Culture-based diversity of endophytic fungi of three species of Ferula grown in Iran.

A total of 1,348 endophytic fungal strains were isolated from Ferula ovina, F. galbaniflua, and F. persica. They included Eurotiales (16 species), Pleosporales (11 species), Botryosphaeriales (1 species), Cladosporiales (2 species), Helotiales (6 species), Hypocreales (31 species), Sordariales (7 species), Glomerellales (2 species), and Polyporales (1 species). F. ovina had the richest species composition of endophytic fungi, and the endophytic fungi were most abundant in their roots compared to shoots. Chao, Margalef, Shannon, Simpson, Berger-Parker, Menhinick, and Camargo indices showed that F. ovina roots had the most endophytic fungal species. The frequency distribution of fungal species isolated from Ferula spp. fell into the log-series model, and F. ovina roots had the highest Fisher alpha. The dominance indices showed that there are no dominant species in the endophytic fungal community isolated from Ferula spp., indicating community stability. Evenness values were 0.69, 0.90, 0.94, and 0.57 for endophytic fungi isolated from F. ovina roots, F. ovina shoots, F. galbaniflua roots, and F. persica roots, respectively, indicating a species distribution that tends toward evenness. The fungal species community isolated from each of F. ovina roots, F. ovina shoots, F. galbaniflua roots, and F. persica roots was a diverse species group originating from a homogeneous habitat. Their distribution followed a log-normal distribution, suggesting that the interactions of numerous independent environmental factors multiplicatively control species abundances. Principal component analysis showed that the highest species diversity and dominance were observed in the endophytic fungal community isolated from F. ovina and F. persica roots, respectively.

Guided blood transfusion of trauma patients with rotational thromboelastometry: a single-center cohort study.

BACKGROUND: Rotational thromboelastometry (ROTEM) is a blood test used to measure in vitro clot strength as a surrogate for a patient's ability to form clots in vivo. This provides information about induction, formation, and clot lysis, allowing goal-directed transfusion therapy for specific hemostatic needs. We sought to evaluate the effect of ROTEM-guided transfusion on blood product usage and in-hospital mortality among patients with a traumatic injury. METHODS: This was a single-center observational cohort analysis of emergency department patients in a Level 1 trauma center. We compared blood usage in trauma patients in whom ratio-based massive hemorrhage protocols were activated in the twelve months before the introduction of ROTEM (pre-ROTEM group) to the twelve months following the introduction of ROTEM (ROTEM-period group). ROTEM was implemented in this center in November 2016. The ROTEM device allowed clinicians to make real-time decisions about blood product therapy in resuscitation for trauma. RESULTS: The pre-ROTEM group contained 21 patients. Forty-three patients were included from the ROTEM-period, of whom 35 patients received ROTEM-guided resuscitation (81% compliance). The use of fibrinogen concentrate was significantly higher in the ROTEM-period group (pre-ROTEM mean 0.2 vs. ROTEM-period mean 0.8; p = 0.006). There was no significant difference in the number of units of red blood cells, platelets, cryoprecipitate, or fresh frozen plasma transfused between these groups. There was no significant difference in the mortality rate between the pre-ROTEM and ROTEM-period groups (33% vs. 19%; p = 0.22). CONCLUSIONS: The introduction of ROTEM-guided transfusion at this institution was associated with increased fibrinogen usage, but this did not impact mortality rates. There was no difference in the administration of red blood cell, fresh frozen plasma, platelet, and cryoprecipitate. Future research should focus on increased ROTEM compliance and optimizing ROTEM-guided transfusion to prevent blood product overuse among trauma patients.

Science fiction or clinical reality: a review of the applications of artificial intelligence along the continuum of trauma care.

Artificial intelligence (AI) and machine learning describe a broad range of algorithm types that can be trained based on datasets to make predictions. The increasing sophistication of AI has created new opportunities to apply these algorithms within within trauma care. Our paper overviews the current uses of AI along the continuum of trauma care, including injury prediction, triage, emergency department volume, assessment, and outcomes. Starting at the point of injury, algorithms are being used to predict severity of motor vehicle crashes, which can help inform emergency responses. Once on the scene, AI can be used to help emergency services triage patients remotely in order to inform transfer location and urgency. For the receiving hospital, these tools can be used to predict trauma volumes in the emergency department to help allocate appropriate staffing. After patient arrival to hospital, these algorithms not only can help to predict injury severity, which can inform decision-making, but also predict patient outcomes to help trauma teams anticipate patient trajectory. Overall, these tools have the capability to transform trauma care. AI is still nascent within the trauma surgery sphere, but this body of the literature shows that this technology has vast potential. AI-based predictive tools in trauma need to be explored further through prospective trials and clinical validation of algorithms.

