Functional Characterization of the MeSSIII-1 Gene and Its Promoter from Cassava.

Soluble starch synthases (SSs) play important roles in the synthesis of cassava starch. However, the expression characteristics of the cassava SSs genes have not been elucidated. In this study, the MeSSIII-1 gene and its promoter, from SC8 cassava cultivars, were respectively isolated by PCR amplification. MeSSIII-1 protein was localized to the chloroplasts. qRT-PCR analysis revealed that the MeSSIII-1 gene was expressed in almost all tissues tested, and the expression in mature leaves was 18.9 times more than that in tuber roots. MeSSIII-1 expression was induced by methyljasmonate (MeJA), abscisic acid (ABA), and ethylene (ET) hormones in cassava. MeSSIII-1 expression patterns were further confirmed in proMeSSIII-1 transgenic cassava. The promoter deletion analysis showed that the -264 bp to -1 bp MeSSIII-1 promoter has basal activity. The range from -1228 bp to -987 bp and -488 bp to -264 bp significantly enhance promoter activity. The regions from -987 bp to -747 bp and -747 bp to -488 bp have repressive activity. These findings will provide an important reference for research on the potential function and transcriptional regulation mechanisms of the MeSSIII-1 gene and for further in-depth exploration of the regulatory network of its internal functional elements.

Paeonia lactiflora Pall. ameliorates acetaminophen-induced oxidative stress and apoptosis via inhibiting the PKC-ERK pathway.

ETHNOPHARMACOLOGICAL RELEVANCE: Paeonia lactiflora Pall. (PLP), a traditional Chinese medicine, is recognized for its antioxidative and anti-apoptotic properties. Despite its potential medicinal value, the mechanisms underlying its efficacy have been less explored, particularly in alleviating acute liver injury (ALI) caused by excessive intake of acetaminophen (APAP). AIM OF THE STUDY: This study aims to elucidate the role and mechanisms of PLP in mitigating oxidative stress and apoptosis induced by APAP. MATERIALS AND METHODS: C57BL/6 male mice were pre-treated with PLP for seven consecutive days, followed by the induction of ALI using APAP. Liver pathology was assessed using HE staining. Serum indicators, immunofluorescence (IF), immunohistochemical (IHC), and transmission electron microscopy were employed to evaluate levels of oxidative stress, ferroptosis and apoptosis. Differential expression proteins (DEPs) in the APAP-treated and PLP pre-treated groups were analyzed using quantitative proteomics. Subsequently, the potential mechanisms of PLP pre-treatment in treating ALI were validated using western blotting, molecular docking, molecular dynamics simulations, and surface plasmon resonance (SPR) analysis. RESULTS: The UHPLC assay confirmed the presence of three compounds, i.e., albiflorin, paeoniflorin, and oxypaeoniflorin. Pre-treatment with PLP was observed to ameliorate liver tissue pathological damage through HE staining. Further confirmation of efficacy of PLP in alleviating APAP-induced liver injury and oxidative stress was established through liver function serum biochemical indicators, IF of reactive oxygen species (ROS) and IHC of glutathione peroxidase 4 (GPX4) detection. However, PLP did not demonstrate a significant effect in alleviating APAP-induced ferroptosis. Additionally, transmission electron microscopy and TUNEL staining indicated that PLP can mitigate hepatocyte apoptosis. PKC-ERK pathway was identified by proteomics, and subsequent molecular docking, molecular dynamics simulations, and SPR verified binding of the major components of PLP to ERK protein. Western blotting demonstrated that PLP suppressed protein kinase C (PKC) phosphorylation, blocking extracellular signal-regulated kinase (ERK) phosphorylation and inhibiting oxidative stress and cell apoptosis. CONCLUSION: This study demonstrates that PLP possesses hepatoprotective abilities against APAP-induced ALI, primarily by inhibiting the PKC-ERK cascade to suppress oxidative stress and cell apoptosis.

Optimized therapeutic potential of Yinchenhao decoction for cholestatic hepatitis by combined network meta-analysis and network pharmacology.

