Familial Hypercholesterolemia (FH) in Iran: Findings from the Four-Year FH Registry

BACKGROUND

Familial hypercholesterolemia (FH) is a common autosomal dominant disease. Its diagnosis in Iran was uncommon. Iran registry of FH (IRFH) has been started from 2017 from Isfahan. In this study, we report the four-year FH registry.

METHODS

The Iran FH registry is an ongoing study which is followed by a dynamic cohort. It has been started from 2017. The patients are selected from laboratories due to high cholesterol level and who have history of premature cardiovascular disease. The Dutch Lipid Clinic Network (DLCN) criteria are used for the detection of FH. Cascade screening is performed for detection of first-degree relative of patients.

RESULTS

Among the 997 individuals included in this registry, they were 522 (mean age 51.41 ± 12.91 year), 141 (mean age 51.66 ± 8.3 year), and 129 (mean age 41 ± 16.5 year) patients from laboratories, premature cardiovascular disease, and relatives, respectively. In total, 263 patients were diagnosed with probable or definite FH, and others were in the possible group. Low-density lipoprotein cholesterol (LDL) level was 141.42 ± 45.27 mg/dl in the laboratory group and 54.9% of patients were on LLT treatment. In patients with premature cardiovascular disease and FH, the LDL level was 91.93 ± 32.58 and was on LLT treatment. The LDL concentration in the first relative of FH patients was 152.88 ± 70.77 and 45.7% of them are on LLT therapy.

CONCLUSIONS

Most of FH patients were underdiagnosed and undertreated before their inclusion in the IRFH. Cascade screening helps in the improvement of diagnosis.

AC electrokinetic isolation and detection of extracellular vesicles from dental pulp stem cells: Theoretical simulation incorporating fluid mechanics

Extracellular vesicles (EVs) are cell-derived nanoscale vesicles involved in intracellular communication and the transportation of biomarkers. EVs released by mesenchymal stem cells have been recently reported to play a role in cell-free therapy of many diseases. However, the demand for better research tools to replace the tedious conventional methods used to study EVs is getting stronger. EVs' manipulation using alternating current (AC) electrokinetic forces in a microfluidic device has appeared to be a reliable and sensitive diagnosis and trapping technique. Given that different AC electrokinetic forces may contribute to the overall motion of particles and fluids in a microfluidic device, EVs' electrokinetic trapping must be examined considering all dominant forces involved depending on the experimental conditions. In this paper, AC electrokinetic trapping of EVs using an interdigitated electrode arrays is investigated. A 2D numerical simulation incorporating the two significant AC electrokinetic phenomena (Dielectrophoresis and AC electroosmosis) has been performed. Theoretical predictions are then compared with experimental results and allow for a plausible explanation of observations inconsistent with DEP theory. It is demonstrated that the inconsistencies can be attributed to a significant extent to the contribution of the AC electroosmotic effect.

A simple, low cost and reusable microfluidic gradient strategy and its application in modeling cancer invasion

Microfluidic chemical gradient generators enable precise spatiotemporal control of chemotactic signals to study cellular behavior with high resolution and reliability. However, time and cost consuming preparation steps for cell adhesion in microchannels as well as requirement of pumping facilities usually complicate the application of the microfluidic assays. Here, we introduce a simple strategy for preparation of a reusable and stand-alone microfluidic gradient generator to study cellular behavior. Polydimethylsiloxane (PDMS) is directly mounted on the commercial polystyrene-based cell culture surfaces by manipulating the PDMS curing time to optimize bonding strength. The stand-alone strategy not only offers pumpless application of this microfluidic device but also ensures minimal fluidic pressure and consequently a leakage-free system. Elimination of any surface treatment or coating significantly facilitates the preparation of the microfluidic assay and offers a detachable PDMS microchip which can be reused following to a simple cleaning and sterilization step. The chemotactic signal in our microchip is further characterized using numerical and experimental evaluations and it is demonstrated that the device can generate both linear and polynomial signals. Finally, the feasibility of the strategy in deciphering cellular behavior is demonstrated by exploring cancer cell migration and invasion in response to chemical stimuli. The introduced strategy can significantly decrease the complexity of the microfluidic chemotaxis assays and increase their throughput for various cellular and molecular studies.

