A Crowdsourcing Approach to Develop Machine Learning Models to Quantify Radiographic Joint Damage in Rheumatoid Arthritis.

Importance: An automated, accurate method is needed for unbiased assessment quantifying accrual of joint space narrowing and erosions on radiographic images of the hands and wrists, and feet for clinical trials, monitoring of joint damage over time, assisting rheumatologists with treatment decisions. Such a method has the potential to be directly integrated into electronic health records. Objectives: To design and implement an international crowdsourcing competition to catalyze the development of machine learning methods to quantify radiographic damage in rheumatoid arthritis (RA). Design, Setting, and Participants: This diagnostic/prognostic study describes the Rheumatoid Arthritis 2-Dialogue for Reverse Engineering Assessment and Methods (RA2-DREAM Challenge), which used existing radiographic images and expert-curated Sharp-van der Heijde (SvH) scores from 2 clinical studies (674 radiographic sets from 562 patients) for training (367 sets), leaderboard (119 sets), and final evaluation (188 sets). Challenge participants were tasked with developing methods to automatically quantify overall damage (subchallenge 1), joint space narrowing (subchallenge 2), and erosions (subchallenge 3). The challenge was finished on June 30, 2020. Main Outcomes and Measures: Scores derived from submitted algorithms were compared with the expert-curated SvH scores, and a baseline model was created for benchmark comparison. Performances were ranked using weighted root mean square error (RMSE). The performance and reproductivity of each algorithm was assessed using Bayes factor from bootstrapped data, and further evaluated with a postchallenge independent validation data set. Results: The RA2-DREAM Challenge received a total of 173 submissions from 26 participants or teams in 7 countries for the leaderboard round, and 13 submissions were included in the final evaluation. The weighted RMSEs metric showed that the winning algorithms produced scores that were very close to the expert-curated SvH scores. Top teams included Team Shirin for subchallenge 1 (weighted RMSE, 0.44), HYL-YFG (Hongyang Li and Yuanfang Guan) subchallenge 2 (weighted RMSE, 0.38), and Gold Therapy for subchallenge 3 (weighted RMSE, 0.43). Bootstrapping/Bayes factor approach and the postchallenge independent validation confirmed the reproducibility and the estimation concordance indices between final evaluation and postchallenge independent validation data set were 0.71 for subchallenge 1, 0.78 for subchallenge 2, and 0.82 for subchallenge 3. Conclusions and Relevance: The RA2-DREAM Challenge resulted in the development of algorithms that provide feasible, quick, and accurate methods to quantify joint damage in RA. Ultimately, these methods could help research studies on RA joint damage and may be integrated into electronic health records to help clinicians serve patients better by providing timely, reliable, and quantitative information for making treatment decisions to prevent further damage.

Corrigendum: Statistical Enrichment Analysis of Samples: A General-Purpose Tool to Annotate Metadata Neighborhoods of Biological Samples.

[This corrects the article DOI: 10.3389/fdata.2021.725276.].

Statistical Enrichment Analysis of Samples: A General-Purpose Tool to Annotate Metadata Neighborhoods of Biological Samples.

Unsupervised learning techniques, such as clustering and embedding, have been increasingly popular to cluster biomedical samples from high-dimensional biomedical data. Extracting clinical data or sample meta-data shared in common among biomedical samples of a given biological condition remains a major challenge. Here, we describe a powerful analytical method called Statistical Enrichment Analysis of Samples (SEAS) for interpreting clustered or embedded sample data from omics studies. The method derives its power by focusing on sample sets, i.e., groups of biological samples that were constructed for various purposes, e.g., manual curation of samples sharing specific characteristics or automated clusters generated by embedding sample omic profiles from multi-dimensional omics space. The samples in the sample set share common clinical measurements, which we refer to as "clinotypes," such as age group, gender, treatment status, or survival days. We demonstrate how SEAS yields insights into biological data sets using glioblastoma (GBM) samples. Notably, when analyzing the combined The Cancer Genome Atlas (TCGA)-patient-derived xenograft (PDX) data, SEAS allows approximating the different clinical outcomes of radiotherapy-treated PDX samples, which has not been solved by other tools. The result shows that SEAS may support the clinical decision. The SEAS tool is publicly available as a freely available software package at https://aimed-lab.shinyapps.io/SEAS/.

