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| 2. |
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| 3. |
- Chatron, N., et al.
(author)
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Bi-allelic GAD1 variants cause a neonatal onset syndromic developmental and epileptic encephalopathy
- 2020
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In: Brain. - : Oxford University Press (OUP). - 0006-8950 .- 1460-2156. ; 143:5, s. 1447-1461
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Journal article (peer-reviewed)abstract
- Developmental and epileptic encephalopathies are a heterogeneous group of early-onset epilepsy syndromes dramatically impairing neurodevelopment. Modern genomic technologies have revealed a number of monogenic origins and opened the door to therapeutic hopes. Here we describe a new syndromic developmental and epileptic encephalopathy caused by bi-allelic loss-of-function variants in GAD1, as presented by 11 patients from six independent consanguineous families. Seizure onset occurred in the first 2 months of life in all patients. All 10 patients, from whom early disease history was available, presented with seizure onset in the first month of life, mainly consisting of epileptic spasms or myoclonic seizures. Early EEG showed suppression-burst or pattern of burst attenuation or hypsarrhythmia if only recorded in the post-neonatal period. Eight patients had joint contractures and/or pes equinovarus. Seven patients presented a cleft palate and two also had an omphalocele, reproducing the phenotype of the knockout Gad1(-/-) mouse model. Four patients died before 4 years of age. GAD1 encodes the glutamate decarboxylase enzyme GAD67, a critical actor of the c-aminobutyric acid (GABA) metabolism as it catalyses the decarboxylation of glutamic acid to form GABA. Our findings evoke a novel syndrome related to GAD67 deficiency, characterized by the unique association of developmental and epileptic encephalopathies, cleft palate, joint contractures and/or omphalocele.
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| 4. |
- Hommadi, Ali H., et al.
(author)
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Evaluation of Actual Evapotranspiration and Crop Coefficient in Carrot by Remote Sensing Methodology Using Drainage and River Water to Overcome Reduced Water Availability
- 2023
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In: Engineering. - : Scientific Research Publishing. - 1947-3931 .- 1947-394X. ; 15:05, s. 352-366
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Journal article (peer-reviewed)abstract
- Searching for alternative methods for traditional irrigation is World trend at days due to a reduction in water and increased of drought due to climate changes therefore farmers need use modern methods of scheduling water and minimizing water losses while also increasing yield. To meet the future increasing demands water and food there is a need to utilize alternative methods to reduce evaporation, transpiration and deep percolation of water. Any countries use recycled water (drain and sewage) and desalination water from the sea or drains to irrigate crops plus computing actual crop evapotranspiration (ETc) so as to calculate the amount of water to apply to a crop.The paper aims to assess the actual evaporation and evaporation coefficient of carrots, by planting carrots in a field and the crop was exposed to several sources of water (DW and RW) and comparing ETc, Kc and production among plots of three sites (A, B and C). The study used two types of irrigation water (drain water (DW) and river water (RW)). The results were to monthly rate and accumulated actual evapotranspiration to C (irrigation by RW only) more than A (67% RW and 33% DW) and B (17% RW and 83%DW) via 7% and 58%, respectively. The yield to C more than A and B by 17% and 75%, respectively. In conclusion the use of DW can cause a reduction in crop consumptive of carrot crops also causes a reduction in yield, crop length, root length, root size, canopy of crop, number of leaves and biomass of the plant therefore, the drainage water needs to treated before irrigating crops And making use of it to irrigate the fields and fill the shortfall in the amount of water from the river. The drain water helped on filling the water shortage due to climate changes and giving production of carrot crop but less than river water.
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| 5. |
- Hommadi, Ali H., et al.
