Predicting 18F-FDG SUVs of metastatic pulmonary nodes from CT images in patients with differentiated thyroid cancer by using a convolutional neural network

PurposeThe aim of this study was to predict standard uptake values (SUVs) from computed tomography (CT) images of patients with lung metastases from differentiated thyroid cancer (DTC-LM).MethodsWe proposed a novel SUVs prediction model using 18-layer Residual Network for generating SUVmax, SUVmean, SUVmin of metastatic pulmonary nodes from CT images of patients with DTC-LM. Nuclear medicine specialists outlined the metastatic pulmonary as primary set. The best model parameters were obtained after five-fold cross-validation on the training and validation set, further evaluated in independent test set. Mean absolute error (MAE), mean squared error (MSE), and mean relative error (MRE) were used to assess the performance of regression task. Specificity, sensitivity, F1 score, positive predictive value, negative predictive value and accuracy were used for classification task. The correlation between predicted and actual SUVs was analyzed.ResultsA total of 3407 nodes from 74 patients with DTC-LM were collected in this study. On the independent test set, the average MAE, MSE and MRE was 0.3843, 1.0133, 0.3491 respectively, and the accuracy was 88.26%. Our proposed model achieved high metric scores (MAE=0.3843, MSE=1.0113, MRE=34.91%) compared with other backbones. The predicted SUVmax (R2 = 0.8987), SUVmean (R2 = 0.8346), SUVmin (R2 = 0.7373) were all significantly correlated with actual SUVs.ConclusionThe novel approach proposed in this study provides new ideas for the application of predicting SUVs for metastatic pulmonary nodes in DTC patients

Overlapping Root Architecture and Gene Expression of Nitrogen Transporters for Nitrogen Acquisition of Tomato Plants Colonized with Isolates of <i>Funneliformis mosseae</i> in Hydroponic Production

Understanding the impact of arbuscular mycorrhizal fungi (AMF) upon the nitrogen (N) uptake of tomato (Lycopersicum esculentum L.) plants is crucial for effectively utilizing these beneficial microorganisms in industrial hydroponic tomato production. Yet it remains unknown whether, besides fungal delivery, the AMF also affects N uptake via altered plant root growth or whether, together with changed N transporters expression of hosts, this impact is isolate-specific. We investigated tomato root architecture and the expression of LeAMT1.1, LeAMT1.2, and LeNRT2.3 genes in roots inoculated with five isolates of Funneliformis mosseae, these collected from different geographical locations, under greenhouse conditions with nutritional solution in coconut coir production. Our results revealed that isolate-specific AMF inoculation strongly increased the root biomass, total root length, surface area, and volume. Linear relationships were found between the total root length and N accumulation in plants. Furthermore, expression levels of LeAMT1.1, LeAMT1.2, and LeNRT2.3 were significantly up-regulated by inoculation with F. mosseae with isolate-specific. These results implied N uptake greater than predicted by root growth, and N transporters up-regulated by AMF symbiosis in an isolate-specific manner. Thus, an overlap in root biomass, architecture and expression of N transporters increase N acquisition in tomato plants in the symbiosis

Identification of Novel QTL for Mercury Accumulation in Maize Using an Enlarged SNP Panel

Mercury (Hg) pollution not only poses a threat to the environment but also adversely affects the growth and development of plants, with potential repercussions for animals and humans through bioaccumulation in the food chain. Maize, a crucial source of food, industrial materials, and livestock feed, requires special attention in understanding the genetic factors influencing mercury accumulation. Developing maize varieties with low mercury accumulation is vital for both maize production and human health. In this study, a comprehensive genome-wide association study (GWAS) was conducted using an enlarged SNP panel comprising 1.25 million single nucleotide polymorphisms (SNPs) in 230 maize inbred lines across three environments. The analysis identified 111 significant SNPs within 78 quantitative trait loci (QTL), involving 169 candidate genes under the Q model. Compared to the previous study, the increased marker density and optimized statistical model led to the discovery of 74 additional QTL, demonstrating improved statistical power. Gene ontology (GO) enrichment analysis revealed that most genes participate in arsenate reduction and stress responses. Notably, GRMZM2G440968, which has been reported in previous studies, is associated with the significant SNP chr6.S_155668107 in axis tissue. It encodes a cysteine proteinase inhibitor, implying its potential role in mitigating mercury toxicity by inhibiting cysteine. Haplotype analyses provided further insights, indicating that lines carrying hap3 exhibited the lowest mercury content compared to other haplotypes. In summary, our study significantly enhances the statistical power of GWAS, identifying additional genes related to mercury accumulation and metabolism. These findings offer valuable insights into unraveling the genetic basis of mercury content in maize and contribute to the development of maize varieties with low mercury accumulation

Hierarchical Self-Assembly of Cyclodextrin and Dimethylamino-Substituted Arylene–Ethynylene on N‑doped Graphene for Synergistically Enhanced Electrochemical Sensing of Dihydroxybenzene Isomers

An electrochemically active sensing nanomaterial (denoted as CD-MPEA-NG) has been successfully constructed by an hierarchical self-assembly of cyclodextrin (CD) and <i>N</i>,<i>N</i>-dimethyl-4-(phenylethynyl)­aniline (MPEA) on N-doped graphene (NG) in a low-temperature hydrothermal process. The unique nanostructure of the high-performance CD-MPEA-NG was confirmed by utilizing Fourier transform infrared spectra, an X-ray diffractometer, and differential pulse voltammetry (DPV), etc. In particular, the method of density functional theory with dispersion energy (DFT-D) of wB97XD/LanL2DZ was employed to optimize and describe the face-to-face packing structure of heterodimers of NG and MPEA. The CD-MPEA-NG sensor exhibits highly sensitive performance toward dihydroxybenzene isomers, without relying on expensive noble metal or a complicated preparation process. The experimental results demonstrate that given the synergistic effect of NG and MPEA as a coupled sensing platform, CD as a supramolecular cavity can significantly enhance the electrochemical response. The detection limits (<i>S</i>/<i>N</i> = 3) for catechol (CT), resorcinol (RS), and hydroquinone (HQ) are 0.008, 0.018, and 0.011 μM by DPV, respectively. Besides, the CD-MPEA-NG sensor shows a superb anti-interference, reproducibility, and stability, and satisfactory recovery aimed at detecting isomers in Nanjing River water. The encouraging performance as well as simplified preparation approach strongly support the CD-MPEA-NG sensor is a fascinating electrode to develop as a seamless and sensitive electroanalytical technique