Development of high-throughput tissue culture-free plant transformation systems.

Efficient transformation systems are highly desirable for plant genetic research and biotechnology product development efforts. Tissue culture-free transformation (TCFT) and minimal tissue culture transformation (MTCT) systems have great potential in addressing genotype-dependency challenge, shortening transformation timeline, and improving operational efficiency by greatly reducing personnel and supply costs. The development of Arabidopsis floral dip transformation method almost 3 decades ago has greatly expedited plant genomic research.

Water demand forecasting in multiple district metered areas based on a multi-scale correction module neural network architecture.

Short-term water demand forecasting (STWDF) for multiple spatially and temporally correlated District Metering Areas (DMAs) is an essential foundation for achieving more refined management of urban water supply networks. However, due to the greater uncertainty associated with specific DMA demand compared to overall water usage, accurately predicting STWDF poses significant challenges. This study introduces an innovative network architecture-the multi-scale correction module neural network, built upon Long Short-Term Memory (LSTM) networks and Convolutional Neural Networks (CNN) enhanced with Attention mechanisms-for simultaneous STWDF with a temporal resolution of one hour over a week for 10 DMAs located in a single city in northern Italy.

Urban stormwater discharge contributes more micropollutants to surface water in humid regions of China: Comparison with treated wastewater.

Micropollutants have raised increasing concern due to their adverse effect on ecosystems and human health. So far, the effects of micropollutants in urban stormwater discharge on surface water quality or ecosystem health remains unclear. In this study, target and non-target screening methods were used to quantify and identify micropollutants in urban stormwater, wastewater, and surface water in humid regions of China.

The correlation between patients with type 2 diabetes mellitus and chronic microvascular complications during the glucose peak time.

Introduction: To assess the Type 2 Diabetes Mellitus (T2DM) patients in association with Chronic Microvascular Complications at Glucose Peak Time and the association among chronic microvascular complications in T2DM patients and the glucose peak period in the typical steamed bread meal test.

Methods: Overall 1095 T2DM patients were classified as three groups: (1) Group G1: glucose peak time ≤ 1 h (n = 84), Group G2: 1 h < glucose peak time ≤ 2 h (n = 648) and Group G3: glucose peak time > 2 h (n = 363). The clinical characteristics, insulin characteristics and glucose peak time and chronic microvascular complications markers of patients in each group was analyzed and compared.