(author)
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Scheduling the Laterals of Shattulhilla River by Utilizing the Genetic Algorithm as Water Sustainability Technique
- 2024
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In: Proceedings of the 4th International Conference on Recent Innovation in Engineering ICRIE 2023, University of Duhok, College of Engineering, 13th – 14th September 2023. - : University of Garmian. ; , s. 84-93
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Conference paper (peer-reviewed)abstract
- Open channels are very important to deliver water from main sources to laterals especially for developing countries. Production is subjective by the way that the water is scheduled, and this scheduling is subject to several irrigation constraints. In open channel projects, for instance, maximum discharge of the laterals and main channels, depending on the size of their dimensions and the water requirements for fields. The current paper shows how efficient water scheduling, regarding the delivering water from the main channel to laterals in consequent time slots, can be done by utilizing a genetic algorithm optimisation technique. This research is intended to be applied for scheduling the Shattulhilla River in Babylon City and has broad applications for open channel projects in Iraq. The obtained results clarify how the genetic algorithm optimisation modelling is a sophisticated tool which operators of irrigation projects could now utilize to timetable open channels of irrigation systems.
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| 6. |
- Hussien, Abdelazim, et al.
(author)
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Recent Advances in Harris Hawks Optimization : A Comparative Study and Applications
- 2022
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In: Electronics. - : MDPI. - 2079-9292. ; 11:12
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Research review (peer-reviewed)abstract
- The Harris hawk optimizer is a recent population-based metaheuristics algorithm that simulates the hunting behavior of hawks. This swarm-based optimizer performs the optimization procedure using a novel way of exploration and exploitation and the multiphases of search. In this review research, we focused on the applications and developments of the recent well-established robust optimizer Harris hawk optimizer (HHO) as one of the most popular swarm-based techniques of 2020. Moreover, several experiments were carried out to prove the powerfulness and effectivness of HHO compared with nine other state-of-art algorithms using Congress on Evolutionary Computation (CEC2005) and CEC2017. The literature review paper includes deep insight about possible future directions and possible ideas worth investigations regarding the new variants of the HHO algorithm and its widespread applications.
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| 7. |
- Rosenhahn, Erik, et al.
(author)
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Bi-allelic loss-of-function variants in PPFIBP1 cause a neurodevelopmental disorder with microcephaly, epilepsy, and periventricular calcifications
- 2022
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In: American Journal of Human Genetics. - : Cell Press. - 0002-9297 .- 1537-6605. ; 109:8, s. 1421-1435
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Journal article (peer-reviewed)abstract
- PPFIBP1 encodes for the liprin-β1 protein, which has been shown to play a role in neuronal outgrowth and synapse formation in Drosophila melanogaster. By exome and genome sequencing, we detected nine ultra-rare homozygous loss-of-function variants in 16 individuals from 12 unrelated families. The individuals presented with moderate to profound developmental delay, often refractory early-onset epilepsy, and progressive microcephaly. Further common clinical findings included muscular hyper- and hypotonia, spasticity, failure to thrive and short stature, feeding difficulties, impaired vision, and congenital heart defects. Neuroimaging revealed abnormalities of brain morphology with leukoencephalopathy, ventriculomegaly, cortical abnormalities, and intracranial periventricular calcifications as major features. In a fetus with intracranial calcifications, we identified a rare homozygous missense variant that by structural analysis was predicted to disturb the topology of the SAM domain region that is essential for protein-protein interaction. For further insight into the effects of PPFIBP1 loss of function, we performed automated behavioral phenotyping of a Caenorhabditis elegans PPFIBP1/hlb-1 knockout model, which revealed defects in spontaneous and light-induced behavior and confirmed resistance to the acetylcholinesterase inhibitor aldicarb, suggesting a defect in the neuronal presynaptic zone. In conclusion, we establish bi-allelic loss-of-function variants in PPFIBP1 as a cause of an autosomal recessive severe neurodevelopmental disorder with early-onset epilepsy, microcephaly, and periventricular calcifications.
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| 8. |
- Daqaq, Fatima, et al.
