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Peptic ulcer disease remains a prevalent gastrointestinal disorder worldwide. Current treatments often have limitations, sparking interest in alternative therapies from medicinal plants. This review examines the gastroprotective potential of 54 North African medicinal plants against peptic ulcers. An extensive literature search was conducted, focusing on plants with preclinical and clinical evidence of anti-ulcer efficacy and documented use in North African traditional medicine. The review identified several promising plant species, such as licorice ( Glycyrrhiza glabra ), chamomile ( Matricaria chamomilla ), olive ( Olea europaea ), pomegranate ( Punica granatum ), Aloe vera, and black seed ( Nigella sativa ), along with their bioactive constituents, including flavonoids, tannins, and terpenoids. These compounds exhibit gastroprotective properties through multiple mechanisms, such as enhancing the gastric mucosal barrier, inhibiting acid secretion, displaying antioxidant and anti-inflammatory effects, promoting ulcer healing, and combating Helicobacter pylori infection. The evidence presented includes in vitro assays, animal models, and some clinical studies. While many of the 53 plants reviewed demonstrated significant anti-ulcer effects compared to standard drugs, further clinical research is needed to establish efficacy and safety in humans. The synergistic actions of phytochemical mixtures in medicinal plant extracts likely contribute to their therapeutic potential. This review highlights the role these North African medicinal plants may play in the prevention and treatment of peptic ulcers and identifies promising candidates for further research and development of evidence-based botanical therapies., Competing Interests: The authors declare no conflicts of interest., (© 2024 The Author(s). Food Science & Nutrition published by Wiley Periodicals LLC.)

Juncus maritimusan extremophilous microorganism speciesknown for its medicinal properties was collected in the Biskra region with the aim of its valorization. The volume size of polyphenols, flavonoids and condensed tannins was performed using the Folin-Ciocalteu method, aluminum trichloride and vanillin respectively. The volume of Polyphenols was 127.73±0.20 μg EAG/mg ES, the volume offlavonoids was 16.42±0.42 μg EQ/mg ES, and the volume ofcondensed tannins was 10.10±0.35 μg EC/mg ES. The results of the antioxidant activity tests using the DPPH and ABTS methods reveal that the ethyl acetate extract had the highest activity in both tests. The results of the in vitro anti-inflammatory activity, using the BSA protein denaturation assay, showed that the percentage of denaturation inhibition wasproportional to the concentration of the extract. At a concentration of 5 mg/mL, the inhibition percentage of the extract were 82.03 % and 80.23 %, respectively,which wereclose tothose of theanti-inflammatory drug Diclofenac.Furthermore, molecular docking simulations indicated that Berberine has high binding affinity to the targets COX-2 and PLA-2 In fact,bioisosteric replacement is being usedto discover new analogs of Berberine. Finally, ADME-Tox predictions demonstrated that this compound and its analogs were not hepatotoxic. This result may lead to the selection ofBerberine and its analogs as active compounds with anti-inflammatory and antioxidant effects., (© 2024 Wiley-VHCA AG, Zurich, Switzerland.)

2-(( E )-((4-((( E )-4-Nitrobenzylidene)amino)phenyl)imino)methyl)naphthalen-1-ol, was synthesised followed by metalation with Fe(III), Co(III), Cu(II), Zn(II) and Ni(II) metals. The compounds were characterised by different methods CHN, AAS, IR, NMR, XRD, TGA and UV-Vis. The results reveal that the ligand has bidentate behavior, and it is bound with metals by a coordination bond through both the nitrogen atom of the azomethine group and the oxygen atom, this provided an octahedral geometry. The X-ray diffraction of the compounds indicate that the ligands and complexes of Co(III), Fe(III) and Zn(II) have a crystalline nature, whereas the Ni(II) and Cu(II) have an amorphous structure. The agar diffusion method (hole plate) was used to evaluate the ligand's and its complexes' antibacterial and antifungal effects on Salmonella enterica serovar typhi and Candida albicans , respectively. It was observed that the Fe(III) complex had the best activity among the compounds against microbial strains. Cytotoxicity of new metal complexes was also assessed against A549, HepG-2 and PC-3 cancer cells. Results demonstrated that the Cu(II) complex displayed the preeminent activity among the synthesised compounds against all the tested cell lines. Furthermore, molecular docking simulation revealed that the Fe(III) complex is shown to have a high affinity with the active sites of two targets of microbial strains. Also, the Cu(II) complex shown to has a high affinity with the active sites of three targets of A-549, HepG-2 and PC-3 cancer cells, which was confirmed by the formation of the different modes of interaction.Communicated by Ramaswamy H. Sarma.

