Tumor-repopulating cells evade ferroptosis via PCK2-dependent phospholipid remodeling.

Whether stem-cell-like cancer cells avert ferroptosis to mediate therapy resistance remains unclear. In this study, using a soft fibrin gel culture system, we found that tumor-repopulating cells (TRCs) with stem-cell-like cancer cell characteristics resist chemotherapy and radiotherapy by decreasing ferroptosis sensitivity. Mechanistically, through quantitative mass spectrometry and lipidomic analysis, we determined that mitochondria metabolic kinase PCK2 phosphorylates and activates ACSL4 to drive ferroptosis-associated phospholipid remodeling. TRCs downregulate the PCK2 expression to confer themselves on a structural ferroptosis-resistant state. Notably, in addition to confirming the role of PCK2-pACSL4(T679) in multiple preclinical models, we discovered that higher PCK2 and pACSL4(T679) levels are correlated with better response to chemotherapy and radiotherapy as well as lower distant metastasis in nasopharyngeal carcinoma cohorts.

A genome-wide association study identifies a transporter for zinc uploading to maize kernels.

The Zn content in cereal seeds is an important trait for crop production as well as for human health. However, little is known about how Zn is loaded to plant seeds. Here, through a genome-wide association study (GWAS), we identify the Zn-NA (nicotianamine) transporter gene ZmYSL2 that is responsible for loading Zn to maize kernels. High promoter sequence variation in ZmYSL2 most likely drives the natural variation in Zn concentrations in maize kernels. ZmYSL2 is specifically localized on the plasma membrane facing the maternal tissue of the basal endosperm transfer cell layer (BETL) and functions in loading Zn-NA into the BETL. Overexpression of ZmYSL2 increases the Zn concentration in the kernels by 31.6%, which achieves the goal of Zn biofortification of maize. These findings resolve the mystery underlying the loading of Zn into plant seeds, providing an efficient strategy for breeding or engineering maize varieties with enriched Zn nutrition.

IGF2BP2 inhibits invasion and migration of clear cell renal cell carcinoma via targeting Netrin-4 in an m6A-dependent manner.

Clear cell renal cell carcinoma (ccRCC), the most common subtype of renal cell carcinoma, often leads to a poor prognosis due to metastasis. The investigation of N6-methyladenosine (m6A) methylation, a crucial RNA modification, and its role in ccRCC, particularly through the m6A reader insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2), revealed significant insights. We found that IGF2BP2 was notably downregulated in ccRCC, which correlated with tumor aggressiveness and poor prognosis. Thus, IGFBP2 has emerged as an independent prognostic factor of ccRCC. Moreover, a strong positive correlation was observed between the expression of IGF2BP2 and Netrin-4. Netrin-4 was also downregulated in ccRCC, and its lower levels were associated with increased malignancy and poor prognosis. Overexpression of IGF2BP2 and Netrin-4 suppressed the invasion and migration of ccRCC cells, while Netrin-4 knockdown reversed these effects in ccRCC cell lines. RNA immunoprecipitation (RIP)-quantitative polymerase chain reaction validated the robust enrichment of Netrin-4 mRNA in anti-IGF2BP2 antibody immunoprecipitates. MeRlP showed significantly increased Netrin4 m6A levels after lGF2BP2 overexpression. Moreover, we found that IGF2BP2 recognized and bound to the m6A site within the coding sequence of Netrin-4, enhancing its mRNA stability. Collectively, these results showed that IGF2BP2 plays a suppressive role in the invasion and migration of ccRCC cells by targeting Netrin-4 in an m6A-dependent manner. These findings underscore the potential of IGF2BP2/Netrin-4 as a promising prognostic biomarker and therapeutic target in patients with ccRCC metastasis.

DDX3X Is Hijacked by Snakehead Vesiculovirus Phosphoprotein To Facilitate Virus Replication via Stabilization of the Phosphoprotein.

