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Abstract Background Intracranial arterial aneurysms in the paediatric age group constitute less than 5% of all aneurysms. The most common form is spontaneous dissecting aneurysms (SDAs) (Peron et al. in Acta Neurochir 152(9):1511–1517, 2010; Huang et al. in Surg Neurol 63(5):424–432, 2005; Krishna et al. in Acta Neurochir 147(5):469–476, 2005; Ihn and Jung in J Korean Soc Radiol 65(5):441–445, 2011). It occurs most commonly in the posterior circulation and rarely in the anterior circulation, including the middle cerebral artery (MCA) (Chuang et al. in Asian J Surg 35(1):42–48, 2012; Ozaki et al. in World Neurosurg 113:208–211, 2018). MCA dissecting aneurysm even rarely presents with intracerebral haemorrhage (Ete et al. in J Case Rep 3(2):451–454, 2013; Ahmad in Interdiscip Neurosurg 18:100510, 2019; Bartoš et al. in Brain Sci 11(1):29, 2020). Case description A 12 years old non-diabetic, non-hypertensive female presented with distal right MCA (M2-M3 junction) dissecting aneurysm with right parieto-temporal haemorrhage. The patient was well managed with endovascular coil embolization with a good functional outcome. Conclusion Endovascular coil embolization had favourable clinical and angiographic outcomes in distal MCA dissecting aneurysms.

Abstract Background We needs to study Primary Large cell Non-Hodgkin’s Lymphoma of the cranial vault, which is rare, and its association with COVID19 has not been reported, which may have an immunosuppressive effect to aggravate its progression. Patient details Our patient, a 53-year-old male, noticed fast growth of posterior cranial vault lesion from 2 to 10 cm size in last 6 months after COVID 19 affliction. MRI brain with contrast revealed lesions suggesting meningioma. The whole-body PET scan was normal. Following Subtotal excision of the mass, histopathology revealed large B-cell Non-Hodgkin’s lymphoma (DLBCL). Immunohistochemistry showed positive results for CD10, CD20, CD45 (LCA), ALK, and BCL-VE with a Ki-67 index of 90–95%. Following radiotherapy and chemotherapy patient is disease-free on imaging and doing well at 5 months of follow-up. Conclusions Early intervention with excisional biopsy and timely chemo and radiotherapy in favorable immunostaining may add survival benefits even in malignant features induced by immunosuppressing diseases such as COVID19 in diffuse large B-cell lymphoma (DLBCL) of the scalp.

In General, the 5G is a fifth-generation technology that works at speeds of 4G to 100 times the network speed. The main objective of introducing modern information technologies is to facilitate and facilitate access to public services. The use of new technologies is a key factor in improving the overall structure of public administration and increasing its efficiency. In addition, it is important to improve the infrastructure of all types of communications. The telecom operators are often willing to invest more in infrastructure development. In this paper, a new model was proposed to enhance the bandwidth allocation and utilization. It is a requirements-based network that allows the users to increase the speed of wireless networks. This proposed method also increases the amount of data that can be transmitted over wireless networks.

In general, an antenna is an interface that transmits signal data and receives incoming signal data. The radio waves received through this interface help to do the necessary things for the transmitter and receiver circuit systems used there. Also a radio transmitter antenna transmits different waves generated from the current generated at its tip to different areas. In this paper, the functions of increasing its bandwidth by making changes in some dimensions of the antenna are proposed. The oscillating current used in its transmitter area increases its vibration waves. This increases the amount of airwaves generated there and the number of data transmitted through it. So its bandwidth is more likely to be high. Furthermore these functions generate varying magnetic fields so that the time taken by the cross-sectional magnetic fields of the antenna varies.

Introduction: Cardiac strain has become a prevalent cause of firefighters’ death. Standards and regulations set forth a framework to monitor the cardiovascular fitness of firefighters, encourage fitness and create a pathway to diagnosis or detection of disorders. The effectiveness of these standards relies on continuous evaluation of firefighters’ health and updating the protocols. Methods: This study intended to assess the physiological response of 172 firefighters in the middle east for the first time and considered the effect of body mass index, age, gender, and seasonal ambient temperature on their responses before and after a fire and rescue training. The end results should compile the behavioral patterns of firefighters from the region and help authorities to update current health monitoring standards for firefighters accordingly. Blood pressure, heart and respiratory rates were sampled for participants after one minute after when training finished. Non-Parametric statistical analysis was conducted using Nonparametric Spearman rank correlation coefficients and Kruskal-Wallis H- test to evaluate the correlation of age, gender, BMI, and seasonal temperature with participant’s physiological response. Results: This study found obesity in 20% of the sampled population with more cases among male participants. Also, in this study, the hypertension prevalence ratio found as 19.8% at baseline and 26.7% in post-training measurements. Conclusion: This study could confirm that body mass index and seasonal ambient temperature affect blood pressure, heart and ventilation rates. Heart rate significantly changes with ambient temperature. Also, the results found the gender of participants affects all physiological responses, especially heart rate.

