Comparison of healing assessments of periapical endodontic surgery using conventional radiography and cone-beam computed tomography: A systematic review

Purpose@#This systematic review aimed to compare assessments of the healing of periapical endodontic surgery using conventional radiography and cone-beam computed tomography (CBCT). @*Materials and Methods@#This review of clinical studies was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist. All articles published from 1990 to March 2020 pertaining to clinical and radiographic healing assessments after endodontic surgery using conventional radiography and CBCT were included. The question was “healing assessment of endodontic surgery using cone-beam computed tomography.” The review was conducted by manual searching, as well as undertaking a review of electronic literature databases, including PubMed and Scopus. The studies included compared radiographic and CBCT assessments of periapical healing after periapical endodontic surgery. @*Results@#The initial search retrieved 372 articles. The titles and abstracts of these articles were read, leading to the selection of 73 articles for full-text analysis. After the eligibility criteria were applied, 11 articles were selected for data extraction and qualitative analysis. The majority of studies found that CBCT enabled better assessments of healing than conventional radiography, suggesting higher efficacy of CBCT for correct diagnosis and treatment planning. A risk of bias assessment was done for 10 studies, which fell into the low to moderate risk categories. @*Conclusion@#Three-dimensional radiography provides an overall better assessment of healing, which is imperative for correct diagnosis and treatment planning.

Ongoing Clinical Trials of Vaccines to Fight against COVID-19 Pandemic

Coronavirus disease 2019 (COVID-19) has developed as a pandemic, and it created an outrageous effect on the current healthcare and economic system throughout the globe. To date, there is no appropriate therapeutics or vaccines against the disease. The entire human race is eagerly waiting for the development of new therapeutics or vaccines against severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Efforts are being taken to develop vaccines at a rapid rate for fighting against the ongoing pandemic situation. Amongst the various vaccines under consideration, some are either in the preclinical stage or in the clinical stages of development (phase-I, -II, and -III). Even, phase-III trials are being conducted for some repurposed vaccines like Bacillus Calmette–Guérin, polio vaccine, and measlesmumps-rubella. We have highlighted the ongoing clinical trial landscape of the COVID-19 as well as repurposed vaccines. An insight into the current status of the available antigenic epitopes for SARS-CoV-2 and different types of vaccine platforms of COVID-19 vaccines has been discussed. These vaccines are highlighted throughout the world by different news agencies. Moreover, ongoing clinical trials for repurposed vaccines for COVID-19 and critical factors associated with the development of COVID-19 vaccines have also been described.

Does Body Mass Index affect Tooth Eruption Sequence? A Study among 6-7 Years Old Schoolchildren in Chennai, India.

BACKGROUND: Changes in eruption pattern cause malocclusion and crowding, which lead to poor oral hygiene as well as periodontal disorders. Hence, it is important for the dentist to know the exact tooth eruption sequence to educate the parents. Tooth eruption sequence we follow is based on the Western population. AIM: As Indian population differs from the Western population in ethnicity, racially, and dietary habits, etc., an attempt was undertaken to compare eruption sequence of Indian children in accordance with the Western population and also to correlate whether body mass index (BMI) affects tooth eruption. MATERIALS AND METHODS: Body mass index and eruption status of permanent mandibular central incisors and first molars were recorded among 529 schoolchildren in Chennai. Eruption status was examined with the help of mouth mirrors and illumination under natural light. The recorded data were entered into Microsoft Excel 2007 and were analyzed using Chi-square test, z test, and Spearman's correlation test. Level of significance was set as 0.05. RESULTS: Eruption values attained from our study were not consistent with the eruption values reported by Logan and Kronfeld. The present study showed that girls have early tooth eruption than boys. Our findings showed negative correlation with respect to BMI and eruption sequence of 31 (r = -0.133), 41 (r = -0.140), 36 (r = -0.08), and 46 (r = -0.076). CONCLUSION: Eruption values reported by Logan and Kronfeld are inappropriate for Indian population. It is also found that obese children had delayed tooth eruption when compared with underweight children who had early tooth eruption. HOW TO CITE THIS ARTICLE: Anu V, Brindha JR, Carol PT, et al. Does Body Mass Index affect Tooth Eruption Sequence? A Study among 6-7 Years Old Schoolchildren in Chennai, India. Int J Clin Pediatr Dent 2020;13(3):261-263.

