Freeprotmap: waiting-free prediction method for protein distance map.

BACKGROUND: Protein residue-residue distance maps are used for remote homology detection, protein information estimation, and protein structure research. However, existing prediction approaches are time-consuming, and hundreds of millions of proteins are discovered each year, necessitating the development of a rapid and reliable prediction method for protein residue-residue distances. Moreover, because many proteins lack known homologous sequences, a waiting-free and alignment-free deep learning method is needed. RESULT: In this study, we propose a learning framework named FreeProtMap. In terms of protein representation processing, the proposed group pooling in FreeProtMap effectively mitigates issues arising from high-dimensional sparseness in protein representation. In terms of model structure, we have made several careful designs. Firstly, it is designed based on the locality of protein structures and triangular inequality distance constraints to improve prediction accuracy. Secondly, inference speed is improved by using additive attention and lightweight design. Besides, the generalization ability is improved by using bottlenecks and a neural network block named local microformer. As a result, FreeProtMap can predict protein residue-residue distances in tens of milliseconds and has higher precision than the best structure prediction method. CONCLUSION: Several groups of comparative experiments and ablation experiments verify the effectiveness of the designs. The results demonstrate that FreeProtMap significantly outperforms other state-of-the-art methods in accurate protein residue-residue distance prediction, which is beneficial for lots of protein research works. It is worth mentioning that we could scan all proteins discovered each year based on FreeProtMap to find structurally similar proteins in a short time because the fact that the structure similarity calculation method based on distance maps is much less time-consuming than algorithms based on 3D structures.

Computer-based facial recognition as an assisting diagnostic tool to identify children with Noonan syndrome.

BACKGROUND: Noonan syndrome (NS) is a rare genetic disease, and patients who suffer from it exhibit a facial morphology that is characterized by a high forehead, hypertelorism, ptosis, inner epicanthal folds, down-slanting palpebral fissures, a highly arched palate, a round nasal tip, and posteriorly rotated ears. Facial analysis technology has recently been applied to identify many genetic syndromes (GSs). However, few studies have investigated the identification of NS based on the facial features of the subjects. OBJECTIVES: This study develops advanced models to enhance the accuracy of diagnosis of NS. METHODS: A total of 1,892 people were enrolled in this study, including 233 patients with NS, 863 patients with other GSs, and 796 healthy children. We took one to 10 frontal photos of each subject to build a dataset, and then applied the multi-task convolutional neural network (MTCNN) for data pre-processing to generate standardized outputs with five crucial facial landmarks. The ImageNet dataset was used to pre-train the network so that it could capture generalizable features and minimize data wastage. We subsequently constructed seven models for facial identification based on the VGG16, VGG19, VGG16-BN, VGG19-BN, ResNet50, MobileNet-V2, and squeeze-and-excitation network (SENet) architectures. The identification performance of seven models was evaluated and compared with that of six physicians. RESULTS: All models exhibited a high accuracy, precision, and specificity in recognizing NS patients. The VGG19-BN model delivered the best overall performance, with an accuracy of 93.76%, precision of 91.40%, specificity of 98.73%, and F1 score of 78.34%. The VGG16-BN model achieved the highest AUC value of 0.9787, while all models based on VGG architectures were superior to the others on the whole. The highest scores of six physicians in terms of accuracy, precision, specificity, and the F1 score were 74.00%, 75.00%, 88.33%, and 61.76%, respectively. The performance of each model of facial recognition was superior to that of the best physician on all metrics. CONCLUSION: Models of computer-assisted facial recognition can improve the rate of diagnosis of NS. The models based on VGG19-BN and VGG16-BN can play an important role in diagnosing NS in clinical practice.

Facial recognition models for identifying genetic syndromes associated with pulmonary stenosis in children.

