The Plaque Analysis Classifies the Coronary Artery Disease-Reporting and Data System (CAD-RADS) Stenosis and Plaque Burden Categories: Association of the Plaque Features, Fat Attenuation Index, Coronary Computed Tomography Fractional Flow Reserve, and the Combination of Stenosis and Calcification.

BACKGROUND: The coronary artery disease-reporting and data system (CAD-RADS) 2.0 is used to standardize the reporting of coronary computed tomography angiography (CCTA) results. Artificial intelligence software can quantify the plaque composition, fat attenuation index, and fractional flow reserve. OBJECTIVE: To analyze plaque features of varying severity in patients with a combination of CAD-RADS stenosis and plaque burden categorization and establish a random forest classification model. METHODS: The data of 100 patients treated between April 2021 and February 2022 were retrospectively collected. The most severe plaque observed in each patient was the target lesion. Patients were categorized into three groups according to CAD-RADS: CAD-RADS 1-2 + P0-2, CAD-RADS 3-4B + P0-2, and CAD-RADS 3-4B + P3-4. Differences and correlations between variables were assessed between groups. AUC, accuracy, precision, recall, and F1 score were used to evaluate the diagnostic performance. RESULTS: A total of 100 patients and 178 arteries were included. The differences of computed tomography fractional flow reserve (CT-FFR) (H = 23.921, p < 0.001), the volume of lipid component (H = 12.996, p = 0.002), the volume of fibro-lipid component (H = 8.692, p = 0.013), the proportion of lipid component volume (H = 22.038, p < 0.001), the proportion of fibro-lipid component volume (H = 11.731, p = 0.003), the proportion of calcification component volume (H = 11.049, p = 0.004), and plaque type (χ2 = 18.110, p = 0.001) was statistically significant. CONCLUSION: CT-FFR, volume and proportion of lipid and fibro-lipid components of plaques, the proportion of calcified components, and plaque type were valuable for CAD-RADS stenosis + plaque burden classification, especially CT-FFR, volume, and proportion of lipid and fibro-lipid components. The model built using the random forest was better than the clinical model (AUC: 0.874 vs. 0.647).

A wild rice CSSL population facilitated identification of salt tolerance genes and rice germplasm innovation.

Salt stress is one of the major factors that limits rice production. Therefore, identification of salt-tolerant alleles from wild rice is important for rice breeding. In this study, we constructed a set of chromosome segment substitution lines (CSSLs) using wild rice as the donor parent and cultivated rice Nipponbare (Nip) as the recurrent parent. Salt tolerance germinability (STG) was evaluated, and its association with genotypes was determined using this CSSL population. We identified 17 QTLs related to STG. By integrating the transcriptome and genome data, four candidate genes were identified, including the previously reported AGO2 and WRKY53. Compared with Nip, wild rice AGO2 has a structure variation in its promoter region and the expression levels were upregulated under salt treatments; wild rice WRKY53 also has natural variation in its promoter region, and the expression levels were downregulated under salt treatments. Wild rice AGO2 and WRKY53 alleles have combined effects for improving salt tolerance at the germination stage. One CSSL line, CSSL118 that harbors these two alleles was selected. Compared with the background parent Nip, CSSL118 showed comprehensive salt tolerance and higher yield, with improved transcript levels of reactive oxygen species scavenging genes. Our results provided promising genes and germplasm resources for future rice salt tolerance breeding.

Impact of ambient air pollution on colorectal cancer risk and survival: insights from a prospective cohort and epigenetic Mendelian randomization study.