An Exploration of Impact of COVID 19 on mental health -Analysis of tweets using Natural Language Processing techniques

Twitter is one of the worlds biggest social media platforms for hosting abundant number of user-generated posts. It is considered as a gold mine of data. Majority of the tweets are public and thereby pullable unlike other social media platforms. In this paper we are analyzing the topics related to mental health that are recently (June, 2020) been discussed on Twitter. Also amidst the on-going pandemic, we are going to find out if covid-19 emerges as one of the factors impacting mental health. Further we are going to do an overall sentiment analysis to better understand the emotions of users. Executive SummeryNovel Corona viruss spread and its impact on various aspects of national and individuals well-being has been at the center of lot of discussions across micro-blogging sites and various social media platforms ever since it commenced in December 2019. Users are voicing their opinions on several topics related to covid-19. Social distancing as prescribed by Government and Local Administration We all are aware that the Novel Corona virus has significantly affected our physical health; however the current social distancing norms are taking a toll on the psychological well-being of individuals. The research paper presents a two-phased analysis of most recent 2000 tweets related to mental health pulled out twice over a span of one month on 28 June 2020 and 28 July2020 respectively, thereby analyzing 4000 tweets in total. The second phase analysis was conducted exactly after a gap of one month to validate the results generated by the first analysis. The intention is to analyze to what extent people have discussed about mental health in the past few months based on the information disseminated on Twitter. Data was extracted using Twitters search application programming interface (API) and Pythons tweepy library. A predefined keyword like mental health was given to find out if Covid-19 emerges as a reason for the same. Several natural language processing (NLP) techniques like tokenization, removing URL and stop words, stemming and lemmatization were used to pre-process the text data and make it ready for analysis. These collected tweets were analyzed using word frequencies of single and double words (unigram, bigram). A very unique feature of this analysis includes a network diagram that shows interconnections between the set of most common words used in to its and the connections (if any) are represented through links. Topic modeling technique in NLP visualizes the top concerns of tweeters through a word cloud. At present we have many methods to do topic modeling. In this paper we are using the Latent Dirichlet Allocation (LDA) method which is a probabilistic approach of modeling given by Prof David H.B in 2003. This model deals with distribution of topics to tweets and allocation of those topics to documents and words to topics. Finally a sentiment analysis is done using text mining techniques to analyze the sentiment of the tweets in the form of positive, negative and neutral.

Covid-19 Pandemic Data Analysis and Forecasting using Machine Learning Algorithms

India reported its first Covid-19 case on 30th Jan 2020 and the number of cases reported heavily escalated from March, 2020. This research paper analyses COVID -19 data initially at a global level and then drills down to the scenario obtained in India. Data is gathered from multiple data sources-several authentic government websites. The need of the hour is to accurately forecast when the numbers will reach at its peak and then diminish. It will be of huge help to public welfare professionals to plan the preventive measures to be taken keeping the economic balance of the country as well. Variables such as gender, geographical location, age etc. have been represented using Python and Data Visualization techniques. Time Series Forecasting techniques including Machine Learning models like Linear Regression, Support Vector Regression, Polynomial Regression and Deep Learning Forecasting Model like LSTM(Long short-term memory) are deployed to study the probable hike in cases and in the near future. A comparative analysis is also done to understand which model fits the best for our data. Data is considered till 30th July, 2020. The results show that a statistical model named sigmoid model is outperforming other models. Also the Sigmoid model is giving an estimate of the day on which we can expect the number of active cases to reach its peak and also when the curve will start to flatten. Strength of Sigmoid model lies in providing a count of date that no other model offers and thus it is the best model to predict Covid cases counts -this is unique feature of analysis in this paper. Certain feature engineering techniques have been used to transfer data into logarithmic scale as is affords better comparison removing any data extremities or outliers. Based on the predictions of the short-term interval, our model can be tuned to forecast long time intervals.

