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Programmed cell death ligand 1 (PD‐L1), inducing T cell exhaustion to facilitate immune escape of tumor cells, is upregulated by interleukin 6 (IL‐6) in T cell lymphoma and ovarian cancer. The purpose of this study is to investigate the expression of IL‐6 and PD‐L1 in thyroid cancer, and whether IL‐6 regulates PD‐L1 expression. As a result, IL‐6 and PD‐L1 were highly expressed in thyroid cancer tissues. Multivariate logistic analysis showed that tumor size, distant metastasis, and risk stratification were significantly associated with IL‐6 expression (P, IL‐6 and PD‐L1 are highly expressed in thyroid cancer and correlate with disease aggressiveness. IL‐6 activates the MAPK and JAK‐STAT3 signaling pathways in thyroid cancer. In addition, IL‐6 promotes PD‐L1 transcription through the MAPK and JAK‐STAT3 signaling pathways, which function via transcription factors c‐Jun and stat3.

Background Pressure injuries (PrI) are serious complications for many with spinal cord injury (SCI), significantly burdening health care systems, in particular the Veterans Health Administration. Clinical practice guidelines (CPG) provide recommendations. However, many risk factors span multiple domains. Effective prioritization of CPG recommendations has been identified as a need. Bioinformatics facilitates clinical decision support for complex challenges. The Veteran’s Administration Informatics and Computing Infrastructure provides access to electronic health record (EHR) data for all Veterans Health Administration health care encounters. The overall study objective was to expand our prototype structural model of environmental, social, and clinical factors and develop the foundation for resource which will provide weighted systemic insight into PrI risk in veterans with SCI. Methods The SCI PrI Resource (SCI-PIR) includes three integrated modules: (1) the SCIPUDSphere multidomain database of veterans’ EHR data extracted from October 2010 to September 2015 for ICD-9-CM coding consistency together with tissue health profiles, (2) the Spinal Cord Injury Pressure Ulcer and Deep Tissue Injury Ontology (SCIPUDO) developed from the cohort’s free text clinical note (Text Integration Utility) notes, and (3) the clinical user interface for direct SCI-PIR query. Results The SCI-PIR contains relevant EHR data for a study cohort of 36,626 veterans with SCI, representing 10% to 14% of the U.S. population with SCI. Extracted datasets include SCI diagnostics, demographics, comorbidities, rurality, medications, and laboratory tests. Many terminology variations for non-coded input data were found. SCIPUDO facilitates robust information extraction from over six million Text Integration Utility notes annually for the study cohort. Visual widgets in the clinical user interface can be directly populated with SCIPUDO terms, allowing patient-specific query construction. Conclusion The SCI-PIR contains valuable clinical data based on CPG-identified risk factors, providing a basis for personalized PrI risk management following SCI. Understanding the relative impact of risk factors supports PrI management for veterans with SCI. Personalized interactive programs can enhance best practices by decreasing both initial PrI formation and readmission rates due to PrI recurrence for veterans with SCI.

ObjectiveTo analyze the association between peri-ictal brainstem posturing semiologies with postictal generalized electroencephalographic suppression (PGES) and breathing dysfunction in generalized convulsive seizures (GCS).MethodsIn this prospective, multicenter analysis of GCS, ictal brainstem semiology was classified as (1) decerebration (bilateral symmetric tonic arm extension), (2) decortication (bilateral symmetric tonic arm flexion only), (3) hemi-decerebration (unilateral tonic arm extension with contralateral flexion) and (4) absence of ictal tonic phase. Postictal posturing was also assessed. Respiration was monitored with thoracoabdominal belts, video, and pulse oximetry.ResultsTwo hundred ninety-five seizures (180 patients) were analyzed. Ictal decerebration was observed in 122 of 295 (41.4%), decortication in 47 of 295 (15.9%), and hemi-decerebration in 28 of 295 (9.5%) seizures. Tonic phase was absent in 98 of 295 (33.2%) seizures. Postictal posturing occurred in 18 of 295 (6.1%) seizures. PGES risk increased with ictal decerebration (odds ratio [OR] 14.79, 95% confidence interval [CI] 6.18–35.39,p< 0.001), decortication (OR 11.26, 95% CI 2.96–42.93,p< 0.001), or hemi-decerebration (OR 48.56, 95% CI 6.07–388.78,p< 0.001). Ictal decerebration was associated with longer PGES (p= 0.011). Postictal posturing was associated with postconvulsive central apnea (PCCA) (p= 0.004), longer hypoxemia (p< 0.001), and Spo2recovery (p= 0.035).ConclusionsIctal brainstem semiology is associated with increased PGES risk. Ictal decerebration is associated with longer PGES. Postictal posturing is associated with a 6-fold increased risk of PCCA, longer hypoxemia, and Spo2recovery. Peri-ictal brainstem posturing may be a surrogate biomarker for GCS severity identifiable without in-hospital monitoring.Classification of EvidenceThis study provides Class III evidence that peri-ictal brainstem posturing is associated with the GCS with more prolonged PGES and more severe breathing dysfunction.

BackgroundSudden unexpected death in epilepsy (SUDEP) is a leading cause of premature death in patients with epilepsy. If timely assessment of SUDEP risk can be made, early interventions for optimized treatments might be provided. One of the biomarkers being investigated for SUDEP risk assessment is postictal generalized EEG suppression [postictal generalized EEG suppression (PGES)]. For example, prolonged PGES has been found to be associated with a higher risk for SUDEP. Accurate characterization of PGES requires correct identification of the end of PGES, which is often complicated due to signal noise and artifacts, and has been reported to be a difficult task even for trained clinical professionals. In this work we present a method for automatic detection of the end of PGES using multi-channel EEG recordings, thus enabling the downstream task of SUDEP risk assessment by PGES characterization.MethodsWe address the detection of the end of PGES as a classification problem. Given a short EEG snippet, a trained model classifies whether it consists of the end of PGES or not. Scalp EEG recordings from a total of 134 patients with epilepsy are used for training a random forest based classification model. Various time-series based features are used to characterize the EEG signal for the classification task. The features that we have used are computationally inexpensive, making it suitable for real-time implementations and low-power solutions. The reference labels for classification are based on annotations by trained clinicians identifying the end of PGES in an EEG recording.ResultsWe evaluated our classification model on an independent test dataset from 34 epileptic patients and obtained an AUreceiver operating characteristic (ROC) (area under the curve) of 0.84. We found that inclusion of multiple EEG channels is important for better classification results, possibly owing to the generalized nature of PGES. Of among the channels included in our analysis, the central EEG channels were found to provide the best discriminative representation for the detection of the end of PGES.ConclusionAccurate detection of the end of PGES is important for PGES characterization and SUDEP risk assessment. In this work, we showed that it is feasible to automatically detect the end of PGES—otherwise difficult to detect due to EEG noise and artifacts—using time-series features derived from multi-channel EEG recordings. In future work, we will explore deep learning based models for improved detection and investigate the downstream task of PGES characterization for SUDEP risk assessment.

Fine particulate matter (PM2.5) is the primary air pollutant that is able to induce airway injury. Compelling evidence has shown the involvement of IL‐17A in lung injury, while its contribution to PM2.5‐induced lung injury remains largely unknown. Here, we probed into the possible role of IL‐17A in mouse models of PM2.5‐induced lung injury. Mice were instilled with PM2.5 to construct a lung injury model. Flow cytometry was carried out to isolate γδT and Th17 cells. ELISA was adopted to detect the expression of inflammatory factors in the supernatant of lavage fluid. Primary bronchial epithelial cells (mBECs) were extracted, and the expression of TGF signalling pathway‐, autophagy‐ and PI3K/Akt/mTOR signalling pathway‐related proteins in mBECs was detected by immunofluorescence assay and Western blot analysis. The mitochondrial function was also evaluated. PM2.5 aggravated the inflammatory response through enhancing the secretion of IL‐17A by γδT/Th17 cells. Meanwhile, PM2.5 activated the TGF signalling pathway and induced EMT progression in bronchial epithelial cells, thereby contributing to pulmonary fibrosis. Besides, PM2.5 suppressed autophagy of bronchial epithelial cells by up‐regulating IL‐17A, which in turn activated the PI3K/Akt/mTOR signalling pathway. Furthermore, IL‐17A impaired the energy metabolism of airway epithelial cells in the PM2.5‐induced models. This study suggested that PM2.5 could inhibit autophagy of bronchial epithelial cells and promote pulmonary inflammation and fibrosis by inducing the secretion of IL‐17A in γδT and Th17 cells and regulating the PI3K/Akt/mTOR signalling pathway.

