A machine learning-based radiomics model for prediction of tumor mutation burden in gastric cancer

Purpose: To evaluate the potential of machine learning (ML)-based radiomics approach for predicting tumor mutation burden (TMB) in gastric cancer (GC).Methods: The contrast enhanced CT (CECT) images with corresponding clinical information of 256 GC patients were retrospectively collected. Patients were separated into training set (n = 180) and validation set (n = 76). A total of 3,390 radiomics features were extracted from three phases images of CECT. The least absolute shrinkage and selection operator (LASSO) model was used for feature screening. Seven machine learning (ML) algorithms were employed to find the optimal classifier. The predictive ability of radiomics model (RM) was evaluated with receiver operating characteristic. The correlation between RM and TMB values was evaluated using Spearman’s correlation coefficient. The explainability of RM was assessed by the Shapley Additive explanations (SHAP) method.Results: Logistic regression algorithm was chosen for model construction. The RM showed good predictive ability of TMB status with AUCs of 0.89 [95% confidence interval (CI): 0.85–0.94] and 0.86 (95% CI: 0.74–0.98) in the training and validation sets. The correlation analysis revealed a good correlation between RM and TMB levels (correlation coefficient: 0.62, p < 0.001). The RM also showed favorable and stable predictive accuracy within the cutoff value range 6–16 mut/Mb in both sets.Conclusion: The ML-based RM offered a promising image biomarker for predicting TMB status in GC patients

A unified construction of weightwise perfectly balanced Boolean functions

At Eurocrypt 2016, Méaux et al. presented FLIP, a new family of stream ciphers {that aimed to enhance the efficiency of homomorphic encryption frameworks. Motivated by FLIP, recent research has focused on the study of Boolean functions with good cryptographic properties when restricted to subsets of the space $\mathbb{F}_2^n$. If an $n$-variable Boolean function has the property of balancedness when restricted to each set of vectors with fixed Hamming weight between $1$ and $n-1$, it is a weightwise perfectly balanced (WPB) Boolean function. In the literature, a few algebraic constructions of WPB functions are known, in which there are some constructions that use iterative method based on functions with low degrees of 1, 2, or 4. In this paper, we generalize the iterative method and contribute a unified construction of WPB functions based on functions with algebraic degrees that can} be any power of 2. For any given positive integer $d$ not larger than $m$, we first provide a class of $2^m$-variable Boolean functions with a degree of $2^{d-1}$. Utilizing these functions, we then present a construction of $2^m$-variable WPB functions $g_{m;d}$. In particular, $g_{m;d}$ includes four former classes of WPB functions as special cases when $d=1,2,3,m$. When $d$ takes other integer values, $g_{m;d}$ has never appeared before. In addition, we prove the algebraic degree of the constructed WPB functions and compare the weightwise nonlinearity of WPB functions known so far in 8 and 16 variables

milR20 negatively regulates the development of fruit bodies in Pleurotus cornucopiae

The mechanism underlying the development of fruit bodies in edible mushroom is a widely studied topic. In this study, the role of milRNAs in the development of fruit bodies of Pleurotus cornucopiae was studied by comparative analyses of the mRNAs and milRNAs at different stages of development. The genes that play a crucial role in the expression and function of milRNAs were identified and subsequently expressed and silenced at different stages of development. The total number of differentially expressed genes (DEGs) and differentially expressed milRNAs (DEMs) at different stages of development was determined to be 7,934 and 20, respectively. Comparison of the DEGs and DEMs across the different development stages revealed that DEMs and its target DEGs involved in the mitogen-activated protein kinase (MAPK) signaling pathway, protein processing in endoplasmic reticulum, endocytosis, aminoacyl-tRNA biosynthesis, RNA transport, and other metabolism pathways, which may play important roles in the development of the fruit bodies of P. cornucopiae. The function of milR20, which targeted pheromone A receptor g8971 and was involved in the MAPK signaling pathway, was further verified by overexpression and silencing in P. cornucopiae. The results demonstrated that the overexpression of milR20 reduced the growth rate of mycelia and prolonged the development of the fruit bodies, while milR20 silencing had an opposite effect. These findings indicated that milR20 plays a negative role in the development of P. cornucopiae. This study provides novel insights into the molecular mechanism underlying the development of fruit bodies in P. cornucopiae

Dual-Polarized Frequency-Diverse Metaimager for Computational Polarimetric Imaging

A dual-polarized frequency-diverse metaimager (DFM) applicable for computational polarimetric imaging (CPI) is proposed in this paper. The proposed DFM working from 18 to 22 GHz can generate spatially-random measurement modes at different operating frequencies as well as under varying polarization states. The DFM is a low-profile metacavity etched with sparsely arrayed cross-shaped slots. Firstly, a high-dispersion random metasurface consisting of 100 different kinds of elements is designed for the realization of frequency-diverse field distributions inside the metacavity. The simulated annealing algorithm is used to optimize the element positions. Additionally, the cross-shaped slot capable of working independently under two orthogonal polarization states is also designed, which facilitates low-correlated dual-polarized radiation. Then, the performance of the DFM is evaluated. The S11 of the DFM is under -10 dB, ensuring a good impedance match. In total 100 dual-polarized measurement modes with correlation coefficients smaller than 0.35 are obtained from 18 to 22 GHz. Finally, the DFM-based imaging experiments are implemented to verify the feasibility of the proposed DFM architecture. Comparative experiments are also carried out to demonstrate the advantage of leveraging dual-polarimetric information

