Differentiating the Invasiveness of Lung Adenocarcinoma Manifesting as Ground Glass Nodules: Combination of Dual-energy CT Parameters and Quantitative-semantic Features.

RATIONALE AND OBJECTIVES: To evaluate the diagnostic performance of dual-energy CT (DECT) parameters and quantitative-semantic features for differentiating the invasiveness of lung adenocarcinoma manifesting as ground glass nodules (GGNs). MATERIALS AND METHODS: Between June 2022 and September 2023, 69 patients with 74 surgically resected GGNs who underwent DECT examinations were included. CT numbers on virtual monochromatic images were calculated at 40-130 keV generated from DECT. Quantitative morphological measurements and semantic features were evaluated on unenhanced CT images and compared between pathologically confirmed adenocarcinoma in situ (AIS)-minimally invasive adenocarcinoma (MIA) and invasive lung adenocarcinoma (IAC). Multivariable logistic regression analysis was used to identify independent predictors. The diagnostic performance was assessed by the area under the receiver operating characteristic curve (AUC) and compared using DeLong's test. RESULTS: Monochromatic CT numbers at 40-130 keV were significantly higher in IAC than in AIS-MIA (all P < 0.05). Multivariate logistic analysis revealed that CT number of 130 keV (odds ratio [OR] = 1.02, P = 0.013), maximum cross-sectional long diameter (OR =1.40, P = 0.014), deep or moderate lobulation sign (OR =19.88, P = 0.005), and abnormal intranodular vessel morphology (OR = 25.57, P = 0.017) were independent predictors of IAC. The combined prediction model showed a favorable differentiation performance with an AUC of 0.966 (95.2% sensitivity, 94.3% specificity, 94.8% accuracy), which was significantly higher than that for each risk factor (AUC = 0.791-0.822, all P < 0.05). CONCLUSION: A multi-parameter combined prediction model integrating monochromatic CT numbers from DECT and quantitative-semantic features is promising for the preoperative discrimination of IAC and AIS-MIA in GGN-predominant lung adenocarcinoma.

Identification of D/Yama2019 Lineage-Like Influenza D Virus in Chinese Cattle.

Outbreaks of influenza D virus (IDV) continue to be reported in many countries. On the basis of the hemagglutinin-esterase fusion (HEF) gene, five IDV genetic lineages have been identified: D/OK, D/660, D/Yama2016, D/Yama2019 and D/CA2019 lineages. Previously reported IDV strains in China all form a sub-clade (D/China sub-lineage) within D/OK lineage. From October 2021 to February 2022, nasal swab samples (n = 250) were collected from apparently healthy cattle in slaughterhouses around the city of Guangzhou, China, and screened for IDV by RT-PCR. Ten samples were positive for IDV. An IDV strain with nearly complete genome sequences was identified and designated as D/bovine/CHN/JY3001/2021. Importantly, sequence alignments and phylogenetic analyses revealed that this IDV strain is genetically close to the strains (>98% homology) in the D/Yama2019 lineage that has been found only in Japan, but distant from the previously reported Chinese IDV strains (~95% similarity). These results demonstrate the emergence of D/Yama2019 lineage IDV in Chinese cattle herds, highlighting a need for future surveillance of D/Yama2019-like viruses toward better understanding both epidemiology and diversity of IDV in China.

A hybrid and scalable brain-inspired robotic platform.

Recent years have witnessed tremendous progress of intelligent robots brought about by mimicking human intelligence. However, current robots are still far from being able to handle multiple tasks in a dynamic environment as efficiently as humans. To cope with complexity and variability, further progress toward scalability and adaptability are essential for intelligent robots. Here, we report a brain-inspired robotic platform implemented by an unmanned bicycle that exhibits scalability of network scale, quantity and diversity to handle the changing needs of different scenarios. The platform adopts rich coding schemes and a trainable and scalable neural state machine, enabling flexible cooperation of hybrid networks. In addition, an embedded system is developed using a cross-paradigm neuromorphic chip to facilitate the implementation of diverse neural networks in spike or non-spike form. The platform achieved various real-time tasks concurrently in different real-world scenarios, providing a new pathway to enhance robots' intelligence.

Synergistic anticancer effect of rAd/P53 combined with 5-fluorouracil or iodized oil in the early therapeutic response of human colon cancer in vivo.

Exogenous wild-type p53 (wt-p53) tumor suppression increases the sensitivity of tumor cells to radiotherapy and chemotherapy. An iodized oil emulsion was used as a p53 vector for intra-arterial gene delivery to treat hepatic tumors. Whether the chemotherapeutic agent or the iodized oil affects exogenous wt-p53 activity remains poorly understood. In the present study, the early therapeutic response of rAd/p53, combined with 5-fluorouracil (5-FU) or with iodized oil, was observed in a human colon cancer model. Allograft models in 82 nude mice with human colon carcinoma SW480 were divided randomly into four groups and administered with physiologic saline, rAd/p53, rAd/p53+5-FU, and rAd/p53+iodized oil by intratumoral injection. At 24, 48, 72, 120, and 168 h after treatment, p53 expression, the Ki-67 index (KI), and the degree of tumor necrosis were assessed. The p53 expression and tumor necrosis in the therapeutic groups were higher than those in the control group. p53 expression reached its peak at 120 h in the rAd/p53 group, at 72 h in the rAd/p53+5-FU group, and at 48 h in the rAd/p53+iodized oil group. The p53 expression in the rAd/P53+5-FU group and the iodized oil group was significantly higher than those in the rAd/P53 group at 24 and 48 h. The results revealed that tumor necrosis is positively correlated with p53 expression. The KI of the rAd/p53+5-FU group increased significantly at 24 h. 5-FU and iodized oil increase the anticancer effect of rAd/p53, and 5-FU combined with rAd/p53 has a synergistic anticancer effect.