Using deep neural networks and biological subwords to detect protein S-sulfenylation sites

2020 ◽  
Author(s):  
Duyen Thi Do ◽  
Thanh Quynh Trang Le ◽  
Nguyen Quoc Khanh Le
Keyword(s):  
Cell Biology ◽  
Area Under The Curve ◽  
Protein S ◽  
Cost Effective ◽  
Hydroxyl Group ◽  
Sequence Information ◽  
Post Translational Modifications ◽  
Performance Statistics ◽  
Sensitivity Specificity ◽  
Sulfenic Acids

Abstract Protein S-sulfenylation is one kind of crucial post-translational modifications (PTMs) in which the hydroxyl group covalently binds to the thiol of cysteine. Some recent studies have shown that this modification plays an important role in signaling transduction, transcriptional regulation and apoptosis. To date, the dynamic of sulfenic acids in proteins remains unclear because of its fleeting nature. Identifying S-sulfenylation sites, therefore, could be the key to decipher its mysterious structures and functions, which are important in cell biology and diseases. However, due to the lack of effective methods, scientists in this field tend to be limited in merely a handful of some wet lab techniques that are time-consuming and not cost-effective. Thus, this motivated us to develop an in silico model for detecting S-sulfenylation sites only from protein sequence information. In this study, protein sequences served as natural language sentences comprising biological subwords. The deep neural network was consequentially employed to perform classification. The performance statistics within the independent dataset including sensitivity, specificity, accuracy, Matthews correlation coefficient and area under the curve rates achieved 85.71%, 69.47%, 77.09%, 0.5554 and 0.833, respectively. Our results suggested that the proposed method (fastSulf-DNN) achieved excellent performance in predicting S-sulfenylation sites compared to other well-known tools on a benchmark dataset.

Discriminating Malignancy in Thyroid Nodules: The Nomogram Versus the Kwak and ACR TI-RADS

2020 ◽  
Vol 163 (6) ◽  
pp. 1156-1165
Author(s):  
Juan Xiao ◽  
Qiang Xiao ◽  
Wei Cong ◽  
Ting Li ◽  
Shouluan Ding ◽  
...  
Keyword(s):  
Thyroid Nodules ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Diagnostic Study ◽  
Diagnostic Efficiency ◽  
Training Set ◽  
Multivariable Logistic Regression Model ◽  
Predictive Values ◽  
Validation Set ◽  
Sensitivity Specificity

Objective To develop an easy-to-use nomogram for discrimination of malignant thyroid nodules and to compare diagnostic efficiency with the Kwak and American College of Radiology (ACR) Thyroid Imaging, Reporting and Data System (TI-RADS). Study Design Retrospective diagnostic study. Setting The Second Hospital of Shandong University. Subjects and Methods From March 2017 to April 2019, 792 patients with 1940 thyroid nodules were included into the training set; from May 2019 to December 2019, 174 patients with 389 nodules were included into the validation set. Multivariable logistic regression model was used to develop a nomogram for discriminating malignant nodules. To compare the diagnostic performance of the nomogram with the Kwak and ACR TI-RADS, the area under the receiver operating characteristic curve, sensitivity, specificity, and positive and negative predictive values were calculated. Results The nomogram consisted of 7 factors: composition, orientation, echogenicity, border, margin, extrathyroidal extension, and calcification. In the training set, for all nodules, the area under the curve (AUC) for the nomogram was 0.844, which was higher than the Kwak TI-RADS (0.826, P = .008) and the ACR TI-RADS (0.810, P < .001). For the 822 nodules >1 cm, the AUC of the nomogram was 0.891, which was higher than the Kwak TI-RADS (0.852, P < .001) and the ACR TI-RADS (0.853, P < .001). In the validation set, the AUC of the nomogram was also higher than the Kwak and ACR TI-RADS ( P < .05), each in the whole series and separately for nodules >1 or ≤1 cm. Conclusions When compared with the Kwak and ACR TI-RADS, the nomogram had a better performance in discriminating malignant thyroid nodules.

