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Objective To implement and evaluate a large-scale online cervical cancer screening programme in Hubei Province, China, supported by artificial intelligence and delivered by trained health workers. Methods The screening programme, which started in 2017, used four types of health worker: sampling health workers, slide preparation technicians, diagnostic health workers and cytopathologists. Sampling health workers took samples from the women on site; slide preparation technicians prepared slides for liquid-based cytology; diagnostic health workers identified negative samples and classified positive samples based on the Bethesda System after cytological assessment using online artificial intelligence; and cytopathologists reviewed positive samples and signed reports of the results online. The programme used fully automated scanners, online artificial intelligence, an online screening management platform, and mobile telephone devices to provide screening services. We evaluated the sustainability, performance and cost of the programme. Results From 2017 to 2021, 1 518 972 women in 16 cities in Hubei Province participated in the programme, of whom 1 474 788 (97.09%) had valid samples for the screening. Of the 86 648 women whose samples were positive, 30 486 required a biopsy but only 19 495 had one. The biopsy showed that 2785 women had precancerous lesions and 191 had invasive cancers. The cost of screening was 6.31 United States dollars (US$) per woman for the public payer: US$ 1.03 administrative costs and US$ 5.28 online screening costs. Conclusion Cervical cancer screening using artificial intelligence in Hubei Province provided a low-cost, accessible and effective service, which will contribute to achieving universal cervical cancer screening coverage in China. Objectif Deployer et evaluer un programme en ligne de grande envergure destine au depistage du cancer du col de l'uterus dans la province du Hubei, en Chine, reposant sur l'intelligence artificielle et mis en oeuvre par des agents de sante formes a cet effet. Methodes Le programme de depistage, qui a debute en 2017, s'appuyait sur quatre types d'agents de sante: des agents charges de prelever les echantillons, des techniciens charges de preparer les lames, des agents charges d'etablir le diagnostic et des cytopathologistes. Les premiers ont preleve des echantillons aupres des femmes sur place, les deuxiemes ont prepare les lames pour la cytologie en phase liquide, les troisiemes ont identifie les echantillons negatifs et classe les echantillons positifs selon le systeme de Bethesda apres analyse cytologique a l'aide d'une intelligence artificielle en ligne, tandis que les cytopathologistes ont examine les echantillons positifs et signe les rapports de resultats en ligne. Le programme etait constitue de scanners entierement automatises, d'une intelligence artificielle en ligne, d'une plateforme de gestion du depistage en ligne, ainsi que d'appareils de telephonie mobile pour les services de depistage. Nous avons evalue la viabilite, les performances et le cout d'un tel programme. Resultats Entre 2017 et 2021, 1 518 972 femmes residant dans 16 villes de la province du Hubei ont participe au programme, et 1 474 788 (97,09%) d'entre elles ont presente des echantillons valides pour le depistage. Sur les 86 648 femmes dont les echantillons se sont reveles positifs, 30 486 ont eu besoin d'une biopsie, mais seulement 19 495 en ont effectue une. La biopsie a montre que 2785 femmes presentaient des lesions precancereuses et que 191 etaient atteintes de cancers invasifs. Le cout du depistage s'elevait a 6,31 dollars americains (USD) par femme pour le payeur public: 1,03 USD pour les frais administratifs et 5,28 USD pour le depistage en ligne. Conclusion Le depistage du cancer du col de l'uterus assiste par intelligence artificielle dans la province du Hubei est un service abordable, accessible et efficace, qui contribuera a garantir une couverture universelle en la matiere dans le pays. Objetivo Implementar y evaluar un programa de deteccion del cancer del cuello uterino en linea a gran escala en la provincia de Hubei (China), con el apoyo de la inteligencia artificial y a cargo de trabajadores sanitarios formados. Metodos El programa de deteccion, que comenzo en 2017, utilizo cuatro tipos de trabajadores sanitarios: trabajadores sanitarios de muestreo, tecnicos de preparacion de portaobjetos, trabajadores sanitarios de diagnostico y citopatologos. Los trabajadores sanitarios de muestreo tomaban muestras de las mujeres in situ, los tecnicos de preparacion de portaobjetos preparaban los portaobjetos para la citologia mediante liquidos, los trabajadores sanitarios de diagnostico identificaban las muestras negativas y clasificaban las muestras positivas segun el Sistema Bethesda tras la evaluacion citologica mediante inteligencia artificial en linea, y los citopatologos revisaban las muestras positivas y firmaban los informes de los resultados en linea. El programa utilizo escaneres totalmente automatizados, inteligencia artificial en linea, una plataforma de gestion de la deteccion en linea y dispositivos de telefonia movil para proporcionar servicios de deteccion. Se evaluaron la sostenibilidad, el rendimiento y el coste del programa. Resultados Entre 2017 y 2021, 1 518 972 mujeres de 16 ciudades de la provincia de Hubei participaron en el programa, de las que 1 474 788 (97,09%) tenian muestras validas para la deteccion. De las 86 648 mujeres cuyas muestras dieron positivo, 30 486 necesitaron una biopsia, pero solo 19 495 se sometieron a ella. La biopsia mostro que 2785 mujeres tenian lesiones precancerosas y 191 canceres invasivos. El coste de la deteccion fue de 6,31 dolares estadounidenses (US$) por mujer para el organismo publico pagador: US$ 1,03 de costes administrativos y US$ 5,28 de costes de deteccion en linea. Conclusion La deteccion del cancer del cuello uterino mediante inteligencia artificial en la provincia de Hubei proporciono un servicio de bajo coste, accesible y eficaz, que contribuira a lograr la cobertura universal de deteccion del cancer del cuello uterino en China., Introduction Cervical cancer is a threat to women's health. According to data released by the International Agency for Research on Cancer, the cancer research agency of the World Health Organization [...]