Distant metastases are rarely observed in patients with initial pathologically proven benign follicular nodules of the thyroid. This study aimed to evaluate the clinicopathological features and independent variables associated with survival in such patients with distant metastases. In total, 10,992 consecutive differentiated thyroid cancer (DTC) patients treated with 131I after total or near-total thyroidectomy from 2000 to 2018 were retrospectively reviewed. Thirty-nine patients with initial pathologically proven benign follicular nodules of the thyroid were enrolled. Among them, 26 were pathologically diagnosed as thyroid adenoma, 8 as benign nodular goiter, 4 as thyroid adenoma combined with benign nodular goiter, and 1 as normal thyroid tissue. Of 26 patients with the initial pathological slides obtained, eight cases were rediagnosed as minimally invasive thyroid carcinoma (MI-FTC), 10 as follicular tumor of uncertain malignant potential (FT-UMP), and five as well-differentiated tumor of UMP (WDT-UMP). Monitoring of thyroglobulin (Tg) changes after initial thyroidectomy and preablation-stimulated Tg (psTg) level were significantly associated with 5-year OS rate (P = 0.007 and P = 0.005, respectively). The presence of radioactive-refractory DTC (RR-DTC), monitoring of Tg changes after initial thyroidectomy, and psTg level had significant effects on 10-year OS rate (P = 0.002, P

Background There remains uncertainty about the impact of menopausal hormone therapy (MHT) on women’s health. A systematic, comprehensive assessment of the effects on multiple outcomes is lacking. We conducted an umbrella review to comprehensively summarize evidence on the benefits and harms of MHT across diverse health outcomes. Methods and findings We searched MEDLINE, EMBASE, and 10 other databases from inception to November 26, 2017, updated on December 17, 2020, to identify systematic reviews or meta-analyses of randomized controlled trials (RCTs) and observational studies investigating effects of MHT, including estrogen-alone therapy (ET) and estrogen plus progestin therapy (EPT), in perimenopausal or postmenopausal women in all countries and settings. All health outcomes in previous systematic reviews were included, including menopausal symptoms, surrogate endpoints, biomarkers, various morbidity outcomes, and mortality. Two investigators independently extracted data and assessed methodological quality of systematic reviews using the updated 16-item AMSTAR 2 instrument. Random-effects robust variance estimation was used to combine effect estimates, and 95% prediction intervals (PIs) were calculated whenever possible. We used the term MHT to encompass ET and EPT, and results are presented for MHT for each outcome, unless otherwise indicated. Sixty systematic reviews were included, involving 102 meta-analyses of RCTs and 38 of observational studies, with 102 unique outcomes. The overall quality of included systematic reviews was moderate to poor. In meta-analyses of RCTs, MHT was beneficial for vasomotor symptoms (frequency: 9 trials, 1,104 women, risk ratio [RR] 0.43, 95% CI 0.33 to 0.57, p < 0.001; severity: 7 trials, 503 women, RR 0.29, 95% CI 0.17 to 0.50, p = 0.002) and all fracture (30 trials, 43,188 women, RR 0.72, 95% CI 0.62 to 0.84, p = 0.002, 95% PI 0.58 to 0.87), as well as vaginal atrophy (intravaginal ET), sexual function, vertebral and nonvertebral fracture, diabetes mellitus, cardiovascular mortality (ET), and colorectal cancer (EPT), but harmful for stroke (17 trials, 37,272 women, RR 1.17, 95% CI 1.05 to 1.29, p = 0.027) and venous thromboembolism (23 trials, 42,292 women, RR 1.60, 95% CI 0.99 to 2.58, p = 0.052, 95% PI 1.03 to 2.99), as well as cardiovascular disease incidence and recurrence, cerebrovascular disease, nonfatal stroke, deep vein thrombosis, gallbladder disease requiring surgery, and lung cancer mortality (EPT). In meta-analyses of observational studies, MHT was associated with decreased risks of cataract, glioma, and esophageal, gastric, and colorectal cancer, but increased risks of pulmonary embolism, cholelithiasis, asthma, meningioma, and thyroid, breast, and ovarian cancer. ET and EPT had opposite effects for endometrial cancer, endometrial hyperplasia, and Alzheimer disease. The major limitations include the inability to address the varying effects of MHT by type, dose, formulation, duration of use, route of administration, and age of initiation and to take into account the quality of individual studies included in the systematic reviews. The study protocol is publicly available on PROSPERO (CRD42017083412). Conclusions MHT has a complex balance of benefits and harms on multiple health outcomes. Some effects differ qualitatively between ET and EPT. The quality of available evidence is only moderate to poor., In an umbrella review, Guo-Qiang Zhang and colleagues comprehensively summarize evidence on the benefits and harms of menopausal hormone therapy across diverse health outcomes., Author summary Why was this study done? By 2050, it is estimated that worldwide more than 1.6 billion women will have reached menopause or be postmenopausal, up from 1 billion in 2020. Up to 75% of menopausal women are affected by bothersome menopausal symptoms, such as hot flashes and night sweats. Menopausal hormone therapy (MHT) is the most effective treatment for alleviating menopausal symptoms, but its effects on numerous health outcomes remain uncertain. What did the researchers do and find? We included 60 published systematic reviews of MHT use in menopausal women, involving 102 meta-analyses of randomized controlled trials and 38 of observational studies, and synthesized the evidence on 102 health outcomes. Overall, MHT had a complex balance of benefits and harms; for example, beyond alleviation of menopausal symptoms, it was associated with decreased risks of bone fracture, diabetes mellitus, and esophageal, gastric, and colorectal cancer, but increased risks of stroke, venous thromboembolism, gallbladder disease, and breast and ovarian cancer. The available clinical data in support of MHT reducing the risk of coronary heart disease and all-cause mortality in women aged

Aim: To investigate the effect of cod skin oligopeptide (CSO), a natural hydrolysis product obtained from Pacific cod skin gelatin, on the growth of human gastric cancer cells.Methods: Morphological changes were observed in CSO-treated BGC-823 cells under a microscope. The viability of BGC-823 cells was examined by cell counting kit-8 assay. The efficacy of CSO in vivo was evaluated using a xenograft tumor model. Apoptotic cells were identified by flow cytometry. Pro-apoptotic protein expression was verified by western blotting.Results: CSO significantly inhibited BGC-823 cell growth in a dose- and time-dependent manner in vitro and also inhibited the growth of murine gastric cancer xenografts. Flow cytometric assays showed that treatment of BGC-823 cells with CSO significantly increased the percentage of apoptotic cells. Mechanistically, CSO effectively induced expression of pro-apoptotic cleaved caspase-3 and cleaved caspase-9 and down-regulated anti-apoptotic Bcl-2.Conclusion: CSO inhibits gastric cancer cell proliferation while inducing apoptosis by modifying the expression of pro-apoptotic proteins, suggesting a potential therapeutic role for CSO in gastric cancer treatment.

Background The role of atopy patch test (APT) in the diagnosis of food allergy (FA) remains largely controversial. In our meta-analysis, we aimed to evaluate the accuracy of APT for diagnosing FA in children. Methods Pubmed, Embase and Cochrane Library were searched for studies regarding the diagnostic value of APT for FA in children compared to oral food challenge (double-blind placebo-controlled food challenge and/or open food challenge). The last search was conducted on November 11, 2017. Two reviewers independently screened relevant studies and assessed the quality by QUADAS-2. Meta-analysis was performed to calculate the pooled sensitivity, specificity, DOR (diagnostic odds ratio), PLR (positive likelihood ratio), NLR (negative likelihood ratio) with their 95% confidence intervals (CIs). Subgroup analyses were conducted according to different food allergens, atopic dermatitis, gastrointestinal symptoms, and age younger than 3 years. Results Forty-one studies were included in the meta-analysis. The pooled sensitivity, specificity, PLR, NLR and DOR were 50.30% (95% CI 48.40%-52.30%), 86.60% (95% CI 85.30%-87.80%), 3.405 (95% CI 2.594-4.470), 0.545 (95% CI 0.469-0.634) and 7.528 (95% CI 5.507-11.206), respectively. However, for children with FA-related gastrointestinal symptoms, the pooled sensitivity and specificity were 57.40% (95% CI 52.10%-62.50%) and 91.50% (95% CI 88.30%-94.10%) respectively. Conclusions Our findings suggest that APT is specific but not sensitive for diagnosing FA in children, especially in children with FA-related gastrointestinal symptoms.

