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Introduction Lung cancer (LC) is the most common cause of cancer-related deaths worldwide. Its early detection can be achieved with a CT scan. Two large randomised trials proved the efficacy of low-dose CT (LDCT)-based lung cancer screening (LCS) in high-risk populations. The decrease in specific mortality is 20%–25%.Nonetheless, implementing LCS on a large scale faces obstacles due to the low number of thoracic radiologists and CT scans available for the eligible population and the high frequency of false-positive screening results and the long period of indeterminacy of nodules that can reach up to 24 months, which is a source of prolonged anxiety and multiple costly examinations with possible side effects.Deep learning, an artificial intelligence solution has shown promising results in retrospective trials detecting lung nodules and characterising them. However, until now no prospective studies have demonstrated their importance in a real-life setting.Methods and analysis This open-label randomised controlled study focuses on LCS for patients aged 50–80 years, who smoked more than 20 pack-years, whether active or quit smoking less than 15 years ago. Its objective is to determine whether assisting a multidisciplinary team (MDT) with a 3D convolutional network-based analysis of screening chest CT scans accelerates the definitive classification of nodules into malignant or benign. 2722 patients will be included with the aim to demonstrate a 3-month reduction in the delay between lung nodule detection and its definitive classification into benign or malignant.Ethics and dissemination The sponsor of this study is the University Hospital of Nice. The study was approved for France by the ethical committee CPP (Comités de Protection des Personnes) Sud-Ouest et outre-mer III (No. 2022-A01543-40) and the Agence Nationale du Medicament et des produits de Santé (Ministry of Health) in December 2023. The findings of the trial will be disseminated through peer-reviewed journals and national and international conference presentations.Trial registration number NCT05704920.

Summary: Severe combined immunodeficiency (SCID) is fatal if not treated with immune reconstitution. In Egypt, T‐B+ SCID accounts for 38·5% of SCID diagnoses. An accurate genetic diagnosis is essential for choosing appropriate treatment modalities and for offering genetic counseling to the patient's family. The objectives of this study were to describe the clinical, immunological and molecular characteristics of a cohort of twenty Egyptian patients with T‐B+ SCID. The initial diagnosis (based on clinical features and flow cytometry) was followed by molecular investigation (whole‐exome sequencing). All patients had the classic clinical picture for SCID, including failure to thrive (n = 20), oral candidiasis (n = 17), persistent diarrhea (n = 14), pneumonia (n = 13), napkin dermatitis (n = 10), skin rash (n = 7), otitis media (n = 3) and meningitis (n = 2). The onset of manifestations was at the age of 2·4 ± 1·6 months and diagnosis at the age of 6·7 ± ·5 months, giving a diagnostic delay of 4·3 months. JAK3 gene variants were most frequent (n = 12) with three novel variants identified, followed by IL2Rγ variants (n = 6) with two novel variants. IL7Rα and CD3ε variants were found once, with a novel variant each. T‐B+NK− SCID accounted for approximately 90% of the Egyptian patients with T‐B+SCID. Of these T‐B+NK− SCID cases, 60% were autosomal recessive syndromes caused by JAK3 mutations and 30% were X‐linked syndromes. It might be useful to sequence the JAK3 gene (i.e. targeted Sanger sequencing) in all T‐B+ SCID patients, especially after X‐linked SCID has been ruled out. Hence, no more than 10% of T‐B+ SCID patients might require next‐generation for a molecular diagnosis. [ABSTRACT FROM AUTHOR]

Summary: Mutations affecting recombination activation genes RAG1 and RAG2 are associated with variable phenotypes, depending on the residual recombinase activity. The aim of this study is to describe a variety of clinical phenotypes in RAG‐deficient patients from the highly consanguineous Egyptian population. Thirty‐one patients with RAG mutations (from 28 families) were included from 2013 to 2017. On the basis of clinical, immunological and genetic data, patients were subdivided into three groups; classical T–B– severe combined immunodeficiency (SCID), Omenn syndrome (OS) and atypical SCID. Nineteen patients presented with typical T–B–SCID; among these, five patients carried a homozygous RAG2 mutation G35V and five others carried two homozygous RAG2 mutations (T215I and R229Q) that were detected together. Four novel mutations were reported in the T–B–SCID group; three in RAG1 (A565P, N591Pfs*14 and K621E) and one in RAG2 (F29S). Seven patients presented with OS and a novel RAG2 mutation (C419W) was documented in one patient. The atypical SCID group comprised five patients. Two had normal B cell counts; one had a previously undescribed RAG2 mutation (V327D). The other three patients presented with autoimmune cytopaenias and features of combined immunodeficiency and were diagnosed at a relatively late age and with a substantial diagnostic delay; one patient had a novel RAG1 mutation (C335R). PID disorders are frequent among Egyptian children because of the high consanguinity. RAG mutations stand behind several variable phenotypes, including classical SCID, OS, atypical SCID with autoimmunity and T–B+ CID. RAG1/2 mutations stand behind variable clinical phenotypes.‎ The different phenotypes extend to include T–B+SCID and combined immunodeficiency ‎with granuloma and/or autoimmunity.‎ The genotype–phenotype correlation is not absolute and is affected by epigenetics, early ‎exposure to infections and other environmental factors. [ABSTRACT FROM AUTHOR]

We propose a new method to build exact solutions of Einstein field equations in case of ‘‘hypersurface-homogeneous space-times.’’ The energy-momentum tensor is of perfect fluid type. Starting from SE solutions we are able to build new classes of solutions which add to the rare solutions not satisfying the equation of state p=(γ-1)μ. We study the geometrical and physical properties of some of the solutions obtained. [ABSTRACT FROM AUTHOR]

A method for generating exact Bianchi type II cosmological models with a perfect fluid distribution of matter is presented. Two new classes of Bianchi type II solutions have been generated from Lorenz’s solution [D. Lorenz, Phys. Lett. A 79, 19 (1980)]. A detailed study of physical and kinematic properties of one of them has been carried out. [ABSTRACT FROM AUTHOR]

Many exact solutions for the spherically symmetric perfect fluid distribution of matter with shear, acceleration, and expansion are obtained. One of them is expressed in terms of Painlevé's third transcendent. [ABSTRACT FROM AUTHOR]