Immunomodulation of adipose-derived mesenchymal stem cells on peripheral blood mononuclear cells in colorectal cancer patients with COVID-19.

BACKGROUND: Accumulating evidence has shown that adipose tissue-derived mesenchymal stem cells (ADSCs) are an effective therapeutic approach for managing coronavirus disease 2019 (COVID-19); however, further elucidation is required to determine their underlying immunomodulatory effect on the mRNA expression of T helper cell-related transcription factors (TFs) and cytokine release in peripheral blood mononuclear cells (PBMCs). AIM: To investigate the impact of ADSCs on the mRNA expression of TFs and cytokine release in PBMCs from colorectal cancer (CRC) patients with severe COVID-19 (CRC+ patients). METHODS: PBMCs from CRC+ patients (PBMCs-C+) and age-matched CRC patients (PBMCs-C) were stimulated and cultured in the presence/absence of ADSCs. The mRNA levels of T-box TF TBX21 (T-bet), GATA binding protein 3 (GATA-3), RAR-related orphan receptor C (RORC), and forkhead box P3 (FoxP3) in the PBMCs were determined by reverse transcriptase-polymerase chain reaction. Culture supernatants were evaluated for levels of interferon gamma (IFN-γ), interleukin 4 (IL-4), IL-17A, and transforming growth factor beta 1 (TGF-ß1) using an enzyme-linked immunosorbent assay. RESULTS: Compared with PBMCs-C, PBMCs-C+ exhibited higher mRNA levels of T-bet and RORC, and increased levels of IFN-γ and IL-17A. Additionally, a significant decrease in FoxP3 mRNA and TGF-ß1, as well as an increase in T-bet/GATA-3, RORC/FoxP3, IFN-γ/IL-4, and IL-17A/TGF-ß1 ratios were observed in PBMCs-C+. Furthermore, ADSCs significantly induced a functional regulatory T cell (Treg) subset, as evidenced by an increase in FoxP3 mRNA and TGF-ß1 release levels. This was accompanied by a significant decrease in the mRNA levels of T-bet and RORC, release of IFN-γ and IL-17A, and T-bet/GATA-3, RORC/FoxP3, IFN-γ/IL-4, and IL-17A/TGF-ß1 ratios, compared with the PBMCs-C+alone. CONCLUSION: The present in vitro studies showed that ADSCs contributed to the immunosuppressive effects on PBMCs-C+, favoring Treg responses. Thus, ADSC-based cell therapy could be a beneficial approach for patients with severe COVID-19 who fail to respond to conventional therapies.

Telocinobufagin, a PLK1 suppressor that inhibits tumor growth and metastasis by modulating CDC25c and CTCF in HNSCC cells.

BACKGROUND: The high metastasis and mortality rates of head and neck squamous cell carcinoma (HNSCC) urgently require new treatment targets and drugs. A steroidal component of ChanSu, telocinobufagin (TBG), was verified to have anti-cancer effects in various tumors, but its activity and mechanism in anti-HNSCC were still unknown. PURPOSE: This study tried to demonstrate the anti-tumor effect of TBG on HNSCC and verify its potential mechanism. METHODS: The effect of TBG on cell proliferation and metastasis were performed and the TBG changed genes were detected by RNA-seq analysis in HNSCC cells. The GSEA and PPI analysis were used to identify the pathways targeted for TBG-regulated genes. Meanwhile, the mechanism of TBG on anti-proliferative and anti-metastasis were investigated in vitro and in vivo. RESULTS: The in vitro and in vivo experiments confirmed that TBG has favorable anti-tumor effects by induced G2/M phase arrest and suppressed metastasis in HNSCC cells. Further RNA-seq analysis demonstrated the genes regulated by TBG were enriched at the G2/M checkpoint and PLK1 signaling pathway. Then, the bioinformatic analysis of clinical data found that high expressed PLK1 were closely associated with poor overall survival in HNSCC patients. Furthermore, PLK1 directly and indirectly modulated G2/M phase and metastasis (by regulated CTCF) in HNSCC cells, simultaneously. TBG significantly inhibited the protein levels of PLK1 in both phosphorylated and non-phosphorylated forms and then, in one way, inactivated PLK1 failed to activate G2/M phase-related proteins (including CDK1, CDC25c, and cyclin B1). In another way, be inhibited PLK1 unable promote the nuclear translocation of CTCF and thus suppressed HNSC cell metastasis. In contrast, the anti-proliferative and anti-metastasis effects of TBG on HNSCC cell were vanished when cells high-expressed PLK1. CONCLUSION: The present study verified that PLK1 mediated TBG induced anti-tumor effect by modulated G2/M phase and metastasis in HNSCC cells.