Programmed cell death-ligand 1 (PD-L1) expression on tumor tissue has been associated with favorable response to anti-programmed cell death-receptor 1/PD-L1 therapy in many human cancers. Studies have reported that PD-L1 is also expressed in thyroid cancer. The objective of this paper is to introduce the potential predictive and therapeutic values of PD-L1 in thyroid cancer.A literature search was conducted in the PubMed database using the terms "PD-L1," "B7-H1," and "thyroid cancer." PD-L1 positivity was determined by immunohistochemical assay.The frequency of PD-L1 positivity in different studies ranged from 6.1 to 82.5% in papillary thyroid cancer (PTC) patients and 22.2 to 81.2% in anaplastic thyroid cancer (ATC) patients. PD-L1 positivity rate was higher in ATC than in PTC within the same studies, and its expression intensity was significantly higher in tumor tissue than in the corresponding nontumor thyroid tissues. Moreover, PD-L1 expression was positively associated with the aggressiveness and recurrence of thyroid cancers and negatively associated with the differentiation status and outcomes. PD-L1 checkpoint pathway blockade may emerge as a promising therapeutic target in the treatment of thyroid cancers.PD-L1 is a potential biomarker to predict the recurrence and prognosis of thyroid cancers. It is also a novel immunotherapy target for optimizing the management landscape of radioiodine-refractory and ATCs.ATC = anaplastic thyroid cancer; DTC = differentiated thyroid cancer; IHC = immunohistochemical; OS = overall survival; PD-1 = programmed cell death-receptor 1; PD-L1 = programmed cell death-ligand 1; PD-L2 = programmed cell death-ligand 2; PTC = papillary thyroid cancer; TNM = tumor-node-metastasis; Treg = regulatory T cell.

ObjectiveThis study aimed to assess the morphology of the femoral medullary canal in subjects with developmental dysplasia of the hip (DDH) with the intent of improving the design of femoral stems in total hip arthroplasty.MethodsComputed tomography images of 56 DDH hips, which were classified into Crowe I to Crowe IV, and 30 normal hips were collected and used to reconstruct three-dimensional morphology of the femoral medullary cavity. Images of twenty-one cross sections were taken from 20 mm above the apex of the lesser trochanter to the isthmus. The morphology of femoral cavity was evaluated on each cross section for the longest canal diameter, the femoral medullary torsion angle (FMTA), and the femoral medullary roundness index (FMRI).ResultsThe Crowe IV group displayed the narrowest medullary canal in the region superior to the end of the lesser trochanter, but then gradually aligned with the medullary diameter of the other groups down to the isthmus. The FMTA along the femoral cavity increased with the severity of DDH, but the rate of variation of FMTA along the femoral canal was consistent in the DDH groups. The DDH hips generally showed a larger FMRI than the normal hips, indicating more elliptical shapes.ConclusionA femoral stem with a cone shape in the proximal femur and a cylindrical shape for the remainder down to the isthmus may benefit the subjects with severe DDH. This design could protect bone, recover excessive femoral anteversion and facilitate the implantation in the narrow medullary canal.

Rationale: Currently, there is some ambiguity over the role of postictal generalized electro-encephalographic suppression (PGES) as a biomarker in sudden unexpected death in epilepsy (SUDEP). Visual analysis of PGES, known to be subjective, may account for this. In this study, we set out to perform an analysis of PGES presence and duration using a validated signal processing tool, specifically to examine the association between PGES and seizure features previously reported to be associated with visually analyzed PGES.Methods: This is a prospective, multicenter epilepsy monitoring study of autonomic and breathing biomarkers of SUDEP in adult patients with intractable epilepsy. We studied videoelectroencephalogram (vEEG) recordings of generalized convulsive seizures (GCS) in a cohort of patients in whom respiratory and vEEG recording were carried out during the evaluation in the epilepsy monitoring unit. A validated automated EEG suppression detection tool was used to determine presence and duration of PGES.Results: We studied 148 GCS in 87 patients. PGES occurred in 106/148 (71.6%) seizures in 70/87 (80.5%) of patients. PGES mean duration was 38.7 ± 23.7 (37; 1–169) seconds. Presence of tonic phase during GCS, including decerebration, decortication and hemi-decerebration, were 8.29 (CI 2.6–26.39, p = 0.0003), 7.17 (CI 1.29–39.76, p = 0.02), and 4.77 (CI 1.25–18.20, p = 0.02) times more likely to have PGES, respectively. In addition, presence of decerebration (p = 0.004) and decortication (p = 0.02), older age (p = 0.009), and hypoxemia duration (p = 0.03) were associated with longer PGES durations.Conclusions: In this study, we confirmed observations made with visual analysis, that presence of tonic phase during GCS, longer hypoxemia, and older age are reliably associated with PGES. We found that of the different types of tonic phase posturing, decerebration has the strongest association with PGES, followed by decortication, followed by hemi-decerebration. This suggests that these factors are likely indicative of seizure severity and may or may not be associated with SUDEP. An automated signal processing tool enables objective metrics, and may resolve apparent ambiguities in the role of PGES in SUDEP and seizure severity studies.

The availability of large healthcare datasets offers the opportunity for researchers to navigate the traditional clinical and translational science research stages in a nonlinear manner. In particular, data scientists can harness the power of large healthcare datasets to bridge from preclinical discoveries (T0) directly to assessing population-level health impact (T4). A successful bridge from T0 to T4 does not bypass the other stages entirely; rather, effective team science makes a direct progression from T0 to T4 impactful by incorporating the perspectives of researchers from every stage of the clinical and translational science research spectrum. In this exemplar, we demonstrate how effective team science overcame challenges and, ultimately, ensured success when a diverse team of researchers worked together, using healthcare big data to test population-level substance use disorder (SUD) hypotheses generated from preclinical rodent studies. This project, called Advancing Substance use disorder Knowledge using Big Data (ASK Big Data), highlights the critical roles that data science expertise and effective team science play in quickly translating preclinical research into public health impact.

Background: Coronavirus disease 2019 (COVID-19) has been associated with coagulopathy, and D-dimer levels have been used to predict disease severity. However, the role of D-dimer in predicting mortality in COVID-19 patients with acute ischemic stroke (AIS) remains incompletely characterized.Methods: We conducted a retrospective cohort study using the Optum® de-identified COVID-19 Electronic Health Record dataset. Patients were included if they were 18 or older, had been hospitalized within 7 days of confirmed COVID-19 positivity from March 1, 2020 to November 30, 2020. We determined the optimal threshold of D-dimer to predict in-hospital mortality and compared risks of in-hospital mortality between patients with D-dimer levels below and above the cutoff. Risk ratios (RRs) were estimated adjusting for baseline characteristics and clinical variables.Results: Among 15,250 patients hospitalized with COVID-19 positivity, 285 presented with AIS at admission (2%). Patients with AIS were older [70 (60–79) vs. 64 (52–75), p < 0.001] and had greater D-dimer levels at admission [1.42 (0.76–3.96) vs. 0.94 (0.55–1.81) μg/ml FEU, p < 0.001]. Peak D-dimer level was a good predictor of in-hospital mortality among all patients [c-statistic 0.774 (95% CI 0.764–0.784)] and among patients with AIS [c-statistic 0.751 (95% CI 0.691–0.810)]. Among AIS patients, the optimum cutoff was identified at 5.15 μg/ml FEU with 73% sensitivity and 69% specificity. Elevated peak D-dimer level above this cut-off was associated with almost 3 times increased mortality [adjusted RR 2.89 (95% CI 1.87–4.47), p < 0.001].Conclusions: COVID-19 patients with AIS present with greater D-dimer levels. Thresholds for outcomes prognostication should be higher in this population.

Applying machine learning to healthcare sheds light on evidence-based decision making and has shown promises to improve healthcare by combining clinical knowledge and biomedical data. However, medicine and data science are not synchronized. Oftentimes, researchers with a strong data science background do not understand the clinical challenges, while on the other hand, physicians do not know the capacity and limitation of state-of-the-art machine learning methods. The difficulty boils down to the lack of a common interface between two highly intelligent communities due to the privacy concerns and the disciplinary gap. The School of Biomedical Informatics (SBMI) at UTHealth is a pilot in connecting both worlds to promote interdisciplinary research. Recently, the Center for Secure Artificial Intelligence For hEalthcare (SAFE) at SBMI is organizing a series of machine learning healthcare hackathons for real-world clinical challenges. We hosted our first Hackathon themed centered around Sudden Unexpected Death in Epilepsy and finding ways to recognize the warning signs. This community effort demonstrated that interdisciplinary discussion and productive competition has significantly increased the accuracy of warning sign detection compared to the previous work, and ultimately showing a potential of this hackathon as a platform to connect the two communities of data science and medicine.