Asp-Glu-Ala-Asp (DEAD) box helicase 3 X-linked (DDX3X) plays important regulatory roles in the replication of many viruses. However, the role of DDX3X in rhabdovirus replication has seldomly been investigated. In this study, snakehead vesiculovirus (SHVV), a kind of fish rhabdovirus, was used to study the role of DDX3X in rhabdovirus replication. DDX3X was identified as an interacting partner of SHVV phosphoprotein (P). The expression level of DDX3X was increased at an early stage of SHVV infection and then decreased to a normal level at a later infection stage. Overexpression of DDX3X promoted, while knockdown of DDX3X using specific small interfering RNAs (siRNAs) suppressed, SHVV replication, indicating that DDX3X was a proviral factor for SHVV replication. The N-terminal and core domains of DDX3X (DDX3X-N and DDX3X-Core) were determined to be the regions responsible for its interaction with SHVV P. Overexpression of DDX3X-Core suppressed SHVV replication by competitively disrupting the interaction between full-length DDX3X and SHVV P, suggesting that full-length DDX3X-P interaction was required for SHVV replication. Mechanistically, DDX3X-mediated promotion of SHVV replication was due not to inhibition of interferon expression but to maintenance of the stability of SHVV P to avoid autophagy-lysosome-dependent degradation. Collectively, our data suggest that DDX3X is hijacked by SHVV P to ensure effective replication of SHVV, which suggests an important anti-SHVV target. This study will help elucidate the role of DDX3X in regulating the replication of rhabdoviruses. IMPORTANCE Growing evidence has suggested that DDX3X plays important roles in virus replication. In one respect, DDX3X inhibits the replication of viruses, including hepatitis B virus, influenza A virus, Newcastle disease virus, duck Tembusu virus, and red-spotted grouper nervous necrosis virus. In another respect, DDX3X is required for the replication of viruses, including hepatitis C virus, Japanese encephalitis virus, West Nile virus, murine norovirus, herpes simplex virus, and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Because DDX3X has rarely been investigated in rhabdovirus replication, this study aimed at investigating the role of DDX3X in rhabdovirus replication by using the fish rhabdovirus SHVV as a model. We found that DDX3X was required for SHVV replication, with the mechanism that DDX3X interacts with and maintains the stability of SHVV phosphoprotein. Our data provide novel insights into the role of DDX3X in virus replication and will facilitate the design of antiviral drugs against rhabdovirus infection.

Structure of the Spring Viraemia of Carp Virus Ribonucleoprotein Complex Reveals Its Assembly Mechanism and Application in Antiviral Drug Screening.

Spring viremia of carp virus (SVCV) is a highly pathogenic Vesiculovirus infecting the common carp, yet neither a vaccine nor effective therapies are available to treat spring viremia of carp (SVC). Like all negative-sense viruses, SVCV contains an RNA genome that is encapsidated by the nucleoprotein (N) in the form of a ribonucleoprotein (RNP) complex, which serves as the template for viral replication and transcription. Here, the three-dimensional (3D) structure of SVCV RNP was resolved through cryo-electron microscopy (cryo-EM) at a resolution of 3.7 Å. RNP assembly was stabilized by N and C loops; RNA was wrapped in the groove between the N and C lobes with 9 nt nucleotide per protomer. Combined with mutational analysis, our results elucidated the mechanism of RNP formation. The RNA binding groove of SVCV N was used as a target for drug virtual screening, and it was found suramin had a good antiviral effect. This study provided insights into RNP assembly, and anti-SVCV drug screening was performed on the basis of this structure, providing a theoretical basis and efficient drug screening method for the prevention and treatment of SVC. IMPORTANCE Aquaculture accounts for about 70% of global aquatic products, and viral diseases severely harm the development of aquaculture industry. Spring viremia of carp virus (SVCV) is the pathogen causing highly contagious spring viremia of carp (SVC) disease in cyprinids, especially common carp (Cyprinus carpio), yet neither a vaccine nor effective therapies are available to treat this disease. In this study, we have elucidated the mechanism of SVCV ribonucleoprotein complex (RNP) formation by resolving the 3D structure of SVCV RNP and screened antiviral drugs based on the structure. It is found that suramin could competitively bind to the RNA binding groove and has good antiviral effects both in vivo and in vitro. Our study provides a template for rational drug discovery efforts to treat and prevent SVCV infections.

