Enhancing lung cancer detection through hybrid features and machine learning hyperparameters optimization techniques.

Machine learning offers significant potential for lung cancer detection, enabling early diagnosis and potentially improving patient outcomes. Feature extraction remains a crucial challenge in this domain. Combining the most relevant features can further enhance detection accuracy. This study employed a hybrid feature extraction approach, which integrates both Gray-level co-occurrence matrix (GLCM) with Haralick and autoencoder features with an autoencoder. These features were subsequently fed into supervised machine learning methods. Support Vector Machine (SVM) Radial Base Function (RBF) and SVM Gaussian achieved perfect performance measures, while SVM polynomial produced an accuracy of 99.89% when utilizing GLCM with an autoencoder, Haralick, and autoencoder features. SVM Gaussian achieved an accuracy of 99.56%, while SVM RBF achieved an accuracy of 99.35% when utilizing GLCM with Haralick features. These results demonstrate the potential of the proposed approach for developing improved diagnostic and prognostic lung cancer treatment planning and decision-making systems.

AI-driven Discovery of Celecoxib and Dexamethasone for Exploring their Mode of Action as Human Interleukin (IL-6) Inhibitors to Treat COVID-19-induced Cytokine Storm in Humans.

BACKGROUND: In the case of COVID-19 patients, it has been observed that the immune system of the infected person exhibits an extreme inflammatory response known as cytokine release syndrome (CRS) where the inflammatory cytokines are swiftly produced in quite large amounts in response to infective stimuli. Numerous case studies of COVID-19 patients with severe symptoms have documented the presence of higher plasma concentrations of human interleukin-6 (IL-6), which suggests that IL-6 is a crucial factor in the pathophysiology of the disease. In order to prevent CRS in COVID-19 patients, the drugs that can exhibit binding interactions with IL-6 and block the signaling pathways to decrease the IL-6 activity may be repurposed. METHODS: This research work focused on molecular docking-based screening of the drugs celecoxib (CXB) and dexamethasone (DME) to explore their potential to interact with the binding sites of IL-6 protein and reduce the hyper-activation of IL-6 in the infected personnel. RESULTS: Both of the drugs were observed to bind with the IL-6 (IL-6 receptor alpha chain) and IL-6Rα receptor with the respective affinities of -7.3 kcal/mol and -6.3 kcal/mol, respectively, for CXB and DME. Moreover, various types of binding interactions of the drugs with the target proteins were also observed in the docking studies. The dynamic behaviors of IL-6/IL-6Rα in complex with the drugs were also explored through molecular dynamics simulation analysis. The results indicated significant stabilities of the acquired drug-protein complexes up to 100 ns. CONCLUSION: The findings of this study have suggested the potential of the drugs studied to be utilized as antagonists for countering CRS in COVID-19 ailment. This study presents the studied drugs as promising candidates both for the clinical and pre-clinical treatment of COVID-19.

Isoform switching leads to downregulation of cytokine producing genes in estrogen receptor positive breast cancer.

Objective: Estrogen receptor breast cancer (BC) is characterized by the expression of estrogen receptors. It is the most common cancer among women, with an incidence rate of 2.26 million cases worldwide. The aim of this study was to identify differentially expressed genes and isoform switching between estrogen receptor positive and triple negative BC samples. Methods: The data were collected from ArrayExpress, followed by preprocessing and subsequent mapping from HISAT2. Read quantification was performed by StringTie, and then R package ballgown was used to perform differential expression analysis. Functional enrichment analysis was conducted using Enrichr, and then immune genes were shortlisted based on the ScType marker database. Isoform switch analysis was also performed using the IsoformSwitchAnalyzeR package. Results: A total of 9,771 differentially expressed genes were identified, of which 86 were upregulated and 117 were downregulated. Six genes were identified as mainly associated with estrogen receptor positive BC, while a novel set of ten genes were found which have not previously been reported in estrogen receptor positive BC. Furthermore, alternative splicing and subsequent isoform usage in the immune system related genes were determined. Conclusion: This study identified the differential usage of isoforms in the immune system related genes in cancer cells that suggest immunosuppression due to the dysregulation of CXCR chemokine receptor binding, iron ion binding, and cytokine activity.

Developing an Efficient Cancer Detection and Prediction Tool Using Convolution Neural Network Integrated with Neural Pattern Recognition.

The application of computational approaches in medical science for diagnosis is made possible by the development in technical advancements connected to computer and biological sciences. The current cancer diagnosis system is becoming outmoded due to the new and rapid growth in cancer cases, and new, effective, and efficient methodologies are now required. Accurate cancer-type prediction is essential for cancer diagnosis and treatment. Understanding, diagnosing, and identifying the various types of cancer can be greatly aided by knowledge of the cancer genes. The Convolution Neural Network (CNN) and neural pattern recognition (NPR) approaches are used in this study paper to detect and predict the type of cancer. Different Convolution Neural Networks (CNNs) have been proposed by various researchers up to this point. Each model concentrated on a certain set of parameters to simulate the expression of genes. We have developed a novel CNN-NPR architecture that predicts cancer type while accounting for the tissue of origin using high-dimensional gene expression inputs. The 5000-person sample of the 1-D CNN integrated with NPR is trained and tested on the gene profile, mapping with various cancer kinds. The proposed model's accuracy of 94% suggests that the suggested combination may be useful for long-term cancer diagnosis and detection. Fewer parameters are required for the suggested model to be efficiently trained before prediction.

Multi-Epitope Vaccine Design against Monkeypox Virus via Reverse Vaccinology Method Exploiting Immunoinformatic and Bioinformatic Approaches.