Multi-Attribute Group Decision-Making Methods Based on Entropy Weights with q-Rung Picture Uncertain Linguistic Fuzzy Information

This paper introduces a new concept called q-rung picture uncertain linguistic fuzzy sets (q-RPULSs). These sets provide a reliable and comprehensive method for describing complex and uncertain decision-making information. In addition, q-RPULSs help to integrate the decision maker’s quantitative assessment ideas with qualitative assessment information. For the q-RPUL multi-attribute group decision-making problem with unknown weight information, an entropy-based fuzzy set method for q-rung picture uncertainty language is proposed. The method considers the interrelationships among attributes and builds a q-rung picture uncertain language model. In addition, the q-RPULMSM operator and its related properties are discussed in this paper. This operator enables the fusion of q-RPULSs and helps to reach consensus in decision-making scenarios. To demonstrate the validity of the methodology, we provide a real case study involving commodity selection. Based on this case study, the reasonableness and superiority of the method are evaluated, highlighting the practical advantages and applicability of q-RPULSs in decision-making processes

Effects of simulated nitrogen deposition on soil microbial biomass and community function in subtropical evergreen broad-leaved forest

Aim of the study: The aim of this study was to examine the effects of a 5-year simulated nitrogen (N) deposition on soil microbial biomass carbon (MBC), nitrogen (MBN), microbial community activity and diversity in subtropical old-growth forest ecosystems.Area of study: The study was conducted in forest located at subtropical forest in Anhui, east China.Material and methods: Three blocks with three fully randomized plots of 20 m × 20 m with similar forest community and soil conditions were established. The site applied ammonium nitrate (NH4NO3) to simulate N deposition (50 and 100 kg N ha−1 year −1). From three depths (0–10, 10–20 and 20–30 cm), were collected over four seasons (December, March, June and September), and then measured by community-level physiological profiles (CLPPs).Main results: N addition had no significant effect on MBC and MBN. The spatiotemporal variations in MBC and MBN were controlled by seasonality and soil depth. Soil microbial activities and diversity in the growing season (June and September) were apparently higher than the dormant season (March and December), there were significantly lower diversity indices found following N addition in September. However, N addition enhanced microbial activities and increased diversity indices in the dormant season. Redundancy analysis showed that pH, soil moisture, NO3--N and total phosphorus were the most important factors controlling the spatial pattern of microbial metabolic activity.Research highlights: These results suggest that soil microbial community function is more easily influenced than microbial biomass. The site has a trend of P-limited or near-N saturation, and will threaten the whole forest ecosystem with the increasing duration of N addition.Keywords: Nitrogen deposition; Seasonality; Soil microbial biomass; Microbial community; Subtropical old-growth forest

The Metacaspase Gene <i>PoMCA</i>1 Enhances the Mycelial Heat Stress Tolerance and Regulates the Fruiting Body Development of <i>Pleurotus ostreatus</i>

Pleurotus ostreatus is one of the most cultivated edible mushrooms worldwide, of which the fruiting body development is a highly complex process involving the precise genetic regulatory network and suitable environmental factors. Metacaspases play important roles in developmental processes and programmed cell death (PCD) induced by some environmental stress in many organisms. In this study, a type I metacaspase, PoMCA1, was identified via the analysis of the enzyme domain and alignment with homologous metacaspases. PoMCA1 overexpression and RNAi mutants were generated via Agrobacterium tumefaciens-mediated transformation (ATMT) into the P. ostreatus mycelium. The roles of the PoMCA1 gene in heat stress and fruiting body development were examined. The results show that both of the overexpression transformants were more tolerant to heat stress than the wild-type strain, while the opposite phenomenons were found for the two RNAi strains. Compared with the wild-type strain, the overexpression strain OE-7 had faster formation of the fruiting body, while the two RNAi strains produced significantly more primordia and young fruiting bodies, and presented morphological deformities and slower fruiting body development. All of the results suggest that the PoMCA1 gene is involved in the positive regulation of heat stress tolerance and fruiting body development in P. ostreatus

Characterization of the complete chloroplast genome sequence of Malus kansuensis (Rosaceae)

The Malus kansuensis belongs to the Malus genus of Rosaceae family and it is an important apple rootstock resource native to China. Here, its complete chloroplast genome was sequenced and assembled by high-throughput Illumina sequencing data. The DNA was circular in shape with 160,133 bp length, containing IRA and IRB inverted repeat regions (26,354 bp), large single-copy region (LSC) (88,141 bp), and small single-copy region (SSC)(19,284 bp). In the chloroplast genome, 129 functional genes were predicted, including 85 protein-coding genes, 36 tRNA genes, and 8 rRNA genes. The phylogenetic tree basically accords with the traditional taxonomy of the order Malus genus of Rosaceae family