Tripartite motif-containing protein 31 confers protection against nonalcoholic steatohepatitis by deactivating mitogen-activated protein kinase kinase kinase 7.

BACKGROUND AIMS: As a global health threat, NASH has been confirmed to be a chronic progressive liver disease that is strongly associated with obesity. However, no approved drugs or efficient therapeutic strategies are valid, mainly because its complicated pathological processes is underestimated. APPROACH RESULTS: We identified the RING-type E3 ubiquitin transferase-tripartite motif-containing protein 31 (TRIM31), a member of the E3 ubiquitin ligases family, as an efficient endogenous inhibitor of transforming growth factor-beta-activated kinase 1 (mitogen-activated protein kinase kinase kinase 7; MAP3K7), and we further confirmed that TRIM31 is an MAP3K7-interacting protein and promotes MAP3K7 degradation by enhancing ubiquitination of K48 linkage in hepatocytes. Hepatocyte-specific Trim31 deletion blocks hepatic metabolism homeostasis, concomitant with glucose metabolic syndrome, lipid accumulation, up-regulated inflammation, and dramatically facilitates NASH progression. Inversely, transgenic overexpression, lentivirus, or adeno-associated virus-mediated Trim31 gene therapy restrain NASH in three dietary mice models. Mechanistically, in response to metabolic insults, TRIM31 interacts with MAP3K7 and conjugates K48-linked ubiquitination chains to promote MAP3K7 degradation, thus blocking MAP3K7 abundance and its downstream signaling cascade activation in hepatocytes. CONCLUSIONS: TRIM31 may serve as a promising therapeutic target for NASH treatment and associated metabolic disorders.

Trace gas sensor based on a multi-pass-retro-reflection-enhanced differential Helmholtz photoacoustic cell and a power amplified diode laser.

A high-sensitive photoacoustic spectroscopy (PAS) sensor, which is based on a multi-pass-retro-reflection-enhanced differential Helmholtz photoacoustic cell (DHPAC) and a high power diode laser amplified by erbium-doped fiber amplifier (EDFA), is presented in this work for the first time. In order to improve the interaction length between the light and target gas, the incident light was reflected four times through a multi-pass-retro-reflection-cell constructed by two right-angle prisms. A 1.53 µm distributed feedback (DFB) diode laser was selected to excite photoacoustic signal. Moreover, its power was amplified by an EDFA to 1000 mW to improve the amplitude of photoacoustic signal. Acetylene (C2H2) was chosen as the target analysis to verify the reported sensor performance. Compared to double channel without multiple reflections, the 2f signal of double channel with four reflections was improved by 3.71 times. In addition, when the output optical power of EDFA was 1000 mW, the 2f signal has a 70.57-fold improvement compared with the multi-pass-retro-reflection-cell without EDFA. An Allan deviation analysis was carried out to evaluate the long-term stability of such PAS sensor. When the averaging time was 400 s, the minimum detection limit (MDL) of such PAS sensor was 14 ppb.

Multitask deep learning for prediction of microvascular invasion and recurrence-free survival in hepatocellular carcinoma based on MRI images.