Background Convolutional neural network (CNN) has achieved state-of-art performance in many electroencephalogram (EEG) related studies. However, the application of CNN in prediction of risk factors for sudden unexpected death in epilepsy (SUDEP) remains as an underexplored area. It is unclear how the trade-off between computation cost and prediction power varies with changes in the complexity and depth of neural nets. Methods The purpose of this study was to explore the feasibility of using a lightweight CNN to predict SUDEP. A total of 170 patients were included in the analyses. The CNN model was trained using clips with 10-s signals sampled from the original EEG. We implemented Hann function to smooth the raw EEG signal and evaluated its effect by choosing different strength of denoising filter. In addition, we experimented two variations of the proposed model: (1) converting EEG input into an “RGB” format to address EEG channels underlying spatial correlation and (2) incorporating residual network (ResNet) into the bottle neck position of the proposed structure of baseline CNN. Results The proposed baseline CNN model with lightweight architecture achieved the best AUC of 0.72. A moderate noise removal step facilitated the training of CNN model by ensuring stability of performance. We did not observe further improvement in model’s accuracy by increasing the strength of denoising filter. Conclusion Post-seizure slow activity in EEG is a potential marker for SUDEP, our proposed lightweight architecture of CNN achieved satisfying trade-off between efficiently identifying such biomarker and computational cost. It also has a flexible interface to be integrated with different variations in structure leaving room for further improvement of the model’s performance in automating EEG signal annotation.

Background Sudden Unexpected Death in Epilepsy (SUDEP) has increased in awareness considerably over the last two decades and is acknowledged as a serious problem in epilepsy. However, the scientific community remains unclear on the reason or possible bio markers that can discern potentially fatal seizures from other non-fatal seizures. The duration of postictal generalized EEG suppression (PGES) is a promising candidate to aid in identifying SUDEP risk. The length of time a patient experiences PGES after a seizure may be used to infer the risk a patient may have of SUDEP later in life. However, the problem becomes identifying the duration, or marking the end, of PGES (Tomson et al. in Lancet Neurol 7(11):1021–1031, 2008; Nashef in Epilepsia 38:6–8, 1997). Methods This work addresses the problem of marking the end to PGES in EEG data, extracted from patients during a clinically supervised seizure. This work proposes a sensitivity analysis on EEG window size/delay, feature extraction and classifiers along with associated hyperparameters. The resulting sensitivity analysis includes the Gradient Boosted Decision Trees and Random Forest classifiers trained on 10 extracted features rooted in fundamental EEG behavior using an EEG specific feature extraction process (pyEEG) and 5 different window sizes or delays (Bao et al. in Comput Intell Neurosci 2011:1687–5265, 2011). Results The machine learning architecture described above scored a maximum AUC score of 76.02% with the Random Forest classifier trained on all extracted features. The highest performing features included SVD Entropy, Petrosan Fractal Dimension and Power Spectral Intensity. Conclusion The methods described are effective in automatically marking the end to PGES. Future work should include integration of these methods into the clinical setting and using the results to be able to predict a patient’s SUDEP risk.

Periprosthetic joint infection (PJI) represents one of the most challenging complications after total joint arthroplasty (TJA). Despite the availability of a variety of diagnostic techniques, the diagnosis of PJI remains a challenge due to the lack of well-established diagnostic criteria. The leucocyte esterase (LE) strips test has been proved to be a valuable diagnostic tool for PJI, and its weight in PJI diagnostic criteria has gradually increased. Characterized by its convenience, speed and immediacy, leucocyte esterase strips test has a prospect of broad application in PJI diagnosis. Admittedly, the leucocyte esterase strips test has some limitations, such as imprecision and liability to interference. Thanks to the application of new technologies, such as machine reading, quantitative detection and artificial intelligence, the LE strips test is expected to overcome the limitations and improve its accuracy.

Fast temporal query on large EHR-derived data sources presents an emerging big data challenge, as this query modality is intractable using conventional strategies that have not focused on addressing Covid-19-related research needs at scale. We introduce a novel approach called Event-level Inverted Index (ELII) to optimize time trade-offs between one-time batch preprocessing and subsequent open-ended, user-specified temporal queries. An experimental temporal query engine has been implemented in a NoSQL database using our new ELII strategy. Near-real-time performance was achieved on a large Covid-19 EHR dataset, with 1.3 million unique patients and 3.76 billion records. We evaluated the performance of ELII on several types of queries: classical (non-temporal), absolute temporal, and relative temporal. Our experimental results indicate that ELII accomplished these queries in seconds, achieving average speed accelerations of 26.8 times on relative temporal query, 88.6 times on absolute temporal query, and 1037.6 times on classical query compared to a baseline approach without using ELII. Our study suggests that ELII is a promising approach supporting fast temporal query, an important mode of cohort development for Covid-19 studies.

Background The Kentucky Cancer Registry (KCR) is a central cancer registry for the state of Kentucky that receives data about incident cancer cases from all healthcare facilities in the state within 6 months of diagnosis. Similar to all other U.S. and Canadian cancer registries, KCR uses a data dictionary provided by the North American Association of Central Cancer Registries (NAACCR) for standardized data entry. The NAACCR data dictionary is not an ontological system. Mapping between the NAACCR data dictionary and the National Cancer Institute (NCI) Thesaurus (NCIt) will facilitate the enrichment, dissemination and utilization of cancer registry data. We introduce a web-based system, called Interactive Mapping Interface (IMI), for creating mappings from data dictionaries to ontologies, in particular from NAACCR to NCIt. Method IMI has been designed as a general approach with three components: (1) ontology library; (2) mapping interface; and (3) recommendation engine. The ontology library provides a list of ontologies as targets for building mappings. The mapping interface consists of six modules: project management, mapping dashboard, access control, logs and comments, hierarchical visualization, and result review and export. The built-in recommendation engine automatically identifies a list of candidate concepts to facilitate the mapping process. Results We report the architecture design and interface features of IMI. To validate our approach, we implemented an IMI prototype and pilot-tested features using the IMI interface to map a sample set of NAACCR data elements to NCIt concepts. 47 out of 301 NAACCR data elements have been mapped to NCIt concepts. Five branches of hierarchical tree have been identified from these mapped concepts for visual inspection. Conclusions IMI provides an interactive, web-based interface for building mappings from data dictionaries to ontologies. Although our pilot-testing scope is limited, our results demonstrate feasibility using IMI for semantic enrichment of cancer registry data by mapping NAACCR data elements to NCIt concepts.

Background To explore the kinetic changes in virology, specific antibody response and imaging during the clinical course of COVID-19. Methods This observational study enrolled 20 patients with COVID-19, who were hospitalized between January 20–April 6, 2020, in the two COVID-19 designated hospitals of Zhoushan, Zhejiang and Rushan, Shandong, China, The laboratory findings, imaging, serum response to viral infection, and viral RNA level in the throat and stool samples were assessed from onset to recovery phase in patients with COVID-19. Results SARS-COV-2 RNA was positive as early as day four. It remained positive until day 55 post-onset in the sputum-throat swabs and became negative in most cases (55%) within 14 days after onset. Lymphocytopenia occurred in 40% (8/20) of patients during the peak infection period and returned to normal at week five. The most severe inflammation in the lungs appeared in week 2 or 3 after onset, and this was completely absorbed between week 6 and 8 in 85.7% of patients. All patients had detectable antibodies to the receptor binding domain (RBD), and 95% of these patients had IgG to viral N proteins. The antibody titer peaked at week four. Anti-S IgM was positive in 7 of 20 patients after week three. Conclusions All COVID-19 patients in this study were self-limiting and recovered well though it may take as long as 6–8 weeks. Our findings on the kinetic changes in imaging, serum response to viral infection and viral RNA level may help understand pathogenesis and define clinical course of COVID-19.