First reference on reproductive biology of Butis koilomatodon in Mekong Delta, Vietnam.

BACKGROUND: The key to fishery management is knowing the appropriate reproductive strategies of the targeted fish. For most gobiid species, the iteroparous pattern is dominant compared to semelparity. Albeit Butis koilomatodon plays an important role in the Mekong Delta's food supply, its reproductive biological data have not been known. Hence, this study was conducted to provide new fundamental knowledge of reproductive traits of Butis koilomatodon in the Mekong Delta. RESULTS: A total of 1314 individuals (903 males and 411 females) were monthly collected by bottom gill nets from July 2019 to June 2020 at six sampling sites along estuarial and coastal regions, from Tra Vinh to Ca Mau provinces, southern of Vietnam. pH and salinity of these six sampling sites are 7.72-7.93 pH and 11.17-26.17‰, respectively. The pH varies with sites, but not seasons; whereas a reverse case is found in salinity. Different types of oocytes are found in histological specimens of ovaries prove that B. koilomatodon is a multi-spawner. The gonadosomatic index value, together with the monthly presence of mature ovaries reveal that this species spawns throughout the year. The length at first mature male Butis koilomatodon (5.1-8.6 cm) is higher than that of females (4.8-6.7 cm), except in Hoa Binh and Dong Hai. Batch fecundity (3085 to 32,087 eggs/female) increases with fish weight (1.48-12.30 g) and length (4.8-9.0 cm) due to high determination values (r2 > 0.6). CONCLUSION: Knowledge of reproductive traits gained from this study was a reference source for future studies and helped manage this species' resources.

Effect of Different Culture Media, Grain Sources and Alternate Substrates on the Mycelial Growth of Pleurotus eryngii and Pleurotus ostreatus.

BACKGROUND AND OBJECTIVE: Oyster mushroom Pleurotus is one of the most aromatic edible mushrooms. This study evaluated a few selected determinants for promoting mycelial growth and spawn production of P. eryngii and P. ostreatus such as culture media, grain sources and alternate substrates. MATERIALS AND METHODS: Seven different substrate formulations were evaluated, viz: TS1 (100% wheat straw-S), TS2 (100% cardboard-C), TS3 (100% spent coffee ground-SCG), TS4 (50% S+50% C), TS5 (50% S+50% SCG), TS6 (80% S+20% C) and TS7 (80% S+20% SCG). The efficiency of different culture media potato dextrose agar (PDA), yeast malt agar ( YMA) and malt extract agar (MEA) and selected grains (wheat, rye, barley and oat) was investigated. Each study was arranged in the complete randomized design with 4 replicates. RESULTS: PDA media was the most suitable for mycelial growth of P. eryngii while P. ostreatus had a better mycelial growth on YMA and MEA media. Barley and rye grains were the most favourable for the mycelium growth of P. eryngii while oat grains were the best source that enhanced both of mycelial extension and density levels of P. ostreatus. The supplement of wheat straw (S) with SCG substrate improved mycelial extension while the substrate containing 50% S+50% C was the most favourable for both of mycelial growth and primordia formation in P. eryngii and P. ostreatus. CONCLUSION: The results revealed the feasibility of using recyclable wastes of cardboards and spent coffee ground for Pleurotus mushrooms cultivation. This would alleviate accumulation of urban generated wastes thus protecting the environment.

DeCoST: A New Approach in Drug Repurposing From Control System Theory.

In this paper, we propose DeCoST (Drug Repurposing from Control System Theory) framework to apply control system paradigm for drug repurposing purpose. Drug repurposing has become one of the most active areas in pharmacology since the last decade. Compared to traditional drug development, drug repurposing may provide more systematic and significantly less expensive approaches in discovering new treatments for complex diseases. Although drug repurposing techniques rapidly evolve from "one: disease-gene-drug" to "multi: gene, dru" and from "lazy guilt-by-association" to "systematic model-based pattern matching," mathematical system and control paradigm has not been widely applied to model the system biology connectivity among drugs, genes, and diseases. In this paradigm, our DeCoST framework, which is among the earliest approaches in drug repurposing with control theory paradigm, applies biological and pharmaceutical knowledge to quantify rich connective data sources among drugs, genes, and diseases to construct disease-specific mathematical model. We use linear-quadratic regulator control technique to assess the therapeutic effect of a drug in disease-specific treatment. DeCoST framework could classify between FDA-approved drugs and rejected/withdrawn drug, which is the foundation to apply DeCoST in recommending potentially new treatment. Applying DeCoST in Breast Cancer and Bladder Cancer, we reprofiled 8 promising candidate drugs for Breast Cancer ER+ (Erbitux, Flutamide, etc.), 2 drugs for Breast Cancer ER- (Daunorubicin and Donepezil) and 10 drugs for Bladder Cancer repurposing (Zafirlukast, Tenofovir, etc.).