BACKGROUND: Williams-Beuren syndrome, Noonan syndrome, and Alagille syndrome are common types of genetic syndromes (GSs) characterized by distinct facial features, pulmonary stenosis, and delayed growth. In clinical practice, differentiating these three GSs remains a challenge. Facial gestalts serve as a diagnostic tool for recognizing Williams-Beuren syndrome, Noonan syndrome, and Alagille syndrome. Pretrained foundation models (PFMs) can be considered the foundation for small-scale tasks. By pretraining with a foundation model, we propose facial recognition models for identifying these syndromes. METHODS: A total of 3297 (n = 1666) facial photos were obtained from children diagnosed with Williams-Beuren syndrome (n = 174), Noonan syndrome (n = 235), and Alagille syndrome (n = 51), and from children without GSs (n = 1206). The photos were randomly divided into five subsets, with each syndrome and non-GS equally and randomly distributed in each subset. The proportion of the training set and the test set was 4:1. The ResNet-100 architecture was employed as the backbone model. By pretraining with a foundation model, we constructed two face recognition models: one utilizing the ArcFace loss function, and the other employing the CosFace loss function. Additionally, we developed two models using the same architecture and loss function but without pretraining. The accuracy, precision, recall, and F1 score of each model were evaluated. Finally, we compared the performance of the facial recognition models to that of five pediatricians. RESULTS: Among the four models, ResNet-100 with a PFM and CosFace loss function achieved the best accuracy (84.8%). Of the same loss function, the performance of the PFMs significantly improved (from 78.5% to 84.5% for the ArcFace loss function, and from 79.8% to 84.8% for the CosFace loss function). With and without the PFM, the performance of the CosFace loss function models was similar to that of the ArcFace loss function models (79.8% vs 78.5% without PFM; 84.8% vs 84.5% with PFM). Among the five pediatricians, the highest accuracy (0.700) was achieved by the senior-most pediatrician with genetics training. The accuracy and F1 scores of the pediatricians were generally lower than those of the models. CONCLUSIONS: A facial recognition-based model has the potential to improve the identification of three common GSs with pulmonary stenosis. PFMs might be valuable for building screening models for facial recognition. Key messages What is already known on this topic:  Early identification of genetic syndromes (GSs) is crucial for the management and prognosis of children with pulmonary stenosis (PS). Facial phenotyping with convolutional neural networks (CNNs) often requires large-scale training data, limiting its usefulness for GSs. What this study adds:  We successfully built multi-classification models based on face recognition using a CNN to accurately identify three common PS-associated GSs. ResNet-100 with a pretrained foundation model (PFM) and CosFace loss function achieved the best accuracy (84.8%). Pretrained with the foundation model, the performance of the models significantly improved, although the impact of the type of loss function appeared to be minimal. How this study might affect research, practice, or policy:  A facial recognition-based model has the potential to improve the identification of GSs in children with PS. The PFM might be valuable for building identification models for facial detection.

Development, Validation, and Application of a Human Reproductive Toxicity Prediction Model Based on Adverse Outcome Pathway.

A growing number of environmental contaminants have been proved to have reproductive toxicity to males and females. However, the unclear toxicological mechanism of reproductive toxicants limits the development of virtual screening methods. By consolidating androgen (AR)-/estrogen receptors (ERs)-mediated adverse outcome pathways (AOPs) with more than 8000 chemical substances, we uncovered relationships between chemical features, a series of pathway-related effects, and reproductive apical outcomes─changes in sex organ weights. An AOP-based computational model named RepTox was developed and evaluated to predict and characterize chemicals' reproductive toxicity for males and females. Results showed that RepTox has three outstanding advantages. (I) Compared with the traditional models (37 and 81% accuracy, respectively), AOP significantly improved the predictive robustness of RepTox (96.3% accuracy). (II) Compared with the application domain (AD) of models based on small in vivo datasets, AOP expanded the ADs of RepTox by 1.65-fold for male and 3.77-fold for female, respectively. (III) RepTox implied that hydrophobicity, cyclopentanol substructure, and several topological indices (e.g., hydrogen-bond acceptors) were important, unbiased features associated with reproductive toxicants. Finally, RepTox was applied to the inventory of existing chemical substances of China and identified 2100 and 7281 potential toxicants to the male and female reproductive systems, respectively.

Epigenetic silencing of E-cadherin gene induced by lncRNA MALAT-1 in acute myeloid leukaemia.

