Off-Design Operation and Cavitation Detection in Centrifugal Pumps Using Vibration and Motor Stator Current Analyses.

Centrifugal pumps are essential in many industrial processes. An accurate operation diagnosis of centrifugal pumps is crucial to ensure their reliable operation and extend their useful life. In real industry applications, many centrifugal pumps lack flowmeters and accurate pressure sensors, and therefore, it is not possible to determine whether the pump is operating near its best efficiency point (BEP). This paper investigates the detection of off-design operation and cavitation for centrifugal pumps with accelerometers and current sensors. To this end, a centrifugal pump was tested under off-design conditions and various levels of cavitation. A three-axis accelerometer and three Hall-effect current sensors were used to collect vibration and stator current signals simultaneously under each state. Both kinds of signals were evaluated for their effectiveness in operation diagnosis. Signal processing methods, including wavelet threshold function, variational mode decomposition (VMD), Park vector modulus transformation, and a marginal spectrum were introduced for feature extraction. Seven families of machine learning-based classification algorithms were evaluated for their performance when used for off-design and cavitation identification. The obtained results, using both types of signals, prove the effectiveness of both approaches and the advantages of combining them in achieving the most reliable operation diagnosis results for centrifugal pumps.

The phenotypic changes of Schwann cells promote the functional repair of nerve injury.

Functional recovery after nerve injury is a significant challenge due to the complex nature of nerve injury repair and the non-regeneration of neurons. Schwann cells (SCs), play a crucial role in the nerve injury repair process because of their high plasticity, secretion, and migration abilities. Upon nerve injury, SCs undergo a phenotypic change and redifferentiate into a repair phenotype, which helps in healing by recruiting phagocytes, removing myelin fragments, promoting axon regeneration, and facilitating myelin formation. However, the repair phenotype can be unstable, limiting the effectiveness of the repair. Recent research has found that transplantation of SCs can be an effective treatment option, therefore, it is essential to comprehend the phenotypic changes of SCs and clarify the related mechanisms to develop the transplantation therapy further.

Transcriptome analysis reveals the key network of axillary bud outgrowth modulated by topping in citrus.

Topping, an important tree shaping and pruning technique, can promote the outgrowth of citrus axillary buds. However, the underlying molecular mechanism is still unclear. In this study, spring shoots of Citrus reticulata 'Huagan No.2' were topped and transcriptome was compared between axillary buds of topped and untopped shoots at 6 and 11 days after topping (DAT). 1944 and 2394 differentially expressed genes (DEGs) were found at 6 and 11 DAT, respectively. KEGG analysis revealed that many DEGs were related to starch and sucrose metabolism, signal transduction of auxin, cytokinin and abscisic acid. Specially, transcript levels of auxin synthesis, transport, and signaling-related genes (SAURs and ARF5), cytokinin signal transduction related genes (CRE1, AHP and Type-A ARRs), ABA signal responsive genes (PYL and ABF) were up-regulated by topping; while transcript levels of auxin receptor TIR1, auxin responsive genes AUX/IAAs, ABA signal transduction related gene PP2Cs and synthesis related genes NCED3 were down-regulated. On the other hand, the contents of sucrose and fructose in axillary buds of topped shoots were significantly higher than those in untopped shoots; transcript levels of 16 genes related to sucrose synthase, hexokinase, sucrose phosphate synthase, endoglucanase and glucosidase, were up-regulated in axillary buds after topping. In addition, transcript levels of genes related to trehalose 6-phosphate metabolism and glycolysis/tricarboxylic acid (TCA) cycle, as well to some transcription factors including Pkinase, Pkinase_Tyr, Kinesin, AP2/ERF, P450, MYB, NAC and Cyclin_c, significantly responded to topping. Taken together, the present results suggested that topping promoted citrus axillary bud outgrowth through comprehensively regulating plant hormone and carbohydrate metabolism, as well as signal transduction. These results deepened our understanding of citrus axillary bud outgrowth by topping and laid a foundation for further research on the molecular mechanisms of citrus axillary bud outgrowth.