The Effects of Curcumin Supplementation on Muscle Damage, Oxidative Stress, and Inflammatory Markers in Healthy Females with Moderate Physical Activity: A Randomized, Double-Blind, Placebo-Controlled Clinical Trial.

BACKGROUND: Exercise-induced oxidative stress, muscle damage, and inflammation represent major contributors to why athletes use ergogenic aids. Turmeric is used as a spice because of its polyphenol ingredient named curcumin. We assessed the effects of curcumin supplementation on inflammatory, oxidative stress markers, muscle damage, and anthropometric indices in women with moderate physical activity. METHODS: This double-blind, placebo-controlled clinical trial was conducted on 80 women with moderate physical activity levels (defined as walking or swimming for at least 1 h per day) for 8 weeks. Mean ± SD of age (years) all participants was 21 ± 2. Participants were randomly assigned into two groups: curcumin (500 mg/day) and placebo (500 mg/day cornstarch). Serum C-reactive protein (CRP), total antioxidant capacity (TAC), malondialdehyde (MDA), lactate dehydrogenase (LDH) levels, body composition, and maximum oxygen uptake (VO2 max) were evaluated before and after an intervention. RESULTS: Sixty-five subjects completed the 8-week intervention. Within analysis indicated a significant decrease in CRP, LDH, MDA levels, and a significant increase in VO2 max in the curcumin group after an intervention (P < 0.05). There were significant decreases in CRP (P = 0.002), LDH (P = 0.041), and MDA (P = 0.005), no significant increase in TAC, and significant increase in VO2 max (P = 0.0001) levels in the curcumin group compared with placebo group. There were no significant changes in weight, body mass index, body fat, and lean body mass between two groups. CONCLUSIONS: Our findings indicated that 8-week curcumin administration could significantly improve CRP, LDH, MDA, and VO2 max. Curcumin supplementation did not elicit significant changes in anthropometric indices in this study.

A hybrid model based on general regression neural network and fruit fly optimization algorithm for forecasting and optimizing paclitaxel biosynthesis in Corylus avellana cell culture.

BACKGROUND: Paclitaxel is a well-known chemotherapeutic agent widely applied as a therapy for various types of cancers. In vitro culture of Corylus avellana has been named as a promising and low-cost strategy for paclitaxel production. Fungal elicitors have been reported as an impressive strategy for improving paclitaxel biosynthesis in cell suspension culture (CSC) of C. avellana. The objectives of this research were to forecast and optimize growth and paclitaxel biosynthesis based on four input variables including cell extract (CE) and culture filtrate (CF) concentration levels, elicitor adding day and CSC harvesting time in C. avellana cell culture, as a case study, using general regression neural network-fruit fly optimization algorithm (GRNN-FOA) via data mining approach for the first time. RESULTS: GRNN-FOA models (0.88-0.97) showed the superior prediction performances as compared to regression models (0.57-0.86). Comparative analysis of multilayer perceptron-genetic algorithm (MLP-GA) and GRNN-FOA showed very slight difference between two models for dry weight (DW), intracellular and extracellular paclitaxel in testing subset, the unseen data. However, MLP-GA was slightly more accurate as compared to GRNN-FOA for total paclitaxel and extracellular paclitaxel portion in testing subset. The slight difference was observed in maximum growth and paclitaxel biosynthesis optimized by FOA and GA. The optimization analysis using FOA on developed GRNN-FOA models showed that optimal CE [4.29% (v/v)] and CF [5.38% (v/v)] concentration levels, elicitor adding day (17) and harvesting time (88 h and 19 min) can lead to highest paclitaxel biosynthesis (372.89 µg l-1). CONCLUSIONS: Great accordance between the predicted and observed values of DW, intracellular, extracellular and total yield of paclitaxel, and also extracellular paclitaxel portion support excellent performance of developed GRNN-FOA models. Overall, GRNN-FOA as new mathematical tool may pave the way for forecasting and optimizing secondary metabolite production in plant in vitro culture.

Mathematical Modeling of Growth and Paclitaxel Biosynthesis in Corylus avellana Cell Culture Responding to Fungal Elicitors Using Multilayer Perceptron-Genetic Algorithm.