BACKGROUND: Epigenetic abnormalities in acute myeloid leukaemia provide us with a target for novel therapeutic strategies. The aim of the study was to verify the epigenetic regulatory mechanism of E-cadherin gene silencing induced by long non-coding RNA MALAT-1 in AML. METHODS: Expression of MALAT-1, E-cadherin, EZH2, SUZ12 and EED genes in AML patients was detected by RT-qPCR. After MALAT-1 silencing in AML cell lines, levels of the E-cadherin, EZH2, SUZ12, EED, DNMT1, DNMT3A and DNMT3B genes and encoded proteins were detected by RT-qPCR and Western blotting. The level of CpG island methylation and trimethylation modification of histone H3K27 in the promoter region of E-cadherin was detected by pyrosequencing and ChIP-qPCR. RIP-qPCR was used to detect the interaction between MALAT-1 and proteins. RESULTS: MALAT-1, EZH2 and EED gene expression was markedly increased in AML patients with E-cadherin down-regulation. A positive correlation between EZH2 or SUZ12 and MALAT-1 expression was observed. After MALAT-1 silencing, the expression of E-cadherin was up-regulated, whereas the expression of EZH2, SUZ12, DNMT1, DNMT3A and DNMT3B was down-regulated. Results of Western blotting were consistent with those of RT-qPCR. Methylation levels of E-cadherin in AML patients were higher than that in normal controls, which appeared to increase with age. Methylation of the CpG island and H3K27 trimethylation of E-cadherin were decreased after MALAT-1 silencing. RIP-qPCR suggested that MALAT-1 might be enriched by EZH2 and SUZ12. CONCLUSION: Our findings verified that MALAT-1 might lead to the transcriptional silencing of E-cadherin gene through the trimethylation of H3K27 mediated by recruiting EZH2 and SUZ12.

Structures of Endocrine-Disrupting Chemicals Correlate with the Activation of 12 Classic Nuclear Receptors.

Endocrine-disrupting chemicals (EDCs) can inadvertently interact with 12 classic nuclear receptors (NRs) that disrupt the endocrine system and cause adverse effects. There is no widely accepted understanding about what structural features make thousands of EDCs able to activate different NRs as well as how these structural features exert their functions and induce different outcomes at the cellular level. This paper applies the hierarchical characteristic fragment methodology and high-throughput screening molecular docking to comprehensively explore the structural and functional features of EDCs for the 12 NRs based on more than 7000 chemicals from curated datasets. EDCs share three levels of key fragments. The primary and secondary fragments are associated with the binding of EDCs to four groups of receptors: steroidal nuclear receptors (SNRs, including androgen, estrogen, glucocorticoid, mineralocorticoid, and progesterone), retinoic acid receptors, thyroid hormone receptors, and vitamin D receptors. The tertiary fragments determine the activity type by interacting with two key locations in the ligand-binding domains of NRs (N-H5-H3-C and N-H7-H11-C for SNRs and N-H5-H5'-H2'-H3-C and N-H6'-H11-C for non-SNRs). The resulting compiled structural fragments of EDCs together with elucidated compound NR binding modes provide a framework for understanding the interactions between EDCs and NRs, facilitating faster and more accurate screening of EDCs for multiple NRs in the future.

Prognostic nomogram for 30-day mortality of deep vein thrombosis patients in intensive care unit.

BACKGROUND: We aimed to use the Medical Information Mart for Intensive Care III database to build a nomogram to identify 30-day mortality risk of deep vein thrombosis (DVT) patients in intensive care unit (ICU). METHODS: Stepwise logistic regression and logistic regression with least absolute shrinkage and selection operator (LASSO) were used to fit two prediction models. Bootstrap method was used to perform internal validation. RESULTS: We obtained baseline data of 535 DVT patients, 91 (17%) of whom died within 30 days. The discriminations of two new models were better than traditional scores. Compared with simplified acute physiology score II (SAPSII), the predictive abilities of two new models were improved (Net reclassification improvement [NRI] > 0; Integrated discrimination improvement [IDI] > 0; P < 0.05). The Brier scores of two new models in training set were 0.091 and 0.108. After internal validation, corrected area under the curves for two models were 0.850 and 0.830, while corrected Brier scores were 0.108 and 0.114. The more concise model was chosen to make the nomogram. CONCLUSIONS: The nomogram developed by logistic regression with LASSO model can provide an accurate prognosis for DVT patients in ICU.

