SlPHL1 positively modulates acid phosphatase in response to phosphate starvation by directly activating the genes SlPAP10b and SlPAP15 in tomato.

Increased acid phosphatase (APase) activity is a prominent feature of tomato (Solanum lycopersicum) responses to inorganic phosphate (Pi) restriction. SlPHL1, a phosphate starvation response (PHR) transcription factor, has been identified as a positive regulator of low Pi (LP)-induced APase activity in tomato. However, the molecular mechanism underlying this regulation remains to be elucidated. Here, SlPHL1 was found to positively regulate the LP-induced expression of five potential purple acid phosphatase (PAP) genes, namely SlPAP7, SlPAP10b, SlPAP12, SlPAP15, and SlPAP17b. Furthermore, we provide evidence that SlPHL1 can stimulate transcription of these five genes by binding directly to the PHR1 binding sequence (P1BS) located on their promoters. The P1BS mutation notably weakened SlPHL1 binding to the promoters of SlPAP7, SlPAP12, and SlPAP17b but almost completely abolished SlPHL1 binding to the promoters of SlPAP10b and SlPAP15. As a result, the transcriptional activation of SlPHL1 on SlPAP10b and SlPAP15 was substantially diminished. In addition, not only did transient overexpression of either SlPAP10b or SlPAP15 in tobacco leaves increase APase activity, but overexpression of SlPAP15 in Arabidopsis and tomato also increased APase activity and promoted plant growth. Subsequently, two SPX proteins, SlSPX1 and SlSPX4, were shown to physically interact with SlPHL1. Moreover, SlSPX1 inhibited the transcriptional activation of SlPHL1 on SlPAP10b and SlPAP15 and negatively regulated the activity of APase. Taken together, these results demonstrate that SlPHL1-mediated LP signaling promotes APase activity by activating the transcription of SlPAP10b and SlPAP15, which may provide valuable insights into the mechanisms of tomato response to Pi-limited stress.

Molecular characterization of the grass carp bscl2 gene and its expression response to lipid accumulation, nutritional status, insulin and glucagon.

Bscl2 plays a role in lipid metabolism of mammals, however its role in teleost fish remains unclear. Using the grass carp (Ctenopharyngodon idella) as a model, the bscl2 gene was isolated from the brain and characterized. Thereafter, the tissue distribution of the gene was examined, before expression was analyzed as a function of fasting, refeeding, oral glucose administration and overfeeding. In addition, bscl2 mRNA levels were evaluated in grass carp primary hepatocytes treated with glucagon, insulin, oleic acid, and glucose. Results showed that the cloned bscl2 gene was 1341 bp, encoding 446 amino acids, and was highly expressed in the brain, heart, and gonad. Following oral glucose administration, bscl2 expression increased. Expression of bscl2 decreased in fasted fish but increased following refeeding. Overfeeding, which resulted in elevated lipid accumulation, also stimulated bscl2 expression. In primary hepatocytes, bscl2 levels were increased by glucose, oleic acid, and insulin treatments, and reduced by glucagon treatment. These data suggest that bscl2 may play an important role in nutrient metabolism in teleost fish.

Cloning grass carp (Ctenopharyngodon idella) ccdc3 and its expression affected by nutrition state, insulin, and glucagon.

As an adipokine, coiled-coil domain-containing 3 (CCDC3) plays multiple physiological roles in fatty liver, lipid metabolism, and abdominal obesity. Grass carp was selected as the experimental animal in this study to investigate the roles of Ccdc3 in teleosts. Results showed that the open reading frame (ORF) of cloned ccdc3 was 831 bp and encoded 276 amino acids. Three N-glycosylation sites and a predicted coiled-coil domain motif were located in the identified Ccdc3. Moreover, a nuclear localization signal (NLS) was contained in the coiled-coil domain motif of the identified Ccdc3. The results on tissue distribution revealed that ccdc3 was highly detected in grass carp fat and brain tissue. In the oral glucose tolerance test (OGTT), the expression of ccdc3 increased remarkably in the brain, hypothalamus, and visceral fat in the glucose treatment group. In the fasting and refeeding experiment, the ccdc3 expression levels were remarkably reduced in the brain, hypothalamus, and visceral fat after 14 days of fasting. In the refeeding group, the ccdc3 expression levels were considerably elevated compared with those in the fasting group. In the induced overfeeding experiment, the ccdc3 expression increased remarkably in the hepatopancreas, brain, and visceral fat tissues. The ccdc3 expression in the primary hepatocytes was remarkably increased with glucose, oleic acid, and insulin treatment. However, ccdc3 expression was markedly decreased with glucagon treatment. In conclusion, these results indicate that Ccdc3 is involved in regulating glucose and lipid metabolism of teleosts.