BACKGROUND: This study investigates the associations between air pollution and colorectal cancer (CRC) risk and survival from an epigenomic perspective. METHODS: Using a newly developed Air Pollutants Exposure Score (APES), we utilized a prospective cohort study (UK Biobank) to investigate the associations of individual and combined air pollution exposures with CRC incidence and survival, followed by an up-to-date systematic review with meta-analysis to verify the associations. In epigenetic two-sample Mendelian randomization analyses, we examine the associations between genetically predicted DNA methylation related to air pollution and CRC risk. Further genetic colocalization and gene-environment interaction analyses provided different insights to disentangle pathogenic effects of air pollution via epigenetic modification. FINDINGS: During a median 12.97-year follow-up, 5767 incident CRC cases among 428,632 participants free of baseline CRC and 533 deaths in 2401 patients with CRC were documented in the UK Biobank. A higher APES score was associated with an increased CRC risk (HR, 1.03, 95% CI = 1.01-1.06; P = 0.016) and poorer survival (HR, 1.13, 95% CI = 1.03-1.23; P = 0.010), particularly among participants with insufficient physical activity and ever smokers (Pinteraction > 0.05). A subsequent meta-analysis of seven observational studies, including UK Biobank data, corroborated the association between PM2.5 exposure (per 10 µg/m3 increment) and elevated CRC risk (RR,1.42, 95% CI = 1.12-1.79; P = 0.004; I2 = 90.8%). Genetically predicted methylation at PM2.5-related CpG site cg13835894 near TMBIM1/PNKD and cg16235962 near CXCR5, and NO2-related cg16947394 near TMEM110 were associated with an increased CRC risk. Gene-environment interaction analysis confirmed the epigenetic modification of aforementioned CpG sites with CRC risk and survival. INTERPRETATION: Our study suggests the association between air pollution and CRC incidence and survival, underscoring the possible modifying roles of epigenomic factors. Methylation may partly mediate pathogenic effects of air pollution on CRC, with annotation to epigenetic alterations in protein-coding genes TMBIM1/PNKD, CXCR5 and TMEM110. FUNDING: Xue Li is supported by the Natural Science Fund for Distinguished Young Scholars of Zhejiang Province (LR22H260001), the National Nature Science Foundation of China (No. 82204019) and Healthy Zhejiang One Million People Cohort (K-20230085). ET is supported by a Cancer Research UK Career Development Fellowship (C31250/A22804). MGD is supported by the MRC Human Genetics Unit Centre Grant (U127527198).

Q negatively regulates wheat salt tolerance through directly repressing the expression of TaSOS1 and reactive oxygen species scavenging genes.

The Q transcription factor plays important roles in improving multiple wheat domestication traits such as spike architecture, threshability and rachis fragility. However, whether and how it regulates abiotic stress adaptation remain unclear. We found that the transcriptional expression of Q can be induced by NaCl and abscisic acid treatments. Using the q mutants generated by CRISPR/Cas9 and Q overexpression transgenic lines, we showed that the domesticated Q gene causes a penalty in wheat salt tolerance. Then, we demonstrated that Q directly represses the transcription of TaSOS1-3B and reactive oxygen species (ROS) scavenging genes to regulate Na+ and ROS homeostasis in wheat. Furthermore, we showed that wheat salt tolerance protein TaWD40 interacts with Q to competitively interfere with the interaction between Q and the transcriptional co-repressor TaTPL. Taken together, our findings reveal that Q directly represses the expression of TaSOS1 and some ROS scavenging genes, thus causing a harmful effect on wheat salt tolerance.

Initial experience with radiomics of carotid perivascular adipose tissue in identifying symptomatic plaque.

Background: Carotid atherosclerotic ischemic stroke threatens human health and life. The aim of this study is to establish a radiomics model of perivascular adipose tissue (PVAT) around carotid plaque for evaluation of the association between Peri-carotid Adipose Tissue structural changes with stroke and transient ischemic attack. Methods: A total of 203 patients underwent head and neck computed tomography angiography examination in our hospital. All patients were divided into a symptomatic group (71 cases) and an asymptomatic group (132 cases) according to whether they had acute/subacute stroke or transient ischemic attack. The radiomic signature (RS) of carotid plaque PVAT was extracted, and the minimum redundancy maximum correlation, recursive feature elimination, and linear discriminant analysis algorithms were used for feature screening and dimensionality reduction. Results: It was found that the RS model achieved the best diagnostic performance in the Bagging Decision Tree algorithm, and the training set (AUC, 0.837; 95%CI: 0.775, 0.899), testing set (AUC, 0.834; 95%CI: 0.685, 0.982). Compared with the traditional feature model, the RS model significantly improved the diagnostic efficacy for identifying symptomatic plaques in the testing set (AUC: 0.834 vs. 0.593; Z = 2.114, p = 0.0345). Conclusion: The RS model of PVAT of carotid plaque can be used as an objective indicator to evaluate the risk of plaque and provide a basis for risk stratification of carotid atherosclerotic disease.

The coupling of anammox with microalgae-bacteria symbiosis: Nitrogen removal performance and microbial community.