AaSEPALLATA1 integrates jasmonate and light-regulated glandular secretory trichome initiation in Artemisia annua.

Glandular secretory trichomes (GSTs) can secrete and store a variety of specific metabolites. By increasing GST density, valuable metabolites can be enhanced in terms of productivity. However, the comprehensive and detailed regulatory network of GST initiation still needs further investigation. By screening a complementary DNA library derived from young leaves of Artemisia annua, we identified a MADS-box transcription factor, AaSEPALLATA1 (AaSEP1), that positively regulates GST initiation. Overexpression of AaSEP1 in A. annua substantially increased GST density and artemisinin content. The HOMEODOMAIN PROTEIN 1 (AaHD1)-AaMYB16 regulatory network regulates GST initiation via the jasmonate (JA) signaling pathway. In this study, AaSEP1 enhanced the function of AaHD1 activation on downstream GST initiation gene GLANDULAR TRICHOME-SPECIFIC WRKY 2 (AaGSW2) through interaction with AaMYB16. Moreover, AaSEP1 interacted with the JA ZIM-domain 8 (AaJAZ8) and served as an important factor in JA-mediated GST initiation. We also found that AaSEP1 interacted with CONSTITUTIVE PHOTOMORPHOGENIC 1 (AaCOP1), a major repressor of light signaling. In this study, we identified a MADS-box transcription factor that is induced by JA and light signaling and that promotes the initiation of GST in A. annua.

Recent advances of bioactive proteins/polypeptides in the treatment of breast cancer.

Proteins do not only serve as nutrients to fulfill the demand for food, but also are used as a source of bioactive proteins/polypeptides for regulating physical functions and promoting physical health. Female breast cancer has the highest incidence in the world and is a serious threat to women's health. Bioactive proteins/polypeptides exert strong anti-tumor effects and exhibit inhibition of multiple breast cancer cells. This review discussed the suppressing effects of bioactive proteins/polypeptides on breast cancer in vitro and in vivo, and their mechanisms of migration and invasion inhibition, apoptosis induction, and cell cycle arrest. This may contribute to providing a basis for the development of bioactive proteins/polypeptides for the treatment of breast cancer.

Sanggenon C Suppresses Tumorigenesis of Gastric Cancer by Blocking ERK-Drp1-Mediated Mitochondrial Fission.

Sanggenon C is a flavonoid extracted from the root bark of white mulberry, which is a traditional Chinese medicine with anti-inflammatory, antioxidative, and antitumor pharmacological effects. In this study, sanggenon C was found to inhibit human gastric cancer (GC) cell proliferation and colony formation, induce GC cell cycle arrest in the G0-G1 phase, and promote GC cell apoptosis. Moreover, sanggenon C was found to decrease the level of mitochondrial membrane potential in GC cells and inhibit mitochondrial fission. Mechanistically, RNA sequencing, bioinformatics analysis, and a series of functional analyses confirmed that sanggenon C inhibited mitochondrial fission to induce apoptosis by blocking the extracellular regulated protein kinases (ERK) signaling pathway, and constitutive activation of ERK significantly abrogated these effects. Finally, sanggenon C was found to suppress the growth of tumor xenografts in nude mice without obvious side effects to the vital organs of animals. This study reveals that sanggenon C could be a novel therapeutic strategy for GC treatment.

Characterization of the complete chloroplast genome of Euphorbia pekinensis Rupr. (Euphorbiaceae).