High-Speed and Accurate Diagnosis of Gastrointestinal Disease: Learning on Endoscopy Images Using Lightweight Transformer with Local Feature Attention.

In response to the pressing need for robust disease diagnosis from gastrointestinal tract (GIT) endoscopic images, we proposed FLATer, a fast, lightweight, and highly accurate transformer-based model. FLATer consists of a residual block, a vision transformer module, and a spatial attention block, which concurrently focuses on local features and global attention. It can leverage the capabilities of both convolutional neural networks (CNNs) and vision transformers (ViT). We decomposed the classification of endoscopic images into two subtasks: a binary classification to discern between normal and pathological images and a further multi-class classification to categorize images into specific diseases, namely ulcerative colitis, polyps, and esophagitis. FLATer has exhibited exceptional prowess in these tasks, achieving 96.4% accuracy in binary classification and 99.7% accuracy in ternary classification, surpassing most existing models. Notably, FLATer could maintain impressive performance when trained from scratch, underscoring its robustness. In addition to the high precision, FLATer boasted remarkable efficiency, reaching a notable throughput of 16.4k images per second, which positions FLATer as a compelling candidate for rapid disease identification in clinical practice.

AMP-EBiLSTM: employing novel deep learning strategies for the accurate prediction of antimicrobial peptides.

Antimicrobial peptides are present ubiquitously in intra- and extra-biological environments and display considerable antibacterial and antifungal activities. Clinically, it has shown good antibacterial effect in the treatment of diabetic foot and its complications. However, the discovery and screening of antimicrobial peptides primarily rely on wet lab experiments, which are inefficient. This study endeavors to create a precise and efficient method of predicting antimicrobial peptides by incorporating novel machine learning technologies. We proposed a deep learning strategy named AMP-EBiLSTM to accurately predict them, and compared its performance with ensemble learning and baseline models. We utilized Binary Profile Feature (BPF) and Pseudo Amino Acid Composition (PSEAAC) for effective local sequence capture and amino acid information extraction, respectively, in deep learning and ensemble learning. Each model was cross-validated and externally tested independently. The results demonstrate that the Enhanced Bi-directional Long Short-Term Memory (EBiLSTM) deep learning model outperformed others with an accuracy of 92.39% and AUC value of 0.9771 on the test set. On the other hand, the ensemble learning models demonstrated cost-effectiveness in terms of training time on a T4 server equipped with 16 GB of GPU memory and 8 vCPUs, with training durations varying from 0 to 30 s. Therefore, the strategy we propose is expected to predict antimicrobial peptides more accurately in the future.

SlPHL1 is involved in low phosphate stress promoting anthocyanin biosynthesis by directly upregulation of genes SlF3H, SlF3'H, and SlLDOX in tomato.

