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The rise in consumption of energy-dense foods has resulted in the displacement of several essential dietary gaps, causing numerous long-lasting diseases, including obesity, stroke, hypertension, and several forms of cancer. Epidemiological studies encourage more fruit consumption to prevent these diseases. The defensive mechanisms provided by these fruits against illness are due to the existence of several antioxidants. Recent studies proved that (poly) phenolic compounds are ideally the core phytochemicals with both functional and health-promoting properties found in the plant's kingdom, and low intake could result in the risk of certain diseases. Phytonutrients are powerful antioxidants that can modify metabolic activation and detoxification of carcinogens. The ideal motive of this review is to provide an overview as well as illuminate the polyphenolic merits of fruits in general. Fruits have several merits, including weight maintenance, proper health development, and satiety. There are many analytical methods for determining and measuring the phenolic content of different products. Phenolic compounds are of nutritional interest since they aid in the retardation and inhibition of lipids by acting as scavengers that prevent and protect the proliferation of oxidative chains. Future studies are required to help identify the physiological metabolic activities as well as to improve human health., Competing Interests: The authors have declared no conflict of interest., (Copyright © 2020 Mohammed Sharif Swallah et al.)

Background: There is a crosstalk between endoplasmic reticulum stress (ERS) and autophagy, and autophagy could attenuate endoplasmic reticulum stress-mediated apoptosis. Ginkgo biloba leaf extract (GBE) exerts vascular protection functions. The purpose of the present study is to investigate the role of autophagy in diabetic atherosclerosis (AS) and the effect of GBE on autophagy and ERS., Methods: Network pharmacology was utilized to predict the targets and pathways of the active chemical compounds of Gingko biloba leaf to attenuate AS. ApoE -/- mice were rendered diabetic by intraperitoneal ingestion with streptozotocin combined with a high-fat diet. The diabetic mice were divided into five groups: model group, atorvastatin group, rapamycin group, and low- and high-dose GBE groups. Serum and tissue markers of autophagy or ERS markers, including the protein expression, were examined., Results: The mammalian target of rapamycin (mTOR) and NF- κ B signaling pathways were targeted by the active chemical compounds of GBE to attenuate AS predicted by network pharmacology. GBE reduced the plaque area/lumen area and the plaque lipid deposition area/intimal area and inhibited the expressions of CD68, MMP2, and MMP9. Rapamycin and GBE inhibited the expression of mTOR and SQSTM1/p62 which increased in the aorta of diabetic mice. In addition, GBE reduced the expression of ERS markers in diabetic mice. GBE reduced the serum lipid metabolism levels, blood glucose, and inflammatory cytokines., Conclusion: Impaired autophagy and overactive endoplasmic reticulum stress contributed to diabetic atherosclerosis. mTOR inhibitor rapamycin and GBE attenuated diabetic atherosclerosis by inhibiting ERS via restoration of autophagy through inhibition of mTOR.

The aim of our current research was to synthesize some transition metal complexes of Naproxen, determine their physical properties, and examine their relative stability under various conditions. Characterizations of these complexes were done by 1H-NMR, Differential Scanning Calorimetry (DSC), FT-IR, HPLC, and scanning electron microscope (SEM). Complexes were subjected to acidic, basic, and aqueous hydrolysis as well as oxidation, reduction, and thermal degradation. Also the reversed phase high-performance liquid chromatography (RP-HPLC) method of Naproxen outlined in USP was verified for the Naproxen-metal complexes, with respect to accuracy, precision, solution stability, robustness, and system suitability. The melting points of the complexes were higher than that of the parent drug molecule suggesting their thermal stability. In forced degradation study, complexes were found more stable than the Naproxen itself in all conditions: acidic, basic, oxidation, and reduction media. All the HPLC verification parameters were found within the acceptable value. Therefore, it can be concluded from the study that the metal complexes of Naproxen can be more stable drug entity and offer better efficacy and longer shelf life than the parent Naproxen.

