Genome-wide analysis of HECT E3 ubiquitin ligase gene family in Solanum lycopersicum.

The E3 ubiquitin ligases have been known to intrigue many researchers to date, due to their heterogenicity and substrate mediation for ubiquitin transfer to the protein. HECT (Homologous to the E6-AP Carboxyl Terminus) E3 ligases are spatially and temporally regulated for substrate specificity, E2 ubiquitin-conjugating enzyme interaction, and chain specificity during ubiquitylation. However, the role of the HECT E3 ubiquitin ligase in plant development and stress responses was rarely explored. We have conducted an in-silico genome-wide analysis to identify and predict the structural and functional aspects of HECT E3 ligase members in tomato. Fourteen members of HECT E3 ligases were identified and analyzed for the physicochemical parameters, phylogenetic relations, structural organizations, tissue-specific gene expression patterns, and protein interaction networks. Our comprehensive analysis revealed the HECT domain conservation throughout the gene family, close evolutionary relationship with different plant species, and active involvement of HECT E3 ubiquitin ligases in tomato plant development and stress responses. We speculate an indispensable biological significance of the HECT gene family through extensive participation in several plant cellular and molecular pathways

Neural Network With Nlp

This thesis is about neural networks and how their algorithmic systems work. Neural networks are well-suited to aiding people with complex challenges in real-world situations. Thesis topics include nonlinear and complicated interactions between inputs and outputs, as well as making inferences, discovering hidden links, patterns, and predictions, and modeling highly volatile data and variations to forecast uncommon events. Neural networks have the potential to help people make better decisions. NLP is a technique for analyzing, interpreting, and comprehending large amounts of text. We can no longer evaluate the text using traditional approaches due to the massive volumes of text data and the exceedingly unstructured data source, which is where NLP comes in. As a result, the research focuses on what a neural network is and how different types of neural networks are used in natural language processing. NLP (natural language processing) is a method for analyzing, interpreting, and comprehending vast amounts of text. Due to the huge volumes of text data and the extremely unstructured data source, we can no longer analyze the text using standard approaches, which is where NLP comes in. As a result, the study concentrates on what a neural network is and how various types of neural networks are used in natural language processing. Due to their exceptional success in numerous NLP tasks, BERT in particular has gotten a lot of attention. Google\u27s Bidirectional Encoder Representations from Transformers (BERT) is a Transformer-based machine learning methodology for pre-training in natural language processing (NLP)

A rare case report of spontaneous frothy secretion from intact skin: Role of fungal allergic disease

Fungi are common aeroallergens which form a major part of bioaerosol. About 2-6% of the general population is allergic to fungi belonging to genera Aspergillus, Penicillium, Alternaria and Fusarium in developed countries. Here, we report a case series of 8 school going children of age 8 to 9 years who simultaneously reported with chief complaints of spontaneous mysterious white frothy secretion oozing from the surface of the intact skin while they were attending their classes. The role of fungal allergic reaction was suspected and skin secretions were sent for fungal as well as bacterial culture. Fungal culture done on air sampling plates was found positive for Aspergillus species. Cutaneous manifestations in the form of urticaria, angioedema have been reported in the previous literature, this case report shows a rare phenomenon of spontaneous oozing frothy white secretion which has not been reported in the literature so far

Machine Unlearning for Recommendation Systems: An Insight

This review explores machine unlearning (MUL) in recommendation systems, addressing adaptability, personalization, privacy, and bias challenges. Unlike traditional models, MUL dynamically adjusts system knowledge based on shifts in user preferences and ethical considerations. The paper critically examines MUL's basics, real-world applications, and challenges like algorithmic transparency. It sifts through literature, offering insights into how MUL could transform recommendations, discussing user trust, and suggesting paths for future research in responsible and user-focused artificial intelligence (AI). The document guides researchers through challenges involving the trade-off between personalization and privacy, encouraging contributions to meet practical demands for targeted data removal. Emphasizing MUL's role in secure and adaptive machine learning, the paper proposes ways to push its boundaries. The novelty of this paper lies in its exploration of the limitations of the methods, which highlights exciting prospects for advancing the field.Comment: In Proceedings of 7th INTERNATIONAL CONFERENCE ON INNOVATIVE COMPUTING AND COMMUNICATION 2024 (https://icicc-conf.com/