Phosphate (Pi) deficiency is a common stress that limits plant growth and development. Plants exhibit a variety of Pi starvation responses (PSRs), including anthocyanin accumulation. The transcription factors of the PHOSPHATE STARVATION RESPONSE (PHR) family, such as AtPHR1 in Arabidopsis, play central roles in the regulation of Pi starvation signaling. Solanum lycopersicum PHR1-like 1 (SlPHL1) is a recently identified PHR involved in PSR regulation in tomato, but the detailed mechanism of its participation in Pi starvation-inducing anthocyanin accumulation remains unclear. Here we found that overexpression of SlPHL1 in tomato increases the expression of genes associated with anthocyanin biosynthesis, thereby promoting anthocyanin biosynthesis, but silencing SlPHL1 with Virus Induced Gene Silencing (VIGS) attenuated low phosphate (LP) stress-induced anthocyanin accumulation and expression of the biosynthesis-related genes. Notably, SlPHL1 is able to bind the promoters of genes Flavanone 3-Hydroxylase (SlF3H), Flavanone 3'-Hydroxylase (SlF3'H), and Leucoanthocyanidin Dioxygenase (SlLDOX) by yeast one-hybrid (Y1H) analysis. Furthermore, Electrophoretic Mobility Shift Assay (EMSA) and transient transcript expression assay showed that PHR1 binding t (sequence (P1BS) motifs located on the promoters of these three genes are critical for SlPHL1 binding and enhancing the gene transcription. Additionally, allogenic overexpression of SlPHL1 could promote anthocyanin biosynthesis in Arabidopsis under LP conditions through the similar mechanism to AtPHR1, suggesting that SlPHL1 might be functionally conserved with AtPHR1 in this process. Taken together, SlPHL1 positively regulates LP-induced anthocyanin accumulation by directly promoting the transcription of SlF3H, SlF3'H and SlLDOX. These findings will contribute to understanding the molecular mechanism of PSR in tomato.

An Actinic Keratosis Auxiliary Diagnosis Method Based on an Enhanced MobileNet Model.

Actinic keratosis (AK) is a common precancerous skin lesion with significant harm, and it is often confused with non-actinic keratoses (NAK). At present, the diagnosis of AK mainly depends on clinical experience and histopathology. Due to the high difficulty of diagnosis and easy confusion with other diseases, this article aims to develop a convolutional neural network that can efficiently, accurately, and automatically diagnose AK. This article improves the MobileNet model and uses the AK and NAK images in the HAM10000 dataset for training and testing after data preprocessing, and we performed external independent testing using a separate dataset to validate our preprocessing approach and to demonstrate the performance and generalization capability of our model. It further compares common deep learning models in the field of skin diseases (including the original MobileNet, ResNet, GoogleNet, EfficientNet, and Xception). The results show that the improved MobileNet has achieved 0.9265 in accuracy and 0.97 in Area Under the ROC Curve (AUC), which is the best among the comparison models. At the same time, it has the shortest training time, and the total time of five-fold cross-validation on local devices only takes 821.7 s. Local experiments show that the method proposed in this article has high accuracy and stability in diagnosing AK. Our method will help doctors diagnose AK more efficiently and accurately, allowing patients to receive timely diagnosis and treatment.

Data-Driven Assisted Decision Making for Surgical Procedure of Hepatocellular Carcinoma Resection and Prognostic Prediction: Development and Validation of Machine Learning Models.

Background: Currently, surgical decisions for hepatocellular carcinoma (HCC) resection are difficult and not sufficiently personalized. We aimed to develop and validate data driven prediction models to assist surgeons in selecting the optimal surgical procedure for patients. Methods: Retrospective data from 361 HCC patients who underwent radical resection in two institutions were included. End-to-end deep learning models were built to automatically segment lesions from the arterial phase (AP) of preoperative dynamic contrast enhanced magnetic resonance imaging (DCE-MRI). Clinical baseline characteristics and radiomic features were rigorously screened. The effectiveness of radiomic features and radiomic-clinical features was also compared. Three ensemble learning models were proposed to perform the surgical procedure decision and the overall survival (OS) and recurrence-free survival (RFS) predictions after taking different solutions, respectively. Results: SegFormer performed best in terms of automatic segmentation, achieving a Mean Intersection over Union (mIoU) of 0.8860. The five-fold cross-validation results showed that inputting radiomic-clinical features outperformed using only radiomic features. The proposed models all outperformed the other mainstream ensemble models. On the external test set, the area under the receiver operating characteristic curve (AUC) of the proposed decision model was 0.7731, and the performance of the prognostic prediction models was also relatively excellent. The application web server based on automatic lesion segmentation was deployed and is available online. Conclusions: In this study, we developed and externally validated the surgical decision-making procedures and prognostic prediction models for HCC for the first time, and the results demonstrated relatively accurate predictions and strong generalizations, which are expected to help clinicians optimize surgical procedures.