(author)
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A leader supply-demand-based optimization for large scale optimal power flow problem considering renewable energy generations
- 2023
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In: Scientific Reports. - : NATURE PORTFOLIO. - 2045-2322. ; 13:1
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Journal article (peer-reviewed)abstract
- The supply-demand-based optimization (SDO) is among the recent stochastic approaches that have proven its capability in solving challenging engineering tasks. Owing to the non-linearity and complexity of the real-world IEEE optimal power flow (OPF) in modern power system issues and like the existing algorithms, the SDO optimizer necessitates some enhancement to satisfy the required OPF characteristics integrating hybrid wind and solar powers. Thus, a SDO variant namely leader supply-demand-based optimization (LSDO) is proposed in this research. The LSDO is suggested to improve the exploration based on the simultaneous crossover and mutation mechanisms and thereby reduce the probability of trapping in local optima. The LSDO effectiveness has been first tested on 23 benchmark functions and has been assessed through a comparison with well-regarded state-of-the-art competitors. Afterward, Three well-known constrained IEEE 30, 57, and 118-bus test systems incorporating both wind and solar power sources were investigated in order to authenticate the performance of the LSDO considering a constraint handling technique called superiority of feasible solutions (SF). The statistical outcomes reveal that the LSDO offers promising competitive results not only for its first version but also for the other competitors.
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| 9. |
- Hashim, Ahmed, et al.
(author)
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Pattern of novel psychoactive substance use among patients presented to the poison control centre of Ain Shams University Hospitals, Egypt : A cross-sectional study
- 2022
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In: Heliyon. - : Elsevier BV. - 2405-8440. ; 8:8
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Journal article (peer-reviewed)abstract
- Background: Novel psychoactive substances (NPSs) are relatively new substances in the illicit drug market, notpreviously listed in the United Nations Office on Drugs and Crime (UNDOC). Strox and Voodoo are consideredsome of the most popular blends of NPS in the Egyptian drug market.Objectives: The current study was conducted to assess NPS's use pattern: Voodoo and Strox among acutelyintoxicated patients presented to the poison control center of Ain Shams University Hospitals (PCC- ASUH).Methods: A single center based cross-sectional study was carried out in the PCC-ASUH among acutely intoxicatedpatients presenting to the emergency department (ED) over four months (from January–April 2019. using apreviously adopted and validated Fahmy and El-Sherbini socioeconomic scale (SES). Data were presented asmean, median and range as appropriate. Both smoking and crowding indexes were calculated and presented aspreviously reported.Results: Fifty-one patients were presented to the ED of PCC-ASUH during the study period. A total of 96.1% (n ¼49) were males. The mean age was 25 7.5 years. The most common NPS used was Strox: 54.9% (n ¼ 28),followed by Voodoo: 27.4% (n ¼ 14). Neurological and gastrointestinal (GI) symptoms were the most frequentpresentations. The most common motive behind NPS use was the desire to give a trial of new psychoactivesubstances. The mean SES score was 35.1 13.17. Most patients have the preparatory as the highest education36.0% (n ¼ 18).Conclusions: NPS use is common among young males in preparatory education from different social classes,starting it most commonly as a means to experiencing a new high. Neurological and GI manifestations are themost common presenting symptoms of NPS intoxication.
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| 10. |
- Hashim, Fatma A., et al.
(author)
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An efficient adaptive-mutated Coati optimization algorithm for feature selection and global optimization
- 2023
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In: Alexandria Engineering Journal. - : ELSEVIER. - 1110-0168 .- 2090-2670. ; 85, s. 29-48
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Journal article (peer-reviewed)abstract
- The feature selection (FS) problem has occupied a great interest of scientists lately since the highly dimensional datasets might have many redundant and irrelevant features. FS aims to eliminate such features and select the most important ones that affect classification performance. Metaheuristic algorithms are the best choice to solve this combinatorial problem. Recent researchers invented and adapted new algorithms, hybridized many algorithms, or enhanced existing ones by adding some operators to solve the FS problem. In our paper, we added some operators to the Coati optimization algorithm (CoatiOA). The first operator is the adaptive s-best mutation operator to enhance the balance between exploration and exploitation. The second operator is the directional mutation rule that opens the way to discover the search space thoroughly. The final enhancement is controlling the search direction toward the global best. We tested the proposed mCoatiOA algorithm in solving) in solving challenging problems from the CEC'20 test suite. mCoatiOA performance was compared with Dandelion Optimizer (DO), African vultures optimization algorithm (AVOA), Artificial gorilla troops optimizer (GTO), whale optimization algorithm (WOA), Fick's Law Algorithm (FLA), Particle swarm optimization (PSO), Harris hawks optimization (HHO), and Tunicate swarm algorithm (TSA). According to the average fitness, it can be observed that the proposed method, mCoatiOA, performs better than the other optimization algorithms on 8 test functions. It has lower average standard deviation values compared to the competitive algorithms. Wilcoxon test showed that the results obtained by mCoatiOA are significantly different from those of the other rival algorithms. mCoatiOA has been tested as a feature selection algorithm. Fifteen benchmark datasets of various types were collected from the UCI machine-learning repository. Different evaluation criteria are used to determine the effectiveness of the proposed method. The proposed mCoatiOA achieved better results in comparison with other published methods. It achieved the mean best results on 75% of the datasets.
