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BackgroundIncreasing evidence indicates that neuroinflammation is a critical factor contributing to the progression of various neurodegenerative diseases. The IKK/NF-κB signalling system is a central regulator of inflammation, but it also affects neuronal survival and differentiation. A complex interplay between different CNS resident cells and infiltrating immune cells, which produce and respond to various inflammatory mediators, determines whether neuroinflammation is beneficial or detrimental. The IKK/NF-κB system is involved in both production of and responses to these mediators, although the precise contribution depends on the cell type as well as the cellular context, and is only partially understood. Here we investigated the specific contribution of neuronal IKK/NF-κB signalling on the regulation of neuroinflammatory processes and its consequences. To address this issue, we established and analysed a conditional gain-of-function mouse model that expresses a constitutively active allele of IKK2 in principal forebrain neurons (IKK2nCA). Proinflammatory gene and growth factor expression, histopathology, microgliosis, astrogliosis, immune cell infiltration and spatial learning were assessed at different timepoints after persistent canonical IKK2/NF-κB activation.ResultsIn contrast to other cell types and organ systems, chronic IKK2/NF-κB signalling in forebrain neurons of adult IKK2nCA animals did not cause a full-blown inflammatory response including infiltration of immune cells. Instead, we found a selective inflammatory response in the dentate gyrus characterized by astrogliosis, microgliosis and Tnf-α upregulation. Furthermore, downregulation of the neurotrophic factor Bdnf correlated with a selective and progressive atrophy of the dentate gyrus and a decline in hippocampus-dependent spatial learning. Neuronal degeneration was associated with increased Fluoro-jade staining, but lacked activation of apoptosis. Remarkably, neuronal loss could be partially reversed when chronic IKK2/NF-κB signalling was turned off and Bdnf expression was restored.ConclusionOur results demonstrate that persistent IKK2/NF-κB signalling in forebrain neurons does not induce overall neuroinflammation, but elicits a selective inflammatory response in the dentate gyrus accompanied by decreased neuronal survival and impaired learning and memory. Our findings further suggest that chronic activation of neuronal IKK2/NF-κB signalling, possibly as a consequence of neuroinflammatory conditions, is able to induce apoptosis-independent neurodegeneration via paracrine suppression of Bdnf synthesis.

The purpose of this work is to provide an effective social distance monitoring solution in low light environments in a pandemic situation. The raging coronavirus disease 2019 (COVID-19) caused by the SARS-CoV-2 virus has brought a global crisis with its deadly spread all over the world. In the absence of an effective treatment and vaccine the efforts to control this pandemic strictly rely on personal preventive actions, e.g., handwashing, face mask usage, environmental cleaning, and most importantly on social distancing which is the only expedient approach to cope with this situation. Low light environments can become a problem in the spread of disease because of people’s night gatherings. Especially, in summers when the global temperature is at its peak, the situation can become more critical. Mostly, in cities where people have congested homes and no proper air cross-system is available. So, they find ways to get out of their homes with their families during the night to take fresh air. In such a situation, it is necessary to take effective measures to monitor the safety distance criteria to avoid more positive cases and to control the death toll. In this paper, a deep learning-based solution is proposed for the above-stated problem. The proposed framework utilizes the you only look once v4 (YOLO v4) model for real-time object detection and the social distance measuring approach is introduced with a single motionless time of flight (ToF) camera. The risk factor is indicated based on the calculated distance and safety distance violations are highlighted. Experimental results show that the proposed model exhibits good performance with 97.84% mean average precision (mAP) score and the observed mean absolute error (MAE) between actual and measured social distance values is 1.01 cm.

Abstract Fish is consumed as a rich and cheaper source of white meat and proteins all over the world. Fish farming is the leading source of income generation throughout the world. The present research study was conducted with aims to investigate the ecto and endo parasitic fauna of S. plagiostomus (snow trout) in River Swat. A total of 96 fish samples were collected on monthly basis from July-2018 to February-2019, from upper, middle and lower reaches. Fish samples were collected with the help of cast net, hand net and fishing rods. Local fishermen and experts help were also sought out for fish collection. 61 out of 96 fishes were found infected by helminth parasites. The total prevalence and intensity of 63.54% and 2.90 was observed respectively during data analysis. Highest monthly prevalence of 83.33% was recorded during July and August, while lowest prevalence of 33.33% was noted during February. Five species of helminths parasites were detected from S. plagiostomus, of which two were trematodes (Rhabdochona shizothoracis and Rhabdochona species), one species of Monogenia (Diplozoon paraddoxum), one species of Cestodes (Nippotaenia species), and one species of Acanthocephalan (Neoechynorhynchus devdevi). Highest parasite wise prevalence, intensity and relative density of 21.87%, 4.09 and 0.895 was noted for R. schizothoracis while the lowest prevalence, intensity and relative density of 4.16%, 1.25 and 0.052 was noted for N. devdevi. Highest infection of 76.08% was observed in adults host while lowest, 40% infestation rate was observed in young fish samples. 73.68% prevalence was observed in female hosts while only 56.90% prevalence was observed in male individuals. Higher infection (83.33%) was noticed during summer season, while lowest infection (44.44%) was observed during winter season. Similarly 71.79% fishes were found infected that were collected from lower reaches of the River Swat than the fish samples collected from upper reaches (52%).

