Electrocatalytic nitrate reduction using iron single atoms for sustainable ammonium supplies to increase rice yield.

Increasing food production and ensuring drinking water safety have always been a focus of attention, especially for people in underdeveloped regions of the world. Traditional excessive fertilizer applications have increased crop yield but also caused groundwater nitrate pollution. Agricultural irrigating water is an important reservoir for nitrogen (N) (e.

A self-sustaining effect induced by iron sulfide generation and reuse in pyrite-woodchip mixotrophic bioretention systems: An experimental and modeling study.

Dual electron donor bioretention systems have emerged as a popular strategy to enhance dissolved nitrogen removal from stormwater runoff. Pyrite-woodchip mixotrophic bioretention systems showed a promoted and stabilized removal of dissolved nutrients under complex rainfall conditions, but the sulfate reduction process that can induce iron sulfide generation and reuse was overlooked. In this study, experiments and models were applied to investigate the effects of filler configuration and dissolved organic carbon (DOC) dissolution rate on treatment performance and iron sulfide generation in pyrite-woodchip bioretention systems.

Diverse metabolism drives comammox in continental-scale agricultural streams: Important ammonia oxidation but low NO production.

Agriculture receives approximately 25 % of the annual global nitrogen input, 37 % of which subsequently runs off into adjacent low-order streams and surface water, where it may contribute to high nitrification and nitrous oxide (NO). However, the mechanisms of nitrification and the pathways controlling NO production in agricultural streams remain unknown. Here, we report that the third microbial ammonia oxidation process, complete ammonia oxidation (comammox), is widespread and contributes to important ammonia oxidation with low ammonia-NO conversion in both basin- and continental-scale agricultural streams.

Ammonium-derived nitrous oxide is a global source in streams.

Global riverine nitrous oxide (NO) emissions have increased more than 4-fold in the last century. It has been estimated that the hyporheic zones in small streams alone may contribute approximately 85% of these NO emissions. However, the mechanisms and pathways controlling hyporheic NO production in stream ecosystems remain unknown.

Machine learning-based identification of contrast-enhancement phase of computed tomography scans.

Contrast-enhanced computed tomography scans (CECT) are routinely used in the evaluation of different clinical scenarios, including the detection and characterization of hepatocellular carcinoma (HCC). Quantitative medical image analysis has been an exponentially growing scientific field. A number of studies reported on the effects of variations in the contrast enhancement phase on the reproducibility of quantitative imaging features extracted from CT scans.

Aptamer-based nanointerferometer enables amplification-free ultrasensitive detection and differentiation of SARS-CoV-2 variants.

The state-of-the-art SARS-CoV-2 detection methods include qRT-PCR and antibody-based lateral flow assay (LFA) point-of-care tests. Despite the high sensitivity and selectivity, qRT-PCR is slow, expensive and needs well-trained operators. On the other extreme, LFA suffers from low sensitivity albeit its fast detection speed, low detection cost and ease of use.

PUNDIT: Pulmonary nodule detection with image category transformation.

Background: Convolutional neural networks (CNNs) have achieved great success in pulmonary nodules detection, which plays an important role in lung cancer screening.

Purpose: In this paper, we proposed a novel strategy for pulmonary nodule detection by learning it from a harder task, which was to transform nodule images into normal images. We named this strategy as pulmonary nodule detection with image category transformation (PUNDIT).

Corncob-pyrite bioretention system for enhanced dissolved nutrient treatment: Carbon source release and mixotrophic denitrification.

Solid biomass waste amendment and substrates modification in bioretention systems have been increasingly used to achieve effective dissolved nutrients pollution control in stormwater runoff. However, the risk of excess chemical oxygen demand (COD) leaching from organic carbon sources is often overlooked on most occasions. Pyrite is an efficient electron donor for autotrophic denitrification, but little is known about the efficacy of autotrophic-heterotrophic synergistic effect between additional carbon source and pyrite in bioretention.

Distinguishing benign and malignant lesions on contrast-enhanced breast cone-beam CT with deep learning neural architecture search.

Purpose: To utilize a neural architecture search (NAS) approach to develop a convolutional neural network (CNN) method for distinguishing benign and malignant lesions on breast cone-beam CT (BCBCT).

Method: 165 patients with 114 malignant and 86 benign lesions were collected by two institutions from May 2012 to August 2014. The NAS method autonomously generated a CNN model using one institution's dataset for training (patients/lesions: 71/91) and validation (patients/lesions: 20/23).

Burden and etiology of moderate and severe diarrhea in children less than 5 years of age living in north and south of China: Prospective, population-based surveillance.

Background: Diarrhea remains the leading cause of childhood illness in China. Better understanding of burden and etiology of diarrheal diseases is important for development of effective prevention measures.