Predicting Survival Using Whole-Liver MRI Radiomics in Patients with Hepatocellular Carcinoma After TACE Refractoriness.

PURPOSE: To develop a model based on whole-liver radiomics features of pre-treatment enhanced MRI for predicting the prognosis of hepatocellular carcinoma (HCC) patients undergoing continued transarterial chemoembolization (TACE) after TACE-resistance. MATERIALS AND METHODS: Data from 111 TACE-resistant HCC patients between January 2014 and March 2018 were retrospectively collected. At a ratio of 7:3, patients were randomly assigned to developing and validation cohorts. The whole-liver were manually segmented, and the radiomics signature was extracted. The tumor and liver radiomics score (TLrad-score) was calculated. Models were trained by machine learning algorithms and their predictive efficacies were compared. RESULTS: Tumor stage, tumor burden, body mass index, alpha-fetoprotein, and vascular invasion were revealed as independent risk factors for survival. The model trained by Random Forest algorithms based on tumor burden, whole-liver radiomics signature, and clinical features had the highest predictive efficacy, with c-index values of 0.85 and 0.80 and areas under the ROC curve of 0.96 and 0.83 in the developing cohort and validation cohort, respectively. In the high-rad-score group (TLrad-score > - 0.34), the median overall survival (mOS) was significantly shorter than in the low-rad-score group (17 m vs. 37 m, p < 0.001). A shorter mOS was observed in patients with high tumor burden compared to those with low tumor burden (14 m vs. 29 m, p = 0.007). CONCLUSION: The combined radiomics model from whole-liver signatures may effectively predict survival for HCC patients continuing TACE after TACE refractoriness. The TLrad-score and tumor burden are potential prognostic markers for TACE therapy following TACE-resistance.

Low temperature acclimation of electroactive microorganisms may be an effective strategy to enhance the toxicity sensing performance of microbial fuel cell sensors.

Microbial fuel cell (MFC) sensing is a promising method for real-time detection of water biotoxicity, however, the low sensing sensitivity limits its application. This study adopted low temperature acclimation as a strategy to enhance the toxicity sensing performance of MFC biosensor. Two types of MFC biosensors were started up at low (10 °C) or warm (25 °C) temperature, denoted as MFC-Ls and MFC-Ws respectively, using Pb2+ as the toxic substance. MFC-Ls exhibited superior sensing sensitivities towards Pb2+ compared with MFC-Ws at both low (10 °C) and warm (25 °C) operation temperatures. For example, the inhibition rate of voltage of MFC-Ls was 22.81 % with 1 mg/L Pb2+ shock at 10 °C, while that of MFC-Ws was only 5.9 %. The morphological observation showed the anode biofilm of MFC-Ls had appropriate amount of extracellular polymer substances, thinner thickness (28.95 µm for MFC-Ls and 41.58 µm for MFC-Ws) and higher proportion of living cells (90.65 % for MFC-Ls and 86.01 % for MFC-Ws) compared to that of MFC-Ws. Microbial analysis indicated the enrichment of psychrophilic electroactive microorganisms and cold-active enzymes as well as their sensitivity to Pb2+ shock was the foundation for the effective operation and good performance of MFC-Ls biosensors. In conclusion, low temperature acclimation of electroactive microorganisms enhanced not only the sensitivity but also the temperature adaptability of MFC biosensors.

Heparan sulfate selectively inhibits the collagenase activity of cathepsin K.

Cathepsin K (CtsK) is a cysteine protease with potent collagenase activity. CtsK is highly expressed by bone-resorbing osteoclasts and plays an essential role in resorption of bone matrix. Although CtsK is known to bind heparan sulfate (HS), the structural details of the interaction, and how HS regulates the biological functions of CtsK, remains largely unknown. In this report, we discovered that HS is a multifaceted regulator of the structure and function of CtsK. Structurally, HS forms a highly stable complex with CtsK and induces its dimerization. Co-crystal structures of CtsK with bound HS oligosaccharides reveal the location of the HS binding site and suggest how HS may support dimerization. Functionally, HS plays a dual role in regulating the enzymatic activity of CtsK. While it preserves the peptidase activity of CtsK by stabilizing its active conformation, it inhibits the collagenase activity of CtsK in a sulfation level-dependent manner. These opposing effects can be explained by our finding that the HS binding site is remote from the active site, which allows HS to specifically inhibit the collagenase activity without affecting the peptidase activity. At last, we show that structurally defined HS oligosaccharides effectively block osteoclast resorption of bone in vitro without inhibiting osteoclast differentiation, which suggests that HS-based oligosaccharide might be explored as a new class of selective CtsK inhibitor for many diseases involving exaggerated bone resorption.

