Interventions in reducing caesarean section in the world: A systematic review

Caesarean section without medical indication imposes many problems to families, personnel and medical equipment causing some side effects to pregnant woman and foetus, compared to natural childbirth. The present study aimed to evaluate the interventions in reducing caesarean section in the world. This study was a systematic review using Embase, PubMed, Scopus, Web of Science, Science Direct, Magiran and SID databases and grey literature. All studies conducted during 2000–2018 were reviewed and finally the studies with inclusion and exclusion criteria were selected. A total of 19 studies were selected among 5,559 studies. The interventions conducted for reducing caesarean section included training the specialists and women by using Six Sigma method, changing the guidelines, reviewing the definition of natural childbirth various stages, encouraging the natural childbirth and expanding painless childbirth. All interventions were divided into educational strategy and managerial strategy. The interventions can be implemented to change the behaviour of physicians and attitude of pregnant women in order to reduce caesarean section. In this regard, the authorities are recommended to make more efforts

Synthesis, Molecular Docking, Molecular Dynamics Studies, and Biological Evaluation of 4H-Chromone-1,2,3,4-tetrahydropyrimidine-5-carboxylate Derivatives as Potential Antileukemic Agents

A series of 4H-chromone-1,2,3,4-tetrahydropyrimidine-5-carboxylates derivatives were synthesized via a three component one-pot condensation of chromone-3-carbaldehyde, alkyl acetoacetate, and urea or thiourea, using MCM-41-SO3H as efficient nanocatalysts and evaluated for their anticancer activity using a combined in silico docking and molecular dynamics protocol to estimate the binding affinity of the title compounds with the Bcr-Abl oncogene. Two programs, AutoDock 4 and AutoDock Vina software were applied to dock the target protein with synthesized compounds and ATP. AutoDock runs resulted in binding energy scores from -7.8 to -10.16 kcal/mol for AutoDock 4 and -6.9 to -8.5 (kcal/mol) for AutoDock Vina. Furthermore, molecular dynamics (MD) simulations are performed using Gromacs for up to 20 ns simulation time investigating the stability of a ligand-protein complex. Finally, a theoretical experiment using MD simulation for 10 ns was performed without defining the initial coordinates, and the affinity binding of ligand to receptors was directly studied, which revealed that the ligand approaches the active sites. The relative free binding energy for the structure 06 (S06), which has the highest binding energy in Autodock 4 and Autodock Vina (-10.10 and -8.5 kcal/mol, respectively), was also evaluated by molecular mechanics (MM) with Poisson-Boltzmann (PB) and a surface area solvation (MM-PBSA) method using g_mmpbsa tools for the last 15 ns MD. On the basis of binding energy scores, a negative binding energy value of 73.6 kcal/mol, S06, was recognized as the dominant potential inhibitors. The cytotoxic properties of S06 was evaluated against three cell lines, acute T cell leukemia (Jurkat), human chronic myelogenous leukemia, (K562) and human foreskin fibroblast (Hu02) using the microculture tetrazolium test MTT assay. Cisplatin was used as the reference agent. The results indicated that S06 has a higher safety index (SI = 0.73, IC50 = 152.64 μg/mL for Jurkat and IC50 = 110.25 μg/mL for Hu02, P < 0.05 means ± SD for four independent experiments) compared to cisplatin (SI = 0.56, IC50 = 8.86 μg/mL for Jurkat and IC50 = 4.96 μg/mL for Hu02). The in silico results indicated that the proposed structures, which have no toxic effects, are potential tyrosine kinase inhibitors (TKIs) that target Bcr-Abl and thus prevent uncontrolled cell growth (proliferation) but not necessarily cell death (apoptosis) and might potentially constitute an interesting novel class of targeted antileukemic drugs, which deserve further studies

Interventions in reducing caesarean section in the world:A systematic review

Caesarean section without medical indication imposes many problems to families, personnel and medical equipment causing some side effects to pregnant woman and foetus, compared to natural childbirth. The present study aimed to evaluate the interventions in reducing caesarean section in the world. This study was a systematic review using Embase, PubMed, Scopus, Web of Science, Science Direct, Magiran and SID databases and grey literature. All studies conducted during 2000–2018 were reviewed and finally the studies with inclusion and exclusion criteria were selected. A total of 19 studies were selected among 5,559 studies. The interventions conducted for reducing caesarean section included training the specialists and women by using Six Sigma method, changing the guidelines, reviewing the definition of natural childbirth various stages, encouraging the natural childbirth and expanding painless childbirth. All interventions were divided into educational strategy and managerial strategy. The interventions can be implemented to change the behaviour of physicians and attitude of pregnant women in order to reduce caesarean section. In this regard, the authorities are recommended to make more efforts