Organoid Technology: Current Standing and Future Perspectives

Organoids are powerful systems to facilitate the study of individuals' disorders and personalized treatments. Likewise, emerging this technology has improved the chance of translatability of drugs for pre-clinical therapies and mimicking the complexity of organs, while it proposes numerous approaches for human disease modeling, tissue engineering, drug development, diagnosis, and regenerative medicine. In this review, we outline the past/present organoid technology and summarize its faithful applications, then, we discuss the challenges and limitations encountered by 3D organoids. In the end, we offer the human organoids as basic mechanistic infrastructure for "human modelling" systems to prescribe personalized medicines. © AlphaMed Press 2021 SIGNIFICANCE STATEMENT: This concise review concerns about organoids, available methods for in vitro organoid formation and different types of human organoid models. We, then, summarize biological approaches to improve 3D organoids complexity and therapeutic potentials of organoids. Despite the existing incomprehensive review articles in literature that examine partial aspects of the organoid technology, the present review article comprehensively and critically presents this technology from different aspects. It effectively provides a systematic overview on the past and current applications of organoids and discusses the future perspectives and suggestions to improve this technology and its applications.

Inefficiency of SIR models in forecasting COVID-19 epidemic: a case study of Isfahan

The multifaceted destructions caused by COVID-19 have been compared to that of World War II. What makes the situation even more complicated is the ambiguity about the duration and ultimate spread of the pandemic. It is especially critical for the governments, healthcare systems, and economic sectors to have an estimate of the future of this disaster. By using different mathematical approaches, including the classical susceptible-infected-recovered (SIR) model and its derivatives, many investigators have tried to predict the outbreak of COVID-19. In this study, we simulated the epidemic in Isfahan province of Iran for the period from Feb 14th to April 11th and also forecasted the remaining course with three scenarios that differed in terms of the stringency level of social distancing. Despite the prediction of disease course in short-term intervals, the constructed SIR model was unable to forecast the actual spread and pattern of epidemic in the long term. Remarkably, most of the published SIR models developed to predict COVID-19 for other communities, suffered from the same inconformity. The SIR models are based on assumptions that seem not to be true in the case of the COVID-19 epidemic. Hence, more sophisticated modeling strategies and detailed knowledge of the biomedical and epidemiological aspects of the disease are needed to forecast the pandemic.

Model Prediction for In-Hospital Mortality in Patients with COVID-19: A Case-Control Study in Isfahan, Iran

The COVID-19 pandemic has now imposed an enormous global burden as well as a large mortality in a short time period. Although there is no promising treatment, identification of early predictors of in-hospital mortality would be critically important in reducing its worldwide mortality. We aimed to suggest a prediction model for in-hospital mortality of COVID-19. In this case-control study, we recruited 513 confirmed patients with COVID-19 from February 18 to March 26, 2020 from Isfahan COVID-19 registry. Based on extracted laboratory, clinical, and demographic data, we created an in-hospital mortality predictive model using gradient boosting. We also determined the diagnostic performance of the proposed model including sensitivity, specificity, and area under the curve (AUC) as well as their 95% CIs. Of 513 patients, there were 60 (11.7%) in-hospital deaths during the study period. The diagnostic values of the suggested model based on the gradient boosting method with oversampling techniques using all of the original data were specificity of 98.5% (95% CI: 96.8-99.4), sensitivity of 100% (95% CI: 94-100), negative predictive value of 100% (95% CI: 99.2-100), positive predictive value of 89.6% (95% CI: 79.7-95.7), and an AUC of 98.6%. The suggested model may be useful in making decision to patient's hospitalization where the probability of mortality may be more obvious based on the final variable. However, moderate gaps in our knowledge of the predictors of in-hospital mortality suggest further studies aiming at predicting models for in-hospital mortality in patients with COVID-19.