Most instances of Alzheimer’s disease (AD) are sporadic or not associated with a particular mutation. Here, the authors develop knock-in mice that express wildtype human Aβ under control of the mouse App locus, which may have potential for modelling some aspects of sporadic late onset AD.

Abstract Previous studies showed that injection of tissue extracts containing amyloid-β (Aβ) aggregates accelerate amyloid deposition in the brain of mouse models of Alzheimer’s disease (AD) through prion-like mechanisms. In this study, we evaluated whether brain amyloidosis could be accelerated by blood infusions, procedures that have been shown to transmit prion diseases in animals and humans. Young transgenic mice infused with whole blood or plasma from old animals with extensive Aβ deposition in their brains developed significantly higher levels brain amyloidosis and neuroinflammation compared to untreated animals or mice infused with wild type blood. Similarly, intra-venous injection of purified Aβ aggregates accelerated amyloid pathology, supporting the concept that Aβ seeds present in blood can reach the brain to promote neuropathological alterations in the brain of treated animals. However, an amyloid-enhancing effect of other factors present in the blood of donors cannot be discarded. Our results may help to understand the role of peripheral (amyloid-dependent or -independent) factors implicated in the development of AD and uncover new strategies for disease intervention.

Alzheimer’s disease (AD) is the most common type of dementia in the elderly population. The disease is characterized by progressive memory loss, cerebral atrophy, extensive neuronal loss, synaptic alterations, brain inflammation, extracellular accumulation of amyloid-β (Aβ) plaques, and intracellular accumulation of hyper-phosphorylated tau (p-tau) protein. Many recent clinical trials have failed to show therapeutic benefit, likely because at the time in which patients exhibit clinical symptoms the brain is irreversibly damaged. In recent years, induced pluripotent stem cells (iPSCs) have been suggested as a promising cell therapy to recover brain functionality in neurodegenerative diseases such as AD. To evaluate the potential benefits of iPSCs on AD progression, we stereotaxically injected mouse iPSC-derived neural precursors (iPSC-NPCs) into the hippocampus of aged triple transgenic (3xTg-AD) mice harboring extensive pathological abnormalities typical of AD. Interestingly, iPSC-NPCs transplanted mice showed improved memory, synaptic plasticity, and reduced AD brain pathology, including a reduction of amyloid and tangles deposits. Our findings suggest that iPSC-NPCs might be a useful therapy that could produce benefit at the advanced clinical and pathological stages of AD.

Alzheimer's disease (AD) diagnosis is hampered by the lack of early, sensitive, and objective laboratory tests. We describe a sensitive method for biochemical diagnosis of AD based on specific detection of misfolded Aβ oligomers, which play a central role in AD pathogenesis. The protein misfolding cyclic amplification assay (Aβ-PMCA), exploits the functional property of Aβ oligomers to seed the polymerization of monomeric Aβ. Aβ-PMCA allowed detection of as little as 3 fmol of Aβ oligomers. Most importantly, using cerebrospinal fluid, we were able to distinguish AD patients from control individuals affected by a variety of other neurodegenerative disorders or nondegenerative neurological diseases with overall sensitivity of 90% and specificity of 92%. These findings provide the proof-of-principle basis for developing a highly sensitive and specific biochemical test for AD diagnosis.

Bacterial quorum sensing (QS) is a density dependent communication system that regulates the expression of certain genes including production of virulence factors in many pathogens. Bioactive plant extract/compounds inhibiting QS regulated gene expression may be a potential candidate as antipathogenic drug. In this study anti-QS activity of peppermint (Mentha piperita) oil was first tested using the Chromobacterium violaceum CVO26 biosensor. Further, the findings of the present investigation revealed that peppermint oil at sub-MICs strongly interfered with acyl homoserine lactone (AHL) regulated virulence factors and biofilm formation in Pseudomonas aeruginosa and Aeromonas hydrophila. The result of molecular docking analysis attributed the quorum sensing inhibitory activity exhibited by peppermint oil to menthol. Assessment of ability of menthol to interfere with quorum sensing systems of various Gram-negative pathogens comprising diverse AHL molecules revealed that it reduced the AHL dependent production of violacein, virulence factors and biofilm formation indicating broad-spectrum anti-QS activity. Using two E. coli biosensors, MG4/pKDT17 and pEAL08-2, we also confirmed that menthol inhibited both the las and pqs quorum sensing systems. Further, findings of the in vivo studies with menthol on nematode model Caenorhabditis elegans showed significantly enhanced survival of the nematode. Our data identified menthol as a novel broad spectrum quorum sensing inhibitor.

