Search

BackgroundBreast cancer screening with dynamic contrast-enhanced MRI (DCE-MRI) is recommended for high-risk women but has limitations, including variable specificity and difficulty in distinguishing cancerous (CL) and high-risk benign lesions (HRBL) from average-risk benign lesions (ARBL). Complementary non-invasive imaging techniques would be useful to improve specificity.PurposeTo evaluate the performance of a previously-developed breast-specific diffusion-weighted MRI (DW-MRI) model (BS-RSI3C) to improve discrimination between CL, HRBL, and ARBL in an enriched screening population.Study typeProspective.SubjectsExactly 187 women, either with mammography screening recommending additional imaging (N = 49) or high-risk individuals undergoing routine breast MRI (N = 138), before the biopsy.Field strength/sequenceMultishell DW-MRI echo planar imaging sequence with a reduced field of view at 3.0 T.AssessmentA total of 72 women had at least one biopsied lesion, with 89 lesions categorized into ARBL, HRBL, CL, and combined CLs and HRBLs (CHRLs). DW-MRI data were processed to produce apparent diffusion coefficient (ADC) maps, and estimate signal contributions (C1, C2, and C3-restricted, hindered, and free diffusion, respectively) from the BS-RSI3C model. Lesion regions of interest (ROIs) were delineated on DW images based on suspicious DCE-MRI findings by two radiologists; control ROIs were drawn in the contralateral breast.Statistical testsOne-way ANOVA and two-sided t-tests were used to assess differences in signal contributions and ADC values among groups. P-values were adjusted using the Bonferroni method for multiple testing, P = 0.05 was used for the significance level. Receiver operating characteristics (ROC) curves and intra-class correlations (ICC) were also evaluated.ResultsC1, √C1C2, and logC1C2C3$$ \log \left(\frac{{\mathrm{C}}_1{\mathrm{C}}_2}{{\mathrm{C}}_3}\right) $$ were significantly different in HRBLs compared with ARBLs (P-values

The reported fatality rate of COVID-19 was significantly differ between different countries, provinces in a country, and hospitals in a province. It is important to find and analysed the source of variation in fatality rates to control future epidemics of infection disease. This study propose an approach to investigates the hospital quality of care and its impact on the in-hospital fatality rates of COVID-19 among over 30 years old patients in Iran. The study included 78,217 COVID-19 hospitalized patients over 30 years old from 34 hospitals in Razavi Khorasan province between January 20, 2020, and June 20, 2021. Attribute control charts were employed to evaluate the quality of care in hospitals during four peaks of COVID-19. To account for the impact of hospital quality on in-hospital fatality rates by adjusting on patient characteristics, two predictive models; Poisson and Binomial regression were utilized. The adjusted odds ratio of COVID-19 fatality in no quality confirmed (NQC) hospitals to the quality confirmed (QC) hospitals is 3.48 C.I.95% (2.38, 5.10) at the first peak among patients without other risk factors. The significant negative interactions with QC and peaks indicates that the provision of quality care serves to mitigate the risk of fatality in NQC hospitals during these peaks. The significant negative interaction between diabetes and QC demonstrated that the relative risk in NQC hospitals for no diabetes patient is higher than diabetic patients. There is no significant interaction between age, SaO2, and ARDS with QC; it means that the odds of fatality in NQC hospitals is not depends to these factors. The use of attribute control charts facilitated timely identification of trends and outliers, enabling proactive interventions to enhance patient care. This research underscores the critical role of hospital quality in managing patient outcomes during the COVID-19 pandemic and emphasizes the necessity for continuous monitoring and quality improvement initiatives in healthcare settings. The findings advocate for collaborative efforts among healthcare providers to implement best practices, particularly during surges in cases, to optimize resource allocation and improve overall quality of care. [ABSTRACT FROM AUTHOR]