S-CCCapsule: Pneumonia detection in chest X-ray images using skip-connected convolutions and capsule neural network

2021 ◽  
pp. 1-25
Author(s):  
Kwabena Adu ◽  
Yongbin Yu ◽  
Jingye Cai ◽  
Victor Dela Tattrah ◽  
James Adu Ansere ◽  
...  
Keyword(s):  
Neural Network ◽  
Human Error ◽  
Medical Center ◽  
Confusion Matrix ◽  
Area Under The Curve ◽  
Dynamic Routing ◽  
Sigmoid Function ◽  
Radiological Society ◽  
Chest X Ray ◽  
Sensitivity Specificity

The squash function in capsule networks (CapsNets) dynamic routing is less capable of performing discrimination of non-informative capsules which leads to abnormal activation value distribution of capsules. In this paper, we propose vertical squash (VSquash) to improve the original squash by preventing the activation values of capsules in the primary capsule layer to shrink non-informative capsules, promote discriminative capsules and avoid high information sensitivity. Furthermore, a new neural network, (i) skip-connected convolutional capsule (S-CCCapsule), (ii) Integrated skip-connected convolutional capsules (ISCC) and (iii) Ensemble skip-connected convolutional capsules (ESCC) based on CapsNets are presented where the VSquash is applied in the dynamic routing. In order to achieve uniform distribution of coupling coefficient of probabilities between capsules, we use the Sigmoid function rather than Softmax function. Experiments on Guangzhou Women and Children’s Medical Center (GWCMC), Radiological Society of North America (RSNA) and Mendeley CXR Pneumonia datasets were performed to validate the effectiveness of our proposed methods. We found that our proposed methods produce better accuracy compared to other methods based on model evaluation metrics such as confusion matrix, sensitivity, specificity and Area under the curve (AUC). Our method for pneumonia detection performs better than practicing radiologists. It minimizes human error and reduces diagnosis time.

scholarly journals The Potential Diagnostic Accuracy of Circulating MicroRNAs for Leukemia: A Meta-Analysis

2021 ◽  
Vol 20 ◽  
pp. 153303382110119
Author(s):  
Wen-Ting Zhang ◽  
Guo-Xun Zhang ◽  
Shuai-Shuai Gao
Keyword(s):  
Diagnostic Accuracy ◽  
Likelihood Ratio ◽  
Subgroup Analysis ◽  
Meta Analysis ◽  
Area Under The Curve ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Diagnostic Odds Ratio ◽  
Circulating Micrornas ◽  
Sensitivity Specificity

Background: Leukemia is a common malignant disease in the human blood system. Many researchers have proposed circulating microRNAs as biomarkers for the diagnosis of leukemia. We conducted a meta-analysis to evaluate the diagnostic accuracy of circulating miRNAs in the diagnosis of leukemia. Methods: A comprehensive literature search (updated to October 13, 2020) in PubMed, EMBASE, Web of Science, Cochrane Library, Wanfang database and China National Knowledge Infrastructure (CNKI) was performed to identify eligible studies. The sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under the curve (AUC) for diagnosing leukemia were pooled for both overall and subgroup analysis. The meta-regression and subgroup analysis were performed to explore heterogeneity and Deeks’ funnel plot was used to assess publication bias. Results: 49 studies from 22 publications with a total of 3,489 leukemia patients and 2,756 healthy controls were included in this meta-analysis. The overall sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio and area under the curve were 0.83, 0.92, 10.8, 0.18, 59 and 0.94, respectively. Subgroup analysis shows that the microRNA clusters of plasma type could carry out a better diagnostic accuracy of leukemia patients. In addition, publication bias was not found. Conclusions: Circulating microRNAs can be used as a promising noninvasive biomarker in the early diagnosis of leukemia.

scholarly journals Novel Regeneration Approach for Creating Reusable FO-SPR Probes with NTA Surface Chemistry

