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Ammonia nitrogen is one of the main toxic substances in aquatic cultivation environments. Chronic exposure to excessive amounts of ammonia-N creates toxic consequences, retarding the growth of aquatic organisms. This study investigated the growth performance, morphological and physiological alterations, and transcriptome changes in the hepatopancreas and gills of white shrimp Litopenaeus vannamei. The results showed that there was no significant difference in the survival rate (p > 0.05), whereas growth performance was reduced significantly in the treated groups compared to the control groups (p < 0.05). Significant structural damage and vacuolation occurred in hepatopancreas and gill tissues in the treated groups. Superoxide dismutase (SOD) activity and Na+/K+-ATPase content were significantly increased by chronic ammonia-N exposure in the two tissue groups. In addition, catalase (CAT) activity and malondialdehyde (MDA) levels were significantly altered in the hepatopancreas groups (p < 0.05), whereas no differences were observed in the gill groups (p > 0.05). There were 890 and 1572 differentially expressed genes identified in the hepatopancreas (treated versus control groups) and gills (treated versus control groups), respectively, of L. vannamei under chronic ammonia-N exposure. Functional enrichment analysis revealed associations with oxidative stress, protein synthesis, lipid metabolism, and different serine proteases. The gills maintained cellular homeostasis mainly through high expression of cytoskeleton and transcription genes, whereas the hepatopancreas down-regulated related genes in the ribosome, proteasome, and spliceosome pathways. These genes and pathways are important in the biosynthesis and transformation of living organisms. In addition, both tissues maintained organismal growth primarily through lipid metabolism, which may serve as an effective strategy for ammonia-N resistance in L. vannamei. These results provided a new perspective in understanding the mechanisms of ammonia-N resistance in crustaceans.

Mainstream deepfake detection algorithms generally fail to fully extract forgery traces and have low accuracy when detecting forged images with natural corruptions or human damage. On this basis, a new algorithm based on an adversarial dual-branch data augmentation framework and a modified attention mechanism is proposed in this paper to improve the robustness of detection models. First, this paper combines the traditional random sampling augmentation method with the adversarial sample idea to enhance and expand the forged images in data preprocessing. Then, we obtain training samples with diversity and hardness uniformity. Meanwhile, a new attention mechanism is modified and added to the ResNet50 model. The improved model serves as the backbone, effectively increasing the weight of forged traces in the multi-scale feature maps. The Jensen–Shannon divergence loss and cosine annealing algorithms are introduced into the training process to improve the model’s accuracy and convergence speed. The proposed algorithm is validated on standard and corrupted datasets. The experiments show that the algorithm proposed in this paper significantly improves effectiveness and robustness, with accuracies of 4.16%, 7.37%, and 3.87% better than the baseline model on DeepFakes, FaceSwap, and FaceShifer, respectively. Most importantly, its detection performance on the corrupted datasets DeepFakes-C, FaceSwap-C, and FaceShifer-C is much higher than that of mainstream methods.

In recent years, voice deepfake technology has developed rapidly, but current detection methods have the problems of insufficient detection generalization and insufficient feature extraction for unknown attacks. This paper presents a forged speech detection method (HuRawNet2_modified) based on a self-supervised pre-trained model (HuBERT) to improve detection (and address the above problems). A combination of impulsive signal-dependent additive noise and additive white Gaussian noise was adopted for data boosting and augmentation, and the HuBERT model was fine-tuned on different language databases. On this basis, the size of the extracted feature maps was modified independently by the α-feature map scaling (α-FMS) method, with a modified end-to-end method using the RawNet2 model as the backbone structure. The results showed that the HuBERT model could extract features more comprehensively and accurately. The best evaluation indicators were an equal error rate (EER) of 2.89% and a minimum tandem detection cost function (min t-DCF) of 0.2182 on the database of the ASVspoof2021 LA challenge, which verified the effectiveness of the detection method proposed in this paper. Compared with the baseline systems in databases of the ASVspoof 2021 LA challenge and the FMFCC-A, the values of EER and min t-DCF decreased. The results also showed that the self-supervised pre-trained model with fine-tuning can extract acoustic features across languages. And the detection can be slightly improved when the languages of the pre-trained database, and the fine-tuned and tested database are the same.

