on heterogeneous biological networks.

BACKGROUND: Accurate annotation of protein function is the key to understanding life at the molecular level and has great implications for biomedicine and pharmaceuticals. The rapid developments of high-throughput technologies have generated huge amounts of protein-protein interaction (PPI) data, which prompts the emergence of computational methods to determine protein function. Plagued by errors and noises hidden in PPI data, these computational methods have undertaken to focus on the prediction of functions by integrating the topology of protein interaction networks and multi-source biological data. Despite effective improvement of these computational methods, it is still challenging to build a suitable network model for integrating multiplex biological data. RESULTS: In this paper, we constructed a heterogeneous biological network by initially integrating original protein interaction networks, protein-domain association data and protein complexes. To prove the effectiveness of the heterogeneous biological network, we applied the propagation algorithm on this network, and proposed a novel iterative model, named Propagate on Heterogeneous Biological Networks (PHN) to score and rank functions in descending order from all functional partners, Finally, we picked out top L of these predicted functions as candidates to annotate the target protein. Our comprehensive experimental results demonstrated that PHN outperformed seven other competing approaches using cross-validation. Experimental results indicated that PHN performs significantly better than competing methods and improves the Area Under the Receiver-Operating Curve (AUROC) in Biological Process (BP), Molecular Function (MF) and Cellular Components (CC) by no less than 33%, 15% and 28%, respectively. CONCLUSIONS: We demonstrated that integrating multi-source data into a heterogeneous biological network can preserve the complex relationship among multiplex biological data and improve the prediction accuracy of protein function by getting rid of the constraints of errors in PPI networks effectively. PHN, our proposed method, is effective for protein function prediction.

A novel method to predict essential proteins based on tensor and HITS algorithm.

BACKGROUND: Essential proteins are an important part of the cell and closely related to the life activities of the cell. Hitherto, Protein-Protein Interaction (PPI) networks have been adopted by many computational methods to predict essential proteins. Most of the current approaches focus mainly on the topological structure of PPI networks. However, those methods relying solely on the PPI network have low detection accuracy for essential proteins. Therefore, it is necessary to integrate the PPI network with other biological information to identify essential proteins. RESULTS: In this paper, we proposed a novel random walk method for identifying essential proteins, called HEPT. A three-dimensional tensor is constructed first by combining the PPI network of Saccharomyces cerevisiae with multiple biological data such as gene ontology annotations and protein domains. Then, based on the newly constructed tensor, we extended the Hyperlink-Induced Topic Search (HITS) algorithm from a two-dimensional to a three-dimensional tensor model that can be utilized to infer essential proteins. Different from existing state-of-the-art methods, the importance of proteins and the types of interactions will both contribute to the essential protein prediction. To evaluate the performance of our newly proposed HEPT method, proteins are ranked in the descending order based on their ranking scores computed by our method and other competitive methods. After that, a certain number of the ranked proteins are selected as candidates for essential proteins. According to the list of known essential proteins, the number of true essential proteins is used to judge the performance of each method. Experimental results show that our method can achieve better prediction performance in comparison with other nine state-of-the-art methods in identifying essential proteins. CONCLUSIONS: Through analysis and experimental results, it is obvious that HEPT can be used to effectively improve the prediction accuracy of essential proteins by the use of HITS algorithm and the combination of network topology with gene ontology annotations and protein domains, which provides a new insight into multi-data source fusion.

NPF:network propagation for protein function prediction.

BACKGROUND: The accurate annotation of protein functions is of great significance in elucidating the phenomena of life, treating disease and developing new medicines. Various methods have been developed to facilitate the prediction of these functions by combining protein interaction networks (PINs) with multi-omics data. However, it is still challenging to make full use of multiple biological to improve the performance of functions annotation. RESULTS: We presented NPF (Network Propagation for Functions prediction), an integrative protein function predicting framework assisted by network propagation and functional module detection, for discovering interacting partners with similar functions to target proteins. NPF leverages knowledge of the protein interaction network architecture and multi-omics data, such as domain annotation and protein complex information, to augment protein-protein functional similarity in a propagation manner. We have verified the great potential of NPF for accurately inferring protein functions. According to the comprehensive evaluation of NPF, it delivered a better performance than other competing methods in terms of leave-one-out cross-validation and ten-fold cross validation. CONCLUSIONS: We demonstrated that network propagation, together with multi-omics data, can both discover more partners with similar function, and is unconstricted by the "small-world" feature of protein interaction networks. We conclude that the performance of function prediction depends greatly on whether we can extract and exploit proper functional information of similarity from protein correlations.

MicroRNA-590-5p functions as a tumor suppressor in breast cancer conferring inhibitory effects on cell migration, invasion, and epithelial-mesenchymal transition by downregulating the Wnt-ß-catenin signaling pathway.