A radiomics model of contrast-enhanced computed tomography for predicting post-acute pancreatitis diabetes mellitus.

Background: Diabetes mellitus can occur after acute pancreatitis (AP), but the accurate quantitative methods to predict post-acute pancreatitis diabetes mellitus (PPDM-A) are lacking. This retrospective study aimed to establish a radiomics model based on contrast-enhanced computed tomography (CECT) for predicting PPDM-A. Methods: A total of 374 patients with first-episode AP were retrospectively enrolled from two tertiary referral centers. There were 224 patients in the training cohort, 56 in the internal validation cohort, and 94 in the external validation cohort, and there were 86, 22, and 27 patients with PPDM-A in these cohorts, respectively. The clinical characteristics were collected from the hospital information system. A total of 2,398 radiomics features, including shape-based features, first-order histogram features, high order textural features, and transformed features, were extracted from the arterial- and venous-phase CECT images. Intraclass correlation coefficients were used to assess the intraobserver reliability and interobserver agreement. Random forest-based recursive feature elimination, collinearity analysis, and least absolute shrinkage and selection operator (LASSO) were used for selecting the final features. Three classification methods [eXtreme Gradient Boosting (XGBoost), Adaptive Boosting, and Decision Tree] were used to build three models and performances of the three models were compared. Each of the three classification methods were used to establish the clinical model, radiomics model, and combined model for predicting PPDM-A, resulting in a total of nine classifiers. The predictive performances of the models were evaluated by the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and F1-score. Results: Eleven radiomics features were selected after a reproducibility test and dimensionality reduction. Among the three classification methods, the XGBoost classifier showed better and more consistent performances. The AUC of the XGBoost's radiomics model to predict PPDM-A in the training, internal, and external cohorts was good (0.964, 0.901, and 0.857, respectively). The AUC of the XGBoost's combined model to predict PPDM-A in the training, internal, and external cohorts was good (0.980, 0.901, and 0.882, respectively). The AUC of the XGBoost's clinical model to predict PPDM-A in the training, internal, and external cohorts did not perform well (0.685, 0.733, and 0.619, respectively). In the external validation cohort, the AUC of the XGBoost's radiomics model was significantly higher than that of the clinical model (0.857 vs. 0.619, P<0.001), but there was no significant difference between the combined and radiomics models (0.882 vs. 0.857, P=0.317). Conclusions: The radiomics model based on CECT performs well and can be used as an early quantitative method to predict the occurrence of PPDM-A.

A Novel Rat Model to Simulate the Benign Esophageal Stricture Induced by Endoscopic Submucosal Dissection.

Objective: This study aimed to establish a rat model that simulates benign esophageal strictures induced by endoscopic submucosal dissection (ESD). Materials and Methods: Sixteen male Sprague-Dawley rats were randomly divided into mucosal resection (n = 8) and sham-operated groups (n = 8). The rats in the mucosal resection group underwent a 5-mm three-fourths mucosal resection by way of a 3-mm incision in the distal esophagus under direct visualization via laparotomy. Rats in the sham-operated group underwent a 3-mm incision of the muscularis propria layer in the distal esophagus via laparotomy without mucosal resection. Dysphagia score, weight gain, mucosal constriction rate, and histology were evaluated 2 weeks after surgery. Results: Technical success was achieved in all the animals. One rat in the mucosal resection group died of infection, and no other complications were observed. Weight gain (P < 0.001) and luminal diameter derived from the esophagograms (P < 0.001) were significantly lower in the mucosal resection group than those in the sham-operated group. Dysphagia score (P < 0.001) and mucosal constriction rate (P < 0.001) were significantly higher in the mucosal resection group than those in the sham-operated group. The inflammation grade (P = 0.002), damage to the muscularis propria (P < 0.001), number of nascent microvessels (P = 0.006), and degree of α-SMA positive deposition (P = 0.006) were significantly higher in the mucosal resection group. Conclusion: A rat model of benign esophageal stricture induced by ESD was successfully and safely established by mucosal resection.