A retrospective analysis of risk factors associated with catheter-related thrombosis: a single-center study.

BACKGROUND: Catheter-related thrombosis may lead to catheter infections and failure, further deep venous thrombosis, and pulmonary embolism. Recognizing the risk factors for catheter-related thrombosis is extremely important to inform the development of catheter care guidelines. METHODS: Data were collected from a total of 1,532 patients who had undergone venous catheterization, including indwelling catheterization from 19 March 2019 to 30 March 2019 in the Sun Yat-sen Memorial Hospital. The factors for which data were to be collected included the patients' physical characteristics, catheter-related factors, and catheter care-related factors. Logistic regression analysis, the chi-squared test, Fisher's exact test, and the t-test were used to analyze the data. RESULTS: Of the 1,532 patients studied, 28 developed intraductal thrombi, and of the factors analyzed, malignancy, a catheterization history, a history of thrombophilia, surgery during the week before catheterization, the catheterization duration, and anticoagulant therapy were significant risk factors associated with catheter-related thrombosis (all p < 0.05). There were no significant associations between the catheter brand, the number of lumens, the insertion direction, or the factors associated with catheter care and catheter-related thrombosis (all p > 0.05). CONCLUSION: Our study incorporated clear and systematic risk factors associated with catheter-related thrombosis. Malignancy, history of thrombophilia, history of catheterization, surgery during the week before catheterization, and catheterization duration were associated with increased risks of catheter-related thrombosis. Prophylactic anticoagulation was effective for preventing and treating catheter-related thrombosis.

Critical appraisal of international guidelines for the prevention and treatment of pregnancy-associated venous thromboembolism: a systematic review.

BACKGROUND: Pregnancy-associated Venous thromboembolism (VTE) is one of the most common causes of maternal morbidity and mortality in developed countries. In this study, we aimed to systematically review and critical appraisal of guidelines to compare the recommendations in pregnancy-associated VTE. METHODS: Guidelines in English between January 1, 2009 and November 31, 2018 were searched using Medline via PubMed, as well as the guidelines' website. The guidelines containing the recommendations on pregnancy-associated VTE were included. Through the Appraisal of Guidelines Research and Evaluation II (AGREE II) instrument, three reviewers appraised the quality of the included guidelines. The recommendations were also summarized and compared to analyze the consistency. RESULTS: Fifteen guidelines from 13 organizations were included. Ten guidelines from nine organizations, namely, ACCP, ANZJOG, ASH, Australia, ESC, Korea, RCOG, SASTH, SOCC, were regarded as "strongly recommended for use in practice". Most of the included guidelines scored low in lower scores in domain 3 (Rigor of development) and domain 6 (Editorial independence). Recommendations on prevention are contained in ten guidelines while treatment are included in seven. The main conflicting recommendations were mainly at the anticoagulant choice for prevention on pregnant women and prevention after cesarean section. The duration of VTE treatment in pregnant women was also controversial. CONCLUSIONS: In summary, the quality of pregnancy-associated VTE guidelines varied widely, especially in Rigor of development and Editorial independence. Recommendations were inconsistent both in prevention and treatment across guidelines. Increased efforts are required to provide high-quality evidence specific to the pregnancy population. Guideline developers should also pay more attention to methodological quality.

Critical appraisal of international guidelines for the screening and treatment of asymptomatic peripheral artery disease: a systematic review.

