m. ghasemzadeh

In the 80s, cord blood stem cells were used for the first time to treat diseases in humans, and contrary to the opinion of the opponents of using this new cell source, the result was satisfactory, and since then, cord blood has been an important source for cell therapy in humans. Considering the dominant approach to increase the clinical use of umbilical cord blood and the expansion of experimental and research studies in this field, this review article has discussed the current applications and future perspectives while examining the biology of cord blood stem cells.

To conduct this review, the key words “cell bank, umbilical cord blood, Wharton's jelly, stem cell and mesenchymal stem cell” were searched in PubMed and Google scholar databases in the period from 1990 to 2022.

Cord blood cells have significant biological differences compared to other sources (bone marrow and peripheral blood).The absolute number of lymphocytes in cord blood is higher than the peripheral blood and the relative number of natural killer cells in cord blood is higher. Also, cells derived from umbilical cord blood have longer telomeres and more self-renewal capacity than peripheral blood and bone marrow, which makes them very potent.

Conclusions :

This source is of interest not only because of its high immunomodulatory properties in the treatment of inflammatory, autoimmune and systemic diseases, but also because of its anti-inflammatory properties, high differentiation ability and high proliferation capacity, as an ideal option for cell therapy in diseases in addition to hematological disorders. In addition, the preparation, processing, maintenance and storage of cells derived from umbilical cord blood are easy and inexpensive, which is an important point for treatment systems worldwide.

The chlorophyll biosynthesis pathway is a main target for genetic modification to change plant photosynthesis and growth rate to support a greater demand for food in the growing world population. In this study, the effect of overexpression of GSA gene one of gene involved in biosynthesis pathway of chlorophyll on physiological condition of tobacco plant was investigated. 5-Aminolevulinate (ALA) is product of GSA gene. ALA is a precursor for all tetrapyrrole, these components have impotent roles in living cell, as pigments, light receptor (Phytochrome), prosthetic group of many different proteins (like cytochromes, hemoglobin, myoglobin, and leghemoglobin) and enzymes (for example Catalase, Ascorbate, Peroxidase and etc.). Nowadays, ALA has received wide attention for its widespread usage in agriculture, forestry and medication. ALA at low concentrations increases photosynthesis, growth, development, yield and productivity, also promoted fruit color appearance and quality and taste of products in treated plants under both normal and stressful conditions. ALA also improves antioxidant features, absorption of nutrient, water use efficiency and osmotic balance in plants.

 In this research, according to bioinformatics studies, MsGSA gene cDNA of Alfalfa (Medicago sativa L. cv. Isfahani) was selected to transfer to Xanthi tobacco (Nicotiana tabacum) plant, the binary expression vector pBI121 which has Kanamycin antibiotic resistance gene for selection in bacteria and plants, cutting sites for SacI and BamHI enzyme, CaMV35S promoter (cauliflower mosaic virus promoter), nos transcription termination sequences and ß-glucuronidase (GUS) reporter gene was used. After constructing the gene construct pBI121-GSA and confirming the transfer of the construct using PCR cloning methods, enzymatic digestion and sequencing were performed, then the corresponding construct was transferred to Agrobacterium tumefaciens strain LB4404 using Agrobacterium with the gene construct. The corresponding gene was transferred to the tobacco plant genome and the transgenic plants were selected on the medium containing kanamycin and the presence of the gene was confirmed by performing PCR in the regenerated plants. The rooted transgenic sprouts were transferred to the soil. The level of GSA gene expression in the resulting transgenic plants was evaluated by real-time PCR, and their growth rate and biochemical content were also evaluated.

 It was observed that the growth of transgenic plants increased significantly depending on the level of GSA gene expression, and the content of ALA (aminolevulinic acid) and chlorophyll a, b and total chlorophyll, which are the products of the corresponding gene expression. The results also showed the content of anthocyanin, flavonoids and phenol of plants have significantly increased in proportion to the increase in GSA gene expression compared to wild type tobacco plants.