Purpose. The present study was designed to investigate the antinociceptive, anxiolytic, CNS depressant, and hypoglycemic effects of the naproxen metal complexes. Methods. The antinociceptive activity was evaluated by acetic acid-induced writhing method and radiant heat tail-flick method while anxiolytic activity was evaluated by elevated plus maze model. The CNS depressant activity of naproxen metal complexes was assessed using phenobarbitone-induced sleeping time test and the hypoglycemic test was performed using oral glucose tolerance test. Results. Metal complexes significantly (P < 0.001) reduced the number of abdominal muscle contractions induced by 0.7% acetic acid solution in a dose dependent manner. At the dose of 25 mg/kg body weight p.o. copper, cobalt, and zinc complexes exhibited higher antinociceptive activity having 59.15%, 60.56%, and 57.75% of writhing inhibition, respectively, than the parent ligand naproxen (54.93%). In tail-flick test, at both doses of 25 and 50 mg/kg, the copper, cobalt, silver, and zinc complexes showed higher antinociceptive activity after 90 minutes than the parent drug naproxen. In elevated plus maze (EPM) model the cobalt and zinc complexes of naproxen showed significant anxiolytic effects in dose dependent manner, while the copper, cobalt, and zinc complexes showed significant CNS depressant and hypoglycemic activity. Conclusion. The present study demonstrated that copper, cobalt, and zinc complexes possess higher antinociceptive, anxiolytic, CNS depressant, and hypoglycemic properties than the parent ligand.

The parasites of genera Haemoproteus, Plasmodium, and Leucocytozoon are well-known avian haematozoa and can cause declined productivity and high mortality in wild birds. The objective of the study was to record the prevalence of haematozoan parasites in a wide range of wetland birds in Bangladesh. Six species of Haemoproteus, seven species of Plasmodium, one unidentified species of Leucocytozoon, and one unidentified microfilaria of the genus Paronchocerca were found. Data on the morphology, size, hosts, prevalence, and infection intensity of the parasites are provided. The overall prevalence among the birds was 29.5% (95 out of 322 birds). Of those, 13.2% (42 of 319) of birds were infected with Haemoproteus spp., 15.1% with Plasmodium spp. (48 of 319) and 0.6% with Leucocytozoon spp. (2 of 319). Two birds were positive for both Haemoproteus sp. and Plasmodium sp. A single resident bird, Ardeola grayii, was found positive for an unidentified microfilaria. Prevalence of infection varied significantly among different bird families. Wild birds of Bangladesh carry several types of haematozoan parasites. Further investigation with a larger sample size is necessary to estimate more accurately the prevalence of haematozoan parasites among wild birds as well as domestic ducks for better understanding of the disease ecology.

Tumour detection, classification, and quantification in positron emission tomography (PET) imaging at early stage of disease are important issues for clinical diagnosis, assessment of response to treatment, and radiotherapy planning. Many techniques have been proposed for segmenting medical imaging data; however, some of the approaches have poor performance, large inaccuracy, and require substantial computation time for analysing large medical volumes. Artificial intelligence (AI) approaches can provide improved accuracy and save decent amount of time. Artificial neural networks (ANNs), as one of the best AI techniques, have the capability to classify and quantify precisely lesions and model the clinical evaluation for a specific problem. This paper presents a novel application of ANNs in the wavelet domain for PET volume segmentation. ANN performance evaluation using different training algorithms in both spatial and wavelet domains with a different number of neurons in the hidden layer is also presented. The best number of neurons in the hidden layer is determined according to the experimental results, which is also stated Levenberg-Marquardt backpropagation training algorithm as the best training approach for the proposed application. The proposed intelligent system results are compared with those obtained using conventional techniques including thresholding and clustering based approaches. Experimental and Monte Carlo simulated PET phantom data sets and clinical PET volumes of nonsmall cell lung cancer patients were utilised to validate the proposed algorithm which has demonstrated promising results.