Challenges and opportunities of digital health in a post-COVID19 world

Digital health as a rapidly growing medical field relies comprehensively on human health data. Conventionally, the collection of health data is mediated by officially diagnostic instruments, operated by health professionals in clinical environments and under strict regulatory conditions. Mobile health, telemedicine, and other smart devices with Internet connections are becoming the future choices for collecting patient information. Progress of technologies has facilitated smartphones, wearable devices, and miniaturized health-care devices. These devices allow the gathering of an individual's health-care information at the patient's home. The data from these devices will be huge, and by integrating such enormous data using Artificial Intelligence, more detailed phenotyping of disease and more personalized medicine will be realistic. The future of medicine will be progressively more digital, and recognizing the importance of digital technology in this field and pandemic preparedness planning has become urgent.

Asymptomatic carriers of coronavirus disease 2019 among healthcare workers in Isfahan, Iran

Aim: This study aimed to investigate the prevalence of coronavirus disease 2019 (COVID-19) among healthcare workers (HCWs) in Isfahan, Iran. Materials & methods: HCWs in COVID-19 wards of three referral COVID-19 hospitals in Isfahan were screened and tested for COVID-19 infection. Results: In total, 102 HCWs were screened whose median age was 43 years old. Moreover, 21 (20.5%) of them had a history of suspected infection with SARS-CoV2, mostly (66.6%) without any symptoms while six (28.5%) of them suffered from relatively mild diseases and one (4.7%) was diagnosed with pulmonary embolism. Conclusion: It was found that HCWs were prone to be asymptomatic carriers while their computed tomography images were normal. Therefore, it is recommended that reverse-transcriptase real-time-PCR be essential for the diagnosis of infections.

The role of hypoxia in the tumor microenvironment and development of cancer stem cell: a novel approach to developing treatment

Hypoxia is a common feature of solid tumors, and develops because of the rapid growth of the tumor that outstrips the oxygen supply, and impaired blood flow due to the formation of abnormal blood vessels supplying the tumor. It has been reported that tumor hypoxia can: activate angiogenesis, thereby enhancing invasiveness and risk of metastasis; increase survival of tumor, as well as suppress anti-tumor immunity and hamper the therapeutic response. Hypoxia mediates these effects by several potential mechanisms: altering gene expression, the activation of oncogenes, inactivation of suppressor genes, reducing genomic stability and clonal selection. We have reviewed the effects of hypoxia on tumor biology and the possible strategiesto manage the hypoxic tumor microenvironment (TME), highlighting the potential use of cancer stem cells in tumor treatment.

A meta-analysis of microRNA expression profiling studies in heart failure

Heart failure (HF) is a major consequence of many cardiovascular diseases with high rate of morbidity and mortality. Early diagnosis and prevention are hampered by the lack of informative biomarkers. The aim of this study was to perform a meta-analysis of the miRNA expression profiling studies in HF to identify novel candidate biomarkers or/and therapeutic targets. A comprehensive literature search of the PubMed for miRNA expression studies related to HF was carried out. The vote counting and robust rank aggregation meta-analysis methods were used to identify significant meta-signatures of HF-miRs. The targets of HF-miRs were identified, and network construction and gene set enrichment analysis (GSEA) were performed to identify the genes and cognitive pathways most affected by the dysregulation of the miRNAs. The literature search identified forty-five miRNA expression studies related to CHF. Shared meta-signature was identified for 3 up-regulated (miR-21, miR-214, and miR-27b) and 13 down-regulated (miR-133a, miR-29a, miR-29b, miR-451, miR-185, miR-133b, miR-30e, miR-30b, miR-1, miR-150, miR-486, miR-149, and miR-16-5p) miRNAs. Network properties showed miR-29a, miR-21, miR-29b, miR-1, miR-16, miR-133a, and miR-133b have the most degree centrality. GESA identified functionally related sets of genes in signaling and community pathways in HF that are the targets of HF-miRs. The miRNA expression meta-analysis identified sixteen highly significant HF-miRs that are differentially expressed in HF. Further validation in large patient cohorts is required to confirm the significance of these miRs as HF biomarkers and therapeutic targets.

The role of hackathon in education: Can hackathon improve health and medical education?