The 2019 novel coronavirus disease (COVID-19) pandemic: A zoonotic prospective

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel coronavirus (CoV), has recently emerged as a significant pathogen for humans and the cause for the recent outbreak of the 2019 novel coronavirus disease (COVID-19) throughout the globe. For developing any preventive measure, an understanding of the zoonotic pattern for this virus is a necessity. We should have a clear knowledge of its reservoir host, its distribution pattern and spreading routes. Information about zoonotic reservoirs and its transmission among them can help to understand the COVID-19 outbreaks. In this article, we discuss about the bats as the zoonotic reservoir of several CoV strains, co-existence of bats and CoV/viruses, the sequence similarity of SARS-CoV-2 with bat SARS-like CoV, the probable source of the origin of SARS-CoV-2 strain and COVID-19 outbreak, intermediate host of CoVs and SARS-CoV-2, human to human transmission and the possibility to maintain the zoonotic barriers. Our knowledge about the zoonotic reservoir of SARS-CoV-2 and its transmission ability may help develop the preventive measures and control for the future outbreak of CoV.

Lactobacillus pentosus Modulates Immune Response by Inducing IL-10 Producing Tr1 Cells

Several gut commensals have been shown to modulate host immune response. Recently, many food derived microbes have also been reported to affect the immune system. However, a mechanism to identify immunostimulatory and immunoregulatory microbes is needed. Here, we successfully established an in vitro screening system and identified an immunoregulatory bacterium, Lactobacillus pentosus KF340 (LP340), present in various fermented foods. LP340 induced a regulatory phenotype in mice Ag presenting cells which, in turn, induced IL-10 and IFN-γ producing Type 1 regulatory T cells (Tr1 cells) from naïve CD4⁺ T cells. Naïve CD4⁺ T cells co-cultured with LP340 treated dendritic cells highly expressed cytokine receptor IL-27R and were CD49b and lymphocyte-activation gene 3 double positive. Oral administration of LP340 in mice with atopic dermatitis reduced cellular infiltration in affected ear lobes and serum IgE levels, thus, ameliorating the disease symptoms. This suggests a systemic immunoregulatory effect of LP340. These findings demonstrate that LP340, a bacterium derived from food, prevents systemic inflammation through the induction of IL-10 producing Tr1 cells.

Lysophosphatidic acid enhances breast cancer cells-mediated osteoclastogenesis

Lysophosphatidic acid (LPA) is known to play a critical role in breast cancer metastasis to bone. In this study, we tried to investigate any role of LPA in the regulation of osteoclastogenic cytokines from breast cancer cells and the possibility of these secretory factors in affecting osteoclastogenesis. Effect of secreted cytokines on osteoclastogenesis was analyzed by treating conditioned media from LPA-stimulated breast cancer cells to differentiating osteoclasts. Result demonstrated that IL-8 and IL-11 expression were upregulated in LPA-treated MDA-MB-231 cells. IL-8 was induced in both MDA-MB-231 and MDA-MB-468, however, IL-11 was induced only in MDA-MB-231, suggesting differential LPARs participation in the expression of these cytokines. Expression of IL-8 but not IL-11 was suppressed by inhibitors of PI3K, NFkB, ROCK and PKC pathways. In the case of PKC activation, it was observed that PKCδ and PKCμ might regulate LPA-induced expression of IL-11 and IL-8, respectively, by using specific PKC subtype inhibitors. Finally, conditioned Medium from LPA-stimulated breast cancer cells induced osteoclastogenesis. In conclusion, LPA induced the expression of osteolytic cytokines (IL-8 and IL-11) in breast cancer cells by involving different LPA receptors. Enhanced expression of IL-8 by LPA may be via ROCK, PKCu, PI3K, and NFkB signaling pathways, while enhanced expression of IL-11 might involve PKCδ signaling pathway. LPA has the ability to enhance breast cancer cells-mediated osteoclastogenesis by inducing the secretion of cytokines such as IL-8 and IL-11.