Background While electronic health records (EHR) bring various benefits to health care, EHR systems are often criticized as cumbersome to use, failing to fulfill the promise of improved health care delivery with little more than a means of meeting regulatory and billing requirements. EHR has also been recognized as one of the contributing factors for physician burnout. Objective Specialty-specific EHR systems have been suggested as an alternative approach that can potentially address challenges associated with general-purpose EHRs. We introduce the Epilepsy Tracking and optimized Management engine (EpiToMe), an exemplar bespoke EHR system for epilepsy care. EpiToMe uses an agile, physician-centered development strategy to optimize clinical workflow and patient care documentation. We present the design and implementation of EpiToMe and report the initial feedback on its utility for physician burnout. Methods Using collaborative, asynchronous data capturing interfaces anchored to a domain ontology, EpiToMe distributes reporting and documentation workload among technicians, clinical fellows, and attending physicians. Results of documentation are transmitted to the parent EHR to meet patient care requirements with a push of a button. An HL7 (version 2.3) messaging engine exchanges information between EpiToMe and the parent EHR to optimize clinical workflow tasks without redundant data entry. EpiToMe also provides live, interactive patient tracking interfaces to ease the burden of care management. Results Since February 2019, 15,417 electroencephalogram reports, 2635 Epilepsy Monitoring Unit daily reports, and 1369 Epilepsy Monitoring Unit phase reports have been completed in EpiToMe for 6593 unique patients. A 10-question survey was completed by 11 (among 16 invited) senior clinical attending physicians. Consensus was found that EpiToMe eased the burden of care documentation for patient management, a contributing factor to physician burnout. Conclusions EpiToMe offers an exemplar bespoke EHR system developed using a physician-centered design and latest advancements in information technology. The bespoke approach has the potential to ease the burden of care management in epilepsy. This approach is applicable to other clinical specialties.

Inflammation is crucial to tumorigenesis and progression of many cancers. Inflammatory molecules in tumor microenvironment exert pro- or anti-tumor effects. Among them, interleukin, mainly produced by CD3+ and CD4+ T lymphocytes, is a class of small molecule proteins which play an important role in intercellular communication. Numerous studies have confirmed that interleukins are closely related to thyroid cancer. Interleukins regulate the proliferation and migration of thyroid cancer cells and they have prospects in discriminating benign and malignant thyroid diseases, predicting the risk of tumorigenesis, evaluating the prognosis and monitoring the recurrence of thyroid cancer. Besides, the effective application of interleukins in treatment of thyroid cancer has been confirmed by some cell and animal researches. The present review will introduce the potential mechanisms of interleukins in thyroid cancer and focus on the applications of interleukins in clinical practice of thyroid cancer, which will help update understanding of the progress of interleukins researches in thyroid cancer.

PURPOSE To audit and improve the completeness of the hierarchic (or is-a) relations of the National Cancer Institute (NCI) Thesaurus to support its role as a faceted system for querying cancer registry data. METHODS We performed quality auditing of the 19.01d version of the NCI Thesaurus. Our hybrid auditing method consisted of three main steps: computing nonlattice subgraphs, constructing lexical features for concepts in each subgraph, and performing subsumption reasoning with each subgraph to automatically suggest potentially missing is-a relations. RESULTS A total of 9,512 nonlattice subgraphs were obtained. Our method identified 925 potentially missing is-a relations in 441 nonlattice subgraphs; 72 of 176 reviewed samples were confirmed as valid missing is-a relations and have been incorporated in the newer versions of the NCI Thesaurus. CONCLUSION Autosuggested changes resulting from our auditing method can improve the structural organization of the NCI Thesaurus in supporting its new role for faceted query.

Background: The inflammatory microenvironment is closely related to the occurrence and development of cancer. Members of the interleukin-12 (IL-12) cytokine family play synergistic or antagonistic roles in the tumor microenvironment, in the form of classic heterodimers or newly discovered monomers or homodimers. Objective: The purpose of this study was to investigate the association between IL-12A and the clinicopathology and prognosis of differentiated thyroid cancer (DTC). Methods: A total of 101 pathologically confirmed DTC patients were included in this study. Immunohistochemistry was performed to assess IL-12A expression in DTC and corresponding paracancerous tissues. The associations of IL-12A with clinicopathology and prognosis were evaluated. Results: IL-12A was expressed in both normal thyroid tissues and DTC, but its expression level was significantly higher in DTC than in normal thyroid tissues (p < 0.001). IL-12A was positively correlated with tumor size (p = 0.027), risk stratification (p = 0.020), and TNM (Tumor-Node-Metastasis) stage (p = 0.024), but not with age, sex, pathological type, multifocality, extrathyroid extension, lymph node metastasis, and distant metastasis (all p > 0.05). Lymphocytic thyroiditis was found in 26/101 patients (25.7%), which was negatively associated with IL-12A expression (p = 0.018). Multivariate logistic regression analysis showed that risk stratification was the significant independent predictor of IL-12A expression. The rate of disease persistence or recurrence (P&R) was 13/101 (12.9%), and a positive relationship was found between IL-12A expression and P&R (p = 0.020). Disease-free survival was affected by factors such as tumor size, extrathyroid extension, tumor stage (T stage), and IL-12A expression, with p values of 0.006, 0.048, 0.002, and 0.012, respectively. Multivariate Cox proportional-hazards analysis showed that tumor size ≥2 cm (hazard ratio [HR] = 4.041 [95% CI: 1.144–14.274], p = 0.031) and high IL-12A expression (HR = 4.027 [95% CI 1.014–15.994], p = 0.049) were independent predictors of prognosis of DTC patients. Conclusions: IL-12A is highly expressed in DTC and is associated with disease aggressiveness. In addition, IL-12A is an independent predictor of the outcome of DTC.

BackgroundThere are few data on the prevalence of acquired drug resistance mutations (ADRs) in Hunan Province, China, that could affect the effectiveness of antiretroviral therapy (ART).ObjectivesThe main objectives of this study were to determine the prevalence of acquired drug resistance (ADR) the epidemic characteristics of HIV-1-resistant strains among ART-failed HIV patients in Hunan Province, China.MethodsART-experienced and virus suppression failure subjects in Hunan between 2012 and 2017 were evaluated by genotyping analysis and mutations were scored using theHIVdb.stanford.edualgorithm to infer drug susceptibility.ResultsThe prevalence of HIV-1 ADR were 2.76, 2.30, 2.98, 2.62, 2.23and 2.17%, respectively, from 2012 to 2017. Overall 2295 sequences were completed from 2932 ART-failure patients, and 914 of these sequences were found to have drug resistance mutation. The most common subtype was AE (64.14%), followed by BC (17.91%) and B (11.50%). Among those 914 patients with drug resistance mutations,93.11% had NNRTI-associated drug resistance mutations, 74.40% had NRTI drug resistance mutations (DRMs) and 6.89% had PI DRMs. Dual-class mutations were observed in 591 (64.66%) cases, and triple-class mutations were observed in 43 (4.70%) cases. M184V (62.04%), K103N (41.90%) and I54L (3.83%) were the most common observed mutations, respectively, in NRTI-, NNRTI- and PI-associated drug resistance. 93.76% subjects who had DRMs received the ART first-line regimens. CD4 count, symptoms in the past 3 months, and ART adherence were found to be associated with HIV-1 DR.ConclusionsThis study showed that although the prevalence of HIV-acquired resistance in Hunan Province is at a low-level, the long-term and continuous surveillance of HIV ADR in antiretroviral drugs (ARVs) patients is necessary.

Cholestasis causes the intrahepatic accumulation of bile acids leading to hepatobiliary injury. Recently obeticholic acid, a farnesoid X receptor (FXR) agonist, was FDA-approved to treat cholestatic liver diseases, providing a new therapeutic strategy for cholestasis. The purpose of the current study was to characterize a novel FXR agonist and verify the anti-cholestatic effect of hesperidin (HP) in vivo and in vitro. Based on a molecular docking study that predicted that HP would bind to FXR, the hepatoprotective effect of HP against cholestasis and hepatotoxicity was evaluated in mice and in normal and FXR-suppressed HepaRG cells. HP prevented bile acid toxicity in HepaRG cells, and this effect was blocked by FXR silencing. HP appears to activate FXR to prevent cholestatic liver injury. Dynamic change analysis of bile acids revealed that HP promoted bile acid excretion into feces and reduced hepatic accumulation via the regulation of the FXR-target genes bile salt export pump, multi-drug resistance-associated protein 2, and Na+-taurocholate cotransporting polypeptide. Furthermore, HP down-regulated enzymes involved in bile acid synthesis including cholesterol 7α-hydroxylase and sterol 27-hydroxylase. HP produced a protective effect against cholestasis via FXR activation, and may be an effective approach for the prevention and treatment of cholestatic liver diseases.