(1) Background: The monkeypox virus is a zoonotic orthopox DNA virus that is closely linked to the virus. In light of the growing concern about this virus, the current research set out to use bioinformatics and immunoinformatics to develop a potential vaccine against the virus. (2) Methods: A multiepitope vaccine was constructed from the B-cell and T-cell epitopes of the MPXVgp181 strain using adjuvant and different linkers. The constructed vaccine was predicted for antigenicity, allergenicity, toxicity, and population coverage. In silico immune simulation studies were also carried out. Expression analysis and cloning of the constructed vaccine was carried out in the pET-28a(+) vector using snapgene. (3) Results: The constructed vaccine was predicted to be antigenic, non-allergenic, and non-toxic. It was predicted to have excellent global population coverage and produced satisfactory immune response. The in silico expression and cloning studies were successful in E. coli, which makes the vaccine construct suitable for mass production in the pharmaceutical industry. (4) Conclusion: The constructed vaccine is based on the B-cell and T-cell epitopes obtained from the MPXVgp181 strain. This research can be useful in developing a vaccine to combat the monkeypox virus globally after performing in-depth in vitro and in vivo studies.

Nontoxic and Naturally Occurring Active Compounds as Potential Inhibitors of Biological Targets in Liriomyza trifolii.

In recent years, novel strategies to control insects have been based on protease inhibitors (PIs). In this regard, molecular docking and molecular dynamics simulations have been extensively used to investigate insect gut proteases and the interactions of PIs for the development of resistance against insects. We, herein, report an in silico study of (disodium 5'-inosinate and petunidin 3-glucoside), (calcium 5'-guanylate and chlorogenic acid), chlorogenic acid alone, (kaempferol-3,7-di-O-glucoside with hyperoside and delphinidin 3-glucoside), and (myricetin 3'-glucoside and hyperoside) as potential inhibitors of acetylcholinesterase receptors, actin, α-tubulin, arginine kinase, and histone receptor III subtypes, respectively. The study demonstrated that the inhibitors are capable of forming stable complexes with the corresponding proteins while also showing great potential for inhibitory activity in the proposed protein-inhibitor combinations.

A case report of Adult-onset Still's disease as a cause of severe mitral regurgitation.

BACKGROUND: Adult-onset Still's disease (AOSD) is an uncommon systemic inflammatory disease, causing spiking fever, skin rash, and arthritis. Pericarditis and myocarditis are the most common cardiac manifestation of AOSD but valvular involvement is rarely reported. CASE SUMMARY: An 18-year-old boy presented with gradually worsening shortness of breath for 6 months. There was a history of low-grade intermittent fever and polyarthralgia affecting ankles, knees, and elbows. He was in heart failure with cardiogenic and septic shock. He was managed initially with antibiotics, inotropes, and diuretics. Echocardiography showed flail anterior mitral leaflet with severe mitral regurgitation. He remained febrile with persistent negative blood cultures. Intravenous antibiotics led to neutropenia without any response to fever and clinical status. On further workup, he was diagnosed to have AOSD, and he responded dramatically to oral steroid therapy. Later his mitral valve was replaced surgically. On follow-up, he was stable with mild exertional dyspnoea. His international normalized ratio was in therapeutic range and his follow-up echocardiography showed normally functioning mitral prosthesis. He is following rheumatology and currently on the maintenance dose of steroids. DISCUSSION: Adult-onset Still's disease is a systemic illness with diagnosis is based on clinical features and exclusion of other illnesses. Adult-onset Still's disease should be considered as a differential diagnosis in culture-negative endocarditis, especially in those with systemic features and non-responders to antibiotics.

Arterial Switch for Transposition of the Great Arteries With Large Ventricular Septal Defect and for Taussig Bing Anomaly: Experience From a Tertiary Care Center in the Developing World.

BACKGROUND: Results of the arterial switch operation (ASO) for transposition of the great arteries (TGA) with large ventricular septal defect (VSD) and for Taussig Bing anomaly (TBA) in a tertiary care center of a developing country were retrospectively analyzed. METHODS: From January 2007 through June 2013, a total of 30 patients with TBA and 54 patients having TGA with large VSD underwent ASO with VSD closure. Age at surgery for TBA was 27 days to 7 years (median age 3 months) and for TGA with VSD it was 1 day to 6 years (median age 2 months). In all, 46.7% of patients with TBA and 30% of patients with TGA/VSD presented with sepsis secondary to pneumonitis and were taken for surgery when the infection was under control. In all, 13% of patients with TBA and 5.5% of patients with TGA/VSD were on intermittent positive pressure ventilation (IPPV) prior to and continuing up to the time of surgery. RESULTS: On multivariate analysis, factors associated with mortality were the presence of preoperative IPPV for pneumonia (P < .006) and the need for peritoneal dialysis following surgery (P < .028). Neither diagnosis of TBA or TGA/VSD nor any associated anatomical feature (including aortic arch obstruction, unusual coronary anatomy, great artery relationship, or mitral valve anomaly) was found to be related to high early mortality or late complications. Follow-up was 92% complete, with a mean duration of follow-up of 4.1 years. Freedom from reoperation was 98% at five years, and actuarial survival was 83.3% at five years. CONCLUSIONS: Our experience at a tertiary center in a developing country suggests that preoperative need for IPPV for pneumonia is a major determining factor for mortality and morbidity in patients undergoing ASO for TBA and TGA/VSD. This appears to be of greater consequence than details of the underlying disease per se.