Improved prognostic prediction model for liver cancer based on biomarker data screened by combined methods.

Liver cancer is a common cause of death from cancer in the population, with the 4th highest mortality rate from cancer worldwide. The high recurrence rate of hepatocellular carcinoma after surgery is an important cause of high mortality among patients. In this paper, based on eight scheduled core markers of liver cancer, an improved feature screening algorithm was proposed based on the analysis of the basic principles of the random forest algorithm, and the system was finally applied to liver cancer prognosis prediction to improve the prediction of biomarkers for liver cancer recurrence, and the impact of different algorithmic strategies on the prediction accuracy was compared and analyzed. The results showed that the improved feature screening algorithm was able to reduce the feature set by about 50% while ensuring that the prediction accuracy was reduced within 2%.

Feeding tea polysaccharides affects lipid metabolism, antioxidant capacity and immunity of common carp (Cyprinus carpio L.).

Tea polysaccharides plays a role in lipid metabolism, antioxidant capacity and immunity of mammals. To investigate the functions of tea polysaccharides on fish, the common carp (Cyprinus carpio L.) was selected as the animal model in this study. In our study, the common carp (45±0.71g) were randomly divided into four groups and were fed fodder with 50% carbohydrate. The common carp were orally administrated with 0 mg/kg BW (control group), 200 mg/kg BW (low-dose group), 400 mg/kg BW (medium-dose group) and 800 mg/kg BW (high-dose group) tea polysaccharide for two week. At the end of experiment, the serum glucose, TG, MDA contents and antioxidase activities were measured by commercial kits. The serum immune factors levels were tested by ELISA. The genes expression levels related to antioxidant capacity, metabolism and immunity were measured by real-time PCR. The results showed that the glucose, TG and MDA contents in serum were significantly decreased by tea polysaccharides treatment. The serum activities of SOD were significantly increased by low-dose tea polysaccharides treatment. The serum activities of GPX were significantly increased by medium-dose tea polysaccharides treatment. The serum levels of IL-1ß and TNFα were significantly decreased in the tea polysaccharides treatment group. In the high-dose treatment group, the serum level of TGFß was significantly increased, and the serum level of IL-12 was markedly decreased. In the hepatopancreas, the expression of acc1, fas, srebp1c, lpl, gys and pparγ were significantly reduced, and the expression of pygl, cat, mnsod, ho-1 and gr were significantly up-regulated in the tea polysaccharides group. In the intestine, the expression of zo-1, occ and gip was significantly up-regulated in the high-dose treatment group. Moreover, the expression of glut2 and sglt1 were significantly down regulated. In the spleen, the expression of il-12, tnfα and il-6 were significantly decreased, and the expression of il-10 and tgfß was significantly increased by the tea polysaccharides. In the spleen cells, the tea polysaccharides could relieve the LPS-induced immune damage. In conclusion, tea polysaccharides can improve antioxidant capacity, lipid metabolism and immunity of common carp.

Molecular Characterization of Grass Carp GIPR and Effect of Nutrition States, Insulin, and Glucagon on Its Expression.

GIP plays an important regulatory role in glucose and lipid metabolism. As the specific receptor, GIPR is involved in this physiological process. To assess the roles of GIPR in teleost, the GIPR gene was cloned from grass carp. The ORF of cloned GIPR gene was 1560 bp, encoding 519 amino acids. The grass carp GIPR was the G-protein-coupled receptor which contains seven predicted transmembrane domains. In addition, two predicted glycosylation sites were contained in the grass carp GIPR. The grass carp GIPR expression is in multiple tissues and is highly expressed in the kidney, brain regions, and visceral fat tissue. In the OGTT experiment, the GIPR expression is markedly decreased in the kidney, visceral fat, and brain by treatment with glucose for 1 and 3 h. In the fast and refeeding experiment, the GIPR expression in the kidney and visceral fat tissue was significantly induced in the fast groups. In addition, the GIPR expression levels were markedly decreased in the refeeding groups. In the present study, the visceral fat accumulation of grass carp was induced by overfed. The GIPR expression was significantly decreased in the brain, kidney, and visceral fat tissue of overfed grass carp. In primary hepatocytes, the GIPR expression was promoted by treatment with oleic acid and insulin. The GIPR mRNA levels were significantly reduced by treatment with glucose and glucagon in the grass carp primary hepatocytes. To our knowledge, this is the first time the biological role of GIPR is unveiled in teleost.