Background Sudden unexpected death in epilepsy (SUDEP) is second only to stroke in neurological events resulting in years of potential life lost. Postictal generalized electroencephalogram (EEG) suppression (PGES) is a period of suppressed brain activity often occurring after generalized tonic-clonic seizure, a most significant risk factor for SUDEP. Therefore, PGES has been considered as a potential biomarker for SUDEP risk. Automatic PGES detection tools can address the limitations of labor-intensive, and sometimes inconsistent, visual analysis. A successful approach to automatic PGES detection must overcome computational challenges involved in the detection of subtle amplitude changes in EEG recordings, which may contain physiological and acquisition artifacts. Objective This study aimed to present a random forest approach for automatic PGES detection using multichannel human EEG recordings acquired in epilepsy monitoring units. Methods We used a combination of temporal, frequency, wavelet, and interchannel correlation features derived from EEG signals to train a random forest classifier. We also constructed and applied confidence-based correction rules based on PGES state changes. Motivated by practical utility, we introduced a new, time distance–based evaluation method for assessing the performance of PGES detection algorithms. Results The time distance–based evaluation showed that our approach achieved a 5-second tolerance-based positive prediction rate of 0.95 for artifact-free signals. For signals with different artifact levels, our prediction rates varied from 0.68 to 0.81. Conclusions We introduced a feature-based, random forest approach for automatic PGES detection using multichannel EEG recordings. Our approach achieved increasingly better time distance–based performance with reduced signal artifact levels. Further study is needed for PGES detection algorithms to perform well irrespective of the levels of signal artifacts.

Metformin is always used as the baseline antidiabetic therapy for patients with type 2 diabetes mellitus (T2DM) and hyperuricemia. Metformin is excreted into urine through active secretion mediated by rOCTs and rMATE1.The aim of this study was to identify the effects of high uric acid on the disposition and its mechanism. For the in vivo study, a hyperuricemic animal model was induced by intraperitoneal injection of potassium oxonate (250 mg/kg) in rats. Metformin (100 mg/kg) was administered orally to investigate the pharmacokinetics in control and hyperuricemic rats, respectively. For the in vitro study, HEK293 and HepaRG cells were used to investigate the effect of uric acid (15 mg/dl) on the expression of OCT1, OCT2 and MATE1 and the disposition of metformin, respectively. The in vivo study showed that the AUC0 → 600 of metformin was significantly decreased by 33.3%, whereas the cumulative urinary excretion of metformin was increased by 25.4% in hyperuricemic rats compared with that in control rats. The renal rOCT1, rOCT2 and rMATE1 and hepatic rMATE1 levels were increased in hyperuricemic rats compared with those in control rats, respectively. The in vitro study showed that uric acid could upregulate the expression of OCT2 and MATE1 in HEK293 cells and MATE1 in HepaRG cells and increase the intracellular metformin concentration in these two cell lines. These results demonstrated that a high uric acid level promoted urinary metformin excretion and decreased the plasma metformin concentration; the in vivo and in vitro studies provided a possible explanation being that high uric acid could upregulate the expression of renal metformin transporters OCTs and MATE1.

Objectives Gardenia Jasminoides Ellis (Zhizi), belonging to Rubiaceae family, has been traditionally used for treatment cholestasis and jaundice for centuries in Asian countries. In the theory of Traditional Chinese Medicines, Zhizi could dispel dampness and heat via the urine to execute its choleretic effects. However, the potential molecular mechanism has been still poorly clarified. Here, we investigated the effect of different dose of Zhizi aqueous extract powder (0.3 g/kg/d and 0.9 g/kg/d) on urinary excretion of bile acids (BAs), and defined the potential mechanism via renal BAs efflux transporters Mrp2 and Mrp4 in normal rats. Methods Male Wistar rats were orally administrated with 0.3 or 0.9 g/kg/d dose of Zhizi aqueous extract powder for 2 weeks, then body weight, serum aminotransferase, total BAs concentrations in liver, bile, serum, kidney and urine, 1 h bile flow, 12-h urinary volume, biliary and urinary excretion amount of total BAs as well as protein expression of major renal BAs efflux transporter Mrp2 and Mrp4, were all evaluated. Results Zhizi especially the high dose of Zhizi aqueous extract powder could reduce hepatic total BAs concentration. Additionally, bile flow and biliary excretion had no significant difference, but the remarkable increasing urinary excretion of BAs and 2 to 3 folds up-regulated renal Mrp2 expression were observed after administrated with Zhizi as compared with the control group. Conclusion The findings indicate that Zhizi reduces hepatic total BAs level by increasing urinary excretion rather than the biliary excretion of BAs, which, in turn ascribed to elevated protein expression of Mrp2 at apical membrane of renal tubular epithelial cells.

Papillary thyroid carcinoma (PTC) with pulmonary metastases is rare in children and adolescents. Unlike adults, limited data are available on children with this disease. Thus, this study evaluated the therapeutic efficacy and prognostic factors of individuals less than 21 years of age with pulmonary metastases from PTC. Seventy-six children and adolescents with pulmonary metastases from PTC treated with 131I were retrospectively analyzed. Therapeutic efficacy was evaluated by changes in serum thyroglobulin (Tg) and chest computed tomography (CT). Factors predictive of progression-free survival and overall survival were measured by the Kaplan-Meier method. Among the 76 patients included in this study, 22.4% (17 of 76) were less than 15 years old and 65.8% (50 of 76) were female. Under the evaluation of stimulated serum Tg levels, RAI treatment were effective in 55.9% (38 of 68), stable in 26.5% (18 of 68) and ineffectvie in 17.6% (12 of 68) of patients. Changes on anatomical imaging suggested complete response (CR), partial response (PR), stable disease (SD) and progressive disease (PD) in 8.5, 62.0, 15.5, and 14.1% of individuals, respectively. Univariate analysis showed that size and tumor doubling time of pulmonary metastases were independent factors affecting therapeutic efficacy. Extra-thyroidal extension, tumor diameter of pulmonary metastases and tumor doubling time were significant independent factors regarding progression-free survival rates, while only tumor doubling time and tumor diameter were significant risk factors associated with overall survival rate. Radioactive iodine therapy is an effective treatment for children and adolescents with pulmonary metastases from PTC. Extra-thyroid extension was associated with disease progression while did not show significant influence on overall survival. Tumor doubling time and tumor diameter were the main factors influencing both progression-free survival and overall survival.

ObjectivesUnderstanding the molecular mechanisms underlying human cartilage degeneration and regeneration is helpful for improving therapeutic strategies for treating osteoarthritis (OA). Here, we report the molecular programmes and lineage progression patterns controlling human OA pathogenesis using single-cell RNA sequencing (scRNA-seq).MethodsWe performed unbiased transcriptome-wide scRNA-seq analysis, computational analysis and histological assays on 1464 chondrocytes from 10 patients with OA undergoing knee arthroplasty surgery. We investigated the relationship between transcriptional programmes of the OA landscape and clinical outcome using severity index and correspondence analysis.ResultsWe identified seven molecularly defined populations of chondrocytes in the human OA cartilage, including three novel phenotypes with distinct functions. We presented gene expression profiles at different OA stages at single-cell resolution. We found a potential transition among proliferative chondrocytes, prehypertrophic chondrocytes and hypertrophic chondrocytes (HTCs) and defined a new subdivision within HTCs. We revealed novel markers for cartilage progenitor cells (CPCs) and demonstrated a relationship between CPCs and fibrocartilage chondrocytes using computational analysis. Notably, we derived predictive targets with respect to clinical outcomes and clarified the role of different cell types for the early diagnosis and treatment of OA.ConclusionsOur results provide new insights into chondrocyte taxonomy and present potential clues for effective and functional manipulation of human OA cartilage regeneration that could lead to improved health.

One of the basic challenges in developing structural methods for systematic audition on the quality of biomedical ontologies is the computational cost usually involved in exhaustive sub-graph analysis. We introduce ANT-LCA, a new algorithm for computing all non-trivial lowest common ancestors (LCA) of each pair of concepts in the hierarchical order induced by an ontology. The computation of LCA is a fundamental step for non-lattice approach for ontology quality assurance. Distinct from existing approaches, ANT-LCA only computes LCAs for non-trivial pairs, those having at least one common ancestor. To skip all trivial pairs that may be of no practical interest, ANT-LCA employs a simple but innovative algorithmic strategy combining topological order and dynamic programming to keep track of non-trivial pairs. We provide correctness proofs and demonstrate a substantial reduction in computational time for two largest biomedical ontologies: SNOMED CT and Gene Ontology (GO). ANT-LCA achieved an average computation time of 30 and 3 sec per version for SNOMED CT and GO, respectively, about 2 orders of magnitude faster than the best known approaches. Our algorithm overcomes a fundamental computational barrier in sub-graph based structural analysis of large ontological systems. It enables the implementation of a new breed of structural auditing methods that not only identifies potential problematic areas, but also automatically suggests changes to fix the issues. Such structural auditing methods can lead to more effective tools supporting ontology quality assurance work.