BACKGROUND: Cholestatic hepatitis is recognized as a significant contributor to the development of liver fibrosis and cirrhosis. As a well-known classic formula for the treatment of cholestatic hepatitis, Yinchenhao decoction (YCHD) is widely used in countries in Asia, including China, Japan, and Korea. However, in recent years, a risk of liver injury has been reported from Rheum palmatum L. and Gardenia jasmonoides J.Ellis which are the main ingredients of YCHD. Therefore, the question arises whether YCHD is still safe enough for the treatment of cholestatic hepatitis or whether an optimized ratio of ingredients should be applied. These is inevitable questions for the clinical application of YCHD. PURPOSE: To provide a scientific basis for the clinical application of YCHD through a combination of meta-analysis and network pharmacology and to find the best ratio of components to ensure optimal therapeutic efficacy and safety. At the same time, a deeper understanding of the mechanisms of YCHD was explored. METHODS: We retrieved relevant trials from various databases including PubMed, Web of Science, EMBASE, Cochrane Library, China National Knowledge Infrastructure (CNKI), VIP and Wanfang databases up to August 2023. After screening for inclusion and exclusion criteria, we assessed efficiency, ALT, AST, and TBIL as outcome parameters. The relevant data underwent a network meta-analysis using STATA 16.0 software. Based on network pharmacology, we screened the disease targets, active ingredients, and targets related to YCHD. The targets were visualized using Cytoscape 3.9.1. Then, potential mechanisms were explored based on bioinformatic techniques. RESULTS: Twenty eligible studies were finally screened and a total of 1,591 patients who fulfilled the inclusion criteria were enrolled in the study. The meta-analysis results indicated that TG-c (treatment group c) [(Artemisia capillaris Thunb. : Gardenia jasminoides J.Ellis : Rheum palmatum L. = 10:5:2-10:5:3) + CT] was the most promising therapeutic approach, demonstrating superior efficacy and notable improvements in both AST and TBIL levels. For ALT, TG-d [(Artemisia capillaris : Gardenia jasminoides : Rheum palmatum = 5:1:1-5:2:1) + CT] exhibited the greatest potential as optimal therapy option. Based on the surface under the cumulative ranking curve (SUCRA) values, TG-c was the best therapy in terms of efficiency and improvement in TBIL levels, while TG-d was the most effective in reducing ALT levels. For AST levels, TG-e [(Artemisia capillaris : Gardenia jasminoides : Rheum palmatum = 5:2:2-5:3:3) + CT] was the most effective therapy. The comprehensive analysis revealed that TG-c exhibited the most pronounced efficacy. Combined network pharmacology, GO enrichment analysis and KEGG pathway enrichment analysis displayed that the key target genes of Artemisia capillaris, Rheum palmatum, and Gardenia jasminoides were closely involved in inflammation response, bile transport, apoptosis, oxidative stress, and regulation of leukocyte migration. Notably, bile secretion dominated the common pathway of the three herbs. On the other hand, Artemisia capillaris exhibited a unique mode of action by regulating the IL-17 signaling pathway, which may play a crucial role in its effectiveness. CONCLUSION: Based on our findings, the optimal TG-C demonstrated the most favorable overall therapeutic efficacy by increasing the dosage of Artemisia capillaris while reducing the dosage of Gardenia jasminoides and Rheum palmatum. This is attributed to the potent ability of Artemisia capillaris. to effectively modulate the IL-17 signaling pathway, thereby exerting a beneficial therapeutic effect. Conversely, Gardenia jasminoides and Rheum palmatum may potentially enhance the activation of the NF-кB signaling pathway, thereby elevating the risk of hepatotoxicity.

Separation of Mono-/Divalent Ions via Controlled Dynamic Adsorption/Desorption at Polythiophene Coated Carbon Surface with Flow-Electrode Capacitive Deionization.