 The growth rate as well as the content of chlorophyll a, b, total chlorophyll, ALA, anthocyanin, flavonoids and phenol of transgenic GSA plants is proportional to the increase in the expression of the GSA gene. The results from this study indicate that an increase in transgenic growth rate as well as an increase in the secondary metabolites content in transgenic plants were influenced by GSA transferred gene and an increase in the content of ALA. These results imply that transgenic tobacco plants expressing MsGSA gene had higher resistance potential to stresses than the wild type tobacco plants.

Gamma irradiation (GI) of platelet concentrates (PCs) is done to prevent the risk of Transfusion associated graft versus host disease (TA-GVHD). However, some of studies indicate a lower post-transfusion responses and aggravation of platelet storage lesion (PSL) after GI. In this study, the effect of GI on the platelet metabolic status in stored PRP-PCs was investigated.

in our experimental study, 10 PRP-PC were randomly obtained from Iranian Blood Transfusion Organization (IBTO). Then, two ABO- and D matched PRP-PC units were pooled and splited into two bags, one kept as control while other was gamma-irradiated with 30 Gray. Within 7-day storage, glucose concentration and LDH activity were measured by enzymo-colorimetric method. PLT count and pH were measured using a hematology whole blood analyzer and the pH meter, respectively. Swirling was evaluated by visual assessment. Statistical data were analyzed by Kruskal-Wallis test with Dunn’s multiple comparison test and Wilcoxon Mached-Pair test. P values of less than 0.05 were considered to be significant.

Swirling was maintained in both groups throughout the storage period. Platelet count significantly decreased on Days 5 and 7 of storage but there was no significant difference between irradiated and non-irradiated PCs. Glucose decreased whilst LDH activity increased during storage period. The increments of LDH activities were significant on Days 5 (P<.05) and 7 of storage (P<.01) in non-irradiated groups.

Conclusions  :

The quality of irradiated PCs is well maintained throughout the storage period, with minimal difference in metabolic parameters compared to non-irradiated PLTs.

Gamma irradiation (GI) to platelet products is a usual therapeutic procedure for preventing the transfusion associated graft versus host disease (TA-GVHD) in susceptible recipients. Nevertheless, some studies indicate a decrease in platelet recovery after transfusion, associated with higher levels of platelet storage lesion (PSL) in gamma irradiated platelets. In addition, the induction of oxidant stress, especially the increase in the production of reactive oxygen species (ROS) following the treatment of platelet products with gamma rays, has been reported in some studies. Therefore, given the known effects of ROS on PSL induction, the review presented here, while introducing different sources of ROS production during storage, also discusses the importance of storage-dependent oxidative stress in platelet products exposed to gamma radiation. For this purpose, studies published in MEDLINE, PubMed and Google scholar were searched for relevant keywords, among which 66 studies were cited in this review.

This research is related to the development of technology in the field of automatic text to image generation. In this regard, two main goals are pursued; first, the generated image should look as real as possible; and second, the generated image should be a meaningful description of the input text. our proposed method is a Multi Sentences Hierarchical GAN (MSH-GAN) for text to image generation. In this research project, we have considered two main strategies: 1) produce a higher quality image in the first step, and 2) use two additional descriptions to improve the original image in the next steps. Our goal is to focus on using more information to generate images with higher resolution by using more than one sentence input text. We have proposed different models based on GANs and Memory Networks. We have also used more challenging dataset called ids-ade. This is the first time; this dataset has been used in this area. We have evaluated our models based on IS, FID and, R-precision evaluation metrics. Experimental results demonstrate that our best model performs favorably against the basic state-of-the-art approaches like StackGAN and AttGAN.

During storage, platelets may lose their functional capability and structural integrity. This process is often called as "platelet storage lesion" (PSL), which is characterized with changes in morphology, metabolism, membrane structure, and expression of platelet activation and apoptotic markers. Apoptosis, or programmed cell death, is an energy-dependent physiological mechanism that results in the controlled removal of unwanted or damaged cells. While it has long been attributed exclusively to nucleated cells, many studies demonstrated that apoptosis also occurs in anucleate cells and platelets.