A novel method for high level production of protein glutaminase by sfGFP tag in Bacillus subtilis.

Protein glutaminase (PG; EC 3.5.1.44) is a novel deamidase that helps to improve functional properties of food proteins. Currently, the highest activated PG enzyme activity was 26 U/mg when recombinantly expressed via the twin-arginine translocation (Tat) pathway in Corynebacterium glutamicum. In this study, superfolder green fluorescent protein (sfGFP) was used to replace traditional signal peptides to facilitate efficient heterologous expression and secretion of Propeptide-Protein glutaminase (PP) in Bacillus subtilis. The fusion protein, sfGFP-PP, was secreted from 12 h of fermentation and reached its highest extracellular expression at 28 h, with a secretion efficiency of about 93 %. Moreover, when fusing sfGFP with PP at the N-terminus, it significantly enhances PG expression up to 26 U/mL by approximately 2.2-fold compared to conventional signal-peptides- guided PP with 11.9 U/mL. Finally, the PG enzyme activity increased from 26 U/mL to 36.9 U/mL after promoter and RBS optimization. This strategy not only provides a new approach to increase PG production as well as extracellular secretion but also offers sfGFP as an effective N-terminal tag for increased secreted production of difficult-to-express proteins.

Key candidate genes for male sterility in peppers unveiled via transcriptomic and proteomic analyses.

This study aimed to enhance the use of male sterility in pepper to select superior hybrid generations. Transcriptomic and proteomic analyses of fertile line 1933A and nucleic male sterility line 1933B of Capsicum annuum L. were performed to identify male sterility-related proteins and genes. The phylogenetic tree, physical and chemical characteristics, gene structure characteristics, collinearity and expression characteristics of candidate genes were analyzed. The study identified 2,357 differentially expressed genes, of which 1,145 and 229 were enriched in the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases, respectively. A total of 7,628 quantifiable proteins were identified and 29 important proteins and genes were identified. It is worth noting that the existence of CaPRX genes has been found in both proteomics and transcriptomics, and 3 CaPRX genes have been identified through association analysis. A total of 66 CaPRX genes have been identified at the genome level, which are divided into 13 subfamilies, all containing typical CaPRX gene conformal domains. It is unevenly distributed across 12 chromosomes (including the virtual chromosome Chr00). Salt stress and co-expression analysis show that male sterility genes are expressed to varying degrees, and multiple transcription factors are co-expressed with CaPRXs, suggesting that they are involved in the induction of pepper salt stress. The study findings provide a theoretical foundation for genetic breeding by identifying genes, metabolic pathways, and molecular mechanisms involved in male sterility in pepper.

Mono+ algorithm assessment of the diagnostic value of dual-energy CT for high-risk factors for colorectal cancer: a preliminary study.