Ridge tillage is one of the essential tillage methods in China. It affects the soil structure by altering the soil-water environment. With the rapid development of agricultural mechanization, the mechanized ridge tillage technology that combines modern mechanized agriculture with conservation tillage has become a pertinent agricultural production technology in the hilly regions. However, to date, the effects of mechanized ridge tillage on soil structure have garnered little attention. In this study, a field plot experiment involving the following four treatments: conventional tillage with rice and winter fallow (CK1), conventional tillage with rice-rape rotation (CK2), wide ridge tillage with rice-rape rotation (BT), and narrow ridge tillage with rice-rape rotation (RT) was conducted to study the effects of mechanized ridge tillage with rice-rape rotation on soil aggregate stability and soil porosity. The results indicated that mechanized ridge tillage could reduce the porosity of pores > 30 μm in diameter and increase the porosity of pores < 0.5 μm. Furthermore, mechanized ridge tillage could increase soil aggregate stability; the order of average mass diameter and geometric average diameter was RT > BT > CK2 > CK1. The BT and RT treatments could increase the agglomeration degree of the soil particles, which followed the order of RT > BT > CK2 > CK1. Therefore, mechanized ridge tillage with rice-rape rotation is effective in enhancing soil structure.

Purpose: This study aimed to employ the incremental digital image correlation (DIC) method to obtain displacement and strain field data of the cornea from Corvis ST (CVS) sequences and access the performance of embedding these biomechanical data with machine learning models to distinguish forme fruste keratoconus (FFKC) from normal corneas., Methods: 100 subjects were categorized into normal (N = 50) and FFKC (N = 50) groups. Image sequences depicting the horizontal cross-section of the human cornea under air puff were captured using the Corvis ST tonometer. The high-speed evolution of full-field corneal displacement, strain, velocity, and strain rate was reconstructed utilizing the incremental DIC approach. Maximum (max-) and average (ave-) values of full-field displacement V, shear strain γxy, velocity VR, and shear strain rate γxyR were determined over time, generating eight evolution curves denoting max-V, max-γxy, max-VR, max-γxyR, ave-V, ave-γxy, ave-VR, and ave-γxyR, respectively. These evolution data were inputted into two machine learning (ML) models, specifically Naïve Bayes (NB) and Random Forest (RF) models, which were subsequently employed to construct a voting classifier. The performance of the models in diagnosing FFKC from normal corneas was compared to existing CVS parameters., Results: The Normal group and the FFKC group each included 50 eyes. The FFKC group did not differ from healthy controls for age ( p = 0.26) and gender ( p = 0.36) at baseline, but they had significantly lower bIOP ( p < 0.001) and thinner central cornea thickness (CCT) ( p < 0.001). The results demonstrated that the proposed voting ensemble model yielded the highest performance with an AUC of 1.00, followed by the RF model with an AUC of 0.99. Radius and A2 Time emerged as the best-performing CVS parameters with AUC values of 0.948 and 0.938, respectively. Nonetheless, no existing Corvis ST parameters outperformed the ML models. A progressive enhancement in performance of the ML models was observed with incremental time points during the corneal deformation., Conclusion: This study represents the first instance where displacement and strain data following incremental DIC analysis of Corvis ST images were integrated with machine learning models to effectively differentiate FFKC corneas from normal ones, achieving superior accuracy compared to existing CVS parameters. Considering biomechanical responses of the inner cornea and their temporal pattern changes may significantly improve the early detection of keratoconus., Competing Interests: The authors declare no conflicts of interest.

Keratoconus (KC), a leading cause of vision impairment, has an unclear aetiology. This study used Mendelian randomization (MR) to explore the causal links between various factors (smoking, asthma, Down syndrome, inflammatory bowel disease, atopic dermatitis, and serum 25-hydroxyvitamin D levels) and KC. A two-sample MR design, grounded in genome-wide association study (GWAS) summary statistics, was adopted using data from FinnGen, UK Biobank, and other GWAS-related articles. The inverse-variance weighted (IVW) method was employed, complemented by the Wald ratio method for factors with only one single-nucleotide polymorphism (SNP). Sensitivity and stability were assessed through Cochrane's Q test, the MR-Egger intercept test, MR-PRESSO outlier test, and the leave-one-out analysis. The IVW results for the ORA (Ocular Response Analyzer) biomechanical parameters indicated significant associations between tobacco smoking (CH: p < 0.001; CRF: p = 0.009) and inflammatory bowel disease (CH: p = 0.032; CRF: p = 0.001) and corneal biomechanics. The Wald ratio method showed tobacco smoking was associated with a lower risk of KC ( p = 0.024). Conversely, asthma ( p = 0.009), atopic dermatitis ( p = 0.012), inflammatory bowel disease ( p = 0.017), and serum 25-hydroxyvitamin D levels ( p = 0.039) were associated with a higher risk of KC by IVW, and the same applied to Down syndrome ( p = 0.004) using the Wald ratio. These results underscore the role of corneal biomechanics as potential mediators in KC risk, warranting further investigation using Corvis ST and Brillouin microscopy. The findings emphasise the importance of timely screening for specific populations in KC prevention and management.