Nanomaterials ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 186
Author(s):  
Jia-Huan Qu ◽  
Karen Leirs ◽  
Remei Escudero ◽  
Žiga Strmšek ◽  
Roman Jerala ◽  
...  
Keyword(s):  
Surface Chemistry ◽  
Fluorescent Protein ◽  
Cost Effective ◽  
Nitrilotriacetic Acid ◽  
Antibody Fragments ◽  
Rapid Screening ◽  
Red Fluorescent Protein ◽  
Effective Manner ◽  
Surface Regeneration ◽  
Sensitivity Specificity

To date, surface plasmon resonance (SPR) biosensors have been exploited in numerous different contexts while continuously pushing boundaries in terms of improved sensitivity, specificity, portability and reusability. The latter has attracted attention as a viable alternative to disposable biosensors, also offering prospects for rapid screening of biomolecules or biomolecular interactions. In this context here, we developed an approach to successfully regenerate a fiber-optic (FO)-SPR surface when utilizing cobalt (II)-nitrilotriacetic acid (NTA) surface chemistry. To achieve this, we tested multiple regeneration conditions that can disrupt the NTA chelate on a surface fully saturated with His6-tagged antibody fragments (scFv-33H1F7) over ten regeneration cycles. The best surface regeneration was obtained when combining 100 mM EDTA, 500 mM imidazole and 0.5% SDS at pH 8.0 for 1 min with shaking at 150 rpm followed by washing with 0.5 M NaOH for 3 min. The true versatility of the established approach was proven by regenerating the NTA surface for ten cycles with three other model system bioreceptors, different in their size and structure: His6-tagged SARS-CoV-2 spike fragment (receptor binding domain, RBD), a red fluorescent protein (RFP) and protein origami carrying 4 RFPs (Tet12SN-RRRR). Enabling the removal of His6-tagged bioreceptors from NTA surfaces in a fast and cost-effective manner can have broad applications, spanning from the development of biosensors and various biopharmaceutical analyses to the synthesis of novel biomaterials.

scholarly journals Predictive Evaluation on Cytological Sample of Metastatic Melanoma: The Role of BRAF Immunocytochemistry in the Molecular Era

Diagnostics ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1110
Author(s):  
Andrea Ronchi ◽  
Marco Montella ◽  
Federica Zito Marino ◽  
Michele Caraglia ◽  
Anna Grimaldi ◽  
...  
Keyword(s):  
Metastatic Melanoma ◽  
Molecular Analysis ◽  
Predictive Value ◽  
Diagnostic Performance ◽  
Cost Effective ◽  
Needle Aspiration ◽  
Braf V600e ◽  
Mutational Status ◽  
Needle Aspiration Cytology ◽  
Sensitivity Specificity

Background: Cutaneous malignant melanoma is an aggressive neoplasm. In advanced cases, the therapeutic choice depends on the mutational status of BRAF. Fine needle aspiration cytology (FNA) is often applied to the management of patients affected by melanoma, mainly for the diagnosis of metastases. The evaluation of BRAF mutational status by sequencing technique on cytological samples may be inconvenient, as it is a time and biomaterial-consuming technique. Recently, BRAF immunocytochemistry (ICC) was applied for the evaluation of BRAF V600E mutational status. Although it may be useful mainly in cytological samples, data about BRAF ICC on cytological samples are missing. Methods: We performed BRAF ICC on a series of 50 FNA samples of metastatic melanoma. BRAF molecular analysis was performed on the same cytological samples or on the corresponding histological samples. Molecular analysis was considered the gold standard. Results: BRAF ICC results were adequate in 49 out of 50 (98%) cases, positive in 15 out of 50 (30%) cases and negative in 34 out of 50 (68%) of cases. Overall, BRAF ICC sensitivity, specificity, positive predictive value and negative predictive value results were 88.2%, 100%, 100% and 94.1%, respectively. The diagnostic performance of BRAF ICC results was perfect when molecular evaluation was performed on the same cytological samples. Hyperpigmentation represents the main limitation of the technique. Conclusions: BRAF ICC is a rapid, cost-effective method for detecting BRAF V600E mutation in melanoma metastases, applicable with high diagnostic performance to cytological samples. It could represent the first step to evaluate BRAF mutational status in cytological samples, mainly in poorly cellular cases.