Angiotensin-converting enzyme 2 (ACE2) and accessory proteases (TMPRSS2 and CTSL) are needed for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cellular entry, and their expression may shed light on viral tropism and impact across the body. We assessed the cell-type-specific expression of ACE2, TMPRSS2 and CTSL across 107 single-cell RNA-sequencing studies from different tissues. ACE2, TMPRSS2 and CTSL are coexpressed in specific subsets of respiratory epithelial cells in the nasal passages, airways and alveoli, and in cells from other organs associated with coronavirus disease 2019 (COVID-19) transmission or pathology. We performed a meta-analysis of 31 lung single-cell RNA-sequencing studies with 1,320,896 cells from 377 nasal, airway and lung parenchyma samples from 228 individuals. This revealed cell-type-specific associations of age, sex and smoking with expression levels of ACE2, TMPRSS2 and CTSL. Expression of entry factors increased with age and in males, including in airway secretory cells and alveolar type 2 cells. Expression programs shared by ACE2+TMPRSS2+ cells in nasal, lung and gut tissues included genes that may mediate viral entry, key immune functions and epithelial-macrophage cross-talk, such as genes involved in the interleukin-6, interleukin-1, tumor necrosis factor and complement pathways. Cell-type-specific expression patterns may contribute to the pathogenesis of COVID-19, and our work highlights putative molecular pathways for therapeutic intervention.

The effect of pachymic acid (PA) on pulmonary fibrosis in rats was expected to be investigated in this study. Firstly, bleomycin (BLM) was used to establish pulmonary fibrosis rat model, then PA (10, 20, or 40 mg/kg) was intragastrically administered to the rats for 14 days. Subsequently, a variety of tests was performed to observe changes in sample tissues after different treatments. Briefly, the degree of pulmonary edema in rats was assessed through dry/wet weight ratio. Hematoxylin and eosin (H&E) staining and Masson's trichrome staining were used to observe the pathological injury and fibrosis of lung tissue. Biochemical kits were applied to measure the levels of hydroxyproline (Hyp), transforming growth factor beta‐1 (TGFβ‐1), malondialdehyde (MDA), reactive oxygen species (ROS), and adenosine triphosphate (ATP) and the activities of superoxide dismutase (SOD) and catalase (CAT) in rat lung tissues of each group. The mitochondrial DNA (mtDNA) copy number in rat lung tissue was tested using qRT‐PCR. Additionally, the western blot was employed to detect the expression levels of pulmonary fibrosis‐related proteins and endoplasmic reticulum (ER) stress‐related proteins in each group of rat lung tissue. By virtue of experimental verification above, PA was discovered to alleviate BLM‐induced pulmonary edema, pulmonary fibrosis and histopathological damage. On the one hand, PA treatment decreased Hyp and TGF‐β1 levels and down‐regulated pulmonary fibrosis‐related protein expression [collagen I, α‐smooth muscle actin (α‐SMA), and fibronectin] in the lung tissue of BLM rats. On the other hand, it significantly increased the levels of SOD, CAT and ATP while decreased the activities of MDA and ROS in BLM rat lung tissues. In addition, the expression levels of ER stress‐related proteins [glucose‐regulated protein 78 (GRP78), C/EBP homologous protein (CHOP), Caspase 9, and activating transcription factor 4 (ATF4)] were significantly down‐regulated in the lung tissue of BLM rats after PA treatment. Collectively, PA may ameliorate BLM‐induced pulmonary fibrosis and histopathological damage in rats through inhibiting ER stress and improving mitochondrial function. [ABSTRACT FROM AUTHOR]

Azobenzene-based probes have been widely used in biosensing, bioimaging and nanomedicine; however, their water solubility was not good enough, especially for long-term processes. To address the problem, cyclodextrins (CDs) were utilized as water-soluble hosts to facilitate the dispersion of azo molecules separately in the aqueous solution, which avoided aggregation to improve water solubility. In addition, an azobenzene-based pH probe was developed to serve as a model molecule to investigate the influence on responsive performance after host–guest interaction. Compared with α-and β-CD, γ-CD with the biggest cavity size and weakest host–guest interaction displayed the best improvement on water solubility and minimized influence on the pH-responsive performance, providing a universal approach to improve the water solubility of azobenzene-based probes while with a minimal negative effect on the responsive performance, which will be of interest to researchers in the fields of supramolecular chemistry, materials science and nanotechnology. [ABSTRACT FROM AUTHOR]