Miracle-dz/UniFAR-FTUs huggingface dataset:
A comparison of comorbidity measures for predicting mortality after elective hip and knee replacement: A cohort study of data from the National Joint Registry in England and Wales

Background The risk of mortality following elective total hip (THR) and knee replacements (KR) may be influenced by patients’ pre-existing comorbidities. There are a variety of scores derived from individual comorbidities that can be used in an attempt to quantify this. The aims of this study were to a) identify which comorbidity score best predicts risk of mortality within 90 days or b) determine which comorbidity score best predicts risk of mortality at other relevant timepoints (30, 45, 120 and 365 days). Patients and methods We linked data from the National Joint Registry (NJR) on primary elective hip and knee replacements performed between 2011–2015 with pre-existing conditions recorded in the Hospital Episodes Statistics. We derived comorbidity scores (Charlson Comorbidity Index—CCI, Elixhauser, Hospital Frailty Risk Score—HFRS). We used binary logistic regression models of all-cause mortality within 90-days and within 30, 45, 120 and 365-days of the primary operation using, adjusted for age and gender. We compared the performance of these models in predicting all-cause mortality using the area under the Receiver-operator characteristics curve (AUROC) and the Index of Prediction Accuracy (IPA). Results We included 276,594 elective primary THRs and 338,287 elective primary KRs for any indication. Mortality within 90-days was 0.34% (N = 939) after THR and 0.26% (N = 865) after KR. The AUROC for the CCI and Elixhauser scores in models of mortality ranged from 0.78–0.81 after THR and KR, which slightly outperformed models with ASA grade (AUROC = 0.77–0.78). HFRS performed similarly to ASA grade (AUROC = 0.76–0.78). The inclusion of comorbidities prior to the primary operation offers no improvement beyond models with comorbidities at the time of the primary. The discriminative ability of all prediction models was best for mortality within 30 days and worst for mortality within 365 days. Conclusions Comorbidity scores add little improvement beyond simpler models with age, gender and ASA grade for predicting mortality within one year after elective hip or knee replacement. The additional patient-specific information required to construct comorbidity scores must be balanced against their prediction gain when considering their utility.
A computational method for identifying an optimal combination of existing drugs to repair the action potentials of SQT1 ventricular myocytes

Mutations are known to cause perturbations in essential functional features of integral membrane proteins, including ion channels. Even restricted or point mutations can result in substantially changed properties of ion currents. The additive effect of these alterations for a specific ion channel can result in significantly changed properties of the action potential (AP). Both AP shortening and AP prolongation can result from known mutations, and the consequences can be life-threatening. Here, we present a computational method for identifying new drugs utilizing combinations of existing drugs. Based on the knowledge of theoretical effects of existing drugs on individual ion currents, our aim is to compute optimal combinations that can ‘repair’ the mutant AP waveforms so that the baseline AP-properties are restored. More specifically, we compute optimal, combined, drug concentrations such that the waveforms of the transmembrane potential and the cytosolic calcium concentration of the mutant cardiomyocytes (CMs) becomes as similar as possible to their wild type counterparts after the drug has been applied. In order to demonstrate the utility of this method, we address the question of computing an optimal drug for the short QT syndrome type 1 (SQT1). For the SQT1 mutation N588K, there are available data sets that describe the effect of various drugs on the mutated K+ channel. These published findings are the basis for our computational analysis which can identify optimal compounds in the sense that the AP of the mutant CMs resembles essential biomarkers of the wild type CMs. Using recently developed insights regarding electrophysiological properties among myocytes from different species, we compute optimal drug combinations for hiPSC-CMs, rabbit ventricular CMs and adult human ventricular CMs with the SQT1 mutation. Since the ‘composition’ of ion channels that form the AP is different for the three types of myocytes under consideration, so is the composition of the optimal drug.
Elucidate microbial characteristics in a full-scale treatment plant for offshore oil produced wastewater