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| 11. |
- Hassan, Mohamed H., et al.
(author)
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An enhanced hunter-prey optimization for optimal power flow with FACTS devices and wind power integration
- 2023
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In: IET Generation, Transmission & Distribution. - : INST ENGINEERING TECHNOLOGY-IET. - 1751-8687 .- 1751-8695. ; 17:14, s. 3115-3139
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Journal article (peer-reviewed)abstract
- This paper proposes an improved version of the Hunter-prey optimization (HPO) method to enhance its search capabilities for solving the Optimal Power Flow (OPF) problem, which includes FACTS devices and wind power energy integration. The new algorithm is inspired by the behavior of predator and prey animals, such as lions, wolves, leopards, stags, and gazelles. The primary contribution of this study is to address the tendency of the original HPO approach to get trapped in local optima, by proposing an enhanced Hunter-prey optimization (EHPO) approach that improves both the exploration and exploitation phases. This is achieved through a random mutation for exploration and an adaptive process for exploitation, which balances the transition between the two phases. The performance of the EHPO algorithm is compared with other optimization algorithms, and subsequently, it is used to solve the OPF problem incorporating FACTS devices and wind power. The results demonstrate the effectiveness and superiority of the proposed algorithm. In conclusion, this study successfully enhances the EHPO algorithm to provide better accuracy and faster convergence in finding optimal solutions for complex real-world problems.
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| 12. |
- Hassan, Mohamed H., et al.
(author)
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Optimal power flow analysis considering renewable energy resources uncertainty based on an improved wild horse optimizer
- 2023
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In: IET Generation, Transmission & Distribution. - : INST ENGINEERING TECHNOLOGY-IET. - 1751-8687 .- 1751-8695. ; 17:16, s. 3582-3606
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Journal article (peer-reviewed)abstract
- In recent years, electricity networks across the globe have undergone rapid development, especially with the incorporation of various renewable energy sources (RES). The goal is to increase the penetration level of RES in the power grid to maximize energy efficiency. However, the optimal power flow (OPF) problem for conventional power generation with RES integration is highly complex, non-linear, and non-convex, and this complexity is further compounded when stochastic RES is integrated into the network. To address this problem, this article proposes an elite evolutionary strategy (EES) based on evolutionary approaches to improve the Wild Horse Optimizer (WHO), creating an enhanced hybrid technique called EESWHO. The proposed techniques effectiveness and robustness were tested on 23 numerical optimization test functions, including seven unimodal, six multimodal, and ten composite test functions. Furthermore, the EESWHO was applied to the modified IEEE-30 bus test system to demonstrate its supremacy and efficacy in achieving the optimal solution. The simulation results show that the proposed EESWHO algorithm is highly effective and robust in achieving the optimal solution to the OPF problem with stochastic RES. This approach provides a practical solution to the challenges posed by the integration of RES into power networks, allowing for maximum energy efficiency while minimizing system complexity.
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| 13. |
- Hassan, Mohamed H., et al.