To develop the next generation of healthcare innovators, students at all levels of education should be trained and encouraged to employ innovative and entrepreneurial approaches to deal with complicated challenges of today's health system. Applying innovation and entrepreneurship training to solve complex problems and focus on solution design has recently become common in medical universities all over the world. This paper clarifies the role of hackathons as an innovative educational approach in healthcare education systems. We propose a process model concerned with organizing hackathon events in the healthcare education system. This model can be used in the academic and practical design of hackathons for innovation purposes.

Effects of standardized Cannabis sativa extract and ionizing radiation in melanoma cells in vitro

Context

Melanoma causes the highest number of skin cancer-related deaths worldwide. New treatment methods are essential for the management of this life-threatening disease.

Aims

In this study, we investigated the efficacy of a standardized Cannabis sativa extract alone or in combination with single radiation dose (6 Gy) in B16F10 mouse melanoma cells in an extract dose-dependent manner.

Materials and Methods

C. sativa extract at three concentrations (25, 12.5, and 6.25 μg/mL) alone for 72 h or in combination with radiation (24 h incubation after the extract treatment + 48 h incubation after exposure to radiation) were evaluated for cell viability of melanoma cells using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay. Cells were also treated with 6.25 μg/mL extract alone for 72 h before analyzing C. sativa-induced cell death by flow cytometry.

Results

Administration of the extract alone or alongside radiation substantially inhibited melanoma cell viability and proliferation in the extract dose response-dependent manner. The inhibition of melanoma cell viability was paralleled by an increase in necrosis but not apoptosis when melanoma cells were treated with the extract alone. Radiation alone did not have any antiproliferative effects, and radiation also did not synergize antiproliferative effects of the extract when the extract and radiation were combined.

Conclusion

Our data suggest that C. sativa extract may have significant health and physiological implications for the treatment of melanoma. The results of this study also indicate that B16F10 mouse melanoma cells are radioresistant. Taken together, these findings may lead to the identification of new therapeutic strategy for the management of melanoma.

SARS-CoV-2 antibody seroprevalence in the general population and high-risk occupational groups across 18 cities in Iran: a population-based cross-sectional study

Background

Rapid increases in cases of COVID-19 were observed in multiple cities in Iran towards the start of the pandemic. However, the true infection rate remains unknown. We aimed to assess the seroprevalence of antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in 18 cities of Iran as an indicator of the infection rate.

Methods

In this population-based cross-sectional study, we randomly selected and invited study participants from the general population (from lists of people registered with the Iranian electronic health record system or health-care centres) and a high-risk population of individuals likely to have close social contact with SARS-CoV-2-infected individuals through their occupation (from employee lists provided by relevant agencies or companies, such as supermarket chains) across 18 cities in 17 Iranian provinces. Participants were asked questions on their demographic characteristics, medical history, recent COVID-19-related symptoms, and COVID-19-related exposures. Iran Food and Drug Administration-approved Pishtaz Teb SARS-CoV-2 ELISA kits were used to detect SARS-CoV-2-specific IgG and IgM antibodies in blood samples from participants. Seroprevalence was estimated on the basis of ELISA test results and adjusted for population weighting (by age, sex, and city population size) and test performance (according to our independent validation of sensitivity and specificity).

Findings

From 9181 individuals who were initially contacted between April 17 and June 2, 2020, 243 individuals refused to provide blood samples and 36 did not provide demographic information and were excluded from the analysis. Among the 8902 individuals included in the analysis, 5372 had occupations with a high risk of exposure to SARS-CoV-2 and 3530 were recruited from the general population. The overall population weight-adjusted and test performance-adjusted prevalence of antibody seropositivity in the general population was 17·1% (95% CI 14·6–19·5), implying that 4 265 542 (95% CI 3 659 043–4 887 078) individuals from the 18 cities included were infected by the end of April, 2020. The adjusted seroprevalence of SARS-CoV-2-specific antibodies varied greatly by city, with the highest estimates found in Rasht (72·6% [53·9–92·8]) and Qom (58·5% [37·2–83·9]). The overall population weight-adjusted and test performance-adjusted seroprevalence in the high-risk population was 20·0% (18·5–21·7) and showed little variation between the occupations included.