Oil-produced wastewater treatment plants, especially those involving biological treatment processes, harbor rich and diverse microbes. However, knowledge of microbial ecology and microbial interactions determining the efficiency of plants for oil-produced wastewater is limited. Here, we performed 16S rDNA amplicon sequencing to elucidate the microbial composition and potential microbial functions in a full-scale well-worked offshore oil-produced wastewater treatment plant. Results showed that microbes that inhabited the plant were diverse and originated from oil and marine associated environments. The upstream physical and chemical treatments resulted in low microbial diversity. Organic pollutants were digested in the anaerobic baffled reactor (ABR) dominantly through fermentation combined with sulfur compounds respiration. Three aerobic parallel reactors (APRs) harbored different microbial groups that performed similar potential functions, such as hydrocarbon degradation, acidogenesis, photosynthetic assimilation, and nitrogen removal. Microbial characteristics were important to the performance of oil-produced wastewater treatment plants with biological processes.
Necessity of Fine-Needle Aspiration in Probably Benign Sonographic Appearance of Thyroid Nodules

Introduction: The management of thyroid nodules has been proposed based on US features and information obtained from Fine-Needle Aspiration Cytology (FNAC). In this study, we checked the diagnostic value of ultrasound in comparison with FNAC in probably benign nodules of thyroid. Materials and Methods: Patients with thyroid nodules referred to the Radiology department from 2015 to 2020, were classified into five types based on the American College of Radiology/thyroid imaging reporting and data system (TI-RADS) standards. The patients with TI-RADS III-V were examined by FNA biopsy. Subsequently, the collected data of 535 patients having thyroid nodules with TI-RADS III were statistically analyzed. Results: The mean age of the patients was estimated at 46.57. The analysis of TI-RADS III cases examined by the FNA biopsy revealed that 99.1% of the cases were diagnosed with benign lesions. The mean size of benign and malignant nodules was 27mm and 41mm, respectively. There was no significant correlation between the size of the nodules or patients age, and thyroid malignancy (P-values > 0.05). Conclusion: There was a very low chance of malignancy (0.9%) in thyroid nodules with thyroid imaging classification of TI-RADS III. Furthermore, no meaningful correlation was observed between the size of the nodules and their malignancy. Therefore, the use of FNAC, based on the current guidelines, on thyroids for nodules larger than 2.5 cm might need to be revised.
Differential responses of salivary cortisol, amylase, and chromogranin A to academic stress

Salivary biomarkers have been widely used to help diagnose stress, anxiety, and/or depression. This study aimed to compare the responses of three commonly investigated salivary stress biomarkers that represent the hypothalamic-pituitary-adrenal activity (cortisol; sCort) and the sympathetic activity (alpha-amylase; sAA and chromogranin A; sCgA), using academic oral presentation as a model of stress. Twenty postgraduate dental students attended the seminar class as presenter and audience. The presenters’ performances were evaluated by the instructors suggesting more stress than the audience. The saliva was collected two times: before attending class and after an academic presentation (for presenters) or during the class (for audience). The pulse rates (PR) were also recorded. The results showed that the levels of all three biomarkers, as well as PR, were significantly higher in the presenter group compared with the audience group; however, the changes were most prominent with sCort and sAA (99.56 ± 12.76% for sCort, 93.48 ± 41.29% for sAA, 16.86 ± 6.42% for sCgA, and 15.06 ± 3.41% for PR). When compared between pre-post presentation, the levels of sCgA were not different, while those of sCort and sAA were significantly increased. These results suggest more sensitive reactivity to academic stress of sCort and sAA compared with sCgA and that the response of sCgA did not necessarily follow sAA pattern even though both are claimed to reflect the sympathetic activity. More studies are needed to elucidate the roles of sCgA in stress.
First evidence of enterovirus A71 and echovirus 30 in Uruguay and genetic relationship with strains circulating in the South American region