Discovering Salient Anatomical Landmarks by Predicting Human Gaze

Anatomical landmarks are a crucial prerequisite for many medical imaging tasks. Usually, the set of landmarks for a given task is predefined by experts. The landmark locations for a given image are then annotated manually or via machine learning methods trained on manual annotations. In this paper, in contrast, we present a method to automatically discover and localize anatomical landmarks in medical images. Specifically, we consider landmarks that attract the visual attention of humans, which we term visually salient landmarks. We illustrate the method for fetal neurosonographic images. First, full-length clinical fetal ultrasound scans are recorded with live sonographer gaze-tracking. Next, a convolutional neural network (CNN) is trained to predict the gaze point distribution (saliency map) of the sonographers on scan video frames. The CNN is then used to predict saliency maps of unseen fetal neurosonographic images, and the landmarks are extracted as the local maxima of these saliency maps. Finally, the landmarks are matched across images by clustering the landmark CNN features. We show that the discovered landmarks can be used within affine image registration, with average landmark alignment errors between 4.1% and 10.9% of the fetal head long axis length.Comment: Accepted at IEEE International Symposium on Biomedical Imaging 2020 (ISBI 2020

Ecofriendly Synthesis of DHPMs using Copper-based Nano catalysts and Evaluation of Antibacterial Activity

A new catalytic approach has been developed under microwave irradiation for the multicomponent reaction (MCR) of aromatic aldehydes, urea/thiourea and ethylacetoacetate to give corresponding dihydropyrimidinones (DHPMs) by using CuFe2O4/CuO-CeO2 nanoparticles (NPs) as heterogeneous and recyclable catalysts. 3, 4-Dihydropyrimidin-2(1H) ones/thiones are synthesized in higher yields (80-95 %) and short reaction time (8−10 minutes) at 245 Watts. It is applicable for both types of aromatic aldehydes containing EWS as well as EDS. Further, the synthesized compounds were evaluated for antibacterial activity against E. coli, B. subtilis, B. megaterium, and P. vulgaris. Among the compounds tested, ethyl-6-methyl-2-oxo-4-(4-chlorophenyl)-1,2,3,4-tetrahydropyrimidin-5-carboxylate, 4c showed response against B. subtilis, B. megaterium, and P. vulgaris and ethyl-6-methyl-2-oxo-4-(4-fluorophenyl)-1,2,3,4-tetrahydropyrimidin-5-carboxylate, 4h showed –ve response against E. coli, B. subtilis, B. megaterium, and P. vulgaris

Biodiversity, Biochemical Profiling, and Pharmaco-Commercial Applications of Withania somnifera:A Review

Withania somnifera L. Dunal (Ashwagandha), a key medicinal plant native to India, is used globally to manage various ailments. This review focuses on the traditional uses, botany, phytochemistry, and pharmacological advances of its plant-derived constituents. It has been reported that at least 62 crucial and 48 inferior primary and secondary metabolites are present in the W. somnifera leaves, and 29 among these found in its roots and leaves are chiefly steroidal compounds, steroidal lactones, alkaloids, amino acids, etc. In addition, the whole shrub parts possess various medicinal activities such as anti-leukotriene, antineoplastic, analgesic, anti-oxidant, immunostimulatory, and rejuvenating properties, mainly observed by in vitro demonstration. However, the course of its medical use remains unknown. This review provides a comprehensive understanding of W. somnifera, which will be useful for mechanism studies and potential medical applications of W. somnifera, as well as for the development of a rational quality control system for W. somnifera as a therapeutic material in the future

A Clinical and Radiological Evaluation of Chronic Rhinosinusitis

Introduction The diagnosis of rhinosinusitis is based on clinical grounds having characteristic symptoms, combined with objective evidence of mucosal inflammation. We studied the corelation between the symptoms of the patients, clinical and endoscopic findings with CT scan findings in chronic rhinosinusitis (CRS). Materials and Methods Patients above the age of 15yrs fulfilling the criteria of Chronic sinusitis laid by European position paper on rhinosinusitis and nasal polyps (EPOS) 2012 were prospectively studied. Demographic and clinical profile were noted. Diagnostic Nasal Endoscopy was done and findings were recorded. Patients were undergone CT evaluation after giving appropriate medical management. Clinical, endoscopic and radiological findings were compared with similar studies. Data was analysed using IBM SPSS software version 20. Results This study included 118 patients of Chronic Rhinosinusitis. Patients commonly male between the age group of 21-30 years presented with nasal obstruction, headache and nasal discharge in order of presentation. Diagnostic Nasal endoscopy revealed Septal deviation in 64.4% and medialize uncinate process in 15.2% of cases. Nasal discharge (48.3%) was commonest finding. CT scan suggested deviated nasal septum (70.4%), concha bullosa (30.5%), blocked osteo-meatal complex (68.6%) in patients of CRS. Presence of Agger Nasi cell (49.2%), Haller cell (12.7%) and Onodi cell (15.7%) seen in these patients. Conclusion CT scan and diagnostic endoscopy along with detailed clinical examination are essential component for assessment of a patient with chronic rhinosinusitis. CT scan is considered as gold standard but endoscopy is also a valuable tool for diagnostic evaluation of patients with CRS