Capacitive deionization for selective separation of ions is rarely reported since it relies on the electrostatic attraction of oppositely charged ions with no capability to distinguish ions of different valent states. Using molecular dynamic simulation, a screening process identified a hybrid material known as AC/PTh, which consists of activated carbon with a thin layer of polythiophene (PTh) coating. By utilizing AC/PTh as electrode material implementing the short-circuit cycle (SCC) mode in flow-electrode capacitive deionization (FCDI), selective separation of mono-/divalent ions can be realized via precise control of dynamic adsorption and desorption of mono-/divalent ions at a particular surface. Specifically, AC/PTh shows strong interaction with divalent ions but weak interaction with monovalent ions, the distribution of divalent ions can be enriched in the electric double layer after a couple of adsorption-desorption cycles. At Cu2+/Na+ molar ratio of 1:40, selectivity toward divalent ions can reach up to 110.3 in FCDI SCC mode at 1.0 V. This work presents a promising strategy for separating ions of different valence states in a continuously operated FCDI device.

Developing an Improved Cycle Architecture for AI-Based Generation of New Structures Aimed at Drug Discovery.

Drug discovery involves a crucial step of optimizing molecules with the desired structural groups. In the domain of computer-aided drug discovery, deep learning has emerged as a prominent technique in molecular modeling. Deep generative models, based on deep learning, play a crucial role in generating novel molecules when optimizing molecules. However, many existing molecular generative models have limitations as they solely process input information in a forward way. To overcome this limitation, we propose an improved generative model called BD-CycleGAN, which incorporates BiLSTM (bidirectional long short-term memory) and Mol-CycleGAN (molecular cycle generative adversarial network) to preserve the information of molecular input. To evaluate the proposed model, we assess its performance by analyzing the structural distribution and evaluation matrices of generated molecules in the process of structural transformation. The results demonstrate that the BD-CycleGAN model achieves a higher success rate and exhibits increased diversity in molecular generation. Furthermore, we demonstrate its application in molecular docking, where it successfully increases the docking score for the generated molecules. The proposed BD-CycleGAN architecture harnesses the power of deep learning to facilitate the generation of molecules with desired structural features, thus offering promising advancements in the field of drug discovery processes.

Accurate prediction of solvent flux in sub-1-nm slit-pore nanosheet membranes.

Nanosheet-based membranes have shown enormous potential for energy-efficient molecular transport and separation applications, but designing these membranes for specific separations remains a great challenge due to the lack of good understanding of fluid transport mechanisms in complex nanochannels. We synthesized reduced MXene/graphene hetero-channel membranes with sub-1-nm pores for experimental measurements and theoretical modeling of their structures and fluid transport rates. Our experiments showed that upon complete rejection of salt and organic dyes, these membranes with subnanometer channels exhibit remarkably high solvent fluxes, and their solvent transport behavior is very different from their homo-structured counterparts. We proposed a subcontinuum flow model that enables accurate prediction of solvent flux in sub-1-nm slit-pore membranes by building a direct relationship between the solvent molecule-channel wall interaction and flux from the confined physical properties of a liquid and the structural parameters of the membranes. This work provides a basis for the rational design of nanosheet-based membranes for advanced separation and emerging nanofluidics.

Multimodal fused deep learning for drug property prediction: Integrating chemical language and molecular graph.

Accurately predicting molecular properties is a challenging but essential task in drug discovery. Recently, many mono-modal deep learning methods have been successfully applied to molecular property prediction. However, mono-modal learning is inherently limited as it relies solely on a single modality of molecular representation, which restricts a comprehensive understanding of drug molecules. To overcome the limitations, we propose a multimodal fused deep learning (MMFDL) model to leverage information from different molecular representations. Specifically, we construct a triple-modal learning model by employing Transformer-Encoder, Bidirectional Gated Recurrent Unit (BiGRU), and graph convolutional network (GCN) to process three modalities of information from chemical language and molecular graph: SMILES-encoded vectors, ECFP fingerprints, and molecular graphs, respectively. We evaluate the proposed triple-modal model using five fusion approaches on six molecule datasets, including Delaney, Llinas2020, Lipophilicity, SAMPL, BACE, and pKa from DataWarrior. The results show that the MMFDL model achieves the highest Pearson coefficients, and stable distribution of Pearson coefficients in the random splitting test, outperforming mono-modal models in accuracy and reliability. Furthermore, we validate the generalization ability of our model in the prediction of binding constants for protein-ligand complex molecules, and assess the resilience capability against noise. Through analysis of feature distributions in chemical space and the assigned contribution of each modal model, we demonstrate that the MMFDL model shows the ability to acquire complementary information by using proper models and suitable fusion approaches. By leveraging diverse sources of bioinformatics information, multimodal deep learning models hold the potential for successful drug discovery.