Interpretations

Seroprevalence is likely to be much higher than the reported prevalence of COVID-19 based on confirmed COVID-19 cases in Iran. Despite high seroprevalence in a few cities, a large proportion of the population is still uninfected. The potential shortcomings of current public health policies should therefore be identified to prevent future epidemic waves in Iran.

Funding

Iranian Ministry of Health and Medical Education.

Translation

For the Farsi translation of the abstract see Supplementary Materials section.

Isfahan and Covid-19: Deep spatiotemporal representation

The coronavirus COVID-19 is affecting 213 countries and territories around the world. Iran was one of the first affected countries by this virus. Isfahan, as the third most populated province of Iran, experienced a noticeable epidemic. The prediction of epidemic size, peak value, and peak time can help policymakers in correct decisions. In this study, deep learning is selected as a powerful tool for forecasting this epidemic in Isfahan. A combination of effective Social Determinant of Health (SDH) and the occurrences of COVID-19 data are used as spatiotemporal input by using time-series information from different locations. Different models are utilized, and the best performance is found to be for a tailored type of long short-term memory (LSTM). This new method incorporates the mutual effect of all classes (confirmed/ death / recovered) in the prediction process. The future trajectory of the outbreak in Isfahan is forecasted with the proposed model. The paper demonstrates the positive effect of adding SDHs in pandemic prediction. Furthermore, the effectiveness of different SDHs is discussed, and the most effective terms are introduced. The method expresses high ability in both short- and long- term forecasting of the outbreak. The model proves that in predicting one class (like the number of confirmed cases), the effect of other accompanying numbers (like death and recovered cases) cannot be ignored. In conclusion, the superiorities of this model (particularity the long term predication ability) turn it into a reliable tool for helping the health decision-makers.

A one-year hospital-based prospective COVID-19 open-cohort in the Eastern Mediterranean region: The Khorshid COVID Cohort (KCC) study

The COVID-19 is rapidly scattering worldwide, and the number of cases in the Eastern Mediterranean Region is rising. Thus, there is a need for immediate targeted actions. We designed a longitudinal study in a hot outbreak zone to analyze the serial findings between infected patients for detecting temporal changes from February 2020. In a hospital-based open-cohort study, patients are followed from admission until one year from their discharge (the 1st, 4th, 12th weeks, and the first year). The patient recruitment phase finished at the end of August 2020, and the follow-up continues by the end of August 2021. The measurements included demographic, socio-economics, symptoms, health service diagnosis and treatment, contact history, and psychological variables. The signs improvement, death, length of stay in hospital were considered primary, and impaired pulmonary function and psychotic disorders were considered main secondary outcomes. Moreover, clinical symptoms and respiratory functions are being determined in such follow-ups. Among the first 600 COVID-19 cases, 490 patients with complete information (39% female; the average age of 57±15 years) were analyzed. Seven percent of these patients died. The three main leading causes of admission were: fever (77%), dry cough (73%), and fatigue (69%). The most prevalent comorbidities between COVID-19 patients were hypertension (35%), diabetes (28%), and ischemic heart disease (14%). The percentage of primary composite endpoints (PCEP), defined as death, the use of mechanical ventilation, or admission to an intensive care unit was 18%. The Cox Proportional-Hazards Model for PCEP indicated the following significant risk factors: Oxygen saturation < 80% (HR = 6.3; [CI 95%: 2.5,15.5]), lymphopenia (HR = 3.5; [CI 95%: 2.2,5.5]), Oxygen saturation 80%-90% (HR = 2.5; [CI 95%: 1.1,5.8]), and thrombocytopenia (HR = 1.6; [CI 95%: 1.1,2.5]). This long-term prospective Cohort may support healthcare professionals in the management of resources following this pandemic.

Current status of COVID-19 pandemic; characteristics, diagnosis, prevention, and treatment

Humans have always been encountered to big infectious diseases outbreak throughout the history. In December 2019, novel coronavirus (COVID-19) was first noticed as an agent causing insidious pneumonia in Wuhan, China. COVID-19 was spread rapidly from Wuhan to the rest of the world. Until late June 2020, it infected more than 10,000,000 people and caused more than 500,000 deaths in almost all of countries in the world, creating a global crisis worse than all previous epidemics and pandemics. In the current review, we gathered and summarized the results of various studies on characteristics, diagnosis, treatment, and prevention of this pandemic crisis.