Breast cancer remains one of the foremost primary causes of female morbidity and mortality worldwide. During the current study, the effect of miR-590-5p and paired-like homeodomain transcription factor 2 (PITX2) on proliferation, invasion, migration, and epithelial-mesenchymal transition (EMT) of human breast cancer via the Wnt-ß-catenin signaling pathway was investigated. Breast cancer-related genes and related signaling pathways were obtained from KEGG database. The PITX2 regulatory microRNA was predicted. To define the contributory role by which miR-590-5p influences the progression of breast cancer, the interaction between miR-590-5p and PITX2 was explored; the proliferation, invasion, and migration abilities as well as the tumor growth and metastasis in nude mice were detected following the overexpression or silencing of miR-590-5p. PITX2 was determined to share a correlation with breast cancer and miR-590-5p was selected for further analysis. PITX2, Wnt-1, ß-catenin, N-cadherin, and vimentin all displayed higher levels, while miR-590-5p and E-cadherin expression were lower among breast cancer tissues than in the adjacent normal tissue. After overexpression of miR-590-5p or si-PITX2, the expression of E-cadherin was markedly increased, decreases in the expression of Wnt-1, ß-catenin, N-cadherin, and vimentin, as well as inhibited cell proliferation, invasion, migration, metastasis, and EMT were observed. This study provides evidence suggesting that the transfection of overexpressed miR-590-5p can act to alleviate the effects of breast cancer demonstrating an ability to inhibit the processes of cell proliferation, migration, and invasion as well as EMT by suppressing the expression of PITX2 and activation of the Wnt-ß-catenin pathway.

Prevalence of burnout and associated factors among general practitioners in Hubei, China: a cross-sectional study.

BACKGROUND: High occupational burnout among general practitioners (GPs) is an important challenge to China's efforts to strengthen its primary healthcare delivery; however, data to help understand this issue are unavailable. This study aimed to investigate the prevalence of burnout and associated factors among GPs. METHODS: A cross-sectional design was used to collect data from December 12, 2014, to March 10, 2015, with a self-administered structured questionnaire from 1015 GPs (response rate, 85.6%) in Hubei Province, Central China. Burnout was measured using a 22-item Maslach Burnout Inventory-Human Services Survey (MBI-HSS). MBI-HSS scores and frequency were analyzed by the three dimensions of emotional exhaustion (EE), depersonalization (DP), and personal accomplishment (PA). Factors associated with burnout among GPs were estimated using a multiple linear regression model. RESULTS: Of the respondents, 2.46% had a high level of burnout in all three dimensions, 24.83% reported high levels of EE, 6.21% scored high on DP, and 33.99% were at high risk of PA. GPs who were unmarried, had lower levels of job satisfaction, and had been exposed to workplace violence experienced higher levels of burnout. Intriguingly, no statistically significant associations were found between burnout and the duration of GP practice, age, sex, income, practice setting, and professional level. CONCLUSION: This is the first study of occupational burnout in Chinese general practice. Burnout is prevalent among GPs in Hubei, China. Interventions aimed at increasing job satisfaction, improving doctor-patient relationships and providing safer workplace environments may be promising strategies to reduce burnout among GPs in Hubei, China.

Association between shift work and risk of prostate cancer: a systematic review and meta-analysis of observational studies.

Observational studies suggest that shift work may be associated with prostate cancer. However, the results are inconsistent. The objective of this study is to quantitatively assess the association between shift work and the risk of prostate cancer. Relevant studies were identified by a comprehensive search of the PubMed, Embase, Web of Science and China National Knowledge Infrastructure databases to September 2017. We also reviewed the reference lists from retrieved articles. Observational studies that reported relative risk (RR) with 95% confidence intervals (CIs) for the association between shift work and the risk of prostate cancer were included. Linear and non-linear dose-response meta-analyses were performed. Fifteen studies with 16 independent reports involving 2 546 822 individuals and 10 715 patients with prostate cancer were included. The pooled adjusted RR for the association between ever exposure to shift work and prostate cancer risk was 1.23 (95% CI, 1.08-1.41; P < 0.001). A non-linear association of prostate cancer risk with duration of shift work was identified (P for non-linearity = 0.001). Subgroup analysis demonstrated a higher pooled RR of prostate cancer for studies among Asian populations (RR = 1.98, 95% CI, 1.34-2.93; P = 0.618). A positive association was observed in rotating shift groups (RR = 1.10, 95% CI, 1.00-1.26; P = 0.156), but not in other shift groups. Integrated evidence from this meta-analysis suggests that shift work is significantly associated with an increased risk of prostate cancer, and a non-linear association between duration of shift work and prostate cancer was found.