Molecular insights into experimental models and therapeutics for cholestasis.

Cholestatic liver disease (CLD) is a range of conditions caused by the accumulation of bile acids (BAs) or disruptions in bile flow, which can harm the liver and bile ducts. To investigate its pathogenesis and treatment, it is essential to establish and assess experimental models of cholestasis, which have significant clinical value. However, owing to the complex pathogenesis of cholestasis, a single modelling method can merely reflect one or a few pathological mechanisms, and each method has its adaptability and limitations. We summarize the existing experimental models of cholestasis, including animal models, gene-knockout models, cell models, and organoid models. We also describe the main types of cholestatic disease simulated clinically. This review provides an overview of targeted therapy used for treating cholestasis based on the current research status of cholestasis models. In addition, we discuss the respective advantages and disadvantages of different models of cholestasis to help establish experimental models that resemble clinical disease conditions. In sum, this review not only outlines the current research with cholestasis models but also projects prospects for clinical treatment, thereby bridging basic research and practical therapeutic applications.

Enhanced CO2 Capture through SAPO-34 Impregnated with Ionic Liquid.

The concurrent utilization of an adsorbent and absorbent for carbon dioxide (CO2) adsorption with synergistic effects presents a promising technique for CO2 capture. Here, 1-butyl-3-methylimidazole acetate ([Bmim][Ac]), with a high affinity for CO2, and the molecular sieve SAPO-34 were selected. The impregnation method was used to composite the hybrid samples of [Bmim][Ac]/SAPO-34, and the pore structure and surface property of prepared samples were characterized. The quantity and kinetics of the sorbed CO2 for loaded samples were measured using thermogravimetric analysis. The study revealed that SAPO-34 could retain its pristine structure after [Bmim][Ac] loading. The CO2 uptake of the loaded sample was 1.879 mmol g-1 at 303 K and 1 bar, exhibiting a 20.6% rise compared to that of the pristine SAPO-34 recording 1.558 mmol g-1. The CO2 uptake kinetics of the loaded samples were also accelerated, and the apparent mass transfer resistance for CO2 sorption was significantly reduced by 11.2% compared with that of the pure [Bmim][Ac]. The differential scanning calorimetry method revealed that the loaded sample had a lower CO2 desorption heat than that of the pure [Bmim][Ac], and the CO2 desorption heat of the loaded samples was between 30.6 and 40.8 kJ mol-1. The samples exhibited good cyclic stability. This material displays great potential for CO2 capture applications, facilitating the reduction of greenhouse gas emissions.

Rational synthesis of a heparan sulfate saccharide that promotes the activity of BMP2.

Heparan sulfate (HS) is a glycosaminoglycan (GAG) found throughout nature and is involved in a wide range of functions including modulation of cell signalling via sequestration of growth factors. Current consensus is that the specificity of HS motifs for protein binding are individual for each protein. Given the structural complexity of HS the synthesis of libraries of these compounds to probe this is not trivial. Herein we present the synthesis of an HS decamer, the design of which was undertaken rationally from previously published data for HS binding to the growth factor BMP-2. The biological activity of this HS decamer was assessed in vitro, showing that it had the ability to both bind BMP-2 and increase its thermal stability as well as enhancing the bioactivity of BMP-2 in vitro in C2C12 cells. At the same time no undesired anticoagulant effect was observed. This decamer was then analysed in vivo in a rabbit model where higher bone formation, bone mineral density (BMD) and trabecular thickness were observed over an empty defect or collagen implant alone. This indicated that the HS decamer was effective in promoting bone regeneration in vivo.