Evaluation of Radiation and Ammonium Lactate Effects on Hyaluronic Acid Expression as a Pro-cancerous Factor in Supernatant and Exosome Isolated from Supernatant of Primary Mouse Fibroblast Cell Culture

Background:

Previous studies show that aberrant synthesis of Hyaluronan accelerates tumor growth, angiogenesis, and metastasis. The fibroblasts are probably responsible for most of the hyaluronic acid (HA) accumulation in tumor microenvironment after radiotherapy. Our goal is to investigate and compare radiation and lactate effects on HA levels in supernatant and exosome isolated from supernatant of primary mouse fibroblast cell culture.

Methods:

Fibroblast cells were prepared from skin of C57BL6 mouse. These cells were divided into three groups (no treatment, cells treated with 10 mM ammonium lactate, and irradiated cells). Then supernatant was harvested from FBS-free culture media after 48 h. Exosomes were purified by differential centrifugation (300 × g for 10 min, 2000 × g for 30 min, 16500 g for 30 min) and were pelleted by ultracentrifugation (150,000 × g for 180 min). Size of exosomes was determined using a Zetasizer. HA concentration measured using a HA ELISA Kit. Data were analyzed using one-way ANOVA.

Results:

There was a significant increase in HA-coated exosomes isolated from supernatants of irradiated cells compared to untreated cell and cells treated with 10 mM ammonium lactate (P < 0.001). As well, there was a significant increase in the HA concentration in the supernatants of cells treated with 10 mM ammonium lactate relative to untreated cells and irradiated cells (P < 0.05).

Conclusions:

It seems that routine radiation therapy leads to massive shedding of HA-coated exosomes by normal fibroblast cells and thus exosomes-HA may contribute to tumor promotion and induce of the premetastatic niche.

In vitro versus in vivo models of kidney fibrosis: Time-course experimental design is crucial to avoid misinterpretations of gene expression data

Background:

In vitro models are common tools in nephrology research. However, their validity has rarely been scrutinized.

Materials and Methods:

Considering the critical role of transforming growth factor (TGF)-β and hypoxia pathways in kidney fibrosis, kidney-derived cells were exposed to TGF-β and/or hypoxic conditions and the expression levels of some genes related to these two signaling pathways were quantified in a time-course manner. Furthermore, a unilateral ureteral obstruction mouse model was generated, and the expressions of the same genes were assessed.

Results:

In all in vitro experimental groups, the expression of the genes was noisy with no consistent pattern. However, in the animal model, TGF-β pathway-related genes demonstrated considerable overexpression in the ureteral obstruction group compared with the sham controls. Interestingly, hypoxia pathway genes had prominent fluctuations with very similar patterns in both animal groups, suggesting a periodical pattern not affected by the intervention.

Conclusion:

The findings of this study suggest that in vitro findings should be interpreted cautiously and if possible are substituted or supported by animal models that are more consistent and reliable. Furthermore, we underscore the importance of time-course evaluation of both case and control groups in gene expression studies to avoid misconceptions caused by gene expression noise or intrinsic rhythms.

Neutrophil-to-Lymphocyte ratio as a potential biomarker for disease severity in COVID-19 patients

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Controlling age and sex, NLR>6.5 increases the chance of disease severity by 4 times.

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NLR>6.5 increases the chance of death about 1.8 times after age and sex adjustments.

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The average value of WBC among severe patients was higher than non-severe.

PPAR γ agonist, pioglitazone, suppresses melanoma cancer in mice by inhibiting TLR4 signaling

BACKGROUND

Although previous studies demonstrated an anticancer effect for the ligands of peroxisome proliferator-activated receptor gamma (PPARγ) through activation of its anti-inflammatory responses, nevertheless the anti-tumor mechanism of PPARγ has not been intensively investigated. One of the molecules involved in cancer progression is toll-like receptor 4 (TLR4).

