All-in-One: Plasmonic Janus Heterostructures for Efficient Cooperative Photoredox Catalysis.

Janus heterostructures consisting of multiple jointed components with distinct properties have gained growing interest in the photoredox catalytic field. Herein, we have developed a facile low-temperature method to gain anisotropic one-dimensional Au-tipped CdS (Au-CdS) nanorods (NRs), followed by assembling Ru molecular co-catalyst (RuN5) onto the surface of the NRs. The CdS NRs decorated with plasmonic Au nanoparticles (NPs) and RuN5 complex harness the virtues of metal-semiconductor and inorganic-organic interface, giving directional charge transfer channels, spatially separated reaction sites, and enhanced local electric field distribution. As a result, the Au-CdS-RuN5 can act as an efficient dual-function photocatalyst for simultaneous H2 evolution and valorization of biomass-derived alcohols. Benefiting from the interfacial charge decoupling and selective chemical bond activation, the optimal all-in-one Au-CdS-RuN5 heterostructure shows greatly enhanced photoactivity and selectivity as compared to bare CdS NRs, along with a remarkable apparent quantum yield of 40.2 % at 400 nm. The structural evolution and working mechanism of the heterostructures are systematically analyzed based on experimental and computational results.

An automated two-stage approach to kidney and tumor segmentation in CT imaging.

BACKGROUND: The incidence of kidney tumors is progressively increasing each year. The precision of segmentation for kidney tumors is crucial for diagnosis and treatment. OBJECTIVE: To enhance accuracy and reduce manual involvement, propose a deep learning-based method for the automatic segmentation of kidneys and kidney tumors in CT images. METHODS: The proposed method comprises two parts: object detection and segmentation. We first use a model to detect the position of the kidney, then narrow the segmentation range, and finally use an attentional recurrent residual convolutional network for segmentation. RESULTS: Our model achieved a kidney dice score of 0.951 and a tumor dice score of 0.895 on the KiTS19 dataset. Experimental results show that our model significantly improves the accuracy of kidney and kidney tumor segmentation and outperforms other advanced methods. CONCLUSION: The proposed method provides an efficient and automatic solution for accurately segmenting kidneys and renal tumors on CT images. Additionally, this study can assist radiologists in assessing patients' conditions and making informed treatment decisions.

Enhancing the health benefits of air quality improvement: a comparative study across diverse scenarios.

In many studies, linear methods were used to calculate health benefits of air quality improvement, but the relationship between air pollutants and diseases may be complex and nonlinear. In addition, previous studies using reference number as average number of diseases may overestimate the health benefits. Therefore, the nonlinear model estimation and resetting of the reference number were very important. Hospital admission data for coronary heart disease (CHD), meteorological data, and air pollutant data of Zibo City from 2015 to 2019 were collected. The generalized additive model (GAM) was used to explore the association between air pollutants and hospital admission for CHD, and to evaluate the effects on health benefits under different reference number settings. A total of 21,105 hospitalized cases for CHD were reported in Zibo during the study period. The results of the GAM showed there was a log-linear exposure-response relationship between O3 and hospital admissions for CHD, with RR (relative risk) of 1.0143 (95% CI: 1.0047 ~ 1.0239). There were log-nonlinear exposure-response relationships between PM10, PM2.5, SO2, and hospital admissions for CHD. With the increase of pollutants concentrations, the risk for hospital admission showed a trend of increasing first and then decreasing. Compared with the average hospital admissions as the reference number, health benefits calculated by hospital admissions predicted by the GAM model yielded lower. Using the World Health Organization air quality guidelines as reference, attributable fractions of O3, PM10, and PM2.5 were 1.97% (95% CI: 0.63 ~ 3.40%), 11.82% (95% CI: 8.60 ~ 15.24%), and 11.82% (95% CI: 8.79 ~ 15.04%), respectively. When quantifying health benefits brought by improving air quality, corresponding calculation methods should first be determined according to the exposure-response relationships between air pollutants and outcomes. Then, applying the average hospital admissions as reference number may overestimate health benefits resulting from improved air quality.

Soil selenium enhanced the resistance of oilseed rape to Sclerotinia sclerotiorum by optimizing the plant microbiome.