Royal jelly (RJ) is a highly nutritious secretion of the honeybees' hypopharyngeal glands (HPGs). During RJ production, colonies are occasionally subjected to manual interventions, such as sucrose feeding for energy supplementation. This study aimed to assess the impact of sucrose feeding on the composition of RJ. The results indicated that RJ obtained from sucrose-fed colonies exhibited significantly higher levels of fructose, alanine, glycine, tyrosine, valine, and isoleucine compared to the honey-fed group. However, no significant differences were observed in terms of moisture content, crude protein, 10-HDA, glucose, sucrose, minerals, or other amino acids within the RJ samples. Moreover, sucrose feeding did not have a significant effect on midgut sucrase activity, HPGs development, or the expression levels of MRJP1 and MRJP3 in nurse bees. Unsealed stored food samples from sucrose-fed bee colonies demonstrated significantly higher sucrose levels compared to sealed combs and natural honey. Additionally, natural honey exhibited higher moisture and Ca levels, as well as lower levels of Zn and Cu, in comparison to honey collected from bee colonies fed sucrose solutions. Based on these findings, we conclude that sucrose feeding has only a minor impact on the major components of RJ.

Tomato fruit is highly susceptible to infection by Botrytis cinerea ( B. cinerea ), a dominant pathogen, during storage. Recent studies have shown that autophagy is essential for plant defense against biotic and abiotic stresses. Autophagy-related gene 5 ( ATG5 ) plays a key role in autophagosome completion and maturation, and is rapidly induced by B. cinerea , but the potential mechanisms of ATG5 in Solanum lycopersicum (SlATG5 ) in postharvest tomato fruit resistance to B. cinerea remain unclear. To elucidate the role of SlATG5 in tomato fruit resistant to B. cinerea , CRISPR/Cas9-mediated knockout of SlATG5 was used in this study. The results showed that slatg5 mutants were more vulnerable to B. cinerea and exhibited more severe disease symptoms and lower activities of disease-resistant enzymes, such as chitinase (CHI), β- 1,3-glucanase (GLU), phenylalanine ammonia-lyase (PAL), and polyphenol oxidase (PPO), than the wild type (WT). Furthermore, the study observed that after inoculation with B. cinerea , the relative expression levels of genes related to salicylic acid (SA) signaling, such as SlPR1 , SlEDS1 , SlPAD4 , and SlNPR1 , were higher in slatg5 mutants than in WT. Conversely, the relative expression levels of jasmonic acid (JA) signaling-related genes SlLoxD and SlMYC2 were lower in slatg5 mutants than in WT. These findings suggested that SlATG5 positively regulated the resistance response of tomato fruit to B. cinerea by inhibiting the SA signaling pathway and activating the JA signaling pathway.

N7-Methylguanosine (m7G) modification holds significant importance in regulating posttranscriptional gene expression in epigenetics. Long non-coding RNAs (lncRNAs) have been demonstrated to play a crucial role in cancer progression. m7G-related lncRNA may be involved in the progression of pancreatic cancer (PC), although the underlying mechanism of regulation remains obscure. We obtained RNA sequence transcriptome data and relevant clinical information from the TCGA and GTEx databases. Univariate and multivariate Cox proportional risk analyses were performed to build a twelve-m7G-associated lncRNA risk model with prognostic value. The model was verified using receiver operating characteristic curve analysis and Kaplan-Meier analysis. The expression level of m7G-related lncRNAs in vitro was validated. Knockdown of SNHG8 increased the proliferation and migration of PC cells. Differentially expressed genes between high- and low-risk groups were identified for gene set enrichment analysis, immune infiltration, and potential drug exploration. We conducted an m7G-related lncRNA predictive risk model for PC patients. The model had independent prognostic significance and offered an exact survival prediction. The research provided us with better knowledge of the regulation of tumor-infiltrating lymphocytes in PC. The m7G-related lncRNA risk model may serve as a precise prognostic tool and indicate prospective therapeutic targets for PC patients.

