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Most of the pulmonary endobronchial lesions are malignant in origin. In rare instances, benign lesions such as endobronchial hamartoma may be the cause of the endobronchial tree obstruction. We present the case of a 57-year-old male patient from North Africa who presents with a history of a 5-month cough. Imaging, particulary CT scan, showed a mass on the right intermediate bronchus whose radiological characteristics are consistent with hamartoma. A biopsy of the mass obtained via bronchoscopy revealed chronic inflammation with no evidence for malignancy. The patient was treated surgically, and anatomopathology confirmed the diagnosis of hamartoma.

Empyema necessitans is a rare condition where tuberculosis is the most common cause. It can be found in both immunocompromised and immunocompetent patients, especially in endemic areas. We report a case of a 29-year-old male from North Africa, with an enlarging mass on the right thoracic wall. Imaging, particularly CT showed a cystic lesion in the right chest wall communicating with homolateral pleural effusion, compatible with empyema necessitans. It also showed patterns of pulmonary tuberculosis in the right upper lung. Treatment of empyema necessitans is a combination of medical and surgicaltreatment. Our patient underwent a surgical treatment consisting of flattening of the empyema with a Gene X-pert study of the fluid and the shell, followed by an anti-TB treatment. Anatomopathology confirmed the diagnosis of caseo-follicular tuberculosis.

Abstract Background In the current treatment landscape for non-small cell lung cancers, epidermal growth factor receptor-tyrosine kinase inhibitors have emerged as a well-established treatment option for patients with advanced or metastatic disease. This is particularly true for those with commonly occurring epidermal growth factor receptor mutations. However, the therapeutic efficacy of these agents for so-called rare epidermal growth factor receptor mutations, and in particular those characterized by a high degree of complexity, such as double mutations, remains a subject of clinical uncertainty. Case presentation In this context, we present the case of a 64-year-old man of Moroccan descent, a lifelong non-smoker, diagnosed with metastatic non-small cell lung cancer characterized by a complex epidermal growth factor receptor mutation encompassing L858R and S768I. The patient subsequently underwent afatinib-based treatment, showing notable clinical results. These included a remarkable overall survival of 51 months, with a median progression-free survival of more than 39 months. Conclusions This case report is a compelling testimony to the evolving therapeutic landscape of non-small cell lung cancers, providing valuable insight into the potential therapeutic efficacy of epidermal growth factor receptor-tyrosine kinase inhibitors in the realm of rare and complex epidermal growth factor receptor mutations.

Purpose: To propose an intelligent, non-invasive, highly precise, and rapid method to predict the mutation status of the Epidermal Growth Factor Receptor (EGFR) to accelerate treatment with Tyrosine Kinase Inhibitor (TKI) for patients with untreated adenocarcinoma Non-Small Cell Lung Cancer. Materials and methods: Real-world data from 521 patients with adenocarcinoma NSCLC who performed a CT scan and underwent surgery or pathological biopsy to determine EGFR gene mutation between January 2021 and July 2022, is collected. Solutions to the problems that prevent the model from achieving very high precision, namely: human errors made during the annotation of the database and the low precision of the output decision of the model, are proposed. Thus, among the 521 analyzed cases, only 40 were selected as patients with EGFR gene mutation and 98 cases with wild-type EGFR. Results: The proposed model is trained, validated, and tested on 12,040 2D images extracted from the 138 CT scans images where patients were randomly partitioned into training (80 %) and test (20 %) sets. The performance obtained for EGFR gene mutation prediction was 95.22 % for accuracy, 960.2 for F1_score, 95.89 % for precision, 96.92 % for sensitivity, 94.01 % for Cohen kappa, and 98 % for AUC. Conclusion: An EGFR gene mutation status prediction method, with high-performance thanks to an intelligent prediction model entrained by highly accurate annotated data is proposed. The outcome of this project will facilitate rapid decision-making when applying a TKI as an initial treatment.

IntroductionIn this paper, we introduce an advanced robotic system integrated with an adaptive optimization algorithm, tailored for Brachytherapy in prostate cancer treatment. The primary innovation of the system is the algorithm itself, designed to dynamically adjust needle trajectories in response to the real-time movements of the prostate gland during the local intervention.MethodsThe system employs real-time position data extracted from Magnetic Resonance Imaging (MRI) to ensure precise targeting of the prostate, adapting to its constant motion and deformation. This precision is crucial in Brachytherapy, where the accurate placement of radioactive seeds directly impacts the efficacy of the treatment and minimizes damage to surrounding safe tissues.ResultsOur results demonstrate a marked improvement in the accuracy of radiation seed placement, directly correlating to more effective radiation delivery. The adaptive nature of the algorithm significantly reduces the number of needle insertions, leading to a less invasive treatment experience for patients. This reduction in needle insertions also contributes to lower risks of infection and shorter recovery times.DiscussionThis novel robotic system, enhanced by the adaptive optimization algorithm, improves the coverage of targets reached by a traditional combinatorial approach by approximately 15% with fewer required needles. The improved precision and reduced invasiveness highlight the potential of this system to enhance the overall effectiveness and patient experience in prostate cancer Brachytherapy.