In this paper, a data set of [ 3 H] diazepam derivatives was analyzed using various computational methods: molecular docking/dynamic simulations, and QSAR analysis. The main aims of these studies are to understand the binding mechanisms by which benzodiazepines allosterically modulate GABA A receptor α 1 β 2 γ 2 subtypes, from inducing neuronal inhibition at lower doses to the anesthetic effect at higher doses, and also, to define the structural requirements that contribute to improving the response of GABA A /α 1 β 2 γ 2 receptor to benzodiazepine drugs. The results of the molecular docking study allowed selecting Ro12-6377 and proflazepam as the best modulators for the four binding sites simultaneously. Subsequently, the stability of the selected complexes was investigated by performing molecular dynamics simulation. The latter confirmed the features of both modulators to exert direct effects on the chloride-channel lining residues. Pharmacokinetics and drug-likeness profile were assessed through in silico tool. Furthermore, a QSAR analysis was conducted using an improved vemolecular dynamics simulations proposed byrsion of PLS regression. The goodness of fit and the predictive power of the resulting PLS model were estimated according to internal and external validation parameters: R 2  = 0.632, R 2 adj  = 0.584, F  = 0.813. Clearly, the obtained results ensure the predictive ability of the developed QSAR model for the design of new high-potency benzodiazepine drugs.p- value = 6.2050e - 07, Q 2 loo  = 0.639, and Q 2 F3  = 0.813. Clearly, the obtained results ensure the predictive ability of the developed QSAR model for the design of new high-potency benzodiazepine drugs., Supplementary Information: The online version contains supplementary material available at 10.1007/s11224-022-02029-4., Competing Interests: Conflict of interestThe authors declare no competing interests., (© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022, Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)

Multiphase machines have recently been promoted as a viable alternative to traditional three-phase machines. Most experts are looking for strategies to estimate the rotation speed of such complex systems, since speed data are required for high-performance control purposes. Traditionally, electromechanical sensors were used to detect the rotor speed of electric motors. These devices are extremely accurate, but they are also delicate and costly to deploy. New speed estimating algorithms must be created for these situations. This paper looks at how to estimate rotor speed in symmetrical six-phase induction motors (IMs) using a novel strategy for rotor speed estimation based on the Short Time Fourier Transform (STFT) method. The technique is based on tracking the frequencies of the rotor slot harmonics (RSH) seen in most squirrel-cage IM stator currents, thus assuring a broad range of applications. To monitor the RSH, the STFT employs a sliding window to perform the discrete Fourier transform technique, making it more suitable for online use with noisy and nonstationary signals. Experimental tests demonstrate the effectiveness of the suggested approach.