Queen bees and worker bees both develop from fertilized eggs, whereas queens live longer than workers. The mechanism of this phenomenon is worth exploring. Antioxidant capacity, immune and IIS are the conserved mechanisms of aging. The importance of gut bacteria for health prompted us to connect with bee aging. Therefore, the differences of antioxidant, immune, IIS and gut microflora between queen and worker bees were compared to find potential mechanisms of queens' longevity. The results showed queens had stronger antioxidant capacity and lower immune pathway and IIS activity than workers. The higher expression level of catalase and SOD1/2 in queens resulted in the stronger ROS scavenging ability, which leads to the lower ROS level and the reduced accumulation of oxidative damage products in queens. The lower IMD expression and higher antimicrobial peptides (AMPs) expressions in queens suggested that queens maintain lower immune pathway activity and stronger immune capacity than workers. Gut bacteria composition analysis indicated that queens had supernal Acetobacteraceae (notably Commensalibacter and Bombella) , Lactobacillus and Bifidobacterium over workers. In conclusion, antioxidant, immune, IIS, and gut symbiotic bacteria all contribute to the longevity of queens. This study provides more insights into revealing the mechanisms of queens' longevity.

'Dancong' tea is a famous traditional Oolong tea. In order to keep the original taste of "ancient tea trees", most of the 'Dancong' tea plants are planted in a single plant pattern without pruning. The objective of this study was to explore the effects of long-term non-pruning on main quality constituents in 'Dancong' tea. The results showed that the contents of free amino acids, chlorophylls, and floral-honey aromatic substances in tea leaves of unpruned tea plants were higher than those in every year pruned tea plants, while the catechin content in leaves of pruned tea plants was higher than that in leaves of unpruned tea plants. Quantitative proteomics analysis showed that most enzymes involved in biosynthesis of catechins were downregulated in leaves of unpruned tea plants. Five proteins involved in chlorophyll metabolism and 12 proteins related to photosynthesis were upregulated, and the results suggested that higher chlorophyll content and more efficient photosynthetic energy conversion may be important for the higher accumulation of special quality components in leaves of unpruned tea plants. The findings of this study will advance our understanding of the mechanism of formation of different metabolites in leaves of unpruned and pruned tea plants.

The role of Langerhans cells (LCs) in vitiligo pathogenesis remains unclear, with published studies reporting contradictory results regarding the quantity of LCs and no data on the features of LCs in vitiligo. Here, we aimed to analyze the presence, density, and morphological features of LCs in the epidermis of patients with vitiligo. Skin biopsies were stained for LCs using anti-CD1a/anti-langerin antibodies and analyzed by immunocytochemistry with light and electron microscopy. Compared with healthy controls, we detected significantly increased numbers of epidermal LCs in lesional skin from vitiligo in the progressive state. These LCs exhibited striking morphological alterations, including an elevated number of dendrites, with increased length and more branches than dendrites from controls. Ultrastructure examination via immuno-electron microscopy revealed markedly reduced Birbeck granules (BGs) and shorter BG rods in LCs from progressive vitiligo, with higher expression of langerin. Additionally, expression of S100B, the activity biomarker of vitiligo, was increased in these LCs. This work provides new insight on the cellular composition of LCs in vitiliginous skin, revealing altered morphology and increased LC numbers, with elevated S100B expression. Our data suggest LCs might play a critical role in vitiligo pathogenesis and thus may represent a novel therapeutic target for this disease.

Salicylic acid (SA) is a well-known immune-related hormone that has been well studied in model plants. However, less attention has been paid to the presence of SA and its derivatives in economic plants, such as tea plants ( Camellia sinensis ). This study showed that tea plants were rich in SA and responded differently to different pathogens. Feeding experiments in tea tissues further confirmed the transformation of SA into salicylic acid 2- O -β-glucoside (SAG) and methyl salicylate. Nonaqueous fractionation techniques confirmed that SA and SAG were mostly distributed in the cytosol of tea leaves, consistent with distributions in other plant species. Furthermore, the stem epidermis contained more SA than the stem core both in C. sinensis cv. "Jinxuan" (small-leaf species) and "Yinghong No. 9" (large-leaf species). Compared with cv. "Yinghong No. 9", cv. "Jinxuan" contained more SAG in the stem epidermis, which might explain its lower incidence rate of wilt disease. This information will improve understanding of SA occurrence in tea plants and provide a basis for investigating the relationship between SA and disease resistance in tea plants.

Amino acids contribute to the nutritional value and quality of black tea. Fermentation is the most important stage of the black tea manufacturing process. In this study, we investigated protein degradation and proteinaceous amino acid metabolism associated with enzymatic reactions during fermentation in the black tea manufacturing process. The results showed that the concentrations of both protein and free amino acids decreased during fermentation. We also confirmed that proteins were broken down into free amino acids by artificially synthesized dipeptide benzyloxycarbonyl glutamyl-tyrosine (Z-Glu-Tyr). Metabolites of the amino acid metabolic pathway increased significantly during fermentation. Furthermore, we confirmed that free amino acids were degraded to volatile compounds in a tracer experiment with the isotope precursor. These results provide information that will help black tea manufacturers improve the quality of black tea.