Abortion can be a very stressful experience for women, and many social and psychological factors can influence this stress. The present study aims to investigate the impact of perceived social support on the marital satisfaction of women who have undergone an abortion. The study also explored whether resilience played a mediating role in this relationship. Data were analyzed from the cross-sectional study. The Perceived Social Support (including Social support, friend support, and other support subscales), ENRICH marital satisfaction, and Connor-Davidson Resilience questionnaire were completed by 150 women who had undergone an abortion and were referred to hospitals and clinics of Jahrom University of Medical Sciences from April 2021 to June 2021. The structural equation modeling (SEM) approach was used to obtain the direct and indirect effects of Perceived Social Support subscales and Resilience on marital satisfaction. The study found that the women who participated had high marital satisfaction and social support scores, while their resilience scores were moderate. The results indicated a positive correlation between social support dimensions and marital satisfaction and resilience. The study also revealed that family support (β = 0.41, p < 0.001), other supports (β = 0.46, p < 0.001), and resilience as a mediating variable (β = 0.15, p < 0.001) had a direct and significant positive impact on marital satisfaction. However, none of the three domains of perceived social support showed any indirect significant relationship with marital satisfaction. The study's findings demonstrate that the perception of social support from family members and other individuals can significantly impact the level of satisfaction in a marriage. Appropriate social support can increase resilience and help couples better cope with the stress associated with abortion. This study suggests that educating families, healthcare providers, and other individuals can help women experiencing this issue by providing them with counseling and support. This can ultimately help women maintain their mental and sexual health. [ABSTRACT FROM AUTHOR]

"Green chemistry" describes the development of new technologies that reduce or eliminate the need for hazardous compounds or the production of them. In order to accomplish this goal, we have developed a new magnetic recyclable biocatalyst in this study by successfully applying aspartic acid to magnetic nanoparticles. Aspartic acid's molecular makeup made it possible for it to stabilize on magnetic nanoparticles using a straightforward method. We characterized the synthesized catalyst using microscopic and spectroscopic techniques such as Fourier transform infrared (FT-IR), X-ray diffraction (XRD), Field emission scanning electron microscopy (FE-SEM), Energy-dispersive X-ray spectroscopy (EDS), vibrating sample magnetometer (VSM) and transmission electron microscopy (TEM). The catalytic activity of this organocatalyst was evaluated for the synthesis of benzo[b]pyran and pyrano[3,2–c] chromene derivatives, exhibiting excellent efficiency. This protocol offers several benefits, such as using a low-cost biocatalyst, nontoxicity, high product yield, easy separation, short reaction times, catalyst reusability, and H2O/EtOH solvent. In summary, our research indicates a feasible approach towards developing a novel magnetic biocatalyst suitable for application in organic synthesis. [ABSTRACT FROM AUTHOR]

This research aimed to present a model for the competitiveness of selected Iranian knowledge-based companies in the fourth industrial revolution. Therefore, in terms of the goal, it is applied research because, in addition to the awareness and scientific aspect, it will also have a practical element for the relevant organizations. According to the purpose and nature of this research, in terms of method, it was qualitative research conducted by interviewing research experts. The statistical population of the study included Iran’s knowledge-based companies, which, according to the classification of the working group for evaluating and recognizing the competence of knowledge-based companies and institutions, the field of electricity and electronics, laser and photonics, were chosen due to their greater dependence on the components of the fourth industrial revolution. The approach of the qualitative part has been grounded in theory. The results showed that the competitiveness model of selected Iranian knowledge-based companies in the fourth industrial revolution includes internal organizational factors, Extra-organizational factors, agility, capable intellectual resources, value chain, innovative services and products, environmental factors, organizational factors, international drivers of the fourth industrial revolution, data challenges in the implementation of technology 04, governance factors in the fourth industrial revolution, industry’s relationship with University, increasing information literacy, continuous research and development, identification of technological advantage, capability building, laws appropriate to the characteristics of the fourth industrial revolution, attention to the environment, attention to the market and the needs created by the fourth industrial revolution, determining strategy, investment in technology, survival, and value creation. [ABSTRACT FROM AUTHOR]

Mesenchymal stem cells (MSCs) have gained considerable attention in the field of regenerative medicine due to their ability to secrete small extracellular vesicles (EVs) known as exosomes. This review delves into the various biological activities of MSCs and the cell interactions enabled by these exosomes, with a focus on their potential for neuronal regeneration and the treatment of neurological disorders. We scrutinize findings from multiple studies that underscore the neuroprotective and neuro-regenerative effects of exosomes derived from MSCs, illuminating their mechanisms of action and therapeutic applications. This review thoroughly investigates all related pathways, miRNAs, and factors to suggest potential strategies for enhancing therapy for neurological disorders using exosomes and miRNAs, and for boosting neuronal regeneration. [ABSTRACT FROM AUTHOR]