Pain Sensitivity and Acute Postoperative Pain in Patients Undergoing Abdominal Surgery: The Mediating Roles of Pain Self-Efficacy and Pain Catastrophizing.

BACKGROUND: Inadequately managed postoperative pain remains a common issue. Examining factors like pain sensitivity, pain catastrophizing, and pain self-efficacy can help improve postoperative pain management. While these factors have been identified as potential predictors of acute postoperative pain, their effects have been inconsistent. Few studies have explored the interactions between these factors. AIM: To investigate the influence of preoperative pain sensitivity, pain catastrophizing, and pain self-efficacy on acute postoperative pain in abdominal surgery patients and to determine the mediating roles of pain catastrophizing and pain self-efficacy in the relationship between pain sensitivity and acute postoperative pain, as per the gate control theory. METHODS: A total of 246 patients were enrolled in this study. General information was collected before surgery, and the Pain Sensitivity Questionnaire (PSQ), Pain Catastrophizing Scale (PCS), and Pain Self-Efficacy Questionnaire (PSEQ) were administered. After surgery, patients' average pain scores over the 24 hours were reported using the Numerical Rating Scale (NRS). Correlation analyses and a structural equation model were used to examine the relationships among these variables. RESULTS: NRS scores over 3 during the 24 hours post-surgery were reported by 21.54% of patients. Postoperative acute pain was found to be associated with pain sensitivity (rs = 0.463, p < .001), pain catastrophizing (rs = 0.328, p < .001), and pain self-efficacy (rs = -0.558, p < .001). A direct effect on postoperative acute pain was exerted by pain sensitivity (effect = 0.250, p = .001), along with indirect effects through: (A) pain catastrophizing (effect = 0.028, p = .001); (B) pain self-efficacy (effect = 0.132, p = .001); and (C) the chain mediation of pain self-efficacy and pain catastrophizing (effect = 0.021, p = .008). CONCLUSIONS: The severity of postoperative acute pain can be predicted by pain self-efficacy and pain catastrophizing, and the connection between moderate pain sensitivity and postoperative acute pain severity is mediated by them. Therefore, intervention programs aimed at boosting pain self-efficacy and reducing pain catastrophizing can enhance postoperative pain outcomes for abdominal surgery patients.

Assessing early tubular protective effects of SGLT2 inhibitor empagliflozin against type 2 diabetes mellitus using functional magnetic resonance imaging.

AIMS: To observe the alterations in functional magnetic resonance imaging parameters in normoalbuminuric type 2 diabetic patients undergoing SGLT2 inhibitor empagliflozin treatment and investigate the early tubular protective effects of the inhibitor. METHODS: This study was performed in normoalbuminuric type 2 diabetes mellitus patients (UACR < 30 mg/g, eGFR ≥ 60 ml/min/1.73 m2). The patients were divided into the intervention group (empagliflozin) and the control group (27 cases each). The intervention group was treated with 10 mg/day empagliflozin tablets orally, while the control group had adjustments to their basic treatment stage. The patients were treated for 6 weeks. RESULTS: The baseline clinical data of the two groups were comparable (P˃0.05). The intervention group exhibited better improvements in blood lipid profiles and more significant reductions in blood uric acid levels compared to the control group (P < 0.05). The two groups had No significant difference in blood pressure changes (P˃0.05). Notably, the intervention group demonstrated a greater reduction in UACR and a more substantial decline in eGFR than the control group (P < 0.05). Regarding functional magnetic resonance imaging parameters, the MD value of the renal medulla region in the intervention group increased after treatment, while the MR2* value of the renal medulla region decreased (P < 0.05). CONCLUSIONS: SGLT2 inhibitor empagliflozin can reduce UACR and eGFR levels in early type 2 diabetic patients with normal proteinuria. Moreover, empagliflozin therapy led to an increase in the MD value and a decrease in the MR2* value of the renal medulla, evidencing the early tubular protective effects of this therapy.

Knowledge, Attitude, and Practice of Insulin Pump Among Non-Endocrinology Nurses in South China.