Background: Risk factors for colorectal cancer (CRC) affect the way patients are subsequently treated and their prognosis. Dual-energy computerized tomography (DECT) is an advanced imaging technique that enables the quantitative evaluation of lesions. This study aimed to evaluate the quality of DECT images based on the Mono+ algorithm in CRC, and based on this, to assess the value of DECT in the diagnosis of CRC risk factors. Methods: This prospective study was performed from 2021 to 2023. A dual-phase DECT protocol was established for consecutive patients with primary CRC. The signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), overall image quality, lesion delineation, and image noise of the dual-phase DECT images were assessed. Next, the optimal energy-level image was selected to analyze the iodine concentration (IC), normalized iodine concentration (NIC), effective atomic number, electron density, dual-energy index (DEI), and slope of the energy spectrum curve within the tumor for the high- and low-risk CRC groups. A multifactor binary logistic regression analysis was used to construct a differential diagnostic regression model for high- and low-risk CRC, receiver operating characteristic (ROC) curves were plotted, and the area under the curve (AUC) was calculated to assess the diagnostic value of the model. Results: A total of 74 patients were enrolled in this study, of whom 41 had high-risk factors and 33 had low-risk factors. The SNR and CNR were best at 40 keV virtual monoenergetic imaging (VMI) based on the Mono+ algorithm (VMI+) (SNR 8.79±1.27, P<0.001; CNR 14.89±1.77, P=0.027). The overall image quality and lesion contours were best at 60 keV VMI+ and 40 keV VMI+, respectively (P=0.001). Among all the DECT parameters, the arterial phase (AP)-IC, NIC, DEI, energy spectrum curve, and venous phase-NIC differed significantly between the two groups. The AP-IC was the optimal DECT parameter for predicting high- and low-risk CRC with AUC, sensitivity, specificity, and cut-off values of 0.96, 97.06%, 87.80%, and 2.94, respectively, and the 95% confidence interval (CI) of the AUC was 0.88-0.99. Integrating the clinical factors and DECT parameters, the AUC, sensitivity, specificity, and predictive accuracy of the model were 0.99, 100.00%, 92.68%, and 94.67%, respectively, and the 95% CI of the AUC was 0.93-1.00. Conclusions: The DECT parameters based on 40 keV noise-optimized VMI+ reconstruction images depicted the CRC tumors best, and the clinical DECT model may have significant implications for the preoperative prediction of high-risk factors in CRC patients.

Revealing the Effect of the [CoO]6 Microstructure in Pseudocapacitance by Controlled Delithium of LiCoO2.

Revealing the in-depth structure-property relationship and designing specific capacity electrodes are particularly important for supercapacitors. Despite many efforts made to tune the composition and electronic structure of cobalt oxide for pseudocapacitance, insight into the [CoO]6 octahedron from the microstructure is still insufficient. Herein, we present a tunable [CoO]6 octahedron microstructure in LiCoO2 by a chemical delithiation process. The c-strained strain of the [CoO]6 octahedron is induced to form higher valence Co ions, and the (003) crystalline layer spacing increases to allow more rapid participation of OH- in the redox reaction. Interestingly, the specific capacity of L0.75CO2 is nearly four times higher than that of LiCoO2 at 10 mA g-1. The enhanced activity originated from the asymmetric strain [CoO]6 octahedra, resulting in enhanced electronic conductivity and Co-O hybridization for accelerated redox kinetics. This finding provides new insights into the modification strategy for pseudocapacitive transition metal oxides.

Heparan sulfate selectively inhibits the collagenase activity of cathepsin K.

Cathepsin K (CtsK) is a cysteine protease with potent collagenase activity. CtsK is highly expressed by bone-resorbing osteoclasts and plays an essential role in bone remodeling. Although CtsK is known to bind heparan sulfate (HS), the structural details of the interaction, and how HS ultimately regulates the biological functions of CtsK, remains largely unknown. In this report, we determined that CtsK preferably binds to larger HS oligosaccharides, such as dodecasaccharides (12mer), and that the12mer can induce monomeric CtsK to form a stable dimer in solution. Interestingly, while HS has no effect on the peptidase activity of CtsK, it greatly inhibits the collagenase activity of CtsK in a manner dependent on sulfation level. By forming a complex with CtsK, HS was able to preserve the full peptidase activity of CtsK for prolonged periods, likely by stabilizing its active conformation. Crystal structures of Ctsk with a bound 12mer, alone and in the presence of the endogenous inhibitor cystatin-C reveal the location of HS binding is remote from the active site. Mutagenesis based on these complex structures identified 6 basic residues of Ctsk that play essential roles in mediating HS-binding. At last, we show that HS 12mers can effectively block osteoclast resorption of bone in vitro. Combined, we have shown that HS can function as a multifaceted regulator of CtsK and that HS-based oligosaccharide might be explored as a new class of selective CtsK inhibitor in many diseases that involve exaggerated bone resorption.

