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Objective: This study aimed to investigate the chest computed tomography (CT) findings of SARS-CoV-2 Omicron variants in elderly patients with underlying diseases. Methods: We retrospectively analyzed data from 140 elderly patients with underlying diseases who were infected with SARS-CoV-2 Omicron variants. The patients were divided into a moderate group and a severe/critical group based on their clinical classifications. Clinical data, laboratory results, and chest CT data (including lesion distribution, morphology, image signs, and lung lobe score) were collected and analyzed for all patients. Results: Hypertension and hyperlipidemia were the most prevalent underlying diseases among elderly patients with the Omicron variant of SARS-CoV-2. Ground-glass density opacity was the main chest CT manifestation, typically presenting as a mixed distribution across multiple lung lobes. Common clinical symptoms include fever, cough, and sputum production. The proportion of patients with fever was significantly higher in the severe/critical group compared to the moderate group. Additionally, the lymphocyte count was higher in the moderate group compared to the severe/critical group, while the procalcitonin level was significantly higher in the severe/critical group. Pleural thickening was also more prevalent in the severe/critical group. The right inferior lobe score was the highest in both groups (2 (1,3) and 3 (2,4) for moderate and severe/critical groups, respectively), with the total score and individual lobe scores being significantly higher in the severe/critical group. Conclusions: Chest CT scans play a crucial role in classifying disease severity and evaluating disease progression in elderly patients with underlying diseases infected with the Omicron variant of the novel coronavirus. These findings can also guide clinical treatment decisions.

Objective: To investigate the chest computed tomography (CT) findings and dynamic changes in patients infected with SARS-CoV-2 Omicron variants. Methods: 200 patients infected with SARS-CoV-2 Omicron variants were collected in Beijing Ditan Hospital, Capital Medical University from November 2022 to January 2023. These patients were divided into mild group, moderate group and severe/critical group according to the clinical classification. All patients’ clinical, laboratory and chest CT data were retrospectively analyzed. Results: Among 200 cases infected with SARS-CoV-2 omicron variant, the main clinical manifestations were fever, cough, sore throat and fatigue. There was a statistically significant difference in white blood cell count between the mild group and the medium group, and between the mild group and the severe/critical group. There were significant differences in erythrocyte sedimentation rate between mild and moderate groups, and between mild and severe/critical groups. Most of the lesions in mild group were subpleural (53.6%), while most of the lesions in moderate group (77.9%) and severe/critical group (88.9%) were mixed. The crazy-paving sign was statistically significant between the mild and severe/critical groups, and between the mild and moderate groups. There were significant differences in air bronchogram sign between the mild and the severe/critical groups, the mild and severe/critical groups , and the mild and moderate groups. The frequency of Ground Glass Opacity (GGO) was the highest at different intervals between the onset and the first chest CT. The proportion of GGO with consolidation/consolidation and air bronchogram sign gradually increased when the interval was more than 4 days. The proportion of GGO with consolidation/consolidation and air bronchogram sign gradually increased when the interval was more than 4 days. The highest proportion (95.4%) of crazy-paving sign appeared within the interval of 5-9 days, after which the proportion decreased. The frequency of irregular linear opacities, the proportion of pleural thickening and pleural effusion increased in patients with an interval more than 14 days. The median times to occurrence of GGO, GGO with crazy-paving sign, GGO with consolidation or consolidation and irregular linear opacities respectively were 4 days (2 days, 7 days), 9 days (7 days, 11 days), 13 days (10 days, 16 days) and 16 days (13 days, 19 days). Conclusions: Chest CT can reflect the distribution, morphology, dynamic imaging development and outcome of lesions in patients infected with SARS-CoV-2 Omicron variant, which is helpful for clinical treatment decision-making and efficacy evaluation.

Tomatoes are one of the most widely cultivated vegetables in China and are popular among consumers. In recent years, as the demand for healthy food has grown, the quality of tomatoes has aroused increasing attention. While tomatoes are generally uniform in shape, there are significant differences in size, fruit type and color among tomato varieties, and tomatoes contain a variety of nutrients with complex chemical structures, so its quality is difficult to assess. The traditional tomato quality testing methods are subjective, destructive, time-consuming and laborious, and thus cannot meet the demand of large-scale quality testing. Recently, with the development of non-destructive testing technologies, new detection methods such as machine learning, multispectral techniques, and electronic nose/electronic tongue have been developed and applied for the rapid and non-destructive testing of tomato quality. This paper provides a summary of the development and application of artificial intelligence based on image recognition, electronic nose technology and spectroscopic technologies for the non-destructive testing of tomatoes in order to provide a reference for future research and development of tomato quality inspection.