(author)
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Supply-demand optimizer for economic emission dispatch incorporating price penalty factor and variable load demand levels
- 2023
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In: IET Generation, Transmission & Distribution. - : INST ENGINEERING TECHNOLOGY-IET. - 1751-8687 .- 1751-8695. ; 17:14, s. 3211-3231
-
Journal article (peer-reviewed)abstract
- The Economic and Emission Dispatch (EED) method is widely used to optimize generator output in a power system. The goal is to reduce fuel costs and emissions, including carbon dioxide, sulphur dioxide, and nitrogen oxides, while maintaining power balance and adhering to limit constraints. EED aims to minimize emissions and operating costs while meeting power demands. To solve the multi-objective EED problem, the supply-demand optimization (SDO) algorithm is proposed, which employs a price penalty factor approach to convert it into a single-objective function. The SDO algorithm uses a swarm-based optimization strategy inspired by supply-demand mechanisms in economics. The algorithms performance is evaluated on seven benchmark functions before being used to simulate the EED problem on power systems with varying numbers of units and load demands. Established algorithms like the Grey Wolf Optimizer (GWO), Moth-Flame Optimization (MFO), Transient Search Optimization (TSO), and Whale Optimization Algorithm (WOA) are compared to the SDO algorithm. The simulations are conducted on power systems with different numbers of units and load demands to optimize power generation output. The numerical analyses demonstrate that the SDO technique is more efficient and produces higher quality solutions than other recent optimization methods.
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| 14. |
- Hegazy, Mohamed-Elamir F., et al.
(author)
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Terpenoid bio-transformations and applications via cell/organ cultures : a systematic review
- 2020
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In: Critical reviews in biotechnology. - : Informa UK Limited. - 0738-8551 .- 1549-7801. ; 40:1, s. 64-82
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Research review (peer-reviewed)abstract
- Structurally diverse natural products are valued for their targeted biological activity. The challenge of working with such metabolites is their low natural abundance and complex structure, often with multiple stereocenters, precludes large-scale or unsophisticated chemical synthesis. Since select plants contain the enzymatic machinery necessary to produce specialized compounds, tissue cultures can be used to achieve key transformations for large-scale chemical and/or pharmaceutical applications. In this context, plant tissue-culture bio-transformations have demonstrated great promise in the preparation of pharmaceutical products. This review describes the capacity of cultured plant cells to transform terpenoid natural products and the specific application of such transformations over the past three decades (1988-2019).
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| 15. |
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| 16. |
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| 17. |
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| 18. |
- Hussien, Y, et al.
(author)
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Multiple sclerosis: expression of CD1a and production of IL-12p70 and IFN-gamma by blood mononuclear cells in patients on combination therapy with IFN-beta and glatiramer acetate compared to monotherapy with IFN-beta
- 2004
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In: Multiple sclerosis (Houndmills, Basingstoke, England). - : SAGE Publications. - 1352-4585 .- 1477-0970. ; 10:1, s. 16-25
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Journal article (peer-reviewed)abstract
- Current therapy of multiple sclerosis (MS) with interferon-beta (IFN-b) or glatiramer acetate (GA) has modest effects on the course of MS. Both compounds affect several immune variables, like expression of cell surface molecules and cytokine levels. Here we compared untreated MS, therapy with IFN-b alone and combined with GA, and healthy controls (HC), regarding expression on HLA -DR+ blood mononuclear cells (MNC) of C D1a that is a cell surface molecule with capacity to present glycolipids to T cells, and of C D80 and C D86 which are costimulatory molecules that activate Th1 and Th2 responses. C ytokine production by MNC was also measured. Flow cytometry and ELISA were used. C ross-sectional comparisons revealed that untreated MS patients had higher C D1a+ HLA -DR+ MNC and lower IL-10 production compared to patients treated with IFN-b or IFN-b+G A or HC. Untreated MS patients also had higher spontaneous IFN-g and IL-12p70 production compared to MS patients treated with IFN-b+G A or HC, but not when compared to MS patients on monotherapy with IFN-b. Low C D1a+ HLA -DR+ MNC and low spontaneous production of IL-12p70 and IFN-g were more pronounced in patients treated with IFN-b+G A than with IFN-b alone. In order to clarify whether these changes reflect disease activity or treatment effects, we performed a follow up study. Nineteen MS patients with disease progression, despite monotherapy with IFN-b for more than one year, were re-examined after one to three and four to six months of treatment with IFN-b+G A. This combination therapy was associated with normalization of C D1a+ HLA -DR+ MNC, IL-12p70 and IFN-g. It remains to be shown whether these immunological changes imply a clinical benefit. Follow up studies of immune variables versus clinical effects during combined therapy of MS with IFN-b+G A are ongoing.