Euphorbia pekinensis Rupr. 1859 is a medicinal herb endemic to China and distributed throughout the country, particularly across the northern part of the mainland. However, the systematic classification of Euphorbiaceae remains controversial. Therefore, studying the chloroplast genome of E. pekinensis is crucial for the resolution of this taxonomic dispute, clarification of the systematic status of Euphorbia, and establishment of an accurate classification system for Euphorbiaceae. In this study, we sequenced the complete chloroplast genome of E. pekinensis using Illumina sequencing technology and annotated it using GeSeq. The complete chloroplast genome was 162,002-bp-long with a guanine-cytosine (GC) content of 35.7%. It included one large single-copy (LSC), one small single-copy (SSC), and two inverted repeat sequence regions (IRa and IRb), which were 90,225 bp, 18,067 bp, and 26,855 bp in length, respectively, and are indicative of a typical tetrad structure. The genome encoded 129 functional genes, comprising 85 protein-coding genes, 36 tRNA genes, and eight rRNA genes. According to the maximum-likelihood phylogenetic tree that was constructed using 16 complete chloroplast genomes, E. pekinensis was found to be closely related to E. ebracteolata. Therefore, the complete chloroplast genome of E. pekinensis provides a better understanding of Euphorbia genetics.

Cellulose nanocrystal and ß-cyclodextrin chiral nematic composite films as selective sensor for methanol discrimination.

Due to the serious threat of methanol to human health, the convenient, quick and specific detection of methanol is of great importance. Therefore, in this study, a biomass-derived chiral nematic composite film is fabricated by the co-evaporation of cellulose nanocrystals (CNC) and water-soluble polymer of ß-cyclodextrin (PCD). The freestanding iridescent CNC-PCD film shows distinguishing structural colors of red and yellow green for methanol and ethanol respectively, realizing the identification of the two homologous alcohols by naked eyes. Besides, the quick, reversible and quantitative colorimetric sensing of the CNC-PCD film to methanol is verified. As its structural color and maximum reflection wavelength redshift to the greatest extent for methanol than other alcohols, the CNC-PCD film exhibits the specificity and selectivity for methanol detection in both single and mixed solvents. Such less-consumed and easy-to-handle CNC-PCD film may be useful as a colorimetric sensor to detect or discriminate methanol in some industrial products.

MADS-box gene AaSEP4 promotes artemisinin biosynthesis in Artemisia annua.

The plant Artemisia annua is well known for its production of artemisinin, a sesquiterpene lactone that is an effective antimalarial compound. Although remarkable progress has been made toward understanding artemisinin biosynthesis, the effect of MADS-box family transcription factors on artemisinin biosynthesis is still poorly understood. In this study, we identified a MADS transcription factor, AaSEP4, that was predominantly expressed in trichome. AaSEP4 acts as a nuclear-localized transcriptional activator activating the expression of AaGSW1 (GLANDULAR TRICHOME-SPECIFIC WRKY1). Dual-luciferase and Yeast one-hybrid assays revealed that AaSEP4 directly bound to the CArG motif in the promoter region of AaGSW1. Overexpression of AaSEP4 in A. annua significantly induced the expression of AaGSW1 and four artemisinin biosynthesis genes, including amorpha-4,11-diene synthase (ADS), cytochrome P450 monooxygenase (CYP71AV1), double-bond reductase 2 (DBR2) and aldehyde dehydrogenase 1 (ALDH1). Furthermore, the results of high-performance liquid chromatography (HPLC) showed that the artemisinin content was significantly increased in the AaSEP4-overexpressed plants. In addition, RT-qPCR results showed that AaSEP4 was induced by methyl jasmonic acid (MeJA) treatment. Taken together, these results explicitly demonstrate that AaSEP4 is a positive regulator of artemisinin biosynthesis, which can be used in the development of high-artemisinin yielding A. annua varieties.

Digital competence as a protective factor against gaming addiction in children and adolescents: A cross-sectional study in Hong Kong.