Probiotics as a Potential Immunomodulating Pharmabiotics in Allergic Diseases: Current Status and Future Prospects

The prevalence of allergic disorders has dramatically increased over the past decade, particularly in developed countries. Apart from gastrointestinal disorders, neoplasia, genital and dermatological diseases etc., dysregulation of gut microbiota (dysbiosis) has also been found to be associated with increased risk of allergies. Probiotics are increasingly being employed to correct dysbiosis and, in turn, to modulate allergic diseases. However, several factors like strain variations and effector metabolites or component of them in a bacterial species can affect the efficacy of those as probiotics. On the other hand, host variations like geographical locations, food habits etc. could also affect the expected results from probiotic usage. Thus, there is a glaring deficiency in our approach to establish probiotics as an irrefutable treatment avenue for suitable disorders. In this review, we explicate on the reported probiotics and their effects on certain allergic diseases like atopic dermatitis, food allergy and asthma to establish their utility. We propose possible measures like elucidation of effector molecules and functional mechanisms of probiotics towards establishing probiotics for therapeutic use. Certain probiotics studies have led to very alarming outcomes which could have been precluded, had effective guidelines been in place. Thus, we also propose ways to secure the safety of probiotics. Overall, our efforts tend to propose necessary discovery and quality assurance guidelines for developing probiotics as potential immunomodulatory ‘Pharmabiotics.’

Qualitative and Quantitative Comparison of Contrast-Enhanced Fluid-Attenuated Inversion Recovery, Magnetization Transfer Spin Echo, and Fat-Saturation T1-Weighted Sequences in Infectious Meningitis

OBJECTIVE: To compare the contrast-enhanced fluid-attenuated inversion recovery (CE-FLAIR), the CE T1-weighted (CE-T1W) sequence with fat suppression (FS) and magnetization transfer (MT) for early detection and characterization of infectious meningitis. MATERIALS AND METHODS: Fifty patients and 10 control subjects were evaluated with the CE-FLAIR and the CE-T1W sequences with FS and MT. Qualitative assessment was done by two observers for presence and grading of abnormal leptomeningeal enhancement. Quantitative assessment included computation of net meningeal enhancement, using single pixel signal intensity software. A newly devised FLAIR based scoring system, based on certain imaging features including ventricular dilatation, ependymal enhancement, infarcts and subdural effusions was used to indicate the etiology. Data were analysed using the Student's t test, Cohen's Kappa coefficient, Pearson's correlation coefficient, the intraclass correlation coefficient, one way analysis of variance, and Fisher's exact test with Bonferroni correction as the post hoc test. RESULTS: The CE-FLAIR sequence demonstrated a better sensitivity (100%), diagnostic accuracy (95%), and a stronger correlation with the cerebrospinal fluid, total leukocyte count (r = 0.75), protein (r = 0.77), adenosine deaminase (r = 0.81) and blood glucose (r = -0.6) values compared to the CE-T1W sequences. Qualitative grades and quantitative meningeal enhancement on the CE-FLAIR sequence were also significantly greater than those on the other sequences. The FLAIR based scoring system yielded a diagnostic accuracy of 91.6% and a sensitivity of 96%. A strong inverse Pearson's correlation (r = -0.95) was found between the assigned score and patient's Glasgow Coma Scale at the time of admission. CONCLUSION: The CE-FLAIR sequence is better suited for evaluating infectious meningitis and could be included as a part of the routine MR imaging protocol.

Quercetin induces apoptosis and cell cycle arrest in triple-negative breast cancer cells through modulation of Foxo3a activity

Quercetin, a plant-derived flavonoid found in fruits, vegetables and tea, has been known to possess bioactive properties such as anti-oxidant, anti-inflammatory and anti-cancer. In this study, anti-cancer effect of quercetin and its underlying mechanisms in triple-negative breast cancer cells was investigated. MTT assay showed that quercetin reduced breast cancer cell viability in a time and dose dependent manner. For this, quercetin not only increased cell apoptosis but also inhibited cell cycle progression. Moreover, quercetin increased FasL mRNA expression and p51, p21 and GADD45 signaling activities. We also observed that quercetin induced protein level, transcriptional activity and nuclear translocation of Foxo3a. Knockdown of Foxo3a caused significant reduction in the effect of quercetin on cell apoptosis and cell cycle arrest. In addition, treatment of JNK inhibitor (SP 600125) abolished quercetin-stimulated Foxo3a activity, suggesting JNK as a possible upstream signaling in regulation of Foxo3a activity. Knockdown of Foxo3a and inhibition of JNK activity reduced the signaling activities of p53, p21 and GADD45, triggered by quercetin. Taken together, our study suggests that quercetin induces apoptosis and cell cycle arrest via modification of Foxo3a signaling in triple-negative breast cancer cells.