BACKGROUND AND AIMS: Accurate preoperative prediction of microvascular invasion (MVI) and recurrence-free survival (RFS) is vital for personalised hepatocellular carcinoma (HCC) management. We developed a multitask deep learning model to predict MVI and RFS using preoperative MRI scans. METHODS: Utilising a retrospective dataset of 725 HCC patients from seven institutions, we developed and validated a multitask deep learning model focused on predicting MVI and RFS. The model employs a transformer architecture to extract critical features from preoperative MRI scans. It was trained on a set of 234 patients and internally validated on a set of 58 patients. External validation was performed using three independent sets (n = 212, 111, 110). RESULTS: The multitask deep learning model yielded high MVI prediction accuracy, with AUC values of 0.918 for the training set and 0.800 for the internal test set. In external test sets, AUC values were 0.837, 0.815 and 0.800. Radiologists' sensitivity and inter-rater agreement for MVI prediction improved significantly when integrated with the model. For RFS, the model achieved C-index values of 0.763 in the training set and ranged between 0.628 and 0.728 in external test sets. Notably, PA-TACE improved RFS only in patients predicted to have high MVI risk and low survival scores (p < .001). CONCLUSIONS: Our deep learning model allows accurate MVI and survival prediction in HCC patients. Prospective studies are warranted to assess the clinical utility of this model in guiding personalised treatment in conjunction with clinical criteria.

Iodine Adsorption-Desorption-Induced Structural Transformation and Improved Ag+ Turn-On Luminescent Sensing Performance of a Nonporous Eu(III) Metal-Organic Framework.

Posttreatment of pristine metal-organic frameworks (MOFs) with suitable vapor may be an effective way to regulate their structures and properties but has been less explored. Herein, we report an interesting example in which a crystalline nonporous Eu(III)-MOF was transferred to a porous amorphous MOF (aMOF) via iodine vapor adsorption-desorption posttreatment, and the resulting aMOF showed improved turn-on sensing properties with respect to Ag+ ions. The crystalline Eu-MOF, namely, Eu-IPDA, was assembled from Eu(III) and 4,4'-{4-[4-(1H-imidazol-1-yl)phenyl]pyridine-2,6-diyl}dibenzoic acid (H2IPDA) and exhibited a two-dimensional (2D) coordination network based on one-dimensional secondary building blocks. The close packing of the 2D networks gives rise to a three-dimensional supramolecular framework without any significant pores. Interestingly, the nonporous Eu-IPDA could absorb iodine molecules when Eu-IPDA crystals were placed in iodine vapor at 85 °C, and the adsorption capacity was 1.90 g/g, which is comparable to those of many MOFs with large BET surfaces. The adsorption of iodine is attributed to the strong interactions among the iodine molecule, the carboxy group, and the N-containing group and leads to the amorphization of the framework. After immersion of the iodine-loaded Eu-IPDA in EtOH, approximately 89.7% of the iodine was removed, resulting in a porous amorphous MOF, denoted as a-Eu-IPDA. In addition, the remaining iodine in the a-Eu-IPDA framework causes strong luminescent quenching in the fluorescence emission region of the Eu(III) center when compared with that in Eu-IPDA. The luminescence intensity of a-Eu-IPDA in water suspensions was significantly enhanced when Ag+ ions were added, with a detection limit of 4.76 × 10-6 M, which is 1000 times that of pristine Eu-IPDA. It also showed strong anti-interference ability over many common competitive metal ions and has the potential to sense Ag+ in natural water bodies and traditional Chinese medicine preparations. A mechanistic study showed that the interactions between Ag+ and the absorbed iodine, the carboxylate group, and the N atoms all contribute to the sensing performance of a-Eu-IPDA.

MicroRNA miR-722 Inhibits Cyprinid Herpesvirus 3 Replication via Targeting the Viral Immune Evasion Protein ORF89, Which Negatively Regulates IFN by Degrading IRF3.