Background: Digital competence can help children and adolescents engage with technology for acquiring new knowledge and for broadening social contact and support, while reducing the risk of inappropriate media use. This study investigated the effects of digital competence on the risk of gaming addiction among children and adolescents. We explored whether students with good digital competence were protected from the adverse effects of media use and the risk of gaming addiction. Methods: 1956 students (690 primary and 1266 secondary) completed a digital competence assessment and a self-report questionnaire on their mental health status, use of digital devices, and experiences of cyberbullying. Multiple regression analyses with further mediation and moderation analyses were performed to investigate the association of digital competence with gaming addiction and mental health in children and adolescents. Findings: Regression analyses showed that children and adolescents with better digital competence were less likely to develop gaming addiction (ß = -0.144, p < 0.0001) and experienced less cyberbullying behaviour as perpetrators (ß = -0.169, p < 0.0001) and as victims (ß = -0.121, p < 0.0001). Digital competence was found to mediate the relationship between digital device usage time and gaming addiction. Interpretation: Digital competence is associated with less gaming addiction and could potentially lead to better mental wellbeing by reducing the risks of gaming addiction and cyberbullying. Education that promotes digital competence is essential to maximize the benefits of media use, while reducing the potential adverse effects from the inappropriate use of digital devices. Funding: This study was supported by a grant from the Research Grants Council of the HKSAR Government (#T44-707/16N) under the Theme-based Research Scheme.

Severity of SARS-CoV-2 Omicron BA.2 infection in unvaccinated hospitalized children: comparison to influenza and parainfluenza infections.

There has been a rapid surge of hospitalization due to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variants globally. The severity of Omicron BA.2 in unexposed, unvaccinated, hospitalized children is unknown. We investigated the severity and clinical outcomes of COVID-19 infection during the Omicron wave in uninfected, unvaccinated hospitalized children and in comparison with influenza and parainfluenza viral infections. This population-based study retrieved data from the HK territory-wide CDARS database of hospitalisations in all public hospitals and compared severe outcomes for the Omicron BA.2-dominant fifth wave (5-28 February 2022, n = 1144), and influenza and parainfluenza viruses (1 January 2015-31 December 2019, n = 32212 and n = 16423, respectively) in children 0-11 years old. Two deaths (0.2%) out of 1144 cases during the initial Omicron wave were recorded. Twenty-one (1.8%) required PICU admission, and the relative risk was higher for Omicron than influenza virus (n = 254, 0.8%, adjusted RR = 2.1, 95%CI 1.3-3.3, p = 0.001). The proportion with neurological complications was 15.0% (n = 171) for Omicron, which was higher than influenza and parainfluenza viruses (n = 2707, 8.4%, adjusted RR = 1.6, 95%CI 1.4-1.9 and n = 1258, 7.7%, adjusted RR = 1.9, 95%CI 1.6-2.2, p < 0.001 for both, respectively). Croup occurred for Omicron (n = 61, 5.3%) more than influenza virus (n = 601, 1.9%, adjusted RR = 2.0, 95%CI 1.5-2.6, p < 0.001) but not parainfluenza virus (n = 889, 5.4%). Our findings showed that for hospitalized children who had no past COVID-19 or vaccination, Omicron BA.2 was not mild. Omicron BA.2 appeared to be more neuropathogenic than influenza and parainfluenza viruses. It targeted the upper airways more than influenza virus.

PTMdyna: exploring the influence of post-translation modifications on protein conformational dynamics.

Protein post-translational modifications (PTM) play vital roles in cellular regulation, modulating functions by driving changes in protein structure and dynamics. Exploring comprehensively the influence of PTM on conformational dynamics can facilitate the understanding of the related biological function and molecular mechanism. Currently, a series of excellent computation tools have been designed to analyze the time-dependent structural properties of proteins. However, the protocol aimed to explore conformational dynamics of post-translational modified protein is still a blank. To fill this gap, we present PTMdyna to visually predict the conformational dynamics differences between unmodified and modified proteins, thus indicating the influence of specific PTM. PTMdyna exhibits an AUC of 0.884 tested on 220 protein-protein complex structures. The case of heterochromatin protein 1α complexed with lysine 9-methylated histone H3, which is critical for genomic stability and cell differentiation, was used to demonstrate its applicability. PTMdyna provides a reliable platform to predict the influence of PTM on protein dynamics, making it easier to interpret PTM functionality at the structure level. The web server is freely available at http://ccbportal.com/PTMdyna.