Abstract Fish provides main source of high quality protein to more than one billion people in the world. Fish parasites directly affect the productivity of fish and indirectly on human health. This research was aimed to assess the helminth parasites in Schizothorax plagiostomus (the snow trout) from river Panjkora, KP, Pakistan. A total of 88 fish samples (n= 88) were collected from the upper, middle and lower regions of the river through cast nets, hand nets and hooks. All the collected fish samples were examined in the Parasitology Laboratory, Department of Zoology, University of Malakand for helminth parasites during July 2018 to February 2019.Among these fishes nematodes, trematodes, cestodes and acanthocephalan were isolated and identified. Overall prevalence of the fish parasites was 60.22% (53/88). The intensity of the parasite was observed from 1.7% to 4.61%. Highest prevalence was reported in summer season 86.36% while lowest in the winter season 36.36%. This study shows that summer season affects the fish business and result in poor quality fish meat with risk of zoonotic diseases. Adults were highly infected 82.25% while no infection was found in juvenile specimens. Female fish samples had higher prevalence 68.22% than males 48.22%. Fishes of the lower reaches had highest prevalence 60.22% than the upper reaches 40.0%. Fish samples with maximum length and weight were highly 76.92% infected than small sized fish with low body weight. Present study addresses that Rhabdochona schizothoracis in the intestine and Diplozoon paradoxum in gills of snow trout fish has a long term relationship and call as a natural infection in cyprinids and it is zoonotic threat to human.

One of the major challenges of nano-biotechnology is to engineer potent antimicrobial nanostructures (NS) with high biocompatibility. Keeping this in view, we have performed aqueous olive leaf extract mediated one pot facile synthesis of CuO-NS and CeO2-NS. Prepared NS were homogenous, less than 26 nm in size, and small crystallite units as revealed by scanning electron microscopy (SEM) and X-ray diffraction (XRD) analyses. Fourier transform infrared spectroscopy (FTIR) of CuO-NS and CeO2-NS showed typical Cu-O prints around 592–660 cm-1 and Ce-O bond vibrations at 453 cm-1. The successful capping of CuO-NS and CeO2-NS by compounds present in the plant extract was further validated by high performance liquid chromatography (HPLC) and thermal gravimetric analysis (TGA). Active phyto-chemicals from the leaf extract simultaneously acted as strong reducing as well as capping agent in the NS synthesis. NS engineered in the present study showed antibacterial potential at extremely low concentration against highly virulent multidrug-resistant (MDR) gram-negative strains (Escherichia coli, Enterobacter cloacae, Acinetobacter baumannii and Pseudomonas aeruginosa), alarmed by World Health Organization (WHO). Furthermore, CuO-NS and CeO2-NS did not show any cytotoxicity on HEK-293 cell lines and Brine shrimp larvae indicating that the NS green synthesized in the present study are biocompatible.

Breast cancer covers a large area of research because of its prevalence and high frequency all over the world. This study is based on drug discovery against breast cancer from a series of imidazole derivatives. A 3D-QSAR and activity atlas model was developed by exploring the dataset computationally, using the machine learning process of Flare. The dataset of compounds was divided into active and inactive compounds according to their biological and structural similarity with the reference drug. The obtained PLS regression model provided an acceptable r2 = 0.81 and q2 = 0.51. Protein-ligand interactions of active molecules were shown by molecular docking against six potential targets, namely, TTK, HER2, GR, NUDT5, MTHFS, and NQO2. Then, toxicity risk parameters were evaluated for hit compounds. Finally, after all these screening processes, compound C10 was recognized as the best-hit compound. This study identified a new inhibitor C10 against cancer and provided evidence-based knowledge to discover more analogs.