Safety of a 90-min duration of intravenous infusion of obinutuzumab in patients with B-cell non-Hodgkin's lymphoma in a tertiary hospital in China: a prospective, open-label, exploratory clinical trial.

This study aimed to analyze the safety and applicability of a 90-min duration of infusion (SDI) of obinutuzumab in patients with B-cell non-Hodgkin's lymphoma (NHL) in a tertiary hospital in China. This exploratory clinical trial was performed at Jiangsu Province Hospital. All patients were treated with the standard infusion regimen for the first infusion. If no grade ≥3 infusion-related reactions (IRRs) occurred, the subsequent infusions were given as SDI. The primary endpoint was the incidence of IRR during the standard infusion (3-4 h) and 90-min SDI regimens. This study enrolled 208 patients and all completed cycle 1. Forty-one patients (19.71%) had IRRs: five (2.40%) with grade 1, twenty-eight (13.46%) with grade 2, and eight (3.85%) with grade 3. The 41 patients had 71 IRRs, mainly fever (40.85%), chest pain/tightness (12.68%), and dyspnea (9.86%). The occurrence of IRRs in the first infusion was significantly lower in patients who received oral acetaminophen prophylaxis than those who did not (10.72% vs 30.21%, P<0.001). For the subsequent cycles with 90-min SDI, only two (0.25%) IRRs occurred among 814 infusions (one grade 1 hand numbness and one grade 2 chill/fever). The 90-min obinutuzumab SDI might be safe and feasible in patients with B-cell NHL in China.

Safety of a 90-min duration of intravenous infusion of obinutuzumab in patients with B-cell non-Hodgkin's lymphoma in a tertiary hospital in China: a prospective, open-label, exploratory clinical trial

This study aimed to analyze the safety and applicability of a 90-min duration of infusion (SDI) of obinutuzumab in patients with B-cell non-Hodgkin's lymphoma (NHL) in a tertiary hospital in China. This exploratory clinical trial was performed at Jiangsu Province Hospital. All patients were treated with the standard infusion regimen for the first infusion. If no grade ≥3 infusion-related reactions (IRRs) occurred, the subsequent infusions were given as SDI. The primary endpoint was the incidence of IRR during the standard infusion (3-4 h) and 90-min SDI regimens. This study enrolled 208 patients and all completed cycle 1. Forty-one patients (19.71%) had IRRs: five (2.40%) with grade 1, twenty-eight (13.46%) with grade 2, and eight (3.85%) with grade 3. The 41 patients had 71 IRRs, mainly fever (40.85%), chest pain/tightness (12.68%), and dyspnea (9.86%). The occurrence of IRRs in the first infusion was significantly lower in patients who received oral acetaminophen prophylaxis than those who did not (10.72% vs 30.21%, P<0.001). For the subsequent cycles with 90-min SDI, only two (0.25%) IRRs occurred among 814 infusions (one grade 1 hand numbness and one grade 2 chill/fever). The 90-min obinutuzumab SDI might be safe and feasible in patients with B-cell NHL in China.

Efficient Windows malware identification and classification scheme for plant protection information systems.

Due to developments in science and technology, the field of plant protection and the information industry have become increasingly integrated, which has resulted in the creation of plant protection information systems. Plant protection information systems have modernized how pest levels are monitored and improved overall control capabilities. They also provide data to support crop pest monitoring and early warnings and promote the sustainable development of plant protection networks, visualization, and digitization. However, cybercriminals use technologies such as code reuse and automation to generate malware variants, resulting in continuous attacks on plant protection information terminals. Therefore, effective identification of rapidly growing malware and its variants has become critical. Recent studies have shown that malware and its variants can be effectively identified and classified using convolutional neural networks (CNNs) to analyze the similarity between malware binary images. However, the malware images generated by such schemes have the problem of image size imbalance, which affects the accuracy of malware classification. In order to solve the above problems, this paper proposes a malware identification and classification scheme based on bicubic interpolation to improve the security of a plant protection information terminal system. We used the bicubic interpolation algorithm to reconstruct the generated malware images to solve the problem of image size imbalance. We used the Cycle-GAN model for data augmentation to balance the number of samples among malware families and build an efficient malware classification model based on CNNs to improve the malware identification and classification performance of the system. Experimental results show that the system can significantly improve malware classification efficiency. The accuracy of RGB and gray images generated by the Microsoft Malware Classification Challenge Dataset (BIG2015) can reach 99.76% and 99.62%, respectively.