Combining Preoperative and Postoperative Inflammatory Indicators Can Better Predict the Recurrence of Hepatocellular Carcinoma After Partial Hepatectomy.

PURPOSE: Previous studies have shown that various preoperative inflammatory indicators can predict the prognosis of hepatocellular carcinoma (HCC), but the role of postoperative inflammatory indicators remains unclear. This study aimed to explore the prognostic value of postoperative inflammatory indicators and whether combining preoperative and postoperative inflammatory indicators can improve the predictive performance of the prognostic model. PATIENTS AND METHODS: Eighty-eight patients with primary HCC were included in this study. A preoperative model, postoperative model, and combined model that integrated preoperative and postoperative inflammatory indicators were established. The prognostic value of the models was evaluated by the area under the curve of time-dependent receiver operating characteristic curves (td-AUC). RESULTS: Multivariate analysis of preoperative and postoperative inflammatory indicators and clinicopathological indicators found that tumor number, alpha-fetoprotein (AFP) level, and the preoperative platelet-lymphocyte ratio (prePLR), preoperative prognostic nutritional index (prePNI), and postoperative neutrophil-lymphocyte ratio (postNLR) were independent prognostic factors for the disease-free survival. The prognostic efficacy of the postNLR at 2 years and 3 years was better than that of tumor number, AFP level, and the prePLR, and prePNI. The combined model had higher td-AUC values than the preoperative model, postoperative model, American Joint Committee on Cancer 8th edition stage, and Barcelona Clinic Liver Cancer stage at 2 years (0.814 vs 0.754, 0.765, 0.513 and 0.527, respectively), and 3 years (0.786 vs 0.749, 0.753, 0.509 and 0.529, respectively). The predictive performance of the combined model was better than that of the preoperative model, postoperative model, and traditional clinical stage. CONCLUSION: Postoperative inflammatory indicators were valuable prognostic indicators. The combination of preoperative and postoperative inflammatory indicators improved the predictive performance of the prognostic model. We should pay more attention to postoperative inflammatory indicators.

Simultaneous realization of electromagnetically induced transparency and electromagnetically induced reflectance in a metasurface.

The analogue of electromagnetically induced transparency (EIT-like) and electromagnetically induced reflectance (EIR-like) effects have been intensively studied and achieved by using metasurfaces. Nevertheless, previous designs could realize only one of them and were unable to support both effects in a metasurface. Here we numerically and experimentally demonstrate a metasurface simultaneously exhibiting EIT-like and EIR-like effects. Qualitative analyses and quantitative calculations based on the electromagnetic multipole decomposition method are performed to reveal their formation mechanisms. Our work offers a simple avenue for simultaneously realizing EIT-like and EIR-like effects in a metasurface, which may find potential applications in sensing, filtering, and slow wave devices.

Prognostic value of the postoperative neutrophil-lymphocyte ratio in solid tumors: A meta-analysis.

PURPOSE: Numerous studies have demonstrated that a variety of systemic inflammatory markers were associated with the survival of different tumors. However, the association between elevated postoperative neutrophil-lymphocyte ratio (postNLR) and long-term outcomes, including overall survival (OS), disease-free survival (DFS), in patients with solid tumors remains controversial. A systematic review was conducted to explore the association between the postNLR and long-term outcomes in solid tumors. MATERIALS AND METHODS: Relevant literature was identified using PubMed, Embase, Web of Science, and the Cochrane Library from the initiation of the databases to October 2020. Data were extracted from included studies reporting hazard ratio (HR) and 95% confidence intervals (CI), and were pooled using generic inverse-variance and random-effects modeling. 25 studies reporting on7539 patients were included in the analysis. RESULTS: Elevated postNLR was associated with poor OS (HR 1.87, 95% CI = 1.53-2.28; P < 0.00001), and worse DFS (HR 1.69, 95% CI = 1.28-2.22; P = 0.0002). Subgroup analyses showed that the trend of the pooled HR for most of the subgroups was not changed, and the heterogeneity of the same tumor type was not obvious. However, there was no correlation between high postNLR obtained within 7days and poor DFS (n = 3, HR 1.25, 95CI% = 0.54-2.88; P = 0.60). CONCLUSIONS: Elevated postNLR might be a readily available and inexpensive biomarker for long-term outcomes in solid tumors. Multicenter and prospective studies are needed to explore the impact of the postNLR on the prognosis of solid tumors.