Heparan sulfate promotes TRAIL-induced tumor cell apoptosis.

TRAIL (TNF-related apoptosis-inducing ligand) is a potent inducer of tumor cell apoptosis through TRAIL receptors. While it has been previously pursued as a potential anti-tumor therapy, the enthusiasm subsided due to unsuccessful clinical trials and the fact that many tumors are resistant to TRAIL. In this report, we identified heparan sulfate (HS) as an important regulator of TRAIL-induced apoptosis. TRAIL binds HS with high affinity (KD = 73 nM) and HS induces TRAIL to form higher-order oligomers. The HS-binding site of TRAIL is located at the N-terminus of soluble TRAIL, which includes three basic residues. Binding to cell surface HS plays an essential role in promoting the apoptotic activity of TRAIL in both breast cancer and myeloma cells, and this promoting effect can be blocked by heparin, which is commonly administered to cancer patients. We also quantified HS content in several lines of myeloma cells and found that the cell line showing the most resistance to TRAIL has the least expression of HS, which suggests that HS expression in tumor cells could play a role in regulating sensitivity towards TRAIL. We also discovered that death receptor 5 (DR5), TRAIL, and HS can form a ternary complex and that cell surface HS plays an active role in promoting TRAIL-induced cellular internalization of DR5. Combined, our study suggests that TRAIL-HS interactions could play multiple roles in regulating the apoptotic potency of TRAIL and might be an important point of consideration when designing future TRAIL-based anti-tumor therapy.

Identifying the source and fate of boron in geothermal water: Evidence from B/Na and B isotopes.

High level dissolved B, which poses risks to human health, has been widely observed in geothermal water. In the Guide Basin, NW China, a series of geothermal water samples along a fault show a wide range of B contents ranging from 3.14 to 8.33 mg/L, which are higher than the WHO Guideline value equaling 2.4 mg/L in drinking water. To identify the sources and fate of B, we conduct a comprehensive analysis of hydrochemistry and stable isotopes (D, 18O and 11B) of three thermal fields representing three stages of hydrogeochemical evolution (stages I, II and III). From stage I to III, there are trends of increasing mineral dissolution, which is supported by increasing mean reservoir temperature and concentrations of conservative elements (Cl, Na, K, Li and Si). Geothermal water in stage I with meteoric origin and the lowest reservoir temperature has the highest B/Na resulting from silicate dissolution and falls on the mixing line between granitoids and cold water on the plot of δ11B versus 1/B, showing the control of silicate dissolution. However, geothermal water in stage III has lower Ca, B Sr and B/Na than that in stage II. Because of the occurrence of other processes, geothermal water in stages II and III deviates from the LMWL. Compared with geothermal water in stage I, the increased Sr/Ca and decreased B/Ca show that B are removed by both coprecipitation and vapor separation. With the aid of B isotopes, we find vapor separation dominates in stage II, whereas carbonate precipitation dominates in stage III. Overall, a combined use of three isotopes (H, O and B) and three element ratios (B/Na, B/Ca and Sr/Ca) leads to a complete understanding of B cycle and hydrogeochemical evolution in hydrothermal systems.

Elucidation of the effects of autochthonous starter on nitrogen-containing compounds during fermentation of Yujiangsuan by metabolomics.

To understand the role of microorganisms in nitrogen (N)-containing compound changes during the processing of Yujiangsuan by autochthonous starter cultures, the GC-TOF-MS-based metabolomics method was adopted to investigate the effects of Weissella cibaria and Lactobacillus plantarum. The results demonstrated that inoculation of autochthonous strains led to differential metabolites, such as fatty acids, organic oxygen compounds, and carboxylic acids on day 4 to day 12 of fermentation. The N-containing compounds under the inoculated fermentation group showed a faster relative concentration change. Nucleotide metabolism and arginine and proline metabolism exerted an influence on the formation of N-containing compounds. Apart from that, the effect of W. cibaria and L. plantarum on the hydrolysis of macromolecules was the main factor causing differences in major N-containing compounds.

Molecular physiology for the increase of soluble sugar accumulation in citrus fruits under drought stress.