Purpose: To investigate the knowledge, attitude, and practice (KAP) on insulin pump among non-endocrinology nurses in Southern China. Methods: This multicenter cross-sectional study enrolled non-endocrinology nurses in Southern China between November 2020 and December 2020. A structured questionnaire about insulin pumps was designed and used to collect data. Results: A total of 1118 nurses from 29 hospitals participated in the study. The majority of them were female (98.48%), and 513 worked in the department of internal medicine (45.89%), followed by surgery (235, 21.00%), pediatrics (147, 13.14%), gynecology (127, 11.35%), and oncology (96, 8.71%). None of the nurses answered all questions correctly in the knowledge section. The score of knowledge was 50.12 ± 3.42 (total score range, 0 to 85). The attitude score of nurses in the department of gynecology was 47.76 ± 5.11 (total score range, 10 to 50), followed by nurses in the department of internal medicine (47.43 ± 4.65), pediatrics (46.71 ± 4.96), surgery (46.77 ± 5.78) and oncology (46.25 ± 5.87). The practice score of nurses in the internal medicine department was 79.16 ± 9.03 (total score range, 17 to 85), followed by nurses in the department of gynecology (78.76 ± 10.76), surgery (78.14 ± 10.09), oncology (76.89 ± 12.70) and pediatrics (73.35 ± 19.04). Conclusion: There was limited knowledge regarding insulin pumps among nurses, although they had a positive attitude and attached importance to the management of insulin pumps. In clinical practice, their implementation of insulin pump management norms was acceptable.

Correlation Between Functional Magnetic Resonance Imaging and Renal Tubular Injury Markers in Early Assessment Of Renal Tubular Injury in Type 2 Diabetes Mellitus.

Objective: Both functional magnetic resonance imaging and renal tubular injury markers have been proved to be able to detect early renal damage in normoalbuminuric diabetic patients. This study mainly explored the functional magnetic resonance imaging parameters and renal tubular injury markers in the early evaluation of type 2 diabetes. Methods: A case observation study was established, and 62 patients with early-stage low-risk type 2 diabetes mellitus with normoalbuminuric (UACR<30 mg/g, eGFR≥60 ml/min/1.73 m2) were included for analysis. Urine kidney damage was determined by ELISA. Kidney injury molecule 1 (KIM-1) and neutrophil gelatinase-associated lipocalin (NGAL) assessment of renal tubular injury, and use of intravoxel incoherent motion magnetic resonance Imaging (intravoxel incoherent motion, IVIM) and blood oxygen level dependent magnetic resonance imaging (blood oxygen level dependent, BOLD) to evaluate renal cortex, medulla blood perfusion, water molecule diffusion, oxygenation level and other functional information, using linear correlation to analyze the correlation between functional magnetic resonance imaging parameters and markers of renal tubular injury. Results: The correlation analysis between IVIM parameters and renal tubular injury markers showed that KIM-1 was inversely correlated with the MD value of the renal medulla region parameter (r = -0.24, P = .03), and was closely related to the other IVIM cortex and medulla. There was no correlation between qualitative parameters (P > .05), and no correlation between NGAL and all parameters of IVIM (P > .05). The correlation analysis between BOLD parameters and renal tubular injury markers showed that KIM-1 was positively correlated with renal medulla region parameter MR2* value (r = 0.26, P = .04) and MCR value (r = 0.28, P = .03), respectively. There was also a positive correlation between NGAL and renal medulla region parameter MR2* value (r = 0.24, P = .04). Conclusion: In the early low-risk type 2 diabetic patients with normoalbuminuria, the more obvious the renal medullary water molecule diffusion disorder, the higher the renal tubular injury marker KIM-1, and the more severe renal medullary hypoxia, the renal tubular injury. The higher the markers KIM-1 and NGAL are, it is proved that the hypoxia and water diffusion disorder in the early renal medulla are related to renal tubular damage.

Natural products targeting tumour angiogenesis.