Human enteroviruses (EVs) comprise more than 100 types of coxsackievirus, echovirus, poliovirus and numbered enteroviruses, which are mainly transmitted by the faecal-oral route leading to diverse diseases such as aseptic meningitis, encephalitis, and acute flaccid paralysis, among others. Since enteroviruses are excreted in faeces, wastewater-based epidemiology approaches are useful to describe EV diversity in a community. In Uruguay, knowledge about enteroviruses is extremely limited. This study assessed the diversity of enteroviruses through Illumina next-generation sequencing of VP1-amplicons obtained by RT-PCR directly applied to viral concentrates of 84 wastewater samples collected in Uruguay during 2011–2012 and 2017–2018. Fifty out of the 84 samples were positive for enteroviruses. There were detected 27 different types belonging to Enterovirus A species (CVA2-A6, A10, A16, EV-A71, A90), Enterovirus B species (CVA9, B1-B5, E1, E6, E11, E14, E21, E30) and Enterovirus C species (CVA1, A13, A19, A22, A24, EV-C99). Enterovirus A71 (EV-A71) and echovirus 30 (E30) strains were studied more in depth through phylogenetic analysis, together with some strains previously detected by us in Argentina. Results unveiled that EV-A71 sub-genogroup C2 circulates in both countries at least since 2011–2012, and that the C1-like emerging variant recently entered in Argentina. We also confirmed the circulation of echovirus 30 genotypes E and F in Argentina, and reported the detection of genotype E in Uruguay. To the best of our knowledge this is the first report of the EV-A71 C1-like emerging variant in South-America, and the first report of EV-A71 and E30 in Uruguay.
No Significant Changes of Glycemic Control and Renal Function in Patients with Advanced-Stage Diabetic Kidney Disease by Switching from Linagliptin to Teneligliptin

Purpose We compared the efficacy of teneligliptin versus linagliptin for glycemic control and renoprotection in patients with advanced-stage diabetic kidney disease. Patients and Methods Changes in the glycated hemoglobin (HbA1c), fasting blood glucose concentration, urine albumin-to-creatinine ratio (UACR), and estimated glomerular filtration rate (eGFR) during a 12-month period were retrospectively analyzed after switching from linagliptin to teneligliptin in 13 patients with advanced-stage diabetic kidney disease (teneligliptin group). Thirteen propensity score-matched patients who were treated with linagliptin alone served as controls (linagliptin group). Results The HbA1c, fasting blood glucose concentration, and UACR did not change during the 12-month study period in either group. The annual change rate in the eGFR did not differ between before and after baseline in either group. Conclusion Switching from linagliptin to teneligliptin may not improve glycemic control, reduce urinary protein excretion, or ameliorate the rate of renal function decline in patients with advanced-stage diabetic kidney disease. These results suggest that teneligliptin may not be more advantageous for glycemic control and renoprotection compared with linagliptin in patients with advanced-stage diabetic kidney disease.
Protective Activity of Aspirin Eugenol Ester on Paraquat-Induced Cell Damage in SH-SY5Y Cells

Aspirin eugenol ester (AEE) is a new pharmaceutical compound esterified by aspirin and eugenol, which has anti-inflammatory, antioxidant, and other pharmacological activities. The aim of this study was to investigate the protective effect of AEE on paraquat- (PQ-) induced cell damage of SH-SY5Y human neuroblastoma cells and its potential molecular mechanism. There was no significant change in cell viability when AEE was used alone. PQ treatment reduced cell viability in a concentration-dependent manner. However, AEE reduced the PQ-induced loss of cell viability. Flow cytometry, terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL), and 4′6-diamidino-2-phenylindole (DAPI) staining were used to evaluate cell apoptosis. Compared with the PQ group, AEE pretreatment could significantly inhibit PQ-induced cell damage. AEE pretreatment could reduce the cell damage of SH-SY5Y cells induced by PQ via reducing superoxide anion, intracellular reactive oxygen species (ROS), and mitochondrial ROS (mtROS) and increasing the levels of mitochondrial membrane potential (ΔΨm). At the same time, AEE could increase the activity of glutathione peroxidase (GSH-Px), catalase (CAT), and superoxide dismutase (SOD) and decrease the activity of malondialdehyde (MDA). The results showed that compared with the control group, the expression of p-PI3K, p-Akt, and Bcl-2 was significantly decreased, while the expression of caspase-3 and Bax was significantly increased in the PQ group. In the AEE group, AEE pretreatment could upregulate the expression of p-PI3K, p-Akt, and Bcl-2 and downregulate the expression of caspase-3 and Bax in SH-SY5Y cells. PI3K inhibitor LY294002 and the silencing of PI3K by shRNA could weaken the protective effect of AEE on PQ-induced SH-SY5Y cells. Therefore, AEE has a protective effect on PQ-induced SH-SY5Y cells by regulating the PI3K/Akt signal pathway to inhibit oxidative stress.
Impact of the DREAMS interventions on educational attainment among adolescent girls and young women: Causal analysis of a prospective cohort in urban Kenya