Knowledge and Attitude of Iranian Dental Students and Specialists about Obstructive Sleep Apnea

Objective Obstructive sleep apnea (OSA) is a relatively common sleep disorder, which leads to multiple sleep arousals and hypoxemia. We aimed to assess the knowledge and attitude of students and faculty members of ShahidBeheshti Dental School, Tehran, Iran about OSA. MethodsWe conducted a cross-sectional study on undergraduate and postgraduate students and faculty members of oral and maxillofacial (OMF) surgery, orthodontics, and oral medicine departments of ShahidBeheshti Dental School. The Obstructive Sleep Apnea Knowledge and Attitude (OSAKA) questionnaire was used to obtain information. We used the Chi-square, Kruskal Wallis, and Mann-Whitney U tests for statistical analysis. The data were analyzed by SPSS 22.0 (α &lt;0.05). Results One hundred ninety-seven participants, including 43 dental students, 68 postgraduate students, and 64 faculty members filled out the questionnaire. The mean knowledge score among all participants was 10.69±3.133. Overall, OMF medicine and OMF surgeryfaculty members had significantly higher correct answer choices in the knowledge section than fifth and sixth-year dental students (P&lt;0.001). There was no significant difference among other groups (P&gt;0.05). About attitude, 91% of respondents reported that OSA is an important or extremely important disorder. However, only 10.2% and 16.9% felt confident about the ability to manage patients with OSA and identifying patients at risk of OSA, respectively. Overall, gender and educational level were correlated with the mean attitude score (P&lt;0.05). Conclusion All participants had poor knowledge but a positive attitude towards OSA. This shows the necessity of better education about OSA

The effect of low-dose aspirin on aspirin triggered lipoxin, interleukin 1 beta, and prostaglandin E2 levels in periapical fluid: a double-blind randomized clinical trial

Abstract Background The role of pro-resolving mediators in inflammation is a new concern in research. The effect of low-dose aspirin on production of a special kind of these mediators named aspirin triggered lipoxin (ATL) has been studied on different tissues. This randomized clinical trial evaluated the effect of low-dose aspirin on ATL and pro-inflammatory mediators’ level in periapical fluid of necrotic teeth with large lesions. Methods Twenty-four patients with necrotic pulp and periapical lesion were randomly assigned to low-dose aspirin and placebo groups. In the first appointment, canals were shaped up to F3 size and #40 K-file and cleaned with 10 milliliters 2.5% sodium hypochlorite and 17% Ethylenediaminetetraacetic acid. Periapical fluid was sampled by a paper cone. The tooth was temporized without any intracanal medication. Tablets were administered for 7 days, then the teeth were re-opened and the sampling were repeated. Interleukin-1 beta (IL-1β), prostaglandin E2 (PGE2) and ATL were analyzed by enzyme-linked immunosorbent assay. Data were analyzed with paired t-test using SPSS statistical software, version 21 (α = 0.05). Results A significant reduction in PGE2 and IL-1β was noted in the aspirin-treated group while an increase in ATL was observed (P  0.05). Conclusion Low-dose aspirin can influence the inflammatory process by reducing pro-inflammatory mediators such as PGE2 and IL-1β, as well as increasing the pro-resolving mediators such as ATL. Trial registration IRCT20191211045702N1

Synthesis, Molecular Docking, Molecular Dynamics Studies, and Biological Evaluation of 4<i>H</i>‑Chromone-1,2,3,4-tetrahydropyrimidine-5-carboxylate Derivatives as Potential Antileukemic Agents