System-of-systems (SoS) face major challenges, including heterogeneity, scalability, and intricate interactions among component systems (CSs). These systems typically operate in dynamic environments, introducing uncertainty and stochastic behavior. Many existing studies tend to oversimplify these complexities, with limited research focusing on supervising SoS under such conditions. Graph models, such as hypergraphs (HG), have been effective in modeling SoS organizations, while stochastic and weighted hypergraphs have been successfully used to handle stochasticity in other complex systems. In this article, we present the Multi-Level Stochastic Hypergraph (MLSHG) model, designed to address the challenges of modeling stochastic SoS. We also propose a novel algorithm for supervising large-scale SoS, integrating bottom-up monitoring with top-down reconfiguration to detect the addition or failure of CSs and manage the overall system’s capacity to achieve long-term objectives. In a case study on a mushroom harvesting SoS, the results showed that incorporating stochastic elements with an adaptive threshold enabled early reconfiguration, reducing deviations from the final goal. Additionally, the capability-based reconfiguration approach exhibited low computational time, with performance scaling linearly with the number of CSs, thus enhancing the system’s scalability.

Fibrosing mediastinitis, also known as sclerosing mediastinitis, is an uncommon condition marked by abnormal proliferation of fibrous tissue in the mediastinum. This condition may accrue either as an idiopathic condition or as a complication of an underlying disease process. Its pathogenesis remains unknown. However, most reported cases are incriminating abnormal immune-mediated hypersensitivity responses to Histoplasma infection. Other rare causes include tuberculosis, blastomycosis, and an idiopathic form that may be associated with other miscellaneous conditions. CT and MR imaging play a vital role in the diagnosis and management of this disease. We present a rare case of fibrosing mediastinitis as a late complication of tuberculosis in a 34-year-old man with a prior history of mediastinal tuberculosis, mimicking initially a neoplastic mediastinal process. We will describe this clinical case in the light of the literature and point out the contribution of radiological imaging in the diagnosis of this rare pathology.

Abstract Background Lung cancer is the leading cause of cancer death in the world. Non-small-cell lung cancer (NSCLC) accounts for 85% of primary lung tumors. Epidermal growth factor receptors (EGFRs) are found on the surface of tumor cells, and their role is to send a growth signal to the cell nucleus. Tumor cells with EGFR mutations are very sensitive to cancer treatments called "Targeted Therapies." The search for EGFR mutations requires lung biopsies. Some studies have shown a correlation between clinico-radiological characteristics and the EGFR mutation. In this study, an attempt was made to identify the relevant clinico-radiological characteristics associated with the EGFR mutation in patients with NSCLC. Objectives The main objective of this study was to evaluate the clinico-radiological characteristics useful for predicting the risk of EGFR mutation in patients with NSCLC. Materials and methods This is a retrospective cross-sectional study, carried out in 149 patients followed up for lung adenocarcinoma who benefited from an EGFR mutation study at the anatomopathology department of the University Hospital of Fez, spread over a period of 4 years (between January 2018 and December 2021). A database was compiled from this study, including sociodemographic, clinical, anatomopathological and radiological data. A statistical analysis was carried out in order to identify the factors associated with EGFR mutation. Results According to the inclusion and exclusion criteria, of the 149 patients included, the mean age was 61.05 + / − 11.095 years. Males predominated with a percentage of 70.5% (n = 105). Fifty-seven point seven percent of patients were smokers or ex-smokers. Forty-one patients had an EGFR mutation, representing a percentage of 27.5%. Multivariate analysis by logistic regression revealed an association of the EGFR mutation with irregular contours (ORA = 6.43; CI95% 1.26;32.78), with the presence of spiculations (ORA = 5.81; CI95% 1.96;17.22), with pleural attachment (ORA = 3.53; CI95% 1.32;9.42), with heterogeneous enhancement (ORA = 30.679; CI95% 5.149;182.778), with absence of emphysema (ORA = 4.815; CI95% 1.966;17.220) and with presence of distant metastasis (ORA = 4.123; CI95% 1.373;12.383). Conclusions This study provides substantial evidence to support the assertion that irregular contours, the presence of spiculations, pleural attachment, heterogeneous enhancement, the absence of emphysema and the presence of distant metastasis are statistically correlated with EGFR mutations. The model developed within this study, encompassing all relevant clinical and CT characteristics, has demonstrated its effectiveness as a reliable predictor for EGFR mutations (AUC: 0.7659) and consequently as a key determinant of EGFR-TKI treatment response.

Objective This study aims to show the place of muscle-sparing posterolateral thoracotomy in the treatment of spontaneous pneumothorax.