To investigate the mechanism for drought promoting soluble sugar accumulation will be conducive to the enhancement of citrus fruit quality as well as stress tolerance. Fruit sucrose mainly derives from source leaves. Its accumulation in citrus fruit cell vacuole involves in two processes of unloading in the fruit segment membrane (SM) and translocating to the vacuole of fruit juice sacs (JS). Here, transcript levels of 47 sugar metabolism- and transport-related genes were compared in fruit SM or JS between drought and control treatments. Results indicated that transcript levels of cell wall invertase genes (CwINV2/6) and sucrose synthase genes (SUS2/6) in the SM were significantly increased by the drought. Moreover, transcript levels of SWEET genes (CsSWEET1/2/4/5/9) and monosaccharide transporter gene (CsPMT3) were significantly increased in SM under drought treatment. On the other hand, SUS1/3 and vacuolar invertase (VINV) transcript levels were significantly increased in JS by drought; CsPMT4, sucrose transporter gene 2 (CsSUT2), tonoplast monosaccharide transporter gene 2 (CsTMT2), sugar transport protein gene 1 (CsSTP1), two citrus type I V-PPase genes (CsVPP1, and CsVPP2) were also significantly increased in drought treated JS. Collectively, the imposition of drought stress resulted in more soluble sugar accumulation through enhancing sucrose download by enhancing sink strength- and transport ability-related genes, such as CwINV2/6, SUS2/6, CsSWEET1/2/4/5/9, and CsPMT3, in fruit SM, and soluble sugar storage ability by increasing transcript levels of genes, such as CsPMT4, VINV, CsSUT2, CsTMT2, CsSTP1, CsVPP1, and CsVPP2, in fruit JS.

AffinityVAE: A multi-objective model for protein-ligand affinity prediction and drug design.

In the prediction of protein-ligand affinity, the traditional methods require a large amount of computing resources, and have certain limitations in predicting and simulating the structural changes. Although employing data-driven approaches can yield favorable outcomes in deep learning, it entails a lack of interpretability. Some methods may require additional structural information or domain knowledge to support the interpretation, which may limit their applicability. This paper proposes an affinity variational autoencoder (AffinityVAE) using interaction feature mapping and a variational autoencoder, which consists of a multi-objective model capable of end-to-end affinity prediction and drug discovery. In this study, the limitations of affinity prediction in terms of interpretability are tackled by proposing the concept of a protein-ligand interaction feature map. This increases the diversity and quantity of protein-ligand binding data by designing an adaptive autoencoder of target chemical properties to generate new ligands similar to known ligands and adding them to the original training set. AffinityVAE is then retrained using this extended training set to further validate the protein-ligand binding affinity prediction. Comparisons were conducted between the AffinityVAE and recent methods to demonstrate the high efficiency of the proposed model. The experimental results show that AffinityVAE has very high prediction performance, and it has the potential to enhance the diversity and the amount of protein-ligand binding data, which promotes the drug development.

Conjugation with glucagon like peptide-1 enables targeted protein degradation.

Lysosome-targeting chimeras (LYTACs) have emerged as a promising technique to extend the scope of targeted protein degradation to extracellular proteins, e.g., secreted proteins and membrane-anchored proteins. However, up to now, only a small number of lysosomal targeting receptors (LTRs), such as cation-independent mannose 6-phosphate receptor (CI-M6PR) and asialoglycoprotein receptor (ASGPR), were reported to build LYTACs for degradation of extracellular proteins. Therefore, it is important to explore more functionalized ligands for the relevant LTRs to expand the LYTAC framework. Herein, we demonstrate a new LTR ligand-glucagon like peptide 1 (GLP-1) based targeted degradation platform, termed GLP-1 receptor-targeting chimeras (GLP-1-LYTAC). GLP-1-LYTACs are formed by conjugating GLP-1 with targeted binder (such as antibody) through Click Chemistry, showing efficiently lysosomal degradation of both extracellular proteins (GFP and Neutravidin) as well as cell membrane proteins (EGFR and PD-L1). We believe that this novel GLP-1-LYTAC will open up a new dimension for targeted protein breakdown.