Tumour angiogenesis is the formation of new blood vessels to support the growth of a tumour. This process is critical for tumour progression and metastasis, making it an attractive approach to cancer therapy. Natural products derived from plants, animals or microorganisms exert anti-angiogenic properties and can be used to inhibit tumour growth and progression. In this review, we comprehensively report on the current status of natural products against tumour angiogenesis from four perspectives until March 2023: (1) the role of pro-angiogenic factors and antiangiogenic factors in tumour angiogenesis; (2) the development of anti-tumour angiogenesis therapy (monoclonal antibodies, VEGFR-targeted small molecules and fusion proteins); (3) the summary of anti-angiogenic natural agents, including polyphenols, polysaccharides, alkaloids, terpenoids, saponins and their mechanisms of action, and (4) the future perspectives of anti-angiogenic natural products (bioavailability improvement, testing of dosage and side effects, combination use and discovery of unique natural-based compounds). Our review aims to better understand the potential of natural products for drug development in inhibiting tumour angiogenesis and further aid the effective transition of these outcomes into clinical trials.

Prediction of Hypoglycemia in Diabetic Patients During Colonoscopy Preparation.

OBJECTIVE: To explore the clinical outcomes and establish a predictive model of hypoglycemia during colonoscopy preparation for diabetic patients. METHODS: Three-hundred ninety-four patients with diabetes who received colonoscopy were retrospectively enrolled in this study and assigned to hypoglycemia or non-hypoglycemia groups. Information about clinical characteristics and outcomes during colonoscopy preparation was collected and compared between the two groups. Logistic regression analysis was applied to identify the risk factors of hypoglycemia. These risk factors were used to construct a hypoglycemia predictive model verified by the receiver operating characteristic (ROC) curve and Hosmer-Lemeshow goodness fit test. RESULTS: Among 394 participants, 66 (16.8%) underwent a total of 88 hypoglycemia attacks during the bowel preparation. Grade 1 hypoglycemia (≤3.9 mmol/L) comprised 90.9% (80/88) of all hypoglycemia attacks and grade 2 hypoglycemia accounted for 9.1% (8/88), signifying that grade 1 hypoglycemia is the most common type. No severe hypoglycemia was identified. The incidence of nocturnal hypoglycemia was 15.9%. Logistic regression analyses revealed that the main risk factors of hypoglycemia during colonoscopy preparation were postprandial C-peptide, serum triglyceride, gender, type of diabetes mellitus, and insulin injection frequencies. The area under the ROC curve of the hypoglycemia prediction model was 0.777 (95% CI: 0.720-0.833). CONCLUSION: Diabetic patients are prone to develop mild to moderate hypoglycemia during colonoscopy preparation. This study proposes a predictive model that could provide a reference for identifying patients with a high risk of hypoglycemia during colonoscopy preparation.

Negative-emotion-induced reduction in speech-in-noise recognition is associated with source-monitoring deficits and psychiatric symptoms in mandarin-speaking patients with schizophrenia.

BACKGROUND: Patients with schizophrenia (SCH) have deficits in source monitoring (SM), speech-in-noise recognition (SR), and auditory prosody recognition. This study aimed to test the covariation between SM and SR alteration induced by negative prosodies and their association with psychiatric symptoms in SCH. METHODS: Fifty-four SCH patients and 59 healthy controls (HCs) underwent a speech SM task, an SR task, and the assessment of positive and negative syndrome scale (PANSS). We used the multivariate analyses of partial least squares (PLS) regression to explore the associations among SM (external/internal/new attribution error [AE] and response bias [RB]), SR alteration/release induced by four negative-emotion (sad, angry, fear, and disgust) prosodies of target speech, and psychiatric symptoms. RESULTS: In SCH, but not HCs, a profile (linear combination) of SM (especially the external-source RB) was positively associated with a profile of SR reductions (induced especially by the angry prosody). Moreover, two SR reduction profiles (especially in the anger and sadness conditions) were related to two profiles of psychiatric symptoms (negative symptoms, lack of insight, and emotional disturbances). The two PLS components explained 50.4% of the total variances of the release-symptom association. CONCLUSION: Compared to HCs, SCH is more likely to perceive the external-source speech as internal/new source speech. The SM-related SR reduction induced by the angry prosody was mainly associated with negative symptoms. These findings help understand the psychopathology of SCH and may provide a potential direction to improve negative symptoms via minimizing emotional SR reduction in schizophrenia.