Background DREAMS promotes a comprehensive HIV prevention approach to reduce HIV incidence among adolescent girls and young women (AGYW). One pathway that DREAMS seeks to impact is to support AGYW to stay in school and achieve secondary education. We assessed the impact of DREAMS on educational outcomes among AGYW in Nairobi, Kenya. Methods and findings In two informal settlements in Nairobi, 1081 AGYW aged 15−22 years were randomly selected in 2017 and followed-up to 2019. AGYW reporting invitation to participate in DREAMS during 2017–18 were classified as “DREAMS beneficiaries”. Our main outcome was being in school and/or completed lower secondary school in 2019. We used multivariable logistic regression to quantify the association between being a DREAMS beneficiary and the outcome; and a causal inference framework to estimate proportions achieving the outcome if all, versus no, AGYW were DREAMS beneficiaries, adjusting for the propensity to be a DREAMS beneficiary. Of AGYW enrolled in 2017, 79% (852/1081) were followed-up to 2019. In unadjusted analysis, DREAMS beneficiaries had higher attainment than non-beneficiaries (85% vs 75% in school or completed lower secondary school, Odds Ratio (OR) = 1.9; 95%CI: 1.3,2.8). The effect weakened with adjustment for age and other confounders, (adjusted OR = 1.4; 95%CI: 0.9,2.4). From the causal analysis, evidence was weak for an impact of DREAMS (estimated 83% vs 79% in school or completed lower secondary school, if all vs no AGYW were beneficiaries, difference = 4%; 95%CI: -2,11%). Among AGYW out of school at baseline, the estimated differences were 21% (95%CI: -3,43%) among 15−17 year olds; and 4% (95%CI: -8,17%) among 18−22 year olds. Conclusions DREAMS had a modest impact on educational attainment among AGYW in informal settlements in Kenya, by supporting both retention and re-enrolment in school. Larger impact might be achieved if more AGYW were reached with educational subsidies, alongside other DREAMS interventions.
The Role of the Anterior Cingulate Cortex and Insular Cortex in Suicidal Memory and Intent

Research on the brain regions involved in suicidal behavior has led to the identification of a number of regions as being implicated in the neurobiology of suicide. Some of the brain regions identified have a clear correlation between the levels of activity and suicidal behavior. For some regions, such as the insular cortex and anterior cingulate cortex (ACC), both hyperactivity and hypoactivity have been correlated with suicidal behavior. More studies are needed to characterize more clearly the activity of the insular cortex and ACC when it comes to suicidal behavior. The case report presented adds to the literature seeking to clarify the correlation between ACC and insular activities and suicidal behavior. Structural damage of the insular region and ACC, thus leading to a decline in their activity level, was found in a patient who had resolution of suicidal intent after hypoxic brain injury. We discuss the significance of our findings for the neurobiology of suicide.
A Core Drug Discovery Framework from Large-Scale Literature for Cold Pathogenic Disease Treatment in Traditional Chinese Medicine

