Personalized treatment of well-differentiated gastric neuroendocrine tumors based on clinicopathological classification and grading: A multicenter retrospective study.

BACKGROUND: The incidence of well-differentiated gastric neuroendocrine tumors (G-NET) is increasing annually, and while they have a good prognosis and low mortality rate, their high recurrence rate makes treatment options controversial. This study aims to determine the relationship between individualized treatment plans and the recurrence of G-NET. METHODS: We performed a multicenter, retrospective study of 94 patients with highly differentiated G-NET and treated at Peking Union Medical College Hospital, Yantai Yuhuangding Hospital, and Beijing Zhong-Neng-Jian Hospital from November 2015 to September 2023. Risk factors for recurrence of G-NETs were investigated using chi-squared test and multifactorial logistic regression analysis. RESULTS: After a median follow-up of 49 months, the overall recurrence rate among the 94 G-NET patients was 14% (13/94). The recurrence rates of endoscopic mucosal resection (EMR), endoscopic submucosal dissection (ESD), somatostatin analog (SSA) therapy, and surgery were 43% (6/14), 10% (5/49), 5% (1/22), and 11% (1/9), respectively. Post-treatment recurrence rates were significantly different ( P = 0.014) among four treatments (EMR, ESD, SSA, and surgery), and further subgroup comparisons revealed lower recurrence rates in the ESD and SSA groups than in the EMR group. From the second month onward, SSA therapy considerably reduced the gastrin levels from 1081.0 (571.5, 2472.8) pg/mL to 461.5 (255.3, 795.0) pg/mL ( Z = -3.521, P <0.001). Both chi-squared test and multifactorial logistic regression analysis suggested that among the clinicopathological parameters studied, only the pre-treatment gastrin level ( P = 0.018 and 0.005) and the type of treatment ( P = 0.014 and 0.017) were significantly associated with G-NET recurrence. CONCLUSIONS: Individualized treatment strategies may reduce the risk of relapse after G-NET treatment. Long-term SSA therapy may be a secure and efficacious treatment option for type 1 G-NET with more than six lesions, and it substantially decreases the incidence of post-treatment recurrence.

Genome-Wide Identification and Expression Analysis of the Cucumber FKBP Gene Family in Response to Abiotic and Biotic Stresses.

The FKBP (FK506-binding protein) gene family is an important member of the PPlase protease family and plays a vital role during the processes of plant growth and development. However, no studies of the FKBP gene family have been reported in cucumber. In this study, 19 FKBP genes were identified in cucumber, which were located on chromosomes 1, 3, 4, 6, and 7. Phylogenetic analysis divided the cucumber FKBP genes into three subgroups. The FKBP genes in the same subgroup exhibited similar structures and conserved motifs. The cis-acting elements analysis revealed that the promoters of cucumber FKBP genes contained hormone-, stress-, and development-related cis-acting elements. Synteny analysis of the FKBP genes among cucumber, Arabidopsis, and rice showed that 12 kinds of syntenic relationships were detected between cucumber and Arabidopsis FKBP genes, and 3 kinds of syntenic relationships were observed between cucumber and rice FKBP genes. The tissue-specific expression analysis showed that some FKBP genes were expressed in all tissues, while others were only highly expressed in part of the 10 types of tissues. The expression profile analysis of cucumber FKBP genes under 13 types of stresses showed that the CsaV3_1G007080 gene was differentially expressed under abiotic stresses (high temperature, NaCl, silicon, and photoperiod) and biotic stresses (downy mildew, green mottle mosaic virus, Fusarium wilt, phytophthora capsica, angular leaf spot, and root-knot nematode), which indicated that the CsaV3_1G007080 gene plays an important role in the growth and development of cucumber. The interaction protein analysis showed that most of the proteins in the FKBP gene family interacted with each other. The results of this study will lay the foundation for further research on the molecular biological functions of the cucumber FKBP gene family.

System-level biological effects of extremely low-frequency electromagnetic fields: an in vivo experimental review.

During the past decades, the potential effects of extremely low-frequency electromagnetic fields (ELF-EMFs) on human health have gained great interest all around the world. Though the International Commission on Non-Ionizing Radiation Protection recommended a 100 µT, and then a 200 µT magnetic field limit, the long-term effects of ELF-EMFs on organisms and systems need to be further investigated. It was reported that both electrotherapy and possible effects on human health could be induced under ELF-EM radiation with varied EM frequencies and fields. This present article intends to systematically review the in vivo experimental outcome and the corresponding mechanisms to shed some light on the safety considerations of ELF-EMFs. This will further advance the subsequent application of electrotherapy in human health.