Paclitaxel is the top-selling anticancer medicine in the world. In vitro culture of Corylus avellana has been made known as a promising and inexpensive strategy for producing paclitaxel. Fungal elicitors have been named as the most efficient strategy for enhancing the biosynthesis of secondary metabolites in plant cell culture. In this study, endophytic fungal strain HEF17 was isolated from C. avellana and identified as Camarosporomyces flavigenus. C. avellana cell suspension culture (CSC) elicited with cell extract (CE) and culture filtrate (CF) derived from strain HEF17, either individually or combined treatment, in mid and late log phase was processed for modeling and optimizing growth and paclitaxel biosynthesis regarding CE and CF concentration levels, elicitor adding day, and CSC harvesting time using multilayer perceptron-genetic algorithm (MLP-GA). The results displayed higher accuracy of MLP-GA models (0.89-0.95) than regression models (0.56-0.85). The great accordance between the predicted and observed values of output variables (dry weight, intracellular, extracellular and total yield of paclitaxel, and also extracellular paclitaxel portion) for both training and testing subsets supported the excellent performance of developed MLP-GA models. MLP-GA method presented a promising tool for selecting the optimal conditions for maximum paclitaxel biosynthesis. An Excel® estimator, HCC-paclitaxel, was designed based on MLP-GA model as an easy-to-use tool for predicting paclitaxel biosynthesis in C. avellana CSC responding to fungal elicitors.

Modeling of paclitaxel biosynthesis elicitation in Corylus avellana cell culture using adaptive neuro-fuzzy inference system-genetic algorithm (ANFIS-GA) and multiple regression methods.

Paclitaxel as a microtubule-stabilizing agent is widely used for the treatment of a vast range of cancers. Corylus avellana cell suspension culture (CSC) is a promising strategy for paclitaxel production. Elicitation of paclitaxel biosynthesis pathway is a key approach for improving its production in cell culture. However, optimization of this process is time-consuming and costly. Modeling of paclitaxel elicitation process can be helpful to predict the optimal condition for its high production in cell culture. The objective of this study was modeling and forecasting paclitaxel biosynthesis in C. avellana cell culture responding cell extract (CE), culture filtrate (CF) and cell wall (CW) derived from endophytic fungus, either individually or combined treatment with methyl-ß-cyclodextrin (MBCD), based on four input variables including concentration levels of fungal elicitors and MBCD, elicitor adding day and CSC harvesting time, using adaptive neuro-fuzzy inference system (ANFIS) and multiple regression methods. The results displayed a higher accuracy of ANFIS models (0.94-0.97) as compared to regression models (0.16-0.54). The great accordance between the predicted and observed values of paclitaxel biosynthesis for both training and testing subsets support excellent performance of developed ANFIS models. Optimization process of developed ANFIS models with genetic algorithm (GA) showed that optimal MBCD (47.65 mM) and CW (2.77% (v/v)) concentration levels, elicitor adding day (16) and CSC harvesting time (139 h and 41 min after elicitation) can lead to highest paclitaxel biosynthesis (427.92 µg l-1). The validation experiment showed that ANFIS-GA method can be a promising tool for selecting the optimal conditions for maximum paclitaxel biosynthesis, as a case study.

Whole fungal elicitors boost paclitaxel biosynthesis induction in Corylus avellana cell culture.

Paclitaxel is an effective natural-source chemotherapeutic agent commonly applied to treat a vast range of cancers. In vitro Corylus avellana culture has been reported as a promising and inexpensive system for paclitaxel production. Fungal elicitors have been made known as the most efficient strategy for the biosynthesis induction of secondary metabolites in plant in vitro culture. In this research, C. avellana cell suspension culture (CSC) was exposed to cell extract (CE) and culture filtrate (CF) derived from Camarosporomyces flavigenus, either individually or combined treatment, in mid and late log phase. There is no report on the use of whole fungal elicitors (the combined treatment of CE and CF) for the elicitation of secondary metabolite biosynthesis in plant in vitro culture. The combined treatment of CE and CF significantly led to more paclitaxel biosynthesis and secretion than the individual use of them. Also, multivariate statistical approaches including stepwise regression (SR), ordinary least squares regression (OLSR), principal component regression (PCR) and partial least squares regression (PLSR) were used to model and predict paclitaxel biosynthesis and secretion. Based on value account for (VAF), root mean square error (RMSE), coefficient of determination (R2), mean absolute percentage error (MAPE) and relative percent difference (RPD) can be concluded that mentioned regression models effectively worked only for modeling and predicting extracellular paclitaxel portion in C. avellana cell culture.

Fungal Cell Wall and Methyl-ß-Cyclodextrin Synergistically Enhance Paclitaxel Biosynthesis and Secretion in Corylus avellana Cell Suspension Culture.