Cyprinid herpesvirus 3 (CyHV-3) has caused severe economic losses to carp culture, but its pathogenicity is far from clear. Our previous study has revealed that microRNA (miR)-722 was upregulated during CyHV-3 infection, indicating that miR-722 might play an important role in CyHV-3 replication. In this study, we found that overexpression of miR-722 inhibited CyHV-3 replication and promoted IFN expression. The putative target gene of miR-722 was searched over the CyHV-3 genome, and ORF89 was identified and validated as a target gene of miR-722. Overexpression of ORF89 markedly reduced the expression of IFN and IFN-stimulated genes. Mechanistically, ORF89 interacted with and degraded IFN regulatory factor 3 (IRF3), and inhibited the entry of IRF3 into the nucleus by suppressing the dimerization of IRF3. Moreover, ORF89-mediated suppression of IFN expression could be restored by adding miR-722. To our knowledge, our findings confirm a novel virus-host combat, in which CyHV-3 evades host antiviral immunity by its ORF89 protein, whereas host miR-722, upregulated on CyHV-3 infection, targets ORF89 to impede CyHV-3 replication.

Genetic associations between bipolar disorder and brain structural phenotypes.

Patients with bipolar disorder (BD) and their first-degree relatives exhibit alterations in brain volume and cortical structure, whereas the underlying genetic mechanisms remain unclear. In this study, based on the published genome-wide association studies (GWAS), the extent of polygenic overlap between BD and 15 brain structural phenotypes was investigated using linkage disequilibrium score regression and MiXeR tool, and the shared genomic loci were discovered by conjunctional false discovery rate (conjFDR) and expression quantitative trait loci (eQTL) analyses. MiXeR estimated the overall measure of polygenic overlap between BD and brain structural phenotypes as 4-53% on a 0-100% scale (as quantified by the Dice coefficient). Subsequent conjFDR analyses identified 54 independent loci (71 risk single-nucleotide polymorphisms) jointly associated with BD and brain structural phenotypes with a conjFDR < 0.05, among which 33 were novel that had not been reported in the previous BD GWAS. Follow-up eQTL analyses in respective brain regions both confirmed well-known risk genes (e.g. CACNA1C, NEK4, GNL3, MAPK3) and discovered novel risk genes (e.g. LIMK2 and CAMK2N2). This study indicates a substantial shared genetic basis between BD and brain structural phenotypes, and provides novel insights into the developmental origin of BD and related biological mechanisms.

Research and application of a novel selective stacking ensemble model based on error compensation and parameter optimization for AQI prediction.

With the ongoing process of industrialization, the issue of declining air quality is increasingly becoming a critical concern. Accurate prediction of the Air Quality Index (AQI), considered as an all-inclusive measure representing the extent of pollutants present in the atmosphere, is of paramount importance. This study introduces a novel methodology that combines stacking ensemble and error correction to improve AQI prediction. Additionally, the reptile search algorithm (RSA) is employed for optimizing model parameters. In this study, four distinct regional AQI data containing a collection of 34864 data samples are collected. Initially, we perform cross-validation on ten commonly used single models to obtain prediction results. Then, based on evaluation indices, five models are selected for ensemble. The results of the study show that the model proposed in this paper achieves an improvement of around 10% in terms of accuracy when compared to the conventional model. Thus, the model introduced in this study offers a more scientifically grounded approach in tackling air pollution.

Therapeutic Potential of Danyankang Capsule in High-Fat Diet-Induced Cholelithiasis and Its Impact on Liver FXR Signaling and Gut Microbiota.

