Second Primary Malignancies after Autologous Hematopoietic Cell Transplantation for Multiple Myeloma

AbstractRecent studies demonstrate an increased risk of second primary malignancies (SPMs) in patients with multiple myeloma (MM) receiving maintenance lenalidomide after autologous stem cell transplantation (ASCT). We explored the possibility of other risk factors driving post-ASCT SPMs in patients with MM through analysis of our large transplantation database in conjunction with our Long-Term Follow-Up Program. We conducted a retrospective cohort study of 841 consecutive patients with MM who underwent ASCT at City of Hope between 1989 and 2009, as well as a nested case-control analysis evaluating the role of all therapeutic exposures before, during, and after ASCT. Median duration of follow-up for the entire cohort was 3.4 years (range, 0.3-19.9 years). Sixty cases with a total of 70 SPMs were identified. The overall cumulative incidence of SPMs was 7.4% at 5 years and 15.9% at 10 years when nonmelanoma skin cancers (NMSCs) were included and 5.3% at 5 years and 11.2% at 10 years when NMSCs were excluded. Multivariate analysis of the entire cohort revealed associations of both older age (≥55 years; relative risk, 2.3; P < .004) and race (non-Hispanic white; relative risk, 2.4; P = .01) with an increased risk of SPM. Furthermore, thalidomide exposure demonstrated a trend toward increased risk (odds ratio, 3.5; P = .15); however, an insufficient number of patients were treated with lenalidomide to allow us to accurately assess the risk of this agent. Exclusion of NMSCs retained the association with these variables but was accompanied by loss of statistical significance. This large single-institution analysis identified associations between race and older age and increased risk of developing SPM. The trend toward increased risk with thalidomide exposure suggests a class effect from immunomodulatory drugs that might not be restricted to lenalidomide

Improvement of drought tolerance in rice (Oryza sativa L.): genetics, genomic tools, and the WRKY gene family

Drought tolerance is an important quantitative trait with multipart phenotypes that are often further complicated by plant phenology. Different types of environmental stresses, such as high irradiance, high temperatures, nutrient deficiencies, and toxicities, may challenge crops simultaneously; therefore, breeding for drought tolerance is very complicated. Interdisciplinary researchers have been attempting to dissect and comprehend the mechanisms of plant tolerance to drought stress using various methods; however, the limited success of molecular breeding and physiological approaches suggests that we rethink our strategies. Recent genetic techniques and genomics tools coupled with advances in breeding methodologies and precise phenotyping will likely reveal candidate genes and metabolic pathways underlying drought tolerance in crops. The WRKY transcription factors are involved in different biological processes in plant development. This zinc (Zn) finger protein family, particularly members that respond to and mediate stress responses, is exclusively found in plants. A total of 89 WRKY genes in japonica and 97 WRKY genes in O. nivara (OnWRKY) have been identified and mapped onto individual chromosomes. To increase the drought tolerance of rice ( Oryza sativa L.), research programs should address the problem using a multidisciplinary strategy, including the interaction of plant phenology and multiple stresses, and the combination of drought tolerance traits with different genetic and genomics approaches, such as microarrays, quantitative trait loci (QTLs), WRKY gene family members with roles in drought tolerance, and transgenic crops. This review discusses the newest advances in plant physiology for the exact phenotyping of plant responses to drought to update methods of analysing drought tolerance in rice. Finally, based on the physiological/morphological and molecular mechanisms found in resistant parent lines, a strategy is suggested to select a particular environment and adapt suitable germplasm to that environment

Internet addiction and its psychosocial risks (depression, anxiety, stress and loneliness) among Iranian adolescents and young adults: a structural equation model in a cross-sectional study

Internet addiction has become an increasingly researched area in many Westernized countries. However, there has been little research in developing countries such as Iran, and when research has been conducted, it has typically utilized small samples. This study investigated the relationship of Internet addiction with stress, depression, anxiety, and loneliness in 1,052 Iranian adolescents and young adults. The participants were randomly selected to complete a battery of psychometrically validated instruments including the Internet Addiction Test, Depression Anxiety Stress Scale, and the Loneliness Scale. Structural equation modeling and Pearson correlation coefficients were used to determine the relationship between Internet addiction and psychological impairments (depression, anxiety, stress and loneliness). Pearson correlation, path analysis, multivariate analysis of variance (MANOVA), and t-tests were used to analyze the data. Results showed that Internet addiction is a predictor of stress, depression, anxiety, and loneliness. Findings further indicated that addictive Internet use is gender sensitive and that the risk of Internet addiction is higher in males than in females. The results showed that male Internet addicts differed significantly from females in terms of depression, anxiety, stress, and loneliness. The implications of these results are discussed

