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Neuropathic pain arises from impairments or malfunctions within the nervous system, resulting in atypical transmission and interpretation of pain signals. In the present study, we examined the neuroprotective effects of agomelatine (AGM) and agomelatine‐loaded nanostructured lipid carriers (AGM‐NLCs) in neuropathic animal models induced by chronic constriction injury (CCI) of the sciatic nerve. Male Sprague Dawley rats were divided into seven experimental groups to compare the effects of AGM and AGM‐NLCs, which were administered at 20 mg/kg for 14 consecutive days after CCI. Our finding demonstrated that CCI triggered the onset of analgesia in these animals, corroborated by mechanical allodynia and thermal hyperalgesia. Furthermore, CCI induced an elevation in inflammatory mediators such as interleukin (IL)‐1β and inducible nitric oxide synthase (iNOS), and downregulated heme oxygenase‐1 (HO‐1) and nuclear factor E2‐related factor (Nrf2). Treatment with AGM and AGM‐NLCs reversed inflammatory cascades and elevated antioxidant enzyme levels, leading to a reduction in paw withdrawal latency and threshold in rats. To further investigate the effect of AGM and AGM‐NLCs, all‐trans retinoic acid (ATRA) was administered, which antagonizes Nrf2. ATRA substantially downregulated Nrf2 expression and exacerbated thermal hyperalgesia, whereas Nrf2 and HO‐1 expressions were significantly upregulated after AGM‐NLCs administration. Overall, the results demonstrated that AGM‐NLCs offer promising antinociceptive and anti‐inflammatory properties in alleviating neuropathic pain symptoms, which can be attributed to improved drug delivery and therapeutic outcomes compared with AGM alone. [ABSTRACT FROM AUTHOR]

Objective: Cissampelos pareira Linn. (Menispermaceae) has been reported for improving memory and cognitive behavior, and also as a folk remedy, for various neurodegenerative disorders. We investigated Cissampelos pareira for evaluating its neuroprotective effect on rodent model of focal cerebral ischemia. Methods: Male Sprague–Dawley rats (270-300 g) were subjected to permanent middle cerebral artery occlusion (MCAO). The animals were divided into five groups as control, MCAO, and MCAO + Cissampelos pareira (n -hexane, ethyl acetate (EtOAc), and methanol (MeOH) extracts; 50 mg/kg; n = 14). The expression of various inflammatory factors and enzymes including cyclooxygenase (COX-2), c-Jun N-terminal Kinase (p-JNK), and nuclear factor kappa-light-chain-enhancer of activated B cells (p-NF-κB) was detected in response to disease and extracts by immunohistochemistry and enzyme-linked immunosorbent assay. Results: The n -hexane extract (LD50 > 5.0 g/kg) reduced the infarction area significantly from in n -hexane extract + MCAO group, reversed neuronal death (P <.01), and relieved the neurobehavioral deficits. The reduced levels of antioxidant enzymes (GST, GSH, CAT, SOD, and GPx), in case of MCAO were significantly elevated in response to n-hexane extract. 1,2-benzenedicarboxylic acid was detected (through gas chromatography/mass spectrometry) as the major component in n -hexane extract. Conclusion: n -hexane extract has the potential to be of therapeutic value in stroke patients, and thus further studies are warranted to elucidate the neuroprotective effects of this extract. [ABSTRACT FROM AUTHOR]

The detection of rice leaf disease is significant because, as an agricultural and rice exporter country, Pakistan needs to advance in production and lower the risk of diseases. In this rapid globalization era, information technology has increased. A sensing system is mandatory to detect rice diseases using Artificial Intelligence (AI). It is being adopted in all medical and plant sciences fields to access and measure the accuracy of results and detection while lowering the risk of diseases. Deep Neural Network (DNN) is a novel technique that will help detect disease present on a rice leave because DNN is also considered a state-of-the-art solution in image detection using sensing nodes. Further in this paper, the adoption of the mixed-method approach Deep Convolutional Neural Network (Deep CNN) has assisted the research in increasing the effectiveness of the proposed method. Deep CNN is used for image recognition and is a class of deep-learning neural networks. CNN is popular and mostly used in the field of image recognition. A dataset of images with three main leaf diseases is selected for training and testing the proposed model. After the image acquisition and preprocessing process, the DeepCNNmodel was trained to detect and classify three rice diseases (Brown spot, bacterial blight, and blast disease). The proposed model achieved 98.3% accuracy in comparison with similar state-of-the-art techniques. [ABSTRACT FROM AUTHOR]

Substances such as tobacco and cannabis can negatively modulate seminal parameters and sex hormones and lead to fertility problems in males. The present study aimed to determine the effect of cigarettes, dipping tobacco, and cannabis on semen parameters and sex hormones in infertile males. A total of 160 infertile healthy participants (cigarette smokers n = 40, dipping tobacco users n = 40, cannabis users n = 40 and infertile controls n = 40) were included in the study. Fasting blood samples were collected from all the participants using the aseptic technique, and semen samples were collected by masturbation following sexual abstinence of 2–7 days. The levels of serum testosterone, follicle-stimulating hormone (FSH), and luteinizing hormone (LH) were determined using ELISA. The serum level of FSH was significantly higher in cannabis users relative to the control group (p = 0.043). A mild non-significant decrease in sperm count, serum LH and testosterone levels were observed in all drug users compared to controls. In conclusion, chronic use of tobacco and cannabis mildly modulates semen and hormonal parameters in infertile males. [ABSTRACT FROM AUTHOR]