Simulation Study of cDNA Dataset to Investigate Possible Association of Differentially Expressed Genes of Human THP1-Monocytic Cells in Cancer Progression Affected by Bacterial Shiga Toxins.

Shiga toxin (Stxs) is a family of structurally and functionally related bacterial cytotoxins produced by Shigella dysenteriae serotype 1 and shigatoxigenic group of Escherichia coli that cause shigellosis and hemorrhagic colitis, respectively. Until recently, it has been thought that Stxs only inhibits the protein synthesis and induces expression to a limited number of genes in host cells, but recent data showed that Stxs can trigger several signaling pathways in mammalian cells and activate cell cycle and apoptosis. To explore the changes in gene expression induced by Stxs that have been shown in other systems to correlate with cancer progression, we performed the simulated analysis of cDNA dataset and found differentially expressed genes (DEGs) of human THP1-monocytic cells treated with Stxs. In this study, the entire data (treated and untreated replicates) was analyzed by statistical algorithms implemented in Bioconductor packages. The output data was validated by the k-fold cross technique using generalized linear Gaussian models. A total of 50 DEGs were identified. 7 genes including TSLP, IL6, GBP1, CD274, TNFSF13B, OASL, and PNPLA3 were considerably (<0.00005) related to cancer proliferation. The functional enrichment analysis showed 6 down-regulated and 1 up-regulated genes. Among these DEGs, IL6 was associated with several cancers, especially with leukemia, lymphoma, lungs, liver and breast cancers. The predicted regulatory motifs of these genes include conserved RELA, STATI, IRFI, NF-kappaB, PEND, HLF, REL, CEBPA, DI_2, and NFKB1 transcription factor binding sites (TFBS) involved in the complex biological functions. Thus, our findings suggest that Stxs has the potential as a valuable tool for better understanding of treatment strategies for several cancers.

HAPPI-2: a Comprehensive and High-quality Map of Human Annotated and Predicted Protein Interactions.

BACKGROUND: Human protein-protein interaction (PPI) data is essential to network and systems biology studies. PPI data can help biochemists hypothesize how proteins form complexes by binding to each other, how extracellular signals propagate through post-translational modification of de-activated signaling molecules, and how chemical reactions are coupled by enzymes involved in a complex biological process. Our capability to develop good public database resources for human PPI data has a direct impact on the quality of future research on genome biology and medicine. RESULTS: The database of Human Annotated and Predicted Protein Interactions (HAPPI) version 2.0 is a major update to the original HAPPI 1.0 database. It contains 2,922,202 unique protein-protein interactions (PPI) linked by 23,060 human proteins, making it the most comprehensive database covering human PPI data today. These PPIs contain both physical/direct interactions and high-quality functional/indirect interactions. Compared with the HAPPI 1.0 database release, HAPPI database version 2.0 (HAPPI-2) represents a 485% of human PPI data coverage increase and a 73% protein coverage increase. The revamped HAPPI web portal provides users with a friendly search, curation, and data retrieval interface, allowing them to retrieve human PPIs and available annotation information on the interaction type, interaction quality, interacting partner drug targeting data, and disease information. The updated HAPPI-2 can be freely accessed by Academic users at http://discovery.informatics.uab.edu/HAPPI . CONCLUSIONS: While the underlying data for HAPPI-2 are integrated from a diverse data sources, the new HAPPI-2 release represents a good balance between data coverage and data quality of human PPIs, making it ideally suited for network biology.

Cholinergic neurons in the mouse rostral ventrolateral medulla target sensory afferent areas.