Carbon capture and storage using chemical absorption is a viable method for reducing CO2 emissions from the industrial sector. Thermodynamic analysis of MDEA-PZ aqueous alkanolamine solution is of paramount importance to better simulate and improve the efficiency of CO2 capture processes. In this study, we use the Aspen Plus simulator (V12.1) to compare the theoretical differences and the regression results of the two-liquid activity coefficient models ELECNRTL and ENRTL-RK in terms of CO2 solubility. The quaternary system CO2-MDEA-PZ-H2O vapor-liquid equilibrium (VLE) data found in the open literature are first collected. After excluding anomalous points according to some criteria, 521 confirmed data ranging from 40 °C to 120 °C are then used to regress the binary interaction parameters of molecule-molecule and molecule-electrolyte pairs for both models using the maximum likelihood method. The fitting results show an accuracy enhancement of 34 % for ELECNRTL and 68 % for ENRTL-RK compared to the Aspen default models. The regressed models can be used to improve the accuracy of absorber and stripper simulations in CO2 capture processes.

As part of vehicle to everything (V2X) environments, intelligent connected vehicles (ICVs) generate a large amount of data, which can be exploited securely and effectively through decentralized techniques such as federated learning (FL). Existing FL systems, however, are vulnerable to attacks and barely meet the security requirements for real-world applications. If malicious or compromised ICVs upload inaccurate or low-quality local model updates to the central aggregator, they may reduce the accuracy of the global model, thereby reducing drivers safety and efficiency. This paper aims to alleviate these concerns by presenting BV-ICVs, a blockchain-enabled and privacy-preserving FL framework for ICVs in an edge-envisioned V2X environment. This system uses Zero-Knowledge Succinct Non-Interactive Argument of Knowledge (zkSNARKs) verification that is compiled as smart contracts to prevent malicious, compromised or even rational ICVs from uploading unreliable, erroneous or low-quality model updates. The verification process is embedded within the consensus of the underlying permissioned blockchain, which maximizes both the efficiency of the process and the utilization of computer resources. As demonstrated by discussions, security analysis, and numerical results, BV-ICVs reduced data poisoning attacks and increased the privacy protection and accuracy of FL.

This study presents a detailed comparative analysis of online evaluation platforms aimed at identifying the most suitable one for integrating an adaptive revision plugin. The study uses both the analytic hierarchy process (AHP) and multi-criteria decision making (MCDM) to give a structured and thorough evaluation of different learning management systems (LMSs). By scrutinizing the capabilities, interfaces, and underlying technologies of these systems, the analysis seeks to pinpoint the platform that offers optimal compatibility, flexibility, functionality, and user experience. The central objective of this study is to enhance the effectiveness of adaptive learning tools within educational technologies. This is achieved by evaluating different platforms to ascertain which one best supports the integration of adaptive revision functionalities. Our comprehensive analysis clearly identifies Moodle as the superior platform due to its robust adaptability and enhanced customization capabilities, which are essential for implementing effective adaptive learning tools. The results underscore Moodle's potential to significantly enhance the educational experience by supporting tailored learning paths and dynamic content adjustments. This study not only highlights Moodle's advantages but also sets the groundwork for future advancements in adaptive educational technologies. [ABSTRACT FROM AUTHOR]

Abstract In this paper, we present a numerical study along with an exhaustive adsorption investigation in a binary dilute mixture model nearby the solvent’s critical point in a configuration relevant for soil remediation. By means of this model, mass and heat transfer efficiency were qualitatively and quantitatively discussed through this work. The convergence of the solution was evaluated on the values of the Nusselt and Sherwood numbers. The results reveal intense convection expanding into the cavity close to the critical point, thus enabling homogeneous adsorption of the solute. Moreover, the mass fraction perturbation isolines exhibit the existence, along the adsorbent plate, of a thin boundary layer which becomes thinner when approaching the critical point.

Background: We herein report the case of a patient with advanced lung adenocarcinoma who presented a heterogeneous distribution of EGFR mutation. Case report: A 74-year-old Moroccan male former smoker was diagnosed with advanced lung adenocarcinoma, harboring S768I exon 20 substitution mutation confirmed by Real Time PCR and Pyrosequencing, but not detected by direct sequencing despite 70% of tumor cells. The present report describes a case of minor histologic intratumoral heterogeneity with heterogeneous distribution of EGFR mutation. Conclusion: Both sensitivity and specificity of molecular methods can provide evidence of intratumoral heterogeneity, which may explain the mismatch between the validation of oncology biomarkers and predicting therapeutic response to targeted therapy.

There are very few data in the literature describing the occurrence of venous thrombosis in children. This raises the essential problem of late diagnosis, especially in asymptomatic or pauci-symptomatic presentations where this pathology may be unrecognized.The post-traumatic context of venous thrombosis in children, reported in a few cases, should lead to the suspicion of thrombophilia and to a clinical, biological and radiological etiological assessment.We report in our work the observation of a 14-year-old girl admitted in the context of a polytrauma with minimal mechanism in whom the lesion assessment revealed an extensive thrombosis of the inferior vena cava in the supra renal area, with a review of the literature.

Park et al. characterise the interactome, localisation and function of Actin-Related Protein-Testis1 protein (ARP-T1), encoded by the ACTRT1 gene, associated with inherited basal cell cancer. They find that ARP-T1 is localised to the primary cilia basal body in epidermal cells, interacts with the cilia machinery, and is needed for proper ciliogenesis.