Web-Based Quantitative Structure-Activity Relationship Resources Facilitate Effective Drug Discovery.

Traditional drug discovery effectively contributes to the treatment of many diseases but is limited by high costs and long cycles. Quantitative structure-activity relationship (QSAR) methods were introduced to evaluate the activity of compounds virtually, which saves the significant cost of determining the activities of the compounds experimentally. Over the past two decades, many web tools for QSAR modeling with various features have been developed to facilitate the usage of QSAR methods. These web tools significantly reduce the difficulty of using QSAR and indirectly promote drug discovery. However, there are few comprehensive summaries of these QSAR tools, and researchers may have difficulty determining which tool to use. Hence, we systematically surveyed the mainstream web tools for QSAR modeling. This work may guide researchers in choosing appropriate web tools for developing QSAR models, and may also help develop more bioinformatics tools based on these existing resources. For nonprofessionals, we also hope to make more people aware of QSAR methods and expand their use.

In Silico Resources of Drug-Likeness as a Mirror: What Are We Lacking in Pesticide-Likeness?

Unfavorable bioavailability is an important aspect underlying the failure of drug candidates. Computational approaches for evaluating drug-likeness can minimize these risks. Over the past decades, computational approaches for evaluating drug-likeness have sped up the process of drug development and were also quickly derived to pesticide-likeness. As a result of many critical differences between drugs and pesticides, many kinds of methods for drug-likeness cannot be used for pesticide-likeness. Therefore, it is crucial to comprehensively compare and analyze the differences between drug-likeness and pesticide-likeness, which may provide a basis for solving the problems encountered during the evaluation of pesticide-likeness. Here, we systematically collected the recent advances of drug-likeness and pesticide-likeness and compared their characteristics. We also evaluated the current lack of studies on pesticide-likeness, the molecular descriptors and parameters adopted, the pesticide-likeness model on pesticide target organisms, and comprehensive analysis tools. This work may guide researchers to use appropriate methods for developing pesticide-likeness models. It may also aid non-specialists to understand some important concepts in drug-likeness and pesticide-likeness.

Evaluation of axial length/total corneal refractive power ratio as a potential marker for ocular diagnosis of Marfan's syndrome in children.

AIM: To investigate whether the axial length (AL)/total corneal refractive power (TCRP) ratio is a sensitive and simple factor that can be used for the early diagnosis of Marfan's syndrome (MFS) in children. METHODS: The relationship between the AL/TCRP ratio and the diagnosis of MFS for 192 eyes in 97 children were evaluate. The biological characteristics, including age, sex, AL, and TCRP, were collected from medical records. Receiver operating characteristic (ROC) curve analysis was performed to investigate whether the AL/TCRP ratio effectively distinguishes MFS from other subjects. The Youden index was used to re-divide the whole population into two groups according to an AL/TCRP ratio of 0.59. RESULTS: Of 96 subjects (mean age 7.46±3.28y) evaluated, 56 (110 eyes) had a definite diagnosis of MFS in childhood based on the revised Ghent criteria, 41 (82 eyes) with diagnosis of congenital ectopia lentis (EL) were included as a control group. AL was negatively correlated with TCRP, with a linear regression coefficient of -0.36 (R 2=0.08). A significant correlation was found between age and the AL/TCRP ratio (P=0.023). ROC curve analysis showed that the AL/TCRP ratio distinguished MFS from the other patients at a threshold of 0.59. MFS patients were present in 24/58 (41.38%) patients with an AL/TCRP ratio of ≤0.59 and in 34/39 (87.18%) patients with an AL/TCRP ratio of >0.59. CONCLUSION: An AL/TCRP ratio of >0.59 is significantly associated with the risk of MFS. The AL/TCRP ratio should be measured as a promising marker for the prognosis of children MFS. Changes in the AL/TCRP ratio should be monitored over time.