The partial nitrification-anammox process for ammonia nitrogen wastewater treatment requires mechanical aeration to provide oxygen, which is not conducive to energy saving. The microalgae-bacteria symbiotic system (MaBS) has the advantages of low carbon and energy saving in wastewater biological nitrogen removal. Therefore, this study combined the MaBS with an anammox process to provide oxygen, through the photosynthesis of microalgae instead of mechanical aeration. We investigated the nitrogen removal efficiency and long-term operation of a co-culture system comprising microalgae, nitrifying bacteria (NB), denitrifying bacteria (DnB), and anaerobic ammonium-oxidation bacteria (AnAOB) in a sequencing batch reactor without mechanical aeration. The experiment was divided into three steps: firstly, cultivating NB; then, adding three kinds of microalgae which were Chlorella sp., Anabaena sp., and Navicula sp. to the bioreactor to construct a microalgae-bacteria symbiotic system; finally, adding anammox sludge to construct the anammox and microalgae-bacteria symbiosis (Anammox-MaBS) system. The results demonstrated that nitrification, denitrification, and anammox processes were coupled successfully, and the maximum TN removal efficiency of the stable Anammox-MaBS system was 99.51 % when the concentration of the influent NH4+-N was 100 mg/L. The addition of microalgae in ammonia wastewater promoted the enrichment of DnB and AnAOB, which were Denitratisoma, Haliangium, unclassified_Rhodocyclaceae, and Candidatus_Brocadia. Furthermore, the unique biofilm structure could effectively alleviate the photoinhibition of light-sensitive bacteria, which may be the reason for the long-term adaptation of Candidatus_Brocadia to light conditions. This research can provide a low-cost solution to bacterial photoinhibition in the coexistence system of microalgae and bacteria without mechanical aeration, offering theoretical support for low-carbon and energy-efficient treatment of wastewater.

Relationship Analysis Between Pericoronary Fat Attenuation Index and Parameters of Single Plaque.

OBJECTIVE: The aim of the study is to investigate the relationship between plaque parameters and pericoronary fat attenuation index (FAI). METHODS: A retrospective collection was performed on 227 patients with coronary heart disease who underwent coronary computed tomography angiography examinations in our hospital from May 2021 to April 2023, with a total of 254 right coronary or left anterior descending coronary arteries exhibiting solitary plaques within the FAI measurement area. Based on whether the proximal coronary FAI value was ≥ -70.0 HU, patients and coronary arteries were divided into FAI-positive group (67 cases, 73 coronary arteries) and FAI-negative group (160 cases, 181 coronary arteries). Quantitative parameters of coronary solitary plaques were collected, including stenosis severity, plaque length, plaque volume, plaque composition ratios, minimal luminal area, and calcification score, as well as qualitative parameters such as plaque types and high-risk plaques. Differences in plaque parameters between the FAI-positive and FAI-negative groups were compared. RESULTS: The proportion of positive remodeling in the FAI-positive group (73 coronary arteries) was higher than that in the FAI-negative group (181 coronary arteries) with statistical significance (89.0% vs 78.5%, P = 0.049). Multivariate analysis revealed that positive remodeling was a risk factor for abnormal FAI values in solitary plaques (odds ratio, 2.271, P = 0.049). CONCLUSIONS: The FAI-positive group had a higher proportion of positive remodeling, and positive remodeling was an independent risk factor for positive FAI values.

Estimation of Gait Parameters for Adults with Surface Electromyogram Based on Machine Learning Models.

Gait analysis has been studied over the last few decades as the best way to objectively assess the technical outcome of a procedure designed to improve gait. The treating physician can understand the type of gait problem, gain insight into the etiology, and find the best treatment with gait analysis. The gait parameters are the kinematics, including the temporal and spatial parameters, and lack the activity information of skeletal muscles. Thus, the gait analysis measures not only the three-dimensional temporal and spatial graphs of kinematics but also the surface electromyograms (sEMGs) of the lower limbs. Now, the shoe-worn GaitUp Physilog® wearable inertial sensors can easily measure the gait parameters when subjects are walking on the general ground. However, it cannot measure muscle activity. The aim of this study is to measure the gait parameters using the sEMGs of the lower limbs. A self-made wireless device was used to measure the sEMGs from the vastus lateralis and gastrocnemius muscles of the left and right feet. Twenty young female subjects with a skeletal muscle index (SMI) below 5.7 kg/m2 were recruited for this study and examined by the InBody 270 instrument. Four parameters of sEMG were used to estimate 23 gait parameters. They were measured using the GaitUp Physilog® wearable inertial sensors with three machine learning models, including random forest (RF), decision tree (DT), and XGBoost. The results show that 14 gait parameters could be well-estimated, and their correlation coefficients are above 0.800. This study signifies a step towards a more comprehensive analysis of gait with only sEMGs.