Studies published in MEDLINE, PubMed, and Google scholar are assessed for keywords and 55 articles is cited

The present review article describes the different apoptosis pathways in platelets, while adressing the markers, methods and probes used for evaluating apoptosis in platelet concentrates.

The evaluation of apoptosis can play an important role in identifying the mechanisms involved in platelet storage lesion.

The decision tree is one of the most important algorithms in the classification which offers a comprehensible model of data. In building a tree we may encounter a memory limitation. The present study aimed to implement an incremental scalable approach based on fast splitting and present pruning to construct the decision tree on a large dataset as the complexity of the tree decreases. The proposed algorithm constructs the decision tree without storing the entire dataset in the primary memory by using a minimum number of parameters. Furthermore, the J-max Pre pruning method was used to reduce the complexity with acceptable results. Experimental results show that this approach can create a balance between the accuracy and complexity of the tree and overcome the difficulties of the complexity of the tree. In spite of the appropriate accuracy and time, the proposed algorithm could produce a decision tree with less complexity on the large dataset.

Regarding optimization problems, there is a high demand for high-performance algorithms that can process the problem solution-space efficiently and find the best ones quite quickly. An approach to get this target is based on using swarm intelligence algorithms; these algorithms apply a population of simple agents to communicate locally with one another and with their surroundings. In this paper, we propose a novel approach based on combining the characteristics of the two algorithms: Cat Swarm Optimization (CSO) and the Shuffled Frog Leaping Algorithm (SFLA). The experimental results show the convergence ratio of our hybrid SFLA-CSO algorithm is seven times higher than that of CSO and five times higher than the convergence ratio of the standard SFLA algorithm. The obtained results also revealed that the hybrid method speeds up the convergence significantly, and reduces the error rate. We compared the proposed hybrid algorithm against the famous relevant algorithms PSO, ACO, ABC, GA, and SA; the results are valuable and promising.

This research work is concerned with the predictability of ensemble and singular tree-based machine learning algorithms during the recession and prosperity of the two companies listed in the Tehran Stock Exchange in the context of big data. In this regard, the main issue is that economic managers and the academic community require predicting models with more accuracy and reduced execution time; moreover, the prediction of the companies recession in the stock market is highly significant. Machine learning algorithms must be able to appropriately predict the stock return sign during the market downturn and boom days. Addressing the stated challenge will upgrade the quality of stock purchases and, subsequently, will increase profitability. In this article, the proposed solution relies on the utilization of tree-based machine learning algorithms in the context of big data. The proposed solution exploits the decision tree algorithm, which is a traditional and singular tree-based learning algorithm. Furthermore, two modern and ensemble tree-based learning algorithms, random forest and gradient boosted tree, has been utilized for predicting the stock return sign during recession and prosperity. The mentioned cases were implemented by applying the machine learning tools in python programming language and PYSPARK library that is used explicitly for the big data context. The utilized research data of the current study are the shares information of two companies of the Tehran Stock Exchange. The obtained results reveal that the applied ensemble learning algorithms have performed better than the singular learning algorithms. Additionally, adding 23 technical features to the initial data and subsequent applying of the PCA feature reduction method have demonstrated the best performance among other modes. In the meantime, it has been concluded that the initial data do not possess the proper resolution or generalizability, either during prosperity or recession.

This paper presents a new method for determining the middle band of discrete cosine transform based on the combination of genetic algorithm and tabu search. As embedded watermark is visible in low frequencies, and not resistant against attacks in high frequencies, the most suitable band for embedding is the middle band. In the Fourier domain, it can be determined by some filters but such a method does not exist in the discrete cosine domain. In discrete cosine transform the arrangement of frequency components does not have the orderliness of the Fourier transform itself, so, it is tried to find the middle band of image by Fourier transform and then find the exact location of the  middle band of discrete cosine transform by genetic algorithm and tabu search. In this method, we minimize the difference between the image that is obtained by applying the middle band of discrete cosine transform mask and the image obtained by the Fourier transform mask. Also, the proposed method can be used for low and high band of discrete cosine transform masks. The implementation and tests for low, middle and high bands resulted in 0.0062, 0.0149 and 0.0061 averages errors, respectively. These results for the test images are satisfactory.

