Rice Under Dry Cultivation-Maize Intercropping Improves Soil Environment and Increases Total Yield by Regulating Belowground Root Growth.

Under the one-season-a-year cropping pattern in Northeast China, continuous cropping is one of the main factors contributing to the degradation of black soil. Previous studies (on maize-soybean, maize-peanut, and maize-wheat intercropping) have shown that intercropping can alleviate this problem. However, it is not known whether intercropping is feasible for maize and rice under dry cultivation, and its effects on yield and soil fertility are unknown.

Successive Years of Rice Straw Return Increased the Rice Yield and Soil Nutrients While Decreasing the Greenhouse Gas Intensity.

Straw return has important impacts on black soil protection, food security, and environmental protection. One year of straw return (S1) reduces rice yield and increases greenhouse gas (GHG) emissions. However, the effects of successive years of straw return on rice yield, soil nutrients, and GHG emissions in the northeast rice region are still unclear.

Building microbial consortia to enhance straw degradation, phosphorus solubilization, and soil fertility for rice growth.

Straw pollution and the increasing scarcity of phosphorus resources in many regions of China have had severe impacts on the growing conditions for crop plants. Using microbial methods to enhance straw decomposition rate and phosphorus utilization offers effective solutions to address these problems. In this study, a microbial consortium 6 + 1 (consisting of a straw-degrading bacterium and a phosphate-solubilizing bacterium) was formulated based on their performance in straw degradation and phosphorus solubilization.

Discrimination of ground-glass nodular lung adenocarcinoma pathological subtypes via transfer learning: A multicenter study.

Background: The surgical approach and prognosis for invasive adenocarcinoma (IAC) and minimally invasive adenocarcinoma (MIA) of the lung differ. However, they both manifest as identical ground-glass nodules (GGNs) in computed tomography images, and no effective method exists to discriminate them.

Methods: We developed and validated a three-dimensional (3D) deep transfer learning model to discriminate IAC from MIA based on CT images of GGNs.

Identification, characteristics and rice growth promotion of a highly efficient cellulolytic bacterial strain, ZJW-6, isolated from paddy soil in central China.

The microbial degradation of lignocellulose is the best way to treat straw, which has a broad application prospect. It is consistent with the idea of agricultural sustainable development and has an important impact on the utilization of biomass resources. To explore and utilize the microbial resources of lignocellulose degradation, 27 lignocellulose degrading strains were screened from 13 regions in China.

Preoperative prediction of tumor deposits in rectal cancer with clinical-magnetic resonance deep learning-based radiomic models.

Background: This study aimed to establish an effective model for preoperative prediction of tumor deposits (TDs) in patients with rectal cancer (RC).

Methods: In 500 patients, radiomic features were extracted from magnetic resonance imaging (MRI) using modalities such as high-resolution T2-weighted (HRT2) imaging and diffusion-weighted imaging (DWI). Machine learning (ML)-based and deep learning (DL)-based radiomic models were developed and integrated with clinical characteristics for TD prediction.

Effects of Continuous Straw Returning on Soil Functional Microorganisms and Microbial Communities.

This study examined the changes in soil enzymatic activity, microbial carbon source metabolic diversity, and straw decomposition rates in paddy fields treated with 1, 2, or 3 years of straw returning (SR1-SR3). The soil's ability to decompose straw and cellulolytic bacteria increased with the number of treatment years (1: 31.9% vs.

Predictive Efficacy of a Radiomics Random Forest Model for Identifying Pathological Subtypes of Lung Adenocarcinoma Presenting as Ground-Glass Nodules.

Purpose: To establish and verify the ability of a radiomics prediction model to distinguish invasive adenocarcinoma (IAC) and minimal invasive adenocarcinoma (MIA) presenting as ground-glass nodules (GGNs).

Methods: We retrospectively analyzed 118 lung GGN images and clinical data from 106 patients in our hospital from March 2016 to April 2019. All pathological classifications of lung GGN were confirmed as IAC or MIA by two pathologists.

Construction of dominant rice population under dry cultivation by seeding rate and nitrogen rate interaction.

This study used the rice cultivar Suijing 18 to investigate the effects of morphological characteristics, photosynthetic changes, yield, as well as nitrogen absorption and utilization. The interaction between seeding rate and nitrogen rate was also assessed to identify the most suitable values of the dominant population for both factors under dry cultivation. Furthermore, the photosynthetic physiological characteristics of the upper three leaves in the dominant population were also explored.