[Finite element analysis of the effect of plate placement angle on cervical spine stability in anterior cervical fusion surgery].

OBJECTIVE: Using the method of finite element analysis, to compare the biomechanical properties between the plate deviating from the long axis of the cervical spine and the standard placement of the plate in the anterior cervical fusion surgery. METHODS: A healthy female volunteer was selected and CT scan (C1-T1) was performed. Using Mimics 19.0, Geomagic Studio 2015, Solidworks 2018, Ansys Workbench 17.2 to establish a lower cervical spine (C3-C7) model and to verify the reliability of the model. Subsequently, anterior cervical plates of different angles and lengths were placed to establish an anterior cervical discectomy fusion (ACDF) model. Applying 73.6 N axial pressure and 1 NM pure moment on C3 to make the model produce flexion, extension, lateral bending and rotation activities, observed the model stress cloud diagram and recorded the maximum stress value of the instrument and the intervertebral mobility. RESULTS: The lower cervical spine (C3-C7) finite element model was established and verified against the published literature on the range of motion (ROM) of cervical spine. Effect of steel plate offset axis on stress distribution, maximum stress value and intervertebral ROM of internal fixation apparatus was minimal, and the mechanical effect of steel plate offset was less in double section steel plate than in single section steel plate. CONCLUSION: Little effect on the mechanical stability of the cervical spine was anticipated when the anterior cervical plate was not perfectly aligned with the long axis of the cervical spine. If the tilt of the plate in clinical surgery is less than 20°, there is no need to readjust the position of the plate.

HISNAPI: a bioinformatic tool for dynamic hot spot analysis in nucleic acid-protein interface with a case study.

Protein-nucleic acid interactions play essential roles in many biological processes, such as transcription, replication and translation. In protein-nucleic acid interfaces, hotspot residues contribute the majority of binding affinity toward molecular recognition. Hotspot residues are commonly regarded as potential binding sites for compound molecules in drug design projects. The dynamic property is a considerable factor that affects the binding of ligands. Computational approaches have been developed to expedite the prediction of hotspot residues on protein-nucleic acid interfaces. However, existing approaches overlook hotspot dynamics, despite their essential role in protein function. Here, we report a web server named Hotspots In silico Scanning on Nucleic Acid and Protein Interface (HISNAPI) to analyze hotspot residue dynamics by integrating molecular dynamics simulation and one-step free energy perturbation. HISNAPI is capable of not only predicting the hotspot residues in protein-nucleic acid interfaces but also providing insights into their intensity and correlation of dynamic motion. Protein dynamics have been recognized as a vital factor that has an effect on the interaction specificity and affinity of the binding partners. We applied HISNAPI to the case of SARS-CoV-2 RNA-dependent RNA polymerase, a vital target of the antiviral drug for the treatment of coronavirus disease 2019. We identified the hotspot residues and characterized their dynamic behaviors, which might provide insight into the target site for antiviral drug design. The web server is freely available via a user-friendly web interface at http://chemyang.ccnu.edu.cn/ccb/server/HISNAPI/ and http://agroda.gzu.edu.cn:9999/ccb/server/HISNAPI/.

Bioinformatics toolbox for exploring protein phosphorylation network.

A clear systematic delineation of the interactions between phosphorylation sites on substrates and their effector kinases plays a fundamental role in revealing cellular activities, understanding signaling modulation mechanisms and proposing novel hypotheses. The emergence of bioinformatics tools contributes to studying phosphorylation network. Some of them feature the visualization of network, enabling more effective trace of the underlying biological problems in a clear and succinct way. In this review, we aimed to provide a toolbox for exploring phosphorylation network. We first systematically surveyed 19 tools that are available for exploring phosphorylation networks, and subsequently comparatively analyzed and summarized these tools to guide tool selection in terms of functionality, data sources, performance, network visualization and implementation, and finally briefly discussed the application cases of these tools. In different scenarios, the conclusion on the suitability of a tool for a specific user may vary. Nevertheless, easily accessible bioinformatics tools are proved to facilitate biological findings. Hopefully, this work might also assist non-specialists, students, as well as computational scientists who aim at developing novel tools in the field of phosphorylation modification.