This paper investigates the relationship between vulnerability types and their workarounds. Via a  workaround solution, users prevent or mitigate the risk of a vulnerability without the need of eliminating it. So far, little attention has been paid to this fruitful approach, whereas workaround solutions can perform so efficiently when dealing with vulnerabilities. In this research, a proper dataset from four mostly referred vulnerability databases (OSVDB, Security Tracker, Cert CC Vulnerability Notes and NVD) is compiled. In this dataset which we have called VuWaDB, the workarounds are organized in six main categories configuration, code modification, route alteration, elimination, access restriction and utility tools. The CWEs that the NVD was assigned to, are used to determine vulnerability types. In order to discover the   relationship between vulnerabilities and their related workaround solutions, after a statistical survey, a  relevant bipartite graph is constructed. The obtained results are analyzed and presented in related tables, which provide the relation between software vulnerabilities and their workarounds.

Learning models and related results depend on the quality of the input data. If raw data is not properly cleaned and structured, the results are tending to be incorrect. Therefore, discretization as one of the preprocessing techniques plays an important role in learning processes. The most important challenge in the discretization process is to reduce the number of features’ values. This operation should be applied in a way that relationships between the features are maintained and accuracy of the classification algorithms would increase. In this paper, a new evolutionary multi-objective algorithm is presented. The proposed algorithm uses three objective functions to achieve high-quality discretization. The first and second objectives minimize the number of selected cut points and classification error, respectively. The third objective introduces a new criterion called the normalized cut, which uses the relationships between their features’ values to maintain the nature of the data. The performance of the proposed algorithm was tested using 20 benchmark datasets. According to the comparisons and the results of nonparametric statistical tests, the proposed algorithm has a better performance than other existing major methods.

Macrolophus pygmaeus Rambur is an most omnivorous predator which has considered in integrated pest management programs, especially for greenhouse pest management. In this study, biological properties and life table statistics of M. pygmaeus by feeding on Artemia urmiana Gunther cysts and Ephestia kuehniella Zeller eggs were studied under laboratory conditions (25±1°C, 65±5 % relative humidity and 16:8h L: D photoperiod) with 60 replications. The pods of green bean Phaseoulus vulgaris L. served as oviposition substrate and the moisture source. Developmental time of nymphal stages which fed by of E. kuehniella eggs and Artemia cysts were 17.04±0.11, 18.06±0.18 d for males and 17.31±0.09, 18.17±0.15 d for females respectively and were significantly different as well as intrinsic rate of increase (rm) was 0.080±0.005 and 0.064±0.006 d–1 respectively. Also, net reproductive rate (R0) was 18.12±2.97 and 10.70±2.43 eggs/individual on those food regims respectively. Furthermore, mean generation time (T) was estimated as 35.93±0.33 and 36.66±0.53 d respectively. Meanwhile, the reproductive parameters on flour moth larvae have been significantly higher than Artemia cyst. The results showed that feeding on E. kuehniella reduces nymphal period, while increases productivity and longevity of adults. According to the present findings, E. kuehniella is more suitable prey for rearing of this predator, but in absence of access to E. kuehniella, rearing on Artemia cysts is also possible.

Sexual desire is a complex issue influenced by a variety of factors particularly psychological factor. Therefore, the aim of this research was to investigate the effectiveness of schema therapy on married women with hypo-active sexual desire living in Sirjan City.

In this semi-experimental study, among married women with hypo- active sexual desire disorder referred to counseling centers of Sirjan City, 30 women were purposefully selected and were then divided into two groups of  15, experimental and control group. Experimental group received 10 weekly sessions of schema therapy. The data were collected by the Holbert Sexuality Index (1992) and analyzed by covariance test.

The findings of the present study indicated that the average score of hypo-active sexual desire in the experimental group was significantly decreased compared to control group (59.00 ± 17.62 vs 47.98 ± 14.05, p<0.05).

According to the findings of this study, schema therapy may be an effective method for treatment of female hypo-active sexual desire disorder.