Genetic and phenotypic characteristics of four Chinese families with fundus albipunctatus.

Fundus albipunctatus (FA) is a rare autosomal recessive form of stationary night blindness characterized by the presence of white or white-yellow dots in the perimacular area and the periphery of the retina, with or without macular involvement. In this study, we examined four Chinese families with FA. Patients were given complete ophthalmic examinations, and blood samples were collected for DNA extraction. Three genes, RDH5, RLBP1 and RPE65, were screened by direct sequencing. Mutations in RDH5 were identified in three families and mutations in RPE65 were identified in one family. This is the second reported case of FA caused by mutations in RPE65.

Coupling between energy and phase in hollow-core fiber based f-to-2f interferometers.

The dependence of the carrier-envelope (CE) phase of the pulses from a hollow-core fiber on the input laser energy was studied using two f-to- 2f interferometers. The CE phase in the in-loop f-to-2f interferometer was measured with the octave spanning white-light spectrum from the hollow-core fiber, whereas the out-of-loop interferometer was based on a sapphire plate. By modulating the input power of the in-loop interferometer and measuring the out-of-loop CE phase at the same time, the coupling coefficient between the measured CE phase and the laser energy for the hollow-core fiber was determined to be 128 mrad per 1% energy change .

Mechanism of phase-energy coupling in f-to-2f interferometry.

White-light generation has been used widely in single-shot f-to-2f interferometers for stabilizing the carrier-envelope (CE) phase of laser amplifiers. The accuracy of the relative phase values measured by such an interferometer is affected by fluctuations in the laser pulse energy. A simple two-step model is proposed to explain the mechanism that couples the laser energy and the CE phase. The model explains the experimentally observed dependence of the group delay between the f and the 2f pulses on the laser energy, as well as the CE phase shift caused by the pulse energy variation.

Generation of 0.5 mJ, few-cycle laser pulses by an adaptive phase modulator.

Previously, pulses shorter than 4 fs were generated by compressing white light from gas-filled hollow-core fibers with adaptive phase modulators; however, the energy of the few-cycle pulses was limited to 15 microJ. Here, we report the generation of 550 microJ, 5 fs pulses by using a liquid crystal spatial light modulator in a grating-based 4f system. The high pulse energy was obtained by improving the throughput of the phase modulator and by increasing the input laser energy. When the pulses were used in high harmonic generation, it was found that the harmonic spectra depend strongly on the high order spectral phases of the driving laser fields.

Double optical gating of high-order harmonic generation with carrier-envelope phase stabilized lasers.

We demonstrated a novel optical switch to control the high-order harmonic generation process so that single attosecond pulses can be generated with multiple-cycle pulses. The technique combines two powerful optical gating methods: polarization gating and two-color gating. An extreme ultraviolet supercontinuum supporting 130 as was generated with neon gas using 9 fs laser pulses. We discovered a unique dependence of the harmonic spectra on the carrier-envelope phase of the laser fields, which repeats every 2 pi radians.

Determining the phase-energy coupling coefficient in carrier-envelope phase measurements.

For f-to-2f interferometers based on white-light generation in sapphire plates, the accuracy of the carrier-envelope (CE) phase measurement and stabilization is affected by the laser energy fluctuation. The coupling coefficient between the CE phase and the laser energy has been determined by modulating the pulse energy in an in-loop f-to-2f interferometer while measuring the CE phase variation with an out-loop interferometer. When the total spectral phase measured by the in-loop interferometer was locked, a 1% change in laser energy caused a 160 mrad shift in the CE phase of the output pulses.