Objective We introduce a structural-lexical approach for auditing SNOMED CT using a combination of non-lattice subgraphs of the underlying hierarchical relations and enriched lexical attributes of fully specified concept names. Our goal is to develop a scalable and effective approach that automatically identifies missing hierarchical IS-A relations. Methods Our approach involves 3 stages. In stage 1, all non-lattice subgraphs of SNOMED CT’s IS-A hierarchical relations are extracted. In stage 2, lexical attributes of fully-specified concept names in such non-lattice subgraphs are extracted. For each concept in a non-lattice subgraph, we enrich its set of attributes with attributes from its ancestor concepts within the non-lattice subgraph. In stage 3, subset inclusion relations between the lexical attribute sets of each pair of concepts in each non-lattice subgraph are compared to existing IS-A relations in SNOMED CT. For concept pairs within each non-lattice subgraph, if a subset relation is identified but an IS-A relation is not present in SNOMED CT IS-A transitive closure, then a missing IS-A relation is reported. The September 2017 release of SNOMED CT (US edition) was used in this investigation. Results A total of 14,380 non-lattice subgraphs were extracted, from which we suggested a total of 41,357 missing IS-A relations. For evaluation purposes, 200 non-lattice subgraphs were randomly selected from 996 smaller subgraphs (of size 4, 5, or 6) within the “Clinical Finding” and “Procedure” sub-hierarchies. Two domain experts confirmed 185 (among 223) suggested missing IS-A relations, a precision of 82.96%. Conclusions Our results demonstrate that analyzing the lexical features of concepts in non-lattice subgraphs is an effective approach for auditing SNOMED CT.

Aim: To analyze clinical significance of preoperative liver stiffness measurement (LSM) by FibroScan in postcurative resection hepatitis B virus (HBV) related hepatocellular carcinoma (HCC). Patients & methods: A total of 263 patients underwent preoperative LSM and curative operation for primary HBV-positive HCC were enrolled. The correlation between preoperative LSM and survival was analyzed. Results: All patients were stratified into two groups using the optimal cut-off value (13.2 kPa) of LSM using the receiver–operating characteristic. Patients with an LSM ≥13.2 kPa had poorer overall survival (median, 61.3 vs 48.2 months, hazard ratio: 0.15; p = 0.009) and recurrence-free survival (median, 60.4 vs 47.0 months; hazard ratio: 0.32; p = 0.011) than patients with an LSM

Objective: Quality assurance of large ontological systems such as SNOMED CT is an indispensable part of the terminology management lifecycle. We introduce a hybrid structural-lexical method for scalable and systematic discovery of missing hierarchical relations and concepts in SNOMED CT. Material and Methods: All non-lattice subgraphs (the structural part) in SNOMED CT are exhaustively extracted using a scalable MapReduce algorithm. Four lexical patterns (the lexical part) are identified among the extracted non-lattice subgraphs. Non-lattice subgraphs exhibiting such lexical patterns are often indicative of missing hierarchical relations or concepts. Each lexical pattern is associated with a potential specific type of error. Results: Applying the structural-lexical method to SNOMED CT (September 2015 US edition), we found 6801 non-lattice subgraphs that matched these lexical patterns, of which 2046 were amenable to visual inspection. We evaluated a random sample of 100 small subgraphs, of which 59 were reviewed in detail by domain experts. All the subgraphs reviewed contained errors confirmed by the experts. The most frequent type of error was missing is-a relations due to incomplete or inconsistent modeling of the concepts. Conclusions: Our hybrid structural-lexical method is innovative and proved effective not only in detecting errors in SNOMED CT, but also in suggesting remediation for these errors.

To the Editor, In a report in this journal on risk factors for severe COVID-19, older age, C-reactive protein, and lymphocyte count were identified [1]. We here focus on a likely complicating role ...

Isoniazid (INH)-induced liver injury may be associated with inhibition of the liver farnesoid X receptor (FXR). However, the relationship between FXR and INH-induced liver injury remained unclear. The present study was performed to clarify the role of inhibition of FXR in the pathogenesis of INH-induced liver injury and to further identify potential inhibitors of FXR from INH and its metabolites. HepaRG cells were treated with INH (10 mM) plus mixed bile acids (BA) and rats were treated with INH (60–600 mg/kg p.o.) or INH plus obeticholic acid (OCA, 10 mg/kg), a potent FXR agonist, for seven days. INH can cause BA-dependent toxicity and apoptosis with elevated intracellular bile acids in vitro; indeed, in these studies, liver bile acids and mRNA levels for Cyp7a1, an FXR target gene were increased, while mRNA levels for FXR and Shp were significantly decreased, and these changes could be prevented by co-treatment with the FXR agonist OCA. In silico molecular docking studies showed that INH, acetyl isoniazid, isonicotinic acid and PIH may be potential FXR inhibitors, and a TR-FRET FXR-coactivator assay confirmed that PIH is a strong antagonist of FXR (IC50 = 52 nM). To further determine if PIH also inhibits FXR activity in vivo, rats were treated with PIH directly (5 mg/kg). Liver total bile acids were significantly increased while FXR expression was not changed, but Shp mRNA levels were significantly decreased and Cyp7a1 mRNA was significantly increased, consistent with PIH acting as an FXR antagonist. In summary, PIH inhibition of liver FXR function leading to bile acid accumulation in hepatocytes may be an early pathogenesis event in INH-induced liver injury.

Background: The lung is the most frequent site of distant metastasis from differentiated thyroid cancer (DTC). However, lung metastasis from papillary thyroid cancer (PTC) with persistently negative thyroglobulin (Tg) and elevated Tg antibody (TgAb) levels is an extremely rare entity, and the prognosis is therefore elusive. We investigated the clinical characteristics, long-term outcomes, and prognostic factors of lung metastases in PTC patients with persistently negative thyroglobulin (Tg) and elevated Tg antibody (TgAb) levels during radioactive iodine (131I) treatment and follow-up.Methods: We retrospectively reviewed 10,482 patients with DTC who underwent postoperative 131I treatment from 2007 to 2017 at Shanghai Sixth's People's Hospital. The relationships between progression-free survival (PFS) and several variables were assessed by univariate and multivariate analyses using the Kaplan–Meier method and a Cox proportional hazards model, respectively.Results: Forty-seven patients with PTC were enrolled in this study (4.48‰ of all patients with DTC). The median age at the initial diagnosis of lung metastasis was 39.6 ± 15.4 years, and the patients comprised 14 male and 33 female patients (male: female ratio = 1.00:2.36). Twenty-five patients had 131I avidity and 22 had non-131I avidity. At the end of the 5-years follow-up, 12 patients exhibited progressive disease (PD), and 2 patients had died. At the end of the 10-years follow-up, 21 patients showed PD and five patients had died. The 5- and 10-year PFS rates were 74.47 and 53.32%, respectively; the 5- and 10-years overall survival (OS) rates were 95.74 and 89.36%, respectively. The timing of diagnosis of lung metastases, maximal size of lung metastases, and 131I avidity were significantly associated with the 5-years PFS rate (P = 0.035, P = 0.030, and P

Postsurgical management of differentiated thyroid cancer in China has gained a great success in the last twenty years, but there are still gaps to be filled. Here, we briefly review the current status and also extend an outlook for future development.

Epilepsy is a heterogeneous condition with disparate etiologies and phenotypic and genotypic characteristics. Clinical and research aspects are accordingly varied, ranging from epidemiological to molecular, spanning clinical trials and outcomes, gene and drug discovery, imaging, electroencephalography, pathology, epilepsy surgery, digital technologies, and numerous others. Epilepsy data are collected in the terabytes and petabytes, pushing the limits of current capabilities. Modern computing firepower and advances in machine and deep learning, pioneered in other diseases, open up exciting possibilities for epilepsy too. However, without carefully designed approaches to acquiring, standardizing, curating, and making available such data, there is a risk of failure. Thus, careful construction of relevant ontologies, with intimate stakeholder inputs, provides the requisite scaffolding for more ambitious big data undertakings, such as an epilepsy data commons. In this review, we assess the clinical and research epilepsy landscapes in the big data arena, current challenges, and future directions, and make the case for a systematic approach to epilepsy big data.