Cholelithiasis, commonly known as gallstones, represents a prevalent hepatobiliary disorder. This study aimed to elucidate the therapeutic role and mechanism of Danyankang capsulein treating cholelithiasis induced by a high-fat diet in C57BL/6 mice. The therapeutical potential of Danyankang was assessed through biochemical analyses, histopathological examinations, protein detection, and 16S rDNA sequencing. A high-fat diet resulted in cholelithiasis manifestation in mice, with discernable abnormal serum biochemical indices and disrupted biliary cholesterol homeostasis. Danyankang treatment notably ameliorated liver inflammation symptoms and rectified serum and liver biochemical abnormalities. Concurrently, it addressed biliary imbalances. Elevated expressions of toll-like receptor 4 (TLR4), nuclear factor-kappaB (NF-κB)/pNF-κB, HMGCR, CYP7A1, and CYP8B1 observed at the inception of cholelithiasis, were notably reduced upon Danyankang administration. Furthermore, 16S rDNA analysis revealed a decline in species number and diversity of the intestinal flora in cholelithiasis-treated mice, while the decline was reversed with Danyankang treatment. Danyankang capsules reduced the abundance of Verrucomicrobiota and increased the abundance of Actinobacteriota and Proteobacteria. In conclusion, the present study demonstrates that Danyankang exerts potent therapeutic efficacy against high-fat diet-induced cholelithiasis. This beneficial outcome is potentially linked to the inhibition of the TLR4/pNF-κB and SHP/CYP7A1/CYP8B1 signaling pathways, as well as the enhancement of intestinal flora species abundance.

Sinomenine attenuates pulmonary fibrosis by downregulating TGF-ß1/Smad3, PI3K/Akt and NF-κB signaling pathways.

BACKGROUND: Since COVID-19 became a global epidemic disease in 2019, pulmonary fibrosis (PF) has become more prevalent among persons with severe infections, with IPF being the most prevalent form. In traditional Chinese medicine, various disorders are treated using Sinomenine (SIN). The SIN's strategy for PF defense is unclear. METHODS: Bleomycin (BLM) was used to induce PF, after which inflammatory factors, lung histological alterations, and the TGF-/Smad signaling pathway were assessed. By administering various dosages of SIN and the TGF- receptor inhibitor SB-431,542 to human embryonic lung fibroblasts (HFL-1) and A549 cells, we were able to examine proliferation and migration as well as the signaling molecules implicated in Epithelial-Mesenchymal Transition (EMT) and Extra-Cellular Matrix (ECM). RESULTS: In vivo, SIN reduced the pathological changes in the lung tissue induced by BLM, reduced the abnormal expression of inflammatory cytokines, and improved the weight and survival rate of mice. In vitro, SIN inhibited the migration and proliferation by inhibiting TGF-ß1/Smad3, PI3K/Akt, and NF-κB pathways, prevented the myofibroblasts (FMT) of HFL-1, reversed the EMT of A549 cells, restored the balance of matrix metalloenzymes, and reduced the expression of ECM proteins. CONCLUSION: SIN attenuated PF by down-regulating TGF-ß/Smad3, PI3K/Akt, and NF-κB signaling pathways, being a potential effective drug in the treatment of PF.

Clinical significance and potential pathogenesis of VCAN in adult non-cystic fibrosis bronchiectasis: a retrospective study.

BACKGROUND: The pathogenesis of adult non-cystic fibrosis (CF) bronchiectasis is complex, and the relevant molecular mechanism remains ambiguous. Versican (VCAN) is a key factor in inflammation through interactions with adhesion molecules. This study constructs a stable panoramic map of mRNA, reveals the possible pathogenesis of bronchiectasis, and provides new ideas and methods for bronchiectasis. METHODS: Peripheral blood and tissue gene expression data from patients with bronchiectasis and normal control were selected by bioinformatics analysis. The expression of VCAN in peripheral blood and bronchial tissues of bronchiectasis were obtained by transcriptome sequencing. The protein expression levels of VCAN in serums were verified by the enzyme-linked immunosorbent assay (ELISA). The mRNA expression levels of VCAN in co-culture of Pseudomonas aeruginosa and bronchial epithelial cells were verified by real-time quantitative polymerase chain reaction (RT-qPCR). In addition, the biological function of VCAN was detected by the transwell assay. RESULTS: The expression of VCAN was upregulated in the bronchiectasis group by sequencing analysis (P < 0.001). The expression of VCAN in the bronchial epithelial cell line BEAS-2B was increased in P. aeruginosa (P.a), which was co-cultured with BEAS-2B cells (P < 0.05). The concentration of VCAN protein in the serum of patients with bronchiectasis was higher than that in the normal control group (P < 0.05). Transwell experiments showed that exogenous VCAN protein induced the migration of neutrophils (P < 0.0001). CONCLUSIONS: Our findings indicate that VCAN may be involved in the development of bronchiectasis by increasing the migration of neutrophils and play an important role in bronchial pathogenesis.