scholarly journals Comparison of saliva with healthcare workers- and patient-collected swabs in the diagnosis of COVID-19 in a large cohort

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Mitnala Sasikala ◽  
Yelamanchili Sadhana ◽  
Ketavarapu Vijayasarathy ◽  
Anand Gupta ◽  
Sarala Kumari Daram ◽  
...  
Keyword(s):  
Healthcare Workers ◽  
Early Stage ◽  
Cost Effective ◽  
Hospitalized Patients ◽  
Detection Sensitivity ◽  
Nasopharyngeal Swab ◽  
Predictive Values ◽  
Qrt Pcr ◽  
Asymptomatic Patients ◽  
Sensitivity Specificity

Abstract Background A considerable amount of evidence demonstrates the potential of saliva in the diagnosis of COVID-19. Our aim was to determine the sensitivity of saliva versus swabs collected by healthcare workers (HCWs) and patients themselves to assess whether saliva detection can be offered as a cost-effective, risk-free method of SARS-CoV-2 detection. Methods This study was conducted in a hospital involving outpatients and hospitalized patients. A total of 3018 outpatients were tested. Of these, 200 qRT-PCR-confirmed SARS-CoV-2-positive patients were recruited for further study. In addition, 101 SARS-CoV-2-positive hospitalized patients with symptoms were also enrolled in the study. From outpatients, HCWs collected nasopharyngeal swabs (NPS), saliva were obtained. From inpatients, HCWs collected swabs, patient-collected swabs, and saliva were obtained. qRT-PCR was performed to detect SARS-CoV-2 by TAQPATH assay to determine the sensitivity of saliva detection. Sensitivity, specificity and positive/negative predictive values (PPV, NPV) of detecting SARS-CoV-2 were calculated using MedCalc. Results Of 3018 outpatients (asymptomatic: 2683, symptomatic: 335) tested by qRT-PCR, 200 were positive (males: 140, females: 60; aged 37.9 ± 12.8 years; (81 asymptomatic, 119 symptomatic). Of these, saliva was positive in 128 (64%); 39 of 81 asymptomatic (47%),89 of 119 symptomatic patients (74.8%). Sensitivity of detection was 60.9% (55.4–66.3%, CI 95%), with a negative predictive value of 36%(32.9–39.2%, CI 95%).Among 101 hospitalized patients (males:65, females: 36; aged 53.48 ± 15.6 years), with HCW collected NPS as comparator, sensitivity of saliva was 56.1% (47.5–64.5, CI 95%), specificity 63.5%(50.4–75.3, CI95%) with PPV of 77.2% and NPV of 39.6% and that of self-swab was 52.3%(44–60.5%, CI95%), specificity 56.6% (42.3–70.2%, CI95%) with PPV 77.2% and NPV29.7%. Comparison of positivity with the onset of symptoms revealed highest detection in saliva on day 3 after onset of symptoms. Additionally, only saliva was positive in 13 (12.8%) hospitalized patients. Conclusion Saliva which is easier to collect than nasopharyngeal swab is a viable alternate to detect SARS-COV-2 in symptomatic patients in the early stage of onset of symptoms. Although saliva is currently not recommended for screening asymptomatic patients, optimization of collection and uniform timing of sampling might improve the sensitivity enabling its use as a screening tool at community level.