Large-scale unit commitment under uncertainty: an updated literature survey

The Unit Commitment problem in energy management aims at finding the optimal production schedule of a set of generation units, while meeting various system-wide constraints. It has always been a large-scale, non-convex, difficult problem, especially in view of the fact that, due to operational requirements, it has to be solved in an unreasonably small time for its size. Recently, growing renewable energy shares have strongly increased the level of uncertainty in the system, making the (ideal) Unit Commitment model a large-scale, non-convex and uncertain (stochastic, robust, chance-constrained) program. We provide a survey of the literature on methods for the Uncertain Unit Commitment problem, in all its variants. We start with a review of the main contributions on solution methods for the deterministic versions of the problem, focussing on those based on mathematical programming techniques that are more relevant for the uncertain versions of the problem. We then present and categorize the approaches to the latter, while providing entry points to the relevant literature on optimization under uncertainty. This is an updated version of the paper "Large-scale Unit Commitment under uncertainty: a literature survey" that appeared in 4OR 13(2), 115--171 (2015); this version has over 170 more citations, most of which appeared in the last three years, proving how fast the literature on uncertain Unit Commitment evolves, and therefore the interest in this subject

Neuropsychological function is related to irritable bowel syndrome in women with premenstrual syndrome and dysmenorrhea

Background There is increasing evidence demonstrating the co-occurrence of primary dysmenorrhea (PD), premenstrual syndrome (PMS), and irritable bowel syndrome (IBS) in women. This study aimed to investigate whether women who have symptoms of IBS in addition to PD and PMS also report more severe or frequent menstruation-associated symptoms and psychological complications compared to women with PD and PMS alone. Methods The study group included 182 female University students aged 18–25 years. IBS was diagnosed using the Rome III criteria. The severity of PMS and PD was determined using a 10-point visual analog scale and PSST (Premenstrual Syndrome Screening Tool), respectively. Neuropsychological functions including cognitive function, depression score, anxiety score, stress, insomnia, daytime sleepiness, quality of life and personality were assessed using standard questionnaires. Results Of the 182 young females, 31 (17.0%) had IBS. Average days of bleeding during the menstrual cycle and mean pain severity on the PSST scale were significantly greater in the group with IBS compared to the non-IBS group (p < 0.01). The non-IBS individuals scored more favorably than the women with IBS with respect to severity of depression, insomnia, daytime sleepiness (p < 0.05). The PSST scores were significantly correlated with scores for depression (r = 0.29; p < 0.001), anxiety (r = 0.28; p < 0.001), stress (r = 0.32; p < 0.001), insomnia (r = 0.34; p < 0.001) and daytime sleepiness (r = 0.31; p < 0.001); while, they were negatively correlated with cognitive abilities (r = − 0.20; p = 0.006) and quality of life (r = − 0.42; p < 0.001). Linear regression analysis showed that the PSST scores were possibly significant factors in determining the scores for depression, anxiety, stress, quality of life, insomnia and daytime sleepiness (p < 0.05). Conclusion IBS is related to psychological comorbidities, in particular depression, sleep problems and menstrual-associated disorders. IBS may exacerbate the features of PMS which should be taken into account in the management of PMS

Emergency Response to a Hospital Fire: A Report From the Field

As the most important centers providing medical services during disasters and emergencies, hospitals have special structural complexities. Furthermore, the hospitals are exposed to many intrinsic and extrinsic hazards, including fire. On November 28, 2018, at 9:25 am (local time), a fire started in Ayatollah Taleghani Hospital of Ilam, affiliated with Ilam University of Medical Sciences, Iran. Immediately, to save patients' lives and prevent injuries to them, the horizontal and then vertical evacuation was performed to transfer patients to other hospitals by helping the support organizations. No physical injuries or deaths were reported in this incident. The results of this case study showed that hospitals should be sufficiently prepared to respond effectively to accidents and disasters, so it is needed to prepare and practice response programs and train hospital staff and managers

Investigating the human hemoglobin fructation in the presence of propolis in vitro