Integrated Metabolomic and Transcriptomic Analyses Reveals Sugar Transport and Starch Accumulation in Two Specific Germplasms of Manihot esculenta Crantz.

As a starchy and edible tropical plant, cassava (Manihot esculenta Crantz) has been widely used as an industrial raw material and a dietary source. However, the metabolomic and genetic differences in specific germplasms of cassava storage root were unclear. In this study, two specific germplasms, M. esculenta Crantz cv. sugar cassava GPMS0991L and M. esculenta Crantz cv. pink cassava BRA117315, were used as research materials. Results showed that sugar cassava GPMS0991L was rich in glucose and fructose, whereas pink cassava BRA117315 was rich in starch and sucrose. Metabolomic and transcriptomic analysis indicated that sucrose and starch metabolism had significantly changing metabolites enrichment and the highest degree of differential expression genes, respectively. Sugar transport in storage roots may contribute to the activities of sugar, which will eventually be exported to transporters (SWEETs), such as (MeSWEET1a, MeSWEET2b, MeSWEET4, MeSWEET5, MeSWEET10b, and MeSWEET17c), which transport hexose to plant cells. The expression level of genes involved in starch biosynthesis and metabolism were altered, which may result in starch accumulation. These results provide a theoretical basis for sugar transport and starch accumulation and may be useful in improving the quality of tuberous crops and increasing yield.

A drug repurposing approach for individualized cancer therapy based on transcriptome sequencing and virtual drug screening.

RNA-sequencing has been proposed as a valuable technique to develop individualized therapy concepts for cancer patients based on their tumor-specific mutational profiles. Here, we aimed to identify drugs and inhibitors in an individualized therapy-based drug repurposing approach focusing on missense mutations for 35 biopsies of cancer patients. The missense mutations belonged to 9 categories (ABC transporter, apoptosis, angiogenesis, cell cycle, DNA damage, kinase, protease, transcription factor, tumor suppressor). The highest percentages of missense mutations were observed in transcription factor genes. The mutational profiles of all 35 tumors were subjected to hierarchical heatmap clustering. All 7 leukemia biopsies clustered together and were separated from solid tumors. Based on these individual mutation profiles, two strategies for the identification of possible drug candidates were applied: Firstly, virtual screening of FDA-approved drugs based on the protein structures carrying particular missense mutations. Secondly, we mined the Drug Gene Interaction (DGI) database (https://www.dgidb.org/) to identify approved or experimental inhibitors for missense mutated proteins in our dataset of 35 tumors. In conclusion, our approach based on virtual drug screening of FDA-approved drugs and DGI-based inhibitor selection may provide new, individual treatment options for patients with otherwise refractory tumors that do not respond anymore to standard chemotherapy.

LIGHT Amplification by NF-κB Contributes to TLR3 Signaling Pathway-Induced Acute Hepatitis.

LIGHT is a member of the TNF superfamily and a proinflammatory cytokine involved in liver pathogenesis. Many liver diseases involve activation of Toll-like receptor 3 (TLR3), which is activated by double-stranded RNA (dsRNA). However, the involvement of LIGHT in TLR3 implicated liver diseases is not clear. In this study, we investigated the role of LIGHT in TLR3 involved liver pathogenesis by using a mouse model of TLR3 agonist poly(I:C)-induced hepatitis. We found LIGHT expression at both protein and mRNA level in liver tissues is dramatically increased during the course of poly(I:C)-induced liver injury. This induction depends on NF-κB activation as pretreating the mice with a NF-κB inhibitor abrogates LIGHT upregulation. Importantly, blockade of the LIGHT signaling pathway with the recombinant LIGHT receptor HVEM protein ameliorates liver injury in poly(I:C)-induced hepatitis. Conclusions. These results indicate that LIGHT amplification by NF-κB plays a significant role in TLR3 involved hepatitis and points LIGHT to be a potential drug target for liver disease therapy.