METHODS

B16F10 melanoma cells were cultured with or without LPS for 24 hr. The cells were subcutaneously injected to two groups of C57BL/6 mice. After the development of palpable tumors each group of animals were divide to four sub-groups and received pioglitazone in different dose ranges (0,10,50,100 mg/kg/day) for 10 days. At the end of the study, the expression of Tlr4, Myd-88, Nf-kb1 genes was evaluated by qRT-PCR in different groups in mice tumor. The TLR-4 protein expression was evaluated by IHC. TNF-α level in mice tumor and serum were measured by ELISA kits. Tumor volume was measured with Vernier calipers.

RESULTS

We observed that activation of PPARγ by its agonist, pioglitazone, reduces tumor volume, Tlr-4, Myd-88, Nf-kb1 mRNA expression, TLR4 protein expression and TNF-α production in melanoma tumor especially in groups that were injected with LPS -stimulated cells. Moreover, treatment of melanoma cells with pioglitazone showed that the inhibitory effects of pioglitazone on LPS-induced inflammatory responses were TLR4 dependent.

CONCLUSIONS

The results indicate that pioglitazone, a PPARγ agonist, has a beneficial protective effect against melanoma via interfering with the TLR4-dependent signaling pathways.

Therapeutic inhibition of microRNA-21 (miR-21) using locked-nucleic acid (LNA)-anti-miR and its effects on the biological behaviors of melanoma cancer cells in preclinical studies

BACKGROUND

Melanoma is a cancer that has a high mortality rate in the absence of targeted therapy. Conventional therapies such as surgery, chemotherapy, and radiotherapy are associated with poor prognosis. The expression of miR-21 appears to be of clinical importance, and the regulation of its expression appears to be an opportunity for treatment.

METHODS

In this current study, we aimed to evaluate the effects of miR-21 inhibition in- vitro and in-vivo. In-vitro studies have investigated LNA-anti-miR-21 in mouse melanoma cells (B16F10), and in-vivo studies have proposed a model of melanoma in male C57BL/6 mice. To evaluate the anticancer effects of LNA-anti-miR-21, a QRT-PCR analysis was performed using the 2-ΔΔCT method to determine the degree of inhibition of oncomiR-21. The MTT test, propidium iodide/AnnexinV in-vitro, and tumor volume measurement using the QRT-PCR test with the 2-ΔΔCT method were used to estimate the inhibition of miR-21 and the expression of downstream genes including: SNAI1, Nestin (Nes), Oct-4, and NF-kB following miR-21 inhibition. Finally, immunohistochemistry was conducted for an in-vivo animal study.

RESULTS

MiR-21 expression was inhibited by 80% after 24 h of B16F10 cell line transfection with LNA-anti-miR-21. The MTT test showed a significant reduction in the number of transfected cells with LNA-anti-miR-21. The transfected cells showed a significant increase in apoptosis in comparison with the control and scrambled LNA groups. According to our in vivo findings, anti-miR-21 could reduce tumor growth and volume in mice receiving intraperitoneal anti-miR after 9 days. The expression of the SNAI1gene was significantly reduced compared to the controls. Immunohistochemical analysis showed no change in CD133 and NF-kB markers.

CONCLUSION

Our findings suggest LNA-anti-miR-21 can be potentially used as an anticancer agent for the treatment of melanoma.

Atorvastatin enhances the antitumor activity of tamoxifen in B16f10 mouse melanoma cell lines

Introduction: Tamoxifen has been used in the treatment of metastatic malignant melanoma more common with other agents in the combined therapy. Up-regulated activity of the mevalonate pathway has been shown in a range of different cancers. Atorvastatin is the most commonly used statin approved for cholesterol reduction by inhibiting the mevalonate pathway and has been shown to inhibit tumor growth. In the present study, we used atorvastatin and tamoxifen combination therapy on B16f10 mouse melanoma cell lines to study whether atorvastatin could increase the sensitivity of melanoma cells to the chemotherapeutic agent such as tamoxifen. Methods: The cell line was treated with different concentrations of tamoxifen and/or atorvastatin for 24 and 48h and the effects of treatment on p53 and RhoA were investigated using quantitative RT-PCR. Results: The combination of atorvastatin and tamoxifen resulted in a potentiation antitumor effect via up-regulation of p53 and down-regulation of RhoA expression against melanoma tumors in vitro. Furthermore, we demonstrated the combination of atorvastatin with tamoxifen could reduce tamoxifen dose to minimize possible detrimental side effects in melanoma. Conclusion: Our results suggested that atorvastatin as a combined therapy with tamoxifen may provide a new approach for improving the efficacy and treating against melanoma cancer but needs further exploration in clinical trials.