Prevalence and Risk Factors Associated With Workplace Violence Against General Practitioners in Hubei, China.

OBJECTIVES: To assess the prevalence and factors associated with physical and nonphysical violence in a sample of general practitioners (GPs). METHODS: We used a cross-sectional design to collect data from December 2014 to March 2015 with a structured self-administered questionnaire from 1015 GPs in Hubei Province, Central China (response rate, 85.6%). We used a multivariable logistic regression model to identify the predictors associated with workplace violence toward GPs. RESULTS: Of the respondents, 62.2% of respondents reported exposure to workplace violence in the preceding year, including 18.9% and 61.4% who encountered physical and nonphysical violence, respectively. Multivariable logistic regression analysis suggested that GPs who were male, at a higher professional level, and who had a lower average monthly income were more likely to experience physical violence. Male GPs, less-experienced GPs, and those with administrative responsibility were more likely than their counterparts to encounter nonphysical violence. CONCLUSIONS: This study shows that the prevalence of workplace violence against GPs is high in Hubei, China. Creating a prevention strategy and providing safer workplace environments for GPs should be urgently prioritized.

Factors influencing government insurance scheme beneficiary acceptance of the gatekeeper policy: a cross-sectional study in Wuhan, China.

BACKGROUND: Gatekeeper policy, requiring a patient to visit a primary care provider first, and the patient needs to get his or her primary care provider's referral before seeing a specialist or going to a hospital, has been implemented in China for about ten years, and it is necessary to assess the patients' acceptance of gatekeeper policy and to explore the factors influencing patients' acceptance. METHODS: A cross-sectional study with 1162 respondents was conducted between July and September 2015 at four community health centers (CHCs) in Wuhan, China. Face-to-face interview was used to collect information on demographics, acceptance of the gate keeper policy and satisfaction with community health services. Patients' satisfaction with community health service was evaluated using the European Patients Evaluate General/Family Practice scale and binary logistic regression model was used to examine the factors influencing patients' acceptance of community health services as gate keepers. RESULTS: A total of 512 (43.06%) patients accepted gatekeeper policy. Mandatory reimbursement provision (OR: 1.63, 95% CI: 1.23-2.15), patient satisfaction with the aspects of medical care (OR: 1.92, 95% CI: 1.12-3.29) and organization of care (OR: 1.66, 95% CI: 1.05-2.62) were associated with acceptance of gatekeeper policy, after adjusting for potential confounders. Moreover, young people (OR: 0.35, 95%CI: 0.22-0.56) seemed to be more reluctant to accept the policy, when compared with the elder. CONCLUSIONS: Our study suggests that mandatory reimbursement provision greatly affects patients' acceptance of gatekeeper policy, therefore, the policy-maker should pay attention to the negative effect of its mandatory reimbursement provision on patients' acceptance of the policy. However, improving the aspects of medical care and organization of care will contribute to implementation of gatekeeper policy.

An efficient method for protein function annotation based on multilayer protein networks.

BACKGROUND: Accurate annotation of protein functions is still a big challenge for understanding life in the post-genomic era. Many computational methods based on protein-protein interaction (PPI) networks have been proposed to predict the function of proteins. However, the precision of these predictions still needs to be improved, due to the incompletion and noise in PPI networks. Integrating network topology and biological information could improve the accuracy of protein function prediction and may also lead to the discovery of multiple interaction types between proteins. Current algorithms generate a single network, which is archived using a weighted sum of all types of protein interactions. METHOD: The influences of different types of interactions on the prediction of protein functions are not the same. To address this, we construct multilayer protein networks (MPN) by integrating PPI networks, the domain of proteins, and information on protein complexes. In the MPN, there is more than one type of connections between pairwise proteins. Different types of connections reflect different roles and importance in protein function prediction. Based on the MPN, we propose a new protein function prediction method, named function prediction based on multilayer protein networks (FP-MPN). Given an un-annotated protein, the FP-MPN method visits each layer of the MPN in turn and generates a set of candidate neighbors with known functions. A set of predicted functions for the testing protein is then formed and all of these functions are scored and sorted. Each layer plays different importance on the prediction of protein functions. A number of top-ranking functions are selected to annotate the unknown protein. CONCLUSIONS: The method proposed in this paper was a better predictor when used on Saccharomyces cerevisiae protein data than other function prediction methods previously used. The proposed FP-MPN method takes different roles of connections in protein function prediction into account to reduce the artificial noise by introducing biological information.

Factors Affecting Patient Satisfaction with Community Health Service under the Gatekeeper System: A Cross-sectional Study in Nanjing, China.