Background: Propolis is a complex resinous mixture that is gathered and processed by honeybees from resin they collect from trees and plants. This substance has various biological properties. Glycation is a reaction, which occurs between a protein and a reducing sugar and finally causes structural alterations and destruction of proteins. The role of glycation has been approved in the development and aggravation of diabetic complications. This study aimed to examine the effect of ethanolic extract of propolis (EEP) on fructation and destruction of hemoglobin protein structure. Materials and Methods: In this experimental study, purified hemoglobin was incubated alone and with fructose in the presence and absence of different concentrations of EEP (10, 20 and 40µg/ml) for 5 weeks. The extent of hemoglobin fructation was determined by measuring the amount of heme release, blue shift in soret band, releasing the products of heme destruction and assessing the amyloid structures using the UV-visible and fluorescence spectroscopy. Results: Incubation of hemoglobin with fructose was led to the hemoglobin destruction and heme release. Hemoglobin fructation was inhibited up to 45 in the presence of EEP with a concentration of 40µg/ml. The two lower concentrations of EEP showed the lower degrees of inhibition. Moreover, fluorescence studies of products resulting from heme degradation and fibrillar structures are indicative of the reduction in hemoglobin fructation in the presence of EEP. Conclusion: Hemoglobin is drastically glycated in the presence of fructose and EEP can decrease the hemoglobin fructation in a concentration-dependent manner

ASSESMENT AND EVLUATION OF THE IMPACT OF USING POLSAR IMAGERIES WITH DIFERENT INCIDENT ANGLES IN FOREST CLASSIFICATION

Forests are a dominant biome of the earth and have an important impact on its economic and environmental well-being. Forestry applications of radar remote sensing are addressed in the context of both forest management and ecosystem understanding, modelling and monitoring. Nowadays, radar remote sensing is being used for a lot of applications in various fields. Due to the applications of polarimetric radar in recent decades, many researchers have tended to this field. One of the main advantages of SAR images is that these images are independent over the time (day and night) and weather condition. The polarimetric SAR (POLSAR) images compared with other remote sensing images are more informative. Classification of radar images is a way by which we can separate different types of forest species. In addition to the main characteristics of the target, the backscatter from a SAR image is widely dependant on various radar system parameters. One of these system parameters is the incident angle of the radar system. In this paper, the impact of using PolSAR images with different incidence angles for the classification of forest areas is investigated. Two polSAR images with different incident angles taken by RADARSAT-2 in fine quad polarized mode (FQ4 and FQ18) have been used in this study. The study area is located in the Petawawa Research Forest (PRF) near Chalk River, Ontario, Canada The methodology of this paper contains three steps: (1) preprocessing, (2) wishart classification and (3) evaluating & analyzing the results. The preprocessing steps consist of the speckle noise filtering, covariance matrix extraction and georeferencing. In the second step, each incidence angle image was classified by using the supervised Wishart classification. The Wishart classification method has the capability of having multiple images at the same time. Thus, in the next experiment the classification was performed using both incidence angle images. Finally, the obtained results from each class and the classification results in each of three cases were evaluated and analyzed. The results showed that Wishart classification provides an overall accuracy of % 67.17 using the lower incidence angle PolSAR image and % 65.38 for the higher incidence angle POLSAR image. Also, the overall accuracy of the simultaneous classification by using the extracted covariance matrix from both images is 72.63 %. Those results showed a better performance of the image with lower incident angle compared to that of an image with higher incident angle for forest classification. It is also shown that combining extracted covariance matrix from the FQ4 image with extracted covariance matrix from the FQ18 image can significantly improve the classification accuracy (overall accuracy)

Emergency Response to a Hospital Fire: A Report From the Field

As the most important centers providing medical services during disasters and emergencies, hospitals have special structural complexities. Furthermore, the hospitals are exposed to many intrinsic and extrinsic hazards, including fire. On November 28, 2018, at 9:25 am (local time), a fire started in Ayatollah Taleghani Hospital of Ilam, affiliated with Ilam University of Medical Sciences, Iran. Immediately, to save patients' lives and prevent injuries to them, the horizontal and then vertical evacuation was performed to transfer patients to other hospitals by helping the support organizations. No physical injuries or deaths were reported in this incident. The results of this case study showed that hospitals should be sufficiently prepared to respond effectively to accidents and disasters, so it is needed to prepare and practice response programs and train hospital staff and managers