Plant can recruit beneficial microbes to enhance their ability to resist disease. Selenium is well established as a beneficial element in plant growth, but its role in mediating microbial disease resistance remained poorly understood. Here, we investigated the correlation between selenium, oilseed rape rhizosphere microbes and Sclerotinia sclerotiorum. Soil application of 0.5 and 1.0 mg/kg selenium significantly increased the resistance of oilseed rape to Sclerotinia sclerotiorum compared with no selenium application, and the disease inhibition rate was higher than 20%. The disease resistance of oilseed rape was related to rhizosphere microorganisms, and beneficial bacteria isolated from the rhizosphere inhibited Sclerotinia stem rot. Burkholderia cepacia, and synthetic community enhanced plant disease resistance through transcriptional regulation and activated plant-induced systemic resistance to protect plants. Besides, inoculation of isolated bacteria optimized the bacterial community structure of leaves and enriched beneficial microorganisms such as Bacillus, Pseudomonas and Sphingomonas. Bacillus isolated from the leaves were sprayed on the detached leaves, and it also performed a significant inhibition effect on Sclerotinia sclerotiorum. Overall, our results suggested that selenium drive plant rhizosphere microorganisms to increase resistance to Sclerotinia sclerotiorum in oilseed rape.

Transcriptome analysis and development of EST-SSR markers in the mushroom Auricularia heimuer.

Auricularia heimuer, the third most frequently cultivated edible mushroom species worldwide, has high medicinal value. However, a shortage of molecular marker hinders the efficiency and accuracy of genetic breeding efforts for A. heimuer. High-throughput transcriptome sequencing data are essential for gene discovery and molecular markers development. This study aimed to clarify the distribution of SSR loci across the A. heimuer transcriptome and to develop highly informative EST-SSR markers. These tools can be used for phylogenetic analysis, functional gene mining, and molecular marker-assisted breeding of A. heimuer. This study used Illumina high-throughput sequencing technology to obtain A. heimuer transcriptome data. The results revealed 37,538 unigenes in the A. heimuer transcriptome. Of these unigenes, 24,777 (66.01%) were annotated via comparison with the COG, Pfam, and NR databases. Overall, 2510 SSRs were identified from the unigenes, including 6 types of SSRs. The most abundant type of repeats were trinucleotides (1425, 56.77%), followed by mononucleotides (391, 15.58%) and dinucleotides (456, 18.17%). Primer pairs for 102 SSR loci were randomly designed for validity confirmation and polymorphism identification; this process yielded 53 polymorphic EST-SSR markers. Finally, 13 pairs of highly polymorphic EST-SSR primers were used to analyze the genetic diversity and population structure of 52 wild A. heimuer germplasms, revealing that the 52 germplasms could be divided into three categories. These results indicated that SSR loci were abundant in types, numbers, and frequencies, providing a potential basis for germplasm resource identification, genetic diversity analysis, and molecular marker-assisted breeding of A. heimuer.

Efficient electrocardiogram generation based on cardiac electric vector simulation model.

This study introduces a novel Cardiac Electric Vector Simulation Model (CEVSM) to address the computational inefficiencies and low fidelity of traditional electrophysiological models in generating electrocardiograms (ECGs). Our approach leverages CEVSM to efficiently produce reliable ECG samples, facilitating data augmentation essential for the computer-aided diagnosis of myocardial infarction (MI). Significantly, experimental results show that our model dramatically reduces computation time compared to conventional models, with the self-adapting regression transformation matrix method (SRTM) providing clear advantages. SRTM not only achieves high fidelity in ECG simulations but also ensures exceptional consistency with the gold standard method, greatly enhancing MI localization accuracy by data augmentation. These advancements highlight the potential of our model to generate dependable ECG training samples, making it highly suitable for data augmentation and significantly advancing the development and validation of intelligent MI diagnostic systems. Furthermore, this study demonstrates the feasibility of applying life system simulations in the training of medical big models.

Fish sonar image recognition algorithm based on improved YOLOv5.

Fish stock assessment is crucial for sustainable marine fisheries management in rangeland ecosystems. To address the challenges posed by the overfishing of offshore fish species and facilitate comprehensive deep-sea resource evaluation, this paper introduces an improved fish sonar image detection algorithm based on the you only look once algorithm, version 5 (YOLOv5). Sonar image noise often results in blurred targets and indistinct features, thereby reducing the precision of object detection. Thus, a C3N module is incorporated into the neck component, where depth-separable convolution and an inverse bottleneck layer structure are integrated to lessen feature information loss during downsampling and forward propagation. Furthermore, lowercase shallow feature layer is introduced in the network prediction layer to enhance feature extraction for pixels larger than $ 4 \times 4 $. Additionally, normalized weighted distance based on a Gaussian distribution is combined with Intersection over Union (IoU) during gradient descent to improve small target detection and mitigate the IoU's scale sensitivity. Finally, traditional non-maximum suppression (NMS) is replaced with soft-NMS, reducing missed detections due to occlusion and overlapping fish targets that are common in sonar datasets. Experiments show that the improved model surpasses the original model and YOLOv3 with gains in precision, recall and mean average precision of 2.3%, 4.7% and 2.7%, respectively, and 2.5%, 6.3% and 6.7%, respectively. These findings confirm the method's effectiveness in raising sonar image detection accuracy, which is consistent with model comparisons. Given Unmanned Underwater Vehicle advancements, this method holds the potential to support fish culture decision-making and facilitate fish stock resource assessment.