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| 19. |
- Ibrahim, Mahmoud A. A., et al.
(author)
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In silico drug discovery of major metabolites from spices as SARS-CoV-2 main protease inhibitors
- 2020
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In: Computers in Biology and Medicine. - : Elsevier BV. - 0010-4825 .- 1879-0534. ; 126
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Journal article (peer-reviewed)abstract
- Coronavirus Disease 2019 (COVID-19) is an infectious illness caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), originally identified in Wuhan, China (December 2019) and has since expanded into a pandemic. Here, we investigate metabolites present in several common spices as possible inhibitors of COVID-19. Specifically, 32 compounds isolated from 14 cooking seasonings were examined as inhibitors for SARS-CoV-2 main protease (MPrn), which is required for viral multiplication. Using a drug discovery approach to identify possible antiviral leads, in silico molecular docking studies were performed. Docking calculations revealed a high potency of salvianolic acid A and curcumin as MPr inhibitors with binding energies of 9.7 and 9.2 kcal/mol, respectively. Binding mode analysis demonstrated the ability of salvianolic acid A and curcumin to form nine and six hydrogen bonds, respectively with amino acids proximal to MPr 's active site. Stabilities and binding affinities of the two identified natural spices were calculated over 40 ns molecular dynamics simulations and compared to an antiviral protease inhibitor (lopinavir). Molecular mechanics-generalized Born surface area energy calculations revealed greater salvianolic acid A affinity for the enzyme over curcumin and lopinavir with energies of 44.8, 34.2 and 34.8 kcal/mol, respectively. Using a STRING database, protein-protein interactions were identified for salvianolic acid A included the biochemical signaling genes ACE, MAPK14 and ESR1; and for curcumin, EGFR and TNF. This study establishes salvianolic acid A as an in silico natural product inhibitor against the SARS-CoV-2 main protease and provides a promising inhibitor lead for in vitro enzyme testing.
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| 20. |
- Lalani, Tahaniyat, et al.
(author)
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In-hospital and 1-year mortality in patients undergoing early surgery for prosthetic valve endocarditis
- 2013
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In: JAMA Internal Medicine. - : American Medical Association (AMA). - 2168-6106. ; 173:16, s. 1495-1504
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Journal article (peer-reviewed)abstract
- IMPORTANCE: There are limited prospective, controlled data evaluating survival in patients receiving early surgery vs medical therapy for prosthetic valve endocarditis (PVE). OBJECTIVE: To determine the in-hospital and 1-year mortality in patients with PVE who undergo valve replacement during index hospitalization compared with patients who receive medical therapy alone, after controlling for survival and treatment selection bias. DESIGN, SETTING, AND PARTICIPANTS: Participants were enrolled between June 2000 and December 2006 in the International Collaboration on Endocarditis-Prospective Cohort Study (ICE-PCS), a prospective, multinational, observational cohort of patients with infective endocarditis. Patients hospitalized with definite right- or left-sided PVE were included in the analysis. We evaluated the effect of treatment assignment on mortality, after adjusting for biases using a Cox proportional hazards model that included inverse probability of treatment weighting and surgery as a time-dependent covariate. The cohort was stratified by probability (propensity) for surgery, and outcomes were compared between the treatment groups within each stratum. INTERVENTIONS: Valve replacement during index hospitalization (early surgery) vs medical therapy. MAIN OUTCOMES AND MEASURES: In-hospital and 1-year mortality. RESULTS: Of the 1025 patients with PVE, 490 patients (47.8%) underwent early surgery and 535 individuals (52.2%) received medical therapy alone. Compared with medical therapy, early surgery was associated with lower in-hospital mortality in the unadjusted analysis and after controlling for treatment selection bias (in-hospital mortality: hazard ratio [HR], 0.44 [95% CI, 0.38-0.52] and lower 1-year mortality: HR, 0.57 [95% CI, 0.49-0.67]). The lower mortality associated with surgery did not persist after adjustment for survivor bias (in-hospital mortality: HR, 0.90 [95% CI, 0.76-1.07] and 1-year mortality: HR, 1.04 [95% CI, 0.89-1.23]). Subgroup analysis indicated a lower in-hospital mortality with early surgery in the highest surgical propensity quintile (21.2% vs 37.5%; P = .03). At 1-year follow-up, the reduced mortality with surgery was observed in the fourth (24.8% vs 42.9%; P = .007) and fifth (27.9% vs 50.0%; P = .007) quintiles of surgical propensity. CONCLUSIONS AND RELEVANCE: Prosthetic valve endocarditis remains associated with a high 1-year mortality rate. After adjustment for differences in clinical characteristics and survival bias, early valve replacement was not associated with lower mortality compared with medical therapy in the overall cohort. Further studies are needed to define the effect and timing of surgery in patients with PVE who have indications for surgery.