A series of 4<i>H</i>-chromone-1,2,3,4-tetrahydropyrimidine-5-carboxylates derivatives were synthesized via a three component one-pot condensation of chromone-3-carbaldehyde, alkyl acetoacetate, and urea or thiourea, using MCM-41-SO₃H as efficient nanocatalysts and evaluated for their anticancer activity using a combined in silico docking and molecular dynamics protocol to estimate the binding affinity of the title compounds with the Bcr-Abl oncogene. Two programs, AutoDock 4 and AutoDock Vina software were applied to dock the target protein with synthesized compounds and ATP. AutoDock runs resulted in binding energy scores from −7.8 to −10.16 kcal/mol for AutoDock 4 and −6.9 to −8.5 (kcal/mol) for AutoDock Vina. Furthermore, molecular dynamics (MD) simulations are performed using Gromacs for up to 20 ns simulation time investigating the stability of a ligand–protein complex. Finally, a theoretical experiment using MD simulation for 10 ns was performed without defining the initial coordinates, and the affinity binding of ligand to receptors was directly studied, which revealed that the ligand approaches the active sites. The relative free binding energy for the structure 06 (<b>S06</b>), which has the highest binding energy in Autodock 4 and Autodock Vina (−10.10 and −8.5 kcal/mol, respectively), was also evaluated by molecular mechanics (MM) with Poisson–Boltzmann (PB) and a surface area solvation (MM-PBSA) method using g_mmpbsa tools for the last 15 ns MD. On the basis of binding energy scores, a negative binding energy value of 73.6 kcal/mol, <b>S06</b>, was recognized as the dominant potential inhibitors. The cytotoxic properties of <b>S06</b> was evaluated against three cell lines, acute T cell leukemia (Jurkat), human chronic myelogenous leukemia, (K562) and human foreskin fibroblast (Hu02) using the microculture tetrazolium test MTT assay. Cisplatin was used as the reference agent. The results indicated that <b>S06</b> has a higher safety index (SI = 0.73, IC50 = 152.64 μg/mL for Jurkat and IC50 = 110.25 μg/mL for Hu02, <i>P</i> < 0.05 means ± SD for four independent experiments) compared to cisplatin (SI = 0.56, IC50 = 8.86 μg/mL for Jurkat and IC50 = 4.96 μg/mL for Hu02). The <i>in silico</i> results indicated that the proposed structures, which have no toxic effects, are potential tyrosine kinase inhibitors (TKIs) that target Bcr-Abl and thus prevent uncontrolled cell growth (proliferation) but not necessarily cell death (apoptosis) and might potentially constitute an interesting novel class of targeted antileukemic drugs, which deserve further studies

Artificial Intelligence in Cancer Care: From Diagnosis to Prevention and Beyond

&lt;p&gt;Artificial Intelligence (AI) has made significant strides in revolutionizing cancer care, encompassing various aspects from diagnosis to prevention and beyond. With its ability to analyze vast amounts of data, recognize patterns, and make accurate predictions, AI has emerged as a powerful tool in the fight against cancer. This article explores the applications of AI in cancer care, highlighting its role in diagnosis, treatment decision-making, prevention, and ongoing management. In the realm of cancer diagnosis, AI has demonstrated remarkable potential. By processing patient data, including medical imaging, pathology reports, and genetic profiles, AI algorithms can assist in early detection and accurate diagnosis. Image recognition algorithms can analyze radiological images, such as mammograms or CT scans, to detect subtle abnormalities and assist radiologists in identifying potential tumors. AI can also aid pathologists in analyzing tissue samples, leading to more precise and efficient cancer diagnoses. AI's impact extends beyond diagnosis into treatment decision-making. The integration of AI algorithms with clinical data allows for personalized treatment approaches. By analyzing patient characteristics, disease stage, genetic markers, and treatment outcomes, AI can provide valuable insights to oncologists, aiding in treatment planning and predicting response to specific therapies. This can lead to more targeted and effective treatment strategies, improving patient outcomes and reducing unnecessary treatments and side effects. Furthermore, AI plays a crucial role in cancer prevention. By analyzing genetic and environmental risk factors, AI algorithms can identify individuals at higher risk of developing certain cancers. This enables targeted screening programs and early interventions, allowing for timely detection and prevention of cancer. Additionally, AI can analyze population-level data to identify trends and patterns, contributing to the development of public health strategies for cancer prevention and control. AI's involvement in cancer care goes beyond diagnosis and treatment, encompassing ongoing management and survivorship. AI-powered systems can monitor treatment response, track disease progression, and detect recurrence at an early stage. By continuously analyzing patient data, including imaging, laboratory results, and clinical assessments, AI algorithms can provide real-time insights, facilitating timely interventions and adjustments to treatment plans. This proactive approach to disease management improves patient outcomes and enhances quality of life.&lt;/p&gt