Effects of extreme temperature events on deaths and its interaction with air pollution.

BACKGROUND: Both extreme temperature events (ETEs) and air pollution affected human health, and their effects were often not independent. Previous studies have provided limited information on the interactions between ETEs and air pollution. METHODS: We collected data on deaths (non-accidental, cardiovascular, and respiratory) in Zibo City along with daily air pollution and meteorological data from January 2015 to December 2019. Distributed lag non-linear model was used to explore the health effects of ETEs on deaths. Non-parametric binary response model, hierarchical model and joint effect model were used to further explore the interaction between ETEs and air pollution in different seasons. Meanwhile, subgroup analysis by gender and age (≥ 65 years old and < 65 years old) was conducted to identify the vulnerable population. RESULTS: ETEs increased death risk, especially for cardiovascular and respiratory deaths. Heat waves had a stronger impact than cold spells. Cold spells had a longer lag and fluctuating trend. Heat waves had a short-term impact, followed by a decrease. Females and those aged ≥ 65 were more affected, but subgroup differences were not significant. During ETEs and non-ETEs, there were different effects on deaths with per IQR increase in air pollutant concentrations. Joint effect models revealed that there was a significant interaction between ETEs and air pollution on non-accidental deaths. The interaction between PM2.5 and cold spells was antagonistic in the cold season. In the warm season, the health effects of heat waves and high O3 concentration were enhanced. The relative excess risk due to interaction (RERI) of cold spells and PM2.5 in total population was -0.09 (95 % CI: -0.17, -0.01), and 9 % (95 % CI: 1 %, 17 %) of the total effect was attributable to interaction. Subgroup analysis confirmed the interactions in females and those aged ≥ 65. CONCLUSIONS: Significant association observed between ETEs and deaths. Females and ≥ 65 age groups were vulnerable. There were interactions between ETEs and air pollution. The effect of PM2.5 on deaths decreased during cold spells, while the effect of O3 increased during heat waves. In addition to improving air quality, it is necessary to further strengthen the prevention and control of ETEs.

Microencapsulated Limosilactobacillus reuteri Encoding Lactoferricin-Lactoferrampin Targeted Intestine against Salmonella typhimurium Infection.

Salmonella enterica serovar Typhimurium (S. typhimurium) is an important foodborne pathogen that infects both humans and animals and develops acute gastroenteritis. As porcine intestines are relatively similar to the human ones due to their relatively similar sizes and structural similarity, S. typhimurium causes analogous symptoms in both. Novel strategies for controlling S. typhimurium infection are also desired, such as mucosal-targeted delivery of probiotics and antimicrobial peptides. The bovine lactoferricin-lactoferrampin-encoding Limosilactobacillus reuteri (LR-LFCA) strain improves intestinal barrier function by strengthening the intestinal barrier. Weaned piglets were selected for oral administration of microencapsulated LR-LFCA (microcapsules entrap LR-LFCA into gastro-resistant polymers) and then infected with S. typhimurium for 3 days. We found that orally administering microencapsulated LR-LFCA to weaned piglets attenuated S. typhimurium-induced production of inflammatory factors in the intestinal mucosa by inhibiting the nuclear factor-kappa B (NF-κB) and P38 mitogen-activated protein kinases (MAPK) signaling pathway. Moreover, microencapsulated LR-LFCA administration significantly suppressed the oxidative stress that may correlate with gut microbiota (reduced Salmonella population and increased α-diversity and Lactobacillus abundance) and intestinal function (membrane transport and metabolism). Our work demonstrated that microencapsulated LR-LFCA effectively targeted intestine delivery of Lactobacillus and antimicrobial peptides and modulated gut microbiota and mucosal immunity. This study reveals a novel targeting mucosal strategy against S. typhimurium infection.