The gatekeeper policy has been implemented for approximately ten years on a pilot population in China. It is necessary to assess the satisfaction of patients utilizing community health service (CHS) under the gatekeeper system. Our study showed that the cognition of gatekeeper policy was associated with four dimensions including doctor-patient relationships, information and support, organization of care, and accessibility (P < 0.001). One or more factors such as gender and self-perceived health scores also affected their satisfaction. General practitioners must be prepared to focus on these aspects of information and support, organization of care, and accessibility as indicators of potential opportunities for improvement. Additionally, policymakers can improve patients' satisfaction with CHS by strengthening their awareness of the gatekeeper policy.

Clinical analysis of thoracoscopic surgery combined with intraoperative autologous blood transfusion in the treatment of traumatic hemothorax.

From January 2013 to January 2015, 19 patients of traumatic hemothorax with hemorrhagic shock were treated in our department by thoracoscopic surgery combined with autologous blood transfusion. This study retrospectively analyzed the therapeutic effect and shared our experience. The average amount of blood transfused back was 662.41 ml ± 269.15 ml. None of the patients developed transfusion reaction and were all discharged uneventfully. Thoracoscopic surgery combined with autologous blood trans- fusion is effective in the rescue of patients with progressive hemothorax and hemorrhagic shock. When corresponding indications are well managed, treatment for these patients is quicker, safer, and more effective.

Facile access to bicyclo[2.1.1]hexanes by Lewis acid-catalyzed formal cycloaddition between silyl enol ethers and bicyclo[1.1.0]butanes.

Saturated three-dimensional carbocycles have gained increasing prominence in synthetic and medicinal chemistry. In particular, bicyclo[2.1.1]hexanes (BCHs) have been identified as the molecular replacement for benzenes. Here, we present facile access to a variety of BCHs via a stepwise two-electron formal (3 + 2) cycloaddition between silyl enol ethers and bicyclo[1.1.0]butanes (BCBs) under Lewis acid catalysis. The reaction features wide functional group tolerance for silyl enol ethers, allowing the efficient construction of two vicinal quaternary carbon centers and a silyl-protected tertiary alcohol unit in a streamlined fashion. Interestingly, the reaction with conjugated silyl dienol ethers can provide access to bicyclo[4.1.1]octanes (BCOs) equipped with silyl enol ethers that facilitate further transformation. The utilities of this methodology are demonstrated by the late-stage modification of natural products, transformations of tertiary alcohol units on bicyclo[2.1.1]hexane frameworks, and derivatization of silyl enol ethers on bicyclo[4.1.1]octanes, delivering functionalized bicycles that are traditionally inaccessible.

A novel approach to full-mouth rehabilitation of dentinogenesis imperfecta type II: Case series with review of literature.

RATIONALE: Dentinogenesis imperfecta (DI) is an autosomal-dominant disorder. The most common clinical manifestations, including obliterated tooth tissues and severe tooth wear, usually lead to tooth extractions. It remains a great challenge for dentists to preserve the residual tooth tissue and establish the esthetics and occlusion of dentitions. PATIENTS CONCERNS: 25-year-old twin sisters, who had suffered from dentinogenesis imperfecta type II for more than 10 years, presented with continuous tooth wear and discomfort from wearing a removable partial denture for more than 3 years. DIAGNOSIS: Intraoral examination showed extensive tooth wear with enamel exfoliation and typical amber-brown color with an opalescent discoloration. Their panoramic radiographs revealed completely obliterated tooth tissues and severe tooth wear. INTERVENTIONS AND OUTCOMES: The dentitions were restored with post-and-core crowns and pin lays after preparing root post paths and pin holes guided by computer-aided design/computer-aided manufacturing (CAD/CAM) procedures, resulting in a successful repair. LESSONS: Severe tooth wear and tooth tissue obliteration are typical clinical manifestations in DI-affected dentitions, increasing the complexity and difficulty in dental restorations. Early diagnosis and appropriate treatments are essential to achieve a favorable prognosis. CAD/CAM procedures, permitting accurate and effective treatment, possess promising potential in the treatment of DI-affected dentitions.

Palladium-catalyzed Hiyama-type cross-coupling reactions of arenesulfinates with organosilanes.

Palladium-catalyzed Hiyama-type cross-coupling reactions of various arenesulfinates with organosilanes were achieved in good to excellent yields under aerobic conditions at 70 °C. Fluoride is essential, and tetrabutylammonium fluoride (TBAF) was shown to be the most efficient additive for these cross-coupling reactions. These cross-coupling reactions of the arenesulfinates provide high yields and show wide functional group tolerance, making them attractive alternative transformations to traditional cross-coupling approaches for carbon-carbon bond construction.