Iran encompasses various climate zones, with approximately 85% of its agricultural land located in arid and semi-arid regions. To mitigate the effects of drought stress and enhance crop adaptation and yield, numerous advanced techniques, including hormone applications, have been extensively studied. This research aimed to investigate the effects of foliar application of different concentrations of salicylic acid and jasmonic acid on the morphological, physiological, and biochemical characteristics of garden thyme under water deficit stress conditions. The study was conducted using a split-factorial design within a randomized complete block framework, with three replications at the Varamin and Absard research fields in Iran during the 2019 growing season. The primary factor was irrigation, assessed at two levels: normal and water-deficit stress. Sub-factors were the foliar application of salicylic acid and jasmonic acid at various concentrations, and the treatment groups were in factorial arrangements. Salicylic acid was applied at concentrations of 0, 25, and 50 mg L-1, while jasmonic acid was applied at 0, 1, and 2 mg L-1. The results demonstrated that water deficit stress significantly reduced plant height, dry weight yield, and chlorophyll a, b, and total chlorophyll content, while it increased proline accumulation. Under water deficit stress, the maximum levels of dityrosine and 8-hydroxy-2'-deoxyguanosine (34.18 and 13.52 nmol mg-1 protein, respectively) were observed, which were 11% and 20% higher, respectively, than those under well-watered conditions. Furthermore, the interaction between foliar applications of different concentrations of salicylic acid and jasmonic acid mitigated the detrimental effects of water deficit stress, enhancing the tolerance of garden thyme. Overall, the findings suggest that under drought conditions, the application of salicylic acid and jasmonic acid can significantly improve the performance of garden thyme. [ABSTRACT FROM AUTHOR]

Background & Aim: Timely identification of the patients requiring intensive care unit admission (ICU) could be life‐saving. We aimed to compare different machine learning algorithms to predict the requirements for ICU admission in COVID‐19 patients. Methods: We screened all patients with COVID‐19 at six academic hospitals in Tehran comprising our study population. A total of 44,112 COVID‐19 patients (≥18 years old) were included, among which 7722 patients were hospitalized. We used a Random Forest algorithm to select significant variables. Then, prediction models were developed using the Support Vector Machine, Naıve Bayes, logistic regression, lightGBM, decision tree, and K‐Nearest Neighbor algorithms. Sensitivity, specificity, accuracy, F1 score, and receiver operating characteristic‐Area Under the Curve (AUC) were used to compare the prediction performance of different models. Results: Based on random Forest, the following predictors were selected: age, cardiac disease, cough, hypertension, diabetes, influenza & pneumonia, malignancy, and nervous system disease. Age was found to have the strongest association with ICU admission among COVID‐19 patients. All six models achieved an AUC greater than 0.60. Naıve Bayes achieved the best predictive performance (AUC = 0.71). Conclusion: Naïve Bayes and lightGBM demonstrated promising results in predicting ICU admission needs in COVID‐19 patients. Machine learning models could help quickly identify high‐risk patients upon entry and reduce mortality and morbidity among COVID‐19 patients. [ABSTRACT FROM AUTHOR]

In this study, we delved into the intricate world of autism spectrum disorder (ASD) and its connection to the disturbance in the Wnt signaling pathway and immunological abnormalities. Our aim was to evaluate the impact of silibinin, a remarkable modulator of both the Wnt signaling pathway and the immune system, on the neurobehavioral and molecular patterns observed in a zebrafish model of ASD induced by valproic acid (VPA). Because silibinin is a hydrophobic molecule and highly insoluble in water, it was used in the form of silibinin nanoparticles (nanosilibinin, NS). After assessing survival, hatching rate, and morphology of zebrafish larvae exposed to different concentrations of NS, the appropriate concentrations were chosen. Then, zebrafish embryos were exposed to VPA (1 μM) and NS (100 and 200 μM) at the same time for 120 h. Next, anxiety and inattentive behaviors and the expression of CHD8, CTNNB, GSK3beta, LRP6, TNFalpha, IL1beta, and BDNF genes were assessed 7 days post fertilization. The results indicated that higher concentrations of NS had adverse effects on survival, hatching, and morphological development. The concentrations of 100 and 200 μM of NS could ameliorate the anxiety‐like behavior and learning deficit and decrease ASD‐related cytokines (IL1beta and TNFalpha) in VPA‐treated larvae. In addition, only 100 μM of NS prevented raising the gene expression of Wnt signaling‐related factors (CHD8, CTNNB, GSK3beta, and LRP6). In conclusion, NS treatment for the first 120 h showed therapeutic effect on an autism‐like phenotype probably via reducing the expression of pro‐inflammatory cytokines genes and changing the expression of Wnt signaling components genes. [ABSTRACT FROM AUTHOR]