In India, cotton holds a significant position as a key cash crop. Despite its economic importance, cotton crops are subject to a variety of illnesses that can reduce output and quality. Early detection of these diseases is crucial for minimizing damage and preserving the crop. Cotton is vulnerable to diverse ailments, includes powdery mildew, leaf curl, bacterial blight, target spot, leaf spot, and nutrient deficits. To put effective mitigation methods into place, it is imperative that one correctly recognizes these illnesses. The prevalence of cotton leaf diseases poses a substantial challenge for Indian farmers. This paper proposes the application of machine learning, specifically Convolutional Neural Networks (CNN), for disease detection as a promising solution. Leveraging technology for disease identification can empower farmers to take prompt actions, mitigating the risk of significant crop losses. Machine learning, with its demonstrated success in various domains, including agriculture, offers valuable tools for disease detection and classification. CNNs, known for their proficiency in image-related tasks, can learn to recognize disease-specific patterns in plant leaves. This paper contributes by conducting a comprehensive review of prior research on crop disease detection and introducing an innovative approach that makes use of artificial intelligence techniques to detect illnesses in cotton leaves. [ABSTRACT FROM AUTHOR]

The Indus River dolphin (Platanista minor) is a severely threatened species of freshwater dolphin that occurs only in the lower Indus River system of Pakistan and India. The dolphin's range has declined by 80% since the 1870s, and total species abundance is estimated as approximately 2000 individuals.In 2007, a remnant population of Indus dolphins was discovered above Harike Barrage, in the Beas River in India, 600 km away from all other individuals of its species. This paper provides an overview of the conservation status of Indus dolphins in the Beas River, details the threats they face, and suggests priorities for their conservation and management.Between 2011 and 2022, 40 dolphin direct count surveys were conducted. Indus dolphins occur only in the lower third of the Beas River and reported counts have been from one to eight individuals. The data do not indicate an increase in abundance, and instead suggest a potential decrease; however, sightings of calves continue to be reported annually indicating reproduction is still taking place.Threats to the Beas River dolphin population include accidental entanglement in fishing gear, pollution, escapement downstream of Harike barrage, altered and depleted river flow regimes' and the effects of a very small population size. Urgent conservation measures are essential if this small, but important satellite population is to persist.Recommended management actions include the complete removal of fishing nets from dolphin habitat, reducing pollution, ensuring adequate river discharge to sustain aquatic ecology including dolphins, evaluating and monitoring dolphin movement through Harike barrage and into canals, and engaging riverside communities to protect dolphins. In addition, the possibility of conservation translocations to supplement this population with individuals from larger healthy populations elsewhere in the range of the species should be explored. [ABSTRACT FROM AUTHOR]

In the contemporary world, energy stands as an essential driving force behind socio-economic development. However, with the alarming levels of environmental pollution, there has been a growing focus on renewable energy sources. These sustainable alternatives are gaining increasing attention, particularly as the depletion of fossil fuels becomes more ap-parent. Natural components such as sunlight, wind, and rainfall are used to generate renewable energy. Among these non-traditional renewable sources, solar energy emerges as a prominent contender for power generation. Solar power generation has gained recognition as a promising and environmentally sustain-able renewable energy source to meet growing global energy demands while minimizing cli-mate change consequences. This paper extensively examines solar power generation techniques, encompassing Photovoltaic (PV) Systems and Solar Thermal Technologies. The paper explores the present state of solar power generation technology, outlines its advantages, and researches the various challenges obstructing its widespread adoption. Furthermore, the study offers insights into potential solutions and outlines future directions for advancing solar power generation techniques. [ABSTRACT FROM AUTHOR]

Digital images are more important in numerous contemporary applications, and the need for images in the technical field is also increasing drastically. It is used to recognize signatures and faces in many industries and is applicable for intelligent departments. The images are usually associated with the noise content; this may happen due to the instrument imperfections, troubleshooting while collecting data from the acquisition process, and another natural phenomenon. Poisson noise, also known as photon noise, is caused in the images due to the statistical essence of electromagnetic waves. X‐ray, visible light, and gamma rays are electromagnetic waves. The enhancement of the convolution model in addressing images is challenging due to the various constituents such as optical aberrations, noise level, and optical setup. The modeling configuration of the image is attained using the point spread function (PSF), which is responsible for the system's impulse response. The quality image is retrieved by denoising and super‐resolution (SR) methods; these methods simultaneously eliminate the noise content from the images. A Richardson–Lucy and alternating direction method of multipliers type of non‐blind iterative algorithmic approaches associated with the PSF performance in addressing image is comparatively analyzed. The deep learning approach, convolutional neural networks (CNNs), is also employed to understand the nonlinear mapping relationship between the observed data and ground reality. The performance of the various network approaches is compared in this article. The result obtained shows that the deep learning CNNs achieved higher accuracy in producing denoising images. The goal of the proposed system model is to remove the interference noise in images. The high‐resolution images are obtained by implementing a SR‐based CNN model. [ABSTRACT FROM AUTHOR]