Limitations of Available Literature: Nowadays, coronavirus disease 2019 (COVID-19) is the world-wide pandemic due to its mutation over time. Several works done for covid-19 detection using different techniques however, the use of small datasets and the lack of validation tests still limit their works. Also, they depend only on the increasing the accuracy and the precision of the model without giving attention to their complexity which is one of the main conditions in the healthcare application. Moreover, the majority of healthcare applications with cloud computing use centralization transmission process of various and vast volumes of information what make the privacy and security of personal patient's data easy for hacking. Furthermore, the traditional architecture of the cloud showed many weaknesses such as the latency and the low persistent performance., Method Proposed by the Author With Technical Information: In our system, we used Discrete Wavelet transform (DWT) and Principal Component Analysis (PCA) and different energy tracking methods such as Teager Kaiser Energy Operator (TKEO), Shannon Wavelet Entropy Energy (SWEE), Log Energy Entropy (LEE) for preprocessing the dataset. For the first step, DWT used to decompose the image into coefficients where each coefficient is vector of features. Then, we apply PCA for reduction the dimension by choosing the most essential features in features map. Moreover, we used TKEO, SHEE, LEE to track the energy in the features in order to select the best and the most optimal features to reduce the complexity of the model. Also, we used CNN model that contains convolution and pooling layers due to its efficacity in image processing. Furthermore, we depend on deep neurons using small kernel windows which provide better features learning and minimize the model's complexity.The used DWT-PCA technique with TKEO filtering technique showed great results in terms of noise measure where the Peak Signal-to-Noise Ratio (PSNR) was 3.14 dB and the Signal-to-Noise Ratio (SNR) of original and preprocessed image was 1.48, 1.47 respectively which guaranteed the performance of the filtering techniques.The experimental results of the CNN model ensure the high performance of the proposed system in classifying the covid-19, pneumonia and normal cases with 97% of accuracy, 100% of precession, 97% of recall, 99% of F1-score, and 98% of AUC., Advantages and Application of Proposed Method: The use of DWT-PCA and TKEO optimize the selection of the optimal features and reduce the complexity of the model.The proposed system achieves good results in identifying covid-19, pneumonia and normal cases.The implementation of fog computing as an intermediate layer to solve the latency problem and computational cost which improve the Quality of Service (QoS) of the cloud.Fog computing ensure the privacy and security of the patients' data.With further refinement and validation, the IFC-Covid system will be real-time and effective application for covid-19 detection, which is user friendly and costless., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2022 Elsevier Ltd. All rights reserved.)

Lobularia libyca ( L. libyca ) is a traditional plant that is popular for its richness in phenolic compounds and flavonoids. The aim of this study was to comprehensively investigate the phytochemical profile by liquid chromatography, electrospray ionization and tandem mass spectrometry (LC-ESI-MS), the mineral contents and the biological properties of L. libyca methanol extract. L. libyca contains significant amounts of phenolic compounds and flavonoids. Thirteen compounds classified as flavonoids were identified. L. libyca is rich in nutrients such as Na, Fe and Ca. Moreover, the methanol extract of L. libyca showed significant antioxidant activity without cytotoxic activity on HCT116 cells (human colon cancer cell line) and HepG2 cells (human hepatoma), showing an inhibition zone of 13 mm in diameter. In silico studies showed that decanoic acid ethyl ester exhibited the best fit in β-lactamase and DNA gyrase active sites; meanwhile, oleic acid showed the best fit in reductase binding sites. Thus, it can be concluded that L. libyca can serve as a beneficial nutraceutical agent, owing to its significant antioxidant and antibacterial potential and due to its richness in iron, calcium and potassium, which are essential for maintaining a healthy lifestyle.

The purpose of this work is to evaluate the homology modeling, in silico prediction, and characterization of somatotropin and erythropoietin from Cyprinus carpio as well as molecular docking and simulation experiments between the modeled proteins and surfactants sodium dodecyl sulfate (SDS), sodium laureth sulfate (SLES) and cetylpyridinium chloride (CPC). Using the best fit template structure, homology modeling of somatotropin and erythropoietin of Cyprinus carpio respectively was conducted. The model structures were improved further with 3Drefine, and the final 3D structures were verified with PROCHEK, ERRATA and ProQ. The physiochemical, as well as the stereochemical parameters of the modeled proteins, were evaluated using ExPASy's ProtParam. Molecular docking calculations, protein-ligand interactions, and protein flexibility analysis were carried out to determine the binding pattern of each ligand to the targeted proteins and their effect on the overall proteins' conformation. Our in silico analysis showed that hydrophobic interactions with the active site amino acid residues of the modeled proteins (somatotropin and erythropoietin) were more prevalent than hydrogen bonds and salt bridges that affect the flexibility and stability of the somatotropin and erythropoietin as revealed from our protein flexibility analysis. The in vivo analysis showed that sublethal concentrations of SDS, SLES, and CPC negatively affected the growth and hematological parameters of Cyprinus carpio . Hence, it may be inferred from the study that the alterations in the flexibility of somatotropin and erythropoietin of Cyprinus carpio upon addition of SDS, CPC and SLES might be attributable to the reduction in growth and hematological parameters.