BACKGROUND: Peripheral artery disease (PAD) is often asymptomatic but increases the risk of developing cardiovascular events. Due to the uncertainties regarding the quality of related guidelines and a lack of clear-cut evidence, we performed a systematic review and critical appraisal of these guidelines to evaluate their consistency of the recommendations in asymptomatic PAD population. METHODS: Guidelines in English between January 1st, 2000 to December 31th, 2017 were screened in databases including Medline via PubMed, EMBASE, the G-I-N International Guideline Library, the National Guidelines Clearinghouse, the Canadian Medication Association Infobase and the National Library for Health. Those guidelines containing recommendations on screening and treatment for asymptomatic PAD were included, and three reviewers evaluated the quality of the guidelines using Appraisal of Guidelines Research and Evaluation (AGREE) II instrument. Related recommendations were then fully extracted and compared by two reviewers. RESULTS: Fourteen guidelines were included finally and the AGREE scores ranged from 39 to 73%. Most of included guidelines scored low in Rigor of development and Editorial independence, and only two guidelines (ACCF/AHA, AHA/ACC) reached the standard on Conflict of Interest from Institute of Medicine (IOM). Eight guidelines recommended screening at different strength while the others found insufficient evidence or were against screening. Conflicting recommendations on treatment were found in the target value of the lipid lowering and antiplatelet therapy. The treatment policies in three guidelines (BWG, CEVF, ESC) appeared more aggressive, but they had low transparency between guideline developer and industry or did not reach the standard of IOM. CONCLUSIONS: Current guidelines on asymptomatic PAD varied in the methodological quality and fell short of the standard in the rigor of development and editorial independence. Conflicting recommendations were found both on the screening and treatment. More effort is needed to provide clear-cut evidences with high quality and transparency among guideline developer and industry.

Extended Virtual Screening Strategies To Link Antiandrogenic Activities and Detected Organic Contaminants in Soils.

A tiered screening strategy based on extensive virtual fractionation and elucidation was developed to simplify identification of toxicants in complex environments. In tier1-virtual fractionation, multivariate analysis (MVA) was set up as an alternative of physical fractionation. In tier2-virtual structure elucidation, in-house quantitative structure-retention relationship (QSRR) models and toxicity simulation methods were developed to simplify nontarget identification. The efficiency of the tiered virtual strategy was tentatively verified by soil samples from a chemical park contaminated by antiandrogenic substances. Eight out of 18 sites were detected as antiandrogenic, while none of them exhibited androgenic agonist potencies. Sixty-seven peaks were selected for further identification by MVA, among which over 90% were verified in androgenic fractions in traditional effect-directed analysis (EDA). With 579 tentative structures generated by in silico fragmentation, 74% were elucidated by QSRR and 65% were elucidated by in silico toxicity prediction. All prior peaks were identified at different confidence levels with over 40% of the identified peaks above confidence level 2b, which has been increased over 40% with less than half of the time spent compared to traditional EDA. Such a combination of tiered virtual screening methods provides more efficient and rapid identifications of key toxicants at contaminated sites.

Identification of Thyroid Hormone Disruptors among HO-PBDEs: In Vitro Investigations and Coregulator Involved Simulations.

Some hydroxylated polybrominated diphenyl ethers (HO-PBDEs), that have been widely detected in the environment and tissues of humans and wildlife, bind to thyroid hormone (TH) receptor (TR) and can disrupt functioning of systems modulated by the TR. However, mechanisms of TH disrupting effects are still equivocal. Here, disruption of functions of TH modulated pathways by HO-PBDEs was evaluated by assays of competitive binding, coactivator recruitment, and proliferation of GH3 cells. In silico simulations considering effects of coregulators were carried out to investigate molecular mechanisms and to predict potencies for disrupting functions of the TH. Some HO-PBDEs were able to bind to TR with moderate affinities but were not agonists. In GH3 proliferation assays, 13 out of 16 HO-PBDEs were antagonists for the TH. In silico simulations of molecular dynamics revealed that coregulators were essential for identification of TH disruptors. Among HO-PBDEs, binding of passive antagonists induced repositioning of H12, blocking AF-2 (transactivation function 2) and preventing recruitment of the coactivator. Binding of active antagonists exposed the coregulator binding site, which tended to bind to the corepressor rather than the coactivator. By considering both passive and active antagonisms, anti-TH potencies of HO-PBDEs could be predicted from free energy of binding.

Integrated Analysis of Expression Profile Based on Differentially Expressed Genes in Middle Cerebral Artery Occlusion Animal Models.