Methods: Population-based diarrhea surveillance was conducted in Sanjiang (southern China) year-round and Zhengding (northern China) in autumn/winter.

Using a single abdominal computed tomography image to differentiate five contrast-enhancement phases: A machine-learning algorithm for radiomics-based precision medicine.

Purpose: The clinical adoption of quantitative imaging biomarkers (radiomics) has established the need for high quality contrast-enhancement in medical images. We aimed to develop a machine-learning algorithm for Quality Control of Contrast-Enhancement on CT-scan (CECT-QC).

Method: Multicenter data from four independent cohorts [A, B, C, D] of patients with measurable liver lesions were analyzed retrospectively (patients:time-points; 503:3397): [A] dynamic CTs from primary liver cancer (60:2359); [B] triphasic CTs from primary liver cancer (31:93); [C] triphasic CTs from hepatocellular carcinoma (121:363); [D] portal venous phase CTs of liver metastasis from colorectal cancer (291:582).

Immune response to different types of hepatitis B vaccine booster doses 2-32 years after the primary immunization schedule and its influencing factors.

Objective: To assess the immune effect of different types of hepatitis B vaccine (HepB) booster doses 2-32 years after primary immunization, explore the influencing factors, and offer guidance regarding the necessity and timing of boosters.

Methods: In total, 1163 participants who were born from 1986 to 2015, received the HepB full-course primary vaccination, were hepatitis B surface antigen (HBsAg) and hepatitis B core antibody (anti-HBc) negative, and had hepatitis B surface antibody (anti-HBs) <10 mIU/mL were enrolled. Individuals were randomly divided into two groups and received a booster dose of HepB.

Long-term protection at 20-31 years after primary vaccination with plasma-derived hepatitis B vaccine in a Chinese rural community.

: To assess the long-term protection conferred by plasma-derived hepatitis B vaccine at 20-31y after primary immunization during infancy in Chinese rural community.: Participants born between 1986 and 1996, who received a full course of primary vaccination with plasma-derived hepatitis B vaccine and had no experience with booster vaccination were enrolled. An epidemiological investigation was performed, and blood samples were collected to detect hepatitis B surface antigen (HBsAg), hepatitis B surface antibody (anti-HBs), and hepatitis B core antibody (anti-HBc).

Automated Identification of Optimal Portal Venous Phase Timing with Convolutional Neural Networks.

Objectives: To develop a deep learning-based algorithm to automatically identify optimal portal venous phase timing (PVP-timing) so that image analysis techniques can be accurately performed on post contrast studies.

Methods: 681 CT-scans (training: 479 CT-scans; validation: 202 CT-scans) from a multicenter clinical trial in patients with liver metastases from colorectal cancer were retrospectively analyzed for algorithm development and validation. An additional external validation was performed on a cohort of 228 CT-scans from gastroenteropancreatic neuroendocrine cancer patients.

Immune persistence 17 to 20 years after primary vaccination with recombination hepatitis B vaccine (CHO) and the effect of booster dose vaccination.

Background: To assess the immune persistence conferred by a Chinese hamster ovary (CHO)-derived hepatitis B vaccine (HepB) 17 to 20 years after primary immunization during early life.

Methods: Participants born between 1997 and 1999 who received a full course of primary vaccination with HepB (CHO) and who had no experience with booster vaccination were enrolled. Blood samples were required from each participant for measurement of hepatitis B surface antibody (anti-HBs), surface antigen and core antibody levels.

Improved False Positive Reduction by Novel Morphological Features for Computer-Aided Polyp Detection in CT Colonography.

Computer-aided detection (CAD) systems can assist radiologists in reducing the interpretation time and improving the detection results in computed tomographic colonography (CTC). However, existing false positives (FPs) impair the advantages of CAD systems. This study aims to develop new morphological features for the FP reduction while maintaining high detection sensitivity.

The Role of PET-Based Radiomic Features in Predicting Local Control of Esophageal Cancer Treated with Concurrent Chemoradiotherapy.

This study was designed to evaluate the predictive performance of F-fluorodeoxyglucose positron emission tomography (PET)-based radiomic features for local control of esophageal cancer treated with concurrent chemoradiotherapy (CRT). For each of the 30 patients enrolled, 440 radiomic features were extracted from both pre-CRT and mid-CRT PET images. The top 25 features with the highest areas under the receiver operating characteristic curve for identifying local control status were selected as discriminative features.

Investigation of NO conversion by different types of sewage sludge chars under low temperature.

Different types of sludge chars, i.e. the original (S1), HNO washed (S2), KOH activated (S3), and H reduced chars, were prepared to investigate their performances for NO conversion under low temperature.