Determining genetic variants in children and adolescents suffering from tetralogy of Fallot with a positive family history: methodology

BACKGROUND AND AIM

Congenital heart disease (CHD) affects near 1% of all live births and is considered to be the main reason of morbidity and mortality in early childhood. In this study, we investigated molecular genetics factors associated with Tetralogy of Fallot (TOF) using high throughput technologies in the consanguineous families with at least 2 affected individual.

METHOD

This family study started in March 2017 to May 2018 in pediatric cardiovascular research center, Cardiovascular Research Institute, Isfahan, Iran. After obtaining informed consent, we invited families who had at least 2 individuals in one generation or previous generations with familial marriage history and they were included in the study. Genomic DNA was extracted from peripheral blood lymphocytes of the patient and samples were investigated for structural variations such as deletion or duplication in the genome using single nucleotide polymorphism array (SNP array). In the next step, if the SNP array is negative, next generation study will be performed in the propend and after analyzing the raw data and filtering for rare pathogenic variants.

RESULTS

In this study, totally 5 families were evaluated. All affected and unaffected individuals of each family included in the pedigree.  This study comprised 14 subjects (9 males and 5 females; 8.92 ± 6.21 years old). Baseline characteristics and clinical data of the study subjects are presented in Table 1. The prevalence of consanguineous marriage is 92.2% among parents, 71.4% among mother grandparents and 28.6% among father grandparents. 64.3 % of our participants have sibling with similar disease. The prevalence of atrial septal defect (ASD), ventricular septal defect (VSD), and arrhythmia and TOF was 7.1%.

CONCLUSION

We found some families with 2 or more CHD and with a high rate of consanguineous marriage and probably suffering from a genetic predisposition. We aim to exam them further with next generation study (NGS) to find any genetic defect and then to exam other CHD's in our region. Key words: gene mutations, children, adolescents, tetralogy of Fallot, family history.

Genetic Variation in Cytochrome P450 2R1 and Vitamin D Binding Protein Genes are associated with Vitamin D Deficiency in Adolescents

Background: Genome Wide Association Studies (GWAS) have evaluated several genes related to vitamin D synthesis, metabolism and transport. They have proposed a genetic basis for low levels of vitamin D in the blood. The current study aims to investigate the relationship between certain vitamin D-associated gene variants and vitamin D deficiency in Iranian adolescents. Methods: In this case-control study, the genomic DNA was extracted by Real Time PCR High Resolution Melt (HRM). All measurements were carried out with triple repetition. The following factors were assessed: single nucleotide polymorphisms (SNPs) in Vitamin D binding protein (DBP, rs2282679), 7-Dehydrocholesterol reductase (DHCR7, rs12785878) and Cytochrome P450 2R1 (CYP2R1, rs10741657). Results: the genomic DNA of blood samples obtained from 481 adolescents. Participants with hypovitaminosis D were compared with a control group. The average vitamin D level of sufficient subjects (controls) was 44.88±14.01 ng/mL, while subjects who were insufficient (cases) had an average vitamin D level of 7.03±1.24 ng/mL. No statistically significant differences were found in the allelic and genotypic distributions between genders. The SNP frequency in CYP2R1 (rs10741657) and DBP (rs2282679) in the vitamin D deficient group was significantly higher than in the control group (p-values < 0.001 and 0.01 respectively). There were no statistically significant differences in the DHCR7 SNP (rs12785878) distributions between the Vitamin D deficient group and control group. Conclusion: The present study demonstrated evidence of the ability of the SNPs under investigation to predict circulating vitamin D concentration. Further study is needed to better understand if and how genetic factors contribute to vitamin D levels, and certain skeletal-associated disorders in adolescents.