Stroke is one of the most common causes of death, only second to heart disease. Molecular investigations about stroke are in acute shortage nowadays. This study is intended to explore a gene expression profile after brain ischemia reperfusion. Meta-analysis, differential expression analysis, and integrated analysis were employed on an eight microarray series. We explored the functions and pathways of target genes in gene ontology (GO) enrichment analysis and constructed a protein-protein interaction network. Meta-analysis identified 360 differentially expressed genes (DEGs) for Mus musculus and 255 for Rattus norvegicus. Differential expression analysis identified 44 DEGs for Mus musculus and 21 for Rattus norvegicus. Timp1 and Lcn2 were overexpressed in both species. The cytokine-cytokine receptor interaction and chemokine signaling pathway were highly enriched for the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. We have exhibited a global view of the potential molecular differences between middle cerebral artery occlusion (MCAO) animal model and sham for Mus musculus or Rattus norvegicus, including the biological process and enriched pathways in DEGs. This research helps contribute to a clearer understanding of the inflammation process and accurate identification of ischemic infarction stages, which might be transformed into a therapeutic approach.

Phenotypic and genotypic spectrum of noonan syndrome: A retrospective analysis of 46 consecutive pediatric patients presented at a regional cardiac center in China.

Background: Noonan syndrome (NS) is relatively common but poorly recognized. We aimed to describe the phenotypic and genotypic spectrum of NS in a Chinese cohort. Method: The study retrospectively investigated consecutive pediatric patients who presented at the Guangdong cardiovascular institute between 2018 and 2020 with confirmed known NS-relevant mutations determined by exome sequencing. Dates of genetic testing, Age, sex, institution of genetic testing, mutated gene (related to NS) and its classification, heterozygosity, and parental origin were identified from the sequencing reports. Facial features, cardiac defect and other clinical characteristics were also assessed. Comparisons of categorical variables between groups were examined by Chi-square test or Fisher's exact test when appropriate. Intraclass correlation coefficient (ICC) was performed to evaluate the reliability of evaluation of facial features between different evaluators. Results: The most prevalent mutated genes were PTPN11 (37.0%) and RAF1 (19.6%), and most mutations were pathogenic (67.4%) and de novo (87.0%). Most patients were with NS-relevant facial features (97.4%) and cardiac defects (92.7%), where ventricular hypertrophy, pulmonary valve stenosis, and atrial septal defect were the most prevalent. Patients with mutated RAF1 appeared to be diagnosed at an older age than those with mutated PTPN11, and with higher prevalence of mitral regurgitation, hypertrophic cardiomyopathy, and ventricular hypertrophy, but lower prevalence of pulmonary valve stenosis and pulmonary artery stenosis. Patients presented at an age ≥2 years appeared to be with fewer NS-relevant facial features and cardiac defects than those aged <2 years. Conclusions: These findings indicated featured distributions of phenotypic and genotypic spectrum in Chinese pediatric patients, which might be helpful for early NS diagnosis.

Discrepancy between arterial oxygen saturation and pulse oximetry measurement in a Chinese pediatric patient cohort.

Background: Increasing evidence suggest a racial bias in pulse oximetry measurement, but this was under investigated in Asian pediatric populations. Methods: Via the Pediatric Intensive Care database, this retrospective study included pediatric patient records of arterial oxygen saturation (SaO2) and oxygen saturation on pulse oximetry (SpO2) measured within 10 min. Discrepancy was examined, and potential predictors of occult hypoxemia (defined as SaO2 <88% with the paired SpO2 ≥92%) as well as its association with outcomes were explored by logistic regression. Results: A total of 390 patients were included with 454 pairs of SaO2-SpO2 readings. The study population consisted of Han Chinese (99.0%) and 43.6% were female. Occult hypoxemia was observed in 20.0% of the patients, with a mean SaO2 of 71.4 ± 15.8%. Potential predictors of occult hypoxemia included female, being first admitted to cardiac ICU, congenital heart disease, increased heart rate, while patients with prior surgery records were less likely to experience occult hypoxemia. Patients with occult hypoxemia had numerically higher in-ICU mortality (16.7% versus 10.9%) and in-hospital mortality (17.9% versus 10.9%), but the associations were not statistically significant. Conclusions: There was a substantial proportion of hypoxemia that was not detected by pulse oximetry in the Chinese pediatric patients, which might be predicted by several characteristics and seemed to associate with mortality.