A new insight into the mechanism of dichlorodiphenyltrichloroethane-induced hepatotoxicity based on GSDME-mediated pyroptosis.

There have been persistent concerns about the safety risks associated with DDT residues in the environment. Studies have shown that exposure to DDT or its metabolites can cause various liver diseases. However, the mechanisms of liver toxicity haven't been well studied. In our current investigation, we observed that DDT triggers pyroptosis in human liver cells (HL-7702), representing a novel form of programmed cell death. Our results delineated DDT (0-100 µM) induced pyroptosis in HL-7702 cells, which was confirmed through morphological changes, lactate dehydrogenase (LDH) release, gasdermin E (GSDME) cleavage and Annexin-V/PI staining. Knockdown of GSDME reduced cell death and transferred the mode of cell death from pyroptosis to apoptosis. Notably, DDT exposure markedly increased reactive oxygen species (ROS) production, concurrent with c-Jun N-terminal kinase (JNK) phosphorylation. Intervention with a ROS inhibitor or JNK inhibitor SP600125 restored cell viability and hindered GSDME-mediated pyroptosis. Our results firstly demonstrate that DDT suppresses HL-7702 cells growth by inducing pyroptosis mainly through the ROS/JNK/GSDME pathway. These findings not only contribute to an in-depth understanding of DDT toxicity but also open avenues for gaining valuable insights into potential mitigation strategies and therapeutic interventions.

Single intravenous and oral dose pharmacokinetics of the antiseizure medication brivaracetam in healthy cats.

The number of available antiseizure medications with demonstrated efficacy in cats is limited. As such, there is a need to evaluate the pharmacokinetics of newer medications so that proper dosing regimens can be made. Brivaracetam (BRV) is a more potent analogue of levetiracetam, and is Food and Drug Administration approved for use in people. The goal of this study was to describe the pharmacokinetics of intravenous and oral doses of BRV in healthy cats. A cross-over study involving eight healthy cats, that were administered 10 mg of BRV intravenously as a bolus and orally in the fasted state. Blood samples were collected over 24 h. Analysis was performed using liquid chromatography-mass spectrometry. Data were subjected to non-compartmental analysis. Median (min-max) of maximal concentration, time to maximal concentration, area under the curve, elimination half-life and oral absolute bioavailability were 902 (682-1036) ng/mL, 0.6 (0.5-2.0) h, 6.4 (5.2-7.2) h, 8145 (6669-9351) ng × h/mL and 100% (85-110) respectively. BRV appeared to be well tolerated by all cats. A single dose of BRV is well tolerated both orally and intravenously. Maximal concentrations are produced rapidly and within the human reference interval considered to be therapeutic.

Simultaneously predicting SPAD and water content in rice leaves using hyperspectral imaging with deep multi-task regression and transfer component analysis.

BACKGROUND: Water content and chlorophyll content are important indicators for monitoring rice growth status. Simultaneous detection of water content and chlorophyll content is of significance. Different varieties of rice show differences in phenotype, resulting in the difficulties of establishing a universal model. In this study, hyperspectral imaging was used to detect the Soil and Plant Analyzer Development (SPAD) values and water content of fresh rice leaves of three rice varieties (Jiahua 1, Xiushui 121 and Xiushui 134). RESULTS: Both partial least squares regression and convolutional neural networks were used to establish single-task and multi-task models. Transfer component analysis (TCA) was used as transfer learning to learn the common features to achieve an approximate identical distribution between any two varieties. Single-task and multi-task models were also built using the features of the source domain, and these models were applied to the target domain. These results indicated that for models of each rice variety the prediction accuracy of most multi-task models was close to that of single-task models. As for TCA, the results showed that the single-task model achieved good performance for all transfer learning tasks. CONCLUSION: Compared with the original model, good and differentiated results were obtained for the models using features learned by TCA for both the source domain and target domain. The multi-task models could be constructed to predict SPAD values and water content simultaneously and then transferred to another rice variety, which could improve the efficiency of model construction and realize rapid detection of rice growth indicators. © 2024 Society of Chemical Industry.