Nondestructive monitoring of annealing and chemical-mechanical planarization behavior using ellipsometry and deep learning.

The Cu-filling process in through-silicon via (TSV-Cu) is a key technology for chip stacking and three-dimensional vertical packaging. During this process, defects resulting from chemical-mechanical planarization (CMP) and annealing severely affect the reliability of the chips. Traditional methods of defect characterization are destructive and cumbersome. In this study, a new defect inspection method was developed using Mueller matrix spectroscopic ellipsometry. TSV-Cu with a 3-µm-diameter and 8-µm-deep Cu filling showed three typical types of characteristics: overdishing (defect-OD), protrusion (defect-P), and defect-free. The process dimension for each defect was 13 nm. First, the three typical defects caused by CMP and annealing were investigated. With single-channel deep learning and a Mueller matrix element (MME), the TSV-Cu defect types could be distinguished with an accuracy rate of 99.94%. Next, seven effective MMEs were used as independent channels in the artificial neural network to quantify the height variation in the Cu filling in the z-direction. The accuracy rate was 98.92% after training, and the recognition accuracy reached 1 nm. The proposed approach rapidly and nondestructively evaluates the annealing bonding performance of CMP processes, which can improve the reliability of high-density integration.

A Reflectivity Enhanced 3D Optical Storage Nanostructure Application Based on Direct Laser Writing Lithography.

To enable high-density optical storage, better storage media structures, diversified recording methods, and improved accuracy of readout schemes should be considered. In this study, we propose a novel three-dimensional (3D) sloppy nanostructure as the optical storage device, and this nanostructure can be fabricated using the 3D laser direct writing technology. It is a 900 nm high, 1 × 2 µm wide Si slope on a 200 nm SiO2 layer with 200 nm Si3N4 deposited on top to enhance reflectivity. In this study, we propose a reflected spectrum-based method as the readout recording strategy to stabilize information readout more stable. The corresponding reflected spectrum varied when the side wall angle of the slope and the azimuth angle of the nanostructure were tuned. In addition, an artificial neural network was applied to readout the stored information from the reflected spectrum. To simulate the realistic fabrication error and measurement error, a 20% noise level was added to the study. Our findings showed that the readout accuracy was 99.86% for all 120 data sequences when the slope and azimuth angle were varied. We investigated the possibility of a higher storage density to fully demonstrate the storage superiority of this designed structure. Our findings also showed that the readout accuracy can reach its highest level at 97.25% when the storage step of the encoded structure becomes 7.5 times smaller. The study provides the possibility to further explore different nanostructures to achieve high-density optical storage.

A Laplace sensitivity operator enhances the calculation efficiency of OCD metrology.

In integrated circuit manufacturing, optical critical dimension measurement is an efficient and non-destructive metrology method. It is also a model-based metrology in which a numerical model of the target device is formed to simulate the optical spectrum. The result is then reconstructed by fitting the simulated spectrum to the experimentally measured optical spectrum. Normally, the measured optical spectrum contains a great deal of data points that consume the storage space, and increase the fitting time. Therefore, it is worth finding an appropriate approach to downsample these data points without losing much accuracy. To quickly and accurately extract critical data with high sensitivity, we propose a Laplace sensitivity operator that is widely used for feature extraction. Compared with traditional sensitivity calculation, the Laplace sensitivity operator focuses more on the correlation and coupling between multiple parameters. Thus, the sensitivity can be properly analyzed from different dimensions. To test the feasibility and correctness of the proposed method, three basic structures were used for single-parameter verification: thin film, one-dimensional grating, and two-dimensional grating, and a vertical gate-all-around device used for multi-parameter analysis. Using the Laplace sensitivity operator, the extracted data showed better results in most cases than those achieved by the traditional sensitivity calculation method. The data volume was compressed by approximately 70%, the result matching loss was not significantly increase in terms of the root mean square error, and the calculation speed was increased by a factor of 2.4. Compared to the traditional sensitivity operator, the Laplace sensitivity operator was able to reduce the RMSE by up to 50%.

Genome-wide in silico identification of glutathione S-transferase (GST) gene family members in fig (Ficus carica L.) and expression characteristics during fruit color development.