The rostral ventrolateral medulla (RVLM) primarily regulates respiration and the autonomic nervous system. Its medial portion (mRVLM) contains many choline acetyltransferase (ChAT)-immunoreactive (ir) neurons of unknown function. We sought to clarify the role of these cholinergic cells by tracing their axonal projections. We first established that these neurons are neither parasympathetic preganglionic neurons nor motor neurons because they did not accumulate intraperitoneally administered Fluorogold. We traced their axonal projections by injecting a Cre-dependent vector (floxed-AAV2) expressing either GFP or mCherrry into the mRVLM of ChAT-Cre mice. Transduced neurons expressing GFP or mCherry were confined to the injection site and were exclusively ChAT-ir. Their axonal projections included the dorsal column nuclei, medullary trigeminal complex, cochlear nuclei, superior olivary complex and spinal cord lamina III. For control experiments, the floxed-AAV2 (mCherry) was injected into the RVLM of dopamine beta-hydroxylase-Cre mice. In these mice, mCherry was exclusively expressed by RVLM catecholaminergic neurons. Consistent with data from rats, these catecholaminergic neurons targeted brain regions involved in autonomic and endocrine regulation. These regions were almost totally different from those innervated by the intermingled mRVLM-ChAT neurons. This study emphasizes the advantages of using Cre-driver mouse strains in combination with floxed-AAV2 to trace the axonal projections of chemically defined neuronal groups. Using this technique, we revealed previously unknown projections of mRVLM-ChAT neurons and showed that despite their close proximity to the cardiorespiratory region of the RVLM, these cholinergic neurons regulate sensory afferent information selectively and presumably have little to do with respiration or circulatory control.

Fractal analysis of contours of breast masses in mammograms via the power spectra of their signatures.

Contours of benign breast masses and malignant tumors in mammograms differ substantially in their shape and complexity; the former are usually round and smooth, whereas the latter are typically spiculated and irregular. We demonstrate the usefulness of fractal analysis via a frequency domain approach applied to one-dimensional signatures of the two-dimensional contours of breast masses. The 1/ƒ model was applied to power spectra of signatures to estimate the fractal dimension. Tests with a dataset of 111 contours, including those of 65 benign masses and 46 malignant tumors, indicated a high classification performance of 0.89 in terms of the area under the receiver operating characteristic curve.

Mixing insulin aspart with detemir does not affect glucose excursion in children with type 1 diabetes.

OBJECTIVE: We hypothesized that insulin detemir mixed with aspart had equivalent effects on blood glucose as if being given as separate injections in pediatric type 1 diabetes patients. RESEARCH DESIGN AND METHODS: Fourteen children with type 1 diabetes were randomly assigned to either Study A (mixed insulins) or Study B (separate insulins) for the first 10 days and crossed over for the last 10 days. Each subject underwent continuous glucose monitoring on the last 72 h of each study. RESULTS: The 48-h area under the curve (mmol/hour/l), M-value, and mean amplitude of glucose excursion (mmol/l) for Study A versus Study B were 457 +/- 70 versus 469 +/- 112 (P = 0.58), 39.67 +/- 15.37 versus 39.75 +/- 9.69 (P = 0.98), and 6.35 +/- 1.92 versus 5.98 +/- 0.92 (P = 0.42), respectively. CONCLUSIONS: Insulin detemir mixed with aspart had equivalent effects on blood glucose versus giving them as separate injections in children with type 1 diabetes.

Effect of pixel resolution on texture features of breast masses in mammograms.

The effect of pixel resolution on texture features computed using the gray-level co-occurrence matrix (GLCM) was analyzed in the task of discriminating mammographic breast lesions as benign masses or malignant tumors. Regions in mammograms related to 111 breast masses, including 65 benign masses and 46 malignant tumors, were analyzed at pixel sizes of 50, 100, 200, 400, 600, 800, and 1,000 µm. Classification experiments using each texture feature individually provided accuracy, in terms of the area under the receiver operating characteristics curve (AUC), of up to 0.72. Using the Bayesian classifier and the leave-one-out method, the AUC obtained was in the range 0.73 to 0.75 for the pixel resolutions of 200 to 800 µm, with 14 GLCM-based texture features using adaptive ribbons of pixels around the boundaries of the masses. Texture features computed using the ribbons resulted in higher classification accuracy than the same features computed using the corresponding regions within the mass boundaries. The t test was applied to AUC values obtained using 100 repetitions of random splitting of the texture features from the ribbons of masses into the training and testing sets. The texture features computed with the pixel size of 200 µm provided the highest average AUC with statistically highly significant differences as compared to all of the other pixel sizes tested, except 100 µm.