A novel method combining deep learning with the Kennard-Stone algorithm for training dataset selection for image-based rice seed variety identification.

BACKGROUND: Different varieties of rice vary in planting time, stress resistance, and other characteristics. With advances in rice-breeding technology, the number of rice varieties has increased significantly, making variety identification crucial for both trading and planting. RESULTS: This study collected RGB images of 20 hybrid rice seed varieties. An enhanced deep super-resolution network (EDSR) was employed to enhance image resolution, and a variety classification model utilizing the high-resolution dataset demonstrated superior performance to that of the model using the low-resolution dataset. A novel training sample selection methodology was introduced integrating deep learning with the Kennard-Stone (KS) algorithm. Convolutional neural networks (CNN) and autoencoders served as supervised and unsupervised feature extractors, respectively. The extracted feature vectors were subsequently processed by the KS algorithm to select training samples. The proposed methodologies exhibited superior performance over the random selection approach in rice variety classification, with an approximately 10.08% improvement in overall classification accuracy. Furthermore, the impact of noise on the proposed methodology was investigated by introducing noise to the images, and the proposed methodologies maintained superior performance relative to the random selection approach on the noisy image dataset. CONCLUSION: The experimental results indicate that both supervised and unsupervised learning models performed effectively as feature extractors, and the deep learning framework significantly influenced the selection of training set samples. This study presents a novel approach for training sample selection in classification tasks and suggests the potential for extending the proposed method to image datasets and other types of datasets. Further exploration of this potential is warranted. © 2024 Society of Chemical Industry.

Detection of peach soluble solids based on near-infrared spectroscopy with High Order Spatial Interaction network.

BACKGROUND: Due to the scalability of deep learning technology, researchers have applied it to the non-destructive testing of peach internal quality. In addition, the soluble solids content (SSC) is an important internal quality indicator that determines the quality of peaches. Peaches with high SSC have a sweeter taste and better texture, making them popular in the market. Therefore, SSC is an important indicator for measuring peach internal quality and making harvesting decisions. RESULTS: This article presents the High Order Spatial Interaction Network (HOSINet), which combines the Position Attention Module (PAM) and Channel Attention Module (CAM). Additionally, a feature wavelength selection algorithm similar to the Group-based Clustering Subspace Representation (GCSR-C) is used to establish the Position and Channel Attention Module-High Order Spatial Interaction (PC-HOSI) model for peach SSC prediction. The accuracy of this model is compared with traditional machine learning and traditional deep learning models. Finally, the permutation algorithm is combined with deep learning models to visually evaluate the importance of feature wavelengths. Increasing the order of the PC-HOSI model enhances its ability to learn spatial correlations in the dataset, thus improving its predictive performance. CONCLUSION: The optimal model, PC-HOSI model, performed well with an order of 3 (PC-HOSI-3), with a root mean square error of 0.421 °Brix and a coefficient of determination of 0.864. Compared with traditional machine learning and deep learning algorithms, the coefficient of determination for the prediction set was improved by 0.07 and 0.39, respectively. The permutation algorithm also provided interpretability analysis for the predictions of the deep learning model, offering insights into the importance of spectral bands. These results contribute to the accurate prediction of SSC in peaches and support research on interpretability of neural network models for prediction. © 2024 Society of Chemical Industry.