Cold pathogenic disease is a widespread disease in traditional Chinese medicine, which includes influenza and respiratory infection associated with high incidence and mortality. Discovering effective core drugs in Chinese medicine prescriptions for treating the disease and reducing patients' symptoms has attracted great interest. In this paper, we explore the core drugs for curing various syndromes of cold pathogenic disease from large-scale literature. We propose a core drug discovery framework incorporating word embedding and community detection algorithms, which contains three parts: disease corpus construction, drug network generation, and core drug discovery. First, disease corpus is established by collecting and preprocessing large-scale literature about the Chinese medicine treatment of cold pathogenic disease from China National Knowledge Infrastructure. Second, we adopt the Chinese word embedding model SSP2VEC for mining the drug implication implied in the literature; then, a drug network is established by the semantic similarity among drugs. Third, the community detection method COPRA based on label propagation is adopted to reveal drug communities and identify core drugs in the drug network. We compute the community size, closeness centrality, and degree distributions of the drug network to analyse the patterns of core drugs. We acquire 4681 literature from China national knowledge infrastructure. Twelve significant drug communities are discovered, in which the top-10 drugs in every drug community are recognized as core drugs with high accuracy, and four classical prescriptions for treating different syndromes of cold pathogenic disease are discovered. The proposed framework can identify effective core drugs for curing cold pathogenic disease, and the research can help doctors to verify the compatibility laws of Chinese medicine prescriptions.
Acute vaping exacerbates microbial pneumonia due to calcium (Ca2+) dysregulation

As electronic cigarette (E-cig) use, also known as “vaping”, has rapidly increased in popularity, data regarding potential pathologic effects are recently emerging. Recent associations between vaping and lung pathology have led to an increased need to scrutinize E-cigs for adverse health impacts. Our previous work (and others) has associated vaping with Ca2+-dependent cytotoxicity in cultured human airway epithelial cells. Herein, we develop a vaped e-liquid pulmonary exposure mouse model to evaluate vaping effects in vivo. Using this model, we demonstrate lung pathology through the use of preclinical measures, that is, the lung wet: dry ratio and lung histology/H&E staining. Further, we demonstrate that acute vaping increases macrophage chemotaxis, which was ascertained using flow cytometry-based techniques, and inflammatory cytokine production, via Luminex analysis, through a Ca2+-dependent mechanism. This increase in macrophage activation appears to exacerbate pulmonary pathology resulting from microbial infection. Importantly, modulating Ca2+ signaling may present a therapeutic direction for treatment against vaping-associated pulmonary inflammation.
A comparison of attentional neural network architectures for modeling with electronic medical records

Abstract Objective Attention networks learn an intelligent weighted averaging mechanism over a series of entities, providing increases to both performance and interpretability. In this article, we propose a novel time-aware transformer-based network and compare it to another leading model with similar characteristics. We also decompose model performance along several critical axes and examine which features contribute most to our model’s performance. Materials and methods Using data sets representing patient records obtained between 2017 and 2019 by the Kaiser Permanente Mid-Atlantic States medical system, we construct four attentional models with varying levels of complexity on two targets (patient mortality and hospitalization). We examine how incorporating transfer learning and demographic features contribute to model success. We also test the performance of a model proposed in recent medical modeling literature. We compare these models with out-of-sample data using the area under the receiver-operator characteristic (AUROC) curve and average precision as measures of performance. We also analyze the attentional weights assigned by these models to patient diagnoses. Results We found that our model significantly outperformed the alternative on a mortality prediction task (91.96% AUROC against 73.82% AUROC). Our model also outperformed on the hospitalization task, although the models were significantly more competitive in that space (82.41% AUROC against 80.33% AUROC). Furthermore, we found that demographic features and transfer learning features which are frequently omitted from new models proposed in the EMR modeling space contributed significantly to the success of our model. Discussion We proposed an original construction of deep learning electronic medical record models which achieved very strong performance. We found that our unique model construction outperformed on several tasks in comparison to a leading literature alternative, even when input data was held constant between them. We obtained further improvements by incorporating several methods that are frequently overlooked in new model proposals, suggesting that it will be useful to explore these options further in the future.