Clot imaging characteristics predict first pass effect of aspiration—first approach to thrombectomy

2021 ◽  
pp. 159101992110191
Author(s):  
Muhammad Waqas ◽  
Weizhe Li ◽  
Tatsat R Patel ◽  
Felix Chin ◽  
Vincent M Tutino ◽  
...  
Keyword(s):  
Internal Carotid ◽  
Validation Cohort ◽  
Area Under The Curve ◽  
Large Vessel Occlusion ◽  
Vessel Occlusion ◽  
First Pass Effect ◽  
Imaging Characteristics ◽  
First Pass ◽  
Sensitivity Specificity ◽  
Youden’S Index

Background The value of clot imaging in patients with emergent large vessel occlusion (ELVO) treated with thrombectomy is unknown. Methods We performed retrospective analysis of clot imaging (clot density, perviousness, length, diameter, distance to the internal carotid artery (ICA) terminus and angle of interaction (AOI) between clot and the aspiration catheter) of consecutive cases of middle cerebral artery (MCA) occlusion and its association with first pass effect (FPE, TICI 2c-3 after a first attempt). Results Patients ( n = 90 total) with FPE had shorter clot length (9.9 ± 4.5 mm vs. 11.7 ± 4.6 mm, P = 0.07), shorter distance from ICA terminus (11.0 ± 7.1 mm vs. 14.7 ± 9.8 mm, P = 0.048), higher perviousness (39.39 ± 29.5 vs 25.43 ± 17.6, P = 0.006) and larger AOI (153.6 ± 17.6 vs 140.3 ± 23.5, P = 0.004) compared to no-FPE patients. In multivariate analysis, distance from ICA terminus to clot ≤13.5 mm (odds ratio (OR) 11.05, 95% confidence interval (CI) 2.65–46.15, P = 0.001), clot length ≤9.9 mm (OR 7.34; 95% CI 1.8–29.96, P = 0.005), perviousness ≥ 19.9 (OR 2.54, 95% CI 0.84–7.6, P = 0.09) and AOI ≥ 137°^ (OR 6.8, 95% CI 1.55–29.8, P = 0.011) were independent predictors of FPE. The optimal cut off derived using Youden’s index was 6.5. The area under the curve of a score predictive of FPE success was 0.816 (0.728–0.904, P < 0.001). In a validation cohort ( n = 30), sensitivity, specificity, positive and negative predictive value of a score of 6–10 were 72.7%, 73.6%, 61.5% and 82.3%. Conclusions Clot imaging predicts the likelihood of achieving FPE in patients with MCA ELVO treated with the aspiration-first approach.

scholarly journals Evaluation of alpha-l-fucosidase for the diagnosis of hepatocellular carcinoma based on meta-analysis

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Lei Xi ◽  
Chunqing Yang
Keyword(s):  
Hepatocellular Carcinoma ◽  
Operating Characteristic ◽  
Meta Analysis ◽  
Area Under The Curve ◽  
Diagnostic Odds Ratio ◽  
Diagnostic Value ◽  
Receiver Operating Characteristic Curves ◽  
Sensitivity Specificity ◽  
Review Manager

AbstractObjectivesThe main aim of the present study was to assess the diagnostic value of alpha-l-fucosidase (AFU) for hepatocellular carcinoma (HCC).MethodsStudies that explored the diagnostic value of AFU in HCC were searched in EMBASE, SCI, and PUBMED. The sensitivity, specificity, and DOR about the accuracy of serum AFU in the diagnosis of HCC were pooled. The methodological quality of each article was evaluated with QUADAS-2 (quality assessment for studies of diagnostic accuracy 2). Receiver operating characteristic curves (ROC) analysis was performed. Statistical analysis was conducted by using Review Manager 5 and Open Meta-analyst.ResultsEighteen studies were selected in this study. The pooled estimates for AFU vs. α-fetoprotein (AFP) in the diagnosis of HCC in 18 studies were as follows: sensitivity of 0.7352 (0.6827, 0.7818) vs. 0.7501 (0.6725, 0.8144), and specificity of 0.7681 (0.6946, 0.8283) vs. 0.8208 (0.7586, 0.8697), diagnostic odds ratio (DOR) of 7.974(5.302, 11.993) vs. 13.401 (8.359, 21.483), area under the curve (AUC) of 0.7968 vs. 0.8451, respectively.ConclusionsAFU is comparable to AFP for the diagnosis of HCC.