Hip aspirations used to detect a periprosthetic joint infection (PJI) are usually performed under fluoroscopy or ultrasound. The aim of this study was to evaluate the results of simply using anatomic landmarks for aspiration and detecting PJI without the use of any complicated technologies. The authors retrospectively reviewed a total of 186 consecutive hip aspirations performed between April 2015 and December 2018. All patients were suspected to have infections after total hip arthroplasty. The procedures were performed with the patients in the supine position. The authors aimed to aspirate at the neck of the prosthesis. They located the y-axis of the puncture point approximately 2 to 3 cm lateral to the pulse of the femoral artery in the region of the inguinal ligament. The x-axis was estimated by using the pubic symphysis or greater trochanter according to an anteroposterior radiograph of the hip joint. The aspiration failure rate, incidence of complications, and culture results were recorded. The overall aspiration failure rate was 3.8% (7 of 186). No obvious complications related to aspiration were observed. The saline lavage and reaspiration rate was 45.3% (81 of 179) due to “dry taps.” The sensitivity, specificity, positive predictive value, and negative predictive value of the remaining 169 patients with definite diagnoses were 0.781 (95% CI, 0.678–0.860), 0.939 (95% CI, 0.857–0.977), 0.931 (95% CI, 0.841–0.975), and 0.802 (95% CI, 0.706–0.874), respectively. Anatomic landmark-guided hip aspiration was a convenient method that could provide satisfactory detection of PJI. [ Orthopedics . 2021;44(1):e85–e90.]

About 20% of individuals with attention deficit hyperactivity disorder (ADHD) are first diagnosed during adolescence. While preclinical experiments suggest that adolescent-onset exposure to ADHD medication is an important factor in the development of substance use disorder (SUD) phenotypes in adulthood, the long-term impact of ADHD medication initiated during adolescence has been largely unexplored in humans. Our analysis of 11,624 adolescent ADHD patients in the Truven database indicates that temporal medication features are the important factors on the health consequences related to SUD and ADHD medication initiation during adolescence.

Insomnia is prevalent in the general population and is often difficult to be identified reliably. The sleep spindle is a key electroencephalograph (EEG) signal that plays an important role in the preservation of sleep continuity. Previous studies on the relationship between spindle and insomnia mainly focus on the density distribution of spindle waves. In this article, we leverage the large amount of sleep data in the National Sleep Research Resource (NSRR) to develop two sequence models to take into consideration the temporal features of sleep spindles in the whole night sleep recording, and treat the interplay between insomnia and sleep spindle wave as a continuous process. The experimental results on two study cohorts of NSRR show that our method achieved the best performance among all the compared methods, indicating that it is the temporal feature of spindles, rather than stationary features (i.e., frequency, duration, amplitude) that are critical for identifying insomnia patients.

About 20% of individuals with attention deficit hyperactivity disorder are first diagnosed during adolescence. While preclinical experiments suggest that adolescent-onset exposure to attention deficit hyperactivity disorder medication is an important factor in the development of substance use disorder phenotypes in adulthood, the long-term impact of attention deficit hyperactivity disorder medication initiated during adolescence has been largely unexplored in humans. Our analysis of 11,624 adolescent enrollees with attention deficit hyperactivity disorder in the Truven database indicates that temporal medication features, rather than stationary features, are the most important factors on the health consequences related to substance use disorder and attention deficit hyperactivity disorder medication initiation during adolescence.

To assess outcomes in obese patients with chronic obstructive pulmonary disease (COPD) who sustained an osteoporotic vertebral compression fracture (OVCF) treated by percutaneous vertebroplasty (PVP) in the improved prone position and right lateral position.Between January 2015 and May 2016, a total of 60 patients were enrolled in this randomized controlled study. Patients in group A were placed in the improved prone position for a bilateral transpedicular technique, and those in group B were placed in the right lateral position for a left transverse process-pedicle approach. Clinical and radiologic outcomes were assessed and compared between the 2 groups during the 12-month follow-up period.All operations were successfully completed without any serious sequelae. The operation time, fluoroscopic time, scores for respiratory condition during the operation, intravertebral cement volume, and incidence of cement leakage were significantly greater in group A compared with group B (P0.01). During the follow-up period, all patients in both groups experienced significant improvement in pain relief. Satisfactory functional improvement was obtained at 3 months postoperatively.Treatment of obese patients with COPD suffering from painful OVCF by PVP in both the improved prone position with a bilateral technique and the right lateral position with a unilateral technique was relatively safe and effective. However, unilateral PVP in the right lateral position was associated with a shorter operation time, limited fluoroscopic time, and minimal cement leakage.

Breast cancer, the most frequently occurring malignant tumor, has high mortality rate, especially triple-negative breast cancer (TNBC). LncRNA-differentiation antagonizing non-protein coding RNA (lncRNA DANCR) has been found that its aberrant expression was associated with tumor progression and it was promising to be a potential target for cancer therapy. The goal of the present study was to explore the biological effects and underlying mechanism of DANCR in breast cancer. Our results showed that DANCR was up-regulated in TNBC tissues and breast cancer cells compared with normal breast tissues and cells, and higher DANCR level suggested poorer prognosis, implying that it was promising to be a novel biomarker used for TNBC diagnosis and prognosis. To better research the functions and mechanism of DANCR on breast cancer cells, we selected two cell lines used for next study: one TNBC cell line–MDA-MB-231 and one ER-positive breast cancer cell line–MCF-7. Further study indicated that DANCR overexpression significantly promoted cell proliferation and invasion in vitro and contributed to tumor growth in vivo. To deeply understand its molecular mechanism, miRNA-216a-5p was identified as a target of DANCR by bioinformatic analysis. Experiments demonstrated that miRNA-216a-5p interacted with DANCR and its inhibitor could weaken the influences induced by DANCR knockdown for cancer cells, including cell proliferation and invasion, and the expression of Nanog, SOX2, and OCT4. Therefore, DANCR might act as a tumor promoter by targetting miRNA-216a-5p, which might provide a potential therapy target for breast cancer treatment.

The present study investigated the effect of the transdifferentiation of bile duct epithelial cells (BECs) into myofibroblasts on the pathogenesis of secondary cholestatic hepatic fibrosis and examined the underlying mechanisms. A total of 60 male rats with hepatic fibrosis were randomly divided into two groups: A secondary cholestatic hepatic fibrosis model group induced by ligation of the bile duct (BDL) and a sham group, which only underwent segregation of the choledochus. Rats in the BDL group were dynamically observed after week 1, 2, 3 and 4 post-BDL, and the remaining rats were sacrificed after week 5 to determine histological changes and hydroxyproline content. The cellular co-localization of cytokeratin (CK)7/α-smooth muscle actin (SMA) or α-SMA/desmin was detected by immunofluorescence staining and laser confocal microscopy, while the protein expression levels of CK7, α-SMA and desmin were determined by western blot analysis. Sirius red staining was also performed and quantified. The results revealed a significant correlation between the protein expression of CK7 and α-SMA (r=0.9692, P

Background Genomic medicine is poised to improve care for common complex diseases such as epilepsy, but additional clinical informatics and implementation science research is needed for it to become a part of the standard of care. Epilepsy is an exemplary complex neurological disorder for which DNA diagnostics have shown to be advantageous for patient care. Objective We designed the Implementation Science for Genomic Health Translation (INSIGHT) study to leverage the fact that both the clinic and testing laboratory control the development and customization of their respective electronic health records and clinical reporting platforms. Through INSIGHT, we can rapidly prototype and benchmark novel approaches to incorporating clinical genomics into patient care. Of particular interest are clinical decision support tools that take advantage of domain knowledge from clinical genomics and can be rapidly adjusted based on feedback from clinicians. Methods Building on previously developed evidence and infrastructure components, our model includes the following: establishment of an intervention-ready genomic knowledge base for patient care, creation of a health informatics platform and linking it to a clinical genomics reporting system, and scaling and evaluation of INSIGHT following established implementation science principles. Results INSIGHT was approved by the Institutional Review Board at the University of Texas Health Science Center at Houston on May 15, 2020, and is designed as a 2-year proof-of-concept study beginning in December 2021. By design, 120 patients from the Texas Comprehensive Epilepsy Program are to be enrolled to test the INSIGHT workflow. Initial results are expected in the first half of 2023. Conclusions INSIGHT’s domain-specific, practical but generalizable approach may help catalyze a pathway to accelerate translation of genomic knowledge into impactful interventions in patient care. International Registered Report Identifier (IRRID) PRR1-10.2196/25576