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| 21. |
- Mohamed, Tarik A., et al.
(author)
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Plant cell cultures : An enzymatic tool for polyphenolic and flavonoid transformations
- 2022
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In: Phytomedicine. - : Elsevier BV. - 0944-7113 .- 1618-095X. ; 100
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Journal article (peer-reviewed)abstract
- Background: In the pharmaceutical sector, tissue culture techniques for large-scale production of natural chemicals can be a less expensive alternative to large-scale synthesis. Although recent biotransformation research have used plant cell cultures to target a wide range of bioactive compounds, more compiled information and synopses are needed to better understand metabolic pathways and improve biotransformation efficiencies.Purpose: This report reviews the biochemical transformation of phenolic natural products by plant cell cultures in order to identify potential novel biotechnological approaches for ensuring more homogeneous and stable phenolic production year-round under controlled environmental conditions.Methods: Articles on the use of plant cell culture for polyphenolic and flavonoid transformations (1988 - 2021) were retrieved from SciFinder, PubMed, Scopus, and Web of Science through electronic and manual search in English. Following that, the authors chose the required papers based on the criteria they defined. The following keywords were used for the online search: biotransformation, Plant cell cultures, flavonoids, phenolics, and pharmaceutical products.Results: The initial search found a total of 96 articles. However, only 70 of them were selected as they met the inclusion criteria defined by the authors. The analysis of these studies revealed that plant tissue culture is applicable for the large-scale production of plant secondary metabolites including the phenolics, which have high therapeutic value.Conclusion: Plant tissue cultures could be employed as an efficient technique for producing secondary metabolites including phenolics. Phenolics possess a wide range of therapeutic benefits, as anti-oxidant, anti-cancer, and antiinflammatory properties. Callus culture, suspension cultures, transformation, and other procedures have been used to improve the synthesis of phenolics. Their production on a large scale is now achievable. More breakthroughs will lead to newer insights and, without a doubt, to a new era of phenolics-based pharmacological agents for the treatment of a variety of infectious and degenerative disorders.
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| 22. |
- Mostafa, Reham R., et al.
(author)
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An enhanced chameleon swarm algorithm for global optimization and multi-level thresholding medical image segmentation
- 2024
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In: Neural Computing & Applications. - : SPRINGER LONDON LTD. - 0941-0643 .- 1433-3058.