Doing More With Less: Pragmatic Implementation of Vancomycin Area-Under-the-Curve (AUC) Monitoring

2021 ◽  
pp. 089719002110272
Author(s):  
Joanne Huang ◽  
Jeannie D. Chan ◽  
Thu Nguyen ◽  
Rupali Jain ◽  
Zahra Kassamali Escobar
Keyword(s):  
Quality Improvement ◽  
High Risk ◽  
Therapeutic Drug Monitoring ◽  
Paradigm Shift ◽  
Area Under The Curve ◽  
Cost Effective ◽  
Practical Method ◽  
Therapeutic Drug ◽  
Short Term ◽  
Quality Improvement Process

Universal area-under-the-curve (AUC) guided vancomycin therapeutic drug monitoring (TDM) is resource-intensive, cost-prohibitive, and presents a paradigm shift that leaves institutions with the quandary of defining the preferred and most practical method for TDM. We report a step-by-step quality improvement process using 4 plan-do-study-act (PDSA) cycles to provide a framework for development of a hybrid model of trough and AUC-based vancomycin monitoring. We found trough-based monitoring a pragmatic strategy as a first-tier approach when anticipated use is short-term. AUC-guided monitoring was most impactful and cost-effective when reserved for patients with high-risk for nephrotoxicity. We encourage others to consider quality improvement tools to locally adopt AUC-based monitoring.

scholarly journals New screening approach to detecting congenital syphilis in China: a retrospective cohort study

2020 ◽  
pp. archdischild-2020-320549
Author(s):  
Fang Hu ◽  
Shuai-Jun Guo ◽  
Jian-Jun Lu ◽  
Ning-Xuan Hua ◽  
Yan-Yan Song ◽  
...  
Keyword(s):  
Predictive Value ◽  
Congenital Syphilis ◽  
Area Under The Curve ◽  
Diagnostic Tools ◽  
Operating Characteristics ◽  
Loss To Follow Up ◽  
Sensitivity Specificity ◽  
Mother To Child ◽  
Rule Out

BackgroundDiagnosis of congenital syphilis (CS) is not straightforward and can be challenging. This study aimed to evaluate the validity of an algorithm using timing of maternal antisyphilis treatment and titres of non-treponemal antibody as predictors of CS.MethodsConfirmed CS cases and those where CS was excluded were obtained from the Guangzhou Prevention of Mother-to-Child Transmission of syphilis programme between 2011 and 2019. We calculated sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) using receiver operating characteristics (ROC) in two situations: (1) receiving antisyphilis treatment or no-treatment during pregnancy and (2) initiating treatment before 28 gestational weeks (GWs), initiating after 28 GWs or receiving no treatment for syphilis seropositive women.ResultsAmong 1558 syphilis-exposed children, 39 had confirmed CS. Area under the curve, sensitivity and specificity of maternal non-treponemal titres before treatment and treatment during pregnancy were 0.80, 76.9%, 78.7% and 0.79, 69.2%, 88.7%, respectively, for children with CS. For the algorithm, ROC results showed that PPV and NPV for predicting CS were 37.3% and 96.4% (non-treponemal titres cut-off value 1:8 and no antisyphilis treatment), 9.4% and 100% (non-treponemal titres cut-off value 1:16 and treatment after 28 GWs), 4.2% and 99.5% (non-treponemal titres cut-off value 1:32 and treatment before 28 GWs), respectively.ConclusionsAn algorithm using maternal non-treponemal titres and timing of treatment during pregnancy could be an effective strategy to diagnose or rule out CS, especially when the rate of loss to follow-up is high or there are no straightforward diagnostic tools.

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