Paclitaxel is the top-selling chemotherapeutic drug used for the treatment of lung, ovarian and breast cancer as well as Kaposi's sarcoma. Cell suspension culture (CSC) of Corylus avellana has been addressed as a promising alternative for producing paclitaxel. In this study, endophytic fungus strain YEF33 was isolated from Taxus baccata and identified as Coniothyrium palmarum. The effects of the elicitors derived from this fungus including cell extract, culture filtrate and cell wall (CW) and also chitin, alone or in combination with Methyl-ß-Cyclodextrin (MBCD), on paclitaxel biosynthesis in C. avellana CSC were assayed for the first time. CW of C. palmarum was the most efficient fungal elicitor for paclitaxel biosynthesis in C. avellana CSC. The results revealed that MBCD affected paclitaxel biosynthesis differently depending on fungal elicitor type and vice versa. MBCD, either alone or in combination with fungal elicitors, induced a high secretion of paclitaxel, suggesting the decrement of toxicity and retro-inhibition processes of paclitaxel for cells. The joint effects of C. palmarum CW (2.5% (v/v) on 17th day) and 50 mM MBCD synergistically enhanced paclitaxel biosynthesis (402.4 µg l-1; 5.8-fold), 78.6% of which (316.5 µg l-1) were secreted into culture medium, a level 146% higher than that in control.

New synergistic co-culture of Corylus avellana cells and Epicoccum nigrum for paclitaxel production.

Paclitaxel is a main impressive chemotherapeutic agent with unique mode of action and broad-spectrum activity against cancers. Hazel (Corylus avellana) is a paclitaxel-producing species through bioprospection. Endophytic fungi have significant roles in plant paclitaxel production. This study evaluated the effect of co-culture of C. avellana cells and paclitaxel-producing endophytic fungus, Epicoccum nigrum strain YEF2 and also the effect of elicitors derived from this fungal strain on paclitaxel production. The results clearly revealed that co-culture of C. avellana cells and E. nigrum was more effective than elicitation of C. avellana cells by only cell extract or culture filtrate of this fungal strain. Co-culture of C. avellana cells and E. nigrum surpassed monocultures in terms of paclitaxel production designating their synergistic interaction potential. Fungal inoculum amount, co-culture establishment time and co-culture period were important factors for achieving the maximum production of paclitaxel in this co-culture system. The highest total yield of paclitaxel (404.5 µg L-1) was produced in co-culture established on 13th day using 3.2% (v/v) of E. nigrum mycelium suspension, which was about 5.5 and 136.6 times that in control cultures of C. avellana cells and E. nigrum, respectively. This is the first report on positive effect of co-culture of paclitaxel-producing endophytic fungus and non-host plant cells for enhancing paclitaxel production.

A Novel Medium for Enhancing Callus Growth of Hazel (Corylus avellana L.).

Paclitaxel is a powerful antimitotic agent with excellent activity against a range of cancers. Hazel has been described as a paclitaxel-producing species among angiosperms. Fast-growing callus is a prerequisite for the success of callus production and then paclitaxel production. Therefore, optimizing the medium culture for enhancing callus growth is a crucial step for paclitaxel production. In this research, Murashige and Skoog (1962) (MS) medium was optimized for improving callus growth of hazel (Corylus avellana L.). The M10 medium (MS medium with pH 6.0 and supplemented with 1000 mg l-1 spirulina powder, 1000 mg l-1 casein hydrolysate and 3 g l-1 gelrite) significantly improved hazel callus growth. This modified MS medium increased callus fresh weight (55.8%) as compared to the control. M10 medium increased fatty acids yield of callus (66.7%) as compared to the control. Liquid M10 medium maintained growth over a longer period of time and also increased slightly, the paclitaxel production as compared to the control. This novel medium is promising for facilitating the mass production of hazel callus as a source of valuable metabolites including paclitaxel, linoleic and oleic acids.

Knowledge of and attitudes toward breast self-examination in Iranian women: a multi-center study.

BACKGROUND: In Iran, breast cancer is the second most common malignancy among women and diagnosed in advanced stages almost a decade earlier than women living in western countries. OBJECTIVE: To determine the level of knowledge and attitudes toward breast self-examination (BSE) among Iranian women. METHODS: In a cross-sectional multi-center study, 3,060 women aged between 25 and 54 years attending between July and October 2009 to 11 general health care centers located in 11 cities of Iran, were interviewed to assess their knowledge and attitudes toward BSE. RESULTS: Of the total, the data of 3,030 were found eligible for analyses. The median (interquartile range [IQR]) age of participants was 40 (14) years; 2,687 (88.7%) were married; 1496 (49.4%) women performed BSE, 290 of whom (19.4% of performers and 9.6% of all studied women) did it using a correct method and at an appropriate time. More than three-quarters of performers (n=1141) learned about BSE from a health care provider; 248 (16.6%, 95% confidence interval [CI]: 14.7% to 18.5%) had abnormal findings, 11 (0.7% , 95% CI: 0.3% to 1.2%) of which were malignant. Of 1,534 (50.6%) non-performers, 474 (30.9%) did not know how to do BSE; the remaining women did not do BSE for fear of being found positive for cancer or did not care about it. Being a health care provider, married, educated, and knowing of a person with breast cancer was associated with performing BSE. CONCLUSIONS: The level of BSE practice and knowledge among Iranian women is unsatisfactory. We should emphasize appropriate education of women.