Targeting blood glucose management in school improves glycemic control in children with poorly controlled type 1 diabetes mellitus.

We hypothesized that school nurse supervision of glucose and insulin-dose adjustment significantly improves the hemoglobinA(1c) (HbA(1c)) level in pediatric patients with poorly controlled type 1 diabetes mellitus (HbA(1c) > or = 9%). A total of 36 subjects were enrolled and 18 subjects were randomized to receive the 3-month intervention. Their average HbA(1c) was lowered by 1.6%, suggesting that this intervention helps this difficult group of patients.

Serum 1,5-anhydroglucitol (Glycomark) levels in children with and without type 1 diabetes mellitus.

Postprandial hyperglycemia associated with diabetes is a risk factor for cardiovascular disease. Currently, glycated hemoglobin A(1c) (HgbA(1c)) and glycated protein fructosamine are not sensitive markers for acute and short-term hyperglycemia. 1,5-Anhydroglucitol (1,5-AG) (Glycomark; Tomen America, New York, NY, USA) is reported in adults with type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM) as a marker for postmeal hyperglycemia. However, the reference ranges for 1,5-AG in normal children and children with T1DM are not known. We studied 1,5-AG levels in 10 control children (6 males and 4 females) and 10 children with T1DM (7 males and 3 females). The levels of 1,5-AG in the normal controls were higher than those in children with T1DM (24.60 +/- 3.99 microg/mL vs. 4.75 +/- 2.95 microg/mL; p < 0.0001). There were no gender differences noted. The 1,5-AG levels were negatively correlated with HgbA(1c) (r =-0.9366; p < 0.0001) and the peak postmeal plasma glucose concentrations (Pearson r =-7230; p = 0.0003). Our findings suggest that despite good glycemic control, postprandial glucose concentrations are elevated and that 1,5-AG showed a difference between controls and children with T1DM. The data are comparable with previous studies in normal adults and in those with T1DM and T2DM. They support the use of 1,5-AG concentrations, together with HgbA(1c), to evaluate therapy, especially to target postprandial hyperglycemia.

Fractal analysis of contours of breast masses in mammograms.

Fractal analysis has been shown to be useful in image processing for characterizing shape and gray-scale complexity. Breast masses present shape and gray-scale characteristics that vary between benign masses and malignant tumors in mammograms. Limited studies have been conducted on the application of fractal analysis specifically for classifying breast masses based on shape. The fractal dimension of the contour of a mass may be computed either directly from the 2-dimensional (2D) contour or from a 1-dimensional (1D) signature derived from the contour. We present a study of four methods to compute the fractal dimension of the contours of breast masses, including the ruler method and the box counting method applied to 1D and 2D representations of the contours. The methods were applied to a data set of 111 contours of breast masses. Receiver operating characteristics (ROC) analysis was performed to assess and compare the performance of fractal dimension and four previously developed shape factors in the classification of breast masses as benign or malignant. Fractal dimension was observed to complement the other shape factors, in particular fractional concavity, in the representation of the complexity of the contours. The combination of fractal dimension with fractional concavity yielded the highest area (A ( z )) under the ROC curve of 0.93; the two measures, on their own, resulted in A ( z ) values of 0.89 and 0.88, respectively.

Stenting of atherosclerotic stenoses in anomalously arising coronary arteries.

This description of five cases brings to 37 the total number of reported patients in whom atherosclerotic lesions of anomalously arising coronary arteries have been stented. One-half of these have been right coronary arteries arising from the left sinus of Valsalva, followed in frequency by branches of single coronary arteries arising from solitary aortic ostia and left circumflex arteries arising from the right sinus of Valsalva or from the proximal portion of the right coronary artery. Proper guide-catheter selection, essential for successful stenting, usually matches the guide's configuration to the sinus of Valsalva from which the anomalous artery originates rather than to the final distribution of the coronary artery.