Diffusion kurtosis imaging in evaluating gliomas: different region of interest selection methods on time efficiency, measurement repeatability, and diagnostic ability.

OBJECTIVES: Comparing the diagnostic efficacy of diffusion kurtosis imaging (DKI) derived from different region of interest (ROI) methods in tumor parenchyma for grading and predicting IDH-1 mutation and 1p19q co-deletion status of glioma patients and correlating with their survival data. METHODS: Sixty-six patients (29 females; median age, 45 years) with pathologically proved gliomas (low-grade gliomas, 36; high-grade gliomas, 30) were prospectively included, and their clinical data were collected. All patients underwent DKI examination. DKI maps of each metric were derived. Three groups of ROIs (ten spots, ROI-10s; three biggest tumor slices, ROI-3s; and whole-tumor parenchyma, ROI-whole) were manually drawn by two independent radiologists. The interobserver consistency, time spent, diagnostic efficacy, and survival analysis of DKI metrics based on these three ROI methods were analyzed. RESULTS: The intraexaminer reliability for all parameters among these three ROI methods was good, and the time spent on ROI-10s was significantly less than that of the other two methods (p < 0.001). DKI based on ROI-10s demonstrated a slightly better diagnostic value than the other two ROI methods for grading and predicting the IDH-1 mutation status of glioma, whereas DKI metrics derived from ROI-10s performed much better than those of the ROI-3s and ROI-whole in identifying 1p19q co-deletion. In survival analysis, the model based on ROI-10s that included patient age and mean diffusivity showed the highest prediction value (C-index, 0.81). CONCLUSIONS: Among the three ROI methods, the ROI-10s method had the least time spent and the best diagnostic value for a comprehensive evaluation of glioma. It is an effective way to process DKI data and has important application value in the clinical evaluation of glioma. KEY POINTS: • The intraexaminer reliability for all DKI parameters among different ROI methods was good, and the time spent on ROI-10 spots was significantly less than the other two ROI methods. • DKI metrics derived from ROI-10 spots performed the best in ROI selection methods (ROI-10s, ten-spot ROIs; ROI-3s, three biggest tumor slices ROI; and ROI-whole, whole-tumor parenchyma ROI) for a comprehensive evaluation of glioma. • The ROI-10 spots method is an effective way to process DKI data and has important application value in the clinical evaluation of glioma.

Cloud 3D-QSAR: a web tool for the development of quantitative structure-activity relationship models in drug discovery.

Effective drug discovery contributes to the treatment of numerous diseases but is limited by high costs and long cycles. The Quantitative Structure-Activity Relationship (QSAR) method was introduced to evaluate the activity of a large number of compounds virtually, reducing the time and labor costs required for chemical synthesis and experimental determination. Hence, this method increases the efficiency of drug discovery. To meet the needs of researchers to utilize this technology, numerous QSAR-related web servers, such as Web-4D-QSAR and DPubChem, have been developed in recent years. However, none of the servers mentioned above can perform a complete QSAR modeling and supply activity prediction functions. We introduce Cloud 3D-QSAR by integrating the functions of molecular structure generation, alignment, molecular interaction field (MIF) computing and results analysis to provide a one-stop solution. We rigidly validated this server, and the activity prediction correlation was R2 = 0.934 in 834 test molecules. The sensitivity, specificity and accuracy were 86.9%, 94.5% and 91.5%, respectively, with AUC = 0.981, AUCPR = 0.971. The Cloud 3D-QSAR server may facilitate the development of good QSAR models in drug discovery. Our server is free and now available at http://chemyang.ccnu.edu.cn/ccb/server/cloud3dQSAR/ and http://agroda.gzu.edu.cn:9999/ccb/server/cloud3dQSAR/.