Radiomics models to predict bone marrow metastasis of neuroblastoma using CT.

Background: Bone marrow is the leading site for metastasis from neuroblastoma and affects the prognosis of patients with neuroblastoma. However, the accurate diagnosis of bone marrow metastasis is limited by the high spatial and temporal heterogeneity of neuroblastoma. Radiomics analysis has been applied in various cancers to build accurate diagnostic models but has not yet been applied to bone marrow metastasis of neuroblastoma. Methods: We retrospectively collected information from 187 patients pathologically diagnosed with neuroblastoma and divided them into training and validation sets in a ratio of 7:3. A total of 2632 radiomics features were retrieved from venous and arterial phases of contrast-enhanced computed tomography (CT), and nine machine learning approaches were used to build radiomics models, including multilayer perceptron (MLP), extreme gradient boosting, and random forest. We also constructed radiomics-clinical models that combined radiomics features with clinical predictors such as age, gender, ascites, and lymph gland metastasis. The performance of the models was evaluated with receiver operating characteristics (ROC) curves, calibration curves, and risk decile plots. Results: The MLP radiomics model yielded an area under the ROC curve (AUC) of 0.97 (95% confidence interval [CI]: 0.95-0.99) on the training set and 0.90 (95% CI: 0.82-0.95) on the validation set. The radiomics-clinical model using an MLP yielded an AUC of 0.93 (95% CI: 0.89-0.96) on the training set and 0.91 (95% CI: 0.85-0.97) on the validation set. Conclusions: MLP-based radiomics and radiomics-clinical models can precisely predict bone marrow metastasis in patients with neuroblastoma.

Comparative study of three cultivars of jaboticaba berry: nutrient, antioxidant and volatile compounds.

Jaboticaba is a tropical plant and its fruit rich in nutrients, volatile compounds, and biological activities, which considered to be an edible health benefits plant. Despite its popularity for fresh consumption, jaboticaba is rarely used in intensive processing in China. The content of nutrients and antioxidant in jaboticaba greatly impacts how it is processed healthy food. In this study, we evaluated the nutrients, antioxidant capacity, and volatile compounds of three jaboticaba cultivars including Sabara, Argentina, and Fukuoka, respectively. Our results revealed each variety has its merits. Sabara had an abundance of volatile compounds, a suitable acid-sugar ratio, and a slightly lower antioxidant capacity, making it suitable for fresh consumption. Argentina is the richest in volatile compounds in ripe fruit, but slightly lighter in taste and acid-sugar ratio, making it suitable for dry products. The large size, juicy flesh, low acid-sugar ratio, and less volatile compounds content of Fukuoka also make it suitable for juice processing. Three cultivars of jaboticaba berry exhibited different characteristics, providing reference evidence for the manufacturing and processing of jaboticaba health food.

Trio-pharmacophore DNA-encoded chemical library for simultaneous selection of fragments and linkers.

The split-and-pool method has been widely used to synthesize chemical libraries of a large size for early drug discovery, albeit without the possibility of meaningful quality control. In contrast, a self-assembled DNA-encoded chemical library (DEL) allows us to construct an m x n-member library by mixing an m-member and an n-member pre-purified sub-library. Herein, we report a trio-pharmacophore DEL (T-DEL) of m x l x n members through assembling three pre-purified and validated sub-libraries. The middle sub-library is synthesized using DNA-templated synthesis with different reaction mechanisms and designed as a linkage connecting the fragments displayed on the flanking two sub-libraries. Despite assembling three fragments, the resulting compounds do not exceed the up-to-date standard of molecular weight regarding drug-likeness. We demonstrate the utility of T-DEL in linker optimization for known binding fragments against trypsin and carbonic anhydrase II and by de novo selections against matrix metalloprotease-2 and -9.