Glutathione S-transferase (GSTs), a large and diverse group of multi-functional enzymes (EC 2.5.1.18), are associated with cellular detoxification, various biotic and abiotic stress responses, as well as secondary metabolites transportation. Here, 53 members of the FcGST gene family were screened from the genome database of fig (Ficus carica), which were further classified into five subfamilies, and the tau and phi were the major subfamilies. These genes were unevenly distributed over all the 13 chromosomes, and 12 tandem and one segmental duplication may contribute to this family expansion. Syntenic analysis revealed that FcGST shared closer genetic evolutionary origin relationship with species from the Ficus genus of the Moraceae family, such as F. microcarpa and F. hispida. The FcGST members of the same subfamily shared similar gene structure and motif distribution. The α helices were the chief structure element in predicted secondary and tertiary structure of FcGSTs proteins. GO and KEGG indicated that FcGSTs play multiple roles in glutathione metabolism and stress reactions as well as flavonoid metabolism. Predictive promoter analysis indicated that FcGSTs gene may be responsive to light, hormone, stress stimulation, development signaling, and regulated by MYB or WRKY. RNA-seq analysis showed that several FcGSTs that mainly expressed in the female flower tissue and peel during 'Purple-Peel' fig fruit development. Compared with 'Green Peel', FcGSTF1, and FcGSTU5/6/7 exhibited high expression abundance in the mature fruit purple peel. Additionally, results of phylogenetic sequences analysis, multiple sequences alignment, and anthocyanin content together showed that the expression changes of FcGSTF1, and FcGSTU5/6/7 may play crucial roles in fruit peel color alteration during fruit ripening. Our study provides a comprehensive overview of the GST gene family in fig, thus facilitating the further clarification of the molecular function and breeding utilization.

Integrated Analysis of Transcriptome and Metabolome Reveals New Insights into the Formation of Purple Leaf Veins and Leaf Edge Cracks in Brassica juncea.

Purple leaf veins and leaf edge cracks comprise the typical leaf phenotype of Brassica juncea; however, the molecular mechanisms and metabolic pathways of the formation of purple leaf veins and leaf edge cracks remain unclear. In this study, transcriptome and metabolome analyses were conducted to explore the regulation pathway of purple leaf vein and leaf edge crack formation based on four mustard samples that showed different leaf colors and degrees of cracking. The results showed genes with higher expression in purple leaf veins were mainly enriched in the flavonoid biosynthesis pathway. Integrating related genes and metabolites showed that the highly expressed genes of ANS (BjuA004031, BjuB014115, BjuB044852, and BjuO009605) and the excessive accumulation of dihydrokaempferol and dihydroquercetin contributed to the purple leaf veins by activating the synthetic pathways of pelargonidin-based anthocyanins and delphinidin-based anthocyanins. Meanwhile, "alpha-farnesene synthase activity" and "glucan endo-1, 3-beta-D-glucosidase activity" related to the adversity were mainly enriched in the serrated and lobed leaves, indicating that the environmental pressure was the dominant factor controlling the change in leaf shape. Overall, these results provided new insights into the regulation pathways for formation of purple leaf veins and leaf edge cracks, which could better accelerate the theoretical research on purple leaf vein color and leaf edge cracks in mustard.

Genome-Wide Identification, Phylogenetic and Expression Pattern Analysis of GATA Family Genes in Cucumber (Cucumis sativus L.).

GATA transcription factors are a class of transcriptional regulatory proteins that contain a characteristic type-IV zinc finger DNA-binding domain, which play important roles in plant growth and development. The GATA gene family has been characterized in various plant species. However, GATA family genes have not been identified in cucumber. In this study, 26 GATA family genes were identified in cucumber genome, whose physicochemical characteristics, chromosomal distributions, phylogenetic tree, gene structures conserved motifs, cis-regulatory elements in promoters, homologous gene pairs, downstream target genes were analyzed. Tissue expression profiles of cucumber GATA family genes exhibited that 17 GATA genes showed constitutive expression, and some GATA genes showed tissue-specific expression patterns. RNA-seq analysis of green and virescent leaves revealed that seven GATA genes might be involved in the chloroplast development and chlorophyll biosynthesis. Importantly, expression patterns analysis of GATA genes in response to abiotic and biotic stresses indicated that some GATA genes respond to either abiotic stress or biotic stress, some GATA genes such as Csa2G162660, Csa3G017200, Csa3G165640, Csa4G646060, Csa5G622830 and Csa6G312540 were simultaneously functional in resistance to abiotic and biotic stresses. Overall, this study will provide useful information for further analysis of the biological functions of GATA factors in cucumber.