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Journal article (peer-reviewed)abstract
- Medical image segmentation is crucial in using digital images for disease diagnosis, particularly in post-processing tasks such as analysis and disease identification. Segmentation of magnetic resonance imaging (MRI) and computed tomography images pose distinctive challenges attributed to factors such as inadequate illumination during the image acquisition process. Multilevel thresholding is a widely adopted method for image segmentation due to its effectiveness and ease of implementation. However, the primary challenge lies in selecting the optimal set of thresholds to achieve accurate segmentation. While Otsu's between-class variance and Kapur's entropy assist in identifying optimal thresholds, their application to cases requiring more than two thresholds can be computationally intensive. Meta-heuristic algorithms are commonly employed in literature to calculate the threshold values; however, they have limitations such as a lack of precise convergence and a tendency to become stuck in local optimum solutions. In this paper, we introduce an improved chameleon swarm algorithm (ICSA) to address these limitations. ICSA is designed for image segmentation and global optimization tasks, aiming to improve the precision and efficiency of threshold selection in medical image segmentation. ICSA introduces the concept of the "best random mutation strategy" to enhance the search capabilities of the standard chameleon swarm algorithm (CSA). This strategy leverages three distribution functions-Levy, Gaussian, and Cauchy-for mutating search individuals. These diverse distributions contribute to improved solution quality and help prevent premature convergence. We conduct comprehensive experiments using the IEEE CEC'20 complex optimization benchmark test suite to evaluate ICSA's performance. Additionally, we employ ICSA in image segmentation, utilizing Otsu's approach and Kapur's entropy as fitness functions to determine optimal threshold values for a set of MRI images. Comparative analysis reveals that ICSA outperforms well-known metaheuristic algorithms when applied to the CEC'20 test suite and significantly improves image segmentation performance, proving its ability to avoid local optima and overcome the original algorithm's drawbacks. Medical image segmentation is essential for employing digital images for disease diagnosis, particularly for post-processing activities such as analysis and disease identification. Due to poor illumination and other acquisition-related difficulties, radiologists are especially concerned about the optimal segmentation of brain magnetic resonance imaging (MRI). Multilevel thresholding is the most widely used image segmentation method due to its efficacy and simplicity of implementation. The issue, however, is selecting the optimum set of criteria to effectively segment each image. Although methods like Otsu's between-class variance and Kapur's entropy help locate the optimal thresholds, using them for more than two thresholds requires a significant amount of processing resources. Meta-heuristic algorithms are commonly employed in literature to calculate the threshold values; however, they have limitations such as a lack of precise convergence and a tendency to become stuck in local optimum solutions. Due to the aforementioned, we present an improved chameleon swarm algorithm (ICSA) in this paper for image segmentation and global optimization tasks to be able to address these weaknesses. In the ICSA method, the best random mutation strategy has been introduced to improve the searchability of the standard CSA. The best random strategy utilizes three different types of distribution: Levy, Gaussian, and Cauchy to mutate the search individuals. These distributions have different functions, which help enhance the quality of the solutions and avoid premature convergence. Using the IEEE CEC'20 test suite as a recent complex optimization benchmark, a comprehensive set of experiments is carried out in order to evaluate the ICSA method and demonstrate the impact of combining the best random mutation strategy with the original CSA in improving both the performance of the solutions and the rate at which they converge. Furthermore, utilizing the Otsu approach and Kapur's entropy as a fitness function, ICSA is used as an image segmentation method to select the ideal threshold values for segmenting a set of MRI images. Within the experiments, the ICSA findings are compared with well-known metaheuristic algorithms. The comparative findings showed that ICSA performs better than other competitors in solving the CEC'20 test suite and has a significant performance boost in image segmentation.
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| 23. |
- Selim, Ali, et al.
(author)
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Allocation of distributed generator in power networks through an enhanced jellyfish search algorithm
- 2023
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In: Energy Reports. - : ELSEVIER. - 2352-4847. ; 10, s. 4761-4780
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Journal article (peer-reviewed)abstract
- This study presents the Jellyfish Search Optimizer (JS), a novel metaheuristic optimization algorithm, for the efficient allocation of multi-type distributed generations (DGs) in distribution power systems. To further enhance the performance of the original JS algorithm, a leader-based mutation-selection approach called LJS is proposed to circumvent local optima. The effectiveness of LJS is evaluated with various benchmark problems and compared with other competitive optimization algorithms. Moreover, LJS is utilized to allocate different types of DGs (Type I, Type II, and Type III) in standard IEEE and practical Portuguese distribution systems. The opti-mization problem of the DG allocation is performed to minimize the power loss and enhance the voltage profile by minimizing the voltage deviation (VD) and maximizing the voltage stability index (VSI) as single-and multi-objectives optimization problems. The results obtained demonstrate the superior performance of LJS in achieving optimal solutions for benchmark problems as well as for the allocation of multi-type DGs. Notably, the inte-gration of DG Type III leads to a remarkable reduction in total power loss, achieving a reduction of 94.44 %, 98.10 % and 96.07 in IEEE 33-bus,IEEE 69-bus and 94 bus systems, respectively.
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